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--- title: Predictive Value of Prognostic Nutritional Index for Early Postoperative Mobility in Elderly Patients with Pertrochanteric Fracture Treated with Intramedullary Nail Osteosynthesis authors: - Leon Marcel Faust - Maximilian Lerchenberger - Johannes Gleich - Christoph Linhart - Alexander Martin Keppler - Ralf Schmidmaier - Wolfgang Böcker - Carl Neuerburg - Yunjie Zhang journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003114 doi: 10.3390/jcm12051792 license: CC BY 4.0 --- # Predictive Value of Prognostic Nutritional Index for Early Postoperative Mobility in Elderly Patients with Pertrochanteric Fracture Treated with Intramedullary Nail Osteosynthesis ## Abstract Background: Early postoperative mobilization is essential for orthogeriatric patients. The prognostic nutritional index (PNI) is widely used to evaluate nutritional status. This study sought to investigate the predictive value of PNI for early postoperative mobility in patients with pertrochanteric femur fractures. Materials and methods: This study included 156 geriatric patients with pertrochanteric femur fractures treated with TFN-Advance™ (DePuy Synthes, Raynham, MA, USA). Mobility was evaluated on the third postoperative day and by discharge. Stepwise logistic regression analyses were performed to evaluate the association significance of PNI with postoperative mobility together with comorbidities. The optimal PNI cut-off value for mobility was analyzed using the receiver operating characteristic (ROC) curve. Results: Three days postoperatively, PNI was an independent predictor of mobility (OR: 1.14, $95\%$ CI: 1.07–1.23, $p \leq 0.01$). By discharge, it was found that PNI (OR: 1.18, $95\%$ CI: 1.08–1.30, $p \leq 0.01$) and dementia (OR: 0.17, $95\%$ CI: 0.07–0.40, $p \leq 0.001$) were significant predictors. PNI correlated weakly with age (r = −0.27, $p \leq 0.001$). The PNI cut-off value for mobility on the third postoperative day was 38.1 (specificity = $78.5\%$, sensitivity = $63.6\%$). Conclusions: Our findings indicate that PNI is an independent predictor of early postoperative mobility in geriatric patients with pertrochanteric femur fractures treated with TFNA™. ## 1. Introduction Trochanteric fractures were the second most common fracture among German adults from 2009–2019 after femoral neck fractures, and $87\%$ of patients diagnosed with trochanteric fractures were aged ≥70 [1]. A hazard ratio for one-year mortality of 2.78 was shown in geriatric patients suffering from a hip fracture in comparison to the same age group without a prevalence of hip fracture [2] with a one-year mortality of $30\%$ [3]. Postoperative care should focus on preventing complications and promoting quick mobilization with full weight-bearing as tolerated. Ottesen et al. found that restricted postoperative weight-bearing in geriatric patients with a hip fracture was associated with significantly higher rates of adverse events, such as sepsis, pneumonia, delirium, transfusion, and increased length of hospitalization [4]. A previous study reported that prolonged immobility after hip fracture was related to higher six-month mortality and lower functional levels two months after the event [5]. Using patient-specific factors is a crucial step to identify patients at risk for immobility. An early assessment can lead to therapeutic changes according to the patient’s needs and thereby reduce postoperative morbidity and mortality [6]. The correlation between nutritional status and postoperative outcomes has drawn more attention in the current literature. Ihle et al. found that malnourished geriatric trauma patients showed delayed postoperative mobilization compared to patients with a regular nutritional status [7]. Moreover, they reported an increased prevalence of malnutrition in older trauma patients, as malnutrition was prevalent in roughly $12\%$ of patients aged <65, $31\%$ of patients aged 65–80, and $60\%$ in patients aged >80 [7]. Malnutrition can be evaluated by various methods, for example, with the mini nutritional assessment (MNA) [8], nutritional risk screening (NRS) [9], body mass index (BMI), or laboratory parameters. The prognostic nutritional index (PNI) is a laboratory index based on serum albumin and total lymphocyte count [10]. PNI was initially developed to preoperatively assess perioperative risks in gastrointestinal surgery. In recent research, PNI was shown to be a promising prognostic factor and predictor of postoperative outcomes in different tumor entities such as pancreatic cancer, colorectal cancer, or lung cancer [11,12,13]. Low PNI was found to be a predictive factor for postoperative delirium, infectious complications, and ICU admission in hip fracture patients [14,15]. Geriatric hip fracture patients with hypoalbuminemia were shown to have significantly higher postoperative adverse events and mortality rates compared to patients with normal serum albumin concentration [16,17]. However, the value of PNI in predicting the postoperative mobility of hip fracture patients remains unclear. This study aims to investigate the prognostic value of the PNI on postoperative mobility in trochanteric hip fracture patients. We hypothesized that patients with low PNI have reduced postoperative mobility. ## 2.1. Patient Selection The study protocol was approved by the local ethics committee (approval number: 20-0247). Geriatric patients (age ≥ 65 years) suffering from pertrochanteric femoral fractures (ICD-10 code: S72.1, AO: 31A1.2, 31A1.3, 31A2.2, 31A2.3 [18], Evans: Type I [19]) and treated with the TFN-ADVANCED™ Proximal Femoral Nailing System (TFNA, DePuy Synthes, Raynham, MA, USA) consecutively from 1 June 2020 to 1 May 2022 in our university teaching hospital were retrospectively enrolled. Notably, isolated single trochanteric fracture and intertrochanteric (reverse obliquity) fracture were excluded due to the different treatment strategies (AO: 31A1.1, 31A3, and Evans Type II). Five deceased patients were excluded due to their lack of mobility status. Notably, there were no patients with chronic liver dysfunction or end-stage liver disease included in our study. The surgical procedure can be described briefly as follows: After either general or regional anesthesia, the patients were placed supine on a table with a leg holder for closed reduction. An incision (about 3 cm) was made proximal to the greater trochanter after a successful closed reduction. This was followed by the insertion of the TFNA-Nail after the measurement of intramedullary width. The femoral blade and an anti-rotational screw could be then inserted via 1 cm incisions guided by the provider instruments. After a satisfying intraoperative X-ray control, the wounds were closed and a whole-leg spica bandage was applied. ## 2.2. Data Selection The historical patient data were retrieved from the inpatient database of our hospital (Meona Ltd., Freiburg, Germany) and irreversibly anonymized before analysis in a confidential database (Microsoft Excel 2018, Microsoft Corporation, WA, USA). Demographic data, including age, gender, and body mass index (BMI), were collected. Preoperative comorbidities such as urinary tract infection (UTI), atrial fibrillation, chronic kidney disease (CKD), dementia, stroke, as well as anesthesia types, status of the American Society of Anesthesiologists (ASA), and operation length, were collected. Postoperative events within 3 postoperative days such as moderate or severe electrolyte disorder (defined as Na+ < 135 mmol/L/ > 145 mmol/L and K+ < 3.5 mmol/L/ > 5 mmol/L), pneumonia, postoperative anemia requiring blood transfusion, and treatment necessity from the intermediate care (IMC) or the intensive care unit (ICU) were also included. On the first postoperative day, blood testing was routinely performed in our laboratory institute for postoperative control, including vitamin D levels for osteoporosis diagnosis. The PNI was calculated from these laboratory results as well, using the formula: 10 × albumin value + 0.005 × total lymphocyte count from peripheral blood [10]. All patients received a high-caloric supplement (Fresubin, Bad Homburg, Germany) to compensate for the increased metabolism caused by trauma and operation. Vitamin D deficiency was orally supplemented. Specific osteoporosis therapy such as anti-resorptive therapy or bisphosphonate was not routine during the acute management. After the surgery, all patients received physiotherapy on the first postoperative day to regain mobility. Pain-adapted full weight-bearing was allowed immediately after surgery for all patients. In case full weight-bearing was not possible, a stepwise mobilization protocol with passive training, repositioning in bed, and assisted mobilization out of bed was performed. The postoperative mobilization achievements were documented daily. Patients who were mobile with or without help such as walking with a forearm walking frame, a rollator, or crutches were defined as mobilizable. Patients documented as lying, sitting, and standing were defined as immobile. The mobility status of patients on the third postoperative day, as well as by discharge was used as the outcome of the current study. ## 2.3. Statistics The statistical analysis was performed using SPSS version 29 (SPSS Inc., Chicago, IL, USA) and R version 4.0.5. Categorical data were compared using Fischer’s exact test or the Pearson chi-square test and presented as percentages. The Kolmogorov–Smirnov test was performed to verify the normality of quantitative data, which were presented with an average ± standard deviation. If confirmed, the student t-test was used to determine the significance; if not confirmed, the Mann–Whitney U test was applied. The Pearson correlation coefficient (r) was used to identify the strength of the correlation. Analysis of variance on ranks followed by the Student–Newman–Keuls method was used to estimate stochastic probability in intergroup comparison. The receiver operating characteristic (ROC) curve was performed to calculate the optimal cut-off value of PNI for the mobility on the third postoperative day by the highest Youden index. Stepwise regression was used to investigate the risk factors. Univariate logistic regression analyses were performed to filter the relevant independent variables with a p-value < 0.1 to be used in the final model. Multivariate logistic regression analyses were then performed for the final evaluation. An odds ratio (OR) greater than 1.0 indicated a higher chance of mobility, whereas an OR less than 1.0 indicated a higher chance of immobility. The area under the curve (AUC) was calculated to examine the performance of the regression models. A two-tailed $p \leq 0.05$ was considered significant. The post hoc analysis was performed using G-Power [20] (Heinrich-Heine-University, Düsseldorf, Germany). ## 3. Results A total of 156 patients who suffered trochanteric fractures and underwent surgery using TFNA™ were consecutively enrolled in the current study. The average length of hospital stay was 13.5 ± 6.4 days (ranging from 5–30 days). The probability of 1-ß error was 0.96 using the post hoc analysis. The best cut-off value of PNI to predict patients’ early mobility on the third postoperative day was 38.1 (sensitivity: $63.6\%$, specificity: $78.5\%$, and AUC: 0.73) according to the maximum Youden index using ROC. Using the best cut-off value as a reference, the patients were divided into two groups (Table 1). The result suggested that low PNI was significantly associated with age ($$p \leq 0.01$$), postoperative anemia ($$p \leq 0.01$$), the necessity of treatment in IMC ($$p \leq 0.01$$) or ICU ($p \leq 0.01$), vitamin D deficiency ($$p \leq 0.01$$), UTI ($$p \leq 0.04$$), atrial fibrillation ($$p \leq 0.02$$), dementia ($$p \leq 0.02$$), and operation length ($$p \leq 0.02$$). A negative and weak correlation was found between PNI and age (r = −0.27, y = −0.17x + 51.12, $p \leq 0.001$, Figure 1). PNI and BMI showed no significant correlation ($$p \leq 0.205$$). Univariate regression was first performed to determine the relevant independent prognostic factors for patients’ mobility three days after TFNA™ surgeries (Table 2), from which the following factors were selected for the multivariate logistic regression: PNI ($p \leq 0.0001$), the necessity of treatment in IMC ($$p \leq 0.07$$), or ICU ($$p \leq 0.03$$), vitamin D deficiency ($$p \leq 0.09$$), UTI ($$p \leq 0.09$$), atrial fibrillation ($$p \leq 0.06$$), dementia ($$p \leq 0.02$$), and stroke ($$p \leq 0.06$$). The multivariate logistic regression showed that only PNI (OR: 1.14, $95\%$ CI: 1.07–1.23, $p \leq 0.01$) was significantly associated with patients’ mobility three days after TFNA™ surgeries. The AUC of this model was 0.80. Stepwise regression was also performed to evaluate prognostic factors for the final mobility by the end of the stationary therapy (Table 3). PNI ($p \leq 0.0001$), transfusion ($p \leq 0.001$), IMC ($$p \leq 0.08$$), or ICU ($p \leq 0.001$) treatment, UTI ($$p \leq 0.04$$), and dementia ($p \leq 0.0001$) were recognized as relevant variables. The multivariate logistic regression showed that PNI (OR: 1.18, $95\%$ CI: 1.08–1.30, $p \leq 0.01$) and dementia (OR: 0.17, $95\%$ CI: 0.07–0.40, $p \leq 0.001$) were significantly related to the final mobility by discharge. With each unit increase of the PNI, there was an $18\%$ higher chance for patients to reach mobility, whereas the presence of dementia was associated with an $83\%$ chance of immobility by discharge. The AUC of this model was 0.86. The means of PNI from patients with different mobility three days after TFNA™ surgeries and by discharge were calculated, and inter-group comparisons were performed (Figure 2). The patients who were able to walk with crutches and forearm walking frames three days after TFNA™ surgeries, as well as by discharge, exhibited significantly higher PNI than immobilized patients. By discharge, the bedridden patients had a significantly lower PNI than patients walking with crutches, rollators, and walking frames. The means of PNI in patients with different AO classifications were analyzed. No significant inter-group differences were found in different severities of pertrochanteric fractures (Figure 3). ## 4. Discussion The objective of the present study was to investigate the prognostic value of the PNI on postoperative mobility in patients with trochanteric hip fractures after TFNA™ surgery. Mobility status was evaluated on the third postoperative day and by discharge in our study. In a prospective study analyzing factors influencing early postoperative mobilization, Said et al. found that only $43\%$ of patients with a hip fracture were able to mobilize within 48 h after surgery [21]. The second mobility evaluation was performed by discharge. There is a high level of clinical interest in the patient’s final status at the end of primary inpatient treatment. This might be the milestone for further therapy and the potential necessity of rehabilitation or ambulatory care. Our main finding indicated that PNI was an independent prognostic factor for mobility three days postoperatively and by discharge. An increment of each unit in PNI was associated with a $14\%$ (OR = 1.14, $p \leq 0.001$) higher probability for patients to reach mobility on the third postoperative day, and $18\%$ by discharge (OR = 1.18, $p \leq 0.001$). To our knowledge, this is the first study investigating the prognostic value of PNI to predict postoperative mobility in patients with trochanteric fractures. Dementia was a significant factor by discharge, as the presence of dementia was associated with an $83\%$ risk of immobility (OR = 0.17, $p \leq 0.001$). Hou et al. reported concurring results in a systematic review of the effects of dementia on patients undergoing hip fracture surgery [22]. Another study found that dementia was a significant factor for the unsuccessful recovery of pre-fracture walking ability by discharge in geriatric patients with hip fractures [23]. This might be due to the lack of motivation and compliance in demented patients, so they benefited less from the physiotherapeutic training. Interestingly, dementia was not a significant factor three days postoperatively. This finding implicated the fact that the acute re-mobilization shortly after the surgery depended more on the general condition than the cognitive status of the patients. However, cognitive status showed its importance in progress and in the eventual achievement of mobility at the end of the acute medical treatment. Notably, postoperative delirium (POD) was found as one of the significant factors for delayed mobilization [21]. However, POD could develop any time after the surgery, which was thus not included in our analysis as a predictive factor. All demented patients would surely have a consistent POD. Dementia from anamnesis was thus a good alternative with a good predictive perspective. Patients with a PNI below the cut-off had a significantly higher prevalence of ambulant UTI, postoperative anemia, and vitamin D deficiency. Further, low PNI was associated with the necessity of IMC or ICU treatment. This is in line with previous literature, reporting higher rates of postoperative complications, as well as a higher incidence of UTI and vitamin D deficiency in patients with low PNI [12,13,14,15]. Interestingly, our result showed that a low PNI was not associated with a higher complexity of the pertrochanteric fracture. Similar findings were described in that there was no association between the nutrition status and the severity of hip or radius fracture [24,25]. Currently, evidence on the prognostic role of PNI regarding intraoperative complications is lacking. No significant correlation could be found between BMI and PNI in the current study. This was an interesting finding suggesting that the BMI alone was misleading to reflect the real nutritional status. This was also in line with the recent opinion that obesity and malnutrition could coexist. The fat accumulation could cause nutritional derangement, affecting the nutritional status negatively both directly through metabolic change and indirectly through chronic or acute diseases [26,27]. Mean PNI was significantly lower in patients standing, sitting, or lying on the third postoperative day than in patients mobilized with crutches or a rollator. A trend was found in the current study: The higher the PNI value the better the postoperative mobilization might be. Patients with higher PNI tended to mobilize themselves more independently. By the time point of discharge, great numbers of patients made progress and were relocated to the better mobility groups. The averages of PNI were still higher in these groups compared to the groups with immobility. This implied that a greater expectation of independent mobility could be given to patients with higher PNI before discharging them from primary care even if they could not mobilize themselves well at the very beginning. The final mobility would be an interesting outcome measure. Commonly performed score systems such as fracture mobility score and Parker mobility score are often used to evaluate the 6-month functional outcome and 1-year mortality of patients, especially those with hip fractures [28]. However, these score systems were based on the mobility level after the discharge. Consequently, they cannot serve the acute assessment immediately after the surgery. Although nutritional status evaluation with PNI is widespread in the surgical region for over 40 years [10,29,30], malnutrition can be assessed by various alternative methods. There is no defined gold standard for malnutrition assessment. The geriatric nutritional risk index (GNRI), based on albumin and BMI, and the controlling nutritional status score (CONUT), based on lymphocyte count and albumin, are two alternative tools [31,32]. In comparison, PNI is easier for the physician to collect, with only simple scores from routine laboratory tests. Other methods such as MNA and NRS are screening tools based on patient data (BMI, gender, age) and questionnaires covering weight loss, eating habits, and medical history [8,9]. The reliability of answering questionnaires as a part of MNA and NRS deviates from demented patients, who could be commonly found in the geriatric patient group. A few limitations of this study should be recognized. First, it is a single-center study, data was raised retrospectively. The sample size is rather small. However, the recruited patients were all geriatric patients with trochanteric fractures and identically received TFNA™. Moreover, PNI was calculated based on postoperative laboratory results, while practically, preoperative laboratory results might serve as a better patient screening method [10]. Due to the retrospective study design, the parameters required for PNI calculation could only be collected postoperatively. Surgery may alter postoperative lymphocyte count or albumin levels. A decrease in lymphocytes in the peripheral blood after surgery due to redistribution toward lymphatic tissue has been described by Toft et al. [ 33]. Therefore, postoperative PNI calculation in the current study may lead to a systemic lowering of the values. Our findings suggest that malnutrition, assessed by PNI, could lead to reduced postoperative mobility after trochanteric fracture treatment with TFNA™. This is consistent with previous research [7,17]. It raises the question, of whether perioperative nutritional supplementation might have a positive effect on postoperative mobility in geriatric patients. Recent literature offers inconsistent results on the benefit of nutritional supplementation. A retrospective study examined the effect of oral nutritional supplementation (ONS) with enriched formula after hip surgery and reported no significant reduction of postoperative complications and mortality [34]. Williams et al. found a significantly reduced length of hospital stay (LOS) in elderly patients, who received early postoperative ONS, after hip fracture treatment [35]. However, a recent systematic review of five randomized controlled trials on the effect of preoperative ONS in hip fracture patients found a significantly lower risk of postoperative complications but no significant difference in LOS [36]. The malnourished status in geriatric patients might be a consequence of multiple factors. For example, mal-resorption due to chronic gastritis [37], swallowing disorder [38], advanced liver diseases [39], or the diet itself could all contribute to chronic malnutrition. Simply improving oral intake might not be sufficient for this complex situation. 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--- title: Ginsenoside Rb1 Improves Post-Cardiac Arrest Myocardial Stunning and Cerebral Outcomes by Regulating the Keap1/Nrf2 Pathway authors: - Long Chen - Na Geng - Taiwei Chen - Qingqing Xiao - Hengyuan Zhang - Huanhuan Huo - Lisheng Jiang - Qin Shao - Ben He journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003120 doi: 10.3390/ijms24055059 license: CC BY 4.0 --- # Ginsenoside Rb1 Improves Post-Cardiac Arrest Myocardial Stunning and Cerebral Outcomes by Regulating the Keap1/Nrf2 Pathway ## Abstract The prognosis of cardiac arrest (CA) is dismal despite the ongoing progress in cardiopulmonary resuscitation (CPR). ginsenoside Rb1 (Gn-Rb1) has been verified to be cardioprotective in cardiac remodeling and cardiac ischemia/reperfusion (I/R) injury, but its role is less known in CA. After 15 min of potassium chloride-induced CA, male C57BL/6 mice were resuscitated. Gn-Rb1 was blindly randomized to mice after 20 s of CPR. We assessed the cardiac systolic function before CA and 3 h after CPR. Mortality rates, neurological outcome, mitochondrial homeostasis, and the levels of oxidative stress were evaluated. We found that Gn-Rb1 improved the long-term survival during the post-resuscitation period but did not affect the ROSC rate. Further mechanistic investigations revealed that Gn-Rb1 ameliorated CA/CPR-induced mitochondrial destabilization and oxidative stress, partially via the activation of Keap1/Nrf2 axis. Gn-Rb1 improved the neurological outcome after resuscitation partially by balancing the oxidative stress and suppressing apoptosis. In sum, Gn-Rb1 protects against post-CA myocardial stunning and cerebral outcomes via the induction of the Nrf2 signaling pathway, which may offer a new insight into therapeutic strategies for CA. ## 1. Introduction Sudden cardiac arrest (CA) carries a high burden of mortality and morbidity worldwide, despite the ongoing efforts to improve the “chain of survival” over the past 20 years [1]. A recent study showed that the global incidence of CA was around 3.7 million every year [2]. In America, the current survival rates of out-of-hospital CA are $11.4\%$ and $10.4\%$ for children and adults, respectively, contrasted with the rates for in-hospital CA, which are $41.1\%$ and $25.8\%$ for children and adults [3]. Of those survivors, up to $60\%$ suffer from moderate to severe cognitive deficits, and $65\%$ are attacked by post-arrest myocardial dysfunction, including left ventricular diastolic or systolic dysfunction, and low cardiac index [2]. In China, more than 500,000 new cases occur annually, and the prognosis, despite successful resuscitations and the return of spontaneous circulation (ROSC), is poor due to the limited options for treatment [4]. Paying attention to the pathogenesis of CA and searching for therapies that are more efficient and potent is thus, of the utmost importance. CA results in whole-body ischemia reperfusion (I/R) injury, which is related to myocardial dysfunction and neurological deficit. Notably, mitochondria destabilization and oxidative stress act as core pathological components of CA and I/R injury [5,6]. Mitochondria is a substantial source of reactive oxygen species (ROS), and it also represents a target for its deleterious effects. Excessive oxidative stress may cause mitochondria destabilization, which induces the enhanced production of free radical, thus triggering a vicious cycle that aggravates oxidative injury, and thereby, affects oxidative phosphorylation and energy metabolism [7]. Therefore, targeting the mitochondria and oxidative stress may hold promise for therapeutic treatments. Ginseng, a naturally occurring herb, has been widely used in East Asian countries such as China, Korea, and Japan for centuries to maintain body homeostasis and energy enhancement. Ginsenoside is the main bio-active component, which is extracted from ginseng. Currently, more than 100 ginsenosides have been identified [8], of which ginsenoside Rb1 (Gn-Rb1) is the most active and abundant monomer. A recent clinical study demonstrated the protective effect of Gn-Rb1 in chronic kidney disease, and the pharmacological mechanism involved anti-oxidative stress and anti-inflammation [9]. Previous works have observed the potential benefits of Gn-Rb1 in animal models of I/R settings for various organs including the heart [10,11,12], brain [13], spinal cord [14], intestine [15], and kidney [16]. Modern pharmacology researches have revealed multiple pharmacological properties of Gn-Rb1 on the cardiovascular system, including anti-oxidative, anti-apoptotic, and anti- inflammatory [10,11,12]. However, the effects of Gn-Rb1 against post-cardiac arrest syndrome, which is complicated by the whole-body I/R injury after ROSC following CA, has hitherto remained obscure. In the current study, we found that the administration of Gn-Rb1 during the early cardio-pulmonary resuscitation (CPR) period improved post-CA myocardial stunning and secondary brain injury. These findings provided new insights into the role of Gn-Rb1 in cardioprotection, which could pave the way for developing novel therapeutic strategies for post-cardiac arrest syndrome. ## 2.1. Baseline and Procedural Characteristics of the Animals A total of 256 mice were subjected to the sham operation ($$n = 35$$) or the potassium chloride-induced CA/CPR ($$n = 221$$). In the CA/CPR group, 30 mice were used to summarize ROSC-related characteristics. Of the other 127 successfully resuscitated mice, 100 survived for more than 3 h. The remaining 100 resuscitated mice were then randomly assigned to either the 72 h group ($$n = 40$$) or the 3 h group ($$n = 60$$) for the following investigation (Figure 1b). There were no differences in the resuscitation-related variables between the post-arrest mice treated with Gn-Rb1 or not, such as chest compression rate, ventilator parameters, body weight, heart rate, body temperature, and so on. ## 2.2. Gn-Rb1 Treatment Improved the Prognosis of CA/CPR Mice Gn-Rb1 has been shown to protect the heart against I/R injury or ameliorate myocardial dysfunction in a different context [17,18,19,20,21]. However, the role of Gn-Rb1 in CA/CPR remains unknown. In the CA/CPR mouse model, no difference was observed in the ROSC rate between the CA group and CA+Rb1 group ($53.3\%$ vs. $66.7\%$ and $$p \leq 0.248$$), whereas the time for ROSC was significantly improved in the Gn-Rb1 treated group ($p \leq 0.05$) (Figure 2b,c). The effect of Gn-Rb1 in impro ving the ROSC time suggested that Gn-Rb1 may be involved in the CA/CPR period. The effect of Gn-Rb1 on the post-resuscitation restoration of cardiac function was ascertained by transthoracic echocardiography. As shown in Figure 2d–g, CA/CPR induced severe depression of the LVEF, LVFS and CO during the first 3 h following the ROSC, which were significantly improved by the Gn-Rb1 treatment (32.65 ± $1.42\%$ vs. 45.70 ± $1.36\%$, $p \leq 0.05$; 14.78 ± $2.78\%$ vs. 22.01 ± $3.08\%$, $p \leq 0.05$, and 3.88 ± 0.46 vs. 6.76 ± 0.70, $p \leq 0.05$, respectively). Of note, the LVEF, LVFS, and CO did not differ significantly between the sham-operated mice and the 12 h post-arrest mice, regardless of treatment with Gn-Rb1 or not. The survival of mice in the CA group and CA+Rb1 group was monitored for 72 h ($15\%$, 3 of 20 vs. $50\%$, 10 of 20, and $p \leq 0.05$, respectively). All ten mice in the sham group survived. The Kaplan–Meier survival curves indicated a rapid decline in survival within the first 12 h after ROSC (Figure 2h). Overall, these results indicate that Gn-Rb1 treatment during the early stage of CPR preserved the cardiac function and improved survival in CA/CPR mice. ## 2.3. Gn-Rb1 Attenuated Myocardial Oxidative Stress Following CA/CPR CA/CPR is known to trigger oxidative damage, which contributes to myocardial dysfunction [22]. To probe the mechanisms underlying the cardioprotection of Gn-Rb1, we examined the effects of Gn-Rb1 in regulating CA/CPR-induced myocardial oxidative stress. As shown in Figure 3a–f, CA/CPR remarkably induced the production of superoxide accumulation, as shown by DHE staining, as well as peroxide byproducts, such as 4 hydroxynonenal (4-HNE) and nitrotyrosine (NT). As predicted, Gn-Rb1 improved the deposition of CA/CPR-induced ROS in the myocardium. In addition, the changes in the antioxidant proteins SOD2 and oxidative markers gp91 were a partial remission by Gn-Rb1 (Figure 3g,h). As a potential site to drive the ROS production, NADH dehydrogenase was activated in cardiomyocytes during reperfusion [23]. Thus, we wondered what changes in NADH dehydrogenase would occur after CA/CPR. Our results indicated that CA/CPR activated NADH dehydrogenase, while Gn-Rb1 reduced its activity. In accordance, Gn-Rb1 inhibited the protein expression of some subunits of NADH dehydrogenase, such as NDUFS4, NDUFV1, and NDUFV2 (Figure 3i–k). Collectively, these data indicated that the improvement of cardiac dysfunction by Gn-Rb1 is partly due to its antioxidant properties. ## 2.4. Gn-Rb1 Improves Mitochondrial Homeostasis and Energy Metabolism following CA/CPR Multiple mechanisms underlying myocardial stunning have been reported, among which metabolic destabilization is one of the main culprits [24]. Mitochondrial homeostasis is a key mechanism contributing to energy metabolism. We therefore assessed the role of Gn-Rb1 on the mitochondrial dynamics and morphology, as well as ATP production, in the CA/CPR mice model. As shown in Figure 4a, the TEM analysis of the myocardial mitochondrial in CA mice revealed a substantial loss of matrix density, swelling, and cristae disruption. However, those pathological abnormalities were partially reversed by Gn-Rb1. Mitochondrial fusion and fission are considered the basic mechanisms for maintaining mitochondrial dynamics and morphology. As shown in Figure 4b,e, CA/CPR induced Drp1 translocation to the mitochondria and triggered phosphorylation of Drp1 at serine 616, whereas the Gn-Rb1 treatment prevented this effect. Notably, no significant differences were observed in the mitochondrial fusion proteins, such as OPA1 and MFN2. A reduction in the mitochondrial membrane potential (△ψ) and ATP production are hallmarks of mitochondrial dysfunction, shown in Figure 4f,g. However, Gn-Rb1 treatment improved the pathological status. ## 2.5. Gn-Rb1 Activates the Keap1/Nrf2 Signaling Pathway Next, we investigated the molecular mechanisms of Gn-Rb1 protecting the myocardium. The Keap1/Nrf2 axis is the key for the cellular regulation of redox homeostasis, mitochondrial physiology, and metabolism [20,25]. Upon cardiac I/R injury (I/R), Keap1 is inactivated and NRF2 accumulates in the nucleus. Activation of Nrf2 attenuates myocardial I/R injury [26,27]. Studies have indicated that Gn-Rb1 may participate in the regulation of the Nrf2 signaling pathway to counteract I/R injury and oxidative damage [28,29]. Accordingly, we assumed that Gn-Rb1 attenuated oxidative stress and improved mitochondrial homeostasis, partly empowered by the activation of the Nrf2 signaling pathway. As shown in Figure 5a,b, Gn-Rb1 attenuated the CA/CPR-induced up-regulation of keap1, a main repressor of the Nrf2 signal. In parallel, Gn-Rb1 promoted the translocation of Nrf2 into the nucleus, while the level of Nrf2 in the cytoplasm was down-regulated accordingly. There was no difference in the HO-1 and NQO1 proteins and the Nrf2 downstream antioxidant genes in the CA group as compared to sham, while all of which were partly up-regulated by the Gn-Rb1 treatment. This detailed mechanism needs to be further explored. Next, we introduced siRNA to knock down the Nrf2 expression (Figure 5c,d). Of note, the Nrf2 knockdown partly attenuated the Gn-Rb1-induced HO-1 expression and NQO1 expression in the context of hypoxia/reoxygenation (H/R). Collectively, the activation of the Keap1/Nrf2 axis may, in part, explain the protective effect of Gn-Rb1 in CA/CPR-induced myocardial injury. ## 2.6. Gene Knockdown of Nrf2 Attenuates the Ameliorative Effect of Gn-Rb1 on Oxidative Stress after Hypoxia/Reoxygenation(H/R) To further substantiate the involvement of Nrf2 signaling in the protective action of Gn-Rb1 in the mouse CA/CPR model, NRCM were transfected with NC siRNA or Nrf2 siRNA. As shown in Figure 6a–c, the siRNA transfection decreased Nrf2 mRNA expression by ≥$70\%$ in NRCM. The intracellular ROS level was determined by DHE staining and a fluorescent probe (DCFH-DA). Superoxide within the mitochondrial was analyzed using the MitoSOXred reagent. Gn-Rb1 alleviated H/R-induced intracellular oxidative stress and mitochondrial ROS production, while the gene knockdown of Nrf2 partly abrogated the antioxidant effects (Figure 6d,e). Consistent with this, changes in gp91 and SOD2 protein expression were affected by the knockdown of Nrf2 (Figure 6f,g). In addition, we examined the protein levels of the subunits of NADH dehydrogenase. Among the five subunits, NDUFV1 was not affected by the Nrf2. However, the Nrf2 knockdown partly offset the effect of Gn-Rb1 on the NADH dehydrogenase activity (Figure 6h,i). ## 2.7. Gene Knockdown of Nrf2 Attenuates the Ameliorative Effect of Gn-Rb1 on Mitochondrial Injury and Metabolic Destabilization after Hypoxia/Reoxygenation Mitochondrial calcium overloading and the drop of the mitochondrial membrane potential (△Ψm) were hallmarks of mitochondrial dysfunction. Therefore, we measured mitochondrial Ca2+ with Rhodamine-2 (Rhod-2) and measured mitochondrial membrane potential with JC-1 staining. As shown in Figure 7a–d, the enhancement of mitochondrial Rhod-2 fluorescence and reduction in mitochondrial transmembrane potential after reoxygenation were improved partially by Gn-Rb1, while the gene knockdown of Nrf2 partly abrogated the protective effects. We next examined the impact of Nrf2 on mitochondrial morphology. Notably, Nrf2 regulated mitochondrial fission proteins, such as p-Drp1 (ser616) in total cell and Drp1 or Fis1 in mitochondrial, while it did not affect mitochondrial fusion proteins such as MFN2 and OPA1 (Figure 7e–h). ## 2.8. Gn-Rb1 Treatment Improved Neurological Outcomes Neurological damage is one of the major cause of disability and death after CA/CPR. As shown in Figure 8a, the neurological deficit scores were dramatically improved in the Gn-Rb1-treated group before 24 h following CA/CPR. However, the differences between the two groups were not statistically significant at 72 h. Gn-Rb1 improved CA/CPR-induced oxidative injury and cell apoptosis, as shown in DHE staining and TUNEL staining. The changes in the antioxidant proteins SOD2 and oxidative markers gp91, as well as apoptosis-related or anti-apoptosis-related proteins also support this point of view (Figure 8b–i). ## 3. Discussion The present investigations offered the following new insights concerning the effects of Gn-Rb1 in post-CA myocardial stunning: (a) Gn-Rb1 significantly improved long-term survival during the post-resuscitation period, but did not affect the ROSC rate. ( b) Gn-Rb1 ameliorated CA/CPR-induced mitochondrial destabilization and oxidative stress partially via the activation of Keap1/Nrf2 axis. ( c) Gn-Rb1 improved neurological outcome after resuscitation, partially by balancing the oxidative stress and suppressing apoptosis. In summary, these findings provided the first evidence that Gn-Rb1 protected against CA-induced myocardial stunning through ameliorating mitochondrial destabilization and oxidative stress in a Nrf2-dependent manner. Our findings provide a valuable reference and great insight for developing new agents to treat CA. Previous researchers have suggested that post-CA myocardial dysfunction was reversible, and that the evolving process was consistent with myocardial stunning [30,31]. This is in agreement with clinical observations and our findings, to a certain extent. After a 12 h recovery period, the cardiac systolic and diastolic function largely returned to normal levels (Figure 2). Therefore, the effect of Gn-Rb1 on cardiac function, at this time point, was slightly less pronounced. However, insufficient cardiac output in the early post-resuscitation phase may worsen global I/R injuries, and contributes to the early deaths [32]. Accordingly, early improvement of myocardial stunning and increased support for the circulatory system are critical. We found that Gn-Rb1 significantly improved the cardiac contractility, output, and diastolic functions 3 h after the ROSC, compared with the vehicle group (Figure 2). Actually, an abundance evidence has supported the notion that Gn-Rb1 could improve cardiac function and remodeling in decompensated heart failure [19,20,33]. However, the role of Gn-Rb1 in post-cardiac arrest syndrome has not yet been identified. We demonstrated that Gn-Rb1 induced positive inotropic effects in CA/CPR mice, thus stabilizing or improving circulatory failure, resulting in a better post-resuscitation prognosis. CA is related to both global and focal I/R injuries of the heart, and one of the main pathological mechanisms of I/R injury is mitochondrial ROS burst. The vicious cycle of mitochondrial destabilization and oxidative stress is a well-known precipitating factor of post-cardiac arrest myocardial stunning [24]. Previously, multiple studies have demonstrated the therapeutic potential of Gn-Rb1 for cardiac I/R injury, and the underlying mechanisms were involved in antioxidant, antiapoptosis, and the regulation of mitochondrial homeostasis [10,34,35,36]. Therefore, we hypothesized that Gn-Rb1 protected against post-CA myocardial stunning by improving oxidative stress and mitochondrial destabilization. We found that Gn-Rb1 reduced the deposition of CA/CPR-induced superoxide and peroxide byproducts such as 4-HNE and NT (Figure 3a–f). In addition, the changes in the antioxidant proteins SOD2 and oxidative markers gp91 were a partial remission by Gn-Rb1 (Figure 3g–h). Gp91phox is the catalytic subunit of NADPH oxidase that triggers superoxide anions, and the superoxide contains the maximum burden of free radicals in I/R insult [37]. Superoxide dismutases (SOD), especially the manganese SOD (MnSOD, SOD2), is a mitochondrial antioxidant enzyme that is involved in the scavenger of superoxide [38]. NADH dehydrogenase is a key site to drive ROS production. Jiang et al. [ 10] reported that the inhibition of mitochondrial NADH dehydrogenase may elucidate the probable mechanism of Gn-Rb1 in alleviating cardiac I/R injury. As such, we examined the NADH dehydrogenase activity and the related subunit protein expression. Notably, Gn-Rb1 reduced the activity of NADH dehydrogenase, and some subunits showed corresponding changes as well, in the context of CA/CPR (Figure 3i,k). However, the expression of the subunits of NADH dehydrogenase may not necessarily be related to the activity of NADH dehydrogenase. In addition, the level of NADH dehydrogenase activity has complex concerns for the oxidation status post-CA and depends on the degree of mitochondrial electron transport chain dysfunction and organ-specificity. Therefore, further study is needed to explore these issues. All in all, our results supported the antioxidant activity of Gn-Rb1 in the CA/CPR context, which is consistent with the experimental results described in the literature [39,40]. Much of the studies in the literature have observed mitochondrial destabilization in the heart after CA/CPR, including morphologic alterations and dysfunctional disorder [41,42,43]. Actually, excessive oxidative stress triggers mitochondrial destabilization and then affects respiratory chain, ATP generation, and cell fate; while mitochondrial destabilization exacerbates oxidative injury in turn. The vicious cycle contributes to myocardial dysfunction. We found that CA/CPR triggered mitochondrial fission, while changes in mitochondrial fusion protein were not obvious (Figure 4d,e). This result was consistent with prior studies that argued for mitochondrial fission as the pathogenesis for post-CA myocardial stunning [44,45]. In addition, a reduction in ATP production and mitochondrial membrane potential (Δψ) is hallmark of mitochondrial defects. However, Gn-Rb1 treatment improves those pathological status. Gn-Rb1 has previously been reported to regulate energy metabolism in other disease settings, such as diabetic cardiomyopathy, heart failure, and I/R injury [10,19,20,21,34]. Here, we demonstrated the regulatory action of Gn-Rb1 on energy metabolism in the CA/CPR heart. Neurological damage is one of the major cause of disability and death after CA/CPR. Notably, multiple studies have demonstrated the efficacy of Gn-Rb1 in the treatment of cerebral ischemia–reperfusion injury [46,47,48]. However, whether Gn-Rb1 plays a role in CA/CPR-induced cerebral outcomes is yet to be determined. We found that Gn-Rb1 improved the neurological deficit scores in the mouse model of CA/CPR, and the pharmacological effects involved multiple mechanisms such as oxidative stress and apoptosis (Figure 8). The activation of the Keap1/Nrf2 axis might explain, at least in part, the beneficial effects of Gn-Rb1 on post-CA myocardial stunning. However, whether Gn-Rb1 functions similarly in the brain as is proposed in the heart remains unknown. Huang et al. [ 49] found that Gn-Rb1 had the effects against cerebral I/R injury, which were related to the antioxidative stress and Nrf2/HO-1 signaling pathway. Li et al. [ 50] suggested that Gn-Rb1 was capable of alleviating cerebral I/R injury in mice by the NF-κB pathway, oxidative stress pathway, and cytokine network pathway. As such, the Nrf2 signaling pathway may also explain the pharmacological effects of Gn-Rb1 on neurological damage following CA/CPR, but further study is required to unveil this issue. Nrf2, a master transcriptional regulator of redox regulation, activates adaptive responses against oxidative stress, autophagy, apoptosis, and inflammation, through the transcriptional induction of over 600 antioxidant enzymes [51]. Unstimulated, Nrf2 is sequestered by Keap1, and ubiquitinated and degraded in the cytoplasm [52]. Keap1 is inactivated under oxidative stress, allowing Nrf2 to be released from Keap1 and translocated into the nucleus. The activation of the Nrf2 signaling pathway is a major mechanism in the cellular defense against CA/CPR-induced myocardial stunning [53,54]. Our study has several limitations. First, CA was induced in healthy mice with no underlying coronary lesions or cardiac arrhythmia, which may have minimized its clinical relevance. In addition, Gn-Rb1 may exert different effects on cardiac arrest induced by structural heart disease and non-structural heart disease, and it may involve different mechanisms [55,56]. Second, the prognosis of CA was affected by systemic I/R injury, rather than single components. As such, the target organ, possibly Gn-Rb1-primary-specific, remains to be identified. Third, a well-established in vitro model mimicking CA/CPR situations is lacking currently, which disturbs the research of the underlying molecular mechanism. Fourth, we did not test the dose–response study on the mouse CA/CPR model. Fifth, whether Gn-Rb1 functions similarly in the brain as is proposed in the heart remains to be investigated in future. Thus, further investigations are needed to answer these questions. ## 4.1. Reagents and Antibodies Gn-Rb1 was purchased from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Antibodies against gp91phox, SOD2, 3-nitrotyrosine, 4 hydroxynonenal, DRP1, DRP1 (phospho S637), DRP1 (phospho S616), Mitofusin 2, OPA1, Fis1, Histone H3, caspases-3, cleaved caspases-3, and VDAC1 were obtained from Abcam (Cambridge, MA, USA). GAPDH, Bax, and Bcl-2 were obtained from Cell Signaling Technology (Beverly, MA, USA). Nrf2, keap1, NQO1, HO1, Ndufs1, Ndufv1, Ndufs6, Ndufs4, Ndufv2, and Ndufa12 were obtained from Abmart (Shanghai, China). Dihydroethidium (DHE) wasobtained from Beyotime (Jiangsu, China). ## 4.2. Experimental Animals Animal procedures were approved by the Institute’s Animal Ethics Committee of Shanghai Chest Hospital, Shanghai Jiao Tong University (Shanghai, China) (KS(Y)1839). Male C57 mice (8 weeks old) were obtained from Beijing Sibefu Biotechnology Co., Ltd. (Beijing, China) and housed at 25 ± 2 °C with 40–$60\%$ humidity under a normal 12 h light/dark cycle, with food and water available ad libitum. As described previously, the CA/CPR model was developed [53]. Briefly, mice were anesthetized using isoflurane ($1.5\%$ isoflurane/medical air mixture), and then intubated with a rodent respirator. The right jugular vein was cannulated with a polyethylene tube for fluid administration. ECG monitoring was obtained using limb electrodes. By injecting 0.08 mg of KCl/g body weight, CA was induced, and after an EKG was confirmed to be flat, the ventilator was turned off. Fourteen and a half minutes after onset of CA, mechanical ventilation resumed, and chest compression were delivered at a rate of 350–400 bpm for 15 min. After 20 s of chest compression, mice received 0.4 μg epinephrine/g body weight combined with Gn-Rb1 (50 mg/kg), or epinephrine only. This dose of Gn-Rb1 was given on the basis of previously published reports [10,17]. Additional doses of epinephrine were given at 1 min intervals until return of spontaneous circulation (ROSC) or after 5 min of CPR (Figure 1a). A total of 3 h after ROSC, mice were euthanized. Randomization was performed using simple randomization method via a random number table. The left ventricular apex tissues were embedded in OCT compound or kept in paraffin, and the residual heart tissues were then frozen at −80 °C for molecular analysis. ## 4.3. Echocardiography Cardiac structure and function were determined using the Vevo770 system (VisualSonics, Toronto, Canada) at the indicated times of post-ROSC. The mice were anaesthetized by inhalation of $2\%$ isoflurane, and M-mode images of the parasternal long axis were obtained to calculate left ventricular fractional shortening (LVFS), cardiac output (CO), and left ventricular ejection fraction (LVEF), as previously described [53]. ## 4.4. Immunohistochemistry Serial sections (5 µm) were prepared from formalin-fixed, paraffin-embedded left ventricular apex tissues. The 4 hydroxynonenal (4HNE) staining and 3-nitrotyrosine (NT) staining were used to evaluate the oxidative stress in myocardium. Quantitative image analysis of immunohistochemistry was performed using Image J analysis software [38]. ## 4.5. Dihydroethidium (DHE) Staining The collected left ventricular apex tissues and brain tissues were embedded in OCT and cut into 6 μm sections. Cryosections were washed 3 times for 5 min using PBS and incubated with 10 μmol/L dihydroethidium for 30 min. After washing with PBS 3 times again, the slides were viewed under a fluorescence microscope (DM2500, Leica). The maximum excitation wavelength is 300 nm, and the maximum emission wavelength is 610 nm. The fluorescence intensity of DHE staining was measured using ImageJ software (version 2.0.0). ## 4.6. Transmission Electron Microscopy (TEM) Mitochondrial morphology was evaluated by transmission electron microscopy, as previously described [53]. Briefly, the left ventricles were fixed, dehydrated, embedded, and cut into ultrathin slices (70 nm), and then observed and imaged using TEM (Hitachi HT-7800, Tokyo, Japan). ## 4.7. Western Blot Analysis Extraction of cytoplasm and nuclear proteins was realized using Nuclear and Cytoplasmic Protein Extraction Kit (Beyotime, China). Total proteins were extracted from heart tissues, brain tissues, or primary cardiomyocytes according to product manual (Roche, USA). Protein concentration was quantified using a BCA protein assay (Thermo Fisher Scientific). The amount of protein was adjusted to 20 μg per lane. Proteins were separated using 7.5–$12.5\%$ SDS-PAGE and transferred onto 0.22 μm PVDF membranes. After being blocked with $5\%$ BSA for 1 h and rinsed with PBS, the membrane was incubated for 12 h at 4 °C with the primary antibody. On the following day, the primary antibodies were removed with three rinses of PBS. The immunoblot bands were visualized using chemiluminescence (Millipore) via ImageQuant LAS 4000 Imager (General Electric, Pittsburgh, PA, USA.) after incubation with the corresponding secondary antibodies (ab288151, 1:10000, Abcam, Cambridge, UK) for 1 h at room temperature. The ratio of the gray value of the target bands to the internal reference band (GAPDH) was used as the relative expression of the protein. ## 4.8. Real-Time Quantitative PCR Total RNA from cells or tissues was extracted using TRIzol® reagent (Invitrogen, USA). Isolated RNA was reverse-transcribed and duplicated using PrimeScript™ RT Master Mix (Vazyme, Nanjing, China) and SYBR qPCR master mix (Vazyme, Nanjing, China) in iScript cDNA Synthesis Kit (Takara BIO, Otsu, Japan) and the Light-Cycler 480 Real-Time PCR System (Roche, San Francisco, CA, USA). Primers sequences are listed in Supplementary Table S1. The results were normalized to GAPDH and expressed as percentage of controls. ## 4.9. Terminal Deoxynucleotidyl Transferase dUTP Nick-End Labelling (TUNEL) Assay TUNEL staining was performed using a TUNEL Apoptosis Assay Kit (Beyotime, Shanghai, China). TUNEL-positive nuclei were identified as apoptotic cells stained with FITC (green), and nuclei were simultaneously counterstained with DAPI. Images were captured using a Leica DMIRE2 fluorescence microscope. The excitation wavelength range was 450–500 nm, and the emission wavelength range was 515–565 nm. TUNEL-positive signals were normalized to the total nuclei signals for each field. ## 4.10. Mitochondrial Isolation Mitochondrial isolation from the hearts or NRCMs was performed using the Mitochondrial Isolation Kit (Beyotime, Shanghai, China) [25]. Briefly, cells and tissue were mechanically homogenized for 30 strokes using a tight pestle on ice in mitochondrial isolation buffer added with PMSF, and centrifuged at 600 g for 10 min at 4 °C, and then the resulting supernatant was centrifuged again at 11,000 g for 10 min at 4 °C to obtain mitochondria. The isolated mitochondria and cytoplasm were used for subsequent experiments. ## 4.11. Cell Culture and Transfection The neonatal rat cardiomyocytes (NRCMs) were isolated from heart ventricles of 1- to 3-day-old SD rats [57]. In brief, the ventricles were minced and digested with collagenase type II (Invitrogen) and pancreatase myocyte digestion buffer (Sigma-Aldrich, USA). After differential adhesion, the supernatants of primary cultures of myocardial cells were plated and then grown in DMEM with $10\%$ FBS (fetal bovine serum, GIBCO, Billings, MT, USA), 100 U/mL penicillin, and 100 μg/mL streptomycin at 37 °C and $5\%$ CO2 for 48 h. NRCMs at a density of 50–$70\%$ were transfected with Nrf2 small interfering RNAs (siRNAs, 50 nM, purchased from Genepharma, Shanghai, China) to silence Nrf2 using Lipo3000 (Invitrogen, Carlsbad, CA, USA). Sequences of the Nrf2 siRNA sequence were as follows: forward oligo, 5′-GGAUGAAGAGACCGGAGAAUU tt-3′, reverse oligo, and 5′-AAUUCUCCGGUCUCUUCAUCC tt-3′. We investigated the following groups after 72 h of transfection. Standard incubators were used to culture the blank group without transfection. Cells transfected with Nrf2 siRNA (Nrf2 siRNA group), or negative control siRNA (NC group) were exposed to hypoxia for 12 h and reoxygenation for 3 h, to simulate I/R injury. Based on Nrf2 siRNA group and NC group, Nrf2 siRNA+Rb1 group and NC + Rb1 group were treated with Gn-Rb1 (10 µM) during reoxygenation for 3 h [10,14,34]. ## 4.12. Detection of Cellular Reactive Oxygen Species Production of reactive oxygen species (ROS) was detected using DCFH-DA fluorescent probe kit (Beyotime, Shanghai, China). In brief, the plates were incubated in the dark for 20 min with DCFH-DA (10 M), and then cells were washed 3 times to remove DCFH-DA. Subsequently, cells were visualized using Leica DMIRE2 fluorescence microscope. We used 488nm excitation wavelength and 525 nm emission wavelength. ## 4.13. Detection of Mitochondrial ROS (mROS) mROS production was measured using MitoSOX Red (Invitrogen, USA). In brief, cells from different groups were washed 3 times with PBS and incubated for 30 min with 1 µM MitoSOX Red, and then counterstained with Hoechst. After washing 3 times with PBS, images of mROS level were obtained (Excitation/Emission $\frac{396}{610}$ nm) using a fluorescence microscope (Leica DM400B, Leica Microsystems, Ltd., Wetzlar, Germany). ## 4.14. Assessment of Neurological Function A 12-point mouse neurologic scoring system was used to assess neurological deficits in mice after CA [58]. Six domains were evaluated with scores ranging from 0 (no response) to 2 (normal): righting reflex, motor-focal, breathing, spontaneous movement, paw pinch, and motor-global. For each domain, a blinded score was calculated and summed to obtain a neurologic score. The comparisons between the two groups were performed using unpaired t-test. ## 4.15. Cellular ATP Assay Cellular ATP levels were measured using the Enhanced ATP Assay Kit (Beyotime, Shanghai, China). The cardiac tissues and treated NRCMs were lysed with ATP assay lysis buffer. The lysed cells were centrifuged in 12,000 g for 5 min at 4 °C, and then we collected supernatant. Afterward, we added ATP detection working solution to a 96-well black plate and incubated for 5 min, and then added supernatant to the plate quickly. The RLU of samples was detected by luminometer within 30 min. We normalized the luminescence signals to the protein concentrations in order to calculate the total ATP levels. ## 4.16. Mitochondrial Membrane Potential Examination A mitochondrial membrane potential assay kit with JC-1 (Beyotime, China) was used to detect the mitochondrial membrane potential. Briefly, cells were incubated with JC-1 working solution for 20 min, and then washed twice with JC-1 staining buffer. Cells were imaged using fluorescence microscope (Leica Microsystems). The potential gradient of the mitochondrial membrane potential (Δψm) was indicated by the ratio of green fluorescence to red fluorescence. For heart tissue, the isolated mitochondria were incubated with JC-1, as described previously. Green (488 nm excitation and 530 nm emission) and red (543 nm excitation and 590 nm emission) fluorescence were detected by Fluoromax-2 spectrophotometer (Horiba Jobin Yvon, Paris, France). ## 4.17. NADH Dehydrogenase Activity Assays NADH dehydrogenase activity assay was performed using the kit of Tong Wei (TW, reagent, Shanghai, China) according to the manufacturer’s instructions. Briefly, mash the tissue with an appropriate amount of normal saline, and then put it in 3000 centrifuge for 10 min to obtain the supernatant. In the micropores coated with NADH dehydrogenase antibodies, samples, standard samples, and HRP-labeled antibodies were added successively, incubated (37 ℃, 60 min), and washed thoroughly. The substrate TMB was used to develop color. The absorbance (OD value) was determined by enzyme-labeling instrument at 450 nm wavelength, and the activity of the sample was calculated. Protein concentration was determined by BCA method. ## 4.18. Statistical Analyses The normality of data distribution was tested using the Shapiro–Wilk normality test. Normally distributed variables were presented as means ± standard deviation (SD), while categorical variables were presented as frequencies or percentages. To test for statistical significance, continuous variables following normal distribution were compared using Student’s t-test, while data that did not follow a normal distribution were analyzed by using non-parametric test. Comparisons among multiple groups were performed using one-way ANOVA. Categorical data were compared using the Chi-square test. For survival analysis, Kaplan–Meier survival analysis was used, and comparisons between groups were made using a log-rank (Mantel–Cox) test. $P \leq 0.05$ was considered statistically significant. All analyses were performed using Graph-Pad Prism 8 (GraphPad Software, LLC, San Diego, CA, USA). ## 5. 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--- title: 'Simvastatin Improves Benign Prostatic Hyperplasia: Role of Peroxisome-Proliferator-Activated Receptor-γ and Classic WNT/β-Catenin Pathway' authors: - Zhen Wang - Shu Yang - Yan Li - Yongying Zhou - Daoquan Liu - Jianmin Liu - Michael E. DiSanto - Xinhua Zhang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003121 doi: 10.3390/ijms24054911 license: CC BY 4.0 --- # Simvastatin Improves Benign Prostatic Hyperplasia: Role of Peroxisome-Proliferator-Activated Receptor-γ and Classic WNT/β-Catenin Pathway ## Abstract Benign prostatic hyperplasia (BPH) is a common disease in elderly men with an uncertain etiology and mechanistic basis. Metabolic syndrome (MetS) is also a very common illness and is closely related to BPH. Simvastatin (SV) is one of the widely used statins for MetS. Peroxisome-proliferator-activated receptor gamma (PPARγ), crosstalking with the WNT/β-catenin pathway, plays important roles in MetS. Our current study aimed to examine SV-PPARγ-WNT/β-catenin signaling in the development of BPH. Human prostate tissues and cell lines plus a BPH rat model were utilized. Immunohistochemical, immunofluorescence, hematoxylin and eosin (H&E) and Masson’s trichrome staining, construction of a tissue microarray (TMA), ELISA, CCK-8 assay, qRT-PCR, flow cytometry, and Western blotting were also performed. PPARγ was expressed in both prostate stroma and epithelial compartments and downregulated in BPH tissues. Furthermore, SV dose-dependently triggered cell apoptosis and cell cycle arrest at the G0/G1 phase and attenuated tissue fibrosis and the epithelial–mesenchymal transition (EMT) process both in vitro and in vivo. SV also upregulated the PPARγ pathway, whose antagonist could reverse SV produced in the aforementioned biological process. Additionally, crosstalk between PPARγ and WNT/β-catenin signaling was demonstrated. Finally, correlation analysis with our TMA containing 104 BPH specimens showed that PPARγ was negatively related with prostate volume (PV) and free prostate-specific antigen (fPSA) and positively correlated with maximum urinary flow rate (Qmax). WNT-1 and β-catenin were positively related with International Prostate Symptom Score (IPSS) and nocturia, respectively. Our novel data demonstrate that SV could modulate cell proliferation, apoptosis, tissue fibrosis, and the EMT process in the prostate through crosstalk between PPARγ and WNT/β-catenin pathways. ## 1. Introduction Benign prostate hyperplasia (BPH), characterized by unregulated hyperplasia of the periurethral prostate gland, is the most common disease among elderly men, increasing sharply with age, from $50\%$ in men older than 50 years to almost $80\%$ in men aged over 80 years old [1,2]. BPH contributes to lower urinary tract symptoms (LUTSs). Both BPH and LUTSs greatly impact quality of life (QoL) and lead to severe financial burden [3,4,5]. It is known that BPH is closely associated with aging and androgen levels [6]. Although the molecular mechanism of BPH has been extensively studied, including the imbalance between cell proliferation and apoptosis, stromal–epithelial interactions, abnormal sex hormone ratio, cytokines and growth factors, autoimmune and inflammation, stem cells, and oxidative stress (OS) [7,8], the exact pathogenesis remains unclear. In recent years, numerous studies have shown that metabolic syndrome (MetS) is closely related to BPH/LUTSs [9,10,11]. With the improvement of people’s living standards, the incidence of MetS has increased tremendously [12]. A sedentary lifestyle, higher socioeconomic status, high waist circumference, and central obesity are significantly attributed to the development of MetS [13,14], consisting of dyslipidemia, hypertension, hyperglycemia, and visceral obesity [15]. In addition, Hammarsten et al. proposed that BPH could be viewed as a novel aspect of MetS [16]. Indeed, $48.59\%$ of MetS patients are complicated with BPH (MetS-BPH), including its onset, occurrence, and progression [17,18]. Actually, Vignozzi et al. found that rabbits with MetS developed dyslipidemia, increased the accumulation of visceral fat, and decreased gonadotropin, excessive estrogen, and prostatic inflammation [19]. They also proposed that BPH may be a novel metabolic disease [20]. In addition, several studies have revealed that dyslipidemia plays a crucial role in prostate cell proliferation and differentiation and prostate volume change, suggesting that MetS can be used as an independent predictor of BPH/LUTS [21,22,23], especially for total prostate volume > 40 mL [24]. In contrast, high-density lipoprotein cholesterol levels were negatively correlated with total prostate volume, transition zone volume, and intravesical prostatic protrusion [25]. Statins, such as simvastatin (SV), are widely used to suppress cholesterol synthesis by inhibiting 3-hydroxy-3-methylglutaryl-Coenzyme A (HMG-CoA) reductase activity. In addition to lowering cholesterol, statins have anti-proliferative, pro-apoptotic, anti-fibrotic, anti-inflammatory, antioxidant, and protective effects on the vascular endothelium [26,27,28,29]. Indeed, statins have been shown to improve the prognosis of BPH [30]. A prospective study by Zhang et al. [ 31] showed that SV could significantly reduce prostate volume (PV) and slow the clinical progression of BPH/LUTS. However, the specific mechanism of SV in the development of BPH is still unclear. Moreover, previous studies demonstrated that SV ameliorated heart failure [32] and other cardiovascular events by activating Peroxisome-proliferator-activated receptor gamma (PPARγ)-dependent pathways [33], and modulation of PPARγ signals helps provide pleiotropic protection of SV [34]. PPARγ, a ligand-activated transcription factor and a representative member of the nuclear receptor (NR) superfamily [35], is mainly expressed in adipose tissue and participates in lipid metabolism by selectively enhancing lipid uptake via inducing lipogenesis and increasing lipid storage [36]. More specifically, PPARγ could increase the expression of lipoprotein lipase (LPL), phosphoenolpyruvate carboxykinase (PEPCK), and perilipin, thereby promoting fatty acid storage in adipocytes instead of lipolysis to fatty acid release [37]. PPARγ is activated by binding its ligand-binding domain (LBD), either by a natural ligand (15D-prostaglandin J2, 15D-PGJ2) [38] or a synthetic ligand (thiazolidinedione, TZD) [39]. It then forms heterodimers with the nuclear receptor retinoid X receptor α (RXRα), finally combining with genomic DNA at specific sites [40]. Therefore, it could regulate metabolism, immunity, inflammation, cell differentiation, and cell proliferation [36,41,42]. Several studies have shown that PPARγ plays a crucial role in neural cell differentiation and tumor cell growth [43,44,45]. It was observed that the knockdown of PPARγ in normal human prostate cell lines decreased the expression of prostate differentiation markers [46]. PPARγ can also interfere with prostate cancer cell growth by regulating androgen receptor (AR) levels and activity [47,48,49]. Furthermore, PPARγ is involved in the regulation of the epithelial–mesenchymal transition (EMT) of cancer stem cells and alveolar lipofibroblast [50,51]. Interestingly, PPARγ could reverse pulmonary fibrosis by dedifferentiating myofibroblasts [52]. Finally, it is also known that activation of PPARγ could inhibit classical WNT/β-catenin pathway signaling. On the other hand, WNT/β-catenin pathway activation could lead to PPARγ inactivation in many tissues [53]. Canonical WNT signaling is mediated by the interaction of WNT ligands with specific targets, leading to cytosolic β-catenin aggregation and nuclear translocation, whose nuclear activation triggers the stimulation of downstream factors [54]. Subsequently, it could induce several process, such as cell proliferation, differentiation, apoptosis, inflammation, fibrosis, and EMT [55,56,57,58,59]. Importantly, dysregulation of the classical WNT pathway has been observed in most cancers and other human diseases including BPH [56,58]. In our current study, we investigated the localization of PPARγ in human prostate tissues and the relative expression profiles in normal and hyperplastic prostate tissues. We further treated human prostate cells with SV and a PPARγ inhibitor (GW9662) to detect changes in cell proliferation, cell cycle, apoptosis, fibrosis, and EMT-related markers, and also to detect genes involved in the canonical WNT/β-catenin pathway. In addition, a rat model of BPH established by testosterone supplementation was treated with SV and restored with GW9662 to elucidate the specific role and mechanism of SV in BPH via PPARγ and WNT/β-catenin. ## 2.1. The Expression and Localization of PPARγ in Human Prostate Tissues and Cell Lines Normal (8 control samples) and hyperplastic prostate tissues (8 BPH samples) were harvested from patients and donors at our institute. The mRNA and protein levels of PPARγ were more than four times and three times higher in the normal prostate than in the hyperplastic prostate, respectively (Figure 1A,B). In addition, immunofluorescence showed that PPARγ was localized in both the epithelial and stromal compartments of the human prostate (Figure 1C,D). Similarly, PPARγ expression was localized in the cytoplasm and nucleus of BPH-1 and WPMY-1 cells. ## 2.2. SV Inhibits Cell Survival by Promoting Cell Apoptosis and Inducing G0/G1 Phase Arrest through PPARγ Human prostate cells were treated with 1 μM and 5 μM SV. The CCK-8 assay was used to detect cell viability. SV inhibited BPH-1 and WPMY-1 cell survival in a dose-dependent manner with significant differences observed at days 2, 3, and 4 (Figure 2C). In addition, the mRNA and protein levels of PPARγ in both cell lines were dose-dependently elevated (Figure 2A,B). Flow cytometry analysis was used to detect the effects of SV on the cell cycle and apoptosis. As shown in Figure 2D, the percentage of apoptotic BPH-1 and WPMY-1 cells increased significantly at 1 μM ($p \leq 0.01$) and 5 μM ($p \leq 0.01$). Furthermore, SV significantly increased the proportion of G0/G1 cells in BPH-1 ($p \leq 0.01$) and WPMY-1 ($p \leq 0.001$) cells at 1 μM. More significant differences were shown at higher concentrations of 5 μM (Figure 2E). We further examined related proteins involved in apoptosis and the cell cycle by Western blot, showing a dramatic upregulation of BAX and downregulation of Bcl-2, as well as a significant decrease in proteins involved in the regulation of the G0/G1 phase of the cell cycle (CDK$\frac{2}{4}$ and Cyclin D1). Moreover, we also found an increase in Cyto c, indicating that SV can promote prostate cell apoptosis in a mitochondria-dependent manner (Figure 2F). Subsequently, both cells were preincubated with/without 20, 40, and 60 μM PPARγ antagonist GW9662 and then treated with 5 μM SV. Consistently, 5 μM SV resulted in cell apoptosis and triggered cell cycle arrest at the G0/G1 phase in BPH-1 and WPMY-1 cells (Figure 3A,B), which were reversed in a dose-dependent manner by pretreating with PPARγ antagonist GW9662 (Figure 3A,B). In addition, both cell-cycle- and apoptosis-related protein alterations induced by SV were significantly reversed by GW9662 (Figure 3C). Additionally, SV-mediated upregulation of PPARγ was reversed by its antagonist GW9662 (Figure 3C). ## 2.3. SV Attenuates Fibrosis and EMT Process in Prostate Cells through PPARγ Pathway We further investigated the effect of SV on relevant indicators of EMT and fibrosis in prostate cells. As shown in Figure 4A,B, in SV-treated BPH-1 cells, it was observed that E-cadherin expression was amplified, whereas N-cadherin, Vimentin, and Snail were significantly lowered at both mRNA and protein levels. In addition, SV significantly suppressed the mRNA and protein expression of fibrosis markers α-smooth muscle actin (α-SMA) and collagen I in WPMY-1 cells (Figure 4C,D). Again, PPARγ antagonist GW9662 significantly rescued the aforementioned changes produced by SV (Figure 4E,F). ## 2.4. WNT/β-Catenin Pathway Crosstalks with PPARγ in Prostate Cells The WNT/β-catenin pathway is closely related to PPARγ as a fundamental signaling pathway with a wide range of effects. SV dose-dependently attenuated the protein levels of WNT-1 and β-catenin in BPH-1 and WPMY-1 cells (Figure 5A). On the other hand, this inhibitory state generated by 5 μM SV could be abolished by PPARγ antagonist GW9662 in a concentration-dependent manner (Figure 5B). Moreover, 10 μM WNT/β-catenin pathway activator HLY78 could restore the SV-induced alterations of proteins (E-cadherin, BAX, and Cyto c were upregulated; N-cadherin, Vimentin, Snail, α-SMA, collagen I, Bcl-2, CDK$\frac{2}{4}$, Cyclin D1 were downregulated) (Figure 5C). Interestingly, PPARγ upregulated by SV was similarly rescued with pretreatment of HLY78, maintaining a negative correlation with β-catenin (Figure 5C). ## 2.5. SV Suppressed BPH by Increasing PPARγ In Vivo The BPH rat model was demonstrated by an increase in the weight of androgen-sensitive organs (1.8-fold and 2-fold increase in the ventral prostate and seminal vesicle, respectively) (Figure 6A and Supplementary Table S1, $p \leq 0.01$). Meanwhile, the body weight of BPH rats was significantly reduced (Supplementary Table S1, $p \leq 0.01$). The Prostate index (prostate wet weight (mg)/body weight (g)) of BPH rats was 2.5-fold higher than that of controls (Supplementary Table S1, $p \leq 0.01$). The body weight and ventral prostate weight of the SV-treated rats were decreased by $10.8\%$ and $23\%$, respectively, and the prostate index decreased by $26.7\%$ (Figure 6A and Supplementary Table S1, $p \leq 0.01$). When GW9662 was administered 15 min before each SV treatment, it was found that the body weight and ventral prostate weight of the SV-treated rats increased by 1.1-fold and 1.2-fold, respectively, and the prostate index increased by 1.4-fold (Figure 6A and Supplementary Table S1, $p \leq 0.05$). Triglycerides and cholesterol in rat serum were measured by ELISA. SV can significantly reduce the serum concentrations of triglyceride and cholesterol, and GW9662 can reverse these changes to a certain extent (Figure S1A,B, $p \leq 0.001$). H&E and Masson trichrome staining were used to observe the histopathological differences of rats in different treatment groups. In BPH rats, BPH mainly occurred in the epithelium, and epithelial cells within the gland are multilayered or with protrusion into the lumen of the papillary lobe. Nevertheless, SV blocked the progression of BPH induced by testosterone. Atrophied glands are lined with a single columnar epithelium to low cubic cells with mild edema. GW9662, in turn, counteracted the effect of SV (Figure 6B). Masson trichromic staining further confirmed that BPH mainly occurred in the epithelium (1.4-fold increase in epithelial cells, $p \leq 0.05$), while there was no significant difference in stromal components in BPH rats. Interestingly, the stromal component was lower (SM loss of $44.3\%$, collagen loss of $49.8\%$) in the SV-treated BPH rats, besides the epithelial component being reduced by $25.5\%$. In GW9662-plus-SV-treated BPH animals, the epithelial component was elevated by 1.2-fold when compared with the SV-treated group, while the stromal component increased more significantly (SM increased by 1.5-fold, collagen increased by 1.6-fold) (Figure 6C,D). Consistent with our in vitro findings, GW9662 rescued PPARγ that was upregulated by SV in vivo (Figure 6G). The expression of BAX and E-cadherin was upregulated and the expression of α-SMA, collagen I, Bcl-2, CDK2, CDK4, Cyclin D1, N-cadherin, Vimentin, Snail, WNT-1, and β-catenin was downregulated in BPH rats treated with SV. GW9662 significantly ameliorated the above changes induced by SV (Figure 6E–G). ## 2.6. PPARγ/WNT-1/β-Catenin Is Associated with Several Clinical Parameters in Patients with BPH Finally, we obtained BPH tissues from 104 patients and constructed tissue microarrays (TMAs). The percentage of PPARγ, WNT-1, and β-catenin-positive area on the TMA was calculated. As shown in Figure 7 and Figure 8, positive staining for PPARγ, WNT-1, and β-catenin was observed in both the stromal and epithelial compartments of the human prostate. In addition, we analyzed the correlation among the expression of these three proteins in TMA. PPARγ was negatively correlated with β-catenin, but not with WNT-1 (Table 1). As important markers of the WNT/β-catenin pathway, WNT-1 and β-catenin have a very strong positive correlation (Table 1). Meanwhile, we also analyzed the correlation between the expression of these proteins and clinical data. Interestingly, PPARγ was negatively correlated with prostate volume (PV) and free prostate-specific antigen (fPSA) and positively correlated with maximum urinary flow rate (Qmax) (Table 2). WNT-1 and β-catenin exhibited a positive relationship with International Prostate Symptom Score (IPSS) and nocturia, respectively (Table 2). ## 2.7. Overview of SV-PPARγ-WNT/β-Catenin Pathway in BPH As shown in Figure 9, SV can regulate target genes through crosstalk between PPARγ and WNT/β-catenin pathways, such as CDK2, CDK4, cyclin D1, BAX, Bcl-2, N-cadherin, Vimentin, Snail, E-cadherin, α-SMA, and collagen I, which subsequently regulate cell proliferation, cell apoptosis, the cell cycle, EMT, and the fibrosis process. ## 3. Discussion Our novel data show that PPARγ is localized in the epithelial and stromal compartments of human prostate tissue and is downregulated in hyperplastic prostate tissue. We also demonstrate that SV ameliorates the progression of BPH both in vivo and in vitro through apoptosis, cell cycle arrest at the G0/G1 phase, attenuation of tissue fibrosis, and the EMT process via upregulating PPARγ and inhibiting the WNT/β-catenin pathway. SV is one of the established statins for the treatment of MetS/hyperlipidemia. Recently, statins were also observed to exhibit therapeutic advantages in patients with BPH/LUTS [31]. Actually, BPH is now regarded as a metabolic disease. As a kind of drug for lowering cholesterol, statins have anti-proliferative, pro-apoptotic, anti-fibrotic, anti-inflammatory, antioxidant, and protective effects on the vascular endothelium [26,27,28,29]. Moreover, it was reported that the PPARγ pathway could contribute to SV, mediating the aforementioned biological process [33]. However, statin-PPARγ signaling had not been completely elucidated, especially for BPH. PPARγ is a transcription factor belonging to the nuclear receptor superfamily [35]. Genome-wide integration analysis of human-tissue-specific expression [60] has shown that PPARγ is widely expressed in adipose tissue, colon, placenta, bladder, prostate, and other tissues. There are two major isoforms of PPARγ, PPARγ1, and PPARγ2, derived from separate transcription start sites. They are mainly expressed in adipose cells, but PPARγ1 is also expressed at low levels in other tissues, such as the liver, brain, macrophages, and muscle [61,62]. Studies have shown that the expression level of PPARγ1 in human subcutaneous and visceral fat is negatively correlated with obesity, while the expression level of PPARγ2 in human fat is positively correlated with obesity [63]. KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis revealed that the PPARγ1-specific peaks were enriched for pathways that include the PPAR signaling pathway and regulation of lipolysis in adipocytes, while PPARγ2-specific peaks were enriched for the cAMP signaling pathway and vascular smooth muscle contraction pathway [64]. In addition, PPARγ1 plays an important role in cancer. The PPARγ1 ligand can induce G0/G1 phase arrest of human hepatoma cells, and phosphorylation of PPARγ1 can reduce its transcriptional activity and promote the proliferation of human fibrosarcoma cells [65,66]. However, another study has demonstrated that endogenous PPARγ1 could promote ErbB2-mediated breast tumor occurrence and development [67]. Recently, Fang et al. [ 68] found that PPARγ1 and PPARγ2 regulated the proliferation, apoptosis, and differentiation of proadipocytes in the same way, and the effect of PPARγ2 is more obvious than that of PPARγ1 in the presence of ligands. In conclusion, the specific functions and differences of PPARγ1 and PPARγ2 need to be further studied. Indeed, our current study showed that PPARγ was abundantly expressed in cultured human prostate cell lines, human prostate tissues, and rat ventral prostate. Consistent with a report from Forootan et al. [ 69], we observed that PPARγ was expressed both in the prostate epithelium and stroma, determined via immunohistochemical staining. Moreover, we found that both the mRNA and protein expression levels of PPARγ were downregulated in the hyperplastic prostate compared with the normal prostate. To further explore the underlying mechanisms, human prostate cell lines, BPH-1 (epithelial cells) and WPMY-1 (stromal cells), were used and both cell lines were treated with various concentrations of SV. We observed that SV inhibited cell proliferation and caused cell cycle arrest at the G0/G1 phase by reducing the abundance of proteins involved in G0/G1 phase regulation (CDK$\frac{2}{4}$ and cyclin D1). Simultaneously, upregulation of BAX (a proapoptotic molecule) and downregulation of Bcl-2 (an antiapoptotic molecule) activated intrinsic apoptotic pathways leading to increased apoptosis [70]. This pathway is associated with disruption of the mitochondrial outer membrane potential (MOMP) through BAX activation, leading to the release of cytochrome C from the intermembranous space of mitochondria to the cytoplasm and making cytochrome C further activate BAX [71]. Thus, our data indicated that SV could induce mitochondria-mediated apoptosis. Furthermore, we also observed that SV incubation upregulated the mRNA and protein levels of PPARγ in prostate cells, which was parallel to studies on liver cancer cells and bladder cancer cells [72,73]. In addition to cell growth and death, studies have shown that EMT-involved accumulation of mesenchymal cells was another important process in the development of BPH [74,75,76]. The present study did demonstrate that SV inhibited the EMT process in BPH-1 cells, in which the level of the epithelial marker E-cadherin was upregulated, while the levels of mesenchymal markers N-cadherin, Vimentin, and Snail were downregulated. Moreover, fibrosis could be attributed to BPH progression, which is not responsive to current first-line drugs (α-blockers and 5α-reductase inhibitor) and often leads to surgical intervention. In our current study, we determined that SV incubation decreased the protein expression levels of fibrosis markers α-SMA and collagen I in cultured WPMY-1 cells. Therefore, SV could inhibit cell proliferation, induce apoptosis, and attenuate the EMT and fibrosis process in the prostate. It has been shown that statins can trigger apoptosis in human lung cancer cells [34], and prevent cell proliferation and EMT in bladder cancer cells through a PPARγ-dependent pathway [73]. To determine whether the aforementioned SV-induced effects on prostate cells were PPARγ-dependent, we pretreated BPH-1 and WPMY-1 cells with the PPARγ-antagonist GW9662. Indeed, SV-induced PPARγ upregulation, increased apoptosis, and attenuated proliferation were significantly reversed by GW9662. This was further supported by the changes in protein levels with increased CDK$\frac{2}{4}$ and cyclin D1, lowered BAX, and elevated Bcl-2. Moreover, the SV-generated inhibition of EMT and the fibrosis process were also recovered by antagonization of PPARγ. Therefore, the alterations produced by SV could be mediated through PPARγ-dependent signaling. Additionally, our current study demonstrates that SV-induced upregulation of PPARγ is accompanied by downregulation of the WNT/β-catenin pathway (decreased WNT-1 and β-catenin protein levels). In addition, this change was reversed by pretreatment of cells with GW9662. On the other hand, when cells were pretreated with the WNT/β-catenin agonist HLY78, we observed that SV-induced PPARγ elevation was blocked. Consistently, interactions between PPARγ and WNT/β-catenin pathways had been found in arrhythmogenic right ventricular cardiomyopathy and type 2 diabetes [53]. Moreover, we show that HLY78, like GW9662, can partially reverse the above biological changes generated by SV in prostate cells. Thus, SV could modulate cell growth, cell death, EMT, and fibrosis in prostate cells through crosstalk between PPARγ and the WNT/β-catenin pathway. Similarly, the inverse interaction between the canonical WNT/β-catenin pathway and PPARγ has been demonstrated in many diseases. In cancers, such as glioma and colon cancer, the canonical WNT/β-catenin pathway is upregulated in association with decreased PPARγ expression [77,78]. However, cardiovascular diseases such as cardiac hypertrophy and cardiac overload are diseases in which the canonical WNT/β-catenin pathway is reduced and PPARγ is upregulated [53]. In fact, PPARγ and the WNT/β-catenin pathway interact through a catenin-binding domain within PPARγ and a TCF/LEF β-catenin domain [79,80]. GSK-3β is known to be one of the components of the beta-catenin destruction complex. The phosphatidylinositol 3 kinase/protein kinase B (PI3K/AKT) pathway negatively regulates PPARγ expression through phosphorylation of GSK-3β [81]. In addition, PPARγ agonists activate GSK-3β to reduce β-catenin expression [82]. Therefore, there is a negative correlation between PPARγ and β-catenin, which is consistent with the results of our in vitro and in vivo experiments and TMA. In addition, PPARγ agonists activate Dickkopf-1 (DKK1, a WNT inhibitor) to reduce the canonical WNT/β-catenin pathway [83]. DKK1 can competitively bind lipoprotein-receptor-related protein $\frac{5}{6}$ (LPR$\frac{5}{6}$) to block the associations between WNT-1 and LPR$\frac{5}{6}$, thus antagonizing WNT signaling [84]. Our in vitro experiments reveal a negative correlation between PPARγ and WNT-1, but TMA shows no significant correlation between them. This may be due to the insufficient sample size of our TMA. We further translated our in vitro studies into in vivo. Our BPH model induced by testosterone propionate was confirmed by a significant weight increase of the prostate and seminal vesicles when compared with the controls. In addition, SV treatment was validated with significantly lowered serum cholesterol and triglycerides. Similar to our previous observation, a body weight loss was found in BPH rats, which may be due to an increase in daily activities and an increase in lean body mass/fat body mass ratio caused by exogenous testosterone supplementation. Therefore, BPH rats had an even higher relative prostate weight/body weight ratio than that of controls. In addition, consistent with previous studies [85,86], T injection mainly resulted in a significant degeneration of acinar epithelial hyperplasia, such as increased acinar number, protrusion of papillary lobes into the glandular lumen, and thickening of the epithelial layer without a change in the percentage of stromal components. However, the relative prostate weight/body weight ratio of BPH rats was significantly decreased by SV (i.g.) for 28 days. Unlike untreated BPH animals, both epithelial and stromal components of the prostate were reduced in SV-treated BPH rats, which was possibly attributed to SV affecting both the stroma and epithelium. Instead, T mainly showed an influence on the gland. Parallel to our in vitro experiments, GW9662 could significantly reverse the therapeutic effect of SV on the prostate. Moreover, Western blot showed that SV increased the expression of PPARγ, BAX, E-cadherin, and Cyto c and decreased the expression of CDK2, CDK4, cyclin D1, Bcl-2, α-SMA, collagen I, N-cadherin, Vimentin, and Snail. In addition, PPARγ antagonist GW9662 (i.p.) reversed the above changes induced by SV to a certain extent. All these in vivo observations are consistent with our in vitro findings. Recently, Gong et al. [ 87] reported that SV alleviated prostatic hyperplasia by alleviating local inflammation in prostate tissue. In their study, the BPH rat model was induced by a high-fat diet and no relevant human tissues and cells data. In addition, their study focused on inflammation-related signaling, instead of PPARγ. Another previous study [88] found that atorvastatin ameliorated T-induced rat BPH. Their study did not provide human data; however, they revealed an inhibitory effect of atorvastatin on oxidative stress markers. Again, their study did not explicitly validate the role of PPARγ. Actually, our study complemented the existing studies by more comprehensively revealing the role and underlying mechanisms of statins in the progression of BPH from human, rat, and cultured cell data. Finally, the TMA of 104 cases of BPH tissues was constructed, and the correlation among PPARγ, WNT-1, and β-catenin and also their correlation with corresponding clinical data were analyzed. Parallel to our cell and rat studies, it was shown that PPARγ was negatively correlated with β-catenin, but not with WNT-1. In addition, WNT-1 and β-catenin had a very strong positive correlation. Furthermore, we found that PPARγ was negatively correlated with prostate volume (PV) and free prostate-specific antigen (fPSA) but positively correlated with maximum urinary flow rate (Qmax), which is consistent with the inhibitory effect of PPARγ on prostate cell lines. Interestingly, WNT-1 and β-catenin exhibited a positive relationship with International Prostate Symptom Score (IPSS) and nocturia, respectively. Nocturia is reported by a large proportion of untreated patients with BPH and severely affects their quality of life (QoL) [4]. The prevalence of nocturia was positively correlated with age in both men and women. In addition, prostate volume (PV) and prostate-specific antigen (PSA) could be used as predictors of BPH patients who developed bladder outlet obstruction (BOO) [89]. Our findings revealed that PPARγ is negatively associated with the progression of BPH, whereas WNT-1 and β-catenin are involved in promoting the progression of BPH. However, further investigations will be required on the association of PPARγ/Wnt-1/β-catenin with clinical data of BPH patients. In conclusion, our study demonstrates that PPARγ is expressed in both stromal and epithelial compartments of the prostate and is downregulated in hyperplastic prostate tissues. Our novel data also show that SV could ameliorate the progression of BPH from multiple pathways, including inhibition of cell proliferation, promotion of cell apoptosis and cell cycle arrest at the G0/G1 phase, and inhibition of prostate fibrosis and the EMT process through crosstalk between PPARγ and WNT/β-catenin pathways. Our data suggest that SV may have an ameliorating effect on BPH progression and that the PPARγ-WNT/β-catenin system pathway could play important roles. Further exploration is required to fully elucidate the interaction between the PPARγ and WNT/β-catenin pathway, which may provide new therapeutic targets for the treatment of BPH. ## 4.1. Overview of Common Methods Cell lines acquisition and culture, CCK-8 assays analysis, flow cytometry analysis, quantitative real-time polymerase chain reaction (qRT-PCR), Western blot analysis, immunofluorescence staining, H&E staining, and Masson trichrome staining were performed as described in our previous studies [90,91,92]. The primer sequences involved are listed in Supplementary Table S2. ## 4.2. Animals and Tissues Forty-eight specific pathogen-free male Sprague–Dawley rats, aged 6 weeks, weighing 200–250 g, were divided into 4 groups using a random number table method, with 9 rats in each group: Blank control group, Corn oil (MCE, MedChemExpress, China) injection (subcutaneous (s.c.) + intraperitoneal (i.p.)) + dimethyl sulfoxide (DMSO) (MCE, China) administration ((i.p.) + gavage (i.g.)) + PEG300 (MCE, China) administration (i.g.) + normal saline (MCE, China) administration (i.g.); T group, T (Testosterone propionate, Sigma-Aldrich, St. Louis, MO) (2 mg/day)/corn oil injection (s.c.) + corn oil administration (i.p.) + DMSO administration (i.p. + i.g.) + PEG300 administration (i.g.) + normal saline administration (i.g.); T + SV group, T (2 mg/day)/corn oil injection (s.c.) + SV (MCE, China) (20 mg/kg/day)/PEG300/normal saline/DMSO administration (i.g.) + DMSO (i.p.) + corn oil administration (i.p.); T + SV + GW9662 group, T (2 mg/day)/corn oil injection (s.c.) + SV (MCE, China) (20 mg/kg/day)/PEG300/saline/DMSO administration (i.g.) + GW9662 (PPARγ-antagonist, sigma-aldrich, Cat. # M6191) (2 mg/kg/day)/corn oil/DMSO administration (i.p.). SV and GW9662 were dosed according to previous studies [87,93]. Animals were kept at room temperature: 18–22 °C and humidity: 40–$60\%$. On day 28, the rats were euthanized under isoflurane anesthesia (40 mg/kg), and the ventral prostate and seminal vesicles were collected and weighed. Tissues were snap-frozen in liquid nitrogen, followed by storage at −80 °C for subsequent analysis or fixed in $4\%$ paraformaldehyde (PFA) for histological observation. In addition, we collected blood from the rats and left it at 4 °C until the blood clotted to absorb the upper layer of serum, and then stored it at −80 °C for subsequent studies. We were blinded to group assignments when assessing the in vivo effects of SV and GW9662 on the rat prostate. Animal experiments were carried out in the Animal Center of Zhongnan Hospital of Wuhan University and approved by the Medical Ethics Committee for Laboratory Animals of Zhongnan Hospital of Wuhan University. Prostate tissues were obtained from 8 young brain-dead men who underwent organ donation in Zhongnan Hospital of Wuhan University as controls. The prostate samples of 104 BPH patients with clinical data who underwent transurethral resection of the prostate in the Department of Urology, Zhongnan Hospital of Wuhan University were collected. Postoperative pathological examination confirmed the diagnosis of BPH. Prostate tissues were divided into two parts, which were stored in liquid nitrogen for PCR and Western blot analysis and in $4\%$ PFA for immunofluorescence microscopy and TMA construction. All human specimens were collected and processed in accordance with the guidelines approved by the Ethics Committee of Zhongnan Hospital of Wuhan University and the principles of the Declaration of Helsinki. ## 4.3. The Construction and Immunohistochemical Analysis of TMA Descriptive statistics of the clinical parameters of 104 BPH patients are presented in Table 3. Tissue from each of the 104 patient cases was fixed, made into donor wax block sections, stained with H&E for pathological diagnosis and lesion tissue localization, and evaluated and confirmed by senior pathologists. A 1.5 mm diameter core was taken from each sample wax block. Finally, we obtained tissue cores from all BPH samples, and the resulting TMA was then serially cut into sections with a thickness of 4 μm. In brief, paraffin sections were dewaxed and placed in citrate buffer (pH 6.0) for antigen repair, followed by blocking of endogenous peroxidase activity in $0.3\%$ H2O2. Next, the above sections were incubated with the corresponding primary and secondary antibodies (listed in Supplementary Tables S3 and S4, respectively). Antibody localization was identified by addition of peroxidase and 3, 3′-diaminobenzidine tetrahydrochloride. An Olympus DP72 light microscope (Olympus, Japan) was used to image stained sections. Two pathologists blinded to sample type quantified the expression of PPARγ, WNT-1, and β-catenin in prostate tissues derived from the TMA. Image J was used to measure the percentage of positive area for the three proteins. ## 4.4.1. SV Treatment BPH-1 and WPMY-1 cells were seeded in six-well or 96-well plates, cultured for 24 h, and treated with SV (0, 1, and 5 μM, dissolved and diluted with DMSO) for 48 h. Subsequent assays were then performed. ## 4.4.2. GW9662 Treatment After 24 h of culture, BPH-1 and WPMY-1 cells were pretreated with GW9662 (0, 20, 40 and 60 μM, dissolved and diluted with DMSO) for 24 h, and then treated with SV (5 μM) for 48 h. ## 4.5. Enzyme-Linked Immunosorbent Assay (ELISA) Triglyceride and cholesterol concentrations in rat serum were measured using Rat Triglyceride, TG ELISA Kit (MEIMIAN, MM-0610R, China) and Rat Cholesterol, CH ELISA Kit (MEIMIAN, MM-0674R, China) according to the manufacturer’s protocol. 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--- title: Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Is a Promising Signature to Predict Prognosis and Therapies for Hepatocellular Carcinoma (HCC) authors: - Yuyan Chen - Senzhe Xia - Lu Zhang - Xueqian Qin - Zhengyi Zhu - Tao Ma - Shushu Lu - Jing Chen - Xiaolei Shi - Haozhen Ren journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003122 doi: 10.3390/jcm12051830 license: CC BY 4.0 --- # Mitochondria-Associated Endoplasmic Reticulum Membrane (MAM) Is a Promising Signature to Predict Prognosis and Therapies for Hepatocellular Carcinoma (HCC) ## Abstract Background: The roles of mitochondria and the endoplasmic reticulum (ER) in the progression of hepatocellular carcinoma (HCC) are well established. However, a special domain that regulates the close contact between the ER and mitochondria, known as the mitochondria-associated endoplasmic reticulum membrane (MAM), has not yet been investigated in detail in HCC. Methods: The TCGA-LIHC dataset was only used as a training set. In addition, the ICGC and several GEO datasets were used for validation. Consensus clustering was applied to test the prognostic value of the MAM-associated genes. Then, the MAM score was constructed using the lasso algorithm. In addition, uncertainty of clustering in single-cell RNA-seq data using a gene co-expression network (AUCell) was used for the detection of the MAM scores in various cell types. Then, CellChat analysis was applied for comparing the interaction strength between the different MAM score groups. Further, the tumor microenvironment score (TME score) was calculated to compare the prognostic values, the correlation with the other HCC subtypes, tumor immune infiltration landscape, genomic mutations, and copy number variations (CNV) of different subgroups. Finally, the response to immune therapy and sensitivity to chemotherapy were also determined. Results: First, it was observed that the MAM-associated genes could differentiate the survival rates of HCC. Then, the MAM score was constructed and validated using the TCGA and ICGC datasets, respectively. The AUCell analysis indicated that the MAM score was higher in the malignant cells. In addition, enrichment analysis demonstrated that malignant cells with a high MAM score were positively correlated with energy metabolism pathways. Furthermore, the CellChat analysis indicated that the interaction strength was reinforced between the high-MAM-score malignant cells and T cells. Finally, the TME score was constructed, which demonstrated that the HCC patients with high MAM scores/low TME scores tend to have a worse prognosis and high frequency of genomic mutations, while those with low MAM scores/high TME scores were more likely to have a better response to immune therapy. Conclusions: MAM score is a promising index for determining the need for chemotherapy, which reflects the energy metabolic pathways. A combination of the MAM score and TME score could be a better indicator to predict prognosis and response to immune therapy. ## 1. Introduction Hepatocellular carcinoma (HCC) is the most common (70–$90\%$) liver cancer and the fifth most common cancer globally [1]. Although the five-year survival rate of early radical surgery for HCC can reach $75\%$, no typical symptoms are generally observed in the early stages of HCC. Most of the patients are already in the advanced stage when they are diagnosed, sometimes accompanied by distant metastasis, resulting in poor survival rates [2]. In the past few years, there has been some progress in the clinical application of drugs, such as sorafenib and lenvatinib, for the treatment of liver cancer [3]. Although these drugs can prolong the prognosis of patients to some extent, multi-center studies have demonstrated that these drugs have little effect on the long-term survival of HCC patients because of side effects such as chemotherapy resistance [4]. Therefore, early diagnosis is crucial for the long-term survival of HCC patients. At present, the prediction of prognosis in HCC patients depends on the tumor size, the number of lymph nodes, and distant metastasis [5]. However, HCC patients showed different outcomes, even with the same clinical characteristics. Several studies have demonstrated that HCC is highly heterogeneous due to its complex regulatory mechanisms [6,7]. Therefore, it is beneficial to predict the long-term survival of patients by exploring the mechanisms underlying the occurrence and development of HCC. In recent years, with the extensive development of its clinical trials, tumor immunotherapy has demonstrated primary benefits, and immunotherapy for advanced HCC has become a popular area of research [8]. With the development of single-cell sequencing technology, several studies have demonstrated the unique functions of different cell types in HCC. Consequently, several immune therapies targeted at cell types, such as CAR-T and DC-CIK, have shown their effectiveness in various tumors, especially in some blood cancers [9]. However, the effects of these therapies on most solid tumors fail to live up to the expectations because of the T cell exhaustion in the tumor microenvironment (TME) [10,11]. Hence, a deeper understanding of TME shaped by the tumor can be beneficial for the immunotherapy of HCC patients. As in a typical inflammatory type of tumor, immune tolerance and escape mechanisms play important roles in the HCC progression [12]. In TME, cancer cells, cytokines, immune cells, and the extracellular matrix constitute a dynamic and complex system. Thus, as the oncogenic and anti-tumor effects exist and interact at the same time, we considered that investigating the regulatory mechanisms within the TME may help predict the prognosis and immune responses of HCC patients. The endoplasmic reticulum (ER) and mitochondria, the two typical dynamic organelles, play important roles in several cellular activities. The mitochondria-associated endoplasmic reticulum membrane (MAM) is a specialized domain that functions as membrane contact sites between the ER and mitochondria and was first discovered by J. Vance et al. in 1990 [13]. Further study with electron microscopes showed that the distance between the mitochondria outer membrane and endoplasmic reticulum remains at about 10–25 nm, but they do not fuse, maintaining the organelles’ unique structure, and provide a functional platform with various enrichment proteins. Notably, MAM mediates communication between the two organelles and is involved in the exchange of proteins and metabolites, including Ca2+ and reactive oxygen species (ROS) [14]. In addition, the distance between the ER and mitochondria is a key checkpoint regulating cellular functions. Several studies have observed that close contact between the ER and mitochondria led to mitochondrial Ca2+ overload and apoptosis. In other words, the destruction of ER–mitochondrial contact points could stimulate mitochondrial oxidative respiration and ATP production [15,16]. Furthermore, MAM could also play an important role in tumor progression. Wang et al. observed that FUNDC1-dependent MAM is involved in angiogenesis in cancers [17]. Li et al. observed that GRP75-facilitated MAM controls cisplatin resistance, thus shortening the prognosis in ovarian cancer patients [18]. However, the effects of MAM on HCC progression and the underlying mechanism still remain unclear. In this study, due to the strong heterogeneity of HCC, targeted therapy has not been very effective. In this study, to understand the potential mechanisms regulating the progression of HCC, we generated a MAM score to predict the prognosis and chemotherapy response of patients. Finally, we investigated the potential mechanisms underlying the impact of MAM structure on HCC progression by using single-cell data. Therefore, the current study provides a novel basis for the treatment of HCC. ## 2.1. Public Data Collection Acquisition The expression of the MAM-related genes in the HCC and normal groups was analyzed by downloading several GEO microarray datasets, including GSE14520, GSE25097, GSE36376, GSE39791, GSE45436, GSE54236, GSE76427, GSE77314, GSE102083, and GSE 112790 from the GEO database “https://www.ncbi.nlm.nih.gov/geo/ (accessed on 12 January 2023)”. In addition, the clinical data of GSE14520 were also analyzed. In particular, the MAM scores in the transcatheter arterial chemoembolization (TACE) response and no response groups were analyzed based on GSE104580. The differences in the MAM scores of nine HCC single-cell samples were obtained from GSE125449. The detailed quality control procedure of individual cells is described in the “Single-cell data analysis” section below. The transcriptional data and clinical data were downloaded from the International Cancer Genome Consortium (ICGC) LIRI-JP database “https://dcc.icgc.org/ (accessed on 12 January 2023)”. The transcriptional data, clinical data, copy number variation (CNV) data, and mutation data were downloaded from the TCGA-LIHC database using the R package “TCGAbiolinks”. Additionally, the data from the Cancer Cell Line Encyclopedia (CCLE) were downloaded from the CCLE website “https://sites.broadinstitute.org/ccle (accessed on 12 January 2023)” for testing the drug sensitivity of the low- and high-MAM-score groups. ## 2.2. Consensus Clustering Analysis The patients were divided into two clusters in the TCGA, ICGC, and GSE14520 datasets using the R package “ConsensusClusterPlus” for validating whether the MAM-related genes could influence the prognosis of HCC patients. ## 2.3. Comparison of the Different Molecular Classifications of HCC The detailed methods have been described by Shu et al. [ 19]. Briefly, the generated classifications in this study were compared with other classifications based on the TCGA-LIHC database in previous studies. ## 2.4. MAM-Score and TME-Score Calculations The MAM scores were calculated for five genes based on lasso Cox regression using the R package “glmnet”. A MAM score was calculated as follows: (−0.002405788) × ACAT1 + (0.005653644) × PACS2 + (0.001473221) × VDAC1 + (0.028582795) × MFN1 + (0.011694457) × ATAD3A. The HCC samples were divided into low and high groups based on the median MAM score in the TCGA HCC dataset and ICGC-LIRI-JP cohort. The CIBERSORT algorithm was initially used to assess the 22 immune cell type scores of each sample of the TCGA and ICGC datasets [20], and then a TME score was calculated as follows: (−5.860781) × activated NK cells + (−3.393689) × resting memory CD4+ T cells + (−3.283541) × CD8+ T cells. In addition, when a sample was identified as belonging to the “high-MAM-score/high-TME-score” or “low-MAM-score/low-TME-score” subgroups, it was recognized as a “mixed” group. ## 2.5. Prognostic Model Validation The Kaplan–Meier (KM) analysis, time-dependent receiver operating characteristic (ROC) curves, univariate and multivariate Cox regression analyses, and nomogram were analyzed using the R packages “survival”, “survminer”, and “survivalROC” for evaluating the HCC prognosis prediction [21]. ## 2.6. Single-Cell Data Analysis The cell control quality criteria were set as follows: cell counts > 200, percent of mitochondria < 10, and percent of erythrocytes < 3. A total of 3821 cells from nine samples were finally identified by R package “Seurat”. “ LogNormalize” function in the R package Seurat was used for standardizing the expression at the single-cell level. Further, the principal component analysis (PCA) and the subsequent t-distributed stochastic neighbor embedding (T-SNE) analysis were performed for the dimension reduction of the single-cell data. In addition, the cell types provided by the authors of this GEO series were used. As a result, the cells were divided into 7 cell types: cancer-associated fibroblasts (CAF), tumor-associated endothelial cells (TEC), tumor-associated macrophages (TAM), hepatic progenitor cells (HPC-like), malignant cells, T cells, and B cells. ## 2.7. Single-Cell Gene Set Enrichment Analysis The Uncertainty of Clustering in single-cell RNA-seq data using a gene co-expression network (AUCell) analysis was used to calculate the MAM scores of the single-cell gene sets [22]. For enrichment analysis, the marker genes of all the cell types were initially calculated, and then ToppGene “https://toppgene.cchmc.org/enrichment.jsp (accessed on 12 January 2023)” was used for the analysis of the enriched pathways of each cell type. In addition, the R package “scMetabolism” was used to predict the metabolism score for the cell types [23]. ## 2.8. Mapping Specific Regulon Networks by SCENIC The R package “SCENIC” was applied to analyze the activated regulons of each cell type following the standard procedure [22]. Then, “runGenie3” and “RcisTarget” analyses were performed for determining the potential transcription factors of each cell type. In addition, the regulon activity score was calculated by R package “AUCell” and represented by “T-SNE” plots. ## 2.9. CellChat Analysis R package “CellChat” was applied to determine the co-communications between the malignant cells and other cell types in the low- and high-MAM-score groups. In addition, the differences in the receptor ligands in the low- and high MAM-malignant cells were visualized using the “netVisual-bubble” function. ## 2.10. Regulon Analysis As previously described, the R package “RTN” was used for constructing the transcriptional regulatory regulons of 17 transcriptional factors (TFs), which regulated the malignant cells, CAF, and TEC, in the low- and high MAM-groups [24]. ## 2.11. Calculation of Microenvironment Cell Abundance and Immune Infiltration in the Low- and High-MAM-Score Groups First, CIBERSORT and ESTIMATE algorithms were used for calculating the MAM and TME scores related to specific microenvironment cells, and comparing the immune checkpoints, immune cell proportions, and several immune processes. In addition, the signature scores of the MAM–TME subgroups were calculated as previously described to evaluate the differences in the distribution of microenvironment-related signatures of different groups [25]. ## 2.12. Prediction of the Response to Immunotherapy in HCC The exclusion scores and the responses to TIDE therapy are available at “http://tide.dfci.harvard.edu/ (accessed on 12 January 2023)”. Then, the TIDE scores were used to calculate and determine whether each sample from the different groups is sensitive to PD1 and CTAL4 treatment in the submap platform, which is an algorithm for drawing inferences by comparing the similarities between the expression profiles “https://cloud.genepattern.org/gp (accessed on 12 January 2023)”. In addition, the Cancer Immunome Atlas (TCIA) database was used for obtaining the immunephenoscore (IPS) data from HCC patients. Subsequently, the IPS differences between the high-MAM/low-TME-scores, low-MAM/high-TME-scores, and the mixed subgroups were analyzed using the boxplots. ## 2.13. Prediction of the Response to Chemotherapy in HCC To determine the drug sensitivity of the cancer cell line, the PRISM dataset “https://depmap.org/portal/prism/ (accessed on 12 January 2023)” and Cancer Therapeutics Response Portal (CTRP, “https://portals.broadinstitute.org/ctrp (accessed on 12 January 2023)”) were used for calculating the area under the curve (AUC) and the correlations between the low- and high-MAM-score groups. In addition, the CMAP platform “clue.io/query (accessed on 12 January 2023)” was also used for evaluating the drug susceptibility differences between the low-MAM-score and high-MAM-score subgroups. ## 2.14. Statistical Analysis All the statistical data analyses were conducted using R software 4.1.3, and most of the plots were obtained using the R package “ggplot2” [26]. Some of the plots were drawn using the Hiplot “https://hiplot-academic.com (accessed on 12 January 2023)”. The data were evaluated using Wilcoxon tests when two groups were compared, and Kruskal–Wallis tests were used when three groups were compared. Statistical significance was described as follows: ns, not significant; * $p \leq 0.05$; ** p ≤ 0.01; *** p ≤ 0.001; and **** p ≤ 0.0001. ## 2.15. Work Flow In this study, we investigated the expression of the MAM-related genes in several public datasets. Further, the MAM score was generated and validated in the TCGA and ICGC datasets. Subsequently, the single-cell data were used and it was observed that the MAM score was higher in the malignant cells and was closely related to energy metabolic pathways. In addition, the study results indicated that patients with high MAM scores tend to show a better response to chemotherapy. Furthermore, the TME scoring system (TME score) was constructed, which further helps the MAM score to classify the tumor immune infiltration environment. Finally, the results indicated that the HCC patients with a high MAM score/low TME score tend to have a worse prognosis and high frequency of genomic mutations, while patients with a low MAM score/high TME score were more likely to respond better to immune therapy. The workflow is illustrated in Figure 1. ## 3.1. Identification of the Expression and Prognostic Value of MAM in HCC MAM functions as a dynamic organelle for the transmission of ATP, Ca2+, and ROS, and is illustrated in Figure 2A. The commonly identified MAM resident proteins are involved in a series of cytological functions. In this study, several HCC datasets were identified by analyzing the expression of these genes between the HCC and normal groups. However, some genes could not be detected due to the limitations of microarray. It was observed that the expression of several genes in HCC patients was different from that in the normal samples (Figure 2B). Moreover, for investigating the clinical indices of the MAM molecular subtypes in HCC, the samples were divided into two groups (C1 and C2) according to the optimal cluster number ($k = 2$) in the TCGA, ICGC, and GSE14520 datasets. Notably, it was observed that MAM subtypes in TCGA were closely related to other HCC subtypes, including LEE, Hoshida, Boyault, and Chiang (Figure 2C). In addition, the KM analysis was used for investigating the prognostic value of the C2 and C1 groups and it was observed that the MAM subtypes could reasonably have the potential to predict the survival rates of HCC patients in the TCGA, ICGC, and GSE14520 datasets (Figure 2D–F). Together, these results revealed the MAM-related genes could distinguish the HCC samples and predict the poor prognosis of HCC patients. ## 3.2. Construction and Verification of the MAM-Based Score in HCC The lasso algorithm was applied for the construction of the MAM score model in TCGA, which was used to predict the prognostic value of the 28 MAM-related genes in HCC samples. Finally, five genes, ACAT1, PACS2, VDAC1, MFN1, and ATAD3A, were identified. In this study, the TCGA dataset was used as a training set, and the ICGC dataset was used as a validation set. First, the distribution of the expression of five MAM-related genes, survival status, MAM scores, and KM curve between the training and verification sets were plotted (Figure 3A,B). In addition, the correlations between the expressions of five MAM-related genes and MAM scores were examined in this study, and the results indicated that while ACAT1 was negatively correlated with the other four genes, the other four genes were positively correlated with each other (Figure 3C). Then, the prognostic value of the MAM score was determined through the KM analysis, and the results indicated that the high-MAM-score subgroup of HCC patients had shorter overall survival (OS) than the low-MAM-score subgroup (TCGA: $$p \leq 0.0004$$; ICGC: $$p \leq 0.0004$$, Figure 3D,E). Further, a time-dependent ROC curve was used for evaluating the predictive ability of the MAM score. The AUC in the training set was 0.61 at one year, 0.64 at three years, 0.67 at four years, and 0.75 at five years, while the AUC in the validation set was 0.70 at one year, 0.70 at three years, 0.72 at four years, and 0.73 at five years (Figure 3F,G). Furthermore, the univariate and multivariate analysis revealed that high MAM score was an independent factor for short OS in the training set ($$p \leq 0.0019$$; HR = 1.8; $95\%$ CI: 1.2–2.6, Figure 3H–J) and the validation set ($$p \leq 0.002$$; HR = 2.9; $95\%$ CI: 1.5–5.7, Figure 3I–K). Lastly, a nomogram was generated to examine the MAM scores and other clinical characteristics, indicating higher clinical use of the nomogram relative to the MAM score and TNM stage in OS prediction (Figure 3L,M). Thus, these results suggested that the MAM score might serve as a candidate prognostic factor in HCC. ## 3.3. Identification of the MAM Score and Its Potential Enriched Pathways at the Single-Cell Level Firstly, the cells were classified into seven types, including CAF, TEC, TAM, HPC-like, malignant, T, and B cells, based on a previous study [27]. As shown in Figure 4A, these cells were visualized by T-SNE. To further evaluate the MAM score at the single-cell level, the AUCell was used to analyze the MAM scores in the seven cell types, and it was observed that the MAM scores in the non-immune cell types (CAF, TEC, HPC-like, and malignant cells), especially the malignant cells, were higher than those in the immune cell types (TAM, T, and B cells; Figure 4B,C). The enrichment analysis conducted to investigate the unique functions of each cell type revealed that TEC is involved in several pathways linked with VEGFR, CAF plays a critical role in the extracellular organization, TAM plays a key role in the innate immune system, T and B cells tend to influence several immune-related pathways, and malignant cells are closely correlated with several metabolic pathways, such as ATP synthesis and the electron transport chain in the mitochondria (Figure 4D). Notably, these processes are regulated by the mitochondria, which are the most important organelles for energy generation. Furthermore, the metabolism score for each cell was independently calculated, which also proved that malignant cells could play a crucial role in metabolic processes (Figure 4E–G). Finally, the enrichment analysis was conducted for comparison of the metabolic processes between the high- and low-MAM-score malignant cells. This indicated that the high-MAM-score malignant cells were positively correlated with the citrate (TCA) cycle, oxidative phosphorylation, mitochondrial ATP synthesis, NADH dehydrogenase activity, glycolysis/gluconeogenesis, etc. ( Figure 4H). Together, the above results implied that MAM may depend on several mitochondrial metabolic processes, thus driving the malignant cells in HCC. ## 3.4. Identification of the Underlying Mechanisms of MAM The “SCENIC” method employed to identify the underlying specific TFs of each cell type demonstrated that ELK3 (81 g) was higher in TEC, NR2F2 (11 g) was higher in CAF, STAT4 (14 g) was higher in T cells, and NFKB1 (58 g) was higher in TAM. CEBPA-extended (60 g) was higher in malignant cells, and BHLJE41-extended (12 g) was higher in B cells (Figure 5A). As previously mentioned, MAM scores in the non-immune cells, especially the malignant cells, were higher than those in the immune cells. Then, the activities of TFs were revealed by T-SNE, which demonstrated that the activities of TFs were higher in the high-MAM-score group than in the low-MAM-score group (Figure 5B–G). In addition, “RTN” was used to calculate the regulon scores of these TFs and examine whether these scores were different between the high- and low-MAM-score groups in the TCGA dataset. The results showed that most of the regulon scores were higher in the high-MAM-score group than in the low-MAM-score group (Figure 5H). Moreover, the cell-to-cell communication between the low- and high-MAM-score groups was tested, and the results indicated the enhanced strength of the high-MAM-score malignant cells and T cells (Figure 5I). In addition, the differences in the receptor ligands between low- or high-MAM-score malignant cells and other cell types implied the upregulation of multiple signaling pathways in the non-immune cell types, such as SPP1-CD44, and the downregulation in some immune cell types, such as MIF-(CD74 + CXCR4, Figure 5J,K). From the above results, we found that high-MAM-score malignant cells could influence the non-immune cell types and immune cell types, especially T cells, which revealed the role of MAM in influencing the tumor environment. ## 3.5. Differences in the Tumor Microenvironment Infiltration between Different MAM—Subgroups To further determine the influence of TME on the HCC prognosis, CIBERSORT was used to estimate the fractions of each cell type of TME, which could prolong the prognosis of HCC (Appendix A). Three cell types (activated NK cells, resting memory CD4+ T cells, and CD8+ T cells) were selected, and it was speculated that these TME-related cell types could protect the normal cells from the invasion of tumor cells. We hypothesized that T cells and NK cells could be beneficial to the HCC prognosis. Notably, the CellChat analysis in this study indicated that malignant cells with high-MAM-score could transmit an increasing signal to T cells. Hence, the combined index considering both the MAM score and TME score was evaluated for predicting the prognosis of HCC patients. Further, *Cox analysis* was conducted to calculate the TME score of each sample, and the samples were divided into three subgroups, including the high MAM/low TME group, mixed group, and low MAM/ high TME group. KM analysis was conducted to evaluate the prognostic value between the three groups, and the results indicated that the high-MAM/low-TME-score group had shorter OS than other groups (Figure 6A,B; TCGA: $p \leq 0.0001$; ICGC: $$p \leq 0.034$$). The correlation between the combined marker and other classified markers was further investigated, indicating that the combined marker was closely related to other HCC subtypes, including CTTNB1, LEE, Hoshida, Boyault, and Chiang (Figure 6C). In addition, immune scores, stromal scores, scores of the immune checkpoints, and immune cell types were determined to elucidate the tumor immune infiltration landscape in the three groups. This indicated that though several immune checkpoints had no differences between the three groups, the immune-related points were higher in the high MAM/low TME group (Figure 6D). Mariathasan et al. established several tumor immune infiltration signatures [28]. According to these signatures, it was observed that the effector CD8+ T cell score was higher in the low MAM/high TME group and almost all the scores were higher in the high MAM/low TME group, except antigen processing machinery and EMT1, which is in agreement with the previous results (Figure 6E). Thus, combining the TME scores and MAM scores could better distinguish the tumor immune infiltration environment and improve the prognosis of HCC patients. ## 3.6. Mutation Landscape and Response to the Immune Checkpoint Block (ICB) Therapy In this study, the landscape of genomic variations between the three heterogeneous clusters was represented, indicating that TP53 mutation was higher in the high MAM/low TME group (Figure 7A,B). TP53 is the most frequently mutated gene in HCC. Figure 7A shows several CNV, indicating that though there are no obvious differences in the amplification arm between the three groups, the mutation frequency of the depletion in the arm was much higher in the high MAM/low TME group, while much lower in the low MAM/high TME group. The TIDE platform demonstrated that the observed exclusion score was higher in the high MAM/low TME group, which is known to reflect the sensitivity to ICB (Figure 7C). Furthermore, two methods for predicting the response to ICB were applied. First, the IPS of CTLA and PD1 in the three groups was determined, which indicated that the sensitivity was higher in the low MAM/high TME group (Figure 7D). Then, the TIDE and submap platform were used to demonstrate the better response of the low MAM/high TME group to the ICB of PD1 (Figure 7E,F). Together, these results indicated that a combined index of the MAM and TME scores shows promising results for ICB, demonstrating that HCC patients in the low MAM/high TME group could better respond to ICB. ## 3.7. Response of the High- and Low-MAM-Score Groups to Chemotherapy To date, TACE is widely used in clinical practice for HCC [29]. Hence, GSE104580 based on 66 samples from responders to TACE and 81 samples from non-responders to TACE was applied, and it was observed that the low-MAM-score group could better respond to TACE ($$p \leq 0.004$$, Figure 8A). The results implied that the MAM score could be a promising indicator to assess the suitability of a patient for chemotherapy. In addition, the PRISM dataset was used to identify the latent therapeutic drugs considering the CCLE data as a reference. The results indicated a positive correlation between lovastatin, fluvastatin, and simvastatin with low MAM (Figure 8B,C). It is well known that HMG-COA is the common target of the three compounds, and is involved in several metabolic pathways, such as cholesterol synthesis and oxidative stress [30]. When the expression of HMG-COA was analyzed in this study, HMG-COA expression levels were found to be higher in the high-MAM-score group (Figure 8E). Furthermore, the CMAP platform demonstrated that fasudil exerted more inhibitory effects on the high-MAM-score group when compared with the low-MAM-score group (Figure 8D). Fasudil is a potent Ca2+ channel antagonist and vasodilator [31]. Further, the expression of ATP2A2, which is a core gene to reflect the Ca pump and ER Ca2+ transportation, was investigated [32], and the results indicated that ATP2A2 was higher in the high-MAM-score group (Figure 8F). According to these results, we speculated HCC patients with a low MAM score may benefit from chemotherapy. ## 4. Discussion MAM-related genes play crucial roles in the indirect system, which regulates the transmission of second messengers, such as Ca2+ [33]. The study results elucidated that the index based on the classification of these genes could predict the prognosis in the three datasets. In addition, large-scale transcriptome and microarray data proved the differences in the expression and stability of these genes. Generally, the MAM-related genes play crucial roles in the progression of HCC. Hence, a MAM-based score was constructed, which exhibited 5-year AUC values of 0.75 and 0.73 in the TCGA and ICGC cohorts, respectively, indicating the prognostic utility of this model. Five core genes (ACAT1, PACS2, VDAC1, MFN1, and ATAD3A) playing critical roles in cancer were identified in this study. ACAT1 is recognized as a tumor suppressor and is involved in several mitochondrial-induced metabolic pathways. In addition, it has also been noted in the literature that ACAT1 is highly expressed in lung cancer and prostate cancer. We speculated that this may be caused by the strong heterogeneity of tumors, which also needs to be verified in our follow-up experiments [34,35]. Deng et al. observed that PACS2 could regulate MAM to impair erectile function in rats with prostate cancer [36]. VDAC1 is one of the major Ca2+ transport channels in the mitochondria. MAM regulates the transfer of Ca2+ from the ER to mitochondria via the VDAC1-GRP75-IP3R3 macromolecular complex [37]. In addition, Azeez et al. observed that VDAC1 could also mediate progesterone-triggered-Ca2+ in breast cancer [38]. Li et al. believed that the MFN1/MFN2 pathway could promote ferroptosis through MAM in pancreatic cancer [39]. At the same time, Lang et al. reviewed several cancer-related studies on ATAD3A and concluded that ATAD3A could control the progression of cancers by regulating the mitochondrial dynamics and ER [40]. The findings indicated that these genes could regulate the MAM to control the mitochondrial functions, thus promoting cancer progression. Therefore, it was speculated that the MAM score could indicate tumor progression and contribute to the prediction of prognosis in HCC patients. Due to the high heterogeneity in HCC, a single clinical index could not reflect the complexity of TME. As a result, drug tolerance and immune exclusion were observed post chemotherapy or immune therapy. The development of a single-cell technology led to the identification of the landscape of TME. The AUCell analysis indicated that the MAM score was higher in the non-immune cell types, especially malignant cells, than the immune cells. Additionally, malignant cells exhibited more metabolism characteristics. In particular, the energy metabolism pathways were dependent on the mitochondrial functions, which further proved our approach. Additionally, drug sensitivity analysis revealed the potential drugs, including statins and fasudil, for HCC patients with low MAM scores. Notably, these drugs are individually used to reduce cholesterol and Ca2+ levels. Aleix and co-workers found that CAV1 knockout results in the low stability of ER-mitochondrial contact sites, which led to the accumulation of free cholesterol in MAMs [41]. This implied that the control of metabolism by the underlying compounds could help in a better prognosis of HCC. Except for Ca2+ signaling, other energy signals and kinases were also observed to be active in malignant cells. Notably, the tumor cells are more likely to go through the state of cellular senescence for defense against cancer. During this period, ROS from MAM impacts the energy balance of mitochondria, thus activating the AMPK signaling pathway, Ca2+ overload, and mitochondrial dysfunction [42]. In addition, the NAD/NADH ratio is also an energy indicator to assess the stability of MAM tethering [18]. Thus, controlling the distance between mitochondria and ER is vital for the energy metabolism of cancer cells. In particular, the classification based on the MAM-related genes and other HCC subtypes was compared, which indicated that the MAM subtype was closely related to other subtypes. Hence, it was speculated that similar to the MAM subtype, these subtypes may also be involved in several pathways of energy metabolism. However, over the past few years, research focused on the second messengers, while ignoring the subcellular organelles, which functioned to transmit these signals. To date, most of the research has concentrated on the organelle functions, such as lysosomes, ribosomes, etc. [ 43,44]. Thus, the results from this study verified that MAM may influence energy metabolism, thereby promoting HCC progression. The results from the CellChat analysis demonstrated that the malignant cells delivered enhanced signals to T cells when compared to other cell types. In addition, the co-interaction strength was higher in the high-MAM-score malignant cells than in the low-MAM-score malignant cells. In addition, the AUCell analysis indicated that the MAM score was higher in the malignant cells and relatively lower in the T cells. Hence, it was concluded that the antagonism of T cells and high-MAM-score malignant cells may decide the destiny of HCC patients. Then, CIBERSORT was used to identify three immune cell types (activated NK cells, resting memory CD4+ T cells, and CD8+ T cells), which could prolong the prognosis of HCC patients. It is well known that NK and CD8+ T cells could specifically kill the tumor cells through several common pathways, including perforin, granzyme, Fas/FasL, TNF-α, and IFN-γ. In addition, CD4+ T cells could assist CD8+ T cells to simultaneously participate in cellular immune response as well as clear cell tumors [45,46]. Based on the evidence, it was speculated that an immune-related prognostic signature could be better to distinguish the TME and predict the prognosis of HCC patients. As expected, HCC patients with a high MAM score/low TME score tend to have a worse prognosis and higher tumor immune infiltration signatures. To date, the major limitation of CART therapy in solid tumors is CD8+ T cell exhaustion. The CD8+ T cells that lose their functional capabilities express a high level of PD-1, thus shaping the TME and promoting cancer progression [47]. Hence, further investigation on the correlation between CD8+ T cell exhaustion and MAM score could help us better understand the regulatory mechanisms of TME. Briefly, a combination of the MAM score and TME score could be a promising marker for predicting the survival rates of HCC. In addition to the above results, genome somatic mutations and CNV also revealed the heterogeneity of HCC [48]. *The* gene mutations can directly affect the TME by recruitment or exclusion of immune cell penetration. Some studies have demonstrated that cancer cells in HCC patients with TP53 mutations tend to escape from immune therapy, and HCC patients with CCTNB1 mutations are more likely to show immune tolerance and exclusion [49,50]. Jérôme et al. observed that TP53 mutation status was also related to TME [51]. It has also been demonstrated that the immunogenicity of TP53 mutations is driven by complex dynamics, including the affinity of T cell antigen receptor (TCR), transport of T cells to TME, etc. [ 52]. Notably, the study results indicated high TP53 and CCNTB1 mutation frequency, especially the TP53 mutation, in the high-MAM-score/low-TME-score group. In addition, the alterations in CNV had a larger contribution to immune therapy than somatic mutations. In this study, the results revealed that patients in the high-MAM-score/low-TME-score group tend to acquire a high frequency of depletion in the arm, thereby indicating that the patients in the high-MAM-score/low-TME-score group may be insensitive to immune therapy. As expected, the patients in the low-MAM-score/high-TME-score group have a better response to PD-1 immune therapy. In recent years, immune checkpoint inhibitors have brought fundamental changes to the treatment of HCC. PD-1 is an immune checkpoint molecule, and the latest clinical trials on HCC have shown unprecedented success in immunotherapy targeting the PD-1/PD-L1 axis [53,54,55]. However, it still faces great challenges, and its low remission rate is yet to be solved. For most HCC patients, the PD-1/PD-L1 pathway is not the only limiting factor of antitumor immunity, and blocking only the PD-1/PD-L1 axis is not enough to stimulate an effective antitumor immune response. After first-line immunotherapy combination treatment, second-line targeted treatment is a viable option. Notably, Yu and co-workers discovered that disturbed mitochondrial dynamics reinforce T cell exhaustion and PD1 to reconstruct TME [56]. Hence, it can be speculated that the maintenance of the MAM could help stabilize the mitochondria and strengthen the anti-tumor immune system. *In* general, this study showed that a combination of the MAM score and TME score could be a promising marker for predicting the response of HCC patients to ICB therapy. In summary, this study is the first investigation of MAM in HCC considering publicly available data. As an organelle that transmits energy, MAM plays a crucial role in the HCC progression. The results from this study also showed that the MAM score could be used to identify the suitability of HCC patients for chemotherapy. It is well known that different molecular characteristics usually reflect different pathological features. Due to the high heterogeneity of HCC, a single index cannot reflect the differences in the tumor immune infiltration. Therefore, the combination of the TME score and MAM score considered in this study could be a better solution to distinguish TME and predict the prognosis of HCC. However, there are some limitations to this approach that should be considered. First, a few GEO datasets including the detailed prognosis information do not detect the expression of some MAM-associated genes, which restricts us to expand our patient cohorts. Second, all the patients enrolled in this research were retrospective, and a prospective study should be considered for validation of the results. Nevertheless, this research showed that the MAM score reflected the metabolic characteristics, and combining the MAM score with the TME score could better predict the prognosis of HCC patients. ## 5. 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--- title: Genetic Determinants of Leisure-Time Physical Activity in the Hungarian General and Roma Populations authors: - Péter Pikó - Éva Bácsné Bába - Zsigmond Kósa - János Sándor - Nóra Kovács - Zoltán Bács - Róza Ádány journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003125 doi: 10.3390/ijms24054566 license: CC BY 4.0 --- # Genetic Determinants of Leisure-Time Physical Activity in the Hungarian General and Roma Populations ## Abstract Leisure-time physical activity (LTPA) is one of the modifiable lifestyle factors that play an important role in the prevention of non-communicable (especially cardiovascular) diseases. *Certain* genetic factors predisposing to LTPA have been previously described, but their effects and applicability on different ethnicities are unknown. Our present study aims to investigate the genetic background of LTPA using seven single nucleotide polymorphisms (SNPs) in a sample of 330 individuals from the *Hungarian* general (HG) and 314 from the Roma population. The LTPA in general and three intensity categories of it (vigorous, moderate, and walking) were examined as binary outcome variables. Allele frequencies were determined, individual correlations of SNPs to LTPA, in general, were determined, and an optimized polygenetic score (oPGS) was created. Our results showed that the allele frequencies of four SNPs differed significantly between the two study groups. The C allele of rs10887741 showed a significant positive correlation with LTPA in general (OR = 1.48, $95\%$ CI: 1.12–1.97; $$p \leq 0.006$$). Three SNPs (rs10887741, rs6022999, and rs7023003) were identified by the process of PGS optimization, whose cumulative effect shows a strong significant positive association with LTPA in general (OR = 1.40, $95\%$ CI: 1.16–1.70; $p \leq 0.001$). The oPGS showed a significantly lower value in the Roma population compared with the HG population (oPGSRoma: 2.19 ± SD: 0.99 vs. oPGSHG: 2.70 ± SD: 1.06; $p \leq 0.001$). In conclusion, the coexistence of genetic factors that encourage leisure-time physical activity shows a more unfavorable picture among Roma, which may indirectly contribute to their poor health status. ## 1. Introduction Urbanization and the spread of technological innovations [1], as well as the restrictions during the COVID-19 pandemic [2], have contributed greatly to the sudden decline in physical activity in recent years. Today, physical inactivity is a severe public health problem, as the prevalence of a sedentary lifestyle among adults is increasing worldwide [3]. Physical inactivity is an important preventable risk factor for non-communicable diseases [3,4]. Leisure-time physical activity (LTPA) is a well-known modifiable lifestyle factor associated with a wide range of cardiometabolic outcomes, including obesity, hypertension, type 2 diabetes, metabolic syndrome, and cardiovascular diseases in general [5]. Various psychological, biological, social, and environmental factors affecting leisure-time physical activity have been investigated and identified [6,7,8]. Demographic and health variables associated with levels of physical activity include sex, age, education, and body mass index (BMI) [9]. Recognizing the demographic, environmental, and social determinants of physical activity among adults is important for designing effective intervention strategies to promote it [10]. Several studies have shown that some determinants, such as age, higher educational attainment, and higher income, are associated with increased participation in LTPA for some groups [11,12]. Despite this knowledge and continued efforts to encourage physical activity, in most developed countries prevalence remains low and participation rates for women are consistently lower than for men [13]. Leisure-time physical activity is influenced by a combination of several factors, of which genetic heritability is estimated by studies to be between $30\%$ and $52\%$ [7]. A study published in 2009 involving 1644 unrelated Dutch and 978 Americans of European ancestry found that the heritability of leisure-time physical activity behavior is explained by a large number of genetic variants with small individual effect sizes [14]. A 2014 study by Kim et al. [ 15] in a sample of 8842 Koreans found similar results, with no significant association of single nucleotide polymorphisms (SNPs) with LTPA at the individual level, but 59 SNPs (in 76 genes) were identified using multiple SNP bootstrap analysis. LTPA varies between different ethnic groups [16,17], which can be partly explained by the environmental and lifestyle characteristics mentioned above, but differences in the genetic background cannot be excluded [18]. The Roma comprise the largest minority (10–12 million) in Europe, originating from the Punjab region of northern India as a nomadic people, and arriving in Europe between the eighth and tenth centuries A.D. [19,20]. The health status of *Roma is* generally much worse than that of the general population, regardless of the country where they live [21,22,23]. Studies on their health are almost exclusively descriptive on the prevalence of certain diseases [24], particularly infectious [25,26] and certain genetics-related diseases/conditions [27,28,29], and health determinants [20,30,31,32,33,34] and cardiovascular risk factors [35,36,37,38,39,40], while comprehensive exploratory studies are lacking. Although the association between the very unfavorable socioeconomic circumstances and unfavorable health status [31,41,42] of *Roma is* evident, it seems that the differences observed in comparison with the general populations cannot be explained solely by their poorer socioeconomic characteristics [30,43]. Recent studies on the genetic background of increased risk of various non-communicable diseases among them [44,45,46,47,48] further support the hypothesis that their health status is determined by the complex interactions of health-related genetic and non-genetic factors. The physical activity of Roma has not been well characterized; data on physical activity from the 2011 cross-sectional, population-based HepaMeta survey in Slovakia showed that LTPA was significantly lower among Roma women than among non-Roma [49]. Regarding the health risk behavior of Roma adolescents in segregated settlements in Slovakia compared to non-Roma, the differences were not statistically significant, except for the significantly higher rate of physical inactivity among Roma women [50]. The results of a complex health survey carried out by our research team in 2018 [51] are similar to those reported in Slovakia, in that while there is no significant difference in LTPA between Roma and non-Roma men, Roma women were found to have significantly lower levels than non-Roma. An article published in 2019 [52], comparing the physical activity levels of two Roma subgroups (Gabor and Băieși) and non-Roma groups in Romania, found that both Roma subgroups had significantly lower levels of daily physical activity (with gender differences). In addition, both Roma subgroups were less active than non-Roma in sports and gardening. Previous studies have shown that there is a marked difference in the genetic background of the Roma and majority population in cardiometabolic health-related factors such as high-density lipoprotein cholesterol (HDL-C) levels [44,46], type 2 diabetes [53,54], obesity [55,56,57,58], venous thrombosis [45,59,60], hypertension [61], smoking [62], and alcohol consumption [63,64]. Given that physical activity is to a large extent genetically determined and that there are differences in leisure-time physical activity between the *Hungarian* general and the Roma population, the question arises whether these differences are not due, at least partly, to different genetic backgrounds resulting from their different origins. Our study aims to investigate whether LTPA is also genetically determined in the *Hungarian* general and Roma populations and how this contributes to the lower LTPA among Roma using previously identified polymorphisms that promote LTPA. ## 2.1. Characteristics of the Study Populations by Sex No significant differences were found in mean age, abdominal circumference, and BMI between the two study populations by sex. In the Roma population, the proportion with lower levels of education were significantly higher, and the proportion of people traveling by vehicle was significantly lower (HGmen = $81.4\%$ vs. Romamen = $26.6\%$, $p \leq 0.001$; HGwomen = $68.1\%$ vs. Romawomen = $24.7\%$, $p \leq 0.001$) in both sexes. See Table 1 for more details. *In* general, the proportion of people who did LTPA was not significantly different between the two study populations for either sex. For men in the *Hungarian* general population, the proportion of participants with LTPA of vigorous (HG: $39.3\%$ vs. Roma: $12.7\%$, $p \leq 0.001$) and moderate (HG: $32.4\%$ vs. Roma: $10.2\%$, $$p \leq 0.016$$) intensity was significantly higher than among Roma, while the proportions of people walking in leisure time did not differ significantly between the two study populations (HG: $53.8\%$ vs. Roma: $54.4\%$, $$p \leq 0.927$$). For women, similarly to men, a significantly higher proportion of the *Hungarian* general population did vigorous (HG: $32.4\%$ vs. Roma: $10.2\%$, $p \leq 0.001$) or moderate (HG: $42.7\%$ vs. Roma: $25.1\%$, $p \leq 0.001$) intensity of LTPA and there was no significant difference in walking (HG: $62.7\%$ vs. Roma: $57.9\%$, $$p \leq 0.316$$). See Table 2 for more details. For men, a significant difference in metabolic equivalent of task minutes per week (MET-min/week) values was only measured in the LTPA category of vigorous-intensity between the two study populations (HG: 792.0 vs. Roma: 323.1, $p \leq 0.001$). Among women in the *Hungarian* general population, the average MET-min/week values for LTPA in general (HG: 1357.6 vs. Roma: 1052.5, $$p \leq 0.028$$) as well as in vigorous (HG: 647.2 vs. 311.3, $p \leq 0.001$), moderate (HG: 559.9 vs. 407.3, $$p \leq 0.003$$), and walking (HG: 463.2 vs. 247.73, $$p \leq 0.011$$) subdomains were significantly higher than among Roma. See Table 3 for more details. ## 2.2. Results of Linkage Disequilibrium (LD), Hardy-Weinberg Equilibrium (HWE), and Power Analyses and Comparison of Genotype Distribution between Sample Populations In LD analysis of ten SNPs, there was no linkage between SNPs. For three SNPs (rs12405556, rs429358, and rs6092090), significant deviations from HWE were measured and these SNPs were excluded from further analysis. For four (rs10252228, rs12612420, rs459465, and rs10887741) of the seven SNPs included in the study, a significant allele frequency difference was found between the *Hungarian* general and Roma populations and the statistical power varied between 0.147 and 0.985. See Supplementary Table S1 for more details. ## 2.3. The Result of the Association of SNPs with LTPA of Different Intensities Only the C allele of rs10887741 showed a significant positive association with LTPA in general (odds ratio (OR) = 1.48, $95\%$ CI: 1.12–1.97, $$p \leq 0.006$$), but none of the seven SNPs included in the study showed a significant association with any intensity category. For more details see Table 4. ## 2.4. Calculation and Comparison of Optimized Polygenic Score (PGS) for LTPA in the Hungarian General and Roma Populations The PGS optimization process tests the cumulative effect of SNPs by starting with the SNP showing the strongest association with LTPA (rs10887741: OR = 1.48, $$p \leq 0.006$$) and in decreasing order to the weakest one (rs459465: OR = 1.01, $$p \leq 0.967$$). During the process, rs6022999 and rs7023003 increased the strength of association of optimized polygenic score (oPGS) with LTPA in general. The remaining four SNPs (rs12612420, rs10252228, rs8097348, and rs459465) did not increase the strength of association and were therefore excluded from further analysis. See more details in Supplementary Table S2. Based on univariate analysis, oPGS showed a significant positive correlation with the LTPA in general (OR = 1.40, $95\%$ CI: 1.17–1.68; $p \leq 0.001$) and in intensity categories of vigorous (OR = 1.32, $95\%$ CI: 1.09–1.59; $$p \leq 0.004$$) and moderate (OR = 1.23, $95\%$ CI: 1.04–1.46; $$p \leq 0.013$$). After adjusting for confounders (ethnicity, age, waist circumference, BMI, education, and driving), the association remained significant only for the LTPA in general (OR = 1.40, $95\%$ CI: 1.16–1.70, $p \leq 0.001$). For more details see Table 5. In the groups defined based on oPGS values, we examined how the METS-min/week values changed for LTPA in general and its intensity categories and conducted a trend analysis. With the increase in oPRS, there was a significant upward trend in LTPA expressed in MET-min/week in general (p for trend = 0.002) as well as in the vigorous intensity category (p for trend = 0.015). The moderate (p for trend = 0.028) and walking (p for trend = 0.019) intensity categories showed no significant correlation with the oPGS categories after the test correction. For more details see Table 6. We also examined how the oPGS values are related to the weekly frequency of LTPA, i.e., the average number of days with at least 10 min that a person engages in leisure-time physical activity in general and its intensity categories. In this case, as in the MET-min/week results, there is a significant trend between the increase in oPGS values and the number of days per week of leisure-time physical activity in general (p for trend = 0.001), as well as for the vigorous (p for trend = 0.003), moderate (p for trend = 0.014), and walking (p for trend = 0.009) intensity categories. For more details see Supplementary Table S3. The distribution of oPGS differed significantly between the two study populations (oPGSRoma: 2.19 ± SD:0.99 vs. oPGSHG: 2.70 ± SD:1.06; $p \leq 0.001$). A strong rightward shift (to the higher values) is observed for the HG population compared with the Roma. See Figure 1 for more details. ## 3. Discussion LTPA is low in both the *Hungarian* general and Roma populations [51], which may be due to the influence of genetic background [7,65] in addition to known environmental and lifestyle factors [66]. The aim of the present study is to test this hypothesized genetic effect and, if it exists, to compare its magnitude between the *Hungarian* general and Roma populations. Based on a systematic literature search, ten SNPs were selected to investigate the genetic background of LTPA. Of the ten SNPs selected, three were excluded based on HWE, while four of the remaining seven had significant allele frequency differences between the two populations. When examining the individual effects of SNPs, only the C allele of rs10887741 showed a significant association with LTPA. PGS optimization identified three SNPs for which the combined effect showed a strong positive significant association with LTPA in general, and oPGS categories are significantly correlated with an increasing trend in MET-min/week values as well as with the frequency of LTPA in general and vigorous-intensity categories. The distribution of the populations by oPGS shows a significant shift to the right in the *Hungarian* general population compared with the Roma population. This finding suggests that the *Hungarian* general population has a higher genetic predisposition to doing leisure-time physical activity compared to the Roma. The rs10887741 polymorphism in the 3′-phosphoadenosine 5′-phosphosulfate synthase 2 (PAPSS2) gene showed the strongest individual association with LTPA in general. The enzyme encoded by the PAPSS2 gene is involved in the sulfation of many molecules in addition to glycosaminoglycans. At present, the mechanisms by which the PAPSS2 gene affects participation in leisure-time physical activity are not known, but mutations in it cause spondyloepimetaphyseal dysplasia, a disease characterized by short stature and limbs in both mice and humans [67]. A study on siblings found a correlation between the 10q23 region harboring the PAPSS2 gene and maximum physical performance [68]. This further supports the hypothesis that physical fitness may be an important determinant of leisure-time physical activity behavior [69]. The rs6022999 SNP is located in the CYP24A1 (Cytochrome P450 family 24 subfamily A member 1) gene, whose protein product is responsible for the conversion of vitamin D into its physiologically inactive form. Vitamin D is essential for proper muscle function [70,71], and polymorphisms of the vitamin D receptor in humans are associated with altered muscle strength regardless of sex [72]; these changes are likely to affect levels of physical activity. The rs7023003 is located in an intergenic region between the RN7SK and SLC44A1 genes. This SNP showed the strongest association with LTPA in a Korean study but still did not reach genome-wide association study significance [15]. Its significant association with LTPA was not confirmed in the Japanese population [73]. Currently, no research has investigated its role in LTPA through direct or indirect processes. The importance of understanding the genetic reasons behind differences in individual (leisure-time) physical activity is supported by recently published articles. Doherty and colleagues investigated the genetic background of physical activity and sleep duration (both were based on measured data) in 91,105 individuals registered in the UK Biobank [74]. They successfully identified 14 significant loci (seven novel–five for LTPA and two for sleeping) accounting for $0.06\%$ of physical activity and $0.39\%$ of sleep duration. They found that the heritability was higher in women than in men for general activity ($23\%$ vs. $20\%$, $$p \leq 1.5$$ × 10−4) and sedentary behavior ($18\%$ vs. $15\%$, $$p \leq 9.7$$ × 10−4). Klimentidis et al. [ 75] also investigated UK Biobank samples and identified ten loci with a significant ($p \leq 5$ × 10−9) effect on all physical activity measures. Of these, the variant rs429358 in the APOE gene (which was excluded from our study due to its deviation from HWE) was most strongly associated with moderate to vigorous physical activity. A GWAS study by Wang et al. [ 76] successfully identified a combination of 99 genetic variants associated with self-reported moderate to vigorous leisure-time physical activity, leisure-time screen time and/or sedentary behavior at work. Results summarized in a review article by De Geus in 2023 [77] support the general opinion that genetic factors strongly contribute to physical activity either self-reported or measured by accelerometer. The heritability of physical activity was found to be approximately $43\%$ across the lifespan. It has also been shown that a polygenic score based on genetic variants influencing PA (which we also use) could help to improve the success of targeted interventions. This study has its strengths and limitations. First, the correct identification of ethnicity is a common challenge in studies like ours [78]. Roma ethnicity was determined solely through self-identification, and consequently, there may be Roma individuals in the *Hungarian* general population, so the effect of ethnic differences in the study may be underestimated. Another limitation is that individuals who are above 65 years of age were not included in the study. Owing to a lack of information on gene-gene and gene-environment interactions, epigenetic factors, and structural variants, we did not consider them in our analysis. In the current study, ten SNPs related to LTPA were included for the calculation of oPGS. Theoretically, incorporating a larger number of SNPs may further improve the predictive ability of the PGS model. Nonetheless, adding many SNPs into the PGS model does not necessarily lead to a better predictive ability, as could be seen in the optimization process. Despite the limitations of the study, it should be emphasized that this is the first study to examine the possible genetic causes of the unfavorable level of leisure-time physical activity in the Roma population in comparison with that in the *Hungarian* general population. In conclusion, the present study demonstrates that the differences in the prevalence of different intensity categories of LTPA between the *Hungarian* general and Roma populations can be partly explained by genetic causes. ## 4.1. Sample Populations and Questionnaire-Based Interviews Data used in our present study were obtained in a cross-sectional three-pillar (i.e., questionnaire-based, physical examination, and laboratory examination) complex (i.e., health behavior and examination) survey carried out in 2018. Sampling and data collection are described in detail elsewhere [79]. Briefly, the *Hungarian* general (HG) and Roma sample populations were recruited from two counties (Hajdú-Bihar and Szabolcs-Szatmár-Bereg) in Northeast Hungary, the area where the representation of *Roma is* the highest and where most segregated Roma colonies are located. First, twenty-five colonies, and then from each colony 20 households, were randomly selected and one person (aged 20–64) from each household was invited to participate in the survey. Participants’ ethnicity was determined by self-declaration. The *Hungarian* general population included randomly selected individuals aged 20 to 64 years, living in private households in the same counties, and registered with general practitioners. From each of the 20 randomly selected GP practices, 25 randomly selected individuals were invited to participate in the study. The planned sample size of the survey was 500 persons per population, but the final study sample, for the present study, was reduced to 797 (410 HG and 387 Roma) after excluding individuals with incomplete records. The main part of the questionnaire used in the complex health survey was the European Health Interview Survey wave 2 (EHIS 2) questionnaire [80], which consists of four modules: (a) health status, (b) health care utilization, (c) determinants of health, and (d) socioeconomic variables. The EHIS 2 questionnaire has been extended with some additional sets of questions, including the long version of the International Physical Activity Questionnaire (IPAQ) to measure physical activity by domains and dimensions. Only activities performed for at least ten minutes during the last seven days were recorded in the questionnaire. ## 4.2. Characterization of LTPA by Sub-Domains and Intensity Categories The IPAQ measures time spent in different areas (sub-domains): [1] work, [2] transport, [3] home and gardening, and [4] leisure in three intensity categories (walking, moderate-intensity activity, and vigorous-intensity activity). For details on calculating physical activity levels, see elsewhere [51]. Briefly, individuals who (regardless of intensity category) performed any form of physical activity in their leisure time (strictly outside working hours) were included in the group of people who performed LTPA. The three intensity categories of LTPA are based on the form of exercise performed: Walking: leisure walks outside working hours; Moderate: non-strenuous exercise (outside of walking in leisure time), such as light cycling, swimming, table tennis, jogging, etc.; Vigorous: strenuous leisure time activity, such as: running, fast cycling, swimming, dancing, aerobics, etc. In addition, LTPA intensity was quantified as weekly metabolic equivalent task minutes (MET-min/week) based on participants’ responses according to the IPAQ scoring protocol [81]. Total minutes over the last seven days spent on different types of LTPA were defined for each individual to create MET-min/week scores for activity sub-domains, and average values were calculated for both sample populations by sex. ## 4.3. DNA Extraction, SNP Selection, Genotyping, Testing Hardy-Weinberg Equilibrium, and Linkage Disequilibrium DNA was extracted from EDTA-anticoagulated blood samples using the MagNA Pure LC system (Roche Diagnostics, Basel, Switzerland) following the manufacturer’s instructions. Using online search engines such as PubMed, Ensemble, and HuGE navigator, a systematic literature search was conducted to identify SNPs statistically significantly associated with LTPA. The search time frame related to the present study was until 5 August 2019. Keywords and their combinations used in the search: leisure time physical activity, recreational physical activity, genetics, genome-wide association study (GWAS), candidate gene, genotype. In the selection of SNPs, particular attention was focused on the results of the three GWAS [14,15,73] and a candidate gene study [82], which were the most relevant in this field. The literature search identified a total of ten SNPs, and these were genotyped using the MassARRAY platform (Sequenom Inc., San Diego, CA, USA) with iPLEX Gold chemistry in the Mutation Analysis Core Facility (MAF) of the Karolinska University Hospital, Sweden. The MAF conducted validation, concordance analysis, and quality control according to their protocols. The Hardy-Weinberg Equilibrium (HWE) and linkage disequilibrium (LD) structure of the genotyped SNPs were calculated by Haploview software (version 4.2; Broad Institute; Cambridge, MA, USA). ## 4.4. Calculation and Optimization of the Polygenic Score Individuals with any missing SNP genotypes were excluded from further analyses; thus, 330 participants from the HG sample and 314 Roma individuals were included in genotype analysis. In the PGS calculation, each person was assigned a score based on the number of effect alleles carried. The effect allele was considered to be the allele that promotes LTPA. Homozygous effect alleles were considered as “2”, heterozygotes as “1”, and genotypes with no effect allele were considered as “0”. By using these codes, a simple count score was calculated as described by Equation [1], in which *Gi is* the number of the effect alleles for the ith SNP. This model sums up all alleles over all loci as a summary score, assuming that all alleles have the same effect in direction and size. [ 1] GRS=∑$i = 1$IGi The polygenic model optimization procedure aimed to select SNPs (identified in the systematic literature search) that had a strong association with LTPA in both study populations. For PGS optimization, adjusted logistic regression analyses (for age, ethnicity, sex, education, traveling by vehicle, BMI, and waist circumference) were used, and these analyses were also performed on a combined sample of the two populations. The SNPs were tested in ascending order of p-value, in which process each SNP was inserted into the statistical model one by one, starting from the SNP with the strongest association (with the lowest p-value), and the association between oPGS and LTPA was examined after each insertion. SNPs were selected and used for final oPGS only if they increased the strength of association of oPGS (decreased p-value and increased Cox-Snell R-squared value) with LTPA. SNPs that did not affect or weaken the model’s association, i.e., increased the p-value and decreased the R-squared, were excluded from further analyses. Genetic predisposition categories were formed based on the population distribution of oPGS, four groups were created, and trend analysis was used to examine the association of these groups with LTPA in general and its intensity categories. ## 4.5. Statistical Analysis The χ2 test was used to compare the differences between nonquantitative variables and to examine the HWE of genotyped SNPs. Statistical power for each SNP was calculated by using the Online Sample Size Estimator (OSSE) online tool (http://osse.bii.a-star.edu.sg/calculation1.php) (accessed on 10 January 2023). The Shapiro–Wilk test was used to examine whether the quantitative variables were normally distributed or not, and, if necessary, Templeton’s two-step method was considered to transform the non-normal variables into normal ones [83]. The Mann–Whitney U test was used to assess the distribution of age, waist circumference, BMI, oPGS, and MET-min/week between the study populations. Multiple logistic regression analyses were used to determine the association between genetic factors (individual SNPs and oPGS) and LTPA. All regression analyses were conducted using a model adjusted for relevant factors (e.g., age, ethnicity, sex, education, vehicle travel, BMI, and waist circumference). The Jonckheere–Terpstra trend test [84] was used to analyze the trend of association between oPGS categories and MET-min/week values. Ethnicity was used as a covariate when the two populations were combined and examined together. Statistical analyses were performed using IBM Statistical Package for the Social Sciences (SPSS) version 26 (Armonk, NY, USA). For multiple statistical analyses (all calculations involving the oPGS), the Bonferroni correction method was used (the conventional p-value of 0.05 was divided by the number of independent polymorphisms). ## 4.6. Ethics Declarations Informed consent was recorded for all subjects who were included in the study. 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--- title: Phytochemical Study on Seeds of Paeonia clusii subsp. rhodia—Antioxidant and Anti-Tyrosinase Properties authors: - Vithleem Klontza - Konstantia Graikou - Antigoni Cheilari - Vasilios Kasapis - Christos Ganos - Nektarios Aligiannis - Ioanna Chinou journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003135 doi: 10.3390/ijms24054935 license: CC BY 4.0 --- # Phytochemical Study on Seeds of Paeonia clusii subsp. rhodia—Antioxidant and Anti-Tyrosinase Properties ## Abstract In this study, the black fertile (BSs) and the red unfertile seeds (RSs) of the Greek endemic *Paeonia clusii* subsp. rhodia (Stearn) Tzanoud were studied for the first time. Nine phenolic derivatives, trans-resveratol, trans-resveratrol-4′-O-β-d-glucopyranoside, trans-ε-viniferin, trans-gnetin H, luteolin, luteolin 3′-O-β-d-glucoside, luteolin 3′,4′-di-O-β-d-glucopyranoside, and benzoic acid, along with the monoterpene glycoside paeoniflorin, have been isolated and structurally elucidated. Furthermore, 33 metabolites have been identified from BSs through UHPLC-HRMS, including 6 monoterpene glycosides of the paeoniflorin type with the characteristic cage-like terpenic skeleton found only in plants of the genus Paeonia, 6 gallic acid derivatives, 10 oligostilbene compounds, and 11 flavonoid derivatives. From the RSs, through HS-SPME and GC-MS, 19 metabolites were identified, among which nopinone, myrtanal, and cis-myrtanol have been reported only in peonies’ roots and flowers to date. The total phenolic content of both seed extracts (BS and RS) was extremely high (up to 289.97 mg GAE/g) and, moreover, they showed interesting antioxidative activity and anti-tyrosinase properties. The isolated compounds were also biologically evaluated. Especially in the case of trans-gnetin H, the expressed anti-tyrosinase activity was higher than that of kojic acid, which is a well-known whitening agent standard. ## 1. Introduction Paeonia is the sole genus in Paeoniaceae plant family, distributed within Europe and Asia, and is named after Paeon, a student of the Greek father of medicine Asclepius. The plant has been cultivated in China since the Han dynasty, and is known as the “king of flowers” and/or “flowers of richness and honor” [1]. It is known commercially for its ornamental value due to its impressive and often fragrant flowers. Since antiquity, the use of peonies has been reported in traditional medicine for the treatment of epilepsy conditions, as described by Dioscorides in the 1st century A.D. [2]. In Traditional Chinese Medicine, peonies have been used for the treatment of gynecological problems, cramps, and pain and have been used for their antioxidant, anti-inflammatory, analgesic, and antimicrobial properties [3,4,5]. So far, hundreds of secondary metabolites have been isolated from the various peony species, which have been classified into the following chemical categories: monoterpene glycosides, stilbenes, triterpenes, tannins, steroids, flavonoids, and phenols [3]. Paeoniflorin, a water-soluble monoterpene glycoside, has been observed in all peony species examined to date. It has not been found in any other genus beyond that of peonies and is therefore a chemo-taxonomic indicator of the genus, and it is also suspected to be responsible for some of the medicinal properties of the plant [6,7,8]. Trans-gnetin H, a resveratrol (3,5,4′-trihydroxystilbene) trimer that is usually found in plants of the Paeoniaceae and Vitaceae botanical families, has shown equally important pharmacological properties, such as antioxidant, cytotoxic antidiabetic, and anti-inflammatory effects, [9,10,11]. In Greece, eight wild Greek *Paeonia taxa* have been recognized and botanically characterized to date, namely, P. clusii subsp. clusii, P. clusii subsp. rhodia, P. mascula subsp. mascula, P. mascula subsp. hellenica, P. mascula subsp. icarica, P. mascula subsp. russi, P. peregrina, and P. parnassica [12,13]. Until now, only the roots of P. clusii Stern subsp. clusii and P. mascula L. subsp. hellenica and P. parnassica have been studied phytochemically, mainly based on the traditional uses and reports described in the literature. These subspecies’ in vitro antimicrobial properties, as well as their prophylactic anticonvulsant properties, have been also reported [2,14,15]. Melanogenesis, and, by extension, the pigmentation of the skin, are the most important factors in protecting against UV radiation, which damages the skin. On the contrary, excessive melanin synthesis and accumulation appears in many types of skin disorders, such as melasma, poikiloderma of Civatte, nevi, periorbital hyperpigmentation, cafe-au-lait spots, and freckles, and it is also associated with an increased risk of developing skin cancer [16]. Tyrosinase is a widely distributed enzyme, which is also found in high concentration in melanocytes and is essential for the biosynthesis of melanin. In recent years, natural products have attracted attention for the development of whitening agents as cosmeceuticals [17,18]. Several assays have exhibited that molecules of plant origin and plant extracts present these activities with the Moraceae family being a characteristic example [19,20]. P. clusii subsp. rhodia (Stearn) Tzanoud. is a Greek endemic species of the Paeoniaceae family that can be found in the mountains of the island of Rhodes, which has characteristic white flowers and large palm-shaped leaves [12]. We report herein a phytochemical study of its seeds, specifically its black fertile seeds (BSs) and red infertile seeds (RSs), which have not been previously studied. In the present research, four stilbene derivatives of resveratrol (trans-resveratrol, trans-resveratrol-4′-O-β-d-glucopyranoside, trans-ε-viniferin, and trans-gnetin H) were isolated and structurally determined, together with three flavonoids in the form of aglycons and/or glycosides (luteolin, luteolin 3′-O-β-d-glucoside, luteolin 3′,4′-di-O-β-d-glucopyranoside), one monoterpene glycoside (paeoniflorin), and phenolic benzoic acid from both BSs and RSs of the plant. Furthermore, the metabolite-rich BS extract was subjected to UHPLC-HRMS analysis, in which 33 metabolites were identified. In parallel, through GC-MS and HS-SPME analyses of the volatiles of RSs, 19 substances were detected. The total phenolic content (TPC) and the antioxidative and anti-tyrosinase activity were evaluated via an enzymatic assay. ## 2.1. Identification of Secondary Metabolites The BSs of P. clusii subsp. rhodia were studied phytochemically through UHPLC-HRMS analysis, and 33 metabolites were tentatively identified from the methanolic extract (Figure S1), including 6 monoterpene glycosides of the paeoniflorin type with the characteristic cage-like terpenic skeleton found only in plants of the genus Paeonia, 6 gallic acid derivatives, 10 oligostilbene compounds, and 11 flavonoid derivatives (Table 1). The GC-MS analysis of the RS dichloromethane extracts led to the detection of 11 substances, whereas nine substances were detected in the pentane extract (Table 2). Furthermore, the HS-SPME analysis led to the identification of 10 metabolites, and the main metabolites for all of these analyses were myrtanal and nopinone (Table 2). ## 2.2. Isolation of Secondary Metabolites From the BS methanolic extract, eight secondary metabolites were isolated through the use of chromatographic techniques and structurally elucidated based on spectral data: Trans-resveratol [34], trans-ε-viniferin [9], trans-gnetin H [35], trans-resveratrol-4′-O-β-d-glucopyranoside [36], luteolin [37], luteolin 3′-O-β-d-glucoside, luteolin 3′,4′-di-O-β-d-glucopyranoside [38], and paeoniflorin [39]. Moreover, from the RS dichloromethane extract, benzoic acid, which has been previously detected in several peony species, was isolated [35]. ## 2.3. Total Phenolic Content (TPC) The methanolic extracts of the BSs and RSs exhibited high phenolic contents: 204.62 ± 4.0 mg GAE/g extract for the BS extract and 177.59 ± 7.5 GAE/g extract for the RS extract. ## 2.4. DPPH Assay The antioxidant properties of both seeds’ methanolic extracts and of selected isolated compounds were determined using the DPPH assay and the results are displayed in Table 3 as percentages of DPPH inhibition in three different concentrations. Two-way analysis of variance (ANOVA) was used to evaluate results (p-value summary: $p \leq 0.0001$) and the significance of differences between means was determined by means of Tukey’s post hoc test. Multiple-comparisons differences at $p \leq 0.05$ were regarded as statistically significant. ## 2.5. Tyrosinase Inhibitory Activity The tyrosinase inhibitory activity of the studied methanolic extracts of BSs and RSs and of selected isolated compounds is presented in Table 4. One-way ANOVA was used to compare IC50 mean values ($p \leq 0.0001$) and two-way ANOVA (p-value summary: $p \leq 0.0001$) followed by Tukey’s post hoc test was used to evaluate the significance of differences between means of the inhibition activity percentages. A p-value < 0.05 was considered an indicator of statistical significance. ## 3. Discussion Monoterpenes and monoterpene glucosides are predominant in Paeonia species, according to data in the literature [40]. In this study, six monoterpene glycosides were characterised, including paeoniflorin, galloyl-paeoniflorin, dibenzoyl-paeoniflorin, methyl-debenzoyl-paeoniflorin, albiflorin, and one that was not further identified, referred to in Table 1 as a paeoniflorin isomer. Paeoniflorin is commonly found in the Paeoniaceae family and it is considered a chemotaxonomic marker for this family, having been reported in P. lactiflora, P. suffruticosa, P. emodi, P. osii, and P. anomala [35], as well as in the roots of the Greek species P. clusii subsp. clusii [14,15]. To date, stilbenes have been isolated only from the seeds of Paeonia species and appear to be resveratrol oligomers. In this study, 10 oligostilbene compounds were identified: trans- and cis- resveratrol, as well as their dimers trans and cis-ε-viniferin and two trimers in the form of trans-gnetin H isomers, along with their glucosides (trans and cis-resveratrol hexosides, trans and cis-ε-viniferin hexosides). Resveratrol and its oligomers have attracted the interest of researchers as potential therapeutic agents for various diseases due to the wide variety of biological and pharmacological activities they have presented [41,42,43,44]. For this reason, extensive research has been undertaken to find natural stilbene agents, which have so far been reported in plant families such as Dipterocarpaceae, Vitaceae, Cyperaceae, Gnetaceae, Fabaceae (Leguminosae), Paeoniaceae, and Apiaceadoraceae [45,46]. In the family Paeoniaceae, they have been found only in the seeds of peony species such as P. suffruticosa, P. lactiflora [3,9], P. rockii [47], and other paeony trees of Chinese origin, and only in P. officinalis [36] from Europe. A number of gallic derivatives from Paeonia species have been observed previously. The results of this study indicated that six of them, including gallic acid, methyl gallate, glucogallin, trigalloyl glucose, tetragalloylglucose, and di-O-galloyl-β-d-glucopyranose, were detected in the studied Greek plant. These compounds have been very recently reported only once in the seed kernels and hulls of P. lactiflora Pall. [ 21]. Furthermore, benzoic acid has been previously detected in several peony species [35]. In addition to the above constituents, 11 flavonoids, including kaempferol and luteolin and their glucosides, as well as two tetrahydroxyflavone hexosides, were present in the black seeds of the studied peony species. Furthermore, in the chemical category of flavonoids, luteolin and its glucosides (luteolin 3′-O-β-d-glucopyranoside and luteolin 3′,4′-di-O-β-d-glucopyranoside) were isolated and structurally determined, whereas luteolin-glucopyranosides were isolated for the first time in peonies and in the whole Paeoniaceae family. Furthermore, many of the compounds which were identified in the non-polar extracts of RS through GC-MS and HS-SPME, such as nopinone and myrtanal, which were the most abundant compounds, as well as cis- and trans-myrtanol, E-myrtenol, myrtenal, β-pinene oxide, camphene, α-methylbenzyl alcohol, and phellandral, have been found in previous studies in several peonies, mainly in their roots and flowers [14,48,49,50] but here they were detected for the first time in seeds and especially in RSs (red seeds) from this genus. Additionally, among the identified metabolites, luteolin and other flavonoid derivatives, such as kaempferol glucoside and di-glucoside, were found to possess significant DPPH radical scavenging activity in the study presented in [51], suggesting that a high flavonoid content (kaempferol- and luteolin-glycosides) is directly related to strong antioxidant properties [52]. In addition, polyphenols such as gallic acid and methyl gallate were previously reported to be more effective in scavenging free-radicals than the known antioxidant compound α-tocopherol [53]. Stilbenes such as resveratrol dimers (trans- and cis-ε-viniferin) and trimers (trans-gnetin H) exhibited the strongest antioxidant activity among the stilbenes referred to in the literature [10]. Moreover, resveratrol showed moderate activity which was higher than that of its glycosides trans and cis-resveratroloside, suggesting that its glucosylation decreased its antioxidant activity, probably due to its low affinity to biological lipid membranes [10,54]. Paeoniflorin and monoterpenes with pinane structures have been found not to inhibit free-radical DPPH [53], which was also confirmed by our results. Therefore, the correlation between the synergistic, antagonistic, and antioxidant activities of phenolic substances in peonies should be further examined in the future. No previous studies have been conducted on the antioxidant activity of P. clusii subsp. rhodia, but after comparing our results with those presented for other peonies in the literature, we concluded that the activity of this subspecies is significantly higher than that reported for other subspecies. Specifically, Sevim and coworkers [55] reported that seed extracts from seven herbaceous peony species in Turkey exerted low to moderate radical scavenging activity (below $50\%$ at 2000 μg/mL) against DPPH. In another study [56], the authors concluded that the antioxidant capacity of seed coats of Paeonia ranged from 66.56 mg/g to 82.85 mg/g (expressed as GAE mg per 1 g DW). Therefore, it seems that the studied red seeds (RSs) from Greek peonies may serve as a good source for extracts with high antioxidant capacity (84.0 ± 2.1 at 100 μg/mL), but further investigation is suggested and required. Regarding the isolated compounds, luteolin (IC50 = 13.2 ± 3.5 μg/mL) was characterized as a strong antioxidant in relation to gallic acid (IC50 = 4.2 ± 0.1 μg/mL), which is confirmed by the literature [57]. In addition, trans-resveratrol showed higher activity than its glycoside and trans-ε-viniferin, whereas trans-gnetin H showed low inhibition, a fact that is also confirmed by the literature [58,59]. Finally, paeoniflorin showed a negative ability to inhibit free-radical DPPH, as was also confirmed in the literature by Picerno et al. [ 53] and Wu et al. [ 60], and according to Matsuda et al. [ 61], the presence of the galloyl group is essential for the radical scavenging effect. Another study comparing the antioxidant effects of oxypaeoniflorin and paeoniflorin reported that oxypaeoniflorin has strong antioxidant potential in comparison to paeoniflorin although they have very similar chemical structures [62]. Therefore, the pinane structure, combined with the lack of a galloyl group and the lack of a hydroxyl group in its aromatic ring, further weaken the antioxidant potential of paeoniflorin as it has no free electrons to contribute. According to the anti-tyrosinase test results, the BS extract showed good inhibitory activity in all three concentrations (300, 150, and 75 μg/mL) with IC50 = 20.8 ± 1.8 μg/mL, whereas the RS extract showed low inhibitory activity. All three of the tested and isolated secondary metabolites—trans-resveratrol-4′-O-β-d-glucopyranoside, trans-gnetin H, and trans-ε-viniferin—inhibited the tyrosinase enzymes by more than $50\%$ at all tested concentrations, with IC50 values of 28.7 ± 6.8 μg/mL, 5.1 ± 2.3 μg/mL, and 3.7 ± 0.1 μg/mL, respectively. Trans-gnetin H and trans-ε-viniferin exerted comparable and/or higher anti-melanogenic potency than the standard compound kojic acid (IC50 = 2.0 ± 0.7 μg/mL) used. These results confirmed previous enzyme assay outcomes reported in the literature [10,36], in which trans-ε-viniferin was found to be more potent than kojic acid and ascorbic, whereas resveratrol exhibited a moderate inhibitory activity quite similar to that of arbutin [63]. ## 4.1. Plant Material Fresh black (BSs) and red seeds (RSs) of P. clusii subsp. rhodia (Stearn) Tzanoud. ( Figure 1) were obtained from Prophet Elias mountain (798 m in height) on the island of Rhodes (South Aegean, Greece) in April 2020. The sample was identified botanically by Dr Bazos I., Section of Ecology and Systematics, Department of Biology, National and Kapodistrian University of Athens, Greece. The seeds were naturally dried, ground using a laboratory mill, and stored in darkness at room temperature. ## 4.2. Chemicals and Reagents Stationary phases for column chromatography (CC) and vacuum liquid chromatography (VLC): silica gel (Kieselgel 60 H Merck), Sephadex LH-20 (25–100 mm, Pharmacia), gradient elution with the solvent mixtures indicated in each case. The solvents used were HPLC-grade and were purchased from Fisher Chemical (Fisher Scientific, Loughborough, Leics, UK). Fractionation was always monitored via TLC: *Merck silica* gel 60 F254 (0.2 mm layer thickness), Merck RP-18 F254S, and Merck cellulose. For preparative thin-layer chromatography (prepTLC), 60 F254 (Merck) silica gel was used. Detection on TLC plates was enabled using UV light (254 and 366 nm), H2SO4-vanillin spray reagent on silica gel, and Naturstoff spray reagent on cellulose, followed by heating. ## 4.3.1. Black Seeds of P. clusii subsp. rhodia The dried fragmented BSs of P. clusii subsp. rhodia (16.0 g) were successively extracted in 1 L methanol (MeOH) for 24 h at room temperature to obtain crude methanolic extract (7.5 g). The methanolic extract was subjected to vacuum liquid chromatography (VLC) (gradient elution with cyclohexane/CH2Cl2 70:30 to 0:100, CH2Cl2/EtOAc 80:20 to 0:100, and am EtOAc/MeOH gradient of 99:1 to 70:30) to yield 84 fractions (PB1-PB84). Fractions PB6, PB7, PB8, and PB9, eluted with CH2Cl2/EtOAc (80:20 to 50:50), were combined (1.4 gr) and further fractionated via CC over silica gel using as eluent mixtures of CH2Cl2/EtOAc/MeOH (9.7:0.3:0 to 0:7:30) and afforded trans-resveratol (12 mg), luteolin (11 mg), trans-ε-viniferin (57 mg), and trans-gnetin H (428 mg). Fractions PB27 to PB36, eluted with CH2Cl2/EtOAc/MeOH (1:9:0 to 0:9.9:0.1), were combined (717.2 mg) and subjected to CC over silica gel using as eluents mixtures of cyclohexane/EtOAc (50:50 to 0:100) and EtOAc/MeOH (99:1 to 70:30) to afford trans-resveratrol-4′-O-β-d-glucopyranoside (25.6 mg) and another fraction (231 mg) was further purified through CC with silica gel using CH2Cl2/MeOH (95:5 to 30:70) as eluent mixtures to yield paeoniflorin (52.6 mg) and luteolin 3′-O-β-d-glucopyranoside (5.3 mg). Combined fractions PB78 to PB85, eluted with EtOAc/MeOH (30:70), were subjected to CC over Sephadex (MeOH) and yielded luteolin 3′,4′-di-O-β-d-glucopyranoside (5.6 mg). ## 4.3.2. Red Seeds of P. clusii subsp. rhodia The dried fragmented RSs of P. clusii subsp. rhodia (6 g) were successively extracted using 40 mL methanol for 24 h at room temperature to obtain crude methanol extract (1.1 g). One part of the extract (700 mg) was subjected to MPLC with gradient elution with mixtures of H2O: MeOH of reduced polarity as mobile phase to collect 70 fractions (PR1-PR70). Fractions PR11 and PR12, which were eluted with H2O/MeOH (80:20 and 70:30), were combined (36.1 mg) and subjected to preparative TLC with a mixture of CHCl3:MeOH at 75:25 to afford paeoniflorin (15.2 mg). A part of the dried fragmented RSs (500 mg) was extracted with 10 mL of dichloromethane (DCM) and another quantity of 500 mg with 10 mL of pentane C5H12 using ultrasound for 30 min at 25 °C to yield 7.4 mg and 5.1 mg, respectively. These extracts were further analyzed through GC-MS. A part of the crude RS DCM extract (25 mg) was subjected to preparative TLC with a mixture of toluene:EtOAc 70:30 v/v as a mobile phase to afford benzoic acid (2.1 mg). ## 4.4.1. Headspace Solid-Phase Microextraction (HS-SPME) The aroma of the P. clusii subsp. rhodia red seeds was studied through HS-SPME/GC-MS analyses [64]. HS-SPME was performed with Supelco SPME fiber 100 μm PDMS (polydimethylsiloxane coating) and Supelco SPME fiber 75 μm PDMS/DVB (polydimethylsiloxane/divinylbenzene coating) attached to a manual SPME fiber holder (Supelco, Bellefonte, PA, USA). First, the fiber was conditioned in the GC at 250 °C for 30 min and then was inserted into the sample vial. For SPME extraction, 500 mg of the sample in a glass vial (15 mL), closed with a PTFE-coated silicone rubber septum, was used. The temperature in our experiment was set at 60 °C and the vial with the sample was placed on the hotplate for 30 min. After that time, the fiber was exposed to the sample for 30 min at 60 °C and then it was transferred to perform GC-MS analysis. The initial temperature of the column was 55 °C for 2 min with an increase of 5 °C/min until it reached 240 °C, where it remained for 2 min. The total analysis time was 41 min. The substances were identified by comparing the mass spectrum of each substance with those of the Wiley 275 library and the literature. ## 4.4.2. GC-MS Analysis The analyses were performed on an Agilent Technologies Gas Chromatography 7820A sysem (Shanghai, China), connected to an Agilent Tecnologies 5977B mass spectrometer (Santa Clara, CA, USA), which worked via EI with an ionization energy of 70 eV. The gas chromatograph was equipped with a split/splitless injector and a 30 m long HP 5MS capillary column with an inner diameter of 0.25 mm and a membrane thickness of 0.25 μm. The temperature in the injection sample was 250 °C and the carrier gas was helium. The following temperature program was used: an initial column temperature of 60 °C was kept constant for 5 min and with an increase of 3 °C/min it reached 280 °C, where it remained for 15 min. The total analysis time was 93 minutes. Identifications were made using the Wiley275 library and bibliographic data. ## 4.5. Nuclear Magnetic Resonance (NMR) 1H NMR and 2D-NMR (COSY, HMBC, HSQC) spectra were recorded on a Bruker (Rheinstetten, Germany) DRX 400 (400 MHz) spectroscopy instrument using CD3OD, CDCl3 as a solvent and TMS as an internal standard. ## 4.6. Analysis through UHPLC-HRMS Ultra-high-performance liquid chromatography was performed employing a Vanquish UHPLC system (Thermo Fisher Scientific, Germering, Germany) equipped with a binary pump, an autosampler, an online vacuum degasser, and a temperature-controlled column compartment. LC-MS-grade acetonitrile (ACN), methanol (MeOH), and formic acid (FA) were purchased from Fisher Scientific (Thermo Fisher Scientific, Leicestershire, UK) and LC-MS water was produced using a Barnstead MicroPure Water Purification System (Thermo Scientific, Germany). An Accucore Vanquish UPLC C18 (2.1 × 50 mm, 1.5 μm) reverse-phase column (Thermo Scientific, Germany) was used for the analysis. High-resolution mass spectrometry was performed on an Orbitrap Exactive Plus mass spectrometer (Thermo Scientific, Germany). Samples were injected at concentrations of 100 ppm diluted in MeOH/H2O at 50:50. The mobile phase consisted of solvents A (aqueous $0.1\%$ (v/v) formic acid) and B (acetonitrile). Different gradient elutions were performed for positive- and negative-ion-mode detection and after optimization of the chromatography the gradient applied was: $T = 0$ min, $5\%$ B; $T = 3$ min, $5\%$ B; $T = 21$ min, $95\%$ B; $T = 26$ min, $95\%$ B; $T = 26.1$ min, $5\%$ B; $T = 30$ min, $5\%$ B. The flow rate was 0.3 mL/min and the injection volume was 5 μL. The column temperature was kept at 40 °C and the sample tray temperature was set at 10 °C. The ionization was performed at HESI, in both positive and negative modes. The conditions for the HRMS for both negative and positive ionization modes were set as follows: capillary temperature, 320 °C; spray voltage, 2.7 kV; S-lense Rf level, 50 V; sheath gas flow, 40 arb. units; aux gas flow, 8 arb. units; aux. gas heater temperature, 50 °C. Analysis was performed using the Fourier transform mass spectrometry mode (FTMS) in the full-scan ion mode, applying a resolution of 70,000, whereas the acquisition of the mass spectra was performed in every case using the centroid mode. The data-dependent acquisition capability was also used at 35,000 resolution, allowing for MS/MS fragmentation of the three most intense ions of every peak exceeding the predefined threshold, applying a 10 s dynamic exclusion window. The normalized collision energy was set at 35. Data acquisition and analysis were completed employing Xcalibur 2.1. ## 4.7. Total Phenolic Content (TPC) The total phenolic content of the samples was determined by means of the Folin–Ciocalteu method [64]. In a 96-well plate, 25 μL of extracts with different concentrations (4, 2, 1 mg/mL) or standard solutions of gallic acid (2.5, 5, 10, 12.5, 20, 25, 40, 50, 80, 100 g/mL), both diluted in DMSO, were added to 125 μL of a Folin–Ciocalteu solution ($10\%$), followed by the addition of 100 μL of $7.5\%$ sodium carbonate. The plate was incubated for 30 min in darkness at room temperature. The absorbance at 765 nm was measured using a TECAN Infinite m200 PRO multimode reader (Tecan Group, Männedorf, Switzerland). All measurements were performed in triplicate, the mean values were plotted on a gallic acid calibration curve, and the total phenolic content was expressed as mg equivalents to gallic acid (GAE) per gram of dry extract. ## 4.8. DPPH (2,2-DiPhenyl-1-PicrylHydrazyl) Assay The antioxidant activity of the samples was evaluated based on DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity according to the literature [65]. For the DPPH assay, the methanol extract and the isolated compounds (1, 2, 3, 4, 5, and 6) (concentration of stock solution: 4 mg/mL) were prepared using dimethylsulfoxide (DMSO) as a solvent. Ten [10] μL of each sample were mixed with 190 μL of DPPH solution (12.4 mg/100 mL in ethanol) in a 96-well plate and then subsequently incubated, at room temperature, for 30 min in darkness. Finally, the absorbance was measured at 517 nm using an Infinite M200 Pro TECAN photometer (Tecan Group, Männedorf, Switzerland). All evaluations were performed in triplicates, whereas gallic acid was used as positive control (IC50 = 4.2 ± 0.1 μg/mL). The percentage inhibition of the DPPH radical for each dilution was calculated using the following formula: % inhibition = [(A − B) − (C−D)]/(A − B) × 100, where A: control (w/o sample), B: blank (w/o sample, w/o DPPH), C: sample, D: blank sample (w/o DPPH). All the samples were tested at final concentrations of 200 μg/mL, 100 μg/mL, and 50 μg/mL, whereas for the most active of them (DPPH inh. >$70\%$ at concentration $C = 50$ μg/mL), the IC50 value was calculated. ## 4.9. Tyrosinase Inhibition The methanolic extract, as well as compounds 3, 4, and 5, were investigated for their ability to inhibit the oxidation of L-DOPA (L-3,4-dihydroxyphenylalanine) to dopaquinone and subsequently to dopachrome by the enzyme tyrosinase [19]. The fractions were initially dissolved in DMSO (10 mg/mL) and subsequently diluted in the proper concentration in phosphate buffer, $\frac{1}{15}$ M (NaH2PO4/Na2HPO4), pH 6.8. Final concentrations of DMSO in the well did not exceeded $3\%$. In 96-well plates, 80 μL of phosphate buffer $\frac{1}{15}$ M (NaH2PO4/Na2HPO4), pH 6.8, 40 μL of sample in the same buffer and 40 μL mushroom tyrosinase (92 Units/mL) in the same buffer, were mixed. The contents of each well were incubated for 10 min at 25 °C, before 40 μL of 2.5 mM L-DOPA were added into the same buffer. After incubation at 25 °C for 5 min, the absorbance at 475 nm of each well was measured. Samples were evaluated at 75 μg/mL, 150 μg/mL, and 300 μg/mL, in triplicate, and blank samples for every fraction were also measured, whereas kojic acid was used as a positive control. The percentage inhibition of tyrosinase activity was calculated using the following equation: [(A − B) − (C − D)]/(A − B) × 100, where A: control (w/o sample), B: blank (w/o sample, w/o tyrosinase), C: sample, D: blank sample (w/o tyrosinase). ## 4.10. Statistical Analysis All in vitro tests were performed in triplicate and values are expressed as mean values ± S.D. of the three independent experiments, calculated in Excel. Then, statistical analysis was performed on the means of the triplicates using GraphPad Prism Version 8.3.0, applying one-way ordinary analysis of variance (ANOVA) for tyrosinase IC50 and two-way ANOVA for the rest of the experiments. ## 5. Conclusions The black fertile seeds (BSs) and the red unfertile seeds (RSs) of the Greek endemic *Paeonia clusii* subsp. rhodia were studied and nine [9] phenolic derivatives were isolated, whereas thirty-three [33] metabolites were identified from BSs through UHPLC-HRMS. The total phenolic content of BSs was extremely high, as well as the anti-tyrosinase activity. The high antioxidant activity expressed by the extracts could suggest that the studied extract could be useful for the treatment of the effects of oxidative stress, which can lead to several skin disorders. 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--- title: Brain-targeted delivery of Valsartan using solid lipid nanoparticles labeled with Rhodamine B; a promising technique for mitigating the negative effects of stroke authors: - Shereen A. Sabry - Amal M. Abd El Razek - Mohamed Nabil - Shaimaa M. Khedr - Hanan M. El-Nahas - Noura G. Eissa journal: Drug Delivery year: 2023 pmcid: PMC10003139 doi: 10.1080/10717544.2023.2179127 license: CC BY 4.0 --- # Brain-targeted delivery of Valsartan using solid lipid nanoparticles labeled with Rhodamine B; a promising technique for mitigating the negative effects of stroke ## Abstract The brain is a vital organ that is protected from the general circulation and is distinguished by the presence of a relatively impermeable blood brain barrier (BBB). Blood brain barrier prevents the entry of foreign molecules. The current research aims to transport valsartan (Val) across BBB utilizing solid lipid nanoparticles (SLNs) approach to mitigate the adverse effects of stroke. Using a 32-factorial design, we could investigate and optimize the effect of several variables in order to improve brain permeability of valsartan in a target-specific and sustained-release manner, which led to alleviation of ischemia-induced brain damage. The impact of each of the following independent variables was investigated: lipid concentration (% w/v), surfactant concentration (% w/v), and homogenization speed (RPM) on particle size, zeta potential (ZP), entrapment efficiency (EE) %, and cumulative drug release percentage (CDR) %. TEM images revealed a spherical form of the optimized nanoparticles, with particle size (215.76 ± 7.63 nm), PDI (0.311 ± 0.02), ZP (-15.26 ± 0.58 mV), EE (59.45 ± $0.88\%$), and CDR (87.59 ± $1.67\%$) for 72 hours. SLNs formulations showed sustained drug release, which could effectively reduce the dose frequency and improve patient compliance. DSC and X-ray emphasize that Val was encapsulated in the amorphous form. The in-vivo results revealed that the optimized formula successfully delivered Val to the brain through intranasal rout as compared to a pure Val solution and evidenced by the photon imaging and florescence intensity quantification. In a conclusion, the optimized SLN formula (F9) could be a promising therapy for delivering Val to brain, alleviating the negative consequences associated with stroke. ## Introduction Stroke is the most common cause of permanent disability in adults worldwide and the second greatest cause of death in industrialized countries (Tapeinos et al., 2017). It has been found that stroke is accompanied by an increased level of angiotensin II and angiotensin II type-1 (AT1) receptor, and the outcome of stroke is determined by the volume of the ischemic core, the extent of secondary brain damage which manifested by brain swelling, and impaired microcirculation and inflammation (Barakat et al., 2014). Angiotensin receptor blockers (ARBs) have been shown to ameliorate peripheral and central actions of angiotensin II, mediated by AT1-receptors, and also to stimulate unopposed angiotensin II type 2 (AT2) receptors that are up-regulated in ischemic area (Barakat et al., 2014; Pai et al., 2016). Additionally, it has been confirmed in large clinical trials, that ARBs demonstrate an essential role in preventing both primary and secondary stroke (Dahlof, 2009). The blood-brain barrier (BBB) is a highly effective system that separates the central nervous system (CNS) from general circulation. The capacity of a certain molecule to cross BBB is a critical prerequisite in the formulation of any drug targeting the CNS. Basically, it promotes selective transport of essential molecules for brain function (Morsi et al., 2013). Therefore, screenings that predict BBB permeability of candidate compounds are indispensable for enhancing the field of drug discovery and finding effective therapeutics for many CNS related diseases. Although, there is a lot of ongoing research to evaluate BBB permeability, yet it is time-intensive and inefficient (Tang et al., 2022). Valsartan (Val) is one of ARBs that is available in both solution and tablet dosage forms, however, it is a tetrazole derivative that is slightly soluble in water with bioavailability of about $25\%$ and a volume of distribution of 17 liters. This indicates that Val does not distribute extensively into tissues (Michel et al., 2013), and as a result, it either crosses the BBB to a very low extent or not at all (Michel et al., 2016). Hence, there was a strong demand for enhancing Val delivery to brain. One possible approach for circumventing the BBB is through the use of SLNs (He et al., 2019). It is among the safest and most cost-effective drug carriers, allowing for the nontoxic and successful treatment of neurological illnesses. SLNs are simply made up of a drug encapsulated within a lipid core and a surfactant in the outer coat. Accordingly, SLNs are considered an excellent alternative to polymeric systems with minimal possible toxicity (Ghorab et al., 2015). The intranasal route allows drugs to be delivered directly to the CNS. So, drugs loaded into SLNs can directly penetrate the BBB from the nasal cavity (Duong et al., 2020). This work attempted to improve *Val aqueous* solubility and enhance its transport across the BBB by loading it into SLNs designed to be delivered through the nasal cavity. The efficiency of the drug being delivered to the brain was explored by tracing fluorescently labeled nasal Val-SLN with rhodamine b. (Rh-B). Namely, drug deposition in the brain was detected by imaging and quantifying fluorescence intensity (Photon *Imager optima* - Bio space lab, France, Software version: 3.5.10.1464). The procedure was modeled using a three-factor two-level [23] full factorial design (8 runs), design was employed to investigate the impact of three independent variables, namely lipid concentration (X1), surfactant concentration (X2), and homogenization speed (X3), on four dependent variables, namely particle size (PS-Y1), zeta potential (ZP-Y2), entrapment efficiency % (EE-Y3), and cumulative drug release % (CDR). ## Materials Valsartan (Val) was obtained as a gift sample from Servier Egypt Industries, Egypt. Glyceryl monostearate (GMS), Poloxamer 407 (P407), and egg lecithin were kindly provided by Egyptian International Pharmaceutical Industries Co., (EIPICO.), Egypt. Rhodamine B (Rh-B) was purchased from Lab vision Trade Company, Egypt. Chloroform, acetone, disodium hydrogen phosphate, and potassium dihydrogen phosphate were purchased from El-Gomhouria Company for trading chemicals and medical appliances, Cairo, Egypt. ## Preparation of Val-loaded SLNs Valsartan loaded SLNs were prepared by emulsification solvent evaporation process (Palei & Das, 2013) with slight modifications (volume and type of organic solvent and stirring rate). Briefly, Val ($1\%$ w/v) was dissolved in a mixture of chloroform: acetone (5 ml: 2 ml) in which GMS and egg lecithin were previously dissolved by stirring at 40 °C using a magnetic stirrer. This oily phase was then dripped into 25 ml of an aqueous P407 solution kept at the same temperature (40 °C) and emulsified by homogenization for 15 minutes to prepare O/W emulsion. The formed dispersion was stirred continuously at 700 rpm for 3.5 h using a mechanical stirrer to assure complete evaporation of the organic solvent residue. The lipid was precipitated out in the aqueous medium, resulting in SLN formation. Thereafter, the formulations were sonicated for 4 minutes by a pan sonicator and kept at room temperature overnight. Then, they were stored in the refrigerator for further studies. Plain SLNs were prepared by the same procedure mentioned above, but without the addition of the drug. These plain SLNs were used as a blank. To prepare Val-SLNs coupled with Rh-B for in-vivo fating, Rh-B (1 mg/100 mg lipid) was added at the lipid phase step, and the procedure was completed in the same way as previously mentioned (Topal et al., 2020). Eight formulations of SLNs (F1 to F8) were prepared according to 23 full-factorial experimental design as represented in Table 1. **Table 1.** | Formulation code | Lipid % (w/v) | SAA % (w/v) | Homogenization speed (rpm) | | --- | --- | --- | --- | | F1 | 3 | 0.5 | 10000 | | F2 | 3 | 0.5 | 15000 | | F3 | 3 | 1.5 | 10000 | | F4 | 3 | 1.5 | 15000 | | F5 | 5 | 0.5 | 10000 | | F6 | 5 | 0.5 | 15000 | | F7 | 5 | 1.5 | 10000 | | F8 | 5 | 1.5 | 15000 | ## Particle size (PS), polydispersity index (PDI) and zeta potential (ZP) The particle size, PDI, and zeta potential of different SLN formulations were measured by dynamic light scattering (DLS) technique (Malvern Zetasizer Nano–ZS90). A fixed volume of each SLN formulation was diluted with distilled water and then injected into a clear disposable zeta cell (Kaur et al., 2016a; Ibrahim et al., 2019). Results were presented as mean values ± standard deviation (SD). ## Entrapment efficiency (EE) % A dialysis technique was employed to separate the free drug from Val-loaded SLNs. A certain volume of SLNs dispersion equivalent to (40 mg) Val was placed into a dialysis bag (molecular weight cutoff 12,000–14,000 Da) previously soaked in Sörensen phosphate buffer solution (PBS) of pH 6.4 overnight and then immersed in a screw-capped bottle containing 100 ml of PBS (pH 6.4). The entire system was kept at 25 °C with continuous stirring in a thermostatic shaker water bath (Kotterman Shaker D3165 Hangisen, W-Germany) at 100 rpm. The free drug was dialyzed for one hour each time against 100 ml of PBS (pH 6.4) and assayed at λ max of 242 nm for Val content. The procedure was repeated till there was no Val in the medium, and the total free *Val is* the sum of all readings (Tamizharasi et al., 2009). The percentage of EE of SLN formulations was determined using the following equation (Alajami et al., 2022). EE (%) =Total amount of Val added− Amount of free ValTotal amount of Val ×100 ## In-vitro cumulative drug release study (CDR%) In-vitro Val release study was conducted for pure Val solution in PBS (pH 6.4) and all formulations of SLNs for 72 hours, using the dialysis bag technique (Misra et al., 2016; Chandana et al., 2021). Dialysis bags were soaked in PBS (pH 6.4) overnight before use. Fixed volume of pure drug solution and SLN formulations equivalent to (40 mg Val) were transferred to dialysis bags, the two ends firmly sealed and then suspended in a preheated receptor medium (100 ml PBS of pH 6.4) at 37 ± 0.5 °C under stirring at 100 rpm in a thermostatic shaking water bath. An aliquot of the dissolution medium (3 ml) was withdrawn at different time intervals, passed through a 0.22 µm filter, and replaced with an equal volume of fresh medium to maintain a constant volume. The drug concentration in each aliquot was analyzed by UV spectroscopy at 242 nm. All measurements were performed in triplicate, and the cumulative drug release percent (CDR%) was represented as mean ± SD. ## Kinetic study of drug release The release data of all SLN formulations were subjected to explore the mechanism of release kinetics according to the following models: zero order model (Qt = Ko.t), first order model (log Qt = log Qo – K.t/2.303), Higuchi release model (Qt = KH.t0.5), Korsmeyer-Peppas model (Qt/Q∞ = Kk.tn) and Hixson–Crowell model (Qo$\frac{1}{3}$ – Qt$\frac{1}{3}$ = Ks.t); where, Qt: amount of drug released, t: time interval, Qo: initial drug amount, Q∞: the amount of drug released at time infinity (∞), Ko, K, kH, Ks, Kk: release rate constants and n: release exponent (El-Nahas, 2010; Sheshala et al., 2019). The highest correlation coefficients (R2) referred to the drug release order, which was further confirmed by the release exponent value (n) of the Korsmeyer-Peppas model (Ibrahim et al., 2021). ## Stability study of SLN formulations All prepared SLNs formulations were stored at refrigerator temperature (4 °C) for 4 months. At the end of this period, the means of PS, PDI, and ZP were measured (Palei & Das, 2013). ## Statistical analysis Student’s t-test and one-way ANOVA were adopted to assess the significance of the difference between different formulations using Graph-Pad Prism version 5.02. Values were represented as the mean ± SD (Hasan et al., 2020; Hassan et al., 2020; Nair et al., 2021). ## Optimization of Val-loaded SLNs Formula optimization was conducted by factorial design software. The optimization strategy was reliant on the preferred target of each response (P.$S = 150$ nm, ZP = −20 mV, EE% = 60, and CDR% = 90). The values suggested by the software to prepare the optimized formulation (F9) were $4.9379\%$ w/v lipid, $0.6507\%$ w/v SAA, and 10000 rpm as homogenization speed. ## Differential scanning calorimetry (DSC) The melting and crystallization behavior of pure Val, P407, egg lecithin, GMS, and optimized Val-loaded SLN (F9) were studied by DSC (DSC-60; Shimadzu Corporation, Tokyo, Japan). For each measurement, accurately weighed samples (2 mg) were sealed in aluminum pans and analyzed over a temperature range of 0-250 °C under a nitrogen purge (50 ml/min) with a heating rate of 10 °C/min. ## Fourier transform infrared (FTIR) spectroscopy FTIR analysis was performed for the same components as in DSC analysis. An FTIR spectrometer (Perkinelmer 1600 FTIR spectrophotometer, USA) was used to record the FTIR spectra between 4.000 and 500 cm−1 using the KBr. FTIR was performed to investigate the possible type of interaction between pure Val and optimized formula components by elucidating the reduction, shifting, or disappearance of absorption bands of the studied samples. Figure 5 compares the FTIR spectra of the pure Val, the optimized formula, and its raw materials. **Figure 5.:** *FTIR spectra of (a) Pure drug; (b) P407; (c) egg lecithin; (d) GMS; (e) optimized Val-loaded SLN (F9).* In agreement with Chandana et al., Val showed characteristic peaks at 2963 cm−1 and 2932 cm−1 (C-H stretching, alkane), 1732 cm−1 (acidic C = O stretching), 1603 (ketonic C = O stretching), and 3430 cm−1 (carboxylic group, -COOH) (Chandana et al., 2021). The spectrum of GMS showed absorption bands at 3398 cm−1 for O-H stretching from the unesterified hydroxyl group of the glyceryl moiety, 1734 cm−1 (C = O, stretching), and 2918 cm−1 for C-H stretch in CH2 groups in the acyl chain of the fatty acid (Patel et al., 2014). In the case of the optimized formulation (F9), the characteristic peaks unique to the drug were not observed, indicating drug encapsulation into the nanocarrier (Ghorab et al., 2015; Omwoyo & Moloto, 2019). As well, there was a slight increase in the (O-H) band of GMS, which might be due to the formation of a hydrogen bond between Val and GMS. ## X-ray diffraction (XRD) study The encapsulation of the drug inside the nanoparticles was further confirmed by XRD (Ultima IV; Rigaku Corporation, Tokyo, Japan, using a Goniometer PW18120 as a detector). Samples were exposed to Cu·Kα radiation (40 kV, 25 mA, $k = 0.15418$ nm) and analyzed at (2θ) from 10° to 80°. Bragg’s equation was used to transform the data from scattering angle to the spacing of lipid chains. ## Transmission electron microscopy (TEM) The morphology of F9 with and without Rh-B coupling was investigated using TEM (Model JEM-1230, JOEL, Tokyo, Japan), in which a few drops of the formula were mounted on a carbon-coated grid, left for 2 minutes to allow better adsorption on the carbon film, excess liquid was removed with a filter paper, and then a drop of phospho-tungstic acid ($1\%$) was added (Kurakula et al., 2016; Al Ashmawy et al., 2021). ## In-vivo study of optimized SLN formulation Male albino mice (weighing 25 ± 3 g) and aged 12 weeks were obtained from VACSERA (Giza, Egypt). Nude mice were chosen to allow the detection of faint light signals (Mannucci et al., 2020). Mice were accommodated for one week prior to the start of the experiments, which were conducted totally under the supervision of veterinary microsurgery and with the agreement of Zagazig University’s Animal Ethics Committee (ZU-IACUC) under approval protocol No, ZU-IACUC/3/F/$\frac{106}{2020.}$ ## Administration of studied formulations to animals For ethical reasons, a small but statistically significant number of mice were used (Mannucci et al., 2020). Twenty mice were divided into four groups (5 mice per group). Group 1 received a vehicle (control group). Group 2 received the optimized Val-loaded SLN (F9), group 3 received blank SLN (F10), and group 4 received a pure Val solution (F11). All in-vivo tested formulations (F9, F10, and F11) were pigmented by Rh-B, as previously mentioned to be able to be tracked in the brain under in-vivo optical imaging (Aboud et al., 2016). Twenty microliters of each formulation were administered intranasally to mice, which was equivalent to 10 mg of valsartan per kg of mice (Sironi et al., 2004; Hadi et al., 2015). The permanent stroke of the distal middle cerebral artery was induced using an electrothermic coagulator, as previously described by Llovera et al. [ 2014]. For surgical proceedings, the mice were anesthetized by i.p. administration of ketamine/xylazine cocktail at a dose level (0.1 ml and 0.1 ml/100 g body weight, respectively). Mice were shaved gently on the back area of the skull and an antisepsis of the area was performed with $4\%$ alcohol-based iodine. At the place of the operation, a small incision was induced, then gently removing a piece of the skull to expose the middle cerebral artery and allow for the electro cautery drill. Post-surgically, all the animals were kept separately in their cages, and the wounds were cleaned daily without any dressing or covering over the wound. All formulations were administered by micropipette into both nostrils, following the protocol discussed by Hanson and coworkers, three days before stroke induction and continuing for another three days after stroke. At the end of the third day after stroke, mice were sacrificed ethically through an isoflurane overdose according to IACUC (Institutional Animal Care and Use Committee) recommendations. After perfusion, both lung and brain were excised and imaged (Hanson et al., 2013; Mannucci et al., 2020). ## Principles of photon imaging experiment The noninvasive detection and quantification of fluorescence distributed throughout the isolated organs (brain and lung) were performed by (photon *Imager optima* - Bio Space Lab, France, Software Version: 3.5.10.1464), allowing the evaluation of the biodistribution of fluorescently labeled formulations (Mannucci et al., 2020). Fluorescent images were obtained for dissected brain and lung isolated from all groups at λex = 539 nm and λem= 615 nm. ## Particle size, polydispersity index and zeta potential Results of PS, PDI and ZP are showed in Table 2. **Table 2.** | Formulation code | Particle size (nm) | PDI | Zeta potential (mv) | | --- | --- | --- | --- | | F1 | 99.05 ± 4.62 | 0.358 ± 0.03 | −19.16 ± 0.37 | | F2 | 138.33 ± 1.89 | 0.528 ± 0.02 | −18.66 ± 0.23 | | F3 | 1925.60 ± 75.07 | 0.716 ± 0.07 | −17.56 ± 0.28 | | F4 | 639.46 ± 39.71 | 1 ± 0.00 | −15.36 ± 0.51 | | F5 | 98.28 ± 5.63 | 0.259 ± 0.08 | −17.66 ± 0.20 | | F6 | 101.89 ± 2.84 | 0.195 ± 0.03 | −17.4 ± 0.36 | | F7 | 394.10 ± 18.37 | 0.191 ± 0.03 | −16.76 ± 0.80 | | F8 | 213.63 ± 0.50 | 0.556 ± 0.03 | −22.06 ± 0.66 | ## Particle size The particle size (Y1) of all formulations was in the range of 98.28 nm to 1925.60 nm for F5 and F3, respectively. The influence of independent variables and their interactions on particle size could be identified by the following polynomial regression equation: Y1 = 451 − 249 X1 + 342 X2−178 X3−240 X1*X2 + 134 X1*X3 − 189 X2*X3 From the obtained results, it was observed that, when increasing the lipid concentration from 3 to 5 (% w/v), there was a strong significant negative correlation with particle size (Pearson coefficient (r) = −0.426 and P value = 0.014) (Gardouh et al., 2010). The particle size decreased from 138.33 ± 1.89 nm to 101.89 ± 2.84 nm (F2, F6), 1925.60 ± 75.075 nm to 394.10 ± 18.37 nm (F3, F7), and 639.46 ± 39.71 nm to 213.63 ± 0.503 nm (F4, F8) as elucidated in Figure 1a and Table 2. These results were in harmony with Steiner and Bunjes, who related this behavior to the non-linear increase in the viscosity of the continuous phase, which is inversely proportional to the droplet size (Steiner & Bunjes, 2021). **Figure 1.:** *Effect of lipid % (a), SAA % (b) and homogenization speed (c) on particle size.* Another explanation might be that the size of SLN is affected by the number of carbon atoms in the fatty acid chain of the lipid. GMS had a smaller number of carbon atoms on its fatty acid chain, resulting in a smaller SLN. Therefore, increasing Glyceryl mono-stearate concentration resulted in the formation of small sized SLN (Gamal et al., 2020). Increasing SAA concentration from 0.5 to 1.5 (% w/v) showed a strong significant positive correlation on particle size ($r = 0.584$ and P value < 0.0001). These results were in accordance with Soma et al. [ 2017]. By the increase of SAA concentration from 0.5 to 1.5 (% w/v), a significant increase in particle size was noticed from 99.05 ± 4.62 nm to 1925.60 ± 75.075 nm (F1, F3), 138.33 ± 1.89 nm to 639.46 ± 39.71 nm (F2, F4), 98.28 ± 5.63 nm to 394.10 ± 18.37 nm (F5, F7) and 101.89 ± 2.84 nm to 213.63 ± 0.503 nm (F6, F8) as obvious in Figure 1b. These results were matched with Alajami and coauthors, who attributed these findings to the accumulation of excess SAA molecules at the nanoparticle surface or due to the expansion of the interfacial film by increasing SAA concentration (Asasutjarit et al., 2007; Alajami et al., 2022). Another justification for increasing particle size by increasing SAA concentration is the dehydration of propylene oxide and ethylene oxide blocks within the poloxamer molecule during emulsification and hot homogenization, leading to a reduction of steric repulsion (Gamal et al., 2020). Results in Figure 1c verified that, when homogenization speed was increased from 10,000 to 15,000 rpm at constant lipid and SAA concentration, particle size decreased significantly from 1925.60 ± 75.07 nm to 639.46 ± 39.71 nm (F3, F4) and 394.10 ± 18.37 nm to 213.63 ± 0.503 nm (F7, F8). This result might be due to inefficient speed to reduce the particles at a lower speed. Whereas, the high-speed homogenization was sufficient to decrease the particle size through the high intensity of the shearing force acting on the particles (Kushwaha et al., 2013). ## Polydispersity index Polydispersity index is a measurement of the broadness of the particle size distribution. Values which less than 0.5 are usually accepted by researchers, while 0.3 and below are most favorable (Hassan et al., 2020). PDI values of all SLNs ranged between 0.191 ± 0.036 and 1 ± 0.00 for F7 and F4, respectively as shown in Figure 2. F4, F5, and F6 had PDI< 0.3, indicating a homogeneous population of lipid vesicles (Danaei et al., 2018). **Figure 2.:** *Effect of lipid % (a), SAA % (b) and homogenization speed (c) on PDI values.* Figure 2a clarified that, increasing the lipid concentration from 3 to $5\%$, led to a significant decrease in PDI from 0.358 ± 0.03 to 0.259 ± 0.08 (F1, F5), 0.528 ± 0.02 to 0.195 ± 0.03 (F2, F6), 0.716 ± 0.07 to 0.191 ± 0.03 (F3, F7), and from 1 ± 0.00 to 0.556 ± 0.03 (F4, F8). This could be due to the reduction in particle size upon increasing lipid content. This was in accordance with Suhaimi and coworkers, who found that a decrease in the particle size was associated with a reduction in PDI values (Suhaimi et al., 2015). The increase in SAA concentration from 0.5 to $1.5\%$; resulted in an increase in PDI from 0.358 ± 0.03 to 0.716 ± 0.07 (F1, F3), 0.528 ± 0.02 to 1 ± 0.00 (F2, F4), and 0.195 ± 0.03 to 0.556 ± 0.03 (F6, F8), as demonstrated in Figure 2b. These results confirmed that the larger the particle size, the greater the PDI, and vice versa (Kaur et al., 2016a). Increasing PDI values upon increasing SAA% might be related to increasing the viscosity of the aqueous phase, which affected the emulsification efficiency during SLN preparation. As a result, particles of varying sizes were formed that contributed to a higher PDI (Hassan et al., 2020). Increasing the homogenization speed from 10000 to 15000 rpm; resulted in an increase in PDI from 0.358 ± 0.03 to 0.528 ± 0.02 (F1, F2), 0.716 ± 0.07 to 1 ± 0.00 (F3, F4), and 0.191 ± 0.03 to 0.556 ± 0.03 (F7, F8) as distinct in Figure 2c. Similar findings were obtained by Anarjan and coauthors, who found that the PDI of the nanodispersion systems was increased by increasing the speed of the homogenization process (Anarjan et al., 2015). ## Zeta potential Zeta potential is the overall charge of the particles, which helps to assess the formulation stability during storage (Radwan et al., 2019). The obtained results showed a non-linear correlation between ZP values and the independent variables, as observed in the following polynomial equation: Y2 = −18.077−0.393 X1+ 0.143 X2 − 0.292 X3− 1.083 X1*X2 −0.967 X1*X3− 0.482 X2*X3 All SLN formulations showed ZP values with negative charges, which indicated the stable nature of nanoparticles (Remya & Damodharan, 2018). The negative charge of SLNs might be attributed to the fatty acids released from GMS hydrolysis and the negative phospholipids from lecithin (Schuh et al., 2014; Emami et al., 2015). As demonstrated in Table 2, Val-loaded SLNs showed ZP ranges between −15.36 ± 0.51 mV and −22.06 ± 0.67 mV for F4 and F8, respectively. This ascertained better stability and dispersion in the medium (Shah et al., 2017). ## Entrapment efficiency % (Y3) Regression analysis equation that interprets the effect of independent variables on EE% (Y3) is represented as following: Y3 = 41.49 + 6.00 X1+2.65 X2+3.02 X3−4.74 X1*X2−6.53 X1*X3+0.43 X2*X3 From the obtained results in Figure 3a, it was evident that an increase in the lipid ratio from 3 to $5\%$ w/v led to increased EE% from 13.3 ± $0.521\%$ to 59.2 ± $1.37\%$ (F1, F5) and 38.56 ± $0.34\%$ to 42.8 ± $0.99\%$ (F3, F7) at constant SAA% and homogenization speed. **Figure 3.:** *Effect of lipid % (a), SAA % (b) and homogenization speed (c) on EE%.* These results might be contributed to excessive drug accommodation within lipid core with high lipid concentration (Emami et al., 2015). Similar results were obtained by Emami et al., and Soma et al., who found that, increasing the lipid content, led to increasing the viscosity of the medium and faster solidification of nanoparticles, thus preventing drug diffusion into the external phase (Emami et al., 2015; Soma et al., 2017). As observed in Figure 3b, there was a significant positive correlation between SAA concentration and EE%. Increasing P$407\%$ from 0.5 to $1.5\%$ w/v led to a significant increase in EE% from 13.3 ± $0.521\%$ to 38.56 ± $0.347\%$ (F1, F3), 42.88 ± $1.17\%$ to 47.2 ± $1.536\%$ (F2, F4), and 39.95 ± $0.79\%$ to 48 ± $0.92\%$ (F6, F8). These results might be attributed to, increasing the surface coverage of SLNs by increasing the SAA% and thus preventing drug leaching from the lipid matrix and consequently increasing the EE% (Kushwaha et al., 2013; Maqsood et al., 2022(. On the other hand, the combinatory effect caused by the simultaneous increase in the concentration of P407 in the aqueous phase decreased the EE% of Val from 59.2 ± $1.37\%$ to 42.8 ± $0.99\%$ (F5, F7) upon increasing SAA% from 0.5 to $1.5\%$ w/v at ($5\%$ lipid and 10000 rpm). This was also observed by Da Silva et al. [ 2011] and Emami et al. [ 2015], who found that P407 might favor the solubilization of Val in the aqueous medium. The obtained results in Figure 3c detected that, the increase in homogenization speed from 10000 to 15000 rpm at constant lipid and SAA %, led to a significant increase in EE% from 13.3 ± $0.52\%$ to 42.88 ± $1.17\%$ (F1, F2), 38.56 ± $0.34\%$ to 47.2 ± $1.53\%$ (F3, F4) and 42.8 ± $0.99\%$ to 48 ± $0.92\%$ (F7, F8). These results were also reported by Mai et al. [ 2018]. ## In-vitro release study The in-vitro release of Val from pure drug solution and all SLN formulations was studied for 72 hours using the dialysis bag method in a BPS medium (pH 6.4). Pure Val showed a rapid release of about $90\%$ in the first six hours, as observed in Figure 4. The effect of the independent factors on CDR% is illustrated in the following polynomial equation: Y4 = 85.621− 3.726 X1 − 4.661 X2 − 3.831 X3 − 0.231 X1*X2 − 2.191 X1*X3 + 1.834 X2*X3 **Figure 4.:** *CDR % of all SLNs formulations compared to pure drug solution.* The release pattern of most SLN formulations was noticed to be biphasic, with an initial burst release within the first four hours, this might be attributed to the drug on the surface of SLNs and its solubility in the selected medium (Kaur et al., 2016b; Rana et al., 2020), followed by sustained release over 72 hours (Yassin et al., 2010; Remya & Damodharan, 2018). The sustained release might be due to increasing the diffusional path length and hindering effects attained by the surrounding lipid core (Alajami et al., 2022). There was a negative correlation between X1, X2, and X3 on CDR% as indicated by Pearson correlation coefficients (-0.418, −0.523 and −0.430), respectively. For most formulations, increasing the lipid concentration, maintaining the drug release up to 72 hours by restricting the entry of medium and inhibited fast immobilization of Val from the lipid core and thus, extended the release % (Parvez et al., 2020). In another explanation, the diffusion distance from the lipid matrix decreased with the increase in lipid concentration (El-Say & Hosny, 2018; Bhattacharyya & Reddy, 2019). ## Kinetic studies As seen in Table 3, the Higuchi model had a higher R2 value for in-vitro drug release of all SLN formulations than the Hixson-Crowell model. In addition, R2 value for the first order model was higher than that of zero order. These findings established that the drug release from all formulations followed the diffusion mechanism (Ibrahim et al., 2021). The n value of the Korsmeyer-Peppas model provided additional confirmation about the type of diffusion (Bibi et al., 2022). As detected in Table 3, n-value was found to be less than 0.5, indicating that the drug release mechanism was quasi-Fickian diffusion (Basak et al., 2008; Olejnik et al., 2017). **Table 3.** | Formulation code. | R2 | R2.1 | R2.2 | R2.3 | R2.4 | n-value of Korsmeyer–Peppas model | | --- | --- | --- | --- | --- | --- | --- | | Formulation code. | Zero | First | Higuchi | Korsmeyer | Hixon | n-value of Korsmeyer–Peppas model | | F1 | −1.2561 | 0.8465 | 0.0219 | | −0.1506 | | | F2 | −1.1221 | 0.8453 | 0.1484 | 0.8700 | −0.0276 | 0.183 | | F3 | −2.0670 | 0.9831 | −0.4425 | 0.8106 | −0.6813 | 0.129 | | F4 | −0.2790 | 0.1229 | 0.6192 | 0.9456 | −0.0204 | 0.251 | | F5 | −0.4761 | 0.5519 | 0.5154 | 0.9307 | 0.2395 | 0.231 | | F6 | −1.7367 | 0.7595 | −0.2277 | 0.8248 | −0.4008 | 0.147 | | F7 | −0.1446 | 0.4398 | 0.7205 | 0.9888 | 0.2834 | 0.269 | | F8 | 0.3359 | 0.6126 | 0.8762 | 0.9654 | 0.5254 | 0.340 | | Optimized SLN (F9) | −1.1569 | 0.8045 | 0.0837 | 0.8049 | −0.0298 | 0.179 | ## Stability study of SLNs formulations Color change, particle aggregation, or phase separation were not seen in stored SLN formulations. According to the findings in Table 4, the particle size of certain formulations decreased significantly after being stored at refrigerator temperature. The decrease in particle size was correlated with the increase in the ZP as observed in F1, F3, and F7 respectively. Decreasing the particle diameter on storage at refrigerator temperature might be attributed to the microviscosity phenomenon, which is a property of the surfactant that prevents particle agglomeration and is a temperature-dependent factor that increases at refrigerator temperature (Shah et al., 2014; Makoni et al., 2019). **Table 4.** | Code | Particle size (nm) | Particle size (nm).1 | PDI | PDI.1 | Zeta potential (mV) | Zeta potential (mV).1 | | --- | --- | --- | --- | --- | --- | --- | | Code | Fresh formulations | Stored formulations | Fresh formulations | Stored formulations | Fresh formulations | Stored formulations | | F1 | 99.05 ± 4.62 | 89.35 ± 1.32* | 0.358 ± 0.034 | 0.41 ± 0.03# | −19.16 ± 0.37 | −17.7 ± 0.26* | | F2 | 138.33 ± 1.89 | 133.23 ± 7.97# | 0.528 ± 0.02 | 0.418 ± 0.01* | −18.66 ± 0.23 | −17.60 ± 0.51# | | F3 | 1925.60 ± 5.07 | 1644.40 ± 34.46* | 0.716 ± 0.078 | 0.56 ± 0.03# | −17.56 ± 0.28 | −14.46 ± 0.05* | | F4 | 639.46 ± 39.71 | 713.83 ± 46.42# | 1 ± 0.00 | 0.55 ± 0.03* | −15.36 ± 0.51 | −14.93 ± 0.92# | | F5 | 98.28 ± 5.63 | 150.67 ± 7.48* | 0.259 ± 0.086 | 0.59 ± 0.01* | −17.66 ± 0.21 | −15.63 ± 0.251* | | F6 | 101.89 ± 2.84 | 123.46 ± 13.43# | 0.195 ± 0.03 | 0.35 ± 0.06* | −17.4 ± 0.36 | −16.16 ± 0.35# | | F7 | 394.10 ± 18.37 | 336.80 ± 12.60 | 0.191 ± 0.036 | 0.58 ± 0.09* | −16.76 ± 0.81 | −14.66 ± 0.37# | | F8 | 213.63 ± 0.50 | 255.63 ± 39.70# | 0.556 ± 0.036 | 0.316 ± 0.01* | −22.06 ± 0.66 | −19.20 ± 0.20* | ## Design optimization As obvious in Table 5, the particle size of the optimized formulation (F9) without Rh-B coupling was higher than predicted (215.76 ± 7.47 nm to150 nm, respectively), but this value is still acceptable for brain targeting of SLNs, as demonstrated by Neves and coauthors, who reported that the particle size of most successfully used nanoparticles for drug delivery across the BBB ranged from 150-300 nm (Neves et al., 2015). However, particle size of (F9) which was loaded with Rh-B and administered in animals for in-vivo experiments was 166 ± 5.33 nm. Other measurements (PDI, ZP, and CDR%) were in good harmony with the predicted values as detectable in Table 5, which clarifies that the experimental design closely predicted the relationship between the dependent and independent variables and successfully assisted in setting up a model for optimizing Val-loaded SLNs (Gupta et al., 2016). **Table 5.** | Response | Predicted value | Observed value | | --- | --- | --- | | Y1: particle size (nm) | 150 | 215.76 ± 7.47 | | Y2: zeta potential (mV) | −20 | −15.26 ± 0.58 | | Y3: EE (%) | 60 | 59.45 ± 0.88 | | Y4: CDR (%) | 90 | 87.59 ± 1.67 | ## Differential scanning calorimetry DSC patterns of Val, P407, egg lecithin, GMS, and optimized SLN (F9) were shown in Figure 6. It was clear that the melting peaks of bulk GMS and pure Val were at 61.1 °C and 101.62 °C, respectively. The sharp peak of Val crystals (101.62 °C) was absent in the thermogram of Val-loaded SLN (F9), which confirmed drug solubilization in the lipid matrix. Moreover, the endothermic peak of GMS in F9 was broadened and shifted to 69.1 °C compared to bulk GMS (61.1 °C), which indicated SLN formation (Sharma et al., 2021). The same manner was seen by Song and coworkers, who attributed this shift to the small particle size effect (nanometer range), their high specific surface area, and the presence of surfactant (Song et al., 2016). **Figure 6.:** *DSC thermogram of (a) Pure drug; (b) P407; (c) egg lecithin; (d) GMS; (e) optimized Val-loaded SLN (F9).* ## X-ray diffraction study The XRD spectra of pure Val, optimized SLN (F9), and its components are represented in Figure 7. The diffraction spectra of pure Val showed characteristic peaks at a diffraction angle of 2θ degrees of 13.696, 14.194, 17.393, 21.775, and 25.182. These results were in great agreement with Sharma & Jain [2010], Zaini et al. [ 2017], and Abbaspour et al. [ 2021]. Glyceryl monostearate is high crystalline in nature with characteristic peaks at 2θ of 18.823, 19.137, 21.146, 22.676, 23.23 and 36.51 with the highest intensity peak at 19.137 representing the β-crystal form (Su et al., 2016). **Figure 7.:** *XRD spectra of (a) Pure drug; (b) P407; (c) egg lecithin; (d) GMS; (e) optimized Val-loaded SLN (F9).* The intensity of crystalline peaks of Val was reduced in the SLN formulation, which provided additional support that the drug was encapsulated within the carrier system (Parmar et al., 2011). The intensity of lipid peaks was also decreased in the SLN formulation which confirmed the decreased crystallinity of lipid in the SLN formulation (Parmar et al., 2011; Kushwaha et al., 2013; Rohit & Pal, 2013; Gupta et al., 2016; Behbahani et al., 2017). ## Transmission electron microscope (TEM) The shapes of the optimal Val-loaded SLN formulation (F9) with and without Rh-B coupling are shown in Figures 8 and 9. The particles examined were spherical and homogenous in shape, with a coating encapsulating the nanoparticles. TEM images showed slightly smaller particle sizes of nanoparticles compared to those measured with a Zetasizer instrument based on dynamic light scattering (Rubab et al., 2021). **Figure 8.:** *TEM images of optimized SLN formulation (F9) loaded with rhodamine B.* **Figure 9.:** *TEM images of optimized SLN formulation (F9) without rhodamine B.* ## Fluorescence imaging and photon quantification The fluorescent formulations were administered intranasally in mice, and fluorescence was investigated in the brain and lung to verify whether the drug was successfully distributed to the brain or not. The fluorescence intensity-per-area was identified by a color ranging from dark blue (low accumulation) to red (maximum accumulation) (El-Mezayen et al., 2018). Measurements were done by tracing a region of interest (ROI) on the fluorescent images, utilizing (PhotoAcquisition M3Vision analysis software) for photon quantification. These measurements were performed for lung and brain for all in-vivo tested formulations (Mannucci et al., 2020). The obtained results in Figure 10 showed that mice received the optimized formulation (F9) showed an apparent red fluorescence signal at the brain site, reflecting higher drug accumulation in the brain and successful delivery of Val loaded nanoparticle formulation across the BBB, as compared to the mice received the pure drug solution (F11), which showed a blue fluorescence at the brain site indicated the poor permeability of the pure drug across the BBB. These results were additionally confirmed by quantifying the fluorescence intensity in the brain and the lung. **Figure 10.:** *Fluorescent images acquired by Photon-imager of dissected brain and lung of: F9: SLN loaded with Val F10: Blank SLN; F11: Pure Val solution; N.B. organ in the right side of the image referred to the brain and organ in the left side referred to the lung.* The obtained results in Figure 11 depict that the optimized SLN formulation (F9) showed significantly higher fluorescence intensity in the brain as compared to the pure Val solution (F11). Furthermore, there was a non-significant difference ($P \leq 0.05$) in florescence intensity between F11 and the control group which confirmed poor delivery of pure Val to brain. The organ distribution study revealed a higher accumulation of optimized formula in the brain as compared to free drug solution, confirming the successful delivery of Val-loaded SLN formulation to the brain. **Figure 11.:** *Fluorescence intensity in brain and lung of: F9: SLN loaded with Val F10: Blank SLN F11: Pure Val solution.* ## Conclusion The results of various experiments led to the conclusion that the optimal SLN formula (F9), as suggested by full factorial design [23] was at a lipid concentration of $4.9379\%$ w/v, $0.6507\%$ w/v P407, and 10,000 rpm, demonstrated acceptable particle size, EE%, and sustained drug release over three days, which could be beneficial in decreasing dose frequency and increasing patient compliance. In-vivo photon imaging and fluorescence intensity quantification in dissected brain and lung of all animal groups indicated that the optimized Val-loaded SLN successfully delivered Val to the brain. 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--- title: Composite Coatings Based on Recombinant Spidroins and Peptides with Motifs of the Extracellular Matrix Proteins Enhance Neuronal Differentiation of Neural Precursor Cells Derived from Human Induced Pluripotent Stem Cells authors: - Ekaterina V. Novosadova - Oleg V. Dolotov - Lyudmila V. Novosadova - Lubov I. Davydova - Konstantin V. Sidoruk - Elena L. Arsenyeva - Darya M. Shimchenko - Vladimir G. Debabov - Vladimir G. Bogush - Vyacheslav Z. Tarantul journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003142 doi: 10.3390/ijms24054871 license: CC BY 4.0 --- # Composite Coatings Based on Recombinant Spidroins and Peptides with Motifs of the Extracellular Matrix Proteins Enhance Neuronal Differentiation of Neural Precursor Cells Derived from Human Induced Pluripotent Stem Cells ## Abstract The production and transplantation of functionally active human neurons is a promising approach to cell therapy. Biocompatible and biodegradable matrices that effectively promote the growth and directed differentiation of neural precursor cells (NPCs) into the desired neuronal types are very important. The aim of this study was to evaluate the suitability of novel composite coatings (CCs) containing recombinant spidroins (RSs) rS$\frac{1}{9}$ and rS$\frac{2}{12}$ in combination with recombinant fused proteins (FP) carrying bioactive motifs (BAP) of the extracellular matrix (ECM) proteins for the growth of NPCs derived from human induced pluripotent stem cells (iPSC) and their differentiation into neurons. NPCs were produced by the directed differentiation of human iPSCs. The growth and differentiation of NPCs cultured on different CC variants were compared with a Matrigel (MG) coating using qPCR analysis, immunocytochemical staining, and ELISA. An investigation revealed that the use of CCs consisting of a mixture of two RSs and FPs with different peptide motifs of ECMs increased the efficiency of obtaining neurons differentiated from iPSCs compared to Matrigel. CC consisting of two RSs and FPs with Arg–Gly–Asp–Ser (RGDS) and heparin binding peptide (HBP) is the most effective for the support of NPCs and their neuronal differentiation. ## 1. Introduction Tissue engineering aims to develop functional biological substitutes that restore, maintain, or improve broken tissue function by combining matrices, cells, and biologically active macromolecules. However, despite the notable successes of modern developments in the creation of various tissue engineering constructs, the task of obtaining matrices with optimized properties that improve the differentiation of NPCs into the desired types of neurons, the survival of transplanted neural cells and the high rate and degree of their vascularization and innervation required to ensure sufficient blood supply and normal functioning of the reconstructed nervous tissue still remain unsolved [1]. One of the attractive materials for such matrices are spidroins, which make up the frame filaments (dragline silk) of the spider web of orb weaving spiders. These proteins are characterized by unique mechanical properties—a combination of the highest values of strength and elasticity, which leads to high values of energy of rupture; they are also resistant to high and low temperatures and aggressive chemical influences [2]. Recombinant analogues of spidroins (RSs) have been obtained and their properties are largely close to natural [3]. Aside from high mechanical properties, RSs are biocompatible with any tissues of animals and humans, non-immunogenic, non-allergenic, and biodegradable to amino acids. Due to their self-assembly ability, RSs can form various supramolecular structures such as hydrogels including microgels, transparent elastic films, highly porous spongy 3D scaffolds, nonwoven materials, etc. [ 4]. In addition, the positive surface charge of these proteins and all devices based on them is very important for the adhesion of any cells including nerve cells to the substrate [5]. Another advantage of RS-based matrices is the possibility of introducing various biologically active peptides (BAPs) including motifs of the extracellular matrix (ECM) proteins into their structure. This allows obtaining matrices with unique predetermined properties, which are superior to synthetic and natural materials in terms of their breadth of application and the set of useful properties [6]. For tissue engineering, the sources of human nerve cells are also important. Significant progress in the technology of their production is associated with the creation of a reprogramming methodology, allowing for the transformation of the somatic cells of adult organisms into induced pluripotent stem cells (iPSCs) [7]. Various cocktails of small molecules and growth factors are used for directed neuronal differentiation of iPSCs, and the substrate on which this differentiation occurs is also extremely important. Currently, one of the most commonly used substrate is Matrigel (MG), derived from the basal membrane of Engelbreth–Holm–Swarm mouse sarcoma, which is rich in various ECM proteins including laminin, collagen IV, proteoglycans, heparin sulfates, and growth factors. However, this matrix cannot be used for regenerative medicine due to its oncogenic origin and potential for pathogen contamination [8]. Among the currently used matrix materials, RSs appear to be among the most promising for dealing with neuronal differentiation of cells derived from iPSCs in vitro. Some RSs have been shown to be effective agents in brain repairing after stroke due to the presence of multiple repeats of the GRGGL sequence recognized by NPC [9]. RS-based matrices support the proliferation and neuronal differentiation of neural stem cells. They have a more suitable surface charge (positive over the entire range of physiological pH values) and stiffness to support NSC growth than matrices made from silk fibroin or polylysine [10]. Previously, it has also been shown that the nonwoven matrix based on RSs rS$\frac{1}{9}$ and rS$\frac{2}{12}$, polycaprolactone and platelet-rich plasma, supports growth and neuronal differentiation of human NPCs [11]. The aim of this study was to evaluate the suitability of novel CCs containing RSs rS$\frac{1}{9}$ and rS$\frac{2}{12}$ in combination with the first time obtained by genetic engineering fused proteins (FPs) containing SUMO, RS rS$\frac{1}{9}$ “monomer”, and some BAP of the ECM proteins, for the growth of NPCs derived from human iPSCs and their differentiation into dopaminergic (DA) neurons. ## 2.1. The Influence of Different CC Variants on the Proliferative Activity of NPCs Differentiating from iPSCs The following CCs were used in this work: SP1: rS$\frac{2}{12}$ + FP(RGDS); SP2: rS$\frac{2}{12}$ (control for SP1 and SP5); SP3: rS$\frac{1}{9}$ + rS$\frac{2}{12}$ + FP(RGDS) + FP(HBP); SP4: rS$\frac{1}{9}$ + rS$\frac{2}{12}$ (control for SP3); SP5: rS$\frac{2}{12}$ + FP(GRGGL), where FP(RGDS) is the fused protein with the RGDS motif; FP(HBP) is the fused protein with the heparin binding peptide (HBP) motif; and FP(GRGGL) is the fused protein with the GRGGL motif. The Matrigel coating (MG) was used as the positive control. In the first stage of the work, we evaluated the ability of five different variants of CCs based on RSs rS$\frac{1}{9}$ + rS$\frac{2}{12}$, both individually and in combination with FP, to support the growth and proliferation of NPCs obtained by the directed differentiation of human induced pluripotent cells (iPSCs). The MG coating served as a comparison. A schematic of the experiment is shown in Figure 1. Nerve cells derived from iPSCs at different stages of differentiation (NPC, IDN, and DN) were initially characterized using qPCR by the level of transcription of early and late neuronal markers in them. It was shown that as neuronal differentiation proceeds, the expression level of early neuronal markers (NESTIN, PAX6, SOX2) decreased in the cells, while the expression level of late ones (TUBB3), in contrast, increased (Figure 2). Next, the ability of NPCs and IDNs to proliferate when cultured on CCs compared with the MG coating was assessed (Figure 3). As can be seen from the histograms in Figure 3a, the proliferation of NPCs is reduced when cultured on all CCs compared to MG with the exception of SP3. At the same time, the observed decrease in IDN proliferative activity when cultured on SP3 was minimal compared to the other variants including MG. The adhesive properties of most of the studied CCs for NPS and IDN were also decreased compared to MG, the only exception being SP3 (Figure 3). ## 2.2. Study of the Effect of Cultivation on CCs on the Differentiation of NPS into IDNs To evaluate the effect of different CC variants on NPC differentiation, the expression levels of mRNA specific for early (PAX6, SOX2 and NESTIN) and late (TUBB3) neuronal genes were analyzed in these cells using qPCR. NPCs were dispersed onto coating-treated culture dishes and cultured for 5 days. We found that the expression level of early and late neuronal marker genes did not differ significantly by cultivation NPCs on all of the analyzed coatings (Table 1). Analysis of early neuronal marker expression at the protein level using immunocytochemical staining showed that the NPC stage contained more than $75\%$ SOX2-positive cells in the population (Figure 4). The number of such cells was not statistically different when cultured on different CCs and MG, which confirms the data from the qPCR analysis (Figure 4a). Given the fact that NPCs can differentiate in both the neuronal and glial direction, we estimated the number of spontaneously differentiated glial cells and showed that they represented less than $1\%$ of the total population (Figure 4a). Figure 4b shows the representative photos of the immunocytochemical staining of the resulting cell population. Next, we analyzed the effect of cultivation on different CCs on IDN differentiation from the NPCs. For this purpose, the NeuN protein, which is a nuclear protein present in postmitotic neurons, was used as a marker protein. We found that the number of NeuN-positive cells did not differ between different cells up to 41 days of cultivation (Figure 5). ## 2.3. Influence of Cell Cultivation on CCs on Differentiation of NPCs into DA Neurons The dopaminergic (DA) neurons play an essential role in maintaining the human brain’s normal sensation, voluntary movement, emotion, and cognition [12]. The previously described protocol was used for the directed production of DA neurons from NPCs [13]. In IDN and DN obtained by the cultivation of NPS on different CCs, we performed a comparative study of the mRNA expression levels of the genes’ characteristic of DA neurons—tyrosine hydroxylase (TH) and the aromatic L-amino acid decarboxylase (AADC) (Figure 6). As can be seen from Figure 6, there was a significant increase in the expression of TH and AADC genes specific to DA neurons in DNs formed by cultivation on different CCs. This suggests that these CCs are very effective in affecting differentiation when using our protocol of the directed differentiation of NPCs into DA neurons. Using immunocytochemical analysis with anti-TH antibodies, we showed that in DNs, despite a significant increase in TH gene transcription, this change was less significant at the protein level (about $40\%$) and was observed only when cells were cultivated on the SP3 and SP5 coatings (Figure 7). Figure 8 shows the representative photographs of DN cultured on different CCs. ## 2.4. Influence of Cell Cultivation on CCs on Synaptogenesis in Emerging NPCs and IDNs The study of the transcription of marker genes responsible for synaptogenesis showed that the expression of the SNAP25, STX1A, SNPT, SYN2, and SYN3 genes did not differ significantly from all the CCs and MG used for the cultivation NPCs (Table 2). Further differentiation of NPCs into IDNs when cultivated on all CCs (except SP4) resulted in the increased expression of the synapse-specific genes SNAP25, STX1A, SYN2, and GSG1L compared to MG. By day 45 of differentiation, the expression levels of the studied genes in DN generally leveled off. There was only an increase in SNPT expression in DNs when they were cultivated on SP1 and SP5 (Table 3). Synapsins (SYN, SYN2, and SYN3) are also important markers of cellular synaptogenesis ability. As can be seen from Table 4, only IDNs showed a marked increase in the transcription of individual genes of this family when cells were cultivated on CCs. Thus, we can conclude that the studied coatings based on RSs and FPs compared to MG contribute to the enhancement of synaptogenesis in the process of neuronal differentiation of NPS into IDN. The main difference in the expression of genes involved in synaptogenesis mainly occurs with coatings with BAP (SP1, SP3 and SP5). ## 2.5. Effect of FPs on the Efficiency of Synaptogenesis during Neuronal Differentiation on CCs To establish the role in synaptogenesis of BAPs included in SP1, SP3, and SP5 coatings (RGDS, RGDS + HBP and GRGGL motifs, respectively), as part of FP, the effect of these CCs was compared with that of the CCs without BAPs (SP2 and SP4). SP2 consisting only of rS$\frac{2}{12}$ was used as the internal controls for SP1 and SP5, and SP4 coatings consisting only of a mixture of two RSs (rS$\frac{1}{9}$ + rS$\frac{2}{12}$) were used as a control for SP3. For this purpose, we compared the expression levels of genes involved in synaptogenesis in the IDNs and DNs obtained by cultivating on different controls with their internal controls. Table 5 and Table 6 present the data of the qPCR analysis of the transcription of various genes involved in synaptogenesis as ratios of the gene expression levels in IDN and DN cultured on the coating with added FPs (SP1, SP3, SP5) to SP2 and SP4 not containing these proteins. In the intermediate stage of neuronal differentiation (IDN), all coatings with BAP showed an increased expression of the synaptogenesis marker genes GSG1L and SYN2. The expression in the STX1A gene was enhanced in IDNs obtained when the cells were cultured on SP5, and the expression of the SNAP25 gene was enhanced in IDNs obtained on the SP3 coating. At the same time, the maximum difference in expression was observed with the SP3 coating compared with MG (Table 6). Thus, we can conclude that the presence of BAP in the coatings contributes to the enhancement in the expression of a number of genes involved in synaptogenesis in IDNs. The maximum activation of the transcription of these genes was observed when cells were cultured on the SP3 coating containing BAPs both with RGDS and HBP motifs. ## 2.6. Effect of Cultivation on CCs on the Expression of Neurotrophic Factors (NTF) Genes in IDNs and DNs Formed on Them Next, we investigated the effect of the coatings analyzed on the expression in the IDNs and DNs of neurotrophic factor (NTF) genes, which are necessary for normal differentiation and the maintenance of neuronal viability. When cultured on all coatings in the IDN intermediate stage, there was a significant increase in the expression of the BDNF, GDNF, and NGF genes, while in contrast, the NT3 gene decreased its expression (Table 7). At the same time, in DNs cultured on CCs, the NTF expression levels were commensurate with the cells cultured on MG. The protein amounts of BDNF and GDNF were assessed in DNs differentiated on different CCs using commercial enzyme-linked immunosorbent assay (ELISA) kit. It was found that when cells were cultured on the SP1, SP3 and SP5 coatings, the levels of both BDNF and GDNF in the cell lysates were many times (more than 10-fold) higher than when MG was used as a coating (Figure 9). At the same time, BDNF and GDNF were not detected in the conditioned media collected from the corresponding cultures. Since the SP1, SP3, and SP5 coatings contain FPs with BAPs, the results indicate that peptides of ECM proteins contribute to the enhancement of NTF synthesis in CC-forming DNs. ## 3. Discussion Cell therapy for neurodegenerative diseases requires the creation of functionally active neuronal constructs that can be used for transplantation. This goal, first of all, requires the selection of NPCs as well as the selection of matrices that allow these cells to grow and differentiate into mature neurons. The task of the present study was to find the optimal composition of RS-based matrices that would most effectively promote the growth and directed differentiation of human iPSC-derived NPCs into the desired neuronal types and provide increased survival of transplanted nerve cells after their transplantation. Our previous experience of using RSs in the form of microgels, highly porous spongy like 3D scaffolds, isotropic and anisotropic nonwoven matrices indicates that these materials are effective for neuronal cell growth and differentiation and can induce neoangiogenesis and neoinnervation when transplanted into the lesion area in the animal body, which is crucial for damaged tissue regeneration. The choice of RSs as a base material for such matrices is associated with the previously obtained results of successful applications of these proteins for the cultivation of various types of cells and in experiments on laboratory animals. For example, a layer of isolated neonatal rat cardiomyocytes was grown on a nonwoven matrix of RS rS$\frac{1}{9}$, rS$\frac{2}{12}$, and rS$\frac{2}{12}$-RGDS obtained by electrospinning and not containing any additional biologically active compounds. Optical excitation mapping proved that the cells do indeed form syncytium, and the excitation impulse travels through the grown tissue, causing synchronous cell contraction, as in in vivo cardiac tissue [14,15]. In experiments on laboratory animals, it was found that bioengineered microparticles from RS perform not only the function of a framework for cells, but are themselves capable of influencing the immune response and have pro-regenerative properties [16]. It was also shown that rS$\frac{1}{9}$-based anisotropic nonwoven matrices in combination with platelet-rich plasma are a suitable biocompatible substrate for reprogrammed NPCs when implanted into the brain and spinal cord of rhesus macaques [11]. BAPs with ECM motifs have long been utilized in the creation of scaffolds for neural tissue cells as components of matrices [17]. Cultivation of NPCs on anisotropic matrices based on rS$\frac{1}{9}$ PC and BAPs with motifs from ECM proteins (RGD from fibronectin, IKVAV laminin pentapeptide, and VAEIDGIEL motif from tenascin-C) mainly preserved their stemness in the growth medium [18]. It was demonstrated that different motifs have different effects on neurogenesis: the RGD motif promotes the formation of a smaller number of neurons with longer neurites, whereas the IKVAV motif is characterized by the formation of more NF200-positive neurons with shorter neurites. In experiments with nonwoven matrices made of RS with oriented fibers, they have been shown to direct the migration of Schwann cells and accelerate axonal growth from mouse dorsal ganglia as well as induce the migration of smooth muscle and aortic endothelial cells [19]. The present work is a logical continuation of our series of studies on the effect of RS-based matrices and their derivatives on the growth and differentiation of human and animal nerve cells in vitro and in vivo. In contrast to previous studies, the object of the present work was NPCs derived from human iPSCs. To study the growth and differentiation of NPS in vitro, a mixture of previously genetically engineered RS (rS$\frac{1}{9}$ and rS$\frac{2}{12}$) and FPs with three BAPs was used as a coating: RGDS tetrapeptide from fibronectin that recognizes the integrins of most cells; the GRGGL pentapeptide, which is recognized by NCAM and provides good adhesion of neural precursors, and heparin-binding peptide (HBP). HBP is part of laminin, which is a major component of the basal membrane surrounding the brain and blood vessels throughout the CNS [20], and is also present in the ventricular zone of the developing neocortex. Laminins have been shown to promote the expansion, migration, and differentiation of NSCs in vitro [21,22]. In addition, HBPs have been found to be involved in the binding of various growth factors and to interact with syndecans in the cell membrane [23]. Cultivating NPS and NDN on most of the studied CCs revealed a decrease in the adhesive properties and ability to support cell proliferation compared to MG, the only exception being SP3 coatings (Figure 3). At the same time, we found no change in the expression levels of early and late neuronal marker genes in cultivated NPCs on all the analyzed coatings (Table 1). However, a further comparison of the effect on the growth and differentiation of NPCs when they were cultured on CCs and standardly used MG, showed a marked advantage of the former. It was shown that in the DA neurons formed on CCs, there was a multiple increase in the expression of the AADC and TH genes characteristic of this cell type (Figure 6). These data were partially confirmed by immunocytochemical staining with antibodies to tyrosine hydroxylase: in particular, there was an increase in the number of DA neurons on the SP3 and SP5 coatings (Figure 7). Thus, we can conclude that these CCs are more effective than the MG coating for the directed differentiation of NPCs into DA neurons. In addition, IDNs cultured on CCs (Table 4 and Table 5) showed a marked increase in the transcription of certain genes involved in synthapogenesis compared to cells cultured on the MG coating (Table 3 and Table 4). This may indirectly indicate the acceleration of neuronal differentiation on the studied CCs. The maximum number of genes that changed their expression at this differentiation stage was observed when the cells were cultured on CCs SP1, SP3, and SP5. At the stage of DN, an increase in the expression of the SNPT gene was noted when cells were cultured on SP1 and SP5. To assess the role in the synaptogenesis of BAPs included in the FPs of the SP1, SP3, and SP5 coatings, the effects of these coatings were compared with the effects of CCs without BAPs (SP2 and SP4). It was found that all BAPs, to varying degrees, caused the upregulation of the studied genes. The maximum number of upregulated genes (SNAP25, SNPT, PSD95, SYN2, and GSG1L) was observed for SP3. The cultivation of cells on SP5 led to increased expression of STX2, SYN2, and GSG1L, and on SP1, only SYN2 and GSG1L. The secretion of NTFs, secretory dimeric proteins that have a significant influence on all biological processes of neurons during pre- and postnatal ontogenesis, is essential for the normal development and viability of neurons. In the developing nervous system, neurotrophins regulate cell division, cell migration, differentiation, establishment, and maintenance of intercellular contact activity as well as the initiation of apoptosis [24,25,26]. It was shown that the expression of most of the studied NTF genes (BDNF, GDNF, NGF) was enhanced at the NDN stage, the only exception being NT3, whose expression, in contrast, was decreased in all CC variants compared to the MG coating (Table 7). The maximum difference was observed for the SP1, SP3, and SP5 coatings, while for these same CCs, the increased expression of these genes persisted in DN, which was confirmed for BDNF and GDNF at the protein level (Figure 9). The fact that the increased expression of most of the studied genes involved in neuronal differentiation was observed for the SP5 variant containing the GRGGL sequence, in contrast to the SP2 variant that does not contain this sequence, which indicates the effect of GRGGL on the differentiation process. At the same time, a significant increase in the expression of the studied genes was found when the cells were cultivated on the SP5 coating compared to SP4 containing the rS$\frac{1}{9}$ protein, which includes 18 repeats of the GRGGL sequence [27]. This can be explained by the lower availability of GRGGL for contact with NCAM in the cell walls compared to the same in SP5, where it was exposed above the surface of the coating due to the presence of a 14-mer linker (SGG)4S, which ensures the binding of this peptide to the rest of FP and gives it extra mobility. The found influence of various BAPs on the differentiation of neural progenitors through the activation of the expression of the studied genes normally involved in differentiation is associated with the known role of these peptides in cell activation. This activation is mediated via various pathways of interaction of the BAPs with cells: RGDS interacts with integrins, BAP interacts with syndecans, GRGGL interacts with NCAM. A positive effect on the expression of genes involved in neuronal differentiation was already observed for individual BAPs (RGDS and GRGGL in SP1 and SP5, respectively). At the same time, the maximum effect, as expected, was found for the SP5 coating containing all three BAPs used in the work (GRGGL in the rS$\frac{1}{9}$ protein, RGDS, and HBP). These results are in good agreement with the known literature examples of the use of similar BAPs for the adhesion, proliferation, and differentiation of neuronal cells [28,29,30]. Thus, certain newly created RS- and FP-based CCs with ESM motifs promote NPC differentiation into DN by enhancing the expression of genes involved in synaptogenesis, stimulating the synthesis of a number of NTFs and contributing to the production of human DA neurons. ## 4.1. Isolation and Purification of Full Size RSs We used two RS—rS$\frac{1}{9}$ and rS$\frac{2}{12}$, whose genes we previously cloned in *Saccharomices cerevisiae* [14,27]. The rS$\frac{1}{9}$ molecule has a molecular mass of 94 kDa and consists of nine so called monomers, consisting of four initial repeats. Each of them contains GGX tripeptides (X = L, Y, Q) and one poly-Ala cluster consisting of five to eight Ala residues. This protein also contains 18 repeats of the NCAM-binding sequence GRGGL, which is a signal for binding neuronal cells. The rS$\frac{2}{12}$ molecule has a molecular mass of 113 kDa and consists of 12 so called monomers, consisting of five initial repeats. Each repeat contains pentapeptides GPGGY and GPGQQ and also one poly-Ala cluster consisting of five to eight Ala residues. These poly-Ala clusters form β-sheets, which, in turn, form crystallites that provide a unique stability to the materials based on spidroins [27]. Yeast biomass production, RS isolation, and purification by ion-exchange chromatography using a HiPrep $\frac{16}{10}$ SP FF column (GE Healthcare, Chicago, IL, USA) and an ACTA purifier TM chromatograph (GE Healthcare, Chicago, IL, USA) with pH exchange (pH 4.0–pH7.0–pH4.0) were carried out in accordance with previously published protocols [18]. The RSs were eluted from the column and dialyzed against deionized water and then frozen and lyophilized as described. ## 4.2. Obtaining and Purification Fused Peptides (FPs) FPs containing different BAPs were designed according to the same scheme: H6-SUMO-rS$\frac{1}{1}$-G(SGG)4S-[BAP], where H6 is the his-tag for ease purification of FPs on a Ni-column; SUMO (Small Ubiquitin Like Modifier) is a peptide product of the yeast *Smt3* gene [31], which, according to the literature [32] and our experience, increases the yield of the product in E.coli cells (can dramatically improve protein solubility, achieve native protein folding, and increase total yield by improving expression and decreasing degradation); rS$\frac{1}{1}$—monomer of rS$\frac{1}{9}$, which acts as an “anchor” in the interaction with full-sized RSs; G(SGG)4S is a neutral linker that promotes the exposure of biologically active peptide (BAP) over the matrix surface; BAP—any of the cloned BAP. We chose the following polypeptides as BAPs: RGDS, a tetrapeptide from fibronectin that recognizes the integrins of most cells [33,34]. GRGGL is a pentapeptide that is recognized by NCAM, interacts with neuron surface receptors, and upregulates NCAM expression in primary cortical neurons from embryonic day 18 (E18) Sprague–Dawley rats [9]; HBP—heparin binding peptide (GGGGSPPRRARVTY) [35], which is involved in the binding of various growth factors and interacts with syndecans in the cell membrane [23]. *The* genes of all three FPs were designed and chemically synthesized. The codons in the sequences were optimized to facilitate the synthesis of the construct: the rarest codons in E. coli were removed. The resulting constructs were cloned in the pET-28a-Novagen expressive vector (Novagen, Merck KGaA, Darmstadt, Germany) at the NcoI and XhoI restriction sites and transformed into the E. coli strain BL21(DE3) (Novagen, Merck KGaA, Darmstadt, Germany)) using the same vector. As a result, three strains, producing FPs: FP(RGDS), FP(GRGGL), and FP(HBP) were obtained. To isolate FPs, the strain producers were grown in a 10 L fermenter in a growth medium (20 g/L soy peptone Amresco 140 (VWR Life Science AMRESCO, Cambridge, MA, USA); 10 g/L yeast extract Maisons-Alfort, France; 5 g/L glucose (Acros Organics, Waltham, MA, USA); 5 g/L NaCl (Scharlab, Sentmenat, Barcelona, Spain); 0.5 g/L kanamycin (VWR Life Science AMRESCO, Radnor, PA, USA)); up to stationary phase; induction was carried out with lactose as part of the feed (20 g/L soy peptone Amresco 140; 10 g/L yeast extract; 30 g/L glucose; 5 g/L NaCl; 0.5 g/L kanamycin). The process was carried out at 28 °C, pH 7.0 with a typical growth time of 16–18 h. Biomass was harvested by centrifugation (14,000× g at 4 °C for 30 min) and suspended in buffer (0.05 M Na-Pi buffer, pH 8.0; 0.2 M NaCl; $5\%$ glycerin; 0.02 M imidazol) at a ratio of 9:1. Suspension was sonicated in 50 mL of buffer and clarified by centrifugation. To purify the FP, chromatography with the FPLC system ÄCTApurifierTM an ACTA (GE Healthcare, Chicago, IL, USA) with an installed HiTrap 5 mL of the NiNTA resin column (GE Healthcare, Chicago, IL, USA) was utilized. The elution was carried out stepwise using a decrease in pH to 6.0 and an increase in the content of imidazole (BioFroxx, Bruckberg, Germany) to 0.45 M in a buffer of the same composition. The desired proteins were detected using electrophoresis in $15\%$ PAAG-SDS. The proteins after chromatographic purification were dialyzed against deionized water, frozen at −70 °C and freeze-dried. Protein concentrations were determined by spectrometry at 280 nm. After purification, the samples contained >$95\%$ of the target protein. ## 4.3. Preparation of Mixed Protein Solutions for Dishes Coating Freeze-dried proteins (both full-length RSs and FPs) were dissolved in concentrated ($99.7\%$) formic acid (Helicon, RF) to a final concentration of 400 mg/mL for 14–16 h until complete dissolution. Then, the protein solutions were mixed in such a way that the final total concentration of all proteins was equal to 400 mg/mL, while the total concentration of FP in each solution was $10\%$ of the total protein. After that, each sample was diluted 100 times with deionized water. The final total protein concentration for all samples was 2 mg/mL, and the concentration of formic acid was $1\%$. Solutions were centrifuged at 18,000× g at 4 °C for 30 min to remove protein aggregates immediately prior to use. In the preliminary experiments, it was found that the optimal ratio between the full-size RSs and FPs was a ratio of 9:1 (by weight), so this ratio was used in all experiments. This meant that the total mass of full-sized RSs in the mixture was always $90\%$, and the total mass of FPs was $10\%$. At the same time, both rS$\frac{1}{9}$ and rS$\frac{2}{12}$ among themselves, and FP among themselves had always been in an equal ratio. Coating RS and FP mixtures were prepared immediately prior to use. To do this, we mixed the prepared solutions of each protein in the selected ratio. MG solution was prepared according to the manufacturer’s protocols (Corning Life Sciences, NY, USA). In this work, six variants of samples for the coating cups were used: SP1: rS$\frac{2}{12}$ + FP(RGDS) in relation to 9:1; SP2: rS$\frac{2}{12}$ (control for SP1 and SP5); SP3: rS$\frac{1}{9}$ + rS$\frac{2}{12}$ + FP(RGDS) + FP(HBP) in relation to 4.5:4.5:0.5:0.5; SP4: rS$\frac{1}{9}$ + rS$\frac{2}{12}$ (control for SP3) in relation to 5:5; SP5: rS$\frac{2}{12}$ + FP(GRGGL) in relation to 9:1; MG: (Matrigel, positive control). where FP(RGDS) is the fused protein with the RGDS motif; FP(HBP) is the fused protein with the HBP motif; and FP(GRGGL) is the fused protein with the GRGGL motif. ## 4.4. The Coating Preparation The coating was carried out as follows: 1 mL of the prepared protein solutions was poured into a sterile Petri dish ($d = 35$ mm) and incubated in a laminar box for 30 min, the protein solution was removed and to stabilize the coatings, the samples were immersed in $96\%$ (v/v) ethanol for 30 min to induce a β-sheet structure [36]. After that, the dishes were incubated for 30 min in sterile deionized water followed by $70\%$ ethanol for 30 min and then in sterile deionized water. This procedure was repeated 10 more times. The cups were dried and used immediately, or wrapped with Parafilm and stored at +4 °C for a month. A standard cup coating procedure was used for the Matrigel. A total of 1 mL of the solution was poured into a sterile Petri dish ($d = 35$ mm) and incubated for 60 min. The treated cups were used immediately or wrapped with Parafilm and stored at +4 °C for a month. Immediately before use, the Matrigel was removed and washed once with DMEM medium containing penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation). ## 4.5. Ethics Statement The study complies with the World Medical Assembly Declaration of Helsinki—Ethical Principles for Medical Research Involving Human Subjects. This work was approved by the Ethic Committee of the Institute of Molecular Genetics of National Research Centre “Kurchatov Institute” (Protocol no. 3 from 19 February 2018). Donor provided a written informed consent. ## 4.6. Human Pluripotent Stem Cell Culture The work was carried out on the iPSC line (IPSHD1.1S) obtained from skin fibroblasts of a healthy donor using the CytoTune™-iPS 2.0 Sendai Reprogramming Kit. The reprogramming vectors included the four Yamanaka factors, Oct, Sox2, Klf4, and c-Myc, shown to be sufficient for efficient reprogramming. The obtained iPSC expressed the essential pattern of specific pluripotency-associated genes, possessed a normal karyotype, and were capable of producing the derivatives of embryonic threenic germ layers [37]. Cells were cultured in StemMACS iPS-BrewXF medium (Miltenyi Biotec, Nordrhein-Westfalen, Germany) on Matrigel (Corning Life Sciences, NY, USA) treated with Petri dishes. The medium was changed daily. ## 4.7. Generation of Human iPSC-Derived Neural Stem Cells (NSCs) iPSCs were cultured in CO2 incubator ($5\%$ CO2, $80\%$ humidity and 37 °C) in iPS-Brew XF basal medium (Miltenyi Biotec, Nordrhein-Westfalen, Germany) until reaching an $80\%$ confluent monolayer. The culture medium was replaced by the medium for neural progenitors. After 10–14 days of cultivation, neural rosettes with specific “ridges” were formed. Rosettes were mechanically transferred to a 24-well plate with ultra-low adhesion (Corning Life Sciences, NY, USA) and cultivated for 3–5 days until neurospheres were formed. Neurospheres were collected and treated with $0.05\%$ trypsin (ICN Biomedicals, Hackensack, NJ, USA). After trypsin inactivation in DMEM supplemented with $10\%$ FBS (HyClone, Waltman, MA, USA), cells were resuspended in growth medium for neural progenitors with 5 µM Rock (StemoleculeY27632, Stemgent, Cambridge, MA, USA), and transferred to Petri dishes coated with Matrigel (Corning Life Sciences, NY, USA). NPs were cultivated to a dense monolayer, changing the medium every 48 h. After reaching the monolayer, NPCs were plated with $0.05\%$ trypsin on new Petri dishes coated with Matrigel at a dilution of 1:4 or 1:5. Cells were cultured in a CO2 incubator ($5\%$ CO2, $80\%$ humidity, and 37 °C). To study the effect of different matrices on the proliferation and differentiation of NPCs, cells of 2–3 passages were used. NPCs were dispersed onto Petri dishes pretreated with MG and RS. ## 4.8. Media Used for Cultivation and Differentiation of Neurons Culture medium for NPCs: *Neurobasal medium* (Gibco, Carlsbad, CA, USA), penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation), $2\%$ serum replacement (Gibco, Carlsbad, CA, USA), $1\%$ N2 (Life Technologies, Carlsbad, CA, USA), 2 mM L-glutamine (ICN Biomedicals Inc., Hackensack, NJ, USA), 1 mM non-essential amino acids (Paneco, Moscow, Russian Federation), 10 μM SB431542 (Stemgent, Cambridge, MA, USA), and 80 ng/mL recombinant Noggin (Peprotech, Cranbury, NJ, USA). Culture medium for neuronal differentiation type I (NDN): *Neurobasal medium* A, (Gibco, Carlsbad, CA, USA), penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation), $2\%$ serum replacement (Gibco, Carlsbad, CA, USA), $1\%$ B-27 (Life Technologies, Carlsbad, CA, USA), 2 mM L-glutamine (ICN Biomedicals Inc., Hackensack, NJ USA), 1 mM non-essential amino acids (Paneco, Moscow, Russian Federation), 100 ng/mL human SHH (Miltenyi Biotec, Nordrhein-Westfalen, Germany), 100 ng/mL FGF8 (PeproTech, Cranbury, NJ, USA), 10 μM purmorphamine (Sigma-Aldrich, Saint Louis, MO, USA). Culture medium for neuronal differentiation type II (DN): *Neurobasal medium* A, (Gibco, Carlsbad, CA, USA), penicillin–streptomycin (50 U/mL; 50 µg/mL) (Paneco, Moscow, Russian Federation), $2\%$ serum replacement (Gibco, Carlsbad, CA, USA), $1\%$ B-27 (Life Technologies, Carlsbad, CA, USA), 2 mM L-glutamine (ICN Biomedicals Inc, Hackensack, NJ, USA), 1 mM non-essential amino acids (Paneco, Moscow, Russian Federation), 20 ng/mL BDNF (PeproTech, Cranbury, NJ, USA), 20 ng/mL GDNF (PeproTech, Cranbury, NJ, USA), 200 μM ascorbic acid (StemCell, Vancouver, BC, USA), 4 μM Forskolin (Stemgent, Cambridge, MA, USA). ## 4.9. Targeted Differentiation of NPCs in IDN and DN The NPs were disseminated at 200,000 cells per cm² into Petri dishes pre-treated with MG and RS in neuronal precursor medium supplemented with 5 µM Rock (StemoleculeY27632, Stemgent, Cambridge, MA, USA). The next day, the medium was replaced with medium for the differentiation of type I neurons. The cells were cultured for 10 days, with the medium changing every other day. After the cells reached a dense monolayer, they were disseminated to new 1:4 or 1:5 cups. On the ninth day of cultivation, the cells were removed from the substrate with $0.05\%$ trypsin (Gibco, Carlsbad, CA, USA) and disseminated on a prepared culture dish at 400,000 cells per cm2 in medium for the differentiation of type I neurons with the addition of 5 µM Rock (StemoleculeY27632, Stemgent, Cambridge, MA, USA). The next day, the medium was changed to medium for the differentiation of type II neurons and the cells were cultured for 14 days. The medium was changed every other day for the first 7 days and daily thereafter. Cells were cultured in CO2-incubator ($5\%$ CO2, $80\%$ humidity, and 37 °C). ## 4.10. Immunocytochemistry The adherent cells on the Petri dish were washed with PBS, fixed with $4\%$ para-formaldehyde in PBS (pH 6.8) for 20 min at room temperature (RT), and washed in PBS with $0.1\%$ Tween 20 (Sigma-Aldrich, Saint Louis, MO, USA) three times for 5 min. Nonspecific antibody sorption was blocked by incubation in blocking buffer (PBS with $0.1\%$, Triton x100, and $5\%$ fetal bovine serum (HyClone, Waltman, MA, USA)) for 30 min at RT. Primary antibodies (Table 8) were applied overnight at 4 °C, and then washed in PBS with $0.1\%$ Tween 20 three times for 5 min. The secondary antibodies were applied for 60 min at RT, then washed in PBS with $0.1\%$ Tween 20 three times for 5 min. After that, the cell cultures were incubated with 0.1 μg/mL DAPI (Sigma-Aldrich, Saint Louis, MO, USA) in PBS for 10 min for visualization of the cell nuclei, and washed twice with PBS. The cells were investigated using an AxioImager Z1 fluorescence microscope (Carl Zeiss, Oberhohen, Germany), and images were taken with AxioVision 4.8 software (Carl Zeiss, Oberhohen, Germany). For cell counting, the multiple fields that covered the whole dish surface were imaged. The obtained images were analyzed with ImageJ 1.49 software (NCBI, Bethesda, MD, USA) using the ITCN plugin (Center for Bio-image Informatics, Santa Barbara, CA, USA). ## 4.11. Quantification of BDNF and GDNF Protein Levels in Cultured Cells The levels of BDNF and GDNF proteins were quantified using a sandwich ELISA. Culture media were collected at indicated time points, centrifuged at 14,000× g for 5 min at 4 °C, and the supernatants were stored at −80 °C. The cells were washed three times with cold PBS before being lysed in 1 mL of 100 mM PIPES lysis buffer, pH 7.0, containing 500 mM NaCl, $2\%$ BSA, $0.2\%$ Triton X-100, $0.1\%$ NaN3, and protease inhibitors (2 μg/mL aprotinin, 2 mM EDTA, 10 μM leupeptin, 1 μM pepstatin, and 200 μM PMSF) [38]. The sister wells were treated with trypsin and viable cells were counted using trypan blue exclusion and a hemocytometer. After three freeze/thaw cycles, the cell lysates were centrifuged at 14,000× g for 5 min at 4 °C, and the supernatants were stored at −80 °C. The BDNF and GDNF concentrations in the cell supernatants and lysates were determined in duplicate using Human/Mouse BDNF DuoSet ELISA and Human GDNF DuoSet ELISA Kits (R&D Systems, Minneapolis, MN, USA), according to the manufacturer’s instructions. ## 4.12. Quantitative Real-Time PCR (qPCR) Total RNA was extracted from the cells with a Trizol RNA Purification Kit (Invitro-gen, USA) following the manufacturer’s instructions, with a subsequent DNA-Free DNA Removal Kit (Invitrogen, Carlsbad, CA, USA) treatment. cDNA was synthesized on 0.5–2 μg of total RNA using M-MLV Reverse Transcriptase (Evrogen, Moscow, Russian Federation) with random primers. The primer sequences are shown in Table 9. The cDNA obtained was amplified using a CFX96 Touch™ Real-Time PCR Detection System (Bio-Rad, Berkeley, CA, USA) set to the following reaction conditions: denaturation at 95 °C (3 min), cycles $$n = 40$$ (95 °C, 15 s; 60 °C, 20 s; 72 °C, 45 s). The qPCRmix-HS SYBR reaction mixture (Evrogen, Moscow, Russian Federation) was used and 18S rRNA was accepted as the reference gene. ## 4.13. MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) Assay For the quantification of cell growth and viability, adhesive cell cultures were incubated for 4 h in culture medium containing 0.5 mg/mL MTT (Sigma-Aldrich, Saint Louis, MO, USA). Next, the medium was removed and the blue MTT–formazan product was diluted with DMSO (Panreac, Barcelona, Spain). After 2 h of incubation at RT on a shaker setting of 150 rpm/min, the absorbance of the formazan solution was recorded at 600 nm using a spectrophotometer (Metertech, Taiwan). ## 4.14. Statistical Analyses Data were analyzed using GraphPad Prism software. Normality and homogeneity of variance were assessed by Shapiro–Wilk and Brown–Forsythe tests, respectively. Statistical analyses of the data were performed using the Student’s t-test or ordinary one-way ANOVA followed by Dunnett’s post hoc test wherever applicable, as indicated in the figures and tables legend. Results are presented as the mean ± SEM. ## References 1. 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--- title: The Patient’s Physiological Status at the Start Determines the Success of the Inpatient Cardiovascular Rehabilitation Program authors: - Anna Odrovicsné-Tóth - Bettina Thauerer - Barbara Stritzinger - Werner Kullich - Andreas Salzer - Martin Skoumal - Bibiane Steinecker-Frohnwieser journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003145 doi: 10.3390/jcm12051735 license: CC BY 4.0 --- # The Patient’s Physiological Status at the Start Determines the Success of the Inpatient Cardiovascular Rehabilitation Program ## Abstract Multidisciplinary inpatient rehabilitation plays an important role in the recovery of patients with cardiovascular diseases (CVDs). Lifestyle changes, achieved by exercise, diet, weight loss and patient education programs, are the first steps to a healthier life. Advanced glycation end products (AGEs) and their receptor (RAGE) are known to be involved in CVDs. Clarification on whether initial AGE levels can influence the rehabilitation outcome is important. Serum samples were collected at the beginning and end of the inpatient rehabilitation stay and analyzed for parameters: lipid metabolism, glucose status, oxidative stress, inflammation and AGE/RAGE-axis. As result, a $5\%$ increase in the soluble isoform RAGE (sRAGE) (T0: 891.82 ± 44.97 pg/mL, T1: 937.17 ± 43.29 pg/mL) accompanied by a $7\%$ decrease in AGEs (T0: 10.93 ± 0.65 µg/mL, T1: 10.21 ± 0.61 µg/mL) was shown. Depending on the initial AGE level, a significant reduction of $12.2\%$ of the AGE activity (quotient AGE/sRAGE) was observed. We found that almost all measured factors improved. Summarizing, CVD-specific multidisciplinary rehabilitation positively influences disease-associated parameters, and thus provides an optimal starting point for subsequent disease-modifying lifestyle changes. Considering our observations, the initial physiological situations of patients at the beginning of their rehabilitation stay seem to play a decisive role regarding the assessment of rehabilitation success. ## 1. Introduction Although the global mortality rate for cardiovascular diseases (CVDs) has declined in recent years, CVDs remain the leading cause of death in the Western population. The inflammatory processes of atherosclerosis, a disease that functions as an inflammatory systemic disease affecting the arterial walls, are involved in all stages of atherosclerosis formation [1]. Efforts in the prevention of CVDs and their associated risk factors are required to mitigate the epidemic. Advanced glycation end products (AGEs) have been previously discussed and described in the context of cardiological diseases [2]. AGEs, usually associated with aging and diabetes, are modified molecular products, produced by nonenzymatic reactions between the aldehydic group of reducing sugars with proteins, lipids or nucleic acids [3]. They are formed especially in hyperglycemia; however, the production of AGEs also occurs in processes characterized by oxidative stress and inflammation, such as in the development of atherosclerosis. AGEs can also be incorporated in the forms of food that have been exposed to high temperatures, such as through frying, grilling or toasting, and sugar-rich foods. AGEs contribute to vascular damage and the occurrence of atherosclerotic plaque progression through the alteration of the functional properties of molecules of the extracellular matrix of vessel walls, or through activation of cell receptor-dependent signaling [4]. AGE effects are triggered by their binding to their specific receptors (receptor for advanced glycation end products, RAGE). This transmembrane signaling receptor is present in all cells associated with atherosclerosis and is able to influence cellular function, promote gene expression, and to enhance and release proinflammatory molecules. The AGEs can increase the production of reactive oxygen species (ROS) and initiate intracellular oxidative stress. Conversely, the increase in ROS production can in turn promote the production of AGEs, thereby forming a vicious circle between oxidative stress and AGEs [4]. The soluble form of the receptor for AGEs (sRAGE), however, is known to bind circulating AGEs and plays therefore a competitive role. Because the transmembrane domain is lacking, no signal can be forwarded. Thus, a high protective effect can be attributed to the soluble receptor, indicating that the ratio between AGEs and sRAGE acts as an important factor and seems to be more meaningful than the individual values. Because of this reason, we declared the quotient of AGE/sRAGE as AGE activity, which can also serve as an universal biomarker for various diseases [5,6,7,8,9,10]. AGEs bind and accumulate to collagen and elastin in the epithelium and dermis [11]. Several studies have demonstrated that skin autofluorescence reflects accumulation of AGEs in the layers of the skin and tissue levels, because they emit light when exposed to ultraviolet waves [3,12]. Moreover, it has been revealed that AGE measured in skin biopsies correlate with the measurements of skin autofluorescence performed with an AGE reader [13]. One of the proinflammatory enzymes involved in the process of atherosclerosis is myeloperoxidase (MPO). MPO is derived from granules of activated neutrophil granulocytes, monocytes and macrophages and enhances the oxidative potential of its co-substrate hydrogen peroxide by formation of potent oxidants [14,15,16]. The study of Kataoka et al. showed a greater progression of atherosclerosis in diabetic patients by the elevated systemic MPO levels [17]. In addition to findings that MPO promotes endothelial dysfunction and enhances atherosclerotic plaque formation, myocardial infarction also occurs via MPO [18,19]. These observations also underpin the development of therapeutic interventions targeting MPO. Today, adipose tissue is considered as an endocrine organ that releases biologically active factors called adipokines, such as the retinol binding protein-4 (RBP-4) [20,21]. Especially in women, RBP-4 is considered as an established risk factor and is presumed as a predictor for CVDs [22]. Huang et al. demonstrated that patients with higher RBP-4 levels experience an enormous risk of coronary artery calcification [23]. The results of a study over a 10-year follow-up period showed that elevated RBP-4 levels in childhood may predict cardiometabolic risk in adulthood [24]. In serum, RBP-4 levels are negatively correlated with high-density lipoprotein (HDL) but positively correlated with LDL-cholesterol, total cholesterol and triglyceride, indicating its role in lipid metabolism [25]. Therefore, a cardiac rehabilitation program with a balanced diet could aim, among other things, to reduce the levels of lipid metabolic parameters such as cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL) and triglycerides (TGL) [26,27]. The prevalence of CVDs is rapidly increasing in the world and CVD has been positively linked with diabetes mellitus (DM), particularly type 2 diabetes mellitus (T2DM) [28]. DM is a group of metabolic diseases characterized by hyperglycemia, resulting from defects in insulin secretion or response to insulin [29]. Several studies have demonstrated that the elevated levels of long-term glucose, verifiable via Hemoglobin A1c (HbA1c), might contribute to the development of CVDs and are associated with increased risk of death. It was revealed that changes in lifestyle (e.g., quitting smoking, reducing alcohol consumption, regular physical activity, healthy and optimal glycemic control) can lead to an improvement in CV risk and prevention of CVD events [30,31,32,33,34,35]. The most widely recognized marker of inflammation is the C-reactive protein (CRP), synthesized primarily by the liver [36]. Koenig et al. showed that it is released in response to acute inflammatory stimuli and is considered a risk biomarker for cardiovascular events [37]. CRP plays an important role in the atherosclerotic process and acts at early and key stages of plaque formation. Caulin-Glaser et al. showed an improvement in CRP levels in patients who participated in a cardiac rehabilitation program [38]. Evaluation of cardiac performance is often based on the result of ergometer training and maximum exercise capacity, which is equivalent to reaching a theoretical maximum heart rate [39]. In the present study, maximal cycle ergometry cardiovascular responses of individuals participating in a cardiac inpatient rehabilitation program via ergometric parameters (Watt value as well as the age- and weight-related expected cardiovascular exercise capacity) between the beginning and end of the rehabilitation stay were measured. One of the risk factors contributing to the CVDs is hypertension, as it is a significant contributor to CVD-related morbidity and mortality [40]. Normal blood pressure for adults is defined as a systolic pressure of less than 120 mmHg and a diastolic pressure of less than 80 mmHg, while readings of more than 130–$\frac{139}{80}$–89 mmHg signify hypertension [41]. A cornerstone of hypertension treatment is lifestyle modification and increased exercise and smoking cessation, among other things, which are encouraged in cardiac rehabilitation; in addition, the introduction of a Mediterranean diet after rehabilitation can be helpful [42]. Obesity, as well as higher body mass index (BMI), has consistently been associated with an increased risk for metabolic diseases and CVDs [43]. Being overweight can directly increase the risk of restrictive cardiomyopathy and heart failure due to diastolic dysfunction [44]. On the basis of these data, we aimed to demonstrate whether crucial CVD risk factors can be positively influenced by inpatient cardiac rehabilitation and whether the patient’s baseline condition may affect the success of rehabilitation. ## 2. Materials and Methods This study was conducted as a cross-sectional study at the rehabilitation center of the Austrian pension insurance company (PVA) in Saalfelden, from $\frac{05}{2016}$ to $\frac{04}{2017.}$ The procedures described were in accordance with the ethical standards of the Ethics Committee of Salzburg (415-E/$\frac{1988}{7}$-2016) as well as with the Helsinki Declaration. The medical superintendent of the PVA approved the concept. The study was recorded in the German Clinical Trials Register (DRKS00010509). ## 2.1. Study Design The data and serum of the investigated subjects were collected at admission (baseline, T0) and release (discharge, T1) following 3–4 weeks of inpatient rehabilitation stay. The cardiac therapy-induced changes were analyzed by pre–post analysis, comparing T0 with T1. Inclusion criteria were presence of a coronary heart disease such as status post myocardial infarction, PTCA/stent implantation, coronary artery bypass graft surgery, and an age limit of 25–75 years. Exclusion criteria were chronic kidney disease from stadium III (glomerular filtration rate ≤ 60 mL/min), acute inflammatory disease (CRP cut off ˃ 1.0 mg/dL), operation or greater trauma < 6 weeks ago, myocardial infarction < 4 months, pregnancy or lactation period, as well as alcohol and drug abuse. The selection of patients and admission to the study was conducted by doctors of the rehabilitation center Saalfelden. All patients agreed to participate after verbal and written informed consent. Their data were processed anonymously, and data protection was observed in the current version. ## 2.2. Patients Collective Sixty-six patients of the rehabilitation center Saalfelden, of the PVA, were included in this study. Seven of them dropped out: two because of termination of the rehabilitation program, one missed the appointment for skin autofluorescence measurement, one was older than 75 (one of the inclusion criteria) and three of them had higher CRP values (˃1.0 mg/mL). Patients in this study attended rehabilitation with the main indication of cardiovascular disease, and mainly exhibited a decrease in performance, dyspnea, and thoracic discomfort. Therefore, the data of 59 patients (45 men, 14 women) in the age range of 33–75 years with coronary heart disease were used for further investigation. All patients underwent an inpatient multidisciplinary rehabilitation program for 3–4 weeks with active and passive physical therapy. This program comprised a comprehensive rehabilitation medical admission process, the creation of an individual training program, exercise therapy with strength training (this is tailored to the patient and to prevent overload, each workout is controlled by heart rate monitoring), indication-specific training courses, diet and nutritional counseling, patient education program as well as psychosocial support. ## 2.3. Investigations of Serum Samples via Routine Laboratory and ELISA Measurements The following laboratory parameters were taken from the routine laboratory examination at the Saalfelden Rehabilitation Center: fasting blood glucose, CRP, total cholesterol, LDL, HDL, TGL as well as HbA1c. Serum blood samples were collected at baseline and discharge, centrifuged within an hour, and stored at −80 °C. The measurement of special parameters MPO and RBP-4 was conducted by commercial enzyme linked immunosorbent assay (human myeloperoxidase-ELISA, Hölzel Diagnostika Abfrontier, Cat. No. LF-EK0134; retinol binding protein-ELISA, Immundiagnostik, Cat. No. KG6110). In addition, AGE and sRAGE levels were measured by ELISA technique (OxiSelect Advanced Glycation End Product (AGE) Competitive ELISA Kit, Cat. No. STA-817; human sRAGE ELISA, Cat. No. RD191116200R). ELISA measurements were conducted in duplicate to ensure quality. For a better and more understandable representation of the AGE ligand–receptor system, AGE activity was formed from the AGE/sRAGE ratio. A decrease in AGE activity describes rehabilitation success by representing the decrease in AGEs versus the increase in protective sRAGE. ## 2.4. Statistical Analysis All statistical analysis was performed using the statistic program GraphPad Prism 9. Pairwise deletion was used for completely randomly distributed missing data. Normal distribution was assessed using the Shapiro–Wilk test. If data were normally distributed, pre–post groups were compared using paired Student´s t-test, otherwise Wilcoxon matched pairs signed rank test was applied. Correlations were assessed using the Spearman´s rank correlation coefficient (r). Results are expressed as mean ± standard error of mean (SEM) or individual values plus mean. In order to analyze the effects of prior physical activity on specific parameters, the patients were divided into two groups based on their daily activities before the rehabilitation (sport+: patients engaged in 30 min sport activity daily, sport−: patients did not engage in 30 min sport activity daily). ## 2.5. Skin Autofluorescence (SAF) Measurement SAF was measured from the inside of the dominant forearm using an AGE reader (DiagnOptics Technologies BV, Groningen, Netherlands) in a non-invasive way. The AGE reader illuminates skin with ultraviolet light and detects the resulting fluorescent light, while simultaneously detecting light reflected from the skin. SAF is determined as the ratio of light intensity in the 420–600 nm wavelength range and the average excitation light intensity in the 300–420 nm range. ## 2.6. Physical Performance Individual physical performance was documented at baseline (T0) and discharge (T1) with the Ergoselect 200 Ergometer (Ergoline GmbH) by the AMEDTEC ECGpro software, according to the manufacturer’s instructions. ## 3.1. Demographic Data At the beginning of the rehabilitation program, data concerning the frequency distribution of the diagnosis from included patients, with a mean age of 58 (±1.11; $76\%$ ($$n = 45$$) males, $24\%$ ($$n = 14$$) females), were collected (Table 1). Myocardial infarction (MI) and percutaneous coronary intervention (PTCA) showed the highest number of patients, followed by diabetes, coronary artery bypass graft (CABG), positive ergometry and others (e.g., peripheral arterial disease, biodegradable stent, Hashimoto-thyroiditis, arterial hypertension, chronic wound healing, drug eluting stents, positive family history for coronary heart disease, positive risk profile). Most patients were taking nonsteroidal anti-inflammatory drug(s) (NSAIDs) (e.g., Aspirin), statins or ß-blockers. A smaller amount took calcium channel blockers and nitrate derivatives. With regard to medication, no significant changes were observed when baseline values were compared with those at discharge. ## 3.2. Physiological Improvements In this study, physiological parameters such as blood pressure, body weight expressed as BMI, and physical performance, were collected. A statistically significant improvement was observed for both RR–systolic ($18.54\%$ reduction) and RR–diastolic ($12.21\%$ reduction) by the inpatient rehabilitation stay (Figure 1a). The examined rehabilitation patients with cardiovascular diseases were overweight with a body mass index of 29.63 ± 0.60 (mean ± SEM). After the 3–4-week rehabilitation stay, patients, although still in the overweight range, showed significantly decreased BMI values of 28.94 ± 0.56 (mean ± SEM) at discharge (Figure 1b). Accordingly, the weight and abdominal girth of the examined rehabilitation patients improved during the rehabilitation (weight at T0: 87.92 ± 2.27 kg, weight at T1: 85.77 ± 2.08 kg (mean ± SEM, $p \leq 0.001$, $$n = 59$$) girth at T0: 104.60 ± 1.64 cm, girth at T1: 102.7 ± 1.67 cm (mean ± SEM, $p \leq 0.001$, $$n = 53$$)). Values for the bicycle ergometer training were improved over the 3-4-week rehabilitation period regarding wattage, from 146.1 ± 5.91 at baseline to 155.0 ± 6.28 (mean ± SEM) ($6.09\%$ improvement) at discharge and in terms of the expected cardiovascular exercise capacity, from 87.89 ± $2.17\%$ to 96.21 ± $2.53\%$ (mean ± SEM) ($9.47\%$ improvement) (Figure 1c,d). ## 3.3. AGEs and sRAGE in CVD Patients Tissue accumulation of AGEs in the skin was measured non-invasively via the AGE Reader. Because AGEs accumulate in tissues (e.g., skin) over a person’s lifetime, it is not surprising that the 3–4 weeks of the inpatient rehabilitation stay could not change these values significantly (at baseline: 2.39 ± 0.06 AU, at discharge: 2.43 ± 0.06 AU (mean ± SEM)). However, measurements of AGEs in serum showed a nearly $7\%$ reduction in the AGE levels from 10.93 ± 0.65 µg/mL at T0 to 10.21 ± 0.61 µg/mL (mean ± SEM) at T1 (Figure 2a). By comparing the concentration of sRAGE at baseline and discharge, an increase from 891.82 ± 44.97 pg/mL to 937.17 ± 43.29 pg/mL (mean ± SEM) could be observed (Figure 2b). ## 3.4. Changes in AGE Activity and the Rehabilitation The AGE activity was formed out of the quotient AGE/sRAGE. The AGE activity showed a significant reduction of approximately $12.15\%$, which can be equated with the rehabilitation success of the included patients (Figure 2c). By further focusing on AGE activity, their AGE activity(changes) (change = AGE activity(discharge)–AGE activity(baseline)) was correlated to AGE activity(baseline). There was a significant mediate negative correlation (r = −0.564), showing that the higher the AGE activity at the start of rehabilitation, the bigger the AGE activity(changes) (T0 versus T1), resulting in a more negative value (Figure 2d). The correlation between AGE activity(changes) and sRAGE(baseline) was not pronounced (Figure 2e). On the other hand, the correlation between the AGE activity(changes) and AGE(baseline) was highly significant (r =−0.535) (Figure 2f). Despite this, a significant correlation between AGE activity(baseline) and AGE activity(discharge) ($r = 0.653$; $p \leq 0.001$) was calculated. ## 3.5. The Effect of Preceding Physical Activity on the Success of Rehabilitation Physical fitness can modify the success of the rehabilitation, and therefore patients were asked for their self-reported daily exercises, conducted prior to rehabilitation. About $66\%$ of the subjects indicated that they performed 30 min of physical activities per day. Because of this reason, we investigated the changes in AGE activity at baseline (T0) and discharge (T1) in patients with/without prior physical activities. It was obvious that non-sporty-active patients already had higher AGE activity levels at the beginning of the rehabilitation than sporty-active patients; however, due to the small evaluable number, this was not significant. AGE activity decreased in the no-sport group significantly following the rehabilitative measures (Figure 2g). A comparison of the serum levels of sRAGE did not show a significant improvement at discharge (Figure 2h). It is of great interest that AGE per se was higher in the no exercise group. Inpatient rehabilitation significantly reduced AGE. Because of the already lower AGE level in the sport group, no improvement could be detected (Figure 2i). ## 3.6. Analysis of Risk Factors of Cardiovascular Diseases Serum glucose concentrations are a continuous risk factor for CVDs. Blood glucose levels in patients included in our study decreased significantly from 110.7 ± 3.10 mg/dL at baseline to 104.2 ± 2.02 mg/dL (mean ± SEM) at discharge (Figure 3a). Several studies have demonstrated that a higher HbA1c level is also associated with an increased risk of cardiovascular diseases and death. In this study, we were able to investigate the impact of the inpatient rehabilitation on HbA1c serum level by showing a significant decrease from 6.71 ± 0.29 (%) at baseline to 6.36 ± 0.19 (%) at discharge (Figure 3b). Although the HbA1c value indicates changes in blood glucose levels over a period of 3–4 months, we were able to detect a significant difference after only 3–4 weeks. However, despite this significance, this is only an indication of improvement, as only $$n = 17$$ patients were studied here, which does not allow for good reliability. This decrease was also accompanied by an improvement in MPO from 254.1 ± 16.68 ng/mL to 221.3 ± 14.94 ng/mL (Figure 3c). A possible correlation between the AGE activity(changes) and the blood glucose(changes) or MPO(changes) was proven. A positive relationship ($r = 0.034$)—meaning that the higher the changes in AGE activity, the higher the changes in blood glucose level—was detected (Figure 3d). Whereas, a negative correlation was shown for MPO (r =−0.02) (Figure 3e). We can schematically summarize our collected data and show the relationship between CVD risk factors and serum levels of AGEs. Higher blood glucose and MPO levels may lead to higher AGE concentration. HbA1c is a result of advanced glycation, but can also act as a precursor for Hb-AGE, contributing to higher AGE levels (Figure 3f). ## 3.7. Lipid Metabolism, RBP-4 and Rehabilitation Important parameters for the lipid metabolism were investigated (Figure 4a). The cholesterol levels of the patients significantly decreased by $19\%$ at discharge (T1). At discharge (T1), the patients showed a $28.55\%$ decline in LDL level, a $4.92\%$ reduction in HDL level, and a $20.01\%$ reduction in TGL level. In the course of the 3–4 weeks of inpatient rehabilitation, the mean serum level of the parameter RBP-4 decreased significantly by $12.01\%$ (Figure 4b). The cartoon in Figure 4c summarizes the relationship between the heightened level of RBP-4 and the increase in lipid metabolism, by a reduction in the good cholesterol HDL and an increase in triglycerides. Respectively, the further effects of those on cardiovascular diseases are depicted. ## 4. Discussion Several studies have shown that AGEs play a crucial role in the aging process as well as the development of tumor metastasis, and they can contribute to the development of CVDs [45]. Falcone et al. [ 2005] demonstrated the inverse correlation between the levels of sRAGE and the degree of atherosclerosis [46]. Ebert [2019] and her group reported that the ratio of AGEs and sRAGE is a more important marker for age-related diseases than each separately [47]. Confirming this work, we formed the quotient of AGE/sRAGE and named this as AGE activity. Our results proofed the finding of a previous study, which demonstrated that changes in lifestyle can lead to an increase in sRAGE serum levels as well as a decrease in AGE levels and AGE activity [48]. Furthermore, our findings were in line with Hangai et al., who described that the skin autofluorescence measurement using the forearm did not match with serum AGEs [49]. Interestingly, our results showed that AGE serum concentration measured at the beginning of rehabilitation (admission/baseline) seems to be very important for rehabilitation outcome, in the context of applying a CVD-specific rehabilitation program. Physical exercise is one of the most effective non-pharmacological treatments to reduce the risk of atherosclerosis and cardiovascular diseases. It has positive effects on the vascular system. Consistent with these studies, our data also clarified the association between physical activity and lower AGE levels, meaning that patients with no exercise activity had higher AGE levels at admission than subjects who exercised daily [50]. Interestingly, we were able to show that in patients who did not exercise and had a higher baseline level of AGE, these levels were significantly reduced at the end of rehabilitation. Earlier findings of various research groups [51,52] demonstrated that the glycation process in vivo results in two different products, the early reversible products (Schiff bases and Amadori adducts) and the advanced glycation end products (AGEs). Glycated hemoglobin (HbA1c), as a result of early glycation, is a precursor for Hb-AGE formation by slow and complex rearrangements. In addition, serum AGE levels were significantly higher in patients with higher HbA1c levels [53]. Studies report a positive relationship between the elevated levels of blood glucose, HbA1c, as well as MPO and the higher levels of AGEs [54,55,56]. Our findings showed an improvement in these parameters after the 3-4-week intensive rehabilitation program. From this, we can also infer that the observed reduction in AGE activity could be regulated by the rehabilitative effect on the above-mentioned parameters’ observations, once again highlighting the effectiveness of the applied rehabilitation process in patients with CVD. On the contrary, we could not show a significant decrease in the CRP level after the 3–4-week rehabilitation stay, being possibly related to the limited CRP value at baseline. The effective rehabilitation exercise program and the dietary change instructed by a dietician may be responsible for the constant improvement in all parameters of lipid metabolism (total cholesterol, LDL, HDL and triglycerides) during the inpatient rehabilitation stay. RBP-4 is considered as an important risk factor for plaque formation in carotids and the development of cardiovascular diseases [57]. A study of Liu Y et al. indicates a context between the severity of coronary complex lesions and RBP-4. This study, conducted among more than 600 patients, shows that RBP-4 is suitable as a predictor for cardiac death [58]. Zabetian-Targhi et al. published that there is a positive relationship between RBP-4 and oxidative stress marker [59]. High RBP-4 increases blood pressure, and absence of RBP-4 decreases blood pressure, meaning that accelerated RBP-4 levels are correlated with the prevalence of hypertonia and myocardial infarction [60]. In patients with movement training (3 days/week) over a period of 12 months, monitored by physical therapists, decreased RBP-4 levels are accompanied by lower triglyceride levels [61]. These results correlate with our findings which show, already, a decrease in RBP-4 after 3–4 weeks of rehabilitation treatment, and indeed the patients underwent dietary measures. A meta-analysis has also demonstrated that cardiac rehabilitation participation is associated with reductions in blood pressure [62]. In addition, the BMI and blood pressure values improved in the rehabilitation patients, in the form of a reduction in the course of rehabilitation, while a mild correlation between BMI and blood pressure was detected. ## 5. Conclusions Our results impressively show that a 3–4-week inpatient rehabilitation stay related to CVD has a positive effect on physiological parameters, serum levels of AGEs, and sRAGE and AGE activity. Furthermore, the specific rehabilitation program resulted in an improvement in cardiovascular risk factors and lipid metabolism, body mass index, and serum levels of RBP-4 in subjects with CVDs. 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--- title: Inhibitory Effects of Loganin on Adipogenesis In Vitro and In Vivo authors: - Hyoju Jeon - Chang-Gun Lee - Hyesoo Jeong - Seong-Hoon Yun - Jeonghyun Kim - Laxmi Prasad Uprety - Kang-Il Oh - Shivani Singh - Jisu Yoo - Eunkuk Park - Seon-Yong Jeong journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003152 doi: 10.3390/ijms24054752 license: CC BY 4.0 --- # Inhibitory Effects of Loganin on Adipogenesis In Vitro and In Vivo ## Abstract Obesity is characterized by the excessive accumulation of mature adipocytes that store surplus energy in the form of lipids. In this study, we investigated the inhibitory effects of loganin on adipogenesis in mouse preadipocyte 3T3-L1 cells and primary cultured adipose-derived stem cells (ADSCs) in vitro and in mice with ovariectomy (OVX)- and high-fat diet (HFD)-induced obesity in vivo. For an in vitro study, loganin was co-incubated during adipogenesis in both 3T3-L1 cells and ADSCs, lipid droplets were evaluated by oil red O staining, and adipogenesis-related factors were assessed by qRT-PCR. For in vivo studies, mouse models of OVX- and HFD-induced obesity were orally administered with loganin, body weight was measured, and hepatic steatosis and development of excessive fat were evaluated by histological analysis. Loganin treatment reduced adipocyte differentiation by accumulating lipid droplets through the downregulation of adipogenesis-related factors, including peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1). Loganin administration prevented weight gain in mouse models of obesity induced by OVX and HFD. Further, loganin inhibited metabolic abnormalities, such as hepatic steatosis and adipocyte enlargement, and increased the serum levels of leptin and insulin in both OVX- and HFD-induced obesity models. These results suggest that loganin is a potential candidate for preventing and treating obesity. ## 1. Introduction Obesity is a crucial health problem worldwide, and it is caused by hormonal abnormalities, genetic factors, and an imbalance between food intake and energy consumption [1]. Body mass index (BMI), calculated by dividing body weight by the square of height, is the most commonly used diagnostic indicator of obesity [2]. According to the World Health Organization (WHO) guidelines, a BMI of 25–30 and > 30 kg/m2 are considered overweight and obese, respectively [3]. In 2016, 1.9 billion and 650 million adults above 18 years of age were reported to be overweight and obese, respectively [4]. Obesity is characterized by the abnormal deposition of fat in the body, leading to metabolic abnormalities, including fatty liver, elevated plasma insulin/leptin levels, and dyslipidemia [5]. Liver steatosis is caused by an increase in liver fat, which can promote inflammatory signaling pathways that trigger oxidative stress in hepatocytes and produce proinflammatory cytokine. This can lead to the development of non-alcoholic steatohepatitis and macrophage infiltration, which cause liver damage [6,7]. Moreover, excessive fat accumulation alters two main endocrine factors: insulin and leptin [8]. Insulin is a hormone secreted from pancreatic β cells when large amounts of energy are consumed. Insulin regulates energy metabolism by converting glucose into fat. In obese individuals, elevated plasma insulin levels have been observed, in which insulin sensitivity is reduced in insulin-targeted organs such as the liver and adipose tissues, which results in excessive insulin production [9]. Excessive differentiated adipocytes trigger excessive fat accumulation, which leads to an increase in the number or the size of adipocytes (hypertrophy), resulting in a high risk of obesity [10,11]. Adipogenesis is a process in which surplus energy is stored in adipocytes in the form of lipids [12]. Adipogenesis is the process of differentiation of mesenchymal stem cells (MSCs) into adipocytes [13]. MSCs are differentiated by a complex cascade of adipocyte-specific transcription factors, such as peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1) [14,15,16]. *These* genes are essential adipogenesis-related markers regulating adipocyte differentiation [15,16]. Excessive differentiated adipocytes trigger immoderate fat accumulation, which leads to an increase in the number of adipocytes (hyperplasia) or the size of adipocytes (hypertrophy), resulting in a high risk of obesity [17]. Despite having a relatively short life in plasma, adipocytokines such as leptin and adiponectin play a crucial role in regulating fat accumulation, which influences insulin sensitivity [18]. Overweightness is generally caused by abnormal eating behavior (i.e., calorie-rich food intake, irregular eating habits, and snacking after a meal), insufficient exercise, and inadequate sleep time [19]. Recently, pharmacological therapies, including liraglutide (suppressing appetite) and orlistat (decreasing fat absorption) for managing and preventing obesity, have seen an increase in patients with obesity. However, some medications have serious adverse effects and long-term safety limitations, such as vomiting, nausea, satiety, and oily evacuation [20]. Medicinal herbs have been widely considered as alternative conventional therapeutics in the treatment and prevention of various diseases, owing to their long-term safety and fewer adverse effects [21]. A study has demonstrated that single bioactive components derived from herbal products have beneficial therapeutic effects as natural medicines [22]. In addition, studies have shown that several plants containing the iridoid glycoside bioactive compound loganin alleviated hepatic steatosis in a non-alcoholic fatty liver disease mouse model [23], exhibit antidiabetic activities in obese diabetic rats [24] and inhibit adipocyte differentiation and proliferation in rat preadipocytes [25]. Further, loganin prevents inflammatory responses in mouse 3T3-L1 preadipocyte cells and in Tyloxapol-induced mice [26] resulting in decreased body weight gain via improved glucolipid metabolism [25]. Although several beneficial effects of loganin are known, the specific anti-obesity effects of loganin on adipogenesis remain unclear. Therefore, this study aimed to investigate the inhibitory effects of loganin in 3T3-L1 mouse preadipocytes and adipose-derived stem cells (ADSCs) in vitro and in ovariectomy (OVX) and high-fat diet (HFD)-induced mice in vivo. ## 2.1. Loganin Inhibits Adipocyte Differentiation in Mouse Preadipocytes and ADSCs We first examined whether loganin inhibits adipogenesis in 3T3-L1 mouse preadipocyte cells. Cells were induced to differentiate into adipocytes and were co-incubated with different concentrations of loganin (2, 5, and 10 μM) for 8 d. After the induction of adipocyte differentiation, mRNA expression levels of adipogenic-related markers such as Pparg and Cebpa for adipogenesis, Plin2 for mature adipocytes, and Fasn and Srebp1 for upstream activator of adipogenesis were examined using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and accumulated lipid droplets were visualized using oil Red O staining. Loganin significantly decreased the mRNA expression levels of Pparg, Cebpa, Plin2, Fasn, and Srebp1 in a dose-dependent manner, and treatment with 10 μM loganin showed the greatest inhibitory effect on adipocyte differentiation (Figure 1A). Loganin treatment decreased the number of oil Red O-positive cells (Figure 1B). Further, the cellular viability test showed that loganin did not affect cellular viability in 3T3-L1 cells (Supplementary Figure S1). These results indicate that loganin prevents adipocyte differentiation by reducing expressions of Pparγ, Cebpa, Plin2, Fasn, and Srebp1. We further confirmed the anti-adipogenic effects of loganin on ADSCs isolated from mouse adipose tissues. ADSCs were induced to differentiate into adipocytes and were co-cultured with loganin (2, 5, and 10 μM) for 8 d. Consistent with the results obtained in the preadipocyte cell line, mRNA expression levels of adipogenic-related markers, including Pparγ, Cebpa, Plin2, Fasn, and Srebp1 were reduced by loganin treatment (Figure 2A), and the number of oil Red O-positive cells was also decreased (Figure 2B). These results suggest that loganin inhibits adipocyte differentiation by downregulating adipogenic-related markers (Pparγ, Cebpa, Plin2, Fasn, and Srebp1) in both 3T3-L1 mouse preadipocytes and ADSCs. ## 2.2. Loganin Prevents OVX- and HFD-Induced Weight gain in Mice To examine the anti-adipogenic effect of loganin in vivo, we used two different animal models of obesity in mice, i.e., OVX- and HFD-induced obesity. We used the 17β-estradiol (E2; 0.03 μg/kg/d) administration as a positive control for anti-obesity, and strontium chloride (SrCl2; 10 mg/kg/d) administration as a negative control. E2 is a well-known reagent for treating menopausal obesity and SrCl2 is an anti-osteoporotic compound used for treating menopause. As expected, OVX-induced obese mice showed weight gain compared to sham-operated mice because of estrogen deficiency, further hepatic steatosis, and adipose tissue enlargement were observed. Administration of 17β-estradiol (E2), the active form of estrogen, restored OVX-induced estrogen deficiency, resulting in the prevention of weight gain, whereas the negative control group administered with the anti-osteoporotic reagent, strontium chloride (SrCl2), did not show any change in body weight compared to that of OVX-induced obese mice (Figure 3A). However, loganin administration prevented OVX-induced weight gain and reduced hepatic steatosis and adipose tissue enlargement (Figure 3A,B). We further investigated the anti-adipogenic effects of loganin in a mouse model of HFD-induced obesity. Six-week-old mice were fed an HFD, and loganin treatment (2 and 10 mg/kg/d) was orally administered for 12 wk. As expected, HFD increased mouse body weight compared to the normal diet (ND) (Figure 4A), and histological analysis of the HFD-induced animals showed hepatic steatosis and adipocyte enlargement (Figure 4B). However, loganin treatment prevented HFD-induced weight gain and reduced hepatic steatosis and adipocyte expansion (Figure 4A,B). Collectively, these results suggest that loganin administration inhibits OVX- and HFD-induced weight gain, hepatic steatosis, and adipocyte enlargement. ## 2.3. Loganin Reduced Plasma Leptin and Insulin Levels in OVX- and HFD-Induced Obese Mice Finally, we evaluated the effects of loganin on the plasma levels of leptin and insulin in OVX- and HFD-induced obese mice. OVX- and HFD-induced obese mice showed a significant increase in plasma leptin and insulin levels compared to those in the sham-operated and ND groups. However, loganin administration resulted in decreased plasma leptin and insulin levels in both OVX- and HFD-induced obese mice (Figure 5). These results indicate that loganin ameliorated the OVX- and HFD-induced increase in plasma leptin and insulin levels in mice, resulting in anti-adipogenic effects in mouse models of obesity in vivo. ## 3. Discussion Adipogenesis promotes fat accumulation in mature adipocytes during preadipocyte differentiation, and excessive fat accumulation leads to overweightness and obesity. Regarding excessive adipogenesis initiating obesity, understanding adipocyte differentiation is important to prevent obesity-related diseases [27]. This study examined the inhibitory effects of loganin in a preadipocyte 3T3-L1 mouse cell line and in primary cultured ADSCs in vitro as well as in OVX- and HFD-induced mice in vivo. Preadipocyte 3T3-L1 cells derived from a mouse embryonic fibroblast cell line have been widely used in biological research on adipogenesis [28]. Further, ADSCs are MSCs isolated from white adipose tissue that are most likely to recapitulate adipogenesis during adipose tissue development [29]. Complete differentiation of adipocytes is represented by the formation of lipid droplets, which are visualized using oil Red O staining [30]. In this study, 3T3-L1 preadipocytes and ADSCs induced for adipocyte differentiation and evaluated using oil Red O staining showed that loganin treatment inhibited the accumulation of lipid droplets and decreased the number of oil Red O-positive cells, indicating reduced adipocyte differentiation. Adipocyte differentiation is regulated by various transcription factors, including Pparγ, Cebpa, Plin2, Fasn, and Srebp1 [14,15,16]. Pparγ is considered to be a master regulator of adipogenesis and plays a central role in maintaining insulin sensitivity [31]. Cebpa binds to the Pparγ promoter and induces the expression of Pparγ isoform 2, thus enhancing adipogenesis [32]. Plin2, also known as an adipose differentiation-related protein, is a cytoplasmic lipid droplet-binding protein required for storing neutral lipids within lipid droplets in mature adipocytes [33,34]. Further, Fasn stimulates the formation of long-chain fatty acids [35,36], and Srebp1 regulates lipogenesis and fatty acid metabolism in adipocytes [37]. In this study, we examined the mRNA expression of adipogenesis-related genes using qRT-PCR. After the induction of adipocyte differentiation, increased expression of Pparγ, Cebpa, Plin2, Fasn, and Srebp1 was observed. However, loganin treatment inhibited the mRNA expression of adipogenic inducible genes in 3T3-L1 stable cells and primary ADSCs. Collectively, the in vitro results suggest that loganin treatment prevents adipocyte differentiation through the decreased accumulation of lipid droplets and downregulation of adipogenesis-related factors. Mouse models of obesity are widely used to investigate fat development induced by HFD and OVX in mice [38,39]. The HFD contains high amounts of calories from fat and is an appropriate method to trigger excessive fat development in an in vivo obesity model [40,41]. OVX-induced obese mice lack estradiol owing to ovary removal and mimic human menopause with increased susceptibility to gain weight [39]. Based on the in vitro results, we confirmed the attenuating effects of loganin on adipogenesis in HFD- and OVX-induced obese mice. Persistent inappropriate weight gain is strongly associated with metabolic abnormalities, such as hepatic steatosis, adipocyte hypertrophy, and hyperlipidemia [42,43,44]. Liver steatosis and adipocyte enlargement are commonly reported symptoms following excessive fat deposition [45]. A recent study suggested that loganin prevented inflammatory-associated diseases by inhibiting hepatic steatosis [46]. Furthermore, excessively elevated insulin levels inhibit hormone-sensitive lipase, an essential enzyme for lipid digestion [47]. Leptin plays a major role in regulating lipid metabolism through changes in food consumption [48]. In this study, loganin treatment inhibited HFD- and OVX-induced weight gain and fat deposition reduced metabolic abnormalities, such as hepatic steatosis and adipocyte expansion, and increased the plasma levels of insulin and leptin. The results indicated that the protective effects of loganin on metabolic abnormalities induced by HFD and OVX are probably due to anti-obesity effects rather than phytoestrogen activity. Our results thus showed that loganin reduced the total body weight along with adipogenic-associated abnormalities in two mouse models of obesity. Collectively, loganin promoted the reduction of adipocyte differentiation and accumulation of lipid droplets in 3T3-L1 preadipocytes and ADSCs and alleviated obesity-related phenotypes induced by OVX and HFD in vivo. ## 4.1. Reagents, Cell Culture and Induction of Mature Adipocytes Loganin was purchased from Chengdu Biopurify Phytochemicals Ltd., (Sichuan, China) and was completely dissolved in deionized water. The mouse fibroblast cell line, 3T3-L1, was obtained from the Korean Cell Line Bank (KCLB No. 10092.1). 3T3-L1 cells were maintained in high-glucose Dulbecco’s modified Eagle’s medium (DMEM; Invitrogen, Carlsbad, CA, USA) containing $10\%$ bovine calf serum (BCS; Invitrogen, Carlsbad, CA, USA) and $1\%$ antibiotic-antimycotic (AA; Invitrogen, Carlsbad, CA, USA). For adipogenic induction, cells (1×106 cells) were seeded in 6-well plates (SPL Life Sciences, Pocheon, Republic of Korea) and maintained until the cells reached $100\%$ confluent. Then, the cells were replaced with DMEM containing $10\%$ fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA), $1\%$ AA, 1 μM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine, and 10 μg/mL insulin for 3 days. The medium was then incubated with DMEM containing $10\%$ FBS, $1\%$ AA, and 10 μg/mL insulin for 5 days. Insulin was changed every 2 days, and loganin was replaced every time the media was switched. ADSCs were isolated using the stromal vascular fraction, as previously described [49]. Briefly, 9-week-old mouse epidydimal adipose tissue was digested with collagenase type II for 1 h. The digestive solution was neutralized with low-glucose DMEM containing $10\%$ FBS, followed by filtration using a 100 μm cell strainer (Corning, NY, USA). The cells were then centrifuged at 2500 rpm for 10 min and maintained in low-glucose DMEM containing $10\%$ FBS and $1\%$ AA. For the adipogenic induction of ADSCs, cells were incubated with Mesencult™ Adipogenic Differentiation Medium (STEMCELL Technologies, Vancouver, BC, Canada) for 8 d. The “Control” indicates non-treated cells, and the “Mock” indicates adipogenic induction medium-treated cells. To examine cellular viability tests, 3T3-L1 cells were incubated with loganin in cultured media for 8 d and cellular viability was assessed using D-Plus™ CCK cell viability kit (Dongin Biotech, Seoul, Republic of Korea) in absorbance at 450 nm by iMark™ Microplate Absorbance Reader (Bio-Rad, Hercules, CA, USA). ## 4.2. Oil Red O Staining The cells were fixed with $4\%$ paraformaldehyde (BIOSESANG, Seongnam, Republic of Korea) for 15 min and then with $70\%$ isopropanol for 1 min. Thereafter, the cells were incubated with oil Red O (Sigma-Aldrich, St. Louis, MO, USA) for 1 h. Representative images were obtained using a light microscope (Leica Microsystems; Wetzlar, Germany). For quantification of oil Red O-positive cells, cells were destained with $100\%$ isopropanol, and absorbance at 490 nm was measured using a microplate reader (Bio-Rad, Hercules, CA, USA). The values were normalized to the “Mock” sample (1.0) and expressed as relative values for the other samples. ## 4.3. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) Total RNA was isolated using the QIAzol Lysis Reagent (QIAGEN, Hilden, Germany), according to the manufacturer’s instructions. RNA was reverse-transcribed using the RevertAid™ H Minus First Strand cDNA synthesis kit (Fermentas, Hanover, NH, USA) under the following conditions: 2 U of Dnase Ⅰ for 30 min at 37 °C, 50 mM EDTA for 10 min at 65 °C, 1:1 ratio of Random Hexamer and Oilgo (dT) 18 primers for 5 min at 65 °C and 10 mM of dNTP mix, 20 U of RNase Inhibitor, and 200 U of RevertAid H Minus Reverse Transcriptase for 5 min at 25 °C, 1 h at 42 °C and 5 min at 70 °C. qRT-PCR was performed using the SYBR Green I qPCR kit (Takara, Shiga, Japan). *The* gene-specific primers used in this study were as follows: forward 5′-GCG GGA ACG CAA CAA CAT C-3′ and reverse 5′-GTC ACT GGT CAA CTC CAG CAC-3′ for mouse Cebpa, forward 5′-AAG ATG TAC CCG TCC GTG TC-3′ and reverse 5′-TGA AGG CAG GCT CGA GTA AC-3′ for mouse Srebp1, forward 5′-GGA AGA CCA CTC GCA TTC CTT-3′ and reverse 5′-GTA ATC AGC AAC CAT TGG GTC-3′ for mouse Pparg, forward 5′-GAC CTT GTG TCC TCC GCT TAT-3′ and reverse 5′-CAA CCG CAA TTT GTG GCT C-3′ for mouse Plin2, forward 5′-GGA GGT GGT GAT AGC CGG TAT-3′ and reverse 5′-TGG GTA ATC CAT AGA GCC CAG-3′ for mouse Fasn, and forward 5′-AGC TGA AGC AAA GGA AGA GTC GGA-3′ and reverse 5′-ACT TGG TTG CTT TGG CGG GAT TAG-3′ for mouse Arbp. Relative mRNA expression levels were normalized to those of mouse Arbp (ribosomal protein large P0, also known as Rplp0) expression, and fold change was determined using the 2−ΔΔCt method. The values presented in this study were expressed using “Mock” as a standard (1.0), while other values were expressed as relative values. ## 4.4. Animal Study All animal experiments performed in this study were approved by the Institutional Animal Care and Use Committee (IACUC) of Ajou University School of Medicine [2022-0064]. Mice were maintained under specific-pathogen-free conditions at the Animal Care Center at Ajou University School of Medicine and provided with standard food pellets (Feedlab Co., Ltd., Hanam, Republic of Korea) and distilled water ad libitum. The OVX- or HFD-induced obese mice were used as previously described [50,51]. For OVX-induced obese mice, sham-operated ($$n = 5$$) and OVX-induced ddY mice ($$n = 25$$) were purchased from Shizuoka Laboratory Center Inc. (Hamamatsu, Japan). OVX-induced obese mice were divided into five groups: OVX only, OVX plus β-estradiol (E2; 0.03 μg/kg/day, Sigma-Aldrich), OVX plus strontium chloride (SrCl2; 10 mg/kg/day, Sigma-Aldrich), OVX plus loganin (2 mg/kg/day), and OVX plus loganin (10 mg/kg/day). For HFD-induced obese mice, 4-week-old mice were divided into four groups ($$n = 5$$ per group): ND, HFD, HFD plus loganin (2 mg/kg/day), and HFD plus loganin (10 mg/kg/day). The total body weights of the mice were measured using a Micro Weighing Scale (CAS Corporation, Yangju, Republic of Korea) after 4, 8, and 12 weeks of the experiment. E2, SrCl2, and loganin were administered through oral gavage. At the end of the experiment, mice were euthanized using CO2, and tissue samples, including liver and fat, were fixed in $4\%$ paraformaldehyde (BIOSESANG, Seongnam, Republic of Korea). ## 4.5. Histological Analysis Formalin-fixed tissue samples were dehydrated and embedded in paraffin. The paraffin blocks were sectioned using a rotary microtome (3 μm; Leica Microsystems, Wetzler, Germany). The tissue slides were stained with hematoxylin and eosin (H&E; SSN Solutions, London, UK). Briefly, the sectioned slides were deparaffinized using xylene and rehydrated using sequentially treated ethanol ($100\%$, $95\%$, and $70\%$). Slides were stained with Harris hematoxylin solution and differentiated using $1\%$ acid alcohol. Bluing was performed using $0.2\%$ ammonia water and counterstained with eosin Y solution. The slides were then dehydrated using sequentially treated ethanol ($70\%$, $95\%$, and $100\%$), cleared with xylene, and mounted using mounting medium (Leica Microsystems, Wetzler, Germany). Slide scanning was performed using an Axioscan Z1 slide scanner (Carl Zeiss). ## 4.6. Plasma Analysis At the end of the experiment, blood samples were obtained from mice using cardiac puncture, collected in EDTA tubes, and stored at −80 °C until use. Plasma leptin and insulin levels were determined using a customized MILLIPLEX® Mouse Adipokine Magnetic Bead Panel (MADKMAG-71K; Millipore, Billerica, MA, USA) and a MAGPIX® multiplex analyzer (Luminex, Austin, TX, USA). ## 4.7. Statistical Analysis Data in bar graphs are expressed as mean ± standard error of the mean (SEM) using GraphPad Prism 9.2.0 software (GraphPad Software, San Diego, CA, USA). Statistical significance was determined using one-way analysis of variance (ANOVA), followed by Tukey’s honest post hoc test using the professional Statistical Package software (SPSS 25.0 for Windows, SPSS Inc., Chicago, IL, USA). ## 5. Conclusions This study revealed the inhibitory effects of loganin on adipogenesis in 3T3-L1 preadipocytes, ADSCs, and on OVX- and HFD-induced obesity models in mice. Loganin treatment decreased adipocyte differentiation and lipid droplet accumulation by reducing the mRNA expression of adipogenesis-related factors. 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--- title: Peroxisomes Are Highly Abundant and Heterogeneous in Human Parotid Glands authors: - Christoph Watermann - Malin Tordis Meyer - Steffen Wagner - Claus Wittekindt - Jens Peter Klussmann - Sueleyman Erguen - Eveline Baumgart-Vogt - Srikanth Karnati journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003153 doi: 10.3390/ijms24054783 license: CC BY 4.0 --- # Peroxisomes Are Highly Abundant and Heterogeneous in Human Parotid Glands ## Abstract The parotid gland is one of the major salivary glands producing a serous secretion, and it plays an essential role in the digestive and immune systems. Knowledge of peroxisomes in the human parotid gland is minimal; furthermore, the peroxisomal compartment and its enzyme composition in the different cell types of the human parotid gland have never been subjected to a detailed investigation. Therefore, we performed a comprehensive analysis of peroxisomes in the human parotid gland’s striated duct and acinar cells. We combined biochemical techniques with various light and electron microscopy techniques to determine the localization of parotid secretory proteins and different peroxisomal marker proteins in parotid gland tissue. Moreover, we analyzed the mRNA of numerous gene encoding proteins localized in peroxisomes using real-time quantitative PCR. The results confirm the presence of peroxisomes in all striated duct and acinar cells of the human parotid gland. Immunofluorescence analyses for various peroxisomal proteins showed a higher abundance and more intense staining in striated duct cells compared to acinar cells. Moreover, human parotid glands comprise high quantities of catalase and other antioxidative enzymes in discrete subcellular regions, suggesting their role in protection against oxidative stress. This study provides the first thorough description of parotid peroxisomes in different parotid cell types of healthy human tissue. ## 1. Introduction Saliva plays an essential role in mastication, speech, protection, deglutition, digestion, excretion, and tissue repair. Salivary glands are exocrine glands that produce and secrete saliva using a system of ducts and acini. Humans have about 800–1000 minor salivary glands and three major paired salivary glands: parotid glands, sublingual glands, and submandibular glands. Of these, the parotid can be described as the largest, bordered anteriorly and medially by the masseter, superiorly by the zygomatic arch, and posteriorly by the sternocleidomastoid. This gland produces a serous fluid that helps with swallowing, chewing, digestion, and phonation [1]. The produced serous secretion comprises rich amylase, sialomucins, sulfomucins, ions, and water along with glycoconjugates that bind to calcium and are responsible for antimicrobial and enzymatic activities in saliva [2]. As the parotid gland has high intrinsic RNase activity, it is particularly challenging to extract intact RNA. We compared different methods to extract intact RNA from murine and human parotid gland tissue without losing the RNA quality [3]. All eukaryotic cells except erythrocytes and spermatozoa include the single membrane-bound organelle called a peroxisome [4]. The shape, size, quantity, and protein content of peroxisomes differ depending on the organism or cell type being studied [5]. The production of cholesterol and plasmalogens, as well as lipid metabolism, are closely related to peroxisomal functions [4]. Furthermore, peroxisomes play a crucial role in the processes of cellular signaling in inflammatory pathologies [5]. Most information on peroxisomes derives from lung, kidney, or liver research. As shown earlier by our workgroup, healthy and malignant tissue of the human parotid salivary gland express peroxisomal proteins differently. The fact that biosynthesis was upregulated while important antioxidant enzymes were downregulated showed that peroxisomes play a pro-tumorigenic role in parotid gland cancers [6]. However, to the best of our knowledge, minimal information is available on the biology of peroxisomes in the different cell types of human parotid glands. The first series of experiments and research on peroxisomes in the human parotid gland were provided by Riva et al. in the late 90s. The authors exploited the power of electron microscopy using the DAB method and showed the cytochemical localization of catalase [7,8]. Subsequently, peroxisomes in rat parotid glands were defined by utilizing an improved DAB method by Graham and Karnovsky [9,10]. The authors that used this improved method observed the sporadic existence of peroxisomes in intercalated duct cells and acinar cells; however, they concluded that the peroxisomes were more frequent in the striated duct cells [9]. Based on these studies, they presented the detailed ultrastructure of excretory ducts in the parotid glands of rats and defined the occurrence of peroxisomes in epithelial cells [11]. Meanwhile, the existence of peroxisomes in the murine parotid gland was confirmed by employing Karnovsky’s DAB method for determining catalase distribution [12]. Tandler and Walter later used a novel method to confirm the existence of peroxisomes in the parotid glands of free-tailed bats [13,14,15]. However, there is still a considerable amount of work to be done in targeting the localization and characterization of peroxisomal proteins. Therefore, this study aimed to characterize and localize peroxisomal proteins and enzymes in the acinar and striated ducts cells of human parotid glands by employing electron- and light-based microscopic techniques combined with molecular analyses. ## 2. Results Peroxisomes are numerous, and their protein content is highly abundant in the human parotid glands; however, there were significant cell-specific differences observed in their numerical abundance and enzyme content in the acinar and striated duct cells. Parotid tissue was identified with parotid specific protein (PSP) staining. Since the human parotid gland was surgically removed, we ascertained the origin of the isolated tissue with regular morphology before labeling it with antibodies against proteins that are located inside peroxisomes. The human parotid gland tissue showed the typical anatomical structure of lobes and lobuli with intralobular adipose tissue (Figure 1A–C) and exhibited a gland structure of pure serous acini (Figure 1B). The duct system consists of intercalated ducts, striated ducts, excretory ducts, and main excretory ducts (Figure 1C). As already described in the literature, PSP binds to the membrane of secretory granules and is therefore suitable for detecting parotid tissue. The parotid tissue, which was used for further experiments, reacted clearly positive to PSP staining (Figure 1A–C) [16]. Images of the tissue at a higher magnification show serous secretory cells and striated duct cells with several large and plentiful secretory granules (Figure 1B,C). We subsequently utilized post-embedding immunocytochemistry and the ultra-small gold technique at electron microscopic levels to examine the subcellular localization of PSP. Figure 1D–F demonstrates that gold particles are selectively detected in the secretory granules, indicating that the PSP antibody is highly specific. Organelles of other cells, including mitochondria, were negative. The results of the Psp mRNA expression analysis supported the morphological findings. When compared to Gapdh in Figure 1G, the Psp mRNA expression in the human parotid gland was substantially higher. Western blot analysis for PSP yielded a specific band at 28 kDa, as seen in Figure 1H. These results suggest that PSP is an exclusive parotid-specific marker protein and is highly abundant in secretory granules. ## 2.1. Peroxisomes Are Highly Abundant in the Human Parotid Gland We determined the peroxisomal compartment’s distribution pattern in the human parotid gland using peroxisome-specific antibodies. Interestingly, the peroxisomes in the human parotid gland are highly abundant (Figure 2A–F). Immunofluorescence analyses for PEX13p and PEX14p showed a punctate pattern that is typical of peroxisome staining. However, clear visible differences were observed between the acinar cells (Figure 2B,E) and striated duct cells (Figure 2C,F). Acinar cells displayed smaller amounts of stained peroxisomal proteins, as shown by labeling with PEX13p and PEX14p, compared to the striated duct cells (Figure 2B,C,E,F). Both proteins were strongly labeled with peroxisomes in the striated ducts (Figure 2C–F). In light of this, PEX13p and PEX14p Western blot analysis supported the morphological findings, indicating the abundance of both proteins in the human parotid gland (Figure 2I). Further, qRT-PCR analysis for most mRNAs coding for peroxisomal biogenesis proteins (Pex3, Pex5, Pex7, Pex12, Pex13, Pex16, Pex19) and peroxisomal proliferation proteins (Pex11α, Pex11β) revealed significantly higher expression levels compared to Gapdh (all $p \leq 0.0128$) in human parotid glands. In contrast, Pex6, Pex10, and Pex14 showed lower expression levels than Gapdh (Figure 2G,H). ## 2.2. Peroxisomal β-Oxidation Enzymes Are Expressed at High Levels in the Human Parotid Gland We also investigated the peroxisomal β-oxidation enzymes in the human parotid gland. In particular, peroxisomal thiolase (ACAA1), which is involved in the last reaction of peroxisomal β-oxidation, demonstrated a typical peroxisomal staining similar to the peroxisomal biogenesis proteins (Figure 3A–C). Striated duct cells showed more intense labeling of peroxisomal proteins than acinar cells (Figure 3A–C). The qRT-PCR analysis of mRNAs for lipid transporters of the distinct ATP binding cassette subfamily D (Abcd1 and Abcd3) also showed significantly higher expression levels in the human parotid gland in comparison to Gapdh (Figure 3D). Furthermore, the human parotid gland showed significantly higher expression of all β-oxidation enzymes (Acox1, Acox2, Mfp1, Mfp2, and Acaa1) except for Acyl-CoA oxidase 3 (Acox3), which was not expressed at a significantly higher level compared to Gapdh (Figure 3E). Of all the peroxisomal β-oxidation enzymes tested, the mRNA encoding for the protein Mfp2 showed the highest expression in comparison to Gapdh (Figure 3E). Western blot examination confirmed the IF and qRT-PCR findings by demonstrating the presence of peroxisomal thiolase (ACAA1) in the human parotid gland (Figure 3F). ## 2.3. Plasmalogen Synthesizing Enzymes Are Expressed at Significantly High Levels in Human Parotid Glands Glycerone-phosphate O-acyl transferase (Gnpat) and alkylglycerone phosphate synthase (Agps) had significantly higher levels of expression in human parotid glands than Gapdh, according to qRT-PCR data (Figure 4A). Furthermore, compared to GAPDH, the AGPS Western blot analysis showed a considerably increased quantity of this plasmalogen-producing enzyme (Figure 4C). ## 2.4. Cholesterol Synthesizing Enzymes Were Expressed Significantly Higher in the Human Parotid Glands All cholesterol synthesizing enzymes were expressed at high levels in the parotid gland (Figure 4B). The enzyme HMG-CoA reductase (Hmgcr), which is localized in both compartments (peroxisomes and endoplasmic reticulum), has considerably higher levels of mRNA expression in the human parotid gland than Gapdh does [16,17]. In addition, the expression of farnesyl diphosphate synthase (Fsps), phosphomevalonate kinase (Pmvk), and mevalonate 5-disphosphate decarboxylase (Mvd), which are also found in peroxisomes, were also expressed noticeably higher in contrast to Gapdh (Figure 4B). It was also shown that the human parotid gland has elevated levels of 3-hydroxy-3-methylglutaryl-CoA synthase (Hmgcs) and iso-pentenyl diphosphate isomerase (Idi). Human parotid gland expression of the mRNA encoding the ER enzyme squalene synthase (Sqs) was similarly found to be substantially higher than that of Gapdh. ## 2.5. Peroxisomal Antioxidative Enzymes Were Detected in the Human Parotid Gland Peroxisomal catalase staining revealed the typical punctate distribution with numerous large peroxisomes in acinar and striated duct cells of the human parotid gland (Figure 5A–C). We used a modified protocol based on the alkaline DAB method, which allowed us to detect the peroxisomes in the acinar and striated duct cells of the human parotid gland (Figure 5D–I) [18]. The ultrastructure of acinus cells showed a well-developed rough endoplasmic reticulum (rER), mitochondria, and nuclei with euchromatin. The mitochondria were in physical closeness to the nucleus and rER (Figure 5D–H). Peroxisomes were often closely associated with mitochondria and rER (Figure 5E,F,H). We investigated the localization of the catalase protein using post-embedding immunocytochemistry with ultra-small nanogold in addition to the localization of catalase activity at the electron microscopic level. Ultra-small nanogold particles were only found in the peroxisomal matrix of human acinar and striated duct cells, as illustrated in Figure 5I. The nuclei, mitochondria, and other cell organelles were not labeled. Negative controls using the PAG or ultra-nano gold technique on LR white sections revealed relatively few randomly arranged nanogold particles. The peroxisomes had a round shape and showed the typical single membrane-bound border with a distribution pattern next to mitochondria and the nucleus (Figure 5E,F,H,I). The parotid glands also contain antioxidative enzymes from various subcellular compartments in addition to catalase to defend against oxidative damage. In comparison to Gapdh, the human parotid gland revealed a significantly increased expression of mRNAs encoding for peroxisomal antioxidative enzymes, such as peroxiredoxin 1 (Prdx1), glutathione peroxidase (Gpx), and superoxide dismutase 1 [14]. The Western blot analysis for CAT and SOD1 revealed the abundance of these peroxisomal antioxidative enzymes in the human parotid gland (Figure 5K). ## 2.6. Antioxidative Enzymes of Different Cell Compartments Were Also Abundant in Human Parotid Glands The mitochondrial superoxide dismutase 2 (SOD2) was detected via immunofluorescence staining and showed a typical localization pattern of the mitochondria in the acinar and striated duct cells (Figure 6A–C). We found clear and robust differences in the number, shape, and morphology of mitochondria between the acini and the striated ducts of human parotid glands. The SOD2 staining showed that the mitochondria were less numerous and displayed a round pattern in the acini compared to the more numerous and elongated form in striated duct cells (Figure 6A–C and Figure 7A–D). Most SOD2-labeled mitochondria were detected in the basal portion of the striated duct epithelial cells and significantly less at the lateral sides and apical portion of the cells (not shown). Strong SOD2 labeling, on the other hand, revealed elongated and tubular mitochondria with extensive network formation throughout the striated duct cells of the parotid gland (not shown). SOD2 is a crucial superoxide radical scavenger that transforms superoxide radicals into less harmful H2O2 in the mitochondrial matrix (Figure 6C). Interestingly, the qRT-PCR analysis of mRNAs encoding for Sod2 and Trx2 showed a significantly higher expression than Gapdh (Figure 6D). The distribution of different thioredoxin isoenzymes suggests that human parotid gland cells also appear to contain a specialized set of antioxidant enzymes in addition to Sod2. Trx2 was more highly expressed in comparison to Trx1 and glutathione reductase (Gr) in the human parotid gland (Figure 6D). Western blot analysis of antioxidative enzymes showed the abundance of SOD2 and GR in agreement with the qRT-PCR analyses (Figure 6E). ## 2.7. Post-Embedding Immunoelectron Microscopy of SOD2 Localization We chose to investigate the subcellular localization of the SOD2 protein by post-embedding immunocytochemistry of LR white ultrathin cryosections using ultra-small gold-labeled Fab fragments and silver intensification as a secondary detection method in order to achieve the highest sensitivity labeling for SOD2. Our results showed that the ultra-small gold particles used to visualize SOD2 were explicitly and exclusively confined to mitochondria in human acinar and striated duct cells (Figure 7A–D). In immunostainings using SOD2 antigen-specific antibodies, we did not find any gold particles in any other cell compartments. ## 2.8. Peroxisome Proliferator-Activated Receptors (PPARs) Are Highly Expressed in the Parotid Gland It is well known that several peroxisomal proteins involved in lipid metabolism and oxidative stress and the genes encoding for them are regulated by the peroxisome proliferator-activated receptors (PPARs). There are three family members of the PPARs: Pparα, Pparβ, and Pparγ. Pparα was expressed significantly higher in the human parotid gland, whereas Pparγ was expressed significantly lower compared to Gapdh. Furthermore, the expression level of Pparβ did not show any significant differences compared to Gapdh (Figure 8). ## 3. Discussion The parotid gland is an organ that has an important role in the immune and digestive systems. Salivary glands secrete the necessary proteins that initiate the digestion process and provide tissue lubrication in the oral cavity, and they play a vital role in fighting infections and oxidative stress [19,20,21,22]. A plethora of work has been conducted on the cell biology of the parotid gland and the proteome of saliva [23,24,25]. Recent studies have shown that oxidative stress accompanies parotid gland tumors, suggesting that it plays an important part in the pathogenesis of parotid gland tumors [21]. Peroxisomes harbor a set of antioxidative enzymes, and they are a vital player in the degradation of nitrogen and reactive oxygen species [5]. However, to the best of our knowledge, no significant work is available yet that explains the potential role of peroxisomes and their distribution in different cell types of healthy human parotid glands. Therefore, we explored the role of antioxidative enzymes, peroxisomes, and metabolizing enzymes in the different subcellular sections by using light-, electron-, and immunofluorescence microscopy. The results confirmed the presence of peroxisomes in all cell types of the human parotid gland. It was also shown that there is a substantial difference in the abundance of peroxisomal proteins in acinar cells compared to striated duct cells. Human parotid glands contain high quantities of catalase and other antioxidative enzymes in distinct subcellular sections as well as mRNAs encoding for multifunctional protein 2 and Acyl-CoA oxidase 1. ## 3.1. Marker Proteins for the Correct Identification of the Parotid Gland We utilized PSP to categorize the isolated tissue and detected this protein in the parotid gland by using post-embedding immunocytochemistry. The patterns of PSP staining and the respective protein expressions are equivalent to the data provided by Bingle et al., which confirms that parotid tissue was isolated [26]. Moreover, the authors have shown that PSP is an excellent marker to distinguish parotid tissue from surrounding tissue due to its different expression patterns in various tissues and glands [26]. Despite this, the exact role and abundance of PSP is still unknown [26]. ## 3.2. Peroxisomes in the Parotid Gland Electron microscopy was initially used to identify peroxisomes utilizing the cytochemical localization of catalase activity in the parotid glands of humans, mice, and rats [7,8,9,11,12]. These works confirmed the higher number of peroxisomes in the excretory and striated ducts of parotid glands. Few peroxisomes were found in the cells of intercalated and acinar ducts. Grant et al. showed immunofluorescence staining of PEX14p in human submandibular glands [27]. The location of peroxisomal enzymes and the gene expression-based profile of the proteins involved in peroxisomal biogenesis were not specifically covered in the literature. The best peroxisomal generator protein, PEX14p, is evenly distributed throughout the parotid gland [4,28,29]. In addition to PEX14p, the human parotid gland has many metabolic and peroxisomal biogenesis proteins, as well as antioxidative enzymes. This confirms the importance of peroxisomes in lipid metabolism and their role in the reduction of oxidative stress. The mRNAs encoding the PEX11α, -β, and -γ proteins that are involved in the peroxisomal proliferation are also present in the human parotid gland [30,31,32]. The peroxisome count and the respective morphological structure rely on metabolic need and its cell-specific functions [33,34]. ## 3.3. In the Human Parotid Gland, Peroxisomal ß-Oxidation, Cholesterol Production, and Plasmalogen Synthesis Enzymes Are Highly Expressed Degradation of bioactive lipids is assisted by peroxisomal β-oxidation. Eicosanoids, for instance, play a role in the production of polyunsaturated fatty acids and the process of inflammation [35]. The prevalence of peroxisomal thiolase in striated duct and acinar cells must be discussed. The rate-limiting enzymes of pathway 1 of the peroxisomal β-oxidation are peroxisomal enzymes, such as acyl-CoA oxidase 1–3 (ACOX). This helps to regulate the substrate flux by using the β-oxidation chain [36]. The human parotid gland has strongly expressed mRNAs for the distinct peroxisomal β-oxidation pathway 1 (Mfp1) and peroxisomal β-oxidation pathway 2 (Mfp2). The metabolism of straight-chain substrates is the primary focus of the MFP1 enzyme, but MFP2 regulates a sizable portion of the substrates for peroxisomal β-oxidation [37]. It is also worth mentioning that the abundance of such enzymes can guard the epithelium against proinflammatory eicosanoids. The high involvement of ABCD3 in the human parotid gland shows that the transporter facilitates an ingress of the branch-like long-chain unsaturated and saturated substrate into the peroxisomes [38]. However, the precise function of peroxisomal β-oxidation in the lipid-transport and homeostasis has not yet been investigated. Peroxisomal β-oxidation can provide the acetyl-CoA units to generate lipids such as plasmalogens or cholesterol precursors [39]. The lipid synthesizing enzymes present in the peroxisomes might play a vital role in the parotid gland. For example, AGPS, which is abundant in the parotid gland, is involved in the synthesis of ether lipids. Ether lipids are known to trap the reactive oxygen species (ROS) (Karnati and Baumgart-Vogt, 2008); therefore, peroxisomes in the parotid gland might help against oxidative damage. Plasmalogens, the largest class of ether lipids, promote the formation of biologically active lipids for cellular signaling [40]. Remarkably, the abundance of lysoplasmalogens is directly linked with the electrophysiological instabilities in myocytes that repress Na+–K+-ATPase in the renal cells [41]. The striated duct cells contain Na+–K+-ATPase in the basolateral and lateral part of the epithelial cells; however, the function of plasmalogens in striated duct cells is so far unidentified. Cholesterol is also a crucial lipid and a mandatory element of bile acids, steroid hormones, and oxysterols [42]. Like other peripheral tissues, the parotid gland uses cholesterol for cellular growth, as was found in rats [43] and mice [44]. It is worth noting that the peroxisomal enzymes can condense acetyl-CoA, which is derived from long-chain fatty acid oxidation, into farnesyl diphosphate (FPP). The reactions of FPP and mevalonate are exclusively peroxisomal except for the reaction of HMG-CoA reductase [45]. The mRNAs of all proteins involved in the synthesis of cholesterol are found to be abundant in the parotid glands of humans, which can affect cholesterol metabolism. In fact, diabetes mellitus and parotid cholesterol metabolism are linked, as evidenced by the discovery of asymptomatic parotid gland enlargement in diabetic rats [46]. More research is needed to determine how low insulin levels specifically affect parotid cholesterol metabolism. High concentrations of antioxidative enzymes can be found in several subcellular compartments of the human parotid gland. Saliva is comprised of antioxidants with special characteristics to protect against oxidative stress [22]. Previous observations have also highlighted that hyposalivation produces oxidative stress by harming the salivary gland’s structure [47,48]. In this respect, it is essential to highlight that the parotid gland possesses peroxisomal enzymes and several other antioxidative catalysts that detoxify H2O2 produced by peroxisomal oxidases [28]. The striated duct cells within the human parotid gland possess an excessive amount of mitochondrial SOD2, an essential scavenging catalyst that transforms superoxide radicles created by the mitochondrial respiratory chain into less toxic H2O2. Several studies have already shown that ROS derived from mitochondrial production grows with age whereas the body’s antioxidative potential decreases [49]. Therefore, the accumulation of ROS becomes harmful for phospholipids and the cell membrane, which is the primary cause of cellular dysfunction [50]. It is worth mentioning that the human parotid gland possesses antioxidant enzymes that are cleared from the thioredoxin isoenzyme distribution. Intriguingly, mRNAs encoding TRX1, certain PEX genes, and cytoplasmic GR were expressed significantly less in parotid gland tissue. It seems that decreasing the antioxidative potential of saliva can increase the vulnerability of the salivary gland to oxidative destruction and maximize the oxidative stress that is related to oral maladies (dental caries, burning mouth syndrome, and oral inflammatory infections like gingivitis, periodontitis, oral mucosa ulceration, and candidiasis) [51]. ## 3.4. PPARs Are Expressed at a Significantly High Level in the Human Parotid Gland PPARs play vital roles in glucose metabolism, lipid metabolism, aging, stress, and producing transcription factors [52,53,54]. PPARα is highly expressed within the parotid gland of humans, which may explain the peroxisomal compartment induction. It has already been shown that PPARγ also regulates genes for PEX11, a large number of peroxisomal β-oxidation enzymes, and ABCD transporters by attaching to the PPARs’ responsive regions (PPRE) [34,54,55]. Most of the research on the PPARs’ role in parotid tumors has just recently been published. PPARγ upgrades Sjögren’s syndrome, the over-expressive regulation of cytokines within the peripheral blood or salivary gland, in non-obese diabetic mice [56]. PPARα and PPARγ could inhibit IL-1β-made NO growth in cultured cells of the lacrimal gland acini, proposing that PPARs might be a beneficial therapy target for avoiding NO-mediated gland destruction. Despite this, the PPARα and PPARγ effects on the development of salivary gland dysfunction are not apparent. ## 4.1. Surgical Removal and Fixation of the Human Parotid Glands The human parotid tissue was removed during surgical operations on benign parotid gland tumors following the standard operating procedures. Pathologists examined the samples at the Institute for Pathology of the Justus Liebig University Giessen, Germany. Informed patient consent was obtained from all individual participants included in this study. We collected tissue samples during surgery performed on the parotid gland. The obtained tissue was divided. One part was fixed with $4\%$ PFA in PIPES buffer with $2\%$ saccharose and $0.05\%$ glutaraldehyde at pH 7.4 for electron microscopy, another part was snap-frozen in liquid nitrogen for Western blotting, and the last part of the parotid tissue was either immersed in RNA later, with subsequent freezing, or immersed in $4\%$ PFA in PBS at pH 7.4 and kept at 4 °C for paraffin embedding. The ethical review committee of the Justus–Liebig University Giessen approved removing and examining the human tissue (AZ $\frac{95}{15}$, 25 June 2015). All procedures performed in studies involving human participants followed the ethical standards of the institutional and national research committee and the 1964 Helsinki declaration and its later amendments or comparable ethical standards. ## 4.2. Paraffin Embedding, Sectioning, and Immunofluorescence It was previously documented in detail how the tissues were sectioned, paraffin embedded, and then used for antigen retrieval and immunofluorescence [4,28,29]. To read more about the primary and secondary antibodies used to incubate the sections with antibodies against peroxisomal, mitochondrial, and other proteins, see Table 1. In immunofluorescence preparations of paraffin slices of different tissues, all antibodies against peroxisomal proteins had already undergone testing for their specificities (lung [28], brain [57], and testes [58]). The sections were mounted in Mowiol 4.88 with N-propyl gallate in a 3:1 ratio after being counterstained with TOTO-3 iodide to detect nuclear morphology. Parallel negative controls incubated without primary antibodies. Using a Leica TCS SP5 confocal laser scanning microscope with a 63× objective and the “Airy 1” setting, the immunofluorescence preparations were analyzed. ## 4.3. Fixation and Embedding for Electron Microscopy Fresh human tissue was placed into a $4\%$ PFA fixative solution in a 0.1 M sodium cacodylate buffer with $2\%$ sucrose at 4 °C. The embedding was performed with Epon or LR White following the manufacturer’s instructions and placed in a vacuum exsiccator to set. Afterward, the tissue was cut into sections using a thin razor blade. ## 4.4. Cytochemical Localization of Catalase Activity with the Alkaline DAB Method The cytochemical localization of catalase activity with the alkaline DAB-method in human parotid glands was performed as previously described [28]. Briefly, the human parotid gland slices were incubated with an alkaline DAB medium [18] containing $0.2\%$ 3,3′-diaminobenzidine (DAB, Sigma, Steinheim, German), 0.15 % H2O2, and 0.01 M Teorell-Stenhagen buffer at pH 10.5. For the best catalase reaction, the reaction was conducted for two hours at 45 °C in a shaking water bath. The sections were then rinsed three times in 0.1 M cacodylate buffer with a pH of 7.4. The osmicated sections were dehydrated in a succession of increasing concentrations of ethanol solutions before being embedded in epoxy resin 812 (Agar, Essex, England). The trimming of the blocks was done with a diamond trimmer (Reichert TM 60, Austria) and the sectioning with a Leica Ultracut E Ultramicrotome (Leica, Nussloch, Germany). The ultrathin slides were collected on nickel grids covered with formvar, and contrasting was done using lead citrate for 45 s and uranyl acetate for two minutes. A transmission electron microscope, model LEO 906, was used for the study (LEO Electron Microscopy, Oberkochen, Germany). ## 4.5. Post-Embedding Immunoelectron Microscopy According to Newman et al. [ 59], another portion of the previously fixed wet parotid sections was directly dehydrated after being exsiccated in $4\%$ PFA-fixative and implanted in medium grade LR White resin (LR White Resin, Berkshire, England). As previously mentioned, slides were collected on formvar-coated nickel grids after ultrathin sectioning (80 nm) was completed. Blocking was performed with $1\%$ bovine serum albumin (BSA) dissolved in a tris-buffered saline solution (TBS) at pH 7.4 for 30 min to prevent unspecific binding. The sections were treated with a rabbit anti-mouse catalase antibody (1:4000 in $0.1\%$ BSA in TBS; a gift from Denis Crane, Table 2) overnight in a wet chamber. The following day, the sections underwent washing with drops of $0.1\%$ BSA in TBS twelve times. The washed grids were incubated with a protein A-gold complex (PAG, gold particle size 15 nm) diluted with $0.1\%$ BSA in TBS (1:75) [60]. The next step was distilled water washing, then air drying. Uranyl acetate was used for the contrasting for two minutes, followed by lead citrate for 45 s. Other ultrathin sections were used as the negative control, which were also treated with non-specific rabbit IgG and placed on grids. In contrast to the other sections, the negative control was followed by the protein A-gold complex alone without a primary antibody. Subsequently, a LEO 906 transmission electron microscope was used for the examination (LEO Electron Microscopy, Oberkochen, Germany). ## 4.6. Homogenization of Human Parotid Glands to Obtain Tissue Lysates for Western Blotting Snap-frozen human parotid glands were cut into small pieces, and the tissue was homogenized in a buffer containing 0.25 M sucrose and 5 mM MOPS (pH 7.4), 1 mM EDTA, $0.1\%$ ethanol, 0.2 mM DTT, 1 mM aminocaproic acid, and 100 µL cocktail of protease inhibitors (#39102, Serva, Germany). The tissue and homogenization buffer were used over an ice bath and treated with a single stroke of a Potter-Elvehjem homogenizer (B. Braun Biotech International, Melsungen, Germany) for 60 s at 1000 rpm. Centrifugation was done at 2500× g for 20 min at 4 °C to sediment connective tissue, nuclei, and giant mitochondria. The protein concentration was measured with the BCA Protein Assay Kit (Pierce, Thermo Fisher Scientific, Langenselbold, Germany) according to the manufacturer’s instructions using an Infinite M200 PRO NanoQuant plate reader (Tecan Group, Maennedorf, Switzerland) for measurement. ## 4.7. Western Blot Analysis The total proteins of the human parotid glands (40 µg) were separated on $10\%$ resolving gels using the sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The SDS-PAGE was done using a Mini Protean *Tetra electrophoresis* module assembly and a Power Pac Basic (BioRad, Dreieich, Germany). Semi-dry blotting was used to transfer the proteins for 50 min at 10 V while utilizing a Trans-Blot Semi-Dry (BioRad, Dreieich, Germany) and a Protran nitrocellulose membrane (Whatman, Dassel, Germany). The membrane was blocked with $5\%$ fat-free milk powder (Applichem, Darmstadt, Germany) in TBS plus $0.5\%$ Tween 20 (Applichem, Darmstadt, Germany) (TBST) for 1 hr at RT. The primary antibodies were diluted in the blocking solution (exact dilution, see Table 1) and incubated overnight at 4 °C. After the incubation, washing of the membrane was performed with TBST (5 min) and TBS (2 × 5 min), and the secondary antibody (for dilution, see Table 1) was put on for 1 hr in RT diluted in $0.5\%$ BSA in TBST. After the washing step, the detection of the immunoreactive bands was done using the Immun-Star WesternC Chemiluminescent Kit (BioRad, Dreieich, Germany) and the ChemiDoc XRS system (BioRad, Dreieich, Germany) for visualization. ImageLab Version 3.0 (BioRad, Dreieich, Germany) was used for image processing and analysis. The membranes were stripped with a 25 mM glycine and $10\%$ SDS solution followed by a 100 mM sodium hydroxide and $10\%$ SDS solution (15 min each) with subsequent reprobing. ## 4.8. RNA Isolation For RNA isolation, the fresh human tissue was immersed in RNAlater and snap-frozen in liquid nitrogen. The tissue samples were stored at −80 °C before further use. For homogenization of the tissue, a TissueLyser LT (Qiagen, Hilden, Germany) was used. Different methods for RNA isolation were already tested to achieve the best possible RNA quality [3]. Following the manufacturer’s instructions, the subsequent RNA isolation was carried out using the RNeasy Mini Kit (Qiagen, Hilden, Germany). The Agilent 2100 Bioanalyzer system and the Agilent RNA 6000 Nano Kit were used to confirm the RNA quality and concentration (Agilent Technologies, Santa Clara, CA, USA). ## 4.9. cDNA-Synthesis The High-Capacity RNA-to-cDNA Kit (Applied Biosystems, Weiterstadt, Germany) was used for reverse transcription according to the manufacturer’s instructions together with a C1000 Thermal Cycler PCR system (BioRad, Dreieich, Germany). ## 4.10. Quantitative Reverse Transcriptase-Polymerase Chain Reaction (qRT-PCR) The Primer Quest Tool (http://eu.idtdna.com/Primerquest/Home/Index accessed on 20 May 2020) was used to design the primers. Eurofins MWG Operon received the order for the primers. Table 2 contains a list of all the primers used. The StepOnePlus Real-Time PCR System (Life Technologies, Darmstadt, Germany) and SYBR Select Master Mix Kit (Life Technologies, Darmstadt, Germany) were used to perform qPCR in accordance with the manufacturer’s instructions. The PCR was conducted using a primer concentration of 5 pmol/L. Program used: 45 cycles of denaturation at 95 °C for 15 s, annealing at 60 °C for 60 s, and extension at 7 °C for 1 min. ## 4.11. Statistical Analysis For the statistical analysis of the different mRNA expression levels, normalized values were used compared to a stable housekeeping reference gene. A Kolmogorov-Smirnov test was used for the normal distribution of the samples. The values are expressed as means ± SEM using the total RNA from human ($$n = 3$$) parotid gland samples. The difference in expression between the housekeeping gene and the target genes was evaluated using a Student’s t-test for unpaired samples. 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--- title: Heterochronic Parabiosis Causes Dacryoadenitis in Young Lacrimal Glands authors: - Kaitlin K. Scholand - Alexis F. Mack - Gary U. Guzman - Michael E. Maniskas - Ritu Sampige - Gowthaman Govindarajan - Louise D. McCullough - Cintia S. de Paiva journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003158 doi: 10.3390/ijms24054897 license: CC BY 4.0 --- # Heterochronic Parabiosis Causes Dacryoadenitis in Young Lacrimal Glands ## Abstract Aging is associated with inflammation and oxidative stress in the lacrimal gland (LG). We investigated if heterochronic parabiosis of mice could modulate age-related LG alterations. In both males and females, there were significant increases in total immune infiltration in isochronic aged LGs compared to that in isochronic young LGs. Male heterochronic young LGs were significantly more infiltrated compared to male isochronic young LGs. While both females and males had significant increases in inflammatory and B-cell-related transcripts in isochronic and heterochronic aged LGs compared to levels isochronic and heterochronic young LGs, females had a greater fold expression of some of these transcripts than males. Through flow cytometry, specific subsets of B cells were increased in the male heterochronic aged LGs compared to those in male isochronic aged LGs. Our results indicate that serum soluble factors from young mice were not enough to reverse inflammation and infiltrating immune cells in aged tissues and that there were specific sex-related differences in parabiosis treatment. This suggests that age-related changes in the LG microenvironment/architecture participate in perpetuating inflammation, which is not reversible by exposure to youthful systemic factors. In contrast, male young heterochronic LGs were significantly worse than their isochronic counterparts, suggesting that aged soluble factors can enhance inflammation in the young host. Therapies that aim at improving cellular health may have a stronger impact on improving inflammation and cellular inflammation in LGs than parabiosis. ## 1. Introduction Aging leads to an increased risk of the development of many pathologies, including the development of dry eye disease, an ocular surface disorder [1]. Dry eye disease includes the elevation of CD4+ T cells in the conjunctiva, higher ocular surface inflammation, a decline in conjunctival goblet cell density, and disruption of the corneal barrier [2]. Dry eye is more frequent in females than males, but both sexes are affected [3]. Aging affects both the structure and function of the lacrimal gland, the producer of the aqueous layer in the tear film [4,5]. These glands suffer many age-related alterations, such as atrophy, inflammation, and fibrosis [6]. We and others have previously reported an increase in infiltrating mononuclear cells and the disruption of healthy cellular components, such as acinar cells, in aged lacrimal glands [7,8,9]. These infiltrating mononuclear cells are dispersed through the parenchyma of the gland but in many cases accumulate, forming foci of lymphocytes that can be quantified in histological sections by calculating the focus score, a measurement of total gland infiltration [10]. The enhanced infiltration of lymphocytic cells, including CD4+ T cells, B cells, and CD4+Foxp3+ cells is seen with aging [2,4,11]. In addition, the aged lacrimal gland exhibits a decrease in peroxidase secretion and a reduction in afferent and efferent nerve function [4,5]. We have previously characterized the cytokine milieu of aged lacrimal glands and observed a significant increase in B-and-T-cell-related cytokines [12]. These include cytokines that have been implicated in lymphocyte influx [8], such as Il1b and Tnf as broad inflammatory markers and Ciita (Class II major histocompatibility complex transactivator) and cathepsin S (Ctss), which are involved in antigen-presentation and MHC processing [13,14,15,16]. Furthermore, interferon-γ, secreted by activated NK and CD4+ T cells, can cause glandular apoptosis [17,18,19]. B cells are a specialized type of lymphocyte that can be divided into subsets based on extracellular and intracellular markers and have many distinct functions. For example, marginal zone-like B (MZB) cells are innate lymphocytes that can mount T cell-independent responses [20]. There are several markers associated with B cells, including Cxcl13 and Cxcl9, chemokines involved in B cell migration and germinal center formation [21,22]. Parabiosis is a method first developed in 1864 to study the effect of a shared circulatory system [23]. Since then, it has been modified to reduce pain and infection in the animals but always involves surgically joining two animals, allowing for the development of a shared microvasculature between them, creating a shared chimeric circulation [24]. From its invention, parabiosis has been used to identify soluble factors that impact diseases, such as cancer, diabetes, hypertension, and obesity, as well as biological phenomena, such as stem cell differentiation and tissue regeneration, and factors involved in the aging process [25]. In studies of aging, heterochronic parabiosis involves pairing two mice together of different ages, while isochronic parabiosis involves pairing mice of the same age [26]. Parabiotic studies have increased since their revival in 2005 when parabiosis was used to investigate the aging of somatic stem cells [27]. However, few studies have investigated the potential effects of parabiosis and shared circulation on the eye. Hamrah and colleagues used parabiosis to study the turnover rate of bone marrow-derived cells in the cornea [28], and Wieghofer and associates used parabiosis to map myeloid populations in compartments of the eye [29]. In the retina, Heuss et al. made use of parabiosis to study the contribution of circulating mononuclear cells to an optic nerve injury [30]. Finally, Li Rong used parabiosis to investigate the mechanism of retinal aging [31]. However, the effects of parabiosis on the aged lacrimal gland and its effect on age-related dry eye disease have not been studied. The purpose of this work was to use heterochronic parabiosis for the first time to study age-related dry eye disease in the lacrimal gland. We wanted to determine the role of soluble serum factors in the development of pathologies associated with lacrimal gland aging. We hypothesized that aged mice in heterochronic pairings would have reduced inflammation and pathology due to beneficial soluble factors present in the young parabiont. To do this, we made use of young PepBoy mice that carry the pan leukocyte marker CD45.1 and aged B6 mice that carry the marker CD45.2, so that that cellular origin of the leukocyte populations could be determined in the analysis. Our results indicated that while heterochronic parabiosis for a period of eight weeks was not able to reverse the immune infiltration and inflammation seen in the aged lacrimal gland, pairing led to an increase in immune cells found in the young lacrimal gland. Our findings suggest that the aged lacrimal gland cannot be rejuvenated with young soluble factors, but soluble factors or cells from aged mice can lead to phenotypic features of aging in the young lacrimal gland. The identification of these detrimental factors could lead to targeted approaches to reduce eye aging. ## 2.1. Lacrimal Gland Pathology Was Worsened in Heterochronic Young Mice We first investigated the impact of 8-week-parabiosis on male lacrimal gland histology using heterochronic (young [6 months]/aged [20 months]) and isochronic (young/young or aged/aged) pairs (Figure 1). Mice were joined at the thoracic and abdominal area, skin-to-skin. Aged non-parabiotic C57BL/6 (B6; CD45.2) male mice have increased lymphocytic infiltration compared to young PepBoy male mice (CD45.1), which have none (Figure 2A,B). Similarly, isochronic aged male mice had increased lymphocytic infiltration compared to isochronic young male mice (Figure 2C,D). Surprisingly, young isochronic mice had focus scores greater than zero, which was not found in non-parabiotic mice (Figure 2B). Heterochronic young glands had significantly higher focal scores than isochronic young lacrimal glands ($$p \leq 0.047$$) and were not significantly different from heterochronic aged lacrimal gland focus scores ($$p \leq 0.2759$$). A microscopic evaluation of HE-stained lacrimal glands showed that some aged male lacrimal glands (regardless of pairing) had areas of fibrosis that were not only periductal but also extended into the glandular parenchyma (Figure 2E). We confirmed the presence of fibrosis using Masson’s trichrome stain, indicating extensive collagen deposition (Figure 2E). We then compared the frequency of fibrosis in lacrimal glands between aged non-parabiotic and aged parabiotic mice and found that there was some amount of fibrosis regardless of parabiosis. Parabiotic aged lacrimal glands had about a $36\%$ rate of fibrosis, while non-parabiotic aged mice had that of about $33\%$. ## 2.2. Significant Increase in Inflammatory and B-Cell-Related mRNA in Aged Lacrimal Glands Regardless of Parabiosis Because we noted increased lymphocytic infiltration among the parabiotic groups, we next analyzed the fold expression of several inflammatory markers via qPCR. There was no difference in the expression of Il1b or Tnf, although the young heterochronic lacrimal gland had the highest levels of Il1b among the groups (Figure 3A). There was a significant increase in Ifng in the aged heterochronic mice compared to that in isochronic aged mice (Figure 3B). Consistent with the increased focus score in the young heterochronic compared to young isochronic groups, the young heterochronic gland showed elevated levels of Ifng and Ciita. Because we observed an increase in lymphocytic infiltration in the heterochronic young lacrimal gland, we investigated if there was an increase in chemokines. While there were no differences in the expression levels of Cxcl13, there were significant fold increases in Cxcl9, a B-cell-attracting chemokine, in the young heterochronic gland (Figure 3C). Since there was an increase in the expression of a B-cell-related chemokine, we then investigated changes in Cd19, a gene marker for B cells. There was higher fold expression of Cd19 in both the heterochronic young gland and the isochronic aged gland. ## 2.3. Increased T and B Cell Populations in Heterochronic Young Lacrimal Glands The results from the histologic evaluation in Figure 2 and Figure 3 suggest an influx of different immune cell types into the lacrimal gland. To better characterize these cells, we used flow cytometry on single cell lacrimal gland suspensions, taking advantage of the fact that PepBoy mice (young) can be identified with the CD45.1 marker while B6 mice (aged) can be identified with the marker CD45.2 (Figure 4A). Flow cytometry analysis confirmed chimerism of cells into the lacrimal gland: in heterochronic young mice, $35\%$ of immune cells were from its B6 partner; in heterochronic aged mice, $25\%$ of immune cells were from its PepBoy partner. We first investigated the broad composition of the immune cells by using B, CD3, and CD4 antibodies. In isochronic pairings, young mice had a greater percentage of CD3+ T cells but a smaller percentage of B cells compared to those in isochronic aged mice (Figure 4B). In the heterochronic pairing, aged mice had a greater number of CD3+ cells from its young partner than from its own immune system, although this was not significant ($$p \leq 0.0622$$). These CD3+ cells were further divided into CD4+ and CD4− subsets. The young isochronic gland had more CD4+ cells than the isochronic aged ($p \leq 0.0001$), and in the heterochronic pairing, there were significantly more CD4+ cells from the heterochronic young mouse in both glands (Figure 4C). In both heterochronic mice, there were significantly more CD4− cells from its own system than from its partner. Heterochronic aged mice also had a greater increase in immune cells other than B220+ or CD3+ from its own system than from its young partner ($$p \leq 0.0013$$). Significantly, heterochronic aged mice had higher populations of B220+ cells, regardless of the source (Figure 4B). The results above indicated greater influx of B cells. To better characterize these B cells, we used B220 as a positive identifier of B cells for all subsequent subsets (Figure 5) using flow cytometry. Immune cells isolated from lacrimal glands were stained with CD45.1 or CD45.2 and then subsequently gated on B220, CD93, IgM, and CD23 expression. B220+CD93+ were defined as developing B cells. B220+CD93− cells were further divided into MZB cells (CD93−CD23−IgM+) or follicular-like B cells (CD93−CD23+IgM+) depending on the expression of CD23 and IgM. In other panels, cells were stained with CD45.1, CD45.2, B220, and GL7 markers, the IL-10 marker, or with the CD80 marker to identify germinal center cells, B regulatory cells, and memory cells, respectively. The results were therefore normalized as a percentage of B220+ cells. As we did in Figure 4B, cells were examined based on the expression of CD45.1 or CD45.2 to investigate the origin of the infiltrating B cells. MZB cells were the most abundant B220+ subtype among the subtypes (germinal center, developing B cell, follicular, memory, B regulatory, and marginal zone). They were enriched in isochronic aged mice compared to numbers in isochronic young mice ($p \leq 0.001$, Figure 5B). In heterochronic young mice, the highest proportion of MZB cells was from the aged (B6) partner ($p \leq 0.0001$), while in the heterochronic aged mouse, the highest proportion of MZB cells was from itself ($p \leq 0.0001$). There was a decrease in B regulatory cells (IL-10+B220+ cells) in isochronic aged mice compared to numbers in the isochronic young ($$p \leq 0.0184$$). For the evaluation of plasma cells, single cell suspensions were stained with CD45.1, CD45.2, B220, and CD138 antibodies. B220− cells were then gated based on the expression of CD138 (Figure 5C). Heterochronic aged mice had a greater proportion of plasma cells (B220−CD138+) from themselves than from their young partner ($$p \leq 0.0079$$), but these did not migrate to the heterochronic young gland (Figure 5D). ## 2.4. Heterochronic Parabiosis in Female Lacrimal Glands Does Not Improve Lymphocytic Infiltration or Inflammatory Marker Expression To rule out a potential bias in male sex regarding the effects of parabiosis, we added a cohort of female parabionts for analysis. Young female PepBoy and aged female B6 mice were surgically joined as described in the methods and in Figure 1. As with males, female parabiotic mice were analyzed after 8 weeks of parabiosis. First, we analyzed lacrimal gland pathology in histologic sections (Figure 6). Non-parabiotic young PepBoy females had no immune infiltration (focal score = 0), which significantly increased with age ($$p \leq 0.0007$$, Figure 6A,B). Isochronic aged female mice had significantly greater focal scores than isochronic young female mice (Figure 6D, $p \leq 0.0001$). Heterochronic aged female mice had significantly higher focal scores than their heterochronic young partners ($$p \leq 0.0047$$). However, unlike in males, based on a Kruskal–Wallis test followed by post-hoc Dunn’s multiple comparisons test, there were no statistical differences in focus scores between isochronic and heterochronic young females or isochronic and heterochronic aged females. Next, we investigated the same set of genetic markers in the female parabiotic lacrimal gland as we did with male parabiotic glands via qPCR. While there was no change in the broad inflammatory marker Il1b, there was a significant increase in Tnf in the heterochronic young mice compared to levels in young isochronic glands (Figure 7A). There was increased expression of Ctss in the isochronic aged females compared to that in isochronic young females (Figure 7B). Likewise, Ifng showed increased expression in isochronic aged glands compared to that in the isochronic young group. Ciita levels were similar across all four groups. When we investigated markers for B-cell-related chemokines and B cells, we found a significant increase in Cxcl13 and Cd19 in the isochronic aged females compared to levels in isochronic young females (Figure 7C). Interestingly, there was also significant Cd19 expression in the heterochronic aged lacrimal gland compared to that in its heterochronic young partner, suggesting an increase in B cells in the heterochronic young lacrimal gland that mimicked isochronic aged glands. ## 2.5. Aged Male Mice Have Worse Lacrimal Gland Infiltration and a Greater Frequency of Fibrosis than Aged Female Mice To account for sex-specific differences, we compared our results using sex as a biological variable. The differences between male and female lacrimal gland pathology and the genetic expression of inflammatory markers are summarized in Table 1 and in Supplemental Figures S1 and S2. Lacrimal gland total infiltration scores followed similar trends across isochronic aged groups regardless of sex, but young male heterochronic glands had greater focal scores than those of females in the same group ($$p \leq 0.0598$$). Aged male lacrimal glands also had fibrosis, regardless of pairing, while aged female lacrimal glands did not (Supplemental Figure S1C). *Certain* genetic markers were also more broadly expressed in one sex over the other. Tnf and Ctss were expressed at higher levels in the heterochronic aged female mice compared to those in heterochronic aged male mice (Table 1, Supplemental Figure S2). Ctss and Cxcl9 were expressed at higher levels in the isochronic aged female mice than in isochronic aged male mice. Only Cxcl13 was expressed higher in male mice, in isochronic young pairings. In summary, while male mice appeared to have a worse phenotype, based on histology, than female mice, in general, female mice had greater fold expression of inflammatory and B-cell-related genetic markers than male lacrimal glands. ## 3. Discussion Aging is a risk factor for many inflammatory pathologies, including dry eye disease [3,32]. The tear-secreting lacrimal gland contributes the aqueous portion of the tear film [33]. In dry eye disease, its function can be severely disrupted due to the infiltration of lymphocytes, resulting in less tear secretion [34,35]. Likewise, aging results in significant changes to the lacrimal gland, including the loss of function, acinar atrophy, periductal fibrosis, lymphocytic infiltration, and ductal dilation [6,8,36,37,38,39]. It is therefore important to find therapies that can address alterations to the lacrimal gland that occur during aging to increase the lifespan of the gland. In this study, we investigated the use of heterochronic parabiosis as a treatment for age-related lacrimal gland inflammation, since the exchange of blood soluble factors has shown promising results in animal models of cognitive impairment [40] and stem cell rejuvenation [41]. While we hypothesized that heterochronic parabiosis would improve age-related changes in the lacrimal gland, instead we found that the aged gland’s soluble factors and environment eclipsed those of the young glands and caused phenotypic signs of aging and worsened lacrimal gland inflammation (dacryoadenitis) in young parabionts. Therefore, the new findings of our study are that heterochronic parabiosis heightens an aged phenotype in young male lacrimal gland pathology, increases the expression of inflammatory and B-cell-related cytokine transcripts, and results in larger populations of B cells found in the young heterochronic lacrimal gland. To our knowledge, this is the first study investigating the use of an aging heterochronic parabiosis model in studies of age-related lacrimal gland infiltration and inflammation. ## 3.1. Lacrimal Gland Phenotype A surprising and unexpected finding in our results was that the histology of the lacrimal gland was worsened in heterochronic young recipients. While the parabiosis procedure resulted in a greater increase in inflammation, isochronic young male lacrimal glands had less lymphocytic infiltration than heterochronic young male lacrimal glands. Indeed, young male heterochronic lacrimal gland focal scores were not significantly different from those of their heterochronic aged male counterparts, indicating that shared blood circulation with aged mice worsens the cellular environment of the young lacrimal gland, resulting in significantly worse lymphocytic infiltration. Our results agree with other studies showing deleterious effects of heterochronic parabiosis on young recipients. Jeon and colleagues reported an increase in cell and tissue senescence after one transfusion of aged blood to young mice [42]. They identified increased markers of kidney damage, liver fibrosis, and the senescence-associated secretory phenotype. Similarly, Pálovics and colleagues showed that many young tissues, when exposed to aged blood, took on an aging phenotype [43], which agreed with prior work [44]. In aged mice, the aging phenotype was only partially reversed in specific tissues exposed to young blood, most notably the liver, pancreas, and tissues that rely heavily on the mitochondrial electron transport chain. In the brain, heterochronic parabiosis resulted in positive changes for the aged recipients, but negative changes in the young recipients, largely due to activation of cell senescence pathways [45], impairment of neurogenesis [46], and inhibition of cognitive function [47]. Yankova et al. reported that heterochronic parabiosis resulted in a significantly shorter lifespan for young heterochronic recipients compared to that in isochronic young mice [48]. While we did not see an improvement in the heterochronic aged gland after eight weeks of parabiosis, we did find that aged factors from the aged lacrimal gland accelerated the aging phenotype in the young lacrimal gland. Identifying these factors that drive the aging phenotype in young glands could help to identify novel targets to help prevent age-related inflammation and destruction to the eye and lacrimal gland. ## 3.2. Inflammatory Marker Expression Heterochronic parabiosis resulted in a higher fold expression of certain inflammatory and B-cell-related markers in the lacrimal gland, notably Ifng, Ctss, Ciita, and Cxcl9. As aging is accompanied by increased heterogeneity and variability [49,50], we observed a large variability in gene expression in our samples. We had previously shown an increase in Ifng, Ctss, and Ciita in the female aged lacrimal gland [8]. Interferon-γ has been shown to be a key player in aging and in dry eye. It exacerbates conjunctival apoptosis [19], results in goblet cell loss [51], and is secreted by infiltrating natural killer cells and CD4+ T cells to the conjunctiva [18], and its inhibition improves dry eye disease by increasing conjunctival goblet cells [52,53] and preventing lacrimal gland decline and destruction [54]. The increase in this mRNA transcript in both heterochronic recipients indicates an overall increase in inflammation and could be a main reason for the severity of lacrimal gland infiltration in the young heterochronic lacrimal gland. CXCL9 is a Th1-associated chemokine that helps coordinate the migration of Th1 cells. It requires interferon-γ for induction in dry eye disease [55]. Higher expression of Cxcl9 could have led to the greater infiltration of lymphocytes to the lacrimal gland, as was seen with their higher focal score (Figure 2C). Cathepsin S degrades the invariant Ii peptide in MHC II receptors for antigen docking and eventual presentation [56]. It has been implicated in several autoimmune diseases, including autoimmune myasthenia gravis pathogenesis [57], systemic lupus erythematosus [58], diabetes [59], and Sjögren Syndrome, a prototype autoimmune dry eye disease [60,61]. We have reported previously that Ctss mRNA is increased in aged murine female lacrimal glands [62] and that there is increased activity of the protein cathepsin S in both the tears of patients with dry eye disease and aged mice [60,62]. Aged Ctss−/− mice had improved corneal barrier functions and goblet cell density (both hallmarks of dry eye) compared to aged wild-type mice [62]. It is notable that Ctss mRNA expression was increased in heterochronic aged mice compared to that in isochronic aged mice, indicating that a marker for dry eye disease was heightened in the heterochronic parabionts. Ciita regulates MHC II expression [15]. Because of its main role in governing antigen-presenting cells, its presence strongly suggests that antigen-presenting cells are a key player in the pathology of the lacrimal gland. These findings suggest that while heterochronic parabiosis did not improve the pathology of aged lacrimal glands, it caused young lacrimal glands to develop dacryoadenitis, indicating that the exchange of soluble factors with young mice worsened the immune cell response in aged parabiotic glands. ## 3.3. Immune Cell Identification The heterochronic aged lacrimal gland had increased proportions of specific B cell subsets and more T cells than its isochronic counterpart. Most T cells came from the young partner, which suggests that the young mouse provided active CD4+ T cells that circulated throughout both glands. On the other hand, the proportion of B cells from itself and its partner were not significantly different. This suggests that the inflamed microenvironment of the lacrimal gland attracted immune cells indiscriminately and perpetuated inflammation, indicating that the aged microenvironment was a stronger factor than the regulation of immune cells when it came to autoimmune destruction of the tissue. In isochronic aged mice, there was a significant decrease in B regulatory cells compared to levels in isochronic young mice, which might indicate that some of the autoimmune changes seen in the isochronic aged mice were due to a lack of these B regulatory cells. However, the proportions of B regulatory cells did not significantly change in the heterochronic mice, suggesting that other factors are also at play. We have shown that immune cells in the aged lacrimal glands develop ectopic lymphoid structures (or tertiary lymphoid tissue) that have high levels of germinal centers and T follicular helper cells [12]. Here, it is possible that these ectopic lymphoid structures drew circulating immune cells from both recipients to reside in the lacrimal gland. The most important B cell subset was MZB cells, which were significantly increased in isochronic aged mice compared to numbers in the isochronic young group. In the heterochronic young lacrimal gland, MZB cells from its aged partner were significantly more abundant than MZB cells from its own circulation, demonstrating that aged MZB cells are very sensitive to the chemoattractant gradient. We also found that MZB cells accumulate in non-parabiotic lacrimal glands, in contrast to B follicular cells, which accumulate in the draining lymph nodes [12]. MZB cells produce antibodies during infection [20]. The increases seen in both the heterochronic and isochronic lacrimal glands here suggest dysregulation of the immune system associated with aging [63,64,65,66], resulting in higher levels of autoreactive immune cells, including MZB cells. This could also be a reason for the greater infiltration of lymphocytes in the heterochronic young lacrimal gland. Taken together, these results indicate that heterochronic parabiosis results in the circulation of active T cells from the young partner and mostly MZB cells from the aged partner to both lacrimal glands. This resulted in the worse focal scores for the heterochronic young glands (Figure 2C) and is potentially why the heterochronic aged focal scores did not improve when compared to the isochronic aged scores. ## 3.4. Sex Differences in Parabiotic Lacrimal Glands One limitation of this study was the limited availability of aged female mice for analysis; therefore, we restricted our analysis in females to the focus score and gene expression. On a histological level, heterochronic young lacrimal glands were not as severely infiltrated as their male counterparts, suggesting that female parabiosis neither improved the aged mice nor worsened the young in the heterochronic pairs. However, female lacrimal glands exhibited higher fold expression of several inflammatory markers, including Tnf, Ctss, Cxcl9, and Cd19, suggesting a greater number of B cells infiltrating these glands. This might suggest that while there were fewer foci in the gland, there was an increased presence of diffuse lymphocytes to the tissue. Both heterochronic and isochronic aged male lacrimal glands had a high prevalence of fibrosis, which was not seen in young lacrimal glands. This finding was not seen in the female lacrimal glands, indicating a sex-specific difference in the aging lacrimal gland. Work investigating the role of sex hormones in the lacrimal gland also reported significant sex differences in aging due to the effects of estrogen signaling in the male lacrimal gland [67]. When we compared the rate of fibrosis between age-matched parabiotic and non-parabiotic mice, there was no difference in frequency. We also investigated a set of diversity outbred lacrimal glands in our recent publication [12] to see if the incidence of fibrosis was specific to C57BL/6J mice and found fibrosis in the aged males, but not the aged females. Other work has identified sex differences in genetic marker expression in the lacrimal gland, finding significant sex changes in inflammatory markers, such as CXCL9 and CXCL13 [68]. Although we did not find fibrosis in the young heterochronic lacrimal gland, heterochronic parabiosis has resulted in liver fibrosis in young recipients [42,44]. Investigating the sex-specific fibrosis found in the lacrimal glands may prove to be an interesting avenue of further research. Our findings indicate that age-related pathologies in male and female lacrimal glands are different processes. Male mice had increased lymphocytic infiltration because of parabiosis, while female mice had increased expression of several inflammatory cytokines. These data suggest that female and male aged mice responded differently to parabiosis, but aging resulted in an increase in inflammation in both sexes that was not improved with heterochronic parabiosis. ## 4. Materials and Methods All experiments were approved prior to their execution by the University of Texas Health Science Center and Baylor College of Medicine’s Institutional Animal Care and Use Committees. The studies also followed all guidelines for the Use of Animals in Ophthalmic and Vision Research as supported by the Association for Research in Vision and Ophthalmology and the NIH Guide for the Care and Use of Laboratory Animals (NIH Publications No. 8023, revised 1978 [69]). The Ocular Surface Center, Department of Ophthalmology, Baylor College of Medicine (Houston, TX, USA) and the BRAINS Research Laboratory, Department of Neurology, The University of Texas Health Science Center at Houston John P and Katherine G McGovern Medical School (Houston, TX, USA) were where all experiments took place. ## 4.1. Animals Male and female PepBoy mice 4 months of age were surgically joined to either another PepBoy or a C57BL/6J (B6) mouse aged 18 months at the thoracic and abdominal area, skin-to-skin. The peritoneum remained intact. Pairings were either isochronic (young to young or aged to aged) or heterochronic (young to aged), all same-sexed. Male mice were used in the following numbers: isochronic young (YY) = 40 pairs, isochronic aged (AA) = 35 pairs, heterochronic young (YA-Y) = 36 mice, heterochronic aged (YA-A) = 36 mice, non-parabiotic 4-month PepBoy = 10 mice, non-parabiotic 19-month B6 = 10 mice. Female mice were used in the following numbers: YY = 12 pairs, AA = 14 pairs, YA-$Y = 13$ mice, YA-$A = 13$ mice, non-parabiotic 4-month PepBoy = 10 mice, non-parabiotic 21 month B6 = 14 mice. Mice were evaluated 2 months post-surgery. Surgeries were performed at the BRAINS Research Laboratory in the University of Texas Health Science Center at Houston John P and Katherine G McGovern Medical School. After euthanasia, tissues were shared. Extra-orbital lacrimal glands were collected and processed either for histology, gene expression analysis, or flow cytometry. ## 4.2. Calculation of Lymphocytic Infiltration Lacrimal glands (male, number of glands: YY = 29, AA = 32, YA-$Y = 20$, YA-$A = 20$, non-parabiotic young PepBoy = 10, non-parabiotic old B6 = 10; female, number of glands: YY = 24, AA = 11, YA-$Y = 13$, YA-$A = 12$, non-parabiotic young PepBoy = 10, non-parabiotic old B6 = 14) were excised, fixed in $10\%$ formalin, paraffin-embedded, and cut into 4 µm sections using a microtome (ThermoFisher, Microm HM 315, Waltham, MA, USA). Sections were stained with H&E using an autostainer (Gemeni AS, ThermoFisher, Waltham, MA, USA), and coverslips were applied (Tissue Tek Auto Cover Slipper 4764, Sakura, Torrance, CA, USA). These procedures were performed at Precise Pathology Associates, PLLC (The Woodlands, TX, USA). Lacrimal glands were cut into 5 different levels and each staining level was 12 µm apart from the next one. Using a standard light microscope with a 10X objective (Nikon, Tokyo, Japan; Eclipse E400), two blinded observers, to prevent bias, counted lymphocytic infiltrate foci. A minimum of 50 mononuclear cells was counted as one focus. Slides were scanned with a PathScan Enabler V (Meyer Instruments, Houston, TX, USA) and were calibrated according to the manufacturer’s instructions (2.54 µm/pixel) using NIS Elements software (version 5.30.05). The total area of the scanned lacrimal gland was calculated using NIS Elements. The focus score was calculated as the total number of counted foci on a scanned lacrimal gland per 4 mm2, to match human pathologist standards [10]. ## 4.3. Masson’s Trichrome Stain Lacrimal glands (male, number of glands: AA = 4, YA-$A = 4$) were excised, fixed in $10\%$ formalin, paraffin-embedded, and cut into 5 µM sections using a microtome (Microm HM 340E; Thermo Fisher Scientific, Waltham, MA, USA). Masson’s trichrome stain kit (StatLab, McKinney, TX, USA) was used following the manufacturer’s protocol. Using a standard light microscope with a 10X objective (Nikon; Eclipse E400), two masked observers counted sections for fibrosis in lacrimal gland sections (absence = 0; presence = 1). Frequency was analyzed using Chi square analysis in GraphPad 9.1. ## 4.4. RNA Isolation and Real-Time PCR We extracted RNA from excised extraorbital lacrimal glands (male, number of glands: YY = 10, AA = 10, YA-$Y = 10$, YA-$A = 10$; female, number of glands: YY = 10, AA = 6, YA-$Y = 10$, YA-$A = 10$) according to the manufacturer’s protocol, using a QIAGEN RNeasy Plus Mini RNA isolation kit (Qiagen, Hilden, Germany). *To* generate cDNA, we measured the concentration of RNA, calculated 1 µg of RNA for use, and then used the Ready-To-Go™ You-Prime First-Strand kit (GE Healthcare, Chicago, IL, USA). All real-time PCR used minor groove-binding Taqman probes, which were IFN-γ (Ifng, Mm01168134), major histocompatibility complex class II (Ciita, Mm00482914), TNF-α (Tnf, Mm00443258), IL-1β (Il1b, Mm00434228), Cathepsin S (Ctss, Mm00457902), CXCL13 (Cxcl13, Mm00444533), CXCL9 (Cxcl9, Mm00434946), and CD19 (Cd19, Mm00515420). Real-time PCR reactions used TaqMan™ Fast Universal PCR Master Mix (2X) and no AmpErase™ UNG (Thermo Fisher Scientific) and were all carried out on a Taqman Universal PCR system (StepOnePlus™ Real-Time PCR System, Applied Biosystems, Bedford, MA, USA). A housekeeping gene, hypoxanthine phosphoribosyltransferase 1 (HPRT1, Mm00446968), was used to normalize all Ct values. ## 4.5. Flow Cytometry Lacrimal glands (male, number of glands: YY = 18, AA = 21, YA-$Y = 19$, YA-$A = 18$) were excised and incubated with $0.1\%$ collagenase IV. Cell suspensions were frozen in 1 mL of freezing composed of $90\%$ FBS (Gibco/ThermoFisher, Waltham, MA, USA) and $10\%$ DMSO (ThermoFisher, Waltham, MA, USA) and stored in liquid nitrogen until analysis could be performed. Samples were thawed in a water bath and added to 9 mL of warmed RPMI media (ThermoFisher), before proceeding with analysis. Single-cell suspensions were incubated with anti-CD$\frac{16}{32}$ (BioLegend, San Diego, CA, USA) to block Fc receptors for 10 min at 4 °C and subsequently stained with one of three cocktails containing some of the following antibodies: anti-CD45.1_PE (Clone A20, BioLegend), anti-CD45.2_BV510 (Clone 104, BioLegend), anti-CD4_FITC (Clone RM4-5, Invitrogen/ThermoFisher, Waltham, MA, USA), anti-CD3_BB700 (Clone 145-2C11, BD BioSciences, Franklin Lakes, NJ, USA), anti-B220_APC (Clone RA3-6B2, BD BioSciences), anti-IgA_FITC (Clone MA-6E1, Invitrogen/ThermoFisher), anti-CD80_PerCpCy5.5 (Clone 16-10A1, BioLegend), anti-IL-10_PE (Clone JES5-16E3, BioLegend), anti-CD138_BV421 (Clone 281-2, BioLegend), anti-IgM_FITC (Clone RMM-1, BioLegend), anti-GL7_PerCpCy5.5 (Clone GL7, BioLegend), and anti-CD23_BV421 (Clone B3B4, BioLegend). Afterwards, cells were incubated with an infrared fluorescent reactive live/dead dye diluted 1:32 (ThermoFisher) for 20 min, washed, and resuspended in $2\%$ formaldehyde for 15 min. Gates were determined by first finding cells on the forward scatter area versus side scatter area, and then finding singlets based on first forward scatter height versus forward scatter area, followed by a second doublet discrimination of side scatter height versus side scatter area. Alive cells were discriminated from dead using fixable infrared dye versus side scatter, and then, CD45.1+ cells and CD45.2+ cells were gated for subsequent analysis. CD3+CD4+ or B220+ cells were found to calculate the frequency of parents for combinations of subsets. Negative controls consisted of fluorescence minus one (FMO) combined cell suspensions from all animal groups. Cells were acquired with the BD Canto II Benchtop cytometer with BD Diva software version 6.7 (BD Biosciences). Final data were analyzed using FlowJo software version 10 (Tree Star, Inc., Ashland, OR, USA). ## 4.6. Statistical Analysis We used GraphPad Prism (GraphPad Software, San Diego, CA, USA, version 9.1) to perform all statistical analyses. The Kolmogorov–Smirnov normality test was first used. Then, non-parametric (Mann–Whitney) statistical tests were used to make comparisons between two groups. When possible, we used one-way or two-way ANOVA or Kruskal–Wallis followed by post-hoc tests. p < or equal to 0.05 was considered significant. ## 5. Conclusions Altogether, our results indicate that young blood shared with aged recipients does not reduce the pathology of age-associated dacryoadenitis. The aged microenvironment attracts immune cells that perpetuate tissue destruction and inflammation, and soluble factors from this environment go on to increase the aging phenotype and inflammation in the young lacrimal gland. Aged blood had a deleterious effect on the young lacrimal gland, resulting in an increase in lymphocytic infiltration, greater expression of inflammatory transcripts, and an increase in MZB cells. Identification of the factors that accelerated this aging phenotype could provide a novel avenue for therapeutics related to dry eye disease. Furthermore, there were differences in sex across experimental groups. Heterochronic parabiosis in female lacrimal glands had higher inflammatory cytokine expression but less foci infiltration than male lacrimal glands. The difference based on sex underscores a greater need for investigation into sex differences in aging and in response to parabiosis. Treatments for age-related dry eye should pursue addressing the inflamed microenvironment of the lacrimal gland and aged soluble factors to help stop this self-perpetuating cycle. ## References 1. 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--- title: Intrahepatic Cholangiocarcinoma Developing in Patients with Metabolic Syndrome Is Characterized by Osteopontin Overexpression in the Tumor Stroma authors: - Massimiliano Cadamuro - Samantha Sarcognato - Riccardo Camerotto - Noemi Girardi - Alberto Lasagni - Giacomo Zanus - Umberto Cillo - Enrico Gringeri - Giovanni Morana - Mario Strazzabosco - Elena Campello - Paolo Simioni - Maria Guido - Luca Fabris journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003180 doi: 10.3390/ijms24054748 license: CC BY 4.0 --- # Intrahepatic Cholangiocarcinoma Developing in Patients with Metabolic Syndrome Is Characterized by Osteopontin Overexpression in the Tumor Stroma ## Abstract Metabolic syndrome (MetS) is a common condition closely associated with non-alcoholic fatty liver disease/non-alcoholic steatohepatitis (NAFLD/NASH). Recent meta-analyses show that MetS can be prodromal to intrahepatic cholangiocarcinoma (iCCA) development, a liver tumor with features of biliary differentiation characterized by dense extracellular matrix (ECM) deposition. Since ECM remodeling is a key event in the vascular complications of MetS, we aimed at evaluating whether MetS patients with iCCA present qualitative and quantitative changes in the ECM able to incite biliary tumorigenesis. In 22 iCCAs with MetS undergoing surgical resection, we found a significantly increased deposition of osteopontin (OPN), tenascin C (TnC), and periostin (POSTN) compared to the matched peritumoral areas. Moreover, OPN deposition in MetS iCCAs was also significantly increased when compared to iCCA samples without MetS (non-MetS iCCAs, $$n = 44$$). OPN, TnC, and POSTN significantly stimulated cell motility and the cancer-stem-cell-like phenotype in HuCCT-1 (human iCCA cell line). In MetS iCCAs, fibrosis distribution and components differed quantitatively and qualitatively from non-MetS iCCAs. We therefore propose overexpression of OPN as a distinctive trait of MetS iCCA. Since OPN stimulates malignant properties of iCCA cells, it may provide an interesting predictive biomarker and a putative therapeutic target in MetS patients with iCCA. ## 1. Introduction Cholangiocarcinoma (CCA), a primary liver epithelial cancer that can arise from any tract of the biliary tree, is one of the most aggressive and lethal malignancies worldwide. Anatomically, CCAs are classified as intrahepatic (iCCA), peri-hilar (pCCA), and distal (dCCA) [1]. CCA is a rare tumor, at least in the Western countries, with an incidence ranging between 0.3 and 6:100,000 inhabitants/year depending on the geographical area. However, the global incidence is progressively growing in the recent decades, particularly for iCCA [1,2]. Unfortunately, prognosis has not substantially changed, and remains dismal, with a mortality rate of about 1–6:100,000 inhabitants/year and a 5-year survival of only 5–$20\%$ [1]. CCA aggressiveness and propensity to early disseminate is influenced by the dense tumor reactive stroma (TRS), which expands in conjunction with the growth of the malignant epithelial counterpart. TRS is composed by an acellular component, the extracellular matrix (ECM), and by several cell populations, including cancer-associated fibroblasts and a polymorphic inflammatory infiltrate [3,4]. Owing to these features, diagnosis often comes late, and available therapies are of limited efficacy, hampering the drug delivery to the tumoral site [5]. Currently, in CCA, the only curative intervention remains surgical resection or, in selected cases, liver transplantation [6]. Unfortunately, the early spread of CCA to the proximal lymph nodes, occurring in more than $70\%$ of patients and favored by the TRS, often precludes the suitability to curative approaches [7]. Although iCCA often arises in the context of a non-cirrhotic liver, it is thought that the chronicization of the inflammatory response sustained by the hepatic repair mechanisms, as observed in hepatitis C virus (HCV) infection, recurrent acute cholangitis, and primary sclerosing cholangitis, may incite the onset and progression of the tumor [8]. Liver repair is driven by the hepatic reparative/regenerative complex, which is characterized by multiple morphological changes, including the generation of a ductular reaction (DR) and biliary metaplasia of hepatocytes (MHs), in an attempt to restore the normal hepatic homeostasis [9]. Thanks to the ability to secrete a wide range of fibro-inflammatory mediators, encompassing cytokines, chemokines, and growth factors possibly supporting cholangiocarcinogenesis, the DR may hold oncogenic potential [10]. Of note, during biliary tumorigenesis, the normal ECM, mainly composed of collagens (type I to V), fibronectin, laminins, nidogens, and perlecan, is progressively dismantled, and qualitatively modified by a de novo deposition of aberrant matrix proteins. These include periostin (POSTN), tenascin-C (TnC), and osteopontin (OPN), which are not usually secreted in the normal ECM. Interestingly, the expression of these matrix proteins correlates with the tendency to metastasize to the lymph nodes of tumors and a lower overall survival of patients, though the underlying mechanisms are far from being understood [7]. Notably, recent epidemiological studies suggest that metabolic syndrome (MetS), frequently associated with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), may be considered an emerging risk factor for the development of iCCA [11]. NASH, in particular, is characterized by the activation of the hepatic reparative/regenerative mechanisms, resulting in a brisk DR, which correlates with the degree of fibrosis. However, no studies so far have explored the pathophysiological association of MetS with DR, ECM remodeling, and cholangiocarcinogenesis. Of note, ECM remodeling is a key mechanism common to liver repair and cardiovascular complications, which are the leading causes of mortality in NAFLD patients. As the prevalence of NAFLD/NASH is steadily increasing, even in young individuals in the Western population [12,13], it is conceivable to expect a rise in iCCA associated with MetS. Therefore, the identification of putative biomarkers related to liver repair mechanisms predicting the development of this insidious form of cancer may be of great help for risk stratification. Starting from these premises, in the present manuscript, we evaluated morphological differences between iCCAs associated or not with MetS with respect to hepatic reparative/regenerative responses and ECM modifications to unveil elements with pro-tumorigenic significance. ## 2.1. Demographic and Clinical Features of iCCA Patients with and without MetS According to their metabolic profile, patients with iCCA were divided into two cohorts, with (MetS iCCA, $$n = 22$$) and without MetS (non-MetS iCCA, $$n = 44$$). Categorization of MetS was based on the evaluation of the five major clinical components, encompassing obesity (body mass index (BMI) > 30 kg/m2 or waist to hip ratio >0.90 in males and >0.85 in females), type 2 diabetes mellitus (T2DM), elevated blood pressure, increased serum triglyceride levels, or decreased serum high-density lipoprotein (HDL) cholesterol levels (National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) guidelines) (Table 1), which define MetS when clustered at least in three areas. The two cohorts were comparable in terms of age, sex balance, and serological features, whereas, as expected, metabolic abnormalities were more represented in the MetS cohort, except for HDL levels. There were also no significant statistical differences in the entity of liver steatosis in adjacent liver tissue between the two cohorts. Furthermore, no significant differences were observed in treatment modalities and clinical outcome (follow-up time from 95 to 3233 days), evaluated as overall survival (OS), recurrence, and relapse-free survival (RFS) between the two cohorts (Table 2). Assessment of visceral adiposity, the hallmark of MetS, was performed by calculating the total volume and the volume rate of fat in the abdominal computerized tomography (CT) scan. Significantly higher values of both measurements were observed in MetS iCCA patients compared with non-MetS iCCA patients (Figure 1A,B), thereby providing further evidence of the different metabolic dysregulation affecting the two groups of patients. ## 2.2. Histological Analysis of Hepatic Steatosis, DR, MHs, and Fibrosis in Liver Tissue Adjacent to iCCA Showed no Significant Differences between Patients with and without MetS, though Fibrosis Patterns Were Different In the matched peritumoral area of iCCA samples, we performed morphometric analysis to evaluate the presence and extension of hepatic steatosis and the degree and patterns of fibrosis. Moreover, we performed immunostaining for the biliary-specific cytokeratin (K) 7 to evaluate the presence and extension of two elements of the hepatic reparative/regenerative system (DR and MHs). Hepatic steatosis, although higher in MetS than in non-MetS iCCA, did not reach statistical significance (Figure 2). Again, we observe that the extent of the DR and MHs did not differ between the two cohorts of patients (Figure 2). However, by Masson’s trichrome staining performed in serial histological sections of those used for immunohistochemical analysis, we found that the presence of fibrosis in MetS iCCAs was overall higher than in non-MetS ($88\%$ vs. $70\%$, respectively), even though there was a similar percentage of cirrhotic livers. Furthermore, in MetS iCCAs, fibrosis showed a significantly increased septal pattern compared to non-MetS iCCAs, with a prominent pericentral distribution consistent with that typically observed in liver disease associated with metabolic dysfunction (Figure 3A–C). Taken together, these data indicate that, although without significant differences in the activation of the hepatic reparative/regenerative mechanisms, fibrogenesis behaved differently when iCCA developed in the setting of MetS. Starting from these observations, we turned to the evaluation of the qualitative composition of the fibrotic tissue in both peritumoral and tumoral samples by assessing the expression of three pathological components of the ECM associated with iCCA, namely tenascin (TnC), periostin (POSTN), and osteopontin (OPN) [7]. ### OPN Was More Expressed in MetS iCCA with Respect to Non-MetS iCCA By comparing the bulk tumor with the peritumoral area, we found a significant up-regulation of all the three ECM proteins, POSTN, TnC, and OPN, in the TRS in both the MetS and non-MetS iCCA. These observations confirm that newly synthesized ECM components accumulate in conjunction with biliary tumorigenesis in either MetS or non-MetS conditions, likely mediating putative pro-oncogenic effects [7] (Figure 4). However, among the three proteins, OPN showed a marked increase in the TRS of MetS iCCA compared to non-MetS iCCA, whereas POSTN and TnC did not show significant differences (Figure 4). Therefore, we identified up-regulation of OPN as a distinctive feature of iCCA developing in the setting of MetS, implying that OPN overexpression may hold a significance related to the metabolic derangement. Once the increased expression of POSTN, TnC, and OPN was confirmed in histological sections of iCCA, we next tested their in vitro effects on a range of hallmarks of tumorigenesis, which included cell viability, cell migration, and induction of stemness features, using a human iCCA cell line, i.e., HuCCT-1 [14,15]. ## 2.4. Treatment with OPN and POSTN but Not with TnC Slightly Sustained Cell Viability in iCCA Cells In Vitro Treatments with OPN and POSTN but not TnC exerted a small but significant stimulus ($p \leq 0.05$ vs. untreated controls) on cell viability of the HuCCT-1 cell line (Figure 5). It must be underlined that in line with previous studies describing a pro-proliferation effect of these ECM proteins, our data showed that this effect, though detectable, was not so pronounced. ## 2.5. Treatment with OPN, TnC, and POSTN Potently Stimulated iCCA Cell Motility Unlike cell viability, OPN, TnC, and POSTN induced a potent time-dependent pro-migratory stimulus on HuCCT-1 cells. Twenty-four-hour treatment with OPN, TnC, and POSTN was nearly able to close the scar produced on cell monolayers for a wound healing assay with a comparable action. This effect was significantly higher as compared to untreated controls (Figure 6). Therefore, these data confirm the role of these deregulated ECM proteins to sustain cell motility mechanisms in malignant intrahepatic cholangiocytes. ## 2.6. Treatment with OPN, TnC, and POSTN Induced iCCA Cells to Acquire Cancer-Stem-Cell-like Phenotypic Traits An additional effect exerted by cell–ECM interactions occurring in the TRS is the gain of a cancer stem cell (CSC)-like phenotype, which is relevant for tumor initiation, chemoresistance, and tumor recurrence. By assessing the mRNA levels of CD133 and CD44, two well-established markers displayed by CSCs, we found that 24 h treatment of HuCCT-1 cells with OPN, TnC, and POSTN variably modulated their expression of CD133 and CD44, which increased significantly after challenge with OPN and POSTN, but not with TnC (Figure 7). Taken together, these data indicate that de novo expression of abnormal ECM components in the TRS of iCCA is functionally relevant to promote motility and CSC features of malignant cholangiocytes, and in this respect, OPN behaves as a key determinant of the enhanced fibrogenesis featuring MetS-associated iCCA. ## 3. Discussion In recent years, the incidence of CCA has been increasing worldwide, as observed in the Western countries for the iCCA variant. Among the predisposing disease conditions responsible for this heavier epidemiological burden in Europe as well as in the US, MetS represents an emerging risk factor, showing an OR for iCCA of 1.73 in patients with T2DM and 2.2 in patients with NAFLD, the hepatic manifestation of the MetS [1]. Indeed, NAFLD/NASH has become the most widespread chronic liver disease in the Western populations, and its incidence has paralleled the increased diffusion of the MetS [16]. NAFLD/NASH may have a pro-carcinogenic role in the development of iCCA. Thus, recent epidemiological evidence clearly indicates that MetS is a risk factor not only for hepatocellular carcinoma, but also for iCCA [11,17]. However, whereas the mechanisms by which MetS and the related liver involvement, NAFLD/NASH, sustain carcinogenesis towards HCC have drawn attention, underlying the role of the long-lasting inflammatory response induced by the lipotoxicity affecting the hepatocytes [18], how a metabolic derangement may induce pro-oncogenic effects on the cholangiocyte level has not been investigated yet. Starting from the assumption that fibrogenesis is an important mechanism related to chronic inflammation endowing malignant potential, in this study we aimed to verify whether iCCA developing in patients with MetS shows distinctive alterations of fibrosis and ECM components compared to patients with iCCA without MetS. By focusing on three matrix components typically up-regulated in the tumor microenvironment (TME) of iCCA (POSTN, TnC, and OPN), we also evaluated their effects on the biology of iCCA cells. In a single-center series of iCCA patients undergoing surgical resection with curative intent, we considered two cohorts on the basis of their association with MetS, defined by the presence of the five key clinical components including obesity, elevated blood pressure, increased serum glucose or triglyceride levels, or decreased serum HDL cholesterol levels. Apart from these metabolic parameters, the two cohorts were well comparable in terms of clinical and demographic features. As confirmation of the altered metabolic profile, abdominal CT scan was also evaluated to assess visceral adiposity (a hallmark of MetS), which resulted as significantly increased visceral fat volume and rate in the MetS-associated iCCA, further supporting the patient categorization. In patients with iCCA, the presence of MetS is associated with a diverse pattern of fibrosis developing in the peritumoral tissue, whereby activation of the cell elements of the hepatic repair response does not differ. The development of cancer is not an all or nothing phenomenon and usually starts from pre-tumoral lesions, which under a persistent chronic inflammatory stimulus responsible for genomic instability develop into malignant tumors owing to sustained proliferative signaling, resistance to cell death, limitless replicative potential, and loss of growth suppression [8]. In chronic liver diseases, the chronic inflammatory stimulus is driven by the activation of epithelial structures belonging to the hepatic reparative/regenerative system, composed of ductular reactive cells associated with a range of inflammatory cells and myofibroblasts, resulting in a ductular reaction (DR), and in metaplasia of hepatocytes (MHs) [9], which are not present in the normal healthy liver [19]. In this first part of the study, we drew our attention on the matched peritumoral areas of the resected iCCA to evaluate the liver background from which the malignant transformation originated. Although the extent of these aberrant epithelial structures was increased with respect to normal condition [19], no significant differences were found between the two cohorts, indicating the lack of a significant effect of MetS in eliciting a DR/MHs in the liver. Conversely, we found significant differences with respect to the type and extent of fibrosis between the two study groups. In the MetS cohort, we found a significant preponderance of stage 4 (septal) fibrosis, in keeping with the pattern commonly observed in the hepatic metabolic injury [20] and indicating a more advanced fibrotic progression upon metabolic dysregulation. Moreover, our data highlight the concept that MetS behaves as a warning sign of liver fibrosis [21], as suggested by a recent meta-analysis demonstrating that MetS was an independent risk factor for hepatic fibrosis even in the absence of steatosis [22]. Of note, in our study, although the mean percentage of liver steatosis tended to be higher in the group of iCCA with MetS compared with that without MetS (12.05 vs. $5.54\%$), it did not reach statistical significance. ECM in the TRS of iCCA is characterized by de novo deposition of TnC, POSTN, and OPN. After the evaluation of the peritumoral tissue, we turned to the matched bulk tumor to see if ECM protein accumulation was quantitatively and qualitatively different in the TRS between MetS and non-MetS iCCAs. Although development of an abundant TRS is a distinctive feature of iCCA, no data highlighting a different TRS composition across diverse underlying liver disease etiologies of CCA are available. Among the various components of the TRS, herein we focused on the ECM proteins, starting from the assumption that intensive ECM remodeling occurs in MetS [23] and from our evidence indicating a different fibrotic pattern between the two groups of iCCA. In both cohorts, the deposition of TnC, POSTN, and OPN was significantly higher compared with the peritumoral tissue, whereby they were almost absent. This observation confirms the concept that these ECM proteins are newly secreted in conditions of malignant transformation, implying a more complex functional role beyond the structural rearrangement. Moreover, OPN was significantly more expressed in MetS- than non-MetS iCCA tumor specimens, hinting at the possibility that OPN plays a specific role in the tumorigenesis of iCCA in patients with MetS. Recent studies have uncovered that OPN behaves as a regulator at the cross roads of inflammation, obesity, and diabetes [24]. The fundamental role played by OPN in mediating metabolic responses was addressed using different in vivo models. The comparison between OPN−/− and WT control mice both fed with a high-fat diet (HFD) demonstrated that OPN expression is essential for the early onset of insulin resistance [25]. Moreover, obese mice treated with specific neutralizing antibodies against OPN showed inhibition of chronic inflammation induced by obesity as well as of insulin resistance development [26]. Furthermore, several works unveiled a close relationship of OPN overexpression with the development of T2DM complicated by nephropathy [24]. In the liver, different cell types, such as epithelial, endothelial, and immune cells, may secrete OPN in response to chronic injury [27]. In NASH, in vivo and in vitro studies have pinpointed the profibrogenic role of OPN, not only as an ECM protein but also as a cytokine. Upon treatment with the methionine–choline-deficient (MCD) diet (a classical dietary model of NASH), mice showed an up-regulation of OPN in the DR compartment that was accompanied by increased fibrosis in the liver parenchyma. This effect was reduced in OPN−/− mice and was recapitulated and further exacerbated in Patched (Ptc)+/− mice (harboring overactivation of the Hedgehog (Hh) signaling), indicating a combinatorial interaction of OPN with Hh. Interestingly, in NASH patients OPN expression correlated with activation of the Hh pathway and fibrosis stage [28]. In another study, WT mice treated with an HFD developed an inflammatory response mostly mediated by macrophages, as with human NAFLD. Pharmacological inhibition of Smoothened (SMO) (downstream effector of the Hh signaling) with GCD-0449 and LED225, or HFD treatment to nourish Smo-LKO mice, reduced the infiltration of activated macrophages and the expression of pro-inflammatory mediators [29]. Altogether, these observations revealed that up-regulation of OPN is interwoven with an over-activation of the Hh pathway and this pathogenic link is strategic in directing hepatic fibrogenesis in MetS, likely mediated by a macrophage-driven inflammatory response with enhanced ECM remodeling. In vitro, OPN, TnC, and POSTN induce iCCA cells to gain pro-migratory functions and to acquire a stem-cell-like phenotype. To understand the pro-oncogenic potential of fibrosis associated with the up-regulation of aberrant ECM proteins, we conducted in vitro studies using an established cell line of human iCCA, the HuCCT-1 cells. Previous literature dealing with other tumor contexts highlighted the ability of TnC, POSTN, and OPN to regulate several core roles, which orchestrate tumorigenesis and tumor progression, such as proliferation, cell viability, migration, angiogenesis, pro-invasive pathways, and stemness induction [30]. Starting from these premises, we analyzed iCCA cell responses to in vitro treatments with these three proteins. Whereas impact on cell viability of iCCA cells was very mild, effects on cell motility were very pronounced and of similar magnitude with all of them. Although the molecular mechanisms by which OPN, TnC, and POSTN promote cell invasiveness in iCCA cells are far from clear, a role of integrin α5β1 in triggering the phosphatidylinositol 3-kinases (PI3K)/Akt pathway and amplifying Met and/or Erb signaling in response to POSTN has been proposed [31]. Furthermore, we found that OPN and POSTN but not TnC significantly stimulated HuCCT-1 cells to overexpress the CSC biomarkers, CD44 and CD133. In human mammary epithelial cells, POSTN provided breast cancer cells with a stem-cell-like phenotype [15]. In CCA, the accumulation of OPN, TnC, and POSTN increased the content of CSCs [31]. In particular, OPN acts as a critical regulator of the CSC niche. OPN exerts a recruiting effect on cancer-associated fibroblasts (CAFs), which in iCCA are the most abundant cell population of the TRS and functionally support the expansion of the CSC niche. A further effect of OPN is the stimulation of macrophages with the M1 phenotype into tumor-associated macrophages (TAMs), which, as with CAFs, are involved in the regulation of CSC function. These modulatory effects on CSCs have been also demonstrated in other malignant settings of the gastrointestinal system, as in hepatocellular carcinoma [32] and colorectal carcinoma [33]. In conclusion, since CSCs preferentially contribute to tumor initiation, in addition to confirming the pro-tumorigenic role of fibrosis, these observations link fibrosis progression with MetS and identify OPN as a key molecular effector of this pathogenetic link. Notably, OPN can be modified in five isoforms due to alternative splicing (OPNa, OPNb, OPNc, OPN4, and OPN5), which are differentially expressed in different tumors [34,35]. To date, the functions of these splicing variants are not completely clear, and no studies have been conducted on this topic in iCCA, an issue worth being pursued by future research directions. However, since OPN may be also found as a secreted cytokine in biological fluids, including serum, in theory, OPN may provide a tool to monitor the malignant potential of liver fibrosis associated with MetS. In line with this observation, using OPN dosage in serum as a non-invasive biomarker is supported by extensive evidence generated in pancreatic ductal adenocarcinoma and ovarian carcinoma, showing its suitability to evaluate tumor progression and to predict post-operative complications, as found in colorectal cancer [36,37]. ## 4. Methods and Materials Patient selection and clinical data. A total of 66 ($$n = 22$$ with MetS and $$n = 44$$ without MetS) consecutive patients diagnosed with primary iCCA who underwent percutaneous biopsy or laparoscopic liver resection from January 2006 to September 2020 were retrospectively included in this study. The exclusion criteria were as follows: neoadjuvant treatment, both systemic and/or locoregional; less than 3 months survival after surgery; and the absence of sufficient materials for additional immunohistochemical analyses. The inclusion criterion was the diagnosis of iCCA (small and large duct types) according to WHO classification 2019 [38]. Clinical and laboratory data, including gender, age, BMI, diagnosis of hypertension and diabetes, fasting blood glucose, percentage of glycated hemoglobin, serum triglyceride and HDL levels, and microalbuminuria and serum levels of alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen 19.9 (CA19.9) and total bilirubin at the time of surgery, were retrieved from medical records. The presence of any chronic liver or biliary disease, cirrhosis, and any adjuvant, systemic, and/or locoregional treatment was also recorded. For all patients, abdominal pre-surgery CT scans with staging ware recovered. Patients were followed up regularly by measuring serum tumor marker levels and performing CT to detect recurrence of the disease. CT scan evaluation. Analyses of “picture archiving and communication system” (PACS) were performed by using Somatom AS+ system (Siemens Healthineers, Erlangen, Germany). Acquisitions were performed at 100–120 kV with a pitch of 0.9–1.2 and slice thickness of 2 mm with 1 mm increment and automatic tube current modulation (unenhanced scans). Injected contrast medium, if necessary, was Accupaque 350 (GE Healthcare, Cork, Ireland). Complete abdominal scan from diaphragmatic pillars to small pelvis was performed. To avoid bias caused by biopsies or surgery, CT was performed before surgical intervention. Visceral fat volume measurements were performed by using Synapse 3D (Version 5.5.002, Fujifilm Corporation, Tokyo, Japan). The regions of interest (ROI), identifying the fatty tissue, were individuated by adjusting the density intervals from −200 to −50 HU. Histology and histological evaluation. All the slides were stained with hematoxylin–eosin and Masson’s trichrome (to evaluate fibrosis) and were revised in double-blinded methods by skilled pathologists specialized in liver diseases (S.S. and M.G.). All cases were classified according to the latest edition of the WHO classification of digestive system tumors [2019] [38]. Relevant histological features were recorded, including grade of tumor differentiation, T stage (according to the revised 8th edition of the UICC staging system) [20], margin status (for surgical resections), the presence of vascular and perineural invasion and lymph node metastasis, and the presence and extent of steatosis, nuclear glycogenosis, and hepatocyte ballooning in the adjacent liver. Considering all the different etiologies of liver disease included in the study, we evaluated fibrosis in a qualitative manner, as follows: 0, no fibrosis; 1, sinusoidal and perivenular (central) fibrosis only; 2, portal fibrosis only; 3, septal fibrosis; 4, cirrhosis. Immunohistochemistry. Tissue microarrays (TMAs) made of formalin-fixed paraffin-embedded iCCA tissue cores (with a diameter of 4 mm) were obtained by selecting two or three representative areas of tumor and adjacent liver tissue from each liver resection case, depending on tumor dimension. All of the samples were processed by using the TMA Master platform (3DHistech, Budapest, Hungary), a semi-automatic and computer-assisted TMA platform. Immunostains were performed on TMA and liver biopsy sections as follows: briefly, sections were deparaffinized in xylene (Carlo Erba, Milan, Italy) and rehydrated with absolute ethanol (Carlo Erba). Endogenous peroxidase activity was blocked by incubating for 15 min in methanol (Sigma-Aldrich, St. Louis, MO, USA) + $10\%$ hydrogen peroxide (Scharlau, Barcelona, Spain). Following appropriate antigen retrieval (a.r.), sections were washed with $0.05\%$ PBS + tween 20 (PBST, both Sigma-Aldrich) and incubated for 10 min at room temperature with Ultra Vision protein block (Thermo Scientific, Waltham, MA, USA) to inhibit non-specific reactions. Then, slides were incubated for 1 h at room temperature with the following antibodies: anti-K7 (clone OV-TL $\frac{12}{30}$ clone, Cell Marque; mouse monoclonal; working dilution 1:200; a.r. citrate pH6), anti-POSTN (Abcam, Cambridge, UK; rabbit polyclonal; working dilution 1:100; a.r. tris-EDTA pH 9.0), anti-TnC (Abcam, Cambridge, UK; rabbit polyclonal; working dilution 1:500; a.r. tris-EDTA pH 9.0), and anti-OPN (Abcam, Cambridge, UK; rabbit polyclonal; working dilution 1:1000; no a.r.). Sections were then washed with PBST and incubated for 30 min at room temperature with the appropriate conjugated HRP secondary antibody (EnVision, Agilent, Santa Clara, CA, USA). Slides were developed using 3,3’-diaminobenzedine tetrahydrochloride (DAB, Abcam, Cambridge, UK), counterstained with Gill’s Hematoxylin n°2 (Sigma-Aldrich, St. Louis, MO, USA) and mounted with Eukitt (Bio-Optica, Bologna, Italy). Immunohistochemical evaluations of DR, MHs, and ECM proteins. Presence and extent of DR was semi-quantitatively assessed by evaluating K7 staining by two experienced pathologists (S.S. and M.G.), as follows: 0, no DR; 1, DR in less than $50\%$ of portal tracts (PTs); 2, DR in at least $50\%$ of PTs; 3, DR in at least $50\%$ of PTs, with ductular buds extending into the peri-portal acinar parenchyma. The presence of MHs was evaluated as follows: 0, no MHs; 1, MHs around less than $50\%$ of PTs; 2, MHs around at least $50\%$ of PTs. The extent of matrix proteins (POSTN, TnC, and OPN) was evaluated as follows: 0, absence of staining; 1, focal staining, <$25\%$ of the stroma; 2, mild staining, between 25 and $50\%$ of the stroma; 3, diffuse staining, over $50\%$ of the stroma. Cell cultures. Human established CCA cell line HuCCT-1 (Health Science Research Resource Bank, HSRRB, Osaka, Japan) was grown by using RPMI 1640 supplemented with $10\%$ FBS and $1\%$ penicillin (all from Thermo Scientific, Waltham, MA, USA) at 37 °C in a $5\%$ CO2 atmosphere. Mycoplasma contamination was excluded by using a specific biochemical test (Lonza, Basel, Switzerland). Cell viability (MTS). Cell viability was evaluated by MTS (Promega, Madison, WI, USA) assay as suggested by the provider. To achieve that, 5 × 103 cells were seeded in a 96-well plate (Falcon, Glendale, AR, USA), starved for 24 h, and treated with medium supplemented with OPN (50 μg/mL, Prospec, Ness-Ziona, Israel) [39], POSTN (100 ng/mL, Sino Biological, Beijing, China) [31], and TnC (5 μg/mL, R&D Systems, Minneapolis, MN, USA) [40]. Cell migration (wound healing) assay. CCA cells were seeded in a 6-well plate, grown until confluence, and then starved for 24 h. Cells were treated as described above with OPN, POSTN, and TnC, and untreated cells were used as control. Each cell monolayer was scratched three times with a sterile p200 tip, and three micrographs were taken at $t = 0$ h for each wound. Then, on the same scratched area, micrographs were taken again at 2 h, 6 h, and 24 h to measure the area covered by the scratch, by using ImageJ software (NCBI). Values are expressed by normalizing each time point to $t = 0$ h. Real-Time PCR. 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--- title: Study of Potential Synergistic Effect of Probiotic Formulas on Acrylamide Reduction authors: - Siu Mei Choi - Hongyu Lin - Weiying Xie - Ivan K. Chu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003183 doi: 10.3390/ijms24054693 license: CC BY 4.0 --- # Study of Potential Synergistic Effect of Probiotic Formulas on Acrylamide Reduction ## Abstract Acrylamide (AA) is a food processing contaminant commonly found in fried and baked food products. In this study, the potential synergistic effect of probiotic formulas in reducing AA was studied. Five selected probiotic strains (*Lactiplantibacillus plantarum* subsp. plantarum ATCC14917 (L. Pl.), *Lactobacillus delbrueckii* subsp. bulgaricus ATCC11842 (L. B.), Lacticaseibacillus paracasei subsp. paracasei ATCC25302 (L. Pa), *Streptococcus thermophilus* ATCC19258, and *Bifidobacterium longum* subsp. longum ATCC15707) were selected for investigating their AA reducing capacity. It was found that L. Pl. ( 108 CFU/mL) showed the highest AA reduction percentage (43–$51\%$) when exposed to different concentrations of AA standard chemical solutions (350, 750, and 1250 ng/mL). The potential synergistic effect of probiotic formulas was also examined. The result demonstrated a synergistic AA reduction effect by the probiotic formula: L. Pl. + L. B., which also showed the highest AA reduction ability among the tested formulas. A further study was conducted by incubating selected probiotic formulas with potato chips and biscuit samples followed by an in vitro digestion model. The findings demonstrated a similar trend in AA reduction ability as those found in the chemical solution. This study firstly indicated the synergistic effect of probiotic formulas on AA reduction and its effect was also highly strain-dependent. ## 1. Introduction Acrylamide (AA) is a low-molecular-weight organic compound with high polarity and medium activity. It has been considered a neurotoxin and potential carcinogen (Class II) harmful to the human body [1]. AA is formed in food materials by the Maillard reaction when amino acid reacts with reducing sugar at high temperatures, such as in deep fried and baked products [2]. In 2002, Swedish researchers found that plant foods rich in carbohydrates and low protein are prone to produce AA under high-temperature (>120 °C) cooking processes such as frying and baking [3,4]. Under certain conditions, AA will also be produced during the Maillard reaction of non-enzymatic browning of carbonyl compounds (reducing sugars) and amino compounds (proteins, amino acids) [5,6]. The World Health Organization (WHO) and the United Nations Food and Agriculture Organization (FAO) Joint Expert Committee on Food Additives (JECFA) conducted a systematic assessment of the hazards of AA in food, warning of potential hazards to human health. The intake control is 0.001 mg/kg per day [7]. The formation of acrylamide in food is a complex multi-stage reaction process, and its formation mechanism is not completely clear. At present, it was proposed that the formation of acrylamide in food is related to the Maillard reaction of asparagine and reducing sugar under high-temperature conditions. Therefore, in addition to processing conditions, the existence and content of reducing sugars and asparagine in food materials are important factors affecting the formation of acrylamide [2,8,9]. Many studies found that controlling the processing technology, such as soaking raw materials in warm water or citric acid solution, can reduce the AA content in fried French fries [10]. Lowering the processing temperature and reducing the heating time can also reduce the amount of AA produced [11]. During processing, adding inhibitors, such as asparaginase and sodium chloride, can significantly inhibit the AA content in food [11,12,13,14]. A previous study showed that an effective way to reduce acrylamide formation in bread is by using selected lactic acid bacteria (LAB) strains for fermentation of dough [15]. The purpose of this experiment is to prove the potential synergistic effect of probiotic formulas on reducing AA content. In this research, representatives from three bacterial genera were evaluated, namely Lactobacillus, Bifidobacterium, and Streptococcus. They are the gut microbiota which can produce lactic acid and competitively inhibit the pathogenic organism [16]. The genus *Lactobacillus is* the largest genus of the LAB group traditionally associated with dairy products [17]. They can ferment carbohydrates, and together with Streptococcus thermophilus, they both act as major starter cultures in the dairy industry, while the addition of *Bifidobacterium longum* can improve the functional properties of fermented dairy products [18]. Besides the properties of promoting good digestion, boosting the immune system, maintaining a proper intestinal pH value, and competing with pathogens, there are several studies indicating the protective roles of LAB in mitigating the carcinogenic substances such as AA and aflatoxin B1 [19,20,21,22,23]. According to a recent review [23], mechanisms for reduction of AA can be proposed into two ways, one is the effect of asparaginase, and the other is substrate binding by probiotic bacteria. For the first mechanism, the AA formation can be inhibited by adding asparaginase in the raw material, reducing the content of asparagine and inhibiting the Maillard reaction. Thus, the amount of AA formed in the final product could be significantly reduced. This mechanism is applied to reducing AA formation during food processing, while the second mechanism can be applied in the post-processing stage to reduce AA after its formation. For the second mechanism, the cell wall component peptidoglycan plays an important role in AA reduction. The peptidoglycan can bind to the AA due to its high affinity to alanine. They bound AA via hydrogen bonding, holding AA on the surface of the LABs and stopping its further biotransformation in the body [24]. Besides the peptidoglycan, some research also reported that other components of the cell walls such as teichoic acid also help in AA mitigation [25]. Based on the cell wall-binding mechanism, the dead LABs also have potential in AA reduction. Due to the wide exposure route of AA, more studies are needed for a further investigation of the mechanism of AA reduction and to excavate its potential for AA detoxification in daily life. This study aims to examine the potential synergistic effect of AA reduction of LAB formulas which are commonly applied in dairy processing as starter cultures. The study first examined the AA reduction ability by a single strain of probiotic bacteria at different concentrations of AA chemical standard solution. Based on the results, five probiotic formulas were formed and their AA reduction ability was investigated. The probiotic formulas with the highest AA reduction ability were selected for further investigation in food samples and in an in vitro digestion model. ## 2.1.1. Acrylamide Reduction by Single Strains of Probiotic Bacteria As shown in Figure 1, L. Pa., L. Pl., B. L., and S. T. at a cell population of 109 CFU/mL demonstrated significant reduction abilities on AA when exposed to different concentrations of AA chemical solutions ($p \leq 0.05$). At the same cell concentration, the four strains showed different AA reduction abilities, ranging from $75\%$ to $89\%$ when exposed to the same concentration of AA (350 ng/mL). The data showed that L. Pl. demonstrated the highest AA reduction percentage among the tested strains. It was observed that L. Pl. showed the highest reduction percentages of $89\%$ and $67\%$ when exposed to AA solutions of 350 ng/mL and 750 ng/mL, respectively. These findings indicated that different bacterial strains have different AA reduction abilities. Hence, the AA reduction ability of probiotics is strain-specific. Similar results were also observed in a previous study [21]. In addition, the effect of different AA concentrations on the AA reduction ability of probiotics was also obtained. All tested probiotic strains showed an ability to reduce AA and the reduction percentage varied when exposed at different AA concentrations (Figure 1). The highest AA reduction ability was obtained when exposed to the low AA concentration of 350 ng/mL. As shown in Figure 1, L. Pa., L. Pl., B. L., and S. T. (109 CFU/mL) showed a significant reduction (p ≤ 0.05) in their abilities to reduce AA when the AA concentration was increased from 350 ng/mL to 750 ng/mL. Moreover, the AA reduction abilities of tested strains had significantly (p ≤ 0.05) declined when the AA concentration was further increased up to 1250 ng/mL. This result might be explained by the potential reduction mechanism of the probiotic, namely, the physical binding mechanism of the bacterial cell wall [23]. Peptidoglycan is the major cell wall mass of LAB. The structure of glycan chains of repeating N-acetylglusamine and N-acetylmuramic acid residues cross-link via the peptide side chain [26]. This physical binding mechanism was also applied in other toxic substances, such as polyaromatic hydrocarbon and mycotoxins, to explain the toxin-removing ability of LAB [27,28]. The physical binding effect was affected by several factors, including incubation time and toxin concentration. When the acrylamide concentration increased, the peptidoglycan cell wall tended to become saturated with AA and showed a decrease in the ability to remove AA [20]. The current study also demonstrated similar observations that can be explained by the physical binding mechanism. When the bacterial cell concentration was adjusted to 108 CFU/mL (Figure 2), L. Pl. demonstrated the highest AA reduction percentages (43–$51\%$) among the 5 tested probiotic strains when exposed to different AA concentrations of 350 ng/mL, 750 ng/mL, and 1250 ng/mL, respectively. As shown in Figure 2, it was seen that upon increasing the AA concentration, L. Pl. significantly (p ≤ 0.05) decreased its AA reduction abilities. *In* general, all selected probiotic strains exhibited AA reduction abilities at different AA concentrations. Different probiotic strains showed a different AA reduction performance. This may be explained by different probiotic strains functioning differently with variations in the contents of carbohydrates and certain amino acids of their bacterial cell wall [19,21]. As shown in Figure 1 and Figure 2, the selected *Lactobacillus genus* exhibited a more efficient AA reduction ability than two other genera under the testing conditions. L. Pl. yielded the best results, while L. B. and L. Pa. showed similar AA reduction abilities. Some previous studies indicated that the AA absorption effect was related to the roughness of the cell wall and the surface hydrophobicity [22], as well as the bonding interaction with the teichoic acid content of the cell wall [19]. Hence, the difference in the reduction ability of test strains is due to the difference in their cell wall composition. In addition, the percentage of AA reduction was increased when the probiotic cell concentration increased from 108 CFU/mL to 109 CFU/mL. With the 350 ng/mL AA solution, L. Pl. caused a dramatic increase in the AA reduction percentage from $51\%$ to $89\%$ when the cell concentration was increased from 108 CFU/mL to 109 CFU/mL. Similarly, with the 750 ng/mL AA solution, L. Pl. increased its AA reduction percentage from $43\%$ to $67\%$ when the cell concentration was increased from 108 CFU/mL to 109 CFU/mL (Figure 1 and Figure 2). Hence, the current results also demonstrated that the effect of AA reduction by probiotic bacteria is strain-, cell concentration-, and AA concentration-dependent. ## 2.1.2. Acrylamide (AA) Reduction by Probiotic Formulas in Chemical Solution Based on the results of the AA reduction, five probiotic formulas (108 CFU/mL) were formed to evaluate the potential synergetic reduction effect on AA. Due to the highest AA reduction ability, L. Pl. was selected and combined with the other strains. As shown in Figure 3, the results showed that different probiotic formulas had a significant effect on AA reduction when exposed to different AA solutions. The probiotic formula of L. Pl. + L. B. showed the highest AA reduction percentage among the selected formulas (Figure 3). The result also demonstrated a synergistic reduction effect on AA by this probiotic formula (L. Pl. + L. B.). Before combining with L. Pl., L. B. alone showed its AA reduction rate of $12\%$, $30\%$, and $32\%$ at 350 ng/mL, 750 ng/mL, and 1250 ng/mL, respectively. After combining with L. Pl., the AA reduction rate increased to $52\%$, $41\%$, and $41\%$ at 350 ng/mL, 750 ng/mL, and 1250 ng/mL, respectively. L. Pl. can hydrolyze asparagine, the precursor of acrylamide, to generate aspartic acid and ammonia, thereby inhibiting the formation of acrylamide to a certain extent [21]. The combination of probiotic strains also improved the efficacy on AA reduction. In the single-strain condition, S. T. showed a weaker reduction ability than B. L. However, a higher reduction ability was observed when S. T. was combined with L. Pl. when compared with B. L. combined with L. Pl., as shown in Figure 2 and Figure 3. The co-culture concept of different strains led to a surprising discovery, such as the new metabolites or the metabolism pathway modulation [29]. The combination of different probiotic single strains also showed its potential synergistic effect on acrylamide detoxification. However, this synergistic effect was also strain-dependent. The synergistic effect of combined probiotics was also reported in another study [30], which indicated the significant effects of combined probiotics to prevent colon cancer. According to previous findings [31], probiotics and their cell wall extracts could have anticancer ability, and the synergistic effect was found when probiotics were combined with other bio-functional compounds from cranberry juice. Another study [32] also found that the combination of prebiotics and probiotics had a synergistic effect because it promoted the growth of existing beneficial bacteria in the colon, and synbiotics also played a role in improving the survival, implantation, and growth of newly added probiotic strains in rats. One study showed that the probiotic efficiency of probiotic bacteria may be different if they were used in different hosts [33]. ## 2.2. Acrylamide (AA) Reduction by Probiotic Formulas in Food Matrices In this study, the AA content of the selected food samples, biscuits and potato chips, were detected as 55.1 ng/g and 217.0 ng/g, respectively. In Figure 4, the AA reduction ability of two probiotic formulas was investigated under two different food matrices (biscuits and potato chips). The AA content of the selected food samples was significantly reduced. The result showed that the percentage of AA reduction in biscuits was higher than that in potato chips by both probiotic formulas (L. Pl. + S. T. and L. Pl. + L. B.) at 108 CFU/mL. Similar to the results in chemical solution, the formula L. Pl. + L. B. showed the higher AA reduction ability. The AA reduction percentage by the formula of L. Pl. + L. B. was two times higher than that by L. Pl. + S. T. in both biscuit and potato chip samples. Different food compositions in food matrices may affect the effect of probiotics. Previous findings [22] suggested that increasing the roughness of cell walls and increasing the surface hydrophobicity of cells enhanced the adsorption ability of AA. Furthermore, the C-O, C=O, and N-H groups, which were related to the protein and peptidoglycan contents of the cell wall, were evidently involved in AA adsorption. Therefore, different AA reduction percentages by probiotic formulas were obtained in different food models. ## 2.3. Acrylamide (AA) Reduction by Probiotic Formulas in Food Matrices under In Vitro Digestion In Figure 5, the AA reduction ability of two probiotic formulas was further investigated in two different food matrices (biscuits and potato chips) under a simulated digestion model. Similar trends were obtained in food matrices with or without digestive conditions. The result showed that both probiotic formulas: L. Pl. + S. T. and L. Pl. + L. B. (108 CFU/mL), caused a higher AA reduction percentage in the biscuit food model under the digestive condition when compared with that in potato chips. To compare the efficacy of the probiotic formulas, L. Pl. + L. B. showed a higher AA reduction ability than L. Pl. + S. T. Based on the data, the AA reduction ability of probiotic formulas in food matrices was significantly increased under the in vitro digestion condition. In the potato chips model, the AA reduction percentage by L. Pl. + L. B. was increased from $14\%$ to $38\%$ under the in vitro digestion condition (Figure 4 and Figure 5). The use of in vitro simulated digestion model could be considered as a useful tool to estimate the bioavailability of acrylamide under testing conditions. It considered not only the influence of food intrinsic factors (structure, composition, nutrients’ interactions, etc.) but also extrinsic factors associated with the physiological process (gastric and intestinal pH, transit time, enzymatic activities, etc.) [ 25]. The current study may indicate the ability of probiotic formulas to reduce the bio-accessibility of food toxicants under digestive conditions. Previous studies also reported a similar toxin removal capacity of probiotic bacteria under a simulated digestion condition [34,35,36]. ## 3.1. Probiotic Strains and Culture Preparation Lactobacillus delbrueckii subsp. bulgaricus (ATCC® 11842™) (L. B.), Lacticaseibacillus paracasei subsp. paracasei (ATCC®25302™) (L. Pa.), *Lactiplantibacillus plantarum* subsp. plantarum (ATCC®14917™) (L. Pl.), *Streptococcus thermophilus* (ATCC®19258™) (S. T.), and *Bifidobacterium longum* subsp. longum (ATCC®15707™) (B. L.) were used. S. T. was activated in Brain Heart Infusion (BHI) (MEKESSON, Irving, USA) by aerobic cultivation, while the other four strains were activated by de Man Rogosa Sharpe (MRS) broth (Thermo Fisher Scientific Inc., Waltham, MA, USA) under anerobic cultivation. All the tubes were put into the anaerobic jar with an anaerobic atmosphere generation bag. The bacteria were activated in the incubator at 37 °C for at least 24 h to reach maximum growth. Subsequently, subcultures were performed prior to the experiment. For each subculture, an aliquot from the last subculture was added to 100 mL of sterile MRS broth and incubated at 37 °C for at least 24 h to achieve maximum growth. Optical density (OD600) of bacterial strains was measured by a UV-vis single-beam spectrophotometer to obtain the growth curves, and the pour plating method was used to determine the cell concentration (CFU value). All agar plates were incubated under 37 °C for 48 h. The number of colonies was counted for CFU determination. The bacteria were collected by centrifugation at 2100× g for 10 min and washed twice with sterile phosphate buffer saline (PBS) (Sigma-Aldrich, St. Louis, MO, USA). The pellets were re-suspended in sterile PBS to obtain the primary working cultures (109 CFU/mL). All prepared working cultures were temporarily stored at 4 °C prior to analysis [37]. ## 3.2. Reagents Methanol, hydrochloric acid (HCl, 1 M), sodium hydroxide (NaOH, 1 M), sodium chloride (NaCl), potassium chloride (KCl), sodium bicarbonate (NaHCO3), sodium dihydrogen phosphate (NaH2PO4), sodium sulfate (Na2SO4), potassium thiocyanate (KSCN), calcium chloride dihydrate (CaCl2∙2H2O), ammonium chloride (NH4Cl), potassium dihydrogen phosphate (KH2PO4), magnesium chloride (MgCl2), urea, uric acid, mucin, bovine serum albumin (BSA), pepsin, pancreatin, lipase, α-amylase, and bile were used. All reagents were of analytical grade and all organic solvents were of LC/MS HPLC grade, unless otherwise stated. Acrylamide standard (>$99.5\%$) and 13C3-acrylamide as internal standards (500 mg/L in acetonitrile) were purchased from Chem Service Inc. (West Chester, PA, USA) and Sigma-Aldrich (St. Louis, MO, USA), respectively. Oasis HLB cartridge (200 mg, 6 cc) was purchased from Waters Corporation (Milford, MA, USA) and Bond Elut Accuat cartridge (200 mg, 3 cc) was purchased from Agilent Technologies, Inc. (Santa Clara, CA, USA) [37]. The AA standard stock solution (1000 μg/mL) and 13C3-AA internal standard stock solution were prepared. A five-point calibration curve was constructed using the AA working solutions (30 to 500 ng/mL). Various concentrations of AA chemical solutions (350, 750, 1250 ng/mL) were prepared for the experiments on AA reduction ability. All standard solutions were prepared and stored at 4 °C. ## 3.3. Acrylamide Reduction Ability of Single Probiotic Strains and Probiotic Formulas in Standard Chemical Solutions Selected single probiotic strains (L. Pl., L. Pa.., L. B., S. T., B. L.) were incubated with various concentrations of AA chemical solutions under 109 and 108 CFU/mL cell concentrations. The mixtures were briefly vortexed and then incubated at 37 °C for 4 h (close to the total incubation time of the in vitro digestion model) with gentle rotation (55 rpm). After incubation, the mixtures were centrifuged at 20,000× g for 10 min at 25 °C. The content of AA in the supernatant was determined by LC-MS analysis, as described in Section 3.6. The AA reduction percentage of single probiotic strains was calculated. According to the performance of the single probiotic strains on AA reduction, the probiotic formulas (108 CFU/mL) were formed as below and the same procedures were applied to obtain AA reduction percentages of different probiotic formulas in chemical solutions. [ 1]*Lactiplantibacillus plantarum* ATCC14917 ($50\%$) + Lacticaseibacillus paracasei ATCC25302 ($50\%$) (L. Pl. + L. Pa.).[2]*Lactiplantibacillus plantarum* ATCC14917 ($50\%$) + *Lactobacillus bulgaricus* ATCC11842 ($50\%$) (L. Pl. + L. B.).[3]*Lactiplantibacillus plantarum* ATCC14917 ($50\%$) + *Streptococcus thermophilus* ATCC19258 ($50\%$) (L. Pl. + S. T.).[4]*Lactiplantibacillus plantarum* ATCC14917 ($50\%$) + *Bifidobacterium longum* ATCC15707 ($50\%$) (L. Pl. + B. L.).[5]Lacticaseibacillus paracasei ATCC25302 ($50\%$) + *Lactobacillus bulgaricus* ATCC11842 ($50\%$) (L. Pa. + L. B.). ## 3.4. Acrylamide Reduction Ability of Probiotic Formulas in Selected Food Matrices Potato chips and soda biscuits were selected as food samples. These two selected food samples were found to contain a relatively high AA content as AA were the common processing-induced contaminants formed during baking and frying production processes. According to the results of the AA reduction ability of probiotic formulas in part 1 (Section 3.3), two probiotic formulas with the potential synergetic effect were selected for further incubation in food samples. Spiked homogeneous food sample (1.0 g) and 0.5 mL of working cultures of probiotic formulas or PBS solution (control) were added to 4.5 mL of sterile PBS solution, incubating at 37 °C for 4 h with gentle rotation at 55 rpm. The resultant probiotic concentration remained at 108 CFU/mL. After incubation, the mixtures were centrifuged at 20,000× g for 10 min at 25 °C. The incubated samples were then centrifuged, and the supernatant was cleaned up by solid-phase extraction (SPE) and subjected to LC-MS analysis to determine the AA content. ## 3.5. Acrylamide Reduction Ability of Probiotic Formulas under In Vitro Digestion Model To determine the efficacy of probiotic formulas to reduce AA content in food matrices under a stimulated digestion condition, the procedures of Choi et al. [ 37] were followed. The samples for in vitro digestion were prepared as below. Here, 1 g of grounded food sample was added to 5 mL of PBS (control) or working cultures of selected probiotic formulas: [1] *Lactiplantibacillus plantarum* ATCC14917 coupled with *Lactobacillus bulgaricus* ATCC11842 and [2] *Lactiplantibacillus plantarum* ATCC14917 coupled with *Streptococcus thermophilus* ATCC19258 (108 CFU/mL). Digestive fluids (Table S1—Supplementary Materials) were added according to the volume ratio of 1 chemical solution/food:1.3 saliva:2.6 gastric juice:2.6 duodenum juice:1.3 bile:0.44 NaHCO3. All digestive fluids were adjusted to 37 ° C before use. Specifically, 1.3 µL of saliva was added to the mixture and the mixtures were incubated at 37 °C/55 rpm for 5 min in a shaking incubator. This was followed by the adding 2.6 mL of gastric juice and adjusting the pH of the mixtures to 2.5–3.0 with 1 M HCl or NaOH. The mixtures were then incubated at 37 °C and 55 rpm for 2 h. Next, 2.6 mL of duodenum juice, 1.3 mL of bile, and 0.44 mL of NaHCO3 (1.0 M) were added simultaneously, and the pH was adjusted to 6.5–7.0 with 1.0 M HCl or NaOH. Then, the mixtures were incubated at 37 °C and 55 rpm for 2 h. At the end of the digestion process (stomach or small intestine compartment), two aliquots from the upper part of the mixture were centrifuged at 20,000× g for 10 min at 25 °C. Finally, the resulted supernatants were cleaned-up by SPE using the same procedures in Section 3.4 and subjected to LC-MS analysis of AA. ## 3.6. Solid-Phase Extraction To extract AA from the food matrix, solid-phase extraction was used. The Oasis HLB cartridge (Water, Milford, MA, USA) was pre-conditioned with 3.5 mL of methanol followed by 3.5 mL of Milli-Q water, while Bond Elut Accuat cartridge (Agilent Technologies, Santa Clara, CA, USA) was pre-conditioned with 2.5 mL of methanol and 2.5 mL of Milli-Q water, sequentially. After that, 1.5 mL of the clear supernatant was loaded onto the HLB cartridge, followed by washing with 0.8 mL of Milli-Q water (all discarded). Then, the AA was eluted with 3 mL of $50\%$ methanol from the HLB cartridge to the Bond Elut Accuat cartridge. Finally, 25 μL of 13C3-AA (40 ng/mL, internal standard) was added to the 3 mL of effluents and then filtered through a 0.45 μm filter into a LC-MS vial for LC-MS analysis. The recovery rate of the two food samples was evaluated as:[1]Recovery rate (%)=Conc. of AA in spiked sample−Conc. of AA in non-spiked sampleConc. of spiked AA ## 3.7. LC-MS Method for the Analysis of Acrylamide The AA analysis was performed with an Agilent 1260 Infinity II LC-MS system coupled to an Agilent 6120 Single-Quad MS system (Agilent Technologies Inc., Santa Clara, CA, USA) with an electrospray-type ionization source. The column of the LC-MS system used was a Resiek Ultra AQ C18 column (3 µm, 100 mm × 2.1 mm) (Bellefonte, PA, USA). The sample was separated by the mobile phase (aqueous $0.2\%$ acetic acid and $1\%$ methanol) for 7 min at 0.200 mL/min with a 10 µL injection volume after 1 min post-time to equilibrate the column. The column oven temperature was set at 35 °C and the electrospray was operated in positive ion mode. The conditions used in the ionization source were: 250 °C at 12.0 L/min for the drying gas (N2), a nebulizer pressure of 35 psig, and a capillary voltage of 3000 V. AA was determined using the Selective Ion Monitoring mode (SIM), monitoring the ions m/z 72.0 for AA and 75.0 for 13C3-AA (internal standard). By using a five-point calibration curve, the concentrations of AA in the control and samples were determined and then the percentage of AA reduction was obtained using the following equation:[2]AA reduction (%)=Conc. of AA in control (PBS)−Conc. of AA in sampleConc. of AA in control (PBS) ## 3.8. Statistical Analysis Results are expressed as mean ± SEM. Statistical analyses were performed using SPSS Statistics 22. Results were considered statistically significant when $p \leq 0.05$ for specific p-values. ## 4. Conclusions This study demonstrated the AA removal ability of probiotic bacteria, whereby the reduction ability depends on the strains of single probiotic bacteria and probiotic formulas. The current findings showed a potential synergistic effect in some probiotic formulas which could enhance the efficacy of AA reduction. Among the tested probiotic combinations, the best probiotic formula was *Lactiplantibacillus plantarum* ATCC14917 ($50\%$) + *Lactobacillus bulgaricus* ATCC11842 ($50\%$) (L. Pl. + L. B.), which can cause a 41–$52\%$ AA reduction percentage in different AA chemical solutions. This formula also demonstrated its ability to reduce AA in both food samples of biscuits and potato chips with or without the in vitro digestion condition. 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--- title: Tannic Acid Tailored-Made Microsystems for Wound Infection authors: - Inês Guimarães - Raquel Costa - Sara Madureira - Sandra Borges - Ana L. Oliveira - Manuela Pintado - Sara Baptista-Silva journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003198 doi: 10.3390/ijms24054826 license: CC BY 4.0 --- # Tannic Acid Tailored-Made Microsystems for Wound Infection ## Abstract Difficult-to-treat infections make complex wounds a problem of great clinical and socio-economic impact. Moreover, model therapies of wound care are increasing antibiotic resistance and becoming a critical problem, beyond healing. Therefore, phytochemicals are promising alternatives, with both antimicrobial and antioxidant activities to heal, strike infection, and the inherent microbial resistance. Hereupon, chitosan (CS)-based microparticles (as CM) were designed and developed as carriers of tannic acid (TA). These CMTA were designed to improve TA stability, bioavailability, and delivery in situ. The CMTA were prepared by spray dryer technique and were characterized regarding encapsulation efficiency, kinetic release, and morphology. Antimicrobial potential was evaluated against methicillin-resistant and methicillin-sensitive *Staphylococcus aureus* (MRSA and MSSA), Staphylococcus epidermidis, Escherichia coli, Candida albicans, and *Pseudomonas aeruginosa* strains, as common wound pathogens, and the agar diffusion inhibition growth zones were tested for antimicrobial profile. Biocompatibility tests were performed using human dermal fibroblasts. CMTA had a satisfactory product yield of ca. $32\%$ and high encapsulation efficiency of ca. $99\%$. Diameters were lower than 10 μm, and the particles showed a spherical morphology. The developed microsystems were also antimicrobial for representative Gram+, Gram−, and yeast as common wound contaminants. CMTA improved cell viability (ca. $73\%$) and proliferation (ca. $70\%$) compared to free TA in solution and even compared to the physical mixture of CS and TA in dermal fibroblasts. ## 1. Introduction The skin wound healing process embraces a cascade of coordinated events after a skin injury, trauma, or laceration, which is followed by the natural regeneration of the skin’s protective barrier. In complex wounds, the healing process is characterized by a prolonged and sustained inflammatory phase that impairs dermal and epidermal cells from responding to chemical signals [1]. As a result, wounds are prominent to inflammation and, consequently, to oxidative stress that may lead to delayed or difficult-to-heal, infection, amputations, or even lethal septicemia [1,2]. The problem of complex wounds is thus serious, emerging, and global. In a retrospective analysis of Medicare beneficiaries in 2018, it was reported that 8.2 million people had complex wounds with/without infection, and the cost of wound treatment ranged from $28.1 billion to $96.8 billion. These rising health care costs, as well as the difficult-to-treat infections, make complex wounds a problem of great clinical and socio-economic impact [3]. The mechanisms of wound regulation are attributable to several mediators and many types of cells, including platelets, inflammatory cells, fibroblasts, keratinocytes, also cytokines, growth factors, and matrix metalloproteinases [4]. Any impairment of one of the stages of the normal healing process can cause delay or failure of skin repair. Therefore, the use of substances capable of accelerating healing internally and/or externally is as fundamental as necessary [1,5]. Nonetheless, classic therapies of wound care are increasing the antibiotic resistance and becoming a critical problem, beyond healing. Therefore, there is an emerging demand from researchers around the world to explore bio-based compounds with both antimicrobial and antioxidant activities to heal, strike infection, and fight the inherent microbial resistance. In this sense, plants represent a rich source of phytochemicals, which are more easily absorbed than synthetic drugs and are recognized as accessible treatment options that eliminate the restrictions associated with conventional therapies [6]. Additionally phytochemicals also control infection, inflammation, and the inborn oxidative processes [1], which is a vital phenomenon since the excessive free radical production in response to an injury may hamper the healing process by affecting proteins, lipids, and extracellular matrix elements [6]. Tannic acid (chemical formula C76H52O46) is a water-soluble polyphenol with antioxidant, hemostatic, anti-inflammatory, anticarcinogenic, and antimicrobial activities with low cytotoxicity [1,7]. Its promising properties allows it to be a potential efficient alternative to commercial antibiotics, responding to the need to find new options for wound care. Nonetheless, as a polyphenol, TA may have some drawbacks when targeting wound applications, such as low stability, weak bioavailability, light sensitivity, and consequent decreased biological performance at the wound site [8]. To overcome these limitations, polymeric-based systems (i.e., nano/microsystems, nanoemulsions, hydrogels, films) have been developed as carriers of polyphenols for wound healing, improving its stability, controlling the release kinetics, and therefore increasing the performance and effectiveness [9,10]. Chitosan is one of the most used natural polymers as coating materials as well as a common polymer used in microparticulate systems for skin wound dressing [10] and drug delivery [11], due to biocompatibility, biodegradability, antimicrobial activity, and hemostasis capacity [12,13]. Hereupon, it’s intended to design new CMTA, as a promising drug delivery system, capable of controlling oxidation and possible wound infection, thus promoting a faster and effective tissue regeneration. ## 2. Results and Discussion Chitosan-microparticles-loaded TA were characterized regarding their physicochemical properties, including the size, morphology, FTIR, and DSC analysis. To simulate wound delivery conditions and to predict the behavior of microparticles over a spaced period, until 24 h, a controlled release study of TA encapsulation was performed. Additionally, the product yield of the microencapsulation technique and the association efficiency of microparticles were also assessed. The biological in vitro profile as antioxidant, and antimicrobial systems, as well as the effect upon cell viability and proliferation, were also tested. ## 2.1.1. Product Yield Product yield of spray drying was calculated in order to predict the efficiency of the method in the production of CMTA. The product yield obtained for this process was $32\%$. Although product yield values of spray drying process may be higher than $50\%$, recent studies reported, for polyphenols encapsulation into CS microparticles by spray drying, values from $29.63\%$ to $57.3\%$ [14,15,16]. According to these works, product yield obtained is considered a satisfactory value for the laboratory scale and for the materials that were used. Besides the natural loss of final product associated with adherence of powdered microparticles to the cyclone walls, solid losses from small particles suctioned by the vacuum filter, and the inability of the separation devices to collect the smallest particles [16,17], the yield values might also be affected by the type of encapsulating material. During the microencapsulation process, the adherence of CS to the drying chamber wall was observed, probably caused by its natural viscosity. The viscosity of the initial solution should be the lowest possible to allow homogenous pumping of the solution and atomization [18]. In this sense, the CS chosen was the lowest molecular weight instead the medium molecular weight. Still its viscosity might not be the ideal for the spray drying process. Another way to control the physical properties can be related to the feed temperature: the higher the inlet temperature, the lower the viscosity of the solution and, consequently, the better the conditions to increase the yield value. However, higher values of that temperature may be responsible for degradation of some heat-sensitive compounds, like polyphenols (i.e., TA). Therefore, the choice of inlet temperature value was chosen according to the temperature that can be used safely without damaging the compound [19]. Besides the temperature, the pump rate can also significantly affect the yield of spray drying. According to Plamen D. Katsarov et al. [ 20], the lower the pump rate of CS solution, the higher the yield of the process, since the quicker the solution is sprayed, the more energy is needed to evaporate the solvent from the particles. Therefore, more experiments should be performed in order to increase the product yield of spray drying, regarding the encapsulation of TA, through the use of other inlet and outlet temperatures, the flow rate, and, consequently, the time of the spray drying process. ## 2.1.2. Particles Characterization: Size Distribution and Morphology Control of the size and morphology of microparticles is considered an indispensable analysis due to their influence in the sustained and controlled release of encapsulated agents and microparticles stability [21]. Results of size distribution in the number of CMTA microparticles are presented in Figure 1. The results showed that microparticles had a mean diameter of 7.4 μm. This result is concordant to the size of microparticles usually produced by spray drying (1–50 μm) [18,22]. The range of values between 25 μm and 53 μm showed to be discrepant results, probably due to an agglomeration zone of microparticles, as can be observed from the following SEM images (Section 2.3) [23,24]. Therefore, this range was not considered for the calculated mean of the size distribution. Particles with a relative low size value, within the micrometric scale have considerable advantages. In addition, despite the fact that microparticles provide a slower extracellular drug release due to a low surface-to-volume ratio, small sized particles may provide a larger surface area, improve the active compound penetration into wound bed, as well as promote intracellular uptake [25]. Therefore, it is believed that the size of obtained microparticles by spray drying is appropriate for wound care. ## 2.1.3. Fourier Transform Infrared Spectroscopy Depending on the structure of a compound, its functional groups produce characteristic absorption bands in the spectrum, which are analyzed by FTIR. With these bands, it is possible to draw conclusions about the possible chemical interactions, namely covalent bonds, between compounds. Therefore, FTIR analysis of CMTA, its substrates, and the physical mixture between CS and TA were measured. The results are presented in Figure 2. Chitosan displays a typical vibrational absorption band between 1595 and 1308 cm−1 that are attributed to the stretching of specific bonding of amides. However, the peaks presented on CS spectra are not defined, when compared to reported results. The C–O stretching was identified by the presence of peaks at 1057 and 1021 cm−1. At the end, the band located at 896 cm−1 is attributed to the stretching of the glycosidic bond [26,27]. Tannic acid spectra were consistent with values given by other studies [28]. Its FTIR spectrum exhibited characteristic bands of aromatic rings in the wavenumber range of 1445–1698 cm−1. The two bands around 1314 and 1180 cm−1 result from O–H and C–O stretches. The vibration of C=C in benzene rings was identified at 757 cm−1 [28]. Spectrum of CMTA microparticles showed that all the above characteristics are maintained at the same wavenumber, indicating no interaction between the drug and carrier. These results are concordant with a previous study [27]. Besides that, no new peaks appeared in the CMTA microencapsulation spectrum or in the physical mixture of the substrate, indicating that no new covalent bonds were detected from the CMTA production. Therefore, the integrity of TA is expected even after the microencapsulation process. ## 2.1.4. Differential Scanning Calorimetry Differential scanning calorimetry analyses were performed to provide information about physical and chemical changes of CMTA that involve endothermic and exothermic variations. The graphs of heat flow (J/g), depending on the temperature (°C) of CMTA and its substrates are illustrated in Figure 3. The results showed a broad endothermic band between 93.69 and 120.67 °C for CS and an exothermic peak 203.20 and 211.70 °C. As other previous studies reported, the endothermic peak, corresponding to a transition that absorbs energy, endorses the loss of water related to hydrophilic groups of CS [29]. Although CS was in powder form, it might have some associated humidity that gave rise to this peak. In turn, the exothermic one, corresponding to a transition that releases energy, is assigned to the thermal degradation of the polymer or melting transition temperature. That degradation may occur due to glycoside bond cleavage or monomer dehydration [29]. Thermogram of TA exhibited a very broad endothermic band at 96.07 °C, related to the evaporation of hydration water molecules, as reported from the literature [30]. Besides that, TA did not show any defined peak, which reveal that the phenolic compound is thermally stable from 25 to 230 °C. At the tested range of temperature, it was not possible to detect the band assessed to thermal degradation, but it was reported that the degradation of this phenolic compound occurs around 260 °C [27]. Chitosan microparticles loaded with TA displayed a sharper endothermic transition on the same values of CS thermogram, due to water that remains after the spray drying process. Its degradation temperature was not detected at tested temperatures, but it can be observed that possibly an exothermic peak would occur above 230 °C. According to Yingju Jing et al. [ 27], who studied the interaction between TA and CS to functionalize CS, the decomposition peak of TA with CS appeared around 280 °C. Therefore, more assays would be needed at a higher temperature range in order to understand when the degradation occurs. However, based on the obtained results, the interaction between TA and CS led to an increase in the thermal stability of microparticles compared to its substrates. ## 2.1.5. Association Efficiency Tannic acid association efficiency was 98.50 ± $0.02\%$. Recent studies showed values of AE ranging from 52.7 to $92.6\%$ for polyphenols encapsulated in CS microparticles by spray drying [14,15]. Therefore, AE of the microencapsulation process used in the present work is considered an excellent result when compared to reported values and considering the viscosity of the liquid feed caused by CS. Besides the properties of encapsulating material, pH upon microparticles formation could also have some influence on the AE values for encapsulation of TA in CS microparticles. Chitosan in acidic media can interact with negatively charged groups due to the protonation of chitosan amino groups. Therefore, the polyphenol and the polymer may interact with each other through bonding between hydroxyl groups (–OH) or carboxyl groups (–COO) of TA and hydroxyl (–OH) or amino groups (–NH3) of CS [31,32]. A possible interaction between TA and CS is illustrated in Figure 4. It is believed that there is a higher tendency of interaction with –NH3 because, for CS in acidic media, the positive regions concentrate on the protonated amino group [31,32]. Since that reversible interaction through noncovalent bonds is stronger with lower pH values, it is expectable that the acidic media of feed solution, as well as the low molecular weight of CS, are conditions that may positively influence the amount of TA in CS microparticles produced by spray drying [24]. ## 2.1.6. In Vitro Release of Tannic Acid from Chitosan Microparticles The controlled release of TA was evaluated in physiological conditions to assure the desirable time and rate in wound bed. Topical delivery conditions were simulated in PBS over 24 h. Results showed a controlled release profile. The release of the core material depends on the type of the encapsulated material, the core-to-coating proportion, as well as the environment where microparticles will be implemented [24]. The peak of TA (6.611 min) was similar to values reported on the study which describes the method used of TA detection [33]. The quantification of the phenolic compound was quick and easily performed. According to obtained results 0.77 ± $0.002\%$ of the total encapsulated TA was released on the first time point (T0 h), and 0.77 ± $0.003\%$ on the following 24 h (T24 h). The amount of released TA was practically the same (≈$0.8\%$) during the first 24 h. Results seem to indicate that, probably, the TA content entrapped in the core of the particles was not successfully released in 24 h. Although further testing would have to be done to secure this premise, a possible justification for the obtained values may be related to the amount of TA that can remain on the microparticles surface after the spray drying process [24]. In other words, the amount that was read in HPLC might be the portion of polyphenol in the microparticles’ surface, which means that the microsystem did not even depredate to release TA. The non-degradation of microparticles might be associated with the conditions of the release medium, in particular alkaline pH values of PBS. According to Neculai Aelenei et al. [ 34], the release of TA is significantly lower in pH values higher than 7.4 such as PBS, due to the partial insolubility of CS in an alkaline medium. However, in acidic medium, more than $90\%$ of the encapsulated TA is released during the first 20 h. The pH values of diabetic wound/chronic wounds are typically alkaline (from 7.2 to 8.9), which hinder the healing process and create a great environment for the growth and multiplication of bacteria [35]. In contrast, lower pH values on the chronic wound surface provide an acidic environment, which helps the wound healing by controlling wound infections [36]. In this sense due to the alkaline pH of complex wounds, the TA release is expected to be slow over time. In a clinical point of view, this lagging release may allow its bioactivity control for 2 to 3 days, until the wound dressing is replaced by medical or nursing services. This may represent a time-regulated regeneration and infection control. Nonetheless, the chronic wound environments are also characterized by containing degradative enzymes, for instance, lysozymes or proteases [37]. These enzymatic phenomena may promote a fast release of TA entrapped within the core of CS particles, due to an erosion of the encapsulating material (CS) [38]. Therefore, and regardless the slow kinetic profile of TA in this assay, it is believed that a fast release could happen in situ, by the enzymatic and inflammatory cascade typical in the wound bed [39]. Once more and to guarantee the veracity of the obtained results, more studies and tests should be done. Further experiments could be done on the studied CS particles to simulate enzyme degradation in PBS, using Protease XIV from *Streptomyces griseus* at a concentration of 3.2 U/mg and temperature (37 °C), according to previous works [40]. ## 2.2.1. Antioxidant Activity Evaluation The antioxidant activity of TA free in solution and encapsulated into CS microparticles was analyzed using the ABTS radical scavenging assay. In addition, antioxidant activity of CS and CMTA were also evaluated. The results are present in Table 1. All samples were analyzed in $1\%$ (w/v). As a polyphenol and, consequently, a powerful antioxidant compound due to its abundant phenolic hydroxyl groups, the best antioxidant activity results (917.9 ± 33.0 eq. [ Trolox] µmol/g) were obtained for TA ($1\%$) free in solution. As expected, CS had a much lower antioxidant activity due to its insufficient H-atom donors (160.0 ± 10.2 eq. [ Trolox] µmol/g) [27]. Comparing to TA free in solution, encapsulated TA showed a significant reduction of antioxidant activity (832.2 ± 80.8 eq. [ Trolox] µmol/g), certainly caused by the entrapment of the polyphenol into the microparticles. However, the microencapsulation of TA does not eliminate its antioxidant activity, which is concordant with a previous study related to the microencapsulation of polyphenols using CS as a microcarrier [15]. Despite that significant decay, antioxidant activity of CMTA is still high when compared to TA free in solution, probably due to the amount of TA that remained on the microparticles surface after the spray drying process. ## 2.2.2. Antimicrobial Potency Agar diffusion method was used to analyze the antimicrobial activity of TA, CMTA, CS, and acetic acid qualitatively against all six studied microorganisms: MRSA, MSSA, S. epidermidis, E. coli, P. aeruginosa, and C. albicans. All the results are plotted in Table 2, where the standard deviation was calculated from the triplicates performed for each experiment. The obtained values demonstrated that TA was able to inhibit all Staphylococcus spp. strains (i.e., MRSA, MSSA, and S. epidermidis) from the concentration of 2 mg/mL. Furthermore, TA had shown an inhibition zone against E. coli and C. albicans, also at a concentration of 2 mg/mL. It is possible to observe that, in most cases, the higher the concentration of TA, the higher the diameter of the inhibition zone. However, the phenolic compound was not able to inhibit the growth of P. aeruginosa. There are different mechanisms proposed to justify tannins’ antimicrobial potential, such as changes in the intracellular functions caused by hydrogen binding of tannins to enzymes, what leads to an extracellular enzyme inhibition and unavailability of substrates for digestion [41]. However, it was shown that the primary site of their inhibitory action is the microbial cell membrane through morphological changes of the cell wall by interaction with proteins, which lead to their precipitation and, consequently, an increase of the membrane permeability and microorganism death [41,42]. The different behaviors of polyphenols between Gram+ and Gram- are still a controversial issue. It is known that the cell wall is mainly composed of peptidoglycan [43]. Results from a study from Guofeng Dong et al. [ 43] revealed that TA can link to peptidoglycan of the cell wall, and it may inhibit the formation of the biofilm. However, a Gram- bacterium has an outer membrane layer composed by lipopolysaccharide molecules and phospholipid that is external to the peptidoglycan cell wall. It was proven that Staphylococcus spp. was more susceptible to tannins than P. aeruginosa due to the lipopolysaccharide molecules negatively charged on the outer membrane. Therefore, normally, tannins have been more effective against Gram+ bacteria than Gram-, which is concordant with the obtained results [43,44,45]. These are the most prevalence of microorganisms in diabetic foot ulcers. The polyphenol and CS were able to kill both S. aureus. Antimicrobial activity of CS against S. aureus was already reported. Its main underlying mechanism is related to the linkage of positive charged amino groups (NH3+) and the negatively charged molecules such as proteins, anionic polysaccharides, and nucleic acids in bacterial membrane, leading to altered membrane permeability with the release of cellular contents, causing cell death. Relatively to encapsulated TA, CMTA also showed inhibitory activities against MRSA and MSSA at 6 mg/mL due to a possible synergy between the of CS with the possible released TA caused by hydration of microparticles. The synergy between antimicrobial activity of CS and antimicrobial activity of certain polyphenols, such as caffeic acid, ferulic acid, and hydroxycinnamic acid were already studied and validated [46]. These results are in accordance with previous studies regarding nanofibrous scaffolds of CS and TA that exhibited excellent antibacterial activity against MSSA and *Escherichia coli* [47]. A hydrogel containing polydopamine/TA/CS/poloxamer hydrogel also showed promising in vitro antibacterial results with bactericidal rates against MSSA and *Escherichia coli* under Near-infrared irradiation (NIR) irradiation of $99.994\%$ and $99.91\%$, respectively [48]. ## 2.3. Biocompatibility of Tannic Acid and Chitosan Microparticles Loaded Tannic Acid in Primary Human Dermal Fibroblasts In order to evaluate the biocompatibility of CMTA particles, the cytotoxic and proliferative effects were tested in vitro using primary HDF cells. After 24 h of treatment, our results, as depicted in Figure 5, show that free TA presents cytotoxicity (21.39 ± $1.91\%$) and inhibits the proliferation (22.35 ± $0.55\%$) of dermal fibroblasts. This effect was minimized once TA is combined with CS solution (CS+TA) and even more reduced in CMTA (72.50 ± $6.51\%$) for viability assay and (70.08 ± $9.28\%$) for cell proliferation, when compared to untreated cells (control group). Since the inhibitory effect is around $30\%$, it is considered to be clinically acceptable, according to EN ISO 10993-5. The antiproliferative effect of TA is already documented in the literature in vitro and in vivo. Pattarayan and colleagues [49] studied TA, using a mouse embryonic fibroblast cell line and denoted an inhibitory effect on cell viability, in concentrations higher than 10 µM. The authors also described an inhibition on fibroblast proliferation and cell cycle arrest, under tissue growth factor (TGF)-β1 stimulation, pointing out a therapeutic role for TA in preventing pathological fibrosis. Adhesiveness and physiochemical characteristics of an enzymatically crosslinked hydrogel based on chitosan and alginate after TA post-treatment, also revealed significantly high adhesive strength (up to 18 kPa), storage modulus (40 kPa), and antioxidant activity (>$96\%$), antibacterial activity, proliferation, and viability of 3 T3-L1 fibroblast cells [50]. A pre-clinical study [51] described a cardioprotective effect of TA in a mouse-induced model of cardiac fibrosis, possibly through the suppression of toll like receptor 4 (TLR4)-mediated nuclear factor kappa B (NF-κB) signaling pathway. Fibrosis is a common complication after a skin injury, especially in chronic wounds, suggesting that CMTA could be topically applied as a debridement product, to exert antioxidant effect, control infections and prevent fibrosis at the wound site. ## 2.3.1. Particles Morphology with Cells In order to evaluate the effect of CMTA on primary HDF cells morphology, SEM analysis was performed, and the images are presented in Figure 6. CMTA microcapsules (control without cells) were also viewed and showed to be polydisperse, with a particle size ranging between 2 and 10 μm with no relevant differences, which was in accordance with size measurements presented in Section 2.3.1. The CMTA exhibited a spherical shape with some concavities on the outer surface. The observed tendency to agglomerate was expected due to the microencapsulation process used [24]. According to some studies, the type of morphology obtained for powdered microparticles, also called “raisin-like”, is typical for CS microparticles as well as for CS microparticles-loaded polyphenols produced by spray drying [15,52,53,54]. This roughness and recesses of particles may be caused by the rapid evaporation of drops of liquid during the drying process in the atomizer, and even by the interaction of amino groups of CS (positively charged groups) within the polymer itself [15,55]. Traditionally, the surface of microparticles is normally smooth, but, although there is little information about the impact of the surface on the release efficacy, it is believed that a rough surface with some concavities might be favorable for tissue healing and cell growth due to the similarity of its structure to the extracellular matrix network as well as to a strong surface adhesion [56]. Therefore, regardless how the microparticles would be applied in practice, collapsed, or swelled, their morphology in both cases can be considered appropriated for wound application. In these SEM micrographs, the beneficial effect of the encapsulation of TA in CS particles can be verified by the adequate adaptability of HDF cells in morphology and proliferation, after contact with CMTA in comparison with both free TA in solution and even with physical mixture with CS. This demonstrates the beneficial protective effect of the particle, as well as its prolonged release profile. The results are in agreement with previously above-mentioned cell culture assays and with other TA reports [49,51]. ## 3.1. Standards All standards and reagents, including TA powder, CS of low molecular weight with a viscosity lower than 100 mPa·s and a deacetylation degree of $85\%$, acetic acid, 2,2-azinobis (3-ethyl-benzothiazoline-6-sulforic acid) and ethanol ($96\%$) were obtained from Sigma-Aldrich (St. Louis, MO, USA). For HPLC analysis, methanol ($100\%$) was obtained from VWR International (Radnor, PA, USA). Ultrapure water was obtained in the laboratory using Milipore Mili-Q water purification equipment (Millipore, Bedford, MA, USA). ## 3.2. Microbial Strains and Inoculum Preparation for Antimicrobial Experiments Stock cultures, including methicillin-resistant *Staphylococcus aureus* (MRSA), methicillin-sensitive *Staphylococcus aureus* (MSSA), Staphylococcus epidermidis, Escherichia coli, Candida albicans, and Pseudomonas aeruginosa, were used for antimicrobial activities evaluation of TA free in solution and in CMTA. Test organisms were first activated from glycerol by transfer in nutrient broth at 37 °C for 24 h, then streaking on Mueller–Hinton agar (MHA) (Sigma-Aldrich, USA). A single pure colony was streaked on MHA and incubated at 37 °C for 24 h. Then the concentrations of microorganisms were adjusted with the turbidity of 0.5 McFarland (equal to 1.5 × 108 colony-forming units (CFU)/mL). Turbidity of the microbial suspensions were prepared in sterile saline solution and measured at 600 nm using a mini 1240 UV-Vis spectrophotometer (Shimadzu Corp., Kyoto, Japan), followed by the experiment. ## 3.3. Preparation of Chitosan Microparticles Loaded Tannic Acid Chitosan solution was prepared with a concentration of $1\%$ (w/v) in an aqueous solution of $1\%$ (v/v) acetic acid. Tannic acid solution of $6\%$ (w/v) was mixed with CS solution in a proportion of 1:5 (v/v). Mixture solutions were prepared with deionized water at room temperature and homogenized, protected from light, for 1 h before the spray-drying procedure. Microencapsulation was performed using a BÜCHI mini spray dryer B-191 (Buchi, Barcelona, Spain). The mixture was fed into the spray dryer under the following conditions: inlet temperature, flow rate, as well as air pressure were, respectively, set at 115 °C, 3.90 mL/min ($17\%$), and 6 bar [15]. The solution was dispersed into fine droplets through a 0.7 mm nozzle. The outlet temperature was kept at 60 °C to preserve the stability of the compounds. The dried powder was collected and stored protected from light in a desiccator. A schematic illustration is presented in Figure 7. ## 3.4.1. Product Yield Product yield (%) was calculated for microencapsulation experiment and was expressed as the ratio of the mass of powder collected after drying to the content of the initial infeed solution (Equation [1]). [ 1]Product yield %=Mass of powder obtained at the spray dryerMass of the initial feed solution×100 ## 3.4.2. Particle Characterization: Size Distribution Particle size distribution was measured by Coulter-LS 230 particle size analyzer (Beckman Coulter Inc., Miami, FL, USA). Before the analysis, suspensions were prepared in water by adding $0.1\%$ (w/v) of powdered microparticles, following by vortexing. The particles were characterized considering a number distribution. Three replicates were performed. Size distribution was expressed in terms of the mean diameter. ## 3.4.3. Fourier-Transform Infrared Analysis Fourier-transformed infrared analysis (FTIR) was used to evaluate the structure of TA, CS, and CMTA. The structure is generally interpreted through absorption bands based on the specific vibration of the chemical bonds of each substance. Infrared spectroscopy analysis was performed in a Spectrum 100 FTIR spectrometer equipped with a horizontal attenuated total reflectance sampling accessory (PIKE Technologies, Scientific Products, Pleasantville, NY, USA), the Horizon MBTM FTIR software, and a diamond/ZnSe crystal. All spectra were acquired using 16 scans and a 4 cm−1 resolution in the region of 4000–600 cm−1. In addition, baseline, point adjustment, and spectra normalization were performed. ## 3.4.4. Differential Scanning Calorimetry The thermal analysis of TA, CS, and CMTA were performed using a differential scanning calorimetry—DSC (Shimadzu DSC 60, Scientific Instruments, Columbia, MD, USA). A 5.0 mg portion of each sample was crimped in a standard aluminium pan and heated from 25 to 230 °C at a constant heating rate of 10 °C/min under constant purging of nitrogen at 20 mL/min. ## 3.4.5. Association Efficiency Association efficiency (AE) was evaluated considering the amount of TA associated with the microparticles. The AE was measured by the difference between the total TA used to prepare the particles and the amount of residual TA in the solution immediately after dispersion of the particles in water [57]. The AE of TA was obtained according to the following expression (Equation [2]):[2]AE (%)=Total amount of TA−Free amount of TA in supernatantTotal amount of TA ×100 ## 3.4.6. In Vitro Release of Tannic Acid from Chitosan Microparticles The release of TA from CMTA was tracked to predict the diffusion and kinetic behaviour of the microsystems, and it was tested in simulated physiological environment. For this purpose, $0.1\%$ (w/v) of CMTA were suspended in phosphate-buffered saline (PBS), and transferred to clean Eppendorf tubes, followed by placement in a water bath at 37 °C under stirring [57]. PBS was used to simulate physiological conditions at pH 7.4, and its ionic strength was 0.075 M, which is in the optimal range for physiological environment proof-of-concept testing and characterization. Aliquots were collected from the bath over time (0 min, 30 min, 1 h, 2 h, 4 h, 6 h, 8 h, and 24 h) and centrifugated at 14,000 rpm for 5 min (BOECO, Hamburg, Germany). After centrifugation, supernatants were analysed by high performance liquid chromatography (HPLC) to calculate the amount of TA released from the microparticles over the specified time. The quantification was performed by HPLC using the following described method. ## 3.4.7. High Performance Liquid Chromatography Analysis and Tannic Acid Quantification Chromatographic analysis was performed using the Waters Alliance e2695 Separate Module HPLC. The results were acquired and processed with Empower® 3 Software 2010 for data acquisition (Mildford, MA, USA), on an Ace® Equivalence 5 C18 column (250 × 4.6 mm i.d.). The conditions of HPLC analysis were applied according to a method already tested and validated for chromatograms determination of standard phenolic compounds, namely TA, the retention time of which was 4.974 min. The mobile phase was composed of two solvents: Solvent A (acetic acid in water (1:25 (v/v)) and Solvent B (methanol), at a flow rate of 0.8 mL/min. The injection volume was 20 μL, and the detection wavelength was 280 nm. The gradient program was begun with $100\%$ of Solvent A and was maintained at that concentration for the first 4 min. For the next 6 min, B decreased to $50\%$ and increased to $80\%$ for the next 10 min. At the last two minutes, B reduced to $50\%$ again. Stock standard solutions of TA (10 mg/mL) were prepared and used to construct the calibration curve (R2 = 0.9983), composed of six standard concentrations of the phenolic compound: 0.02, 0.05, 0.1, 0.2, 0.3, and 0.5 mg/mL. ## 3.5.1. Antioxidant Activity Assessment The ABTS ((2,20-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt) radical scavenging assay was used to estimate the antioxidant capacity of the encapsulated TA in a 96-well microplate. This method is based on the ability of the antioxidant compounds in solution to capture the ABTS∙+ cation, obtained by the reaction between ABTS and potassium persulfate. The working solution was prepared by mixing 10 mL of the stock solution of 7.4 mM ABTS aqueous solution and 10 mL of 2.45 mM potassium persulfate aqueous solution. The mixture was allowed to react for 16 h at room temperature in the dark. The antioxidant potential was measured according to the percentage inhibition, which was between 20 and $80\%$ after 6 min of the reaction between diluted ABTS and the sample [58]. Three sample replicates were performed for each sample: $1\%$ (w/v) of TA, CS, and CMTA. The absorbance was measured using a multidetection plate reader at a wavelength of 734 nm (Synergy H1, Winooski, VT, USA). The percentage of inhibition was then estimated using Trolox (6-hydroxy-2,5,7,8-tetramethylchromane-2-caboxylic acid) [25–175 M] as a standard curve. The result was expressed as equivalent concentration of Trolox (in µmol/g), using the calibration curve. ## 3.5.2. Antimicrobial Potential Antimicrobial activities of TA, CS, CMTA, and acetic acid were evaluated using a well diffusion method on MHA. The inhibition zones were reported in centimeters (cm). MRSA, MSSA, S. epidermidis, E. coli, C. albicans, and P. aeruginosa were used as references for the antimicrobial assay. Mueller–Hinton agar plates were inoculated with microbial strain under aseptic conditions, and 20 µL of the test samples were placed and incubated at 37 °C for 24 h. After the incubation period, the diameter of the growth inhibition zones was measured and compared. ## 3.6.1. Cells Primary human dermal fibroblasts (HDF; ATCC - American Type Culture Collection, Manassas, VA, USA) were cultured in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with $10\%$ (v/v) FBS (Invitrogen Life Technologies, Paisley, UK) and $1\%$ (v/v) penicillin/streptomycin (Invitrogen Life technologies, UK). All experiments were performed between passages 6 and 10. Tannic acid, CS, and the physical mixture between CS+TA, and the CMTA all at $1\%$ (w/v), were dissolved in cell culture medium. Controls were performed using cell culture medium. Cells were maintained at 37 °C in a humidified $5\%$ CO2 atmosphere. ## 3.6.2. MTT Viability Assay HDF (1 × 105 cells/mL) were allowed to grow until 70–$90\%$ confluence and then incubated with each treatment for 24 h. Cellular viability was assessed using MTT reagent, according to the instructions provided by the manufacturer. Optical density was measured at 470 nm in a microplate reader (Synergy H1, Winooski, VT, USA). Results are expressed as percentage of control, which was considered to be $100\%$. ## 3.6.3. BrdU Proliferation Assay HDF (1 × 105 cells/mL) were allowed to grow until 70–$90\%$ confluence and then incubated with each treatment for 24 h. Cells were incubated with a 5′-bromodeoxyuridine (BrdU) solution and then in situ detection was performed using an in situ detection kit (Roche, Amadora, Portugal), according to manufacturer’s instructions. Optical density was measured at 550 nm in a microplate reader (Synergy H1, Winooski, VT, USA). Results are expressed as percentage of control, which was considered to be $100\%$. ## 3.6.4. Particles Morphology and Interaction with Cells Scanning electron microscopy (SEM) was used to assess the morphology of the HDFs when exposed to the different treatments (CM, TA, CMTA, physical mixture of the two components of CMTA, CS, and TA). Briefly, after 24 h of treatment, all samples were washed twice with PBS 1×, fixed for 30 min at room temperature with a $2.5\%$ glutaraldehyde and washed twice with ultrapure water. Samples were then dehydrated in a graded series of ethanol (from $10\%$ to $100\%$) and immersed in hexamethyldisilazane (HMDS). After 5 min, samples were dried under a nitrogen airflow, mounted on aluminium stubs with carbon tape, sputter- coated with a gold/palladium alloy, and viewed using Phenom Pro Desktop SEM (Thermo Scientific, Eindhoven, Netherlands). SEM was operated using the secondary electron detector (SED) with an electron beam of 5 kV and magnifications of 700× (cell culture samples) and 4000× (particle morphology assessment). ## 3.7. Statistical Analysis Every assay was performed at least in three independent experiments. Statistical analysis was performed using IBM®SPSS®Statistics software, version 20.0. In order to evaluate the differences in antioxidant levels of TA, CS, and CMTA, t-student test was used. Statistical significance of different groups was evaluated by ANOVA followed by the Dunnett post-hoc test. Differences were considered to be significant at a level of $p \leq 0.05.$ ## 4. Conclusions There is an emerging demand from researchers around the world to explore natural, biodegradable, and ecological solutions as potent alternatives to conventional antibiotics. In this work, CMTA were designed for the first-time loaded TA, by spray-drying without resorting to other harmful reagents. This method represents an automated and scalable system with green and natural reagents. The systems proved to be promising for wound healing and in TA bioavailability protection. CMTA proved to be a sustained release system, with antioxidant, regenerative, and inflammation control properties and with surprising antimicrobial potential. 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--- title: Vitamin D, a Regulator of Androgen Levels, Is Not Correlated to PSA Serum Levels in a Cohort of the Middle Italy Region Participating to a Prostate Cancer Screening Campaign authors: - Felice Crocetto - Biagio Barone - Giulio D’Aguanno - Alfonso Falcone - Rosamaria de Vivo - Monica Rienzo - Laura Recchia - Erika Di Zazzo journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003229 doi: 10.3390/jcm12051831 license: CC BY 4.0 --- # Vitamin D, a Regulator of Androgen Levels, Is Not Correlated to PSA Serum Levels in a Cohort of the Middle Italy Region Participating to a Prostate Cancer Screening Campaign ## Abstract Prostate cancer (PCa) is the most common non-cutaneous malignancy in men worldwide, and it represents the fifth leading cause of death. It has long been recognized that dietary habits can impact prostate health and improve the benefits of traditional medical care. The activity of novel agents on prostate health is routinely assessed by measuring changes in serum prostate-specific antigen (PSA) levels. Recent studies hypothesized that vitamin D supplementation reduces circulating androgen levels and PSA secretion, inhibits cell growth of the hormone-sensitive PCa cell lines, counteracts neoangiogenesis and improves apoptosis. However, the results are conflicting and inconsistent. Furthermore, the use of vitamin D in PCa treatments has not achieved consistently positive results to date. In order to assess the existence of a correlation between the PSA and 25(OH)vitamin D levels as widely hypothesized in the literature, we analyzed the serum PSA and 25(OH)vitamin D concentration on a cohort of one hundred patients joining a PCa screening campaign. Additionally, we performed medical and pharmacological anamnesis and analyzed lifestyle, as sport practice and eating habits, by administering a questionnaire on family history. Although several studies suggested a protective role of vitamin D in PCa onset prevention and progression, our preliminary results revealed a clear absence of correlation between the serum vitamin D and PSA concentration levels, suggesting that vitamin D has no impact on PCa risk. Further investigations enrolling a huge number of patients are needed with particular attention to vitamin D supplementation, calcium intake, solar radiation that influences vitamin D metabolism and other potential indicators of health to confirm the absence of correlation observed in our study. ## 1. Introduction Prostate cancer (PCa) is the third most commonly diagnosed cancer in men, with an estimated 1.4 million diagnoses worldwide in 2021, and it represents the fifth leading cause of cancer death [1,2]. Several risk agents, including genetic factors, elderly, ethnicity, high testosterone levels and lifestyle play a pivotal role in PCa onset [3]. The PCa incidence varies among different geographical areas, showing a high incidence in developed and industrialized countries. The geographical differences are linked to disparities in screening tests frequency and potency among countries with a different development level [4]. In addition, it has been estimated that PCa incidence augments with the increasing age of the patients: all-age incidence is 31 per 100,000 males, with a lifetime cumulative risk of $3.9\%$ and, more than one in four men over 75 years is affected by PCa [5,6]. Prostate-specific antigen (PSA) is a glycoprotein secreted exclusively by prostate epithelial cells [7]. A PSA blood test represents the first step to evaluate suspicious PCa. Serum PSA testing is an early, comfortable and relatively inexpensive marker. However, since PSA is produced by both benign and malignant prostate epithelial cells, this serum marker shows limitations as a screening test for PCa. An elevated serum PSA level, indeed, can be detected in several not-malignant conditions, including prostatitis and benign prostatic hyperplasia (BPH) [8]. Furthermore, the PSA cut-off level is still not standardized, and despite its role as a PCa independent predictor, its use alone could be misleading, conducting to unnecessary biopsies [9,10,11,12]. The low PSA serum level specificity prompted the evaluation of additional markers of PCa risk. In this scenario, several years ago, researchers proposed the use of PSA velocity, considering that men with PCa show a more rapid rate of increase in PSA levels than those without PCa [13]. Recently, liquid biopsy has been proposed as a novel tool for cancer diagnosis and follow-up. It could be speculated that in the next few years, PCa diagnosis could be revolutionized by integrating novel, accurate and specific diagnostic markers with PSA serum level [14,15]. In recent years, a great enthusiasm on the potential vitamin D role in cancer prevention has been registered. It has been hypothesized that high vitamin D levels could counteract indolent PCa progression, considering that African-Americans show low vitamin D levels and high risk of advanced PCa. However, even if racial disparities among vitamin D and PSA levels were reported in the literature, the topic is still controversial, with unclear results in intervention studies [16,17]. Vitamin D bioavailability depends not only on diet and supplement use but also skin biosynthesis in response to ultraviolet B radiation exposure. Accordingly, countries with varying sunlight exposure show a high PCa incidence, whereas increased sun exposure has been suggested to decrease the advanced PCa risk [18,19,20]. In addition to the well-established vitamin D role in calcium homeostasis, it has been demonstrated that vitamin D exerts anti-cancer effects, counteracting inflammation and angiogenesis, and promoting apoptosis [21,22]. PCa tissue and cell lines express vitamin D receptors, while calcitriol exerts anti-proliferative effects in normal prostate epithelial cells [23]. Furthermore, PCa patients showed lower serum vitamin D levels than matched controls, and PCa risk decreased with increasing serum calcitriol levels [24]. In biopsy-naïve men, low levels of both plasma and serum vitamin D are associated with an increased PCa risk compared to high vitamin D levels [25,26]. Additionally, a meta-analysis revealed that an increase of 20 nmol/L plasma vitamin D decreased the overall and PCa specific mortality [27]. Several mechanisms have been proposed to support the putative protective role of vitamin D on prostate health. Vitamin D binds to the vitamin D receptors (VDR), and it is a member of the steroid receptors’ superfamily. Upon vitamin D treatment, a heterodimer VDR-retinoid-X receptors exists. The activated VDR then binds to the promoter region of specific genes with vitamin D response elements (VDREs) to regulate the transcription of genes involved in prostate cell differentiation and metabolism [28,29,30]. Again, the active vitamin D metabolite inhibits the local conversion of dehydroepiandrosterone to active androgens, showing prostate growth-stimulation [31]. However, the literature data show conflicting results, and the topic still remains highly debated. A meta-analysis showed that men with elevated vitamin D serum levels had a higher risk of developing PCa than men with low serum levels of vitamin D [32]. In addition, it seems that the vitamin D serum level could be associated to PCa aggressiveness [25]. Furthermore, some studies suggested a positive association between PSA and high vitamin D serum level in PCa [33]. In addition, an inverse association between solar UV exposure and serum PSA concentration, especially during seasons of low UV (i.e., winter and spring), has been noted [33]. The relationship between vitamin D, UV exposure and serum PSA did not seem to have implications in PCa primary prevention, but some vitamin D supplementation trials have shown that vitamin D supplementation for PCa patients in active surveillance reduced the number of the positive core at the control repeat biopsy and post-radical prostatectomy PSA levels [34,35]. Based on the aforementioned literature data, revealing some controversial evidence, and considering the proposal of vitamin D supplementation to prevent PCa incidence, we aim to assess the correlations eventually existing, between serum vitamin D and serum PSA levels in a middle Italy region cohort of men participating in a PCa screening campaign. ## 2.1. Study Sample All participants are Caucasians living in Molise, a small region in the middle of Italy, attending a prostate cancer screening campaign prompted by Asrem—Azienda Sanitaria Regionale del Molise. All participants aged between 50 and 70 years were recruited between November 2021 and December 2021 and were asked to complete a questionnaire containing questions about demographic characteristics, prostate health, food, alcohol and smoking habits, drugs and supplements used, medical history and type, duration, and frequency of physical activity, prior to their first clinic visit. We selected one hundred participants aged between 50 and 70 years “free of prostate disease’ (participants have not previously received a diagnosis of PCa, benign prostatic hyperplasia, or prostatitis and have not referred symptoms suggestive of the aforementioned diseases). Additionally, the patients have been screened with a digital rectal examination that have not indicated a significant increase in gland volume [36]. Digital rectal examination has not affected the inclusion or exclusion criteria. We excluded participants under 50 years of age and over 70 years of age with a PCa diagnosis. Participants provided written approved consent. ## 2.2. Study Design A retrospective study was conducted utilizing questionnaire data and blood samples which were collected from participants to the “Novembre azzurro” initiative prompted by ASReM (Azienda Sanitaria Regionale del Molise). The retrospective use of data collected for the present study was approved by ASReM (Azienda Sanitaria Regionale del Molise), according to the institution ethical guidelines. ## 2.3. Sample Collection Fasting blood samples were collected from participants before digital rectal exploration. Whole blood samples were allowed to clot and then centrifugated to separate serum. Serum aliquots were stored at −80 °C until samples were processed. Total PSA and vitamin D analyses were carried out at “Cardarelli” Hospital, Campobasso, Italy, using the Atellica Solution (Siemens Healthineers) analyzer with the Siemens Atellica IM PSA method (Siemens) calibrated against the WHO standard. The Atellica IM PSA method is a 2-site sandwich chemiluminometric immunoassay using constant amounts of 2 antibodies. The first antibody is a goat polyclonal anti-PSA antibody labeled with acridinium ester. The second antibody, contained in the solid phase, is a mouse monoclonal anti-PSA antibody covalently linked to paramagnetic particles. Serum vitamin D levels were measured on the Atellica Solution (Siemens Healthineers) instrument using the Siemens Atellica IM VitD method (Siemens) calibrated against the WHO standard. The Atellica IM VitD method is a competitive immunoassay using a fluorescein labeled-mouse monoclonal antibody covalently bound to paramagnetic particles, an ester-acridinium labeled anti-25(OH)vitamin D mouse monoclonal antibody, and a fluorescein-labeled vitamin D analogue. The analytical performance has been assessed by control sample (Biorad) measurement that showed values falling within the recommended limits. Sera were stored frozen at −80 °C until the end of sample collection, after which remaining analyses were performed simultaneously, in duplicate. From the Laboratory Informatics System, we retrieved records that included the following fields: anonymous patient identification number; gender; age; date of measurement; the name of the measured parameter; test results; reference range and unit; and instrument used for testing. The value of 4 ng/mL has been chosen as the cut-off for PSA. Accordingly, men have been divided into two groups based on their PSA serum level: men with a serum PSA levels below 4 ng/mL (normal PSA) and men with serum PSA > 4 ng/mL (abnormal PSA). Vitamin D serum levels were grouped as follows: vitamin D serum concentration < 21 ng/mL (vitamin D deficiency); vitamin D serum concentration between 21 and 30 ng/mL (vitamin D insufficiency); vitamin D serum concentration > 30 ng/mL (vitamin D recommended), values > 100 ng/mL (vitamin D toxicity). ## 2.4. Statistical Analysis Patients were enrolled using a random sampling technique. Descriptive characteristics of patients involved were expressed as means and standard deviations for continuous variables, while absolute counts and percentages were used for categorical variables. The normality of variable distributions was assessed via the Kolmogorov–Smirnov test. The Chi-square test was used to assess the relationship between PSA and vitamin D expressed as categorical variables (normal versus abnormal PSA for PSA serum levels; deficiency versus insufficiency versus recommended for vitamin D serum levels) in a contingency table while the Spearman’s rank correlation test was used to assess the correlation among PSA and vitamin D expressed as continuous variables. All statistical analyses were conducted using IBM SPSS software (version 27, IBM Corp, Armonk, NY, USA), considering p-value < 0.05 as statistically significant. ## 3. Results A total of one hundred and twenty-five patients were enrolled. The descriptive characteristics of patients involved, obtained from the questionnaire previously mentioned, are reported in Table 1. Mean age was 61.14 ± 5.66, while mean Body Mass Index (BMI), obtained from height and weight data, was 27.97 ± 3.53. In addition, $23\%$ of patients regularly take supplements and drugs, reporting, among the most commonly used drugs, antihypertensive, hypolipidemic, hypoglycemic, diuretic, anticoagulant and antiplatelet, hypouricemic, gastroprotective and anti-inflammatory drugs. Overall, $20.6\%$ refer to some kind of disease, with $14.3\%$ and $4.8\%$ reporting hypertension and diabetes, respectively. In addition, only $4\%$ of patients report familiarity for PCa. Regarding smoking habits, $5.6\%$ smoke cigarettes, while $94.4\%$ do not smoke or have quit for over 10 years. Regarding the consumption of alcohol, $18.3\%$ of patients declared to consume a glass of wine or beer with meals. Finally, regarding the sedentary or dynamic lifestyle, $77\%$ of patients reported practicing an hour of brisk walking at least twice a week, while $23\%$ of patients declared a sedentary lifestyle with minimal or no physical activity. By analyzing PSA concentration, it emerged that $60.3\%$ of patients showed physiological PSA concentration, while $39.7\%$ of patients showed a PSA value higher than the threshold. By analyzing vitamin D concentration, $61.9\%$ of patients showed vitamin D deficiency (<21 ng/mL), while $24.6\%$ of patients showed a vitamin D insufficiency (values between 21 and 30 ng/mL). Results of the Chi-square test are reported in Table 2 and Figure 1. Overall, $70\%$ of patients with an abnormal PSA reported a vitamin D deficiency compared to $57.3\%$ of patients with a normal PSA. Similarly, $16\%$ and $14\%$ of patients with an abnormal PSA reported, respectively, an insufficiency and a recommended vitamin D level, compared to $29.3\%$ and $13.3\%$ of patients with a normal PSA. Nevertheless, the test did not report a statistical significance, with $$p \leq 0.223.$$ A similar result was obtained when continuous PSA levels and vitamin D levels were correlated. Indeed, the Spearman’s rank correlation computed to assess the relationship between PSA and vitamin D reported a negative correlation between the two variables, with r[2] = −0.123, $$p \leq 0.170$$, which did not reach statistical significance as well (Figure 2). ## 4. Discussion Although the role of vitamin D deficiency in PCa risk has been hypothesized in several studies, the topic still remains controversial, with a lack of consistent findings in the literature. The protective vitamin D effect against PCa onset was firstly proposed, in 1990, by Schwartz and Hulka, based on the evidence that PCa risk was increased in the elderly with low serum vitamin D levels [18]. Nevertheless, more recent studies have increased the controversy on this issue. A meta-analysis involving 21 observational studies (for a total of 11,941 patients involved) performed by Xu et al. in 201 showed an elevated PCa risk in patients with increased vitamin D levels (up to $17\%$) [32]. Additionally, a more recent meta-analysis of 19 prospective studies, involving a total of 12,786 patients, reported a significant correlation between higher vitamin D concentration and PCa risk, suggesting per every 10 ng/mL increment of circulating vitamin D concentration, an elevation of approximately $4\%$ of PCa risk [32,37]. A large randomized controlled trial by Manson et al., involving 25,871 participants supplemented with vitamin D or placebo for a median follow-up of 5.3 years, reported instead no differences in PCa incidence compared to placebo [35]. Another debunked hypothesis has been related to the high PCa incidence in Nordic countries due to the fluctuating sun exposure [38,39]. As reported in a Danish cohort study involving over 70,000 patients, no association was found between serum vitamin D and PCa risk, albeit overall survival was lowest for serum vitamin D deficiency [40]. A 2018 meta-analysis revealed that vitamin D supplementation not only could not be beneficial for PCa, patients but, although it was not statistically significant, it might increase the risk of overall mortality [41]. Finally, Ramakrishnan et al. showed a decreased risk of high aggressive PCa in men with an increased serum levels of vitamin D albeit the complex nature of vitamin D pathway warrants careful analysis of results obtained [42]. Several additional reports suggested an inverse relationship between vitamin D levels and the risk and aggressiveness of PCa [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46]. Although there is evidence that vitamin D has tumor suppressor effects on prostatic tissue, studies on the effect of vitamin D in preventing PCa occurrence yielded inconclusive results [35,47,48]. Considering the wide variability of results obtained, it was reasonable to postulate that the effect of vitamin D levels on prostate health would be reflected also in PSA concentrations. A prospective study enrolling 105 healthy men with a physiological PSA concentration has not reported variations in PSA levels upon vitamin D administration and concomitant increase in vitamin D blood levels [16]. Another study enrolling 1705 subjects found no direct relationship between PSA and vitamin D levels in patients without PCa [33]. Furthermore, another interesting finding was reported in a meta-analysis performed by Toth et al., which showed no effects on PSA levels in different vitamin D subgroups, while in the meta-analysis performed by Shahvazi et al., PSA levels decreased in patients with vitamin D supplementation compared to placebo, although the results were not statistically significant [41,46]. Consistent with those data, our results similarly showed no association between serum vitamin D concentrations and PSA levels in healthy men. Although the number of participants enrolled was small, our findings have two major implications. Firstly, it raises concerns about the vitamin D contribution to prostate diseases associated with slightly or moderately elevated PSA levels. Secondly, it reinforces for clinicians that they should not adjust PSA reference ranges and threshold values to vitamin D levels during the decision-making process. We are conscious of different limitations of our study. First, the retrospective nature of our work, associated with the relatively limited sample size, does not permit drawing certain conclusions; secondly, the absence of a stratified PSA according to the age of patients, which, if one on side could have been an interesting aspect of our work, could have further limited the recruited sample size in smaller groups; thirdly, we assumed as a normal PSA a mean value <4 ng/mL which could not be associated with older patients [49,50,51,52,53]. We aim to evaluate these aspects and resolve these pitfalls in the next study. ## 5. Conclusions In the present study, an absence of correlation between the serum vitamin D concentration levels and PCa risk (elevated serum PSA values) has been observed. Considering the limited sample size of the present study, further studies in a larger patient cohort and in a wider geographic area, which will also consider vitamin D supplementation, immunomarkers and other health status indicators, are needed. The role of calcium intake as a confounding factor in the vitamin D/PCa association as well as the role of solar radiation in the vitamin D metabolism should also be assessed. ## References 1. Di Zazzo E., Galasso G., Giovannelli P., Di Donato M., Di Santi A., Cernera G., Rossi V., Abbondanza C., Moncharmont B., Sinisi A.A.. **Prostate cancer stem cells: The role of androgen and estrogen receptors**. *Oncotarget* (2016.0) **7** 193-208. DOI: 10.18632/oncotarget.6220 2. 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--- title: 'Human Neuromuscular Junction on a Chip: Impact of Amniotic Fluid Stem Cell Extracellular Vesicles on Muscle Atrophy and NMJ Integrity' authors: - Martina Gatti - Katarina Stoklund Dittlau - Francesca Beretti - Laura Yedigaryan - Manuela Zavatti - Pietro Cortelli - Carla Palumbo - Emma Bertucci - Ludo Van Den Bosch - Maurilio Sampaolesi - Tullia Maraldi journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003237 doi: 10.3390/ijms24054944 license: CC BY 4.0 --- # Human Neuromuscular Junction on a Chip: Impact of Amniotic Fluid Stem Cell Extracellular Vesicles on Muscle Atrophy and NMJ Integrity ## Abstract Neuromuscular junctions (NMJs) are specialized synapses, crucial for the communication between spinal motor neurons (MNs) and skeletal muscle. NMJs become vulnerable in degenerative diseases, such as muscle atrophy, where the crosstalk between the different cell populations fails, and the regenerative ability of the entire tissue is hampered. How skeletal muscle sends retrograde signals to MNs through NMJs represents an intriguing field of research, and the role of oxidative stress and its sources remain poorly understood. Recent works demonstrate the myofiber regeneration potential of stem cells, including amniotic fluid stem cells (AFSC), and secreted extracellular vesicles (EVs) as cell-free therapy. To study NMJ perturbations during muscle atrophy, we generated an MN/myotube co-culture system through XonaTM microfluidic devices, and muscle atrophy was induced in vitro by Dexamethasone (Dexa). After atrophy induction, we treated muscle and MN compartments with AFSC-derived EVs (AFSC-EVs) to investigate their regenerative and anti-oxidative potential in counteracting NMJ alterations. We found that the presence of EVs reduced morphological and functional in vitro defects induced by Dexa. Interestingly, oxidative stress, occurring in atrophic myotubes and thus involving neurites as well, was prevented by EV treatment. Here, we provided and validated a fluidically isolated system represented by microfluidic devices for studying human MN and myotube interactions in healthy and Dexa-induced atrophic conditions—allowing the isolation of subcellular compartments for region-specific analyses—and demonstrated the efficacy of AFSC-EVs in counteracting NMJ perturbations. ## 1. Introduction Skeletal muscle is a very plastic tissue, but its regenerative potential is hampered during aging [1]. The loss of muscle mass and function associated with muscle-wasting conditions greatly affects the quality of life in elderly populations [2]. Muscle atrophy is characterized by an activation of proteolytic systems that leads to the elimination of contractile proteins and organelles, with loss of skeletal muscle mass, quality, and strength [1,3]. In addition to this, the loss of alpha motor neurons (MNs) and negative alterations of neuromuscular junctions (NMJs) play a key role in musculoskeletal impairment that occurs with aging [4,5]. NMJs are specialized regions where muscle and nerve can communicate—a fundamental connection to govern vital processes, such as breathing and voluntary movements [6]. In physiological conditions, after neuronal loss, denervated orphan muscle fibers, together with some other types of cells, such as terminal Schwann cells, produce chemotactic signals that stimulate the growth of new neurites and, consequently, their re-innervation. These compensatory strategies start failing with aging and the fibers that have not re-innervated become apoptotic, leading to a decline in muscle capabilities [7,8,9]. Moreover, the depletion of adult satellite cells (SCs), the characteristic muscle stem cell compartment, aggravates this dramatic context [10]. This loss in muscle integrity leads to alterations in NMJ morphology that becomes fragmented, and to functional changes in neuromuscular transmission [11]. This initial NMJ change is accompanied by an increase in inflammatory cytokine production and loss of trophic support with consequent neurodegeneration [12]. Furthermore, the age-associated increase in oxidative stress and mitochondrial dysfunction plays a crucial role in NMJ degeneration and muscle atrophy. This oxygen metabolism defect, associated with the reduction in mitochondrial energy production and increase in intracellular calcium, intensifies the pre-synaptic decline and reduces the release of synaptic vesicles. The increase in reactive oxygen species (ROS)—due to mitochondrial dysfunction—in both muscle and neural tissues leads to an accumulation of damaged cell components with alteration in their communication [6,13]. Nevertheless, in this fundamental crosstalk, it has not yet been clarified whether NMJ alteration precedes or follows muscle decline, nor what role oxidative stress components play under such circumstances. Based on these considerations, combining neuro-muscular protection, anti-inflammatory, and antioxidant capabilities may be a promising way to counteract NMJ degeneration. In recent years, mesenchymal stem cells (MSCs), including amniotic fluid stem cells (AFSCs), have been proposed as a potential therapy for human tissue repair and regeneration, given the encouraging evidence in different experimental neuromuscular disease models [14,15]. Moreover, recent studies demonstrated the potential of MSCs, isolated from different tissues (adipose, umbilical cord, and bone marrow), to induce muscle regeneration [16,17,18]. Human amniotic fluid stem cells (hAFSCs) have different advantages, such as their minimal ethical concerns and being easy to obtain from leftover discarded samples of routine prenatal screening amniocentesis (II trimester of gestation). Among the scientific community, it has become increasingly accepted that the therapeutic potential of these cells can be at least in part attributable to bioactive molecules secreted into extracellular vesicles (EVs). Furthermore, EVs have the advantage of being a cell-free therapy candidate, reducing the risks associated with live cell transplantation. In a recent work, Villa et al. demonstrated the human AFSC pro-survival effect on damaged cardiomyocytes, counteracting apoptosis and mitochondrial impairment [19]. Additionally, the neurogenic potential of these cells has been demonstrated by the presence—although in low amounts—of the neural growth factor BDNF in their EVs cargo, suggesting a neurotrophic activity promoting neuronal survival and neurodevelopmental processes [20]. The beneficial potential of MSC transplantation in amyotrophic lateral sclerosis (ALS) mice has been demonstrated by several studies that have shown a reduction in disease phenotype and progression, but above all else, a partial recovery of motor functions [21,22,23]. It is well known that NMJs become vulnerable in degenerative diseases [24], however evidence on the efficacy of MSC-EVs on NMJ complexes is still lacking. Based on that, the present study aims to explore the paracrine antioxidant and neuroprotective effects of human AFSC-EVs against NMJ perturbations in age-related muscle degeneration. The use of innovative commercially available microfluidic devices allowed us to set up an in vitro model of muscle atrophy induced by glucocorticoid supplementation. ## 2.1. Effect of Human AFSC-EVs on In Vitro Model of Muscle Atrophy Induced by DEXAMETHASONE Muscle atrophy was induced in vitro by myotube exposure to 20µM Dexamethasone for 24 h. Preliminary studies have identified this non-cytotoxic concentration (Supplementary Figure S1A,B) as the one able to induce an atrophic phenotype (Supplementary Figure S1C) in hMAB-myotubes. The analysis of immunofluorescence (IF) images of myotubes—stained with myosin heavy chain (MyHC), a typical marker for mature muscle differentiation—showed a reduction in number of nuclei per myotube, and above all, myotube thickness—the main sign of muscle atrophy—after Dexa treatments, while all these typical differentiation indexes were restored by AFSC-EV treatment, although the fusion index was not fully restored (Figure 1A). Moreover, we did not observe significant alterations in the total nuclei number among the different conditions. In addition, an increased number of MyHC-negative cell nuclei compared to the control one in AFSC-EV-treated samples suggests possible improved preservation of stemness. Increasing evidence links oxidative stress and reactive oxygen species (ROS) to muscle atrophy [25,26]. Therefore, we decided to investigate the ROS content alteration during the early phase of atrophy induction in hMABs (Figure 1B) by DCFH-DA probe. This analysis showed a significant increase in oxidative stress level, prevented by AFSC-EV exposure. Moreover, gene expression analysis confirmed the ability of AFSC-EV treatment in restoring the morphological impairment in our in vitro atrophy model (Figure 1C). Indeed, several muscle-specific genes, such as MyHC1, MyHC3, Pax3, and desmin, redox-sensitive signal pathway genes including the forkhead box class O 3 (FOXO3), main regulator of oxidative stress defenses [27], and autophagy-related genes (LC3β and beclin-1) were dysregulated with Dexa treatment. Notably, EV exposure restored the levels of those genes and the increased expression of both FOXO3 and SIRT1 was accompanied by an upregulation of SOD1, GPX, PDRX3, and TrxR3 antioxidant genes. ## 2.2. Effect of Dexamethasone on Mature iPSC-MNs *To* generate in vitro functional and morphological mature motor neurons (MNs), we used human-iPSCs differentiated via the 28-day differentiation protocol already published by Guo et al. [ 28]. The differentiation success was confirmed by gene expression analyses that showed, at day 28, the upregulation of typical pan-neuronal (MAP2 and β-tubulinIII) but also of specific motor neuron (HB9 and Islet-1) markers, and the downregulation of pluripotency markers (NANOG, SOX2), compared to day 10 of differentiation (Supplementary Figure S2A). Additionally, IF images confirmed the positivity of differentiated MNs for synaptophysin (SYPH) and Islet-1 (Isl-1) (Supplementary Figure S2B). Moreover, to be sure that the effect on MNs in co-culture was mediated only by myotubes, we demonstrated that the 20 µM Dexa treatment (24 h) has no effect on motor neuron morphology and differentiation potential (Supplementary Figure S3A), nor does it have a significant impact on the expression of differentiation, redox, and apoptosis marker genes (Supplementary Figure S3B), as demonstrated by immunofluorescence and RT-qPCR analyses. ## 2.3. Distribution of Myotubes and Neurites into Microfluidic Devices—Muscle Compartment and NMJ Formation To understand the consequences of muscle atrophy on NMJ integrity, we set up an in vitro model of a motor neuron-myotube co-culture using microfluidic devices (Figure 2). Then, to study the potential of AFSC-EVs in counteracting muscle atrophy injuries, we only treated the muscle compartment with Dexamethasone and examined the modification in myotube and neurite distribution. Dexa treatment reduced the number of MyHC-positive myotubes, while the exposure to EVs recovered the myotube presence (Figure 3A). In parallel, the analysis of neurite density into the muscle compartment was carried out. Interestingly, AFSC-EV exposure was able to restore the neurite density affected during muscle atrophy induction (Figure 3B). These results led us to study the possible consequences of these impairments on NMJ formation. NMJs were identified as co-localizations between αBtx-positive AChRs and NEFH/SYPH-positive neurites on myotubes (Figure 4A). While the percentage of innervated myotubes was not significantly reduced upon Dexa treatment (Figure 4B), a reduction in NMJ numbers per myotube was observed (Figure 4C) and human AFSC-EVs were effective in counteracting this affection. In addition, NMJs could be distinguished for their morphology as single-contact-point NMJs—less mature—when a neurite touches a AChR cluster one time, or multiple-contact-point NMJs—characteristic of a more mature development state of co-culture—when neurites will fan out and engage with the AChR cluster over a larger surface [29]. Based on this, we observed a reduction in both of these types of interaction in the Dexa-induced atrophy model, while it was prevented by EV pre-exposure (Figure 4D). ## 2.4. Functionality of NMJs after MN-Stimulation in an In Vitro Atrophy Model In order to investigate the functional consequences of morphological alteration in this muscle atrophy model and the therapeutic potential of AFSC-EVs, live-cell calcium imaging was performed (Figure 5A,B). As shown in Figure 5C, Dexa treatments significantly reduced the percentage of motor neuron-stimulated active myotubes, compared to untreated ones, while EV exposure prevented the Dexa-mediated impairment compared to the control. This result brought us to investigate the intracellular calcium transient waves. While significant modifications of the cellular calcium intensity peak were not observed (Figure 5D), this analysis showed a delay of Ca2+ peak onset after Dexa treatment, indicating an alteration in myotube functionality. On the other hand, AFSC-EVs were able to reduce this delay in myotube functionality (Figure 5E). ## 2.5. NMJ Oxidative Stress Modulation by Human AFSC-EVs during Atrophy Among many factors, oxidative stress and mitochondrial dysfunction may perform key roles in NMJ decline, muscle strength, and integrity loss [4]. To investigate the oxidative stress alteration in our system, we performed live-imaging assays using fluorescent probes for intracellular ROS and mitochondrial O2•− detection. A schematic overview of experiments is shown in Figure 6A. First, we measured the ROS level variations in neurites after up to 28 min of treatment with Dexa. Dexa exposure increased the ROS content in the neurites that have crossed the microgrooves to contact the myotubes. Notably, EVs protected MN elongations from oxidative stress induced by atrophic muscle cells, in all time points of analysis (Figure 6B). To investigate the implication of mitochondrial superoxide (O2•−) in this oxidative context, MitoSoxTM live-cell imaging analysis of neurites was performed (Figure 6C). EV pre-treatment was able to reduce mitochondrial O2•− levels, increased by Dexa exposure, for every investigated time point (Figure 6D). ## 3. Discussion In recent years, human AFSCs have been proposed as potential therapeutic approaches for human tissue repair and regeneration, thanks to the encouraging results obtained from different experimental disease models [14,15]. Many of the observed effects can be, at least in part, attributed to the presence of bioactive molecules secreted into extracellular vesicles (EVs), such as antioxidant and anti-inflammatory compounds. Despite the complexity, the pathogenesis of age-related muscle wasting conditions, such as muscle atrophy, could be linked to a reduction in protein synthesis and/or an enhanced proteolysis, associated with an increase in oxidative stress [30]. In the present study, we aimed to deepen the understanding of the therapeutic potential of EVs, obtained from AFSCs, in rescuing the pathological atrophic phenotypes and detrimental consequences on NMJ integrity induced by Dexa. Dexa is a synthetic glucocorticoid widely used as a treatment to control different pathological alterations linked to inflammation [31]. Despite its beneficial effects, its abuse can lead to skeletal muscle atrophy, mainly via two pathways: the glucocorticoid receptor (GR)-mediated catabolic processes and the oxidative stress-related pathway [32,33,34]. Given the similar mechanism of muscle damage to age-related atrophy, glucocorticoids are largely used in research for this purpose. FOXO3 plays a crucial role in these catabolic events, regulating both metabolism and oxidative stress defenses. FOXO3 controls the two principal systems of muscle proteolysis: ubiquitin-proteasomal and autophagic/lysosomal pathways. In our in vitro atrophy model, we observed gene expression increase in FOXO3, associated with an overexpression of autophagy-related markers Beclin-1 and LC3β [35]. Moreover, the myotube morphology appeared affected, as shown by the fusion index, nuclei per myotube, and myotube thickness reduction, accompanied by a downregulation of late muscle differentiation markers (myosin heavy chain 1 and 3). Contrarily, the expression of structural muscle protein Desmin appeared increased. Desmin is an intermediate filament fundamental for the maintenance of muscle structure, cellular integrity and size, mitochondrial homeostasis, and proteostasis [36]. Recent studies demonstrated that *Desmin* gene expression levels increase in different models of heart failure, as a compensatory mechanism for its augmented misfolding and degradation [37,38,39]. Therefore, we assume that a similar self-rescuing response occurred in our atrophy model. Notably, AFSC-EV treatment restored not only the myotube morphology affected by Dexa but also gene expression of all the altered muscle activation/differentiation markers. Considering the central role of oxidative stress in muscle atrophy progression, and the potential of extracellular vesicles in redox modulation, we investigated it in our Dexa-induced atrophy model. Interestingly, in the presence of EVs, we observed a significant reduction in ROS levels increased by Dexa, accompanied by an upregulation of Sirtuin 3 (Sirt3), FOXO3, and antioxidant genes superoxide dismutase 1 (SOD1), glutathione peroxidase (GPx), peroxiredoxin 3 (PDRX3), and thioredoxin reductase 3 (TrxR3). Sirt3 is a mitochondrial NAD-dependent histone deacetylase (HDAC) principally implicated in stress-adaptive responses by inhibiting mitochondrial oxidative stress. Moreover, the main targets of Sirt3 are FOXO family transcription factors, which once deacetylated increase their transcriptional activity and reduce their degradation via phosphorylation and/or ubiquitination [40]. The FOXO3-activated pathway by Sirtuins upregulates a set of FOXO3a-dependent mitochondrial antioxidant enzymes including superoxide dismutase, thioredoxin, and peroxiredoxin [41]. Additionally, we recently demonstrated that AFSC-EV exposure counteracts oxidative stress in an in vitro model of Alzheimer’s disease and osteoporosis, at least in part by reinforcing the Sirtuin/FOXO antioxidant defenses pathway [42,43]. The results obtained in this work led us to hypothesize a similar mechanism, although it has not been further investigated since our main focus was on NMJ alterations. Considering the bi-directional communication between nerve and muscle, recent findings have highlighted that skeletal muscle can be a fundamental source of signals for neuron survival, axonal growth, and maintenance of synaptic connection [6]. Based on this, we investigated the muscle impairment consequences on distal axon and the protective potential of vesicles from AFSCs. In order to study the atrophy consequences in a more complex system focusing on NMJs, we used microfluidic devices to set up an in vitro co-culture of human iPSC-derived motor neurons and myotubes with an atrophic phenotype induced by Dexa. The fluidically isolated compartments, where only neurites can growth through microgrooves, not only allows the maintenance of a cell-type-specific microenvironment, but also allows the isolation of subcellular compartments, as distal and proximal parts of the axon, to carry out region-specific analyses [44,45]. Interestingly, the muscle wasting environment induced by Dexa affected the neurite presence in the muscle side and the NMJ maintenance. Furthermore, both types of NMJs—mature multiple contact point and newly formed compensatory single contact point—were impaired due to Dexa treatment. Moreover, AFSC-EVs presence prevented all these neural alterations, probably protecting motor neurons from the detrimental environment created into the synaptic space during atrophy-related muscle wasting. Upon exploring the functional consequences, we noticed a reduction in the number of active myotubes after MN stimulation, compared to the total active myotubes, in the Dexa-atrophy model. Even though we did not observe significant alterations in the calcium influx intensity peak between different conditions during stimulation, the myotube response reactivity to MN stimulation over time was delayed in atrophic conditions. This effect could be reversed by AFSC-EV pre-treatment. Notably, several studies on amyotrophic lateral sclerosis (ALS) models demonstrated that increased oxidative stress and compromised mitochondria, in both muscle and nerve, are among the major contributory factors in affecting presynaptic heath [46,47,48]. In particular, NMJ in vitro exposure to exogenous H2O2 induces a strong inhibition of spontaneous neurotransmitter release in frog sartorius muscle [49]. In light of this, we propose that the observed alterations in the timing of myotube contraction could be explained as an impairment in the synaptic vesicles’ release by presynaptic terminals affected by an atrophy-related redox imbalance. Nevertheless, we cannot exclude that this may also be due to an impairment in myotube contractile machinery. Furthermore, experiments on mutant SOD1 mouse models demonstrated that oxidative stress originates from distal muscles before the onset of ALS pathology. This suggests that oxidative damage starts at the postsynaptic side of the muscle and propagates to motor neurons’ presynapse and further up to the axon in a retrograde manner towards the neuronal soma, ultimately leading to apoptosis of the entire cell [50,51,52]. To evaluate this hypothesis in our model, the oxidative stress and the mitigating effect of EVs in atrophy-related NMJ alterations were investigated. To this purpose, we followed the redox modification of neurites reaching the myotube area, the ones likely creating NMJs. We observed that the treatment with AFSC-EVs reduced not only the increased ROS levels but also the mitochondrial superoxide (O2•−) overproduction in neurites, associated with muscle atrophy induction. Antioxidant proteins carried by AFSC-EVs, including SOD1, could have a direct effect on ROS scavenging, re-equilibrating the redox balance affected in NMJs. Importantly, increased local activities of ROS are linked to a reduction in motor neuron and NMJ integrity and efficiency in muscle contraction, and the permanence of this oxidative stimuli leads to a permanent disruption in their structure and functionality [53,54]. The analysis of our data demonstrated that the re-equilibration of redox balance by AFSC-EVs, together with their immunomodulatory and neurogenic activity, have a protective effect on NMJ and motor neuron damage associated with muscle atrophy. ## 4.1. Human Amniotic Fluid Collection The human amniotic fluid stem cells (hAFSCs) were obtained from amniotic fluids collected from 3 healthy pregnant women at the 16th week of gestation who underwent amniocentesis per maternal request (not foetal anomalies) at the Unit of Obstetrics and Gynecology, Policlinico Hospital of Modena (Modena, Italy). The amniocentesis was performed under continuous ultrasound guidance, in a sterile field, with a 23-Gauge needle. The risk related to the procedure and the purpose of the study were explained to all patients before the invasive procedure, and the ob-gyn specialist collected a signed consent form before starting the exam (protocol $\frac{360}{2017}$, dated 15 December 2017 and approved by Area Vasta Emilia Nord). For this study, unused (supernumerary) flasks of AF cells cultured in the Laboratory of Genetics of the TEST Lab (Modena, Italy) for 2 weeks were used. ## 4.2. Human Amniotic Fluid Stem Cell Isolation and Culture hAFSCs were isolated as previously described [55]. Briefly, human amniocentesis cultures were harvested by trypsinization and subjected to c-kit immunoselection by MACS technology (Miltenyi Biotech, Germany). hAFSCs were subcultured routinely at 1:3 dilution and not allowed to grow beyond $70\%$ confluency. hAFSCs were grown in αMEM culture medium (Corning, Manassas, VA, USA) supplemented with $20\%$ fetal bovine serum (FBS) (Gibco, Waltham, MA, USA), 2 mM L-glutamine, 100 U/mL penicillin, and 100 µg/mL streptomycin (all reagents from EuroClone Spa, Milano, Italy). ## 4.3. Extracellular Vesicles Isolation hAFSCs were grown in 75cm2 flasks until sub-confluence (around 106 cells). Then, cells were maintained in FBS-free culture medium (10 mL) for 4 days, to avoid contamination by EVs from the FBS solution. The collected conditioned medium (CM) was centrifuged at 300× g for 10 min at 4 °C to eliminate cellular debris, and then concentrated up to 2 mL by using centrifugal filter units with a 3K cut-off (Merk Millipore, Burlington, MA, USA) [54]. The concentrated CM was again centrifuged at 10,000× g for 30 min at 4 °C and then, the supernatant was ultracentrifuged in polypropylene ultracentrifuge tubes (13.5 mL, Beckman Coulter) at 100,000× g for 90 min at 4 °C in a Beckman Coulter Optima L-90 K centrifuge (SW-41 rotor); the supernatants were discarded and the pellets were resuspended in 13 mL DPBS (Corning, Manassas, VA, USA) and ultracentrifuged again (100,000× g, 90 min at 4 °C) [56]. The pellet was resuspended in 100 µL of DPBS for subsequent analyses and treatments. Size distribution and concentration of EVs were analyzed, after a 1:100 dilution, by a NanoSight particle tracker from NanoSight Ltd. (Malvern Panalytical, Worcestershire, UK). ## 4.4. Derivation, Maintenance, Differentiation, and Treatment of Human Mesoangioblasts Human Mesoangioblasts (hMABs) were isolated as previously described [57,58]. hMABs were cultured on collagen from calf skin-coated flasks in IMDM growth medium (Sigma, Milan, Italy) supplemented with $1\%$ sodium pyruvate, $1\%$ non-essential amino acids, $1\%$ L-glutamine, $1\%$ insulin transferrin selenium (all reagents from EuroClone Spa, Milano, Italy), 5 ng/mL recombinant human basic fibroblast growth factor (bFGF) (PeproTech, Rocky Hill, NJ, USA). Medium was changed every 3 days. Since physical contact between hMABs initiates fusion and reduces the myogenic potential, cells were trypsinized before $70\%$ confluency [59]. To induce myotube differentiation, confluent hMABs were exposed for 1 week to a differentiation medium composed of 1:1 DMEM/F12 (Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with $2\%$ horse serum (Thermo Fisher Scientific, Waltham, MA, USA) and $1\%$ sodium pyruvate (EuroClone Spa, Milano, Italy) on collagen from calf skin-coated supports. In order to induce muscle atrophy, after 7 days myotubes, were treated with 20 µM Dexamethasone (Dexa) (Sigma Aldrich, St Louis, MO, USA) in differentiation medium for 20 min (for ROS analysis) or 24 h (for all other experiments). AFSC-EVs t (1.3 × 108 particles/cm2) were added 24 h before Dexa treatment and maintained for the glucocorticoid treatment time. ## 4.5. Differentiation of iPSCs into Mature Motor Neurons and Treatment To obtain mature motor neurons (MNs) from iPSCs (GibcoTM Episomal hiPSC Line) (Gibco, Thermo Fisher Scientific, Waltham, MA, USA), the protocol by Dittlau et al. was applied [28,29]. Briefly, iPSCs were harvested using Collagenase type IV (Gibco, Waltham, MA, USA), transferred into Ultra-low attachment multi6-well plates (Corning Manassas, VA, USA) to promote cluster formation and maintained in *Neuronal medium* ($50\%$ DMEM/F12 and $50\%$ Neurobasal Medium (both from Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) with 2 mM L-glutamine, 100 U/mL penicillin, and 100 µg/mL streptomycin (all reagents from EuroClone Spa, Milano, Italy), $1\%$ N2 supplement, $2\%$ B-27TM without vitamin A, $0.1\%$ β-mercaptoethanol (all reagents from Thermo Fisher Scientific, Waltham, MA, USA), 0.5 µM ascorbic acid (Sigma-Aldrich, Milan, Italy)) supplemented with 5 µM Y-27632 (Merck Millipore, Burlington, MA, USA), 0.2 µM LDN-193189 (Stemgent, Beltsville, MA, USA), 40 µM SB431542, and 3 µM CHIR99021 (both from Tocris Bioscience, Bristol, UK) for 2 days, changing the medium every day. From day 2, *Neuronal medium* was supplemented with 0.1 µM retinoic acid (Sigma-Aldrich, Milan, Italy), 500 nM smoothened agonist (SAG) (Merck Millipore, Burlington, MA, USA), and from day 7, brain-derived neurotrophic factor (BDNF) and glial cell-derived neurotrophic factor (GDNF) (both from PeproTech, Rocky Hill, NJ, USA) were added. On day 9, 20 µM DAPT (Tocris Bioscience, Bristol, UK) was added. On day 10, single cells were obtained from floating clusters by $0.05\%$ trypsin (Gibco, Waltham, MA, USA) treatment, and seeded onto poly-L-ornithine- (PLO) and laminin- (both from Sigma, St Louis, MO, USA) coated plates. Single cell neural progenitor cells (NPCs) were maintained in culture until experiments in *Neuronal medium* supplemented with BDNF, GDNF, and CNTF (ciliary neurotrophic factor) were conducted, and the medium was refreshed every 2 days. To test the effect of Dexa on mature motor neurons, at day 27 of differentiation, Dexa treatment was applied at a concentration of 20 µM for 24 h. ## 4.6. Preparation of Microfluidic Devices Microfluidic devices (XonaTM Microfluidics, Temecula, CA, USA; Cat N° XC150) were sterilized in $90\%$ ethanol and left to air-dry in a sterile laminar flow hood. Devices were placed individually in 10 cm petri dishes for easy handling. Before cell seeding, devices were coated using 100 µg/mL poly-L-ornithine (PLO) in DPBS for 3 h and then 20 µg/mL laminin (both from Sigma, St Louis, MO, USA) in *Neurobasal medium* (Life Technologies, Thermo Fisher Scientific, Waltham, MA, USA) overnight. All coated materials were incubated at 37 °C, $5\%$ CO2, and a volume difference of 100 µL between two sides was applied to allow the coating to pass through the microgrooves (maximum capacity for each device well: 200 µL). The day after, devices were carefully washed once with DPBS before neural cell plating. ## 4.7. Co-Culturing Myotubes and MNs in Microfluidic Devices and Treatments Myotubes and MNs were co-cultured into XonaTM microfluidic devices according to a previously described protocol [59]. Briefly, day 10 MN-precursor cells were seeded into one side of devices at a seeding density of 1.25 × 105 cells/well (total 2.5 × 105 cells/side) and maintained in day-specific differentiation medium according to the differentiation protocol. After 1 week (day 17), hMABs were seeded into the opposite compartment (105 cells/well, total 2 × 105 cells/side), and the day after (day 18), myotube differentiation was started (differentiation medium described in section “Derivation, Maintenance, Differentiation, and Treatment of Human Mesoangioblasts”). On day 21, a chemotactic and volumetric gradient was established: neuronal compartments received 100 µL/well of neuronal medium without neurotrophic factors, while myotube compartments received 200 µL/well neuronal medium supplemented with 30 ng/mL BDNF, GDNF, CTNF (all reagents from PeproTech, Rocky Hill, NJ, USA), 20 µg/mL laminin (Sigma, St Louis, MO, USA), and 0.01 µg/mL recombinant human agrin protein (R&D Systems, Minneapolis, USA). The gradient and laminin/agrin treatment were maintained until the end of the co-culture period. At day 26, AFSC-EVs were added to both compartments in day 21 medium (4.16 × 107 particles/well), and after 24 h, only the myotube compartment was also treated with 20 µM Dexa for 20 min for oxidative stress analysis or 24 h for all other analyses. ## 4.8. RNA Isolation and Quantitative Real-Time PCR For the quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) assay, the Purelink® RNA mini kit (Thermo Fisher Scientific, Waltham, MA, USA) was used to isolate total RNA, and RNA samples were purified by a TurboTM DNA-free kit (Thermo Fisher Scientific, Waltham, MA, USA) following manufacturers’ instructions. First, 1 µg of RNA was reverse-transcribed using the Superscript III Reverse Transcriptase First-Strand Synthesis SuperMix (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturers’ protocol. Then, Platinum SYBR Green QPCR SuperMix-UDG (Thermo Fisher Scientific, Waltham, MA, USA) was used to dilute cDNA (1:5). The RT-qPCR was performed by a Viia7 384-plate reader (Thermo Fisher Scientific, Waltham, MA, USA) [60]. Oligonucleotide primer forward/reverse sequences are listed in Table 1. ## 4.9. Immunofluorescence Confocal Microscopy and Image Analysis For immunofluorescence analysis, cells—seeded on coverslips or into microfluidic devices—were processed and confocal imaging was performed using a Nikon A1 confocal laser scanning microscope, as previously described [43,59]. Primary antibodies to detect neurofilament heavy chain (NEFH) (Abcam, Cambridge, UK), synaptophysin (SYPH) (Cell Signaling Technology, Lieden, Netherlands), Islet-1 (Isl-1) (Millipore, Burlington, MA, USA), β-tubulinIII (βtubIII) (Cell Signaling Technology, Lieden, Netherlands), and myosin heavy chain (MyHC) (In-house, SCIL, dil. 1:20) were used following the datasheet-recommended dilutions. α-Bungarotoxin-tetramethylrhodamine (Sigma-Aldrich, MO, USA) was incubated with secondary antibodies according to the manufacturers’ protocol. Alexa secondary antibodies (Thermo Fisher Scientific, Waltham, MA, USA) were used at a 1:200 dilution. To obtain three-dimensional projections, the confocal serial sections were processed with ImageJ software [61], while image rendering was performed with Adobe Photoshop software [62]. For myotube fusion index, nuclei per myotube, myotube thickness analyses, and NMJ quantifications, MyHC-positive cells containing multiple nuclei were selected as myotubes. Fusion index percentage was calculated as a ratio percentage between the number of nuclei inside myotubes and total nuclei. Myotube thickness was measured using ImageJ software. For NMJ quantification into microfluidic devices, 40× magnification images of MyHC-positive myotubes were collected using an inverted confocal microscope. The number of co-localizations between NEFH/SYPH and α-bungarotoxin (αBtx) (Sigma, St Louis, MO, USA), for Acetylcholine Receptor (AChR) identification, was counted manually through each z-stack, and the number of co-localizations was normalized to the number of myotubes present in the z-stack. NMJ morphology, single or multiple contact point, was analyzed looking at neurite interactions with AChR clusters, as previously described by Dittlau et al., 2021 [29]. Briefly, NMJs were identified as a single contact point when a neurite touched a AChR cluster once, while a multiple contact point was defined as a neurite fanning out and engaging with the AChR cluster over a larger surface. ## 4.10. Neurite Density-Outgrowth Quantification Neurite density-outgrowth quantification was performed as previously described by Dittlau et al. 2021 [29]. Briefly, tile scan images of NEFH fluorescence were taken using an inverted Leica SP8 DM18 confocal microscope and neurites were isolated using Ilastik 1.3.3post1 Pixel Classification software. A custom ImageJ 1.52p software linear *School analysis* script was used to quantify the total number of pixels that intersect an intersection line (distance between lines: 50 µm). The measuring was started at a 100 µm distance from the microgrooves due to the high neurite density at the exit of microgrooves. ## 4.11. Calcium Fluorescent Imaging After AFSC-EV and/or Dexamethasone treatments, the myotube compartment was incubated with 5 µM Fluo-4 AM (Thermo Fisher Scientific, Waltham, MA, USA) for 25 min in the dark ($5\%$ CO2, 37 °C). MNs were stimulated with 50 mM KCl and Fluo-4 fluorescence was recorded in the myotube compartment (1 picture/second for a total of 60 s, 10× magnification). Calcium transients were recorded after KCl stimulations in two different fields for each replicate. The fluidic isolation of the compartments in the microfluidic devices ensured no direct contact between the high KCl solution and the myotubes. To verify the myotube functionality, a positive test was performed by direct stimulation of myotubes with 50 mM KCl in the myotube compartment. The percentage of MN-stimulated active myotubes was calculated as a ratio between MN-stimulated active myotubes and total active myotubes. Recordings were acquired and analyzed using a Nikon A1R confocal microscope and NIS-Elements AR 4.30.02 software. Calcium waves were calculated as a ratio between the myotube fluorescence at each analyzed point and the fluorescence mean during the first 5 s of recording. Time intensity peak was calculated considering the time of peak starting onset. ## 4.12. Viability Assay hMABs were seeded and differentiated into 96-well plates (5 × 105 cell/well) with 5 replicates for each condition. After 7 days, myotubes were treated with 1, 10, 20, or 40 µM Dexamethasone (Dexa) (Sigma Aldrich, St Louis, MO, USA) in differentiation medium for 24 h. At the end of the treatments, 0.5 mg/mL MTT was added and incubated for 3 h at 37 °C. After incubation, the medium was removed, and acidified isopropanol was added to solubilize the formazan salts. The adsorbance was measured at 570 nm using a microplate spectrophotometer (Appliskan, Thermo-Fisher Scientific, Vantaa, Finland). ## 4.13. ROS Detection To evaluate the intracellular ROS levels, a dichlorodihydrofluorescein diacetate (DCFH-DA) assay was performed as previously described [63]. For myotube oxidative stress investigation, hMABs were seeded and differentiated into 96-well plates (5 × 105 cell/well) with 5 replicates for each condition, while for co-culture oxidative stress analysis, myotubes and MNs were cultured in microfluidic devices as described above. Culture medium was removed from each well and 5 µM DCFH-DA was incubated in PBS with 1 gr/L of glucose for 20 min at 37 °C and $5\%$ CO2. Dexa 20 µM treatment was only added to myotubes with the probe in the meantime and maintained for 20 min. In the 96-well plates, the probe solution was replaced with PBS/glucose and the fluorescence was read at 485 nm (excitation) and 535 nm (emission) using the multiwell reader Appliskan (Thermo Fisher Scientific, Waltham, MA, USA). Cellular autofluorescence was subtracted as a background using the values of the wells not incubated with the probe. For devices, after 20 min of Dexa treatment, the probe solution was replaced with PBS/glucose buffer and the neurite fluorescence was recorded for 8 min into the muscle compartment with a Nikon A1 confocal laser scanning microscope equipped with a live-cell imaging system. Live images were taken between microgroove exits and myotubes in order to select the neurites most likely to have contacted myotubes and to avoid myotube fluorescence noise. ## 4.14. Mitochondrial Oxidative Stress Analysis Confocal images were obtained using a Nikon A1 confocal laser scanning microscope equipped with a live-cell imaging system. During live imaging, cells were maintained in a PBS-glucose (1g/L) buffer at 37 °C, $5\%$ CO2. All acquisition settings, including detector sensitivity and camera exposure time, were maintained constant during recording. To avoid photobleaching and to reduce cell stress, laser power was set to minimum. To identify mitochondria, at day 27—after 24 h of AFSC-EVs exposure—both microfluidic device compartments were washed once with PBS/glucose buffer and then incubated with 100 nm MitoTrackerTM Green FM probe (Invitrogen, Waltham, MA, USA) in PBS/glucose buffer, and, in only the myotube compartment, with 20 µM Dexa for 20 min at 37 °C, $5\%$ CO2. After the first 10 min, 5 µM MitoSoxTM Red was added to both compartments to identify mitochondrial superoxide production. After the incubation time, microfluidic devices were gently washed 3 times and maintained in PBS/glucose during live imaging analysis. MitoSoxTM and MitoTrackerTM fluorescence was recorded in myotube compartments next to the microgrooves exit (20× magnification, with 10 s interval for a duration of 8 min). MitoSoxTM signal was normalized on MitoTrackerTM for each time point. ## 4.15. Statistics All the experiments were performed with 3 biological replicates. For quantitative comparisons, the values were reported as the mean ± SD based on a triplicate analysis for each sample. One-way ANOVA with a Bonferroni post hoc test or a Student’s t-test were applied to test the significance of the observed differences amongst the study groups. Statistical significance was considered as a p-value < 0.05. Statistical analysis and plot layout were obtained by using GraphPad Prism® release 8.0 software. ## 5. Conclusions In this study, we investigated the protective effect of AFSC-EV treatment upon Dexa-induced muscle atrophy and its consequences on the presynaptic part of NMJs. 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--- title: Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection authors: - Silvia D’Ambrosi - Stavros Giannoukakos - Mafalda Antunes-Ferreira - Carlos Pedraz-Valdunciel - Jillian W. P. Bracht - Nicolas Potie - Ana Gimenez-Capitan - Michael Hackenberg - Alberto Fernandez Hilario - Miguel A. Molina-Vila - Rafael Rosell - Thomas Würdinger - Danijela Koppers-Lalic journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003255 doi: 10.3390/ijms24054881 license: CC BY 4.0 --- # Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection ## Abstract Despite the diversity of liquid biopsy transcriptomic repertoire, numerous studies often exploit only a single RNA type signature for diagnostic biomarker potential. This frequently results in insufficient sensitivity and specificity necessary to reach diagnostic utility. Combinatorial biomarker approaches may offer a more reliable diagnosis. Here, we investigated the synergistic contributions of circRNA and mRNA signatures derived from blood platelets as biomarkers for lung cancer detection. We developed a comprehensive bioinformatics pipeline permitting an analysis of platelet-circRNA and mRNA derived from non-cancer individuals and lung cancer patients. An optimal selected signature is then used to generate the predictive classification model using machine learning algorithm. Using an individual signature of 21 circRNA and 28 mRNA, the predictive models reached an area under the curve (AUC) of 0.88 and 0.81, respectively. Importantly, combinatorial analysis including both types of RNAs resulted in an 8-target signature (6 mRNA and 2 circRNA), enhancing the differentiation of lung cancer from controls (AUC of 0.92). Additionally, we identified five biomarkers potentially specific for early-stage detection of lung cancer. Our proof-of-concept study presents the first multi-analyte-based approach for the analysis of platelets-derived biomarkers, providing a potential combinatorial diagnostic signature for lung cancer detection. ## 1. Introduction With 1.8 million deaths per year, lung cancer remains the leading cause of cancer mortality worldwide [1]. This high mortality can be attributed to two main reasons: late diagnosis and the inefficiency of the treatments available. Most of the patients present an advanced stage of the disease at the time of diagnosis, leading to an expected survival at 5 years below $10\%$ [2,3,4,5]. Novel reliable, sensitive, and accurate diagnostic tests are required since early-stage identification is associated with longer life expectancy. In recent years, liquid biopsy (LB) has been proposed as a highly promising diagnostic approach for the detection and management of cancer patients. An analysis of tumor-derived biomarkers present in human body fluids offers a minimally invasive, safe, and sensitive alternative or complementary approach to tissue biopsies. Besides the commonly used blood-based biosources and biomolecules, such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), and extracellular vesicles (EVs), blood platelets have recently emerged as promising novel carriers of cancer biomarkers [6,7,8]. Platelets dynamically interact with tumor cells, which can lead to a direct and an indirect alteration of their transcriptome [9]. Changes in the RNA profile of these tumor-educated platelets (TEPs) can be used as a surrogate signature for the detection, localization, and molecular profiling of different types of cancer [10,11,12,13,14]. Furthermore, it has been established that a considerable fraction of platelets are also generated within the lung, which may position them as a more advantageous indicator of lung cancer due to the possible impact of the disease on platelet formation [15,16,17,18]. Platelet RNA repertoire includes several types of RNA families which can be potentially used as biomarkers. A first insight of the diagnostic potential of the TEPs transcriptome was described during the profiling of the platelet mRNA repertoire of metastatic lung patients and asymptomatic individuals. This study discovered that the presence of cancer results in altered spliced mRNA profiles [19]. Afterwards, the use of platelet spliced mRNA as a biomarker for the detection and classification of various tumor types has been investigated in numerous studies [10,11,20,21,22]. More recently, the expression of other types of RNAs has been found dysregulated in platelets [14,23]. In particular, human platelets are highly enriched in circular RNA (circRNA) [24]. This type of RNA is characterized by a covalent loop structure generated by a noncanonical alternative splicing process named back-splicing. Due to their high stability, abundance, and spatiotemporal specific expression, circRNA have received increasing attention for their potential role as cancer biomarkers [25]. Recently, we have provided evidence that platelet-derived circRNA profile changes in the presence of NSCLC, indicating that circRNA may hold the potential as a biomarker for liquid biopsy tests [14]. Previous studies on platelet transcriptome were based on the use of RNA-seq technology. Although RNA-seq is currently the most used methodology for genomic-based biomarker discovery, its implementation in the clinic has several limitations due to its time-consuming and elaborate library preparation protocol, the lack of standardized methods, the high cost, and complex data analysis [26]. NanoString nCounter, a platform for the high-throughput analysis of gene expression, has grown in popularity both in clinical settings and in translational research due to its fast, simple, and reliable protocol. By directly hybridizing and counting the individual targets, nCounter technology enables the multiplex analysis of signatures up to 800 genes with high reliability and reproducibility. In contrast to RNA-seq methods, nCounter RNA analysis does not require reverse transcription, amplification, nor cDNA library construction. Altogether, all these features make this system less prone to bias, leading to a more accurate quantification of the targets. Clinical tests have been developed employing nCounter technology, including the FDA-approved nCounter Prosigna test, which stratifies breast cancer subtypes and predicts recurrence risk in post-menopausal women [27,28], and the tumor inflammation signature (TIS) assay, which forecasts PD-1 checkpoint blockade and clinical response across several tumor types [29]. This platform has also been employed for the discovery of potential biomarker signatures in various types of LB biosources, including cfDNA, cell-free RNA (cfRNA), EVs (including DNA, micro RNA (miRNA) and mRNA), as well as CTCs [30,31,32,33,34,35,36]. However, the platelet transcriptome has not been explored yet through this technology for LB purposes. Here, we present the development of a protocol for the interrogation of platelet mRNA and circRNA repertoire using NanoString nCounter technology and machine learning (ML) approaches. We applied this methodology to the platelet transcriptome obtained from lung cancer and non-cancer individuals in order to identify and evaluate the diagnostic value of each of the individual mRNA and circRNA signatures. Since a single type of biomarker may lack sensitivity and specificity for the enrichment of reliable clinical diagnostics information, we also explore a multi-analyte-based approach, using a combinatorial analysis of platelets-derived mRNA and circRNA to improve the detection of lung cancer. ## 2.1. Analysis of Blood Platelet-Derived RNA Using NanoString nCounter Technology We investigated if a direct platelet RNA analysis might provide adequate gene expression information without performing any pre-amplification step. Due to the limited amount of total RNA present in platelets, we tested different concentrations to determine the minimum amount of RNA input necessary to preserve critical gene expression information. Six different RNA concentrations (1 ng, 3 ng, 6 ng, 12 ng, 24 ng, and 48 ng) obtained from platelets of a lung cancer patient and a non-cancer individual (indicated as control) were analyzed by using the human immunology v2 panel (Supplementary Figure S1A) [37]. As expected, the highest total number of counts (after negative background removal) was observed using 48 ng of total RNA (Figure 1a,b, Supplementary Table S1A,B). The number of counts decreases along with the concentration, following a linear regression model (R2 = 0.99, p-value < 0.0001, both for cancer and control samples, Figure 1a,b), suggesting that hybridization efficiency between probes and RNA remains consistent also at the lowest concentrations. Similar results were obtained when considering the average counts per transcript (R2 = 0.98, p-value < 0.0001, for control and R2 = 0.97, p-value < 0.0002 for cancer, Supplementary Figure S1B) confirming the previous observations. However, we found a significant drop in the number of transcripts detected when 1 ng and 3 ng of total RNA were used compared with higher concentrations (Supplementary Table S1A,B). Using PCA analysis, we observed that samples generated with total RNA inputs of 1 ng and 3 ng deviated from the main cluster that encompassed the other concentrations examined. This implies that the RNA profiles of samples generated with 3 ng or less of RNA input are not consistent with those acquired with higher RNA input, which could hamper subsequent gene expression analyses (Figure 1c,d). Therefore, we conclude that a minimum concentration of 6 ng of platelet RNA without pre-amplification process is recommended for sufficient and robust transcripts expression profiles for platelet-RNA analysis with nCounter. ## 2.2. Profiling mRNA and circRNA Derived from Lung Cancer Patients and Non-Cancer Individuals Using Human Immunology V2 Panel and 78-circRNA Custom Panel Following the protocol described in Figure 2, we investigated the potential use of platelet mRNA (using human immunology v2 panel [37]) and circRNA (with the 78-circRNA custom panel [38]) as diagnostic biomarkers. We selected a cohort of 60 platelet samples isolated from lung cancer patients ($$n = 30$$) and non-cancer controls ($$n = 30$$) equally distributed per age and gender (Table 1). Since early-stage detection is crucial for lung cancer diagnosis, we selected samples from patients with mainly early-stage (from stage IA to stage IIIA) lung cancer ($$n = 20$$) while the remaining samples were from patients diagnosed with metastatic tumor stage ($$n = 10$$). We include both asymptomatic individuals ($$n = 27$$) and samples from patients with confirmed benign lung nodules ($$n = 3$$) in the control group. Total RNA extracted from platelets was stored in RNAlater (as explained in Section 4 Materials and Methods) and checked for quality before further processing (Supplementary Figure S2A–F). After subtracting the background (negative control) signal, we observed that 159 out of the 594 genes in the human immunology v2 panel were not present in any of the processed samples. A total of 402 platelets-derived mRNA were detected in both the control and cancer groups, whereas 18 transcripts were exclusively found in the control group and 15 in the lung cancer group (Figure 3a). All the 78 circRNAs present in the custom-made panel were detected in at least one of the samples. Only three circRNAs (circNOL6, circPTPRM, circGAyS8) were exclusively detected in the lung cancer group (Figure 3b). All these three circRNAs have been previously found to be dysregulated in lung cancer [39,40,41,42]. The analysis of the average number of transcripts detected per group using the human immunology v2 panel revealed 185 ± 97 mRNAs in the control group and 218 ± 85 mRNAs in the cancer group (Figure 3c). Although the average number of transcripts is slightly higher in the cancer group than in the control, the difference is not statistically significant (ns) (Mann–Whitney’s U p-value > 0.05) (Figure 3c). Out of the 78 circRNA present in the custom-made panel, an average of 54 ± 8 circRNA were detected in the cancer group and 53 ± 9 for the control group (Figure 3d). Moreover, in this case, no statistical difference between the two groups was observed (Mann–Whitney’s U p-value > 0.05) (Figure 3d). ## 2.3. Normalization of the Raw Counts and Differential Gene Expression between Lung Cancer Patients and Non-Cancer Individuals mRNA raw count data (Supplementary Figure S3A) was evaluated prior to normalization through analytical exploratory analysis. Assessment of the unnormalized mRNA raw data analysis utilizing a PCA plot reveals no significant batch effect or clear group cluster separation (Supplementary Figure S3B,C). To prevent inaccurate normalization due to genes with low expression and background noise, we removed 314 mRNA targets (as explained in Section 4 Materials and Methods) from the analysis. Moreover, based on the interquartile range method (1.5 IQR rule), two out of sixty samples were identified as possible outliers (Supplementary Figure S3D). Additionally, these samples also presented aberrant values for binding density and positive control linearity; therefore, they were excluded from subsequent data processing. Since an optimal normalization of the data is key for precise and consistent outcomes, we compared two different approaches: edgeR and DESeq2. Based on the RLE analysis, DESeq2 was found to perform better than edgeR in normalizing the mRNA data (DESeq2 R2 = 0.002 (Figure 4a) and edgeR R2 = 0.036 (Supplementary Figure S3E)). Differential expression analysis between lung cancer and the control group revealed a total of 25 significantly differentially expressed mRNA (|FC| > 0.5 and p-adj < 0.05), of which 15 were upregulated and 10 downregulated in lung cancer patients (Figure 4b). The circRNA raw count data (Supplementary Figure S4A) have been processed following the same filtering and normalization procedure as previously performed for mRNA data. The PCA plot evaluation reveals no apparent class grouping or substantial batch impact (Supplementary Figure S4B,C). Only five of the seventy-eight circRNA targets were excluded due to low expression (see Section 4 Materials and Methods). Two samples were flagged by IQR analysis as potential outliers (Supplementary Figure S4D). Since neither of them deviated from the main cluster in the PCA plot or showed any anomalies on the standard control metrics supplied by NanoString, both samples were kept in the dataset for further analysis. Similarly for the mRNA data, the DESeq2 package was found to obtain a more precise normalization of the data (DESeq2 R2 = 0.002 (Figure 4c) and edgeR R2 = 0.023 (Supplementary Figure S4E)). Differential expression analysis identified only one circRNA (circFUT8) as significantly upregulated in the lung cancer group (|FC| > 0.5 and p-adj < 0.05, Figure 4d). Interestingly, this circRNA was previously reported to be one of the 10 most upregulated circRNA in lung cancer tissue [43]. ## 2.4. ML-Classifier Development and Performance for Detection of Lung Cancer Patients Using Human Immunology V2 Panel and 78-circRNA Custom Panel To evaluate the potential use of the human immunology v2 panel as platelet signature for lung cancer detection, we employed ML approaches (as explained in Materials and Methods). The RFECV algorithm selected a final 28 mRNAs signature (Supplementary Figure S5A and Supplementary Table S2). To investigate the performance of different ML algorithms, two ML classifiers were tested (ETC and RF) using 5CV method. RF classifier testing on the 28-mRNA signature leads to the highest ROC AUC of 0.88 ± 0.1 and an accuracy of $76\%$ compared with ETC algorithm. Sensitivity and specificity were respectively $77\%$ and $75\%$, resulting in 44 out of 58 cases being correctly classified (Figure 5a, Supplementary Figure S5b,c). Classification scores were significantly different between the lung cancer group and the control group (Mann–Whitney U test $p \leq 0.0001$, Figure 5b). The same ML approach was applied to investigate the diagnostic potential of the 78 circRNA custom panel. The RFECV method selected a signature of 21 circRNAs (Supplementary Figure S5D and Supplementary Table S2). Both RF and ETC classifiers resulted in a final AUC of 0.81 ± 0.08 and an accuracy of $72\%$ (Figure 5c and Supplementary Figure S5E). The two models differ in sensitivity and specificity; the RF model shows a higher sensitivity (Sensitivity RF: $77\%$) compared with ECT (Sensitivity ETC: $70\%$), but a lower specificity (Specificity RF: $67\%$ and Specificity ETC: $73\%$) (Supplementary Figure S5F). The classification scores of both models were confirmed to be significantly different between the two groups (Mann–Whitney U test $p \leq 0.0001$, Figure 5d). ## 2.5. Combinatorial Analysis: mRNA and circRNA Signature for the Detection of Lung Cancer Patients Combinatorial analysis of different types of molecular biomarkers has not yet been investigated in platelets. Our unique cohort of samples allows the exploration of both platelet mRNA and circRNA derived from the same source. Using the same ML approach applied before, we built a new predictive model using features derived from both the mRNA and circRNA panel (total features = 338) and excluding the two previously identified outlier samples (Supplementary Figure S3D). The RFECV algorithm selected a signature of six mRNAs (BTK, IRAK2, PSMB9, RUNX1, SYK, and LILRB1) and two circRNA (circSLC8A1 and circCHD9) (Supplementary Figure S6A and Supplementary Table S2). Once again, the RF classifier yielded the predictive model with the highest ROC AUC (0.92 ± 0.06) and accuracy ($81\%$) (Figure 6a and Supplementary Figure S6B). Sensitivity and specificity were $77\%$ and $87\%$, respectively (negative predicted value (NPV) = 0.77 and positive predicted value (PPV) = 0.85), resulting in 47 out of 58 samples being correctly classified (Figure 6b). The classification scores of the cancer and control groups showed statistically significant differences (Mann–Whitney U test, p-value < 0.0001, Figure 6c). In terms of AUC, accuracy, and specificity, this model outperforms the results seen in the previous models using an independent signature of mRNA or circRNA, suggesting a potential synergistic role of the combinatorial use of these two RNA types as molecular biomarkers. ## 2.6. Early-Stage Lung Cancer Detection Using Combinatorial Signature of mRNA and circRNA The outcome of the combinatorial mRNA-circRNA analysis suggests that the inclusion of different RNA types from the same biosource provides a biomarker signature for the detection of lung cancer. Based on these results, we sought to design a computational method for identifying a specific early-stage disease signature. For the identification of this signature, we employed and re-analyzed the 20 early-stage lung cancer samples (stage IA to IIIA) together with the control cohort ($$n = 30$$) (Supplementary Figure S7A–C). The combinatorial analysis of mRNA and circRNA panel was run through the ML algorithm, which selected a signature of only five features including two circRNAs (circSLC8A1 and circCHD9) and three mRNAs (PSMB9, RUNX1, and LILRB1). Based on this new signature, the algorithm was able to classify early-stage lung cancer samples and controls with an AUC of 0.96 ± 0.03 and an accuracy of $86\%$ (Supplementary Figure S8A). The sensitivity and specificity reached by this early-stage predictive model were $85\%$ and $86\%$, respectively. Although we observed three false negative samples, which were derived from two patients with stage IIIA and one stage IA (Supplementary Figure S8B), the classification score analysis showed a significant separation of the two groups of interest (Mann–Whitney U test, $p \leq 0.0001$, Supplementary Figure S8C). Cumulatively, our data strongly suggest that combinatorial analysis of different RNA types found in blood platelets enables optimal classification of lung cancer patients and demonstrates the potential for early-stage detection. ## 3. Discussion Platelet transcriptome is a rich source of cancer biomarkers. In this study, we developed a novel and reliable methodology for the interrogation of platelet mRNA and circRNA repertories in order to discover and assess the diagnostic value of each individual RNA type. However, most current liquid biopsy tests rely on the use and analysis of one single type of molecular biomarker, which may often lack the sensitivity and specificity required to obtain clinically reliable information. Therefore, we investigated whether combinatory analysis of platelet mRNA and circRNA derived from the same source may help us to improve the detection of lung cancer patients compared to using the single signature of both types of biomarkers. Most of the current studies on platelet transcriptome have been based on RNA sequencing data. Although RNA-seq represents a powerful tool to perform high-throughput analysis, its clinical use is limited by the long turnaround time, high cost, and the complex computational analysis. NanoString nCounter technology represents a valid alternative for the clinical implementation of LB tests. Different from the qPCR and NGS assays, this methodology permits a robust and reliable quantification of the RNA molecules without the bias introduced by reverse transcription or amplification. The automated processing minimalizes in-between steps handling errors. The time from sample preparation to data results requires only three days. However, this technology has not yet been largely utilized for liquid biopsy profiling. Clinical samples, specifically liquid biopsy specimens, often suffer from a limited amount of RNA material for subsequent gene expression analysis. We investigated whether direct usage of platelet RNA in the analysis could provide adequate gene expression profile with the least amount of input. Our findings led us to the conclusion that no pre-amplification step is required to assess gene expression in platelets from as little as 1 ng of total RNA. However, a minimum of 6 ng of RNA is recommended as initial input to reduce intrasample variability and increase the reproducibility of the assay. In this proof-of-concept study, mRNA and circRNA profiles of human platelets derived from lung cancer patients ($$n = 30$$) and non-cancer individuals ($$n = 30$$) were investigated using two different gene panels. The human immunology v2 panel includes 594 genes involved in the immune response such as cytokines, enzymes, interferons, and their receptors [37]. Out of the 594 mRNAs present in the panel, 435 mRNAs were detected in platelet samples analyzed, whereas 18 were exclusively expressed in the control group and 15 in the cancer samples. The second custom-made panel comprised 78 circRNA targets, including circRNA candidates described to be differentially expressed in lung cancer tissues, cell lines, or body fluids [38]. All 78 targets were detected in platelet samples investigated. Three of them appear to be present exclusively in the cancer group. These three circRNAs were previously found dysregulated in lung cancer tissues with an important role in cancer progression and regulation [39,44,45]. They function as a sponge and regulate the activity of important miRNA, controlling tumorigenesis, cancer progression, and proliferation processes [39,40,41,42]. In order to analyze and determine the diagnostic potential of platelet transcriptome, we developed a complete computational workflow based on nCounter data analysis and machine learning. This bioinformatic pipeline can be divided essentially into four main parts (Figure 2). In the first part, the quality controls and the filtering of possible sample and gene outliers are performed. This step is particularly important to improve and correct the data to obtain an optimal normalization and reduce bias due to the intra-variability of the samples. Based on these criteria, only two samples processed with human immunology v2 panel were excluded from downstream analysis (Control-3 and Control-5). In the second and third parts, we used and assessed two different biostatistical packages for normalization and DE analysis. Based on RLE plot analysis, DESeq2 outperformed edgeR normalization for both panels studied. DE analysis of the mRNA panel resulted in a total of 25 DE mRNA (Figure 4b). According to gene ontology (GO) analysis, the upregulated genes are mostly involved in inflammatory pathways mediated by chemokine and cytokine signaling, oxidative stress response, and cell signaling. While the downregulated genes are mainly associated with B cell and T cell activation, EGF, TGFβ, Wnt, PDGF signaling pathway, and inflammatory response. The circRNA DE analysis indicates only one significant differentially expressed circRNA between the cancer and control group (Figure 4d). Previous studies confirmed hsa_circRNA_101367 (circFUT8) as one of the most upregulated circRNA in lung cancer [43]. This circRNA can regulate the proliferation, invasion, and apoptosis of lung cancer cells by sponging miR-145 or controlling miR-944/YES1 axis [46,47]. The fourth section of this dry lab workflow employs machine learning approaches to generate prediction models. ML can be considered a novel method for developing predictive signatures that typically outperforms individual biomarkers identified by differential expression analysis. Using individual mRNA and circRNA data profiles, the ML prediction models generated reached an AUC of 0.88 using a selected signature of 28-mRNA and an AUC of 0.81 using a 21-circRNA signature (Figure 5a,c). However, the combinatorial analysis performed by combined data derived from both RNA types outperforms the results obtained with the single signature. The RFECV algorithm identified a signature of only eight biomarkers (six mRNA and two circRNA), six of which (BTK, PSMB9, RUNX1, SYK, LILRB1, and circSLC8A1) were previously selected in the individual mRNA and circRNA signatures, while IRAK2 and circCHD9 were newly included. Using these features, the prediction model showed an AUC of 0.92 with a sensitivity of $77\%$ and a specificity of $87\%$ using the RF classifier (Figure 6a). Combinatorial analysis not only reduces the number of features of the predictive model, but it also increases the AUC, improving the classification of the two groups of interest. These results indicate that a combination of different types of biomarkers possibly enhances the prediction value over that of single ones. Despite improvements in terms of AUC, accuracy, and specificity, an increase in the sensitivity of the test is not observed. Post-analysis examination of incorrectly classified samples indicated that six out of the seven false negative samples originated from patients diagnosed with stage III ($$n = 3$$) and stage IV ($$n = 3$$). This implies that the selected biomarkers from our prediction model most likely reflect the gene expression signature of the earlier stages of the disease. This hypothesis was further supported by the combinatorial analysis performed only with samples diagnosed as surgically resectable tumors (stages Ia–IIIa). This model, indeed, confirmed that five out of the eight biomarkers previously selected (circSLC8A1, circCHD9, PSMB9, RUNX1, and LILRB1) generated a predictive model specifically for early-stage cancer detection reaching an AUC of 0.96, sensitivity of $85\%$, and specificity of $86\%$ (Supplementary Figure S8A). Taken together, current findings suggest that these biomarkers may be sensitive to detecting lung cancer at early stage. Although the restricted number of platelet samples used in our current study imposes a limitation, our proof-of-concept results seem encouraging. This also includes the results from a small group of individuals diagnosed with lung nodules, as a control for non-cancerous disease, that were correctly classified by all our prediction models. A larger cohort of samples for the training and an independent validation group is needed to confirm the clinical efficacy of the combinatorial mRNA-circRNA signatures identified. Platelet transcriptome is a promising liquid biopsy biosource of cancer-related biomarkers. Although the methodology for generating platelets-derived transcriptome analysis is available [21], the implementation of platelet-derived tests in routine practice is currently hampered by a lack of standardized automated procedures for collecting and processing large numbers of clinical samples in multicenter settings and clinical validation. In this study, our goal was to design and establish, for the first time, a workflow for the nCounter analysis of mRNA and circRNA from platelets for the development of a liquid biopsy test for the detection of lung cancer. We have demonstrated the feasibility of using nCounter for the investigation of both platelet-derived mRNAs and circRNAs, including differential expression analysis, and the development of an ML predictive model. Importantly, our results, using a first multi-analytical approach for combinatorial analysis of mRNA and circRNA signature derived from blood platelets, emphasizes that the combination of the different types of RNAs may help to improve the detection of early-stage lung cancer patients. ## 4.1. Sample Collection and Population Study Whole blood samples from lung cancer patients ($$n = 30$$), asymptomatic individuals ($$n = 27$$) and people with benign lung nodules ($$n = 3$$) were provided by the Amsterdam UMC (VU University Medical Center, Amsterdam, The Netherlands) and Maastricht University Medical Center (Maastricht, The Netherlands). Whole blood was drawn at the Amsterdam UMC into EDTA-coated BD Vacutainer tubes. At the Maastricht University Medical Center, BD Vacutainer tubes containing $3.2\%$ buffered sodium citrate were used for blood-sample collection. Both collection protocols guarantee minimal platelet activation [10,21,48,49]. Patients with cancer had their blood drawn at the time of diagnosis or, in the event of surgically treatable (resectable) tumors, one day before surgery. Histological analysis of the tumor tissue biopsy was performed to determine the diagnosis. Asymptomatic individuals had no prior or current medical records of any kind of cancer during the time of blood collection and no additional examinations were carried out to verify the absence of cancer. Clinical information about the patients was gathered, including their age, gender, type of tumor, and level of metastasis (Supplementary File S1). For the current study, age- and gender-matching was done by incorporating samples of non-cancer controls and cancer patients with comparable median ages and gender distributions between the two groups. Clinical follow-up of asymptomatic controls was not available due to the anonymization of these samples in accordance with the ethical guidelines of the hospitals. The Declaration of Helsinki’s guiding principles were followed in the conduct of this investigation. This study has received approval from the medical ethics committees of the two participating hospitals (approval code: 11-4-117.4/pl, 2016.268 and 2017.545). The informed permission form for blood collection and blood platelet analysis was given to and signed by each participant. ## 4.2. Isolation of Blood Platelets Platelets isolation from the whole blood sample was performed as previously described [21]. Briefly, to separate platelet-rich plasma (PRP) and nucleated blood cells, collected blood was spun at 120× g for 20 min, followed by PRP centrifugation at 360× g for 20 min at room temperature. Resulting platelets pellet was re-suspended in RNAlater (Thermo Scientific, Waltham, MA, USA), incubated at 4 °C over-night, and stored at −80 °C until use. At the Maastricht University Medical Center, PRP was obtained by centrifuging blood sample at 240× g for 15 min. PRP was supplemented with iloprost (50 nM) to reduce ex vivo platelet activation. PRP was centrifuged for two minutes at 1600× g to pellet the platelets, followed by the addition of RNAlater and storage at −80 °C until use. Both procedures guarantee the isolation of highly pure platelet pellets with minimal leukocyte contamination and platelet activation. There were no discernible deviations detected in downstream analyses between the two methods [21,48,49]. ## 4.3. Total RNA Isolation Total RNA isolation was carried out using the mirVana RNA isolation kit according to the manufacturer’s instructions (Ambion, Thermo Scientific, cat. no. AM1560). Extracted RNA was eluded in 30 μL of mirVana buffer and the quantity and quality were assessed by RNA 6000 Picochip (Bioanalyzer 2100, Agilent, Santa Clara, CA, USA). RNA samples with RIN values higher than 7 and/or with distinguishable rRNA peaks were considered for further analysis. ## 4.4. Gene Expression Analysis Using nCounter The assays were performed using the NanoString nCounter Flex System (NanoString Technologies, Seattle, WA, USA) with two different nCounter panels for the analysis of platelet-derived RNA. The human immunology v2 panel (NanoString Technologies) targets 594 genes involved in the immune response such as cytokines, enzymes, interferons, and their receptors [37]. For each sample, 6 ng of total platelet RNA was hybridized with the biotinylated capture probe and the reporter probe attached to color-barcode tags for 18 h at 65 °C. The second panel was a custom-made panel targeting 78 circRNAs (78-circRNA panel), 6 linear reference genes and 4 mRNAs [38]. For this analysis, 8 ng of total platelet RNA from each sample was hybridized with the capture and reporter probes for 18 h at 67 °C. The automated nCounter® Prep Station was used to process the samples. The samples were purified and immobilized in a sample cartridge for data collection, where the target mRNA and circRNA in each hybridized sample were quantified, using the nCounter® Digital Analyzer. Output data in the report code count (RCC) format was exported into the nSolver analysis software (version 4.0.70). The background of each sample was computed using the geomean of the counts of the negative probe (negative controls, NCs) plus two times the standard deviation. Raw counts below the negative background value were excluded from further analysis. ## 4.5. Data Normalization and Differential Expression Analysis Pre-processing and normalization of the data were performed using R (version 4.0.3) and RStudio as graphical interface (version 2022.02.2). The quality of the raw RCC proprietary format data was initially assessed by using the NanoStringQCPro (version 1.22.0) package. Standard control metrics embedded by NanoString, such as imaging, binding density, positive control linearity, and limit of detection, were used to search for any potential outlier samples. Additionally, all samples were also subjected to supplementary exploratory examination, including the principal component analysis (PCA) and inter quartile range (IQR) method for outlier detection. Samples higher than the upper bound (Q3 + 1.5 × IQR) or lower than the lower bound (Q1 − 1.5 × IQR) were excluded from subsequent analysis. Prior to normalization, negative control probes embedded to each panel were used to filter out targets with poor expression and high background noise. Consequently, the background values were firstly calculated, by taking the mean of each sample’s negative controls increased by two times the standard deviation, and then removed from each sample. Any transcript that indicated a score of less or equal to 0 in more than $75\%$ of the examined samples was excluded from further examination. After these filtering steps, the data was again evaluated using a PCA plot. Two different packages were compared for the normalization of the data: DESeq2 (version 1.30.1) and edgeR (version 3.32.1). The normalization performance was assessed using the standard relative log expression (RLE) plot. DESeq2 was chosen as the default to perform the normalization of the data. Differential expression (DE) analysis was performed to find significantly differentially (|FC| > 0.5 and p-adj < 0.05) expressed genes between the cancer and control groups. ## 4.6. Feature Selection and Classification Analysis The machine learning approach was implemented in Python (v3.9.13) using the Scikit-learn (v1.1.0) library. Initially, the DESeq2-normalised data, along with each sample’s classification label, were imported into the python environment. For combinatorial analysis, the mRNA and circRNA normalized datasets were merged together with previous analysis. Highly correlated (higher than 0.95), as well as quasi-constant features, were excluded from further analysis. The recursive feature elimination with cross-validation (RFECV) algorithm was then utilized along with the random forest (RF) classifier to perform the feature selection in addition to the leave-one-out cross-validator (LOOCV). RFECV determined automatically the number and the composition of the most relevant features. This subset of genes, which composes the prognostic gene signature, would further be used as an input to our classification models. Two different supervised machine learning algorithms, RF and extra trees classifiers (ETC), were selected along with the selected features to perform this classification problem. In our case, the 5-fold cross-validation (5CV) was used. In a more detailed manner, the dataset was randomly divided into 5 folds, with $\frac{4}{5}$ of the data being used to train the model and the remaining $\frac{1}{5}$ being used to test its behavior. This process was repeated 5 times. The use of $k = 5$ was chosen to reduce the bias in the testing set due to the limited number of samples available. The classifier with the highest mean AUC ROC value was then selected. Probability scores for each sample were obtained from the final classifier. 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--- title: 'Recovery of Corneal Innervation after Treatment in Dry Eye Disease: A Confocal Microscopy Study' authors: - Alberto Barros - Javier Lozano-Sanroma - Juan Queiruga-Piñeiro - Luis Fernández-Vega Cueto - Eduardo Anitua - Ignacio Alcalde - Jesús Merayo-Lloves journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003258 doi: 10.3390/jcm12051841 license: CC BY 4.0 --- # Recovery of Corneal Innervation after Treatment in Dry Eye Disease: A Confocal Microscopy Study ## Abstract Purpose: To analyze the changes in corneal innervation by means of in vivo corneal confocal microscopy (IVCM) in patients diagnosed with Evaporative (EDE) and Aqueous Deficient Dry Eye (ADDE) and treated with a standard treatment for Dry Eye Disease (DED) in combination with Plasma Rich in Growth Factors (PRGF). Methods: Eighty-three patients diagnosed with DED were enrolled in this study and included in the EDE or ADDE subtype. The primary variables analyzed were the length, density and number of nerve branches, and the secondary variables were those related to the quantity and stability of the tear film and the subjective response of the patients measured with psychometric questionnaires. Results: The combined treatment therapy with PRGF outperforms the standard treatment therapy in terms of subbasal nerve plexus regeneration, significantly increasing length, number of branches and nerve density, as well as significantly improving the stability of the tear film ($p \leq 0.05$ for all of them), and the most significant changes were located in the ADDE subtype. Conclusions: the corneal reinnervation process responds in a different way depending on the treatment prescribed and the subtype of dry eye disease. In vivo confocal microscopy is presented as a powerful technique in the diagnosis and management of neurosensory abnormalities in DED. ## 1. Introduction The cornea is one of the most densely innervated tissues in the human body, mainly by sensory and autonomic nerve fibers. In addition to the importance of its sensory functions, corneal nerves help maintain the functional integrity of the ocular surface by releasing trophic substances that promote epithelial homeostasis and by activating circuits in the brainstem that stimulate tear production and blinking [1]. Damage to these nerve endings, whether mechanical in the case of eye surgery, or caused by ocular and systemic diseases, can lead to long-term damage to the integrity of the ocular surface [1,2]. Dry Eye Disease (DED) is one of the most common diseases in ocular surface consultationss worldwide [3], and it is accompanied by discomfort or pain sensations [4]. The Tear Film and Ocular Surface Society (TFOS) Dry Eye Workshop (DEWS) II [4] defined DED as a multifactorial disease of the ocular surface characterized by a loss of homeostasis of the tear film, and accompanied by ocular symptoms, in which tear film instability and hyperosmolarity, ocular surface inflammation and damage, and neurosensory abnormalities play etiological roles [4]. Two main subtypes of dry eye have been described [5]. In evaporative dry eye (EDE), tear hyperosmolarity is the result of excessive tear film evaporation in the presence of normal tear function, while in aqueous deficient dry eye (ADDE) hyperosmolarity is due to reduced tear secretion in the presence of a normal evaporation rate [6]. There is a growing interest in the study of neurosensory alterations of corneal innervation related with DED [6]. In vivo corneal confocal microscopy (IVCM) is a safe and noninvasive technique for the study and analysis of corneal innervation. Recently, several studies have used IVCM to analyze changes in the subbasal nerve plexus in DED [7,8,9], and also to evaluate the differences in this innervation between different types of dry eye [10,11]. This technique has been previously used to analyze corneal innervation in different ocular conditions, such as corneal dystrophies [12], trauma [13], infections [14], or in systemic diseases such as diabetes [15,16]. More recently, IVCM has been used to evaluate changes in the subbasal nerve plexus of patients affected by neurodegenerative diseases, such as Fibromyalgia [17,18], Parkinson’s disease [19,20], *Multiple sclerosis* [21,22,23] and even to evaluate small fiber neuropathy after viral infection with Sars-CoV-2 [24]. DEWS II established treatment strategies for DED to address tear film insufficiency (artificial tears), alterations of the palpebral margin (lid hygiene), inflammation (corticosteroids [25] immunosuppressants and immunomodulators such as Cyclosporine A, Tacrolimus and Lifitegrast [26]). Surgical approaches and nutritional supplements (diets, vitamin supplements) are also used to treat DED [27]. Artificial tears composed of blood derivatives have been gaining prominence in the treatment of DED, most notably Autologous Serum (AS), which was the first derivative of a patient’s own blood to be used for the treatment of DED [28,29]. In recent years, a type of blood-based eye drops has been described, known as PRGF–Endoret® (BTI, Vitoria, Spain), which is a plasma rich in growth factors, including epidermal growth factor (EGF), transforming growth factor–β1(TGF-β1), platelet-derived growth factor (PDGF), insulin-like growth factor I (IGF-I), vascular endothelial growth factor (VEGF), nerve growth factor (NGF), and fibronectin among others. In contrast to AS, PRGF–Endoret® is formulated without inflammatory cells such as leukocytes [30,31]. PRGF treatments have shown regenerative effects on the ocular surface epithelium in neurotrophic keratitis [32], persistent epithelial defects [33], and postoperative processes [34,35]. In addition, the safety and efficacy of PRGF for the treatment of DED have been previously demonstrated [36,37] and a clinical trial using PRGF–Endoret® compared with AS in the treatment of moderate and severe dry eye is currently under way, with results expected in 2023 [38]. However, little is known about the effect of PRGF treatment on the recovery of corneal innervation. The purpose of this study was to analyze the changes in corneal innervation in patients diagnosed with evaporative and aqueous deficient dry eye and treated with a standard treatment for dry eye disease in combination with plasma rich in growth factors. ## 2. Methods This observational retrospective, longitudinal study was conducted in accordance with the Declaration of Helsinki and approved by the Committee on Ethics in Medical Research of the Principality of Asturias with the code number 2022.167 of 11 May 2022. It follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). Prior to data collection, patients were informed about the purpose of the study and the procedures were read and signed by them. Eighty-three patients with a diagnosis of DED were recruited in this study. Inclusion criteria were Ocular Surface Disease Index (OSDI) score over 13, indicating moderate grade or higher of the disease, and tear break up time less than 10 s. In addition, subjects who had a Schirmer’s test of less than 5.5 mm were included in the subgroup of predominantly aqueous deficient dry eye (ADDE), while those above 5.5 mm were included in the predominantly—evaporative dry eye group (EDE) [6,39]. Other eye diseases that could indirectly affect corneal integrity were exclusion criteria (glaucoma, macular degeneration, previous ocular surgery procedures or corneal infections such as herpes virus, bacterial or fungal keratitis, adenovirus, and Acanthamoeba). Patients presenting systemic diseases that could cause alterations in corneal innervation such as Diabetes, Fibromyalgia, Parkinson, dysautonomia, etc. were also excluded. ## 2.1. In Vivo Confocal Microscopy (IVCM) Patients were examined using a Heidelberg® Retina Tomograph III confocal microscope equipped with the Rostock Cornea Module (Heidelberg Engineering. Heidelberg, Germany) with a 670 nm wavelength Helium-Neon diode laser, 63x objective and numeric aperture of 0.9. Before the beginning of the examination with the IVCM, topical anesthetic (Tetracaine $0.1\%$ + Oxibuprocaíne; Alcon Cusí) was applied to the eye and a sterile cap (TomoCap©, Heidelberg Engineering) was attached to the lens of the microscope and a high viscosity gel (Recugel®, Baush & Lomb®, Vaughan, ON, Canada) was used as a bonding agent between the cap and the lens. One eye of each patient was randomly selected (randomizer.org, accessed on 6 September 2022) and images of the corneal nerves of the selected eye were taken using the section mode in the central and paracentral cornea. A total of 15 to 25 images of five non overlapping areas of each eye were selected. The examination addressed the analysis of the entire corneal thickness from the epithelium to the anterior stroma, in order to make sure that the level of the sub basal nerve plexus was swept. The size of the images obtained was 384 × 384 pixel, which corresponds to an area of 400 × 400 µm. The images were analyzed and quantified automatically with ACCMetrics© software (MA Dabbah, Imaging science and Biomedical engineering, Manchester, UK) [40,41]. This software reported the measurements of the following seven parameters: Corneal Nerve Fiber Density (CNFD), which shows the total number of nerves per mm2; Corneal Nerve Branch Density (CNBD), the number of first branches originating from primary axons per mm2; Corneal Nerve Fiber Length (CNFL), which measures the total length of all nerve fibers and branches in mm/mm2; Corneal Total Branch Density (CTBD), the total number of branches/mm2; Corneal Nerve Fiber Area (CNFA) in mm2/mm2; Corneal Nerve Fiber Width (CNFW), which shows the average nerve fiber width of the sub basal plexus in mm/mm2, and Corneal Nerve Fractal Dimension (CNFrD), which is an indicator of the structural complexity of the corneal nerve image (Figure 1). The same images were also analyzed using the cell counter plugin of FIJI© image analysis software (ImageJ 1.53c: NIH, Bethesda, MD, USA) with the objective of quantify the incidence of neuromas (total number of neuromas per frame), beaded axons (count of the number of nerves which presented beaded axons per frame), and number of dendritic cells per frame of the central cornea. This part of the measurements was carried out in a semi-automatic way, in which the operator marked the presence of each of the disturbances in each image, and the Cell Counter plugin automatically calculated the total numbers [42]. The images were analyzed by a single experienced researcher. The final value used for each parameter was the average of the measure of all selected images of each patient. To avoid any mistake in the classification of selected IVCM morphological alterations, once a pathological sign of the three items mentioned previously was located, the corneal structure was examined in detail with the aim of differentiating them from similar anatomical structures [43,44]. Both types of analysis with ACCMetrics® and ImageJ® software were applied to each of the images from all patients. The average of the values obtained for each parameter were used for statistical analysis. ## 2.2. Tear Film Break Up Time To assess tear film stability, a drop of preservative-free $2\%$ sodium fluorescein was instilled into the lower fornix of the patient’s eye. The eye was then observed at the slit lamp at low magnification and the patient was urged to blink several times and keep the eyelids open until dark areas were observed within the green staining provided by the fluorescein. The time between the last blink and the appearance of the dark areas was recorded. ## 2.3. Schirmer Test To quantify tear production, the Schirmer test (Katena®, Denville, NJ, USA) was performed on all patients by placing the paper strips on the temporal part of the inner edge of the lower eyelid for 5 min after instillation of a drop of topical anesthetic to minimize reflex tearing [45,46]. After 5 min, the millimeters of impregnated strip were measured. ## 2.4. Diagnostic Questionnaires The presence of symptoms of ocular surface disease as well as their perceived severity, were assessed with the Ocular Surface Disease Index (OSDI) and the severity and intensity scales of the Symptoms Analysis in Dry Eye (SANDE). ## 2.5. Treatment The patients were divided into two groups according to the treatment therapy prescribed by the ocular surface unit of Fernández-Vega Ophthalmological Institute. Thirty-two patients were treated with a DED treatment therapy consisting of a corticosteroid regimen with Fluorometholone $0.1\%$ (FML®, Allergan©) in a descending pattern of 4 times a day for one week, three times a day for one week, twice a day for one week and once a day for one week, combined with ocular surface hydration with Trehalose $3\%$ and sodium hyaluronate $0.15\%$ (Thealoz Duo®, Thea, Milan, Italy) 4 times a week and eyelid hygiene once a day, both until the follow-up visit. This group was named as the standard treatment group. Fifty-one patients were treated with the same treatment therapy as the previous group, plus an ocular surface regeneration treatment consisting of Plasma Rich in Growth Factors 4 times a day until 3 months. According to manufacturer’s instructions, blood from this treatment group was collected into 9-mL tubes with $3.8\%$ (wt/v) sodium citrate or in serum collection tubes (Z Serum Clot activator, Vacuette, GmbH, Kremsmünster, Austria). Blood samples were centrifuged at 580× g for 8 min at room temperature in an Endoret System centrifuge (BTI Biotechnology Institute, S.L., Miñano, Alava, Spain); the whole plasma column over the buffy coat was collected using Endoret ophthalmology kit (BTI Biotechnology Institute, S.L., Miñano, Alava, Spain) avoiding the layer containing leukocytes. Platelets and leukocytes counts were performed with a hematology analyzer (Micros 60, Horiba ABX, Montpellier, France). Plasma preparations were incubated with Endoret activator (BTI Biotechnology Institute©, S.L., Miñano, Alava, Spain) at 37 °C for 1 h and PRGF supernatants were filtered, aliquoted and stored at 80 °C until use. All procedures were performed under sterile conditions inside a laminar flow hold. The patients were instructed to keep the PRGF eye drops dispensers at −20 °C for a maximum of 3 months [47,48,49]. This group was named PRGF treatment group. All patients repeated the same tests at the follow-up visit. ## 2.6. Statistical Analysis The SPSS statistical software v. 22 for Windows (SPSS Inc., Chicago, IL, USA) was used for the analysis of the data. Values were expressed as mean ± standard error of the mean (SEM). Normality of the sample was checked with the Kolmogórov–Smirnov and Shapiro Wilk tests according to the sample size. The Student’s t-test and the Wilcoxon test were used to compare the means of the different study variables of paired samples according to the distribution of the data. In addition, the effect size was calculated with Cohen’s d for each of the variables in all study groups. ## 3. Results This observational, longitudinal, and retrospective study involved 83 patients with diagnosis of Dry Eye Disease who have visited the Fernández-Vega Ophthalmological Institute between January 2020 and April 2022. Table 1 shows the demographic data; no statistically significant differences were found from the inclusion criteria for both groups. ## 3.1.1. Corneal Nerve Quantification As shown in Table 2, the automatic analysis of corneal nerves using ACCMetrics® software showed that the morphology of the subbasal nerve plexus was not significantly altered in the standard group. The data revealed an increase in nerve branching (CNBD and CTBD) and fractal dimension (CNFrD), which was not significant in any of the parameters. The rest of the values extracted from the automatic analysis such as CNFD, CNFL, CNFW, CNFA saw slightly decreased values at follow-up with respect to the baseline visit, without being statistically significant for any of the morphological parameters. The PRGF treatment group showed an evident increase in CNFD and CNFL ($p \leq 0.001$), CNBD, CNFA and Fractal Dimension ($p \leq 0.005$) and CTBD ($p \leq 0.05$). Corneal Nerve Fiber Width did not show any differences. ## 3.1.2. Morphological Alterations and Cell Infiltration The semi-automatic analysis of IVCM images using FIJI® software showed a significant reduction in the presence of dendritic cells for the standard treatment group ($p \leq 0.05$), as well as in the count of Axonal Beads for both groups ($p \leq 0.005$ for standard treatment group and $p \leq 0.05$ for PRGF treatment group). Although the presence of neuromas was low in both groups, the changes observed were not significant after treatment. ## 3.1.3. Tear Film and Ocular Surface Disease Questionnaires The assessment of tear quantity with the Schirmer test did not show statistically significant differences in either treatment group at the follow-up visit. Tear stability measured with the Fluorescein Break Up Time was significantly increased in the PRGF treatment group ($p \leq 0.005$) compared to the standard treatment group ($$p \leq 0.654$$). The OSDI score decreased significantly for both the standard treatment group ($p \leq 0.005$) and the PRGF combination therapy group ($$p \leq 0.005$$). The SANDE frequency and severity questionnaire score were also significantly decreased for both treatment groups ($p \leq 0.001$). ## 3.2. Subtypes of Dry Eye Disease To study the response of corneal innervation according to the type of dry eye, the sample was divided into EDE and ADDE according to the measurement of tear quantity. ## 3.2.1. Difference between Subtypes of Dry Eye Disease Baseline data were compared to identify differences between the two subtypes of dry eye disease studied. The CNFD values for the ADDE subtype was 15.007 ± 8.122 fibers per mm, while for the EDE group it was 18.218 ± 5.99 ($$p \leq 0.066$$). CNBD was 18.766 ± 16.323 branches per mm in the ADDE and 21.129 + 13.541 ($$p \leq 0.339$$) for the evaporative subgroup. For CNFL the values for the ADDE were 10.784 ± 4.228 mm per mm, and 12.185 ± 3.130 ($$p \leq 0.147$$) for the EDE. Differences were also not statistically significant for both groups in neuromas ($$p \leq 0.195$$), dendritic cells ($$p \leq 0.700$$) and axonal beadings ($$p \leq 0.861$$). For the ADDE group, the psychometric questionnaires showed an OSDI of 41.337 ± 23.638, SANDE frequency of 65.943 ± 28.673 and SANDE intensity of 60.188 ± 25.850, while for the EDE group the values were OSDI 38.400 ± 20.648 ($$p \leq 0.748$$), SANDE frequency 71.142 ± 26.297 ($$p \leq 0.326$$) and SANDE intensity of 65.535 ± 21.745 ($$p \leq 0.420$$). ## 3.2.2. Evaporative Dry Eye Subtype Fifteen patients of this subtype of Dry Eye were treated with PRGF while fourteen patients were treated with the standard treatment group. Baseline values were compared according to the assigned treatment, finding no significant differences for any of the treatment groups ($$p \leq 0.363$$ for CNFD, $$p \leq 0.692$$ for CNBD, $$p \leq 0.233$$ for CNFL, $$p \leq 0.234$$ for Schirmer, $$p \leq 0.870$$ for Fbut, $$p \leq 0.847$$ for dendritic cell count, $$p \leq 0.477$$ for neuromas count, $$p \leq 0.533$$ for Beadings count, $$p \leq 0.486$$ for OSDI score, $$p \leq 477$$ for neuromas count, $$p \leq 0.533$$ for Beadings count, and $$p \leq 0.062$$ for SANDE intensity questionnaire) apart from the SANDE frequency questionnaire which showed significant differences in baseline values according to treatment groups ($$p \leq 0.027$$). As shown in Figure 2, nerve parameters such as density, length and number of branches increased slightly in the PRGF-treated group at the follow-up visit but were not statistically significant. The same values decreased for the standard treatment group, being significant for CNFD ($p \leq 0.05$) and for CNFL ($$p \leq 0.01$$). The morphological alterations of nerves (neuromas and beadings) and cell infiltration (dendritic cells) showed no relevant differences in any of the parameters analyzed, apart from the dendritic cell count in the PRGF treatment group ($p \leq 0.05$). Although not significant, a certain increase in the presence of neuromas was observed at the follow-up visit for the PRGF treatment group. Focusing on the tear film and psychometric questionnaires, results in Figure 3 showed that tear film volume was reduced was reduced for both treatment therapies, with the reduction being statistically significant for the standard treatment group ($$p \leq 0.045$$). Tear break-up time did not change significantly for either treatment group at the follow-up visit. The OSDI questionnaire remained significantly unchanged at the follow-up visit in both the standard and combined PRGF treatment groups. For the SANDE frequency and intensity questionnaires, reductions were significant for both groups of treatment at the follow-up visit ($p \leq 0.005$). ## 3.2.3. Aqueous Deficient Dry Eye Subtype Thirty-three patients of this subtype of Dry Eye were treated with PRGF while eighteen patients were treated with the standard treatment group. Data for one patient in the PRGF treatment group was estimated as a missing value because no post-treatment tear volume value was available. As in the EDE subtype, baseline values were compared according to treatment type and no significant differences were found for CNBD ($$p \leq 0.148$$), FBut ($$p \leq 0.749$$), Schirmer ($$p \leq 0.232$$), dendritic cell count ($$p \leq 0.916$$), neuromas ($$p \leq 0.619$$), OSDI score ($$p \leq 0.286$$), SANDE frequency ($$p \leq 0.798$$) and SANDE intensity ($$p \leq 0.250$$). However, significant differences in these values were identified for CNFD ($$p \leq 0.001$$), CNFL ($$p \leq 0.003$$) and axonal beads count ($$p \leq 0.013$$). In this subtype of DED, Figure 4 shows a statistically significant increase for length, density, and number of nerve branches ($p \leq 0.05$ for all of them) after combined treatment with PRGF, compared to the standard treatment group, which also showed an increase, without statistical significance. In the case of morphological alterations and presence of inflammation, axonal beads significantly decreased in the standard treatment group ($$p \leq 0.05$$). No other relevant differences were observed in any of the parameters analyzed, although their values decreased at the follow-up visit in both treatment subgroups. The tear film study showed (Figure 5) an increase for the combined PRGF treatment subgroup and the standard treatment subgroup, but this was not significant for either of them. An increase in tear break-up time was found in the PRGF subgroup ($$p \leq 0.005$$) while the same value decreased slightly for the standard treatment subgroup ($$p \leq 0.248$$). As for the psychometric questionnaires, both OSDI and SANDE frequency and intensity had significantly reduced values at the follow-up visit, with $p \leq 0.005$ for each of them in both treatment subgroups. ## 3.3. Effect Size To answer the question of how big the change in the analyzed variables after each of the treatments was, the effect size was calculated for each of them according to the subtype of DED, comparing the values obtained at the baseline visit with those at the follow-up visit. ( Table 3). For the EDE subtype, the standard treatment had a negative effect for CNFD, CNBD and CNFD, and for nerve length was at the edge of the medium size. With PRGF treatment, the effect size, although low, was positive for the same variables. As for morphological alterations of the subbasal nerve plexus in this type of DED, the effect size was negative for all of them, apart from neuromas in the PRGF treatment group, although with a low effect. The effect size value was at the limit of the medium consideration for dendritic cells in the PRGF treatment group. The tear film study did not reveal a significant effect size on tear break-up time. However, a negative effect of medium size on tear quantity—quantified by Schirmer’s test—was observed for the standard treatment group. No significant effect size was observed in both treatment groups for the OSDI score, while for the SANDE questionnaires this value was medium-high for both groups and higher for the PRGF treatment group. In the aqueous deficient dry eye subtype, the two treatment groups had a positive effect on CNFD, CNBD and CNFL, with Cohen’s d being higher for the PRGF treatment group for these three variables. The effect was negative for all of the three subbasal nerve plexus morphological alterations studied, with a value of 0.756—medium-high effect size—for axonal bead count in the standard treatment group. Tear analysis for this dry eye subtype showed higher Cohen’s d values in the PRGF treatment group. Note the negative effect for BUT in the standard treatment group. The effect size was medium for the OSDI score in both treatment groups and for the SANDE questionnaires in the standard treatment group, while in the PRGF treatment group the effect found was high. ## 4. Discussion We conducted a study including 83 eyes of 83 patients diagnosed with DED to compare the changes in corneal innervation when treated with a standard treatment and the same treatment in combination with plasma rich in growth factors. The results of the study suggested that the combined treatment therapy with PRGF outperforms the standard treatment therapy in terms of subbasal nerve plexus regeneration, significantly increasing length, number of branches and nerve density, as well as significantly improving the stability of the tear film analyzed with fluorescein BUT. Our findings were consistent with previous studies analyzing the response of corneal innervation to different topical treatments. The positive effect of hematic derivatives on the ocular surface has been studied repeatedly. Fox et al. [ 28] described in 1984 an improvement in the symptomatology and objectivity of fifteen patients treated with artificial tears made from the patient’s serum, which had not improved with conventional artificial tears. These results were also confirmed by other authors, including a randomized clinical trial [50], which is consistent with our results in a significant decrease in OSDI, improvement in BUT and also found no significant changes in the Schirmer’s measurement. The effect that hematic derivatives induce in corneal innervation has also been the subject of previous studies. In this regard, there has been some discrepancy between publications. Giannaccare et al. [ 51] found a significant increase in CNFD, CNFL and CNFrD in patients treated with peripheral allogenic blood serum and umbilical cord blood serum in their prospective study, although with a short follow-up period. On the other hand, Mahelkova’s prospective work [52] found no differences in subbasal plexus nerve fibers in patients treated with autologous serum tears. These discrepancies may be explained by the difference in measuring devices, the cause of the DED, the sample size or the type of hematic derivative. PRGF–Endoret® is an autologous platelet plasma rich in growth factors, standardized to reduce the proinflammatory cytokines in its formulation by removing leukocytes and by a heating treatment [53]. This feature would help to treat DED, as it is associated with a chronic inflammatory process [54]. Due to the high concentration in growth factors, PRGF-based eye drops promote a range of biological events, including cell proliferation, migration, and differentiation, while protecting against microbial contamination on the ocular surface [47,55,56]. A higher concentration of most growth factors was found in PRGF formulations than in AS [57]. Among growth factors, NGF has been shown to stimulate corneal epithelium proliferation and promote subbasal nerve plexus regeneration [58]. Our results showed no statistically significant differences in the subbasal nerve plexus between the two DED subtypes analyzed, with smaller values for ADDE. Other studies found significant reductions in corneal nerves in ADDE versus EDE using a semi-automated quantification method that reports higher values for these parameters than we obtained with the technique used in our study [10]. However, when we grouped our sample into the two dry eye subtypes according to the treatment prescribed, we found significant differences in the baseline values of CNFD and CNFL of the ADDE, with lower values in the subgroup of combined treatment with PRGF. This treatment subgroup also had higher OSDI and SANDE values and previous studies found a negative correlation between OSDI and CNFD [59]. This may be explained by the fact that in professional practice within the ocular surface unit, the ophthalmologist could have prescribed combined treatment with plasma rich in growth factors to patients who showed a higher subjective severity as measured by psychometric questionnaires, based on his previous experience and research in this field [32,35,55,60]. On the other hand, we found no significant changes in corneal innervation at the follow-up visit in the standard treatment group, and even a slight decrease in CNFL and CNFD. There are some discrepancies between previous studies regarding how corticosteroid [61,62] and immunomodulation-based treatments [63,64] affect the subbasal nerve plexus in DED. Reduction in subbasal nerves, as seen in cases of DED treated with cyclosporine A [64], may be explained by reduced NGF production and other cytokines, such as IL-1 and TNF-α. Although it is known that these treatments act by intervening in the inflammatory process associated with the disease, their mechanisms of action on corneal innervation remains unclear. Consistent with a reduction of inflammation, we observed a significant reduction in the dendritic cell count in the standard treatment group. Villani et al. [ 62] also found no significant changes in the subbasal nerve plexus in their open-label and masked study, using a semi-automated nerve fiber quantification system. This study and that of Li Bei [65] are also consistent with ours in the reduction of dendritic cells after treatment with topical steroids. The DEWS established at its first meeting in 2007 that hyperosmolarity and tear film instability are the starting point for the development of dry eye disease [66] The main cause of EDE is known to be tear film disruption accompanied by Meibomian gland dysfunction, and reduced tear secretion secondary to age-related degeneration of the lacrimal gland is the main cause of lacrimal secretion deficit dry eye [6]. It is therefore difficult to draw the line between dry eye due to a lack of secretion and evaporative dry eye, so it would be more accurate to talk about which is the predominant category in each case [5]. Our results suggest that the combined treatment with PRGF in DED contributes to the creation of the ocular surface regeneration scenario, in which corneal regeneration is promoted [3,67]. When this regenerative scenario occurs in ADDE, it induces an improvement in the stability and quantity of the tear film, as well as anti-inflammatory agents and growth factors, which create the perfect context for the corneal reinnervation process, and we observed a significant increase in this process compared to the group treated with standard treatment. However, when the scenario occurs in EDE, the treatment also contributes to the regeneration of the ocular surface, but without solving one of the main problems which is the alteration of the eyelids and dysfunction of the Meibomian glands, which will continue to generate a situation of evaporative excess and instability of the tear film, which are described as one of the main pathogenic factors of the vicious circle in ocular surface disease [67]. As a limitation of the study, in the analyzed sample, all the patients were prescribed for eyelid hygiene protocol, but the condition of the eyelids was not monitored, so it could not be concluded whether the alterations at this level were resolved at the follow-up visit. This may explain why the most significant changes at the level of the sub basal nerve plexus are in the ADDE and raises the need for future studies quantifying the status of the eyelids and the degree of Meibomian gland dysfunction. Moreover, all the patients included in our study had a BUT below 10 s, so all had an evaporative component, and were subsequently grouped according to the reduction in tear secretion, so our study is limited by not having subjects with BUT greater than 10 s accompanied by low Schirmer values. The sample size, although in line with other published studies, can be considered small and unrepresentative and our study is also limited in this aspect, so prospective studies with larger samples are needed. ## 5. Conclusions The corneal reinnervation process responds in a different way depending on the treatment prescribed and the subtype of dry eye disease. 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--- title: An Early and Sustained Inflammatory State Induces Muscle Changes and Establishes Obesogenic Characteristics in Wistar Rats Exposed to the MSG-Induced Obesity Model authors: - Matheus Felipe Zazula - Diego Francis Saraiva - João Lucas Theodoro - Mônica Maciel - Eliel Vieira dos Santos Sepulveda - Bárbara Zanardini de Andrade - Mariana Laís Boaretto - Jhyslayne Ignácia Hoff Nunes Maciel - Gabriela Alves Bronczek - Gabriela Moreira Soares - Sara Cristina Sagae Schneider - Gladson Ricardo Flor Bertolini - Márcia Miranda Torrejais - Lucinéia Fátima Chasko Ribeiro - Luiz Claudio Fernandes - Katya Naliwaiko journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003260 doi: 10.3390/ijms24054730 license: CC BY 4.0 --- # An Early and Sustained Inflammatory State Induces Muscle Changes and Establishes Obesogenic Characteristics in Wistar Rats Exposed to the MSG-Induced Obesity Model ## Abstract The model of obesity induced by monosodium glutamate cytotoxicity on the hypothalamic nuclei is widely used in the literature. However, MSG promotes persistent muscle changes and there is a significant lack of studies that seek to elucidate the mechanisms by which damage refractory to reversal is established. This study aimed to investigate the early and chronic effects of MSG induction of obesity upon systemic and muscular parameters of Wistar rats. The animals were exposed to MSG subcutaneously (4 mg·g−1 b.w.) or saline (1.25 mg·g−1 b.w.) daily from PND01 to PND05 ($$n = 24$$). Afterwards, in PND15, 12 animals were euthanized to determine the plasma and inflammatory profile and to assess muscle damage. In PND142, the remaining animals were euthanized, and samples for histological and biochemical analyses were obtained. Our results suggest that early exposure to MSG reduced growth, increased adiposity, and inducted hyperinsulinemia and a pro-inflammatory scenario. In adulthood, the following were observed: peripheral insulin resistance, increased fibrosis, oxidative distress, and a reduction in muscle mass, oxidative capacity, and neuromuscular junctions, increased fibrosis, and oxidative distress. Thus, we can conclude that the condition found in adult life and the difficulty restoring in the muscle profile is related to the metabolic damage established early on. ## 1. Introduction The model of obesity induced by perinatal injections of monosodium glutamate is widely studied and known in the literature [1,2,3]. The main alteration determined in this model is the damage and cell death of neurons in the hypothalamic nuclei, mainly in the arcuate nucleus (ARC), where this neuronal loss impairs the signaling mediated by insulin and affects the energy balance of the organism [3,4,5,6]. Due to the hyperphagic characteristic of the MSG model [7], the excessive consumption of nutrients is associated with the energy imbalance promoted by the hypothalamic lesion. In this model, obesity is associated with the secretion of pro-inflammatory cytokines by adipose tissue, which leads to insulin resistance, stimulating cell damage and impairing metabolic homeostasis in the adipose tissue, liver, pancreas, brain, and muscles [1,2,8,9,10,11,12,13]. It is recognized in the literature that insulin sensitivity and resistance depend on AMPK-mediated signaling pathways, where the main effect of this pathway is the increased GLUT4 translocation in the membranes of insulin-dependent tissues [8,14,15]. As a consequence of this activation, there is a reduction in the phosphorylation rate of the mTOR protein [16,17]. As insulin sensitivity is reduced, especially in skeletal muscle, mTOR signaling which has been implicated in insulin resistance and obesity pathogenesis contributes to the development of the inflammatory process by stimulating the activation of the NfᴋB pathway [1,17,18,19,20]. The reduction in the body growth of animals exposed to the MSG model has been evidenced by several authors [1,9,21,22,23]. This reduction can be identified immediately after the induction period, depending on the concentration and frequency of injections, and is also confirmed in adulthood [22,24]. In addition, the changes in growth caused by this model are not reversible when considering muscle tissue, which suggests that metabolic impairment may be established earlier than has been described in the literature and may resemble models of metabolic programming that affect muscle development and maturation [25,26,27]. Although the endocrine, metabolic, and autonomic aspects of obesity induced by MSG have been extensively studied and described for adult animals, the early effects of MSG exposure and the establishment of muscle changes are less understood and have been little explored. Thus, the present study aimed to identify whether the changes found in adulthood were established early by exposure to MSG. ## 2.1.1. Lactation Period To access the effect of MSG injections on the animals’ developmental delay, the pups were weighed and measured every 2 days. Evaluating the body weight of these offspring, we could observe that from PND07 onwards, MSG animals showed reduced weight gain when compared to CTL ($p \leq 0.0001$; Figure 1A), and this difference persisted until euthanasia (PND15). Likewise, MSG animals showed less gain in nasoanal length from PND07 when compared to the CTL group ($p \leq 0.0001$; Figure 1B). However, when evaluating the Lee index, it was only possible to observe lower values in MSG animals in PND09 ($$p \leq 0.002$$; Figure 1C). However, when we observed the total gain during the period, through the calculation of the area under the curve, we could observe that in terms of body weight ($p \leq 0.0001$; Figure 1A’), nasoanal length ($p \leq 0.0001$; Figure 1B’), and in the Lee index ($$p \leq 0.0223$$; Figure 1C’), MSG animals showed reduced development. ## 2.1.2. Post-Weaning Period To assess whether the effect of MSG injections would persist into adulthood and whether it participates in the onset of metabolic syndrome and obesity, the animals were weighed, and their food intake was measured once a week from weaning until euthanasia (day 142 of age). The percentage of body weight gain ($p \leq 0.0001$; Figure 2A) in MSG animals was minor when compared to CTL from week 8 ($$p \leq 0.0134$$). Interestingly, this difference was accentuated from week 10, the period where puberty started ($p \leq 0.001$) and worsened from week 14 with the onset of adulthood ($p \leq 0.0001$). As expected, the MSG effect on general food consumption was higher in MSG animals when compared to CTL animals ($$p \leq 0.0019$$; Figure 2B). Furthermore, to confirm those findings, the area under the curve of total body weight gain and total food consumption was calculated. In both situations, differences between the groups were found. Thus, the total weight gain was lower in MSG animals when compared to CTL ($$p \leq 0.0026$$; Figure 2A’), while the total food intake was higher in MSG animals when compared to CTL ($$p \leq 0.0018$$; Figure 2B’). ## 2.2. Intraperitoneal Glucose Tolerance Test (ipGTT) and Insulin Measurement A glucose tolerance test was performed to assess whether alteration of glucose sensibility and metabolism had been established at 135 days of life, followed by a measurement of plasma insulin levels. In this sense, when we evaluated the response in the ipGTT test ($p \leq 0.0001$; Figure 3A), we could observe that even with no difference in baseline blood glucose levels between the groups, the MSG animals had higher blood glucose levels at T15 ($$p \leq 0.0167$$) and a smaller decrease in blood glucose at T30 ($$p \leq 0.0492$$) when compared to CTL. When assessing insulin levels ($p \leq 0.0001$; Figure 3B), it was identified that MSG animals had elevated basal insulin concentrations when compared to CTL animals. Furthermore, this elevation of insulin concentrations was maintained throughout the test when compared to CTL, suggesting a picture of persistent hyperinsulinemia. When calculating the area under the curve for the total concentration of glucose and insulin throughout the experiment, it was observed that the MSG animals had higher glycemia ($$p \leq 0.0317$$; Figure 3A’) and this was accompanied by higher plasma insulin ($p \leq 0.0001$; Figure 3B’). ## 2.3.1. Corporal Characterization On day PND15, MSG animals presented lower weight ($p \leq 0.0001$) and nasoanal length ($$p \leq 0.0002$$) when compared to CTL. However, when calculating the Lee index, there was no difference between the groups ($$p \leq 0.6851$$) Figure 4. ## 2.3.2. Plasmatic Profile When we evaluated the plasma of MSG and CTL animals, no differences were identified for glucose ($$p \leq 0.312$$), total cholesterol ($$p \leq 0.9248$$), LDL ($$p \leq 0.6471$$), VLDL ($$p \leq 0.9951$$), triacylglycerols ($$p \leq 0.9951$$), and HDL ($$p \leq 0.3501$$). When calculating the dyslipidemia predictors, no change was identified in the lipid ratio ($$p \leq 0.4318$$), in the Castelli index 1 ($$p \leq 0.9485$$), and in the Castelli index 2 ($$p \leq 0.9485$$). Similar results were identified for muscle damage markers, where lactate ($$p \leq 0.7789$$) and creatine kinase ($$p \leq 0.8872$$) levels were not different in MSG animals when compared to CTL, Figure 5. Interestingly, when measuring insulin levels and calculating HOMA-IR, it was observed that MSG animals showed an increase when compared to CTL ($p \leq 0.0001$, in both). Meanwhile, the calculation of QUICKI ($p \leq 0.0001$) showed a reduction in MSG animals when compared to CTL. However, MSG animals showed increased concentrations of TNFα ($$p \leq 0.0284$$), IL-06 ($p \leq 0.0001$), and IL-10 ($$p \leq 0.0053$$), Figure 6. ## 2.3.3. Skeletal Muscle Antioxidant System and Oxidative Damage When evaluating the antioxidant system and oxidative damage of the skeletal muscle pool, it was again identified that there were no differences between the MSG and CTL groups in the activity of the enzymes superoxide dismutase ($$p \leq 0.5249$$), catalase ($$p \leq 0.5198$$), and total cholinesterase ($$p \leq 0.3159$$), as well as in the levels of soluble proteins ($$p \leq 0.8843$$), lipid peroxides ($$p \leq 0.5253$$), and non-protein thiols ($$p \leq 0.9972$$), Figure 7. ## 2.4.1. Corporal Characterization The analysis of the animals in the PND142 showed that the MSG animals had a lower weight ($p \leq 0.0001$) and nasoanal length ($$p \leq 0.0002$$) when compared to the CTL animals. However, when compared to the CTL animals, the MSG animals had a higher Lee index ($$p \leq 0.0153$$) and higher adiposity ($p \leq 0.0001$), Figure 8. ## 2.4.2. Plasmatic Profile When the plasma profile of the animals was evaluated, the MSG animals showed an increase in glucose ($$p \leq 0.0011$$), total cholesterol ($p \leq 0.0001$), LDL ($p \leq 0.00$,01), and VLDL ($$p \leq 0.0052$$) cholesterol fractions, as well as in total triacylglycerols levels ($$p \leq 0.0052$$). There was no difference in HDL between the groups ($$p \leq 0.0657$$). When performing the calculation of dyslipidemia predictors, an increase in the lipid ratio was identified ($$p \leq 0.0115$$), in the Castelli index 1 ($$p \leq 0.0001$$), and the Castelli index 2 ($$p \leq 0.0061$$). Likewise, when evaluating some muscle damage markers, an increase in lactate levels ($$p \leq 0.0008$$) and a decrease in creatine kinase concentrations ($p \leq 0.0001$) were identified in the MSG animals when compared with the CTL animals, Figure 9. Interestingly, when measuring the insulin levels and calculating HOMA-IR, it was observed that the MSG animals showed an increase when compared to the CTL animals ($p \leq 0.0001$, in both). Meanwhile, the calculation of QUICKI ($p \leq 0.0001$) showed a reduction in MSG animals when compared to the CTL animals, Figure 10. ## 2.4.3. Skeletal Muscle Structure When we evaluated the macroscopic characteristics of the muscle, the MSG animals had lower EDL muscle weight ($p \leq 0.0001$) and shorter SOL ($$p \leq 0.0011$$) and EDL muscle length ($p \leq 0.0001$) when compared to the CTL animals. When evaluating the muscular structure of the EDL and SOL, it was identified that the MSG animals had a higher density of fibers per mm2 in both muscles ($$p \leq 0.0022$$; $p \leq 0.0001$, respectively), when compared to the CTL animals, accompanied by a reduction in the cross-sectional area of muscle fibers, observed in both muscles of the MSG animals ($$p \leq 0.0020$$; $p \leq 0.0001$, respectively). In addition, we found a reduction in the largest ($$p \leq 0.0003$$; $p \leq 0.0001$, respectively) and smallest ($$p \leq 0.0006$$; $p \leq 0.0001$, respectively) diameters in both muscles of the MSG animals when compared to the CTL animals. It was also possible to identify that the SOL of the MSG animals showed a reduction in the diameter ratio, an important predictor of muscle fiber rounding ($$p \leq 0.0178$$), Table 1. Another feature evaluated was the distribution of capillaries and nuclei in the cells of both muscles. MSG animals showed a greater distribution of capillaries in EDL when compared to CTL ($p \leq 0.0001$), while the distribution of capillaries was reduced in SOL ($p \leq 0.0001$). In the distribution of nuclei, the MSG animals showed lower values in SOL ($p \leq 0.0001$) when compared to the CTL animals. However, when we evaluated the presence of nuclei in a central position in the muscle fibers, we could observe that for both the EDL and SOL muscles, the MSG animals showed an increase comparable to the CTL animals ($p \leq 0.0001$, in both). In the case of the myonuclear domain, there was a reduction in MSG animals compared to the CTL animals for EDL only ($$p \leq 0.0081$$), Table 1. When evaluating the distribution of connective tissue in the EDL and SOL muscles, it was found that in MSG animals there was an increase in total connective tissue in both muscles when compared to the CTL animals ($p \leq 0.0001$; $$p \leq 0.0008$$, respectively). In addition, in the MSG animals higher values of connective tissue in the epimysium ($p \leq 0.0001$, in both) and perimysium ($p \leq 0.0001$, in both) in both muscles were shown. However, endomysium thickening was identified only in the EDL of MSG animals ($$p \leq 0.0004$$). The evaluation of the type of collagen in each of the muscles revealed that in the EDL, the MSG animals showed a reduction in type I collagen ($$p \leq 0.0014$$) and an increase in type III collagen ($$p \leq 0.00014$$), while in the SOL, only type III collagen reduction ($$p \leq 0.0078$$) could be identified in MSG animals when compared to the CTL animals, Table 1. ## 2.4.4. Fiber Types Profile and Neuromuscular Junction Structure When analyzing the prevalence of each type of f, the MSG animals showed a reduction in the proportion of type I fibers in EDL and SOL ($p \leq 0.0001$, in both) and a reduction in the cross-sectional area of type I fibers in EDL and SOL ($p \leq 0.0001$, in both) when compared to the CTL animals. In SOL, MSG animals showed an increase in the proportion of IIA-type fibers ($p \leq 0.0001$), and in both muscles, EDL and SOL, there was a reduction in the cross-sectional area of IIA-type fibers ($$p \leq 0.0093$$; $p \leq 0.0001$, respectively) of the MSG animals when compared to the CTL. Furthermore, it was identified that the MSG animals showed a reduction in the cross-sectional area of the neuromuscular junctions both in the EDL ($$p \leq 0.0167$$) and in the SOL ($p \leq 0.0001$) when compared to the CTL animals. The MSG animals showed a reduction in the major ($p \leq 0.0001$) and minor ($p \leq 0.0001$) diameters in the SOL muscle junctions when compared to the CTL animals. Therefore, when evaluating the ratio between the largest and smallest diameters, a predictor of damage to the structure, it was observed that the MSG animals had a lower ratio ($$p \leq 0.0102$$) when compared to the CTL animals. Finally, when analyzing the antioxidant system and oxidative damage in EDL and SOL, it was identified that catalase activity was reduced in EDL ($$p \leq 0.0101$$) and increased in SOL ($p \leq 0.0001$) in MSG animals compared to the CTL animals. However, in both muscles, the MSG animals showed an increase in the concentration of proteins ($$p \leq 0.0268$$, in both), of lipid peroxides ($$p \leq 0.0405$$; $p \leq 0.0001$, respectively), and a reduction in the concentration of non-protein thiols ($p \leq 0.0001$; $$p \leq 0.0003$$, respectively), when compared to the CTL animals. Finally, when we evaluated the total cholinesterase activity in both muscles, the MSG animals showed a decrease in activity when compared to the CTL animals ($$p \leq 0.0001$$; $$p \leq 0.0003$$, respectively), Table 1. ## 2.5. Multivariate Analysis When the interaction between the variables was evaluated, it was observed that the MSG animals already had body impairment characteristics of the model in the PDN15 (F1,10 = 2.7748, R2 = 0.2172, $$p \leq 0.0021$$, Figure 11A). These characteristics are due to the delay in body development (F1,10 = 13.4489, R2 = 0.5735, $$p \leq 0.0027$$, Figure 11B) and the inflammatory profile established in the animals, associated with the state of hyperinsulinemia (F1,10 = 28.0549, R2 = 0.7372, $$p \leq 0.0025$$, Figure 11E). Despite these findings, changes in plasma (F1,10 = 0.2948, R2 = 0.0286, $$p \leq 0.9722$$, Figure 11C) or in the muscle antioxidant system (F1,10 = 0.3958, R2 = 0.0381, $$p \leq 0.2875$$, Figure 11D), which are commonly described as fundamental factors for establishing of the condition in adult animals, were not identified at this age. We also observed that the alterations observed in the young animals intensified in adulthood, producing the body impairment characteristic of MSG induction (F1,14 = 18.3229, R2 = 0.5668, $$p \leq 0.0002$$, Figure 12A). These model characteristics are due to delayed body development, reduced muscle mass, and fat accumulation (F1,14 = 24.7399, R2 = 0.6386, $$p \leq 0.0002$$, Figure 12B). In this sense, it is possible to identify the establishment of the metabolic syndrome in these animals (F1,14 = 21.0869, R2 = 0.6009, $$p \leq 0.0002$$, Figure 12C). These factors are fundamental for the impairment identified in the muscle structure, such as the reduction in fiber size, alteration in the distribution of nuclei and capillaries, and thickening of the connective envelopes (F1,14 = 20.9169, R2 = 0.5991, $p \leq 0.0001$, Figure 12D). It was also possible to observe a reduction in the oxidative capacity of muscle fibers (F1,14 = 19.5689, R2 = 0.5629, $$p \leq 0.0001$$, Figure 12E) and a reduction in neuromuscular junctions (F1,14 = 12.8698, R2 = 0.4789, $$p \leq 0.0002$$, Figure 12F), in addition to the accumulation of oxidative damage markers accompanied by impairment of the muscular antioxidant system (F1,14 = 12.8419, R2 = 0.4784, $$p \leq 0.0002$$, Figure 12G). ## 3. Discussion The literature has reported the effects of MSG as an inducer of obesity, where the main object of study is adult animals with obesity already installed. Here, we present a new study proposal, where the main objective was to investigate whether exposure to MSG in the first days of postnatal life could produce early metabolic changes. In this study, instead of evaluating only the conditions of the animals in the adult phase, we sought to identify the characteristics of the animals 10 days after the end of the monosodium glutamate injections. The main results obtained agree with the results established in the literature for the MSG-obesity model; however, significant alterations in the inflammatory and insulin profile were identified, early in the installation of obesity parameters. These results suggest a slightly different scenario from that classically found for this model, in which damage to the hypothalamic nuclei may be associated with early identified pro-inflammatory disorders and hyperinsulinemia. Thus, it is likely that the muscle changes induced by the model are due not only to the chronicity of the metabolic condition in adulthood but also to this metabolic pattern established early on. The induction of obesity by MSG causes cytotoxic damage to the hypothalamic nuclei, which induces significant changes in the development of animals, mainly due to cell loss in the GH-secreting hypothalamic nuclei [28], as has been well described in the literature [7] and previously identified in works by our research group [9,21,29,30]. The relationship between reduced body growth and reduced muscle growth has also been extensively explored [1,22,28], with a consensus in the literature that MSG cytotoxicity also results in a model of short stature due to hormonal insufficiency that leads to low growth [22,31]. In this sense, the reduction in body weight gain accompanied by a lower nasoanal length in the MSG animals suggests that from the second day after the end of the injections (PND07) such changes are being established, corroborating that the effects of MSG reach different tissues, since the start of the exhibition. It is known that GH participates in the close relationship between factors that repress the development and differentiation of muscle fibers, such as myostatin, and that in the MSG-induced obesity model, GH-secreting hypothalamic nuclei are affected, altering GH secretion. Thus, it is possible that in this model this injury results in the attenuation of the feedback mechanisms that repress myostatin activity, producing a reduction in the size of muscle fibers and altering the proportion of fiber types during the final process of development [32,33]. Here, the data obtained demonstrate that in the presence of MSG, muscle fibers are smaller, suggesting the participation of regulation mediated by GH-myostatin, in the reduction of muscle fiber size. Furthermore, such results may be due to an imbalance in the secretion of growth factors, due to muscle damage induced by the obesity model. The model may promote the reduction of growth factors, such as the fibroblast growth factor, required by the muscle for proliferation, as well as for the growth and differentiation of mesenchymal cells during development [8,34,35]. It has also been reported that the metabolic changes associated with the model may originate from lesions that occur in several central structures of the paraventricular region of the hypothalamus, where the arcuate and ventromedial nuclei are the most affected. It is believed that about 80 to $90\%$ of the control of food consumption, energy expenditure, and glucose homeostasis is due to the neuronal activity of these nuclei [12,14,36]. Dysfunction of these structures promotes an imbalance i metabolic pathways, causing the increase in plasma lipid concentrations and their incorporation into adipose tissue, as found in the adult animals of this work [1,12]. Dysfunction of these structures promotes an imbalance of metabolic pathways, causing an increase in plasma lipid concentrations and their incorporation into adipose tissue, as found in the adult animals of this work [37]. By evaluating the levels of insulin and plasmatic cytokines, we could see that through a reduction in glucose sensibility, it is first possible that signaling of peripheral insulin resistance, accompanied by a pro-inflammatory profile, evidenced by increased concentrations of IL-6 and TNFα, is already identifiable in PND15. The increase in IL-6 associated with the MSG model has an important effect on muscle development, as it reduces IGF-1 secretion and muscle sensitivity to insulin, negatively modulating the differentiation, and growth of muscle fibers [38,39,40]. In models of dietary obesity, increased IL-6 secretion has also been associated with reduced muscle mass [41,42]; however, in models that use MSG exposure, there is a recurrent reduction in the secretion of this cytokine in animals. The effect of MSG was also evaluated in adulthood, which supports the idea that there may be early metabolic programming in the active phase of obesity [43,44]. Finally, we found an increase in plasma TNFα secretion associated with this scenario, which may be related to the lower availability of MyoD for the paracrine effect, causing a reduction in the differentiation of myoblasts into myocytes, in addition to a reduction in the fusion of myotubes, which is implicated in the muscular alterations identified in the study. In addition, the increase in TNFα is related to reduced insulin sensitivity, increased muscle catabolism, sarcomere ubiquitination, and NADPH oxidation, which together may negatively modulate muscle development and differentiation [38,39,40,41]. The characteristics related to the number, position, and structure of the myonuclei of MSG-obese animals in the present study, have been associated with the response mediated by the chronic stress resulting from the established metabolic syndrome [45,46], which may be indicative of damage caused by the incomplete state of differentiation muscle, resulting from the early inflammatory process. Furthermore, this set of changes found in the proposed obesity model is essential to induce the phenotypic transition of muscle fibers [47,48,49]. The condition of insulin resistance promoted by the inflammatory process, which becomes chronic due to the dyslipidemic profile, is a determining factor for the reduction of muscle oxidative capacity, especially when associated with the characteristics of reduced size and the number of types I and IIA fibers and the increase in type I fibers and IIB fibers [49,50,51]. The establishment of the early hyperinsulinemic condition, found in the PND15 of MSG-obese animals, may indicate the anticipation of the dynamic phase of obesity, where the induction of increased glucose uptake by insulin-responsive tissues seems to occur. However, maintenance of this condition in PND142, where obesity was chronic due to persistent damage, reinforces the establishment of peripheral reduction in glucose sensibility, as observed in MSG animals [52,53,54]. During the worsening of obesity, damage resulting from MSG-induced hepatotoxicity is common, which causes an increase in the generation of reactive oxygen species and feeds back the inflammatory process [15,55,56]. In addition, the inflammatory process, mainly mediated by the increase in TNFα, negatively and significantly modulates the rate of lipolysis, favouring adipose tissue hypertrophy and an increase in fat panicles [12,31,57]. Something intriguing in the MSG cytotoxicity model of obesity induction is the difficulty in applying treatment protocols that restore the physiological state of these animals, after the establishment of obesity. In a resistance exercise model, obese MSG animals submitted to the training protocol showed partial reversal of the obesogenic parameters, but even though they were significant, the reduction in lipemia and adipose panicles did not return to the values found in the control animals [15]. Likewise, after applying a swimming model, the reduction in adiposity and insulin secretion did not return to physiological patterns, and changes in intestinal structure were still persistent [58]. Previous data from our research group show that whole-body vibration training was not able to completely repair the soleus [29,59], extensor digitorum longus [30], tibialis anterior [21], and diaphragm [60] muscles despite promoting anti-obesogenic effects. Furthermore, it did not restore the physiological levels, biochemical, and structural parameters of the liver, adipose tissue, and plasma [9]. Finally, models with leucine [61] and taurine [62] supplementation, as well as herbal treatment [63], showed a partial reduction in body adiposity and food intake, accompanied by improvement in glucose metabolism and insulin sensitivity and cardiovascular effects. Considering all the initial characteristics of the neurotoxic effect of MSG, associated with the hyperinsulinemic and pro-inflammatory condition in the dynamic phase of obesity induction, we can correlate these developmental alterations with the muscular characteristics found. Thus, as obesity becomes chronic and metabolic syndrome sets in, it is reasonable that most studies find similar results in obese adult animals under the influence of MSG. Although there were several forms of administration, the doses and periods proposed and evaluated, the analyses have the observation of animals at a certain moment in common, when obesity is already well established. Despite this limitation, it is common to find studies that manage to partially repair the damage caused, a fact that reinforces our hypothesis that early damage is established and prevents the correct development of animals, suggesting that exposure to MSG, in the perinatal phase, is capable of inducing some metabolic programming that becomes worse over time. Thus, although the MSG model is remarkably effective in inducing obesity, limitations arising from the proposed study setting may underestimate the systemic effects of MSG and the possible effects of treatment protocols. Finally, considering the role of muscle tissue in metabolic regulation, obtaining results that support muscle restructuring may represent an important strategy for improving metabolic conditions, even in the absence of the reversal of body parameters of obesity. ## 4.1. Ethical Approval All trials in this study were conducted following national and international recommendations and legislation [64] and with the approval of the University Animal Care Committee (protocol # $\frac{08}{18}$). ## 4.2. Animals and Experimental Design From postnatal day (PND) 01 to PND05, male Wistar rats ($$n = 24$$) received daily subcutaneous injections of MSG solution in the dorsocervical region (4 mg·g−1 body weight, MSG group) or equimolar saline solution (1.25 mg g−1 body weight, control group—CTL) [3,9]. Every two days, the animals were weighed and their nasoanal length was measured, until the 14th day of life. In PND15, 12 animals were euthanized ($$n = 6$$ per group) to assess the establishment of molecular damage. After weaning (PND21), food consumption and the evolution of body weight were monitored weekly. All of the animals were housed in standard cages at a constant temperature (22 ± 1 °C), on a 12 h light-dark cycle, and had ad libitum access to water and standard laboratory chow (BioBase®, Santa Catarina, Brazil). ## 4.3. Intraperitoneal Glucose Tolerance Test (ipGTT) and Insulin Dosage The ipGTT was performed after eight hours of fasting and consisted of a small cut in the tail of the animals followed by the collection of blood samples to measure glucose with the aid of an Accu Chek glucometer (Roche Diabetes Care Brasil LTDA, São Paulo, Brazil). Blood was collected in the fasted state (time 0) and 15, 30, 60, and 90 min after IP injection of a glucose overload (2 g·kg−1 of body weight). Additional blood samples were collected with heparinized glass capillaries and then centrifuged at 4 °C and 12,000× g for 10 min. The supernatant was stored in a freezer at −80 °C for later measurement of insulin by radioimmunoassay. ## 4.4. Euthanasia and Material Collection In PND15, the Lee index (∛bodyweight / nasalanal length × 1000) was calculated. The animals were then desensitized in a carbon dioxide chamber and then euthanized by decapitation [7]. Blood was collected in heparinized tubes and centrifuged at 4 °C, at 12,000× g for 10 min to measure the plasma biochemical and inflammatory profile. The abdominal wall and pelvic limb muscles were collected (approximately 0.2 g) and intended for the analysis of oxidative damage markers. In PND142, the Lee index (∛bodyweight/nasalanal length × 1000) was calculated. The animals were then desensitized in a carbon dioxide chamber and then euthanized by decapitation [7]. Retroperitoneal, perigonadal, and brown fats were removed, weighed, normalized to g·100 g−1 of body weight, and used to calculate body adiposity [2]. Blood was collected in heparinized tubes and centrifuged at 4 °C, at 12,000× g for 10 min to measure the plasma biochemical profile. The extensor digitorum longus (EDL) and soleus muscle (SOL) were dissected, collected, weighed, measured, and destined for biochemical and morphological analysis. ## 4.5. Skeletal Muscle Structure Analysis The muscle was sectioned in the middle region of the muscle belly, and the proximal fragments of the right antimere were fixed in metacarn and stored in $70\%$ alcohol. Subsequently, they were submitted to the histological procedure with dehydration in an increasing series of alcohol, diaphanization in N-butyl alcohol, and inclusion and embedding in histological paraffin, after which they were cut transversely at 5 µm with the aid of a microtome. For the study of muscle fibers, the sections were stained with hematoxylin–eosin (HE), morphologically analyzed under a light microscope, and 10 visual fields of interest were photographed at 400× magnification. In the images obtained, the cross-sectional area of the fiber and cores, fiber density, number, and position of nuclei were analyzed. The distal fragments of the right antimere were used for histoenzymological analysis, which analyzes the oxidative and glycolytic metabolism of muscle fibers. For this, immediately after collection, they were covered with neutral talc for tissue preservation and subsequently frozen in liquid nitrogen, conditioned in cryotubes, and stored in a Biofreezer at −80 °C, up to a 7 µm section in a cryostat chamber (LUPETEC CM 2850 Cryostat Microtome) at −20 °C. The sections were submitted to the enzymatic reaction of NADH–TR (nicotinamide adenine dinucleotide—tetrazolium reductase). This analysis quantifies the different types of muscle fibers (I, IIa, and IIb) according to the tone presented in the fibers after the reaction. For each animal, five microscopic fields were randomly chosen at 200× magnification to count and analyze the area size of the different types of fibers. The proximal fragments of the left antimere were used for the study of JNM, and they were immersed in Karnovisky’s fixative. The muscles were cut longitudinally into small portions with stainless steel blades, and the selected cuts were found in the nonspecific esterase reaction. Subsequently, a morphological analysis of the slides was performed with a light microscope, photomicrographing the visual fields of interest at 200× magnification. The size of the area, the largest diameter, and the smallest diameter of 150 JNM per animal were measured. The morphological analyzes were performed in the Image ProPlus 6.0 (Media Cybernetics, Inc., Rockeville, MD, USA) program, and in each image the muscle fasciculus was scanned to randomly select ten fibers, thus totaling 120 fibers per animal. ## 4.6. Antioxidant System and Oxidative Damages Analysis For the evaluation of the antioxidant system, the distal portion of the left antimer of EDL muscle was homogenized with Tris-HCl buffer (0.4 M, pH 7.4) and centrifugated for 20 min at 4 °C and 12,000× g. Tissue protein quantification was determined by the Bradford method, using bovine serum albumin as a standard. All of the samples were normalized to 1 mg protein × mL−1. The enzymatic activity of the superoxide dismutase (SOD—EC 1.15.1.1) of the muscles was determined by inhibiting the formation of formazan blue by reducing nitrotetrazolium blue (NBT); increasing absorbance by reducing NBT by the superoxide anion was monitored at 560 nm (RS: 182 mM sodium carbonate buffer pH 10.2; 50 µM EDTA; 100 µM NBT; 36.86 mM hydroxylamine sulfate). The values were expressed in U × mg protein−1 [65]. The enzyme activity of the catalase (CAT—EC 1.11.1.6) of the muscles was determined through the formation of H2O and O2 from the consumption of H2O2, the reduction in absorbance by the consumption of H2O2 was monitored at 240 nm (RS: 50 mM of potassium phosphate buffer pH 7.0; 10 mM H2O2). The values were expressed in mM of H2O2 consumed × min−1 × mg protein−1 [66]. The lipid peroxidation index (LPO) of the muscles was determined by the generation of complexes between Fe+2 and xylenol orange and the formation of a chromophore stabilized by butylated hydroxytoluene. The absorbance by the generation of the chromophore was measured at 560 nm. The values were expressed in nM hydroperoxides × mg protein−1 [67]. The enzymatic activity of total cholinesterase (ChE—EC 3.1.1.8) was determined by the generation of 2-nitrobenzoate-5-mercaptothiocholine from the interaction of thiocholine and DTNB; the increase in absorbance by the formation of the chromophore was monitored at 405 nm (RS: 487 µM DTNB; 2.25 mM acetylthiocholine iodide). The values were expressed in nM acetylthiocholine hydrolyzed × min−1 × mg protein−1 [68]. ## 4.7. Statistical Analysis Data were expressed as mean ± standard deviation and analyzed using descriptive and inferential statistics in the R program version 4.0.3 [45]. Data were evaluated for normality (Shapiro–Wilk test). Parametric data were evaluated by the Student’s t-test. In the case of non-parametric data, the test used was the Mann–Whitney U test. 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--- title: κ-Selenocarrageenan Oligosaccharides Prepared by Deep-Sea Enzyme Alleviate Inflammatory Responses and Modulate Gut Microbiota in Ulcerative Colitis Mice authors: - Kai Wang - Ling Qin - Junhan Cao - Liping Zhang - Ming Liu - Changfeng Qu - Jinlai Miao journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003262 doi: 10.3390/ijms24054672 license: CC BY 4.0 --- # κ-Selenocarrageenan Oligosaccharides Prepared by Deep-Sea Enzyme Alleviate Inflammatory Responses and Modulate Gut Microbiota in Ulcerative Colitis Mice ## Abstract κ-Selenocarrageenan (KSC) is an organic selenium (Se) polysaccharide. There has been no report of an enzyme that can degrade κ-selenocarrageenan to κ-selenocarrageenan oligosaccharides (KSCOs). This study explored an enzyme, κ-selenocarrageenase (SeCar), from deep-sea bacteria and produced heterologously in Escherichia coli, which degraded KSC to KSCOs. Chemical and spectroscopic analyses demonstrated that purified KSCOs in hydrolysates were composed mainly of selenium-galactobiose. Organic selenium foods through dietary supplementation could help regulate inflammatory bowel diseases (IBD). This study discussed the effects of KSCOs on dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in C57BL/6 mice. The results showed that KSCOs alleviated the symptoms of UC and suppressed colonic inflammation by reducing the activity of myeloperoxidase (MPO) and regulating the unbalanced secretion of inflammatory cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-6 and IL-10). Furthermore, KSCOs treatment regulated the composition of gut microbiota, enriched the genera Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus and inhibited Dubosiella, Turicibacter and Romboutsia. These findings proved that KSCOs obtained by enzymatic degradation could be utilized to prevent or treat UC. ## 1. Introduction Carrageenan is a sulfated linear polysaccharide extracted from the cell wall of red algae. Based on the difference in the number of sulfate groups and the presence of 3,6-anhydro-α-D-galactopyranosyl (3,6-AG), carrageenans are further classified into κ-, ι- and λ-carrageenans [1]. κ-*Carrageenan is* alternately composed of 4-linked-α-D-3,6-anhydrogalactose (DA) and 3-linked-4-O-sulfated-β-D-galactopyranose (G4S), which has been recognized as safe by the U.S. Food and Drug Administration [2,3]. However, its application is limited due to poor solubility and low bioavailability [4]. κ-Carrageenan oligosaccharides obtained by κ-carrageenan degradation can greatly improve these properties. Moreover, κ-carrageenan oligosaccharides exhibited antioxidant [5], anticoagulation [6] and antitumor effects [7]. It is well known that *Se is* an indispensable trace element for human health and can only be obtained from food. KSC is a kind of Se polysaccharide made from natural κ-carrageenan, in which Se partially replaces sulfur (S) [8]. It is reported that KSC had an immunomodulatory function and inhibited tumor growth in H22 tumor-bearing mice [9]. Theoretically, low molecular weight KSCOs hydrolyzed by KSC possess remarkable bioactivity. At present, KSCOs were created chemically using sodium selenite and κ-carrageenan oligosaccharides, but the unstable structure of products makes this process unsuitable for large production. In contrast, enzymatic hydrolysis yields products with a controlled structure and no contamination, which is now the preferred method for oligosaccharides production. However, the enzyme hydrolyzing KSC to KSCOs has rarely been researched. In the previous study, we described a potential κ-selenocarrageenase isolated from the cold seep in the South China Sea [8]. Here, this κ-selenocarrageenase was expressed in *Escherichia coli* and its degradation activity was demonstrated. Therefore, a novel and easy strategy for the utilization of KSC to produce functional KSCOs was provided. UC is a chronic and recurrent inflammation of the intestine with a high incidence in Western countries [10,11]. The pathogenesis of UC is thought to be related to genetic susceptibility, immunity, environment and intestinal mucosal barrier loss [12]. The main clinical symptoms of UC include abdominal pain, diarrhea, bloody mucus and purulent stools [13,14]. It is worth noting that UC increases the risk of colorectal cancer, the third most common malignant tumor in the world [15]. Nevertheless, current drugs used to treat UC, such as aminosalicylate and mesalazine, tend to decline in response to treatment over time and lead to disease complications [11]. In addition, such drugs may induce adverse reactions, such as dilated cardiomyopathy and severe heart failure [16]. Therefore, it is urgent to develop new therapeutic drugs. In fact, nutrition plays a crucial role in preventing IBD [17]. Nutritional deficiencies, including micronutrients, are common in patients with IBD [18,19]. It has been demonstrated that dietary Se supplementation enhanced intestinal antioxidant function and relieved inflammation [20]. On the other hand, previous studies have shown that carrageenan oligosaccharides had potent effects on inhibiting the release of inflammatory cytokines [21,22,23]. However, the beneficial effects of KSCOs remain unclear for IBDs, such as UC. In this work, we heterologously expressed and characterized a κ-selenocarrageenase from a marine bacterium named Bacillus sp. N1-1. The structure of KSCOs obtained from κ-selenocarrageenase hydrolysis of KSC was analyzed. KSCOs possess the activity of both selenium and κ-carrageenan oligosaccharides. Thus, we speculated that KSCOs may have effects on the treatment of UC. DSS is a polymer of anhydroglucose that induces UC when introduced through drinking water in rodents, such as guinea pigs, rabbits and mice [24,25]. This chemical compound is now widely used in basic research related to colitis. In this study, we aimed to explore the effects of KSCOs on DSS-induced UC in mice and investigated the underlying mechanism of action. ## 2.1.1. Bioinformatics Analysis of SeCar As our previous study mentioned, a deep-sea bacterium Bacillus sp. N1-1 has been preliminarily demonstrated to degrade κ-selenocarrageenan [8]. The SeCar gene (GenBank accession number: MW366920) from N1-1 genome was predicted as a candidate κ-selenocarrageenase as it was noted to be coding a putative glycoside hydrolase 16 (GH 16) protein. The open reading frame (ORF) of this gene consisted of 2184 bp and encoded 728 deduced amino acid residues, the first 25 amino acid residues of which were identified as a signal peptide sequence. The theoretical molecular weight of the mature protein was 79.51 kDa and the predicted isoelectric point was 4.40. It was predicted to be a stable hydrophilic protein with mean hydrophilicity (gravy) of −0.735, fat coefficient of 66.46 and instability index of 33.46. According to the conserved domain analysis (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 16 August 2020), the complete sequence of SeCar is mainly composed of four domains, of which the amino acid residues Arg153-Lys353 belongs to the GH16 family domain. GH16 family is concluded as a polyspecific glycoside hydrolase family and contains different enzymes, including κ-carrageenase, β-agarase, β-porphyranase, licheninase and laminarinase [26,27]. Multiple sequence alignment was carried out between SeCar and other reported GH 16 family κ-carrageenases (Figure S1). On the basis of alignment results, SeCar contained the conserved region ExDxxE, which is responsible for the double displacement mechanism in κ-carrageenase catalysis [28,29]. The above bioinformatics analysis elucidated the characteristics of SeCar as a κ-carrageenase. Additionally, the BLASTP analysis showed that SeCar shared the highest sequence identity of $28.12\%$ with the κ-carrageenase of *Pseudoalteromonas tetraodonis* JAM-K142 among all characterized proteins [30]. ## 2.1.2. Expression and Purification of SeCar For better characterization, the SeCar gene was cloned and expressed successfully in Escherichia coli. It was shown that the purified κ-selenocarrageenase was analyzed by SDS-PAGE in Figure S2. After the gene fused with (His)6-tag was expressed, the molecular weight of the purified recombinant protein was approximately 80 kDa, which was larger than the theoretical molecular weight (79.51 kDa). The activity of purified recombinant SeCar was 133 U/mg, which was much higher than that of the wild enzyme (18.58 U/mg). ## 2.1.3. Biochemical Properties of SeCar Figure 1A shows that the optimal temperature of purified SeCar was 40 °C. In addition, its activity remained stable at 20 °C, and $80\%$ of its initial activity was maintained at 30 °C for up to 2 h (Figure 1B). The thermal stability of SeCar facilitates its storage and biotransformation in industrial production. The effects of various metal ions and chemical reagents on SeCar activity are shown in Figure 1C. K+ and Mn2+ slightly stimulated the enzyme activity. Cu2+, Fe2+ and Fe3+ inhibited the enzyme activity, among which Cu2+ had the greatest inhibitory effect, causing $80\%$ of the enzyme activity impaired. The kinetic parameters of purified SeCar were determined using κ-selenocarrageenan as the substrate. The Vmax and Km values were 12.0048 mg/(mL·min) and 0.2389 mg/mL, respectively (Figure 1D), indicating that the κ-selenocarrageenase SeCar showed high affinity to the κ-selenocarrageenan. ## 2.2. Determination and Evaluation of KSCOs Structure According to the high-performance gel permeation chromatography (HPGPC) spectra (Figure S3A) and the detailed values (Table S1), the KSCOs were mainly distributed below 1500 Da, among which $37.14\%$ were 1379.49 Da and $31.69\%$ were 816.82 Da. ## 2.2.1. Electrospray Mass Spectrometry (ESI-MS) Analysis To clarify the structure of KSCOs, MS analysis at negative ESI mode was conducted. The MS image of KSCOs (Figure S3B) revealed peaks at m/z 437 and m/z 546, corresponding to [(DA-G4Se)]− and [(DASe-G4Se)]−, respectively. The over selenated disaccharide units of DASe-G4Se are attributed to the mixing of ι-carrageenan in commercial κ-carrageenan [31,32]. The disaccharide unit in ι-carrageenan contains two sulfate groups, which might be replaced by selenate. Combined with the result of thin layer chromatography (TLC) analysis (Figure S4), we speculated that the peaks at m/z 341.1, m/z 665.2 and m/z 989 were representative of (DA-G4)−, [(DA-G4)2]− and [(DA-G4)3]−, respectively, without carrying the selenate group. This deselenylation was possibly caused by the high cone voltage in the mass spectrometer [31,33]. ## 2.2.2. Fourier Transform Infrared (FTIR) Spectroscopy Analysis The FTIR spectra analysis of KSCOs was shown in Figure 2. The intense peak at 3283 cm−1 was ascribed to the stretching vibration of O-H. The weak stretching band near 2925 cm−1 was ascribed to the stretching vibration of C-H. The peak at approximately 1598 cm−1 was associated with the stretching vibration of C=O. In addition to characteristic absorption peaks of polysaccharides, the peak near 1250 cm−1 was ascribed to the stretching vibration of S=O, indicating that the sulfate groups in κ-selenocarrageenan were not completely replaced. However, due to the selenylation modification, the absorption peaks near 1375 cm−1 and 762 cm−1 were attributed to the Se=O asymmetric stretching and C–O–Se symmetric vibrations, respectively [34]. Additionally, a strong absorption near 1024 cm−1 was assigned to the stretching vibration of the C–O–C glycosidic bond, indicating a pyranose unit in the carrageenan basic structure [35]. ## 2.2.3. Nuclear Magnetic Resonance (NMR) Spectroscopy In the 1H NMR spectrum of the KSCOs (Figure 3A), there were signals of α and β configurations at the reducing end of G4S. The signal at δ 5.39 ppm was attributed to G4S-H-1α, while the chemical shift signal of G4S-H-1β appeared at δ 4.67 ppm [36]. Since selenylation occurred at C-4, the chemical shift of H-4 after selenite moved to the low field near δ 4.86 ppm. However, due to the overlap with the hydrogen signal in the solvent HOD, the chemical shift was not obvious. It has been reported that the signal δ 5.25 ppm was attributed to the H-1 of DA [37]. In this study, DA-H-3 and DA-H-5 were located in the region of δ 4.67 ppm and δ 4.17 ppm, respectively, due to the dehydration reaction at C-3 and C-6 of DA. As shown in Figure 3B, there were four anomeric carbon signals, which were 101.6, 101.3, 97.4 and 93.5 ppm, respectively. κ-*Carrageenan is* an alternating galactan of 1,3-linked β-D-galactopyranose 4-O-sulfate and 1,4-linked 3,6 anhydro-α-D-galactopyranose [2]. The anomeric carbon of β-D galactose was more than 100.0 ppm, while the terminal carbon of α-D galactose was less than 100.0 ppm. Therefore, the signals at 101.6 and 101.3 ppm were attributed to →3)-β-G4s-(1→ and →3)-β-G4Se-(1→ anomeric carbon. At 97.4 ppm, it was →4)-α-DA (1→ anomeric carbon signal; 93.5 ppm was →3)-G4Srα reducing anomeric carbon signal. The high field 62.1 ppm was →3)-β -G4s -(1→ C-6 signal. All chemical shifts were summarized in Table 1 and Table 2. The 1H and 13C spectra of KSCOs were analyzed, and it was found that selenylation had no significant influence on the basic structure of κ-carrageenan, which was consistent with the previous report [38]. Since no substitution of the C-6 position was found in the DEPT 135° spectrum, we speculated that selenylation did not occur in position C-6 of →4)-α-DA-(1→. Therefore, combining ESI-MS, FTIR and NMR data, the selenium oligosaccharides in KSCOs were mainly composed of selenium-galactobioses and the predicted structure was shown in Figure S3C. ## 2.3.1. KSCOs Relieved Symptoms of UC The degree of UC in mice was assessed through body weight, disease activity index (DAI) and colon length. There was a significant decrease in the body weight of the DSS mice in this study ($p \leq 0.001$) (Figure 4A). KSCOs exhibited significant improvement in body weight loss ($p \leq 0.001$). Additionally, as shown in Figure 4B, mice treated with KSCOs exhibited an improved health status compared to mice with only DSS according to DAI. Furthermore, compared with DSS only, KSCOs treatment reduced the shortening of the colon significantly in mice ($p \leq 0.01$) (Figure 4C,D). According to the morphological examination (Figure 5A), colon tissues of the DSS group showed obvious erosion, goblet cell disappearance and inflammatory cell infiltration compared with the intact inner wall of the normal group, while KSCOs treatment alleviated these pathological changes of colonic tissue in colitis. The above phenomenon revealed that KSCOs relieved the systemic (weight loss and DAI) and local (CL shortened and HDS) symptoms of UC. ## 2.3.2. KSCOs Regulated the Inflammatory Responses As shown in Figure 5B, MPO activity was significantly activated in the colon tissue of the DSS group ($p \leq 0.001$), indicating an excessive inflammatory response. However, KSCOs reduced MPO activity dramatically ($p \leq 0.001$) compared with the DSS group. In addition, we measured the contents of proinflammatory cytokines including TNF-α and IL-6 and the anti-inflammatory cytokine IL-10 in serum. As shown in Figure 5C,D, compared to the normal group, DSS exposure increased the contents of TNF-α ($p \leq 0.01$) and IL-6 ($p \leq 0.001$) significantly, while it reduced the content of IL-10 ($p \leq 0.001$). ## 2.3.3. KSCOs Reshaped the Composition of Gut Microbiota A total of 713,927 sequences were obtained from 18 samples among the normal group, DSS group, and KSCOs group. Richness (Ace index) and diversity (Shannon and Simpson indices) of microbial communities were shown by alpha-diversity analysis (Figure S5A–C). The Ace, Shannon, and Simpson indices in the DSS group all displayed a decline when compared to the normal group. Although the Ace, Shannon, and Simpson indices did not significantly increase following the administration of KSCOs in comparison to the DSS group, the increase in gut microbial richness and diversity was partially explained. The rarefaction curves tended to be saturated platforms (Figure S5D), which indicated that the majority of the microbial diversity had been collected and the sequencing coverage was adequate. As shown in Figure 6A, gut microbiota of mice in the three groups were mainly composed of Firmicutes and Bacteroidota at the phylum level. However, administration of KSCOs decreased the relative abundance of Firmicutes while increasing the relative abundance of Bacteroidota in DSS-induced colitis mice. *In* general, compared with the normal group, DSS significantly increased the ratio of Firmicutes to Bacteroidota (F/B) ($p \leq 0.05$), while this phenomenon was significantly reversed by KSCOs ($p \leq 0.05$) (Figure 6C). To further assess the predominant bacterial communities in the intestine across the three groups, linear discriminant analysis (LDA) and effect size (LefSe) was carried out. *The* generated cladogram reflected different gut microbiota compositions among mice from all groups (Figure 7A). The LDA discriminant histogram counted the microbial taxa with significant effects in multiple groups. Greater relative species abundance is represented by higher LDA scores. Via LDA scores, the findings revealed that Bifidobacterium, Lachnospirace-ae NK4A136 group, and Ruminococcus were prevalent in the KSCOs group while Dubosiella, Turicibacter and Romboutsia were prominent in the DSS group (Figure 7B). Specific differences between groups were evaluated at the genus level to further illustrate how KSCOs treatment affected the composition of gut microbiota (Figure 6B). At the genus level, compared to DSS group, KSCOs administration significantly enhanced the relative abundance of Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus (Figure 7D–F). Additionally, compared to the normal group, the relative abundance of Dubosiella ($p \leq 0.001$), Turicibacter ($p \leq 0.01$) and Romboutsia ($p \leq 0.01$) increased significantly in the DSS group, while this increase was inhibited by KSCOs administration (Figure 7G–I). Acetate, propionate, butyrate and total SCFA concentrations were all considerably lower after receiving DSS without treatment, as shown in Figure 8 ($p \leq 0.001$, $p \leq 0.05$, $p \leq 0.01$ and $p \leq 0.001$, respectively). However, compared with the DSS group, KSCOs increased the concentration of butyrate significantly ($p \leq 0.05$) and tended to promote the biosynthesis of acetate and propionate. ## 3. Discussion KSC is a marine selenium polysaccharide synthesized by selenization modification of κ-carrageenan, which has been included in the national safety standard for the use of the food nutrition fortification standard [39]. However, KSC has a high molecular weight and low bioavailability. The chemical or physical degradation process of KSC is uncontrollable, and the structure of degradation products is unstable. To date, there have been few studies on the hydrolysis of KSC by κ-selenocarrageenanase. In this study, we prepared KSCOs from a κ-selenocarrageenanase named SeCar. The novelty of the SeCar sequence suggests that it may exhibit properties distinct from other κ-carrageenases. It is worth noting that this is the first demonstration of KSC degradation by a κ-carrageenase. There are multiple factors contributing to the pathogenesis of IBD, including the influence of micronutrients [40]. Summarizing recent reviews, Se exhibited an important role in the pathogenesis of IBD and Se deficiency was common in IBD patients [20,41]. Hence, the essential trace element Se has been drawn more attention for IBD prevention and treatment. Compared with inorganic Se, organic Se possesses lower toxicity and higher bioavailability. Here, we investigated the effects of KSCOs on DSS-induced colitis. According to the acceptable upper limit of adult Se intake (400 μg/d) recommended by WHO [2004] and Chinese Nutrition Society [2013], the doses of KSCOs were designed as 1.6, 3.2 and 6.4 mg/kg, which were equivalent to 25.5, 51 and 102 μg/kg of oral Se in mice, respectively [42]. The results showed that KSCOs relieved the systemic (weight loss and DAI) and local (CL shortened and HDS) symptoms of UC. MPO is a proinflammatory oxidase secreted by neutrophils and macrophages, which can destroy intestinal mucosal cells and cause inflammatory responses; therefore, it usually shows high activity in UC patients [43]. Additionally, after the occurrence of colitis, proinflammatory cytokines, such as TNF-α, IL-6 and IL-1β, are secreted and accumulated in large quantities due to the excessive activation of immune cells. These cytokines directly caused mucosal and tissue damage, triggering disease-specific inflammatory responses in colitis [44]. Regulating the secretion of these cytokines is extremely important for alleviating the inflammatory responses in colitis. Therefore, KSCOs could reduce inflammatory responses in UC mice via ameliorating neutrophil infiltration and regulating the level of inflammatory cytokines (TNF-α, IL-6 and IL-10). The gut microbiota is considered as an important factor influencing the occurrence and severity of DSS induced colitis [45]. The positive effects of dietary Se supplementation on intestinal inflammation have been well demonstrated [40,46]. Moreover, as previously reported, at least part of the mechanism was due to Se altering the gut microbiota rather than directly affecting the gut [47]. To identify whether KSCOs regulates gut microbiota, 16S rRNA sequencing in fecal bacteria DNA was conducted and the high dose (6.4 mg/kg) group of KSCOs was selected to be sequenced. In this research, it can be found that dietary selenium KSCOs regulated the diversity and composition of gut microbiota in the DSS-induced mice, consistent with previous reports [48,49]. Specifically, KSCOs showed a function of reducing the ratio of Firmicutes to Bacteroidota (F/B). F/B is commonly denoted as the degree of dysbiosis in IBD [50,51], and a high proportion of *Bacteroidota is* associated with the resistance to inflammation [52]. Thus, it can be indicated that KSCOs could restore intestinal homeostasis by regulating the abundance of Firmicutes and Bacteroidota. At the genus level, KSCOs enhanced the abundance of Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus. Bifidobacterium is recognized as a probiotic, promoting intestinal health in the following aspects. In the intestine, Bifidobacterium can synthesize exopolysaccharides as the fermentation substrate of microbiota, which is beneficial to intestinal health [53,54]. Additionally, Bifidobacterium can enhance intestinal epithelial barrier function through metabolites and inhibit the inflammatory responses [55,56]. Furthermore, Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus were reported to promote the production of SCFAs, which were capable of maintaining epithelial health and immune balance of the intestine [57,58,59]. KSCOs administration inhibited the growth of harmful bacteria, such as Dubosiella, Turicibacter and Romboutsia. The trends in the relative abundance of Dubosiella between groups were consistent with previous reports about UC [60,61,62]. However, more research is needed to determine the effect of Dubosiella on colitis. Increases in both Turicibacter and Romboutsia are associated with the development of colitis. It has been reported that Turicibacter with high abundance aggravated intestinal damage and led to serious complications [63]. Moreover, *Romboutsia is* considered as a pathogen, and its abundance is increased in many diseases, such as neurodevelopmental disorders [64], irritable bowel syndrome [65] and gastric cancer [66]. It can be found that the abundance of Romboutsia was increased in the intestine of DSS-induced colitis mice compared with that of healthy mice in this study, consistent with views in relevant studies [67,68,69]. SCFA has also been reported to ameliorate colitis through suppressing proinflammatory cytokines, such as TNF-α and IL-6 [70,71]. The reason for the higher SCFA content in the KSCOs group compared with the DSS group might be due to enriched Bifidobacterium, Lachnospiraceae_NK4A136_group and Ruminococcus. Moreover, a previous report found that organic sources of Se promoted the biosynthesis of propionate and butyrate [72]. There have been many studies on the remodeling of gut microbiota by different Se sources, such as selenium-enriched yeast [72], selenium-enriched probiotics [49] and selenium-containing tea polysaccharides [73]. The mechanism, however, is complex and few studies have clarified it. In this study, we described the effects of KSCOs on the gut microbiota in mice for the first time, but the role of Se in gut microbiota needs to be further explored in subsequent research. Taken together, KSCOs might alter the composition and metabolites of gut microbiota to relieve DSS-induced colitis. ## 4.1. Enzymology Experiment The κ-selenocarrageenase (SeCar) gene (Locus_tag: N1.1_GM000361) was obtained from the whole genome of Bacillus sp. N1-1 (GenBank accession number: CP046564). κ-Selenocarrageenan was purchased from Qingdao Pengyang Biological Engineering Co., Ltd., Qingdao, China. ## 4.1.1. Bioinformatics Analysis Bioinformatics prediction and analysis of the amino acid sequence were carried out online. Physicochemical properties of amino acids were predicted using ExPASyProtparam (https://web.expasy.org/protparam/, accessed on 16 August 2020). The hydrophobicity of protein was predicted by ExPASyScale (https://web.expasy.org/protscale/, accessed on 16 August 2020). The prediction of signal peptide sequence was used by SignalP 5.0 Server (http://www.cbs.dtu.dk/services/SignalP/, accessed on 16 August 2020). Alignments of the amino acid sequences and other κ-carrageenases in NCBI database were performed using ClustalX (Version 1.8). ## 4.1.2. Expression and Purification Genomic DNA of Bacillus sp. N1-1 was extracted using the FastPure Bacteria DNA Isolation Mini Kit (Vazyme Biotech, Nanjing, China). *The* gene SeCar without the predicted signal sequence was amplified by PCR using the forward and reverse primers 5′-CACGAAAAAGAAAAAGATAATAATAAAAGTGAAC-3′ and 5′-CGTTACGCCTTCAATCGTAAC-3′. SeCar was cloned and ligated into pEASY-blunt E2 vector (TransGen Biotech, Beijing, China) to conduct recombinant plasmid. The constructed plasmid was transformed into BL21(DE3) competent cells (TransGen Biotech, Beijing, China) and then screened on Luria-Bertani (LB) medium supplemented with ampicillin. After incubation for 10 h, the positive colony was selected and cultured in LB medium with ampicillin in a shaker at 180 rpm at 37 °C until the absorbance value of bacterial solution reached OD600 = 0.8. The enzyme was prepared by adding isopropyl-beta-D-thiogalactopyranoside into recombinant *Escherichia coli* culture and then shaken at 150 rpm for 12 h at 16 °C. Cells were pelleted (7500× g; 15 min), resuspended in 50 mL of phosphate buffered saline (PBS), and lysed on ice by sonicating (300 w, 20 min). The supernatant after centrifugation was the crude enzyme of SeCar and was purified by Ni-affinity chromatography. The methods of gene expression and protein purification refer to the previous description [74,75]. ## 4.1.3. Biochemical Properties Coomassie brilliant blue binding method was used to determine the total protein concentration. The enzyme activity was determined by 3,5-dinitrosalicylic acid (DNS) method with galactose as standard [76]. The amount of enzyme releasing 1 µmol galactose per minute under standard conditions is defined as one unit (U) of enzyme activity. The optimum reaction temperature was determined by measuring the activity of SeCar in the range of 20 °C to 80 °C with $0.1\%$ κ-selenocarrageenan as substrate. SeCar was incubated in PBS buffer at 20–60 °C for 0–24 h, and the residual activity was detected to assess thermostability. The optimal pH for SeCar activity was determined using different buffers, such as sodium citrate buffer (pH 3.0–6.0), phosphate buffer (pH 6.0–8.0), Tris-HCl buffer (pH 8.0–9.0) and glycine buffer (pH 9.0–11.0), at 40 °C with $0.1\%$ (w/v) κ-selenocarrageenan as the substrate. SeCar was preincubated with the above buffers at 20 °C for 2 h, and the residual enzyme activity was detected to assess pH stability. In order to evaluate the effects of metal ions and chemical reagents on SeCar, the enzyme assay was performed in the presence of 5 mM Na+, K+, Cu2+, Mg2+, Mn2+, Ca2+, Fe2+, Fe3+ and EDTA. Enzyme activity was measured at 40 °C and pH 7.0. The reaction without adding metal ions and chemical reagents was used as the control. For the values of Km and Vmax, the purified enzyme reacted with 0.025–$0.2\%$ κ-selenocarrageenan as substrate at 40 °C for 30 min, which were calculated by double reciprocal plotting. All of the above activity assays were performed in 3 replicates. ## 4.2. Isolation of the KSCOs The KSCOs were prepared and isolated according to the previously described method with modifications [77,78]. The reaction system, containing 6 U of purified SeCar and 25 mM KSC, was conducted at 40 °C for 12 h. The lysate was boiled for 10 min to inactivate κ-selenocarrageenase and centrifuged for 15 min at 6000 r/min to remove impurities. Finally, four volumes of $95\%$ ethanol (v/v) were added to precipitate the undegraded KSC. After centrifugation at 10,000 r/min, the supernatant was concentrated using a rotary evaporator at 60 °C and then lyophilized under vacuum at −60 °C to obtain crude KSCOs. ## 4.3. Molecular Weight of KSCOs The molecular weight (MW) of KSCOs was evaluated by HPGPC [79]. The analysis was performed on a high-performance liquid chromatography (HPLC) instrument equipped with a TSK G2500PW column and eluted with deionized water, which filtered through a filter membrane (pore size 0.22 μm) at a flow rate of 0.3 mL/min. A total of 20 μL of $1\%$ sample solutions in deionized water was injected. The molecular weight was evaluated with maltose (MW: 342, 668, 990 Da) and dextran (MW: 2000, 5900, 9600 Da) as standards. ## 4.4. Purification of KSCOs KSCOs were purified by chromatography using a modified method previously described [80]. The freeze-dried samples were dissolved in 0.02 mol/L NH4HCO3, and the supernatant after centrifugation (4000 rpm, 10 min) was purified by Bio-Gel P4 chromatography eluting with 0.02 mol/L NH4HCO3 at a flow rate of 3.0 mL/h. The components collected by the automatic collector were desalted with Bio-GEL P4 column, eluted with 3.0 mL/h distilled water, and freeze-dried after concentration. ## 4.5.1. ESI-MS and TLC Analysis In order to further analyze the structure, KSCOs were analyzed by ESI-MS in negative ion mode [33]. KSCOs (2.0 mg) were dissolved in acetonitrile: water (1:1, v/v) to make the concentration within the range of 5–10 pmol/L, and the sample volume was 5 µL. In the process of mass spectrometry, N2 was used as the solvent of blow-drying gas and spray gas, and the flow rates were 250 and 15 L/h, respectively. The mobile phase was acetonitrile: water (1:1, v/v). Driven by the pump, the sample was injected at a flow rate of 10 µL/min. The parameters involved a capillary voltage of 3 kV, a cone-hole voltage of 50 eV, an ionic element volatilization temperature of 80 °C and a solvent volatilization temperature of 150 °C. The hydrolysate of KSC was analyzed by TLC plate developed with n-butane: ethanol: water (3:2:2, v/v/v) according to the previous description [75]. After drying, the plate was stained with a mixture of vitriol: ethanol (3:17, v/v; with $0.2\%$ resorcinol, w/v) and heated until the appearance of clear bands. ## 4.5.2. Spectroscopy Analysis FTIR and NMR assays were carried out according to previous methods [80,81]. For FTIR spectra, KSC and its oligosaccharides (2.0 mg) were mixed with KBr (200 mg) powder, ground and pressed, and then measured on a Nicolet Nexus 470 spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). For NMR spectra, KSC (50 mg) was dissolved in 500 μL $99\%$ of the D2O, freeze-dried and repeated 3 times. The sample was then redissolved in 500 μL D2O and transferred to an NMR tube. Finally, 1H-NMR/13C-NMR with Agilent DD2 500 MHz NMR spectrometer was performed with acetone as the internal standard. ## 4.6.1. Experimental Animals A total of 40 male C57BL/6 mice (20–22 g) were purchased from Pengyue experimental animal breeding Co., Ltd. (Jinan, China). All animals were raised under the conditions of 20–25 °C, 60–$70\%$ relative humidity and $\frac{12}{12}$ h light/dark cycle. They were randomly divided into six groups after a one-week acclimatization period ($$n = 8$$ per group). All animal experiments were in line with the National Laboratory Animal Ethics Committee of China and were approved by the Animal Care Review Committee (approval number SYXK2020-0422), Qingdao University of Science and Technology, China. ## 4.6.2. Experimental Procedures In the normal group, the mice drank water freely from day 0 to day 14. In the DSS group, the mice drank water freely from day 0 to day 7, followed by administration of $3.0\%$ (w/v) DSS (36 kDa-50 kDa, MP biomedicals) for 7 days. In the KSCOs intervention groups, low-dose (LS, 1.6 mg/kg), medium-dose (MS, 3.2 mg/kg) and high-dose (HS, 6.4 mg/kg) KSCOs were given by gavage every day throughout the experimental cycle and DSS was added to the drinking water from day 7 to day 14. The grouping and respective treatments are detailed in Figure 9. The weight of mice was recorded daily. ## 4.6.3. Assessment of Colitis DAI was determined by assessing clinical symptoms including weight loss, fecal traits and hematochezia in mice, then the average of these scores was calculated, as previously described [82]. The specific scoring rules are shown in Table 3. The proximal colon of each group was fixed with $4\%$ paraformaldehyde and embedded in paraffin, which were stained with hematoxylin−eosin (H&E) for histopathological observation. ## 4.6.4. MPO Activity Analysis Colon tissues (~0.1 g) were ground in cold normal saline to prepare $10\%$ homogenate. The activity of MPO was measured using homogenate according to the kit (Nanjing Jiancheng, Nanjing, China) instruction. ## 4.6.5. Level of Cytokines in Serum The concentrations of interleukin (IL)-6, TNF-α and IL-10 in serum were measured using enzyme-linked immunosorbent assay (ELISA) kits (MultiSciences, Hangzhou, Zhejiang, China) following the manufacturer’s protocol. ## 4.6.6. SCFAs Analysis Fecal samples (25 mg) were dissolved in 500 μL of water containing $0.5\%$ phosphoric acid and then were frozen and ground for 3 min (50 HZ), followed by ultrasound for 10 min and centrifugation at 13,000× g for 15 min. After that, all of supernatant was removed and n-butanol (0.2 mL) was added to extract SCFAs. Finally, the extract was analyzed by gas chromatograph–mass spectrometer (GC-MS) [59]. ## 4.6.7. Gut Microbiota Analysis The methods of DNA extraction, PCR amplification and 16S rRNA sequencing were performed as previously described [83]. Genomic DNA was extracted from fecal sample using OMEGA kit and detected by $1\%$ agarose gel electrophoresis. Primers (338F-5′-ACTCCTACGGGAGGCAGCAG-3′ and 806R-5′-GGACTACHVGGGTWTCTAAT-3′) with barcode were synthesized for V3-V4 region amplification of 16S rRNA. Miseq library was constructed and sequenced. PE reads were firstly spliced according to overlap, then the sequence quality was controlled and filtered (Majorbio Bio-Pharm Technology Co. Ltd., Shanghai, China). Operational taxonomic unit (OTU) clustering was performed for nonrepeating sequences according to $97\%$ similarity. Ribosomal database project (RDP) classifier (version 2.13) was used to classify OTU representative sequences. Alpha diversity and Beta diversity were assigned using QIIME software 1.9.1 (Rob Knight, CA, USA). The principal coordinate analysis (PCoA), principal component analysis (PCA) and community structure differences among groups were analyzed with QIIME software and R software 3.5.3 (UoA, AKL, NZ). ## 4.7. Statistical Analysis The results were expressed as mean ± standard deviation (SD). Data were analyzed via one-way ANOVA with Tukey’s test to determine the statistical significance ($p \leq 0.05$) using SPSS version 22.0 and GraphPad Prism version 7.0 software (Inc., La Jolla, CA, USA). ## 5. Conclusions In this study, a κ-selenocarrageenase from the deep-sea bacterium Bacillus sp. N1-1 was characterized and expressed in Escherichia coli. The reaction temperature was optimized to facilitate the preparation of KSCOs. KSC could be efficiently hydrolyzed by SeCar and yielded a large proportion of small molecular KSCOs (<1500 Da). Spectral analysis showed that selenium oligosaccharides in the hydrolysate of κ-selenocarrageenan were mainly composed of selenium-galactobiose. At present, the application of KSCOs in the treatment of UC is still limited. In this study, the effects of KSCOs administration (1.6 mg/kg, 3.2 mg/kg, 6.4 mg/kg) on UC mice were evaluated. 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--- title: A 3-miRNA Risk Scoring Signature in Early Diabetic Retinopathy authors: - Jiali Wu - Ke Shi - Fang Zhang - Xiaodong Sun journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003264 doi: 10.3390/jcm12051777 license: CC BY 4.0 --- # A 3-miRNA Risk Scoring Signature in Early Diabetic Retinopathy ## Abstract Purpose: The aim of our study was to investigate a comprehensive profile of streptozotocin (STZ)-induced early diabetic retinopathy (DR) mice to identify a risk scoring signature based on micorRNAs (miRNAs) for early DR diagnosis. Methods: RNA sequencing was performed to obtain the gene expression profile of retinal pigment epithelium (RPE) in early STZ-induced mice. Differentially expressed genes (DEGs) were determined with log2|fold change (FC)| > 1 and p value < 0.05. Functional analysis was carried out based on gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein–protein interaction (PPI) network. We predicted the potential miRNAs via online tools and ROC curves were then conducted. Three potential miRNAs with AUC > 0.7 were explored via public datasets and a formula was further established to evaluate DR severity. Results: In total, 298 DEGs (200 up-regulating and 98 down-regulating) were obtained through RNA sequencing. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 were three predicted miRNAs with AUC > 0.7, suggesting their potential to distinguish healthy controls from early DR. The formula of DR severity score = 19.257 − 0.004 × hsa-miR-217 + 5.09 × 10−5 × hsa-miR-26a-5p − 0.003 × hsa-miR-129-2-3p was established based on regression analysis. Conclusions: In the present study, we investigated the candidate genes and molecular mechanisms based on RPE sequencing in early DR mice models. Hsa-miR-26a-5p, hsa-miR-129-2-3p and hsa-miR-217 could work as biomarkers for early DR diagnosis and DR severity prediction, which was beneficial for DR early intervention and treatment. ## 1. Introduction Diabetic retinopathy (DR) is one of the leading causes of vision impairment and even blindness in the working-age population. It is estimated that there are more than 90 million DR patients worldwide [1]. Clinically, DR is divided into two stages: non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). NPDR is the early stage of DR without severe symptoms; therefore, most patients are not vigilant about being diagnosed. However, many pathological alterations, including increased vascular permeability and capillary occlusion, begin to occur at this stage [2]. Once NPDR progresses to PDR, vision dramatically decreases, posing a massive medical and economic burden on both patients and society. Therefore, a comprehensive study of early-stage DR is indispensable for early diagnosis and timely intervention. Traditionally, DR was classified as a microvascular complication of diabetes. With the development of modern technologies, researchers gradually realized that DR not only affects the retina, but also influences the RPE and neuronal units in the early stage [3,4]. RPE has vital physiological functions, including the formation of the outer blood retinal barrier (oBRB), transportation of nutrients to photoreceptors (PRs), absorption of scattered light, recycling of retinoid and phagocytosis of shed PR outer segment membrane [5]. Therefore, depicting the gene profile of RPE and studying their function could help enrich the understanding of early DR and further develop novel diagnosis and treatment strategies [6,7]. In our study, we carried out the RNA sequencing for RPEs from early DR mice models. Potential miRNAs were predicted based on the DEGs in RPE and subsequently validated via a public dataset. A formula was then constructed to score the DR risk with potential miRNAs. ## 2.1. Animal Model of STZ-Induced DR Male C57BL/6J mice aged 6–8 weeks were purchased from Shanghai Laboratory Animal Center. Intraperitoneal injection of 55 mg/kg of STZ was performed for 5 consecutive days to induce diabetes while PBS was utilized as a control. Blood glucose levels were tested via tail vein blood after one week, and animals with blood glucose concentrations of ≥ 200 mg/dL were considered to be successful models. Optical coherent tomography (OCT) was performed to observe the retinal structure before sacrifice. All animal experiments were approved by the Ethics Committee of Shanghai Jiao Tong University, China, and were in accordance with the requirements of the Association for Research in Vision and Ophthalmology Statement for the Use of Animals in Ophthalmic and Vision Research. The approval number of Animal Ethical *Committee is* 2019AW055. ## 2.2. RNA Sequencing Gene expression profile in the RPEs was identified by RNA sequencing. RPE–choroid complexes were separated along the corneal limbus and transferred to 1.5 mL tubes with RNA protect Cell Reagent (QIAGEN, Dusseldorf, Germany) to enrich RPE cells. TRIzol (Invitrogen, Carlsbad, CA, USA) was subsequently used to extract total RNA. *The* genes with log2|fold change (FC)| > 1 and p values < 0.05 were defined as differentially expressed genes (DEGs) and visualized by volcano plots and heatmaps using R3.5.0 (R Foundation for Statistical Computing, Vienna, Austria). The expression pattern was available in Table S1. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using Metascape (https://metascape.org/gp/index.html#/main/step1 accessed on 9 December 2022). GO, KEGG and reactome terms with p values < 0.05 were presented. ## 2.3. Protein–Protein Interaction (PPI) Network Construction The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) (https://string-db.org/ accessed on 9 December 2022) was utilized to evaluate the protein–protein interaction (PPI) of DEGs. Cytospace (version 3.8.2) was further applied to construct the network with Cytohubba plug-in unit and the genes were ranked according to MCC algorithm. The redder gene represented the higher rank. ## 2.4. Construction of miRNA–mRNA Network miRNet (https://www.mirnet.ca/ accessed on 9 December 2022) tool was utilized to predict miRNAs targeting DEGs, and Cytospace (version 3.8.2) was used to visualize the network. ## 2.5. Electroretinogram (ERG) Recording Electroretinogram (ERG) recording was carried out with a scotopic Ganzfeld ERG system (Phoenix Research Labs, New York, NY, USA). The mice were anesthetized by intraperitoneally injecting $1.5\%$ sodium pentobarbital (100 μL/20 g) and the pupils were dilated with tropicamide after dark adaptation overnight. The reference needle electrode was placed behind the ears while the ground one was plunged into the tail. As described below, the ERG was measured with four different stimulus intensities, 1.0, 2.0, 3.0 and 4.0 log cd s/m2 with intermittent intervals of 10, 20, 20 and 30 s. A-wave and B-wave values were recorded and analyzed. ## 2.6. Hematoxylin and Eosin (H & E) Histological Staining of Eyeballs Eyeballs were enucleated and fixed in eyeball fix solution (Servicebio, Wuhan, China) after sacrifice. After wax embedding, eyeball cross sections were prepared (5 μm). The slides were stained in Hematoxylin solution for 5 min, followed by Hematoxylin differentiation solution and water rinse. Then, the slides were treated with Hematoxylin Scott Tap Bluing and rinsed with water again. Lastly, the slides were dehydrated and sealed with neutral gum. ## 2.7. Raw Data Acquisition Raw data of the public datasets utilized in our study were acquired from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/ accessed on 9 December 2022). GSE1603086, based on GPL20301 platform, was a smallRNA profile consisting of retina samples from 43 donors. GSE1409597 was an miRNA profile with three different biological fluids, including aqueous humor, vitreous and plasma from 27 patients, which was established on GPL16384 platform. ## 2.8. Statistical Analysis Data were shown as the mean ± SD. All the experiments were performed for at least three biological replicates and differences between the two groups were analyzed by a Student’s t-test. Linear regression analysis was used for analyzing relationships among miRNAs and DR severity. p values < 0.05 were considered statistically significant. Statistical analysis in our study was performed with SPSS Statistics 26 (IBM, Armonk, NY, USA). ## 3.1. Identification of DEGs in Diabetic RPE via RNA Sequencing To our knowledge, there are no published sequencing data on RPEs in STZ-induced early DR models yet. Therefore, we established early DR mice models by STZ intraperitoneal injections. After 2-month STZ induction, diabetic mice showed lighter weight and higher blood glucose than control ones (Figure 1A,B). Electroretinograms (ERGs) were carried out to evaluate functional alterations. A wave of ERG represented the function of photoreceptors, while B wave indicated the function of the outer retina. ERG was taken with four different stimulus intensities, 1.0, 2.0, 3.0 and 4.0 log cd s/m2 with intermittent times of 10, 20, 20 and 30 s. As the stimulus increased, amplitudes gradually increased. As shown in the recordings, amplitudes of the B wave declined significantly in early diabetic mice while A waves showed no significant change. This finding suggested detectable functional damage to the retina instead of RPE at this stage (Figure 1C–F). Morphology changes were evaluated via H & E staining, from which we could observe a slight decrease in the outer nuclear layer. This thinning trend was consistent with that in OCT in vivo, both demonstrating retinal alterations in STZ-induced early diabetic models (Figure 1G,H). We further performed RNA sequencing with STZ-induced early diabetic models, in an attempt to demonstrate a comprehensive gene profile ($$n = 3$$). PCA plot showed the reproducibility of our data within two groups (Figure 2A). Further, results of the sequencing were relatively uniform, seen by a distribution boxplot (Figure 2B). Genes with log2|FoldChange| > 1 and p value < 0.05 were identified as RPE-DEGs in our study. A total of 200 up-regulating and 98 down-regulating DEGs are shown by the volcano plot and heatmap (Figure 2C,D). ## 3.2. Pathway and Function Enrichment Analysis of RPE-DEGs Metascape tool was utilized to carry out GO and KEGG analysis for RPE-DEGs. Neurotransmitter transport, ion transmembrane transport and regulation of amine transport were clustered in GO analysis for up-regulating DEGs (Figure 3A). Nicotine addiction, neuroactive ligand–receptor interaction, heparan sulfate metabolism and N-*Glycan biosynthesis* were enriched in KEGG pathways. Transmission across chemical synapses, neuronal system, neurotransmitter receptors and postsynaptic signal transmission and glycosaminoglycan metabolism were the top enriched reactome gene sets. When analyzing down-regulating genes, response to reactive oxygen species, inflammatory responses, regulation of cytokine production and fatty acid biosynthetic process were significantly enriched (Figure 3B). The PPI networks were constructed for up-regulating and down-regulating DEGs separately via STRING database and further Cytoscape software. For the up-regulating DEGs, in total, 88 genes were identified. SLC32A1, KCNA1, CPNE6, OPCML, SLC6A7, SYN2, CBLN4, NCAN, NRXN2 and RBFOX3 were the top 10 genes ranked by the MCC method (Figure 4A). The Molecular Complex Detection (MCODE) algorithm was utilized to identify densely connected network components and 14 gene lists were gathered (Figure 4B). As for the down-regulating DEGs, MAG, MOG, MOBP, 0LIG1, PLP1, BFSP1, GJA3, GRIFIN, CRYGD and CRYGB were tagged as the top ten genes among 28 genes ranked (Figure 4C) and 5 individual gene sets were identified via the MCODE algorithm (Figure 4D). ## 3.3. Construction of miRNA–mRNA Regulatory Network To further investigate the regulatory profile of these DEGs, we predicted and constructed miRNA–mRNA networks using the miRNet tool. In an attempt to search for the most promising miRNAs, we set the threshold of miRNAs targeting to at least $10\%$ of DEGs. Thus, 15 miRNAs were mined targeting at least 9 up-regulating DEGs (Figure 5A) while 43 miRNAs were identified targeting at least 3 down-regulating DEGs (Figure 5B). miRNA–mRNA networks were further formed by Cytoscape. Among them, hsa-mir-27a-3p had potential to sponge with 37 up-regulating genes, and hsa-mir-146a-5p was the top miRNA, with the ability to target 14 down-regulating DEGs. ## 3.4. Confirmation of Potential miRNAs by GSE160308 and GSE140959 After establishing the candidate miRNAs in early DR mice models, we further explored them in early-stage DR patient samples. GSE160308 was made up of 20 healthy control samples, 20 samples from diabetic patients without ocular manifestations, 19 non-proliferative DR patient samples and 5 DME patient samples. ROC curve analysis was performed for potential miRNAs. AUC > 0.7 was set as a meaningful cut-off value and AUC values of miR-129-2-3p (AUC = 0.797, $95\%$CI 0.654–0.941), miR-217 (AUC = 0.724, $95\%$CI 0.557–0.890) and miR-26a-5p (AUC = 0.708, $95\%$CI 0.540–0.875) were higher than 0.7, suggesting that they had potential to distinguish healthy controls from NPDR patients (Figure 6A–C). What’s more, miR-129-2-3p and miR-217 decreased along with the severity of DR while miR-26a-5p had an increasing trend (Figure 6D). The PCA plot also demonstrated that these three miRNAs could well distinguish NPDR from healthy controls (Figure 6E). GSE140959 was included for verification and miR-217 expression in this dataset also represented a decreasing tendency in aqueous, vitreous and plasma (Figure 6F). Association of these three miRNAs and severity of DR were further analyzed by regression analysis (Table 1). Results demonstrated that miR-129-2-3p (B = −0.003, β = −0.37, $$p \leq 0.002$$) and miR-217 (B = −0.004, β = −0.325, $$p \leq 0.028$$) were negatively related to DR progression. miR-26a-5p ($B = 5.09$ × 10−5, β = 0.584, $$p \leq 0.000$$) was positively associated with the risk of DR. This linear association could be calculated by: DR severity score = 19.257 − 0.004 × hsa-miR-217 + 5.09 × 10−5 × hsa-miR-26a-5p − 0.003 × hsa-miR-129-2-3p. ## 4. Discussion DR is one of the leading causes of vision impairment in the working-age population. As a complex and multifactorial disorder, current therapies for DR, such as laser photocoagulation and anti-vascular endothelial growth factor injection, are not effective for all patients 4. The progression of NPDR to PDR is a vision-threatening turning point, and it is also the key point physicians should consider. By analyzing the gene expressions that change significantly in early DR, we predicted and constructed an miRNA-based risk signature for early DR diagnosis and therapy. The role of RPE in DR is not well studied currently. RPE was a metabolically active tissue responsible for glucose trans-epithelial transport into the outer retina via GLUT1. Glucose was then utilized for synthesis of phospholipids via tricarboxylic acid cycle and oxidative phosphorylation. Therefore, RPE functioned as a bridge between choroid and photoreceptors to efficiently utilize glucose [8]. Diabetes not only disrupted RPE structure but also hampered the function of RPE cells. To the best of our knowledge, no sequencing study for RPE in diabetic mice has been reported yet. Therefore, we carried out RNA sequencing to investigate the gene profile in RRE cells. Further, 200 up-regulating and 98 down-regulating DEGs were identified in our study. Functional analysis suggested that up-regulating DEGs played a vital role in neurotransmitter transport, ion transmembrane transport and regulation of amine transport. RPE was able to transport iron and iron was a necessary component in biological processes. However, excessive iron contributed to various pathological events, such as oxidative stress and lipid peroxidation. Iron accumulation was detected in postmorten human diabetic patients. With an HFE knockout (KO) mice model of genetic iron overload, researchers found that iron overload during diabetes exacerbated DR progression [9]. Excessive intracellular iron could be a fuse of ferroptosis, which was featured with mitochondrial atrophy and mitochondrial cristae structure change. In human retinal pigment epithelial (ARPE 19) cells treated with high glucose, intracellular ferrous iron increased and ferroptosis took place [10]. Neural deficits involving the GABA signaling pathway have been detected. GABA increases in the vitreous of PDR patients [11,12]. Hyperglycemia interferes with GABA signaling in the inner retina and rod-bipolar cells. It directly influences the GABA ρ subunit composition of GABAC receptors on retinal neurons [12,13,14,15]. When the GABAB receptor is activated, it can alleviate apoptosis and oxidative stress in neuronal cells via the PI3K-Akt signaling pathway in Alzheimer’s disease [16]. We further studied potential miRNAs targeting DEGs via the miRNet online tool and dozens of miRNAs were established. The public dataset GSE160308 was utilized for miRNA ROC curve exploration. Hsa-miR-217, hsa-miR-26a-5p and hsa-miR-129-2-3p were identified with AUC > 0.7, suggesting their potential to diagnose early DR. What’s more, miR-129-2-3p and miR-217 decreased along with the severity of DR while miR-26a-5p had an increasing trend. GSE140959 was then included and only one of three miRNAs, miR-217, was detected. Expression of miR-217 in this dataset represented a decreasing tendency in aqueous, vitreous and plasma of proliferative DR patients, which was consistent with that in GSE160308. All results suggested the vital roles of these three miRNAs in early DR. miR-26a-5p was reported as a circulating biomarker for early-stage retinal neurodegeneration via plasma RNA sequencing from NPDR patients [17]. Mechanically, miR-26a-5p delayed thinning of neuroretinal layers by regulating PTEN expression. Further, miR-26a-5p up-regulation significantly decreased IL-1beta, NF-kapaB and VEGF expression [18]. Effects of miRNA-217 were investigated in high-glucose-treated ARPE-19 cells. miR-217 down-regulation augmented cell viability and alleviated cell apoptosis by sponging SIRT1. In addition, miR-217 inhibitor significantly reduced the expression of IL-1beta, IL-6 and tumor necrosis factor α [19]. miR-129-2-3p has not been reported in DR yet, but it was found to be beneficial to diabetic wound healing. Overexpression of miR-129-2-3p could accelerate wound healing by regulating inflammation and apoptosis directly [20]. Notably, the functions of most miRNAs we predicted have not yet been thoroughly elucidated, especially in early DR. Thus, further investigations are meaningful for prospective value validation. In our results, these three miRNAs were all dis-regulated in DR. ROC curve analysis suggested their potential as early biomarkers for DR. What’s more, we found that the expression of three miRNAs was negatively or positively correlated with DR severity. Therefore, we further carried out regression analysis for them. miR-129-2-3p (B = −0.003, β = −0.37, $$p \leq 0.002$$) and miR-217 (B = −0.004, β = −0.325, $$p \leq 0.028$$) were negatively related to DR progression. miR-26a-5p ($B = 5.09$ × 10−5, β = 0.584, $$p \leq 0.000$$) was positively associated with DR severity. 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--- title: The β1 Adrenergic Blocker Nebivolol Ameliorates Development of Endotoxic Acute Lung Injury authors: - Esra Nurlu Temel - Mehtap Savran - Yalcın Erzurumlu - Nursel Hasseyid - Halil Ibrahim Buyukbayram - Gozde Okuyucu - Mehmet Abdulkadir Sevuk - Ozlem Ozmen - Ayse Coskun Beyan journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003295 doi: 10.3390/jcm12051721 license: CC BY 4.0 --- # The β1 Adrenergic Blocker Nebivolol Ameliorates Development of Endotoxic Acute Lung Injury ## Abstract Acute lung injury (ALI) is a disease, with no effective treatment, which might result in death. Formations of excessive inflammation and oxidative stress are responsible for the pathophysiology of ALI. Nebivolol (NBL), a third-generation selective β1 adrenoceptor antagonist, has protective pharmacological properties, such as anti-inflammatory, anti-apoptotic, and antioxidant functions. Consequently, we sought to assess the efficacy of NBL on a lipopolysaccharide (LPS)-induced ALI model via intercellular adhesion molecule-1 (ICAM-1) expression and the tissue inhibitor of metalloproteinases-1 (TIMP-1)/matrix metalloproteinases-2 (MMP-2) signaling. Thirty-two rats were split into four categories: control, LPS (5 mg/kg, intraperitoneally [IP], single dose), LPS (5 mg/kg, IP, one dosage 30 min after last NBL treatment), + NBL (10 mg/kg oral gavage for three days), and NBL (10 mg/kg oral gavage for three days). Six hours after the administration of LPS, the lung tissues of the rats were removed for histopathological, biochemical, gene expression, and immunohistochemical analyses. Oxidative stress markers such as total oxidant status and oxidative stress index levels, leukocyte transendothelial migration markers such as MMP-2, TIMP-1, and ICAM-1 expressions in the case of inflammation, and caspase-3 as an apoptotic marker, significantly increased in the LPS group. NBL therapy reversed all these changes. The results of this study suggest that NBL has utility as a potential therapeutic agent to dampen inflammation in other lung and tissue injury models ## 1. Introduction Sepsis is an exaggerated response that a host develops against an infection; the lungs are greatly affected because they have excessive blood flow. More than half of patients diagnosed with sepsis experience lung problems, such as acute lung injury (ALI). Despite current antibiotic and supportive treatment strategies to combat sepsis and related pulmonary problems, ALI still presents a notable mortality rate [1,2,3]. In a typical ALI, extensive pulmonary inflammation, which results in the apoptosis of alveolar epithelial cells, is the main mechanism of damage. The inflammatory state of the lungs can be modeled by a challenge with LPS, a part of the Gram-negative bacterial cell wall, to understand the underlying mechanisms of ALI [4]. The recognition of LPS by a specific Toll-like-receptor-4 (TLR-4) receptor on the pulmonary epithelium stimulates the secretion of pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), which subsequently increases inflammation and capillary membrane permeability. Increased permeability directs leukocytes to interstitial lung tissue. In addition, inflammation is known to induce oxidative stress, DNA damage, apoptosis, and necrosis, all of which contribute to the ALI process individually [4,5,6,7,8]. Metalloproteinases (MMP), whose zymogen forms originate from various types of cells and are secreted into the matrix, are proteinases that regulate the tissue structure by degrading extracellular matrix (ECM) components [9]. The level of MMP-2 decreases after pulmonary maturation, whereas its expression is induced in inflammation to create a chemotactic gradient to eliminate inflammatory cells [10]. TIMP-1 is a member of the protein family that functions as a tissue inhibitor of MMPs, especially MMP-2 and MMP-9 [11]. The balance of MMPs/TIMP-1 is important for ECM turnover in the lung. Additionally, TIMP-1 is known to be induced by acute-phase reactants in inflammation, so the balance of MMPs/TIMP-1 is affected by inflammatory cell secretions [12,13]. ICAM-1 is a cell-surface glycoprotein expressed in the endothelium and epithelium. It regulates leukocyte recruitment from the circulation to infections due to induction by inflammatory cytokines [14]. NBL, a third-generation β1-adrenoreceptor antagonist, acts as a vasodilator agent by enhancing the levels of nitric oxide (NO) in addition to the other properties of beta blockers. In the literature, NBL has been shown to modulate the inflammation both in vivo and in vitro. In addition to reducing the inflammation that occurred in hypertensive patients, NBL protected the lung, liver, kidney of rats and type-II collagen tissue in cell cultures by reducing various cytokines of inflammation, such as IL-6, ICAM-1, and TNF-α [15,16,17,18,19,20,21,22]. Despite research on the protective effects of NBL in cardiovascular pathologies, the beneficial features of NBL on ALI are not yet known. Therefore, this research is the first to investigate NBL’s impact on inflammation-induced lung injury through transendothelial migration via MMP2/TIMP-1 signaling and ICAM-1 expressions. ## 2. Materials and Methods Suleyman Demirel University’s local animal ethics commission approved this research (Decision Number 06-25, 11.09.20). The experiment was conducted according to ARRIVE (Animal Research: Reporting in Vivo Experiments) guidelines, Version 2.0 protocol. Thirty-two adult male Wistar albino rats, weighing 300–350 g, were housed at 21–22 °C and 60 ± $5\%$ humidity with a 12 h light:12 h dark cycle. A standard commercial chow (Korkuteli Yem, Antalya, Turkey) was administered ad libitum with water. Four experimental groups were formed as follows: Negative controls ($$n = 8$$): For three days, 1 mL of normal saline (NS) was administered via oral gavage. Thirty minutes after the last NS, one dosage of 1 mL of NS was injected IP into the right inguinal region of the rat. Positive (LPS) controls ($$n = 8$$): For three days, 1 mL of NS was administered via oral gavage. Thirty minutes after the last NS, one dosage of 5 mg/kg LPS (048K4126, Sigma Aldrich, USA) soluble in NS was injected IP into the right inguinal region of the rat [23]. LPS + NBL group ($$n = 8$$): For three days, 1 mL of 10 mg/kg NBL (Nexivol, Abdi İbrahim, Turkey) soluble in NS was applied via oral gavage. Thirty minutes after the last NBL administration, one dosage of 5 mg/kg LPS soluble in NS was injected IP into the right inguinal region [24]. NBL group ($$n = 8$$): For three days, 1 mL of 10 mg/kg NBL soluble in NS was administered via oral gavage, and one dosage of 1 mL of IP saline was applied 30 min after the last NBL administration. For anesthesia, 100 mg/kg ketamine (Alfamine, Alfasan IBV) and xylazine 10 mg/kg (Alfazin, Alfasan IBV) were administered 6 h after LPS stimulation [24]. Surgical exsanguination by blood withdrawal from the inferior vena cava following abdominal incision was used for euthanasia. After lung tissue extraction for histological evaluation, they were inflated and frozen in liquid nitrogen and kept at −20 °C for gene expression and biochemical examination. The remaining extracted tissues were maintained for immunohistochemical and histopathological examination following fixation with $10\%$ buffered formalin. ## 2.1. Histopathological Analyses The routine pathology tissue-processing of pulmonary specimens was carried out by an automatic tissue processor (Leica-ASP300S, Wetzlar, Germany), followed by embedding in paraffin wax. Afterward, 5μm-thick pieces were cut from the paraffin blocks using a Leica-RM2155 rotary microtome (Leica Microsystems, Wetzlar, Germany). Subsequently, hematoxylin-eosin (H&E) staining was performed by mounting with a coverslip and examination under a light microscope. For the histopathological injury score of the lungs, each rat was evaluated by two expert pathologists who were unaware of the groups using a modified scoring system [25]. Histopathological lesions were graded from 0 to 3, as shown in Table 1, by evaluating the findings of hyperemia, edema, infiltration, and septal thickening. By averaging the evaluations of the two pathologists, a score for each animal was determined. ## 2.2. Immunohistochemical Analyses For the immunohistochemistry, two series of sections from all blocks drawn on poly-L-lysine-coated slides were stained for the expression of caspase-3 (Cas-3) [Anti-caspase-3 Antibody (E-8):sc-7272, $\frac{1}{100}$ dilution] and ICAM-1 [ICAM-1(M/K-2):sc-18864, $\frac{1}{100}$ dilution, Santa Cruz, Texas, USA] using the streptavidin–biotin method as per the manufacturer’s instructions. For 60 min, the section was incubated with the primary antibody. Secondary antibodies (EXPOSE Mouse and Rabbit Specific HRP/DAB Detection IHC kit [ab80436, Abcam, Cambridge, UK]) included streptavidin-alkaline phosphatase conjugate and biotinylated secondary antibodies. Diaminobenzidine (DAB) was chosen as the chromogen (DAB). An antigen dilution solution, but not the primary antibody, was used for negative controls. Two specialized pathologists from different universities evaluated all the blinded samples. The sections were independently examined for individual antibodies during immunohistochemical analyses. Semiquantitative analyses were performed to assess the immunostaining degree of cells using a ranking from 0 to 3: 0 = no staining, 1 = poor focal staining, 2 = poor diffuse staining, and 3 = strong diffuse staining [26]. For each section, 10 fields at 400X magnification were evaluated. Statistical analyses were conducted by averaging the scores of both pathologists for each lung. The Database Manual cellSens Life Science Imaging Software System (Olympus Co., Tokyo, Japan) was used for microphotography and morphometric analysis. ## 2.3. Biochemical Analyses First, the lung tissues were diluted five-fold (w/v) with phosphate-buffered saline (10 mM sodium phosphate) at pH 7.4. Next, tissues were homogenized with a tissue homogenizer (IKA Ultra Turrax T25, Janke & Kunkel, Staufen, Germany). At the end of the homogenization, the samples were centrifuged at 2000 rpm/20 min./+4 °C (Nüve NF 1200R, Ankara, Turkey). Tissue total antioxidant status (TAS) and total oxidant status (TOS) concentrations were assayed from the supernatant of the samples using an automated biochemistry analyzer (Beckman Coulter AU 5800, Brea, CA, USA) and colorimetric methods developed by Erel [27,28,29]. TOS results were μmol H2O2 Equiv./L, and TAS results were mmol Trolox Equiv/l. The oxidative stress index (OSI) was calculated by dividing the TOS levels by TAS levels, that is, TOS/TAS × 100 [25]. ## 2.4. Quantitative Polymerase Chain Reaction Analysis RNA was isolated from lung tissues using TRIzolTM (Thermo Fisher Scientific, Carlsbad, CA, USA) (New England BioLabs). The amount and purity of the RNAs were measured using a nanodrop device (VWR MySPEC, Darmstadt, Germany). Moreover, 1 μg of RNA of 1.8–2.1 purity was taken, and cDNA was obtained in a thermal cycler (Thermo Scientific, Waltham, MA, USA) with the iScript cDNA Synthesis kit according to the manufacturer’s protocol. Real-time PCR amplification was performed with a Bio-Rad CFX96 instrument using the iTaq Universal SYBR Green Supermix (Bio-Rad, Hercules, CA, USA). Primers were designed using the NCBI primer-BLAST (Table 2). GAPDH expression was used for normalization. The reaction volume was adjusted to 25 μL using 100 ng of the cDNA sample, and the RT–qPCR conditions were determined according to the manufacturer’s protocol. The relative measurement of gene expression was executed using the Livak method and the 2−ΔΔCt method [30]. A melting curve analysis was performed on RT–qPCR products to ascertain the specificity of the amplification. Fold changes are given graphically (Table 2). ## 2.5. Statistical Analyses For statistical analyses of the immunohistochemical and biochemical scores of the groups, the SPSS 22.00 (SPSS Inc., Chicago, IL, USA) program was used, and the significance of the scores were compared between the groups. One-way ANOVA and post hoc Bonferroni and Duncan tests were conducted to evaluate the significance among the groups. The data are presented as the mean ± SD. Values with $p \leq 0.05$ were deemed significant. ## 3.1. Immunohistochemical and Histopathological Results In the control group, the histopathological investigation indicated a normal histoarchitecture. Severe hyperemia, interstitial edema, and increased thickness of septal tissue were the marked findings in the LPS group. In addition, inflammatory cell infiltrations mainly comprising neutrophils were commonly seen in this group. NBL treatment decreased histopathological findings. Normal lung histology was observed in the NBL group (Figure 1). In addition, the degree of lung damage was scored using a semiquantitative histopathology system according to alveolar septa hyperemia, alveolar hemorrhage, edema, and neutrophil leukocyte infiltrations. It was observed that LPS resulted in a substantial rise in histopathological scores in the lungs. However, NBL treatment markedly lessened lung injury scores (Table 3). In an immunohistochemical examination, the negative to slight expression of Cas-3 and ICAM-1 was seen in the control group. Comparing the LPS group to the control, there was a significantly higher expression of Cas-3 and ICAM-1 ($p \leq 0.001$). NBL treatment was associated with a marked decrement in these expressions compared with animals subjected to LPS ($p \leq 0.001$). See Figure 2 and Figure 3. Only in the NBL-administered group were negative to very slight expressions noticed. Immunohistochemical expressions were detected in lung alveolar cells and in inflammatory cells. The results of the statistical analyses of immunohistochemical scores are displayed in Table 3. ## 3.2. Biochemical Results TAS levels did not differ significantly across groups. TOS levels considerably increased in the LPS ($p \leq 0.001$) and LPS + NBL groups ($p \leq 0.01$) compared to the controls. TOS levels were markedly lower in the LPS + NBL group compared to the LPS exposure ($p \leq 0.001$). In only the NBL-administered group, TOS values were notably lower compared to the LPS and LPS + NBL groups ($p \leq 0.001$ and $p \leq 0.05$, respectively). OSI levels were slightly higher in the LPS ($p \leq 0.001$) and LPS + NBL groups ($p \leq 0.01$) compared to the negative controls. OSI levels were noticeably lower ($p \leq 0.01$) in LPS plus NBL-exposed animals compared to only LPS exposure. In only the NBL-administered group, OSI values were considerably lower compared to the LPS and LPS + NBL groups ($p \leq 0.001$ and $p \leq 0.05$, respectively). See Figure 4. ## 3.3. Gene Expression Results The TIMP-1 level was noticeably higher in the LPS group than in the control, LPS + NBL, and NBL groups ($p \leq 0.001$ for all). TIMP-1 levels were higher in the LPS + NBL group than in the control ($$p \leq 0.019$$) and NBL groups ($p \leq 0.001$). In the NBL-administered group, TIMP-1 levels were considerably lower than in the control group ($p \leq 0.001$). MMP-2 levels were noticeable higher in the LPS group than in the control, LPS + NBL, and NBL groups ($p \leq 0.001$ for all). In addition, MMP-2 levels were higher in the LPS + NBL group than in the control and NBL groups ($$p \leq 0.042$$ and $p \leq 0.001$, respectively). MMP-2 levels were considerably lower only in the NBL-administered group than in the control ($p \leq 0.001$). See Figure 5. ## 4. Discussion This study, using a chemically induced ALI model, showed the presence of increased markers of inflammation (ICAM-1, MMP-2 and TIMP-1), oxidative stress (TOS and OSI) and apoptosis (Cas-3) in the LPS groups. NBL treatment restored these alterations. Many harmful factors, such as infection, activate receptors on cell-surface membranes. In addition, this triggers some post-receptor intracellular signaling mechanisms and leads to the production of some inflammatory cytokines such as TNF-α, interleukin (IL) 1-beta, and IL-6 [31]. These cytokines aggravate leucocyte transendothelial migration by enhancing capillary membrane permeability. It was also shown that the secretion and activation of nuclear factor kappa beta (NF-kB) is the primary stone for inducing the abovementioned proinflammatory cytokines. NBL has been known to mitigate NF-kB activation and subsequent proinflammatory cytokine secretion [22]. Thus, NBL inhibits transendothelial migration by reducing capillary membrane permeability mediated by secreted cytokines. The damage findings observed in the groups treated with LPS indicate inflammation, which supports the literature [32]. Inflammatory cell infiltration with a predominance of neutrophils indicates pulmonary damage begins to develop in the early phase of inflammation as an acute response. Neutrophils play a pivotal role in ALI, as their levels in various body fluids relate to the severity of diseases [33]. However, neutrophilic infiltration into an injury site develops either in an integrin-dependent or independent manner, varying according to the type of inflammatory stimulus [34]. Although there is a paper that shows integrin-independent neutrophilic migration in an LPS-challenged lung model [35], it has been commonly stated that in LPS-induced models, integrin proteins, such as ICAM-1, are involved in neutrophil migration in pulmonary tissue [36]. In our study, increased expressions of ICAM-1 in LPS-treated groups emphasized that ICAM-1 is a critical component of inflammation and may explain the necessity of ICAM-1 for the transmigration of neutrophils. However, the effect of NBL on ICAM-1 expression in cardiac tissues has been demonstrated in some in vivo and in vitro studies [16,37]. On the other hand, our study is the first to illustrate the decreasing effect of NBL on pulmonary ICAM-1 level. Except for ICAM-1, other adhesion molecules such as ICAM-2, ICAM-3, E and P selectins, and vascular cell adhesion molecule-1 (VCAM-1) have also been indicated to decrease by NBL [18,38]. These molecules could be downregulated in lung tissues treated by NBL and should be evaluated in further studies. Edema due to greater capillary permeability is one of the most characteristic features of ALI and eventually impairs oxygenation. Edema also accompanies neutrophilic infiltration during lung injury [33]. In addition, the septal thickening of alveolar membranes contributes to damage. To combat impaired oxygenation and related inflammation, enhanced expression of hypoxic inducible factor alpha (Hıf-1α) triggers eNOS-related NO production [39]. In a recent study, NBL has been shown to induce AKT1/eNOS/HIF1 α signaling to decrease inflammatory conditions [20]. In our study, edema and septal thickening in alveolar membranes increased due to inflammation caused by LPS. The observed decrements in the findings due to NBL confirm its anti-inflammatory properties. Enhancements in these parameters are important, as they can directly reflect the clinical response by recovering breathing. The roles of MMPs and the proteolytic degradation of ECM in physiological and pathological processes are well known [40]. Moreover, proteolytic reactions can activate or inactivate inflammatory cytokines and chemokines and antagonize chemokine functions to regulate the inflammatory process [41]. Studies have shown that raising MMP-2 levels with LPS administration causes pulmonary ECM degradation and aggravates pulmonary inflammation [42,43,44,45]. MMP-2-induced degradation products can exacerbate inflammation, so MMP-2 has become a critical marker for acute inflammatory lung injuries [46]. To the best of our knowledge, LPS-induced elevations in MMP-2 levels were noticed in our study. Papers that focus on the effect of NBL on MMP-2 levels have been performed on cardiac and vascular tissues, as NBL is indicated in hypertension. However, these studies reveal conflicting results [47,48,49,50]. Furthermore, MMP-2 levels, shown for the first time to decrease with NBL in lung tissue in our study, are crucial for detailing the effect of NBL on acute lung pathologies. One of the critical results revealed by our research is the decrease in MMP-2 levels observed in the NBL-only treated group. Although there are publications reporting NBL-induced decreases in MMP-2, these studies were performed on hypertensive rats with an inflammatory condition [47,48]. The findings in our study show that NBL has the potential to decrease MMP-2 levels even without a provocative challenge in lung tissue, and this is an important result for further studies characterizing anti-inflammatory mechanisms. TIMPs regulate the activity of MMPs [51]. Therefore, TIMP-1, is linked with various inflammation-based diseases. Although TIMP-1 participates in post-injury tissue repair processes and the resolution of inflammation in an anti-inflammatory condition, it acts as a pulmonary macrophage-derived proinflammatory cytokine in the lung to strengthen acute inflammation [52]. In the current study, the elevation of TIMP-1 should be considered an acute marker of inflammation rather than MMP-2 inhibition. Thus, simultaneous increases in TIMP-1 and MMP-2 in the LPS group and ameliorations in these values by NBL exhibit the inflammatory and anti-inflammatory natures of LPS and NBL, respectively. Transcriptional changes seen in TIMP-1 and MMP-2 could be considered moderate due to the acute design of the study. However, these alterations could be more dramatic later and should be clarified in further studies. The effects of NBL on TIMP-1 has been studied in cardiac tissue. Although no effect on TIMP-1 levels by NBL was shown in some studies [47,49], others reported decreased TIMP-1 levels by NBL [38]. As our study demonstrated, lower MMP-2 and TIMP-1 levels by NBL may reflect tissue remodeling in the lung, which revealed improvements in alveolar septal thickness using histological analysis. Additionally, in a renal fibrosis model, ICAM-1 was upregulated as one of the substrates of TIMP-1 [53]. In our study, it also can be said that TIMP-1 levels modulate inflammation over ICAM-1 expression and, hence, neutrophil transmigration. Similar to MMP-2 results, TIMP-1 levels, too, were decreased in the NBL-only treated group in addition to LPS + NBL. Although TIMP-1 levels were shown to be decreased in a cell-culture model and in senile heart failure, our result is the first to show that NBL could decrease TIMP-1 in the absence of inflammation, which may indicate the anti-inflammatory potential of NBL [49,54] During the development of ALI, the influx of neutrophils and macrophages into the alveolar space causes the secretion of reactive oxygen species (ROS) and other proinflammatory cytokines. Although it is physiologically involved in cellular functions, excessive oxidative stress, similar to inflammation, causes tissue damage [55]. LPS-induced oxidative damage is a well-known consequence and is also depicted in our study [56]. Nonetheless, the antioxidant features of NBL have been shown in cardiac tissue [57,58]. In our research, the protective effects of NBL against oxidative stress were indicated by decreased TOS and OSI levels, without changes in TAS levels. These results suggest that NBL reduced oxidative stress secondary to the regression of inflammation, not by increasing the amount of antioxidant enzymes. LPS induces epithelial and endothelial apoptosis in the lung, and preexisting inflammation and oxidative stress also help develop apoptosis [59]. In the current study, histopathologically, a significant increase in LPS and reduction in the NBL-treated group were observed using cas-3. Considering that the increase in cas-3 is associated with cell death, NBL can be said to illustrate an anti-apoptotic effect similar to that in the literature [60]. 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--- title: 'Risk of Gestational Diabetes and Pregnancy-Induced Hypertension with a History of Polycystic Ovary Syndrome: A Nationwide Population-Based Cohort Study' authors: - Seung-Woo Yang - Sang-Hee Yoon - Myounghwan Kim - Yong-Soo Seo - Jin-Sung Yuk journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003301 doi: 10.3390/jcm12051738 license: CC BY 4.0 --- # Risk of Gestational Diabetes and Pregnancy-Induced Hypertension with a History of Polycystic Ovary Syndrome: A Nationwide Population-Based Cohort Study ## Abstract Objective: To evaluate the risks of developing gestational diabetes (GDM) and pregnancy-induced hypertension (PIH) in women with polycystic ovary syndrome (PCOS) using data from Korea’s National Health Insurance Service. Method: The PCOS group comprised women aged 20 to 49 years diagnosed with PCOS between 1 January 2012, and 31 December 2020. The control group comprised women aged 20 to 49 years who visited medical institutions for health checkups during the same period. Women with any cancer within 180 days of the inclusion day were excluded from both the PCOS and control groups, as were women without a delivery record within 180 days after the inclusion day, as well as women who visited a medical institution more than once before the inclusion day due to hypertension, diabetes mellitus (DM), hyperlipidemia, DM in pregnancy, or PIH. GDM and PIH were defined as cases with at least three visits to a medical institution with a GDM diagnostic code and a PIH diagnostic code, respectively. Results: Overall, 27,687 and 45,594 women with and without a history of PCOS experienced childbirth during the study period. GDM and PIH cases were significantly higher in the PCOS group than in the control group. When adjusted for age, SES, region, CCI, parity, multiple pregnancies, adnexal surgery, uterine leiomyoma, endometriosis, PIH, and GDM, an increased risk of GDM (OR = 1.719, $95\%$ CI = 1.616–1.828) was observed among women with a history of PCOS. There was no increase in the risk of PIH among women with a history of PCOS (OR = 1.243, $95\%$ CI = 0.940–1.644). Conclusion: A history of PCOS itself might increase the risk of GDM, but its relationship with PIH remains unclear. These findings would be helpful in the prenatal counseling and management of patients with PCOS-related pregnancy outcomes. ## 1. Introduction Polycystic ovary syndrome (PCOS) affects 8–$13\%$ of women of reproductive age [1] and is associated with dysfunctional gonadotropin secretion [2]. In terms of clinical implications, infertility caused by chronic ovulatory dysfunction, abnormal gonadotropin secretion, and metabolic disturbances, such as central obesity, dyslipidemia, insulin resistance, and hyperinsulinemia, can coincide with PCOS [3]. Women with PCOS have increased risks of pregnancy and delivery complications. A woman with a PCOS-affected pregnancy is more likely to have increased oxidative stress and experience infertility requiring assisted conception [4,5,6]. Normal pregnancy induces a state of insulin resistance that may manifest as impaired glucose tolerance or gestational diabetes (GDM) [7]. Because women with PCOS have a reported incidence of 25–$70\%$ of insulin resistance, they would appear to be at increased risk of developing GDM complications [8]. Several previous meta-analyses have suggested that PCOS influences the development of GDM and pregnancy-induced hypertension (PIH) [5,9,10,11]. The early meta-analysis of Boosma et al. found that PCOS-affected pregnancy was associated with significantly higher risks of developing GDM, gestational hypertension, and preeclampsia (PE) [9]. The largest meta-analysis was reported in 2019 and included over 224,000 pregnant women [11], and suggested that PCOS, independent of obesity, increases the risks of developing GDM and PIH. However, the fundamental limitations of meta-analysis meant significant heterogeneity in the included samples, primarily due to differing study designs and ethnic backgrounds. Therefore, further evaluations of PCOS as an independent risk factor for GDM and PIH with comprehensive adjustments for confounding factors are still needed. A significant finding of recent studies is that PCOS is an independent risk factor for worse birth outcomes. A large population-based cohort study that included 9.1 million births in women with PCOS found that across all pregnancies, women with PCOS were 2-fold and 1.38-fold more likely to develop GDM and PIH, respectively, after controlling for obesity, IVF use, and other confounders [12]. However, that study was characterized by considerable heterogeneity in ethnicity and the sizes of the included samples (14,882 PCOS patients vs. 9,081,906 controls) and did not control for PIH confounding factors such as parity, multifetal pregnancy, and GDM itself. Additionally, there are considerable ethnicity variations in the manifestation of PCOS, with a low body mass index (BMI) and mild hirsutism in East Asian women with PCOS compared with Western and South Asian women with PCOS [13,14]. Therefore, the purpose of the present study was to determine the associations of PCOS with GDM and PIH in Korean women of reproductive age using nationwide population-based data. ## 2.1. Database Single-payer healthcare is provided to most of the Korean population. Korea’s National Health *Insurance is* mandatory for all residents [15]. The National Health Insurance Service of Korea provides information about medical records, including gender, age, disease name, income level, kind of medical insurance, name of prescription medicine, surgery received, and hospitalizations. The Health Insurance Review and Assessment Service (HIRA) is an independent organization that evaluates the appropriateness of medical bills to avoid disputes between the National Health Insurance Corporation and medical institutions about insurance premium payments. As a result, the HIRA holds most of the National Health Insurance Corporation’s medical record information. This population-based retrospective cohort study analyzed HIRA health insurance data collected from 1 January 2011 to 31 December 2020. ## 2.2. Selection of Participants Subject selection and outcome confirmation were based on the ICD-10 and Korea Health Insurance Medical Care Expenses (2016 and 2019 versions). The PCOS group was drawn from women aged 20 to 49 years diagnosed with PCOS between 1 January 2012 and 31 December 2020. Throughout the research period, the clinical guidelines of the Korean Society of Gynecologic Endocrinology suggested only applying the Rotterdam 2003 criteria for diagnosing PCOS [16]. Only women with PCOS who visited medical institutions at least three times with an ICD-10 code of E28.2 were included in the study. The inclusion day was the first PCOS-related visit to a medical institution. The control group comprised women aged 20 to 49 years who visited medical institutions for health checkups between 1 January 2012 and 31 December 2020, excluding women diagnosed with PCOS. If a medical institution was visited at least twice for a health checkup, the date of the initial visit was taken as the inclusion day. Women who visited the hospital for PCOS or a health checkup in 2011 were not eligible to wash out. Women with any cancer (ICD-10 diagnostic code of “any Cxx”) diagnosed within 180 days of the inclusion day were excluded from the PCOS and control groups. Additionally, women without a delivery record within 180 days after the inclusion day were excluded from both groups. Women who visited a medical institution more than once before the inclusion day due to hypertension (HTN) (ICD-10 code = I10~I15), diabetes mellitus (DM) (E10~E14), hyperlipidemia (E78), DM in pregnancy (O24), or PIH (O14~O15) were excluded from both study groups. ## 2.3. Outcome GDM and PIH were defined as cases with at least three visits to a medical institution with the ICD-10 diagnostic codes for GDM (O24.4) and PIH (O14~O15), respectively. ## 2.4. Variables When medical aid was the only sort of insurance available to a subject, they were classified as having a low socioeconomic status (SES). If the inclusion region was not urban, it was classified as rural. CCI was determined from the date of inclusion to 1 year prior using diagnostic codes [17]. Parity (primiparity or multiparity) and multiple pregnancies were determined from delivery records. HTN (I10~I15), DM (E10~E14), hyperlipidemia (E78), and obesity (BMI > 25 kg/m2, E66) were defined as two or more visits to a medical institution with the associated diagnosis codes. Adnexal surgery was defined as being present when excision of an adnexal tumor, adnexectomy, ovarian wedge resection, or incision and drainage of an ovarian cyst was performed at least once before the inclusion day. Those who visited a medical institution at least twice before the inclusion day with a diagnosis code related to uterine fibroids (D25) or endometriosis (N80) were considered to have the corresponding disease. ## 2.5. Statistical Analyses SAS Enterprise Guide (version 7.15, SAS Institute, Cary, NC, USA) was used for all statistical analyses, with R software (version 3.5.1, The R Foundation for Statistical Computing, Vienna, Austria) serving as an accessory. A two-sided test was applied in each statistical analysis, and a p-value of 0.05 or less was considered statistically significant. Pearson’s chi-square or Fisher’s exact test was used for analyzing categorical variables, and t-test or Mann–Whitney U-test was used to analyze continuous variables. Logistic regression analysis was used to evaluate the risks of GDM and PIH in PCOS in the presence of certain confounding factors. The inclusion day was chosen as the starting point, and the end date was chosen as the first delivery date after inclusion. The listwise deletion approach was used when there were fewer than $10\%$ missing values, while the regression imputation method was used when there were more than $10\%$ missing values. The validity of our study’s findings was evaluated using logistic regression analysis to determine the risks of GDM and PIH for PCOS in women with a moderate-to-high SES. ## 2.6. Ethics The IRB of Sanggye Paik Hospital approved this study (approval no.: SGPAIK 2021-12-005). Variables that could be used to identify individuals were de-identified in the study. The analyses were conducted entirely on an offline server provided by HIRA; only calculated numerical values (tables, figures, and numbers) were exportable from the server. This protocol ensured no risk in the study participants being identified. Additionally, the need to obtain informed consent was not required under South Korea’s Bioethics and Safety Act. According to HIRA’s privacy policy, only research results were exportable from the server, meaning raw data cannot be made available to readers. Although this study used HIRA data, HIRA had no interest in the results. ## 3. Results Patient data on 724,307 women (aged 20–49 years) who underwent a medical checkup or were diagnosed with PCOS during 2012–2020 were extracted from the HIRA database. Extracting data according to delivery status within 180 days after the inclusion day and excluding cancer, HTN, and DM resulted in 73,281 women being enrolled: 45,594 without PCOS and 27,687 with PCOS (Figure 1). Table 1 lists the detailed characteristics of these patients. Their median age was 30 years (interquartile range = 27–33 years). The rate of primiparity was higher in the control group, while the multiple pregnancy rate was higher in the PCOS group. The rate of obesity differed significantly between the two groups. Table 2 indicates that GDM and PIH incidence rates were higher in the PCOS group than in the control group (GDM: $5.1\%$ vs. $8.4\%$, $p \leq 0.001$; PIH: $0.3\%$ vs. $0.4\%$, $$p \leq 0.016$$). PCOS was a risk factor for both GDM (relative risk (RR) = 1.709, $95\%$ CI = 1.610–1.814, $p \leq 0.001$) and PIH (RR = 1.385, $95\%$ CI = 1.062–1.808, $$p \leq 0.016$$). Logistic regression analysis was performed to identify the risk factors of PCOS for GDM and PIH (Table 3). In adjusted logistic regression, PCOS was a risk factor for GDM (RR = 1.719, $95\%$ CI = 1.616–1.828, $p \leq 0.001$) but not for PIH (RR = 1.243, $95\%$ CI = 0.940–1.644, $$p \leq 0.127$$) (Figure 2). However, primiparity (RR = 2.293, $95\%$ CI = 1.292–4.082, $$p \leq 0.005$$), multiple pregnancies (RR = 3.668, $95\%$ CI = 2.605–5.165, $p \leq 0.001$), and endometriosis (RR = 2.399, $95\%$ CI = 1.310–4.395, $$p \leq 0.005$$) were significantly associated with PIH. ## 4. Discussion PCOS is one of the most common endocrine disorders in women of reproductive age [18]. Pregnancy is a diabetogenic state in which progressive insulin resistance that develops during pregnancy due to placental production of diabetogenic hormones decreases glucose entry into maternal cells and preserves fuel for the developing fetus [19]. Therefore, the basic pathophysiologies of insulin resistance and obesity can result in PCOS affecting the progression of the diabetogenic status of pregnancy to adverse metabolic complications, such as androgen excess, dyslipidemia, or low-grade chronic inflammation [20]. Additionally, induced metabolic abnormalities in women with PCOS increase oxidative stress [6]. Therefore, these clinical and biochemical characteristics associated with trophoblast invasion and placentation directly affect pregnancy complications. [ 21,22] As mentioned above, several previous studies have suggested that PCOS could be an independent risk factor for GDM and PIH. However, the considerable heterogeneity between the studies, including in the ethnic backgrounds of the subjects, means that the relationships remain inconclusive. In the present study, after adjusting confounding factors, PCOS was isolated as a risk factor for GDM, whereas its relationship with PIH remained unclear in a homogeneous East Asian population. We found that PCOS was associated with an increased risk for GDM of slightly lower than twofold (adjusted RR = 1.719, $95\%$ CI = 1.616–1.828). Compared with previous studies, the present study had a large cohort, and the risk was slightly lower. This difference is probably due to differences in the ethnicity heterogeneity of the included populations and in the confounding factors. Regarding ethnicity, the GDM incidence in this study was affected by the entire included population being Korean. The prevalence of GDM has been estimated at $14\%$ for all pregnancies in the US and has been increasing in multiethnicity populations [23,24]. In contrast, only $2\%$ to $5\%$ of all pregnant Korean women reportedly develop GDM [25]. Regarding confounding factors, the present study was designed to evaluate the risk of PCOS by itself, and so, the analyzed data set excluded a previous history of GDM, PIH, HTN, and DM, which affect multifetal pregnancies, and this would affect the identified risks. The risk associated with PIH appeared similar to that in a previous study (crude RR = 1.385, $95\%$ CI = 1.062–1.808, $$p \leq 0.016$$). However, after adjusting confounding factors, the association was not statistically significant (adjusted RR = 1.243, $95\%$ CI = 0.940–1.644). PIH is a multiorgan disease, so its risk factors are multifactorial [26]. In particular, multifetal pregnancy, nulliparity, and GDM are also suggested as PIH risk factors that were not adjusted in the previous cohort study. Additionally, ethnicity heterogeneity affects PIH development. Table 3 indicates that primiparity and multifetal pregnancy affected the PCOS independent risk presentation. Endometriosis was found to be a risk factor for PIH in our study. Similarly, a recent, large-cohort study suggested that endometriosis affects adverse pregnancy outcomes, including PIH (adjusted RR = 1.17, $95\%$ CI = 1.03–1.33) [27]. Previous research has suggested that women with endometriosis have higher levels of local and systemic inflammation that may influence the risk for specific pregnancy outcomes such as preterm birth, PIH, and pregnancy-induced PE and eclampsia [28,29,30]. The limitation of this study is that it performed a retrospective analysis utilizing an administrative database, which relies on the accuracy and consistency of the individuals coding the data. Obesity is a major clinical presentation of PCOS and a significant risk factor for GDM and PIH. In this study, the incidence of obesity was very low in the control group ($0.1\%$) and the PCOS group ($0.2\%$), which might be due to missing data or inaccurate data coding. Further evaluations with other BMI data, therefore, need to be performed. However, Ryu et al. found only a tiny difference in the obesity rates between normal and PCOS groups in a Korean population ($14.4\%$ vs. $15.7\%$), which was much smaller than that found in the cohort study performed by Mills et al. ( $3.5\%$ vs. $22.3\%$) [12,31]. Therefore, although further confirmation is necessary, it appears that obesity did not exert marked effects in the present cohort. Despite the limitations, the strength of the present study was that it assessed pregnancy risk factors related to PCOS in a large cohort with a single Asian ethnicity. Additionally, multiple confounding factors such as pregestational HTN and DM were excluded, and multifetal pregnancy, parity, and GDM were adjusted to identify the actual risk of PCOS in pregnancy. The incidence of PCOS varies according to the diagnostic criteria employed. PCOS is commonly diagnosed using three diagnostic criteria: NIH criteria, Rotterdam criteria, and Androgen Excess *Society criteria* [32]. 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--- title: Key Stratification of Microbiota Taxa and Metabolites in the Host Metabolic Health–Disease Balance authors: - Alfonso Torres-Sánchez - Alicia Ruiz-Rodríguez - Pilar Ortiz - Margarita Aguilera journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003303 doi: 10.3390/ijms24054519 license: CC BY 4.0 --- # Key Stratification of Microbiota Taxa and Metabolites in the Host Metabolic Health–Disease Balance ## Abstract Human gut microbiota seems to drive the interaction with host metabolism through microbial metabolites, enzymes, and bioactive compounds. These components determine the host health–disease balance. Recent metabolomics and combined metabolome–microbiome studies have helped to elucidate how these substances could differentially affect the individual host pathophysiology according to several factors and cumulative exposures, such as obesogenic xenobiotics. The present work aims to investigate and interpret newly compiled data from metabolomics and microbiota composition studies, comparing controls with patients suffering from metabolic-related diseases (diabetes, obesity, metabolic syndrome, liver and cardiovascular diseases, etc.). The results showed, first, a differential composition of the most represented genera in healthy individuals compared to patients with metabolic diseases. Second, the analysis of the metabolite counts exhibited a differential composition of bacterial genera in disease compared to health status. Third, qualitative metabolite analysis revealed relevant information about the chemical nature of metabolites related to disease and/or health status. Key microbial genera were commonly considered overrepresented in healthy individuals together with specific metabolites, e.g., Faecalibacterium and phosphatidylethanolamine; and the opposite, *Escherichia and* Phosphatidic Acid, which is converted into the intermediate Cytidine Diphosphate Diacylglycerol-diacylglycerol (CDP-DAG), were overrepresented in metabolic-related disease patients. However, it was not possible to associate most specific microbiota taxa and metabolites according to their increased and decreased profiles analyzed with health or disease. Interestingly, positive association of essential amino acids with the genera Bacteroides were observed in a cluster related to health, and conversely, benzene derivatives and lipidic metabolites were related to the genera Clostridium, Roseburia, Blautia, and Oscillibacter in a disease cluster. More studies are needed to elucidate the microbiota species and their corresponding metabolites that are key in promoting health or disease status. Moreover, we propose that greater attention should be paid to biliary acids and to microbiota–liver cometabolites and its detoxification enzymes and pathways. ## 1. Introduction Gut microbiota is considered a complex ecosystem with a wide array of microorganisms linked to host health. Multiple studies suggested that the structure and composition of the gut microbiota in metabolic-related diseases, such as atherosclerosis, colitis, diabetes, hyperlipidemia, hypertension, metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), obesity, and steatosis, exhibit significant changes compared to healthy individuals and that those changes are related to host physiopathology. In this context, the analysis and description of trends in microbial populations associated with disease and health status become a key issue to elucidate possible signatures of metabolic-related diseases. The gut microbiota of patients with metabolic-related diseases shows differences at different taxonomic levels. Many studies showed that Parabacteroides, Bifidobacterium, Oscillospira, and Bacteroides were decreased in patients with obesity [1,2,3,4,5,6,7,8,9,10,11,12,13]. Moreover, Faecalibacterium and Bifidobacterium were decreased [14,15,16,17,18,19,20,21] and species from Lactobacillaceae family [22] and Blautia were increased [7,13,19,20,21,22,23,24,25,26,27] in diabetic patients. Other metabolic diseases related to intestinal diseases seem to be related to increased *Escherichia and* decreased Faecalibacterium [28,29,30,31,32,33,34,35,36,37]. Recently, the combination of metagenomics and metabolomics has received extensive attention due to the growing number of studies that establish positive and negative correlations between gut microbiota taxa, metabolites, and health status. Therefore, future studies will contribute to elucidate the essential role of gut microbiota in metabolite synthesis, metabolite modifications, and metabolic pathway regulations. In this sense, metabolites such as short-chain fatty acids (SCFA), amino acids (AA), or bile acids (BA) can play a crucial role in maintaining metabolic functions or, on the contrary, they might be involved in disease development, such as choline derivatives in the case of cardiovascular diseases [38,39,40,41]. Metabolite influences are not restricted to the intestine and distribution to other physiological locations has been described through different axes, such as the gut–liver axis, in which the gut microbiota is related to liver diseases, including NAFLD, NASH, fibrosis, or liver cancer [42]. Gut microbiota partially impacts the host BA profile as it is involved in primary bile acid transformation into secondary free bile acids, such as deoxycholic acid, lithocholic acid, and ursodeoxycholic acid, contributing to the modulation of host total bile acid production [43]. The chemical structure of many endogenous compounds, including gut microbiota metabolites, can be modified, resulting in changes in their bioactivity and half-life [44]. This kind of modifications are related to the development of complex metabolic networks between host and gut microbiota, where final substances could be potentially more toxic than the original ones [45]. Traditional probiotics, mainly consisting of species from Lactobacillaceae and Bifidobacteria and a few from other genera, have been largely applied as a useful strategy in the context of clinical intervention in metabolic-related diseases [46,47]. However, the development of new procedures using Next Generation Probiotics (NGP) opens a new world of possibilities due to the beneficial effects that have already been described in murine models and, to a lesser extent, in humans. In this context, murine models show Akkermansia muciniphila, Faecalibacterium prausnitzii, Bacteroides uniformis, Bacteroides acidifaciens, Clostridium butyricum, and Prevotella copri as interesting microorganisms with potential applications in obesity [48,49,50,51,52,53], liver diseases [52,54,55,56,57,58,59], diabetes [48,49,50,51,52,53,58,60,61], colitis [62], and hyperlipidemia [53,58]. This work will contribute to finding out microbial and metabolite patterns and their correlation with diseases that have been studied independently or not yet extensively studied. Therefore, the principal aim of this work is to identify and describe the association between human gut microbiota taxa changes in metabolic-related diseases, incorporating the correlations with metabolites, and how they can modulate host health. ## 2.1.1. PRISMA Analysis Gut microbial taxa differences in diabetes, obesity, metabolic syndrome, and liver and cardiovascular diseases, highlight links between gut microbiota and host health status. In this context, Figure 1 summarizes updated and available information about gut microbial taxa changes in these metabolic-related diseases. ## 2.1.2. Microbial Taxa Decreased in Patients Suffering from Metabolic-Related Diseases Increased and decreased trends in gut microbiota taxa were assessed through an extensive literature search including information about metabolic diseases investigated by different authors. In this context, the approach we followed offered some drivers of specific changes in gut microbiota composition that could be related to host health. The analysis of 75 studies involving changes of the main taxa altered in patients suffering metabolic-related diseases disclosed 121 differentially abundant microbial genera (complete data are available in Supplementary Material S1). Figure 2 shows representative genera count value comparison obtained in metabolic diseases after microbial taxa variation analysis. Gut microbiota genera such as Oscillibacter, Butyricicoccus, Odoribacter, and Paraprevotella were exclusively decreased in individuals affected by metabolic diseases. On the other hand, Faecalibacterium, Bifidobacterium, Ruminococcus, Parabacteroides, Roseburia, Akkermansia, Alistipes, Coprococcus, and Oscillospira were both decreased and increased in metabolic-related diseases. However, overall, these microbial genera showed a negative association with the metabolic diseases studied here. ## 2.1.3. Microbial Taxa Increased in Patients Suffering Metabolic-Related Diseases *Microbial* genera such as Klebsiella, Collinsella, and Enterococcus were exclusively present in those cases in which individuals were affected by metabolic diseases. However, taxa belonging to Escherichia, Lactobacillaceae, Blautia, Streptococcus, and Dorea were also identified in patients without metabolic-related diseases. These microbial genera showed an upward trend in metabolic-related diseases studied here. Figure 3 shows the distribution of representative microbial taxa linked to metabolic-related diseases. In a previous study exploring next generation probiotics for metabolic and microbiota dysbiosis linked to xenobiotic exposure [63], we tried the first approach to describe changes in gut microbial taxa associated to metabolic-related disease. As a result, potential associations between bacterial genera and metabolic diseases were described despite the lesser number of analyzed studies. In this case, Table 1 shows an expansion of the current knowledge available in this field, including the relevant information identified in the previous study. ## 2.2. Differential Microbial Metabolites and Stratification According to Their Representation in Metabolic Diseases The analysis of the 16 selected studies involving correlations between gut microbiota taxa altered in patients suffering from metabolic diseases, metabolites, and host health status allowed us to shed light on potential critical pathways to modulate homeostatic processes (complete data are available in Supplementary Material S2 [103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118] Figure 4 summarizes available information about gut microbiota–metabolite correlations and host health status. Several gut microbiota taxa showed a high metabolite count linked to disease or health status. In that regard, increased microbial metabolite counts in health status were obtained in gut microbiota genera such as Holdemania, Porphyromonas, and Dialister; further, they were also higher for Bacteroides, Clostridium, and Alistipes, but with more similar counts in both groups. Figure 5 shows representative genera differential values associated to health-related metabolite count analysis. Increased metabolite counts related to disease status were linked to gut microbiota taxa such as Ruminococcus, Eubacterium, Blautia, Roseburia, Oscillibacter, Subdoligranulum, Gemmiger, Butyricicoccus, Akkermansia, Veillonella, Dorea, Coprococcus, Escherichia, Parabacteroides, Enterobacter, Lachnospira, Gemella, and Fusobacterium. Figure 6 shows representative genera differential values associated to disease-related metabolite count analysis. According to the total metabolites linked to disease and health status, 171 metabolites were associated with metabolic-related diseases; among these, 143 were exclusively associated with this group and 28 were shared with health status. Moreover, 63 metabolites were related to health status, and 35 were exclusively associated with this group. A qualitative metabolite analysis was performed considering total disease/health-related metabolites. Table 2 shows disease/health-related metabolites classified according to three main chemical groups: fatty acids and conjugates, amino acids and derivatives, and bile acids and derivatives. A further association analysis of the number of studies where a specific association between a metabolite and a bacterial genus was found showed very interesting clustering patterns. For instance, butyrate-producer genera when present in a healthy status associated with bile acid metabolites and, to a lesser extent, with essential amino acids; however, when they are overrepresented in metabolic diseases, they are associated with lipid metabolism, clustering in two distinct groups. We also observed that essential amino acids clustered together, and they might have an important role for the metabolism of Bacteroides in health status, according to Figure 7. ## 3. Materials and Methods We performed a comprehensive literature search covering the period from 1995 to November 2022 using Scopus, Web of Science, and PubMed databases, using the search strategies showed in systematic review and dividing this review into two main study issues: gut microbial taxa variations in metabolic-related diseases and gut microbiota–metabolite correlations in metabolic-related diseases. Studies involving changes in gut microbial taxa in atherosclerosis, colitis, diabetes, hyperlipidemia, hypertension, metabolic syndrome, NAFLD, NASH, obesity, and steatosis and studies involving microbiota–metabolite correlations in metabolic-related diseases were assessed, screened, and selected according to PRISMA 2020 flow diagrams (Figure 1 and Figure 4) [111]. In the microbial taxa variation analysis, gut microbial taxa identified in selected studies were divided into two groups: decreased in metabolic-related diseases and increased in metabolic-related diseases, based on research findings. Metabolite counts were calculated for each microbial genus. To determine representative gut microbiota taxa, an arbitrary criterion was applied. *Microbial* genera were considered representative if the absolute frequency difference between decreased–increased counts was greater than three. In the gut microbiota–metabolite correlation analysis, gut microbiota, microbial metabolites, and host status correlations were assessed. First, gut microbial genera were classified into increased in health status or increased in diseases, according to metabolite absolute frequencies displayed for each genus. Second, considering metabolites related to representative genera in health or disease status, a qualitative metabolite analysis was performed. Metabolites correlated with health or disease status were classified into three main groups: fatty acids and conjugates (FA), amino acids and derivatives (AA), and bile acids and derivatives (BA), according to PubChem and related chemical database classification. Furthermore, a bioinformatics analysis was performed to establish potential biomarkers, which revealed the association between specific disease/health balances. Heatmap shows the analysis where a specific association between a metabolite and bacterial genera was found in a health and/or a disease stage (as indicated by “_H” or “_D”, respectively). For simplicity, only the representative genera and the most found metabolites (metabolites that appeared least five times either associated with health or disease in the studies analyzed here) were included. First, we selected only the genera with more than 10 metabolites associated and then we kept only the metabolites that appeared at least five times, either associated with health or disease, in the studies analyzed here. Figure 7 shows the performance of R (version 4.1.1.) using the package “pheatmap” [112]. ## 4. Discussion There is a growing interest in the analysis of the gut microbiome and its metabolome [113,114]. However, integrating data from both fields to understand how gut microbiota, microbial metabolites, and host status are correlated not always provide concise information. Thus, it can hinder researchers in establishing clear links between the presence of a particular gut bacterial taxa and/or metabolites and disease or health status. This task is especially challenging in the context of searching gut microbial biomarkers that allow predicting future phenotypes or classifying individuals into disease and non-disease status. This is mainly due to the fact that contradictory results about microbial taxa abundance and metabolites related to disease or non-disease status can be found in the literature. In this case, this approach showed that Faecalibacterium, Bifidobacterium, Ruminococcus, Parabacteroides, Roseburia, Akkermansia, Alistipes, Coprococcus, Oscillospira, Oscillibacter, Butyricicoccus, Odoribacter, and Paraprevotella could represent a downregulated microbial cluster in metabolic-related disease patients and, on the contrary, Escherichia, species from Lactobacillaceae family, Blautia, Streptococcus, Klebsiella, Collinsella, Dorea, and Enterococcus cluster upregulation could be involved in metabolic-related disease status. Due to relevant information underlined by many authors and results obtained in this review, Ruminococcus and Bifidobacterium, as well as taxa belonging to Lactobacillaceae family, Blautia, and Dorea should be identified at the species level to establish similarities with the results already available in the microbiological databases. According to metabolite absolute frequencies in disease and health status and representative gut microbiota taxa, we tried to search for possible trends between those elements and host physiopathology. When we compared representative metabolites and microbial taxa results, only Alistipes, from the down-regulated proposed cluster, showed high counts in both gut microbial taxa variation analysis and metabolite count analysis related to health. In the same way, Escherichia, Blautia, Streptococcus, Collinsella, Dorea, and Enterococcus, from the proposed upregulated cluster, showed high counts in both gut microbial taxa analysis and metabolite count analysis in disease/disorder group. Following this approach, Faecalibacterium and *Akkermansia* genera [115,116], frequently described as key microorganisms related to health status, were decreased in metabolic-related diseases, indicating a possible relationship with health status. However, a link with disease status could be identified according to metabolite absolute frequencies described for both genera Faecalibacterium and Akkermansia. A similar result can be observed in other microorganisms frequently associated with metabolic diseases [117], where microbial taxa analysis showed links with obesity-related diseases. However, metabolite absolute counts showed links with health status. Interestingly, preliminary data results derived from the biomarker search have demonstrated the positive association of essential amino acids with health in the genera Bacteroides, and conversely, benzene derivatives have been related to disease and the genera Clostridium. We also observed that lipid metabolites grouped several taxa overrepresented in diseases, but it will be necessary to determine the results to the species level. These results showed which bacterial taxa of the gut microbiota and their derived metabolites could be related to host status manifestations. However, study limitations and lack of available data in some fields make it impossible to establish final and solid conclusions in this way. Human health is not only affected by gut microbiota composition and its derived metabolites but also many exogenous and endogenous factors, which can also impact in genotypic and phenotypic manifestations. Recently, the holistic concept of the One Health approach and the exposome include multidisciplinary analysis of a complex reality that affect different but linked items [118]. Nowadays, solid evidence about specific microbial and metabolite signatures in cases of metabolic-related disease is still limited and more concrete information on the correlations between gut microbiota, gut metabolites, and host health status is needed. This synergic approach will lead to a better management of well-known microbiota–metabolic related diseases. To increase the availability of scientific data on the interaction between gut microbiota taxa in different health contexts, metabolite synthesis, and metabolite modification and impact on the host health, integrated metagenome and metabolome analysis should be continually reviewed, since it seems to be a possible cornerstone involved in the determination of potential microbial and metabolite signatures related to physiological alterations. ## 5. Conclusions Despite the existence of microbial taxa–metabolite-health correlations, there is no evidence of a clear gut microbiota and derived metabolite patterns into healthy or metabolic-related disease status that is able to predict or classify patients into one or the other. Most of the taxa and metabolites did not show representative oscillations between disease and health groups, so bacterial genera with potential interest should continue to be monitored as new information on their abundance in metabolic-related disease appearance. Implementation of the One Health holistic approach combined with exposome principles can provide new perspectives and evidence about how endogenous and exogenous substances interact with gut microbiota and microbial-derived substances and how the pull of interactions finally affects human homeostasis. ## References 1. 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--- title: Beneficial Effects of Dinitrosyl Iron Complexes on Wound Healing Compared to Commercial Nitric Oxide Plasma Generator authors: - Alexandra Igrunkova - Alexey Fayzullin - Natalia Serejnikova - Tatiana Lipina - Alexandr Pekshev - Anatoly Vanin - Victoria Zaborova - Elena Budanova - Dmitry Shestakov - Igor Kastyro - Anatoly Shekhter journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003304 doi: 10.3390/ijms24054439 license: CC BY 4.0 --- # Beneficial Effects of Dinitrosyl Iron Complexes on Wound Healing Compared to Commercial Nitric Oxide Plasma Generator ## Abstract Nitric oxide (NO) is a gaseous molecule which plays a key role in wound healing. Previously, we identified the optimal conditions for wound healing strategies using NO donors and an air plasma generator. The aim of this study was to compare the wound healing effects of binuclear dinitrosyl iron complexes with glutathione (B-DNIC-GSH) and NO-containing gas flow (NO-CGF) at their optimal NO doses (0.04 mmol for B-DNIC-GSH and 1.0 mmol for NO-CGF per 1 cm2) in a rat full-thickness wound model over a 3-week period. Excised wound tissues were studied by light and transmission electron microscopy and immunohistochemical, morphometrical and statistical methods. Both treatments had an identical stimulating impact on wound healing, which indicated a higher dosage effectiveness of B-DNIC-GSH compared to the NO-CGF. B-DNIC-GSH spray application reduced inflammation and promoted fibroblast proliferation, angiogenesis and the growth of granulation tissue during the first 4 days after injury. However, prolonged NO spray effects were mild compared to NO-CGF. Future studies should determine the optimal B-DNIC-GSH solution course for a more effective wound healing stimulation. ## 1. Introduction Nitric oxide (NO) is an endogenous gaseous signaling molecule which regulates multiple biological functions, including vasospasm, transmission of nerve impulses and inflammation. It has been thoroughly demonstrated that NO plays a key role in wound healing [1,2,3]. The application of exogenous NO became a popular trend in wound therapy based on the fact that insufficient NO tissue concentration disrupts regeneration [4]. NO application was shown to be beneficial in a range of medical conditions varying from traumatic and diabetic wounds to acute respiratory distress syndrome [1,5,6,7]. There are two main NO-therapy directions used for wound healing stimulation: NO containing plasma and pharmaceutical NO donors or NO-synthase inductors [4,8,9,10]. The variety of NO donors and their ability to be locally delivered as components of implantable biomaterials and tissue-engineered constructs make them the most promising candidates for NO-therapy [4,11]. Dinitrosyl iron complex (DNIC) is the primary storage form of NO in organisms. Its mononuclear form (M-DNIC) ((RS-)2Fe2+(NO)(NO+)) consists of an iron atom, two thiol residues and two nitrosyl ligands, namely, the neutral NO molecule and the nitrosonium cation (NO+) [10,11]. DNIC has been broadly studied in cardiology, oncology and pulmonology. The clinical trials of Oxacom (DNIC with a glutathione ligand) demonstrated its safety and pronounced hypotensive effect when administered intravenously at a dose of 1 mg/kg/min [12,13]. DNIC induced tumor cell apoptosis in experiments on prostate cancer cell lines (PC-3), breast cancer (SKBR-3) and non-small cell lung cancer (CRL5866) [14]. In vivo studies have also confirmed the efficacy of DNIC on microvasculature growth control in oncology [15]. Burgova et al. demonstrated that intraperitoneal injections of DNIC with thiol ligands at a dose of 20 µM/kg for 10–12 days completely suppressed the growth of endometriosis tumor nodes [16]. Several research groups have reported that DNIC administration, primarily in the form of wound bottom injections, can accelerate wound healing [11,17,18,19,20]. However, these injections are associated with local traumatization and systemic complications. To solve this problem, we developed a new delivery form of DNIC (spray) and determined the most effective dose for facilitation of wound healing. We identified the most effective dosage for spray with binuclear dinitrosyl iron complexes with glutathione (B-DNIC-GSH, formula ((GS−)2Fe2+2(NO)2(NO+)2)), which was 16.6 mg/cm2 (0.02 mmol B-DNIC-GSH per 1 cm2 calculated in relation to one atom of iron in this nuclear complex) [19]. Since each iron atom in the compound is bound to two nitrosyl ligands, a maximum of 0.04 mmol NO could be released in gaseous form from 0.02 mmol B-DNIC-GSH. This dosage of B-DNIC-GSH inhibited inflammation and promoted the growth and maturation of granulation tissue by day 4 of wound healing. Plasma medicine is a rapidly developing field utilizing plasma which contains a varying range of active components with pro-regenerative effects, including inert gas molecules, ions and oxides. The dermatology and cosmetology markets have created demand for medical plasma devices: kINPen MED (INP Greifswald/neoplas tools GmbH, Greifswald, Germany), PlasmaDerm VU-2010 (CINOGY Technologies GmbH, Duderstadt, Germany), PlasmaCare (Terraplasma Medical, Garching, Germany), SteriPlas (Adtec Ltd., London, UK) and PlasmaJet (Plasma Surgical Ltd., Atlanta, GA, USA) [9,21,22]. *Plason* generates high concentrations (up to ~5000 ppm) of nitric oxide and small amounts of by-products, including Nitrogen Dioxide (NO2), OH and H2O2, in comparison to the other devices [22]. This unique feature of the Plason defines the treatment effects related to NO mechanisms of action. It has been used in clinical practice since 2000 to treat wounds, trophic and diabetic ulcers, burns, cornea injuries, sports injuries, arthritis and other pathologies [1,23]. The bulk of clinical evidence allows us to use it as a commercial control in our study. We demonstrated in our previous studies that effective treatment of skin wounds with NO-CGF generated by the Plason device was achieved by applying 30 mg (1 mmol) of NO per 1 cm2 of wound surface [8]. This value, in a millimolar ratio, was 25 times higher than the above dose of NO released from B-DNIC-GSH for the optimal healing effect. This fact may indicate the high efficiency of these complexes as compounds that accelerate the healing of skin wounds. However, before making such a conclusion, it was necessary to investigate whether the wound healing effects of these agents would be the same in all morphological, biochemical and physiological parameters at the specified optimal doses. This hypothesis was tested in the present work. ## 2.1. Gross Examination On Day 4, the wound surfaces in the control groups (air, saline) were covered with a relatively thick layer of loose fibrin and exudate (Figure 1A,I). Fibrin accumulation was observed along the wound edges in three animals treated with NO-CGF (Figure 1E). In the DNIC group, a thin layer of exudate covered the wound bottoms, and a loose whitish film of fibrin was observed along the wound edges in two rats (Figure 1M). Moderate exudation and fibrin production indicated development of the inflammatory phase of wound healing. The other animals of the experimental groups had smooth and shiny wound surfaces. On Day 7, all the wounds were covered with dense fibrin clots with a rough surface; they were tightly bound to the underlying tissues (Figure 1B,F,J,N). The animals in the experimental groups had the smallest wound areas (2.4 ± 0.12 cm2 for NO-CGF and 2.5 ± 0.14 cm2 for DNIC). They were significantly smaller than in the saline control group (2.94 ± 0.12 cm2) ($p \leq 0.01$) or air control group (2.9 ± 0.11 cm2) ($p \leq 0.01$) (Figure 2). On Day 14, we revealed a pronounced marginal epithelialization and wound area reduction in the experimental groups. The wound bottoms of the animals of the control groups were clean, except for one case of purulent inflammation in the saline control group (Figure 1C,K). The areas of the NO treated wounds were significantly smaller than in the saline control group (0.52 ± 0.10 cm2 for NO-CGF and 0.61 ± 0.12 cm2 for DNIC against 1.23 ± 0.27 cm2 for saline) ($p \leq 0.01$) (Figure 1G,O and Figure 2). By Day 21, the wounds were completely epithelialized in five out of six animals of the NO-CGF group and four out of six rats in the DNIC group (Figure 1H,P). The wound areas in these groups, especially where NO-CGF was applied, were statistically smaller compared to the saline control group ($p \leq 0.05$) (Figure 1H,L and Figure 2). In the air control group, complete epithelialization was observed in three animals (Figure 1D). ## 2.2. Histological Study On Day 4, thick fibrin clots covered the wound bottoms in the air control group (Figure 3A and Figure A1 Appendix A). Microbial colonies were observed in fibrin clots in two out of six animals. Under them, islets of immature granulation tissue consisted of chaotically orientated vimentin and alpha smooth muscle actin (α-SMA) positive cells, inducible Nitric Oxide synthase (iNOS) positive fibroblasts, singular capillaries, diffuse immune cell infiltration with neutrophils and Nuclear factor kappa B (NF-κß) positive macrophages (Figure 3B, Figure 4A,B, Figure 5A,B and Figure 6A,B). Collagen fibers had intensive anisotropy in the deep wound area (Figure 3C). In the NO-CGF group, the signs of inflammation were moderate and microbial contamination was absent (Figure 3D and Figure A2). NF-κß and iNOS expression in macrophages and fibroblasts was more intensive compared with the air control group ($p \leq 0.05$) (Figure 4E,F and Figure 7). The collagen fibers were orientated along the wound bottom. The tissue was rich with proliferating vimentin and α-SMA-expressing cells, and the blood vessels were stretched between the wound surface and deeper layers of soft tissues (Figure 3E, Figure 5E,F and Figure 6E,F). Anisotropy of granulation tissue fibers was low (Figure 3F). In the saline control group, the fibrin clots were thick, and they contained bacterial colonies. The granulation tissue was characterized by a low content of collagen fibers, α-SMA-positive cells, vasculitis and diffuse lymphocyte and iNOS-positive macrophage infiltration (Figure 3G,H, Figure 4J and Figure 5I,J). Fibroblasts were vimentin positive and expressed NF-κß-positive in cytoplasm (Figure 4I and Figure 6I,J). Polarized light microscopy revealed thin collagen fibers with green anisotropy (Figure 3I). In the DNIC group, the fibrin clots were thin and contained singular bacterial colonies. Immune cell infiltration with iNOS-positive macrophages and lymphocytes and microcirculatory disorders were less pronounced (Figure 3J and Figure 4N). The inflammatory index showed a significantly lower intensity than in the previous group ($p \leq 0.01$) (Figure 6). In this group, the NF-κß activity index was $42\%$ higher than in the air control group ($p \leq 0.01$) and $27\%$ higher than in the saline control group ($p \leq 0.01$) (Figure 4M and Figure 7). The granulation tissue layer was $57\%$ thicker than in the air control group and $59\%$ thicker than in the saline control group (Figure 8). It consisted of vertically oriented capillaries and densely packed vimentin-positive fibroblasts (Figure 3J and Figure 6M,N). Multiple collagen fibers were stained blue by picro-Mallory (Figure 3K). The α-SMA expression index was lower than in the groups where the wounds were blown with NO-CGF or air ($p \leq 0.05$) (Figure 5M,N and Figure 9). Polarized light microscopy revealed the predominance of yellow glowing of collagen fibers in the deep wound areas (Figure 3L). These signs suggest the maturation of the granulation tissue. On Day 7, we observed marginal epithelization of wounds in all study groups. Central parts of the wounds were covered with fibrin clots. The thickest fibrin clot was in the air control group. The granulation tissue comprised fibroblasts with NF-κβ cytoplasmic expression, mild diffuse lymphocyte and iNOS-positive macrophage infiltration, and many congested capillaries, with productive endo- and panvasculitis (Figure 4C,D and Figure 10A). The area of cells with cytoplasmic α-SMA expression was significantly lower compared to the groups in which wounds were treated with NO ($p \leq 0.01$) (Figure 5C,D and Figure 9). Collagen fibers were found only in deep wound areas (Figure 10B). They had low anisotropy and maturity (Figure 10C). In this group, the mean area of vimentin-positive cells was $63.25\%$ (±8.75), which was almost 1.5-fold higher than in the DNIC group ($p \leq 0.01$) and about 2-fold higher than in the saline control group ($p \leq 0.01$) (Figure 6C,D and Figure 11). We found bacterial contamination in only one animal of the group treated with NO-CGF. The fibrin clot thickness was thinner than in the previous group. Half of the animals had immature granulation tissue, while it was mature in the rest (Figure 10D). Spindle-shaped fibroblasts intensively expressed iNOS (Figure 4H). Vimentin-positive cells (fibroblasts) occupied the largest area relative to the other groups ($65.5\%$ (±7.55)), and the area of α-SMA-positive cells was $53\%$ larger than in the saline control group (Figure 5G,H, Figure 6G,H, Figure 9 and Figure 11). Collagen fibers were arranged in parallel, and capillaries were oriented vertically toward the wound surface. The NF-κß activity index in fibroblasts was significantly higher than in the control groups (air, saline) ($p \leq 0$,01) (Figure 4G and Figure 7). Picro-Mallory staining showed the prevalence of collagen fibers in this group compared to the air control group (Figure 10E). Polarized light microscopy revealed the red color of collagen fibers, mainly in the deep layers of the wound (Figure 10F). In the saline control group, the granulation tissue was very immature in four out of six cases. It was characterized by the moderate proliferation of iNOS and NF- κß-positive fibroblasts, poor angiogenesis, lymphostasis and diffuse infiltration with immune cells (Figure 4K,L, Figure 10G and Figure A3). The α-SMA expression index and the area of vimentin-positive cells was minimum (mean 0.43 ± 2.8) (Figure 5K,L, Figure 6K,L, Figure 9 and Figure 11). Picro-Mallory staining revealed numerous collagen fibers of dark blue color, which had very weak birefringence in polarized light microscopy (Figure 10H,I). The DNIC spray application reduced the severity of exudation, inflammatory infiltration and microcirculatory disorders more effectively related to the other groups. The number of macrophages decreased, but they expressed iNOS $30\%$ more actively than in the saline control group ($p \leq 0.05$) (Figure 4P and Figure 7). The granulation tissue’s maturity was higher compared to Day 4, but the volume did not change significantly (Figure 8, Figure 10J and Figure A4). The area of α-SMA-positive cells was higher by $43\%$ than in the saline control group ($p \leq 0.05$) (Figure 5O,P and Figure 9). Vimentin-positive cells (fibroblasts) with intensive NF-κβ cytoplasmic expression were orientated in parallel to the wound surface and actively produced collagen fibers, which was detected by picro-Mallory staining (Figure 4O, Figure 6O,P and Figure 10K). Under polarized light microscopy, thin, newly-formed collagen appeared green and yellow in color (Figure 10L). On Day 14, in the air control group, the fibrin clot covered the wound’s center, while epithelialization was detected only along the edges. Mature granulation tissue comprised thick collagen fibers (dark blue by picro-Mallory), numerous α-SMA-positive cells (myofibroblasts), singular blood vessels and spindle-shaped fibroblasts in the deep layers of the wound (Figure 12A,B, Figure 13A,B and Figure A5). In this group, vimentin-positive cells occupied the maximum area (Figure 11 and Figure 14A,B). The cells were located in parallel and close to each other. The collagen had low maturity and anisotropy in polarized light microscopy (Figure 12C). A highly differentiated epithelium completely covered the wound’s surface in three out of six animals from the NO-CGF group. Scar tissue was observed along the wound’s periphery (Figure 12D and Figure A6). The area of α-SMA-positive cells in wound centers was evidently larger than in the saline control group ($p \leq 0.01$) (Figure 9 and Figure 13E,F). We revealed a high content of collagen fibers; they were stained dark blue by picro-Mallory and had a red color in polarized light microscopy (Figure 12E,F). The number of fibroblasts decreased in the granulation tissue as it matured. Thus, the cells encompassed a smaller area than on Day 7, despite intensive vimentin expression (Figure 6 and Figure 14E,F). In the saline control group, the wound centers were covered with a dense fibrin clot, and immune cell infiltration and microcirculatory disorders were observed in two out of six animals. The granulation tissue volume and maturity were minimal: the wound contained few α-SMA and vimentin-positive spindle-shaped cells (Figure 12G, Figure 13I,J and Figure 14I,J). Picro-Mallory staining demonstrated a relatively low content of collagen fibers (Figure 12H). They were birefringent and characterized by pale green and yellow color (Figure 12I). The wound surfaces were completely epithelized in two out of six animals from the DNIC group. The granulation tissue was less mature than in the NO-CGF group (Figure 12J). It comprised vimentin-positive fibroblasts synthesizing collagen fibers parallel to the wound and capillaries with perpendicular orientation to the wound surface (Figure 12K and Figure 14M,N). The α-SMA expression index was higher than in the saline control group ($p \leq 0.05$) (Figure 9 and Figure 13M,N). Polarized light microscopy revealed red-stained fibers along the periphery along with yellow and green fibers in the wound center, which indicated collagen maturation (Figure 12L). On Day 21, in control group 1 (air), the epithelium covered only the wound’s edges. The wound’s bottom tissues were characterized by high cellularity (inflammatory infiltration, α-SMA and vimentin-positive cells) and collagen fiber content, clearly visible in picro-Mallory staining (Figure 13C,D, Figure 14C,D, Figure 15A,B and Figure A7). They appeared bright and red–yellow under polarized light (Figure 15C). In the NO-CGF group, five out of six experimental animals had completely epithelized wound bottoms. The wound centers looked like mature granulation tissue with singular capillaries, vimentin-positive fibroblasts and thick collagen fibers with weak anisotropy (Figure 14G,H, Figure 15D–F and Figure A8). The area of α-SMA-positive cells was $19\%$ smaller than in the air control group ($p \leq 0.05$) (Figure 9 and Figure 13G,H). No wounds that were treated with saline healed completely. Immune cell infiltration and numerous vimentin-positive fibroblasts were observed in the majority of rats (Figure 14K,L and Figure 15G). The α-SMA expression index was $31\%$ higher than in the DNIC group ($p \leq 0.05$) (Figure 9 and Figure 13K,L). Picro-Mallory staining revealed few collagen fibers, which had a weak birefringence in red color when studied by polarized light microscopy (Figure 15H,I). The other animals had less pronounced inflammatory findings and more mature granulation tissue with aligned collagen fibers. In the DNIC group, the wound bottoms were epithelized. The collagen fibers and skin appendages regenerated, and the number of vimentin-positive cells decreased relative to Day 14 (Figure 14O,P and Figure 15J). The area of α-SMA-positive cells was $29.5\%$ smaller compared to the air control group ($p \leq 0.05$) (Figure 9 and Figure 13O,P). Picro-Mallory staining revealed thick bundles of intertwined fibers (Figure 15K). Polarized light microscopy revealed strongly birefringent red collagen in the wound’s periphery dermis (Figure 15L). The dynamic histological study revealed the maximum intensity of inflammation in the saline control group. NO-CGF application decreased inflammation and facilitated regeneration (fibroblast proliferation, angiogenesis, granulation tissue volume and maturity) during the wound healing period starting at the seventh day after surgery. The DNIC spray had little effect on inflammation but effectively increased the granulation tissue maturation at day 4 after surgery. ## 2.3. Transmission Electron Microscopy On Day 3 in the control groups, the inflammatory infiltrates mainly contained neutrophils with segmented nuclei, a dense cytoplasm and phagosomes (Figure 16A,B). In addition, we determined many macrophages with scalloped nuclei, numerous dense cytoplasmic granules (lysosomes) and long outgrowths of the plasma membrane (Figure 16B). Collagen fibers (apparently pre-existing operations) represented the extracellular matrix. Some of them did not have a specific cross-striation, which indicated their destruction. Young oval-shaped fibroblasts with a large nucleus with weakly condensed chromatin, Golgi apparatus, a poorly developed endoplasmic reticulum (ER) and a few free ribosomes predominated in the experimental groups (Figure 16A). In the experimental groups, macrophages predominated in the inflammatory infiltrate. The number of young and maturating (with developed granular ER) fibroblasts significantly increased (Figure 16C,D). Intermediate substances (glycosaminoglycans) represented the extracellular matrix; collagen production was absent. On Day 7, the number of fibroblasts increased in all groups. In the control groups, they had a less developed granular ER (low synthetic activity) and *Golgi apparatus* than in the experimental ones (Figure 17A–D). The extracellular matrix was comprised predominantly of fibrin and proteoglycan fibers, whereas, in the experimental groups, it contained collagen fiber bundles. In experimental group 2 (DNIC), we revealed numerous newly formed capillaries. By Day 14, in the control groups (air, saline), there were fewer fibroblasts than in the experimental ones. The cells had a light cytoplasm, few organelles and a poorly developed endoplasmic reticulum, which suggests their immaturity. The extracellular matrix consisted of singular collagen fibers among intermediate substances (Figure 18A,B). In experimental groups (NO-CGF, DNIC), fibroblasts were orientated along dense bundles of collagen fibers (Figure 18C). The cells had large mitochondria. Dilated cisterns of granular ER were surrounded by ribosomes and polysomes, which indicates their high synthetic activity (Figure 18C,D). The current histological study proved that NO-therapy effectively stimulates regeneration by activating fibroblast and myofibroblast proliferation, the growth and maturation of granulation tissue acceleration and NF-κß pathway modulation in the early stages of wound healing. However, NO-CGF had more prolonged effects on wound contraction and epithelialization and the decrease in inflammation than the DNIC spray. ## 3. Discussion The Nobel Prize in Medicine and Physiology for NO molecule discovery (Furchgott R.F., Ignarro L.J., Murad F.) in 1998 initiated the bulk of studies investigating the properties and biological effects of NO and its compounds. Around the world, many researchers began to develop NO donors and methods for NO delivery [11,14,15,18,20]. The NO-therapy’s popularity is associated with the versatility of NO regulatory functions in normal conditions and pathology. This unique molecule penetrates through skin, cornea, mucous membranes and wound surfaces [3,6]. In the early stages of wound healing, NO reacts with superoxide and forms peroxynitrite. Its degradation products decrease the wound’s pH and enhance inflammation and bactericidal effects [4]. These effects are associated with multiple molecular pathways activations, in particular, NF-κβ. Nitric oxide and reactive nitrogen species can modify NF-κß activity in different ways [24]. In an inactive form, NF-κβ is located in the cytoplasm. When introduced to peroxynitrite, ultraviolet radiation, active radicals and other factors, it activates and translocates into the cell nucleus, stimulating activation of physiological and pathological processes, including the synthesis of pro-inflammatory cytokines, cell proliferation, apoptosis and the S-phase of the cell cycle, which is important for wound healing [25,26]. The NO molecule inhibits NF-κB activation by neutralization of pro-oxidative molecules and decreases the peroxynitrite formation at the end of the inflammatory phase of wound healing [27]. We calculated the NF-κβ activity as the ratio of the nuclear expression index to the cytoplasmic index. Our study demonstrated the activation of this protein in the macrophages of wounds treated with NO-therapy on the first week of wound healing. In these groups, the intensity of inflammation was significantly lower than in the control. This can be explained by NF-κβ stimulation of leukocyte phagocytic function [28]. The activation of this protein in wound fibroblasts can promote their proliferation as an NF-κß signaling pathway [26]. NF-κß dimer activation directly induces iNOS formation, a pro-inflammatory enzyme that is involved in the synthesis of endogenous NO in the wound in response to injury [29]. iNOS inhibition significantly reduces collagen synthesis, thus, NO-therapy can compensate for this effect [28]. As the concentration of NO increases, the modulation of NF-κß stops, the production of pro-inflammatory cytokines decreases and the antioxidant system is activated [26]. However, we did not observe the strong correlation between NF--κß and iNOS levels. This can be related to other signal molecules contributing to this enzyme expression, for instance, signal transducers and activators of transcription 3 (STAT3) and activator protein-1 (AP-1) [30,31]. The products of NO oxidation include an excess of nitrite anions, activated NO metabolism and synthesis of its endogenous donor, DNIC, in low pH conditions [2,32]. We identified significant differences in macrophage iNOS expression between groups in which wounds were treated with DNIC and saline on Day 7 after surgery. This observation did not correlate with the intensity of inflammation in these groups. Previously, it was considered that iNOS was one of the main enzymes involved in active radical formation and negatively affected cell survival. Later studies revealed that, besides irreversible damage to cell organelles, proteins and DNA, its low or moderate concentrations activate intracellular signaling pathways, stimulating the production of factors important for cell growth and proliferation [3]. An increase in iNOS expression in the macrophages impacts the inflammatory reaction through suppression of bacterial contamination and elimination of necrotic tissue at the early stages of wound healing [26]. An increase in the iNOS expression index in fibroblasts by Day 7 is important for the stimulation of collagen production in the healing wound. In our study, we observed a significant intensification of fibroblast proliferation and vascularization in the groups with NO-therapy. According to the literature data, NO stimulates angiogenesis through cGMP-dependent cascade activation and regulates the fibroblast’s synthetic activity, even in low tissue concentrations [33,34]. Vimentin is one of the main fibroblast markers which is used to evaluate connective tissue growth. Persistence of vimentin-positive cells at the late period of wound healing is associated with scar formation [35]. Our results demonstrated that NO-therapy increased vimentin expression and fibroblast proliferation, accelerating the proliferation phase of wound healing during the first week after injury. On Day 4, most intensive morphological findings of regeneration were observed in the DNIC group. On Day 7 after injury, the maximum number of vimentin-positive cells was observed in wounds treated with NO-CGF. These results indicate that both NO delivery approaches have strong pro-regenerative effects on fibroblasts. NO-therapy contributed to a decrease in the area with vimentin-positive cells, starting from the 14th day after surgery. By Day 21, the number of vimentin-positive cells in the experimental groups decreased faster than in the controls. It is possible that NO facilitates scar reduction, which is beneficial for the outcome of wound healing. α-SMA is a marker of myofibroblasts, the cells which are important for wound contraction in the early stages of wound healing [36]. We detected a significant decrease in wound areas in the experimental groups on Day 7. In the later stages of wound healing, the number of myofibroblasts reduced because of apoptosis. It prevented excessive contraction of the wound edges and scarring [35,36]. NO-therapy-stimulated epithelialization of the wound defect and its healing without excessive contraction with a linear scar were achieved by Day 21. In the present study, we proved that DNIC spray and NO-CGF application accelerated the reduction in wound areas in the early stages of wound healing (7 days) by stimulating myofibroblasts’ differentiation and the prevention of scar tissue remodeling at a later stage (21 days) because of a decrease in the number and activity of these cells (Figure 19). A complex comparative study of skin wound healing effects of optimal doses of DNIC spray and NO-CGF did not reveal a significant difference in their impact on the molecular mechanisms of regeneration, judging by the expressions of NF-kB, iNOS, α-SMA and vimentin in wound tissues. We proved that the application of DNIC spray and NO-CGF at their optimal doses (0.02 and 1 mmol, respectively) accelerated the reduction in wound areas at the early stages of wound healing (7 days) by stimulating myofibroblast transdifferentiation and prevented scar tissue formation at a later stage (21 days) by decreasing the number and activity of these cells. This result allows us to conclude, definitively, that DNIC spray is more dosage effective as a pro-healing agent than NO-CGF considering differences in their molar doses. The question then arises: what is the reason for this higher wound healing activity of DNIC spray? In other words, why does the incorporation of NO molecules into DNIC followed by their release from these complexes significantly improve their healing effect on wounds compared to NO molecules existing initially in the gas phase? On the one hand, this composition protects molecular NO from various negative factors (for example, from the harmful effect of superoxide anions), and, on the other hand, does not impede its release from B-DNIC-GSH, which is necessary for the wound healing action of NO. The results of previous studies of B-DNIC-GSH and similar complexes with other thiol-containing ligands support this statement. First, the duration of the existence of DNIC with thiol-containing ligands in a solution, varying from several hours to several days depending on the nature of these ligands, is an indicator that the incorporation of NO into these complexes transforms it from a volatile gaseous agent into non-volatile water-soluble complexes [12]. As a result, when NO is introduced into the wound as part of DNIC, it escapes only after the disintegration of these complexes. When NO is delivered to the wound in gaseous form, a significant part of this agent can quickly evaporate from it without having a wound healing effect. Secondly, the experiments with protein-bound DNICs showed that the reaction constant of the free radical reaction between NO molecular ligands in these complexes and superoxide anions is three orders of magnitude lower than the similar reaction constant between these anions and NO in the gaseous phase [37]. If, however, we take into account that, upon entering animal tissues, low-molecular-weight M- and B-DNICs are almost completely (as a result of the transfer of iron-dinitrosyl fragments from these complexes to the thiol groups of proteins) converted into protein-bound DNICs, then the phenomenon of NO protection from the destructive effect of superoxide anions on it becomes crucial [12]. Thirdly, free NO molecules can bind to the heme groups of various proteins, concentrate in the lipid compartments of cells and tissues and, finally, be oxidized by oxygen and other oxidizing agents. Such behavior of NO molecules should obviously be largely prevented by the incorporation of NO into such very stable complexes as DNICs associated with thiol groups of proteins—protein-bound DNICs. The subsequent transfer of NO from the complexes to the target of its biological action—the heme-containing protein guanylate cyclase (a key regulator of wound healing)—is carried out by low-molecular-weight DNICs that intercept the iron–dinitrosyl group from the protein-bound DNICs with subsequent transfer of NO to the heme group of guanylate cyclase. It is clear that this transfer is determined, primarily, by the high affinity of this group for NO compared to the iron atom in DNIC and, secondly, by the selective binding of DNIC to the guanylate cyclase apo protein. ## 4.1. NO-Containing Gas Flow We used the Plason device serial number 450, manufactured by Center BMSTU, LLC (Moscow, Russia). It was equipped with a standard manipulator with an outlet channel diameter of 1.4 mm. The distance to the wound surface was 120 mm. The NO-containing gas flow had the following axial parameters: temperature—50 °C, velocity—5 m/s, NO concentration—500 ppm, NO2 concentration—30 ppm, NO consumption—1.7 mg/s and mass flow rate of NO2—0.15 mg/s. The average NO consumption density during the 120 s long wound treatments was ~0.25 mg/(s∙cm2); the mass dose of NO supplied to the wound was 90 mg [8,20]. ## 4.2. DNIC Containing Spray DNIC with glutathione was obtained according to the procedure described by Borodulin and Vanin [38]. Solutions with a concentration of 50 mg/L were prepared by dissolving lyophilized DNIC-glutathione powder in sterile PBS at 25 °C. The spraying dosage of DNIC was 16.6 mg of the active substance per 1 cm2. Then, they were aliquoted into 4 plastic spray bottles of 50 mL (BX202005C, Ningbo Beixuan International Trading Co., Ltd., Ningbo, China) and frozen at −70 °C until application. The sprayability, stability of the spray and dosage were tested as described in our previous report [19]. ## 4.3. Animal Studies The experiment on 96 Wistar rats (males, 180–220 g) was approved by the Local Ethical Committee of Sechenov University (Protocol 15-$\frac{19}{25}$ November 2019). The animals were kept under the standard vivarium conditions of one animal per cage and were provided with complex granulated laboratory chow and constant access to water. Full-thickness skin wounds were modeled in 96 Wistar rats. For anesthesia, a $25\%$ urethane solution (Sigma, St. Louis, MI, USA) intraperitoneal injection was used at the dose of 80 mg of active ingredient per 100 g of animal weight. In the interscapular space, a circle with a diameter of 8–10 mm was excised to the fascia propria. We used Teflon rings with an inner diameter of 195 mm for the first 4 days after surgery. They prevented early wound contraction, which is usually more rapid than epithelialization in rats [39]. Moreover, the Teflon rings proved to be useful because of the elasticity of rat skin and its adhesion to the propria fascia. Furthermore, this ring was useful for treatment dosage control. It was covered with a perforated plastic wrap to prevent drying, external contamination and early wound contraction. All the wounds had a standard area of 3 cm2. On postoperative days 1, 2 and 3, the animals were injected with ZOLETIL 100 (Virbac France, Carros, France) at a dose of 300 µg of the active ingredient per 100 g of the animal’s body weight for sedation. Then, the protective film was removed from the ring, and the wounds were assessed for signs of inflammation: edema, hyperemia, exudation and infiltration of the surrounding tissues. After that, the wounds were treated with atmospheric air ($$n = 24$$, air control group), NO-CGF ($$n = 24$$, NO-CGF group), sterile $0.9\%$ Saline Solution ($$n = 24$$, saline control group) or DNIC spray ($$n = 24$$, DNIC group) (Figure 20). Six animals from every study group were sacrificed on days 4, 7, 14 and 21 after the operation, and the wound tissues were excised for histological analysis. Small pieces of central parts of the samples were excised for transmission electron microscopy on days 4, 7 and 14. ## 4.4. Wound Area Measurement At 7, 14 and 21 days of the experiment, the contours of the wounds were outlined with a permanent marker on polyethylene film. Then, the figures were visualized and measured in micrometers using the Leica Application Suite, version 4.9.0 (Wetzlar, Germany). The values were recalculated in cm2 using a ruler scale bar. ## 4.5. Histological Study The animals were sacrificed on days 4, 7, 14 and 21 after the operation, and the wound tissues were excised for histological analysis. Then, 4 μm-thick sections of the formalin-fixed, paraffin-embedded tissue samples were stained with hematoxylin and eosin (H & E) (BioVitrum, St. Petersburg, Russia), picrosirius red (BioVitrum, St. Petersburg, Russia), toluidine blue (BioVitrum, St. Petersburg, Russia) and by picro-Mallory (BioVitrum, St. Petersburg, Russia). A LEICA DM4000 B LED microscope equipped with a LEICA DFC7000 T digital camera running under the LAS V4.8 software (Leica Microsystems, Wetzlar, Germany) was used for the examination of the samples. Sections stained with picrosirius red were examined by polarized light microscopy. The panels were composed of microphotographs of central parts of the wounds for standardized assessment of wound healing. ## 4.6. Morphometrical Analysis To evaluate morphological findings of inflammation (exudation, contamination, immune cell infiltration, microcirculatory disorders) and regeneration (angiogenesis, fibroblast proliferation, volume and maturity of granulation tissue), we used a 0 to 4 score system (0—absence of the findings, 4—maximum intensity of the findings). The granulation tissue layer thickness was measured perpendicular to the epithelial layer in each sample at 5 random sites located at least 400 μm apart from each other. The measurements were made using the Leica Application Suite, version 4.9.0 (Leica Microsystems, Wetzlar, Germany). ## 4.7. Immunohistochemical Study Sections, 4 μm thick, of the formalin-fixed, paraffin-embedded tissue samples were deparaffinized, underwent heat-induced epitope retrieval ($5\%$ Trilogy 20× solution (Cell Marque, Rocklin, CA, USA), 30 min in 80 °C water bath), incubation in $3\%$ H2O2 for 15 min and block with Background Block (Cell Marque, Rocklin, CA, USA). Vimentin (ab92547, Abcam, Cambridge, UK, diluted 1:400) was chosen as a marker of fibroblasts, and α-SMA (ab5694, Abcam, Cambridge, UK, diluted 1:400) was chosen as a marker of myofibroblasts. We also studied the expressions of the NF-kß (ab16502, Abcam, Cambridge, UK, diluted 1:200) and iNOS (PA1-036, Invitrogen, Waltham, MA, USA, diluted 1:200), the enzyme involved in the synthesis of NO in the wound. After overnight incubation, HRP-conjugated secondary goat antibodies (G-21040, Invitrogen, Waltham, MA, USA, diluted 1:1000) and diaminobenzidine (DAB, 34002, Thermo Fisher Scientific, Waltham, MA, USA) were applied. Slides were counterstained with hematoxylin (Biovitrum, St. Petersburg, Russia). For evaluation of IHC markers’ expression in the wounds, five different fields of view of each section were photographed at ×400 magnification and examined by two blinded pathologists using the formula: Expression Index (E) = (Positive Cells/Total Cells) × Label Intensity. The Label Intensity was determined by a pattern of IHC reaction on the microphotograph, where “0”—no reaction, “1”—weakly positive staining of singular cells, “2”—positive staining of less than $50\%$ of cells and “3”—positive staining of more than $50\%$ of cells. We evaluated the expression of iNOS and NF-kß separately in fibroblasts (spindle shaped cells with centrally placed oval nucleus) and macrophages (characterized by round shape and large elongated nucleus). Since the role of NF-kß depends on the subcellular localization, the activity of this marker (A) was calculated using the formula: A = E1/E2, where E1 is the expression index in the nucleus and E2 is the expression index in the cytoplasm. ## 4.8. Transmission Electron Microscopy The samples were fixed in $4\%$ glutaraldehyde (Pan Real, Spain) in 0.1 M phosphate buffer, pH 7.2–7.4 (Amresco, Boise, ID, USA; pH 7.2–7.4) at 4 °C for a day and postfixed in $1\%$ OsO4 for 2 h. They were washed with a buffer solution, dehydrated in a graded series of ethanol-water washes and $2\%$ uranyl acetate for a night and embedded in Epon (Epon 812, Fluka, Buchs, Germany). Cross-sections from central areas of the wounds were 1 μm in thickness. They were prepared on pyromitom for spatial orientation of the material and stained with $1\%$ methylene blue (Biovitrum, St. Petersburg, Russia). Ultrathin cross-sections were poststained with $2\%$ uranyl acetate (541-09-3, VWR International, Radnor, PA, USA) and alkaline lead citrate (Reynolds, 1963) and observed in a JEOL JEM-1011 transmission electron microscope (JEOL, Tokyo, Japan) at magnifications of 8000×, 15,000×, and 25,000×. ## 4.9. Statistical Analysis Statistical analysis of the data was performed with the standard software package of GraphPad Prism, version 8.00 for Windows (GraphPad Software, Inc., San Diego, CA, USA). The distribution of the quantitative data was checked by Shapiro–Wilk’s normality test. The intergroup differences were analyzed using the two-way ANOVA followed by Tukey’s multiple comparison test. The differences in the histological scores were evaluated by a Kruskal–Wallis test followed by Dunn’s multiple comparison test. The statistical analysis results were presented as interleaved bar graphs of the mean values (for quantitative data) and standard deviations of the mean (SD) or median values (for collagen maturity, inflammation and regeneration indexes) and $95\%$ confidence interval; p-values ≤ of 0.05 were considered statistically significant. ## 5. Conclusions Our research demonstrated that both methods of NO delivery accelerated wound healing by having an impact on the same mechanisms of regeneration. NO-therapy reduced inflammation and promoted fibroblast proliferation, growth of granulation tissue and wound epithelization. DNIC spray application was particularly effective in stimulating the early wound healing process during the first 4 days after trauma. Further intensity of wound healing differed slightly. It should be taken into account that the content of the effective dose of NO in NO-CGF is 25 times higher than in DNIC. ## References 1. 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--- title: 'Alterations in Cervical Nerve Root Function during Different Sitting Positions in Adults with and without Forward Head Posture: A Cross-Sectional Study' authors: - Maryam Kamel - Ibrahim M. Moustafa - Meeyoung Kim - Paul A. Oakley - Deed E. Harrison journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003310 doi: 10.3390/jcm12051780 license: CC BY 4.0 --- # Alterations in Cervical Nerve Root Function during Different Sitting Positions in Adults with and without Forward Head Posture: A Cross-Sectional Study ## Abstract The current study aimed to determine whether participants with and without forward head posture (FHP) would respond differently in cervical nerve root function to various sitting positions. We measured peak-to-peak dermatomal somatosensory-evoked potentials (DSSEPs) in 30 participants with FHP and in 30 participants matched for age, sex, and body mass index (BMI) with normal head posture (NHP), defined as having a craniovertebral angle (CVA) >55°. Additional inclusion criteria for recruitment were individuals between the ages of 18 and 28 who were in good health and had no musculoskeletal pain. All 60 participants underwent C6, C7, and C8 DSSEPs evaluation. The measurements were taken in three positions: erect sitting, slouched sitting, and supine. We identified statistically significant differences in the cervical nerve root function in all postures between the NHP and FHP groups ($p \leq 0.001$), indicating that the FHP and NHP reacted differently in different positions. No significant differences between groups for the DSSEPs were identified for the supine position ($p \leq 0.05$), in contrast to the erect and slouched sitting positions, which showed a significant difference in nerve root function between the NHP and FHP ($p \leq 0.001$). The NHP group results were consistent with the prior literature and had the greatest DSSEP peaks when in the upright position. However, the participants in the FHP group demonstrated the largest peak-to-peak amplitude of DSSEPs while in the slouched position as opposed to an erect position. The optimal sitting posture for cervical nerve root function may be dependent upon the underlying CVA of a person, however, further research is needed to corroborate these findings. ## 1. Introduction Sustained sitting postures and the related load on the cervical spine are important contributors to the high prevalence of neck pain [1]. Prolonged hours of sitting have shown a large incidence of pain in the head, neck, and shoulder region [2,3,4,5]. The optimum sitting position is generally accepted to be a maintained and erect upright spinal position [6]. As described by physiotherapists, an optimal sitting posture is the position with the least amount of muscle activation and the most relaxed and comfortable posture for the entire spine [7,8]. Presumptuously, any deviations away from this erect sitting posture is causative of pain and discomfort [9]. One issue regarding these mechanical ideologies, and popular clinical assumptions supporting the erect sitting posture, is that there is no evidence-based agreement on the optimal sitting posture, especially regarding the neck region [9,10,11,12]. Several studies support the erect sitting as an optimal posture for the head and neck region as mechanically, a more upright sitting posture reduces forward head translation and cervical flexion positions [11,13]. Reducing forward head posture (FHP) and cervical flexion posture by changes in sitting position modification has a direct influence on neck flexor and extensor muscles [14,15]. An issue that is not typically addressed when assessing sitting posture is the presence of pre-existing spinal misalignment or poor postures. FHP is a common poor posture that is associated with a greater load transmitted to the neck [16,17], greater muscle activation and fatigue [18], lower endurance of the deep neck extensors and flexors [19], as well as substantial effects on the biomechanics of the nervous system by causing unfavorable mechanical strain [20,21], which causes the blood vessels to constrict [22] and the nerve root sleeves to unfold and become taut, predisposing individuals to altered or inefficient neurophysiological symptoms [23,24]. Accordingly, we believe the combined effects of sitting with a pre-existing FHP may likely exacerbate any overstraining of the spine and soft tissues, including any neurophysiological effects. Those with FHP have been demonstrated to exhibit abnormal sensorimotor control as well as autonomic nervous system dysfunction as compared to persons without FHP [23]. It has also been shown that the therapeutic correction of FHP and cervical lordosis aids in the improvement of sensorimotor control [24]. It is unknown, however, whether immediate changes in sitting posture have the potential to create alterations in neurophysiologic parameters and how these may differ between persons with and without pre-existing FHP. Consequently, the current study aimed to determine whether participants with and without FHP would respond differently in terms of dermatomal somatosensory-evoked potentials (DSSEPs) to variations in sitting positions versus a supine posture. In terms of neurophysiological outcomes, dermatomal somatosensory-evoked potentials (DSSEPs) are methods for recording cerebral-evoked reactions to the stimulation of specific regions innervated by single nerve roots, with the goal of supplying pure sensory input to the central nervous system through individual spinal segments to provide reliable information about segmental nerve root function [25]. ## 2. Methods Sixty [60] healthy participants voluntarily agreed to participate in this cross-sectional study. These two groups were parallel matched in age, body mass index (BMI), and sex. Ethics approval was obtained from University of Sharjah Research Ethics Committee in April 2021 REC-19-10-31-02-S. Following Ethics Committee approval, participant recruitment was from April 2021 to August 2022. Informed consent was obtained from all participants prior to the experiment according to relevant guidelines and regulations. Participants in the NHP group were allocated as closely as possible to match those in the FHP group. Their age was accepted if it was within 2 years apart, the BMI was likewise matched if their BMI varied within 1–2 points. All participants were screened prior to enrollment into the study. The exclusion criteria were as follows: any inflammatory joint disease, systemic pathologies, previous history of musculoskeletal injuries or surgery, spinal disorders, extremity pathologies, or musculoskeletal pain 3 months prior to the study. Exclusion criteria information was obtained through each participant’s medical records. Exclusions were further made of participants during the analysis of the peripheral nerve folly (N9), as detailed below in the neurophysiological assessment section. Participants with an abnormal N9 were excluded. DSSEP peaks follow a normal known structure, and any abnormalities appear clearly. The N9 DSSEP peak represents the afferent signals coming from the brachial plexus. Therefore, any participants with an abnormal N9 were excluded, to remove any possibility of unrelated peripheral factors. The study inclusion criteria for recruitment were any individual between the ages of 18 and 28 who was in good health and had no musculoskeletal pain. The specific allocation of participants to either the FHP or the NHP group was determined by the photogrammetric craniovertebral angle (CVA) of each person [26]. Participants having a CVA below 50° were assigned to the FHP group while participants having a CVA greater than 55° (considered as the cut-off for non-FHP) were assigned to the normal head posture (NHP) group. The CVA measurement method is shown in Figure 1. ## 2.1.1. Evaluation of CVA The CVA has a high inter-rater and intra-rater reliability in the assessment of FHP [27]. CVA is defined by the angle measured between the horizontal line bisecting the spinous process of C7 and the diagonal line going from the C7 spinous process to the tragus of the ear. As mentioned, we considered a CVA less than 50° to be the threshold for our FHP as this is related to an increased FHP, and FHP is related to increased disability [27]. We followed the published protocol of Falla et al. for the CVA assessment [28]: neutral lateral photos of every participant were taken. Each participant was instructed to sit up in a neutral and comfortable position on a chair and look forward. The photograph was then assessed for the CVA. A digital single-lens reflex camera was placed on a tripod 0.8 m away from the participant. The camera was perpendicular to the sagittal plane of the individuals’ seated position at a height that corresponded with the seventh cervical vertebra of each seated participant. Florescent adhesive markers were used to identify the tragus and the C7 spinous process for the photos. All participants assumed and were assessed in the following three positions for the experiment. ## 2.1.2. Positions All 60 participants in their respective group underwent C6, C7 and C8 dermatomal somatosensory-evoked potentials (DSSEPs). For each of the cervical nerves (C6, C7 and C8), measurements were taken in three positions for each participant:Supine position (which acted as a reference for DSSEPs measurement);After assuming the erect sitting posture for 30 min;After assuming the slouched sitting posture for 30 min. ## Erect Sitting Position As shown in Figure 2, the participants sat on a chair supporting their back. Their hips and knees were positioned at a 90° angle, where the base of support was perpendicular to the chair. The arms were rested on the armrest and the spine was assumed in a ‘neutral upright position’ (i.e., neutral kyphosis and lordosis angles); therefore, achieving a slight anterior rotation of the pelvis. Participants were instructed to look forward at a stationary point straight ahead of them. ## Slouched Sitting Position Participants sat on the same chair with their back supported and were instructed to relax their thoracolumbar spine to produce a hyperkyphotic angle at the thorax and a straightened lordotic curve at the lumbar region, as shown in Figure 2. This causes a posterior tilt of the pelvis, hyper-kyphosis of the thoracic spine, and a pronounced forward head posture. ## Supine Position Participants were instructed to lay back on a flat plinth with the arms in an extended anatomical position. The hip angle was at 180 degrees [29]. The head was supported by a pillow to prevent interference or movement of the electrode placements [30]. ## DSSEPs Neurophysiological findings for C6, C7, and C8 were measured in this study as the peak-to-peak amplitude of DSSEPs. An electromyography device (Neuropack S1 MEB-9400K, Nihon Koden, Tokyo, Japan) was used for these neurophysiological assessments. DSSEPs were stimulated with a continuous electrical pulse wave (0.5 ms) at 3 Hz, delivered by three standard surface gel electrodes (20 mm) placed over the respective cervical dermatome; a reference electrode, a recording electrode, and a grounding electrode were used. The stimulation intensity used was above each participant’s perception threshold. All participants initially assumed a relaxed supine position where they were instructed to lay quietly and with eyes closed during the procedure. After parting the hair and using alcohol to prepare the skin, Nuprep gel and Ag–AgCl disc recording electrodes (10 mm with 60 inch lead wires) were fixed with Elefix paste to the scalp (Nihon Kohden, Tokyo, Japan) (Figure 3 shows the electrode placement). The grounding electrode was attached to a strap, which was secured around the forearm. The impedance of all three electrodes was kept below 5 kΩ for an even reading. Three recordings were done for each of the dermatomes stimulated (C6, C7, and C8). The stimulation points were radial forearm 1 inch above the wrist, the middle of the palm right below the middle finger, and the ulnar side of the palm, respectively. ## 2.3.1. Sample Size Estimates of mean and standard deviations (SD) from a pilot study of 10 individuals who received the same program were collected to determine the required number of participants in this study. The mean differences and SD of the peak-to-peak amplitude of DSSEPs for different levels C6, 7, and 8 for the different sitting postures: supine, erect and slouched, were: C6: −0.1 (SD 0.3), −0.17 (SD 01.2), −0.86 (SD 0.6); C7: −0.07 (SD 0.9), −0.6 (SD 0.9), −1.6 (SD 1.00); and C8: −0.1 (SD 0.4), −0.9 (SD 0.8), −1.6 (SD 0.9), respectively. The sample size was calculated independently for each of the key outcomes using a Bonferroni correction to adjust the significance level. The greatest sample size value was then used as the trial’s final sample size. Given a statistical power of $80\%$, the current investigation required at least 25 individuals in each group. To accommodate for probable dropouts, the sample size was increased by $20\%$. ## 2.3.2. Data Analysis Levene’s test of equality of error variances was used to determine the normality distribution of the dataset at $95\%$ confidence interval and p-value < 0.05. The dataset had a 2 × 3 factorial design. Descriptive statistics (mean ± SD) were summarized for each position and cervical nerve root. The unpaired t-test for continuous variables was used to compare the means and determine the significance of the interaction between the nerve roots in the different sitting positions. A two-way analysis of variance (ANOVA) was then used to test the relationships between the head posture (NHP vs. FHP) and sitting position (supine, slouched, and erect) on the cervical nerve roots (C6, C7, and C8). A p-value of 0.05 or less was considered a statistically significant difference in the dataset. Following that, the Tukey honestly significant difference (HSD) post hoc tests were used. SPSS version 29.0 software was used for analyzing data (SPSS Inc., Chicago, IL, USA). ## 3. Results Ninety-five potential participants were initially screened. Thirty participants with FHP and thirty age-, BMI-, and sex-matched controls without FHP were recruited for the NHP group. Figure 4 shows the participant flow chart with numbers excluded and reasons why. Descriptive data for the baseline participant demographics are presented in Table 1. No statistically significant differences between the NHP and the FHP group were found at baseline for their demographic variables. Table 1 shows the mean and distribution of CVA for both groups. While the number of females in both groups was nearly double that of males, adding sex as a fixed variable to our statistical models in this study did not produce any difference in the outcome findings. A two-way analysis of variance (two-way ANOVA) identified significant head posture × sitting position effects on the outcome of peak-to-peak amplitudes of the cervical nerve roots C6, C7 and C8. Results showed a statistically significant interaction between the head posture and sitting position ($F = 32.867$) ($p \leq 0.001$), ($F = 38.926$) ($p \leq 0.001$), ($F = 40.348$) ($p \leq 0.001$) for C6, C7 and C8, respectively. Table 2, Table 3 and Table 4 presents these data. Following the prolonged sitting position of 30 min, the between-group statistical analysis was significantly different, showing a more favorable nerve root function in the slouched sitting position for the FHP group compared to the NHP group, while the erect sitting position demonstrated a significant favorability to the NHP group, as shown in Table 2. Figure 5 and Figure 6 show short latency DSSEPs for C6, C7 and C8 pre and post 30 min of sitting in a participant from the NHP group. The scatterplots in Figure 7, Figure 8 and Figure 9 show that for all three cervical nerve roots (C6, C7, C8), their amplitudes increased in the slouched position for the FHP group compared to the erect position. Contrarily, the NHP group displayed a higher amplitude in the erect position than the slouched position. Both groups showed similarity in the nerve root functions in the prolonged supine position. Simple main effects analysis showed that the head posture had a statistically significant effect on the cervical nerve root functions of C6 ($$p \leq 0.030$$), C7 ($$p \leq 0.025$$), and C8 ($p \leq 0.001$). As for the sitting posture, a statistical significance was also detected on the cervical nerve roots C6 ($p \leq 0.001$), C7 ($$p \leq 0.025$$), and C8 ($p \leq 0.001$). Analysis with Levene’s test of equality of error variances showed that the homogeneity of variances in our data can be assumed for C6 ($$p \leq 0.235$$), for C7 ($$p \leq 0.02$$), and for C8 ($$p \leq 0.068$$). ## 4. Discussion As we had initially hypothesized, the cervical nerve root DSSEPs were identified to have significant differences between each of the positions tested: erect sitting, slouched sitting, and lying supine. Interestingly, our intergroup results (NHP vs. FHP groups) showed a pattern contrary to popular belief. The NHP group displayed the greatest peaks for DSSEPs while in the erect sitting position, and this is generally consistent with the previous literature on ideal sitting posture; namely, that altered cervical posture has damaging effects. In contrast, the individuals in the FHP group had the greatest peak-to-peak amplitude of DSSEPs while in the slouched position as opposed to the erect position. While the erect position is deemed the most correct and healthy position for the spine, our results show otherwise relative to the initial posture of the participant. Thus, our findings indicate the importance of considering the initial presenting cervical sagittal alignment of the individual as a significant factor when determining the ideal sitting posture. To our knowledge, this is the first research investigation that considers the cervical sagittal alignment as a contributing factor when assessing different sitting postures. These findings give new insights into an essential consensus of sitting that seem to suggest the uniqueness of the individual’s alignment. In other words, what works well for one person may create discomfort for another. Our main findings are in agreement with that of Dunk et al. who reported that individuals may respond differently to various sitting postures and the variables that influence sitting posture are still not fully understood [31]. Similarly, Adams suggested that sustained postures, including the erect posture if maintained for a prolonged period, can lead to discomfort and even injury [32]. One of the most important findings in this study was that for participants who already had FHP, adopting the erect sitting position negatively affected their nerve root function, as manifested by significant reductions in the peak-to-peak amplitude of the DSSEPs for the nerve roots tested. Some authors have noted that an erect sitting posture [14,15] may lead to increased levels of fatigue resulting from increased muscle activation compared with the habitual sitting posture of an individual. In contrast, Nishikawa et al. [ 18] identified that FHP compared to NHP was associated with a greater cervical spine muscle activity and subjective fatigue using high density surface EMG. These seemingly contradictory findings are challenging to explain and likely involve complex interactions between an individual’s perception of their natural posture, specific spine geometric alignments of the sagittal plane curvatures, muscle length tension relationships, and yet-undetermined variables. It has been reported that FHP is associated with the weakening of isometric strength and endurance of the deep neck flexors [33]. The endurance of the deep neck flexor muscles directly affects the function of the cervical spine, and the strength of these muscles are important in maintaining the posture and stability of the neck [33,34,35]. Along with the shoulder girdle muscles, the deep neck flexors are crucial for the control and support of the neck, supporting the weight of the head against gravity and stabilizing the head [36]. Accordingly, it is expected that assuming the erect posture for people with FHP will induce more fatigue. Due to this, it is believed that FHP participants will be more comfortable if they adopt a slouched posture while relying on passive structures of the spine (ligaments and bone). During a slouched or slumped posture, it is proposed that this posture relies mainly on the passive (e.g., spinal ligaments) structures to maintain a resting sitting position. This results in a diminished requirement for muscle activity [37,38]. Related research has shown that muscle fatigue occurs when erect postures (such as upright sitting) are sustained for as little as 30 min, even if contractions are as low as $2\%$ to $5\%$ of the maximum voluntary contraction [39]. This offers a possible explanation as to why participants might prefer a slumped sitting posture—because it is perceived as less physically demanding [37,38]. Still, it is necessary to note that the decline in stabilizing potential of the paraspinal muscles, the associated compensatory antagonistic coactivation, and the related increase in spinal load are associated with muscle fatigue. As documented in many studies, fatigue-related changes in muscle stiffness may reduce the capacity of the paraspinal muscles to stabilize the spine. If fatigue is not severe (as expected in our study), then the compensatory recruitment of antagonistic co-contraction may restore stability, but this will contribute to increased spinal load and an associated risk of overload injury [40,41,42]. This aberrant spinal load caused by muscular fatigue might be a possible explanation for the decrease in the peak-to-peak amplitude of DSSEPs. A final explanation for the reduced amplitude of the DSSEPs being different in the NHP vs. FHP groups during different sitting positions could be the amount and distribution of the cervical lordotic curve in the participants. It is known that abnormal cervical sagittal alignment (kyphosis, s-curves, etc.) creates changes in loading on the vertebrae and soft tissues [43]. Gong et al. [ 33] reported that reduced and kyphotic cervical curves coupled with FHP reduced the endurance of the deep neck flexors. Since it is known that increased FHP causes flexion of the lower cervical spine and extension of the upper cervical spine [44], it could be that slumped sitting in already FHP individuals causes a more dramatic increase in the lower cervical spine due to the increased thoracic kyphosis that also occurs in this posture. The increased cervical lordosis in this specific ‘exaggerated’ postural position might reduce the net tension on the lower cervical spinal cord and nerve roots, leading to an increased amplitude of the DSSEPs [20,45]. Though speculative, this seems like a plausible explanation that needs to be confirmed in future investigations using spine imaging. ## Study Limitations and Suggestions for Future Research The following limitations should be considered when interpreting the current study’s findings. We only examined the lower cervical spine nerve roots C5, C6 and C7, without looking at other cervical levels. Additionally, participants in this study were young adults, and as result, the findings might not be applicable to other age groups. Given the limitations of the current study, future research is needed to analyze the other cervical nerve roots, to shed more light on the upper cervical region related to different sitting postures. Investigating the effects of different sitting postures in different age groups may also help researchers in understanding the function of age as a contributing factor. Lastly, we did not specifically investigate the smoking status of a participant as an independent variable herein. However, the fact that there were almost an equal number of smokers in the two groups eliminated the possibility that smoking could have an impact on the outcome measure as a confounding variable between our two groups, as was shown. Still, we suggest that future research should take smoking status into consideration. Finally, our investigation did not formally investigate the true ideal geometric sitting posture of the thoracic and thoraco-lumbar pelvic region, nor did it investigate mechanisms for attaining or improving altered posture positions in participants, as has been performed in previous investigations [46,47]. Future work could incorporate the key findings herein of how the CVA of an individual affects nerve root function in different sitting positions and how variations in ideal sitting postures and its training or re-training are affected. ## 5. Conclusions We identified statistically significant differences in the cervical nerve root function in all postures between the NHP and FHP groups ($p \leq 0.001$), indicating that the FHP and NHP reacted differently in different positions. For the supine reference position, we found no significant differences between the FHP and NHP groups for the DSSEPs of nerve roots C6–C8. In contrast, both the erect and slouched sitting positions were found to have significant differences in nerve root amplitudes between the NHP and FHP groups. Specifically, the NHP group was found to have the greatest peaks for nerve root DSSEPs while in the erect sitting position and this is generally consistent with the previous literature on ideal sitting posture; namely, that altered cervical posture has damaging effects in sitting posture. However, the participants in the FHP group demonstrated the largest peak-to-peak amplitude of DSSEPs for nerve roots C6–C8 while in the slouched position as opposed to an erect position. The ideal sitting posture and its influence on cervical nerve root function may be dependent upon the underlying initial forward head posture presentation of a person, however, further research is needed to corroborate these findings in patients with and without cervical spine disorders. ## References 1. 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--- title: Prediction of Postoperative Pulmonary Edema Risk Using Machine Learning authors: - Jong Ho Kim - Youngmi Kim - Kookhyun Yoo - Minguan Kim - Seong Sik Kang - Young-Suk Kwon - Jae Jun Lee journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003313 doi: 10.3390/jcm12051804 license: CC BY 4.0 --- # Prediction of Postoperative Pulmonary Edema Risk Using Machine Learning ## Abstract Postoperative pulmonary edema (PPE) is a well-known postoperative complication. We hypothesized that a machine learning model could predict PPE risk using pre- and intraoperative data, thereby improving postoperative management. This retrospective study analyzed the medical records of patients aged > 18 years who underwent surgery between January 2011 and November 2021 at five South Korean hospitals. Data from four hospitals ($$n = 221$$,908) were used as the training dataset, whereas data from the remaining hospital ($$n = 34$$,991) were used as the test dataset. The machine learning algorithms used were extreme gradient boosting, light-gradient boosting machine, multilayer perceptron, logistic regression, and balanced random forest (BRF). The prediction abilities of the machine learning models were assessed using the area under the receiver operating characteristic curve, feature importance, and average precisions of precision-recall curve, precision, recall, f1 score, and accuracy. PPE occurred in 3584 ($1.6\%$) and 1896 ($5.4\%$) patients in the training and test sets, respectively. The BRF model exhibited the best performance (area under the receiver operating characteristic curve: 0.91, $95\%$ confidence interval: 0.84–0.98). However, its precision and f1 score metrics were not good. The five major features included arterial line monitoring, American Society of Anesthesiologists physical status, urine output, age, and Foley catheter status. Machine learning models (e.g., BRF) could predict PPE risk and improve clinical decision-making, thereby enhancing postoperative management. ## 1. Introduction Postoperative pulmonary edema (PPE) is a well-known complication with multiple possible causes [1]. Preexisting cardiac disease, including heart failure, is the most common cause of PPE. Fluid overload results in increased hydrostatic pressure and worsening left ventricular function [2]. Regardless of preexisting heart disease, fluid overload itself can cause PPE. In particular, excessive postoperative fluid administration and transfusions increase the risk of PPE [1,3]. Neurogenic pulmonary edema is another potential cause of PPE [4]. Although neurogenic pulmonary edema is sometimes regarded as a form of acute respiratory distress syndrome, its pathophysiology and prognosis differ from the characteristics of acute respiratory distress [4,5]. PPE can also be caused by anaphylaxis, which results in negative pressure and acute lung injury [1,6]. It is often difficult to determine the cause of PPE during its early stages, particularly in patients with overlapping etiologies [1,6,7]. There is a need to identify patients at high risk of PPE to allow prevention and early treatment. Several studies have reported the causes and risk factors for PPE, but early diagnosis and management are difficult, more so in patients with overlapping etiologies or uncertain causes [1,2,3,4,5,6,7,8,9,10]. Advances in computing have enhanced several key areas of clinical research; artificial-intelligence-based methods may have additional applications. Machine learning (ML) systems are widely used in clinical research to analyze big data. Compared to traditional scoring systems, ML models perform better when predicting various clinical conditions [11,12,13]. They have been successfully used to predict postoperative complications [14,15,16,17,18,19]. However, there is no reported ML model to predict PPE. In the present study, we hypothesized that ML could predict PPE risk with good performance, and then developed ML models to predict PPE. ## 2.1. Data Collection This retrospective cohort study protocol was approved by the Clinical Research Ethics Committee of Chuncheon Sacred Heart Hospital, Hallym University. The need for informed consent was waived because of the retrospective study design. The medical records of patients treated between 1 January 2011 and 15 November 2021 were obtained from the clinical data warehouses of five hospitals affiliated with Hallym University Medical Center. The hospitals were located in Seoul (Kangnam Sacred Heart Hospital and Hangang Sacred Heart Hospital), Gyeonggi Province (Hallym University Sacred Heart Hospital and Dongtan Sacred Heart Hospital), and Gangwon Province (Chuncheon Sacred Heart Hospital). A clinical data warehouse is a database of medical records, prescriptions, and test results, which can be used to identify patients based on prescriptions, examinations, and diagnostic data. The timing and results of investigations, drug administration, transfusions, and other information were extracted in an unstructured text format. The requested data were provided in a de-identified format, but the data of specific patients could be extracted using a key. ## 2.2. Patients and Pulmonary Edema The study included adult patients aged > 18 years who did not exhibit preoperative pulmonary edema. The exclusion criteria and outlier data were missing. Pulmonary edema was diagnosed by radiologists on the basis of chest radiographs. Patients were presumed not to have PPE if they lacked perioperative respiratory symptoms and did not undergo chest radiography. ## 2.3. Dataset The dataset involved the following 98 perioperative variables: age, male sex, and order of surgery; the statuses of preoperative atelectasis, preoperative effusion, preoperative pneumothorax, preoperative pneumonia, preoperative pulmonary thromboembolism, and preoperative acute respiratory distress; body mass index; the statuses of congestive heart failure, cardiac arrhythmia, valvular diseases, pulmonary circulation disorders, peripheral vascular disorders, hypertension (uncomplicated vs. complicated), paralysis, other neurological disorders, chronic pulmonary diseases, diabetes (uncomplicated vs. complicated), hypothyroidism, renal failure, liver diseases, peptic ulcer diseases (excluding bleeding), acquired immune deficiency syndrome/human immunodeficiency virus, lymphoma, metastatic cancer, solid tumors (without metastasis), and rheumatoid arthritis/collagen vascular diseases; alcohol consumption, current smoking status, smoking frequency (packs), smoking duration (years), emergency status, American Society of Anesthesiologists physical status of >2, use of general anesthesia, maintenance anesthetics administered, N2O use, anesthesia time (min), surgery time (min), intraoperative blood and fluid administration, intraoperative urine output, and estimated blood loss; the statuses of arterial line monitoring, central venous pressure monitoring, Foley catheter, Levin tube, and patient-controlled analgesia; the administration of intraoperative packed red blood cells, frozen fresh plasma, platelets (concentration and cryoprecipitate), rocuronium, vecuronium, atracurium, cisatracurium, succinylcholine, pyridostigmine, neostigmine, sugammadex, fentanyl, alfentanil, sufentanil, remifentanil, and pethidine; blood urea nitrogen level, creatinine level, glomerular filtration rate, prothrombin time, activated partial thromboplastin time, and platelet count; the levels of sodium, potassium, uric acid, protein, and albumin; and the statuses of robotic surgery, laparoscopic surgery, heart surgery, abdominal surgery, breast surgery, ear surgery, endocrine surgery, eye surgery, head and neck surgery, musculoskeletal surgery, neurosurgery, obstetric and gynecological surgery, spine surgery, thoracic surgery, transplant surgery, urogenital surgery, vascular surgery, and skin and soft tissue surgery. The dataset was divided into training and test sets. The training set included data from Kangnam Sacred Heart Hospital, Hangang Sacred Heart Hospital, Hallym University Sacred Heart Hospital, and Dongtan Sacred Heart Hospital. The test set included data from Chuncheon Sacred Heart Hospital. The training set was used for model learning, whereas the test set was used to evaluate model performance. Both datasets were standardized using min.–max. scaling based on the training set. ## 2.4. Machine Learning The study used supervised learning, which is an ML paradigm for data consisting of labeled examples (i.e., each data point contains variables and an associated label). Five ML algorithms were used: random forest, light-gradient boosting machine, extreme-gradient boosting machine, multilayer perceptron, and logistic regression [20,21,22,23,24]. Random forest is a regression tree technique that uses bootstrap aggregation and predictor randomization to achieve high predictive accuracy. Various random forest input parameters were explored [25]. A light-gradient boosting machine continuously divides a leaf node with maximum data loss without a consideration of tree balance, resulting in a deep and asymmetric tree [26]. Extreme-gradient boosting machine is an optimized gradient boosting algorithm that involves parallel processing, tree-pruning, missing value management, and regularization to avoid overfitting/bias [27]. Multilayer perceptron is a neural network with ≥1 intermediate layer between the input and output layers. The network is connected in the direction of the input, hidden, and output layers; there are no connections within the layers, but the output layer is directly connected to the input layer through a feedforward network [28]. Logistic regression can solve the binary classification problems associated with the linear model. The dataset was imbalanced and may have caused low model performance. Therefore, we used the synthetic minority oversampling technique for all algorithms except random forest [29]. After the ratio of pulmonary edema had been balanced, we trained the models with a training set that included synthetic samples. The random forest algorithm includes a classifier method known as balanced random forest (BRF); therefore, the synthetic minority oversampling technique was not used for the random forest algorithm. Data processing and the ML process are summarized in Figure 1. Feature importance was calculated to assess the best model using the built-in function in the algorithm package. ## 2.5. Modified Dataset An additional carved dataset was used to modify the prediction model based on the large and complex dataset. This dataset was learned and validated using the best prediction algorithm from the original data. First, the test dataset was reduced by under-sampling using the Tomek’s link method to validate our best model [30]. Second, a simplified prediction model was made using 20 important features of the best model, and was validated using a test dataset that included these features. ## 2.6. Metrics and Statistics Six metrics were calculated for model performance. The primary metric was the area under the receiver operating characteristic curve. The average precisions of precision-recall curve, best threshold, precision, recall and f1 score, and accuracy were calculated. Google Colab (Python version 3.7; Google, Mountain View, CA, USA) was used to calculate model metrics. Descriptive analysis was performed to compare the characteristics of patients with and without PPE. Categorical variables were presented as numbers (%) and compared using the chi-squared test. Continuous variables were presented as medians (interquartile ranges) and compared using the Mann–Whitney U test. p-values of < 0.05 were considered statistically significant. ## 3.1. Patient Characteristics The study included 287,976 patients aged > 18 years who did not exhibit preoperative pulmonary edema. After the exclusion of 26,597 patients with missing ($$n = 26$$,593) and outlier ($$n = 4$$) data, and 4480 preoperative PPE patients, a total of 256,899 patients were included in the analysis. PPE occurred in 5480 ($2.8\%$) patients. The training and test sets included 221,908 and 34,991 patients, respectively. PPE occurred in 3584 ($2.1\%$) and 1896 ($7.4\%$) patients in the training and test sets, respectively (Table 1 and Table 2). ## 3.2. Model Performance BRF exhibited the best performance for the prediction of PPE risk. As the primary metric, the area under the receiver operating characteristic curve for BRF was 0.91 ($95\%$ confidence interval: 0.84–0.98). The performances of the remaining models are summarized in Figure 2. BRF also exhibited the best performance based on the average precision of the precision-recall curve (0.44). The average precisions of the precision-recall curve for the remaining models are summarized in Figure 3. BRF had the best recall (0.832) and f1 score (0.372), whereas the light-gradient boosting machine model had the best precision (0.531) and accuracy (0.946). The remaining metrics are summarized in Table 3. ## 3.3. Feature Importance The evaluation of feature importance in the BRF model revealed that arterial line monitoring was the most important feature. Ten major features in the BRF model are shown in Figure 4. ## 3.4. Validation of under-Sampling Test Dataset and Simplified Model After under-sampling of the test dataset, PPE patients were 1896 and No-PPE patients were 32,621. In the simplified prediction model, the included features were as follows: arterial monitoring, American Society of Anesthesiologists physical status, age, urine output, intraoperative fluid, estimated blood loss, foley catheter, anesthesia time, albumin, glomerular filtration rate, central venous pressure monitoring, operation time, prothrombin time, blood urea nitrogen, protein, creatinine, prothrombin time-international normalized ratio, platelet, body mass index, and intraoperative packed red blood cell. Validation results are summarized in Table 4. ## 4. Discussion We used ML to develop models for the prediction of PPE. Model training using data from 221,908 patients was followed by model testing using data from 34,991 patients. Five algorithms were used to develop the models, whereas six metrics were used to evaluate their performances. BRF exhibited the best performance in terms of area under the receiver operating characteristic curve, recall, and accuracy. However, no model had a good precision or f1 score. Numerous studies have developed ML models to predict postoperative pulmonary complications. Peng et al. developed and validated a deep-neural-network model based on combined natural language data and structured data to predict pulmonary complications in geriatric patients [15]. Xue et al. developed an ML model to predict postoperative pulmonary complications after emergency gastrointestinal surgery in patients with acute diffuse peritonitis [18]. Chen and colleagues developed an ML model to predict postoperative pneumonia in orthotopic liver transplant patients [14]. Although the outcomes of the above studies included PPE, their findings differed from ours because they also assessed other complications. An ML model to predict PPE risk after any type of surgery has not been developed. PPE has various causes, several of which can occur simultaneously. PPE may be cardiogenic or noncardiogenic, but it is difficult to distinguish between these etiologies because of their similar clinical features. In patients with acute myocardial infarction, cardiogenic pulmonary edema may be complicated by noncardiogenic edema related to the aspiration of gastric contents, syncope, or cardiac arrest. Conversely, in patients with severe trauma or infections accompanied by noncardiogenic pulmonary edema, fluid resuscitation may cause pulmonary edema through volume overload and increased pulmonary vascular hydrostatic pressure [1,6,31]. Therefore, PPE prediction and the preemptive management of risk factors are important. The present study investigated the important features of the best model for the prediction of PPE risk. Ten major PPE risk factors were included, primarily those related to fluid and hydrostatic pressure rather than the other causes of PPE. This means that the PPE prediction model could mainly predict cardiogenic and hydrostatic pulmonary edema. However, the evidence is not conclusive because the etiologies of PPE in this study were not known. The most important feature was arterial line monitoring, which is required in patients who need continuous blood pressure monitoring or multiple blood sampling during surgery [32]. Arterial line monitoring is the standard of care for patients at risk of rapid hemodynamic changes. Patients with a poor preoperative status and those who undergo major surgeries can develop rapid hemodynamic changes and often need multiple sampling [33]. American Society of Anesthesiologists physical status and age also indicate preoperative patient condition. Patients with high American Society of Anesthesiologists physical status grades may develop heart, lung, kidney, and brain problems [34,35]. Old age is generally associated with compromised organ function, resulting in a greater risk of PPE [36]. Urine output, fluid volume, EBL, albumin, and glomerular filtration rate directly and indirectly affect body fluid status, which is associated with hydrostatic pressure [37,38,39,40,41]. To the best of our knowledge, our model is the first to predict PPE risk, and its performance was better than the previous PPE models. However, the present study had some limitations. First, the overall performance of the model was good, but its precision and f1 scores were low, even for the best threshold. Because recall (sensitivity) was good, the proportion of false positives may be high, presumably because of the low proportion of patients with pulmonary edema in the overall dataset. Thus, our model interpreted the normal state as PPE in many cases. There were similar results in the validation with the under-sampling dataset. Second, our model requires many features to predict PPE, which reduces its practicality. Although the performance was not significantly worse in the model with twenty features, this limitation of the model could not be resolved. A prediction model based on fewer features while maintaining the performance may be needed in the future. To resolve the first two limitations, additional datasets should be acquired and learned, or features with better predictive values should be selected. Third, our model could not distinguish between cardiogenic and noncardiogenic PPE. Additional studies are needed to develop models that can distinguish between the two PPE types and predict the risk of each type. In conclusion, we developed an ML model that could predict PPE risk in patients undergoing surgery. The model was superior to previously reported prediction models for postoperative pulmonary complications. Our ML model may improve clinical decision-making, thereby enhancing postoperative management. 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--- title: Proteomics- and Metabolomics-Based Analysis of Metabolic Changes in a Swine Model of Pulmonary Hypertension authors: - Payel Sen - Bachuki Shashikadze - Florian Flenkenthaler - Esther Van de Kamp - Siyu Tian - Chen Meng - Michael Gigl - Thomas Fröhlich - Daphne Merkus journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003314 doi: 10.3390/ijms24054870 license: CC BY 4.0 --- # Proteomics- and Metabolomics-Based Analysis of Metabolic Changes in a Swine Model of Pulmonary Hypertension ## Abstract Pulmonary vein stenosis (PVS) causes a rare type of pulmonary hypertension (PH) by impacting the flow and pressure within the pulmonary vasculature, resulting in endothelial dysfunction and metabolic changes. A prudent line of treatment in this type of PH would be targeted therapy to relieve the pressure and reverse the flow-related changes. We used a swine model in order to mimic PH after PVS using pulmonary vein banding (PVB) of the lower lobes for 12 weeks to mimic the hemodynamic profile associated with PH and investigated the molecular alterations that provide an impetus for the development of PH. Our current study aimed to employ unbiased proteomic and metabolomic analyses on both the upper and lower lobes of the swine lung to identify regions with metabolic alterations. We detected changes in the upper lobes for the PVB animals mainly pertaining to fatty acid metabolism, reactive oxygen species (ROS) signaling and extracellular matrix (ECM) remodeling and small, albeit, significant changes in the lower lobes for purine metabolism. ## 1. Introduction Pulmonary hypertension (PH) due to pulmonary vein stenosis (PVS) is a life-threatening disease, which mainly affects the pediatric population [1]. This type of PH, which ultimately results in a left ventricular inflow tract obstruction, is classified under type II PH [2]. PVS presents mostly with congenital heart defects (univentricular heart disease, ventricular septal defect, atrial septal defect or persistent arterial duct), lung disease (bronchopulmonary dysplasia) or Down syndrome or other trisomy [3,4]. In rare cases, PVS can also occur in adults because of radiofrequency ablation therapy after atrial fibrillation [5]. This particular type of PH is characterized by an initial passive increase in pulmonary artery pressure brought on by increased resistance due to the banding. The increased mean pulmonary artery pressure results in vascular remodeling, which further raises pulmonary vascular resistance and causes an additional increase in pressure. Surgical interventions and/or stenting of the lesions in patients with PVS frequently lead to restenosis, and the use of vasodilators comes with the risk for pulmonary edema [6]. The complex molecular mechanisms involved in PH are limiting factors in the development of novel therapeutic interventions. Previous work by our group has shown that endothelial factors are important in the development of PH in a swine model using pulmonary vein banding (PVB) of the lower lobes for 12 weeks to induce type II PH [7]. This procedure results in areas of the lung with a varied hemodynamic profile within the lung; the lower lobes experience high pressure and low flow (HF/LF) whereas the upper lobes experience high pressure and high flow (HP/HF). High and low shear stress have very striking effects on the endothelial cells of the lung vasculature. Endothelial cells typically respond to high shear stress with strong nitric oxide synthesis, but they “activate” a pro-inflammatory profile at low shear stress, characterized by low nitric oxide production [8]. In this study, we conducted a quantitative LC-MS/MS-based proteomic analysis of lung samples along with untargeted metabolomics from swine with PVB and control (Cntrl) swine. We analyzed tissues from the upper and lower lobes to investigate how different hemodynamic profiles impact protein and metabolite expression due to PH in the lobes. ## 2.1. Characteristics of Pulmonary Hypertension Pulmonary vein banding in the PVB group animals resulted in significant stenosis in the inferior pulmonary confluence as shown in the angiogram (Figure 1A). Twelve weeks after banding, this resulted in a significantly higher mean pulmonary artery pressure (38 ± 8 mmHg) in the PVB animals compared to the control (mean of 20 ± 4 mmHg, $p \leq 0.05$) (Figure 1D) as well as an increased pulmonary vascular resistance and reduced pulmonary artery compliance (Figure 1E,F). Histology of the lung tissue revealed more picrosirius red staining in the PVB animals in the upper and lower lobe, depicting more fibrosis compared to the Cntrl (Figure 1B,C). ## 2.2. Proteomic Analysis of PVB vs. Control in the Upper and Lower Lobe To explore the chronic effects of flow and pressure alterations in the lung tissue, we performed a label-free liquid chromatography–tandem mass spectrometry analysis (LC-MS/MS) of PVB vs. Cntrl samples from the upper as well as the lower lobes ($$n = 6$$ for PVB; $$n = 7$$ for Cntrl). Using LC-MS/MS-based proteomics, we identified 5112 proteins with high confidence (false discovery rate < 0.01) (Supplementary Data 1, Table S1). The dataset has been submitted to the ProteomeXchange *Consortium via* the PRIDE partner repository with the dataset identifier PXD038982 [9]. Differential abundance analysis revealed significant differences between groups. The principal component analysis showed clustering of the PVB animals compared to the Cntrls in the upper (HP/HF) lobe, whereas similar clustering was absent in the lower lobe (HP/LF) (Figure 2A,B). In total, 104 proteins were found to be differentially abundant (Benjamini–Hochberg corrected p-value < 0.05 and fold change ≥ 1.5) between PVB and Cntrl in the upper lobes (Supplementary Data S1, Table S2). In the lower lobes, 52 proteins differed significantly in abundance between PVB and Cntrl (Supplementary Data S1, Table S3). Volcano plots were used to visualize proteome alterations between conditions (Figure 3A,B). In the upper lobe, several apolipoproteins (APOF, APOA, APOC3), complement cascades (C6, C7, C8, C9) and coagulation proteins (Serpins, HRG, PROC) were found to be downregulated in the PVB animals, while several membrane transport proteins (SCGB1A1, SFTPA1) were found to be upregulated. In the lower lobe, DNA binding and ribosomal proteins (H1-2, H1-1, RPS6) were upregulated, while membrane remodeling proteins (GMPR, ALF1, SIGLEC1) were downregulated. We performed a STRING preranked functional enrichment analysis of proteome profiles from the upper and lower lobe to reveal lobe-specific signatures for PVB and Cntrl animals. From the Gene Ontology (GO) biological processes database, 67 and 7 significantly enriched terms were found in the upper and lower lobe, respectively (enrichment factor >1) (Figure 3C, Supplementary Data S1, Tables S4 and S5), PVB upper lobes showed a distinct downregulation of proteins related to humoral immune regulation, lipoprotein particle organization, cholesterol esterification and triglyceride homeostasis and an upregulation of proteins related to platelet degranulation, coagulation, cholesterol efflux and intermembrane lipid transport. Proteins related to the extracellular matrix were found to be both up- as well as downregulated in PVB animals, indicating altered matrix turnover. In the lower lobe, PVB showed fewer enriched pathways compared to the upper lobe. The majority of the pathways were related to blood coagulation, extracellular matrix reorganization, actin cytoskeletal organization and carbohydrate metabolism. Since ECM-related proteins were altered in both lobes, we also compared the proteins in this pathway in both upper and lower PVB lobes with the established lung matrix gene set and found several proteins (collagens, serpins, etc.) that were differentially regulated (Supplementary Figure S1A) [10]. ## 2.3. Metabolomic Profiling of the Lower and Upper Lobe versus Control Next, we performed untargeted metabolomics on these lung tissues to better understand the ongoing metabolic alterations caused by variations in flow and pressure. To detect the relevant metabolites, we used statistical analysis with XCMS and MetaboAnalyst 5:0 software. Supplementary Data S2, Table S1 lists the metabolites that were detected in the HILIC-negative mode MS. On the MetaboAnalyst platform, a 3D PCA analysis (Figure 4A,B) and a supervised orthogonal partial least squares discriminant analysis (OPLS-DA) (Figure 4C,D) were performed for both the upper and lower lobes. In the upper lobe, 3D PCA and OPLS-DA analysis revealed separation between the PVB and Cntrl groups. Similar to the case for our proteomics findings, the lower lobe groups did not show a clear separation in metabolomics either. The OPLS-DA analysis also allowed for the identification of the metabolites that contributed the most to group segregation, known as variable importance in the projection (VIP) scores, and they were ranked accordingly (Figure 5A). Metabolites with a VIP score of ≥1 were interpreted as highly influential (Supplementary Data S2, Tables S2 and S4), and we performed an enrichment analysis of metabolites with $p \leq 0.05$ to differentiate control from PVB animals (Figure 5B). In comparison to Cntrl, we found 82 such metabolites in the PVB upper lobe (Supplementary Data S2, Table S3) and 29 metabolites in the PVB lower lobe (Supplementary Data S2, Table S5). Enrichment analysis for the PVB upper lobe revealed 25 metabolic pathways, of which the following six pathways had a p-value of <0.05: linoleic acid metabolism, ubiquinone biosynthesis pathway, transfer of acetyl groups into mitochondria, arginine, proline metabolism and glycerolipid metabolism. The lower lobe showed enrichment of 11 pathways, but none were significantly altered ($p \leq 0.05$). We detected the pathway for purine metabolism ($$p \leq 0.06$$) to be the most differentially regulated (Supplementary Figure S2). ## 2.4. Network Analysis of Proteomics and Metabolomics Datasets A combined analysis of the two omics datasets was carried out in order to identify commonly altered pathways and to provide additional insight into the process of pulmonary vascular remodeling. The metabolite–metabolite and the gene–metabolite interaction networks provide an overview of functionally related metabolites and proteins found to be most differentially abundant in metabolomics and proteomics. The metabolite–metabolite pathway interaction network derived from the KEGG database is shown in Figure 6A and highlights functional interactions among the top altered metabolites such as oleic acid, linoleic acid, palmitic acid, prostaglandin E2 and L-malic acid, butyric acid, NADP, proline, threonine, S-adenosylhomocysteine and arachidonic acid. Next, the most significantly altered proteins and metabolites identified were mapped to the gene–metabolite molecular interactions to create a network (Figure 6B). The network includes 31 nodes (protein, metabolites) and shows that the metabolites (squares) are upregulated whereas the proteins (filled circles) are downregulated. The metabolite chondroitin sulfate, a major component of the extracellular matrix (ECM), is upregulated in the upper lobe of the PVB group and formed a network with proteins important for wound healing such as serpinc1, serpinD1, F12, PROC, VTN, AMBP and TNC. Plasminogen (PLG), another prominent protein involved in wound healing and ECM remodeling, is functionally linked to both chondroitin sulfate and oleic acid. The PVB upper lobe was enriched in oleic acid, linoleic acid, palmitic acid, butyric acid and arachidonic acid, which formed a network with downregulated proteins in the PVB group such as ApoA1, ApoB, AdipoQ and ALB. These proteins and metabolites together participate in fatty acid metabolism. Prostaglandin E2, a common byproduct of arachidonic acid, is also upregulated in the PVB upper lobe and has formed a network with complement cascade members C8A and C3 as well as the chemokine PPBP, which are involved in inflammation. Finally, the monosaccharide metabolite glucose was downregulated in the upper lobe and functionally linked with the surfactant protein SFPTD and the blood coagulation protein HBB, indicating altered glucose metabolism. The PVB lower lobe presented with a metabolite–metabolite interaction network involving only four metabolites: guanosine monophosphate, inosinic acid, glyceric acid and dodecanoic acid (Supplementary Figure S3A). *The* gene metabolite network showed a simple network involving only guanosine monophosphate and inosinic acid (Supplementary Figure S3B). They functionally connected with the downregulated the enzyme guanosine monophosphate reductase (GMPR) and HPRT1 in the PVB lower lobe. Furthermore, the metabolite guanosine monophosphate was connected to the interferon-induced guanylate binding protein (GBP1). ## 2.5. Protein and Transcriptional Regulation of Fatty Acid Uptake in the Upper Lobe The protein abundance of members of apolipoproteins in the upper lobe as well as the lower lobe was further compared in dot plot analysis, and members of this fatty acid uptake pathway were validated at a transcriptional level (Figure 7A–C, Supplementary Figure S4A). ApoE was found to be significantly altered in both proteomics as well as at the transcriptional level in the upper lobe of the PVB group. In addition, further transcripts coding for proteins important for fatty acid uptake such as CD36 ($$p \leq 0.1$$) showed a trend toward a decrease in the PVB upper lobe compared to Cntrls along with significant upregulation of the LDLR (low-density lipoprotein receptor). In contrast, we did not see similar changes at the mRNA level for these proteins in the lower lobe of PVB compared to Cntrls. ## 3. Discussion The main findings in this study were that (i) chronic alterations in flow and pressure induced by PVB impact the proteomic and metabolomic profile in the lung tissue and result in increased ECM and collagen production in lobes with both HP/HF and HP/LF; (ii) upper lung lobes with HP/HF adapt by altering the fatty acid metabolism as well as ROS signaling and (iii) the lower lobes with HP/LF increase their purine metabolism in order to cope with the increased demand of cellular proliferation (Figure 8). We have previously demonstrated that PH caused by pulmonary vein stenosis results in a progressive increase in pulmonary vascular resistance, which is accompanied by functional (increased contribution of endothelin, phosphodiesterase 5) as well as structural (increased media thickness) pulmonary vascular remodeling [7,11]. Banding of the confluence of veins from the lower lobes results in areas of the lungs with distinct hemodynamic profiles: HP/HF in the unbanded upper lobes and HP/LF in the banded lobes. This model is, therefore, well suited for the study of mechano-metabolic coupling and its role in pulmonary vascular remodeling in PH, as it has been demonstrated that metabolic and structural changes are coupled to each other [12]. Here, we present a thorough proteome and metabolome profile analysis of lung tissue with these distinct mechanical profiles. Pathway enrichment analysis in PVB animals demonstrated changes in several pathways that have been associated with the progression of PH. Thus, alterations were observed for extracellular matrix proteins involving integrins, matrix metalloproteases, collagen, vitronectin, serpins and others observed in both lobes of the animals. This is in accordance with our histological data, suggesting increased ECM deposition around the vessels. We also detected high amounts of phosphatidylcholine (PC) as well as prostaglandins, which indicate plasma membrane break and inflammatory signaling due to high shear stress [13]. In line with these findings, the comparison with the lung matrix database revealed that further extracellular matrix proteins were altered in the upper and lower lobes of PVB swine (Supplementary Figure S1A). ECM proteins such as FGB, COL1A and COL15A1 were significantly upregulated in the PVB lower lobe, whereas in the upper lobe, the analysis revealed synergistic downregulation of extracellular proteolytic proteins such as MMP9 and serpins [14,15]. Strikingly, proteins of the apolipoprotein family were significantly altered in abundance in PVB animals. The key protein component of HDL-C, apolipoprotein A (APOA), which was downregulated in the upper lobe, was not shown to be differentially regulated in the lower lobe. Downregulation of APOA1 is in accordance with data showing that ApoA-1 is less prevalent in PH, which contributes to oxidative stress and endothelial dysfunction [16]. Furthermore, administration of a peptide mimetic of ApoA-1 reduced pulmonary hypertension in rodent models with PH [17]. Along with ApoA, we also detected significantly reduced levels of ApoE at the proteomics as well as at the transcription level in the PVB upper lobe. The metabolomics data in the upper lobe further point to an ongoing alteration of lipid homeostasis and detected increased fatty acids such as oleic acid, linoleic acid, arachidonic acid and palmitic acid in the PVB group, indicating a reduced uptake of fatty acids due to decreased levels of apolipoproteins [18]. High amounts of linoleic and oleic acids have been found to significantly lower nitric oxide (NO) levels in endothelial cells and exert their deleterious effects via ROS [11,19,20]. It has been shown that HIF-1α activation, a common dysregulated pathway in PH and lung diseases, can inhibit β-oxidation of long-chain fatty acids leading to accumulation of fatty acids [21]. However, we did not detect increased accumulation of carnitine and acyl-carnitine, which reflects inhibition of mitochondrial fatty acid β-oxidation and has been previously shown to be involved in the development of PH [22]. In keeping with studies from Umar et al. who showed higher oxidized LDL in the lungs and plasma in PH with a decrease in CD36, our proteomic analysis did detect modifications of pathways regulating cholesterol levels consisting primarily of the downregulation of fatty acid transporters such CD36 and LDLRAP1 [23]. Along with this, we detected significant upregulation of the protein LDLR in the PVB upper lobe. LDLR mainly binds to apolipoprotein B100 (APOB) and APOE to clear cholesterol from the blood [24]. Both ApoB and ApoE are high-affinity ligands for LDLR and are expressed in various immune and vascular cells [24,25]. Negative feedback inhibition from transcriptional and posttranscriptional mechanisms closely controls the LDLR pathway, and disruption of this tightly controlled pathway can influence lipid and cholesterol regulation [26]. These data are also in accordance with integrated proteomic and metabolomics data on HUVECs presented by Venturini et al., showing that high shear stress upregulates the lipoprotein metabolism and increases the expression of LDLR [27]. Additionally, we found metabolites such as oxaloacetic acid and L-malic acid, both intermediate products of the TCA cycle, to be enriched in the PVB upper lobe along with decreased glucose. These metabolites take part in anaplerotic reactions in which the intermediate metabolites exit the TCA cycle and are used by proliferating cells due to an increased demand for protein and fatty acids in PH [12]. These data support the presence of the Warburg effect, showing that glucose metabolism is increased in PH [28,29,30,31]. Further evidence for this Warburg effect is the lower amount of NADP in the PVB upper lobe. NADP maintains the redox balance in the cells and supports the biosynthesis of the fatty acids and is essential for maintaining a large number of biological processe [32]. In agreement with this finding, Nukula et al. reported a lower NADPH/NADP ratio in CTEPH patients’ endothelial cells compared to healthy subjects, implying increased oxidative stress and endothelial cell dysfunction [30]. A key metabolite that was downregulated in the PVB upper lobe and deemed important from our network analysis was S-adenosylhomocysteine (SAH). Asymmetric dimethyl arginine (ADMA), a negative regulator of endothelial nitric oxide synthase, is formed by the hydrolysis of methylated proteins, and the methylated proteins are derived when S-adenosyl methionine (SAM) is converted to SAH. We also simultaneously observed increased aspartic arginine (VIP > 1, Supplementary Data S2, Table S2), which is a source of NO in endothelial cells, in the upper lobe of the PVB group [23,24]. In our previous work, we have shown that NO production is increased in HP/HF areas, likely as a compensatory mechanism to maintain vasodilation [33]. Our current data suggest that low SAH, and hence low ADMA, in combination with high arginine, the substrate for endothelial NO synthesis, facilitates NO synthesis in the PVB upper lobe vasculature. Notably, proteomic and metabolic alterations were less pronounced between PVB and Cntrls in the lower lobes. The STRING analysis points to reduced glucose synthesis in the PVB lower lobes, which supports the notion that glycolysis predominates over other metabolic activities in PH in the lower lobes as well [22]. Another intriguing observation was that the purine pathway metabolites adenosine monophosphate (AMP) and guanosine monophosphate (GMP) were significantly enriched, and the enzyme guanosine monophosphate reductase (GMPR), which converts GMP to inosine monophosphate (IMP), was downregulated. Additionally, our proteome data revealed that the PVBs had a decreased abundance of the enzyme HPRT, which transforms hypoxanthine into IMP and is crucial for the salvage pathway for recycling nucleotides [34]. We also found more inosine in the metabolome of PVB lower lobes, which indicated that the cells increased de novo purine production rather than using the standard active salvage pathway. These data are consistent with the study by Hautbergue et al., wherein modifications to the purine metabolic pathway in the right ventricle and plasma of PH rats were shown [35]. The purine metabolite levels in endothelial cells from PAH patients have also been found to be higher, the same was true for the serine to glycine ratio, which is mediated by the mitochondrial enzyme serine hydroxymethytransferase (SHMT) [36]. Although SHMT was unchanged in our lung tissue samples, we did observe an increase in the metabolite serine (VIP > 1) in the PVB lower lobes (Supplementary Data 2, Table S4). Moreover, in atherosclerosis models, it has been shown that vessels with low flow and shear stress have decreased endothelial nitric oxide synthase (eNOS) along with increased cell proliferation and collagen deposition [31]. ## 4. Materials and Methods Lung tissue was used from experiments that have previously been published [7,11,33]. These experiments followed the guiding principles in the care and use of laboratory animals, which are endorsed by the Council of the American Physiological Society, and the protocol was approved by the Animal Care Committee at Erasmus University Medical Center (EMC3158, 109-13-09). ## 4.1. Outline of Study For all surgical procedures, swine were sedated with an intramuscular injection of a mixture of tiletamine/zolazepam (5 mg kg−1, Virbac, Barneveld, The Netherlands), xylazine (2.25 mg kg−1, AST Pharma, Oudewater, The Netherlands) and atropine (0.5 mg) and intubated and ventilated (O2:N2 (1:2)). Isoflurane ($2\%$ vol/vol, Pharmachemie, Haarlem, The Netherlands) was added to the gas mixture to induce anesthesia. Post-surgical analgesia was administered by means of an i.m. injection (0.3 mg buprenorphine i.m. Indivior, Slough, UK) and a fentanyl slow-release patch (6 or 12 μg h−1 depending on body weight, 72 h). Crossbred Landrace x Yorkshire pigs of either sex (8 ± 2 kg) underwent non-restrictive inferior pulmonary vein banding ($$n = 6$$) via the third right intercostal space or a sham procedure ($$n = 7$$). All 13 animals, underwent chronic instrumentation 4 weeks later, enabling hemodynamic assessments on awake animals. Following a left-sided thoracotomy in the fourth intercostal space, fluid-filled catheters (Braun Medical Inc., Bethlehem, PA, USA), were inserted in the aorta, the pulmonary artery, the left and right ventricle and the left atrium for the measurement of blood pressure. A flow probe (20PAU, Transonic systems, Ithaca, NY, USA) was placed around the ascending aorta for the measurement of cardiac output. Aorta flow was indexed to bodyweight. The total pulmonary vascular resistance index was calculated as the ratio of mean PAP and cardiac index, while pulmonary vascular compliance was calculated as stroke volume index/(systolic PAP − diastolic PAP). Hemodynamics were recorded (WinDaq, Dataq Instruments, Akron, OH, USA) in the awake state, with swine standing quietly, and analyzed offline using a custom written program (Matlab, version R2007b, The MathWorks). Twelve weeks after the PVB procedure, swine were re-anesthetized; the thorax was opened using sternotomy, and the heart and lungs were excised, snap-frozen in liquid nitrogen and processed for further analysis. ## 4.2. Real-Time Quantitative PCR of Lung Tissue Lung tissue was snap-frozen and 30 mg of tissue was homogenized, and mRNA was extracted using the RNeasy Fibrous Tissue Mini kit (Qiagen, Hilden, Germany). cDNA was synthesized using 500 ng of mRNA and the SenSi FAST cDNA synthesis kit (Bioline, London, UK). *Target* genes were normalized against beta-actin and cyclophilin using the CFX manager software 3.1 (BioRad, CA, USA). *Relative* gene expression was calculated using the delta–delta Ct method. ## 4.3.1. Sample Preparation for Proteome Analysis Frozen lung tissue samples were placed into precooled tubes and cryopulverized in a CP02 Automated Dry Pulverizer (Covaris, Woburn, MA, USA) with an impact level of 5 according to the manufacturer’s instructions. Tissue lysis was performed in 8 M urea/0.5 M NH4HCO3 with ultrasonication (18 cycles of 10 s) using a Sonopuls HD3200 (Bandelin, Berlin, Germany). Total protein concentration was quantified using a Pierce 660 nm Protein Assay (Thermo Fisher Scientific, Rockford, IL, USA). Fifty micrograms of protein were digested sequentially, firstly with Lys-C (FUJIFILM Wako Chemicals Europe GmbH, Neuss, Germany) for 4 h and, subsequently, with modified porcine trypsin (Promega, Madison, WI, USA) for 16 h at 37 °C. ## 4.3.2. Nano-Liquid Chromatography (LC)–Tandem Mass Spectrometry (MS) Analysis and Bioinformatics 1 μg of the digest was injected on an UltiMate 3000 nano-LC system coupled online to a Q Exactive HF-X instrument operated in the data-dependent acquisition (DDA) mode. Peptides were transferred to a PepMap 100 C18 trap column (100 µm × 2 cm, 5 µM particles, Thermo Fisher Scientific) and separated on an analytical column (PepMap RSLC C18, 75 µm × 50 cm, 2 µm particles, Thermo Fisher Scientific) at a 250 nL/min flow rate with a 160 min gradient of 3–$25\%$ of solvent B followed by a 10 min ramp to $40\%$ and a 5 min ramp to $85\%$. Solvent A consisted of $0.1\%$ formic acid in water and solvent B of $0.1\%$ FA in acetonitrile. MS spectra were acquired using a top-15 data-dependent acquisition method on a Q Exactive HF-X mass spectrometer. Protein identification was carried out using MaxQuant (v.1.6.7.0) [37] and the NCBI RefSeq *Sus scrofa* database (v.7-5-2020). All statistical analyses and data visualization were performed using R (https://www.r-project.org/) (accessed on 29 December 2022). Prior to statistical analysis, potential contaminants, only identified by site and reverse hits were excluded. Proteins with at least two peptides detected in at least three samples of each condition were quantified using the MS-EmpiRe algorithm as previously described [38,39]. The R script used for quantitative analysis is available at https://github.com/bshashikadze/pepquantify (accessed on 7 September 2022). Proteins with a Benjamini–Hochberg corrected p-value ≤ 0.05 and fold change ≥ 1.5 were regarded as significantly altered. *Preranked* gene set enrichment analysis using STRING was employed to reveal biological processes related to differentially abundant proteins [40]. Signed (based on fold change) and log-transformed p-values were used as ranking metrics and the false discovery rate was set to $1\%$. The redundancy of the significantly enriched biological processes was minimized using REVIGO tool [41]. ## 4.4. Metabolomics Approximately 50 mg of sample material was weighed in a 2 mL bead beater tube (CKMix, Bertin Technologies, Montigny-le-Bretonneux, France) filled with 2.8 mm and 5.0 mm ceramic beads. Then, 1 mL of a methanol/water mixture ($\frac{70}{30}$, v/v) was added, and the samples were extracted with a bead beater (Precellys Evolution, Bertin Technolgies, Montigny-le-Bretonneux, France) supplied with a Cryolys cooling module 3 times each for 20 s with 15 s breaks in between at 10,000 rpm. After centrifugation at 13,000 U/min for 10 min, the supernatants were dried by vacuum centrifugation, suspended in 150 µL of methanol/water ($\frac{70}{30}$, v/v) and subjected to MS analysis. Untargeted analysis was carried out on a Nexera UHPLC system connected to a Q-TOF mass spectrometer (TripleTOF 6600, AB Sciex, MA, USA). Chromatographic separation was achieved by using a HILIC UPLC BEH Amide 2.1 × 100, 1.7 µm column with a 0.4 mL/min flow rate. The mobile phase consisted of 5 mM ammonium acetate in water (eluent A) and 5 mM ammonium acetate in acetonitrile/water ($\frac{95}{5}$, v/v) (eluent B). The following gradient profile was used: $100\%$ B from 0 to 1.5 min, $60\%$ B at 8 min, $20\%$ B at 10 min to 11.5 min and $100\%$ B at 12 to 15 min. Aliquots of 5 µL per sample were injected into the UHPLC-TOF-MS. The autosampler was cooled to 10 °C, and the column oven was heated to 40 °C. A quality control (QC) sample was pooled from all samples and injected after every 10 samples. MS settings in the positive mode were as follows: gas 1 55, gas 2 65, curtain gas 35, temperature 500 °C, ion spray voltage 5500, declustering potential 80. The mass range of the TOF-MS scans was 50–2000 m/z, and the collision energy was ramped from 15 to 55 V. MS settings in the negative mode were as follows: gas 1 55, gas 2 65, cur 35, temperature 500 °C, ion spray voltage −4500, declustering potential −80. The mass range of the TOF-MS scans was 50–2000 m/z, and the collision energy was ramped from −15 to −55 V. The “msconvert” tool from ProteoWizard [42] was used to convert raw files to mzXML (denoised by centroid peaks). The bioconductor/R package xcms [43] was used for data processing and feature identification. More specifically, the matched filter algorithm was used to identify peaks (full width at half maximum set to 7.5 s). Then the peaks were grouped into features using the “peak density” method. The area under the peak was integrated to represent the abundance of features. The retention time was adjusted based on the peak groups presented in most samples. To annotate features with the names of metabolites, the exact mass and MS2 fragmentation pattern of the measured features were compared to the records in HMBD [44] and the public MS/MS spectra in MSDIAL [45], referred to as MS1 and MS2 annotation, respectively. Missing values were imputed with half of the limit of detection (LOD) methods, i.e., for every feature, the missing values were replaced with half of the minimal measured value of that feature in all measurements. To confirm that an MS2 spectrum was well annotated, we manually reviewed our MS2 fragmentation pattern and compared it with records in the public database or previously measured reference standards to evaluate the correctness of the annotation. The MetaboAnalyst 5.0 platform was utilized to conduct multivariate data analysis, for PCA and OPLS-DA. The contribution of each variable to the classification was indicated by the VIP value that was calculated in the OPLS-DA model after Pareto scaling. The Student’s t-test at the univariate level was further employed to measure the significance of metabolites with VIP > 1.0. Metabolites with a p-value < 0.1 were considered as differential metabolites, while those with a p-value < 0.05 were recognized as statistically significant differential metabolites. Enrichment analysis and network analysis was performed using only the significant metabolites and significant genes using the KEGG pathway database. ## 5. Conclusions In conclusion, our combined omics study showed PVB-related key metabolic alterations in a compartment-specific manner. The combination of a model of PH, with specific changes in shear stress in different areas of the lung, with proteome and metabolomic data shows that particular metabolic pathways, including fatty acid absorption and purine synthesis, are altered in early PH. 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--- title: In Situ Formation of Injectable Gelatin Methacryloyl (GelMA) Hydrogels for Effective Intraocular Delivery of Triamcinolone Acetonide authors: - Chaolan Shen - Xuan Zhao - Zewen Ren - Bing Yang - Xiaohui Wang - Andina Hu - Jie Hu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003315 doi: 10.3390/ijms24054957 license: CC BY 4.0 --- # In Situ Formation of Injectable Gelatin Methacryloyl (GelMA) Hydrogels for Effective Intraocular Delivery of Triamcinolone Acetonide ## Abstract A novel drug delivery system designed for intraocular injection, gelatin methacryloyl (GelMA), has attracted much attention due to its sustained-release character and low cytotoxicity. We aimed to explore the sustained drug effect of GelMA hydrogels coupled with triamcinolone acetonide (TA) after injection into the vitreous cavity. The GelMA hydrogel formulations were characterized using scanning electron microscopy, swelling measurements, biodegradation, and release studies. The biological safety effect of GelMA on human retinal pigment epithelial cells and retinal conditions was verified by in vitro and in vivo experiments. The hydrogel exhibited a low swelling ratio, resistance to enzymatic degradation, and excellent biocompatibility. The swelling properties and in vitro biodegradation characteristics were related to the gel concentration. Rapid gel formation was observed after injection, and the in vitro release study confirmed that TA-hydrogels have slower and more prolonged release kinetics than TA suspensions. In vivo fundus imaging, optical coherence tomography measurements of retinal and choroid thickness, and immunohistochemistry did not reveal any apparent abnormalities of retinal or anterior chamber angle, and ERG indicated that the hydrogel had no impact on retinal function. The GelMA hydrogel implantable intraocular device exhibited an extended duration, in situ polymerization, and support cell viability, making it an attractive, safe, and well-controlled platform for treating the posterior segment diseases of the eye. ## 1. Introduction Globally, a wide range of diseases of the posterior segment of the eye is responsible for severe vision loss and blindness. These disorders include age-related macular degeneration (AMD), diabetic retinopathy (DR), diabetic macular edema (DME), retinal vein occlusions (RVOs), proliferative vitreoretinopathy (PVR), posterior uveitis, diseases that occur as a result of alterations in the vasculature of the retina, genetic eye disorders, and tumors. Eye structures are endowed with multiple protective mechanisms such as corneal, scleral, and blood-retinal barriers; thus, designing and evaluating drug delivery systems for use in the treatment of posterior segment ocular diseases is extremely challenging. Conventional administration techniques include eye drops and periocular (subconjunctival and retrobulbar) injection. Unfortunately, the cornea and sclera act as anatomic barriers, and the conjunctival, choroidal, and retinal circulation act as functional barriers. They may either block drug penetration into the eye or accelerate its removal. This problem has been largely overcome by intraocular injection when the properties of the administered drug permit [1,2,3,4,5]. However, the intravitreal route of drug administration has limitations related to the need for repeated injections, poor patient compliance, and the risk of serious complications. Frequent injections are known to cause retinal detachment and endophthalmitis. Therefore, methods that allow the localization of drugs within the vitreous cavity followed by sustained release could guarantee several benefits: improving the disease condition, decreasing the frequency of intravitreal (IV) injection, lowering the risk of developing infections, and enhancing patient compliance. In recent decades, multiple drug delivery systems have been developed for IV administration. These include in situ formation of hydrogels, microspheres, poly(lactide) (PLA), and poly(ethylene glycol) (PEG) [6,7]. The selection of appropriate materials for the preparation of long-acting, sustained-release implants is crucial for achieving easy fabrication and functionalization, biocompatibility, sustained drug release, and controllable degradation rates of the implant. Toxicity or inflammatory degradation products restrict the application of drug delivery systems such as chitosan, PLA, and poly(methylidene malonate) (PMM), and these systems are only used for topical or transscleral administration [8,9]. Commercially available implants can be nondegradable (e.g., Iluvien®) or degradable (e.g., Ozurdex®) [10,11]. PEG is a nondegradable material that has been reported to load triamcinolone acetonide and ovalbumin, a model protein [7]. However, reservoir material remains at the implantation site after drug depletion. In recent years, work on ocular implants has shifted its focus to using biodegradable polymers. The most widely studied commercially available polymer is poly(lactic-co-glycolic acid) (PLGA). PLGA can achieve the prolonged release of several small molecules [6,12,13]. Commercially, PLGA is coextruded with dexamethasone to create Ozurdex®, a product that allows several weeks of drug delivery. PLGA is degraded hydrolytically to lactic acid and glycolic acid, which create a highly acidic environment [14] and induce local inflammatory reactions [15]. In situ-forming hydrogels are considered attractive biomaterials that can be engineered to offer several advantages, including less frequent administration, increased patient comfort, and cost reduction. Gelatin methacryloyl (GelMA)-based hydrogels have been used as materials with bioadhesive properties, tissue engineering, and drug delivery [16,17,18]. Photocrosslinking of GelMA obtained from natural hydrogel gelatin presents some interesting advantages [19]. The existence of peptide moieties such as arginine–glycine–aspartic acid allows cell attachment and protease degradation, making GelMA a close mimic of the natural extracellular matrix [20]. On the other hand, GelMA is a versatile material that can be easily modified to possess various biofunctionalities through the encapsulation of molecules such as drugs, growth factors, and cytokines [21]. It has been engineered as an injectable material for the delivery of cells in a minimally invasive manner [22]. Considering the versatile properties of GelMA, we believe that GelMA is a promising material for developing systems for sustained drug release. In this study, TA based on gelatin methacryloyl (GelMA) was prepared for use as an intraocular delivery system, and its in vitro/ex vivo properties were evaluated regarding their possible application in the prolonged vitreous release of TA. The swelling behavior, in vitro biodegradability, and cytotoxicity of the hydrogels were evaluated. Given its easy injectability, biosafety, and long-lasting nature, this platform can potentially be applied to deliver drugs used to treat a plethora of posterior eye diseases and reduce side effects of repeat injection. ## 2.1. Properties of GelMA-TA GelMA hydrogels were formed by the photochemical reaction of methacryloyl units on GelMA chains and activated by LAP, which absorbs visible light at a wavelength of 405 nm (Figure 1A). Light at 405 nm falls within the safer UV range (≈405 nm), preventing retinal damage caused by UV light exposure. The spontaneous gelation speed was 1 min. GelMA hydrogels without TA showed a lighter pale-yellow color after solidification, and the colors became deeper as the GelMA concentration was increased (Figure 1B). The GelMA-drug delivery system (DDS) samples used in in vitro assays were manufactured using a mixed technique. TA particles were homogenized so that they entered each pore of the material (Figure 1B SEM image). The GelMA hydrogel demonstrates a cross-linking porous architecture. The average pore diameter of different concentrations was measured from scanning electron microscopy images. With increasing GelMA concentration, the pore size of the hydrogel decreased, indicating a denser structure. The apparent pore size decreased from 17.0 ± 3.35 μm to 10.7 ± 2.75 μm as the GelMA concentration was increased from $10\%$ (w/v) to $20\%$ (w/v). The pore size diameter was approximately 10–100 μm, which is suitable for the attaching small particles and cells [23,24]. The swelling rate is a crucial indicator for judging the advantages and disadvantages of drug delivery systems. A lower swelling rate is beneficial for materials that are to be used for vitreous injection. In terms of the application of IV drugs, a low swelling rate can help avoid an increase in ocular volume. Our results showed that the concentration of GelMA used in the preparation of the hydrogels directly affected the swelling rate (Figure 2A–D). With increasing GelMA concentration, the swelling rate of the hydrogels decreased, and the weight and volume of the hydrogel reached equilibrium after 8 h and 12 h, respectively. G5 ($5\%$GelMA) had the highest swelling rate (31.69 ± $1.43\%$), while G20 ($20\%$GelMA) had the lowest (14.57 ± $0.87\%$). Compact materials absorb less water and have lower swelling rates. Enzymatic degradation is another major factor that affects the rate of drug release. To investigate the protease-mediated degradation of GelMA and its effect on drug release, we incubated GelMA in a collagenase solution. Changes in the wet weight of GelMA were recorded and used to calculate the rate of degradation of the hydrogel. As shown in Figure 2E,F, G5 degraded rapidly within 12 h ($40\%$), while G20 showed only $20\%$ degradation after 72 h. ## 2.2. Ex Vivo Permeation Study We evaluated the hydrogels and characterized drug release in PBS to determine diffusive release kinetics in vitro release conditions. The profile of TA release from the GelMA-TA hydrogels in PBS is shown in Figure 3. To evaluate the effects of hydrogel’s concentration on drug release, two different concentrations of GelMA ($10\%$ and $20\%$, designated G10 and G20, respectively) were used to encapsulate the same dose of TA (1 mg). Our study compared in vitro release profiles of G10 +1 mg TA and 1 mg TA suspension. First, 88.23 ± $1.94\%$ TA was slowly dissolved from the 1 mg TA suspension on the 30 th day of incubation, compared with 42.42 ± $1.66\%$ released from G10 + 1 mg TA (Table 1). On the 90th day of incubation, 97.51 ±$1.99\%$ TA was released from G10 + 1 mg TA (Figure 3C). This means that the implant can release TA over a period that is substantially longer than 90 days. The time taken to reach $50\%$ release (t50, release) was 14 d for 1 mg suspension, 37 days for G10 + 1 mg TA, and 46 days for G20 + 1 mg TA. On the other hand, the mean TA release from G10 + 1 mg was 14.14 ± 2.11 μg, a slight increase compared to the 11.71 ± 1.78 μg observed for G20 + 1 mg, but the total cumulative release at 30 d decreased from $42\%$ to $35\%$. The loose structure of the G10 hydrogel favored a faster release and higher cumulative release of TA. GelMA-DDA caused a noticeably decreased release, demonstrating that release can be tailored by adjustment of the concentration of GelMA used in TA encapsulation (Figure 3). To assess the effect of the dose parameter on diffusive drug release in PBS, several doses of TA (1 mg, 2 mg, 4 mg, and 8 mg) were added to the precursor solutions with stirring. As the G10 + TA drug concentration was increased from 1 mg/mL to 8 mg/mL, the peak release increased from 16.50 ± 0.98 μg to 75.76 ± 8.33 μg (Table 1). In vitro release level of TA from 1 mg TA suspension was approximately the same as G10 + 4 mg TA hydrogel, the mean release of the drug exhibited sustained release at 28.67 ± 13.31 for 1 mg TA suspension vs 36.73 ± 9.97 for G10 + TA 4 mg. The increase in TA release corresponded to the increased TA load dose, whereas the TA dose was a significant parameter that allowed us to tailor drug delivery (Figure 3B). ## 2.3. In Vitro Assessment of Cytocompatibility We further performed in vitro cell biocompatibility studies in 2D-cell cultures of HRPE cells. It enabled us to consider the effects of the structural properties of GelMAs with different crosslinking densities on the cellular biocompatibility of the hydrogel. We used a standard live/dead assay to measure cell viability by determining the percentage of live cells remaining after seeding in medium-leached (Figure 4A) and 2D (Figure 4B) cultures. The results demonstrated that cell viability remained >$90\%$ after 1, 3, and 5 days in GelMA + TA leached and 2D cultures (Figure 4A,B). In the in vitro study, the effect of GelMA + TA on HRPE cell migration was analyzed. Cell migration was measured using wound healing assays. As Figure 4C shows, gap closure by migrating cells did not obviously differ from that in the control group during incubation of the cells in GelMA + TA leaching medium for 10 h or 24 h after scratching. We tested the stimulatory effect of GelMA + TA in primary cultured RPE cells. As shown in Figure 4D, TA stimulation induced IL-10 upregulation and TGF-β2 downregulation in the cells, indicating that TA affects the anti-inflammatory response in primary RPE cells. Furthermore, 8 min of exposure to 405 nm light induced Nrf2 expression and inhibited H2O2-mediated damage in primary cultured RPE cells (Figure 4E). ## 2.4. In Vivo Release of TA from Implants In vivo, a functional assessment of the retina was performed by electroretinography (ERG). Rabbits’ eyes that had been injected with $10\%$ GelMA hydrogel with or without 1 mg TA showed only slightly low amplitudes of the DA 0.01 b-wave and LA 30 Hz flicker at 7 d and recovery by 2 months. At 2 months, there were no significant changes in DA 0.01 b-waves, DA 10 a-waves or b/a ratios, LA 3 b-waves or b/a ratios, or 30 Hz flicker ERG amplitudes in the eyes injected with G10 and G10 + 1 mg TA hydrogel compared to the unoperated eyes (Figure 5). As assessed by slit lamp examination and fundus evaluation, rabbits whose eyes had been implanted with G10 or G10 + 1 mg TA hydrogels showed no significant inflammation in either the anterior or posterior segment of the eye (columns (i–iii) in Figure 6A–C) and had normal IOP. Furthermore, $10\%$ GelMA demonstrated superior long-term biocompatibility (2 months) in vivo; the injected eyes presented clear corneas, absence of cataracts (Figure 7(Bi)), normal IOP (between 6 and 15 mmHg, Figure 8C), and normal retinal thickness and choroid thickness as determined by both SD-OCT and H&E histology (Figure 7(Biii,Biv); Figure 8A,B). Compared with the non-operated group, the eyes of the G10 and G10 + 1 mg TA groups displayed no disorganized microstructure, apparent inflammatory cells, hemorrhage, or edema two months after injection of the hydrogel (Figure 7A–C). No inflammatory cells were found in the anterior chamber angle in any of the sections examined (Column (v) in Figure 7A–C). These results indicate that the functions of the entire layer of neuroretinal tissue were normal in GelMA-injected eyes. Furthermore, normal IOP values were observed in eyes injected with G10 and G10 + 1 mg TA for 2 months after injection (Figure 8C). ## 3. Discussion The data presented in this study show that the GelMA hydrogel has several unique functions. First, it can be delivered by a simple injection and cured in 60 s at 37° under 405 nm visible light after injection. It offers a safe, biodegradable implant that can be placed in a posterior vitreous location and acts as a controlled drug release system. This hydrogel, therefore, has the potential to provide a new class of biomaterials suitable for ophthalmic applications. Clinically, easy injectability is a critical factor in intraocular drug application. *In* general, conventional pellet-shaped implants require an expensive engineered delivery applicator that is invasive because it usually requires the use of large-gauge needles that must be placed in a region of the sclera that is uncomfortable for the patient [25,26,27]. GelMA that allows in situ sol–gel transition could be used to develop injectable materials that can be delivered locally in a minimally invasive and cost-effective manner. After injection in the soluble state using a standard 23 G or 25 G instrument, it gels within minutes after photocrosslinking with 405 nm light. We tested the expression of the oxidative stress-related gene Nrf2 and its dependent gene HO-1 to characterize oxidative stress following the application of 405 nm light. Our results did not show any increase in oxidative stress in HRPE cells after exposure to visible light at a wavelength of 405 nm for 4 min. Eight minutes of light exposure can induce oxidative stress that inhibits the compensatory upregulation of Nrf2. The photocurability of the material allows temporal and spatial control of the reaction with the assistance of a photoinitiator. From a clinical viewpoint, the most significant advantage of the light-curing adhesive system is that it provides surgeons with sufficient working time to properly position the graft before using light to gelatinize it. Various drug delivery systems (DDSs) have been explored in the scientific literature, including membranes [28], nanoparticles [29], liposomes [30], and hydrogels [31]. Hydrogels are a particularly interesting class of materials for use as DDSs and have been extensively used in many branches of medicine and tissue engineering. We focused on the impact of drug loading on the equilibrium swelling and the GelMA-DDS mesh size. Mesh size is the primary physical parameter that controls drug diffusion [31]. SEM images of the GelMA hydrogels at different GelMA concentrations are shown in Figure 1. As shown in the images, the crosslinked network forms a porous three-dimensional structure, and the pores are uniformly distributed in the structures. The pore size decreased as the GelMA concentration increased, and the increased density of the hydrogel network hindered the release of the loaded drugs from the hydrogel. The porous structure provides appropriate channels for medium flow and drug transport, making the hydrogel favorable for drug release. Other studies have demonstrated that increasing the GelMA concentration decreases the hydrogel mesh size [32,33], leading to higher stiffness and lower permeability [34]. Tests of a material’s mechanical properties are crucial when designing implantable hydrogel-DDSs that possess stability and degradability. Figure 2E shows that the enzymatic resistance of hydrogels improved with increasing GelMA concentration. The degradation of GelMA was slow, requiring approximately 100 h for G5 and 150 h for G20. During the degradation process, the hydrogel gradually shrinks and eventually disappears instead of breaking into several pieces. It is important for intraocular applications, as small fragments may obstruct the trabecular meshwork. Figure 1 shows that with increasing GelMA concentration, the hydrogels show a denser structure and have a low swelling rate. In terms of their use to deliver IV drugs, a low swelling rate can help avoid an increase in ocular volume. However, increasing the compactness of the GelMA leads to higher stiffness and lower injectability. Therefore, we chose a suitable concentration, G10, to achieve easy injectability and a low swelling rate. The hydrogel tensile strength and strain at break averaged 18–45 kPa and 34–$48\%$, respectively. Young’s modulus of the hydrogels prepared at different concentrations of GelMA ranged from 20 KPa (G5) to 98 KPa (G20) in our previous study [17]. Overall, the expected range of mechanical properties observed for $10\%$ GelMA is consistent with that reported in other studies [35,36]. Triamcinolone acetonide (TA) is a synthetic corticosteroid structured as 9-fluoro-11b,16a,17,21-tetrahydroxypregna-1,4-diene-3,20-dione cyclic 16,17-acetal with acetone. TA is used extensively in treating ocular diseases characterized by inflammation, edema, and neovascularization. To understand the effect of GelMA in vitro drug release, TA was used as a model drug and loaded into hydrogels prepared at different GelMA concentrations. We evaluated the release of the drug in PBS to obtain diffusive release kinetics in vitro release conditions. The release kinetics of TA from GelMA were assessed over 90 d. Figure 3 shows that the drug release rate was dependent on the hydrogel concentration and that TA release rate decreased with increasing gel concentration. Intravitreal injection of 1 mg/0.1 mL TA suspensions is the most popular choice for ophthalmologists. Previous studies showed that 1 mg TA release in vivo was 99.1 ± $0.4\%$ complete after just 21 days, and with a half-life of 15.4 ± 1.9 days [37,38]. Increasing the dose of intravitreal TA could prolong the effects of the drug on the retina, the calculated half-lives of intravitreal TA were 24 days for the 4 mg dose and 34 days for the 8 mg dose [39]. Unfortunately, the high dosage was associated with an increased risk of steroid-related IOP rise [40,41]. In vitro release level of TA from 1 mg TA suspension was approximately the same as G10 + 4 mg TA hydrogel. The mean release of the drug exhibited sustained release at 28.67 ± 13.31 μg for 1 mg TA suspension vs 36.73 ± 9.97 μg for G10 + TA 4 mg. The release concentrations of 1 mg TA doses decreased gradually with time, and the peak concentration was the initial concentration. The initial concentration was 6-fold the amount released at 30 days. However, in GelMA platform, there is no apparent initial release burst, preventing an undesired high initial dosage. More important, T50, release for G10 + TA 4 mg was 60 days compared to 14 days for 1 mg TA suspension. We observed that GelMA reservoirs achieved more drug release as the drug dose was increased, demonstrating the dose-dependent characteristics of drug release. The use of a controlled release rate of TA could reduce the risk of cytotoxicity. An appropriate degradation rate of the material is crucial in selecting materials for long-acting, sustained-release implants. The first generation of ocular drug delivery systems commonly use nonbiodegradable implants. Retisert® and Vitrasert®, which are drug tablets coated with nonbiodegradable polymers, are two examples. However, after depletion of the drug, the drug reservoir requires surgical removal or is allowed to remain at the implantation site, increasing the likelihood of complications. In recent years, interest in using biodegradable polymers as ocular implants has grown. Among such biodegradable polymers, PLGA is the most widely discussed in the literature and is the most widely commercially available [12,13]. In the commercial product Ozurdex® (Allergan, Dublin, Ireland), PLGA is coextruded with dexamethasone to achieve 3 months of drug delivery. A limitation of PLGA is that it is degraded to lactic acid and glycolic acid, which create a highly acidic environment [14] and cause local inflammatory reactions [15]. Previous studies have demonstrated that GelMA hydrogels consist of gelatin backbones and that their degradation products consist of Amide A, Amide I, Amide II, and Amide III [42]. Thus, to imitate the in vivo environment, we also evaluated the degradation behavior of GelMA hydrogels in collagenase solution by monitoring the percentage of residual hydrogel mass as a function of time (Figure 2E,F). As expected, more rapid loss of mass was observed for the GelMA hydrogels with lower concentrations. As presented in Figure 2E,F, the enzymatic resistance of hydrogels was improved as the GelMA concentration was increased, similar to the swelling rate trend. The degradation time of G5 was the shortest (approximately 100 h), while that of G20 was the longest (approximately 150 h). The degradation time of 50 μL G10 in rabbit eyes was 3 months. GelMA hydrogels are based on gelatin, an inexpensive denatured form of collagen susceptible to enzymatic degradation. Clinically, this is a major advantage of its use in ocular implants. The potential cytotoxicity of the Id hyIrIgels is important for Iheir use in intravitreal ocular drug delivery. GelMA has been widely used in biomedical applications such as drug carriers and cell ECM and showed low cellular cytotoxicity [21,43]. This study measured the viability of RPE cells by live/dead assays to evaluate the cytotoxicity of the GelMA and TA mixture hydrogels prepared in this study. The cells were incubated for 1, 3, or 5 d with hydrogel leachates, during which time the medium was not changed. The results show that GelMA hydrogels are promising ocular drug carriers that may not affect the viability of cells. Testing the ocular tolerability of a drug delivery system designed for ocular instillation is extremely important. The complications are associated with intravitreal triamcinolone therapy include secondary ocular hypertension in approximately $40\%$ of the eyes injected, medically uncontrollable high intraocular pressure leading to secondary open-angle glaucoma and requiring antiglaucomatous surgery in approximately $1\%$ to $2\%$ of the eyes injected, posterior subcapsular cataract and nuclear cataract leading to cataract surgery in approximately $15\%$ to $20\%$ of elderly patients within 1 year after injection, postoperative infectious endophthalmitis at a rate of approximately 1:1000, noninfectious endophthalmitis, perhaps due to a reaction to the solvent agent, and pseudoendophthalmitis in which triamcinolone acetonide crystals appeared in the anterior chamber of the eye [44]. As previously mentioned, the most important adverse reaction to administration of intraocular TA (IVTA) is elevated IOP. In several studies, white particles were found in the anterior chamber and angle after IVTA injection, and these were correlated with an IOP rise [45,46]. It might be related to the spillover of TA into the anterior chamber and a reduction in the outflow capacity of the trabecular meshwork. To examine the in vivo drug side effects, the effects on IOP of administration of 1 mg TA mixed with $10\%$ GelMA (w/v) were evaluated and compared with the effects of administration of the conventional solution (suspension). There were no significant differences in IOP among the three groups during the 60-day study period. In this work, intraocular tissues were evaluated via OCT and H&E staining to determine the levels of inflammation after implantation of the hydrogel. It could pave the way for further clinical research. Compared with normal control eyes, full-field ERG shows both scotopic and photopic function at three months in rabbits. No abnormal changes were found on ERG examination 2 months after implantation of GelMA in the rabbits’ eyes (Figure 5). The GelMA and GelMA + TA groups showed no disorganized microstructure, apparent inflammatory cells, hemorrhage, or edema at one month after implantation, and no inflammatory cells were found in the ciliary bodies in any of the sections examined (Figure 7A–C). Collectively, the function and structure examinations further proved that the novel hydrogel could be an excellent choice for use in vitreous implant drug applications. A limitation of our study is that we did not measure TA concIntrations in rabbits to demonstrate the pharmacokinetic features of the hydrogels in vivo. However, TA is a well-studied drug, and drugs in the vitreous can be eliminated through the retina-choroid layer that surrounds the vitreous and/or by the aqueous humor outflow pathways in the anterior of the eye. Furthermore, GelMA has a binding affinity for growth factors, suggesting a potential role for this material as a biological medicine carrier [47]. ## 4.1. Materials GelMA (EFL-GM-90, $90\%$ graft degree) and lithium phenyl-2,4,6- trimethybenzoylphosphinate (LAP) were purchased from Suzhou Intelligent Manufacturing Research Institute (Suzhou, Jiangsu, China). All cell culture-related reagents were purchased from Gibco BRL (Grand Island, New York, NY, USA) and dispase (Roche, Indianapolis, IN, USA). Fluorescent F-actin/DAPI staining fluorescent and LIVE/DEAD assay kits were purchased from Invitrogen (Thermo Fisher Scientific, Shanghai, China). PrimerScript RT Master Mix and SYBR Green Supermix were obtained from TaKaRa Biotechnology (Kusatsu, Japan). Triamcinolone acetonide (TA) was purchased from Zhejiang Xianju Pharmaceutical Co., Ltd. (Taizhou, Zhejiang, China). The anti-RPE65 antibody was purchased from Abcam (Shanghai, China). Anti-rabbit IgG (4412, Alexa Fluor 488 conjugate) antibodies were purchased from Cell Signaling Technology (CST, Danvers, MA, USA). Collagenase II was purchased from Sigma-Aldrich (St. Louis, MO, USA). ## 4.2. Preparation of the GelMA Hydrogels Solutions and TA-Loaded GelMA Solution LAP was dissolved in PBS to a concentration of $0.25\%$ (w/v) and heated at 55 °C to ensure complete dissolution. GelMA powder and LAP solution were mixed thoroughly at concentrations of $5\%$, $10\%$, and $20\%$ (w/v). TA was loaded at concentrations of 20 mg/mL, 40 mg/mL, 80 mg/mL, and 160 mg/mL into the prepared GelMA solution by a simple mixing technique. The precursor solutions were incubated at 37 °C for 10 min to form Schiff bases and then photocrosslinked with visible light (405 nm, 30 mW/cm [2]) for 1 min using a light source (Suzhou Intelligent Manufacturing Research Institute, Suzhou, China). ## 4.3. Scanning Electron Microscope Imaging The morphology and external surfaces of the lyophilized samples were examined by scanning electron microscopy (SEM, EVO18; Zeiss, Jena, Germany). Freezing of the samples was performed at −80 °C for 24 and was followed by lyophilization at −50 °C for 72 h by applying a vacuum of 10−1 mbar. ## 4.4. Swelling Measurement The swelling kinetics of GelMA hydrogels (~500 μL) at various concentrations ($5\%$, $10\%$, and $20\%$) were determined at 37 °C. After gel formation at 37 °C for 24 h, the gels were further incubated in PBS (pH = 7.4) at 37 °C. At predetermined time intervals (1, 2, 4, 6, 8, 10, 12, and 24 h), the excess PBS was removed, and the surface water on the hydrogels was blotted gently with filter paper. The gels were then weighed. The swelling ratio was calculated using the following equation, in which swelling ratio = (Wt − Wi)/Wi × $100\%$, where *Wt is* the wet weight at a specific time point and *Wi is* the initial weight before swelling. Every reported value was the average of at least three measurements. ## 4.5. In Vitro Degradation Study of GelMA The enzymatic degradation of GelMA hydrogels was evaluated using collagenase, as reported elsewhere [48]. Briefly, the GelMA solution (200 μL) was transferred to a PDMS mold ($d = 6$ mm and th = 3 mm) and polymerized to yield disc-shaped constructs. The discs were then equilibrated overnight in PBS solution. They were then soaked in 5 mL of 0.1 M Tris–HCl buffer (pH 7.4) containing 5 mM CaCl2 for 1 h to reabsorb the water. Subsequently, collagenase (Sigma-Aldrich, USA) solution was added to give a final concentration of 1 mg/mL. The collagenase solution was changed every 8 h, and the residue was carefully removed from the solution, gently blotted on filter paper, and weighed. The degradation rate ($$n = 3$$) was calculated using the following equation: Lost Weight (%) = 100 (Wt − Wi/Wi × 100, where *Wt is* the residual wet weight at a specific time point and *Wi is* the initial wet weight. ## 4.6. In Vitro Drug Release The in vitro release of TA from hydrogels in PBS (pH 7.4) at 37 °C was measured. First, 1–8 mg amount total TA was loaded into the precursor GelMA solution (200 μL). After the formation of hydrogel, 25 mL phosphate buffer saline (PBS, pH 7.4, 37 °C) containing $10\%$ methanol, which is used to improve the solubility of TA in PBS, was added into the vial as the release medium. The whole experiment setups were placed in a shaking water bath adjusted at a temperature of 37 °C and shaken at a rate of 50 strokes per min. At predetermined time intervals, 2 mL of the sample was withdrawn, and the same volume of fresh PBS was added to the dissolution vessel. The released TA was detected by high-performance liquid chromatography (HPLC, LC-20 A, Shimadzu, Kyoto, Japan) on a C18 reversed-phase analytical column with spectrometric detection at 239 nm. The mobile phase consisted of 525 parts methanol and 475 parts deionized water. The flow rate was 1.0 mL/min, and the separation was performed at 40 °C. The amount of TA present was determined using a standard curve. The amount of drug release was expressed as the cumulative percentage of TA released in PBS. The experiments were performed at least in triplicate for each sample. The average values of the obtained results were calculated and used to plot the in vitro time-release profile. ## 4.7.1. Cell Cultures Cytotoxicity studies were conducted using human retinal pigment epithelial cells (HRPE) because this cell line is widely used for cytotoxicity testing in the literature. A pair of human eyes from a 7-year-old donor was obtained from the eye bank of Zhongshan Ophthalmic Center. The research protocol was approved by the Medical Ethics Committee of Zhongshan Ophthalmic Center, Sun Yat-sen University (Approval No. 2018KYPJ034, Approval Date 1 March 2018), and the tenets of the Declaration of Helsinki were followed throughout the study. RPE cells were harvested under sterile conditions as described below. Briefly, the anterior segment of each eye was removed by cutting around the iris. The opened eye was transferred to a new plate, the neural retina was removed, and the remaining part of the eye was rinsed several times with PBS to eliminate remaining neural tissues, blood, and other residual tissue. The retinal pigment epithelium-choroid was then carefully separated from the sclera and placed face up in a small sterile Petri dish containing 2 U/mL dispase in Ca2+- and Mg2+-free Hank’s balanced salt solution. After incubation at 37 °C for 1 h with occasional shaking, the supernatant was carefully aspirated and transferred to a sterile centrifuge tube. The sample was then centrifuged at 1000 rpm for 5 min, and the resulting pellet was resuspended gently in Dulbecco’s modified Eagle’s medium (DMEM)/F12 supplemented with $10\%$ fetal bovine serum and 100 U/mL penicillin and streptomycin. The suspended cells were transferred to 25 cm2 flasks and cultured in DMEM/F12 containing $10\%$ fetal bovine serum in a humidified incubator at 37 °C and $5\%$ CO2. Subculture using trypsinization with trypsin/EDTA solution was performed when the cells reached $80\%$ confluence. Experiments were conducted on cells at passages 3 to 7. For hydrogel leaching medium culture, the hydrogels were immersed in culture medium at a ratio of 1 mL medium per 0.1 g gel and incubated with the cells at 37 °C in a humidified atmosphere of $5\%$ CO2 for 24 h. For two-dimensional (2D) culture, the precursor solutions were prepared as described above and filtered through a 0.22-μm filter (Merck Millipore, Burlington, MA, USA). The sterile solutions were then added to tissue culture plates and photocrosslinked in the wells. After three washes with the culture medium, HRPE cells were seeded on top of the hydrogels. The culture medium was replaced every 2 days. ## 4.7.2. Assessment of HRPEs Cell Viability The viability of cells was evaluated using a LIVE/DEAD® Viability/Cytotoxicity kit for mammalian cells (Invitrogen™) according to the manufacturer’s instructions. Briefly, cells were incubated with 0.5 μL/mL calcein AM and 2 μL/mL ethidium homodimer-1 (EthD-1) in DPBS for 15 min at 37 °C in the cell culture incubator to allow simultaneous staining of living and dead cells. At 1, 3, and 5 days post-seeding, live (green-stained) and dead (red-stained) cells were imaged using an inverted fluorescence microscope (Observer 7, Zeiss, Germany). The numbers of live and dead cells were quantified using ImageJ software. Viability was then calculated using the following equation: Cell viability (%) = Living cells/ (Living cells + Dead cells) × $100\%$. ## 4.7.3. HRPE Migration Function Cell migration was measured using wound healing assays. For the wound healing assay, HRPE cells (5 × 105 cells/mL) were seeded in 6-well plastic culture plates. When the cells reached approximately 80–$90\%$ confluence, straight scratches were made in the cell monolayer using a micropipette tip. The plain culture medium and containing the G10 + TA1 mg leaching culture medium were then added to the wounded cells. At intervals thereafter, the width of the scratch width was quantified using ImageJ software, and the percentage of the gap covered by migrated HRPE cells was taken to indicate the migration rate. The data used in the quantification were obtained in three independent experiments. ## 4.7.4. UV Radiation Procedure HRPE cells were exposed to blue visible light (405 nm, 30 mW/cm2) for 30 s, 1 min, 2 min, 4 min, and 8 min at a distance of 1 cm, followed by culturing in basal medium. ## 4.7.5. Quantitative Real-Time PCR (qRT-PCR) Treated cells were collected, total RNA was extracted using TRIzol reagent (Invitrogen, Waltham, MA, USA), and 1 μL of the extracted total RNA was reverse-transcribed for cDNA synthesis using a SYBR PrimeScript™ RT-PCR Kit (Takara, Dalian, China) according to the manufacturer’s instructions. The expression levels of interleukin-6 (IL-6), interleukin-10 (IL-10), nuclear factor E2-related Factor 2 (NrF2), heme oxygenase-1 (HO1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), transforming growth factor beta 1 (TGF-β1) and transforming growth factor beta 2 (TGF-β2) were measured by qRT-PCR. using a LightCycler480 II Sequence Detection System (Roche, Switzerland). Relative target gene expression was calculated using the ΔΔCt method. The primer sequences were as follows: IL-6, forward: 5′-AAGCCAGAGCTGTGCAGATGAGTA-3′, reverse: 3′-TGTCCTGCAGCCACTGGTTC-5′; IL-10, forward: 5′-TAATTTATCTTGTCTCTGGGCTTGG-3′, reverse: 3′-AAGTGGTTGGGGAATGAGGTT-5′; TGF-β1, forward: 5′-CGCATCCTAGACCCTTTCTCCTC-3′, reverse: 3′-GGTGTCTCAGTATCCCACGGAAAT-5′; TGF-β2, forward: 5′-TTACACTGTCCCTGCTGCACTT-3′, reverse: 3′-GGTATATGTGGAGGTGCCATCAA-5′; NrF2, forward: 5′-CGGTATGCAACAGGACATTG-3′, reverse: 3′-ACTGGTTGGGGTCTTCTGTG-5′; HO1, forward: 5′-AAGATTGCCCAGAAAGCCCTGGAC-3′, reverse: 3′-AACTGTCGCCACCAGAAAGCTGAG-5′; and GAPDH, forward: 5′-GCACCGTCAAGGCTGAGAAC-3′, reverse: 3′-TGGTGAAGACGCCAGTGGA-5’. ## 4.8. Animal Studies All experimental protocols, including experimental procedures and the transport and care of the animals, complied with the Association for Research in Vision and Ophthalmology Statement for the Use of Animals in Ophthalmic and Vision Research and the guidelines provided by the Animal Care and Use Committee of Zhongshan Ophthalmic Center (Guangzhou, Guangdong, China). ## 4.8.1. Intravitreal Gel Injection Eight- to twelve-week-old male New Zealand White rabbits (Guangzhou Huadu Hua Dong Xin Hua Experimental Animal Farm, Guangdong, China) were used in this study. The rabbits were randomly divided into three groups (a GelMA group, a GelMA + TA group, and a control group), with 3 animals in each group. The rabbits were housed under standard conditions (25 °C, relative humidity $50\%$) in the animal facilities of the Zhongshan Ophthalmic Center (Sun Yat-Sen University) and given free access to food and water. For hydrogel injection, the rabbits were placed under general anesthesia by intravenous injection of $2\%$ pentobarbital sodium (30 mg/kg). After intramuscular injection of xylazine solution (0.5 mL/kg body weight), topical anesthesia ($0.5\%$ Alcaine (Alcon)) was administered to reduce the animals’ discomfort. While anesthetized, the rabbits were kept on a heating pad to enable them to maintain their body temperature. The pupils were dilated with topical $1\%$ tropicamide (Alcon). The ocular surface and surrounding tissue were sterilized with diluted iodophor solution followed by saline. Using C-ring and a coverslip, the posterior eye chamber and the retina could be visualized under a surgical microscope, allowing real-time monitoring of the procedure. An incision was then made into the vitreous using a 25-gauge trocar (Alcon) without disturbing the posterior capsule, lens, or retina. Fifty microliters of prepared precursor solutions were injected into the vitreous through a sterilized 1 mL syringe. The injected precursor solutions were then photopolymerized by exposure to 405 nm visible light for 1 min. Finally, an Elizabeth collar was used to prevent the animal from scratching its eyes. The postoperative regimen included tobramycin and dexamethasone eye ointment (Tobradex, Alcon, Fort Worth, TX, USA) once daily for one week. ## 4.8.2. Slit-Lamp, Color Fundus Photos, and Optical Coherence Tomography Evaluation for Ocular Media and Retinal Tissue Slit lamp biomicroscopy (Topcon system) was performed to evaluate anterior chamber (AC) transparency and possible pathological changes. Color fundus photography was performed using a Topcon Fundus Camera (Topcon system) at designated time points to evaluate the retina and detect any changes in the hydrogel. Images showing the structure and thickness of the retina and the choroid tissue were obtained by spectral-domain OCT (Heidelberg Engineering) and used in the evaluation. ## 4.8.3. Assessment of Retinal Function by Electroretinography (ERG) ERG was recorded before (baseline) and 1 week, 2 weeks, and 4 weeks after injection of GelMA hydrogel into the vitreous to determine whether GelMA is harmful to the electrophysiological function of the retina. In each rabbit, the maximum dark-adapted b-wave amplitudes were recorded. The ratio of the amplitudes measured before and after injection of the eye was used in the analysis to avoid possible artifacts caused by individual variation in ERG amplitude. ## 4.8.4. Intraocular Pressure (IOP) Measurements The IOP of rabbits was measured using an Applanation Tonometer (Tono-Pen Avia; Reichert, Inc., Depew, NY, USA) by gently and vertically touching the center of the cornea after administration of a topical anesthetic. Each measurement was performed at 10–11 a.m. by the same technician. Baseline IOP was obtained after anesthesia but before the operation. IOP measurements were obtained again immediately after surgery and at each sampling time point thereafter. Ten data points per eye were measured and averaged. ## 4.8.5. Histopathological Examination One rabbit in each group was euthanized 2 months after injection. The rabbit’s eyeballs were removed and immediately fixed in $4\%$ paraformaldehyde. The eyes were then embedded in paraffin, cut, and dewaxed. Sections (10 μm in thickness) were subjected to hematoxylin and eosin (HE) staining. HE staining of the retinal sections was imaged using Tissue Fax software and analyzed using ImageJ. In each retinal section, the number of endothelial cells that broke through the inner limiting membrane was counted. ## 4.9. Statistical Analysis All data are presented as mean ± standard deviation. 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--- title: Metformin, Empagliflozin, and Their Combination Modulate Ex-Vivo Macrophage Inflammatory Gene Expression authors: - Adittya Arefin - Matthew C. Gage journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003317 doi: 10.3390/ijms24054785 license: CC BY 4.0 --- # Metformin, Empagliflozin, and Their Combination Modulate Ex-Vivo Macrophage Inflammatory Gene Expression ## Abstract Type-2 Diabetes *Mellitus is* a complex, chronic illness characterized by persistent high blood glucose levels. Patients can be prescribed anti-diabetes drugs as single agents or in combination depending on the severity of their condition. Metformin and empagliflozin are two commonly prescribed anti-diabetes drugs which reduce hyperglycemia, however their direct effects on macrophage inflammatory responses alone or in combination are unreported. Here, we show that metformin and empagliflozin elicit proinflammatory responses on mouse bone-marrow-derived macrophages with single agent challenge, which are modulated when added in combination. In silico docking experiments suggested that empagliflozin can interact with both TLR2 and DECTIN1 receptors, and we observed that both empagliflozin and metformin increase expression of Tlr2 and Clec7a. Thus, findings from this study suggest that metformin and empagliflozin as single agents or in combination can directly modulate inflammatory gene expression in macrophages and upregulate the expression of their receptors. ## 1. Introduction Type-2 Diabetes Mellitus (T2DM) is a complex, chronic illness characterized by persistent high blood glucose levels [1]. In 2017, 425 million people were reported to be suffering from T2DM, with this number projected to rise by $48\%$ by the year 2045 to 629 million [2]. The global yearly expenditure for healthcare costs of diabetes is projected to rise from 727 billion USD [2017] to 778 billion USD [2045] [2]. Acute complications of T2DM include hypoglycemia, diabetic ketoacidosis, and hyperglycemic hyperosmolar nonketotic coma [3,4]. T2DM is strongly correlated with microvascular complications (including diabetic retinopathy, neuropathy, and nephropathy) and macrovascular complications (such as cardiovascular diseases), which are the most common comorbidity associated with T2DM [5]. Intense management of blood glucose levels has been shown to reduce the microvascular complications associated with T2DM [6,7], but its impact on the outcome of cardiovascular diseases such as atherosclerosis is less clear [6,8]. T2DM is a metabolic disease primarily characterized by decreasing sensitivity of cells in the body towards the endogenous insulin (insulin resistance) and decreasing insulin secretion [3], resulting in hyperglycemia. Reduced insulin response may be due to a variety of factors, including lipotoxicity, mitochondrial dysfunction, ER stress, hyperglycemia, and inflammation [9]. ## 1.1. Macrophages Play a Significant Role in T2DM Progression Macrophages are monocyte-derived phagocytic leukocytes of the innate immune system that are commonly associated with response to infection and play important homeostatic roles in angiogenesis and tissue repair. Macrophages also play a central role in the progression of T2DM through their ability to affect insulin response on metabolic tissues, such as liver, muscle, and adipose, through local inflammatory cytokine secretion activating JNK signaling pathways, causing aberrant phosphorylation of insulin receptor substrate proteins [10]. Depending on the tissue microenvironment, monocytes can differentiate into macrophages and have historically been described to polarize into proinflammatory (M1/classical) or anti-inflammatory (M2/alternative) macrophages, though more recent literature demonstrates how macrophage subsets can exist on a spectrum between these two extremes [11,12,13,14,15]. Recent studies have demonstrated that obesity and hyperglycemia promote myelopoiesis in mice and cause an expansion in the pool of circulating classical monocytes [16,17]. Classical short-lived monocytes produce inflammatory cytokines, and these monocytes selectively penetrate the inflamed tissues [11,12,13,14,15]. This metabolic inflammation has become a major focus of research linking obesity, insulin resistance, and T2DM [18], and is characterized by increased immune cell infiltration into tissues, inflammatory pathway activation in tissue parenchyma, and altered circulating cytokine profiles. TNFα, IL1β, IFNγ, and IL6 are major inflammatory cytokines, which are upregulated in diabetes [19] and atherosclerosis [20], and are expressed in macrophages [21]. ## 1.2. Treating Patients with T2DM The management of T2DM is complex due to the chronic nature of the disease, often progressing over decades and integrating the management and treatment of its associated comorbidities [22]. Patients are advised to partake in lifestyle modifications, including maintaining a healthy diet, regular physical activity, and weight-loss [23]. Unfortunately, this is often ineffective [22], and so patients are then prescribed different classes of anti-diabetes agents depending on their blood glucose levels and glycosylated hemoglobin level (% HbA1c) [24]. Common anti-diabetes drugs are aimed at reducing the hyperglycemia [2,25,26], by targeting tissues which directly impact blood glucose levels, for example metformin targets the liver by reducing hepatic glucose output [25] and empagliflozin blocks glucose reabsorption from the kidneys [25]. The availability of different drugs to control hyperglycemia provides ample opportunities for tailoring the treatment regimen according to the individual need of the patient. Typically, patients may be prescribed a single drug or a combination of drugs depending on the severity of their disease [24,25,26], in accordance with health research association guidelines such as the National Institute of Health Care Excellence (NICE) or American Diabetic Association (ADA). This approach imparts an increasing therapeutic burden on the patient, either in the form of dosage upregulation or additional medications [27,28]. The administration of long-term drugs is not without risks [29]. These agents may reduce insulin resistance and increase insulin secretion and glucose absorption from blood [30,31]. However, many of these agents may worsen the co-morbid metabolic disorders in T2DM patients [25,28,30,31]. For example, Thiazolidinediones are potent anti-hyperglycemic agents, yet they have been associated with worsening cardiovascular disease (CVD) and related mortality [32]. Insulin secretagogues, for example sulfonylureas, meglitinides, and DPP-4 inhibitors, have also been associated with higher CVD risk [33,34,35,36]. Recently, the use of anti-inflammatory agents has shown improvement in hyperglycemia control in T2DM patients and disease models [18,37]. Two common features of all of these agents are persistent reduction of inflammation (reduction in CRP levels in blood) and reservation of beta cell function, which collectively resulted in better hyperglycemia management [38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54]. Thus, investigation of how immune cells such as macrophages respond to anti-diabetes agents requires closer attention. Further knowledge of any advantageous or disadvantageous effects of these drugs on the immune system can be utilized to better treat T2DM patients. ## 1.3. Metformin and Empagliflozin Can Affect Macrophages Responses Several oral anti-diabetic agents have been reported to modulate macrophage polarization towards the M2 anti-inflammatory phenotype, including metformin and empagliflozin [55,56,57]. However, the mechanisms underlying these effects are still poorly understood and may conflict. Metformin has been reported to promote M2 polarization [58] and antitumor or anti-angiogenic M1 polarization [59]. It has previously been shown in murine bone marrow-derived macrophages (BMDM) that lipopolysaccharide (LPS) stimulated phosphorylation of p65 and JNK1 was decreased by metformin, leading to reduced pro-inflammatory cytokine levels [60]. In LPS-stimulated macrophages, the reduction of ApoE expression has been reported to have been reversed by metformin via retarding nuclear translocation of NF-κB [61]. It has also been reported that metformin can inhibit IL1β-stimulated release of IL6 and IL8 from macrophages, human smooth muscle cells, and endothelial cells in a dose-dependent manner [62,63]. It has been recently suggested that the cardio-protective activity of empagliflozin [63] may be due to its anti-inflammatory effect [56]. For example, empagliflozin has been reported to reduce the levels of C reactive protein and polarize macrophages towards the M2 phenotype in patients [56,57]. Empagliflozin reduces obesity-induced inflammation via polarizing M2 macrophages in white adipose tissue and liver [64], and empagliflozin has been reported to decrease M1 macrophages and increase M2 in macrophages in the liver and epididymal white adipose tissue of mice [65]. In ex vivo experiments with macrophages stimulated with ATP, it has been observed that empagliflozin can attenuate NLRP3 activation [66]. It has been speculated that combining metformin with other drugs with anti-inflammatory effects on the macrophages (e.g., empagliflozin) may help to strengthen the therapeutic potential of metformin [67]. However, while this combination remains to be investigated, it has been previously reported that drug combinations can enhance the anti-inflammatory and anti-oxidant activities in stimulated macrophages [68], and the combination of empagliflozin and gemigliptin has been seen to exert anti-inflammatory activity on LPS-stimulated macrophages [69]. In this investigation, we sought to define the direct immunomodulatory properties of metformin and empagliflozin on macrophages as single agents or in combination, reflecting a clinical approach to patient treatment. ## 2.1. Metformin Promotes Tnfa and Il1b Inflammatory Gene Expression in Macrophages To explore the direct effects of metformin on inflammatory gene expression in macrophages, we examined mRNA expression of four well-established inflammatory genes (Tnfa, Il1b, Il6 and Ifng) in mouse BMDM at physiologically relevant concentrations of 1 µM and 10 µM [70,71] at 2 h and 24-h timepoints. We observed that metformin increased mRNA expression of Tnfa after 2 h at 1 µM (Figure 1A, 1.41-fold, $$p \leq 0.002$$) and 10 µM (Figure 1A, 1.36-fold, $$p \leq 0.002$$) and Il1b after 24 h (Figure 1F, 6.2-fold, $$p \leq 0.031$$). ## 2.2. Empagliflozin Promotes Tnfa, Il1b, Il6, and Ifng Inflammatory Gene Expression in Macrophages To explore the direct effects of empagliflozin on inflammatory gene expression in macrophages, we examined mRNA expression of the same four inflammatory genes at identical physiologically relevant concentrations [72] and timepoints. We observed that empagliflozin increased mRNA expression of Tnfa after 2 h at 1 µM (Figure 2A, 1.7-fold, $$p \leq 0.031$$), Il1b at 10 µM after 24 h (Figure 2F, 5.8-fold, $$p \leq 0.016$$), Il6 at 1 µM (Figure 2C, 13.7-fold, $$p \leq 0.037$$), and Ifng at 10 µM (Figure 2D, 4.5-fold, $$p \leq 0.011$$) after 2 h. ## 2.3. Metformin and Empagliflozin in Combination have Contrasting Effects on Macrophage Inflammatory Gene Expression As metformin and empagliflozin are commonly prescribed in combination, we decided to investigate how the combination of these drugs might compare to the responses observed in the BMDM when they were added as single agents. We observed that in contrast to single drug responses, the combination of metformin and empagliflozin had no effect on mRNA expression of Tnfa at 2 h at 10 µM (Figure 3A), however after 24 h incubation, the levels of Tnfa mRNA expression were significantly increased (Figure 3E, 1.4-fold, $$p \leq 0.019$$). The combination of metformin and empagliflozin reduced mRNA expression of Il1b after 24 h (Figure 3F) and Il6 after 24 h (Figure 3G) when compared to single agent responses (Figure 1 and Figure 2). ## 2.4. In Silico Docking of Empagliflozin with TLR2 and DECTIN1 The direct effects of metformin and empagliflozin on basal macrophage gene expression have not been reported previously. *Inflammatory* gene expression in macrophages can be induced through the macrophage’s expression of pathogen-associated molecular pattern (PAMP) recognition receptors, which include the toll-like receptors (TLRs) [73] and DECTIN1 [74]. Therefore, we speculated that the proinflammatory signaling we observed may be induced through these receptors. When investigating the structure of empagliflozin (PubChem CID: 11949646), we noticed that empagliflozin has a similar moiety to yeast zymosan (PubChem CID: 64689) (Figure 4B). Zymosan is a well-established activator of inflammatory gene expression in macrophages through TLR2 and DECTIN1 [75,76,77]. In silico protein–ligand docking assessment suggests that both zymosan (Figure 4A) and empagliflozin (Figure 4C) could interact with the TLR2 through hydrogen bond interactions with amino acid residues R423, V425, D444, S445, and S447 (Figure 4). Remarkably, despite having multiple H-bond donor and acceptor groups, the H-bond formation between the residues of TLR2 and empagliflozin seemed to be facilitated only by the moiety identical to zymosan (Figure 4 and Table 1) with better predicted binding energy (−6.0 kcal/mol) than zymosan (−4.2 kcal/mol) (Table 1). A similar result was observed during docking simulations with DECTIN1-Zymosan and DECTIN1-empagliflozin. Zymosan (Figure 5A) can interact with DECTIN1 receptor through H-bond formation with H126, K128, S129, Y131, N159, and E241 amino acid residues. On the other hand, empagliflozin can form H-bonds with Y131 and N159 amino acid residues of DECTIN1 (Figure 5C). Again, the interaction of empagliflozin with DECTIN1 seems to be facilitated by the moiety identical to zymosan (Figure 5 and Table 2) and yields better binding energy (−6.1 kcal/mol) than zymosan (−5.0 kcal/mol) (Table 2). ## 2.5. Metformin and Empagliflozin can Interact with Tlr2 and Clec7a and Modulate Their Expression Follow-up experiments investigating the effects of metformin and empagliflozin either as single agents or in combination with Tlr2 and Clec7a (the gene symbol for DECTIN1) expression revealed that empagliflozin and metformin added as single agents at 10 µM increase Tlr2 expression (Figure 6A,C) at 2 h (1.53-fold, $$p \leq 0.0002$$; 1.38-fold, $$p \leq 0.003$$) and 24-h timepoints (1.37-fold, p = <0.0001; 1.26-fold, $$p \leq 0.0005$$), respectively. However, in combination, Tlr2 expression was less elevated (Figure 6A,1.24-fold, $$p \leq 0.045$$) or negated (Figure 6C). Interestingly, this mirrors the expression pattern of Tnfa after 2-h exposure (Figure 3A). Regarding Clec7a expression, exposures of 10 µM metformin or 10 µM empagliflozin also showed a trend towards increased Clec7a expression (Figure 6D) at 24-h (2.33-fold, $$p \leq 0.06$$; 2.23-fold, $$p \leq 0.08$$), respectively. However, at the 2 h time point tested (Figure 6B), metformin, empagliflozin, and their combination reduced Clec7a expression. ## 3. Discussion Depending on the severity of their disease, patients with type 2 diabetes may be treated with monotherapy (such as metformin) or dual therapy combinations (such as metformin and empagliflozin combination) [25]. Macrophage-driven inflammation plays a significant role in the progression of T2DM [78] and its associated comorbidities, such as atherosclerosis [79]. While reports are emerging of the indirect effect of anti-diabetes drugs on macrophages through polarization [80], the direct responses of anti-diabetes drugs on these cells have remained unstudied. In this investigation, we sought to determine the direct immunomodulatory properties of two of the most commonly prescribed anti-diabetes drugs, metformin and empagliflozin, on macrophages. Metformin is a biguanide whose mode of action in reducing blood glucose is through reducing hepatic glucose production. Metformin does not require metabolization for its biological activity [70], and physiological plasma levels for biological activity were reported to be between 1 µM to 40 µM with a half-life of 6.5 h [71]. Empagliflozin is an SGLT2 inhibitor whose mode of action is to block glucose reabsorption in the kidney. The physiological plasma levels for biological activity of empagliflozin varies between 1.87 µM to 4.74 µM based on the administered dosing (10 mg and 25 mg, respectively), and it is excreted from the body in an unchanged form after activity. The half-life of empagliflozin is 12.4 h [72]. Therefore, to ensure the clinically relevancy of our experiments, we used metformin and empagliflozin at 1 µM and 10 µM for 2 h and 24 h to determine their direct immunomodulatory effect on murine bone marrow derive macrophages. Murine BMDM from LdlrKO mice are a well-established model for investigating macrophage responses in a cardiometabolic setting [81,82,83,84]. Exposing BMDM to metformin at 1 µM and 10 µM for 2 h increased the mRNA expression of Tnfa (Figure 1A) and 24-h exposure at 10 µM significantly increased the mRNA expression of Il1b (Figure 1F). Exposing BMDM to empagliflozin also induced Tnfa expression at 1 µM within 2 h (Figure 2A), and Il1b mRNA expression was significantly increased after 24 h (Figure 2F). Significant increases in mRNA expression were also observed with Il6 at 1 µM within 2 h (Figure 2C), and Ifng within 2 h at 10 µM (Figure 2D). Therefore, within the first 24 h, after physiologically relevant concentrations of metformin or empagliflozin exposure, several major inflammatory genes were observed to be upregulated. Tnfa, Il1b, and Il6 are activated through TLR signaling [85]. Therefore, we speculated that the proinflammatory signaling we observed may be induced through these receptors. When investigating the structure of empagliflozin (PubChem CID: 11949646), we noticed that empagliflozin has a similar moiety to yeast zymosan (PubChem CID: 64689) (Figure 4B). Zymosan is a well-established activator of inflammatory gene expression, including Tnfa and Il1b in macrophages [75,76,77] through toll-like receptor 2 (TLR2) and DECTIN1 (mouse gene symbol Clec7a) [74,77], and we speculated that the drug–receptor interaction may be TLR2- and DECTIN1-mediated. To test this hypothesis, in silico molecular docking experiments were performed with crystal structures of TLR2 (Figure 4) and DECTIN1 (Figure 5) and the molecules zymosan and empagliflozin. The docking simulations not only suggested that empagliflozin can interact with both TLR2 and DECTIN1 receptors by similar amino acid residue interactions (Table 1 and Table 2) but also yielded better predicted binding energies for both the receptors compared to zymosan (Table 1 and Table 2). These in silico docking experiments also revealed that only the zymosan-moiety in the empagliflozin chemical structure was predicted to be able to interact with TLR2 (Figure 4B,C) and DECTIN1 (Figure 5B,C) receptor amino acid residues. Collectively, these observations indicate a probable recognition of pathogen-associated molecular pattern (PAMP) in the empagliflozin chemical structure by the macrophages. Ligand–receptor binding often modulates mRNA expression of the receptors involved [86]. Further investigation revealed that empagliflozin modulates Tlr2 and Clec7a mRNA expression (Figure 6) in BMDM within the same timeframes observed for inflammatory gene expression, lending support to their possible interaction. Regarding the possible mechanism of metformin’s upregulation of the inflammatory genes observed, there is little in the literature regarding metformin’s direct effect on macrophages. Metformin has historically been characterized by its ability to reduce hepatic glucose production through the transient inhibition of the mitochondrial respiratory chain complex I [70,71] and activation of the cellular metabolic sensor AMPK [87]. Under physiological conditions, metformin exists in a positively charged protonated form, which may rely on different isoforms of the organic cation transporters (OCT) to enter the cell [88,89,90]. However, over the last 15 years, a much more complex picture of metformin’s roles is emerging, reflecting multiple modes of action which have AMPK independent mechanisms, with the new findings varying depending on the dose and duration of metformin used [91]. Our experiments revealed that metformin also upregulated Tlr2 and Clec7a mRNA expression (Figure 6), providing an opportunity for the mechanism behind this observation to follow-ups in future investigations. TNFα is an early response cytokine secreted by macrophages in response to pathogens, which stimulates an acute phase immune response via pathogen-associated molecular pattern (PAMP) receptors such as Toll like receptor 2 (TLR2) by regulating chemokine release and aiding further immune cell recruitment [92]. In macrophages, the half-life of TNFα is approximately 45 min and at least 30 min for mRNA [93] and protein [94], respectively. Our results suggest that macrophages upregulate Tnfa expression after being exposed to single antidiabetic agents (Figure 1A and Figure 2A). A similar increase was also observed after 24-h exposure (Figure 1E), however this did not reach statistical significance, possibly reflecting the more immediate nature of the TNFα response. The difference in effects observed at the higher concentration of 10 µM resembles typical responses observed through PAMP receptor stimulation, whereby higher doses of PAMPs lead to a more intense immune response [95,96]. Like TNFα, IL1β is also a pyrogenic cytokine produced by macrophages to initiate an inflammatory response to stimuli in its microenvironment. IL1β also regulates cytokine release, acting as a chemoattractant for recruitment of immune cells to the site of inflammation [92]. One key difference between the two cytokines is that IL1β is synthesized as a leaderless precursor that must be cleaved by inflammasome-activated caspase-1 and then secreted as a mature isoform [97]. Thus, compared to TNFα secretion and action, IL1β secretion and action become evident at a later time point. Our results demonstrate a similar pattern with exposure to single antidiabetic agents as significant increases in Il1b expression are observed at the later 24-h timepoint (Figure 1F and Figure 2F). IL6 is a pleotropic cytokine with both inflammatory [96] and anti-inflammatory [98] effects and shared regulation pathways with TNFα and IL-1β production and secretion [92,99]. It has been previously observed in murine macrophages that TLR2 activation results in NF-κB activation, which leads to an up-regulation of Il6 expression [100]. Our results suggest that the increases we observe in Il6 mRNA expression (Figure 1C and Figure 2C) may also be TLR2-mediated. IFNγ primes macrophages for enhanced microbial killing and inflammatory activation by TLRs [101,102,103]. In response to classic TLR stimulators (e.g., LPS), macrophages produce IFNγ [104,105]. Our results also suggest simultaneous upregulation of Ifng and post TLR-activation Tnfa expression [92] (Figure 1A,D and Figure 2A,D). In addition, it has been reported that TLR2 stimulation in macrophages can retard the effects observed at 24-h exposure to IFNγ [106,107]. Observations from our study suggest that post-TLR-activation Tnfa levels remained upregulated at 24-h exposure to the drugs or combination (Figure 1E, Figure 2E, and Figure 3E), and Tlr2 expression also remained significantly upregulated (Figure 6C), although the previously observed upregulation in Ifng expression was lost at 24-h exposure (Figure 1H, Figure 2H, and Figure 3H). Thus, it is possible that the drugs metformin and empagliflozin, alone or in combination, have mounted a potent TLR2-mediated initial response, augmented with upregulated Ifng expression. Our results are in contrast to the majority of studies which report anti-inflammatory properties of metformin [56,61,62,63,68] and empagliflozin [57,65,66,67,108]. However, these studies either report [1] indirect systemic anti-inflammatory effects, which may be due to confounding factors such as reductions in hyperglycemia [56,57,61,63,64,68], or [2] polarizing effects [58,60,64,65,66,87]. As metformin and empagliflozin are often administrated in combination [26] to patients with type 2 diabetes, we continued our investigation by exploring the effects of these drugs at 10 μM and at 2 h and 24 h time points. We observed that when added in combination, the pro-inflammatory effects observed with single drug exposure at 2-h were negated (Figure 3A,F). A similar pattern of differential modulation was seen with 24-h exposure for Tlr2 expression (Figure 6A). The mechanism of these reduced responses with metformin and empagliflozin combination may be due to these drugs being recognized by the same set of pattern recognition receptors and leading to competitive inhibition or development of tolerance due to sequential or simultaneous treatment with multiple or higher doses of PAMP [95]. Surprisingly, the exposure to combination of drugs significantly increased Tnfa mRNA expression at 24 h (Figure 3E), and the same combination significantly decreased Il6 mRNA expression at 24 h (Figure 3G). Our data highlight the complexities of individual-gene macrophage inflammatory response regulation; we showed a clearly coordinated proinflammatory response mediated by several genes to a single agent challenge (Figure 1 and Figure 2), which can be negated (Figure 3A,F) or amplified (Figure 3E) when challenged by a combination of those same agents (Figure 7). Based on our observations, to discover the exact mode of binding of these drugs to macrophages, further techniques for studying drug–receptor interactions (e.g., X-ray crystallography or surface plasmon resonance) would need to be explored. During the EMPA-REG BASALTM trial (a part of the EMPA-REG OUTCOME trial), it was reported that after therapy with empagliflozin, pancreatic beta cell function and sensitivity to glucose were significantly improved, along with a significant reduction in fasting blood glucose and % HbA1c levels [109,110]. However, these studies attributed these remarkable beneficial effects of empagliflozin to its potency in reducing glucotoxicity [109,110,111] via SGLT-2 inhibition. It has recently been reported that the postprandial phase potentiates macrophage-derived IL-1β production that in turn stimulates insulin secretion, synergistically promoting both glucose disposal and inflammation [112]. From our study, it has become evident that Il1b expression in macrophages is significantly upregulated at 24 h exposure to empagliflozin. Thus, there is the possibility that in people with diabetes, empagliflozin can potentiate IL-1 β secretion from macrophages, which may explain the improvement in pancreatic beta cell function and sensitivity to glucose observed in the EMPA-REG BASALTM trial [109,110,111]. Further studies could be conducted to profile blood-derived macrophages and their IL-1β secretion levels in type 2 diabetes patients being treated with empagliflozin to explore a potential correlation. ## 4.1. Animal Work and Cell Culture All animal procedures and experimentation were approved by the UK’s Home Office under the Animals (Scientific Procedures) Act 1986, PPL 1390 ($\frac{70}{7354}$). In keeping with previous in vivo cardiometabolic studies [81,82,83,84], BMDM were prepared from low-density lipoprotein receptor knock-out mice (LdlrKO) and cultured as described before [113,114]. In brief, L929 Conditioned Medium (LCM) was used as a source of M-CSF for the differentiation of the macrophages. After 6 days of differentiation, LCM-containing medium was removed, and cells were washed three times in warm PBS and incubated in DMEM containing low endotoxin (≤10 EU/mL) $1\%$ FBS and 20 µg/mL gentamycin without any LCM before being treated with anti-diabetes drugs (metformin; Sigma-Aldrich, Gillingham, UK, empagliflozin; Generon, Slough, UK) for the concentrations and durations indicated. ## 4.2. Gene Expression Analysis Total RNA from BMDM was extracted with TRIzol Reagent (Invitrogen, Loughborough, UK). The sample concentration and purity was determined using a NanoDrop™ 1000 Spectrophotometer and cDNA was synthesized using the qScript cDNA Synthesis Kit (Quantabio, Leicestershire, UK). *Specific* genes were amplified and quantified by quantitative Real Time-PCR, using the PerfeCTa SYBR Green FastMix (Quantabio, Leicestershire, UK) on an MX3000p system (Agilent, Stockport, UK). Primer sequences are shown in Supplementary Table S1. The relative number of mRNAs was calculated using the comparative Ct method and normalized to the expression of cyclophilin. ## 4.3. In Silico Molecular Docking Simulation A high resolution (2.4 Å) 3D crystal structure of TLR2 (PDB ID: 3A7C) was selected from the protein data bank [115] and converted to PDB format. This structure was then processed to present the proper size, orientation, and rotations of the protein [116]. The processing was carried out in UCSF Chimera (version 1.14) (https://www.cgl.ucsf.edu/chimera/ (accessed on 16 December 2021) to remove non-standard amino acids, water molecules, ligands and ions, add missing hydrogen atoms, and to perform energy minimization of the protein structure [117]. The 3D structures of Zymosan (PubChem CID: 64689) and Empagliflozin (PubChem CID: 11949646) were obtained in sdf format from PubChem [118]. As total equalization of electronegativity of compounds (or ligands) lead to chemically unacceptable predictions, in order to prepare the ligands for docking simulation, partial charges were assigned to each compound following the Gasteiger method [119], followed by energy minimization in UCSF Chimera (version 1.14). After processing, these molecules were saved as ‘mol2’ files for molecular docking. The docking experiments were conducted with processed protein and ligands using PyRx 0.8 docking software [120]. The same process was repeated with a high resolution (2.8 Å) 3D crystal structure of Dectin-1 (PDB ID: 2CL8) to assess probable interaction with Zymosan (PubChem CID: 64689) and Empagliflozin (PubChem CID: 11949646). ## 4.4. Statistical Analysis Results are expressed as mean ± SEM. Comparisons within groups were made using one-way ANOVA with Dunnett’s correction applied. p ≤ 0.05 was considered statistically significant. ## 5. 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--- title: Traumatic Brain Injury Induces Microglial and Caspase3 Activation in the Retina authors: - Tamás Kovács-Öller - Renáta Zempléni - Boglárka Balogh - Gergely Szarka - Bálint Fazekas - Ádám J. Tengölics - Krisztina Amrein - Endre Czeiter - István Hernádi - András Büki - Béla Völgyi journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003323 doi: 10.3390/ijms24054451 license: CC BY 4.0 --- # Traumatic Brain Injury Induces Microglial and Caspase3 Activation in the Retina ## Abstract Traumatic brain injury (TBI) is among the main causes of sudden death after head trauma. These injuries can result in severe degeneration and neuronal cell death in the CNS, including the retina, which is a crucial part of the brain responsible for perceiving and transmitting visual information. The long-term effects of mild–repetitive TBI (rmTBI) are far less studied thus far, even though damage induced by repetitive injuries occurring in the brain is more common, especially amongst athletes. rmTBI can also have a detrimental effect on the retina and the pathophysiology of these injuries is likely to differ from severe TBI (sTBI) retinal injury. Here, we show how rmTBI and sTBI can differentially affect the retina. Our results indicate an increase in the number of activated microglial cells and Caspase3-positive cells in the retina in both traumatic models, suggesting a rise in the level of inflammation and cell death after TBI. The pattern of microglial activation appears distributed and widespread but differs amongst the various retinal layers. sTBI induced microglial activation in both the superficial and deep retinal layers. In contrast to sTBI, no significant change occurred following the repetitive mild injury in the superficial layer, only the deep layer (spanning from the inner nuclear layer to the outer plexiform layer) shows microglial activation. This difference suggests that alternate response mechanisms play a role in the case of the different TBI incidents. The Caspase3 activation pattern showed a uniform increase in both the superficial and deep layers of the retina. This suggests a different action in the course of the disease in sTBI and rmTBI models and points to the need for new diagnostic procedures. Our present results suggest that the retina might serve as such a model of head injuries since the retinal tissue reacts to both forms of TBI and is the most accessible part of the human brain. ## 1. Introduction The term traumatic brain injury (TBI) is used as a collective term for pathological changes due to external forces that can lead to physiological, cognitive, and psychosocial disorders of the central nervous system. It is most commonly caused by accidents, sports injuries, and falls [1]. These injuries can result in a variety of disorders, disabilities, and sometimes seizures [2]. Road traffic accidents often lead to severe head injuries that can be effectively reduced by road measures. Moreover, there is an increased risk of head injuries among elderly patients and athletes [3,4]. Categorization of different types of head injury is challenging, as—mainly due to the diverse directions and magnitude of physical forces besides widely varying environmental conditions—the location, type, and extent of the induced pathoanatomical and pathophysiological sequelae may substantially differ case by case [5]. The estimated rate of post-TBI and TBI-related deaths worldwide is more than 1.5 million per year [6], mostly as a result of the lack of diagnostic abilities and/or life-saving brain surgeries [7]. The intensity and speed of the different forces acting on the head determine the extent of tissue damage. The brain essentially moves in the cerebrospinal fluid and various harmful mechanical forces, including shear and rotation, induce the displacement of the brain and corresponding tissue damage [8]. Based on pathoanatomical considerations, these lesions can be divided into focal and diffuse types. Focal damage usually occurs at the site of the impact or on the contralateral side of the brain. Meanwhile, focal lesions (epidural, subdural, intracerebral hemorrhages, and contusions) are more often associated with moderate or severe head injuries in most TBI cases and a mixture of focal and diffuse (edema, hypoxic–ischemic injury, microvascular injury, diffuse neuronal injury, and diffuse axonal injury) types of pathological lesions develop [9]. Diffuse pathological lesions—triggered by the shearing and rotational forces to the head—may occur in remote regions of the CNS (e.g., retina) compared to the direct impact site. Based on the time course of the injury, we can speak of a primary injury that occurs at the time of the accident such as fractures and intrusions. On the other hand, secondary injury processes initiated at the moment of injury become clinically apparent hours or days after the initial impact (edema, ischemia, hypoxia, neuroinflammatory processes) and may develop even years or decades after the injury (such as chronic traumatic encephalopathy, post-traumatic stress disorder, dementia, or endocrine deficiencies), causing severe quality of life issues for the affected patients as well as a huge socio-economic burden [10]. Therefore, there is an unmet clinical need for efficient diagnostic (and prognostic) possibilities. The retina is not only one of our most important sensory organs, but it is also a part of our CNS, directly linked to the brain and located peripherally, thus providing easy access for diagnostic measures. Studies show that characteristic retinal TBI symptoms include photophobia, double or blurred vision, visual paralysis, optic nerve disorders, and damaged or changed image processing [11]. TBI also includes visual dysfunction, which, according to current data, occurs in up to $90\%$ of those affected by TBI [12]. Mapping these lesions and also milder effects on the retina may help to understand the pathophysiology of TBI and may be an indicative factor in screening for severe cases. Our work is important, pioneering research that seeks to expand our understanding of brain injuries and offers a potential diagnostic tool. Even when cellular and apoptotic lesions are present elsewhere in the brain, the retina can be a direct and most accessible indicator for TBI. However, at present, we lack the necessary information to connect direct retinal damage with TBI. Microglia are the resident immune cells in the brain, including the retina. They are immunocompetent cells constantly monitoring their environment to interact with possible threats. Microglial activation in the retina is present in a cohort of disease phenotypes [13,14], hence it is important to understand how they contribute to the pathophysiology. In the central nervous system (CNS) their activation ranges on a continuum from neuroprotective to neurotoxic [15]. Their vast activation can contribute to further deterioration of the disease phenotype in the neuronal tissue via pro-inflammatory and phagocytosis mechanisms [13,16]. Caspase3 (Casp3) is a central effector for apoptotic cell death. It can be widely activated in TBI [17], and retinal diseases or detrimental conditions [18]. Microglial activation is highly dependent on caspase activation [19]. To the best of our knowledge, our study is the first to show how the retina is affected by sTBI and rmTBI. The latter is caused by multiple low-level impacts common among athletes (especially boxing and soccer) and is increasingly recognized as a major cause of neurological diseases [20]. Our results show rising numbers of activated microglial cells as well as activated Casp3 (act-Casp3)-positive cells in the retina in both traumatic models. Our data reinforce views that emphasize the severity of rmTBI and recommend attention similar to that given to sTBI. Act-Casp3 is a common executor of different apoptotic pathways induced by various types of damage including ischemia, excitotoxicity, and radiation [21]. Microglia can show elevated levels of act-Casp3 without cellular death as they have a bypass mechanism to avoid apoptosis [19]. This suggests a different action in the course of the disease and points to new diagnostic procedures for TBI. ## 2. Results Throughout the treatment, we used three animal model groups: SHAM-operated, sTBI, and rmTBI, and investigated differences between them. The latter were treated with either a high-impact (2 m), single drop of a weight or five consecutive low-height (15 cm) weight drops on a skull-fixed helmet to mimic severe and repetitive–mild injuries and to be able to differentiate between their effects. Twenty-four hours after the last treatment, the animals were sacrificed, and their retinas were fixed for further experiments (Figure 1). ## 2.1. Effects of TBI on Retinal Microglia In both rmTBI and sTBI samples, extensive microglial activation could be observed on merged stacks of the superficial layer (SL) and the deep layer (DL) (Figure 2). This activation manifested in various morphological changes, including enlarged, disorganized soma, relative soma size increase, amoeboid and leaf-like structures on the dendritic endfeet, and aggregated occurrence of these activated microglial (MG) morphologies (details in Section 4.3 and the Table in Section 4.4). After counting and sorting microglial cells into activated/non-activated categories, according to the expressed morphological criteria (the Table in Section 4.4), we found that TBI resulted in a significant increase in the number of activated microglia in both the deep layer (mean = 43.3; Figure 3; Supplementary Table S1) and superficial MGs (mean = 64.35; Figure 3; Supplementary Table S1). However, this increase was observed only in sTBI among SL MGs, whereas only DL MGs were activated significantly in rmTBI (Figure 3). ## 2.2. Specific Caspase3 Activation due to Traumatic Brain Injury in the Superficial Layer of the Retina Act-Casp3 is a reliable marker to summarize apoptotic cell death [21], therefore, we used it to show widespread apoptosis in the retina. Act-Casp3 activation was analyzed first in the superficial layers of the retina, where Casp3 activation was already observed in confocal LSM images of both sTBI and rmTBI samples, which unfolded in two ways. On one hand, Casp3 was present in the nuclei or perinuclearly and in the cytosol of cells of a distinct cell population in the neurofilament layer, and on the other hand, it showed granular labeling in the ganglion cell layer (Figure 4c). We observed a large, 10.54× increase in the total number of act-Casp3 cells in sTBI, compared to SHAM (15.67 → 165.20), while a slightly smaller but still large 7.52× increase in activated cell number in rmTBI (15.67 → 117) (Figure 4b, Supplementary Table S1). We should note that in the case of rmTBI, the standard deviation of our sample was much larger, but still showed a significant prominent increment (Figure 4b, Supplementary Table S1). The large number of act-Casp3 cells described was identified using several markers (non-correlated markings are not provided here). Finally, Casp3 activation in SL was found in colocalizations with the two markers. These markers were glial–fibrillar acidic protein (GFAP) and ionized calcium-binding adapter molecule 1 (Iba1), the signaling of which is mainly restricted to astrocytes and microglia, respectively, in the retina [22,23]. Using the related markers, we identified astrocytes and microglia in SL as the main source of Casp3+ labeling (Figure 4c). Interestingly, the localization of the label differed between the two cell types. In GFAP+ astrocytes, the Casp3 signal was clearly restricted to the nucleus and its surrounding region, whereas the Casp3 localization of microglia was more limited to the protrusions. This could be observed in most of the cells in correlation with the Iba1 microglial marker (Figure 4c, arrows). ## 2.3. Loss of Axonal Connections due to Traumatic Brain Injury in the Neurofilament Layer of the Retina Axonal injury and loss are the common concomitants in TBI, hence in addition to the obvious microglial activation and Casp3 activation we tested the SL of the rat retina with SMI312 (neurofilament H) labeling (prepared using SMI31 and 32 together) that showed a decline in the axonal numbers in the neurofilament layer (NFL) of the sTBI and rmTBI retinas in comparison to the SHAM (Figure 5a). ## 2.4. Caspase3 Is Activated due to Traumatic Brain Injury in the DL of the Retina The DL is rich in cellular elements, including bipolar, amacrine, and horizontal cells in addition to the MGs found here, interacting with these cell types. Here, we tested if the two TBI models have a different effect on these cells. Subsequent analyses of the Casp3 labeling in the DL unfolded in two ways. A massive (21.5- and 39.9-fold) increase in Casp3 activation was obvious after counting the individual cells with the help of NT labeling (Figure 6b,c, Supplementary Table S3) in both the rm- and sTBI samples. After closer examination, we identified the Casp3+ cells mainly as bipolar cells based on their soma diameters (mainly from 4–7 µm) [24] and clear colabeling with NT. A second cohort of cells were not NT labeled with bright Casp3 labeling. The soma diameters of these latter cells were larger compared to bipolar cells and the somas were located distally from the innermost sublamina of the INL where amacrine cells could be observed (based on the strong NT labels and the relatively large, 7–14 µm somata [25]). Therefore, this second cohort of non-NT-labeled Casp3+ cells were identified as Müller cells. ## 3. Discussion Retinal ganglion cells (RGCs) actively project their axons to over 40 subcortical brain regions [26,27]. RGC axons are openly exposed to the effects of different injuries (sTBI or rmTBI) and the retina can actively intercept signals from the brain tissue, projected by axonal connections and indicated by the cells of the retina [28,29], including MGs as primary immune cells. ## 3.1. Microglial Activation due to Traumatic Brain Injury Based on our results, microglial activation clearly occurred in both the sTBI and rmTBI models. This suggests that the assumption from previous research about only $40\%$ of TBI patients having a negative retinal impact appears to be highly underestimated [12,29]. Surprisingly, although we observed a high level of activation in sTBI, the data measured in rmTBI were close to those measured in sTBI (Figure 2 and Figure 3), which may be alarming in cases where someone (e.g., in sports such as football, boxing) is continuously exposed to minor cranial injuries [30]. SMI312 labels ganglion cells, including their axons in control retinas. Axons in the NFL show a decline in the SMI312 labeling after both types of treatment (Figure 5), similarly to other related studies working with synaptophysin [29]. Compared to that, the microglia show differential SL/DL activation in sTBI and rmTBI. Our results show no significant microglial activation in the SL after rmTBI, only after sTBI, whereas in the deep layer microglia are similarly activated in the DL of the retina (Figure 3). The possible explanation for this could be the different effect that is mediated by rmTBI but further studies should be carried out to unravel the background of this difference in activation. It is important to mention that microglial cells can have different morphologies in the retina following the spatial organization patterns of other cells but the rat retina does not have a fovea (nor a pronounced central zone or visual stripe) as in many other animals, that may result in microglial differences [31], therefore, in our study we did not analyze these topological variations. However, to avoid any baseline difference our measurements were made from a mid-central region of the rat retina. Microglial cells continuously scan their environment, and their activation state faithfully reflects the state of the retina and changes that are taking place in the tissue, hard-wired to diverse parts of the brain. The activation status of microglia may be different (M0, -1, -2) and treatment options may vary accordingly. Many drugs (e.g., CB2 inverse agonists) can affect the activation state of microglia and can reverse the noxious inflammatory M1 phase to the reparative M2 [32]. The differential activation of microglia can be of further interest for the right treatment of TBI-induced disease. However, in addition to the choice of treatment options, activation of microglial cells could be used as a biomarker of TBI in the future, as these cells may be visualized by a combination of different staining procedures and fluorescent coherent optical tomography (fOCT) methods [33]. As not all lesions can be traced with current imaging methods, the development of new in vivo procedures is needed. As shown before, vital stains can help in aiming for different cell types in the retina, such as NeuroTrace in pericytes [34]. However, no real breakthrough has yet been made in the development of imaging methods or microglia-specific live stains in the retina or the brain. Only one technique, adaptive optics-based imaging, could be able to breach this limitation at present, where we can see individual cell morphologies in the living eye [35]. Activated microglia can release a number of factors (e.g., tumor necrosis factor α, interleukin-1β) that can induce inflammatory and degenerative processes in the retina [36]. Unfortunately, we are not able provide any labeling on these at this time, only Casp3, however, in the future labeling these factors could indicate microglial state since the neuroprotective effect of microglia is also well known, which can be a major help in preserving vision [37]. The detection and further examination of these factors represent great advances in determining the exact role of microglia in TBI or measuring their activation state. ## 3.2. Caspase3 Activation, Cell Death Marker Caspases play a role in both apoptosis and inflammatory processes [19,38,39]. Animal studies have demonstrated activation of caspases [3, 7, 9, 12] in TBI in the brain [40,41], where Casp3 activation is a key, cumulative marker of cell death since it signals the onset of both the intrinsic and extrinsic pathways of apoptosis. Studies suggest dimerization as part of activation that binds inactive monomers together [42,43]. We chose Casp3, together with other markers, to summarize apoptotic processes. One of the main markers that we used as a global cell marker is NT640. This fluoro-Nissl stain labels neuronal cells and vascular cells (mainly pericytes) in the fixed retina and is also capable of labeling living cells if used in the right concentration [34], therefore it was the perfect candidate to pair with Casp3 to see how the neurons and some other cells are affected. Other markers such as GFAP only show astrocytes and strongly affected Müller cell endfeet [44]. According to our results, the SL clearly indicates Casp3 activation in GFAP+ cells, which we identified as astrocytes. Astrocyte activation also occurs in high intraocular pressure (IOP) conditions, such as glaucoma [45]. Further markers can subserve to identify apoptotic cell types. However, in the DL of the retina, it is difficult to identify distinct cell types expressing the Casp3+ signal due to the greater number of cells, the many cell types, the relatively small soma sizes as well as the lack of cell type-specific markers (e.g., amacrine, bipolar subtypes). We, however, tried to underline the fact that bipolar and amacrine cells could be easily differentiated based on their soma size. Previous Prox1 labeling in the INL to determine cell size differences showed ~$35\%$ amacrine vs. bipolar size difference (amacrine diameters for cat: 9.65 ± 0.29 μm, $$n = 9$$; rat: 8.27 ± 0.14 μm, $$n = 15$$; mouse: 9.33 ± 0.19 μm, $$n = 21$$, vs. bipolar: cat: 6.09 ± 0.09 μm, $$n = 238$$, $p \leq 0.001$, rat: 5.33 ± 0.14 μm, $$n = 344$$, $p \leq 0.001$, mouse: 6.30 ± 0.11 μm, $$n = 379$$, $p \leq 0.001$ in t-test against horizontal cell profiles, in [46]). On the other hand, various cell types involved can be more easily identified with cell-type-specific markers labeling the SL cells with fine morphological detail, therefore we used SMI312 and GFAP. By quantifying the labeling, and also adding SMI312 and GFAP, resulting in clear cellular morphology, we were able to identify the activated cells. In the GFAP+ population, the cells’ nuclei were colabeled with Casp3, and we were able to visualize subcellular granular Casp3+ labeling colocalized with Iba1. As GFAP labels the astrocytes, and Iba1 the MGs, in the retina [18,47], we identified them as the most affected population in both TBI models. However, the differential labels in the two cell populations may indicate that Casp3 might have different effects on them. The neuronal marker SMI312, in some cells, coexpressed with Casp3, indicates the involvement of RGCs, however, we did not encounter extensive labeling of neurons. The axonal degeneration is obvious by the lack of SMI312+ axonal labeling in both sTBI and rmTBI. This result thus coincided with neuronal survival in similar works by other research groups [48]. However, it may be that more neuronal Casp3 activation could have been observed with longer survival time, giving more time for apoptotic processes. The extent of diffuse axonal injury (DAI) in sTBI and rmTBI may come from other brain areas. This type of injury first arises in the axonal head and by disorganization of the cytoskeleton and transport mechanisms, which in turn deteriorates the axon and the soma of the affected cell through a Ca2+ and calpain-induced process [49]. Even now, it is still a matter of debate if the surviving GCs are able to maintain normal visual function in the long term [48,49,50], thus further studies are required in the future on this subject. In addition to neuronal colocalization, the use of GFAP was evident in the retina, as activation of astrocytes by TBI could also be expected. The results we obtained show that astrocytes began large-scale mass activation of Casp3, providing a clear sign of apoptosis. The astrocyte network is responsible for the health of retinal neurons by maintaining homeostasis and involvement in the blood–retinal barrier [51]. We observed Casp3 activation of microglia in both rm- and sTBI. However, it is important to note that activation of Casp3 in microglia does not necessarily imply a commitment toward cell death, as these cells have a bypass mechanism to avoid cell death. In microglial cells, various inflammatory factors induce the activation of Casp8 and then Casp3. Active Casp3, in turn, promotes the activation of microglial inflammatory pathways through a protein kinase Cδ-dependent pathway without induction of cell death [19]. Activation of Casp3 occurs as a two-step process in which the zymogen is first cleaved by upstream caspases, such as Casp8, to form an intermediate but active cytoplasmic p19/p12 complex. An autocatalytic process then creates the fully mature form of the enzyme p17/p12, which is then transferred to the nucleus. Induction of the cellular inhibitor of apoptosis protein 2 (cIAP2) upon microglial activation prevents the conversion of the p19 subunit of Casp3 to the p17 subunit, which is responsible for the cessation of Casp3 activity. By reversing the cIAP2-dependent process, the repressive effects are exerted, reactivate the inflammatory function of microglial cells, and may eventually promote their death [52]. We can assume that somehow Casp3 accumulation might act as a key for phenotype change. Considering this, however, in our case we do not expect extensive cell death in many Casp3+ microglia. Instead, our results, as such, are further evidence of the activation of microglial cells beyond the morphological features. These microglia do not necessarily induce cell death and phagocytes but may be involved in tissue protection [52] for cells in which Casp3 activation is not associated with the process. Therefore, Casp3 activation can be an additional marker for TBI. ## 3.3. Fate of Different Cell Types under the Influence of TBI As mentioned in combination with Casp3, other cell-specific markers can be identified. However, with the markers we used, we could only draw the following conclusions. Only a limited number of markers could be used in the experiments. Unfortunately, we could not coadminister SMI312 with Casp3 in the entire sample set due to the lack of available secondary channels in IHC. However, no cell-specific Casp3 activation was examined with further specific markers, but damage to other cell types could not be completely ruled out. This can be observed through further experiments in the future. GFAP may be expressed in Müller cell endings [45] in some cases due to severe damage, however, no Müller cell endings were observed with the GFAP label, morphologically, based on our experiments. Since no Müller cell-specific marker was used (e.g., glutamine synthetase, Sox9, RLBP9; [53]), their involvement cannot be completely ruled out based on our study. SMI312 labels both the non-phosphorylated and phosphorylated neurofilament H (NF-H) and is therefore specific for RGCs [54]. This marker potentially labels living cells, hence the intermediate filaments decompose in apoptosis [55]. NF-H can also be detected in serum after the onset of DAI, peaking at 12–48 h after injury [49]. NF-H is considered the most convenient marker of DAI diagnosis and, together with MG imaging, this might be the next step for a more accurate diagnosis of TBI pathology in the future. In conclusion, we showed that both sTBI and rmTBI comparably had a detrimental effect on the retina with the exception of DL activation, where rmTBI had less effect. We showed that act-Casp3 is elevated in numerous cells, identifying astrocytes and microglia as major contributors. In the DL, act-Casp3 is present in bipolar and Müller cells. We also identified a progressive decline in SMI312+ axonal bundles suggesting an interference with further cellular connections. Our results highlight the importance of retinal involvement in TBI and suggest that monitoring the retina’s health status could be utilized as a future biomarker tool for diagnostic purposes, able to detect the fine changes shown here. ## 4.1. Animals and Preparation Animal handling, housing, and experimental procedures were reviewed and approved by the ethical committee of the University of Pécs (BA$\frac{02}{2000}$-$\frac{69}{2017}$). Adult, male Long Evans rats ($$n = 12$$, Charles River Laboratory, Göttingen, Germany) weighing 300–400 g were used in the experiment. All animals were treated in accordance with the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. All efforts were made to minimize pain and discomfort during the experiments. TBI injuries were performed identically to Tadepalli et al. [ 56]. The methodological background had been established and the outcomes of both sTBI and rmTBI were proven here to similarly affect the brain. Briefly, to induce experimental TBI, we used an impact acceleration weight-drop model, originally published by Marmarou and Foda [57,58,59,60]. The steps of the surgical protocol are explained briefly as follows. Anesthesia was induced in an induction box with $5\%$ isoflurane (Baxter, Budapest, Hungary) in a 70:30 N2:O2 gas mixture. Once the anesthesia stabilized, we fixed the animal’s head in a stereotaxic frame. From this point, the anesthesia was carried out with $2\%$ isoflurane in the same gas mixture. After removing the hair from the animal’s scalp, we made a midline incision and removed the periosteum associated with the top of the skull. Halfway between the exposed bregma and lambda sutures, we fixed a stainless-steel disc, the so-called “helmet”, directly to the bone with cyanoacrylate glue. Then, we laid the animal on a foam bed in a prone position. The helmet was positioned centrally under s weight-leading plexiglass tube. Experimental diffuse TBI was induced by dropping the weight from the height corresponding to the desired severity level. After TBI induction, the helmet was removed, and the surgical area was cleaned and disinfected. The wound was sutured, and the animal was returned to its cage to recover. Through the surgical procedure, the physiologic parameters of the animals were monitored by a pulse oximeter (MouseOx Plus, Starr Life Corp., Oakmont, PA, USA). Body temperature was monitored by the Homothermic Monitoring System (Harvard Apparatus, Holliston, MA, USA) and maintained with a heating pad on the same device at 37 °C. To investigate the acute pathological effects of experimental diffuse TBI on the retina, we divided the animals into 3 groups ($$n = 4$$ in each group). In the first, single severe TBI (sTBI) group, we induced the injury with a 450 g weight from a 2 m height. In the second, repetitive mild TBI (rmTBI), group we used the same weight from a 15 cm height 5 times with 24 h intervals. Finally, to eliminate the possible effects of anesthesia/environmental conditions, our third group (SHAM) did not receive weight-drop treatment, only anesthesia, and the surgical protocol of fixing the helmet on the skull. This experimental design allowed us to investigate pathological alterations between injuries of different degrees of severity and frequency. Following the treatments, the animals were sacrificed after 24 h. Control and TBI rats were perfused transcardially with $4\%$ PFA ($4\%$ paraformaldehyde in PBS: 137 mM NaCl; 2.7 mM KCl; 10 mM Na2HPO4·7H2O, pH 7.4), and their eyes were immediately removed. The eyes were dissected in PBS by removing the cornea and lens. The resulting eyecups were additionally fixed in $4\%$ PFA at room temperature for 15 min for better sample retention. After washing them three times for 10 min in PBS, the retinas were dissected from the eyecups, or the eyecups were kept for up to 3 weeks in $0.05\%$ Na-azide in PBS at 4 °C until processed (for details, see Figure 1). ## 4.2. Immunohistochemistry Flat-mounted retinas were blocked in 100 μL of CTA ($5\%$ Chemiblocker, $0.5\%$ TritonX-100, $0.05\%$ Na-azide in PBS) overnight, room temp., humidified. After blocking, the retinas were treated with the primary antibodies (1000× + 1000× mouse SMI31 + SMI32 = SMI312, NE1022/NE1023—Calbiochem; 1000× rabbit Caspase3, AF835—NovusBio; 2000× guinea pig Iba1, 234,004—SySy), diluted in CTA, for 48 h, room temperature (RT). Retinas were incubated for 48 h at RT. After subsequent washing in PBS, three times, secondary antibodies were applied: 500× anti-rabbit Cy3 (715-165-150—Jackson), 1000× anti-mouse A488 (A11017—Invitrogen), and 1000× anti-mouse A647 (A21237—Invitrogen) or anti-guinea pig A647 (A21450—Invitrogen) in CTA, and incubated overnight at room temperature (see Table 1 for antibodies). After washing three times for 10 min in PBS, they were coverslipped with Vectashield (Vector Laboratories, Peterborough, UK) using coverslip nr. 1 (protocol based on and previously validated in [18,61]). ## 4.3. Microscopy Retinas were inspected using a Zeiss LSM 710 confocal laser scanning microscope (Plan Apochromat 10×, 20×, and 63× objectives (NA: 0.45, 0.8, 1.4, Carl Zeiss Inc., Jena, Germany)) with normalized laser power and filter settings making 1.5 and 0.5 μm thin optical sections (further details in Balogh, 2021 [18]). ## 4.4. Measurement of Microglial and Casp3 Activation All measurements were performed using FIJI (NIH, Bethesda, MD, USA, [62]). First, we performed two z-merges from the 5–5 optical stacks (3.75 µm) for the superficial and deep regions of MGs using only scans from mid-central retinal regions. The microglia were separated from the other signals based on their expression of ionized calcium-binding adapter molecule 1 (Iba1). Cells were manually grouped one by one according to their morphologies into activated and non-activated, using the “Cell-counter” plugin in FIJI, according to the morphological classifications of Lawson and colleagues and others [63,64,65]. Only cells with the whole visible area were included, we omitted the ones on the edges. In order to objectively verify the choices of the trained observers, reconstructions of the dendritic arbor of every fifth recorded MG were created using the Simple Neurite Tracer plugin [66] of FIJI. Subsequently, *Sholl analysis* was performed (1 μm radius) and the following relevant parameters were measured (Green and colleagues [67]): [1] peak values, [2] total number of dendrites, [3] total length of dendrites, [4] total number of branches, [5] path orders, [6] convex hull size, elongation, and roundness, utilizing the same plugin. Finally, the maximum cross-sectional area of the soma and the dendritic field was measured, from which a ratio was calculated (Supplementary Figure S1). These parameters were used to compare the cells classified into resting and reactive morphologies by the trained observer, confirming their choices, and they were also used to determine the effect of the TBI treatment on the MGs in the retina, an example of which can be seen in Supplementary Figure S1f–h. We divided superficial (SL) and deep layers (DL) in the z-stacks for MGs in the 20× images following the layers of blood vessels, overlapping NFL+GCL for SL, and INL to ONL for DL. A “z-merge” was carried out from 5 consecutive optical sections. During microglial activation, counting and classifying cells with different morphologies ($$n = 1957$$ cells in 12 retinas) were performed one by one using the “Cell-counter” plugin in FIJI. Differential morphological characteristics listed in Table 2 (based on the work of Davis and his colleagues [68]) were considered during selection. To preserve objectivity, the names of sample images were randomized. To examine Casp3 activation in the SL and DL, we used the same z-merges, and the activated cells were separated from the background using other signals (GFAP, SMI312) together with the act-Casp3 signal to define retinal layer borders better and possible cell types affected. ## 4.5. Statistical Analysis Data were curated in MS Excel. One-way ANOVA analyses were performed using Origin18 (Origin, Version 2018b, OriginLab Corporation, Northampton, MA, USA) and JASP (JASP Team [2022] (Version 0.16.3)). 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--- title: Influence of Left Ventricular Diastolic Dysfunction on the Diagnostic Performance of Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve authors: - Zhixin Xie - Tianlong Wu - Jing Mu - Ping Zhang - Xuan Wang - Tao Liang - Yihan Weng - Jianfang Luo - Huimin Yu journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003343 doi: 10.3390/jcm12051724 license: CC BY 4.0 --- # Influence of Left Ventricular Diastolic Dysfunction on the Diagnostic Performance of Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve ## Abstract Objectives: Our study aimed to demonstrate the influence of left ventricular (LV) diastolic dysfunction on the diagnostic performance of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR). Methods: One hundred vessels from 90 patients were retrospectively analyzed. All patients underwent echocardiography, coronary computed tomography angiography (CCTA), CT-FFR, invasive coronary angiography (ICA), and fractional flow reserve (FFR). The study population was divided into normal and dysfunction groups according to the LV diastolic function, and the diagnostic performance in both groups was assessed. Results: There was a good correlation between CT-FFR and FFR ($R = 0.768$ $p \leq 0.001$) on a per-vessel basis. The sensitivity, specificity, and accuracy were $82.3\%$, $81.8\%$, and $82\%$, respectively. The sensitivity, specificity, and accuracy were $84.6\%$, $88.5\%$, and $87.2\%$ in the normal group and $81\%$, $77.5\%$, and $78.7\%$ in the dysfunction group, respectively. CT-FFR showed no statistically significant difference in the AUC in the normal group vs. the dysfunction group (AUC: 0.920 [$95\%$ CI 0.787–0.983] vs. 0.871 [$95\%$ CI 0.761–0.943], $Z = 0.772$ $$p \leq 0.440$$). However, there was still a good correlation between CT-FFR and FFR in the normal group ($R = 0.767$, $p \leq 0.001$) and dysfunction group ($R = 0.767$ $p \leq 0.001$). Conclusions: LV diastolic dysfunction had no effect on the diagnostic accuracy of CT-FFR. CT-FFR has good diagnostic performance in both LV diastolic dysfunction and the normal group and can be used as an effective tool for finding lesion-specific ischemia while screening for arterial disease in patients. ## 1. Introduction Fractional flow reserve (FFR) is the gold standard for evaluating ischemic lesions [1]. Compared with angiography-guided revascularization strategies, FFR-guided PCI has been shown to improve clinical outcomes with long-term follow-up [2,3]. However, the measurement of FFR is a costly and invasive procedure and can inherently increase the risk of serious complications. In recent years, CT-FFR has been rapidly developing. Several prospective multicenter studies have shown that CT-FFR can be used to identify ischemic stenosis. Compared with FFR, CT-FFR has good diagnostic performance, with high sensitivity and specificity to identify whether there are hemodynamically related disorders, and CT-FFR does not require additional interventional procedures or the use of drugs such as adenosine to induce coronary congestion [4,5,6]. Multiple factors, such as motion artifacts, image quality, calcification, artifacts, and microcirculation disturbance, affect the accuracy of CT-FFR [7,8,9]. The impact of diastolic dysfunction on its diagnostic performance has not been reported thus far. Studies have shown that microcirculation disturbance is an important mechanism of LV diastolic dysfunction, which is affected by coronary blood congestion [9,10]. The abnormal early diastolic function of patients with coronary heart disease is related to myocardial ischemia and hypoxia caused by coronary stenosis and gradually increases with the expansion of the stenosis range and the aggravation of the degree of stenosis. In addition, diastolic function precedes systolic function. Abnormality occurs [11], so LV diastolic dysfunction may have an impact on CT-FFR values, which, in turn, leads to differences in the diagnostic performance of CT-FFR. Our study aimed to investigate the diagnostic performance of CT-FFR and explore its consistency in LV normal and dysfunctional diastolic function using invasive FFR as the standard of reference. ## 2. Materials and Methods We conducted a retrospective observational study. The flowchart of the study is presented in Figure 1. The study was approved by the Guangdong Provincial People’s Hospital Ethics Committee. Since the retrospective nature of the study involved only chart review, the patient consent requirement was waived. ## 2.1. Study Population We retrospectively analyzed 100 vessels from 90 patients who underwent CCTA and coronary angiography (CAG) in Guangdong Provincial People’s Hospital from 2015 to March 2022. These patients underwent CCTA and echocardiography testing 90 days prior to coronary angiography and invasive FFR testing for at least one coronary lesion. The exclusion criteria included: previous coronary artery bypass surgery or stenting, poor echocardiographic images for evaluation, severe valvular disease, severe tortuous or calcified lesions, severe left main disease, severe artifacts, dislocation, noise and calcification present in the CCTA image, causing the CT-FFR analysis to be impossible, and an unqualified pressure curve for FFR analysis. ## 2.2. Coronary Computed Tomography Angiography Analysis The CTA examination was performed on the patients using Somatom Definition Flash, a Siemens second-generation dual-source CT scanner. Due to the high time resolution of dual-source CT, CCTA has a wide range of applications and does not require human control of the heart rate. Prior to the examination, the patients were trained to hold their breath and were connected to ECG gating. The subject would lay on the examination bed with their head advanced, hands raised, and heart placed in the scanning center. The adaptive prospective ECG gating sequence scanning mode was adopted, relative value scanning was performed, and the scanning time window was set to 30~$70\%$. The scanning range was 1 cm below the tracheal bifurcation to the heart diaphragm. The scanning parameters were as follows: automatic real-time dynamic radiation dose adjustment technology (CAREDose 4D), reference tube voltage 120 kV, reference tube current 380 mAs, elastic rotation time (automatically adjusted according to the heart rate), and width of the collimator 128 × 0.6 mm. The reconstruction parameters were as follows: reconstruction layer thickness 1 mm. The interval between the reconstruction layers was 0.7 mm. The reconstruction algorithm SAFIRE iterative reconstruction was level 3. The contrast agent injection scheme was as follows: 70 mL of the nonionic contrast agent Iopamiro 370 was injected through a cubital vein at a speed of 5 mL/s. After the contrast agent injection, 30 mL normal saline was used to flush the tube at a flow rate of 5 mL/s. Blous tracking technology was used to start scanning. The contrast agent was injected, and tracking started 10 s later. The tracking level was 1 cm below the tracheal bifurcation, and the area of interest was located in the ascending aorta. There were four groups of images of the automatic optimal diastolic period, automatic optimal systolic period, and manual $45\%$ and manual $75\%$ were reconstructed after scanning. All images were uploaded to the workstation, and the images were reconstructed and analyzed by 2 experienced radiologists. ## 2.3. CT-FFR Analysis The CT-FFR calculation and coronary artery remodeling were performed by Ray-sight Inc. using a blinded protocol. The process involved four main steps: [1] anatomic model reconstruction, [2] centerline definition, [3] boundary condition, and [4] CT-FFR calculation. Anatomic model reconstruction. The 3-dimensional patient-specific model, including the heart and coronary artery tree, was automatically derived from CTA. During the model construction, the Frangi algorithm was used to extract the chambers, myocardium, and aorta. Coronary artery segmentation was performed using an automatically generated centerline model and grown. For the finite element method used in calculating CT-FFR, a mesh model including millions of vertices was generated from the geometric model of the aorta and coronary artery tree. Centerline definition. On the basis of the anatomic model, we extracted the centerline of each coronary artery, which was useful for locating the boundary regions (coronary outlets) and setting boundary conditions. First, the cross-sectional image perpendicular to the centerline was reconstructed, and a region-of-interest contour (1 mm2) located at the center of the cross-sectional image was defined. Then, the mean Hounsfield unit value of the region of interest was calculated from the ostium to the distal level, where the vessel cross-sectional area fell below 2.0 mm2. Boundary conditions. We used patient-individualized brachial pressure to derive the aortic pressure, and the mean aortic pressure was coupled at the inlet boundary. As for the outlet boundary conditions, the blood flow based on the cardiac output and myocardial mass were computed and coupled. Specifically, the total resting blood flow (including aorta and coronary) was estimated from the cardiac output, while the total resting coronary blood flow was computed using the myocardial mass. To estimate hyperemia, the distal resistance of each artery and aortic pressure were reduced to 0.24 times and 0.8 times the resting state value, respectively [12]. CT-FFR calculation. A CFD simulation was performed on a standard desktop workstation that used a finite volume approach to solve the Navier–Stokes equations. Blood was treated as a noncompressible, viscous Newtonian fluid, and the vessel wall was assumed to be rigid, with a no-slip boundary condition. Finally, the velocity and pressure at each vertex of the mesh model was generated, and the CT-FFR values were calculated as the pressure ratio. The CT-FFR software used in this study has been validated previously in a prospective, multicenter study [13]. ## 2.4. Invasive Angiography and FFR Measurement Invasive angiography was recorded by a digital subtraction angiography machine (Allura, Philips, Amsterdam, the Netherlands) at 15 frames, either through the femoral or the radial approach. Nitroglycerin was injected into the coronary artery before coronary angiography, and manual or high-pressure injection via a syringe was performed for injecting the nonionic contrast medium. In this study, FFR (RadiAnalyzer Xpress) was performed during ICA in at least 1 vessel with a diameter 2 mm and $10\%$ to $90\%$ visual stenosis and was chosen at the discretion of the operator blinded to the CT findings. The pressure wire (St. Jude’s Medical) was calibrated and electronically equalized with the aortic pressure before being placed in the distal third of the coronary artery being interrogated. Intracoronary glyceryl trinitrate (100 mm) was injected to minimize vasospasm. Intravenous adenosine was administered (140 mm/kg per min) through an intravenous line in the antecubital fossa. At steady-state hyperemia, FFR was recorded and calculated by dividing the mean coronary pressure measured with the pressure sensor placed distally to the stenosis by the mean aortic pressure measured through the guide catheter. The pressure sensor was then pulled back into the tip of the guiding catheter, and only runs with ≤0.03 drift were accepted for analysis. ## 2.5. Echocardiographic Assessment of Left Ventricular Diastolic Function The Philips i E33 color Doppler ultrasound system, probe S5-1, frequency 1~5 MHz and the GE vivid dimension color Doppler ultrasound system, probe M3S, frequency 1.5~4.2 MHz were used in this study. According to the 2016 American Echocardiography Society (ASE) guidelines [14], the assessment of diastolic dysfunction included an evaluation of the septal/lateral tissue Doppler imaging (TDI) e0 velocity, E/e0 ratio, mitral valve E/A ratio, tricuspid regurgitation (TR) velocity, and left atrial volume index (LAVI). ## 2.6. Statistical Analysis Continuous variables were expressed as the mean ± standard deviation or the median (interquartile range), categorical variables were expressed as frequencies (percentages), and the Kolmogorov–Smirnov test was used to assess the normality of the distribution of the continuous variables. Normally or nonnormally distributed variables were compared using independent samples t-tests or Mann–Whitney tests, respectively. FFR was indicated as the gold standard diagnosis of lesion-specific ischemia with a cutoff value of 0.80, which was consistent with most contemporary studies. The diagnostic performance of CT-FFR is expressed by a receiver operating characteristic curve, which is acceptable if the area under the curve (AUC) is greater than 0.70. Spearman’s correlation was used to analyze the correlation between CT-FFR and invasive FFR values. The Bland–Altman statistic was used to plot the difference between CT-FFR and mean invasive FFR. The Z test was performed to compare the diagnostic performance of CT-FFR in the patients in the normal and dysfunction groups. All statistics were performed using IBM SPSS version 25 and MedCalc software. ## 3.1. Baseline Characteristics The patient characteristics and echocardiographic parameters are shown in Table 1. A total of $67.8\%$ of the patients were male, the mean age was 64.1 years, 70 vessels were LAD, 12 vessels were LCX, 18 vessels were RCA, and the patients with normal diastolic function were assigned to one group ($$n = 39$$). The patients with dysfunctional diastolic function were assigned to the second group ($$n = 61$$). Figure 2 shows typical cases examined by CCTA, CT-FFR, and CAG in the left anterior descending branch. ## 3.2. Diagnostic Performance of CT-FFR Compared with FFR Consistent with most contemporary studies, we used an FFR cutoff of 0.80, and the following analysis was performed at the per-vessel level. Table 2 shows CT-FFR in relation to FFR, and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were $82.3\%$, $81.8\%$, $82\%$, $70\%$, and $90\%$, respectively. As shown in Figure 3, the CT-FFR was well correlated with the invasive FFR (R2 = 0.768, $p \leq 0.001$), and the AUC was 0.892 [$95\%$ CI 0.814–0.945]. Further analysis of the systematic differences was performed, which indicated that the mean difference between FFR and CT-FFR was 0.036, and the $95\%$ confidence interval was 0.022 to 0.05. ## 3.3. Diagnostic Performance and Correlation of CT-FFR to Invasive FFR between the Normal and Dysfunction Groups in Left Ventricular Diastolic Function As shown in Table 2, the sensitivity, specificity, accuracy positive predictive value, and negative predictive value were $84.6\%$, $88.5\%$, $87.2\%$, $78.6\%$, and $92\%$ in the LV diastolic normal group vs. $81\%$, $77.5\%$, $78.7\%$, $65.4\%$, and $88.6\%$ in the dysfunction group. As shown in Figure 4, CT-FFR showed no statistically significant difference in the area under the receiver operating characteristic curve (AUC) in the normal group vs. the dysfunction group (AUC: 0.920 [$95\%$ CI 0.787–0.983] vs. 0.871 [$95\%$ CI 0.761–0.943], $Z = 0.772$, $$p \leq 0.440$$). There was still a good correlation between CT-FFR in the normal group ($R = 0.767$, $p \leq 0.001$), mean difference: 0.035, and $95\%$ confidence interval 0.018–0.053 vs. the dysfunction group ($R = 0.767$, $p \leq 0.001$), mean difference: 0.037, and $95\%$ confidence interval 0.017–0.057. ## 4. Discussion Our study focused on the diagnostic performance of CT-FFR and found that CT-FFR had good diagnostic accuracy compared with FFR, which was maintained in the subgroup analysis of different diastolic functions. LV diastolic dysfunction did not affect the diagnostic performance of CT-FFR. FFR is currently the “gold standard” for assessing whether coronary stenosis leads to myocardial ischemia. Under the guidance of FFR, the effectiveness of a coronary intervention can be increased, and unnecessary stenting can be reduced. However, FFR is an invasive technique that requires a pressure guide wire to be placed into the diseased vessel through a catheter under coronary angiography. The cost is expensive, and there is a risk of damage to the vessel during the operation, which limits the clinical application of this test in China [15,16,17]. In recent years, coronary computed tomography angiography-derived fractional flow reverse (CT-FFR) has injected new vitality into the assessment of coronary function. Different from the traditional and invasive gold standard for coronary functional assessment, CT-FFR technology is a noninvasive detection method based on coronary CT that combines coronary anatomy and a functional assessment. The functional analysis of simulated fluid dynamics has the advantages of CTA and FFR at the same time. It has certain advantages in identifying vascular stenosis and guiding treatment strategies. Early DISCOVER-FLOW and DeFACTO studies confirmed that CT-FFR has good diagnostic efficiency, sensitivity, and specificity [4,18]. CT-FFR is mainly used in outpatient clinics and has been shown to reduce the number of unnecessary CAG procedures in patients with nonfunctional significant CAD [19,20]. Donnelly et al. [ 21] demonstrated CT-FFR with $91\%$ sensitivity, $72\%$ specificity, and $78\%$ accuracy; van Hamersvelt et al. [ 22] also demonstrated that CT-FFR has a sensitivity of $89\%$, a specificity of $78\%$, and an accuracy of $83\%$, all comparable to the results of our current study. We also observed a good correlation between CT-FFR and FFR by simple linear analysis and Bland–Altman plots. This is consistent with our research. Studies have shown that microcirculation disturbance is an important mechanism of LV dysfunction [9,10]. Long-term microcirculation disturbance will cause myocardial ischemia and hypoxia, which will cause myocardial compensatory hypertrophy, and eventually, decompensation of the cardiac function will occur with the progression of the disease. Due to the imbalance of myocardial blood supply and oxygen supply and abnormal ventricular wall motion, abnormal calcium ion transport in myocardial cells and poor diastolic coordination affect the cardiac compliance, resulting in cardiac diastolic and systolic dysfunction. A number of previous studies have shown that, in the early stage of coronary heart disease, the diastolic function is abnormal before the systolic function [23]. Therefore, the abnormal diastolic function in patients with coronary heart disease in the early stage is more related to the myocardial ischemia and hypoxia caused by coronary stenosis. Ryberg et al. believed that LV diastolic function is closely related to the degree of coronary stenosis [24], and it gradually increases with the expansion of the stenosis and the aggravation of the degree of stenosis. Bogsert et al. concluded that premature intervention causing diastolic dysfunction in stenotic vessels rescues ischemic cardiomyopathy [11]. Ren et al. found a strong association of moderate to severe left ventricular diastolic dysfunction with heart failure hospitalization events and cardiac death [25]. For patients with LV diastolic dysfunction who are suspected of having coronary heart disease, timely diagnosis and treatment, such as revascularization, are closely related to the prognosis of the patients [26]. Williams and Kim successively confirmed the presence of localized diastolic dysfunction in patients with coronary heart disease using different methods of echocardiography, and reduced diastolic function can be used as a sensitive indicator of myocardial ischemia [27,28]. Hemodynamic factors, induced by pulsatile blood flow, play a crucial role in vascular health and diseases, such as the initiation and progression of atherosclerosis. Computational fluid dynamics, finite element analysis, and fluid–structure interaction simulations have been widely used to quantify detailed hemodynamic forces based on vascular images commonly obtained from computed tomography angiography, magnetic resonance imaging, ultrasound, and optical coherence. Its steps include medical imaging, image processing, spatial discretization to generate computational mesh, setting up boundary conditions and solver parameters, visualization and extraction of hemodynamic factors, and statistical analysis [29,30]. Based on coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) combined with coronary CTA anatomy and FFR functional evaluation, no special scanning protocol and the use of additional drugs are required, only based on resting CTA data, computational fluid dynamics (CFD) method is used to simulate intracoronary blood flow and pressure, and then after complex image processing and operation processes (including image segmentation and extraction of the coronary tree, maximum blood flow estimation, computational fluid dynamics evaluation, etc.), FFR at any point of the coronary tree can be obtained, the values are affected by various factors, such as motion artifacts, image quality, calcification artifacts, microcirculatory disturbances, etc. In patients with microvascular disease, the adenosine-mediated hyperemia model may overestimate the degree of vasodilation, resulting in lower CT-FFR values than the measured FFR values [7,8,31], so LV diastolic dysfunction may have an impact on the CT-FFR values, leading to differences in the diagnostic performance of CT-FFR. Hassan Tahir et al. [ 32] found that diastolic dysfunction is an important risk factor leading to discordance between iFR and FFR. Kawata et al. also found that coronary flow reserve (CFR) is associated with left ventricular diastolic dysfunction in patients with type 2 diabetes [33]. The accuracy of CT-FFR has not been reported in patients with normal vs. impaired left ventricular diastolic function. Our study is the first to analyze the diagnostic performance of CT-FFR in different LV diastolic functions, and we divided the patients into a normal LV diastolic function group and a dysfunction group according to echocardiography. Statistical analysis was performed on the two groups; the results showed that CT-FFR and FFR had good consistency and diagnostic performance in the two groups; and there was no significant difference between them. Limitations of this study: First, this study is a retrospective study including all patients undergoing echocardiography, CCTA, CT-FFR, ICA and FFR, 46 out of 136 patients were excluded because they had not undergone echocardiography, had a history of PCI, and failed the CT-FFR analysis; thus, potential selection bias can affect the diagnostic accuracy of CT-FFR in identifying lesion-specific ischemia. Second, the sample size was relatively small, and thus, the results still need to be confirmed in a larger sample-sized study. Third, CT-FFR accuracy relies more on high-quality CTA images, and microcirculatory disturbances affect them less. Finally, the results still need to be confirmed by studies with larger sample sizes. ## 5. Conclusions LV diastolic dysfunction did not affect the diagnostic performance of CT-FFR. 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--- title: A pH-Responsive Asymmetric Microfluidic/Chitosan Device for Drug Release in Infective Bone Defect Treatment authors: - Hongyu Chen - Wei Tan - Tianyi Tong - Xin Shi - Shiqing Ma - Guorui Zhu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003349 doi: 10.3390/ijms24054616 license: CC BY 4.0 --- # A pH-Responsive Asymmetric Microfluidic/Chitosan Device for Drug Release in Infective Bone Defect Treatment ## Abstract Bacterial infection is currently considered to be one of the major reasons that leads to the failure of guided bone regeneration (GBR) therapy. Under the normal condition, the pH is neutral, while the microenvironment will become acid at the sites of infection. Here, we present an asymmetric microfluidic/chitosan device that can achieve pH-responsive drug release to treat bacterial infection and promote osteoblast proliferation at the same time. On-demand release of minocycline relies on a pH-sensitive hydrogel actuator, which swells significantly when exposed to the acid pH of an infected region. The PDMAEMA hydrogel had pronounced pH-sensitive properties, and a large volume transition occurred at pH 5 and 6. Over 12 h, the device enabled minocycline solution flowrates of 0.51–1.63 µg/h and 0.44–1.13 µg/h at pH 5 and 6, respectively. The asymmetric microfluidic/chitosan device exhibited excellent capabilities for inhibiting *Staphylococcus aureus* and *Streptococcus mutans* growth within 24 h. It had no negative effect on proliferation and morphology of L929 fibroblasts and MC3T3-E1 osteoblasts, which indicates good cytocompatibility. Therefore, such a pH-responsive drug release asymmetric microfluidic/chitosan device could be a promising therapeutic approach in the treatment of infective bone defects. ## 1. Introduction Bone defects caused by trauma, severe infection or tumors are a critical problem for many patients who need surgery and remain a major challenge in clinical practice [1]. Nowadays, guided bone regeneration (GBR) technology is generally accepted as a therapeutic modality in the treatment of periodontal disease or bone defects in other parts of the body [2]. As a key medical device of GBR procedures, GBR membranes (GBRM) can prevent cell migration from connective tissue and epithelium into bone defect sites, thereby providing space for osteoblast cell growth and achieving bone regeneration [3,4]. Owing to their good biocompatibility and low toxicity, polytetrafluoroethylene (PTFE) membranes, collagen membranes and artificial or natural polymer membranes are the main commercial membranes currently used in clinics [5,6]. Even though current commercial GBRMs are well tolerated by the human body, they suffer from prospective complications like implant-associated infection, resulting in implant failure along with delayed healing [7,8,9]. The implanting surgery of GBR may cause bacterial infection, and severe bacterial infection then leads to the failure of GBR therapy, especially for the application in the oral environment [8,10]. Consequently, bacterial infection may lead to secondary surgery, which could increase not only patient suffering but also health costs. Such problems motivate researchers to develop functional GBRMs with excellent antibacterial functions that can fight infection for better bone regeneration [11]. Most previous works have been devoted to the preparation of GBRMs loaded with antibiotics through physical or chemical approaches [12]. Xue et al. [ 13] developed a GBR membrane by electrospinning poly(ε-caprolactone) (PCL) and gelatin blended with metronidazole (MNA), and the antibiotic thereof was used to prevent infection. In addition, GBR membranes with antibacterial coatings have been developed [14]. Nardo et al. [ 15] improved the antibacterial effects of a PTFE membrane by coating AgNO3 on the surface of the membrane. In fact, direct doping of antibiotics into the membrane or making antibacterial coatings are a simple approach, but these strategies can lead to the spontaneous nondependent release of drugs [16]. Delivery of antibiotics by external stimulations including temperature, ultrasound or magnetic fields have been developed [17,18]. For instance, Sirinrath et al. [ 19] embedded ciprofloxacin (CIP) and iron oxide magnetic nanoparticles (NPs) in PCL microspheres. Through the action of an alternating magnetic field, antibiotic CIP was released from the microspheres. These approaches can achieve antibiotic release at a specified location and time, but they do not have an intrinsic ability to respond to the bacterial-infection-induced local microenvironment, and they have to rely on external stimulations [20]. Some approaches have been developed that do not release antibiotics in infection-free environments but furnish antibiotics in acid circumstances caused by bacterial infection [21]. Under normal physiological conditions, the pH is 7.4. Bacterial infection is associated with acidity and the pH decreases to 4.5–6.5 at the site of infection [22,23]. Such drug-delivery systems use pH-responsive polymers/hydrogels to entrap the desired drug into their polymeric network or pH-responsive acid-labile linkers to incorporate drugs in biomaterials. One scenario is that these pH-responsive polymers/hydrogels [24] undergo swelling or degradation in acid environments, thereby allowing the diffusion of therapeutic agents [25]. Another scenario is that, under the action of the acid cleavable linker, drugs in biomaterials can be released [26]. Although many controlled drug-delivery systems have shown potential, their ability of precise control needs to be further strengthened. In recent years, the microfluidic technique has garnered increasing attention in the field of drug release due to its precise control of fluids [27,28,29]. Lee et al. [ 30] proposed a microdevice concept for ocular drug delivery, where the device consisted of reservoirs and microchannels. Drug solutions diffused in the microchannel could achieve a stable flowrate, and different flowrates were controlled by changing microchannel configurations. For the control of activation time of drug release, Yang et al. [ 31] developed a microfluidic device that had release channels filled with polymer poly (DL-lactide-coglycolide). The degradation of polymers delayed the pace of drug release. Indeed, biodegradable polymers with different degradation speeds can modulate the starting time of drug release. Some non-mechanical micropumps have been used for drug delivery, without the need for external stimulation. Drug release can be actuated by environmental changes [32,33,34]. Kim et al. [ 35] developed a leaf-inspired hydrogel micropump, which consisted of a thermo-sensitive porous membrane and agarose gel. The membrane absorbed water from the reservoir and delivered it to the agarose gel via an evaporation-induced water potential difference. Since the shrinking and swelling behaviors of the membrane could be manipulated by temperature variation, this responsiveness of the membrane enabled the control of evaporation and pumping rates. Antibiotic-loaded implants giving spontaneous and nondependent drug release with an inappropriate dose may increase the risk of antimicrobial resistance [36]. Therefore, it is necessary to develop novel systems that can store antibiotics in infection-free environments and release them in acid circumstances caused by bacterial infection. Furthermore, it is also necessary to control the drug release process to avoid high-dose-induced adverse side effects. Herein, we introduce the microfluidic technique into GBR implants, and put forward a novel device that can achieve pH-responsive drug release and has a more controlled drug release process. In this work, we propose an asymmetric microfluidic/chitosan device that is ready for drug loading, can be manufactured by simple methods, and can achieve pH-responsive drug release without the need for external stimulation. As shown in Figure 1, we hypothesize that the chitosan membrane side is beneficial for osteoblast adhesion and proliferation, whereas the microfluidic side can prevent fibrous tissue infiltrating into the bone defect region and realize pH-responsive drug release for bacterial infection treatment at the same time. The microfluidic side is a pH-regulated drug-delivery micropump that utilizes a pH-sensitive hydrogel as an actuator to dispense antibiotics. The micropump has a polymeric chamber that serves as the drug reservoir with a hydrogel inside. A thin elastic membrane separates the hydrogel and the drug solution, and deflects when the hydrogel starts to swell, thus forcing the drug out of the reservoir. The pH-sensitive hydrogel has a higher swelling ratio in acid environments than in neutral conditions, thus different drug release performances occur under different pH values. Herein, the antibiotic minocycline was chosen due to its broad-spectrum antibacterial properties. The antibacterial performance of the microfluidic/chitosan device was tested against *Staphylococcus aureus* (S. aureus) and *Streptococcus mutans* (S. mutans). In addition, the assessments of cytocompatibility of the microfluidic/chitosan device were examined using L929 fibroblasts and MC3T3-E1 osteoblasts. ## 2.1. pH-Sensitive Hydrogel Swelling Kinetics The swelling ratio of the hydrogel at three different pH values is shown in Figure 2. It is obvious that the PDMAEMA hydrogel has pronounced pH-sensitive properties. The swelling ratio decreases with the increase of the pH, and in the acid environment the swelling ratio is much higher than that in the neutral one. This is because PDMAEMA hydrogels are cationic polymers. In acid conditions, the tertiary amine groups in the PDMAEMA polymer chains undergo protonation thus creating cationic charge within the polymer. The electrostatic repulsion between the polymeric chains prompts them to move away from each other [37,38], and induces an increasing of the volume and the swelling rate of the gel in low pH environments. In the neutral environment, the tertiary amine groups have a low degree of protonation, thus resulting in a low swelling ratio. As shown in Figure 2, as time went by, the swelling ratio of the hydrogel increased over 24 h. There was no significant difference in the hydrogel swelling ratio between 24 h and 30 h at all three pH conditions, which indicates that the hydrogel reached an equilibrium state within 24 h. The equilibrium swelling ratio of the hydrogel was 15.61, 11.76 and 3.61 at pH 5, 6 and 7.4, respectively. At pH 7.4, the hydrogel showed a slight volume transition during the whole swelling process, and at pH 5 and 6 the swelling ratio of the hydrogel increased significantly. The hydrogel also showed a faster swelling rate in the early stage, especially in the first 1 h. In the pH 5 condition, the swelling ratio was 4.72 in 1 h, and was 3.48 in the pH 6 condition. Figure 2c shows the vertical view of three hydrogel bars (same initial size) when they reached the equilibrium state at different pH conditions. These results reveal that in acid pH conditions (bacterial infection regions) the hydrogel undergoes a large volume change, which is higher than that in non-infection regions (neutral pH). Thus, the PDMAEMA hydrogel is regarded as an actuator to trigger drug release when bacterial infection occurs. ## 2.2. Drug Release Performance The quantitative characterization of drug-delivery capacity of the asymmetric microfluidic/chitosan device is presented in Figure 3. Minocycline release was driven by volume transition of the hydrogel and we monitored the release process within 12 h. Overall, there was no minocycline release at pH 7.4 due to the low swelling ratio of the hydrogel, while the release of antibiotic thereof only occurred in acid environments, which indicates that selective drug release can be achieved under the control of hydrogel. Under the pH 5 condition, hydrogel exhibited a higher swelling ratio and thus could lead to a higher release amount than under the pH 6 condition. The cumulative release amount reached 14.94 µg and 12.17 µg in12 h, respectively. In acid environments, faster flowrates were found in the first 1 h, as a result of the rapid increase of the hydrogel swelling rate. The average flowrate in the first 1 h at pH 5 was 5.97 µg/h, and 3.99 µg/h at pH 6. Although there was an initial burst release of minocycline, in the following period the flowrate varied slightly between 0.51 and 1.63 µg/h and 0.44 and 1.13 µg/h at pH 5 and 6 conditions, respectively. In essence, the flowrate can be controlled by the volume transition rate. If using hydrogels with different volumes or crosslinking degrees, flowrates over a period can change because of the distinguishing volume transition rates. We also assessed the ‘on–off’ characteristics of the device to verify its sensitivity to pH changes. First, in order to study the swelling and de-swelling performance of the hydrogel in a low–high pH cycle, we put the hydrogel over pH 5 buffer solution for 2 h then transferred it to a pH 7.4 condition for 1 h, and the volume of hydrogel was monitored up to 8 h. As shown in Figure 4a, when the hydrogel was transferred from pH 5 to 7.4, the swelling ratio decreased. This can be explained by the fact that, at the pH 7.4 condition, the tertiary amine groups of the hydrogel had a low degree of protonation, thereby the electrostatic repulsion between polymer chains decreased and the hydrophilicity of chains decreased at the same time. When the hydrogel was in contact with a pH 5 environment, the protonation degree increased and it started to swell again. The device was also subjected to the aforementioned low–high pH cycle. The device released 6.49 µg at pH 5 over 2 h, and at pH 7.4 this amount remained for over 1 h (see Figure 4b). The next cycle illustrated a similar pattern, and the cumulative release amount was 10.12 µg at the end of 8 h. According to the results, in non-infection or healed regions, no drug was released from the device, while, with the occurrence of bacterial infection, the device started releasing minocycline and, under the control of a hydrogel actuator, could achieve a relatively stable flowrate. ## 2.3. In Vitro Antibacterial Performance Implant-related infection can be caused by different bacterial species. Minocycline was chosen as an appropriate antibiotic in our experiments due to its broad-spectrum antibacterial ability [39]. We used Staphylococcus aureus, the common bacteria at the infection site, and Streptococcus mutans, which only grows in oral environments to validate the antibacterial properties of the asymmetric microfluidic/chitosan device. Minocycline release solution was obtained at certain times (2, 6, 12, 24 h) from the pH 5 and 6 buffer. The bacteria were cultured in a mixture of the minocycline solution and medium with a volume ratio of 1:1. After 24 h of cocultivation, the OD value of each group was measured. Similarly, buffer release solutions (pH 5 and 6) from blank samples were cocultured with the bacteria in a 1:1 (v/v) ratio. The buffer solution containing minocycline was replaced by phosphate buffer saline (PBS) in the control group. Figure 5a,b show that the OD values of each group decreased to a low level for the minocycline release solution coculture with S. aureus and S. mutans, in comparison with the buffer release solution from the blank samples. It was also found that when bacteria were cultured in an acid environment their growth could be inhibited to some extent, and the results indicated that S. aureus and S. mutans were both less acid tolerant. ## 2.4. In Vitro Cytocompatibility In order to study the effect of minocycline concentration on L929 fibroblast growth, we prepared a minocycline-containing medium whose concentration was equivalent to when the asymmetric microfluidic/chitosan device released at pH 5 for 24 h. As shown in Figure 6a, the CCK-8 testing results suggest that the cells proliferated continuously in both groups and grew rapidly after one day. The OD values of these two groups were similar on the first day, then, according to the data from the third and fifth day, cells that were cultured with the minocycline-containing medium showed a better proliferation trend compared with the control group. Some previous studies have showed that an appropriate amount of minocycline can promote the proliferation of periodontal ligament fibroblasts [40]. We further performed an AO/EB dyeing experiment for 1, 3, and 5 days, and the results in Figure 6b show that cells cultured with minocycline-containing medium proliferated normally in 5 days. Fibroblasts were also seeded on the surface of the micropump to study the effect of PLA materials on cell growth. It can be seen that the cells on the surface of the micropump spread normally over 5 days and were in spindle morphology (Figure 6b). The loose chitosan membrane of the asymmetric microfluidic/chitosan device was used to promote osteoblast adhesion and proliferation. Figure 7a shows the CCK-8 assay results of the MC3T3-E1 osteoblasts seeded in the wells and on the surface of the chitosan membrane after 1, 3, and 5 days. After 1 day, cells seeded on the surface of the chitosan membrane proliferated and underwent an increasing trend, where the OD value on the fifth day was higher than that of the control group, which indicates that the chitosan membrane promoted osteoblast proliferation. LSCM images in Figure 7b showed after 5 days of culturing that the cells in the control and chitosan conditions spread normally over 5 days. A SEM micrograph of the chitosan surface with osteoblasts, shown in Figure 7c, displayed a loose and porous morphology. After 5 days of culturing, the osteoblasts showed a round shape and were anchored to the chitosan surface. Thus, we can conclude that the asymmetric microfluidic/chitosan device had satisfactory cytocompatibility. In order to fight bacterial infection for achieving better bone regeneration, many studies have been devoted to the preparation of GBRMs loaded with antibiotics by doping antibiotics into the membranes through physical or chemical approaches. Drugs are released from the membrane in a spontaneous and nondependent manner. In this study, we proposed an asymmetric microfluidic/chitosan device that can achieve a pH-responsive drug release. On-demand release of minocycline relies on a hydrogel actuator. The PDMAEMA hydrogel has pronounced pH-sensitive properties, i.e., the swelling ratio of the hydrogel in acid environments is much higher than that in a neutral environment. The flowrates can be controlled by the volume transition rate of the hydrogel. Furthermore, compared with the method of doping antibiotics into membranes, our device is readily for drug loading. The drug in the drug reservoir can be easily replaced according to the requirements, which is more flexible in clinical use. In addition, the device in this study shows satisfactory antibacterial ability and cytocompatibility. The pH-responsive asymmetric microfluidic/chitosan device developed in the current study can be an efficient drug-delivery system due to its on-demand release capability. In this study, we introduced a microfluidic technique into GBR implants and put forward a concept of using the volume transition of the hydrogel to control the drug release rate. A future study will investigate the tissue compatibility and bone regeneration behavior of the implants in vivo. ## 3.1. Ethics Statement All cell lines used in this paper (Mouse Fibroblast L929 and Mouse Osteoblast MC3T3-E1) were provided by Tianjin Medical University (Tianjin, China). All experiments were performed in accordance with the relevant guidelines set by the National Health Commission of the People’s Republic of China and approved by the ethics committee at Tianjin Medical University (Tianjin, China). ## 3.2. Syntheses of PDMAEMA Hydrogel Poly [2-(dimethylamino) ethyl methacrylate] (PDMAEMA) is a kind of pH-sensitive polymer and it has been widely used in the biomedical field due to several advantageous features such as non-toxicity and biocompatibility [41,42]. The PDMAEMA hydrogel was prepared through the radical aqueous solution polymerization route. A total of 4 g 2-(dimethylamino) ethyl methacrylate (DMAEMA) (Sigma Aldrich, Shanghai, China) was passed through a basic alumina column (DIKMA, Beijing, China) before using, in order to remove its inhibitor. A DMAEMA monomer was dissolved in 16 mL de-ionized water, then 0.06 g Methylene-bis-acrylamide (MBA, cross-linking agent) (Sigma Aldrich, China) and 0.04 g potassium persulfate (KPS, initiator) (Sigma Aldrich, China) were added. The solution was mixed under a nitrogen atmosphere for 10 min to remove oxygen, then the sealed reaction tube was kept for 24 h at a 60 °C atmosphere for the completion of polymerization. After the reaction, the tube was cooled to room temperature and the plunger was opened to take out the sample, with subsequent cutting of the prepared gel into small pieces. The pieces were soaked and washed with de-ionized water, while changing the water continuously to remove the unreacted monomer, cross-linking agent and initiator. After 3 days, the gel was taken out and dried for later use. ## 3.3. Device Fabrication The structure of the asymmetric microfluidic/chitosan device for treating bone defects is shown in Figure 8. It contains two parts, named as loose chitosan membrane side (part 1) and microfluidic side (part 2). The loose structure that contacts the bone defect space directly is beneficial for osteoblast adhesion and blood clot stabilization [43,44]. Chitosan(poly(1,4-D-glucosamine)) is a natural biopolymer and it is easily processed into membranes. Due to its biocompatibility and non-toxicity, some studies have used chitosan membrane for bone tissue regeneration [1,45,46]. As such, a loose chitosan membrane was chosen to contact with bone defect spaces. The microfluidic side is a pH-regulated drug-delivery micropump, which can release minocycline to treat possible bacterial infection. The 3D exploded view of the pH-regulated drug-delivery micropump is shown in Figure 8a. The top layer is a polylactic acid (PLA) drug reservoir with a groove structure, and the intermediate layer is a PLA elastic membrane (10 µm). Due to the biocompatibility, low cost and non-toxicity of PLA, it has been widely used in GBR technology [47,48]. Under the elastic membrane, a pH-sensitive hydrogel (4 × 4 × 1 mm3) is wrapped and embedded in the drug reservoir (16 mm in diameter, 2 mm height). The elastic membrane separates the minocycline solution and the hydrogel, and the minocycline solution is stored in the drug reservoir. The bottom layer is a PLA grid plate (300 µm), which is attached to the hydrogel, exposing the hydrogel to the aqueous contents while simultaneously providing mechanical protection. The micro-outlets prevent the leakage of solution without external force, and the hydrostatic pressure is insufficient to overcome surface tension. Drug outlets are distributed along the circumference, and the number of outlets can be varied according to the requirements. The micropump in this work has four drug outlets (0.8 mm in diameter) in different directions. Figure 9 shows the fabrication process of the asymmetric microfluidic/chitosan device. For the microfluidic side, the hydrogel was located in the center of the grid plate, then using the elastic membrane to cowl the hydrogel, the elastic membrane and the grid plate were bonded together by medical grade adhesive. Finally, the drug reservoir was stuck on the top of the elastic membrane. The loose chitosan membrane (400 µm) was on the upper layer of the drug reservoir. For loose chitosan membrane synthesis, 2 g chitosan powder (Sigma Aldrich, China) was dissolved in $2\%$ acetic acid solution to prepare a $2\%$ (w/v) chitosan solution, and the mixed solution was stirred evenly with a magnetic stirrer. Then, the chitosan solution was slowly poured on a polytetrafluoroethylene mold at room temperature to obtain even liquid films; thereafter the films were immersed in liquid nitrogen together with the mold for 10 s. Subsequently, the films were lyophilized at −80 °C for 24 h, and the loose chitosan membrane obtained after vacuum freeze-drying. The asymmetric microfluidic/chitosan device (16 mm in diameter, 2.7 mm height) was obtained by adhering the chitosan membrane on the upper layer of the drug reservoir. All components were bonded by medical grade adhesive. ## 3.4. Swelling Kinetics of the pH-Sensitive Hydrogel In order to study the swelling behavior of the pH-sensitive hydrogel, the PDAMEMA hydrogel was cut into 4 × 4 × 1 mm3 and then put it on the grid plate over three different pH buffer solutions (5, 6 and 7.4) for 30 h at 37 °C atmosphere, where pH 7.4 was for normal physiological conditions, and pH 5 and 6 were in the typical pH range for an infected region. The swelling ratio is defined as the volume ratio between the swollen hydrogel at certain times and that of its initial state. All tests were repeated three times and averaged. ## 3.5. Drug Delivery Characterizations For characterizing the drug-delivery capability of the asymmetric microfluidic/chitosan device, we put the device over a set of different constant pH buffer solutions (5, 6 and 7.4) at 37 °C for 12 h. The concentration of minocycline solution was 0.1 mg/mL, and the released solution was sampled periodically. In order to verify the ‘on–off’ performance of this device, it was subjected to a low–high pH cycle, where pH 5 and 7.4 buffers were chosen, with pH 5 representing the typical pH in infection regions, and pH 7.4 representing normal conditions. Within each cycle, the device was first allowed to release minocycline over pH 5 buffer for 2 h, and then for 1 h over pH 7.4 buffer. High performance liquid chromatography (HPLC) (Waters E-2695, Shanghai, China) was used to determine the minocycline concentration. All tests were repeated three times and averaged. ## 3.6. Antibacterial Activity of Minocycline Released at Different pH Values The antibacterial efficiency of minocycline released from the device at different pH values was tested against S. aureus and S. mutans, as S. aureus is the most common bacteria in infection regions and S. mutans is the bacteria endemic to oral environments [49]. In order to ascertain the antibacterial activity of pH-responsive minocycline release, 1 mL minocycline solution released under different pH (5 and 6) was collected at specified times (2, 6, 12, 24 h), and then S. aureus or S. mutans suspensions (1 × 106 CFU/mL) were added into the minocycline release solution in a 1:1 (v/v) ratio. Specimens were put into 6-well plates and incubated at 37 °C for 24 h. After the experiment, 100 µL of each bacterial culture solution was transferred into a 96-well plate, and the absorbance was measured at 600 nm in a microplate reader (RT-6000, Rayto, Shenzhen, China) to obtain the OD (optical density) value. The OD value indicates the optical density absorbed by the tested solution. Similarly, release buffer solutions (pH 5 and pH 6) from blank samples were cocultured with the bacteria in a 1:1 (v/v) ratio. The phosphate buffer saline (PBS) solution was used as the control group to culture with bacteria suspensions in a 1:1 (v/v) ratio. All tests were repeated more than three times. ## 3.7. Cytocompatibility Evaluation MC3T3-E1 osteoblasts and L929 fibroblasts were used to evaluate the cytocompatibility of the asymmetric microfluidic/chitosan device. The proliferation of the cells was assessed by using a CCK-8 assay. As for the microfluidic side, in order to ascertain the effect of minocycline concentration on cells, we prepared a minocycline-containing complete growth medium (DMEM with $10\%$ fetal bovine serum, 100 mg/mL of streptomycin, and 100 U/mL of penicillin), and the concentration of minocycline was equivalent to the amount released by the device in 24 h at pH 5. Subsequently, 5000 fibroblasts in the minocycline-containing medium were seeded into a 24-well plate. In the control group, cells in medium without minocycline were seeded into a 24-well plate. In order to study the effect of PLA material on cell growth, 5000 fibroblasts in normal medium were seeded on the surface of the micropump. As for the chitosan side, 5000 osteoblasts in medium were seeded onto the surface of the chitosan membrane and placed in a 24-well plate; cell suspensions added into wells with no samples were regarded as controls. Plates were incubated at 37 °C under $5\%$ CO2 atmosphere. At days 1, 3, and 5 of culture, 100 µL of medium was transferred for CCK-8 assay, and the absorbance was measured at 450 nm in a microplate reader to obtain the OD value (RT-6000, Rayto, China). For morphological observation, at days 1, 3, 5 of culture, cells in wells and on the surface of samples were washed with PBS three times, and the cells were stained using a Live/Dead Cell Double Staining Kit and observed using laser confocal microscopy (LSCM) (Fv-1000, Olympus, Tokyo, Japan). Furthermore, the morphologies of the adhered cells on the surface of the chitosan membrane were also observed using a scanning electron microscope (SEM) (Apreo, FEI, Brno, Czech Republic). Cells on the membrane were fixed using 2.5 vol% glutaraldehyde in 0.1 M sodium cacodylate buffer for 24 h at 4 °C, dehydrated using graded ethanol (25, 50, 75, 90 and $100\%$) and then dried before being sputtered with gold. All tests were repeated more than three times. ## 3.8. Statistical Analysis The results were reported as the mean ± standard deviation. Significant differences between the two groups were determined by the Student’s t-test. When performing a hypothesis test in statistics, a p-value helps to determine the significance of the results. The p-value is the probability of obtaining a result at least as extreme as the one that was actually observed, given that the null hypothesis (no difference between groups) is true. A p-value stands for the probability that an observed difference could have occurred just by random chance. A difference at $p \leq 0.05$ was considered to be significant. ## 4. Conclusions A novel asymmetric microfluidic/chitosan device was manufactured for pH-responsive drug release to treat bacterial infection. A PLA pH-regulated drug-delivery micropump was assembled with a loose chitosan membrane, and a pH-sensitive hydrogel in the micropump acted as an actuator. The swelling behavior of PDMAEMA hydrogel under different pH conditions was elucidated. The equilibrium swelling ratios were 15.61, 11.76 and 3.61 at pH 5, 6 and 7.4, respectively. This significant volume change in acid environments resulted in minocycline release only at pH 5 and 6, while the asymmetric microfluidic/chitosan device maintained a zero-delivery rate in the normal physiological environment. Within 12 h, the flowrates were stabilized between 0.51 and 1.63 µg/h and 0.44 and 1.13 µg/h at pH 5 and 6, respectively. The microfluidic/chitosan device also showed good ‘on–off’ characteristics. When the device was subjected to a low–high pH cycle, minocycline only released at pH 5 and stopped releasing at pH 7.4. Minocycline released from the device efficiently inhibited S. aureus and S. mutans growth in vitro within 24 h. Biocompatibility experiments showed that the asymmetric microfluidic/chitosan device had no negative effect on cell morphology, viability and proliferation of L929 fibroblasts and MC3T3-E1 osteoblasts. In short, our findings suggest that this antibacterial asymmetric microfluidic/chitosan device could be a potent therapeutic approach to control implant infection. This device can use hydrogels with different volumes and crosslinking degrees, since the change in the hydrogel’s volume transition rates could result in different drug release rates. It can also incorporate other smart hydrogels, responsive to different stimuli (specific ions, glucose, etc.) in order to achieve a broader application in the biomedical field. ## References 1. 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--- title: Interrelationships of Sleep Quality, Obesity Severity, and Clinical Headache Features among Women with Comorbid Migraine and Obesity authors: - Leah M. Schumacher - Samantha G. Farris - J. Graham Thomas - Richard B. Lipton - Jelena Pavlovic - Angeliki Vgontzas - Dale S. Bond journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003353 doi: 10.3390/jcm12051742 license: CC BY 4.0 --- # Interrelationships of Sleep Quality, Obesity Severity, and Clinical Headache Features among Women with Comorbid Migraine and Obesity ## Abstract Obesity and migraine are often comorbid. Poor sleep quality is also common among individuals with migraine and may be influenced by comorbidities such as obesity. However, understanding of migraine’s relationship with sleep and the potential exacerbating effect of obesity remains limited. This study evaluated the associations of migraine characteristics and clinical features with sleep quality among women with comorbid migraine and overweight/obesity and assessed the interplay between obesity severity and migraine characteristics/clinical features in relation to sleep quality. Women seeking treatment for migraine and obesity ($$n = 127$$; NCT01197196) completed a validated questionnaire assessing sleep quality (Pittsburgh Sleep Quality Index-PSQI). Migraine headache characteristics and clinical features were assessed using smartphone-based daily diaries. Weight was measured in-clinic, and several potential confounders were assessed using rigorous methods. Nearly $70\%$ of participants endorsed poor sleep quality. Greater monthly migraine days and the presence of phonophobia related to poorer sleep quality, and specifically poorer sleep efficiency, controlling for confounders. Obesity severity was neither independently associated nor interacted with migraine characteristics/features to predict sleep quality. Poor sleep quality is common among women with comorbid migraine and overweight/obesity, although obesity severity does not appear to uniquely relate to or exacerbate the association between migraine and sleep in this population. Results can guide research on mechanisms of the migraine–sleep link and inform clinical care. ## 1. Introduction Migraine is a neurological condition characterized by recurrent moderate-to-severe headaches with accompanying sensory, autonomic, and affective features [1]. Migraine affects approximately $12\%$ of the population [2] and is more prevalent and often experienced as more chronic and severe among individuals with obesity, especially women [3,4,5,6]. Poor sleep quality is common among individuals with migraine [7,8,9,10]. The relationships between sleep and migraine are complex, bidirectional, and multifactorial; migraine can interfere with sleep and poor sleep can trigger a migraine attack and exacerbate pain sensitivity [10,11]. The association of poor sleep quality and migraine may be explained by common pathophysiological mechanisms, shared comorbidities, or both [10]. One comorbidity that may influence the sleep–migraine link but has received limited attention is obesity. Individuals with comorbid migraine and overweight/obesity may be especially prone to poor sleep quality [12]. For example, both excess weight and migraine headache symptoms have potential to disturb sleep (e.g., due to pain, breathing-related difficulties) and to affect aspects of sleep including sleep quality and efficiency. Both migraine and obesity are also associated with increased fatigue [13,14,15], which could affect behavioral sleep patterns (e.g., napping [16], more time spent in bed). When migraine and overweight/obesity are experienced together, the impact on sleep may be heightened. However, limited research has examined sleep quality in the context of comorbid migraine and overweight/obesity. Additionally, while several sensory and autonomic features associated with migraine may affect sleep among this patient population, limited research has investigated the association between these symptoms and sleep. For example, allodynia (i.e., abnormal pain in response to tactile stimuli, such as light touch or wearing jewelry), photophobia (i.e., hypersensitivity to light), and phonophobia (i.e., hypersensitivity to sound) may all make it more difficult for individuals to fall or stay asleep due to heightened responses to normative tactile stimuli and ambient light and sound [17]. Likewise, the physical discomfort associated with migraine-related nausea may interfere with sleep [18]. Improved understanding of migraine characteristics and clinical features that relate to impaired sleep quality is critical to guide research on underlying mechanisms of the migraine–sleep link and to inform clinical intervention (e.g., identify who may be at greatest risk for poor sleep and might benefit from additional sleep-related intervention) [19]. A pragmatic strategy for learning more about sleep quality in the context of comorbid migraine and overweight/obesity is through use of secondary analysis of existing clinical trial data. The Women’s Health and Migraine (WHAM) study [20] was a randomized trial comparing behavioral and educational interventions to reduce weight and headache frequency and severity. All participants had overweight/obesity, met diagnostic criteria for migraine, and completed validated measures of sleep and several potential confounders during the pretreatment baseline phase of the WHAM trial. The current study aimed to leverage the pretreatment data from the WHAM trial to evaluate sleep quality and its associations with migraine characteristics, cardinal clinical features, and obesity severity. The potential impact of obesity severity on the associations between migraine and sleep was also evaluated. The primary aims were to: [1] assess the relative frequency of poor sleep quality among a sample of women with comorbid migraine and overweight/obesity; [2] evaluate the associations of obesity severity and of migraine characteristics (monthly migraine days [MMD], pain intensity, attack duration), cardinal clinical features (nausea, photophobia, and phonophobia), and allodynia with overall sleep quality and specific dimensions of sleep quality, when controlling for potential confounders; and [3] assess the interplay between obesity severity and migraine characteristics/clinical features in relation to sleep quality. We hypothesized that: [1] poor sleep quality would be common in this population, [2] more frequent or severe migraine characteristics and clinical features, as well as greater obesity severity, would relate to poorer sleep quality, and [3] obesity severity would moderate the association of migraine characteristics/clinical features with sleep quality, such that more frequent or severe migraine characteristics/clinical features would be most strongly related to poorer sleep quality among those with more severe obesity. ## 2. Materials and Methods The current study involved a secondary exploratory analysis of data from a randomized clinical trial that compared behavioral weight loss to migraine education for decreasing headache among women with comorbid migraine and obesity (the WHAM study) [20]. Participants were recruited from the community and neurological clinical settings from November 2012 to March 2016. Eligibility required identifying as a woman, being 18–50 years old, having both overweight/obesity (body mass index [BMI]: 25.0–49.9 kg/m2) and neurologist-confirmed migraine (see below), and experiencing ≥3 migraine attacks and 4 to 20 migraine headache days during each of the past 3 months. For the parent trial, the decision was made to focus only on women because the association between migraine and obesity is strongest in women of reproductive age [3]. Exclusion criteria included headache disorder other than migraine or migraine with tension-type; current participation in a weight loss program or use of prescription weight loss medication; previous bariatric surgery; ≥$5\%$ weight loss in the past 6 months; current pregnancy, breastfeeding, or plans to become pregnant during the study period; cancer diagnosis in the past year; and presence of another condition that the study team believed may preclude adherence to the protocol (e.g., plans to move out of the area, severe psychiatric problem). The WHAM protocol details, including full inclusion/exclusion criteria, were previously published [20]. The study took place at the Weight Control and Diabetes Research Center of The Miriam Hospital and was approved by The Miriam Hospital’s IRB. Informed consent was obtained from all participants involved in the study. The parent study was registered at clinicaltrials.gov (NCT01197196); the secondary exploratory analyses reported here were not preregistered. All data utilized in the present study were collected as part of the baseline assessment for the parent trial, prior to any clinical intervention. Participants did not receive monetary compensation for completing the baseline assessment. ## 2.1. Migraine Diagnosis, BMI, and Medical History Migraine diagnosis was confirmed by a neurologist using International Classification for Headache Disorders third edition criteria [21]. Weight and height were measured via a digital scale and stadiometer, respectively; a body mass index (BMI) of ≥25.0 kg/m2 indicated the presence of overweight or obesity. Participants completed a health history questionnaire, which assessed lifetime diagnosis of obstructive sleep apnea (OSA; Yes/No) and current continuous positive airway pressure (CPAP) machine use. ## 2.2. Sleep Quality The Pittsburgh Sleep Quality Index (PSQI) [22] is a 19-item self-report assessment of past 30-day sleep quality. A global score can be derived (possible range 0 to 21), with higher scores indicating worse overall sleep quality. A score of >5 denotes poor sleep quality and a score of ≤5 indicates good sleep quality [22]. In addition to producing a global score, the PSQI allows for evaluation of distinct sleep domains. While the PSQI can yield scores for seven sleep domains (sleep duration, habitual sleep efficiency, sleep latency, subjective sleep quality, frequency of sleep medication use, sleep disturbances, and daytime dysfunction) [22], a previously validated three component scoring system can also be used for parsimony and to limit the number of statistical tests conducted while still obtaining meaningful information about different aspects of sleep quality [23,24]. This alternate scoring system combines items from each of the seven potential sleep domain scores into the following three components: sleep efficiency (i.e., sleep duration + habitual sleep efficiency items), perceived sleep quality (i.e., sleep latency, subjective sleep quality, + frequency of sleep medication use items), and daily disturbances (i.e., sleep disturbances + daytime dysfunction items) [23,24]. Given our interest in assessing the associations among sleep quality and multiple migraine characteristics/clinical features, we utilized the three component scoring method to minimize risk of type I error. ## 2.3. Migraine Characteristics, Clinical Features, and Allodynia Migraine characteristics and clinical features were assessed via daily diary. Participants received a smartphone equipped with a diary application to report on migraine headache activity for 28 days, including migraine headache occurrence each day (Yes/No; several follow-up items differentiated migraine headaches from non-migraine headaches [e.g., unilateral vs. bilateral pain, pulsating/throbbing vs. pressing/tightening pain]), maximum pain intensity (0–10), attack duration (hours), and presence of the following clinical features: nausea, photophobia, and phonophobia. The following variables were derived from the diary responses: MMD, average maximum pain intensity, average attack duration, and percentage of episodes at which each clinical feature was endorsed. Diary responses were checked daily for completeness and participants were contacted by phone to obtain missing data. In addition, the severity of cutaneous allodynia symptoms was assessed using the Allodynia Symptom Checklist [25], a 12 item self-report measure that yields a total severity score (possible range 0 to 24), with higher values reflecting greater symptomatology. ## 2.4. Potential Confounders The Center for Epidemiological Studies-Depression (CES-D) [26] scale was used to assess depression, with scores ≥16 indicting clinically meaningful depressive symptoms, and the Generalized Anxiety Disorder Questionnaire (GAD-7) [27] was used to assess anxiety, with scores ≥10 indicating clinically elevated anxiety symptoms. The Perceived Stress Scale [28] was used to assess stress levels. Average daily minutes of moderate-to-vigorous physical activity was mesaured with a SenseWear Mini Armband monitor (BodyMedia Inc., Pittsburgh, PA, USA), which participants were asked to wear over the upper left triceps muscle during all waking hours for 7 consecutive days. This multi-sensor monitor integrates data from a triaxial acceleromter, physiologic metrics from several sensors (e.g., galvanic skin response), and participant demographic information (e.g., sex, body weight) to estimate the intensity of activities using proprietary software (SenseWear Professional Software, version 7.0). The SenseWear monitor has been shown to provide estimates of time spent in activity of various intensities similar to other monitors [29,30]. A metabolic equivalents value of ≥3 was used to classify daily minutes of moderate-to-vigorous physical activity [31]. Caffeine intake and alcohol intake was assessed via three, nonconseutive (two weekday and one weekend), mulitple-pass, 24-h diet recalls. Each recall was conducted over the phone by a trained interviewer using Nutrition Data Systems for Research (Version 2013, Nutrition Coordinating Center (NCC), University of Minnesota, Minneapolis, MN) [32]. Data from the weekdays (Monday-Friday) and weekend days (Saturday and Sunday) were weighted to create average daily caffeine (in mg) and average daily alcohol (in g) intake variables [33]. ## 2.5. Analytic Plan Data were analyzed using SPSS version 25. The threshold for statistical significance was set at 0.05 with two-tailed tests. Data were screening for missingness, outliers, and normality. Data from one participant were excluded due to extreme outlier values reported across measures that led to violations of model assumptions. One participant was missing data on diary-assessed migraine clinical features (nausea, photophobia, phonophobia) and was excluded from that subset of analyses. Two cases were excluded from analyses pertaining to migraine attack duration due to outlier values. Thus, data from a total of 127 participants were analyzed in most models, with 126 included in analyses pertaining to diary-assessed clinical features and 125 included in analyses of migraine attack duration. See Figure 1 for an outline of participant flow. For outcome variables, PSQI global scores and the PSQI daily disturbance scores were normally distributed. PSQI sleep efficiency and sleep quality scores were non-normally distributed (i.e., skewness and/or kurtosis values more than twice its standard error). Data transformations (square root for efficiency and natural log for sleep quality) were thus performed to achieve more normal distributions for analyses. For migraine variables, MMD, attack duration, and allodynia were positively skewed and were also transformed. However, as the same pattern of results was observed when conducting analyses with untransformed and transformed independent variables; values from models with untransformed independent variables are reported to enhance interpretability. The distributions of phonophobia and photophobia scores were highly skewed, with modes at the minimum (i.e., $58.3\%$ of participants reported phonophobia at no episodes) or maximum (i.e., $60.6\%$ of participants reported photophobia at every episode) values, respectively. We thus categorized participants as experiencing phonophobia at no ($0\%$) or any (1–$100\%$) episodes and as experiencing photophobia at no/some (0–$99\%$) or all ($100\%$) episodes. The distribution for nausea was also non-normal, exhibiting a bimodal distribution with $17.9\%$ of participants reporting nausea at no episodes and $16.4\%$ reporting nausea at every episode. We thus categorized participants as low (0–$33.3\%$), medium (33.4–$66.7\%$) or high (66.8–$100\%$) for nausea. Variables were descriptively characterized with means and standard deviations and medians and the interquartile range (continuous variables) or with frequencies and percentages (categorical and ordinal variables). Associations of each migraine characteristic/clinical feature with sleep quality (global score and each of the three domains) and its interaction with BMI were assessed using separate hierarchical linear regression models. The migraine variable of interest (MMD, pain intensity, attack duration, allodynia, nausea, phonophobia, or photophobia), BMI, and potential confounders (anxiety, depression, stress, average daily moderate-to-vigorous physical activity, average daily caffeine intake, average daily alcohol intake) were entered in the first step. The interaction of BMI and the migraine variable was then entered in the second step. BMI was centered, and migraine variables were centered if continuous or dummy-coded if categorical or ordinal (reference group = no or minimal symptoms). The sample size was determined through a power analysis for the main trial’s primary outcomes [20]. ## 3.1. Participant Flow and Descriptive Characteristics Table 1 displays participant characteristics for the overall sample and for participants with poor vs. good sleep, as classified by the PSQI and reported below. Participants had a mean age of approximately 38 years, and a majority identified as White and non-Hispanic. Approximately $61\%$ were married or living with a partner, and approximately $61\%$ had a college or graduate degree. Approximately $6\%$ ($$n = 8$$) endorsed lifetime diagnosis of OSA, with half of those individuals endorsing current CPAP use. Age, race, ethnicity, educational attainment (as categorized in Table 1), and marital status (as categorized in Table 1) did not relate to overall sleep quality or BMI (p’s > 0.10). However, participants who reported lifetime OSA had higher average BMI’s ($M = 42.2$, SD = 6.2) and poorer overall sleep quality ($M = 11.1$, SD = 3.9) than those without OSA (BMI: $M = 35.0$, SD = 6.4; $F = 9.34$, $$p \leq 0.003$$; PSQI global score: $M = 7.7$, SD = 3.6, $F = 6.78$, $$p \leq 0.010$$). Table 2 and Table 3 show descriptive statistics for the full sample (Table 2) and for those with poor vs. good sleep (Table 3). Notably, a majority ($69.3\%$) of participants were classified as having poor sleep based on their PSQI score, while $30.7\%$ were classified as having good sleep. The average BMI was approximately 35 kg/m2, indicating class II obesity. Participants reported an average of approximately 8 MMD, a mean maximum pain intensity of 6, a mean attack duration of 18 h, and a mean allodynia score of approximately 5, indicating mild allodynia. ## 3.2. Migraine Characteristics/Clinical Features and BMI in Relation to Sleep Quality Similar patterns of results were observed across all regression models. Table 4 thus presents an example full model output for one of the hierarchical regression models predicting overall sleep quality. As shown, the first step in all models significantly predicted sleep quality, with several confounders (e.g., depression) emerging as independently related to sleep quality. BMI was not related to sleep quality in any model, and the inclusion of the interaction between BMI and the migraine characteristic/clinical feature (e.g., MMD) in step two did not improve prediction in any model. Given this consistent pattern of findings, Table 5 presents a summary of results from the other hierarchical linear regression models, displaying only b values for the association between each migraine characteristic/clinical feature and the sleep outcome of interest, when adjusting for BMI and confounders in step one. As shown in Table 5, MMD and phonophobia were independently related to sleep quality when controlling for BMI and potential confounders (p’s < 0.05). Figure 2 displays differences in overall sleep quality based on MMD and phonophobia. Regarding specific dimensions of sleep quality, sleep efficiency was the only dimension of sleep quality related to migraine characteristics/clinical features, with MMD, nausea, and phonophobia all relating to sleep efficiency (p’s < 0.05). ## 4. Discussion This study examined sleep quality and its association with several migraine characteristics/features and obesity severity among a treatment-seeking sample of women with comorbid migraine and overweight or obesity. Our results suggest that poor sleep is common in this population—a population that continues to increase as obesity rates rise. We found that nearly $70\%$ of our sample had poor sleep quality based on a validated questionnaire. This high rate of poor sleep quality is consistent with the broader literature on sleep quality among individuals with migraine [7,8,9,10,23] and is higher than rates observed in some studies with migraine and headache patients [7,23]. The higher rates of poor sleep quality in the present sample could be due to all individuals having overweight or obesity, which has been shown to itself relate to poorer sleep quality [34,35]. Although past research shows presence of overweight/obesity relates to poorer sleep quality in the general population [34,35], obesity severity, as measured by BMI, was not related to sleep quality in our sample. These unexpected findings could be due to the restricted range in BMI, the limited ability of the PSQI to detect sleep problems most relevant to obesity (e.g., OSA-related), or the modest rate of OSA in this sample. In partial support of a role for OSA, participants who endorsed OSA reported both poorer overall sleep quality and more severe obesity than those without OSA. While caution is needed when interpreting these findings given that only eight participants endorsed OSA, it may be that obesity severity is most relevant to sleep-related breathing disorders, such as OSA and its associated symptoms among individuals with migraine. Obesity severity may be less relevant to other aspects of sleep quality, which may be affected among many individuals across the overweight/obesity spectrum. It is also possible that the relationships between migraine, obesity, and sleep quality differ or are moderated by OSA; we were underpowered to explore such relationships. Given that obesity is a major risk factor for OSA [36] and that OSA may impact migraine headache symptoms [11], additional research on the associations of OSA, obesity severity, and migraine is needed. Inclusion of both men and women (vs. just women) in these studies will be important, as OSA is more prevalent among men [37]. When evaluating overall sleep quality, we also found that poorer overall sleep was related to several specific migraine characteristics/features, namely greater MMD and the presence of phonophobia. These findings are consistent with some prior research [7,8,38]. Although we cannot determine directionality from this cross-sectional study, given the bidirectional associations between migraine and sleep [10,11] it may be that those with poorer sleep are prone to having more frequent migraine attacks and/or that more frequent migraine attacks negatively affect sleep. Such associations could be due to both behavioral and biological factors. For example, more frequent discomfort from regular headaches could make it difficult for individuals to fall and stay asleep, or dysfunction in brainstem networks involved in switching between sleep stages (e.g., networks in the hypothalamus) in patients with migraine could negatively affect important aspects of sleep such as amount of time in slow wave sleep and sleep–wake transitions [11]. For the phonophobia findings, it is possible that sensitivity to sound (but not light) may uniquely interfere with sleep as it may be easier to escape light in a dark room than it is to escape sound. Again, physiological abnormalities that lead to sensory hypersensitivity among migraine patients could also affect biological mechanisms involved in sleep regulation [11]. These findings are consistent with the notion that migraine is a disorder of sensory amplification, although additional research is warranted to elucidate mechanisms that link sensory disturbances and poor sleep quality in migraine [39]. Notably, the observed associations between migraine characteristics/features and poor sleep quality were significant above and beyond relevant factors know to affect sleep quality, including mood and stress-related variables, physical activity, and caffeine and alcohol intake. These findings underscore the importance of assessing and attending to sleep complaints in people with migraine, as sleep interventions may not only improve sleep but also migraine frequency and severity [19,40]. When evaluating how specific components of sleep related to migraine characteristics/clinical features to deepen understanding of the associations discussed above, we found that sleep efficiency, which reflects sleep duration and the percentage of the total time in bed that one spends asleep, was the specific dimension of overall sleep quality that related to migraine characteristics/clinical features (i.e., MMD, phonophobia, nausea). These findings add to a mixed literature on migraine and sleep efficiency and duration [23,41,42,43]. Discrepant findings across studies may be due to differences in methodologies (e.g., self-report vs. actigraphy measures of sleep), study designs (e.g., studies assessing day-to-day associations between migraine and sleep vs. studies assessing these associations on average across several weeks), and sample characteristics (e.g., inclusion of individuals across the weight spectrum vs. only those with overweight/obesity, which itself relates to shorter sleep duration and poorer efficiency [44,45,46]). These data help elucidate which migraine characteristics/clinical features relate to different aspects of sleep quality, with potential to inform both mechanistic research and clinical care [40]. The major strengths of the current study include: evaluation of associations of both migraine characteristics and clinical features with sleep quality in a sample of individuals with comorbid migraine and overweight/obesity who are thus at potential elevated risk for poor sleep; use of smartphone-based daily diaries to obtain ecologically valid assessment of migraine characteristics and clinical features; and consideration of numerous confounders, including actigraphy-assessed physical activity and caffeine and alcohol intake as assessed by interviewer-administered recalls. Limitations include inclusion of only women, assessment of sleep quality at a single timepoint using a retrospective questionnaire, no assessment of sleep disorders other than OSA, and reliance on self-report of OSA diagnosis using a health history questionnaire (vs. a more validated OSA screener such as STOP-Bang) [47]. The study also did not assess day-to-day associations between sleep and migraine (i.e., the short-term effects of migraine today on sleep tonight or the effects of sleep tonight on migraine tomorrow), nor did it examine the influence of nocturnal migraine on sleep. Additionally, the sample was less racially and ethnically diverse than the U.S. population. It is critical for future studies assessing the migraine–sleep link to have more representative samples, particularly given significant disparities in migraine prevalence, pain and disability, and care [48,49]. Future studies would also benefit from including men and women; using both subjective measurement of sleep quality and objective measurement of physiological sleep paramaters; using a validated screener such as STOP-Bang or polysomnography to assess OSA; and further exploring optimal approaches for evaluating specific sleep domains when using the PSQI. It would also be advantagoues to apply a more interdisciplinary lens to understanding the relationships among migraine, sleep, and obesity (e.g., evaluating potential physiological abnormalities that contribute to poor sleep in this population, including hypothamalic dyfunction or disruptions in melatonin production [50]) and to consider assessing these associations over time to help tease apart these complex associations (e.g., evaluating whether sleep improves following successful migraine treatment that reduces migraine-related symptoms even if weight remains stable). ## 5. Conclusions In conclusion, this study shows that poor sleep quality is highly prevalent among women with migraine and overweight/obesity, although obesity severity was not uniquely related to sleep quality and did not moderate the associations between migraine and sleep quality. 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--- title: A Diet Containing Rutin Ameliorates Brain Intracellular Redox Homeostasis in a Mouse Model of Alzheimer’s Disease authors: - Paloma Bermejo-Bescós - Karim L. Jiménez-Aliaga - Juana Benedí - Sagrario Martín-Aragón journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003355 doi: 10.3390/ijms24054863 license: CC BY 4.0 --- # A Diet Containing Rutin Ameliorates Brain Intracellular Redox Homeostasis in a Mouse Model of Alzheimer’s Disease ## Abstract Quercetin has been studied extensively for its anti-Alzheimer’s disease (AD) and anti-aging effects. Our previous studies have found that quercetin and in its glycoside form, rutin, can modulate the proteasome function in neuroblastoma cells. We aimed to explore the effects of quercetin and rutin on intracellular redox homeostasis of the brain (reduced glutathione/oxidized glutathione, GSH/GSSG), its correlation with β-site APP cleaving enzyme 1 (BACE1) activity, and amyloid precursor protein (APP) expression in transgenic TgAPP mice (bearing human Swedish mutation APP transgene, APPswe). On the basis that BACE1 protein and APP processing are regulated by the ubiquitin–proteasome pathway and that supplementation with GSH protects neurons from proteasome inhibition, we investigated whether a diet containing quercetin or rutin (30 mg/kg/day, 4 weeks) diminishes several early signs of AD. Genotyping analyses of animals were carried out by PCR. In order to determine intracellular redox homeostasis, spectrofluorometric methods were adopted to quantify GSH and GSSG levels using o-phthalaldehyde and the GSH/GSSG ratio was ascertained. Levels of TBARS were determined as a marker of lipid peroxidation. Enzyme activities of SOD, CAT, GR, and GPx were determined in the cortex and hippocampus. ΒACE1 activity was measured by a secretase-specific substrate conjugated to two reporter molecules (EDANS and DABCYL). Gene expression of the main antioxidant enzymes: APP, BACE1, a Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), caspase-3, caspase-6, and inflammatory cytokines were determined by RT-PCR. First, overexpression of APPswe in TgAPP mice decreased GSH/GSSG ratio, increased malonaldehyde (MDA) levels, and, overall, decreased the main antioxidant enzyme activities in comparison to wild-type (WT) mice. Treatment of TgAPP mice with quercetin or rutin increased GSH/GSSG, diminished MDA levels, and favored the enzyme antioxidant capacity, particularly with rutin. Secondly, both APP expression and BACE1 activity were diminished with quercetin or rutin in TgAPP mice. Regarding ADAM10, it tended to increase in TgAPP mice with rutin treatment. As for caspase-3 expression, TgAPP displayed an increase which was the opposite with rutin. Finally, the increase in expression of the inflammatory markers IL-1β and IFN-γ in TgAPP mice was lowered by both quercetin and rutin. Collectively, these findings suggest that, of the two flavonoids, rutin may be included in a day-to-day diet as a form of adjuvant therapy in AD. ## 1. Introduction Decline in cognitive function is a fundamental clinical neurodegeneration symptom strictly related to age [1]. The impact of nutrition on age-associated cognitive decline is an increasingly growing topic, as it is a vital factor that can easily be modified. Pathological changes in the brain observed during cognitive decline take place well before any clinical manifestation, which mostly occur in old age. This provides a lengthy period of time to establish prevention strategies concerning age-related cognitive decline and dementia, which is a major public health concern [2]. For many years, intensive research on compounds of natural origin, found in day-to-day diets, has been carried out on cognitive-enhancing therapy [3]. One of the most common age-related neurodegenerative diseases is Alzheimer’s disease (AD), which is characterized by two neuropathological hallmarks: amyloid-β (Aβ) plaques and neurofibrillary tangles. In terms of research on animals, animal models can simulate the asymptomatic phase of AD by modifying the Aβ precursor protein (APP), for example [4,5]. It is remarkable that several bioactive phytochemicals derived from plants associated with various health benefits and decreased risk of many diseases have been screened for forming noncovalent complexes with the amyloid-β (Aβ) peptide [3]. Although numerous traditional medicines and natural dietary products have shown great progress toward AD pathology mitigation, we are fully aware of the limitations of AD animal models, since promising effects of those substances are not always replicable in human studies [6]. However, due to the difficulty of analyzing brain tissue in humans, especially at very early stages of progression, studies in rodent models are necessary. As a result, these experimental models may support the development of useful agents from traditional medicines and safe natural compounds to delay the progression of neurodegenerative diseases. Thus, testing natural compounds, found in day-to-day diets, for disease prevention and protection against the risk of AD, should be a priority. Among these important dietary natural agents is quercetin, which is the main polyphenolic flavonoid in several fruits and vegetables [7]. Quercetin is mainly present in its glycoside form, i.e., rutin. For its part, rutin (quercetin-3-O-rutinoside) has shown profound effects on the various cellular functions that underpin several pathological conditions, namely antimicrobial, anticarcinogenic, antithrombotic, cardioprotective, and neuroprotective. These pharmacological effects are mainly associated with rutin’s anti-inflammatory and antioxidant activities. Due to its ability to cross the blood–brain barrier, and/or its metabolites, it has been demonstrated that rutin is able to alter both cognitive and behavioral symptoms of neurodegenerative diseases [8]. Our previous studies have found that both flavonoids, quercetin and rutin, affect various signaling pathways and molecular networks associated with the modulation of proteasome functions in neuroblastoma cells [9]. In addition, it has been demonstrated that BACE1 expression and APP processing are regulated by the ubiquitin–proteasome pathway [10] and that supplementation with reduced glutathione (GSH) protected neurons from proteasome inhibition [11]. GSH depletion in the brain is a common finding in patients with neurodegenerative diseases, such as AD, and can cause neurodegeneration prior to disease onset [12]. Ubiquitination of BACE1 and blocking the ubiquitin–proteasome pathway inhibits BACE1 degradation and, consequently, leads to increased production of BACE1 enzymatic activity [10]. Based on these findings, and that dietary habits and supplementation can affect the cellular redox status, we aimed to explore the effects of a diet containing quercetin or rutin on intracellular redox homeostasis of the brain (GSH/GSSG), its correlation with BACE1 activity, and APP expression in mice models of AD (bearing human Swedish mutation Amyloid Precursor Protein APP transgene, APPswe). Finally, as there is convincing evidence of an effect of flavonoid supplementations in improving specific cognitive domains and/or MRI findings [13], we attempted to mimic, in animals, an intervention by delivering a healthy diet containing moderate amounts of a particular potential active ingredient (quercetin or rutin) as an effective strategy for preventing the expression of AD markers. ## 2.1. Genotyping of Mice The TgAPP mouse colony was developed in our laboratory from Tg2576 heterozygous males and wild-type females. Genotyping of mice was performed to detect transgenic individuals. Of all the mice tested, approximately $40\%$ were found to be transgenic (TgAPP). The PCR products obtained were separated by electrophoresis in $1.5\%$ agarose gels in 0.5X TBE (Tris-Borate-EDTA) buffer at 70 V (constant voltage) and then imaged by staining with GelRed (Millipore). The amplification profile for both transgenic and WT mice is shown in Figure 1. ## 2.2. Glutathione In order to evaluate intracellular redox homeostasis in neurons in TgAPP mice, GSH and GSSG levels were quantified, and the GSH/GSSG ratio was determined as a marker of cellular-reducing power in both males and females (Figure 2). In the assessment of the effect of the transgene on the glutathione system, a decline in the cellular-reducing power (GSH/GSSG) was observed in the TgAPP mice with respect to WT animals, in both males and females, and in both areas of the brain (Figure 2C3,H3), especially in hippocampus. In both WT and TgAPP mice, the GSH/GSSG ratio was significantly lower in males than in females (Figure 2C3,H3; $p \leq 0.05$). While in TgAPP females this decline is the result of lower GSH levels (Figure 2C1,H1), in TgAPP males it is mostly attributed to an increase in GSSG levels (Figure 2C2,H2). Changes in GSH and GSSG levels of TgAPP mice, respectively, upon quercetin or rutin treatment, are more prominent in males than in females. It seems that quercetin tends to augment GSH levels (Figure 2C1,H1; $p \leq 0.05$) and rutin to lower GSSG levels (Figure 2C2,H2; $p \leq 0.05$). Quercetin and rutin treatments, in both males and females, were able to reverse the fall in the ratio GSH/GSSG in hippocampus (Figure 2H3) where the recovery of redox power was significant versus the untreated TgAPP mice. In males, this index achieved similar values to those of WT mice in hippocampus (H3). In females, although this ratio is not raised up to that of the WT mice, treatment with quercetin and rutin enhanced it significantly in comparison to that of the TgAPP mice in their hippocampi (H3: quercetin, $p \leq 0.001$; rutin, $p \leq 0.05$). ## 2.3. Thiobarbituric Acid Reactive Substances (TBARs) Levels of TBARs were determined as a marker of lipid peroxidation. Using calibration curves, the results were expressed as malondialdehyde (MDA) concentration (Figure 3). Following APP overexpression, a significant increase in MDA levels when compared to WT mice was observed in both the cortex (Figure 3C) and the hippocampus (Figure 3H), and in both males and females ($p \leq 0.001$). In TgAPP females, both quercetin and rutin treatments almost restored MDA levels to the same as those of WT mice (Figure 3C,H). In TgAPP males, likewise, both quercetin and rutin treatments reinstate MDA levels to the same as those of WT mice in the cortex (Figure 3C), and are decreased even further in the hippocampus (Figure 3H). In both WT and TgAPP mice, untreated and flavonoid diet-treated, MDA levels were sex-dependent (Figure 3C,H; $p \leq 0.05$), except for the quercetin-treated TgAPP mice in hippocampus. ## 2.4. Enzyme Activity and Expression of Antioxidant Enzymes To address whether regulation of the enzymatic activity or the gene expression of the main antioxidant enzymes, or both, occurs upon a quercetin or rutin diet, determination of the enzymatic activity and mRNA levels was performed. Figure 4 shows the enzyme activities of SOD, CAT, GR, and GPx, determined in female and male mice, in the cerebral cortex (Figure 4a) and the hippocampus (Figure 4b). As a consequence of APP overexpression, only a significant decrease in CAT activity was observed in TgAPP mice compared to WT mice in both the cortex (Figure 4a(C2); $p \leq 0.05$) and the hippocampus (Figure 4b(H2); $p \leq 0.05$). Quercetin treatment did not produce any significant variation in enzyme activities in comparison to TgAPP mice, in males or females, in the brain areas studied. In contrast, animals treated with rutin experienced an increase in CAT activity in the cortex (Figure 4a(C2)) and in GR activity in the hippocampus (Figure 4b(H3)) in both males and females ($p \leq 0.05$). Moreover, rutin increased hippocampal CAT activity in TgAPP males (Figure 4b(H2)) and GPx activity in females (Figure 4b(H4)). Figure 5 shows the gene expression of the main antioxidant enzymes, SOD, CAT, GR, and GPx, determined in female and male mice, in the cerebral cortex (Figure 5a) and the hippocampus (Figure 5b). No differences in gene expression between TgAPP and WT mice are observed for the main antioxidant enzymes (Figure 5a,b). TgAPP males treated with rutin showed a significant increase in the expression of CAT in the hippocampus (Figure 5b(H2)). As for the hippocampal GPx, a similar pattern to CAT was observed, although the increase was not significant (Figure 5b(H4)). ## 2.5. APP Processing: BACE1 and ADAM10 The results of BACE1 enzyme activity in both the cerebral cortex and the hippocampus in males and females are shown in Figure 6, expressed as percentages of activity with respect to untreated TgAPP mice. In Figure 6, BACE1 enzyme activity in TgAPP mice was found to increase by around $10\%$ when compared to WT mice, in both the brain areas under investigation and in both sexes, and was found to be statistically significant ($p \leq 0.05$). The increase in activity observed in the transgenic mice was lowered by both quercetin and rutin treatments, both in the cortex and in the hippocampus. Nevertheless, it could still be noted that the rutin effect was slightly greater than that of quercetin in males. Once the activity of BACE1 was known, we decided to carry out the gene expression study of APP, the main characteristic of the transgenic animal model, and its main processing enzymes: BACE1 and ADAM10. Figure 7 shows the results obtained in female and male mice, both in the cortex and the hippocampus. In both sexes, a significant increase in APP expression greater than $85\%$ was observed with respect to WT mice, demonstrating the overexpression of the gene both in the cerebral cortex (Figure 7C1; $p \leq 0.05$) and in the hippocampus (Figure 7H1; $p \leq 0.05$). Treatments with quercetin and rutin were able to reduce this expression by more than $45\%$ ($p \leq 0.05$) for both male and female mice in both brain areas under investigation (Figure 7C1,H1), with the effects being more prominent in the hippocampus (Figure 7H1). As for the BACE1 protein expression, though BACE1 activity was altered, there were no significant differences between transgenic and non-transgenic mice regardless of sex and flavonoid treatment examined. Thus, we evaluated the ADAM10 expression involved in the non-amyloidogenic processing of APP. Although the changes in ADAM10 expression in TgAPP mice in comparison to WT mice were not statistically significant, a slight decrease was observed. Regarding the flavonoid treatments, rutin displayed an increasing trend in ADAM10 expression, both in males and females and in both areas of the brain (Figure 7C3,H3). ## 2.6. Expression of Caspase-3 and Caspase-6 TgAPP mice showed an increase in caspase-3 gene expression (Figure 8C1,H1), which was significant and greater than $30\%$ compared to the hippocampi of WT mice (Figure 8H1; $p \leq 0.05$). As for caspase-6 expression, no differences were observed between transgenic and non-transgenic mice (Figure 8C2,H2). Quercetin and rutin treatments were able to lower caspase-3 mRNA levels in the hippocampus in a statistically significant manner (Figure 8H1; $p \leq 0.05$), with inhibition percentages of around $17\%$ and $27\%$ for female and male mice, respectively. In the cerebral cortex, significant differences were only observed in the treatment with rutin in males (Figure 8C1; $p \leq 0.05$). With regard to caspase-6, quercetin and rutin treatments did not exert any statistically significant effect in the cortex or in the hippocampus (Figure 8C2,H2), though in the latter the Caspase-6 in TgAPP males showed a tendency to decrease (Figure 8H2). ## 2.7. Inflammation Markers The results obtained for gene expression of the inflammatory mediators IL-1β, TNF-α, and IFN-γ are shown in Figure 9. In the TgAPP, there was a significant increase in IL-1β gene expression of around $20\%$ in the cortex and hippocampus in both sexes compared to WT mice (Figure 9C1,H1; $p \leq 0.05$). As regards TNF-α, although higher mRNA levels are shown in TgAPP, they are not statistically significant in relation to WT mice (Figure 9C2,H2). Regarding IFN-γ, there was an increase of around $30\%$ in its expression in males, which was only statistically significant in the cortex (Figure 9C3; $p \leq 0.05$). Treatments with quercetin and rutin, both in females and males, were able to diminish IL-1β expression in the cerebral cortex and hippocampus in comparison to control TgAPP mice (Figure 9C1,H1; $p \leq 0.05$), obtaining similar values to those of WT mice, and particularly lower in the hippocampi of male mice (Figure 9H1; $p \leq 0.05$). The overall effect of both flavonoid treatments on IL-1β expression was not observed with TNF-α nor with INF-γ. Thus, TgAPP males, upon quercetin treatment, underwent a significant decrease in hippocampal TNF-α (Figure 9H2; $p \leq 0.05$) and in cortical IFN-γ expression (Figure 9C3; $p \leq 0.05$). ## 2.8. Assessment of Degenerating Neurons and Its Projections No characteristic signs of neurodegeneration were observed at the age at which the transgenic TgAPP mice were tested, compared to WT mice, nor did treatments with quercetin and rutin show any change for 4 weeks in comparison to TgAPP (Figure S1, Supplementary data). ## 2.9. Expression of Ionotropic Glutamate Receptors No significant differences were found in receptor expression, comparing the values obtained for the control TgAPP mice with those obtained for the WT mice. There were also no notable effects on the expression of these ionotropic receptors in the presence of quercetin or rutin treatment (Table S5, Supplementary data). ## 3. Discussion The purpose in our present study was to assess the impact of two flavonoids, quercetin and rutin, at the first stages of AD pathogenesis, regardless of their effect on neurodegeneration and/or cognitive function. The cortex and hippocampus were the areas of the brain under analysis, as they are the most affected brain structures in AD. It should be taken into account that quercetin and rutin were administered through a formulated diet containing either one of the two flavonoids, with the aim to mimic, in an AD animal model, the intake of a healthy human diet, containing an active ingredient. In particular, the transgene APPswe in the C57B6 mouse exerted a significant impact on GSH/GSSG ratio, MDA levels, antioxidant enzyme capacity, APP expression, BACE1 activity, and caspase-3 and IL-1β expression. Whilst APP mutations in humans generally result in typical AD, they are predominantly linked to solely amyloid pathology in APP transgenic mice and there is no noticeable neurodegeneration [14,15], as there were no characteristic signs observed in our transgenic mice TgAPP, contrary to the WT mice (Supplementary data, Figure S1). Counterstaining with 4′-6-diamidino-2-phenylindole (DAPI) of hippocampal neurons allowed us to observe the nuclear morphology, as this compound is a fluorescent dye for nucleic acids. We did not observe fragmented or lobular nuclei, typically apoptotic; nor did we observe any remarkable differences comparing the hippocampal histological sections of the control transgenic line TgAPP with respect to the WT sections; nor did we observe any differences between the quercetin and rutin treatments with respect to the control TgAPP mice. In the panel of AD biochemical features to be analyzed, we focused primarily on determining the GSH/GSSG ratio upon either one of the two flavonoid diets, since depletion of GSH levels represents one of the most important early biochemical markers in AD [16,17] and has been observed during its pathogenesis and disease progression. Measurement of brain GSH levels [18] and, more recently, blood GSH levels [19] have been promising as diagnostic markers for early stages of AD. Moreover, efforts have also been made to supplement endogenous GSH stores by themselves or their precursors [20,21,22]. In our study, a decline in the cellular reducing power (GSH/GSSG) was observed in the TgAPP mice with respect to WT animals, in both males and females, and in both areas of the brain. In cortex and hippocampus of both WT and TgAPP mice, the GSH/GSSG ratio was lower in male than in female. Quercetin and rutin diets significantly increased the GSH/GSSG ratio in comparison to untreated TgAPP mice, and this increase was more pronounced in the hippocampus. The changes in GSH and GSSG levels and GSH/GSSG ratio upon quercetin or rutin treatment of males, regarding increasing redox power, were more prominent than in females. The results from our determinations may reveal an important basis underlying sex-associated differences in Tg2576 mice in the susceptibility to the oxidative damage of macromolecules on one hand, since the glutathione system is a versatile reductant in multiple biological functions, and in the impact of preventive flavonoid diets in restoring its physiological status on the other hand. As we will see throughout this discussion, we have set the increase in the GSH/GSSG ratio as the main axis that might explain the set of effects observed in the TgAPP mice. It has recently been proposed that the GSH/GSSG ratio, rather than simply functioning as a redox buffer, would instead operate as a main regulatory mechanism, allowing proteins to attain their native conformation and functionality by tightly controlling the thiol-disulphide balance of the cellular proteome. In short, the glutathione system arises as essential to preserve a healthy proteome, showing that disruption of glutathione redox homeostasis (i.e., genetically or pharmacologically) increases protein aggregation due to disturbances in the efficacy of autophagy [23]. Therefore, strategies aimed at maintaining glutathione redox homeostasis may have a therapeutic potential in diseases associated with protein aggregation, such as AD. Closely related to the preservation of the proteome is the ubiquitin–proteasome degradation machinery, which is involved in the pathogenesis of AD. The proteasome selectively degrades multiple substrates that are crucial in maintaining neuronal homeostasis, including the catabolism of oxidized and aggregated proteins. BACE1 undergoes ubiquitination, and it has been demonstrated that blocking the ubiquitin–proteasome pathway will inhibit BACE1 degradation and consequently lead to increased production of BACE1 enzymatic activity, more β-cleavage product C99, and increases in both Aβ1-40 and Aβ1-42 in neuronal and non-neuronal cells [10]. Our previous studies have found that both flavonoids, quercetin and rutin, affect various signaling pathways and molecular networks associated with modulation of proteasome function in neuroblastoma cells [9]. In addition, it has been demonstrated that neurons supplemented with reduced glutathione (GSH) recovered the proteasome activity and reduced aggregate formation [11], since the proteasome function is redox status-regulated [24]. Therefore, the increase in the GSH/GSSG ratio experienced by the animals upon having a quercetin or rutin diet is consistent with the modulation of proteasome by quercetin and rutin, demonstrated ex vivo previously. As previously mentioned, redox imbalance leads to highly oxidatively-modified proteins that tend to accumulate and create aggregates resulting in proteasome impairment [25]. Thus, given the crucial role of oxidative stress in the pathogenesis of AD, biomarkers of oxidative stress, including lipid peroxidation (MDA levels) and antioxidant enzymes, were assessed in the cortex and hippocampus in the TgAPP and WT mice. SOD, CAT, GR, and GPx are the most important antioxidant enzymes that act against oxygen free radicals and regulate the metabolism of free radicals in the body and play a role in the free radical scavenging system, protecting the cells in the body from lipid peroxidation. In our study, as a consequence of APP overexpression, a generalized decrease in antioxidant enzyme activities was observed in TgAPP mice compared to WT mice, being statistically significant for CAT. Consistent with reduced GSH levels, lipid peroxidation was significantly increased in the TgAPP mice. While the source of oxidative stress in human AD is highly complex and multifactorial, the amyloid pathology developed in mice seems to be sufficient to initiate the pathological process leading to increased oxidative stress in the brain [26]. Animals treated with rutin experienced an increase in CAT activity in the cortex and in GR activity in the hippocampus, in both males and females. Only animals treated with rutin experienced changes in gene expression of CAT and GR in the cortex and the hippocampus in both males and females, and GPx in the hippocampi of female mice. In this context, several natural compounds have been shown to affect the crosstalk between the proteasome and redox regulation. More precisely, quercetin is a known Nrf2 activator [27] which exhibits antioxidant properties through the stimulation of proteasome function, promoting increased oxidative stress resistance and conferring enhanced cell longevity [28]. Tissue-specific expression of BACE1 is critical for normal APP processing, and its dysregulation expression may play a role in AD pathogenesis. BACE1 is predominantly expressed in hippocampal neurons, the cortex, and the cerebellar granular layer [10]. It should be noted that earlier studies have shown that Swedish mutant APP transgenic mice had significantly increased brain levels of Aβ at a steady state [29], suggesting that BACE1 plays an essential role in the amyloidogenic pathway in AD pathogenesis and is a good therapeutic target for AD treatment. In our study, we observed a significant reduction of BACE1 activity upon quercetin and rutin treatments, which might contribute to the decrease of Aβ deposition in mice. We argue that more than solely operating as BACE1 inhibitors of the enzyme, quercetin and rutin might exert a reduction in BACE1 activity related to an increase in the ratio GSH/GSSG, based on the hypothesis of an enhancing recovery of proteasome activity. In this sense, it is known that targeting of BACE1 inhibitors to the β-cleavage site of APPswe (Swedish mutation) occurs before it reaches the plasma membrane, whereas APPwt (Wild-type) is processed in an early endosome originating at the cell surface. Therefore, BACE1 that cleaves APPwt is sometimes bound to the BACE1 inhibitor on the cell surface prior to APP processing, however, the enzyme that processes APPswe is not [30]. It is for this reason that the aberrant localization of APPswe processing might significantly lower the potency of quercetin and rutin as BACE1 inhibitors. Thus, we are more inclined to support that the BACE activity’s decreasing in this in vivo model is not so much due to the inhibition of the enzyme but to the increase in the GSH/GSSG ratio. In any case, reduced BACE1 activity could be interpreted as a putative attempt to reduce β-amyloid production in the TgAPP mice. As for the most remarkable effect of quercetin and rutin in the hippocampus on BACE1 activity attenuation, it is worth noting that the cortex has a significantly higher neuron density than the hippocampus [31], and a selective impairment of the proteasome in AD pathological phenotype makes the cortex more vulnerable and affected than the hippocampus [32]. After determining the effect of the treatments on BACE1 enzyme activity, we were interested in evaluating its expression. Curiously, no significant differences in BACE1 expression were found between TgAPP mice compared to WT mice and no noticeable changes were observed with quercetin or rutin treatment. Therefore, it seems that the increase in BACE1 enzyme activity is not associated with an increase in expression. In this context, it is remarkable that Apelt et al. [ 14] found an increase in cortical BACE1 activity in Tg2576 mice between ages of 9 and 13 months while the expression level of BACE1 protein and mRNA did not change with age. Furthermore, evidence has been found supporting that fibrillar amyloid Aβ1–42., rather than soluble amyloid Aβ1–42, is able to upregulate BACE1 protein expression, and thus small modifications in the ratio of amyloid isoforms may modulate amyloid aggregate conformations and cell damage [33]. Thus, the absence of change in BACE1 expression upon an increase of its activity that we found may account for the prevalence of soluble amyloid Aβ1–42 over the fibrillar amyloid Aβ1–42 isoform in our mouse model TgAPP. Following the determination of gene expression of the enzymes involved in APP processing, we evaluated the effect of quercetin and rutin on the enzyme α-secretase involved in the non-amyloidogenic processing of APP. We focused on ADAM10 because it is the physiologically most important constitutive isoform of α-secretase. ADAM10 counteracts the generation of neurotoxic oligomeric Aβ plaques via cleaving APP within the Aβ domain to produce sAPPα and C-terminal fragment (α-CTF) [34,35]. Although the changes in ADAM10 expression found in our study were not statistically significant, a slight decrease in ADAM10 expression was observed in TgAPP mice relative to WT mice. Predominantly, rutin treatment showed a tendency to increase ADAM10 gene expression in both brain areas under study. Postina et al. [ 36] showed that the up-regulation of wild-type ADAM10 in the hippocampus of an AD mouse model mediated sAPPα secretion, leading to inhibition of Aβ plaques generation. The effect of quercetin has been studied in an aluminum chloride-induced AD rat model showing a significant enhancement of the α-secretase (ADAM10 and ADAM17) in the hippocampus compared to untreated ones. This indicates that quercetin possesses the potential to increase the non-amyloidogenic pathway through the activation of α-secretase genes [37]. Preclinical data reinforce the hypothesis that enhancing brain sAPPα levels is a potential strategy to improve AD-related symptoms and attenuate synaptic deficits. ADAM10 and BACE1 compete for the APPβ cleavage, therefore potentiating ADAM10 activity might inhibit the neurotoxic amyloid generation. Moreover, sAPPα can prevent the activation of the stress JNK-signaling pathway, leading to activation of NF-κB-induced phosphorylation activity, which leads to proteasome degradation [38]. Therefore, the formation and the accumulation of disease-related protein aggregates are significantly reduced, and the cellular proteasome activity is enhanced, thereby providing evidence for a function of sAPPα in the regulation of proteostasis [39]. Furthermore, it has been demonstrated that sAPPα specifically upregulates glutamate AMPA receptor synthesis and its trafficking [40]. In our study, we explored whether the slight increase of ADAM10 expression upon rutin treatment exerts some influence in glutamatergic synaptic transmission. As shown in the *Supplementary data* section, no significant effects on the expression of these ionotropic receptor were observed upon quercetin and rutin diets, perhaps due to a weak increase in ADAM10 expression, which is not sufficient for the upregulation of the AMPA receptor (Supplementary data, Figure S2 and Table S5). It should be taken into consideration that in vitro studies have shown a wide variety of ADAM10 substrates [41], and therefore, undesirable effects obtained by non-specific ADAM10-targeting might be found in cancer proliferation, cell adhesion, promotion of T cell/NK-cell precursor and inflammation, etc. [ 42]. To circumvent this constraint, our study suggests a strategy aimed at promoting the release of sAPPα in a more physiological manner. This approach might be based on a long-term intake of an active ingredient (quercetin or rutin), which is consumed through a healthy human diet. However, further studies are needed to find out whether the increase in ADAM10 is flavonoid dose-dependent and whether the potential beneficial effects outweigh putative side effects. As for the expression of APPswe, although the insertion of the human APP transgene in the mouse genome guarantees that APPswe is overexpressed from birth, it has been reported that APP mRNA and protein hippocampal levels show significant fluctuations during the animal development, being maximal when mice are asymptomatic (1-month-old) and decreasing when full symptomatology occurs [43]. Notwithstanding this issue, APP expression both in the cortex and the hippocampus was significantly higher compared to that of WT mice in our study. Further treatment with quercetin or rutin was able to significantly reduce such expression for both male and female mice, in both areas of the brain. These findings are in line with those reported by Augustin et al. [ 44] who studied a standardised extract of *Ginkgo biloba* (Egb761), rich in flavonols such as quercetin, in 4-month-old female TgAPP mice, finding decreased APP mRNA and protein levels. Taking into consideration that upregulation of APP translational in Tg2576 mice occurs in the prodromal and early symptomatic stages [45], it is likely that a restoration of APP translation by quercetin or rutin might have taken place in our TgAPP mice and, likely, in an early symptomatic stage, resulting in reduction of cortical and hippocampal levels of APP, BACE1 activity, and caspase-3 activation. Furthermore, it has been reported elsewhere that in Tg2576 mice (in the absence of neuronal loss) there is an increase in caspase-3 activation in the hippocampus [46], as found in our study, at the onset of memory impairment, together with a reduction in dendritic spines prior to the deposition of extracellular amyloid [46]. There is evidence in support of non-apoptotic roles for caspases in the nervous system without neuronal death [47], and caspase-3 activity has been localized to dendritic spines where it may elevate calcineurin levels. In turn, the dephosphorylation of GluR1 subunit of AMPA-like receptors, triggered by calcineurin is thought to result in postsynaptic dysfunction. Our values of caspase-3 expression, as a consequence of transgenesis, are in agreement with those obtained by other researchers who reported an increase in caspase-3 expression at the level of dendritic spines in the hippocampus of TgAPP mice [48]. Since APP contains three distinct cleavage sites for caspase-3 in its amino acid sequence, two of which are located at the level of the extracellular domain and one in the intracellular C-terminal portion of the APP tail [49], hydrolysis of APP by caspase-3 may alter the proteolytic processing of APP in favor of the amyloidogenic pathway [50], leading to the release of a cytotoxic C-terminal-derived peptide of 31 amino acids in length (C31), for example [51]. This suggests that, since caspase-3 can mediate the amplification of toxic fragment release from APP, lowering caspase-3 expression by quercetin or rutin may allow for the clearance of aggregated protein. In addition, as mentioned earlier, we have explored the influence of both the increase and decrease of caspase-3 expression in glutamatergic synaptic transmission, based on the ability of calcineurin-activated caspase-3 to dephosphorylate the GluR1 subunit of AMPA receptors at the postsynaptic level. These molecular modifications alter glutamatergic synaptic transmission and neuronal plasticity at the level of dendritic spines in the hippocampus [48]. Theoretically, pharmacological inhibition of caspase-3 activity in TgAPP mice might save the AD-like phenotypes from a mechanism that drives synaptic failure. However, despite the augmentation in caspase-3 expression in our TgAPP mouse, we found no significant differences in AMPA receptor expression compared to that in WT mice, as mentioned earlier. It might be that the changes in caspase-3 expression are not prominent enough to produce significant modifications in AMPA receptor expression (Supplementary data, Figure S2 and Table S5). As for the values of caspase-6 expression, no significant differences were found between TgAPP and WT mice. Activation of caspase-6 has been identified as an important mediator of neuronal stress that cleaves important cytoskeletal proteins (Tau and α-tubulin), thus disrupting the ubiquitin–proteasome degradation of misfolded proteins, and a number of actin-regulating post-synaptic density proteins [52]. The unchanged expression of caspase-6 in our study agrees with the absence of characteristic signs of neurodegeneration at the age at which these transgenic mice were evaluated, compared with the WT mice (Supplementary data, Figure S1). A marked increase in neuroinflammatory mediators has been observed in AD patients, mainly around senile plaques [53,54,55]. Astrocytes are the main supplier of GSH to microglia and neurons. During chronic inflammation and oxidative stress, astrocytes release toxic inflammatory mediators and free radicals, accelerating activation of microglia and neurodegeneration [56]. It is worth noting that decreased intracellular glutathione is related to the activation of the inflammatory pathways, p38 MAP-kinase, Jun-N-terminal kinase (JNK), NF-κB, in human microglia and astrocytes [57]. In this regard, we decided to quantify the levels of IL-1β, IFN-γ, and TNF-α in our animal model and determine the effect of quercetin and rutin on them. As is known, inflammation promotes defective processing of Aβ peptide and APP, promoting Aβ peptide aggregation and in turn modifying Aβ reactivity [58]. Thus, in our study, we observed that TgAPP mice had increased mRNA levels of the pro-inflammatory mediators IL-1β, TNF-α and IFN-γ, compared to WT mice, showing that overexpression of APPswe might induce neuro-inflammatory cascades triggering a series of molecular pathways in glia and neurons, which would activate the inflammatory response. Quercetin and rutin were able to attenuate IL-1β gene expression in both males and females and in the brain areas studied. Several pieces of evidence support the anti-inflammatory effect exerted by quercetin at the CNS level, as it may inhibit the activation of transcription factors such as the nuclear factor-kappa B (NF-κB) [59], involved in the induction of iNOS, and therefore, decrease the release of mediators such as IL-1β, TNF-α and IFN-γ [60]. Regarding the impact of GSH on the inflammatory response, it should be noted that GSH is involved in the maintenance of optimal cytokine levels in such a way that the expression of pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) are increased due to GSH depletion, whereas the expression of anti-inflammatory cytokines (i.e., IL-10) remained unaltered. This GSH homeostasis alteration happens due to upregulation in NF-κB and JNK signaling pathway which could be the feasible apoptotic pathway towards neuronal cell death [61]. In our study, down-regulation of NF-κB by quercetin and rutin might be a plausible mechanism to recover the GSH/GSSG homeostasis and therefore the cause of the balance between pro-inflammatory and anti-inflammatory cytokines. Lastly, since BACE1 promotor has an NF-κB binding site, inflammation-induced activation of NF-κB facilitates the upregulation of BACE1 expression, and subsequently increases Aβ production [62]. Thus, if down-regulation of NF-κB occurs upon quercetin and rutin diets, BACE1 activity would decrease as a result of the release regulation of pro-inflammatory and not anti-inflammatory cytokines. ## 4.1. Experimental Animals A transgenic mouse (Tg2576, B6;SJL-Tg(APPswe)2576 Kha) that expresses the Swedish double mutation of human amyloid precursor protein (hAPP) was used as the animal model of experimental AD [14]. The mouse is a knock-in heterozygote line which expresses the human AβPP695 isoform with the double Swedish mutation (K670N/M671L; Lys670→Asn and Met671→Leu) under the control of the hamster prion protein promoter [63]. As a result, this mouse exhibits levels of human amyloid-β precursor protein (Aβ PP), six times greater than that of a mouse’s Aβ PP levels. In addition, this mouse shows higher levels of Aβ40 and Aβ42. Aβ deposits begin at 9 months of age [63]. Within the Tg2576 hippocampus and cortex, APPswe transgene expression is primarily neuronal [64]. As a negative control, wild-type (WT) mice from the same colony [65,66] were used. The Tg2576 (B6;SJL-Tg(APPswe)2576 Kha) mouse colony was developed in our laboratory from Tg2576 heterozygous males and wild-type females. The transgenic parents were donated by Dr. Diana Frechilla from the Neuroscience Division at the Centre for Applied Medical Research at the University of Navarra (Pamplona, Spain) [67]. Animals were housed in individual ventilated cages and kept at 22–24 °C on a 12-h light/dark cycle in 50–$60\%$ humidity. Animal protocols were approved by the Institutional Animal Care and Use Committee (IACUC) at the Complutense University of Madrid and were in full accordance with the European Directive $\frac{2010}{63}$/on the protection of animals used for scientific purposes and Spanish legislation on Animal Welfare (Royal Decree $\frac{53}{2013}$, 1 February 2013). ## 4.2. Genotyping Analyses of Mice Transgenicity was determined within 30 days of birth by tail biopsy. Genotyping analyses of animals were carried out by PCR. Considering that Tg2576 (TgAPP) is a heterozygous line, the insertion gene (PrP, from prion protein) was used as a positive reaction control. Genomic DNA was extracted from mouse tails digested with proteinase K (0.1 μg/μL) in NID buffer (50 mM KCl, 50 mM Tris-HCl pH 8.3, 50 mM MgCl2, $0.05\%$ gelatin, $0.45\%$ NP-40 and $0.4\%$ Tween 20) at 56 °C for 3 h and shaken. DNA fragments were precipitated with isopropanol and washed with $70\%$ ethanol. DNA precipitates were dissolved in 30 μL of TE buffer (10 mM Tris-1 mM EDTA). The purity and concentration of DNA was determined at 260 and 280 nm. The PrP and APP genes were amplified by PCR. Sequences of primers used to screen the transgenic mice were as follows: PrP forward: CCTCTTTGTGACTATGTGGACTGATGTCGG; PrP reverse: GTGGATACCCCCTCCCCCAGCCTAGACC; APP reverse: CCAGATCTCTGAAGTGAAGATGGATG. The steps of the PCR reaction were as follows: denaturation at 94 °C for 90 s, 39 cycles at 60 °C for 60 s and 72 °C for 90 s, then final extension at 72 °C for 7 min. In all cases, negative controls (without DNA mold) and positive controls of the APP gene were considered. The PCR products obtained were separated by electrophoresis in $1.5\%$ agarose gels in 0.5X TBE (Tris-Borate-EDTA, Merck KGaA, Darmstadt, Germany) buffer at 70 V (constant voltage) and then imaged by staining with GelRed (Millipore). ## 4.3. Animal Treatments TgAPP mice and wild-type littermates, both aged 6–7 weeks with an initial body weight of 16.2 ± 0.8 g, were randomized into the following four groups ($$n = 8$$/group): (a) Untreated TgAPP; (b) Quercetin-treated TgAPP; (c) Rutin-treated TgAPP; and (d) Untreated wild-type. Since both male and female mice were studied, two sets of groups were established. At the age of 45 weeks, the mice started to be treated with quercetin or rutin for 4 weeks. Quercetin (3,3′,4′,5,7-pentahydroxyflavone) and rutin hydrate (quercetin-3-O-rutinoside hydrate) were ≥$95\%$ pure and purchased from Sigma–Aldrich. Each one of the flavonoids was incorporated into a standard diet (Harlan Ibérica, Barcelona, Spain) at a concentration of 200 ppm, corresponding to an intake of 30 mg flavonoid/kg body weight/day. The untreated mice received exclusively the un-supplemented standard diet. Diets and water were provided for ad libitum intake. ## 4.4. Brain Tissue Preparation for Biochemical and Histological Assays At the end of treatment, mice were fasted overnight, they were euthanized by means of cervical dislocation, and the entire brain was quickly removed. The brain was rinsed in saline at 4 °C and the arachnoid membrane was carefully removed. Then, the hippocampus and cortex were isolated. Samples were immediately stored at −80 °C until further use. The entire brains of some animals were used for obtaining histological sections, for which, once euthanized by means of cervical dislocation, brains were frozen by immersion in isopentane at −80 °C. Immediately afterwards, coronal sections of the brain (30 μm of thickness) were made from the olfactory bulb to the cerebellum, 120 μm apart in a cryostat (Leica CM1850, Nussloch, Germany). The whole procedure was performed at −20 °C. Histological sections were collected on slides and kept at −80 °C until analysis (See Supplementary Methods). ## 4.5. Glutathione For glutathione tests, cerebral cortex and hippocampus samples were homogenized in a redox-quenching buffer-$5\%$ Trichloride acetic acid (RQB-$5\%$ TCA) (previously bubbled with N2 for 15 min on ice) at a concentration of 25 mg/mL (w/v). Samples were resuspended by sonication for 10 s, then centrifuged at 12,000× g for 10 min at 4 °C, and supernatants were collected. Then, in the supernatant obtained, spectrofluorometric methods were adopted to determine GSH and GSSG levels using the o-phthalaldehyde method, described by Senft et al. [ 68]. GSH and GSSG values were corrected for spontaneous reaction in the absence of biological sample. In both cases, supernatants were incubated for 30 min at room temperature and afterwards fluorescence was measured using a FLUOSTAR microplate reader (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany), with the excitation filter set at 360 nm (bandwidth 5 nm) and the emission filter set at 460 nm (bandwidth 5 nm). The concentration of GSH and GSSG in each sample was interpolated from known GSH standards. Concentrations of both GSH and GSSG were expressed as nmol GSH/mg protein, which allowed for the calculation of the glutathione redox ratio GSH/GSSG. The remaining pellets were vortexed until completely dissolved in 240 μL of 0.1 M NaOH to measure protein concentration by the bicinchoninic acid (BCA) method, using bovine serum albumin as a standard. ## 4.6. Thiobarbituric Acid-Reactive Substances (TBARs) The content of TBARs was used as an index of lipoperoxidation. In brain tissue, 50 mM phosphate buffer (pH 7.4) was added to a concentration of 25 mg/mL (w/v) and the suspension was homogenized by sonication for 10 s. To 30 μL of the homogenate, 250 μL of $1\%$ phosphoric acid and 75 μL of $0.6\%$ thiobarbituric acid (TBA) were added. The reagent mixture was incubated at 100 °C in a water bath for 45 min, after which it was cooled in an ice bath and then centrifuged at 3000× g for 10 min at 4 °C. A volume of 150 μL of supernatant was taken from each sample. Fluorescence was measured using a FLUOSTAR microplate reader (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany) with the excitation filter set at 485 nm (bandwidth 5 nm) and the emission filter set at 530 nm (bandwidth 5 nm). A calibration curve was prepared using malondialdehyde (MDA) as a standard. The results were expressed in pmol MDA/mg protein. ## 4.7. Enzymatic Activity of the Main Antioxidant Enzymes For the determination of enzyme activity in brain tissue, a lysis buffer containing 50 mM phosphate buffer (pH 7.4) and antiproteases (1 mM EDTA, 1 mM PMSF, 1 g/mL pepstatin and 1 g/mL leupeptin) was added to a concentration of 50 mg/mL (w/v). Then, suspension was sonicated for 30 s in an ice bath, and the homogenate was centrifuged at 10,000× g for 15 min at 4 °C. Supernatants were collected for the determination of the enzymatic activity of the antioxidant enzymes. Superoxide dismutase (SOD) activity was measured by following the inhibition of pyrogallol autoxidation at 420 nm [69]. One unit of enzyme was defined as the amount of enzyme required to inhibit the rate of pyrogallol autoxidation by $50\%$. The SOD enzymatic activity was expressed as international units (IU)/mg protein. Catalase (CAT) activity was measured in Triton-X-100 ($1\%$, v/v)-treated supernatants by following hydrogen peroxide (H2O2) disappearance at 240 nm [70], and enzyme activity was reported as substrate (μmol H2O2) transformed/min ∙ mg protein. Total glutathione peroxidase (GPx) was determined following NADPH oxidation at 340 nm in the presence of excess GR, GSH, and cumene hydroperoxide [71]. GPx activity was expressed as substrate (nmol NADPH) transformed/min mg protein. Glutathione reductase (GR) activity was analyzed following NADPH oxidation at 340 nm in the presence of GSSG [72] and expressed as substrate (nmol NADPH) transformed/min ∙ mg protein. GR and both GPx activities were corrected for spontaneous reaction in the absence of biological samples (in the absence of enzyme). ## 4.8. BACE1 Activity Test The ΒACE1 test protocol involves the use of a secretase-specific substrate (peptide) which is conjugated to two reporter molecules, namely EDANS and DABCYL, which results in the release of a fluorescent signal [73,74]. The BACE1 activity was measured both in the cortex and hippocampus lysates. The reaction was carried out at 37 °C for 1 h using 10 μM substrate in 50 mM sodium acetate buffer (pH 4.5). Fluorescence intensity measurements were done using a FLUOSTAR microplate reader (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany) with the excitation filter set at 360 nm (bandwidth 5 nm) and the emission filter set at 530 nm (bandwidth 5 nm). The level of secretase enzymatic activity is proportional to the fluorometric reaction, and the data are expressed as x-fold increase in fluorescence over that of background controls (reactions in the absence of substrate or tissue). The BACE1 activity was normalized with protein concentration. The mice’s BACE1 activity, quercetin or rutin-treated, was expressed as the percentage of activity of that of TgAPP control mice. ## 4.9.1. Total RNA Extraction and Purification We analyzed the different areas of the brain, namely the cortex and hippocampus, stored at −80 °C. To a known amount of brain tissue, Triomol® lysis buffer was added at a ratio of 1:10 (w/v). Samples were homogenized for 30 s using a Cordless motor (Pellet pestle, Sigma-Aldrich), and incubated for 5 min at 25 °C to allow for complete dissociation of nucleoprotein complexes. Then, 0.2 mL of chloroform was added for each mL of Triomol® lysis buffer used. The tubes were shaken vigorously for 15 s and incubated at 25 °C for 3 min. Then, they were centrifuged at 11,000× g for 15 min at 4 °C. After centrifugation, three phases were obtained, with RNA in the upper phase. To isolate the RNA, the upper phase was transferred to another tube and precipitated by adding 0.5 mL isopropanol. After thorough mixing of isopropanol and aqueous solution by inversion, the mixture was incubated at room temperature for 10 min to promote precipitation, and centrifuged at 12,000× g for 10 min at 4 °C. The supernatants were removed, and the pellets were washed with $75\%$ ethanol and centrifuged at 7500× g for 5 min at 4 °C. The pellets were dried at room temperature and dissolved in 50 μL of DEPC-treated water. To remove traces of DNA, 2.5 μL of DNase (RNase-free) was added and incubated at 37 °C for 30 min. Finally, samples were incubated at 64 °C for 5 min to inactivate the DNase. Subsequently, the concentrations of RNA were measured in a UV-VIS spectrophotometer (BMG LABTECH, Ortenberg, Baden-Württemberg, Germany) at 260 nm and the purity was assessed considering the absorbance ratio at 260 and 280 nm (A260/A280). The determination of RNA integrity and purity was performed by electrophoresis in a $1\%$ agarose gel stained with GelRed and visualized under UV light, where, if the RNA was intact, two upper bands corresponding to ribosomal RNA (28S and 18S) and two lower bands corresponding to transfer RNA (tRNA) and 5S ribosomal RNA had to be observed. ## 4.9.2. Complementary DNA (cDNA) Synthesis cDNA is much more stable than RNA and therefore allows for more convenient and safer sample handling. The cDNA was synthesized from mRNA by retrotranscription using the First Strand cDNA Synthesis Kit for RT-qPCR (Fermentas Life Sciences). In order to carry out the retrotranscription for cDNA synthesis to 2 μg of RNA, 11 μL of DEPC-treated water and 1 μL of 10X Random primers were added. Then, the mixture was incubated at 65 °C for 10 min to denature the RNA. After this time, the tubes were immediately brought to 4 °C for 5 min to avoid renaturation of the RNA. The reagent mix for cDNA synthesis is shown in Table S1 (Supplementary data). Eight μL of the reaction mixture was added to each sample. The entire volume was brought to the bottom of the tubes and incubated at 42 °C for 60 min. Finally, the reaction was stopped by inactivating the reverse transcriptase by heating it at 70 °C for 10 min. ## 4.9.3. Real-Time PCR The main feature of real-time PCR is that the analysis of the products takes place during the amplification process by determining the fluorescence. In this way, the amplification and detection processes occur simultaneously in the same tube or vial without the need for any further action. For real-time PCR, thermal cyclers are used, which can amplify and detect fluorescence simultaneously. We utilized the LightCycler real-time thermal cycler (Roche Diagnostics, Mannheim, Germany). Table S2 (Supplementary data) lists the reagents required for real-time PCR, using sequence-specific primers and DNA-binding dye (SYBR Green I, Roche Molecular Systems, Inc., Rotkreuz, Switzerland) as a detection system. For the design of the primers for the different quantified markers, the Primer3Plus bioinformatics program (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi, accessed on 21 January 2023) was used, for which we took the cDNA sequences of the genes of interest from the Medline open-access database (http://www.ncbi.nlm.nih.gov/entrez, accessed on 21 January 2023). The primers were supplied by Merck (Sigma-Aldrich). The hybridization temperature and the sequence of the different primers used are shown in Table S3 (Supplementary data). The reaction conditions for the amplification of the genes of interest are shown in Table S4 (Supplementary data). Finally, the samples were subjected to a melting program: 95 °C for 15 s, 65 °C for 30 s, and up to 98 °C at a rate of 0.1 °C/s with continuous fluorescence recording. For the quantification of cDNA levels, the cycle threshold (Ct) comparison method [75] was used, using GADPH as a housekeeper. The amplification of the housekeeper was done in parallel with the analyzed gene. Ct values were calculated using the 4.0 software provided by LightCycler (Roche Diagnostics, Mannheim, Germany). The software allows distinguishing between fluorescence due to sample amplification and due to background. Melting curves were also recorded. Determination of the melting temperature of the amplified fragment allowed for characterization of the amplified product. The size of the bands was checked on a $1.5\%$ agarose gel. The variation of the expression of the gene under study with the quercetin or rutin treatment was expressed as a function of the control TgAPP (mice without treatment) and normalizing this expression with the levels of GADPH. The Change Fold (2−ΔΔCt) represents the number of times that the gene of interest is modified under the particular treatment with respect to the control mice. ## 4.10. Statistical Analyses All tests were performed at least in duplicate and in three different experiments. The results obtained are expressed as the mean ± standard error. One-way analysis of variance (ANOVA) was performed once the data were tested and demonstrated that it fits a normal distribution. The Newman–Keuls multiple comparison post-hoc test was run, examining mean differences between groups. Values of $p \leq 0.05$ were considered significant. SigmaPlot 11.0 software was used for statistical analyses. ## 5. Conclusions Dietary habits and supplementation can affect the cellular redox status. On this basis, we aimed to ameliorate the cellular redox homeostasis in an AD mouse model by a flavonoid diet containing quercetin or rutin in order to alleviate amyloid pathology, considering the interplay between cellular redox status and proteasome-dependent amyloid features in asymptomatic AD. Our datasets are relevant, since the flavonoid effects displayed in the TgAPP mouse model are consistent with those reported earlier in our in vitro and ex vivo models. In conclusion, our findings show that initiating a diet treatment at the asymptomatic stage or at the onset of AD-like symptoms might reinstate cellular redox status and APP physiological processing via concurrent regularization of APP expression and BACE1 activity. Although it is difficult to extrapolate our findings to the human condition, they may have broad implications for the human response to future therapeutics. 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--- title: Vapor-Induced Pore-Forming Atmospheric-Plasma-Sprayed Zinc-, Strontium-, and Magnesium-Doped Hydroxyapatite Coatings on Titanium Implants Enhance New Bone Formation—An In Vivo and In Vitro Investigation authors: - Hsin-Han Hou - Bor-Shiunn Lee - Yu-Cheng Liu - Yi-Ping Wang - Wei-Ting Kuo - I-Hui Chen - Ai-Chia He - Chern-Hsiung Lai - Kuo-Lun Tung - Yi-Wen Chen journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003357 doi: 10.3390/ijms24054933 license: CC BY 4.0 --- # Vapor-Induced Pore-Forming Atmospheric-Plasma-Sprayed Zinc-, Strontium-, and Magnesium-Doped Hydroxyapatite Coatings on Titanium Implants Enhance New Bone Formation—An In Vivo and In Vitro Investigation ## Abstract Objectives: Titanium implants are regarded as a promising treatment modality for replacing missing teeth. Osteointegration and antibacterial properties are both desirable characteristics for titanium dental implants. The aim of this study was to create zinc (Zn)-, strontium (Sr)-, and magnesium (Mg)-multidoped hydroxyapatite (HAp) porous coatings, including HAp, Zn-doped HAp, and Zn-Sr-Mg-doped HAp, on titanium discs and implants using the vapor-induced pore-forming atmospheric plasma spraying (VIPF-APS) technique. Methods: The mRNA and protein levels of osteogenesis-associated genes such as collagen type I alpha 1 chain (COL1A1), decorin (DCN), osteoprotegerin (TNFRSF11B), and osteopontin (SPP1) were examined in human embryonic palatal mesenchymal cells. The antibacterial effects against periodontal bacteria, including *Porphyromonas gingivalis* and Prevotella nigrescens, were investigated. In addition, a rat animal model was used to evaluate new bone formation via histologic examination and micro-computed tomography (CT). Results: The ZnSrMg-HAp group was the most effective at inducing mRNA and protein expression of TNFRSF11B and SPP1 after 7 days of incubation, and TNFRSF11B and DCN after 11 days of incubation. In addition, both the ZnSrMg-HAp and Zn-HAp groups were effective against P. gingivalis and P. nigrescens. Furthermore, according to both in vitro studies and histologic findings, the ZnSrMg-HAp group exhibited the most prominent osteogenesis and concentrated bone growth along implant threads. Significance: A porous ZnSrMg-HAp coating using VIPF-APS could serve as a novel technique for coating titanium implant surfaces and preventing further bacterial infection. ## 1. Introduction Titanium dental implants have revolutionized dentistry and become one of the most common treatment options for replacing missing teeth in partially or fully edentulous patients [1]. Osseointegration is defined as the direct functional and structural connection between living bone and the load-bearing surface of a titanium implant [2]. Osseointegration includes primary stability (mechanical stability) and secondary stability (biological stability). Mechanical stability is determined by the bone density and implant design, whereas biological stability is associated with physiologic bone healing. The cellular and molecular phenomena that occur during osseointegration form a cascade including blot clot formation, angiogenesis, the migration of osteoprogenitor cells, woven bone formation, and bone remodeling [3]. Therefore, the surface treatment of a dental implant may influence bone deposition and determine the implant success at an early stage. Various studies have proposed increasing surface hydrophilicity and attracting osteoprogenitor cells using the advantages of metal ions [4,5,6,7,8]. Treating titanium implant surfaces with calcium phosphate deposition via immersion in simulated body fluid under physiological conditions of temperature (37 °C) and pH (7.4) has been proven to enhance surface hydrophilicity, attract osteoinductive agents, and promote bone healing [9]. Strontium (Sr) has been reported to regulate osteoblast-related gene expression, enhance alkaline phosphatase (ALP) activity, and reduce osteoclast differentiation [5]. Strontium ranelate has been demonstrated to increase runt-related transcription factor 2 (Runx2) expression and matrix mineralization and attenuate bone resorption in an osteopenic mouse model [6]. Zinc (Zn) and magnesium (Mg) are essential elements for increasing alkaline phosphatase activity [7,8] and bone protein synthesis [10], thus promoting bone formation [11]. Peri-implantitis is defined as soft tissue inflammation and progressive bone loss around dental implants and is considered a polymicrobial anaerobic infection associated with biofilms [12,13]. Various clinical regimes for preventing and treating peri-implantitis have been proposed based on its pathophysiology, including mechanical debridement, laser treatment, locally delivered antiseptics, local or systemic antibiotics, and surgical access and regenerative procedures. However, a gold standard protocol for treating peri-implantitis has yet to be established [14]. Metal coatings, such as Ag+, Zn2+, Sr2+, Mg2+, Ca2+, F−1 and Sc+3, and antimicrobial peptides have been reported to inhibit bacterial adhesion and enhance osseointegration [15,16,17,18,19]. Hydroxyapatite (HAp) coatings doped with 1 wt% AgNO3 (AgHA1.0) exhibit the ability to minimize the initial adhesion of *Streptococcus aureus* and *Staphylcoccus epidermidis* [20]. Metal ions can prevent the emergence of drug-resistant bacteria resulting from the overuse of antibiotics. Titanium plates coated with a copper-HAp composite via two-stage electrochemical synthesis have demonstrated excellent antibacterial properties against *Escherichia coli* (Gram-negative) and S. aureus (Gram-positive) [21]. Moreover, Zn has been added to toothpaste and mouth rinses to inhibit calculus deposition and the growth of cariogenic bacteria [22]. Therefore, the development of an implant surface with antimicrobial properties is essential. Implant coating materials, such as metals (titanium and its alloys, aluminum alloys, cobalt, and zirconium), ceramics (HAp), and polymers (polyurethane and polyethylene), are crucial to maintaining superior mechanical properties, corrosion resistance, and antimicrobial properties [23]. Surface modification treatments, including physical (electron beam evaporation, thermal spraying, pulsed laser deposition, and thermal evaporation) and chemical methods (chemical vapor deposition, electrophoretic deposition, and sol–gel coating), have been widely applied to improve surface properties [23]. HAp is among the most in-demand materials for the modification of surface properties for optimal osseointegration in implantology [24,25,26]. Furthermore, HAp is resistant to X-ray and UV irradiation and does not display visible aging/structural damage [27,28]. Our previous study proved that the vapor-induced pore-forming atmospheric plasma spraying (VIPF-APS) technique could effectively produce a porous HAp coating and contribute to a more bioactive coating for osteoblast proliferation [29]. Sr- and Mg-doped HAp implants were demonstrated to enhance osteoblast proliferation and new bone formation in a beagle dog model [29]. To the best of our knowledge, the effect of Zn-, Sr-, and Mg-multidoped HAp-coated titanium implants on the enhancement of bone formation has yet to be investigated. In addition, Zn-, Sr-, and Mg-multidoped HAp coatings produced using the VIPF-APS technique have never been examined. Therefore, the novelty of this study lies in the use of the VIPF-APS technique to create Zn-, Sr-, and Mg-multidoped HAp porous coatings on titanium discs and implants. The mRNA and protein levels of osteogenesis-associated genes such as collagen type I alpha 1 chain (COL1A1), decorin (DCN), osteoprotegerin (TNFRSF11B), and osteospontin (SPP1) were examined. The antibacterial effects against periodontal bacteria, including *Porphyromonas gingivalis* and Prevotella nigrescens, were investigated. Moreover, a rat model was used to evaluate osseointegration via histologic examination and micro-computed tomography (micro-CT). ## 2.1. ZnSrMg-HAp Promotes Osteointegration-Associated Gene and Protein Expression in HEPM Cells The HEPM cells were incubated on titanium discs coated with HAp, Zn-HAp, or ZnSrMg-HAp for 3 (Figure 1A), 7 (Figure 1B), and 11 days (Figure 1C). The purified cellular total RNA was used for a qPCR assay with primer sets of COL1A1, DCN, TNFRSF11B, and SPP1. The mRNA levels of TNFRSF11B and SPP1 significantly increased in the ZnSrMg-HAp group after 7 days of incubation compared with those of the HAp group (Figure 1B). Moreover, the mRNA levels of TNFRSF11B and DCN also significantly increased in the ZnSrMg-HAp group after 11 days of incubation compared with those of the HAp group (Figure 1C). To confirm the protein expression level according to the previous qPCR results, the cellular lysate was used in a Western blot assay. The protein levels of TNFRSF11B and SPP1 significantly increased in the ZnSrMg-HAp group after 7 days of incubation compared with those of the HAp group (Figure 2A,B). Moreover, the protein levels of TNFRSF11B and DCN significantly increased in the ZnSrMg-HAp group after 11 days of incubation compared with those of the HAp group (Figure 2C,D). These results demonstrated that the titanium discs coated with ZnSrMg-HAp prominently increased the expression of osteointegration-associated genes and proteins and suggested that the ZnSrMg-HAp coating promoted osteointegration ability. ## 2.2. Antibacterial Activity Test of HAp, Zn-HAp, and ZnSrMg-HAp Coatings on Titanium Discs against P. gingivalis and P. nigrescens The ZnSrMg-HAp group demonstrated superior antibacterial activity against P. gingivalis compared with the Zn-HAp and HAp groups (Figure 3A). The ZnSrMg-HAp and Zn-HAp groups demonstrated prominent antibacterial activity against P. nigrescens. However, no difference was observed between the ZnSrMg-HAp and Zn-HAp groups (Figure 3B). In contrast, the HAp group did not demonstrate an apparent antibacterial effect against P. gingivalis or P. nigrescens. ## 2.3. Micro-CT Assessment Micro-CT reconstruction images are shown in Figure 4A. Within the ROI of 0.85 mm and 1.1 mm, the bone coverage rate was significantly higher in the Zn-HAp and ZnSrMg-HAp groups compared to the HAp group at 2 and 4 weeks (Figure 4B,C). BV/TV was also significantly higher in the Zn-HAp and ZnSrMg-HAp groups at 2 and 4 weeks compared to the HAp group (Figure 4D). In contrast, the Zn-HAp and ZnSrMg-HAp groups exhibited significantly lower BMDs at 2 and 4 weeks compared to the HAp group (Figure 4E). ## 2.4. Histological Findings Figure 5 shows that the ZnSrMg-HAp group exhibited better osteointegration than the HAp and Zn-HAp groups. At 2 weeks after implantation, the HAp group only achieved integration within the cortical bone area (the first and second threads). A focal discontinuous deposit of the bone on the implant surface was observed down to the interthread area between the third and fourth threads. Similar effects were also discerned in the Zn-HAp group, with a patchy surface bony deposit present down to the region slightly beyond the tip of the fifth thread (the third thread in the cancellous bone). In contrast, continuous bone formation on the implant surface was evident down to the lower slope of the sixth thread in the ZnSrMg-HAp group. The advantage of ZnSrMg-HAp surface processing in terms of osteointegration was more profound 4 weeks after implantation. Continuous and complete bone coverage was identified on all threads in the cancellous bone in the ZnSrMg-HAp group, whereas this feature could only be found down to the fourth and fifth threads in the HAp and Zn-HAp groups, respectively. At higher magnification (100×, thickened bone deposition was more apparent on the implant surface in the ZnSrMg-HAp group than in the HAp and Zn groups. ## 3. Discussion This was the first study to use VIPF-APS to prepare porous coatings on dental implant surfaces. In addition, three-element doped HAp was successfully produced using ion doping technology. Compared with multi-element doped HAp prepared using the traditional solid-phase method [30], the coprecipitation method adopted in this study controlled the amount of ion doping more precisely and suppressed the generation of other non-targeted substances resulting from HAp phase transformation or an incomplete oxidative process [31]. Various coating techniques, such as plasma spraying, hydrocoating, two-stage processing, physical vapor deposition, thermally applied coating, and nanoscale technology, have been developed for implant surface modification [32]. Plasma spraying is the most commonly used technique for applying ion coatings on implant surfaces. The physical principles of the novel VIPF-APS technique in this study are based on the penetration of expansive vapors through melted HAp. The porous structure serves as a cavity for the recruitment of undifferentiated mesenchymal cells to the implant surface compared with the dense HAp coatings using traditional APS. Achieving a balance between mechanical strength and adequate pore size for bone ingrowth is critical for implant surface modification. In this study, the pore diameter of the coatings on titanium discs prepared via VIPF-APS was approximately 38 μm [33]. Our previous study demonstrated that the VIPF-APS technique could effectively produce porous HAp coatings that are favorable for higher osteoblast proliferation and alkaline phosphatase activity. The size of interconnecting pores is critical in affecting bone ingrowth. A pore size between 100 and 400 μm has been suggested to be favorable for bone ingrowth [34]. Another study showed that a pore size range of approximately 50 to 400 μm is optimal for fixation strength (17 MPa) [35]. The HAp coatings prepared using the VIPF-APS technique had more than $8\%$ porosity compared to the traditional APS technique [31]. Therefore, we used the advantage of the VIPF-APS technique to produce Zn-, Sr-, and Mg-doped HAp coatings on titanium discs and implants. In addition to the successful preparation of porous HAp coatings on dental implants, this study also succeeded in preparing a three-element doped HAp coating powder for VIPF-APS. HEPM cells are preosteoblasts that can differentiate into osteoblasts on titanium plates [36]. The growth and differentiation of osteoblasts can be divided into three periods based on the different genes expressed in each period: proliferation, extracellular matrix maturation, and extracellular matrix mineralization. First, collagen 1 and 2 (COL1, 2) are upregulated in the early stages of osteoblast differentiation. Next, SPP1 is required for extracellular matrix maturation. Finally, in the period of extracellular matrix mineralization, Ca2+ binding proteoglycans such as biglycan and DCN are secreted [37]. In addition, DCN has been proven to modulate collagen matrix assembly and mineralization [38] and regulate the cell cycle [39]. Otherwise, TNFRSF11B, a tumor necrosis factor receptor superfamily member, functions as a negative regulator of bone resorption by regulating osteoclast development [40]. Thus, we quantified the mRNA and protein expression of gene markers, including COL1, SPP1, DCN, and TNFRSF11B at different stages of HEPM (3, 7 and 11 days). The results showed that Zn-HAp had significantly higher COL1 and DCN mRNA than the HAp group on the third day. On the 11th day, Zn-HAp and ZnSrMg-HAp had significantly higher DCN and TNFRSF11B activity than HAp. In a previous study, human dental pulp stem cells cultured on Zn-modified titanium plates were proven to enhance the expression of osteoblast-related genes, such as COL1, bone morphogenetic protein 2, ALP, Runx2, osteopontin, and vascular endothelial growth factor A in vitro [41]. Our results were in agreement with previous studies that demonstrated the upregulating ability of Zn in an osteoblast culture (24–72 h) [42,43]. In addition, ZnSrMg-HAp had significantly higher SPP1 and TNFRSF11B activity than the HAp group on the seventh day. In bone-defect mice, the promoter activity of nuclear factor-kappa beta and vascular endothelial growth factor receptor-2 is upregulated by Sr supplementation [44]. Mg supplementation has been proven to upregulate the mRNA of peroxisome proliferator-activated receptor gamma and glucose transporter 1 in peripheral blood mononuclear cells from women with gestational diabetes [4]. The results of this study were in line with the process of bone differentiation and proved that Zn alone or ZnSrMg were effective in improving bone growth and maturation. In other words, ZnSrMg plays a critical role in the process of osteoblast growth and differentiation in vitro. Antibiotics represent the most effective method for treating peri-implantitis in a clinical setting. However, bacterial resistance could be a concern because of excessive antibiotic usage [45]. To examine the effect of element-doped HAp coatings against periodontal pathogens, we chose P. gingivalis and P. nigrsecens as the target bacteria. Our results showed that the antibacterial activity of the ZnSrMg-HAp group was superior to that of the Zn-HAp group. Previous studies have reported that Zn, Sr, and Mg ions released from HAp coatings enhanced bone mineralization and exhibited antibacterial properties [46,47,48]. The release of mental ions from HAp coatings formed an alkaline environment and was not favorable for bacterial growth. Moreover, the membrane potential difference caused by metal ions may result in electron transfer and generate excessive amounts of reactive oxygen species, which further kills bacteria [49]. An implant surface with antibacterial properties, particularly the inhibition of biofilm formation and bacterial adhesion, is the most promising strategy for preventing or treating peri-implantitis. Unlike the results regarding protein expression shown in Figure 2, the bone coverage rate in the Zn-HAp group was not significantly different from that of the ZnSrMg-HAp group. The reason might be that animals were sacrificed after at least 2 weeks, which was longer than the examination time for protein expression. The bone growth for osteointegration occurs very early after implant placement. The ZnSrMg-HAp group exhibited a higher bone coverage rate at an ROI of 0.85 mm compared with the Zn-HAp group at both 2 and 4 weeks (Figure 4B). In contrast, the bone coverage rate was higher in the Zn-HAp group than in the ZnSrMg-HAp group at an ROI of 1.1 mm (Figure 4C). However, no significant difference was found for both ROIs. The Sr2+ and Mg2+ ions released from ZnSrMg-HAp could stimulate osteogenesis and new bone formation concentrated along the implant threads. Therefore, the bone coverage rate of the ZnSrMg-HAp group was more prominent at the smaller ROI (0.85 mm). These results were in agreement with the histological findings, which demonstrated that the ZnSrMg-HAp group exhibited more prominent continuous bone coverage on implant threads compared with the HAp and Zn-HAp groups (Figure 5). In addition, the concentrated bone growth on implant threads observed during the histological examination was not composed of cancellous bone. The bone volume fraction (BV/TV) did not differ significantly between the Zn-HAP and ZnSrMg-HAp groups (Figure 4D). The reason for this may be that the BV/TV was examined at an ROI of 1.1 mm and the animals were sacrificed at least 2 weeks after implant placement, as discussed previously. Compared with HAp coatings on titanium implants, the Zn-HAp and ZnSrMg-HAp groups showed significantly less bone mineral density (Figure 4E); these two groups exhibited more newly formed and unmineralized woven bone around the titanium implants, which in turn caused the lower bone mineral density. ## 4.1. Preparation of HAp, Zn-Doped HAp, and Zn-Sr-Mg-Doped HAp Coatings on Titanium Implants Using the VIPF-APS Technique The preparation details of HAp, Zn-doped HAp, and Zn-Sr-Mg-doped HAp powders were described in a previous study [30]. Briefly, HAp coatings doped with different metal ions were prepared and denoted as HAp, Zn-HAp [Zn/(Ca+Zn) = $2.5\%$], and ZnSrMg-HAp [Zn/(Ca+Zn+Sr+Mg) = $2.5\%$, Sr/(Ca+Zn+Sr+Mg) = $5\%$, Mg/(Ca+Zn+Sr+Mg) = $5\%$]. The molar ratio of Ca(NO3)2/(NH4)2HPO4 was 10:6 for HAp, that of [Ca(NO3)2 + Zn(NO3)2]/(NH4)2HPO4 was 10:6 for Zn-HAp, and that of [Ca(NO3)2 + Sr(NO3)2 + Mg(NO3)2 + Zn(NO3)2]/(NH4)2HPO4 was 10:6 for ZnSrMg-HAp. The synthetic parameters were pH = 10 and a calcination temperature of 800 °C. The VIPF-APS technique was used to deposit HAp, Zn-HAp, and ZnSrMg-HAp on titanium implants (Stryker Leibinger GmbH & Co. KG, Freiberg, Germany) that were made of Ti6Al4V alloy, 5 mm in length and 1.2 mm in diameter (Figure 6). The technique involved water vapor being splashed on the titanium implant. The surfaces of the implant were roughened by sandblasting to Ra = 11.20 μm and then sprayed with a thin layer of HAp coating. After immersion in pure water, a single spray cycle was applied to the implant surface repeatedly until the desired thickness of HAp coating was achieved (30 µm). Finally, a porous surface structure was formed [33]. ## 4.2. Reverse Transcriptase Quantitative Polymerase Chain Reaction Human embryonic palatal mesenchymal (HEPM) cells (ATCC®CRL-1486TM) were incubated on titanium discs (diameter: 15 mm, thickness: 2 mm, Biomate Swiss GmbH, Zug, Switzerland) coated with HAp, Zn-HAp, or ZnSrMg-HAp for 3, 7, and 11 days. Subsequently, HEPM cells were used with TRIzol reagent (15596026, Invitrogen, Waltham, MA, USA) to extract mRNA. Purified cellular total RNA (100 ng) was used with the Power SYBR™ Green RNA-to-CT™ 1-Step Kit for reverse-transcription reaction. The corresponding cDNA was used in a quantitative polymerase chain reaction (qPCR) assay with Biorad CFX96 (Bio-Rad, Hercules, CA, USA) with primer sets of COL1A1, F: GATTCCCTGGACCTAAAGGTGC, and R: AGCCTCTCCATCTTTGCCAGCA; DCN, F: AGCTGAAGGAATTGCCAGAA, and R: CTCTGCTGATTTTGTTGCCA; TNFRSF11B, F: GAACCCCAGAGCGAAATAC, and R: CGCTGTTTTCACAGAGGTC; SPP1, F: CGAGGTGATAGTGTGGTTTATGG, and R: GCACCATTCAACTCCTCGCTTTC; and GAPDH, F: GTCTCCTCTGACTTCAACAGCG, and R: ACCACCCTGTTGCTGTAGCCAA [50,51]. ## 4.3. Cell Culture, Protein Extraction, and Immunoblot Analysis HEPM cells were cultured on titanium discs coated with HAp, Zn-HAp, or ZnSrMg-HAp for 7 and 11 days at 37 ℃ in an incubator with $5\%$ CO2 in Dulbecco’s modified Eagle’s medium/F12 (1:1) (1×) (21041-025, Gibco™ - Thermo Fisher Scientific, Waltham, MA, USA) supplemented with $10\%$ fetal bovine serum and $1\%$ antibiotic pen-strep-amphotericin. HEPM cells were lysed using radioimmunoprecipitation assay buffer (W-7849-500, Goal Bio, Taipei, Taiwan) and cellular lysates were centrifuged at 12,000× g rpm for 5 min for supernatant collection. The extracted protein was quantified using a protein assay kit (500-0006, Bio-Rad, Hercules, CA, USA). Equal amounts of protein were separated using $10\%$ sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to Amersham Hybond P 0.45 μm polyvinylidene fluoride (10600023, GE Healthcare, Chicago, IL, USA). After blocking with $5\%$ skimmed milk, the membranes were incubated with various primary antibodies and then incubated with the corresponding secondary antibodies. The protein bands were detected using an Amersham ECL Select Western Blotting Detection Reagent (RPN2235, GE Healthcare, Chicago, IL) and quantified using ImageQuant 5.2 software (Healthcare Bio-Sciences, Pittsburgh, PA, USA). All experiments were repeated in triplicate ($$n = 3$$). ## 4.4. Antibacterial Activity Test P. gingivalis (ATCC 33277) and P. nigrescens (ATCC 332563) were stored at −80 °C and separately cultured on Brucella blood agar plates (Taiwan Prepared Media, Taipei, Taiwan) at 37 °C for 7 days under standard anaerobic conditions ($80\%$ N2, $10\%$ H2, and $10\%$ CO2). A strain of a single colony of these bacteria was then separately cultured in 5 mL of brain heart infusion broth (Neogen, Lansing, MI, USA) with 5 g of yeast extract (Thermo Fisher, Waltham, MA, USA) and an L-cysteine solution (0.5 g/mL) (Sigma-Aldrich, Lyon, France) at 37 °C under anaerobic conditions for 48 h. Subsequently, these bacteria were collected via centrifugation at 3000× g rpm for 10 min. Each resultant bacterial pellet was washed 3 times with sterile phosphate-buffered saline and then adjusted to a concentration of 1.6 × 108 colony-forming units (CFU)/mL before use [52]. The test samples were sterilized using saturated steam at 121 °C for 30 min. The HAp, Zn-HAp and ZnSrMg-HAp titanium discs were placed in P. gingivalis and P. nigrescens broth and incubated at 37 °C under anaerobic conditions for 120 h ($$n = 4$$). The bacterial suspension served as the control group. After 120 h, 1 mL was taken from each suspension, pipetted onto anaerobic blood agar, and cultured at 37 °C under standard anaerobic conditions for 120 h to count the CFU. ## 4.5. Animal Model Eight-week-old male Sprague Dawley rats (The Jackson Laboratory, BioLASCO Taiwan Co., Ltd., Taipei, Taiwan, 232.11 ± 20.33 g) were used ($$n = 18$$, randomly divided into 6 groups in 6 cages) following the guidelines and protocols of the Institutional Animal Care and Use Committee of National Taiwan University (IACUC-20200127). All animals were given free access to water and standard rat food (fat 50 g/kg, protein 226 g/kg, and metabolizable energy 3030 kcal/kg). The environment was maintained at a temperature between 20 °C and 24 °C and relative humidity between $40\%$ and $70\%$. Moreover, the rats were kept under a 12 h light/dark cycle. All animal experiments complied with the ARRIVE guidelines and were conducted following the National Research Council’s Guide for the Care and Use of Laboratory Animals. ## 4.6. Implantation Thirty-six titanium implants were coated with HAp, Zn-HAp, and ZnSrMg-HAp ($$n = 12$$). The titanium implants were randomly allocated to 2 experiment durations (2 and 4 weeks, $$n = 6$$ each) and placed in the tibia of 18 rats that were anesthetized with 20–40 mg/kg of Zoletil® 50 (Virbac, Carros, France) mixed with 5–10 mg/kg of Rompun® (Bayer, Leverkusen, Germany). Each rat received a 5–6 mm longitudinal skin incision along the tibia. After soft tissue dissection, 2 holes were drilled into the tibia bone using a 1.0 mm electronic drill at low speeds (800–2000 rpm), and 3 types of titanium implants were randomly allocated to be inserted into the holes. The wound was sutured layer by layer, and the stitches were removed after 1 week of healing. In addition, analgesics and antibiotics were provided in the drinking water (0.2 mg/mL of ibuprofen and 0.268 mg/mL of ampicillin in $5\%$ dextrose) to reduce post-surgical pain and infection. All rats were sacrificed after 2 and 4 weeks of implantation. A flowchart of the animal experiment is shown in Figure 7. ## 4.7. Micro-CT Evaluation The tibia was harvested and scanned using the high-resolution SKYSCAN 1076 micro-CT apparatus (Skyscan NV, Kontich, Belgium). The bone coverage rate was defined as the percentage of direct bone-to-implant contact on the titanium implants. Two cylinders (0.85 and 1.1 mm in radius, 2.0 mm in length) starting from the first thread of the titanium implant were defined as the region of interest (ROI) [53,54]. For the evaluation of the bone volume fraction (bone volume/total volume, BV/TV) and bone mineral density (BMD), the ROI was defined as a cylinder (1.1 mm in radius and 2.0 mm in length) starting from the first thread of the titanium implant. The micro-CT technician and histological analyzer were blind to the sample groups. ## 4.8. Histological Examination After fixation, serial dehydration, and embedding, resin blocks were trimmed to an appropriate size. The implant was sectioned into symmetrical halves using a low-speed saw (Isomet, Buehler Ltd., Lake Bluff, IL, USA) with a wafering diamond blade (6.6 cm × 0.15 mm) [55]. Cutting was performed at a blade speed of 100 to 500 rpm, using tap water as a lubricant, and with a force of 0.3 to 7 N acting on the specimen. The surface of the exposed specimen was polished using 600- or 800-grit silicon carbide paper followed by 4000-grit paper under water lubrication to remove cutting marks and obtain a highly polished surface. Subsequently, specimens were stained with Stevenel’s blue and then counterstained with alizarin red S for histological examination. ## 4.9. Statistical Analysis An analysis of variance was used to examine the differences among all the groups, and Tukey’s post hoc test was used for qPCR and Western blotting to identify significant differences between 2 specific groups. A p-value less than 0.05 was considered statistically significant. ## 5. Conclusions In conclusion, porous ZnSrMg-HAp was successfully coated on titanium implants using the VIPF-APS technique. The ZnSrMg-HAp group was the most effective at inducing mRNA and protein expression of TNFRSF11B and SPP1 after 7 days of incubation, and TNFRSF11B and DCN after 11 days of incubation. The ZnSrMg-HAp group also demonstrated superior antibacterial activity against P. gingivalis. The animal model suggested that BV/TV was significantly higher in the Zn-HAp and ZnSrMg-HAp groups at 2 and 4 weeks compared to the HAp group. In addition, continuous bone coverage and thickened bone deposition was more apparent on the implant surface in the ZnSrMg-HAp group than in the HAp and Zn groups. However, notably, bone adjacent to the implant surface does not equate to a structural or functional connection between bone and the implant. Both osteointegration and antibacterial properties are essential characteristics for preventing peri-implantitis. Therefore, ZnSrMg-HAp has the potential to be used as a bioactive coating material for implant surfaces and consequently improve the survival rate in clinical use. ## References 1. 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--- title: Antiviral Effect of Ginsenosides rk1 against Influenza a Virus Infection by Targeting the Hemagglutinin 1-Mediated Virus Attachment authors: - Xia Yang - Hailiang Sun - Zhening Zhang - Weixin Ou - Fengxiang Xu - Ling Luo - Yahong Liu - Weisan Chen - Jianxin Chen journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003360 doi: 10.3390/ijms24054967 license: CC BY 4.0 --- # Antiviral Effect of Ginsenosides rk1 against Influenza a Virus Infection by Targeting the Hemagglutinin 1-Mediated Virus Attachment ## Abstract Influenza A virus (IAV) infections have been a serious hazard to public health everywhere. With the growing concern of drug-resistant IAV strains, there is an urgent need for novel anti-IAV medications, especially those with alternative mechanisms of action. Hemagglutinin (HA), an IAV glycoprotein, plays critical roles in the early stage of virus infection, including receptor binding and membrane fusion, making it a good target for developing anti-IAV drugs. Panax ginseng is a widely used herb in traditional medicine with extensive biological effects in various disease models, and its extract was reported to show protection in IAV-infected mice. However, the main effective anti-IAV constituents in panax ginseng remain unclear. Here, we report that ginsenoside rk1 (G-rk1) and G-rg5, out of the 23 screened ginsenosides, exhibit significant antiviral effects against 3 different IAV subtypes (H1N1, H5N1, and H3N2) in vitro. Mechanistically, G-rk1 blocked IAV binding to sialic acid in a hemagglutination inhibition (HAI) assay and an indirect ELISA assay; more importantly, we showed that G-rk1 interacted with HA1 in a dose-dependent manner in a surface plasmon resonance (SPR) analysis. Furthermore, G-rk1 treatment by intranasal inoculation effectively reduced the weight loss and mortality of mice challenged with a lethal dose of influenza virus A/Puerto Rico/$\frac{8}{34}$ (PR8). In conclusion, our findings reveal for the first time that G-rk1 possesses potent anti-IAV effects in vitro and in vivo. We have also identified and characterized with a direct binding assay a novel ginseng-derived IAV HA1 inhibitor for the first time, which could present potential approaches to prevent and treat IAV infections. ## 1. Introduction Influenza A virus (IAV), a single-stranded RNA virus belonging to the Orthomyxoviridae family, is the cause of influenza, a contagious and acute respiratory disease accompanied by fever [1]. IAV has a broad host range and comprises many subtypes [2], causing severe health problems, mortality, and socio-economic losses globally. Seasonal IAV infections result in 290,000 to 650,000 fatalities yearly worldwide [3]. Outbreaks of highly pathogenic avian influenza (HPAI), such as H5N1 (1997 and 2003), H7N7 [2003], and H7N9 [2013], have resulted in alarmingly high fatality rates [4,5,6]. Vaccines and drugs are the two main approaches to prevent and treat IAV infections. However, IAV vaccines have many limitations that affect their efficacy, including the potential genetic mismatching between virus strains used in the vaccines and those circulating and in the elderlies with reduced or compromised immunity. There are now three kinds of flu medications that have FDA approval: neuraminidase (NA) inhibitors (NAIs) (i.e., oseltamivir, zanamivir, and peramivir), matrix protein 2 (M2) inhibitors (amantadine and rimantadine) [7], and a cap-dependent endonuclease inhibitor (Baloxavir marboxil) [8]. Unfortunately, M2 ion channel inhibitors have very limited effect because of extensive resistance from clinically circulating strains [9]. Meanwhile, resistant IAV strains against NAIs and Baloxavir are also increasing [10,11,12]. Therefore, developing novel anti-IAV agents is of great importance. So far, the core targets included RNA-dependent RNA polymerase (RdRp), hemagglutinin (HA), neuraminidase (NA), and M2 proton channel [13]. However, since HA plays a critical role during viral entry, inhibition of HA means blocking the initial step of viral infection, which could be especially significant if conserved sites in HA are blocked to potentially have broad-spectrum anti-influenza effects [14]. Therefore, HA is an attractive target for the development of anti-influenza drugs. Two phylogenetic groups—group 1 (H1, H2, H5, H6, H8, H9, H11, H12, H13, H16, H17, and H18) and group 2 (H3, H4, H7, H10, H14, and H15)—can be formed from the 18 distinct HA subtypes that have been reported [15]. In the form of a homotrimer, mature HA is essential for viral attachment and membrane fusion. The primary translation product, HA0, which has numerous glycosylations, is cleaved into two disulfide-linked polypeptides, HA1 (which contains the receptor binding site (RBS)) and HA2 (which contains the fusion domain), to form the HA monomer [16]. Recent preclinical studies have reported significant therapeutic effects of anti-HA neutralizing antibodies, such as C05, CR9114, CR6261, and CR8020, but there are still challenges with their manufacturing and supply [17,18,19]. Small compounds, as opposed to antibodies, offer great shelf stability and are relatively inexpensive to produce [20]. Therefore, developing novel HA inhibitors is urgently needed for controlling seasonal influenza and potential outbreaks of epidemics induced by newly emerging IAVs in the future. Panax ginseng, a well-known herbal nutritional supplement commonly used in traditional medicine, is widely utilized in East Asian countries, such as China and Korea [21]. Currently, more and more attention is being paid to Panax species due to their extensive biological effects in various disease models. It contains a plethora of pharmacologically active compounds, including ginsenosides, polysaccharides, polyacetylenes, phytosterols, and essential oils. Over 280 ginsenosides have been identified from Panax species and are believed to be the primary bioactive components [22]. Ginsenosides have a wide range of biological actions, including anti-cancer, anti-cardiovascular disease, anti-obesity, anti-diabetes, and anti-central nervous system disorder effects, as well as enhancing strength and sexuality [23]. Additionally, ginseng extracts or ginsenosides were reported to have antiviral activities against human pathogenic virus infections, such as hepatitis (HAV and HBV), HIV-1, human herpes (HSV-1, HSV-2), and respiratory syncytial virus (RSV) [24,25,26,27,28]. Wang et al. reported that fermented ginseng extracts improved the survival of mice infected with various IAV strains, including H1N1, H3N2, and H7N9 [29]. Additionally, feeding mice and ferrets a diet rich in red ginseng prevented them from contracting the highly pathogenic H1N1 influenza virus, which can be fatal [30]. Dong et al. reported that ginsenoside rb1 (G-rb1) protected mice from lethal 2009 pandemic H1N1 infection. Moreover, G-rb1 inhibited IAV infection by preventing viral particles’ attachment to α 2-3′ sialic acid (SA) receptors on Chinese hamster ovary cells [31]. Unfortunately, G-rb1 administration after viral infection did not show any protection on 2009 panH1N1-infected mice, and this study also used a very high concentration of G-rb1 (450 µM) in vitro, indicating a likely weak interaction between G-rb1 and viral HA. However, ginseng extracts have shown significant antiviral effects against IAV infection in vivo [29,30]. Therefore, we speculated that there might be more effective antiviral constituents in ginseng, which would certainly deserve further exploration. This study focused on identifying anti-IAV ginsenosides and the underlying antiviral mechanism. Our results demonstrate that G-rk1 and G-rg5 possess remarkable anti-IAV effects in IAV-infected A549 cells, and G-rk1 intranasal administration exhibited significant protection in IAV (PR8, H1N1)-infected mice. To the best of our knowledge, this is the first concrete proof that ginseng-derived G-rk1 binds HA1 and may act as an inhibitor of IAV entry. ## 2.1. Cell Cytotoxicity and Inhibitory Effects of G-rk1 and G-rg5 against IAV Infection in A549 Cells According to the quantity of hydroxyl and glycosidic linkages connecting the aglycone moiety to the ginsenoside, ginsenosides are divided into two groups: protopanaxadiol (PPD) and protopan-axatriol (PPT). The smaller and less polar ginsenosides were created during the steaming of ginseng through hydrolysis, dehydration, and isomerization at C-3, C-6, or C-20 [32]. To identify the antiviral properties of ginsenosides, the inhibitory effects of 14 PPDs (Figure S1) and 9 PPTs (Figure S2) at 10 μM against PR8 replication in A549 cells were evaluated using IFA. Ribavirin, a well-known inhibitor of viral RNA synthesis [33], is used as a positive control that significantly inhibits the replication of IAV PR8 (Figure S3). Out of the 23 compounds, 6 ginsenosides, including ginsenoside rg1, Mb, 20(S)-rg2, 20(R)-rg2, rg5, and rk1, exhibited significant inhibition of PR8 replication, reflected by reduced viral NP expression. Noticeably, less polar ginsenosides (20(S)-rg2, 20(R)-rg2, G-rk1, and G-rg5) exhibited stronger antiviral activity than ginsenosides rg1 and Mb, and G-rk1 and G-rg5 displayed the strongest inhibition (Figure S4). The CC50 and EC50 values were determined, as shown in Table S1. To determine the safety and efficacy of G-rk1 and G-rg5 (their chemical structures are shown in Figure 1A) against PR8 infection, we first evaluated their cytotoxicity in A549 cells using the MTT assay. G-rk1 was not cytotoxic to A549 cells at doses of 20 μM after 48 h of treatment or 15 μM after 72 h of therapy (Figure 1B). A549 cells had a slightly greater safety dose for G-rg5, a structurally geometric isomer of G-rk1. No overt cytotoxicity on A549 cells was seen at concentrations of 30 μM after 48 h of treatment and 15 μM after 72 h of treatment. Based on these results, we selected 15 μM as the maximum concentration in subsequent studies. G-rk1 and G-rg5 had CC50 values of 34.8 and >40 μM, respectively, on A549 cells after 72 h (CC50 is the concentration needed to cut normal cell viability by $50\%$). The antiviral activity of the two compounds was confirmed by IFA. As shown in Figure 2A, G-rk1 and G-rg5 attenuated viral NP expression dose-dependently. Noticeably, 15 μM of G-rk1 protected $95\%$ of cells from PR8 infection. Our results showed that 80 μM of ribavirin exhibited obvious protection on PR8-infected A549 cells, as well. Cytopathic effects in G-rk1- or G-rg5-treated wells were reduced (Figure 2B), indicating the protection of the two compounds on A549 cells from PR8 infection. Additionally, we used virus titration at 48 hpi to investigate the antiviral activity of G-rk1 and G-rg5 against PR8 infection. Treatment with G-rk1 or G-rg5 greatly decreased the amount of virus (Figure 2C). Compared to the DMSO-treated control, 15 μM of G-rk1 and G-rg5 caused a 2.8 or 2.4 log reduction, respectively, in the virus titer. Next, we investigated the IAV inhibition kinetics in A549 cells with G-rk1 and G-rg5 at 15 μM by measuring virus titers at 24, 48, or 72 h post PR8 infection. At all time points, treatment of G-rk1 or G-rg5 dramatically reduced the viral titer (Figure 2D). Treatment of 80 μM ribavirin exhibited similar inhibition to that of 15 μM G-rk1 and G-rg5 at all time points. As expected, viral NP mRNA expression exhibited similar profiles to the virus titer (Figure 2E). Adding 15 µM G-rk1 or G-rg5 or 80 µM ribavirin dramatically reduced viral NP mRNA levels at all time points. To explore whether G-rk1 and G-rg5 possess broad inhibition of various subtypes of IAV strains, their effect on H5N1- and H3N2-infected A549 cells was evaluated. Both G-rk1 and G-rg5 showed dose-dependent antiviral activity against both H5N1 and H3N2 at 48 hpi, indicating their antiviral effect was not limited to a specific subtype. By counting infected cells from IFA images, the $50\%$ effective concentrations (EC50) of G-rk1 and G-rg5 against the three IAV strain infections were found to range from 6.2 to 14.8 M, and the corresponding selectivity index (SI) ranged from 2.6 to 5.6 (Table 1). ## 2.2. G-rk1 Interferes with IAV Entry Given that G-rk1 and G-rg5 are geometric isomers, and the two compounds share very similar chemical structures and anti-IAV activities, we selected G-rk1 to investigate the antiviral mechanisms against PR8 infection in A549 cells. We conducted time-course analyses of the inhibitory effects of G-rk1 at 15 μM to determine the stage(s) of the IAV lifecycle during which G-rk1 plays its inhibitory role (Figure 3A). Pre-treating A549 cells with G-rk1 did not affect viral NP expression (Figure 3B), demonstrating that G-rk1 did not affect the cells’ sensitivity to the PR8 virus. Co-treatment of G-rk1 at 4 °C (only IAV attached to the cell surface) and 37 °C (virus attachment and internalization) led to a reduction of viral NP expression, indicating that G-rk1 may prevent virus attachment to and/or entry into cells. Viral NP synthesis was reduced by $93\%$ when the cells were treated with G-rk1 for 24 h following PR8 infection (post-treatment), demonstrating that G-rk1 might also exert its antiviral effect when it is added during the post-virus binding stages. This is likely the result of G-rk1′s inhibiting role on the entry of the progeny virus. As expected, ribavirin’s antiviral activity was only observed post-treatment, but not in pre- and co-treatment models, as it is an RNA synthesis inhibitor. Intriguingly, the combination of 10 μM G-rk1 and 40 μM ribavirin significantly increased the inhibition of NP protein expression compared to those when either was used alone, indicating an additive or synergistic antiviral effect of G-rk1 and ribavirin against IAV replication. This finding further indicates they function at various stages of the viral lifecycle (Figure S5). ## 2.3. G-rk1 Interacts with HA via the HA1 Subunit Binding of HA1 to the sialic acid-containing receptor mediates IAV attachment to target cells, and the membrane fusion is mainly mediated by HA2 [34]. The HAI assay has been widely used to evaluate compounds for their inhibitory effect on the interaction between HA and its cell receptor. [ 35]. We examined G-rk1′s suppression of IAV-mediated hemagglutination to see if HA was the target. A total of 15 μM of G-rk1 did not affect chicken red blood cells (CRBCs) settling into the bottom of assay wells without IAV, whereas 15 μM G-rk1 treatment inhibited hemagglutination caused by H1N1, H5N1, and H3N2, reflected by CRBCs settling into the bottom of assay wells (Figure 4A). These results demonstrate that G-rk1 could block the binding between HA from IAV group 1 (H1N1 and H5N1) and group 2 (H3N2) with the host cellular receptors. The interaction between G-rk1 and HA and its subunits, HA1 or HA2 protein, was then studied using surface plasmon resonance (SPR) analysis. The results revealed that G-rk1 had a dose-dependent interaction with HA (Figure 4B) and its subunit HA1 (Figure 4C), with equilibrium dissociation constants (KD) of 14.6 nM and 93.3 nM, respectively, but it had a neglectable interaction with HA2 (KD: 0.22 M) (Figure 4D). FKBP12 (FK506 Binding Protein 1A, 12 kDa), used as an irrelevant control protein in the SPR experiment, did not interact with G-rk1. Hence, we believed that the interaction between G-rk1 and HA/HA1 was specific. These findings indicate that HA1 is the most likely target of G-rk1 for inhibiting viral attachment and cell entry. After identifying HA (HA1) as the target, we investigated whether G-rkl had an impact on the ability of the influenza virus HA to bind to sialic acid receptors, a crucial step for viral attachment [36], via an indirect ELISA using a sialic acid-coated plate. The results showed that the PR8 virus strongly bound to the coated sialic acid receptors, which were weakened or blocked in a dose-dependent manner after the virus was treated with G-rk1 (Figure 4E). Based on these results, we conclude that G-rk1 inhibits virus attachment by blocking HA’s (H1 subtype) binding to its sialic acid receptor. ## 2.4. G-rk1 Reduces IAV-Induced Morbidity and Mortality following Lethal PR8 Infection in Mice To evaluate G-rk1′s anti-IAV effects in vivo, we first determined the safe dose of G-rk1 in mice by intragastric administration and intranasal inoculation. The results showed that all doses administered via either route were tolerated, and the mice did not exhibit obvious weight loss or any other adverse symptoms (piloerection, altered respiratory rates, alopecia, signs of hunching, or unresponsiveness) (Figure S6). The 100 mg/kg/d of G-rk1 via intragastric administration (i.g.) or 25 mg/kg/d of G-rk1 via intranasal inoculation (i.n.) in BALB/C mice for 6 consecutive days were both tolerated well. Therefore, these doses were chosen as the maximal drug dose for in vivo anti-IAV evaluations. BALB/C mice intranasally infected with a dose of 5 × LD50 of PR8 were administrated by intragastric or intranasal inoculation with G-rk1 once daily for 6 consecutive days, starting on day 1 before infection. Figure 5A,B show that intranasally administrated G-rk1 protected mice from PR8 infection, significantly reflected by decreased weight loss and increased survivals, $66.7\%$ ($\frac{4}{6}$) and $83.3\%$ ($\frac{5}{6}$) in G-rk1-treated mice at 12.5 and 25 mg/kg/d, respectively, as no mouse survived in the PR8-infected untreated group. However, G-rk1 administered via the intragastric route showed much lower protection, only $33.3\%$ ($\frac{2}{6}$) and $16.7\%$ ($\frac{1}{6}$) survivals in mice treated with 50 and 100 mg/kg/d, respectively. Therefore, intranasal inoculation was identified as the more effective route for G-rk1 administration and was applied in further G-rk1 evaluations against PR8 infection. Figure 5C confirms that intranasal administration of 25 mg/kg/d and 12.5 mg/kg/d of G-rk1 resulted in significantly reduced mortality compared to the PBS control, with $80\%$ ($\frac{8}{10}$) and $70\%$ ($\frac{7}{10}$) survival, respectively, while only $10\%$ of PR8-infected mice survived without treatment. This was accompanied by a comparable decrease in weight loss following PR8 infection in mice treated with 25 and 12.5 mg/kg/d G-rk1 (Figure 5D). On day 4 after PR8 infection, G-rk1 treatment reduced total lung tissue virus titers, consistent with the in vitro results (Figure 5E). Peramivir, one of the IAV neuraminidase inhibitors widely used clinically, was used as the positive control in our in vivo studies, and 20 mg/kg/d of peramivir showed $100\%$ protection of PR8-infected mice. Significant reductions in weight loss and lung tissue viral titers following PR8 infection were also observed in the peramivir-treated mice. Our data suggest that G-rk1 by intranasal inoculation robustly protects mice from lethal IAV infection. To investigate whether delayed G-rk1 administration would affect its protection for IAV-infected mice, which might mimic early clinical treatment, 25 mg/kg/d of G-rk1 was given to mice by intranasal inoculation at 24 or 4 h prior to or 24, 48, or 72 h post PR8 virus infection, followed by G-rk1 treatment for 6 consecutive days. The results showed that delayed G-rk1 administration sharply decreased the protection of PR8-infected mice. Overall, $83.3\%$ ($\frac{5}{6}$) of mice treated with G-rk1 initiated at 24 h or 4 h prior to virus infection survived, while among those initiated at 24, 48, and 72 h post-infection, only $33.3\%$ ($\frac{2}{6}$), $16.7\%$ ($\frac{1}{6}$), and $0\%$ ($\frac{0}{6}$) survived, respectively (Figure 5F). These results suggest that early intervention with G-rk1 is crucial for a maximal protecting effect on IAV-infected mice. ## 3. Discussion White ginseng (WG, dried ginseng), red ginseng (RG, dried and steamed ginseng), and black ginseng (BG, dried and steamed several times) are the three most used species for commercial ginseng products [37]. Many studies have reported that BG possesses more potent biological activities than RG and WG [38,39], and the absorption rate of ginsenosides in BG is higher in healthy adults [40]. Eun-Ha Kim et al. reported that RG extract was inferior to BG extract in inhibiting A(H1N1) pdm09 infection, likely due to BG’s higher contents of functional ginsenosides, such as rg3, rk1, and rg5 [41]. However, the substance(s) that exert the crucial antiviral activity in BG are still unknown. In this study, we assessed the anti-IAV effects of 23 ginsenosides and discovered that G-rk1 and G-rg5 have considerable effects against different IAV infections. We have shown that G-rk1 inhibits viral entry by interfering with the binding of HA to its sialic acid receptor. In vivo, intranasal injection of G-rk1 therapy decreased IAV PR8-induced weight loss and mortality in infected mice. Since the initial step in the viral replication cycle is viral attachment onto the target cells, preventing viral attachment and entry would prevent viral infection. Seven entry inhibitors have been authorized to treat clinical infectious illnesses caused by RSV, HIV, and herpes simplex virus (HSV) [42]. The sialic acid receptor for HA1 mediates IAV attachment to target cells. Next, the low pH (5.5 to 5.0) of the endosome triggers HA conformational change, leading to the fusion of the virus envelope and the endosomal membrane [43]. Among licensed anti-IAV drugs, arbidol is the only viral entry inhibitor inhibiting IAV replication by blocking viral membrane fusion. However, it is only approved for clinical use in Russia and China [44]. Some compounds were documented to block IAV binding to host cells, including teicoplanin derivatives [45], neoechinulin B and its analogs [46], and aureonitol [47]. However, these results were obtained heavily depending on HAI assay and needed more direct demonstration and in vivo study. In our study, G-rk1 and G-rg5 suppressed three different IAV infections in A549 cells with a low EC50 ≤ 14.8 µM, a much lower concentration compared with that from the reported G-rb1 (450 µM) [31], whereas 10 µM of G-rb1 did not exhibit any inhibition of PR8 replication in A549 cells in our antiviral compound screening. G-rk1 at 15 µM robustly inhibited three IAVs’ adsorption to CRBCs. Furthermore, our results revealed that G-rk1 binds tightly to the HA and HA1, which blocks IAV binding to the cellular sialic acid receptor in a dose-dependent manner, whereas it has little interaction with HA2 (Figure 4). These results demonstrate that G-rk1 acts as a potent IAV entry inhibitor by targeting HA1 rather than HA2. It has been demonstrated that combining inhibitors with different mechanisms increases their antiviral effect and reduces drug resistance [17]. As expected, the combination of G-rk1 with ribavirin, a well-known viral RNA synthesis inhibitor, resulted in a stronger antiviral effect than either compound used alone (Figure S5), suggesting that G-rk1 could be a novel compound used in combination with other anti-IAV drugs. From our in vivo studies, intranasally delivered G-rk1 showed marked antiviral activity against PR8 infection, leading to decreased weight loss and mortality, with an $80\%$ survival rate. However, G-rk1 administrated intragastrically showed minimum protection. The discrepancy between the two routes could be attributed to poor oral bioavailability. It was reported that the bioavailability of 50 mg/kg G-rk1 after oral administration was only $4.23\%$, which might be caused by poorer intestinal mucosal permeability and potentially altered compound stability in the gastrointestinal tract [48,49]. Importantly, although some mice treated with G-rk1 at 24 or 48 hpi were protected, mice treated with G-rk1 even just 4 h before infection showed significantly higher survival rates, indicating that G-rk1 is most suitable for prevention. The good protection of G-rk1 administrated by intranasal inoculation on PR8-infected mice suggests that it could potentially be developed into an anti-influenza aerosol, a common and practical drug administration strategy for respiratory infectious diseases in the clinic [50]. For instance, inhaled ribavirin decreases the progression to lower respiratory tract infections and mortality in immunocompromised patients [51,52]. Therefore, it is possible to use G-rk1 in an inhalation, alone, or combined with other anti-IAV drugs to treat influenza patients during the early infection. ## 4.1. Cell Lines and Virus Strains We purchased Madin-Darby canine kidney cells (MDCK cells) and A549 human lung cancer cells (A549 cells) from the Center of Cellular Resource, Chinese Academy of Sciences (Shanghai, China). The cells were cultured in a 37 °C, $5\%$ CO2 incubator in Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco, NY, USA), supplemented with $10\%$ fetal bovine serum (FBS), 100 U/mL of penicillin, and 100 g/mL streptomycin. The Chinese Center for Disease Control and Prevention provided the H1N1 IAV strain A/Puerto Rico/$\frac{8}{34}$ (H1N1, PR8) and H3N2 IAV strain A/Guangdong/Dongguan/$\frac{1100}{2006}$ viruses (Beijing, China). The Veterinary Technology Center of South China Agricultural *University* generously donated avian IAV strains A/Duck/Guangdong/$\frac{212}{2004}$ (H5N1) (Guangzhou, China). For 48 h, virus stocks were passaged in 10-day-old chicken embryonated eggs. After harvesting the allantoic fluid, aliquots were kept at −80 °C until needed. Utilizing the endpoint dilution test as previously published, viral titers were calculated as the $50\%$ tissue culture infectious dose (TCID50/mL) in confluent MDCK cells in 96-well microtiter plates [53]. A biosafety level 3 lab was used for all experiments involving H5N1 virus strains. ## 4.2. Compounds Ginsenosides rk1 (G-rk1) and rg5 (G-rg5), and 21 other ginsenosides with HPLC purities ≥$98\%$, were bought from Chengdu Gelipu Biotechnology Co., Ltd. in Chengdu, China. With a purity of $99\%$, ribavirin hydrochloride (Rib) was bought from Guangdong Star Lake Bioscience Co., Ltd. in Zhaoqing, China. Guangzhou Nucien Pharmaceutical Co., Ltd. sold peramivir in a sterile $0.9\%$ NaCl solution (0.3 g/100 mL) (Guangzhou, China). G-rk1, G-rg5, and 21 other ginsenosides were dissolved in dimethyl sulfoxide (DMSO) at a concentration of 30 mM as stock solutions for in vitro tests. Ribavirin hydrochloride was dissolved in PBS. For intranasal inoculation, G-rk1 was first dissolved in DMSO to a 250 mg/mL stock solution and then diluted with PBS to a 25 mg/mL work solution for nasal drop use. For intragastric administration, G-rk1 was prepared as a 10 mg/mL concentration in a $0.3\%$ sodium carboxymethyl cellulose solution. Peramivir solution was intraperitoneally injected after a proper dilution with PBS. ## 4.3. Mice We purchased female BALB/C mice from Jinan Pengyue Medical Laboratory Animal Ltd. (Jinan, China). Mice were kept in special pathogen-free isolators (SPF). According to the regulations for the care and use of animals for scientific reasons, experiments were carried out on mice that were 6 to 8 weeks old and were approved by South China Agricultural University’s Institutional Animal Care and Use Committee. ## 4.4. Cytotoxicity Assay An MTT test was used to measure the viability of A549 cells in the presence of various doses of G-rk1 or G-rg5. To achieve $100\%$ confluency, the cells were cultured in 96-well plates for 24 h at 37 °C. Fresh medium was added, and serially diluted compounds were incubated at 37 °C for 48 or 72 h. After that, the cells were stained with a 0.5 mg/mL solution of 3-(4,5-dimethylthiozol-2-yl)-3,5-diphenyl tetrazolium bromide (MTT; Sigma-Aldrich, Saint. Louis, MO, USA). The cell viability index was calculated using the mean optical density (OD) readings from six replicated wells for each treatment. Using GraphPad Prism 8.0, the $50\%$ cytotoxic concentration (CC50) was determined (GraphPad Software, San Diego, CA, USA). ## 4.5. Indirect Immunofluorescence Assay (IFA) We utilized an indirect immunofluorescence technique to quickly assess drugs’ antiviral efficacy against IAV infection. IAV-infected or uninfected cells were briefly fixed with $4\%$ paraformaldehyde for 15 min, followed by permeabilization with $0.3\%$ Triton X-100 for 10 min at room temperature (RT) and blocked with $5\%$ bovine serum albumin (BSA) for 60 min at 37 °C. Anti-NP antibodies (1:500 dilution, Sino Biological, Beijing, China) were then incubated with the cells overnight at 4 °C, after 3× washes with PBS, and the anti-mouse IgG antibody coupled with Alexa Fluor® 488 (green) (Cell Signaling Technology, Danvers, MA, USA) was added to the cells for 1 h at 37 °C, followed by 3x PBS washes. Finally, 50 μL of 4, 6-diamidino-2-phenylindole was used to stain the cells’ nuclei (DAPI, 300 nM; Sigma-Aldrich, Saint. Louis, MO, USA). A Leica DMI 4000B fluorescence microscope was used to record immunofluorescence (Leica, Wetzlar, Germany). The infection rate was defined as the proportion of infected cells to all cells. The ratio of the infection rate in the compound-treated groups to that in the DMSO-treated control was used to calculate the relative infected-cell percentage. Using the GraphPad Prism 8.0 software, the relative infected-cell percentage was plotted as a function of compound concentration to get the EC50 value (the concentration necessary to protect $50\%$ of cells from IAV infection). ## 4.6. Viral Inhibition Assay A549 monolayers were first infected by IAV. Cells were then treated with DMEM containing ranged doses of the test compound after removing supernatants containing unbound viral inoculums. At indicated time points, the cells were collected and underwent three freeze–thaw cycles at −80 °C and 4 °C to release cellular virions. The final virus titers of cells and supernatants were calculated and expressed as log10 TCID50/mL using MDCK cells in an endpoint dilution test. ## 4.7. Real-Time Reverse-Transcription PCR (RT-PCR) Following the manufacturer’s instructions, total RNA from the A549 cells was extracted using a total RNA quick extraction kit (Fastagen, Shanghai, China) and reverse-transcribed into cDNA using a reverse transcription kit (TaKaRa, Kyoto, Japan). Using the CFX96 Real-time PCR machine, 2 RealStar Green Power Mixture (including SYBR Green I Dye) (Genstar, Beijing, China) was used to perform real-time quantitative reverse transcription PCR (qRT-PCR) (Bio-Rad, California, USA). The following are the sense and anti-sense primer sequences: NP (5′-ACCAGAAGATKTGTCMTTCCAGGG-3′ and 5′-TACTCCTCCGCATTGTCTCCGAAG-3′); GAPDH (5′-GCACCGTCAAGGCTGAGAAC-3′ and 5′-TGGTGAAGACGCCAGTGGA-3′). Relative mRNA expression was calculated by the 2−ΔΔCT method [54], and GAPDH expression served as the endogenous control. ## 4.8. Time-Course Inhibition Assay A549 cells were infected by IAV PR8 in 24-well plates for 2 h at 37 °C. In pre-treatment, cells were incubated with the appropriate compound for 2 h at 37 °C, washed three times with PBS, and then exposed to PR8 for 2 h at 37 °C. In the co-treatment, cells were treated with compound and infected with PR8 simultaneously for 2 h at 4 °C or 37 °C, respectively, and then washed three times with PBS. In post-treatment, cells were first infected with PR8 for 2 h at 37 °C, followed by three washes with PBS, and then incubating in fresh medium containing the compound. At 24 hpi, the virus infection level in the treated cells was assessed using IFA, as mentioned above. ## 4.9. Hemagglutination Inhibition Assay (HAI) We used a hemagglutination assay to determine whether G-rk1 inhibited HA-mediated hemagglutination of chicken red blood cells (CRBCs). In total, 25 μL G-rk1 (5 μM or 15 μM) were mixed with 25 μL serially diluted influenza virus at RT for 30 min, then 50 μL $1\%$CRBCs was added and incubated for 15 min at 37 °C. The results were recorded by taking images of the hemagglutination in the plates. ## 4.10. Surface Plasmon Resonance (SPR) Analysis A Berthold bScreen LB 991 (LabXMedia company, Midland, Canada) was used to examine the interactions between IAV HA or HA1, or HA2 and G-rk1 at 4 °C. IAV strain A/Puerto Rico/$\frac{8}{1934}$ (H1N1) HA protein or its subunit HA1 or HA2 (Sino Biological Inc, Beijing, China) were immobilized on a sensor chip (Photo-cross-linker SensorCHIPTM) using an amine coupling kit (GE Healthcare, Buckinghamshire, UK). Then, using PBST (10 mM phosphate buffered salt solution containing $0.1\%$ Tween 20, pH 5.0) as the running buffer, the chemical was administered as analytes at varied concentrations, with contact times of 600 s and dissociation times of 360 s. After each test cycle, the chip platforms were cleaned with regeneration buffer (Glycine-HCl, pH 2.0). Using the data analysis software of the bScreen LB 991 unlabeled microarray system, the process and analysis of association and dissociation rate constants (Ka/Kon and Kd/Koff, respectively), as well as the equilibrium dissociation constant (kD, kd/ka), were calculated following a single-site binding model (1:1 Langmuir binding), with mass transfer limitations for binding kinetics determination. ## 4.11. The Influence of G-rk1 on Sialic Acid Receptor Binding Ability of IAV by an Indirect ELISA Using an indirect ELISA, as previously mentioned, the receptor binding capacity of PR8 treated with varied doses of G-rkl was determined [55]. In brief, 100 μL of 5 μg/mL streptavidin was added to each well of a 96-well plate, and the plate was rinsed three times with PBS before being incubated at 4 °C for 16 h. The 96-well plate was coated with the sialic acid receptors, Neu5Ac2-3Gal1-4GlcNAc-PAA-biotin (3′-SLN) (GlycoTech Inc., Gaithersburg, MD, USA), which had been diluted with PBS. The plate was then incubated at 4 °C for 12 h, after which the supernatant was discarded. The plate was then blocked with $5\%$ skim milk for 8 h at 4 °C, after which the supernatant was removed, and was washed three times with PBST. G-rkl was applied to the PR8 of 64 hemagglutinin units at doses of 0, 15, 30, and 60 μM for 2 h each at 37 °C. Both treated and untreated viruses were added into the sialic acid-coated plate. The plate was then incubated at 4 °C for 12 h, washed, and anti-HA mouse monoclonal antibody (clone M100016) (Zoono-gene, Beijing, China, 1:1800) was added for 60 min. The plate was again washed three times with PBST, and HPR-labeled goat anti-mouse IgG (1:12,000) was added for 2 h at 4 °C before being washed with PBS, and tetramethylbenzidine-H2O2 substrate solution (Solarbio, Beijing, China) was then added and left at room temperature for 10 min. Then, 0.2 M H2SO4 was added to the plate, and the OD values at 450 nm were measured on a plate reader. ## 4.12. In Vivo Viral Challenge and G-rk1 Treatment In lethal PR8 infections, BALB/C mice were intranasally infected with 5 times LD50 of the PR8 virus (in 30 μL PBS) under methoxyflurane anesthetization. G-rk1 was administered gavagely or intranasally. G-rk1 administration began 24 h before the infection and continued for 6 consecutive days. A positive control compound, peramivir, was injected intraperitoneally at the indicated doses. Each mouse underwent daily weight and mortality assessments. ## 4.13. Lung Tissue Viral Titers After being taken out of the mouse, the lungs were weighed, cleaned in PBS, homogenized in 1 mL of PBS with 100 U/mL penicillin and 100 g/mL streptomycin, and then centrifuged at 3600× g for 5 min at 4 °C. After that, supernatants were collected for assessing the virus titer in MDCK cells using the endpoint dilution test, as previously mentioned. ## 4.14. Statistical Analysis All values are shown as the mean SD of at least three experiments. When just two groups were compared, the Student’s t-test was used to evaluate the statistical significance; when more than two groups were compared, a one-way analysis of variance (ANOVA) was used. To conduct the statistical analysis, GraphPad Prism 8 was used (GraphPad Software, San Diego, CA, USA). * $p \leq 0.05$, ** $p \leq 0.01$, and *** $p \leq 0.001$ were considered statistically significant at different levels. The survival curves were plotted in GraphPad Prism 8 and compared with a log-rank (Mantel–Cox) test. ## 5. Conclusions In summary, our study revealed that, among the evaluated 23 ginsenosides, G-rk1 and G-rg5 showed the strongest inhibition of infected A549 cells by various IAV strains. Mechanistically, G-rk1 interferes with IAV’s attachment to its host cells via binding to HA1, thus blocking the binding of HA to its sialic acid receptors. 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--- title: 'Classification of Common Food Lipid Sources Regarding Healthiness Using Advanced Lipidomics: A Four-Arm Crossover Study' authors: - Milena Monfort-Pires - Santosh Lamichhane - Cristina Alonso - Bjørg Egelandsdal - Matej Orešič - Vilde Overrein Jordahl - Oda Skjølsvold - Irantzu Pérez-Ruiz - María Encarnación Blanco - Siv Skeie - Catia Martins - Anna Haug journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003363 doi: 10.3390/ijms24054941 license: CC BY 4.0 --- # Classification of Common Food Lipid Sources Regarding Healthiness Using Advanced Lipidomics: A Four-Arm Crossover Study ## Abstract Prospective studies have failed to establish a causal relationship between animal fat intake and cardiovascular diseases in humans. Furthermore, the metabolic effects of different dietary sources remain unknown. In this four-arm crossover study, we investigated the impact of consuming cheese, beef, and pork meat on classic and new cardiovascular risk markers (obtained from lipidomics) in the context of a healthy diet. A total of 33 young healthy volunteers (23 women/10 men) were assigned to one out of four test diets in a Latin square design. Each test diet was consumed for 14 days, with a 2-week washout. Participants received a healthy diet plus Gouda- or Goutaler-type cheeses, pork, or beef meats. Before and after each diet, fasting blood samples were withdrawn. A reduction in total cholesterol and an increase in high density lipoprotein particle size were detected after all diets. Only the pork diet upregulated plasma unsaturated fatty acids and downregulated triglycerides species. Improvements in the lipoprotein profile and upregulation of circulating plasmalogen species were also observed after the pork diet. Our study suggests that, within the context of a healthy diet rich in micronutrients and fiber, the consumption of animal products, in particular pork meat, may not induce deleterious effects, and reducing the intake of animal products should not be regarded as a way of reducing cardiovascular risk in young individuals. ## 1. Introduction Diet is one of the most important modifiable risk factors associated with obesity and non-communicable chronic diseases (NCDs) [1,2], the latter being the leading cause of mortality worldwide [1,2]. Among the dietary factors, the intake of saturated fatty acids (SFAs) has been implicated in increased inflammation, impaired insulin signaling, and increased cardiovascular disease (CVD) risk [3,4,5]. Although the deleterious metabolic effects of SFAs have been widely demonstrated in experimental models [3,4,6,7], prospective studies and meta-analyses have failed to establish a causal relation between overall SFA consumption and CVD or all-cause mortality in humans [8,9,10,11], possibly due to the synergistic effects of human dietary habits. Nevertheless, dietary guidelines have been recommending limiting the consumption of animal products containing SFA, especially red meat and regular-fat dairy products to reduce all-cause and CVD mortality risks [12,13]. Studies conducted in the last 15 years investigating the effects of meat and dairy products on the CVD risk profile have shown conflicting results [10,14,15,16,17,18]. Although some studies have found an increased risk for CVD from red-meat intake [10,14], others observed an increased risk only for processed meat intake [15], or no effect at all [18]. The source of red meat (pork, beef, or other types of meat), as well as the degree of processing (such as salting, smoking, or the inclusion of additives), could, at least in part, explain the different results across studies [10,14,15,18]. Moreover, controversial findings have also been reported for cheese consumption [16,17,19]. Some studies, but not all, associated cheese and/or dairy consumption with lower CVD risk, although the mechanisms remain elusive [17,19]. It has been hypothesized that the elevated calcium content in cheese (which may lead to higher fecal fat excretion rates), or the fermentation process, could offer protective effects on CVD outcomes [16,20,21], despite the high content of palmitic and myristic acids, which has been previously associated with inflammation and insulin resistance [3,7,20]. More recently, advanced techniques, such as lipidomics by mass spectrometry (MS) and lipoprotein subclass analysis using nuclear magnetic resonance (NMR) spectroscopy, have shed new light on the effects of dietary fats on biomarkers of health outcomes [22]. It has been reported that the consumption of SFAs, but not polyunsaturated fatty acids (PUFAs), is associated with higher plasma sphingolipids (including ceramides and sphingomyelins), which are shown to affect metabolic processes related to CVDs, promoting insulin resistance and inflammation [23,24]. Moreover, increased plasmalogens, glycerophospholipids that play a key role in biological functions and act as a potential antioxidant [25], were observed after 18 months of a healthy Nordic diet rich in fiber, fish, and berries, but not after a diet with average nutrient intake in Nordic countries [26]. This indicates the potential for MS/NMR to identify underlying metabolic pathways associated with the intake of nutrients and early CVD risk in young individuals. Few clinical trials have investigated the effects of products that are major sources of SFAs in the context of a healthy diet [27]. In addition, it is not clear whether different animal products, with their distinct fatty acid composition, would have specific effects on metabolic outcomes, and little is known about the effects of distinct animal products on the plasma lipids species and lipoprotein subclasses. Thus, this study aims to investigate whether some of the main meat and dairy products that contribute to animal fat intake in the Norwegian diet (two cheese varieties—Gouda- and Goutaler-type cheeses, pork, and beef meat) could affect health parameters, lipoprotein subclasses (as measured by two-dimensional proton nuclear magnetic resonance spectroscopy—2D-1H-NMR), and lipid species (analyzed with chromatography coupled to mass spectrometry—UHPLC–MS) in healthy non-obese young individuals. ## 2.1. Characteristics of the Sample Out of 50 subjects screened, 38 subjects started the dietary intervention study. A total of 5 out of 38 participants dropped out within the first two weeks of the intervention, mainly due to the COVID-19 situation. Of 33 participants, 30 completed the intervention (8 time-points), while two males and one female had only 6 and 4 time-point data, respectively. Baseline clinical and biochemical parameters from the available participants ($$n = 33$$) according to sex and in the total sample are shown in Table 1. Although we had a higher number of female participants ($$n = 23$$) compared to males ($$n = 10$$), the enrolled subjects were age-matched ($p \leq 0.05$). In addition, the mean values of most clinical and biochemical parameters were within the normal range of being healthy. The diet registrations for each baseline period (before each diet intervention) are summarized in Supplementary Table S1. The habitual diet remained similar throughout the study in all four diet registration periods for both sexes (Supplementary Table S1). A trend towards increased energy intake (in kilocalories—kcal) during the washout periods was detected among females ($$p \leq 0.07$$), while no differences were detected in males. When comparing the test diets with the participants’ habitual diets, we observed similar macronutrient distributions (on average: 40–$43\%$ carbohydrates, 36–$39\%$ fat, and 16–$19\%$ protein of total energy intake—TEI). Moreover, the habitual fiber consumption among participants (11.3 g/1000 kcal for males and 13.4 g/1000 kcal for females) was lower than the amount provided in the test diets (18.3 g fiber/1000 kcal for group F2 and 20 g fiber/1000 kcal for group M2). Supplementary Table S2 depicts detailed information regarding the comparisons of macro- and micronutrients for the intervention and habitual diets in the sample. Since no differences were detected between the four washout periods, we calculated the habitual diet as the average of the four periods. Because the diet we provided had more fruits, vegetables, and fiber than the habitual diet, differences in nutrient intake were expected when comparing them. Indeed, we detected differences between the test diets and the participants’ habitual diet regarding most micronutrients analyzed, except for retinol, sodium, vitamin B6, and vitamin A, that were similar between the habitual diet and at least one of the test diets (Supplementary Table S2). Interestingly, for B12, the highest intake was observed in the habitual diet when compared to the test diets. Moreover, we compared the four test diets and observed differences among the cheese test diets and beef and pork test diets for the following nutrients: niacin (higher in beef and pork diets), phosphorus (higher in cheese diets), potassium (higher in beef and pork diets), retinol (higher in cheese diets), iron, and sodium (both higher in the beef and pork diets). In addition, the pork diet also showed a higher content of selenium and thiamin compared to others, while the beef test diet had a higher B12 content. Even though there were some differences in the nutrient content among the test diets, the major differences detected were between the habitual and test diets, indicating the significance of the quality of the diets provided during the intervention. It is worth mentioning that the proportion of nutrients and types of fats were similar between the habitual and, at least, one of the test diets. The intake of total fat in the habitual diet was similar to the test diets and the SFA intake was not different from the cheese diets, only from the beef and pork test diets. As mentioned above, the main differences between habitual and test diets were detected in the dietary fiber, MUFA, and PUFA intakes, which were higher in the test diets. To avoid changes in physical activity levels, participants were instructed to maintain their activities throughout the study. At the end of the four test diets, a new physical activity questionnaire was filled out, and the results showed no changes in leisure-time physical activity or sitting times (Supplementary Table S3). ## 2.2. Impact of the Test Diets on Clinical Parameters Figure 1 highlights the effects of each test diet on the clinical parameters (Figure 1 and Supplementary Table S4). We found that all test diets promoted weight loss and reductions in body mass index (BMI), although the decline was not significant for the pork diet (Figure 1A, Supplementary Table S4). Remarkably, no significant change in weight between diets was found (Figure 1B, overall diet effect). Furthermore, a significant decrease in waist circumference (Figure 1C) was detected only after the Goutaler-type cheese diet; however, these results should be interpreted cautiously since not all waist circumference measurements were taken due to the COVID-19 contamination risk (around $15\%$ of the measurements are missing). Interestingly, LDL cholesterol (Figure 1E) and apolipoprotein B (Figure 1M) were significantly lowered only after the pork ($p \leq 0.01$) and beef ($p \leq 0.05$) test diets. A similar trend was observed after the Gouda-type cheese test diet (Figure 1E, $p \leq 0.10$), but no differences were observed when comparing the four test diets (Figure 1F,N). Total cholesterol was reduced after all test diets (Supplementary Table S4), and significant reductions in both HDL cholesterol (Figure 1G) and apolipoprotein A (Figure 1K) were observed for all test diets, with there being no differences between them (Figure 1H,L). Furthermore, we observed that triglyceride levels (Figure 1I) were significantly reduced only after the pork test diet ($p \leq 0.01$, Figure 1I), showing a trend to decrease more than the other dietary interventions (Figure 1J). Similar findings were observed for HOMA-IR (Figure 1Q) and C-peptide (Figure 1S). Additionally, uric acid concentrations showed opposite patterns when comparing pork and beef with the cheese test diets (Figure 1O). Whereas the two cheese diets led to reduced levels, the pork and beef test diets increased uric acid concentrations (Figure 1P). Vitamin D levels (Supplementary Figure S1) increased after all test diets; however, the changes were period-dependent, and there was no difference between the diets (outlined in Supplementary Figure S1). ## 2.3. Impact of the Test Diets on Lipidomics Figure 2 illustrates the serum lipidome alteration during the four different dietary interventions. When comparing the data from before and after the intervention periods, we observed that the pork test diet had a profound impact on the serum lipidomic profile. Out of the 421 lipids investigated, 247 lipids differed after the pork diet (nominal $p \leq 0.05$, Supplementary Table S5). Of these lipids, 124 passed significance at the selected false discovery rate (FDR) threshold of 0.05. After beef test diet interventions, 223 lipids were altered (nominal $p \leq 0.05$, Supplementary Table S6), and 84 of these lipids passed significance at the selected FDR threshold. Similarly, 181 and 220 individual lipids were modulated after the Gouda- and Goutaler-type cheese test diets, respectively (nominal $p \leq 0.05$, Supplementary Tables S7 and S8, respectively). After the FDR adjustment, 27 and 64 lipids remained altered following the Gouda- and Goutaler-type cheese diets, respectively (Figure 2 and Supplementary Tables S7 and S8). The lipid class-wise percentage of change before and after intervention for each diet is depicted in Figure 2. We found that mono- and polyunsaturated free fatty acids were increased after the pork test diet, while the free fatty acid (FFA) 18:1n increased after the Goutaler-type cheese test diet (Figure 2; Supplementary Figure S2). In addition, the pork test diet elevated the serum concentration of the oxidized fatty acid hydroxyoctadecadienoic acid (HODE) and acylcarnitine 18:1 n-9 (Figure 2). There were no significant (FDR threshold of 0.05) differences in diacylglycerol (DG) levels after the intervention; however, important changes were observed in TGs and ether lipids after the test diets. In particular, TGs were significantly reduced after the pork diet intervention, while some ether-linked lipids remained upregulated (Figure 2). Low levels of sphingomyelins and ceramides were observed after the beef and pork test diets (Figure 2). Figure 3A highlights the individual circulating TG species analyzed before and after each intervention. Interestingly, 43 out of 72 TGs were significantly downregulated after the pork test diet, while 20 were decreased after the beef test diet intake (Figure 3A). For the Goutaler-type cheese test diet, a few TGs were altered. However, no clear changes with respect to the Gouda-type cheese test diet were observed (Figure 3A). At the lipid class level, only the pork and beef test diets promoted significant decreases in TG species (Figure 3B). Of all the downregulated TGs, decreased levels of TG 54:2 (Figure 3C) and TG 48:0 (Figure 3D) after the pork test diet (Figure 3E) may be of metabolic significance, as these have previously been associated with CVD and hypertension. In addition, both the pork and beef test diets also reduced TGs 48:1 (Figure 3E) and 48:2 (Figure 3F), which have been linked to hypertension. Furthermore, we observed that pork consumption had a profound impact on ether phospholipid species (Figure 4A). The heatmap depicts that pork consumption upregulated some vinyl-ether-linked phospholipids (P-PC, P-LPE, and P-PE; also known as plasmalogens) and ether-linked phospholipids (O-PC and O-LPC). On the other hand, the cheese test diets had opposite effects when compared to the pork test diet. We noticed contrasting results for PE P-18:$\frac{1}{20}$:4, PC O-16:$\frac{0}{18}$:2, and PC O-38:5. Moreover, Goutaler-type cheese and pork showed contrasting results for a total of eight individual ether phospholipid species (Figure 4A). At the lipid-class level, the P-PEs and P-PCs were downregulated after the cheese test diets (Figure 4B,F) whereas O-PCs were reduced only after the Goutaler-type cheese diet (Figure 4E). Interestingly, the pork test diet showed a non-significant trend of an increase in the O-LPE class, and this was significantly different for the other test diets (Figure 4C). No changes were detected for the O-LPC (Figure 4G) and P-LPC classes (Figure 4H); however, P-LPE (Figure 4F) was reduced after the beef test diet (Figure 4D). The heatmap for ceramides is shown in Supplementary Figure S3A. Although the ceramide class showed no significant differences after the test diets (Supplementary Figure S3B), we observed that all interventions significantly downregulated Cer 18:$\frac{1}{24}$:0 (Supplementary Figure S3C), while all but the Gouda diet downregulated Cer 18:$\frac{1}{22}$:0 (Supplementary Figure S3D). Then, we sought to determine the impact of the intervention test diets on the lipoprotein profile using NMR spectroscopy (Figure 5). The heatmap presented shows the percentage of fold changes when comparing the data from before and after test diets (Figure 5A), whereas the lipidic silhouettes illustrate the summarized lipoprotein risk profiles for each test diet (Figure 5B). We found that the pork test diet significantly reduced LDL cholesterol (Figure 5C), LDL-TG (Figure 5D), as well as total TG in lipoproteins (Figure 5E). Although no differences were detected among the test diets, pork reduced non-HDL cholesterol (Supplementary Figure S4A) and VLDL and IDL cholesterol levels (Supplementary Figure S4B), whereas all test diets downregulated HDL cholesterol after two weeks of intervention (Supplementary Figure S4C). Along the same line, all test diets downregulated the HDL particle number (HDL-P) (Supplementary Figure S4J) and small HDL-P (Supplementary Figure S4K); however, only pork decreased VLDL-TG and IDL-TG (Supplementary Figure S4D), HDL-TG (Supplementary Figure S4E), VLDL-P (Supplementary Figure S4G), small VLDL-P (Supplementary Figure S4H), large VLDL-P (Supplementary Figure S4I), LDL-P (Figure 5F), and non-HDL-P (Figure 5G). Interestingly, HDL size (HDL-z) was upregulated after all test diets (Figure 5H). The silhouette figures show that all the diets promote benefits to the summarized lipoprotein risk profile. Notably, although all test diets promoted benefits to CV risk (as the green line is closer to the outer ring for several markers), the pork test diet showed a distinct reduction in most of the CV risk markers (Figure 5B). ## 3. Discussion In this four-arm crossover clinical trial, we showed that adding regular-fat animal products, in particular pork meat, to a healthy diet rich in fiber and micronutrients may not promote deleterious metabolic outcomes. The diets containing pork, beef, or cheese products exhibited positive health effects when compared to the participants’ habitual diets, showing benefits to classical cardiovascular risk markers, as well as two new CVD markers, such as subclasses of lipoproteins and molecular lipid species, as analyzed by lipidomics. We observed that the consumption of a healthy diet with pork meat resulted in the greatest benefits to CVD risk by improving the lipid profile, downregulating TGs and ceramide lipid species, and upregulating ether lipids, especially plasmalogens, when compared to the other test diets. For the last 50 years, different guidelines have been recommending limiting or reducing saturated fats to less than $10\%$ of TEE to reduce CVD risk [12,13], especially the intake of products rich in lauric, myristic, and palmitic acids that have been associated with deleterious effects [3,4,5]. Nevertheless, the evidence for the association between different sources of SFAs, such as regular-fat dairy or meat, and health outcomes in humans remains controversial [9,20,28,29]. Indeed, the data from prospective studies and meta-analyses indicate that products from different sources could have hindered the associations observed between SFAs and CVDs in humans [10,16,20,28,29] and that dairy products might be inversely correlated with diabetes and CVDs, even when regular-fat products are investigated [16]. On the other hand, most of these studies established a positive association between red meat consumption and CVDs [10,14], albeit the underlying mechanisms remain to be elucidated. Contrary to these findings, in our study, some benefits were detected in participants after the four test diets, including both the cheese and meat test diets, when compared to the participants’ habitual diets that provided similar proportions of SFAs. All test diets, except the pork test diet, led to reductions in body weight when compared to pre-intervention values, and reductions in total cholesterol were observed after the test diets, even after adjusting for body weight changes. Nevertheless, it is worth noting that the statistically significant reductions in body weight were quite minor and should not have an impact on the metabolic effects, especially not on lipids. Indeed, the beneficial effects on body weight can be at least partially attributed to the high content of fiber in the diet we provided. Nonetheless, improvements in the lipid profile were unexpected due to the high quantity of animal products given to the participants (more than $10\%$ was from SFAs in the cheese and beef test diets). In addition, our experiment included non-obese, healthy individuals, and this could have had an impact on our findings since the majority of CVDs are obesity-related. Nevertheless, our findings are consistent with a previous study in which a cheese (96–120 g) or meat diet consumed for 3 weeks showed no effects on LDL and total cholesterol levels [30]. Similar findings were observed by others after 20 weeks of a low-carbohydrate diet, rich in SFAs ($21\%$ of TEI), whilst some studies detected increased total and LDL cholesterol levels after high-SFA diets [31,32]. Different from those studies, our test diets were healthy, rich in essential nutrients from natural sources, and had commonly used food items, providing between 8 and $14\%$ of TEI from SFAs, which could explain the different results. Nonetheless, most of our test diets provided more than the recommended $10\%$ of SFAs. Remarkably, we also observed reductions in apolipoprotein B, an important CVD risk marker, after the meat test diets (pork and beef), but not after the cheese interventions. This could be explained, at least in part, by the higher palmitic and myristic acid contents in the cheese products compared to the meat diets (six and ten times more in cheese than in meat, respectively) [7,33] as these fatty acids have been associated with deleterious effects in experimental studies [3,4,7,33]. In contrast to our findings, Bergeron and colleagues [31] detected increased LDL and apolipoprotein B concentrations after the consumption of a red meat diet rich in SFAs. This discrepancy may be associated with the sources of SFAs, product matrices [29], the content of SFAs (8–$12\%$ in the meat diets), or the quality of the diet provided to the participants. When we compared pre- and post-intervention values, a secondary aim of our study, other important cardiovascular risk variables were favorably modulated by all interventions. HDL particle size, which has been inversely associated with CVDs [34], was increased after all test diets, despite the recorded reductions in HDL cholesterol. Increased HDL size has been previously reported after diets rich in fatty fish or vegetable oils, but not after cheese, pork, or beef consumption [35,36,37]. In addition to HDL size, the data from the lipidomics analysis indicate that two ceramide species (Cer 18:$\frac{1}{22}$:0 and Cer 18:$\frac{1}{24}$:0) were downregulated after the test diets. Ceramides have been shown to impair insulin signaling through different pathways, directly affecting cell metabolism and increasing CVD risk [7,23,26,38,39]. Furthermore, one of the downregulated ceramides, Cer (18:$\frac{1}{24}$:0), was associated with dysglycemia in participants from the Framingham Heart Study [40]. Similar to our intervention data, ceramides were shown to be reduced after nutrient-rich diets in previous studies [26,35]; however, an increase in ceramides are usually detected after SFA consumption [24]. One of the most interesting findings of our study regards the effects of the pork test diet on lipid species and lipoprotein subclasses. Even though all test diets were healthy and provided benefits, the results from the pork diet suggested increased benefits from this product compared to others. In effect, our results shed new light on the potential CVD benefits of a healthy diet enriched with pork. Unlike the other test diets, the pork intervention showed profound metabolic benefits, improving both classical CVD markers and novel parameters, such as lipid species associated with reduced CVD risk. Intriguingly, reductions in insulin, HOMA-IR, and triglycerides were detected only on the pork test diet. Studies investigating the metabolic effects of diets with pork (and not total red meat) are limited [27,41]; however, recent data from an Australian study indicate that adding pork to a Mediterranean diet does not affect the lipoprotein profile [27]. The plausible explanation for this is that the contents of MUFAs (almost $50\%$ of total fat content) and PUFAs ($17\%$ of total fat content), as well as a lower SFA content, in the pork meat could have influenced the outcome. Indeed, the benefits of diets rich in MUFAs and PUFAs on glucose and lipid profiles have been widely described [42,43,44]. Indeed, a recent study showed that an important part of the Mediterranean diet’s benefits could be attributed to the MUFA content [45]. We also found a beneficial impact on the lipoprotein profile after the pork diet. LDL-cholesterol and LDL-TG, as well as total TGs in lipoproteins, non-HDL cholesterol, VLDL and IDL-cholesterol, VLDL-TG, IDL-TG, HDL-TG, VLDL-P, small VLDL-P, large VLDL-P, LDL-P, and non-HDL-P were significantly reduced after the pork diet, resulting in a better overall cardiovascular risk profile. Previous studies suggest that diets high in SFAs can increase LDL cholesterol, Apo B, and total, medium-, and small-sized LDL particles after only 3 weeks [31]. However, it is noteworthy that the researchers provided $18\%$ TEI of SFAs, compared to the 8–$10\%$ in our pork diet, and the intervention was conducted for a longer period than our study (3 weeks). In addition, pork was not the main source of SFA in that study. In fact, our results regarding lipoprotein subclasses after the pork diet were remarkable. Lipid subclasses measured with NMR are important cardiovascular risk markers because they provide a better overview of the quality of lipoproteins [36]. Moreover, reductions in some parameters, such as LDL-P, LDL-TG, and HDL-TG, have been previously associated with a decreased risk of CVDs [38]. Although improvements in the lipoprotein profile could be attributed to the consumption of a healthy diet rich in fibers and vegetables [46], this does not fully explain the differences detected among pork and other animal products in our study. The extra benefits associated with this diet could be credited, at least partially, to the distribution of fatty acids, i.e., the higher content of MUFAs and PUFAs, as well as the slightly lower content of SFAs in this diet (8–$9\%$ versus 10–$14\%$ in beef and cheese, respectively). Furthermore, the lipidomic analysis provided evidence for the beneficial metabolic effects of the test diets, especially the pork intervention. We detected an increase in circulating MUFAs and PUFAs after the pork diet and a reduction in TG species after the intervention, several of which were saturated. The data from large-cohort studies have identified short-chain TGs with fewer double bonds as markers of increased CV risk [47,48]. Additionally, a previous study demonstrated that saturated and short-chain TG species were reduced after a weight loss program, and this change was directly associated with an increase in insulin sensitivity among individuals with insulin resistance [49]. Indeed, we observed increased reductions in TGs with either lower chains and/or fewer double bonds after the pork test diet. Interestingly, for some of the TG species, a significant reduction was also observed after the beef diet, but not after the cheese diets, indicating a beef meat-product-specific effect. Interestingly, previous studies conducted by Djekic and colleagues [50] observed lower levels of saturated TGs after a vegetarian diet when compared to a meat-based diet. Meanwhile, our finding is in line with a study in which reductions in TG species that contained odd-chain fatty acids were observed after consuming a healthy Nordic diet when compared to a control diet [26]. Similar to this study, our test diets provided elevated consumption levels of MUFA, PUFA, and fiber when compared to the participants’ habitual diets. Interestingly, in our study, reductions in TG species that have been directly associated with CVD risk were detected after the pork diet intervention. TG 54:2, which has been associated with a higher CVD risk [51], and TG 48:0, which has been associated with hypertension [52,53], were reduced only after the pork intervention, while both pork and beef test diets downregulated the TG species 48:1 and 48:2, which have also been shown to be correlated with hypertension [52,53]. One of the most unexpected findings from our study is related to the effects of the test diets on ether phospholipids. We observed opposing results when comparing meat (mainly pork) and cheese diets, the latter showing a trend of decreases in several P-PE and P-PC species. On the other hand, the pork diet, and in some cases the beef diet, were shown to upregulate P-PE, P-PC, P-LPE, O-LPC, and O-PC species. Several important metabolic functions have been attributed to plasmalogens (P-LPE, P-PE, and P-PC species) [25]. It is suggested that the vinyl-ether linkage of the plasmalogens can be oxidized by reactive oxygen species and that they could play a role in protecting lipids’ membranes from oxidation [25,54]. Using a protocol of a high-fat diet enriched with lard for eight weeks in rodents, Gowda and colleagues observed reductions in some lipid species, such as PC and ethereal PC, but not LPC, PE, and LPE [55]. Contrary to our results, the HFD used in this study was rich in palmitic and stearic acids, which was not observed for our pork meat. Moreover, the authors observed that PUFA-derived lipids were inversely associated with obesity, which could also explain some of our findings [55]. In humans, the data from cohorts evidenced negative associations between plasmalogens and CVDs [25,56]. In addition, inverse associations between both ether- and vinyl-ether-linked PC species (P-PC and O-PC species) with prediabetes and type 2 diabetes have been reported [56]. Similarly, one study that investigated the effects of a Nordic diet rich in unsaturated fats and fiber showed an upregulation of plasmalogens after 12 but not 18 weeks [26]. Additionally, the changes were positively associated with n-3 and n-6 intakes. It is somewhat possible that the higher content of PUFAs in the pork diet (9–$10\%$ versus 7–$8\%$ of TEI), as well as the MUFAs ($18\%$ versus 13–$15\%$), or the lower content of SFAs in this diet (8–$9\%$ versus 12–$14\%$), could have to some extent influenced these results. Altogether, our data suggest that animal products, which are important sources of SFAs, should not be classified as having similar effects, as their composition can directly affect metabolic outcomes. It is worth mentioning that we detected differences in the content of micronutrients when comparing the habitual diet of the participants, and that most of the nutrients were higher in the test diets. Even though we cannot exclude that some of these nutrients may have influenced our results, most values were within the normal range for both habitual and test diets and, therefore, are not expected to promote metabolic changes of great magnitude within two weeks. Indeed, a recent meta-analysis showed that only folic acid and omega-3 FA supplementation provided high-quality evidence for reducing CVD risk [57]. Moreover, very few differences were detected among the four test diets. Some micronutrients were higher in the cheese test diets (such as calcium), whereas others in the pork and/or beef diets (such as iron), which could not fully explain the differences observed among the test diets, especially regarding the pork diet. Nonetheless, not all our results were favorable to CVD risk. Reductions in HDL cholesterol, HDL-P, and small HDL-P, as well as apolipoprotein A, were detected after all test diets to a similar degree. Most studies investigating the effects of diets rich in either SFAs, meat, or cheese reported increases in HDL and apolipoprotein A [5,18,20,58,59], even when the participants received a low carbohydrate/high SFA ($21\%$ TEI) dietary intervention [60], which was not the case in this study. Unlike our study, Ebbeling and colleagues detected elevated, large HDL-P after the low-carbohydrate/high-SFA diet when compared to a high-carbohydrate control diet. Furthermore, an increase in uric acid after pork and beef test diets, but not after cheese diets, was detected in our study. Elevated uric acid has been reported to be associated with a higher serum total antioxidant capacity in patients with atherosclerosis, which might indicate a mechanism to reduce oxidative damage [61]. Thus, the observed uric acid reduction after the cheese diets could help explain the underlying mechanisms linking dairy intake and reduced risk for CVDs. It is noteworthy that it is not clear whether these negative effects could counterbalance the benefits of the test diets. Our study had some limitations. Although we had a strong study design, with four different test diets in a crossover design that allowed us to have a baseline/control diet for each intervention, we could not objectively assess the participant’s compliance with the intervention periods. However, the participants reported no major problems with test products after the intervention periods. Additionally, we obtained information regarding all washout period diets, and no differences were detected throughout the periods, which indicates that the participants went back to their habitual diet during the washout periods and that we provided them with a diet with better nutritional quality. Even though a run-in period and/or controlled washout periods would be ideal, all participants were instructed to maintain their habitual diets and their compliance was confirmed by the diet registration information they provided. Although it might be suggested that the metabolic benefits detected can be attributed to a controlled diet, the participants were allowed to control their energy intake by changing their carbohydrate consumption, and no changes in total energy intake were detected when comparing the test diets with the habitual diet. Furthermore, we assessed both the classical and novel markers of CVD risks, such as lipid species and subclasses of lipoproteins, which yielded important results regarding the effects of the intake of animal products, especially after the pork test diet. Even though three of the test diets promoted weight loss, the absolute values were low, with an average reduction of less than one kilogram (in participants that were mostly lean and healthy according to the initial metabolic profile). Moreover, this small change in body weight does not explain the benefits detected in our study as small changes in body weight have been shown to affect the lipid profile at a low magnitude [62]. In addition, it is worth noting that the pork diet, which showed the greatest benefits, had no significant effect on body weight. However, it is not clear whether the metabolic changes observed could have been different if the participants of the study were older, in the overweight/obese categories, and/or had high CV risks. ## 4. Material and Methods The intervention study was ethically assessed and approved by the Regional Committee for Medical and Health Research Ethics, REK south-east, Norway, case number 139404. Participants had to sign a consent form before participating in the intervention study. In addition, they were able to withdraw their consent at any time without justification. If they withdrew, their health information and biological material were not researched further. The study was conducted according to the declaration of Helsinki and registered as a clinical trial in the ISRCTN registry (ISRCTN39863778). ## 4.1. Participants All volunteers were recruited at the Norwegian University of Life Sciences (NMBU), in Ås, Norway. The recruitment was conducted with the help of Internet advertising, as well as information posters distributed at the university campus. A total of 50 people were recruited (12 men and 38 women), and 33 were included in this analysis (23 women and 10 men, Figure 6C). The higher number of dropouts ($$n = 12$$) occurred before the study started, due to enhanced COVID-19 restriction measures at baseline. ## 4.2. Inclusion Criteria Inclusion criteria were men and women aged between 18 and 40 years with a BMI between 18.5 and 30 kg/m2, who were healthy, and who performed less than 10 h of moderate/intense physical activity per week. ## 4.3. Exclusion Criteria Volunteers who were taking any medication except for birth control pills, who did not consume meat and/or dairy products, who were trying to lose weight, or who had food allergies were excluded. In addition, during the first blood withdrawal, participants with vein problems that could affect blood withdrawal were also excluded. Because the length of the menstrual cycle is usually around 28 days, all our test diets were administered in the same phase of the cycle. ## 4.4. Design of the Study and Research Protocol This study was a four-arm crossover clinical trial in which participants were assigned to four test diets in a random order (Figure 6A) in a Latin square design. Each test diet was conducted for 14 days, followed by 2 weeks of washout between them; thus, the total duration of the study was 14 weeks (3.5 months). This means each test diet had its own control as in pre-intervention values (either baseline or washout values depending on the test diet order). The study was conducted between January and May 2021 (winter and spring), and the last participant was enrolled at the beginning of March. At the beginning and end of all test diets, the participants attended university facilities to deliver urine and feces samples and to provide blood, anthropometric measurements, and blood pressure data (Figure 6A) on eight different occasions (before and after each test diet). All clinical data were collected on weekdays (Tuesday to Friday). All food items were delivered in plastic bags tagged with the participant’s code (according to their energy needs). The food items were delivered to the NMBU campus once a week and, therefore, they had to pick up the food twice for each intervention. In case the participant had problems coming to the university once a week, they received all food items for two weeks. To increase the adherence to the protocol, researchers provided recipes with all food items. ## 4.5. Test Diets All participants received a healthy test diet, with a low percentage of ready-to-eat foods and foods with a high degree of processing (less than $20\%$ of TEI), and with food ingredients regularly consumed in Norway: apple, avocado, bouillon powder, wholegrain bread, carrot, celery root, garlic, strawberry jam, margarine, rapeseed oil, onion, orange, parsnip, wholegrain pasta, oatmeal, salmon spread, squash, and tomato. In addition, participants received iodized salt (2 g per week) and vitamin D pearls (15 µg) along with one of the four animal test products: Gouda-type cheese (150 g/day), Goutaler-type cheese (150 g/day), raw pork meat (225 g/day), or raw beef meat (230 g/day) (Figure 6B). The amounts of animal test products were higher than what is usually consumed, since the aim of the study was to investigate the differences between the different animal fats. All test products had similar energy contents, and the amounts were determined to match the same macronutrient distribution. For raw pork and beef, a reduction of $20\%$ of the total weight of the product was expected after the heating process. The amounts of the test products were the same for all participants; however the other food items (fruits, vegetables, oil, and pasta) were adjusted to individual energy needs to maintain the macronutrient composition, as well as the distribution of fats (Figure 6B; Supplementary Tables S9–S11). The energy requirements were determined according to a Norwegian online diet planner that provides information about food and health from the Norwegian Health and Food Authorities (kostholdsplanleggeren.no). To calculate the energy requirements, age, sex, and self-reported physical activity level were considered. Additionally, physical activity level was assessed with the International Physical Activity Questionnaire (IPAQ) [63] that was filled out by the participants at baseline and at the end of the study. Based on the energy requirements of participants, six groups were created: three for women (F1, F2, and F3) and three for men (M1, M2, and M3). Of the 23 women included, 15 were classified as F2 (2300 kcal/day), 6 as F3 (2600 kcal/day), and 1 as F1 (2200 kcal/day). Among men, seven were classified as M2 (3000/day kcal), two as M3 (3600/day kcal), and one as M1 (2800/day kcal). The nutritional composition of the four test diets provided to groups F2 and M2 (the most frequent groups) and nutritional analysis of one test diet (Gouda cheese) for groups M1, M3, F1, and F3, and all food items provided to participants in groups F2 and M2 (in grams/day or units/day) are depicted in Table 2 and Supplementary Tables S9 and S10, respectively. Due to the fact that not all participants within each group had the exact same energy requirements, they were instructed to adjust their energy intake by slightly increasing or reducing the intake of carbohydrates (pasta and bread). Apart from the food items described in the Supplementary Table S10, participants were allowed to consume coffee and tea of up to a maximum of 5 cups per day and to abstain from alcohol and soft drinks (especially those with added sugar). In specific situations when the participant had difficulties with adherence, one glass of sugar-free soda per day was allowed. Participants were advised to consume four meals per day, distributing the test product between two and three meals per day. They were also instructed to eat all the test products and inform the researchers if they had any problems with them. Those who found it difficult to eat all test products were asked to estimate deviations. This instruction was continuously given to the participants who stayed sufficiently close to the requested test dietary pattern. Table 2 shows the energy intake and macronutrient distribution ranges. The energy intake and macronutrient composition range of the test diets for groups F2 (2300 kcal/day) and M2 (3000 kcal/day) were as follows: total energy (in kcal): $2.6\%$ variation between test diets for women and $2.0\%$ variation between test diets for men. Regarding the macronutrient distribution, the test diets presented a variation between 46 to $48\%$ of energy intake from carbohydrates, 15 to $16\%$ of total energy from proteins, and 37–$38\%$ of total energy from fat. The proportion of SFAs varied between 8 and $14\%$ of TEI, while monounsaturated fatty acids (MUFAs) represented 13–$18\%$ of TEI. Additionally, PUFA intake corresponded to 7 to $9\%$ of TEI. The test products given to participants provided the following energy values per day: Gouda-type cheese 528 kcal, Goutaler-type cheese 527 kcal, pork 547 kcal, and beef 504 kcal. The food composition analysis is detailed in the Supplementary File. In the test diets, a healthy diet with recommended amounts of vitamins and minerals according to the Nordic Nutrition Recommendations [13] was provided. In addition, as the intakes of iodine and vitamin D were known to be deficient, both micronutrients were supplemented. Participants received Vitamin D pearls from Pharma Nord© throughout the study (14 weeks) and were instructed to take three vitamin D pearls/day (15 µg/day), including washout periods. In addition, iodized salt produced in Denmark for the Swedish market (Jozo©, Hadsundvej 17, 9550 Mariager, Denmark) was given to participants every week (2 g/day, 14 g/week). The salt from Sweden has 50 µg iodine/g salt, while the Norwegian salt has 10 times less. Although all test diets included one animal product and they had almost identical macro- and micronutrient compositions, there were differences regarding the proportion of different fatty acids among the test products. The test products provided around 40 g of fat (ranging between 37 g from beef to 41.4 g from pork), but the proportion of SFAs was higher for the cheese test products (27.5 and 27.3 g for Gouda- and Goutaler-types, respectively) compared to pork and beef (14.0 and 17.0 g, respectively). On the other hand, MUFA was higher in pork meat (19.4 g compared to 8.1 and 7.8 g for Gouda- and Goutaler-type cheeses, respectively, and 14.7 g for beef). In addition, both cheese products provided 0.8 g of PUFAs, which was similar to beef (1.0 g), but much less than pork, which comprised 7.0 g of PUFAs in its composition. ## 4.6. Food Composition Analysis The food composition analysis is detailed in the Supplementary File [64,65]. ## 4.7. Diet Assessment At the baseline and during each of the three washout periods, all participants had to complete three days of diet registrations. They were instructed to register their daily intake of food and beverages online at the Norwegian diet planner (kostholdsplanleggeren.no). During the washout periods, the participants were instructed to register their diets from “normal” days and to avoid registrations from “special” days (holidays, celebrations, etc.), when their diets were expected to deviate from normal. Due to COVID-19 restrictions, social activities were rare during the intervention period. The diet registrations were from recurring days. ## 4.8. Health Questionnaire, Risk Analysis, and Physical Activity A health questionnaire was given to all participants before each test diet, and its content and the risk analysis are detailed in the Supplementary File [66]. Physical activity level was assessed at the beginning and end of the study with the IPAQ [63]. Leisure time and total physical activity (in minutes/week), as well as sitting time, were analyzed. ## 4.9. Anthropometric Measurementsand Clinical Variables Height was measured in centimeters to one decimal place using a portable stadiometer (Charder HM200P Portstad). Weight was measured in kilograms to one decimal place using the Tanita TBF-300A Body Composition Analyzer scale and with participants wearing light clothes and no shoes. Waist circumference was measured by trained staff at the midpoint between the lowest rib and iliac crest using a Seca 203 Ergonomic Circumference Measuring Tape. Weight and waist circumference, blood pressure, and blood glucose were recorded before and after each 14-day intervention sequence. Height was measured once, at baseline. Blood pressure was measured using an A&D medical automatic blood pressure monitor (A&D, Tokyo, Japan). After participants rested for 10 min in a sitting position, three consecutive measurements were taken, and the average of the three measurements was used. If the participant had any contact with anyone who had tested positive for COVID-19 in the previous days, waist circumference and blood pressure measurements were not taken to avoid an increased risk of staff infection. ## 4.10. Blood Sampling Participants’ blood samples were taken before and after each test diet period, after 12 h of fasting. In addition, the participants provided urine and feces samples. The blood samples were processed on the recommendation of the Fürst medical laboratory (Norway) and/or according to the procedures for lipidomics analysis at OWL Metabolomics (Derio, Spain). The tubes were centrifuged in a swing-out centrifuge (after 0.5–1 h) at 1500 g for 12 min. After the serum and plasma were separated into cryotubes, they were placed in a −80 °C freezer until analysis. ## 4.11. Analytical Procedures Fasting glucose, insulin, C-peptide, total serum triacylglycerol, HDL-cholesterol, LDL-cholesterol, apolipoprotein A, apolipoprotein B, alanine transaminase (ALT), aspartate transaminase (AST), C-reactive protein, uric acid, calcium, ferritin, iron, vitamin D, and vitamin B12 were measured using accredited methods at a commercial medical laboratory in Norway (Fürst Medical Laboratory, Oslo, Norway), which also provided the method codes and analytical coefficient of variation. Interleukin 1β (IL-1 β) and interleukin-6 (IL-6) were analyzed using R&D enzyme-linked immunosorbent assays (ELISAs) (R&D Systems, Minneapolis, MN, USA). ## 4.12. Lipidomics and Lipoprotein Profile Lipidomics and lipoprotein profile NMR were performed at OWL Metabolomics (Spain). The detailed procedures are described in the Supplementary File [67,68,69,70,71,72]. ## 4.13. Power Calculation The power calculation was based on other studies investigating the effects of 2-week dietary interventions on health producing changes in the lipid profile as the main outcome [73]. Based on our own data, we calculated the sample size estimating a change of 0.3 mmol LDL cholesterol /L serum and a standard deviation of 0.8 mmol LDL cholesterol/L serum to ensure an $80\%$ chance of ending up with a p-value less than 0.05 (estimated sample of 32 participants). A dropout of $15\%$ was assumed based on former intervention studies of this group and, therefore, to reach the estimated sample size, 37 subjects were deemed necessary. Since we had 4 intervention diets, the closer multiple of 4 was selected (40 participants). ## 4.14. Statistical Analyses: Clinical and Biochemical Data IBM SPSS Statistics for Windows, Version 27.0. ( IBM Corp, Armonk, NY, USA) and GraphPad Prism version 9.0 for Windows (GraphPad Software, San Diego, CA, USA) were used for statistical analyses. Data are presented as means and standard deviations or standard errors of the mean (for figures). The Kolmogorov–Smirnov test was used to analyze the distribution of the data, and for variables without a normal distribution, a non-parametric test was performed. To investigate the effects of each test diet (pre/post comparisons) on clinical variables, a repeated-measures ANOVA (RM-ANOVA) was employed using sex and body weight change as covariates and the order of the intervention as a between-subject factor (for each test diet separately). To compare the effects of the four different test diets (a/b/c/d comparisons) on the clinical variables, the percentage of change from baseline to the end of each intervention period was calculated (100 × (after − before)/before). Thus, a mixed-effect model for repeated measures with sex and diet as the fixed effects and body weight change and intervention order as the random effects was employed. Adjustments for multiple comparisons were performed using the Sidak method. For all analyses, $p \leq 0.05$ was considered significant. ## 4.15. Lipidomics and NMR Lipoprotein Profile Data Data are represented as median ± SD of the percentage of change, calculated as 100 × (After−Before)/before. Differences between paired diets (before and after each diet) were tested using the adjusted Wilcoxon signed-rank test (Holm–Sidak method). Differences among diets, as a percentage of the changes, were evaluated using the Kruskal–Wallis H-test. A false discovery rate threshold of $p \leq 0.05$ was used. Calculations were performed using Python v3.7.4. The statistical analyses were performed using pandas v1.1.3 [70], NumPy v1.20.3, SciPy v1.5.2 5 [71], and Seaborn library v0.11.1 6 [73]. Since no differences were detected between males and females at the baseline visit in the multivariate data analysis and the number of women was much higher to the number of men, no sex-specific analysis was conducted. ## 5. Conclusions In summary, our study showed that, in the context of a healthy diet rich in micronutrients and fiber, consuming regular-fat animal products, in particular pork, had no major adverse effects on the classical and novel CVD risk markers. On the contrary, we observed that the test diets consumed promoted CVD benefits after only two weeks when compared to the participant’s habitual diet, which reinforces the importance of investigating the effects of animal fats in the context of healthy diets. Remarkably, we showed here that the consumption of a healthy diet including pork meat led to numerous metabolic benefits, including improvements to lipoprotein subclasses, reductions in lipid species associated with CVDs, and the upregulation of some plasmalogens, which play an important role as endogenous antioxidants. Our study suggests that the quality of the diet is more important than the restriction of regular-fat animal products, at least for this age group. Moreover, our findings indicate that the composition of the pork meat is capable of promoting increased benefits when compared to the other animal products analyzed. Although it is difficult to generalize our findings to other populations, our data indicate that the consumption of regular-fat animal products, especially unprocessed pork meat, within the context of nutrient-dense diets, should not be discouraged as a measure to reduce CVD risk. 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--- title: Changes in the Histology of Walnut (Juglans regia L.) Infected with Phomopsis capsici and Transcriptome and Metabolome Analysis authors: - Leming Zhou - Tianhui Zhu - Shan Han - Shujiang Li - Yinggao Liu - Tiantian Lin - Tianmin Qiao journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003368 doi: 10.3390/ijms24054879 license: CC BY 4.0 --- # Changes in the Histology of Walnut (Juglans regia L.) Infected with Phomopsis capsici and Transcriptome and Metabolome Analysis ## Abstract Phomopsis capsici (P. capsici) causes branch blight of walnuts, which leads to significant economic loss. The molecular mechanism behind the response of walnuts remains unknown. Paraffin sectioning and transcriptome and metabolome analyses were performed to explore the changes in tissue structure, gene expression, and metabolic processes in walnut after infection with P. capsici. We found that P. capsici caused serious damage to xylem vessels during the infestation of walnut branches, destroying the structure and function of the vessels and creating obstacles to the transport of nutrients and water to the branches. The transcriptome results showed that differentially expressed genes (DEGs) were mainly annotated in carbon metabolism and ribosomes. Further metabolome analyses verified the specific induction of carbohydrate and amino acid biosynthesis by P. capsici. Finally, association analysis was performed for DEGs and differentially expressed metabolites (DEMs), which focused on the synthesis and metabolic pathways of amino acids, carbon metabolism, and secondary metabolites and cofactors. Three significant metabolites were identified: succinic semialdehyde acid, fumaric acid, and phosphoenolpyruvic acid. In conclusion, this study provides data reference on the pathogenesis of walnut branch blight and direction for breeding walnut to enhance its disease resistance. ## 1. Introduction Walnuts are a quality food for human health and an essential cash crop with important medicine and health functions [1]. Walnut branch blight occurs worldwide and causes threats to the yield and quality of walnuts, seriously jeopardizing the income of fruit farmers and reducing the economic development of walnut-growing regions [1,2]. Walnut branch blight is a plant disease caused by the presence of one or several fungi that mainly affects branches, particularly new branches that are more sensitive to infection. Walnut trees affected with this disease have a low yield and poor quality [3]. Phomopsis (Diaporthe) is a group of fungi of importance in planting pathology. Numerous fungi in this genus can infect plants and cause disease, resulting in plant ulcers, leaf blight, branch dieback, leaf spot, fruit rot, root rot, and bark necrosis [4,5]. Walnut branches infected with P. capsici were collected from Jiange County, Guangyuan City, Sichuan Province, China, in 2017 for pathogenic isolation and identification, and the results indicated that the pathogenic bacterium was P. capsici; this was the first report of P. capsici causing walnut branch blight disease in China [6]. However, the pathogen’s pathogenic mechanism for walnuts is not yet clear. Currently, the main chemical control methods are effective against branch blight, but they are very harmful to the environment [7]. Physical control is beneficial but inefficient and time-consuming, and biological control has yet to be widely available. To effectively control this disease, understanding the pathogenesis of the disease and breeding new varieties that are resistant to the disease are issues that are still to be addressed It has been observed in sections of lentils infected with Fusarium acnes that the mycelium first colonizes the bast and begins to expand into the xylem four days after inoculation. In addition, it has been found that the release of phenolic compounds in the early stages of lentil infection with wilt contributes to the delayed development of wilt; the carboxylated polysaccharides secreted by lentils in the later stages of wilt development cause blockage of xylem vessels and disrupt xylem function [8]. In addition, the resistance of plants to pathogen invasion relies mainly on the thickening of cell walls and the formation of structures, such as papillae, invaginations, wall layers, brown matter, and corking of cortical parenchyma cells [9,10]. Host plants undergo substantial physiological, biochemical, metabolic, and phenotypic changes during pathogen invasion. It is widely known that plant recognition of pathogenic bacteria triggers a hypersensitivity response, usually accompanied by programmed cell death in the host plant; the hypersensitivity response includes Ca2+ influx, oxidative bursts, and phytohormone signaling [11,12]. On the one hand, the basic ways in which plants respond to pathogen invasion are primarily through the regulation of metabolism-related pathways, including the biosynthesis of secondary metabolites, phenylpropanoid biosynthesis, amino acid and sugar metabolism, photosynthesis, and, to a lesser extent, the regulation of plant–pathogen interactions and MAPK signaling pathways, and the regulation of phytohormones [7]. Plants infected with pathogens are first affected by substances related to the signaling pathway, such as salicylic acid, ethylene, methyl jasmonic acid, methyl salicylic acid, and nitrogen oxides [13,14]; this is followed by primary metabolites, including carbohydrates, organic acids, amino acids, and lipids, and, finally, secondary metabolites, including terpenoids, polyphenols, and mustard oleo sides, which are closely related to plant disease resistance [15,16]. In existing studies, the presence of endophytic *Diaporthe fungus* significantly influenced the metabolic pathways of plants, and the biosynthesis of primary metabolites, such as threonine, malate, and N-acetylmannosamine, which are the precursors of specific metabolites and participate in plant self-defense, was improved [17]. On the other hand, plants may produce toxic substances to kill pathogens or inhibit their growth. It has been shown that the phenolic and organic acid content of different varieties of pepper increases when subjected to Halyomorpha halys [18]. Host–pathogen interactions often affect metabolic levels and metabolic pathways in plants [19]. Zeiss et al. identified secondary metabolites involved in plant defense in four tomato species infected with Ralstonia solanacearum, with the phenol–propane pathway, which is epitomized by flavonoids and hydroxycinnamic acid, taking an essential role in the defense response [20]. Fungal infection in plants resulted in significant differences in the production of various metabolic components, such as flavonoid compounds, phenols, terpenoids, and various defense proteins, which helped to elucidate the molecular mechanisms of forest tree defense processes and fungal pathogenesis [21,22,23,24]. This study investigated the response of walnuts to P. capsici through histological observation of walnut bast and xylem cells and transcriptome and metabolome analyses. The aim is to provide a theoretical basis for the pathogenesis of walnut branch blight and walnut breeding. ## 2.1. Section Observation of Walnut in Response to P. capsici Infection Tissue sections of walnut branches are shown in Figure 1. The periderm of walnuts in the control group (CK) group had obvious collenchyma; within these tissues were different-sized and thin-walled parenchyma cells arranged in a close and orderly manner. The interior of the phloem had darkly stained bast fibers. The cambium cells had a clear morphology and were arranged in an orderly manner. The xylem had a large caliber vessel and a clear and clean morphology with neat cell arrangements and structural integrity. At five days post-infection (5 DPI), the periderm had been slightly invaded, a few parenchyma cells were sparsely arranged, and there were cavities between cells; some xylem cells were broken, and the vessel contained a small amount of dissolved tissue fragment. At ten days post-infection (10 DPI), the periderm showed an obvious invagination: phloem cells were sparsely arranged; cambium cells were lysed; dissolved tissue fragments were visible in the transverse section of the xylem, and a large number of vessel elements were interrupted in the longitudinal section. At fifteen days post-infection (15 DPI), all cells were scattered, and their structures were destroyed; the infection in the vessel could be clearly seen in the transverse section of the xylem. In summary, after P. capsici infection, the internal cell arrangement of walnut branches became gradually more sparse and the structure was destroyed, with the most obvious damage to the xylem. ## 2.2.1. RNA Quality Detection and Sequencing Results In a total RNA assay, six extracted RNA samples were free of DNA and impurity contamination and degradation, meeting the requirements for library construction. Thus, six cDNA libraries were constructed, and 272,661,616 raw reads were obtained after RNA sequencing. In all, 262,331,938 clean reads ($95.82\%$ of the raw reads) were obtained after removing adapter sequences, reads containing poly n, and low-quality reads. Then, the high-quality cleaned read sequences were compared to the reference sequences, and 243,883,980 reads ($92.97\%$) were localized to the reference genome of walnut. The average figures for data Q20 and Q30 were $98.01\%$ and $94.21\%$, respectively. The GC content was greater than $45.22\%$. The length of the reads for the six samples was 150 bp. The transcriptome sequencing results met the quality requirements for subsequent assembly analysis. See Table 1 for sequencing information. ## 2.2.2. Identification of Infected DEG and Functional Analysis The results of the DEG analysis for Infected vs. CK combinations are shown in Figure 2. The Infected and CK combinations have 20,435 identical DEGs (Figure 2A). Among these, 5634 genes show significant differences, including 1911 upregulated genes and 3723 downregulated ones (Figure 2B and Table S1). These results indicate that the gene expression of walnut is inhibited by P. capsici invasion. The Gene Ontology (GO) functional enrichment analysis revealed that 1624 DEG are significantly enriched in 52 GO categories, involving 20 biological processes, 5 cellular compositions, and 27 molecular functions (Table S2). The biological processes are mainly “carbohydrate biosynthetic”, “cellulose metabolic”, “cellulose biosynthetic”, “glucan metabolic”, “defense response”, “polysaccharide biosynthetic”, and “glucan biosynthetic processes.” The cell compositions are mainly enriched in “thylakoid”, “thylakoid part”, “photosynthetic membrane”, “photosystem”, and “photosystem I reaction center.” The molecular functions are mainly “glucosyltransferase activity”, “cellulose synthase activity”, “calcium ion binding”, “serine-type exopeptidase activity”, “serine hydrolase activity”, and “structural constituents of ribosomes.” From these results, the 10 most significant terms were selected for each function, and 30 terms were plotted (Figure 2C). There are more downregulated genes than upregulated ones in each main category; however, among the cellular components, ribosomes have more upregulated than downregulated genes (Figure S1). The GO analysis showed that the metabolic processes of cellular carbohydrates are the most significant. The *Kyoto encyclopedia* of genes and genomes (KEGG) enrichment analysis showed that 1930 DEGs are annotated to 121 metabolic pathways, among which 367 DEGs are significantly enriched in “photosynthesis”, “ribosomes”, “carbon metabolism”, “glyoxylate and dicarboxylate metabolism”, “carbon fixation in photosynthetic organisms”, “ABC transporters”, “flavonoid biosynthesis”, “alanine”, “aspartate and glutamate metabolism”, and “phenylalanine metabolism” (Table S3). The 20 most significant pathways were selected to draw the scatter plots (Figure 2D). Of these, 88 DEGs are annotated to the carbon metabolism pathway and 113 DEGs are annotated to the ribosome. The KEGG results suggest that carbohydrate metabolism and ribosome-related genes play essential roles in walnut branch blight. ## 2.2.3. Verification by Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) To verify the RNA sequencing data, we used RT-qPCR to assess the expression of walnut genes before and after infection. We randomly selected 11 DEGs to confirm the changes in expression. *All* genes show the same change trend as the transcriptome sequencing results (Figure 3), proving the reliability of the transcriptome data. ## 2.3.1. Data Quality Control Pearson coefficients and principal component analysis (PCA) of the quality control (QC) samples were calculated based on the relative quantitative values of the metabolites; the results are shown in Figure 4. The R2 between the QC samples is close to one (Figure 4A,B), indicating that the whole testing process is constant and the quality of the data are excellent. PCA was used to analyze all QC samples’ pre- and post-infection peaks (Figure 4C,D). The distribution of the QC samples is clustered, indicating that there is minimal variation in the QC samples and the method is stable throughout with the high-quality data. ## 2.3.2. Metabolite Pathways and Classification Notes According to the Human Metabolome Database (HMDB) in the pos (Figure 5A) and neg modes (Figure 5D), 92 and 50 metabolites correspond to phenylpropanoids and polyketones, 76 and 42 metabolites correspond to lipids and lipid-like molecules, and 60 and 32 metabolites correspond to organic heterocyclic compounds. The metabolites identified by the secondary profiles were subjected to the KEGG website for metabolic pathway analysis. In the pos (Figure 5B) and neg modes (Figure 5E), most metabolites were mainly annotated to the global and overview maps, amino acid metabolism, biosynthesis of other secondary metabolites, and carbohydrate metabolism. LIPID MAPS annotation was performed on the identified metabolites, and the results showed that in the pos (Figure 5C) and neg modes (Figure 5F), the metabolites were mainly enriched in flavonoids, fatty acids and conjugates, and isoprenoids. The results of the metabolite annotation are shown in Figure 5. ## 2.3.3. DEM Screening and KEGG Pathway Annotation The two groups were screened for differences in metabolites. In total, 993 metabolites were screened under the pos mode, and 434 metabolites were differentially expressed (254 upregulated and 180 downregulated); 521 metabolites were screened under the neg mode, and 226 metabolites were differentially expressed (120 upregulated and 106 downregulated). The metabolites screened for KEGG annotation found that, in the pos mode, a total of 156 metabolites were annotated, of which 69 differential metabolites were annotated to 22 metabolic pathways (Table S4). In the neg mode, 99 metabolites were annotated, of which 39 differential metabolites were annotated to 32 metabolic pathways (Table S5). Based on these results, bubble maps of the top 20 enriched pathways were drawn, as shown in Figure 6. The pentose phosphate pathway, carbon fixation in photosynthetic organisms, and flavone and flavonol biosynthesis are the most enriched. All three differential metabolites (rutin, kaempferol, and luteolin) annotated in flavone and flavonol biosynthesis are reduced in levels. The metabolites D-Xylulose 5-phosphate and D-Sedoheptulose 7-phosphate are jointly annotated in the pentose phosphate pathway and the carbon fixation pathway of photosynthetic organisms and express downward, indicating that these metabolites play an important role in walnut branch blight. ## 2.3.4. Transcriptome and Metabolome Association Analysis A comprehensive transcriptome and metabolome analysis was performed using the Pearson correlation coefficient method to identify statistically significant genes and metabolites. The top 50 DEMs and the top 100 DEGs with significant correlation in the pos (Figure S2) and neg (Figure S3) ion modes were identified, and KEGG analysis was performed. The results of the transcriptomic and metabolomic KEGG association analysis found that, in the pos (Table S6) and neg (Table S7) modes, the enrichment categories involved in DEMs and DEGs are membrane transport, signal transduction, amino acid metabolism, biosynthesis of other secondary metabolites, carbohydrate metabolism, energy metabolism, lipid metabolism, metabolism of cofactors and vitamins, metabolism of other amino acids, metabolism of terpenoids and polyketides, and nucleotide metabolism. The main pathways enriched are 10 metabolic pathways involved in the annotation to carbohydrate metabolism, 6 annotations to amino acid metabolism, 4 annotations to the biosynthesis of other secondary metabolites, and 4 annotations to the metabolism of cofactors and vitamins. The results are shown in Table 2. In carbohydrate metabolism, intermediate metabolites decrease in all pathways, except for d-sorbitol and xylitol, including fumaric acid, phosphoenolpyruvic acid, cis-Aconitic acid, D-Xylulose 5-phosphate, D-Galacturonic acid, etc. The normal metabolism of carbohydrates is an essential basis for plant growth and development. It follows that the invasion of P. capsici inhibits walnut development. In amino acid metabolism, metabolites 3-hydroxy phthalic acid, glutathione, fumaric acid, succinic semialdehyde, phenylglyoxal, lecithin, N6-acetyl-L-lysine, 2-oxo adipic acid, and glutaric acid are decreased, while only N-acetyl-L-phenylalanine and L-glycine are increased. In the biosynthesis of other secondary metabolites, the number of up-regulated DEMs is greater than the number of down-regulated DEMs. In nicotinate and nicotinamide metabolism, vitamin B6 metabolism, ubiquinone and other terpenoid–quinone biosynthesis, and one carbon pool by folate pathways, fumaric acid, succinic semialdehyde, succinic semialdehyde, p-coumaric acid, and shikonin and folinic acid are decreased, while only phylloquinone is increased, as shown in Table 2. In this study, it is found that P. capsici infestation inhibits the metabolism and synthesis of carbohydrates (pyruvate, butanoate, pentose, glucuronate, fructose, and mannose), amino acids (tyrosine, cysteine, methionine, alanine, aspartate, glutamate, phenylalanine, tryptophan, and lysine), and other secondary metabolites (terpenoids and vitamins) in walnuts. However, the synthesis of secondary metabolites (mainly flavonoids) is enhanced. Remarkably, succinic semialdehyde acid, fumaric acid, and phosphoenolpyruvic acid are annotated to multiple metabolic pathways, indicating that these three metabolites play essential regulatory roles in the metabolism of walnuts. ## 3. Discussion We used a combination of paraffin tissue sectioning, transcriptome sequencing, and metabolomics to analyze walnut branch blight and provide a theoretical basis for enhancing disease resistance in walnuts. Like many blight pathogens, P. capsici targets xylem vessel molecules [25]. Pathogens enter the epidermis through the wounds, continue through the cortex and endodermis, and eventually reach the xylem, where they proliferate and spread [26]. The disintegration of the cortex and cambium cells primarily affects the division of plant cells and the transport of nutrients [27,28,29]. The primary role of the xylem in plants is to transport water, minerals, and numerous signal molecules [30,31,32,33]; this tissue consists of lignified vessel elements, fibers, and parenchyma cells. It has been suggested that plants of susceptible species have larger vascular molecules, a feature that may benefit infection [34]. The proliferation of xylem vascular wilt pathogens in the xylem leads to a breakdown of water and mineral transport, which leads to heavy wilting and death among infected plants. Remarkably, the xylem is found to block infection through the production of phenolic compounds, which is in line with the results of previous studies [8,35]. At post-infection, the expression of most genes in walnut is suppressed. Among them, the most DEGs are annotated in carbon metabolism and ribosomes. The expression of intermediate metabolites of the pentose phosphate pathway (PPP) and the carbon fixation pathway of photosynthetic organisms was suppressed in walnut. Carbon metabolism is the most important basic metabolism in the life cycle of plants, involving in the degradation and conversion of photosynthetic products, such as starch and sucrose synthesis, as well as respiratory processes, such as glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway, the ethanoic acid oxidation pathway, and the glyoxalate cycle, which provide the necessary raw materials and energy for amino acid, protein, and nucleic acid synthesis. Carbon metabolic processes in plants are closely related to plant growth and may also be involved in mechanisms of plant disease resistance [36,37,38]. Downregulation of genes related to carbon metabolism affects the levels, distribution, and imbalance of soluble sugars and starch in stem xylem and bast, and the pathways related to sugar and starch metabolism, thereby promoting plant disease development [38]. Ribosome is the site of intracellular protein synthesis and is essential in plant growth, development, and defense responses [39]. Upon infestation by pathogenic bacteria, host plants induce the production and accumulation of various defense-related genes and pathogenesis-related proteins (PR) [40]. Therefore, in this study, we hypothesized that up-regulated expression of ribosomal genes enables host plants to produce more PRs to resist pathogenic attacks. There are many metabolic functions in which the PPP performs a key role, including the generation of NADPH, biosynthesis of nucleotides, and carbon homeostasis [41,42]; this pathway produces four-, five-, and seven-carbon compounds and transketolases and transaldolases, which are also related to photosynthesis. Many existing studies have shown that the intermediate metabolites of the PPP play a crucial role in plant resistance to pathogenic bacterial attack [43,44,45]; therefore, the PPP is inhibited and the plant’s carbon fixation is slowed down in response, which in turn affects walnut growth and development, and increases plant susceptibility to disease. Amino acids combine to form proteins and are also the precursors for the synthesis of many plant hormones [46]; some amino acids (e.g., proline) can enhance plant resistance [47,48,49]. Some vitamins are recognized as essential antioxidants and work in stress response [50], such as a weakened biosynthesis of vitamin B6 promotes plant susceptibility to disease [51]. Terpenoids are widespread; some are involved in fundamental plant processes, such as photosynthesis, respiration, and growth and development. Some specialized metabolites show a wide range of biological activities, including antibacterial, anti-disease and anti-inflammatory actions, cytotoxic actions, and anti-tumor agent and enzyme inhibition [52,53]. Phenylpropanoid metabolite biosynthesis is a complex network that produces various critical secondary metabolites, including lignans and naringin, and its regulatory mechanism is essential for plant growth, development, and biotic stress protection. There are two main roles attributed to lignans and naringin: plant defense and antioxidant activity [49,54]. Flavonoids and flavonols in plants have important defensive functions against fungi [50,51]. In plants, flavonols serve to protect plants against various stimuli of the environment. Kaempferol and lignan are common polyphenolic substances, and rutin is the most common flavonol glycoside compound; they have antiviral, antifungal, and anti-biofilm abilities, as well as antioxidant activity and pharmacological properties [53]. In our study, increased walnut phenolic compounds facilitated the resistance to P. capsici infestation. Succinic semialdehyde acid is a significant metabolite of gamma-aminobutyric acid. The results of previous studies suggest that succinate semialdehyde functions initiate a quorum-quenching mechanism, which reduces quorum-sensing signals and, thus, avoids eliciting plant defense, Succinic semialdehyde acid gene silencing has been reported to increase disease susceptibility in tomatoes [55]; it has also been shown that succinic acid can enhance the viability of bacteria throughout an infection [56]. Fumaric acid is an organic acid that positively affects resistance to fungi, and plants can inhibit pathogen colonization and survival through the release of fumaric acid [57,58,59]. However, some studies have shown that the accumulation of fumaric acid can cause accelerated decay in plants [60], and it is found in Panax notoginseng that fumaric acid stimulates fungal growth and chemotaxis. Fungal antagonistic activity may also be affected by fumaric acid [61]. Rice induces phosphoenolpyruvic acid when being treated with insecticides to defend itself against insecticide damage [61]. Previous studies have also reported that phosphoenolpyruvic acid accumulates under abiotic stresses, such as blue light [62], high salt [63] and low nitrogen concentrations [64], and it is assumed that phosphoenolpyruvic acid can enhance the resistance of organisms to stress. Proper metabolism of organic acids can promote plant growth and disease resistance, but too much or insufficient metabolism can cause plant growth disruptions. In this study, succinic semialdehyde acid, fumaric acid, and phosphoenolpyruvic acid were significantly suppressed in walnut post-infection, confirming that the walnut variety “xiangling” was sensitive to P. capsici. In this study, infection of walnuts by P. capsici resulted in the gradual lysis of walnut cells; the inhibition of the expression of genes related to the carbon metabolism pathway (mainly PPP); the enhanced expression of genes in the ribosome; and the inhibition of the biosynthesis and metabolism of metabolite pathways, such as carbohydrates, and amino acids and cofactors, while enhancing the biosynthesis of secondary metabolites. We hypothesized that P. capsici infection caused a dysregulation of sugar and organic acid production in walnuts, thereby disrupting intracellular homeostasis and leaving walnuts in a susceptible state. At this point, P. capsici induced cellulase reactive oxygen species, causing a hypersensitive cellular response that induced programmed cell death and leading to the cell lysis phenomenon presented on walnut sections. At the same time, walnuts responded to the pathogenic stress by increasing the expression of secondary metabolites (e.g., prunin, luteolin, kaempferol, and (−)-epigallocatechin). In conclusion, this study provides data reference on the pathogenesis of walnut branch blight and direction for breeding walnut to enhance its disease resistance. However, the exact mechanism of how walnut resists P. capsici is open to debate. ## 4.1. Plant Materials and Pathogenic Bacterial Inoculation The walnut variety “xiangling” from Guangyuan City, Sichuan Province, China, was used as the material. The preserved P. capsici strain was inoculated in a traditional PDA medium. After 3 days of activation, the cake was punched out with a 5 mm diameter punch for inoculation experiments. The inoculation sites were annual branches of walnut. The inoculation area was disinfected with $75\%$ alcohol, rinsed with sterilized water, and dried. In the middle part of the inoculation zone, a wound of 1 cm × 1 cm size was scraped out with a knife, and the prepared bacteriophage cake was inoculated onto the wound. The branches were inoculated with a sterile medium as a control (CK), and each treatment was set up with nine biological replicates. These treatments were placed in the College of Forestry, Sichuan Agricultural University, until the onset of the disease. ## 4.2. Paraffin Sectioning of Walnut Branches The branches were infected with P. capsici at different times (5 DPI, 10 DPT, and 15 DPI), and CK were selected for sectioning. Conventional paraffin sectioning was used. The stem samples were cut transversely into 5 mm thick segments and placed in a FAA fixative for 24 h. Then, the samples were placed in a dehydration chamber with a plant-softening solution (Wuhan Safeway Biotechnology Co., Ltd., Wuhan, China). The softening fluid treatment occurred for seven days and the fluid was changed daily. After softening, the samples were rinsed with running water for 30 min; soaked in $15\%$ ethanol for 2 h, $30\%$ alcohol for 1 h, $50\%$ alcohol for 1 h, $75\%$ alcohol for 1.5 h, $90\%$ alcohol for 1.5 h, $1.5\%$ alcohol for 5 h, $100\%$ alcohol for 1 h, xylene for 8 min, and xylene for 20 min; and dehydrated after each soaking. The samples were placed in paraffin wax for 30 min, paraffin wax for 1 h, and paraffin wax for 2 h; then, they were placed on an embedding rack and removed and trimmed after the wax solidified. The sections were cut to a thickness of 5 μm, dried, and stored at room temperature. Next, the sections were placed in xylene I for 20 min, xylene II for 20 min, anhydrous ethanol I for 5 min, anhydrous ethanol II for 5 min, and $75\%$ alcohol for 5 min; then, they were washed with tap water. The sections were treated with toluidine blue for 2–5 min, rinsed with tap water, placed in a clean xylene clearing solution (Sinopharm Chemical Reagent Co., Ltd., Shanghai, China) for 10 min, sealed with a neutral glue (Sinopharm Chemical Reagent Co., Ltd.), and finally observed under microscopy. ## 4.3. RNA Sequencing The 15 DPI was the critical time when the yellow-brown spots were just beginning to appear on the inoculated walnut branches, which was the beginning of the walnut branch blight. A 1 cm × 2 cm section of the bark was taken immediately below the diseased tissue as a sample, and from the exact location in the CK, three replicates of each group were made. The samples were labeled and frozen in liquid nitrogen, and RNA extraction was immediately performed. Total RNA was extracted using the phenol-chloroform method. Sample quality was inspected on an Agilent 2100 Bioanalyzer system by assessing RNA integrity. Transcriptomes were sequenced on an Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA) platform by Novogene Bioinformatics Technology Co. (Beijing, China) The raw RNA-seq data had been submitted to the National Genomics Data Centre. ( Bioproject: PRJNA867174). ## 4.4. Transcriptome Analysis The clean reads were obtained by fine filtering after RNA sequencing to remove linker information, low-quality bases, and non-detected bases from the raw reads. Q20, Q30, and GC content were calculated for the clean reads, and the clean reads were compared to the reference genome using the HISAT2 software. DEG was identified using fragment per million exons mapping (FPKM), and genes with absolute values |log2(Fold Change)| ≥ 1 & padj ≤ 0.05 were considered significant DEGs. DEGs were annotated according to the non-redundant database (Nr), SwissProt/UniProt Plant Protein, KEGG, and eggNOG. Then, they were analyzed for enrichment of the KEGG pathways and GO functions. ## 4.5. RT-qPCR Verification To further confirm the expression levels of genes, RT-qPCR analyses were performed. We used cDNAs of mRNA reverse transcripts from the sequenced samples as templates and randomly selected 11 genes with high differential multiplicity, including upregulated DEGs and downregulated DEGs, with GAPDH as a reference gene. The RT-qPCR primers were designed using the CDS regions of 11 candidate genes, with GAPDH as the internal reference gene, and the Primer Premier 5.0 software was used for primer design (Supplementary Table S8). The primers were 18–25 bp in length, and the target amplification bands were 150–300 bp. Changes in the expression of the 11 candidate DEGs were quantified using a fluorescent quantitative polymerase chain reaction (CFX96-Real-Time System, San Diego, CA, USA). The RT-qPCR system was composed of the following parts: 10 μL Mix (Servicebio, Chengdu, China), 8 μL ddH2O, F/R 0.5 μL, and 1 μL cDNA (CK/Infected). The RT-qPCR was carried out as follows: 94 °C for 20 s, 94 °C for 10 s, and 60 °C for 20 s, and 38 cycles were repeated from step 2 to step 3. Three replicates of each RT-qPCR run were performed, the mean values were calculated, and the data were analyzed using the 2–△△Ct method. ## 4.6. Metabolite Extraction and Detection The samples were taken in the same manner and at the same sites as for the transcription group, with six sample replicates. Then, 100 mg of walnut tissues were taken from each sample, ground in liquid nitrogen, and placed separately in EP tubes. The sample was extracted as follows: 500 µL aqueous $80\%$ methanol was added to the vortex suspension homogenate; the supernatant was incubated on ice for 5 min, centrifuged at 15,000× g for 20 min at 4 °C, and diluted with LC-MS-grade water to a concentration containing $53\%$ methanol; and then the supernatant was centrifuged again at 15,000× g for 20 min at 4 °C and injected into the LC-MS/MS system for analysis. Using a Vanquish UHPLC system (Thermo Fisher, Berlin, Germany) and an Orbitrap Q ExactiveTMHF-X mass spectrometer (Thermo Fisher, Germany), we carried out UHPLC-MS/MS analysis at Novogene Ltd. (Beijing, China). The testing parameters were default company standard parameters. ## 4.7. Data Processing and Metabolite Identification The (raw) files were processed using the CD 3.1 library search software, setting a quality deviation of 5 ppm, a signal intensity deviation of $30\%$, a signal-to-noise ratio of 3, a minimum signal intensity, and summing the ions. Simultaneously, the peak areas were quantified, and then the target ions were integrated; this was followed by molecular ion peaks and fragment ions for molecular formula prediction and comparison with the mzCloud, mzVault, and Masslist databases. The background ions were removed using the blank samples, and the raw quantification results were normalized. ## 4.8. Data Analysis The KEGG database (https://www.genome.jp/kegg/pathway.html, accessed on 13 February 2022), the HMDB database (https://hmdb.ca/metabolites, accessed on 14 February 2022), and the LIPIDMaps database (https://www.lipidmaps.org/, accessed on 16 February 2022) were used to annotate the metabolites. PCA and partial least squares discriminant analyses were performed using metaX, and the VIP values were available for each metabolite. In the univariate analysis, statistical significance (p-value) and fold change (FC) were calculated for the metabolites based on t-tests. The default criteria for DEM screening are VIP > 1, p value < 0.05, and FC ≥ 2 or FC ≤ 0.5. The volcano map was plotted using the R package ggplot2; the clustering heat map was created using the R package Pheatmap; the metabolite data were normalized using z-score; the Pearson correlation coefficient was performed using the R language cor (); statistical significance was achieved using cor.mtest() in R; the correlation map was plotted using the R language complot package; and the KEGG database was used to study metabolite function and metabolic pathways. ## 4.9. Metabolome and Transcriptome Association Analysis We selected CK1, CK2, CK3, Infected 1, Infected 2, and Infected 3 of the transcription group for quantitative comparative analysis with CK1, CK2, CK3, Infected 1, Infected 2, and Infected 3 of the metabolism group. 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--- title: Exosomes Derived from Adipose Stem Cells Enhance Bone Fracture Healing via the Activation of the Wnt3a/β-Catenin Signaling Pathway in Rats with Type 2 Diabetes Mellitus authors: - Dong Zhang - Weidong Xiao - Changjiang Liu - Zheng Wang - Yuhang Liu - Yifeng Yu - Chao Jian - Aixi Yu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003369 doi: 10.3390/ijms24054852 license: CC BY 4.0 --- # Exosomes Derived from Adipose Stem Cells Enhance Bone Fracture Healing via the Activation of the Wnt3a/β-Catenin Signaling Pathway in Rats with Type 2 Diabetes Mellitus ## Abstract Nonunion and delayed union are common complications of diabetes mellitus that pose a serious health threat to people. There are many approaches that have been used to improve bone fracture healing. Recently, exosomes have been regarded as promising medical biomaterials for improving fracture healing. However, whether exosomes derived from adipose stem cells can promote bone fracture healing in diabetes mellitus remains unclear. In this study, adipose stem cells (ASCs) and exosomes derived from adipose stem cells (ASCs-exos) are isolated and identified. Additionally, we evaluate the in vitro and in vivo effects of ASCs-exos on the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and bone repair and the regeneration in a rat model of nonunion via Western blotting, immunofluorescence assay, ALP staining, alizarin red staining, radiographic examination and histological analysis. Compared with controls, ASCs-exos promoted BMSC osteogenic differentiation. Additionally, the results of Western blotting, radiographic examination and histological analysis show that ASCs-exos improve the ability for fracture repair in the rat model of nonunion bone fracture healing. Moreover, our results further proved that ASCs-exos play a role in activating the Wnt3a/β-catenin signaling pathway, which facilitates the osteogenic differentiation of BMSCs. All these results show that ASCs-exos enhance the osteogenic potential of BMSCs by activating the Wnt/β-catenin signaling pathway, and also facilitate the ability for bone repair and regeneration in vivo, which provides a novel direction for fracture nonunion in diabetes mellitus treatment. ## 1. Introduction Over the last century, diabetes mellitus (DM) has developed into one of the most serious public health problems which leads to life threatening, disabling and costly complications, and seriously impairs life expectancy and quality worldwide [1,2]. In 2021, according to the data reported via the International Diabetes Federation, in excess of 1 in 10 adults currently have diabetes mellitus globally, and the number of patients with diabetes mellitus will continue to increase quickly in the future [3]. More seriously, diabetes mellitus often causes various difficult complications including stroke, coronary artery disease, neuropathy, kidney disease, hard-healing wounds and peripheral vascular disease [4,5]. Among these complications, the negative effects of diabetes mellitus on bone health have drawn much attention, and growing research has shown that diabetes mellitus may lead to osteoporosis, increase the risk of fracture and have an adverse impact on fracture healing [6]. When compared with non-diabetes, studies have shown that there is a higher risk of delayed union and nonunion, with diabetes patients experiencing double the time to heal a fracture [7]. Over the past few decades, despite significant investments in this field, there have been few satisfactory strategies introduced to enhance nonunion bone fracture healing [8,9]. Recently, mesenchymal stem cells (MSCs) derived from various sources, including bone marrow, umbilical cord and adipose tissue, have been seen as an effective tool for bone repair and regeneration [10,11]. Among the various sources of MSCs, ASCs have gradually been developed as a major approach in the field of repair and reconstruction based on their abundance and easier accessibility with minimally invasive procedures [12]. When compared with MSCs derived from other sources, ASCs hold great potential for proliferation and expansion [13]. In addition, they also have paracrine and immunomodulatory properties related to their specific secretome [14]. However, in spite of the above advantages, there are some associated risks bordering the underlying application of stem cell transplantation in the clinic to facilitate fracture healing, including immunosuppression, cell dedifferentiation and tumor formation [15,16]. Recently, a growing number of researchers have been holding the view that MSCs could promote tissue repair and reconstruction in a paracrine way via secreting bioactive factors. This viewpoint offers insight into the exploration of MSC derivates. Exosomes are 50–150 nm in diameter and naturally released from almost all types of cells [17]. Recently, exosomes have opened a new door into bone repair and regeneration research, and have been broadly studied in the context of regeneration medicine [18,19]. Additionally, there is evidence that exosomes derived from serum, macrophages or MSCs are capable of being stably transferred into BMSCs, and are beneficial for the treatment of fracture healing [20,21,22]. More importantly, it has been confirmed that the application of transplanting exosomes displays similar therapeutic outcomes and functional properties as directly transplanted stem cells, but has less adverse effects such as immune rejection cell dedifferentiation and malignant transformation when using stem cells directly [23,24]. Among various cell types, ASCs represent an abundant MSC source, and are regarded as one of the most promising exosome sources due to a series of advantages [25,26,27]. Recent studies have demonstrated that ASCs-exos exhibit great potential in numerous exosome-based therapeutics for wound healing, cardiac injury and other reasons for tissue loss in DM [24,28,29,30]. Although these studies suggest that ASCs-exos are the key contributor for tissue repair, few research studies have focused on the therapeutic effects of ASCs-exos on promoting bone fracture healing in diabetes mellitus. Thus, this study aims to shed light on whether ASCs-exos can promote bone fracture healing in DM and affect the underlying mechanisms. Additionally, they may provide effective approaches for the treatment of impaired fracture healing in diabetes mellitus. ## 2.1. Characterization of ASCs-exos ASCs were harvested from the subcutaneous fat in the groin of a rat, as described in the Materials and Methods section. The ASCs were identified by morphology, multipotent differentiation potential and flow cytometry. As shown in Figure 1A, ASCs displayed a shuttle-shaped morphology and could be induced to cause adipogenic, osteogenic or chondrogenic differentiation. Additionally, ASCs were positive for classical markers such as CD44+ and CD90+, but were negative for CD34+ and CD45+ (Figure 1B). All these results demonstrated that ASCs were successfully harvested. To identify the exosomes derived from ASCs, Western blotting, transmission electron microscopy (TEM) and dynamic light scattering (DLS) were performed. TEM analysis showed that the morphology of the ASCs-exos was cup-shaped (Figure 1C). The particle sizes of ASCs-exos were evaluated using DLS, and the results exhibited that their size distribution ranged from 30 to 200 nm (Figure 1D). Additionally, Western blotting results showed that ASCs-exos were positive for CD9, CD63 and TSG101, which are characteristic surface markers of exosomes (Figure 1E). All these data indicated that ASCs and ASCs-exos were successfully isolated. In addition, we further explored whether ASCs-exos can be internalized via BMSCs. In our following experiments, the results showed that the labeled ASCs-exos could be internalized by BMSCs (Figure 1F). ## 2.2. ASCs-exos Promote BMSC Osteogenesis Differentiation In Vivo To further explore the effect of ASCs-exos on the ability for BMSC osteogenesis differentiation, BMSCs were co-cultured with PBS, ASCs-exos-free supernatant (AEFS) and ASCs-exos. As shown in Figure 2A,B, the protein expression of the osteogenesis-related genes was improved via ASCs-exos when compared with the control group. However, only the protein expression of Runx2 was improved via the AEFS in comparison with the PBS group. In addition, the immunofluorescence assay demonstrated that ASCs-exos promoted Runx2, collagen I and OCN protein expression in BMSCs on day 14 (Figure 2C). The results of alizarin red staining (ARS) and ALP staining (ALPS) showed that the proportion of mineralization was improved in the ASCs-exos group when compared with the PBS group, but there was no significant difference between the PBS group and the AEFS group (Figure 2D,E). In summary, these results demonstrated that ASCs-exos could promote osteogenic differentiation. ## 2.3. Successful Establishment of the Type 2 Diabetes Mellitus Rat Model The results were similar to those from our previously published article, in which the same method was utilized to create the T2DM rat model. Our data demonstrated that all streptozocin (STZ)-induced rats on a high-fat diet (HFD) showed type 2 diabetes mellitus (T2DM). As shown in Figure 3B, food intake, water consumption and urine output in the T2DM group were significantly higher than that of the control group. On the contrary, rats in the T2DM group were thinner than those in the control group (Figure 3C). These characteristics are regarded as the typical symptoms of T2DM. Meanwhile, there was significance in two groups concerned with random blood glucose (RBG), and rats with T2DM had an RBG that was continually higher than 16.7 mmol/L (Figure 3D). Additionally, for the investigation of glucose tolerance and insulin sensitivity, we performed an insulin tolerance test (ITT) and intraperitoneal glucose tolerance test (IPGTT). As shown in Figure 3E, the level of blood glucose (BG) quickly declined in the normal group after insulin treatment, but was slow or did not reduce BG in the T2DM group within 30 min. In addition, the data in Figure 3F display how the rats with T2DM had hyperglycemia when compared with the control group for 120 min after glucose administration. *In* general, all these results suggest that we have successfully established a T2DM rat model with the characteristics of insulin resistance and hyperglycemia. ## 2.4. ASCs-exos Enhance T2DM-Delayed Fracture in Rat Model The bone fractures in the DM rat model were treated with 600 μL ASCs-exos at a concentration of 200 μg/mL, and an equal volume of PBS and AEFS was applied around the fracture sites every three days after surgery to explore the effect of ASCs-exos on the treatment of fractures. The Western blotting results showed a significantly increased expression of Runx2, collagen I and OCN in the ASCs-exos group, and the AEFS group had no significant expression of osteogenesis-related genes compared with the PBS group (Figure 4A,B). Additionally, the digital imaging, X-ray imaging and micro-CT examinations were performed to evaluate the fracture repair at the fracture site. As shown in Figure 4C,D, the images demonstrated that, in comparison with the control group, the ASCs-exos group had a thicker callus volume and smaller fracture gap. Additionally, quantitative analysis of micro-CT data demonstrated that the bone volume/total volume (BV/TV) values of the ASCs-exos group were significantly increased in comparison with the control groups (Figure 4E). A histology examination 28 days after surgery suggested that there was a smaller hindrance in the fracture healing of the femur in ASCs-exos groups compared with other groups (Figure 4F). Collectively, these results implied that ASCs-exos improved the bone fracture healing in the T2DM rat model. ## 2.5. ASCs-exos Activated the Wnt3a/β-Catenin Signaling Pathway in BMSCs under High-Glucose Conditions To explore the specific signaling pathways via which ASCs-exos enhance the osteogenic differentiation of BMSCs, the common signaling pathways related to osteogenesis, including the PI3K/AKT signaling pathway, the MAPK signaling pathway, the NF-κB signaling pathway and the Wnt/β-catenin pathway, were observed via Western blotting. As shown in Figure 5A–C, there were no significant changes detected in the PI3K/AKT signaling pathway, the MAPK signaling pathway and the NF-κB signaling pathway. However, the protein expression of active β-catenin was significantly increased in BMSCs treated with ASCs-exos when compared with the control groups. The results revealed that the Wnt/β-catenin pathway might be involved in the enhancement of the BMSC osteogenic differentiation via ASCs-exos. Additionally, to further detect the role of canonical and noncanonical Wnt signaling, Western blotting was used to examine the expression of Wnt3a, Wnt5a, Wnt8a and Wnt10b. The expression of canonical Wnt3a was significantly upregulated in BMSCs treated with ASCs-exos, indicating that ASCs-exos modulate the Wnt signaling pathway in BMSC osteogenic differentiation (Figure 5D,E). ## 2.6. The Activation of the Wnt3a/β-Catenin Signaling Pathway in BMSCs Treated with ASCs-exos under High-Glucose Conditions Can Be Inhibited via Dickkopf-Related Protein-1 To further verify the involvement of the Wnt3a/β-catenin signaling pathway in BMSCs treated with ASCs-exos under high-glucose conditions, the activating effect of this signaling pathway on BMSC osteogenic differentiation induced via ASCs-exos was investigated. After treatment with Dickkopf-related protein-1 (DKK-1), an effective inhibitor of the Wnt/β-catenin signaling pathway, we found a nearly complete abrogation of the promotive effect on the protein levels of Runx2, collagen Ι and OCN induced by ASCs-exos (Figure 6A,B). Then, the results of the immunofluorescence assay further confirmed that the positive effect of ASCs-exos on the protein levels of Runx2, collagen Ι and OCN can be attenuated via DKK-1 (Figure 6C). Additionally, the mineralization levels were observed with ARS and ALPS, and the results displayed that they were also promoted via ASCs-exos while being inhibited by DKK-1; the effect of ASCs-exos could also be partially reversed via DKK-1 (Figure 6D,E). These results further suggest that there is a possibility of the Wnt3a/β-catenin pathway being involved in the BMSC osteogenic differentiation of the promoting effect of ASCs-exos. ## 3. Discussion As a common complication following DM, bone nonunion is an enormous challenge for patients and surgeons [31,32]. Additionally, researchers have investigated how the balance of bone homeostasis is disturbed during the process of bone nonunion in DM [33,34]. To address this disabling disease, various therapies including allografts, composite artificial bones, steam cell therapy and biological factors have been introduced [35]. Although various therapeutic approaches to fracture management have been explored via surgeons, the nonunion incidence has remained stable at around $10\%$ of all patients with DM [36,37]. Thus, it is imperative to find efficient therapeutic strategies for the treatment of bone nonunion in DM. Nowadays, exosomes have attracted much attention based on their important role in intercellular communications [23,38,39]. Additionally, mounting studies have demonstrated that exosomes from various types of cells have good performance on the tissue repair and regeneration via the delivering of various bioactive mediators, such as proteins, mRNAs or noncoding RNAs [22,40,41]. It is acknowledged that exosomes might have a significant effect on the pathological processes of DM, as well as related complications, from the perspective of cell-to-cell communication that occurs locally and between organs. For example, researchers have suggested that exosomes derived from adipose tissue play an important role in insulin resistance [42]; another study indicated that exosomes can be regarded as the key contributor to diabetic cardiac fibrosis and dysfunction, as they increase inflammatory and profibrogenic responses in fibroblasts [43]. As for bone repair and regeneration, Liao et al. reported that exosomes derived from BMSCs may prevent osteonecrosis of the femoral head via facilitating osteoblast proliferation, differentiation and osteogenesis, as well as angiogenesis [44]. Sun et al. suggested that osteoclast-derived exosomes are able to influence the process of osteoporosis by selectively inhibiting osteoblast activity [45]. Consistent with the above findings, another study suggested that exosomes derived from ASCs can facilitate bone regeneration by improving osteogenesis and angiogenesis [46]. Given the fact that ASCs are more accessible cell sources from which exosomes can be isolated and are able to produce higher amounts of exosomes than other cell types, such as endotheliocytes, fibroblasts or MSCs, we investigated whether ASCs-exos can improve bone fractures in DM or not. In our study, ASCs were successfully acquired and identified via morphology, and their multipotent differentiation potential was determined with flow cytometry; ASCs-exos were isolated from the supernatant of ASCs, and then they were identified via TEM, DLS and Western blotting. Similar to the evidence that exosomes are able to be internalized via target cells to modulate cell functions, our results have shown that exosomes derived from ASCs are taken up into BMSCs, and the osteogenesis ability of BMSCs was significantly improved via ASCs-exos in comparison with those in the PBS group. Similarly, we further displayed that the process of bone repair and regeneration in a DM rat model of fracture was enhanced via injecting ASCs-exos when compared with other groups. To investigate the molecular basis of osteogenic differentiation, we examined the effect of ASCs-exos on the common signaling pathways related to osteogenesis. Our results showed that the Wnt/β-catenin pathway might be involved in the enhancement of BMSC osteogenic differentiation via ASCs-exos. There is a growing amount of research that has demonstrated that the Wnt/β-catenin signaling pathway is regarded as a significant mediator of BMSC differentiation into osteoblasts via regulating β-catenin levels and subcellular localization [47,48]. Wnt/β-catenin signaling pathways include canonical and noncanonical approaches, in which canonical Wnt ligands promote osteogenesis, and noncanonical Wnt5a can inhibit canonical Wnt signaling [49]. In the canonical Wnt approach, the binding of canonical Wnt ligands, such as Wnt3a, Wnt8a and Wnt10b, to frizzled receptors on the cell surface results in the nuclear translocation of β-catenin, which ultimately binds with the TCF/LEF region to initiate the transcription of osteogenic genes such as Runx2 and OCN [50]. Furthermore, our findings further revealed that canonical Wnt3a was involved in the promotive effect of osteogenic differentiation in BMSCs induced via ASCs-exos. More importantly, our in vivo studies demonstrated that the promoting effect of ASCs-exos on the osteogenic differentiation of BMSCs can partially be blocked via DKK-1, which is regarded as an effective inhibitor of the Wnt/β-catenin signaling pathway. All these findings reveal that ASCs-exos have great potential in advancing the osteogenic differentiation of BMSCs via activating the Wnt3a/β-catenin signaling pathway, and provide a novel direction for the treatment of fracture nonunion in DM. In addition, our data show that the AEFS held biological activity, including the upregulation of the protein expression of Runx2 in vitro. These results also suggest the potential usefulness of AEFS for particular situations. However, there are some limitations to our current study. It is well known that exosomal therapeutic potential is mainly based on the content of different patterns of RNAs and proteins; therefore, further research is essential to explore the exact mechanism for improving bone fractures in DM. In addition, we may also need to further investigate the optimal dosage of ASCs-exos that has beneficial effects on bone fractures in DM. ## 4.1. The T2DM Rat Model of Fracture Establishment and Treatment All animal experiments were performed in compliance with the guidelines of the Institutional Animal Care and Use Committee (IACUC) of Wuhan University. Additionally, the experimental protocol was approved by the Committee on the Ethics of Animal Experiments of Wuhan University. All efforts were made to minimize animal suffering. After feeding for one week, the animals were accurately weighed and classified by cage (3 rats/cage), and 36 Sprague Dawley (SD) male rats were randomly distributed into 2 groups. Many studies have shown the procedures for creating a T2DM rat model [22,51]. After 3 weeks of an HFD containing $60\%$ fat, 18 rats in the T2DM group were injected with STZ (40 mg/kg in citrate buffer). The control group with a normal diet received an equal volume of citrate buffer. To consecutively evaluate the blood glucose levels, blood samples were collected from the tail. According to the protocols, rats with more than three RBG samples >16.7 mmol/L were identified to have T2DM after 7 weeks. For the generation of a longstanding diabetes-related complication, animals were given free access to their original diets (the high-fat or control diet) for 12 weeks. For the assessment of the T2DM model, we measured the metabolic index including body weight, food intake, water consumption and volume of excreted urine at several time points, including before being fed the HFD and 12 weeks after STZ injection. In addition, RBG was observed at several special time points, which is shown in Figure 3A. At the end of observation, IPGTT was evaluated. Animals were fasted for 12 h and injected with 1.5 g/kg glucose. BG was measured at 0, 30, 60 and 120 min. Additionally, ITT was carried out by injecting the rats with 0.75 IU/kg insulin, and then BG was obtained at several special time points as was performed for IPGTT. Animals with an RBG below 10 mmol/L at any time were regarded as nondiabetic, and those with an RBG between 10 mmol/L and 16.7 mmol/L were excluded. At 12 weeks after STZ injection, rats in the T2DM group were used to establish the model of bone fracture. Additionally, rats in the control group were used for the isolation of ASCs. Rats were positioned under general anesthesia with ketamine hydrochloride (60 mg/kg body weight) before surgery. To expose the femurs, a lateral incision was made along the proximal femur. The soft tissues including fascia and muscle were divided longitudinally; a transverse osteotomy of the mid-diaphysis of the femur was operated via an oscillating mini-saw. Then, a lateral parapatellar incision with the patella medially dislocated was used to expose the knee. After the femur intercondylar groove was adequately exposed via the full flexion of the knee joint, Kirschner’s wires were inserted to keep the fracture stably fixated at the center of the intercondylar groove, and the tip of the needle was run through the top of the greater trochanter of the femur. Finally, the incision was closed using a 5-0 nylon suture. All the rats were kept in a single cage. Unprotected weight bearing was allowed immediately. Based on the operation of X-ray examinations, the fracture sites of rats were located and marked on the skin. Then, 600 μL of ASCs-exos at a concentration of 200 μg/mL, as well as equal volumes of PBS and AEFS, was locally injected into the fracture site every three days after surgery. In addition, X-ray imaging, micro-CT, histological analysis and Western blot analysis of the fractured femurs were performed 28 days after operation. ## 4.2. Cell Culture ASCs were isolated and cultured following the methods previously described [52]. Eighteen SD rats with a normal diet were used in this part. The subcutaneous fat from the groin of the rat was harvested and washed two times with PBS. Adipose tissue was chopped using sterile operation scissors, which was followed by centrifugation at 1500 rpm for 10 min. Additionally, the supernatant was abolished, and the mixed collagenases were added into the precipitate. After digestion action for 40 min at 37 °C, the completed culture medium consisting of Dulbecco’s modified *Eagle medium* (DMEM, Gibco, CA, USA) high glucose, $10\%$ fetal bovine serum (FBS, Serapro, CA, USA) and $1\%$ penicillin/streptomycin was added to stop the reaction, and the mixture was filtered through a 70 μm filter. After another centrifugation at 1500 rpm for 8 min, the cell was resuspended in the completed culture medium and maintained with fresh culture medium supplemented on the 4th day. After 8 days of being cultured, ASCs were harvested for identification and analyzing the gain of exosomes. Briefly, an $80\%$ confluence of ASCs was washed three times using PBS and cultured in the medium with exosome-depleted FBS. After 48–72 h, the supernatant was collected, centrifuged at 300× g for 10 min at 4 °C and then further centrifuged at 2000× g for 10 min at 4 °C to eliminate whole cells and cellular debris. Afterwards, the supernatant was recollected and centrifuged at 100,000× g for 6 h at 4 °C to pellet the exosomes. After gaining the precipitate that can be regarded as exosomes, the ASCs-exos-free supernatant was also collected for the following experiments. Additionally, the exosomes were washed using PBS to remove the contaminating proteins and continually ultracentrifuged at 100,000× g for 20 min at 4 °C. Finally, the exosomes were resuspended in PBS for the following experiments. The identification of exosomes was performed via TEM (HITACHI, HT7700) to confirm the morphology of the exosomes, DLS (Particle Metrix, Meerbusch, Germany), to analyze the diameter distributions and Western blotting to identify the specific exosome surface markers such as CD9, CD63 and TSG101. The rat BMSCs were from our laboratory, and the isolation and identification of rat BMSCs were described in our previous study [22,53]. A 200 g/L glucose solution was used to alter the glucose concentration of the medium. Before induced osteogenic differentiation, BMSCs were cultured in a medium that consisted of α-MEM supplemented with $10\%$ FBS, 100 U/mL penicillin/streptomycin and 5 mM glucose. Additionally, BMSCs in the passages 3–5 were seeded into 6-well plates for osteogenic differentiation. To mimic the diabetic conditions in vitro, the glucose concentration of the osteogenic-induced medium used for the BMSCs was 30 mM. ## 4.3. Identification of ASCs ASCs were identified via multipotent differentiation potential and flow cytometry. For adipogenic induction, ASCs were cultured in adipogenic induction medium (Cyagen Biosciences, Santa Clara, CA, USA). The adipocytes were stained with Oil red O staining on day 14. To induce osteogenic differentiation, a specific SD rat osteogenic induction medium (Cyagen Biosciences) was used. The cells were stained with ARS on day 14. For chondrogenic differentiation, ASCs were cultured for 2 weeks in chondrogenic induction medium (Cyagen Biosciences). On day 14, the cells were stained with toluidine blue to detect the secretion of sulfated glycosaminoglycans. Additionally, all of the media were replaced every 3 days. In addition, the identification of ASCs was measured via flow cytometry. ASCs were detected with antibodies against CD34 (Invitrogen, Waltham, MA, USA), CD45 (eBioscience, San Diego, CA, USA), CD44 (Invitrogen) and CD90 (BioLegend, San Diego, CA, USA). Results were analyzed via Flowjo software. ## 4.4. Exosome Uptake Assay Based on the manufacturer’s protocol, PKH26 was used to label the exosomes for an exosome uptake assay. Briefly, the mixture of exosomes and PKH26 dye solution was incubated for 20 min at room temperature. Exosomes were obtained with centrifugation (110,000× g, 20 min, 4 °C). Additionally, BMSCs were seeded into a 35 mm confocal dish at the proper density and labeled with DAPI. Moreover, exosomes labeled with PKH26 were mixed with BMSCs labeled with DAPI. Finally, they were co-cultured for 12 h and observed using a fluorescence microscope. ## 4.5. BMSC Osteogenic Differentiation Passage 3 BMSCs were seeded into 6-well plates (2 × 105 cells per well), which were precoated with $0.1\%$ gelatin and incubated for 14 days using a specific osteogenic induction medium (Cyagen Biosciences). For evaluating the effect of ASCs-exos on osteogenic differentiation, 200 μL of ASCs-exos with a concentration of 200 μg/mL and equal volumes of PBS and AEFS was supplemented with the osteogenic induction medium and refreshed every three days. In addition, 500 ng/mL of DKK-1 was applied for investigating the involvement of the Wnt/β-catenin pathway in ASCs-exos by promoting the differentiation of BMSCs. To evaluate the level of osteogenic differentiation, the cells were stained with alkaline phosphatase (ALP) staining and alizarin red staining, and were collected for Western blotting on day 14. ## 4.6. Immunofluorescence Analysis After BMSCs were induced for 2 weeks in different groups, the cells were fixed in $4\%$ paraformaldehyde for 20 min at 25 °C, permeabilized for 30 min in $0.2\%$ Triton X-100 and blocked for 30 min in $2\%$ bovine serum albumin. Fixed cells were washed and incubated for 12 h with anti-Runx2 (1:300; CST), collagen I (1:300; Abcam) or OCN (1:300; PTG). After washing three times with PBS, cells were incubated with a fluorescence-conjugated secondary antibody (ASPEN) for 40 min, and the nuclei were stained with DAPI (Sigma) for 30 min. Finally, cells were observed via a fluorescence microscope. ## 4.7. ALP and Alizarin Red Staining After BMSCs were induced for 14 days with different treatments, the cells washed two times via PBS and fixed with $4\%$ paraformaldehyde for 30 min at room temperature were used for ALPS and ARS. A BCIP/NBT ALP kit (#C3206, Beyotime, Nantong, China) was used for ALPS. After the stained cells were washed using PBS three times, the BCIP/NBT substrate was utilized to treat BMSCs. The colorimetric changes of cells were imaged via microscopy. After removing the whole cells and cellular debris via centrifugation at 2000× g for 10 min at 4 °C, the supernatant was collected and distributed into each well of 96-well plates for an alkaline phosphatase activity assay. Subsequently, the absorbance of the samples was observed via a microplate reader at 405 nm. The quantification of ALPS was calculated by comparing the measured OD values against the standard curve. The 40 mM solution of ARS was used to stain the cells at room temperature for 30 min. Subsequently, the unbound alizarin red dye was eliminated, and stained BMSCs were washed three times using PBS and observed via microscopy. For ARS quantification, $10\%$ acetic acid was added to the stained cells and they were incubated for 15 min at room temperature. After the collection of the supernatant via centrifugation at 2000× g for 10 min at 4 °C, $10\%$ NH4OH was added and mixed into the supernatant. Finally, the absorbance was measured at 507 nm. Values were normalized to a calibration curve. ## 4.8. Radiographic and Histological Analysis The femurs of rats under different treatments were harvested and photographed on day 28 after surgery. To observe the fracture regions, the X-ray images were acquired using an X-ray imaging system for animals. After Kirschner’s wires were removed from the femurs, the fracture sites were scanned by using a micro-CT system (40 μm, 70 kV, 200 µA). Next, 3D structures and bone volume/total volume (BV/TV) of the fracture sites were obtained. After the samples were fixed with $4\%$ paraformaldehyde and decalcified with $20\%$ EDTA at 25 °C for 25 days, the tissues were then embedded in paraffin, and the samples were stained with Masson, H&E and safranin O-fast green staining. Finally, samples were observed using a microscope. ## 4.9. Western Blot Analysis Western blotting was performed using previously described protocols. After the concentrations of protein were measured via BCA (Aspen), the protein was separated into equal amounts via SDS-PAGE (Beyotime Biotechnology, Shanghai, China), transferred into the PVDF membrane (Millipore, Burlington, MA, USA) and then incubated with $5\%$ bovine serum albumin for 1 h at 25 °C. Next, the membranes were incubated overnight with primary antibodies specific for CD9 (Abcam), CD63 (Abcam), TSG101 (Abcam), Runx2 (Abcam), collagen I (Abcam), OCN (Santa), AKT (CST), ERK (CST), JNK (CST), p-65 (CST), β-catenin (CST), Wnt3a (Abcam), Wnt5a (Abcam), Wnt8a (Bioss), Wnt10b (Isbio) and GAPDH (Abcam). Then, samples were mixed with the secondary antibodies (1:2,000, 30 min). The membranes were incubated with Immobilon ECL reagent (Thermo Fisher Scientific, Waltham, MA, USA), and the bands were quantified via software. ## 4.10. Statistical Analysis The data are represented as the mean ± SD, and were analyzed with GraphPad Prism 8.0. All the experiments were repeated at least three times. Student’s t-test was used to analyze the two independent groups. A value of $p \leq 0.05$ was considered to be statistically significant. ## 5. 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--- title: Placental Mesenchymal Stem Cells Alleviate Podocyte Injury in Diabetic Kidney Disease by Modulating Mitophagy via the SIRT1-PGC-1alpha-TFAM Pathway authors: - Xiudan Han - Jiao Wang - Ruilin Li - Meiling Huang - Guanru Yue - Lulu Guan - Yuanyuan Deng - Wei Cai - Jixiong Xu journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003373 doi: 10.3390/ijms24054696 license: CC BY 4.0 --- # Placental Mesenchymal Stem Cells Alleviate Podocyte Injury in Diabetic Kidney Disease by Modulating Mitophagy via the SIRT1-PGC-1alpha-TFAM Pathway ## Abstract The use of mesenchymal stem cells (MSCs) has become a new strategy for treating diabetic kidney disease (DKD). However, the role of placenta derived mesenchymal stem cells (P-MSCs) in DKD remains unclear. This study aims to investigate the therapeutic application and molecular mechanism of P-MSCs on DKD from the perspective of podocyte injury and PINK1/Parkin-mediated mitophagy at the animal, cellular, and molecular levels. Western blotting, reverse transcription polymerase chain reaction, immunofluorescence, and immunohistochemistry were used to detect the expression of podocyte injury-related markers and mitophagy-related markers, SIRT1, PGC-1α, and TFAM. Knockdown, overexpression, and rescue experiments were performed to verify the underlying mechanism of P-MSCs in DKD. Mitochondrial function was detected by flow cytometry. The structure of autophagosomes and mitochondria were observed by electron microscopy. Furthermore, we constructed a streptozotocin-induced DKD rat model and injected P-MSCs into DKD rats. Results showed that as compared with the control group, exposing podocytes to high-glucose conditions aggravated podocyte injury, represented by a decreased expression of Podocin along with increased expression of Desmin, and inhibited PINK1/Parkin-mediated mitophagy, manifested as a decreased expression of Beclin1, the LC3II/LC3I ratio, Parkin, and PINK1 associated with an increased expression of P62. Importantly, these indicators were reversed by P-MSCs. In addition, P-MSCs protected the structure and function of autophagosomes and mitochondria. P-MSCs increased mitochondrial membrane potential and ATP content and decreased the accumulation of reactive oxygen species. Mechanistically, P-MSCs alleviated podocyte injury and mitophagy inhibition by enhancing the expression of the SIRT1-PGC-1α-TFAM pathway. Finally, we injected P-MSCs into streptozotocin-induced DKD rats. The results revealed that the application of P-MSCs largely reversed the markers related to podocyte injury and mitophagy and significantly increased the expression of SIRT1, PGC-1α, and TFAM compared with the DKD group. In conclusion, P-MSCs ameliorated podocyte injury and PINK1/Parkin-mediated mitophagy inhibition in DKD by activating the SIRT1-PGC-1α-TFAM pathway. ## 1. Introduction Diabetic kidney disease (DKD), also known as diabetic nephropathy, is a renal complication of diabetes, is one of the main causes of morbidity and mortality in patients with diabetes mellitus [1]. Epidemiological studies have shown that, compared with other diabetic complications, the prevalence of DKD has not changed significantly in recent decades [2]. DKD has become a global public health issue and has imposed a tremendous economic burden onto society and public health systems. Nearly $40\%$ of people with diabetes mellitus will develop DKD, which is the leading cause of chronic kidney disease and end-stage renal disease worldwide [3]. Albuminuria is a significant clinical symptom of DKD and is closely associated with podocyte damage [4]. Podocytes are terminally differentiated glomerular visceral epithelial cells that can maintain the integrity of the glomerular filtration barrier [5,6]. The injury and loss of podocytes comprise an early feature of DKD that predicts its progressive course [7]. Silencing information regulator 2 related enzyme 1 (sirtuin1, SIRT1), an NAD(+)-regulated deacetylase, plays a significant role in cellular senescence [8]. Protective effects of SIRT1 on podocyte injury in DKD have been reported [9,10]. Hence, maintaining the normal structure and function of podocytes and preventing podocyte damage are important measures in the prevention and treatment of DKD. Autophagy plays a crucial role in maintaining lysosome homeostasis in podocytes under diabetic conditions, and its impairment is an important pathophysiological mechanism of DKD [11]. Mitophagy is a highly conserved autophagic process that selectively removes damaged or unnecessary mitochondria, and it plays an important role in maintaining the stability of the intracellular environment [12]. Phosphatase and tensin homolog-induced kinase 1 (PINK1)/Parkin-mediated mitophagy is a hotspot for research in mammalian cells [13]. Damaged mitochondria accumulate PINK1 in the mitochondrial outer membrane, which then recruits and activates Parkin, resulting in the ubiquitination of mitochondrial proteins. These proteins can then be bound by the autophagic proteins p62/SQSTM1 and LC3, resulting in the degradation of mitochondria by mitophagy [14]. Peroxisome proliferator-activated receptor γ coactivator-1alpha (PGC-1alpha, PGC-1α) and transcription factor A, mitochondrial (TFAM) are involved in mitochondrial biogenesis [15]. Impaired mitophagy and persistent mitochondrial dysfunction play a crucial role in the early stages and progression of DKD [16,17]. Unfortunately, there is no efficient therapy to prevent or even reverse podocyte injury and mitophagy inhibition in DKD. In recent years, the application of mesenchymal stem cells (MSCs) in the treatment of DKD has shown good prospects [18,19]. Placenta derived mesenchymal stem cells (P-MSCs) have many advantages, such as an extensive sources, convenient drawing, less ethical controversy, and strong proliferative ability. Studies have shown that human umbilical cord MSCs prevented podocyte damage in DKD by inhibiting the Toll-like receptor signaling pathway and depressing inflammation [20]. However, no studies have reported the effect of P-MSCs on podocyte injury and mitophagy in DKD, and the underlying mechanism remains unclear. From this background, we will investigate the therapeutic effect of P-MSCs on DKD and the corresponding molecular mechanism from the perspective of podocyte injury and mitophagy inhibition. ## 2.1. Podocyte Injury and PINK1/Parkin-Mediated Mitophagy Inhibition Induced by High Glucose in the Mouse Podocyte Cell Line First, we determined whether high glucose (HG)-aggravated podocyte injury and decreased PINK1/Parkin-mediated mitophagy. We selected the mouse podocyte cell line, the MPC5 cell line, for the cell experiments. MPC5 was treated with different concentrations of glucose (30 mM, 40 mM, and 50 mM) for 48 h. The results showed that as compared with the control group, exposing podocytes to HG conditions inhibited PINK1/Parkin-mediated mitophagy, manifested as a decreased expression of Beclin1, the LC3II/LC3I ratio, Parkin, PINK1 associated with an increased expression of P62 (Figure 1A,B), and aggravated podocyte injury, represented by a decreased expression of Podocin along with an increased expression of Desmin (Figure 1C,D). Moreover, HG suppressed PINK1/Parkin-mediated mitophagy and exacerbated podocyte injury in a concentration-dependent manner. Then, to evaluate the optimal intervention time for HG, we treated MPC5 with HG (50 mM) for 24, 48, and 72 h. Results suggested that the expression of Beclin1 and the LC3II/LC3I ratio were significantly decreased, and the expression of P62 and Desmin were significantly increased after 48 h of HG intervention compared with 24 h and 72 h (Figure 1E–H). Hence, in the subsequent experiments, HG was used at 50 mM for 48 h. ## 2.2. P-MSCs Attenuated HG-Induced Podocyte Injury and PINK1/Parkin-Mediated Mitophagy Inhibition In recent years, MSCs have played an increasingly crucial role in diabetes and its complications [21,22]. We investigated whether P-MSCs could ameliorate podocyte injury and regulate PINK1/Parkin-mediated mitophagy in DKD. To this purpose, we used western blot (WB) and reverse transcription–polymerase chain reaction (RT-PCR) to detect PINK1/Parkin-mediated mitophagy/podocyte injury-related proteins and mRNAs in MPC5 cells. WB analysis showed that the P-MSCs group had an increased expression of Beclin1, the LC3II/LC3I ratio, Parkin, PINK1, Tom20, and Podocin as compared with the HG group, and a decreased expression of P62 and Desmin (Figure 2A,B). The results of the RT-PCR analysis were consistent with those of the WB analysis, except for Podocin (Figure 2C). Furthermore, immunofluorescence analysis revealed that P-MSCs attenuated podocyte injury by increasing the expression of Podocin and decreasing the expression of Desmin (Figure 2D–G). These results illustrated that P-MSCs could reduce the degree of HG-induced podocyte injury and increase the level of PINK1/Parkin-mediated mitophagy. In addition, we used transmission electron microscopy to observe the structure and quantity of the nuclear membrane, autophagosomes, and lysosomes. As shown in Figure 3A, the nuclear membrane was intact along with more autophagosomes (red arrows) and lysosomes (green arrows) in the control group. However, the integrity of the nuclear membrane was disrupted, and was accompanied by fewer autophagosomes and lysosomes under HG conditions. Interestingly, P-MSCs reduced nuclear damage and increased autophagosomes and lysosomes. ## 2.3. P-MSCs Extenuated HG-Mediated Mitochondrial Dysfunction and Reactive Oxygen Species Accumulation We observed mitochondria structure using transmission electron microscopy. As shown in Figure 3B, mitochondria were columnar or reticular, with clear mitochondrial cristae, normal matrix density, and intact mitochondrial membranes in the control group. Mitochondrial structures were significantly damaged in the HG group. Nevertheless, P-MSCs improved the structure of mitochondria (Figure 3B). Additionally, a growing number of studies have implicated that mitochondrial dysfunction was associated with podocyte damage and albuminuria [23,24]. In this study, we measured mitochondrial membrane potential (ΔΨm) and ATP content in different groups, representing the level of mitochondrial function. The results implied that ΔΨm (Figure 4A,C) and ATP content (Figure 4D) were significantly decreased in the HG group as compared with the control group, indicating that mitochondrial function was seriously damaged under HG states. Furthermore, in conditions of hyperglycemia, accumulation of reactive oxygen species (ROS) was observed (Figure 4B,E), which indirectly contributes to podocyte injury. Interestingly, the effects of HG on ΔΨm, ROS, and ATP content were reversed by P-MSCs, suggesting an overall improvement of mitochondrial function (Figure 4A–E). ## 2.4. P-MSCs Alleviated HG-Induced Podocyte Injury and PINK1/Parkin-Mediated Mitophagy Inhibition by Activating the SIRT1-PGC-1α-TFAM Signaling Pathway We performed the following experiments to further explore the mechanism by which P-MSCs affected podocyte injury and PINK1/Parkin-mediated mitophagy. Recent studies have reported that mitophagy is initiated by upregulation of SIRT1 [25,26]. In addition, PGC-1α and TFAM proteins appear to be vital factors in SIRT1-associated mitophagy [27,28]. Hence, we detected the expression levels of SIRT1, PGC-1α, and TFAM in different groups first and foremost. The results of the WB and RT-PCR analyses suggested that the expressions of SIRT1, PGC-1α, and TFAM were notably decreased in the HG group as compared with the control group. However, the influence of HG on the expressions of SIRT1, PGC-1α, and TFAM was reverted by P-MSCs (Figure 5A–C). Immunofluorescence analysis also consistently revealed the same results as WB and RT-PCR analyses (Figure 5D–I). Subsequently, to confirm whether SIRT1 was necessary for P-MSCs to regulate podocyte injury and PINK1/Parkin-mediated mitophagy, SIRT1 expression was overexpressed. We verified the overexpression efficiency using both WB analysis (Figure 6C,D) and RT-PCR analysis (Figure 6E). The changes of the podocyte injury and mitophagy-related proteins and mRNAs after SIRT1 overexpression were then detected again. WB analysis (Figure 6A,B) and RT-PCR analysis (Figure 6F) showed that as compared with the negative control vector (OE-NC) group, the expressions of Beclin1, the LC3II/LC3I ratio, Parkin, PINK1, Tom20, and Podocin were increased. In contrast, the expressions of P62 and Desmin were decreased in the SIRT1 overexpression (OE-SIRT1) group, indicating that by upregulating the expression of SIRT1, P-MSCs play a protective role in HG-induced podocyte injury and PINK1/Parkin-mediated mitophagy. Interestingly, we found that the expression of PGC-1α and TFAM was increased along with SIRT1 overexpression (Figure 6C–E). Furthermore, siRNA was used to knock down the expression of SIRT1. The WB and RT-PCR analyses determined podocyte injury-related markers and mitophagy-related markers. The results demonstrated that the inhibition of SIRT1 expression aggravated podocyte injury, inhibited PINK1/Parkin-mediated mitophagy, and decreased the expression of PGC-1α and TFAM (Figure S1A–G). In addition, to determine whether P-MSCs protected podocytes from damage and enhanced PINK1/Parkin-mediated mitophagy through the SIRT1-PGC-1α-TFAM signaling pathway, we performed rescue experiments. WB analysis data showed that the expressions of Beclin1, the LC3II/LC3I ratio, Parkin, PINK1, Tom20, and Podocin increased, whereas the expressions of P62 and Desmin decreased after SIRT1 overexpression. Nevertheless, when the expression of PGC-1α was inhibited, the expression of Beclin1, the LC3II/LC3I ratio, Parkin, PINK1, Tom20, and Podocin were decreased, and the expression of P62 and Desmin were increased. Notably, mitophagy-related proteins and podocyte injury-related proteins were reversed when SIRT1 was overexpressed and PGC-1α was inhibited at the same time, suggesting that P-MSCs play a protective role in podocyte injury and PINK1/Parkin-mediated mitophagy inhibition through the SIRT1-PGC-1α signaling pathway (Figure 7A,B). Furthermore, when the expression of SIRT1 was overexpressed, the expression of TFAM also increased correspondingly. Meanwhile, the expression of TFAM decreased along with the decrease of PGC-1α expression. Interestingly, when SIRT1 was overexpressed and PGC-1α was inhibited simultaneously, the expression of TFAM was reverted at both protein (Figure 7C,D) and mRNA (Figure 7E) levels, indicating that P-MSCs play a protective role in podocytes via the SIRT1-PGC-1α-TFAM signaling pathway. ## 2.5. P-MSCs Ameliorated Streptozotocin-Induced Podocyte Injury and PINK1/Parkin-Mediated Mitophagy in DKD Rats Our group had previously constructed an streptozotocin (STZ)-induced DKD rat model and successfully injected P-MSCs into DKD rats via the tail vein. The results showed that treatment with P-MSCs can effectively improve blood glucose, serum creatinine, blood urea nitrogen, urinary albumin/creatinine ratio, renal hypertrophy index, and renal pathological injury in DKD rats [29]. To validate the protective effect of P-MSCs on DKD rats in vivo from the perspective of podocyte injury and PINK1/Parkin-mediated mitophagy, we performed an immunohistochemical analysis in this study. The results showed that compared with the control group, the expression of Beclin1, LC3, Parkin, PINK1, and Tom20 were decreased, and the expression of P62 and Desmin were increased in the DKD group. However, the application of P-MSCs largely reversed the markers related to podocyte injury and PINK1/Parkin-mediated mitophagy (Figure 8A–C), meaning that P-MSCs could alleviate podocyte injury and PINK1/Parkin-mediated mitophagy inhibition in DKD rats. Furthermore, the expressions of SIRT1, PGC-1α, and TFAM were markedly decreased in the DKD group compared with the control group. Nevertheless, the injection of P-MSCs into DKD rats significantly increased the expression of SIRT1, PGC-1α, and TFAM in DKD rats (Figure 8D,E). ## 3. Discussion The therapeutic effect of P-MSCs on DKD has not been reported until now. We evaluated for the first time whether P-MSCs ameliorated podocyte injury and PINK1/Parkin-mediated mitophagy inhibition in DKD and further explored the underlying molecular mechanisms. Based on our data, we can draw the following conclusions. First, we found that hyperglycemia induced podocyte injury and PINK1/Parkin-mediated mitophagy inhibition in the cell experiments. Second, P-MSCs not only alleviated HG-induced podocyte injury and PINK1/Parkin-mediated mitophagy inhibition but also prevented mitochondrial dysfunction. In addition, through knockdown, overexpression, and rescue experiments, we demonstrated that P-MSCs extenuated HG-induced podocyte injury and PINK1/Parkin-mediated mitophagy inhibition by activating the SIRT1-PGC-1α-TFAM signaling pathway. Finally, we further verified that P-MSCs improved renal function and attenuated podocyte injury and PINK1/Parkin-mediated mitophagy inhibition induced by STZ in DKD rats. Briefly, P-MSCs ameliorated podocyte injury and PINK1/Parkin-mediated mitophagy inhibition in DKD through the SIRT1-PGC-1α-TFAM signaling pathway. Targeting the PINK1/Parkin-mediated mitophagy and SIRT1-PGC-1α-TFAM signaling pathways may provide a new potential therapeutic approach for P-MSCs in DKD. It is well known that podocytes are highly differentiated epithelial cells attached to the glomerular basement membrane and play a significant role in maintaining the normal filtration function of the kidney [30]. Podocyte injury is a crucial factor in DKD progression [31]. Hence, we wanted to know whether P-MSCs improved podocyte injury in DKD. Previous validation studies have shown that Desmin, a podocyte injury marker, was upregulated in DKD. In contrast, Podocin, a key component of the podocyte slit diaphragm, was downregulated [32,33,34]. These results were consistent with our findings. However, the effect of P-MSCs on podocyte injury in DKD was investigated in this study. Our results found that P-MSCs increased the expression of Podocin and decreased the expression of Desmin, implying that P-MSCs could indeed alleviate podocyte injury in DKD. Mitophagy is a process in which damaged or dysfunctional mitochondria are selectively delivered to lysosomes for degradation [35]. In mammals, it is primarily regulated by the PINK1/Parkin signaling pathway. PINK1/Parkin-mediated mitophagy contributes to maintaining mitochondrial quantity and quality in a variety of cell types [13]. Recent observations have reported that PINK1/Parkin-mediated mitophagy is one pathogenesis of DKD [36,37]. P62/SQSTM1, as an autophagy adaptor, interacts with LC3 and then participates in the process of PINK1/Parkin-mediated mitophagy [38]. Tom20, a functional protein of mitochondria, was associated with mitophagy and mitochondrial function [39]. He et al. showed that when the level of mitophagy was reduced, Beclin1, the LC3II/LC3I ratio, Parkin, PINK1, and Tom20 levels increased and P62 levels decreased. Our results are in accordance with previous studies. We next evaluated the effect of P-MSCs on PINK1/Parkin-mediated mitophagy in DKD. A growing but limited number of studies have found that MSCs can improve cell metabolism and function through mitophagy [40,41] and MSCs prevent the progression of DKD by reversing mitochondrial dysfunction in renal tubular epithelial cells [42]. P-MSCs have the advantages of abundant sources, strong proliferation potential, and low immunogenicity, which make them a valuable biological resource for the promotion of tissue repair. A previous study reported that P-MSCs can improve tissue damage of the testis by promoting autophagy and reducing apoptosis [43]. Li et al. demonstrated that P-MSCs can reduce the damage of pulmonary microvascular endothelial cells and improve mitochondrial function by enhancing autophagy [44]. Some studies have also shown that P-MSCs upregulated markers related to mitophagy and adjusted mitochondrial energy metabolism in trophoblast cells [45,46]. However, no studies have reported the ability of P-MSCs to repair renal injury through mitophagy in DKD. In this study, we found that P-MSCs increased the levels of mitophagy-related markers in in vitro and in vivo experiments. The results of WB, RT-PCR, and immunohistochemical analysis showed that as compared with the HG group, the P-MSCs group increased the expression of Beclin1, the LC3II/LC3I ratio, Parkin, and PINK1 and decreased the expression of P62. Moreover, P-MSCs reduced ROS accumulation and mitochondrial dysfunction, which was manifested by the increase in ΔΨm and ATP content. Finally, we further explored the mechanism of P-MSCs on podocyte injury and PINK1/Parkin-mediated mitophagy in DKD. SIRT1 has good potential as a clinical target for preventing and treating DKD [47]. By increasing the expression of SIRT1, MSCs can reduce inflammasome signaling and apoptosis [48]. Studies have also suggested that the expression of PGC-1α and TFAM are decreased in human podocytes under HG [49]. Mitochondria from MSCs were transferred to macrophages in a co-culture system consisting of MSCs and macrophages. MSCs also ameliorated kidney injury in mice with DKD through mitochondrial transfer, which is dependent on PGC-1α-mediated mitochondrial biogenesis [50]. TFAM is essential for maintaining mitochondrial DNA and mitochondrial biogenesis [51]. Furthermore, the activation of the SIRT1/PGC-1α pathway can increase the level of mitophagy [52], and the SIRT1-PGC-1α-TFAM pathway played a crucial role in regulating mitochondrial function [28]. Based on the above reported literature, we wanted to prove whether P-MSCs alleviated podocyte injury and PINK1/Parkin-mediated mitophagy through the SIRT1-PGC-1α-TFAM signaling pathway. The results of the WB, RT-PCR, immunofluorescence, and immunohistochemistry analyses confirmed that, as compared with the control group, the expression of SIRT1, PGC-1α, and TFAM in the HG group was significantly decreased. The effects of HG on SIRT1, PGC-1α, and TFAM were reversed by P-MSCs. Furthermore, we also demonstrated that P-MSCs attenuated podocyte injury and PINK1/Parkin-mediated mitophagy inhibition via the activation of the SIRT1-PGC-1α-TFAM signaling pathway through knockdown, overexpression, and rescue experiments. Our results suggest that the SIRT1-PGC-1α-TFAM signaling pathway plays an important role in the attenuation of podocyte injury and PINK1/Parkin-mediated mitophagy in DKD for P-MSCs. We not only evaluated the therapeutic efficacy and cellular mechanisms of P-MSCs on DKD, but also affirmed that the therapeutic measures of P-MSCs are safe and effective. However, our study also has some limitations. Firstly, in our vivo experiments, we merely demonstrated the role of P-MSCs in STZ rats instead of db/db mice. However, rats are more similar to humans in cognitive behavior compared to mice. Secondly, in vitro experiments, we only investigated the beneficial effects of P-MSCs on podocyte injury and mitophagy in DKD, so the protective effects of P-MSCs on renal tubular cell injury require further evaluation. Finally, it has been reported in the literature that P-MSCs provide promising applications for clinical treatments [53]. However, we did not continue to further explore the mechanism of P-MSCs in DKD at the organizational level. Consequently, we will continue to carry out relevant clinical studies for the benefit of patients with DKD. In summary, our findings provide important experimental evidence that P-MSCs play an essential role in the treatment of DKD, not only at the cellular level, but also at the animal level. We probed the therapeutic effect of P-MSCs in DKD mainly from the perspective of podocyte injury and PINK1/Parkin-mediated mitophagy inhibition. Interestingly, we detected that the SIRT1-PGC-1α-TFAM signaling pathway played a crucial role in DKD. ## 4.1. Reagents and Antibodies Fetal bovine serum (FBS) was purchased from Gibco (HyClone, Logan, UT, USA). Lipofectamine 2000 was acquired from Invitrogen (Waltham, MA, USA). Anti-Beclin1 (11306-1-AP), anti-LC3B (14600-1-AP), anti-PINK1 (23274-1-AP), anti-Tom20 (11802-1-AP), anti-PGC-1α (66369-1-Ig), and anti-Podocin (20384-1-AP) were purchased from Proteintech (Rosemont, IL, USA). Anti-P62 (ab109012), anti-Parkin (ab77924), anti-Desmin (ab32362), and anti-SIRT1 (ab189494) were purchased from Abcam (Boston, MA, USA). TFAM (AF0531) was obtained from Affinity Biosciences (Cincinnati, OH, USA). Anti-beta actin (anti-β-actin) and horseradish peroxidase-conjugated secondary antibodies were acquired from Beijing Zhong Shan Golden Bridge Biological Technology Co., Ltd. (Beijing, China). ## 4.2. Cell Culture The MPC5 cell line was purchased from GuangZhou Jennio Biotech Co., Ltd. (Guangzhou, China). P-MSCs were kindly provided and prepared in the GMP laboratory of the Stem Cell Engineering Research Center of Jiangxi Province (Shangrao, China). P-MSCs were isolated based on methods previously described [54,55,56]. Briefly, human placenta was obtained from a healthy mother. Informed consent was obtained from participants in all studies. Placental tissues were treated with collagenase II (Gibco, Grand Island, NY, USA) at 37 °C for 1 h and further digested with trypsin (Gibco) at 37 °C for 30 min with gentle agitation. The surface markers and differentiation capacity of P-MSCs have been previously identified [57]. P-MSCs and MPC5 were seeded separately in T25 flasks (Corning, NY, USA) and cultured in Dulbecco’s Modified Eagle’s Medium (Gibco) containing $10\%$ FBS at 37 °C in a $5\%$ CO2 humidified incubator. MPC5 was divided into different groups, which were treated with normal glucose (5.6 mM), HG (30 mM, 40 mM, and 50 mM), and HG plus P-MSCs. P-MSCs and MPC5 were co-cultured at a ratio of 1:10. ## 4.3. Transfections of Plasmids and Small Interfering RNAs To effect changes in SIRT1, MPC5 was treated with SIRT1 plasmid using Lipofectamine 2000 as the transfection reagent and nonsense strand negative control (NC) as controls. Full sequences of SIRT1 plasmid can be found in Supplementary Table S1. Briefly, cells were starved for 2 h in six-well plates before transfection. Lipofectamine 2000 was mixed with 250 μL Opti-MEM, whereas SIRT1 plasmid was mixed with 250 μL Opti-MEM at a 1 μg target dose (the plasmid group was supplemented with 10 μL Lipofectamine 2000 reagent/well). The two commixtures were mixed together for 20 min and then added to the cell culture medium. After 6 to 8 h, the transfection medium was removed, and the cells were treated with corresponding stimuli. Cells were incubated for 48 h, and then collected for subsequent experiments. Predesigned and validated small interfering RNAs (siRNAs) specific for SIRT1 (sense: CAUCUUGCCUGAUUUGUAATT; antisense: UUACAAAUCAGGCAAGAUGTT), PGC-1α (sense: CCAAGACUCUAGACAACUATT; antisense: UAGUUGUCUAGAGUCUUGGTT), and NC were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Transfection was performed using Lipofectamine 2000 according to the manufacturer’s instructions. Transfection and intervention were similar to the experiments described in the previous phase. Each experiment was carried out at least in triplicate. ## 4.4. WB Assay Cell total protein was extracted using RIPA lysis buffer (APPLYGEN) supplemented with a protease inhibitor and phosphatase inhibitor (GLPBIO). The protein concentration was quantified by the bicinchoninic acid protein assay kit (TransGen Biotech, Beijing, China). Equal amounts of protein samples were separated by sodium dodecyl sulfate/polyacrylamide gel electrophoresis and then transferred to polyvinylidene difluoride membranes (Millipore, Burlington, MA, USA). After sealing with $5\%$ nonfat dry milk in phosphate-buffered saline (PBS) with Tween 20 (PBST) for 60 min, the membrane was incubated with the primary antibodies anti-Beclin1 (1:1000), anti-Lc3B (1:2000), anti-Pink1 (1:800), anti-Tom20 (1:10,000), anti-PGC-1α (1:10,000), anti-Podocin (1:600), anti-P62 (1:40,000), anti-Parkin (1:2000), anti-Desmin (1:50,000), anti-SIRT1 (1:1000), and TFAM (1:1000) overnight at 4 °C. The membrane was washed three times with PBST and incubated with the horseradish peroxidase-conjugated secondary antibody for 2 h at room temperature to combine with the primary antibodies. Finally, images of the target protein were developed and collected using a gel imaging system (Bio-Rad, Hercules, CA, USA). Protein bands were visualized by enhanced chemiluminescent (TIANGEN Biotech, Beijing, China) detection reagents. The expressions were quantified by ImageJ software. To eliminate deviations, each assay was repeated at least three times. ## 4.5. RT-PCR Total RNA was isolated from the cell lines using a TRIzol reagent (TransGen Biotech) and reverse-transcribed into cDNA with an EasyScript® One-Step gDNA Removal and cDNA Synthesis SuperMix (TransGen Biotech) according to the manufacturer’s instructions. RT-PCR was performed using the QuantiNova™ SYBR Green PCR (QIAGEN, Hilden, Germany). All primers were designed and synthesized by Generay Biotech Co., Ltd. (Shanghai, China) and are listed in Table S2. The relative mRNA expression was quantified using the 2−ΔΔCT method. β-actin was used for normalization. Three independent experiments were performed for each sample. ## 4.6. Immunofluorescence Cells were washed in PBS, fixed with $4\%$ paraformaldehyde for 20 min, made permeable with $0.1\%$ Triton X in PBS for 5 min, and sealed with $3\%$ bovine serum albumin in PBS for 30 min. Subsequently, primary antibody was added overnight at 4 °C, and secondary antibody was added at room temperature for 30 min in darkness. DAPI was incubated for 5 min and then washed with PBS. Finally, we observed the cells under a confocal laser scanning microscope and quantified the results using ImageJ v1.8.0 The average integrated optical density value was used to represent the protein expression. ## 4.7. ΔΨm, ATP Content, and ROS Determination ΔΨm and ROS were detected using the JC-1 assay kit (Beyotime Biotechnology, Beijing, China) and ROS assay kit (Beyotime Biotechnology), respectively, and then analyzed by flow cytometry. The production of ATP was measured using an ATP assay kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, Jiangsu, China) according to the manufacturer’s instructions. ## 4.8. Transmission Electron Microscopy Cells were washed in PBS and fixed with $2.5\%$ glutaraldehyde for eight hours. After fixation, cells were rinsed three times with 0.1 M phosphate buffer (pH 7.4) for 15 min each and fixed with $1\%$ osmium acid and 0.1 M phosphate buffer for two hours at room temperature. Then, cells were observed with an electron microscope after dehydration, permeabilization, embedding, sectioning, and staining. ## 4.9. Experimental Animals Six-week-old male Sprague–Dawley rats (specific pathogen-free grade), 160–180 g, purchased from Hunan SJA Laboratory Animal Co., Ltd. (Changsha, Hunan, China) were injected intraperitoneally with normal saline (control, $$n = 6$$) or STZ (60 mg/kg body weight). Seventy-two hours after the STZ injection, tail vein blood glucose levels were detected. If the random blood glucose level was higher than 16.7 mmol/L for three consecutive tests, the diabetes model was considered to be successful. Eight weeks after STZ injection, the rats were randomly divided into the following two groups: DKD model group ($$n = 10$$) and P-MSCs treatment group (tail vein injection, 1 × 106 in 2 mL PBS, per rat, $$n = 10$$). The animal license number is SYXK (Gan) 2021-0003. ## 4.10. Immunohistochemistry After dewaxing, rehydration, antigen retrieval, inactivating endogenous peroxidase activity, and blocking, the renal tissue sections were incubated with various primary antibodies: anti-Beclin1 (11306-1-AP, Proteintech), anti-P62 (bs-2951R, Bioss, Woburn, MA, UA), anti-Desmin (ab32362, Abcam), anti-SIRT1 (ab189494, Abcam), anti-PGC-1α (sc-518025, Santa Cruz Biotechnology), and anti-TFAM (AF0531, Affinity Biosciences) at 4 °C overnight. The sections were then incubated with secondary antibody for 30 min after washing with PBS for three times. Diaminobenzidine was used as the chromogen. Finally, sections were stained with hematoxylin and examined using a microscope. ## 4.11. Statistical Analysis All data collected in our experiments are expressed as means ± standard deviation. Student’s t test was used to compare two groups. Three or more groups were compared using one-way analysis of variance. p values < 0.05 were considered to be statistically significant. ## 5. Conclusions This is the first study to investigate whether P-MSCs ameliorate podocyte injury and PINK1/Parkin-mediated mitophagy inhibition, and we found for the first time that P-MSCs play a therapeutic role via the SIRT1-PGC-1α-TFAM signaling pathway. We propose that enhancing PINK1/Parkin-mediated mitophagy and the expression of SIRT1, PGC-1α, and TFAM in podocytes may be a novel strategy for the treatment of DKD. ## References 1. Lin Y.C., Chang Y.H., Yang S.Y., Wu K.D., Chu T.S.. **Update of pathophysiology and management of diabetic kidney disease**. *J. 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--- title: Aphanizomenon flos-aquae (AFA) Extract Prevents Neurodegeneration in the HFD Mouse Model by Modulating Astrocytes and Microglia Activation authors: - Giacoma Galizzi - Irene Deidda - Antonella Amato - Pasquale Calvi - Simona Terzo - Luca Caruana - Stefano Scoglio - Flavia Mulè - Marta Di Carlo journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003388 doi: 10.3390/ijms24054731 license: CC BY 4.0 --- # Aphanizomenon flos-aquae (AFA) Extract Prevents Neurodegeneration in the HFD Mouse Model by Modulating Astrocytes and Microglia Activation ## Abstract Obesity and related metabolic dysfunctions are associated with neurodegenerative diseases, such as Alzheimer’s disease. Aphanizomenon flos-aquae (AFA) is a cyanobacterium considered a suitable supplement for its nutritional profile and beneficial properties. The potential neuroprotective effect of an AFA extract, commercialized as KlamExtra®, including the two AFA extracts Klamin® and AphaMax®, in High-Fat Diet (HFD)-fed mice was explored. Three groups of mice were provided with a standard diet (Lean), HFD or HFD supplemented with AFA extract (HFD + AFA) for 28 weeks. Metabolic parameters, brain insulin resistance, expression of apoptosis biomarkers, modulation of astrocytes and microglia activation markers, and Aβ deposition were analyzed and compared in the brains of different groups. AFA extract treatment attenuated HFD-induced neurodegeneration by reducing insulin resistance and loss of neurons. AFA supplementation improved the expression of synaptic proteins and reduced the HFD-induced astrocytes and microglia activation, and Aβ plaques accumulation. Together, these outcomes indicate that regular intake of AFA extract could benefit the metabolic and neuronal dysfunction caused by HFD, decreasing neuroinflammation and promoting Aβ plaques clearance. ## 1. Introduction The increase in lifespan leads to a growth in the incidence of age-related diseases, including neurodegenerative diseases. These disorders significantly impact the quality of life of patients and their caregivers and relatives, becoming a social and economic burden. However, aging is not the only risk factor for neurodegenerative diseases onset. Increasing evidence in humans and animals has shown a robust correlation between obesity and the development of neurodegenerative diseases, such as Alzheimer’s disease (AD) [1,2]. This pathology is characterized by progressive cognitive and memory loss that ultimately ends in dementia [3]. At the root of this condition is the widespread loss of neurons and their synapses in the particular brain area known as the hippocampus and entorhinal cortex. AD histopathological hallmarks are the so-called senile plaques, and neurofibrillary tangles obtained, respectively, by deposition of the aggregated β amyloid peptide (Aβ) and hyperphosphorylated Tau protein [4]. Metabolic changes caused by overweight and unhealthy lifestyle habits are associated with central nervous system (CNS) dysfunction, leading to neuronal death and alteration of synaptic plasticity that impairs memory ability. Intake of foods rich in fats and sugars and poor in vitamins and minerals are major risk factors for obesity and associated neurodegeneration [5,6]. The standard biological and molecular mechanisms involved in obesity and neurodegenerative diseases include insulin resistance, inflammatory cytokines activation, oxidative stress generation, mitochondrial dysfunction, and cell death. Brain insulin resistance is when brain cells fail to respond to insulin [5,7]. In AD and related disorders, insulin resistance is due to impaired insulin signaling, so AD is denominated as brain diabetes or “Type 3 Diabetes” [8,9]. In addition, central insulin resistance induces mitochondrial alterations, such as mitophagy, mitochondrial quality control, mitochondrial dysfunction, and apoptosis [10]. In agreement with these outcomes, High-Fat Diet (HFD) consumption causes cognitive impairments, reduces synaptic plasticity, induces neuroinflammation, and changes mitochondrial function and astrocytes activation [11,12]. However, the involved mechanisms are not well clarified, and several studies seek discoveries regarding their pathophysiology and prevention. Since an unhealthy diet is the cause of metabolic dysfunctions and the development and progression of associated comorbidity, nutrition rich in antioxidant and anti-inflammatory compounds could help to reduce the risk of metabolic diseases, such as obesity or Type 2 Diabetes (T2D), and protect from related neurodegenerative disorders. The beneficial effect of antioxidant phytochemicals, as components of functional foods or used in supplementation, on obesity, neurodegeneration, and related comorbidity has been demonstrated in in vitro and in vivo model systems [13,14,15,16,17,18]. Recent data showed that the daily consumption of pistachios and honey could increase obesity-related dysmetabolic conditions, such as T2D, adiposity, and neurodegeneration in an animal model of diet-induced obesity [19,20,21,22,23,24,25,26]. Among supplements with potent antioxidant and anti-inflammatory effects, the extracts of blue-green algae play a relevant role. Spirulina, for example, contains numerous bioactive molecules, including beta-carotene, phycocyanin, tocopherols, micronutrients, fatty acids, and phenolic compounds [27]. It possesses antioxidant and anti-inflammatory properties and lipid-lowering ability. Further, its benefits on obesity and neurodegeneration can be extended to antiviral, anticancer, antidiabetic, hepatoprotective, and cardioprotective properties [27]. Recently, a growing interest has existed in the Aphanizomenon flos-aquae (AFA), another blue-green alga. AFA is a cyanobacterial unicellular organism endowed with several health-enhancing properties and spontaneously grows in Upper Klamath Lake (southern Oregon, USA). AFA contains all the vitamins; it is the only living food with 72 minerals; and it has the most comprehensive spectrum of carotenes, such as beta-carotene, xanthophyll, and an unusually high concentration of chlorophyll [28,29]. Among its bioactive molecules, particularly relevant are phenylethylamine, an important neuromodulator, and a particular type of AFA phycocyanin, also composed of phycoerythrocyanin, with very high antioxidant, anti-inflammatory and antiproliferative properties, that are reinforced by the further presence of mycosporine-like amino acids (MAAs) and various polyphenols [30,31,32,33]. Further, it has been reported that the AFA extract Klamin® which concentrates phenylethylamine, can influence mood, reduce anxiety, and enhance attention and learning, suggesting that it could have a role in clinical brain areas [34,35]. An in vitro study on neuronal cells stimulated with Aβ demonstrated that the AFA extract Klamin® plays a protective role in neurodegenerative processes, such as oxidative stress generation, inflammation, and formation of amyloid plaques [36]. Further, the possibility of using the AFA extract to develop functional food for the health and wellness market has been evaluated. Another study considered employing the AFA extract as an additive in biscuit dough, demonstrating that AFA antioxidant properties are also maintained after exposure to high temperatures [37]. Moreover, cellular molecules and mechanism that joins dysmetabolism and obesity-related neurodegeneration have yet to be thoroughly explored. Neuroinflammation is closely related to the pathogenesis of AD and obesity/T2D [38]. In the brain, astrocytes and microglia cells maintain homeostasis and support many functions of neurons. Moreover, they play an essential role in the inflammatory process of neurodegenerative diseases [39]. Recently a new AFA product reached the market, KlamExtra®, which combines the Klamin® extract (EU patent n° 2046354), which has more specific neuromodulatory and immunomodulatory properties, with the AphaMax® extract (EU patent n° 2032122), which concentrates the AFA-phycocyanins and, so, has increased antioxidant and anti-inflammatory properties. Here, we aimed to study the effect of KlamExtra® on the molecular mechanisms involved in neurodegeneration induced by obesity. Further, by using glial fibrillary acid protein (GFAP) and soluble triggering receptors expressed on myeloid cells-2 (sTREM-2) as biomarkers, we explored the possibility that AFA can mitigate the central inflammatory process induced by the HFD diet by modulating astrocytes and microglia activation. A possible protective response of AFA in reducing Aβ deposits was also explored. From now on, we shall define KlamExtra® as AFA. ## 2.1. AFA and Metabolic Parameters The effects of the AFA assumption on animal body weight, food intake, and circulating lipids are illustrated in Figure 1. HFD animals gradually and more rapidly enhanced throughout the twenty-eighth week compared with the Lean group. In AFA-fed mice, the body weight gain was lower than in HFD mice (Figure 1A). At the end of the experimental protocol, the body weight mean values were 34.74 ± 2.14 g for Lean mice, 50.85 ± 1.00 g for HFD animals, and 46.00 ± 2.20 g for the HFD supplemented with AFA groups (Figure 1B). Food intake was approximately similar between the HFD and HFD + AFA groups, but it was significantly different from the Lean group (Figure 1C). Plasma Triglycerides (TG) and Cholesterol (Chol) levels were higher in HFD mice compared with the Lean group or the HFD + AFA group (Figure 1D). To investigate the effects of AFA on glucose homeostasis, we measured the fasting plasma glucose and performed intraperitoneal glucose and insulin tolerance tests. Interestingly, in the AFA-supplemented HFD group, fasting blood glucose concentration (128.3 ± 6.23 mg/dL) was lower than in the HFD group (153 ± 11.78 mg/dL), and there was no statistically significant difference between Lean animals (122 ± 3 mg/dL) and the HFD + AFA group (Figure 2A). Figure 2B represents the blood glucose concentrations over 2h after i.p. glucose injection in different mice. The glucose tolerance curve and the related AUC in HFD were significantly higher compared with Lean mice (Figure 2B,C), indicating an impairment of glucose tolerance. The curve and AUC in HFD + AFA were considerably lower than in HFD, suggesting a beneficial effect on glucose homeostasis. During the insulin tolerance test, HFD mice displayed higher blood glucose concentration than Lean mice (Figure 2D,E), suggesting impaired insulin sensitivity. In HFD + AFA mice, we found lower glycemic values and decreased AUC after insulin injection, suggesting an improved insulin sensitivity (Figure 2D,E). Insulin concentrations were significantly higher in HFD in comparison with Lean and HFD + AFA mice (Figure 2F). In addition, HOMA-IR was slightly ameliorated in HFD + AFA mice (Figure 2G). These results indicate that AFA chronic ingestion improves insulin resistance and glucose intolerance in HFD mice. ## 2.2. AFA Improves Brain Insulin Resistance in HFD Mice A reduction of insulin receptor expression and impairment of insulin signaling characterizes insulin resistance. In the brain, insulin resistance has been associated with neurodegenerative disorders [2]. In HFD-fed mice, phosphorylated brain insulin receptor (p-IR) protein expression was decreased compared with the control group, suggesting that cerebral insulin resistance is diet-induced. In contrast, the HFD + AFA group showed a level of expression of p-IR similar to the Lean group (Figure 3A,B). Furthermore, we analyzed the expression of proteins involved in insulin signaling in the brain. Decreased levels of posho-Akt were found in HFD mice compared with the Lean group (Figure 3A,B). In contrast, HFD + AFA-fed mice showed higher levels of phospho-AKT, suggesting that AFA extract ingestion can counteract HFD-induced brain insulin resistance (Figure 3A,B). ## 2.3. AFA Consumption Induces Neuroprotection The effect of the different diets on brain morphology was analyzed by staining with Hematoxylin–Eosin. Histopathological analysis showed, in the cortex of the HFD group, damaged/disorganized neurons and the presence of numerous pyknotic cells. Further, a robust vacuolization in other brain cortical layers was observed. In contrast, in the HFD + AFA group, neuronal morphology was comparable to the Lean controls, except for certain pyknotic cells (Figure 4A). Further, a clear-cut result regarding the protective role of AFA extract on neurons was obtained by TUNEL assay. A significantly increased number of fragmented nuclei were detected in the cerebral cortex of the HFD group compared with the Lean and HFD + AFA mice, suggesting that AFA extract consumption can attenuate the degenerative neuronal process induced by the HFD diet (Figure 4B,C). Furthermore, synaptic loss is present in obesity-related neurodegeneration [40]. The presynaptic protein synaptophysin and the postsynaptic protein PSD95 were downregulated in the HFD-fed mice compared with the Lean group. In contrast, HFD + AFA-fed mice exhibited a significant increase in synaptophysin. Although it does not reach significance, a trend towards an increase in PSD95 levels has been observed, suggesting a beneficial effect of AFA extract on synaptic transmission (Figure 4D,E). ## 2.4. AFA Reduces Aβ Accumulation We also examined the levels of expression of BACE1 and PSN1, two enzymes involved in processing APP and Aβ production [41]. Although not significant, BACE1 expression shows an upward trend in the HFD compared with the HFD + AFA group (Figure 5A,B). Furthermore, in the HFD brain, PS1 expression levels showed an increase in both the whole protein (Holo) and the proteolytic fragments NTF and CTF. In the HFD + AFA group, the NTF fragment was reduced (Figure 5A,B). Further, we investigated neuronal APP-Aβ presence in the brain of different animal groups. Aβ immunoreactivity was reduced in the Lean and HFD + AFA groups compared with the HFD mice. In addition, in the Lean and HFD + AFA groups, we observed diffuse staining around the nuclei, indicating accumulation of intraneural Aβ. In contrast, in HFD mice, an APP punctate staining around the neurons was found, suggesting an increase in APP processing and Aβ aggregation (Figure 5C). Furthermore, this result was validated by staining with Thioflavin T (Figure 5D), a dye used to visualize the presence of β-sheet protein aggregates or amyloid plaques, whose existence was detected mainly in HFD mice. ## 2.5. AFA Counteracts Neuroinflammation Peripheral inflammation triggered by obesity is associated with neuroinflammation [5]. Increased expression of TNF-α (Figure 6A) and decreased expression of IL-10 (Figure 6D) were detected in the brain of HFD-fed mice as compared with the Lean group, indicating activation of the inflammatory response. In contrast, in the HFD + AFA group, an expression level similar to that of the Lean mice was found for IL-10 (Figure 6D). Further, we analyzed the expression of GFAP, a biomarker for the activation of astrocytes [42]. The increase of GFAP expression observed in the HFD group with respect to the lean group was significantly counteracted by AFA consumption (Figure 6A). Accordingly, immunofluorescence analysis showed an increase in GFAP intensity mainly in the hippocampus (Figure 6C) of HFD-fed mice compared with the Lean group. In addition, a significant reduction of fluorescent intensity in the brain of HFD + AFA-fed mice indicate that the increase of astrocytes in response to HFD can be counteracted by adding an AFA supplement to the food (Figure 6A–C). Further, we analyzed the expression levels of TREM2, a receptor expressed mainly on microglia and modulated in obesity-induced insulin resistance [43], a condition in which TREM2 exerts anti-inflammatory and neuroprotective effects. Consistent with the IL-10 result, TREM2 decreased in the brains of the HFD group. In contrast, higher levels of this protein were detected in HFD + AFA-fed mice brains (Figure 6D). We also observed higher TREM2 immunoreactivity especially in the cortex of the Lean and HFD + AFA mice than the HFD group, suggesting a protective effect on microglial cell viability (Figure 6E). All these results indicate that the bioactive molecules contained in AFA extract can have an impact on multiple mechanisms of the neuro-inflammation process and promote the healthy neuronal homeostasis. ## 2.6. AFA Modulates Astrocytes and Microglia Activation and Aβ Deposition Hippocampus brain sections of Lean, HFD, and HFD + AFA-fed mice were used for GFAP and Aβ staining. Analysis of GFAP immunoreactivity astrocytes increase in response to the HFD diet and the presence of Aβ deposition that was attenuated in HFD + AFA-fed mice (Figure 7A,B). We also examined the presence of TREM2 and Aβ accumulation in the cortex of the different groups. TREM2 reduction observed in HFD-fed mice affected the clustering of microglia around the Aβ deposits, which was improved by AFA supplementation (Figure 7C,D). ## 3. Discussion Growing evidence indicates how unhealthy nutrition can be considered a potential cause of metabolic-related disease and disorders of the central nervous system (CNS). A correct lifestyle and constant physical exercise can prevent these pathologies, and nutritional supplements can help with this. Here, we explored the impact of the two AFA extracts (KlamExtra®) intake in the brain of obese mice. We applied an HFD feeding protocol to induce obesity and neurodegeneration in mice. We observed the preventive action of AFA extract as a dietary supplement in reducing brain metabolic and molecular impairment. AFA bioactive molecules have the chemical characteristics to cross the BBB, and its dietary consumption can be seen as a way to compensate for the loss of efficacy of the endogenous defenses [44]. A slight but significant reduction in body weight after regular food intake of KlamExtra® was observed in comparison with the obese control group. A considerable reduction of plasma triglyceride levels was also observed in the obese group supplemented with AFA. A high amount of dietary fiber and anti-obesity active compounds, including carotenoids, could account for the positive effect of these algae. Analysis of metabolic parameters showed that HFD fasting glycemia, insulin concentration, and HOMA index were more elevated than in Lean mice, indicating an impairment of glucose metabolism and insulin resistance condition, which was lightly improved by AFA consumption. Thus, the effects of regular AFA extract intake can be assigned to beneficial actions on glucose metabolism. In line with previous results and in accordance with metabolic data, we demonstrated that brain dysfunction in long-term HFD-fed mice is associated with peripheral and central insulin resistance [2]. Brain insulin resistance in HFD-fed mice at molecular levels was confirmed by the reduced expression of insulin receptors and molecules involved in insulin signaling, such as Akt/p-Akt. In contrast, a supplement of AFA extract counteracted insulin sensitivity and insulin signaling impairment. It has been widely reported that HFD consumption causes increased neuroinflammation and neuron loss [45]. AFA seems to reduce the neuroinflammatory profile modulating the expression of cytokines and activating astrocytes and microglia through the action of GFAP and TREM2 proteins. An increase of TREM2 and a decrease of GFAP expression in the AFA group suggest a protective reaction to the damage of brain homeostasis induced in the HFD model. In addition, our results could indicate that AFA protects from Aβ injury produced by the HFD diet by promoting microglial clearance. AFA consumption mitigated degeneration and loss of neurons induced by the HFD diet, as demonstrated by histopathological analysis and TUNEL assay. Further, in the HFD group, loss of neurons was associated with loss of synapses, as suggested by the reduced expression of PSD95 and synaptophysin that was prevented by AFA addition, signifying a beneficial effect of the supplement on neurons’ health and communication. Consistent with this result, we found that specific proteins related to APP processing, including BACE1 and PSN1, were up-regulated in the brain of HFD-fed mice. In contrast, although not significant, their expression level was reduced in HFD + AFA mice. The increased presence of these proteins is associated mainly with the augmented production of Aβ. This complies with the accumulation of extracellular insoluble Aβ fibrillar aggregates and amyloid plaques found in the cerebral cortex of HFD brain sections and evidenced by ThT staining. In contrast, Aβ intracellular presence in the HFD + AFA group suggested that AFA could exert a neuroprotective role by interfering with APP processing and Aβ aggregation. GFAP is an astrocyte protein overexpressed after a neurological insult known as astrogliosis [46,47]. The astroglial reaction has been observed in a different case in which memory performance is weakened [48]. We found an increase of GFAP and astrocytes in response to hypercaloric feeding suggesting a neuroinflammatory state and the occurrence of astrogliosis that was prevented by AFA supplementation. It has been reported that unhealthy nutrients and metabolites in an HFD diet can impact brain function by crossing the blood–brain barrier (BBB), interacting with neurons and triggering glia [49]. AFA extract intake could reduce or eliminate metabolites peripherally generated by the HFD diet which, no longer being transported to the brain, elude astrogliosis. In addition, our results agree with the finding that growth factors and cytokines, such as IL-1, IL-6, TNF-α, and reactive oxygen species are among the main signaling molecules that can regulate astrogliosis [46,47]. Several studies have demonstrated that TREM2 protects against neurodegeneration by controlling neuroinflammation closely related to the pathogenesis of AD and obesity [50]. Overexpression of TREM2 was reported to upregulate synaptic proteins synaptophysin and PSD95, improving synaptic transmission in long-term HFD-fed mice, whose loss is related to memory and learning impairment [51]. Similarly, supplementation of AFA to HFD upregulates TREM2 and synaptic proteins, suggesting that it supports neuron metabolism and synapses. While astrocytes have been assigned the role of filling tissue voids caused by degenerative events, microglia, the brain’s immune cells, function as brain phagocytes responsible for removing debris from degenerating neurons and Aβ deposit that interferes with neuron communication [52]. Further, it was also demonstrated that TREM2 is essential for promoting microglial clustering around fibrillar Aβ plaques in AD mouse models and postmortem human brain sections [53]. Its deletion induces a reduction in plaque-associated microglia [53,54]. In addition, during AD development, homeostatic microglia respond to Aβ accumulation evolving into disease-associated microglia (DAM) [55]. This is consistent with the immunofluorescence results in which, in the AFA group, an increase of TREM2 is associated with a reduction of the formation of Aβ deposits. Further, the data examined here indicate that TREM-2 regulates microglia activation in response to dietary factors. Recently, a study on patients affected by neurogenerative diseases has evidenced altered levels of GFAP and TREM-2 in CSF, suggesting that they could be used as biomarkers of central inflammation and have been proposed as prognostic tools of neurodegenerative progression [56]. However, we cannot exclude that the improved metabolic conditions and the restored homeostasis observed in the brain of the HFD + AFA group might have slowed down the APP processing and Aβ deposition, favoring the microglia response. In conclusion, our results suggest that KlamExtra®, a natural product, works as a “functional food” to activate a compensatory mechanism mainly for mitigating HFD-induced systemic and central dysmetabolism. AFA extract can alleviate central neuroinflammation HFD- induced by regulating astroglial and microglial activation and modulating anti-inflammatory cytokines. These outcomes associated with increased synaptic protein expression and Aβ plaques removal suggest that AFA extract could have promising protective activity on neurodegenerative diseases. However, additional investigations are necessary to confirm our findings. ## 4.1. Animals and Diets All animals received care in compliance with the recommendations of the European Economic Community ($\frac{2010}{63}$/UE) and the guidelines for animal experimentation (Italian D.L. No. $\frac{26}{2014}$ and subsequent variations). The Ministry of Health authorized the experimental protocol (Rome, Italy; Authorization Number $\frac{46}{2020}$-PR, date of approval: 21 January 2020). KlamExtra® includes the two AFA extracts Klamin® and AphaMax® whose composition was previously described in EU patents n° 2046354and 2032122 and by Nuzzo et al. [ 36]. Four-weeks-old male C57BL/6J mice were purchased from Harlan Laboratories (San Pietro al Natisone, Udine, Italy). As described in previous papers [22,23], after a 1-week habituation period, the animals were weighed and divided into separated three groups: (A) Lean group (Lean, $$n = 8$$) fed a standard diet consisting of $70\%$ of energy as carbohydrate, $20\%$ proteins and $10\%$ fat (code 4RF25, Mucedola, Milan, Italy); (B) High-Fat Diet group (HFD, $$n = 8$$) fed HFD (PF4215, Mucedola, Milan, Italy) that supplied $60\%$ of energy as fat, $20\%$ proteins and $20\%$ carbohydrates; (C) mice fed a HFD supplemented with KlamExtra® (HFD-AFA, $$n = 8$$) for 28 weeks. HFD-AFA was custom designed and prepared by Mucedola S.r.l (4RF25), obtained by adding 8.3 g of KlamExtra/Kg HFD. All animals (two animals per cage) were maintained under a 12 h dark–light cycle at 23 ± 1 °C and $55\%$ ± $5\%$ humidity, with free access to food and water ad libitum. Bodyweight and food intake were detected weekly throughout the study. At the end of the study period, metabolic parameters were analyzed, then the animals were sacrificed by cervical dislocation. Blood was immediately drawn by cardiac puncture, and plasma was recovered after centrifugation at 3000 rpm at 4 °C for 15 min and stored at −80 °C until analysis. The aorta was cannulated and perfused with Dulbecco’s buffered solution containing 2 mM EDTA, and the right atrial incision allowed blood outflow. Brains were explanted, weighed, and processed for subsequent analysis. AFA (0.9 mg/mouse) was administered daily for 28 weeks. The doses given to the Diet-Induced Obese (DIO) mice were extrapolated from the human dosage (1.6 g/day) and calculated on the basis of the average body weight (40 mg) [22]. ## 4.2. Metabolic Parameters Plasma triglyceride and total cholesterol were measured using the ILAB 600 Analyzer (Instrumentation Laboratory, Bedford, MA, USA). Fasting blood glucose concentrations were determined by a glucometer (GlucoMen LX meter, Menarini, Florence, Italy). Intraperitoneal glucose tolerance test (IPGTT) and insulin tolerance test (ITT) were carried out in overnight-fasting mice. For IPGTT, mice were injected intraperitoneally (i.p.) with glucose (2 g/kg b.w.) ( D-glucose, Sigma-Aldrich, Milan, Italy) in $0.9\%$ saline. For ITT, mice were injected i.p. with insulin (0.5 U/kg b.w.) ( Insuman Rapid, Sanofi Aventis, Italy) in $0.9\%$ saline. Tail-vein-measured glucose concentrations were taken at different time points (0, 15, 30, 60, and 120 min). Plasma insulin was quantified using a mouse ELISA kit (Alpco diagnostics, Salem, NH, USA) according to the manufacturer’s instructions, and the HOMA-IR, index of insulin resistance, was calculated as the ratio of fasting insulin (ng/mL) and fasting glucose (mg/dL) divided by the constant 22.5. ## 4.3. Total Protein Extraction and Western Blot Brain tissue from Lean, HFD and HFD + AFA mice was homogenized in RIPA buffer (20 mM Tris-HCl pH 7.4, 150 mM NaCl, 1 mM Na3VO4, 10 mM NaF, 1mM EDTA, 1 mM EGTA, 0.2 mM phenylmethylsulfonyl fluoride, $1\%$ Triton, $0.1\%$ SDS, and $0.5\%$ deoxycholate) with protease inhibitor (Amersham, Life Science, Les Ulis, France) and phosphatase inhibitor cocktail (Sigma-Aldrich, Poole, Dorset, UK). The samples were sonicated and centrifuged for 30 min at 14,000 rpm at 4 °C to remove insoluble material, and the supernatants were quantified by the Bradford method (Bio-Rad) and collected. Proteins (50 μg) were separated by $10\%$ or $12\%$ acrylamide gel and were transferred onto a nitrocellulose filter. The filter was incubated with the anti-insulin receptor (IR) (1:1000, Invitrogen, Waltham, MA, USA), anti-phospho insulin receptor (p-IR) (1:1000, Invitrogen, Waltham, MA, USA), anti-protein kinase B (Akt) (1:1000, Cell Signaling Technology, Danvers, MA, USA), anti-phospho protein kinase B (p-Akt) (1:1000, Cell Signaling Technology, Danvers, MA, USA), anti-presenilin1 (PSN1) (1:200, Santa Cruz Biotechnology, Santa Cruz, CA, USA), anti-beta secretase enzyme 1 (BACE1) (1:500, Cell Signaling Technology, Danvers, MA, USA), anti-postsynaptic density protein 95 (PSD-95) (1:1000, Santa Cruz Biotechnology, Santa Cruz, CA, USA), anti-synaptophysin (1:1000, Santa Cruz Biotechnology, Santa Cruz, CA, USA), anti-tumor necrosis factor α (TNFα) (1:500, Thermo Fisher, Preprotech, Waltham, MA, USA), anti-glial fibrillary acidic protein (GFAP) (1:1000, Cell Signaling Technology Danvers, MA, USA), anti-interleukin 10 (IL-10) (1:500, Santa Cruz Biotechnology, Santa Cruz, CA, USA), an anti-triggering receptor expressed on myeloid cells 2 (TREM2) (1:1000, Invitrogen, Waltham, MA, USA), and anti-β-actin (β-Actin; 1:10,000, Sigma-Aldrich, St. Luois, MO, USA). Primary antibodies were detected using the Odyssey® scanner (Li-cor), according to the manufacturer’s instructions, using secondary antibodies (anti-mouse and anti-rabbit) labeled with IR790 and IR680 (1:10,000; Life Technology, Carlsbad, CA, USA). Band intensities were analyzed with ImageJ software, and expression was adjusted to β-Actin expression. The protein levels were expressed as intensity relative to the control. ## 4.4. Histopathology and Immunohistochemistry For histopathological and immunohistochemical analyses, whole-brain specimens/samples were collected and fixed in $4\%$ paraformaldehyde in 0.1 M PBS (pH 7.4) overnight at 4 °C and then transferred into dehydrated in graded ethanol and paraffin-embedded. Serial sagittal sections (5μ thick) were deparaffinized in xylene, rehydrated with a graded series of ethanol, and then processed for routine hematoxylin and eosin (HE) used according to the manufacturer’s instructions. For immunofluorescence assays, sections were treated in 10 mM citrate buffer (pH 6.0) with microwaves for 6 min at 500 W for antigen retrieval. Then, cells were blocked with $10\%$ normal goat (NGS) serum in PBS for 1 h at room temperature (RT) and were incubated at 4 °C overnight with anti-GFAP (1:200), anti-TREM2 (1:200), and anti-Aβ (1:100) primary antibodies ($3\%$ NGS in PBS and 0,$3\%$ Triton X-100, PBS-T). Immunopositive reactions were detected by incubation with the anti-rabbit Alexa 488 or anti-mouse Alexa 555 (1:500; Cell Signaling Technology) secondary antibodies ($2\%$ NGS in PBS) for 2 h at RT. Finally, all sections were coverslipped using Sigma mounting medium, including 4,6-diamidino-2-phenylindole (DAPI; Vector Laboratories), and visualized with Axioskop-2 Zeiss or Leica DM4000 microscope. All photomicrographs were collected using the same magnification (10×, 20×, or 40× objectives), exposure time, and other parameters, and the representative images from five sections for each brain specimen were edited with Adobe Photoshop software. Negative controls were performed for every set of experiments by omitting the primary antibodies. For quantitative analysis, the images were imported into the ImageJ software program (NIH, Bethesda, MD), converted to grayscale, and the total area of immunoreactivity was quantified by measuring the mean intensity of all stained areas of each micrograph, and the data were expressed as mean density. ## 4.5. Thioflavin T Staining Following deparaffinization with xylene and ethanol, tissue sections were incubated in 70 μM of Thioflavin T (ThT, Sigma-Aldrich, St. Louis, MO, USA) for 10 min at RT. Sections were then rinsed in $70\%$ ethanol. After washing in deionized water, the slides were mounted in aqueous mounting media. The images were visualized by a Leica DM4000 microscope at 10× magnification. The number and area of plaques detected by ThT were quantified using Image J software. ## 4.6. TUNEL Assay In situ detection of DNA fragmentation was performed using the DeadEnd™ Fluorometric TUNEL Detection System kit (Promega, Madison, WI, USA), following the manufacturer’s instructions. Pre-incubating sections performed positive controls with DNase I for 10 min at room temperature, and negative controls by omitting the TdT enzyme. Nuclei were stained with DAPI (Vector Lab, Burlingame, CA, USA), and the slides were analyzed using a fluorescent microscope (Leica Microsystems) at a magnification of 20X. TUNEL-positive cells were quantified and results were expressed as mean ± SEM values of three different experiments. ## 4.7. Statistical Analysis The results are presented as the mean ± the standard error of the mean (SEM). The letter ‘n’ indicates the number of animals. 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--- title: Proteotranscriptomic Discrimination of Tumor and Normal Tissues in Renal Cell Carcinoma authors: - Áron Bartha - Zsuzsanna Darula - Gyöngyi Munkácsy - Éva Klement - Péter Nyirády - Balázs Győrffy journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003397 doi: 10.3390/ijms24054488 license: CC BY 4.0 --- # Proteotranscriptomic Discrimination of Tumor and Normal Tissues in Renal Cell Carcinoma ## Abstract Clear cell renal carcinoma is the most frequent type of kidney cancer, with an increasing incidence rate worldwide. In this research, we used a proteotranscriptomic approach to differentiate normal and tumor tissues in clear cell renal cell carcinoma (ccRCC). Using transcriptomic data of patients with malignant and paired normal tissue samples from gene array cohorts, we identified the top genes over-expressed in ccRCC. We collected surgically resected ccRCC specimens to further investigate the transcriptomic results on the proteome level. The differential protein abundance was evaluated using targeted mass spectrometry (MS). We assembled a database of 558 renal tissue samples from NCBI GEO and used these to uncover the top genes with higher expression in ccRCC. For protein level analysis 162 malignant and normal kidney tissue samples were acquired. The most consistently upregulated genes were IGFBP3, PLIN2, PLOD2, PFKP, VEGFA, and CCND1 ($p \leq 10$−5 for each gene). Mass spectrometry further validated the differential protein abundance of these genes (IGFBP3, $$p \leq 7.53$$ × 10−18; PLIN2, $$p \leq 3.9$$ × 10−39; PLOD2, $$p \leq 6.51$$ × 10−36; PFKP, $$p \leq 1.01$$ × 10−47; VEGFA, $$p \leq 1.40$$ × 10−22; CCND1, $$p \leq 1.04$$ × 10−24). We also identified those proteins which correlate with overall survival. Finally, a support vector machine-based classification algorithm using the protein-level data was set up. We used transcriptomic and proteomic data to identify a minimal panel of proteins highly specific for clear cell renal carcinoma tissues. The introduced gene panel could be used as a promising tool in the clinical setting. ## 1. Introduction Clear cell renal carcinoma (ccRCC) is the malignant transformation of epithelial cells of the kidney and is the most frequent form of kidney tumors with approx. $70\%$ of all kidney cancer cases [1]. In 2020, there were 431,288 new cases and 179,368 deaths from kidney and renal pelvis cancer worldwide [2]. Although the rate of new cases seems to rise, in the past decades, the mortality rates are stagnating in the US [3]. Risk factors of ccRCC include obesity, smoking, hypertension, older age, and male gender. Patients with a family history of ccRCC also have a higher risk of developing this disease [4]. Diagnosis of ccRCC is usually based on radiological imaging and tissue slide-based histopathological examination. Histopathological confirmation is essential before systematic therapy initiation. [ 4] Treatment of ccRCC can include surgery, percutaneous ablation [5], and targeted drugs including VEGF inhibitors [6] and mTOR inhibitors [7]. In the case of localized disease, surgical intervention is the first-line therapy, and depending on the size and stage, the intervention can range from partial to radical nephrectomy. If the tumor mass is relatively small, ablative techniques (such as cryo-, thermo-, or radio-ablation) are also available [5]. Patients with early-stage and lack of distant metastasis have more favorable survival rates than those with advanced disease [8]. Patients with advanced disease (stage IV) also require systemic therapy using mTOR inhibitors, VEGF inhibitors, or checkpoint inhibitors such as nivolumab, avelumab, pembrolizumab, ipilimumab, and interleukin 2 therapy [9]. MS was introduced almost half a century ago in endocrinology and toxicology for drug, steroid, and organic acid quantitation and got its main medical application in the widespread newborn screening [10,11]. Although the setup of MS-based diagnostic applications can be costly and complicated at the beginning, their versatility and reliability lead to new applications in clinical settings. In recent years, MS has been proven to be a comparatively cost-effective, precise, and quick analysis tool in microbial identification [12]. With the advent of proteomics and proteogenomics, MS-based techniques have an increasing role in cancer diagnostics, as well [13]. Uncovering a protein abundance-based panel specific to ccRCC could provide valuable support for the everyday clinical diagnostic and therapeutic decision-making process. Our study aimed to utilize large-scale transcriptomic studies to find genes showing higher expression in ccRCC. Then, by using our patient cohort with available proteomic and clinical data, we investigated the abundance of expressed proteins and the effect of these proteins on survival. By specifically focusing on markers with higher expression in tumor tissues, we aim to increase the specificity of our analysis to solidify future clinical application of the results. ## 2.1. Database Setup Altogether, we included 23 GEO series which contained 715 samples. Out of these 715 samples, 277 were from normal kidney tissues, and 438 were from ccRCC. Out of the entire gene array database, 414 samples were paired samples (207 pairs), and we used the paired specimens for the identification of differentially expressed genes. The entire analysis pipeline is summarized in Figure 1. Patient characteristics are listed in Table 1. ## 2.2. Genes Over-Expressed in ccRCC We uncovered significantly differentially expressed genes between paired ccRCC and adjacent normal tissues. IGFBP3 was found to be the most upregulated gene in tumor tissues (FC gene chip = 8.15, $$p \leq 5.88$$ × 10−32). The most significant genes include previously established molecular targets like VEGFA (FC gene chip = 3.02 $$p \leq 5.1$$ × 10−31) and CCND1 (FC gene chip = 4.12, $$p \leq 4.1$$ × 10−31). PLIN2 and PLOD2 also showed notable gene expression differences with FC values of 3.85 and 4.2 and adjusted p values of 3.09 × 10−31 and 5.24 × 10−32, respectively. The top differentially expressed genes are shown in Figure 2 and listed in detail in Supplementary Table S2. ## 2.3. Proteomic Analysis Proteomic analysis was performed using 162 normal and malignant tissue samples. Of the complete list of the 31 selected genes from gene chip results, we were able to successfully measure 22 in the targeted LC-MS/MS. Top differentially expressed genes include PLIN2 (FC = 26.01, $$p \leq 3.9$$ × 10−39), PLOD2 (FC = 15.83, $$p \leq 6.51$$ × 10−36), PFKP (FC = 12.78, $$p \leq 1.01$$ × 10−47), IGFBP3 (FC = 3.04, $$p \leq 7.53$$ × 10−18), CCND1(FC = 7.9, $$p \leq 1.04$$ × 10−24) and VEGFA (FC = 3.5, $$p \leq 1.4$$ × 10−22) shown in Figure 3. Differential analysis between male and female patients resulted in no significant differences. Regression analysis of age and protein expression showed a significant result only in the case of IGFBP2, however, the adjusted R-squared value was 0.064. Thus, we can conclude that neither age nor gender can be considered as a covariate factor. Further results are provided in the Supplementary Table S4. Using the clusterProfiler R package, we performed an enrichment analysis; mostly enriched GO terms are connected to migration and adhesion. Results of the enrichment analysis are presented in Figure 4 and Supplemental Figure S1. Detailed results of the protein expression changes are also presented in Table 2. Intensities of the 22 best protein-specific peptides are presented in Supplemental Figure S2. ## 2.4. Survival Analysis Using Proteome-Level Data To estimate the potential effects of protein expression on patient survival, we performed a survival analysis using all available proteins. Five out of the investigated proteins showed a correlation with survival. Patients with elevated expression of PLOD2 protein showed significantly worse overall survival compared to subjects with lower expression ($$p \leq 2.42$$ × 10−7, HR = 5.03). Overexpression of further proteins such as TIMP1 ($p \leq 3$ × 10−2, HR = 4.71), VIM ($p \leq 3$ × 10−2, HR = 2.49), LGALS1 ($p \leq 3$ × 10−2, HR = 2.47), and P4HA1 $p \leq 3$ × 10−2, HR = 2.6) also showed significant correlation with impaired overall survival. Kaplan–Meier curves of the best-performing proteins are shown in Figure 5; further results of survival analysis are presented in Supplemental Table S3 and as supplementary figures ## 2.5. Validation Using Data from CPTAC To further support our analysis, we validated our results using CPTAC data from the study of Clark et al. [ 14]. Out of the 22 proteins identified by our current study, 21 were also available in the CPTAC dataset. The FC values between the two MS analyses had comparable results. Correlation analysis of the log2FC values of the CPTAC and SE cohorts resulted in a significant correlation ($R = 0.91$, $$p \leq 3.7$$ × 10−9, Figure 6). Top proteins identified, such as PLIN2 (FC = 6.92, $$p \leq 1.7$$ × 10−33), PLOD2 (FC = 4.89, $$p \leq 7.4$$ × 10−33), PFKP (FC = 4.2, $$p \leq 4.3$$ × 10−56), IGFBP3 (FC = 2.28, $$p \leq 2.1$$ × 10−31), and VEGFA (FC = 3.12, $$p \leq 3$$ × 10−32), had significant differences between normal kidney and ccRCC in the CPTAC study. Further results are displayed in Table 3. ## 2.6. ccRCC-Specific Model Creation MS-based protein abundance data of the investigated proteins in the 162 patient samples were used for establishing the most robust classification algorithm. We investigated multiple machine learning methods (including k-nearest neighbors, random forest, logistic regression, and support vector machines) to build a model which can differentiate between normal and malignant kidney tissues. For the proper estimation of the optimal gene panel, we performed recursive feature elimination. Of the four methods, SVM delivered the best performance in both test and training cohorts using nine proteins as input. SVM was able to identify tumor tissues from MS quantification data with a classification accuracy of 0.98 in the test set (Kappa = 0.95, sensitivity = 0.95, specificity = 1). Results of all four methods (SVM, k-nearest neighbors, random forest, and logistic regression) in both training and test sets are displayed in Table 4; the list of optimal genes is provided in Table 5, and the accuracy of each method with different gene panels is presented in Supplemental Figure S3. ## 3. Discussion Current clinical diagnostics of cancer rely mainly on pathological examination using tissue slide staining or immune histochemistry. The importance of tissue inspection is undoubted. However, with the increasing burden of workload in pathological diagnostics, the need for further potent diagnostic possibilities and tools capable to provide sufficient pathological decision support is necessary. While transcriptome-based methods are useful for this purpose, several studies with promising results were published recently in the proteome field as well. Establishing proteins with differential abundance in malignant samples compared to healthy tissues can provide valuable information in diagnostics and therapeutic target identification. For example, a breast cancer study comparing malignant breast cancer samples to adjacent normal samples using MS identified a novel luminal subtype [15]. A comparison of normal prostate and prostate adenocarcinoma samples was performed to identify a new prognostic biomarker [16]. Like other cancer types, early surgical intervention is the best solution for total recovery in ccRCC as well. Especially in the early stages, when the disease is localized, partial or radical nephrectomy is the most frequently performed treatment option [5]. In the present study, by using transcriptomic data, we uncovered genes with higher expression in ccRCC, and we then developed an algorithm capable of identifying ccRCC tissues with accuracy high enough for future clinical application. We focused on genes having higher expression in the tumor tissues. By using targeted MS data of the selected proteins, our algorithm can differentiate between normal and malignant tissues and could provide valuable decision support during the pathological diagnostic process. The final discriminative algorithm is based on the differential expression of nine proteins. Of these, VEGFA and CCND1 are well-known cancer biomarkers. VEGFA (vascular endothelial growth factor A) is used as a target molecule in ccRCC treatment [6]. CCND1 (cyclin D1), a member of the cyclin family, acts as a regulator of cyclin-dependent kinases (CDKs). CDK inhibitors are widely used in the treatment of breast cancer [17]. PLOD2 (procollagen-lysin 2-oxoglutarate 5-dioxygenase) has a role in the maintenance of intermolecular collagen cross-links [18]. The aberrant function of PLOD2 might have a role in ovarian cancer [18] and gastric cancer progression [19]. PFKP (phosphofructokinase platelet isoform) is responsible for one of the early steps of glycolysis [20]. It might also have a crucial part in metabolic reprogramming in multiple cancer types like breast cancer [21] and non-small cell lung cancer [22]. IGFBP3 (insulin-like growth factor binding protein 3) acts as a carrier protein of several types of IGF molecules, and it is related to cell growth and differentiation [23]. IGFBP3 has been shown to be important in the development of colorectal and breast cancer [23,24]. PLIN2 (perilipin 2) is a member of the perilipin family and takes part in the formation of intracellular lipid storage droplets in multiple tissue types [25]. It has been connected to the development of atherosclerosis [26] but it has relevance in cancer initiation and progression as well [25]. Using Western blot technique, an earlier study has proposed PLIN2 as a potential plasma biomarker in ccRCC [27]. As both IGFP3 and PLIN2 can be detected in the plasma, we hypothesize that they could also serve as potential diagnostic biomarkers of ccRCC. Using our current knowledge, however, we lack any robust evidence for our hypothesis. By survival analysis, we identified five proteins with a high expression which correlates with poor survival outcomes. Out of these five, PLOD2, VIM, and P4HA1 are also highlighted by our model. Both PLOD2 and P4HA1 are enzymes involved in collagen-related pathways and proved to be a biomarker of epithelial-to-mesenchymal transition (EMT) in multiple types of cancers [28,29]. While vimentin acts as an important structural protein and a known marker of EMT, overexpression of these proteins in patients with poor survival outcomes implies their involvement in EMT and metastasis formation in renal cell clear carcinoma. We must note an important limitation of our approach. Although transcriptome-based examinations can provide valuable input of new potential biomarkers, due to mechanisms like alternative splicing, mutations, and post-translational modifications, RNA expression only moderately correlates with protein expression [30]. A further limitation of our model is the incapability of tumor stage estimation, as staging is usually based on imaging, pathological examination, and further clinical characteristics. In conclusion, we used a database of renal samples of paired normal and tumor tissues to identify biomarkers differentiating renal clear cell cancer (ccRCC) and normal kidney tissues. With a support vector machine-based machine learning algorithm using nine genes, we set up a model which can differentiate between normal and malignant ccRCC tissues using proteomic data. Finally, a set of proteins showed a significant correlation with poor survival outcomes and might serve as potential biomarkers of progression. ## 4.1. Gene Chip Database Comprising Normal and Tumor Tissues To set up the gene chip cohort, we searched the NCBI GEO repository (https://www.ncbi.nlm.nih.gov/geo/, accessed on 21 January 2021) for potential ccRCC and normal specimens using keywords “ccRCC” AND “normal” OR “GPL570” OR “GPL571” OR “GPL96”. Only those datasets involved contained normal tissues adjacent to tumors from HGU133, HGU133A_2, and HGU133A platforms. We filtered the datasets to exclude xenograft experiments, pooled samples, and cell line studies. Samples with insufficient description, nonexistent raw data, and repeatedly published data with distinct identifiers have been removed. To achieve this, the expression of the first twenty genes was determined, and samples with identical values were identified. In each case, the first published version was retained in the dataset. After the manual selection, the remaining samples were normalized using the MAS5 algorithm by utilizing the Affy Bioconductor library [31]. Finally, a second scaling normalization was executed to set the mean expression on each array to 1000. JetSet correction and annotation package was used to pick the proper probe set for each gene [32]. ## 4.2. Determining Differentially Expressed Genes Data processing and analysis were performed in R version 4.1.0 (https://www.r-project.org, accessed on 6 June 2021). Wilcoxon test was used to compare the tumorous and adjacent normal samples. Genes showing significant differences according to the Wilcoxon test ($p \leq 0.01$) have been selected and ranked based on their fold-change values (FC). The Benjamini–Hochberg method was used for p-value adjustment. Finally, the top 31 genes with an FC over two were selected for further investigation. ## 4.3. Ethics Statement ccRCC samples were collected at the Department of Urology of the Semmelweis University. An institutional ethical review board approved the study under the number ID 7852-$\frac{5}{2014}$/EKU by Semmelweis University Regional and Institutional Committee of Science and Research Ethics. All subjects were treated under the tenets of the Declaration of Helsinki and written informed consents were obtained before sample collection. ## 4.4. Sample Collection Clear cell renal carcinoma and adjacent normal samples were collected during surgical resection, and the tissue samples were stored immediately at −80 °C. Protein isolation was performed using the AllPrep DNA/RNA/Protein Mini Kit by the manufacturer’s protocol using 30 mg of tissue samples. ## 4.5. Targeted Liquid Chromatography Coupled Tandem Mass Spectrometry (LC-MS/MS) Analysis The expression of selected target proteins was verified by targeted LC/MS-MS. After isolation, protein samples were stored in guanidine isothiocyanate and stored at −80 °C. For targeted quantification, we used stable isotope labeled (SIL) peptides (1–5 respectively for each protein, labeled at Arg:13C6;15N4, Lys:13C6;15N2); the peptide sequences of the 75 SIL peptides are listed in Supplementary Table S1. Protein concentration was determined by the bicinchoninic acid (BCA) test. Samples were reduced by dithiothreitol (DTT) and alkylated using iodoacetamide followed by protein precipitation; then, samples were re-dissolved in $5\%$ SDS/50 mM ammonium-bicarbonate for the BCA test. Sample volumes representing 50 μg protein content were digested by trypsin according to the S-trap protocol (https://files.protifi.com/protocols/s-trap-mini-long-4-1.pdf, accessed on 9 January 2023). LC-MS/MS analysis was performed using an ACQUITY UPLC M-Class system (Waters, Milford, MA, USA) with HPLC coupled to an Orbitrap Fusion Lumos Tribrid (Thermo Fisher Scientific, Waltham, MA, USA) mass spectrometer on the mixture of the protein digests spiked with the mixture of the SIL peptides. Samples were loaded onto a trap column, ACQUITY UPLC M-Class Symmetry C18 Trap (100 Å, 5 µm, 180 µm × 20 mm, 2G, V/M); the sample loading time was 5 min; the flow rate was 5 µL/min, and separation was performed on an ACQUITY UPLC M-Class Peptide BEH C18 (130 Å, 1.7 µm, 75 µm × 250 mm) column with a flow rate of 400 nL/min. MS data acquisition was performed in an internal standard triggered parallel reaction monitoring fashion [33], where the presence of the corresponding SIL peptides, verified by their expected retention time and MS2 fragmentation pattern, triggers data acquisition of the targeted peptides with high sensitivity and resolution. MS signal intensities of the SIL peptides were between 1–5 × 107. Raw MS data were analyzed using the Skyline software and the MSstats statistical analysis tool. During the data processing steps, we performed the inbuilt normalization steps of the MSstats software package, which includes median polishing and log2 transformation. ## 4.6. Statistical and Functional Analysis, Data Visualization T-test was used to compare the log2 transformed protein intensity values between the tumorous and adjacent normal samples. In order to examine if any of the gene candidates are affected by covariates, we performed a t-test to see if any of the proteins show differential expression between male and female patients. To examine age as a covariate factor, we performed regression analysis to see if any of the examined proteins are influenced by age. Functional analysis was performed using the clusterProfiler R package [34]. For each protein, we performed Cox proportional hazard regression analysis. To estimate the best cutoff value for each protein, we examined each possible cutoff values between the lower and the upper quartiles; these cutoff values have been used for Kaplan–Meier plot visualization. The Benjamini–Hochberg method was used for p-value adjustment. For survival analysis, we used the survminer and survival R packages. Further visualization has been done using the R packages ggplot2 [35], ComplexHeatmap [36], and ggrepel (https://cran.r-project.org/web/packages/ggrepel/index.html, accessed on 13 December 2022). ## 4.7. Building a Model for ccRCC Detection Using the results of the targeted LC/MS-MS log2 intensity values, we tried four supervised AI methods, k-nearest neighbors (KNN), random forest (RF), logistic regression (LOGIT), and support vector machines (SVM), to set up the most accurate model for cancer detection. 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--- title: Transfer of Proteins from Cultured Human Adipose to Blood Cells and Induction of Anabolic Phenotype Are Controlled by Serum, Insulin and Sulfonylurea Drugs authors: - Günter A. Müller - Timo D. Müller journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003403 doi: 10.3390/ijms24054825 license: CC BY 4.0 --- # Transfer of Proteins from Cultured Human Adipose to Blood Cells and Induction of Anabolic Phenotype Are Controlled by Serum, Insulin and Sulfonylurea Drugs ## Abstract Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are anchored at the outer leaflet of eukaryotic plasma membranes (PMs) only by carboxy-terminal covalently coupled GPI. GPI-APs are known to be released from the surface of donor cells in response to insulin and antidiabetic sulfonylureas (SUs) by lipolytic cleavage of the GPI or upon metabolic derangement as full-length GPI-APs with the complete GPI attached. Full-length GPI-APs become removed from extracellular compartments by binding to serum proteins, such as GPI-specific phospholipase D (GPLD1), or insertion into the PMs of acceptor cells. Here, the interplay between the lipolytic release and intercellular transfer of GPI-APs and its potential functional impact was studied using transwell co-culture with human adipocytes as insulin-/SU-responsive donor cells and GPI-deficient erythroleukemia as acceptor cells (ELCs). Measurement of the transfer as the expression of full-length GPI-APs at the ELC PMs by their microfluidic chip-based sensing with GPI-binding α-toxin and GPI-APs antibodies and of the ELC anabolic state as glycogen synthesis upon incubation with insulin, SUs and serum yielded the following results: (i) Loss of GPI-APs from the PM upon termination of their transfer and decline of glycogen synthesis in ELCs, as well as prolongation of the PM expression of transferred GPI-APs upon inhibition of their endocytosis and upregulated glycogen synthesis follow similar time courses. ( ii) Insulin and SUs inhibit both GPI-AP transfer and glycogen synthesis upregulation in a concentration-dependent fashion, with the efficacies of the SUs increasing with their blood glucose-lowering activity. ( iii) Serum from rats eliminates insulin- and SU-inhibition of both GPI-APs’ transfer and glycogen synthesis in a volume-dependent fashion, with the potency increasing with their metabolic derangement. ( iv) In rat serum, full-length GPI-APs bind to proteins, among them (inhibited) GPLD1, with the efficacy increasing with the metabolic derangement. ( v) GPI-APs are displaced from serum proteins by synthetic phosphoinositolglycans and then transferred to ELCs with accompanying stimulation of glycogen synthesis, each with efficacies increasing with their structural similarity to the GPI glycan core. Thus, both insulin and SUs either block or foster transfer when serum proteins are depleted of or loaded with full-length GPI-APs, respectively, i.e., in the normal or metabolically deranged state. The transfer of the anabolic state from somatic to blood cells over long distance and its “indirect” complex control by insulin, SUs and serum proteins support the (patho)physiological relevance of the intercellular transfer of GPI-APs. ## 1. Introduction Soon after the discovery that certain cell surface proteins are anchored at the outer leaflet of the plasma membranes (PMs) of eukaryotic cells by a glycosylphosphatidylinositol (GPI) glycolipid that is covalently bound to the carboxy terminus of the protein moiety [1,2], the question concerning the role of membrane anchorage by GPI arose. Approximately 200 GPI-anchored proteins (GPI-APs) have been predicted or identified so far in mammalian cells, based on the carboxy-terminal consensus sequence for GPI addition and biochemical analysis, respectively [3,4]. The highly conserved GPI consists of amphiphilic phosphatidylinositol with two long-chain (mostly saturated) fatty acyl chains and a hydrophilic glycan core composed of glycosidically linked nonacetylated glucosamine and three mannose residues, which are amide-linked to the carboxy-terminus of the protein moiety via an ethanolamine-phosphodiester bridge (for structural details see Supplementary Materials, Supplementary Figure S1). GPI-APs are assembled along the secretory pathway (for a review, see [5,6,7]). Low space requirement at PMs, increased lateral mobility within the plane of the outer PM leaflet, capability for accumulation at higher density, in particular at certain cell surface microdomains, such as lipid rafts [8] (for a review, see [9,10,11,12]), and the possibility of the specific, rapid and controlled release from the cell surface by a single type of enzyme, GPI-specific phospholipases (GPI-PLs; for a review, see [13,14,15,16]), rather than by a multitude of different proteases, have been regarded as potential main reasons for the cell surface anchorage of proteins via GPI rather than by typical proteinaceous transmembrane domains. The functional implications of GPI anchorage apparently differ for each GPI-AP, since the exchange of a GPI for a transmembrane anchor by recombinant technology has been demonstrated to result in complete loss, impairment only or even maintenance of the function for the GPI-APs studied [17,18,19,20]. Considering the controlled release of GPI-APs, a multitude of GPI-APs, among them lipoprotein lipase, glycolipid-anchored cAMP-binding/phosphodiesterase ectoprotein Gce1 and 5’-nucleotidase CD73 [21,22,23], have been demonstrated to be lipolytically cleaved from the surface of a variety of eukaryotic cells, such as rat primary and cultured (3T3-L1) adipocytes, under certain (patho)physiological conditions or in response to certain hormones and stimuli, among them glucose [21,24], insulin [23,25,26,27] and antidiabetic sulfonylureas (SUs) [22,23,28]. In particular, the treatment of primary or cultured rodent adipocytes, cultured RAW264 or microglial cells with pharmacological concentrations of the antidiabetic SU of the 3rd generation, glimepiride (for structural details see Supplementary Materials, Supplementary Figure S2), a potent amphiphilic-to-hydrophilic conversion and release from the cell surface as soluble proteins were observed for a subset of GPI-APs, such as Gce1 and CD14, respectively, which is due to the activation of an endogenous GPI-PLC, with its catalytic ectodomain exposed at the cell surface [21,22,23,24,25,26,27,28]. The identity of the mammalian GPI-PLC(s), in particular the insulin- and SU-dependent one(s), remains to be elucidated as holds true for the molecular mechanism(s) of their activation, albeit tyrosine kinase signaling [29] and glucose transport-dependent [21,24] pathways have been suggested. Experimental findings obtained over the last two decades have increasingly focused on the apparently labile cell surface anchorage of GPI-APs with resulting amphitropic localization at both cell surfaces and in extracellular compartments, as a consequence of their spontaneous nonenzymic release from the outer leaflet of PMs due to the fact of their pronounced overall amphiphilic character (i.e., large hydrophilic protein moiety coupled to amphiphilic GPI) (for a review, see [15,16]). The capability of full-length GPI-APs for spontaneous release from and insertion into PM, as deduced from this large body of experimental data obtained in vitro, immediately raised the possibility of a physiological function of the intercellular transfer of GPI-APs in multicellular (e.g., mammalian) organisms between donor and acceptor cells of the same type over a short distance (i.e., within the same tissue depot) and in the so-called “direct” mode, i.e., without interference by other (e.g., serum) proteins. In fact, “direct” transfer has recently been demonstrated for large heavily lipid-loaded and small less lipid-loaded adipocytes [30], which may shift the burden of lipid synthesis from the former to the latter in case of the need of excessive fat deposition in adipose tissues. In contrast, GPI-AP transfer between different cell types over a long distance (i.e., between different tissue depots) has been considered as unwanted: transfer of GPI-APs typically covering a broad spectrum of functions, such as receptors, binding proteins, enzymes, cell adhesion, and matrix proteins [5,7,13], across extracellular compartments, such as interstitial spaces and blood, to acceptor cells of different tissue depots, which do not express them at the surface in the normal state, could lead to deleterious effects. Consequently, it has been postulated that mammalian organisms had to develop strategies to prevent the transfer of GPI-APs between cells over a long distance via the circulation. In agreement, upregulated cleavage by the major serum protein, GPI-specific phospholipase D (GPLD1) [31,32], and interaction with serum proteins of the GPI of GPI-APs have been reported [33,34] and correlated to the elevated release of the latter in response to adverse effectors, such as age and metabolic state, thereby blocking their transfer in the so-called “indirect” mode, i.e., with the aid of other (e.g., serum) proteins. In the present study, a putative role of the controlled lipolytic release of GPI-APs from donor cells with loss of their GPI anchor in concert with serum GPI-binding proteins in the prevention of GPI-AP transfer to and associated effects in acceptor cells different and distant from the donor cells was investigated. For this, the previously introduced transwell co-culture of differentiated human adipocytes [30] as donor cells and mutant erythroleukemia K562 (EL) cells (ELCs), which fail to express GPI-APs at their surface [35], as acceptor cells and detection of the transferred GPI-APs with a chip-based microfluidic sensor system [36,37] were used. The latter relies on the propagation of surface acoustic waves (SAWs) along the chip surface, which is affected in the course of binding to the chip of any entities, in general, and interaction between partners of interest, in particular, one of which, here PMs, became immobilized onto the chip surface with the aid of ionic and covalent capturing procedures. The other one, binding-proteins against the immobilized partner, here α-toxin for the GPI anchor (for a review, see [38]) or antibodies against the protein moieties of the transferred GPI-APs, is subsequently injected into the chip channels (single or in sandwich). The resulting rightward phase shift (i.e., increase in difference in phase or decrease in frequency) of the SAWs represents a real-time measure for the mass loaded, here the nature and amount of full-length GPI-APs that were transferred during the previous incubation of the ELCs, onto the immobilized sample analyte, here their PMs. Both insulin and glimepiride caused the downregulation of the transfer of GPI-APs from human adipocytes to ELCs and the accompanying stimulation of glycogen synthesis. Unexpectedly, in the presence of serum insulin and glimepiride this led to increased GPI-AP transfer and glycogen synthesis, dependent on the metabolic state of the rats, from which the serum was derived. The differential serum-dependent effects of insulin and glimepiride on GPI-AP transfer were shown to rely on the displacement of full-length GPI-APs from serum GPI-binding proteins by GPI-APs lipolytically cleaved in response to insulin or SUs. Taken together, the present study suggests that the transfer of GPI-APs between different and distant cells (e.g., from donor adipose to acceptor blood cells) may exert (patho)physiological roles in the acceptor cells (e.g., stimulation of glycogen synthesis), which is under the “indirect” control of a complex interplay of serum proteins (e.g., GPLD1), signals (e.g., insulin) and drugs (e.g., SUs). ## 2.1. Stimulation of Basal Glycogen Synthesis upon Transfer of GPI-APs Depends on Their Localization at the PMs of the Acceptor ELCs Full-length GPI-APs with the complete GPI anchor remaining attached become released from and inserted into the outer leaflets of PMs of human donor adipocytes and acceptor ELCs, respectively, with the accompanying upregulation of glycogen synthesis in the latter, as recently demonstrated using transwell co-culture and SAW sensing [29]. However, it has been left open whether the transferred GPI-APs remain localized at the PMs in order to exert their putative biological function. The extra- vs. intracellular localization of the transferred GPI-APs, in particular their possible internalization in the acceptor cells, which has been amply documented with native GPI-APs after their biogenesis in various cell types, was assayed with GPI-deficient ELCs as acceptor cells, which facilitate the detection of the putative physiological effects of GPI-AP transfer due to the missing background of endogenous GPI-APs (for a more detailed explanation, see [30]). After incubation with human adipocytes as donor cells for the induction of the transfer (i) and further incubation in the absence of the donor adipocytes for increasing periods to provoke their internalization (ii), PMs were analyzed for the expression of the total and individual GPI-APs (iii; Figure 1a,b) and, in parallel, glycogen synthesis was measured at low (basal) and high concentrations of glucose (iv; Figure 1c,d). For the determination of the rather low amounts of GPI-APs transferred during the transwell co-culture (for more details, see [30]), a chip-based microfluidic sensor system of very high sensitivity, accurateness and reproducibility, as well as robustness, towards the turbidity and viscosity caused by the lipidic entities in the samples was used. It relies on the propagation of SAWs along the gold surface of the chip channels, which is affected by any interaction of macromolecules with the channels, e.g., by capture of PMs through combined ionic and covalent bonds upon their injection, as well as subsequent binding of antibodies directed towards transmembrane proteins or GPI-APs expressed at those PMs. The resulting rightward phase shift (decrease in frequency) of the SAWs represents a measure for the mass (i.e., relevant antibodies) loaded onto the chip (as single entities or in sandwich) and, consequently, for the amount of a specific membrane protein at the PMs. Thus, both successful capture of the PMs, prepared from the acceptor cells, by the TiO2 chip surface (not shown here; for details, see [30]) and the nature and amount of specific GPI-APs expressed at the acceptor PMs after their (i) transfer to and (ii) eventual internalization by the acceptor ELCs during transwell co-culture together with donor adipocytes (i) and then alone (ii) can be monitored as increases in the phase shift. The SAW sensing of the PMs of acceptor cells that were incubated with medium alone did not result in phase shift increases upon the injection of anti-TNAP, CD73 and AChE antibodies (Figure 1a, Δ Control, 1800–2700 s) in agreement with the lack of expression of those GPI-APs by GPI-deficient ELCs, as has been recently reported [35,39]. However, the phase shift Δ between incubation (i) (for one week) of the acceptor ELCs with (Figure 1a, Δ 0 min of incubation [ii]) but not without (Figure 1a, Δ Control) donor adipocytes increased in stepwise fashion, indicating the transfer of TNAP, CD73 and AChE from the PMs of donor adipocytes to the PMs of acceptor ELCs. By contrast, no phase shift Δ were measured for the transmembrane proteins Band-3 and Glut4, as well as the atypical caveolae-specific membrane protein Cav1, which were all endogenously expressed by the GPI-deficient ELCs but failed to be transferred from the human adipocytes during transwell co-culture incubation (i) (Figure 1a, Δ Control, 800–1800 s). The expression of proteins at PMs is typically determined by the rates of their synthesis/exocytosis and internalization/degradation, which are at equilibrium during continuous cell growth. This holds true with the transmembrane proteins, since the antibody-induced phase shifts did not increase upon incubation (ii) of the ELCs with medium alone (i.e., upon the removal of the insert wells with the donor adipocytes from the bottom wells with the ELCs) for increasing periods (Figure 1a, Δ 0 min-8 h, 800–1800 s). By contrast, antibody-induced phase shift increases for the transferred GPI-APs declined over time of the incubation (ii) in the absence of the donor cells (Figure 1a, Δ 0 min-8 h, 1800–2700 s). Eight hours after the termination of the GPI-AP transfer, the phase shift reached control levels, as observed for the missing transfer upon incubation with medium alone (Figure 1a, Δ Control, 1800–2700 s). These data reflect the continuous internalization (during incubation [ii]) of the transferred GPI-APs in the GPI-deficient ELCs, which only became apparent upon the termination of the transfer (during incubation [i]), leading to a rightward shift of the steady state of the PM expression of GPI-APs between their transfer and internalization. Bacterial PI-PLC specifically cleaves off the diacylglycerol moiety of GPI anchors from GPI-AP protein moieties. Moreover, it may release those PM vesicles from the chips, which have been immobilized through ionic/covalent capture of GPI-APs. In fact, the injection of bacterial PI-PLC (Figure 1a, 2700–2900 s) following that of the antibodies led to a decline in antibody-induced phase shifts in sandwich compatible with anchorage of the corresponding transferred and internalized proteins through full-length GPI. The only 30 to $50\%$ reduction may be explained by partial lipolytic digestion only due to the fact of the impaired accessibility of the GPI-APs for bacterial PI-PLC, which is known to depend on the type of both cell and protein. Importantly, acylation at the 2-position of the myo-inositol residue of the glycan core of human GPI-APs, which occurs during early biogenesis (and becomes reversed during later stages for some but not all human cell types and GPI-APs, such as for erythrocyte AChE, decay accelerating factor and placental alkaline phosphatase), was reported to impair cleavage by bacterial PI-PLC [5,6,7,40,41]. An only partial regain of deacylase expression during prolonged culture of ELCs could be responsible for the removal of only a portion of the transferred GPI-APs, the deacylated ones, from PMs (Figure 1a, 2700–2900 s). The portions of the phase shift increase corresponding to acylated GPI-APs, which were transferred (incubation [i]) yet not internalized (during the initial period of incubation [ii]; Δ 0 min–2 h) and resisted PI-PLC, were completely eliminated following the injection of TX-100 (Figure 1a, 3000–3200 s). This agreed with the solubilization of the captured PM and confirmed that any alteration in phase shift measured by SAW sensing relied on the PMs captured by the chips. The quantitative evaluation of the number of GPI-APs left at the PMs of GPI-deficient ELCs immediately after the termination of transfer (after one week of incubation [i]; see Figure 1a, green curve, Δ 0 min) and after subsequent incubation (ii) for increasing periods (see Figure 1a, Δ 15 min–8 h) revealed the time-dependent loss from PMs, i.e., internalization of the total and individual transferred GPI-APs (Figure 1b). The kinetics revealed its completion after 6 to 8 h for all GPI-APs but with significant differences in the half-life times, ranging from 20 to 25 min for AChE to up to 50 to 55 min for TNAP. Previous data have shown that the transfer of total adipocyte GPI-APs to GPI-deficient ELCs is correlated to the upregulation of basal glycogen synthesis, as measured at a low glucose concentration [30]. Importantly, this apparent biological effect of GPI-AP transfer is glucose-dependent and declined with increasing concentrations of glucose, as shown here by the transfer of GPI-APs from donor adipocytes (Figure 1c, 0 min, green lines) or control incubation (Figure 1c, medium, blue lines), subsequent incubation of the acceptor ELCs in the insert wells of the transwell co-culture with increasing concentrations of radiolabeled glucose (at identical specific radioactivity) and final assay for the amount of glycogen synthesized. As expected, radiolabeled glycogen increased with increasing concentrations of glucose in ELCs lacking, as well as harboring, transferred GPI-APs due to the fact of mass action. However, the stimulation of glycogen synthesis by the transferred GPI-APs was more pronounced at low (0.1–5 mM) glucose concentrations. This led to a leftward shift of the concentration–response curve for ELCs with transferred GPI-APs, as revealed by the lower glucose concentration effective for half-maximal stimulation (1.6 mM) compared to GPI-deficient ELCs (3.9 mM) (Figure 1c). Next, the effect of the internalization of the transferred GPI-APs in ELCs on glucose-dependent glycogen synthesis was investigated (Figure 1d). The stimulation of glycogen synthesis by the transferred GPI-APs decreased with the increasing periods of incubation (ii) after the termination of transfer (incubation [i]) and start of the decline of the GPI-APs at PMs (Figure 1d, 0 min), irrespective of the glucose concentration present during the assay. The half-life times, as well as the time points, for the complete abrogation of glycogen synthesis stimulation (Figure 1d, 4–8 h) were like those for the internalization of the transferred GPI-APs (Figure 1b). Moreover, at the start of the internalization (zero time point), the fold-stimulation of glycogen synthesis (at identical, specific radioactivity) by transferred adipocyte GPI-APs was highest at 0.1 mM glucose and significantly decreased with increasing glucose concentrations to up to the complete loss of stimulation at 15 mM. In conclusion, the comparable kinetics of the internalization of the transferred GPI-APs and downregulation of (predominantly basal) glycogen synthesis in the acceptor ELCs argued for a mechanistic link between the transfer to and residence at their PMs of GPI-APs and sensitization of glycogen synthesis towards glucose. These findings prompted the investigation of the effects of the inhibition of the internalization of the transferred GPI-APs on their residence at the PMs in parallel to the basal glycogen synthesis in the acceptor ELCs. For this, small-molecule inhibitors of the endocytosis of typical or atypical transmembrane proteins involving either clathrin-coated vesicles (chlorpromazine, Dynasore) or caveolae (filipin, Dynasore) (Figure 2a–c) [42], as well as siRNAs directed towards components of the GPI-AP-enriched endosomal compartment (GEEC [42,43,44,45,46]) (Rac1, RhoA, Cdc42 [47]) engaged in endocytosis of GPI-APs (Figure 2d–f) were used. The downregulation by the siRNAs, alone or in combination, was demonstrated for the corresponding RNAs by qPCR (Müller and Müller, unpublished data) and proteins by SAW sensing (Supplementary Materials, Supplementary Figure S3, Supplementary Table S1) and found to be specific and efficient (by 82 to $89\%$ and 65 to $78\%$, respectively). After the termination of the GPI-AP transfer (incubation [i]) by removal of the donor adipocytes from the acceptor ELCs in the transwell co-culture, the inhibitors were added to incubation (ii) (480 min) for putative interference with the internalization of the GPI-APs. As expected, an analysis of the PMs of the ELCs by SAW sensing for typical (Band-3, Glut1) or atypical (Cav1) transmembrane proteins (TMPs) revealed significant increases in phase shift (Figure 2a; 800–1800 s; summation signals) and, thus, expression at PMs (Figure 2b; calculated total and individual TMPs, presence vs. absence of inhibitor) of Band-3 and Glut1 (to up to 2.2-fold) in response to chlorpromazine and Dynasore, and of Cav1 (to up to 1.6-fold) in response to filipin and Dynasore. In contrast, filipin, chlorpromazine and Dynasore did not significantly affect the PM expression of the GPI-APs TNAP, CD73 and AChE (Figure 2a; 1800–2700 s, Figure 2b). The measurement of the glycogen synthesis of the ELCs after increasing periods of internalization confirmed the time-dependent decline of the transfer-induced basal glycogen synthesis (see Figure 1b), with complete loss after 480 min (Figure 2c, green line), but it did not reveal any effect of filipin, chlorpromazine or Dynasore on the kinetics of glycogen synthesis downregulation (Figure 2c). The presence of siRNAs directed towards Rac1, RhoA and Cdc42 compared to their absence (Figure 2d; orange curve) after the termination of transfer during internalization led to significant upregulation of the amounts of transferred GPI-APs left at PMs, in this ranking order of increasing efficacy of the siRNAs (Figure 2d). The time courses of internalization, which were calculated as the number of transferred total GPI-APs left at PMs of the ELCs, were shifted to the right by the siRNAs, with those directed towards Cdc42 and Rac1 being most and least efficient, respectively (Figure 2e). After 480 min of incubation with Rac1, RhoA and Cdc42, approximately 40, 60 and $80\%$ of the transferred total GPI-APs, respectively, was left at PMs compared to the absence of siRNAs (Figure 2d,e; green lines). Importantly, the time courses of the internalization of the GPI-APs (Figure 2e) and downregulation of the glycogen synthesis (Figure 2f) in the ELCs in the course of silencing were similar, with rightward shifts by 15 to 30 min for both and Cdc42 being most effective in interfering with both. Importantly, silencing of Rac1, RhoA and Cdc42 did not affect expression at PMs of Band-3, Glut1 and Cav1 (Figure 2d; 800–1800 s) compared to “no-transfer” (Figure 2d; blue curve) and no-siRNA (Figure 2d; orange curve) control. Together the data (Figure 1 and Figure 2) imply that the physiological function of transferred GPI-APs does not depend on their endocytosis. ## 2.2. Insulin and Antidiabetic SUs Inhibit Both GPI-AP Transfer to and Transfer-Induced Glycogen Synthesis in Acceptor ELCs Previous research [30,48] and the above data have demonstrated that the intercellular transfer of GPI-APs and the accompanying stimulation of anabolic processes (glycogen and lipid synthesis) in the acceptor cells critically depend on the preservation of the complete GPI anchor of the GPI-APs, as well as their localization at the PMs of the acceptor cells. Insulin and the antidiabetic SUs of the 2nd and 3rd generation, glibenclamide and glimepiride (for the structure of typical representatives, see Supplementary Materials, Supplementary Figure S2), are known to release GPI-APs from the surface of insulin target cells, such as primary and cultured adipose and muscle cells, by induction of a GPI-specific phospholipase C (GPI-PLC), as well as to stimulate glucose transport and utilization, such as lipid and glycogen synthesis, respectively [22,23,25,26,27,49,50,51,52] (for the concentration-dependent stimulation of lipid synthesis in human adipocytes by insulin and glimepiride, see also Supplementary Materials, Supplementary Figure S4a,b). From these data it might be concluded that both insulin and SUs interfere with the transfer of full-length GPI-APs from donor to acceptor cells, and the accompanying induction of anabolic processes and vice versa that the anabolic processes elicited by insulin and SUs are not mediated by intercellular GPI-AP transfer. In fact, the presence of insulin (Figure 3a,b) or SUs (Figure 3c,d) during transwell co-culture led to the concentration-dependent reduction of the transfer of TNAP, CD73 and AChE from human adipocytes to GPI-deficient ELCs by up to $77\%$ (30 nM insulin) and $61\%$ (50 μM glimepiride) with the half-maximal inhibition at 2.3 nM and 4.9 μM, respectively. Importantly, FGF21 (Figure 3a), which exerts anabolic effects in adipocytes [53], as well as the insulin-releasing drugs meglitinide [54] and tolbutamide [55] (Figure 4c,d), had no effect on the transfer. Both insulin and SU inhibition of transfer was almost completely abrogated by an inhibitor of the GPI-PLC, GPI2350 [52] (Figure 3a–d). This argued for the lipolytic cleavage of the GPI-APs upon exposure of the donor human adipocytes to insulin, glimepiride and glibenclamide prior to initiation and completion of their transfer, in that ranking order of decreasing potency, as reflected in the leftward shift of the concentration–response curve of the former vs. the latter (Figure 3d). Remarkably, the transfer of each GPI-AP studied was significantly elevated by glucose at high (5 mM) compared to low (0.1 mM) concentration (as routinely used in the transwell co-culture) (Figure 3e,f). This may be explained best by the upregulation of release from rather than insertion into the PMs of human adipocyte donor and EL acceptor cells, respectively. Previous findings have shown that release rather than insertion and donor rather than acceptor cells are susceptible towards stimulatory exogenous and endogenous factors, such as hyperglycemia or hyperinsulinemia [56], age or lipid-loading [33]. Strikingly, at high glucose, insulin failed to block total GPI-AP transfer (Figure 3e,f). At variance, the inhibition of transfer by glimepiride alone or together with insulin was maintained at high glucose concentrations (Figure 3e,f) and only tended to be lower compared to low glucose (55.6 vs. $61.3\%$ alone and 76.9 vs. $80.7\%$ with insulin). Apparently, at high glucose, glimepiride but not insulin manages to compensate for the increased glucose-dependent release of full-length GPI-APs by the activation of the GPI-PLC and thereby to restrict transfer. This can be explained best by the reported failure of high glucose to elicit the desensitization of the GPI-PLC towards stimulation by insulin but not by glimepiride [57]. To assess whether the inhibition of intercellular GPI-AP transfer by insulin and SUs leads to impairment of transfer-induced glycogen synthesis, the acceptor ELCs from the above transwell co-culturing with donor adipocytes (see Figure 3) were incubated with [U-14C]glucose after the termination of transfer (i.e., removal of the adipocytes). Insulin (Figure 4a), as well as glimepiride (Figure 4b), did not affect the glycogen synthesis in ELCs that had been cultured only with medium (control no transfer). This is in agreement with the complete lack of responsiveness of those cells towards both insulin and glimepiride (see Supplementary Materials, Supplementary Figure S4c,d). The co-culturing of human adipocytes and ELCs in the absence of insulin and SUs led to 2.5- to 3.1-fold increases in glycogen synthesis (Figure 4a,b) due to the GPI-AP transfer, in agreement with previous findings [30]. Both insulin (Figure 4a) and glimepiride (Figure 4b) caused the downregulation of transfer-induced glycogen synthesis in a concentration-dependent fashion with IC50 of 2.8 nM and 4.3 μM, respectively. Glibenclamide (IC50 of 19.1 μM) was significantly less potent, and tolbutamide was inactive (Figure 4b). As expected, insulin (Figure 4a), as well as glimepiride (Figure 4b), inhibition of transfer-induced glycogen synthesis was abrogated by GPI2350, compatible with the inhibition of insulin- and glimepiride-induced cleavage and transfer of GPI-APs. Strikingly, glucose at high concentrations present during transfer significantly stimulated transfer-induced glycogen synthesis in ELCs (Figure 4c, right panel), which was not abrogated by insulin (at variance with low glucose, see left panel). In contrast, it was impaired by glimepiride alone or in combination with insulin. The reduction by approximately 60 and $70\%$, respectively (Figure 4c, right panel), was of a similar degree as measured for low glucose (see left panel). Together, these findings imply that both insulin and SUs stimulate the lipolytic release of GPI-APs from the human adipocytes and thereby prevent their transfer to and induction of transfer-induced glycogen synthesis in the ELCs. ## 2.3. Insulin and SU inhibition of GPI-AP Transfer and Transfer-Induced Glycogen Synthesis Is Controlled by Serum Apparently, the inhibition of GPI-AP transfer to and transfer-induced glycogen synthesis in acceptor cells is provoked by three structurally different signals, insulin and antidiabetic SUs of the 2nd and 3rd generation, as demonstrated above, and certain serum proteins, such as GPLD1 and BSA, as has been shown previously [30], and based on two different molecular mechanisms of interference with GPI-AP transfer, cleavage by insulin-/SU-dependent GPI-PLC (see above) and interaction with certain serum GPI-binding proteins [30]. This raised the possibility of the sub-additive, additive or synergistic inhibition of GPI-AP transfer, as well as transfer-induced glycogen synthesis, in the course of cooperation of insulin or SUs and serum. As expected, both insulin alone (Figure 5a,b; no serum) and serum (from obese ZDF rats) alone without (Figure 5b) or with the Ca2+-chelating agent Pha (Figure 5a,b; no insulin) decreased the transfer of the GPI-APs studied (Figure 5a; control transfer) by approximately $75\%$ compared to the absence of donor cells (Figure 5a; control no transfer). This indicated the efficient reduction of the number of GPI-APs competent for transfer in the course of insulin-induced cleavage or binding to serum proteins, respectively, of the GPI anchors. Importantly, the serum effects cannot be attributed to insulin, which was certainly left in the serum samples at considerable concentrations, in particular, in those obtained from obese rats (see Supplementary Materials, Supplementary Table S2). Firstly, the samples were considerably diluted resulting in a final assay concentration of rat insulin, which fell below the insulin sensitivity of even typical insulin target cells, such as adipocytes. Secondly, the ELCs did not display any insulin responsiveness (see Supplementary Materials, Supplementary Figure S4c) due to the fact of the missing expression of insulin receptors [39]. However, unexpectedly, the combination of insulin and serum (from obese ZDF rats) in the presence of Pha led to the restoration of the transfer to approximately $70\%$ (Figure 5a,b) compared to the maximal transfer in the absence of both (Figure 5a, control transfer; b). Strikingly, in the absence of Pha, the transfer was even further increased to approximately $170\%$ (Figure 5b). The latter indicates that Ca2+ fosters the stimulation of transfer by the combined action of insulin and serum. This may be due to the weakening of the interaction between certain serum GPI-binding proteins, such as GPLD1, and full-length GPI-APs, which has previously been shown to depend on Ca2+ [34]. An explanation for the apparent contradiction that insulin and serum each, per se, inhibit but in concert stimulate GPI-AP transfer may be that serum GPI-binding proteins, such as GPLD1 and BSA, act as source of full-length GPI-APs, from which they become transferred upon their release in response to insulin. This hypothesis was tested by various pretreatments of serum (from obese ZDF rats) envisaged for the depletion of full-length GPI-APs (Figure 5b). In fact, the digestion of serum with bacterial PI-PLC, human GPLD1 and proteinase K, which cleave off the GPI anchor and protein moiety, respectively, of the GPI-APs, as well as the addition of α-toxin or anti-TNAP/CD73/AChE antibodies, each coupled to Sepharose beads, which bind to the GPI anchor of each and the protein moiety of individual GPI-APs, respectively, significantly reduced the concerted insulin- and serum-stimulated transfer of each GPI-AP at varying degrees. Interestingly, pretreatment of serum with phenyl Sepharose beads, which has previously been demonstrated to bind to the anchor of detergent-solubilized GPI-APs [58], did not affect the transfer of GPI-APs (Figure 5b). This is presumably due to the fact of their tight interaction with serum GPI-binding proteins, which prevents binding of phenyl Sepharose to the GPI anchors and thereby interference of the beads with insertion of the anchors into the PMs of acceptor cells (Figure 5b). BSA has previously been shown to interact with full-length GPI-APs [30]. Nevertheless, defatted BSA from commercial sources did not substitute for serum in supporting insulin stimulation of transfer (Figure 5b). This is explained best by those charges of BSA having lost full-length GPI-APs during the defatting procedures. Together, these data supported the view that serum (from obese ZDF rats) provides full-length GPI-APs, which are bound to proteins and apparently released thereof in response to insulin, thereby gaining competence for transfer to acceptor cells. In accordance with this explanation, the restoration of the insulin-inhibited GPI-AP transfer (Figure 5c; insulin no serum) by serum (from obese ZDF rats) (Figure 5c) was dependent on its volume and reached $50\%$ of the control transfer (absence of insulin and serum) with 250 µL (Figure 5c,d). Moreover, it was affected by the nature of the serum (Figure 5a,d), with that from obese ZDF rats being most effective (Figure 5a; to up to $70\%$ of control transfer), followed by serum from obese ZF, obese Wistar, lean ZDF, lean ZF and lean Wistar rats in that ranking order of declining efficacy (Figure 5a). This ranking order was also reflected in the volumes of the different sera required for the half-maximal restoration of insulin-inhibited transfer (Figure 5d). In fact, the calculation of the IV50 enabled the differentiation between the different metabolic states, except for obese ZDF and obese ZF rats, as well as obese ZF and obese Wistar rats (Figure 5d). Metabolically dysregulated rats were chosen since they represent a widely acknowledged animal model of type II diabetes mimicking the different stages of normoglycemia/insulinemia- to hyperglycemia/insulinemia (see Supplementary Materials, Supplementary Table S2 for a detailed characterization of the metabolic states) along the pathogenesis, driven by both genotype (Wistar, ZF and ZDF) and feeding (normal and high-fat diet) (for a review, see [59,60,61]). The above conclusion that full-length GPI-APs bound to certain serum proteins become transferred to acceptor ELCs in the course of action of insulin-dependent GPI-PLC at the donor adipocytes raised the question concerning the underlying mechanism. Strikingly, PIG41, which structurally closely resembles the glycan core of human AChE [62,63], in combination with serum (100 μL, obese ZDF) led to drastically increased transfer (Figure 5c) compared to insulin combined with serum, which even exceeded the control transfer (absence of serum and insulin). This suggests that PIG41 causes dissociation of full-length GPI-APs from serum GPI-binding proteins. Thus, in the transwell co-culture in the presence of serum, the rate of the intercellular transfer of GPI-APs was determined by the efficacy of their dissociation from GPI-binding proteins and their amounts, i.e., serum volume and type. This agrees with previous [30,34] and the above findings (Figure 5b) that only full-length GPI-APs not bound to serum proteins are competent for transfer. The transfer in response to the combination of insulin and serum was time dependent (Figure 5e,f) and detectable after 5 min at the earliest and then for up to two weeks. The combined insulin- and serum-stimulated transfer (with insulin inhibition for each period subtracted) was positively correlated to the transfer period (Figure 5f) and dependent on the type of serum. Serum from obese ZDF and lean Wistar rats was most and least potent, respectively (Figure 5f). These findings add further evidence that in the presence of insulin and serum in the transwell co-culture, the full-length GPI-APs that were competent for transfer most likely originated from serum GPI-binding proteins rather than the donor adipocytes. The transfer of full-length GPI-APs upon their dissociation from serum GPI-binding proteins by either PIG41 or insulin suggests that lipolytically cleaved GPI-APs (PIG-proteins) released from donor cells by the insulin-/SU-dependent GPI-PLC mediate GPI-AP transfer from human adipocytes to ELCs during the simultaneous presence of serum and SUs. As expected, glimepiride or glibenclamide alone (Figure 6a,b; no serum), as well as serum from obese ZDF rats (without or with Pha; Müller and Müller, unpublished data) alone (Figure 6c), reduced the transfer by approximately $50\%$ compared to their absence (Figure 6a,b; control transfer, 6c). The SU inhibition was almost fully abrogated by the GPLD1 inhibitor GPI2350 (Figure 6c; shown only for glimepiride). This confirmed the prevention of GPI-APs from transfer by SUs as a consequence of their lipolytic cleavage or by serum GPI-binding proteins in the course of binding to their GPI anchors. However, the combination of glimepiride or glibenclamide and serum (from obese ZDF rats) led to approximately 80 and $90\%$ transfer, respectively, of that in absence of both SU and serum (Figure 6a,b; control transfer, 6c). The presence of Pha significantly reduced the combined serum- and glimepiride-induced transfer (Figure 6c). This was compatible with the above explanation that the absence of Ca2+ interferes with transfer as a result of the stabilization of the interaction between full-length GPI-APs and serum GPI-binding proteins. The possibility that serum GPI-binding proteins act as a source for full-length GPI-APs that are competent for transfer upon their SU-induced dissociation was investigated. The digestion of serum (from obese ZDF rats) with bacterial PI-PLC, human GPLD1 or proteinase K, as well as the addition of combined anti-TNAP/CD73/AChE antibodies or α-toxin coupled to Sepharose beads, significantly impaired the combined SU- and serum-induced transfer at variable degrees compared to the untreated serum (Figure 6c). Only phenyl Sepharose beads had no effect (see Figure 5b). BSA instead of serum did not prevent glimepiride inhibition of transfer. In conclusion, the data were compatible with full-length GPI-APs bound to serum GPI-binding proteins becoming competent for transfer upon their dissociation in response to the glimepiride challenge of donor cells. The abrogation of the SU inhibition of transfer by serum was dependent on the metabolic state of the donor rats (Figure 6a,b) and the volume used (Figure 6d). Serum from obese ZDF rats turned out to be the most effective for both glimepiride (Figure 6a) and glibenclamide (Figure 6b) inhibition compared to the control transfer (absence of both SU and serum), followed by obese ZF, obese Wistar, lean ZDF, lean ZF and lean Wistar rats in that ranking order of declining efficacy. This ranking order was also reflected in the volumes of the different sera effective in the half-maximal stimulation of transfer (EV50) in the presence of glimepiride (Figure 6d), which enabled the differentiation between obese ZDF and ZF, ZF and Wistar or ZDF and Wistar rats. Next it was investigated whether the abrogation of the insulin and SU inhibition of GPI-AP transfer by serum is reflected in the stimulation of glycogen synthesis in the acceptor cells. For this, human adipocytes as donor cells and GPI-deficient ELCs as acceptor cells were incubated in transwell co-culture in the presence of insulin (Figure 7a,b) or SUs (Figure 7c,d) without or with serum from rats of different metabolic states (Figure 7b,d), which had been pretreated to get rid of (full-length) GPI-APs (Figure 7a,c). The assaying of the ELCs for basal glycogen synthesis (5 mM glucose) revealed that serum (from obese ZDF rats), insulin and glimepiride each alone and independent of the absence or presence of Pha (Müller and Müller, unpublished results) did not exert any significant effect (Figure 7a,c). However, either insulin or glimepiride or glibenclamide but not tolbutamide or meglitinide in combination with serum significantly stimulated glycogen synthesis in that ranking order of declining potency. These effects were considerably diminished by Pha. Lipolytic and proteolytic pretreatments of the serum, as well as α-toxin Sepharose beads, completely blocked serum-stimulated glycogen synthesis in the presence of either insulin (Figure 7a) or glimepiride (Figure 7c). Strikingly, antibodies against TNAP, CD73 and AChE coupled to Sepharose beads had no impact. BSA did not substitute for serum in stimulating glycogen synthesis (Figure 7a,c). Thus, the positive correlation between the upregulation of GPI-AP transfer (see Figure 5 and Figure 6) and glycogen synthesis in ELCs (see Figure 7a,c) in the course of the combined challenge of donor cells with serum and either insulin or glimepiride is compatible with full-length GPI-APs, which are not identical with TNAP, CD73 and AChE, mediating the upregulation of basal glycogen synthesis upon their dissociation from serum GPI-binding proteins, which are not identical with albumin, and subsequent transfer to the PMs of the acceptor cells. Subsequent analysis of the volume dependence for sera from rats of different metabolic state in stimulating glycogen synthesis in acceptor ELCs in the presence of either insulin (Figure 7b) or glimepiride (Figure 7d) revealed identical rankings, i.e., obese ZDF, obese ZF, obese Wistar, lean ZDF, lean ZF, lean Wistar, in that order of decreasing potency, which were identical to those for serum stimulation of GPI-AP transfer in the presence of insulin (Figure 5) or glimepiride (Figure 6). ## 2.4. Full-Length GPI-APs Displaced from Serum Proteins by PIG(-Proteins) Are Transferred to and Stimulate Glycogen Synthesis in Acceptor Cells The above experiments revealed that serum from obese ZDF rats added to the transwell co-culture abrogates insulin and SU inhibition of GPI-AP transfer (Figure 6), as well as glycogen synthesis in ELCs (Figure 7). These findings led to the hypothesis that full-length GPI-APs bound to serum GPI-binding proteins become displaced by PIG-proteins, lipolytically cleaved off from full-length GPI-APs of donor cells in response to insulin or SUs. Consequently, serum from rats of different metabolic state was assayed for binding of full-length GPI-APs and their displacement by PIGs or lipolytically cleaved GPI-APs (PIG-proteins). GPLD1 has been identified so far as the only serum protein that interacts with full-length GPI-APs [34]. Experimental demonstration of the interaction was favored by the presence of Pha, which inhibits the Ca2+-dependent lipolytic activity of GPLD1 [31,32]. Therefore, sera from rats of different metabolic states were studied for the expression of GPLD1 and its interaction with as well as displacement by PIG(-proteins) of GPI-APs (Figure 8). For this, SAW chips were generated with protein A being covalently coupled to the gold surface and a monoclonal antibody against rodent GPLD1 subsequently being immobilized at their channels (Figure 8a). Both steps (0–400 and 400–700 s, respectively) were monitored by considerable increases in phase shift. The injection of serum from obese ZDF rats (700–900 s) together with Pha (Figure 8a; blue curve) but not without Pha (turquoise curve) caused the additional upregulation of phase shift vs. buffer (red curve) in the anti-GPLD1 antibody (blue curve) but not the anti-IgG control (green curve) channel. Phase shift was further elevated by the injection of α-toxin (1000–1200 s), as well as anti-CD55 (1200–1500 s), CD59 (1500–1800 s), TNAP (1800–2100 s) and CD73 (2400–2700 s), but not AChE antibodies (2100–2400 s) in a successive fashion (Figure 8a). This is compatible with binding to rather than cleavage by rat serum GPLD1 of GPI-APs in the absence of Ca2+, among them CD55, CD59, TNAP and CD73, which all represent minor constituents of rat serum [3,4,13]. The approximately $50\%$ decreases of the α-toxin- and multiple-antibody-induced phase shifts following PIG41 and TX-100 injections (Figure 8a; blue curve) argued for the involvement of the GPI anchor glycan core and micelle-like complexes constituted by GPI-APs, cholesterol and (lyso)phospholipids [33,64], respectively, in the recognition of GPI-APs by GPLD1. The former hypothesis was confirmed by co-injection of PIG41 and serum or pretreatment of serum with bacterial PI-PLC (700–900 s), which both led to an approximately $50\%$ reduction of the serum-, α-toxin- and antibody-induced phase shift increases (Figure 8a, yellow and brown curves, respectively). This hints to the critical role of the full-length GPI anchor for the interaction of GPLD1 and GPI-APs. Again, the remaining phase shift increase is explained best by only partial deacylation of the myo-inositol residue of the GPI anchor of the GPI-APs expressed in human ELCs, which is a prerequisite for their cleavage by bacterial PI-PLC (see above). The considerable increases in phase shift upon the final injection of a polyclonal antibody cross-reactive for human and rat GPLD1 in all channels, except for those with no GPLD1 or serum injected (Figure 9a; green and red curves, respectively), confirmed the capture of GPLD1 from the serum of obese ZDF rats. Taken together, SAW sensing using chips with immobilized anti-GPLD1 antibody can be used for the analysis of the interaction of full-length GPI-APs and GPLD1 in rat serum and their displacement by PIGs. Under these conditions, the serum-, α-toxin- and anti-CD55-, CD59-, TNAP- and CD73-induced phase shift increases were most pronounced for serum from obese ZDF rats, followed by obese ZF, Wistar rats, lean ZDF, ZF rats and, lastly, lean Wistar rats (Figure 8b). The relative amounts of GPLD1 and interacting full-length GPI-APs contained in serum were determined with increasing serum volumes and the calculation of the EV50 for the half-maximal phase shift increases for each serum (Figure 8c). The lowest EV50 for obese ZDF rats was indicative of the highest amount of both serum GPLD1 and interacting full-length GPI-APs, including CD55, CD59, TNAP and CD73, but not AChE, which was followed by those for obese ZF, obese Wistar, lean ZDF, lean ZF and, finally, lean Wistar rats in that ranking order of declining amounts. The analysis of the potency of structurally different PIGs (for structural details, see Supplementary Materials, Supplementary Figure S5) in displacing GPI-APs (here CD73) from serum GPLD1 (here from obese ZDF rats) revealed that PIG41 was the most efficient, followed by PIG37, PIG45, PIG7 and, lastly, PIG1, in that ranking order of decreasing potency (Figure 8d). The EC50 of the PIGs for the half-maximal displacement of full-length GPI-APs from the serum GPLD1 of obese ZDF (Figure 8e) and lean ZF rats (Figure 8f) were the lowest for PIG41 and then increased with PIG37, PIG45, PIG7 and, lastly, PIG1. The findings that full-length GPI-APs become displaced from serum GPLD1 and presumably other GPI-binding proteins by PIGs raised the possibility of their transfer to acceptor cells upon incubation with serum and PIGs. To test for this, the numbers of GPI-APs expressed at the PMs that had been prepared from the intensively washed acceptor ELCs were measured by chip-based SAW sensing with α-toxin and anti-CD55, CD59, TNAP, AChE and CD73 antibodies. The PMs from GPI-deficient ELCs incubated with serum from obese ZDF rats (Figure 9a, turquoise curve) compared to its absence (Figure 9a, olive green curve) expressed considerably elevated amounts of total and individual GPI-APs, as reflected in the corresponding successive α-toxin- and anti-CD55, CD59, TNAP and CD73 antibody-induced phase shift increases, respectively. These were further upregulated by the presence of Pha during serum preparation (Figure 9a, dark green curve), PIG41 during serum injection (Figure 9a, black curve) and Pha and PIG41 in combination (Figure 9a, blue curve) in that ranking order of increasing efficacy. This demonstrates the transfer of CD55, CD59, TNAP and CD73 but not AChE from the serum proteins to the ELCs. The transfer was most efficient during the (i) inhibition of serum GPLD1 and concomitant stabilization of the interaction between serum GPI-binding proteins and GPI-APs by Ca2+-removal (i.e., Pha) during serum preparation, (ii) its destabilization by Ca2+ (i.e., absence of Pha) during serum injection and (iii) displacement of the GPI-APs from the serum GPI-binding proteins by PIG41 during serum injection. Phase shift increases by captured PMs, per se, did not vary significantly under either condition (Figure 9a; 0–300 s). This is compatible with only subtle mass loading onto the chip due to the transfer of GPI-APs and excludes unspecific binding of serum proteins to the PMs. Unspecific binding of serum proteins to the chip channels was assessed by the injection of serum into the chips lacking captured PMs and accounted for only 14 to $17\%$ of the α-toxin- and antibody-induced phase shifts (Figure 9a, brown curve). Nevertheless, the accompanying minor successive phase shift increases confirmed the apparent interaction of serum GPI-binding proteins with GPI-APs, in general, and CD55, CD59, TNAP and CD73 but not AChE, in particular (see Figure 8a,b). The specificity of the transfer of GPI-APs was corroborated by drastic decreases in α-toxin- and anti-GPI-AP antibody-induced phase shifts upon injection of α-toxin Sepharose beads together with the serum (Figure 9a, yellow curve). Presumably, the beads specifically bound to the GPI glycan core via α-toxin interfered with the insertion of the GPI anchor into the PMs. Pretreatment of the serum with proteinase K (Figure 9a, grey curve) and bacterial PI-PLC (Figure 9a, red curve) led to similar phase shift decreases. The latter condition was used as a background control for the following experiments (Figure 9b,e; blue and black curves). Importantly, the injection of PIG41 led to reductions of the phase shift increases for each incubation condition (Figure 9a, 1950–2150 s), which thereby compensated the corresponding α-toxin-induced increases (300–500 s). Furthermore, the final injection of TX-100 caused the complete loss of the remaining phase shift increases for each incubation condition (Figure 9a, 2150–2300 s), compatible with the transfer of full-length GPI-APs to the PMs of the GPI-deficient ELCs. The transfer of GPI-APs from serum to ELCs was strictly dependent on its volume (Figure 9b) and type, i.e., metabolic state of the rats (Figure 9c). The calculation of the volumes effective in stimulating PIG-dependent transfer of GPI-APs by $25\%$ (EV25) revealed the following ranking of increasing EV25 and, thus, declining potency: Obese ZDF > ZF > Wistar > lean ZDF > ZF > Wistar rats (Figure 9d). Furthermore, stimulation of transfer by the combination of serum and PIGs compared to serum alone was strictly dependent on the structure of the PIGs (Figure 9e). The calculation of their concentrations effective in stimulating serum-dependent GPI-AP transfer by $15\%$ (EC15) demonstrated the following ranking order of increasing EC15 and, thus, declining potency: PIG41 > 37 > 45 > 7 > 1 (Figure 9f). Taken together, these results strongly argue for the transfer of full-length GPI-APs from rat serum GPI-binding proteins, preferably from those of metabolically dysregulated obese ZDF rats, to GPI-deficient ELCs upon their PIG-induced dissociation. These data raised the possibility that glycogen synthesis is stimulated in ELCs upon exposure to serum GPI-binding proteins with bound full-length GPI-APs under conditions that induce their dissociation. The GPI-deficient ELCs incubated with serum from obese ZDF rats (in the presence of Ca2+) caused significant stimulation of glycogen synthesis, which was further increased by the presence of Pha during the preparation of the serum, presence of PIG41 and, most potently, by these two conditions in combination (Figure 10a). The elevated glycogen synthesis was reduced by the presence of α-toxin Sepharose beads during the incubation of the serum with the cells, or pretreatment of the serum with bacterial PI-PLC or proteinase K in that ranking order of increasing efficacy. In contrast, anti-CD55, CD59, TNAP, CD73 and AChE antibody Sepharose beads or phenyl Sepharose beads present during the incubation of the serum with the cells (in the presence of Ca2+) did not compromise the stimulation of glycogen synthesis by PIG41 combined with serum, which was prepared in the presence of Pha. Finally, BSA failed to substitute for serum in upregulating glycogen synthesis in ELCs in the presence of PIG41 (Figure 10a). This is explained best with the stimulation of glycogen synthesis in GPI-deficient ELCs in the course of the transfer of full-length GPI-APs to their PMs from serum GPI-binding proteins. However, transferred CD55, CD59, TNAP, CD73 and AChE apparently have no effect on glycogen synthesis. Importantly, glycogen synthesis stimulation was fostered most efficiently by the inhibition of serum GPLD1 in parallel to the stabilization of the interaction between serum GPI-binding proteins and GPI-APs by the chelating of Ca2+ during the serum preparation in combination with the efficient displacement of the GPI-APs from the serum GPI-binding proteins by PIG41 during serum injection in the presence of Ca2+ (Figure 10a). The stimulation of glycogen synthesis by PIG41 and serum GPI-binding proteins was strictly dependent on the type of serum and its volume (Figure 10b). The calculation of the volumes effective in stimulating PIG-dependent glycogen synthesis by $25\%$ (EV25) revealed the following ranking order of increasing EV25 and, thus, declining potency of the sera: obese ZDF, obese ZF, obese Wistar, lean ZDF, lean ZF and lean Wistar rats (Figure 10b). Furthermore, the stimulation of the serum-dependent glycogen synthesis by PIGs was strictly dependent on their structure (Figure 10c). The calculation of the concentrations of PIGs effective in stimulating serum-dependent glycogen synthesis by $20\%$ (EV20) demonstrated the following ranking order of increasing EC20 and, thus, declining potency: PIG41, -37, -45, -7 and -1 (Figure 10c). Taken together, these data strongly argue for the stimulation of glycogen synthesis in GPI-deficient ELCs upon transfer of full-length GPI-APs from rat serum GPI-binding proteins, preferably from those of metabolically dysregulated rats, upon their PIG-induced displacement. ## 3. Discussion The major aim of this study was to corroborate a causal relationship between the transfer of full-length GPI-APs to and the induction of anabolic effects in acceptor cells and, in addition, to identify intrinsic and/or extrinsic modulators of GPI-AP transfer, which may hint to its (patho)physiological relevance. ## 3.1. Residence at PMs of Transferred GPI-APs as a Prerequisite for the Induction of Anabolic Effects First, the kinetics of residence at and disappearance from the PMs of acceptor cells of transferred GPI-APs were compared with the time course of the stimulation of glycogen synthesis (Figure 1 and Figure 2). Transwell co-cultures of human donor adipocytes with GPI-deficient EL acceptor cells under normal conditions (Figure 1) or blockade of internalization of the transferred GPI-APs by chemical inhibitors (Figure 2a–c) or siRNAs (Figure 2d–f) revealed positive correlations between the amount of GPI-APs at PMs of the acceptor cells and the rate of their glycogen synthesis. This strongly argued for a mechanistic link of transfer of GPI-APs to and induction of anabolic effects in acceptor cells, at least under conditions of a low or missing expression of endogenous GPI-APs. The kinetics of the internalization of the transferred GPI-APs seem to be comparable to that of endogenously expressed counterparts in wild-type cells [43,47,65,66]. Thus, internalization of GPI-APs at acceptor cells may lead to underestimation of the rate of GPI-AP transfer and even mask it in case of the high “background” of endogenously expressed GPI-APs in wild-type cells. The use of GPI-deficient acceptor cells and SAW sensing, with its exquisite sensitivity, helped to overcome this issue. Alternative pulse-chase experiments with wild-type acceptor cells and radiolabeled transferred GPI-APs are more complex regarding the design and difficult to interpret due to the unknown pool sizes of the endogenous GPI-APs. Interestingly, the transfer of GPI-APs to GPI-deficient ELCs significantly increases the glucose sensitivity of the glycogen synthesis machinery and thereby enables the considerable accumulation of glycogen at a blood glucose concentration at the basal state (5 mM) in the absence of typical stimuli of glucose metabolism, such as insulin or antidiabetic SUs. In fact, ELCs do not respond at all to insulin, glimepiride or glibenclamide (see Supplementary Materials, Supplementary Figure S4c,d), most likely due to the fact of the missing expression of the insulin receptor and lipid rafts, respectively, as has already been demonstrated (see [39] and below) and/or the insulin-/SU-dependent GPI-PLC. ## 3.2. “Indirect” Transfer of GPI-APs and Its Control by Insulin and SUs Insulin and the antidiabetic SUs, glimepiride and glibenclamide, were found to interfere with the transfer of GPI-APs from human donor adipocytes to GPI-deficient EL acceptor cells in a concentration-dependent fashion at physiological and pharmacological concentrations, respectively (Figure 3), and concomitantly with transfer-induced glycogen synthesis (Figure 4). Both insulin and SU inhibition of GPI-AP transfer are most likely due to the induction of lipolytic cleavage of full-length GPI-APs at PMs of the donor adipocytes by insulin-/SU-dependent GPI-PLC. Its activation has previously been demonstrated to be more pronounced with insulin than glimepiride and, lastly, glibenclamide [67,68], which corresponds well to their ranking of the inhibition of GPI-AP transfer and transfer-induced glycogen synthesis. Unexpectedly, both insulin and SU inhibition were found to be abrogated by serum added to the transwell co-culture (Figure 5, Figure 6 and Figure 7). Previously, the inhibition of GPI-AP transfer and transfer-induced glycogen synthesis by serum, per se, has been reported [30]. Thus, the observation of the considerable transfer (Figure 5 and Figure 6) and transfer-induced glycogen synthesis (Figure 7) in the presence of insulin or SU together with serum seems to be curious, since each of these factors causes inhibition if assayed alone. Serum from obese ZDF rats, which display the most pronounced dysregulation of their metabolic state (see Supplementary Materials, Supplementary Table S2), was the most effective compared to sera from metabolically less dysfunctional rats. Pretreatment of the serum demonstrated that the full-length GPI-APs that are transferred to (Figure 7) and induced glycogen synthesis (Figure 8) in the acceptor cells in the simultaneous presence of serum and insulin or SUs do originate from serum proteins loaded with full-length GPI-APs, so-called serum GPI-binding proteins, rather than from the donor adipocytes. These findings prompted to differentiate between an “indirect” mode of transfer, with GPI-APs originating from serum GPI-binding proteins with loaded full-length GPI-APs, as assayed by transwell co-culturing in the presence of serum from metabolically deranged rats, and a “direct” mode, with GPI-APs derived from donor cells, as assayed without serum or in the presence of serum from normal rats. Thus, the “indirect” transfer critically depends on the metabolic state of the tissue/organism rather than on the release of full-length GPI-APs from the PMs of donor cells and tissues. So far, serum GPLD1 has been identified as the only GPI-binding protein in serum (Figure 8a) and found to be most abundant and/or pronouncedly loaded with GPI-APs in serum from metabolically dysregulated rats (Figure 8b,c). Recent experimental evidence has suggested that, in addition to GPLD1, certain Ca2+-dependent and -independent serum proteins operate as binding entities for full-length, as well as lipolytically cleaved, GPI-APs through the recognition of their highly conserved GPI glycan core [34]. Conversely, the inhibitory potency of serum alone on the transfer of GPI-APs, caused by their Ca2+-dependent interaction with the GPI-binding proteins and the resulting prevention from insertion into the acceptor cell PMs, is not significantly affected by the metabolic state (Figure 5). Therefore it is tempting to speculate that only a minor portion of the binding sites of the serum GPI-binding proteins is occupied by (full-length) GPI-APs, provided the levels of insulin or SUs are rather low and concomitantly the rate of release of full-length GPI-APs from PMs in that organism is not very high, i.e., in the case of a normal or only moderately deranged metabolic state. In conclusion, rat serum GPI-binding proteins seem to operate as both donors and acceptors for full-length GPI-APs that are destined for or prevented from transfer, respectively, depending on the metabolic state. This raised the question concerning the mechanism of integration of the signals elicited by insulin, SUs and the metabolic state for the differential operation of serum GPI-binding proteins as donors and acceptors of full-length GPI-APs and, in consequence, for the (pathophysiological) control of the “indirect” mode of GPI-AP transfer. A crucial finding was the concentration-dependent displacement of serum full-length GPI-APs from GPLD1 by synthetic PIGs, which structurally resemble the glycan core of the GPI anchor (Figure 8d–f). PIG41 displaying the highest structural similarity (see Supplementary Materials, Supplementary Figures S3,S5) was most potent. This led to speculation that GPI-APs lipolytically released from PMs of donor cells upon challenge with insulin or SUs, so-called PIG-proteins, act as physiological competitors for the displacement of full-length GPI-APs from serum GPI-binding proteins, such as GPLD1, thereby initiating their transfer to and anabolic effects in acceptor cells. This hypothesis was tested by incubation of GPI-deficient ELCs with serum in the presence of PIGs rather than donor cells. In fact, PIG41 and, with reduced potency, PIGs of lower structural similarity to the GPI glycan core managed to elicit GPI-AP transfer (Figure 9) and glycogen synthesis upregulation (Figure 10) in a concentration-dependent fashion. In agreement with serum proteins as a source for full-length GPI-APs transferred upon their displacement, adsorption to α-toxin Sepharose beads and lipolytic or proteolytic digestion of serum (Figure 9a and Figure 10a) eliminated both transfer and glycogen synthesis upregulation, and both were found to be strongly correlated to the serum volume and the metabolic state of the rat donors (Figure 9b–d and Figure 10b), with serum from obese ZDF rats, apparently loaded with the highest amounts of GPI-APs (Figure 8b,c), being most potent. The apparent correlation between PIG-induced GPI-AP transfer and glycogen synthesis further argued for their mechanistic coupling. The components that are specifically involved in this coupling, in particular the GPI-APs transferred and their actions downstream to the glycogen synthesis machinery without involvement of their internalization, remain to be elucidated in future studies, which may continue relying on transwell co-cultures and SAW sensing, in part. Previous studies have shown that in the absence of serum the release of full-length GPI-APs from the PMs of donor cells in response to endogenous or exogenous stimuli is rate-limiting for “direct” transfer rather than their insertion into the PMs of acceptor cells, which proceeds with fast kinetics [48,69]. Therefore, it is reasonable to assume that also in the presence of serum the observed considerable time requirement for both insulin- and glimepiride-stimulated “indirect” transfer of GPI-APs, as measured in transwell co-cultures (Figure 5e,f), does not rely on the insertion step but rather is caused by the process of their dissociation from the serum GPI-binding proteins upon stimulation of the donor cells by insulin and glimepiride. However, the activation of the insulin-/SU-dependent GPI-PLC and the resulting lipolytic conversion of GPI-APs to PIG-proteins, as the competitors of full-length GPI-APs for binding to the serum GPI-binding proteins, are known to represent rapid processes [22,23,70]. Consequently, de novo synthesis and transport along the secretory pathway of full-length GPI-APs, as precursors for the PIG-proteins, in insulin-responsive donor cells may represent the rate-limiting step for the insulin-/SU-stimulated “indirect” transfer of GPI-APs from serum GPI-binding proteins to acceptor cells. ## 3.3. Contribution of the “Indirect” Intercellular Transfer of GPI-APs to Insulin and SU Action Both insulin and antidiabetic SUs lower blood glucose by the stimulation of glucose uptake and incorporation into lipids and glycogen in adipose, muscle and liver tissues, albeit through engagement of completely different molecular mechanisms. Insulin activates canonical signaling from the insulin receptor via insulin receptor substrate and phosphatidylinositol-3 kinase (PI-3K) downstream to intracellular Glut4 vesicles, which ultimately fuse with PMs, as well as to key enzymes of glycogen and lipid synthesis, which became activated (for a review, see [71,72]). SUs bind to sulfonylurea receptors at PMs of pancreatic ß-cells, thereby inducing their depolarization and accompanying Ca2+-dependent exocytosis of insulin-containing granules (for a review, see [73,74]). Importantly, SUs of the 1st, 2nd and 3rd generations, such as tolbutamide, glibenclamide and glimepiride, respectively, exhibit considerable differences in structure (see Supplementary Materials, Supplementary Figure S2) and pharmacological activity. Tolbutamide lowers blood glucose by stimulation of insulin secretion from pancreatic ß-cells, exclusively [74,75,76]. In contrast, glibenclamide and glimepiride elicit blood glucose decrease by induction of insulin release to a major degree [77,78], as well as to a minor degree by insulin-independent stimulation of transport and nonoxidative metabolism of glucose in adipose [57,68,79,80] and muscle [80,81,82] cells in vitro, and in animals [69,78] and patients [83,84,85,86,87]. Interestingly, with regard to the insulin-independent insulin-mimetic activity at peripheral target cells, glimepiride turned out to be significantly more potent than glibenclamide both in vitro [57,67,68,79,81,88] and in vivo [46,89,90,91,92], whereas glibenclamide is more efficient in releasing insulin (for a review, see [67,84,93,94]). The molecular mechanism underlying the initiation of this insulin-mimetic so-called extrapancreatic activity of glimepiride has been attributed to engagement of the insulin-/SU-dependent GPI-PLC at PMs of cells at peripheral tissues [22,23,28] and the resulting generation of cleavage fragments derived from free GPI lipids or GPI anchors of GPI-APs with structural similarity to PIGs or PIG-proteins, respectively. Those molecules have been postulated to act as intracellular soluble mediators of metabolic insulin-mimetic action (for a review, see [25,26,51,95,96,97,98]). In fact, the chemically synthesized PIGs used in this study [99,100] or other structurally similar ones [101,102,103] and PIG-proteins, which were prepared from human acetylcholinesterase [104], trypanosomal VSG [105] and yeast Gce1p [106,107], have been demonstrated to stimulate glucose transport and lipid and glycogen synthesis upon incubation of adipocytes, myocytes and hepatocytes in medium containing serum (cultured cells) or (minute amounts of) blood (left in course of preparation of primary cells). As shown in this study, both insulin and glimepiride stimulate glycogen synthesis in human ELCs but only in transwell co-culture upon simultaneous incubation with adipocytes and serum. ELCs lack both the insulin receptor [39] and lipid rafts (Müller and Müller, unpublished data), which are known to mediate activation of the insulin-/SU-dependent GPI-PLC by glimepiride. Its activation by insulin or glimepiride in insulin target cells has been amply documented, as reflected in the release of GPI-APs, among them CD73, Gce1, lipoprotein lipase and alkaline phosphatase, from the surface of isolated and cultured muscle, liver and adipose cells [22,23,28]. Importantly, its activation by glimepiride does not involve canonical (wortmannin-sensitive) insulin signaling (see Supplementary Materials, Supplementary Figure S4b) but seems to rely on the engagement of a nonreceptor tyrosine kinase anchored at the inner leaflet of PMs, within so-called lipid rafts. Hydrophobic glimepiride molecules have been demonstrated to spontaneously intercalate into this nano- or microdomains [108,109,110]. They are characterized by resistance towards detergent solubilization and low buoyant density due to the presence of high concentrations of cholesterol, glycolipids and GPI-APs equipped with long-chain saturated fatty acids [8] (for a review, see [9,10,11,12]). Glimepiride intercalation leads to the redistribution of the lipid raft constituents including the GPI-PLC and its PI-3K-insensitive activation. Importantly, the stimulation of lipid synthesis in human adipocytes was completely abrogated by the downregulation of the insulin-/SU-dependent GPI-PLC (Supplementary Materials, Supplementary Figure S4b) using a synthetic inositol derivative, GPI2350, which inhibits bacterial, trypanosomal and serum (G)PI-PLC/D with high potency and selectivity and reduces the insulin-/SU-inducible lipolytic release of GPI-APs from the surface of intact rat adipocytes [52,92]. In contrast, the inhibition of the insulin-/SU-dependent GPI-PLC failed to interfere with the insulin stimulation of lipid synthesis in human adipocytes (Supplementary Materials, Supplementary Figure S4a). Thus, it is tempting to speculate that activation of the insulin-/SU-dependent GPI-PLC is a prerequisite for the induction of anabolic effects in insulin nontarget cells, such as ELCs, or in cells lacking insulin receptor or with defective insulin signaling, rather than in insulin target cells. Thus, insulin and glimepiride share activation of the insulin-/SU-dependent GPI-PLC in adipocytes, resulting in the release of PIG-proteins from full-length GPI-APs of adipocyte PMs. These PIG-proteins apparently operate as physiological competitors for the displacement of (nonadipocyte) full-length GPI-APs from serum GPI-binding proteins rather than as intracellular mediators of insulin-like action as originally thought (see for this view [25,26,96,97]). The displaced full-length GPI-APs subsequently transferred to PMs of acceptor cells, rather than the generated PIG-proteins themselves induce the reported anabolic effects. Thus, glimepiride seems to exert its insulin-mimetic effects via the “indirect” mode of GPI-AP transfer. Importantly, in both in vitro [67,68,79,80,81,94] and clinical studies [85,86,87] the insulin-mimetic action on peripheral cells and tissues has been shown to be more pronounced for glimepiride compared to glibenclamide and tolbutamide. The same ranking order of declining potency for SUs of the 3rd, 2nd and 1st generations was found in the present study for the stimulation of GPI-AP transfer (Figure 6a,b) and glycogen synthesis (Figure 7c,d) in the presence of serum. These correlations represent important hints to the relevance of the “indirect” mode of transfer of GPI-APs from serum GPI-binding proteins to peripheral cells for the insulin-independent (extrapancreatic) blood glucose-lowering activity of antidiabetic SUs which, however, must be further delineated in future animal studies. At variance with glimepiride, insulin exerts its metabolic effects in insulin target cells predominantly via engagement of canonical insulin signaling. This conclusion was exemplified best by the lacking effect of GPI2350 on insulin stimulation of lipid synthesis in 3T3 adipocytes [52], which excludes a major role of the insulin-/SU-dependent GPI-PLC in metabolic insulin signaling and action in insulin target cells (see Supplementary Materials, Supplementary Figure S4a). The minor portion of the anabolic effects of insulin mediated by the “indirect” mode of GPI-AP transfer is most likely over-run by the considerably more potent canonical signaling to and activation of the anabolic effector systems. ## 3.4. The Interplay between the “Indirect” and the “Direct” Modes of GPI-AP Transfer The differentiation between the “indirect” mode of GPI-AP transfer in the presence of serum GPI-binding proteins and insulin or antidiabetic SUs, as described in the present study, and the “direct” mode in their absence, as reported previously [30], raises the possibility that the two modes are linked to distinct physiological roles. The requirement for the absence of serum GPI-binding proteins for the “direct” mode suggests that this GPI-AP transfer occurs between cells of the same tissue depot and over short distance (i.e., across interstitial spaces), exclusively and solely depends on the efficacy of the release of full-length GPI-APs from donor cells and insertion into PMs of acceptor cells in the immediate neighborhood. For both steps, the size and metabolic state of the donor and acceptor cells has previously been found to be critical, with those of large and small sizes or from metabolically deranged and normal rats favoring the release and insertion, respectively [30,47]. In the case of adipose and liver tissue depots, GPI-AP transfer may result in the upregulation of basal lipid and glycogen synthesis, respectively, in “empty” acceptor cells, which take over the burden of lipid and glycogen storage from the neighboring donor cells with completely filled lipid and glycogen stores, respectively. In fact, the heterogeneity of the size and metabolic state of cells within the same adipose or liver tissue depots has been amply documented [111,112]. Thus, the “direct” mode of GPI-AP transfer may be regarded as a mechanism to compensate for the unequal distribution of glycogen and lipid synthesizing capabilities, which could be associated with unequal expression of “relevant” GPI-APs, between different liver or adipose cells within the same tissue depots. Furthermore, upregulation of lipid and glycogen synthesis in insulin target tissues, such as adipose and liver, in response to the “direct” transfer of GPI-APs may be interpreted as a mechanism to override peripheral insulin resistance in type II diabetic patients to a certain (limited) degree. The “Indirect” transfer of full-length GPI-APs from donor to acceptor cells located at distinct tissue depots over long distance along the circulation engages the interaction with and dissociation from serum GPI-binding proteins and, therefore, depends on several parameters: (i) concentration of full-length GPI-APs in blood, which is determined by their release from tissues in response to the metabolic state; (ii) concentration of GPI-binding proteins in blood; (iii) concentration of lipolytically cleaved GPI-APs (i.e., PIG-proteins) in blood, which is determined by the activation state of the insulin-/SU-dependent GPI-PLC; and (iv) efficacy of the insertion of full-length GPI-APs into the acceptor cell PM. Insulin and/or SUs will block the “direct” mode of GPI-AP transfer in the course of the lipolytic removal of their GPI anchor and in parallel stimulate the “indirect” mode by inducing the dissociation of full-length GPI-APs from serum GPI-binding proteins. Thus, the insulin-, SU- and metabolic state-controlled integration of parameters (i–iv) will ultimately determine the “direct” vs. the “indirect” mode of GPI-AP transfer. In the metabolically dysregulated state, such as type II diabetes and obesity, the “indirect” mode will override the “direct” one due to the (i) upregulation of the release of full-length GPI-APs from PMs of metabolically dysregulated (insulin target) cells and tissues (e.g., adipose and liver); (ii) interaction of those with serum GPI-binding proteins, which are systemically distributed along the circulation; (iii) generation of lipolytically cleaved GPI-APs (PIG-proteins) by insulin-/SU-dependent GPI-PLC in the hyperinsulinemic/hyperglycemic state and/or insulin or glimepiride therapy, which displace full-length GPI-APs from the serum GPI-binding proteins; and (v) final insertion of the full-length GPI-APs into PMs of metabolically dysregulated acceptor cells, including noninsulin responsive or noninsulin target cells. Thus, it is conceivable that the “indirect” mode of GPI-AP transfer operates in insulin responsive, as well as nonresponsive cells, i.e., in acceptor cells lacking canonical insulin signaling and located far away from the insulin responsive donor cells. It may thereby lead to the stimulation of glycogen and lipid synthesis that is additive to and independent of canonical insulin signaling. In the future, it will be interesting to investigate whether other hormonal and therapeutic signals or extrinsic factors affect the “direct” and “indirect” modes of the intercellular transfer of GPI-APs and the resulting shift of the acceptor cell phenotype. Oxidative challenge may represent a (patho)physiological candidate and this even more so because an important role of glucose as a major antioxidant, in general, and of glycogen stores in the resistance of cells towards oxidative stress, in particular, has been suggested [113]. Moreover, it remains to be clarified (i) whether cellular phenotypes other than the anabolic state become transmitted by intercellular protein transfer, (ii) what cells/tissues are involved, (iii) what mechanisms (“direct” or “indirect”) are engaged and (iv) what GPI-APs are transferred. Regarding the induction of the anabolic phenotype in ELCs and adipocytes, the present data strongly argue that the relevant GPI-APs are different from CD55, CD59, TNAP, CD73 and AChE, which are transferred along with the phenotype, however, apparently without any mechanistic coupling to it. Unfortunately, the repertoire of commercially available antibodies against GPI-APs, suitable for their immune depletion during transwell co-culture or from serum GPI-binding proteins with resulting blockade of transfer in parallel to phenotypic changes in the acceptor cells, is rather limited. Thus, an experimental alternative may represent downregulation of individual GPI-APs by siRNAs in donor cells of transwell co-cultures at large scale if the lack of their expression is compatible with donor cell viability. ## 4.1. Ethical Approval All experimental procedures regarding the handling of animals (housing of and blood sampling from rats, see [56]) were conducted in accordance with the German Animal Protection Law (paragraph 6) and corresponded to international animal welfare legislation and rules. ## 4.2. Transwell Co-Culture of Human Adipocytes and GPI-Deficient ELCs Transwell co-culture was used with GPI-deficient ELCs as acceptor cells seeded at the bottom of 12-well tissue culture plates (Falcon Companion TC Plate, No. 353503, Falcon/Corning, Tewksbury, MA, USA, for 1.4–2.3 mL medium) and human adipocytes of lipid-loading stage II or IV [30], differentiated from hADSCs (see below), as donor cells seeded in the 12-well cell culture inserts (Falcon Cell Culture Insert, No. 353103, for 0.4–1.0 mL medium). This enabled the detection of the transfer of full-length GPI-APs between donor and acceptor cells at a distance (from the membrane to the bottom of wells) of 0.9 mm through a porous membrane (pore size 1.0 µm, high pore density 1.6 ± 0.6 × 106 pores/cm2, polyethylene terephthalate track-etched, transparent). The hADSCs were expanded in “hADSCs Growth Medium” (iXCells Inc., San Diego, CA, USA) for 3–4 passages, as described in detail previously [30,114], and then seeded at 5 × 103 cells/cm2 in the transwell inserts (12-well plate formate) and thereafter grown to confluence with medium change every 2–3 days until the cells reached 70–$80\%$ confluence. For this, a cell culture insert was removed from the package with sterile forceps and then gently placed into the bottom companion well culture plate, taking care to avoid trapping air under the insert by tilting the insert while lowering it onto the well. Upon correct positioning, the inserts with the flanges rested in the notches on the top edge of each well in diagonal arrangement. For seeding, the cells and 1 mL of medium were added to the cell culture insert at the density given above and cultured under routine conditions. Thereafter, hADSCs were differentiated into human adipocytes in vitro using “hADSC Adipocytes Differentiation Medium” (iXCells Inc.), as reported previously [30], until medium or heavy lipid-loading (stage II or IV, respectively) was reached (i.e., Oil Red-stained lipid droplets accounted for $50\%$ or more than $80\%$ of the cytoplasmic area, respectively). Following washing with Dulbecco’s modified *Eagle medium* (DMEM, Gibco-BRL, Thermo Fisher Scientific, Waltham, MA, USA) containing $1\%$ sodium pyruvate, 100 U/mL of penicillin and 100 µg/mL of streptomycin, the human adipocytes were used for transfer experiments (lipid-loading stage IV for routine use, stage II as indicated). Mutant ELCs, incapable of the coupling of nonacetylated glucosamine to phosphatidylinositol during GPI anchor biosynthesis and, thus, completely deficient in expression of GPI-APs [35,39], were seeded at 0.3–1.2 × 106 cell/mL in the bottom wells (12-well formate) in RPMI 1640 medium supplemented with $10\%$ FBS and $1\%$ penicillin/streptomycin (DMEM, Gibco-BRL, Thermo Fisher Scientific, Waltham, MA, USA) and grown to confluence. The ELCs were washed two times with Ca2+-free PBS and then two times with serum-free medium for transfer experiments. For initiation of transfer, the inserts were first moved to one side using a sterile 1 mL pasteur pipet to remove media from above and below the membrane. Subsequently, 2 mL and 1 of fresh medium containing or lacking serum, as indicated, were added to the wells of the bottom companion and insert cell culture plates, respectively. Following incubation under the conditions indicated, the insert wells were removed and then the medium was aspirated from the bottom wells. Thereafter, the ELCs of the bottom wells were rinsed two times with 1 mL each of PBS and then used for the preparation of PMs to determine the amount of GPI-APs for the assay of GPI-AP transfer or for incubation with D-[U-14C]glucose (PerkinElmer, Waltham, MA, USA) to assay glycogen synthesis. ## 4.3. Assay of GPI-AP Transfer PMs were prepared from the ELCs in the bottom wells of transwell co-culture, as described previously [30], and then immobilized at the chip surface by ionic and covalent capture with high efficacy. For ionic capture, PMs (0.2 mg protein per mL of 2 mM Ca2+, 100 mM NaCl, 10 mM Hepes/NaOH, pH 7.5) containing positively charged, negatively charged or zwitterionic phospholipids or combinations thereof were injected into the chips with uncoated negatively charged and highly hydrophilic TiO2 channels together with immobilization buffer (10 mM sodium acetate, pH 5.5) at a flow rate of 25 μL/min for 4 min at 30 °C, which fostered the formation of salt bridges between the chip surface and the PM phospholipids. After the termination of the flow for 20 min at 30 °C for the stabilization of immobilization, the chips were washed with 10 mM Hepes/NaOH (pH 7.5) and 100 mM NaCl at a flow rate of 150 μL/min for 20 min at 30 °C. For the subsequent covalent capture via the protein moieties of GPI-APs, as well as the extracellular domains of TMPs, the microfluidic channels of the uncoated TiO2 chips were primed with three injections of 250 μL each of immobilization buffer at a flow rate of 50 μL/min. Then, the channel surface was activated by a 250 μL injection of 0.2 M EDC and 0.05 M Sulfo-NHS (Pierce/ThermoFisher Scientific, Waltham, MA, USA; mixed from 2×-stock solutions right before the injection) at a flow rate of 50 μL/min. After a waiting period of 3 min (flow rate 0) and subsequent washing of the channels with two 300 μL portions of PBS containing 2.5 mM EGTA (PBSE) at a flow rate of 180 μL/min, the residual activated groups on the channel surface were capped by injecting 200 μL of 1 M ethanolamine (pH 8.5) at a flow rate of 60 μL/min. Thereafter, the channels were washed two times with 125 μL of PBSE each at a flow rate of 150 μL/min and then two times with 160 μL of 10 mM Hepes/NaOH (pH 7.5) each at the same flow rate. The amounts of GPI-APs and TMPs were determined by sequential injection of 75 μL of appropriate antibodies (diluted as given in Supplementary Materials) at a flow rate of 15 μL/min according to the order indicated in the figures. Finally, for demonstration of anchorage by GPI at the immobilized PMs of the acceptor ELCs, 75 μL of PI-PLC (Bacillus cereus, 5 ng; Merck/Sigma-Aldrich, Darmstadt, Germany) at a flow rate of 15 μL/min were injected, followed by injection of three portions of 220 μL of $0.1\%$ (w/v) Triton X-100 at a flow rate of 200 μL/min for the demonstration of incorporation into the phospholipid bilayer of the immobilized PMs. Phase shifts are given upon correction for unspecific interactions (no PMs immobilized) and normalization for the varying efficacy in immobilization of the PMs between different chips [33]. ## 4.4. Assay of Glycogen Synthesis After disassembly of the transwell co-culture, the ELCs of the bottom wells were washed two times with KRB containing $0.1\%$ BSA and then incubated (120 min, 37 °C) with 0.5 mL of the same buffer containing D-[U-14C]glucose (PerkinElmer, Waltham, MA, USA, 250-360 mCi/mmol) and 0.1 to 15 mM glucose, as indicated, and a constant specific radioactivity (0.1 to 15 μCi per test) in a shaking water bath, as has been previously described [30]. The assay was terminated by placing the bottom plate on ice (20 min) and subsequent three washings of the cells with 1 mL of ice-cold PBS each. Thereafter, the ELCs were detached with Accutase (Merck/Sigma-Aldrich, Darmstadt, Germany) and then homogenized (0 °C, ten up- and down-pipettings with a 0.1-mL pipette) in 0.1 mL of 25 mM Tris/HCl (pH 7.4), 5 mM EDTA, 100 mM NaF and 0.1 mM PMSF. The homogenate was then centrifuged (10,000× g, 20 min, 4 °C). Then, 40 µL aliquots of the supernatant were transferred into new 2.5 mL tubes, supplemented with 20 µL of 5 mg/mL “carrier” glycogen and 1 mL of $30\%$ KOH, and then heated (45 min, 100 °C) and subsequently adjusted to $70\%$ ethanol by the addition of 1.5 mL of $100\%$ ethanol. After incubation (4 h, −20 °C), the samples were centrifuged (2000× g, 15 min, 4 °C). The precipitated glycogen pellets were washed four times with $70\%$ ethanol and then dissolved in 200 µL of distilled water. Three 60 µL portions were spotted on 2 cm2 filter papers, which were dried before liquid scintillation counting. The amount of glucose incorporated into glycogen was calculated for each aliquot of the homogenate after the subtraction of the radioactivity measured for a “mock” incubation of cells with D-[U-14C]glucose together with KOH and subsequent identical processing. ## 4.5. siRNA Transfection of Human Adipocytes Human adipocytes were transfected with siRNAs targeting human CDC42, Rac1 or RhoA gene with lipofectamine RNAiMAX according to the manufacturer’s instructions (ThermoFisher Scientific, Waltham, MA, USA). For control of the silencing efficacy, total RNA was extracted for qPCR determination at 48 h after transfection. This protocol was based on the SYBR Green detection system. Primers were used at 10 pM each. The mix included 10 μL of SYBR Green qPCR Mix, 0.4 μL of each primer, 8.2 μL of sterile PCR grade water. Next, 1 μL of template cDNA was added in a final volume of 20 μL. The samples were amplified as follows: an initial denaturation step at 95 °C for 2 min, followed by 40 cycles at 95 °C for 15 s (denaturation) and 60 °C for 1 min (annealing and elongation). After amplification, melting curve analyses were performed to evaluate the silencing efficacies in comparison to scrambled siRNA, which were considered to be $0\%$. ## 4.6. Immobilization of Anti-GPLD1 Antibody at the Chip Surface For the generation of chips that capture GPLD1, a 200 µL portion of protein A (50 mg/mL in PBS, 0.1 mM EDTA, $10\%$ glycerol) diluted 10-fold in immobilization buffer (10 mM sodium acetate, pH 5.5) was injected at a flow rate of 40 µL/min into the channels of activated (0.2 M EDC and 0.05 M Sulfo-NHS, mixed from 2×-stock solutions right before injection) long-chain 3D carboxymethyl (CM) dextran chips (SAW Instruments Inc., Bonn, Germany) in a SamX instrument (SAW Instruments Inc., Bonn, Germany). The residual activated groups on the chip surface were capped by injecting 100 µL of 1 M ethanolamine (pH 8.5) at a flow rate of 60 µL/min. Thereafter, 50 µL of monoclonal anti-GPLD1 antibody (diluted 1:750 with running buffer) or as a “blank” control IgG (same concentration) were injected at a flow rate of 15 µL/min. After washing with 200 µL of PBST at a flow rate of 120 µL/min, 100 µL of serum, diluted 20-fold with PBST, was injected at a flow rate of 30 µL/min. Measurement of the phase shift was performed at 22 °C. The start and termination points of the sample injections or washing cycles are indicated with green and black arrows, respectively, in the figures. The chips were regenerated by successive injections of 60 µL of 10 mM glycine (pH 3.5) and 30 µL of 4 M urea with waiting for 5 min after each injection and the final injection of 300 µL of regeneration buffer (PBS, pH 7.4, 1 M NaCl, $0.03\%$ Tween and $0.5\%$ glycerol) and 300 µL of PBST. Chips with immobilized protein A were used to up to 24 times without significant loss of capacity of capturing of GPLD1. ## 4.7. Statistical Analysis All numerical data are presented as the means ± SD. The statistical significance was calculated using GraphPad Prism6 software (version 6.0.2, GraphPad Software, New York City, NY, USA) on the basis of ordinary one-way/two-way ANOVA, tested by Sidak’s multiple comparison tests. p ≤ 0.05 was considered to be significant. ## 4.8. Miscellaneous The preparation of PMs [92], protein determination [57] and SAW sensing with long-chain 3D CM-dextran sam®5 chips using a SamX instrument (SAW/Nanotemper, Bonn/Munich, Germany) and evaluation [56,64] were performed as previously described in detail. ## 5. Conclusions The main findings of the present study are as follows: (i) the transfer of GPI-APs from human adipocytes to blood cells stimulates basal glycogen synthesis; (ii) insulin and antidiabetic SU drugs inhibit the transfer and stimulation of glycogen synthesis; (iii) serum GPI-binding proteins counteract the insulin and SU inhibition of transfer and glycogen synthesis stimulation; (iv) GPI-AP transfer proceeds via two (i.e. “direct” and “indirect”) modes that differ regarding the absence or presence of serum GPI-binding proteins, respectively, and the origin of the transferred full-length GPI-APs (donor cells or serum GPI-binding proteins, respectively). It may be insightful to compare the “indirect” mode of transfer of GPI-APs, which presumably reflects the physiology of mammalian organisms, with other modes of the intercellular transfer of membrane proteins, in general, and GPI-APs, in particular: (i) the “direct” mode of GPI-AP transfer lacks control by exogenous cues, such as serum proteins, hormones, and drugs, and only operates between cells of the same tissue depot and over short distance; (ii) for the transfer of membrane proteins via extracellular vesicles between the same or different cell types/tissues over a short or long distance, a control by exogenous signals has not been described so far; (iii) the same holds true for the short-distance delivery of the complete set of membrane systems including their constituting membrane proteins, among them PMs, endoplasmic reticulum, mitochondria, etc., from somatic mother to daughter cells along cell division or from gametes to zygotes along cell fusion. Thus, the “indirect” mode of the intercellular transfer of full-length GPI-APs may be of special biological relevance within the repertoire of nongenetic inheritance of biological matter since it is under control of environmental factors. Meanwhile, many studies have addressed the role of the protein vs. the GPI moieties of GPI-APs in human health and disease (e.g., [115]; for a review, see [9,116]). Furthermore, the interaction with and displacement by PIGs from human serum proteins, among them GPLD1, of full-length human GPI-APs, among them CD55, TNAP and AChE, have been demonstrated (Müller and Müller, manuscript in preparation). Those findings together with the present ones obtained with human cells and serum from a rat model for a human disorder may foster future experimentation as to whether the (“indirect” and/or “direct”) intercellular transfer of GPI-APs has (a) (patho)physiological role(s) in humans. ## References 1. 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--- title: Initial Evidence for Positive Effects of a Psychological Preparation Program for MRI “iMReady” in Children with Neurofibromatosis Type I and Brain Tumors—How to Meet the Patients’ Needs Best authors: - Liesa Josephine Weiler-Wichtl - Jonathan Fries - Verena Fohn-Erhold - Agathe Schwarzinger - Angelika Elisabeth Holzer - Thomas Pletschko - Julia Furtner-Srajer - Daniela Prayer - Paul Bär - Irene Slavc - Andreas Peyrl - Amedeo Azizi - Rita Hansl - Ulrike Leiss journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003409 doi: 10.3390/jcm12051902 license: CC BY 4.0 --- # Initial Evidence for Positive Effects of a Psychological Preparation Program for MRI “iMReady” in Children with Neurofibromatosis Type I and Brain Tumors—How to Meet the Patients’ Needs Best ## Abstract To provide an effective alternative to sedation during MRI examinations in pediatric cancer and NF1 patients, the aims of the present study were to [1] exploratively evaluate a behavioral MRI training program, to [2] investigate potential moderators, as well as to [3] assess the patients’ well-being over the course of the intervention. A total of $$n = 87$$ patients of the neuro-oncology unit (mean age: 6.83 years) underwent a two-step MRI preparation program, including training inside the scanner, and were recorded using a process-oriented screening. In addition to the retrospective analysis of all data, a subset of 17 patients were also analyzed prospectively. Overall, $80\%$ of the children receiving MRI preparation underwent the MRI scan without sedation, making the success rate almost five times higher than that of a group of 18 children that opted out of the training program. Memory, attentional difficulties, and hyperactivity were significant neuropsychological moderators for successful scanning. The training was associated with favorable psychological well-being. These findings suggest that our MRI preparation could present an alternative to sedation of young patients undergoing MRI examinations as well as a promising tool for improving patients’ treatment-related well-being. ## 1. Introduction Magnetic resonance imaging (MRI) can be a demanding and stressful procedure for both children and their parents, requiring patients to lie motionless in a narrow, noisy tube [1,2]. Especially young children tend to have difficulties with self-restraint; the longer the procedure, the higher the risk for poor image quality due to motion artifacts, since the amount of patient movement within the scanner determines image quality and accuracy [3]. Possible strategies to reduce the risk of patient movement in young children are general anesthesia (GA) and sedation. In addition to requiring additional time, hospital bed and highly trained staff [4], sedation is also associated with rare, yet serious, well-documented adverse effects such as respiratory complications, aspiration, cardiac arrest, and vomiting [5,6]. A growing body of evidence supports an alternative approach: behavioral preparation and training methods show promising results in reducing the necessity of GA in young children [7]. Most studies have focused on how to increase compliance for non-sedated MRIs in various neurological and non-neurological patient groups (e.g., patients with diabetes, sickle-cell-disease, obsessive compulsive disorder) and healthy controls. However, very young children, children with developmental disorders, attention problems, or cognitive issues were often excluded in these samples. Specifically, only a few studies have included children with attention deficit hyperactivity disorder (ADHD), developmental delay, autism spectrum disorders (ASD), neurological impairment, anxiety, and other problems to lie still in the sample for the development and evaluation of preparation for MRI examinations [8,9,10]. The results illustrate the need for a differentiated consideration of predicting factors to increase compliance and to successfully comply with an MRI examination. Cognitive and psychological issues are common and well-documented in pediatric brain tumor survivors and children with neurofibromatosis type 1 (NF-1), who are at an increased risk of developing a brain tumor. These issues include problems with attention, memory, processing speed, visuomotor function, learning difficulties, age related issues, as well as disease related stress factors (such as the recurrent experience of medical procedures) for patients and parents [11,12,13,14]. In brain tumor survivors, medical follow-up requires up to four regular MRI procedures per year [15]. The average duration of an MRI examination for these purposes is 30–60 min depending on which body parts need to be examined (brain MRI, brain and spinal cord MRI) [16,17]. Considering the frequency and duration of MRI examinations, as well as the specific challenges arising due to developmental, cognitive, or emotional issues, these children would considerably benefit from customized preparation programs that avoid the additional emotional and physical strain of GA [18,19,20]. The methods and aims of preceding studies on the topic are heterogenous, mostly focusing either on the reduction of sedation rates or on limiting movement artifacts to improve MRI image quality in pediatric patients, e.g., [10,21,22,23]. Preparations with a mock MRI, e.g., [7,24] or other techniques such as video animation [25,26], play therapy [26,27] or animal-assisted therapy [28] to prepare children for an MRI, as well as exposure to distracting techniques before [25] and during the MRI scan, e.g.,[23] have been demonstrated to effectively reduce the need for sedation. Furthermore, indirect effects have been reported, such as elevated sensitivity to the topic in the radiology department [25,29] and reduced waiting time for MRI due to fewer patients needing sedation/anesthesia [26]. However, little research has investigated the underlying methods of successful non-sedated MRI and the effects of MRI preparation programs on the psychological well-being of children undergoing scans. So far, temperament, medical experience, and parental expectations have been linked to higher MRI success [10]. Furthermore, some studies have focused on the reduction of anxiety and distress via appropriate MRI preparation [25,28,30]. Thus, the purpose of the present study was to retrospectively evaluate the effectiveness of MRI training “iMReady”, which aims to address the objectives discussed above, in addition to investigating the underlying mechanisms for non-sedated MRI success. Furthermore, the psychological effects of the training on its participants were analyzed prospectively to derive specific needs of a neuro-oncological patient group comprised of brain tumor and NF-1 patients. ## 2.1. Development and Content of the Training “iMReady” The first version of the MRI training procedure “iMReady” was originally developed in 2008 and further adapted to become the standard of care at the local neuro-oncology unit. Its aim was to provide all children and adolescents with anticipatory guidance and developmentally appropriate preparatory information about the MRI, thereby implementing two standards formulated in 2015 in the Psychosocial Standards of Care Project for Childhood Cancer [18,20]. In line with the standards, the program addresses a wide variety of psychological concepts to decrease the psychosocial challenges caused by medical and diagnostic procedures and to increase compliance in MRI procedures overall, with or without GA. The incorporated concepts include psychoeducation, resource- and solution-oriented techniques, communication techniques, relaxation techniques, and reflection. At the beginning of the training, every child receives an MRI training booklet containing important information about the MRI in a standardized, age-appropriate and visually appealing way. The booklet also provides practical material with enhanced stimulating elements to encourage the child to explore actively and multimodally, thereby contributing equally to the developmental and neuropsychological aspects of learning. Psychoeducational, active, practical, and reflective aspects are covered in two face-to-face training sessions. To reinforce the comprehension of the training process and to promote self-efficacy, the child is encouraged to bring the booklet to every session as well as to the diagnostic MRI. Considering age, developmental aspects, and interdisciplinary evaluation, a clinical psychologist or pediatrician may decide whether a patient qualifies for MRI training; children are referred to the training during a routine visit in the interdisciplinary outpatient clinic. Parents are informed about the purpose, conditions, and procedure of the training and encouraged to actively participate as co-therapists in the training to guarantee transfer and reinforce the effect of the training. The MRI training sessions are performed by an interdisciplinary team of medical doctors, radiologists, and nurses, but coordinated by a clinical psychologist trained to consider developmental and motivational aspects and possible cognitive, emotional, or social deficits in the participants. The training program consists of the following two sessions:[1]The primary goal of the first session is the psychological and medical preparation, while also discussing the pros and cons about having the MRI without anesthesia. Hence, in addition to basic information and procedural knowledge about the MRI, instructions regardin appropriate clothing, metal objects, lying still, and the sound of the MRI are discussed with the participants. Role play techniques are used to build and practice coping strategies and action control. To further explore the topic, the children receive instructions for exercises, which they are asked to complete at home together with their parents. The homework is composed of two exercises: building a shoebox-sized paper MRI model (e.g., suitable for LEGO figurines) and continuing the role-play techniques with the paper model (Figure 1).[2]In session two, the topics of the previous session are repeated before self-instruction and relaxation techniques for children are introduced and practiced. *In* general, it would be beneficial if MRI companies would build dummy machines for performing the training, in order not to occupy the scanning facilities. Considering available options, children and parents undergo a practice run in a 1.5 Tesla MRI (Siemens Aera) to build a relationship with MRI staff and to explore the MRI environment. During the practice run, children and parents can experience the MRI procedure and develop further helping strategies such as the use of additional blankets or pillows, a mirror on the head coil, or additional earplugs. The child has the opportunity to experience the room where the MRI takes place, the changing positions of the scanner bed, as well as the positions of parent, psychologist, and scanning administrator in a procedure that is convenient for them, involving age-appropriate communication methods. This includes methods for communication between the child and parent and/or team, which are developed individually (e.g., a hand signal from the child to the parent who is holding the hand or handset). One MRI sequence of approximately five minutes is performed, which gives children and parents the opportunity to experience the sound of the magnet and to make a first evaluation about picture quality. Finally, children, parents, and the psychologist reflect on the MRI training and together they decide whether the examination will be done with or without sedation. Children and parents are further instructed to regularly repeat and practice the acquired skills at home, while using relaxation, self-control, and operant techniques. More details on the proceedings can be found in Figure 1. In 2017 the training was integrated into a quality improvement project (“Mein Logbuch—Ich kenne mich aus!”/“My Logbook—I know my way around!”) aiming to guide children throughout the entire disease trajectory (Trial registration identifier: NCT04474678). This is a method to apply the evidence-based S3 guideline for Psychosocial Care in Pediatric Oncology and Hematology [31], using a multi-stage process of Plan-Do-Study-Act (PDSA) cycles [32], including a Delphi survey to incorporate the expertise of psychosocial workers in the German-speaking region. Results emphasize the necessity of standardized psychological support to enable an evaluation and optimization of psychosocial care. This paper relies on adopting the patients’ perspective to evaluate the patients’ emotional well-being and their subjective sense of expertise (evaluated by medical staff and the patients themselves) [33]. The resulting tool consists of various booklets, each focusing on one topic and the corresponding psychosocial stressors encountered by patients during cancer treatment (e.g., “ABC of chemotherapy”, “Mission stem cell transplantation”), including “iMReady” as crucial examination [33]. ## 2.2. Ethical Approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the local Ethics Committee of the Medical University of Vienna. ## 2.3. Participants The total study sample was composed of 105 patients with a mean age of 6.83 years (SD = 2.04; range = 4 to 14). All children aged four or older that were admitted to the facility where this program was developed were invited to participate in the training session. They were given the voluntary option to participate in the ongoing explorative study to evaluate the training’s effectiveness. Since we expected that all children could benefit from this training program, no specific exclusion criteria were applied. For the 53 female participants ($50.5\%$), the mean age was 6.21 (SD = 1.64). For male participants it was 7.46 (SD = 2.23). All in all, 37 children attended pre-school or kindergarten. The 52 children and adolescents who attended school were on average in second grade (median). For the 16 remaining children, no education information was available. The majority of participants spoke German as their first language ($66\%$). For children who did not speak German, non-verbal methods were used and, if possible, parents helped in translation. Most of the patients ($72.69\%$) suffered from brain tumors. The mean onset age of the medical condition was at 3.01 years (SD = 2.76). Thirty-three patients suffered from NF1 in the absence of brain tumors. There was a certain degree of overlap between the NF1 and the tumor group. Twenty-one of the patients afflicted by NF1 also exhibited brain tumor diagnoses. More information on sample characteristics as well as the patients´ medical details can be found in Table 1. Of all the participants enrolled in the program, 87 ($83\%$) received MRI training, while 18 ($17\%$) did not, due to scheduling reasons ($$n = 9$$) or because the parents did not want their children to receive the intervention ($$n = 8$$); for one child, the reason was unknown. Although the current study did not recruit a matched control group, we used this group of non-participating children as a reference group. This group will henceforth be referred to as “dropout group”. The dropout group was composed of 8 girls ($44\%$) and 10 boys ($56\%$). The mean age in the dropout group was 7 years (SD = 2.33). In terms of diagnosis, five children suffered from NF-1 ($28\%$), while 13 ($72\%$) suffered from a brain tumor in the absence of NF-1. As part of the evidence- and consensus-based development of the training, the updated version was deployed in the fall of 2018. This second phase involved a longitudinal assessment of emotional well-being. Of 17 patients participating, 10 were female ($59\%$). The mean age was 5.65 years (SD = 1.37, range = 4 to 9 years). Twelve children spoke German as their first language ($71\%$). Thirteen patients suffered from brain tumors ($76\%$), while 4 did not ($24\%$). Eight participants suffered from NF1; 4 of these also had brain tumors. All patients with brain tumors received oncological treatment according to protocol. Participants in the prospective analysis were a subsample of the total sample ($$n = 105$$). These children underwent the same procedure as the remainder of the sample; however, the emotional assessment was exclusively carried out in this subsample. ## 2.4.1. Retrospective Analysis In this explorative, observational study, all MRI training referrals between January 2014 and October 2018 were retrospectively investigated for training effectiveness and underlying medical, neuropsychological, or sociodemographic moderators of MRI success. MRI training was labeled successful when patients could lie still for a minimum of one MRI sequence. An MRI scan was labeled successful when it yielded interpretable results (with none to moderate movement artifacts) as defined by a neuroradiologist, and which did not require the use of sedation/anesthesia. The quality of MRI pictures was rated on a three-point scale (no or mild motion artifacts; moderate motion artifacts; severe motion artifacts or termination). As part of the standard of care protocol at the neuro-oncology unit, all patients were administered a comprehensive neuropsychological test battery before or after the MRI training. For this retrospective study, the different pre-existing neuropsychological test results relevant to the study question were included in the analysis. Details on the neuropsychological tests administered can be found in Table 2. ## 2.4.2. Prospective Analysis The prospective analysis followed an explorative approach as well. In this second part of the current research, we focused on the patients’ perceived well-being, knowledge about the procedure of the MRI examination, and how to cope with the stress potentially caused by it. To this end, we assessed the patients’ emotions using an intuitive, visual approach. The evaluation of patients’ emotional well-being was carried out using an array of images representing emotional states [44]. The participating children were asked to choose three of the 18 presented images that best described their emotional well-being throughout the MRI training. For subsequent analysis, these emotional displays were categorized into positive, neutral, and negative emotions. The evaluation of emotional well-being was conducted longitudinally over five different time points—before and after session one, before and after session 2, and after the diagnostic MRI. The evaluation of the degree of confidence and knowledge of the children and their parents was carried out by medical staff in the radiology department during the diagnostic MRI scan. Due to procedural constraints, data were only available for children that completed their MRI without general anesthesia. Medical staff scored each category (child well-informed, child secure, accompanying person well-informed, accompanying person secure) on a scale from 1 to 10. ## 2.5. Statistical Analysis For data analysis, a combination of descriptive statistics and statistical inference was used. The sample was described using common statistical indicators. If the level of measurement allowed for it, a Welch’s t-test was applied due to its robustness with unequal variances and sample sizes. This test generates non-discrete degrees of freedom [45]. Categorical variables were analyzed using Chi-squared-tests of independence. Where possible, measures of effect size were computed. In two-group comparisons, Cohen’s d was calculated. For contingency tables with polytomous categorical variables, Cramér’s V was calculated, whereby an odds ratio for 2 × 2 contingency tables was adopted. The patients in this intervention reported their emotional state at five different points of time over the course of the study by selecting three faces out of a range of emotional displays. Subsequently, these emotions were categorized into positive, neutral, and negative emotions. Since the data was categorical and non-independent due to the longitudinal design, general linear model techniques were not applicable. Therefore, the change of selected emotions over the course of the intervention was analyzed using generalized linear mixed models (GLMM) with Poisson distribution and log link function. Maximum likelihood with Laplace approximation was used as an estimation method. These models are extensions of the general linear model which have been adapted to account for the categorical and dependent nature of the data [46]. A type I error rate of 0.05 was chosen in all analyses, thus tests that yielded probabilities below that level were considered statistically significant. No adjustments for type I error inflation were made; instead, effect sizes were reported [47]. In all analyses, the statistical programming environment R (version 3.60 for Mac OS) was applied; for GLMM analyses, the R package lme4 was used (version 1.1-24); graphics were created using the R package ggplot2 (version 3.4.1). ## 3.1. Effect of MRI Training (Retrospective Analysis) The principal goal of this intervention was to empower children and adolescents to manage undergoing an MRI without the need for general anesthesia. The term MRI success will be used for MRI performance without general anesthesia. All patients attended MRI training. The overall success rate for the total sample of 105 patients was $74\%$. The group that participated in the training program ($$n = 87$$) performed significantly better ($80\%$ success rate, 70 out of 87) compared to the group ($$n = 18$$) that did not receive training ($44\%$ success rate, 8 out of 18; χ2 = 9.1, df = 1, $p \leq 0.01$). The odds ratio indicates that the chance of successfully managing an MRI without anesthesia was almost five times as high in the group that received MRI training compared to the group that did not (OR = 4.92, $95\%$ CI = 1.64; 14.73, p = <0.01). Moreover, MRI picture quality was acceptable in the intervention group. See Figure 2 for a visual comparison of MRI success rates per group. ## 3.2.1. Sociodemographic and Medical Associations There was no sex difference in the probability of MRI success (χ2 = 0.78, df = 1, $$p \leq 0.28$$, OR = 0.66). Age ($t = 0.33$, df = 47.18, $$p \leq 0.74$$, Cohen’s $d = 0.07$) and grade (t = −1.06, df = 33.33, $$p \leq 0.30$$, Cohen’s d = −0.21) did not differ among patients that managed their scans without general anesthesia and those who required anesthesia. There was no significant association between the type of education and MRI success (χ2 = 0.00, df = 1, $$p \leq 0.95$$, OR = 0.95), i.e., the rate of need for sedation during scans did not vary between children in special education compared to patients in regular schools. Notably, patients’ first languages were not associated with MRI success, indicating that non-German native speakers did not have more difficulties than German native speakers (χ2 = 0.02, df = 1, $$p \leq 0.90$$, OR = 1.06). MRI success rates in patients suffering from NF1 (without a brain tumor) were compared with patients suffering from a brain tumor; there was no significant association between the two variables (χ2 = 1.84, df = 1, $$p \leq 0.17$$, OR = 1.9). Furthermore, the MRI success rates between different treatment options were categorized into four tiers: observance only, surgery only, surgery and chemo-, radio- or antiangiogenic therapy, chemo-, radio- or antiangiogenic therapy. Subsequent comparison showed no significant association between the treatment arm and MRI success (χ2 = 3.62, df = 3, $$p \leq 0.30$$, Cramér’s $V = 0.19$). However, the onset age of the diagnosed medical condition differed significantly between patients that managed the MRI without anesthesia and those that required anesthesia (t = −2.17, df = 56.69, $$p \leq 0.03$$, Cohen’s d = −0.44). Patients that required anesthesia exhibited a significantly lower mean age (2.21 vs. 3.1 years, respectively) at the onset of their medical conditions. ## 3.2.2. Neuropsychological and Behavioral Associations The successful completion of their MRI scans without requiring general anesthesia could not be explained by IQ, attention, or concentration. However, memory (VLMT [40] or WET [41]) showed a significant, medium effect size which is visualized in a boxplot in Figure 3. See Table 2 for the tests used and Table 3 for more detailed information on neuropsychological data. Patients that needed anesthesia scored significantly lower in their memory tests ($M = 25.91$, SD = 22.44) compared to patients that did not need general anesthesia ($M = 46.33$, SD = 31.12). To test for associations between MRI success and behavioral or emotional symptoms (SDQ) [43], the scores were dichotomized into the categories normal and critical range. The only category that showed a significant association with MRI success was hyperactivity and attentional difficulties. Forty-eight percent of patients that required anesthesia during the MRI exhibited high or very high levels of hyperactivity and attentional difficulties, whereas only 19 percent of patients that did not require anesthesia exhibited high or very high levels (Table 3). The dropout group did not differ significantly from the intervention group regarding memory ($t = 0.82$, df = 20.25, $$p \leq 0.53$$, $d = 0.22$) or their scores in SDQ hyperactivity and attentional difficulties (χ2 = 2.21, df = 3, $$p \leq 0.53$$, Cramér’s $V = 0.60$). ## 3.2.3. Evaluation of Patients’ Emotional Well-Being (Prospective Analysis) We analyzed the frequencies of positive, neutral, and negative emotions at each point of the prospective study. Figure 4. shows the frequency at which patients selected each category over the course of the study. Separate GLMM’s were applied for positive, neutral, and negative emotions. The point of time was included as a fixed-effect variable, while participant ID was included as a random-effect variable to account for the dependent data structure. Over the course of the five points of measurement across the study, negative emotions dropped significantly (beta = −0.41, z = −3.64, $p \leq 0.01$, R2marginal = 0.12), indicating a reduction of 0.41 in the count of negative emotions reported by participants with every point of measurement over the course of the study. Meanwhile, positive emotions were selected more frequently (beta = 0.27, z = −2.68, $$p \leq 0.00$$, R2marginal = 0.14), indicating that participants reported 0.27 positive emotions more with every point of measurement. Neutral emotions showed a moderate decline which did not reach statistical significance (beta = −0.11, z = −1.38, $$p \leq 0.17$$, R2marginal = 0.02). In these models, R2marginal signifies the amount of variance explained by change over the course of the intervention. ## 3.2.4. Interdisciplinary Evaluation (Prospective Analysis) All categories evaluated by the medical staff exhibited median values above “8” on a visual analog scale (0–10), indicating generally favorable values. “ Child secure” exhibited the lowest median as well as the largest variance ($M = 8.74$, SD = 1.34), with an overall high information level (“child well-informed” $M = 9.25$, SD = 0.73) The highest medians and the smallest variances were found in the categories concerning the accompanying persons, “Accompanying person well-informed/secure” ($M = 9.42$/9.42, SD = $\frac{0.51}{0.52}$). ## 4. Discussion In this exploratory, observational study, our primary goal was to demonstrate a novel training procedure designed to prepare children for MRI exams. Although the design of the current study does not allow for causal inference, these initial results suggest that the children who participated in the program were more likely to exhibit desirable outcomes in MRI exams. Furthermore, our results suggest that over the course of the intervention, negative emotionality declined, while positive emotionality increased. Children who received prior training exhibited a five times higher chance of having a successful diagnostic MRI scan than children who did not receive a training. Furthermore, $81.4\%$ of children who received the MRI training managed the diagnostic MRI scan with good image quality, while children who did not receive the training had only a $47\%$ chance of a successful MRI. Considering the high burden of disease and the great frequency at which childhood cancer patients must undergo investigations, this chance of reducing the number of interventions and sedations could help reduce psychological and physiological stress in patients and their families. The encountered success rate is comparable to success rates in children with developmental delay and ADHD [10] but slightly lower than in prior studies with different patient populations [21,24,41]. The lower success rates in children who suffer from brain tumors or neurofibromatosis compared to other patient groups could be explained by the high mental stress faced by families when checking for treatment success or possible tumor recurrence, as well as cognitive issues often faced in these patient groups, e.g., [13,14]. Another possible explanation could address differences in the duration of MRI scans among the study samples [10] ranging from 7 [29] up to 100 min [24]. Hence, randomized control trials need to be carried out to enable a more valid and well-founded judgement of the benefits of this novel program. Since the overall image quality was judged to be satisfactory in the entire group, it appears that for the future, image quality alone will not be the essential outcome criterion for the successful completion of an MRI training. From a clinical perspective, it seems even more appropriate to focus on the experienced well-being as well as the level of information as outcome criteria, which both contribute significantly to higher compliance and even more to a resilient outcome in life-long disease management [8,24,48,49]. Only a small number of studies have investigated the mechanisms underlying successful MRI scans in children showing associations with cognitive and language skills, [22] age [50], temperament, patients’ knowledge of the procedure, and previous medical experience [10]. Interestingly, in the present study neither age, gender, treatment arm, nor the mother tongue had an influence on success rates. However, neuropsychological risk factors for MRI success are low scores in long-term memory, as well as reported attentional problems, two cognitive impairments that pediatric brain tumor and NF1 patients are especially vulnerable to [51]. Moreover, difficulties regarding memory and attention are often related to genetic components and early disease onset [52,53], which in turn was associated with a reduced MRI success rate. This is clinically plausible, since, for example, memory deficits do not only make it more difficult to remember the content of the training and particularly strategies, to lie still and to cope with stressful situations, but can also lead to an increased feeling of insecurity, which might be multiplied in stress evoking situations such as MRI scans [54]. Overall, the neuropsychological moderators clearly show that it is important to customize the training to the patient’s neuropsychological outcome and developmental stage, which in turn need highly specialized and well-trained psychological staff. Further research is necessary to evaluate if prior memory or attentional training leads to an even higher success rate. The value of integrating the parents’ perspective is further underlined by the fact that only attentional difficulties based on external observation by the parents modified MRI success while results in tests on attention and concentration did not. However, this might be due to the nature of the tests chosen to check for attentional difficulties. In addition to the evaluation of focused attention (KHV-VK and KITAP—distractibility condition), future studies should include an assessment of other dimensions of attention as well as record the exact duration of the individuals’ sessions to allow for an investigation of a possible relationship between intervention time and the program’s effectiveness, to derive practical implications for clinical assessment. Compared to other MRI training tools, the major difference of the present approach lies in the integration of role play techniques as well as in vivo training, two learning strategies that are especially effective for elaborating and solidifying the training content [27,55]. In a preventive sense, strategies considering emotional outcome (e.g., reduction and/or avoidance of fears) are implemented at an early stage to ensure short-term and long-term follow-up care [16,23,49]. The results emphasize the importance of the training being performed by clinical psychologists specializing in child development and neuropsychology who closely work together with medical doctors and radiotechnology assistants in an integrated care system [26,56,57]. In the future it would be of great interest to adopt the assessment scale of the interdisciplinary report to get more detailed information on the performance during MRI to derive further practical implications for psychosocial support. Transferring the training methods into daily life can additionally help to solidify the learned content, which was supported in the evaluated program by the parents acting as co-therapists. Additionally, in the aim of increasing immediate treatment success, the close interaction with and evaluation of the patients by this comprehensive team can also enable the professionals to better judge whether patients are prepared to undergo MRI examinations without sedation. In turn, the risk of stress and trauma can be reduced [10,17]. Hence, the present study was the first to show that children experience a variety of emotions with regard to an MRI, which might change over time. While prior work has exclusively focused on fear, anxiety, and distress [8,22,23,28,30] the use of an array of 18 different emotional displays categorized into positive, neutral, and negative, allowed for a more detailed evaluation of patients’ feelings in relation to the MRI procedure. The results illustrate a high variability of emotional experience and highlight positive emotions associated with dealing with an MRI examination. Tracking the emotional state over five time points, a decrease in negative and an increase in positive emotions was evident, the latter reaching a peak after the completion of the diagnostic MRI, which might be related to relief after the completion of the diagnostic procedure. The changes in emotional wellbeing (a reduction followed by an increase in positive emotions, only with continuation of the training), illustrate the shifting process in the therapeutic procedure: information transfer (disengagement—reduction of positive emotions); learning new strategies in dealing (shift—reduction of positive emotions); integration into everyday life (engage—stabilization or increase of positive emotions) [17]. The results highlight the fact that simple information is not sufficient. Moreover, standing alone without follow-up appointments offering coping strategies can thus have the opposite effect and increase uncertainty. The underlying aim of the current study was to systematically visualize experiences from clinical practice in terms of outreach opportunities, outcome in well-being, and evidence of perceived levels of information as important aspects of health literacy and resilient coping with necessary medical procedures. Furthermore, we assume that these results will provide a basis for further research in the context of controlled randomized studies. This may reveal more insight concerning the effects of the individual training aspects as well as the actual strategies used to successfully complete an MRI examination (both in terms of image quality, but also in terms of a positive processing of the situation). ## 5. Limitations and Future Directions Significantly, the current study was explorative in nature. This is reflected by specific aspects of the research. First, hypotheses of the study were not pre-registered, thus results of all analyses are not to be interpreted as confirmatory hypothesis tests but as preliminary findings. Moreover, to estimate the effectiveness of the “iMReady” program, we employed a group of children that did not take part in the intervention as reference group (i.e., the dropout group). These children cannot be considered a matched control group because they opted out of the “iMReady” program for various reasons that were not controlled by the researchers and may have introduced systematic bias into the comparisons. Thus, the findings of intervention to the dropout group comparisons must be interpreted as explorative effect estimates. Future research carried out in the form of controlled trials will reveal if these effects are robust and reproducible. Emotional well-being was only assessed with a limited number of patients during the latter part of the study for which no reference group was available. Therefore, although the findings are promising, the decline in negative emotions and simultaneous increase in positive emotions cannot be causally attributed to the MRI preparation program. Future endeavors should evaluate whether the observed treatment effect also emerges within a controlled design. The sustainability of stress relieving strategies and coping mechanisms promoted through MRI training is an interesting field for further research. We would expect, among other things, that children with NF1 need more support in preparation, even though this has not been shown in the data. A differentiated evaluation with respect to disease and tumor entities is particularly desirable to allow for more specific statements regarding selected risk groups. ## 6. Conclusions The MRI Training “iMReady” is a highly feasible, evidence-based tool, which can easily be adjusted to the special needs of the heterogenous patient group in pediatric neuro-oncology. The results of the present study suggest that treatment compliance is moderated by disease-related cognitive, physical, and behavioral difficulties. Tailored trainings, such as the one demonstrated here, may be a promising strategy in counteracting compliance problems and increasing MRI performance. Furthermore, it was the first study to evaluate patients’ emotional experiences related to MRI procedures, indicating a substantial improvement in patients’ self-reported emotional well-being throughout the psychoeducational program. Further studies with larger sample sizes as well as a randomly assigned, matched control group are necessary to more thoroughly investigate the patient characteristics that are most relevant to prediction of successful treatment, to allow for the trainings to be tailored to individual needs. In addition, to ensure implementation and to avoid competition between training time slots (20–30 min) and actual MRI examinations (amounting to increased waiting time), it would be beneficial if the MRI companies would build dummy machines with which to perform the training. ## References 1. 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--- title: Selective Targeting of Class I HDAC Reduces Microglial Inflammation in the Entorhinal Cortex of Young APP/PS1 Mice authors: - Chunyang Wang - Di Shen - Yingqiu Hu - Jie Chen - Jingyun Liu - Yufei Huang - Xuebin Yu - Haiying Chu - Chenghong Zhang - Liangwei Yin - Yi Liu - Haiying Ma journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003411 doi: 10.3390/ijms24054805 license: CC BY 4.0 --- # Selective Targeting of Class I HDAC Reduces Microglial Inflammation in the Entorhinal Cortex of Young APP/PS1 Mice ## Abstract BG45 is a class Ⅰ histone deacetylase inhibitor (HDACI) with selectivity for HDAC3. Our previous study demonstrated that BG45 can upregulate the expression of synaptic proteins and reduce the loss of neurons in the hippocampus of APPswe/PS1dE9 (APP/PS1) transgenic mice (Tg). The entorhinal cortex is a pivotal region that, along with the hippocampus, plays a critical role in memory in the Alzheimer’s disease (AD) pathology process. In this study, we focused on the inflammatory changes in the entorhinal cortex of APP/PS1 mice and further explored the therapeutic effects of BG45 on the pathologies. The APP/PS1 mice were randomly divided into the transgenic group without BG45 (Tg group) and the BG45-treated groups. The BG45-treated groups were treated with BG45 at 2 months (2 m group), at 6 months (6 m group), or twice at 2 and 6 months (2 and 6 m group). The wild-type mice group (Wt group) served as the control. All mice were killed within 24 h after the last injection at 6 months. The results showed that amyloid-β (Aβ) deposition and IBA1-positive microglia and GFAP-positive astrocytes in the entorhinal cortex of the APP/PS1 mice progressively increased over time from 3 to 8 months of age. When the APP/PS1 mice were treated with BG45, the level of H3K9K14/H3 acetylation was improved and the expression of histonedeacetylase1, histonedeacetylase2, and histonedeacetylase3 was inhibited, especially in the 2 and 6 m group. BG45 alleviated Aβ deposition and reduced the phosphorylation level of tau protein. The number of IBA1-positive microglia and GFAP-positive astrocytes decreased with BG45 treatment, and the effect was more significant in the 2 and 6 m group. Meanwhile, the expression of synaptic proteins synaptophysin, postsynaptic density protein 95, and spinophilin was upregulated and the degeneration of neurons was alleviated. Moreover, BG45 reduced the gene expression of inflammatory cytokines interleukin-1β and tumor necrosis factor-α. Closely related to the CREB/BDNF/NF-kB pathway, the expression of p-CREB/CREB, BDNF, and TrkB was increased in all BG45 administered groups compared with the Tg group. However, the levels of p-NF-kB/NF-kB in the BG45 treatment groups were reduced. Therefore, we deduced that BG45 is a potential drug for AD by alleviating inflammation and regulating the CREB/BDNF/NF-kB pathway, and the early, repeated administration of BG45 can play a more effective role. ## 1. Introduction Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with declining cognitive function associated with age [1]. Morbidity from AD dramatically increases after the age of 65 and shows a growing trend [2]. The main histological characteristic of AD is the accumulation of extracellular amyloid β (Aβ), evident as senile plaques and intracellular neurofibrillary tangles (NFTs) caused by hyperphosphorylated tau [3]. Evidence has shown that the degree of dementia is closely connected to the level of soluble oligomers of Aβ species in AD patients’ brains [4]. The Aβ oligomer, formed by redundant Aβ42, can contribute to the damage of ion channels and calcium homeostasis, reduced energy metabolism, and glucose regulation [4,5], as it disrupts neuronal regulation and synaptic plasticity and causes eventual neuron death. Studies have reported that Aβ oligomers first appeared in the brain in 2-month-old APP/PS1 mice [6], senile plaques were detected in 4-month-old mice [7], and the numbers and areas of plaques increased with age. Therefore, the early treatment of AD is crucial. The classical lesions of AD can occur as early as 20 years prior to the development of symptoms and disease indicators [8]. These early changes are likely to occur at the epigenetic level, where gene expression is controlled [9]. Histone acetylation is a common form of genetic post-translational modification and plays an important role in histone transcription regulation [10]. Histone deacetylases (HDACs) are a superfamily of enzymes that are key parts of the epigenetic regulation of gene expression and cellular activity [11]. In normal neurons, histone acetyltransferase (HAT) and HDAC protein levels and their corresponding activities are always maintained at a high balance [12]. They play crucial roles in regulating gene expression, which is associated with normal neurophysiological functions such as long-term potentiation, learning, and memory [13,14]. In neurodegenerative diseases, however, acetylation homeostasis is disrupted and synaptic plasticity is injured [15,16]. The classical HDAC family can be divided into three types according to the homology of yeast: class I HDACs (HDAC1, 2, 3, and 8), class II HDACs (HDAC4, 5, 6, 7, 9, and 10), and class III HDACs [17,18]. Studies have demonstrated that HDAC2-overexpressing mice will have deregulated gene expression and damaged synaptic plasticity, learning, and memory [19], and HDAC2 KO mice have increased dendritic spine density and numbers of synapses [20]. Moreover, HDAC3 overexpression in the hippocampuses of APP/PS1 mice can increase Aβ levels, activate microglia, and injure synaptic plasticity [21,22]. HDAC inhibitors (HDACIs) represent prototypical “epigenetic” agents that act by modifying gene expression to restore the normal differentiation or death programming of transformed cells [23]. There is powerful evidence suggesting that HDACIs may be useful in the treatment of AD and AD-like pathologies [24,25]. HDACI can activate CREB-CBP-dependent transcription [11]. cAMP response element binding protein (CREB), a transcriptional coactivator with HAT activity, has been proved to be associated with synaptic plasticity and long-term memory [26,27]. Studies have suggested that HDACI improves gene transcription ability and facilitates the phosphorylation of CREB at serine 133, driving CRE-mediated transcription [13]. The CREB transcription factor family regulates the transcription of brain-derived nerve factor (BDNF), especially the activation of BDNF promoter IV [28]. Moreover, BDNF levels can affect the chronic inflammatory state of the brain by influencing the release of TNF-α and IL-1β [29]. Aβ deposition can activate microglia, which will release pro-inflammatory cytokines such as TNF-α, IL-1β, and IL-6, leading to tau hyperphosphorylation and neuronal loss [30]. Therefore, HDACI may improve synaptic plasticity by regulating inflammation. BG45, a novel class I HDAC inhibitor (C11H10N4O, 214.22), has been evidenced to selectively inhibit the expression of HDAC3 (IC50 = 289 nM). It also inhibits HDAC1 and HDAC2 with reduced potency [31]. The entorhinal cortex has been shown to be an interface between the hippocampus and neocortical regions, and it plays a crucial role in the formation and consolidation of memory [32,33]. In our previous studies, we found that BG45 can reduce Aβ deposition, increase the expression of synaptic proteins, and upregulate the expression of α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor subunits (GluR2, GluR3, and GluR4) [34,35]. We hypothesized that BG45 might be a promising factor to rescue synaptic plasticity in AD. In this study, we explored the timing of Aβ deposition and the increased activation of glial cells in the entorhinal cortex. Subsequently, we investigated the effect of BG45 treatment on these changes at different times. We discovered that BG45 reduced the number of degenerative neurons and the activation of microglia and astrocytes in the entorhinal cortexes of 6-month-old mice if they were treated with BG45 at 2 months of age. ## 2.1. Age-Related Changes in Aβ in the Entorhinal Cortexes of the APP/PS1 and Wt Mice Immunohistochemistry revealed the differences in the Aβ depositions of the mice of different ages. Positive Aβ deposition in the entorhinal cortex was first identified in 3-month-old APP/PS1 mice, which gradually accumulated with age. However, there was no significant Aβ immunoreactivity in 2-month-old to 8-month-old Wt mice (Figure 1). ## 2.2. Age-Related Changes in Microglia and Astrocytes in the Entorhinal Cortexes of the APP/PS1 and Wt Mice Using immunohistochemistry, microglia and astrocytes with the corresponding IBA1 and GFAP antibodies were detected in the entorhinal cortexes at different ages. The results showed that the positive expression of IBA1 and GFAP was significantly increased in 3-month-old mice as they got older. However, compared with 2-month-old Wt mice, there were no significant changes in the IBA1-positive microglia and GFAP-positive astrocytes in the 8-month-old Wt mice (Figure 2). ## 2.3. BG45 Promoted H3K9K14/H3 Acetylation and Inhibited the Expression of HDAC1, HDAC2, and HDAC3 in the Entorhinal Cortexes of the APP/PS1 Mice The effects of BG45, a class I HDAC inhibitor, on H3K9K14/H3 acetylation and HDAC1, HDAC2, and HDAC3 expression were evaluated by Western blot analysis. As shown in Figure 3A,C, H3K9K14/H3 acetylation was decreased in the Tg group compared with the Wt group ($p \leq 0.05$). However, compared with the Tg group, H3K9K14/H3 acetylation was increased to different degrees in the three BG45 treatment groups ($p \leq 0.05$, $p \leq 0.001$, and $p \leq 0.05$, respectively), and the levels of H3K9K14/H3 acetylation in the 2 and 6 m group were the highest. As shown in Figure 3B,D–F, HDAC1, HDAC2, and HDAC3 expression was increased in the Tg group compared with the Wt group ($p \leq 0.05$, $p \leq 0.05$, and $p \leq 0.01$, respectively). HDAC1 expression in the 2 m and 2 and 6 m groups was decreased compared with the Tg group ($p \leq 0.01$ and $p \leq 0.01$, respectively). However, there was no significant difference between the 6 m and Tg groups. HDAC2 and HDAC3 expression in three BG45-treated groups was decreased compared with the Tg group ($p \leq 0.05$, $p \leq 0.05$, and $p \leq 0.05$, respectively, and $p \leq 0.001$, $p \leq 0.001$, and $p \leq 0.05$, respectively). ## 2.4. BG45 Alleviated Neuronal Degeneration in the Entorhinal Cortexes of the APP/PS1 Mice The severity of neuronal degeneration was evaluated by Fluoro-Jade C (FJC) straining. We found that there were many more positive FJC-stained cells in the entorhinal cortexes of the Tg group than there were in the Wt group ($p \leq 0.001$). Compared with the Tg group, the number of FJC-positive cells decreased in the three groups receiving BG45 treatment ($p \leq 0.001$, $p \leq 0.001$, and $p \leq 0.01$) (Figure 4). ## 2.5. BG45 Reduced Aβ Deposition and Downregulated p-tau Expression in the Entorhinal Cortexes of the APP/PS1 Mice As shown in Figure 5A, Aβ deposition in all BG45-treated groups (2 m, 2 and 6 m, and 6 m) was decreased compared with the Tg group ($p \leq 0.001$, $p \leq 0.001$, and $p \leq 0.01$, respectively). More Aβ deposition was found in the entorhinal cortexes of the mice treated at 6 months of age than in the mice treated at 2 months of age ($p \leq 0.001$), and the least amount was found in the mice treated twice at 2 months and 6 months of age. In addition, tau protein phosphorylation levels were also detected. The results indicated that p-tau expression was lower in all treated groups than in the Tg group ($p \leq 0.01$, $p \leq 0.001$, and $p \leq 0.05$, respectively), and it was lowest in the 2 and 6 m group (Figure 5B,C). ## 2.6. BG45 Increased Synaptic Protein Expression in the Entorhinal Corteesx of the APP/PS1 Mice To verify the protective effect of the synaptic plasticity of BG45, several synapse-related proteins were detected by Western blot analysis. The results showed that compared with the Wt group, the expression levels of PSD95, SYP, and spinophilin were decreased in the Tg group ($p \leq 0.05$, $p \leq 0.05$, and $p \leq 0.05$, respectively). However, the expression levels of SYP were higher in the 2 m and 2 and 6 m groups than in the Tg group ($p \leq 0.01$ and $p \leq 0.05$, respectively). In all BG45-treated groups, PSD95 and spinophilin were increased compared with the Tg group ($p \leq 0.01$, $p \leq 0.001$, and $p \leq 0.05$, respectively, and $p \leq 0.001$, $p \leq 0.01$, and $p \leq 0.05$, respectively), and PSD95 and spinophilin expression levels were higher in the 2 and 6 m group than in the two other treated groups (Figure 6). ## 2.7. BG45 Decreased the Number of IBA1-Positive Microglia and GFAP-Positive Astrocytes and Downregulated the Levels of IL-1β and TNF-α Gene Expression in the Entorhinal Cortexes of the APP/PS1 Mice Neuroinflammation is considered to be a critical driver of the cognitive deficits associated with AD. Overactivated neuroglial cells, such as microglia and astrocytes, contribute to neuroinflammation and neurodegenerative disorders. Both the microglia and astrocytes in the entorhinal cortexes of the 2 m, 2 and 6 m, and 6 m groups were decreased compared with the Tg group ($p \leq 0.001$, $p \leq 0.001$, and $p \leq 0.01$, respectively, and $p \leq 0.001$, $p \leq 0.001$, and $p \leq 0.001$, respectively). Moreover, the amount of IBA1-positive microglia and GFAP-positive astrocytes was the lowest in the 2 and 6 m group, and there were more positive cells in the 6 m group than in the 2 m group ($p \leq 0.01$ and $p \leq 0.001$, respectively) (Figure 7). RT-qPCR was used to detect the gene levels of inflammatory cytokines in the entorhinal cortex samples. The results showed that the mRNA levels of IL-1β and TNF-α were higher in the Tg group than in the Wt group ($p \leq 0.001$ and $p \leq 0.001$, respectively), and the levels of IL-1β and TNF-α gene expression in the 2 m and 2 and 6 m groups decreased compared with the Tg group ($p \leq 0.01$ and $p \leq 0.01$, respectively, and $p \leq 0.01$ and $p \leq 0.01$, respectively), but there was no significant difference between the 6 m group and the Tg group (Figure 7). ## 2.8. BG45 Changed the Expression of Key Factors in the CREB/BDNF/NF-kB Pathway in the Entorhinal Cortexes of the APP/PS1 Mice In order to investigate the potential mechanism by which BG45 alleviated the inflammatory factors and improved the levels of synaptic proteins, the key factors in the CREB/BDNF/NF-kB pathway were detected. The results revealed that p-CREB/CREB, BDNF and its receptor, TrkB, and p-NF-kB/NF-kB showed significant differences between the Tg group and the Wt group. Compared with the Tg group, the levels of p-CREB/CREB in the 2 m, 2 and 6 m, and 6 m groups were upregulated ($p \leq 0.001$, $p \leq 0.001$, and $p \leq 0.01$, respectively), and they were the highest in the 2 and 6 m group. At the same time, BG45 upregulated the expression of BDNF and TrkB in all the treated groups compared with the Tg group ($p \leq 0.01$, $p \leq 0.001$, and $p \leq 0.05$, respectively, and $p \leq 0.001$, $p \leq 0.01$, and $p \leq 0.01$, respectively). However, the p-NF-kB/NF-kB level was inhibited by BG45 treatment. Similarly, they both showed more significant changes in the 2 and 6 m group compared with the other two treatment groups (Figure 8). ## 3. Discussion Both amyloid precursor protein (APP) and presenilin (PSEN) gene mutations are associated with familial Alzheimer’s disease (FAD) and with the early onset of the disease. A mouse model of amyloid is used around the world to study the cognitive, behavioral, and neuropathological changes related to AD [36]. This study mainly explored the therapeutic effects of BG45 on APP/PS1 transgenic mice at different months of age before and after Aβ plaque formation. Previous studies have found that chronic local inflammatory responses occur in pathologically vulnerable areas of the AD brain, such as the frontal lobe and hippocampus [33]. Microglia have two different effects on the development of AD. On the one hand, they can clean Aβ peptides and reduce Aβ plaque accumulation, which, in turn, protects neurons [37]. On the other hand, microglia also have a negative influence on neurons. For example, they can injure synapses and thus contribute to neuronal death by secreting inflammatory factors or activating astrocytes [37]. In this study, we found that the number of amyloid plaques consistent with IBA1-positive microglia and GFAP-positive astrocytes gradually increased from 3 to 8 months, confirming that Aβ plaques and the activation of microglia and astrocyte are closely associated in the studied region of the entorhinal cortex in AD (Figure 1 and Figure 2). Studies have shown that persistent epigenetic changes may affect gene expression patterns and lead to neurodegenerative disorders, including AD [38,39]. Acetylation is dysregulated in AD and associated with various impairments in signaling, inflammation, and neuronal plasticity, contributing to negatively impacted memory and cognition [40]. In a study on post-mortem AD brains, the protein levels of the total histones H3 and H4 were significantly increased [41]. Klein et al. verified the positive correlation between H3K9 acetylation and transcriptional activity in the human cortex. H3K9 acetylation level is broadly associated with tau pathology [42]. In the entorhinal cortex, AD-associated differentially acetylated peaks were enriched in some processes related to Aβ metabolic processes and synaptic proteins, and this included regions annotated to genes (APP, PSEN1, and PSEN2) involved in AD pathologic hallmarks [43]. It was reported that HDAC3 inhibitors increased histone H3 and H4 acetylation and relieved memory impairment [21]. HDAC3, a class I HDAC, plays a crucial role in the pathology of AD because it is expressed not only in the nucleus but also in the cytoplasm, unlike other HDACs. HDAC3 overexpression can impair long-term memory and lead to the death of neurons [21,22]. The previous studies proved that BG45 can rescue the expression of synaptic proteins in the prefrontal cortex of APP/PS1 transgenic mice [44]. Consistent with the situation in the hippocampus and the prefrontal cortex [34,44], in this study, our data showed that BG45 rescued synaptic proteins and neuronal degeneration in the entorhinal cortexes of APP/PS1 mice. The expression levels of HDAC1, HDAC2, and HDAC3 in the entorhinal cortexes were higher in the APP/PS1 mice than in the Wt mice (Figure 3). Further research found that BG45 effectively reduced the levels of HDAC1, HDAC2, and HDAC3 in the APP/PS1 mice by increasing the ratio of H3K9K14 to H3, i.e., the 9 and 14 double positions of histone 3, possibly resulting in dissociating histone octamers from DNA and facilitating gene transcription, as well as contributing to increased synaptic proteins, such as PSD95, spinophilin, and SYP [34]. Therefore, epigenetic mechanisms related to BG45 may contribute to gene expression events for memory and regenerative growth. HDACIs are a group of small molecules with HDAC-inhibitory activity and can increase the level of histone acetylation to modulate biological functions [45]. It can acetylate the lysine 9 and 14 positions of H3 of CBP, accelerating the dissociation of histone, which can promote the phosphorylation of CREB [46]. CREB, located in promoter IV of BDNF, can promote gene transcription and boost the protein level of BDNF [28,47]. Increased BDNF promotes the phosphorylation of GSK-3β at the ser9 site to inhibit GSK-3β activity through the PI3K/AKT pathway and, subsequently, tau phosphorylation at multiple sites [48,49,50]. In addition, the change in the BDNF/TrkB pathway may indicate memory deficits and injured synaptic plasticity and neurons [51,52]. At the same time, BDNF can inhibit microglia from releasing NF-kB, which can reduce the expression of TNF-α and IL-1β and the activation of microglia and astrocytes [53,54]. In this study, we detected the key factors in the CREB/BDNF/TrkB pathway in Tg mice with or without BG45 treatment. The results showed that BG45 downregulated the inflammatory cytokines TNF-α and IL-1β. The increased levels of p-CREB/CREB, BDNF, and TrkB and the reduced p-NF-kB/NF-kB levels with BG45 treatment demonstrated that the regulation of glial cells and inflammation by BG45 involves the CREB/BDNF/TrkB pathway (Figure 8). Recent reports have also shown that HDAC3 expression and activity are associated with the expression of several AD-related genes, pro-inflammatory TNF-α and IL-6 and GFAP [40], while the neuroprotective effect of HDAC3 inhibitor (RGFP966) on modulating neuronal memory [55] and extensive neurite outgrowth [56] increases histone H3 and H4 acetylation, reducing Aβ expression and the level of tau phosphorylation [21]. Together, these studies suggest that HDAC3 inhibitors may be a promising epigenetic therapy for AD. Importantly, in this study, we found that some pathological changes in AD mice were better improved with BG45 treatment at the age of 2 months compared to those treated at 6 months of age, and BG45 significantly reduced the activation of microglia in the 2 and 6 m group, in which the mice were injected twice with BG45 at 2 and 6 months of age. Therefore, this demonstrated the effectiveness of early and repeated interventions with AD therapy at the epigenetic level. In summary, the molecular mechanisms of AD are complicated. More and more studies are reporting novel hypotheses such as mitochondrial defects, the phosphorylation of tau protein, molecular genetics and etiology, inflammation, oxidative stress and free radical, virus theory, etc. However, the unbalanced production or discharge of Aβ caused by various factors, including neuroinflammation, is still the focus of AD research [57]. Amyloid β can cause neuron death by causing the leakage of ions, disruption of the cellular calcium balance, and losses in membrane potential [58]. BG45, a class I HDAC inhibitor, increased H3K9K14/H3 acetylation and alleviated the pathology of the entorhinal cortexes in APP/PS1 mice by reducing Aβ deposition and upregulating the expression of synaptic proteins. We deduced that this positive effect may be due to BG45 inhibiting the activation of microglia and astrocytes and reducing the levels of inflammatory factors through the CREB/BDNF/NF-kB pathway. Therefore, it is worth further studying BG45 as a promising HDAC inhibitor for the treatment of AD. To perform the omics analysis to find the interactions of the signaling pathways involved in the role of BG45 would provide more favorable evidence for its use as a therapeutic target. ## 4.1. Animals and Drug Administration The APP/PS1 transgenic (Tg) mice were purchased from the Nanjing Biomedical Research Institute of Nanjing University. All mice were raised under a 12 h light/dark cycle at 22 °C with free access to food and water. All procedures were approved by the Institutional Animal Care and Use Committee of Dalian Medical University (AEE18086). Wild-type C57BL/6 mice were used as normal controls (Wt group). Two-month-old male, 20–22 g APP/PS1 mice were randomly divided into 4 groups, and 3 of the groups were intraperitoneally injected with BG45 (Selleck, 926259-99-6, Houston, USA) at different times, as follows: Tg group, control; 2 m group, injected at 2 months of age; 6 m group, injected at 6 months of age; and 2 and 6 m group, separately injected at 2 and 6 months of age. The mice in all treatment groups were injected with BG45 once a day for 12 days (30 mg/kg of BG45, 0.2 mL per mouse, where the BG45 was first dissolved into a 1 mg/mL stock solution in DMSO and then diluted 1:1000 with normal saline for use). The Tg group and the Wt group were also injected with same volume of vehicle. There were 5 mice in each group. All mice were killed within 24 h after the last injection at 6 months. Their entorhinal cortexes were harvested for subsequent experiments. ## 4.2. Immunohistochemistry Staining The sections were deparaffinized and rehydrated, and antigen retrieval was performed. Blocking endogenous peroxidase solution (SP-9100, ZSGB-BIO, Beijing, China) was added to each section, and they were incubated for 15 min at room temperature to block endogenous peroxidase [59]. The sections were blocked with a goat serum solution (SP-9100, ZSGB-BIO, Beijing, China) for 15 min at room temperature. Then the sections were incubated with primary antibody Aβ1–42 (NBP2-13075, Novus Biologicals, Littleton, CO, USA), IBA1 (1094-1-AP, Proteintech, Wuhan, China), or GFAP (80788, Cell Signaling Technology, Boston, MA, USA) at 4 °C overnight. After being washed with PBS (SW132-01, Seven, Beijing, China), the sections were incubated with an appropriate amount of biotin-labeled goat anti-mouse/rabbit IgG for 15 min at room temperature. Subsequently, the sections were incubated with streptozotocin-peroxidase for 15 min at room temperature. Diaminobenzidine (DAB) (ZLI-9018, ZSGB-BIO, Beijing, China) solution was added to the sections for 10 s to 5 min. Finally, hematoxylin was used to stain the nuclei [59]. Three random slices were selected from each group, and three random visual fields in the entorhinal cortex of each slice were observed [59]. The expression of Aβ1–42, IBA1, and GFAP was quantified by ImageJ software (U. S. National Institutes of Health, Bethesda, MD, USA). ## 4.3. Western Blotting All samples from the entorhinal cortex were thawed and washed in PBS buffer (SW132-01, Seven, Beijing, China). Then, the samples were sonicated in RIPA lysis buffer (SW104, Seven, Beijing, China) and incubated on ice for 30 min [60]. The proteins were extracted by centrifugation at 10,000× g for 10 min at 4 °C, and the concentrations were detected using a BCA Protein Assay Kit (P0010, Beyotime Biotechnology, Shanghai, China). The proteins were separated by 10 or $12\%$ SDS PAGE and transferred to polyvinylidene difluoride membranes, which were blocked in $5\%$ skim milk. Next, the membranes were incubated with rabbit polyclonal antibodies synaptophysin (SYP) (ab32127, Abcam, London, UK); BDNF (ab108919, Abcam, London, UK); P-CREB/CREB (9197, Cell Signaling Technology, Boston, MA, USA; ab32096, Abcam, London, UK); postsynaptic density protein 95 (PSD-95) (ab18258, Abcam, London, UK); p-tau (Ser404) and tau (20194 and 46687, Cell Signaling Technology, Boston, MA, USA); spinophilin (ab18561, Abcam); HDAC1, HDAC2, and HDAC3 (34589, 57156, and 85057, Cell Signaling Technology, Boston, MA, USA); H3K9K14 (GTX122648, GeneTex, San Antonio, TX, USA); H3 (17168-1-AP, Proteintech, Wuhan, China); NF-kB and p-NF-kB (Ser536) (10745-1-AP, Proteintech, Wuhan, China; 3033, Cell Signaling Technology, Boston, MA, USA); TrkB (4603, Cell Signaling Technology, Boston, MA, USA); and β-actin (AC026, ABclone, Wuhan, China) for 12 h at 4 °C. Then, the membranes were blotted with horseradish peroxidase (HRP)-conjugated secondary antibody at the room temperature for 1 h and imaged using a ChemiDoc XRS System and Image Lab software (Bio-Rad Laboratories, Inc., Hercules, CA, USA). ## 4.4. Fluoro-Jade C Staining The sections were dewaxed per the immunohistochemistry protocol and washed with ddH2O twice for 1 min each time [61]. The dilution, which was mixed with solution B (potassium permanganate, Merck Millipore, Massachusetts, USA) and ddH2O (1:9), was added to each section, and the sections were incubated in the dark for 10 min. Then, the solution was replaced with $0.5\%$ Triton for 30 min. The sections were washed with ddH2O twice for 1 min each time. Then, one part of solution C (Fluoro-Jade C) was mixed with 1 part of DAPI and 8 parts of ddH2O, and the mixture was added to the slices to incubate for 10 min in the dark. After being washed 3 times for 1 min each time, the slices were placed in a drying oven at 50–60 °C for 5 min. The dried sections were immersed in xylene for at least 5 min. The sections were observed by a Nikon Eclipse 800 microscope. Three random slices were selected from each group, and for each slice, 3 random fields were counted. The data are expressed as the numbers of degenerative neurons. ## 4.5. Real-Time Quantitative Polymerase Chain Reaction All samples were homogenated by TRIzol reagent (Takara, Kyoto, Japan). After adding chloroform to accelerate the RNA extraction, the solution was centrifuged for separation. The supernatant was transferred into an EP tube and isopropanol was added to make the RNA precipitate. After washing precipitate three times with the $75\%$ ethyl alcohol, the precipitate was dried at room temperature. The concentration of RNA was measured, then transcribed using a reverse transcription kit (Transgene, Strasbourg, France). Samples of mRNA were added to the solution, which was mixed with primer and 2× TransStart Top Green qPCR SuperMix (Transgene, Strasbourg, France), amounting to 20 µL. The qPCR reaction system was operated according to the manufacture’s protocol (Transgene, AQ601, Strasbourg, France) (30 s at 94 °C and 5 s at 95 °C, followed by 45 cycles for 30 s at 60 °C). The primer sequences were as follows:TNF-α5-GACGTGGAACTGGCAGAAGAG-3 5-TTGGTGGTTTGTGAGTGTGAG-3IL-1β5-GCCCATCCTCTGTGACTCAT-3 5-AGGCCACAGGTATTTTGTCG-3GAPDH5-GAGCCCTTCCACAATGCCAAAGTT-3 5-TGTGATGGGTGTGAACCACGAGAA-3 ## 4.6. Statistical Analysis All values are expressed as means ± standard deviations (SDs) from three independent experiments. One-way analysis of variance (ANOVA) followed by Tukey’s post hoc tests were used to analyze the differences between means of several subgroups of a variable, and a t-test was used for comparisons between two groups using GraphPad Prism8 (GraphPad Software, La Jolla, CA, USA). 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--- title: Consequences of Obesity on Short-Term Outcomes in Patients Who Underwent Off-Pump Coronary Artery Bypass Grafting Surgery authors: - Ihor Krasivskyi - Ilija Djordjevic - Borko Ivanov - Kaveh Eghbalzadeh - Clara Großmann - Stefan Reichert - Medhat Radwan - Rodrigo Sandoval Boburg - Anton Sabashnikov - Christian Schlensak - Thorsten Wahlers - Christian Jörg Rustenbach journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003424 doi: 10.3390/jcm12051929 license: CC BY 4.0 --- # Consequences of Obesity on Short-Term Outcomes in Patients Who Underwent Off-Pump Coronary Artery Bypass Grafting Surgery ## Abstract The correlation between off-pump coronary artery bypass (OPCAB) surgery and obesity-related outcomes is still uncertain. The aim of our study was to analyse the pre-, intra-, and postoperative short-term outcomes between obese and non-obese patients after off-pump bypass surgery. We performed a retrospective analysis from January 2017 until November 2022, including a total of 332 (non-obese ($$n = 193$$) and obese ($$n = 139$$)) patients who underwent an OPCAB procedure due to coronary artery disease (CAD). The primary outcome was all-cause in-hospital mortality. Our results showed no difference regarding mean age of the study population between both groups. The use of the T-graft technique was significantly higher ($$p \leq 0.045$$) in the non-obese group compared to the obese group. The dialysis rate was significantly lower in non-obese patients ($$p \leq 0.019$$). In contrast, the wound infection rate was significantly higher ($$p \leq 0.014$$) in the non-obese group compared to the obese group. The all-cause in-hospital mortality rate did not differ significantly ($$p \leq 0.651$$) between the two groups. Furthermore, ST-elevation myocardial infarction (STEMI) and reoperation were relevant predictors for in-hospital mortality. Therefore, OPCAB surgery remains a safe procedure even in obese patients. ## 1. Introduction The prevalence of obesity in Europe has increased dramatically in recent years [1,2,3]. High-grade obesity is associated with comorbidities such as arterial hypertension, dyslipidaemia, and Type 2 diabetes mellitus [4]. Furthermore, research groups have found a correlation between obesity and a higher rate of postoperative complications after a coronary artery bypass grafting (CABG) procedure [5,6]. In contrast, other authors showed no differences regarding the short-term outcomes between obese and non-obese patients after open-heart surgery [7]. Thus, the effect of BMI on postoperative complications after a bypass procedure remains unclear [5,8]. Reeves et al. [ 8] showed no significant differences in outcomes between obese and non-obese groups after a CABG procedure. However, Simopoulos et al. found a significantly higher prevalence of superficial and deep sternal wound infection rates in obese patients after bypass surgery [5]. Additionally, the mortality rate was significantly lower in the non-obese group compared to the obese one [5]. To date, most studies have compared the relation between a high-grade body mass index (BMI) and on-pump (CABG) procedure complications; only a minority of these studies have investigated the association between obesity and off-pump coronary artery bypass (OPCAB) surgery [9,10,11]. The OPCAB procedure is a crucial treatment for patients with triple vessel disease [10,11]. Particularly for high-risk patients, OPCAB surgery provides the maximum level of safety and avoids complications that may be caused by cardiopulmonary bypass (CPB), such as hepatic, renal, and cardiac damage [12,13]. Moreover, the off-pump strategy may prevent myocardial ischemia [14]. The association between OPCAB surgery and obesity-related outcomes remains uncertain [12,13,14]. Our main objective was to analyse the pre-, intra-, and postoperative short-term outcomes between obese and non-obese patients after OPCAB surgery. Our secondary objective was to identify relevant predictors for in-hospital mortality. ## 2. Materials and Methods Retrospective double centre analysis of the OPCAB cohort was performed. From January 2017 until November 2022, a total of 359 patients underwent off-pump coronary artery bypass procedures due to coronary artery disease in the department of cardiovascular surgery in the universities of Cologne and Tuebingen in Germany. To compare the unequal patient groups, a propensity score-based matching (PSM) analysis was applied (Figure 1). ## 2.1. Definition of Obesity Our methods were previously described in [15]. Based on the World Health Organization (WHO)’s obesity classification, our sample was divided into 6 categories:Underweight: BMI <18.5 kg/m2Normal weight: BMI 18.5–24.9 kg/m2Overweight: BMI 25.0–29.9 kg/m2Obese class I: BMI 30.0–34.9 kg/m2Obese class II: BMI 35.0–39.9 kg/m2Obese class III: BMI >40.0 kg/m2 *For analysis* of the obesity-dependent factors on clinical outcomes, patients were divided into non-obese (BMI < 30 kg/m2, $$n = 193$$) and obese (BMI ≥ 30 kg/m2, $$n = 139$$) before PSM, and into non-obese (BMI < 30 kg/m2, $$n = 124$$) and obese (BMI ≥ 30 kg/m2, $$n = 124$$) groups after PSM. Underweight patients ($$n = 27$$) were excluded. In order to provide more specific results through our analysis, we created 3 obesity classes in our sample. Both primary and secondary outcomes were evaluated for patients suffering obese classes I, II, and III. ## 2.2. Surgical Procedure All patients included in this study underwent OPCAB surgery. Patients who underwent CABG with CPB were excluded. All operations were performed through a median sternotomy. After local stabilisation was achieved with an automatic pod spread for effective visualisation of the anastomotic site, a longitudinal incision of the coronary artery was performed. Subsequently, a temporary shunt was inserted into the lumen of the targeted vessel to allow continuous blood flow during anastomosis and to limit possible bleeding. Monofilament sutures (8–0) were used in most cases. Our methods were previously described in [15]. ## 2.3. Data Collection We collected the data during the patients’ in-hospital stay from the databases of both hospitals. The collected data include the following:patients’ baseline characteristics (age, gender, Euroscore II, ejection fraction, left main coronary artery disease, history of Non-ST-elevation myocardial infarction (NSTEMI), history of ST-elevation myocardial infarction (STEMI), cardiogenic shock, previous stenting, previous stroke, reoperation rate, diabetes mellitus, hyperlipidaemia, peripheral vascular disease, arterial hypertension, pulmonary hypertension, chronic obstructive pulmonary disease, chronic kidney disease and dialysis);intraoperative characteristics (use of both internal thoracic arteries, total arterial revascularization, T-graft technique, endoscopic saphenous vein harvesting, heartstring use, catecholamine use, temporary pacer use, duration of bypass surgery, extracorporeal membrane oxygenation (ECMO) use, and intra-aortic balloon pump (IABP) use);postoperative data (transient ischemic attack (TIA), stroke, delirium, low cardiac output syndrome (LCOS), CK, CK-MB, lactate, creatinine, acute kidney injury, dialysis, wound infection, plastic covering, permanent pacemaker implantation (PPI), bleeding with reoperation, intensive care unit (ICU) stay, hospital stay, and in-hospital mortality);primary and secondary endpoints due to obesity classes I, II, and III;combined risk factors of in-hospital mortality (age, body mass index, diabetes mellitus, STEMI, NSTEMI, and reoperation rate). ## 2.4. Outcome Analysis The primary endpoint in our study was all-cause in-hospital mortality after OPCAB surgery. Secondary endpoints were dialysis, bleeding with reoperation, wound infection, and length of in-hospital stay. Furthermore, risk factors for in-hospital mortality were analysed and are presented in our study. ## 2.5. Ethics This study was realised in accordance with the Declaration of Helsinki (revised version of 2013). The Ethics Committee of the Medical Faculty of the University of Cologne and the Ethics Committee of the Medical Faculty of the University of Tuebingen stated that we are exempted from applying for ethical approval under German law. Purely retrospective clinical studies do not require ethical approval by the ethics committee. ## 2.6. Statistical Methods All data are presented as continuous or categorical variables. Categorical data are expressed as total numbers and percentages. Continuous data were evaluated for normality using a one-sample Kolmogorov–Smirnov test and were expressed as the mean ± standard deviation (SD) in cases of normally distributed data or as the median (min/max) in cases of non-normally distributed data. Either Pearson’s χ² test or Fisher’s exact test was used for comparison of categorical data, depending on the minimum expected count in each cross-table. Univariate and multivariate analyses were performed using binary logistical regression. Logistical regression was conducted in order to create the predicted variables. A rigorous 1:1 nearest neighbour-matching algorithm without replacement was used with a 0.2 calliper set. p-values < 0.05 were considered statistically significant. Statistical analysis was performed using Statistical Package for Social Sciences, version 28.1 (SPSS Inc., Chicago, IL, USA). ## 3.1. Preoperative Data Preoperative characteristics of the two groups before (non-obese, $$n = 193$$; obese, $$n = 139$$) and after (non-obese, $$n = 124$$; obese, $$n = 124$$) PSM are shown in Table 1. Women were significantly more prevalent ($$p \leq 0.002$$) in the obese group compared to the non-obese group before PSM. Cardiogenic shock ($$p \leq 0.033$$), diabetes mellitus ($p \leq 0.001$), chronic obstructive lung disease (COPD) ($$p \leq 0.002$$), chronic renal insufficiency ($$p \leq 0.007$$), and dialysis ($$p \leq 0.006$$) were significantly higher in obese patients compared to non-obese patients before PSM. In contrast, left main coronary artery disease (CAD) ($$p \leq 0.002$$) was significantly lower in the obese group before PSM. However, preoperative data was well-equalized between the two groups after 1:1 PSM. ## 3.2. Intraoperative Characteristics The intraoperative data of both groups before (non-obese ($$n = 193$$) and obese ($$n = 139$$)) and after (non-obese ($$n = 124$$) and obese ($$n = 124$$)) PSM are shown in Table 2. Total arterial revascularization (TAR) ($$p \leq 0.005$$) and the use of the T-graft technique ($p \leq 0.001$) were significantly higher in non-obese patients compared to obese patients before PSM. Likewise, the use of the T-graft technique was significantly higher ($$p \leq 0.045$$) in the non-obese group compared to the obese group after PSM. Further intraoperative data did not differ significantly between the two groups. ## 3.3. Postoperative Data Postoperative data before (non-obese, $$n = 193$$; obese, $$n = 139$$) and after (non-obese, $$n = 124$$; obese, $$n = 124$$) PSM are summarized in Table 3. The dialysis rate was significantly higher before ($p \leq 0.001$) and after ($$p \leq 0.019$$) PSM in the obese group compared to the non-obese group. In contrast, the wound infection rate was significantly higher ($$p \leq 0.014$$) in non-obese patients compared to obese patients. Regarding further secondary outcomes (bleeding requiring reoperation ($$p \leq 0.216$$), transient ischemic attack ($$p \leq 0.102$$), postoperative delirium ($$p \leq 0.450$$), and length of in-hospital stay ($$p \leq 0.058$$)), no significant differences were found between the non-obese and obese groups after PSM. The in-hospital mortality rate also did not differ between the two groups ($$p \leq 0.651$$) after matching. ## 3.4. Postoperative Data in Obese Patients Table 4 shows the postoperative data in obese patients, which are separated according to obesity class. Transient ischemic attack was significantly higher ($$p \leq 0.008$$) in the obesity class III compared to the other two obesity classes. In contrast, dialysis was significantly higher ($p \leq 0.001$) in obesity class II compared to the other classes. In-hospital mortality did not differ significantly ($$p \leq 0.230$$) between these patients. ## 3.5. Combined Risk Factors of In-Hospital Mortality The combined risk factors for in-hospital mortality after OPCAB surgery are shown in Table 5. Univariate analysis followed by multivariate analysis showed STEMI and the reoperation rate were relevant predictors for in-hospital mortality. Age, body mass index (BMI), diabetes mellitus, and non-ST-elevation myocardial infarction (NSTEMI) had no relevant impact on mortality. ## 4. Discussion This study compares non-obese and obese patients’ short-term outcomes after isolated OPCAB surgery. Our study showed that being obese (BMI≥30 kg/m2) was not associated with in-hospital mortality ($$p \leq 0.651$$) in OPCAB-treated patients. Other secondary outcomes, except dialysis and wound infections, were comparable between the two groups mentioned above. These results are consistent with data in the literature [10,12,13,14], but several authors investigated the short- and long-term results after mixed on-pump and off-pump CABG surgery [16,17]. So far, the data after isolated OPCAB surgery is insufficient [10,12,18]. The impact of obesity on short-term and long-term outcomes after OPCAB surgery still remains controversial [19,20]. Furthermore, authors reported a significantly higher 30-day mortality rate after OPCAB surgery in patients with decreased BMI [10,20]. Potapov et al. [ 21] analysed a large cohort of patients with low and high BMI. Authors found significantly higher morbidity and mortality rates in the underweight group compared to patients with high BMI [21]. In addition, Engelman et al. [ 7] mentioned that low BMI was associated with poor outcomes after off-pump cardiac surgery. However, underweight status was not a predictor for the increased mortality rate [7]. Moreover, Straten et al. [ 18] showed that both underweight status and morbid obesity could be predictors for early mortality after a CABG procedure. Further study showed that very low and very high BMI are associated with worse outcomes after bypass surgery [22]. In contrast, other authors did not show an increased mortality rate in obese patients after a CABG procedure [23]. Prapas et al. [ 24] analysed the effect of obesity on morbidity and mortality rates after isolated OPCAB procedures. Likewise, authors could not find any significant differences between the obese and non-obese groups [24]. Prabhakar et al. [ 25] showed that extreme obesity could be a significant predictor for adverse outcomes after bypass surgery. However, the mortality rate was not significantly higher in the obese group compared to the non-obese group [25]. Likewise, all-cause in-hospital mortality was not significantly higher ($$p \leq 0.651$$) in obese patients compared to normal-weight patients in our study. Obese patients in our study were not younger compared to non-obese patients, but they had a higher prevalence of comorbidities such as diabetes mellitus ($p \leq 0.001$), COPD ($$p \leq 0.002$$), chronic renal insufficiency ($$p \leq 0.007$$), and dialysis ($$p \leq 0.006$$). Other illnesses such as history of arterial hypertension, hyperlipidaemia, pulmonary hypertension, and peripheral vascular disease were similar in both groups. However, the short-term follow-up might not show the negative impact of obesity on mortality, and it may lead to potential bias [26,27]. The effects of obesity on wound healing are well-known [28,29]. Note that the authors all found that obese patients are at higher risk of deep sternal wound infections after open heart surgery [29]. Furthermore, inadequate haemostasis and the extreme use of diathermy were reported to increase the postoperative proliferation of microorganisms within the wound [28,29]. In addition, prolonged operative time and insufficient use of antibiotics might relieve bacterial contamination and lead to faster development of deep sternal wound infections in obese patients [28,30]. However, in our analysis, we found a significantly higher ($$p \leq 0.014$$) wound infection rate in non-obese patients compared to obese patients. Note that this may be due to the fact that both internal mammary arteries were used more frequently in the non-obese group. Several studies reported the association between the use of both internal thoracic artery (ITA) grafts and the increased risk of wound infection after bypass surgery [31,32]. These authors suggested that the removal of the two mentioned grafts may lead to decreased blood supply to the tissue, which is associated with an increased wound infection rate postoperatively [30,31,32]. The appropriate timing for surgical treatment in patients with NSTEMI and STEMI has been the subject of critical debate in recent years [33,34]. The recent guidelines have not provided any precise recommendations regarding the right operative timing for the above mentioned patients’ cohort [35]. Hochman et al. [ 36] showed that early (<72 h) CABG procedures in patients after STEMI in cardiogenic shock was associated with improved outcomes. The right timing for surgical therapy in patients with NSTEMI in cardiogenic shock was critically discussed [35]. Moreover, several studies stated that patients in acute coronary syndrome (ACS) who underwent CABG in the first 72 h showed adverse outcomes and higher mortality postoperatively [37,38]. However, patients were not divided into ACS subgroups, which could affect results [38]. Liakopoulos et al. [ 33] reported evidence of a lower survival rate associated with the strategy of emergency revascularisation in patients with ACS and a risk factor for in-hospital mortality. In contrast, Davierwala et al. [ 39] did not show any statistical difference regarding in-hospital mortality between emergency and delayed surgery in patients after NSTEMI only. Further authors hypothesized that delaying bypass procedures in patients after NSTEMI does not improve outcomes and could be associated with immense resource use and costs [40]. The short-, mid-, and long-term outcomes after STEMI compared to NSTEMI in obese patients after CABG surgery are controversial [33,34,40]. A previously published study showed that patients with STEMI showed poorer outcomes in the long-term follow-up compared to patients with NSTEMI after bypass surgery [41]. A significantly higher mortality rate was also described in patients with STEMI compared to patients with NSTEMI after acute myocardial infarction [41]. Additionally, a STEMI was shown to be an independent predictor of higher mortality [33,41]. We are able to demonstrate that STEMI still remains a relevant predictor of in-hospital mortality in our study. Several studies mentioned that obesity might be a risk factor for ischemic stroke [42,43]. In contrast, further authors found better functional outcomes after stroke in obese patients compared to non-obese patients after bypass surgery [44]. It could be hypothesized that the inflammatory response could be reduced due to the “protective” role of peripheral fat in overweight patients [44]. This controversial finding was described as the “obesity paradox” in previous studies [42,43,44,45]. We did not detect statistically significant differences in transient ischaemic attacks (TIA) and strokes in the obese group compared to the non-obese group in our study group. However, after dividing the obese patients by obesity classes, we found a significantly higher ($$p \leq 0.008$$) rate of TIA in patients from obesity class II compared to other obesity classes. As previously described, obesity was associated with an increased risk of renal failure and the development of end-stage renal disease after cardiac surgery [46,47]. Authors mentioned that oxidative stress and endothelial dysfunction could play a crucial role in the pathogenesis of kidney failure postoperatively [46]. In addition, increased inflammatory responses and endothelial dysfunction in obese patients were further risk factors of postoperative kidney failure development [48,49]. Moreover, further epidemiologic studies found that obesity was an independent predictor of chronic renal insufficiency after open-heart surgery [46,50]. The number of dialyses was also significantly higher in obese patients compared to non-obese patients after OPCAB procedures in our study ($$p \leq 0.019$$). In addition, patients belonging to obesity class II were statistically significantly more likely to have dialysis (<0.001) than patients belonging to classes I and III. These results could be replicated both before and after PSM analysis. According to our results, $28.6\%$ of patients from obesity class II had dialysis before PSM, and $20.8\%$ had dialysis after PSM. In contrast, Moulton et al. [ 51] could not find any differences regarding end-stage renal disease between these groups in their analysis [51]. The controversial results from the already mentioned trials could be related to the small patient cohorts and could be potentially biased [46,50,51]. Therefore, larger, ideally prospective trials are needed to verify or controvert these findings in the future. In conclusion, the expertise of the heart centre and perioperative treatment might have a significant influence on the patient’s outcome after bypass surgery, and they should be taken into consideration in our outcome evaluation. ## 5. Study Limitations Several limitations are associated with this study. First, it was a retrospective analysis at two centres with a non-large patient cohort. The sample size was not calculated due to the investigative character of the study. In addition, we focused on short-term outcomes and did not investigate long-term outcomes. Additionally, OPCAB surgery was performed by different surgeons, which could lead to a possible bias in the results presented. ## 6. Conclusions Obesity was not associated with increased in-hospital mortality in patients undergoing OPCAB procedures in our study. Nevertheless, STEMI and reoperation rates were relevant predictors of in-hospital mortality. 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--- title: Citral Modulates MMP-2 and MMP-9 Activities on Healing of Gastric Ulcers Associated with High-Fat Diet-Induced Obesity authors: - Rie Ohara - Felipe Lima Dario - Maycon Tavares Emílio-Silva - Renata Assunção - Vinícius Peixoto Rodrigues - Gabriela Bueno - Priscila Romano Raimundo - Lúcia Regina Machado da Rocha - Clelia Akiko Hiruma-Lima journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003425 doi: 10.3390/ijms24054888 license: CC BY 4.0 --- # Citral Modulates MMP-2 and MMP-9 Activities on Healing of Gastric Ulcers Associated with High-Fat Diet-Induced Obesity ## Abstract Obesity causes low-grade inflammation that results in the development of comorbidities. In people with obesity, exacerbation of gastric lesion severity and delayed healing may aggravate gastric mucosal lesions. Accordingly, we aimed to evaluate the citral effects on gastric lesion healing in eutrophic and obese animals. C57Bl/6 male mice were divided into two groups: animals fed a standard diet (SD) or high-fat diet (HFD) for 12 weeks. Gastric ulcers were induced using acetic acid ($80\%$) in both groups. Citral (25, 100, or 300 mg/kg) was administered orally for 3 or 10 days. A vehicle-treated negative control ($1\%$ Tween 80, 10 mL/kg) and lansoprazole-treated (30 mg/kg) were also established. Lesions were macroscopically examined by quantifying regenerated tissue and ulcer areas. Matrix metalloproteinases (MMP-2 and -9) were analyzed by zymography. The ulcer base area between the two examined periods was significantly reduced in HFD 100 and 300 mg/kg citral-treated animals. In the 100 mg/kg citral-treated group, healing progression was accompanied by reduced MMP-9 activity. Accordingly, HFD could alter MMP-9 activity, delaying the initial healing phase. Although macroscopic changes were undetectable, 10-day treatment with 100 mg/kg citral exhibited improved scar tissue progression in obese animals, with reduced MMP-9 activity and modulation of MMP-2 activation. ## 1. Introduction In 2016, it was estimated that $39\%$ of the global adult population aged ≥ 18 years ($39\%$ of males and $40\%$ of females) were overweight, and $13\%$ were deemed obese [1]. Obesity is characterized by excessive adipose tissue accumulation due to an imbalance between high consumption and low energy expenditure [2]. The excessive adipose tissue is deposited as visceral adipose tissue, which is well-known to secrete pro-inflammatory cytokines, resulting in a low-grade inflammatory condition. More recently, visceral adipose tissue accumulation has been associated with the development of comorbidities, such as insulin resistance, dyslipidemia, hypertension, and cardiovascular disease [3]. Obesity-induced systemic inflammation is triggered by immune cell recruitment, the interaction and activation of these immune cells, and the release of inflammatory molecules. In addition, a combination of other events participates in maintaining this inflammatory condition [4]. The offer of a high-fat diet (HFD) is an important preclinical model for the obesity study in animals, as it induces an increase in adipose tissue and has been identified as an important factor in the inflammation development during the disease [5]. Rapid adipose tissue expansion after ingestion of an HFD can induce systemic physiological changes that directly impact the functioning of certain organs [4]. Individuals with obesity often experience altered gastric emptying time [6]. Abdominal obesity, known to be characterized by increased visceral fat, has been associated with the onset of several gastrointestinal tract diseases, owing to an increase in intra-abdominal pressure due to excessive adipose tissue accumulation [7]. Furthermore, adipose tissue can locally secrete adipocytokines and other factors, such as tumor necrosis factor (TNF)-α and interleukin (IL)-6, which may be involved in the aggravate gastric lesions; this has been observed in studies investigating the mechanism of action of antiulcerogenic agents, where the inhibition of these cytokines afforded gastroprotection [7,8]. The association between obesity and peptic ulcers has been previously explored; however, the results remain controversial. Recently, a cohort study demonstrated a direct correlation between genetically predicted obesity and peptic ulcer disease, mainly, when observed with non-NSAIDs user patients, another important factor of the development of peptic ulcers [9]. Furthermore, it can be speculated that mechanisms underlying the potential association between obesity and peptic ulcers could be aggravated by low-grade chronic inflammation [7]. Although an association between the two diseases remains elusive, obesity-induced poor vascularization directly impacts the skin healing process, given the hindered recruitment of angiogenic factors necessary for the complete healing of the lesion [10]. Disruption of the mucous layer of the stomach results in ulcer formation. Several factors have been implicated in ulcer formation, including decreased production of mucus and bicarbonate, which may be attributed to the insufficient blood supply, *Helicobacter pylori* infection, or overuse of nonsteroidal anti-inflammatory drugs (NSAIDs) [11,12] Gastric lesions can be histologically classified into two parts: the base and margin of the ulcer. The base of the ulcer is the necrotic region, where granulation connective tissue, comprising fibroblasts, macrophages, and endothelial cells, is known to predominate. Conversely, the ulcer margin, referred to as regenerating tissue in the present study, consists of dedifferentiated proliferating epithelial tissue, expressing high levels of growth factors [13]. Currently, the main treatment strategy for gastric ulcers involves the use of acid secretion inhibitors, primarily proton pump inhibitors and histamine receptor antagonists; however, these drugs often induce adverse reactions, such as abdominal pain, nausea, constipation, and flatulence. Prolonged use of proton pump inhibitors has also been associated with liver damage and an increased risk of developing gastric cancer, thereby restricting the treatment duration, in addition to causing adverse effects in other systems, such as kidney disease, dementia, and bone fractures [14,15]. Therefore, all currently employed drugs fail to promote effective re-epithelialization of the lesion with new vessel formation for adequate blood supply to the tissue, thereby leading to ulcer recurrence and worsening [16]. Similar to gastric ulcer formation, the healing process is multifactorial and complex and involves re-epithelialization, restoration of glands, angiogenesis, and extracellular matrix (ECM) deposition [13]. The ECM is a complex multimolecular structure comprising collagen and elastin fibers and structural glycoproteins, including fibronectin, laminin, and mucopolysaccharides. Under physiological conditions, a balance exists between the synthesis, deposition, and degradation of ECM components, and its composition varies among multicellular structures, with fibroblasts and epithelial cells being the most common cell types [17]. The main enzymes participating in ECM synthesis and degradation include matrix metalloproteinases (MMPs), zinc-dependent proteases that play a crucial role in ECM remodeling via proteolytic degradation of its components, surface protein activation, and release of membrane-bound receptor molecules [18]. MMPs with gelatinase activity hydrolyze gelatin into polypeptides, peptides, and amino acids, which are subsequently secreted across the cell membrane. MMP-2 and -9 are gelatinases that facilitate the binding of gelatin and collagen through three fibronectin type II-like repeat domains inserted into the catalytic domain of the structure. MMP-2 and -9 are fundamental in the healing process, as they play a pivotal role in accelerating cell migration and re-epithelialization, respectively [18,19]. In gastric ulcers, degradation of the gastric mucosa is directly related to ECM degradation. MMP-9 is secreted mainly by neutrophils and macrophages and acts during the initial phase of healing. Patients with gastric ulcers reportedly exhibit increased MMP-9 production at the edge of the lesion. Furthermore, elevated MMP-9 activity was detected in tissues where the lesion was associated with a high risk of ulcer recurrence, suggesting that MMP-9 is a marker for poor healing [20]. MMP-2 is primarily secreted by fibroblasts and leukocytes, and its activity is considered critical during the initial phase because it accelerates cell migration. However, in the proliferative phase, this increase is related to the fragility of the regenerated tissue [21]. Some pathological processes, such as adipose tissue expansion, are involved in regulating proteolytic enzymes. Reportedly, patients with obesity exhibit increased plasma levels of MMP-2 and -9. In addition, HFD-fed animals exhibited increased MMP-9 expression in visceral adipose tissues [17,22]. Considering the multifactorial nature of obesity associated with gastrointestinal diseases, a promising alternative for treating this condition is utilizing molecules from natural products, given that their multi-target potential has been reported [23]. Natural products are excellent resources for identifying new pharmacological agents, given their structure and potential template for synthetic modification and optimization of selectivity and bioavailability [24]. Citral is a compound of plant origin found in lemon grass (*Cymbopogon citratus* and C. flexuosus), lemon balm (Melissa officinalis), and ginger (Zingiber officinale). It is widely used in the food, cosmetic, chemical, and pharmaceutical industries and is incorporated into fragrances, food, and beverages [25,26,27,28]. Chemically, citral is classified as an acyclic monoterpene, which is a mixture of two isomers: the neral cis isomer and geranial trans isomer [29]. Monoterpenes have been pharmacologically explored for their anti-inflammatory, antioxidant, and antibiotic activities. Considering gastric ulcers, monoterpenes were shown to exhibit activities ranging from injury prevention to accelerating the healing process [30]. Previously, we have reported that citral can promote gastroprotection in an NSAID-induced gastric injury model [31] however, the effect of citral on gastric ulcer healing in an obesity model remains unexplored. Therefore, we aimed to evaluate the effect of citral during the initial and late phases of the gastric ulcer healing process in eutrophic and obese mice. ## 2.1. Induction of Obesity by HFD Ingestion For the pharmacological evaluation of citral, the C57Bl/6 strain was used, given that this strain is more prone to the development of comorbidities resulting from obesity. Over 12 weeks (84 days), the body mass of each animal was measured twice weekly and from the third week onward. We detected a significant increase ($10.1\%$; $p \leq 0.05$) in the body mass of HFD-fed animals when compared with that of SD-fed animals. Figure 1 shows the statistical difference from the third week after initiating HFD ingestion compared with animals fed an SD. At the end of the obesity induction period, the body mass of mice fed different diets differed by $51.8\%$ ($p \leq 0.0001$), demonstrating that the employed strain responds well to the ingestion of an HFD, considering body weight gain. At the end of the treatment, animals were euthanized, and their abdominal (TAA), epididymal (TAE), and retroperitoneal (TAR) adipose tissues were harvested. To calculate the adiposity index, the masses of TAA, TAE, and TAR were summed, and the total value was divided by the mass of the animal. HFD-fed animals exhibited a 2.3-fold greater adiposity index ($p \leq 0.0001$) than those fed the SD (Table 1). To verify the metabolic alterations, the lipid profile and the blood glucose levels of groups treated for 10 days were evaluated (Table 1). As shown in Table 1, the total cholesterol in HFD-fed animals was $31.8\%$ ($p \leq 0.001$) higher than that in SD-fed animals. Likewise, the serum level of LDL was altered, with an increase of 1.8-fold ($p \leq 0.0001$) detected in HFD-fed animals when compared with that in SD-fed animals (Table 1). Despite the increase in total cholesterol and LDL, HDL levels were unchanged in the HFD-fed animals (Table 1). Therefore, we confirmed that at the end of 12 weeks of HFD ingestion, C57Bl/6 mice exhibited increased body mass, elevated adiposity index, and high serum levels of total and LDL cholesterol. ## 2.2. Acetic Acid-Induced Gastric Ulcer Herein, we detected no regenerating tissue in the early phase of healing (Figure 2). Accordingly, Figure 3 represents a comparison between treatments only in the regenerating tissue area of animals treated for 10 days after lesion induction. There was no significant difference in tissue regeneration areas between animals that received different treatments and the vehicle. We compared the base areas of the ulcer regardless of treatment and observed that HFD-fed animals exhibited a reduction in lesion area in $35.2\%$ of the stomachs when compared with that in SD-fed ($p \leq 0.001$); this difference is shown in Figure 4B. Despite the difference in the initial phase, there was no significant difference in the area of injury between diets after 10 days of treatment, indicating that the healing rate in SD-fed animals was higher and faster than those in HFD-fed animals. Regarding the evolution of healing, all groups fed an SD showed a significant reduction in the ulcer base area over time. Among HFD-fed animals, only the groups that received daily treatment with 100 and 300 mg/kg citral exhibited a significant reduction in the ulcer base area between days 3 and 10 after ulcer induction. Figure 5 presents a representative image of one stomach from each experimental group. ## 2.3. MMP Activity To more specifically evaluate the effects of citral, especially at doses exhibiting a significant reduction in the ulcer base area in HFD-fed animals, we quantified the activity of MMP-2 and -9 ($$n = 4$$–5), which are known to mediate ECM degradation, cellular migration, and re-epithelialization (Figure 6). Regarding temporal evolution, comparing only the different treatment periods regardless of the treatment received, we detected a $20\%$ increase in MMP-2 activity in the stomachs of animals that received treatment for 10 days when compared with those treated for 3 days ($p \leq 0.05$). Figure 6A shows the rate of MMP-2 activation. The MMP-2 activation rate was significantly increased in all groups, except in HFD-fed animals administered 100 mg/kg citral and SD-fed animals administered 300 mg/kg citral. It should be noted that groups exhibiting no changes in MMP-2 activation rate demonstrated the highest rate of lesion area reduction. Considering the MMP-9 activity, we detected no difference between treatments when comparing groups that received the same diet and those treated for the same period. In addition, diet change induced no significant difference within animal groups receiving the same treatment for the same duration. We evaluated the temporal evolution of MMP-9 activity and detected a difference between the initial and late phase MMP-9 activity in the SD-fed animals administered 25 mg/kg citral. Within the HFD-fed animals, the MMP-9 activity was significantly increased between days 3 and 10 in animals administered lansoprazole and 100 mg/kg citral (Figure 6B). We speculate that the reduction in the ulcer base area could be associated with decreased MMP-9 activity, given that this enzyme acts mainly in the inflammatory phase of the lesion; consequently, reduced MMP-9 activity indicates the resolution of the lesion and its progression to the proliferative phase, during which its activity is more harmful than beneficial. ## 3. Discussion Diet is an important determinant of human health and disease, and imbalanced eating habits are critical risk factors for obesity and metabolic disorders [4]. Ingestion of a HFD induces an increase in free fatty acids, responsible for raising the amount of reactive oxygen species, which defines oxidative stress and is responsible for the increased expression of pro-inflammatory cytokines, resulting in chronic low-grade inflammation [32]. The association between obesity and peptic ulcers has been studied, but the results of these investigations are still limited. A study carried out with health professionals in the United States of America showed an increased risk of gastric ulcers in people with obesity [33]. Therefore, the objective of the present study was to determine whether citral could overcome these changes in the healing of gastric ulcers induced by acetic acid. To examine the association between obesity and the ulcer healing profile, we selected the C57Bl/6 strain, as it has a greater predisposition for developing metabolic alterations associated with HFD ingestion [34]. Some studies have shown that the time of HFD ingestion can impact serum changes [4]. In the present study, we confirmed changes in body weight, adiposity index, and lipid profile (Table 1); therefore, the use of the C57Bl/6 strain proved to be efficient in meeting our objective. The main limitation of this study was the severity of the injury caused by acetic acid in the stomach of mice. In studies using rat models, lansoprazole, belonging to the class of proton pump inhibitors and the most frequently used pharmacological class for treating gastric ulcers, was found to be effective in reducing the lesion area of animals with acetic acid-induced ulcers [35]. However, in the present study, we did not detect a significant difference in the lesion area between lansoprazole- and vehicle-treated animals. Despite this limitation, we detected changes in the healing process promoted by other oral treatments administered. We evaluated 3- and 10-day treatment durations, given that these are established healing phases during which distinct types of mediators are known to act: three days after lesion induction, inflammatory cells are predominant, along with tissue necrosis and formation of granulation tissue in the ulcer margin. Until approximately day 10 after injury induction, intense migration of epithelial cells occurs. It leads to re-epithelialization of the ulcer and angiogenesis in the ulcer bed, at which point the completion phase of the healing process is initiated [36]. Herein, our data were corroborated by the significant differences in the area of regenerated tissue between animals treated for 3 and 10 days (Figure 4). The ECM has been widely explored as a pharmacological target, especially when tissue repair is required, as the dynamics of this complex structure can determine several crucial factors for the healing process [37]. Gastric lesions are directly associated with the degradation of the ECM, wherein MMPs play a crucial role [20]. Experimental and clinical studies have reported that the synthesis and activities of MMP-2 and -9 are altered during metabolic syndrome or according to variations in diet types ingested. Patients with obesity reportedly exhibit an increase in both MMP-2 and -9 plasma levels [22]. In animal models, MMP levels in adipose tissue differ according to the type of diet administered; a decrease in MMP-9 was reported in animals fed a diet rich in sucrose, with no change in plasma levels. However, in HFD-induced obese animals, increased MMP-9 activity has been reported in abdominal adipose tissue [17]. Regarding the healing of gastric ulcers, it can be postulated that appropriate healing will occur when activities of MMP-2 and -9 decrease gradually, given that in the late period, their actions are detrimental to the healing process [18]. In the present study, the reduction in the ulcer base area observed in the C2-HFD group could be associated with decreased MMP-9 activity, as this enzyme mainly acts during the inflammatory phase of the lesion. Consequently, the reduction in its activity indicates the resolution of the lesion and its progression to the proliferative phase, during which MMP-9 activity is more harmful than beneficial [18]. Furthermore, the presence of MMP-9 in chronic ulcers has been linked to lesion recurrence [20]; hence, in the late phase of healing, the reduction in its activity can be considered advantageous for the resolution of tissue injury. Herein, we analyzed MMP-2 bands separately and classified them as pro and active. Based on these values, we obtained the activation rate of these enzymes for each treatment. Notably, only animals in the SD-C3 and HFD-C2 groups did not exhibit a significant and gradual increase in MMP-2 activation. Considering this finding along with the lesion area of each treatment, we suggest that modulation of MMP-2 activity was achieved by treatments that did not significantly increase MMP-2 activation within 10 days of lesion induction, thereby potentially contributing to the reduced lesion area, as high MMP-2 activity in the late healing phase is indicative of poor healing. Several studies in different models of gastric lesion induction show the importance of metalloproteinases in the course of healing, and the results obtained in this investigation provide information that can be used to deepen studies on the role of citral in the synthesis and degradation of each of the components of the extracellular matrix [38,39,40]. Thus, we demonstrated the effect of citral on temporal modulation of MMP-2 and -9 in wound healing in acetic acid-induced gastric ulcers in SD and HFD-fed mice. It is also known that the association between MMPs and collagen synthesis is an important factor in the development of wound healing. The collagen is the most abundant protein in ECM, which gives structural and functional support for cells, and its degradation is involved in tissue repair and wound healing. The denatured collagen is called gelatin and is degraded by gelatinases, mainly MMP-2 and 9. These MMPs also degrade some ECM glycoproteins and cytokines such as IL-8 and IL-1β [41]. Collagen deposition in ulcer bed is a determinant factor for healing while collagen peptides can promote cell migration and proliferation. In a study that evaluated the oral treatment with human-like collagen and human-like collagen products in rats, a reduction in lesion area was shown and these treatments enhanced cell and microvessel proliferation. Furthermore, the human-like collagen treatment promoted collagen deposition [15]. Moreover, an in vitro study has shown that citral treatment in osteoblast-like MG-63 cells induced an increase of collagen levels, leading to an osteogenic effect [42]. In addition to it, a study evaluating the effect of nano emulsion polyvinyl alcohol/chitosan hybrid incorporated with citral on healing of infected full-thickness skin wound showed an elevation in the amount of collagen and fibroblast infiltration in granulation tissue, accompanied by significant ulcer area reduction [43]. In present study, it is possible to hypothesize that citral acts in collagen availability in the gastric tissue, mainly due to the significant decrease in MMP-9 activity, the non-exacerbated elevation of MMP-2 activity in ulcers, decreasing the ulcer bed area after 10 days of treatment. When evaluating the action of citral against gastric ulcer associated with obesity, we found that citral promotes different responses in animals that receive different diets. The initial hypothesis of this study was that the low-grade inflammatory condition caused by obesity would make it difficult to respond to pharmacological treatments, but the results obtained so far have shown the opposite. The variation in the pharmacological response in animals fed SD and HFD may be due to the increase in adipose tissue, which generates an increase in body weight and changes physiological functions such as blood flow distribution, modifying the pharmacokinetics of drugs in obese individuals [44]. There are some hypotheses to explain the different responses observed in the same treatment: the direct interaction of the treatment administered with the food ingested, which can occur due to physiological reactions, including changes in pH, gastrointestinal tract motility or secretion of bile acids. In addition, body composition also influences drug pharmacokinetics with regard to drug absorption, distribution, and metabolism. Some drugs are affected by food intake in general, and it is suggested that diets with a high calorie and lipid content have the greatest effect on pharmacokinetic properties [44]. Therefore, the results observed in the present study reiterate the importance of particularly evaluate the pharmacological activity in organisms with different nutritional conditions. ## 4.1. Animals C57Bl/6 male mice, 120 fed SD and 120 fed HFD (total = 250 mice, 120 for each period evaluated), aged 4 to 6 weeks, from the Multidisciplinary Center for Biological Research in the Field of Science in Laboratory Animals (UNICAMP). All animals were acclimatized to the conditions of the sectorial vivarium for at least seven days before experimental manipulation, under a controlled temperature ranging between 23 and 25 °C and a 12-h light-dark cycle. The mice were housed in solid-bottom boxes lined with wood shavings and were fed a commercial diet (Presence, Jaguaribara, CE, Brazil) or high-fat diet (PragSoluções Biociências, Jaú, SP, Brazil) and water ad libitum. All protocols were approved by the Ethics Committee on the Use of Animals of the Institute of Biosciences of Botucatu (approval number 1208). ## 4.2. Obesity Induction For obesity induction, animals were divided into two groups. The first group received a commercial diet (SD, Presence, Jaguaribara, CE, Brazil) and the second group received a high-fat diet (HFD, PragSoluções Biociências, Jaú, SP, Brazil). The HFD, which has $60\%$ of its total calories from lipids, was prepared following the supplier’s instructions (PragSoluções Biociências, Jaú, SP, Brazil). All components, shown in Table 2, were weighed on a precision scale and mixed, respecting biosafety and then stored in 1 kg packages at 4 °C. Comparatively, the SD has only $16\%$ of its total calories from lipids. The dietary intervention was performed for 12 weeks (84 days), and animals were weighed twice weekly, along with the food intake. Comparatively, the SD has only $16\%$ of its total calories from lipids. The dietary intervention was performed for 12 weeks (84 days), and animals were weighed twice weekly, along with the food intake [44]. ## 4.3. Experimental Design We evaluated the citral (Sigma, St. Louis, MO, USA)-mediated effects during the early (3 days) and late phases (10 days) of healing. For both, mice were divided into two diet groups: standard diet (SD) and high-fat diet (HFD). After obesity induction, each diet group was redivided into six subgroups ($$n = 10$$/each) according to oral treatments: vehicle (V—Tween 80, $1\%$); lansoprazole (L—30 mg/kg); three doses of citral (C1—25 mg/kg; C2—100 mg/kg and C3—300 mg/kg) and sham, the subgroup that underwent laparotomy without lesion induction and was not treated (Figure 7). These divisions totalize 24 subgroups considering healing phases, diets and oral treatments. Citral doses were selected based on previous studies [31]. For inducing euthanasia, mice were anesthetized with isoflurane (Isoforine®, Cristália–Produtos Químicos Farmacêuticos Ltd.a., Itapira, SP, Brazil), and blood was obtained by cardiac puncture 24 h after administering the last treatment; subsequently, blood was centrifuged to collect the sera for further biochemical estimations. ## 4.4. Acetic Acid-Induced Gastric Ulcer For lesion induction, animals were anesthetized using isoflurane. The induction rate was $2\%$, and the maintenance rate was 2.5 to $3\%$ in the low-flow inhalation anesthesia system equipment (Bonther, Ribeirão Preto, SP, Brazil). After anesthesia induction, the animals underwent laparotomy, and the stomach was exposed topically to 25 µL of acetic acid $80\%$. The contact area with acetic acid was limited using a plastic ring (diameter, 3.75 mm). After 20 s of exposure, acetic acid was removed, and the stomach was washed with saline ($0.9\%$ NaCl) to remove any residue. After establishing the lesion, the animals were sutured and returned to their respective boxes [45,46]. To evaluate the effects of citral, the animals were divided into five treatment groups: vehicle (V), Tween 80, $1\%$, used as a negative control; lansoprazole (L) (Ravoos Laboratories, Hyderabad, India), at a dose of 30 mg/kg, a drug used to treat gastric ulcers; citral (Sigma, St. Louis, MO, USA) at doses of 25, 100, and 300 mg/kg (C1, C2, and C3, respectively). For each experiment, the sham group included animals that underwent laparotomy without inducing injury. As the protocol involved a surgical procedure, a considerable loss of animals was observed during and after surgery until the experimental endpoint. Herein, we recorded a loss of approximately $25\%$ in eutrophic and obese animals. ## 4.5. Biochemical Parameter The serum levels of glucose, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL) and triglycerides were evaluated, using the colorimetric kits for glucose (Ref. K082 BioClin, Belo Horizonte, MG, Brazil), tryglicerides (Ref. K117, BioClin, Belo Horizonte, MG, Brazil), LDL (Ref. K088, BioClin, Belo Horizonte, MG, Brazil), HDL (Ref. F03120B, DIALAB Produktion und Vertrieb von chemisch-technischen Produkten und Laborinstrumenten, Neudorf, Austria) by dry chemistry according to the manufacturer’s instructions. ## 4.6. Macroscopic Analysis To analyze the lesion area, we adopted the methodology previously described to identify ulcer structures [15]. The established methodology was modified to allow macroscopic aspect evaluation according to the following classification: the ulcer was considered the thinnest part surrounded by the regenerating tissue (Figure 2). Tumescent tissue around the ulcer was classified as regenerating tissue. Quantification was performed using the ImageJ software (National Institute of Mental Health, Bethesda, MD, USA). ## 4.7. Quantification of MMP-2 and MMP-9 by Zymography The lesion tissue was separated and homogenized with an extraction buffer (50 mM Tris-HCl pH 7.4, 0.2 M NaCl, $0.1\%$ Triton-X 100, 10 mM CaCl2, and $1\%$ protease inhibitor cocktail). The homogenates were subjected to $8\%$ sodium dodecyl sulfate-polyacrylamide gel electrophoresis containing 1 mg/mL gelatin (Sigma, St. Louis, MO, USA) under non-reducing conditions. The gels were washed twice in $2.5\%$ Triton-X-100 (Sigma, St. Louis, MO, USA) and then incubated in calcium assay buffer (40 mM Tris and HCl, pH 7.4, 0.2M NaCl, and 10 mM CaCl2) for 18 h at 37 °C. The gels were stained with $0.1\%$ Coomassie blue, followed by decolorization. Zones with gelatinolytic activity served as negative staining. The zymographic bands were quantified using optical densitometry linked to ImageJ software (National Institute of Mental Health, Bethesda, MD, USA) [46]. ## 4.8. Statistical Analysis Data are expressed as mean ± standard error of the mean (S.E.M.) of examined parameters. A one-way analysis of variance (ANOVA) followed by the Student’s t-test was performed to compare the effect of diets, regardless of the treatment administered. To evaluate the temporal evolution of healing, different periods of the same treatment were compared between animals receiving the same diet; for this comparison, a two-way ANOVA followed by the Bonferroni test was performed. To compare the treatment effects within groups receiving the same diet, the Dunnet test was performed, in which comparisons were made between groups that received lansoprazole and citral at three doses relative to the negative control group. Comparisons were separately performed for the 3- and 10-day treatments. Finally, to verify the effects of different diets, we compared the evolution of lesions within the same treatment administered for the same period using the Bonferroni post-test. For all analyses, $p \leq 0.05$ was accepted as statistically significant. All experimental dates were analyzed using GraphPad Prism (GraphPad Software, San Diego, CA, USA). ## 5. Conclusions Herein, we demonstrated that 100 mg/kg citral administration could enhance the healing rate in obese C57Bl/6 mice when compared with the other treatments and diet ingestion. This improvement of the reduced lesion area was accompanied by decreased tissue MMP-9 and modulation of MMP-2 activation. ## References 1. **WHO|Overweight and Obesity** 2. Hall K.D., Guo J.. **Obesity Energetics: Body Weight Regulation and the Effects of Diet Composition**. *Gastroenterology* (2017.0) **152** 1718-1727.e3. DOI: 10.1053/j.gastro.2017.01.052 3. 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--- title: Treatment with the Olive Secoiridoid Oleacein Protects against the Intestinal Alterations Associated with EAE authors: - Beatriz Gutiérrez-Miranda - Isabel Gallardo - Eleni Melliou - Isabel Cabero - Yolanda Álvarez - Marta Hernández - Prokopios Magiatis - Marita Hernández - María Luisa Nieto journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003427 doi: 10.3390/ijms24054977 license: CC BY 4.0 --- # Treatment with the Olive Secoiridoid Oleacein Protects against the Intestinal Alterations Associated with EAE ## Abstract Multiple sclerosis (MS) is a CNS inflammatory demyelinating disease. Recent investigations highlight the gut-brain axis as a communication network with crucial implications in neurological diseases. Thus, disrupted intestinal integrity allows the translocation of luminal molecules into systemic circulation, promoting systemic/brain immune-inflammatory responses. In both, MS and its preclinical model, the experimental autoimmune encephalomyelitis (EAE) gastrointestinal symptoms including “leaky gut” have been reported. Oleacein (OLE), a phenolic compound from extra virgin olive oil or olive leaves, harbors a wide range of therapeutic properties. Previously, we showed OLE effectiveness preventing motor defects and inflammatory damage of CNS tissues on EAE mice. The current studies examine its potential protective effects on intestinal barrier dysfunction using MOG35-55-induced EAE in C57BL/6 mice. OLE decreased EAE-induced inflammation and oxidative stress in the intestine, preventing tissue injury and permeability alterations. OLE protected from EAE-induced superoxide anion and accumulation of protein and lipid oxidation products in colon, also enhancing its antioxidant capacity. These effects were accompanied by reduced colonic IL-1β and TNFα levels in OLE-treated EAE mice, whereas the immunoregulatory cytokines IL-25 and IL-33 remained unchanged. Moreover, OLE protected the mucin-containing goblet cells in colon and the serum levels of iFABP and sCD14, markers that reflect loss of intestinal epithelial barrier integrity and low-grade systemic inflammation, were significantly reduced. These effects on intestinal permeability did not draw significant differences on the abundance and diversity of gut microbiota. However, OLE induced an EAE-independent raise in the abundance of Akkermansiaceae family. Consistently, using Caco-2 cells as an in vitro model, we confirmed that OLE protected against intestinal barrier dysfunction induced by harmful mediators present in both EAE and MS. This study proves that the protective effect of OLE in EAE also involves normalizing the gut alterations associated to the disease. ## 1. Introduction Multiple sclerosis (MS) is an immune-mediated, chronic neurodegenerative disease characterized by a persistent inflammatory and oxidative state that leads to axon demyelination and neuroaxonal degeneration [1,2]. The etiology is not well understood, but arises from a complex interplay between genetics and environmental factors [3]. The heterogeneity of the MS symptoms includes muscle weakness, spasticity, paralysis, blurred vision, and gastrointestinal problems, among others [4]. Bladder and bowel symptoms have been rated as the third most important after spasticity and incoordination. Alterations of gut-derived products, intestinal permeability, and enteric nervous system functions have been described in MS patients, and the gut-brain axis is being considered as a key player in MS pathogenesis [5,6]. Thus, intestinal mucosal barrier breakdown will allow microorganisms, pathogens, and potentially large antigenic molecules to pass through; it will destroy the immune homeostasis and, subsequently, trigger systemic inflammatory response, and participate in the development of autoimmune diseases in the final [7]. At present, no cure for MS is known, and current therapies are directed towards modulation of the immune response to reduce the severity and relapses of the disease. However, given the increasing evidence that support oxidative stress as an important component in the pathogenesis of MS, other treatment regimens, including antioxidants, might confer beneficial effects [2,8]. Furthermore, looking for non-canonical targets may guide the field towards future therapeutic approaches in MS. Experimental autoimmune encephalomyelitis (EAE) induced with a myelin oligodendrocyte glycoprotein (MOG) peptide is one of the most popular experimental models used for studying MS [9]. The MOG35-55-induced EAE in rodents closely resembles the clinical and immunopathological features of the human disease, including some intestinal alterations [10,11]. Oleacein (OLE) is one of the main secoiridoids of extra virgin olive oil (EVOO). OLE is released during the mechanical extraction process by the action of the olive fruit enzymes acting on precursor molecules such as oleuropein. Many of the beneficial health properties of EVOO have been attributed to a high content of monounsaturated acids, as well as to other minor components, among which phenolic alcohols and secoiridoid derivatives such as the OLE are found [12,13]. Although OLE does not exist in the intact olive leaves, it can be very easily produced from them, as has recently been shown [14]. OLE can be produced during the extraction procedure by the combined action of oleuropein glucosidase and demethylase, which are present in the leaves, on oleuropein, which is the most abundant secoiridoid in the olive leaves. The production of OLE from olive leaves using a large-scale and affordable method of selective extraction has offered easy access to this molecule for further investigation and also for development as an ingredient of food supplements or potential new drugs. OLE has demonstrated to possess antioxidant, anti-inflammatory, anti-proliferative and immunomodulatory bioactivities that are partially responsible for the beneficial effects of EVOO on human health [13,14,15,16,17,18]. Moreover, in vivo administration of OLE did not exhibit signs of toxicity [19]. The wide spectrum of its biological activities includes cardioprotective, antimicrobial, neuroprotective, and anti-cancer effects [15,20,21]. In a recent preclinical study, we observed that, by targeting immune–inflammatory and oxidative responses, OLE improved clinical signs and motor deficits of EAE mice, suggesting a protective role of this secoiridoid against this neurodegenerative disorder. However, the effect of OLE on the intestinal alterations linked to MS/EAE has not been addressed. In this study, we focused on EAE-intestinal dysfunction and we unraveled the impact of OLE treatment on gut barrier protection. ## 2.1. OLE Treatment Protected against EAE-Induced Intestinal Mucosal Barrier Damage in Mice In previous research, we demonstrated that OLE administration to EAE mice protected CNS tissues from inflammatory damage and was sufficient to ameliorate the classical EAE neurological signs. Herein, we addressed the OLE effect on EAE-associated gut intestinal dysfunction. The study was performed on day 24 after EAE induction (acute phase of the disease): Mice of the untreated-EAE group showed one-sided hind limb paralyses (clinical score 2), at minimum, and mice in the OLE-treated EAE group showed an inability to curl the distal end of the tail (clinical score 0.5) (Figure 1B and Figure S1). EAE disease severity was quantified using a standard numerical scale as described in Methods [22]. Although OLE treatment significantly reduced the disease severity in EAE mice, no major changes were found on disease incidence (Untreated EAE, $\frac{10}{10}$; OLE-treated EAE mice, $\frac{9}{10}$). Firstly, we performed a macroscopic inspection of the intestine. We did not observe significant differences in the ratio colon length/body weight among mice of the different experimental groups (Figure 1C,D). Besides, cecal examination showed that the full cecal weight, as well as the ratio full cecum weight/body weight (cecal index), were higher in EAE mice, and OLE treatment prevented this increase (Figure 1E,F); this change may warrant further investigation. Next, to investigate the impact of OLE treatment on intestinal barrier function on EAE mice, we evaluated ex vivo the intestinal permeability to 40 kDa FITC-labelled dextran in a non-everted gut sac model using two different segments of intestine: colon and ileum (Figure 2A,B). Colonic and ileal sacs from EAE mice tissues exhibited an increased paracellular permeability when compared to those of the control group ($p \leq 0.001$). However, intestinal sacs from OLE-treated EAE mice displayed a reduced FD40 passage demonstrating that OLE was able to preserve the gut barrier function. In addition, we evaluated surrogate serological markers of impaired intestinal permeability and microbial translocation; the intestinal fatty acid-binding protein (iFABP) and sCD14. As shown in Figure 2C, EAE induction significantly increased the serum levels of iFABP and sCD14 compared with healthy control mice ($p \leq 0.001$), whereas OLE treatment significantly attenuated this response ($p \leq 0.01$). Next, AB-PAS staining was conducted to determine changes in mucins content in the colon of mice of the different experimental groups. As shown in Figure 3A, OLE treatment prevented the significant decrease in the overall AB/PAS staining detected in colon sections from untreated-EAE mice. Although we observed a significant reduction in the expression of both acidic and neutral mucins in colon of EAE mice, the ratio acidic/neutral mucin species between the healthy control and EAE mice kept constant at 2:1. The expression levels of galectin-3 (Gal-3), a protein linked to mucin expression, were decreased in colon from EAE mice, compared with healthy control mice ($p \leq 0.01$), whereas treatment with OLE prevented this reduction, keeping values similar to those of the control group (Figure 3B). In contrast, higher Gal-3 levels were found in the serum of EAE mice when compared with the control group, and OLE administration protected them from this rise (Figure 3C). In addition, the expression levels of the glial-derived neurotrophic factor (GDNF), a novel regulator of the intestinal epithelial barrier function, was diminished in both colon and serum of EAE mice, and OLE treatment abolished this reduction (Figure 3B,C) [23]. It is worth noting that OLE administration to the control group did not significantly affect any of the above studied parameters. ## 2.2. OLE Treatment Reduced Colon Levels of Inflammatory Markers in EAE Mice We also examined parameters of intestinal inflammation in the different experimental groups. We found that OLE significantly reduced the levels of the pro-inflammatory cytokines TNFα and IL-1β, which were observed up-regulated in colon tissue from EAE mice (Figure 4). Additionally, the expression levels of the two potent type-2 inducing cytokines IL-33 and IL-25 were down-regulated in colon from EAE mice, compared to healthy control mice; and OLE treatment protected against this decrease (Figure 4). ## 2.3. OLE Treatment Reduced Colon Levels of Oxidative Stress in EAE Mice To measure intestinal stress injuries, superoxide anion (O2·−) accumulation was measured in situ using the DHE stain (Figure 5A). We observed elevated red fluorescence in colon sections from EAE mice compared to control mice ($p \leq 0.001$), which indicated excess superoxide levels. In contrast, OLE treatment prevented these increases ($p \leq 0.001$). Other parameters which indirectly reflect the oxidative extent of cells/tissues, the levels of MDA (as a lipid peroxidation marker) and AOPP (as an oxidative modified proteins marker) were also found significantly augmented in colon from EAE mice ($p \leq 0.001$; Figure 5B,D), whereas FRAP levels (as an indicator of non-enzymatic antioxidant status) were significantly decreased when compared with the healthy control group ($p \leq 0.001$; Figure 5C). In contrast, in the OLE-treated EAE mice, both the MDA and AOPP levels were remarkably lowered ($p \leq 0.001$ and $p \leq 0.05$, respectively), and the FRAP levels were found notably elevated ($p \leq 0.01$), reaching levels close to those in the normal group. ## 2.4. Effect of OLE on Microbioma in EAE Mice Fecal DNA was isolated from mice of the different experimental groups to check whether OLE treatment could modulate gut microbioma in EAE mice. 16S rDNA sequencing analysis revealed diverse microbial populations in the experimental groups, but no significant differences were detected among them in the assessed α-diversity metrics: Chao1, Shannon and Simpson indexes (Figure 6A). In Figure 6B are shown the microbioma profiles according to taxonomic classification at different levels. No major differences could be seen in the composition of gut microbiota at the phylum, order, and family levels among mice of the different experimental groups. At the phylum level, Bacteroidetes and Firmicutes were major phyla in the gut bacteria of all groups with the combination of the two phyla making up approximately $90\%$ of the total community. Proteobacteria and Verrucomiceobia showed low abundance. Though not statistically significant, the Firmicutes abundance dropped approximately 1.4 fold, from $48\%$ in untreated-control mice to $34\%$ in OLE-treated mice. Thus, the ratio Firmicutes to Bacteroidetes in the OLE-treated groups tended to decrease compared to the control group, as shown in Figure 6C, but no significant difference was found ($p \leq 0.05$). Some differences were observed at family level among the experimental groups, but only those of Akkermansiaceae, which belong to phylum Verrucomicrobia, achieved significant relevance. Compared to the untreated groups, the relative abundance of Akkermansiaceae was significantly higher in the OLE-treated groups (Figure 6D). The Bacteroidaceae, a family in the phylum Bacteroidota, was also increased in the OLE-treated mice, though not significantly, when compared to untreated ones (as it can be appreciated in the family graph of Figure 6B). ## 2.5. In Vitro Effects of OLE on Human Intestinal Epithelial Caco-2 Cell Monolayers Finally, to study whether the protective intestinal effects observed in OLE-treated EAE mice also involved direct actions on cells that are essential for maintaining a functional intestinal barrier, mono-cultures of Caco-2 cells were exposed to OLE. We treated Caco-2 cell monolayers with the oxidants hydrogen peroxide (H2O2) and tert-butyl hydroperoxide (t-BOOH), as well as with some relevant inflammatory cytokines such as TNFα and IL-1β, which were found to be enhanced in the EAE mice model. Firstly, we demonstrated that the presence of OLE had no significant influence on the viability of Caco-2 cells (Figure 7A). Then, we evaluated the ability of OLE to protect Caco-2 cell monolayers from oxidative stress. H2O2 and t-BOOH stimulation induced a significant ROS accumulation in Caco-2 cells compared to untreated ones, and OLE pretreatment abolished this response (Figure 7B). We also investigated the ability of OLE to regulate the secretion of proinflammatory cytokines, such as IL-8, a crucial inflammatory mediator of intestinal injury that exerts deleterious effects on the intestinal mucosa [24]. As shown in Figure 7C, the exposure of cells to IL-1β led to an increasing secretion of IL-8, whereas the presence of OLE inhibited this up-regulated response in a dose-dependent manner. Moreover, we studied the effect of OLE on Caco-2 cells, and epithelial barrier function was assessed by measurements of TEER and FD-40 permeability (Figure 7D). The presence of OLE at 5 and 10 µM did not affect Caco-2 epithelial barrier function. However, TNFα stimulation induced a significant decrease in TEER and a significant increase in FD-40 permeability on Caco-2 cells. As expected, cell pre-treatment with OLE attenuated the epithelial barrier dysfunction induced by TNFα. ## 3. Discussion Growing evidence supports the role of the gut-brain axis in MS pathogenesis [5,6,7]. Therefore, it is interesting to explore new therapeutic strategies that can restore/prevent intestinal alterations in MS and its preclinical model, EAE. Intestinal barrier integrity is essential for the maintenance of intestinal health and homeostasis of internal environment [25]. We had previously observed that EAE causes inflammation and oxidative stress in the intestine of mice, resulting in tissue injury and increased intestinal permeability [11]. OLE, a natural antioxidant and anti-inflammatory active substance, has been shown to be effective in the prevention and treatment of EAE, and we have now demonstrated the capability of OLE to prevent barrier defects and inflammation, as well as oxidative stress, in intestinal tissue of EAE mice. In line with the in vivo data, OLE suppressed IL-1β-induced inflammatory IL-8 production, as well as TNFα-induced barrier dysfunction in human intestinal Caco-2 cell monolayers. Therefore, our findings shed new light on the beneficial role of OLE on intestinal homeostasis, specifically in pathologies, such as EAE/MS, but also with potential use in other diseases associated with intestinal barrier dysfunction [26]. Some gastrointestinal diseases, where the intestinal barrier is impaired, have also been associated with CNS demyelination [27]. Although a causal link between intestinal barrier breakdown and CNS demyelination cannot be concluded with certainty in these cases, there appears to be an association not solely explained by their shared epidemiological and immunological characteristics. The association between these entities is certainly complex and requires further study. OLE is a secoiridoid derivative present in EVOO. Recently, several studies have also highlighted the positive EVOO actions on gut health. Although specific beneficial effects of some of its phenolic compounds, such as hydroxytyrosol, tyrosol, and oleuropein, have already been examined at the intestinal level, OLE effectiveness on protecting intestinal barrier has not yet been investigated [27,28,29,30,31]. Currently, it has been described that the small intestine plays an important role in OLE absorption, and herein, our study demonstrates the beneficial effect of OLE mitigating gut damage in EAE mice, but it does not address the presence of OLE in intestinal tissue [32,33]. Further research to investigate this point is needed, in order to clarify whether the biological effects attributed to it are due to OLE itself or its biotransformed metabolites. Although OLE is an ingredient of olive oil from which it has been isolated in the past, a recent new method permitted its isolation from olive leaves [14]. In the current application of the new isolation method, we used olive leaves with elevated oleuropein content, which was used as precursor molecule for the production of oleacein during the extraction procedure. For this purpose, and after the screening of olive leaves from several different varieties, we identified a population of wild olive trees that showed high oleuropein content, which were used as the starting material for the production of OLE with yield > $1\%$ w/w of dried leaves. The currently applied method permitted the isolation of OLE through a selective extraction procedure without the need for expensive and laborious chromatographic methods. In many chronic inflammatory diseases afflicting humankind, both gastrointestinal and non-gastrointestinal increase in intestinal permeability is pointed out as a key element, by allowing the entrance of pathogenic components into the lamina propria and later on into systemic circulation. In MS patients, and likewise in its preclinical models, an increased gut permeability has been widely reported [5,6,10,34]. In MOG35-55-induced EAE in C57BL/6 mice, the disease is characterized by intestinal barrier disruptions and the presence of flawed goblet cells [10,11]. In this study, we found that OLE effectively exerted an inhibitory effect on these alterations, showing a reduced FITC-dextran translocation using the ex vivo non-everted gut sac model. Accordingly, Caco-2 cells, stimulated with TNFα to induce cell monolayer permeability, confirmed the protective effect of OLE. TNFα is an inflammatory cytokine found notably elevated in colon from EAE mice, which, in intestinal Caco-2 cells, decreases the transepithelial electrical resistance (TEER) while increasing FITC-dextran permeation [35]. Therefore, we confirm that OLE pretreatment was effective in maintaining the Caco-2 cell monolayer integrity, proving its ability to maintain the integrity of the intestinal barrier. In addition to the permeability analysis, variations in leaky gut-related markers were also evaluated in serum samples. In EAE mice, a previous study by our group reported that the serum levels of surrogate biomarkers of these events, sCD14 and iFABP, augmented significantly compared to control mice. I-FABP is an intracellular protein specifically expressed in enterocytes and it is released into the circulation when intestinal mucosal damage occurs; and sCD14 is a soluble LPS co-receptor released from monocytes in response to bacterial translocation into plasma, also a sign of an active inflammatory response [36,37,38,39]. In the present study, we observed that EAE-increased levels of these markers were significantly attenuated by OLE treatment. Additionally, we found that OLE treatment also diminished EAE-induced goblet cell damage in colon. Goblet cells are mucin-secreting epithelial cells that play vital roles in sustaining the intestinal mucosal barrier [40]. Clinical observations and data from experimental animal models have reported the presence of defective goblet cells and a reduced production of mucosal barrier-related molecules, as critical factors in the triggering of the disorders affecting the gastrointestinal tract [41,42,43].. It is interesting to note that OLE administration to EAE mice not only preserved goblet cells mucins in intestinal tissues, but it was also able to prevent the reduction in galectin-3 levels observed in the colon of untreated mice. Since cell surface-associated mucins form strong complexes with galectin-3, preserving the integrity of the mucosal barrier, these results show how OLE might be contributing to the restoration of the epithelial barrier in EAE [44]. We also found that the expression levels of the neurotrophic factor GDNF were down-regulated in the colon of EAE mice, but when daily treated with OLE, levels were restored. A similar expression pattern was observed in serum samples. Although GDNF is mainly secreted by enteric glial cells, another crucial component of the intestinal mucosal defense system also enterocytes synthesize significant amounts of this neurotrophic factor [45]. GDNF has protective roles on barrier functions by modulating its maturation, as well as the proliferation and apoptosis of the intestinal epithelial cell [23,46]. Reduced levels of GDNF lead to morphological and functional abnormalities of the intestinal barrier function, both in patients with intestinal diseases and in preclinical models [47,48]. Our findings in the EAE model are consistent with these considerations. Interestingly, some phytochemicals, such as polyphenols, have shown neurotrophic factor-like activity by binding to neurotrophic factor receptors; future research should unravel whether OLE also possesses neurotrophic functions through a direct agonistic effect on these receptors [49,50]. A compromised intestinal barrier function has unequivocally been associated with inflammatory conditions in the gut [51,52]. In accordance, high levels of the inflammatory TNFα and IL-1β were observed in the colon of EAE mice, compared to control. An increased presence of pro-inflammatory cytokines has been observed in patients and preclinical models of intestinal diseases, and treatments suppressing the inflammatory response alleviated the intestinal dysfunction [53,54,55,56,57,58]. Consistent with these data, the current study demonstrated that OLE treatment decreased the pro-inflammatory cytokine levels in the colon of EAE mice. In addition, the immunoregulatory cytokines, IL-33 and IL-25, were preserved in the colon of OLE-treated EAE mice. A protective function has already been described for these cytokines on mucosal tissue. In line with our observations, decreased IL-25 levels have been found in the intestine of both IBD patients and preclinical models, and IL-25 treatment inhibits experimental intestinal damage in mice [59,60]. Regarding IL-33, this cytokine is associated to goblet cells proliferation and mucin expression, hence, it promotes epithelial integrity and restoration of intestinal homeostasis [61,62]. Moreover, IL-33 and IL-25 possess the ability to influence innate and adaptive immunity, promoting protective Th2 cytokine-mediated responses [59]. In EAE, deviation of the immune system towards a Th2 response correlates with disease resistance. Accordingly, treatment with either IL-25 or IL-33 protects mice from EAE diseases, whereas its deficiency or blockade results in an accelerated/exacerbated EAE phenotype [63,64,65,66,67]. Thus, taking together these reports, preserving the expression of these cytokines may be valuable for OLE-induced protection to EAE mice. Although precise molecular mechanisms involved in these protective actions of OLE have not been addressed in this study, regulation of CD14/TLR4/CD14/MyD88 axis, JAK/STAT, MAPKs and inflammasome, as well as post-translational modification in histone H3 are signaling mediators modulated by OLE that deserve further investigation in the EAE context [18,68]. Since oxidative stress and inflammation is a feedback, another essential factor in the pathogenesis of gastrointestinal mucosal diseases is ROS over-accumulation [69,70]. The amelioration of the oxidative response exerted by OLE in gut tissues was also evidenced, when oxidative stress markers were evaluated. In MS patients a reduced antioxidant capacity has been observed [71]. Accordingly, in EAE mice tissues, including gut, oxygen radicals are overproduced, shifting the endogenous oxidant/antioxidant balance, which is consistent with our present findings [11]. Some of the beneficial effects of OLE might be ascribed to its strong antioxidant capacities [72,73,74] and, herein, it has been demonstrated that OLE significantly reduced ROS accumulation in the colon of EAE mice, as well as the levels of MDA and AOPP indicating that OLE lowered the degree of lipid and protein oxidation to suppress intestinal oxidative stress. In consonance, FRAP values, which reflect the overall redox status, were increased in colon of EAE mice treated with OLE, highlighting its protective antioxidant effect. A direct protective effect of OLE against oxidative stress was also observed in Caco-2 cells, after these cells were incubated with OLE, which significantly attenuated ROS accumulation following exposure to the stressors, hydrogen peroxide or tert-butyl hydroperoxide. Therefore, the antioxidant activity of OLE contributes to the above-mentioned gut-integrity strengthening effect. Another disturbance we observed in the gut of EAE mice was an increase in the cecal index and OLE treatment prevented this enhancement. Usually, full cecum increases are associated to increased fermentation, consequently, to changes in microbial metabolism. Further investigations are required to elucidate whether these observed changes are due to alterations in the cecal microbe composition or in the bacterial enzymatic expression and activity [75]. Likewise, regarding the protective effect of OLE, its direct impact on cecal microbioma should be considered, as well as its actions on proteins involved in microbial activities [76] Studies on MS patients and the EAE mouse model suggest that the gut microbiome plays a significant role in both disease progression and severity [77,78,79]. In our experimental condition to examine the effects of OLE administration on mice gut microbiota, specific changes in the abundance of Akkermansiaceae, a family of mucin-degrading bacteria, were detected in fecal samples from mice treated with OLE, EAE-induced or not. Interestingly, the bacteria *Akkermansia muciniphila* (the better studied member of the Akkermansiaceae family with epithelium remodeling properties) positively correlates with mucus layer thickness and intestinal barrier integrity, and promotes the development of host innate and adaptive immune systems with anti-inflammatory effects [80]. Decreased contents of these bacteria in the intestine are associated with the development of several intestinal diseases, whereas increasing its proportion in gut microbiota through dietary modification or pharmacological intervention has beneficial effects in host health. In our study, it might suggest that OLE increasing the Akkermansiaceae family abundance favors a protective gut environment. In line, recent studies have suggested that dietary polyphenols play a role in the modulation of the gut microbiota that may favor positive outcomes [81]. Thus, polyphenols from black tea, red wine grape extract/grape pomace extract or cranberry extract stimulate the growth of beneficial bacteria in the gut microbiota such as Akkermansia, belonging to the *Verrumicrobiota phylum* [81]. Although the exact mechanisms of action have not yet been fully established, differences in susceptibility between bacterial groups may depend on resistance to any of the mechanisms by which polyphenols interact with bacteria [82], e.g., through short-chain fatty acids production, which stimulates the goblet cells to produce more mucus to preserve intestinal barrier integrity. Focusing on the olive bioactive constituents, a recent study has shown that the diminished abundance observed in bacteria belonging to the phyla Bacteriodetes and Verrumicrobiota in mice fed with a high fat diet, were also restored by treatment with an olive leaf extract [83]. Moreover, the authors point that this microbiota restauration is associated with the improvement of the gut barrier function, as well as with the beneficial effect induced by the extract on the metabolic and vascular alterations associated to obesity. In this study, we found that the OLE-mediated increase in the relative abundance of the Akkermansiaceae family paralelled the prevention of the intestinal barrier damage induced in EAE mice. However, a causal relationship should be stated by the oral administration of these bacteria (i.e., as a probiotic), or a family member such as Akkermansia muciniphila, in future studies. Additionally, in our study we noted a trend toward an increase in Bacteroidaceae family in mice of OLE-treated groups, but those changes were not significant. Interestingly, other investigations, in EAE mice and MS patients, reported that a dietary intervention that confers protection in the EAE model and improves the disability status scale of the disease on MS patients, also significantly increased the Bacteroidaceae family richness [77,78]. Therefore, our findings from the OLE-treated mice are worthy of attention, it being possible that using a higher dose of OLE or a different administration route, the changes in Bacteroidaceae family richness could achieve a significant impact. We should also consider that in our experimental design, mice were sacrificed at a time where perturbations to the gut microbial populations have not reached a maximum. Additional work should be performed to test these possibilities. ## 4.1. Disease Induction and Treatment Female 8 to 10-week-old C57BL/J6 mice (from Charles River Laboratories, Barcelona, Spain) were housed in the animal care facility at the Medical School of the University of Valladolid and provided with food and water ad libitum. All animal care and experimental protocols were reviewed and approved by the Animal Ethics Committee of the University of Valladolid [3008787] and complied with the European Communities directive $\frac{86}{609}$/ECC and Spanish legislation (BOE $\frac{252}{34367}$-91, 2005) regulating animal research. EAE was induced according to our previous study [21]. EAE-immunized mice received an intraperitoneal injection with vehicle control (DMSO/saline, $$n = 9$$) or 10 mg/kg/day of OLE ($$n = 9$$) starting from immunization day until the end of the experiment, when untreated EAE mice showed hind limb paralysis (about day 24 post-immunization). Control mice (without EAE induction) were also injected daily with OLE ($$n = 9$$) or vehicle control ($$n = 9$$) for an equivalent timeframe. OLE was dissolved in normal saline containing $5\%$ DMSO. Animals were monitored blindly and daily by two independent observers and neurological signs were assessed on a scale of 0 to 5, with 0.5 points for intermediate clinical findings as previously described: grade 0, no abnormality; grade 0.5, partial loss/reduced tail tone, assessed by inability to curl the distal end of the tail; grade 1, tail atony; grade 1.5, slightly/moderately clumsy gait, impaired righting ability or combination; grade 2, hind limb weakness; grade 2.5, partial hind limb paralysis; grade 3, complete hind limb paralysis; grade 3.5, complete hind limb paralysis and fore limb weakness; grade 4, tetraplegic; grade 5, moribund state or death, [11,22]. Blood and intestinal sections were collected. Tissues were frozen at −80 °C for protein studies or fixed in $4\%$ paraformaldehyde in PBS, followed by paraffin embedding or OCT embedding then frozen. ## 4.2. Oleacein Isolation Fresh olive leaves (2 kg) were collected from wild trees growing in Volvi Estate, the largest compact population of wild olive trees in Northern Greece. The leaves were manually separated by the stems and air-dried at room temperature for 10 days until the moisture content was less than <$10\%$ (w/w). Then the intact leaves were mixed with water (10 L) at 25 °C and cut into small pieces in the presence of water using a blender. The mixture remained at 25 °C for 30 min and then it was filtered. The aqueous phase was collected and extracted with dichloromethane (5 L). The organic phase was collected and evaporated using a rotary evaporator under reduced pressure affording a viscous liquid containing oleacein (14 g, purity $95\%$ (w/w)) with NMR data in accordance with those previously described [14]. In Figure 1A the oleacein structure is shown. ## 4.3. Ex Vivo Intestinal Permeability Assay Ex vivo detection of intestinal permeability was performed using “intestinal sacs” and following the protocol of Zhong et al. with some modifications [84]. Colon tissue samples were extracted into Krebs-Henseleit bicarbonate buffer (KHBB) containing 8.4 mM HEPES, 119 mM NaCl, 4.7 mM KCl, 1.2 mM MgSO4, 1.2 mM KH2PO4, 25 mM NaHCO3, 2.5 mM CaCl2, and 11 mM glucose (pH 7.4). Then, one end was sutured and from the other end 100 μL of fluorescein-labeled dextran-40 (FD-40, MW 40 kDa, 10 mg/mL) was injected using a gavage needle, and tied to form a 5 cm sac. After a quick dip in KHBB to remove the presence of fluorophore on the outside, the intestinal sac was incubated in 2 mL of new buffer, at 37 °C for 20 min. Finally, the fluorescence of the FD-40 transferred from the intestinal lumen to the incubation solution (Ex./Em. $\frac{485}{530}$ nm) was measured in a fluorimeter. Intestinal permeability was expressed in micrograms of extravasated FD-40/cm/min. ## 4.4. Histological Studies For histological analysis, mouse colons were fixed in $4\%$ paraformaldehyde, processed and embedded in paraffin. 5-μm-thick tissue sections were stained with Periodic acid-Schiff (PAS) and Alcian blue (AB) (Sigma-Aldrich) to stain general intestinal carbohydrate moieties. Acidic mucins stain blue with AB (pH 2.5), neutral mucins stain pink with PAS, and mixtures of neutral and acidic mucins appear purple. The sections from all experimental groups were stained in one single batch to ensure that differences in the staining pattern were not due to technical manipulations, thereby allowing the comparability of the different samples. The evaluation was performed, in a blinded fashion, in each specimen to control the changes that occurred along the treatment. Histopathological examination was performed with a Nikon Eclipse 90i (Nikon Instruments Inc., Amstelveen, The Netherlands). For quantitative analysis, images were acquired from at least three random fields of view per slice and processed using the ImageJ image analysis program (NIH, Bethesda, MD, USA). The area AB/PAS positive was identified as the ratio to the total tissue area ## 4.5. Analysis of Superoxide Anion Production in Colon from EAE Mice Colon segments were collected and frozen immediately in Tissue-Tek O.C.T. To evaluate the intracellular superoxide anion (O2·−) the oxidative fluorescent dye dihydroethidium (DHE, Invitrogen Life Technologies, Burlington, Canada), was used as previously described [11]. Briefly, frozen samples cut into 12-μm thickness sections using a cryostat were equilibrated in Krebs-HEPES buffer (NaCl 130 mM, KCl 5.6 mM, CaCl2 2 mM, MgCl2 0.24 mM, HEPES 8.3 mM, glucose 11 mM, pH 7.4) in a humidified and light-protected chamber at 37 °C. The sections were then incubated with 5 μM of DHE for 30 min at 37 °C. Fluorescence signals were viewed using a fluorescence microscope (Nikon TE2000, Japan) under a 10× objective (100× final magnification) and a 20× objective (200× final magnification). At least five images of each colon sample were captured for analysis using a fixed exposure time for all groups. The intensity of fluorescence signals was quantified using ImageJ software (NIH, Bethesda, MD, USA). A single researcher who was unaware of the experimental groups performed the analysis. ## 4.6. Inflammatory Markers on EAE Mouse Samples Using an Enzyme-Linked Immunosorbent Assay (ELISA) Serum and colon tissue samples were collected from animals on day 24 after immunization. Colon tissues were weighed and homogenized (1:10, w/v) in ice-cold PBS supplemented with 0.4 M NaCl, $0.05\%$ Tween 20, $1\%$ EDTA and a protease inhibitor cocktail containing PMSF, leupeptin and aprotinin (Sigma-Aldrich, St Louis, MO, USA), and centrifuged at 10.000 rpm for 10 min at 4 °C. All samples were immediately stored at −80 °C. Mouse TNFα, IL-1β, pro-IL-1β, and IL-25 ELISA kits from eBioscience (San Diego, CA, USA). Mouse sCD14, IL-33 and Galectin-3 (Gal-3) DuoSet ELISA Kits were from R&D (R&D Systems, Minneapolis, MN, USA). Mouse iFABP and GDNF ELISA kit were from Cusabio (Cusabio Biotech Co., Ltd., Wuhan, China). Mice $$n = 5$$–7 per group. ## 4.7. Analysis of Ferric Reducing Antioxidant Power (FRAP) of Colon Colon homogenate samples were used to measure the total antioxidant activity using the FRAP assay following the method described by Benzie and Strain [85]. FRAP values were calculated according to the calibration curve for FeSO4·7H2O and expressed as µM of Fe2+ equivalents. ## 4.8. Determination of Malondialdehyde (MDA) Colon homogenate samples were assessed in duplicates to determine the presence of lipid peroxidation products as malondialdehyde (MDA) concentration. The lipid peroxidation level was measured spectrophotometrically by the estimation of MDA concentration based on the reaction with thiobarbituric acid [86]. Briefly, colon supernatans were added to a reaction mixture consisting of $0.373\%$ thiobarbituric acid, $15\%$ trichloroacetic acid and $0.015\%$ BHT. Then, the mixture was heated at 95 °C for 40 min, and cleared by centrifugation at 3.800 rpm for 10 min. The absorbance was measured at 532 nm using a 96-well plate. ## 4.9. Determination of Advanced Oxidation Protein Products (AOPP) Colon homogenate samples were assessed in duplicates to determine the presence of advanced oxidation protein products (AOPP) as a biomarker of oxidative stress. 20 µL colon supernatant samples were pipetted into a 96-well microplate and diluted into 100 µL in PBS. Then, 10 µL of 1.16 M KI, and 20 µL absolute acetic acid were added to each well of the microtiter plate. The absorbance of the reaction mixture was immediately read at 340 nm on the VERSAmax microplate reader against a blank containing 100 µL PBS, 20 µL acetic acid, and 10 µL KI solution. AOPP were calibrated with a chloramine-T solution (0–100 µM) that absorbs at 340 nm in the presence of 10 µL of 1.16 M potassium iodide. AOPP concentrations were expressed as µM chloramine-T equivalents. ## 4.10. Microbiota Analysis Bacterial DNA was extracted from 220 mg of the fecal content from each animal using QIAamp Fast DNA Stool Mini Kit (Qiagen, QIAGEN Iberia, S.L. Spain) according to manufacturer’s instructions with prior disruption using silica beds in a Fastprep® device (QBiogene, Carlsbad, CA, USA). The DNA concentration was determined using a Qubit® fluorimeter (Invitrogen, Waltham, MA, USA). Microbial diversity was studied by sequencing the amplified V3–V4 region of the 16S rRNA gene using previously reported primers and PCR conditions [87]. Sample multiplexing, library purification, and sequencing were carried out as described in the “16S Metagenomic Sequencing Library Preparation” guide by Illumina. Libraries were sequenced on a MiSeq platform, leading to 300-bp, paired-end reads. Demultiplexed fastq files were processed using QIIME2 ™ pipeline version 2022.8 for quality filtering of the reads, merging of the paired ends, chimera removal, and assignation of amplicon sequence variants (ASV) [88]. ## 4.11. In Vitro Studies Cell culture: Human Caco-2 cells (kindly provided by Dr. E. Arranz, IBGB-UVa/CSIC, Spain) were routinely maintained in DMEM (glutamine, high glucose), supplemented with $10\%$ FCS, 100 U/mL penicillin and 100 pg/mL streptomycin (Life Technologies, Carlsbad, CA, USA), and were incubated at 37 °C in $5\%$ CO2. Medium was changed every 2 days and cells were used between passage 19 and 35. The monoculture of Caco-2 cells formed tight junctions at day 17–21 post-confluence. Differentiated cell layers showing high transepithelial resistance (TEER) values (~400–500 Ω × cm2), were measured with Millicell electrodes (Millicell-ERS, Millipore, Billerica, MA, USA). Viability assay: Cell viability was evaluated by using the Promega kit (Madison, WI, USA), Cell Titer 96® Aqueous One Solution Cell Proliferation Assay, according to the manufacturer’s recommendations. Briefly, Caco-2 cells were seeded in 96-well plates (10 × 103 cells/well) and serum starved for 24 h. Then, cells were incubated in the presence of different doses of OLE. After 24 h of incubation, formazan product formation was assayed by recording the absorbance at 490 nm in a 96-well plate reader (OD value). Formazan is measured as an assessment of the number of metabolically active cells. Three different assays were each performed in triplicate. Cytokines analysis: Supernatants of Caco-2 cells stimulated with 25 ng/mL of IL-1β for 48 h in the presence of different doses of OLE were used to quantify IL-8 production. The specific human IL-8 ELISA Ready-Set-Go kit (eBioscience, San Diego, CA, USA) was used according to the manufacturer’s protocol. Measurement of intracellular reactive oxygen species (ROS) levels: ROS levels were measured with the probe dichlorodihydrofluorescein diacetate (DCFH-DA; Molecular Probes, Eugene, OR). Briefly, Caco-2 cells were seeded in 96-well microplates at 1 × 104/well and after serum starvation, cells were incubated overnight at 37 °C with the indicated doses of OLE. Then, cells were loaded with 10 μM of DCFH-DA for 30 min at 37 °C. After that, cells were stimulated with 500 μM of H2O2 or 400 μM of tert-butyl hydroperoxide (t-BOOH) for 1 h. The fluorescent signal was measured at Ex. 485 nm-Em. 530 nm, using a plate reader Fluoroskan Ascent FL (Thermo Electron Corporation, Waltham, MA, USA). Results were expressed as an n-fold increase over the values of the control group. Transepithelial electrical resistance (TEER) measurement: The integrity of a Caco-2 monolayer was determined by measuring the TEER value [89]. Cells were grown in 24-well plates and seeded at 1 × 105 cells/insert onto polycarbonate membrane Transwell inserts with 0.4 μm pore size, and 0.33 cm2 growth surface (Corning, Inc.; Lowell, MA, USA). Cells were cultured for 21 days to reach differentiation. After that, Caco-2 cell monolayers were pretreated with the indicated doses of OLE for 30 min (apical) and then stimulated with 100 ng/mL of TNFα for 24 h at 37 °C. TEER values were measured with Millicell electrodes (Millicell-ERS, Millipore, Billerica, MA, USA). TEER recorded in unseeded Transwell inserts was subtracted from all values. TEER measures were normalized to untreated-control cell and expressed as a percentage of control. Permeability studies: Permeability of the cell monolayer was determined by using the macromolecular tracer FITC-labeled Dextran (FD-40, Sigma Chemical Co. St. Louis, MO, USA). Confluent and differentiated Caco-2 cell monolayers were pretreated with the indicated doses of OLE for 30 min (apical) and then stimulated with 100 ng/mL of TNFα for 24 h. Then, the medium was aspirated and both chambers were washed with HBSS. After that, 200 μL of 10 mg/mL FITC-dextran dissolved in HBSS was added at the apical compartment of each insert. After 1 h incubation at 37 °C, 200 μL aliquots were taken from the basolateral chamber and plated into a black, flat-bottom 96-well plate. The fluorescence intensity was measured in a Fluoroskan Ascent FL microplate reader (Thermo Electron. Corporation, Waltham, MA, USA) with the setting of Ex. 485 nm and Em. 530 nm. The amount of FITC-Dextran transported into the basolateral compartment (permeability flux) was extrapolated from a standard curve and expressed as mg/mL/h. Results were expressed as apparent permeability coefficient (Papp) and defined as cm/h. “Papp” is derived from the ratio of flux rate (mg/mL/h) to that of initial concentration (in mg/mL) and surface area of the membrane. ## 4.12. Statistical Analyses Data analyses were performed using one-way ANOVA (for multiple comparisons) or two-way ANOVA (for four-groups comparisons). The Bonferroni test was utilized for post hoc analysis among multiple groups where appropriate. Results described as mean ± SD. $p \leq 0.05$ were considered statistically significant. Statistical analyses were performed using the GraphPad Prism Version 4 software (San Diego, CA, USA). ## 5. 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--- title: Sustained ACE2 Expression by Probiotic Improves Integrity of Intestinal Lymphatics and Retinopathy in Type 1 Diabetic Model authors: - Ram Prasad - Yvonne Adu-Agyeiwaah - Jason L. Floyd - Bright Asare-Bediako - Sergio Li Calzi - Dibyendu Chakraborty - Angela Harbour - Aayush Rohella - Julia V. Busik - Qiuhong Li - Maria B. Grant journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003436 doi: 10.3390/jcm12051771 license: CC BY 4.0 --- # Sustained ACE2 Expression by Probiotic Improves Integrity of Intestinal Lymphatics and Retinopathy in Type 1 Diabetic Model ## Abstract Intestinal lymphatic, known as lacteal, plays a critical role in maintaining intestinal homeostasis by regulating several key functions, including the absorption of dietary lipids, immune cell trafficking, and interstitial fluid balance in the gut. The absorption of dietary lipids relies on lacteal integrity, mediated by button-like and zipper-like junctions. Although the intestinal lymphatic system is well studied in many diseases, including obesity, the contribution of lacteals to the gut–retinal axis in type 1 diabetes (T1D) has not been examined. Previously, we showed that diabetes induces a reduction in intestinal angiotensin-converting enzyme 2 (ACE2), leading to gut barrier disruption. However, when ACE2 levels are maintained, a preservation of gut barrier integrity occurs, resulting in less systemic inflammation and a reduction in endothelial cell permeability, ultimately retarding the development of diabetic complications, such as diabetic retinopathy. Here, we examined the impact of T1D on intestinal lymphatics and circulating lipids and tested the impact of intervention with ACE-2-expressing probiotics on key aspects of gut and retinal function. Akita mice with 6 months of diabetes were orally gavaged LP-ACE2 (3x/week for 3 months), an engineered probiotic (Lactobacillus paracasei; LP) expressing human ACE2. After three months, immunohistochemistry (IHC) was used to evaluate intestinal lymphatics, gut epithelial, and endothelial barrier integrity. Retinal function was assessed using visual acuity, electroretinograms, and enumeration of acellular capillaries. LP-ACE2 significantly restored intestinal lacteal integrity as assessed by the increased expression of lymphatic vessel hyaluronan receptor 1 (LYVE-1) expression in LP-ACE2-treated Akita mice. This was accompanied by improved gut epithelial (Zonula occludens-1 (ZO-1), p120-catenin) and endothelial (plasmalemma vesicular protein -1 (PLVAP1)) barrier integrity. In Akita mice, the LP-ACE2 treatment reduced plasma levels of LDL cholesterol and increased the expression of ATP-binding cassette subfamily G member 1 (ABCG1) in retinal pigment epithelial cells (RPE), the population of cells responsible for lipid transport from the systemic circulation into the retina. LP-ACE2 also corrected blood–retinal barrier (BRB) dysfunction in the neural retina, as observed by increased ZO-1 and decreased VCAM-1 expression compared to untreated mice. LP-ACE2-treated Akita mice exhibit significantly decreased numbers of acellular capillaries in the retina. Our study supports the beneficial role of LP-ACE2 in the restoration of intestinal lacteal integrity, which plays a key role in gut barrier integrity and systemic lipid metabolism and decreased diabetic retinopathy severity. ## 1. Introduction The incidence of T1D is continuously increasing globally and in the United States [1], as are the ocular complications associated with T1D, including diabetic retinopathy (DR), macular edema, cataracts, and glaucoma. In the first two decades of T1D occurrence, over $90\%$ of individuals develop DR. A critical cell in the pathogenesis of DR is the retinal pigment epithelium (RPE). RPE cells are multifunctional cells that regulate key physiological functions, including nutrient transport, light absorption, and cytokine/chemokine secretion. Impaired RPE function can lead to visual abnormalities and contribute to the pathogenesis of DR. Under the diabetic state, RPE cells are exposed not only to hyperglycemia but also to abnormal levels of circulating lipids resulting in dyslipidemia. The role of dyslipidemia and retinal lipid metabolism in diabetes remains an area of active investigation [2]. The renin–angiotensin system (RAS) is widely studied in mammals [3,4,5]. In addition to systemic RAS, there is a local RAS in tissues. Studies on T1D have shown dysregulated RAS and a decreased abundance of ACE2 [6,7,8,9,10,11,12]. ACE2, a homolog of ACE, is a monocarboxypeptidase that converts angiotensin II (Ang II) into angiotensin 1–7 (Ang 1–7) [13,14,15,16]. Previously, we have shown reduced levels of tissue-specific ACE2, such as in the retina, intestine, heart, and bone marrow of diabetic rodents and the existence of a dysregulated RAS axis in diabetes [6,7,8,9,10,11]. In the past several years, ACE2 has garnered much attention as it serves as a receptor for the entry of the SARS-COV2 virus, and it has been considered to be a therapeutic target [17,18,19,20]. The small intestine has the highest expression of ACE2 of any tissue in the body. The small intestine consists of finger-like projections known as villi. Each villus is comprised of an epithelial cell layer, enterocytes, goblet cells, enteroendocrine cells, and the lamina propria. The lacteals or intestinal lymphatics are in the central part of lamina propria and contribute to the intestine’s immune response and to the absorption of dietary lipids [21,22,23,24,25,26,27,28]. Previously, we have shown a central role of ACE2 in the intestinal pathophysiology of T1D using rodent models and human studies [11,12]. We showed that T1D individuals with DR exhibit a loss of intestinal barrier function that is identified with multiple biomarkers of gut barrier disruption, such as peptidoglycan (PGN), lipopolysaccharide-binding protein (LBP), and fatty-acid-binding protein 2 (FABP2); this increase in gut permeability was associated with gut-derived immune cell activation and, importantly, with worsening DR severity. Hyperglycemia and hyperlipidemia promote an impaired gut barrier (epithelial/endothelial) as evidenced by decreased expression of ZO-1, p-120 catenin, and VE-cadherin and fosters the increase in gut microbial peptides into the systemic circulation [11,12]. Circulating gut microbial peptides, such as PGN, reach the retina, and cause retinal vascular permeability by targeting TLR2-mediated MyD88/ARNO/ARF6 signaling and contribute to the development of a DR in T1D mice. *The* genetic depletion of ACE2 intensified this damage. Though the local effect of enteral ACE2 was assessed by analyzing intestinal pathophysiology, the impact of enteral ACE2 on systemic ACE2 remains unexplored [11,12]. In the present study, we explored the role of the probiotic expressing soluble ACE2 on dyslipidemia and lacteal integrity in a T1D model while evaluating the impact on DR endpoints. ## 2.1. Chemicals and Antibodies Primary antibody specific for lacteal marker lymphatic vessel endothelial hyaluronan receptor-1 (LYVE1; #67538), p120-catenin (#59854), and Vascular cell adhesion molecule 1 (VCAM1; #39036) from cell signaling (Danvers, MA, USA), Zonula occludens-1 (ZO1; #sc-33725) from Santa Cruz Biotechnology (Dallas, TX, USA), Plasmalemma vesicle-associated protein 1 (PLVAP1; #NB100-77668), and ATP-binding cassette subfamily G member 1 (ABCG1; #NB400-132) from Novus (Centennial, CO) were purchased. The ELISA assay kits for LDL-cholesterol (#79980) and HDL-cholesterol (#79990) were purchased from Crystal Chem (Elk Grove Village, IL, USA). Triglyceride assay (#10010303) and Free Fatty Acid assay (#STA-618) kits were purchased from Cayman chemicals (Ann Arbor, MI, USA) and Cell Biolabs, Inc. (San Diego, CA, USA), respectively. ## 2.2. Experimental Animals and LP-ACE2 Treatment Akita mice (an animal model of T1D), originally purchased from the Jackson Laboratory (Strain#003548; Bar Harbor, ME), were housed in the animal facility at the University of Alabama (UAB) and bred using an in-house breeding scheme to generate the experimental mice. The experimental mouse colonies were maintained under standard housing conditions ($\frac{12}{12}$ h, dark and light cycle; the temperature of 24 ± 2 °C, and humidity of 50 ± $10\%$). The mice were fed a standard AIN76A diet and water ad libitum. The Institutional Animal Care and Use Committee (IACUC) approved the proposed study at UAB under animal protocol number 21196. The heterozygous Akita mouse model is a monogenic model of T1D that develops hyperglycemia, hypoinsulinemia, polydipsia, and polyuria within 3 to 4 weeks of age [11]. As the diabetic phenotype is more severe in males than in females, only age-matched male mice were used in this study. To determine the effect of enteral ACE2, a healthy gut bacterium, Lactobacillus paracasei (LP), was engineered to produce soluble humanized ACE2 (LP-ACE2) and given via gavage into the intestinal lumen, as described in Prasad et al. [ 12]. Akita mice were randomly divided into two groups: (i) mice received control probiotics (LP) and (ii) mice received LP-ACE2. Both groups were aged to 6 months. After 6 months of diabetic onset, the experimental mice were treated (200 μL, 1 × 1010 colony-forming units (CFU)/mouse; 3 times/week) with either LP or PL-ACE2. At the end of the study, the intestinal tissues, plasma, and eyes were collected and stored at −80 °C until further analysis. The wildtype littermates, obtained after the genotyping of the Akita mice, were used as age-matched controls [12]. ## 2.3. Assessment of Retinal Functions and Acellular Capillaries Quantification To determine the effect of 3 months of treatment (LP or LP-ACE2), retinal function was assessed by electroretinography (ERG) and visual acuity by optokinetic nystagmus (OKN). All of the cohorts underwent dark adaption, and then ERGs were performed using the LKC Bigshot ERG system [29,30]. Scotopic rod signaling was assessed with 10 increasing intensities of white light, and the responses were averaged and analyzed using the LKC EM software. Acellular capillaries were assessed to evaluate the effect of LP-ACE2 on DR phenotype, as reported by Asare-Bediako et al. [ 29]. ## 2.4. Circulating Lipid Profile Assay Circulating levels of LDL-cholesterol, HDL-cholesterol, Triglycerides (TGA), and free fatty acids (FFA) were measured in the plasma samples of all three cohorts, followed by the manufacturer’s protocol. ## 2.5. Immunofluorescence Staining of Intestinal Lacteal, Gut Barriers, and Retina To determine the effect of LP-ACE2 on intestinal lymphatic, gut barrier integrity, and retinal damage in Akita mice, immunofluorescence staining was performed as described previously [12] using the intestinal lacteal marker LYVE1, the gut endothelial marker PLVAP1 and epithelial makers (ZO-1 and P120 catenin) specific antibodies. Retinal damage was assessed by the immunostaining of ZO-1 and VCAM1-specific antibodies. The expression of reverse cholesterol efflux transporter, ABCG1, was stained in the retina. Briefly, paraffin sections were deparaffinized, epitope retrieved, dehydrated, and then incubated with specific primary antibodies (1:200) overnight at 4 °C. After overnight incubation, the sections were washed in PBS and incubated with secondary color-conjugated antibodies at room temperature for 2 h. Images were collected using a Nikon A1R-HD confocal microscope equipped with NIS-Elements AR Software and a Zeiss Axio epifluorescence microscope. Nuclei were stained with DAPI (blue) in all immunofluorescence images. The fluorescence intensity was quantified by measuring mean gray intensity using ImageJ software (Java 8). Representative images for immunofluorescence staining were selected from a data point closest to the mean or median intensity from its representation. ## 2.6. RNA Isolation and qRT-PCR The total RNA was extracted from retinal tissue using QIAGEN RNeasy Plus Micro Kit (#74004; Germantown, MD, USA), followed by cDNA synthesis using Bio-Rad iScript cDNA synthesis kit (#1708890). qRT-PCR for primers specific to ATP binding cassette family A protein 1 (ABCA1; # qMmuCID0021182) was carried out using an advanced universal SYBR supermix (#1725271; Bio-Rad, Hercules, CA, USA) following the manufacturer’s instructions. The reaction mixture contained 5 µL supermix, 1 µL primer, 1 µL cDNA, and 3 µL nuclease-free water. The PCR conditions were: 98 °C for 30 s, 95 °C for 15 s and 60 °C for 30 s (35 cycles), 60 °C−95 °C for 5 s (0.5 °C increment). The mRNA expression was normalized to cyclophilin A and presented as relative gene expression. ## 2.7. Statistical Analysis The data were evaluated for outliers and adherence to a normal distribution using GraphPad Prism, version 8.1 software. Statistical significance was assessed one way ANOVA and Tukey’s multiple comparison test. The data sets were considered significantly different if the p-value was <0.05. ## 3.1. LP-ACE2 Treatment Attenuates Diabetes-Induced Lacteal Defects and Gut Barrier Dysfunction in Akita Mice We investigated whether intestinal lacteals are altered in the Akita mice using immunofluorescence staining of LYVE1, a widely accepted marker of lymphatic endothelium. As shown in Figure 1A, the length of lacteals was reduced in Akita mice. The quantification of the intensity data suggests that the expression of LYVE1 was decreased significantly in Akita mice (2.07 ± 0.19 vs. 5.74 ± 1.16; $p \leq 0.005$) compared with the WT cohort. The LP-ACE2 treatment significantly restores LYVE1 expression up to $89.96\%$ (5.16 ± 0.43; $p \leq 0.001$) in Akita mice compared with the LP-treated Akita cohort (Figure 1B). To maintain the lymphatic vessel integrity, lymphatic endothelial cells are connected to each other with specialized cell–cell junctions regulated by adherens junctional molecules. The disruption of these endothelial barriers impairs vessel function. Thus, we determine the effect of the LP-ACE2 treatment on PLVAP1, a marker of endothelial barrier integrity which increases with worsening disruption. The expression of PLVAP1 was strongly over-expressed in Akita mice (4.05 ± 1.03 vs. 1.05 ± 0.3; $p \leq 0.0$) compared with the WT mice (Figure 1C,D). The expression of PLVAP1 was significantly reduced (1.54 ± 0.3, $p \leq 0.02$) to normal levels in LP-ACE2-treated Akita mice. Enterocytes, the uppermost epithelial cell layer of the villus, maintain cell–cell contact to form an interface between the intestinal lumen and internal milieu. Studies reported that $50\%$ of the body’s cholesterol is absorbed by the intestine and passes through the barriers by diffusion from the intestine to enterocytes [26]. Impaired epithelial barriers increase paracellular transport and affect the absorption of dietary lipids. Next, the effect of LP-ACE2 treatment was tested on the integrity of the intestinal epithelial barrier. The expression of ZO-1 was significantly less in Akita mice (0.60 ± 0.15 vs. 3.22 ± 0.33; $p \leq 0.001$) compared with their WT littermates (Figure 1E,F). The oral administration of LP-ACE2 for 3 months substantially increased ZO-1 levels in Akita mice. Similar changes were observed in the p120-catenin expression (Figure 1E,G). Together, these results suggest that LP-ACE2 administration corrects diabetes-induced gut lymphatic barrier disruption in T1D mice. ## 3.2. Effect of Oral Administration of LP-ACE2 on Circulating Lipid Levels To determine whether impaired lacteals and a dysfunctional endothelial and epithelial gut barrier influenced circulating lipid levels, we measured LDL cholesterol and HDL cholesterol levels in the plasma of the experimental cohorts and assessed whether LP-ACE2 administration impacted cholesterol levels. LDL cholesterol was significantly increased (72.37 ± 7.62 vs. 45.28 ± 3.72; $p \leq 0.01$) in Akita mice compared to WT, and the levels were decreased ($p \leq 0.007$) following LP-ACE2 treatment (Figure 2A). In contrast, the levels of HDL cholesterol were reduced considerably (30.91 ± 4.19 vs. 65.41 ± 5.12; $p \leq 0.0006$) in the Akita cohort compared to the WT mice, and HDL cholesterol increased (43.94 ± 4.83; $p \leq 0.01$) after LP-ACE2 treatment in Akita mice compared with the untreated Akita cohort (Figure 2B). Elevated levels of circulating triglycerides (TGs) were observed in the Akita mice, and in the LP-ACE- treated Akita, TGs were reduced (338.7 ± 22.03 vs. 190.2 ± 31.15 vs; $p \leq 0.0028$) (Figure 2C). Although the levels of free fatty acids (FFA) in the plasma of Akita mice were higher (1971 ± 298.7 vs. 882.2 ± 130; $p \leq 0.02$) compared with WT cohort (Figure 2D), after LP-ACE2 treatment in Akita mice, a nonsignificant reduction in the FFA levels was observed. Collectively these results suggest that LP-ACE2 corrects key dyslipidemia endpoints in Akita mice. ## 3.3. LP-ACE2 Restored Reverse Cholesterol Transport Protein (ABCG1/ABCA1) in the Retina of Akita Mice We next examined if LP-ACE2 administration could modulate retinal lipid homeostasis, a process largely regulated by RPE cells. RPE cells in the posterior retina are responsible for the phagocytosis of lipid-rich photoreceptors and for the uptake of circulating lipids from the choriocapillaris [31]. To protect against excess intracellular accumulation, RPE cells recycle these lipids and export them with the help of the ABCA1/ABCG1efflux pathway [31,32,33]. Thus, we determined the effect of LP-ACE2 treatment on reverse cholesterol transport proteins. The expression of ABCG1 was strongly decreased in Akita mice (783.0 ± 87.94 vs. 1113.0 ± 64.24; $p \leq 0.04$) compared with WT mice (Figure 3A,B). The expression of ABCG1 was significantly restored (1273.0 ± 124.5, $p \leq 0.007$) to normal levels in LP-ACE2-treated Akita mice. The expression of ABCA1 mRNA in the retina of diabetic and WT mice was measured. Although the mRNA expression of ABCA1 was reduced in Akita mice, it was not significant (Figure 3C). However, following LP-ACE2 treatment of the Akita cohort ABCA1 was significantly upregulated compared with untreated Akita mice. These results in the retina suggest that LP-ACE2 increased circulating ACE2 levels, a point which has been previously established [12]. Thus, the increasing systemic ACE2 levels likely lead to increased retinal ACE2, which increased ABCG1/ABCA1 expression and improved retinal lipid metabolism. ## 3.4. LP-ACE2 Inhibits Diabetes-Induced Blood-Retinal Barrier (BRB) Dysfunction and Microglial Inflammation in Akita Mice BRB participates in transporting the fatty acids required for retinal function [34,35]. To assess the possible damage of BRB, the expression of ZO-1 was measured in the retina of the experimental cohorts (Figure 4A,B). While expression of ZO-1 was decreased in diabetes, the expression was restored in the LP-ACE2 treated Akita mice (32.41 ± 9.00 vs. 49.80 ± 7.62; ns); however, the changes did not reach significance. VCAM-1 is a glycoprotein expressed in retinal endothelial cells. The expression of VCAM-1 is increased in the diabetic retina by pro-inflammatory cytokines, high glucose, and TLR agonists [36,37]. As seen in Figure 4A,C, retinal endothelial cells of Akita mice demonstrated increased VCAM-1 expression (12.33 ± 1.18 vs. 7.19 ± 1.35; $p \leq 0.03$) compared to WT mice. LP-ACE2 treatment decreases VCAM-1 expression below the control level (5.89 ± 0.53; $p \leq 0.02$) in the retina of Akita mice. ## 3.5. Effect of LP-ACE2 Treatment Improves Retinal Function and Reduces the Number of Acellular Capillaries in the Akita Cohort Next, we confirmed our previous findings and showed that after 9 months of diabetes, the Akita mice demonstrated a significant reduction in scotopic a wave (127.8 ± 23.76 vs. 235.5 ± 29.89; $p \leq 0.03$) and the scotopic b wave (275.6 ± 19.05 vs. 501.2 ± 73.48; $p \leq 0.02$) compared to the age-matched WT mice (Figure 5A,B). LP-ACE2 treatment for 3 months significantly restored the scotopic a wave (252.7 ± 22.46; $p \leq 0.01$) and the scotopic b wave (534.9 ± 31.01; $p \leq 0.009$) in Akita mice compared with the Akita control cohort. LP-ACE2 treatment also significantly improved visual acuity (0.41 ± 0.007 vs. 0.33 ± 0.02; $p \leq 0.02$) in Akita mice compared with the untreated Akita group (Figure 5C), as observed by measuring the spatial frequency. We also enumerated acellular capillaries, a hallmark feature of DR. As shown in Figure 5D, a significantly higher number of acellular capillaries (12.33 ± 1.18 vs. 7.19 ± 1.35; $p \leq 0.03$) occur in the retina of Akita mice compared to WT mice. The increased number of acellular capillaries was almost 1.5-fold in Akita mice compared to their WT littermates. LP-ACE2 significantly reduced the number of acellular capillaries (5.89 ± 0.53; $p \leq 0.02$) in Akita mice. ## 4. Discussion The salient features of our study include the demonstration that T1D promotes lacteal permeability and gut barrier defects, impairing intestinal lipid metabolism. LP-ACE2 treatment of Akita mice for 3 months corrected gut barrier defects, including improving lacteal morphology to maintain intestine lipid metabolism. LP-ACE2 significantly reduced circulating levels of LDL cholesterol, triglycerides, and FFAs, and increased HDL cholesterol. LP-ACE2 treatment repaired BRB dysfunction and reduced diabetes-induced retinal inflammation, as observed by increased ZO-1 expression and reduced VCAM-1 expression and the reduced generation of acellular capillaries. Improved visual function, as observed by measuring scotopic a and b waves and visual acuity, further demonstrated the beneficial effect of LP-ACE2. Our data support the fact that LP-ACE2, by increasing systemic ACE2 levels, improved retinal lipid metabolism and LP-ACE2 was able to restore the cholesterol efflux pathway in RPE cells by increasing the expression of ABCA1 mRNA and protein. The small intestine is a complex organ that contributes to dietary lipid metabolism. The lacteals absorb dietary fat and regulate the intestinal immune systems. However, little is known about the function of lacteals in healthy contexts or in diabetes. Previously, we have shown that hyperglycemia promotes gut barrier permeability resulting in the release of microbial peptides into the systemic circulation and contributing to endothelial dysfunction, including in the retina [11,12]. We showed in T1D diabetic individuals that gut permeability correlates with disease severity, as the highest levels of PGN, FABP-2 and LBP were seen in the most advanced retinopathy. In our murine studies, diabetes-induced retinal endpoints were further worsened in the ACE2-/y diabetic mice and maintenance of enteral ACE2 either by engineered probiotics similar to what was used in this study or by genetic overexpression of ACE2 in the gut epithelium of murine models, protected the gut barrier from the adverse consequences of diabetes [12]. We also observed that the use of LP-ACE2 improved glucose homeostasis, as measured by reduced random blood glucose and glycated A1C [12]. In contrast, although we noticed that the genetic approach of selectively expressing ACE2 in the gut epithelium of Akita mice corrected gut barrier defects and improved retinal function in Akita mice, it failed to restore normal glucose homeostasis. Thus, the ocular benefit we observed was due to ACE2 and not solely to improving glucose levels that will also prevent the progression of DR. This study brings into consideration the significance of ACE2 on lacteals function, in not only the restoration of a key aspect of the gut barrier but also by improving lipid homeostasis in the systemic circulation and in the retina. Accumulating evidence clearly demonstrated that impaired lacteals, an essential part of the small intestine, promote diet-induced obesity and contribute to hyperlipidemia. Ablation of intestinal lacteals causes disruption of blood vessels and villi architecture, which leads to the invasion of intestinal pathogens into the circulatory system and can trigger systemic inflammation. The importance of gut lymphatics in lipid metabolism is now emerging. Numerous studies have advanced our knowledge that regulating lipid uptake by gut lymphatics and correcting lacteal defects could reverse diet-induced obesity in rodent models [38,39]. However, the role of ACE2 in protecting gut lymphatics has not been explored until the present study. The LP-ACE2 administration is known to increase circulating levels of ACE2 [30,40]; thus, we postulate that increased ACE2 in the circulation will provide more ACE2 delivery to the retina via the choriocapillaris which serves to improve the diabetes-induced reduction in the expression of lipid transporters in the RPE. The mechanisms responsible for our observations are incompletely understood [41]. Photoreceptors in the retina demand high energy levels for their function and rely on retinal lipids for substrates for the photoreceptor’s mitochondria [42]. Though lipids are crucial for retinal function, an abnormal abundance of lipids within the retina or its surrounding environment can result in retinal dysfunction, RPE cell death, and retinal degeneration [43]. Reduced endothelial nitric oxide (NO) bioavailability and increased inducible NO drive inflammatory pathways; thus, the abnormally high retinal lipid levels promote endothelial dysfunction and likely contribute to the pathogenesis of diabetic vascular complications. Hyperlipidemia also contributes to the pathogenesis of DR and age-related macular degeneration by endothelial dysfunction and breakdown of the BRB [44]. Individuals with higher LDL are more likely to develop retinal hard exudates than individuals with normal lipid profiles [45,46,47]. Clinical and epidemiological studies demonstrated a positive correlation between circulating levels of LDL and DR pathology [2,45,48]. Therapies lowering dietary lipids also reduce retinal hard exudates [2]. Cao et al. demonstrated a positive correlation between skeletal muscle lipid metabolism and ACE2 [49]. ACE2 deficient mice showed increased lipid accumulation in skeletal muscle, while restored endogenous ACE2 in db/db mice (an animal model of type 2 diabetes) improved lipid metabolism through the IKKβ/NF-κB/IRS-1 signaling [49]. Though the beneficial effect of ACE2 has been reported in lipid metabolism in adipose tissue, liver, and skeletal muscle, no direct evidence of ACE2 in retinal lipid metabolism has been previously reported. We reported here that systemic ACE2 improves retinal lipid metabolism. LP-ACE2, by increasing the expression of ABCG1/ABCA1, activates the cholesterol efflux pathway in RPE cells. Improved visual function and visual acuity, and reductions in acellular capillaries further demonstrated the beneficial effect of LP-ACE2. Our study has certain limitations. The current study was limited to male mice. Our study looked at mRNA expressions for the lipid transporter; however, we did not directly measure lipid synthesis and turnover. These would represent the focus of future studies. We have previously measured systemic and ocular ACE2 levels but did not in the current study to confirm the proposed increase in both systemic and retinal ACE2 levels. ## 5. Conclusions In summary, our studies examined intestinal lymphatics in a model of T1D and the role of ACE2 in systemic and retinal lipid homeostasis in this model. Our results demonstrate that oral administration of engineered probiotics expressing ACE2 (LP-ACE2) beneficially influences intestinal lymphatics and systemic lipid homeostasis, improving retinal function in T1D. 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--- title: Platelet Reactivity and Cardiovascular Mortality Risk in the LURIC Study authors: - Martin Berger - Alexander Dressel - Marcus E. Kleber - Winfried März - Peter Hellstern - Nikolaus Marx - Katharina Schütt journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003439 doi: 10.3390/jcm12051913 license: CC BY 4.0 --- # Platelet Reactivity and Cardiovascular Mortality Risk in the LURIC Study ## Abstract Background: The clinical and prognostic implications of platelet reactivity (PR) testing in a P2Y12-inhibitor naïve population are poorly understood. Objectives: This explorative study aims to assess the role of PR and explore factors that may modify elevated mortality risk in patients with altered PR. Methods: Platelet ADP-induced CD62P and CD63 expression were measured by flow-cytometry in 1520 patients who were referred for coronary angiography in the Ludwigshafen Risk and Cardiovascular Health Study (LURIC). Results: High- and Low-platelet reactivity to ADP were strong predictors of cardiovascular and all-cause mortality and risk equivalent to the presence of coronary artery disease. ( High platelet reactivity 1.4 [$95\%$ CI 1.1–1.9]; Low platelet reactivity: 1.4 [$95\%$ CI 1.0–2.0]). Relative weight analysis indicated glucose control (HbA1c), renal function ([eGFR]), inflammation (high-sensitive C-reactive protein [hsCRP]) and antiplatelet therapy by Aspirin as consistent mortality risk modifiers in patients with Low- and High-platelet reactivity. Pre-specified stratification of patients by risk modifiers HbA1c (<$7.0\%$), eGFR (>60 mL/min/1.73 m2) and CRP (<3 mg/L) was associated with a lower mortality risk, however irrespective of platelet reactivity. Aspirin treatment was associated with reduced mortality in patients with high platelet reactivity only (p for interaction: 0.02 for CV-death [<0.01 for all-cause mortality]. Conclusions: Cardiovascular mortality risk in patients with High- and Low platelet reactivity is equivalent to the presence of coronary artery disease. Targeted glucose control, improved kidney function and lower inflammation are associated with reduced mortality risk, however independent of platelet reactivity. In contrast, only in patients with High-platelet reactivity was Aspirin treatment associated with lower mortality. ## 1. Introduction The clinical and prognostic implications of platelet reactivity testing in a P2Y12-inhibitor naïve population are unclear. While clinical and experimental findings suggest that platelet reactivity by P2Y1 and P2Y12 receptor-dependent purinergic signaling predicts atherothrombosis and cardiovascular mortality, routine platelet reactivity testing is not recommended by the current ACC/AHA guidelines and ESC guidelines [1,2,3,4,5,6]. This recommendation mainly arose from large clinical trials (i.e., TRIGGER-PCI, ARCTIC, ANTARCTIC, GRAVITAS), which demonstrated that escalation of antiplatelet therapy in patients with residual-high P2Y12 reactivity failed to demonstrate a significant clinical benefit in PCI settings [7,8,9,10,11]. Interestingly, a prespecified sub-study of the ARCTIC trial demonstrated that treatment intensification halved residual P2Y12 reactivity but did not result in a significant cardiovascular benefit [12]. This lack of a clinical benefit suggests other factors potentially confound the relationship between platelet reactivity and cardiovascular event rates. Therefore, we hypothesized that platelet reactivity might constitute a biomarker that is altered by a distinct cardiovascular risk profile. Following this hypothesis, identifying and adjusting risk modifiers may serve as a rational therapeutic strategy to address atherothrombotic and cardiovascular mortality risks. Therefore, the aim of the current explorative study was to identify and investigate the role of risk modifiers on mortality in patients with abnormal platelet reactivity and assess these for the potential of cardiovascular mortality risk reduction. ## 2. Methods An extended description of clinical characteristics and methodology is available in the Supplementary Materials. ## 2.1. Study Design, Participants and Clinical Characterization A total of 3316 patients, who were referred for coronary angiography to the Ludwigshafen Heart Center in Germany, were recruited between July 1997 and January 2000 [13]. The study was approved by the ethics committee at the Ärztekammer Rheinland-Pfalz and was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent. Inclusion criteria were: German ancestry, clinical stability except for acute coronary syndromes, and the availability of a coronary angiogram. Individuals suffering from any acute illness other than acute coronary syndromes, chronic non-cardiac diseases, or malignancy within the past five years and those unable to understand the purpose of the study were excluded. Clinically relevant coronary artery disease (CAD) was defined as the occurrence of ≥1 stenosis of ≥$50\%$ in ≥1 of 15 coronary segments. Individuals with stenoses < $20\%$ were considered not to have CAD. ## 2.2. Reagents Adenosine diphosphate (ADP) and thrombin receptor activating pepetide-6 (TRAP) were from Sekisui Virotech (Ruesselsheim, Germany) and from Bachem (Bubendorf, Switzerland), respectively. The monoclonal antibodies against CD41-PC7 and CD63-PE were purchased from Beckman Coulter (Krefeld, Germany). The antibodies against CD62P-PC5 and Fibrinogen-FITC were from BioLegend (Koblenz, Germany). ## 2.3. Platelet Reactivity Testing Platelet reactivity was tested on the day coronary angiography was performed, and blood was drawn before the procedure by atraumatic venipuncture using a modification of a procedure described previously [14]. Briefly, after discarding the first 2 mL, citrated whole blood (1 part 0.106 mmol/L sodium citrate + 9 parts blood) was obtained using Sarstedt monovettes (Nümbrecht, Germany). After resting at 37 °C for 30 min, the whole blood was diluted 1:10 with calcium-free Tyrode’s buffer. Immediately thereafter, 36 µL diluted whole blood was mixed with 4 µL of 100 µM ADP or 100 µM thrombin receptor activating pepetide-6 (TRAP) to achieve final concentrations of 10 µM of ADP or TRAP, respectively, and subsequently incubated for 10 min at 37 °C. After the addition of 20 µL of antihuman monoclonal antibodies against CD62P-PC5, CD63-PE, or Fibrinogen-FITC and further incubation for 5 min at 37 °C in the dark, the reaction was quenched with 1 ml of ice-cold Tyrode’s buffer. Platelet activity marker expression was measured on a Coulter Epics XL flow cytometer (Coulter, Krefeld, Germany) and expressed as median fluorescence intensity (MFI) relative to the basal expression of the respective activity marker. Ten-thousand single platelets were gated based on forward and sideward-scatter characteristics and CD41 (PC-7 labeled) expression. Prior to analysis, MFI was normalized to correct for lot-to-lot variations by fluorescent beads. Ten-thousand single platelets were gated based on forward and sideward-scatter characteristics and CD41-PC-7 expression. Isotype controls were used to estimate non-specific binding. To prevent the false-positive classification of ADP-induced platelet reactivity, patients on the P2Y12 inhibitor clopidogrel ($$n = 104$$, $5.8\%$) and those who were unresponsive (i.e., preactivated) to ADP-stimulation (defined as ADP-induced activation marker expression relative to basal marker expression < 1.0; $$n = 156$$, $8.7\%$) were excluded from any subsequent analysis (Supplementary Material Figure S2). Therefore, platelet reactivity data were available in $\frac{1520}{1780}$ ($85.4\%$) patients. ## 2.4. Follow-Up and Endpoints There was a follow-up for all-cause and cardiovascular mortality. Information on the vital status was obtained from local person registries. Using death certificates, two experienced clinicians independently classified the causes of death. They were blinded to any data of the study participants. In cases of disagreement or uncertainty concerning the coding of a specific cause of death, classification was made by a principal investigator of the LURIC study (W. M.). In 1520 patients, a total of 452 deaths (284 of cardiovascular cause) occurred during a mean follow-up time of 8.4 (±2.8) years. ## 2.5. Statistical Analysis The baseline characteristics are reported as median with inter-quartile ranges and percentages in cases of categorical variables and means with standard deviations (resp. medians with inter-quartile ranges) in cases of continuous variables. Continuous variables were tested for normal distribution using the Kolmogorov–Smirnov test and log-transformed before analysis when required. Data were stratified into three groups according to platelet reactivity (i.e., High-, Low-platelet reactivity, and Reference group). Platelet CD63 expression demonstrated better discrimination for Low-platelet reactivity than CD62P and was therefore chosen for stratification (cf. results for details). The High- and Low-platelet reactivity groups were derived from an age- and sex-adjusted Cox model (model 1) by restricted cubic splines (RCS) when hazard ratios for cardiovascular mortality significantly deviated from 1.0 in Low ($$n = 464$$) and High ($$n = 511$$) CD63 expressors (Supplementary Materials Figure S1). The remaining patients were considered as the Reference group ($$n = 545$$). Cut-offs were <1.22 for Low-platelet reactivity, 1.22–1.50 for the Reference group, and >1.50 for High-platelet reactivity (i.e., ADP-CD63 [MFI]/basal CD63 [MFI]). Comparisons between High-, Low-platelet reactivity and the Reference group were made with the Kruskal-Wallis ranks sum test for continuous variables and with the two-sided Fisher test for binary variables (cf. Supplementary Materials “Statistical methods” for details). The RCS was set up to have five knots at the 5th, 27.5th, 50th, 72.5th, and 95th percentile for CD62P and CD63 expression, respectively. Splines were adjusted for potential confounders as follows: *In a* basic model (model 1), we adjusted for age and sex. In a second model (model 2), we additionally adjusted to living conditions (alone/not alone), smoking, alcohol intake, and anti-platelet therapy. In a third model, we adjusted for the glomerular filtration rate (eGFR), hsCRP, low-density lipoprotein cholesterol (LDL-C), HbA1c%, body mass index (BMI), and systolic blood pressure. In the last model (model 4), we additionally adjusted for the Charlson comorbidity Index and Friesinger Score. The stability of all models was confirmed by repeated random resampling (cf. Supplementary Materials “Statistical methods” for details). Relative weight analysis was performed for each of the 3 groups (i.e., High-, Low-platelet reactivity, and Reference group) individually according to the methodology by Heller et al. as previously described [15,16]. To omit multiple testing, only modifiable factors with an R2 > 0.01 were used for further assessment. Based on these risk modifiers, risk groups were created. Cut-offs for risk groups were determined a priori based on a guideline recommendation [17] for treatment targets and risk markers (e.g., HbA1c < $7\%$ in patients with diabetes mellitus; eGFR < 60 mL/min) or observational studies [18] (i.e., hsCRP < 3 mg/L). In any case, where Cox regression has been performed, the global test for the proportional hazard assumption by scaled Schönfeld residuals provided a p-value larger than 0.05. ( cf. Supplementary Materials “Statistical methods” for details). All analyses were performed using the SPSS 26.0 statistical package (IBM SPSS Inc., Ehningen, Germany) and R (version 4.0.2). All statistical tests were 2-sided, and p values <0.05 were considered significant. ## 3.1. Platelet Reactivity and Cardiovascular and All-Cause Mortality in the LURIC Study Among the 1520 patients investigated, 452 deaths occurred (284 of cardiovascular cause) within a mean follow-up time of 8.4 ± 2.8 years. ADP-induced platelet reactivity at baseline measured by Fibrinogen-binding, CD62P, and CD63 expression was a significant predictor of cardiovascular and all-cause mortality, and all three markers demonstrated a U-shaped relationship with cardiovascular mortality rates (Supplementary Materials Figure S3). CD63 expression was a better discriminator for patients with Low-platelet reactivity and was thus chosen for all subsequent analyses to assess the full range of abnormal platelet reactivity (Figure 1A,B). Based on the hazard for cardiovascular mortality, patients were stratified into a High- and Low-platelet reactivity risk population (High platelet reactivity: 511 [$33.6\%$]; Low platelet reactivity: $$n = 464$$ [$30.52\%$]). Within these risk groups, the association of High- and Low platelet reactivity with cardiovascular mortality remained significant after additional adjustment for age, sex, living conditions, smoking, alcohol, antiplatelet therapy, eGFR, hsCRP, LDL-C, HbA1c, systolic blood pressure, Charlson Comorbidity Index and Friesinger Score (Model 4: Low-platelet reactivity: 1.4 [$95\%$ CI 1.0–2.0], $$p \leq 0.0254$$ [1.2 for death]; High-platelet reactivity: 1.4 [$95\%$ CI 1.1–1.9], $$p \leq 0.0175$$ [1.2 for death]) (Figure 1C,D). TRAP-induced platelet reactivity was not predictive of cardiovascular and all-cause mortality (Supplementary Materials Figure S4). ## 3.2. Baseline Characteristics in Patients with Abnormal Platelet Reactivity Clinical and laboratory characteristics stratified by ADP-induced platelet reactivity are shown in Table 1. Atherosclerosis-associated diseases and heart failure were equally distributed among all groups at baseline. However, patients with High-platelet reactivity had a distinct cardiovascular risk profile with a significantly higher prevalence of chronic kidney disease (CKD) and diabetes mellitus as well as a higher Framingham Risk Score (FRS) and Charlson Comorbidity Index (CCI). In addition, plasma levels of HbA1c and hsCRP were significantly higher in the High-platelet reactivity group, whilst eGFR was lower. In contrast, clinical characteristics of patients with Low-platelet reactivity were statistically equivalent to the reference group. Patients that received aspirin at baseline were equally distributed among all groups, whilst the proportion of patients that received diuretics was significantly higher in the High-platelet reactivity group (Table 2). ## 3.3. Abnormal Platelet Reactivity Is a Coronary Artery Disease Risk Equivalent Since both, High- and Low-platelet reactivity were associated with increased mortality, we next pooled these patients and compared mortality risk with the risk of patients with angiographically verified coronary artery disease (CAD). We stratified patients into four groups based on the presence and absence of CAD and High/Low platelet reactivity, respectively, and calculated survival curves. Patients with CAD and High/Low platelet reactivity had the highest mortality risk while patients without CAD and normal platelet reactivity had the lowest risk. ( Figure 2A,B) Strikingly, patients with CAD and normal platelet reactivity exhibited a similar cardiovascular and all-cause mortality risk compared to patients without CAD but High/Low platelet reactivity, suggesting that abnormal platelet reactivity is a CAD risk equivalent in our study population (log-rank test: $$p \leq 0.86$$ for cardiovascular mortality [$$p \leq 0.16$$ for all-cause mortality]. This risk-equivalence persisted when CAD mortality was compared with High- and Low-platelet reactivity separately (Supplementary Figures S5 and S6). ## 3.4. Relative Importance of Risk Markers in Patients with High- and Low-Platelet Reactivity To investigate potential differences in risk profiles among patients with High- and Low-platelet reactivity, we analyzed the association of predefined risk markers in a Cox model for all groups separately (Figure 3A,B). Given the risk-equivalence of High- and Low-platelet reactivity to CAD, we focused on risk markers considered to be of importance in cardiovascular disease prevention [17]. Age and Charlson Comorbidity Index (CCI) were among the strongest relative contributors in the Cox model irrespective of platelet reactivity status. In addition, eGFR and HbA1c were relatively high-ranked contributors in all groups (all R2 > 0.01). However, HbA1c ranked highest in patients with High-platelet reactivity compared to Low-platelet reactivity and the reference group in particular with respect to cardiovascular mortality (High platelet reactivity: R2 0.037, Low platelet reactivity: R2 0.015, Reference Group: R2 0.011). In addition, high-sensitive CRP and antiplatelet therapy with Aspirin was associated with cardiovascular mortality in the high platelet reactivity group but did not reach the threshold of R2 ≥ 0.01 in the remaining groups (High platelet reactivity: R2 0.015 [hsCRP]; 0.015 [Aspirin], Low platelet reactivity: R2 0.003 [hsCRP]; 0.001 [Aspirin], Reference Group: R2 0.008 [hsCRP]; 0.003 [Aspirin]). Other cardiovascular risk factors, including smoking and LDL-C, were of relatively little importance among all groups, irrespective of cardiovascular and all-cause mortality (all < R2 0.01). ## 3.5. Risk Assessment in Patients with Abnormal Platelet Reactivity Next, we selected the four highest ranked risk-modifiers (i.e., eGFR, HbA1c in patients with diabetes, hsCRP, and Aspirin therapy), identified by the relative weight analysis and tested in a hypothesis-generating approach whether these may modulate elevated cardiovascular or overall mortality risk in patients with High and Low platelet reactivity (Figure 4A,B). Patients with either High- or Low-platelet reactivity were stratified based on the presence or absence of these modifiers. Mortality risk was compared to the risk of the reference group in the absence of a risk modifier or the presence of therapy (i.e., the group with the lowest mortality risk). Following this strategy, we found that an eGFR > 60 mL/min, HbA1c < $7.0\%$ (in subjects with diabetes mellitus), and hsCRP < 3 mg/L were associated with a cardiovascular and all-cause mortality risk reduction in patients with either High- or Low-platelet reactivity (Figure 4A,B). Interaction analysis indicated that the effect of risk modification was equal for all groups (all $p \leq 0.05$). In contrast, interaction analysis of Aspirin therapy indicated a higher treatment effect in patients with High-platelet reactivity compared to the reference group (p for interaction: 0.02 [all-cause mortality: <0.001] that was not present in patients with Low-platelet reactivity (p for interaction: 0.83 [all-cause mortality: 0.20]. Prediction functions for eGFR, HbA1c, and hsCRP to assess the mortality risk modulation on a linear scale are presented in the Supplementary Materials (Supplementary Figure S8). ## 4. Discussion The present explorative study demonstrates that High- and Low-ADP-induced platelet reactivity measured by CD63 expression, are predictors of cardiovascular and all-cause mortality in the LURIC study and risk-equivalent to the presence of CAD. In a hypothesis-generating approach, we explored potential modifiers of elevated cardiovascular and overall mortality risk in patients with High- and Low- platelet reactivity and identified (i) normal-near glucose control in subjects with diabetes mellitus, (ii) preserved kidney function, and (iii) low hsCRP levels as potential risk modifiers. The presence of these risk-modifiers was associated with a cardiovascular risk reduction in all patients, however irrespective of platelet reactivity status. In contrast, patients with High-platelet reactivity had a significantly higher cardiovascular and all-cause mortality risk reduction when treated with Aspirin. High- and Low-platelet reactivities predict atherothrombosis, bleeding, and mortality risk under various conditions assessed by multiple assays, including the VerifyNow, Multiplate analyzer, Light transmission aggregometry, and the VASP assay [1,2,3,4,5,9,10,11,19,20,21,22,23,24]. While most of the present studies investigated the role of platelet reactivity to assess drug resistance in highly-selected populations on dual antiplatelet therapy, the LURIC study encompasses an unselected, P2Y12 naïve population, scheduled for angiography in a real-world setting. Given the long-term follow-up of 8.4 years, our approach allowed us to investigate the prognostic role of platelet reactivity in a population with a high number of fatal endpoints ($29.3\%$ mortality events; $18.8\%$ of cardiovascular cause). Remarkably, we found that both High- and Low-platelet reactivity were equally associated with an increased risk, as platelet reactivity demonstrated a U-shaped relationship with cardiovascular and all-cause mortality. Therefore, our study extends previous observations by Puurunen et al. and Thaulow et al., who focused on the prognostic role of High-platelet reactivity in comparable cohort studies [2,5]. We found all three activity markers, including Fibrinogen-binding, CD62P, and CD63 to be associated with an increased mortality risk. However, CD63 demonstrated better discrimination for patients with low-level platelet reactivity and was therefore used for all analyses presented. Of note, Fibrinogen-binding is an indirect marker of the active conformation of αIIbβIII; CD62P indicates alpha granules release [25] while CD63 indicates dense granules release and therefore, all markers may represent different phenotypes of platelet activation [26]. Fibrinogen-binding is a relatively imprecise marker of active αIIbββIII and may therefore diminish the ability of the marker to detect platelet with low-platelet reactivity. In addition, rapid CD62P shedding [27,28] may explain the inferior ability of CD62P to identify patients with low platelet reactivity, since patients with increased shedding and true low-platelet reactivity will both have decreased levels of CD62P. Therefore, some studies suggest that CD63 expression may be a better marker for ongoing platelet activation which may have a different prognostic meaning [29]. However, the comparison of Fibrinogen-binding, CD62P, and CD63 was beyond the scope of this study and remains speculative. Impaired platelet reactivity is associated with increased bleeding risk in numerous studies [30,31,32,33]. While fatal bleeding events were not present in the studied population, non-fatal bleeding events were not explicitly recorded in the LURIC study. Indeed, the ASCEND trial of aspirin for primary prevention in patients with diabetes mellitus demonstrated that patients with the highest risk of non-fatal bleeding events were those with the highest cardiovascular mortality risk [34]. However, the reason for the increased rate of cardiovascular mortality in patients with Low-platelet reactivity is incompletely understood. It can be speculated that patients with Low-platelet reactivity have an increased rate of intramural hematomas of the coronary vessels that increases their cardiovascular event risk. In addition, if Low-platelet reactivity is an indicator of non-fatal bleeding, anti-platelet therapy may have been stopped prematurely in these patients, leaving them at increased cardiovascular event risk. Considering the available literature, it needs to be underlined that these patients represent a yet incompletely understood patient group that is clinically challenging and deserves further attention in future trials. Most importantly, patients with High- and Low-platelet reactivity had the same cardiovascular and all-cause mortality risk as patients with CAD and normal platelet reactivity, suggesting that abnormal platelet reactivity is a CAD risk equivalent. In addition, the analogous progression of the survival curves over time underlines the prognostic importance of platelet reactivity as a biomarker. However, in contrast to established treatment algorithms in patients with CAD, therapeutic strategies for patients with abnormal platelet reactivity are poorly defined. Given the uncertainty of therapeutic strategies, we set out to explore whether certain risk markers or therapies may modulate cardiovascular or overall mortality risk in patients with abnormal platelet reactivity. To this end, we employed a combined strategy of a relative weight analysis, stratified cox proportional hazard models, and prediction functions by restricted cubic splines to identify potential risk factors and markers, inspired by a similar strategy by Rawshani and colleagues [16]. For stratification and evaluation of risk groups, we used treatment recommendations from the ESC for cardiovascular disease prevention and observational studies [17,18]. Following this strategy, we identified the presence of antiplatelet therapy by Aspirin as a potential risk modifier that was associated with a higher risk reduction in patients with High-platelet reactivity compared to patients in the Reference- and Low-platelet reactivity groups. This observation is strengthened by the fact that Aspirin treatment rates were similar among all platelet reactivity risk groups. However, we cannot exclude that Aspirin therapy constitutes a confounder in the LURIC study for pre-identified high-risk patients that may have received better treatment. Therefore, it remains unclear whether the risk reduction is a direct treatment effect or indicates better medical treatment and thus should be interpreted with caution. However, given the ongoing debate on Aspirin therapy in primary prevention [34,35,36], it is attractive to speculate that ADP-induced CD63 expression may constitute a potential marker to identify patients that may benefit more from Aspirin therapy. Nevertheless, prospective trials are needed to address this question. In addition, we identified (i) HbA1c < $7.0\%$ in patients with diabetes mellitus, (ii) eGFR > 60 mL/min/1.73 m2, and (iii) hsCRP < 3mg/L as potential risk modifiers. The presence of these risk modifiers was associated with a risk reduction that was similar in all patients and therefore indicated effects independent of platelet reactivity. However, given the increased absolute mortality risk of patients with either High- or Low-platelet reactivity, the net risk reduction is higher in patients with abnormal platelet reactivity. Of note, given the nature of this study, we were unable to demonstrate causality, and prospective trials are needed to validate these findings. Our study has some limitations: We included a Caucasian patient population undergoing coronary angiography without any major non-cardiac diseases. Therefore, our data cannot be generalized to populations of other ethnicities, younger ages, or those with additional comorbidities. In addition, the LURIC study only recorded fatal outcomes. Therefore, non-fatal outcomes could not be evaluated (i.e., myocardial infarction, stent-thrombosis, bleeding, etc.). In addition, our study included more male subjects ($68\%$) than females, and therefore a bias toward the male sex cannot be excluded. In this study, we utilized the degranulation markers CD62P and CD63 as markers of ADP-induced platelet reactivity. Despite the widely used platelet activity markers in experimental research, these markers are less well characterized in a clinical setting. Nevertheless, we were able to demonstrate that (i) both markers increased expression in response to stimulation (Supplementary Materials; Figure S7) and (ii) both markers identified patients at risk of cardiovascular and all-cause mortality. In summary, our study extended current knowledge on the prognostic importance of High- and Low-platelet reactivity and suggests that both are CAD risk equivalents. In addition, we demonstrated a close association of mortality in patients with High and Low platelet reactivity with renal function, glucose control, inflammation. 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--- title: COVID-19 Patients with Early Gastrointestinal Symptoms Show Persistent Deficits in Specific Attention Subdomains authors: - Juliana Schmidt - Maria Cruz - Julio Tolentino - Aureo Carmo - Maria Paes - Glenda de Lacerda - Ana Gjorup - Sergio Schmidt journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003448 doi: 10.3390/jcm12051931 license: CC BY 4.0 --- # COVID-19 Patients with Early Gastrointestinal Symptoms Show Persistent Deficits in Specific Attention Subdomains ## Abstract Previous studies have shown that COVID-19 inpatients exhibited significant attentional deficits on the day of discharge. However, the presence of gastrointestinal symptoms (GIS) has not been evaluated. Here, we aimed to verify: [1] whether COVID-19 patients with GIS exhibited specific attention deficits; [2] which attention subdomain deficits discriminated patients with GIS and without gastrointestinal symptoms (NGIS) from healthy controls. On admission, the presence of GIS was recorded. Seventy-four physically functional COVID-19 inpatients at discharge and sixty-eight controls underwent a Go/No-go computerized visual attentional test (CVAT). A Multivariate Analysis of Covariance (MANCOVA) was performed to examine group differences in attentional performance. To discriminate which attention subdomain deficits discriminated GIS and NGIS COVID-19 patients from healthy controls, a discriminant analysis was applied using the CVAT variables. The MANCOVA showed a significant overall effect of COVID-19 with GIS on attention performance. The discriminant analysis indicated that the GIS group could be differentiated from the controls by variability of reaction time and omissions errors. The NGIS group could be differentiated from controls by reaction time. Late attention deficits in COVID-19 patients with GIS may reflect a primary problem in the sustained and focused attention subsystems, whereas in NGIS patients the attention problems are related to the intrinsic-alertness subsystem. ## 1. Introduction The bidirectional connection between the brain and the gut has been a topic of great interest in the last decade [1]. The brain–gut axis includes the central nervous system, the hypothalamic–pituitary–adrenal axis, the enteric innervation, and more recently the intestinal microbiota [2]. Several studies have shown that disturbances in the microbiota-gut–brain axis are involved in the physiopathology of many disorders, including functional gastrointestinal disorders, Alzheimer’s disease, Parkinson’s disease, Attention-deficit/hyperactivity disorder, and COVID-19 [3,4,5,6,7]. In addition, recent evidence suggests an association between gastrointestinal dysfunction and cognitive impairment [8]. COVID-19, a respiratory disease at origin, has emerged as a systemic disease related with several extrapulmonary manifestations, including gastrointestinal symptoms (GIS) [9]. GIS such as diarrhea, nausea, anorexia, and abdominal pain have been described in more than $10\%$ of COVID-19 patients [10,11,12]. A multicenter study with 106 patients infected by COVID-19, including $40\%$ with GIS, described that almost half of the participants presented an acute mucosal injury [12]. Of note, most of the endoscopy findings were found early during hospital admission. SARS-CoV-2 may invade the gastrointestinal tract through angiotensin-converting enzyme 2 (ACE) receptors and Type II transmembrane serine protease, which are present in the brush border and ciliated cells of intestinal enterocytes [13]. As a result, SARS-CoV-2 infection might cause mucosal damage and thus increase mucosal permeability, allowing bacterial translocation and potentially inflammation [13]. Gut microbiota dysbiosis has also been described in COVID-19 patients and may be an indirect result of ACE-2 dysregulation [7]. Thus, ACE-2 regulation is associated with gut microbiota balance, and its disturbance may play a role in the gastrointestinal symptoms reported by COVID-19 patients [7]. It has been hypothesized that after invading the gastrointestinal tract, SARS-CoV-2 may reach the central nervous system through the vagal nerve, vascular, and/or lymphatic systems [10]. Bostanciklioglu proposed that virus-welded gut inflammation may affect cognitive functions via the vagus nerve [10]. Accordingly, cognitive problems have also been described in COVID-19 patients after hospital discharge [14,15,16,17,18,19,20]. The cognitive deficits include executive functions, memory, and attention [14,15,16,17,18,19,20]. Recently, do Carmo et al. [ 2022] demonstrated significant attentional deficits in post-COVID patients [19]. In COVID-19 patients after hospital discharge, delayed cognitive deficits may operate independently or instead secondary to reductions in lower order domains, such as basic attention [21]. Attention consists of four subdomains, referred to as intrinsic alertness, sustained attention, focused attention, and behavioral inhibition [22]. These subdomains can be assessed with Go/No-go tests, such as the Continuous Visual Attention Test (CVAT) [22,23,24,25]. It is worth mentioning that the CVAT scores are independent of educational level [22,23,24]. Therefore, a short, computerized education-free attention task could provide relevant information on the cognitive outcome of patients with COVID-19 at the discharge day. As cognitive deficits can be attributed to different attentional subdomains, untangling their relative contribution may help clarify the cognitive impairments observed in post-COVID-19 patients with GIS on the admittance day. Despite the influence of the enteric system on cognition and the role played by the attention subdomains on cognitive performance, there is a lack of information on this subject. We hypothesize that the presence of GIS at baseline would be associated with the presence of persistent attention deficits in COVID-19 patients on the day of discharge from the hospital. The present study aimed to verify whether COVID-19 patients with GIS at baseline exhibit specific attention subdomain deficits on the day of discharge from the hospital. We also verified which attention subdomain deficits discriminated COVID-19 patients with GIS and without gastrointestinal symptoms (NGIS) from the control group. ## 2.1. Participants (Patients and Controls) COVID-19 patients (positive RT-PCR) for SARS-CoV-2 were recruited from two reference hospitals in Rio de Janeiro, Brazil. Thirty patients were recruited at the University Hospital and assessed by Aureo do Carmo. This subsample is detailed by Do Carmo et al. [ 2022] [19]. Another 42 patients were recruited at Lagoa Federal Hospital and assessed by Maria Alice Paes. The symptoms at admittance were recorded for all patients. The patients who, at hospital admission, declared to have acute onset of nausea, vomiting, abdominal pain, diarrhea, and constipation were included in the GIS group. The functional status of COVID-19 patients on the day of discharge was assessed by the physician on duty on that day. The patient should be able to eat, walk, and use a toilet without assistance. At the day of discharge, the patients performed a visual attention task (CVAT). The control group consisted of age- and sex-matched subjects who had not had a previous infection with SARS-CoV-2 before the CVAT assessment. The controls included hospital employees, patients’ relatives, and volunteers who agreed to participate in the study. They all performed the CVAT. Exclusion criteria for all groups were: age higher than 70 or <18 years; use of antiseizure or psychotropic drugs; reduced kidney or hepatic function; past head trauma or loss of consciousness; alcohol/substance abuse; pre-existing neurologic or psychiatric disorders; non-corrected hearing or visual impairments; and previous cognitive impairment. We excluded COVID-19 patients who presented delirium, new neurological symptoms, or orotracheal intubation. Criteria for discharge were a minimum oxygen saturation of $94\%$ in ambient air without oxygen supplementation for 24 h. The participation was voluntary, and the research protocol was approved by the Gaffrée and Guinle University Hospital Ethics Committee (CAA: 30547720.3.0000.0008). The study was performed in accordance with the Helsinki Declaration. Informed written consent was obtained from all the participants. ## 2.2. Attention Task (CVAT) (Figure 1) Subjects were seated in front of a computer. The distance between the center of the monitor and the eyes was approximately 50 cm. The examiner instructed the subject to press the spacebar on the keyboard as fast as possible each time a specific target was displayed. The test started with instructions and a practice session. There was one block with 90 trials (two figures presented, one each time, target or non-target). The interstimulus time interval was 1 s. Each stimulus was displayed for 250 milliseconds. The test took 1.5 min to complete. The types of measures included omission errors (OE, focused attention), commission errors (CE, response inhibition), average reaction time of correct responses (RT, intrinsic alertness), and variability of correct reaction times (VRT, sustained attention). VRT was estimated by a per-person measure of the standard deviation (SD) of individual RTs for the correct responses. The total number of correct targets was 72. The participants had to reach more than $50\%$ of the total correct hits (minimum number of correct RT measurements per participant = 37). Previous studies have shown that RT and VRT can be reliably measured by tests as short as 52 s with 20 items [26]. This short version of the CVAT has been applied in previous studies, including for individuals with Alzheimer’s disease and mild cognitive impairment, COVID-19 patients, and in healthy subjects [19,23,24,27]. **Figure 1:** *Schematic overview of the set-up of the attentional test (CVAT). (A)—The CVAT starts with the following instructions: “In this test, the computer alternately displays the indicated figures in the center of the screen. You must press the spacebar using your dominant hand as fast as you can whenever the star appears in the center of the screen. If the other figure appears, you should not press the space”. (B)—The target (star) stays on the screen for 250 milliseconds. (C)—The non-target (diamond) remains on the screen for 250 ms. The test has 90 trials and takes 1.5 min to complete. Variables provided by the test: omission errors, commission errors, average Reaction Time of the correct responses (RT), and Intraindividual Variability of Reaction Time (standard deviation of the RTs during the test). The CVAT is open for research and for clinical use (licensed psychologists), upon request to Prof. Sergio L. Schmidt (corresponding author). The test has versions in English, Spanish, and Portuguese. All patients and controls were from Brazil and the Portuguese version was used.* ## 2.3. Statistical Analysis Demographic variables were analyzed using independent sample t-tests for normally distributed continuous variables or chi-square tests for categorical variables. All the following statistical procedures were performed using the dependent variables (OE, CE, RT, and VRT). Regarding the sample size, we calculated the minimum number of subjects that would be necessary to find clinically significant differences for each CVAT variable. Based on a previous larger sample of healthy subjects, considering α = Type I error = 0.05 and β = Type II error = 0.20 (power= 1 − β = 0.80), we estimated that the minimum number of subjects was 15. It should be mentioned that the CVAT is very reliable in the age range of this investigation. To assess the effect of COVID-19 on attention subdomains, a Multivariate Analysis of Covariance (MANCOVA) was performed to examine group differences (COVID-19 vs. controls) for the CVAT variables, using age and sex as covariates. In case of a significant overall MANCOVA, post hoc analysis of covariance (ANCOVAs) for each dependent variable was conducted for statistical significance. For the MANCOVA and each of the ANCOVAs, η2 (Eta-squared) was computed to calculate the effect size of the results. Cohen has suggested that η2 = 0.01 should be considered a small effect size, 0.06 a medium effect size, and 0.14 a large effect size [28]. The procedures described above are all based on mean comparisons. Comparing averages can indicate variable between-group CVAT differences. However, it does not indicate which variables effectively discriminate between groups with and without GI from the control group. Thus, a stepwise discriminant analysis was performed using the raw scores of the attention test (OE, CE, RT, and VRT). Initially, the equality of the group means was tested using Wilk’s λ. Then, the assumptions of the discriminant analysis were tested (linearity, normality, multilinearity, equal variances, and multivariate normal distribution). Box’s M tests were performed to test the assumption of homogeneity of the covariance matrices. The Box’s M test was interpreted in conjunction with inspection of the natural log determinants. The discriminant analysis considered the linear combination of the variables that were necessary and sufficient to discriminate the groups. The canonical discriminant function coefficients were calculated to obtain the Discriminant Functions (DFs). Chi-squared tests (χ2) were performed to verify if the DFs were better than chance at separating the groups. Wilk’s λ was used to measure how each function separated the cases. With the aid of each DF, the accuracy of the classification was measured. To exclude the possibility that a participant’s VRT might be related to the average of the individual RTs, we calculated the coefficient of variability (CV = VRT/RT) for each participant [24]. Therefore, MANCOVAs, ANCOVAs, and the DISCRIMINANT ANALYSES were retested using OE, CE, and CV as dependent variables. Direct comparisons of the effect of COVID-19 on the different variables of the CVAT were done using standardized non-dimensional scores calculated using the means and the standard deviations of the control group for each CVAT variable. This score showed how many standard deviations a particular patient was above or below the control group mean. ## 3.1. Demographics (Table 1) After applying the exclusion and inclusion criteria, 68 controls, 18 eligible COVID-19 inpatients for the GIS group, and 56 for the NGIS group were selected. All demographic information can be found in Table 1. For all the participants ($$n = 142$$), the age ranged from 18 to 69 years (mean = 47.2; standard deviation = 13.4), and $53\%$ were women. The participants included in this study denied the presence of prior gastrointestinal disorder. Length of stay in the hospital ranged from 1–37 days. No significant demographic differences were found among the groups. **Table 1** | Unnamed: 0 | Unnamed: 1 | COVID-19 | GIS | NGIS | Control | All | | --- | --- | --- | --- | --- | --- | --- | | | | (n = 74) | (n = 18) | (n = 56) | (n = 68) | (n = 142) | | Female gender (%) | | 47% | 44% | 48% | 59% | 53% | | Age (years) | Mean (SD) | 50.0 (13.6) | 50.6 (12.5) | 49.7 (14.0) | 44.6 (12.9) | 47.2 (13.4) | | | Minimum | 18 | 25 | 18 | 18 | 18 | | | Maximum | 69 | 67 | 69 | 68 | 69 | | Length of stay (days) | Mean (SD) | 12 (7.6) | 8.6 (4.3) | 11.2 (8.4) | - | - | | | Minimum | 1 | 3 | 1 | - | - | | | Maximum | 37 | 15 | 37 | - | - | ## 3.2. Mean Differences Amount the Groups As the present study included 74 patients and 68 controls, and the sample size for each subgroup was always >15, we concluded that the sample size reached the number required to find clinically reliable conclusions. After adjusting for the covariates (age and sex), the MANCOVA showed a significant overall effect of COVID-19 on the attention performance in NGIS patients as compared to controls ($F = 23.16$, df = $\frac{4}{117}$, $p \leq 0.001$, η2 = 0.44). The univariate tests showed that COVID-19 in NGIS patients affected OE ($F = 28.26$, df = $\frac{1}{120}$, $p \leq 0.001$, η2 = 0.19), RT ($F = 62.37$, df = 1 /120, $p \leq 0.001$, η2 = 0.34), and VRT ($F = 75.17$, df = $\frac{1}{120}$, $p \leq 0.001$, η2 = 0.38), but not CE ($F = 0.14$, df = $\frac{1}{120}$, $$p \leq 0.71$$, η2 = 0.001). The same was observed in the GIS group. Thus, in patients with GIS at baseline, the MANCOVA showed a significant overall effect of COVID-19 on the attention performance ($F = 19.91$, df = $\frac{4}{79}$, $p \leq 0.001$, η2 = 0.50). The univariate tests in GIS patients showed that COVID-19 affected OE ($F = 55.49$, df = $\frac{1}{82}$, p = <0.001, η2 = 0.40), RT ($F = 39.33$, df = $\frac{1}{82}$, $p \leq 0.001$, η2 = 0.32), and VRT ($F = 46.80$, df = $\frac{1}{82}$, $p \leq 0.001$, η2 = 0.36), but not CE ($F = 0.087$, df = $\frac{1}{82}$, $$p \leq 0.77$$, η2 = 0.001). When VRT and RT were replaced by CV, the effect of COVID-19 on attention performance in NGIS patients remained significant ($F = 19.16$, df = $\frac{3}{118}$, $p \leq 0.001$, η2 = 0.33). The univariate tests confirmed that COVID-19 affected OE ($F = 28.26$, df = $\frac{1}{120}$, $p \leq 0.001$, η2 = 0.19) and CV ($F = 49.24$, df = $\frac{1}{120}$, $p \leq 0.001$, η2 = 0.29). CE was not affected by COVID-19 ($F = 0.14$, df = 1 /120, $$p \leq 0.71$$, η2 = 0.001). The same was found in GIS patients. The MANCOVA tests showed that the effect of COVID-19 on attention performance remained significant ($F = 22.57$, df = $\frac{3}{80}$, $p \leq 0.001$, η2 = 0.46). The univariate tests in GIS patients demonstrated that COVID affected OE ($F = 55.49$, df = $\frac{1}{82}$, $p \leq 0.001$, η2 = 0.404) and CV ($F = 26.95$, df = $\frac{1}{82}$, $p \leq 0.001$, η2 = 0.247). In addition, CE was not affected by COVID-19 ($F = 0.087$, df = $\frac{1}{82}$, $$p \leq 0.77$$, η2 = 0.001). ## 3.3. Discriminant Model (Table 2) For the NGI group, considering the CVAT variables (OE, CE, RT, VRT), there were two significant discriminant dimensions [χ2 [2] = 68.1, $p \leq 0.001$]. The pooled within-group correlations identified large correlations with the discriminant model: VRT and RT (Table 2). Therefore, VRT and RT were able to discriminate among the groups. The subjects were correctly classified with 77.4 % accuracy. When VRT and RT were replaced by CV, we found only one significant dimension for the NGIS group [χ2 [1] = 42.54, $p \leq 0.001$]. The pooled within-group correlations identified that CV alone was capable of discriminating the control group from the NGI group, with $73.4\%$ accuracy. **Table 2** | Group without Gastrointestinal Symptoms vs. Control Group | Loadings | | --- | --- | | Variability of reaction time * | 0.91 | | Reaction Time * | 0.86 | | Omission errors (NI) | 0.35 | | Commission errors (NI) | 0.37 | | Group with Gastrointestinal Symptoms vs. Control Group | Loadings | | Variability of reaction time * | 0.81 | | Reaction Time (NI) | 0.52 | | Omission errors * | 0.89 | | Commission errors (NI) | 0.23 | For the GIS group, there were two significant discriminant dimensions [χ2 [2] = 53.4, $p \leq 0.001$]. The pooled within-group correlations identified large correlations with the discriminant model: OE and VRT. Therefore, OE and VRT discriminated GIS patients from controls, and the subjects were correctly classified with 90.7 % accuracy. When VRT and RT were replaced by CV, we still found two significant dimensions for the GIS group [χ2 [2] = 50.01, $p \leq 0.001$]. The pooled within-group correlations identified that CV and OE were capable of discriminating the control group from the GIS group with $90.7\%$ accuracy. The results based on the discriminant analyses are summarized in Figure 2. ## 3.4. Standardized Score The inspection of the standardized scores based on the control group indicated that in the NGIS group, RT was the most affected variable. In the GIS group, OE and CV were primarily affected. In the GIS group, an increase in CV reflected an increase in VRT independent of RT, as indicated by a non-significant correlation between CV and RT ($$p \leq 0.17$$). ## 4. Discussion The ANCOVAs indicated that RT, VRT, and OE attention subdomains were significantly affected by COVID-19, irrespective of the presence of GIS. However, the discriminant analysis (Figure 1) indicated that the NGIS group could be better differentiated from controls by the effect of COVID-19 on the RT variable. This shows that the primary variable affected in the NGIS group at the baseline is the alertness system (RT). In contrast, the GIS group could be better differentiated from controls by the effect of COVID-19 on the VRT and the OE variables. This indicates that the presence of GIS at the baseline causes a later effect on focused and sustained attention. ## 4.1. How COVID-19 Affects the Gut–Brain Axis Studies have demonstrated that COVID-19 has the potential to dysregulate the gut–brain axis by promoting systemic inflammation, gut microbiota dysbiosis, and psychological distress [29,30,31,32,33,34]. The virus’s impact on the gut–brain axis may result in neuroinflammation, brain damage, and an increased risk of developing neurodegenerative and neuropsychiatric disorders [29,30,31,32,33,34]. Several authors have proposed that gut dysbiosis may play a major role in the development of neurological disorders in patients infected by SARS-CoV-2 [29,30,31,33,34]. Some of the mechanisms that have been described include impaired production of short-chain fatty acids, increased circulation of lipopolysaccharides, neurotransmitter imbalance, and exacerbated production of proinflammatory cytokines [29,30,31,32,33,34]. ## 4.2. The Pronounced RT Increase in Patients without Early Gastrointestinal Symptoms (Figure 2 and Figure 3) In the present study, the VRT of each participant was estimated by the standard deviation (SD) of the individual’s RTs. Previous studies based on a wide range of different RT tasks have described a linear relation between RT mean and SD [35,36]. Our result in the NGIS group suggests that the general increase in VRT reflects a general slowing of RTs. This is corroborated by our results showing that RT was significantly related to VRT and CV. RT is supposed to be linked to brainstem arousal systems and the anterior cingulate gyrus to maintain alertness [37,38]. Accordingly, Ayalon et al. suggested that a longer average RT is associated with a lower arousal index [39]. Therefore, the greater RT exhibited by COVID-19 patients in the NGIS group may reflect a direct effect of the disease on these brainstem circuits necessary for alertness. **Figure 3:** *Hypothetical explanation for the attention deficits in the NGIS group. NGIS: COVID-19 patients without gastrointestinal symptoms; RT: reaction time. The arrow indicates an increase in the RT variable.* Young suggested that SARS-CoV-2 may damage the brainstem through viral invasion, inflammation, and vascular activation [40]. As a result, the virus may disrupt neurotransmitter systems in the brain, triggering neurological and cognitive manifestations. It has been proposed that cognitive dysfunction in COVID-19 patients after hospital discharge may be a result of systemic inflammation [41]. In this regard, Zhou et al., in a study including 29 recovered COVID-19 individuals, demonstrated that RT was positively correlated with C-reactive protein, suggesting a general underlying inflammatory process [41]. Indeed, a growing body of evidence suggests that viral infections can cause chronic inflammation, triggering long-lasting cognitive manifestations after the infection period [42]. However, most of the studies including attention assessments were performed with non-respiratory viruses, such as HIV and Hepatitis C [43,44,45,46]. In one of the few studies including a respiratory virus, Smith et al. described that Influenza B affects attentional performance on a simple task by about 20–$40\%$ [47]. Conversely, when the subjects were retested, one month later, their RT did not differ from the control group [47]. We suggest that in the NGIS group, the systemic inflammation might be linked with lung dysbiosis. Indeed, a recent study found that COVID-19 patients present higher levels of dysbiosis in the respiratory microbiota compared to healthy controls [48]. ## 4.3. The VRT and OE Increase in Patients with Early Gastrointestinal Symptoms (Figure 2 and Figure 4) The cerebral underpinnings of VRT have been studied less extensively than those of RT itself [49]. Previous studies using a Go/No-Go task in healthy subjects showed that increased VRT was related to an increased response in a network comprising the frontal and parietal regions [50,51]. **Figure 4:** *Hypothetical explanation for the attention deficits in the GIS group. GIS = COVID-19 patients with gastrointestinal symptoms; VRT = variability of reaction time; OE = omission errors. The arrows indicate an increase in the VRT and OE variables.* It should be mentioned that GIS may also be a result of dysfunction of the nucleus tractus solitarius and dorsal motor nucleus of the vagus due to its afferent and efferent neuronal projections with the gastrointestinal tract [40]. In addition, previous investigators have suggested that systemic cytokine release may lead to cortical dysfunction, resulting in cerebral hypometabolism and cognitive impartment [52]. Hosp et al. [ 2021] performed PET scans on average 1 month after symptom onset and observed predominant parietal hypometabolism in two-thirds of 15 COVID-19 patients [52]. Unfortunately, the presence of GIS was not recorded in the study of Hosp et al. [ 2021]. The higher VRT exhibited by GIS patients might be caused by deficits associated with the sustained attention subdomain, because the VRT variable reflects the stability of response times as the test progressed. The number of omission errors (OEs) was also found to be increased in GIS patients, which indicates a further deficit in the focused-attention subdomain. Simultaneous deficits in OE and VRT might reflect lapses in attention during slow RTs [35]. In the present study, the discriminant analysis gives support for the hypothesis that the results on VRT and OE are explained by the VRT variable in the GIS group. As VRT and OE are related to lapses in attention, we concluded that COVID-19 patients with GIS exhibited sustained attention problems secondary to a primary deficit associated with VRT [25]. ## 4.4. The Disrupted Microbiome–Gut–Brain Axis: Early Effect on Vagus Nerve and Later on the Parietal Cortex (Figure 4) An alternative hypothesis is related to gut dysbiosis and disrupted microbiota–gut–brain axis. Current evidence suggests that microbiota abnormalities are present even after virus clearance and that gut microbiota of COVID-19 patients mirrors disease severity [53]. In addition, in non-COVID-19 patients, the presence of GIS is reflective of gut dysbiosis and disrupted microbiota–gut–brain axis [3]. Thus, we speculate that patients with GIS might present a gut dysbiosis signature that probably impacts the brain attention circuits via the vagus nerve and later the parietal cortex. However, no study has explored the possible association between gut microbiota and cognition dysfunction in post-COVID-19 patients with GIS. Therefore, further investigations are necessary to fully address these hypotheses. Recently, Kohn et al. provided evidence for associative patterns between the gut microbiota and brain network connectivity. They found that an abundance of Bifidobacterium was associated with frontoparietal attention networks in healthy subjects [54]. In addition to the brain, gut dysbiosis also affects the lungs [55]. Since SARS-CoV-2 potentially disrupts the gut–brain–lung axis, further studies should investigate if lung dysbiosis plays a role in the cognitive problems observed in COVID-19 patients with GIS at baseline or after infection. ## 4.5. Limitations and Strengths This article has some limitations. Due to the small sample size, we did not reach statistical power to analyze the influence of other cofactors such as fatigue status, medication use, and comorbidities. In addition, the lack of microbiota and immunological analyses limit the interpretation of the current data. Finally, the study design (cross-sectional) poses a further limitation to the data interpretation. An important strength of this study is the use of an education- and culture-free test. ## 5. Conclusions In conclusion, the present findings suggest that cognitive problems, commonly observed in COVID-19 patients with GI symptoms, may reflect a primary problem in the sustained and focused attention subsystems. 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--- title: Alzheimer’s Amyloid β Peptide Induces Angiogenesis in an Alzheimer’s Disease Model Mouse through Placental Growth Factor and Angiopoietin 2 Expressions authors: - Abdullah Md. Sheikh - Shozo Yano - Shatera Tabassum - Shingo Mitaki - Makoto Michikawa - Atsushi Nagai journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003449 doi: 10.3390/ijms24054510 license: CC BY 4.0 --- # Alzheimer’s Amyloid β Peptide Induces Angiogenesis in an Alzheimer’s Disease Model Mouse through Placental Growth Factor and Angiopoietin 2 Expressions ## Abstract Increased angiogenesis, especially the pathological type, has been documented in Alzheimer’s disease (AD) brains, and it is considered to be activated due to a vascular dysfunction-mediated hypoxic condition. To understand the role of the amyloid β (Aβ) peptide in angiogenesis, we analyzed its effects on the brains of young APP transgenic AD model mice. Immunostaining results revealed that Aβ was mainly localized intracellularly, with very few immunopositive vessels, and there was no extracellular deposition at this age. Solanum tuberosum lectin staining demonstrated that compared to their wild-type littermates, the vessel number was only increased in the cortex of J20 mice. CD105 staining also showed an increased number of new vessels in the cortex, some of which were partially positive for collagen4. Real-time PCR results demonstrated that placental growth factor (PlGF) and angiopoietin 2 (AngII) mRNA were increased in both the cortex and hippocampus of J20 mice compared to their wild-type littermates. However, vascular endothelial growth factor (VEGF) mRNA did not change. Immunofluorescence staining confirmed the increased expression of PlGF and AngII in the cortex of the J20 mice. Neuronal cells were positive for PlGF and AngII. Treatment of a neural stem cell line (NMW7) with synthetic Aβ1–42 directly increased the expression of PlGF and AngII, at mRNA levels, and AngII at protein levels. Thus, these pilot data indicate that pathological angiogenesis exists in AD brains due to the direct effects of early Aβ accumulation, suggesting that the Aβ peptide regulates angiogenesis through PlGF and AngII expression. ## 1. Introduction Alzheimer’s disease (AD) is a common dementia disease characterized by a progressive decline in cognitive functions [1]. Pathologically, amyloid plaques and intraneuronal neurofibrillary tangles are the main diagnostic criteria of AD [2]. Amyloid plaques primarily contain an aggregated form of amyloid β (Aβ), a 39–42 amino acids-long peptide fragment generated from membranous amyloid precursor protein (APP) by β- and γ-secretase enzyme activities [2,3]. This peptide is aggregation-prone and deposited in the brain parenchyma as oligomers or amyloid fibrils [4]. Aggregated Aβ shows neurodegenerative and neuroinflammatory properties [5,6]. These features (neurodegeneration and neuroinflammation) are always found in AD brains, indicating the potential importance of aggregation and deposition of the Aβ peptide in the pathology [3]. Probable causes of Aβ deposition are suggested to be increased production or decreased clearance [7]. After production, Aβ is cleared from the brain by enzymatic degradation and by phagocytic cells [8,9,10,11]. However, a bulk of the peptide is cleared through perivascular pathways [7]. Due to its high aggregation properties, Aβ may aggregate during its clearance and interfere with the perivascular pathways. Hence, the deposition of the peptide around the vessels could be an important feature of AD pathology. Indeed, deposition of Aβ is frequently seen around the vessels that cause amyloid angiopathy, along with AD pathology [12]. Such deposition causes the vessel to become fragile, resulting in microbleeds and associated inflammation [13]. In addition to neurodegeneration and neuroinflammation, increased angiogenesis is frequently seen in AD brains [14]. Aβ peptide demonstrated toxicity, not only towards neurons, but also towards the vascular cells, including endothelial cells and smooth muscle cells [15,16]. It is suggested that Aβ deposition might cause the dysfunction of vessel function, resulting in a hypoxic condition in AD brains [17]. Additionally, vascular dysfunction can induce an inflammatory response [18]. All these signals trigger the angiogenic process [14,19]. Hence, angiogenesis in AD is considered an indirect consequence of Aβ deposition-dependent vascular dysfunction. Such angiogenesis is mainly a pathologic type, which might cause the extravasation of blood constituents and the aggravation of the neuroinflammatory condition [10]. However, Aβ can directly induce inflammatory conditions [20]. Since inflammation and angiogenesis are intimately related [21], it is possible that Aβ can directly induce angiogenesis long before the occurrence of vascular dysfunctions and the related inflammation. Therefore, we hypothesized that angiogenesis is an early feature of AD pathology, which is a direct consequence of excess Aβ in the brain. In this study, we investigated the direct effects of Aβ on angiogenesis in AD using disease model mice and in vitro cell culture systems. To eliminate the role of vascular dysfunction in AD angiogenesis, we used young AD model animals prior to Aβ deposition in the vessels. We found that Aβ can directly induce pathological angiogenesis by altering the expression of several angiogenesis factors. ## 2.1. Aβ Deposition and Vessel Density in J20 Mice Brains Increased angiogenesis has been documented in AD brains due to vascular dysfunction and hypoxia [22,23]. Since Aβ deposition in vessel walls is considered a main pathological cause of vascular dysfunction and subsequent angiogenesis in AD [3,17], it was evaluated in APP transgenic mice (J20 strain) brains at an earlier time point (2 months). Immunostaining results showed that Aβ was mainly intraneuronal in the cortex and hippocampal areas at this time point, and very few vessels were Aβ immunopositive (Figure 1A and Supplementary Figure S1). The staining demonstrated a wide distribution pattern of Aβ in the cortex, but in the hippocampus CA1 areas, Aβ mainly positive in the pyramidal cell layer (Figure 1A). Quantification of the staining showed that at 2 months of age, the levels of Aβ in the J20 mice brains were higher than those in the wild-type mice (cortex Wt: 0.1 ± 0.09 vs. J20: 2.9 ± 1.2, $p \leq 0.001$; hippocampus Wt: 0.1 ± 0.09 vs. J20: 2.4 ± 0.75, $p \leq 0.001$), in which they was almost negative (Figure 1B). Then, double immunofluorescence staining was performed to identify Aβ-positive cells. The results demonstrated that Aβ was mainly positive in NeuN-positive neurons at this age (Supplementary Figure S1C). Since the antibody used for Aβ staining (6E10) can also detect amyloid precursor protein (APP) [24], immunostaining was performed using an APP-specific antibody. The results showed that at this time point, the staining pattern of APP was comparable to Aβ (Supplementary Figure S2). Moreover, APP-positive areas in the cortical and hippocampal areas of wild-type mice were similar to those of J20 (Supplementary Figure S2B). At 15 months of age, extracellular deposits of Aβ were found both in the cortical and hippocampal areas of J20 mice, and the immunopositive areas in both regions were increased compared to those of the 2-month-old mice (Supplementary Figure S1A,B). Since Aβ has the propensity to oligomerize, immunostaining was performed using an oligomer-specific antibody. The results showed that anti-oligomer immunopositive cells were mainly located in the cortical areas, with a few positive cells in the hippocampus (Figure 1C). Quantification of the staining revealed that the anti-oligomer immunopositive areas were increased both in the cortex and hippocampus of the J20 mice compared to the wild-type mice, in which they were almost negative (cortex Wt 0.19 ± 0.06 vs. J20 3 ± 0.76, $p \leq 0.01$; hippocampus Wt 0.22 ± 0.05 vs. J20 0.53 ± 0.17, $p \leq 0.05$) (Figure 1C,D). The vessel staining with STL showed that the number was increased only in the cortex (Wt: 30.5 ± 1.4 vs. J20: 43.7 ± 1.7, $p \leq 0.001$), but not in the hippocampal areas of J20 mice (Wt: 22.5 ± 2.1 vs. J20: 27.1 ± 4.5, $$p \leq 0.08$$) (Figure 1E,F). ## 2.2. Evaluation of Angiogenesis in J20 Brains Endothelial cells, especially angiogenic endothelial cells, express CD105 [25]. Immunostaining of CD105 showed a round-shaped appearance, along with long vessel-like structures in the cortex of the mice. The areas of such round-shaped CD105 positive structures were increased in J20 mice at 2 months of age (Wt: 2.4 ± 0.38 vs. J20: 6 ± 0.59, $p \leq 0.05$) (Figure 2A,B). However, in the hippocampus, the CD105-positive areas appeared to be similar between the Wt and J20 mice (Figure 2A,B). Next, the types of newly formed vessels were evaluated by double immunofluorescence staining of CD105 and collagen4 (Col4), where Col4 was used as a basement membrane marker. The results demonstrated that in the cortex of the J20 mice brains, many CD105-positive vessels lacked Col4 (Figure 2C). ## 2.3. Evaluation of the Expression of Angiogenesis Regulators in J20 Mice Brains First, the expression of angiogenesis regulators was evaluated at mRNA levels. The real-time PCR results showed that the mRNA of angiogenesis inducers such as VEGF was not increased in the cortex or hippocampal areas of J20 mice brains (cortex Wt: 0.88 ± 0.1 vs. J20: 0.81 ± 0.6, $$p \leq 0.044$$; hippocampus Wt: 0.74 ± 0.26 vs. J20: 1.32 ± 0.99, $$p \leq 0.23$$) (Figure 3A,B). However, the mRNA of PlGF, an angiogenesis inducer of the VEGF family [26], was increased in both the cortex and the hippocampus of J20 mice brains compared to those of their wild-type counterparts (cortex Wt: 1.17 ± 0.25 vs. J20: 2.94 ± 0.5, $p \leq 0.01$; hippocampus Wt: 1.12 ± 0.1 vs. J20: 5.2 ± 2.1, $p \leq 0.05$) (Figure 3A,B). Additionally, the mRNA of angiopoietin2 (Ang2), an angiogenesis regulator that destabilizes the vessels, was increased in those areas (cortex Wt: 1.47 ± 0.42 vs. J20: 3 ± 0.62, $p \leq 0.05$; hippocampus Wt: 2.19 ± 0.62 vs. J20 2.97 ± 0.15, $p \leq 0.05$) (Figure 3A,B). Conversely, the mRNA of Ang1 was not changed (cortex Wt: 0.87 ± 0.11 vs. J20: 0.78 ± 0.15, $$p \leq 0.21$$; hippocampus Wt: 1.06 ± 0.36 vs. J20: 1.61 ± 0.42, $$p \leq 0.08$$). Then, the expression of angiogenesis regulators in J20 mice brains at the protein level was evaluated. The immunostaining results showed that although the % immunopositive area of VEGF protein was increased in the cortical areas, it was not changed in the hippocampus of J20 mice brains compared to their wild-type counterparts (cortex Wt: 0.52 ± 0.17 vs. J20: 2.5 ± 0.66, $p \leq 0.01$; hippocampus Wt: 0.5 ± 0.6 vs. J20: 0.74 ± 0.23, $$p \leq 0.11$$) (Figure 4A,C and Supplementary Figure S3A). Moreover, the levels of VEGF and HIF-1α were very low in both the cortex and hippocampus of Wt and J20 mice at this time point (Figure 4B,C and Supplementary Figure S3B). Next, we evaluated the expression of PlGF and AngII in the J20 mouse brains at protein levels. Immunostaining results demonstrated that PlGF was expressed mainly in the neuron-like cells in the cortex (Figure 4D). Its expression in the hippocampus was lower than in the cortex. Quantification of immunostaining results showed that the % immunopositive area of PlGF protein was significantly increased in the cortex of J20 mice compared to their wild-type counterparts, whereas it was not changed in the hippocampus (cortex Wt: 1.36 ± 0.29 vs. J20: 4.84 ± 0.82, $p \leq 0.01$; hippocampus Wt: 2.05 ± 0.35 vs. J20: 1.56 ± 0.27, $$p \leq 0.39$$) (Figure 4F). In the case of Ang2, the staining pattern showed a round-shaped appearance (Figure 4E). Similar to PlGF, the % immunopositive area of Ang2 protein was higher in the cortex compared to the hippocampus. Compared to the wild-type, Ang2 was increased both in the cortex and hippocampus of J20 mice (cortex Wt: 0.52 ± 0.21 vs. J20: 4.2 ± 0.98, $p \leq 0.01$; hippocampus Wt: 0.07 ± 0.05 vs. J20: 1.8 ± 0.3.1, $p \leq 0.01$) (Figure 4F). ## 2.4. Identification of PlGF and AngII Expressing Cells in J20 Mice Brain To identify whether neurons expressed PlGF and AngII in J20 mouse brains, double immunofluorescence experiments were performed using NeuN neuronal labeling. The results showed that in J20 mice brains, many neurons were positive for PlGF in the cortex (Figure 5A and Supplementary Figure S4). Some of the neurons in the hippocampus were also positive (Figure 5A). Conversely, a few neurons were positive for AngII only in the cortical areas (Figure 5B and Supplementary Figure S5). ## 2.5. Effects of Aβ Peptide on PlGF and AngII Expression in an In Vitro Neural Stem Cell Culture Since neurons expressed both PlGF and AngII in vivo in J20 mice brains, we investigated the direct effects of the Aβ peptide on the expression of PlGF and AngII in a mouse neural stem cell line (NMW7) culture. After stimulating NMW7 with a synthetic Aβ1–42 peptide, the mRNA levels of both PlGF and AngII were significantly increased compared to moderately stimulated cells (PlGF: (−): 1.18 ± 0.19, Aβ: 3.28 ± 0.64, $p \leq 0.05$; AngII: (−): 1.08 ± 0.08, Aβ: 4.68 ± 1.8 $p \leq 0.05$) (Figure 6A). Evaluation of AngII expression at protein levels by immunocytochemistry also confirmed the Aβ1–42-induced increased expression of AngII in NMW7 culture (Figure 6B and Supplementary Figure S6). ## 3. Discussion In this study, we demonstrated that a pathological angiogenesis process is active in AD model mouse brains from an early age, which is not dependent on vascular dysfunction or hypoxic condition. Moreover, we elucidated the underlying molecular mechanism of such an early angiogenesis process, where PlGF and AngII play an important role. Since this is a transgenic model that expresses an increased amount of APP, the probable cause of such angiogenesis could be increased levels of Aβ peptide. Further in vitro experiments confirmed that Aβ indeed has the ability to increase PlGF and AngII expression in neuron cultures. Angiogenesis, especially vascular dysfunction, and subsequent hypoxia-dependent pathological angiogenesis are reported in the brains of AD subjects, which is manifested as a redistribution of tight junction proteins and impaired blood-brain barrier function [27,28,29]. Such angiogenesis type and vascular dysfunction are suggested to play an important role in the development and progression of AD [14,17]. Hence, understanding the molecular mechanism of this process could be important for developing a new therapeutic intervention that targets angiogenesis and BBB restoration. Such therapy could not only inhibit the onset, but also slow the progression of AD pathology. In this respect, the findings of our study are important because we demonstrated that in addition to vascular dysfunction-mediated hypoxic angiogenesis, Aβ-dependent angiogenesis exists in the AD condition, and it appeared early in the pathology. Such findings may help to devise a more effective strategy to combat angiogenesis and thereby the onset and progression of AD pathology. Staining data of the vessels, especially endoglin-positive new vessels, showed that the numbers were increased in the cortical areas of APP transgenic mice, whereas in the hippocampal region, they were largely unaffected. These results suggest that angiogenesis starts mainly in the cortical region of the mice at early time points, which may then spread to hippocampal areas. Aβ positive neurons are widely spread in the cortical areas, whereas the positive cells were found in compact areas at the pyramidal cell layer and dentate gyrus of the hippocampus. Such distribution might initially increase the Aβ-induced expression of angiogenesis regulators in a wide area of the cortex. Indeed, angiogenesis regulators, including PlGF and AngII, were mainly increased in the cortex, emitting a strong signal that induces angiogenesis in these areas. In humans, cerebral amyloid angiopathy and related vascular dysfunction are suggested to affect small vessels in the cortical areas [30,31]. Moreover, amyloid deposits start in the cortical areas and spread to the hippocampal areas at a later stage [32,33]. These findings suggest that cortical areas are the initial target of Aβ-dependent vascular pathology and hypoxia-dependent angiogenesis. In this report, we demonstrated that PlGF-mediated angiogenesis signals exist in the same areas early in the disease process before the development of hypoxic conditions or vessel amyloid deposits. Another important aspect of this type of angiogenesis is that AngII levels were increased without affecting AngI levels. The balance and synchronized expression of AngI and AngII is necessary for effective angiogenesis, because AngI is known to stabilize newly formed vessels, and AngII antagonizes this effect [34,35,36]. Consequently, increased expression of AngII might prevent the stabilization of newly formed vessels, resulting in pathological angiogenesis. In addition, VEGF family proteins, including PlGF, are known to induce angiogenesis by destabilizing the vessels and reducing endothelial tight junction proteins [37]. Hence, the combined effects of increased PlGF and AngII might induce pathological angiogenesis at this early time point. Decreased basement proteins and endothelial tight junction complexes are considered markers of pathological angiogenesis [38,39]. Here, we showed that some of the newly formed vessels are devoid of basement membrane protein collagen4. Moreover, in a recent report, we have shown that tight junction protein claudin-5 levels are decreased in this AD model mouse at 2 months [40], indicating that here, angiogenesis is a pathological type. Although the cause of decreased tight junction protein claudin-5 in such pathological conditions could be due to increased PlGF protein, the reduction of collagen4 requires some protease activity. In angiogenesis conditions, proteases, including matrix metalloprotease 9 (MMP9), are considered important [41,42]. MMP9 has been shown to be increased in AD [43]. Such increased MMPs might participate in the angiogenesis process by degrading matrix proteins and tight junction complexes, along with other angiogenesis regulators. It will be interesting to investigate the regulations of protease activities at earlier time points in AD models, along with their relationships with the pathological processes. Several reports of both animal models and human post-mortem studies demonstrated the presence of pathological angiogenesis in AD, which is suggested to be the consequence of impaired cerebral blood flow seen in AD [27,44,45]. The cause of impaired blood flow could be due to Aβ deposition and subsequent pathological changes in cerebral blood vessels [46]. In response, the expression of hypoxia-inducing factor 1α (HIF-1α) and its downstream factors, including VEGF expression, are increased, leading to a pathological angiogenic condition [47]. In our model of AD, we find that Aβ deposition around cerebral vessels is not extensive at 2 months, at which time they mainly showed an intracellular localization in the neuron-like cells. Moreover, HIF-1α protein levels were low at this time point. These results suggest that at an early time point, HIF-1α- and VEGF-dependent angiogenesis might not be important. However, Aβ peptide is known to induce an inflammatory condition, such as the expression of IL-1β, that may induce VEGF expression [48,49]. Since the neuroinflammatory condition is found to increase with time in this mouse model, such neuroinflammation-induced angiogenesis might also be important, and it should be investigated in this model in a time-dependent manner. In vessel analysis experiments, we observed that both the total vessel numbers and the endoglin-positive new vessel numbers were increased in the APP transgenic mice cortex at 2 months of age. However, the difference in endoglin-positive new vessel numbers between APP transgenic mice and their wild-type counterparts was more pronounced than the difference in total vessel numbers. Such differences in total and new vessel numbers might be caused by the simultaneous presence of angiogenesis and vessel degradation signals in this area. The Aβ peptide showed a direct inhibitory effect on endothelial cell proliferation, and it induces apoptosis [15,27,50]. Hence, endothelial cell death by Aβ might have a negative effect on the difference in total vessel numbers between APP transgenic mice and their wild-type counterparts. As a source of PlGF and AngII, we found that neurons can produce both, especially in the cortical areas. PlGF was found to be almost exclusively expressed by neurons, whereas AngII-positive neurons were very few. The morphology of the majority of AngII-positive cells was round-shaped, indicating the microglial type. Although we did not evaluate the involvement of microglia, our in vitro neuronal culture study demonstrated that the Aβ peptide can directly increase the mRNA expression of both PlGF and AngII in the neurons. Previous studies showed that both AngII and PlGF expression can be regulated by NF-κB transcription factors [51,52]. In fact, NOX2-mediated ROS production is important for NF-κB activation and subsequent AngII expression [52]. In neurons, Aβ has the ability to increase NOX2 activity and ROS production [53]. Additionally, ROS can activate NF-κB in neurons [53]. Taken together, it is possible that Aβ-induced ROS production activates NF-κB in neurons, which leads to the induction of PlGF and AngII. PlGF can also be regulated by endoplasmic reticulum (ER) stress and inflammation [54,55]. Aβ can cause ER stress in the neurons and neuroinflammation [56]. Moreover, our immunostaining results showed that intracellular Aβ was oligomerized. Such oligomerized Aβ might regulate the ER stress and neuroinflammation in a way that affects the expression of PlGF. Nevertheless, a detailed study is necessary to understand the exact mechanisms of how Aβ regulates PlGF expression. ## 4.1. Animals and Brain Tissue Preparation In this study, B6.Cg-Zbtb20Tg(PDGFB-APPSwInd)20Lms/2Mmjax mice, commonly known as J20, were used as an AD model. Both J20 and their wild-type littermates were generous gifts from Dr. Makoto Michikawa of Nagoya City University, Japan. This transgenic mouse model expresses human amyloid precursor proteins harboring both the Swedish (K670N/M671L) and the Indiana (V717F) mutations. As a control, a non-transgenic littermate of the same age was used. All animal experimental procedures were approved by the ethical committee of Shimane University, and the animals were handled according to the guidelines of the Animal Institute of Shimane University and the guidelines of the Declaration of Helsinki. Animals were kept under a constant room temperature of 23 ± 2 °C under a 12 h light-dark cycle, with free access to water and normal chow. For immunohistochemical analysis, both J20 transgenic mice and their wild-type littermates at 2 months and 15 months (5 mice in a group) of age were deeply anesthetized with isoflurane and transcardially perfused with normal saline and $4\%$ paraformaldehyde. The brains were extracted, postfixed, and cryoprotected, and 2 mm thick tissue blocks were prepared. ## 4.2. Immunohistochemical Analysis and Quantitation For staining, 8 μm thick tissue slices were sectioned on a cryostat (Leica biosystem, Buffalo Grove, IL, USA). Tissue sections were treated with a blocking solution ($5\%$ normal goat or horse serum, $0.2\%$ Triton X-100 in PBS) for 30 min, followed by incubation in anti-Aβ IgG (6E10, Rabbit, 1:200, Novus, Continental, CO, USA), anti-CD105 IgG (rat, 1:200, BioLegend, San Diego, CA, USA), anti-collagen4 IgG (rabbit, 1:200, Abcam, Cambridge, UK), anti-VEGF IgG (rabbit, 1:200, Santa Cruz, Dallas, TX, USA), anti-HIF-1α IgG (mouse, 1:200, Santa Cruz, CA, USA), anti-PlGF IgG (rabbit, 1:100, ProteinTech, Chicago, IL, USA), anti-APP IgG (rabbit, 1:100, AnaSpec, San Jose, CA, USA), anti-NeuN IgG (mouse, 1:200, Millipore), anti-oligomer IgG (A11, rabbit, 1:50, Invitrogen, Carlsbad CA, USA), or anti-AngII IgG (rabbit, 1:100, Novus) overnight at 4 °C. For the detection of immunoreactive proteins with fluorophores, the tissue sections were treated for 1 h at room temperature with species-specific IgG conjugated with Texas Red or FITC. During light microscopy, the section was treated with species-specific IgG conjugated with biotin (1:100, Vector, Ingold Road, CA, USA) at room temperature for 1 h. Then the tissue was treated with an avidin-biotin-peroxidase complex (ABC, Vector, Burlingame, CA, USA) for 30 min at room temperature. The immune reaction products were visualized with 3, 30-diaminobenzidine (DAB, Sigma, St. Louis, MO, USA) and counterstained with hematoxylin. Stained sections were examined under a fluorescent microscope (NIKON, ECLIPSE E600). Two tissue sections about 1 mm apart, starting from −1.54 mm from bregma to −2.7 mm, were used for the quantification of immunoreactive areas in the hippocampus. For the frontal cortex, two tissue sections of about 1 mm apart, starting from +0.5 mm to −0.5 mm from bregma, were used. Photomicrographs were taken at ×400 magnifications in five random microscopic fields of the designated areas. The immunoreactive areas were evaluated using ImageJ and expressed as a percent of the total area of the field. When immune reactions were detected by DAB, the IHC profiler Plugins of ImageJ were used for the quantification of the areas. ## 4.3. Solanum Tuberosum Lectin (STL) Staining To identify vessels in the brain tissues, FITC-conjugated STL was used. After a brief wash with PBS, an 8 μm thick brain tissue section was incubated with STL (1:200, Vector) for 1 h. The tissue was washed 3 times for 5 min with PBS, mounted with a water-based mount medium, and examined under a fluorescent microscope (NIKON, ECLIPSE E600). Photomicrographs were taken at ×400 magnifications in five random microscopic fields of the designated areas, and the vessels were counted using ImageJ. ## 4.4. Cell Culture A neural stem cell (NSC) line (NMW7) was generated from a mouse fetal brain, as described previously [57]. The cells were cultured with medium containing high glucose DMEM (Wako Pure Chemicals, Richmond, VA, USA): F12 ham (Wako) 1:1, bFGF (PeproTech, Rocky Hill, NJ, USA), 20 ng/mL, EGF (peproTech), 20 ng/mL, N2 supplement (ThermoFisher, Waltham, MA, USA), and $2\%$ FBS (Gibco, Invitrogen) in an attached culture condition. The NSC was sub-cultured every 48 h. During stimulation, high glucose DMEM medium containing $0.2\%$ FBS, with or without indicated concentrations of Aβ1–42 (Peptide Institute, Osaka, Japan), was used. Aβ1–42 was added to the culture as a monomer, and the stimulations were continued for the indicated times. ## 4.5. Total RNA Isolation, Reverse Transcription, and Quantitative Real-Time PCR Total RNA was isolated from cultured cells after appropriate treatment, or from the cortical or hippocampal tissues of the mice using Trizol reagent (Invitrogen), according to the manufacturer’s instructions. To prepare the first strand cDNA, 2 μg of total RNA was reverse transcribed with reverse transcriptase enzyme (RiverTraAce, Toyobo, Osaka, Japan) in a 20 μL reaction mixture. To analyze mRNA levels, real-time PCR was performed with a SyBr green PCR system (Applied Biosystem, Warrington, UK) and appropriate gene-specific primers using an ABI Prism 7800 Sequence Detector system (Applied Biosystems). The mRNA level was normalized by corresponding GAPDH mRNA and quantified using the relative quantification method. ## 4.6. Immunocytochemistry For immunocytochemistry, NMW7 cells were cultured in the wells of 8-well chamber slides. After appropriate treatment, the cells were fixed with $4\%$ paraformaldehyde in PBS for 10 min. Cells were incubated in a blocking solution ($5\%$ normal goat serum, $0.5\%$ TritonX100 in PBS) for 30 min and then incubated with anti-AngII IgG (Novus) overnight at 4 °C. The cells were treated with goat anti-rabbit IgG conjugated with biotin (1:100, Vector) at room temperature for 1 h. Then, the tissue was treated with an avidin-biotin-peroxidase complex (ABC, Vector) for 30 min at room temperature. The immune reaction products were visualized with 3, 30-diaminobenzidine (DAB, Sigma, St. Louis, MO, USA) and counterstained with hematoxylin. For fluorescent microscopy, the immunoreactive protein was detected using FITC-conjugated goat anti-rabbit IgG (1:100, Santa Cruz), and the fluorescence signals were examined under a fluorescent microscope (NIKON, ECLIPSE E600). Nuclei were identified with Hoechst. The fluorescent intensities were quantified using ImageJ. ## 4.7. Statistical Analysis All numerical data are presented here as average ± standard deviation (SD). The statistical analysis to evaluate the differences between the two groups was performed using T TEST (Microsoft Excel). ## 5. 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--- title: Characterization of Different Types of Epiretinal Proliferations by Synchrotron Radiation-Based Fourier Transform Infrared Micro-Spectroscopy authors: - Sofija Andjelic - Martin Kreuzer - Marko Hawlina - Xhevat Lumi journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003457 doi: 10.3390/ijms24054834 license: CC BY 4.0 --- # Characterization of Different Types of Epiretinal Proliferations by Synchrotron Radiation-Based Fourier Transform Infrared Micro-Spectroscopy ## Abstract Pathological tissue on the surface of the retina that can be of different etiology and pathogenesis can cause changes in the retina that have a direct consequence on vision. Tissues of different etiology and pathogenesis have different morphological structures and also different macromolecule compositions usually characteristic of specific diseases. In this study, we evaluated and compared biochemical differences among samples of three different types of epiretinal proliferations: idiopathic epiretinal membrane (ERMi), membranes in proliferative vitreoretinopathy (PVRm), and proliferative diabetic retinopathy (PDRm). The membranes were analyzed by using synchrotron radiation-based Fourier transform infrared micro-spectroscopy (SR-FTIR). We used the SR-FTIR micro-spectroscopy setup, where measurements were set to achieve a high resolution that was capable of showing clear biochemical spectra in biological tissue. We were able to identify differences between PVRm, PDRm, and ERMi in protein and lipid structure; collagen content and collagen maturity; differences in proteoglycan presence; protein phosphorylation; and DNA expression. Collagen showed the strongest expression in PDRm, lower expression in ERMi, and very low expression in PVRm. We also demonstrated the presence of silicone oil (SO) or polydimethylsiloxane in the structure of PVRm after SO endotamponade. This finding suggests that SO, in addition to its many benefits as an important tool in vitreoretinal surgery, could be involved in PVRm formation. ## 1. Introduction The growth of pathological tissue on the surface of the retina can cause changes that have a direct consequence on vision. The etiology and pathogenesis of such changes are diverse. Risk factors and pathophysiological processes involved in the formation of nonvascular idiopathic epiretinal membranes (ERMi), membranes in proliferative vitreoretinopathy (PVRm), and neovascular membranes in proliferative diabetic retinopathy (PDRm) are different in many respects [1]. Vitreoretinal interface disorders are conditions where epiretinal proliferation often occurs. A common occurrence in vitreoretinal interface disorders is an epiretinal membrane (ERM), which is a fibrotic membrane over the retina that contracts, wrinkling the underlying retina. Due to the predilection for central localization on the surface of the macula, in the more severe forms of ERM, the vision is often affected because of the disruption of macular anatomy [2]. ERMs are made by non-angiogenic fibroglial tissue [2]. They are composed of bundles of non-cellular extracellular matrix (ECM) proteins as the outermost layer, which is laid upon the inner limiting membrane, and an inner cellular sheet, which can be either single or multi-layered [3]. The membranes comprise different types of cells like retinal pigment epithelial (RPE) cells, glial cells, hyalocites, fibrocytes, fibrous astrocytes and myofibroblast-like cells [4,5,6,7,8]. ECM made from collagen plays a crucial role in ERM construction as well as in cell proliferation and migration [2]. Another nonvascular formation representing a pathological condition of the retina is PVR [9], which represents a process of the growth of membranes on the inner and outer retinal surface—which gradually turn into scars in patients with rhegmatogenous retinal detachment (RRD). It is the major complication following retinal detachment surgery and is also a leading cause of failure in the management of RRD [10]. Histologically, these membranes are fibrocellular sheets composed of ECM and different types of cells, like RPE cells, glial cells, fibroblasts, myofibroblast-like cells, and ECM [9]. PDR is the advanced stage of the ocular manifestations of diabetes mellitus [11]. The disease is hallmarked by neovascularization as a response to ischemia, which at its latest stage changes to fibrovascular and fibrous proliferations on the surface of the retina, leading to tractional retinal detachment and loss of vision [12]. In contrast to the cellular structure of PDRms that has been widely and evaluated in more detail, the nature of the ECM of these membranes is less investigated. The pathological changes occurring in the retina during diabetes mellitus are not fully understood yet. Despite the fact that the structure of angiogenic and non-angiogenic proliferations on the retina has been precisely analyzed by immunochemical and histochemical methods, so far, there have been very few reports on the analysis of their molecular content and their conformational changes [13]. In this study, we evaluated and compared biochemical differences: protein conformational changes and changes in lipids and carbohydrates among three samples of different types of epiretinal proliferation: ERMi, PVRm and PDRm. To assess bio-macromolecules and to provide their molecular fingerprint for better understanding—among the others—of the ECM proteins in nonvascular and neovascular ocular pathological membranes, we used synchrotron radiation-based Fourier transform infrared (SR-FTIR) micro-spectroscopy. SR-FTIR micro-spectroscopy is a vibrational spectroscopic imaging technique, which has the potential for macromolecule analysis in a single cell, and detects different spectra of proteins [14], lipids [15], carbohydrates, and nucleic acids [16]. Spectral data analysis provides qualitative and quantitative information on the basis of peak shifts, bandwidths, and band intensities. ## 2. Results The spectra of three different types of epiretinal membranes were analyzed for protein, lipid, nucleic acids, and carbohydrate regions. Additionally, we used principal component analysis (PCA) of the FTIR spectra and concentrated on the first two principal components, PC1 and PC2, at each spectral region. ## 2.1. Lipid Region Figure 1A demonstrates FTIR average spectra with standard deviations acquired from the lipid region (2800–3100 cm−1) [17,18]. A PCA of this region is demonstrated in Figure 1, together with the loadings plots (Figure 1B) and the PCA score (Figure 1C). The analysis shows that the PVRm is pronouncedly different from the others, with PC1 showing the strongest difference and biggest expression of the band with a maximum at 2962 cm−1, corresponding to the asymmetric CH3 vibration. On the other hand, in PVRm, there is a lower contribution at 2920 cm−1, corresponding to the asymmetric vibration of CH2, and 2850 cm−1, corresponding to the symmetric vibration of CH2, both being more expressed in ERMi and PDRm. From the spectra, it can be seen that ERMi showed the highest absorbance at 2922 cm−1, corresponding to the presence of asymmetric vibration of CH2 and also at 2851 cm−1, corresponding to symmetric vibration of CH2. In comparison with ERMi, PVRm had fewer contributions of the same wavenumbers, 2922 cm−1 and 2851 cm−1, and corresponding constituents, as visible from the difference in absorbance intensity. PDRm showed maxima at 2956 cm−1 and 2933 cm−1 and smaller ones at 2876 cm−1 and 2851 cm−1, corresponding to the asymmetric vibration of CH3 and CH2 and the symmetric vibration of CH3 and CH2, respectively. ## 2.2. Protein Region The Amide I and Amide II regions, including the ester group (1485–1765 cm−1), are demonstrated in Figure 2 [17,18,19]. We noted the Amide I band maxima at 1650 cm−1 for PVRm, 1653 cm−1 for ERMi, and 1657 cm−1 for PDRm. We also noted differences in the Amide II band positions with maxima at 1543 cm−1 for PVRm, at 1547 cm−1 for ERMi, and at 1553 cm−1 for PDRm. The first component of the PCA (Figure 2B) indicated the contributions of 1666 cm−1 and 1558 cm−1, being the most expressed in PDRm, with the first associated with the turns and loops secondary structure in proteins and the second with the NH bend and C-N stretch of Amide II in proteins. The second component of the PCA (Figure 2B) showed contributions of the bands at 1520 cm−1 and 1650 cm−1, with the first being associated with tyrosine proteins and the second with the α-helix structure, being more expressed in PVRm and ERMi than in PDRm. ## 2.3. Protein Region Band Deconvolution With the aim of analyzing the discovered changes in the secondary protein structure in ERMi, PVRm, and PDRm more thoroughly, the Amide I and II bands have been deconvoluted using 12 Gaussian functions. The Gaussian curves’ maxima positions have been approximated in accordance with the article by Kreuzer et al., 2020 [19]. Figure 3A reveals the deconvolution of a single spectrum as an example. The allocation of the identified bands within the Amide I band (1600–1700 cm−1) was performed utilizing formerly described spectral components connected with different secondary protein structures [19,20,21]. The bands correlating with the region 1605–1620 cm−1 are assigned to side chains; 1620–1630 cm−1 to cross β-sheets; 1630–1637 cm−1 to parallel β-sheets; 1638–1646 cm−1 to unordered structures; 1647–1662 cm−1 to α-helices; 1662–1678 cm−1 to loops and turns; and 1690–1697 cm−1 to anti-parallel β-sheets. Additionally, the band assigned to the carbonyl group between 1730–1760 cm−1 has also been analyzed. The bands of the Amide II group at 1548 cm−1 and 1515 cm−1 are attributed to α-helices (Figure S1) and Tyrosine (Figure S1), respectively [22]. This analysis was focused on the Amide I band. The areas under all Gaussian peaks have been integrated for each spectrum and shown as box plots for ERMi, PDRm, and PVRm (Figure S1). Additionally, the box plot for α-helix is shown in Figure 3B. Interestingly, α-helix showed the highest expression in ERMi and the lowest expression in PVRm. Regarding Amide I, the deconvolution showed that the difference between ERMi, PDRm, and PVRm is the most noticeable for the turns and loops secondary structure with the peak maximum at 1666 cm−1 being the most expressed in PDRm and the less expressed in PVRm (Figure S1). PVRm also had the lowest expression of α-helices in Amide II (Figure S1), β-sheet (Figure S1) and oligomers (Figure S1). The analysis further confirmed that in PDRm, there is the lowest presence of Tyr (Figure S1) and side chain as Tyr, Glu, and Asp residues (Figure S1), which showed the biggest expression in PVRm. In PDRm, there is also the lowest presence of side chains such as Tyr and Asn (Figure S1), turns and loops with the peak maximum at 1681 cm−1 (Figure S1), and a carbonyl group (Figure S1), which showed the biggest expression in ERMi. In ERMi, there is also the biggest expression of α-helices in Amide II (Figure S1). ## 2.4. Nucleic Acids and Carbohydrates Regions The wavenumber region between 950 and 1485 cm−1 corresponds to the nucleic acids and carbohydrates (Figure 4A) [17,18]. Besides the common bands of biological samples, the spectra of PVRm show a very pronounced peak with a maximum of 1261 cm−1. This peak is connected to the CH3 symmetric deformation of polydimethylsiloxane (PDMS) [23]. In addition, PDMS demonstrates two strong bands at 1090 cm−1 and 1022 cm−1, corresponding to Si–O–Si stretching vibrations. The peak at 1033 cm−1, associated with the sugar rings in carbohydrate residues in collagen and proteoglycans [24], shows a stronger expression in ERMi and a weaker expression in PDRm. The scores plot demonstrates that the groups strongly separate along PC1 (Figure 4C). The PC1 loadings have contributions at 1237 cm−1 (maximum), 1454 cm−1 (maximum), 1261 cm−1 (minimum), and 1098 cm−1 (minimum) (Figure 4B). The first maximum corresponds to PO2- asymmetric stretch in deoxyribonucleic acid (DNA) and the second to the CH2, CH3 deformation modes in proteins. They are more expressed in PDRm than in ERMi, with very low expression in PVRm. The minima correspond to PDMS and are strongly expressed in PVRm. ## 2.5. Additional Protein Analysis The peak at 1338 cm−1 corresponds to the amount of collagen present [25,26,27]. The intensities have been compared after a baseline correction of the single peak has been performed, according to Liu et al., 2006 [26]. The peak is the highest for PDRm (Figure 5A). We also analyzed the ratio of the areas for $\frac{1660}{1690}$ cm−1 that corresponds to the degree of collagen maturity [24]. The ratio is the highest for PDRm and the lowest for PVRm (Figure 5B). The band ratio inspecting the spectral changes in the protein regions 1654 cm−$\frac{1}{1554}$ cm−1 has also been analyzed. The absorbance peak at 1654 cm−1 corresponds to the protein C=O stretching of the structural protein (Amide I), while 1554 cm−1 corresponds to the N-H bending and C-N stretching of the polypeptides and protein background (Amide II) [28]. ERMi has the highest ratio, and PVRm has the lowest (Figure 5C). ## 3. Discussion Chemical alterations precede and/or accompany morphological changes that are symptomatic of disease [29]. FTIR is a method that enables the analysis of the biochemical status and differences in the molecular composition of tissue, cells, and ECM. We were interested in finding the possible differences between three different types of pathological tissue on the surface of the retina: ERMi, PVRm, and PDRm. Here, we did a pilot study in evaluating bio-macromolecules and detecting and assigning the proteins’ conformational changes, and also changes in collagens, lipids, carbohydrates, and nucleic acids in the three samples. It was recently indicated that FTIR is a helpful analytical technique for the analysis of ERMs and that it allows the analysis of the spatial distribution of protein secondary structures in the ERMs [13]. Unlike the mentioned study, we utilized SR-FTIR with high spatial resolution. SR-FTIR micro-spectroscopy is also a powerful method for a fast and thorough chemical structural characterization of collagen characteristics from various origins, including different natural and synthetic collagens [30]. Biochemical differences connected with lipid metabolism can be recognized by the investigation of the high-wavenumber region, with the bands that are associated with the asymmetric (νas) and symmetric (νs) methyl (CH3) and methylene (CH2) groups’ stretching vibrations detected at ~2960 [νas(CH3)], 2923 [νas(CH2)], 2873 [νs(CH3)], and 2850 cm−1 [νs(CH2)] [17]. We discovered that the asymmetric and symmetric CH2 vibrations are more expressed in ERMi. PDRm showed the strongest contribution in the asymmetric CH3 vibration. The CH2 bands are mostly because of the saturated chains in lipids, whereas the CH3 bands are because of the vibrations of the methyl groups in proteins, lipids, and nucleic acids [17]. A high lipid concentration arrives from plasma membranes and microsomal pellets such as endosomes and secretory vesicles, whilst just a low lipid concentration arrives from the cytoplasm [17]. The vibration of CH2 was the most expressed in ERMi, suggesting a higher lipid concentration, and it shifted toward higher wavelengths for PDRm. The CH2 groups’ symmetric stretching mode location can be a pointer to the lipid-membrane’s order and disorder that is influenced by the content, composition, and hydration of membrane proteins [31]. In such instances, a helpful parameter can be the shift in the CH2 stretching vibration’s wavenumber, being the case for PDRm that point to alterations in acyl chain flexibility [32]. The shifting towards lower frequencies can also point to an augmentation in the number of trans isomers of lipids or a different lipid milieu that can be associated with an augmentation in lipid order and chain rigidity [33]. The lipid region of the PVRm spectra was pronouncedly different from the other epiretinal proliferations with the biggest expression at 2962 cm−1 [νas(CH3)], asymmetric CH3 vibration. The appearance of the PVRm spectrum was surprisingly very much like a combination of polydimethylsiloxane (PDMS) [23] with common biological tissue. PDMS, also known as dimethylpolysiloxane, is one of several types of polymerized siloxanes or silicone oil (SO), which has wide applications in industry, medicine, and cosmetics. SOs for ophthalmic use, also named organosiloxane, are synthetic polymers composed of PDMS with different chain lengths [34]. They are constituted of silicon–oxygen bonds and have hydrocarbon radicals as radical side groups [35]. The purpose of the use of SO in vitreoretinal surgery is to serve as either a short-term or long-term endo-tamponade of the retina in complicated vitreoretinal diseases, such are complex retinal detachments and PDR [34,35]. In our case with retinal detachment and PVR, SO was also used as an intraocular tamponade implant. Despite the advantages and the fact that SO has been in use in ophthalmology for half a century, there have been constant concerns about the complications that arise when using it. Most of the complications are related to the tendency of SOs to emulsify [35]. The emulsified droplets have the potential to move to different intraocular structures. These emulsified particles have been shown to stimulate macrophages and other proliferating cells within proliferative ERMs, leading to their impregnation and vacuolization [36,37]. The process of formation and the confluence of intracytoplasmic vacuoles is believed to occur by the mechanism of endocytosis of SO droplets, mainly by macrophages and cells of glial origin [37]. A very dissimilar appearance of proliferating cells in PVR membranes on transmission electron microscopy with membrane-bound vacuoles has been described by different authors earlier [36,37,38,39,40]. Although the presence of emulsified SO in intracytoplasmic cell vacuoles in PVR membranes has not been directly proven, it was predicted on the basis of indirect facts [37]. We believe that the results of our analysis, for the first time, demonstrate the presence of SO or PDMS in the structure of a PVR membrane, which confirms previous assumptions that cells in PVRm formed in patients with RRD and tamponade with SO are vacuolated and that vacuoles are filled with SO. However, the results have to be verified by increasing the study group and probing a larger number of PVRm samples. The impact of PDMS must be taken into consideration when interpreting the different wavenumber regions of the PVRm spectra. Although PVRm spectra show the contribution of the PDMS, PVRm spectra differ from the PDMS spectra in the region from 1300 cm−1 to 1700 cm−1 [23], which hence belongs to the membrane itself. Therefore, in the Amide I and Amide II regions, there is the contribution mostly from the biological tissue as part of the PVRm. As a result of the high impact of PDMS in the spectra of PVRm, it was possible to compare three types of membranes only for the Amide region but not for the lipids, oxidative stress, and carbohydrate regions. Our results show that the Amide I band maxima were found at 1650 cm−1, 1653 cm−1, and 1657 cm−1, and Amide II bands maxima at 1543 cm−1, 1547 cm−1, and 1553 cm−1 for PVRm, ERMi, and PDRm, respectively, indicating differences in the secondary structure content of all three membrane types (Figure 2A). The band deconvolution showed the presence and the individual contributions of the α-helix (1658 cm−1) for the different membranes (Figure 3B). A characteristic of the connective tissue is the absorbance triad in the region of the Amide III vibrations, i.e., 1206 cm−1, 1238 cm−1, and 1280 cm−1 coming mostly from collagen [17]. Our results, based on the bands at 1204 cm−1 (Figure 4A) and 1338 cm−1 (Figure 5A), suggest the strongest collagen deposition in PDRm, less in ERMi, and absent in PVRm. Ratiometric analysis on the spectra for each type of membrane was performed for the collagen maturity (1660 cm−$\frac{1}{1690}$ cm−1) [24] (Figure 5B) and protein conformation (1654 cm−$\frac{1}{1554}$ cm−1) [28] (Figure 5C). Differences in the protein conformations—calculated by utilizing the ratio of the protein C= O stretching of the structural protein (Amide I) to the N-H bending and C-N stretching of the polypeptides and protein background (Amide II)—may correlate with the alterations in the structural reorganization of present proteins or the new proteins’ expression with various structural properties. These alterations are believed to be because of the deposition of ECM proteins like collagen, fibronectin, and laminin in the course of fibrosis development [28]. The upregulated ECM collagen-like proteins in ERM and PDR were demonstrated in the study by George et al. [ 1]. Using the ratio 1654 cm−$\frac{1}{1554}$ cm−1, we found the strongest changes in protein conformations in ERMi, smaller in PDRm and the smallest in PVRm (Figure 5C). We showed that the PDRm contained more β sheets than ERMi, suggesting the higher content of type IV collagen in PDRm (Figure S1). Elevated levels of collagen type IV in PDR membranes have been previously demonstrated by immunohistochemical analysis together with its upregulation by molecular methods [1,9]. The existence of collagen types I, type IV, entactin, and fibronectin in ERMi has been demonstrated by Altera et al., with immunofluorescence and confocal microscopy [41]. The band at 1033 cm−1 is allocated to the sugar rings in carbohydrate residues in collagen and proteoglycans [24]. We found its stronger presence in ERMi and weaker presence in PDRm (Figure 4A). It has been shown that growth in the intensity of the bands at 1080 cm−1 and between 990 cm−1 and 970 cm−1 mirrors continually raised the phosphorylation of proteins [17]. We found it at a higher level also in ERMi and less in PDRm (Figure 4A). Therefore, glycoprotein- and collagen-associated carbohydrate moieties were present in ERMi and less in PDRm (Figure 4). Even though the collagens’ and cells’ FTIR spectra are thought to be highly analogous, the existence of different types and configurations of proteins in cells, as well as other types of macromolecules, may alter the positions and shapes of the Amide bands [42]. The band at 1454 cm−1 is assigned to the CH2 and CH3 deformation modes and asymmetric methyl deformation, represented in proteins [43]. We found the higher expression in PDRm, lower in ERMi, and the lowest for PVRm (Figure 5A). The PO2- asymmetric stretch at 1237 cm−1, which represents DNA [44], showed the highest expression in PDRm, lower in ERMi, and it was absent in PVRm (Figure 4A), suggesting possible higher cell content in PDRm. This study has some limitations. The main limitation is the small number of samples. However, although we have analyzed a small number of samples, the differences between them are very pronounced and specific to each type of membrane, which is a novelty and a good basis for further investigations. Another limitation is that three different membranes taken from the eye were all stored in PFA. Nevertheless, the differences among them were clear and could be compared regardless of the PFA treatment. The tissue preparation methods’ importance for biological tissues’ FTIR micro-spectroscopical analysis is discussed in Zohdi et al., 2015 [45]. Two characteristic bands of collagen at 1205 cm−1 and 1285 cm−1 were noticeable in the wet hearts’ tissue spectra but were only weakly revealed in the formalin-fixed and ethanol-dehydrated tissue spectra and were lacking from the desiccated sample spectra [45]. In our spectra, the shoulders for 1205 cm−1 and 1285 cm−1 were observed for PDRm and with smaller intensity for ERMi but not for PVRm (Figure 4A). ## 4.1. Sample Preparation The membranes were collected from routine pars plana vitrectomy performed at the Eye Hospital, University Medical Centre, Ljubljana, Slovenia. The sample collection complied with the tenets of the Helsinki Declaration. Informed consent was provided before surgery for each patient. In the case of a 75-year-old female with ERMi, the surgery was indicated due to deterioration of visual acuity and metamorphopsia. The membrane was obtained during uneventful surgery. The epiretinal tissue was peeled off by using microforceps. PDRm was obtained from a 65-year-old male with PDR undergoing vitrectomy due to vitreous hemorrhage and tractional retinal detachment. PVRm was obtained from a 63-year-old male after surgery with 2000 centistoke silicone oil (SO) endotamponade due to RRD and PVR stage C6. SO was removed 6 months after surgery. During the same procedure, PVRm was peeled off using microforceps. The removed tissue was, in all cases, immediately stored in paraformaldehyde (PFA). Each membrane was washed after collection in a high-glucose medium (DMEM; Sigma, no. 5671, St. Louis, MO, USA) supplemented with $10\%$ fetal bovine serum (FBS) and $1\%$ antibiotics (penicillin–streptomycin; Sigma, no. 4333). ERMs were then prepared for FTIR micro-spectroscopy studies: firstly, being rinsed in 5 mL NaCl for 10 min and then, by using microdissecting tweezers (WPI by Dumont, Med. Biologie, Germany), were placed by gently stretching and plating adherently on circular 13 mm × 0.5 mm calcium fluoride, CaF2 slides (Crystan Ltd., Dorset, UK). After this, the samples were dried under sterile conditions in the laminar flow at room temperature and then stored with silica gel until the measurements at the ALBA synchrotron. ## 4.2. Synchrotron Radiation-Based FTIR Micro-Spectroscopy For the purpose of assessing the organic compounds’ profiles, we carried out measurements at the infrared micro-spectroscopy beamline MIRAS at the ALBA synchrotron light source (Barcelona, Spain) [46] using SR-FTIR micro-spectroscopy. Conventional FTIR spectroscopy is a helpful tool for investigating larger cell populations in the tissues. However, the restricted standard infrared light sources’ brightness generally prevents measurements with high spatial (single-cell) resolution in comparison with SR-FTIR micro-spectroscopy [18]. All SR-FTIR micro-spectroscopic absorption spectra were collected in transmission mode using the infrared microscope Hyperion 3000 coupled to a Vertex 70 spectrometer (Bruker, Germany), equipped with a liquid nitrogen-cooled mercury cadmium telluride detector and the mid-infrared region of the synchrotron light as the infrared light source. Each spectrum was acquired after co-adding 128 scans at a spectral resolution of 4 cm−1. OPUS Version 8.2 (Bruker, Germany) software package was used for data collection. For the purpose of achieving the single-cell data acquisition and analysis, we obtained the spectra of 10 × 10 µm2 areas of the tissue by using the microscope’s aperture and the highly focused synchrotron source’s infrared light. Visible images of the postoperative tissue of ERMi, PVRm, and PDRm were obtained in reflection geometry (Figure 6A–C) and transmission geometry (Figure 6D–F), the latter also showing the measured points. Spectra with infrared absorbance higher than 2, at the wavenumbers 1650 cm−1 and 1020 cm−1, were not considered in the analysis. In total, 129 measured individual areas/spectra were analyzed: 67, 44, and 18 individual areas/spectra from the measured (71, 63 and 71) individual areas/spectra from the ERMi, PVRm and PDRm, respectively. The spectral analysis was concentrated on three regions of the spectra: (950–1485 cm−1), i.e., nucleic acids and carbohydrates, and Amide I and II (1485–1760 cm−1), i.e., proteins and lipids (2800–3100 cm−1). In the regions of interest, spectra were baseline-corrected, and unit vectors were normalized. Quasar 1.3.0 software package (Bioinformatics Laboratory of the University of Ljubljana, Version 3.20.1) with the spectroscopy package [47] was used for data correction and further analysis. Principal component analysis (PCA) was used for the data sets’ comparison and concentrated on the first two principal components. In addition, Amide I and II bands and carbonyl region (1480–1800 cm−1) were deconvoluted for each spectrum by using Quasar 1.3.0. with the spectroscopy add-on Peak Fit. The region was fitted using 12 Gaussian functions for each spectrum. The center Gaussians’ positions have been approximated from the article by Kreuzer et al., 2020, while 1580 cm−1 was included to get a better baseline [19]. The center positions were fixed. For all Gaussians regarding Amide I, the full wideness at half maximum was set fixed to 30 cm−1 (σ = 12.77 cm−1). The resulting areas underlying the Gaussian bands were calculated for each spectrum and plotted in boxplots. Values are shown with the data’s probability density and mean +/− SD. ## 5. Conclusions We have already used SR-FTIR to study the lens epithelial cells’ macromolecular compounds in human cortical and nuclear types of cataracts [19] as well as the UV effect on human anterior lens capsule macro-molecular composition [48]. The present results give further evidence that SR-FTIR is sensitive to the pathologic processes of epiretinal proliferations. Each of the studied samples showed a different spectral profile, which suggests a different macro-molecular composition of three different types of epiretinal proliferation originating from different constituents and metabolic processes is taking place. PVRm differs the most from ERMi and PDRm in all spectral regions. Further studies on a larger number of samples and also samples in different stages of evolution are needed. With this work, we hope to stimulate further investigations. Different ultrastructural studies have shown the complex molecular structure of epiretinal proliferations. The presence of a variety of cells and ECM composed of proteoglycans and fibrous proteins such as collagen, fibronectin, elastin, and laminin has been demonstrated in previous reports. 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--- title: Genetic Risk Assessment of Nonsyndromic Cleft Lip with or without Cleft Palate by Linking Genetic Networks and Deep Learning Models authors: - Geon Kang - Seung-Hak Baek - Young Ho Kim - Dong-Hyun Kim - Ji Wan Park journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003462 doi: 10.3390/ijms24054557 license: CC BY 4.0 --- # Genetic Risk Assessment of Nonsyndromic Cleft Lip with or without Cleft Palate by Linking Genetic Networks and Deep Learning Models ## Abstract Recent deep learning algorithms have further improved risk classification capabilities. However, an appropriate feature selection method is required to overcome dimensionality issues in population-based genetic studies. In this Korean case–control study of nonsyndromic cleft lip with or without cleft palate (NSCL/P), we compared the predictive performance of models that were developed by using the genetic-algorithm-optimized neural networks ensemble (GANNE) technique with those models that were generated by eight conventional risk classification methods, including polygenic risk score (PRS), random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and deep-learning-based artificial neural network (ANN). GANNE, which is capable of automatic input SNP selection, exhibited the highest predictive power, especially in the 10-SNP model (AUC of $88.2\%$), thus improving the AUC by $23\%$ and $17\%$ compared to PRS and ANN, respectively. Genes mapped with input SNPs that were selected by using a genetic algorithm (GA) were functionally validated for risks of developing NSCL/P in gene ontology and protein–protein interaction (PPI) network analyses. The IRF6 gene, which is most frequently selected via GA, was also a major hub gene in the PPI network. Genes such as RUNX2, MTHFR, PVRL1, TGFB3, and TBX22 significantly contributed to predicting NSCL/P risk. GANNE is an efficient disease risk classification method using a minimum optimal set of SNPs; however, further validation studies are needed to ensure the clinical utility of the model for predicting NSCL/P risk. ## 1. Introduction Orofacial clefts (OC), which are the second most common congenital anomaly with a wide range of etiologies, can occur as an isolated form or as a syndrome. The prevalence of OC varies by region and ethnicity, with the highest incidence being observed in Asian populations [1]. According to a nationwide cohort study, the overall prevalence of OC in Korea was 1.96 per 1000 live births, and approximately $76.45\%$ of all cases occur in the nonsyndromic form. Specifically, cleft lip only (CL), cleft lip with cleft palate (CLP), and cleft palate only (CP) accounted for $26.47\%$, $26.56\%$, and $52.97\%$ of total cases, respectively [2]. As CP has been considered a distinct malformation, recent genetic studies have primarily focused on nonsyndromic cleft lip with or without cleft palate (NSCL/P), which is known to be more heritable [3]. From the 1990s to the early 2000s, family-based studies have provided evidence that chromosomal regions (such as 2p, 4q, and 6p) and genes (such as COL11A1 and TGFA) are linked with nonsyndromic OCs. However, genetic association studies have shown much greater statistical power in detecting susceptibility genes for complex diseases, and genes involved in craniofacial development, such as IRF6 and MSX1, have been identified to be associated with NSCL/P [4]. Since around 2010, genome-wide association studies (GWASs), which represent a hypothesis-free approach using millions of single nucleotide polymorphism (SNP) markers, have identified novel loci for NSCL/P, such as 8q24, 10q25.3, and 17q22 [5,6,7]. Although previous studies have been primarily conducted in populations with European ancestry, genetic heterogeneity among ethnic groups has become a major concern in identifying susceptibility variants for NSCL/P, as reported in a study of 8q24.21 and a Chinese GWAS [8,9]. With the accumulation of susceptibility SNPs discovered in GWAS, the demand for developing methods for predicting genetic risk is rapidly growing. Polygenic risk scoring (PRS), which is defined as a weighted sum of individual risk alleles, has been widely applied to predict multifactorial disease risk; however, its reliance on an additive model limits its application to elucidate complex interactions among genetic variants [10,11]. Furthermore, machine learning (ML) algorithms have been applied for the risk prediction of complex diseases, due to their strength in identifying patterns and interactions among multiple inputs by employing multivariate, nonparametric methods [12]. Zhang et al. [ 2018] evaluated seven ML techniques, including random forest (RF) and artificial neural network (ANN), by using forty-three NSCL/P-associated SNPs and reported that the logistic regression model had the highest classification performance in Han Chinese (AUC of 0.90) [13]. In a Brazilian study, RF and ANN effectively classified NSCL/P patients and normal subjects with greater than $94\%$ accuracy by using 13 SNPs [14]. The recent advent of deep learning (DL) has further improved the classification capability for a disease by using individual SNP data, as was observed in a case–control study on obesity (AUC of 0.99) [15,16]. DL has been shown to be superior in mapping complex non-linear interactions and for integrating different types of data [17,18]; however, highly complex networks demand a large dataset to ensure sufficient predictive power and generalization of results [19,20,21]. Especially, given the difficulty of obtaining large numbers of human samples in the field of genomic medicine, appropriate feature selection directly affects model performance by reducing the noise and dimensionality of data in both traditional ML- and DL-based risk prediction methods [22,23,24]. *The* genetic algorithm (GA) is a promising method for optimizing feature selection. Tong and Schierz [2011] have successfully applied a hybrid genetic algorithm neural network (GANN) to extract highly informative genes from a microarray-based gene expression dataset [25]. In a separate study, Zhang et al. [ 2015] improved the performance of predicting immunogenic T-cell epitopes from epitope sequences through the use of an ensemble RF model that was trained on individual features selected with GA [26]. To the best of our knowledge, this study represents the first application of the GANNE approach to disease risk assessment and the first genetic risk prediction study for NSCL/P in the Korean population. Herein, we first performed a genetic association analysis by using 92 SNPs that were genotyped in 143 Korean children with NSCL/P and 119 healthy controls. We subsequently compared the predictive performance of the PRS and various ML methods. To improve predictive power, we proposed the use of a deep learning model that uses automatic feature selection for NSCL/P classification; specifically, we used the genetic-algorithm-optimized neural networks ensemble (GANNE). Finally, we functionally validated the genes selected by GANNE using pathway and network analyses. ## 2.1. Genetic Association Analysis for NSCL/P Four SNPs (rs10790330, rs906830, rs17104928, and rs3917211) demonstrated HWE p-values less than 0.05; however, none of the SNPs showed evidence of deviation from HWE ($p \leq 0.01$) in the control data, and the MAFs of all ninety-two SNPs were >$1\%$ in both the case and control groups. In the Fisher’s exact test, two intronic SNPs of IRF6 in linkage disequilibrium (LD) with a r2 value of 0.80 (rs2235373 and rs2235371) were found to be significantly associated with NSCL/P ($$p \leq 3.5$$ × 10−4 and $$p \leq 4.5$$ × 10−4, respectively). Moreover, SNPs located near or within five other genes (RUNX2, ARNT, TGFB3, MTHFR, and TCOF1) also showed significant associations in Korean NSCL/P patients ($p \leq 0.05$) (Table 1). After accounting for pairwise LD (r2 < 0.8, see Table S1), we identified three SNPs that were associated with NSCL/P at the level of $p \leq 0.01$, as well as ten SNPs with nominal significance ($p \leq 0.05$) and sixteen SNPs with marginal significance ($p \leq 0.1$). ## 2.2. Genetic Risk Prediction The predictive performance of the PRS models for NSCL/P risk increased as the number of SNPs increased (accuracy = 0.676 and AUC = 0.711 for the 92-SNP model). When evaluating the models generated by the six traditional machine learning algorithms, the training accuracies significantly improved to above $95\%$ for the 10-SNP model, especially for four of the ML algorithms. However, the testing accuracies remained in the $60\%$ range. Out of the 18 models categorized by the number of SNPs and the type of machine learning algorithm, the SVM utilizing 10 SNPs demonstrated the highest predictive performance (test accuracy = 0.677, F1 = 0.678, AUC = 0.685). On the other hand, LightGBM demonstrated the lowest predictive performance among the machine learning algorithms (test accuracy = 0.565, F1 = 0.566, AUC = 0.568). We trained the four sets of SNPs by using the ANN deep learning algorithm but did not observe a significant improvement in predictive performance compared to PRS and the machine learning models (test accuracy = 0.63, F1 = 0.65, AUC = 0.71) (Figure 1). In the current study, we developed a model to improve NSCL/P classification by using the GANNE algorithm. We first prepared a set consisting of the top SNPs that were identified in the genetic association analysis, along with five optimal sets of SNPs that were selected by using GA, to be used as inputs for ANN deep learning. GANNE significantly improved predictive performance across all three SNP settings, especially the best model selected from six sets of ten SNPs (AUC of $88.2\%$), which increased AUC (∆AUC) by $17\%$, $23\%$, and $28.5\%$, respectively, compared to ANN, PRS, and RF (Figure 1). Despite the lower weighted F1-score of 0.76 compared to AUC, the 10-SNP GANNE model still demonstrated superior performance when accounting for class imbalance in the binary data. In addition, the test accuracy of the 10-SNP GANNE ($74.2\%$) increased within the range of $6.5\%$ (SVM) to $14.5\%$ (RF) compared to other methods, and it increased by $11.3\%$ compared to the deep-learning-based ANNs. GANNE models with three SNPs and sixteen SNPs exhibited similar test results (accuracy = 0.694, F1 = 0.709, AUC of approximately 0.744), but the 16-SNP GANNE demonstrated better training accuracy than the 3-SNP GANNE (Figure 1, Table 2). The GANNE utilized 46, 25, and 15 different SNPs that were located in 14, 12, and 8 genes, respectively, at least once for the 3-, 10-, and 16-SNP models. Five SNPs from IRF6 (including rs2013162), rs11204737 (ARNT), rs7715100 (TCOF1), rs16873348 (RUNX2), and rs3917192 (TGFB3) were used in all three SNP models. Among the SNPs that were selected for the 10-SNP GANNE models, rs2013162 (IRF6) was the most potent SNP included in all six sets, followed by rs3917192 (TGFB3) in five sets (Table S2). To verify the reproducibility of the deep learning models, we performed 100 iterations, and the average of the results in each iteration followed the trend of the best model results for each set of SNPs. As expected, the 10-SNP GANNE model produced the highest accuracy and AUC, even at 100 iterations (average training accuracy = $92.1\%$, average test accuracy = $65.4\%$, average test AUC = $75.2\%$), with the highest AUC of $89.5\%$ (Table 2). ## 2.3. In Silico Functional Analysis By using DAVID, we identified a total of 52 GO terms that were significantly associated with 12 genes harboring 25 SNPs used at least once in the 10-SNP GANNE ($p \leq 0.05$ and FDR < 0.1). In particular, the most enriched GO term (GO:0009888~tissue development) was associated with the following nine genes: IRF6, RUNX2, TBX22, MTHFR, PVRL1, PAX9, TGFB3, TCOF1, and VAX1. In addition, four genes (RUNX2, PVRL1, PAX9, and TGFB3) showed significant enrichment in GO:0042476~odontogenesis. In the PPI network analysis, nine of the twenty candidate genes that were evaluated in this study showed multiple interactions with other genes based on experimental evidence of co-expression. In particular, MSX1 and IRF6 were the most important hubs in this network, and genes such as PAX9, TBX22, RUNX2, TGFB3, and VAX1 also appeared to interact with more than one gene. However, eight genes (TCOF1, NSF, ADH1C, RARA, WNT3, ARNT, ZNF385B, and BCL3) did not show an interaction at a confidence score of 0.45 (Figure 2). ## 3. Discussion As the discovery of genetic variants associated with complex diseases increases, the demand for personalized health care services using genetic information is also rapidly increasing. To overcome the limitations of regression-based PRS and conventional ML algorithms, artificial intelligence (AI) has recently begun to be applied to risk prediction and the early diagnosis of complex diseases [11]. Unlike traditional machine learning algorithms, deep learning is helpful in solving complex problems with far more parameters but requires a large-scale dataset to avoid overfitting and to generalize results [27]. Therefore, state-of-the-art deep learning algorithms are not widely applied in genomic medicine due to the difficulty of large-scale sample collection. In the current study, we improved the classification ability for NSCL/P in Korean individuals by performing a deep-learning-based ANN with informative SNPs selected via GA to reduce dimensionality while also increasing test accuracy. GANNE performed best for all three SNP settings compared to the eight conventional methods for risk prediction. In conjunction with the results of the in silico functional analysis, we also demonstrated the possibility of explaining interactions among genetic features, which have been considered a black box in ML applications. The machine learning algorithms, including GANNE, showed the highest classification accuracy when using 10 SNPs but the performance declined as the number of input SNPs increased. On the other hand, PRS, a widely used method in predicting complex disease risk, exhibited a consistent improvement in its AUC with the addition of more SNPs. Despite the simplicity in implementation, logistic-regression-based methods, such as LR and PRS, may not be effective in dealing with non-linear or highly correlated input data [10]. Our findings underscore the issue of dimensionality, whereby the number of required datasets increases exponentially as the input dimensionality increases when using ML algorithms as genetic risk predictors [24]. Supervised machine learning algorithms, RF and SVM, tend to perform well in high-dimensional data, but are prone to overfitting and are computationally intensive [12]. In this study, we found SVM to be more suitable for the non-linear binary classification task, as it showed better predictive performance (F1 = 0.678) compared to RF (F1 = 0.598). Boosting algorithms, including XGBoost, Adaboost, and LightGBM, are ensemble techniques that combine multiple models with weak predictive performance to form a more potent model [28]. Among the nine classification methods used in this study, LightGBM exhibited the lowest predictive performance. Further studies are necessary to investigate the impact of the strengths and limitations of each ML algorithm on disease risk prediction accuracy. There have been attempts to improve predictive accuracy by combining results from different SNP models, but most statistical association analyses have limitations in selecting different subsets of SNPs [29]. Although there are 7 trillion possibilities to select a set of 10 SNPs out of 92 SNPs in our dataset, GANNE can efficiently select an optimal set of SNPs by initializing the first population with the best SNPs that were identified in the association analysis. In particular, the 10-SNP GANNE model showed excellent performance and improved the AUC by $28.6\%$, $23\%$, and $17\%$ compared to the RF, PRS, and ANN methods, respectively, by including SNPs that did not show a strong association with NSCL/P, which was likely due to a lack of statistical power. GA selected the SNPs that were significantly associated with NSCL/P while also extracting SNPs (such as rs7103685 in the PVRL1 gene) that did not show significant associations but that were used in four of the six SNP sets ($$p \leq 0.46$$). Although a further evaluation of gene–gene interactions by using PLINK did not yield statistical significance, a functional protein association network analysis suggests that GA considers functional interactions of genes in SNP selection. The IRF6 gene that was most frequently selected by GA was also a major hub gene in the PPI network, and its association with NSCL/P has been reported in previous studies [30]. However, MSX1, which is another hub gene in the PPI network, was selected by GA in the 16-SNP subset but not in the 10-SNP subset. Moreover, all three SNP markers for the MSX1 gene were not statistically significant in this case–control analysis, but its association with NSCL/P remains controversial with inconsistent results, especially in Asian studies [31,32,33]. GANNE has demonstrated the potential to identify significant interactions among genes when used in conjunction with the PPI network analysis. Due to the fact that there may be valid interactions between SNPs that cannot be detected by using statistical analysis, neural-network-based genetic interaction studies using tools such as class activation mapping or attention modules may be needed in the future [34]. In this study, we demonstrated that GANNE, which is an ensemble neural network with automated feature selection, outperforms existing methods in predicting NSCL/P risk with genotype data by reducing the input dimension of each network through the use of a GA. Although GANNE achieves better generalization and robustness than other classification methods, given the number of samples that were trained in this study, further studies with larger samples are needed to validate the accuracy of the model. *In* genetic association studies, adjustments for age as a potential confounder are usually unnecessary, as differences in age between cases and controls may be associated with disease outcome but unlikely with genotype [35]. ## 4.1. Study Subjects We evaluated 143 Korean NSCL/P patients (91 males and 52 females) from 258 Korean families with nonsyndromic OC who visited Seoul National University Dental Hospital and SAMSUNG Medical Center. At each hospital, an orthodontist diagnosed the types of NSCL/P in the cases (nine cases with cleft lip only, twenty-six cases with cleft lip and alveolus, and one hundred and eight cases with cleft lip and palate). As a control group, we selected 119 healthy Korean adults without OC (60 males and 59 females) from a community-based cohort that was jointly developed by Hallym University College of Medicine and Chuncheon Sacred Heart Hospital. A trained dentist or clinician interviewed the participants and collected peripheral venous blood samples after obtaining informed written consent. The Institutional Review Board of each institution approved this study protocol. The details of the data collection can be found elsewhere [36,37]. ## 4.2. SNP Genotyping By using literature reviews, we identified nineteen candidate genes, including PAX9 and TGFA, and two chromosomal loci (8q24.21 and 10q250), which have been reported to be associated with NSCL/P in previous studies. By using a web browser known as, ‘TAG SNP selection (TagSNP)’ (https://snpinfo.niehs.nih.gov/snpinfo/snptag.html) [38], we identified SNP markers that were frequently found in East Asian populations among SNPs located within 2 kb from each of the 5′ and 3′ ends of the candidate genes. Genomic DNA was isolated from each blood sample by using a commercial DNA extraction kit (Quiagen Inc., Valencia, CA, USA) at the Samsung Biomedical Research Center, and genotype data were generated via SNP Genetics Inc. (Seoul, Republic of Korea) by using VeraCode Technology (Illumina Inc., San Diego, CA, USA). Details of these procedures are presented elsewhere [39]. ## 4.3. Genetic Association Analysis We subsequently analyzed only 92 SNPs in Hardy–*Weinberg equilibrium* (HWE p-values greater than 0.01) with both genotype and sample call rates greater than $95\%$ and a minor allele frequency (MAF) greater than $1\%$. After SNP quality control, a pairwise LD was estimated by calculating r2 via the Haploview program in the control group. The missing genotypes were imputed by considering the calculated LD [40]. We performed Fisher’s exact test by using PLINK 1.9 for genetic association analysis [41]. ## 4.4.1. SNP Subset Selection Based on the statistical significance obtained by the Fisher’s exact test, we selected four subsets of SNP markers for the binary classification of NSCL/P risk: three SNPs ($p \leq 0.01$), ten SNPs ($p \leq 0.05$), sixteen SNPs ($p \leq 0.1$), and ninety-two SNPs (all). SNPs in LD (r2 > 0.8) were excluded (except for the 92-SNP set). Of the 262 samples, we used 200 samples (100 cases and 100 controls) in the training process (180 samples for training and 20 samples for validation) and 62 samples (43 cases and 19 controls) for testing purposes. ## 4.4.2. Polygenic Risk Score We calculated the PRS for each jth subject by using the equation PRSj=∑$i = 1$M(logORi×xij), where M is the number of SNP markers, logORi is the natural logarithmically transformed odds ratio (OR) of the ith susceptibility SNP, and xij is the count of the risk alleles (0, 1, or 2) at the ith SNP in the jth individual. We performed a logistic regression analysis on the PRS that was calculated to determine case–control status [42]. ## 4.4.3. Traditional Machine Learning Algorithms We evaluated the risk prediction performance of six commonly used machine learning algorithms: support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), logistic regression (LR), light gradient boosting model (LGBM), and adaptive boosting (ADA). This evaluation was performed by using the Python Scikit-learn package [43]. ## 4.4.4. Artificial Neural Network To classify NSCL/P cases, we constructed four ANN models for each given set of SNPs by using the Keras package of TensorFlow [44]. Our ANN contains two dense layers followed by a rectified linear unit (ReLU). We set the number of neurons in each layer to 8, 16, 32, and 64 for the 3-, 10-, 16-, and 92-SNP models, respectively. In addition, we constructed a dense output layer with sigmoid activations to classify NSCL/P and utilized the Adam method for optimization with an initial learning rate of 5×10−3 and a decay rate of 10−5 [45]. We trained each ANN model in the 100 epochs setting and measured the binary cross-entropy loss to evaluate the model performance. At the end of the training, each set was replaced with the best weight with low validation loss and high training accuracy. ## 4.4.5. Genetic-Algorithm-Optimized Neural Networks Ensemble Our model implemented the GA that was proposed by Tong and Schierz [25] to extract an optimal set of SNPs for classification, followed by an ensemble of ANN results trained with each optimal set. Total cycles and population size were set to 30, and each population consisted of a fixed number of SNPs. To speed up the identification of the local minima, we initialized one population with a set consisting of the most significant SNPs that were found in the association analysis. The goodness-of-fit of the GA was calculated by adding the training loss and the validation loss. For each of the three settings (three, ten, and sixteen SNPs), we created six sets of SNPs, which consisted of five sets from GA and one set from the association analysis. The six SNP sets were trained on each ANN with the same settings as described above. The final value of the ensemble prediction was the average of the prediction values of multiple neural networks (Figure 3). ## 4.5. Model Evaluation and Validation As evaluation metrics, we calculated the accuracy, which represents the percentage of correctly classified samples, and the area under the receiver operating characteristic curve (AUC). The performance of the ML and DL models was further evaluated using the weighted average F1-score, which balances precision and recall. To address the potential for variability in the results of the ANN models when trained on a GPU server, we repeated the training process 100 times and calculated the average and $95\%$ confidence intervals ($95\%$ CIs) of both accuracy and AUC for each model to ensure the reproducibility of the results. ## 4.6. In Silico Functional Analysis We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.8 to analyze gene ontology (GO) terms to identify the central function of the SNP markers [46]. We further examined the functional relevance between candidate genes with the protein–protein interaction (PPI) network by using STRING v11 [47]. ## 5. Conclusions GANNE, a deep-learning-based approach for disease risk classification, has shown promise in overcoming the sample size limitations of population-based genetic association studies by utilizing genetic algorithms to select the optimal set of SNP markers. Nevertheless, due to the limited sample size in this study, it is necessary to validate the results in larger, independent Korean populations, as well as to conduct comparative analyses of the model performance across different ethnic groups. 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--- title: Transcriptomic Analyses of Brains of RBM8A Conditional Knockout Mice at Different Developmental Stages Reveal Conserved Signaling Pathways Contributing to Neurodevelopmental Diseases authors: - Colleen McSweeney - Miranda Chen - Fengping Dong - Aswathy Sebastian - Derrick James Reynolds - Jennifer Mott - Zifei Pei - Jizhong Zou - Yongsheng Shi - Yingwei Mao journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003467 doi: 10.3390/ijms24054600 license: CC BY 4.0 --- # Transcriptomic Analyses of Brains of RBM8A Conditional Knockout Mice at Different Developmental Stages Reveal Conserved Signaling Pathways Contributing to Neurodevelopmental Diseases ## Abstract RNA-binding motif 8A (RBM8A) is a core component of the exon junction complex (EJC) that binds pre-mRNAs and regulates their splicing, transport, translation, and nonsense-mediated decay (NMD). Dysfunction in the core proteins has been linked to several detriments in brain development and neuropsychiatric diseases. To understand the functional role of Rbm8a in brain development, we have generated brain-specific Rbm8a knockout mice and used next-generation RNA-sequencing to identify differentially expressed genes (DEGs) in mice with heterozygous, conditional knockout (cKO) of Rbm8a in the brain at postnatal day 17 (P17) and at embryonic day 12. Additionally, we analyzed enriched gene clusters and signaling pathways within the DEGs. At the P17 time point, between the control and cKO mice, about 251 significant DEGs were identified. At E12, only 25 DEGs were identified in the hindbrain samples. Bioinformatics analyses have revealed many signaling pathways related to the central nervous system (CNS). When E12 and P17 results were compared, three DEGs, Spp1, Gpnmb, and Top2a, appeared to peak at different developmental time points in the Rbm8a cKO mice. Enrichment analyses suggested altered activity in pathways affecting cellular proliferation, differentiation, and survival. The results support the hypothesis that loss of Rbm8a causes decreased cellular proliferation, increased apoptosis, and early differentiation of neuronal subtypes, which may lead ultimately to an altered neuronal subtype composition in the brain. ## 1. Introduction The maturation of RNA transcripts is a tightly regulated process. Pre-mRNAs usually undergo extensive modifications including splicing, polyadenylation at the 3′ end, and addition of guanosine nucleotide cap at the 5′ end before becoming translatable, mature mRNA. Diverse groups of RNA-binding proteins (RNPs) are responsible for these different RNA modifications and control RNA splicing, transport, translation, and stability, within the cell. RBM8A, also known as Y14, is a protein that was first identified by its RNA-binding sequence [1]. RBM8A participates in an assembly of proteins known as the Exon Junction Complex (EJC), which contains the protein factors eukaryotic translation initiation factor 4A3 (EIF4A3), Magoh, cancer susceptibility candidate 3 (Casc3), and many other peripherally associated factors [2]. The EJC and its general functions are conserved across a wide range of species, with homologs being studied in different models including yeast, fly, worm, zebrafish, mouse, and human [3,4,5,6,7,8,9,10,11]. Spliceosomes assemble the EJC on spliced pre-mRNA [12]. The EJC can direct further splicing and regulate transcription or mRNA transport and translation when it accompanies the mature transcript out of the nucleus [2]. In addition to binding and modifying transcripts, the EJC has been shown to participate in Nonsense Mediated mRNA Decay (NMD), which identifies mRNA with premature termination codons (PTCs) during translation and causes the faulty mRNA to be degraded. The core components of the EJC also play their independent roles and bind to differential targets out of the EJC complex [3,13,14]. RBM8A mutations have been implicated in a variety of clinical phenotypes. Compound mutations in RBM8A have been found to cause thrombocytopenia with absent radius syndrome (TAR syndrome) [15,16,17]. This disorder is characterized primarily by low blood platelet counts (thrombocytopenia), and missing radii bones. Additional features of TAR patients include short ulnas, low megakaryocyte numbers, the axial root of the kidney, renal and heart defects, agenesis of the corpus callosum, and hypoplasia of the cerebellum [18,19,20,21]. In a case study, a TAR patient exhibited partial seizures, psychomotor retardation, and cerebral dysgenesis [20]. *The* genetic cause of TAR syndrome was found to have compound mutations with a microdeletion of around 200 bp in the 1q21.1 region of the genome (including RBM8A) on one inherited chromosome, and a low-frequency noncoding SNP in RBM8A on the other inherited chromosome 1 (rs139428292 or rs201779890) [15,17]. In addition to clinical phenotypes of TAR syndrome, RBM8A is also associated with various neuropsychiatric disease cases. RBM8A is located in the 1q21.1 region of the genome, which is highly associated with neuropsychiatric diseases as a result of copy number variations (CNVs) (both duplication and deletions) [22,23,24,25]. Additionally, de novo mutations in RBM8A have been associated with autism spectrum disorders (ASD) [26] and the Mayer–Rokitansky–Küster–Hauser (MRKH) syndrome (MIM 277000) [27,28]. However, how different variants of RBM8A give rise to different clinical symptoms remains unknown. To investigate the role of RBM8A in the nervous system, our lab previously demonstrated that the mouse homolog Rbm8a is crucial in regulating neural progenitor cell (NPC) populations and that genes downstream of Rbm8a expression include risk genes for intellectual disability, schizophrenia, and autism spectrum disorder [29]. Dysregulation of RBM8A leads to anxiety behaviors [30]. Consistent with its essential role in neurodevelopment, we and other groups have developed Rbm8a cKO mouse lines and showed that Rbm8a is required for the proliferation of cortical NPC and interneuron progenitors at the ganglionic eminence as well as megakaryocyte differentiation [31,32,33]. However, the underlying molecular mechanism causing these defects is still unclear. The p53 activation has been shown to mediate the cell cycle defects observed in the EJC cKO mice [33,34,35]. To further examine how the downstream molecular mechanism of Rbm8a causes abnormal development of the brain at different developmental periods, in this study, we analyze the changes in the transcriptome of mice with Rbm8a haploinsufficiency in the brain during embryonic and postnatal stages. We identified over 300 transcripts that showed significant fold changes between WT and Rbm8a cKO mice, including 34 genes with known functions in nervous system development. This provides a starting point for choosing a narrower subset of genes or cellular processes to observe in future studies. We further observed that neural transcription factors were upregulated in the early postnatal brain, accompanied by gene expression typically associated with mature neurons in the adult brain. Considering these results, we believe that Rbm8a is required to delay cell differentiation and maturation, allowing the precursor cells of the nervous system to proliferate and fully populate their organs. ## 2.1. Rbm8a cKO Mouse Model Our previous results indicate that RBM8A is essential for neural development, and more specifically, is a positive regulator of NPC proliferation [29]. However, these observed effects are limited to a small portion of the cortex, due to the limitations of in utero electroporation. To further probe this developmental role of RBM8A, and to examine its effects on the entirety of the nervous system, we generated a cKO mouse [31]. The mouse line contains the homozygous loxP allele, Rbm8af/f, on a C57BL/6 background (Figure 1A). The Rbm8af/f mice contain loxP sites that guide Cre recombinase to delete three exons in the Rbm8a gene (Figure 1A). To create brain-specific Rbm8a cKO mice, the Rbm8af/f mice were crossed with nestin-Cre (Nes-Cre) transgenic mice from the Jackson Laboratory, B6.Cg-Tg (Nes-Cre) 1 Kln/J, stock number 003771 [36]. The Nes-Cre mouse line has hemizygous Cre recombinase driven by a nestin promoter. Nestin has heavily biased expression in embryonic neural stem cells, allowing nervous system-specific expression of Cre at early embryonic day 10 (E10). This enabled us to examine all of the cortex, and other areas of the nervous system, and to examine how Rbm8a deletion in the brain affected mouse brain structure and behavior. Although nestin has been reported in a few cells in the heart or kidney, our study used the brain tissues for RNAseq to avoid contamination of other cells. The resulting progeny consisted of $50\%$ Nes-Cre; Rbm8af/+ mice and $50\%$ Rbm8af/+ mice. This indicates that the mice that are haploinsufficient for Rbm8a are born at the expected Mendelian ratio. Littermates without nestin can be used as comparative controls. As reported previously [31], the resulting Rbm8a haploinsufficient mice were significantly smaller compared to littermate controls (Figure 1B) and had microcephaly, which is a greater than $50\%$ reduction in brain size at P17 (Figure 1C). A large, visible gap between the two cerebral hemispheres was typical of the cKO brains, in contrast to the tightly aligned hemispheres in the WT brains. Most of these Nes-cre; Rbm8af/+ pups only survived until postnatal day 20 (P20). As these mice have thin cortices, we hypothesized that they also had perturbations in the cortical layers. This could manifest in the form of thinner layers, or disorganized cortical layers (cells migrating to the wrong layer). To test this, we immunostained the coronal brain section of P17 Nes-Cre; Rbm8af/+ mice and littermate controls with deep cortical layer marker FOXP2. FOXP2 staining was revealed to be abnormal; instead of staining layers $\frac{5}{6}$ as in the control, FOXP2 labeling was found in the middle cortex, spanning to layers 3–6 (Figure 1D). ## 2.2. General DEG Analysis of the Whole Brain at P17 Next, we sought to determine the molecular pathways that govern Rbm8a’s role in brain development. To do this, we utilized RNAseq to determine transcriptomic changes in Rbm8a haploinsufficient mouse brains at P17. RNA was isolated from the whole brain of P17 mice (control and cKO) and converted to cDNA and sequences using the Illumina HiSeq 2500. In the P17 whole brain, 19,622 genes have quantifiable transcript readings that were plotted in a volcano plot (Figure 2A). A total of 251 DEGs show a significant false discovery rate (FDR) (q < 0.05), and 140 of them had expressional changes of twofold or more in either direction. This list of differentially expressed transcripts was then used for further analysis. To obtain an overall assessment of the features of these DEGs, we used the online ShinyGO analytic tool [37]. First, we determined that the DEGs are primarily protein-coding RNAs ($98.1\%$) and lincRNAs ($1.9\%$), which is significantly different from the expected transcript distribution pattern (Figure 2B). This is consistent with the fact that EJC factors have little effect on small noncoding RNAs, such as miRNA and snRNAs. Second, DEGs from the P17 RNAseq dataset are generally evenly distributed across different chromosomes (Supplemental Figure S1B). However, we identified four regions in chromosomes 11 and Y that are enriched with DEGs (FDR < 0.05) (Supplemental Figure S1A). Interestingly, DEGs have longer coding sequences, transcript, 5′ untranslated region (UTR), 3′ UTR, and higher GC contents (Figure 2C–G). However, the number of exons (Supplemental Figure S1C) and the number of transcript isoforms per coding gene (Supplemental Figure S1D) were as expected in all genes. To further examine which functions these differentially expressed transcripts mediate, we tested them in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway [38] and looked for functional clusters that were enriched for genes in our DEG dataset. Consistent with our previous findings that Rbm8a is critical for interneuron development [31], the KEGG pathway analysis revealed that three major signaling pathways are enriched: neuroactive ligand–receptor interaction, complement and coagulation cascades, and the GABAergic synapse (Figure 3). DEGs relevant to neural functions are shown in the neuroactive ligand–receptor interaction (Supplemental Figure S2) and the GABAergic synapse (Supplemental Figure S3). Particularly, GABA-A receptor subunits, such as Gabrd and *Gabrq* genes, are enriched in the GABAergic synapse pathway, suggesting an imbalance of excitation and inhibition (E/I) that are prevalent in patients with neurodevelopmental disorders. ## 2.3. Gene Ontology (GO) Analyses on Upregulated and Downregulated DEGs at P17 This characterization of DEGs helps determine potential functions that can lead to changes in neurodevelopment by RBM8A. At P17, upregulated and downregulated CNS-related DEGs were examined with the GO Enrichment Analysis tool in ShinyGO. The downregulated DEGs are significantly enriched in multiple biological processes (Figure 4A,B), including fear response, chemical synaptic transmission, neuron development, neurogenesis, and transcriptional regulation. Using a network plot in which two pathways (nodes) are connected if they share $20\%$ (default) or more genes, we detected two major clusters (Figure 4B). One regulates behavior and the other regulates neurodevelopment, which is consistent with the neurodevelopmental phenotypes of Nes-Cre; Rbm8af/+ mice (Figure 1). When DEGs were examined in the GO cellular component analysis, which is defined as “A location, relative to cellular compartments and structures, occupied by a macromolecular machine when it carries out a molecular function” in GO term [39,40,41], they are significantly enriched in several cellular compartments, such as dendrites, vesicle lumens, and neuronal spines (Figure 4C,D), suggesting a critical role of RBM8A in synaptic transmission. Although the cellular distributions of DEGs are enriched in dendritic compartments, the GO molecular functions of these DEGs are clustered in transcriptional factors (Figure 4E,F). Among the downregulated group, two transcription factors stood out: Neuronal differentiation 1 (Neurod1) and Engrailed 2 (En2). Neurod1 is a transcription factor critical for neurodevelopment [42,43]. It promotes neuronal cell phenotypes when overexpressed in stem cells, and in neurons [44,45,46]. En2 also promotes the differentiation of neuronal subtypes [47,48,49]. With these observations, it is possible that Rbm8a is required for the activity of neural transcription factors, which allows more NPCs to remain in the progenitor pool and proliferate. Consistent with previous observations [29,31,32], if neuronal differentiation is impeded by Rbm8a, the competing process of brain development would be impaired. Next, we investigated the upregulated DEGs at P17 in the GO analysis. Intriguingly, Rbm8a cKO significantly increases genes that participate in kidney development, blood vessel development, and ion transport (Figure 5A,B). Network analysis revealed two separate biological processes that are involved in ion transport and tube morphogenesis (Figure 5B). These results suggest that Rbm8a cKO in the nervous system suppresses the expression of neural genes, yet promotes other organ development, such as the renal system. Major cellular components were identified in the plasma membrane and extracellular matrix (Figure 5C,D). Interestingly, the serotonergic synapse, platelet alpha granule, and cell surface compartment are separated from other clusters in network analysis (Figure 5D). Consistent with GO cellular component analysis, upregulated DEGs are involved in active transmembrane transporters and growth factor binding (Figure 5E,F). Among the top upregulated DEGs, transthyretin (Ttr) encodes a homo-tetrameric carrier protein to transport thyroid hormones or vitamin A in the plasma and cerebrospinal fluid [50]. Mutations in Ttr can lead to several deadly diseases such as cardiomyopathy and neuropathy, which affect autonomic, motor, and sensory systems [51]. Folate receptor 1 (Folr1) is a cell surface marker of midbrain dopaminergic neuron precursor cells and immature neurons of the same type [52]. These results further support the crucial role of RBM8A in neural and other organ development. ## 2.4. Alternative Splicing (AS) Analyses of RNAseq Dataset at P17 RBM8A is primarily known for its role in RNA regulation, including NMD and splicing. Therefore, we decided to investigate whether Rbm8a cKO led to changes in alternative splicing. We used MISO to determine if any alternatively spliced transcripts are significantly changed in our RNAseq results [53]. A total of 71 alternative splicing events in 62 genes were identified, with the majority being skipped exons (Figure 6A). Interestingly, the gene list did not overlap with any DEGs, suggesting that the levels of DEGs are not regulated by AS. *The* genes that were alternatively spliced were identified and input into GO analysis to determine if they mediate any biological functions. Intriguingly, the alternatively spliced genes in Nes-Cre; Rbm8af/+ mice at P17 affected functional pathways mediating gliogenesis, oligodendricyte development, and translational readthrough (Figure 6B,C). Together, these analyses reveal that RBM8A could regulate multiple neural functions and processes via controlling transcript abundance and AS. ## 2.5. DEG Analysis in the E12 Hindbrain Our previous study conducted RNAseq analysis on the E12 cortex of control and Nes-Cre; Rbm8af/+ mice [31]. As the Rbm8a cKO mouse also has a small hindbrain (Figure 1B), we further tested the gene expression in the E12 hindbrains using RNAseq (Figure 7, supplemental Figure S4). We were interested in whether different groups of genes would be affected by Rbm8a cKO in the different brain regions. A volcano plot was generated to display all genes that had quantifiable readings in both the WT and KO hindbrains (Figure 7A). About 28,000 genes were plotted in the graph. A total of 25 DEGs had significant q-values (<0.05), and 23 of them had expressional changes of twofold or more in either direction (Figure 7A). The heatmap for these 23 DEGs was compared between the WT and KO mice in Supplemental Figure S4. Similarly, these DEGs from E12 hindbrains are enriched in protein-coding genes (Figure 7B). Because the number of DEGs is low, they are localized in chromosomes 1, 2, 4, 5, 6, 7, 10, 11,17, X, and Y (Supplemental Figures S5 and S6A). Four enriched regions were identified in chromosomes 2, 6, and Y (Supplemental Figure S5). The only significant feature of DEGs from E12 hindbrains is the 5′ UTR length compared to the overall genome (Figure 7C). No significant changes were identified in the number of exons (Supplemental Figure S6B), or the number of isoforms per coding gene (Supplemental Figure S6C). In contrast to the P17 whole brain data, DEGs from E12 hindbrains have normal lengths in the coding sequence (Supplemental Figure S6D), transcript length (Supplemental Figure S6E), 3′UTR (Supplemental Figure S6F), and normal GC content (Supplemental Figure S6G). To further examine the functions of these DEGs, we tested them in the KEGG pathway [38]. Intriguingly, the KEGG pathway analysis revealed only one enriched major signaling pathway—the P53 pathway (Figure 7D, Supplemental Figure S7)—suggesting a defect in the P53-mediated cell death pathway during embryonic neurodevelopment. To examine the affected pathways, we further examined the DEGs from E12 hindbrain data in GO analysis. Among 25 DEGs, 8 DEGs are downregulated and no significant Biological *Process is* detected. We only identified some cellular components, such as translational initiation factor 2 complex and P granule (Figure 8A), and molecular function on histone H3 trimethylation (Figure 8C), in GO analyses. However, we were able to identify more enriched functions from upregulated DEGs (Figure 8C–H). Consistently, GO biological function analysis identified apoptosis, DNA damage, P53-mediated signal transduction, and epithelial cell maturation (Figure 8C,D), suggesting an increase in cell death during embryonic hindbrain. These DEGs are localized in various compartments (Figure 8E), but mainly in the two clusters centered in neuronal projection and protein kinase signaling complexes such as the TOR complex (Figure 8F). In addition to the kinase signaling pathways, GO molecular function analysis found more neural-related functions in dopamine β-mono-oxygenase activity, and opioid peptide activity (Figure 8G). These molecular functions are loosely connected in the network analysis (Figure 8H). Compared to the E12 time point, even with hindbrain and cortex DEGs combined, many more genes showed significant expressional changes at P17. However, fewer genes overlapped between the P17 whole brain and the E12 brain regions than between the two E12 regions (Figure 9). Nrgn and Anoctamin 3 (Ano3) were upregulated in the E12 cortex but in the opposite direction at P17. Ano3 is a calcium-dependent phospholipid scramblase highly expressed in the brain and skin [54]. Meanwhile, Top2a was downregulated at both E12 and P17, whereas Spp1 and Gpnmb were upregulated at both E12 and P17. These findings suggest that some downstream effects of Rbm8a cKO are temporally distinct, while others may underlie a long period of development in the CNS. In all the time points/brain regions, Fam212b was significantly changed. However, the exact pathways implicating Fam212b are not yet known. In the embryonic brain, Fam212b is expressed by rapidly proliferating NPCs, while in the postnatal brain, it is expressed in limited, immature neuronal subtypes [55]. This increase in Fam212b could indicate a larger population of proliferating NPCs, contradicting our other findings, but it could also be the product of a compensatory mechanism among a dwindling pool of NPCs. Overall, when we compared the hindbrain dataset with our E12 cortex dataset, fewer DEGs were significant at any level in the E12 hindbrain than in the cortex. Ten DEGs overlapped between those detected in the cortex and hindbrain; all of these were upregulated. Their names and functions are presented in Supplemental Table S1. Of note, six of these ten common upregulated DEGs are known to directly influence cellular proliferation. These were Cdkn1a [56], Ccng1 [57], and Phlda3 [58], which are known to slow or arrest the cell cycle. Sesn2, which protects cells from programmed death during stress [59]; Eda2r, which increases programmed cell death [60]; and Fam212b [55], which is highly expressed in rapidly proliferating NPCs in the embryonic mouse brain. ## 3. Discussion In this study, three RNAseq datasets were analyzed to explore the altered transcriptome of Rbm8a cKO mice. Transcriptomes were assessed at E12 and P17, and at E12, the brain was split into cortex and hindbrain for separate sequencing. The results showed that the different brain regions and time points had many expressional changes, with little overlap between them. Therefore, loss of Rbm8a has temporally and spatially restricted effects during CNS development. At E12, in the cortex, 19 DEGs significant at q < 0.05 were known to be implicated in the CNS [31]. They affect many aspects of nervous system development ranging from cell proliferation to myelin maintenance to calcium signaling. The hindbrain at E12 shared ten upregulated DEGs with the cortex, more than half of which could modulate the rate of cell proliferation and turnover. Some of them were pro-apoptotic and some were anti-apoptotic, while others regulated the progression of the cell cycle. Based on this data alone, it is not possible to conclude whether cell populations increased or decreased. However, the small body size and microcephaly of the mice suggest that the cells were less proliferative or more prone to dying [31]. At P17, a much different set of CNS-related DEGs was identified. Significant Neurod1 and En2 upregulation at P17, as well as downregulation of several genes associated with the immature CNS, indicates that neurons were possibly reaching terminal differentiation long before the CNS should have stopped developing. There was also evidence that the distribution of cell types was abnormal in the Rbm8a cKO brains, based on the decrease in Lhx8 expression, which regulates the NPC’s decision to differentiate into a GABAergic versus a cholinergic neuron [61,62,63]. These results correlate with our previous findings that Rbm8a generally suppresses NPC differentiation. Apparently, loss of Rbm8a may also disrupt the ratios of NPCs that differentiate into each neuronal subtype. A few of the significant DEGs from E12 reappeared in the P17 cKO brains. Notably, three of them had changed significantly at both E12 and P17. Spp1 and Gpnmb were upregulated at both ages in cKO than control mice, while Fam212b was downregulated at P17 and upregulated at E12. This supports that some pathways are not continuously active, but rather are active on different timelines. Interestingly, both Spp1 and Gpnmb play important roles in microglia and macrophage during brain damage and many other pathological conditions [64,65,66,67]. Upregulation of Spp1 and Gpnmb indicates activation of microglia and neuroinflammatory responses in Rbm8a-deficient brains [68]. Their expressional changes could also be compensatory for other disruptions in the CNS. Additionally, both Spp1 and Gpnmb participate in bone and tissue remodeling [69]. Fam212b was the only DEG that is upregulated at E12 but downregulated at P17 (q < 0.05). According to previous explorative studies, Fam212b is expressed by highly proliferative NPCs, immature neurons in the postnatal developing brain, and very specific subtypes of mature neurons in the adult forebrain [55]. Unfortunately, the exact pathways that this protein participates in are unknown. Further investigation is necessary to elucidate the role of Fam212b in CNS development, and its relation to Rbm8a. Enrichment analysis showed that several pathways were affected by Rbm8a cKO in the brain. A few patterns that appeared across the three RNAseq datasets were enrichments in genes related to cellular differentiation, regulation of RNA transcription, proliferation, and cell death. Changes in differentiation pathways can result in delayed differentiation, premature differentiation, or an unbalanced distribution of cell types at maturity. Among enriched and depleted pathways, cell fates including oligodendrocytes, osteoblasts, neurons, and specific neuronal subtypes were named. Considering that several genes expected to be expressed in the adult brain were upregulated in the embryonic cortex, as well as the fact that negative regulation of photoreceptor differentiation was depleted, we hypothesized that the Rbm8a cKO mouse nervous system differentiates prematurely, resulting in the underdevelopment of nervous system tissues. Closely tied to differentiation is the renewal of progenitor cell populations, regulated by signals for cell cycle progression versus arrest, and survival versus apoptosis. In the E12 cortex, genes for the cell division process were depleted; likewise in the hindbrain, negative regulation of proliferation was increased, and neural precursor proliferation was specifically determined to be depleted. This falls in line with our previous observations that Rbm8a promotes the renewal of NPCs and inhibits the differentiation of neuronal subtypes. In the P17 brain, it appears that the nervous system gets a head start and develops quickly in Rbm8a cKO mice: neuronal development genes are enriched, and pathways pertaining to synaptic plasticity and behavior are more active. However, these could also be the results of premature differentiation of neurons. At a stage when the nervous system should still be expanding, the neurons are settling into their mature roles, approaching terminal differentiation. Furthermore, synaptic plasticity and behavior changes are observed in both juvenile and adult animals. Increased activity of these pathways is not necessarily an advantage for animals at such an early developmental stage. Intriguingly, Rbm8a cKO mice die at the postnatal stage even with another intact copy of the Rbm8a gene, which is different from human patients with 1q21 deletion or TAR syndrome who can live to adulthood. Although the mouse model can recapitulate some aspects of human disease, species variances between human and mouse models exist. This difference could be a lack of unknown compensatory mechanisms in mice. RBM8A modulates mostly protein-coding genes that likely play a large role in the observed phenotypes, but RBM8A also regulates a proportion of lincRNAs. In the future, the location of the lincRNAs should be further investigated to determine which protein-coding genes they potentially modulate. This insight may lead to clues to the overall mechanism of RBM8A’s developmental role. Taken together, the DEG analysis and GO enrichment analysis support our hypothesis that RBM8A maintains renewal of the neural precursor population and inhibits differentiation. Additionally, we uncovered specific genes and pathways for further investigation that may be critical to early CNS development. Finally, our RNAseq analysis featured several genes whose functions have not been elucidated in the context of early brain development, including Spp1, Gpnmb, and Fam212b. We hope that these data will provide the lead for further studies of brain development in mice and other mammalian models. ## 4.1. Mice Wild-type male and female C57/BL6N mice were obtained from Taconic (Germantown, NY, USA) C57BL/6N male mice were housed 2–4 mice per cage in a room with a light/dark cycle at 12 h intervals (lights on at 7:00 am), and provided ad libitum access to food and water. All procedures on mice were reviewed and approved by The Pennsylvania State University IACUC Committee, under IACUC protocol, 44057, to Yingwei Mao. ## 4.2. RNA-Sequencing Sample preparation for RNA sequencing was done by Dr. Yingwei Mao. Eight mouse embryos at E12 were collected for RNA sequencing. Four of them were Rbm8afl/+, and the other four were Nes-Cre; Rbm8afl/+. The hindbrain and cortex regions were dissected from the rest of the brain and stored separately. Six more mice, three for each condition, were euthanized on postnatal day 17 (P17); their whole brains were collected. These three sets of brain samples were sent to the Penn State Genomics Core Facility for sequencing with the Illumina HiSeq 2500 on a paired-read protocol. A total of 20 million paired reads were run per sample, producing 40 million total reads per sample. Raw reads were processed with paired-end analysis. ## 4.3. Analysis of DEGs Three sequencing datasets were obtained, corresponding to the E12 cortex, E12 hindbrain, and P17 whole brain. The raw Illumina output was processed by the Penn State Bioinformatics Consulting Center, in collaboration with Dr. István Albert. Using TopHat (version 2.0.6), reads were aligned to the NCBI *Mus musculus* genome, assembly GRCm38.p6, available to the public through the NCBI Genome database. Subsequently, Cuffdiff was used to calculate the statistical significance of expressional changes. After sorting DEGs by significance, DEGs were compared between the E12 cortex and hindbrain regions, as well as between the E12 and P17 time points. We identified genes that were significant at q < 0.05 in both conditions being compared and noted whether these shared DEGs had changed in the same direction. The E12 cortex and P17 DEGs were further sorted to distinguish those pertinent to the CNS and establish targets of interest for further investigation in Rbm8a cKO animals. The CNS-related DEGs of the E12 cortex were categorized manually, based on literature reports of their known functions and expressional patterns. This was less feasible for the large number of DEGs at P17 because the analysis named all CNS-related genes it recognized from the submitted DEGs. Therefore, we instead used the Gene Ontology (GO) enrichment analysis tool to classify CNS-related genes DEGs in the P17 data. ## 4.4. Analysis of Enriched Gene Clusters *Overrepresented* gene clusters and pathways were identified among significantly upregulated and downregulated DEGs using the Gene Ontology Consortium’s free online resource, GO enrichment analysis [39,40], and the ShinyGO analytic tool [37]. GO enrichment analysis groups genes by function and pathway, then estimates how many genes from each group are expected in a list of a given number of genes. If the actual number of genes from the same group greatly exceeds the expected number, then that group of genes is determined to be enriched. The software requires an input list with a sufficient number of genes to accurately identify gene cluster enrichments; we began by inputting the DEGs significant at q < 0.05. The E12 cortex and hindbrain and the P17 whole brain were analyzed individually, with inputted DEGs further separated by direction of change (upregulation or downregulation). The PANTHER Overrepresentation Test was used to recognize groups of genes within the DEGs that occurred at significantly higher or lower counts than expected, relative to all known expressional patterns in the mouse genome. ## 4.5. Alternative Splicing Analysis For the alternative splicing analysis, all bam files created by TopHat [70] were merged into a single file using samtools (version 1.1) [71]. The total number of reads that support the individual variants associated with each of the predicted functional alternative splicing events was determined using the MISO (Mixture of Isoform) package (version 0.5.3) [53] using events annotated as of 26 June 2013. Significant differentially spliced events were determined by requiring a Bayes’ factor > 10 and Δψ > 0.2 in a comparison of control and Rbm8a cKO. 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--- title: Renal Insufficiency Increases the Combined Risk of Left Ventricular Hypertrophy and Dysfunction in Patients at High Risk of Cardiovascular Diseases authors: - Xiaozhao Lu - Qiang Li - Jingru Deng - Yu Kang - Guoxiao Liang - Linxiao Deng - Lei Guo - Haodong Ruan - Zibi Peng - Jiaxi Li - Ning Tan - Jiyan Chen - Jin Liu - Amanda Y. Wang - Yong Liu journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003474 doi: 10.3390/jcm12051818 license: CC BY 4.0 --- # Renal Insufficiency Increases the Combined Risk of Left Ventricular Hypertrophy and Dysfunction in Patients at High Risk of Cardiovascular Diseases ## Abstract Background: The identification of asymptomatic structural and functional cardiac abnormalities can help us to recognize early and intervene in patients at pre-heart failure (HF). However, few studies have adequately evaluated the associations of renal function and left ventricular (LV) structure and function in patients at high risk of cardiovascular diseases (CVD). Methods: Patients undergoing coronary angiography and/or percutaneous coronary interventions were enrolled from the Cardiorenal ImprovemeNt II (CIN-II) cohort study, and their echocardiography and renal function were assessed at admission. Patients were divided into five groups according to their estimated glomerular filtration rate (eGFR). Our outcomes were LV hypertrophy and LV systolic and diastolic dysfunction. Multivariable logistic regression analyses were conducted to investigate the associations of eGFR with LV hypertrophy and LV systolic and diastolic dysfunction. Results: A total of 5610 patients (mean age: 61.6 ± 10.6 years; $27.3\%$ female) were included in the final analysis. The prevalence of LV hypertrophy assessed by echocardiography was $29.0\%$, $34.8\%$, $51.9\%$, $66.7\%$, and $74.3\%$ for the eGFR categories >90, 61–90, 31–60, 16–30, and ≤15 mL/min per 1.73 m2 or for patients needing dialysis, respectively. Multivariate logistic regression analysis showed that subjects with eGFR levels of ≤15 mL/min per 1.73 m2 or needing dialysis (OR: 4.66, $95\%$ CI: 2.96–7.54), as well as those with eGFR levels of 16–30 (OR: 3.87, $95\%$ CI: 2.43–6.24), 31–60 (OR: 2.00, $95\%$ CI: 1.64–2.45), and 61–90 (OR: 1.23, $95\%$ CI: 1.07–1.42), were significantly associated with LV hypertrophy. This reduction in renal function was also significantly associated with LV systolic and diastolic dysfunction (all P for trend <0.001). In addition, a per one unit decrease in eGFR was associated with a $2\%$ heightened combined risk of LV hypertrophy and systolic and diastolic dysfunction. Conclusions: Among patients at high risk of CVD, poor renal function was strongly associated with cardiac structural and functional abnormalities. In addition, the presence or absence of CAD did not change the associations. The results may have implications for the pathophysiology behind cardiorenal syndrome. ## 1. Introduction Heart failure (HF) is globally recognized as a major public health problem, with increasing prevalence and mortality in developing countries [1]. In the latest guideline for the management of HF, pre-HF is defined as a phase of asymptomatic structural and functional cardiac abnormalities [2]. Early recognition and intervention can delay the development of HF and improve the prognosis of patients with HF. Therefore, the early detection of structural and functional changes may help clinicians to recognize patients at pre-HF earlier. Prior studies and guidelines suggest that renal function insufficiency is one of the most important risk factors for the progression and poorer prognosis of HF [2,3,4]. The changes in heart structure and function are the key pathophysiological elements of heart failure, which may meanwhile underlie the renal pathology, based on interactions through the sympathetic signaling changing of the renin–angiotensin–aldosterone system (RAAS) [5,6,7]. Previous studies indicated that in the general population or patients with CKD, poor renal function was associated with abnormal LV structure and dysfunction [8,9,10]. However, some studies demonstrated inconsistently negative associations between renal function and LV structure and function among the general population or CKD patients [10,11,12]. Few studies have investigated the associations between the cardiac profile and renal function in patients at high risk of HF or cardiovascular diseases (CVD). Therefore, we design this study to systematically examine the associations of renal function with LV structure and systolic diastolic function in high-risk CVD patients. ## 2.1. Study Population This multicenter study cohort was recruited from the Cardiorenal ImprovemeNt II (CIN-II, NCT05050877) study, conducted among five regional central tertiary teaching hospitals in China. Patients who underwent coronary angiography (CAG) and/or percutaneous coronary intervention (PCI) were included. The indications of CAG or PCI were signs or symptoms of ischemia, elevated diagnostic enzymes, or abnormal electrocardiogram findings. All treatments were performed based on the standard clinical practice guidelines [13,14]. We enrolled patients (≥18 years) who underwent echocardiographic assessment (structure, systolic, and diastolic function) and had measurements of serum creatinine, height, and weight on admission. Patients with temporary dialysis or outlier eGFR values (>120 mL/min per 1.73 m2) were excluded. Finally, 5610 patients were included in this study (Figure 1). The study was approved by the Ethics Committee of Guangdong Provincial People’s Hospital (No. GDREC2019555H[R1]) and conducted in accordance with the principles of the Declaration of Helsinki. All participating sites received institutional review board approval from their own ethics committees. ## 2.2. Data Collection and Definitions All clinical data of the enrolled patients were collected from the electronic medical record system for all the participant hospitals, including demographic characteristics, medical history, procedures, laboratory examinations, echocardiographic data, and discharge medications. The eGFR was calculated using the Chronic Kidney Diseases Epidemiology Collaboration equation [15]. CKD was defined as eGFR < 60 mL/min per 1.73 m2 and end-stage renal disease (ESRD) was defined as eGFR < 15 mL/min per 1.73 m2 or the maintenance of dialysis [16,17]. Congestive heart failure (CHF) was defined as New York Heart Association (NYHA) functional class > 2 or Killip class > 1 [18]. ## 2.3. Echocardiography Assessment Echocardiography was performed by the same team of trained cardiac ultrasound doctors at Guangdong Provincial People’s Hospital for all the patients at the time of admission using Philips EPIQ5. The structural indices assessed on echocardiography included the left ventricular (LV) thickness (interventricular septal wall thickness (IVS), posterior wall thickness (PWT), and relative wall thickness (RWT)), LV size (LV end-systolic diameter (LVESD) and LV end-diastolic diameter (LVEDD)), LV systolic function (LV ejection fraction (LVEF)), and LV diastolic function (early mitral inflow peak velocity (E), early mitral annulus TDI velocity (e’), peak velocity flow in the early to late diastole (E/A)). The LV mass was calculated using the linear method and indexed to the body surface area as the LV mass index (LVMI). The RWT was calculated using the formula (2 × diastolic PWT)/LVEDD and was considered to be increased if the result was >0.42. LV hypertrophy was defined as LVMI > 115 g/m2 in men and LVMI > 95 g/m2 in women. The LV geometry was classified using the LVMI and RWT as normal (no LV hypertrophy and normal RWT), concentric remodeling (no LV hypertrophy and increased RWT), concentric hypertrophy (LV hypertrophy and increased RWT), and eccentric hypertrophy (LV hypertrophy and normal RWT) [19]. LV systolic dysfunction was defined as LVEF < $55\%$, and LV diastolic dysfunction was defined as E/e’ > 14 [20]. ## 2.4. Statistical Analysis The patients were divided into five groups according to their eGFR levels (>90, 61–90, 31–60, 16–30, and ≤15 mL/min per 1.73 m2 or the need for dialysis). Data were presented as the mean with standard deviation (SD) or median with interquartile range (IQR) for continuous variables and as the quantity and frequency (%) for categorical variables. The categorical variables were compared using Pearson’s chi-squared test, and the continuous variables were compared using t-test. Univariable and multivariable logistic regression was used to test the associations between the eGFR categories and LV hypertrophy, as well as LV systolic and diastolic dysfunction. A linear trend test was applied using 5 groups as a continuous variable by assigning the median value of each group to the variable. Restricted cubic splines were plotted to reveal the potential linear associations between the eGFR as a continuous variable and the odds ratio (OR) of LV hypertrophy and LV systolic and diastolic dysfunction. Model 1 was unadjusted, Model 2 was adjusted for age, gender, and body mass index, and Model 3 was adjusted according to Model 2, adding diabetes mellitus (DM), hypertension (HT), CHF, high-density lipoprotein cholesterol, β-blocker, and angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB). All analyses were performed using R software (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). A two-sided p-value < 0.05 indicated significance for all the analyses. ## 3.1. Baseline Characteristics The baseline characteristics of the study cohort are presented in Table 1. The average age of the 5610 patients was 61.6 ± 10.6 years, and 1535 ($27.3\%$) were female. Of those patients, $17.1\%$ ($$n = 962$$) had CKD and $2\%$ ($$n = 113$$) had ESRD. In comparison with those who had a higher eGFR, patients with a lower eGFR tended to have a worse cardiovascular risk profile (older, with a higher prevalence of hypertension, diabetes mellitus, CHF, CAD, and stroke). With a lower eGFR, there were progressive decreases in the mean LVEF and increases in the mean echo parameters of the LV thickness (IVS and PWT), LV size (LVEDD and LVESD), and LV diastolic dysfunction (E/e’). There was also a correlation between a lower eGFR and a higher proportion of concentric hypertrophy. In total, $36.4\%$, $25.4\%$, and $34.0\%$ of the patients had combined LV hypertrophy and LV systolic and diastolic dysfunction, respectively. The associations of the ORs for LV hypertrophy and LV systolic and diastolic dysfunction with eGFR in the fully adjusted restricted cubic spline plots are presented in Figure 2. When fully adjusted for confounders, the associations between eGFR and LV hypertrophy, as well as LV systolic and diastolic dysfunction, remained significant. As depicted in Figure 2, the combined risk of LV hypertrophy and LV systolic and diastolic dysfunction rapidly increases in patients with a lower eGFR. Subsequently, we ran logistic regression models to evaluate the associations between the eGFR categories and LV hypertrophy, as well as LV systolic and diastolic dysfunction. In the multivariate logistic regression analysis, patients with a lower eGFR were still significantly associated with a higher risk of LV hypertrophy and LV systolic and diastolic dysfunction (Table 2), and a per one unit decrease in eGFR was associated with a $2\%$ heightened risk of combining with LV hypertrophy and systolic and diastolic dysfunction. Compared with the reference of eGFR > 90 mL/min per 1.73 m2, patients in the four groups based on the eGFR categories of 61–90, 31–60, 16–30, and ESRD had a higher risk of LV hypertrophy (OR: 1.23; $95\%$ CI: 1.07–1.42, OR: 2.00; $95\%$ CI: 1.64–2.45, OR: 3.87; $95\%$ CI: 2.43–6.24, and OR: 4.66; $95\%$ CI: 2.96–7.54, respectively, P for trend <0.001). Meanwhile, the same increased risk of LV systolic and diastolic dysfunction was observed in the unadjusted and multi-variables adjusted models (all P for trend <0.001). ## 3.2. Subgroup Analysis The subgroup analyses were consistent with the primary results (Table 3). When the analysis was stratified according to the coronary artery disease (CAD) status, the associations of the eGFR with LV hypertrophy and LV systolic and diastolic dysfunction did not differ significantly among individuals stratified by CAD without interaction (P for interaction: 0.519, 0.348, and 0.779, respectively). ## 4. Discussion To our knowledge, this is the first study to systematically evaluate the association between renal function and LV structure and systolic and diastolic function among patients at high risk of CVD. Among these patients, more than $\frac{1}{3}$ had combined LV hypertrophy, of which concentric hypertrophy formed the highest proportion among the abnormal LV geometries. Almost $\frac{1}{4}$ and $\frac{1}{3}$ of the patients combined systolic and diastolic dysfunction, respectively. The proportion of LV hypertrophy and systolic and diastolic dysfunction increases directly to the renal function, and a per one unit decrease in eGFR was associated with a $2\%$ heightened combined risk of LV hypertrophy and systolic and diastolic dysfunction. LV hypertrophy is considered a key pathophysiological feature of patients at pre-HF and a strong predictor of poor prognosis among the general population [2,21]. In our study, $36.4\%$ of patients at high risk of CVD had LV hypertrophy, and $30.8\%$ had concentric hypertrophy. Among patients with CKD stages 3–5 of the Chronic Renal Insufficiency Cohort, Park M. showed that almost half of 3487 patients were classified as having LV hypertrophy, and concentric hypertrophy formed the highest proportion of cases of abnormal LV geometry [10], which is comparable to our study. Matsushita K. reported that the prevalence of LV hypertrophy was $10.6\%$ among 4175 patients in a cohort from Atherosclerosis Risk in Communities population [8]. In addition, the above and other studies of the CKD cohort showed that renal insufficiency was independently associated with LV hypertrophy, especially in advanced CKD. However, several studies demonstrated no independent relations between lower renal function and abnormal LV structure [11,22,23]. The negative results of these studies should be interpreted as aimed at patients with a low risk of a poor cardiovascular profile due to the restricted enrollment of patients with cardiac conditions. In our study, concerning the patients at high risk of CVD, poor renal function was independently associated with LV hypertrophy after adjusting the confounders. Although no strong associations were observed in the relation of renal function and LV hypertrophy in the patients stratified by CAD, it should be noted that a lower eGFR is an independent risk factor for abnormal LV structure, which may require attention in clinical practice. Systolic and diastolic dysfunction denotes the subsequent changes in LV remodeling and are important predictors for HF and poor prognosis. Previous studies have been inconsistent in determining the association between eGFR and LV systolic and diastolic function, regardless of whether they examined general patients, patients with CKD, or patients with DM [10,12,24]. In addition, strong associations related to LV dysfunction were observed more frequently in patients with advanced CKD. All these studies enrolled patients at a lower risk of CVD than those in our study. Previous studies showed the high prevalence of abnormal LV structure and function in patients with CVD and demonstrated that left ventricular hypertrophy was reversible, whereas diastolic dysfunction was difficult to be improved in patients at high risk of CVD [25,26]. Our study highlighted the high prevalence of LV systolic and diastolic dysfunction in patients at high risk of CVD and showed that even a mild eGFR reduction was consistently associated with a higher proportion of LV systolic and diastolic dysfunction. Renal insufficiency is associated with structural and functional abnormalities based on multiple mechanisms, representing one of the essential risk factors for patients with pre-HF, and is associated with the development and poor prognosis of HF. There are several possible explanations for these cardiac changes with poor renal function. Firstly, poor renal function increases the burden of salt retention and volume overload, which leads to cardiovascular compensatory changes such as LV remodeling, hypertrophy, and even decompensatory alternations in function [5]. Secondly, patients with CKD are more likely to have diabetes or insulin resistance which may aggravate LV hypertrophy and, subsequently, diastolic and systolic dysfunction through the phosphoinositide-3 kinase–AKT pathway [17,27]. Thirdly, fibroblast growth factor-23 (FGF-23) was found to be elevated in the cases of poor renal function, as it can directly upregulate RAAS by inhibiting angiotensin 2 [28]. Additionally, elevations in FGF-23 can lead to 1,25(OH)2D deficiency through 1-α-hydroxylase suppression [29]. All of these factors may contribute to accelerated hypertrophy and dysfunction. This study has clinical significance and several research implications. Our results demonstrated that poor renal function is an independent predictor of LV hypertrophy and dysfunction among patients at high risk of CVD. Poor renal function is considered a major risk factor for HF, and in recent years, the evaluation of renal function has received more attention from clinicians. However, the assessment of the phenotype of pre-HF and the impact of renal function on the heart are undervalued in clinical practice. This highlights the need for physicians to integrate the early recognition of changes in LV structure and function in clinical routines, especially for patients with mild renal insufficiency. Albuminuria is a well-established risk factor of CVD, and ACEI/ARB use may halt or reverse the progression of albuminuria [30]. In addition, the progression of renal function is significantly associated with increased cardiovascular risk, and multifactorial interventions for risk factors could improve cardiovascular renal outcomes and prognosis. Therefore, early intervention aiming to delay renal function progression or improve the LV structure and function is required in clinical practices [31,32,33,34]. Therefore, future study is needed to verify the efficacy of interventions in protecting renal function upon changes in LV structure and function and their prognostic value for patients with high-risk CVD. ## 5. Limitations There are several limitations to our study that should be taken into consideration. Firstly, this study was a retrospectively multicenter study, and, thus, our findings reflect statistical associations and do not imply cause–effect relationships. Secondly, our study only used the LVEF and E/e’ for the evaluation of LV systolic and diastolic function, which is one of several parameters used to assess systolic and diastolic function. However, these are easily accessible parameters in clinical practice and can represent the cardiac function of patients. Thirdly, other validated renal function measurements such as the albuminuria level were not incorporated into our study, which could enhance better determination of patients. Fourthly, echocardiography was performed by a team of cardiac ultrasound doctors which may elevate variability and bring an erroneous stratification. Fifthly, the study was aimed at patients with high-risk CVD, who were mainly elderly patients. Although we adjusted for age, the findings should be cautious to extrapolate for other populations. Therefore, more prospective studies are required to evaluate the influence and mechanisms of the relationship between renal function and LV structure and function. ## 6. Conclusions In summary, a reduction in eGFR was associated with increased LV hypertrophy and reduced systolic and diastolic function among patients at high risk of CVD. In addition, the presence or absence of CAD did not change the outcome. 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--- title: Effect of Chitosan-Diosgenin Combination on Wound Healing authors: - Lubomir Petrov - Olya Stoilova - Georgi Pramatarov - Hristiyana Kanzova - Elina Tsvetanova - Madlena Andreeva - Almira Georgieva - Dimitrinka Atanasova - Stanislav Philipov - Albena Alexandrova journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003508 doi: 10.3390/ijms24055049 license: CC BY 4.0 --- # Effect of Chitosan-Diosgenin Combination on Wound Healing ## Abstract The difficult-to-heal wounds continue to be a problem for modern medicine. Chitosan and diosgenin possess anti-inflammatory and antioxidant effects making them relevant substances for wound treatment. That is why this work aimed to study the effect of the combined application of chitosan and diosgenin on a mouse skin wound model. For the purpose, wounds (6 mm diameter) were made on mice’s backs and were treated for 9 days with one of the following: $50\%$ ethanol (control), polyethylene glycol (PEG) in $50\%$ ethanol, chitosan and PEG in $50\%$ ethanol (Chs), diosgenin and PEG in $50\%$ ethanol (Dg) and chitosan, diosgenin and PEG in $50\%$ ethanol (ChsDg). Before the first treatment and on the 3rd, 6th and 9th days, the wounds were photographed and their area was determined. On the 9th day, animals were euthanized and wounds’ tissues were excised for histological analysis. In addition, the lipid peroxidation (LPO), protein oxidation (POx) and total glutathione (tGSH) levels were measured. The results showed that ChsDg had the most pronounced overall effect on wound area reduction, followed by Chs and PEG. Moreover, the application of ChsDg maintained high levels of tGSH in wound tissues, compared to other substances. It was shown that all tested substances, except ethanol, reduced POx comparable to intact skin levels. Therefore, the combined application of chitosan and diosgenin is a very promising and effective medication for wound healing. ## 1. Introduction Skin injuries are referred to as wounds [1]. Both acute and chronic wounds fall under this category. A sudden injury to the skin is known as an acute wound. It can be cured in two to three months depending on its size and depth in the epidermis or dermis layers of the skin [2]. In addition, burns, leg ulcers, decubitus ulcers, infections, etc., are life-threatening chronic wounds because they do not heal quickly [1]. Accordingly, the difficult-to-heal wounds continue to be a serious problem for modern medicine. Therefore, the development of more advanced, affordable and cost-effective wound dressings is urgently needed. The healing process begins as soon as a wound develops. The phases that overlap and interact during the complex, dynamic and wound repair process are coagulation, immunological response, inflammation, proliferation and remodeling [3,4]. The inflammatory phase is characterized by the migration of inflammatory cells to the wound to defend against pathogens followed by activation of the skin cells. Neutrophils and macrophages are stimulated during this phase by producing pro-inflammatory cytokines, including interleukin-1β, tumor necrosis factor, as well platelet-derived, transforming and fibroblast growth factors [5,6,7]. The wound-healing process involves the participation of reactive oxygen species (ROS). They are powerful oxidizing agents and significant sources of cell deterioration, but also serve positive functions and are essential for setting up the normal wound healing response [8,9,10]. *By* generating cell-survival signaling, low levels of ROS help to protect tissues from infection and promote efficient wound healing [11,12]. However, excessive ROS generation can exceed the ability of endogenous antioxidants to scavenge them causing oxidative stress (OS). This redox imbalance damages cells, promotes inflammation and dysregulates the healing process [13]. Consequently, a good equilibrium between low and high ROS levels is crucial for the wound-healing process. It is commonly accepted that the ideal wound covering should mimic many properties of human skin—adhesion, elasticity, durability and impermeability to bacteria [14]. Hence, bioactive polymers have received considerable attention as effective wound-healing agents not only because of their biocompatibility and biodegradability, but also because they have an active therapeutic effect on one or more stages of wound healing [15]. One of the most studied and promising biopolymers for wound healing purposes is chitosan [16]. Chitosan, a renewable natural polysaccharide, composed of randomly distributed N-acetyl-D-glucosamine (N-acetylglucosamine) and 2-amino-2-deoxy-glucose (glucosamine) units, represents excellent biocompatibility, biodegradability, hemostatic, mucoadhesive and wound healing properties, as well anti-inflammatory, antioxidant, antimicrobial activity [17]. In addition, it is believed that chitosan hastens the production of fibroblasts and aids in the initial stages of healing [18,19]. Due to these benefits, and the ability to absorb exudates and film forming properties, chitosan is a good candidate in wound healing applications. Although it has been demonstrated that chitosan encourages tissue growth and differentiation during wound healing, its usage in wound care is impeded due to its poor mechanical properties [20,21,22]. In order to overcome this drawback, numerous synthetic polymers are used. Among them, polyethylene glycols (PEG) are widely used as plasticizers. Due to their advantageous properties, such as biocompatibility, solubility and low-toxicity, PEGs are suitable for contact with living organisms. In addition, their incorporation improves the release of poorly water-soluble bioactive substances and improves the therapeutic efficacy of various medications [23]. Diosgenin (25R-spirost-5-en-3-ol) (Figure 1), a hydrolysate of dioscin, is a naturally occurring steroidal saponin that is present in a number of plants, including *Trigonella foenum* graecum, Solanum incanum, Solanum xanthocarpum, *Smilax china* Linn and *Dioscorea nipponoca* Makino [24,25]. As a physiologically active phytochemical, diosgenin (Dg) has a variety of effects on plants [26]. It is utilized as a medicine to treat conditions such as diabetes, hypercholesterolemia, climacteric syndrome, leukemia and cancer, as well in the production of steroids [27]. Dg possesses high biocompatibility, immune-protection, anti-inflammatory and antioxidant properties [28,29,30]. Compared to the conventional antioxidant activity of vitamin C, diosgenin extracted from *Costus speciosus* has an efficient antioxidant scavenging affinity against DPPH radicals [31]. Diosgenin also enhances the antioxidant status, prevents lipid peroxidation and reduces inflammation by preventing the generation of cytokines, enzymes, and adhesion molecules which promote inflammation [32]. However, the pharmaceutical applications of diosgenin are very limited because of its poor pharmacokinetics and extremely poor water solubility [33,34]. Recently, it was shown that encapsulation of Dg in chitosan/bovine serum albumin nanoparticles enhanced its bioavailability [34]. Therefore, finding a suitable combination of diosgenin and chitosan will be an alternative strategy to overcome the limitations of diosgenin applications and to improve the healing effect of both substances. The testing of various combinations of substances that accelerate the healing of wounds is the basis for creating new more effective therapies. For this reason, in the present study, it is aimed to investigate the wound healing effect of the combined administration of chitosan and diosgenin on a mouse skin wound model. To the best of our knowledge, there are no publication on the simultaneous application of chitosan and diosgenin in the treatment of wounds. Given the role of inflammation and oxidative stress in wound regeneration, as well the anti-inflammatory and antioxidant effects of chitosan and diosgenin, the lipid peroxidation (LPO), protein oxidation (POx) and total glutathione (tGSH) levels were evaluated. In that way, it was shown that the proposed combination of chitosan and diosgenin, is a very promising formulation with significant potential towards wound dressing and healing applications. ## 2.1. Macroscopic Observations The wound healing effect of the chitosan-diosgenin combination was evaluated by treatment of the wounds made on the mice dorsum. The macroscopic analysis was performed by measuring the wound areas photographed on the 3rd (D3), 6th (D6), and 9th (D9) days and compared with those before the first treatment (D1). Figure 2 shows the macroscopic appearance of wounds treated respectively with polyethylene glycol in $50\%$ ethanol (PEG), chitosan and PEG in $50\%$ ethanol (Chs), diosgenin and PEG in $50\%$ ethanol (Dg) and chitosan, diosgenin and PEG in $50\%$ ethanol (ChsDg) at D1 and D9. In this experiment, a $50\%$ ethanol solution was used as a control. Complete schematic presentation of wound treatment is explained and shown in Section 4.3. All mice survived throughout the period until sacrifice. There was no evidence of necrosis. Clearly, on the 9th day the majority of the wounds appeared to be healed and were reduced significantly in size without external signs of inflammation (Figure 2). The macroscopic appearance of the wounds during the D3 and D6 treatment can be observed in Figure S1. Furthermore, the relative reduction of wound areas vs. the initial wound areas (on D1) after treatment with various combinations is illustrated in Figure 3. The macroscopic results indicated faster healing in the animals tested with Chs and ChsDg. In particular, Chs and ChsDg combinations gave a significantly greater reduction in wound area as early as day 3 (67.2 and $62.6\%$, respectively) compared to PEG ($32.4\%$) and Dg ($8.1\%$). On the 9th day the largest decrease of the wound area was observed in the group treated with ChsDg ($82\%$). The difference in the treated wound areas with Chs and ChsDg was apparent on the 9th day. The advantage is that the measured mean relative contraction of wounds treated with ChsDg was bigger than this treated with Chs ($59.2\%$). PEG also had a good effect, similar to this of ChsDg, but it appeared with a delay—on the 6th day. Thus, in overall, the ChsDg combination demonstrated a better wound healing effect. ## 2.2. Microscopic Observations The changes on the desquamated epithelium regions, erythema, rhagades, loss of skin appendages and corrosive skin effect are listed in Table 1 and Table 2. In addition, the representative histological photomicrographs of the structural organization of test groups are shown in Figure 4. The application of ethanol was accompanied by moderate erythema, a weak skin corrosive effect and the presence of desquamation. Compared with the control, the application of PEG, Dg and Chs gave mild erythema and desquamation. In addition, the treatment of skin wounds with PEG and Dg leads to mild skin corrosive effect, while treatment with PEG and Chs leads to rhagades and focal loss of skin appendages. Healing tests performed in mice using various combinations clearly showed that the ChsDg combination may contribute to faster wound healing without complications. ## 2.3. Oxidative Stress Regarding the indicators of oxidative stress, no differences were detected in LPO levels between intact skin and control skin. LPO was significantly lower in PEG-treated wounds and higher in Chs- and ChsDg-treated wounds compared to tissue from ethanol-treated (Control) wounds (Figure 5). Of the examined substances, only the administration of Dg retained the levels of LPO similar to control. The POx was elevated in ethanol-treated wounds (Control) compared to levels in intact skin. POx values close to those in intact skin were measured in the wounds treated with the tested substances (Figure 6). The concentration of tGSH was non-significantly higher in ethanol-treated wounds (Control) compared to untreated skin (Intact). The application of the investigated substances resulted in a decrease in the concentration of tGSH in wounds except for the ChsDg combination where no significant difference was reported compared to the intact skin samples and the wounds treated with ethanol (Figure 7). ## 3. Discussion Wound healing is known to be a complex and dynamic process, regulated by various physiological and biochemical parameters, which act together to promote tissue restoration [15]. This process can happen more quickly and efficiently with appropriate formulations. In this context, topical formulations based on chitosan attract much attention because of their known active role in the first three stages of wound healing—hemostasis, inflammation, proliferation [19,35]. Moreover, chitosan-based hydrogels may aid the re-establishment of skin architecture and its degradation by-products are non-cytotoxic [36]. It is observed that regardless of the recognized healing effect of chitosan, the number of studies on its various combinations with biological agents is increasing, with the aim of improving this effect. Despite the wide variety of chitosan formulations investigated, the synergistic effect of chitosan and diosgenin on wound healing has not yet been reported. In this study, the focus was on the preparation of a chitosan-diosgenin combination and studying its effect on the wound healing process. For this reason, various combinations were tested—polyethylene glycol in $50\%$ ethanol (PEG), chitosan and PEG in $50\%$ ethanol (Chs), diosgenin and PEG in $50\%$ ethanol (Dg) and chitosan, diosgenin and PEG in $50\%$ ethanol (ChsDg), respectively. The optimum chitosan concentration ($3\%$ w/v) and water to ethanol ratio ($\frac{1}{1}$ v/v) required for film formation were found by varying the ratios. Moreover, lactic acid was used in chitosan dissolution due to its plasticizer characteristic, which gives lower stiffness and a higher percentage of elongation, besides helping the antimicrobial properties. In order to prepare ChsDg combination, the poorly water-soluble diosgenin was firstly dissolved in ethanol, then mixed with the PEG solution in ethanol and finally this solution was added to the aqueous chitosan solution. The use of $50\%$ ethanol has an additional advantage because it minimizes the drying time and promotes faster film formation. The prepared colorless viscous chitosan solution was characterized by dynamic viscosity of 1780 cP and storage module (G’) lower than loss module (G”). Therefore, this chitosan solution was a physical gel with low mechanical properties, which is in accordance with the literature [37]. Hence, in all tested combinations an equal amount of PEG was used as plasticizer. Various wound models have been developed, considering the obstacles in sampling acute skin wounds in humans due to ethical considerations. The use of organotypic-cultured skin approximates the natural process, but does not reflect the overall response of the organism and is influenced by external factors such as the composition of the culture medium [38]. Animal models are the available alternative to study the complex interactions at molecular and cellular levels that occur during the wound healing process in a biologically relevant environment [39]. However, differences in thickness and composition between animal and human skin should be considered when interpreting the obtained data. Indeed, there is no animal model that represents all aspects of wound healing seen in humans. It is assumed that the main disadvantage of the excisional wound model in rodents is that the healing process is through the contraction of the panniculus carnosus while the human wound heals through re-epithelization. However, a disadvantage of the splint model is the possibility of self-mutilation by the animals through the ring, while the protective dressings are difficult to fix due to the movement and activity of the animals. For that reason, in this study the excisional wound model without silicon splint was applied, in accordance to the similar models in the literature [40,41,42]. In addition, some authors revised the considered limits of the excisional wound model because of the perception that rodent wounds heal by contraction while humans heal by re-epithelialization [43]. The data have shown that contraction occurs only after epithelial closure and the notion of the domination of closure by contraction is rather inaccurate. Thus, simple murine excisional wounds provide a valid and reproducible model that heals by both contraction and re-epithelialization [43]. The macroscopic results indicated that the greatest effect on wound retraction was from Chs and ChsDg, followed by PEG. Treatment with Chs and ChsDg led to faster retraction of the wounds—already on the 3rd day, while the effect of PEG reached that of Chs and ChsDg on the 6th day, and the overall effect on the 9th day of ChsDg was larger. These results were expected, because chitosan-based gel formulations have proven antioxidant and anti-inflammatory activities [19,35,36]. It is noteworthy that during the wound healing process, chitosan gradually depolymerizes to release N-acetylglucosamine which initiates fibroblast proliferation [36]. In this way collagen deposition is arranged, stimulating the synthesis of natural hyaluronic acid at high levels at the wound site [36]. Likewise, Dg with its immune-protection and antioxidant status, prevents lipid peroxidation and reduces inflammation [27,29]. In addition, a similar retracting effect of PEG, Chs and their combination was also found by other authors in the therapy of experimental wounds [44]. The histological criteria give an idea of the damage to the skin around the wounds by the studied combinations, which is decisive for their applicability in practice. Moreover, it was observed that chitosan-based gel formulation containing diosgenin was more effective compared to the other-treated groups, especially on the 9th day (Figure 2). Similarly, when wound area shrinkage was examined, recovery in the case of ChsDg was faster (Figure 3). The observed minimal irritant effect of the combination ChsDg (Table 1 and Table 2) and the good therapeutic effects on the experimental wounds (Figure 3) give grounds for continuing studies on the possibilities of using this combination in practice. Apparently, the chitosan-diosgenin combination accelerates wound healing by exhibiting synergistic activity. The implication of chitosan in wound healing is related to its interaction properties with neutrophils, resulting in IL-8 secretion that causes the migration of neutrophils to chitosan [45]. The immunomodulatory effects of chitosan are relatively broad, as it can induce a plethora of cytokines of a pro- or anti-inflammatory nature. Whether these responses are negative or positive depends on various factors. The infiltration of inflammatory cells is essential for wound repair, but excessive cell infiltration accompanied by classical immune cell activation can result in tissue damage [46]. There are data that activated neutrophils generate O2•− which induces lipid peroxidation and stimulates collagen synthesis [47]. This may explain the weak but significantly elevated LPO levels in the wounds treated with Chs and ChsDg. Given the observed beneficial effect of Chs and ChsDg in the wound healing process, it is likely that these small amounts of ROS play a rather positive signaling role [11]. The total protein carbonyl content is one of the most important biomarkers providing a qualitative assessment of the presence of OS in vivo [48]. Elevated protein carbonyl levels measured from biological tissues and fluids are associated with decreased enzyme activities, loss of protein function, inflammation activity, etc. [ 49]. The high level of protein carbonyl groups in the control samples observed in this study indicate that oxidative processes have taken place to some extent. The application of the tested substances (Dg, Chs, ChsDg) led to levels of protein carbonyl groups like that of the intact skin. This finding implies a suppressed inflammatory activity by these components [32,50]. The anti-inflammatory action of Dg could be explained through the stimulation of IFN-γ production [51] and the antioxidant ability of *Chs is* affiliated with the protonated NH2-groups, which are responsible for free radical scavenging [52]. The wound-healing process was better when both were combined. It should be mentioned that the application of Chs and the ChsDg on wounds leads to LPO increase but suppresses the POx (Figure 5 and Figure 6). Probably, the observed significant rise of MDA in contrast to protein carbonyls in Chs-treated wounds is due to the mechanism of LPO that occurs as a chain process after initiation by ROS and the high sensitivity of polyunsaturated fatty acids to oxidative damage [53]. Furthermore, proteostasis includes both protein stabilization and preferential degradation of the modified proteins [54]. Another explanation for the observed increase in MDA is a possible direct reaction of residual chitosan in the wound samples with the thiobarbituric acid used in the LPO assay method [55]. Glutathione is the most prevalent intracellular antioxidant and provides significant protection to the tissue from oxidative stress [56]. Glutathione can act directly as a ROS scavenger or indirectly through its participation as a co-substrate in antioxidant enzyme reactions. Particularly, GSH acts as an electron donor to hydrogen peroxide, forming an oxidized thiol, which is recycled by glutathione reductase. In this way, the antioxidant concentration is maintained at the wound site through regeneration [57]. Another potential reaction is the degradation and excretion from the cell of the oxidized thiol via glutathione-S-transferase [56]. In wounds, the GSH level is significantly lower when compared to undamaged skin [56]. Glutathione is essential for the wound-healing process. It was demonstrated that low antioxidant (incl. GSH) levels play a significant role in delaying wound healing in either aged or diabetic rats [58,59]. The obtained results indicate that administration of the chitosan-diosgenin combination resulted in the highest levels of GSH compared to the other substances tested (Figure 7). This further confirms that both chitosan and diosgenin accelerate wound healing by their synergistic activity. Moreover, the ChsDg combination might contribute wound healing by preventing the prolongation of the inflammation phase with their anti-inflammatory effects. ## 4.1. Materials Commercially available chitosan (Chs, medium molecular weight, viscosity 200–400 cps, $90\%$ degree of deacetylation) was supplied by Yantai Shang Tai Trading Co., Ltd, Yantai, China. Thiobarbituric acid, 5,5′-dithiobis-2-nitrobenzoic acid (DTNB), 2,4-dinitrophenylhydrazine (2,4-DNPH), diosgenin (Dg) and polyethylene glycol (PEG, average molecular weight 400 g/mol) were purchased from Sigma-Aldrich (St. Louis, MI, USA). All chemicals and solvents were of analytical grade and used without further purification. ## 4.2. Preparation of the Combinations The chitosan in PEG (Chs) combination was prepared by dispersing chitosan powder ($3\%$ w/v) in distilled water followed by adding lactic acid under stirring until the complete chitosan dissolution. Subsequently, PEG solution in ethanol ($0.16\%$ w/v) was added to the chitosan solution. The total water:ethanol volume ratio was 1:1.The pH of the prepared solution was 4. In order to prepare the chitosan and diosgenin in PEG combination (ChsDg), a solution of PEG in ethanol ($0.16\%$ w/v) and solution of diosgenin in ethanol ($0.1\%$ w/v) were added to the aqueous chitosan solution ($3\%$ w/v) in lactic acid. The total water:ethanol volume ratio in the prepared ChsDg combination was again 1:1. Blank diosgenin solution in PEG (Dg) in $50\%$ ethanol ($0.1\%$ w/v) and PEG in $50\%$ ethanol ($0.16\%$ w/v) were also prepared. As well, a control of $50\%$ ethanol was used. ## 4.3. In Vivo Experiments In vivo experiments were conducted on 10 albino mice, 25–35 g (10 weeks of age). The mice were kept in a controlled temperature room (24 ± 2 °C) with a 12 h light/dark cycle and with free access to food and water. Before treatments mice were anesthetized with Xylazine (20 mg·kg−1) and Ketamine (100 mg·kg−1). The entire back of the experimental animals was depilated with a trimmer and subsequent total epilation using an epilating cosmetic cream. After depilation, four identical wounds were made with a 6 mm diameter punch. The wounds of 5 of the animals were treated on days 1, 3, and 6 either with $50\%$ ethanol (Control), a solution of PEG in $50\%$ ethanol (PEG), a solution of chitosan and PEG in $50\%$ ethanol (Chs) and combined solution of chitosan, diosgenin and PEG in $50\%$ ethanol (ChsDg). In the remaining 5 mice, one of the wounds was treated with a solution of diosgenin and PEG in $50\%$ ethanol (Dg) instead of PEG (Figure 8). The four wounds were made on the dorsum of the animals and were treated with the various substances studied to make a more objective comparison of the effect of substances on the healing process, avoiding individual differences between animals. The wounds were treated for the first time immediately after the wounds were made. Then, before the next treatment, the wounds were cleaned with $50\%$ ethanol and then re-applied with the same substances. This procedure was repeated at 3 and 6 (D3 and D6) days. Before the first treatment (D1) and on the 3rd (D3), 6th (D6) and 9th (D9) days pictures of wounds were taken using a digital camera, and the wound areas (mm2) were determined using the image analysis program Image J. On day 9, animals were euthanized. An intact skin and wounds from 4 animals were excised for histological analysis and those from 6 animals for measurement of lipid peroxidation (LP), protein oxidation (POx) and total glutathione (tGSH) levels. The mice were maintained and used in accordance with the guidelines of the Care and Use of Laboratory Animals (US National Institute of Health) and the rules of the Ethics Committee of the Institute of Neurobiology, Bulgarian Academy of Sciences (registration FWA 00003059 by the US Department of Health and Human Services). For histological purposes, tissue samples from the wound sites treated with the tested substances were fixed in $10\%$ neutral buffered formalin overnight at 4 °C. Thereafter, the tissues were embedded in paraffin and cut into 6 µm thick sections. The samples were then deparaffinized with xylene and ethanol and processed for the classical histological staining hematoxylin and eosin (H&E). After the reaction, the sections were dehydrated in ethanol, cleared in xylene and coverslipped with Entellan (Merck, Darmstadt, Germany). The slides were observed and carefully photographed with a Nikon research microscope equipped with a digital camera DXM1200c. Equal-weighted skin samples were carefully cut with scissors into small pieces and then homogenized with a D-160 homogenizer (DLAB Scientific Inc., City of Industry, CA, USA). After centrifugation at 3000 rpm, the post-nuclear tissue homogenate was used to measure the total protein content and the tested oxidative stress parameters: lipid peroxidation, protein oxidation, and total glutathione. The Biuret method based on a colorimetric test for total proteins was used to determine the protein content. The 1.10307 Protein Kit was purchased from Sigma-Aldrich (St. Louis, MI, USA). The lipid peroxidation assay was based on the reaction between the end-products of the LPO and thiobarbituric acid according to Ben Mansour [2011] with some modifications [60]. The post-nuclear homogenates of the skin (mg protein ml−1) in 0.15 M KCl-10 mM potassium phosphate buffer, pH 7.2, were heated for 15 min at 100 °C in the presence of $40\%$ trichloroacetic acid, 5N HCl and $2\%$ thiobarbituric acid (2:1:2 v/v) for color developing. The absorbance was measured at 532 nm against dd H2O after cooling and centrifugation. The values were expressed in nmoles malondialdehyde (MDA) per mg protein, using a molar extinction coefficient of 1.56 × 105 M−1 cm−1. Protein carbonyl (PC) groups were quantified by reaction with 2,4-dinitrophenylhydrazine (2,4-DNPH), according to the method of Whitekus et al. [ 2002] with some modifications applied [61]. About 0.2 mL of homogenate without (control) and with 1 mL of 10 mM 2,4-DNPH (in 2 M HCl) were incubated at 37 °C for 90 min. After adding 1 mL of $28\%$ trichloroacetic acid, samples were vortexed for 1 min and then centrifuged for 10 min at 3000× g. The precipitates were washed with ethanol-ethyl acetate in a 1:1 ratio 3 times. Washed samples were then dissolved in 6 M guanidine (in 20 mM potassium phosphate buffer, pH 2.3, adjusted with HCl). Absorbance at 360 nm was measured, and carbonyl content was expressed as nmoles carbonyl.mg−1 protein using a molar extinction coefficient of 2.2 × 104 M−1 cm−1. The amount of tGSH was determined by the method described by Rahman et al. [ 62]. The absorption at 412 nm of the color compound 5′-thio-2-nitrobenzoic acid (TNB) resulting by the reaction between reduced glutathione (GSH) and 5,5′-dithiobis-2-nitrobenzoic acid (DTNB) was read. The reaction rate is proportional to the amount of the reduced glutathione in the sample. The amount of tGSH present was calculated using the standard and represented as ng/mg protein. ## 4.4. Statistical Analyses Descriptive statistics, the Shapiro–Wilks test of normality and One-Way ANOVA with Tukey post hoc test were applied using the statistical program GraphPad Prism 7.0. In the text, all data are presented as the mean ± standard deviation (SD) and in the figures as the mean ± standard error of measurement (SEM). ## 5. Conclusions For the first time, the combined action of chitosan and diosgenin on wound healing was studied. The obtained results indicate that the chitosan-diosgenin combination enhanced the regenerative effect and gave the largest and the most rapid reduction in wound area. Regarding oxidative indicators, the chitosan-diosgenin combination maintained high levels of the non-enzymatic antioxidant glutathione in wound tissues compared to the other substances tested. 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--- title: 'Prevalence of Overweight and Obesity and Their Impact on Spirometry Parameters in Patients with Asthma: A Multicentre, Retrospective Study' authors: - Abdullah A. Alqarni - Abdulelah M. Aldhahir - Rayan A. Siraj - Jaber S. Alqahtani - Hams H. Alshehri - Amal M. Alshamrani - Ahlam A. Namnqani - Lama N. Alsaidalani - Mohammed N. Tawhari - Omaima I. Badr - Hassan Alwafi journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003518 doi: 10.3390/jcm12051843 license: CC BY 4.0 --- # Prevalence of Overweight and Obesity and Their Impact on Spirometry Parameters in Patients with Asthma: A Multicentre, Retrospective Study ## Abstract Introduction: *Obesity is* a common comorbidity in patients with asthma and has a significant impact on health and prognoses. However, the extent to which overweight and obesity impact asthma, particularly lung function, remains unclear. This study aimed to report on the prevalence of overweight and obesity and assess their impacts on spirometry parameters in asthmatic patients. Methods: *In this* multicentre, retrospective study, we reviewed the demographic data and spirometry results of all adult patients with confirmed diagnoses of asthma who visited the studied hospitals’ pulmonary clinics between January 2016 and October 2022. Results: In total, 684 patients with confirmed diagnoses of asthma were included in the final analysis, of whom $74\%$ were female, with a mean ± SD age of 47 ± 16 years. The prevalence of overweight and obesity among patients with asthma was $31.1\%$ and $46.0\%$, respectively. There was a significant decline in spirometry results in obese patients with asthma compared with patients with healthy weights. Furthermore, body mass index (BMI) was negatively correlated with forced vital capacity (FVC) (L), forced expiratory volume in one second (FEV1), forced expiratory flow at 25–$75\%$ (FEF 25–$75\%$) L/s and peak expiratory flow (PEF) L/s (r = −0.22, $p \leq 0.001$; r = −0.17, $p \leq 0.001$; r = −0.15, $p \leq 0.001$; r = −0.12, $p \leq 0.01$, respectively). Following adjustments for confounders, a higher BMI was independently associated with lower FVC (B −0.02 [$95\%$ CI −0.028, −0.01, $p \leq 0.001$] and lower FEV1 (B −0.01 [$95\%$ CI −0.01, −0.001, $p \leq 0.05$]. Conclusions: Overweight and obesity are highly prevalent in asthma patients, and more importantly, they can reduce lung function, characterised mainly by reduced FEV1 and FVC. These observations highlight the importance of implementing a nonpharmacological approach (i.e., weight loss) as part of the treatment plan for patients with asthma to improve lung function. ## 1. Introduction Asthma, a common pulmonary disease, is characterised by airway hyperresponsiveness, inflammation and remodelling, and it is associated with variable airflow limitation and the presence of respiratory symptoms that vary over time and in intensity. Asthma affects around 300 million people worldwide, and it is expected that closer to 400 million people will have this condition by 2025 [1]. Patients with asthma tend to have variable combinations of pulmonary symptoms, including wheeze, cough, shortness of breath and chest tightness. Worsening of these respiratory symptoms (referred to as exacerbation) may lead to frequent visits to emergency departments and impact overall quality of life [2]. Several factors have been suggested to be associated with the exacerbation of asthma symptoms, one of which is obesity. Obesity is one of the most common asthma comorbidities [2] and is defined as an excessive accumulation of body fat that leads to a generalised increase in body mass or adipose tissue, which increases the risk of health problems [3]. Body mass index (BMI), calculated as weight in kilograms (kg) divided by the square of height in metres (m2), is the most widely used screening tool to determine overweight and obesity [4]. According to the World Health Organisation (WHO), BMI values of between 25 and 29.9 kg/m2 are considered to be overweight, while individuals with BMIs of 30 kg/m2 and higher are classified as obese [5]. Obesity is further classified by the Centres for Disease Control and Prevention (CDC) into three different categories: class I, or mild (30–34.9 kg/m2), class II, or moderate (35–39.9 kg/m2), and class III, or morbid (above 40 kg/m2) [6]. Obesity is prevalent among adults and children with asthma worldwide [2]. Although the prevalence of obesity in patients with physician-diagnosed asthma is unclear, previous studies have shown that the prevalence of obesity in individuals with self-reported asthma ranges from $15\%$ to $52\%$ [7,8,9]. More importantly, studies suggest that overweight and obesity in conjunction with asthma may lead to deterioration in pulmonary function, which has been shown to be consistent with poor asthma control [10]. In support of this, it has been reported that asthmatic patients who are obese tend to have a four- to six-fold increased risk of hospitalisation compared with non-obese asthmatic patients [11]. Although the exact pathophysiological mechanism remains unknown, it is thought the lung compression caused by accumulation of body fat around the thoracic and abdominal cavities (abdominal obesity) may lead to airway narrowing and increased airway resistance [12]. In addition, it has been suggested that obesity may increase the production of pro-inflammatory mediators that worsen airway inflammation, subsequently causing airway hyperreactivity [13]. Although the impact of obesity on lung function, including spirometry parameters in adults with asthma, has been reported in previous studies, there is still controversy over whether obesity further worsens airway obstruction [7,8,9]. This controversy is likely due to the fact that some previous studies rely on self-reported asthma diagnoses or self-reported height and weight rather than diagnosis by a physician in clinic or measured height and weight [7,8,9]. Thus, further studies are warranted to better understand the impact of obesity on a wide range of spirometry parameters: peak expiratory flow (PEF), forced expiratory volume in one second (FEV1), ratio of FEV1 to forced vital capacity (FEV1/FVC), FVC and forced expiratory flow at $25\%$ and $75\%$ of the pulmonary volume (FEF 25–$75\%$). Preliminary reports suggest that both asthma and obesity can lead to worsening of respiratory symptoms and increased risk of hospitalisation. However, the prevalence of obesity and the extent to which overweight and obesity impact lung function, particularly spirometry parameters among patients with asthma in Saudi Arabia, has not been studied. Therefore, this study aimed to report on the prevalence of overweight and obesity and assess their impacts on spirometry parameters in asthmatic patients. ## 2.1. Study Design and Settings This multicentre, retrospective study was conducted to investigate the impact of overweight and obesity on spirometry parameters among patients with asthma. The data collection process was carried out between 1 April 2022 and 31 October 2022 at King Abdulaziz University hospital and two Ministry of Health hospitals in Saudi Arabia. ## 2.2. Study Population We retrospectively reviewed the electronic medical records of 1156 outpatients with confirmed asthma diagnoses who had scheduled visits and consultations with specialists and were treated between 1 January 2016 and 31 October 2022. We collected spirometry results and demographic data (e.g., height, weight, BMI, age, gender and smoking status). Demographic data were collected at the time spirometry was performed. Only patients with multidisciplinary-team-confirmed diagnoses of asthma made in accordance with current nationally and internationally accepted criteria were included in the current study [14]. In the final analysis, we only included asthmatic patients with acceptable and reproducible lung function tests at or after age 18, as well as patients without smoking history due to the difficulty in separating asthma from chronic obstructive pulmonary disease in smokers. ## 2.3. Spirometry Parameters Only spirometry tests performed in accordance with the current American Thoracic Society/European Respiratory Society guidelines were included in the current study [15]. All spirometry tests were performed in pulmonary clinics by trained pulmonary function technologists. Although the pulmonary function tests were routinely validated by a respiratory consultant, all spirometry tests used in the present study were manually reviewed by two trained senior respiratory therapists (A.A.A. and A.M.A.). The results were not included in the final analysis if the spirometry tests were not acceptable and reproducible. The included spirometry results were obtained using a Sensor Medics Vmax 22 machine (SensorMedics Inc., Anaheim, CA, USA). The following spirometry parameters were recorded and included in the current study: FVC, FEV1, ratio of FEV1/FVC, FEF 25–$75\%$ and PEF. If the patient had more than one spirometry test performed between 1 January 2016 and 31 October 2022, only the most recent result was included. ## 2.4. Body Mass Index Height and weight were routinely measured in the clinics, with patients barefoot and wearing light clothing, using a medical scale (Adam Equipment Inc., Oxford, CT, USA). We only collected BMI values based on the heights and weights measured before spirometry was performed. All asthmatic patients included in the current study were divided into five groups in accordance with WHO and CDC classifications: [1] patients with BMI values of 18.5 to 24.9 kg/m2 (lean or healthy weight); [2] patients with BMI values of 25 to 29.9 kg/m2 (overweight); [3] patients with BMI values of 30 to 34.9 kg/m2 (mild or class I obesity); [4] patients with BMI values of 35 to 39.9 kg/m2 (moderate or class II obesity); and [5] patients with BMI values of 40 kg/m2 or above (morbid or class III obesity) [5,6]. ## 2.5. Ethical Considerations Prior to the start of this study, ethical approval (HA-02-J-008) was obtained from the Unit of Biomedical Ethics Research Committee at the Faculty of Medicine in King Abdulaziz University, Saudi Arabia. ## 2.6. Statistical Analysis In this study, Stata (version 16) was used for data management and analysis. Figures were generated using GraphPad Prism (version 9). The results are presented as numbers (%) and arithmetic means ± SD for categorical and continuous variables, respectively, unless otherwise stated. The normality of the data was graphically assessed. A one-way ANOVA was performed to compare the mean differences between lean, overweight and specifically classed obesity groups. This was followed by an unpaired Student’s t test to compare the mean differences between the two independent data sets. The correlation of BMI with spirometry measures (FEV1, FVC, FEF 25–$75\%$ and PEF) was determined using Pearson’s correlation coefficient. A multiple linear regression model was also performed to determine the factors associated with spirometry measures. $p \leq 0.05$ was regarded as statistically significant. ## 3.1. Patient Characteristics In total, 1156 subjects with confirmed asthma diagnoses were identified from the databases. After excluding patients <18 years old, smokers and those with BMIs <18.5 kg/m2 or without acceptable spirometry results, a total of 684 asthma patients met our inclusion criteria and were included in the final analysis (Figure 1). The mean ± SD age of the study population was 47 ± 16 years, and there were more females ($74\%$) than males. Of the 684 included patients, $23\%$ had BMIs between ≥18.5 and <25 kg/m2 (lean or healthy weight), $31\%$ had a BMIs between ≥25 and <30 kg/m2 (overweight) and $46\%$ had BMIs of ≥30 kg/m2 (all three classes of obesity). The prevalence of obesity alone and obesity including overweight in patients with asthma was $46\%$ and $77\%$, respectively. The mean ± SD BMI was statistically significantly greater in females than males (30.5 ± 6.9 vs. 28.9 ± 6.1; $p \leq 0.05$). The proportion of female patients was higher in the overweight ($75\%$) and obesity ($87\%$) groups compared with lean subjects ($66\%$). The baseline characteristics for the study population are shown in Table 1. ## 3.2. Associations between BMI and Spirometry Parameters Pearson correlation analyses were performed to determine whether BMI was associated with spirometry parameters. The results showed that there were statistically significant inverse correlations between BMI and FVC (r = −0.22, $p \leq 0.001$), FEV1 (r = −0.17, $p \leq 0.001$), FEF 25–$75\%$ (r = −0.15, $p \leq 0.001$) and PEF (r = −0.14, $p \leq 0.01$) (Figure 2). ## 3.3. Impact of Overweight and Obesity on Spirometry Parameters In order to determine whether a progressive decline in spirometry values was observed as BMI increased, we divided asthmatic patients into four different groups based on their BMI values. A one-way ANOVA showed that the means of the spirometry measures (FVC L, FEV1 L, FEF 25–$75\%$ L/s and PEF L/s) differed significantly according to BMI groups ($p \leq 0.0001$, $p \leq 0.01$, $p \leq 0.01$ and $p \leq 0.05$, respectively) (Figure 3A–D). Unpaired t tests were then performed to assess whether there was a significant difference in each spirometry measure based on the weight category. As shown in Figure 3A, although no difference in the mean FVC was found between normal weight and overweight (3.07 ± 0.06 L and 2.90 ± 0.06 L, respectively), mean FVC was significantly reduced in subjects with class I, class II and class III obesity (2.79 ± 0.06 L, $p \leq 0.01$, 2.65 ± 0.09 L, $p \leq 0.001$ and 2.39 ± 0.13 L $p \leq 0.0001$, respectively) compared with normal weight. In addition, mean FVC was found to be significantly decreased in class II and class III, but not in class I, compared with overweight ($p \leq 0.05$ and $p \leq 0.001$, respectively). Similar to the FVC findings, mean FEV1 did not significantly differ between asthmatic patients with normal weight and overweight (2.13 ± 0.06 L and 1.98 ± 0.05 L, respectively) (Figure 3B). However, mean FEV1 was found to be significantly lower in all classes of obesity (class I, class II and class III) (1.95 ± 0.05 L, $p \leq 0.05$, 1.83 ± 0.07 L, $p \leq 0.01$ and 1.72 ± 0.10 L $p \leq 0.01$, respectively) compared with normal BMI. When compared with overweight patients, mean FEV1 remained unchanged in those with class I and class II obesity but was significantly reduced in asthmatic patients with class III obesity ($p \leq 0.05$) (Figure 3B). Furthermore, mean FEF 25–$75\%$ was significantly reduced in class I, class II and class III obesity (2.11 ± 0.07 L/s, $p \leq 0.05$, 2.07 ± 0.13 L/s, $p \leq 0.05$ and 1.83 ± 0.13 L/s, $p \leq 0.05$, respectively) but not in overweight patients as compared with normal weight (2.41 ± 0.10 L/s) (Figure 3C). Interestingly, we found that mean PEF did not differ in patients with overweight and class I obesity but was significantly reduced in asthmatic patients with class I and II obesity (4.73 ± 0.19 L/s, $p \leq 0.05$ and 4.62 ± 0.26 L/s, $p \leq 0.05$, respectively) compared with normal weight (5.33 ± 0.14 L/s). It was also interesting to find that PEF only decreased in patients with class III obesity when compared with overweight patients ($p \leq 0.05$) (Figure 3D). A multiple linear regression model was performed to assess the independent associations of BMI with spirometry measures. BMI was significantly associated with FVC (L) and FEV1 (L) following adjustments for age and gender (adjusted β: −0.02; $95\%$ CI: −0.028 to −0.01; $p \leq 0.001$) and (adjusted β: −0.01; $95\%$ CI: −0.01 to −0.001; $p \leq 0.05$), respectively. In addition, simple regression models showed that BMI was associated with FEF 25–$75\%$ (β: −0.03; $95\%$ CI: −0.04 to −0.014; $p \leq 0.001$) and PEF (β: −0.03; $95\%$ CI: −0.05 to −0.01; $p \leq 0.01$). However, the associations were nullified upon further adjustments for age and gender (Table 2). ## 4. Discussion To the best of our knowledge, this study is the first to determine overweight and obesity prevalence in asthmatic patients and to assess the impact of overweight and obesity on spirometry measures among asthmatic patients in Saudi Arabia. The main findings of the current study showed that the prevalence of overweight and obesity among patients with asthma was $31\%$ and $46\%$, respectively. Our findings also demonstrated that there was a significant decline in spirometry results (FEV1, FVC, PEF and FEF 25–$75\%$) in obese patients with asthma compared with normal-weight asthma patients. In addition, we found that BMI was negatively correlated with all spirometry measures and that a higher BMI was independently associated with lower FVC and lower FEV1. These findings suggest that obesity can reduce lung function, ultimately leading to poor asthma control, and also highlight the importance of using a nonpharmacological approach (e.g., healthy diet and weight loss) as part of the treatment plan for patients with asthma to improve lung function and, ultimately, asthma management and overall quality of life. Obesity is one of the most common asthma comorbidities and is associated with increased risks of exacerbation and hospitalisation. Our findings that overweight ($31\%$) and obesity ($46\%$) are prevalent in patients with asthma are similar to a previous study reporting that the prevalence of obesity among patients with asthma is $52\%$ in the Netherlands [8] but contrasts with studies demonstrating a low prevalence of obesity ($15\%$ and $27\%$) among asthmatic patients in Taiwan [16] and Norway [9], respectively. This disparity is most likely attributable to the fact that the selection of asthma patients in the previous studies was based on self-reported asthma [9,16], whereas in the current study, only patients with multidisciplinary-team-confirmed diagnoses of asthma carried out in accordance with current nationally and internationally accepted criteria were included. In addition, the fact that the prevalence of obesity has been increasing in recent years among the general population in Saudi Arabia [17] may explain the high obesity prevalence observed in the current study. Despite the differences in prevalence rates, our finding that $77\%$ of asthmatic patients are obese or at risk of obesity (overweight) is alarming and suggests that early identification of obesity and overweight, through a regular screening tool, should be implemented in asthma clinics in order to reduce the risk associated with obesity. Although the mechanism that links asthma with obesity is not fully understood, it has been reported that obesity may be a consequence of asthma maintenance therapies. For instance, evidence suggests that the use of oral and inhaled corticosteroids is associated with increased body weight [18,19]. On the other hand, several studies describe obesity as a risk factor for asthma [20], indicating that obese patients are at a higher risk of developing the condition, leading to a novel disease phenotype (obesity-associated asthma) that requires careful evaluation and management. Further studies are needed to better understand the characteristics of this phenotype and its main underlying mechanisms. Obesity has been suggested to be associated with an increased asthma exacerbation rate, but it is unclear whether airflow obstruction is directly responsible for the deterioration of asthma symptoms. Our findings demonstrated a reduction in spirometry parameters (FEV1, FVC, PEF and FEF 25–$75\%$) in asthmatic patients with obesity compared with patients with normal weight, suggesting that obesity may ultimately impair lung function in patients with asthma. This is likely due to the fact that obesity can cause mechanical compression of the diaphragm, as well as the chest cavity [13], which may lead to a reduction in lung function. In addition, it has been reported that excess adipose tissue in obese individuals can further increase inflammatory mediators (e.g., interleukin 6) [21], which have been shown to be associated with impaired lung function [22,23]. Although the impact of overweight and obesity on PEF and FEF 25–$75\%$ values has not been reported, our findings are supported by a previous study that reported a reduction in FEV1 and FVC in self-reported asthma subjects with overweight and obesity as compared with normal weight [9]. This is further strengthened by the findings of this study that a higher BMI is independently associated with lower FVC and FEV1 even after adjustments for known confounders. A previous study demonstrated that an intensive six-month weight-loss programme was correlated with improvement in FVC and FEV1 in women with BMIs >30 kg/m2 [24]. Our findings, together with these observations, suggest that obesity can cause a decline in lung function, which can be reversed by weight loss. Thus, a screening tool to identify asthmatic patients at high risk for obesity should be implemented in order to improve overall quality of life in patients with asthma. It is also worth noting that we demonstrated that obesity and overweight, in general, are more prevalent among female asthmatic patients ($75\%$ and $77\%$, respectively) than male patients. This finding is supported by a previous study conducted in the US, showing that overweight and obesity are more prevalent in females with asthma ($63\%$ and $82\%$, respectively) than in males [23]. Overweight and obesity have also been reported to be more prevalent in females ($54\%$ and $66\%$, respectively) than males in Norwegian patients with self-reported asthma [9]. Our findings, together with these previous observations, may be explained by the fact that the proportion of asthma, regardless of subjects’ body weight and geographical location, is found to be higher in female than male subjects in the current study ($74\%$ prevalence), as well as in a previous study ($65\%$ prevalence) [25]. In addition, obesity without asthma has been reported to be higher in female than male subjects. A high rate of asthma with obesity in adult women suggests that sex hormones and nutrition quality may play a role in the presence and severity of asthma in obese patients. ## 4.1. Strengths This study has a number of strengths. First, most studies have assessed the impact of overweight and obesity on lung function in patients with self-reported asthma. The current study only included patients whose diagnoses of asthma were made and confirmed in accordance with current nationally and internationally accepted criteria. Second, we only included patients with spirometry tests performed in accordance with the current American Thoracic Society/European Respiratory Society guidelines. In addition, two trained respiratory therapists reviewed all spirometry tests and further excluded tests that were not acceptable and reproducible. Third, some previous studies have relied on self-reported height and weight. In the current study, BMI was calculated based on height and weight measured using medical scales in pulmonary clinics under the supervision of a trained nurse or respiratory therapist. ## 4.2. Limitations The current study is not without limitations. First, we were unable to study lung volumes and diffusion capacity as these tests are either unavailable or not routinely performed in our pulmonary clinics for patients with asthma. Second, it is known that the use of asthma maintenance therapies (e.g., inhaled corticosteroids) can lead to better asthma control and improvement in asthma symptoms and lung function. In the current study, all patients were on inhaled corticosteroids as a maintenance therapy to control asthma symptoms. However, it remains critical in the current study to determine the doses of inhaled corticosteroids, the levels of patient adherence to therapies and whether those patients were on other asthma control therapies due to the unavailability of these data. Thus, it is important to acknowledge that spirometry parameters can also be affected by patient non-adherence to therapies and/or types of therapy added on to existing inhaled corticosteroid treatment. Third, the prevalence of overweight and obesity was assessed in this study based on BMIs calculated from height and weight measured before spirometry was performed. Although BMI is currently considered to be the gold standard and is used by international organisations (e.g., WHO and CDC) to classify overweight and obesity, it should be noted that it lacks the ability to differentiate between fat and lean mass and does not take into account the differences in fat distribution. This is unlikely to affect the results of this study, as previous studies have shown that abdominal and thoracic fat have a differential effect on lung volumes [26]. There is no evidence to suggest that spirometry parameters are affected by differences in fat distribution. Fourth, our entire study population was diagnosed with asthma in Saudi Arabia. Thus, the findings may not translate to individuals with other chronic pulmonary and non-pulmonary diseases and/or other ethnic groups. ## 4.3. Practical Implementation Obesity is an asthma comorbidity that can eventually contribute to worsening respiratory symptoms. We report here that the prevalence of obesity and overweight in asthmatic patients is high, and that obesity can lead to a reduction in lung function in patients with asthma. In addition to pharmacological therapies, our findings highlight the importance of using non-pharmacological add-on therapies (e.g., physical exercise, healthy diet and weight loss) as part of the treatment plan for patients with asthma to improve lung function and, ultimately, asthma symptoms and overall quality of life. Further studies are needed to explore the impact of different lifestyle strategies on the treatment of asthma patients. ## 5. 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--- title: 'Heterogeneity in Kidney Histology and Its Clinical Indicators in Type 2 Diabetes Mellitus: A Retrospective Study' authors: - Shivendra Singh - Prem Shankar Patel - Archana Archana journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003520 doi: 10.3390/jcm12051778 license: CC BY 4.0 --- # Heterogeneity in Kidney Histology and Its Clinical Indicators in Type 2 Diabetes Mellitus: A Retrospective Study ## Abstract The heterogeneous spectrum of kidney disease in diabetes ranges from albuminuric or non-albuminuric diabetic kidney disease to non-diabetic kidney diseases. Presumptive clinical diagnosis of diabetic kidney disease may lead to an erroneous diagnosis. Material and Method: We analyzed the clinical profile and kidney biopsy of a total of 66 type 2 diabetes patients. Based on kidney histology, they were divided into—Class I (Diabetic Nephropathy), Class II (Non-diabetic kidney disease), and Class III (Mixed lesion). Demographic data, clinical presentation, and laboratory values were collected and analyzed. This study tried to examine the heterogeneity in kidney disease, its clinical indicator, and the role of kidney biopsy in the diagnosis of kidney disease in diabetes. Results: Class I consisted of 36($54.5\%$), class II 17($25.8\%$), and class III 13($19.7\%$) patients. The commonest clinical presentation was nephrotic syndrome 33($50\%$) followed by chronic kidney disease 16($24.4\%$) and asymptomatic urinary abnormality 8($12.1\%$). Diabetic retinopathy (DR) was present in 27($41\%$) cases. DR was significantly higher in the class I patients ($p \leq 0.05$). Specificity and positive predictive values of DR for DN were 0.83 and 0.81, respectively (sensitivity 0.61; negative predictive values 0.64). The Association of the duration of diabetes and the level of proteinuria with DN was statistically not significant ($p \leq 0.05$). Idiopathic MN [6] and Amyloidosis [2] were the most common isolated NDKD; whereas diffuse proliferative glomerulonephritis (DPGN) [7] was the commonest NDKD in mixed disease. Another common form of NDKD in mixed disease was Thrombotic Microangiopathy [2] and IgA nephropathy [2]. NDKD was observed in 5($18.5\%$) cases in presence of DR. We noted biopsy-proven DN even in 14($35.9\%$) cases without DR, in 4($50\%$) cases with microalbuminuria and 14($38.9\%$) cases with a short duration of diabetes. Conclusion: Almost half ($45\%$) of cases with atypical presentation have non-diabetic kidney disease (NDKD), though even among these cases with atypical presentation diabetic nephropathy (either alone or in mixed form) is commonly seen in $74.2\%$ of cases. DN has been seen in a subset of cases without DR, with microalbuminuria, and with a short duration of diabetes. Clinical indicators were insensitive in distinguishing DN Vs NDKD. Hence, a kidney biopsy may be a potential tool for the accurate diagnosis of kidney disease. ## 1. Introduction Traditionally, diabetic nephropathy (DN) is diagnosed clinically with evidence of proteinuria and diabetic retinopathy [1,2,3,4]. However, type 2 diabetes patients may develop various non-diabetic kidney diseases (NDKD) which are often missed on clinical grounds. The spectrum and prevalence of NDKD have been variably reported in different studies [5,6,7]. Remarkable heterogeneity in the spectrum and prevalence of NDKD has been demonstrated in a meta-analysis of a study involving kidney biopsy in diabetes [8]. Determining the clinical indicators suggestive of the type of nephropathy in diabetes is challenging. The sensitivity and specificity of these clinical indicators are variable. A recent study on kidney biopsy in diabetic patients has revealed the occurrence of DN or NDKD against their respective clinical indicators [5,7]. This evidence enforces kidney biopsy in diabetes as a gold standard tool for accurate diagnosis. However, the role of kidney biopsy in type 2 diabetes mellitus (DM) is debatable and remains to be elucidated [9,10]. Histological confirmation of DN or NDKD is important, particularly in the presence of atypical clinical presentation; because treatment and prognosis of NDKD are different. This study tried to examine the heterogeneity in kidney disease and its clinical indicator, and highlight the role of kidney biopsy in diagnosing kidney disease in diabetes mellitus. ## 2. Material and Method This retrospective cohort study included type 2 diabetes mellitus patients, who underwent kidney biopsies between October 2016 to October 2022. The study included a total of 66 cases, whose complete clinical data were available for analysis. Patient of age > 18 years and both gender (male and female) was included in the analysis. Patients of age < 18 years and with proteinuria < 30 mg per day were excluded from the analysis. All patients’ demographic data and clinical presentations were reviewed and recorded from hospital records. Fundoscopic evidence of diabetic retinopathy was noted for all patients. Laboratory value of urine analysis, 24 h urinary protein, Complete Blood Count, renal function test, liver function test, lipid profile, immunological marker (RA factor, C3, C4, ANA, Anti ds DNA antibody, PR3 ANCA, MPO ANCA, and Anti GBM Ab), HBsAg, HCV, and HIV were obtained from records. Findings of light microscopy, immunofluorescence, and electron microscopy examination of kidney biopsy were reviewed and noted in detail for all patients. We analyzed the demographic data, clinical presentation, and laboratory value for the clinical syndrome, the indication of biopsy, and the type of nephropathy. Standard guidelines were used to define acute kidney injury (AKI), chronic kidney disease (CKD), and nephrotic syndrome [11,12]. Proteinuria was categorized into three categories: microalbuminuria (30–300 mg/day), Sub nephrotic (>300–3500 mg/day), and nephrotic range (>3500 mg/day) proteinuria. Based on kidney histology, patients were divided into three classes—Class I (Diabetic Nephropathy), Class II (Non-diabetic kidney disease), and Class III (Mixed lesion). Further analysis was done to find out the heterogeneity of kidney diseases, their clinical indicators, and the relevance of clinical indicators in the diagnosis of kidney disease in type 2 diabetes mellitus patients. ## Statistical Analysis Statistical analysis was performed using PSPP version 1.4.1 (GNU Operating System, Free Software Foundation). Descriptive statistics were presented as the mean and SD for continuous, and number and percent for categorical variables. A one-way ANOVA variance analysis test was used to examine the significance of the difference between the three classes. Pearson’s chi-square test was used to compare the three classes for categorical variables. We used multinomial logistic regression to estimate odds ratios (ORs), associated $95\%$ confidence intervals ($95\%$ CIs), and p values to know the association between the clinical indicators and kidney histology. We calculated the sensitivity, specificity, positive predictive value, and negative predictive value of the clinical indicators for DN. Observation considered statistically significant for p-value less than 0.05. ## 3. Result A total of 66 patients (male 52; female 14) with male to female ratio of 3.7:1 was included. The mean age of patients was 51.1 ± 10.5 years. The mean serum creatinine was 2.7 ± 1.8 mg/dL. The average proteinuria of 63 patients was 3.8 ± 2.8 gm per day. Three patients were anuric. The mean duration of diabetes was 7.1 ± 3.9 years (Table 1). Based on kidney histology study, the population was grouped as Class I (Diabetic Nephropathy), Class II (Non-diabetic kidney disease), and Class III (Mixed lesion). Class I consisted of 36($54.5\%$), class II 17($25.8\%$), and class III 13($19.7\%$) patients. Class-wise patient characteristics are mentioned in the table, and the three classes did not have statistically significant differences concerning age, sex, serum creatinine, proteinuria, and duration of diabetes ($p \leq 0.05$) (Table 2). The presenting clinical syndrome and an indication of kidney biopsy were: nephrotic syndrome 33($50\%$), chronic kidney disease 16($24.2\%$), asymptomatic proteinuria and hematuria 8($12.1\%$), acute kidney injury 6($9.1\%$), and acute nephritic syndrome 3($4.5\%$) (Figure 1). Diabetic retinopathy (DR) was found in 27($40.9\%$). Isolated DN was seen in 36($54.5\%$) cases; remaining 30($45.5\%$) cases had NDKD either in isolation 17($25.8\%$) or in mixed 13($19.7\%$) form. Patients with nephrotic syndrome ($$n = 33$$) had isolated DN in 21($63.6\%$), isolated NDKD in 10($30.3\%$), and mixed disease in 2($6.1\%$) cases. In patients with chronic kidney disease; 11($68.7\%$) had isolated DN, and the remaining 4($25\%$) cases had isolated NDKD and one mixed lesion. Four ($50\%$) patients with asymptomatic urinary abnormalities had isolated DN; the remaining had isolated NDKD in 2($25\%$) and NDKD mixed with DN in 2($25\%$) cases. NDKD was the most common lesion in patients presenting with acute kidney injury in 6(isolated NDKD 1, mixed lesion 5) and acute nephritic syndrome in 3($100\%$) (Figure 2). Idiopathic MN [6] and Amyloidosis [2] were the most common isolated NDKD. Membranoproliferative glomerulonephritis, Lupus nephritis, diffuse proliferative GN, Mesangioproliferative GN, Hypertensive Nephropathy, Xanthogranulomatous pyelonephritis, Thrombotic Microangiopathy (TMA), Chronic tubulointerstitial nephritis (CTIN), and Light chain deposition disease (LCDD) were another NDKD each in one case. The commonest NDKD in the mixed lesion were DPGN [7], followed by TMA [2], IgA nephropathy [2], pauciimune GN [1], and ANCA negative renal limited vasculitis [1] (Table 3). Of 8 cases with microalbuminuria, 4($50\%$) had Diabetic Nephropathy (isolated DN 3; mixed 1) and in remaining 4($50\%$) patients had isolated NDKD. In 37 cases with nephrotic range proteinuria; the majority 24($64.9\%$) had isolated DN. However, the remaining 10($27\%$) cases had isolated NDKD, and in 3($8.1\%$) cases mixed lesions. Duration of diabetes was <5 years in 32($48.5\%$), between 5–10 years in 19($28.8\%$), >10 years in 15($22.7\%$) cases. Isolated DN was seen in 14($43.8\%$) patients with diabetes of <5 years; while the remaining cases had isolated NDKD and NDKD mixed with DN in 11($34.3\%$) and 7($21.9\%$) cases, respectively. Predominantly isolated DN was seen in 11($73.3\%$) patients with diabetes of >10 years. However, NDKD either alone or in mixed form was noted in the remaining 4($26.7\%$) cases even with diabetes of >10 years. DR was significantly higher in the class I patients ($p \leq 0.05$). Isolated DN was seen in the majority of 22($81.5\%$) patients with diabetic retinopathy. However, NDKD either alone or in mixed form was noted in the remaining 5($18.5\%$) cases even in presence of DR. Isolated DN was noted in 14($35.9\%$) patients without DR. DN was the predominant lesion in presence of DR ($81.5\%$), while NDKD either alone or in mixed form was a predominant lesion in the majority ($64\%$) in the absence of DR. Sensitivity, specificity, negative and positive predictive value of DR for diabetic nephropathy are mentioned in the Table 4. The association between clinical indicators and non-diabetic kidney disease is shown in Table 5. ## 4. Discussion In the present study, we retrospectively reviewed the demographic data, clinical features, and kidney biopsy of a total of 66 type 2 diabetes patients. The number of participants in the present analysis is low, which could be a reflection of a lack of awareness, resource limitation, limited access to a tertiary health care facility, and a reluctant strategy for a kidney biopsy at this center. This limits the power of the study and restricts the generalization of results. We found the mean age of the patient was 51.1 ± 10.5 years, and the female patient was 14($21\%$). The mean duration of diabetes in our cohort was 7.1 ± 3.9 years. The average amount of proteinuria was 3.8 ± 2.8 gm per day. The mean serum creatinine was 2.7 ± 1.8 mg/dL. The mean age and mean duration of diabetes in Class II (isolated NDKD) were comparatively lower than Class I (DN) and Class III (DN + NDKD). However, the level of 24-h proteinuria in Class II (4.2 ± 3.3 gm) was comparatively higher than in Class I (4.0 ± 2.3 gm) and Class III (2.8 ± 3.2 gm). The mean serum creatinine in Class III was higher than in class I and Class II (3.8 vs. 2.4 vs. 2.6 mg/dL), reflecting either advanced or acute worsening of the disease. The three classes did not have statistically significant differences concerning age, sex, serum creatinine, proteinuria, and duration of diabetes ($p \leq 0.05$). Our findings regarding mean age, duration of diabetes, and 24 h urine protein excretions were like other studies [13,14,15,16]. Most common presentation was nephrotic syndrome in 33($50\%$) patients. Remaining patients presented with chronic kidney disease 16($24.2\%$), asymptomatic urinary abnormality 8($12.1\%$), acute kidney injury 6($9.1\%$) and acute nephritic syndrome 3($4.5\%$). Similarly, other studies also reported the heterogeneous presentation of kidney disease in diabetes [16,17]. DN predominantly presents with either nephrotic syndrome or chronic kidney disease; while NDKD tends to present predominantly with acute kidney injury or acute nephritic syndrome [18]. Indications of kidney biopsy in diabetic patients have not been specified and remain to be elucidated. Policies of kidney biopsy in diabetes vary from center to center, and largely depend on individual factors, clinician decisions, and clinically indicated [8,10,19]. Research indicated kidney biopsy was performed in only a few studies [20]. Kidney biopsy is often considered whenever clinical course the is atypical and there is a strong suspicion of non-diabetic kidney disease. A total of 66 type 2 diabetes patients underwent kidney biopsy for atypical presentations with clinical indications during the study period. Nephrotic syndrome was the commonest indication of kidney biopsy in 33($50\%$) cases in the present series, followed by Chronic kidney disease 16($24.4\%$). At our center in routine clinical practice, we do not perform a kidney biopsy in asymptomatic type 2 diabetes patients without clinical indications, and with a typical clinical course. These could be indications of kidney biopsy for research purposes. Thus, this could be a selection bias in the present study. Our study demonstrated isolated DN in 36($54.5\%$) cases. The reported prevalence of isolated DN varies from $6.5\%$ to $94\%$ in patients with type 2 diabetes in various studies from across the world [8,19,20]. Classical way of diagnosis of diabetic kidney disease (DKD) is the appearance of progressive albuminuria with or without reduction in glomerular filtration rate (GFR) [2]. However, many times such a paradigm is not followed. In the last few decades, this idea has been changed and emerging evidence suggests a more diverse presentation of DKD, which is not consistent with the classical paradigm [3,4,21]. Recently several retrospective studies of kidney biopsy in diabetes have shown histological evidence of DKD in patients with normoalbuminuria [8,21,22]. About $20\%$ of patients with type 2 diabetes and $25\%$ with type 1 diabetes develops biopsy-proven DN without albuminuria (non-albuminuric DKD) [3,4]. Thus, the difference in diagnostic criteria of DKD and the threshold of kidney biopsy in diabetes could be the reason behind the variation in the prevalence of DKD in different studies. The prevalence of NDKD either alone or superimposed on DN varies and ranges from $3\%$ to $82.9\%$ of the total kidney biopsies [8]. We found isolated NDKD in 17($25.8\%$), and NDKD mixed with DN in 13($19.7\%$) cases. Among isolated NDKD, idiopathic MN was the most common lesion in six and followed by Amyloidosis in two patients. The commonest NDKD in the mixed lesion were DPGN [7], followed by TMA [2], IgA nephropathy [2], pauciimune GN [1], and renal limited vasculitis [1]. In a meta-analysis by Fiorentino et al., the most commonly reported NDKD were IgA nephropathy (IgAN) followed by Membranous nephropathy (MN), focal segmental glomerulosclerosis (FSGS), and tubulointerstitial nephritis (TIN) [8]. In an Indian study, the author reported membranous nephropathy (MN) as the commonest NDKD in $12.9\%$ of type 2 diabetic patients [13]. The prevalence of membranous nephropathy in patients with diabetes is variable and ranges from $11.9\%$ [23] to $30\%$ [24]. Thus, our observations also demonstrated the diversity in kidney disease in type 2 diabetes patients as in other studies [5,6,7,8,18]. Prevalence of different types of NDKD was different in the different geographical regions. FSGS is commonly seen in patients from Europe and United State; compared to IgAN in Asia [8,25]. In a study in the United States including 620 patients, the most commonly seen NDKD was (FSGS) [25]. Minimal change disease (MCD) was also reported as NDKD in diabetes [20]. This wide difference in the frequency and spectrum of NDKD in various studies could be due to diversity in the kidney biopsy policy, and regional and/or racial variations of the study cohort. It is important to identify the clinical indicators helpful in the clinical diagnosis of DN vs. NDKD, in performing the kidney biopsy to make a correct diagnosis. Multiple clinical factors like the duration of diabetes, features of DR, and level of proteinuria are used to differentiate DN from NDKD [13,14,15,16,17,18,19,20]. Classically long duration of diabetes (>10 years), presence of DR, and severe proteinuria strongly suggest DKD [25,26,27]. Whereas NDKD either isolated or mixed was more common ($56\%$ vs. $44\%$) than DN in patients with diabetes of <5 years. However, this dictum is not always followed. The majority 11($73\%$) of our patients with diabetes of more than 10 years had isolated DN and approximately $27\%$ cases had non-diabetic kidney disease despite long duration of diabetes. Similarly, Prakash et al., also reported DN as predominant lesion in patients with diabetes duration > 10 years and NDKD as predominant lesion in patients with diabetes duration < 5 years [13]. Thus, our observation supports that a longer duration of diabetes is strongly associated with DN found in other studies [19,24]. Although albuminuria is considered a clinical hallmark of DKD and the prevalence of DKD increases with the degree of proteinuria. The reverse is not true. However, recent evidence has shown that a significant number of diabetes patients had non-albuminuric DKD. Kidney histology in diabetic patients with normoalbuminuria revealed histological features of the advanced diabetic glomerular lesion, and histological changes were diverse in nature [3,4,21,22]. As we earlier discussed regarding the policy of kidney biopsy in diabetes at our center, the present study did not include non-albuminuric patients. However, now a day this subgroup represents significant proportions of diabetic individuals with reduced GFR [3,4]. Thus, this is another limitation of the present study. We observed Diabetic Nephropathy in 4($50\%$) (isolated DN 3; mixed 1) cases with microalbuminuria, and the remaining 4($50\%$) patients had isolated NDKD. Our study also demonstrated the increase in prevalence of DN with increase in level of proteinuria, but a subset of patients with sub-nephrotic ($50\%$) or nephrotic range proteinuria ($35\%$) had biopsy proven NDKD. Patients with a duration of diabetes of fewer than 5 years (odds ratio 4.97; $95\%$ CI, 0.49–50.58; $$p \leq 0.175$$) and microalbuminuria (odds ratio 2.03; $95\%$ CI, 0.28–14.46; $$p \leq 0.479$$) had a high risk of NDKD, but it was not statistically significant. Hence, recent data do not support the classical paradigm of diabetic kidney disease. Thus, our observation reasonably suggests that the level of proteinuria does not discriminate between DN and NDKD, and proteinuria is a poor predictor of the type of nephropathy in type 2 diabetes. The prevalence of diabetic retinopathy vary widely and ranges from 30–$60\%$ [13,14]. In the present study diabetic retinopathy was noted in 27($40.9\%$) cases. The Association of diabetic retinopathy with DKD is well established, although the strength of the association is variably reported [13,16,20,27,28]. A recent meta-analysis revealed that the sensitivity and specificity of DR in predicting DN were only $65\%$ ($95\%$ CI 0.62–0.68) and $75\%$ ($95\%$ CI 0.73–0.78), respectively [28]. However, in another study Tone et al., observed that evidence of DR had the highest sensitivity ($87\%$) and specificity ($93\%$) for DKD. This observation of the absence of DR as a strong indicator of NDKD was also supported by another study [27]. However, recent evidence does not agree with this concept that the mere absence of DR excludes the possibility of NDKD; because various studies had shown a high proportion (50–$70\%$) of DN cases did not have diabetic retinopathy [16,19,20,28]. Prakash et al., have reported DKD in 25–$43\%$ of cases without DR [16]. The prevalence of DR was significantly higher in the class I patients ($p \leq 0.05$). Isolated DN was seen in the majority of 22($81.5\%$) patients with diabetic retinopathy. Although, evidence of DR strongly suggest diagnosis of DKD but does not exclude the possibility of NDKD. Our findings also support the afore statement, because we noted biopsy proven NDKD (either alone or mixed form) in the remaining 5($18.5\%$) cases even in presence of DR. Isolated DN was noted in 14($35.9\%$) patients in absence of DR, while the remaining 25 patients had isolated NDKD in 15($38.5\%$) and NDKD mixed with DN in 10($25.6\%$). DN was the predominant lesion in presence of DR ($81.5\%$), while NDKD either alone or in mixed form was a predominant lesion in the majority ($64\%$) in the absence of DR. Although, specificity and positive predictive values of DR for DN were high (0.83 and 0.81, respectively); it had low sensitivity (0.61) and negative predictive values (0.64). We demonstrated that the absence of diabetic retinopathy was strongly associated with the presence of NDKD (odds ratio 9.61; $95\%$ CI, 1.79–51.45; $$p \leq 0.008$$). Our finding also backs the observation of other published studies [19,20,28]. Thus, diabetic retinopathy is a poor predictor of the type of nephropathy in type 2 diabetes. To summarize, our observation as well as the other published report reasonably suggest the heterogenous nature of kidney disease in type 2 diabetes. Emerging evidence had demonstrated that DKD may occur in a patient with a short duration of diabetes, with normo or microalbuminuria, and in absence of diabetic retinopathy. Thus, clinical indicators are a poor predictor of the type of nephropathy in type 2 diabetes and may lead to an erroneous diagnosis of DKD. Currently, there is no consensus on performing kidney biopsies in diabetes. But evidence enforcing kidney biopsy as the gold standard tool for early and accurate diagnosis of kidney disease in diabetes, many of them are treatable and reversible. ## 5. Conclusions Almost half ($45\%$) of cases with atypical presentation have non-diabetic kidney disease (NDKD), though even among these cases with atypical presentation diabetic nephropathy (either alone or in mixed form) is commonly seen in $74.2\%$ of cases. About one-third ($36\%$) of cases without DR have diabetic nephropathy, and about $20\%$ of cases with DR have non-diabetic kidney disease on kidney biopsy. An almost equal number of cases have Diabetic nephropathy and NDKD in the presence of short diabetes duration. Factors like duration of diabetes, level of proteinuria, and presence of DR are not sensitive indicators for distinguishing DN vs. NDKD. Thus, clinical diagnosis alone may give an erroneous diagnosis. 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--- title: The Important Role of m6A-Modified circRNAs in the Differentiation of Intramuscular Adipocytes in Goats Based on MeRIP Sequencing Analysis authors: - Jianmei Wang - Xin Li - Wuqie Qubi - Yanyan Li - Yong Wang - Youli Wang - Yaqiu Lin journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003525 doi: 10.3390/ijms24054817 license: CC BY 4.0 --- # The Important Role of m6A-Modified circRNAs in the Differentiation of Intramuscular Adipocytes in Goats Based on MeRIP Sequencing Analysis ## Abstract Intramuscular fat contributes to the improvement of goat meat quality. N6-Methyladenosine (m6A)-modified circular RNAs play important roles in adipocyte differentiation and metabolism. However, the mechanisms by which m6A modifies circRNA before and after differentiation of goat intramuscular adipocytes remain poorly understood. Here, we performed methylated RNA immunoprecipitation sequencing (MeRIP-seq) and circRNA sequencing (circRNA-seq) to determine the distinctions in m6A-methylated circRNAs during goat adipocyte differentiation. The profile of m6A-circRNA showed a total of 427 m6A peaks within 403 circRNAs in the intramuscular preadipocytes group, and 428 peaks within 401 circRNAs in the mature adipocytes group. Compared with the intramuscular preadipocytes group, 75 peaks within 75 circRNAs were significantly different in the mature adipocytes group. Furthermore, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of intramuscular preadipocytes and mature adipocytes showed that the differentially m6A-modified circRNAs were enriched in the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption, lysine degradation, etc. m6A-circRNA–miRNA–mRNA interaction networks predicted the potential m6A-circRNA regulation mechanism in different goat adipocytes. Our results indicate that there is a complicated regulatory relationship between the 12 upregulated and 7 downregulated m6A-circRNAs through 14 and 11 miRNA mediated pathways, respectively. In addition, co-analysis revealed a positive association between m6A abundance and levels of circRNA expression, such as expression levels of circRNA_0873 and circRNA_1161, which showed that m6A may play a vital role in modulating circRNA expression during goat adipocyte differentiation. These results would provide novel information for elucidating the biological functions and regulatory characteristics of m6A-circRNAs in intramuscular adipocyte differentiation and could be helpful for further molecular breeding to improve meat quality in goats. ## 1. Introduction Goat is one of the most widely consumed meats in the world. Compared with beef or pork, goat meat is an important source of high-quality protein, healthy fats, low-calorie intramuscular fats and saturated fats [1], and plays a crucial role in human nutrition. Meanwhile, studies have reported that increased intramuscular fat (IMF) content can improve meat quality significantly in pigs [2]. Therefore, IMF, as a main form of fat deposition, is an important factor affecting meat quality traits, such as its tenderness, juiciness and taste, making it an economically important factor in goat breeding. For meat, the content of IMF is an important trait influencing meat quality, and the differentiation of preadipocytes is a key factor affecting IMF deposition [3,4]. Thus, there are intensive efforts for exploring the molecular mechanisms underlying IMF deposition, which is of great significance for improving the quality of goat meat. In recent years, increasing evidence has suggested a potential role for non-coding RNAs (ncRNAs) in IMF deposition at the post-transcriptional level [5]. Circular RNAs (circRNAs), a novel class of endogenous ncRNAs that form covalently closed-loop structures and lack a 5′ cap or 3′ poly-A tail [6], have been widely detected in eukaryotes [7]. Previous studies have reported that circRNAs can participate in various physiopathologic processes by mediating protein–RNA interactions [8,9], such as miRNA or protein sponges [10], or modulating protein translation [11], mostly by acting as competing endogenous RNA (ceRNA) to relieve suppression. With the continuous exploration of its diverse functions, circRNAs have been shown to regulate various biological processes extensively, including fat deposition. However, studies on how circRNAs are regulated before exerting specific biological functions are still limited. m6A is a common epitranscriptomic modification of RNA, which has been found to affect the metabolism of messenger RNAs (mRNAs), including splicing, export, translation, and decay, and plays vital roles in the functions of various ncRNAs, such as long noncoding RNAs (lncRNAs), microRNAs, circRNAs, small nuclear RNAs (snRNAs), and ribosomal RNAs (rRNAs) [12,13]. Interestingly, circRNA can be regulated by m6A modification, showing a different m6A pattern from that of mRNA [14]. Recent studies have shown that m6A-modified circRNAs have been associated with diseases [15,16]. Meanwhile, Hui et al. [ 17] believed that m6A-modified circRNAs were involved in secondary hair follicle (SHF) development and cashmere growth in goats. Unfortunately, there are currently no reports on circRNA m6A modification in the intramuscular adipocyte differentiation of meat goats. Therefore, to further identify the potential function of m6A modification in regulating circRNA, our objective was to explore the regulatory differences in m6A methylation that mediate circRNA translation in the intramuscular adipocytes of meat goats before and after differentiation using MeRIP-seq (m6A-seq) sequencing technology. The findings provide new knowledge to understand the regulatory mechanisms of adipocyte differentiation and fat deposition in meat goats. ## 2.1. Identification of an Intramuscular Preadipocyte Differentiation Model in Goats In order to examine the fat deposition and lipid droplet morphology in the cultured intramuscular adipocytes, we performed Oil Red O and BODIPY staining. After 3 days of induction, lipid droplets could be observed with Oil Red O and BODIPY staining (nuclei were counterstained with DAPI) (Figure 1), which could indicate that intramuscular preadipocytes (IMPA) and adipocytes (IMA) models were successfully established. ## 2.2. Overview of the circRNA-seq and MeRIP-seq Data To investigate the circRNA profile in goat intramuscular adipocytes before and after differentiation, purified cellular RNA was subjected to circRNA-seq (m6A-seq input library) and MeRIP-seq. The sequencing raw reads were generated from the IMPA group and the IMA group. With three biological replicates, the circRNA-seq and MeRIP-seq sequencing of 12 libraries generated a total of 289.49 Gb of data, with each library averaging from 12.98 Gb to 14.22 Gb of data. The Q30 results in each library were >$93.82\%$, and the GC percentage was less than $59\%$, as listed in Table 1. Subsequently, more than $95.30\%$ of the clean reads were perfectly mapped to the goat reference genome (assembly ARS1, https://www.ncbi.nlm.nih.gov/genome/?term=goat (accessed on 11 November 2021)), and 83.78~$91.49\%$ uniquely mapped reads were obtained from the total mapped reads from the 12 samples (Table 2). The goat genome and circRNA-seq and MeRIP-seq data information are provided in Figure S1. The experimental strategy is shown in Figure 2. ## 2.3. Characteristics of m6A-Modified circRNAs in the Intramuscular Adipocytes of Goats before and after Differentiation We used circRNA-seq to compare the differences in circRNAs between intramuscular preadipocytes (IMPA) and adipocytes (IMA) in goats. We found that most circRNAs were between 200–700 bp and derived from sense-overlapping RNAs (Figure S2A,B). Moreover, circRNAs were mainly distributed on chromosome 7 (Figure S2C). The MeRIP-seq data for m6A in the IMPA and IMA groups were compared and analyzed; there were 427 m6A methylation peaks within 403 circRNAs in the IMPA group, and 428 peaks within 401 circRNAs in the IMA group. According to the differences and overlaps in m6A-modified circRNA transcripts, 64 methylation peaks and 63 circRNAs were uniquely modified in the IMPA group, and 65 methylation peaks and 61 circRNAs were uniquely modified in the IMA group. In addition, 363 peaks were consistently observed in the two groups, and 340 circRNAs within both groups were modified by m6A (Figure 3A,B). Further analysis was performed to assess the features of m6A-modified circRNAs. The number of m6A methylation peaks in each circRNA was highly similar in the IMPA and IMA groups (Figure 3C). We found that almost $61.94\%$ of methylated circRNAs hold only one m6A peak, and most circRNAs contain one to three m6A peaks, which indicates that m6A modification sites are not unique in circRNAs. Moreover, the length results of m6A-modified circRNAs in each group showed that the length of most m6A-modified circRNAs were less than 2000 bp, and the length characteristics of the two groups were similar (Figure 3D). The sources of m6A-circRNAs were most correlated with sense-overlapping RNAs (Figure 3E). Finally, chromosome distribution also revealed that m6A-methylated circRNA is more likely to be present on chromosome 7 (Figure 3F). ## 2.4. Differential Expression of m6A-Modified circRNAs in Different Goat Adipocytes Based on a p value < 0.05 and |Log2 (fold change)| > 1.5, 75 m6A methylation peaks within 75 circRNAs were screened out between the IMPA and IMA group. Among them, 44 hypermethylated peaks were within 44 circRNAs (e.g., circRNA_NUCB1), and 31 hypomethylated peaks were within 31 circRNAs (e.g., circRNA_ZMYND8), as seen from Table S1. Data visualization analysis was performed using IGV to show the differential m6A peaks between the IMPA and IMA groups (Figure 4A). The top 10 differentially methylated circRNAs with hypermethylation or hypomethylation in the IMA group compared to the IMPA group are shown in Table 3. Meanwhile, the expression profiling was identified by hierarchical clustering analysis, confirming that undifferentiated and differentiated cells exhibited dramatically differentially expressed methylation circRNAs profiles (Figure 4B). GO and KEGG pathway enrichment analyses for the differentially m6A-modified circRNA source genes were performed (p-value < 0.05). GO annotation of m6A-modified circRNAs illustrated that they were mainly enriched in cytoplasm, nucleus and metal ion binding (Figure 4C). KEGG analysis indicated that they were enriched in the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption and lysine degradation (Figure 4D). ## 2.5. Regulatory Network of the Differential m6A-circRNAs between IMA and IMPA Groups In recent years, studies have found that circRNAs are able to regulate the expression of target genes as sponges for miRNAs based on complementary base pairing. By predicting the target miRNA for both the circRNA and mRNA, we constructed a m6A-circRNA–miRNA–mRNA ceRNA interaction network. In this study, according to a max-score > 150 and max-energy < −30, a total of 12 hypermethylated circRNAs, 14 miRNAs and 55 mRNAs (Figure 5A), and 7 hypomethylated circRNAs, 11 miRNAs, and 22 mRNAs were identified in IMA and IMPA groups (Figure 5B). These associations of m6A-circRNA–miRNA–mRNA interactions are shown in detail in Table S2. In the interaction network of the two groups, many fats deposition and lipid metabolism miRNAs were predicted, such as miR-103-5p, miR-423-5p and miR-423-3p. In addition, we also found that m6A-modified circRNAs exhibited several m6A-circRNA –miRNA–mRNA regulatory pathways. For instance, m6A-circRNA _1659 may sponge two miRNAs (miR-33b-3p and miR-18a-3p) to further individually or cooperatively regulate the expression of their target genes through a ceRNA network mechanism (Figure 5B). ## 2.6. Conjoint Analysis of circRNA-Seq and MeRIP-Seq To further explore the potential function of circRNAs with m6A modification in the IMPA and IMA groups, a conjoint analysis of circRNA-seq and MeRIP-seq was performed. Based on a p value < 0.05 and |Log2 (fold change)| > 1.5, 450 differentially expressed circRNAs were detected in the two groups, including 263 upregulated circRNAs and 187 downregulated circRNAs (Figure 6A). Simultaneously, we constructed a clustered heat map to further explore the potential roles of the circRNAs (Figure 6B). Moreover, GO ontology and KEGG pathway analyses were performed to analyze the differentially expressed circRNAs. The GO analysis of the differentially expressed circRNAs illustrated that the meaningful terms ($p \leq 0.05$) may be related to lung development, protein autophosphorylation, striated muscle myosin thick filament, etc. ( Figure S3A). The KEGG enrichment showed that the top 10 significantly enriched signaling pathways were enriched based on the significantly differentially expressed circRNAs in these two groups ($p \leq 0.05$). These pathways included the MAPK signaling pathway, tight junction, lysine degradation, FoxO signaling pathway, cGMP-PKG signaling pathway, etc. ( Figure S3B). Furthermore, the correlation between the differentially m6A-modified circRNAs and the corresponding circRNA expression levels was analyzed by combining MeRIP-seq and circRNA-seq. There are 20 significantly upregulated circRNAs with hypermethylation (2 annotated genes and 18 unannotated genes), 2 downregulated circRNAs with hypomethylation (1 annotated gene and 1 unannotated gene) and 1 upregulated circRNA with hypomethylation that were found in the preadipocyte and adipocyte groups (Figure 6C). ## 2.7. Verification of circRNA Expression Profiles Using qRT-PCR To verify the reliability of circRNA-seq results, four candidate circRNAs were randomly selected from the differentially methylated circRNAs obtained from the screening, and UXT was used as an internal reference for qRT-PCR analysis. The results showed that circRNA_PAPD7 and circRNA_LMO7 were significantly upregulated during the differentiation of intramuscular adipose cells. On the other hand, circRNA_SP3 and circRNA_CHD9 were significantly downregulated during the differentiation of intramuscular adipose cells. These results were consistent with the circRNA-seq trend, indicating the credibility of the circRNA-seq results (Figure 7). ## 3. Discussion Fat deposition is a very important economic trait that determines goat production, feed efficiency and meat quality, including flavor and tenderness. Studies have shown that the differentiation of intramuscular lipid deposition is a complex biological process regulated by multiple genes, signal pathways and transcription factors [18,19,20,21]. Thus, elucidation of the molecular mechanism underlying meat quality traits in goats will have both biological and economic consequences. Over the past few years, increasing lines of evidence indicate that m6A modification in circRNA molecules plays significant roles in various cells [22,23,24]. Nevertheless, the potential roles of m6A-modified circRNA in most livestock, and especially in the differentiation of goat intramuscular preadipocytes, has remained largely unclear. To the best of our knowledge, our study is the first to screen for m6A-modified circRNA in goat preadipocytes and adipocytes using MeRIP-seq technology. CircRNAs were generated by back splicing of pre-mRNAs through different pathways. It has been confirmed that the major source of circRNAs is derived from exons and exists in a large number of eukaryotic cells [25,26,27]. Some scholars have shown that circRNAs are generated by contranscription and competition with conventional splicing [28]. However, our results indicated that the characteristics of m6A-modified circRNAs changed before and after differentiation of intramuscular adipocytes. Most of the differential m6A-modified circRNAs are longer and come from sense-overlapping regions, which means that these differential and long m6A-modified circRNAs derived from sense-overlapping regions play a more important function, providing new insights into the regulatory mechanism of m6A-modified circRNAs of different adipocytes. In the present study, approximately 75 differentially m6A-modified circRNAs were identified before and after the differentiation of goat intramuscular adipocytes. GO subcategory analysis revealed that they were mainly enriched in the cytoplasm, nucleus and metal ion binding. The KEGG enrichment analysis based on the differentially m6A-modified circRNAs demonstrated that the PKG signaling pathway, endocrine and other factor-regulated calcium reabsorption and lysine degradation play a vital role in the adipose differentiation. Maimaitiyiming et al. [ 29] suggested that increased PKG signaling stimulates brown adipocyte differentiation, promotes healthy expansion and browning of white adipose tissue, and stimulates white adipose tissue lipolysis. Endocrine and other factor-regulated calcium reabsorption is related to the immune system, and it has a critical role in adipose differentiation [30]. In addition, it has been shown that the dietary lysine to energy ratio mainly determines the rate of protein and fat deposition [31]. Yang et al. [ 32] demonstrated that lysine degradation plays a promoting role in the process of fat differentiation, which is conducive to fat deposition. These are consistent with our results. Therefore, we conclude that the different m6A-modified circRNAs might be involved in the differentiation of intramuscular preadipocytes. In recent years, a growing number of studies have found that circRNA can be used as a molecular sponge to interact with miRNA to regulate mRNA [33,34]. By integrating the data from the analyses of circRNAs, miRNAs, and mRNAs, hub ceRNAs networks were constructed for goat adipogenic differentiation. In our ceRNA network, we found that 11 downstream genes in the ceRNA pathways were strongly related to candidate m6A-modified circRNAs in the present study, suggesting that these circRNAs might play functional roles during adipogenesis. It is worth noting that fibronectin type III domain-containing protein 3B (FNDC3B) regulates white fat browning and adipogenesis [35]. Moreover, TTN (Titin) has been related to changes in intramuscular fat deposition, possibly by exerting effects on adipocyte lineage cells or on the milieux surrounding them [36]. In our study, we found that miR-103-5p was able to regulate TTN, ZNF536 and WDR76 in three ceRNA networks, and multiple circRNAs had binding sites with miR-2305. Thus, we speculated that circRNA_1944 (circFNDC3B) and circRNA_0582 (circTTN) potentially regulate goat adipogenesis. However, in-depth studies on the functions of goat circFNDC3B, circTTN, circRNA_0582 (circZNF536) and circRNA_0582 (circWDR76) on adipogenic differentiation are essential. Previous research reported that LAMA5, HDAC11, CCND2, EBF3 were associated with adipogenesis and fat deposition [37,38,39]. We found that circRNA_1689 might influence adipogenic differentiation by regulating downstream genes (LAMA5 and EBF3) through two miRNAs (miR-874-3p and miR-874-3p), and that circRNA_0873 might influence adipogenic differentiation by regulating downstream genes (HDAC11 and CCND2) through one miRNA (miR-1343). Based on the above results, we believe that the m6A-circRNAs, as a “molecular sponge” of these miRNAs, may play essential roles in establishing an optimal expression balance of their target genes during goat adipocyte differentiation, in which m6A modifications may be required, as the m6A-circRNA plays an important role in regulating the proliferation and differentiation of adipocytes and myocytes. To further reveal the relationship between circRNA and m6A modification, we performed an analysis of circRNA-seq. We found a total of 450 circRNAs with expression differences. In the conjoint analysis of MeRIP-seq, we found that a total of 23 circRNAs showed a significant association between expression and m6A modification; of these, 3 were annotated genes and 20 were unannotated genes. Earlier studies have indicated that m6A modification is closely related to circRNA expression [40]. For instance, Zhang et al. suggested that circRNA accumulation is associated with enhanced splicing at the m6A site and m6A modification may interfere with sperm motility by influencing circRNA expression levels [41]. In the present study, we showed that the expression of two m6A-circRNAs, including circRNA_0873 (circRNA_SLC8A3) and circRNA_1161 (circRNA_DEPTOR), were dramatically upregulated in adipocytes as compared to preadipocytes, and the majority of m6A-circRNAs were expressed at a medium level with a positive relationship between circRNA expression and m6A methylation modification. Thus, it can be suggested that these two m6A-circRNAs (circRNA_0873 and circRNA_1161) may be implicated in the physiological process of goat adipocyte differentiation by constituting coordinated regulatory pairs. In this process, the m6A modifications within the circRNAs might play an important role in promoting the differentiation of goat adipocytes. Additionally, the four circRNAs in the comparison of IMF before and after differentiation were verified by qPCR, and the results were basically consistent with those of RNA-seq. This shows that our RNA-seq discovery is reliable. Based on sequencing data, we considered that these circRNAs play a role in the intramuscular adipocytes of goats before and after differentiation. Although these newly identified circRNAs have not been reported in studies of intramuscular adipocyte differentiation, they can provide some preliminary data for further study. ## 4.1. Isolation and Cell Culture of Goat Intramuscular Preadipocytes Goat intramuscular preadipocytes were collected from the longissimus dorsal muscle of 7-day-old Jianzhou Daer goats ($$n = 3$$) (Sichuan Jianyang Dageda Animal Husbandry Co., Ltd., Sichuan, China). The intramuscular preadipocytes were isolated and cultured as described by Xu et al. [ 42]. ## 4.2. Preadipocyte Differentiation Induction DMEM/F12 (Hyclone, Logan, UT, USA) containing $10\%$ FBS (Hyclone, Logan, UT, USA) and 50 μmol·L−1 oleic acid (Sigma, St. Louis, MO, USA) induced differentiation of goat intramuscular adipocytes, and cells were collected at 0 and 3 days [4,43]. ## 4.3. Oil Red O and BODIPY Staining The Oil Red O staining and BODIPY staining were used to distinguish mature adipocytes from preadipocytes during the process of culture. The Oil Red signal was quantified by measuring the absorbance at 490 nm (OD 490) as a semi-quantitative assessment method to determine the extent of differentiation. The fluorescence intensity of the BODIPY signal (arbitrary units, in %) was analyzed using the ImageJ tool (NIH, Bethesda, MD, USA). ## 4.4. RNA Extraction, Library Construction, and Sequencing Total RNA from 6 samples was extracted. We have generally utilized 100 ng of RNA for library construction for MeRIP-circRNA sequencing. Briefly, the mRNA with polyA in the total RNA was enriched by Oligo-dT magnetic beads. The intact mRNA was then fragmented using an ultrasound machine. The segmented RNA was divided into two parts. One part was added to an m6A-capturing antibody to enrich the mRNA fragments containing m6A methylation (MeRIP-seq), and the other part was used as an Input to directly construct a conventional transcriptome sequencing library (circRNA-seq). The m6A antibody was enriched by magnetic beads, and the mRNA fragments containing m6A were recovered. The conventional sequencing library was constructed according to the transcriptome library construction process. Illumina Hiseq X Ten was used for high-throughput sequencing of the library. ## 4.5. Sequencing Data Analysis After paired-end sequencing, raw data were first filtered according to Q30 and GC content; fastp software (v0.20.0) was used to obtain high-quality reads. Hisat2 software (v2.1.0) was used to align high-quality reads to the goat reference genome, CIRI2 software (v2) was used for circRNA detection and identification, and the MeTDiff software was used for methylation peak calling and differential peak identification. The circBase database and Circ2Traits were used to annotate the identified circRNA. Then, DESeq2 software (v1.14.1) was used for data standardization and differentially expressed circRNA screening (log2FC ≥ 1.5, p-value ≤ 0.05). ## 4.6. Bioinformatics Analysis and Statistical Analysis The DAVID database was used to conduct GO enrichment analysis [44]. KOBAS software (http://kobas.cbi.pku.edu.cn (accessed on 14 February 2023)) [45] was used to test the statistical enrichment of differentially expressed circRNA source genes in KEGG pathways. A p value < 0.05 was considered significant. The R language (v1.42.0) and related packages were used to visualize the results. The m6A-circRNAs/miRNA interactions were predicted using miRanda (http://www.microrna.org/ (accessed on 16 September 2022)) [46]. miRanda was used to predict the downstream mRNA targets of the predicted miRNA. The R language (v1.42.0) and related packages were used to visualize the results. Additionally, statistical analysis was conducted with the SPSS 17.0 program (SPSS Inc., Chicago, IL, USA). Results are shown as the mean ± SEM and the data are representative of three biological and two technical replicates. * $p \leq 0.05$, ** $p \leq 0.01.$ ## 4.7. Validation of Gene Expression by RT-qPCR Technique Primers were designed using Primer-BLAST on the NCBI website (Table 4). First-strand cDNA was synthesized using a reverse transcription system (Takara, Shiga, Japan) according to the manufacturer’s instructions, and the cDNA was used for quantitative real-time PCR, which was carried out with the SYBR Prime Script RT-PCR Kit (Takara, Shiga, Japan). UXT was used as the housekeeping gene for normalization of the gene expressions in all samples [47]. Quantification of selected gene expression was performed using the comparative threshold cycle (2−ΔΔCT) method [48]. The experiment was repeated three times. ## 5. Conclusions In conclusion, our present study generated transcriptome-wide maps of the m6A profiles and distribution patterns of goat intramuscular adipocytes before and after differentiation based on the MeRIP-seq technique. 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--- title: The Potential Role of MiRs-139-5p and -454-3p in Endoglin-Knockdown-Induced Angiogenic Dysfunction in HUVECs authors: - Anthony Cannavicci - Qiuwang Zhang - Michael J. B. Kutryk journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003543 doi: 10.3390/ijms24054916 license: CC BY 4.0 --- # The Potential Role of MiRs-139-5p and -454-3p in Endoglin-Knockdown-Induced Angiogenic Dysfunction in HUVECs ## Abstract Hereditary hemorrhagic telangiectasia (HHT) is a rare genetic disease characterized by aberrant angiogenesis and vascular malformations. Mutations in the transforming growth factor beta co-receptor, endoglin (ENG), account for approximately half of known HHT cases and cause abnormal angiogenic activity in endothelial cells (ECs). To date, how ENG deficiency contributes to EC dysfunction remains to be fully understood. MicroRNAs (miRNAs) regulate virtually every cellular process. We hypothesized that ENG depletion results in miRNA dysregulation that plays an important role in mediating EC dysfunction. Our goal was to test the hypothesis by identifying dysregulated miRNAs in ENG-knockdown human umbilical vein endothelial cells (HUVECs) and characterizing their potential role in EC function. We identified 32 potentially downregulated miRNAs in ENG-knockdown HUVECs with a TaqMan miRNA microarray. MiRs-139-5p and -454-3p were found to be significantly downregulated after RT-qPCR validation. While the inhibition of miR-139-5p or miR-454-3p had no effect on HUVEC viability, proliferation or apoptosis, angiogenic capacity was significantly compromised as determined by a tube formation assay. Most notably, the overexpression of miRs-139-5p and -454-3p rescued impaired tube formation in HUVECs with ENG knockdown. To our knowledge, we are the first to demonstrate miRNA alterations after the knockdown of ENG in HUVECs. Our results indicate a potential role of miRs-139-5p and -454-3p in ENG-deficiency-induced angiogenic dysfunction in ECs. Further study to examine the involvement of miRs-139-5p and -454-3p in HHT pathogenesis is warranted. ## 1. Introduction Hereditary hemorrhagic telangiectasia (HHT) is a rare genetic disease inherited in an autosomal dominant fashion that can lead to life-threatening vascular dysplasia. Approximately 1 in 5000 to 8000 people are affected globally [1]. HHT patients can develop vascular malformations that form a direct connection between arteries and veins absent of capillaries, called telangiectasias and arteriovenous malformations (AVMs) [2,3]. Telangiectasias are superficial dilated blood vessels that form on the skin and mucocutaneous tissue [4]. Approximately $95\%$ of patients with HHT develop epistaxis due to nasal telangiectasias [5]. AVMs are greater in size and can develop in various locations, including the lungs, brain, liver and spine [6]. Severe complications can arise from untreated AVMs, including hypoxia, brain abscess, high-output cardiac heart failure, hypertension and ischemic and hemorrhagic stroke [6]. There is no cure for HHT, and effective pharmacological therapies are limited. It was found that mutations in three genes cause HHT, including endoglin (ENG, chromosomal locus 9q34) [7], activin-receptor like kinase 1 (ACVRL1, also known as ALK1, chromosomal locus 12q1) [8] and mothers against decapentaplegic homolog 4 (SMAD4, chromosomal locus 18q21) [9]. Additionally, mutations in growth/differentiation factor 2 (GDF2, chromosomal locus 10q11) [10] and Ras p21 protein activator 1 (RASA1, chromosomal locus 5q14) [10] create HHT-like syndromes. ENG and ACVRL1 mutations are responsible for approximately 70–$90\%$ of confirmed HHT cases and lead to HHT Type 1 and 2, respectively [11,12,13]. SMAD4 mutations are responsible for approximately 1–$2\%$ of HHT cases and can result in a combined juvenile polyposis-HHT syndrome (JP-HHT) [14]. There are over 850 known disease-causing mutations in ENG, ACVRL1 and SMAD4 (https://arup.utah.edu/database/HHT/, https://arup.utah.edu/database/SMAD4/SMAD4_welcome.php, access date: 3 November 2021) that most commonly include missense mutations, although single base pair changes, large deletions, duplications, frameshifts and substitutions have also been documented [15]. ENG, ACVRL1, SMAD4 and GDF2 are all involved in the transforming growth factor beta/bone morphogenetic protein (TGFβ/BMP) signaling pathway, while RASA1 predominately regulates PI3K/Akt signaling [16]. These pathways are integral in the regulation of various cellular processes, including growth, differentiation, apoptosis and, importantly, endothelial cell (EC) function and angiogenesis. The pathogenic role of these mutations has been confirmed in mouse models, where the loss of ENG, ACVRL1 or SMAD4 results in various vascular defects [17,18]. ACVRL1 encodes for a TGFβ receptor I that is mostly expressed on endothelial, lung and placental cells. SMAD4 is a downstream effector of the TGFβ/BMP signaling pathway that upon activation translocates to the nucleus to regulate gene expression. ENG, predominantly expressed in the endothelium, activated monocytes and macrophages, is a co-receptor that ensures a high-affinity bond between ligands and TGFβ receptors I/II. MicroRNAs (miRNAs) are short non-coding RNA molecules, approximately 21–25 nucleotides long, that regulate gene expression in a post-transcriptional manner [19]. Since their discovery in 1993 by the Ambros and Ruvkin groups, over 2000 miRNAs have been identified [20,21]. MiRNAs have been shown to be involved in a vast array of cellular processes regulating approximately $30\%$ of known genes [22,23,24]. Processed in the nucleus and cytoplasm by endoribonucleases, such as RNAase III, they exert their effects through the interaction with the 3′ untranslated region (UTR) of messenger RNA (mRNA) [25]. Typically, human miRNAs bind imperfectly and silence mRNAs through the blockage of translational machinery [22]. These low-fidelity molecules have been shown to target tens to hundreds of genes, while groups of miRNAs expressed from the same transcript, known as clusters or families, share similar target homology [22,26]. MiRNAs are involved in almost every cellular process and have been implicated in the pathogenesis of human diseases [27]. They have been shown to be reliable biomarkers, especially in oncology, and are being investigated as novel therapeutic targets [28,29]. Endoglin (ENG) is primarily expressed in endothelial cells (ECs), and loss of ENG has been shown in numerous studies to result in abnormal angiogenic function in ECs [30]. However, how ENG deficiency contributes to EC dysfunction remains to be fully understood. We hypothesized that ENG depletion results in miRNA dysregulation that contributes to EC dysfunction. To test this hypothesis, we performed a miRNA microarray analysis and RT-qPCR to identify dysregulated miRNAs in ENG-knockdown human umbilical vein endothelial cells (HUVECs) and further characterize their potential role in EC function. ## 2. Results The N shown in all figures is the number of independent experiments. ## 2.1. ENG-Knockdown HUVECs Demonstrated a Potentially Dysregulated MiRNA Profile ENG-siRNA transfection significantly depleted ENG protein in HUVECs compared with that in non-transfected and control siRNA-transfected HUVECs as shown by Western blot analysis (Figure 1). A TaqMan miRNA microarray with 377 human miRNA targets was employed to identify potentially dysregulated miRNAs in ENG-knockdown HUVECs compared with negative control siRNA HUVECs. MiRNAs that had less than a 1.5-fold change and a cycle threshold (Ct) value ≥ 30 were systematically excluded (Figure 2). Three independent miRNA microarray analyses were performed for ENG-knockdown and control HUVECs, that identified a total of 32 miRNAs as potentially downregulated (Table 1) and none as upregulated in ENG-knockdown HUVECs. ## 2.2. Significantly Reduced Levels of MiRs-139-5p and -454-3p in ENG-Knockdown HUVECs The MicroRNA Microarray Card A v2.0 used in this study detects both non-angiogenic and angiogenic miRNAs. Of the 32 potentially dysregulated miRNAs identified by the array analysis, those with unknown EC angiogenic activity, i.e., miR-99a-5p, miR-99b-5p and miR-574-3p, were not chosen for further study. MiRNAs, whose downregulation has been documented in the literature to promote tube formation in ECs, which is discordant with angiogenic dysfunction seen in ENG-deficient ECs, were not characterized further either, such as miR-191-5p, miR-125b-5p, miR-31-5p, etc. [ 31,32,33]. MiR-126-3p, one of the best-characterized angiogenic miRNAs in ECs [34], was not investigated further, as a previous study showed that ENG depletion does not affect the target genes of miR-126-3p in HUVECs [35]. Eventually, miRs-let-7b, -16-5p, -21-5p, -139-5p and -454-3p were selected for RT-qPCR validation. As shown in Figure 3, miRs-139-5p and -454-3p were significantly reduced ($$p \leq 0.0048$$ and $$p \leq 0.0062$$, respectively) in ENG-knockdown HUVECs, while the levels of miRs-let-7b, -16-5p and -21-5p were not significantly different as compared with those in controls. MiR-139-5p demonstrated a 4.4-fold decrease, and miR-454-3p demonstrated a 2-fold decrease in ENG-knockdown HUVECs, respectively. ## 2.3. Inhibition of MiR-139-5p or MiR-454-3p Had No Effect on HUVEC Viability and Proliferation In the context of HHT, the literature demonstrates that HHT Type 1 (ENG-deficient) ECs have increased rates of proliferation and viability [30]. To understand the role miRs-139-5p and -454-3p may play in HUVEC function, we inhibited these miRNAs individually and assessed HUVEC viability and proliferation with a CCK8 assay. MiRs-139-5p and -454-3p were both successfully downregulated after miRNA inhibition as shown in Supplementary Figure S2. The CCK8 assay demonstrated that the inhibition of miR-139-5p or miR-454-3p had no effect on either HUVEC viability or proliferation (Figure 4A,B, respectively). For viability, the inhibition of miRs-139-5p or -454-3p returned an OD of 0.53 ± 0.12 and 0.51 ± 0.11, respectively, compared to the negative control’s OD of 0.48 ± 0.14. In terms of proliferation, the inhibition of miRs-139-5p or -454-3p returned an OD of 0.41 ± 0.16 and 0.40 ± 0.17, respectively, compared to the negative control’s OD of 0.40 ± 0.16. ## 2.4. Inhibition of MiR-139-5p or MiR-454-3p Had No Effect on HUVEC Apoptosis Apoptotic events, determined by the flow cytometric detection of AV, were unchanged when miR-139-5p or miR-454-3p were inhibited in HUVECs compared with those in negative controls (Figure 5). The percentages of double-stained (+/+) or AV+/PI+ events or late apoptotic/necrotic cells were 16.8 ± 4.22, 18.45 ± 3.20 and 16.97 ± 3.325 for negative controls, miR-139-5p inhibition and miR-454-3p inhibition, respectively (Figure 5). The percentages of AV-stained (−/+) or PI−/AV+ events or early apoptotic cells were 29.95 ± 11.54, 30.92 ± 13.00 and 27.47 ± 9.99 for negative controls, miR-139-5p inhibition and miR-454-3p inhibition, respectively (Figure 5). Necrotic cells or only PI-stained events were barely detectable. ## 2.5. Inhibition of MiR-139-5p Augmented HUVEC Migration It has been well established in both in vitro and in vivo models that the loss of ENG results in perturbed EC migration [36,37,38]. To further understand the role miR-139-5p or miR-454-3p plays in EC function, we assessed cell migration with an Ibidi wound healing assay. The inhibition of miR-454-3p in HUVECs had no effect on migration rates compared with that in negative controls shown in Figure 6A. Interestingly, the inhibition of miR-139-5p resulted in significantly increased rates of migration (Figure 6B), as determined by the percentage (%) of open wound area, at 3, 6, 9 and 12 h compared with that in negative controls (Figure 6C). No significant differences in the percentage of open wound area were found at the start of the assay (0 h) between the miRNA inhibitor- and control-transfected HUVECs (Figure 6A,B). Images of cell migration among groups at 3, 6, 9 and 12 h are shown in Figure 6D. ## 2.6. Reduction of MiR-139-5p or MiR-454-3p Impaired Tube Formation of HUVECs In Vitro The role of ENG in angiogenesis has been well established in the general literature [30] as well as in the context of HHT, especially in mouse models [17]. However, to our knowledge, only Fernandez-L et al. have demonstrated deficient in vitro tube formation of HHT Type 1 and 2 blood outgrowth ECs (BOECs) [39]. Interestingly, they determined that the reduced ability of tube formation is correlated with reduced ENG expression in both HHT Type 1 and 2 BOECs [39]. Whether miRs-139-5p and -454-3p contribute to EC dysfunction in this regard remains to be clarified. We investigated how the inhibition of miR-139-5p or miR-454-3p affected the angiogenic capacity of HUVECs with an in vitro tube-formation assay. A significant reduction of tube formation was observed for the inhibition of miR-139-5p or miR-454-3p compared with that in negative controls based on four parameters: segments, nodes, junctions and meshes (Figure 7A). A detailed description of these parameters can be found in Supplementary Figure S3. In brief, segments refer to connected tubes, nodes are central connecting points, junctions are points with three or more connecting segments and meshes are complete ring structures. The number of segments was 90 ± 32 ($p \leq 0.01$), 103 ± 30 ($p \leq 0.05$) and 141 ± 33 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7B). The number of nodes was 237 ± 83 ($p \leq 0.05$), 254 ± 73 ($p \leq 0.05$) and 344 ± 80 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7C). The number of junctions was 67 ± 22 ($p \leq 0.01$), 75 ± 20 and 99 ± 23 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7D). Lastly, the number of meshes was 27 ± 11 ($p \leq 0.01$), 32 ± 11 ($p \leq 0.05$) and 46 ± 12 for miR-139-5p inhibition, miR-454-3p inhibition and negative controls, respectively (Figure 7E). ## 2.7. Overexpression of MiRs-139-5p and -454-3p Rescued ENG-knockdown-Induced HUVEC Dysfunction Next, we sought to explore if the overexpression of miRs-139-5p and -454-3p could rescue ENG-knockdown-induced HUVEC dysfunction. Firstly, we confirmed that HUVECs with ENG-knockdown had a significant reduction in tube formation compared with that in HUVECs transfected with control siRNA (wild type, WT), shown in Figure 8. Segments, nodes, junctions and meshes were all significantly decreased ($p \leq 0.05$) in ENGsi HUVECs (Figure 8B). For the functional rescue assay, miRs-139-5p and -454-3p were introduced into ENGsi HUVECs by transfection with miR mimics (Supplementary Figure S4). Most notably, the simultaneous overexpression of miR-139-5p and miR-454-3p in ENG-knockdown HUVECs rescued HUVEC dysfunction, shown in Figure 9. Segments, nodes, junctions and meshes were all significantly increased in ENG-knockdown HUVECs with miR-139-5p/-454-3p mimics compared with those in negative control mimics (Figure 9B). ## 3. Discussion ENG mutations cause EC dysfunction, leading to HHT Type 1. Animal studies have identified ECs as the main pathological cell in HHT [36,40]. Inducible EC-specific ENG knockout in mice results in retinal AVMs and enlarged veins [36]. Garrido-Martin et al. demonstrated the formation of skin AVMs in EC-specific ENG-knockout mice following wounding [40]. The importance of ENG in EC function has also been highlighted in various EC models, including HUVECs and HHT-patient-derived BOECs, where loss of ENG resulted in enlarged or elongated morphology, dysregulated cellular proliferation, perturbed migration and polarity, and reduced tube formation [30,37,38,39,41,42]. Fernandez-L et al. showed that BOECs derived from HHT Type 1 patients demonstrate decreased tube formation and a disorganized actin cytoskeleton [39]. These researchers also demonstrated that the reduced ability of tube formation is correlated with reduced ENG expression in both HHT Type 1 and 2 BOECs [39]. The aim of this study was to explore the role of miRNAs in EC dysfunction caused by ENG depletion, which has rarely been documented. We performed a microarray assay to identify potentially dysregulated miRNAs for further analysis. Of the five miRNAs measured by RT-qPCR, miR-139-5p and miR-454-3p were found to be significantly downregulated in ENG-knockdown HUVECs, in line with the microarray data. The inhibition of miRs-139-5p or -454-3p reduced the angiogenic capacity of HUVECs as shown by a tube formation assay. Most notably, the overexpression of miRs-139-5p and -454-3p rescued ENG-knockdown-induced angiogenic dysfunction in HUVECs. These novel findings underscore the critical role miRs-139-5p and -454-3p may play in EC function and HHT pathogenesis. A plethora of miRNAs have been identified as key regulators of EC function and ultimately, the angiogenic process. The EC-specific knockdown of Dicer, an endoribonuclease involved in miRNA biogenesis, resulted in the dysregulation of various EC-specific genes, including vascular endothelial growth factor (VEGF) receptor 2 and endothelial nitric oxide synthase [43]. The TGFβ/BMP signaling pathway has also been shown to both be regulated by and regulate various miRNAs in a multitude of cell types and disease states [44,45]. MiR-132 has been demonstrated to be upregulated during the inflammatory phase of wound healing in direct response to TGFβ$\frac{1}{2}$ and enhance the activation of TGFβ signaling by targeting Smad7 [46]. Previous work from our laboratory has demonstrated that circulating miR-210 may be a potential biomarker for the detection of untreated pulmonary AVMs [47]. We have also shown that miR-361-3p and -28-5p were significantly decreased in peripheral blood mononuclear cells (PBMCs), and miR-132-3p was downregulated in myeloid angiogenic cells from HHT patients [48,49]. Tabruyn et al. have shown that circulating miR-205 is significantly decreased and -27a significantly increased in HHT patients [50]. Recently, Ruiz-Llorente et al. identified circulating miR-370 and -10a as candidate biomarkers for the differentiation of HHT Type 1 and 2, respectively [51]. These data and the findings in the present study suggest that, apart from their widely studied role in cancer [52,53,54,55], miRNAs are involved in HHT pathogenesis and may also serve as biomarkers for HHT diagnosis. MiR-139-5p (chromosomal locus 11q13.4) has been extensively studied in the diagnosis, prognosis and tumorigenesis of various cancers, including chronic myeloid leukemia, non-small cell lung carcinoma, prostate cancer, breast cancer and glioblastoma [53]. In tumorigenesis, miR-139-5p predominately acts as a tumor suppressor and is involved in PI3K/Akt, Wnt/β-catenin, RAS/MAPK and TGFβ/BMP signaling, to name a few [53]. The role of miR-139-5p in EC function has also been explored, albeit to a lesser extent. Similarly, miR-454-3p (chromosomal locus 17q22) has also been extensively studied in oncology [54,55,56] but to an even lesser extent in EC function. Previous studies have reported that these miRNAs are critical in EC function yet have demonstrated contradicting roles. Zhang et al. demonstrated that the inhibition of miR-139-5p suppresses VEGF-induced neovascularization of human microvascular endothelial cells by targeting phosphatase and tensin homolog (PTEN) [57]. Interestingly, they also found that miR-139-5p knockdown decreases cell viability and migration [57]. In contrast, Luo et al. reported that the inhibition of miR-139-5p in HUVECs and diabetic-derived BOECs results in increased tube formation by targeting c-Jun [58]. Similar to our findings, the authors also reported that the inhibition of miR-139-5p increases HUVEC migration [58]. Papangeli et al. showed increased HUVEC migration with miR-139-5p inhibition despite demonstrating that the intravenous administration of miR-139-5p inhibitors in the retina of a mouse model results in reduced vascularized area, radial expansion and branch points, corroborating our in vitro findings [59]. Li et al. found that miR-139-5p inhibition in primary endothelial cell cultures from pancreatic tumors results in reduced tube formation and migration [60]. There are few reports on the role of miR-454-3p in EC function. Xia et al. demonstrated that miR-454-3p inhibition results in increased HUVEC tube formation [55]. However, it is difficult to determine any specific effects of miR-454-3p inhibition since tube formation was conducted in the presence of a long non-coding RNA silencer and conditioned tumor medium. Liao et al. demonstrated that the inhibition of miR-454-3p reduces human aortic endothelial cell viability and increases apoptosis [61]. The variability seen in the literature regarding the role of the miRNAs implicated in EC dysfunction can be attributed to their diverse nature. MiRNAs are extremely context-specific and promiscuous biomolecules with tens to hundreds of targets. Their role in any context is dependent on their relative expression, the relative expression of their targets and the crosstalk of multiple regulatory pathways. Different culturing protocols, EC subtypes, experimental conditions and methodologies could all contribute to variable results. Despite the complexity of miRNA function, it is clear that miRs-139-5p and -454-3p play a critical role in EC function, where their differential expression leads to EC dysfunction. Limitations of this study include: [1] only one type of EC, i.e., HUVECs, was used, and [2] targets of miRs-139-5p and -454-3p were not explored. To date, the role of any one miRNA in HHT pathogenesis has yet to be fully explored. The present study has demonstrated three novel findings: [1] ENG-knockdown HUVECs had a dysregulated miRNA profile, [2] miRs-139-5p and -454-3p were found to be significantly decreased in ENG-knockdown HUVECs, and [3] miRs-139-5p and -454-3p were critical for normal HUVEC function. Most importantly, we have shown that the inhibition of miR-139-5p or miR-454-3p resulted in angiogenic dysfunction similar to that shown in HHT Type 1 BOECs and that the overexpression of these miRNAs rescued ENG-knockdown-induced HUVEC dysfunction. The downregulation of miRs-139-5p and -454-3p in ENG-knockdown endothelial cells potentially serves as a novel mechanism in HHT pathogenesis and may be crucial in the identification of novel therapeutic targets. Further research is necessary to understand the role of miRNAs in HHT pathogenesis. ## 4.1. Culture of HUVECs HUVECs purchased from Lonza (Walkersville, MD, USA) were cultured in fibronectin-coated (10 μg/mL) T25 or T75 flasks at 37 °C and $5\%$ CO2. HUVECs were maintained in complete Endothelial Cell Growth Medium-2 (EGM-2) (Lonza, EGM-2 BulletKit, cat# CC-3162) supplemented with $5\%$ fetal bovine serum (FBS). Cells at 80–$90\%$ confluence and ≤ to the fifth passage were used for all experiments. HUVECs were detached with trypsin-EDTA (Multicell Trypsin/EDTA $0.05\%$ trypsin, 0.53 mM EDTA with sodium bicarbonate). HUVECs obtained for this study were tested negative for mycoplasma, bacteria, viruses and fungi by the supplier, and used in low passage. ## 4.2. ENG Short Interfering RNA (siRNA) Transfection This protocol was adapted from our previous work [35]. Six-well plates were seeded with HUVECs (1.5 × 105 cells/well) and cultured until 60–$80\%$ confluence (approx. 24 h). At this point, negative control siRNA- or ENG siRNA-Lipofectamine RNAiMAX complexes were added to each well of cells. The complexes were prepared as follows: 3 μL of 10 μM siRNA (ENG or negative control) and 5 μL of Lipofectamine RNAiMAX were diluted in 250 μL of Opti-MEM reduced serum medium, respectively. These diluted mixes were then combined and incubated for 15 min to allow for complex formation. The complexes were added to cells with 2.5 mL of fresh complete EGM-2 medium (final siRNA concentration: 10 nM). The cells were cultured in the media–complex mixture for 48 h and then used for experimentation. Lipofectamine RNAiMAX (cat# 13778075), Opti-MEM (cat# 31985062), Silencer Select Negative Control No. 2 siRNA (cat# 4390846) and ENG siRNA (cat# 4392420, siRNA ID s4679) were purchased from Thermo Fisher Scientific (Burlington, ON, Canada). ## 4.3. Western Blotting Cellular protein was isolated from HUVECs in RIPA Lysis Buffer (25 mM TrisHCl pH 7.6, 150 mM NaCl, $1\%$ NP-40, $1\%$ sodium deoxycholate, $0.1\%$ SDS) supplemented with a 100× Halt Protease Phosphatase Inhibitor Cocktail (1:100 dilution, Sigma, Oakville, ON, Canada). Protein concentration was measured via a Bradford assay. Protein separation (50 μg/lane) was conducted by SDS-PAGE (4 to $12\%$ Tris-Glycine gel) and electrically transferred onto a 0.2 μm nitrocellulose membrane. The membrane was blocked in 1× TBST (50 mM TrisHCl, 150 mM NaCl, pH 7.5, $0.1\%$ Tween-20) containing $5\%$ skim milk for 1 h at room temperature followed by primary antibody incubation overnight at 4 °C (ENG, 1:1000 dilution; β-actin, 1:10,000 dilution). After incubation, the membrane was washed twice with 1× TBST for 5 min. The membrane was incubated with secondary antibodies (1:5000 dilution) in a blocking buffer (1× TBST containing $5\%$ skim milk) for 1 h in the dark at room temperature. After incubation, the membranes were washed 3 times with 1× TBST for 15 min. Protein bands were visualized with the Odyssey fluorescence imaging system (LI-COR Biosciences, Lincoln, NE, USA). Densitometry analysis was performed with Image Studio Lite Quantification Software 5.0 (LI-COR Biosciences). β-actin was used as an internal loading control. Primary antibodies used: ENG, Cell Signalling Technologies (Oakville, ON, Canada), mouse, cat# 14606S, clone 3A9 and β-actin, ABclonal Technology (Woburn, MA, USA), rabbit, cat# AC026. Secondary antibodies used: Goat anti-mouse, Thermo Fisher Scientific, cat# A32742 and goat anti-rabbit, LI-COR Biosciences, cat# 926-32211. ## 4.4. Total RNA Isolation from HUVECs Total RNA was isolated from HUVECs with a Qiagen RNeasy Mini Kit (cat# 217004, Qiagen, Toronto, ON, Canada). Cells in a well of a 6-well plate were scraped in 700 μL of *Qiazol lysis* reagent and transferred to a 1.5 mL Eppendorf tube. The mixture was incubated for 5 min at room temperature. After incubation, 140 μL of chloroform was added and shaken vigorously for 15 s. The mixture was incubated at room temperature for 3 min and centrifuged at 12,000× g for 15 min at 4 °C. After centrifugation, 300 μL of the supernatant was carefully extracted without disruption of the interphase. Subsequently, 1.5 volumes or 450 μL of $100\%$ ethanol was added and mixed thoroughly by pipetting. To capture the RNA, 700 μL of this mixture was added to an RNeasy Mini column and centrifuged at 10,000× g for 15 s at 4 °C. The column was then washed with 500 μL of Buffer RPE at 10,000× g for 15 s at 4 °C. This was repeated with a 2 min centrifugation. Then, the column was washed with $100\%$ ethanol and centrifuged for 1 min at 10,000× g at 4 °C. Finally, RNA was eluted with 30 μL of RNase-free water at 10,000× g for 1 min at 4 °C. A NanoDrop 2000 spectrophotometer was used to assess the concentration and quality of RNA before storage at −80 °C. All components used were DNase, RNase and pyrogen-free. ## 4.5. MiRNA Microarray of Total RNA from HUVECs To profile miRNAs in HUVECs, a TaqMan Low-Density MicroRNA Microarray (Thermo Fisher Scientific, Card A v2.0, cat# 4398965) covering 377 human miRNAs was used. Total RNA samples were reverse-transcribed into cDNA with a TaqMan MicroRNA Reverse Transcription (RT) Kit (cat# 4366596) and Megaplex RT Primers. The total volume of the RT reaction was 7.5 μL and comprised 3 μL of total RNA (600 ng), 0.8 μL of Megaplex RT primers (10×), 0.2 μL of dNTPs (100 mmol/L), 1.5 μL of MultiScribe Reverse Transcriptase (50 U/μL), 0.8 μL of 10× RT buffer, 0.9 μL of MgCl2 (25 mmol/L), 0.1 μL of RNase inhibitor (20 U/μL) and 0.2 μL of nuclease-free water. The thermocycling protocol for RT was performed as follows: 40 cycles of 16 °C for 2 min, 42 °C for 1 min, and 50 °C for 1 s followed by 85 °C for 5 min and 4 °C hold. The total reaction volume for PCR was 900 μL and comprised 450 μL of 2× TaqMan Universal PCR Master Mix (no AmpErase UNG), 444 μL of nuclease-free water and 6 μL of Megaplex RT product. Then, 100 μL of diluted RT product was dispensed in each of the 8 ports of the Array Card A v2.0. The card was sealed and centrifuged twice at 1200 rpm for 1 min. PCR was performed on a ViiA 7 Real-Time PCR System (Applied Biosystems, Waltham, MA, USA) with a 384-well TaqMan Low-Density Array block. The results were analyzed using RQ Study software 1.4 (Thermo Fisher Scientific) and normalized to U6 snRNA as determined by the NormFinder Excel plugin (https://moma.dk/normfinder-software, access date: 23 February 2021). Select miRNAs of interest were determined based on a fold change of 1.5 or greater and <30 Ct value [62,63]. ## 4.6. Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) for MiRNA Validation As RT for microarray analysis was completed in a single reaction tube using pooled primers (https://assets.fishersci.com/TFS-Assets/LSG/manuals/cms_054742.pdf, access date: 9 December 2022) that may result in mis-priming between two different primers or between a primer and an RNA template, reducing the accuracy of array results, RT-qPCR was performed to measure each select miRNA to validate the array data. The RT reaction was carried out with a total volume of 15 μL consisting of 7 μL of RT master mix, 3 μL of 5× RT primer and 5 μL of RNA sample (total RNA 20 ng). For each reaction, the RT master mix was prepared as follows: 0.15 μL of 100 mM dNTPs, 1 μL of (50 U/μL) MultiScribe Reverse Transcriptase, 1.5 μL of 10× reverse transcription buffer, 0.19 μL of (20 U/μL) RNase inhibitor and 4.16 μL of nuclease-free water. RT was performed on a Veriti 96-well thermal cycler according to the following protocol: 16 °C for 30 min, 42 °C for 30 min, 85 °C for 5 min and 4 °C hold. PCR was performed in a total volume of 10 μL consisting of 1 μL of RT product, 0.5 ul of 20× miRNA PCR primer, 5 μL of 2×TaqMan Fast Advanced Master Mix and 3.5 μL of nuclease-free water. PCR was performed on a QuantStudio 7 Flex Real-Time PCR System (Thermo Fisher Scientific) according to the following thermocycling protocol: 95 °C for 20 s and 40 cycles of 95 °C for 1 s and 60 °C for 20 s. Relative quantification of the expression of individual miRNAs against endogenous U6 snRNA was carried out. ## 4.7. MirVana miRNA Inhibitor or Mimic Transfection For miRNA inhibitor transfection, six-well plates were seeded with HUVECs (1.5 × 105 cells/well) and cultured until 60–$80\%$ confluence (approx. 24 h). MirVana miRNA inhibitors (Thermo Fisher Scientific, cat# 4464084; hsa-miR-139-5p, Assay ID MH11749; hsa-miR-454-3p, Assay ID MH12343) and MiRNA Negative Control #1 (Thermo Fisher Scientific, cat# 4464076) were thawed on ice and spun down before use. MiRNA inhibitor/transfection reagent complexes were generated as follows: 5 μL of Lipofectamine RNAiMAX and 5 μL of 10 μM miRNA inhibitor or negative control were diluted in 125 μL of Opti-MEM reduced serum medium, separately. The diluted reagent and inhibitor were then mixed, incubated for 5 min at room temperature and added to cells replenished with 1.75 mL of fresh complete EGM-2 medium (final miRNA inhibitor concentration: 25 nM). The cells were cultured for 24 h and then used for experimentation. For miRNA mimic transfection, HUVECs were transfected with ENG siRNA and cultured for 24 h as described above. Subsequently, 5 μL of mimics (2.5 μL of 10 μM miR-139-5p plus 2.5 μL of 10 μM miR-454-3p) or 5 μL of miRNA-negative control was used for transfection of ENG-knockdown HUVECs, which was done in the same manner as with miRNA inhibitors. The cells were cultured for another 24 h after mimic transfection for the tube formation assay. ## 4.8. Cell Viability and Proliferation Assay A cell-counting kit-8 (CCK8/WST-8) assay was used for the measurement of cellular viability and proliferation (Sigma, cat# 96992). Ninety-six-well plates were seeded with HUVECs (5 × 103 cells/well for viability, and 2.5 × 103 cells/well for proliferation). The cells were cultured for 24 h in complete EGM-2 medium and then transfected as described above. After transfection, the cells were either supplemented with fresh, complete EGM-2 medium (proliferation) or endothelial basal medium-2 (EBM-2) without serum (viability) and cultured for 24 h. WST-8 was then added, and the cells were incubated for 4 h at 37 °C and $5\%$ CO2. Subsequently, the absorbance (450 nm) was measured with a microplate reader (endpoint analysis) and compared between different groups of cells. All conditions were carried out in triplicate. ## 4.9. Apoptosis Assay Apoptosis was measured via flow cytometric detection of Annexin V (AV). HUVECs were transfected with MirVana miRNA Inhibitors and Negative Control #1 as described above. Appropriate fluorescence controls were used, including unstained and double-stained (AV and propidium iodide (PI)) negative controls (healthy cells) and unstained, single-stained (AV or PI) and double-stained positive controls (Supplementary Figure S1). Positive controls were generated with hydrogen peroxide (10 mM H2O2) treatment for 1–2 h at 37 °C and $5\%$ CO2. The cells were detached with PBS containing 1 mM EDTA for analysis. Positive controls were spiked with negative controls (approx. $50\%$ cell viability) to ensure a background level of healthy cells for appropriate gating. The cells were resuspended at a concentration of 1 × 103 cells/μL in cold 1× Annexin V Binding Buffer (BD Pharmingen, Mississauga, ON, Canada, cat# 51-66121E). Then, 100 μL of each cell suspension was incubated with either 0.5 μL of Alexa Fluor (APC channel) AV (BioLegend, San Diego, CA, USA, cat# 640911), 1.5 μL of PI (PE-CF594-A channel) (BD Pharmingen, cat# 51-66211E) or both at room temperature for 15 min in the dark. After incubation, the cells were put on ice and supplemented with 200 μL of cold 1× Annexin V Binding Buffer (final volume of 300 μL). The cells were analyzed via flow cytometry immediately after staining on a BD LSRFortessa X-20 Cell Analyzer with BD FACSDiva Software 6.1.2. Analysis of flow cytometric data was conducted with FlowJo 10.8.1 software. Forward/side scatter scatterplots were used to exclude cellular debris and doublets of 1 × 104 recorded events. ## 4.10. Cellular Migration Assay The cellular migration assay was performed with an Ibidi wound healing assay (culture-insert 2 well, Ibidi, Martinsried, Germany, cat# 81176) in a 12-well plate. HUVECs were cultured, transfected and detached as described above. Ibidi 2-well culture inserts were placed in the center of the well with slight pressure to ensure adhesion. In each well of the Ibidi 2-well culture inserts, 70 μL (28,000 cells) of cells was seeded. The cells were incubated at 37 °C and $5\%$ CO2 for 24 h with fresh, complete EGM-2 medium until confluent. The plate was handled carefully to prevent shaking. The cells were then serum-starved (EBM-2 medium, $0.5\%$ FBS) for 4 h, and the insert was gently removed with sterile tweezers to create an open wound area. The cells were washed with warm phosphate-buffered saline (PBS) and replenished with serum-reduced EBM-2 medium ($0.5\%$ FBS). Cell migration was carried out at 37 °C under an atmosphere of $5\%$ CO2 and live-imaged for 12 h with a Hamamatsu Camera and a Zeiss Axio Observer microscope (10× magnification) with Zen Pro 3.6 software (Zeiss Canada Ltd., Toronto, Canada). The images were processed with Zen 3.3 Lite (Blue Edition) and analyzed with TScratch 1.0. The percent of the open wound area of 5 fields was calculated and averaged. All conditions were done in duplicate. ## 4.11. Tube Formation Assay Geltrex LDEV-free reduced growth factor basement membrane matrix (Gibco, Burlington, ON, Canada, cat# A1413201) was used. The Geltrex basement membrane matrix was thawed overnight in a 4 °C fridge. Once thawed, it was mixed well and aliquoted (80 μL/well) into a 96-well plate (on ice) with chilled pipette tips. To prevent air bubble formation, the basement membrane was dispensed without a full stop, and the plate was centrifuged at 300× g for 10 min at 4 °C. Then, the coated plate was incubated at 37 °C and $5\%$ CO2 for 30 min. HUVECs were cultured and transfected as described above. The cells were serum-starved for 4 h and detached with trypsin-EDTA, then resuspended at 2 × 105 cells/mL in complete EGM-2 medium. Each coated well received 100 μL of cell suspension (2 × 104 cells/well). Tube formation was carried out at 37 °C under an atmosphere of $5\%$ CO2 and live-imaged with a Hamamatsu Camera and a Zeiss Axio Observer microscope (5× magnification) with Zen Pro 3.6 software. The images were processed at the 16 h time point with Zen 3.3 Lite (Blue Edition) and analyzed with Angiogenesis Analyzer 1.0 software for ImageJ2 or Fiji. All conditions were done in duplicate. ## 4.12. 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--- title: New Insights into the Identification of Metabolites and Cytokines Predictive of Outcome for Patients with Severe SARS-CoV-2 Infection Showed Similarity with Cancer authors: - Susan Costantini - Gabriele Madonna - Elena Di Gennaro - Francesca Capone - Palmina Bagnara - Mariaelena Capone - Silvia Sale - Carmine Nicastro - Lidia Atripaldi - Giuseppe Fiorentino - Roberto Parrella - Vincenzo Montesarchio - Luigi Atripaldi - Paolo A. Ascierto - Alfredo Budillon journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003544 doi: 10.3390/ijms24054922 license: CC BY 4.0 --- # New Insights into the Identification of Metabolites and Cytokines Predictive of Outcome for Patients with Severe SARS-CoV-2 Infection Showed Similarity with Cancer ## Abstract SARS-CoV-2 infection is characterized by several clinical manifestations, ranging from the absence of symptoms to severe forms that necessitate intensive care treatment. It is known that the patients with the highest rate of mortality develop increased levels of proinflammatory cytokines, called the “cytokine storm”, which is similar to inflammatory processes that occur in cancer. Additionally, SARS-CoV-2 infection induces modifications in host metabolism leading to metabolic reprogramming, which is closely linked to metabolic changes in cancer. A better understanding of the correlation between perturbed metabolism and inflammatory responses is necessary. We evaluated untargeted plasma metabolomics and cytokine profiling via 1H-NMR (proton nuclear magnetic resonance) and multiplex Luminex assay, respectively, in a training set of a limited number of patients with severe SARS-CoV-2 infection classified on the basis of their outcome. Univariate analysis and Kaplan–Meier curves related to hospitalization time showed that lower levels of several metabolites and cytokines/growth factors, correlated with a good outcome in these patients and these data were confirmed in a validation set of patients with similar characteristics. However, after the multivariate analysis, only the growth factor HGF, lactate and phenylalanine retained a significant prediction of survival. Finally, the combined analysis of lactate and phenylalanine levels correctly predicted the outcome of $83.3\%$ of patients in both the training and the validation set. We highlighted that the cytokines and metabolites involved in COVID-19 patients’ poor outcomes are similar to those responsible for cancer development and progression, suggesting the possibility of targeting them by repurposing anticancer drugs as a therapeutic strategy against severe SARS-CoV-2 infection. ## 1. Introduction The clinical spectrum of SARS-CoV-2 infection ranges from asymptomatic infection to critical illness leading to hospitalization and intensive care unit (ICU) admission. The most common symptoms observed in infected patients are fever or chills, cough, shortness of breath or difficulty breathing, fatigue, muscle or body aches, headache, loss of taste or smell, sore throat, congestion or runny nose, nausea or vomiting and diarrhea [1]. There is an urgent need for effective therapeutic strategies and for the identification of novel biomarkers associated with poor patient outcomes. In this context, many researchers are applying -omics techniques to detect mutations, discover drug targets and define the biochemical mechanisms involved in SARS-CoV-2 infection and spread. Therefore, all the efforts provided by -omics-scale investigations and applied to COVID-19 research have been defined with the term COVID-omics [2]. COVID-omics approaches have been so far directed to identify and track new variants, to better understand mechanisms of the disease progression as well as to unveil novel drug targets and vaccines [2,3]. Thus, by genomics and transcriptomics, different SARS-CoV-2 mutations, responsible for the occurrence of new variants, have been identified. For example, proteomics and metabolomics approaches have been applied to body fluids, tissues and cells to understand functional alterations due to virus infection, thus suggesting new disease markers to monitor over time [2]. A lipidomic analysis allowed the identification of COVID-19-associated lipid dysregulation, thus suggesting novel drug targets to prevent coronavirus infection [4]. Recently, multiomics data integration obtained from samples from multiple biological matrices (i.e., bronchoalveolar lavage fluid, blood, throat swabs, cell lines, tissues) has been suggested for a better understanding of the COVID-19 pathophysiological processes, the prediction of patient outcomes, and the definition of new molecular targets for therapeutic interventions [5]. In recent years, our group has focused on the application of cytokine profiling and metabolomics approaches to patients with different diseases, including cancers [6,7,8,9,10,11]. Cytokine-release syndrome (CRS) often develops in patients with a severe form of SARS-CoV-2 infection [12]. This process is referred to a “cytokine storm”, which is induced by macrophages and other innate immune cells; is characterized by the release of proinflammatory cytokines such as IL-1β, IL-6 and TNF-α; and leads to multiple organ failure, widespread damage, and fatal clinical outcomes [13,14,15]. Therefore, identifying the key cytokine networks can enable the development of treatment strategies to block this cytokine storm, such as the cytokine-neutralizing antibodies sarilumab and tocilizumab (targeting the IL-6 receptor), as well as adalimumab and infliximab (targeting TNF-α) [16]. In this context, it is noteworthy that COVID-19 disease and cancer share overlapping inflammatory mechanisms and outcomes [17]. Specifically, the host immune system is involved in cancer development by inducing inflammatory responses [18]. Furthermore, cancer immunity contributes to cancer phenotypes and is associated with compromised immune checkpoints, such as programmed cell death protein 1 (PD-1) or its ligand (PD-L1) [19]. Hence, cancer inflammation favors carcinogenesis, and alterations in several inflammatory cytokines contribute to immune evasion, promoting tumor growth and spread [18]. Some authors have discussed that IL-6 production is enhanced during SARS-CoV-2 infection, as well as during other viral infections associated with the initiation of several cancers, such as hepatitis B virus (HBV), hepatitis C virus (HCV), human immunodeficiency virus (HIV) and human papilloma virus (HPV). Thus, this suggested a potentially direct interaction between SARS-CoV-2 and virus-associated cancers, leading to the hypothesis that IL-6 could bridge the gap between COVID-19 and virus-mediated cancers [20]. Moreover, SARS-CoV-2 infection induces modifications in host metabolism, including pathways related to amino acids, energy generation, and lipids, leading to metabolic reprogramming similar to the metabolic changes contributing to cancer development [21]. Several studies were published regarding the evaluation of the serum levels of metabolites in patients with SARS-CoV-2 infection, which provided evidence that dysregulated metabolites correlated with disease severity [22,23,24,25]. Additionally, since the 1960s, an association between metabolism and immunity has been reported [26] and represents a putative determinant of the antitumor immune response in cancer [27]. For example, IL-6 was found to be able to modulate glucose and lipid metabolism, highlighting the key role of cytokines in host metabolism reprogramming [28,29]. Recent studies have shown several dysregulated metabolic pathways linked to hyperinflammation in SARS-CoV-2 patients with severe infection [30,31]. Hence, since studies identifying novel therapeutic strategies to target inflammation and altered metabolism in cancer are ongoing [32,33,34], a better understanding of the link between perturbed metabolism and inflammatory responses in patients with SARS-CoV-2 infection is necessary. Therefore, in this study, we evaluated metabolomics using an 1H-NMR (proton nuclear magnetic resonance) approach, as well as cytokines, chemokines and growth factors via multiplex Luminex assay, in the plasma of patients with severe SARS-CoV-2 infection, in order to identify novel potential biomarkers to predict patient outcome and novel therapeutic targets. We tested a training set of patients, validated the results in a validation set and then compared the results with those obtained from healthy donor samples. ## 2.1. Metabolomic Profiling of Plasma Samples from SARS-CoV-2 Patients by 1H-NMR Blood samples from a group of thirty-six patients with severe SARS-CoV-2 infection were collected and classified into two groups, “Exitus” and “Good Prognosis”, on the basis of their outcome, as reported in the Methods section (Table 1). To evaluate whether plasma metabolomic profiling may be informative when predicting their outcome risk, we took advantage of an 1H-NMR approach analyzing the collected plasma samples from both patient’s groups. Sparse partial least squares discrimination analysis (sPLS-DA) ($18.8\%$ of the total variance) showed that the “Exitus” compared to “Good Prognosis” plasma metabolomics profiles grouped into two different clusters (Figure 1A). An analysis of the PLS loading was then conducted to identify the metabolites found to be most relevant to the class separation (as reported in the Methods section). As shown in the loading plot reporting the top 10 1H₋NMR signals that were significantly different between the two groups, higher levels of 3-hydroxybutyrate, creatinine, glucose, lactate, leucine and phenylalanine and lower levels of glutamine, glycine and sarcosine were evidenced in the “Exitus” group (Figure 1B,C). Notably, two 1H₋NMR signals for phenylalanine were observed, reinforcing the significance of its differential expression between the two patient groups. Moreover, these metabolites were used to perform a metabolite-set enrichment analysis that highlighted a complex interplay between several different metabolic pathways and metabolites (Figure 1D; Table S1). In detail, aminoacyl-tRNA biosynthesis; glycolysis/gluconeogenesis; glyoxylate and dicarboxylate metabolism; glycine, serine and threonine metabolism; phenylalanine, tyrosine and tryptophan biosynthesis; the synthesis and degradation of ketone bodies; nitrogen metabolism; and valine, leucine and isoleucine biosynthesis emerged to play a role in discriminating the plasma metabolic profiles of the two groups. A validation set comprising twenty-four patients with severe SARS-CoV-2 infection, classified as “Exitus” or “Good Prognosis”, twelve for each group (Table S2), was also tested, confirming a clear separation in the score plot (Figure S1A). Notably, the validation set the “Exitus” group was also characterized by significant higher levels of 3-hydroxybutyrate, creatinine, glucose, lactate, leucine and phenylalanine and lower levels of glutamine, glycine and sarcosine (Figure S1B). Furthermore, to add mechanistic insights to our findings, the plasma metabolomics profiling of the first group of thirty-six SARS-CoV-2-infected patients was compared with that of twelve healthy donors (CTRL). As expected, a clear separation between the two groups was evidenced in the score plot (Figure 2A). Interestingly, a targeted analysis of those top 1H₋NMR proton signals reported above (Figure 1C), which discriminate “Exitus” vs. “Good Prognosis” patients, similarly distinguish, with same trend, SARS-CoV-2-infected patients from CTRL (Figure 2B). Next, to establish the optimal cutoff values for the metabolites selected by sPLS-DA, we performed receiver operating characteristic (ROC) curve analysis, which led to area under the curve (AUC) values ranging between 0.63 and 0.83 (Figure S2). Based on the metabolite parameter cutoff values, univariate and multivariate analyses were then conducted to evaluate metabolites potentially associated with patient outcome. Univariate analysis demonstrated that 3-hydroxybutyrate ($$p \leq 0.012$$), lactate ($$p \leq 0.0078$$), leucine ($$p \leq 0.042$$) and phenylalanine ($$p \leq 0.0022$$) predicted SARS-CoV-2-infected patient outcomes (Table 2). As shown by Kaplan–Meier curves related to hospitalization time, lower levels of 3-hydroxybutyrate, lactate, leucine and phenylalanine correlated with a more favorable outcome (Figure 3). Notably, in multivariate analysis, high levels of lactate and phenylalanine retained a significant prediction for survival (Table 2). ## 2.2. Cytokine Profiling of Plasma Samples from SARS-CoV-2 Patients by Multiplex Luminex Assay Moreover, we evaluated the cytokine levels in thirty-six plasma samples from SARS-CoV-2 patients to verify whether the “Exitus” and “Good Prognosis” groups had different levels of pro- and anti-inflammatory cytokines (Figure S3). The sPLS-DA plot ($22.6\%$ of the total variance) showed that the two groups were clearly assembled into two different clusters (Figure 4A). As shown in the loading plot, the “Exitus” group was characterized by higher levels of CXCL9, CXCL10, HGF, IL-6, IL-8 and SCF and lower levels of CTACK, IL-4, IL-9 and PDGF-ββ (Figure 4B and Figure S4). To determine the optimal cutoff values for the significant cytokines, ROC curve analysis was performed, which revealed AUC values ranging between 0.684 and 0.835 (Figure S5). Univariate analysis demonstrated that CXCL9 ($$p \leq 0.0001$$), CXCL10 ($$p \leq 0.039$$), HGF ($$p \leq 0.0001$$), IL-6 ($$p \leq 0.032$$) and SCF ($$p \leq 0.016$$) were able to predict patient outcome (Table 3). As shown by Kaplan–Meier curves related to hospitalization time, lower levels of CXCL9, CXCL10, HGF, IL-6, and SCF correlated with a good outcome in these patients (Figure 5). Notably, in multivariate analysis, high HGF levels retained a significant prediction of survival (Table 3). ## 2.3. Identification of Predictive Signatures Finally, we evaluated the predictive capacity of all the possible combinations of the significant metabolites and cytokines selected via univariate analysis (3-hydroxybutyrate, lactate, leucine, phenylalanine, CXCL9, CXCL10, HGF, IL-6, SCF) using a support vector machine (SVM) algorithm. Notably, only the combination of HGF, lactate and phenylalanine levels, the two metabolites and the only cytokine that also had a significant result during multivariate analysis, showed a significant predictive capacity for survival. Specifically, ROC curve analysis performed using the combination of HGF, lactate and phenylalanine levels led to an AUC value equal to 0.793 ($95\%$ CI: 0.053–0.947) (Figure 6A). Indeed, the combined analysis of the levels of these analytes classified 20 patients in the “Good Prognosis” group and 10 in the “Exitus” group (Figure 6B) and exhibited a positive predictive value of $83.3\%$ (probability of correct identification of the “Good Prognosis” group) and a negative predictive value of $83.3\%$ (probability of correct identification of “Exitus” group), predicting the outcome of $83.3\%$ (accuracy) of the patients. We also evaluated the predictive capacity of lactate and phenylalanine in the validation set using the same SVM algorithm and verified that the combined analysis of the levels of these two metabolites classified 11 patients in the “Good Prognosis” group and 9 in the “Exitus” group (Figure 6C,D), predicting the outcome of $83.3\%$ (accuracy) of the patients, in the same way as in the first analyzed set. ## 3. Discussion In the last two years, many studies have been published regarding the evaluation of the serum levels of cytokines and metabolites in patients with severe SARS-CoV-2 infection. Different metabolite/cytokine profiles have been identified, despite the fact that a complete understanding of how host metabolism correlates with inflammatory responses and, above all, with COVID-19 patient’s outcome is still missing. Our study evaluated untargeted plasma metabolomics and cytokine profiling in a training set of a limited number of patients with severe SARS-CoV-2 infection classified on the basis of their outcome. Notably, the metabolites identified in the training set as able to discriminate patients who died during infection (“Exitus”) from those recovering (“Good Prognosis”), were also confirmed in a validation set comprising additional COVID-19 patients with similar characteristics. Interestingly, these metabolites were also able to discriminate COVID-19 patients from healthy controls, mechanistically suggesting a correlation with poor outcome and confirming somehow the consistency of our data. Similarly, the plasma levels of a large panel of cytokines also clearly distinguish patients based on their outcome. Furthermore, univariate analysis and Kaplan–Meier curves related to hospitalization time showed that lower levels of four metabolites, such as 3-hydroxybutyrate, lactate, leucine and phenylalanine, and of five cytokines/growth factors, such as CXCL9, CXCL10, HGF, IL-6 and SCF, correlated with a good outcome in these patients. However, after the multivariate analysis, only HGF, lactate and phenylalanine retained a significant prediction for survival. On these bases, taking advantage of SVM, we built a multiple biomarker model, that, by combining the plasma levels of HGF, lactate and phenylalanine, evaluated at the time of hospitalization, was able to correctly classify patients from the training set with their outcome with very good accuracy. Notably, we confirmed this result on the validation set using only lactate and phenylalanine, with similar accuracy, suggesting the critical role of these two metabolites and their potential as combined prognostic biomarkers for hospitalized SARS-CoV-2-infected patients to be evaluated together with conventional clinical parameters. On the other hand, our data also suggest that the highlighted cytokines and metabolites, particularly those that emerged as statistically significant after univariate analysis, could be related with COVID-19 pathogenesis, thus also representing potential novel therapeutic targets. In this regard, we found similarities between the altered analytes emerging from the present study and the dysregulated cytokines and metabolites that we and many others have found in the peripheral blood of cancer patients being associated with outcome. For example, higher levels of the pro-inflammatory cytokines and chemokines we have selected in the present study, were also found in cancer patients, because of the strict similarity between the inflammatory mechanisms in patients with severe SARS-CoV-2 infection and those with cancer, and the connection with outcome in both patient groups. In details, in support of our data, other groups reported higher serum levels of IL-6 and IL-8 in patients with SARS-CoV-2 infection at the time of hospitalization. Multivariate analysis showed that IL-6 levels were an independent and significant predictor of disease severity and death in COVID-19 patients [13]. Laing et al. [ 2020] demonstrated that higher serum levels of CXCL10, IL-6 and IL-10 correlated with disease progression and hospitalization time in SARS-CoV-2-infected patients [14]. Conversely, it is known that IL-6 serum levels correlated with a poor prognosis, tumor burden, survival and progression in different cancers [35], thus being proposed as an anticancer therapeutic target [36]. Recently our group demonstrated that higher levels of IL-6 and CXCL10 were significantly associated with poor disease-free survival in metastatic colorectal cancer (mCRC) patients treated with bevacizumab plus oxaliplatin-based regimens [37]. A recent review article confirmed the significance and mechanism of action of CXCL9, CXCL10 and its receptor (CXCR3) in the development and progression of many tumors [38]. On these bases, and after our experience with cancer patients, we and others proposed to repurpose the monoclonal antibody Tocilizumab, an antagonist of interleukine-6, for COVID-19 therapy, an approach that was actually included in treatment guidelines [16,39,40]. Alongside this successful experience, we suggest that anticancer drugs, which were able to target the analytes we selected in the present study, can be considered as potential treatments against severe SARS-CoV-2 infection. The activation of AKT signaling, a well-known activated pathway involved in cancers, is involved in the induction of chemokine transcription in response to SARS-CoV-2 infection in a preclinical model, and treatment with the AKT inhibitor GSK690693 markedly reduced CXCL9, CXCL10 and CXCL11 gene expression [41]. Moreover, these data were confirmed in samples from COVID-19-positive individuals displaying marked increases in CXCL9, CXCL10 and CXCL11 transcripts, and an upregulation of components of the AKT signaling pathway was observed via pathway analysis performed on transcriptomic data from these patients [41]. Perreau et al. [ 2021] showed that in addition to the levels of IL-6, CXCL9 and CXCL10, serum HGF levels were significantly higher in hospitalized ICU patients than in those who were not hospitalized in the ICU. In addition, these authors identified HGF and CXCL13 as biomarkers of disease severity and predictors of ICU admission and death [42]. The increased serum level of HGF, in addition to other analytes, as a marker of COVID-19 severity, was also reported in other studies, although these were conducted using a small number of patients [43,44]. Xu et al. [ 2020] reported that the concentrations of SCF as well as HGF, IL-6, IL-8, CXCL9 and CXCL10 were significantly higher in fatal than severe and/or mild patients with SARS-CoV-2 infection, which is consistent with our data. Indeed, the levels of SCF, in addition to the levels of HGF, IL-6 and IL-8, were substantially higher in fatal patients during the late stages of the disease, especially at day 14 after diagnosis, and, hence, correlated with death in these patients [45]. Regarding metabolic pathway alterations, in accordance with our data, Meoni et al. evidenced an increase in 3-hydroxybutyrate levels in the plasma of COVID-19 patients compared with healthy controls, and this effect was attributed to an impairment of energetic metabolism [23]. Interestingly, Hwang et al. [ 2022], reported that the dysregulation of 3-hydroxybutyrate metabolism plays a role in the development of various types of cancer [46]. In this regard, recently, our group highlighted that higher levels of 3-hydroxybutyrate correlated with poor disease-free survival in metastatic colorectal cancer (mCRC) patients treated with bevacizumab plus oxaliplatin-based regimens [37]. The augmented levels of 3-hydroxybutyrate, a component of ketone bodies and an end product of fatty acid β-oxidation, observed in the serum of cancer patients, was suggested to be due to the increase in protein catabolism and fatty acid oxidation needed to fuel cancer cell growth [47]. Similarly, increased energy demand could be related with COVID-19. Interestingly, targeting metabolic changes through fasting and ketogenic diets seemed capable of inducing beneficial effects in cancer therapy [46], as well as anti-inflammatory and immune-modulating effects in patients with severe SARS-CoV-2 infection, thus preventing and/or modulating cytokine storms [48]. Regarding phenylalanine, its metabolism was indicated as one of the most dysregulated pathways in COVID-19 patients [49]. Correia et al. reported higher levels of phenylalanine in severe COVID-19 patients, suggestive of an altered immune system favoring viral infection [49]. Similarly, the levels of this metabolite are reported as elevated in patients with several cancers [50,51]. In this regard, drugs commonly used in the case of deficiency or mutation of the enzyme phenylalanine hydroxylase (PAH), which catalyzes the hydroxylation of phenylalanine to tyrosine using tetrahydrobiopterin (BH4) and molecular oxygen, can be considered [52]. A systematic review reported that COVID-19 patients with worse outcomes often have higher lactate blood levels compared to those with better outcomes early in the disease’s course [53]. Velavan et al. [ 2021] monitored lactate concentrations in hospitalized patients and in COVID-19 patients in home quarantine, demonstrating that lactate levels decreased significantly during recovery in hospitalized patients and were significantly higher in hospitalized patients than in home patients, confirming a prognostic role of this metabolite [24]. An additional study also reported high levels of lactate correlating with increased disease severity (from mild to moderate and severe), in a cohort of 52 hospitalized COVID-19 patients [25], in accordance, again, with our data. High levels of lactate are typically found in cancer patients, also correlating with poor prognosis [54,55]. Taking advantage of an untargeted metabolomics approach, we found higher plasma levels of lactate as well as of phenylalanine compared to healthy controls in large cohorts of melanoma and colorectal cancer patients (Costantini et al. unpublished observation). Lactate excess creates extracellular acidosis, negatively affecting the immune response [56], thus impairing cancer patients’ outcomes as well as COVID-19 recovery. In this regard, based on the experience of lactate dehydrogenase A (LDHA) inhibitors as anticancer therapeutics, these agents were proposed as therapy for COVID-19, because they can affect SARS-CoV-2 replication by reducing glycolysis [56]. Additionally, new lactate-blocking strategies employed in cancer treatment have been evaluated for their potential benefit in COVID-19 in addition to the readily available beta-blockers as an antagonist to lactate [57]. Overall, in the present study, we proposed a prognostic model, using the combined analysis of lactate and phenylalanine levels, to accurately identify, at the time hospitalization, patients with severe SARS-CoV-2 infection with a poor outcome who could benefit from a more intensive follow-up and treatment approach. Moreover, the analytes selected in our study could be used for monitoring disease evolution. Furthermore, the present study also suggests that the inflammatory mechanisms and the metabolic dysregulation involved in SARS-CoV-2 infection are similar to those responsible for cancer development and progression, also implying the possibility of repurposing anticancer drugs as a therapeutic strategy against SARS-CoV-2 infection. ## 4.1. Study Population and Sample Collection A total of sixty SARS-CoV-2-infected patients (thirty-six in the training set and twenty-four in the validation set) were selected for this study among those hospitalized between 3 March 2020 and 2 May 2020 for respiratory insufficiency at the ‘Azienda Ospedaliera dei Colli Monaldi—Cotugno Hospital’, Italy, but with a negative result for common respiratory pathogens. All patients were hospitalized without a previous positive COVID-19 test. Upon admission to the hospital, a confirmation of SARS-CoV-2 infection was obtained through RT—PCR positivity via an oropharyngeal swab (day onset corresponds to day 0 of hospitalization) following the World Health Organization (WHO) guidelines. The patients were classified based on their outcome: the “Exitus”, which comprised patients who died during infection, and the “Good Prognosis”, which comprised patients who recovered from COVID-19 (Table 1 and Table S2). The study was conducted according to the guidelines of the Declaration of Helsinki and was approved on 8 July 2020 by the Ethical Committee of the ‘AORN Ospedali deiColli—Monaldi—Cotugno—CTO, Napoli, Italy’ (approval number AOC-0020053-2020). Informed consent was obtained from all enrolled patients for the use of their biological samples and clinical data for the purposes of clinical research and the study of diseases. Metabolomics data obtained on plasma samples from twelve healthy donors, nine male and three female, aged >18 years (median = 49; range = 24–60) were obtained within another study from our group (Biocore, IRCCS Pascale Ethical Committee Approval number: $\frac{7}{14}$ OSS) and compared with those obtained within the current study. ## 4.2. Plasma 1H-NMR Spectroscopy The plasma samples obtained from the SARS-CoV-2 patients were prepared for NMR analysis by mixing 330 μL of plasma with 300 μL of PBS (containing $10\%$ v/v D2O) and 70 μL of reference standard D2O solution containing 0.1 mM sodium 3-trimethylsilyl [2,2,3,3-2H4] propionate (TSP). They were then inserted into an NMR tube. All the spectra were recorded using a Bruker Avance 600 NMR spectrometer operated at a 599.97 MHz 1H resonance frequency and equipped with a cryoprobe. To attenuate the broad NMR signals from slowly tumbling molecules due to lipids and proteins, a standard Carr—Purcell—Meiboom—Gill (CPMG) pulse sequence was used to record the 1D spin–echo spectra. To suppress the water peaks, the CPMG presaturation pulse sequence was used using the equation -RD-90°-(t-180°-t) n—ACQ, where RD is the relaxation delay of 2 s; 90° and 180° represent the pulses that trip the magnetization vector; t is the spin–echo delay; n represents the number of loops; and ACQ is the data acquisition period. In our experiment, the data points were acquired using 256 transients. ## 4.3. NMR Data Processing All of the 1H-NMR spectra were manually phased and baseline-corrected and referenced to the CH3 resonance of TSP at 0 ppm. The spectral 0.50–8.60 ppm region of 1H-NMR spectra was integrated in buckets of 0.04 ppm using the AMIX package (Bruker, Biospin, Ettlingen, Germany). In detail, we excluded the water resonance region (4.5–5.2 ppm) during the analysis and normalized the bucketed region to the total spectrum area using Pareto scaling and the MetaboAnalyst v5.0 tool [58]. ## 4.4. Pathway Analysis of Significant Metabolites Pathway analysis of the modulated metabolites was performed using the “Enrichment Functional Analysis” module in the Metaboanalyst v5.0 tool [58]. In detail, we calculated the centrality through pathway impact, a combination of the centrality and pathway enrichment results. Metabolites were selected by evaluating both VIP values of >1 in class discrimination and correlation values of >0.8. Moreover, the Homo sapiens pathway library was chosen and analyzed using Fisher’s exact test for overrepresentation and relative betweenness centrality for pathway topology analysis. ## 4.5. Cytokinome Evaluation A large panel of cytokines, chemokines and growth factors was evaluated in thirty-six plasma samples from COVID-19 patients using the Bio-Plex assay, which contains dyed microspheres conjugated with a monoclonal antibody highly specific for a target protein. The method was carried out according to the manufacturer’s instructions (Bio-Plex Bio-Rad) to assess the cytokine concentrations. In detail, we used the Bio-Plex Pro™ Human Cytokine Screening Panel, 48-Plex, which consists of assays for the measurement of β-NGF, CCL2 (MCP-1), CCL3 (MIP-1α), CCL4 (MIP-1β), CCL7 (MCP-3), CCL11 (Eotaxin), CTACK (CCL27), CXCL1 (GRO-α), CXCL9 (MIG), CXCL10 (IP-10), CXCL12 (SDF-1α), FGFbasic, G-CSF, GM-CSF, HGF, IFN-α2, IFN-γ, IL-1α, IL-1β, IL-1ra, IL-2, IL-2Rα, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-16, IL-17, IL-18, LIF, M-CSF, MIF, PDGF-ββ, RANTES, SCF, SCGF-β, TNF-α, TNF-β, TRAIL and VEGF levels. Protein levels were determined using a Bio-Plex array reader (Luminex, Austin, TX, USA) that quantifies multiplex immunoassays in a 96-well format with very small fluid volumes. The analyte level was calculated using a standard curve with software provided by the manufacturer (Bio-Plex Manager 4.0 Software). ## 4.6. Data Processing and Statistical Analysis The sparse partial-least-squares discriminant analysis (sPLS-DA) algorithm was applied to explain the maximum separation between the defined class samples in the data (metabolites and cytokines). Score and loading plots were used to highlight and assess the role of X-variables (NMR signals) in the classification models and, hence, to prioritize the discriminating peaks for identification. The NMR signals were compared with reference spectra from the HMDB database [58]. Moreover, the nonparametric Mann—Whitney U test was used to evaluate differences between cytokine concentrations (expressed as pg/mL) in the “Exitus” and the “Good Prognosis” groups. One asterisk (*) indicates differences with $p \leq 0.05$, two asterisks (**) indicate differences with $p \leq 0.01$, and three asterisks (***) indicate differences with $p \leq 0.0001.$ The statistical program Prism 6 (GraphPad Software, San Diego, CA, USA) was employed. Receiver operating characteristic (ROC) curves were calculated for metabolites and cytokines that were found to be significantly correlated with patient outcome using the Biomarker Analysis tool on the Metaboanalyst v5.0 tool [58]. The area under the curve (AUC) was used to assess accuracy. The $95\%$ confidence intervals (CIs) were calculated to compute optimal cutoffs for any given feature (significant metabolites and cytokines). The Cox regression model was used to assess the role of the cutoff for metabolite and cytokine parameters in predicting patient outcome via MedCalc statistical software (https://www.medcalc.org accessed on 23 July 2022). Hazard ratios (HR) were derived from Cox regression analysis, and their $95\%$ confidence intervals ($95\%$ CI) were calculated using the proportional hazard model. Univariate analysis assessed the correlation of metabolites and cytokines with patient outcome. Multivariate analysis was performed using MedCalc software (https://www.medcalc.org) according to a backward elimination of factors showing a p value less than 0.05 in the univariate analysis. In all statistical tests, a p value less than 0.05 was considered significant. Using the module “Biomarker Analysis” in the Metaboanalyst 5.0 tool [58], we performed various biomarker analyses based on ROC curves for multiple biomarkers using a support vector machine (SVM) algorithm. 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--- title: Study on Anti-Constipation Effects of Hemerocallis citrina Baroni through a Novel Strategy of Network Pharmacology Screening authors: - Yuxuan Liang - Xiaoyi Wei - Rui Ren - Xuebin Zhang - Xiyao Tang - Jinglan Yang - Xiaoqun Wei - Riming Huang - Gary Hardiman - Yuanming Sun - Hong Wang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003546 doi: 10.3390/ijms24054844 license: CC BY 4.0 --- # Study on Anti-Constipation Effects of Hemerocallis citrina Baroni through a Novel Strategy of Network Pharmacology Screening ## Abstract Daylily (*Hemerocallis citrina* Baroni) is an edible plant widely distributed worldwide, especially in Asia. It has traditionally been considered a potential anti-constipation vegetable. This study aimed to investigate the anti-constipation effects of daylily from the perspective of gastro-intestinal transit, defecation parameters, short-chain organic acids, gut microbiome, transcriptomes and network pharmacology. The results show that dried daylily (DHC) intake accelerated the defecation frequency of mice, while it did not significantly alter the levels of short-chain organic acids in the cecum. The 16S rRNA sequencing showed that DHC elevated the abundance of Akkermansia, Bifidobacterium and Flavonifractor, while it reduced the level of pathogens (such as *Helicobacter and* Vibrio). Furthermore, a transcriptomics analysis revealed 736 differentially expressed genes (DEGs) after DHC treatment, which are mainly enriched in the olfactory transduction pathway. The integration of transcriptomes and network pharmacology revealed seven overlapping targets (Alb, Drd2, Igf2, Pon1, Tshr, Mc2r and Nalcn). A qPCR analysis further showed that DHC reduced the expression of Alb, Pon1 and Cnr1 in the colon of constipated mice. Our findings provide a novel insight into the anti-constipation effects of DHC. ## 1. Introduction Constipation is one of the common gastrointestinal symptoms, and different definitions of constipation lead to a range of reported incidences (from $1\%$ to $80\%$) [1,2,3]. The occurrence of constipation is considered to be multifactorial [4], and it can lead to decreased quality of life and increased medical costs for people [5]. In particular, elderly people and women are more likely to be affected by constipation. Only approximately $25\%$ of constipated people use medical treatments because of the adverse effects of some drugs [5,6,7], indicating safe and effective natural products for constipation relief are attractive. Daylily (*Hemerocallis citrina* Baroni, HC) is an Asphodelaceae plant widely distributed around the world. It is cultivated as an ornamental species in Europe and North and South America [8], and thousands of cultivars have been registered [9]. The flowers of various Hemerocallis species have been used as an important vegetable in Asia, especially for *Hemerocallis citrina* and *Hemerocallis fulva* [10,11]. Among them, dried daylily (DHC) is a popular vegetable because of its delicious taste and various physiological activities. Some ancient medicine books, such as the Compendium of Materia Medica (Ben Cao Gang Mu), recorded that daylily can be used for anti-depression, promoting lactation, etc. These physiological activities of daylily have been reported in recent years [12,13,14]. Ben Cao Fen Jing (an ancient medicine book) also recorded the beneficial effects of daylily on the gut and stomach. In our previous research, we found more than 728 phytochemicals in daylily using UPLC-MS/MS, mainly including flavonoids, lipids, phenolic acids, amino acids and derivatives and organic acids [12,15]. Among them, flavonoids are one of the most abundant classes of compounds in daylily. The physiological activity of daylily polysaccharides was also reported recently [16]. It is well known that the benefits of flavonoids and polysaccharides on intestinal function have been widely reported [17,18,19,20]. However, the anti-constipation role of DHC is still unclear. In this study, we investigated the anti-constipation effects of DHC using the defecation test and gastrointestinal transit test. Secondly, we aimed to evaluate the potential mechanism by measuring the content of short-chain organic acids (SCOAs) and the composition of gut microbiota in cecal contents. Then, we further evaluated the potential mechanism by integrating the network pharmacology and RNA sequencing. Lastly, we measured the expression of the related genes (Alb, Pon1, Cnr1, Nos, Ache and Grp). ## 2.1. Anti-Constipation Effect of DHC Compared with the Normal group (distilled water), the gastrointestinal transit rate and defecation number of the loperamide (Lop) group were significantly regulated ($p \leq 0.05$), which indicated that the constipated model was built successfully (Figure 1). For the gastrointestinal transit test, DHC did not significantly accelerate the gastrointestinal transit rate in constipated mice (Figure 1a). However, for the defecation test, compared with the Lop group, DHC treatment significantly promoted the defecation number of constipated mice (Figure 1b,c, $p \leq 0.05$). These results suggest that the acceleration of large intestinal peristalsis can be responsible for the increased defecation frequency in constipated mice. ## 2.2. Effect of DHC on the Content of Short-Chain Organic Acids The SCOAs of the cecal contents were further evaluated to test the impact of daylily on the intestinal environment in mice (Figure 2). There were no significant differences in the levels of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid and isovaleric acid between the DHC group and the Lop group. However, compared with the Lop group, the administration of DHC elevated the contents of acetic acid (increased by $64.0\%$) and valeric acid (increased by $23.5\%$). ## 2.3. Effect of DHC on Gut Microbiota The 16S rRNA sequencing of the cecal contents was performed to characterize the effect of DHC on the intestinal flora. The results show that the administration of DHC did not significantly promote the alpha diversity of the intestinal flora (Figure 3a), whereas it affected the structure of the gut microbiota (Figure 3b). In addition, the relative abundance of the top 30 genera was further visualized with a heatmap (Figure 4a). To further reveal the difference in the community of gut microbiota, the relative abundance of the genus was analyzed. As shown in Figure 4b, the levels of [Eubacterium]_xylanophilum_group, Monoglobus, Family_XIII_AD3011_group, HT002 and Anaerostipes were significantly reduced in the Lop group compared with those of the Normal group ($p \leq 0.05$). Conversely, the levels of Robinsoniella, Roseburia, Eisenbergiella, Robinsoniella, Ruminococcaceae_unclassified, Odoribacter and Negativibacillus were significantly increased in the Lop group than in those of the Normal group ($p \leq 0.05$). Compared with the Lop group, DHC promoted the levels of Akkermansia, Bifidobacterium, Bacteroidetes_unclassified and Flavonifractor while decreasing the levels of Peptococcaceae_unclassified, Helicobacter, RF39_unclassified, Christensenellaceae_unclassified, Vibrio, Candidatus_Stoquefichus and Negativibacillus in comparison with the Lop group (Figure 4c, $p \leq 0.05$). ## 2.4. Network Pharmacology Strategy According to the target data of the current drug and disease database on constipation indications, a total of 309 constipation-related targets (Homo sapiens) were screened from the GeneCards, DrugBank and DisGeNET databases. After the conversion of species targets in the STRING database, a total of 278 constipation-related targets (Mus musculus) were obtained. ## 2.5. RNA Sequencing of Colon Transcriptome profiling of colon tissue was further used to investigate gene expression regulated by DHC. There are 772 differentially expressed genes (DEGs) found between the Lop group and the Normal group (Figure 5a,b and Table S2). Compared with the Normal group, a total of 634 genes were up-regulated in the Lop group, while 138 genes were down-regulated in the Lop group. In addition, a total of 736 DEGs were observed between the DHC group and the Lop group (Figure 5a,c and Table S3). Compared with the Lop group, a total of 92 genes were up-regulated, whereas 644 genes were down-regulated in the Lop group. ## 2.6. KEGG Pathway Enrichment DEGs between groups were further used to perform KEGG functional enrichment. As a result, the top 10 KEGG pathways between the Lop group and the Normal group were Olfactory transduction, Phototransduction, Maturity onset diabetes of the young, ErbB signaling pathway, Complement and coagulation cascades, Steroid hormone biosynthesis, Neuroactive ligand–receptor interaction, Tight junction, Intestinal immune network for IgA production and Cytokine–cytokine receptor interaction (Figure 5d, $p \leq 0.05$). In addition, the top 10 KEGG pathways between the DHC group and the Lop group were Olfactory transduction, Phototransduction, Cholesterol metabolism, Regulation of lipolysis in adipocytes, PPAR signaling pathway, Neuroactive ligand–receptor interaction, Adipocytokine signaling pathway, Bile secretion, Thyroid hormone synthesis and Starch and sucrose metabolism (Figure 5e, $p \leq 0.05$). ## 2.7. Joint Analysis of Network Pharmacology and RNA Sequencing To further investigate the relationship between DEGs and constipation targets, a Venn diagram was used to illustrate the overlapping targets between the DEGs (DHC vs. Lop) and constipation targets. The results show that seven overlapping targets were found (Figure 6a). To further understand the relationship among these seven targets (Alb, Drd2, Igf2, Pon1, Tshr, Mc2r and Nalcn), the PPI relationships of these seven targets were further displayed using the PPI networks (Figure 6b and Table 1). The results show that Alb and Pon1 were the most closely associated targets in the PPI network. ## 2.8. mRNA Expression Analysis The relative mRNA expression of the core targets (Alb and Pon1) from the PPI network and other constipation-related targets (Cnr1, Nos, Ache and Grp) were further analyzed by qPCR. As a result, compared with the Lop group, DHC treatment significantly reduced the relative expression of Alb, Cnr1 and Pon1 in constipated mice (Figure 7, $p \leq 0.05$). ## 3. Discussion Daylily is a food resource that has a long history of consumption in Asia given its delicious taste and various physiological activities. Previous studies have shown that daylily contains many potential anti-constipation components, such as flavonoids and polysaccharides. In this study, the defecation frequency and gastrointestinal transit were firstly adopted to investigate the anti-constipation effect of DHC. Then, the SCOAs and 16s rRNA sequencing of cecal contents were further performed to investigate the anti-constipation effects of DHC. Lastly, the perspective of the transcriptomes and network pharmacology was adopted to elucidate the underlying mechanisms of DHC. Constipation is a common symptom affecting people of all ages, and it results in an expensive burden on the economy [21]. Although laxative drugs are used to treat constipation and have good effects, side effects have been reported with using these drugs [22]. Recently, dietary supplements (such as natural products, prebiotics and probiotics) with anti-constipation effects have drawn the attention of researchers due to their good effectiveness, high safety and low costs [23,24,25]. In this study, DHC treatment did not promote the gastrointestinal transit but significantly accelerated the defecation frequency of constipated mice. The gut metabolites (SCOAs) are closely related to the development of constipation [26,27]. To investigate the anti-constipation role of DHC, the contents of SCOAs in the cecal contents were further measured by GC. As a result, although increasing trends of acetic acid and valeric acid were found, the contents of SCOAs (acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid and isovaleric acid) were not significantly regulated by DHC. These results suggest that the constipation-relieving effects of DHC may not involve the regulation of SCOAs in the cecum. Accumulating evidence reported that alterations in the intestinal microbiota of the host are closely associated with the regulation of constipation. In this study, 16S rRNA sequencing was performed to characterize the regulation of DHC on the intestinal flora in constipated mice. The results show that 11 genera were significantly regulated ($p \leq 0.05$). Bifidobacterium is a well-known intestinal probiotic, and accumulating evidence suggested that increased Bifidobacterium was beneficial for constipation relief [28,29]. Our results show that DHC significantly promoted the levels of Bifidobacterium ($p \leq 0.05$). Akkermansia reportedly plays a positive role in metabolic modulation and gut health protection [30,31,32,33]. For example, Akkermansia can decrease the pro-inflammatory factor expression to relieve ulcerative colitis [34]. Previous studies reported that some probiotics (*Bifidobacterium longum* and *Lactobacillus plantarum* KFY02) and symbiotics can alleviate constipation, and they all promoted the relative abundance of Akkermansia [32,35,36]. In this study, DHC elevated the levels of Akkermansia ($p \leq 0.05$). Flavonifractor is a flavonoid-degrading bacterium [37], and our results show that DHC promoted the level of increased Flavonifractor, suggesting gut microbiota can utilize flavonoids of DHC to exert a physiological effect. Taken together, these results reveal the anti-constipation effects of DHC involving the proliferation of beneficial bacteria and flavonoid-utilizing bacteria and the inhibition of harmful bacteria. Furthermore, the KEGG pathway enrichment was performed to further reveal the underlying mechanism of DHC in constipation relief. In this study, the KEGG pathway enrichment of DEGs (Lop vs. Normal; DHC vs. Lop) showed that olfactory transduction was the most significantly enriched pathway. In this pathway, LOP up-regulated the expression of 40 genes compared with Normal, whereas DHC down-regulated the expression of 38 genes compared with Lop (Figure 5d,e). It is well known that SCOAs, indoles and ammonia are known to be odorous compounds in feces. SCOAs are considered beneficial to health, while indole and ammonia are the opposite. Feces odor is associated with constipation [38]. Protein catabolism in the gut may produce compounds that are toxic to the host, such as amines and indoles, which can potentially affect intestinal motility [39,40,41]. A previous study reported that lactosucrose treatment significantly reduced the concentrations of p-cresol, indole, skatole and ammonia in feces in the elderly with constipation [42]. We speculate that some harmful odorous compounds are produced in the gut of constipated mice, while DHC treatment reduces the level of these odorous compounds. These results indicate that olfactory transduction is closely related to the anti-constipation role of DHC. However, the role of olfactory transduction in the anti-constipation of DHC still needs further study. In recent years, the network pharmacology method has emerged as an effective strategy for establishing relationships between genes and diseases [43,44]. Herein, we adopted the network pharmacology strategy to systematically collect constipation-related targets through GeneCards, DrugBank and DisGeNET. According to the list of overlapping targets, the indirect relationship between DEGs (DHC vs. Lop) and constipation targets was established. As a result, we found that DEGs (DHC vs. Lop) and constipation targets shared seven overlapping targets, and the PPI network of overlapping targets further revealed that Alb and Pon1 were the two main targets in the PPI network. Alb encodes serum albumin, and the constipation scoring system was significantly and negatively correlated with the serum albumin level [45,46]. Furthermore, Alb was regarded as a core anti-constipation target of raffino-oligosaccharide [47]. Pon1 was found to have been significantly related to chronic constipation in a cross-sectional study [48]. In this study, the administration of DHC significantly down-regulated the expression of Alb and Pon1 in constipated mice ($p \leq 0.05$). Grp codes a gastrin-releasing peptide, which is associated with bowel motility [49,50]. Ache and Nos are important regulators of gut peristalsis, and they are also common genes of interest in gastrointestinal motility studies [51,52,53]. However, in this study, the expression of these genes was not significantly regulated by DHC intervention. A previous study reported that the activation of Cnr1 receptors slowed down the peristalsis of the colon [54], while a Cnr1 inverse agonist relieved the slow gastrointestinal motility [55]. Herein, DHC treatment significantly down-regulated the expression of Cnr1 (Figure 7, $p \leq 0.05$). In a word, the qPCR analysis suggested that the anti-constipation effect of DHC involved the regulation of Alb, Pon1 and Cnr1. ## 4.1. Materials The dried daylily (flower bud) was obtained from Yunxing Lake Modern Agricultural Center (Qidong, China), and it was subjected to superfine grinding according to the research of Hu et al. [ 56]. The loperamide hydrochloride was purchased from Dashenlin Pharmacy, which was produced in Janssen Pharmaceutical Ltd. (Xi’an, China). The active charcoal and gum Arabic were bought from Hengxing (Tianjin, China). ## 4.2. Mice A total of 30 male BALB/c mice (7 weeks old and weighing 20 g ± 2 g) were purchased from Guangdong Medical Laboratory Animal Centre (Guangzhou, China). All mice were fed under standard conditions, and the Ethics Committee of South China Agricultural University (SYXK 2019-0136) approved this experiment. ## 4.3. Animal Experiment Design For defecation test, 30 mice were randomly divided into three groups ($$n = 10$$) after 7 days of adaptive feeding: normal control group (Normal, distilled water), constipation model group (Lop, distilled water) and dried daylily group (DHC, DHC suspension). Three groups were administered with 0.5 mL/mouse/day in the corresponding sample by vialing gavage once a day for 14 days. On this basis, 30 min after completing the original gavage, the Lop group and the DHC group were treated with loperamide (5 mg/kg body weight; 0.5 mL) via gavage from Day 12 to Day 14 to induce constipation [29,57]. Correspondingly, the Normal group was given an additional 0.5mL distilled water from Day 12 to Day 14. Then, the defecation status (fecal numbers in six hours) of each mouse in a separate cage was observed. DHC powder and Lop powder were distributed in distilled water as a suspension. A 10 g/day dosage of dried daylily for an adult (70 kg) was considered, which is equivalent to 0.14 g/kg per day. Referring to the technical standards for testing and assessment of functional food formulated by China Food and Drug Administration and our previous research [57], mice were administered with DHC at a dose of 1.4 g/kg body weight/day. All groups fasted for 16 h (water was available) before measurement of the gastro-intestinal transit. At the end of the experiment, after giving Lop for 30 min, each group was intragastrically given activated carbon suspension (containing $5\%$ activated carbon and $10\%$ gum Arabic) containing corresponding samples (Normal group: water; Lop group: Lop; DHC group: DHC). After 25 min, the mice were anesthetized with pentobarbital and euthanized. The gastrointestinal transit rate was calculated using our previous method [57]. The cecal content and colon tissue were collected and stored at −80 °C. ## 4.4. Short-Chain Organic Acid Determination The cecal contents of acetic acid, propionic acid, butyric acid, isobutyric acid, valeric acid and isovaleric acid in mice were detected by gas chromatography (GC, 7890B, Agilent, Santa Clara, CA, USA), and the corresponding standard samples were obtained from Macklin (Shanghai, China). For GC detection, FFAP elastic quartz capillary column (30 m × 0.25 mm × 0.25 μm) was used, and the initial temperature was 70 °C, then increased at 5 °C/min to 150 °C (maintained 2 min). Nitrogen was used as the carrier gas (flow rate 2 mL/min). The detector temperature was 280 °C, and the injection volume was 2 μL. ## 4.5. 16S rRNA Sequencing The cecal contents of mice were used to perform 16S rRNA sequencing. Cetyltrimethylammonium bromide was used to extract DNA from the cecal content. The primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′) were used to amplify the V3–V4 variable region of 16S rRNA gene by PCR. The paired-end sequenced (2 × 250) was performed on the NovaSeq PE250 platform. Detailed information on the sequencing procedures was shown in the previous study [57]. ## 4.6. Network Pharmacology Strategy The constipation-related therapeutic targets were screened by GeneCards (four times the score of all the targets, the score > 3.79) [58], DrugBank [59] and DisGeNET 7.0 (the score > 0.1) [60]. To reveal the relationship between daylily and constipation, a Venn diagram was used to illustrate the overlapping targets between DHC targets and constipation targets. Protein–protein interaction (PPI) networks of the overlapping targets were constructed by STRING. ## 4.7. Transcriptomic Analysis The proximal colons of the mice were cleaned with saline and stored in a −80 °C freezer until transcriptomic sequencing. The total RNA of these tissues was isolated and purified with the TRIzon kit (CWBIO, Beijing, China) and the RNA was reverse transcribed according to the manufacturer’s instructions. ( Invitrogen, Carlsbad, CA, USA). Quantity and purity of total RNA were evaluated by NanoDrop ND-1000 (NanoDrop, Wilmington, DE, USA), and the integrity of RNA was detected by Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). RNA libraries were created using the TruSeq RNA sample preparation kit (Illumina, San Diego, CA, USA). Illumina NovaseqTM 6000 was used for the RNA sequencing, and the read length of PE150 was adopted. The details of the transcriptomic analysis were consistent with the previous study [61]. For analysis of differential expression, the screening criteria of DEGs were set as FC ≥ 2 or FC ≤ 0.5 and p-value < 0.05. ## 4.8. Quantitative Real-Time PCR The RNA samples for qPCR analysis were selected from the same colon tissues used for RNA sequencing. qPCR analysis was performed using a TB Green® Premix Ex Taq™ II kit (Takara, Shanghai, China) and Bio-Rad C1000 Thermal Cycler Real-Time PCR System (Bio-Rad, Hercules, CA, USA). The reverse transcription reaction system is a final volume of 10 μL, including 1 μg RNA, 1 μL PrimeScript RT Enzyme MixⅠ, 1 μL RT Primer Mix, 4 μL 5 × PrimeScript Buffer and RNase-free water (37 °C for 15 min and then 85 °C for 5 s). Amplification volume was 20 μL containing 2 μL cDNA, 0.8 μL forward primer (10 μM), 0.8 μL reverse primer (10 μM), 0.4 μL ROX Reference Dye (50×), 10 μL SYBR Premix Ex Taq Ⅱ and 6 μL RNase free water. The amplification conditions were a pre-denaturation program (95 °C for 30 s), and the amplification program (95 °C for 5 s, and 60 °C for 34 s) was for 40 cycles. The expression level of Gapdh was normalized [12]. Table S1 provides detailed information on the primers used. The relative expression levels of gene expression were calculated by the ΔΔCt method. ## 4.9. Statistical Analysis The Least Significant Difference Test and Kruskal–Wallis Test (SPSS version 20.0) were used to analyze the differences between groups according to whether the variances were consistent between groups [57,62]. All data were expressed with the mean ± SD, and a $p \leq 0.05$ was considered statistically significant. ## 5. Conclusions Our findings reveal that the administration of DHC accelerated the defecation frequency of mice. It elevated the abundance of Akkermansia, Bifidobacterium and Flavonifractor in cecal contents while reducing the levels of pathogens (such as *Helicobacter and* Vibrio) in cecal contents. A transcriptomic analysis further found 736 DEGs in the colon after DHC intervention, which mainly involved the olfactory transduction pathway. 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--- title: The Prognostic Significance of Early Glycemic Profile in Acute Ischemic Stroke Depends on Stroke Subtype authors: - Paola Forti - Fabiola Maioli journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003561 doi: 10.3390/jcm12051794 license: CC BY 4.0 --- # The Prognostic Significance of Early Glycemic Profile in Acute Ischemic Stroke Depends on Stroke Subtype ## Abstract It is still unclear whether early glycemic profile after admission for acute ischemic stroke (IS) has the same prognostic significance in patients with lacunar and non-lacunar infarction. Data from 4011 IS patients admitted to a Stroke Unit (SU) were retrospectively analyzed. Lacunar IS was diagnosed by clinical criteria. A continuous indicator of early glycemic profile was calculated as the difference of fasting serum glucose (FSG) measured within 48 h after admission and random serum glucose (RSG) measured on admission. Logistic regression was used to estimate the association with a combined poor outcome defined as early neurological deterioration, severe stroke at SU discharge, or 1-month mortality. Among patients without hypoglycemia (RSG and FSG > 3.9 mmol/L), an increasing glycemic profile increased the likelihood of a poor outcome for non-lacunar (OR, 1.38, $95\%$CI, 1.24–1.52 in those without diabetes; 1.11, $95\%$CI, 1.05–1.18 in those with diabetes) but not for lacunar IS. Among patients without sustained or delayed hyperglycemia (FSG < 7.8 mmol/L), an increasing glycemic profile was unrelated to outcome for non-lacunar IS but decreased the likelihood of poor outcome for lacunar IS (OR, 0.63, $95\%$CI, 0.41–0.98). Early glycemic profile after acute IS has a different prognostic significance in non-lacunar and lacunar patients. ## 1. Introduction A transitory hyperglycemia is frequent in the earliest phase of ischemic stroke (IS) as a part of the acute stress reaction [1]. In IS patients, admission hyperglycemia has a robust association with infarct size, initial clinical severity, neurological worsening, and short-term outcome [1,2]. Although a causal association is still unproven, some evidence suggests that hyperglycemia can worsen brain damage by fueling inflammatory mechanisms in the hypoperfused, but still potentially salvageable, area around the ischemic core (penumbra), thus exacerbating reperfusion injury [1]. Lacunar stroke is thought to have a more favorable outcome than other IS subtypes because of its very low acute mortality, but up to $30\%$ of lacunar patients actually develop early neurological deterioration that often leads to important disability [3,4]. Lacunar stroke, being typically caused by the occlusion of small perforating end arteries, usually lacks an ischemic penumbra [4,5]. Therefore, it has been hypothesized that admission hyperglycemia might be unrelated to short-term outcome of lacunar IS or even be beneficial by providing readily available fuel for the viable brain tissue around the ischemic core [6,7]. However, available clinical cohort studies of this issue are few, inconsistent, and based on a single glucose measurement [8,9,10,11]. In acute IS patients without diabetes, stroke onset is usually accompanied by a moderate glycemia increase (<10 mmol/L) followed by a physiological decrease within the subsequent 24 h [12]. However, persistent and delayed hyperglycemia within the first 48 h after stroke can also occur, and these glycemic trajectories seem to have a stronger association with poor short-term outcomes of IS than a single glycemic measure on admission [13,14]. Spontaneous hypoglycemia is also a known predictor of adverse short-term outcomes in both critical [15] and non-critical [16] inpatients but has received small attention by stroke researchers, because it is thought to be a rare occurrence on admission for acute IS [17]. In particular, it is unknown whether its prognostic significance is affected by IS subtype. In this retrospective cohort study, we investigated whether IS subtype affects the association between early glycemic profile and short-term stroke outcome. ## 2. Materials and Methods This is a retrospective, observational single-center study based on a cohort of 4052 IS patients aged ≥18 years who, between January 2006 and December 2018, were consecutively admitted to the Emergency Department of the Maggiore Hospital (Bologna, Italy) within 24 h after symptom onset and subsequently transferred to the local Stroke Unit (SU). At SU admission, written informed consent for future research use of all data included in their medical records was sought from patients or their legally authorized representatives. The study was conducted in accordance with the Declaration of Helsinki. The Maggiore Hospital Ethics Committee approved the study (approval number CE16092). The dataset is not publicly available due to privacy reasons, but data in anonymized form are available on request from the corresponding author. All patients had at least one CT-head scan at hospital admission. IS was classified as lacunar if presenting with one of the five classic lacunar syndromes (pure motor hemiparesis, sensorimotor stroke, ataxic hemiparesis, pure sensory syndrome, and dysarthria-clumsy hand syndrome) [18]. Neuroimaging evidence of lacunar infarction was defined as a subcortical brain infarct <15 mm [4] on CT or MRI. Non-lacunar IS included large artery atherosclerosis, cardioembolic, and other or unknown etiologies as determined at the time of the patient’s discharge [19]. Patients were treated according to standard guidelines for management of acute stroke, which recommend avoidance of intravenous fluids containing glucose and set the glucose target for glycemic control between 7.8 and 10.0 mmol/L [20]. Information about demographic, medical characteristics, and stroke outcome was obtained from medical records. Random serum glucose (RSG) was measured at the Emergency Department, usually within 3 h of admission. Fasting serum glucose (FSG) and glycated hemoglobin ((HbA1c), Diabetes Control and Complications Trial aligned results) were determined the morning after SU admission (median time after admission, 24 h; range, 12–48 h) as a part of the routine biochemistry tests performed on venous blood samples drawn after an overnight fast. All measurements were performed using automated methods at the same central laboratory. Hyperglycemia was defined as serum glucose ≥ 7.8 mmol/L (140 mg/dL), corresponding to the standard threshold for treatment in acute stroke [20]. Hypoglycemia was defined as serum glucose < 3.9 mmol/L (70 mg/dL), corresponding to the standard glucose alert value in clinical practice [21]. Diabetes was defined as pre-admission diagnosis (self-report, evidence from available medical records, or use of antidiabetic agents), new diagnosis made during SU stay, or retrospective diagnosis based on admission HbA1c ≥$6.5\%$ (48 mmol/mol) [22]. Although not fully concordant with traditional blood glucose criteria [23], HbA1c is a convenient choice for diabetes screening in acute stroke because, differently from blood glucose, it remains unaffected by stress response [24]. Prestroke disability was defined as admission modified Rankin Scale ≥ 2 [25]. Initial stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) measured at ED arrival [26]. Acute reperfusion treatment on admission was also recorded. We defined a composite poor outcome including early neurological deterioration (increase in NIHSS score ≥ 4 points or death within 24 h after admission) [27], very severe stroke at SU discharge (NIHSS score ≥25 [28]), or death within 30 days after stroke onset as ascertained from the Italian Regional Mortality Registry. Variables were reported as median (25th–75th percentile) or number (percentage). Univariate associations were tested using the Mann–Whitney or chi-square test as appropriate. In preliminary univariate analyses, patients were categorized into five glycemic trajectories based on RSG and FSG values: hypoglycemia (low FSG or FSG), persistent normoglycemia (normal RSG and normal FSG); persistent hyperglycemia (high RSG and high FSG), delayed hyperglycemia (normal RSG and high FSG), and decreasing hyperglycemia (high RSG and normal FSG). Univariate analyses suggested the possibility of non-linear associations but also showed that for some glycemic trajectories, lacunar patients were so few as to preclude any subsequent reliable statistical estimation by multivariable models based on the multiple categorization of predictors or complex non-linear functions. Therefore, multivariable analysis was performed by a logistic regression model testing for the interaction of IS subtype with both admission RSG and a continuous indicator of early glycemic profile calculated as the difference of FSG and RSG. We assumed that a positive difference in this value indicated a trend toward increasing glucose values, whereas a negative difference indicated a trend toward decreasing glucose values. The model also tested for the interaction of continuous glucose measurements with diabetes, which is known to weaken the adverse prognostic impact of stress hyperglycemia in acute stroke [13]. Covariates included age, sex, disability, reperfusion therapy, and admission NIHSS (log-transformed). Based on results from univariate analyses, this logistic regression model was applied to two partially overlapping subsets of subjects. The first subset included only patients with RSG and FSG > 3.9 mmol in order to focus on the association of poor outcome with high admission RSG and increasing early glycemic profile in the absence of hypoglycemia. The second subset included only patients with FSG <7.8 mmol/L in order to test whether high admission RSG or increasing glycemic profile could take a favorable prognostic significance in the absence of persistent or delayed hyperglycemia. Corollary analyses did not evidence interactions of reperfusion therapy with either admission RSG or early glycemic profile. Analyses were performed with R software version 3.5.3 and Harrell’s rms package [29]. Significance for p value was set at 0.050 (two-tailed). The study power was 0.80 for an OR of 1.3. ## 3.1. Characteristics of Patients The final cohort included 4011 patients (age range 19 to 101 years). We excluded 22 patients who refused/were unable to provide informed consent, nine patients with missing clinical or laboratory data, and 10 patients lost at follow-up after SU discharge. Excluded patients did not differ by age, sex, and admission NIHSS. Reperfusion therapy was administered to 678 patients (560 intravenous fibrinolysis, 29 mechanical thrombectomy, and 89 both). A lacunar stroke syndrome was clinically diagnosed in 834 patients, the most frequent presentation being pure motor ($61\%$), followed by ataxic ($16\%$), and sensory-motor ($9\%$). Only 269 ($32.2\%$) of these patients had evidence of lacunar infarction at the CT scan routinely performed at day 3 after admission. Of the 565 patients with negative CT scan, only 129 also underwent MRI (based on clinical judgment of the attending physician), but lacunar infarction was confirmed in 119 of them ($92.2\%$). The most frequent etiology for non-lacunar IS ($$n = 3177$$) was cryptogenetic ($44.2\%$), which was followed by cardioembolic ($40.3\%$) and large artery atherosclerosis ($12.5\%$). Diabetes was diagnosed in 1161 patients (844 known at admission, 88 newly diagnosed during SU stay, and 229 retrospectively diagnosed based on HbA1c). Table 1 compares baseline characteristics by IS subtype. Lacunar patients were more likely to be younger, men and without prestroke disability than non-lacunar patients. They were also less likely to present with high NIHSS and to undergo reperfusion treatment. Lacunar patients had lower RSG and higher prevalence of hypoglycemia and persistent normoglycemia than non-lacunar patients. However, continuous early glycemic profile did not differ by stroke subtype. The overall prevalence of hypoglycemia in the cohort was $7.8\%$, with only 13 cases due to low admission RSG. Serious hypoglycemia (<3 mmol/L) [21] was rare (less than $1\%$). As expected, single poor outcomes as well as composite poor outcome were more likely in non-lacunar IS, with early neurological deterioration being the most common occurrence. ## 3.2. Univariate Association of Glucose Profile Categories with Poor Outcome Table 2 show the distribution of combined poor outcome across different glycemic trajectories by IS subtype. In non-lacunar patients, poor outcome appeared markedly associated with hyperglycemic trajectories, delayed hyperglycemia having the highest proportion of cases. In lacunar patients, conversely, the highest proportion of cases was found for hypoglycemia, but numerosity was too small for a reliable statistical test. ## 3.3. Multivariable Analysis When applied to the 3699 patients without hypoglycemia, multivariable logistic analysis for prediction of poor outcome showed that IS subtype had a significant interaction with both admission RSG (p-value = 0.032) and early glycemic profile (p-value = 0.028). Significant interactions were also found between diabetes and both glucose predictors (p-value < 0.001). Figure 1 shows how higher admission RSG and increasing glycemic profile were both associated with higher likelihood of poor outcome in non-lacunar but not in lacunar IS. In non-lacunar IS, the adverse prognostic significance of both predictors was weaker if the patient had diabetes. When applied to the 3539 patients without persistent or delayed hyperglycemia, multivariable logistic analysis showed significant interactions of IS subtype with both admission RSG (p-value 0.004) and glycemic profile (p-value 0.003); no significant interactions were found with diabetes. Figure 2 shows how, in non-lacunar IS, both higher admission RSG and increasing glycemic profile remained associated with poor outcome. In lacunar IS, conversely, admission RSG was no more a statistically significant predictor, and patients with an increasing glycemic profile even had a lower likelihood of poor outcome. In corollary analyses contrasting patients with hypoglycemia against the rest of the study cohort, there was no significant association with poor outcome and no significant interaction with IS subtype or diabetes (p-value > 0.200 for all). ## 4. Discussion This study shows that admission RSG and early glycemic profile do not have a similar prognostic significance in patients with lacunar and non-lacunar IS. Higher admission RSG and increasing glycemic profile were both associated with a composite poor outcome in non-lacunar IS, even if the associations were weakened in patients with diabetes. No similar associations were found in lacunar patients, among whom an increasing glycemic profile might even take a favorable prognostic significance when blood glucose remained below the threshold for hyperglycemia. According to findings from animal models and human cohorts [1,7], the adverse association of stress hyperglycemia with severity and outcome of IS depends on the presence of an ischemic penumbra around the irreversibly injured tissue of the infarct core. From an evolutionary perspective, stress hyperglycemia is an adaptive response that aims to provide the brain with ready fuel during an acute threat [30]. In the ischemic penumbra of a brain infarction, however, glucose excess would favor anaerobic glycolysis, so promoting harmful intra- and extra-cellular processes (acidosis from release of lactic acid, accumulation of glutamate, oxygen radicals production) that can accelerate the transition to irreversible injury, expand infarct size, and increase the risk of hemorrhagic transformation [1,2,6,31]. Collateral circulation is a critical determinant of cerebral perfusion in acute cerebral ischemia and may also be important in maintaining perfusion to penumbral regions [32]. A study of 309 IS patients undergoing endovascular thrombectomy clearly showed how higher blood glucose levels significantly reduced the likelihood of good outcome in patients with good collaterals but not in those with poor collaterals [33]. Lacunar infarction usually lacks an ischemic penumbra because this IS subtype generally results from the occlusion of small cerebral arteries with poor collateral circulation [5]. Therefore, in lacunar IS, stress hyperglycemia has been hypothesized to be indifferent to stroke outcome or even to have a favorable effect by acting as a fuel source for the vital brain cells around the ischemic core [7]. However, available literature on this subject is conflicting and limited to few studies, all of which used a single admission RSG measurement and a composite outcome of death or functional disability. In 635 patients from the placebo arm of the TOAST trial [8], those with lacunar IS and higher glycemia had a better 3-month outcome than their normoglycemic counterparts, whereas the opposite occurred in those with non-lacunar IS. A similar finding was reported in 1375 IS patients from two clinical trials of lubeluzole [11]. Conversely, two prospective studies, of 1012 [10] and 2020 patients [9], respectively, reported no association of admission hyperglycemia with poor outcome in lacunar IS. A comparison of these studies is difficult, because only the first one used admission RSG as a continuous variable [8], while the others dichotomized it at different cutoffs (from 6.1 [9] to 8 mmol/L [10,11]). Our study confirmed that an increasing glycemic profile in the early phase of acute IS was unrelated to the short-term outcome of lacunar patients without hypoglycemia. However, our study also showed that an increasing glycemic profile was associated with lower risk of poor outcome in lacunar patients who did not develop sustained or delayed hyperglycemia during the earliest phase of admission. A possible explanation is that this subgroup of lacunar patients includes those with a smaller and more stable infarction. However, some lacunar IS actually have a penumbra area [4]. Moreover, even when well perfused, the brain tissue surrounding an infarct core is exposed to inflammatory damage, excitotoxicity, and a spreading depolarization wave that can affect blood flow and promote enlargement of the infarction [34]. These mechanisms might be exacerbated by an increased glucose availability [35,36]. Since lacunar IS is small by definition, these events may have no clinical relevance unless blood glucose reaches consistently high levels. This might explain the apparent protective effect of an increasing glycemic profile observed in our lacunar patients whose blood levels remained below the threshold for hyperglycemia. These patients might just be the ones with the better trade-off between the pros and cons of an increased glucose availability in their brain. The finding that suggests this favorable association, however, should be considered with caution, because we performed multiple statistical analyses on overlapping subsets of the same population, so increasing the possibility of obtaining statistically significant results by chance alone. A noticeable corollary finding of this study is the lack of association between hypoglycemia and poor outcome regardless of IS subtype and other confounders. Mechanisms by which hypoglycemia could worsen acute ischemic brain damage include: direct neurodamage by bioenergetic deficit; stress of the cardiovascular system as a consequence of the autonomic response; pro-inflammatory and pro-thrombotic effects worsening ischemic damage; and alterations of cerebral vasoregulation [1,31,37]. Stroke literature mostly focused on iatrogenic hypoglycemia occurring during trials of tight glucose control [38]. In these trials, hypoglycemia was usually unrelated to stroke clinical outcomes [39,40,41,42]. The only exception is the GIST-UK trial [43], reporting higher mortality among the insulin-treated patients with the greatest blood glucose reductions. Experimental data from animal stroke models are few and conflicting [2,44]. Data about spontaneous hypoglycemia on admission in IS cohort studies are also limited [45,46,47,48,49]. Reported occurrence of this issue varies from zero [45] to $49\%$ [47]. Evidence of its association with higher risk of death or poor functional status at 3 months is similarly unclear [46,48]. Although there is consistent evidence that spontaneous hypoglycemia is a mortality predictor in patients hospitalized because of several acute conditions, the existence of a true causal relationship is still debated [15,16]. Studies of older inpatients suggest that spontaneous admission hypoglycemia might be just an epiphenomenon of poor pre-admission health [50]. The strengths of our study include the large number of participants, the use of two subsequent glucose measures to define an indicator of early glycemic profile, and the attention paid to identifying diabetes, which might confer a higher cellular tolerance to acute hyperglycemia [15]. Our study has also several major limitations. First, about one-half of the patients with lacunar syndromes lacked neuroradiologic confirmation, and an MRI scan was not systematically performed. Although classic lacunar syndromes are highly suggestive of small deep cerebral infarction, the correlation between clinical syndromes, neuroradiological features and histological findings is not absolute [4], and different etiologies can be found in about $17\%$ of cases [51,52]. However, the radiologic confirmation of lacunar IS can be problematic in clinical practice: TC and conventional MRI often lack the necessary resolution to detect lacunar infarctions, while systematic recourse to techniques with superior precision, such as diffusion-weighted MRI, is not routinely feasible in clinical settings [53]. Second, our measure of glycemic profile was very approximative because it was based only on two, not fully comparable, glucose measurements. Third, since we performed multiple analyses on overlapping subsets of the same population, we cannot exclude that some of our statistically significant results were actually due to chance. Fourth, the study retrospective design prevents from drawing causal inferences. Fifth, although analyses were adjusted for admission clinical severity, no direct measure of infarction size was available. Information about occurrence of epileptic seizures would also have been of interest, as this disorder can be exacerbated under conditions of hyper- or hypoglycemia. Unfortunately, however, such information was not available. Finally, our database did not include information about a major clinical outcome such as post-discharge disability. In conclusion, this study shows that early glycemic profile after acute IS has a different prognostic significance in lacunar and non-lacunar patients. An increasing glycemic profile is clearly associated with poor short-term outcome in non-lacunar patients, but the unfavorable association is not evident in lacunar patients. 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--- title: 'Data-Driven Radiogenomic Approach for Deciphering Molecular Mechanisms Underlying Imaging Phenotypes in Lung Adenocarcinoma: A Pilot Study' authors: - Sarah Fischer - Nicolas Spath - Mohamed Hamed journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003564 doi: 10.3390/ijms24054947 license: CC BY 4.0 --- # Data-Driven Radiogenomic Approach for Deciphering Molecular Mechanisms Underlying Imaging Phenotypes in Lung Adenocarcinoma: A Pilot Study ## Abstract The heterogeneity of lung tumor nodules is reflected in their phenotypic characteristics in radiological images. The radiogenomics field employs quantitative image features combined with transcriptome expression levels to understand tumor heterogeneity molecularly. Due to the different data acquisition techniques for imaging traits and genomic data, establishing meaningful connections poses a challenge. We analyzed 86 image features describing tumor characteristics (such as shape and texture) with the underlying transcriptome and post-transcriptome profiles of 22 lung cancer patients (median age 67.5 years, from 42 to 80 years) to unravel the molecular mechanisms behind tumor phenotypes. As a result, we were able to construct a radiogenomic association map (RAM) linking tumor morphology, shape, texture, and size with gene and miRNA signatures, as well as biological correlates of GO terms and pathways. These indicated possible dependencies between gene and miRNA expression and the evaluated image phenotypes. In particular, the gene ontology processes “regulation of signaling” and “cellular response to organic substance” were shown to be reflected in CT image phenotypes, exhibiting a distinct radiomic signature. Moreover, the gene regulatory networks involving the TFs TAL1, EZH2, and TGFBR2 could reflect how the texture of lung tumors is potentially formed. The combined visualization of transcriptomic and image features suggests that radiogenomic approaches could identify potential image biomarkers for underlying genetic variation, allowing a broader view of the heterogeneity of the tumors. Finally, the proposed methodology could also be adapted to other cancer types to expand our knowledge of the mechanistic interpretability of tumor phenotypes. ## 1. Introduction Lung cancer is one of the most predominant cancer types that are diagnosed with a high incidence ($14.3\%$ of total male and $21.5\%$ of female new cancer cases) and with a high mortality rate worldwide [1]. Currently, the diagnosis, prognosis, and treatment selection of lung cancer are mainly accomplished by histologic inspection of tumor tissue [2], lymph node involvement [3], radiological imaging [4], and mutational status of EGFR, KRAS, ALK, BRAF, ROS1, HER2, RET, MET, and PD-L1 expression analysis [5]. Major challenges include the genetic, temporal, and spatial heterogeneity of tumors, the invasive collection of tumor samples, and the inability to distinguish between clinically relevant subtypes [6]. Genome-wide characterization has recently been utilized in the clinical assessment of lung cancer with multiple molecular assays, including gene expression alterations [7], miRNA expression profiles [8], and epigenetic modifications [9] such as DNA methylation status. However, these genomic sequencing assays fall short of capturing the spatial and temporal heterogeneity of tumors [10]. Medical imaging modalities such as MRI and CT have great potential to provide comprehensive details about tumor shape, intensity, and texture. Using this information as a prognostic biomarker for overall survival has already been proposed by generating a risk score from CT image features in lung cancer [11]. Furthermore, radiological imaging is used as an ongoing clinical routine to monitor tumor progression, angiogenesis, and distant metastasis to other organs [6]. There are several well-performing machine learning-based radiomic signatures for predicting EGFR and KRAS mutation status [12,13]. There is an ongoing effort to describe the biological representation of radiomic features [14]. The recent technological revolutions in clinical imaging (radiology/radiomics) and genomic technologies have led to the emergence of a new research area called “molecular imaging”, “imaging genomics”, or radiogenomics. This field refers to the study of the association between the molecular properties of tumors and their imaging phenotypes. For instance, many radiogenomics studies have reported significant correlations of molecular markers and clinical variables based on CT or MRI image features of lung [15,16,17], prostate [18], and breast neoplasms [19]. These studies hypothesized that alterations in gene expression patterns could lead to specific tumor architectures captured by non-invasive imaging. Recently, the field has gradually broadened. For example, machine and deep learning approaches have predicted mutation status based on the image features of lung tumors [13,20,21]. To improve these studies, radiomic features need to be robust to changes in the setting, such as CT or MRI scanner variables and reconstruction algorithms. Recently, a major step has been taken to define and validate the robustness of the features [22]. In contrast to unconnected molecular or imaging analyses, radiogenomics specifically outlines links between different datasets across a range of spatial and temporal scales [23]. Radiogenomic association maps (RAMs) can represent the correlation of radiomic features, genomic features, and clinical data in visually appealing graphs that reveal complex patterns [24]. Thus, the construction of RAMs could contribute to a better understanding of the tumor biology underlying imaging phenotypes and provide new insights into the identification of non-invasive surrogate biomarkers that accurately predict tumor molecular characteristics and suggest potential therapeutic approaches. This could provide an extension to the currently available methods, such as machine learning-based approaches [11,13,18]. When various molecular assays (multi-omics data) are available, RAM generation could provide more comprehensive insights than just analyzing correlations between, for example, image features and gene expression. For instance, we can learn more comprehensively how biological processes and signaling pathways are reflected in image features. Our methods for constructing RAMs consist of unsupervised cluster-based feature selection, which is well understood and has been applied to other applications such as early diabetes detection [25]. ## 2.1. Overview of the Radiogenomic Approach We developed and applied a bioinformatics workflow to perform an integrative analysis of gene (mRNA) expression, miRNA expression, and clinical and imaging data (Figure 1). All patients with primary tumors were included. The common cohort size used for the integrative analysis is 22 patients with a median age of 67.5 years (min–max, 42–80) (Table 1). Image processing starts with the manual segmentation of the tumor region of interest (ROI) from patient CT scans ($$n = 69$$). Fiji [26] and MATLAB were used to extract and store 86 image features related to four imaging phenotypes: tumor size, texture, morphology, and shape. The expression data of all available mRNA ($$n = 515$$) and miRNA ($$n = 513$$) samples were analyzed by differential expression analysis. The resulting differentially expressed genes (DEGs) and miRNAs (DEMs) were further used to identify over-represented gene ontology (GO) functional terms using gProfiler [27]. We performed gene set enrichment analysis using GO terms and extracted image features via Piano [28]. This provides a summary statistic of the correlations of the extracted image features with the enriched GO terms. We extracted the intersection of enriched GO terms between gene and miRNA expression datasets. For these intersecting GO terms, patients were clustered into phenotypically distinct subgroups according to their gene and miRNA expression signatures using hierarchical clustering, reflecting the biological correlations of these signatures with the corresponding image features. Clinical and mutation data were added to these clusters using the ComplexHeatmap package [29] resulting in a radiogenomic association map. Finally, TFmiR2 [30] was used to construct the gene regulatory network (GRN) of these GO terms that potentially explain the phenotypic differences between patient subgroups. ## 2.2. Differential Expression and Gene Set Enrichment Analysis Differential expression analysis yielded 7214 and 147 differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs), respectively. The postulated functional roles of these dysregulated genes and miRNAs were summarized in 317 significant GO terms (biological processes) for the DEGs and 538 terms for the DEMs (Supplementary Tables S1 and S2). Gene set enrichment analysis was performed to investigate the association between the transcriptional signatures of these significant terms and the tumor radiomic phenotypes. This revealed 7634 and 1156 significant associations between any image feature and any revealed enriched GO term for the DEGs (Supplementary Figure S1, Supplementary Table S1) and the DEMs (Supplementary Figure S2, Supplementary Table S2), respectively. Biological processes highly associated with radiomic phenotypes included nuclear division, cell cycle, cytokine-mediated signaling, and interleukin-6 signaling. Only 11 GO terms overlapped between the association results of both DEGs and DEMs with the radiomic features (Figure 2A). Most of these 11 GO terms were biological processes specific to cell differentiation, such as cell population proliferation or positive regulation of developmental processes. Interestingly, the four studied tumor phenotypes (morphology, shape, texture, and size) show different association patterns with the dysregulated genes (DEGs) and miRNAs (DEMs). For instance, most image features related to tumor size and morphology are mainly associated with DEGs but not with DEMs. Additionally, several texture features calculated based on the neighborhood gray-tone difference matrix negatively correlate with DEGs. By contrast, the texture features calculated from the gray-level run-length matrix positively correlate with DEMs. *The* gene/miRNA expression values of these 11 GO terms were hierarchically clustered to form two patient clusters. We measured the similarity of the clusters between the DEG and DEM datasets by the intersection of common patients (Table 2). We also integrated patient clinical information such as age range, smoking status, tumor stage (T and N), and the incidence of the most common mutations in lung cancer: ALK, EGFR, KRAS, and TP53. As we were interested in basic cellular and biological processes, we narrowed our analysis to the following two GO processes: [1] regulation of signaling, which shows the highest overlap of patients ($\frac{17}{22}$ = $77\%$) between the two patient clusters of DEGs and DEMs, and [2] cellular response to organic substances, which has the highest number of associations between the transcriptomic and image features (see Figure 2B and Table 2). We then analyze these GO terms in more detail to unravel how they were reflected in the radiomic phenotypes. The RAMs of the remaining 11 detected GO terms are depicted in more detail in Supplementary Figures S7–S24. ## 2.3. Regulation of Signaling The regulation of the signaling process incorporates basic signaling genes and miRNAs. Previous studies have shown heterogeneous tumors exhibit different signaling mechanisms and dysregulation patterns of related genes and miRNAs [31]. Our results not only showed that regulation of signaling was significantly associated with varying tumor phenotypes but also allowed for patient clustering based on the expression signatures of the signaling genes/miRNAs (Figure 3) with significant differences in tumor morphology (tumor variance). Moreover, signaling genes and miRNAs positively correlated with tumor variance appear to have an inflammatory function, such as hsa-mir-9 (Supplementary Figures S3 and S4). Consistent with our findings, this miRNA has already been experimentally proposed as a prognostic biomarker based on its correlation with poor overall outcomes [32]. It is also noteworthy that most clinical data, such as tumor stage and mutation status, did not show significant differences between the two patient groups. Furthermore, the DRFs calculated as a differentiator for the two groups with their fold change and p-values are displayed. The assigned image phenotype refers to the group of the image feature (Supplementary Table S3). ## 2.4. Cellular Response to Organic Substance Biological processes related to response to organic substances had the highest number of significant associations between the transcriptomic and image features in lung carcinoma. This is consistent with the fact that one of the main causes of lung cancer is tobacco smoking, which contains carcinogenic substances, such as organic cyclic compounds [33], that damage lung tissue. Most of the texture features were significantly associated with the expression patterns of miRNAs and genes, with a positive correlation observed for the miRNA signature and a negative correlation for the gene signature (Figure 3). Moreover, when clustering patients based on the miRNA expression signature of the biological process “cellular response to organic substances”, patient groups tend to have significant differences in tumor texture features such as homogeneity, contrast, and coarseness (Figure 4C, Supplementary Figures S5 and S6). This highlights the critical role of miRNAs in tumor texture heterogeneity in CT images of lung cancer patients exposed to organic substances. Unexpectedly, the clustering of patients based on gene expression signatures of the BP “cellular response to organic substances” revealed only morphology (i.e., variance) as a difference between the patient subgroups. Figure 4B depicts exemplary CT images for the two patient groups. Notably and in concordance with tumor heterogeneity, inflammatory activity and previous exposure to organic cyclic compounds are positively correlated overall. Similar to the “regulation of signaling” BP, there were no clear, coherent patterns in tumor stage, mutation status, or smoking status (Figure 4A) between the patient subgroups. Furthermore, the DRFs calculated as a differentiator for the two groups are shown with their fold changes and corresponding p-values. The assigned image phenotype refers to the group of the image feature (Supplementary Table S3). In contrast to one DRF (variance) of the mRNA expression-based RAM, the two groups in the miRNA RAM can be differentiated by a set of 14 image features, all belonging to the texture phenotype. ## 2.5. Regulatory Interactions Underlying Phenotypic Differences For each of the two examined biological processes, we constructed a TF–miRNA-mediated regulatory network that combines transcriptional and post-transcriptional interactions between the associated DEGs and DEMs, potentially driving the phenotypic differences between the patient subgroups (Figure 5). The constructed networks encompass three types of molecular interactions: [1] TF → target gene, [2] miRNA → target gene, and [3] TF → miRNA, describing how miRNAs are significantly involved in controlling tumor phenotypes. For the “regulation of signaling”, we identified two main hub genes: TAL1 and TGFBR2, which contribute largely to the regulation of the network (Figure 5A). By contrast, TGFBR2 was identified as the main hub gene for the “cellular response to organic substances” term (Figure 5B). Our results show that TAL1 is a lung-specific gene associated with lung carcinoma and directly regulates TGFBR2, which was previously annotated as a tumor suppressor gene [34]. TAL1 is also known to control normal myeloid differentiation and is an experimental drug target for the treatment of T-cell acute lymphoblastic leukemia [35]. Our analysis suggests a regulatory role for TAL1 in controlling tumor morphology, particularly tumor variance (Figure 3C). Many studies have reported the suppressive function of TGFBR2 in tumorigenesis [35,36], but no previous report has been able to highlight its regulatory role in governing the tumor texture and morphology (Figure 4C). ## 3. Discussion Radiogenomic approaches combine radiological images with underlying molecular information to reveal possible links between these tumor phenotypes and the underlying biology [31]. Biologically plausible associations between gene expression, miRNA expression, and image features could have a clinical context, such as early prediction of appropriate treatments, and a positive impact on overall survival. The decision to utilize the whole transcriptome, in addition to high-evidence genotypes like EGFR mutations, was made to include as yet unknown dysregulated genes. In addition, we did not want to reduce the already small sample size by including only a subset of the patients. For example, EGFR mutations have an estimated prevalence of only 10–$16\%$ in Caucasians and ALK adds up to 1–$10\%$ [37]. We proposed a data-driven approach to construct radiogenomic association maps (RAMs) that link imaging phenotypes to associated molecular features. These RAMs have the potential to identify image features that reflect the transcriptomic and post-transcriptomic regulations behind tumor pathogenesis. Such candidate image features could be used as surrogate biomarkers in the absence of genomic information and as an indicator of the underlying biological processes and pathways. Yeh et al. [ 31] applied a similar approach in breast cancer patients and found positive and negative associations between image phenotypes, such as size and KEGG pathways. In addition to the RAM-based approach, several other methods detect relationships between the image features and genetics, for example, by using PET rather than CT images and associating image features with oncogenic signaling pathways [38]. Other approaches use different methods to associate the imaging phenotypes with genetic signatures, so-called metagenes, using a correlation-based approach [17]. In addition, our approach helped to decipher the complex regulatory interactions between associated genes and miRNAs, explaining the differences between patients in tumor imaging phenotypes. Our approach highlighted biologically plausible associations between imaging phenotypes, dysregulated genes, and miRNAs in lung tumor patients. For instance, the tumor size and morphology phenotypes were exclusively associated with gene expression profiles, whereas the texture phenotypes were associated with gene and miRNA profiles. This relationship sheds light on quantifying the regulatory role of genes and miRNAs in shaping the observed tumor phenotypes in radiological images. Missing interpretability of image features for clinical associations beyond the subcategories defined by image features such as shape or density complicates their evaluation. *As* gene ontology databases provide curated molecular knowledge, this direct connection to previous findings enables the detection of surrogate image features for biological processes involved in tumor phenotypes. Additionally, our approach visually represents the patient’s clinical and mutation data to the constructed RAM in a complex heatmap. Although no differences in clinical and mutational data of EGFR, ALK, TP53, and KRAS were observed, an equivalent analysis with a larger patient cohort could determine yet unknown patterns. Interestingly, the genes involved in the regulation of cell signaling were found to be positively associated with shape and size image features. This connection seems biologically plausible as upregulated signaling pathways in tumors would induce proliferation and, thus, growth. *Both* genes and miRNAs involved in this biological process were negatively associated with tumor variance. This might lead to the conclusion that rapidly growing tumors lose their grayscale variance. Moreover, our RAM analysis shows that this image feature can be used to distinguish the signaling activity of a patient’s tumor. For instance, the miRNAs hsa-mir-9-1, hsa-mir-9-2, and hsa-mir-9-3 are known to cause inflammation and positively correlate with tumor variance in patient group 1 (Figure 3, blue samples). Recent unpublished work analyzed the expression differences of several miRNAs (including mir-9) and showed that these miRNAs show different expression patterns in early, middle, and late tumor stages [39]. In patient group 2, the gene DEPTOR, which is known to inhibit lung tumorigenesis [40], is negatively correlated with tumor variance (Supplementary Figure S4, red samples), suggesting its potential role as a diagnostic biomarker for differentiating patients at high risk of progression. The dysregulated genes and miRNAs related to organic substances were able to distinguish patients with significant differences in tumor texture phenotype. Of particular interest is the state of the inflammatory microenvironment of the tumor. Our results demonstrated evidence that inflammatory activity due to organic cyclic compounds (smoking) correlates with tumor texture and suggests the miRNAs hsa-mir-196a, hsa-mir-187, hsa-mir-133a, and hsa-mir-1 as a potential factor for tumor heterogeneity between patient groups. When constructing the gene–miRNA regulatory networks associated with the two GO terms examined, TAL1 and TGFBR2 were identified as hotspot genes potentially regulating these two GO terms. The stimulation of TGFBR2 by TAL1, specifically in lung tissue, has not been experimentally confirmed. Lo Sardo et al. [ 34] described EZH2 as a suppressor of TGFBR2, resulting in tumor growth mediated by a cluster of miRNAs (miR-25, 93, and 106b). Although this mechanism was not reflected in our GRN, we discovered another cluster of miRNAs (hsa-mir-19a, 20a, and 21) that may be involved in tumor growth and progression, in addition to the findings described by Lo Sardo et al. [ 34]. It is also noteworthy that the transcription of ADRB2, a target gene in the constructed regulatory network, is enhanced by the visualized TAL1-EZH2 axis. It is the encoding gene for beta-adrenoreceptors. In the literature, ADRB2 has been controversially reported to be associated with proliferation, angiogenesis, tumor progression, distant metastasis, and TKI resistance [41]. ## 3.1. Study Limitations Missing freely available repositories for patients’ multi-omics data was the main challenge for this study. We thus used all matched samples to create the RAM. Therefore, the results presented in this study require larger patient cohorts with various radiogenomics profiles to validate the detected RAMs. Furthermore, many radiogenomic studies can be improved by marking the specific biopsy site in the radiomic images to correlate the tissue-specific expression with the corresponding ROI in the image. Another important limitation is the technical challenges in data acquisition and processing, such as image standardization problems when using different CT scanners with varying parameters such as slice thickness, reconstruction algorithms, and radiation detector resolution. Finally, an automated ROI segmentation would compensate for the human bias introduced by manual segmentation. ## 3.2. A Word of Caution We must stress the obvious but often missed fact that association never implies causation when using RAM models. Nevertheless, we spotted literature-confirmed RAM examples generated from different OMICs datasets. Future research is warranted to test/assess the robustness and consistency of the proposed RAM map via receiver operator characteristic curves and cross-validation (CV) techniques—for instance, by building machine learning models to predict the radiographic features from the molecular data and vice versa. A second standard method to validate the detected RAMs is to apply our approach to independent/external patient cohorts and compare the identified association patterns. ## 4.1. Datasets Origin Clinical data, and gene and miRNA expression profiles for lung adenocarcinoma patients were downloaded from The Cancer Genome Atlas (TCGA) portal, namely the TCGA-LUAD project [42]. Genomic datasets were collected at level three. The matching CT studies (imaging traits) were obtained from The Cancer Imaging Archive (TCIA) [43] (Supplementary Table S4). ## 4.2. Image Data Analysis The DICOM images were loaded as image sequences into the ImageJ2 software [44] and segmented using the segmentation manager plugin of Fiji V.8 [26] to create the regions of interest (3D ROIs) delineating the tumor in each CT slide. The resulting ROIs were saved in TIFF format. The statistical and geometric features ($$n = 32$$) of the 3D tumor were extracted using the Fiji 3D-ROI Manager plugin [45]. The texture features ($$n = 54$$ features) were computed by loading the TIFF ROIs (TIFF-stack library) into MATLAB R2018b using the texture toolbox [46,47]. Finally, the two feature sets were combined, resulting in 86 imaging traits for each LUAD patient. ## 4.3. Genomic Data Analysis Gene and miRNA expression profiles were processed by normalization of raw read counts followed by differential expression analysis. We used the DESeq2 v. 1.12.4 R package [48] to identify differentially expressed genes (DEGs) and miRNAs (DEMs) between normal and tumor samples. Genes and miRNAs that exhibited at least a 2-fold change and a p-value cutoff of 0.05 were classified as DEGs and DEMs, respectively. p-values were adjusted using the Benjamini–Hochberg [49] procedure to limit the false discovery rate to $5\%$. ## 4.4. Enrichment Analysis of Differentially Expressed Genes and miRNAs To compare the functional enrichment of the DEGs versus the DEMs, we used the GOSt tool of the gProfiler2 R package [27] with the correction method gSCS to identify significantly enriched (p-value < 0.05) GO biological processes. To study the association between the transcriptomic functional level and the radiomic phenotypes, we used the gene set enrichment analysis (GSEA) implemented in the R package Piano [28]. For each combination of image features and a GO term, we performed GSEA to evaluate the Spearman rank correlation between the gene or miRNAs of the GO term and the image feature values. The p-values (<0.05) obtained from the GSEA were evaluated through 10,000 gene or miRNA set random permutations, and FDR-adjusted. The summary statistic indicates the directionality of the association between the GO term and the image feature in the up or down direction, revealing positive and negative associations between the transcriptomic expression profiles and the image feature. In our further analysis, we restricted our evaluation by considering only GO terms with more than two image features significantly associated with GSEA for both gene and miRNA-based analysis. ## 4.5. Visualization of the Radiogenomic Association Maps Hierarchical clustering with Euclidean distance and the complete method (hclust R function) was used to derive a dendrogram of columns for visualization. T and N classification [4], smoking status, patient age, and mutation status of EGFR, KRAS, ALK, and TP53 were added. The heatmaps were visualized using the ComplexHeatmap R package [29]. ## 4.6. Identification of Differentially Representative Features (DRF) The fold change (FC) for each image feature between two patient groups was calculated and tested for significance using the unpaired statistical t-test. p-values were adjusted using the Benjamini–Hochberg [49] procedure to limit the false discovery rate to $5\%$. ## 4.7. Gene Regulatory Network Construction The TFmiR2 web server [30] was utilized to construct the gene regulatory network (GRN) from the genes and miRNAs significantly associated with the examined GO terms with a p-value of less than 0.01. We contextualized the output network to lung cancer by selecting non-small cell lung carcinoma as the disease attribute. We also considered molecular interactions that were only supported by experimental evidence. The output networks were visualized by Cytoscape V.3.7.1 [50] highlighting edges/interactions that are lung-cancer and tissue-specific. All used methods and software packages are listed in Supplementary Table S5. ## 5. Conclusions We demonstrated a radiogenomics-based approach that deciphers the underlying regulatory machinery behind tumor imaging phenotypes by systematically correlating transcriptomic and image features in lung cancer patients. We have highlighted several biological processes significantly associated with tumor phenotypes (radiomic features) and unraveled the corresponding regulatory interactions with potential driver genes and miRNAs, providing better interpretability of radiologic phenotypes. This data-driven approach can be generalized to other cancer types and complex diseases, given the availability of related multi-omics datasets. Such an approach could be helpful in individualized medicine for detailed non-invasive diagnosis, treatment suggestions, drug susceptibility testing, and patient follow-up. ## References 1. 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--- title: PPARβ/δ Ligands Regulate Oxidative Status and Inflammatory Response in Inflamed Corpus Luteum—An In Vitro Study authors: - Karol Mierzejewski - Aleksandra Kurzyńska - Zuzanna Gerwel - Monika Golubska - Robert Stryiński - Iwona Bogacka journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003567 doi: 10.3390/ijms24054993 license: CC BY 4.0 --- # PPARβ/δ Ligands Regulate Oxidative Status and Inflammatory Response in Inflamed Corpus Luteum—An In Vitro Study ## Abstract Inflammation in the female reproductive system causes serious health problems including infertility. The aim of this study was to determine the in vitro effects of peroxisome proliferator-activated receptor-beta/delta (PPARβ/δ) ligands on the transcriptomic profile of the lipopolysaccharide (LPS)-stimulated pig corpus luteum (CL) in the mid-luteal phase of the estrous cycle using RNA-seq technology. The CL slices were incubated in the presence of LPS or in combination with LPS and the PPARβ/δ agonist—GW0724 (1 μmol/L or 10 μmol/L) or the antagonist—GSK3787 (25 μmol/L). We identified 117 differentially expressed genes after treatment with LPS; 102 and 97 differentially expressed genes after treatment, respectively, with the PPARβ/δ agonist at a concentration of 1 μmol/L or 10 μmol/L, as well as 88 after the treatment with the PPARβ/δ antagonist. In addition, biochemical analyses of oxidative status were performed (total antioxidant capacity and activity of peroxidase, catalase, superoxide dismutase, and glutathione S-transferase). This study revealed that PPARβ/δ agonists regulate genes involved in the inflammatory response in a dose-dependent manner. The results indicate that the lower dose of GW0724 showed an anti-inflammatory character, while the higher dose seems to be pro-inflammatory. We propose that GW0724 should be considered for further research to alleviate chronic inflammation (at the lower dose) or to support the natural immune response against pathogens (at the higher dose) in the inflamed corpus luteum. ## 1. Introduction Increasing infertility due to chronic inflammation has become a serious problem and a challenge for human and veterinary medicine in recent years. Inflammation is a protective response to pathological conditions such as bacterial infections. However, if the inflammatory cascade is not stopped, it transforms into chronic inflammation and leads to organ dysfunction [1]. An inflammatory response in the female reproductive system is often associated with the presence of lipopolysaccharide (LPS), the endotoxin of Gram-negative bacteria, e.g., *Escherichia coli* (E. coli) [2]. LPS binds to TLR and stimulates the synthesis of various pro-inflammatory cytokines such as IL-1β, IL-6, IL-8 and TNF-α [3]. There is evidence that E. coli LPS causes infertility by interfering with ovarian follicular development and the ovulation process [4]. Luttgenau et al. [ 5] reported that luteal TLR2 and TLR4 appear to be involved in the immune response of the corpus luteum (CL), which may be related to the production of pro-inflammatory cytokines and decreased ovarian steroidogenesis in cows. LPS has been reported to alter ovarian axis hormone secretion by affecting GnRH and LH production, CL growth and functions, the timing of ovulation and the estrous cycle [6,7]. In addition, the treatment of cows with LPS altered the structure of the CL and decreased plasma progesterone levels (P4), resulting in a temporary suppression of luteal function [8]. Despite these reports, there is a lack of data on the effect of LPS on the functions of the porcine CL. Furthermore, the great anatomical and physiological similarity of the female and porcine reproductive systems and the course of bacterial infection makes the pig a good model for studying the in vitro effects of infection on the immune response in the CL [9]. Peroxisome proliferator-activated receptors (PPARs) are ligand-dependent transcription factors belonging to the nuclear receptor superfamily. To date, three isoforms of PPARs—α, β/δ and γ—have been described [10]. PPARs have been reported to be involved in the various processes necessary for the proper functioning of the ovaries, such as the regulation of steroidogenesis, angiogenesis, tissue remodeling, cell cycle and apoptosis [11]. There is evidence that PPARγ ligands may play a luteotropic role by increasing the activity of 3β-HSD and the secretion of progesterone [12,13]. However, there is limited information on the role of PPARβ/δ ligands in CL function. The anti-inflammatory effects of PPAR ligands have been widely reported, including in our previous work, but most of this relates to the PPARγ isoform [14,15,16]. The effect of PPARβ/δ on inflammation has not been fully elucidated [17]. In some cases, PPARβ/δ agonists appear to exert anti-inflammatory effects, such as inhibiting the synthesis of pro-inflammatory cytokines TNF-α and MCP-1 in the liver, alleviating inflammation in experimental autoimmune encephalomyelitis, or inhibiting diabetic nephropathy by reducing inflammatory mediators in mice [18,19,20]. There are also reports suggesting that PPARβ/δ signaling promotes inflammation [17]. It has been reported that in mice with arthritis, mesenchymal stem cells (MSCs) had higher anti-inflammatory potential than the MSCs derived from PPARβ/δ knockout mice [21]. The present study was conducted to determine the influence of PPARβ/δ ligands on the global transcriptomic profile of the LPS-stimulated corpus luteum of pigs during the mid-luteal phase of the estrous cycle. In addition, transcriptomic changes in the CL after the treatment with LPS alone have been described. For the first time, our research has revealed the role of PPARβ/δ in the regulation of oxidative stress and genes involved in the inflammatory response. In addition, we have shown a dose-dependent effect of the tested agonists. ## 2.1. Statistics of RNA Sequencing RNA sequencing data were created for 20 cDNA libraries, including four untreated samples (controls), four with LPS, four with GW0724 at a concentration of 1 μmol/L, four with GW0724 at a concentration of 10 μmol/L and four with GSK3787. The analysis produced 968,505,414 raw paired-end reads in total, with an average 48,425,271 per sample and a Q20 value that was on average $99.94\%$. The short reads, low-quality sequences and ambiguous nucleotides were removed from the raw reads, leaving on average of 938,720,608 valid reads per sample, that were used for further analysis (Supplemental Table S2). The filtered reads were mapped to the Ss11.1.98 version of the pig genome with a unique mapped average rate of $94\%$. The analysis of the distribution of mapped reads to gene structures indicated that $94.11\%$ of read pairs (in average per sample) mapped to coding sequences, $3.56\%$ mapped to introns, and $2.33\%$ mapped to intergenic regions (Figure 1). RNA-seq data have been deposited in the ArrayExpress database at EMBL-EBI under accession number E-MTAB-12027. ## 2.2. The Effect of LPS on Differential Gene Expression in the Corpus Luteum The RNA-*Seq analysis* revealed 117 DEGs (63 downregulated and 54 upregulated) in porcine CL on days 10–12 after LPS treatment (Figure 2A and Figure 3A). The Gene Ontology (GO) analysis assigned these DEGs to 159 terms of biological processes, 18 terms of cellular components, and 47 terms of molecular functions (Figure 4A). The treatment of the CL tissue with LPS altered the expression of genes involved in processes such as the regulation of signaling receptor activity (INSL6, IL-6, TNFSF14, IFN-DELTA-7, PDYN, PRL), response to bacterium (C15orf48, NLRP6, ENSSSCG00000037358) or oxidoreductase activity (ALOX12B, ALDH3B2, XDH, SOD2). Moreover, KEEG enrichment analysis revealed that DEGs were involved in signaling pathways such as cytokine–cytokine receptor interaction (TNFRSF9, IL-6, TNFSF14, IL-27, PRL) or the NOD-like receptor signaling pathway (NLRP6, IL-6, ENSSSCG00000007964) (Supplemental Figure S1A). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S3–S5, respectively. ## 2.3. The Effect of PPARβ/δ Agonist on Differential Gene Expression in the Corpus Luteum The results of our study showed that the PPARβ/δ agonist GW0724 at a concentration of 1 μmol/L affected the expression of 102 protein-coding genes (74 downregulated and 28 upregulated) (Figure 2B and Figure 3B). The GO analysis assigned these DEGs to 193 terms of biological processes, 13 terms of cellular components, and 37 terms of molecular functions (Figure 4B). These DEGs were involved, for example, in oxidation–reduction processes (CYP46A1, CYP4A24, ALOX12B, ALDH3B2), immune response (IL-15, CSF3, TNFSF14, VTN) or cell population proliferation (SHH, MAB21L2, CSF3). Furthermore, KEEG analysis showed that these DEGs were engaged in pathways such as cytokine–cytokine receptor interaction (CD27, IL-15, CSF3, TNFSF14) or drug metabolism (TK1, ENSSSCG00000040980, ALDH3B2) (Supplemental Figure S1B). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S6–S8 respectively. In turn, the treatment of the CL with PPARβ/δ agonist GW0724 at a concentration of 10 μmol/L resulted in changes in the expression of 103 genes (57 downregulated and 46 upregulated) (Figure 2C and Figure 3C). The GO analysis assigned these DEGs to 275 terms of biological processes, 18 terms of cellular components, and 42 terms of molecular functions (Figure 5A). These DEGs were involved, for example, in immune and inflammatory response (LTA, CCL3L1, IL-6, TNFSF14, CCL4, ELF3), chemotaxis (PDGFRA, CCL3L1, ENSSSCG00000020934, CCL4), cellular response to lipopolysaccharide (CD180, IL-6, ZFP36) and tumor necrosis factor (CCL3L1, ZFP36, CCL4), or cytokine activity (LTA, CCL3L1, IL-6, TNFSF14, CCL4). Additionally, KEEG analysis indicated that these DEGs were engaged in pathways such as the NF-kappa B signaling pathway (LTA, TNFSF14, CCL4) or Toll-like receptor signaling pathway (LTA, CCL3L1, IL-6, CCL4) (Supplemental Figure S1C). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S9–S11, respectively. ## 2.4. Comparative Analysis between Two Doses of PPARβ/δ Agonist Statistical analysis identified 97 DEGs (19 downregulated and 78 upregulated) in the CL treated with GW0724 at a concentration of 10 μmol/L compared with 1 μmol/L (Supplemental Figure S2A, Supplemental Figure S2B). The GO analysis assigned these DEGs to 148 terms of biological processes, 8 terms of cellular components, and 32 terms of molecular functions (Supplemental Figure S2D). These DEGs were involved, for example, in immune and inflammatory response (ENSSSCG00000007642, CCL19, CSF3, MBL1, IL17B, CCR3), oxidation–reduction processes (CYP4A24, HSD17B3, SURF1) or response to DNA damage stimulus (MRNIP, BATF). Moreover, KEEG analysis indicated that these DEGs were engaged in pathways such as cytokine–cytokine receptor interaction (CCL19, IL17B, CSF3, CCR3, IL-27) and the IL-17 signaling pathway (IL17B, CSF3) (Supplemental Figure S2C). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S12–S14, respectively. ## 2.5. The Effect of PPARβ/δ Antagonist on Differential Gene Expression in the Corpus Luteum The study demonstrated that PPARβ/δ antagonist GSK3787 affected the expression of 88 protein-coding genes (63 downregulated and 25 upregulated) (Figure 2D and Figure 3D). The GO analysis assigned these DEGs to 250 terms of biological processes, 16 terms of cellular components, and 39 terms of molecular functions (Figure 5B). These DEGs were mostly assigned to oxidation–reduction processes and oxidoreductase activity (CYP46A1, ENSSSCG00000003963, ALOX12B, ENOX1, CRYZL1, ENSSSCG00000030195) as well as angiogenesis (ANGPTL4, SHH, EPHB1, HAND1, LEP). Moreover, KEEG analysis indicated that these DEGs were engaged in pathways such as the PPAR signaling pathway (ANGPTL4, PLIN2) and cAMP signaling pathway (GRIN2B, GHRL, CACNA1S, PLN) (Supplemental Figure S1D). All detailed DEGs, GO and KEEG results were described in Supplemental Tables S15–S17, respectively. ## 2.6. Real-Time PCR Analysis The treatment of the CL with LPS increased PPARβ/δ mRNA abundance during the mid-luteal phase of the estrous cycle (Supplemental Figure S3). Real-time PCR expression patterns of the tested DEGs (IL-6, SOD2, CD180, ANGTPL4) were in agreement with RNA-Seq results (Supplemental Figure S4). ## 2.7. Biochemical Analyses Total antioxidant capacity was lower in the LPS-treated CL (21.66 mM Trolox/mg protein) compared with the control (33.97 mM Trolox/mg protein). Analysis of the CL, treated with PPARβ/δ agonist at a concentrations of 1 μmol/L and 10 μmol/L, showed higher TAC levels compared with the LPS-treated CL. Moreover, TAC was enhanced with increasing agonist concentration (38.1 and 43.9 mM Trolox/mg protein, respectively). The total antioxidant capacity of the CL treated with the antagonist was similar to that of the CL treated with LPS (21.63 mM Trolox/mg protein) and no statistical difference was noted (Figure 6A). The activity of peroxidase in the CL increased almost 2-fold after stimulation with LPS compared with the control (226.4 vs. 424.8 μM/mg protein). The difference in peroxidase activity in the agonist-treated CL compared with LPS-treated CL was not statistically significant. However, peroxidase activity in CL, which was treated with an antagonist (200.2 μM/mg protein), was decreased almost two-fold compared with LPS-treated CL (424.8 μM/mg protein) (Figure 6B). The activity of catalase in the CL did not change after LPS administration. Only the lower concentration of agonist compared with LPS-treated CL increased catalase activity (0.47 vs. 2.88 kat/mg protein) (Figure 6C). The trend of the activity of SOD and GST was similar. The treatment of the CL with LPS decreased the activity of SOD almost three-fold compared with the control (9.58 vs. 3.18 a.u./mg protein). In turn, PPARβ/δ agonist GW0724 at concentrations of 1 μmol/L or 10 μmol/L increased the activity of SOD compared with the LPS-treated CL (1 μmol/L–35.77 and 10 μmol/L–32.72 a.u./mg protein) (Figure 6D). A similar observation was made with respect to GST activity. The treatment of the CL with LPS decreased the activity of GST compared with the control (7.69 vs. 2.74 a.u./mg protein), while the treatment with the agonist increased the activity of GST at both low and high concentrations (16.37 and 16.16 a.u./mg protein, respectively) compared with the LPS-treated CL. The activity of SOD or GST was not significantly affected by the PPARβ/δ antagonist (Figure 6E). ## 3. Discussion A growing body of evidence shows a negative impact of lipopolysaccharide from *Escherichia coli* on reproductive functions. There are reports indicating that LPS leads to infertility by impairing ovarian functions [4]. It has been shown that LPS accumulates in follicular fluid, decreases the production of estradiol from granulosa cells, suppresses the expression of gonadotrophin receptors and disrupts blastocyst implantation [22]. Despite this evidence, transcriptome changes in the porcine corpus luteum under the influence of LPS had never been studied. The present results demonstrate for the first time the global transcriptomic profile of the CL of gilts during the mid-luteal phase of the estrous cycle and the effect of LPS as well as PPARβ/δ ligands during LPS-induced inflammation within the structure. We demonstrated that LPS affected the expression of 118 DEGs (63 of which were downregulated, whereas 55 were upregulated). These DEGs were assigned to different biological processes, such as response to bacterium, the negative regulation of endothelial cell proliferation, or the IL-17 signaling pathway. Among the above genes with altered expression after LPS stimulation, we identified those involved in the regulation of oxidative stress and reactive oxygen species (ROS) production (XDH, ALDH3B2, SOD2, ALOX12B). It has been frequently reported that ROS play a significant and diverse role within the ovary, especially in the CL during luteal regression [23]. In addition, the abruptly increased production of ROS (e.g., by LPS during bacterial infection) decreases P4 secretion, which may contribute to functional and structural luteolysis and disturb the proper course of the estrous cycle [24]. Xanthine dehydrogenase (XDH) is the rate-limiting enzyme for purine degradation, metabolizing hypoxanthine/xanthine to uric acid [25]. During these metabolic processes, numerous ROS are produced, including superoxide anion (O2•−) and hydrogen peroxide (H2O2) [26]. In the present study, we demonstrated that XDH was upregulated in the LPS-treated CL during the mid-luteal phase of the estrous cycle. Moreover, we found that LPS downregulated the expression of ALDH3B2 in the CL. *This* gene belongs to the aldehyde dehydrogenase (ALDH) family of enzymes, which is critical for the detoxification of aldehydes [27]. ALDH3B1 has been reported to metabolize and protect cells from aldehydes and oxidative compounds derived from lipid peroxidation (LPO), suggesting an important role of this enzyme in cellular defense against oxidative stress and downstream aldehydes [28]. Mishra et al. [ 29] reported that the exposure of bovine luteal cells to LPS increased the LPO process. Based on our results, we can assume that LPS intensifies LPO and oxidative stress by increasing the expression of XDH and decreasing ALDH3B2 in the porcine CL. Our studies revealed also that LPS increased the expression of SOD2 in the CL during the mid-luteal phase of the estrous cycle. Superoxide dismutase 2 (SOD2) is known to play a crucial role as the major antioxidant defense system with increased expression under inflammatory conditions [30,31]. This enzyme efficiently converts superoxide to the less reactive hydrogen peroxide (H2O2), which can diffuse out of mitochondria and be further detoxified to water by other antioxidant enzymes [32]. It has been reported that the antioxidant system (including SOD2) plays an important role in the maintenance of CL integrity and function during the estrous/menstrual cycle [33]. The luteal expression of SOD2 appears to be dependent on the stage of the estrous cycle as well as the activity of various immune cells [24]. To confirm our transcriptomic results, we performed biochemical analyses to determine antioxidant status. We found that LPS reduced the total antioxidant capacity of the CL and decreased the activity of key antioxidant enzymes such as catalase, superoxide dismutase, and glutathione-s-transferase. It should be noted that SOD2 gene expression was upregulated after LPS treatment, whereas superoxide dismutase activity decreased. The lack of correlation between mRNA and protein expression has been frequently described and is the result of differences in mRNA and protein stability and the differential regulation of post-transcriptional and translational processes [34,35,36]. An interesting part of our present research is the identification of genes involved in the immune response, such as TNFSF14, NLRP6, IL-6 and BMX. Of particular interest seems to be TNFSF14 (TNF Superfamily Member 14), which was upregulated in the CL after the treatment with LPS. TNFSF14 is known to be a pro-inflammatory cytokine produced mainly by macrophages and T cells [37]. TNFSF14 has been shown to promote the activation and maturation of T lymphocytes [38] and increase the production of ROS [39], which subsequently leads to severe inflammation and tissue destruction. In addition, TNFSF14 has recently been proposed as one of the biomarkers for PCOS [40]. These results confirm that the use of LPS in the proposed experimental model induces an inflammatory response in porcine CL. In the present studies, we investigated the effect of PPARβ/δ ligands on the CL treated with LPS under in vitro conditions. It is worth noting that stimulation with LPS increased the expression of PPARβ/δ, suggesting its regulatory role in inflamed tissue. Our experimental model included two concentrations of PPARβ/δ selective agonist (GW0724)—1 μmol/L and 10 μmol/L. We found that 1 μmol/L of GW0724 affected the expression of 102 DEGs (63 DEGs were downregulated and 39 DEGs were upregulated), whereas 10 μmol/L of GW0724 altered the expression of 105 DEGs (58 DEGs were downregulated and 57 DEGs were upregulated). Most of these DEGs were involved in processes related to the regulation of oxidative stress and inflammation. Only the most interesting DEGs are discussed below. In this study, we demonstrated that the activation of PPARβ/δ by GW0724 affected the expression of genes related to the control of oxidative stress, such as ALDH3B2, SURF1, DUOXA2 and PDK4. The treatment of the LPS-stimulated CL with PPARβ/δ agonist at both doses decreased the expression of ALDH3B2 (described earlier in the discussion) and SURF1 (*Surfeit locus* protein 1), which is involved in the proper assembly of cytochrome c oxidase (COX) [41]. It is worth noting that these genes were upregulated after treatment with LPS alone, suggesting that activation of PPARβ/δ reverses the negative effect of LPS. Our study also showed the downregulation of DUOXA2 (maturation factor of DOUX2) after treatment with GW0724 at a concentration of only 1 μmol/L. DUOX2 is a membrane-localized glycoprotein composed of six transmembrane helices. In the presence of DUOXA2, these structural components regulate the transfer of electrons from NADPH to molecular oxygen to generate H2O2 [42]. DOUXA2 expression has been reported to be increased during chronic inflammation and in various cancers, which may be related to the extensive production of ROS [43,44]. DUOX2 upregulation has also been associated with a significant increase in extracellular H2O2 production and DNA damage in tissues [45]. In addition, it has been suggested that the pro-oxidant state resulting from the upregulation of DOUX2 may impede the recovery of tissue damage caused by inflammatory stress [44]. Moreover, the current study also demonstrated that blocking PPARβ/δ by an antagonist upregulated ENOX1 (Ecto-NOX disulfide thiol exchanger), a member of the ecto- NOX family involved in intracellular redox homeostasis [46]. ENOX1 has been reported to induce oxidative stress in human aortic endothelial cells [47]. Biochemical analyses determining antioxidant status confirmed the transcriptomic results. We demonstrated that the PPARβ/δ agonist reversed the LPS effect by increasing the activity of superoxide dismutase, glutathione transferase and catalase. The obtained results suggest that the use of the PPARβ/δ agonist attenuates oxidative stress and prevents tissue damage. Conversely, blocking the receptor may increase oxidative stress. The present study has revealed the regulatory role of GW0724, a PPARβ/δ agonist, in the inflammatory process in the porcine CL. Interestingly, the observed effects appear to be dependent on the dose of ligand administered. The treatment with GW0724 at a concentration of 1 μmol/L revealed six DEGs (CSF3, VTN, IL-15, C1QTNF12, DUOXA2, TNFSF14) involved in the regulation of the inflammatory response or immune processes, according to the Gene Ontology analysis. In this work, we have demonstrated the inhibitory effect of GW0724 on the expression of CSF3 (Granulocyte colony-stimulating factor 3), the major regulator of neutrophil production [48]. CSF3 has been reported to exert pro-inflammatory properties in inflammatory joint diseases. There is also evidence that a deficiency of CSF3 protects mice from acute and chronic arthritis [48]. An inhibitory effect of GW0724 on the expression of a potent proinflammatory cytokine—TNFSF14—was also observed. It is worth noting that this is the opposite effect to that observed after LPS treatment alone. The current results showed that GW0724 (1 μmol/L) decreased the expression of VTN (Vitronectin), a pro-inflammatory glycoprotein that binds to integrin receptors [49]. VNT-deficient mice were found to have lower numbers of neutrophils and lower concentrations of pro-inflammatory cytokines such as IL-1β and IL-6 in the lungs after LPS exposure than VTN-positive mice [50]. Moreover, the exposure of mice to VTN was associated with the decreased apoptosis of neutrophils [51]. In addition to its anti-apoptotic effect, VTN may also exacerbate the severity of acute lung injury by decreasing the uptake and clearance of apoptotic neutrophils by alveolar and tissue-derived macrophages, which is associated with the release of pro-inflammatory mediators [52]. The treatment with GW0724 (1 μmol/L) upregulated the expression of IL-15 in inflamed CL. Interleukin 15 is a pleiotropic cytokine involved in the inflammatory response in various infectious diseases [53]. It has been reported that IL-15 plays an important role in host defense in sepsis induced in mice by E. coli [54]. Mice overexpressing IL-15 were resistant to the septic shock induced by E. coli, which was related to the inhibition of apoptosis triggered by TNF-α. Moreover, the treatment of normal mice with exogenous IL-15 made them resistant to E. coli-induced lethal shock [54]. The treatment of inflamed CL with GW0724 at a concentration of 10 μmol/L affected the expression of eight genes involved in the regulation of inflammatory responses or immune processes (CD180, IL-6, CCL3L1, LTα, CCL4, ELF3, ZFP36, TNFSF14). In contrast to the lower dose of GW0724 (1 μmol/L), which showed an anti-inflammatory character, the higher dose (1 μmol/L) seems to be pro-inflammatory. We have shown that the expression of CD180, a specific inhibitor of TLR4-mediated inflammatory response [55], was downregulated after the treatment of inflamed CL with GW0724 at the higher dose. CD180 is an accessory TLR4 molecule expressed in various cell types, including monocytes and macrophages [30]. In addition, we detected the increased expression of IL-6, CCL3L1, CCL4, LTα and ELF3, which are genes known to possess pro-inflammatory properties, mainly expressed through the induction of chemotaxis and the activation of lymphocytes and macrophages [56,57,58,59]. Statistical analysis performed between the two PPARβ/δ agonist doses revealed 19 downregulated and 77 upregulated genes. The most interesting genes are involved in the regulation of inflammatory and immune responses. Among them are MBL1, CCL19, IL-17β, PGLYRP3 and CSF3, whose expression was higher after treatment with GW0724 at a concentration of 10 μmol/L compared with 1 μmol/L. Mannan-binding lectin (MBL) is an important factor of innate immunity that contributes to the elimination of microorganisms. MBL has been reported to bind to bacteria and then neutralize them by opsonizing and activating complement through the lectin pathway of complement activation [60]. In turn, peptidoglycan recognition protein 3 (PGLYRP3) recognizes bacterial compounds (peptidoglycan) and plays a role in antibacterial innate immunity [61]. Both factors are crucial during the first step of bacterial infection. The chemokine CCL19 triggers T cell proliferation, leading to upregulation of pro-inflammatory cytokine synthesis [62]. It has been reported that IL-17B induces monocytes to produce TNF-α and IL-1β and supports neutrophil recruitment and B cell chemotaxis [63,64]. During infection, immune cells such as granulocytes, macrophages, and lymphocytes are recruited to tissues to clear bacterial infection [6]. We propose that PPARβ/δ may not only play a key role in alleviating chronic inflammation, but may also be helpful in supporting the immune response to bacterial infection in the CL. ## 4.1. Experimental Animals The study was conducted on corpora lutea harvested from gilts intended for commercial slaughter and meat processing in accordance with the guidelines for animal care (the Act of 15 January 2015 on the Protection of Animals Used for Scientific or Educational Purposes and Directive $\frac{2010}{63}$/EU of the European Parliament and the Council of 22 September 2010 on the protection of animals used for scientific purposes). Experimental material was collected from adult crossbred gilts (Large White × Polish Landrace, 7 months old, 100 kg body weight, $$n = 4$$) on days 10–12 of the estrous cycle (mid-luteal phase). On the farm, pigs were observed in two consecutive heat cycles. The first mark of estrus (the behavior of gilts observed in the presence of the boar) was defined as day 0 of the estrous cycle. The animals were transported to the local slaughterhouse where the ovaries were dissected within a few minutes. The removed tissues were transferred to the laboratory on ice in phosphate-buffered saline (PBS) with an antibiotic cocktail (100 IU/mL penicillin and 100 mg/mL streptomycin, PolfaTarchomin, Poland). The phase of the estrous cycle was proven in the laboratory from the morphological characteristics of the ovary [65]. ## 4.2. In Vitro Experiment The procedure for collection and incubation of the porcine CL was previously described [66]. In the laboratory, the CL were dissected from the ovary, connective tissue was removed, and placed on ice in a sterile Petri dish. CLs were cut into small pieces (100 ± 10 mg, in duplicate from each experimental replicate). Each tissue explant was placed in M199 medium (Sigma Aldrich, St. Louis, MO, USA) supplemented with $0.1\%$ BSA fraction V (Roth, Germany) and antibiotics. The explants were pre-incubated for 2 h in a water bath at 37 °C in an atmosphere of $95\%$ O2 and $5\%$ CO2. Then, the explants were treated with LPS (100 ng/mL, from E. coli) for 24 h. Explants not treated with LPS were considered as controls. The medium was removed, and the explants were incubated for 6 h with LPS alone or in combination with the PPAR β/δ ligands: GW0724 (agonist; 1 μmol/L or 10 μmol/L, Cayman Chemical Company, Ann Arbor, MI, USA) or GSK3787 (antagonist; 25 μmol/L, Cayman Chemical Company). Controls also contained dimethyl sulfoxide (DMSO, solvent for the tested PPAR ligands). After the incubation, tissue explants were frozen at −80 °C until further analysis. ## 4.3. RNA Isolation, Library Preparation and Sequencing Procedure Total RNA from 20 samples was isolated using the “RNeasy Mini Kit” (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. The Tecan Infinite M200 plate reader (Tecan Group Ltd., Männedorf, Switzerland) and Agilent Bioanalyzer 2100 (Agilent Technology, Santa Clara, CA, USA) were used to evaluate total RNA quantity and quality. The samples with an RNA Integrity Number (RIN) of >7 were selected for the next analyses. The poly(A) RNA-sequencing library was prepared according to the Illumina TruSeq Stranded mRNA Sample Preparation Protocol. Two rounds of purification were performed using oligo(dT) magnetic beads to purify the poly(A) tailed mRNA. Subsequently, the poly(A) RNA was fragmented at high temperature using a divalent cation buffer, and poly(dT) oligonucleotides were used to transcribe the RNA into cDNA. Subsequently, the cDNA was subjected to 3’ tail adenylation and adapter ligation. Reverse transcription during library construction was strand-specific. Finally, the libraries were pooled and then sequenced. Quality control analysis and quantification of the sequencing libraries were performed using the Agilent Technologies 2100 Bioanalyzer High Sensitivity DNA Chip. Paired-end sequencing was performed using the Illumina NovaSeq 6000 Sequencing System (LC Science, Houston, TX, USA). ## 4.4. Transcript Assembly and Analysis of Differentially Expressed Genes FastQC was used to assess sequence quality. After removing low-quality reads, the remaining 150 bp paired-end sequences were reassembled and mapped to the *Sus scrofa* genome using HISAT2 [67,68]. The mapped reads from each sample were assembled using StringTie [68]. All transcriptomes were then merged to reconstruct a comprehensive transcriptome using Perl scripts and GffCompare. Once the final transcriptome was constructed, StringTie and edgeR [69] were used to estimate the expression levels of all transcripts. StringTie was used to determine the expression of mRNAs by calculating fragments per kilobase of transcript per million (FPKM) [68]. Differentially expressed genes (DEGs) were selected with log2 (fold change) > 1 or log2 (fold change) < −1 and with statistical significance (p-value < 0.05) using the R package edgeR [69]. ## 4.5. Real-Time PCR Differentially expressed genes were validated via real-time PCR using the AriaMx real-time PCR System (Agilent Technology, Santa Clara, CA, USA), as previously described [70]. Primer sequences (Supplemental Table S1) for reference and target genes (IL-6, SOD2, CD180, ANGTPL4, PPARβ/δ) were designed via Primer Express Software 3 (Applied Biosystems, Waltham, MA, USA). The abundance of the tested mRNAs was calculated using the comparative Pfaffl method [71]. The constitutively expressed ACTB and GAPDH genes were implemented as reference genes, and the geometric mean values of the expression levels were used for analysis. Real-time PCR results were analyzed using Statistica software (version 13.1; Statsoft Inc. Tulsa, OK, USA) with Student’s t test and expressed as means ± SEM. Results were considered statistically significant at p ≤ 0.05. ## 4.6.1. Tissue Extract Preparation for Biochemical Analyses The extract of the CL tissue after in vitro culture for biochemical analyses (in 5 technical replicates of each sample) was prepared via mechanical homogenization (Omni tissue Homogenizer, Kennesaw, GA, USA) in sterile PBS. Extracts were centrifuged (5000× g) at 4 °C for 15 min, and the supernatant was transferred to new tubes containing 500 μL. Protein concentration was determined using the bicinchoninic acid method (Pierce BCA Protein Assay Kit, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol. ## 4.6.2. Antioxidant Capacity Total antioxidant capacity (TAC) was analyzed using the improved ABTS radical cation decolorization assay according to Re et al. [ 72]. The pre-formed radical monocation of 2,2’-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS*+) was generated via the oxidation of ABTS with potassium persulfate and was reduced in the presence of such hydrogen-donating antioxidants. The results were calculated as Trolox (a water-soluble analogue of vitamin E) equivalents per L per mg of protein. ## 4.6.3. Peroxidase Activity Preoxidase activity was determined according to the method described by Chance and Maehly [73]. The method consists of determining the content of purpurogallin, an orange crystalline compound in the incubation mixture, formed when pyrogallol is oxidized as a hydrogen donor in the presence of hydrogen peroxide. Samples were mixed with pyrogallol and hydrogen peroxide and incubated at 30 °C for 4 min. Absorbance was measured at 430 nm against air. The difference between the absorbance of the control sample (0.05 M acetate buffer at pH 5.6 was added instead of the tissue homogenate) and the tested sample (tissue homogenate) was a measure of enzyme activity. The millimolar absorbance coefficient for purpurogallin was 2.47/mM·cm. Enzyme activity was converted to mg of protein in the assay. ## 4.6.4. Catalase Activity The measurement method is based on the ability of catalase to decompose hydrogen peroxide [74]. The reaction is accompanied by a decrease in absorbance at a wavelength of 240 nm. Briefly, samples were diluted 20 times with 0.2 M phosphate buffer at pH 7. A total of 100 µL of H2O2 was then added to 200 µL of the sample. The absorbance was measured relative to the control (buffer instead of sample) for 30 s at 5 s intervals. The value of the decrease in absorbance was determined and the activity expressed in katal per mg of protein. ## 4.6.5. Superoxide Dismutase Activity The method for determining the activity of superoxide dismutase (SOD) uses the ability of p-iodonitrotetrazolium [2-(4-iodophenyl-3-(4-nitrophenyl)-5-phenyltetrazolium; INT] to be reduced to a water-soluble product with an absorption maximum at about 505 nm (reddish pink) by superoxide anion (O2−), which is formed during the oxidation reaction of xanthine by xanthine oxidase [74]. The rate of reduction of INT is linearly related to the activity of xanthine oxidase and is inhibited by SOD. Superoxide dismutase inhibits the reduction of INT to purple formazan by scavenging this radical. The rate of formazan formation is a measure of the activity of SOD [75]. The activity of SOD was expressed in arbitrary units [a. u.] per mg of protein. ## 4.6.6. Glutathione S-Transferase Activity The glutathione S-transferase (GST) activity was determined using the Rice-Evans [76] method. Enzyme activity was calculated based on the millimolar absorption coefficient (9.6 mmol−1/cm−1) for the glutathione conjugate formed from 1-chloro-2,4-dinitrobenzene. The GST activity was converted to arbitrary units [a. u.] per mg of protein. ## 4.6.7. Statistical Analysis for Biochemical Analyses Statistical analysis for the obtained results was performed using t-test in Prism 9 software (version 9.1.1 [223]; GraphPad Software Inc., San Diego, CA, USA). Results were considered statistically significant at p ≤ 0.05 (*) and p ≤ 0.002 (**). ## 5. Conclusions In conclusion, this is the first report describing the in vitro effects of different doses of PPARβ/δ agonist (GW0742) on LPS-induced inflammation in the CL. We imply that PPARβ/δ ligands act in two ways depending on the dose. We have shown that both doses of the ligand exert a positive effect on the oxidative status during inflammation. 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--- title: Changes in Bone Metabolism in Patients with Rheumatoid Arthritis during Tumor Necrosis Factor Inhibitor Therapy authors: - Tanja Janković - Momir Mikov - Jelena Zvekić Svorcan - Ivana Minaković - Jelena Mikov - Ksenija Bošković - Darko Mikić journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003627 doi: 10.3390/jcm12051901 license: CC BY 4.0 --- # Changes in Bone Metabolism in Patients with Rheumatoid Arthritis during Tumor Necrosis Factor Inhibitor Therapy ## Abstract Tumor necrosis factor alpha (TNF-α), which enhances osteoclast activity and bone resorption, is one of the key inflammation mediators in rheumatoid arthritis (RA). The aim of this study was to assess the influence of yearlong TNF-α inhibitor application on bone metabolism. The study sample comprised 50 female patients with RA. Analyses involved the osteodensitometry measurements obtained using a “Lunar” type apparatus and the following biochemical markers from serum: procollagen type 1 N-terminal propeptide (P1NP), beta crosslaps C-terminal telopeptide of collagen type I (b-CTX) by ECLIA method, total and ionized calcium, phosphorus, alkaline phosphatase, parathyroid hormone and vitamin D. Analyses revealed changes in bone mineral density (BMD) at L1–L4 and the femoral neck, with the difference in mean BMD (g/cm2) not exceeding the threshold of statistical significance ($$p \leq 0.180$$; $$p \leq 0.502$$). Upon completion of 12-month therapy, a significant increase ($p \leq 0.001$) in P1NP was observed relative to b-CTX, with mean total calcium and phosphorus values following a decreasing trend, while vitamin D levels increased. These results suggest that yearlong application of TNF inhibitors has the capacity to positively impact bone metabolism, as indicated by an increase in bone-forming markers and relatively stable BMD (g/cm2). ## 1. Introduction Rheumatoid arthritis (RA) is a systemic, autoimmune, chronic inflammatory disease that affects bone metabolism by increasing bone resorption, leading to osteoporosis and a high risk of fracture [1,2]. The presence of numerous proinflammatory cytokines in RA is associated with the activation of osteoclastogenesis, with tumor necrosis factor alpha (TNF-α) playing a leading role in this process. TNF-α stimulates the expression of the receptor activator of nuclear factor kB ligand (NF-kB), RANKL, which is instrumental in osteoclast differentiation and maturation. It can also exert its influence through the soluble receptor osteoprotegerin (OPG), or via stromal cells of the bone marrow lineage of osteoblasts, as well as by directly activating the cells in osteoclast lineage [3]. The interaction between RANKL and its receptor-activator of nuclear factor kB (RANK) occurs on the surface of osteoclasts by forming a RANKL/RANK bond that leads to accelerated differentiation, maturation, activation and life extension of osteoclasts, which initiates the bone resorption process. The OPG soluble part of the receptor for RANKL, which is structurally homologous to RANK, by binding to RANKL forms a RANKL/OPG bond that inhibits the final phase of osteoclast differentiation as well as activation of matrix osteoclast suppression, while accelerating osteoclast apoptosis. Therefore, balance between RANKL and OPG is the main regulatory factor of the biological balance involving bone formation and resorption [4,5,6]. TNF-α can stimulate osteoclast precursors directly through TNF receptor 1 (TNFR1) signaling, while soluble TNF is responsible for mobilization of osteoclasts from the bone marrow. Binding of TNF-α to receptors activates intracellular cascades that include NF-κB and mitogenic activation of protein kinase, thus transmitting information from the receptor to the nucleus [7]. Osteoblast differentiation and activity are influenced by TNF-α, while NF-kB signaling inhibits the regulation of bone morphogenetic protein (BMP) [8]. As Wnt uses a co-receptor (frizzled receptor and lipoprotein receptor 5 − LPR5) to activate, its transduction pathway is presently considered the most important for the control of osteoblast differentiation. In addition, in interaction with the Wnt signaling pathway, TNF-α plays an important role in the control and differentiation of osteoblasts, as TNF-α stimulates Dkk-1 (Dickkopf-related protein 1) expression of the endogenous Wnt signal inhibitor. During this process, Dkk-1 binds to the LDL-receptor LRP5 or LRP6 of osteoblasts, which inhibits their activity and enhances osteoclastogenesis [9]. By stimulating the production of sclerostin—a hormone produced by osteocytes—TNF reduces preosteoblast differentiation into osteoblasts and thus inhibits bone tissue formation [10,11]. Clinical tracking of the bone remodeling process consists of the determination of biochemical markers of bone resorption and bone formation in serum and urine, allowing bone metabolism, bone resorption rate and fracture risk to be assessed [12,13]. Together with the determination of inorganic matrix markers (i.e., total and ionized calcium, phosphorus and alkaline phosphatase), hormones closely related to bone metabolism—parathyroid hormone (PTH) and vitamin D—are also determined. The International Osteoporosis Foundation (IOF) and International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) recommend tracking of biochemical marker serum procollagen type I N propeptide (P1NP) as an indicator of bone synthesis and Beta-CrossLaps/serum C-terminal cross-linking telopeptide of type I collagen (b-CTX) as an indicator of bone resorption [14,15]. According to the European League Against Rheumatism (EULAR) guidelines, introduction of biological drugs is recommended in patients with highly active RA that have not responded well to the previously applied therapy [16]. The application of biological drugs—various proteins with immunomodulation capability (i.e., direct regulation of immune response)—has initiated a new concept in RA treatment. Some of the most frequently applied biological drugs are so-called TNF inhibitors, as their mechanism of action is based on blocking proinflammatory cytokine TNF-α. Besides their desirable influence on disease activity, these drugs impact local and general loss of bone mineral density (BMD). Presently, different TNF inhibitors are utilized in RA treatment, including etanercept, adalimumab, golimumab, infliksimab and certolizumab pegol [17,18]. However, TNF inhibitor choice should be individualized to each patient. Etanercept is applied as subcutaneous injections, which are administered once a week in 50 mg doses, while both adalimumab (in 40 mg doses) and certolizumab pegol (in 50 mg doses) are administered at biweekly intervals, and golimumab is applied once a month in 50 mg doses. Infliksimab is applied intravenously starting with 3 mg/kg doses [19,20]. These medications can be particularly beneficial for mitigating the high rate of general bone mass loss in RA patients, given the evidence of 2.1–$2.7\%$ BMD loss in lumbar spine and 1.7–$3.6\%$ in femoral neck in this population [21]. Moreover, in findings yielded by the multi-center study conducted by Chopin et al., as a part of which the impact of 12-month infliksimab therapy on bone metabolism was tracked, this TNF inhibitor had the capacity to increase bone-forming markers and decrease bone resorption markers [22]. Similar results were obtained by Orsolini and colleagues based on treating 68 RA patients with infliksimab [23]. Their findings revealed a significant increase in the bone-forming marker P1NP accompanied by a significant decrease in the bone resorption marker beta-crosslaps. As extant research mostly focused on the capacity of infliximab and adalimumab to induce changes in bone mineral density and the biochemical markers of bone resorption and synthesis, the aim of the present study was to evaluate the effectiveness of 12-month TNF-α inhibitor (etanercept, adalimumab, golimumab and infliximab) therapy in terms of bone metabolism improvements in patients with rheumatoid arthritis. ## 2.1. Study Design and Participants This research involved 50 female patients in whom the rheumatoid arthritis diagnosis was made on the basis of American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria published in 2010 [24], and whose clinical status indicated that they would benefit from biological drugs from the TNF inhibitor group. The study was conducted at the Special Hospital for Rheumatic Diseases Novi Sad, Serbia. It was designed as a 12-month-long retrospective/prospective study that would include all patients treated with a biological drug from the TNF-inhibitor group in the Special Hospital for Rheumatic Diseases in Novi Sad, Serbia. In order to obtain valid results, our sample was as homogeneous as possible in terms of disease type, gender, age, disease length and activity, and treatment method. Our cohort comprised 50 female patients, which was sufficient, as 48 individuals were the minimum required to attain $10\%$ margin of error and $85\%$ confidence level. The study inclusion criteria (all of which had to be present in an individual to be considered for participation in the study) were: menopause duration <5 years, RA diagnosis within the last 10 years, methotrexate (MTX) therapy (at a stable dose of 10 mg/week at a minimum), no glucocorticoid therapy, anatomical stage II of joint destruction, and Disease Activity Score-28 DAS28 > 5.1. The study exclusion criteria (presence of any of which would preclude participation in the study) were: menopause duration > 5 years; RA duration > 10 years, anatomical stage III (destruction of bone as well as cartilage, joint deformities) or stage IV (fibrous or bony ankylosis, advanced muscle atrophy, joint deformities) of joint destruction; presence of any disease with adverse repercussions for bone tissue, such as malignant tumors, kidney and liver insufficiency, endocrine diseases (Cushing syndrome, hyperthyroidism, hyperparathyroidism, hypoparathyroidism, hyperprolactinemia, acromegaly); therapy involving drugs that impact bone metabolism (low-molecular-weight heparin, aromatase inhibitors, anticonvulsants, antipsychotics, antidiabetics, L-thyroxin in supraphysiological doses); and prolonged immobility. All patients that were eligible for participation and were willing to take part in the study signed the informed consent form. Moreover, all participants received vitamin D supplements (800 IU per day) during the study period. All performed procedures were in conformity with the ethical standards of the institutional research committee and with the Helsinki Declaration and its subsequent amendments or comparative ethical standards. The study was approved by the Ethics Committee of the Special Hospital for Rheumatic Diseases, Novi Sad, Serbia, protocol code $\frac{14}{35}$-$\frac{5}{1}$-016, and by the Ethics Committee of the Medical Faculty, University of Novi Sad, Serbia, protocol code 01-$\frac{39}{148}$/1. ## 2.2. Measurements At entry, all medical documentation was reviewed, rheumatologic examination was conducted, pain threshold was determined, and global RA activity was assessed through visual analogue scale (VAS). The VAS is a subjective measure of symptom severity; it was used in the present study to allow respondents to rate perceived extent of pain on a scale from 0 (indicating absence of pain) to 100 mm (corresponding to almost unbearable pain) [25]. For disease activity assessment, clinical index Disease Activity Score-28 with serum CRP levels (DAS28 CRP) and erythrocyte sedimentation rate (ESR) (DAS28 ESR) were adopted. The Disease Activity Score-28 is a combined index that measures disease activity in patients with rheumatoid arthritis based on both 28 tender joint count (TJC) and swollen joint count (SJC), as well as a laboratory measure of acute inflammation (serum CRP levels or erythrocyte sedimentation rate) and patient global health assessment (PGA) of disease severity on a 0–10 cm scale. The activity score can be calculated according to the following formula: DAS28-CRP = 0.56 * √(TJC28) + 0.28 * √(SJC28) + 0.36 * ln (CRP + 1) + 0.014 * (PGA) + 0.96; DAS28-ESR = 0.56 * √(TJC28) + 0.28 * √(SJC28) + 0.70 * ln (ESR) + 0.014 * (PGA) [26]. The final score of DAS28-CRP or ESR ≤ 2 indicates that the patient is in remission, while scores in the 2.6–3.2 and 3.2–5.1 ranges are indicative of low and moderate disease activity, respectively, and those above >5.1 signify high activity [26]. In addition to the aforementioned evaluations, a health assessment questionnaire (HAQ) was administered to all study participants to assess their degree of incapability. It comprises 20 items classified under eight categories pertaining to activities of daily living: dressing, arising, eating, walking, hygiene, reach, grip, and common daily activities. Each item is rated on a 0–3 scale, where 0 indicates “without difficulty” and 3 indicates “unable to do”, and additional points can be added if aids or devices are needed for performing specific activities. The final score is calculated by summing the scores obtained for each of the categories and dividing this value by the number of categories, resulting in the 0–3 range, where a higher figure indicates poorer quality of life [27]. The body mass index (BMI) is a quantitative ratio of body mass expressed in kilograms (kg) and body height expressed in meters squared (m2), and was used to classify the study participants into six groups: severely underweight (BMI ≤ 16.49 kg/m2), underweight (BMI = 16.50–18.49 kg/m2), normal weight (BMI = 18.50–24.99 kg/m2), overweight (BMI = 25.00–29.99 kg/m2), obese (BMI = 30.00–34.99 kg/m2), and severely obese (BMI ≥ 35.00 kg/m2) [28]. Bone mineral density (BMD) was measured in two regions—front-end lumbar spine (LS) region L1–L4 and the left proximal femoral neck—at the beginning and end of the 12-month TNF inhibitor treatment. BMD measurements were performed by the same technician using the dual energy X-ray absorptiometry (DXA) method on the “Lunar” type apparatus. The coefficient of variation (CV) in the measurements performed at our hospital was $0.8\%$, as determined daily using the anatomical spine phantom, and no machine drift was detected during the study period. The short-term in vivo precision error for L2–L4 lumbar spine is 0.012 g/cm2 (LSC = 0.034 g/cm2 at the $95\%$ confidence level) and is 0.013 g/cm2 for femur neck (LSC = 0.035 g/cm2 at $95\%$ confidence level). The obtained T-scores were used to classify the participants into three groups: normal (T-score > −1), osteopenia (T-score in the −1 to −2.5 range) and osteoporosis (T-score < −2.5) [29]. ## 2.3. Biochemical Analysis Blood tests were also performed at the beginning and end of the study, focusing on sedimentation (SE), C-reactive protein (CRP), ionized and total calcium, phosphorus, 25(OH) vitamin D, alkaline phosphatase, parathyroid hormone (PTH), and biochemical bone markers procollagen type I N propeptide (P1NP) and Beta-CrossLaps/serum C-terminal cross-linking telopeptide of type I collagen (b-CTX). Erythrocyte sedimentation rate was determined by the Westergren method, while ionized calcium and phosphorus were measured via the usual spectrophotometric laboratory procedure based on ion exchange using ion exchange electrodes. Alkaline phosphatase was measured by spectrophotometry, and P1NP and b-CTX were determined using ECLIA methods. Blood samples were collected between 7:00 a.m. and 9:00 a.m. after an overnight fast. ## 2.4. Statistical Analysis All statistical analyses were performed using Windows SPSS ver. 24 (Statistical Package for the Social Sciences) with p ≤ 0.05 signifying statistical significance. First, the distribution of numerical variables was examined using the Kolmogorov–Smirnov test. As only age was found to be normally distributed, it was presented as mean ± SD (standard deviation), while median (IQR) was calculated in all other cases, and frequencies and percentages were reported for categorical variables. The differences between the parameters measured at two time points were tested by the non-parametric Wilcoxon signed-rank test (Z). ## 3.1. Baseline Clinical Characteristics The study sample comprised 50 female RA patients aged 51.50 ± 3.94 years, $84\%$ of whom were diagnosed within the preceding 5 years, and $95\%$ and $92\%$ were positive for rheumatoid factor (RF) and anti-cyclic citrulline peptide antibodies (ACPA), respectively. All patients received methotrexate in stabile doses (15–17.5 mg/week) and were treated by TNF inhibitors as the first biological drug, whereby $46\%$, $34\%$, $18\%$, and $2\%$ of the sample received adalimumab, etanercept, golimumab, and infliximab, respectively. Based on their BMI, $62\%$ of the patients were mildly (either slightly or moderately) obese, and the remaining $36\%$ and $2\%$ had optimal weight and were severely obese, respectively (Table 1). TNF inhibitor therapy resulted in a statistically significant improvement in all disease activity parameters compared to the baseline. Specifically, DAS28 SE (Z = −5.71, p ˂ 0.001), SE (mm/h) (Z = −5.97, p ˂ 0.001) and CRP (Z = −5.90, p ˂ 0.001) exhibited statistically significant decreases. ## 3.2. Effect of TNF Inhibitors on Bone Mineral Density The obtained findings indicated changes in the measured BMD (g/cm2) values after 12-month TNF inhibitor therapy relative to the baseline, but the difference did not exceed the threshold of statistical significance ($Z = 1.34$, $$p \leq 0.180$$; $Z = 0.67$, $$p \leq 0.502$$), as shown in (Table 2). Prior to initiating the TNF inhibitor therapy, all but one patient had P1NP values in the reference range (16.3–73.9 ng/mL). Upon therapy completion, all patients had P1NP values in the reference range, and the overall improvement in this biomarker (42.30 [IQR = 21.67] vs. 59.30 [IQR = 18.27]) was statistically significant (Z = −6.07, p ˂ 0.001). Although a majority of patients ($78\%$) had the biochemical marker b-CTX in serum values within the reference range (556–1008 ng/mL) before starting the TNF inhibitor therapy, upon its completion, this percentage increased to $94\%$, (593.00 [IQR = 63.00] vs. 627.50 [IQR = 100.00]), and the overall increase in this parameter was statistically significant (Z = −4.78, p ˂ 0.001). Analyses further revealed that BMI impacted changes in both P1NP and b-CTX values, whereby the greatest increases in P1NP and b-CTX were observed in patients with optimal body mass (Table 3). A further goal of our analysis was to determine if BMD, P1NP and b-CTX changes related to different TNF inhibitors were statistically significant. Since only $2\%$ of patients received infliximab, its influence on the observed parameters was not assessed. Moreover, changes induced by the remaining three TNF inhibitors in T-score (SD) and BMD (g/cm2) were comparable. Even though the differences were not statically significant, the greatest increase in P1NP was noted in patients treated with golimumab, while those treated with etanercept had the greatest increase in b-CTX (Table 4). ## 3.3. Changes in Other Parameters of Bone Metabolism after One-Year Use of TNF Inhibitors The values of other observed bone metabolism parameters also changed following the 12-month TNF inhibitor therapy. Specifically, a decrease in average values was noted for total calcium (from 2.30 [IQR = 0.24] to 2.30 [IQR = 0.20]; Z = −3.07, $$p \leq 0.002$$), ionized calcium (from 1.12 [IQR = 0.09] to 1.10 [IQR = 0.06]; Z = −4.35, p ˂ 0.001), and phosphorus (from 1.00 [IQR = 0.13] to 1.00 [IQR = 0.10]; Z = −2.55, $$p \leq 0.011$$). While 25(OH) vitamin levels increased from 44.00 [IQR = 20.00] mol/L to 51.50 [IQR = 16.25] (Z = −5.06, p ˂ 0.001), no statistically significant changes were noted in the average values of alkaline phosphatase (Z = −1.53, $$p \leq 0.124$$). Two-way analysis of variance (ANOVA) was also conducted to examine the joint effect of TNF-α inhibitors and vitamin D on the examined bone metabolism parameters. The obtained results did not exceed the threshold of statistical significance ($$p \leq 0.037$$). ## 4. Discussion In the extant literature, the presence of numerous proinflammatory cytokines in rheumatoid arthritis (RA) is associated with localized inflammatory bone resorption and generalized bone loss. Available findings further indicate that the receptor activator of nuclear factor kB (RANK)-RANK ligand (RANKL) system is the main driver of inflammatory bone resorption [30]. On the other hand, the use of TNF inhibitors has been shown to affect bone metabolism by increasing the P1NP and osteocalcin (OC) serum level (as bone synthesis markers), and decreasing the levels of serum b-CTX and RANKL (as bone resorption markers in RA), thus slowing down generalized osteoporosis and the development of periarticular erosions [31]. Guided by this evidence, the aim of the present study was to evaluate the impact of 12-month use of TNF inhibitors on changes in bone mineral density and biochemical markers of bone synthesis (P1NP) and resorption (b-CTX). These markers were chosen, as our sample comprised solely women aged 51.50 ± 3.94 years, and it is widely known that estrogen affects bone homeostasis directly (via the effect on bone cells through the RANKL-RANK-OPG pathway), as well as indirectly through an immune mechanism by mitigating the increase in cytokine (such as IL-1, IL-6 and TNF) production caused by estrogen deficiency. In this context, TNF-α (produced by T-lymphocytes in the bone marrow) is particularly significant, as it is the most influential cytokine in bone loss caused by estrogen deficiency. In our cohort, menopause duration did not exceed 5 years, which is relevant as estrogen levels decrease rapidly during menopause, which in turn activates the differentiation and proliferation of osteoclasts while inhibiting the action of osteoblasts and increasing osteocyte apoptosis. All of these effects accelerate bone resorption, as confirmed by extant evidence indicating that the onset of estrogen decline coincides with a phase of rapid bone loss, resulting in $10\%$ and $5\%$ bone mass loss in the spine and hip, respectively, during the 5 five years of menopause. Some estimates further suggest that after 10–15 years of menopause, about $50\%$ of trabecular and $30\%$ of cortical bone is lost [32]. Our findings indicate that 12-month use of TNF inhibitors attenuates the decline in BMD measured at the L1–L4 level as well as in the femoral neck area. Moreover, although the increase in BMD values for the lumbar spine and hip did not exceed the threshold of statistical significance, we observed statistically significant improvements in the corresponding T-score (SD) values. Our findings are in agreement with the results reported by Nutz et al. based on a meta-analysis of 15 studies that included 12-month TNF-inhibitor treatment in patients with RA [33]. Similarly, Zerbini and colleagues analyzed 28 studies in which participants received TNF inhibitors and observed their beneficial effect on preserving or increasing BMD in the lumbar spine and hip, as well as achieving a better biochemical bone marker profile [34]. Findings reported by other authors yielded similar conclusions [35,36,37,38]. It is also worth noting that, by analyzing the effect of TNF inhibitors on bone metabolism in RA patients over a 15-month period, Jura-Poltorak et al. confirmed that they are effective in arresting bone loss. However, in their cohort, the improvements in BMD in the lumbar spine and femoral neck, as well as the corresponding T scores, failed to reach statistical significance. On the other hand, as the authors observed a statistically significant change in the levels of bone synthesis/resorption biochemical markers, it appears that these markers respond more rapidly to TNF inhibitor therapy compared to bone mineral density [39]. In the present study, a higher degree of bone resorption was associated with greater disease activity and b-CTX levels, which correlated with lower BMD values at the onset of TNF inhibitor therapy. Therefore, by monitoring b-CTX levels, we could predict further BMD loss. Our analyses also revealed that TNF inhibitors increased serum P1NP levels and mitigated the b-CTX increase, thus elevating the P1NP/b-CTX ratio. Moreover, TNF inhibitor use was positively correlated with changes in bone biochemical marker levels, which indicated a statistically significant increase in P1NP levels as well as improvements in b-CTX (which did not exceed the threshold of statistical significance). Finally, the observed changes in P1NP and b-CTX upon completion of 12-month TNF inhibitor administration were associated with RA disease activity reduction. Similar findings were reported by Szulc and colleagues based on an investigation involving 54 patients treated with TNF inhibitors for 12 months [40]. However, other authors reported statistically significant improvements in both parameters, while some also noted BMD increases in their cohorts [39]. To position our results in this context, we segregated our sample into younger (below 50 years) and older (50+ years) groups and examined their outcomes. These comparisons revealed that greater improvements in P1NP and b-CTX were associated with younger age ($30\%$ and $10.5\%$ for those under 50 vs. $26.8\%$ and $6.6\%$ for women over 50). Likewise, when the cohort was segregated by BMI, we determined that being underweight (BMI < 19), as well as overweight or obese (BMI > 25), was a risk factor for osteoporosis, as it resulted in more pronounced changes in bone metabolism. These observations concur with the available data, indicating that BMD declines more rapidly in obese individuals due to inadequate physical activity, hypertension, and suboptimal vitamin D levels [41]. In addition, adipose tissue secretes cytokines that affect bone tissue by increasing bone resorption, while adipokines affect the central nervous system by altering the influence of the sympathetic nervous system on bone tissue [42]. Therefore, it is not surprising that the greatest changes in P1NP values ($38\%$) and b-CTX ($8.4\%$) were recorded in patients of normal weight. Hypovitaminosis D is highly prevalent in patients suffering from inflammatory rheumatic diseases, especially RA, and may exacerbate the negative impact of inflammation on BMD. Vitamin D in its active form—25(OH)D—exhibits an immunoregulatory effect that manifests through the regulation of monocytes and macrophages as well as the activity of B and T cells. It is thus believed that vitamin D intake can reduce the production of proinflammatory cytokines such as TNF-α and IL-6, which play a key role in bone resorption in RA patients. Consequently, the potential beneficial role of vitamin D as a modulator of inflammation in RA is increasingly being discussed [43]. In our cohort, 12-month TNF inhibitor therapy resulted in a statistically significant reduction in disease activity (as measured by composite indices DAS28 SE and DAS28 CRP), while increasing average vitamin D, total calcium, ionized calcium, and phosphorus values. These observations are supported by the findings reported by Oelzner et al., indicating that high RA activity is associated with changes in vitamin D metabolism and increased bone resorption [44], which is expected given that lower serum vitamin D levels may contribute to negative calcium balance and inhibition of bone formation. Similar conclusions were reached by Scott et al. and Lin et al. based on their meta-analyses of available studies [45,46]. However, given the paucity of comparative studies focusing on the efficacy of different TNF inhibitors (mostly tocilizumab and abatacept), our findings regarding the changes in BMD and bone synthesis/resorption biochemical markers can only be directly compared with those reported by Sainaghi and colleagues, with which they concur [47]. It is also worth noting that, even though 12-month administration of all tested biological drugs resulted in an increase in P1NP and b-CTX, the highest percentage increase in P1NP was achieved with adalimumab ($34\%$), followed by golimumab ($32.6\%$) and finally etanercept ($18.7\%$). In contrast, b-CTX was most significantly modified by etanercept ($9.21\%$), followed by adalimumab ($7.48\%$) and finally by golimumab ($4.94\%$). The significance of our study derives from the inclusion of biologically naïve patients who were selected based on clearly defined criteria, excluding individuals taking glucocorticoids and other drugs as well as those suffering from diseases that are known to impact bone remodeling (which would affect any changes in BMD that occurred during the study period). This rigorous research design allowed us to obtain a clearer picture of the effect of TNF inhibitors on BMD. Furthermore, several variables—SE, CRP, PTH, vitamin D 25(OH) level, DAS28 SE and DAS28 CRP, and self-reported quality of life—that could potentially affect bone metabolism were monitored. Based on these analyses, we hypothesize that TNF inhibitors are not only effective in controlling inflammation, but may also directly inhibit osteoclast activity. Nonetheless, when interpreting our findings, several limitations to our study should be considered, one of which was a small sample size, which was partly due to the strict study inclusion/exclusion criteria, but was also a result of stringent approval protocols implemented for the administration of biological drugs (including TNF inhibitors). Therefore, as a part of our investigation, we were unable to detect minor changes in the observed variables. Moreover, the 12-month follow-up period was potentially insufficient for emergence of meaningful BMD improvements in our patient cohort. A further limitation of the present study stems from the lack of a control group that would have allowed us to better understand the effect of TNF inhibitors on bone marker values, as any changes in the treatment group could be compared with both the baseline and the controls. This shortcoming should be rectified in future studies, allowing the potential beneficial effects of biological drugs, including TNF inhibitors, on inflammatory bone loss to be assessed more precisely. ## 5. Conclusions In our cohort comprising 50 female RA patients, 12-month TNF inhibitor therapy had a positive effect on bone metabolism. Increased P1NP and b-CTX values were accompanied by rapid bone remodeling, which was not dependent on the changes in BMD values. Moreover, TNF inhibitor application prevented a decline in BMD (g/cm2), whereby changes in BMD values did not differ among examined biological drugs. ## References 1. Chen T.L., Chang K.H., Su K.Y.. **Effects of Biological/Targeted Therapies on Bone Mineral Density in Inflammatory Arthritis**. *Int. J. Mol. Sci.* (2022.0) **23**. DOI: 10.3390/ijms23084111 2. 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--- title: Chronic Exposure to High Fat Diet Affects the Synaptic Transmission That Regulates the Dopamine Release in the Nucleus Accumbens of Adolescent Male Rats authors: - Wladimir Plaza-Briceño - Victoria B. Velásquez - Francisco Silva-Olivares - Karina Ceballo - Ricardo Céspedes - Gonzalo Jorquera - Gonzalo Cruz - Jonathan Martínez-Pinto - Christian Bonansco - Ramón Sotomayor-Zárate journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003643 doi: 10.3390/ijms24054703 license: CC BY 4.0 --- # Chronic Exposure to High Fat Diet Affects the Synaptic Transmission That Regulates the Dopamine Release in the Nucleus Accumbens of Adolescent Male Rats ## Abstract Obesity is a pandemic caused by many factors, including a chronic excess in hypercaloric and high-palatable food intake. In addition, the global prevalence of obesity has increased in all age categories, such as children, adolescents, and adults. However, at the neurobiological level, how neural circuits regulate the hedonic consumption of food intake and how the reward circuit is modified under hypercaloric diet consumption are still being unraveled. We aimed to determine the molecular and functional changes of dopaminergic and glutamatergic modulation of nucleus accumbens (NAcc) in male rats exposed to chronic consumption of a high-fat diet (HFD). Male Sprague-Dawley rats were fed a chow diet or HFD from postnatal day (PND) 21 to 62, increasing obesity markers. In addition, in HFD rats, the frequency but not amplitude of the spontaneous excitatory postsynaptic current is increased in NAcc medium spiny neurons (MSNs). Moreover, only MSNs expressing dopamine (DA) receptor type 2 (D2) increase the amplitude and glutamate release in response to amphetamine, downregulating the indirect pathway. Furthermore, NAcc gene expression of inflammasome components is increased by chronic exposure to HFD. At the neurochemical level, DOPAC content and tonic dopamine (DA) release are reduced in NAcc, while phasic DA release is increased in HFD-fed rats. In conclusion, our model of childhood and adolescent obesity functionally affects the NAcc, a brain nucleus involved in the hedonic control of feeding, which might trigger addictive-like behaviors for obesogenic foods and, through positive feedback, maintain the obese phenotype. ## 1. Introduction Obesity is a health problem worldwide characterized by an excess of fatty tissue and metabolic alterations [1]. In 2016, the World Health Organization (WHO) stated that globally, more than 1900 million adults (>18 years old) were overweight, and 650 million of these were obese [1]. In addition, 340 million children and adolescents (5 to 19 years old) were overweight or obese, representing an increase in the prevalence of overweight and obesity from $4\%$ in 1975 to more than $18\%$ in 2016 [1]. In Chile, according to The National Health Survey (2016–2017), $74.2\%$ of the population over 15 years old, shows some degree of weight excess, and $34.4\%$ of this population has obesity [2]. In this context, the search for new pharmacological treatments and targets for obesity remains a hot topic, mainly when anorectic agents used to combat obesity have been associated with severe adverse events, withdrawing them from the market (e.g., fenfluramine, dexfenfluramine, and sibutramine) [3]. Among the causes of this pandemic are an unhealthy lifestyle and an excess of obesogenic food intake characterized by hypercaloric content and high palatability [4]. Chronic exposure to this kind of diet affects brain areas such as the hypothalamus (associated with homeostatic eating control) and the reward system (related to hedonic eating control), leaving a predisposition to the development of overweight and obesity [5]. In some cases, the hyperstimulation of the reward system by obesogenic food (rich in fats and carbohydrates) could promote dependence or food addiction [6,7,8]. Dopamine (DA) neurons form the reward system or mesocorticolimbic circuit from the ventral tegmental area (VTA) whose efferents go to limbic and cortical regions such as nucleus accumbens (NAcc) and prefrontal cortex (PFC), respectively [9,10]. The VTA DA neurons are tonically inhibited by GABA interneurons [11,12]. Still, natural rewards (e.g., food, water, sex, and social interaction) and drugs of abuse (e.g., cocaine, amphetamine, ethanol, nicotine, and morphine, among others) disinhibit DA neurons, increase their firing rate, and DA release in NAcc and PFC [9,13,14,15]. In NAcc, the medium spiny neurons (MSNs), which are some kinds of GABAergic inhibitory neurons, are segregated by their electrical and synaptic properties into those that express preferentially DA receptor type 1 (D1) or type 2 (D2) [16,17]. It has been suggested that both D1- and D2-expressing MSNs are part of the GABAergic balance that regulates the DA release of DA from VTA [18,19]. In addition, VTA DA neurons are activated by orexinergic/glutamatergic neurons from the lateral hypothalamus (LH) [20], also promoting DA release in the NAcc [21]. Interestingly, LH orexinergic neurons’ activity is strongly controlled by inhibitory neurons from the lateral septum (LS), which also activate the firing of VTA DA neurons by inhibiting VTA GABA interneurons [22,23,24]. Feeding behavior is essential for the species’ survival and is highly regulated by integrating homeostatic and hedonic signals [25]. Chronic stimuli such as obesogenic food (rich in nutrients such as salt, fat, or sweets) promote maladaptive eating behavior that leads to eating disorders or obesity [26]. During the last decade, several works have studied that the reward system and other brain areas are susceptible to inflammation by chronic exposure to stimuli such as drug abuse and hypercaloric diets. For example, chronic exposure to ethanol (2 weeks) increases protein levels of tumor necrosis factor α (TNF-α) and interleukin-17A (IL-17A) in the PFC of female adolescent mice [27]. In contrast, one injection of methamphetamine (10 mg/kg) in rats increases protein levels of interleukin-1β (IL-1β) in VTA, NAcc, and PFC [28]. On the other hand, neuroinflammation in the reward system induced by obesogenic diets has been less studied. Recently, it has been shown that prolonged exposure to a cafeteria diet in male mice for six weeks increases mRNA expression of IL-1β and interferon-γ (IFN-γ) and microglial activation in NAcc [29], while exposure to a high-fat diet (HFD) for 12 weeks produces an increase in body weight and plasma levels of leptin, insulin, glycemia, C-reactive protein, and NAcc gene expression of IKKβ (Inhibitor of Nuclear Factor Kappa B Kinase Subunit Beta, a kinase that activates NF-κB), glial fibrillary acidic protein (GFAP), ionized calcium-binding adapter molecule 1 (Iba-1), IL-1β, IFN-γ, and cluster of differentiation 45 (CD45) [30]. In summary, obesity induces pathophysiological alterations in brain areas associated not only with homeostatic control of food intake but also in nuclei of hedonic control of eating, where patterns of neurotransmitter release, gene expression, and synaptic communications are affected. In this work, we will unravel the molecular, electrophysiological, and neurochemical deregulations in NAcc associated with the childhood and adolescent obesity model. In addition, this work opens the possibility of studying NAcc as a pharmacological target to regulate hedonic food intake. ## 2.1. Murinometric Parameters in Rats Exposed to HFD The growth curve (Figure 1A) shows a positive slope in weight gain for both control and HFD-fed rats. HFD rats have an increased weight from postnatal day (PND) 56 to 62 compared to controls (Interaction: [F[30, 2046] = 14.90; $p \leq 0.0001$]; Time: [F [30, 2046] = 1300; $p \leq 0.0001$]; Diet: [F [1, 2046] = 394.7; $p \leq 0.0001$]). Body weight (Figure 1B; $$p \leq 0.0065$$) and retroperitoneal fat (Figure 1C; $p \leq 0.0001$) at PND 62 were higher in HFD rats compared to those of control rats. ## 2.2. Electrophysiological Recordings in NAcc of Rats Exposed to HFD Excitatory glutamatergic afferents to NAcc MSNs from the prefrontal cortex are modulated by mesolimbic DA neurons in a frequency-dependent manner [31,32,33]. In addition, rewards such as foods and drugs of abuse increase DA release in NAcc and PFC [9]. However, we do not know if, in our childhood and adolescent obesity model, the glutamatergic synaptic activity is affected in NAcc. First, we classify as putative D1-like and D2-like MSNs in NAcc which is a form of short-term synaptic plasticity between control and HFD male rats, stimulating the PFC afferents electrical; according to the electrophysiological characterization of MSN described in the dorsal striatum, the D1-MSNs and D2-MSNs can be identified by exhibiting a non-facilitating and a facilitating response to paired-pulse protocol, respectively (Figure S1) [16,34,35,36,37]. In this work, control and HFD rats showed the two subpopulations of MSNs, which showed a non-facilitation or facilitation by paired-pulse protocol and in turn we named D1-like MSNs and D2-like MSNs, respectively (Figure 2A; control: (D1-like MSNs 0.9270 ± 0.0318, $$n = 10$$ and D2-like MSNs 1.1450 ± 0.0312, $$n = 7$$, $$p \leq 0.0001$$) vs. HFD: (D1-like MSNs 0.8380 ± 0.0506, $$n = 9$$ and D2-like MSNs 1.2230 ± 0.0312, $$n = 9$$, $p \leq 0.0001$)). Interestingly, the proportions of D2-like MSNs in HFD rats ($52.9\%$) were significantly higher than in control rats ($34.5\%$) (Figure 2A; $$p \leq 0.0077$$). Jointly, we found that in basal conditions in overall cells, the frequency of spontaneous excitatory postsynaptic currents (sEPSC) was higher in HFD than in control rats (Figure 2B, basal; HFD 1.395 ± 0.175; $$n = 13$$ vs. control 0.718 ± 0.175; $$n = 11$$; $$p \leq 0.046$$, respectively). This finding suggests that the neurotransmitter release or excitability of glutamatergic afferents in HFD rats increases. Then, to assess if the D1-like and D2-like cells are differentially modified by diet, we separated the sEPSC analysis of D1 or D2- like MSNs, revealing significant changes in control and HFD frequency, except in control D2-like MSNs (Figure 2B, control D1-like MSNs, basal 0.652 ± 0.1949, $$n = 6$$ vs. amphetamine 0.1898 ± 0.0465, $$n = 6$$, $$p \leq 0.0313$$; control D2-like MSNs, basal 0.7972 ± 0.3313, $$n = 5$$ vs. amphetamine 0.2149 ± 0.0622, $$n = 5$$, $$p \leq 0.125$$; HFD D1-like MSNs, basal 0.7904 ± 0.1756, $$n = 7$$ vs. amphetamine 0.4048 ± 0.0917, $$n = 7$$, $$p \leq 0.0156$$; HFD D2-like MSNs, basal 2.100 ± 0.6071, $$n = 6$$ vs. amphetamine 0.4434 ± 0.1355, $$n = 6$$, $$p \leq 0.313$$). The increased number of D2-like MSNs than D1-like MSNs in HFD rats could modify the DA neuromodulation of NAcc synaptic transmission. To test this, we assessed PPR and the EPSC amplitude in response to 0.1 µM amphetamine (AMPH) in control slices and HFD male rats. In control rats, PPR did not change in the presence of AMPH neither D1-like MSNs (before: 0.941 ± 0.037, $$n = 10$$ and after: 1.008 ± 0.047, $$n = 7$$, $$p \leq 0.812$$) nor D2-like MSNs (before: 1.134 ± 0.036 and after: 1.198 ± 0.019, $$n = 5$$, $$p \leq 0.125$$) (Figure 2C, left panel). However, in HFD rats, the PPR of the D2-like MSNs population decreased after adding AMPH (before: 1.213 ± 0.026 and after: 1.069 ± 0.064, $$n = 7$$, $$p \leq 0.049$$), while in D1-like MSNs did not change (before: 0.825 ± 0.055 and after: 0.945 ± 0.085, $$n = 8$$, $$p \leq 0.0780$$) (Figure 2C, right panel), suggesting that AMPH induce a selective increase in glutamate release on the D2-like MSNs. Furthermore, the EPSC amplitude of control rats did not change in the presence of AMPH neither D1-like MSNs (before: 56.47 ± 13.77 and after: 79.03 ± 18.03, $$n = 7$$, $$p \leq 0.109$$) nor D2-like MSNs (before: 52.31 ± 13.53 and after: 67.53 ± 13.92, $$n = 5$$, $$p \leq 0.625$$) (Figure 2D, left panel). However, in HFD rats, the EPSC amplitude of the D2-like MSNs population increased in the presence of AMPH (before: 41.410 ± 8.083 and after: 78.01 ± 16.76, $$n = 7$$, $$p \leq 0.031$$), while in D1-like MSNs the amplitude remained unchanged (before: 53.86 ± 13.27 and after: 59.41 ± 14.23, $$n = 8$$, $$p \leq 0.740$$) (Figure 2D right panel). These findings suggest that HFD showed a higher basal excitatory activity of D2-like MSNs than D1-like MSNs, which is selectively modulated by AMPH-induced DA release, presumably by a heterosynaptic mechanism at pre- and postsynaptic level. ## 2.3. Gene Expression of Neuroinflammatory Markers in NAcc of Rats Exposed to HFD Fatty acids from diet activate an intracellular protein complex member of nucleotide-binding oligomerization domain-like receptor family (NOD-like) pyrin domain containing 3 (NLRP3) [38]. The activation of NLRP3 recruits the adaptor protein (ASC), leading to the activation of caspase-1, a proteolytic enzyme that promotes the cleavage of proinflammatory cytokines to their mature forms (i.e., IL-1 β, IL-18) (Figure 3A) [39]. The pathophysiological implications of inflammasome activation have been related to developing diseases such as diabetes and obesity, among others [40]. In this context, the chronic exposure to HFD for six weeks increased the expression of Il-1b (Figure 3C; $$p \leq 0.0106$$), caspase-1 (Figure 3D; $$p \leq 0.0428$$), Nlrp3 (Figure 3E; $$p \leq 0.0001$$), and Gfap (Figure 3F; $$p \leq 0.0003$$). However, the mRNA levels of ASC were not affected in obese rats (Figure 3B; $$p \leq 0.8099$$). ## 2.4. Monoamine Contents in Brain Nuclei of the Mesolimbic and Nigrostriatal Pathways of Rats Exposed to HFD To evaluate the neurochemical effects of chronic exposure to HFD on DA, serotonin (5-HT), and its primary metabolites, the tissue content of these neurotransmitters was measured using HPLC coupled to electrochemical detection (ED) in NAcc, dorsolateral striatum (DLS), substantia nigra (SN), and VTA. Our data show that both DA (Figure 4A) and 5-HT (Figure 4C) concentration in NAcc, DLS, SN, and VTA were similar between controls and HFD rats. On the other hand, tissue content of 5-hydroxyindoleacetic acid (5-HIAA), a metabolite of 5-HT produced by monoamine oxidase (MAO), was again similar in the micro-dissected brain nuclei of controls and HFD rats (Figure 4D). Interestingly, the content of 3,4-dihydroxyphenylacetic acid (DOPAC), a DA metabolite produced by MAO, was significantly reduced in NAcc ($$p \leq 0.0247$$) and DLS ($$p \leq 0.0052$$) from obese male rats, without affecting its tissue content in SN and VTA (Figure 3B). ## 2.5. Ex-Vivo DA Release in NAcc of Rats Exposed to HFD Fast scan cyclic voltammetry (FSCV), an electrochemical technique, measured DA release in NAcc slices with sub-second resolution. Basal and amphetamine-induced DA release stimulated by a single pulse was reduced in NAcc of HFD rats (Figure 5A Basal $$p \leq 0.0131$$; 0.1 µM amphetamine (AMPH) $$p \leq 0.0125$$). In addition, NAcc DA uptake was decreased in the same conditions (Figure 5B Basal $$p \leq 0.0317$$; AMPH $$p \leq 0.0322$$). Representative peaks and color plots are observed in panel D, showing a lower peak height (DA release) and DA oxidation in NAcc of rats exposed to HFD for six weeks (Figure 5D). NAcc DA release evoked by phasic five-pulse stimulation was higher at 20, 40, and 100 Hz frequencies in HFD rats compared to control rats (Figure 5C) (Interaction: [F[4, 65] = 0.4804; $$p \leq 0.7500$$]; frequencies: [F [4, 65] = 25.87; $p \leq 0.0001$]; Diet: [F [1, 65] = 18.85; $p \leq 0.0001$]). ## 3. Discussion This work aimed to evaluate the synaptic, neurochemical, and molecular changes occurring in NAcc of male rats fed with HFD for six weeks (from PND 21 until PND 62). This period is a stage of infant-juvenile growth where the animals have sustained growth associated with a great anabolism of the musculoskeletal system. However, despite this period of high energy expenditure in our animal model, we can observe a significant increase in body weight and adipose tissue in rats exposed to HFD (Figure 1). In humans, the development of the reward system is established from the age of one to eight, while in rodents, it develops from the first to the fifth postnatal week [25]. Therefore, exposure to HFD during this period could strongly affect the reward system and the hedonic eating control, which is still in development. In this context, the administration of highly palatable foods such as chocolate, sweetened beverages, and snacks increases DA release in NAcc in adult rodents [41,42,43], leading to an increase in dopaminergic neurotransmission, similar to other stimuli such as drugs of abuse [13]. Indeed, chronic exposure to obesogenic foods produces behavioral and neurobiological aspects identical to drug addiction [44,45]. Interestingly, using positron emission tomography in humans, an increase in the availability of D2 was demonstrated in the ventral striatum, putamen, and midbrain of the obese compared to normal-weight subjects [46]. Exposure to a high-fat and sugar diet for 12 weeks in adult mice reduces D1 and increases D2 expression in NAcc [47]. In this sense, our electrophysiological data suggest that in HFD, the putative D2-like MSNs showed a higher basal glutamatergic activity which AMPH downregulates, than that of chow which was our control group. This decrease in sEPSC frequency induced by AMPH occurs along with the increase of glutamate release probability (i.e., PPR; Figure 2C,D) [31,48]. These contradictory AMPH effects could be explained by indirect activation of D2 receptors that [1] downregulate the firing rate of action potentials (AP) on the glutamatergic terminals (i.e., decreasing the sEPSC frequency) and [2] inhibiting the lateral inhibition on glutamatergic and GABAergic terminals on MSNs. However, the regulation by hetero-receptors on cortical and dopaminergic inputs in NAcc (e.g., endocannabinoid, acetylcholine, and adenosine, among others) is an open question in our work [33,49]. Our findings suggest that in obese rats, the high level of glutamatergic activation of the indirect pathway (D2-like MSNs) compared to the direct pathway (D1-like MSNs) could be related at the slightest basal DA release observed in this work (Figure 5). Our results suggest that this imbalance could trigger an abnormal form of hetero-synaptic plasticity, which is sufficient to modify the eating behavior. However, to identify the receptors implicated in these HFD-induced electrophysiological changes, and these should be determined with further pharmacological and molecular experiments. Finally, the classical implications associated with the change in the activity of the D1-MSNs and D2-MSNs, or the changes in the expression patterns of D1 and D2 receptors have been related to exclusive effects on direct or indirect pathways in NAcc. However, this topic is being reconsidered, since studies that have combined electrophysiological, optogenetic, and chemogenetic techniques have shown in NAcc that D1-MSNs innervate the ventral midbrain (direct pathway) and the ventral pallidum (indirect pathway), which receives closely about $90\%$ and $50\%$ of D2-MSNs and D1-MSNs afferents, respectively [19,50]. During the last decade, several studies have suggested that obesity is associated with an inflammatory process characterized by increased plasma levels of proinflammatory cytokines such as TNF-α, IL-6, and C-reactive protein [51]. The inflammation of the nervous system or neuroinflammation induced by foods has been observed in developed societies that have adopted new styles of eating based on ultra-processed foods rich in carbohydrates and fats and low content in vegetables, fiber, and prebiotics [52,53]. Obesogenic foods promote hyperphagia and other behaviors related to malnutrition, facilitating the development of obesity and neuroinflammation [54]. For example, foods with a high glycemic load cause an increase in reactive oxygen species that favor the expression of proinflammatory genes [55]. In this context, inflammation is associated with the activation of an intracellular protein complex called inflammasome, which is assembled in response to damage-associated molecular patterns (DAMP) and pathogen-associated molecular patterns (PAMP) [40]. NLRP3 inflammasome can be activated by cholesterol crystals and ceramides [56], products generated due to the exacerbation of lipolysis in obesity [57]. The NLRP3 inflammasome is made up of a sensor protein (NLRP3), an adapter molecule ASC (apoptosis-associated speck-like protein), and the effector enzyme pro-caspase 1 [58]. The inflammasome activation favors the proteolytic cleavage of Pro-IL-1β and Pro-IL-18 by caspase 1, generating the respective active proteins (IL-1β and IL-18), which promote the inflammatory response [59,60]. Furthermore, IL-1β is a critical pathological mediator of obesity-induced insulin resistance [61], and NLRP3 expression depends on NF-κB [61]. Our results show that chronic exposure to HFD is enough to increase the expression of inflammasome components and GFAP (a marker of astrogliosis) in NAcc (Figure 3). In this context, it has been shown that exposure to HFD increases the NAcc expression of proinflammatory cytokines, NF-κB, Iba-1, and GFAP, respectively [30]. In addition, the increase of proinflammatory cytokines affects the dopaminergic neurochemistry in NAcc, since systemic administration of IL-6 and IL-2 decrease NAcc DA extracellular levels [62]. In our model of chronic HFD exposure, the increase in neuroinflammatory markers in NAcc (Figure 3) may be part of the pathophysiological mechanism associated with the decreased basal levels of NAcc DA observed using FSCV ex vivo in obese animals (Figure 5A,C). It has recently been shown using FSCV ex vivo that exposure to HFD from postnatal days 42 to 84 decreases phasic DA release (5 pulses 20 Hz) and reuptake rate in NAcc slices from mice of both sexes [63]. Interestingly, after restoring baseline values of tonic (monophasic) DA release, the perfusion of ACSF plus IL-6 (10 nM) or ACSF plus TNFα (300 nM) significantly reduces NAcc DA release in mice fed with HFD [63]. Regarding the neurochemical changes, we observed that the total DOPAC content in NAcc and DLS decreased in male rats exposed to HFD for six weeks (Figure 4B). DOPAC is formed through oxidation mediated by the enzyme MAO expressed at the presynaptic terminal and the extracellular level in glial cells. A reduction in DOPAC content may reflect a decrease in DA content (not observed in our work) or a decrease in DA metabolism. On the other hand, a reduction in DAT expression mediated by chronic exposure to HFD may be responsible for the decline in DA reuptake and its presynaptic metabolism. This hypothesis may be supported by results showing that exposure to HFD for 20 days in 12-month-old adult mice increases D2 binding in the striatum and NAcc shell while DAT binding decreases in the identical nuclei [64]. In addition, in synapto-neurosomes obtained from adult male rats exposed for one month to ad libitum food, food restriction, or obesogenic diets, it was observed that striatum DA reuptake was lower in obese rats. It was associated with a decrease in the binding of [3H]-CFT (a radiotracer of DAT) and a decrease in DAT expression in striatum membranes [65]. Our data of ex vivo FSCV show a reduction in basal DA release in NAcc slices of rats exposed to HFD (Figure 5A and C). This reduction in NAcc DA release could be due to an increase in D2 expression and turn, reduced DA release through an auto-receptor mechanism (Figure 5A). In this sense, exposure to HFD plus sugar for 3 to 4 weeks in rats decreased DA release in NAcc core and striatum [66]. Our data show that perfusion of NAcc slices of obese rats with (0.1 µM) AMPH did not produce a statistically significant change in DA extracellular levels (Figure 5A), possibly it is due to HFD-induced decreased DAT expression (pharmacological target of AMPH). It has been shown that exposure to HFD for six weeks in 2-month-old rats reduces DA reuptake in vivo and DAT expression in ventral striatal membranes [67]. Mice that had access for three hours daily, during three days per week, for six weeks in total, presented a high preference for the HFD, an increase of phasic DA release, and a reduction in amphetamine-induced DA uptake inhibition compared to control animals exposed to food chow for six weeks [68]. On the other hand, 42-day-old mice of both sexes fed with HFD for six weeks did not show changes in single-pulse-evoked tonic DA release and the reuptake rate [69]. ## 4.1. Reagents DA, 5-HT, DOPAC and 5-HIAA standards, EDTA, and 1-octanesulfonic acid were purchased from Sigma-Aldrich, Inc. (St. Louis, MO, USA). AMPH sulfate was obtained from Laboratorio Chile S.A. (ISPCH No F-$\frac{1386}{18}$, Ñuñoa, Santiago, Chile). All other reagents were of analytical and molecular grade. Chow diet (Prolab® Isopro® RMH 3000, St. Louis, MO, USA) and HFD (D12492 Research Diets®, New Brunswick, NJ, USA) were purchased from Animal Care (San Joaquín, Santiago, Chile) and PrionLab (Peñaflor, Santiago, Chile), respectively. ## 4.2. Animals Sixty-eight male Sprague-Dawley rats from different litters were considered for the following experimental groups: control ($$n = 32$$) and HFD ($$n = 36$$). Animals from the vivarium of the Faculty of Science of the Universidad de Valparaíso were used and housed in a temperature- and humidity-controlled room (22 ± 2 °C; 50 ± $5\%$, respectively) under artificial illumination (12-h light/12-h dark; light on at 08:00 a.m.), with food and water ad libitum from postnatal (PND) 21 to 62 (Figure 6). Control and HFD male rats were fed with a standard chow diet (calories provided by $26\%$ protein, $14\%$ fat, and $60\%$ carbohydrates) and HFD (calories supplied by $20\%$ protein, $60\%$ fat, and $20\%$ carbohydrates), respectively. Efforts were made to minimize the number of rats used and their suffering. ## 4.3. Experimental Procedure After weaning PND21, the experimental group-housed rats ($$n = 3$$–4) in standard cages under vivarium conditions until PND62. At PND62, rats were anesthetized with isoflurane ($5\%$ in 0.6 L/min air flow) in an induction chamber using an animal anesthesia system (model 510, RWD Life Science Co. Ltd., Shenzhen, China). When the rats were deeply anesthetized, they were euthanized by decapitation with a guillotine (model 51330, StoeltingTM Co., Wood Dale, IL, USA). Their brains were quickly removed for electrophysiological, molecular, and neurochemical experiments. Peripheral tissues such as retroperitoneal fat (Figure 1C), tibial muscle, and serum were collected from each animal. ## 4.4. Electrophysiological Studies: Slice Preparation, Recording, and Analysis A total of 11 control and 13 HFD male rats were used. After deep anesthesia with isoflurane, the animals were euthanized by decapitation with a guillotine. Their brains were quickly removed and placed into ice-cold (4 °C) artificial cerebrospinal fluid (ACSF), concentrations (mM) of which were: 124.0 NaCl, 2.7 KCl, 1.25 KH2PO4, 2.0 Mg2SO4, 26.0 NaHCO3, 2.5 CaCl2, and 10.0 glucose. ACSF was bubbled with carbogen gas ($95\%$ O2; $5\%$ CO2; pH 7.4; Linde Gas Chile S.A.), and brains were cut in coronal slices (300–350 µm) using a vibrating Microtome (model vibroslice VSL; World Precision Instruments, Sarasota, FL, USA). Slices were incubated in ACSF for one hour at room temperature before electrophysiological recordings began. Slices were transferred to an immersion-recording chamber (2 mL), fixed to an upright microscope stage (model FN100 IR; Nikon Inc., Tokyo, Japan) equipped with infrared and differential interference contrast imaging devices and with a 403-water immersion objective. Whole-cell currents and voltage-clamp recordings were performed from MSNs within the NAcc core, identified under visual guidance using infrared video microscopy, and based on cell soma size and firing properties [2]. Whole-cell voltage and current clamp recordings using an amplifier (model EPC-7, Heka Instruments, Germany) were made from MSN voltage clamped at −60 mV, using patch-type pipette electrodes (3–5 MΩ) containing (in mM): 135.0 KMeSO4, 10.0 KCl, 10.0 N-(2-hydroxyethyl)-1-piperazine-ethanesulphonic acid (HEPES), 5.0 NaCl, 5.0 ATP-Mg2+ and 0.4 GTP-Na+ (pH = 7.2). eEPSCs and sEPSC were recorded and imported as HEKA pulse data by Microcal Origin 6.0 software to be analyzed offline and graphed, using analysis software (Clamfit 6.0, Molecular Devices LLC., San Jose, CA, USA). Experiments started after a 5–10 min stabilization period following the establishment of whole-cell configuration. In voltage clamp mode, evoked excitatory postsynaptic currents (eEPSCs) were recorded, filtered at 3.0 kHz, acquired at 4.0 kHz using an A/D converter (model ITC-16, InstruTECH, Reutlingen, Germany), and stored with Pulse FIT software (Heka instruments, Germany). Cells that exhibited a significant change in access resistance (>$20\%$) were excluded from the analysis. Stimulation of mesolimbic pathways (200 ms duration, 2.0 s−1) was performed by introducing two silver chloride electrodes into an ACSF-filled, patch-like pipette made with septum theta capillaries (World Precision Instruments, Sarasota, FL, USA). The stimulation pipette was gently placed medial line around the NAcc core at 200–300 µm to the dendritic tree of the recorded cell (<200 mm) and fixed when a single response was detected. Single stimuli (60 s, 50–100 ms, 20–100 mA; Master 8, AMPI, Israel) through an isolation unit (Isoflex, AMPI, Israel). eEPSCs were recorded and analyzed offline using analysis software (Clamfit 6.0, Molecular Devices LLC., San Jose, CA, USA). Paired-pulse protocol and calculated the paired-pulse ratio (PPR) to estimate putative presynaptic changes. PPR was calculated as (R2/R1), where R1 and R2 are the peak amplitudes of the first and second eEPSC (80 ms apart). The mean eEPSC amplitude values and PPR were obtained for each condition. ## 4.5. RT-qPCR A total of 10 control and 11 HFD male rats were used. Rats were decapitated, and their brains were removed quickly. NAcc and other brain areas were micro-dissected at 4 °C using a micro-punch, weighed on an analytical balance, and stored at −80 °C for further analysis. RT-qPCR was used to determine relative expressions of Asc, Il-1β, caspase-1, Nlrlp3, and Gfap in NAcc of control and HFD rats. Total RNA was extracted using the E.Z.N.A.® Total RNA Kit I (Cat. No R6834-02; Omega BioTek Inc., Norcross, GA, USA) according to the manufacturer’s instructions. RNA was quantified using the microplate Spectrophotometer (model Epoch; BioTek Inc., Winooski, VT, USA), and RNA integrity was assessed through agarose gel electrophoresis. Total RNA from each sample was reverse transcribed with the RevertAid RT kit (Cat. N° K1691, Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions. Real-time RT-PCR was performed using Supermix SsoAdvanced Universal SYBR Green (Cat. N° 1725271, Bio-Rad, Hercules, CA, USA) by the manufacturer’s instructions. For specific gene amplification, a standard protocol of 40 cycles was used in a Real-Time PCR Detection System (model CFX96™; Bio-Rad, Hercules, CA, USA). Ribosomal 18S mRNA was measured in each protocol to normalize the gene expression using primers reported previously [70,71]. The details of the primers used for each analyzed gene are summarized in the following Table 1. The specificity of each generated amplicon was confirmed by performing melting curves at the end of each reaction. Results were expressed as fold change by the 2ΔΔCT method [72]. ## 4.6. Neurochemical Studies A total of 11 control and 12 HFD male rats were used to analyze monoamine content and ex vivo fast-scan cyclic voltammetry experiments. ## 4.6.1. Monoamine Content Quantification Using HPLC-ED A total of 4 control and 4 HFD male rats were used. Rats were anesthetized with isoflurane ($3\%$ in 0.8 L/min air flow) in an induction chamber for 3 min and decapitated. NAcc, DLS, SN, and VTA were at 4 °C using a brain matrix (model 68711; RWD Life Science, Shenzhen, P.R. China) and micro-punch (model 15076 Harris Uni-Core; Ted-Pella Inc., Redding, CA, USA). Brain nuclei were weighed on an analytical balance (model JK-180; Chyo balance corp, Tokyo, Japan) and homogenized in 400 μL of 0.2 M perchloric acid using a sonicator (model Q55; Qsonica, Newtown, CT, USA). The homogenate was centrifuged to 12,000× g for 10 min at 4 °C (model Z233MK-2; Hermle Labor Technik GmbH, Wehingen, Germany), and the supernatant was filtered using HPLC syringe filters (model EW-32816-26; Cole-Parmer, Vernon Hills, IL, USA). Ten microliters of final supernatant were injected into HPLC-ED with the following configuration: Isocratic pump (model PU-2080 Plus; Jasco Co. Ltd., Tokyo, Japan), C18 column (model Kromasil 100-3.5-C18; AkzoNobel, Bohus, Sweden), and electrochemical detector (model LC-4C; Bioanalytical System Inc., West Lafayette, IN, USA) set at 0.650 V (oxidation potential), 0.5 nA (sensitivity), and 0.03 Hz (electrical noise). The composition of the mobile phase was 0.1 M NaH2PO4, 1.5 mM 1-octanesulfonic acid, 1.28 mM EDTA, $2.0\%$ (v/v) tetrahydrofuran, and $4.5\%$ (v/v) CH3CN (pH 4.0). It was pumped at a flow rate of 0.105 mL/min. DA (18.6 min), DOPAC (14.2 min), 5-HIAA (22.3 min), and 5-HT (48.4 min) content were assessed by comparing the respective peak area and elution time of the sample with a reference standard. The quantification was performed using a calibration curve for each neurotransmitter and metabolite (Program ChromPass, Jasco Co. Ltd., Tokyo, Japan). The concentration was expressed as pg per mg of wet tissue. ## 4.6.2. Ex-Vivo Fast Scan Cyclic Voltammetry A total of 7 control and 8 HFD male rats were used. Rats were anesthetized with isoflurane ($3\%$ in 0.8 L/min air flow) in an induction chamber for 3 min and decapitated. The brain was quickly removed and sliced (300–350 µm) using a vibrating Microtome (model vibroslice VSL; World Precision Instruments, Sarasota, FL, USA). Brain slices were obtained in ice-cold (4 °C) artificial cerebrospinal fluid (ACSF), whose composition was: 126.0 mM NaCl, 25.0 mM NaHCO3, 11.0 mM glucose, 2.5 mM KCl, 2.4 mM CaCl2, 1.2 mM MgCl2, 1.2 mM NaH2PO4 and 0.4 mM L-ascorbic acid (adjusted to pH 7.4). ACSF was bubbled with carbogen gas ($95\%$ O2; $5\%$ CO2; pH 7.4; Linde Gas Chile S.A.). A glassy-carbon microelectrode (working electrode) was linearly scanned (−0.4 to 1.2 V and back to −0.4 V vs. Ag/AgCl). Cyclic voltammograms were assessed at the carbon fiber electrode every 100 ms with a scan rate of 400 V/s using a voltammeter/amperemeter (model Chem-Clamp Potentiostat, Dagan Corporation, Minneapolis, MN, USA). In this condition, DA is oxidized at +0.6 V and reduced at −0.4 V. To measure NAcc DA release, a concentric bipolar electrode (model 30200; FHC, Bowdoin, ME, USA) was stimulated with the following parameters: monophasic, 4 ms and 400 μA (current stimulus isolator NL800A; Digitimer, Ltd., Hertfordshire, UK) every 3 min. In addition, an Ag/AgCl reference electrode (model EP2; World Precision Instruments, Sarasota, FL, USA) was used. Phasic DA release was measured using 400 μA of stimulation and trains of 5 pulses at 5, 10, 20, 40, and 100 Hz. For data collection, two National Instruments acquisition cards (NI-DAQ; PCI-6711 and PCI-6052e; National Instruments, Austin, TX, USA) were used to interface the potentiostat and stimulator with Demon Voltammetry and Analysis software (Wake Forest Health Sciences, Winston-Salem, NC, USA) [73]. After phasic stimulation, DA release was measured again with monophasic stimulation described above. AMPH (0.1 μM) dissolved in ACSF was applied to NAcc slices. 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--- title: Geriatric Nutritional Risk Index at Hospital Admission or Discharge in Patients with Acute Decompensated Heart Failure authors: - Masafumi Ono - Atsushi Mizuno - Shun Kohsaka - Yasuyuki Shiraishi - Takashi Kohno - Yuji Nagatomo - Ayumi Goda - Shintaro Nakano - Nobuyuki Komiyama - Tsutomu Yoshikawa journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003647 doi: 10.3390/jcm12051891 license: CC BY 4.0 --- # Geriatric Nutritional Risk Index at Hospital Admission or Discharge in Patients with Acute Decompensated Heart Failure ## Abstract Geriatric Nutritional Risk Index (GNRI) is known both as a reliable indicator of nutritional status and a predictor of long-term survival among patients with acute decompensated heart failure (ADHF). However, the optimal timing to evaluate GNRI during hospitalization remains unclear. In the present study, we retrospectively analyzed patients hospitalized with ADHF in the West Tokyo Heart Failure (WET-HF) registry. GNRI was assessed at hospital admission (a-GNRI) and discharge (d-GNRI). Out of 1474 patients included in the present study, 568 ($40.1\%$) and 796 ($57.2\%$) patients had lower GNRI (<92) at hospital admission and discharge, respectively. After the follow-up (median 616 days), 290 patients died. The multivariable analysis showed that all-cause mortality was independently associated with d-GNRI (per 1 unit decrease, adjusted hazard ratio [aHR]: 1.06, $95\%$ confidence interval [CI]: 1.04–1.09, $p \leq 0.001$), but not with a-GNRI (aHR: 0.99, $95\%$ CI: 0.97–1.01, $$p \leq 0.341$$). The predictability of GNRI for long-term survival was more pronounced when evaluated at hospital discharge than at hospital admission (area under the curve 0.699 vs. 0.629, DeLong’s test $p \leq 0.001$). Our study suggested that GNRI should be evaluated at hospital discharge, regardless of the assessment at hospital admission, to predict the long-term prognosis for patients hospitalized with ADHF. ## 1. Introduction Acute decompensated heart failure (ADHF) has a strong relationship with malnutrition [1]; ADHF can induce anorexia, malabsorption secondary to intestinal edema, high energy demand, and cytokine-induced hypercatabolism, which cause severe nutritional deterioration, while malnutrition could also be a major cause of refractory HF. The combination of ADHF and malnutrition synergistically deteriorate the patient’s systemic condition, leading to further worse prognosis [1]. Notwithstanding the importance of nutritional assessment for ADHF patients, there is a lack of consensus regarding the methodology for the assessment. Some objective scores have been advocated for the purpose of nutritional evaluation among patients with HF. Geriatric Nutritional Risk Index (GNRI) is one of the objective scores to assess a patient’s nutritional condition. GNRI consists of body mass index (BMI) and albumin, both of which are commonly measured in dairy clinical practice, and therefore, GNRI could be easily calculated and applied even in a busy clinical setting [2]. Previous studies revealed that lower GNRI is an independent predictor of short- and long-term mortality in hospitalized patients with ADHF, when evaluated either at hospital admission or discharge [3,4,5,6,7]. However, the nutritional status of ADHF patients could dramatically change, especially in the acute phase, due to an inflammatory response, energy intake/expenditure balance, and/or underlying disease condition [8,9,10]. Thus far, the optimal timing to assess GNRI for predicting the long-term survival of ADHF patients has not been investigated [11]. The present study aimed to investigate the effects of GNRI assessed at the time of hospital admission and discharge on the long-term survival among hospitalized patients presenting with ADHF. ## 2.1. Study Population The present study is a sub-study of the West Tokyo Heart Failure Registry (WET-HF Registry). Details of the WET-HF Registry have been described previously and well-validated by prognostic models for patients hospitalized with heart failure [12,13,14,15,16,17]. Briefly, this database is an ongoing, multicenter, prospective cohort, registry study designed to collect data pertaining to the clinical backgrounds and outcomes of patients who were hospitalized with the clinical diagnosis of ADHF, according to the *Framingham criteria* [18]. Prior to the launch of the registry, the objective and detailed study design were provided for clinical trial registration to the University Hospital Medical Information Network of Japan (UMIN000001171). The study was conducted at six study centers, including three university hospitals and three tertiary referral hospitals. To guarantee the quality of the acquired data, baseline data and outcome were collected from the medical record and/or were obtained by querying treating physicians by dedicated clinical research coordinators if necessary. On-site monitoring was performed by the investigators (Y.S. and S.K.) at least once a year to ensure the proper registration of each patient. Patients who declined to participate in the study or presented with acute coronary syndrome were excluded from the registration. Informed consent was obtained from each subject before enrollment in the study. The study protocol was approved by the institutional review boards at each site, and research was conducted in accordance with the Declaration of Helsinki. ## 2.2. Data Collection and Endpoint We collected conventional clinical variables, including age, sex, etiology of HF, medical history, vital status at admission and discharge, laboratory data (at admission, during hospitalization, and at discharge), and medications (at admission and discharge). Patients who did not have available data of serum albumin and BMI at hospital admission and/or discharge and at the follow-up vital status were excluded from the current study. The primary endpoint of the present study was all-cause mortality at the maximum follow-up period from the discharge of the index hospitalization (defined as day 0), which is the most robust clinical endpoint without the necessity of adjudication. ## 2.3. GNRI We calculated patients’ GNRI at both admission (a-GNRI: GNRI at hospital admission) and discharge (d-GNRI: GNRI at hospital discharge) by the following formula [2]: GNRI = [14.89 × serum albumin (g/dL)] + [41.7 × (body weight/ideal body weight)] = [14.89 × serum albumin (g/dL)] + [41.7 × (BMI/22)] *When a* patient’s body weight exceeded the ideal body weight, “body weight/ideal body weight” was set to 1, according to the original criteria [2]. Patients were classified as lower GNRI (<92) with moderate or severe nutritional risk, or higher GNRI (≥92) with low or mild nutritional risk, according to the threshold of 92 [2]. ## 2.4. Statistical Analysis Continuous variables were reported as median with interquartile range (IQR) and were compared using the Kruskal–Wallis H test. Categorical variables were presented as counts and percentage and were compared using the chi-square test or Fisher’s exact test as appropriate. A scatter plot between a-GNRI and d-GNRI was drawn, depicting the linear regression line with the $95\%$ confidence interval (CI), and the Pearson correlation was used to quantify the relation between a-GNRI and d-GNRI. To visualize the impacts of BMI and albumin on d-GNRI, as well as changes in GNRI from hospital admission to discharge (∆GNRI), we made heatmaps in which d-GNRI and ∆GNRI were color-coded for each observed pair of BMI-albumin at hospital admission and pair of ∆BMI-∆albumin during hospitalization, respectively. The Kaplan–Meier method was used to estimate the cumulative rates of events, and the log-rank test was performed to examine the differences between groups. The cumulative incidence of all-cause death during the follow-up period was compared between the lower GNRI (<92) and higher GNRI (≥92) groups at both timepoints (hospital admission and discharge) using unadjusted and adjusted Cox proportional hazard models to calculate unadjusted and adjusted HRs with $95\%$ CIs, respectively. Adjusted baseline variables included age (years), sex, hypertension, dyslipidemia, diabetes mellitus, renal failure requiring hemodialysis, current smoking, chronic pulmonary occlusive disease (COPD), history of HF admission, New York Heart Association Functional Classification (NYHA class) 3 or 4, laboratory data (serum hemoglobin, Na, blood urea nitrogen [BUN], and serum creatinine) at discharge, left ventricular ejection fraction (LVEF), use of beta-blockers, use of mineralocorticoid receptor antagonists (MRA), use of statins, use of either angiotensin-converting-enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) at discharge, length of index hospitalization (days), and a-GNRI (for d-GNRI) or d-GNRI (for a-GNRI) that had been selected based on prior knowledge of the association of these covariables with the outcomes [19]. The association between a-GNRI or d-GNRI and the primary endpoint was also assessed as a continuous variable, depicting restricted cubic spline curves derived from the unadjusted proportional hazards models. In order to determine the best variable for predicting the clinical outcome, the area under the receiver-operating characteristic (ROC) curves and areas under the curves (AUC) were estimated for several variables, including a-GNRI, d-GNRI, ∆GNRI, BMI at discharge, ∆BMI, albumin at discharge, and ∆albumin for the primary endpoint, and were compared by using the DeLong method [20]. A two-sided p value of less than 0.05 was considered to indicate statistical significance. All analyses were performed in SPSS Statistics, version 29 (IBM Corp., Armonk, NY, USA) and R software version 4.0.1 (R Foundation for Statistical Computing, Vienna, Austria). ## 3. Results From 2006 to 2017, 4000 patients were enrolled in the WET-HF Registry. Out of those patients, 2410 patients who did not have available GNRI data and 116 patients without any follow-up data were excluded in this study. Finally, a total number of 1474 patients (median age, 76 years [IQR: 65–83]; $58.5\%$ male) were included in the present study (Figure 1). ## 3.1. Distribution of a-GNRI and d-GNRI Figure 2 shows the distribution of a-GNRI and d-GNRI, with indication of whether GNRI increased or decreased during the hospitalization for each individual patient. The median GNRI at hospital admission and discharge were 93.8 (IQR: 88.4–99.1) and 90.8 (IQR: 84.6–96.8), respectively. At hospital admission, 906 ($61.5\%$) patients had a higher GNRI (≥92), and 568 ($38.5\%$) patients had a lower GNRI (<92), whereas at hospital discharge, 678 ($46.0\%$) patients had a higher GNRI, and 796 ($54.0\%$) patients had a lower GNRI. Although there was a strong correlation between a-GNRI and d-GNRI with the Pearson correlation coefficient of 0.7 ($p \leq 0.001$), the majority of the patients showed decreased GNRI from hospital admission to discharge (Figure 2). The median value of the changes in GNRI during hospitalization was −2.95 (IQR: −7.30 to +1.49). As components of GNRI, the mean values of the changes in serum albumin and BMI during hospitalization were −0.1 (IQR: −0.4 to +0.2) and −1.53 (IQR: −2.61 to −0.79), respectively. Figure 3A,B shows the relationship among BMI, serum albumin, and GNRI. When predicting d-GNRI according to BMI and albumin values at the time of hospital admission (Figure 3A), most of patients who had serum albumin level >3.0 mg/dL at admission had low or mild nutritional risk at discharge (i.e., d-GNRI ≥ 92), unless the patient’s BMI did not exceed 22 at hospital admission. Moreover, the changes in GNRI during the hospitalization mainly depended on the changes in albumin, rather than those in BMI (Figure 3B). ## 3.2. Other Patient Characteristics Baseline patient characteristics in comparison between patients with lower GNRI and those with higher GNRI, either at hospital admission or discharge, are shown in Table 1. Patients with lower GNRI were older, more often female, and had a higher NYHA classification, higher prevalence of hypertension and valvular disease, and lower prescription rates of ACEI or ARB, MRA, beta-blockers, and statins than those with higher GNRI. Patients with lower GNRI had lower hemoglobin and Na, as well as higher BUN, C-reactive protein, and brain natriuretic peptide (BNP) or NT-proBNP than those with higher GNRI both at admission and discharge. At discharge, compared to patients with higher GNRI, those with lower GNRI had a higher prevalence of hemodialysis, which was not observed at admission, where $56.6\%$ of hemodialysis patients ($\frac{30}{53}$) were classified as low or mild nutritional risk on admission, whereas $17.0\%$ ($\frac{9}{53}$) were classified at discharge. Patients with lower d-GNRI had a higher prevalence of valvular disease and a longer length of hospital stay. Importantly, patients with lower d-GNRI had significantly higher LVEF than those with higher d-GNRI. ## 3.3. Clinical Outcomes According to a-GNRI or d-GNRI During a median follow-up period of 616 days (IQR: 271 to 925 days), 290 of the study patients died. The Kaplan–Meier curves for all-cause death up to 4 years are shown in Figure 4. At the maximum follow-up period, a-GNRI < 92 and d-GNRI < 92 groups had a significantly higher all-cause mortality risk than a-GNRI ≥ 92 and d-GNRI ≥ 92 groups, respectively (both Log-rank $p \leq 0.001$). The unadjusted and adjusted hazard ratios with those $95\%$ Cis, according to a-GNRI or d-GNRI, are shown in Table 2. The crude risk of all-cause death was lower in patients with higher a-GNRI, both as a categorical (<92 vs. ≥92, unadjusted HR: 2.09, $95\%$ CI: 1.66–2.63, $p \leq 0.001$) and a continuous variable (per 1 unit decrease, unadjusted HR: 1.06, $95\%$ CI: 1.04–1.09, $p \leq 0.001$). Similarly, patients who had higher d-GNRI showed a lower risk of all-cause death (<92 vs. ≥92, unadjusted HR: 3.82, $95\%$ CI: 2.89–5.05, $p \leq 0.001$, per 1 unit decrease, unadjusted HR: 1.08, $95\%$ CI: 1.06–1.09, $p \leq 0.001$). After adjusting for confounding variables, patients with higher d-GNRI showed a significantly lower risk of all-cause death, both as a categorical (<92 vs. ≥92, adjusted HR: 1.96, $95\%$ CI: 1.39–2.75, $p \leq 0.001$) and a continuous variable (adjusted HR: 1.06, $95\%$ CI: 1.04–1.09, $p \leq 0.001$). On the other hand, a-GNRI was not independently associated with all-cause death ($p \leq 0.05$). ## 3.4. Predictive Values of a-GNRI and d-GNRI for All-Cause Death Figure 5 shows the predictive ability of a-GNRI or d-GNRI in terms of risk of all-cause death. The restricted cubic spline curves (Figure 5A) suggest that d-GNRI had a stronger association with the risk of all-cause death both below and over 92 compared to a-GNRI, where higher d-GNRI was more associated with survival than higher a-GNRI, and lower d-GNRI was more associated with death than lower a-GNRI. When comparing the ROC curves of several variables, including a-GNRI, d-GNRI, ∆GNRI, BMI at discharge, ∆BMI, albumin at discharge, and ∆albumin, d-GNRI had the best AUC among those variables, although albumin at discharge also had a high prognostic value close to that of d-GNRI, and there was no statistically significant difference between these two variables by DeLong’s test ($$p \leq 0.140$$, Figure 5B). Compared to a-GNRI, d-GNRI had a significantly higher prognostic value for all-cause mortality ($p \leq 0.001$). ## 4. Discussion The major findings of the present study are as follows: [1] Although there was a strong correlation between a-GNRI and d-GNRI, GNRI had decreased significantly during the ADHF hospitalization. The changes in GNRI depended more on serum albumin than on BMI. [ 2] Lower d-GNRI, but not a-GNRI, was independently associated with long-term all-cause mortality in patients with ADHF. [ 3] Compared to a-GNRI, d-GNRI had more prognostic value for long-term mortality. Together, these findings suggest that the GNRI should be evaluated at the time of hospital discharge rather than at admission among patients hospitalized with ADHF so as to evaluate the patients’ prognosis appropriately. Nutritional evaluation is of paramount importance for the management of HF patients [21]. Malnutrition is a frequently observed state in patients with acute and chronic HF, and it impacts on patients’ prognosis [22,23]. Nevertheless, there was no consensus or recommendation on how and when to evaluate nutritional status appropriately [24,25]. There are a number of nutritional assessment tools that were associated with prognosis in HF patients. Among them, GNRI seems to have the strongest prognostic impact on the survival of patients with HF [6,26,27,28,29]; lower GNRI was associated with worse prognosis in HF patients. However, those studies evaluated GNRI at the time of the hospital admission mostly [3,4,5,6]. Since both body weight and the serum albumin level are easily influenced by systemic congestion, hemodilution, inflammatory activation, reduced intake, and/or impaired metabolism, GNRI on admission may not necessarily reflect the nutritional status in patients with ADHF [30,31]. In fact, Sze et al. reported that GNRI was the weakest predictor for mortality among several objective nutritional assessment tools, based on the data on admission [32], which was inconsistent with the authors’ other report where GNRI was evaluated among outpatients [26]. Our study demonstrated that d-GNRI had better predictability for all-cause death than a-GNRI (Figure 5 and Table 2). In the present study, despite a strong correlation between a-GNRI and d-GNRI, as expected, there was a substantial decrease in GNRI from admission to discharge, with the absolute mean difference of 2.97. The change was mostly attributed to changes in albumin, while changes in body weight (BMI) had less impact on the GNRI change (Figure 3). In addition, Figure 5B showed that ∆albumin, as well as ∆GNRI, also had a relatively high prognostic value for predicting mortality, whereas ∆BMI, which could partially reflect congestion relief during hospitalization, did not associate with survival. Considering these results, it might be assumed that hydration status by ADHF at hospital admission would not be a key factor for the lower predictive ability of a-GNRI than d-GNRI, and the superiority of d-GNRI over a-GNRI would be attributed more to taking into account the nutritional changes during the critical event of ADHF rather than merely to congestion relief. Nakayama et al. [ 33] reported that the mean serum albumin changed from 3.51 mg/dL on day 1 to 3.35 mg/dL on day 7, and the increase was independently associated with favorable outcomes. A similar study was reported by Chao et al. [ 34] and Gotsman et al. [ 35], where a decrease in the serum albumin level was associated with mortality in patients with HF. In line with those studies, our study also showed a decrease in the albumin level during hospitalization, although the change was trivial in terms of an average effect (the mean change was only −0.44 mg/dL). In fact, Figure 2 suggested that a certain number of patients experienced an increase in GNRI. Therefore, it is noteworthy that not only the decrease, but also the increase in albumin, as well as GNRI, may play an important role in the reclassification of the nutritional status on an individual basis [10]. In this context, whether or not administration of albumin or other nutritional implements can improve the outcome in patients with lower GNRI may be of great interest, since the efficacy of nutritional interventions on clinical outcomes is still a matter of debate [21]. Our study may pave the way for appropriate measurement of the nutritional status among HF patients and for determining the indication of subsequent nutritional interventions. As shown in Table 1, patients with lower GNRI (both a-GNRI and d-GNRI) had higher age and more comorbidities, such as hypertension and dyslipidemia, which could be expected since malnutrition is strongly related to the patient’s oldness and comorbidities. Notably, patients with lower d-GNRI had significantly higher LVEF, despite higher BNP/NT-proBNP and a higher prevalence of NYHA class III or IV than those with higher d-GNRI (Table 1). This finding may suggest that malnutrition could be more common in patients with higher LVEF, including heart failure with preserved EF (HFpEF), in which the pathophysiologic mechanisms would include systemic inflammation and may be different from those of HF with reduced EF (HFrEF) [36,37]. In addition, the higher BNP/NT-proBNP or higher prevalence of NYHA class III/IV in the lower d-GNRI group might be attributable to the worse HF condition of this group, exemplified by the worse laboratory data, such as lower hemoglobin and higher CRP, or the longer length of hospital stay. In other words, this result may imply that d-GNRI could reflect the patient’s HF status more precisely than LVEF. Of noted, the higher prevalence of hemodialysis in the lower GNRI group was observed at discharge, but not at admission (Table 1). Although the cause of the dynamic changes in GNRI during HF hospitalization among hemodialysis patients remains unclear, patients undergoing hemodialysis might be prone to developing malnutrition by an ADHF event. It would be of crucial importance for those patients to assess the nutritional condition at hospital discharge, irrespective of the assessment at hospital admission. Further studies are warranted to elucidate the mechanism of changes in nutritional status during hospitalization and optimal treatments for patients who are at risk of developing malnutrition [9,10]. ## Limitations Our study has several limitations. First, this was a retrospective observational study. Hence, we could not consider unmeasured or unknown variables affecting the results. Second, we could not analyze a lot of patients enrolled in the WET-HF registry due to the lack of data, which might introduce selection bias. Third, we suggest that higher GNRI indicates a better nutritional condition, though we have no additional confirmatory indices of nutritional status from this cohort, such as controlling nutritional status (CONUT) score or prognostic nutritional index (PNI), due to lack of those data. Finally, we do not have data regarding nutritional intervention or the administration of albumin during hospitalization. Past studies have demonstrated the utility of nutritional intervention in HF patients [38]; however, no study has evaluated GNRI as a decision-making tool to determine whether nutritional intervention is needed. Further investigation will be required to elucidate the optimal treatment strategy incorporating nutritional assessment with GNRI in patients presenting with ADHF [39]. ## 5. Conclusions Among patients hospitalized with ADHF, GNRI at the time of hospital discharge was independently associated with long-term all-cause mortality and had more predictability than GNRI at the time of hospital admission. Our study suggested that GNRI should be evaluated at the time of hospital discharge, regardless of the assessment at hospital admission in ADHF patients. ## References 1. Tevik K., Thürmer H., Husby M.I., de Soysa A.K., Helvik A.-S.. **Nutritional risk is associated with long term mortality in hospitalized patients with chronic heart failure**. *Clin. Nutr. 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--- title: MUC1 Expression Affects the Immunoflogosis in Renal Cell Carcinoma Microenvironment through Complement System Activation and Immune Infiltrate Modulation authors: - Giuseppe Lucarelli - Giuseppe Stefano Netti - Monica Rutigliano - Francesco Lasorsa - Davide Loizzo - Martina Milella - Annalisa Schirinzi - Antonietta Fontana - Francesca Di Serio - Roberto Tamma - Domenico Ribatti - Michele Battaglia - Elena Ranieri - Pasquale Ditonno journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003656 doi: 10.3390/ijms24054814 license: CC BY 4.0 --- # MUC1 Expression Affects the Immunoflogosis in Renal Cell Carcinoma Microenvironment through Complement System Activation and Immune Infiltrate Modulation ## Abstract Mucin1 (MUC1), a glycoprotein associated with an aggressive cancer phenotype and chemoresistance, is aberrantly overexpressed in a subset of clear cell renal cell carcinoma (ccRCC). Recent studies suggest that MUC1 plays a role in modulating cancer cell metabolism, but its role in regulating immunoflogosis in the tumor microenvironment remains poorly understood. In a previous study, we showed that pentraxin-3 (PTX3) can affect the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system (C1q) and releasing proangiogenic factors (C3a, C5a). In this scenario, we evaluated the PTX3 expression and analyzed the potential role of complement system activation on tumor site and immune microenvironment modulation, stratifying samples in tumors with high (MUC1H) versus tumors with low MUC1 expression (MUC1L). We found that PTX3 tissue expression was significantly higher in MUC1H ccRCC. In addition, C1q deposition and the expressions of CD59, C3aR, and C5aR were extensively present in MUC1H ccRCC tissue samples and colocalized with PTX3. Finally, MUC1 expression was associated with an increased number of infiltrating mast cells, M2-macrophage, and IDO1+ cells, and a reduced number of CD8+ T cells. Taken together, our results suggest that expression of MUC1 can modulate the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system and regulating the immune infiltrate, promoting an immune-silent microenvironment. ## 1. Introduction Clear cell renal cell carcinoma (ccRCC) is the most common kidney tumor, and according to recent statistics, in the United States, 79,000 new cases were diagnosed and about 13,920 patients died from this disease in 2022 [1]. Many epidemiological studies have shown that obesity, diabetes, and other metabolic disorders can increase the risk of developing renal cancer [2,3,4]. In addition, in ccRCC, a particular metabolic signature has been described, characterized by a rerouting of the sugar metabolism toward the pentose phosphate pathway, significant accumulations of polyunsaturated fatty acids, and impaired mitochondrial activity [5,6,7,8,9,10,11]. An important goal in current research is to distinguish between different cancer subtypes based on the molecular characteristics that drive an aggressive phenotype, which can help predict clinical outcomes. Recently, we showed that mucin 1 (MUC1)-overexpressing ccRCCs were characterized by a specific metabolic modulation involving glucose and the lipid metabolism pathway [12]. In addition, higher levels of serum CA 15-3 (the soluble form of MUC1) were identified in patients with reduced cancer-specific (CSS) and progression-free survival (PFS) [12]. MUC1 is a cell membrane glycoprotein that is overexpressed and/or abnormally glycosylated in more than $70\%$ of cancers. MUC1 is involved in many functions of cancer cells, such as cell adhesion, proliferation, migration, invasion, and metabolic reprogramming [13]. In addition, MUC1 acts as a modulator of chronic inflammation, although its role in regulating the tumor immune microenvironment (TME), especially in ccRCC, is poorly understood. RCC has been defined as an immunogenic tumor with cytokine-based treatments as standard therapies before the introduction of antiangiogenic drugs and, more recently, immune checkpoint inhibitors (ICI) [14,15,16,17]. In this scenario, we previously showed that pentraxin-3 (PTX3), an acute-phase protein, was able to modulate the immunoflogosis in the ccRCC microenvironment through the activation of the classical pathway of the complement system and the release of pro-angiogenic factors [18,19]. In this study, we evaluated the in situ activation of the complement system (PTX3, C1q, C3aR, C5aR, CD59, and C5b-9) and characterized the immune cell infiltration (mast cells, macrophages, CD4, and CD8+ T cells) in correlation with the different expressions of MUC1 in a cohort of patients with ccRCC. ## 2.1. Gene Set Enrichment Analysis (GSEA) Shows Differences in Gene Expression Patterns between MUC1H and MUC1L Tumors To compare the relative changes in the gene expression in ccRCC with high MUC1 expression (MUC1H) versus tumors with low MUC1 expression (MUC1L), gene expression data from the GSE15641 dataset were downloaded, and the samples were stratified by MUC1 expression. Gene set enrichment analysis (GSEA) [20] demonstrated that MUC1H ccRCC featured multiple enriched gene sets depicting epithelial–mesenchymal transition, hypoxia, angiogenesis, complement system activation, and immune cell infiltration related processes (Figure 1). It is well known that increased expression of MUC1 has been associated with the first two hallmarks, while there are few data about its role in modulating angiogenesis, complement system activation, and immune cell infiltration in ccRCC. In a previous study, we showed that pentraxin-3 (PTX3) can modulate the immunoflogosis in the ccRCC microenvironment through the activation of the classical pathway of the complement system (C1q) and the release of proangiogenic factors (C3a and C5a) [19]. Therefore, to evaluate the above findings according to MUC1 expression, we studied the PTX3 tissue expression and analyzed the activation of the complement system in tumor samples. ## 2.2. MUC1H Renal Tumors Display an Altered Modulation of Immunoflogosis in TME PTX3 tissue expression was significantly higher in MUC1H ccRCC (Figure 2A,I) than in the MUC1L tumors (Figure 2E,I). We then explored the activation of the complement system in both groups of ccRCC. Because PTX3 can activate the complement cascade through the classic pathway, we studied the deposition of C1q. Interestingly, C1q was extensively present in MUC1H ccRCC tissue samples and colocalized with PTX3 (Figure 2A–D,J), while it was virtually absent in MUC1L ccRCC tissue samples (Figure 2E–H,J). To validate the complete activation of the complement system, we next studied the tissue deposition of the terminal complement complex C5b-9, but the increased activation of the classical pathway did not correspond to an increased deposition of this complex. Indeed, C5b-9-specific immunofluorescence was substantially absent in the renal cancer tissue of both groups (Figure 3A–H), with no significant differences (Figure 3I). Subsequently, we evaluated the expression of CD59, a complement system regulatory protein that can inhibit the C5b-9 assembly. Notably, CD59 protein expression was markedly increased in MUC1H ccRCC tissue samples (Figure 3J–M), while it was limited in MUC1L ccRCC (Figure 3N–Q), as shown by quantification of specific fluorescence (Figure 3R). To evaluate the role of anaphylatoxins as potential soluble mediators modulating both cancer cell proliferation and neoplastic angiogenesis, we studied the expression of C3a and C5a receptors. The expression of both trans-membrane proteins was significantly increased in MUC1H cancer tissues (Figure 4A–D,J–M), while it was significantly limited in MUC1L ccRCC (Figure 4E–I,N–R). Moreover, the expressions of CD59, C3aR, and C5aR colocalized with PTX3 in MUC1H cancer tissue (Figure 3M and Figure 4D,M, respectively). ## 2.3. TIMER and TISIDB Analyses Show MUC1 Modulation of Tumor-Infiltrating Immune Cells The TIMER 2.0 (http://timer.cistrome.org, accessed on 10 January 2023) [21] and TISIDB (http://cis.hku.hk/TISIDB/index.php, accessed on 10 January 2023) [22] web resources were used to analyze the association between MUC1 expression and TME composition. TIMER analysis showed that MUC1 mRNA expression significantly correlated with macrophage (in particular M2 phenotype) and CD8+ T-cell enrichment, while MUC1 mRNA levels showed no significant association with CD4+ T-cell infiltration (Figure 5). Analysis based on the TISIDB portal confirmed a positive correlation between MUC1 expression and macrophage abundance (Figure 6A), as well as a positive correlation between MUC1 and mast cell infiltration (Figure 6B). Conversely, a negative correlation was observed between MUC1 and PD-L1 (CD274) expression (Figure 6C). Finally, the analysis of the immune signature showed that MUC1H ccRCC could mainly be classified as C5 (immunologically quiet) cancer immune subtype (Figure 6D). ## 2.4. MUC1 Expression Is Associated with Increased Angiogenesis and Subtype-Specific Immune Cell Infiltration As suggested by the GSEA results, MUC1 is implicated in other additional characteristics of tumor biology, including induction of angiogenesis and immune cell infiltrate modulation. To investigate the angiogenic response, we evaluated the vascular density through CD31 immunostaining in MUC1H versus MUC1L histological specimens derived from ccRCC patients. We found a significantly increased number of CD31+ microvessels in MUC1H ccRCC samples compared with those in MUC1L tumors (Figure 7). Next, ccRCC specimens were immunostained for tryptase, CD68, and CD163 to estimate mast cells, total tumor-associated macrophages (TAMs), and M2-TAMs subpopulations, separately. Much of the evidence suggests that mast cells can promote tumor progression and angiogenesis [23,24]; thus, we evaluated the infiltration of tryptase-positive cells in the tumor microenvironment according to MUC1 expression. MUC1H ccRCC showed an increased number of these cells compared with MUC1L cancer tissues (Figure 7). To estimate macrophage infiltration and the status of polarization, we studied CD68 and CD163 expression. IHC showed an increased expression of these markers in MUC1H ccRCC compared with in MUC1L tumors (Figure 8). In addition, immunofluorescence and confocal laser scanning microscopy demonstrated the colocalization of the two markers (Figure 9), confirming the M2 polarization status of macrophages. In a previous study [25], we showed that activation of the kynurenine (KYN) pathway promoted renal cancer cells’ survival, migration, and chemoresistance and that increased accumulation of KYN in ccRCC was sustained by IDO1+ macrophages. To study the above findings in MUC1-expressing tumors, we performed immunohistochemistry for IDO1 and immunofluorescence for CD68/IDO1 coexpression. Immunostaining demonstrated a stronger signal in MUC1H tumors (Figure 8), and confocal laser scanning microscopy images confirmed a colocalization for both IDO1 and CD68 markers in infiltrating cells, demonstrating that the IDO1-positive cells were macrophages (Figure 10). Considering the role of cancer-associated mucins in modulating immune cell response and TME infiltration, we analyzed the presence of CD8+ and CD4+ T cells, and PD-L1 immunostaining in the ccRCC microenvironment. As concerns CD8-positive cells, their number in MUC1H tumors was very low compared to MUC1L specimens, whereas the number of CD4-positive lymphocytes did not show any significant variation in either group (Figure 11). Finally, we evaluated the role of the MUC1 in modulating the immune checkpoint ligand PD-L1 expression in ccRCC. Our findings showed that MUC1H tumors had reduced expression levels of PD-L1 (Figure 10), and these findings were in accordance with the TISIDB analysis results. ## 2.5. MUC1 Soluble Form (Serum CA15-3) Correlates with PTX3 Serum Levels, KYN-to-Tryptophan Ratio (KTR), and Other Systemic Inflammation Biomarkers We previously showed that serum PTX3 and MUC1 soluble form, also known as CA15-3, could serve as a circulating biomarker to identify ccRCC patients with poor outcomes [12,26]. Moreover, a previous study showed that increased KTR, a clinical marker of IDO1 activity, is a negative prognostic factor for cancer-specific and progression-free survival [25]. In addition, in recent years, different parameters originating from routine complete blood counts have been investigated as potential biomarkers of cancer-associated systemic inflammation. These include the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) [27,28,29,30,31,32]. To evaluate their correlation, CA15-3, serum PTX3, KTR, NLR, PLR, and MLR levels were preoperatively measured in patients who underwent nephrectomy for ccRCC at our institution. Patients with an abnormal value of CA15-3 also had increased serum levels of PTX3 ($p \leq 0.001$) and increased KTR ($p \leq 0.001$), NLR ($p \leq 0.001$), PLR ($p \leq 0.001$), and MLR ($p \leq 0.001$) (Figure 12A). Spearman’s test confirmed these results, showing a positive correlation between CA15-3 and PTX3, KTR, NLR, PLR, and MLR (Figure 12B). ## 3. Discussion In recent years, the multiomics characterization of ccRCC has resulted in the identification of specific molecular pathways that play a critical role in tumor pathogenesis and progression [5,6,7,8,9,10,33]. In addition, a better understanding of the molecular heterogeneity associated with the tumor microenvironment has revolutionized the therapy of patients with metastatic disease owing to the introduction of ICI [34,35,36]. Renal cell carcinoma is typically characterized by intratumor heterogeneity (ITH), and the identification of the mechanisms involved in this process represents a crucial issue also in the clinical setting because ITH is an important factor associated with treatment failure [35]. In a recent study, we showed that MUC1-expressing ccRCC is characterized by a specific signature consisting of impaired glucose and lipid metabolism [12]. In addition, MUC1 expression was associated with increased renal cancer cell proliferation and migration and had a prognostic role in patients affected by ccRCC [12]. To better define the role of MUC1 in additional renal-cancer-associated processes, we performed a GSEA using the Jones cohort (GSE15641) and stratified the patients according to MUC1 expression. Interestingly, this analysis revealed a previously unappreciated significance of MUC1 in modulating complement system activation. In a previous study, we demonstrated that increased expression of PTX3 in ccRCC was associated with the partial activation of the complement system with an overexpression of C1q, C3aR, and C5aR [19]. In the current study, we found that C1q deposition was extensively present in MUC1H ccRCC tissue samples and colocalized with PTX3. Moreover, in accordance with our previous results, the activation of the classical pathway did not correspond to an increased deposition of the terminal complex C5b-9, and this finding was associated with the increased expression of CD59, a complement system regulatory protein that prevents C5b-9 assembly. MUC1H tumors showed overexpression of the receptors of the anaphylatoxins C3a (C3aR) and C5a (C5aR). These proteins modify the immunological makeup of the TME, can activate mast cells and M2 TAMs, and are associated with increased tumor growth [37]. Angiogenesis is a hallmark of RCC and plays a pivotal role in the different phases of ccRCC progression [38,39]. We found that MUC1H tumors were characterized by a higher microvascular density in association with an increased number of mast cells. Tuna et al. observed a significant correlation between microvessel density and mast cell infiltration in RCC [40]. Mast cells are tissue-resident cells that actively participate in the tumor-associated angiogenic switch and shape the immune microenvironment [41,42]. Our findings were confirmed by a TISIDB analysis that showed a positive correlation between MUC1 expression and mast cell abundance. As concerns macrophages, we observed an increased number of CD68+CD163+ and CD68+IDO1+ cells in MUC1H tumor samples, revealing that TAMs were M2-polarized and able to produce KYN. These findings support our previous results that showed the accumulation of this metabolite in MUC1H versus MUC1L ccRCC [25]. The increased levels of KYN could contribute to an aggressive phenotype and CD8+ T-cell depletion observed in MUC1H tumors. Clear cell RCC has been classically identified as an immunotherapy-responsive tumor. The cytokine-based therapeutic protocols have been the standard of care in patients with advanced disease before the introduction of antiangiogenic drugs [43,44]. Recently, the progressive use of ICI has proved to be extremely effective even in this type of tumor, and combination therapies are becoming more widespread [45]. However, it is known that the efficacy of ICI is mainly predicted by PD-1/PD-L1 expression levels in association with tumor mutational burden, tumor-infiltrating lymphocytes, and other immune-related factors. In this scenario, our study showed that PD-L1 (CD274) expression was reduced in MUC1H ccRCC, as predicted by the TISIDB analysis. Finally, we analyzed the correlation between CA15-3—a circulating biomarker derived from MUC1—and different serum parameters associated with cancer-related systemic inflammation. In all cases, the correlation analyses demonstrated a positive relationship between CA15-3 serum levels and the other markers. Taken together, our results suggest that MUC1-expressing tumors can be identified as an immune-silent subgroup of ccRCC, characterized by low immune infiltration, high microvessel density, high M2-TAM response, and altered metabolism [46]. Moreover, in accordance with our findings, the analysis of the immune signature of the TCGA KIRC cohort showed that MUC1H ccRCC can mainly be classified as a C5 (immunologically quiet) cancer immune subtype [47]. In conclusion, this study suggests that expression of MUC1 can modulate the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system and regulating the immune infiltrate, promoting an immune-silent microenvironment. In particular, MUC1-expressing ccRCC is characterized by altered metabolism, high microvessel density, high M2-TAM response, low immune infiltration, and low expression of PD-L1. This particular phenotype would make these tumors more responsive to antiangiogenic therapies rather than ICI. ## 4.1. Study Population, Tissue Collection, and Circulating Biomarkers Evaluation An investigation was conducted in accordance with the Declaration of Helsinki and national and international guidelines and approved by the authors’ institutional review board. Written informed consent to take part was given by all participants. The primary renal tumor ($$n = 36$$) was collected from patients who underwent nephrectomy for ccRCC (Supplementary Table S1). For circulating biomarkers evaluation, serum CA15-3 (normal values: 0–25 U/mL), PTX3 (normal values: 0–2 ng/mL), kynurenine-to-tryptophan ratio (KTR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) were preoperatively measured in a cohort of 86 consecutive patients who underwent radical or partial nephrectomy for ccRCC at our institution. The pathological and clinical characteristics of these patients are summarized in Supplementary Table S2. Measurement of serum CA15-3 was performed with electrochemiluminescence immunoassay (ECLIA) on a fully automated Roche Cobas 8000 analyzer (Roche Diagnostics GmbH, Mannheim, Germany). Measurement of PTX3 was performed with sandwich ELISA on an automated platform (DSX, Technogenetics srl, Milano, Italy). Serum tryptophan (TRP) and kynurenine (KYN) levels were quantitatively determined with a tryptophan ELISA Kit (Abnova Corporation, Taipei, Taiwan) and human kynurenine ELISA Kit (Cusabio Biotech, Wuhan, China). ## 4.2. Gene Set Enrichment Analysis (GSEA) Gene expression data from the GSE15641 dataset were used and GSEA was run to determine the statistically enriched pathways in the ccRCC dataset [20]. ## 4.3. Immunohistochemistry For immunohistochemical evaluation, the following antibodies were used: mouse monoclonal anti-MUC1 (NB-120-22711, Novus Biologicals, Littleton, CO, USA), mouse monoclonal anti-tryptase (NB-100-64820, Novus Biologicals, Littleton, CO, USA), rabbit polyclonal anti-CD31 (ab28364, Abcam, Cambridge, UK), mouse monoclonal anti-CD68 (NCL-CD68-KP1, Novocastra Laboratories Ltd., Newcastle, UK), mouse monoclonal anti-CD163 (NCL-L-CD163, Novocastra Laboratories Ltd., Newcastle, UK), and mouse monoclonal anti-IDO1 (ab156787, Abcam, Cambridge, UK), diluted according to the respective datasheet indications. ## 4.4. Indirect Immunofluorescence and Confocal Laser Scanning Microscopy A double-label immunofluorescence was performed to evaluate the expressions of PTX-3, C1q, C5b-9, CD59, C3aR, C5R1, CD68, IDO1, and CD163 and their eventual co-localizations. 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--- title: Skeletal Muscle-Derived Exosomal miR-146a-5p Inhibits Adipogenesis by Mediating Muscle-Fat Axis and Targeting GDF5-PPARγ Signaling authors: - Mengran Qin - Lipeng Xing - Jiahan Wu - Shulei Wen - Junyi Luo - Ting Chen - Yaotian Fan - Jiahao Zhu - Lekai Yang - Jie Liu - Jiali Xiong - Xingping Chen - Canjun Zhu - Songbo Wang - Lina Wang - Gang Shu - Qingyan Jiang - Yongliang Zhang - Jiajie Sun - Qianyun Xi journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003660 doi: 10.3390/ijms24054561 license: CC BY 4.0 --- # Skeletal Muscle-Derived Exosomal miR-146a-5p Inhibits Adipogenesis by Mediating Muscle-Fat Axis and Targeting GDF5-PPARγ Signaling ## Abstract Skeletal muscle-fat interaction is essential for maintaining organismal energy homeostasis and managing obesity by secreting cytokines and exosomes, but the role of the latter as a new mediator in inter-tissue communication remains unclear. Recently, we discovered that miR-146a-5p was mainly enriched in skeletal muscle-derived exosomes (SKM-Exos), 50-fold higher than in fat exosomes. Here, we investigated the role of skeletal muscle-derived exosomes regulating lipid metabolism in adipose tissue by delivering miR-146a-5p. The results showed that skeletal muscle cell-derived exosomes significantly inhibited the differentiation of preadipocytes and their adipogenesis. When the skeletal muscle-derived exosomes co-treated adipocytes with miR-146a-5p inhibitor, this inhibition was reversed. Additionally, skeletal muscle-specific knockout miR-146a-5p (mKO) mice significantly increased body weight gain and decreased oxidative metabolism. On the other hand, the internalization of this miRNA into the mKO mice by injecting skeletal muscle-derived exosomes from the Flox mice (Flox-Exos) resulted in significant phenotypic reversion, including down-regulation of genes and proteins involved in adipogenesis. Mechanistically, miR-146a-5p has also been demonstrated to function as a negative regulator of peroxisome proliferator-activated receptor γ (PPARγ) signaling by directly targeting growth and differentiation factor 5 (GDF5) gene to mediate adipogenesis and fatty acid absorption. Taken together, these data provide new insights into the role of miR-146a-5p as a novel myokine involved in the regulation of adipogenesis and obesity via mediating the skeletal muscle-fat signaling axis, which may serve as a target for the development of therapies against metabolic diseases, such as obesity. ## 1. Introduction Adipose tissue and skeletal muscle are highly heterogeneous endocrine organs that secrete several hormones, with myokines and adipokines participating in local autocrine/paracrine interactions and crosstalk with other tissues [1]. Myokines and adipokines are essential for the maintenance of body muscle and fat levels and modulation of the body composition [2]. Irisin stimulates uncoupling protein 1 (UCP1) expression on white adipose cells in vitro and in vivo, which results in brown-fat-like development, while muscle-specific expression of PPARγ coactivator-1 α (PGC1α) drives browning of subcutaneous white adipose tissue [3]. As reported, the muscle interleukin-6 (IL-6) influences the main neuropeptides for energy homeostasis in a sex-specific manner [4]. The hormone myostatin inhibits myogenesis and promotes adipogenic differentiation of mesenchymal cells [5]. Prolyl hydroxylase 3 (PHD3) losses during endurance exercise challenges improve exercise capacity [6]. In mice with GR mKOs in the skeletal muscle, muscle mass is increased, while fat tissue is smaller [7]. The present study demonstrated that exercise induces myokines to counteract the negative effects of pro-inflammatory adipokines [8]. In recent years, there has been increased interest in investigating the effects of exercise training on adipose tissue [9]. Exosomes are small extracellular vesicles with a diameter of 50–150 nm, which are formed when multivesicular endosomes fuse with the plasma membrane and contained biologically active substances, such as proteins, RNA, DNA, cholesterol, etc. [ 10,11]. Secreted exosomes are taken up by and deliver their content to the recipient cells, thus representing a novel intercellular communication pathway [12]. Muscle and adipose exosomes can act as a mediator of intercellular communication to exert their physiological regulatory functions. There is increasing evidence that exosomes released by myogenic cells can transport their proteins, mRNAs, and miRNAs to recipient cells and regulate myocyte function in an autocrine or paracrine manner [13]. They can also enter the circulatory system, such as the blood, and may act on distant tissues [14,15]. The incorporation of muscle exosomes into various tissues in vivo, including the pancreas and liver, suggests that skeletal muscle (SKM) could transfer specific signals via the exosomal route to key metabolic tissues [16]. Endocytosis, membrane fusions, and receptor-mediated internalization are the mechanisms by which exosomes are absorbed intracellularly [17]. These variable internalization mechanisms and the signaling molecules presenting in exosomes are the reason why exosomes are widely accepted as important players of intercellular communication in the microenvironment and worthy of investigation [18]. The miRNA gene family adds a new layer of regulation and fine-tuning to gene expression that may affect a wide range of cellular functions, including metabolism, and numerous studies indicate that miRNAs play important roles in diverse aspects of signaling and metabolism, despite their unknown functions [19]. miR-27a released from adipocytes of high-fat diet-fed C57BL/6J mice was associated with a triglyceride accumulation. Exosomal miR-27a derived from adipocytes induces insulin resistance in C2C12 muscle cells through miR-27a-mediated repression of PPARγ and downstream genes involved in obesity [20]. miR-130b’s circulation could act as a metabolic mediator in adipose-muscle crosstalk, as well as a potential contributor to obesity-associated metabolic diseases [21]. MiR-124 secreted by adipose-derived stem cells has been implicated in skin wound healing, possibly by targeting MALAT1 and activating Wnt/catenin signaling pathways [22]. Accumulating evidence indicates that miR-146a-5p is a multifunctional miRNA that can act as a multidirectional target to regulate body metabolism. Mechanistically, miR-146a-5p attenuates TGF-β signaling by directly targeting SMAD family member 4 (SMAD4), thereby inhibiting cell proliferation, and attenuates AKT/mTORC1 signaling by targeting TNF receptor-associated factor 6 (TRAF6) to inhibit the differentiation of intramuscular preadipocytes [23]. Further studies revealed that hepatic miR-146a-5p overexpression significantly improved glucose and insulin tolerance as well as lipid accumulation in the liver by targeting the mediator complex subunit 1 gene (MED1) to promote the oxidative metabolism of fatty acids [24]. In long-living Ame’s dwarf (df/df) mice, miR-146a-5p mimetic treatment increased cellular senescence and inflammation and decreased pro-apoptotic factors in visceral adipose tissue [25]. Furthermore, the miR-146a gene might be a powerful target for preventing age-related bone dysfunctions such as the formation of bone marrow adiposity and osteoporosis [26]. However, whether skeletal muscle-derived exosomes by transferring miRNAs and then affects adipogenesis associated signaling pathways remains elusive. Recently, we compared the expression profiles of miRNA between exosomes derived from skeletal muscle and adipose tissue [27]. The findings showed that the content of miR-146a-5p in skeletal muscle-derived exosomes was more than 50 times higher than that in fat-derived exosomes, indicating that the miR-146a-5p may play a crucial role in regulating the skeletal muscle-fat axis. In this study, we intend to explore the connection between skeletal muscle and adipose tissue via the mediation of exosomes, especially, miR-146a-5p from skeletal muscle-derived exosomes mediating crosstalk between skeletal muscle and adipose tissue. Through transwell assay, gain-of-function and loss-of-function strategies in cell models, and skeletal muscle-specific miR-146a-5p knockout animal models, in vitro and in vivo studies have gradually revealed the exosomal miR-146a-5p released from skeletal muscle as a new myokine involved in the regulation of adipogenesis via mediating the skeletal muscle-fat signaling axis. ## 2.1. Transwell Co-Culture of C2C12 Cells Inhibits the Adipogenesis of 3T3-L1 Cells To further determine whether muscle cells can regulate adipocyte differentiation and lipid deposition via secreted exosomes, we used the transwell co-culture experiments with C2C12 cells and 3T3-L1 cells to test this possibility (Figure 1a). C2C12 myoblasts during proliferation (Pro) were cultured in vitro and induced to differentiate into mature myofibroblasts (Diff) (Figure 1b). The result showed that the differentiated C2C12 cells promoted the deposition of lipid droplets (Figure 1c), and significantly increased the content of TG in 3T3-L1 cells (Figure 1d). Next, we extracted the exosomes from the proliferation stage (Pro-Exos) and differentiation stage (Diff-Exos), respectively, and determined the morphology of Pro-Exos and Diff-Exos by electron microscopy (Figure 1e); nanoparticle tracking analysis (NTA) showed that the exosomes were mainly concentrated at 130–150 nm (Figure 1f), and the exosome marker proteins such as apoptosis-linked gene 2-interacting protein X (Alix), tumor susceptibility gene 101 (TSG101), CD9, and CD63 were mainly enriched in Pro-Exos and Diff-Exos, while the endoplasmic reticulum marker protein Calexin was mainly enriched in cells (Figure 1g), indicating that the exosomes were successfully extracted. Interestingly, we found that the expression of miR-146a-5p in the C2C12 cells’ proliferation stage was significantly higher than that in the differentiation stage of C2C12 cells, and the same expression level of miR-146a-5p also existed in the secreted exosomes (Pro-Exos and Diff-Exos) (Figure 1h). Then, 3T3-L1 cells were treated with Pro-Exos and Diff-Exos and induced to differentiate. RT-qPCR showed that Pro-Exos inhibited the mRNA levels of adipogenesis-related transcriptional factors PPARγ and C/EBPα (Figure 1i–j), and fatty acid synthesis-related genes CD36 and FABP4 (Figure 1k–l), on the contrary, the results of Diff-Exos treatment are reversed. These results suggest that the co-culture of C2C12 cells can inhibit adipogenesis of 3T3-L1 cells, and the reason may be related to exosomal miR-146a-5p secreted by C2C12 cells. ## 2.2. C2C12 Cells-Derived Exosomes Affect Glucose and Fatty Acid Uptake in 3T3-L1 Cells via Transferring of miR-146a-5p To further explore whether skeletal muscle-derived exosomes are involved in regulating adipogenesis and metabolism, especially via miR-146a-5p, we cultured 3T3-L1 adipose precursor cells in vitro to induce their maturation. The results showed that the deposition of lipid droplets and the content of TG in the Pro-Exos treated group was significantly smaller than that of the Diff-Exos group. However, Pro-Exos + i group the miR-146a-5p inhibitor co-treated with Pro-Exos 3T3-L1 cells obtained a similar phenotype to Diff-Exos, indicating that the downregulation of muscle exosomal miR-146a-5p can improve adipogenesis. Similarly, after co-treatment of Diff-Exos with miR-146a-5p mimics (Diff-Exos + m), lipid droplet phenotype and TG content are similar to that of Pro-Exos (Figure 2a,b). Subsequently, the expressions of adipogenesis-related proteins GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related proteins FABP4 and FASN were detected in 3T3-L1 cells of each group. The expression of these proteins was found to be significantly lower in the Pro-Exos and Diff-Exos + m treated groups than in the Diff-Exos and Pro-Exos + i treated groups (Figure 2c,d). To further explore whether skeletal muscle-derived exosomes can affect adipogenesis by affecting glucose and fatty acid uptake in adipocytes, we used fluorescently labeled glucose (2-NBDG) and fatty acids (Bodipy-FA) to observe glycolipid absorption. The amount of glucose absorbed by 3T3-L1 cells in the Pro-Exos treatment group was significantly smaller than that in the Diff-Exos treatment group for the same period. In the Pro-Exos + i group, the glucose uptake of 3T3-L1 cells was significantly greater than that in the Pro-Exos group, and in the Diff-Exos + m group, the absorption of glucose by 3T3-L1 cells was significantly lower than that in the Diff-Exos group (Figure 2e,f). Pro-Exos and Diff-Exos + m treated 3T3-L1 cells had significantly less uptake of free fatty acids than Diff-Exos and Pro-Exos + i treated groups (Figure 2g,h). Experiments showed that C2C12 cells-derived Pro-Exos can inhibit glucose and fatty acid uptake in 3T3-L1 cells, while Diff-Exos can promote glucose and fatty acid uptake in 3T3-L1 cells. Adding the inhibitor and mimics of miR-146a-5p to pro-Exos and diff-Exos, respectively, could reverse the effects of exosomal treatment alone on adipogenesis and glycolipid transport metabolism in 3T3-L1 cells. In summary, the above results highlight the important roles of exosomal miR-146a-5p in mediating the interactions between skeletal muscle cells and the adipocytes’ microenvironment. ## 2.3. miR-146a-5p Significantly Inhibits Adipogenesis, Glucose Uptake and Fatty Acid Absorption in 3T3-L1 Cells To further determine the role of skeletal muscle-derived exosomes in affecting adipogenesis mediated through miR-146a-5p, 3T3-L1 cells were transfected with miR-146a-5p mimics (Mimics) and miR-146a-5p inhibitor (Inhibitor) and induced to mature. The transfection efficiency of miR-146a-5p was quantitatively analyzed first. The expression of miR-146a-5p in 3T3-L1 cells transfected with miR-146a-5p mimics increased 166 times. However, the expression of miR-146a-5p in the miR-146a-5p inhibitor transfected group was also reduced by $33\%$, and both reached a statistically significant level (Figure 3a). For TG content in each group, it was significantly decreased for miR-146a-5p mimics and significantly increased for miR-146a-5p inhibitor (Figure 3b). At the same time, the results of Oil Red O staining showed that miR-146a-5p mimics could significantly reduce lipid droplet synthesis, while there is a significant increase in miR-146a-5p inhibitor (Figure 3c). To confirm the effect of skeletal muscle-derived exosomes on adipocyte glucose uptake and fatty acid absorption is mediated by miR-146a-5p, we used 2-NBDG and Bodipy-FA to examine the efficiency of glycolipid uptake in 3T3-L1 cells. The 3T3-L1 cells with miR-146a-5p inhibitor treatment significantly increased the uptake of glucose and the absorption of free fatty acids, while miR-146a-5p mimics treatment significantly reduced glucose uptake and free fatty acid uptake (Figure 3d–g). It was found by qPCR that miR-146a-5p mimics could significantly reduce the expression of adipogenesis-related genes PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, and FASN, while miR-146a-5p inhibitor significantly increased the expression levels of these genes (Figure 3h). Western blot results were consistent with the quantitative results that miR-146a-5p mimics significantly decreased the expression of adipogenesis-related proteins PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, and FASN, while miR-146a-5p inhibitor significantly increased the expression of these proteins (Figure 3i–j). The results showed that miR-146a-5p significantly inhibited the differentiation, glucose uptake, and fatty acid absorption of 3T3-L1 preadipocytes. ## 2.4. miR-146a-5p as a Negative Regulator of PPARγ Signaling by Directly Targeting GDF5 to Inhibit Adipogenesis To determine the targeting mechanism of miR-146a-5p inhibiting adipogenesis, the bioinformatics database miRDB was used to identify putative target genes for miR-146a-5p given the above adipogenesis-related genes and found that miR-146a-5p has a target interaction with the 3′UTR of GDF5 (Figure 4a). Subsequently, the relationship between miR-146a-5p and GDF5 was verified by dual luciferase and miR-146a-5p targeted the 3′UTR of GDF5 and reduced dual-luciferase expression (Figure 4b). In addition, we examined the protein and gene expression changes of GDF5 after miR-146a-5p overexpression and knockdown. As expected, miR-146a-5p overexpression decreased GDF5 protein expression, whereas miR-146a-5p knockdown increased GDF5 protein expression (Figure 4c,d). At the same time, overexpression of miR-146a-5p reduced GDF5 gene expression, and knockdown of miR-146a-5p increased GDF5 gene expression (Figure 4e), which is in line with the trend of miRNA regulation of target genes, and also indicated that miR-146a-5p targeted GDF5. To verify that miR-146a-5p regulates the PPARγ signaling pathway by targeting GDF5, three siRNAs against GDF5 were designed. First, the protein knockdown efficiency of GDF5 siRNA were verified, and GDF5 siRNA-3 significantly reduced GDF5 protein expression (Figure 4f,g). 3T3-L1 cells were transfected with different miR-146a-5p nucleic acid analogs and siRNA (NC, GDF5 siRNA, miR-146a-5p inhibitor + GDF5 siRNA), and the cells were cultured until mature. In 3T3-L1 cells treated with GDF5 siRNA, the expression levels of adipogenesis-related genes GDF5, PPARγ, C/EBPα and fatty acid synthesis-related genes CD36, FABP4 and FASN were significantly decreased, while in those co-treated with GDF5 siRNA and miR-146a-5p inhibitor, the gene expressions of adipogenesis-related genes GDF5, PPARγ, C/EBPα and fatty acid synthesis-related genes CD36, FABP4 and FASN were significantly increased compared with just GDF5 siRNA treatment (Figure 4h). Western blotting results further verified that 3T3-L1 cells transfected GDF5 siRNA significantly reduced the expressions of adipogenesis-related proteins GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, and FASN, while in those co-transfected with miR-146a-5p inhibitor and GDF5 siRNA, the expressions of adipogenesis-related proteins GDF5, PPARγ, C/EBPα and fatty acid synthesis-related proteins CD36, FABP4, and FASN were significantly increased (Figure 4i–j). We found that the content of TG and lipid droplets in the GDF5 siRNA treatment group were significantly lower than NC group, while the co-treatment of GDF5 siRNA and miR-146a-5p inhibitor significantly increased TG and lipid droplet content (Figure 4k–l). Co-immunoprecipitation (co-IP) test further showed that GDF5 has a protein-protein interaction relationship with PPARγ, C/EBPα, CD36, and FASN (Figure 4m). These results suggested that GDF5 participated in adipogenesis by regulating the PPARγ signaling pathway, indicating that miR-146a-5p regulated the PPARγ signaling pathway by targeting GDF5. ## 2.5. Skeletal Muscle-Specific Knockout miR-146a-5p Significantly Increased Body Weight Gain and Decreased Oxidative Metabolism in Mice To further explore the function of miR-146a-5p, we constructed a skeletal muscle-specific knockout mouse model of miR-146a-5p. Through Sanger sequencing and genotyping results, we confirmed that the mKO mice were successfully constructed (Figure 5a,b). By qPCR, the expression of miR-146a-5p was significantly knocked down in the gastrocnemius (GAS) and tibialis anterior (TA) of mKO mice compared with Flox mice (Figure 5c). Flox and mKO mice were induced with a high-fat diet (HFD) to observe the effect on the growth and metabolism of the mice. During the experiment, it was found that the HFD induction significantly increased the body weight gain of the mKO mice (Figure 5d). We found a significant decrease in muscle mass in both GAS and TA in mKO mice (Figure 5e). However, there was no difference in feed intake (Figure 5f). The skeletal muscle had no significant effect on insulin resistance in miR-146a-5p knockout mice (Figure 5g), but significantly improved glucose tolerance (Figure 5h). In terms of respiratory metabolism, O2 inhalation and CO2 exhalation in the skeletal muscle of miR-146a-5p knockout mice (mKO) were significantly lower than those in the Flox mice (control group) (Figure 5i–l). To a certain extent, O2 inhalation and CO2 exhalation reflect the energy metabolism level of the body. Therefore, the experiment showed that the skeletal muscle-specific miR-146a-5p knockout could increase body weight gain and reduce oxidative metabolism in mice. ## 2.6. Skeletal Muscle-Specific Knockout miR-146a-5p Significantly Increased Adipogenesis in Mice by Up-Regulating GDF5 and PPARγ To further explore how miR-146a-5p knockdown in the skeletal muscle regulates adipogenesis in vivo, the body composition and body imaging of the mice were observed, and the lean mass content of mKO mice was significantly reduced; interestingly, the fat mass content and fat enrichment increased instead, which successfully confirmed the crosstalk in the skeletal muscle and fat axis (Figure 6a,b). For further verification, the tissue weights of inguinal white adipose tissue (IngWAT) and epididymal white adipose tissue (EpiWAT) in mKO mice were found to be significantly higher than those in Flox mice (Figure 6c). At the same time, the HE-stained sections of IngWAT and EpiWAT tissues intuitively revealed that the adipocytes in mKO mice were larger and plumper (Figure 6d). qPCR analysis of adipogenesis-related gene expression showed that the expressions of GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, FASN in IngWAT of mKO mice were significantly increased compared with that of Flox mice (Figure 6e). Consistent with the quantitative results, the proteins of these genes were also more highly expressed in the IngWAT tissues of mKO mice (Figure 6f,g). Similarly, in the EpiWAT tissue of mKO mice, the expression of GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, FASN was significantly higher than that of Flox mice (Figure 6h), and the protein expressions of these genes were also significantly higher than those of Flox mice (Figure 6i–j). These results suggested that skeletal muscle miR-146a-5p knockout significantly increased adipogenesis in mice. ## 2.7. The Internalization of miR-146a-5p into the mKO Mice by Injecting Flox-Exos Inhibits Adipogenesis To further explore the function of skeletal muscle-derived exosomes, two different skeletal muscle-derived exosomes (Flox-Exos, mKO-Exos) were extracted and identified (Supplementary Figure S1a–c), and the expression level of miR-146a-5p was detected (Figure 7a). The skeletal muscle-derived exosomes were labeled with PKH67 and injected into mice via the tail vein, which was distributed in different organs after 24 h. Interestingly, imaging showed that PKH67-labeled exosomes were mainly distributed in IngWAT, EpiWAT, visceral adipose tissue (VAT), brown adipose tissue (BAT), GAS, TA, liver, lung, kidney (with a small enrichment in extensor digitorum longus (EDL)), soleus (SOL), heart, and spleen (Figure 7b). This indicated that skeletal muscle-derived exosomal miR-146a-5p could be specifically taken up into the fat tissues through humoral circulation (Figure 7c). When mice were continuously injected with skeletal muscle-derived exosomes for 3 weeks (Figure 7d), the body weight gain of Flox-Exos injected mice was significantly reduced at 2 weeks (Figure 7e), and the body weight was also different at 3 weeks (Figure 7f), but there was no difference in feed intake (Figure 7g). After aKO mice were injected with Flox-Exos, IngWAT and EpiWAT tissue weight in mice was significantly reduced (Figure 7h), and the fat mass in body composition decreased significantly, while the lean content showed an increasing trend (Figure 7i), and in vivo imaging also showed fat enrichment was decreased compared to injected with mKO-Exos (Figure 7j). In tissue sections, we found decreased accumulation of lipid droplets in the adipose tissue of mice injected with Flox-Exos (Figure 7k,o). Further studies found that IngWAT adipogenesis and fatty acid synthesis-related mRNA levels were significantly reduced in Flox-Exos-injected mice (Figure 7l), and protein levels were also significantly reduced (Figure 7m,n). Similar results were seen for EpiWAT adipogenesis and fatty acid synthesis-related mRNA and protein levels (Figure 7p–r). These results suggested that miR-146a-5p in skeletal muscle-derived exosomes can be specifically enriched in the adipose tissue, further affecting adipogenesis. Taken together, SKM-Exos-mediated intercellular miR-146a-5p has great potential for the prevention and treatment of obesity. ## 3. Discussion By binding the 3′UTR of mRNA, miRNAs regulate metabolic homeostasis by repressing or degrading the translation of target mRNA [28]. miR-146a is lowered in obese and type 2 diabetic patients, and mice fed a high-fat diet (HFD) show exaggerated weight gain, increased adiposity, hepatosteatosis, and dysregulated blood glucose levels compared to wild-type controls [29]. miR-146a may be involved in the regulation of inflammation in orbital fibroblasts, contributing to GO pathogenesis [30]. Exosomes derived from miR-146a-modified ADSCs reduced acute myocardial infarction (AMI)-induced myocardial damage by downregulating early growth response factor 1 (EGR1) [31]. Both in vitro and in vivo, miR-146a negatively regulates osteogenesis and bone regeneration in ADSCs [32]. In WAT, miR-146a may contribute to the regulation of inflammatory processes and prevent an overreaction to inflammation [33]. However, some studies suggest that miR-146a deficiency increases inflammation in the liver tissue without affecting lipid deposition in the liver [34]. Our findings indicate that low-abundance miR-146a-5p skeletal muscle-derived exosomes could be circulated to adipose tissue and increase adipogenesis. This indicates that miR-146a-5p plays different roles in different organs. The interaction between skeletal muscle and fat is dynamic, in which excessive accumulation of fat can cause skeletal muscle atrophy that in turn increases fat differentiation [35]. Adipose tissue is an important fuel reservoir for animal bodies, providing energy for energy-consuming tissues such as the skeletal muscle and ensuring the normal energy operation of the body. The exosome is a natural vehicle for intercellular communication that can penetrate tissues, and diffuse into the blood [36]. These exosomes carry proteins, mRNA, and miRNA for mediating intercellular communication and regulating the function of the recipient cells [37,38]. Previous studies have shown that miR-146a-5p mimics inhibit the proliferation and differentiation of porcine intramuscular adipocyte precursor cells, whereas miR-146a-5p inhibitors promote cell proliferation and adipogenic differentiation of adipogenic precursor cells [23]. After miR-146a-/- systemic knockout, mice were fed a high-fat diet, and their body weight gain was significantly higher; additionally, the sliced cells in the adipose tissue of the mice were significantly larger than those of the control group [39], which is consistent with the phenotype of muscle-specific miR-146a knockout mice in this study. Our study demonstrated that after knocking out miR-146a-5p in mouse skeletal muscle tissue, the adipose tissue showed a promotion effect the same as a miR-146a-5p inhibitor on adipogenic formation, revealing that the skeletal muscle tissue has a potential regulatory effect on adipose development, and the skeletal muscle-derived exosome is the bridge between the two tissues. Thus, the miR-146a-5p is critical for regulating the balance between normal skeletal muscle development and adipogenesis. In this study, the target gene of miR-146a-5p, GDF5, is a member of the TGF-β superfamily. GDF5 is mainly expressed in developing joints and lateral edges of joints and is a key regulator of cartilage and bone formation [40,41,42]. In addition, GDF5 also plays a key role in embryogenesis, limb development, and connective tissue repair [43]. Overexpression of GDF5 promotes brown adipocyte development in a transgenic mouse model [44]. PPARγ is the main regulatory gene of adipocyte proliferation and differentiation, which promotes adipocyte differentiation and increases the expression of lipid metabolism-related genes. As an important marker gene of adipose differentiation, PPARγ is of great significance to study the regulation of miRNAs. Up to now, a large number of studies have reported that miRNAs can directly or indirectly target the PPARγ signaling pathway to regulate lipid metabolism [45,46]. Subsequent studies found that there is a positive correlation between the gene and protein expressions of GDF5 and PPARγ during the differentiation of 3T3-L1 cells [47]. As research continues, the types of miRNAs found that regulate the expression of PPARγ have increased, and their regulatory mechanisms are gradually explored, providing more selectivity for future applications such as obesity treatment. The present study thus shows that miR-146a-5p internalization plays a critical role in SKM-Exos-mediated of adipogenesis, although other signaling pathways being regulated by GDF5/PPARγ-related cannot be completely excluded. ## 4.1. Animals The mice were housed under a 12 h light/12 h dark cycle at a constant temperature (23 ± 2 °C) with free access to food and water. The animals were fed ad libitum with standard mouse chow ($18\%$ protein, $4.5\%$ fat, and $58\%$ carbohydrate, purchased from Guangdong Medical Science Experiment Center, Guangzhou, Guangdong, China) for the first 8 weeks and high-fat chow (60 kcal% Fat from Research Diets, Cat No. D12492) from 8 to 20 weeks. All animal experiments used female mice aged 20 weeks at the time when they were sacrificed. The miR-146a-5p flox/flox (miR-146aflox+/+) and Myf5-Cre mice using CRISPR/Cas9/Cre method were generated (Cyagen, Suzhou, China) and maintained on a C57BL/6 background. They were used to study the metabolic effects of long-term HFD supplementation. *To* generate skeletal muscle-specific miR-146a-5p knockout (mKO) mice, miR-146aflox+/+ mice were first crossed with Myf5-Cre mice to obtain F1(miR-146aflox+/−,Cre+/−). Then the F1 mice mated with miR-146aflox+/+ mice to produce the mKO mice (miR-146aflox+/+,Cre+/−). The primer sequence of mouse genotype identification is shown in Table S1. The care of all animals and procedures at South China Agricultural University complies with “The Instructive Notions with Respect to Caring for Laboratory Animals” issued by the Ministry of Science and Technology of the People’s Republic of China and approved by the Animal Subjects Committee of South China Agricultural University. ## 4.2. NMR Analysis of the Whole-Body Composition Body composition of mice was determined using quantitative magnetic resonance (QMR, Niumag Corporation, Shanghai, China). ## 4.3. IPITT and IPGTT Before the intraperitoneal glucose tolerance test (IPGTT), mice fasted for 12 h. By using a blood glucose meter, blood glucose levels were measured at 0, 15, 30, 60, and 120 min after glucose (1 g∙kg−1) was injected intraperitoneally. In the intraperitoneal insulin tolerance test (IPITT), mice fasted for 6 h prior to the experiment. Insulin (0.7 U∙kg−1) was injected, and blood glucose levels were measured at 0, 15, 30, 60, and 120 min after injection. ## 4.4. In Vivo Oxygen Consumption Assay Utilizing the promotion metabolism measurement system (Sable Systems International, North Las Vegas, NV, USA), we analyzed O2 consumption (VO2) and CO2 production (VCO2) in HFD. ## 4.5. Imaging Experiments The tissue distribution of PKH67 (Sigma-Aldrich) labeled exosomes were visualized using fluorescence parameters as detected by the IVIS Lumina LT SeriesIII®® imaging system after injection of PKH67-labeled exosomes into the tail vein. We isolated all tissue samples within a 1-h post-mortem, rinsed them in cold PBS to remove blood, and observed them. Exosomes labeled with PKH67 (Sigma-Aldrich, St. Louis, MI, USA) were measured at 490 nm and 520 nm. ## 4.6. HE Staining Briefly, an aliquot of IngWAT (inguinal white adipose tissue) and EpiWAT (epididymal white adipose tissue) was fixed with $10\%$ formalin and embedded with paraffin. Then, fixed IngWAT and EpiWAT were sectioned and stained with hematoxylin-eosin (HE). ## 4.7. Cell Lines, Culture Conditions, Transfection The 3T3-L1 cells were grown in high-glucose Dulbecco’s Modified Eagle Medium (DMEM, Gibco) with $10\%$ fetal bovine serum (FBS, Gibco) and $1\%$ penicillin-streptomycin (P/S, Gibco) in a $5\%$ CO2 atmosphere at 37 °C. The differentiation was induced by incubating confluent cells (in 12-well plates) for 2 days in differentiation media, which was comprised of DMEM supplemented with $10\%$ FBS, 0.5 mM 3-isobutyl-1-methylxanthine (IBMX), 1 μM dexamethasone, and 10 μg/mL of insulin. Then the cells were cultured with 10 μg/mL insulin in $10\%$ FBS medium by changing the medium every 2 days until a mature lipid droplet appeared. For miR-146a-5p mimics or miR-146a-5p inhibitor (40 nM) (GenePharma, Shanghai, China) or si-GDF5 (50 nM) (Tsingke, Beijing, China) or exosome (10 μg/mL) transfection, 3T3-L1 cells were plated in 12-well dishes at a density of 1.0 × 105 per well and lipofectamine 2000 (Thermo Fisher, Waltham, MA, USA) transfection started at the cell density reached 60 to $70\%$. The sequence of siRNA transfected by 3T3L-1 cells is shown in Table S2. ## 4.8. Cell Co-Culture Transwell chambers (BIOFIL, TCS016012) were used to construct the co-culture systems. At the beginning of the test, the upper layer of the cell chamber was inoculated with 3T3-L1 cells (2.0 × 104 cells per well), and the lower layer with C2C12 cells (8.0 × 104 cells per well). They were cultured separately, co-cultured, and contacted for 48 h to detect indicators. ## 4.9. Collection of C2C12 Cell Culture Medium Supernatant The C2C12 cells were seeded in 75 cm2 cell culture flasks (1.0 × 106 cells/flasks) (Corning, Corning, NY, USA) exosome-free $10\%$ FBS DMEM and grown for 48 h. Then, the cellular supernatant was collected. The C2C12 cells were plated in 12-well plates (Corning, 3513), seeded with 8.0 × 104 cells per well in DMEM supplemented with $10\%$ FBS and $1\%$ P/S. By adding $2\%$ horse serum (HS, Gibco) after reaching $80\%$ confluency, C2C12 cells became myotubes for 4 days. The supernatant was collected by contacting the cells with $2\%$ exosome-free HS DMEM for 48 h. ## 4.10. Collection of Skeletal Muscle Tissue Culture Medium Supernatant In order to obtain the mice skeletal muscle tissue-derived exosomes, the mice’s were first identified by genotype. After identification, Flox mice and mKO mice were sacrificed by cervical dislocation and immersed in a beaker of $75\%$ alcohol and isolated in a sterile environment. The skeletal muscle tissue of mice was removed, washed with PBS (containing $1\%$ P/S), and placed in a medium containing exosome-free $10\%$ FBS DMEM. Then, the skeletal muscle tissue was carefully cut into 1 mm3 pieces with fine scissors for 10 min and washed with PBS 3 times. Then, they were placed in a petri dish and kept in an incubator of a $5\%$ CO2 atmosphere at 37 °C for 24 h to collect the medium supernatant. The exosomes were named Flox-Exos and mKO-Exos, respectively. ## 4.11. Exosome Isolation Isolation of exosomes in culture supernatant by ultracentrifugation. The specific steps were as follows. After centrifuging the culture supernatant at 2000× g for 10 min and 12,000× g for 30 min, large debris and dead cells were removed. An ultracentrifuge of 100,000× g for 70 min was performed on the supernatant. Finally, the cells were rinsed in 38 mL PBS and ultracentrifuged for 70 min at 100,000× g. We resuspended the pellets in 100 μL of PBS and stored them at −80 °C. ## 4.12. Transmission Electron Microscopy Analysis Exosomes of 10 μL were placed on copper grids coated with formvar, incubated for 5 min, and excess liquid was discarded. Uranyl acetate was added to the grid for negative stain for 1 min, and excess liquid was discarded. At 100 kV, samples were examined using transmission electron microscopy. ## 4.13. Dual-Luciferase Reporter Experiments We seeded HEK293T cells in 96-well plates (Corning) at 2.5 × 104 cells per well and grew them overnight to 70–$80\%$ confluence. The dual-luciferase reporter plasmids were co-transfected with miRNA into HEK293T cells and the dosage of miR-146a-5p NC/mimic and wild-type/mutation/deletion dual-luciferase gene reporter vector per well was 3 pmol and 100 ng, respectively. The Dual-Luciferase Reporter Assay System (Promega) was used to detect luciferase activity after 48 h. ## 4.14. Nanoparticle Tracking Analysis The exosomes were diluted to appropriate concentrations with PBS. The size of exosomes derived from cells or skeletal muscle tissue was measured by nanoparticle tracking analysis (NTA). Refer to the manual for the specific use of the instrument, including sample loading, photo-taking, and result statistics in brief. ## 4.15. Co-IP Experiment The specific steps are shown in the instructions. In short, Pierce™ Protein A/G Magnetic Beads (88803, Thermo Scientific, Waltham, MA, USA) were used to bind GDF5 antibody and added to the lysed samples. The magnetic beads were pulled down with a magnet, and the resulting precipitate was detected using a western blot to confirm whether the target protein exists, and the sample lysate was directly used as the Input group control to detect the target protein. ## 4.16. Oil Red O Staining After being treated and induced to mature, 3T3-L1 cells (24-well plates, Corning) were washed 3 times with PBS buffer, fixed in $4\%$ formaldehyde for 30 min at room temperature, washed 3 times with PBS for 5 min each, and then stained with oil red O (Sigma-Aldrich, Shanghai, China) for 1 h. To create a working solution, oil red O was first diluted with water (3:2) and filtered through filter paper. After staining the cells, the plates were washed 3 times in PBS for 5 min each and then photographed under a microscope (TE2000-E; Nikon, Japan). ## 4.17. Triglyceride Accumulation Triglyceride (TG) content was determined using a colorimetric/fluorometric assay kit (Biovision, Milpitas, CA, USA). 3T3-L1 cells were seeded into a 96-well plate and differentiated with CTE (500–1000 µg/mL) until they became mature adipocytes. A lipid droplet was then extracted by extraction buffer and converted by lipase to glycerol and fatty acid. A wavelength of 570 nm was used to measure the released glycerol. ## 4.18. Fatty Acid and Glucose Uptake Assay Fatty acid and glucose uptake assays were carried out using Bodipy-FA (Invitrogen Cat No. D3835) and 2-NBDG (Sigma Cat No. 186689-07-6), which are fluorescent tracers. ## 4.19. Quantitative Real-Time PCR We extracted the total RNA using TRIzol (Thermo Fisher). 1 µg of RNA was converted into complementary deoxyribonucleic acid (cDNA) using Color Reverse Transcription Kit (EZBioscience, Roseville, MN, USA, Cat No. A0010CGQ). We performed quantitative real-time PCR (qPCR) using a QuantStudio Real-Time PCR System (Bio-Rad C1000 Touch) using 2 × RealStar Fast SYBR qPCR Mix (GenStar, Cat No. A301). The mRNA and miRNA internal references were GAPDH and U6. Quantitative real-time PCR primer sequence is shown in Table S3, and reverse transcription primer sequences are shown in Table S4. ## 4.20. Protein Extraction and Western Blot Analysis Radioimmunoprecipitation assay (RIPA) buffer containing protease and phosphatase inhibitors (BestBio Cat No. BB-3101) was used to extract proteins. The protein concentration was assessed using the Rapid Gold BCA Protein Assay Kit (Thermo Fisher). Western blotting analysis was performed by loading 15 µg of lysate onto sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels, transferring the gels to polyvinylidene difluoride (PVDF) membranes (Millipore), and incubated with rabbit anti-GDF5 (1:1000, #A13167; ABclonal), rabbit anti-PPARγ (1:1000, #2443; CST), rabbit anti-FASN (1:1000, #D262701; Sangon Biotech), rabbit anti-C/EBPα (1:1000, #2295; CST), rabbit anti-FABP4 (1:1000, #2120; CST), rabbit anti-CD36 (1:1000, #ab1336-25; Abcam), rabbit anti-GAPDH (1:5000, #BS65529; Bioworld), rabbit anti-CD9 (1:1000, #AP68-965-100; Abcepta), rabbit anti-CD63 (1:2000, #D160973; Sangon Biotech), rabbit anti-TSG101 (1:2000, #381538; ZEN BIO), rabbit anti-Alix (1:1000, #D262028; Sangon Biotech) or rabbit anti-Calnexin (1:1000, #D262986; Sangon Biotech). Afterward, goat anti-rabbit secondary antibody (1:50000, # BS13278, Bioworld) conjugated with HRP was used. GAPDH levels served as the loading control. The amount of protein was measured using ImageJ software. ## 4.21. Statistical Analysis SPSS 25 and Graphpad prism 9.0 were used for one-way ANOVA and stand-alone sample t-test analysis and plotting. The results were presented as mean ± standard error of the mean (SEM). The significance of the difference was judged by a level of * $p \leq 0.05$ or ** $p \leq 0.01.$ The letters a, b, and c represent the level of statistical significance of the difference between the groups. Different letters mean a significant difference, and the same letters mean the difference is not significant. ## 5. Conclusions In conclusion, our results suggest that high levels of miR-146a-5p in mice are inversely correlated with adipogenesis. Skeletal muscle secreted large quantities of exosomes containing abundant proteins, mRNA, and miRNAs. Additionally, there were notably high levels of miR-146a-5p. 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--- title: Assessment of Lab4P Probiotic Effects on Cognition in 3xTg-AD Alzheimer’s Disease Model Mice and the SH-SY5Y Neuronal Cell Line authors: - Thomas S. Webberley - Ryan J. Bevan - Joshua Kerry-Smith - Jordanna Dally - Daryn R. Michael - Sophie Thomas - Meg Rees - James E. Morgan - Julian R. Marchesi - Mark A. Good - Sue F. Plummer - Duolao Wang - Timothy R. Hughes journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003662 doi: 10.3390/ijms24054683 license: CC BY 4.0 --- # Assessment of Lab4P Probiotic Effects on Cognition in 3xTg-AD Alzheimer’s Disease Model Mice and the SH-SY5Y Neuronal Cell Line ## Abstract Aging and metabolic syndrome are associated with neurodegenerative pathologies including Alzheimer’s disease (AD) and there is growing interest in the prophylactic potential of probiotic bacteria in this area. In this study, we assessed the neuroprotective potential of the Lab4P probiotic consortium in both age and metabolically challenged 3xTg-AD mice and in human SH-SY5Y cell culture models of neurodegeneration. In mice, supplementation prevented disease-associated deteriorations in novel object recognition, hippocampal neurone spine density (particularly thin spines) and mRNA expression in hippocampal tissue implying an anti-inflammatory impact of the probiotic, more notably in the metabolically challenged setting. In differentiated human SH-SY5Y neurones challenged with β-Amyloid, probiotic metabolites elicited a neuroprotective capability. Taken together, the results highlight Lab4P as a potential neuroprotective agent and provide compelling support for additional studies in animal models of other neurodegenerative conditions and human studies. ## 1. Introduction The gut microbiota is a complex stable microbial meta-community heavily influenced by host genetics, diet and the environment and this community of microorganisms has a major impact upon host physiology [1]. A bidirectional communication pathway exists between the gut microbiota and the central nervous system (CNS), termed the ‘gut–microbiota–brain axis’, and there is increasing evidence linking aging [2] and metabolic status [3] with changes/disruptions in this pathway. There is also growing support for a strong association between the composition of the gut microbiota and neurodegenerative conditions such as Parkinson’s disease (PD) and Alzheimer’s disease (AD) [4,5]. AD is the most common form of dementia with estimates of 850,000 sufferers in the UK [6] and over 50 million worldwide [7]. AD is a progressive brain disease characterised by the deposition of extracellular amyloid beta (Aβ) plaques and intracellular neurofibrillary (tau) tangles that result in substantial and progressive neuronal loss with age [7]. An early and critical feature of the neurodegenerative process in AD is the loss of the neuronal synaptic connections that results in disruption of brain function and connectivity [8]. Such changes dramatically impact upon a sufferer’s memory [9] and executive function—an umbrella term for verbal reasoning, problem-solving, planning, ability to maintain sustained attention, resistance to interference, multitasking, cognitive flexibility, and coping with novelty [10]. There is currently no cure for established AD, only strategies to target early stage disease [10] or to alleviate symptom severity [11]. The major risk factors for AD are age and genetics and it is now understood that excessive body weight during early/mid-life is linked with cognitive impairment and a doubled risk of developing AD during later life [12]. It has been shown that diet-induced obesity in genetically modified AD-prone mice leads to accelerated disease progression [13,14,15]. The increasing proportion of people over 65 in the population and the growing prevalence of obesity in society [16] highlight the need for strategies to ameliorate the onset and severity of dementia. One area of research that has recently seen some success in ameliorating disease pathology is dietary supplementation with probiotic bacteria (defined as ‘live microorganisms that when administered in adequate amounts confer a health benefit to the host’ [17]). Probiotics are well recognised for their ability to impart metabolic and immunological benefits to the host [18] and there is growing interest in the potential role/use of probiotic supplementation to combat neurocognitive decline or delay/prevent the onset of AD [19]. Pathological and/or cognitive improvements have been observed in both probiotic treated AD-prone mice [19,20,21,22] and healthy/diseased human cohorts [23,24]. The Lab4P probiotic consortium comprises a combination of lactobacilli and bifidobacteria that has been shown to contribute to neuroprotective effects on human neurons in vitro [25] and improve self-assessed mood rating in a free-living adult population [26]. Lab4P can also impact upon host metabolism evidenced by the inhibition of diet-induced weight gain in C57BL/6J mice wild-type mice [27] and significant weight loss in free-living overweight and obese overtly healthy adults receiving daily supplementation [26,28,29,30]. In addition, clear anti-inflammatory effects have been observed in LDR-/- mice receiving the probiotic [31]. These data imply a potential benefit during neurological disorders although efficacy of Lab4P on AD-related brain pathology has, so far, not been evaluated. In the current study, we test the hypothesis that Lab4P administered to 3xTg-AD mice (with or without a metabolic challenge) will have neuroprotective effects resulting in improved cognition (novel object memory) and reduce hippocampal neuronal spine density loss. This hypothesis was tested further in human SH-SY5Y neuronal cells challenged with β-Amyloid peptides. Our findings provide novel evidence that dietary supplementation with Lab4P has beneficial effects in mouse and cell models of disease. ## 2.1. Lab4P Maintains Cognitive Performance and Preserves Hippocampal Spine Densities in 3xTg-AD Mice (Study A) Male mice ($$n = 54$$) were fed from birth with standard chow diet (Teklad diet by Envigo, Supplementary Table S1) for 24 weeks. The baseline group (BLA; $$n = 18$$) were then sacrificed while the probiotic group ($$n = 18$$) received standard chow supplemented with Lab4P (Chow-P) for 24 weeks and the control group ($$n = 18$$) received standard chow (Chow-C) for 24 weeks (Figure 1A). Calculation of movements of the chow-fed 3xTg-AD mice during Novel Object Recognition (NOR) testing (Figure 1Bi) revealed differences in discrimination ratio (DR) between the Chow-C and Chow-P groups (Figure 1Bii) after 12 weeks ($35.2\%$, $$p \leq 0.0198$$) and 24 weeks ($40.8\%$, $$p \leq 0.317$$) in the intervention favouring the probiotic. The DR at baseline was 0.71 ± 0.02 and for the Chow-P group at 12 weeks, DR was 0.73 ± 0.04 and at 24 weeks it was 0.69 ± 0.05. The Chow-C group dropped significantly from BLA to 0.54 ± 0.05 ($$p \leq 0.009$$) at 12 weeks and 0.49 ± 0.08 ($$p \leq 0.0321$$) at 24 weeks. In the open field test (OFT, Figure 1Biii), no significant between-group differences were observed in total distance travelled, time in the arena centre nor the frequency of rearing, digging or grooming over the course of the study (although Chow-P results were universally higher than Chow-C after 24 weeks supplementation with a trend toward significance for digging: $84.8\%$, $$p \leq 0.0847$$). The behavioural characteristics of the Chow-P group remained consistent with BLA for the entirety of the intervention period, other than digging which increased significantly by 24 weeks ($63.7\%$, $$p \leq 0.0457$$). In the Chow-C group, there were significant decreases in time in arena centre at 12 and 24 weeks (−$36.9\%$, $$p \leq 0.0133$$ and −$49.3\%$, $$p \leq 0.0195$$), respectively, and rearing at 24 weeks (−$60.8\%$, $$p \leq 0.0145$$). The temporal changes in DR and OFT results for chow-fed 3xTg-AD mice over the 12-month study period are shown in Supplementary Figure S1. To determine whether Lab4P offered a beneficial impact on synaptic plasticity, we measured CA1 dendritic spines from chow-fed 3xTg-AD mice (Figure 2i). Between-group differences in spine loss were seen at 12 weeks ($27.1\%$, $p \leq 0.0001$, Figure 2ii) and 24 weeks ($23.0\%$, $$p \leq 0.0073$$), favouring the Lab4P mice (Chow-P). Within groups, the spine density decreased in the Chow-C group from $\frac{11.37}{10}$ μm ± 0.36 at baseline (BLA) to $\frac{9.35}{10}$ μm ± 0.26 ($$p \leq 0.0001$$) after 12 weeks and $\frac{8.78}{10}$ μm ± 0.28, ($p \leq 0.0001$) at 24 weeks. For the Chow-P group, spine density was $\frac{11.88}{10}$ μm ± 0.40 at 12 weeks and $\frac{10.80}{10}$ μm ± 0.50 at 24 weeks. Differential counts of the spines indicated thin spines as the most abundant followed by mushroom and then by stubby (Figure 2iii). At both 12 and 24 weeks of intervention, Chow-C mice displayed fewer mushroom spines with a significant loss of thin spines compared to BLA ($$p \leq 0.0006$$ and $$p \leq 0.0001$$, respectively). In Chow-P mice after 12 weeks intervention, the density of mushroom ($37.3\%$, $$p \leq 0.0001$$) and thin spines ($33.2\%$, $$p \leq 0.0016$$) were higher than in Chow-C and were similar densities to the BLA group. The temporal changes in neuronal spine density in chow-fed 3xTg-AD mice over the 12-week study period are shown in Supplementary Figure S2 and are consistent with AD progression. mRNA expression analysis of the hippocampi of the Chow-P mice (Table 1) indicated significantly lower levels of IL-10 transcripts ($66.4\%$, $$p \leq 0.0005$$) after 24 weeks compared to Chow-C, whereas all other genes were unchanged between groups. ## 2.2. Lab4P Maintains Cognitive Performance and Preserves Hippocampal Spine Densities in HFD-Fed 3xTg-AD Mice (STUDY B) Male mice ($$n = 15$$) were fed from birth with a standard chow diet for 12 weeks. The baseline group (BLB, $$n = 6$$) were sacrificed, while the probiotic group ($$n = 4$$) received a high fat diet (HFD) supplemented with Lab4P (HFD-P) for 12 weeks, and the control group ($$n = 5$$) received HFD alone (HFD-C) for 12 weeks (Figure 3A). Assessment of NOR in HFD mice (Figure 3Bi) revealed significant differences in DR; between groups, the HFD-P group was higher ($65.2\%$, $$p \leq 0.0047$$, Figure 3Bii) than the HFD-C group at 12 weeks. The HFD-P group was (0.76 ± 0.06) comparable to BLB (0.67 ± 0.01), but the HFD-C group decreased significantly over this time (0.46 ± 0.06, $$p \leq 0.0211$$). In the OFT, no significant between-group differences were observed for any behaviour at 12 weeks (Figure 3Biii). Distance travelled, rearing and digging were lower in HFD-P compared to HFD-C, trending towards significance for digging at 12 weeks (−$54.1\%$, $$p \leq 0.0728$$). In the HFD-P group, at the end of the intervention period, all behaviours remained similar to or dropped from BLB trending towards significance for rearing (−$63.2\%$, $$p \leq 0.0617$$). Behavioural patterns in HFD-C were more varied compared with BLB and distance travelled significantly increased from BLB ($52.2\%$, $$p \leq 0.0109$$). At the end of the intervention period, the total number of dendritic spines were reduced in the HFD-C mice ($27.5\%$, $$p \leq 0.0002$$, Figure 4i) compared to BLB. In the HFD-P mice, CA1 spine loss was prevented (compared with HFD-C, $27.1\%$, $p \leq 0.0001$) and similar to that of BLB mice ($\frac{11.21}{10}$ μm ± 0.49 vs $\frac{12.16}{10}$ μm ± 0.46, respectively, Figure 4ii). Subtyping the HFD-C mice dendritic spines based on morphology revealed significant reductions in all three spine subtypes compared to BLB (stubby $$p \leq 0.0248$$, mushroom, $$p \leq 0.0033$$, and thin $p \leq 0.0001$, Figure 4iii). In HFD-P mice, dendritic spines were protected with the density of thin spines comparable to BLB and significantly higher ($38.8\%$, $$p \leq 0.0037$$) than HFD-C. mRNA expression analysis of the hippocampus (Table 2) revealed lower transcript levels of the inflammatory cytokines interleukin (IL)-1β ($72.1\%$, $$p \leq 0.0015$$) and TNF-α ($43.4\%$, $$p \leq 0.0179$$) in the HFD-P group compared to HFD-C at 12 weeks, whilst all other genes were unchanged between groups. In the HFD-C mice, expression levels of IL-1β and TNF-α increased significantly from BLB (~5.5-fold, $p \leq 0.0001$), but HFD-P remained closer to BLB. A similar pattern of change was observed in the case of IL-6 where levels were significantly increased from BLB in HFD-C animals (2.1-fold, $$p \leq 0.0346$$) while those seen in the HFD-P group remained similar to BLB, albeit with no significant difference between intervention groups. ## 2.3. Lab4P CM Promotes Survival in Human SH-SY5Y Cells Challenged with β-Amyloid Successful differentiation of SH-SY5Y into a cholinergic phenotype was confirmed by the development of neuritic projections [32,33,34] (Figure 5Ai,Aii) and increased expression of neuronal and cholinergic mRNA markers (Figure 5Aiii): NeuN [35] (1.3-fold, $$p \leq 0.047$$), TH [35] (158.7-fold, $p \leq 0.001$), SLC18A [32] (6.7-fold, $p \leq 0.001$), CDK5 [32] (1.16-fold, $$p \leq 0.0209$$) and PSEN1 [32] (3.5-fold, $p \leq 0.001$). Exposure to human β-Amyloid 1-42 peptides for 48 h reduced the viability of undifferentiated and differentiated SH-SY5Y cells with maximal toxicity observed in response to 0.1 μM β-Amyloid (Figure 5B), which was used for subsequent neurotoxicity experiments. In undifferentiated SH-SY5Y cells pre-incubated with $50\%$ Lab4P CM prior to the inclusion of the β-Amyloid, the survival rate was $58.7\%$ compared to the vehicle control (Figure 5Ci); it was significantly higher ($$p \leq 0.042$$) than a survival rate of $48.8\%$ in response to incubation with β-Amyloid alone. In differentiated cells pre-incubated with 5 to $50\%$ Lab4P CM for 24 h prior to β-Amyloid inclusion (Figure 5Cii), survival rates ranged between 70.9 and $74.3\%$ compared to the vehicle control; significantly higher ($p \leq 0.001$ for all) than a survival rate of $55.6\%$ in response to β-Amyloid alone. The neurite length of differentiated SH-SY5Y cells was assessed and found to be unaffected by incubation with β-Amyloid 1-42 with or without pre-incubation with $50\%$ Lab4P CM (Supplementary Figure S3). mRNA expression levels of inflammatory and apoptotic genes were assessed in differentiated SH-SY5Y cells exposed to β-Amyloid with or without pre-stimulation with $50\%$ Lab4P CM (Table 3) and revealed a significant reduction in IL-6 expression in the cell exposed to β-*Amyloid plus* Lab4P CM compared with the vehicle control ($72\%$, $$p \leq 0.02$$). No changes in expression were observed in the expression of IL-8 and TNF-α mRNA; IL-1B and IL-10 mRNAs were undetectable in these cells. There were no statistically significant changes in the Bax:Bcl-2 ratios. ## 3. Discussion The data presented in this manuscript demonstrate the preventative effects of the Lab4P probiotic on cognitive decline, neurodegeneration and neuroinflammation in the 3xTg-AD mouse model in the presence or absence of a metabolic challenge, whilst in human SH-SY5Y neurones the probiotic reduced β-Amyloid neurotoxicity. Overall these data suggest that the Lab4P probiotic has the potential to play a role in the mitigation of the cognitive decline and neuroinflammation associated with AD-related pathologies. Cognitive capabilities of rodents, particularly memory and learning, can be assessed using a number of different tests. Here, we used a version of the Novel Object Recognition (NOR) test to generate the discrimination ratios (DRs) of the mice, and declines in performance in the control groups of both the chow- and HFD-fed animals were ameliorated by supplementation with probiotics. The DRs for mice challenged with HFD for 3 months (HFD-C) were found to be lower than those observed for mice fed on standard chow (see Supplementary Figure S1i) indicating that the HFD was worsening disease progression (as observed by other groups [13,14,15]). These outcomes align well with our previous probiotic studies showing reduced cognitive decline in 3xTg mice on a high fat diet [22] and better memory in aged Wistar rats [36]. Other groups have shown probiotic-mediated cognitive improvements with the 3xTg-AD mouse model receiving a multi-strain probiotic [20,37,38] and with other transgenic AD mouse models receiving either a single strain probiotic (Lactobacillus johnsonii) [39] or a multistrain (VSL#3) product [40]. Disease progression in 3xTg-AD mice impacts upon general/stereotypical mouse behaviours such as activity levels, exploration and rearing as illustrated by the open field test (OFT) [41,42]. The Chow-C mice showed indications of less distance travelled (exploration) and rearing than the mice in the Chow-P group. One of the characteristic traits that is absent in 3xTg-AD mice is fear of open spaces [41], but it was found that the Chow-C mice spent progressively less time in the centre of the test arena, whereas no changes were observed in the Chow-P group. The metabolically challenged HFD-C mice showed ‘hyperactive’ OFT responses to exploration, digging and rearing not seen in the HFD-P mice. It has been suggested that HFD feeding accelerates the decline of cognition and behaviour in 3xTg-AD mice [43], although reports are conflicting [44]. 3xTg-AD mice receiving the SLAB51 probiotic showed no impact upon ambulatory or stereotypic behaviour in the open field test [20]. Both aging and metabolic syndrome are associated with neurodegeneration typified by deterioration/loss of neuronal synaptic connections, notably, the loss of postsynaptic terminals (dendritic spines) that play an essential role in synaptic signalling and cognitive function [45,46,47] and spine loss is exacerbated in neurodegenerative conditions such as AD [8,48]. Significant losses in neuronal spine densities were observed on CA1 apical dendrites in the hippocampi of both the Chow-C and HFD-C mice, but no changes were observed in the mice receiving Lab4P which protected neuronal spine plasticity and integrity. In comparison with baseline mice (BLA), there was a decline in spine density in the HFD-C mice after 3 months (see Supplementary Figure S2i), again, indicating an acceleration of decline in response to the HFD [13,14,15]. The dendritic spine phenotypes are believed to have distinct functions with mushroom spines, considered important for memory and thin spines involved in learning [49]. The density of all spine categories was significantly decreased in the HFD-C mice whereas only the density of thin spines decreased significantly in the Chow-C mice, again illustrating the impact of HFD. Lab4P preserved the integrity of the mushroom and thin spines in the chow fed mice and for all spine phenotypes in the HFD-fed mice, and we have previously shown a probiotic impact in 3xTg-AD mice fed a high fat diet [22]. Neuroinflammation driving neuronal loss is a hallmark of AD [50,51,52] and we have previously observed indications of anti-inflammatory changes in the brains of probiotic fed 3xTg-AD mice [22]. IL-10 is an anti-inflammatory cytokine associated with the resolution of neuroinflammation [53] and, in the current study, reduced transcript levels of IL-10 were recorded in the hippocampus of the Chow-P mice, possibly indicating a less inflamed state. In contrast, IL-1β, IL-6 and TNF-α (major pro-inflammatory cytokines associated with synaptic loss [54,55] and neuronal death [56]) increased from baseline in the HFD-C mice. Supplementation with Lab4P significantly abrogated these increases, again indicating an anti-inflammatory capability. This was comparable with findings in works involving the SLAB51 probiotic [20] and with 5xFAD-AD mice supplemented with *Lactobacillus salivarius* [57]. It is worth noting that elevated mRNA levels of pro-inflammatory genes, including IL-1β, IL-6 and TNF-α, were not found in the hippocampi of Chow-C mice, suggesting that the generation of the overtly pro-inflammatory state may be linked to the HFD feeding regime. These data support implications of ‘overweight status’ significantly increasing risks of AD later in life [12,58]. Obesity is recognised as an inflammatory disorder driving both systemic and neurological inflammation [59] and Lab4P has been shown to (i) inhibit diet-induced weight gain in wild-type mice on a HFD [27] and (ii) induce significant weight loss in free-living overweight and obese human adults [26,28]. The Lab4P probiotic had no impact upon the extent of the diet-induced weight gain in the mice (Supplementary Figure S4). Lactic acid (a major probiotic metabolic end product) has been shown to exert anti-inflammatory effects in peripheral blood mononuclear cells [60], and in aging rats receiving probiotics where improvements in learning and memory were found to be associated with increased levels of lactate in the brain [36]. The Lab4P consortium harbours a number of putative genes involved in the generation short chain fatty acids (SCFA) [61] that impact upon plasma SCFA levels in vivo [62]. SCFA are thought to exert anti-inflammatory effects on the brain [63]. The accumulation and deposition of β-*Amyloid is* believed to play a key role in AD pathology in humans and is associated with neurodegeneration and cognitive decline [64]. β-Amyloid deposition was not detected in the hippocampus of our cohort of 3xTg-AD mice [22]—potentially due to the noted phenotypic changes that have occurred in the strain since its generation twenty years ago in 2003 [65,66]. Cholinergic neurones are particularly vulnerable to β-Amyloid [67] which are highly abundant in the hippocampus [68]. We combined human SH-SY5Y neuronal cells (in both their naïve undifferentiated form and after RA/BDNF differentiation into a cholinergic phenotype [32]) with neurotoxic β-Amyloid 1-42 peptides and Lab4P metabolites in order to assess the neuroprotective capabilities of the probiotic. The β-Amyloid exerted significant loss of viability in both naïve and cholinergic SH-SY5Y cells and these effects were abrogated by pre-incubation with Lab4P. In the cholinergic cells, neuroprotection by Lab4P occurred alongside a significant reduction in mRNA levels of the pro-inflammatory cytokine, IL-6, supporting the observations made in the hippocampus of HFD-fed 3xTg-AD mice receiving Lab4P. Our findings align well with the work of Sirin and colleagues in undifferentiated SH-SY5Y cells demonstrating the protective effects of exopolysaccharides from *Lactobacillus delbrueckii* ssp. bulgaricus B3 and *Lactobacillus plantarum* GD2 against β-Amyloid 1-42 toxicity [69]. To date, all other probiotic studies using SH-SY5Y cells have worked solely in non-cholinergic phenotypes and have demonstrated neuroprotective effects against a range of toxic challenges [25,70,71,72,73,74]. Our previous and current work indicates that Lab4P can protect undifferentiated SH-SY5Y cells against (i) rotenone (Parkinson’s disease-like neurodegeneration [75]), (ii) serum deprivation (intracellular reactive oxygen species accumulation and apoptosis [76]) and (iii) D-galactose (cellular senescence/aging in vitro [77], see Supplementary Figure S5). In summary, this study identified the ability of the Lab4P probiotic consortium to slow the progression of cognitive decline and neurodegeneration in 3xTg-AD mice in the presence or absence of a “metabolic” challenge, and a protective effect against neurodegeneration and neuroinflammation was observed in human SH-SY5Y neurones. Together, our findings support further in-depth assessment of the prophylactic neuroprotective potential of Lab4P in both animal models and in human trials. ## 4.1.1. Probiotic Intervention The Lab4P probiotic consortium is composed of *Lactobacillus acidophilus* CUL21 (NCIMB 30156), *Lactobacillus acidophilus* CUL60 (NCIMB 30157), *Lactobacillus plantarum* CUL66 (NCIMB 30280), *Bifidobacterium bifidum* CUL20 (NCIMB 30153) and *Bifidobacterium animalis* subsp. lactis CUL34 (NCIMB 30172) and was administered as a lyophilised preparation (mixed with feed) delivering a daily dose of ~5 × 108 colony forming units (CFU)/mouse/day (human equivalent dose of ~5 × 1010 CFU/day). ## 4.1.2. Mouse Husbandry and Study Designs Mouse experiments were performed under the UK Home Office Project Licence (PPL P8159A562). The 3xTg-AD mice were bred from an in-house colony, founders originally purchased from JAX laboratories (B6;129-Psen1tm1MpmTg (APPSwe,tauP301L) 1Lfa/Mmjax; Genetic Background: C57BL/6; 129X1/SvJ; 129S1/Sv) (Bar Harbor, ME, USA, strain 004807) after generation by Frank LaFerla (University of California, Irvine, CA, USA). These mice contain three mutations associated with familial Alzheimer’s disease (APP Swedish, MAPT P301L, and PSEN1 M146V). All mice were housed in Scantainer vented cages in a light and temperature-controlled environment (12 h on/off light at 22 °C) and had ad libitum access to diet and water. A schematic representation of the study design and the schedule of sample collection/analysis is shown in Figure 1A and Figure 3A. Male mice ($$n = 69$$) were fed from birth with standard chow diet (Teklad diet by Envigo, Supplementary Table S1) for 12 weeks before 54 mice were randomly selected to enter Study A and 15 mice were selected to enter Study B. The mice entering Study A received a chow diet for a further 12 weeks when the baseline group (BLA, $$n = 18$$) was sacrificed; the probiotic group ($$n = 18$$) received standard chow supplemented with Lab4P (Chow-P) for 24 weeks; and the control group ($$n = 18$$) received standard chow (Chow-C) for 24 weeks. In Study B, the baseline group (BLB, $$n = 6$$) were sacrificed immediately; the probiotic group ($$n = 4$$) received a high fat diet (HFD) supplemented with Lab4P (HFD-P) for 12 weeks; and the control group ($$n = 5$$) received HFD alone (HFD-C) for 12 weeks. The HFD comprised $21\%$ (w/w) pork lard with $0.15\%$ (w/w) cholesterol (Special Diets Services, Witham, UK; product code: 821,424, Supplementary Table S2). For both studies, food and water intake were monitored and mice were weighed every two weeks. At the end of the study, all mice were euthanized by schedule 1 CO2 inhalation and blood was collected via cardiac exsanguination. Mice were cardiac-perfused immediately afterwards with 1 X PBS to ensure clearance of blood from vessels and organs. Brains were removed and micro-dissected to obtain key regions. These subsamples were either analysed immediately (for neuronal spine density) or snap frozen (hippocampi) and stored at −80 °C (for mRNA expression analysis). ## 4.1.3. Mouse Behavioural Testing All behavioural testing was performed in a custom-made plastic test arena (39 cm (Height) × 39 cm (Width) × 39 cm (Length)) that was placed in a class II laminar flow hood. Novel object recognition (NOR) testing was performed in three stages over 2 days. On day one, each mouse was placed in the box containing sawdust alone and allowed to explore for 10 min before being returned to its home cage (habituation). The next day, each mouse was again allowed to explore the empty test arena for 10 min (open field test) before being returned to its home cage for 30 min. Mice were returned to the test arena to which two identical objects (familiar objects, FO) had been added for 10 min. Each mouse was again returned to its home cage for 30 min. Finally, one FO was replaced with a novel object (NO) and each mouse was placed in the test arena for a further 10 min. The FOs and NOs were similar in size but differed in colour and shape. Mouse movements and time spent exploring objects were recorded using a GoPro HERO session camera (GoPro, USA) positioned directly above the test arena, and the data were analysed using Ethovision XT 13 software (Noldus, Wageningen, The Netherlands). The time spent exploring the NO (head oriented towards and within 2 cm) was divided by the time spent exploring both the FO and the NO to provide the discrimination ratio (DR). A reduction in DR denotes less interest in the novel object and implies impaired memory. The analyst was blinded to the group allocation during the test. ## 4.1.4. Staining, Imaging and Morphological Classification of Neuronal Dendritic Spines in the Hippocampus Hippocampal CA1 dendritic spines were determined according to previous descriptions [22,48]. In brief, the fluorometric carbocyanine dye 1,1′-Dioctadecyl-3,3,3′,3′-Tetramethylindocarbocyanine Perchlorate (DiI) (Life Technologies, Carlsbad, CA, USA) was dissolved in dichloromethane and applied dropwise to coat 1.67 µm diameter tungsten particles (Bio-Rad, Hercules, CA, USA). Dye coated tungsten particles were funnelled into ethylene tetrafluoroethylene (ETFE) tubing and cut into ‘bullets’ for ballistic DiOlistic labelling onto fresh hippocampal slices (200 μm thick) at 100 psi using a Helios Gene Gun (Bio-Rad, USA) through a 3.0 µm pore size cell culture insert. Dye labelling was checked under a fluorescence microscope to confirm neuronal labelling with subsequent labelling controlled by adjusting delivery pressure and frequent replacement of inserts. Hippocampal slices were placed in Neurobasal-A medium (Life Technologies) and incubated at 37 °C with $5\%$ CO2 for 20 min to facilitate dye diffusion. Slices were fixed in $4\%$ paraformaldehyde (PFA) for 30 min at room temperature, nuclear stained with Hoechst 33342, mounted in FluorSave and stored in the dark at 4 °C until imaging the following day. Dendritic spines were imaged on secondary dendrites within the striatum radium region of hippocampal CA1 neurons using a Leica SP8 laser-scanning confocal microscope with lightning deconvolution (Leica Microsystems, Milton Keynes, UK). Dendritic segments were imaged under a 63× objective (z axis interval 0.2 µm) with images processed under Lightning deconvolution (Leica). Typically, each mouse generated approximately 10–15 slices which corresponded to around 10 labelled CA1 neurons. Dendrite segments longer than 30 µm were 3D reconstructed in BitPlane Imaris software version 9.3.1 using the module Filament Tracer with default thresholding based around a ‘region of interest’. Dendritic spines were classified based on morphology using the Spine Classifier MATLAB extension. Spines were distinguished on the basis of spine length and spine head size and classified as follows: stubby spines were <0.8 µm in length; mushroom spines were >0.8 µm, but ≤3 µm in length with a spine head diameter greater than neck width; and thin spines were >0.8 µm, but ≤3 µm in length but without a bulbous head. Protrusions >3 µm in length were considered to be filopodia, were infrequently detected and therefore not included in the analysis. Each reconstructed dendrite segment was manually checked to ensure correct spine detections with the operator blinded to the experimental condition during reconstruction and data collection. ## 4.1.5. mRNA Expression Analysis of Hippocampus Frozen hippocampal tissues were thawed and homogenised with RiboZol (VWR, UK) for 3 × 20 s in a Fast Prep-24 Bead Beater (MPBIO, Santa Ana, CA, USA) with cooling on ice between each round. RNA was extracted and quantitative PCR (qPCR) was performed as described elsewhere [22] using the gene-specific oligonucleotide primers shown in Supplementary Table S3. mRNA expression levels in relation to the untreated controls were determined using 2−ΔCt, where ΔCt represents the difference between the threshold cycle (CT) for each target gene and the housekeeping gene (β-actin). ## 4.2.1. Maintenance and Differentiation of SH-SY5Y Cell Cultures SH-SY5Y cells were maintained in T75 culture flasks (Costar, Cambridge, UK) in DMEM/F12 (Labtech, Heathfield, UK) supplemented with $10\%$ (v/v) heat inactivated fetal bovine serum (Labtech, UK), penicillin (100 U/mL) and streptomycin (100 U/mL) at 37 °C in $5\%$ CO2 and $95\%$ humidity. When cells reached ~$80\%$ confluence, they were seeded into 96 well (viability assays) or 24 well (mRNA expression assays) tissue culture plates (Costar, Cambridge, UK) at a density of 5 × 105 cells/cm2 and incubated at 37 °C in $5\%$ CO2 and $95\%$ humidity for 24 h prior to experimentation, or differentiation followed by experimentation. Differentiation was achieved according to the method of de Medeiros et al. [ 32]; cells were incubated for 1 day in DMEM/F12 with $10\%$ serum followed by 3 days in DMEM/F12 with $1\%$ serum plus 10 μM Retinoic acid (RA) and then 3 days in DMEM/F12 with $1\%$ serum plus 10 μM RA plus 50 ng/mL bone derived neurotrophic factor (BDNF) (Abcam, Cambridge, UK). ## 4.2.2. Quantification of Neurite Length Images of the cells (8-bit grey scale, ×10 magnification) at the approximate centre of the tissue culture wells (1 image per well) were captured using a Leica Flexacam C3 microscope camera attached to a Leica DMi1 inverted microscope (Leica Microsystems, Solms, Germany) and were analysed for neurite length using the manual tracing facility in NeuronJ [32]. Analysis was performed on 5 cells per image that were randomly selected; an overlay reference grid with sequentially numbered (top left to bottom right) 1 mm2 squares was overlaid onto the image and the cell closest to the centre of a randomly selected square (using a random number generator (https://www.random.org/, last accessed on 24 February 2023) was analysed. The analyst was blinded to the cell treatments. ## 4.2.3. mRNA Expression Analysis in SH-SY5Y Cells Total RNA was extracted and quantitative PCR was performed as described elsewhere [25] using the gene-specific oligonucleotide primers shown in Supplementary Table S3. mRNA expression levels in differentiated cells were expressed in relation to undifferentiated cells or the vehicle control and determined using 2−ΔCt, where ΔCt represents the difference between the threshold cycle (CT) for each target gene and the housekeeping gene (β-actin). ## 4.2.4. Generation of Lab4P Conditioned Media (CM) and SH-SY5Y Cell Stimulation DeMan–Rogosa–Sharpe (MRS) broth was inoculated with lyophilised Lab4P and incubated anaerobically at 37 °C for 18 h. The culture was centrifuged (2500× g for 20 min), washed in phosphate buffered saline (PBS), resuspended at 1 × 109 CFU/mL in a 1:1 mix of Dulbecco’s Modified Eagle’s medium and Ham F-12 medium (DMEM/F12) and incubated without agitation under anaerobic conditions at 37 °C for 5 h. The cells were pelleted (2500× g for 20 min) and the supernatant was filtered (0.22 µm, Gibson, Bedfordshire, UK), adjusted to pH 7.4 using 1 M NaOH and supplemented with 100 U/mL penicillin and 100 U/mL streptomycin (Labtech, Heathfield, UK) to provide the sterile conditioned medium (CM). For experimentation, CM was diluted in DMEM/F12 supplemented with 100 U/mL penicillin and 100 U/mL streptomycin and 200 µL or 2 mL were applied per well of 96- and 12-well plates, respectively. Unconditioned DMEM/F12 supplemented with 100 U/mL penicillin and 100 U/mL streptomycin was used as a control for the CM. Human β-Amyloid 1-42 peptides (Abcam, Cambridge, UK) were dissolved in DMSO prior to application to the cells. ## 4.2.5. Assessment of SH-SY5Y Cell Viability SH-SY5Y cells were washed with 200 µL of PBS (pH 7.4, 37 °C) before exposure to 100 µL of 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) solution (500 µg/mL in DMEM/F12) for 2 h at 37 °C in $5\%$ CO2 and $95\%$ humidity. The cells were washed twice by the repeated addition and removal of 200 µL of PBS (pH 7.4, 37 °C) before the addition of 100 µL of DMSO for 5 min (with occasional agitation by hand). The absorbance at 570 nm was read using a colorimetric spectrophotometer and viability data are expressed as percentage survival compared to the control cells that have been arbitrarily assigned as $100\%$. ## Studies In Vivo and In Vitro All data are presented as the mean ± standard error of the mean (SEM) of the assigned number of mice or independent experiments. The normality of all data was assessed using Q-Q plots. For normally distributed data, values of p were determined using Student’s t-test, one-way analysis of variance (ANOVA) with Tukey’s post-hoc analysis where homogeneity of variance was met (as determined by the modified Levene’s test) or Brown–Forsythe ANOVA with Dunnett’s T3 post-hoc analysis. Where the data were not normally distributed, values of p were determined using the Kruskal–Wallis test with Dunn’s post hoc analysis. All statistical tests were performed using GraphPad Prism (Version 8.2.1). 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--- title: 'Antioxidative and Mitochondrial Protection in Retinal Pigment Epithelium: New Light Source in Action' authors: - Ming Jin - Xiao-Yu Zhang - Qian Ying - Hai-Jian Hu - Xin-Ting Feng - Zhen Peng - Yu-Lian Pang - Feng Yan - Xu Zhang journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003667 doi: 10.3390/ijms24054794 license: CC BY 4.0 --- # Antioxidative and Mitochondrial Protection in Retinal Pigment Epithelium: New Light Source in Action ## Abstract Low-color-temperature light-emitting diodes (LEDs) (called 1900 K LEDs for short) have the potential to become a healthy light source due to their blue-free property. Our previous research demonstrated that these LEDs posed no harm to retinal cells and even protected the ocular surface. Treatment targeting the retinal pigment epithelium (RPE) is a promising direction for age-related macular degeneration (AMD). Nevertheless, no study has evaluated the protective effects of these LEDs on RPE. Therefore, we used the ARPE-19 cell line and zebrafish to explore the protective effects of 1900 K LEDs. Our results showed that the 1900 K LEDs could increase the cell vitality of ARPE-19 cells at different irradiances, with the most pronounced effect at 10 W/m2. Moreover, the protective effect increased with time. Pretreatment with 1900 K LEDs could protect the RPE from death after hydrogen peroxide (H2O2) damage by reducing reactive oxygen species (ROS) generation and mitochondrial damage caused by H2O2. In addition, we preliminarily demonstrated that irradiation with 1900 K LEDs in zebrafish did not cause retinal damage. To sum up, we provide evidence for the protective effects of 1900 K LEDs on the RPE, laying the foundation for future light therapy using these LEDs. ## 1. Introduction Today, light-emitting diodes (LEDs) are widely used because of their low power consumption, ease of use, long service life, and good color rendering index (CRI) scores. However, the harmful blue band portion of phosphor white LEDs may affect human health in two directions: [1] potential retinal phototoxicity [1,2]; [2] disruption of internal circadian rhythm, including health problems associated with circadian rhythm disturbances [3,4,5,6,7,8,9]. To avoid blue-light hazards, LED developers abandoned the principle of using blue LEDs to excite phosphors for generating white light; they instead use silicon substrate InGaN yellow light and AlGaInP red LEDs to synthesize blue-free low-color-temperature phosphor-free LEDs (called 1900 K LEDs for short). The CRI of 1900 K LEDs can exceed 80, and the color temperature is 1600–2200 K, which meets lighting needs. Shortly after the emergence of 1900 K LEDs, we conducted relevant retinal phototoxicity in vitro experiments using these LEDs. We found that the 1900 K LEDs caused less cell death than other high-color-temperature phosphor white LEDs [10]. We also found that the 1900 K LEDs benefited wound healing, hair growth, and melatonin and glutamate secretion. Moreover, the 1900 K LEDs could also protect the ocular surface [11]. The above experiments proved that 1900 K LEDs may have a certain protective effect and high safety. By 2040, the number of people with age-related macular degeneration (AMD) will be nearly 300 million [12], posing a major public health problem with a significant socioeconomic impact. It is well known that progressive degeneration and death of the retinal pigment epithelium (RPE) represent key pathological processes in AMD. Therefore, treatment for RPE is significant [13,14]. Considering the protective effects of 1900 K LEDs on the ocular surface, we hypothesized that the 1900 K LEDs may protect the RPE. Actually, excess reactive oxygen species (ROS) and mitochondrial defects exist in the RPE of AMD [15]. Red–yellow light-related photobiomodulation (PBM) treatment precisely targets the mitochondria and oxidative stress [16,17,18,19]. Therefore, we believe that 1900 K LEDs can play a key role in preventing and treating AMD by protecting the RPE. ARPE-19 cells, a reliable and standard model for AMD research, were mainly used as the experimental object in this study to preliminarily investigate the protective effects of 1900 K LEDs on RPE. In addition, we preliminarily demonstrate in vivo that the irradiation of this new light source posed no harm to the retina in zebrafish. Specific experiments included a cell activity assay, cell death assay, ROS level detection, mitochondrial imaging, mitochondrial DNA (mtDNA) damage detection, Western blotting, and hematoxylin and eosin (H&E) staining. ## 2.1. 1900 K LEDs Regulate Cell Activity According to Irradiance and Light Time After irradiation at 10 W/m2 for 48 h, all LEDs except the 1900 K LEDs decreased cell activity (Figure 1a). The 1900 K LEDs at three irradiances (5, 10, and 15 W/m2) all increased cell activity to varying degrees, with the irradiance at 10 W/m2 increasing cell activity most significantly (Figure 1b). Thus, the irradiance was kept at 10 W/m2. After 1, 2, and 3 days of irradiation with 1900 K LEDs, the cell activity increased by about $30\%$, $70\%$, and $75\%$, respectively (Figure 1c). These experiments led us to determine the parameters of LED illumination in later experiments, i.e., 10 W/m2 illumination for 48 h. Such experiments on the effects of LEDs with different color temperatures on cells are not uncommon. Chen et al. [ 20] found that 7378 K LEDs caused excessive intracellular ROS production and severe DNA damage in cultured human lens epithelial cells (hLECs) compared to 2954 K and 5624 K LEDs, which led to G2/M phase block and apoptosis. Another study found that 7378 K LEDs, but not 2954 K LEDs, induced the upregulation of VEGF-A, IL-6, and IL-8, as well as the downregulation of MCP-1, through an accumulation of ROS and the activation of MAPK and NF-κB signaling pathways [21]. These studies partially support our results. However, the subjects of these experiments did not involve LEDs with such a color temperature of 1900 K. To address this gap, we designed follow-up experiments. ## 2.2. Pretreatment with 10 W/m2 1900 K LEDs Reduced the Death of ARPE-19 Cells To explore the protective effects of the 1900 K LEDs on damaged cells, we chose the hydrogen peroxide (H2O2) damage model, which is classically used for the study of AMD. As shown in Figure 2a, we treated cells with a series of concentrations of H2O2 (200 μM, 400 μM, 600 μM, 800 μM, and 1000 μM) for 6 h before choosing 400 μM as the final concentration. Next, we investigated the effects of two paradigms on ARPE-19 cells and found that the protection of the light post-treatment was limited (Figure 2b). This was also corroborated by the bright-field images and the flow cytometry results on apoptosis (see Supplementary Figure S1). Therefore, we switched to a 1900 K LED pre-illumination paradigm for 48 h, followed by 400 μM H2O2 damage for 6 h. To verify that the protective effect of these LEDs was not transient, we added several detection points (3 h, 9 h, and 24 h) after the removal of H2O2. The cell activity of the 1900 K + H2O2 group was higher than that of the H2O2 group at four time points (Figure 2c–f). Interestingly, we observed no significant difference in cell morphology and apoptosis among the four groups at 0 h after the removal of H2O2 (see Supplementary Figure S2). We posit that 400 μM H2O2 damage for 6 h did not cause cell apoptosis but led to a decrease in cell activity. The 1900 K LEDs prevented the decrease in cell activity caused by H2O2. The negative manifestation of cells after a blow tends to emerge later. To investigate the protection range of LEDs at 10 W/m2 irradiance, we detected the cell state and apoptosis at 1000 μM H2O2 concentration in the light pretreatment paradigm. The number of cells in the 1900 K + H2O2 group was more than that in the H2O2 group. Furthermore, the connection between the cells in the H2O2 group almost disappeared. However, there were still some cell connections among the cells in the 1900 K + H2O2 group, and the percentage of cells with an increased refractive index around the cells was also lower than that in the H2O2 group. The flow cytometry results also confirmed this; the apoptosis rate of the 1900 K + H2O2 group was significantly lower than that of the H2O2 group (Figure 2g–i). In fact, we extended the time of H2O2 injury to 24 h, and 10 W/m2 LED illumination for 48 h also produced a protective effect on the cells (see Supplementary Figure S3). In conclusion, preliminary experiments suggest that the 1900 K LEDs likely had cytoprotective effects. Before us, there were also many experiments in which red lasers, LEDs, or even compound LEDs were used to protect the retinas of animals or volunteers [17,22,23,24,25,26,27]. Some studies suggested that the sequence of light treatments would affect treatment outcomes. Albarracin et al. [ 25] found that 670 nm LED light treatment before and during exposure to damaging white light significantly ameliorated the glare-induced reduction in photoreceptor function. However, photoreceptor function in animals treated with light following intense light-induced injury initially decreased but recovered 1 month after exposure. The above results suggest that phototherapy pretreatment and period treatments may have earlier or greater protective effects, partially consistent with our results. Regarding the different phenomenon in the 1900 K + H2O2 and H2O2 + 1900 K paradigms, our explanation is as follows: compared with other color temperature LEDs, the 1900 K LEDs were able to increase the cell activity of ARPE-19 cells. The interpretation of cell activity results usually requires two aspects; one is cell proliferation, and the other is the alteration of intracellular mitochondrial dehydrogenase activity. We cannot deny that 1900 K LEDs could promote ARPE-19 cell proliferation to a certain extent (see Supplementary Figure S4). We also proved that 1900 K LEDs could increase intracellular activities. The 4000 K and blue-light LEDs elevated intracellular ROS levels, while the 1900 K LEDs reduced them. In addition, mitochondrial imaging and DNA damage experiments showed that 1900 K LEDs could reduce the damage to mitochondria caused by H2O2. Coupled with the above results and the intracellular protein expressions of nuclear factor E2-related factor 2 (NRF2), heme oxygenase-1 (HO-1), microtubule-associated protein 1 light chain 3 beta (LC-3B), dynamin-related protein 1 (DRP1), and optic atrophy protein 1 (OPA1), we assume that pre-irradiation with 1900 K LEDs not only promoted ARPE-19 cell proliferation but also reduced the damage caused by H2O2, which led to the obvious increase in cell activity in the 1900 K group. However, if the cells are first damaged with H2O2, many protective effects may not work under severe trauma [28]. The 1900 K LEDs can also be used for illumination, while most light sources used for treatment in other studies cannot be used for illumination. We assume that 1900 K LEDs play a role in preventing AMD while simultaneously providing illumination, which can greatly improve patient compliance and, most importantly, reduce the cost of treatment. ## 2.3. The 1900 K LEDs Play an Active Role in Antioxidative Stress of ARPE-19 Cells Considering the preliminary proof that 1900 K LED pretreatment could protect ARPE-19 cells, we wanted to explore the possible mechanism. First, we focused on antioxidative stress. We found that red intranuclear fluorescence representing intracellular ROS level increased as the color temperature of LEDs increased (Figure 3a). However, the ROS level of the 1900 K group was much lower than that of the control (Figure 3b,c). We then repeated this experiment in the light pretreatment paradigm. As expected, the ROS level of the 1900 K group was still lower than that of the control, while the situation in the H2O2 group was the opposite. The ROS level of the 1900 K + H2O2 group was between that of the H2O2 group and the 1900 K group (Figure 3d,e). This result is not surprising. Shen et al. [ 17] also found that 670 nm LEDs could reduce the level of ROS in the mitochondria and enhance mitochondrial function in rat primary Müller cells. In the light pretreatment paradigm, we found that NRF2 in the H2O2 group was upregulated, and HO-1 also showed an upregulation trend. NRF2 in the 1900 K group also increased slightly. Interestingly, HO-1 protein decreased in the 1900 K group. The expression of HO-1 in the 1900 K + H2O2 group was lower than that in the H2O2 group. However, the expression of NRF2 was similar to that in the control group (Figure 3f,g). NRF2 is the upstream protein of HO-1. As an inducible enzyme, HO-1 is a measurable indicator of oxidative stress and is upregulated with NRF2 protein [29]. Núñez-Álvarez et al. [ 30] also demonstrated that red light (625–635 nm) at 6.5 W/m2 could reduce the HO-1 caused by blue light. A recent study showed that direct knockdown or pharmacological inhibition of HO-1 significantly blocked oxidative stress-induced ferroptosis in RPE cells [31]. Electrophile reagents and ROS disrupt the interaction between CncC and Keap1 after stress exposure. CncC is not degraded but accumulates in the nucleus, forms heterodimers with Maf-S, binds to AREs, and activates target gene transcription [32,33]. Therefore, after H2O2 injury, NRF2 enters the nucleus and binds to AREs to activate the transcription of target genes, resulting in the upregulation of HO-1. In contrast, 1900 K LEDs can upregulate the expression of NRF2. However, the relatively low intracellular ROS level does not allow NRF2 and Keap1 to disengage into the nucleus to activate downstream genes. It is only during stress that upregulated NRF2 enters the nucleus and increases the cell’s ability to resist oxidative stress. Our ROS results also prove this point. Our experiments preliminarily show that the 1900 K LEDs play a protective role by increasing the nonenzymatic antioxidant system, not the enzymatic one. Considering the effect of 1900 K LEDs on the mitochondria, we suspected the most likely candidate was a coenzyme or glutathione. In addition, oxidative stress can cause an increase in stress-induced autophagy in cells. Therefore, we detected the expression of autophagy-related protein LC3B and found that 400 μM H2O2 could increase the ratio of LC3B-II/LC3B-I, thereby increasing autophagy in ARPE-19 cells. The ratio of LC3B-II/LC3B-I in the 1900 K group was not different from that in the dark group. The autophagy level in the 1900 K+ H2O2 group was much lower than that in the H2O2 group (Figure 3h). A previous study used the same H2O2 concentration of 400 μM and found that the ratio of LC3B-II/LC3B-I in RPE cells was upregulated after H2O2 exposure for 6 h compared with 0 h [34]. The study of Hu et al. also supports our results [35]. Altogether, this suggests that 1900 K LEDs can reduce the level of ROS to protect RPE from death. ## 2.4. The 1900 K LEDs Can Reduce Mitochondrial Damage Caused by H2O2 in ARPE-19 Cells Mitochondrial dysfunction is implicated in the pathophysiology of several age-related diseases, including AMD. Mitochondrial fission, fusion, and mitophagy are important components of mitochondrial quality control [36]. Therefore, the modulation of mitochondrial dynamics may be a valuable strategy for treating retinal degenerative diseases such as AMD. We previously proved that 1900 K LEDs can reduce the level of ROS in ARPE-19 cells and that mitochondria represent the main target of ROS. Therefore, we shifted the spotlight toward the effects of the 1900 K LEDs on mitochondrial function. First, we performed mitochondrial imaging, adopting the experimental parameters from the study of Jang et al. [ 37]. They used 0.5 mM H2O2 to act on ARPE-19 cells for 1 h and observed that mitochondrial fission increased, whereas PARP-1 inhibitors could reduce the degree of fission in ARPE-19 cells. Fluorescence images showed that the mitochondria in the dark group and 1900 K group were linear and reticular in shape. Mitochondria in the shape of short rods, dots, or spheres could be observed after 400 μM H2O2 injury, which could be rescued by 1900 K LEDs (Figure 4a). Then, we quantified the morphology of the mitochondria. We found that H2O2 at the present experimental concentration caused the long, branching mitochondria to be broken into different parts, resulting in an increase in the number of mitochondrial networks but a decrease in the network size (number of branches). This led to an increase in the number of individual mitochondria, as well as a reduction in branch length. A similar phenomenon was observed in [38,39,40]. The 1900 K LEDs could mitigate this phenomenon. However, it is interesting that the 1900 K LEDs also increased mitochondrial fragmentation (Figure 4b–e). Combined with the previous results on autophagy, we do not believe that the 1900 K LEDs caused a negative increase in mitochondrial fragmentation because the 1900 K LEDs did not cause an increase in cellular autophagy but rather accelerated the fusion cleavage cycle due to the increase in mitochondrial exchange. In vitro studies have shown that H2O2-induced oxidative stress leads to RPE cell death by causing preferential damage to their mitochondrial DNA [41,42]. Moreover, mitochondrial DNA damage is more extensive and longer-lasting than nuclear DNA damage in human cells after oxidative stress [43]. Therefore, we can determine the degree of oxidative stress by detecting mitochondrial DNA damage. Our results show that mitochondrial DNA in ARPE-19 cells was damaged after 400 μM H2O2 injury for 6 h. Irradiation with 1900 K LEDs did not cause mitochondrial DNA damage in cells but reduced the mitochondrial DNA damage caused by H2O2 (Figure 4f,g). Combined with the results on ROS levels, it is not difficult to conclude that 1900 K LEDs protect the mitochondrial DNA from damage by reducing intracellular ROS. Indeed, the mitochondrial genome is susceptible to oxidative stress damage, and defects in the mitochondrial DNA repair pathway are important factors in the pathogenesis of retinal degeneration. The use of therapeutic modalities that specifically target the mitochondria to protect them from oxidative stress or promote mtDNA repair may provide a potential alternative for treating retinal degenerative diseases such as AMD [44]. PBM has been shown to enhance mitochondrial activity and restore the function of damaged mitochondria, thus promoting cell survival in vitro by stimulating the activity of cytochrome c oxidase [45]. Gopalakrishnan et al. [ 46] showed that far-infrared PBM improved functional and structural outcomes in animal models of retinal damage and degenerative diseases. A short near-infrared PBM process would preserve mitochondrial metabolic status and reduce photoreceptor loss. Recently, 670 nm LEDs have been used in clinical trials for treating macular edema in humans. The 670 nm LEDs could not only enhance the mitochondrial membrane potential of rodent photoreceptors but also protect Müller cells and photoreceptors from damage in vivo. Moreover, in vitro experiments demonstrated that 670 nm LEDs could enhance mitochondrial function and protect cultured Müller cells from oxidative stress [17]. According to mitochondrial morphology experiments, we detected the mitochondrial fission and fusion proteins. We found that the DRP1 protein was downregulated in the H2O2 group but upregulated in the 1900 K groups. The DPR1 level of the 1900 K + H2O2 group was between that of the H2O2 group and the 1900 K group (Figure 4h). For OPA1, an endomembrane fusion protein, the total protein levels of the four groups were not significantly different (Figure 4i). However, the ratio of L-OPA1/S-OPA1 in the H2O2 group showed a downward trend. The opposite was observed in the 1900 K group. Similar to DRP1, the ratio of L-OPA1/S-OPA1 in the 1900 K + H2O2 group was also between that in the H2O2 and 1900 K groups (Figure 4j). Our previous hypothesis was that H2O2 would upregulate intracellular DRP1 levels, leading to mitochondrial fragmentation. However, the level of DRP1 did not increase after H2O2 treatment; thus, it cannot be excluded that DRP1 may still play a role in oxidation-induced mitochondrial fragmentation [40]. Interestingly, there was an increase in DRP1 in the 1900 K group. Sheng et al. also observed the upregulation of OPA1 and FIS1 in the zebrafish retina after resveratrol treatment [47]. FIS1 is also a mitochondrial fission protein. Under physiological conditions, mitochondrial fusion and fission occur in a dynamic balance, which is altered by external stimulation. The mitochondrial morphology in the 1900 K group was linear and reticular, as also seen in the control group, and the mitochondrial DNA was not damaged; thus, DRP1 levels in the 1900 K group were likely upregulated to balance mitochondrial fusion. The increase in the fusion split cycle would likely promote communication between mitochondria and increase mitochondrial function [48], consistent with the results of the previous mitochondrial morphology experiments. Several studies support our results regarding the OPA1 protein. Li et al. irradiated R28 cells with blue light for different times and found that the total protein level of OPA1 did not change at different time points (0–24 h) [49]. Garcia et al. also found that the overall expression of OPA1 was not altered by H2O2 treatment, but the L-OPA1 isoform in both H9c2 and 143B cell lines was degraded [40]. When the transmembrane potential of the inner mitochondrial membrane is intact, the L-OPA1 isoform is necessary for the process of mitochondrial inner membrane fusion. When the transmembrane potential is lost, L-OPA1 is cleaved by the stress-sensitive overlapping with the m-AAA protease 1 homolog (OMA1) metalloprotease into a short S-OPA1 isoform that cannot promote inner mitochondrial membrane fusion and may even participate in inner mitochondrial membrane fission, resulting in the collapse of the mitochondrial network into fragmented organelle populations [50,51,52]. This is an organismal protection mechanism. If a cell encounters stress above a critical threshold, severely damaged mitochondria can contaminate other mitochondria by rejoining the mitochondrial network before being eliminated by autophagy. The organism has to prevent this from happening. At this time, OMA1 is rapidly activated by a low membrane potential and low levels of adenosine triphosphate (ATP) to cleave L-OPA1. Even in the absence of L-OPA1 or with very low membrane potential, the outer membranes of these mitochondria can still fuse. However, the inner membranes do not, resulting in several inner membrane matrix compartments surrounded by a common outer membrane, akin to peas in a pod, waiting to be eliminated by autophagy [53]. Wang et al. observed a similar phenomenon [39]. Accordingly, we believe that 1900 K LEDs may protect the mitochondria by reducing the stress caused by H2O2, thereby reducing OMA1 activation and L-OPA1 cleavage. The above explanation requires further research to confirm the regulatory effects of protective factors on OPA1 and DRP1. ## 2.5. Irradiation with 1900 K LEDs Did Not Cause Retinal Damage in Zebrafish Zebrafish show great similarities with humans in terms of eye shape, anatomy, gene expression, and function, and they have the advantages of rapid development, in vitro fertilization, transparent embryos, and easy observation. Therefore, they play an important role in research on eye development and diseases [54,55]. In addition, zebrafish have no eyelids; hence, experiment failure caused by eyelids blocking the light can be avoided. We analyzed the changes in the zebrafish retina after exposure to the 1900 K and blue-light LEDs. Compared with the control group, the thickness of the outer nuclear layer (ONL), photoreceptor layer (PRL), and RPE was significantly decreased in the blue light group on day 7, whereas the thickness of ONL, PRL, and RPE in the 1900 K LED light group was not significantly altered (Figure 5). This in vivo experiment preliminarily proves the safety of 1900 K LEDs in the fundus of zebrafish. In recent years, PBM has been recognized as an emerging therapy for treating age-related degenerative and mitochondrial-related diseases [56,57,58]. The main mechanism may be the promotion of cytochrome c oxidase (COX) activity and ATP content. PBM can also promote the release of nitric oxide (NO) from intracellular storage areas (e.g., heme-containing proteins) to enhance its bioavailability, triggering the activation of subsequent protective signaling pathways [57]. Although the light used in PBM previously had to be coherent and polarized, e.g., the light produced by He–Ne lasers, these properties are no longer considered essential. LED arrays can also be used as light sources in photomedicine [59], whereby monochromatic and multi-wavelength LEDs affect different cellular targets with potentially additional benefits [26,27]. The advantages and disadvantages of PBM with laser or LEDs as the radiation source remain controversial. Lasers are coherent, the scattering, absorption, and filtering due to the eye structure are reduced, and the area and dose of treatment can be controlled more precisely. LEDs are safer, less costly, and more readily available, making them a new therapeutic light source with more potential than lasers. However, establishing treatment parameters is more problematic in PBMs using LEDs as radiation sources. There are still many problems with LED-mediated PBMs. Our results further broaden the range of LEDs that can produce cytoprotective effects, and they demonstrate that light sources of PBM are no longer limited to monochromatic LEDs but can also include composite LEDs with illumination functions. In addition, most research on PBM involved basic phenotypic studies. A recent study found that a 632.8 nm red laser reduced the amyloid β protein (Aβ) deposits in Alzheimer’s disease models by activating the PKA/Sirtuin 1 (SIRT1) signaling pathway [60]. This gives us great inspiration; many studies have proven the effectiveness of PBM. Nevertheless, research on the physiological mechanism has been limited; therefore, it will be necessary to explore the signaling pathways in PBM in the future. Accordingly, we examined the effect of the 1900 K LEDs on SIRT1 expression, finding that H2O2 could upregulate the expression of SIRT1 and that the 1900 K LEDs increased the amount of SIRT1 more than the H2O2 group (see Supplementary Figure S5). We also found the increased expression of other members of the SIRT family, such as Sirtuin 3 and Sirtuin 5, after the 1900 K LED treatment (Xu Zhang, unpublished data). We hypothesize that the LEDs might bring some positive effects to the cells by upregulating the sirtuin family. This mechanism is worthy of in-depth studies in the future. As a limitation of this study, we only preliminarily discussed the protective effects of the 1900 K LEDs on RPE cells and zebrafish; further in vivo experiments and related specific mechanisms are lacking. Our study demonstrated that pretreatment with the 1900 K LEDs could counteract H2O2 damage to RPE cells by reducing the generation of oxidative stress and mitochondrial damage in ARPE-19 cells (Figure 6). The 1900 K LEDs may need to be in a certain range of irradiance for optimal protection, which is likely cumulative. In addition, irradiation with the 1900 K LEDs for 7 days did not cause retinal damage in zebrafish. Our research is very meaningful because protecting cells from death is a definite and effective measure in the absence of allopathic treatment. This is the first study to investigate the protective effects of 1900 K low-color-temperature phosphor-free LEDs on RPE and zebrafish. The noninvasiveness, good compliance, convenience, and availability of light therapy using the 1900 K LEDs would make it the most promising emerging tool for preventing and treating AMD. Moreover, light therapy can also provide inspiration for the management of other similar diseases, which is of great benefit to human beings. ## 3.1. Cell Culture We purchased the ARPE-19 cells from the American Type Culture Collection (ATCC, Manassas, Virginia). The cells were cultured in Dulbecco’s modified *Eagle medium* (DMEM/F-12, BI, Israel) supplemented with $10\%$ (v/v) fetal bovine serum (FBS, BI, Israel), 100 U/mL penicillin, and 100 μg/mL streptomycin (Solarbio, Beijing, China) in a cell incubator at 37 °C with $5\%$ CO2. Cell passages were performed every 4 to 5 days. We used ARPE-19 cells from passages 3–10 in our experiments. ## 3.2. Animals All wild-type zebrafish (Danio rerio) of the AB strain were obtained from the China Zebrafish Resource Center, CZRC (Wuhan, China). Zebrafish were maintained in 14 h light/10 h dark cycles at 28.5 °C. The use and manipulation of zebrafish were approved by the ethical review committee, and the study adhered to the ARVO Statement for the Use of Animals in Ophthalmic and Vision Research. ## 3.3. Light Treatment and H2O2 Damage This study mainly used the following LEDs: 1900 K, 4000 K, 6600 K, and blue-light LEDs. The light source and lighting device were the same as described in our previous article (Figure 7a,b) [10]. The entire light box was placed in a cell incubator to ensure normal cell growth. The top panel in Figure 7c shows the light post-treatment paradigm, which involves damaging the cells with 400 μM H2O2 for 6 h and then illuminating the cells using the 1900 K LEDs at 10 W/m2 irradiance for 48 h. The lower panel of Figure 7c shows the light pretreatment paradigm. The light pretreatment paradigm involved exposing the cells to the 1900 K LEDs at 10 W/m2 for 48 h and then damaging them using 400 μM H2O2 for 6 h. ## 3.4. Light Exposure in Animal Experiments Zebrafish were maintained in a transparent aquarium (10 cm × 10 cm × 10 cm), and each aquarium was placed in the center of a light box with reflective interior walls (12 cm × 12 cm × 12 cm). The LEDs were placed on the four side walls of the light box to improve the directional uniformity of the radiation. The light exposure was consistent with the circadian rhythm of zebrafish automatically, and the light intensity was 3000 lux. ## 3.5. Cell Activity Assay We measured the cell activity using the Cell Counting Kit-8 (CCK-8) (40203ES60, Yeasen, Shanghai, China) according to the reagent instructions. ARPE-19 cells were seeded into 96-well plates at a density of 3 × 103 cells per well and then incubated for 24 h. Subsequently, cells received the corresponding treatment. Next, the cells were cultured in a medium supplemented with $10\%$ (v/v) WST-8 for 2 h. The absorbance was measured by a microplate reader (Multiskan Mk3, Thermo Scientific, Shanghai, China). ## 3.6. Cell Death Assay After treatment, the cells were immediately observed under a microscope, and three random fields were recorded. Afterward, we detected apoptosis using an Annexin V–FITC/PI Apoptosis Detection Kit (40302ES50, Yeasen, Shanghai, China). The cells were digested with EDTA-free trypsin, collected, and centrifuged at 300× g at 4 °C for 5 min. After washing twice with PBS, the cells were resuspended in the buffer. Then, a staining solution was added to the cells before incubating them for 10–15 min in the dark at room temperature. After incubation, 1× Binding Buffer was added, and the results were detected using a flow cytometer (DxFLEX, Beckman, Suzhou, China). ## 3.7. ROS Levels Detection According to the instructions, we incubated cells with the DHE medium mixture diluted to 100 μM in the dark at 37 °C for 20 min. Then, we washed the cells with DHE staining solution and randomly photographed three fields of view. In addition, we used the same reagent to quantitatively analyze the level of intracellular ROS. After being stained with DHE, the cells were collected and washed twice, resuspended with PBS, and detected by flow cytometry (DxFLEX, Beckman, Suzhou, China). ## 3.8. Mitochondrial Imaging ARPE-19 cells were seeded into 35 mm confocal dishes at a density of 4 × 105 cells and incubated for 24 h until their confluence reached 50–$70\%$. Then, we transfected ARPE-19 cells using DsRed2-Mito plasmid (Wuhan Miaoling Biotechnology Co., Ltd. Wuhan, China) to label the mitochondria according to the instructions of the Hanheng LipoFiter3 Liposome Transfection Reagent (HB-TRLF3-1000, Hanheng, Shanghai, China). The DsRed2-Mito plasmid encodes a fusion of Discosoma sp. red fluorescent protein (DsRed2; 1, 2) and the mitochondrial targeting sequence from subunit VIII of human cytochrome c oxidase (Mito; 3, 4). Next, 36 h after transfection, cells were irradiated with the 1900 K LEDs for 48 h before adding 400 μM H2O2 for 3 h. The morphology of the mitochondria was observed under a Zeiss confocal microscope (LSM800, ZEISS, Göttingen, Germany), and multiple fields were randomly selected for photographing and recording. Then, we assessed the number and morphology of mitochondria using the Mitochondrial Network Analysis (MiNA) toolset. ## 3.9. Western Blotting According to the manufacturer’s instructions for the radioimmune precipitation assay buffer (RIPA) (Solarbio, Beijing, China) and bicinchoninic acid (BCA) protein assay kit (Solarbio, Beijing, China), we lysed ARPE-19 cells and detected the protein concentration. An equal amount of protein (25 μg) was separated by electrophoresis on $10\%$ or $12\%$ SDS polyacrylamide gels and transferred to polyvinylidene fluoride membranes (PVDF, Millipore, United Kingdom). Then, the membranes were blocked with $5\%$ nonfat milk for 1 h and incubated with the appropriate primary antibody (Table 1 and Table S1) overnight at 4 °C. On the next day, the membranes were washed and incubated with the secondary antibody at room temperature for 1 h. After washing the membrane, the target proteins were detected using the EasySee Western Blot Kit (TRANS, Beijing, China), and digital images were obtained. The bands were quantified by integrating the pixel intensity using ImageJ software. β-tubulin served as an internal control. ## 3.10. Detection of mtDNA Damage We referred to the method of Sheng et al. to detect mitochondrial DNA damage [47]. After the cells were processed, we extracted the total cell DNA and amplified the long and short mitochondrial fragments from 15 ng of total DNA following the steps of the Ezup Column Animal Genomic DNA Extraction Kit (Sangon Biotech, Shanghai, China) and the Long Amplification Taq polymerase kit (P101-d1, Vazyme, Nanjing, China). The primers of the long mitochondrial fragment (16568 bp) were F: ATGATGTCTGTGTGGAAAGTGGCTGTGC and R: GGGAGAAGCCCCGGCAGGTTTGAAGC. The primers of the short mitochondrial fragment (158 bp) were F: GATTTGGGTACCACCCAAGTATTG and R: AATATTCATGGTGGCTGGCAGTA. The PCR amplification conditions for the long mitochondrial fragments were as follows: 95 °C for 5 min, followed by 17 cycles (95 °C for 30 s; 65 °C for 15 min), with a final extension step at 72 °C for 10 min. The PCR amplification conditions for the short mitochondrial fragments were as follows: 95 °C for 5 min, followed by 17 cycles (95 °C for 30 s; 60 °C for 30 s; 72 °C for 30 s), with a final extension step at 72 °C for 10 min. All long- and short-chain PCR reactions were stopped at the linear phase. The PCR products were then separated by $0.8\%$ and $1\%$ agarose gel electrophoresis. Lastly, the gels were visualized under UV irradiation in Image Lab 5.2.1 (SYSTEM GelDoc XR+ IMAGELAB, Bio-Rad, Hercules, CA, USA), and the bands were quantified by ImageJ. ## 3.11. Hematoxylin and Eosin Staining and Histologic Evaluation The specific steps were the same as described in our previous article [61]. Briefly, eyeballs from zebrafish were dehydrated in a stepwise manner after internal and external fixation. Then, eyeballs were processed with xylene and embedded in paraffin. Next, the embedded eyes were cut into 4 μm thick sections before performing H&E staining. 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--- title: Preventing Disused Bone Loss through Inhibition of Advanced Glycation End Products authors: - Cong-Jin Liu - Xiao Yang - Shou-Hui Wang - Xin-Tong Wu - Yan Mao - Jing-Wen Shi - Yu-Bo Fan - Lian-Wen Sun journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003672 doi: 10.3390/ijms24054953 license: CC BY 4.0 --- # Preventing Disused Bone Loss through Inhibition of Advanced Glycation End Products ## Abstract Bone loss occurs in astronauts during long-term space flight, but the mechanisms are still unclear. We previously showed that advanced glycation end products (AGEs) were involved in microgravity-induced osteoporosis. Here, we investigated the improvement effects of blocking AGEs formation on microgravity-induced bone loss by using the AGEs formation inhibitor, irbesartan. To achieve this objective, we used a tail-suspended (TS) rat model to simulate microgravity and treated the TS rats with 50 mg/kg/day irbesartan, as well as the fluorochrome biomarkers injected into rats to label dynamic bone formation. To assess the accumulation of AGEs, pentosidine (PEN), non-enzymatic cross-links (NE−xLR), and fluorescent AGEs (fAGEs) were identified in the bone; 8-hydroxydeoxyguanosine (8-OHdG) was analyzed for the reactive oxygen species (ROS) level in the bone. Meanwhile, bone mechanical properties, bone microstructure, and dynamic bone histomorphometry were tested for bone quality assessment, and Osterix and TRAP were immunofluorescences stained for the activities of osteoblastic and osteoclastic cells. Results showed AGEs increased significantly and 8-OHdG expression in bone showed an upward trend in TS rat hindlimbs. The bone quality (bone microstructure and mechanical properties) and bone formation process (dynamic bone formation and osteoblastic cells activities) were inhibited after tail-suspension, and showed a correlation with AGEs, suggesting the elevated AGEs contributed to the disused bone loss. After being treated with irbesartan, the increased AGEs and 8-OHdG expression were significantly inhibited, suggesting irbesartan may reduce ROS to inhibit dicarbonyl compounds, thus suppressing AGEs production after tail-suspension. The inhibition of AGEs can partially alter the bone remodeling process and improve bone quality. Both AGEs accumulation and bone alterations almost occurred in trabecular bone but not in cortical bone, suggesting AGEs effects on bone remodeling under microgravity are dependent on the biological milieu. ## 1. Introduction Significant losses of weight-bearing bones occur in astronauts during long-term space flight [1]. Specifically, about 1–$1.6\%$ of bone mineral in the spine, femur neck, trochanter, and pelvis can be lost per month; elevated calcium excretion also occurs in astronauts during spaceflight [2,3]. However, the prolonged microgravity-induced bone loss cannot be reversed for a long time after the flight and recovery times are much longer than even the duration of the mission [1,4,5]. Previous studies reported the countermeasures to prevent microgravity-induced bone loss such as physical exercise and drug supply only showed limited efficiency [6,7]. That is because the mechanism of microgravity-induced osteoporosis is still unclear. Recently, our study found non-enzymatic compounds called advanced glycation end products (AGEs) accumulated significantly in the bone matrix under simulated microgravity [8]. These non-enzymatic compounds are formed through the irreversible rearrangements of Amadori products which are formed via a series of reactions of reducing sugars (e.g., blood glucose or ribose) and amino groups in long-lived proteins (e.g., collagen), or through the condensation of amino groups and dicarbonyl compounds, which are derived from the autooxidation of sugars and Amadori products [9]. Indeed, the accumulation of AGEs has been found to be associated with an increased risk of fractures in individuals with age-related and diabetic osteoporosis [10,11,12,13,14,15,16]. AGEs were preserved in old trabeculae and altered the final architecture of trabecular bone and decreased bone toughness in age-related osteoporosis [15,17]. Moreso, they impaired bone microarchitecture, as well as bone mechanical properties, including toughness, energy absorption, yield strength, and failure load, further leading to bone fracture in diabetic osteoporosis [18,19,20,21]. Moreover, on cellular level, AGEs can interact with the receptor for AGEs (RAGE) to suppress osteoblast growth and differentiation and impair mineralization [22,23,24,25]. However, their modulation of osteoclast activity is controversial [26,27,28,29], and some researchers proposed it may be because AGEs had biphasic modulation during the different differentiation stages of osteoclasts [30]. Given the adverse impact of AGEs on bone, more and more studies focused on the use of AGEs inhibitors for improving bone quality and the bone remodeling process under pathological conditions. Previous studies have found that cleaving formed AGEs cross-linking structures can decrease bone fragility in vitro [31,32]. Moreover, blocking the interaction between AGEs with RAGE can rescue the negative effects of AGEs on osteogenic potential of adipose-derived stem cells (ASCs) and affect osteoblast differentiation/activity in an age-dependent manner [33,34]. However, directly blocking AGEs formation at the root can attenuate the deterioration of bone in more ways because it not only prevented the biomechanical degradation of bone and inhibited AGEs-induced damage on cell proliferation and osteogenic differentiation of osteoblasts in vitro, but also was applied on in vivo animal experiments to improve both trabecular microstructure and bone toughness of diabetic mice [35,36]. Therefore, we wish to know that under simulated microgravity, whether blocking AGEs formation can also prevent its accumulation to stop the occurrence of disused bone loss. Of all the inhibitors that prevent the formation of AGEs, Angiotensin II receptor blockers (ARBs) are unique in that they do not trap dicarbonyl precursors for AGEs formation. Instead, they directly inhibit the formation of reactive oxygen species such as carbon-centered and hydroxyl radicals, which in turn suppresses the auto-oxidation of sugars into dicarbonyl precursors. As a result, ARBs are considered more effective than other inhibitors [37]. Irbesartan, as one of the ARBs, was commonly used to lower blood pressure [38]. However, more recently, it has been found in vivo to exhibit therapeutic effects on bone microarchitecture and biomechanical properties in diabetic mice (e.g., ultimate tensile strength, max load, fracture load, and energy absorption) [36]. In order to investigate the issue we mentioned above, we treated tail-suspended rats with irbesartan for 3 weeks at a concentration of 50 mg/kg/day in this study. Three methods were used to evaluate AGEs accumulation in bone matrix. Meanwhile, bone microstructure parameters, bone micromechanical properties, dynamic bone formation, and the activities of osteoblastic and osteoclastic cells were detected. Their relationships with the content of AGEs were analyzed as well. The objectives of this study were [1] to provide detailed information on the relationship between disused bone loss and AGEs, and [2] to determine the effects of irbesartan on matrix AGEs accumulation in bone under simulated microgravity and whether blockage of AGEs formation can alleviate the microgravity-induced bone loss. ## 2.1. Irbesartan Inhibited AGEs Accumulation in Bone Matrix after Tail Suspension Here, we first analyzed PEN content, a standard biomarker for AGEs in bone tissue [38], in different types of bone in rat hindlimb quantitatively. The HPLC results showed that PEN content of cancellous bone obviously increased (Figure 1A, $p \leq 0.05$) after tail suspension, but significantly decreased with irbesartan treatment (TS + Irbe) compared to the TS group ($p \leq 0.05$). However, that of cortical bone showed no significant difference in TS and TS + Irbe group compared to the CON group (Figure 1B). Further at the micro level in the bone matrix, we analyzed NE−xLR by FTIR and fAGEs content by fluorescence microscopy, respectively. The results showed that in cancellous bone NE−xLR (Figure 1C) and fAGEs (Figure 1F) increased significantly ($p \leq 0.05$) in the TS group, but fAGEs decreased significantly with irbesartan treatment in the TS + Irbe group ($p \leq 0.05$). In cortical bone (Figure 1D,G), NE−xLR had no significant difference in the TS and TS + Irbe groups compared to the CON group, whereas fAGEs decreased significantly in the TS + Irbe group compared to the TS group ($p \leq 0.05$). These results indicated that AGEs accumulation in the bone matrix, especially in trabecular bone after tail suspension, was inhibited with irbesartan treatment. ## 2.2. Irbesartan Can Inhibit Reactive Oxygen Species in Bone Matrix after Tail Suspension Because Irbesartan was found to suppress reactive oxygen species (ROS) to inhibit the generation of dicarbonyl compounds, thus suppressing AGEs production [37], here we detected 8-hydroxydeoxyguanosine (8-OHdG), which is a kind of ROS marker, by immunofluorescence staining. The results showed (Figure 2) that 8-OHdG in the bone matrix showed an upward trend in the TS group compared to the CON group, whereas it decreased significantly with the drug treatment in the TS + Irbe group, compared to the TS group ($p \leq 0.05$). These results suggested that irbesartan may suppress reactive oxygen species to inhibit dicarbonyl compounds generation, thus inhibiting the production of AGEs in the bone matrix after tail suspension. ## 2.3. Inhibition of AGEs Partially Improved Bone Microstructure after Tail Suspension The bone microstructure parameters measured by Micro-CT are shown in Figure 3. The results showed that the BMD of cortical (Figure 3B) and cancellous bone (Figure 3C), the trabecular Tb. Th (Figure 3D), Tb. N (Figure 3E), BS/TV (Figure 3F), and BV/TV (Figure 3G) decreased significantly after tail suspension ($p \leq 0.05$), whereas a upward trend with the drug treatment in TS + Irbe group was observed; the trabecular Tb. Sp (Figure 3H), BS/BV (Figure 3I), and SMI (Figure 3J) increased significantly in the TS group compared to the CON group ($p \leq 0.05$), whereas a downward trend in TS + Irbe group compared to TS group was observed. These results suggested that bone microstructure of tail-suspended rats was partially improved with irbesartan treatment. ## 2.4. PEN Content Was Related to Bone Microstructure of Cancellous Bone Further, we analyzed the correlation between bone microstructure parameters and the content of PEN at the corresponding location of micro-CT detection in the right distal femur. The results (Table 1) showed PEN of cancellous bone was negatively correlated with trabecular BMD (R = −0.485, $$p \leq 0.041$$), Tb. N (R = −0.519, $$p \leq 0.028$$), and BS/TV (R = −0.609, $$p \leq 0.009$$), and positively correlated with SMI ($R = 0.505$, $$p \leq 0.032$$), whereas it had negative trend of correlation with BV/TV (R = −0.482, $$p \leq 0.05$$) and had no correlation with Tb. Th, Tb. Sp, and BS/BV. However, PEN of cortical bone had no relationship with cortical BMD (R = −0.114, $$p \leq 0.6232$$). ## 2.5. Inhibition of AGEs Improved Bone Micromechanical Properties after Tail Suspension The bone micromechanical properties detected by nanoindentation are shown in Figure 4. The results showed that the hardness (Figure 4A) and elasticity modulus (Figure 4B) of the cancellous bone were obviously higher ($p \leq 0.05$), whereas both of them decreased significantly in TS + Irbe group compared to TS group ($p \leq 0.05$). However, the hardness (Figure 4C) and elasticity modulus (Figure 4D) of cortical bone showed no significant difference in TS and TS + Irbe groups compared to the CON group. The results suggested that bone micromechanical properties of tail-suspended rats were significantly improved with irbesartan treatment. ## 2.6. NE−xLR Was Related to Bone Micromechanical Properties in Cancellous Bone Because bone micromechanical properties were proved to be directly influenced by the crosslinking structures of AGEs [39], in the present paper we investigated the relationship between non-enzymatic cross-links (NE−xLR) and bone micromechanical properties under tail suspension and irbesartan treatment via combining FTIR and nanoindentation at the same detection location. The results (Table 2) showed that NE−xLR in cancellous bone was positively correlated with hardness ($R = 0.686$, $p \leq 0.0001$) and elastic modulus ($R = 0.547$, $$p \leq 0.0031$$), whereas NE−xLR in cortical bone had no correlation with both hardness and elastic modulus. ## 2.7. Inhibition of AGEs Partially Improved Bone Metabolism after Tail Suspension Dynamic parameters of bone formation were assessed following in vivo calcein and xylenol orange staining. The results showed (Figure 5A–E) that mineral apposition rate (MAR) both at growth plate and trabecula bone decreased significantly in the TS group, as well as bone formation rate (BFR) at trabecular bone in the TS group compared to the CON group. All parameters showed an upward trend in the TS + Irbe group compared to the TS group. The activities of osteoblastic and osteoclastic cells were detected by immunofluorescence staining with Osterix and TRAP. Osterix staining results showed that Osterix (+) cells in growth plate and trabecular bone (Figure 5G,H) decreased significantly ($p \leq 0.05$) in the TS group compared to the CON group, whereas in trabecular bone they increased significantly in the TS + Irbe group compared to the TS group. However, Osterix (+) cells in cortical bone had no significant difference in the TS and TS + Irbe group compared to the CON group (Figure 5I). TRAP staining results showed (Figure 5J–M) that TRAP (+) cells in growth plate, trabecular bone, and cortical bone had no significant difference in the TS group compared to the CON group, whereas in trabecular bone and cortical bone they decreased significantly in the TS + Irbe group compared to the TS group ($p \leq 0.05$). These results suggested that irbesartan increased osteoblastic cells activities but decreased osteoclastogenesis to partially improve bone metabolism in tail-suspended rats. ## 2.8. Fluorescent AGEs in Bone Matrix Was Related to Bone Metabolism Biomarkers Furthermore, we investigated the relationship between fAGEs and Osterix/TRAP (+) cells under tail suspension and irbesartan treatment. The results (Table 3) showed that fAGEs in cancellous bone were negatively correlated with Osterix (+) cells (R = −0.661, $$p \leq 0.005$$), whereas no correlation with TRAP (+) cells was observed. Moreover, fAGEs in cortical bone were positively associated with TRAP (+) cells ($R = 0.554$, $$p \leq 0.026$$), whereas no correlation with Osterix (+) cells was observed. ## 3. Discussion In this study, we mainly investigated the improvement effects of blocking AGEs formation on bone microstructure, bone micromechanical properties, and bone remodeling process of tail-suspended rats through the use of irbesartan, which is a kind of AGEs formation inhibitor. Our study showed that firstly, AGEs accumulated in the cancellous bone matrix and were involved in the deterioration of bone microstructure, bone micromechanical properties, and bone remodeling process under simulated microgravity, and secondly, that blocking AGEs formation by irbesartan can partially prevent the aforementioned disused bone loss. First of all, we demonstrated the simulated microgravity effect had a negative impact on bone at multi-levels. The micro-CT results showed the notable deterioration of trabecular bone density and microstructure after tail suspension, as evidenced by decreased BMD, Tb. Th, Tb. N, BS/TV, and BV/TV, and increased BS/BV, Tb. Sp, and SMI (Figure 3C–G). Nanoindentation results revealed the hardness and elastic modulus of decalcified cancellous bone increased significantly after tail-suspension (Figure 4A,B), suggesting an abnormal increase in the stiffness and fragility of the organic phase (mainly collagen fiber) in the bone matrix. Moreover, the results of dynamic histomorphology revealed a reduction in dynamic bone formation, as indicated by lower values for MAR and BFR, in both the growth plate and trabecular bone following tail suspension (Figure 5A–E), which were consistent with the findings of Macias and Tian et al. [ 40,41]. As for the bone cells activities, Osterix as the transcription fact for osteoblasts differentiation in both growth plate and trabecular bone significantly increased (Figure 5F–I), whereas the number of TRAP (+) cells in growth plate and trabecular bone only showed a downward trend after tail suspension (Figure 5J–M), revealing the lower MAR and BFR in tail-suspended rats may be due to the inhibited differentiation of osteoblastic cells but unrelated to osteoclastic cells. Although inconsistent with the results of ground-based animal studies, our results were consistent with the findings in Sprague–Dawley rat flight studies [42,43,44]. Moreover, we found only the BMD decreased, whereas the mechanical properties, MAR/BFR, and TRAP (+)/Osterix(+) cells in cortical bone had no significant changes under simulated microgravity. This indicated that cancellous bone is more susceptible to be affected by simulated microgravity than cortical bone. In order to investigate the essential factors of bone deterioration under simulated microgravity, we focused on the non-enzymatic glycation in the bone matrix and evaluated three kinds of matrix AGEs in bone from multi-points, including the overall content of PEN in bone, the 2D spatial distribution of crosslink AGEs (NE−xLR), and fluorescent AGEs (fAGEs). These global and microscopic measurements for AGEs not only provided detailed information on the changes in AGEs, but also help to further establish their connections with alterations of bone at different levels. The results found PEN (Figure 1A,B), NE−xLR (Figure 1C,D), and fAGEs (Figure 1E–G) all increased in cancellous bone but not in cortical bone after tail suspension, revealing the significant AGEs accumulation under simulated microgravity, which may be caused by the elevated serum glucose [8]. Meanwhile, the AGEs accumulation is more preferred to occur in cancellous bone first. This phenomenon is similar to bone deterioration under simulated microgravity, which occurred in cancellous bone prior to cortical bone. The reason may be that cancellous bone has a higher surface area per unit volume and a greater rate of metabolic activity compared to cortical bone, so the sugars in cancellous bone may be more easily accessible to matrix proteins and more likely to form AGEs [45,46]. Therefore, we then try to demonstrate that the elevated matrix AGEs played an essential role in the deterioration of bone under simulated microgravity. PEN was an accessible surrogate marker of AGEs in bone [38], and in this study, it was detected at the same anatomical locations with the bone microstructure parameters. Therefore, we analyzed the correlation between PEN and bone microstructure. The results found that accumulated PEN in the trabecular bone matrix is associated with less trabecular BMD, as well as sparser and more rod-like trabecular architecture, independently of cortical BMD (Table 1). These results suggested that the accumulated matrix AGEs can deteriorate the microstructure of the trabecular bone under simulated microgravity, which was similar to the findings in the study on diabetic osteoporosis [21]. Because the crosslinking AGEs formed on collagen can directly stiffen the collagen to reduce bone toughness [15], the elevated NE−xLR (the crosslinking structure AGEs) under simulated microgravity may be the reason for the alteration of bone mechanical properties. Thus, we analyzed the relationship between NE−xLR and the mechanical properties of the decalcified bone matrix via colocalizing the detection sites of FTIR and nanoindentation. According to the results, NE−xLR in cancellous bone but not in cortical bone was found to have a positive correlation with both hardness and elastic modulus (Table 2). Previously studies have not directly investigated AGEs effects on the stiffness of decalcified bone in vivo. It was only found that in vitro, the increased stiffness of decalcified human tibiae bone was related to the accumulation of bone matrix AGEs after incubating with ribose [47], and the nano-scale elastic modulus of cartilage matrix also increased significantly after L-threose treatment [48], suggesting in vitro glycation can stiffen the bone matrix to some extent. From our results, it was demonstrated that the accumulated in vivo matrix AGEs are the vital cause of the pathological stiffening of the cancellous bone matrix under simulated microgravity. Furthermore, fAGEs can evaluate most kinds of AGEs in bone [28,49], and their microscopic distributions were observed in which Osterix/TRAP (+) cell activities were detected in our study. Hence, we analyzed the correlation between fAGEs and bone metabolism indicators. The results showed that fAGEs in cancellous bone were negatively related to Osterix (+) cells (Table 3), revealing matrix AGEs negatively impacted on the differentiation of osteoblasts under simulated microgravity. This is similar to our previous study, which found elevated matrix AGEs in vivo suppressed bone formation activities [50]. Besides, previous in vitro studies also reported AGEs can downregulate Osterix, osteocalcin (OCN), and collagen Ialpha1 (COL Iα1) expression to suppress osteoblast growth and differentiation [22,25,51]. Surprisingly, though both fAGEs and TRAP in cortical bone had no significant changes after tail suspension, the two showed a moderate correlation. Although previous studies were controversial about the role of AGEs in the modulation of osteoclast activity [40,41,42,43], our results were also not sufficient to determine the relationship between AGEs and osteoclast activity under simulated microgravity. This may be because of the sample size, and more samples may be needed in future. Above all, we can infer that the accumulated matrix AGEs in cancellous bone indeed contributed to worsening cancellous bone quality and the bone formation process under simulated microgravity; therefore, we applied irbesartan to inhibit AGEs accumulations in tail-suspended rats. Our results showed AGEs accumulation in cancellous bone in tail-suspended rats was inhibited by irbesartan treatment (Figure 1A–G). Simultaneously, 8-OHdG levels, a kind of ROS marker, in the bone matrix of tail-suspended rats were suppressed after irbesartan treatment (Figure 2A,B) as well. We inferred the reduced AGEs accumulation under simulated microgravity may be because irbesartan can decrease the ROS level in cancellous bone to suppress hydroxyl radical formation, further suppressing the autoxidation of sugars to dicarbonyl precursors of AGEs in order to block AGEs formation. Further, we found inhibition of AGEs by irbesartan treatment can improve bone quality under simulated microgravity. The BMD and microstructure of the bone were partially promoted (Figure 3A–J), and the hardness and elastic modulus of the cancellous bone matrix were reduced in tail-suspended rats (Figure 4A,B). Meanwhile, the number of Osterix (+) cells and MAR/BFR in cancellous bone in tail-suspended rats were promoted (Figure 5A–I). On one hand, these results indicated irbesartan can attenuate AGEs-induced damage in osteoblast differentiation at the cellular level to consequently affect dynamic bone formation. On the other hand, AGEs are directly formed on collagen and may disturb the normal post-translational modification process of collagen and the enzymatic cross-links formation, so that their accumulation may suppress mineral deposition [52]. Therefore, our study indicated the inhibition of AGEs formation may promote mineralization and bone formation through improving collagen structure at tissue level under simulated microgravity. However, more investigations are also needed for the direct effects of AGEs on mineralization in future. Unexpectedly, although we did not find the alteration of osteoclastic cell activities under simulated microgravity, we found irbesartan can significantly inhibit fAGEs and osteoclastogenesis in both trabecular and cortical bone after tail-suspension (Figure 5J–M). Previous studies found angiotensin II (AngII) can promote the expression of Receptor Activator of Nuclear Factor-κ B Ligand (RANKL) and vascular endothelial growth factor (VEGF) in osteoblast to promote osteoclast formation, and ARBs can suppress AngII production to inhibit osteoclastogenesis [53,54]. Hence, suppression of irbesartan, as a kind of ARBs, on osteoclast activity may not be through blocking AGEs formation but may be via inhibiting the formation of AngII under simulated microgravity, which needs to be further studied in the future. In summary, our study confirmed that AGEs preferred to accumulate in the cancellous bone matrix and can adversely affect bone tissue at multi-levels including impairing bone microstructure, bone micromechanical properties, and bone formation process under simulated microgravity. However, irbesartan can suppress AGEs formation in tail-suspended rats via reducing reactive oxygen species to reduce dicarbonyl compounds generation. The inhibition of AGEs then partially alleviated the deterioration of bone quality and bone remodeling process to prevent disused bone loss. The findings in this study may provide a new clue for exploring the mechanism of microgravity-induced osteoporosis and finding effective countermeasures. ## 4.1. Animal Care and Experimental Designs Eight-week-old female Sprague–Dawley rats weighing 200–230 g were obtained from the Vital River Laboratory Animal Technology Co. (Beijing, China). The housing unit of the animal facility was maintained at 25 ± 2 °C with a reversed $\frac{12}{12}$ h light–dark cycle. Each rat was fed separately in a tail box. The rats were given regular chow and water ad libitum. Twenty-four female Sprague–Dawley rats were randomly divided into three groups ($$n = 8$$, each group): the control group (CON), the tail suspension group (TS), and the tail suspension group treated with irbesartan (TS + Irbe). In TS and TS + Irbe groups, rats were elevated to produce a 30° head-down tilt for a duration of 21 days as mentioned in our work previously [55], which simulated the weightlessness of hindlimbs. In addition, rats in the TS + Irbe group were extra administered irbesartan at a concentration of 50 mg/kg/day. Calcein (5 mg/kg) and Xylenol orange (90 mg/kg) were administered 10 and 3 days prior to the end of the study to label actively forming bone surfaces. After that, the rats were sacrificed for subsequent detection. The unloaded hindlimbs of rats were our research objects. Firstly, the proximal femur has a femoral head allowing better separation of trabecular bone tissues, so that was chosen to detect AGEs content and bone indicators at the corresponding anatomical location. The left proximal femurs were used to successively detect the non-enzymatic cross-link (NE−xLR) by Fourier Transform infrared spectroscopy (FTIR), the fluorescent AGEs(fAGEs) by fluorescence microscopy, the bone micromechanical properties by nanoindentation, and the Osterix, TRAP and 8-OHdG expressions by immunofluorescent staining. The proximal ends of the right femurs were used to detect the pentosidine (PEN) content by High Performance Liquid Chromatography (HPLC). Then, the distal femur was found to have relatively rich trabeculae, so that its bone microstructure parameters had an overall representativeness. Thus, the distal femur was used to detect bone microstructure by micro-CT and the local PEN content at the same detected sites by HPLC. Finally, the left proximal tibiae were used to detect the mineral apposition rate (MAR)/bone formation rate (BFR) by dynamic histomorphometric analysis. Key experimental procedures are summarized in Figure 6, and the following are the details on the materials and methods used in this study. ## 4.2. Sample Preparation The proximal end of the left femur was fixed in $4\%$ paraformaldehyde for 48 h and decalcified in 0.5 M EDTA (pH 7.4) for 10d. Then, the decalcified bones were immersed in $20\%$ sucrose and $2\%$ polyvinylpyrrolidone (PVP) solution for 48 h to dehydrate. The tissues were finally embedded and cut into 10 μm thick or 50 μm thick longitudinal slices (coronal plane) by using a freezing microtome (Leica CM1950, Germany). The right femurs were stored at −80 °C. The proximal end of the left tibia was placed in a gradient of ethanol ($70\%$, $75\%$, $80\%$, $95\%$, and $100\%$) for dehydration and embedded in epoxy resin glue (A: $B = 2$:1) for 7 days, and then was cut into 50 μm thick longitudinal slices along a coronal plane by using a hard-tissue microtome (PRESI Mecatom T180, France). ## 4.3. Non-Enzymatic Cross-Links in Bone Matrix Determination by FTIR FTIR imaging and spectra collection of 10 μm thick femoral slices was carried out using a Fourier transform infrared spectrometer equipped with a microscope (Shimadzu AIM-9000, Kyoto, Japan). Several locations (i.e., 7–8 locations) in cancellous and cortical bone were randomly selected for the test. For every location, spectra were acquired at a 100 μm×100 μm pixel size and in the reflective mode over a spectral range of 500 to 3500 cm−1 wave numbers at a resolution of 2 cm−1 with 16 scans per pixel. Then, the spectra were extracted by the AIM solution software (Version 1.1.0.0, Shimadzu, Japan,) and smoothed by IR solution software (Version 2.20, Shimadzu, Japan) with 10 smoothing points. Because the amide I band possesses structural information about the collagen matrix, it was targeted (1600–1710 cm−1) as this band [56] and fit with seven Gaussian components set at 1610, 1630, 1645, 1661, 1678, 1692, and 1702 cm−1 by Origin software (Version 2018, Origin Pro2018, Originlab) as previously reported [57]. Among them, the 1678 cm−1 absorption is associated with the β-turn conformation of collagen, which is a binding residue required for cross-links between two collagen molecules [58], and the 1692 cm−1 serve as a measure of collagen content [56]. Thus, the 1678 cm−1-to 1692 cm−1 ratio [57] was calculated to obtain non-enzymatic cross-links (NE−xLR) in the bone matrix (Figure 1(Fi)). ## 4.4. Bone Micromechanical Properties Determination by Nanoindentation Following FTIR determination, five indentations were performed in the diaphragm at low/high NE−xLR locations relatively in cancellous and cortical bone in the same slices with FTIR, for one slice per rat. Two 2×2 matrices, respectively, for cancellous and cortical regions of each slice (a total of 384 indents among three groups) were randomly selected to perform nanoindentation using a nanoindentation tester (Nano Indenter G200, Agilent, Santa Clara, CA, USA) equipped with a Berkovich diamond tip. The tip was lowered with a loading rate of 10 nm/s to a maximum depth of 700 nm, held for 30 s, and subsequently unloaded. The resulting load-displacement curves were analyzed for hardness (Equation [1]) and elastic modulus (Equation [4]) using the Oliver–Pharr method [59]. [ 1]H=PmaxA [2]S=dPdh [3]Er=πS2A [4]1Er=1−v2E+1−vi2Ei where *Pmax is* the maximum load, A is the contact area, S is the slope of the 95–$40\%$ region of the unloading curve, *Er is* the equivalent elastic modulus, v is the Poisson’s ratio of bone (0.3) [60], Ei and vi are the elastic modulus and Poisson’s ratio of the diamond indenter (1140 GPa and 0.07, respectively). ( Figure 1(Fii)). ## 4.5. Fluorescent AGEs Observation by Autofluorescence Microscopy The spontaneous fluorescence intensity of 50 μm thick left femoral slices was examined using a fluorescence microscope (Olympus DP80, Shinjuku City, Japan) with an excitation filter of 365 ± 5 nm and a barrier filter of 400 nm ± 35 nm as before [28]. The mean fluorescence intensity in cancellous and cortical regions of bone was, respectively, quantified using Image J software (Version 1.8.0, National Institute of Health, Bethesda, MA, USA) (Figure 1(Fiii)). ## 4.6. Bone Metabolism Biomarkers Analysis by Immunofluorescence Staining Following the nano-indentation, immunofluorescence staining of 50 μm thick proximal femur slices was performed as previously described [61]. Briefly, after treatment with $0.3\%$ Triton (9002-93-1, Solarbio, Beijing, China) for 1.5 h, slices were blocked with $4\%$ *Bovine serum* albumin (BSA) at room temperature for 2 h and incubated overnight at 4 °C with primary antibodies: Osterix (ab209484, Abcam, Cambridge, UK, 1:400), TRAP (bs-16578R, Bioss, Beijing, China, 1:800), and 8-OHdG (sc-393871, Santa Cruz, CA, USA, 1:50). Then, secondary antibodies were incubated at room temperature for 2 h to visualize primary antibodies: Cy3-labeled Goat Anti-Rabbit IgG (A0516, Beyotime, Shangahi, China, 1:400) and Alexa Fluor 488-labeled Goat Anti-Rabbit IgG (A0423, Beyotime, China, 1:400). Finally, the slices were mounted with mounting media containing DAPI (36308ES20, Yeasen, Shangahi, China). A laser confocal microscope (CM1950, Leica, Wetzlar, Germany) was used for observation. Positive cells per unit area in the growth plate, and positive cells per unit length around trabeculae and cortical bone were calculated by Image J software (Figure 1(Fiv)). ## 4.7. Pentosidine (PEN) Content of Bone Determination by High Performance Liquid Chromatography (HPLC) The pentosidine, a standard biomarker for AGEs in bone tissue [38], at different anatomic locations in the bone matrix was measured by HPLC. First, the proximal and distal ends of the femur were cut into pieces, and the bone trabecula tissue and cortical bone tissue from the right proximal femur and the micro-CT detected sites in the right distal femur were selected with the attached bone marrow carefully removed. Then, bone tissues were hydrolyzed in a sealed centrifugal tube, containing 5 mL of 6 M HCl, at 110 °C for 24 h. After that, 10 μL of the hydrolysate was extracted for hydroxyproline detection using Hydroxyproline Assay Kit (MAK008, sigma, St. Louis, MO, USA). The remaining part was concentrated by using a centrifugal concentrator (LaboGene ScanVac Maxi Vac, Allerød, Denmark), with 1500 r/min at 60 °C for 20 h, resuspended with 100 μL of distilled water. The PEN content of these samples was quantified by a UHPLC system with a 2475 Multi λ fluorescence detector (ACQUITY Arc, Waters Corp, Milford, MA, USA), as previously described [62]. PEN was separated on Waters XSELECT HSS T3 column (4.6 × 100 mm, 2.5 μm) with a flow rate of 1 mL/min and a temperature of 40 °C, by using a gradient solution. Solvent A consisted $0.2\%$ of trifluoroacetic acid (TFA) in acetonitrile, and solvent B consisted $0.2\%$ of TFA in 18 Ω pure water. PEN was monitored for fluorescence at an emission of 378 nm and an excitation of 328 nm. The content of PEN was calculated based on a standard curve using standards (124505-89-7, Cayman, Ann Arbor, MI, USA) and normalized by the total amount of collagen (7.14 times hydroxyproline, pmol/mg) (Figure 1G). ## 4.8. Bone Microstructure Determination by Micro-CT Analysis Micro-CT (Skyscan 1272, Belgium) was used to scan the distal end of the right femur. The 180 degrees of total rotation scanning was conducted, with increment angle of 0.6 degrees and scanning accuracy of 12 μm. For analysis, a thickness of 1.812 mm was selected from both the cortical and trabecular regions of the distal femur, 1.812 mm distance away from the growth plate. Values for BMD were calculated, as well as microstructure parameters including trabecular thickness (Tb. Th, μm), trabecular number (Tb. N, 1/μm), percent bone volume (BV/TV, %), bone surface/tissue volume (BS/TV, 1/μm), trabecular separation (Tb. Sp, μm), specific surface (BS/BV, 1/μm), and Structure Model Index (SMI) (Figure 1(Hi)). ## 4.9. Dynamic Histomorphometric Analysis of Bone The slices of proximal tibia were imaged using a laser confocal microscope (Leica CM1950, Germany). The mineral apposition rate at regions of growth plate, trabeculae, and cortical endosteum (GMAR, TMAR, EMAR, μm/d, Equations [5]–[7], as well as bone formation rate at trabecular bone (BFR, μm/day, Equation [9]) were measured and calculated by Image J. [5]GMAR=Ir. L.Wi−Gt [6]GMAR=Ir. L.Wi−Gt [7]EMAR=Ir. L.Wi−Et [8]MS/BS=$\frac{1}{2}$sL.Pm+dL.PmTb. Pm [9]BFR=TMAR×MS/BS where t is the time interval of the labeling periods (7 days), Ir. L.Wi−G, Ir. L.Wi−T, and Ir. L.Wi−E are the distances of double label at growth plate, trabeculae and cortical endosteum respectively, sL.Pm and dL.Pm are the single and double labeled perimeter at trabeculae, respectively, and Tb. Pm is the trabecular perimeter (Figure 1I). ## 4.10. Statistical Analysis All data were analyzed using SPSS 19.0 software. The differences between groups were analyzed by a one-way ANOVA and followed by an LSD post hoc test. 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--- title: Brain-Derived Neurotrophic Factor Is Indispensable to Continence Recovery after a Dual Nerve and Muscle Childbirth Injury Model authors: - Brian M. Balog - Kangli Deng - Tessa Askew - Brett Hanzlicek - Mei Kuang - Margot S. Damaser journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003675 doi: 10.3390/ijms24054998 license: CC BY 4.0 --- # Brain-Derived Neurotrophic Factor Is Indispensable to Continence Recovery after a Dual Nerve and Muscle Childbirth Injury Model ## Abstract In women, stress urinary incontinence (SUI), leakage of urine from increased abdominal pressure, is correlated with pudendal nerve (PN) injury during childbirth. Expression of brain-derived neurotrophic factor (BDNF) is dysregulated in a dual nerve and muscle injury model of childbirth. We aimed to use tyrosine kinase B (TrkB), the receptor of BDNF, to bind free BDNF and inhibit spontaneous regeneration in a rat model of SUI. We hypothesized that BDNF is essential for functional recovery from the dual nerve and muscle injuries that can lead to SUI. Female Sprague–Dawley rats underwent PN crush (PNC) and vaginal distension (VD) and were implanted with osmotic pumps containing saline (Injury) or TrkB (Injury + TrkB). Sham Injury rats received sham PNC + VD. Six weeks after injury, animals underwent leak-point-pressure (LPP) testing with simultaneous external urethral sphincter (EUS) electromyography recording. The urethra was dissected for histology and immunofluorescence. LPP after injury and TrkB was significantly decreased compared to Injury rats. TrkB treatment inhibited reinnervation of neuromuscular junctions in the EUS and promoted atrophy of the EUS. These results demonstrate that BDNF is essential to neuroregeneration and reinnervation of the EUS. Treatments aimed at increasing BDNF periurethrally could promote neuroregeneration to treat SUI. ## 1. Introduction Stress urinary incontinence (SUI), the leakage of urine due to increased abdominal pressure, is common among elderly women and diminishes quality of life [1]. During vaginal delivery, the baby’s head can injure the maternal pudendal nerve (PN) and external urethral sphincter (EUS) while passing through the birth canal [2]. Up to $40\%$ of women suffer from post-partum SUI after pregnancy; these women are 2.4 times more likely to develop SUI later in life, suggesting a correlation between post-partum incontinence and SUI later in life [3]. An improved understanding of the pathophysiology could reveal targets for therapies. Rodent models of SUI have demonstrated that a combined pudendal nerve crush (PNC) and vaginal distension (VD) injury results in decreased leak-point pressure (LPP) and SUI, and doubles recovery time compared to either injury alone [4]. PNC + VD also delays PN motor-function recovery, even though VD does not impair PN function [4]. Pan et al. demonstrated that brain-derived neurotrophic factor (BDNF) is dysregulated after PNC + VD, suggesting that BDNF is important for regeneration of the pudendal nerve and re-establishment of continence [5]. Gill et al. showed accelerated regeneration and functional recovery after PNC + VD injury with BDNF treatment [6]. In addition, Yuan et al. demonstrated that BDNF is needed for promotion of regeneration with stem cell secretome treatment [7]. However, it is unknown if BDNF is necessary for spontaneous functional recovery after this dual nerve and muscle injury. Inhibiting the BDNF pathway in vivo is difficult, since BDNF knockouts are lethal [8]. Using a conditional BDNF knockout mice or heterozygous BDNF mouse models is not reliable, as a recent study has challenged the validity of mouse VD models [9]. A tyrosine kinase B (TrkB) fusion chimera (TrkB-Fc) has been previously shown to inhibit the BDNF regeneration pathway in spinal-cord-injury models at a dose of 12 μg per day [10,11]. Additionally, this TrkB-Fc has been shown to bind free BDNF and inhibit the BDNF pathway after PNC [12]. Using TrkB, the aim of this study was to test the hypothesis that BDNF is necessary for spontaneous functional recovery after the dual nerve and muscle injuries that can lead to SUI. ## 2.1. LPP and Electrophysiological Results LPP measured 6 weeks after the PNC + VD injury was not significantly different from that of sham-injured rats (Figure 1 and Figure 2). In contrast, LPP was significantly decreased 6 weeks after PNC +VD injury treated with TrkB compared to LPP after PNC + VD alone ($$p \leq 0.031$$), indicating that TrkB treatment inhibits recovery of LPP after PNC + VD. There were no significant differences in EUS EMG firing rate or amplitude between the Sham Injury group and either the PNC + VD Injury group or the Injury + TrkB group (Figure 3). Although EUS EMG frequency and amplitude in Injury + TrkB rats appeared to be less than those after PNC and VD injury, these differences were not statistically significant. ## 2.2. BDNF and NT4 Plasma Concentration BDNF plasma concentrations 6 weeks after PNC + VD were not significantly different between Injury and Injury + TrkB groups (Figure 4A). In contrast, NT4 plasma concentrations were significantly increased in the Injury + TrkB group compared to Injury alone 6 weeks after injury ($$p \leq 0.049$$; Figure 4B). ## 2.3. EUS Morphology and NMJs Staining EUS morphology of Sham Injured rats showed an intact EUS with little collagen infiltration, and the EUS had some collagen infiltration 6 weeks after injury (Figure 5). In contrast, 6 weeks after injury and TrkB, the EUS was not intact, and all rats demonstrated collagen infiltration between striated muscle fibers of the EUS (Figure 5). NMJ morphology showed that the Sham Injury group had intact NMJs innervated by a single axon, and 6 weeks after PNC + VD, the NMJs were intact, some of which were innervated by multiple axons. Six weeks after injury + TrkB, there were fewer innervated NMJs than after injury alone (Figure 5). ## 3. Discussion While most women recover continence one year after childbirth, many will have reoccurrence within five years [13,14]. Women who suffer from post-partum SUI are also 2.4 times more likely to develop SUI later in life [15], suggesting that tissue regeneration after the maternal injuries of childbirth is insufficient and can lead to later development of SUI [16,17]. Animal models of SUI have shown that BDNF expression is dysregulated in the EUS after PNC + VD injury [18]. The goal of this study was to test the hypothesis that BDNF is necessary for functional recovery after PNC + VD. We have previously demonstrated that TrkB-Fc treatment inhibits continence recovery after PNC, so this method of inhibiting BDNF was utilized in the current study at the same dose [12]. We demonstrated no significant differences in LPP and EUS EMG between the Sham Injury and Injury groups, showing that continence recovered within six weeks after PNC + VD, as has been demonstrated previously [4,19]. LPP was chosen as the primary outcome of the study, as it is a key indicator of SUI [20]. Additionally, the continence mechanism has been shown to have similar contributors (i.e., primarily EUS and urethral smooth muscle) in both humans and rats [21,22]. LPP was significantly decreased after injury and TrkB compared to injury alone, indicating that TrkB inhibited recovery and BDNF is necessary for spontaneous recovery of continence after injury. These results are consistent with previous studies that demonstrate that TrkB-Fc administration inhibits functional recovery from nerve injury [10]. Li et al. showed in a rat model of spinal-cord injury that TrkB treatment inhibited accelerated functional recovery via treadmill training, which is also thought to occur via a BDNF-mediated mechanism [10]. EUS EMG amplitude after injury and TrkB decreased compared to that of the Injury group and trended toward significance ($$p \leq 0.06$$), supporting the LPP outcomes. LPP was the primary outcome of the study, and a sample size analysis indicated that 13 animals per group would be needed to power the analysis. Secondary outcomes, such as EUS EMG, had higher standard errors, resulting in a lack of significant differences between groups. Additionally, the EUS is only one contributor of several to the continence mechanism, which could also explain why we did not see a significant difference in EUS results while seeing a significant difference in LPP [22]. In support of this idea, Dissaranan et al. found that after stem cell treatment, LPP was significantly increased compared to saline treated animals, while not demonstrating a significant increase in EUS EMG outcomes [23]. Likewise, Yuan et al. found that reducing BDNF in stem cell secretome treatment reduced LPP recovery after PNC + VD but resulted in no significant difference in EMG outcomes [7]. The EUS EMG amplitude trend is also in agreement with the results of Byrne et al., who showed a decrease in muscle compound action potential after facial nerve transection treated with an anti-BDNF antibody [24]. The Masson-trichrome-stained specimens supported the recovery of continence 6 weeks after injury, since the morphology results were similar for the Sham Injury group and the Injury group. However, qualitative EUS morphology appeared more disrupted in the Injury + TrkB group than the Injury group. NMJ analysis supports these results, since fewer NMJs were innervated in the Injury + TrkB group compared to the Injury group. Decreased recovery has been associated previously with a smaller number of intact EUS fibers, decreased NMJ innervation, and increased collagen infiltration of the EUS [25]. While a decrease in functional recovery was detected, a reduction in BDNF plasma concentration was not detected in the dual Injury + TrkB group after 6 weeks of treatment. In contrast, previous studies have shown a significant decrease in free BDNF (~$45\%$) with 3 weeks of TrkB treatment, while showing a significant decrease in PN function [12]. Additionally, one week of treatment with TrkB significantly decreased expression of the regeneration-associated gene βII tubulin, which previously has been shown to be key indicator of regeneration [26]. The results of this study, along with those of Balog et al., suggest that by six weeks after dual injury, a compensatory mechanism was increasing BDNF levels, which was suggested by the increase in variability in the BDNF plasma concentration. Additionally, researchers have shown that a reduction in BDNF by $25\%$ in culture has a detrimental effect on dendrite growth, suggesting a decrease of $45\%$ is sufficient to inhibit the regeneration pathway, even if it is only for the first three weeks. Nonetheless, no hypothesized compensatory mechanism was able to improve functional outcomes. Supporting this idea is the significant increase in NT4 plasma concentration in the Injury + TrkB group. TrkB-Fc was previously shown not to significantly change the NT4 plasma concentration with 3 weeks of treatment [12]. In contrast, we observed a significant increase in NT4 concentration with 6 weeks of treatment in this study. Gill et al. demonstrated a compensatory effect when treating the dual nerve and muscle injury model with BDNF, in which BDNF expression was decreased in the EUS [12]. Additionally, Moffat et al. found that inhibiting vascular endothelial growth factor (VEGF)-A expression caused upregulation of VEGF-D expression, suggesting that inhibiting one protein causes a biological system to upregulate related genes in response [27]. Therefore, the same compensatory mechanism could increase the expression of both ligands (BDNF and NT4) that bind to TrkB. In this study, we did not determine if the remaining TrkB-Fc was functionally active after six weeks in the pump. The pumps used in this study were designed to last 44 days, resulting in a small amount of residual volume (~0.0047 mL) being collected after six weeks of use. Thus, while we know from previous studies that the TrkB-Fc molecule was functional at 3 weeks, we cannot be sure it was functional in weeks 3–6. Additionally, although we chose our dose of TrkB-Fc because it had previously been used safely in vivo, a larger dose may have demonstrated a greater effect [10,28]. However, this would require testing multiple doses to ensure safety in vivo, which was outside the scope of this study. Additionally, since we only tested functional recovery at 6 weeks, it is possible that functional recovery was delayed, rather than inhibited, as it could potentially happen at a later time. However, previous studies have shown that functional recovery occurs by 6 weeks after injury, suggesting that in this study, we inhibited the normal regenerative process [4,19]. The results of this study, when examined with the results of Gill et al., support the idea that BDNF is both necessary and sufficient for continence regeneration after a dual nerve and muscle childbirth injury [6]. Gill et al. demonstrated that BDNF administration accelerated LPP recovery 2 weeks after injury [6]. Additionally, Masson’s staining showed EUS morphology in BDNF-treated animals similar to that of sham animals. While the current study showed that TrkB administration inhibited LPP recovery, EUS morphology in TrkB-treated animals showed fewer intact fibers than the saline-treated animals 6 weeks after injury, supporting the functional outcomes. The regenerative capacity of neurons, Schwann cells, and muscle cells decreases over time, as indicated by decreased expression level of regeneration-associated genes [29,30]. This suggests that the longer it takes for the pudendal nerve to regenerate, the less likely it is to encounter a growth-permissive environment, leading to fewer axons reinnervating the EUS, and resulting in more EUS muscle fibers being innervated by a single neuron, as depicted in Figure 6. Continence would be restored in this scenario, but this limited regeneration paradigm could explain the development of SUI decades later—that is, the loss of innervation to muscles with ageing leading to muscle weakness and redevelopment of SUI [31]. Song et al. showed functional recovery with impaired NMJ recovery 9 weeks after a PNC + VD dual injury, suggesting this impaired situation [32]. Insufficient regeneration would not only be compounded by aging but also by other risk factors for SUI, such as smoking, obesity, and multiple vaginal deliveries [3,33]. ## 4. Materials and Methods The Louis Stokes Veterans Affairs Medical Center Institutional Animal Care and Use Committee (IACUC) approved this study. Thirty-seven virgin female Sprague–Dawley rats (250–275 g) were divided into three groups: PNC + VD receiving saline (injury; $$n = 14$$), PNC + VD receiving TrkB-Fc (injury + TrkB; $$n = 11$$), and sham PNC + VD receiving saline (sham injury; $$n = 12$$). In vivo functional testing using leak-point pressure testing (LPP) as the same time as EUS electromyography (EMG) was performed (4–6 times) on the animals six weeks after the injury, a time point selected to ensure spontaneous recovery of the injury group based on prior research [19]. After functional testing, blood and tissues were harvested and stored for assessment of BDNF and Neurotrophin 4 (NT4) and histology and immunofluorescence, respectively. ## 4.1. Osmotic Pump Preparation Osmotic pumps were prepared 40 h before the surgery (model 4004; Alzet, Cupertino, CA, USA). The pumps were filled with either saline or a TrkB-Fc/saline solution such that the animals received 12 μg TrkB-Fc (688-TK; R&D systems; Minneapoliss, MN, USA) per day, as we have done previously [12]. Pump weights were recorded before and after filling. After filling, the regulator was inserted, and the vinyl catheter was attached to the regulator. The pump was then placed in sterile saline in a 37 °C incubator until implantation. The dosage was chosen based on previous publications that used TrkB-Fc [10,11]. ## 4.2. Injury model and Implantation of the Osmotic Pump The creation of the injury and sham injury models was performed as previously described [19]. In summary, rats were anesthetized with 2–$3\%$ isoflurane. Rimadyl (5 mg/kg) was administered subcutaneously at the beginning of the procedure and again on the first postoperative day. The dorsal lumbar–sacral region was shaved and disinfected, and a midline incision was made. The gluteus maximus was cut proximal to the vertebral column. The ischiorectal fossa was gently opened to visualize the pudendal nerve, which was then crushed twice for 30 s with Castroviejo forceps. A subcutaneous pocket was created caudal to the incision site where the osmotic pumps were implanted. The catheter was threaded to the ischiorectal fossa and secured to muscles adjacent to the pudendal nerve near the injury site. This process was then repeated on the contralateral side to ensure both pudendal nerves were crushed and treated. Sham PNC nerves were exposed but not crushed. The gluteus maximus muscle and skin were then closed separately. While remaining anesthetized, animals were moved to the supine position, and the vagina was dilated with a series of lubricated urethral dilators (French 24–32). A modified Foley catheter was then placed inside the vagina and inflated with 3 mL water for four hours. The Foley catheter was then deflated and removed. During the procedure, the animals’ respiration rate was monitored, and isoflurane levels were adjusted to ensure that animals were not over anesthetized. Animals that received sham VD had the vaginal catheter inserted but not inflated. A second dose of rimadyl was given the next day. ## 4.3. Suprapubic Bladder Catheter and Functional Testing Functional outcomes were evaluated as previously described under urethane (1.2 g/kg) anesthesia via intraperitoneal injection [34]. The animals were initially anesthetized with isoflurane (2–$3\%$) during surgery and were then transferred to urethane anesthesia before functional testing. A midline incision was performed in the abdomen ~2 cm above the urethral meatus, and the bladder was exposed. After placing a purse-string suture in the dome of the bladder, an incision was performed at the center, and a catheter with a flared tip (PE-50 tubing) was placed in the bladder. The suture was then tightened around the catheter. After inspecting the bladder incision for leakage during a test filling, the abdominal muscle incision was sutured closed with a single stitch. The skin above the pubic symphysis was opened, and the muscle layer was dissected. The symphysis pubis was cut in the center to access the urethra. A pair of bipolar, parallel platinum–iridium electrodes were placed on the EUS for recording EUS EMG. The electrodes were connected to an amplifier (model PF11; AC Amplifier, Astro-Med; West Warwick, RI, USA; bandpass frequencies: 3 Hz–3 kHz), and recordings were performed using a Powerlab$\frac{8}{35}$ (ADInstruments, Inc., Colorado Springs, CO, USA; 10 kHz sampling rate). The bladder catheter was connected to a pressure transducer (Model PT300; Astro-Med.) and syringe pump (5 mL/hr), and the pressure data were amplified and recorded by the Powerlab system. For LPP testing, when the bladder was approximately half full, gentle pressure was applied to the abdomen, and the external pressure was continued until leakage was observed. The externally applied pressure was then rapidly removed. LPP and EUS EMG were recorded simultaneously and repeated 4–6 times per rat. ## 4.4. Plasma Collection After functional testing, animals were euthanized by anesthetizing them with $5\%$ isoflurane. After opening the chest cavity, blood was collected intracardiacally, placed in EDTA collection tubes, and stored at 4 °C until processing. Samples were centrifuged at 2500 rpm for 15 min at 4 °C. The plasma was collected and stored at −80 °C for later use. ## 4.5. Histology and Immunofluorescence Urethras were flash frozen in OCT and stored at −20 °C. They were sectioned transversely at the EUS (7 and 14 µm thick), and slides were stored at −80 °C. Immunofluorescence of neuromuscular junctions (NMJs) and qualitative assessment were performed as previously described [12]. Innervation of the EUS was probed with anti-neurofilament 68 and 200 antibodies (1:400 dilution each; N0142 and N5139 Sigma-Aldrich, St. Louis, MI, USA), followed by a secondary antibody: Alexa Fluor 488 conjugated donkey anti-mouse IgG (1:400; Item No. R37114, ThermoFisher, Waltham, MA, USA). In total, 4 μg/mL of tetramethylrhodamine-conjugated alpha-bungarotoxin (1:400; Item No. T1175, ThermoFisher, Waltham, MA, USA) was used to identify NMJs, and Alexa Fluor 350 conjugated phalloidin (1:40; Item No. A22281, ThermoFisher, Waltham, MA, USA) was used to identify striated muscle of the EUS. Near sections were stained with Masson’s trichrome for morphological analysis. Two blinded observers qualitatively evaluated representative histology and immunofluorescence images of each specimen, according to the following criteria: Masson’s-trichrome-stained urethral sections were used to assess EUS-striated muscle based on whether the EUS was intact and if collagen had infiltrated between the muscle fibers. EUS NMJs were assessed using immunofluorescence on whether NMJs were compact, innervated, and innervated by a single axon. Four to five animals were analyzed per group using one slide per animal, as we did previously [34,35]. ## 4.6. ELISA An BDNF ELISA assay (Item No. G7610, Promega, Madison, WI, USA) was performed on plasma, as described in the manufacturer’s instructions and as previously described [12]. In brief, the provided Anti-BDNF mouse antibody (1:1000) was coated on the 96-well plate overnight at 4 °C. The plate was then washed five times with 200 µL of tris-buffer saline with tween 20 (TBST) wash buffer. This step was repeated before applying new reagents to the plate throughout the protocol. The plate was then blocked for two hours with 1× blocking and sample buffer (provided in the kit). The plasma samples (1:4 dilution with 1× blocking buffer) and the BDNF standard curve (provided in the kit) were added to the plate and allowed to incubate for two hours at room temperature with shaking (400 rpm). The anti-human BDNF antibody (1:500; provided in the kit) was then applied and incubated for two hours while shaking. The plate was then incubated with an anti-IgY HRP conjugate (1:200; provided in the kit) for one hour with shaking. Then, 100 µL of TMB One solution (provided in the kit) was added to each well. The plate was then incubated for 10 min with shaking before the reaction was stopped by adding 100 µL of 1 N hydrochloric acid. The plate was then read on a plate reader. Neurotrophin 4 ELISA (ERN0114; ABclonal, Woburn, MA, USA) was also performed on plasma as previously described [12]. In brief, samples and standards (provided in the kit) were added to the supplied plate with 50 µL of the supplied enzyme solution and then incubated for 1 h at 37 °C. The plate then washed five times with 400 µL of 1× wash solution. A 1:1 mixture of horseradish peroxidase (substance A 50 µL, provided in the kit) and TMB solution (substance B 50 µL, provided in the kit) was then added to each well and incubated in the dark for 15 min. Then, the stop solution (provided in the kit) was added to each well, and the plate was read on a plate reader. A Mann–Whitney test was used to indicate a statistically significant difference between the groups ($p \leq 0.05$). ## 4.7. Data Analysis As performed previously, LPP was determined by subtracting baseline bladder pressure from peak bladder pressure during LPP testing [34]. Baseline pressure was defined as the bladder pressure just before the application of pressure, and peak pressure was the bladder pressure at which leakage occurred [36]. Analysis of LPP and EUS EMG signals was performed by sequestering 4–6 one-second segments for baseline and peak activity. The amplitude and firing rate of EUS EMG activity were determined as previously described [36]. In brief, a custom threshold for each baseline-peak pair was created to remove background noise. Methods were performed as previously described, using Matlab (V 2012b, Mathworks, Natick, MA, USA) [36]. The increases in amplitude and firing rate during LPP testing were determined by subtracting baseline from peak activity levels. The mean value for each animal for each quantitative variable was calculated and was used to calculate the mean and standard error for each experimental group. A Welsh one-way analysis of variance (ANOVA) with a Dunnett’s T3 post hoc test was used to compare LPP and EUS EMG outcomes between groups with the injury alone group as the control. $p \leq 0.05$ indicated a statistically significant difference between groups. Representative traces of the LPP pressure and corresponding EUS EMG trace were chosen based on means of both outcomes in each group (Figure 1). ## 5. Conclusions In summary, BDNF is essential to functional recovery of the continence mechanism after a dual nerve and muscle injury, since TrkB inhibited or delayed spontaneous functional recovery. Masson’s and NMJ results support these findings, as TrkB treatment also inhibited anatomical recovery. 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--- title: Does the Use of the “Proseek® Multiplex Inflammation I Panel” Demonstrate a Difference in Local and Systemic Immune Responses in Endometriosis Patients with or without Deep-Infiltrating Lesions? authors: - Alexandra Perricos - Heinrich Husslein - Lorenz Kuessel - Manuela Gstoettner - Andreas Weinhaeusel - Thomas Eiwegger - Gabriel Beikircher - René Wenzl journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003683 doi: 10.3390/ijms24055022 license: CC BY 4.0 --- # Does the Use of the “Proseek® Multiplex Inflammation I Panel” Demonstrate a Difference in Local and Systemic Immune Responses in Endometriosis Patients with or without Deep-Infiltrating Lesions? ## Abstract Endometriotic lesions are able to infiltrate surrounding tissue. This is made possible partly by an altered local and systemic immune response that helps achieve neoangiogenesis, cell proliferation and immune escape. Deep-infiltrating endometriosis (DIE) differs from other subtypes through the invasion of its lesions over 5 mm into affected tissue. Despite the invasive nature of these lesions and the wider range of symptoms they can trigger, DIE is described as a stable disease. This elicits the need for a better understanding of the underlying pathogenesis. We used the “Proseek® Multiplex Inflammation I Panel” in order to simultaneously detect 92 inflammatory proteins in plasma and peritoneal fluid (PF) of controls and patients with endometriosis, as well as in particular patients with DIE, in order to gain a better insight into the systemically and locally involved immune response. Extracellular newly identified receptor for advanced gycation end-products binding protein (EN-RAGE), C-C motif Chemokine ligand 23 (CCL23), Eukaryotic translation initiation factor 4—binding protein 1 (4E-BP1) and human glial cell-line derived neurotrophic factor (hGDNF) were significantly increased in plasma of endometriosis patients compared to controls, whereas Hepatocyte Growth factor (HGF) and TNF-related apoptosis inducing ligand (TRAIL) were decreased. In PF of endometriosis patients, we found Interleukin 18 (IL-18) to be decreased, yet Interleukin 8 (IL-8) and Interleukin 6 (IL-6) to be increased. TNF-related activation-induced cytokine (TRANCE) and C-C motif Chemokine ligand 11 (CCL11) were significantly decreased in plasma, whereas C-C motif Chemokine ligand 23 (CCL23), Stem Cell Factor (SCF) and C-X-C motif chemokine 5 (CXCL5) were significantly increased in PF of patients with DIE compared to endometriosis patients without DIE. Although DIE lesions are characterized by increased angiogenetic and pro-inflammatory properties, our current study seems to support the theory that the systemic immune system does not play a major role in the pathogenesis of these lesions. ## 1. Introduction Endometriosis is a benign gynecological disease, defined as the implantation of endometrial-like tissue outside of the uterine cavity [1], occurring with a prevalence of 6–$10\%$ in women of reproductive age [2]. Its clinical presentation varies from asymptomatic women to patients suffering from dysmenorrhea, dyspareunia, dyschezia, dysuria and/or infertility [1]. Due to this range of possible symptoms, diagnosis is often delayed, in many cases taking a great toll on the quality of life of affected women [3]. The unacceptably long time to diagnosis, which has reported to be over eight years, on average, for women suffering from pelvic pain [4], calls for a better understanding of the disease itself and new, non-invasive biomarkers. Depending on the locations and characteristics of the lesions, three endometriosis subtypes have been defined: (superficial) peritoneal lesions, ovarian endometriosis cysts (known as endometriomas) and deep-infiltrating endometriosis (DIE), defined as an infiltration of ≥5 mm into the surrounding tissue, such as, more commonly, the uterosacral ligaments, the bladder or the rectum [5]. Due to its wide range of symptoms, this endometriosis subtype is known to potentially have a severe impact on patient’s quality of life [6]. This underlines the importance of an adequate choice of treatment. Treatment options include a conservative as well as a surgical approach. The choice should be based on the patient’s medical history, symptoms, extent of the disease and personal preference [7]. Despite the invasive nature of these lesions and the wider range of symptoms they can trigger, DIE is described as a stable disease [8]. The exact pathophysiology of this disease still remains unknown. Numerous studies over the years have described inflammation as a key feature in the pathogenesis of endometriosis. Endometriotic lesions are characterized by their ability to implant and proliferate [9,10], thus infiltrating the surrounding tissue [11], triggering neoangiogenesis and an invasion of nerve fibers [12]. Important for their survival is not only their resistance to apoptosis, but also their escape from immune surveillance [13,14]. The first line of defense against any aberrant cells, be it tumor cells or virus-infected cells, are, amongst others, natural killer cells (NK-cells), macrophages, granulocytes and mast cells. These innate cells secrete chemokines (notably from the CC- and CXCL family) and cytokines which recruit additional leukocytes and form the basis for chronic inflammation [15]. In addition, also non hematopoietic cells can contribute to inflammation. This partially explains why high concentrations of these inflammatory proteins have been observed in context with low concentration of NK-cells in the peritoneal milieu of women with endometriosis [14]. Chronicity and lack of clearance of inflammation may be maintained by an impairment of the phagocyting capacities of attracted macrophages [15]. A simultaneous detection of different proteins involved in inflammatory processes has been made possible by multiplex technologies. Several studies have evaluated the usefulness of multiplex technologies for the detection of proteins associated with endometriosis [16,17]. While the analysis of inflammatory proteins in plasma may offer information about the systemic conditions brought on by the disease, the analysis of peritoneal fluid (PF) has established itself as a useful tool to learn more about the local environment of pelvic endometriotic lesions. In this study, we used the “Proseek® Multiplex Inflammation I Panel” in order to expand our understanding of the local intraperitoneal as well as systemic inflammatory mechanisms that underlie the pathogenesis of endometriosis. First, we sought to compare patients suffering from endometriosis to controls to define differences in the immune response brought on by the disease itself. Since characteristics of the endometriosis subtypes differ from each other, we then attempted to define distinct local and systemic inflammatory properties of patients with deep-infiltrating endometriotic lesions. ## 2. Results Eighty-four patients were included in our study. In three of these study participants, however (one patient with endometriosis without DIE, one patient with DIE and one control), ≥$50\%$ of markers were found to be under the limit of detection (LOD), either in plasma or in PF. These three patients were therefore excluded from further analysis. Thus, 81 patients were included in the final calculations, 51 patients with endometriosis (18 of which suffered from DIE) and 30 controls. Patient characteristics are summarized in Table 1. For further data evaluation, we disregarded 23 (underlined in the Supplemental Table S1) out of the 92 analyzed proteins in PF, because they were expressed in less than $50\%$ of patients. The same was carried out for 16 proteins (set in bold in the Supplemental Table S1) measured in plasma. ## 2.1. Patients with Endometriosis vs. Controls The first step of this study focused on comparing all patients with endometriosis to controls, regarding local and systemic inflammatory response. Table 2 presents the markers that differed significantly between the two groups, in both plasma and PF. Heat maps of these proteins are shown in Figure 1 (plasma) and Figure 2 (PF). In plasma, four proteins were significantly increased in endometriosis patients, notably the Extracellular Newly identified Receptor for Advanced Glycation End-products binding protein (EN-RAGE—1.63-fold), Chemokine ligand 23 (CCL23—1.22-fold), Eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1—1.43-fold) and human Glial-derived Neurotrophic factor (hGDNF—1.12-fold), whereas Hepatocyte Growth Factor (HGF) and TNF-Related Apoptosis Inducing Ligand (TRAIL) were significantly decreased in this patient group. When analyzing PF, we merely found three protein concentrations that significantly differed between the groups: Interleukin-6 (IL-6) and Interleukin-8 (IL-8) were increased (2.13- and 2.68-fold respectively), while Interleukin-18 (IL-18) was decreased 0.67-fold in PF of women suffering from endometriosis, compared to controls. ## 2.2. Patients with DIE vs. Patients with Endometriosis without DIE In order to determine the influence of a deep-infiltrating lesion on the local and systemic inflammatory milieu, we compared the inflammation markers in plasma and PF of patients with DIE to women with endometriosis but without DIE. The proteins that differed significantly between these groups are summarized in Table 3. Heat maps of these proteins are shown in Figure 3 (plasma) and Figure 4 (PF). In plasma, two proteins were significantly decreased in patients with DIE. Tumor necrosis factor-related activation-induced cytokine (TRANCE) and chemokine (C-C Motif) ligand 11 (CCL11) were decreased 0.70- and 0.84-fold, respectively, in patients with DIE. In PF four proteins were increased in patients with deep-infiltrating lesions: CCL23 (1.7-fold), CCL11 (1.46-fold), Stem Cell Factor (SCF—1.23-fold) and C-X-C motif chemokine 5 (CXCL5—2.54-fold). ## 3. Discussion The key role of inflammatory processes in the development of endometriosis and its lesions has been evaluated in multiple studies. While many theories have been discussed regarding the pathogenesis of endometriosis, many questions still remain to be answered. In our study, we used a multiplex technology which enabled a simultaneous detection of inflammatory proteins in PF and plasma of patients suffering from endometriosis and controls, in hopes of gaining new insights into underlying pathophysiological mechanisms of endometriosis, and especially of DIE. We therefore performed two sub-analyses in our study, comparing plasma and PF of patients with endometriosis to samples of controls, and in a second step, comparing patients suffering from DIE to endometriosis patients without deep-infiltrating lesions. ## 3.1. Patients with Endometriosis vs. Controls In Table 4 we summarize the main characteristics of proteins that were significantly increased or decreased in patients suffering from endometriosis compared to controls. Two markers (EN-RAGE and CCL23) known for their chemoattractant characteristics were found to be increased in plasma of endometriosis patients compared to controls. EN-RAGE genes were found to be significantly higher expressed in endometrial stromal cells (ESC) in endometriosis patients compared to controls by Sharma et al. [ 32]. EN-RAGE expression seems to be upregulated by its own receptor, RAGE, the expression of which might in turn be activated by estradiol. This led to the conclusion that EN-RAGE might play an important role in the altered inflammatory response in endometriosis patients. Interestingly, an increased expression of EN-RAGE in ESC as described by Sharma would consequently result in an increased expression in PF. Our data, however, merely showed a significant systemic and not local increase in EN-RAGE, as it was increased in plasma and not in PF. CCL23 has never, to our knowledge, been associated with endometriosis in previous studies. Our analysis, however, showed a significant systemic increase in endometriosis patients. The association between HGF and endometriosis has been described in numerous studies [7], promoting cell proliferation and angiogenesis [22], two central characteristics of endometriotic lesions. Most studies, however, focused on the local HGF production, measured in PF, rather than on its systemic expression. Recently, Zhang et al. showed a significantly increased expression of HGF in serum of patients suffering from endometriosis compared to controls, and in particular an increased expression in endometriosis stages III and IV, suggesting that this protein might be used as a future biomarker for diagnosing more advanced stages of this disease [33]. In contrast, we found this protein to be significantly decreased in plasma of patients suffering from various stages of endometriosis. This puts into question the validity of HGF as a future biomarker for this disease. Gene expression of 4EBP1was found to be increased in eutopic endometrium of endometriosis patients yet decreased in ovarian endometriotic lesions in these patients [34]. These changes could not, however, be sufficiently explained. The main function of TRAIL lies in its ability to induce apoptosis. Kim et al. showed results similar to those found in our analyses, with a reduced TRAIL expression in serum of women suffering from endometriosis [35], a trait also seen in some types of cancer cells [26]. This downregulated TRAIL expression might play a significant role in the resistance of endometriotic lesions to apoptosis. Very little data have been published to date regarding the involvement of hGDNF in endometriotic lesions. Chang et al. and Streiter et al. demonstrated the importance of this neurotrophic factor in normal ovarian function and follicular development and suggested that an altered expression might lead to the development of ovarian diseases such as polycystic ovary syndrome (PCOS) or endometriosis [36,37]. To our knowledge, the only study that evaluated a direct link of this protein to endometriosis showed an increased expression in the glandular epithelium of peritoneal ectopic lesions compared to stroma and surrounding peritoneum [38]. In PF of endometriosis patients compared to controls, three pro-inflammatory cytokines (IL-6, IL-8 and IL-18) were significantly differently expressed. The data published regarding IL-18 expression in endometriosis patients show discrepant results. Our results are in line with those described by Zhang et al.: Here too, IL-18 expression was significantly reduced in PF of patients with endometriosis, while this did not correlate with expression in plasma. This finding was used to explain the known reduced NK-cell activity and impaired T-helper-cell immune response seen in patients with endometriosis [39]. In contrast, Oku et al. reported no differences in circulating IL-18 concentrations between these two groups, however, a significantly increased expression in PF of affected patients [40], while Glitz et al. described no differences in serum or PF regarding IL-18 expression but showed a strong positive correlation between serum and PF IL-18 levels [41]. On the other hand, IL-6 and IL-8 were overexpressed in PF of women suffering from endometriosis, which underlines the local pro-inflammatory environment seen in our patient collective. Our data confirm the results found by Wang et al., who described a proliferation-stimulating effect on peritoneal endometriotic lesions [42]. Li et al. further postulated that the increased IL-6 expression induced by macrophages increases secretion of haptoglobin, which in turn helps endometriotic cells escape immune surveillance by binding to macrophages and thus decreasing phagocytosis [43]. As shown in the review by Sikora et al., the increased expression of Il-8 is thought to be linked to an increased expression of other pro-inflammatory factors such as IL-1 and TNF-alpha in patients with endometriosis [31]. Furthermore, it was shown that IL-8 production in human endometrial endothelial cells (HEEC) is stimulated by estrogen and progesterone in women with endometriosis, while these steroid hormones do not have the same effect on HEEC in women without endometriosis [44]. ## 3.2. Patients with DIE vs. Endometriosis Patients without DIE Table 5 summarizes the main characteristics of proteins that were significantly increased or decreased in patients with DIE compared to endometriosis patients without DIE. DIE differs from other endometriosis subtypes in that these lesions penetrate exceeding 5 mm into surrounding tissue. Because of its particular characteristics, the understanding of the pathophysiology of this subtype has become the center of recent studies. Although DIE should not be considered a progressive disease, the impact on patient’s symptoms and the challenges for surgeons dealing with these lesions are high [8]. Zhou et al. recently described different cytokine signatures differentiating between the three previously mentioned subtypes of the disease (peritoneal, ovarian and deep-infiltrating endometriosis). The authors used a multiplex assay of 48 cytokines on PF of endometriosis patients and found a six-cytokine signature of IL-8, IL-12p70, IL-16, IL-18, MCP-1 and MIP-1α, all upregulated in patients with DIE compared to peritoneal endometriosis, as well as a seven-cytokine signature comprising IL-1α, IL-1RA, IL-8, IL-12p40, IL-12p70, IL-16 and TNF-α when comparing patients with ovarian endometriomas and patients with DIE [51]. Although several of these cytokines (IL-8, IL-18, MCP-1 and IL-1α) were included in our analysis, we could not find any corresponding results in our samples. Compared to endometriosis patients without DIE, two proteins were found to be significantly decreased in plasma of patients with DIE. To our knowledge, TRANCE has never been connected to the pathophysiology of endometriosis. Our data show lower values in plasma of patients suffering from DIE, which might contribute to immune escape seen in endometriotic lesions. The important role of CCL11 in endometriotic lesions has been attributed to its recently described angiogenetic potency [52]. In our collective, we found the chemoattractant CCL11 to be diminished in plasma of patients suffering from DIE yet increased in PF of these patients. While in our samples CCL11 concentrations merely differed in patients with DIE compared to endometriosis patients without DIE, previously published data showed lower values in serum [53] and increased values in PF of endometriosis patients compared to controls [26], which correlated with the endometriosis rASRM stage. Suzumori et al. have described significantly elevated levels of CXCL5 in PF of endometriosis patients compared to controls, in particular, however, in patients suffering from more severe stages (stage III and IV) [54]. While our data merely showed differences between DIE and patients without DIE, this may be attributed to the fact that we had significantly more patients with moderate to severe endometriosis in the DIE group. Furthermore, Wunder et al. reported an increased concentration of the chemokine in follicular fluid (FF) of patients with endometriosis. As FF contributes to PF during ovulation, this might add to the inflammatory milieu as well as implantation and neovascularization of endometriotic lesions [55]. An overexpression of CXCL5 has also been previously described in deep-infiltrating lesions themselves, notably in rectovaginal lesions [56]. Another cytokine involved in neoangiogenesis is the previously mentioned CCL23. This cytokine was found to be significantly overexpressed in our patient collective suffering from DIE compared to endometriosis patients without DIE, which might suggest an increased vascularization of these lesions. Osuga et al. analyzed the concentration of SCF in plasma and PF of patients with endometriosis and controls. The authors described an increased expression of SCF only in PF of affected patients. When comparing patients according to their endometriosis rASRM stage, this significant difference was only maintained in patients with stages I and II, compared to controls [49]. Here, it is important to consider, however, that the rASRM score solely takes into account intraperitoneal lesions and does not offer any insight into the extent of possible deep-infiltrating lesions. In our analysis, we found significantly higher SCF concentrations in PF samples of patients with DIE compared to endometriosis patients without DIE. This reconfirms the role of SCF in local inflammation. In vivo data have shown that there seems to be a causal effect of a systemic immune response on the development of endometriotic lesions [57]. However, further studies are needed to clarify whether the role of the immune systems is truly causal or merely a consequence of this disease. In conclusion, while the important role of inflammatory processes in the development and persistence of endometriotic lesions has been repeatedly demonstrated, our multiplex analysis of 92 inflammatory proteins failed to show drastic differences regarding local and systemic inflammatory response in patients suffering from endometriosis compared to controls. Surprising to us were especially the very few differences found in patients with deep-infiltrating lesions. As such, we believe it may be difficult to identify biomarkers that allow the non-invasive diagnosis of DIE. Although these lesions invade deeper into surrounding tissue and create more anatomic distortions, adhesions and tissue fibrosis, our data showed only few differences regarding inflammatory marker levels measured in the “Proseek® Multiplex Inflammation I Panel” in patients suffering from DIE. Although DIE is a subtype characterized by increased angiogenetic and pro-inflammatory properties [58], our current study seems to support the theory that the systemic immune system does not play a major role in the pathogenesis of DIE lesions. The differences seen in published data on inflammatory processes in endometriosis, and in particular DIE, suggest that further studies might be necessary in order to fully understand the role of these cytokines in this enigmatic disease. ## 4.1. Patients The plasma and peritoneal fluid (PF) samples were collected as part of the Endometriosis Marker Austria (EMMA) study, a prospective cohort study conducted at the tertiary, certified referral Endometriosis Center. This study was approved by the Ethics Committee of the Medical University of Vienna (EK $\frac{545}{2010}$). The premenopausal patients selected for this particular study were between 18 and 50 years of age and all underwent laparoscopic surgery during the period of 2010 to 2015 at the Department of Obstetrics and Gynecology at the Medical University of Vienna, for suspected endometriosis, benign ovarian cysts, uterine fibroids, chronic pelvic pain or infertility. All patients included in the “endometriosis group” all had histologically confirmed endometriotic lesions, whereas patients without endometriosis were defined as the “control group”. During the surgery, the endometriosis cases were scored according the rASRM score as minimal (I), mild (II), moderate (III) or severe (IV). In cases of DIE, the disease was furthermore classified according to the ENZIAN scoring system. Information on baseline patient characteristics such as age, BMI, gravidity, parity, as well as the intensity of endometriosis-associated symptoms, notably dysmenorrhea and dyspareunia evaluated using the visual analog scale (VAS), was obtained preoperatively. Statistical testing on patient characteristics included Chi-squared tests, parametric t-tests and Mann–Whitney-U test, and was performed using IBM SPSS statistics version 27. ## 4.2. Sample Analysis Citrate plasma and PF were collected prospectively in accordance with the harmonization guidelines, plasma in a fasting state in the morning on the day of surgery, and peritoneal fluid after a lavage of the peritoneal cavity with 10 mL of sterile $0.9\%$ NaCl. The samples were immediately centrifuged (plasma at 1000 rounds per minute (rpm) and PF at 3000 rpm at 4 °C for ten minutes) and stored in aliquots at −80 °C until analysis. Ninety-two proteins were measured simultaneously using the “Proseek® Multiplex Inflammation I Panel” (OLINK Proteomics, Uppsala, Sweden). A list of all analyzed proteins is shown in Supplemental Table S1. The measurement was carried out according to the Proseek Multiplex 96 × 96 User Manual. Specifically, the Proseek reagents are based on Proximity Extension Assay technology, in which 96 oligonucleotide-labeled antibody probe pairs bind to their respective protein targets in the sample. A polymerase chain reaction (PCR) reporter is formed by a proximity-dependent DNA polymerization event which is detected and quantified by real-time PCR, generating quantitative values in arbitrary units. The Fluidigm raw data’s quality was assessed according to OLINK guidelines (Data Preprocessing v1.0). Values in PF were normalized to the total protein amount (measured with the Bradford Assay) in order to compensate for technical differences due to potentially slightly different lavage volumes during PF sample collection. Biostatistical analysis was performed using BRB Array Tools Version 4.4.1 (developed by the National Cancer Institute, National Institute of Health, Bethesda, United States) and included class comparison (conducted at a significance level of 0.05), whereby different feature selection criteria were applied. The Normalized Protein eXpression (NPX) values were imported into BRB Tools, whereby all normalization methods were disabled, since the data gained in PF were already normalized in the data preprocessing procedure. 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--- title: 'Autoimmune Regulator Gene Polymorphisms and the Risk of Primary Immune Thrombocytopenic Purpura: A Case-Control Study' authors: - Muhammad T. Abdel Ghafar - Ola A. Elshora - Alzahraa A. Allam - Raghda Gabr Mashaal - Shereen Awny Abdelsalam Hamous - Sarah Ragab Abd El-Khalik - Rania Nagi Abd-Ellatif - Reham A. Mariah - Radwa Eissa - Mai Mwafy - Rasha E. Shalaby - Elham Nasif - Rasha A. Elkholy journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003684 doi: 10.3390/ijms24055007 license: CC BY 4.0 --- # Autoimmune Regulator Gene Polymorphisms and the Risk of Primary Immune Thrombocytopenic Purpura: A Case-Control Study ## Abstract This study aimed to assess the possible association between two single nucleotide polymorphisms (SNPs) of the autoimmune regulator (AIRE) gene (rs2075876 G/A and rs760426 A/G) with the risk of primary immune thrombocytopenia (ITP), as well as AIRE serum levels, in the Egyptian population. In this case-control study, 96 cases with primary ITP and 100 healthy subjects were included. Two SNPs of the AIRE gene (rs2075876 G/A and rs760426 A/G) were genotyped via Taqman allele discrimination real-time polymerase chain reaction (PCR). Additionally, serum AIRE levels were measured using the enzyme-linked immunosorbent assay (ELISA) technique. After adjusting for age, gender, and family history of ITP, the AIRE rs2075876 AA genotype and A allele were associated with increased ITP risk (adjusted odds ratio (aOR): 4.299, $$p \leq 0.008$$; aOR: 1.847, $$p \leq 0.004$$, respectively). Furthermore, there was no significant association between AIRE rs760426 A/G different genetic models and ITP risk. A linkage disequilibrium revealed that A-A haplotypes were associated with an increased ITP risk (aOR: 1.821, $$p \leq 0.020$$). Serum AIRE levels were found to be significantly lower in the ITP group, positively correlated with platelet counts, and were even lower in the AIRE rs2075876 AA genotype and A allele, as well as A-G and A-A haplotype carriers (all $p \leq 0.001$). The AIRE rs2075876 genetic variants (AA genotype and A allele) and A-A haplotype are associated with an increased ITP risk in the Egyptian population and lower serum AIRE levels, whereas the SNP rs760426 A/G is not. ## 1. Introduction Immune thrombocytopenia (ITP) is an autoimmune bleeding disorder caused by excessive immune-mediated platelet destruction and inadequate bone marrow production [1]. However, the pathogenesis of ITP is relatively complicated, and the precise etiology and pathogenesis remain unknown. Several environmental factors, including viral infection, autoimmune disorders, and medications, have been linked to ITP pathogenesis. In addition, genetic factors have been identified as a risk factor for the development of ITP [2]. Recent evidence suggests that several mechanisms involving regulatory B- and T-cells, as well as natural killer cells, myeloid-derived suppressor cells, and dendritic cells [3,4,5,6] are all responsible for thrombocytopenia that develops in patients with ITP [7]. However, the mechanism underlying autoreactive T- and B-cell generation in autoimmune diseases remains unclear. Autoimmune Regulator (AIRE) gene is one of the key genes that regulate immune tolerance, making it a candidate for better understanding the pathogenesis of autoimmune disorders [8]. It is located on chromosome 21q22.3 region and has an 11.9 kb genomic region with 14 exons. It encodes a 545 amino acid transcriptional regulator protein of 58 kD. This protein promotes the negative selection of thymic autoreactive T-cells by controlling the expression of a diverse set of self-antigens known as tissue-restricted antigens. The AIRE protein could promote the proteasome pathway, enhancing cell trafficking and DNA repair, as well as self-tolerance via its E3 ubiquitin ligase activity [9,10]. In addition to medullary thymic epithelial cells, evidence suggests that AIRE is also expressed in peripheral lymphoid organs [11]. Extra-thymic AIRE-expressing cells were discovered as a distinct “bone-marrow-derived antigen-presenting CD45low” population that functionally inhibits effector (CD4+) T-cells, preventing co-stimulation and inducing tolerance [12]. Several single nucleotide polymorphisms (SNPs) in the AIRE gene have been identified and reported to be associated with several autoimmune disorders, such as rheumatoid arthritis (RA) [13,14,15], systemic lupus erythematosus (SLE) [16,17], autoimmune thyroiditis, and systemic sclerosis [18], as well as myasthenia gravis [19], vitiligo [20], type 1 diabetes mellitus [21], and autoimmune hepatitis [22]. However, only two SNPs (rs2075876 and rs760426) have received attention due to their significant association with autoimmune disorders, particularly RA and SLE [14], as well as their impact on AIRE expression, particularly the A allele of rs2075876. Experimental studies have shown that AIRE SNPs alter AIRE gene transcription, altering peripheral tissue antigen expression that controls peripheral antigen presentation, providing less efficient negative selection, promoting autoimmune T-cell survival, and increasing susceptibility to autoimmune diseases [23]. Furthermore, depending on the strain’s genetic background, AIRE-deficient mice can exhibit a wide range of autoimmune phenomena [24], including multi-organ lymphocytic infiltration and circulatory antibodies [25], implying a critical role in setting a self-tolerance threshold in immune regulation [26]. On the basis of these data, the AIRE gene may be a candidate gene for several autoimmune disorders. However, the association between AIRE gene polymorphisms and ITP risk has yet to be investigated. Therefore, our study aimed to assess the possible association between two SNPs (rs2075876 G/A and rs760426 A/G) of the AIRE gene with the risk of primary ITP, as well as AIRE serum levels, in the Egyptian population. ## 2.1. Basic Characteristics of the Studied Cohorts In this study, 96 patients with primary ITP and 100 healthy subjects were included. They did not differ significantly in terms of age or gender. However, the ITP group had a significantly higher proportion of positive family history and a lower platelet count than the healthy control group (Table 1). ## 2.2. AIRE SNPs and ITP Risk The Hardy–*Weinberg equilibrium* (HWE) of different genotypes of the two AIRE SNPs (rs2075876 G/A and rs760426 A/G) in the control group was confirmed, indicating that our sample size was sufficient to adequately represent our population. The AIRE rs2075876 AA genotype and A allele were more frequent in the ITP group than in the control group ($$p \leq 0.004$$ and 0.005, respectively; Table 2). After adjusting for age, gender, and family history of ITP, the ITP risk was found to be higher in the AIRE rs2075876 AA genotype (adjusted odds ratio (aOR): 4.299, $95\%$ confidence interval (CI): 1.650–11.202, $$p \leq 0.008$$) and A allele carriers (aOR: 1.847, $95\%$ CI: 1.209–2.822, $$p \leq 0.004$$) than in the GG genotype and G allele carriers. Additionally, an increased ITP risk was observed under the recessive genetic model (aOR: 3.257, $95\%$ CI: 1.406–7.545, $$p \leq 0.005$$) after adjusting to the confounders, whereas the dominant model revealed no association (Table 3). Furthermore, there was no significant difference in the distribution of AIRE rs760426 A/G different genetic models between ITP and healthy control groups. ## 2.3. AIRE SNP Haplotypes and ITP Risk A linkage disequilibrium was detected between the two AIRE SNPs studied (D′ = 0.89), revealing four main haplotypes: G-A; G-G; A-G; and A-A. After adjusting for the confounders, A-A haplotypes were more frequent in the ITP group than in the control group and were associated with an increased ITP risk (aOR: 1.821, $95\%$ CI: 1.099–3.017, $$p \leq 0.020$$) (Table 4). ## 2.4. AIRE SNPs and Haplotypes and Serum AIRE Levels Serum AIRE levels were found to be significantly lower in the ITP group than in the control group (median, 3.1 ng/mL (IQR, 3.2) vs. median, 5.5 ng/mL (IQR, 3.0), respectively, $p \leq 0.001$; Figure 1A). Furthermore, a positive correlation was found between serum AIRE levels and platelet counts ($r = 0.535$, $p \leq 0.001$; Figure 1B). Serum AIRE levels differed significantly among different AIRE rs2075876 genotype and allele carriers (all $p \leq 0.001$), with the lowest levels detected in the AA genotype (Figure 1C) and A allele (Figure 1D) carriers (all $p \leq 0.001$). In contrast, AIRE serum levels did not differ between different AIRE rs760426 genotypes ($$p \leq 0.438$$; Figure 1E) and alleles ($$p \leq 0.748$$; Figure 1F). Furthermore, serum AIRE levels were significantly lower in the A-G and A-A haplotypes than in the G-A and G-G haplotypes (Figure 1G). ## 3. Discussion The hallmark of the normal adaptive immune system is the induction of self-tolerance. For instance, the CD40 gene SNP (rs1883832 C>T) is associated with an increased risk of ITP, particularly when combined with CD40 rs4810485 G>T in the Egyptian population [27,28]. In addition, the histone deacetylase 3 gene SNP (rs2530223 C>T) was found to be associated with increased susceptibility to ITP in all genetic models, with TC/TT genotypes associated with severe thrombocytopenia in the Han population [29]. In this regard, AIRE is regarded as a key player in self-tolerance machinery. Variants in the AIRE gene have been shown to suppress its transcription and protein levels, reducing negative selection and enhancing autoimmune T-cell survival. Autoimmune T-cells play a central role in promoting the development of a variety of immunological disorders via producing a wide range of autoantibodies [23]. Therefore, it is not surprising that the existence of AIRE genetic variations has been linked to a variety of autoimmune disorders [30]. Notably, only two of the eleven SNPs identified in the AIRE gene (rs2075876 G/A and rs760426 A/G) have received attention and have been found to carry a risk for several autoimmune disorders, particularly RA and SLE [17,31]. Although rs2075876 G/A and rs760426 A/G exist in non-coding intronic regions, they have been implicated in inhibiting AIRE gene expression, thereby impairing thymic negative selection and increasing the risk for autoimmune disorders [32,33,34]. Although the mechanisms underlying RA and SLE are unknown, evidence suggests that the loss of self-tolerance with the activation of autoreactive T- and B-cells plays a role [35,36]. In the same vein, ITP is characterized by the excessive activation and proliferation of platelet autoantigen reactive cytotoxic T lymphocytes [37], abnormal T helper cells [38], and B-cells [39], indicating a shared pathogenicity with RA and SLE in terms of altered immune tolerance. Therefore, we conducted this study to assess, for the first time, the association between these two AIRE SNPs and ITP risk in the Egyptian population. Our study revealed that AIRE rs2075876 G/A was associated with increased ITP risk under the additive, recessive, and multiplicative genetic models, with the AA genotype and A allele conferring the higher ITP risk. Other relevant studies revealed that AIRE rs2075876 plays a crucial role in determining the risk for various autoimmune disorders, such as RA and SLE, which is consistent with our findings. In the Chinese population, for instance, the AIRE rs2075876 A allele has been reported to increase RA risk under recessive [31,40] as well as dominant and co-dominant genetic models [13,40]. Furthermore, A. Moneim et al. reported that the AIRE rs2075876 A allele was more frequent in patients with RA than in the healthy subjects under both co-dominant and over-dominant models [15]. Recently, Salesi et al. reported that AIRE rs2075876 homozygous AA and heterozygous AG genotypes increased RA risk when compared to the GG genotype in the Iranian population [41]. In addition, Attia et al. reported an association between this polymorphism and SLE risk in the Egyptian population [17]. On the contrary, Alghamdi et al. found that the AIRE rs2075876 A allele was associated with a low risk of SLE in the Egyptian population [16]. However, no association between this polymorphism and the SLE risk has been reported in the Mexican population [42]. On the other hand, our study findings did not find any significant association between the different genetic models of AIRE rs760426 and ITP risk in our population. In contrast, Shao et al. and Li et al. found that the AIRE rs760426 G allele was more frequent in patients with RA than in healthy controls and was associated with higher RA risk under the recessive model in the Chinese population [31,40]. However, a borderline association between rs760426 and RA risk was detected by Feng et al. [ 13]. Moreover, A. Moneim et al. found that the AIRE rs760426 AG genotype and G allele were more frequent in patients with RA than in healthy controls in both co-dominant and over-dominant genetic models [15]. Furthermore, Attia et al. reported that the AIRE rs760426 homozygous genotype was more frequent in patients with SLE than in healthy controls, indicating a stronger association with SLE risk in the Egyptian population [17]. Since the association between the two studied polymorphisms and autoimmune disorders has been reported, such as in a previous meta-analysis that revealed an association between these two SNPs and high RA risk under all genetic models [23], it is reasonable to assume that linkage disequilibrium may exist between these polymorphisms and may confer a risk for autoimmune disorders. In this study, such linkage disequilibrium was observed, with the A-A haplotype being associated with a 1.821-fold increased ITP risk. In contrast, A. Moneim et al. revealed no evidence of linkage disequilibrium between the two SNPs in RA [15]. In terms of other AIRE SNPs, several SNPs were examined in combination and revealed that AIRE haplotype CCTGCC (AIRE C-103T, C4144G, T5238C, G6528A, T7215C, and T11787C) showed a three-fold increased risk for vitiligo [20]. Furthermore, the AIRE CCTGCT and CGTGCC haplotypes (C-103T, C4144G, T5238C, G6528A, T7215C, and T11787C) showed a 9.47- and 3.51-fold increased risk for alopecia areata, respectively [43]. Furthermore, the haplotype of five AIRE SNPs (rs2075876, rs2075877, rs933150, rs1003854, and rs1078480) and the two SNPs (rs2256817 and rs760426) revealed a 1.852- and 1.950-fold increased risk for RA, respectively [13]. On the other hand, the variant effect prediction for the two studied SNPs in the study revealed that $36\%$ of them are upstream gene variants, and $36\%$ are intronic variants. In contrast, other AIRE SNPs (rs2075876, rs2075877, rs933150, rs1003854, and rs1078480) were $43\%$ intronic variants and $25\%$ noncoding transcript variants. In this study, we estimated serum AIRE levels in the studied groups to investigate the potential impact of AIRE genetic variants (rs2075876 G/A and rs760426 A/G) on its expression levels. Our findings revealed that the AIRE rs2075876 AA genotype and A allele had a strong impact on AIRE expression, lowering its serum levels. This is the first study to investigate the relationship between AIRE SNPs and their protein expression levels in autoimmune disorders; no previous studies have investigated this issue so far. However, this effect was demonstrated in silico using data from the Gene Expression Omnibus (GEO) database for 210 lymphoblastoid cells, revealing that the AIRE rs2075876 A allele was significantly correlated with decreased AIRE transcription and, thus, decreased protein levels [14]. However, GEO revealed no association between the AIRE rs760426 G allele and AIRE expression [44]. Although this study was the first to investigate the association between AIRE rs2075876 G/A and rs760426 A/G genetic variants and haplotypes with ITP risk, as well as serum AIRE levels, it does have some limitations that should be considered. First, this is a single-center study. Second, because this study was conducted on a single population, our findings cannot be generalized to other populations. Third, no functional analysis was conducted to assess the causal relationship between AIRE SNPs on one side and AIRE expression and ITP pathogenesis on the other. Fourth, because the samples were collected prior to any treatment, the impact of treatment, particularly corticosteroids, on serum AIRE levels could not be investigated. Finally, serum AIRE levels were not correlated with the duration of ITP. Further studies on other populations and AIRE SNPs, as well as the impact of ITP treatment on AIRE levels and the relationship between AIRE levels and ITP duration, are warranted to support our findings. ## 4.1. Study Cohort In this case-control study, 96 patients with primary ITP at their initial presentation were recruited from the hematology unit of the Internal Medicine Department, Tanta University Hospitals, as a case group. Their inclusion criteria were all cases diagnosed with ITP based on the standard criteria of the International Working Group of isolated thrombocytopenia (platelet counts of less than 100 × 103/µL in the absence of other causes of thrombocytopenia) [45]. Patients with secondary causes of ITP such as viral infections, drugs, and autoimmune disorders, such as RA, SLE, and Chron’s disease, were excluded from the study. In addition, 100 healthy subjects with normal platelet counts were recruited from those attending the out-patient clinics at Tanta University Hospitals as a control group. The exclusion criteria of the case group were also applied to the control group. This study was conducted in accordance with the Helsinki Declaration and was approved by the local ethical committee of the Faculty of Medicine, Tanta University (approval code no. $\frac{35353}{3}$/22). Informed written consent was obtained from all the participants. ## 4.2. Clinical and Laboratory Assessment All participants were asked about their personal and family history of ITP, and patients with ITP were examined clinically and radiologically via ultrasonography to detect splenomegaly. Data on complete blood count (CBC), bone marrow aspiration cytology, antinuclear antibodies (ANAs), and direct anti-globulin test (if Evan syndrome was suspected) used to diagnose ITP, as well as data on viral screening for hepatitis C, cytomegalovirus, human immunodeficiency virus, and helicobacter pylori antigen in stool to exclude secondary ITP, were obtained from the patients’ medical records. ## 4.3. Sampling Blood samples were collected prior to receiving any treatment. Five milliliters of venous blood was collected via standard venipuncture, and two milliliters was delivered into a K2 EDTA vacutainer tube for genotyping. The remainder was delivered into a gel tube at room temperature, centrifuged at 3000 rpm for 5 min, and the serum was then separated and immediately frozen in −20 °C for the assay of AIRE serum levels. ## 4.4. AIRE SNP Genotyping The genomic DNA was extracted from blood samples using the GeneJet genomic DNA purification kit (Thermo-Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions and kept at −80 °C for AIRE genotyping. Two AIRE SNPs (rs2075876 G/A and rs760426 A/G) were genotyped using real-time polymerase chain reaction (PCR) by allelic discrimination assay with Taqman SNP genotyping assay kit (Thermo-Fisher Scientific, MA, USA). In a total volume of 25 µL, the extracted DNA (25 ng/3 µL) was mixed with 2xTaqman genotyping master mix (12.5 µL), 20xTaqman SNP genotyping assay (1.25 µL), and nuclease-free water. The reaction mixture was then run on an Applied Biosystem StepOne real-time PCR instrument (Foster City, CA, USA) under the following thermal cycling conditions: pre-denaturation at 95 °C for 5 min, followed by 40 cycles of denaturation at 95 °C for 15 s and annealing/extension at 60 °C for 60 s. The genotypes were determined with cycle thresholds on the multicomponent plot. ## 4.5. Serum AIRE Assay Serum AIRE levels were measured using a commercially available enzyme-linked immunosorbent assay (ELISA) kit (Human AIRE, Biovision, Milpitas, CA, USA, catalog no. E4971-100), according to the manufacturer’s instructions, and colorimetrically detected at 450 nm on a Tecan Spectra II Microplate Reader (canton of Zürich, Switzerland). The sample concentration was calculated using a logit–log standard curve. The assay sensitivity was 0.094 ng/mL, with intra-assay and inter-assay coefficients of variation of <$8\%$ and <$10\%$, respectively. ## 4.6. Statistical Analysis All datasets were analyzed using the Statistical Package for the Social Sciences (SSPS) software Version 22 (IBM Corp, Armonk, NY, USA). The data were tested for normality using the Kolmogorov–Smirnov test. The normally distributed numerical variables were presented as mean and standard deviation and were compared using Student’s t-test, while the non-normally distributed variables were presented as median and interquartile range (IQR) and were compared using the Mann–Whitney U test. The categorical variables were presented as numbers and percentages and were compared using the Chi-square χ2 test. The significant comparisons were further corrected (Pcorr) using Bonferroni’s correction for multiple testing. The HWE of AIRE SNPs (rs2075876 and rs760426) genotypes was determined in the control group using the χ2 test. The web-based SHEsisPlus platform (http://shesisplus.bio-x.cn/SHEsis.html (accessed on 8 August 2022)) was used for haplotype analysis. The ITP risk was calculated as a crude OR with a $95\%$ CI for both AIRE SNP genetic models and haplotypes and then adjusted for confounders such as age, gender, and family history of ITP using multiple logistic regression analysis. 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--- title: A Mixture of Cervus elaphus sibiricus and Glycine max (L.) Merrill Inhibits Ovariectomy-Induced Bone Loss Via Regulation of Osteogenic Molecules in a Mouse Model authors: - Dong-Cheol Baek - Seung-Ju Hwang - Jin-Seok Lee - Jing-Hua Wang - Chang-Gue Son - Eun-Jung Lee journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003697 doi: 10.3390/ijms24054876 license: CC BY 4.0 --- # A Mixture of Cervus elaphus sibiricus and Glycine max (L.) Merrill Inhibits Ovariectomy-Induced Bone Loss Via Regulation of Osteogenic Molecules in a Mouse Model ## Abstract Osteoporosis is a metabolic skeletal disease characterized by lowered bone mineral density and quality, which lead to an increased risk of fracture. The aim of this study was to evaluate the anti-osteoporosis effects of a mixture (called BPX) of *Cervus elaphus* sibiricus and Glycine max (L.) Merrill and its underlying mechanisms using an ovariectomized (OVX) mouse model. BALB/c female mice (7 weeks old) were ovariectomized. From 12 weeks of ovariectomy, mice were administered BPX (600 mg/kg) mixed in a chow diet for 20 weeks. Changes in bone mineral density (BMD) and bone volume (BV), histological findings, osteogenic markers in serum, and bone formation-related molecules were analyzed. Ovariectomy notably decreased the BMD and BV scores, while these were significantly attenuated by BPX treatment in the whole body, femur, and tibia. These anti-osteoporosis effects of BPX were supported by the histological findings for bone microstructure from H&E staining, increased activity of alkaline phosphatase (ALP), but a lowered activity of tartrate-resistant acid phosphatase (TRAP) in the femur, along with other parameters in the serum, including TRAP, calcium (Ca), osteocalcin (OC), and ALP. These pharmacological actions of BPX were explained by the regulation of key molecules in the bone morphogenetic protein (BMP) and mitogen-activated protein kinase (MAPK) pathways. The present results provide experimental evidence for the clinical relevance and pharmaceutical potential of BPX as a candidate for anti-osteoporosis treatment, especially under postmenopausal conditions. ## 1. Introduction Osteoporosis is a musculoskeletal disease characterized by low bone mass, microstructural destruction of bone, and an increased risk of fractures [1]. According to a meta-analysis of 103, 334, 579 people over the course of 15 years, the global prevalence of osteoporosis was $18.3\%$, with a prevalence of $23.1\%$ in females and $11.7\%$ in males [2]. More than 3 million cases of osteoporosis and fractures occur annually in the United States, which is expected to account for an economic burden of 25.3 billion dollars by 2025 [3]. *In* general, primary osteoporosis is divided into type 1 postmenopausal osteoporosis and type 2 senile osteoporosis, while secondary osteoporosis results from a clearly defined etiologic clinical disease or medications [4]. In particular, postmenopausal osteoporosis accounts for $80\%$ of all osteoporosis cases in women over the age of 50 [5]. Estrogen is involved in bone metabolism because it leads to dynamic equilibrium that maintains homeostasis by regulating the balance between osteoclasts and osteoblasts [6]. However, as estrogen levels are reduced during menopause, the rate of bone resorption rises due to an increase in osteoclast differentiation rather than osteoblast differentiation [7,8]. As a result, postmenopausal females have increased bone loss, which leads to osteoporosis, and $40\%$ of postmenopausal females are anticipated to suffer from osteoporotic fractures, including those of the spine, hip, and wrist [9,10]. Currently, as bone resorption inhibitors, bisphosphonates are the primary therapeutic agent used to treat osteoporosis [11,12]. However, long-term use of these medicines has been associated with side effects such as atypical fractures, stroke, and coronary artery disease [13,14,15,16]. Another therapeutic approach is to use agents such as teriparatide, abaloparatide, and romosozumab, which promote bone formation. One clinical trial showed less severe adverse effects in bone formation-promoting agents compared with anti-bone resorption therapy with bone-forming treatment in patients with severe osteoporosis [17]. Recently, as an emerging target for osteoporosis, researchers have focused on the bone morphogenetic protein (BMP) pathway to regulate osteogenic differentiation [18]. Owing to the long clinical use especially in Asian countries and a low risk of side effects, natural resources have recently caught the attention of osteoporosis researchers [19]. According to the latest research, natural resource-based medical approaches for the treatment of osteoporosis have the potential to reduce extremely unbalanced bone turnover, resulting in increased bone mineral density as well as minimal bone microstructural degradation by promoting osteogenesis [20]. Based on long-term clinical experience, we used a standardized water extract syrup (called BPX) of the mixture of *Cervus elaphus* sibiricus and Glycine max (L.) Merrill in Daejeon University Hospital, Republic of Korea, since 2020. In a previous study, *Cervus elaphus* sibiricus improved estradiol concentration and femoral bone mineral density (BMD) in the OVX-induced rat model [21,22]. Additionally, treatment with Glycine max (L.) Merrill has been previously shown to cause a reduction in the bone resorption marker and an increase in the bone formation marker, as well as an improvement in bone mineral density (BMD) at the proximal femur in 72 postmenopausal females aged 45 to 65 [23]. Meanwhile, no study of the anti-osteoporotic effect of a combination of both resources has been conducted. We herein aimed to investigate the anti-osteoporotic effects of BPX and its related mechanisms using an ovariectomized mouse model. ## 2.1. Fingerprinting of BPX Four compounds, uracil, daidzin, glycitin, and genistin, were detected at retention times of 3.53, 17.02, 17.74, and 19.72 min, respectively, in the tested samples. Semiquantitative analysis showed 0.01 mg/g uracil, 0.14 mg/g daidzin, 0.03 mg/g glycitin, and 0.22 mg/g genistin in BPX (Figure 1A–C). ## 2.2. BPX Attenuated OVX-Induced Bone Loss DXA 2D images showed the notable induction of osteoporosis in OVX-induced mice, which was supported by the decreases in both bone mineral density (BMD) and bone volume (BV) scores. These parameters for osteoporosis were significantly attenuated by administration of BPX compared with the OVX group ($p \leq 0.05$ or 0.01 for BMD and $p \leq 0.05$ for BV, Figure 2A–D). These anti-osteoporotic effects were similarly observed in all measurements, including the whole body, femur, and tibia (Figure 2B–D). ## 2.3. BPX Attenuated Histological Alterations in the Femur H&E staining revealed that OVX reduced the trabecular bone area but increased bone marrow adipocyte volume in secondary spongiosa of the femur, whereas these alterations were remarkably attenuated by BPX administration (Figure 3A,D). The effects of BPX were also notably supported by other histological findings, including staining for both ALP and TRAP activity and the number of osteoblasts and osteoclasts in both cortical and trabecular bone. ( Figure 3B,C,E–H). In addition, BPX administration notably attenuated OVX-induced downregulation of OPG while inhibiting RANKL expression and the ratio of RANKL/OPG in the femur ($p \leq 0.05$ or $p \leq 0.01$, Figure 3I). ## 2.4. BPX Attenuated Alterations in Bone Formation and Resorption Markers in Serum OVX notably elevated serum levels of TRAP, Ca, and OC compared with the Sham group, but administration of BPX markedly attenuated these alterations, especially for the levels of TRAP ($p \leq 0.05$) and Ca ($p \leq 0.01$) (Figure 4A–C). BPX administration also significantly attenuated the OVX-induced reduction in the serum ALP level ($p \leq 0.05$, Figure 4D). ## 2.5. BPX Modulated the BMP Pathway and Its Related Molecules From osteoblast progenitor cells to matrix mineralization, the proteins and gene expression related to osteoblastogenesis and bone formation was determined. OVX markedly suppressed the protein expression of p-p38, p-smad $\frac{1}{5}$/8, smad 4, and Runx2 in the femur, and BPX administration significantly attenuated these alterations in all molecules ($p \leq 0.01$, Figure 4F,G). *In* gene expression analyses, BPX administration significantly normalized the OVX-induced downregulation of BMP-2, BSP-1, and OSX in the femur ($p \leq 0.05$ or $p \leq 0.01$, Figure 4E). ## 3. Discussion Osteoporosis is a metabolic skeletal disease that weakens bones to the point where they break easily, which leads to physical limitations and poor quality of life [24]. As bone resorption inhibitors and antitumor agents, bisphosphonates are the most standard medication for osteoporosis [25,26]. However, it has been reported that there are still some negative effects, so this should be taken with caution [27]. To investigate the anti-osteoporotic potential of BPX and its underlying mechanisms, we employed an OVX-induced mouse model. According to guidelines from the Food and Drug Administration (FDA), this model is an appropriate preclinical model for postmenopausal osteoporosis [28]. OVX is well known to induce estrogen deficiency-related bone loss and the clinical symptoms of postmenopausal osteoporosis [29,30]. As expected, OVX resulted in a decrease in both bone mineral density (BMD) and bone volume (BV) (Figure 2 and Figure S2B–D) as well as the presence of postmenopausal symptoms such as an increase in the levels of FSH in serum and a reduction in uterus size in our present data (Figure S1A–C). BMD is the quantitative parameter of minerals in bone tissue and is used for the diagnosis of osteoporosis [31,32]. A lower BMD, which indicates a loss of bone mass and deterioration of bone tissue, leads to higher bone fragility. In particular, for females, when estrogen levels become low under postmenopausal conditions, the balance and coupled action of bone resorption and formation are broken, resulting in excessive bone turnover and bone loss [33]. In the first 5 years of menopause, an imbalance in bone remodeling causes continuous and rapid bone loss, primarily in the trabecular bone, followed by affecting cortical bones in the later years [34]. In our study, BPX administration significantly attenuated both the BMD and BV scores in the whole body, femur, and tibia (Figure 2 and Figure S2B–D). The low BMD reflects abnormal bone microarchitecture, which is commonly associated with a decrease in cortical or trabecular bone area and fat accumulation in bone marrow [35,36]. BPX administration notably attenuated the reduction in trabecular bone areas and fat accumulation in the bone marrow of the femur (Figure 3A,D). These results support the anti-osteoporotic effects of BPX under OVX conditions. These anti-osteoporotic actions of BPX were evidenced by other osteogenic parameters, including two bone resorption markers (TRAP and Ca) and two bone formation markers (OC and ALP) (Figure 4A–D). TRAP is secreted by mature osteoclasts during bone resorption, which decomposes bone tissue, resulting in increased Ca release into blood [37]. Especially under low estrogen conditions, osteoclast cells easily become activated, accelerating bone turnover [38]. Thus, serum levels of TRAP and OC have been reported to be significantly higher in osteoporotic females than in non-osteoporotic postmenopausal females [39]. BPX significantly attenuated the elevation in both TRAP and Ca in blood, which indicates anti-osteoclast activity (Figure 3C,G,H and Figure 4A,B). Furthermore, BPX treatment increased the suppression of ALP in serum and osteoblast activity in the femur (Figure 3B,E,F and Figure 4D). As a specific marker of bone formation in both the early and late stages of osteoporosis, the ALP level is increased during the development of the bone matrix [40]. These results support the mRNA expression of OPG, RANKL, and the RANKL/OPG ratio. BPX administration markedly normalized the suppression of OPG and attenuated the elevation in RANKL and the RANKL/OPG ratio in the femur (Figure 3I). OPG and RANKL are important factors in regulating the activity of osteoblasts and osteoclasts, which is a key part of the dynamic equilibrium between bone resorption and bone formation [41]. The higher the RANKL/OPG ratio, the stronger the bone resorption activity, which directly affects the differentiation of osteoclasts and bone metabolism [42]. OC is known to affect the formation of bone by osteoblasts but also interacts with osteoclasts for bone resorption during bone turnover [43]. In the present study, there was a decreasing tendency of serum OC levels (without statistical significance) by BPX treatment (Figure 4C). In a previous pilot study, we confirmed that BPX promoted osteoblast differentiation of MC3T3-E1 (pre-osteoblast cell line) cells through activating ALP (Figure S3C,D). BMP-2 plays a key role in the modulation of osteoblastic bone formation through the canonical BMP/Smad pathway and a non-canonical MAPK pathway [44]. Based on the central role of the BMP pathway in bone formation, we confirmed the effects of BPX on the modulation of BMP-related molecules in the femur (Figure 4F,G). The osteogenic-specific transcription factor Runx2 is activated by both a canonical BMP/Smad pathway and a noncanonical MAPK pathway [44]. The BMP/Smad pathway of mesenchymal stem cells (MSCs) was found to be decreased in subjects with postmenopausal osteoporosis [45], and recombinant human BMP-2 (rhBMP-2) showed positive effects in the OVX-induced mouse model [46] and in a human study of patients with open tibial fractures [47]. We found that BPX administration significantly attenuated the alterations in bone formation-related molecules, such as BMP/Smad (smad $\frac{1}{5}$/8 and smad 4), MAPKs (p38), Runx2, and OSX, in the femur (Figure 4E). From the abovementioned results, we could summarize that the actions of BPX may be linked to both inhibition of bone resorption and promotion of bone formation. HPLC fingerprinting confirmed the major compositional compounds semiquantitatively, including uracil from *Cervus elaphus* sibiricus and isoflavone forms (daidzin, glycitin, and genistin) from Glycine max (L.) Merrill (Figure 1A–C). Cervus elaphus sibiricus increased the BMD of the tibia and trabecular bone area of the femur in an OVX-induced rat model [48,49]. In a previous study, isoflavone from Glycine max (L.) Merrill suppressed bone resorption but activated bone formation in postmenopausal females [50], along with acting on bone formation in an OVX-induced mouse model [51]. These results are consistent with our data and support the anti-osteoporosis effects of BPX; however, limitation of our study is that we could not identify the active compounds in BPX or the change of microstructure, such as connectivity, thickness, and number of trabecular bones. Taken together, we suggest that BPX is a potential candidate for increasing bone formation and suppressing OVX-induced bone loss in postmenopausal osteoporosis. Its underlying mechanisms may involve increased BMP/Smad and MAPK signaling and bone-specific genes. Further research will be necessary to discover the active compounds of BPX and investigate the detailed underlying mechanisms. ## 4.1. Chemicals and Reagents Neutral formalin ($10\%$), acetic acid, a bicinchoninic acid (BCA) protein assay kit, ethylenediaminetetraacetic acid disodium salt dihydrate (EDTA), N-(1-naphthyl)-ethylenediamine dihydrochloride, sodium chloride, tetraethyl ethylenediamine (TEMED), Trizma base, Triton X, and Tween 20 were purchased from Sigma-Aldrich (St. Louis, MO, USA). Additional reagents and chemicals were obtained as follows: $10\%$ ammonium persulfate solution, radioimmunoprecipitation assay (RIPA) buffer, and skim milk were obtained from LPS Solution (Daejeon, Republic of Korea); bovine serum albumin (BSA) was obtained from GenDEPOT (Barker, TX, USA); Mayer’s hematoxylin was obtained from Wako Pure Chemical Industries (Osaka, Japan); ProprepTM was obtained from iNtRON Biotechnology (Seongnam, Republic of Korea); $4\%$ paraformaldehyde (PFA), 10X Tris glycine buffer, and 10X Tris glycine-SDS buffer were obtained from XOGENE (Daejeon, Republic of Korea); protease inhibitor, phosphatase inhibitor, and RNA Later were obtained from Thermo Fisher Scientific (Waltham, MA, USA); methylene alcohol was obtained from Daejung Chemicals & Metals Co. (Siheung, Republic of Korea); polyvinylidene fluoride (PVDF) membranes were obtained from Pall Co. (Port Washington, NY, USA); phospho-p38 (p-p38) antibodies were obtained from Santa Cruz Biotechnology (Dallas, TX, USA); suppressor of mothers against decapentaplegic 4 (smad 4) antibodies were obtained from Abcam (Cambridge, MA, USA); phospho-suppressor of mothers against decapentaplegic $\frac{1}{5}$/8 (p-smad$\frac{1}{5}$/8), suppressor of mothers against decapentaplegic $\frac{1}{5}$/$\frac{8}{9}$ (smad$\frac{1}{5}$/$\frac{8}{9}$), and Runt-related transcription factor 2 (Runx2) antibodies were obtained from Cell Signaling (Danvers, MA, USA); and an actin antibody was obtained from Thermo Fisher Scientific (Waltham, MA, USA). ## 4.2. BPX Preparation and Fingerprinting Cervus elaphus sibiricus and Glycine max (L.) Merrill were purchased from Daehan-Bio pharm (Guri-si, Republic of Korea), and BPX was prepared. All herbs were mixed with 1 L of distilled water and then extracted with boiling water for 2 h. After that, the extracted components of the solution were separated using a Whatman No. 2 filter (Maidstone, UK). Then, the supernatants were filtered again using a Whatman No. 2 filter. The filtrates were concentrated by rotavapor and then lyophilized. These herbal medicine extracts were prepared by mixing them in certain proportions. The final yield of BPX was $10.4\%$ (w/w). The acquired powders were stored at −80 °C for future use. Fingerprinting analyses of BPX were conducted using high-performance liquid chromatography (HPLC). A total of 100 mg of BPX and each reference compound (80 μg of uracil and 160 μg of daidzin, glycitin, and genistin) were dissolved in 1 mL of $50\%$ methanol, and the solution was filtered (0.45 μm). Each sample solution was analyzed using a SunFire C18 (5 μm, 4.6 × 250 mm, Waters, MA, USA). The column was eluted at a flow rate of 1 mL/min and a wavelength of 240 to 450 nm using mobile phases A ($0.05\%$ phosphate in H2O) and B (acetonitrile including phosphate). ## 4.3. Animals and Ovariectomy A total of twenty-four female BALB/c mice (7 weeks old, 16–18 g) were purchased from Dae Han Bio Link (Eumseong, Republic of Korea). All animals were housed at room temperature (22 ± 2 °C) and 60 ± $5\%$ relative humidity under a 12 h light:12 h dark cycle and had free access to a commercial pellet diet (Dooyeol-Biotech, Seoul, Republic of Korea) and tap water. The present study was approved by the Institutional Animal Care and Use Committee of Daejeon University (Daejeon, Republic of Korea; Approval No. DJUARB2022-012) and performed according to the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health (NIH, MD). After acclimation for 7 days, the mice were used for experiments. OVX surgery and experimental design were performed as follows: Seven-week-old mice were intraperitoneally injected with a ketamine and xylazine mix ture (90 mg/kg), and their skins were shaved. The shaved skins were incised longitudinally to remove the bilateral ovaries. The exposed skin and muscles were closed, and the surgical area was disinfected with povidone-iodine. ## 4.4. Drug Treatment The mice were randomly divided into 3 groups ($$n = 8$$ for each group): Sham, OVX, and BPX (OVX + BPX) groups. On the day osteoporosis induction was confirmed, the Sham and OVX groups received a Sham diet, and the BPX group received a BPX diet (1 kg of pellets was treated with 600 mg BPX) for 20 weeks (Figure 1D). The mice were sacrificed at 39 weeks old, and the femur, tibia, uterus, and serum were removed. The femur and tibia were stored at −80 °C. Additionally, to measure the length of the uterus, all the uteri were photographed. ## 4.5. Dual-Energy X-ray Absorptiometry (DXA) Analysis During the experiment, the bone mineral density (BMD) and bone volume (BV) of the whole body, femur, and tibia were measured repeatedly (0, 8, 12, 16, 20, 24, 28, and 32 weeks) by dual-energy X-ray absorptiometry (DXA) with an InAlyzer (Medikors Co., Seongnam, Republic of Korea). The femur (include in the femoral head form proximal to distal) and tibia (form proximal to distal) were assessed by drawing region of interest (ROI) boxes surrounding the relevant locations using image analysis software. The BMD (bone mineral contents; g/bone area; cm2) and BV (cm3) were measured for 1 min, and the radiation exposure was 24 s. The measurement was performed five times, and the mean value was determined. ## 4.6. Histological Analysis Excised femurs and tibias were fixed in $10\%$ neutral formalin for 24 h at room temperature and demineralized with $20\%$ EDTA for four weeks at 4 °C. Then, the femurs were dehydrated using ethanol and xylene and embedded in paraffin. The paraffin blocks were sectioned into 8 μm sections for sagittal slides using a microtome (Leica RM2235, Nussloch, Germany). Mayer’s hematoxylin and eosin (H&E)-stained femur sections were mounted using Canada balsam. In addition, alkaline phosphatase (ALP) and tartrate-resistant acid phosphatase (TRAP) staining procedures were carried out in accordance with the manufacturer’s instructions (MK301, Takara, Japan). The stained sections were observed using an Axio-phot microscope (Carl Zeiss, Jena, Germany). To measure the adipocyte volume/tissue volume (%), adipocyte size (μm2) in secondary spongiosa of the femur, and the stain for ALP and TRAP in both cortical and trabecular bone of the femur, all the femurs were photographed, and Ob. S/BS (%) (osteoblast surfaces/bone surface), osteoblast numbers per mm2 bone surface, Oc. S/BS (%) (osteoclast surfaces/bone surface), and osteoclast numbers per mm2 bone surface were calculated by Image J (NIH). ## 4.7. Enzyme-Linked Immunosorbent Assay (ELISA) After sacrificing, serum was immediately collected from the blood by centrifugation at 3000 rpm for 15 min at 4 °C and stored at −80 °C until use. Serum levels of bone turnover markers, that is, osteocalcin (OC) (E-EL-M0864, Elabscience, Houston, TX, USA), alkaline phosphatase (ALP), and tartrate-resistant acid phosphatase (TRAP) (MK301, Takara, Japan), and the biochemical marker calcium (E-BC-K103-M, Elabscience, Houston, TX, USA) were measured using an enzyme-linked immunosorbent assay (ELISA) kit. The procedures were conducted according to the manufacturer’s instructions. ## 4.8. Western Blot Analysis The left femurs were pulverized into powder using liquid nitrogen with a mortar and pestle, and then RIPA buffer was added. Prepared proteins were separated by $10\%$ polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride (PVDF) membranes using a Mini-PROTEAN Tetra Cell System (Bio-Rad, Hercules, CA, USA). After blocking in $5\%$ skim milk at room temperature for 1 h, the membranes were incubated with primary antibodies against p-p38 (1:1000, sc-166182), p38 (1:1000, ab170099), p-smad$\frac{1}{5}$/9 (1:1000, #13820), smad$\frac{1}{5}$/$\frac{8}{9}$ (1:1000, ab13723), smad4 (1:1000, ab40759), Runx2 (1:1000, #12556), and actin (1:1000, MA5-116869) at 4 °C overnight in a shaking plate. After washing with $0.1\%$ TBS-T, the membranes were incubated with HRP-conjugated anti-mouse (1:5000, to detect p-p38, p38, and actin) or anti-rabbit (1:5000, to detect p-smad$\frac{1}{5}$/8, smad$\frac{1}{5}$/$\frac{8}{9}$, smad4, and Runx2) antibodies for 45 min. The membrane was then developed using an enhanced chemiluminescence (ECL) advanced kit (Thermo Fisher Scientific, Cleveland, OH, USA), and imaging was performed using a FUSION Solo System (Vilber Lourmat, France). Protein expression was semiquantified using Image J (National Institutes of Health, Bethesda, MD, USA). ## 4.9. Quantitative Real-Time PCR Analysis *The* gene expression of bone formation markers was determined in femur tissue using real-time PCR. Excised right femurs were pulverized into powder using liquid nitrogen with a mortar and pestle, and then QIAzol reagent (QIAGEN, Hilden, Germany) was added. Total RNA was extracted using QIAzol reagent (QIAGEN, Hilden, Germany), and cDNA was synthesized using a High-Capacity cDNA Reverse Transcription Kit (4368814, Thermo Fisher Scientific, Cleveland, OH, USA). Quantitative real-time PCR was performed using SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA, USA). Gene expression was analyzed using an IQ5 PCR Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA). The primers were as follows: bone sialoprotein (BSP) (forward: 5′-AAG CAG CAC CGT TGA GTA TGG-3′), (reverse: 5′-CCT TGT AGT AGC TGT ATT CGT CCT C-3′); osterix (OSX) (forward: 5′-AGC GAC CAC TTG AGC AAA CAT-3′), (reverse: 5′-GCG GCT GAT TGG CTT CT-3′); bone morphogenic protein-2 (BMP-2) (forward: 5′-AGC TGC AAG AGA CAC CCT TT-3′), (reverse: 5′-CAT GCC TTA GGG ATT TTG GA-3′); GAPDH (forward: 5′-CAT GGC CTT CCG TGT TCC T′), (reverse: 5′-CCT GCT TCA CCA CCT TCT TGA-3′); receptor activator of nuclear factors κB ligand (RANKL) (forward: 5′-CGA CTC TGG AGA GTG AAG ACA C′), (reverse: 5′-ACC ATG AGC CTT CCA TCA TAG C-3′) and osteoprotegerin (OPG) (forward: 5′-TGT CCA GAT GGG TTC TTC TCA′) (reverse: 5′-CGT TGT CAT GTG TTG CAT TTC C-3′); rotor gene Q software, version 2.3.1.49, from QIAGEN (Hilden, Germany) was used to calculate the relative gene expression. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as a housekeeping gene. ## 4.10. Cell Culture and Cytotoxicity Pre-osteoblast (MC3T3-E1) was cultured in Alpha-MEM supplemented with $10\%$ FBS and $1\%$ antibiotic/antimycotic solution. Murine macrophages (Raw 264.7) were cultured in DMEM supplemented with $10\%$ FBS and $1\%$ antibiotic/antimycotic solution. MC3T3-E1 and Raw 264.7 cells were incubated at 37 °C under $5\%$ CO2, and the cells (1 × 105 cells/well) were seeded into 96-well microplates and then incubated for 12 h. Then, the cells were pretreated with BPX (25, 50, and 100 μg/mL) for 24 h. To evaluate the cytotoxicity of BPX, we determined the cytotoxicity with a WST-8 assay (EZ-Cytox, DoGen, Republic of Korea). The absorbance at 450 nm was measured using a UV spectrophotometer (Molecular Devices, Sunnyvale, CA, USA) (Figure S3A,B). ## 4.11. ALP Staining and Activity Assay in MC3T3-E1 Cell The MG-63 cells (4 × 104 cells/well) were seeded into a 6-well plate and then incubated for 12 h. Then the cells were treated with different doses of BPX (25, 50, and 100 µg/mL) or L-ascorbic acid (50 μg/mL) and β-glycerophosphate (10 mM) every 2 days for 7 days. At day 7 after induction, ALP staining procedures were carried out in accordance with the manufacturer’s instructions (MK301, Takara, Tokyo, Japan). ALP-positive cells were stained blue/purple and observed using an Axio-phot microscope (Carl Zeiss, Germany). The ALP activity was measured using 1-StepTM p-nitrophenyl phosphate substrate solution (Thermo Fisher Scientific, Cleveland, OH, USA). The absorbance was read at 405 nm using a UV spectrophotometer (Molecular Devices, CA, USA). ( Figure S3C,D). ## 4.12. Statistical Analysis The results were expressed as the mean ± standard deviation (SD) or fold changes in the means. 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--- title: The Proteome of Circulating Large Extracellular Vesicles in Diabetes and Hypertension authors: - Akram Abolbaghaei - Maddison Turner - Jean-François Thibodeau - Chet E. Holterman - Christopher R. J. Kennedy - Dylan Burger journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003702 doi: 10.3390/ijms24054930 license: CC BY 4.0 --- # The Proteome of Circulating Large Extracellular Vesicles in Diabetes and Hypertension ## Abstract Hypertension and diabetes induce vascular injury through processes that are not fully understood. Changes in extracellular vesicle (EV) composition could provide novel insights. Here, we examined the protein composition of circulating EVs from hypertensive, diabetic and healthy mice. EVs were isolated from transgenic mice overexpressing human renin in the liver (TtRhRen, hypertensive), OVE26 type 1 diabetic mice and wild-type (WT) mice. Protein content was analyzed using liquid chromatography–mass spectrometry. We identified 544 independent proteins, of which 408 were found in all groups, 34 were exclusive to WT, 16 were exclusive to OVE26 and 5 were exclusive to TTRhRen mice. Amongst the differentially expressed proteins, haptoglobin (HPT) was upregulated and ankyrin-1 (ANK1) was downregulated in OVE26 and TtRhRen mice compared with WT controls. Conversely, TSP4 and Co3A1 were upregulated and SAA4 was downregulated exclusively in diabetic mice; and PPN was upregulated and SPTB1 and SPTA1 were downregulated in hypertensive mice, compared to WT mice. Ingenuity pathway analysis identified enrichment in proteins associated with SNARE signaling, the complement system and NAD homeostasis in EVs from diabetic mice. Conversely, in EVs from hypertensive mice, there was enrichment in semaphroin and Rho signaling. Further analysis of these changes may improve understanding of vascular injury in hypertension and diabetes. ## 1. Introduction Diabetes and hypertension are leading causes of cardiovascular disease (CVD) [1,2,3,4]. The two conditions may present independently or concomitantly, in which case, they synergistically increase cardiovascular risk. In this regard, the prevalence of hypertension is two-times higher in individuals with diabetes compared with those without diabetes [5], and the cardiovascular risk with diabetes is exacerbated by coexistent hypertension [5]. Substantial overlap in etiology and disease mechanisms has been reported between the two conditions, including the involvement of oxidative stress, the renin–angiotensin–aldosterone system, sympathetic nervous system dysregulation, adipokines and peroxisome proliferator-activated receptor signaling [6]. Nevertheless, there are also distinct pathways that are unique to diabetes or hypertension that may also cause vascular injury. Management of cardiovascular risk in these distinct but overlapping conditions requires a clear understanding of the molecular pathogenesis. However, despite significant progress in the understanding of the pathophysiology, the molecular alterations that mediate the initiation and progression of cardiovascular disease in diabetes and hypertension are not fully understood. Circulating large extracellular vesicles (L-EVs) are novel biomarkers of cellular stress/injury [7,8]. L-EVs are 0.1–1.0 μm vesicles shed from the surfaces of cell membranes under conditions of stress [9,10]. Once formed, L-EVs contain membrane and cytosolic protein, mRNA and miRNA typical of their cell of origin, but lack nuclear material. They also play a crucial role in cell-to-cell communication, as they may physically interact and transfer lipids, proteins and nucleic acids from a cell of origin to recipient cells [9]. Crucially, they are present in biological fluids such as urine, blood, saliva and breast milk, and reflect a molecular fingerprint of the releasing cell type [9,11]. The protein composition of some circulating L-EVs may therefore provide more insight into the molecular changes in their cell of origin than analysis of whole plasma. This, in turn, could identify key molecular changes that contribute to vascular injury in diabetes and hypertension. While all types of EVs may provide insight into the cell of origin, L-EVs are particularly suitable for identification of altered pathways in disease, since the majority arise directly from stressed/injured cells [9,12]. The unbiased assessment of protein changes in diabetes has been employed in an effort to identify the dysregulated signaling responsible for diabetic complications. Numerous proteomic studies on diabetic plasma have been conducted, and candidate proteins such as TNFAIP6, CDNF, WIF1 and TGFbR3 have been described as possibly involved in the pathogenesis of vascular injury in diabetes [13,14,15]. Plasma protein profiling of newly diagnosed type 2 diabetes revealed proteins altered at the very early stage, reflecting key metabolic syndrome features, such as insulin resistance, adiposity, fatty liver disease and hyperglycemia [15]. Similarly, the plasma proteome of patients with type 1 diabetes with diabetic nephropathy revealed new putative biomarkers of kidney injury, such as transthyretin, apolipoprotein A1, apolipoprotein C1 and cystatin C [16]. Another study observed that type 1 diabetes was associated with the upregulation of six proteins (prothrombin, alpha-2-macroglobulin, apolipoprotein A-II, β2 glycoprotein I, Ig alpha-2 chain C region and alpha-1-microglobulin) and the downregulation of two proteins (complement C4 and pregnancy zone protein) [17]. In contrast, the number of studies that define proteomic signatures of hypertension is comparatively small. A recent study employed proteomics on plasma from individuals that were hypertensive and matched healthy controls [18]. The study identified 27 molecular alterations, such as osteocalcin, nexilin and phosphoinositide 3-kinase regulator 1; and pathway alterations, including atherogenesis, cellular calcium metabolism, cytoskeletal organization and angiogenesis [18,19,20]. Similarly, a plasma proteomics classifier based on a series of protein changes has been shown to improve risk prediction associated with renal disease in individuals with type 2 diabetes and hypertension [21]. Recently, several groups have examined the proteome of circulating EVs as a strategy to more specifically identify molecular alterations from stressed cells. For example, L-EVs from the plasma of individuals diagnosed with type 2 diabetes are enriched in proteins involved in cell adhesion, inflammation and platelet activation, such as S100A8, S100A9 and CD41 [22]. Interestingly, assessment of circulating EVs in plasma samples from women with gestational diabetes mellitus (GDM) showed altered protein expression as compared to healthy control through a shift towards proteins involved in metabolism, energy production and inflammation [23]. These studies suggest that there is alteration of the EV proteome in diabetes. However, further study and validation of differentially expressed proteins is necessary. Moreover, the EV proteome has not been examined in the context of hypertension. Thus, the aim of this study was to examine the effects of hypertension and diabetes on the molecular composition of circulating EVs, focusing on the L-EV subpopulation. ## 2.1. Physiological and Biochemical Measures Physiological parameters of healthy ($$n = 3$$), OVE26 (diabetic, $$n = 3$$) and TTRhRen (hypertensive, $$n = 3$$) mice, including blood pressure, blood glucose, heart weight, urinary albumin/creatinine and body weight, are presented in Table 1. As expected, blood pressure was elevated in TTRhRen mice, and blood glucose was higher in OVE26 mice, which is consistent with the expected phenotype of these two models. The urinary albumin/creatinine ratio was increased in OVE26 mice. A reduction was also observed in body weight in OVE26. ## 2.2. Characterization of EV Isolates Following differential centrifugation, EV isolates were assessed for size and morphology. Nanoparticle tracking analysis revealed a population of EVs with minimal presence of vesicles less than 100 nm in size (Figure 1A–D). We did not observe differences in EV size or concentration among treatment groups (Figure 1D,E). Transmission electron microscopy analysis showed vesicles approximately 150 nm in size with intact membranes (Figure 1F). Western blot analysis confirmed the presence of vesicle markers flotillin-1 and TSG-101 (Supplementary Figure S1). ## 2.3. Proteomics Analysis and Associated Signaling Pathways To gain insight into the molecular changes associated with hypertension and diabetes, we next examined the protein composition of isolated circulating EVs. Among all samples, LC–MS/MS analysis identified 544 proteins with a minimum of two spectral counts per sample with a $95\%$ peptide threshold and a $99\%$ protein threshold. Of the 544 proteins identified, 408 were common to all groups, whereas 34 were exclusive to healthy mice, 5 to hypertensive mice and 16 to diabetic mice. Seven proteins were common in diabetes and hypertension groups, 34 were common to healthy and hypertension groups and 40 were common to healthy and diabetic mice (Figure 2A). Notably, in hierarchical clustered heatmaps, we observed separation according to disease, confirming that molecular profiles of EVs are most similar within disease conditions and suggesting that EVs may reveal disease-specific protein alterations (Figure 2B). The relative abundance of L-EV protein in diabetic mice in comparison to healthy mice is presented as a volcano plot in Figure 3A. A total of five differentially expressed proteins were identified (Table 2). Of these proteins, three were upregulated (TSP4, HPT, CO3A1) and two were downregulated (ANK1, SAA4) (Figure 3A, Table 2). With respect to hypertensive mice in comparison to healthy, a total of five differentially expressed proteins were identified (Table 3). Of these proteins, two proteins were upregulated (HPT, PPN) and three were downregulated (ANK1, SPTB1, SPTA1) (Figure 3B, Table 3). Finally, for diabetic mice in comparison to hypertensive mice, a total of 11 differentially expressed proteins were identified in EVs (Table 4). Eight proteins were upregulated (IGHA, TSP4, CLC1B, HVM17, CO3A1, PSA3, PSA7,PMGE), and three proteins were downregulated (ZPI, SAMP, SAA4) (Figure 3C, Table 4). ## 2.4. Protein Ingenuity Pathway Analysis To further understand the impacts of diabetes and hypertension on the circulating L-EV proteome, Ingenuity Pathway Analysis (IPA) software was used to assess “diseases and functions”, and “canonical pathways” of all identified proteins. Using all proteins in EVs from diabetes compared to healthy mice, IPA noted enrichment in “diseases and function” for cellular development, cellular growth and proliferation, organismal injury and abnormalities, cell-to-cell signaling and interaction, hematological system development and function, inflammatory response, cardiovascular diseases, skeletal and muscular disorders, cellular function and maintenance and tissue morphology (Figure 4A). Similarly, IPA for “canonical pathways” identified pattern recognition, apelin cardiomyocyte signaling, white adipose tissue browning, SNARE signaling, complement system, PPARα, RxR α activation, IL-8 signaling, NAD homeostasis and CLEAR signaling as enriched in diabetes (Table 5). Among these pathways, the apelin cardiomyocyte signalling pathway, white adipose tissue browning pathway, apelin adipocyte signaling pathway, PPARα, RxR α activation and the IL-8 signaling pathway were enriched pathways associated with inflammation in this group. Other pathways, such as the SNARE signaling pathway, are involved in extracellular vesicle formation or mediate vesicle fusion. The NAD signaling pathway is involved in mitochondrial biogenesis, and the CLEAR signaling pathway is responsible for lysosomal activity (lysosomal expression and regulation) (Figure 4B; Table 5). As shown in Table 5, significantly changed proteins participating in these pathways included complement-related ones (C1QA/C1QB), myosin (MYH10, MYH14, MYH9), mitochondrial proteins (ACADL, ACADM), etc. Next, we examined the “diseases and function” in hypertension compared to healthy. Cell-to-cell signaling and interaction, hematological system development and function, immune cell trafficking, inflammatory response, lipid metabolism, small molecule biochemistry, cell signaling, cellular function and maintenance, molecular transport, vitamin and mineral metabolism were noted as significantly enriched (Figure 5A). For “canonical pathways” the top pathways included signaling pathways such as pattern recognition receptor, white adipose tissue browning, semaphorin neuronal repulsive, RhoA signaling, regulation of Actin-based motility by Rho, phagosome formation, IL-8 signaling, ILK signaling, signaling by Rho family GTPases and actin cytoskeleton (Figure 5B, Table 6). The “canonical pathways” included as white adipose tissue browning pathway (CAMP, LDHA, LDHB, THRB) and IL-8 signaling pathway (CDC42, EGFR, GNA13, GNAI2, GNQ, GNAZ, MMP2, MYL9, RAC1, RAC2, RAP1A, RAP1B, RHOA, VCAM1). ## 3. Discussion Vascular injury and endothelial dysfunction are common features of both hypertension and diabetes. However, as pathogenic mechanisms driving such changes may differ between the two conditions, the approaches to therapeutic management of vascular injury may also differ. The present study examined the effects of hypertension and diabetes on the molecular composition of circulating L-EVs as an indirect measure of vascular alterations. Using well-established mouse models, we observed distinct protein signatures in EV populations and the greatest agreement within disease conditions. Further assessment with IPA identified enrichment in key signaling pathways, including apelin and SNARE signaling (diabetes) and semaphorin and Rho signaling (hypertension). Our results suggest that EV protein composition is reflective of the underlying molecular changes driving disease pathogenesis. In this study, we observed common/distinct changes in proteins in diabetic vs. healthy mice. This study identified a total of five differentially expressed proteins in diabetic mice compared with healthy mice. Of these proteins, three were upregulated (TSP4, HPT, CO3A1) and two were downregulated (ANK1, SAA4). Some of these changes have been identified in other studies and are in accordance with our observations [24,25,26,27,28]. Thrombospondin-4 (TSP4) has been shown previously to cause peripheral arterial disease in diabetes [24]. The fact that TSP4 was elevated in our vesicles, suggests activation of a pathway that may contribute to this process. Increased amounts of type-III collagen (CO3A1) have been noted in tubular epithelial cells in individuals with diabetic nephropathy; however, to the best of our knowledge, this has not been reported in the vasculature [25]. While previous reports have shown elevation in haptoglobin (HPT) in individuals with elevated glucose and metabolic syndrome [26], alterations in ANK-1 do not appear to have been reported previously [27]. Based on the protein composition of EVs, IPA identified the canonical pathways that are most enriched in diabetic vs. control mice. These pathways included apelin signaling, white adipose tissue browning, SNARE signaling, complement activation, PPARα and NAD biogenesis. Previous studies have reported that apelin (a peptide hormone linked with obesity and diabetes) and its receptor inhibit vascular injury in diabetes, including the endocrine response to stress, lipid metabolism, homeostasis and angiogenesis [28,29]. It is possible that enrichment in apelin signaling is a protective mechanism to limit vascular injury in diabetic mice. SNARE proteins are involved in insulin granule exocytosis, but less is known about their relevance to vascular health [30,31,32,33,34] in diabetes. However, SNARE complexes also facilitate EV release, and it is possible that their enrichment is simply a result of altered EV release under diabetic conditions [35]. PPARα signaling has been shown to lower blood pressure and reduce oxidative stress [36,37,38]. The enrichment in this signaling may therefore be evidence of a protective response. Finally, enrichment in proteins related to NAD+ biogenic pathways may be evidence of dysregulation of this pathway, as has been reported in animal and human diabetes [39]. We also examined changes in proteins in EVs between hypertensive mice and healthy ones. A total of five differentially expressed proteins were also identified in this group: two proteins were upregulated (PPN, HPT), and three proteins were downregulated (ANK1, SPTB1, SPTA1). Interestingly, the upregulation of HPT and downregulation of ANK1 were also seen in our diabetes mice, suggesting that these may be common pathways involved in vascular injury in both conditions. Conversely, the upregulation of PPN and downregulation of SPTB1 and SPTA1 were unique to hypertension. In addition to the previously described relationship with blood glucose, increases in HPT have been shown in individuals with elevated blood pressure and metabolic syndrome [26]. Mechanistically, HPT has been shown to lower blood pressure in a model of hemoglobin-induced hypertension [40]. Thus, increased HPT may be a common protective pathway activated in both hypertension and diabetes. When examining the protein composition of EVs from hypertensive and healthy mice, IPA identified canonical pathways that are most enriched in hypertension. These pathways included semaphorin neuronal repulsive signaling, RhoA signaling, phagosome formation, ILK signaling and actin cytoskeleton signaling. RhoA/Rho kinase signaling has long been implicated in hypertension due to its important role in smooth muscle contraction [41,42,43]. Thus, it is perhaps not surprising that this pathway was elevated in EVs from hypertensive mice in our study. As RhoA/Rho kinase also plays important roles in cytoskeletal regulation [44] and phagosome formation [45], enrichment in these pathways may be related to convergent signaling. Interestingly, integrin-linked kinase (ILK) signaling has been implicated in hypertension-mediated organ damage [46,47]. However, to the best of our knowledge, semaphorin signaling has not been implicated in blood pressure regulation and may represent a novel pathway for future study. Our study identified over 500 proteins in circulating L-EVs. The vast majority of those proteins (>400) were found in all groups. Interestingly, only a small number of proteins were found to be exclusive to a particular disease state. These proteins could represent those which were altered in response to the disease condition, or they may have actively contributed to disease pathogenesis. Future research should seek to clarify the roles of these proteins as biomarkers or pathogenic mediators of hypertensive or diabetic vascular injury. Interestingly, our hierarchical clustering algorithm largely separated our L-EV isolates based on disease state. L-EVs from diabetic mice were distinctly categorized, and those from hypertension and wild-type mice were more closely overlapping in protein signatures. While there were large variations within each group, it is reassuring that the greatest similarities were seen within the same experimental group. Whether this will remain the case with larger and more heterogeneous populations (i.e., human cohorts) remains to be seen. The present work represents one of the earliest to examine distinct proteomic changes in diabetic and hypertensive mice and the first to employ EVs as a tool to facilitate this analysis. One of the strengths of this study is the use of well-defined mouse models of diabetes and hypertension. In addition, the inclusion of both hypertension and diabetic mice allowed for the identification of both common and unique enriched pathways that may be contributing to disease pathogenesis and progression. We focused our efforts on the L-EV subpopulation due to the tight linkage between their formation and cellular stress [48]. Nevertheless, there is abundant evidence that other EV populations such as small EVs/exosomes play a role in cardiovascular physiology [49,50]. Future studies should strive to clarify the impacts of diabetes and hypertension on other EV populations. Our study also had some limitations to consider. First, relatively few male mice were studied, and although we did observe greatest similarity within disease, it is likely that the degree of heterogeneity was underestimated. Second, our observations require validation, and the potential for therapeutic targeting of dysregulated pathways is not known at this time. It is also worth noting that the approach to assessing protein signatures in circulating EVs does not provide a complete picture of molecular changes such as epigenetic alterations. Finally, there is also potential for differences in hypertension and diabetes-associated changes between mice and humans. Thus, independent validation in humans is a logical next step. Nevertheless, our results suggest that circulating EVs may be used to assess protein changes to the vasculature in a minimally invasive fashion. ## 4.1. Animals Mouse models of hypertension, type 1 diabetes and their wild-type (WT) littermates (healthy control) were employed on an FVB/N background, and male mice were studied at 20 weeks of age. Hypertensive TTRhRen mice express a modified human pro-renin transgene under the control of the mouse transthyretin promoter [51,52,53]. These mice overexpress human renin, and hemizygotes exhibit elevated systolic blood pressure and cardiac hypertrophy by 4 months of age. To model type 1 diabetes, we employed the transgenic OVE26 mice which have a pancreatic beta cell-specific overexpression of a calmodulin mini-gene and are insulinemic from birth [54]. Hypertensive and diabetic mice, and their healthy littermates, were housed at the University of Ottawa Animal Care Facility with free access to food and water. Protocols were approved by the University of Ottawa Animal Care Committee and conducted in accordance with the guidelines of the Canadian Council on Animal Care. ## 4.2. Blood Pressure Measurement Blood pressure was assessed by tail cuff plethysmography (BP 2000, Visitech Systems, Apex, NC, USA), as described previously [51,52,55]. Following a five-day training period (10 BP readings/day), weekly BP measurements were obtained beginning at 10 weeks. ## 4.3. Physiological Parameters Immediately prior to sacrifice, spot urine samples were collected and centrifuged at 2500× g for 10 min and stored at −80 °C. Urinary albumin was assessed with the Mouse Albumin Elisa Kit (Bethyl Labs, Montgomery, TX, USA), following the manufacturer’s protocol. Albumin levels were normalized to creatinine concentration using the Creatinine Companion Kit (Exocell, Philadelphia, PA, USA). At sacrifice, blood samples were collected into heparinized syringes by cardiac puncture and immediately centrifuged at 2500× g for 10 min at 4 °C. Plasma glucose levels were determined by glucometry (Bayer Contour), and remaining plasma was used for EV isolation. Tibias, kidneys, and hearts were removed and weighed. Organ weights were normalized to tibia length. ## 4.4. EV Isolation Circulating L-EVs were isolated via differential centrifugation from plasma by centrifugation for 20 min at 20,000× g to obtain a L-EV-rich pellet. The isolated vesicles were washed with 1× PBS and re-suspended in PBS (nanoparticle tracking analysis), $2.5\%$ glutaraldehyde in PBS (transmission electron microscopy), or RIPA buffer (proteomics) [10,56]. ## 4.5. Nanoparticle Tracking Analysis To confirm the presence of vesicles between 100 and 1000 nm in diameter (L-EVs) in the vesicle isolates, nanoparticle tracking analysis (NTA) was conducted to assess vesicle size. Briefly, samples were diluted in 1× PBS to the working range of the system and analyzed on a ZetaView PMX110 (Particle Metrix, Meerbusch, Germany) in size mode, as we have done previously [57,58,59,60]. ## 4.6. Electron Microscopy EVs were examined by transmission electron microscopy (TEM), as described previously [59,61]. In brief, L-EVs were isolated from pooled plasma samples and fixed with $2.5\%$ glutaraldehyde in PBS for four hours at room temperature. Next, the pellet was washed in 0.1 M Na cacodylate buffer, post-fixed in $2\%$ OsO4 and dehydrated in a series of graded ethanol dilutions. Samples were embedded in Spurr Resin, and 60 nm sections were prepared on copper grids. Samples were visualized using a JEOL JEM-1400 Plus electron microscope (JEOL Ltd, Tokyo, Japan). ## 4.7. Western Blot Analysis L-EV isolates from pooled plasma samples were examined for the presence of vesicle protein markers by Western blot analysis, as described previously [59,62]. Protein lysates were $10\%$ polyacrylamide gels and levels of the vesicle-associated proteins flotillin-1 (1:2000, BD Biosciences, Franklin Lakes, NJ, USA) and TSG101 (1:2000, Abcam Inc., Toronto, ON, Canada) were assessed. ## 4.8. Proteomic Assessment of EVs EV isolates were separated by gel electrophoresis on a 4–$15\%$ Mini PROTEAN TGX Gel. Separated proteins were excised by a gel excision tool (The Gel Company, San Francisco, CA, USA) and placed in $1\%$ acetic acid. In-gel proteins were digested with trypsin, purified by ZipTip, concentrated in an Eppendorf vacufuge (ThermoFisher Scientific, Nepean, ON, Canada) and re-suspended in $0.1\%$ formic acid. Digested peptides were then analyzed by label-free LC-MS/MS through the OHRI Proteomics Core Facility, as described previously [63]. Briefly, the system consisted of an UltiMate 3000 RSLC nano HPLC, LTQ Orbitrap XL hybrid mass spectrometer (ThermoFisher Scientific, Nepean, ON, Canada) the XCalibur software (version 2.0.7) and a nanospray ionization source. Peptides were eluted over a 60 min gradient of 3–$45\%$ acetonitrile at a flow rate of 300 nL/min through a 10 cm long column with integrated emitter tip (Picofrit PF360-75-15-N-5 from New Objective packed with Zorbax SB-C18, 5 micron from Agilent, Santa Clara, CA, USA). MS scans were acquired in FTMS mode at a resolution setting of 60,000. MS2 scans were acquired in ion-trap CID mode using data-dependent acquisition of the top 5 ions from each MS scan. MASCOT software (Matrix Science, Boston, MA, USA, version 2.5.1) was used to infer peptides and proteins from the observed MS/MS spectra and matched against mouse sequences from SwissProt. Mass tolerance parameters were MS ±10 ppm and MS/MS ±0.6 Da. Enzyme specificities were set to “Trypsin” with ≤2 miscuts; variable modifications was set to oxidation of methionine, protein N-terminal acetylation, pyrocarbamidomethlyation of N-terminal cysteine and conversion of glutamine to pyroglutamate; and fixed modifications was set to carbamidomethylation of cysteine. “ Identified MASCOT peptides and proteins were confirmed using Scaffold (Proteome Software Inc., Portland, OR, USA version Scaffold_4.7.3, Proteome Software Inc., Portland, OR, USA)” 79. The scaffold FDR algorithm accepted peptides with a greater than $95\%$ probability, and proteins were accepted if they contained at least 2 identified peptides and had a greater than $99\%$ probability. The differences in protein composition among diabetes, hypertension and healthy mice were identified using Functional *Enrichment analysis* tool (FunRich version 3.1.4), an open access, standalone functional enrichment and interaction network analysis tool and presented as a Venn diagram [64]. ## 4.9. Bioinformatics Analysis For hierarchical clustered heatmaps, Z-scores of log2 protein abundances (Normalized total spectra) were first calculated, and column clustering was calculated using the linkage function (metric = “Euclidean distance”, Linkage method = “average”) with column clustering through MORPHEUS by Broad Institute (RRID:SCR_017386), a software tool for versatile matrix visualization. ( https://software.broadinstitute.org/morpheus, (accessed on 1 June 2022)). A volcano plot of log2 fold change versus −log10 (significance) of differentially expressed proteins comparing diabetes, hypertension and healthy mice was made using VolcaNoseR (https://huygens.science.uva.nl/VolcaNoseR (accessed on 1 June 2022)) [65] with a −log p value (a –log p value of <1.3010299957, corresponding to $p \leq 0.05$ was considered significant) and the fold change threshold of 1.5. Ingenuity Pathway Analysis (IPA) software (Ingenuity Systems, Mountain View, CA, USA; www.ingenuity.com, (accessed on 17 March 2022)) was used to identify “diseases and functions” and “canonical pathways” that are most significant to the dataset and to categorize differentially dysregulated proteins in specific diseases and functions for the proteins exclusive to three different types of mice. The pathways and diseases with $p \leq 0.05$ were listed and considered significantly different. ## 4.10. Statistical Analysis To analyze differences in physiological parameters between hypertensive, diabetic and healthy mice, a one-way ANOVA was performed followed by Bonferroni correction test [66]. All statistical analyses were conducted using GraphPad Prism version 8.4.2 (GraphPad Software, La Jolla, CA, USA). Statistical significance was considered when $p \leq 0.05.$ ## 5. Conclusions In summary, circulating L-EVs have distinct molecular compositions that are dependent on pathogenic state. We also observed changes that were common to both hypertension and diabetes, and disease-specific changes. Further analysis of these changes may lead to the identification of novel pathways associated with the pathogenesis of vascular injury in hypertension and diabetes. Such knowledge is critical to optimizing and personalizing therapeutic management of vascular injury in these two conditions. ## References 1. 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--- title: Peripubertal Alterations of Leptin Levels in Patients with Autism Spectrum Disorder and Elevated or Normal Body Weight authors: - Katarzyna E. Skórzyńska-Dziduszko - Agata Makarewicz - Anna Błażewicz journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003704 doi: 10.3390/ijms24054878 license: CC BY 4.0 --- # Peripubertal Alterations of Leptin Levels in Patients with Autism Spectrum Disorder and Elevated or Normal Body Weight ## Abstract Leptin, which plays a key role in energy homeostasis, is known as a neurotrophic factor possibly linking nutrition and neurodevelopment. Available data on the association between leptin and autism spectrum disorder (ASD) are confusing. The aim of this study was to explore whether plasma levels of leptin in pre- and post-pubertal children with ASD and/or overweightness/obesity differ from those of BMI- and age-matched healthy controls. Leptin levels were determined in 287 pre-pubertal children (mean age 8.09 years), classified as follows: ASD with overweightness/obesity (ASD+/Ob+); ASD without overweightness/obesity (ASD+/Ob−); non-ASD with overweightness/obesity (ASD−/Ob+); non-ASD without overweightness/obesity (ASD−/Ob−). The assessment was repeated in 258 of the children post-pubertally (mean age 14.26 years). There were no significant differences in leptin levels either before or after puberty between ASD+/Ob+ and ASD−/Ob+ or between ASD+/Ob− and ASD−/Ob−, although there was a strong trend toward significance for higher pre-pubertal leptin levels in ASD+/Ob− than in ASD−/Ob−. Post-pubertal leptin levels were significantly lower than pre-pubertal levels in ASD+/Ob+, ASD−/Ob+, and ASD+/Ob− and higher in ASD−/Ob−. Leptin levels, elevated pre-pubertally in the children with overweightness/obesity as well as in children with ASD and normal BMI, decrease with age, in contrast to the increasing leptin levels in healthy controls. ## 1. Introduction Leptin is a proinflammatory cytokine, primarily synthesized by white adipose tissue. This adipokine is secreted in direct proportion to the amount of white adipose tissue, and therefore, the plasma level of leptin is an indicator of the body’s energy stores and caloric intake [1]. Leptin plays an important role in energy homeostasis via appetite-suppressing and neuroendocrine effects mediated by hypothalamic receptors [1,2]. A complex network of interacting signaling pathways of leptin and insulin appears to regulate food intake, energy balance, and body weight [1,2]. In addition to signaling in the central nervous system, leptin exerts its metabolic effects by acting directly in peripheral tissues [3]. Increased leptin levels are linked to obesity and metabolic syndrome. There is also evidence that leptin is produced by the brain, where it is postulated to act as a paracrine and/or autocrine regulator; however, the role of brain-derived leptin remains unclear [4]. Emerging evidence suggests that leptin alters brain structure, neuron excitability, and synaptic plasticity and regulates feeding circuits, suggesting that it may play a role in the development of the central nervous system [5,6,7]. Leptin signaling is thought to play a critical role in hippocampus-dependent learning through regulation of synaptic plasticity and neurotransmitter receptor trafficking [8]. Moderate concentrations of leptin have been shown to improve memory, whereas high concentrations impair memory and synaptic transmission [9]. Leptin is also a critical neurotrophic factor, and leptin signaling abnormalities during fetal development have been associated with decreased neuronal stem cell differentiation and growth [10]. Several recent studies have shown the possible role of leptin and leptin receptors in the development of neurodegenerative diseases via the modulation of neuroinflammation, dopaminergic neurodegeneration, and neuroprotection [11,12,13]. Furthermore, a postmortem study with brain tissue showed higher concentrations of leptin, together with a number of proinflammatory and modulatory cytokines, in the anterior cingulate gyrus of patients with autism spectrum disorders (ASD) than in that of controls [14]. Autism spectrum disorders are a group of phenotypically diverse neurodevelopmental syndromes that manifest early in development. They include a number of developmental brain disorders with a wide range of symptoms and levels of impairment, characterized by communication difficulties, social impairment, and repetitive or stereotyped behaviors [15]. Several cross-sectional studies have investigated the association between circulating levels of leptin and ASD [16,17,18,19,20,21,22,23,24]; however, the available data are confusing. In some studies plasma levels of leptin were shown to be higher in autistic children of normal or elevated body weight compared with children without ASD [16,17,18,20,21,22,23]. In contrast, Prosperi et al. did not identify any significant correlation between the levels of leptin and the presence or absence of a regression of skills prior to the onset of autism in 85 preschoolers with ASD [24]. Despite the originality and novelty of the cited studies, the interpretation of the data should take into account some limitations. The studies show relatively weak associations between leptin and ASD. Furthermore, except the pilot study by Dhaliwal et al., all of the studies suggesting an association of leptin with ASD were conducted in populations of normal-weight children, without controlling for the effect of BMI on leptin in the context of ASD along with co-existing overweight or obesity. Since higher rates of obesity and overweight continue to be reported among children with ASD compared with the general population [25,26], such studies should be designed to take into account elevated body weight. Thus, further BMI-controlled, drug-naïve human studies are needed to examine leptin levels in the context of ASD. Furthermore, to the best of our knowledge the alterations of leptin levels in children with ASD have not been studied longitudinally in relation to puberty; however, there are several prospective studies focusing on the alterations of leptin over extended periods of time [27,28,29]. Since maternal overweight and obesity are well-known risk factors for autism in children [30,31], a few longitudinal studies addressing leptin levels in the perinatal period and early childhood in the context of ASD have been conducted [27,28,29]. Raghavan at al. showed that extremely rapid weight gain during infancy and elevated leptin levels during early childhood were independently associated with greater ASD risk in later years [27]. Interestingly, no associations were found between birth weight for gestational age or cord leptin and risk of ASD [27]. Similarly, Young et al. reported that there was no significant positive association between maternal second-trimester leptin levels and ASD [28]. In contrast, Iwabuchi et al. found significant associations between cord serum leptin levels and increased autistic symptoms [29]. As demonstrated above, a number of studies have explored the possible link between leptin and ASD, but the available results are confusing or contradictory. To our knowledge, none of the previous studies has focused on peripubertal evaluation of leptin levels in terms of both ASD and elevated body weight. In view of this research gap, the aim of this study was to explore whether plasma levels of leptin in pre- and post-pubertal children with ASD differ from those of healthy controls, in the wider context of an elevated BMI, as well as its peripubertal changes. ## Study and Control Population The study was conducted on a carefully chosen population diagnosed with ASD. The diagnosis was based on the criteria for autistic disorder as defined in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSMV), Autism Diagnostic Interview Revised (ADI-R), and Autism Rating Scale (CARS) [15]. Inclusion criteria included pre-pubertal age and ASD diagnosis. Patients were recruited through local support groups (mainly parents and caregivers) or were referred by specialist clinicians and therapists. The informed consent of the children’s parents or legal guardians was obtained. The control group (neurotypical children and adolescents) was selected from among children visiting the medical center for regularly scheduled check-ups. They were not receiving any medical treatment. All members of the control and study groups were from the same geographic area (central and south-eastern Poland). Exclusion criteria included the presence of any chronic condition, drug treatment for any acute or chronic condition, and refusal to give informed consent. An initial personal interview was conducted by trained personnel to establish household characteristics, dietary behavior, health status, and socioeconomic characteristics. Each child’s weight status was determined using an age- and sex-specific percentile for body mass index (BMI, in kg/m2). Current and representative BMI percentile charts for the Polish population of children and adolescents (3–18 years of age) were used [32]. BMI was divided into two categories representing normal weight or elevated weight (both overweight and obesity). A total of 287 pre-pubertal children (mean age: 8.09 years; standard deviation: 1.36) were recruited into the study and divided into four groups: autistic patients with overweight or obesity (ASD+/Ob+); autistic patients without overweight or obesity (ASD+/Ob−); non-autistic patients with overweight or obesity (ASD−/Ob+); and non-autistic patients without overweight or obesity (ASD−/Ob−). The clinical assessment was repeated after normal puberty in a total of 258 children (mean age 14.26 years, standard deviation 1.37) from the four groups (Figure 1). The study combined data from the $\frac{2014}{2015}$ and $\frac{2019}{2020}$ cycles of measurements to provide more statistically reliable estimates. Both girls and boys were carefully examined for signs of puberty. The gold standard for establishing pubertal onset is physical examination with palpation of breast bud development and testicular enlargement for girls and boys, respectively. All the post-pubertal children enrolled in the post-pubertal phase of the research had commenced puberty at least one year before the post-pubertal clinical assessment and blood sample collection. All females got their first period, and all the males began to have ejaculation at night before the post-pubertal clinical assessment. Children who did not present pubertal onset within the required time frame, as well as those who had developed a chronic condition affecting their weight or limiting their ability to participate in the study or had started any chronic pharmacological treatment, were not enrolled in the second phase of the research. Pre-pubertally, a small group of study participants were diagnosed as underweight ($$n = 39$$) according to the above-mentioned BMI percentile charts (for age and gender) for the Polish population of children and adolescents [32]. BMI values below −1 SD for girls, as well as BMI values less than −1.5 SD for boys, were considered underweight. The pre-pubertally underweight male group ($$n = 34$$; 24 boys from the ASD+/Ob group; 10 boys from the ASD−/Ob− group) was characterized as follows: mean BMI 13.42 kg/m2; standard deviation 0.69; median 13.53 kg/m2; interquartile range 0.9; minimum value 11.9 kg/m2; maximum value 14.69 kg/m2;mean age 7.39 years; standard deviation 1.14; median 7.92 kg/m2; interquartile range 2.0; minimum value 6 years; maximum value 10 years. According to the Polish BMI percentile chart, being underweight in a male at the age of 7.39 years is considered to be below 13.8 kg/m2. The pre-pubertally underweight female group ($$n = 5$$; 1 girl from the ASD+/Ob− group; 4 girls from the ASD−/Ob− group) was characterized as follows: mean BMI 13.4 kg/m2; standard deviation 0.74; median 13.23 kg/m2; interquartile range 1.11; minimum value 12.6 kg/m2; maximum value 14.35 kg/m2;mean age 7.15 years; standard deviation 1.01; median 7.83 kg/m2; interquartile range 1.75; minimum value 6 years; maximum value 8 years. According to the Polish BMI percentile charts, being underweight in a female at the age of 7.15 years is considered to be below 14 kg/m2. All pre-pubertally underweight children presented normal physical development pre- and post-pubertally, and their weight after puberty had normalized spontaneously. The mean difference between the normal BMI cut-offs (stratified for age and gender) and BMI calculated in the underweight group was 0.43 kg/m2. Therefore, we decided to include this group in the study. The single outliers in the data were BMI 11.96 kg/m2 for a 6-year-old boy (the ASD+/Ob− group) and BMI 11.9 kg/m2 for a 6-year-old boy (the ASD−/Ob− group). According to the classification of ASD severity (DSMV), the overwhelming majority of the recruited autistic patients presented a mild level of interference in functioning and support required (the level 1). Very few recruited children with ASD presented a moderate level (the level 2). ## 2.1. Characterization of Study Groups and Wilcoxon Signed-Rank Test Results of the Comparison of Related Samples before and after Puberty A detailed characterization of the children divided into four groups is presented in Table 1. As the variables were not normally distributed and nonparametric median tests were used to compare samples, the mean and standard deviation values are presented only to provide a full characterization of the study groups. Table 1 also presents the Wilcoxon signed-rank test results of the comparison of related samples before and after puberty. Interestingly, the Wilcoxon signed-rank test results of the comparison of leptin levels before and after puberty revealed that they were significantly lower after puberty in three groups, i.e., ASD+/Ob+, ASD+/Ob−, and ASD−/Ob+, as follows: ASD+/Ob+ group ($p \leq 0.001$): pre-pubertal median (Me) = 24.7 ng/mL, interquartile range (IQR) = 13.1 versus post-pubertal Me = 21.85 ng/mL, IQR = 18.5ASD+/Ob− group ($p \leq 0.001$): pre-pubertal Me = 5.6 ng/mL, IQR 5.76 versus post-pubertal Me = 4.6 ng/mL, IQR = 4.8ASD−/Ob+ group ($$p \leq 0.001$$): pre-pubertal Me = 26.7 ng/mL, IQR = 10.1 versus post-pubertal Me = 22.4 ng/mL, IQR = 14.44 In contrast, after puberty, leptin levels were significantly higher ($p \leq 0.001$) only in the ASD−/Ob− group (healthy control group): pre-pubertal Me = 2.86 ng/mL, IQR 1.25 versus post-pubertal Me = 4.73 ng/mL, IQR 2.62. ## 2.2. Kruskal–Wallis ANOVA Test Results of the Comparison of Four Groups (ASD+/Ob+, ASD+/Ob−, ASD−/Ob+, and ASD−/Ob−) All the groups (ASD+/Ob+, ASD+/Ob−, ASD−/Ob+, and ASD−/Ob−) were age-matched before and after puberty. There were no significant differences in pre- or post-pubertal BMI values between the two groups of patients with overweightness/obesity (ASD+/Ob+ and ASD−/Ob+) or between the two groups with normal body weight (ASD+/Ob− and ASD−/Ob−); however, a comparison of the two groups of overweight/obese pre-pubertal children revealed a distinct trend ($$p \leq 0.071$$) toward significance: ASD+/Ob+ group (median (Me) = 25.71 ng/mL, interquartile range (IQR) = 4.7) versus ASD−/Ob+ (Me = 22.69 ng/mL, IQR = 2.19). The trend was not observed after puberty. The extended analysis of the subgroups (ASD+/Ob+, ASD+/Ob−, ASD−/Ob+, and ASD−/Ob−), additionally stratified for gender, confirmed the lack of statistical significance for BMI between the respective groups. Furthermore, the above-mentioned trend toward significance, observed in the comparison of the two groups of overweight/obese pre-pubertal children, was not present in subgroups of females and males. Notably, there were no significant differences, either pre- or post-puberty, in leptin levels between the two groups of patients with overweightness/obesity (ASD+/Ob+ and ASD−/Ob+) or between the two groups with normal body weight (ASD+/Ob− and ASD−/Ob−) (Figure 2 and Figure 3), although the comparison of non-ASD and ASD lean pre-pubertal children revealed a distinct trend toward significance ($$p \leq 0.15$$, higher leptin levels in the ASD+/Ob− group than in the ASD−/Ob− group) (Figure 2). ## 2.3. Kruskal–Wallis ANOVA Test Results of the Comparison of Eight Groups Stratified by the Direction of BMI Changes Presented by Children after Puberty in Comparison to Their Pre-Pubertal BMI The comparative analyses of leptin levels were also conducted in the subgroups stratified for the direction of BMI changes presented by children after puberty in comparison to their pre-pubertal BMI values (Figure 4). There were no significant differences in leptin levels between the groups of patients with and without ASD with pre-pubertal overweight/obesity and sustained overweight/obesity after puberty (ASD+/Ob+/Ob+ versus ASD−/Ob+/Ob+) (Figure 4 and Table 2). The leptin levels in these two groups were significantly higher than in the other tested groups, which included children with or without ASD who had normalized BMI after puberty; children with or without ASD with normal weight pre-pubertally but overweight/obesity after puberty; and children with or without ASD with normal weight both before and after puberty (Figure 4). Very surprisingly, there were no significant differences in leptin levels between children with and without ASD with normal weight both before and after puberty or between children with and without ASD whose BMI had changed after puberty (i.e., who had normalized BMI or had presented increased BMI values after puberty). Multiple comparisons of mean ranks of leptin levels for eight groups stratified by the direction of BMI changes presented by children after puberty in comparison to their pre-pubertal BMI are presented in Table 2. This lack of significant differences in leptin levels between children with normal weight, both before and after puberty, and children whose BMI value had changed after puberty was observed despite the significant differences in BMI values between these groups. The BMI changes are presented in Figure 4 and Table 3. ## 2.4. Regression Analyses of Leptin Serum Levels Associations In the multiple linear regression analyses (Table 4), leptin serum levels showed no significant relationships with the presence of ASD. Leptin serum levels were positively associated with BMI values. ## 2.5. Results of the Comparative Analyses of Leptin Serum Levels in the Subgroups Stratified for Gender The extended analysis of the subgroups (ASD+/Ob+, ASD+/Ob−, ASD−/Ob+, and ASD−/Ob−), stratified for gender, revealed no statistical significance in median leptin levels between females and males with overweight/obesity either before or after puberty (the ASD+/Ob+ and ASD−/Ob+ groups) (Table 5). Interestingly, in all the groups with normal body weight (ASD+/Ob− and ASD−/Ob−, before and after puberty) leptin levels were significantly higher in females than in males (Table 5), despite the lack of significant differences in the BMI values of the respective subgroups. ## 3.1. Leptin Levels in Autistic Patients with Normal Weight Compared to Healthy Controls In the present study we examined the possible association between leptin and ASD before and after puberty. Our findings show that there were no significant differences in leptin levels either before or after puberty between lean patients with ASD (ASD+/Ob−) and age-matched healthy controls (ASD−/Ob−), although the comparative analysis revealed a strong trend toward significance ($$p \leq 0.15$$) for higher leptin levels in the pre-pubertal ASD+/Ob− group (median = 5.6 ng/mL) than in the ASD−/Ob− group (median = 2.86 ng/mL). This lack of significance did not result from the lower median BMI value in the ASD+/Ob− group (14.23 kg/m2) relative to the ASD−/Ob− group (15.99 kg/m2), as the difference between these two medians was not statistically significant ($$p \leq 0.3$$). Interestingly, in post-pubertal children, the trend for higher leptin levels was no longer observed (ASD+/Ob− group, median = 4.6 ng/mL versus ASD−/Ob− group, median = 4.76 ng/mL), and the median BMI values were almost equal in both groups. Several cross-sectional studies have previously shown a positive association between circulating levels of leptin and ASD [16,17,18,19,20,21,22,23]. The trend of higher leptin levels in children with ASD and normal body weight is in agreement with the results of those studies; however, an interpretation of the available data should take into account some limitations. Due to the relatively small sample sizes in these studies, as well as in our research, a generalization of the findings is difficult. There are also several serious methodological differences between these studies and the present study. For example, Ashwood et al. found that leptin levels were significantly higher in age-matched children with autism (70 children) compared with typically developing non-ASD controls (50 age-matched children): median = 2.11 ng/mL versus 0.96 ng/mL, $p \leq 0.006$ [16]. There were no statistical differences in BMI between autism cases (median = 16.79 kg/m2) and controls (median = 16.68 kg/m2) [16]. Since Ashwood’s study group included children whose age varied widely between 2 and 15 years, and median leptin levels in this population were markedly lower than those obtained in our research, the results reported by Ashwood et al. cannot be directly compared to our data [16]. Rodrigues et al. reported that plasma levels of leptin were significantly increased ($p \leq 0.01$) in 30 autistic children (median = 1.691 ng/mL) compared with 19 children without ASD (median = 0.862 ng/mL) [18]. Despite its novelty, the cited research seems to present some limitations: 1/no data were given on either age or BMI values, although the authors stated that they had controlled for the effect of BMI; 2/the reported level of significance ($p \leq 0.01$) was close to the threshold of significance; 3/full statistics were not presented in the study [18]. Similarly, another case-control study reported significantly increased leptin levels (p ≤ 0.01) in a small group of 31 lean pre-pubertal children with autism (ages ranged from 3 to 8 years with mean ± SD = 5.59 ± 2.26 years) compared to 28 healthy age- and sex-matched controls [20]. Blardi et al. observed elevated plasma leptin over one year in 35 young normal-weight post-pubertal autistic patients (mean age at the basal time 14.1 ± 5.4 years), compared to 35 healthy sex- and age-matched subjects [17]. In a study by Çelikkol Sadıç et al., which included a total of 44 (38 boys, 6 girls) children with ASD and 44 (35 boys, 9 girls) healthy controls aged 18–60 months, plasma leptin levels were reported to be significantly higher ($p \leq 0.001$) in the ASD group (2.91 ± 0.94 ng/mL) than in the control group (2.27 ± 0.66 ng/mL); however, the BMI percentile was also found to be higher in children with ASD than in the control group ($$p \leq 0.027$$) [21]. Interestingly, no relationship was found between the severity of ASD symptoms, severity of eating problems, and plasma levels of leptin [21]. In a study by Maekawa et al., leptin level trajectories showed a borderline-significant difference between the ASD ($$n = 123$$) and control ($$n = 92$$) children at 4–12 years of age only in terms of the Spearman’s correlation coefficients ($$p \leq 0.0499$$) [22]. In contrast, a recent report by Prosperi et al. indicated no significant correlation between leptin levels and the presence or absence of a regression of skills prior to the onset of autism in 85 preschoolers with ASD [24]. In conclusion, a comparative analysis of the results is nearly impractical due to the limitations of the research, including relatively small sample groups in all studies; highly varying median age between studies—from very young children to much older post-pubertal teenagers; failure to control for the effect of BMI on leptin levels; weak associations that manifested as borderline p-values in several of the studies; different ranges of leptin levels in most of the studies; very small—but reported as significant—differences between median values of leptin between autistic and neurotypical children in several studies; the absence of data on the use of psychotropic medication in most of the studies; and possible differences between ethnic populations. A well-powered study will be helpful for conclusive confirmation of a positive relationship between leptin levels and ASD in pre-pubertal children with normal weight. This association was revealed in the present study as a strong trend toward significance for higher leptin levels in the ASD+/Ob− group than in the ASD−/Ob− group. The lack of significance in our report was not due to the relatively lower median BMI value in the ASD+/Ob− group (14.23 kg/m2) compared to the ASD−/Ob− group (15.99 kg/m2), as the difference was not statistically significant $$p \leq 0.3.$$ In post-pubertal children, in whom the trend for higher leptin levels was no longer observed, the median BMI values were almost equal. Interestingly, the present study documented for the first time that with increasing age and after the onset of puberty, the difference in leptin levels between ASD and non-ASD children with normal weight disappears. Furthermore, we observed for the first time that leptin levels were significantly lower after puberty in the ASD+/Ob− group ($p \leq 0.001$): pre-pubertal median = 5.6 ng/mL versus post-pubertal median = 4.6 ng/mL. In contrast, in the healthy control group (ASD−/Ob−) leptin levels were significantly higher ($p \leq 0.001$) after puberty (pre-pubertal median = 2.86 ng/mL versus post-pubertal median = 4.73 ng/mL). A post-pubertal increase in leptin levels in healthy subjects is a physiological phenomenon observed during normal puberty. Leptin levels rise gradually with age, prior to puberty, suggesting that a threshold effect may trigger puberty [33,34]. Emerging reports suggest that leptin plays a role in adrenarche, as leptin plasma levels increase with higher levels of body fat, and leptin can modulate both the hypothalamus–pituitary–adrenal axis (HPA) and the hypothalamus–pituitary–gonadal axis (HPG) [35,36]. Importantly, distribution of body fat, particularly gluteofemoral fat, is profoundly associated with start of menarche, more than the amount of total body fat [36,37,38,39]. In boys, leptin plausibly has a minor impact in adrenarche, although androgen levels are suggested to be positively associated with plasma leptin levels in several studies [36,40]. Leptin levels exhibit sexual dimorphism, which is independent of body mass index. Females have higher leptin levels than males due to an increase in leptin expression in subcutaneous adipose tissue, stimulation of leptin synthesis by estrogen, and inhibition of leptin synthesis by testosterone [3,41]. As in previous research [41,42], in our study, the groups with normal body weight (ASD+/Ob− and ASD−/Ob−, before and after puberty) presented significantly higher leptin levels in females than in males despite the lack of significant differences in BMI values between these groups. To conclude, on the basis of the present and previous findings on children with normal body weight, it seems plausible to assume that leptin levels may play a much more important role at birth and early childhood than in later years of adolescence in ASD etiopathology. An association between elevated cord serum leptin levels and later ASD symptoms was shown in 762 Japanese children aged 8–9 years [29]. However, two other studies conducted in much smaller sample groups did not confirm this association [27,28]. Finally, we conclude that leptin levels, elevated pre-pubertally in children with ASD and normal BMI, tend to normalize with age, and after puberty, they do not differ from leptin levels in healthy controls. ## 3.2. Leptin Levels in Patients with ASD and Overweightness/Obesity Compared to Neurotypical Children with Overweightness/Obesity According to current estimates of the World Health Organization, more than one billion people worldwide are obese—650 million adults, 340 million adolescents, and 39 million children. This number is still increasing [43,44]. Higher rates of obesity and overweightness continue to be reported among children with ASD compared with the general population [25,26]. Children with ASD have been observed to have an over $41\%$ greater risk of developing obesity [26]. Emerging evidence suggests that the elevated risk for obesity among children with ASD is attributed to additional, specific risk factors, in addition to typical obesity risk factors [23,25,45]. These specific risk factors include psychotropic medication use, medical comorbidities, and the presence of specific genetic factors [23,25,45]. It was also reported that extremely rapid weight gain during infancy may be associated with a greater risk of ASD development in childhood [27]. In our study, there were no significant differences in BMI values between the two groups of patients who are overweight/obese (ASD+/Ob+ and ASD−/Ob+) either before or after puberty; however, the comparison of these two groups before puberty revealed a distinct trend ($$p \leq 0.071$$) toward significance for higher BMI values in the ASD+/Ob+ group (median = 25.71 ng/mL) than in the ASD−/Ob+ group (median = 22.69 ng/mL). This trend was not observed after puberty. Since the exclusion criteria in our study included the presence of any chronic condition or chronic drug treatment, the role of these additional, specific risk factors in the development of obesity is probably minimized. This may be reflected by the lack of significance between the two groups of patients who are overweigh/obese (ASD+/Ob+ and ASD−/Ob+) in our research. Several studies have documented weight gain in children with ASD treated with olanzapine, risperidone, and aripiprazole [46,47]. Chronic risperidone exposure in children with autism causes weight gain in excess of developmentally expected norms, which follows a curvilinear trajectory and decelerates over time [48]. In a recent cross-sectional analysis by Srisawasdi et al., a total of 168 children and adolescents with ASD treated with a risperidone-based regimen for ≥12 months presented leptin dysregulation in a dose- and duration-dependent manner [49]. Another study in 97 children with a mean of 22.9 ± 2.8 weeks of risperidone exposure showed a weight gain of 5.4 ± 3.4 kg weight gain over 24 weeks ($p \leq 0.0001$), an increase in waist circumference from 60.7 ± 10.4 cm to 66.8 ± 11.3 cm ($p \leq 0.0001$), and significant increases in leptin levels ($p \leq 0.0001$) [50]. In contrast, Esen-Danaci et al. found decreased levels of leptin in patients treated with risperidone [51]. As several studies have documented a positive correlation of leptin levels with BMI in non-autistic children [52], as well as in children with ASD ($$p \leq 0.002$$) [24], it remains unclear whether the increase in leptin levels is a secondary mechanism to the weight gain induced by psychotropic medication use or whether psychotropic medication also acts directly on the synthesis and/or turnover of leptin to modulate its concentration. Despite the originality and novelty of the previously cited studies on the role of leptin in ASD [16,17,18,19,20,21,22,23,24], due to the lack of information on psychotropic medication use in several of these studies (except three studies mentioned below), the potential impact of the possible use of such medicines on BMI values and leptin levels is unclear. Although Rodrigues et al. mentioned psychotropic medication use in ASD children, these data were not included in the results of their statistical analysis [18]. In two other studies, patients with a history of psychiatric medication usage were excluded [21,24]. To the best of our knowledge, the present study is the first longitudinal drug-naïve research designed to investigate a possible association between serum leptin levels and ASD in pre- and post-pubertal children while excluding the impact of psychotropic medication on data collected from patients with elevated BMI values. Previously, we used the same model of research to examine selenium content before and after puberty in euthyroid children diagnosed with ASD compared to age-matched neurotypical controls with respect to overweight or obesity as a co-existing pathology [53]. In the present study, we documented for the first time that there were no significant differences in leptin levels between overweight/obese patients with ASD (ASD+/Ob+) and neurotypical children (ASD−/Ob+), either before or after puberty. Furthermore, we observed for the first time that leptin levels were significantly lower after puberty in the ASD+/Ob+ group ($p \leq 0.001$), with pre-pubertal median = 24.7 ng/mL versus post-pubertal median = 21.85 ng/mL, as well as in the ASD−/Ob+ group ($$p \leq 0.001$$): pre-pubertal median = 26.7 ng/mL versus post-pubertal median = 22.4 ng/mL. In the extended statistical analysis of children who are overweight/obese, stratified for gender, we revealed a lack of statistical significance for median leptin levels between females and males both before and after puberty (while females with normal weight presented higher leptin levels than males). In the multivariate analyses in our study, serum leptin levels showed no significant relationships with the presence of ASD, but they were positively associated with BMI values in concordance with a previous report documenting a positive correlation between leptin levels and BMI in children with ASD ($$p \leq 0.002$$) [24]. To the best of our knowledge, the alterations of leptin levels in children with ASD and overweight/obesity have recently been studied only by Dhaliwal et al. [ 23]. These authors suggested that overweight/obese participants diagnosed with ASD ($$n = 6$$) had higher leptin concentrations ($p \leq 0.02$) than normal weight children with ASD ($$n = 15$$) [23]; however, no comparison was conducted between overweight/obese children with ASD and overweight/obese neurotypical children in that report. A consideration of our findings in the light of existing evidence suggests that a plausible explanation for the decreasing leptin levels in both groups (ASD+/Ob+ and ASD−/Ob+) after puberty could be that males present increasing testosterone levels, which are well known to have a negative effect on leptin concentrations [3,41,54]. In males who are overweight/obese, the decreasing leptin levels that occur with increasing age and maturation may result from the gradually rising levels of testosterone. We assume that during maturation, through the complex interaction between leptin, increasing sexual hormones, and other hormonal factors, leptin levels tend to decrease despite increasing age. Interestingly, the differences between pre-pubertal and normally growing post-pubertal BMI values are much smaller in overweight/obese children (in the ASD+/Ob+ group, there was no difference at all) than in healthy controls with normal body weight. In conclusion, pre-pubertal leptin levels in overweight/obese children are highly elevated as a result of the highly increased content of adipose tissue in relation to age. Since the amount of adipose tissue is the strongest and most important mechanism regulating the leptin level [41,42,55], other mechanisms that may influence leptin levels, including age, gender, and ASD, are suppressed. During maturation, via the triggering of specific hormonal changes, high leptin levels in overweight/obese children may begin to decrease, in contrast to the increasing leptin levels in healthy control children with normal weight. The dynamics and intensity of this alteration should be assessed in further research. The limitation of our research is that we did not assess plasma leptin levels in correlation with plasma concentration of reproductive hormones. Our study was not originally designed to track leptin levels in relation to the increasing levels of reproductive hormones or to the Tanner staging phases. Since reproductive hormone levels may highly vary even between healthy individuals classified in the same phase of the Tanner staging [56,57,58], and leptin levels are also modulated by co-existing ASD and/or elevated body weight, the recruited population must have been numerous enough (and much more numerous than our study group) to achieve sufficient statistical power for the reliable assessment of leptin level changes in relation to reproductive hormone levels in different stages of the Tanner scale for both genders, in the wider context of ASD and/or elevated body weight. Given the interesting link between leptin and ASD in the context of hormonal changes associated with puberty, further studies are needed to support our conclusions and to better clarify the mechanisms involved. ## 3.3. Leptin Levels in the Subgroups of Children Stratified for the Direction of BMI Changes after Puberty in Comparison to Their Pre-Pubertal BMI Values We found no significant differences in leptin levels between the groups of patients with and without ASD with pre-pubertal overweight/obesity and sustained overweight/obesity after puberty. The leptin levels in these two groups were significantly higher than in the other tested groups (which showed no significant differences in leptin levels between them), which included children with and without ASD who had normalized BMI after puberty; children with and without ASD with normal pre-pubertal weight who presented as overweight/obese after puberty; and children with and without ASD with normal weight both before and after puberty. A lack of association between leptin and BMI alterations has previously been reported by Antunes et al., who presented no relationship between BMI variation at 6 months and leptin [41]; nevertheless, there are also conflicting older data that describe a decrease in leptin levels after a five-week weight reduction program [59]. ## 4.1. Blood Samples Blood samples from the cubital vein were collected in the morning after overnight fasting. The study material collected during the two assessment periods consisted of 555 serum samples. The blood samples were centrifuged at 1000× g for 10 min, and plasma fractions were immediately stored at −80 °C until used for measurements. The leptin plasma levels were measured by an enzyme-linked immunoassay using a commercial kit (R&D systems, Minneapolis, MN, USA) according to the manufacturer’s instructions. ## 4.2. Statistical Analyses Descriptive statistics were produced for the overall sample and also stratified by both autism and BMI status. As the Kolmogorov–Smirnov and Lilliefors tests indicated that the variables were not normally distributed, the nonparametric Kruskal–Wallis ANOVA test was used for continuous variables. The Wilcoxon signed-rank test was used to compare related samples before and after puberty. A multiple linear regression analysis was used to evaluate the association between the serum leptin levels and ASD status, BMI, and gender. All analyses were two-tailed with a significance level of 0.05 and a power of $80\%$. Statistical analyses were performed using TIBCO Software Inc. [2017] Statistica, version 13.0.0.0 (TIBCO, Tulsa, OK, USA), licensed to the Medical University of Lublin (used by Katarzyna Skórzyńska-Dziduszko). ## 5. Conclusions We found no significant differences in leptin levels, either before or after puberty, between the two groups of patients who were overweight/obesity (ASD+/Ob+ and ASD−/Ob+) or between the two groups with normal body weight (ASD+/Ob− and ASD−/Ob−), although the comparison of non-ASD and ASD pre-pubertal children with normal body weight revealed a strong trend toward significance for higher leptin levels in the ASD+/Ob− group. This trend is consistent with previous findings indicating this association in children with normal body weight [16,17,18,19,20,21,22,23]; the various levels of statistical significance in the present and cited studies may result from relatively small sample sizes, as well as methodological differences between all the studies. For the first time we found that leptin levels, elevated pre-pubertally in children with ASD and normal BMI, tend to normalize with increasing age, and after puberty they do not differ from leptin levels in healthy controls. Furthermore, we observed for the first time that leptin levels were significantly lower after puberty in the ASD+/Ob+ group as well as in the ASD−/Ob+ group. This may result from the gradually increasing levels of testosterone, which are known to have a negative effect on leptin concentrations [3,41,54]. As in previous research [41,42], in our study the groups with normal body weight (ASD+/Ob− and ASD−/Ob−, before and after puberty) presented significantly higher leptin levels in females than in males, despite the lack of significant differences in BMI values in the respective groups. This association was not observed in overweight/obese children. As the amount of the adipose tissue is the strongest and most important mechanism regulating the leptin level [41,42], other mechanisms that may influence leptin levels, including age, gender, and ASD, are suppressed in overweight/obese children. 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--- title: 'Mental Health and Health-Related Quality of Life in Austrian Adolescents with Chronic Physical Health Conditions: Results from the MHAT Study' authors: - Gudrun Wagner - Andreas Karwautz - Julia Philipp - Stefanie Truttmann - Wolfgang Dür - Karin Waldherr - Gabriele Berger - Michael Zeiler journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003709 doi: 10.3390/jcm12051927 license: CC BY 4.0 --- # Mental Health and Health-Related Quality of Life in Austrian Adolescents with Chronic Physical Health Conditions: Results from the MHAT Study ## Abstract Chronic physical health conditions (CPHC) are on the rise in younger age groups and might have a negative impact on children and adolescents. In a representative sample of Austrian adolescents aged 10–18 years, internalizing, externalizing, and behavioral problems were assessed cross-sectionally using the Youth Self-Report and health-related quality of life (HrQoL) using the KIDSCREEN questionnaire. Sociodemographic variables, life events, and chronic illness specific parameters were considered as associated variables with mental health problems in individuals with CPHC. Of 3469 adolescents, $9.4\%$ of girls and $7.1\%$ of boys suffered from a chronic pediatric illness. Of these individuals, $31.7\%$ and $11.9\%$ had clinically relevant levels of internalizing and externalizing mental health problems, respectively, compared to $16.3\%$ and $7.1\%$ adolescents without a CPHC. Anxiety, depression, and social problems were twice as high in this population. Medication intake due to CPHC and any traumatic life-event were related to mental health problems. All HrQoL domains were deteriorated in adolescents with a double burden of mental and CPHC, whereas adolescents with a CPHC without mental health problems did not differ significantly from adolescents without a chronic illness. Targeted prevention programs for adolescents with a CPHC are urgently needed to prevent mental health problems in the long term. ## 1. Introduction Chronic physical health conditions (CPHC) are often associated with diverse physical, psychological, and social functional limitations, leading to a burden of illness over a sustained period of time [1]. Using a generic or non-categorical definition, chronic health conditions are defined as disorders having a biological, psychological, or cognitive basis, last for at least one year, and produce one of the following sequelae: (a) limited function, activities, or social roles within physical, cognitive, emotional, and social development; (b) connection with a reliance on medication, special diet, medical devices, or personal assistance; (c) the need for medical care or related psychological or educational services [2,3]. In the present paper, we refer to chronic physical conditions only. Epidemiological studies show a range of between $10\%$ and $31\%$ of children and adolescents who are affected by CPHC, depending on the age range and specific diseases included [2,4], with a tendency for increasing incidence of several conditions such as diabetes and cancer [2]. In the Austrian Health Behavior in School-aged Children (HBSC) survey of 2018, $19\%$ of adolescents showed a chronic condition, which is an increase compared to 2010 ($16\%$) and 2006 ($14\%$). An increase by age, especially in girls, has been observed in all three survey waves. In girls, $16.6\%$ of 11-year-old adolescents reported a CPHC, while this percentage increased to $24.1\%$ in 17-year-olds. In boys, the prevalence increased from $13.5\%$ in 11-year-old adolescents to $20.2\%$ in 17-year-olds [5,6,7]. These are lower rates compared to data from the United States, where $31\%$ of all US children suffer from a CPHC [8]. Although many people adjust well to a chronic condition, estimates of a psychological comorbidity in this population amount to $20\%$, which is about double compared to healthy young people [9,10,11]. Further population-based studies and reviews confirmed that people with CPHC are at an increased risk for behavioral and mental health problems [4,12,13]. However, there is a relative dearth of focus on the impact of CPHC on mental health in children and adolescents [2,14]. Cross-sectional associations of CPHC with a preponderance of internalizing disorders, especially anxiety and depression, compared to externalizing disorders have been previously reported, while few longitudinal population-based studies [4,13,15,16] and meta-analyses [14,17] exist. Early age at onset predicted externalizing problems [16]; other surveys state that illness-specificity or gender is associated with elevations in externalizing problems [17]. Overall, small sample sizes, a focus on clinical settings, and a lack of adolescent self-reports have been criticized in previous studies [16]. Existing meta-analyses highlight the need for a specific focus on younger populations [14], while a differentiation between childhood and adolescence is necessary, as it is assumed that poor mental health in this vulnerable population might be associated with CPHC, and a chronic disease might disrupt normal developmental milestones of this period, such as increased autonomy from parents [18]. Factors that contribute to the elevated risk of mental health problems in this population are manifold and may include biological, psychological, and social aspects. Common stressors in CPHC such as treatment regimens and medical monitoring place significant demands on families, increase stress not only in the child but also among parents, and may lead to overdependence in the parent–child relationship [19]. These illness-related demands may prevent children from engaging in social activities that would strengthen friendships and self-development. Illness-related demands may even have a more detrimental impact during adolescent years. The adolescent period is viewed as a critical period of social development and identity formation. Existing evidence suggests that bio-psychosocial changes in adolescence (including pubertal hormones associated with changes in the reward and stress systems) may have a substantial impact on the adjustment of adolescents to their CPHC. They may see the demands and restrictions imposed by their treatment regimen as a barrier to this normative experimentation and separation from parents [1]. They are at risk of delayed attainment of developmental milestones compared to their peers [20]. Trying to appear as “normal” is a major focus of adolescents with CPHC [21], potentially leading to more negative illness cognitions, especially in conditions with physical manifestations of the illness (i.e., insulin pumps in diabetes). Such aspects may put these adolescents more at risk of experiencing victimization during a period of heightened social development. Increased levels of peer victimization have consistently been reported [22]. Contemporary theories view CPHC as a stressor in early development and as an additional barrier to self-esteem and social development in adolescence [2]. Furthermore, mental illness is viewed as an outcome of predisposing and precipitating stressors; however, evidence from epidemiological studies is contradictory [15]. Mental health issues are often neglected in medical care. Adolescents with CPHC are often not systematically screened for mental health problems, and referral to mental health care often fails [23,24]. Indeed, the Lancet series on Global Mental Health concluded that mental health should be incorporated into all aspects of health [2]. Thus, analyzing the prevalence of behavioral problems and mental health risks of children and adolescents with a CPHC helps to understand psychosocial consequences and provides information on who should be screened for mental health problems and the need for prevention in this population [17]. Moreover, an in-depth investigation of which sociodemographic and disease-specific factors contribute to an increased risk for mental health problems in children and adolescents with CPHC is of high importance for the planning of targeted prevention efforts. Although associated with mental health, the concept of health-related quality of life (HrQoL) can also be regarded as a highly relevant outcome variable for individuals with CPHC. HrQoL is seen as a “multidimensional construct covering physical, emotional, mental, social, and behavioral components of well-being” (p. 295) and thus provides important information about how an individual copes with everyday life [25]. All the aforementioned aspects discussed in relation with an elevated risk for mental health problems in young people with CPHC (including self-perception, parent-child relation, social relations with peers, and school environment) are also considered in current HrQoL concepts [26]. Indeed, the existing research suggests that HrQoL and psychosocial functioning might be impaired in adolescents with CPHC [27]. However, there is also evidence that some affected adolescents show an impaired HrQoL while others do not, depending on various factors, such as resilience, personality factors, and family support [28]. Maintaining a good quality of life despite the adversities associated with CPHC may be one of the key goals in this population. Thus, investigating the question of who can maintain a high HrQoL and which factors contribute to an impaired HrQoL is highly relevant, also with regard to the development of targeted prevention initiatives. The Mental Health in Austrian Teenagers (MHAT) study is the first large epidemiological study collecting data on mental health in a representative national sample of adolescents aged 10–18 years in Austria. This study also aims to assess the prevalence of CPHC in the adolescent population, determining comorbid mental health problems in adolescents with and without chronic conditions and associated HrQoL. Moreover, risk factors for developing mental health problems in adolescents with chronic conditions should be identified. Therefore, the aims of our study are [1] to test whether adolescents with CPHC obtained from a representative population survey have higher levels of internalizing and externalizing mental health problems compared to adolescents without CPHC; [2] to assess correlates with elevated mental health risks in the population of adolescents with CPHC including sociodemographic characteristics, disease specific characteristics, chronic diseases in the family, and stress-full life events, and [3] to assess whether a CPHC per se or in combination with mental health problems has impact on several HrQoL domains, including self-perception, family relations, peer-group relations, school performance, and social acceptance. At the European level, the current study is one of the largest population-based surveys on this topic and thus provides valuable insights into the impairment in mental health and HrQoL as well as associated factors that may further guide the development of preventive efforts for children and adolescents with CPHC. ## 2.1. Participants and Recruitment In this study, we used data from the ‘Mental Health in Austrian Teenagers’ (MHAT)-study, an epidemiological survey that aimed to obtain the prevalence of mental health problems in a large representative sample of Austrian adolescents aged 10 to 18 years. The sample was recruited via schools including all school types in all regions of Austria. First, all secondary schools in Austria were informed about the study and asked to participate. Of the schools willing to participate ($$n = 261$$), school classes of the 5th, 7th, 9th, and 11th grade were randomly selected for this study (maximum of 2 classes per school). The selection of classes was stratified by school type and region, resulting in a selection representative for the Austrian landscape of schools. Subsequently, all students within the selected classes were invited to participate, informed about the procedure, and asked to provide informed consent. Inclusion criteria included [1] to be student of a selected class, [2] provision of written informed consent, and [3] to have sufficient German language skills to understand the questionnaire items. Written informed consent was collected from all participants and legal representatives prior to the inclusion in the study. Once the informed consent forms were collected, the participants completed a questionnaire battery to assess the relevant outcome variables (see below). The questionnaire was either completed in a paper-and-pencil or online format, based on the technical equipment of schools, during a school lesson of 50 min. Equivalence between the paper-and-pencil and online questionnaire formats was confirmed [29]. The whole procedure was moderated by a class teacher who received detailed instructions on how to moderate the assessment. The feasibility of this procedure for the teachers was previously checked in a pilot study [30]. Finally, a total of 3610 adolescents from the school sample participated in this study. The response rate was $47.3\%$; the most common reason for non-response was failure to bring signed parental consent to school on the day of data collection. A total of 129 individuals did not provide data on chronic diseases; thus, a sample of 3481 was finally included in the analysis. Ethical approval was obtained from the Ethics Committee of the Medical University of Vienna (#$\frac{1134}{2013}$). More details about the sampling, recruitment strategy, and procedures are published in Zeiler et al. [ 31] and Wagner et al. [ 32], both of which are open-access. ## 2.2.1. Sociodemographic Information and Chronic Physical Health Conditions (CPHC) Apart from sociodemographic information (e.g., sex, age, migration background, socioeconomic status assessed with the Family Affluence Scale [33], living situation, diagnosed somatic and psychiatric disorders in the family) that were used to describe the sample, data on CPHC, mental health problems, and quality of life were included. CPHC were self-reported by the adolescents as a yes/no answer to the question, “Do you suffer from a physical illness or handicap diagnosed by a medical doctor?” The following categories were specified and checked when applicable: diabetes, hypertonia, arthritis, paralysis, asthma/chronic obstructive bronchitis, epilepsy, migraine/headache, orthopedic disease, thyroid disease, cancer, heart disease, gastric disease, allergy, physical handicap, or others (with the possibility of specification). We did not include mental health issues or obesity. Furthermore, illness onset (age of illness onset in years), as well as the necessity of regular medication intake due to the CPHC (yes/no) and regular medical visits (yes/no), were assessed. Allergies were rated as CPHC only when regular medication intake or regular medical visits were necessary. Chronic health conditions (both physical and mental) of other family members (parents, sisters) were collected in the same manner. Additionally, adolescents rated their school performance on a 4-point scale (very good to below average). ## 2.2.2. Mental Health Problems The Youth Self-Report (YSR: [34], German version: [35]), a widely used mental health screening questionnaire [36] to assess emotional and behavioral problems, was used to obtain the prevalence of adolescents at risk for mental health problems. The 103 problem items, measuring behavioral and emotional problems on a three-point scale (0 = not true, 1 = somewhat or sometimes true, 2 = very true or often true) over a six-month time period, are summed into eight syndrome scales (withdrawn, somatic complaints, anxious/depressed, social problems, thought problems, attention problems, delinquent behavior, and aggressive behavior) and three broadband scales (total problem score, internalizing problems, externalizing problems). For the broadband scales, good internal consistencies are reported (Cronbach’s alpha > 0.86); for the syndrome scales, Cronbach’s alpha is 0.56–0.86. YSR ratings are summed per scale and raw-scores are transferred into T-scores using German norm data. Higher scores indicate higher levels of mental health problems. As described in the manual, cut-off scores of T > 63 for the broadband scales and T > 69 for the syndrome scales are used to define clinically relevant high-risk cases. ## 2.2.3. Health-Related Quality of Life (HrQoL) The KIDSCREEN questionnaire [37] was used to obtain several domains of HrQoL, including a global measure of HrQoL (Kidscreen-10), self-perception, parent relations and home life, social support and peers, school environment, and bullying (i.e., social acceptance). This measure can serve as a proxy for psychosocial impairment in different domains. Items are rated on a 5-point Likert scale. Internal consistencies were good for all used dimensions (Cronbach alphas of 0.77–0.89). Raw scores were transferred into T-Scores according to the available German normative data. ## 2.3. Data Analyses The statistical analysis was performed with IBM SPSS Statistics 27.0 (IBM Corporation, Armonk, NY, USA, 2020) A global significance level of α = 0.05 was set for the statistical tests. First, the prevalence of CPHC and several groups of CPHC was calculated for the entire sample. Inverse probability weighting by gender and age group was used to adjust for deviations from the sampling plan, which reflected the *Austrian* general population of adolescents. Additionally, prevalence figures were calculated separately for gender. Next, we compared sociodemographic characteristics between adolescents with vs. without a CPHC using chi² tests. Furthermore, we analyzed whether the group of adolescents with a CPHC differ from those without a CPHC regarding the percentage of clinically relevant mental health problems (YSR total and syndrome scales) using chi² tests and regarding YSR scores using t-tests. To account for multiple testing, the significance level of tests for differences in the YSR syndrome scales was Bonferroni-corrected (8-syndrome scale, adjusted α = 0.006). Moreover, we conducted univariate logistic regressions to predict clinically relevant mental health problems in the sample of adolescents with a CPHC. In this analysis, clinically relevant mental health problems were defined as scoring above the clinical cut-off in at least one of the YSR broadband or syndrome scales. We considered a wide range of sociodemographic variables (gender, age group, family status, migration background, socioeconomic status, place of residence, parental employment status), potentially stressful life events (chronic or psychiatric disorders in the family, any burdensome of traumatic life event), and disease-specific variables (age of onset, number of CPHCs, necessity of regular medical checks or medication intake due to the chronic disorder) as potential predictors. Potential predictors with $p \leq 0.10$ in the univariate analyses were further included in a multivariate logistic regression model. Finally, we conducted general linear models to analyze group differences in HrQoL scores between adolescents with a CPHC and a comorbid mental health problem, adolescents with a CPHC but without a mental health problem, and healthy individuals without a CPHC or mental health problem. Group differences in HrQoL domains were tested on a Bonferroni-adjusted significance level of α = 0.008. ## 3.1. Prevalence of Chronic Physical Health Conditions Overall, $8.3\%$ [$95\%$CI: 7.4; 9.2] of the adolescents reported any CPHC, with a slight preponderance of girls ($9.4\%$, [$95\%$CI: $8.1\%$; $10.7\%$]) compared to boys ($7.1\%$, [$95\%$CI: $5.8\%$, 8.44]). The highest rates were assessed for orthopedic problems ($1.9\%$) and asthma ($1.9\%$), followed by allergies ($1.8\%$) and headaches including migraine ($1.4\%$). For orthopedic problems and migraine, the prevalence for girls was about twice as high than for boys. For all other conditions, the prevalence was below $1\%$ (Table 1). A percentage of $22.5\%$ suffered from more than one CPHC; $33.7\%$ of those with a CPHC reported regular medication intake and $39.7\%$ the need for regular medical visits. The mean age of onset was 7.05 years (SD = 5.61; range 0–12), and the mean duration of illness was 8.23 years (SD = 5.37; range 3–12). Older children were more often affected than younger children ($p \leq 0.001$). Moreover, adolescents with a CPHC reported a higher percentage of having a parent or sibling also suffering from a CPHC ($43.4\%$ vs. $12.6\%$, $p \leq 0.001$) or psychiatric disorder ($7.3\%$ vs. $4.0\%$, $p \leq 0.001$) as well as deteriorated school performance ($$p \leq 0.034$$, Table 2). No differences were reported for SES, migration background, residency, family status, or parental employment (Table 2). ## 3.2. Prevalence of Mental Health Risk in Adolescents with and without Chronic Physical Health Conditions Clinically relevant YSR total problem scores and internalizing problems were almost twice as high in the group with CPHC ($29.4\%$ and $31.7\%$) compared to adolescents without a CPHC ($14.9\%$ and $16.3\%$; both p-values < 0.001). Clinically relevant externalizing problems were also significantly more prevalent in adolescents with a CPHC ($11.9\%$ vs. $7.1\%$; $$p \leq 0.003$$). Regarding YSR syndrome scales, the prevalence of somatic complaints was almost threefold ($14.2\%$ vs. $5.8\%$, $p \leq 0.001$), and anxiety and depression symptoms were about twice as high in adolescents with a CPHC ($8.9\%$ vs. $4.1\%$; $$p \leq 0.001$$). Clinically relevant social problems were about twice as prevalent in the group with a CPHC ($4.3\%$ compared to the adolescents without CPHC ($1.9\%$, $$p \leq 0.006$$)). Social withdrawal, thought problems, attention problems, dissocial behavior, and aggressive behavior did not significantly differ between groups (see Figure 1). When analyzing YSR scores, adolescents with CPHC had significantly higher levels of mental health problems in all domains (all p-values < 0.001), while the effect sizes were in the low-to-medium range (see Supplementary Table S1 for details.) ## 3.3. Associated Variables with Mental Health Problems in Chronic Physical Health Conditions We aimed to identify psychosocial variables associated with mental health problems in the group of adolescents with CPHC. Univariate analyses identified psychiatric disorders of a parent or sibling ($$p \leq 0.050$$), any traumatic life event ($$p \leq 0.001$$), and regular medication intake due to the CPHC ($$p \leq 0.001$$) as associated factors for mental health problems in adolescents with a CPHC (Table S2). Moreover, the number of CPHCs tended to be associated with mental health problems ($$p \leq 0.089$$) and was therefore included in the multivariate model. In the multivariate model, any traumatic life event ($$p \leq 0.002$$) and the need for regular medication intake ($$p \leq 0.001$$) significantly predicted clinically relevant mental health problems in adolescents with a CPHC (Table 3). The omnibus model test yielded a significant result (chi² [5] = 31.489, $p \leq 0.001$; Cox–Snell R² = 0.104, Nagelkerke R2 = 0.143). ## 3.4. Health Related Quality of Life in Adolescents with Chronic Physical Health Conditions and Mental Health Problems vs. without Mental Health Problems and Healthy Controls Adolescents with a CPHC and comorbid clinically relevant mental health problems had by far the lowest HrQoL scores in all domains and strongly differed from chronically ill adolescents without mental health problems and healthy adolescents (Table 4). Regarding overall HrQoL, as well as the self-perception and school environment domains, adolescents with a CPHC but without mental health problems had significantly lower scores compared to healthy adolescents, whereby mean differences were low. Regarding the parent relations and home life, social support and peers, and bullying subscales, chronically ill adolescents without mental health problems did not differ from healthy adolescents. ## 4. Discussion In our representative sample of adolescents in Austria, we found that clinically relevant mental health problems were almost twice as high in adolescents with chronic conditions ($29\%$ vs. $15\%$), especially for internalizing syndromes such as anxiety and depression ($9\%$ vs. $4\%$) and social problems ($4\%$ vs. $2\%$). Potentially traumatizing life events and regular medication intake were related to mental health problems in this population. This finding is in line with the results of systematic reviews confirming higher prevalence rates of anxiety disorders in youths with CPHC compared to the general population [38]. Associations between mental disorders and CPHC were reported in $35\%$ of adolescents in a representative cohort in the US [39]. The combination of physical disorders and anxiety disorders occurred in $21\%$ of the population. Moreover, some evidence for the association between anxiety and adverse disease-related outcomes has been revealed for some of the CPHCs (asthma and inflammatory bowel disease), whereas for others, anxiety was associated with worse as well as better treatment adherence (diabetes) [38]. However, in diabetes, internalizing disorders were only elevated in adolescents who were manipulating their insulin dose, whereas rates of psychiatric comorbidity in adolescents without management problems were comparable to adolescents without a chronic illness [40]. The experience of anxiety is associated with poor prognosis if untreated, as well as with the development of other mental health problems and psychosocial impairments such as deteriorated academic achievement and peer relationships [38]. Higher levels of depression have been found in adolescents with CPHC, with larger effect sizes in studies with a higher proportion of girls [17,41]. Reasons for elevated depression rates have been attributed to the burden of the CPHC (such as symptom exacerbation, daily care regimen) that in turn can affect social relationships, which are crucial for positive development, especially in adolescence [21]. Long-term outcome studies have shown that this comorbidity on the one hand influenced treatment outcome of the illness (such as decreased metabolic control, treatment adherence increased hospitalization in diabetes), and on the other hand affected quality of life, disability, and pain from other diseases (such as heart disease, arthritis) [42]. In adults, comorbidity of a CPHC with depression increased functional disability and absenteeism from work independent from the illness type [43]. Our results add to these findings and show that having a CPHC can lead to a deteriorated school performance, which might have effects on work performance in adulthood. The co-occurrence of mental and physical conditions could have synergistic effects on disability through underlying pathophysiology associated with the functioning of the autonomous nervous system (sympathetic–adrenal–medullary system) and the neuroendocrine system (hypothalamic–pituitary–adrenocortical or HPA axis). Disturbances in both systems have been associated with anxiety and depression and with a range of physical disorders mediated by the cumulative burden of chronic somatic and mental health disease [44]. Other mechanisms include the possibility that depression may exacerbate the disabling effect of a CPHC through its influence on treatment adherence and health behaviors. Moreover, depression may interfere with adjustment to physical conditions. Finally, it is possible that mental comorbidity is a marker of physical condition severity [44]. In summary, there seems to be a vicious cycle that starts with the burden of illness, potentially leading to mental health problems, which in turn has a negative effect on treatment outcome and deteriorates the CPHC, leading to an even higher burden of illness that is associated with worse quality of life and school/work performance. Therefore, it is crucial to support adolescents with CPHC from the time of diagnosis with psychological interventions. Illness acceptance and coping with the CPHC and prevention of mental health problems can be fostered. For those already suffering from a co-morbidity of physical and mental condition, psychotherapeutic interventions should be provided to disrupt this vicious circle. A proactive discussion about mental health at the pediatric hospital in charge of the child and reference to appropriate mental health care services are preferred by parents of children with CPHC [45]. The application of motivational interviewing techniques might be useful to foster psychotherapy uptake [24]. Especially for adolescents, Internet or mobile-based interventions might also be feasible [46]. There is evidence that the COVID-19 pandemic may have further increased mental health problems (particularly depression, anxiety, and stress symptoms) in children and adolescents with a CPHC [47,48], which underlies the current importance of mental health care interventions in this population. In our study, regular medication intake and the presence of a potentially traumatizing life event were related to mental health problems with a more than twofold and threefold increase in risk, respectively. Traumatic life events covered physical and sexual abuse within the family and bullying at school. It is a well-known fact that childhood trauma, especially during key periods of CNS development and maturation, increase the vulnerability for developing mental health problems such as depression, anxiety, post-traumatic stress disorder, substance use disorders, personality disorders, and schizophrenia. The interaction between biological and psychosocial risk factors increase the risk for development of psychiatric disorders [49]. It was previously shown in an adult sample that the history of interpersonal trauma exposure is associated with anxiety symptoms, depressive symptoms, increased alcohol use (i.e., frequency and quantity), and trauma-related distress [50]. Furthermore, anxiety and mood disorders tend to persist into adulthood if untreated [51]. Hence, low-level access to therapeutic and psychological interventions for trauma is needed in order to prevent additional mental health problems in this vulnerable population [52]. The need for regular medication intake may be an indicator for the severity of CPHC, elevating the burden of disease and therefore the risk for mental health problems and psychological distress [53]. One of our key findings is that HrQoL in adolescents with a physical condition but without a comorbid mental health problem only marginally differed from healthy adolescents. However, having an additional mental health problem in chronically ill patients was associated with distinct deterioration of HrQoL in all domains, including self-perception, parent relation, peer relation, school environment, and bullying (i.e., social acceptance). Self-perception is part of the multidimensional construct of the self-concept that comprises global evaluations of the self, such as self-esteem and domain-specific perceptions such as competence and appearance. Results of a meta-analysis have been inconsistent, showing both lower and equal self-esteem in children and adolescents with and without chronic diseases [54]. Our results add to these findings by showing that mental health problems in adolescents with CPHC are associated with deteriorated self-perception. Heterogeneous evidence has been found for parent–child relationships in children and adolescents with CPHC. While on the one hand, lower emotional warmth and higher levels of control and overprotection were found in families with a child that has a physical illness, higher levels of neglectful parenting and both higher and lower levels of authoritative parenting style were also observed compared to families with healthy children [55]. We found no differences with regards to parent relation between adolescents with and without a chronic condition, only in the subgroup with a double burden of mental problems and chronic illness. This finding adds to previous findings and may explain conflicting results. Parental responsiveness (warmth and support) plays a crucial role in psychological development in general and in the adaption to the physical illness specifically and seems to be impaired in the group with the double burden of suffering from a chronic illness and a mental health problem. High expressed emotion in interpersonal interactions is a well-known maladaptive behavior and a factor contributing to the maintenance of psychiatric disorders [56]. Hence, psychological support should also be provided for parents when needed. A supportive family environment providing support when needed and guaranteeing autonomy when possible in the period of adolescence should be a further aim in psychosocial support in this population. Psychosocial care requirements for children and adolescents are integrated in clinical practice guidelines for some chronic physical conditions such as type 1 diabetes [57], while others remain in development [58]. Moreover, peer relations, social acceptance (as opposed to bullying), and school environment/school performance are markedly deteriorated in the group with a double burden of mental health problems and a chronic illness. The Avon Longitudinal Study of Parents and Children exploring mediating factors of the co-occurrence of mental illness in children and adolescence suggests that a chronic illness may impact functioning and social development in early adolescence and consequently may lead to the development of mental illness. In particular, school absenteeism and peer victimization increase this risk over time [15]. Peer victimization and school disconnectedness have been associated with mental health problems rather than with CPHC [59]. Interventions fostering positive peer relationships and opportunities for social inclusion are necessary to avoid bullying and problems at school. International surveys revealed a decreased HrQoL in children and adolescents with chronic conditions and mental health problems [60,61,62,63]. The German KIGGS study highlighted youths with neuro-dermatitis, obesity, and mental health problems as at-risk groups for deteriorated HrQoL and as target populations for prevention programs [42]. Both CPHC and mental conditions need to be targeted for treatment to reduce their possible joint disability burden [44]. For future research, a broad range of psychosocial risk factors for the comorbidity of chronic physical health conditions and mental health problems should be analyzed in prospective long-term cohort studies so that causal relations can be drawn. This study has the following limitations. First, the response rate of $47.3\%$ is low. To detect potential differences between participating and non-participating adolescents, we used teachers’ ratings for all adolescents [32]. Non-participating students showed slightly higher school absenteeism and more concentration problems, were less socially integrated and more socially withdrawn at school, and showed more behavioral problems. However, effect sizes were very low, and thus we expect a small response bias only. Second, the cross-sectional design does not allow causal conclusions for predictor analyses, and potential predictors have to be interpreted with caution. Rather, the findings from this study should be primarily interpreted in terms of correlations. Third, we exclusively used adolescent self-reports to assess CPHC and mental health problems. While the reliance on youth information is useful for internalizing problems, there are other problem areas where parent or teacher information might be more valid (i.e., such as externalizing problems, attention problems, or family SES). Thus, externalizing problems might be underreported in both populations. Moreover, whether mental health problems lead to deteriorated HrQoL aspects or deteriorated HrQol aspects to mental health problems cannot be answered. Furthermore, the validity and reliability of CPHC diagnoses can not be regarded as high as when assessed in a clinical interview. Due to the low number of cases for specific CPHC, we were not able to answer whether the risk for mental health problems is elevated in adolescents with specific CPHC. ## 5. Conclusions The results from the present study have the following implications: First, there is a high need for identifying mental health problems in adolescents with CPHC, and therefore, screening instruments should be implemented in routine service care in pediatric clinics. This seems all the more important, as the COVID-19 crisis might have further increased mental health problems in this population. Second, a mental health screening in this population should not only include the broad assessment of symptoms of psychiatric disorders, but also the assessment of significant life events in the past and adverse psychosocial circumstances (e.g., physical or mental health disorders in other family members), as these factors seem to be substantially associated with mental health. Third, early interventions for those positively screened for mental health problems or with deteriorated quality of life should be provided in order to prevent further deterioration in well-being with all psychosocial consequences (educational and work performance). Hence, the availability of multidisciplinary care is important. A stepped-care approach for children and adolescents with chronic physical health conditions also seems important. Such an approach should span the whole spectrum from universal prevention for those with currently no mental health problems to selected prevention for those with well-known risk factors for mental health problems. Thus, those with mental health problems in the early stage could receive preventative treatment and those with more severe psychiatric symptoms could be referred to psychotherapeutic treatment. The use of online support services and e-health approaches might be particularly attractive for young people, ranging from appointment and medication reminders to delivering interventions such as online cognitive therapy and self-management strategies [2,64]. Indeed, the COVID-19 pandemic was also regarded as a catalyst for digital health interventions, and this included the population of adolescents with chronic conditions [65]. Fourth, apart from mental health problems, HrQoL should be a key target variable for evaluating the effectiveness of (preventive) interventions in this population. Implementing targeted risk-reduction strategies in clinical practice should not only reduce mental disorders in youths with a chronic physical health condition but also create optimal conditions for the best possible quality of life [64]. ## References 1. 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--- title: Discriminating Healthy Optic Discs and Visible Optic Disc Drusen on Fundus Autofluorescence and Color Fundus Photography Using Deep Learning—A Pilot Study authors: - Raphael Diener - Jost Lennart Lauermann - Nicole Eter - Maximilian Treder journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003756 doi: 10.3390/jcm12051951 license: CC BY 4.0 --- # Discriminating Healthy Optic Discs and Visible Optic Disc Drusen on Fundus Autofluorescence and Color Fundus Photography Using Deep Learning—A Pilot Study ## Abstract The aim of this study was to use deep learning based on a deep convolutional neural network (DCNN) for automated image classification of healthy optic discs (OD) and visible optic disc drusen (ODD) on fundus autofluorescence (FAF) and color fundus photography (CFP). In this study, a total of 400 FAF and CFP images of patients with ODD and healthy controls were used. A pre-trained multi-layer Deep Convolutional Neural Network (DCNN) was trained and validated independently on FAF and CFP images. Training and validation accuracy and cross-entropy were recorded. *Both* generated DCNN classifiers were tested with 40 FAF and CFP images (20 ODD and 20 controls). After the repetition of 1000 training cycles, the training accuracy was $100\%$, the validation accuracy was $92\%$ (CFP) and $96\%$ (FAF), respectively. The cross-entropy was 0.04 (CFP) and 0.15 (FAF). The sensitivity, specificity, and accuracy of the DCNN for classification of FAF images was $100\%$. For the DCNN used to identify ODD on color fundus photographs, sensitivity was $85\%$, specificity $100\%$, and accuracy $92.5\%$. Differentiation between healthy controls and ODD on CFP and FAF images was possible with high specificity and sensitivity using a deep learning approach. ## 1. Introduction Optic disc drusen (ODD) are acellular deposits that are located in the optic nerve head of $0.3\%$ to $2.0\%$ of the population [1,2]. In children and younger individuals, ODD are mostly buried deep in the optic nerve head [3,4]. They can be diagnosed using various imaging techniques, such as B-scan ultrasonography or, more recently, swept source (SS) or enhanced depth imaging (EDI) optical coherence tomography (OCT) [5,6]. Most of these cases are asymptomatic [7]. Due to an increase in drusen number, drusen growth or age-related thinning of the overlying retinal nerve fiber layer, ODD become visible with age and can, therefore, be detected on color fundus photography (CFP), fundus autofluorescence (FAF), and ophthalmoscopy [7]. Visible ODD are associated with visual field defects in up to $87\%$ of cases [2,8,9,10]. Consequently, they are associated with high clinical relevance for visual function [11]. Because of the widespread use of multimodal imaging technologies as well as the digital fundus cameras for eye screening programs, there is an increasing amount of data to be analyzed by ophthalmologists, and therefore, a remarkable interest in the automated screening for optic nerve pathologies, such as ODD. Artificial intelligence using deep learning (DL), a subtype of machine learning (ML), is used to solve complex and large-scale problems, such as speech and image recognition and language processing. The three most popular DL models are recurrent neural networks (RNNs), generative adversarial networks (GANs), and convolution neural networks (CNNs), which are particularly well suited for different tasks depending on their architecture. RNNs are widely used in natural language processing and speech recognition tasks, where the input data are sequential in nature, such as text or speech. They use feedback connections that allow previous outputs to be used as inputs for subsequent processing, enabling the network to persist information across multiple steps and analyze complex dependencies in the data [12]. GANs have been applied to generative modeling tasks, such as image generation. They consist of two parts, a generator and a discriminator, that compete with each other to generate new data samples that are indistinguishable from real data [12]. CNNs are designed specifically for image classification tasks and are particularly well suited for recognizing patterns and features in images and have revolutionized data processing in medicine, especially in image-centric disciplines [12], such as Dermatology [13], Radiology [14], Pathology [15], and Ophthalmology [12,16]. In this context, CNNs have already been successfully used for automated image analysis using color fundus images for a number of ophthalmologic diseases with high prevalence, including glaucoma [17], diabetic retinopathy [18], and age-related macular degeneration [19]. ML and DL algorithms have several inherent limitations, including the need for very large, accurate datasets for learning. To overcome this limitation, transfer learning, which uses an already pre-trained deep learning algorithm can be used [19,20,21]. The aim of this study was to evaluate the use of a pre-trained CNN for the automated classification of visible ODD and healthy optic discs on fundus autofluorescence (FAF) and color fundus photography (CFP). ## 2. Materials and Methods This study adhered to the tenets of the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study and the fully anonymized usage of the database. ## 2.1. Patient and Image Selection Patients with a clinical diagnosis of ODD and color fundus photography and fundus autofluorescence image of the optic disc were included in this study. Patients with no evidence of an optic disc pathology as determined by an ophthalmologist were defined as controls. Images were chosen from a database of the Eye Clinics of Muenster University Hospital, compiled between January 2015 and January 2020. A total of 480 CFP and FAF images of the ODD and control group were used. All images were focused on the optic nerve head and were obtained using the same fundus autofluorescence (Spectralis, Heidelberg Engineering, Heidelberg, Germany) and color fundus photography (Visucam 500, Carl Zeiss Meditec AG, Jena, Germany) device. FAF devices produce greyscale images, whereas CFP devices produce Red-Green-Blue (RGB) images. Inclusion criteria were selected in which drusen were visible in FAF as hyperfluorescent material. Images with buried optic disc drusen that were only visible in sonography or OCT were excluded. All images were saved as JPEG files and had an input size of 299 × 299 × 3 pixels. ## 2.2. Deep Learning Training and validation of the DL model (InceptionV3) were performed using TensorFlowTM (Google Inc., Mountain View, CA, USA), which is an open-source software program developed by Google. It provides a high-level interface for designing and training DL models [20,22,23,24,25]. InceptionV3 is a DCNN designed for image classification tasks that was introduced by Szegedy et al. in 2015 [22]. It uses a modular architecture with multiple parallel convolutional paths and a concatenation layer that merges the result. This allows the network to capture both global and local features in the input image. Each layer takes an input and produces an output, which becomes an input to the next processing layer, creating a deep architecture. In each successive layer, the data were represented in an increasingly more abstract way. All layers, with the exception of the last layer, were pre-trained with an ImageNet [26] data set consisting of more than 14 million images of different objects and scenes. InceptionV3 can be fine-tuned for specific image-classification tasks with smaller datasets, which allows for faster and more accurate results. For this study, the last layer was trained with our ophthalmic dataset [27,28]. Two deep learning models were independently trained and validated using 120 FAF photos (ODD: $$n = 60$$; healthy: $$n = 60$$) and 120 CFP images (ODD: $$n = 60$$; healthy: $$n = 60$$) over the course of 1000 training steps (Figure 1). The training and validation accuracy, as well as the cross-entropy, were calculated in each of the training steps to evaluate the effectiveness of both training strategies. Forty FAF and 40 CFP photos (OOD: $$n = 20$$, healthy: $$n = 20$$) were used to assess the performance of both the developed DCNN models once the pre-training was completed (FAF and CFP). The 40 FAF and 40 CFP images used for testing were excluded from the dataset before training and validation of the algorithm were performed. The algorithm, therefore, had no access to the test data set during training and validation. Accordingly, the performance of the algorithm could be tested without bias. ## 2.3. Statistics SPSS was used to perform the statistics (IBM SPSS Statistics 23.0; IBM, Armonk, NY, USA). For descriptive statistics, Prism was utilized (Prism 7, GraphPad Software, Inc. San Diego, CA, USA). Data administration was carried out using Microsoft Excel (Microsoft® Excel® for Mac 2011, 14.6.2; Microsoft®, Redmond, WA, USA). Mean differences in the probability scores of the two classifiers were verified with Mann–Whitney U-test for independent samples. The level of significance was defined as $p \leq 0.05.$ Using a 2 × 2 table, the sensitivity, specificity, and accuracy were computed. Both the DL procedure and the testing were repeated with the same data set to enable the evaluation of the precision of the repeatability of the ODD testing score. Coefficients of variation were computed to evaluate the precision. Bland–Altman plots were employed to evaluate repeatability. ## 3.1. Performance of the Training Process Both classifiers for FAF and CFP images had a training accuracy of $100\%$ after 1000 performed training steps. The validation accuracy of the classifier for CFP and FAF images was $92\%$ and $96\%$, respectively. There were no notable differences in the course of the curves of the training and the validation accuracy. The cross-entropy of both classifiers constantly decreased and was 0.15 (CFP images) and 0.04 (FAF images) after completion of the training process, as seen in Figure 2. ## 3.2. Testing of the Classifiers All FAF images of both ODD and healthy test patients were correctly diagnosed by the classifier trained on this image modality. Consequently, sensitivity, specificity, and accuracy of this classifier were $100\%$, as shown in Table 1. The mean ODD testing scores for the ODD testing group’s photos were 0.91 ± 0.15, and 0.05 ± 0.07 for the healthy control group’s images. The mean healthy testing scores for the ODD testing group’s images were 0.09 ± 0.15, and for the healthy control group’s images, they were 0.95 ± 0.07. All CFP images of the healthy test group were correctly diagnosed by the classifier whose last layer was trained with 120 CFP images. Three CFP images of patients with ODD were misdiagnosed by this classifier. Therefore, this classifier had a sensitivity of $85\%$, a specificity of $100\%$ and an accuracy of $92.5\%$, as shown in Table 2. The mean ODD testing scores were 0.79 ± 0.25 for the images in the ODD testing group and 0.10 ± 0.12 in the healthy control group. The mean healthy testing scores were 0.09 ± 0.15 for the images in the ODD testing group and 0.90 ± 0.12 for the healthy control group. The difference between the mean testing scores for the differentiation of diseased and healthy optic discs was statistically significant ($p \leq 0.001$) for both FAF and CFP images. ## 3.3. Repeatability and Precision The initial computed testing scores and the scores of the repeated testing had a mean coefficient of variation of 0.22 ± $0.59\%$ (FAF) and 3.73 ± $5.83\%$ (CFP), respectively, indicating both classifiers had good precision. Between the two tests, the mean difference had absolute values of 0.001 ± 0.005 (FAF) and 0.006 ± 0.07 (CFP). The Bland–Altman plots indicate high values of repeatability for both classifiers. The results for the classifier using FAF images were even superior to that using CFP images, as seen in Figure 3. ## 4. Discussion Machine learning (ML) and deep learning (DL) have increased the possibilities for automatic image analysis in ophthalmology. DL has been successfully used for the automatic detection of diseases with high prevalence, such as diabetic retinopathy [18,29], age-related macular degeneration [27,30], and glaucoma [17], using different image modalities. In this context, it seems plausible to extend the use of DL to other, less frequent diseases, like optic disc drusen (ODD). Our results show that DL is a suitable approach to facilitate image analysis in this rare diagnosis. Many of the DL studies mentioned above achieved a sensitivity and specificity of more than $90\%$, but in most of them, thousands of images were necessary to train the algorithms [17,18,27]. Despite the small amount of data used due to the low prevalence of ODD, especially when compared to widespread diseases, the classifiers used in this study achieved an accuracy of $100\%$ and $92.5\%$, respectively. Additionally, this approach has already been successfully applied in pre-published work [27,28,31]. Shah et al. were able to show in a preliminary study that DL can be effectively used with a small amount of data for training to classify normal OCT scans and those from patients with Stargardt’s disease at different stages and, therefore, characteristic of the disease [32]. Training and testing data were composed of 749 OCT B-scans of only 93 individuals. Similar to our study, a CNN architecture pre-trained with the ImageNet dataset was used and achieved sensitivity and specificity levels of over $95\%$ [26]. In our study, an even smaller amount of FAF and CFP images was used, achieving similar results with a sensitivity of $100\%$ for both classifiers and a specificity of $100\%$ with fundus autofluorescence and $85\%$ with color fundus imaging. Different aspects could explain why a similar performance of the algorithm was achieved in this study although an even smaller data set was used. First, the use of multiple images of a single eye potentially reduced the diversity within the data set of Shah et al. [ 32]. In our study, only one image of a single eye was used. Second, the use of data from one disease at various stages of Stargardt’s disease leads to a limited ability of the classification model to differentiate images with a milder disease phenotype. In contrast, our study only considered images with superficial drusen. This makes it easier for the algorithm to learn specific aspects of this disease subgroup, although its field of application is limited to a smaller patient collective. In our study, we used FAF and CFP images to analyze ODD because first, superficial ODD visible in FAF have a higher risk of causing a visual field defect compared to buried ODD [11], and second, CFP imaging is a widely used image modality in screening examinations. Thus, the algorithm could be used as s screening tool for visible ODD on color fundus photographs to then initiate further diagnostics, such as performing a visual field examination. Comparing the results of FAF and CFP image analysis, patterns of ODD seemed to be easier to recognize on FAF images for the algorithm. This can be seen in the relatively flatter training accuracy curve in Figure 2 and is an indicator of a higher learning rate. Additionally, the DCNN is able to distinguish more clearly between healthy subjects and ODD on FAF images. All ODD eyes were correctly identified on FAF images, whereas three CFP images were misdiagnosed as being healthy (Figure 4). This may indicate that FAF is superior to CFP in the identification of superficial optic disc drusen. This seems plausible since visible drusen in FAF are clearly distinguishable by autofluorescence [7]. However, RGB images (CFP) are 3-channel color images, while greyscale images (FAF) have only one channel that represents the intensity of the image. When using InceptionV3, the model would expect an input image with the same number of channels as its pre-trained weights. If a grayscale image is fed as an input, it would have to be first converted to an RGP image by repeating the single channel across the three channels. Thus, it could be expected that the DCNN might perform better when given RGB images as input compared to grayscale images. However, if the FAF images contain sufficient information for the task, they may even outperform RGB images, which is the case in our study [33]. Three CFB images were misdiagnosed by the classifier (Figure 4). Due to the black box formation of DCNN the reasons for misdiagnosis of the images by the classifier can only be suspected. However, one reason for this could be that in these three cases, the drusen are not clearly delineated on fundus photographs despite their visibility in fundus autofluorescence. Even though the applicability for FAF images was better, the CFP images analysis also showed promising results. Automated analysis of CFP images will probably play an even more important role in everyday clinical routine. In contrast to FAF, CFP imaging is a widespread procedure in screening, even without symptoms, in many in- and outpatient settings. The increasing usefulness of fundus imaging offers a vast amount of data that clinicians must thoroughly assess quickly. Similar to computer-assisted detection systems created to help radiologists interpret medical pictures, DL methods, as applied in this study, could help radiologists with the diagnosis and treatment of optic disc illnesses [14]. This could increase the usefulness of screening examinations in general and help to ensure that the data collected are actually fully evaluated and a true benefit for the patient can be derived. In a recent study, Milea et al. used a deep learning system to detect papilledema on color fundus photographs using a dataset of 14,341 images. They reached sensitivity levels of $96.4\%$ and specificity of $84.7\%$ [34]. Here, ODD were analyzed as a part of a group of “Disks with Other Abnormalities” and were, therefore, not discussed separately. However, the performance results of the algorithms are comparable [34]. This study was limited by different aspects. First, by training the DCNNs exclusively with visible ODD, the algorithms presented here have questionable relevance to everyday clinical practice. For an ophthalmologist, detecting visible ODD, especially using FAF images, is, in most cases, very simple. Therefore, the high specificity and sensitivity values achieved here are not surprising. In contrast, the detection of buried optic disc drusen and its differentiation from other optic disc pathologies, such as optic disc edema, is both highly clinically significant and challenging. In order to support ophthalmologists in their decision-making based on artificial intelligence in everyday clinical practice, further studies are necessary, including buried optic disc drusen. In this pilot study, however, the primary aim was to detect superficial drusen. The classification of deep ODD and its differentiation from other optic nerve pathologies is planned in a follow-up study. Second, each of our DL classifiers was trained and tested on FAF and CFP images from a single device type. Therefore, the applicability to FAF and CFP images from other devices is unknown. However, we believe that image data from different devices can be used after prior alignment to uniform recording conditions. Third, the image data set for this study was small compared to other AI studies in the field of ophthalmology. However, as explained above, this can also be seen as a strength of our approach since it can be difficult and time-consuming to build up large data pools, especially for rare diseases. Therefore, algorithms that make reliable statements based on smaller data sets offer an exciting perspective. Maybe, the results of our testing will even improve with a higher amount of data. Finally, overfitting is a risk associated with using a small dataset to train a DCNN. This can happen if the model is trained with only a few images or with a large number of training steps. The risk is that the model corresponds too closely to the training data and fails to make reliable predictions on new data. In other words, the model is learning patterns that are unique to the training data but irrelevant to other data. The capacity of the DCNN to detect unseen images decreases with subsequent training steps after an initial improvement. Based on the training and validation accuracy curves, an increasing gap is formed between the training and validation accuracy curves. There were no significant differences in the course of the curves of training and validation accuracy in this study, indicating that neither model is overfitting. ## 5. Conclusions In conclusion, we were able to demonstrate that it is possible to use DL classification models to differentiate between normal FAF and CFP images and those from patients with superficial ODD using a transfer-learning-based DL algorithm. FAF images seem to be superior to CFP images in the diagnostics using our DL approach. 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--- title: Transcriptional analysis links B cells and TERT expression to favorable prognosis in head and neck cancer authors: - Su Xian - Magalie Dosset - Andrea Castro - Hannah Carter - Maurizio Zanetti journal: PNAS Nexus year: 2023 pmcid: PMC10003760 doi: 10.1093/pnasnexus/pgad046 license: CC BY 4.0 --- # Transcriptional analysis links B cells and TERT expression to favorable prognosis in head and neck cancer ## Abstract Telomerase reverse transcriptase (TERT) is a conserved self-tumor antigen overexpressed in ∼$85\%$ of tumor cells and is immunogenic in cancer patients. The effect of TERT expression on the regulation of intratumor adaptive immunity has not yet been investigated. We used RNA sequencing data from The Cancer Genome Atlas (TCGA) in 11 solid tumor types to investigate potential interactions between TERT expression, and B and T cell infiltrate in the tumor microenvironment. We found a positive correlation between TERT expression, B and T cells in four cancer types with the strongest association in head and neck squamous cell carcinoma (HSNCC). In HNSCC a Bhigh/TERThigh signature was associated with improved progression-free survival (PFS) ($$P \leq 0.0048$$). This effect was independent of HPV status and not shared in comparable analysis by other conserved tumor antigens (NYESO1, MUC1, MAGE, and CEA). Bhigh/TERThigh HNSCC tumors also harbored evidence of tertiary lymphoid structure (TLS) such as signatures for germinal center (GC) and switched memory B cells, central memory CD4 and effector memory CD8 T cells. Bhigh/TERThigh HNSCC tumors also showed an up-regulation of genes and pathways related to B and T cell activation, proliferation, migration, and cytotoxicity, while factors associated with immunosuppression and cancer cell invasiveness were down-regulated. In summary, our study uncovers a new association between high TERT expression and high B cell infiltrate in HNSCC, suggesting a potential benefit from therapeutic strategies that invigorate intratumor TERT-mediated T-B cooperation. ## Introduction Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy; it accounts for $90\%$ of all head and neck cancers [1], has a mortality rate of approximately 50–$60\%$ in year one and an overall five-year survival of ∼$50\%$ [2]. Long-term tobacco use, consumption of alcohol, and infection with high-risk types of human papilloma virus (HPV) are considered the main oncogenic drivers [3]. HPV-negative HNSCC patients, which represent the majority of HNSCC tumors, have the worse outcome [4]. The treatment of metastatic, unresectable HNSCC consists of chemotherapy, radiation, and immune checkpoint therapy [5, 6] but only a small fraction of patients benefit from immune checkpoint therapy [7, 8]. In recent years the immunology of HNSCC has received considerable attention. As in most cancer types, a high density of T lymphocyte infiltrate correlates with better clinical outcomes. While the contribution of T cells for durable tumor protection has been extensively studied, the exact role of B cells has not been thoroughly interrogated. B cells are best known for their ability to recognize antigen and produce antibodies, but they can also internalize antigen via the B cell receptor (BCR) serving as antigen-presenting cells (APCs). An initial step of the adaptive immune response is T-B cooperation [9], a twofold process where CD4 T cells are activated by B cells and in turn provide cytokines to B cells to support antibody production and isotype switching. Recent reports have analyzed the antibody response of HNSCC tumor against conserved tumor and HPV antigens, respectively [10, 11], also proposing that B cells in HNSCC tumors are part of tertiary lymphoid structures (TLS), i.e. organized aggregates of various types of immune cells that include B and T cells and dendritic cells (DCs) that resemble follicles in secondary lymphoid organs [12, 13]. TLS are an increasingly common finding in most cancer types and are often linked with better prognosis [13]. HNSCC tumors have a relatively high mutational burden (TMB) compared to other tumor types [14] and significant expression of APOBEC3B in HPV-positive tumors [15]. The AID/APOBEC family of cytidine deaminases is an endogenous source of mutations in many cancers, including HNSCC [16, 17]. In particular, APOBEC3 has been reported to be significantly higher in HPV-positive relative to HPV-negative HNSCC tumors [15]. However, the TMB in HNSCC tumors tends to show no relationship with tumor neoantigen load [18] and the overall response to immune checkpoint inhibitors is modest (13.3–$22\%$) [8], raising the possibility that local adaptive immune responses in HNSCC tumors involve instead conserved tumor antigens [19]. Telomerase reverse transcriptase (TERT) is a component of telomerase, the unique cellular enzyme that synthesizes the tandem 5′-TTAGGG-3′ exonucleotide repeats of telomeric DNA by reverse transcription of its own RNA template [20]. Telomerase confers immortality to cells [21] and is a key hallmark of cancer [22]. It is overexpressed in >$85\%$ of cancer cells and tumors of various histology [23]. Since the discovery that TERT, a self-tumor antigen, is immunogenic in cancer patients [24], numerous studies have shown that TERT can elicit both CD8 [25] and CD4 [26] T cell responses. Furthermore, CD8 and CD4 T cells directed against TERT represent an important component of anticancer immunity (27–29). Finally, we previously showed that a B lymphoblastoid cell line presents endogenous TERT [30], demonstrating that B cells can process and present this self-tumor antigen. Altogether, these factors make TERT a candidate link between B and T cells in a cross-talk to initiate adaptive immunity locally. Here, we used transcriptomic data from The Cancer Genome Atlas (TCGA) to evaluate the prognostic value of TERT and adaptive immune B and T cells in 11 cancer types, including those with accepted HPV pathogenesis and those with prevalent mutations in the TERT promoter region. Compared to Bhigh/TERTlow, a Bhigh/TERThigh tumor profile was significantly associated with favorable clinical outcome for HNSCC, a benefit independent of the tumor HPV status. Importantly, we revealed that the prognosis of patients with Bhigh tumors was not impacted by the amount of other conserved tumor antigens. Although TERT levels did not associate with the abundance of T cell infiltrate and TLS formation, Bhigh/TERThigh tumors had an increased proportion of germinal center (GC) B cells, central memory CD4 T cells, and effector memory CD8 T cells. Compared to the other tumor antigens, Bhigh/TERThigh HNSCC tumors were characterized by a distinct gene expression signature associated with increased B and T cell activation, proliferation, and cytotoxicity. Overall, this study uncovers the singularity of TERT compared to other conserved tumor antigens and the potential importance of a TERT-based B-T cooperation in the generation of an active antitumor immunity providing clinical benefit in HNSCC. The data presented in this report suggest that the Bhigh/TERThigh phenotype is associated with more favorable clinical outcomes suggesting that new approaches leveraging B cells, TERT, or both could be used to reinforce local antitumor immunity. ## TERT expression and adaptive immune cell infiltrate predict survival in HNSCC Here, we analyzed tumor RNA sequencing data from TCGA for 4,535 patients representing 11 solid cancer types: bladder (BLCA), breast (divided into triple negative—TNBC—and non-TNBC), cervical (CESC), colorectal (COAD), glioblastoma (GBM), head and neck (HNSCC), liver (LIHC), rectal (READ), skin (SKCM), and lung (LUAD and LUSC) cancers. We found an association between TERT mRNA expression and adaptive immune B and T cell infiltrates in multiple tumor types. TERT expression positively correlated with infiltration of B and T cells (adaptive immune cells) in non-TNBC, BLCA, SKCM, and LIHC cancers, with the strongest association in HNSCC (FDR < 0.05) (Fig. 1A). By contrast, we found an inverse correlation between TERT expression and adaptive immune cells in LUAD, LUSC, GBM, CESC, COAD, and READ (Fig. 1A). To investigate whether these correlations predict progression-free survival (PFS), a cancer immune score was established based on the infiltration of adaptive immune cells and TERT expression level for each cancer type (Fig. 1B). Specifically, we ranked tumors according to TERT expression or adaptive immune cell infiltrate (B and T cell), scored <$30\%$, 30–$60\%$, and >$70\%$ quantiles as 1 to 3 respectively for each category according to [31], then summed scores to obtain the cancer immune score (TERT adaptive immune score). Tumors with a score ≤3 preferentially displayed low TERT expression and low adaptive immune cell infiltrate, while tumors with a score ≥5 tended to have both high levels of TERT expression and adaptive immune cell infiltrate. Tumors with an intermediate score of 4 tended to have a mixed phenotype, i.e. median expression of both parameters. The distribution of patients according to this score for each cancer type is presented in Fig. 1C. Although there was no clear relationship between this score and patients’ clinical outcome across the cancer types evaluated in this study (Fig. S1), we found a high score to be significantly associated with improved survival in HNSCC (Fig. 1D). A similar trend was observed in non-TNBC but not in TNBC breast cancer nor in the remaining cancer types (Fig. 1D). Thus, elevated TERT expression levels are associated with high adaptive immune cell infiltrate and this association provides survival benefit in HNSCC. Therefore, subsequent analyses were focused on HNSCC. **Fig. 1.:** *Correlation between TERT and T/B cell infiltrate varies across solid cancers and predicts survival. (A) Spearman correlation between TERT mRNA expression and immune cell infiltration signatures across 11 TCGA tumor types (HNSCC, non-TNBC, SKCM, READ, LUAD, LUSC, COAD, TNBC, BLCA, CESC, LIHC, and GBM. BRCA is split into TNBC and non-TNBC). Statistical significance adjusted using the Benjamini–Hochberg method. (B) Development of the TERT immune score using adaptive immune cells and TERT mRNA expression for the 11 cancer types. An ordinal score ranging from 1 ∼ 3 is assigned for adaptive immune cells and TERT, respectively, using quantile cutoffs (score = 1 for quantile < 0.3, score = 2 for quantile between 0.3 and 0.7, score = 3 for quantile above 0.7). The cancer immune score is the sum of the two ordinal scores. See methods for details. (C) Fraction of tumors receiving a given cancer immune score (ranging from 2 ∼ 6) for the 11 tumor types. (D) Forest plot showing the coefficient and 95% CI of the cancer immune score in a Cox proportional hazard model predicting PFS across 11 tumor types. Statistical significance adjusted by the Benjamini–Hochberg method.* A univariate PFS analysis revealed that high tumor infiltration of B cells, CD4 T cells, and CD8 T cells was significantly associated with improved PFS ($P \leq 0.05$), and a similar trend was observed in patients with high TERT expression level ($$P \leq 0.079$$) (Fig. 2A). However, in a multivariable Cox proportional hazard model after adjustment for sex, age, stage, HPV status, and TMB as clinical variables, only B cell infiltrate was found to be an independent marker of increased PFS ($$P \leq 0.02$$), with a strong trend for TERT expression ($$P \leq 0.06$$) (Table 1). **Fig. 2.:** *The combination of high-level TERT and B cells markers is associated with better clinical outcomes in HNSCC. (A) PFS analysis in HNSCC stratified by (from left to right) B cell, CD8 T cell, CD4 T cell signature levels, and TERT mRNA expression. (B) PFS analysis in HNSCC expressing low (blue line) or high (orange line) levels of TERT mRNA expression in (left) Bhigh tumors and (right) Blow tumors. (C) PFS analysis in HNSCC expressing low (blue line) or high (orange line) mRNA expression levels of other common conserved antigens CTAG1B, MUC1, MAGEA3, MAGEA4, and CEACAM5 (from left to right) in Bhigh tumors.* TABLE_PLACEHOLDER:Table 1. Next, we investigated whether combinations of these two variables can refine the prediction of a patient's prognosis: the combination of high TERT expression (TERThigh) with high B cell infiltration (Bhigh) identified a subset of HNSCC patients with favorable outcome ($$n = 49$$; Bhigh/TERThigh group), compared with patients with low TERT expression and high B cells ($$n = 41$$, Bhigh/TERTlow group) (Fig. 2B). Of the 10 additional cancer types examined only non-TNBC showed a significant ($$P \leq 0.044$$) correlation between Bhigh/TERThigh and PFS (Fig. S2). When we compared the Bhigh/TERTlow vs. Blow/TERTlow groups in PFS analysis we found that B cell levels showed no significant difference in survival time ($$P \leq 0.95$$) (Fig. S3). Nor did we observe any significant survival association with B cell levels when restricting the analysis to TERTlow tumors (KM logrank $$P \leq 0.954$$, multivariate Cox PH $$P \leq 0.66$$) (Table S1A, B). Among Bhigh/TERThigh tumors, PFS was independent of tumor mutational burden (TMB) and tumor neoantigen burden in both in TERTlow ($$P \leq 0.70$$ and $$P \leq 0.67$$; Table S1A, B) and TERThigh ($$P \leq 0.75$$ and $$P \leq 0.20$$; Table S1C, D) HNSCC tumors. There was a substantial difference between the Bhigh/TERThigh and Bhigh/TERTlow groups as to the estimated median PFS period. The majority ($75\%$) of Bhigh/TERThigh patients were still alive after ∼3.5 years in contrast to $30\%$ in the Bhigh/TERTlow group ($$P \leq 0.0048$$). The effect on survival was still apparent and significant ($$P \leq 0.0406$$) when splitting the cohort on the median instead. Importantly, TERT expression levels did not influence the outcome of patients with low B cell infiltrate ($$P \leq 0.245$$) (Fig. 2B), suggesting that the presence of B cells in the tumor microenvironment is a necessary complement to TERT overexpression in providing clinical benefit. Of note, benefit by TERT in B high tumors was also observed in non-TNBC breast cancer ($$P \leq 0.044$$) whereas a trend toward the opposite effect on clinical course was found in GBM ($$P \leq 0.165$$) (Fig. S2). The prognostic impact of the Bhigh/TERThigh signature was not influenced by the disease stage. When examined by tumor stages (grouping stage I–II and stage III–IV, respectively the Bhigh/TERThigh signature showed a significant difference in early-stage group ($$P \leq 0.024$$), and a near significant trend in the late-stage group ($$P \leq 0.065$$) (Fig. S4). ## TERT confers a unique survival benefit compared to other conserved tumor antigens We determined whether the association between B cell infiltrate and TERT expression (Bhigh/TERThigh phenotype) was specific or was shared by other conserved tumor antigens previously documented in HNSCC tumors [32]. Noticeably, overexpressed NYESO1 (CTAGB1), MUC1, MAGEA3, MAGEA4, or CEA (CEACAM5) antigens did not correlate with TERT improved PFS of patients with high B cell infiltrate (Fig. 2C), suggesting a selective role of TERT over other common tumor antigens in driving local antitumor immunity. We also performed a multivariable Cox proportional hazard analysis for each antigen independently. With the exception of MAGEA3 that showed a barely significant P-value ($$P \leq 0.05$$), no other conserved tumor antigen reached significance. As to MAGEA3, the effect size was very small (coefficient = −0.01), indicating a very weak effect toward increased survival (Table S2). ## The prognostic value of intratumor Bhigh/TERThigh expression is independent of HPV status The overall prevalence of HPV in HNSCC ranges from 25 to $35\%$ [33, 34]. HPV and its expression have been reported to drive TERT promoter activation [35]. As expected, a significant positive correlation was found between TERT expression and HPV status ($P \leq 0.001$) (Fig. 3A). Fifty percent ($50\%$) of Bhigh/TERThigh patients were HPV-positive vs. ∼$20\%$ in the Bhigh/TERTlow group (odds ratio = 4.13; $$P \leq 0.002$$) (Fig. 3B), consistent with the induction of TERT by the E6 protein expressed in HPV + HNSC tumor cells. To assess whether clinical benefit associated with higher TERT expression was attributable to HPV positivity, we repeated the survival analysis of the HNSCC cohort after removing HPV-positive cases. Surprisingly, the positive impact of TERT expression on favorable PFS persisted ($$P \leq 0.0089$$), suggesting that the benefit of elevated TERT expression in the Bhigh group is independent of HPV status (Fig. 3C). In these tumors, higher TERT expression may be due to promoter mutations or other HPV-independent mechanisms [36]. Of note, although HPV has been considered a factor of good prognosis in HNSCC [37], we did not observe a significant difference in outcome between Bhigh/HPV-positive and Bhigh/HPV-negative patients in this cohort ($$P \leq 0.2324$$) (Fig. 3D). Altogether, these data suggest that TERT up-regulation in HNSCC tumors may not be uniquely driven by HPV positivity, and that other factors may contribute to TERT expression levels in Bhigh tumors. **Fig. 3.:** *The prognostic value of intratumor Bhigh/TERThigh expression is independent of the HPV status. (A) Log2 TPM expression of TERT in HPV + and HPV-samples in HNSCC. (B) Percentage of HPV + samples in Bhigh/TERThigh (n = 52) and Bhigh/TERTlow (n = 41) groups. Fisher's exact test. (C) PFS analysis in HNSCC HPV-negative (HPV-) samples, stratified by Bhigh/TERThigh vs. Bhigh/TERTlow. (D) PFS analysis in Bhigh HNSCC comparing HPV-samples (n = 110) vs. HPV+ samples (n = 46).* ## Bhigh/TERThigh status is associated with increased TLS markers in HNSCC To better define the role of Bhigh/TERThigh status from a local immunodynamic standpoint we used gene expression data to assess the potential involvement of TLS, which are organized comprising T-cell and B-cell areas that arise in the context of chronic inflammation and mediate local antigen-driven responses [12, 38]. They occur in the TME of numerous solid cancer types and gene signatures of TLS have been used as a proxy for spatial imaging-based analysis of cell infiltrates. The presence of TLS and found to correlate with a good prognosis in most cancers including HNSCC [13]. First, we found that HNSCC tumors with high B cell infiltration also displayed high expression of CD4 and CD8 T cell markers (Fig. 4A). However, since no difference in CD4 and CD8 T cell expression levels was found in the Bhigh/TERThigh group vs. the Bhigh/TERTlow group (Fig. 4B), it appears as if TERT overexpression is not a determinant of intratumor T cell infiltration. Quantification of TLS based on five distinct published gene signatures (Table S3) (13, 39–41) showed consistent results with a moderate increase in Bhigh/TERThigh vs. Bhigh/TERTlow tumors irrespective of the gene signature utilized (Fig. 4C). However indicative, a small increase may be interpreted to suggest that while TLS organization results from a variety of antigen-independent local factors [42], TERT mediates the activation of B and T cells that are organized into TLS. **Fig. 4.:** *Correlation of high level of TERT expression and B cells with increased TLS-associated markers. (A) Heatmap showing expression of TERT, CD4 T cell, and CD8 T cell markers (see Data stratification and cell marker in Material and Methods) in Bhigh vs. Blow HNSCC tumors. (B) Levels of expression of CD4 and CD8 T cell infiltrate in Bhigh/TERThigh and Bhigh/TERTlow groups. (C) TLS signature in Bhigh/TERThigh and Bhigh/TERTlow tumors using five signatures from four distinct publications (see Table S1). (D) Barplot of GSEA analysis result revealing differences in B cell and T cell signatures between Bhigh/TERThigh and Bhigh/TERTlow tumors. (E) Heatmap of TFH signature genes from CIBERSORT LM22 across all Bhigh tumor samples. Bhigh/TERThigh and Bhigh/TERTlow status are indicated by the left colorbar. (F) Boxplot of two TFH-associated genes (PASK and LAT) expressed in Bhigh/TERThigh and Bhigh/TERTlow groups (G-I). Scatter plots showing correlation between TFH percentage infiltrate (calculated using CIBERSORT) and B cell markers in Bhigh/TERThigh and Bhigh/TERTlow tumors from (G) the whole HNSCC cohort, and (H) HPV-negative HNSCC patients. (I) Same as in (H) for Bhigh/MUC1high and Bhigh/MUC1low in HPV-tumors.* To better characterize differences in cell population in Bhigh/TERThigh vs. Bhigh/TERTlow HNSCC tumors, we performed gene set enrichment analysis (GSEA) on 11 gene sets from the Molecular Signatures Data Base Immunological signatures (C7) that are associated with B and T cell differentiation (Fig. 4D) [43]. The analysis revealed a statistically significant enrichment for germinal center (GC) and switched memory B cell features in Bhigh/TERThigh tumors, which are typically found in mature TLS [13]. Consistent with this observation, we found that Bhigh/TERThigh up-regulated the expression of AICDA (AID) (Fig. S5A), an essential driver of immunoglobulin somatic hypermutation [44]. Furthermore, CD4 T cells were strongly associated with a central memory signature, while CD8 T cells rather displayed a profile described for effector memory. We also investigated a T follicular helper (TFH) signature based on the expression of the top 20 markers derived from the CIBERSORT LM22 signature [39] (Fig. 4E). Although no significant difference between Bhigh/TERThigh and Bhigh/TERTlow tumors could be identified, two TFH signature-derived genes PASK (PAS domain-containing serine/threonine-protein kinase) and LAT (Linker Activation for T cells) were significantly up-regulated in the Bhigh/TERThigh group ($$P \leq 0.002$$ and $$P \leq 0.022$$, respectively) (Fig. 4F). PASK is a kinase involved in glycolysis, a primary source of energy in effector T cells, while LAT is a transmembrane protein part of the TCR complex that is activated in response to antigen stimulation. Therefore, TERT overexpression in Bhigh HNSCC tumors hallmarks pronounced antigen-specific activation of T cells. Furthermore, we found a strong positive correlation between B cells and TFH in Bhigh/TERThigh vs. Bhigh/TERTlow tumors ($$P \leq 9.61$$e−7). This correlation was also independent of HPV status (Fig. 4G, H) and was not observed, for example, in Bhigh/MUC1high vs. Bhigh/MUC1low tumors (Fig. 4I). This confirms the preferential involvement of TERT as a catalyst of T-B cooperation in HNSCC. Taken together, these data indicate that high TERT expression in HNSCC tumors with high adaptive immune cell infiltrates may promote the formation of more mature TLS and the differentiation of antigen-specific memory T cells. ## The Bhigh/TERThigh signature is associated with adaptive immune response gene expression To gain insight into the benefit of TERT in HNSCC, we investigated genes differentially regulated in the Bhigh/TERThigh group compared to the Bhigh/TERTlow group. Elevated expression levels of TERT in tumors with high B cell infiltrate drove the up-regulation of 2,464 genes and the down-regulation of 2,955 genes, respectively (Fig. 5A). Pathways analysis of the significantly up- and down-regulated genes (FDR < 0.05) revealed that this profile was associated with the induction of genes related to activation and proliferation of B and T cells, and immunoglobulin production (Fig. 5B). Conversely, we found that pathways related to regulation of angiogenesis, glucose transport, lipid storage, and macrophage/myeloid cytokine production were down-regulated (Fig. 5C). Specifically, we identified a cassette of genes differentially (|log2FC| > 0.5, log2CPM > 2.5, FDR < 0.05) regulated in the Bhigh/TERThigh group. High-level intratumor TERT expression was associated with increased expression of genes involved in B cell regulation (CD22, CD40, CD79B, PAX5), T cell activation (IL2RG, IL1R2, LCK, VCAM1, ZAP70), TFH and GC-B cell function (BATF, IL21R, IL27), lymphoid organogenesis (LTB), and T cell cytotoxicity (GZMA, GZMB), PRF1 (Fig. 5D). In contrast, we observed decreased expressions of several genes related to regulatory T cells (Treg) differentiation and function (IGF2, TGFBR2, TGFBR3), and cancer cell invasiveness (ANGPTL2, IL33, ITGA7, PCSK5, PCSK6, PTPRB, TBX3, TGFBR2, TGFBR3) (Fig. 5D). Interestingly, this distinct pattern was not observed in Bhigh/MUC1high, Bhigh/NYESO1high, Bhigh/MAGEhigh or Bhigh/CEAhigh tumors (Fig. 5D), suggesting TERT may be preferentially involved in stimulating specific antitumor immunity in the microenvironment of HNSCC tumors. **Fig. 5.:** *Differential expression analysis between Bhigh/TERThigh and Bhigh/TERTlow reveals increased gene expression in the adaptive immune response. (A) Illustration of the differential expression analysis in HNSCC between Bhigh/TERThigh and Bhigh/TERTlow. (B) and (C) Barplot showing immune-related gene sets evaluated by GO enrichment analysis for (B) 660 up-regulated genes and (C) 1180 down-regulated genes after thresholding using criteria from A). (D) Heatmaps showing the expression of genes involved in immune functions and tumorigenesis across six different conserved antigens (TERT, MUC1, MAGEA3, MAGEA4, CTAG1B, CEACAM5).* Altogether these data revealed that TERT confers a unique transcriptional profile associated with good prognosis in HNSCC tumors with high adaptive immune cell infiltrate, suggesting that TERT may mediate intratumor T-B cooperation for the generation of active and effective local antitumor immunity. ## Discussion Here we report an association between high TERT expression and high levels of B cell tumor infiltrate and favorable PFS in HNSCC. Since no other conserved tumor antigen tested yielded a significant positive correlation, a plausible conclusion is that TERT is preferentially engaged in the activation of adaptive immune cells in the HNSCC tumor microenvironment. An activated phenotype of intratumor B lymphocytes in HNSCC tumors is consistent with a previous report [10]. This report showed higher expression of two conserved tumor antigens (MAGEA1 and MAGEA3) in HPV-negative tumors and a significant decrease of TP53 in HPV-positive tumors, but no attempt was made to link together these antigens, nor to assess the degree of B cell tumor infiltrate and clinical benefit. Here we show that survival benefit is predicted by high B cell tumor infiltrate together with high TERT expression, but not tumor mutational burden or neaoantigen burden, placing TERT as a key antigen in mediating local antitumor immunity and favorable clinical outcome in HNSCC. This is not surprising given the role of TERT in oncogenesis [45, 46] and its expression at every stage of tumor differentiation [47]. The present study points, therefore, to a potential new role for TERT in orchestrating local antitumor immunity via T-B cooperation. The reason why TERT may be presented more effectively than other antigens in HNSCC increasing PFS may have a twofold explanation: (a) the mechanism of TERT reactivation and expression in HNSCC, and (b) the local immunodynamics involving B cells and TLS formation. The TERT promoter is the most important regulatory element of telomerase expression [48]. With few exceptions, TERT is repressed in normal somatic tissues by negative regulators (e.g. p53, RB, WT1, and Mad1) but is reactivated in $85\%$ of human cancers, representing the rate-limiting step in tumorigenesis. Canonical activators of the (wild type) TERT promoter include among others the transcription factor Sp1, the oncogene c-Myc, and the HPV-16 E6 protein [49, 50]. TERT reactivation can also reflect chromatin and DNA methylation [51] and chromatin interaction of the TERT promoter with T-INT2 (Tert INTeracting region 2) through elevated levels of β-catenin and the transcription factor JunD [52]. β-catenin was previously shown to bind to the TERT promoter regulating TERT expression [53] and also be up-regulated by endoplasmic reticulum stress [54]. In HNSCC, TERT promoter mutations are moderately frequent (range 17–$32\%$) [55, 56] compared to melanoma, glioblastoma, and bladder cancer [57], but more frequent in recurrent vs. non-recurrent squamous cell carcinoma of the oral cavity [58]. TERT promoter mutations create de novo binding sites for ETS transcription factors [59], among which GABPA selectively binds and activates a mutated TERT promoter, alone [60] or in association with p52 [61], a member of the NF-κB family. GABPA binding to a mutated TERT promoter mediates long-range chromatin interactions that further drive TERT transcription [62]. Other factors may be implicated in the reactivation of TERT in HNSCC leading to heightened expression. One is a tissue-determined cytodynamic in combination with TERT promoter mutations when cancer stem cells differentiate into mature cancer cells [63], a phenomenon that would favor TERT reactivation and high expression in tissues with high proliferative/regenerative capacity such as the oral cavity [64]. The other is that the TERT gene in HNSCC has been reported to have an increased copy number which would lead to heightened TERT transcription and expression compared to a single-copy gene [65]. Local immunodynamic conditions in HNSCC may favor TERT presentation by B cells to T cells (T-B cooperation). The oropharynx is rich in lymphoid structures known as the Waldeyer's ring which consists of palatine tonsils, nasopharyngeal tonsils, lingual tonsils, and tubal tonsils. Proximity to lymphoid tissue may facilitate trafficking and antigen presentation, steps of critical importance in the interpretation of our findings. A validation of this hypothesis was recently provided in a mouse model of HNSCC in which it was shown that surgical ablation of draining lymphatics eliminated the tumor response to immune checkpoint blockade, worsening overall survival [66]. TCGA data did not permit an assignment of TERT promoter status, leaving unanswered the question as to whether the preferential role of TERT over other antigens and the PFS advantage provided by the Bhigh/TERThigh signature reflect TERT reactivation and expression via wild-type or mutated promoter. Future experiments addressing the complexity of TERT reactivation and expression in HNSCC, and the role of local immunodynamics involving B cells, will be relevant to understand why TERT and the Bhigh/TERThigh signature have a positive impact on PFS in HNSCC. One could argue that the high levels of TERT accounting for the Bhigh/TERThigh signature could be contributed by B cells, implying the presentation of endogenous TERT by B cells. This would rule out any contribution of TERT promoter mutations in the phenomenon, and restrict its interpretation to the activation of intratumor B cells by other antigens, with little role for local immunodynamic. TERT is transiently expressed in germinal center (GC) B cells (centroblasts and centrocytes) during activation by dendritic cells but not in naïve or memory B cells (67–69). Even a transient induction requires the engagement of the B cell receptor together with costimulatory signals and IL-4 [69]. Notwithstanding the fact that GC-like B cells in TLS have been reported [70], and our data point to TLS formation in HNSCC, centroblasts may represent a minority within a population of tumor-infiltrating B cells. Since memory B cells can present antigen and engage in T-B cooperation [70] without population expansion, there would be no necessity to reactivate TERT. An additional consideration is the amount of endogenous TERT transcribed and expressed by activated B cells may be not only transient but also limited quantitatively. For instance, we reported that activated primary B cells are not lysed by autologous TERT-specific CD8 T cells, suggesting poor generation of peptides from endogenous source TERT [71]. Our data do not support the view of B cells being the source of TERT in HNSCC. Using CIBERSORTx to deconvolute the relative proportion of cells in the tumor microenvironment (Table S4) (https://dice-database.org/genes/TERT) [72] and by interrogating single-cell data set of an HNSCC cohort (GSE103322) (Fig. S8), we found little if any evidence for TERT expression in B cells arguing that most TERT expression in HNSCC tissues may be contributed predominantly or solely by tumor cells. A surprising finding of our study is that the Bhigh/TERThigh signature is apparently not dependent on HPV positivity. In HNSCC the overall prevalence of HPV is 25 to $35\%$ [33, 34]. and HPV positivity exhibits an almost complete mutual exclusivity with activating mutations in the TERT promoter and mutations in other known driver genes such as TP53, and CDKN2A [15]. HPV-positive tumors display a significant increase in macrophages and TFH cells [15]. Recent reports showed that HPV-positive HNSCC tumors are enriched for B lymphocytes with GC signature and spatial organization of immune cells consistent with TLS formation [40]. Similarly, Wieland et al. [ 11] reported that HPV-positive HNSCC tumors harbor HPV-specific antibody-secreting cells (ASC) in GC-like spatial organization. Thus, while these reports point to a prevalent role of HPV, our data based on an unbiased analysis point to a facilitating role of TERT that is apparently independent of HPV status. The AID/APOBEC family of cytidine deaminases is an endogenous source of mutations in many cancers, including HNSCC [16, 17]. In particular, APOBEC3 has been reported to be significantly higher in HPV-positive relative to HPV-negative HNSCC tumors [15]. Unexpectedly, compared to Bhigh/TERTlow HNSCC tumors, we found that the Bhigh/TERThigh profile was significantly associated with increased expression of AICDA ($$P \leq 0.010$$, log2FC = 0.585) and APOBEC3B ($$P \leq 0.017$$, log2FC = 0.476) in HPV-negative HNSCC tumors (Fig. S5B). An increase in AID/APOBEC (log2FC = 0.807 and 1.85, respectively) was also observed in Bhigh/TERThigh HPV-positive tumors albeit not significantly, likely due to the small sample size. Thus, the association with TERT expression in both HPV-positive and HPV-negative patients suggests that AID/APOBEC up-regulation in HPV-negative tumors with the Bhigh/TERThigh signature may be due to other factors. As noted above, we found no correlation with PFS and either tumor mutational burden or neoantigen burden in either TERTlow or TERThigh HNSCC tumors. A transcriptional interrogation using five different TLS signatures pointed to the possibility that in our analysis, like in previous reports [11, 40], tumor-infiltrating B cells are part of TLS formation. However, since we did not image their spatial organization, it cannot be firmly concluded if TLS in the HNSCC tumors studied herein are dispersed (immature) or structured (mature). Our results are consistent with the positive role played by TLS in various cancer types [13] including HNSCC [11, 40]. Self-organized intratumor TLS are key tissue-reactive immune events facilitating interactions between adaptive immune cells [12]. Emphasis on B cells is also consistent with the conclusions of explorations on antigen presentation within TLS structures showing that antigen presentation is determined only in part by the uptake of soluble antigen by dendritic cells [73]. An immunological consequence of B cell interactions with other immune cells within TLS is T-B cooperation [9], a key initial step in antigen-specific adaptive immune responses. Since CD4 T cells take also part in the activation of CD8 T cells [74] and their long-lasting maintenance in vivo [75, 76], it stands to reason that B cells could play a pivotal role in orchestrating intratumor antitumor immunity in HNSCC. Since intratumor B cell density restricts Tregs in lung carcinoma [77], it is tempting to propose that the Bhigh/TERThigh signature in HNSCC tumors may provide a twofold advantage: a coordinated induction of local adaptive antitumor immunity, and restriction of Tregs that could down-regulate adaptive T cell responses [78]. Contrary to the idea that antigen may drive the formation of TLS [79], our data support the view that TERT overexpression in HNSCC tumors may not be solely responsible for the formation of TLS since a Bhigh/TERThigh signature drives comparable TLS scores in other tumor types (Fig. S6). Future studies will need to confirm the extent to which B cells present TERT and activate CD4 helper T cells, reshaping the immune response in the tumor microenvironment. The prognostic value of the Bhigh/TERThigh profile differed among various cancer types and was associated with improved PFS only in HNSCC and non-TNBC breast cancer. Except for GBM and READ, most Bhigh/TERThigh tumor types had comparable TLS signature levels (Fig. S6). This argues in favor of factors/mechanisms that oppose the positive effect(s) of the Bhigh/TERThigh signature in other cancer types (Fig. S7A). For instance, we observed that unresponsive tumors up-regulated several factors associated with immunosuppression and/or cancer cell invasiveness (Fig. S7A and B). Among them, IGF2 (insulin-growth factor 2) and PCSK9 (Proprotein convertase subtilisin/kexin type 9) stand out. IGF signaling and high levels of IGF2 binding proteins (IGFBPs) have been implicated in cancer promotion (80–83). PCSK9 that is overexpressed in human cancers was shown to suppress antitumor T cell immunity [84]. In summary, the scenario suggested by our data is that B cells with the surface receptor for TERT internalize TERT and process/present it to CD4 T cells (T-B cooperation) setting in motion an intratumor adaptive immune response. Since TERT is expressed in the vast majority of tumor cells this intratumor mechanism would result in immunity against cancer cell growth and local invasion. This may explain why the Bhigh/TERThigh signature is associated with favorable PFS in HNSCC. Our data also suggest new therapeutic approaches leveraging B cells, TERT, or both to heighten intratumor antitumor immunity in HNSCC. However, a “B cell only” approach may not be sufficient without specific instruction by antigen (TERT), and the induction of “TERT immunity alone” may also not be sufficient if B cells are not engaged. Antibodies to TERT in HNSCC patients have not been previously reported, arguing against their protective role by either antibody-dependent cell-mediated cytotoxicity, antibody-dependent cellular phagocytosis, or complement-dependent cytotoxicity. Instead, new therapeutic approaches that invigorate TERT-mediated T-B cooperation using, for example, autologous B lymphocytes engineered to express TERT, could represent the next frontier in the immunotherapy of HNSCC complementing existing T cell-centered immunotherapies [85]. ## Data stratification and cell marker We performed stratification using the standards of High (higher than $70\%$ quantile), Medium (within 30–$70\%$ quantile), and Low (less than $30\%$ quantile) expression levels for the variables of interest. For two variables, such as B cell High/TERT High (indicated as Bhigh/TERThigh), we took the intersection of samples that satisfied both criteria. For immune cells (B cells, CD4 T cells, CD8 T cells), levels were quantified using the geometric mean of log2TPM of defined cell markers: CD19 and MS4A1 for B cells; CD3D, CD3E, CD3G, CD4 for CD4 T cells; CD3D, CD3E, CD3G, CD8A and CD8B for CD8 T cells. ## Cancer immune score development The cancer immune score is developed using a sum of the adaptive immune cell (B, CD4, and CD8 T cells) and TERT TERT log2TPM expression levels. The adaptive immune cell and TERT level of expressions are stratified into scores of 1 (less than $30\%$ quantile), 2 (within $30\%$ ∼ $70\%$ quantile), and 3 (higher than $70\%$ quantile). The sum of the adaptive immune stratified score and TERT stratified score (ranging from 2 to 6) is called the cancer immune score. ## Kaplan–Meier survival analysis and cox proportional hazard model Survival analysis was done using the lifeline packages, version 0.26.4, and python version 3.8.5. For the Cox proportional hazard analysis, age at diagnosis, sex, stage, HPV status, and log2(TMB) were included as clinical covariates in a model evaluating the impact of TERT and adaptive immune infiltrates (CD8 T cells, CD4 T cells, and B cells) on PFS. HPV status was encoded as 1 for positive and 0 for negative. Tumor stage was ordinal scaled from 1 to 4. The PFS data is obtained from [86] in the supplemental information session. ## mRNA expression data and CIBERSORT The TCGA files were downloaded from the GDC portal on $\frac{12}{27}$/2017, using gdc-client v1.3.0. TCGA RNA-seq alignment files were reprocessed using Sailfish software version 0.7.4 [87] to obtain TPM values using the GRCh38 reference genome with default parameters, including all read sequence duplicates. CIBERSORT immune cell infiltrate estimates were generated using the TCGA HNSCC mRNA expression data as processed and used in Xian et al. [ 31] with all default parameters (LM22 signature). The deconvolution process to infer immune cell gene expression was performed using CIBERSORTx applied to the TCGA HNSCC mRNA expression data under the Impute Cell Expression function. The LM22 signature is merged for 10 major subsets by CIBERSORTx, with all default parameters. ## GSEA analysis for immunologic genesets Gene set enrichment analysis (GSEA) is done using GSEApy packages, version 0.9.5, in python. Two phenotypes are compared, Bhigh/TERThigh vs. Bhigh/TERTlow (see stratifications section for definition). The GSEA analysis was performed using mostly default parameters, as described below. Parameters were set as permutation_type: “gene_set”, permutation_num: 500, method: “t_test”. *The* genesets were downloaded from msigDB [88] C7 immunologic genesets (http://www.gsea-msigdb.org/gsea/msigdb/genesets.jsp?collection=C7). ## Differential expression analysis Differential expression analysis was performed using the edgeR package, version 3.32.1(R version 4.0.5). The RNAseq HT-seq read count file was downloaded from TCGA using the gdc-client on $\frac{09}{11}$/2019 using the manifest file for all tumor types available. Differential expression analysis was performed for HNSCC comparing Bhigh/TERThigh and Bhigh/TERTlow tumors. We then focused on the up-regulated genes and down-regulated genes (FDR < 0.05) that have certain levels of expression (log2CPM > 2.5) and a modest fold change (|log2FC| > 0.5, which corresponds to a 1.44 fold change in either direction). ## GO annotation of significantly up- and down-regulated genes Gene ontology (GO) enrichment analysis was performed using an online platform called g:Profiler [89]. Multiple-testing correction is performed using the Benjamini–Hochberg FDR method. We focused only on the Biological Process (BP) component. ## Tumor mutational burden and tumor neoantigen burden The tumor mutational burden counts and estimate of neoantigen burden were calculated as described in [90]. ## TLS signature computation Five distinct TLS gene signatures were collected from the literature (Table S1) (13, 34–36). For each signature, the TLS score was calculated as the arithmetic mean of the log2 TPM of the gene list. TLS score distributions were compared using the Wilcoxon rank-sum test. The TLS score used in Fig. S4 was computed using the 12 cytokine genes, with the application of single-sample GSEA (ssGSEA), according to [36]. ## HNSCC HPV status The clinical indication of HPV status was downloaded from cBioPortal [91], from the analysis of Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas) (https://www.cbioportal.org/study/clinicalData?id=hnsc_tcga_pan_can_atlas_2018). ## Software packages and version Spearman correlation analysis and Fisher's exact test were performed using the scipy package, version 1.7.3. Multiple-testing correction was performed using the stats.multitest.multipletests function from Statsmodels 0.12.0. All analysis (except differential expression analysis mentioned above using R) was done using python, version 3.8.5. ## Data and materials availability Bioinformatic data have been deposited at https://github.com/cartercompbio/TERT_adaptive_immune_score ## Supplementary material Supplementary material is available at PNAS Nexus online. ## Funding The authors declare no funding. ## Author contributions Conceptualization: M.Z., M.D.; Supervision: H.C., M.Z.; Project Planning and Experimental Design: S.X., M.D., H.C., M.Z.; Data Acquisition and Processing: S.X.; Data Analysis: S.X., M.D., A.C., M.Z.; Writing—original draft: M.Z., M.D.; Writing—review & editing: M.Z., M.D., H.C., S.X., A.C. ## Data availability The results shown here are based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga. The data are available at https://portal.gdc.cancer.gov/. ## References 1. 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--- title: 'The Role of Diet during Pregnancy in Protecting against Gestational Diabetes Mellitus in a Population with Mediterranean Dietary Habits: A Cross-Sectional Study' authors: - Ermioni Tsarna - Anna Eleftheriades - Efthymia Tsomi - Georgia Ziogou - Panagiotis Vakas - Theodoros Panoskaltsis - Panagiotis Christopoulos journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003761 doi: 10.3390/jcm12051857 license: CC BY 4.0 --- # The Role of Diet during Pregnancy in Protecting against Gestational Diabetes Mellitus in a Population with Mediterranean Dietary Habits: A Cross-Sectional Study ## Abstract Gestational diabetes mellitus (GDM) is a common metabolic disorder among pregnant women. Dietary habits during pregnancy might alter the risk of GDM development, and populations following the Mediterranean diet are relatively understudied. This was a cross-sectional, observational study of 193 low-risk women admitted to a private maternity hospital in Greece to give birth. Food frequency data on specific food categories, selected based on previous research, were analyzed. Logistic regression models, both crude and adjusted for maternal age, body mass index before pregnancy, and gestational weight gain, were fitted. We observed no association of carbohydrate-rich meals, sweets, soft drinks, coffee, rice, pasta, bread and crackers, potatoes, lentils, and juices with GDM diagnosis. Cereals (crude $$p \leq 0.045$$, adjusted $$p \leq 0.095$$) and fruits and vegetables (crude $$p \leq 0.07$$, adjusted $$p \leq 0.04$$) appeared to have a protective effect against GDM, while frequent tea consumption was linked to higher risk of GDM development (crude $$p \leq 0.067$$, adjusted $$p \leq 0.035$$). These results strengthen previously identified associations and underline the importance and potential impact of changing dietary habits even during pregnancy in adjusting one’s risk of metabolic pregnancy complications, such as GDM. The importance of healthy dietary habits is highlighted, with the goal of raising awareness amongst obstetric care specialists regarding the provision of systematic nutrition recommendations to pregnant women. ## 1. Introduction Gestational diabetes mellitus (GDM) is a common metabolic disorder diagnosed during pregnancy in women who were normoglycemic before conception [1,2]. According to the International Association of Diabetes and Pregnancy Study Groups (IADPSG), the clinical diagnosis of GDM requires at least one blood glucose value above the normal limit for pregnancy in the 75 g oral glucose tolerance test (OGTT), performed at 24–28 weeks of gestation [3]. GDM has been associated in large international cohorts with several unfavorable pregnancy and perinatal outcomes, including preeclampsia, higher rates of caesarean section and preterm birth, macrosomia and shoulder dystocia, neonatal hypoglycemia and higher insulin levels, neonatal jaundice, and higher rates of neonatal intensive care unit admission [3,4]. The aforementioned outcomes are positively associated with blood glucose levels during pregnancy, even among normoglycemic women [3,5]. Lastly, women diagnosed with GDM have a greater risk of developing type II diabetes mellitus later in their lives [3,6]. The role of diet during pregnancy in GDM development has been explored in many observational epidemiological studies and randomized controlled trials (RCTs). In a relevant systematic review, 25 dietary observational studies were identified [7]. Higher total dietary fiber consumption, fruit and cereal consumption, caffeine intake, and tea consumption were linked to a lower risk of developing GDM [7]. On the contrary, the consumption of sugar-sweetened beverages and potatoes was associated with a greater risk of GDM [7]. It is worth mentioning that among these 25 studies, only two included populations that followed a Mediterranean diet, and in fact, one of these did not examine food intake but rather adherence to the Mediterranean diet in relation to GDM diagnosis [8]. With regard to evidence from RCTs regarding the role of dietary habits in GDM risk, a relevant Cochrane review of five RCTs involving 1279 pregnant women concluded that dietary advice interventions during pregnancy may be effective for GDM prevention, although the meta-analysis results were not statistically significant (RR = 0.60, 0.35–1.04 $95\%$ CI) [9]. However, the quality of evidence was very low and none of these studies were carried out in a Mediterranean diet population [9]. Nutritional epidemiology data are prone to confounding bias that is specific to the dietary habits of the studied population. Inherently, a greater consumption of one food category could be associated with a lower consumption of others, higher total calorie intake, or a combination of the above. Thus, a protective effect of a specific food category might actually reflect the protective effect of lower total calorie intake or the harmful effect of other food categories. Therefore, it is important to confirm results from nutritional epidemiological studies and RCTs in populations following different dietary habits. Although there is no single definition, the Mediterranean diet is characterized by being low in saturated fat and high in vegetable oils, and was firstly observed in Greece and Southern Italy during the 1960s [10]. The Mediterranean diet typically contains a high amount of fruit, vegetables, seeds, nuts, and whole grains, as well as olive oil as the main source of monounsaturated fat. It also includes a moderate amount of fish, poultry, and dairy [10]. The most important characteristic of this dietary pattern is that it has been associated with a reduced risk of coronary heart disease compared to northern European countries and the United States, and interestingly enough, numerous studies report that this happens in a dose-dependent fashion [10]. In other observational studies, the Mediterranean diet has been associated with a decreased incidence of Parkinson’s and Alzheimer’s diseases, and different types of cancers, including colorectal, prostate, oropharyngeal, and breast cancers [10]. As far as pregnancy is concerned, a recent systematic review by Zaragoza et al. published in 2022 concluded that the Mediterranean diet is an optimal diet to consume during pregnancy, since it provides an adequate supply of micronutrients while controlling weight gain during gestation [11]. Growing evidence also suggests the beneficial effect of the Mediterranean diet during pregnancy on children’s health, increasing small airway function in childhood and having a protective role against asthma, allergy, and increased body weight [12,13]. Even though the Mediterranean diet has been shown to be beneficial during pregnancy, the role of specific food categories within the Mediterranean diet is not well understood, which poses a challenge when practitioners provide dietary advice for pregnant women who follow Mediterranean diet. The effect of diet during pregnancy on GDM development in populations with the Mediterranean diet is relatively understudied. The aim of this study is to explore the role of dietary habits such as carbohydrate and caffeine consumption in the development of GDM, studying a population of low-risk pregnant women in Greece. ## 2. Materials and Methods This was a cross-sectional observational study of consecutive pregnant women who were admitted to give birth from March 2019 until August 2019 in a private maternity hospital in Athens, Greece. Women with an elective caesarean section were excluded in order to select a low-risk population that would not be affected by other pregnancy-specific pathologic conditions, such as pregnancy-related hypertension and preeclampsia. In addition, women who did not speak Greek fluently were excluded from this study. After informed consent was obtained, a questionnaire was administered to the pregnant woman, while birth outcomes were recorded later by the research midwife. The study protocol was approved by the Research Ethics Committee of the Maternity Hospital (protocol number: $\frac{1516009106}{27}$-11-2015). Dietary habits during pregnancy were assessed with a semi-quantitative food frequency questionnaire in Greek [14]; the questions used in the statistical analysis of this study are presented in detail in Tables S1 and S2. Women were explicitly instructed to answer the dietary questionnaire taking into consideration the whole pregnancy period, rather than the third trimester. For the aim of this study, we used semi-quantitative data on the consumption frequency of fruits and vegetables, carbohydrate-rich meals, sweets, soft drinks, and coffee, and qualitative data on the consumption frequency of cereals, rice, pasta, bread and crackers, potatoes, lentils, tea, and juices. Unfortunately, a definition for cereals was not provided to the pregnant women. Therefore, apart from healthy choices, such as whole grain and unprocessed cereals, women might have also answered regarding unhealthy choices, such as processed and sugar-sweetened cereals. Furthermore, participants were asked about gravidity and parity status, GDM diagnosis based on the 75 g OGTT at 24–28 weeks of gestation and the IADPSG criteria for GDM diagnosis, pregnancy-related hypertension and preeclampsia, demographic characteristics, and anthropometric characteristics before and at the end of pregnancy [3]. The research midwife cross-checked the self-reported anthropometric characteristics with the ones recorded by the obstetrician who had followed up the pregnancy in the women’s medical folders, in order to ensure high accuracy of variables that were used in the statistical analysis. For descriptive statistics of baseline characteristics of participants and food frequency data, we used means and standard deviation for continuous variables, and frequencies and proportions for categorical variables. Baseline characteristics between study participants with and without GDM were compared with the non-parametric Mann–Whitney U test for continuous variables, and chi-squared test for categorical variables. In order to examine the association of food frequency data with GDM diagnosis, crude and adjusted logistic regression models were fitted. The exposure variable was a categorical variable in all models, and the likelihood ratio test was used to calculate p values. The potential confounders used as covariates in the adjusted models were maternal age, body mass index (BMI) before pregnancy, and gestational weight gain. The last two were used as proxies for total energy intake, for which we did not have any direct data. The level of significance was 0.05 for all the aforementioned statistical analyses. It should be noted that there were no missing data among the variables used in the logistic regression models. All statistical analyses were performed using R statistical software (version 4.1.2; R Foundation for Statistical Computing, Vienna, Austria) [15] and the software packages “tableone” [16] and “psych” [17]. The computer code used for the statistical analysis using the R statistical software can be provided upon request. For the reporting of this study’s results, “Strengthening the Reporting of Observational Studies in Epidemiology” (STROBE) guidelines have been followed [18]. ## 3. Results Out of 224 pregnant women invited to participate in this study, 193 provided informed consent and are included in this analysis. Mean maternal age at neonate’s birth was 31.5 years (Table 1). Pre-gestational BMI was on average 22.81, while gestational weight gain was 13.46 kg (Table 1). Sixty-five women ($33.7\%$) gained weight within the Institute of Medicine (IOM) target range, 61 ($31.6\%$) below the IOM target range, and 67 ($34.7\%$) above the IOM target range (Table 1) [19]. The majority of participants, 124 ($64.2\%$) women, were pregnant for the first time, 43 ($22.3\%$) were pregnant for the second time, and 26 ($13.5\%$) were pregnant for at least the third time (Table 1). With regard to smoking status, 85 ($44\%$) were smoking before conception, 23 ($11.9\%$) continued smoking during pregnancy, and 88 ($45.6\%$) reported being exposed to passive smoking at home during pregnancy. Twelve women ($6.2\%$) were diagnosed with GDM, 7 ($3.6\%$) with pregnancy-induced hypertension, and no women were diagnosed with preeclampsia (Table 1). Concerning neonatal characteristics, mean gestational age at birth was 38.5 weeks, mean birthweight was 3075 g, and 88 ($52.4\%$) of the neonates were assigned female sex at birth. As far as dietary habits are concerned, during pregnancy, most women consumed meals that were rich in carbohydrates one to three times per day. In fact, 53 ($27.5\%$) women consumed such a meal once daily, 86 ($44.6\%$) twice daily, and 41 ($21.2\%$) three times daily (Table S1). Fruits and vegetables were frequently chosen during pregnancy; once per day by 33 ($17.1\%$) women, twice by 74 ($38.3\%$), three times per day by 45 ($23.3\%$), while 38 ($19.7\%$) women ate fruits and vegetables four to five times per day (Table S1). As for sweets, 66 ($34.2\%$) women consumed sweets once or twice weekly, but an alarming $28\%$ (54 women) ate sweets every other day and $18.7\%$ (36 women) did so daily (Table S1). The majority of women did not consume soft drinks during pregnancy (136 women or $70.8\%$) and only 23 ($11.9\%$) consumed them on a daily basis (Table S1). With regard to coffee consumption, $39.9\%$ (77 women) refrained from coffee during pregnancy, $14\%$ (27 women) drank coffee on average three times per week, $39.4\%$ (76 women) once daily, and $6.7\%$ (13 women) drank two or more cups of coffee every day (Table S1). Regarding qualitative food frequency data, cereals were frequently consumed by 133 ($68.9\%$) women, rice by 134 ($69.4\%$), pasta by 158 ($81.9\%$), bread and crackers by 129 ($66.8\%$), potatoes by 137 ($71\%$), lentils by 131 ($67.9\%$), tea by 39 ($20.2\%$), and juices by 140 ($72.5\%$) women (Table S1). In the analysis of the semi-quantitative food frequency data, the consumption frequency of carbohydrate-rich meals, sweets, soft drinks, and coffee did not correlate with GDM diagnosis, neither in the crude nor in the adjusted logistic regression models (Table 2). In contrast, fruit and vegetable consumption frequency was non-significant in the crude analysis ($$p \leq 0.07$$), but gained statistical significance in the adjusted analysis ($$p \leq 0.04$$) (Table 2). Since the null hypothesis is double-sided in the statistical logistic regression models, the odds ratios of each level of the categorical variable used for fruit and vegetable consumption frequency were checked, in order to decide if this significant association reflected a protective or harmful effect. Both in the crude and the adjusted logistic regression models, all odds ratios were below unity with no consumption being the reference category, indicating a protective role of fruit and vegetable consumption during pregnancy against GDM (Table S2). Naturally, the power for each level of fruit and vegetable consumption frequency variable was much lower than the power for the categorical variable as a whole, and none of these odds ratios reached statistical significance on each one. In the analysis of the qualitative food frequency data, the frequent consumption of rice, pasta, bread and crackers, potatoes, lentils, and juices did not correlate with GDM diagnosis, neither in the crude nor in the adjusted logistic regression models (Table 3). Nonetheless, cereal consumption appeared to be protective against GDM in the crude logistic regression model (odds ratio 0.30, $$p \leq 0.045$$) (Table 3). However, this result lost its statistical significance once adjusting for maternal age, BMI before pregnancy, and gestational weight gain (odds ratio 0.35, $$p \leq 0.095$$) (Table 3). In contrast to cereal consumption, tea consumption appeared to be a risk factor for GDM diagnosis; this result was non-significant in the crude analysis (odds ratio 3.09, $$p \leq 0.067$$), but gained statistical significance in the adjusted analysis (odds ratio 3.97, $$p \leq 0.035$$) (Table 3). ## 4. Discussion In this study of 193 pregnant women sampled from a low-risk population that follows the Mediterranean diet, consuming fruits, vegetables, and cereals during pregnancy appeared to decrease the risk of GDM diagnosis. In contrast, frequent tea consumption during pregnancy was associated with a higher risk of being diagnosed with GDM. Fruits, vegetables, and cereals, which were shown to be protective against GDM in our study, are all well-known sources of fiber, in addition to having a low glycemic index. Several mechanisms have been proposed to explain why a high-fiber diet might ameliorate glucose metabolism. Gastric emptying is delayed in presence of high-fiber stomach content and digestion is slower in total, resulting in reduced glucose absorption [20]. In addition, a high-fiber diet has been linked to reduced appetite and total energy intake, and, consequently, reduced adiposity, which is a well-known risk factor for GDM as it enhances insulin intolerance [20]. It is not surprising, therefore, that our results are in line with previous research that has indicated the protective role of fruits, vegetables, and cereals against GDM, even though the vast majority of these research data did not originate from populations that follow a Mediterranean diet [7,9]. Thus, this protective effect seems to be robust across populations with different dietary habits. The role of dietary carbohydrates in GDM development is quite complex. Counterintuitively, a low-carbohydrate dietary pattern has been associated with a higher risk of GDM [21,22]. Women who consume fewer carbohydrates on average consume more fat, which has been positively correlated with GDM risk [21,23]. Nonetheless, in our study, we did not observe any association of self-reported consumption frequency of carbohydrate-rich meals during pregnancy and GDM. With regard to the type of carbohydrates consumed, simple carbohydrates, as opposed to complex ones, are regarded as a contributing factor for GDM due to the steeper increase in blood glucose levels postprandially. It should be noted that the amount of fiber is also of importance, and even foods rich in complex carbohydrates might contribute to GDM if fiber content is low [23]. This might explain why refined grains and starches are considered as potentially harmful for GDM development [23]. In our study, sweets and soft drinks, which are rich in simple carbohydrates, rice, pasta, bread, and crackers, which are usually made from white starches, and potatoes, which have been shown to contribute to GDM development in other observational studies, did not correlate with GDM [7]. Similarly, lentils, which are rich in complex carbohydrates and fiber, as well as juices, which are rich in fiber even though they contain simple carbohydrates, did not correlate with GDM. Whether this lack of association is the result of low power or reflects a true lack of association in a population that follows a Mediterranean diet remains unclear. Caffeine intake has been negatively correlated with GDM diagnosis, indicating a potentially protective role of caffeine [7,24]. Coffee phytochemicals may support the preservation of pancreatic beta cell function by preventing pancreatic cell damage during periods of high insulin secretion and the formation of cell-toxic amyloids [25]. Other theories for the beneficial effects of coffee consumption support the suggestion that coffee compounds lead to the activation of AMPK, which works as a switch between anabolism (ATP expenditure) and catabolism (ATP production) [26]. In contrast to the evidence supporting the suggestion that caffeine consumption may improve glucose metabolism, a few studies have suggested that in individuals with previously diagnosed diabetes, caffeine may have a negative impact on blood glucose concentration. A systematic review of randomized control trials published in 2013 that included a total of nine trials concluded that the consumption of moderate to high doses of a single daily caffeine supplement is associated with elevated post-prandial blood glucose concentrations [27]. These nine trials involved human participants who had the diagnosis of diabetes type I, type II, or GDM [27]. However, the underlying mechanism is not clearly understood and, as the authors imply, high coffee consumption may constitute a marker for other risk factors [27,28]. This systematic review did include a single study of patients with GDM [27]. This study by Robinson et al., which included women with and without GDM (control group), concluded that in the control group, caffeine did not significantly affect blood glucose, insulin sensitivity, or C-peptide, whereas in the GDM group, C-peptide was greater ($p \leq 0.05$), and the insulin sensitivity index was lower ($p \leq 0.05$) [27,29]. However, more studies and additional research are needed since the sample size was very small (women with GDM $$n = 8$$). In our study, neither coffee nor tea, both of which contain caffeine, appeared to have any protective effect against GDM [30]. It should be noted that among our study population, almost $40\%$ of women refrained from coffee during pregnancy. Although the rationale for this refrainment was not recorded in our study, we suspect that it relates to concerns regarding the association of high caffeine consumption with pregnancy loss and fetal growth restriction [31]. In contrast, the frequent consumption of tea during pregnancy was linked to a higher risk of being diagnosed with GDM. Tea has been shown to protect against type II diabetes and its content of catechins and polyphenols that exert an antioxidant effect has been implicated as a possible biological explanation not related to caffeine per se [32,33]. Nonetheless, a previously published analysis of the association between tea consumption and GDM among 86,453 pregnancies from Denmark did not find a statistically significant association despite the large sample size, even though the effect estimates did indicate a potential protective effect of tea [34]. Unfortunately, in our study questionnaire, we did not include any questions on the type of tea consumed and whether it was consumed unsweetened, with honey, or with sugar. It should be noted that not only the type of tea but also brewing time have been shown to affect the levels of caffeine content, which makes it difficult to interpret tea consumption data in terms of caffeine intake [30]. Taking all the aforementioned into consideration, we cannot conclude if our finding of a positive association between tea consumption and GDM risk reflects a true association, an association of sugar consumption with GDM, or if it is merely a reflection of multiple testing. A nutritious diet, balanced with regard to macronutrients and micronutrients, is considered important during gestation both for the mother and the child. In particular, balanced nutrition is thought to contribute to optimal fetal growth, is associated with a lower risk of unfavorable obstetrical and neonatal outcomes, and can affect maternal and child health long-term [35]. Notably, the latest research has suggested that the Mediterranean diet might contribute to improving the immune system of pregnant individuals, also strengthening their immune response to viral infections such as COVID-19 [36]. In contrast, inappropriate maternal nutrition, both in terms of under-nutrition and over-nutrition, has been linked with abnormal fetal growth patterns, including both small and large- for gestational age fetuses, respectively, and also with a higher long-term risk of developing obesity, nonalcoholic fatty liver disease (NAFLD), and cardiovascular diseases [35]. Dietary interventions during pregnancy have been researched and shown to be effective in the prevention of pregnancy-associated hypertension and reducing excessive weight gain during pregnancy [9]. Fibers, whole grains, nuts, vegetables and fruits, legumes, fish, and meals rich in monounsaturated fats are regarded as important components of a nutritious diet during pregnancy [35]. The importance of fatty acid consumption during pregnancy has been highlighted by an RCT, which reported that the consumption of mono- and unsaturated fatty acids from olive oil and pistachios may reduce the incidence of GDM [37]. In contrast, the consumption of limited amounts of refined grains, simple sugars, fatty red meat, processed foods, and trans- and saturated fats is advised during pregnancy [35]. Diets that consistently restrict a macronutrient have been proven to be ineffective and are not recommended for pregnant women, as they can result in micronutrient deficiency and may negatively impact child health [38]. In particular, carbohydrate-restricting diets during pregnancy have been associated with a higher incidence of neural tube defects and excessive weight gain during childhood [35]. To our knowledge, this is one of the very few studies to examine dietary habits during pregnancy and GDM risk in populations following a Mediterranean diet and, thus, it strengthens the robustness of previously found associations. The Mediterranean diet has been shown to be protective both against GDM development and type II diabetes mellitus development among women previously diagnosed with GDM. Nonetheless, the role of specific food categories within the Mediterranean diet remains unclear. In fact, a previous study by Karamanos et al., which was published in 2014 and included a total of 1076 pregnant women, concluded that the adherence to the Mediterranean diet during pregnancy can lead to a better glucose tolerance and, therefore, act protectively against GDM [8]. Interestingly, Tobias et al. demonstrated that the adherence to a healthy dietary pattern, such as the Mediterranean diet, could be associated with a lower type II diabetes mellitus risk among women who were previously diagnosed with GDM [39]. Another study from Tobias et al., published in 2012, which included 15,254 participants, showed that pre-pregnancy adherence to the Mediterranean diet was associated with a significant decrease in GDM risk [40]. These findings demonstrate the importance of the adherence to healthy dietary habits before, during, and after pregnancy, which can lead to a reduction in unfavourable perinatal outcomes as well as to a reduction in cardiovascular mortality. Notwithstanding our findings, this study had several limitations. The sample size was quite small, and a low-risk population was sampled, resulting in a low incidence of GDM and, therefore, low power of this study. Consequently, we chose not to explore novel associations of GDM and dietary habits, which would have given rise to the issue of multiple testing as well, but rather selected specific dietary habits that have been previously recognized to be associated with the risk of GDM. In addition, our study population may not be representative of the general Greek population. With regard to representativeness concerns, we observed that an alarming percentage of women ($44\%$) smoked before getting pregnant, $11.9\%$ continued smoking during pregnancy, and $45.6\%$ of women were exposed to passive smoking during their pregnancy. Since smoking seemed alarmingly frequent in our study population and it is not known whether the effect of dietary habits on GDM risk varies between smokers and non-smokers, we compared smoking status in our study with other birth cohorts in studies that have been recently conducted in populations following the Mediterranean diet. the RHEA cohort, a population-based birth cohort from the Heraklion region in Greece that recruited women in 2007 and 2008, $43.7\%$ of women smoked before pregnancy and $23.8\%$ continued smoking during their pregnancy [41]. In INMA, a birth cohort from Spain recruiting women between 2003 and 2008, $65.8\%$ of pregnant women were exposed to passive smoking at home and $32.5\%$ of them were actively smoking [42]. In contrast, in NASCITA, a representative birth cohort from Italy that recruited women in 2019 and 2020, only $6.5\%$ of women continued smoking during pregnancy [43]. Therefore, in our study population, smoking during pregnancy was less frequent than in other Greek and Spanish birth cohorts, but more frequent than in Italian cohorts. Even though smoking status during pregnancy does not seem to raise a concern regarding sample representativeness, our sample might still differ from the general population with regard to socioeconomic position, occupational activities, and environmental exposures during pregnancy. Since our study participants were recruited in a private maternity hospital in the capital city of Greece, women of lower socioeconomic status are expected to be underrepresented. The same holds true for women with agricultural and livestock occupations that are more common in the Greek countryside, and involve high levels of physical activity, which might interact with dietary habits. Similarly, environmental exposures are expected to differ significantly between urban populations, as in our study, and rural populations. The aforementioned might influence the relevance of our results for the women who are not well represented in our study, but does not affect the scientific inference of our results, since the representativeness of the sample does not bias the results of research on potentially causal associations [44]. In addition, the data collection was cross-sectional; recall bias might have affected our food frequency data and first trimester dietary habits might not be well reflected, especially if pregnant women changed their dietary habits as pregnancy progressed. According to usual care in Greece, women who are diagnosed with GDM receive dietary recommendations on frequently consuming small meals of a low glycemic index, which would result in pregnant women with GDM appearing to have healthier dietary habits, which, in our study, were hypothesized to ameliorate glucose metabolism. Therefore, recall bias is expected to have biased our results towards the null hypothesis, and our effect estimates are expected to be closer to unity than they would be if dietary habits were assessed during the first or even second trimester of pregnancy. Furthermore, the lack of quantitative data is a limitation of this study, since our food frequency data were either semi-quantitative or qualitative. Lastly, our adjusted logistic regression models might be affected by over-adjustment, in which case, all effect estimates might be biased towards the null hypothesis, which is that no association between dietary habits during pregnancy and GDM exists. On one hand, pre-pregnancy BMI is naturally associated with dietary habits before pregnancy, which, in turn, also affect the dietary habits during pregnancy, leading to BMI serving as a mediator of effect. The same holds true for gestational weight gain, which is influenced by dietary habits during pregnancy. To provide an explanatory example, a protective effect of a specific food category can be mediated by lower total calorie intake, as is the case with high fiber intake, which reduces appetite and can affect GDM risk via lower gestational weight gain [20]. By adjusting for pre-pregnancy BMI and gestational weight gain, that effect would be underestimated. In that sense, including pre-pregnancy BMI and gestational weight gain in our adjusted models might bias our results towards the null hypothesis. This increases the probability of a type II error (the probability of failing to reject a null hypothesis that is actually false in the population) [45]. On the other hand, pre-pregnancy BMI is a known risk factor for GDM, and its effect is not mediated solely by dietary habits but also by adiposity and its endocrine functions. In that sense, not adjusting for pre-pregnancy BMI would not account for the bias due to the effect of adiposity on the risk of GDM. This would increase the probability of a type I error (the probability of rejecting a null hypothesis that is actually true in the population) [45]. Despite the aforementioned issue with using BMI-related variables as covariates in statistical models applied in nutritional epidemiology studies, BMI before pregnancy and gestational weight gain are frequently used as covariates in nutritional epidemiological studies for GDM, since adiposity is a well-known confounder. In our study, we might have underestimated the effect of dietary habits during pregnancy on the risk of GDM by adjusting for pre-pregnancy BMI and gestational weight gain. Nonetheless, this was considered preferable over reporting results that could, in reality, reflect a type II error rather than a true association in our population. ## 5. Conclusions In this study, we examined the associations of dietary habits during pregnancy with GDM risk. Among the examined food categories, which were chosen based on previous research findings, we observed no association of carbohydrate-rich meals, sweets, soft drinks, coffee, rice, pasta, bread and crackers, potatoes, lentils, and juices with GDM diagnosis. Cereals, fruits, and vegetables appeared to have a protective effect against GDM, while frequent tea consumption was linked to a higher risk of GDM development. Our results strengthen the associations that have been identified in previously published studies, and underline the importance and potential impact of changing dietary habits during pregnancy in adjusting one’s risk of metabolic pregnancy complications, such as GDM. 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--- title: Taurocholic Acid and Glycocholic Acid Inhibit Inflammation and Activate Farnesoid X Receptor Expression in LPS-Stimulated Zebrafish and Macrophages authors: - Xutao Ge - Shaoze Huang - Can Ren - Lu Zhao journal: Molecules year: 2023 pmcid: PMC10003765 doi: 10.3390/molecules28052005 license: CC BY 4.0 --- # Taurocholic Acid and Glycocholic Acid Inhibit Inflammation and Activate Farnesoid X Receptor Expression in LPS-Stimulated Zebrafish and Macrophages ## Abstract A hyperactive immune response can be observed in patients with bacterial or viral infection, which may lead to the overproduction of proinflammatory cytokines, or “cytokine storm”, and a poor clinical outcome. Extensive research efforts have been devoted to the discovery of effective immune modulators, yet the therapeutic options are still very limited. Here, we focused on the clinically indicated anti-inflammatory natural product *Calculus bovis* and its related patent drug Babaodan to investigate the major active molecules in the medicinal mixture. Combined with high-resolution mass spectrometry, transgenic zebrafish-based phenotypic screening, and mouse macrophage models, taurochiolic acid (TCA) and glycoholic acid (GCA) were identified as two naturally derived anti-inflammatory agents with high efficacy and safety. Both bile acids significantly inhibited the lipopolysaccharide-induced macrophage recruitment and the secretion of proinflammatory cytokines/chemokines in in vivo and in vitro models. Further studies identified strongly increased expression of the farnesoid X receptor at both the mRNA and protein levels upon the administration of TCA or GCA, which may be essential for mediating the anti-inflammatory effects of the two bile acids. In conclusion, we identified TCA and GCA as two major anti-inflammatory compounds in *Calculus bovis* and Babaodan, which could be important quality markers for the future development of Calculus bovis, as well as promising lead compounds in the treatment of overactive immune responses. ## 1. Introduction Bacterial infection is one of the leading causes of death worldwide [1]. Upon inflammation, the innate immune system is activated, which rapidly synthesizes and releases various cytokines and chemokines, such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and c-c motif chemokine ligand 2 (CCL-2), to further augment the inflammatory responses and recruit more innate immune cells to clear the invading pathogens [2,3]. However, dysregulated inflammation can be harmful [4]. During excessive inflammation, the uncontrolled release of proinflammatory cytokines will also damage normal cells [5]. In serious cases such as sepsis, the overactivated immune response can cause organ damage and even death [6,7]. Hyperactivated inflammatory responses and cytokine storm are also correlated with the poor outcome of the SARS-CoV-2 infection. It is proven that severe COVID-19 patients exhibit high levels of inflammatory cytokines and chemokines [8,9]. Current therapies for immune hyperactivation include glucocorticoids and non-steroidal anti-inflammatory drugs (NSAIDs); however, they are cytotoxic and may cause other diseases, including diabetes and osteoporosis [10,11]. Therefore, how to control the inflammatory response during infection remains an overwhelming challenge. Medicinal herbs and animal-sourced natural products have been used to treat inflammation in multiple geographical regions around the world for centuries. The high diversity in chemical structure and bioactivity makes natural products an inviting source for the identification of new lead compounds [12,13]. However, due to the complexity of their chemical components, the active substances and pharmacological mechanisms of most natural products remain unclear, which severely impedes their further application. Calculus bovis (C. bovis) is the dried gallstone of cattle widely used in China, Japan, and many other Asian countries for the treatment of stroke, convulsions, epilepsy, and high fever [14]. C. bovis is also the main component of many patent drugs. Babaodan (BBD), for example, is a traditional Chinese formula, approved in 2020 by the National Medical Products Administration of China (Med-drug permit no. Z10940006), in the treatment of viral hepatitis, cholecystitis, angiocholitis, and urinary tract infection [15]. Despite long-term usage in clinical applications, the pharmacological mechanism of BBD remains unclear. Previous studies suggested the involvement of multiple signaling pathways in BBD-mediated anti-inflammatory responses, such as NLRP3 inflammasome, P13K/AKT/mTOR pathway, AMPK signaling, NF-κB, and MAPK signaling [15,16,17,18,19,20]. Although extensive work has been devoted to the study of C. bovis and its related natural drugs, the bioactive components in these medicinal mixtures remain elusive. Zebrafish is a newly emerged vertebrate organism that has many advantages for chemical screening, such as small body size, high fertility, rapid development, larvae transparency, and low breeding cost. Besides, the innate immune system of zebrafish is highly similar to mammals. Most immune cells, inflammatory mediators, and receptors are evolutionarily conserved between zebrafish and mammals, which makes the zebrafish an appropriate model for the study of inflammation mechanisms [21]. Moreover, the availability of different transgenic lines carrying fluorescence-labeled cells in different organ systems further facilitated the in vivo imaging of zebrafish. For example, macrophage-labeled line Tg(mpeg:eGFP), neutrophil-labeled line Tg(lyz:DsRed), T-cell-labeled line Tg(rag2:DsRed) were all constructed in previous studies, and are suitable to study the endogenous distribution and migration of immune cells [22,23,24]. In our previous study, we used the transgenic lines Tg(lyz:eGFP) and Tg(mpeg:eGFP) to construct an inflammatory bowel diseases(IBD) model and a trauma model in zebrafish and successfully identified the active compounds in two herbal formulae, based on the endogenous imaging of immune cells [25,26]. Therefore, motivated by the high clinical significance of anti-inflammatory therapies and the potential efficacy of C. bovis in regulating the hyperactivated immune process, we propose that it is necessary to further investigate the anti-inflammatory effects and the active components in C. bovis. In this study, we combined both in vivo and in vitro models of lipopolysaccharide (LPS)-simulated bacterial infection, in transgenic zebrafish and mammalian cells, to systematically identify the active substances and potential mechanisms of BBD and C. bovis. The major molecular compositions of bile acids in C. bovis were analyzed by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS), among which taurocholate acid (TCA) and glycocholic acid (GCA) were discovered as novel anti-inflammatory compounds. ## 2.1. BBD Extract Attenuates LPS-Induced Zebrafish Inflammation In order to examine the anti-inflammatory effects of BBD, we constructed an LPS-induced inflammation model in zebrafish as described previously [27]. Briefly, 4 days post-fertilization (dpf) zebrafish larvae were microinjected with LPS at the yolk sac to stimulate acute inflammation, and the severity of inflammation was evaluated by the endogenous imaging of macrophage accumulation in Tg(mpeg:eGFP) transgenic line (Figure 1A). Based on different levels of macrophage aggregation, embryos were classified as normal, mild, medium, and severe (Figure 1B). Next, we evaluated the safety of BBD in zebrafish by evaluating the percentage of healthy embryos (alive embryos without observable developmental defects) after exposure to BBD at different doses from 3 dpf to 4 dpf. No toxic effect on the health of zebrafish embryos was observed for the 10 µg/mL BBD treatment, which concentration was selected for subsequent experiments (Figure 1C). After LPS microinjection, considerably increased macrophage aggregation was observed as compared with the PBS-injected control group, suggesting the successful stimulation of acute inflammation. Treatment with BBD or dexamethasone (DEX, as the positive control) was able to significantly inhibit the aggregation of macrophages (Figure 1D). Moreover, the transcriptional levels of pro-inflammatory cytokines IL-6 and TNF-α, as well as a macrophage chemokine CCL-2 were examined. The upregulated expression of all three biomarkers was greatly inhibited by BBD treatment (Figure 1E). Taken together, our results suggested that BBD has a strong anti-inflammatory effect in the LPS-induced inflammatory zebrafish model. ## 2.2. Calculus bovis Extract Attenuates LPS-Induced Zebrafish Yolk Sac Inflammation As the dried gallstones of cattle, C. bovis has been used to treat fever, stroke, and other diseases in many geographical regions around the world for centuries [14], and is one of the major components in BBD. Therefore, we asked whether C. bovis extract is the major substance mediating the anti-inflammatory effects of BBD. Similarly, a toxicity assay was conducted to evaluate the safety of C. bovis extract in zebrafish embryos, and a concentration of 10 µg/mL was determined for the drug efficiency test (Figure 2A). Using the LPS-injected zebrafish inflammation model, significant downregulation of macrophage aggregation was also observed in embryos treated with C. bovis extract, reaching a similar level as the BBD-treated group regarding the combined percentage of medium and severe phenotypes (Figure 2B). Moreover, C. bovis also effectively reduced the expression of representative pro-inflammatory cytokines and chemokines (Figure 2C). Therefore, these results supported the hypothesis that C. bovis extract is the major anti-inflammatory component in BBD. ## 2.3. Identification of Chemical Constituents in C. bovis Extract Next, we inquired what the major components are in C. bovis extract. A chemical profiling of C. bovis extract was performed by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) analysis. The base peak chromatogram of the C. bovis extract in negative ion mode is shown in Figure 3. We tried to identify the compounds in the six major ion peaks according to their m/z. Based on PeakView software 1.2, the structures of these compounds were further deduced by comparing their molecular formulae and fragment ions with those of existing substances from the literature and public databases (Table 1). Consistent with previous publications [28,29], bile acids were found to be the major components in the ion peaks. A list of eight major bile acids in C. bovis was selected for further pharmacological validation, including Taurodeoxycholate acid (TDCA), Deoxycholic acid (DCA), Taurocholic acid (TCA), Glycocholic acid (GCA), Taurochenodeoxycholic acid (TCDCA), Cholic acid (CA), Glycochenodeoxycholic acid (GCDCA), and Glycodeoxycholic acid (GDCA). ## 2.4. Screening of Anti-Inflammatory Bile Acids in Zebrafish Inflammatory Model Next, the anti-inflammatory effects of the eight bile acids in C. bovis extract were examined in the LPS-induced zebrafish inflammatory model. A rapid phenotypic screening was conducted by assessing the yolk aggregation of fluorescence-labeled macrophages, as described before. All the bile acids were administered at a concentration of 10 µg/mL. As shown in Figure 4A, most bile acids apparently alleviated the inflammation in the yolk sac, and we regarded those groups in which the combined percentage of medium and severe phenotypes is lower than $66.7\%$ as positive hits. Among all the bile acids, TCA and GCA showed the strongest effects on reducing macrophage accumulation. We further examined the regulation of the two compounds on the expression of inflammatory-related biomarkers. Noticeably, the LPS-stimulated upregulation of IL-6, TNF-α, and CCL-2 were significantly inhibited by either TCA or GCA treatment (Figure 4B). Therefore, based on the zebrafish assay, we identified TCA and GCA as two major bile acids in the C. bovis extract exerting endogenous anti-inflammatory activities. ## 2.5. Validation of Anti-Inflammatory Bile Acids in LPS-Stimulated Macrophages In order to further validate the zebrafish screening result and analyze the inflammatory regulatory roles of TCA and GCA directly at the macrophage level, we further evaluated the anti-inflammatory effects of TCA and GCA on the LPS-stimulated mouse macrophage cell line RAW264.7 (Figure 5A). The supernatant was collected subsequently and the concentration of IL-6 and TNF-α was evaluated by the ELISA assay. Similar to the zebrafish analysis, LPS stimulation markedly increased the supernatant concentration of both IL-6 and TNF-α secreted by macrophages, which were significantly rescued by TCA or GCA (Figure 5B,C). The results of the QPCR assay further suggested their function in reducing the transcriptional expression of the two cytokines (Figure 5D). Thus, the anti-inflammatory roles of TCA and GCA were further validated in mouse macrophages. ## 2.6. TCA and GCA Increase the Expression of Farnesoid X Receptor Previous studies suggested that the farnesoid X receptor (FXR) functions as a bile acid receptor and plays essential roles in inflammation inhibition [30,31]. Thus, we investigated the expression level of FXR in macrophages treated with TCA and GCA. Notably, both bile acids were able to greatly increase the transcriptional level of FXR (Figure 6A). In comparison, DEX, which is known to regulate inflammation through the glucocorticoid receptor-related pathway, shows no impact on FXR’s expression. Moreover, the mRNA levels of downstream factors in the FXR signaling, including short heterodimer partner (SHP), ATP-Binding Cassette Transporters G1(ABCG1), and apolipoprotein A1(ApoA1), were also significantly increased after treatment of either TCA or GCA, supporting the positive regulatory roles of both bile acids on the FXR signaling (Figure 6B). We further examined the impact of TCA and GCA on the protein expression of FXR by immunofluorescence. Similarly, TCA or GCA supplementation was able to effectively increase the protein level of FXR (Figure 6C,D). In addition, the impacts of both bile acids on another bile acid receptor, Takeda G protein-coupled receptor 5 (TGR5 or GPBAR1), were also tested. Interestingly, significant upregulation was detected for GCA on the transcriptional level of TGR5. A trend of increased expression of TGR5 was also observed after TCA, although with no statistical significance (Figure S1). Taken together, the above findings prove the positive regulation of TCA or GCA on the expression of bile acid receptors, especially FXR signaling, which may be essential for the anti-inflammatory activities of the two bile acids. ## 3. Discussion Here, we identified TCA and GCA as two major bile acids in C. bovis and the TCM patent drug BBD with regard to their anti-inflammatory effects using both in vivo and in vitro models. TCA and GCA significantly inhibited macrophage migration and the cellular secretion of pro-inflammatory cytokines and chemokines, whose effects are possibly related to the upregulation of FXR expression (Figure 6D). C. bovis is widely used in Asian countries such as China and Japan for the treatment of a variety of diseases, including high fever, convulsions, and stroke. Anti-inflammation has been suggested to be one of the major mechanisms mediating its broad activities by modern studies [14,32]. For example, a study in a formaldehyde-induced inflammatory pain model in rats suggested the protective effects of Taurine, a main component in C. bovis, via suppressing the activities of NF-κB and caspase-3 in brain tissue and downregulating inflammatory factors TNF-α and IL-1 [33]. Oral administration of C. bovis was also found to alleviate the inflammatory damage in the colon tissue of mice ulcerative colitis model induced by dextran sulfate sodium, accompanied by reduced levels of myeloperoxidase, SOD, and mRNA expression of IL-1β, IL-6, and TNF-α [34]. Nevertheless, natural C. bovis is rare and expensive. Only $0.05\%$ of ox is estimated to have gallstones [14]. Moreover, as animal-derived natural products, the chemical components, and thus the bioactivity, may vary a lot. Due to the limited supplies of natural C. bovis, many substitutes are developed and used in some patent natural drugs, including C. bovis Sativus (in vitro cultured C. bovis) and C. bovis artifactus (artificially synthesized C. bovis). However, whether these substitutes can efficiently replace natural C. bovis in drug preparation is still debatable. To solve this problem, systematic deciphering of the active substances in C. bovis is of utmost importance. The most important category of bioactive components in C. bovis is bile acids, with varying amounts in different types of C. bovis [35]. Under physiological conditions, bile acids are synthesized in the liver and secreted to the gastrointestinal tract to facilitate the organism’s digestion and absorption. Bile acids have established roles as signaling molecules in the metabolism and inflammation processes of obesity, type 2 diabetes, dyslipidemia, and nonalcoholic fatty liver disease [30,36,37]. The farnesoid X receptor (FXR; also known as NR1H4) is the first identified nuclear receptor of bile acids [38], which is mainly expressed in the liver, intestine, kidneys, adrenal glands, white adipose tissue, and immune cells [39]. FXR was suggested to downregulate the transcription of IL-6, probably by directly binding to IL-6’s promoter site [40]. A negative regulatory role of FXR on CCL-2 was also reported before, yet the mechanism is less clear [41,42]. Besides, FXR may also induce the expression of the short heterodimer partner (SHP), an atypical nuclear receptor that is increased during macrophage activation and has potential roles in inflammatory diseases [43]. Lack of SHP will lead to the activation of NF-κB and exacerbate hepatic inflammation and fibrosis in mice [44]. Aside from FXR, the ligand of G-protein-coupled receptors (GPCRs, such as TGR5) is also a crucial membrane receptor for bile acids. A recent study reported that through activation of the TGR5-cAMP-PKA axis, bile acids can trigger the phosphorylation and ubiquitination of NLRP3, thus alleviating NLRP3 inflammasome-dependent inflammation [45]. Although the pharmacological effects of C. bovis have been extensively studied, the major active components remain unclear. Here we identified TCA and GCA as the top-ranked bile acids with the strongest anti-inflammatory effect in C. bovis, based on both in vivo and in vitro models. According to the base peak chromatogram of C. bovis in our study, TCA and GCA have the shortest retention times compared to other identified bile acids, which is linked to higher polarity and water solubility. Compared with hydrophobic bile acids, it may be easier for hydrophilic bile acids to pass through the cell membrane and exert their intracellular anti-inflammatory effects. In fact, a previous study examined the content of bile acids in primary macrophages and proved that, although at a lower proportion in plasma [46], TCA and GCA are two bile acids that are enriched most in macrophages [47]. This may be an explanation for the observed strong effects of anti-inflammation and FXR signaling upregulation in our assay, despite the fact that the two bile acids were not among the strongest modulators of FXR [48]. In conclusion, we proposed an in vivo phenotypic screening model using a zebrafish model of acute inflammation induced by LPS microinjection. Combined with macrophage-labeled transgenic lines and fluorescence microscopy, we can quantify the accumulation of inflammation-recruited macrophages endogenously. We applied this model to the drug evaluation and screening of C. bovis and obtained the following major findings: Firstly, the anti-inflammatory effects of BBD and C. bovis were proven in the zebrafish model; Secondly, we identified eight bile acids in C. bovis via chemical analysis and screened for their anti-inflammatory activities in our model system. As a result, TCA and GCA were found to be two efficient anti-inflammatory compounds. Finally, based on an LPS-induced macrophage inflammation model, the anti-inflammatory effects of TCA and GCA were further verified and are possibly mediated through the upregulation of FXR signaling. Based on these findings, we propose that TCA and GCA could be important quality markers for the future development of C. bovis and its related patent drugs and serve as promising lead compounds in the treatment of bacterial infection. Nevertheless, some limitations still remain in our research. Firstly, the total amount of compounds of C. bovis included in our screening is still limited. More comprehensive screening for bioactive compounds in C. bovis is still needed in future studies. Quantitative analysis and multi-drug interaction assays are also necessary to better explain the anti-inflammatory function of C. bovis. Besides, we only examined the anti-inflammatory effects of TCA and GCA in the model of LPS-simulated bacterial infection. The potential roles of these two bile acids in other types of inflammation, such as viral infection, are warranted to be tested. ## 4.1. Sample Preparation One gram of BBD (Xiamen Chinese Medicine Factory, 160730) was dissolved in 20 mL deionized water, ultrasonicated, and centrifugated at 2500 rpm for 5 min. Precipitate was dissolved in 20 mL of $70\%$ ethanol, ultrasonicated, and centrifugated at 2500 rpm for 5 min. The total soluble solid in the $70\%$ ethanol extract was determined and resolved in DMSO (SINOPHARM, 30072418) at a concentration of 5 mg/mL. C. bovis (Xiamen Chinese Medicine Factory) was extracted twice with a 10-fold volume of chloroform-methanol (1:1) for 1 h. The total soluble solid was obtained by centrifugation and concentration, followed by resolving in DMSO at a concentration of 20 mg/mL. Bile acids were dissolved in DMSO at a concentration of 10 mg/mL, including *Taurodeoxycholate sodium* salt (TDCA, DN0032), Deoxycholic acid (DCA, DQ0014), Taurocholic acid Sodium Salt (TCA, DN0030), Glycodeoxycholic acid(GDCA) purchased form Desite (Chengdu, China), Glycocholic acid (GCA, MB5234), Cholic acid (CA, MB5177) purchased form meilunbio (Dalian, China), Taurochenodeoxycholic acid (TCDCA, B20919), Glycochenodeoxycholic acid(GCDCA, B24724), dexamethasone (DEX, B25793) purchased from Yuanye Bio-Technology (Shanghai, China) ## 4.2. Zebrafish Husbandry and Animal Care Ethics Wildtype AB strain and Tg(mpeg:eGFP) transgenic zebrafish were all obtained from the Laboratory Animal Center of Zhejiang University. Zebrafish were maintained following standard protocols. E3 medium (0.29 g/L NaCl, 0.013 g/L KCl, 0.048 g/L CaCl2·2H2O, 0.082 g/L MgCl2·6H2O, pH 7.2) was used as the zebrafish medium. Embryos were obtained through natural spawning. All zebrafish experiments were conducted according to the guidelines of the Animal Ethics Committee of the Laboratory Animal Center, Zhejiang University (No. 24609). ## 4.3. Zebrafish Acute Inflammation Model and Drug Administration Three days post-fertilization (dpf), zebrafish were divided into control (PBS microinjection), model (LPS microinjection), and administration (LPS microinjection + drug administration) groups. Embryos in the administration groups were pretreated with BBD (10 µg/mL), C. bovis (10 µg/mL), bile acids (10 µg/mL), and dexamethasone (DEX, 20 µg/mL) (positive control), respectively. After 24 h of treatment, microinjection was performed in a 1 nL volume per larva with LPS (Solarbio LIFE SCIENCE, L8880) at a concentration of 2.5 mg/mL. The control group used phosphate-buffered saline (PBS) of the same volume as LPS. Embryos were retreated with drugs for 6 h right after recovery from anesthesia ($0.02\%$ tricaine). Wildtype AB strain embryos were used for the qPCR assay, and Tg(mpeg:eGFP) embryos were used for fluorescent phenotype analysis. At least 10 embryos were used for each group. Images were acquired under the Leica DMI 3000 B inverted microscope system (Leica Microsystems Inc., Morrisville, NC, USA). ## 4.4. UPLC-QTOF-MS Analysis LC: Waters UPLC (Waters Corp., Milford, MA, USA), ACQUITY UPLC HSS T3 C18 column (1.7 μm, 2.1 × 150 mm; Waters Corp.) was used in the chromatographic experiments. The mobile phases were $0.1\%$ formic acid-water (A) and $0.1\%$ formic acid-acetonitrile (B). The linear gradient programs were as follows: $\frac{0}{5}$, $\frac{10}{50}$, $\frac{20}{95}$, and $\frac{22}{95}$ (min/B%); sample injection volume, 3 μL; column oven temperature, 50 °C; flow rate, 0.3 mL min−1; and the UV detector was set at 254 nm. Mass spectrometry: AB TripleTOF 5600 Plus System (AB SCIEX, Framingham, USA) was used in the experiment. The optimal MS conditions are negative ion mode: a source voltage of −4.5 kV, and a source temperature of 550 °C. The pressures of Gas 1 (air) and Gas 2 (air) were set at 50 psi. The pressure of curtain gas (N2) was set to 35 psi. The maximum allowed error was set to ±5 ppm. Declustering potential (DP), 100 V; collision energy (CE), 10 eV. For MS/MS acquisition mode, the parameters were almost the same except that the collision energy (CE) was set at ±40 ± 20 eV, ion release delay (IRD) at 67, and the ion release width (IRW) at 25. In a full scan cycle of 1 s, the IDA-based auto-MS2 was performed on the eight most intense metabolite ions. The m/z scan ranges were set at 100–1500 Da for precursor ions and 50–1500 Da for product ions, respectively. The exact mass calibration was performed automatically before each analysis employing the Automated Calibration Delivery System. ## 4.5. Cell Culture and Drug Administration Mice macrophage RAW264.7 cells (ATCC: TIB-71) were purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China). Cells were cultured in high-glucose Dulbecco’s Modified Eagle’s Medium (Gibco) supplemented with $10\%$ heat-inactivated fetal bovine serum (CORNING, 35-076-CV) and $1\%$ Penicillin-Streptomycin-Amphotericin B Solution (Beyotime, C0224) at 37 °C with $5\%$ CO2. Cells were seeded to a 96-well plate (5000 cells/well) for 24 h. Wells were divided into control, model, and administration groups. The control groups were cultured with standard cell culture medium, the model group was treated with LPS (500 ng/mL), and the administration groups were simultaneously treated with LPS (500 ng/mL) and drugs for 24 h. ## 4.6. qPCR Total RNA extraction was conducted using the RNA-Quick Purification Kit (RN001, ES Science) and quantified by nanodrop. Briefly, 2 µg of total RNA was reverse-transcribed into cDNA using a high-performance reverse transcription kit (Easy-Do, Zhejiang, China) according to the manufacturer’s protocol. Quantitative real-time PCR (qPCR) was performed using the UltraSYBR One-Step RT-qPCR Kit (CWBIO) according to the manufacturer’s protocol. Internal standardization was conducted prior to the gene expression of the control group used as a reference, and the 2−∆∆Ct method was utilized for relative quantitative analysis. The primers used for qPCR are listed in Supporting Table S1. ## 4.7. ELISA Assay The concentrations of TNF-α and IL-6 were quantified using ELISA kits which were purchased from eBioscience (San Diego, CA, USA) according to the manufacturer’s instructions. ## 4.8. Immunofluorescence Cells were fixed in $4\%$ paraformaldehyde at room temperature for 0.5 h and permeated by $2\%$ Triton X-100 for 10 min. After 30 min of blocking with PBST ($1\%$BSA and 22.52 mg/mL glycine), FXR primary antibody (1:100) (Proteintech, 25055-1-AP) was added to incubate overnight at 4 °C, followed by adding fluorescent secondary antibody TRITC-conjugated Goat Anti-Rabbit IgG(H + L) (Proteintech, SA00007-2) for 1 h. Then, Hoechst (1:1000) was added and incubated for 10 min to stain the cellular nucleus. Images were taken and analyzed by ImageXpress Micro Confocal (Molecular Devices, San Jose, CA, USA). ## 4.9. Statistical Analysis All data are presented as the mean ± the standard error of the mean (SEM). Differences between the two groups were analyzed using the two-tailed Student’s t-test. Multiple group comparison was conducted by one-way ANOVA. A p-value < 0.05 was considered statistically significant. ## References 1. 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--- title: Regulation of De Novo Lipid Synthesis by the Small GTPase Rac1 in the Adipogenic Differentiation of Progenitor Cells from Mouse White Adipose Tissue authors: - Kiko Hasegawa - Nobuyuki Takenaka - Maaya Yamamoto - Yoshiki Sakoda - Atsu Aiba - Takaya Satoh journal: International Journal of Molecular Sciences year: 2023 pmcid: PMC10003776 doi: 10.3390/ijms24054608 license: CC BY 4.0 --- # Regulation of De Novo Lipid Synthesis by the Small GTPase Rac1 in the Adipogenic Differentiation of Progenitor Cells from Mouse White Adipose Tissue ## Abstract White adipocytes act as lipid storage, and play an important role in energy homeostasis. The small GTPase Rac1 has been implicated in the regulation of insulin-stimulated glucose uptake in white adipocytes. Adipocyte-specific rac1-knockout (adipo-rac1-KO) mice exhibit atrophy of subcutaneous and epididymal white adipose tissue (WAT); white adipocytes in these mice are significantly smaller than controls. Here, we aimed to investigate the mechanisms underlying the aberrations in the development of Rac1-deficient white adipocytes by employing in vitro differentiation systems. Cell fractions containing adipose progenitor cells were obtained from WAT and subjected to treatments that induced differentiation into adipocytes. In concordance with observations in vivo, the generation of lipid droplets was significantly attenuated in Rac1-deficient adipocytes. Notably, the induction of various enzymes responsible for de novo synthesis of fatty acids and triacylglycerol in the late stage of adipogenic differentiation was almost completely suppressed in Rac1-deficient adipocytes. Furthermore, the expression and activation of transcription factors, such as the CCAAT/enhancer-binding protein (C/EBP) β, which is required for the induction of lipogenic enzymes, were largely inhibited in Rac1-deficient cells in both early and late stages of differentiation. Altogether, Rac1 is responsible for adipogenic differentiation, including lipogenesis, through the regulation of differentiation-related transcription. ## 1. Introduction WAT is a type of mammalian adipose tissue serving as storage of lipids, and plays a pivotal role in energy and glucose homeostasis [1]. Triacylglycerol is the main constituent of lipid droplets in white adipocytes, and is synthesized from glucose and fatty acids through multiple metabolic reactions. On the other hand, the transport of glucose and fatty acids into adipocytes from the blood is mediated by various specific transporters. Insulin is known to enhance the synthesis and accumulation of triacylglycerol, as well as glucose and fatty acid uptake in adipocytes. The glucose transporter GLUT4 is responsible for insulin-stimulated glucose uptake in adipocytes [2]. The increase in the level of plasma membrane-localized GLUT4 in response to insulin results in the enhanced uptake of glucose into the cell [2,3]. Signal-transducing pathways downstream of the insulin receptor leading to GLUT4 translocation to the plasma membrane in adipocytes have been investigated extensively for decades, and two major signaling pathways are well characterized [3,4]. One signaling cascade comprises phosphoinositide 3-kinase (PI3K) and the serine/threonine protein kinases PDK1 and Akt2. This signaling cascade plays a crucial role in both adipocytes and skeletal muscle [3,4,5]. Downstream of Akt2, the Akt substrate of 160 kDa, also termed TBC1D4, has been implicated in the regulation of GLUT4 vesicle trafficking in response to insulin, acting as a GTPase-activating protein for the Rab family small GTPase Rab10 in adipocytes [6,7,8]. The other cascade is thought to be specific to adipocytes and independent of PI3K [9]. In addition, the Rho family small GTPase Rac1 has been implicated in insulin-stimulated glucose uptake in primary cultured mouse adipocytes and differentiated mouse 3T3-L1 adipocytes [10,11,12,13]. The guanine nucleotide exchange factor FLJ00068, which is responsible for Akt2-dependent Rac1 activation in skeletal muscle insulin signaling [14,15], was shown to act as a regulator for Rac1 downstream of Akt2 in 3T3-L1 adipocytes [12]. Another small GTPase, RalA, which belongs to the Ras family, also plays an important role in insulin-stimulated GLUT4 translocation [10,11,16,17,18,19]. Considering that RalA is regulated downstream of Rac1 in skeletal muscle insulin signaling [20,21], it is possible that RalA acts downstream of Rac1 in adipocytes as well. Indeed, we demonstrated that RalA regulates GLUT4 translocation downstream of Rac1 in 3T3-L1 adipocytes [11]. To further determine the physiological role of Rac1, we generated mice lacking Rac1 specifically in adipose tissue, adipo-rac1-KO mice [13]. Subcutaneous and epididymal WAT in adipo-rac1-KO mice were significantly smaller than those in wild-type mice. Correspondingly, white adipocytes that lacked Rac1 were smaller than controls [13]. Glucose uptake and GLUT4 translocation in response to insulin were reduced in rac1-KO white adipocytes [13]. In addition, the expression of various enzymes for fatty acid and triacylglycerol synthesis [22,23], including ATP citrate lyase (ACLY), acetyl-CoA carboxylase (ACC), fatty acid synthase (FASN), stearoyl-CoA desaturase 1 (SCD1), and glycerol-3-phosphate acyltransferase 1 (GPAT1), were downregulated in white adipocytes of adipo-rac1-KO mice [13]. Thus, we propose that Rac1 is involved in de novo synthesis of lipids as well as glucose uptake in white adipocytes, regulating hypertrophy of WAT. The expression of the enzymes for the synthesis of fatty acids and triacylglycerol is known to be regulated by a variety of transcription factors, such as the nuclear receptor peroxisome proliferator-activated receptor γ (PPARγ) [24] and CCAAT/enhancer-binding protein (C/EBP) family transcription factors [25], in response to insulin. Thus, it is important to examine expression levels of these transcription factors to clarify the role of Rac1 in the regulation of de novo lipid synthesis in white adipocytes. In this study, we aimed to further reveal the mechanisms underlying atrophy of WAT in adipo-rac1-KO mice, employing in vitro differentiation systems of mouse progenitor cells isolated from WAT and the 3T3-L1 cell line. We show that Rac1 plays a pivotal role in the induction of differentiation into adipocytes, regulating not only glucose uptake but also the expression of diverse enzymes for de novo lipid synthesis. ## 2.1. Establishment and Characterization of an In Vitro Differentiation Assay Using Adipose Progenitor Cells Obtained from Mouse WAT We established an in vitro differentiation assay as a first step to clarify the mechanisms for atrophy of WAT observed in adipo-rac1-KO mice [13]. Collagenase-treated mouse subcutaneous WAT was centrifuged and mature adipocytes as floating cells were removed. We then confirmed that the precipitated stromal vascular fraction (SVF) contained CD34-positive adipose progenitor cells, but not perilipin 1-positive mature adipocytes, by reverse-transcriptase polymerase chain reaction (RT-PCR) analysis [26,27] (Figure 1A). The SVF containing adipose progenitor cells was cultured until cells reached confluence in a culture medium optimized for growth of adipose progenitor cells (KBM ADSC-1) (Figure 1B). The day when cells reached confluence was referred to as day 0. Confluent cells were further cultured for two days in Dulbecco’s modified Eagle’s medium (DMEM)-based growth medium and then subjected to treatment with reagents, such as insulin, which are required for differentiation into adipocytes, as described in Figure 1B. Expression levels of genes for the Cre recombinase and Rac1 during adipogenic differentiation in vitro from progenitor cells were monitored by quantitative RT-PCR analysis (Figure 1C,D). The Cre recombinase transgene is expressed under the control of the adiponectin (Adipoq) promoter, which is specifically activated in adipocytes [28]. Therefore, the expression of the Cre recombinase transgene was expected to increase after the initiation of adipogenic differentiation. In fact, the expression of the Cre recombinase transgene in cells derived from control (adipo-Cre) and adipo-rac1-KO mice was stimulated after 3-day induction of adipogenic differentiation, and reached a plateau at day 4 (Figure 1C). Consistently with these observations, the expression level of the rac1 gene was significantly reduced after 4-day induction of adipogenic differentiation in cells derived from adipo-rac1-KO mice (Figure 1D). The expression of the rac1 gene was enhanced after day 5 in control cells, suggesting a significant role of Rac1 in differentiated adipocytes. After 4-day induction of adipogenic differentiation, small lipid droplets emerged in cells derived from control mice (Figure 1E). In contrast, virtually no cells derived from adipo-rac1-KO mice contained lipid droplets in this stage (Figure 1E). At day 7, a large quantity of lipid droplets was detected in cells from control mice, whereas only a limited number of cells from adipo-rac1-KO mice contained lipid droplets (Figure 1E). Differentiated adipocytes harboring lipid droplets were collected by centrifugation from the cell cultures at day 7, and seeded onto chamber slides. The Rac1 protein and lipid droplets were then stained with an anti-Rac1 antibody and a fluorescent dye for lipid droplets, respectively (Figure 1F). The average size of cells from adipo-rac1-KO mice was significantly less than that of control cells (Figure 1G). The size of lipid droplets in cells from adipo-rac1-KO mice was also measured, and found to be largely reduced compared with that in control cells (Figure 1H,I). Taken together, these results demonstrate that knockdown of the rac1 gene during the process of adipogenic differentiation severely affects the accumulation of lipid droplets in adipocytes. These results also show that the effect of Rac1 deficiency on adipogenic differentiation in vivo is well reproduced by the aforementioned in vitro differentiation assay using adipose progenitor cells. ## 2.2. The Expression of Enzymes for De Novo Synthesis of Fatty Acids and Triacylglycerol during Differentiation of Adipose Progenitor Cells into Adipocytes In Vitro We previously demonstrated that mRNA levels of various enzymes for de novo synthesis of fatty acids and triacylglycerol, such as ACLY, ACC, FASN, SCD1, and GPAT1, were significantly lowered in subcutaneous WAT in adipo-rac1-KO mice [13]. These results suggest that Rac1 is responsible for the regulation of de novo lipid synthesis [13]. To further explore this possibility, we next assessed expression levels of the above enzymes during adipogenic differentiation in vitro. In the control cell culture, the expression of the genes that encode the above enzymes was highly stimulated during adipogenic differentiation (Figure 2). The increase in the expression level of the gene encoding ACLY was observed at day 5, followed by further increase until day 7 (Figure 2A). Likewise, expression levels of genes encoding ACC, FASN and GPAT1 started to increase at day 5, and continued to increase up to the maximal level around day 6 (Figure 2B,C,E). The expression level of the scd1 gene was increased after day 2, and reached a maximum at day 5 (Figure 2D). In marked contrast, virtually no increase in expression levels of all of the above genes was detected in cells derived from adipo-rac1-KO mice (Figure 2). These results provide evidence that Rac1 is intimately involved in the induction of genes that encode enzymes for de novo synthesis of fatty acids and triacylglycerol during adipogenic differentiation. The expression of the scd1 gene was increased until day 3 not only in control cells but also in cells from adipo-rac1-KO mice, because the rac1 gene was not disrupted at this time point (Figure 2D). ## 2.3. The Expression and Phosphorylation of Transcription Factors during Differentiation of Adipose Progenitor Cells into Adipocytes In Vitro To further explore the role of Rac1 in the induction of adipogenic differentiation, we next examined the expression of various transcription factors that have been implicated in the upregulation of differentiation-related genes. PPARγ activates a variety of target genes, regulating adipocyte differentiation and function [24]. The expression level of the gene encoding PPARγ started to increase at day 2, and reached a maximum at day 6 in control cells (Figure 3A). In cells derived from adipo-rac1-KO mice, this gene was induced until day 3, but virtually no additional increase was observed after day 4, at which point the expression of the rac1 gene was suppressed (Figure 3A). Therefore, it is likely that Rac1 is involved in the induction of the gene encoding PPARγ during adipogenic differentiation. Another family of transcription factors, the C/EBP family, is composed of six members, in which the basic leucine zipper (bZIP) domain is conserved at the C terminus [25]. Among them, C/EBPα has been implicated in the control of differentiation into adipocytes through the induction of diverse target genes. The mRNA level of C/EBPα in control cells was increased as adipogenic differentiation proceeded, whereas no induction was observed after day 4 in cells isolated from adipo-rac1-KO mice, similarly to the case of PPARγ (Figure 3B). The expression of genes for C/EBPβ and C/EBPδ isoforms is known to be promoted in the early stage of adipogenic differentiation, and these two isoforms are involved in the induction of PPARγ and C/EBPα [25]. C/EBPβ and C/EBPδ mRNAs were increased to near-maximal levels within two days in cells from both control and adipo-rac1-KO mice (Figure 3C,D). Expression levels of C/EBPβ and C/EBPδ in cells from adipo-rac1-KO mice were largely decreased after 5-day induction of differentiation, in contrast to control cells, in which the expression levels were sustained (Figure 3C,D). Sterol regulatory element-binding protein 1c (SREBP-1c) is a transcription factor implicated in the regulation of fatty acid and triacylglycerol synthesis in the liver and adipose tissue [23,29]. We next examined mRNA levels of SREBP-1c in cells from control and adipo-rac1-KO mice, because SREBP-1c activates genes encoding enzymes for de novo lipid synthesis described above in response to insulin [23,29] (Figure 3E). The mRNA level of SREBP-1c was rapidly increased at day 5 and sustained until day 7 in control cells. In contrast, virtually no increase in the mRNA level was observed in cells derived from adipo-rac1-KO mice. Three different-sized polypeptides, named LAP*, LAP, and LIP, are produced from the C/EBPβ mRNA molecule by alternative use of translation initiation codons [25]. Both transcriptional activation and bZIP domains are present in LAP* and LAP, whereas LIP contains the bZIP domain, but not the transcriptional activation domain. Therefore, LIP is thought to act as a dominant-negative form by dimerizing with LAP* or LAP [25]. Furthermore, sequential phosphorylation of C/EBPβ by mitogen-activated protein kinase, cyclin-dependent kinase 2/cyclin A, and glycogen synthase kinase 3β increases the DNA-binding activity [30]. We then examined protein and phosphorylation levels of LAP*, LAP, and LIP by immunoblot analysis in the late stage of differentiation (Figure 4). Protein levels of LAP* and LAP were sustained from day 5 to day 7 in control cells, whereas the levels in cells derived from adipo-rac1-KO mice were markedly reduced similarly to the mRNA levels (Figure 4A,C,D). The protein level of LIP in cells from control mice was increased at day 6, but rapidly decreased at day 7 (Figure 4A,E). Although the mechanisms for this change remain unclear, the rapid decrease at day 7 may contribute to further induction of target genes. In cells from adipo-rac1-KO mice, the protein level of LIP was also largely suppressed, but its effect on the induction of target genes may be limited due to the low levels of LAP* and LAP (Figure 4A,E). Phosphorylation levels of the above three variants of C/EBPβ were also evaluated by using a phospho-specific antibody. Phosphorylation levels of LAP* and LAP in control cells rapidly decreased at day 7, suggesting lowered transcription activities of these proteins at this point (Figure 4B,F,G). The phosphorylation level of LAP* was largely suppressed in adipo-rac1-KO mice-derived cells from day 5 to day 6, suggesting a role of Rac1 in the regulation of phosphorylation (Figure 4B,F). In contrast, the phosphorylation level of LAP in cells from adipo-rac1-KO mice was similar to that in control cells (Figure 4B,G). The phosphorylation level of LIP was also significantly reduced in cells from adipo-rac1-KO mice (Figure 4B,H). ## 2.4. Protein and Phosphorylation Levels of C/EBPβ in the Early Stage of Differentiation of Adipose Progenitor Cells into Adipocytes In Vitro The induced expression of the rac1 gene after day 5 in control cells suggested an important role of Rac1 in the late stage of differentiation (Figure 1D), and indeed Rac1 was involved in the regulation of lipogenesis in this stage, as described above. It is also important to clarify the function of Rac1 in the early stage of differentiation, because the rac1 gene was significantly expressed (approximately $30\%$ of the maximal level) even before day 3 (Figure 1D), and the activity of Rac1 is generally enhanced through GDP/GTP exchange (GTP-binding) of preexisting Rac1 molecules rather than induced expression [10]. Therefore, we next tested the effect of functional inactivation of Rac1 on the expression and activation of C/EBPβ in the early stage. We cannot examine whether Rac1 is required for adipogenic differentiation before day 3 by Cre-mediated knockdown of the rac1 gene in the in vitro differentiation system using adipose progenitor cells from mouse WAT, because knockdown of Rac1 was initiated at day 4 (Figure 1D). Thus, we employed two types of specific chemical inhibitors of Rac1, RI-II and NSC23766, to address the role of Rac1 in the early stage of adipogenic differentiation. SVF cultures derived from control mouse WAT were treated with RI-II or NSC23766 for 24 h prior to the induction of differentiation, and further treated during differentiation. At day 2, the effect of Rac1 inhibitors on protein and phosphorylation levels of C/EBPβ was examined by immunoblot analysis (Figure 5 and Figure 6). Neither RI-II nor NSC23766 affected cell shape and the formation of lipid droplets in the cell (Figure 5A and Figure 6A). In the absence of the Rac1 inhibitor, protein levels of three C/EBPβ variants were markedly increased at day 2 (Figure 5 and Figure 6). Considering that the increase in the C/EBPβ mRNA level at day 2 was approximately twofold (Figure 3C), it is likely that the rapid increase in the protein level is ascribed to translational upregulation or inhibition of protein degradation. Both RI-II and NSC23766 almost completely inhibited differentiation-associated increase in protein levels of C/EBPβ (Figure 5 and Figure 6). Similarly to the results in the late stage of differentiation (Figure 4), Rac1 inhibition negatively affected the phosphorylation level of LAP*, but not LAP, in the early stage (Figure 5 and Figure 6). On the other hand, Rac1 inhibitors exerted almost no effect on the phosphorylation level of LIP in the early stage (Figure 5 and Figure 6), whereas knockdown of Rac1 resulted in the decreased phosphorylation level of LIP in the late stage (Figure 4). ## 2.5. Role of Rac1 in Differentiation of 3T3-L1 Cells into Adipocytes In Vitro To further confirm that Rac1 plays an important role in adipogenic differentiation, we next examined the effect of Rac1 knockdown in another in vitro differentiation system using the 3T3-L1 preadipocyte line. Adipogenic differentiation of 3T3-L1 cells was induced according to a standard protocol as described previously [11,12] (Figure 7A). The day when cells reached confluence was referred to as day 0. Confluent cells were further cultured for two days in DMEM-based growth medium. At day 2, reagents, such as insulin, were added to the culture medium, inducing adipogenic differentiation (Figure 7A). We infected 3T3-L1 cells with lentivirus expressing control or Rac1-targeting small hairpin RNA (shRNA), and puromycin-resistant cells, which expressed respective shRNAs, were selected. The expression level of Rac1 as determined by immunofluorescent microscopy was actually suppressed in 3T3-L1 cells that expressed Rac1-targeting shRNA (Figure 7B,C). Those 3T3-L1 cells that expressed control or Rac1-targeting shRNA were then subjected to the induction of adipogenic differentiation, as described above. At day 8, a large population of control shRNA-expressing cells harbored lipid droplets, which are characteristic of adipocytes (Figure 7D,E). In marked contrast, lipid droplets were detected in only a small population of cells that expressed Rac1-targeting shRNA (Figure 7D,E). Therefore, it is plausible that Rac1 is required for adipogenic differentiation of 3T3-L1 cells as well. ## 3. Discussion In this study, we investigated the role of Rac1 in adipogenic differentiation using two different in vitro cell systems: adipose progenitor cells obtained from mouse WAT and the 3T3-L1 preadipocyte line. In both systems, functional deficiency of Rac1 led to the attenuated formation of lipid droplets within the cell, a characteristic feature of adipogenic differentiation. Therefore, it is likely that Rac1 is critically involved in the induction of adipogenic differentiation. This conclusion is consistent with our previous findings that subcutaneous and epididymal WAT in adipo-rac1-KO mice is significantly smaller than in control mice, showing severe atrophy [13]. Furthermore, the size of white adipocytes was reduced in adipo-rac1-KO mice compared with those in control mice [13]. A significant observation that needs to be considered is a difference in the adipocyte type between in vivo and in vitro experiments. Although the adipose progenitor cells used in this study were derived from WAT, adipocytes differentiated from these progenitor cells in vitro contained a number of small lipid droplets, but not a single large lipid droplet: these cells were similar in appearance to brown or beige adipocytes, rather than white adipocytes. Further characterization of adipocytes differentiated from the progenitor cells in vitro will be performed in the future. On the other hand, our results lead to the possibility that Rac1 is implicated in the differentiation into brown adipocytes as well as white adipocytes. We are currently investigating this possibility in vivo and in vitro. We have provided evidence that the induction of various enzymes for de novo synthesis of fatty acids and triacylglycerol at the mRNA level during adipogenic differentiation largely depends on Rac1 (Figure 2). This notion was also supported by reduced mRNA levels of these enzymes observed in white adipocytes of adipo-rac1-KO mice in our recent study [13]. These findings are important because defects in de novo lipid synthesis due to the insufficient induction of various enzymes may account, at least in part, for the reduced size of white adipocytes and atrophy of WAT in adipo-rac1-KO mice. Furthermore, we demonstrated that Rac1 contributes to the induction of two transcription factors, PPARγ and C/EBPα, which act as master switches of adipogenic differentiation [24,25] (Figure 3A,B). Towards understanding the mechanisms underlying Rac1-dependent induction of these transcription factors, we then examined the induction of upstream transcription factors—C/EBPβ and C/EBPδ (Figure 3C,D). Moreover, protein and phosphorylation levels of three variants of C/EBPβ were evaluated by immunoblot analysis both in early and late stages (Figure 4, Figure 5 and Figure 6). In the early stage of differentiation (day 2), Rac1 was involved in the rapid increase in the protein level of LAP*, LAP, and LIP. This rapid increase in the protein level is likely to be due to the upregulation of translation or downregulation of protein degradation, given that the increase in the C/EBPβ mRNA level at day 2 was approximately twofold (Figure 3C). The precise roles of Rac1 in the regulation of translation and protein degradation of C/EBPβ remain incompletely understood, and are currently under investigation. In addition, Rac1 was responsible for the induction of C/EBPβ in the late stage (day 5–day 7) (Figure 3 and Figure 4). Rac1 may be involved mainly in transcriptional regulation in this stage, and the detailed mechanisms need to be clarified in future studies. We demonstrated that Rac1 was involved in the induction of the mRNA level of the transcription factor SREBP-1c in the late stage of adipogenic differentiation (Figure 3E). This may also provide an explanation for the decreased expression of various enzymes for the synthesis of fatty acids and triacylglycerol (Figure 2), although the role of SREBP-1c in de novo lipogenesis in white adipocytes remains controversial [23]. Carbohydrate response element-binding proteins (ChREBPs) are also identified as major transcription factors that induce lipogenic enzymes in response to glucose in adipocytes [23]. We did not test the effect of Rac1 knockdown on the induction of ChREBPs in this study, considering that ChREBPs are mostly induced by glucose rather than insulin. However, it is possible that Rac1 knockdown causes insufficient activation of ChREBPs in vivo, because insulin-stimulated glucose uptake in white adipocytes is severely impaired in adipo-rac1-KO mice [13]. This possibility will be tested in our future studies. Rac1 has been implicated in the regulation of insulin-stimulated glucose uptake in white adipocytes [10,11,12,13]. Considering that glucose is utilized for fatty acid synthesis as well as the production of ATP, defects in glucose uptake may be another major cause of the reduced size of white adipocytes in adipo-rac1-KO mice [13]. On the other hand, fatty acid transport from the circulation into adipocytes is also regulated by insulin [31]. Rac1 may be implicated in insulin-stimulated fatty acid uptake because insulin regulates glucose and fatty acid transport across the plasma membrane by similar mechanisms. In this case, defects in fatty acid uptake may be another cause of the impaired accumulation of lipids in white adipocytes in adipo-rac1-KO mice. The expression level of GPAT1, which is responsible for the synthesis of lysophosphatidic acid from glycerol-3 phosphate and fatty acids, was significantly reduced in cells derived from adipo-rac1-KO mice (Figure 2E). Therefore, the synthesis of triacylglycerol is expected to be impaired, at least in part, if sufficient amounts of glucose and fatty acids are incorporated from the blood. Further studies will be needed to better understand the mechanisms. A recent study using a mouse-dedifferentiated fat cell line showed that Rac1 is involved in actin depolymerization-induced differentiation into adipocytes [32]. In particular, insulin-activated Rac1 is thought to regulate the formation of adipocyte-associated cortical actin structures, which is required for the completion of adipogenic differentiation [32]. Therefore, it is likely that Rac1 exerts multiple functions, including the regulation of glucose uptake, the expression of enzymes for lipid synthesis, and cortical actin cytoskeletal rearrangements, in developing adipocytes, and its loss may cause aberrations in these cells. In contrast to our findings, Rac1 has been implicated in negative regulation of the expression of PPARγ and C/EBPα and the accumulation of lipid droplets in 3T3-L1 cells in response to the activation of integrins [33,34]. Thus, Rac1 may exert multiple functions in response to different stimulations in the different processes of adipogenic differentiation. It is important that the results obtained from the analysis of in vitro differentiation systems are interpreted in terms of their relevance to in vivo observations. In the present study, we revealed novel functions of Rac1 that may account for atrophy of WAT in adipo-rac1-KO mice, and further investigations are required to understand the mechanisms in detail. ## 4.1. Materials A mouse monoclonal antibody against Rac1 [610650] was purchased from BD Biosciences (San Diego, CA, USA). A mouse monoclonal antibody against C/EBPβ (sc-7962) was purchased from Santa Cruz Biotechnology (Dallas, TX, USA). A rabbit polyclonal antibody against phospho-(Thr235) C/EBPβ [3084] was purchased from Cell Signaling Technology (Danvers, MA, USA). A mouse monoclonal antibody against α-tubulin (T9026) was purchased from Sigma-Aldrich (St. Louis, MO, USA). A sheep polyclonal antibody against mouse IgG (NA931) conjugated with horseradish peroxidase was purchased from Cytiva (Emeryville, MA, USA). A donkey polyclonal antibody against rabbit IgG (w4018) conjugated with horseradish peroxidase was purchased from Promega (Madison, WI, USA). A donkey polyclonal antibody against mouse IgG conjugated with CF543 [20,305] was purchased from Biotium (Fremont, CA, USA). Rac1-specific inhibitors RI-II [553511] and NSC23766 (S8031) were purchased from Merck (Darmstadt, Germany) and Selleck Chemicals (Houston, TX, USA), respectively. LipiDye (lipid droplet green, FDV-0010) was purchased from Funakoshi (Tokyo, Japan). Insulin was purchased from Eli Lilly (Indianapolis, IN, USA). ## 4.2. Animal Experiments All animal experiments were approved by the Ethics Committee for Animal Experiments at Osaka Metropolitan University (approval codes 20-74, 20-75, 21-81, 21-82, 22-101, and 22-102) and carried out according to the institutional guidelines of Osaka Metropolitan University. All mice used in this study had a C57BL/6 genetic background. We routinely crossbred rac1flox/flox mice [35] with adipo-rac1-KO mice to obtain adipo-rac1-KO mice for experiments. Adipoq-Cre transgenic mice [28] were used as controls throughout this study. Mice were fed a normal chow diet and adult (22- to 26-week-old) male mice were used for all experiments. ## 4.3. Conventional RT-PCR Analysis Total cellular RNA was isolated from the SVF and mature adipocytes using the Sepasol-RNA I Super G (Nacalai tesque (Kyoto, Japan)) according to the manufacturer’s instructions. cDNAs were synthesized using the SuperScript IV first-strand synthesis system for RT-PCR (Thermo Fisher Scientific (Waltham, MA, USA)) and then amplified using KOD FX neo (Toyobo (Osaka, Japan)) and specific primers (Thermo Fisher Scientific) (5′-CTACCACGGAGACTTCTACA-3′ and 5′-ACCATAGTCTCTGAGATGGC-3′ for the cd34 gene, 5′-AGAAGGTGGTAGAGTTCCTC-3′ and 5′-GTGTCGAGAAAGAGTGTTGG-3′ for the perilipin 1 gene, and 5′-CTACAATGAGCTGCGTGTGG-3′ and 5′-CAACGTCACACTTCATGATGG-3′ for the β-actin gene) according to the manufacturer’s instructions. PCR products were analyzed by agarose gel electrophoresis. ## 4.4. Preparation of the SVF from Subcutaneous WAT Subcutaneous WAT was excised from euthanized 22-week-old male mice. Minced subcutaneous WAT was digested in collagenase buffer (20 mM HEPES (pH 7.4), 120 mM NaCl, 5 mM KCl, 4 mM NaHCO3, 1 mM CaCl2, 0.7 mM MgSO4, 0.4 mM KH2PO4, and 0.3 mM Na2HPO4) supplemented with 3 mg/mL collagenase I (031-17601, Fujifilm Wako (Osaka, Japan)) at 37 °C for 1 h. Digested subcutaneous WAT was filtered through 100 μm nylon mesh to get a single-cell suspension, which was then centrifugated at 760× g for 10 min at room temperature. The precipitated SVF was suspended in KBM ADSC-1 (Kohjin Bio, Saitama, Japan) supplemented with 2500 IU/mL penicillin and 2500 μg/mL streptomycin and cultured at 37 °C with $5\%$ CO2 to confluence. ## 4.5. Induction of Differentiation of Adipose Progenitor Cells in the SVF into Adipocytes In Vitro The protocol for differentiation of adipose progenitor cells into adipocytes in vitro is also shown in Figure 1B. The day when cells reached confluence was referred to as day 0. At day 0, the culture medium was changed to DMEM (043-30085, Fujifilm Wako) supplemented with $10\%$ (v/v) fetal bovine serum (FBS) (Corning, NY, USA), 2500 IU/mL penicillin, and 2500 μg/mL streptomycin, and cells were cultured for two days. The culture medium was changed to DMEM supplemented with $10\%$ (v/v) FBS, 100 nM insulin, 1 μM dexamethasone (Dex), 500 μM 3-isobutyl-1-methylxanthine (IBMX), 2 μM rosiglitazone, 2500 IU/mL penicillin, and 2500 μg/mL streptomycin at day 2. After two days, the culture medium was changed to DMEM supplemented with $10\%$ (v/v) FBS, 100 nM insulin, 2500 IU/mL penicillin, and 2500 μg/mL streptomycin, and cells were further cultured for two days. At day 6, the culture medium was changed again to the same medium, and cells were cultured for one more day. In some experiments, cells were treated with 25 μM RI-II or 100 μM NSC23766 from day −1. ## 4.6. Quantitative RT-PCR Analysis Quantitative RT-PCR analysis was carried out essentially as described in [13]. Total cellular RNA was isolated from differentiating cells using the Sepasol-RNA I Super G (Nacalai tesque) according to the manufacturer’s instructions. cDNAs were synthesized using the SuperScript IV first-strand synthesis system for RT-PCR (Thermo Fisher Scientific). PCR was carried out using TB Green Premix Ex Taq II (Takara Bio (Kyoto, Japan)) and specific primers (Thermo Fisher Scientific) with Thermal Cycler Dice Real Time System III (Takara Bio) according to the manufacturer’s instructions. PCR primers are as follows: 5′-AGGTTCGTTCACTCATGGA-3′ and 5′-TCGACCAGTTTAGTTACCC-3′ for the cre gene, 5′-CCTGCCTGCTCATCAGTTAC-3′ and 5′-CCATAGGCCCAGATTCACTG-3′ for the rac1 gene, 5′-GTCTACATCCTTGACTTGGC-3′ and 5′-CACTTTTGGCATCCAGGTCT-3′ for the acly gene, 5′-TACCTGTACAAGCAGTGTGG-3′ and 5′-CAATCCACTCGAAGACCACT-3′ for the acc gene, 5′-TTGCTGGCACTACAGAATGC-3′ and 5′-CTCAGAGCGACAATATCCAC-3′ for the fasn gene, 5′-GAGTACGTCTGGAGGAACAT-3′ and 5′-AGAGCGCTGGTCATGTAGTA-3′ for the scd1 gene, 5′-GCTGGGTGTTACTAAAGCTC-3′ and 5′-GTCAATGTGGGATCTGTGCA-3′ for the gpat1 gene, 5′-AGCATCAGGCTTCCACTATG-3′ and 5′-TGGATCCGGCAGTTAAGATC-3′ for the pparγ gene, 5′-TGGACAAGAACAGCAACGAG-3′ and 5′-GGTCATTGTCACTGGTCAAC-3′ for the c/ebpα gene, 5′-TGAGCGACGAGTACAAGATG-3′ and 5′-AGCTGCTTGAACAAGTTCCG-3′ for the c/ebpβ gene, 5′-GAGCGCAACAACATCGCTGT-3′ and 5′-CGCTGATGCAGCTTCTCGTT-3′ for the c/ebpδ gene, 5′-AACACTGTGACCTCACAGGT-3′ and 5′-CTCCTGCATCTGTCTTCACA-3′ for the srebp1c gene, and 5′-ATGAAGATCAAGATCATTGCTCCTC-3′ and 5′-ACATCTGCTGGAAGGTGGACAG-3′ for the β-actin gene. Relative mRNA levels were determined by the ΔΔCt method followed by normalization with the β-actin mRNA level. ## 4.7. Immunofluorescent Microscopy Immunofluorescent microscopy was carried out essentially as described in [13]. Cells were fixed with 40 mg/mL paraformaldehyde in phosphate-buffered saline (PBS) for 30 min. Rac1 was detected with anti-Rac1 and fluoresceinated secondary antibodies. Lipid droplets and nuclei were stained with LipiDye and 4′,6-diamidino-2-phenylindole, respectively. Images were obtained and analyzed using a confocal laser-scanning microscope (FV1200, Olympus, Tokyo, Japan). Fluorescent intensities were quantified using ImageJ software. ## 4.8. Immunoblot Analysis Immunoblot analysis was carried out essentially as described in [13]. Proteins separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis were transferred onto a 0.45 μm-pore polyvinylidene difluoride membrane (Cytiva, Shanghai, China). Membranes were incubated with primary antibodies, and then horseradish peroxidase-conjugated secondary antibodies. Specific proteins were visualized by Chemi-Lumi One Ultra (Nacalai tesque). Images were captured, and densitometric analysis was carried out using a chemiluminescence imaging system (Ez-Capture MG, Atto, Tokyo, Japan). ## 4.9. Induction of Differentiation of 3T3-L1 Cells into Adipocytes In Vitro Induction of differentiation of 3T3-L1 cells into adipocytes in vitro was carried out essentially as described in [12]. The protocol for differentiation of 3T3-L1 cells into adipocytes in vitro is also shown in Figure 7A. Undifferentiated 3T3-L1 cells were cultured in DMEM supplemented with $10\%$ (v/v) FBS, 100 IU/mL penicillin, and 100 μg/mL streptomycin. The day when cells reached confluence was referred to as day 0. At day 0, the culture medium was changed to the same medium, and cells were cultured for two more days. The culture medium was changed to DMEM supplemented with $10\%$ (v/v) FBS, 100 nM insulin, 1 μM Dex, 500 μM IBMX, 2 μM rosiglitazone, 100 IU/mL penicillin, and 100 μg/mL streptomycin at day 2. After two days, the culture medium was changed to DMEM supplemented with $10\%$ (v/v) FBS, 100 nM insulin, 100 IU/mL penicillin, and 100 μg/mL streptomycin, and cells were further cultured for two days. At day 6, the culture medium was changed again to the same medium, and cells were cultured for two more days. ## 4.10. shRNA-Mediated Knockdown of Rac1 in 3T3-L1 Cells The TRC2-pLKO1-puro plasmid containing shRNA for mouse Rac1 (GGAGACGGAGCTGTTGGTAAA, TRCN0000310888) and the nonmammalian shRNA control plasmid (TRC2-pLKO.5-puro non-target shRNA #1) (SHC202) were purchased from Sigma-Aldrich. Either one of these shRNA expression lentiviral plasmids was introduced into HEK-293TN cells with lentiviral packaging plasmids (pMISSION GAG POL and pMISSION VSV-G) using the TransIT-293 Reagent (Takara Bio). 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--- title: 'Quantitative Assessment of Choroidal Thickness and Choroidal Vascular Features in Healthy Eyes Based on Image Binarization of EDI-OCT: A Single-Center Cross-Sectional Analysis in Chinese Population' authors: - Luping Wang - Wei Wang - Zhuohua Zhou - Hao Wang - Usha Chakravarthy - Tunde Peto - Giuseppe Casalino - Kang Wang - Shuang Li journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003788 doi: 10.3390/jcm12051911 license: CC BY 4.0 --- # Quantitative Assessment of Choroidal Thickness and Choroidal Vascular Features in Healthy Eyes Based on Image Binarization of EDI-OCT: A Single-Center Cross-Sectional Analysis in Chinese Population ## Abstract Purpose: To quantify the structural changes in choroidal vessels and to observe choroid microstructural changes in different age and sex groups in a healthy Chinese population. Methods: Enhanced depth imaging optical coherence tomography (EDI-OCT) was employed to analyze the luminal area, stromal area, total choroidal area, subfoveal choroidal thickness (SFCT), choroidal vascularity index (CVI), large choroidal vessel layer (LCVL), choriocapillaris–medium choroidal vessel layer, and LCVL/SFCT of the choroid in the subfoveal macular area within 1500 μm of the macula. We analyzed the age- and sex-related changes in the subfoveal choroidal structure. Results: A total of 1566 eyes from 1566 healthy individuals were included. The mean age of the participants was 43.62 ± 23.29 years, the mean SFCT of healthy individuals was 269.30 ± 66.43 μm, LCVL/SFCT percentage was 77.21 ± $5.84\%$, and the mean macular CVI was 68.39 ± $3.15\%$. CVI was maximum in the 0–10 years group, decreasing with age, and the lowest values occurred in the >80 years group; LCVL/SFCT was the lowest in the 0–10 years group, increasing with age and reaching a maximum in the >80 years group. CVI showed a significant negative correlation with age, and LCVL/SFCT showed a significant positive correlation with age. There was no statistically significant difference between males and females. Interrater and intrarater reliability was less variable with CVI than with SFCT. Conclusions: The choroidal vascular area and CVI decreased with age in the healthy Chinese population, of which the age-related decrease in vascular components maybe dominated by the decrease in choriocapillaris and medium choroidal vessels. Sex had no effect on CVI. The CVI of healthy populations showed better consistency and reproducibility when compared with SFCT. ## 1. Introduction The choroid is the most vascularized structure in the eye, and choroidal vascular structures are correlated with the pathogenesis of various diseases, including age-related macular degeneration, polypoidal choroidal vasculopathy, central serous chorioretinopathy, and myopic macular degeneration [1,2,3,4,5]. Owing to the anatomical features of the choroid, structural analysis of the choroidal vasculature is challenging and there is a lack of qualitative and quantitative indicators. With the advent of enhanced depth imaging optical coherence tomography (EDI-OCT) technology, which is a modification of standard spectral-domain OCT (SD-OCT) and provides improved signal penetration, the study of the choroidal structure has advanced considerably [6,7,8,9]. Choroidal thickness (CT) is one of the most widely examined choroidal parameters, and has been found to be affected by different variables, such as axial length, refractive error, intraocular pressure, and systolic blood pressure, but does not provide us with information about structural changes in the choroid [10,11]. The application of EDI-OCT image binarization has become a research hotspot in recent years and has made it possible to explore the choroidal structure and its changes in different disease models. Choroidal vascularity index (CVI) is a novel parameter that is calculated from EDI-OCT scans via image binarization. It is defined as the ratio of vascular luminal area (LA) to total choroidal area (TCA), which is presented as a percentage. Several small-sample studies in healthy populations showed that CVI is less affected by physiological variables and has been demonstrated to be a reliable tool, which can quantitatively reflect structural changes in the choroidal vasculature [12,13,14]. CVI combined with subfoveal choroidal thickness (SFCT), LA, and stromal area (SA) can analyze choroidal morphological changes and choroidal blood perfusion. In this study, we assessed the macular choroidal structure in a large sample of healthy Chinese individuals, and analyzed the changes in CVI and the thickness of each choroidal vascular layer with age and sex. We further examined the stability and reproducibility of CVI and SFCT measurements in this healthy population, and performed univariate and multivariate regression analyses. ## 2.1. Population This cross-sectional study was conducted in the Department of Ophthalmology, Beijing Friendship Hospital, from December 2018 to December 2019. Individuals were enrolled according to the inclusion and exclusion criteria. Inclusion criteria: [1] best corrected visual acuity of ≥0.6 and [2] spherical power between +3D and −3D. Exclusion criteria: [1] patients who cannot undergo routine mydriasis; [2] active intraocular inflammation and/or infection, history of any type of intraocular surgery (except cataract surgery); [3] those with retinal and choroidal diseases (except retinal atherosclerosis); [4] those with significant refractive interstitial opacity or abnormalities that affect OCT measurements, such as significant corneal opacity, cataract, vitreous opacity, vitreous hemorrhage, or silicone oil inside the vitreous cavity; [5] those with hypertension, hyperlipidemia, diabetes, heart disease, cerebrovascular disease, pulmonary hypertension, renal disease, and peripheral and central vasculopathy; [6] current smoking and alcohol consumption; [7] those with acute or chronic infectious diseases, infectious inflammatory diseases, and malignancies; and [8] patients who are unable to cooperate in the examination or those in whom clear results cannot be obtained or whose test results cannot be analyzed. This study was approved by the Bioethics Committee of Beijing Friendship Hospital, Capital Medical University (2018-P2-205-01), and conducted in accordance with the tenets of the Declaration of Helsinki. ## 2.2. Data Collection The data included demographic information (age, sex, occupation, marital status, education, and workload), health status (hypertension, diabetes mellitus, coronary atherosclerotic heart disease, hyperlipidemia, cerebrovascular disease, malignancy, peripheral vascular disease, etc.), and daily habits (alcohol consumption and smoking). Ocular data were collected from all enrolled patients, including best-corrected visual acuity, noncontact IOP measurements, slit lamp examination, and color fundus photography. Patients underwent high-definition EDI-OCT scans in both eyes using Spectralis OCT (Heidelberg Engineering, Heidelberg, Germany), and raster scans were performed to cover a 20 × 20° (6 × 6 mm) area. OCT images were acquired from 9:00 a.m. to 12:00 p.m. daily by the same technician (Wei Wang). ## 2.3. Quality Control of Images Patients were enrolled by selecting EDI-OCT images of the left eye first and all data were collected by the same technician (Wei Wang). Three physicians in this study group (Shuang Li, Luping Wang, and Zhuohua Zhou) performed independent assessment of choroidal image clarity in both eyes. If two or more evaluators determined that the image clarity in the left eye was worse than that in the right eye, the patient was enrolled using the right eye image for analysis. After the EDI-OCT images were acquired, three physicians from this study group performed independent evaluations. The images were considered acceptable and used for analysis when two or more investigators determined that the subfoveal choroid was clearly discernible and the choroidal and scleral boundaries were well demarcated. For images with an undefinable sclerochoroidal boundary, two physicians discussed the demarcation. If there was continuing discrepancy between them, the image was given to a third physician for arbitration and if a decision could not be reached, the image was excluded. Subsequent to this process, 27 images were eliminated, leaving 1566 images for consideration. ## 2.4. Range of the Subfoveal Choroidal Area SFCT: defined as the vertical distance from the outer surface of the subfoveal retinal pigment epithelium to the sclerochoroidal junction. SFCT was measured using the built-in software caliper tool (Figure 1). ## 2.5. Thickness Measurement of Each Choroidal Vascular Layer Vascular thickness analysis of each layer of the choroid was performed manually according to Branchini’s method [15]. The large choroidal vessels closest to the fovea were first selected. Large choroidal vessels were defined as those with a diameter of ≥100 μm. A horizontal line was drawn along the inner edge of the large choroidal vessels, and this line intersected the line used to measure the SFCT. Measurements were made from the sclerochoroidal junction to the point where this horizontal line intersected the SFCT measurement line. This length was taken as the thickness of the choroidal large vessel layer. The length of this intersection point to the Bruch’s membrane is equivalent to the thickness of the choriocapillaris–medium choroidal vessel layer (CC+MCVL), which was obtained by subtracting the large choroidal vascular layer (LCVL) thickness from the SFCT. We also calculated the ratio of LCVL to SFCT (Figure 2). ## 2.6. Image Binarization and CVI Measurement The public open-source software Image J (version 1.51) was used to process images (Figure 3). We masked patient information during image processing. The choroidal area centered on the fovea, and nasal and temporal distances of 750 μm were marked. The total choroidal area (TCA) was calculated. We performed 8-bit conversion of the image, and adopted Niblack Auto Local Threshold tool to binarize the selected area. In the binarized image, dark pixels indicated the vascular lumen and white pixels indicated the stromal region. After converting the image to RGB (red, green, and blue) colors, the dark pixels were selected using the color threshold tool, and the LA was calculated. SA was obtained by subtracting LA from TCA. The ratio of LA to TCA constituted CVI. Image segmentation was performed by one of the authors (Shuang Li) (Figure 3). ## 2.7. Interrater and Intrarater Agreement CVI and SFCT were calculated by two examiners (Shuang Li and Zhuohua Zhou) to determine interrater agreement. The CVI and SFCT of the study cohort were calculated by one examiner (Shuang Li) after an interval of 1 week to compute intra-rater reliability. The interrater and intrarater reliability for the measurement of images was measured by the absolute agreement model of the intraclass correlation coefficient (ICC). ICCs of 0.81–1.00 indicate good agreement. ICCs < 0.3 indicate weak or poor agreement. ## 3. Data Analysis The data were analyzed and processed using SPSS 24.0 software. The categorical data were analyzed using the χ2 test. Independent samples t-test and one-way analysis of variance test for normal distributions and Mann–Whitney U test and Kruskal–Wallis test for non-normal distributions were used to compare other parameters between the groups. Univariate and multivariate linear regression analyses were performed to determine the associations among the choroidal parameters, demographic profile, and various ocular factors. The coefficient of variation (CV) was calculated to compare the stability among multiple choroidal parameters. CV = (SD/Mean) × $100\%$. The difference was statistically significant when p-values were <0.05. ## 4.1. Demographic Profile, Ocular and Choroidal Parameters of the Study Participants In this study, 1566 patients were included and 27 were excluded, with a total of 1566 eyes, of which 768 eyes ($49\%$) were in males and 798 eyes ($51\%$) were in females. The mean age was 43.62 ± 23.29 years, ranging from 4 to 94 years. The body mass index (BMI), systolic blood pressure, diastolic blood pressure, fasting blood glucose, and ocular and choroidal parameters are summarized in Table 1. The mean age of men was 46.58 ± 25.81 years, and 46.80 ± 25.25 years for women, with no significant difference between the two groups ($$p \leq 0.886$$). There were no statistically significant differences in age, systolic blood pressure, diastolic blood pressure, fasting blood glucose, ocular characteristics (ocular axis, IOP), and choroidal parameters (TCA, SA, LA, CVI, SFCT, CC+MCVL thickness, LCVL thickness, and LCVL/SFCT) in males compared with those in females (Table 1). ## 4.2. Aging and Choroidal Parameter Changes Patients were grouped based on age, with every 10 years constituting one group. There were nine groups in total (0–10 years, 11–20 years, 21–30 years, 31–40 years, 41–50 years, 51–60 years, 61–70 years, 71–80 years, and >80 years groups). TCA, SA, LA, CVI, SFCT, CC+MCVL thickness, LCVL thickness, and LCVL/SFCT were compared across all nine age groups, and there were statistical differences ($p \leq 0.05$) among groups (Table 2 and Table 3). Figure 4 shows that the CVI was highest in the 0–10 years group (72.42 ± $2.10\%$) and gradually decreased with age, then reached the lowest value in the >80 years group (64.68 ± $3.12\%$). Similarly, SFCT and CC+MCVL thickness peaked in the 11–20 years (280.59 ± 44.23 μm, 75.37 ± 18.69 μm, respectively) and then decreased gradually with age, reaching a minimum in the >80 years group (257.24 ± 63.59 μm, 45.89 ± 14.05 μm, respectively). TCA and SA were least in the 0–10 years group (0.75 ± 0.17 mm2, 0.21 ± 0. 06 mm2, respectively). LA was lowest in the 71–80 years group (0.50 ± 0. 13 mm2) and >80 years age group (0.52 ± 0.15 mm2). LCVL/SFCT was the lowest in the 0–10 years (71.90 ± $6.78\%$), then gradually increased with age and reached the maximum in the >80 years age group (81.98 ± $4.34\%$). ## 4.3. Factors Influencing CVI and LCVL/SFCT Measurements The univariate regression model revealed that age, BMI, ocular axis, LA, SA, LCVL thickness, CC+MCVL thickness, and LCVL/SFCT ratio were significantly correlated with CVI. However, only age, LA, LCVL thickness, and LCVL/SFCT ratio were correlated with CVI in the multiple regression model. Regression analysis showed that CVI decreased with increasing age (Table 4). Age, ocular axis, TCA, LA, SA, CVI, SFCT, and LCVL thickness were significantly correlated with LCVL/SFCT on the univariate regression model. However, only age, TCA, LA, CVI, SFCT, and LCVL thickness were correlated with LCVL/SFCT ratio in the multiple regression model (Table 5). ## 4.4. Coefficient of Variation and Consistency Evaluation The CV was $24.69\%$ for TCA, $26.92\%$ for LA, $25.45\%$ for SA, $4.61\%$ for CVI (LA/TCA), $24.67\%$ for SFCT, $33.16\%$ for CC+MCVL thickness, $26.42\%$ for LCVL thickness, and $7.56\%$ for the LCVL/SFCT ratio. CVI and SFCT were calculated for normal healthy human eyes in the fovea at 1-week intervals by the same examiner, and intergroup consistency was observed using ICC. CVI relative consistency: ICC = 0.987 ($95\%$ confidence interval: 0.982–0.995); SFCT relative consistency: ICC = 0.964 ($95\%$ confidence interval: 0.946–0.975) (Table 6). ## 5. Discussion Recent advances in OCT imaging techniques, especially the EDI-OCT, have helped us better visualize the choroidal layers. Various OCT-related parameters have been developed to evaluate the choroid in healthy and disease states, and mostly evaluating the choroidal thickness and volume [15,16]. CVI is a noninvasive choroidal quantitative parameter, which is easily accessible [17]. The application of CVI has aroused great interest in studying the choroidal vascular structure [17,18]. The use of this quantitative parameter to assess the structural state of the choroid in healthy individuals at different ages can provide additional information for morphological and physiological structures of the choroid [19]. Furthermore, it can aid in observing age-related choroidal changes and help us to better characterize retinal/choroidal diseases, such as age-related macular degeneration, inflammatory chorioretinal disorders, pachychoroid disease spectrum, myopia, and inherited retinal disorders [20,21,22,23,24]. Sonoda et al. [ 15,24] first used image binarization to study LA and SA of the choroid in EDI-OCT images of healthy eyes. They reported a significant decrease in LA, SA, and LA/SA ratios with age, indicating a greater decrease in vascular LA than in SA. Ruiz-Medrano et al. [ 25] studied healthy individuals in a larger age range (3–85 years) and reported a significant decrease in LA and CVI with age while SA remained stable. However, the aforementioned study included only a limited sample size (136 individuals), the number of patients in each group was small, and data were missing for the younger children and the elderly population after stratifying by age [25]. Our study demonstrated a strong correlation between CVI and age in the macular region in this cohort of a healthy Chinese population, and the LA and CVI decreased with age. The SA was found to be smaller in the 0–10 and 11–20 age groups and gradually increased with age, reaching a maximum in the 61–70 age group, and then relatively stabilized. Previous histological studies have shown that the volume of choroidal cells and interstitial components decreases with age [26,27]. Several studies on choroidal immunohistochemistry reported a decrease in CT with age, accompanied by a significant decrease in collagen fibronectin, and cellular components in the choroid [26,27,28]. In addition, it is known that vascular tone and the amount of endothelial nitric oxide synthase (eNOS) decrease with age, thereby leading to a decrease in circulating blood volume [29,30]. All of these observations support the results of the present study. In our study population, both CVI and subfoveal LCVL/SFCT had less variability than that observed in SFCT. Moreover, previous studies showed that CVI and subfoveal LCVL/SFCT are less affected by physiological factors other than age [31]. These observations suggest that CVI and subfoveal LCVL/SFCT are relatively stable markers for studying choroidal changes. The CV of CVI was smaller compared with LCVL/SFCT in the fovea, indicating that CVI is a better and relatively more stable marker for monitoring the choroid and provides more information than a simple SFCT measurement. The univariate analysis of ocular and systemic factors correlated with CVI showed significant correlations with age, BMI, ocular axis, LA, SA, LCVL thickness, CC+MCVL thickness, and LCVL/SFCT ratio. However, age, LA, LCVL thickness, and LCVL/SFCT ratio were factors correlated with CVI in the multiple regression model of this study. Of these, there was a strong correlation with age and a weak correlation with all other factors. Of note in the group of 0–10 years, the ocular axis is shorter, and the CVI is significantly higher. This may be due to the children at this stage having hyperopia and thicker choroid. In groups older than 10 years, natural growth and developmental processes of the eye, such as axial elongation and choroidal thinning, might play a role in reductions in CVI. We also observed that LCVL/SFCT showed a statistically significant correlation with age and CVI. Hence, understanding the age-related changes in choroidal structure in healthy eyes is important for the clinical application of CVI. This can better explain the differences in choroidal structure in patients of different ages and help explore the pathogenesis of various diseases, especially in ocular diseases with a strong correlation to age, such as age-related macular degeneration and adolescent myopia. Furthermore, we observed a significant correlation between BMI and CVI in the univariate analysis. Since the current study included only healthy people with a mean BMI of 23.75 ± 5.72, we intend to study the high BMI population in future research, and analyze the changes in the choroidal vascular structure in the obese population. Agrawal et al. reported that CVI was less variable than SFCT, and SFCT was affected by more factors than CVI [12]. In that population-based study, they included 345 healthy eyes. Except for CVI and SFCT, in the present study, we also measured LCVL, CC+MCVL, and LCVL/SFCT, expecting to find the correlation between the thickness of these two parts of the vascular layer and age. LCVL thickness was the smallest in the age group of 0–10 years, then gradually increased and peaked in the age group of 41–50 years, after which it slightly changed with age. CC+MCVL thickness was the maximum in the age group of 11–20 years, then gradually decreased with age and reached the minimum after 80 years. LCVL/SFCT was the smallest in the group of 0–10 years, then increased gradually with age and reached the maximum in the group of >80 years. LCVL thickness changed very little with age >20 years, but CC+MCVL decreased significantly with age. We inferred that some of the choriocapillaris may occlude and detach with age, which may also be correlated with the occurrence of age-related macular degeneration. The CV of LCVL/SFCT was $7.56\%$. It is also a relatively stable biological parameter for monitoring choroidal vascular structures, an understanding of its age-related changes in normal eyes could enable further exploration of the pathogenesis of various age-related fundus diseases. We further observed the measurement consistency of CVI and SFCT, and the repeatability of both parameters was within the confidence range. Compared to SFCT, the ICC values of CVI were significantly higher and exhibited better measurement consistency. The strengths of our study are [1] *It is* a large-sample observation with a single common ethnicity, and is less likely to be confounded by ethnic heterogeneity. [ 2] Our study applied standardized clinical examination protocols and image processing procedures. [ 3] We confirmed that CVI and LCVL/SFCT had less variability than that observed in SFCT. However, this study has several limitations: [1] Binarization of the images was only conducted in the single eye of each study subject. [ 2] Although OCT images were binarized at standardized protocols, there was a possibility of over or underestimation of LA and SA. [ 3] Our study mainly focused on the subfoveal region, the extramacular choroidal vascular features in individuals have remained largely unexplored. In conclusion, in this study based on a large sample of subjects, we found that CVI of healthy populations showed better consistency and reproducibility when compared with SFCT. In addition, we demonstrated that the choroidal vascular area and CVI significantly decrease with age. Age-related decrease in vascular components maybe dominated by a decrease in CC+MCVL. Our findings provide new insights that may be helpful in future studies on the pathophysiology of the human choroid. Larger datasets in different disease states are needed to further validate the value of these markers for application in clinical practice. ## References 1. 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--- title: Electrochemical Characterisation and Confirmation of Antioxidative Properties of Ivermectin in Biological Medium authors: - Milan Selaković - Mara M. Aleksić - Jelena Kotur-Stevuljević - Jelena Rupar - Branka Ivković journal: Molecules year: 2023 pmcid: PMC10003826 doi: 10.3390/molecules28052113 license: CC BY 4.0 --- # Electrochemical Characterisation and Confirmation of Antioxidative Properties of Ivermectin in Biological Medium ## Abstract Ivermectin (IVM) is a drug from the group of anthelmintics used in veterinary and human medicine. Recently, interest in IVM has increased as it has been used for the treatment of some malignant diseases, as well as viral infections caused by the Zika virus, HIV-1 and SARS-CoV-2. The electrochemical behaviour of IVM was investigated using cyclic (CV), differential pulse (DPV) and square wave voltammetry (SWV) at glassy carbon electrode (GCE). IVM showed independent oxidation and reduction processes. The effect of pH and scan rate indicated the irreversibility of all processes and confirmed the diffusion character of oxidation and reduction as an adsorption-controlled process. Mechanisms for IVM oxidation at the tetrahydrofuran ring and reduction of the 1,4-diene structure in the IVM molecule are proposed. The redox behaviour of IVM in a biological matrix (human serum pool) showed a pronounced antioxidant potential similar to that of Trolox during short incubation, whereas a prolonged stay among biomolecules and in the presence of an exogenous pro-oxidant (tert-butyl hydroperoxide, TBH) resulted in a loss of its antioxidant effect. The antioxidant potential of IVM was confirmed by voltametric methodology which is proposed for the first time. ## 1. Introduction At the onset of the 2019 coronavirus pandemic (COVID-19), before any recognised effective treatment or currently approved vaccine therapy was available, an urgent need arose to re-evaluate existing medicines for the treatment of SARS-CoV-2 virus infection [1]. When IVM, a member of the avermectin family, demonstrated its antiviral potential against the virus [2], interest in IVM skyrocketed and there were numerous attempts to repurpose it for the treatment of COVID-19. IVM was first discovered in the 1970s by microbiologist Satoshi Omura and parasitologist William Campbell and is an anthelmintic drug [3]. IVM is a macrocyclic lactone derived from avermectins and is a mixture of two homologues: 22,23-dihydroavermectin B1a (≥$80\%$) and 22,23-dihydroavermectin B1b (≤$20\%$). It was first marketed for use in animals in 1981, but is also used to treat various diseases in humans, such as onchocerciasis [4]. Ivermectin is considered the drug of choice for various parasitic diseases [1]. IVM has been reported to be used in the treatment of some malignant diseases, as well as viral infections caused by the Zika and HIV-1 viruses and the SARS-CoV-2 virus [5]. Since the spike in interest, a number of electrochemical methods for the detection of IVM have been reported, such as the use of a boron-doped diamond (BDD) electrode cathodically pretreated with 0.5 mol L−1 H2SO4 for detection in pharmaceutical formulations and urine [6]; GCE modified with silver nanoparticles at modified boron and sulphur co-doped reduced graphene oxide nanohybrid (AgNPs B, S@rGO) for detection in injections, urine and tap water [7]; glutaraldehyde-modified GCE for detection in tap water and urine [8]; and β-cyclodextrin/graphene-based electrode for detection in tap water [9]. The BDD electrode provides a sensitive, simple, inexpensive and rapid amperometric flow injection method with results that show good agreement with comparable methods. However, the potentiostatic electrolyses resulted in fouling of the BDD electrode surface, which made it impossible to estimate the number of electrons involved in the process and to propose an oxidation mechanism of the IVM [6]. The modified electrode showed significantly increased sensitivity in IVM determination due to the synergistic effects of AgNPs and B, S@rGO. The proposed sensor exhibited good selectivity, reproducibility and long-term stability [7]. The glutardialdehyde-modified glassy carbon electrode showed high sensitivity, selectivity and stability [8], while the β-cyclodextrin/graphene-based electrode resulted in excellent analytical performance for the electrochemical detection of IVM [9]. None of the methods have characterised the electrochemical behaviour of IVM, none have been performed on a non-modified GCE and none of the methods for detecting IVM have been performed in human serum as biological material in which the distribution of IVM should be expected. Electrochemical characterisation of IVM was performed with the aim of better understanding the redox behaviour of the molecule, as well as predicting possible oxidation/reduction mechanisms and potential transformations during interaction with other electroactive biomolecules. Electrochemical methods are inexpensive, fast and easy to perform, making them ideal candidates for drug analysis. Oxidative stress is the result of an imbalance in cellular antioxidant capacity and cellular levels of reactive oxygen species (ROS) and leads to damage in important cellular components such as DNA, proteins and lipids. The effects of oxidative stress are observed in a number of diseases, as well as in a variety of drug-induced toxicities [10]. Antioxidant activity is traditionally studied by well-known spectrophotometric methods, but they have some disadvantages. Very often, these methods require a lengthy and demanding pretreatment; especially for biological samples, the results may be affected by the turbidity of the sample. Therefore, the electrochemical approach could be very important as an independent and comparative method in the measurement of antioxidants and antioxidant activity due to its fast and simple methodology and the good stability of the electrochemical signal, which is not affected by turbid or opaque samples. Most studies using electrochemical approach in the measurement of antioxidant activity are used for the determination of polyphenolic compounds. Among them, the concept of electrochemical index (EI), defined as the total polyphenolic content obtained by nonselective oxidation of all polyphenols [11,12], is very promising because it uses the peak anodic potential and current to estimate the ease with which the compound is oxidized. In our study on IVM, a different approach was used—we employed DPV and used voltametric peak parameters to estimate the antioxidant properties of IVM in human serum samples. According to the order of occurrence of oxidation peaks, the following rule applies: the lower the oxidation potentials, the greater the ability of the compound to act as an electron donor, which is associated with higher antioxidant activity and antioxidant capacity. The aim of this study is to investigate the redox activity of IVM in human serum pool of healthy individuals in order to compare it with a known antioxidant, Trolox (a water-soluble analogue of vitamin E), and to predict its pro-oxidant and antioxidant activity in vitro, as well as to propose which part of the chemical structure is responsible for the effect. A new electrochemical method to confirm the results of the oxidative stress testing is also proposed. ## 2.1. Electrochemical Characterisation Preliminary tests were performed by CV in a 0.2 mmol L−1 IVM solution in 0.1 mol L−1 acetate buffer pH 4.6. Voltammograms were recorded in three consecutive scans, starting from 0.0 V to +1.6 V and back to −1.6 V; and from 0.0 V to −1.6 V and back to +1.6 V. Both voltammograms were recorded at a scan rate ν = 50 mV s−1. In the case where the potential was scanned towards the positive limit, two peaks appear in the first scan of the voltammogram: one main anodic peak (A1) at a potential of about +1.0 V, which decreases with the subsequent scans, and one cathodic peak (C1) at a potential of about −0.5 V, which does not change. In the second scan, another anodic peak (A2) appears at a potential of about +0.3 V, indicating that it was detected as an oxidation peak of the previously reduced form of the drug (Figure 1). When the scan direction was changed and scanned from 0.0 V to −1.6 V and back to +1.6 V (not shown), IVM again revealed one cathodic peak (C1 at about −0.5 V), but in this case two anodic peaks (A2 at +0.3 V and A1 at +1.0 V), both in the first scan. The appearance of the A2 peak (when scanning in this direction) in the first scan is probably due to the strong negative potential applied previously, which caused the formation of the reduced form of the drug that can be further be oxidised. It should be noted that the intensity of the oxidation peak A2 is very weak compared to the main oxidation product (A1 peak). All recorded CVs of IVM at different pH values (pH range 2–10) showed the same behaviour. The irreversibility of the oxidation and reduction processes was also confirmed, as both the anodically and cathodically recorded peaks did not show a corresponding reversal response. ## 2.2. Oxidation The oxidation of 0.2 mmol L−1 IVM and the corresponding anodic peak (A1) were observed in the supporting electrolytes at different pH values from 2.0 to 10.0 (Figure 2a). The oxidation peak exists at all pH values studied and the peak potential shifts to less positive values with the increasing pH value. Both the potential and the intensity of the A1 peak are pH dependent. The intensity of the peak is highest around pH 7.0, i.e., in neutral solutions. The dependence of Ep vs. pH shows the characteristic “S” shaped curve, with linear dependence in the pH range 4–8, which follows the equation (Figure 2b):Ep,A1 = 1.310 V − 0.050 pH.[1] The slope of 50 mV/pH indicates that the proton–electron ratio is 1:1, which means that the same number of protons and electrons are involved in the electrode process [13]. From the difference between the peak potential and the peak potential at half height for irreversible electrode processes—defined by the equation [2]Ep,A1−Ep$\frac{1}{2}$, A1 =47.7αnn, where the charge transfer coefficient αn can be approximately 0.5—the number of electrons transferred in the rate-determining step (n) can be calculated [14]. In the case of the A1 peak, the above-mentioned potential difference was between 80 and 100 mV (depending on the pH), which indicates that one electron is involved in the reported oxidation process. To investigate the influence of scan rate, CVs were recorded with a concentration of 0.2 mmol L−1 IVM at pH 4.6 and pH 6.9 at different scan rates ranging from 10 to 100 mV s−1. A linear dependence of Ip,A1 vs. the square root of the scan rate (ν$\frac{1}{2}$) was observed at both pH values. The regression equations Ip = 7.361 × 10−7 + 1.112 × 10−4 ν$\frac{1}{2}$,[3] with a correlation coefficient of $r = 0.998$ (pH 4.6), and Ip = −1.840 × 10−6 + 1.669 × 10−4 ν$\frac{1}{2}$,[4] with a correlation coefficient of $r = 0.997$ (pH 6.9)—were determined (Figure 3a). The obtained value of the correlation coefficient, which is close to unity, indicates that IVM oxidation is a diffusion-controlled reaction in mild acidic and neutral solutions. A value of the intercept that slightly deviates from 0 (at both pH values) suggests that the electrode process is preceded by a chemical reaction, i.e., proton transfer. A linear dependence of log Ip,A1 vs. log ν was observed at both pH values (Figure 3b). The corresponding slopes were always close to the theoretical value of 0.5, confirming that the oxidation process of IVM in mild acidic and neutral solutions at the GCE is a diffusion-controlled process. DP voltammograms of 0.2 mmol L−1 IVM solution were recorded in the same supporting electrolytes as for CV at various pH values from 2.0 to 10.0. One well-developed oxidation peak (A1) was observed (Figure 4a). Both the potential and the intensity of the A1 peak are pH-dependent. The intensity of the peak is highest at pH 5.0–6.0. The potential decreases with the increase in pH, with a linear part of the curve in the range 3.5–7.5 with the slope of ΔEp/ΔpH = 52 mV (Figure 4b). When the half peak width (W$\frac{1}{2}$) was analysed, it was found that its value is approximately 90–120 mV at pH ≤ 7 and increased with pH. According to the results of the pH influence on IVM DP voltammograms, the conclusions from CV are confirmed as follows: the oxidation process, represented by the A1 peak, is pH-dependent and proceeds with the exchange of one electron and one proton. SW voltammograms of 0.2 mmol L−1 IVM solution were also recorded in supporting electrolytes at various pH values from 2.0 to 10.0. The same well-developed oxidation peak (A1) (not shown) as in DP voltammograms was observed. As stated, both the potential and the intensity of the A1 peak are pH-dependent. The intensity of the peak is highest at pH 5.0. The peak potential decreases as the pH increases. Since this technique registers both oxidation and reduction currents in the same experiment, the irreversible nature of oxidation was confirmed by analysing the forward and reverse current components of the A1 peak. The second oxidation peak (A2) was only visible in the second and third scans (Figure 1), indicating that it originates from the oxidation of the previously reduced form of the drug. The potential of the A2 peak is pH-dependent and shifts to more negative values with the increasing pH, while the intensity is not pH-dependent. As stated, an “S”-shaped curve was obtained with a linear segment in the narrow pH range (3–5), where the dependence of Ep vs. pH followed the equation (Figure 2c):Ep,A2 = 0.550 V − 0.058 pH.[5] The slope of 58 mV indicates that an equal number of electrons and protons are involved in the electrode process. The A2 peak was not visible in DP and SW voltammograms. ## 2.3. Reduction The reductions of IVM and the corresponding cathodic peak (C1) were observed in supporting electrolytes at different pH values (Figure 2d). In an acidic environment, it is absent; at pH 3.5, it is weak and hardly visible; and with a further increase in pH, the C1 peak increases with uniform intensity. At pH 4.5 < pH < 7.5, a linear dependence of the peak potential on pH was determined according to the following equation:Ep,C1 = −0.259 V − 0.055 pH.[6] The slope of 55 mV indicates that the number of protons involved in the electrode process is equal to the number of electrons. In more alkaline solutions (pH > 7.5) the C1 peak potential flattens out and the slope Ep vs. pH decreases significantly, indicating that the reduction process does not involve proton transfer under these conditions. Since the differences between peak potential and peak potential at half-height (Ep,C1−Ep$\frac{1}{2}$, C1) were −0.095 V (pH 4.6) and −0.097 (pH 6.9), it is indicated that one electron is exchanged in the reduction process represented by the reduction peak C1 [14]. To investigate the influence of scan rate, CVs were recorded with a concentration of 0.2 mmol L−1 IVM at pH 4.6 and pH 6.9 at different scan rates of 10–100 mV s−1. A linear dependence of Ip,C1 vs. the scan rate (ν) was observed at both pH values. The regression equations (Table 1) provide a high correlation coefficient of r > 0.99, indicating that IVM reduction is an adsorption-controlled reaction in acidic and neutral solutions. As previously mentioned, a value of the intercept that slightly deviates from 0 suggests that the electrode process at both pH values is preceded by a proton transfer. Moreover, the linear dependence of log Ip vs. log ν was observed at both pH values (Table 1). The corresponding high slopes close to unity confirm that the reduction process of IVM at GCE is controlled by adsorption. ## 2.4. Reaction Mechanism Based on the electrochemical data obtained and presented, a mechanism of oxidation and reduction is proposed in Figure 5. The oxidation and reduction sites on the IVM structure (Figure 5a) are marked in red and green, respectively. The oxidation takes place at position 8A in the tetrahydrofuran (THF) ring [15]. In the first step, IVM forms an intermediate radical (8-ivermectin radical) in contact with the electrode, which further reacts with the OH radical from the water to form 8-hydroxy ivermectin (8-OH IVM) as the main product (Figure 5b). Considering the experimentally obtained results, we assume that the reduction process of IVM takes place at the 1,4-diene structure in slightly acidic and neutral medium. In the first step, a resonantly stabilised carbocation is formed by protonation, which receives an electron and forms the product IVM-R (Figure 5c). ## 2.5. Antioxidant Properties IVM stock samples were prepared by dissolving in dimethyl sulfoxide (DMSO) or in a mixture of polyethylene glycol and glycerol (PEG/Gly) in a 6:1 ratio. Two sets of serum pool samples were prepared. The first set was incubated for 2 h at 37 °C, and the second for 24 h to mimic the internal conditions of the organism. After incubation, redox status parameters were measured in the prepared serum pool samples: serum pro-oxidant-antioxidant balance (PAB) and serum total oxidant status (TOS) (as representatives of pro-oxidants), and total antioxidant status (TAS) and levels of total sulfhydryl groups (SHG) (as representatives of antioxidants). Z-scores were calculated from the measured parameters to estimate the difference between the redox status of the pool of natural serum samples and the addition of IVM stock samples. The Z-score values enabled the pro-oxidant score (PS, as the average Z-score value of TOS and PAB Z-scores), the antioxidant score (AOS, as the average value of TAS and SHG Z-score values). The oxy-score (OS) was calculated as the difference between the values of PS and AOS. The results are shown in Table 2 and Table 3. The presence of dose-dependent activity was tested with 5 different dilutions in 2 different solvents. Since no significant change was found in the measured parameters, the results presented are the average of all 5 different concentrations. Trolox, which was used as a strong representative of the antioxidants in serum, showed the lowest pro-oxidant and highest antioxidant activity (Figure 6a,b), whereas TBH, which was used as a strong representative of the pro-oxidants, shows the highest pro-oxidant activity in serum (significantly higher than the pro-oxidant activities of Trolox, $p \leq 0.01$). Both IVM solutions showed similar antioxidant properties to Trolox after 2 h of incubation in serum. When TBH is added to serum with the IVM solutions, the oxy-score is significantly higher after 2 h of incubation compared with Trolox (Figure 6c, $p \leq 0.001$), indicating that the antioxidant effect of IVM is present but not sufficient to counteract the potent pro-oxidant effect of TBH. After the 24-h incubation (Figure 7), Trolox alone showed the lowest oxidative effect in serum compared with IVM solutions alone ($p \leq 0.001$), IVM solutions with TBH ($p \leq 0.001$), and TBH alone in serum ($p \leq 0.001$). TBH alone in serum still shows the highest pro-oxidant potential and a statistically significant difference is observed compared to Trolox alone, as well as to both IVM solutions alone in serum. While there is a significant difference between Trolox and IVM solutions when comparing the oxidative and prooxidative values, no difference is observed when comparing the antioxidant value, which means that the behaviour of IVM, which is more similar to Trolox, does not change over time. When comparing the pro-oxidant, antioxidant and oxy-scores of samples incubated for 2 h versus 24 h, a statistically significant difference ($p \leq 0.01$) was observed between the pro-oxidant and antioxidant values (both values were higher after the 24-h incubation) of the IVM solution in PEG/Gly, but no difference was observed in the oxy-scores of the solutions, implying that the differences cancel each other out. Since no difference was observed in the IVM solutions in DMSO, this could be the result of a synergistic effect between the antioxidant effect of DMSO and IVM, which means that IVM solutions in PEG/Gly need more time to develop their effect. However, the use of DMSO up to 0.5 mL has not shown any effect on antioxidant assays, although it could be an antioxidant under certain conditions and/or concentrations [16]. Since it has been concluded that IVM has antioxidant activity, a proposed reaction for the oxidation of IVM is shown in Figure 8. Oxidation occurs in a reaction with oxygen (O2) dissolved in the serum at the THF ring in position 8A (marked in red) and an unstable peroxide is formed [15]. ## 2.6. Electrochemical Analysis of the Antioxidative Properties To confirm the results of the spectrophotometric measurements, voltametric DP measurements were carried out. In a small voltametric cell (volume 1.5 mL), DP voltammograms were recorded from blank serum pool samples and from serum with the addition of IVM, Trolox and TBH. Measurements were taken immediately after addition and after 2 h and 24 h incubation at 37 °C. All investigated substances can be oxidised at the GCE and give oxidation peaks at different potentials: Trolox at Ep = 0.08 V, serum at Ep = 0.40 V, IVM at Ep = 0.85 V and TBH at Ep = 1.255 V (Figure 9a). Considering the increasing values of the oxidation potential of these compounds, it can be assumed that *Trolox is* the easiest and TBH the most difficult to oxidise, which is consistent with the fact that Trolox has a higher antioxidant effect than TBH and is a well-known antioxidant. Since the oxidation of IVM has already been confirmed, the aim of further experiments was to study its behaviour after incubation in serum samples and compare it with Trolox and TBH. As can be seen in Figure 9b, the intensity of the TBH oxidation peak increased sharply with increasing incubation time. In contrast, IVM and Trolox showed no significant change. It is interesting to follow the change in serum oxidation peak after addition and incubation of all compounds (Figure 10a). When TBH was added to the serum sample, its oxidation peak at about 0.4 V disappeared almost immediately and was no longer seen in the voltammogram when incubated for up to 24 h. In the presence of Trolox and IVM, the height of the serum oxidation peak decreased to about $80\%$ and 70 % of its original height, respectively. When TBH was added to the serum along with the IVM solutions, the oxidation peak of IVM (green line) decreased dramatically (blue line), whereas the level of the oxidation peak of IVM changed only insignificantly when Trolox was added (red line) throughout the 24 h incubation period (Figure 10b). The effect of TBH on IVM oxidation could be explained by the fact that TBH, as a strong oxidising agent, completely oxidises the IVM present in the serum sample, leaving nothing behind that could be subsequently oxidised at the electrode. Trolox, on the other hand, as a reducing agent, has no effect on the IVM oxidation process. The summary of the results presented suggests that IVM has similar antioxidant properties to Trolox after incubation in human serum samples, which is consistent with the spectrophotometric measurements and the corresponding oxy-score of IVM, based on the calculated pro-oxidant and antioxidant scores. ## 3.1. Chemicals IVM was obtained from Horster Biotek Pvt. Ltd. India (serial number: 21,005 HBL, LOT: IVR/20-$\frac{21}{011}$, expiration date: 01.2025.). A stock solution of IVM (2 mmol L−1) for electrochemical characterisation was prepared in methanol. Stock solutions of IVM (0.25 mmol L−1) for the biochemical assays were prepared by dissolving IVM in DMSO or PEG/Gly mixture in a 6:1 ratio. Solutions of different concentrations for electrochemical characterisation were obtained by diluting the stock solution with different supporting electrolytes prepared with chemicals of analytical-grade quality. The following supporting electrolytes were used: citric acid/sodium hydroxide buffer (pH 2.20, 3.06), acetate buffer (pH 3.58, 4.63, 5.05, 5.64), phosphate buffer (pH 6.20, 6.96, 7.93) and ammonia/ammonium chloride buffer (pH 8.51, 9.50) [17]. The ionic strength of all solutions was adjusted to 0.1 mol L−1. All experiments were performed at room temperature (25 ± 1 °C). The serum pool was prepared from serum samples of healthy individuals and kindly donated by the Military Medical Academy in Belgrade after daily work in the biochemical laboratory, which would otherwise be destroyed as biological waste. Aliquots of the serum pool were frozen at −80 °C and analysed within 5 days of collection. Biochemical analysis: All samples were incubated in duplicate for 2 and 24 h at 37 °C. Serum pool samples (450 μL) were mixed in 1:10 ratio with different solutions (50 μL) as follows: Trolox (2 mmol L−1), TBH (0.25 mmol L−1) and dilutions of IVM stock solution (0.25–0.015625 mmol L−1). The IVM samples were mixed in equal parts with TBH to test its reactivity in the presence of exogenous pro-oxidants (exactly 25 μL were added to the serum pool samples). Electrochemical assays: Serum pool samples (1.35 mL) were mixed in a 1:10 ratio with different solutions (0.15 mL) as follows: Trolox (2 mmol L−1), TBH (0.25 mmol L−1), IVM (2 mmol L−1 stock solution in methanol), IVM + Trolox (75 μL each) and IVM + TBH (75 μL each). Voltammograms were recorded after addition ($t = 0$ h), after 2 h and after 24 h incubation at 37 °C. ## 3.2. Apparatus A μAUTOLAB analyser (EcoChemie, Utrecht, The Netherlands) and GPES 4.9 software were used for voltametric measurements. A three-electrode system was used in all experiments: GCE (CH Instruments, Inc., Austin, TX, USA, $d = 3$ mm) as the working electrode, an Ag/AgCl as the reference electrode (3 M KCl) and a Pt wire as the auxiliary electrode. pH measurements were performed using a PHM 220 pH meter with a combined electrode Radiometer GK240B. Sonication was performed in an ‘Iskra’ UZ 4R ultrasonic bath (Sentjernej, Slovenia) and a SCALTEC SBC 31 balance was used for weight measurements. Spectrophotometric measurements were performed using the SPECTROstar Nano Microplate Reader (BMG Labtech, Ortenberg, Germany). ## 3.3. Procedures Electrochemical characterisation was performed by CV, DPV and SWV. The effect of pH was studied in the pH range of 2–10. The GCE was manually polished with an aqueous slurry of Al2O3 powder (particle size 0.05 μm) on a smooth polishing pad for 2 min before each experiment. The electrode was rinsed with deionised water and then sonicated in deionised water for 2 min and in absolute ethanol for 2 min and then rinsed with deionised water. The test solutions were deoxygenated by bubbling with high-purity nitrogen before and in-between runs to remove oxygen interference. CV was first performed in the direction of the positive potential—starting at 0 V, increasing to +1.6 V, and decreasing again to −1.6 V—and in the opposite direction towards negative potential—starting at 0 V, decreasing to −1.6 V and increasing to +1.6 V. The scan rate was adjustable and ranged from 0.01 V s−1 to 0.1 V s−1, with a step potential of 0.005 V. DPV was used under the following conditions: step potential 0.005 V, modulation amplitude 0.05 V, modulation time 0.05 s and interval time 1 s. The conditions for SWV were frequency 25 Hz, step potential 0.001 V, effective scan rate of 0.025 V s−1 and pulse amplitude of 0.005 V. The DP and SW voltammograms shown were baseline-corrected by applying the moving average with a step window of 0.005 V. The corrected voltammograms were used only for better visualisation and graphical representation of peaks. All peak current values used and shown in all graphs were obtained from the original, untreated voltammograms. PAB was measured according to a previously published method [18,19]. 3,3′-5,5′-Tetramethylbenzidine (TMB) reacts with both hydrogen peroxide and the antioxidants present in the sample. The reaction of chromogen and H2O2 is enzymatically catalysed by peroxidase, whereas the reaction of chromogen and antioxidants is not. Different proportions (0–$100\%$) of 1 mmol L−1 H2O2 were mixed with 6 mmol L−1 uric acid to obtain the standard solutions. The results are expressed in arbitrary units corresponding to the percentage of H2O2 in the standard solution. TOS was determined according to the Erel’s method [20], which was optimised for our laboratory [18]. The ferrous ion-o-dianisidine complex is oxidised to ferric ion in presence of oxidants. The concentration of oxidant molecules is proportional to the colour intensity of the sample. TOS values are given as μmol H2O2 equivalent L−1, since the method was calibrated with 10–200 μmol hydrogen peroxide aqueous solution. SHG were measured using the optimised Ellman’s method [18,21]. The reaction between the reagent dinitrodithiobenzoic acid (DTNB, conc. 10 mmol L−1) and aliphatic thiol compounds in a basic environment (pH 9.0) provides 1 mol of p-nitrophenol anion per 1 mol of thiol. Method calibration was performed with reduced glutathione (conc. 0.1–1.0 mmol L−1). TAS was determined by Erel’s method [22] modified for our laboratory [18]. Reduced 2,2-azino-bis(3-ethyl-benz-thiazoline-6-sulfonic acid) (ABTS) oxidises in the presence of hydrogen peroxide in acidic medium. Antioxidants present in the sample lead to ABTS discoloration proportional to their concentrations. The reaction was calibrated with 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox) and the results are expressed as μmol Trolox equivalent L−1. The oxidative score was calculated as the difference between the pro-oxidant score (TOS and PAB, i.e., average of Z-scores of all measured pro-oxidants and their products) and the antioxidant score (TAS and SHG, i.e., average of Z-scores of all measured antioxidants and their products). The difference between the original value and the control value divided by the standard deviation of the control values (or population means and standard deviations) gives the Z-score. The OS value is directly proportional to the pro-oxidant effect [23,24]. Statistical analysis was performed with SPSS 18.0 (SPSS inc. Chicago, IL, USA). Data are presented as medians ± interquartile range. The Friedmann’s test (nonparametric repeated-measures ANOVA) followed by Wilcoxon’s paired-samples (post hoc test for related samples) and Mann–Whitney U test were used to test the difference between quantitative variables. A significant difference was considered at $p \leq 0.05$ for each statistical test performed. Electrochemical confirmation of the spectrophotometric analysis was performed by DPV in a small electrochemical cell (1.5 mL) using the same three-electrode system. The GCE was prepared in the same manner as described previously. Samples were tested without deoxygenation before and between runs. Voltammograms were recorded after 0 h, 2 h and 24 h incubation at 37 °C. DPV was used under the following conditions: step potential 0.005 V, modulation amplitude 0.05 V, modulation time 0.05 s and interval time 1 s. All values determined and presented were obtained from the original voltammograms. Baseline-corrected voltammograms (same procedure as described above) were used for display and visualisation only. ## 4. Conclusions Electrochemical characterisation of IVM, a ratified anthelmintic but also a potential antitumor and antiviral drug, was performed using CV, DPV and SWV. IVM can be oxidised and reduced at GCE separately. Both the potential and intensity of the oxidation (A1 and A2) and reduction (C1) peaks are pH dependent. The influence of pH was studied in different buffer solutions in the pH range 2–10. The oxidation process, represented by the A1 peak, takes place as an irreversible, diffusion-controlled process involving the exchange of one electron and one proton in slightly acidic and neutral solutions. The oxidation of IVM occurs at position 8A in the tetrahydrofuran ring, forming an intermediate radical (8-ivermectin radical) that further transitions to 8-OH IVM as the major product. The reduction of IVM is an irreversible, adsorption-controlled process that occurs at the 1,4-diene structure. Upon protonation, a resonance-stabilised carbocation is formed, which, after the consumption of an electron, forms the reduced IVM-R product. The antioxidant activity of IVM was studied in vitro in a human serum pool and compared with a known antioxidant (Trolox) and pro-oxidant (TBH). PAB, TOS, TAS and SHG were determined spectrophotometrically and used to calculate pro-oxidant, antioxidant and oxy-scores of IVM after 2 h and 24 h of incubation. The redox behaviour of IVM showed pronounced antioxidant potential, similar to that of Trolox at short-term incubation, whereas a prolonged stay among biomolecules, e.g., in the presence of an exogenous pro-oxidant (TBH), resulted in a loss of antioxidant activity. 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--- title: The Effect of Two-Generation Exposure to a High-Fat Diet on Craniofacial Morphology in Rats authors: - Saranya Serirukchutarungsee - Ippei Watari - Pornchanok Sangsuriyothai - Masato Akakura - Takashi Ono journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003827 doi: 10.3390/jcm12051903 license: CC BY 4.0 --- # The Effect of Two-Generation Exposure to a High-Fat Diet on Craniofacial Morphology in Rats ## Abstract This study aimed to examine the sexual dimorphism effect of two-generation exposure to a high-fat diet (HFD) on the craniofacial growth of rat offspring. Ten eleven-week-old pregnant Wistar rats were fed either a control or HFD from day 7 of pregnancy until the end of lactation. Twelve male and female offspring from the control-diet-fed mothers were assigned to the CM (control male, $$n = 6$$) and CF (control female, $$n = 6$$) groups. The other twelve from the HFD-fed mothers were assigned to the HFD male (HFDM, $$n = 6$$) and HFD female (HFDF, $$n = 6$$) groups. HFDM and HFDF rats continued with an HFD. The offspring’s weight and fasting blood sugar levels were measured every two weeks. The craniofacial and dental morphologies were studied from lateral X-rays of the head at ten weeks old. The HFDM rats showed an increased body weight and larger neurocranial parameters compared with the CM group. Furthermore, there were slightly significant differences in body weight and viscerocranial parameters between the rats in the HFDF and CF groups. In conclusion, two-generational exposure to an HFD had a greater effect on the male offspring’s body weight and craniofacial morphology. ## 1. Introduction Dietary patterns and physical activity are considered to be important factors for weight gain [1], where an imbalance between energy intake and expenditure results in excessive fat accumulation [1]. Genetics is an underlying factor that controls hunger, satiety, and behaviors. *Relevant* gene defects, such as melanocortin 4 receptor (MC4R), Src-homology-2 (SH2B1), and potassium channel tetramerization domain-containing 15 (KCTD15), were found to be associated with excessive eating behavior and overnutrition. Moreover, the obesogenic environment aggravates the adverse effects of an HFD [2,3]. A post-weaning HFD combined with a maternal HFD resulted in hyperphagia and obesity in offspring [2,3,4]. The body weight and adipose tissue size of offspring following two-generation exposure to an HFD were remarkably higher than offspring from either control-fed or one-generational exposure to HFD rats [2,3,4]. These results suggested that post-weaning overnutrition potentially magnified the detrimental effects of an HFD during pregnancy and lactation. Moreover, maternal food patterns tend to induce the same food patterns in offspring [5,6]. Therefore, a post-weaning obesogenic environment is most likely to happen in most situations. Thus, researchers need to recognize the effect of a high-fat diet (HFD), not only during prenatal life but also post-weaning life, which affects the offspring’s long-term health. A maternal HFD influences bone development in both humans and rodents [7]. A study of 53,922 pairs of mothers and children found an interaction between the maternal intake of a high-fat Western-style diet and forearm fracture in offspring [8]. In rodent studies, the fetal offspring of dams fed a maternal HFD presented decreased bone formation, density, and volume during late gestation [7,9]. Higher senescence in fetal calvarial osteoblast cells potentially interferes with bone formation in fetuses. In contrast, weaned offspring from HFD-fed mothers showed an increased bone mass and density in their long bones [7,10]. An HFD after weaning further reduced trabecular bone volume compared with offspring from HFD-fed dams weaned on the control diet. These results suggest that nutrition is essential to long-term skeletal remodeling in offspring. Moreover, the effect of a maternal HFD could be considerably amplified by a post-weaning HFD, influencing multiple generations [4,7,11,12]. Sexual dimorphism of the craniofacial region has been studied for decades [13,14,15]. The differences in anterior cranial base length, mid-facial length, mandibular length, and the face height of males and females were reported [13]. Furthermore, previous studies demonstrated the sexual differences in metabolic response to an HFD [16,17,18]. In rodents, males were more susceptible to body weight gain than females [16,17,18]. However, the sexual dimorphism effects of an HFD on craniofacial morphology have rarely been studied, especially the combination of pre- and post-weaning HFD consumption. Therefore, this study focused on the sexually different effects of a maternal HFD during pregnancy and lactation combined with post-weaning HFD on offspring’s craniofacial morphology using cephalometric analyses. Understanding the correlations between HFD exposure and the development of offspring’s craniofacial patterns will increase the awareness of health professionals toward its adverse effects, improving their ability to construct appropriate treatment plans for patients. ## 2.1. Animals and Experimental Design Before the study, all animal and experimental procedures were approved by the Institutional Animal Care and Welfare Committee (A2020-148A). They were performed following the Animal Care Standards of Tokyo Medical and Dental University (TMDU) and ARRIVE guidelines. Ten eleven-week-old Wistar rats were purchased from the Sankyo Labo Service Corporation (Tokyo, Japan). All rats were fed either a control diet (CE2, Clea, Tokyo, Japan; $4.6\%$ from fat, 3.402 kcal/g) or an HFD (HFD32, Clea, Tokyo, Japan; $32\%$ from fat, 5.076 kcal/g) from day 7 of pregnancy until the end of the lactation period. Because the embryonic neural folds develop at seven days of gestation, the diet intervention of this study was started synchronously [19]. The offspring from litters containing nine to twelve pups were randomly selected to standardize the litter sizes [2]. The outsized litters from the study were excluded. Therefore, the conditions during the gestation and lactation of all samples were comparable. One to two pups from each litter were randomly selected. In total, 24 offspring were assigned to 4 groups. The male and female offspring of a mother that consumed the control diet were named the CM ($$n = 6$$) and CF ($$n = 6$$) groups, respectively. The other male and female offspring (12 each) of the HFD-fed mothers were assigned to the HFDM ($$n = 6$$) and HFDF ($$n = 6$$) groups, respectively. After weaning, all pups continued consuming the same diet as their mothers to mimic an obesogenic environment (Figure 1). ## 2.2. Body Weight and Fasting Blood Glucose Measurement Body weight was measured every 2 weeks from weaning until the end of the experiment at the age of 10 weeks old. An HFD compromised beta cell development and function and contributed to the development of obesity and insulin resistance [20]. Moreover, high blood sugar levels resulted in craniofacial morphology alteration [21,22]. Therefore, the fasting blood sugar level was observed during the growth period in this study. All rats fasted for 8 h before the measurement of fasting blood sugar (FBS) levels at 4, 6, 8, and 10 weeks old. ## 2.3. Cephalometric Analyses At 10 weeks old, the rats were anesthetized using the three types of mixed anesthesia prepared with medetomidine hydrochloride 0.375 mg/kg (Orion, Hokkaido, Japan), midazolam 2 mg/kg (Sandoz, Basel, Switzerland), and butorphanol tartrate 2.5 mg/kg (Meiji Seika, Tokyo, Japan) [23]. Each rat’s head was fixed firmly with ear rods, with plastic rings for incisors. Then, lateral cephalometric radiographs were taken using a soft X-ray machine (SOFTEXCMB-2, SOFTEX Co., Ltd., Tokyo, Japan) at 50 kVp, 15 mA, and 20 s exposure. The films (Fujifilm, Tokyo, Japan) were developed and scanned at a high resolution (400 dpi, 16 bit) in.tif format. The twenty-two cephalometric landmarks (Table 1) and twenty-eight linear measurements (Table 2 and Table 3) were obtained from previous studies [21,24,25]. All landmarks and linear measurements were analyzed twice using ImageJ software (Wayne Rasband, NIH, Maryland, USA) to ensure reliability and replicability (Figure 2 and Figure 3). Finally, Dahlberg’s formula was used to determine the reproducibility of the measurements and the method error [26]. ## 2.4. Statistical Analysis The power analysis was done using G*Power version 3.1.9.6. The effect size was calculated from the data of the pilot study. Then, the sample size ($$n = 6$$) was determined. All statistical analyses were performed using GraphPad Prism 9 (GraphPad version 9.4.0, USA). The normal distribution of the data was checked using the Shapiro–Wilk test. The statistical significance was set at $p \leq 0.05.$ *The data* are presented as the mean ± standard deviation (SD). The body weight and FBS data were determined using a one-way ANOVA followed by Tukey’s multiple comparisons test. In addition, all cephalometric analyses were analyzed using a two-way analysis of variance (ANOVA) (the two factors were food and sex) followed by Tukey’s multiple comparisons test. The dental measurement data were not normally distributed. Therefore, all data were analyzed using the Kruskal–Wallis test. The level of significance was set at p ≤ 0.05. ## 3.1. Changes in Body Weight but Not FBS in Offspring The body weight and FBS of all groups were compared. The body weights of the HFDM and HFDF were significantly higher than those of the CM and CF at 3 weeks old. The HFDM remained heavier than the CM until the end of the experiment, while the body weight of the HFDF was not significantly different from the CF after 3 weeks old. The FBS was not significantly different between all groups throughout the experiment (Figure 4). ## 3.2. Changes in the Cephalometric Parameters The method errors (mm) evaluated using the *Dahlberg formula* were as follows: total skull length (Po–N) = 0.33909, cranial vault length (Po–E) = 0.5606, total cranial base length (Ba–E) = 0.3923, anterior cranial base length (So–E) = 0.3703, occipital bone length (Ba–CB1) = 0.1403, sphenoid bone length (CB1′–CB2) = 0.1448, posterior cranial base length (Ba–So) = 0.2103, posterior neurocranium height (Po–Ba) = 0.4928, nasal length (E–N) = 0.4875, palate length (Mu2–Iu) = 0.2059, midface length (CB2–Iu) = 0.7432, viscerocranial height (E–Mu1) = 0.1447, posterior corpus length (Go–Mn) = 0.9095, anterior corpus length (M1–Il) = 0.2027, total mandibular length (Co–Il) = 1.0589, ramus height (Co–Gn) = 0.6127, maxillary first molar crown width (UM1) = 0.1474, maxillary second molar crown width (UM2) = 0.1258, maxillary third molar crown width (UM3) = 0.1647, mandibular first molar crown width (LM1) = 0.1927, mandibular second molar crown width (LM2) = 0.1934, mandibular third molar width (LM3) = 0.2500, maxillary incisor width (Uiw) = 0.3123, mandibular incisor width (Liw) = 0.9436, maxillary incisor length (Uil) = 0.3327, mandibular incisor length (Lil) = 0.5544, maxillary first molar crown height (UCH) = 0.2919, maxillary first molar root length (URH) = 0.2401, mandibular first molar crown height (LCH) = 0.2035, and mandibular first molar root length (LRH) = 0.2048. ## 3.2.1. Changes in the Neurocranium A two-way ANOVA was conducted to examine the effect of food and sex on all cephalometric parameters. In the neurocranium, there was a statistically significant interaction between the effects of food and sex on the total skull length (Po–N), cranial vault length (Po–E), total cranial base length (Ba–E), anterior cranial base length (So–E), occipital bone length (Ba–CB1), and posterior cranial base length (Ba–So). A simple main effects analysis showed that food had a statistically significant effect on all parameters, with the exception of the anterior cranial base length (So–E), sphenoid bone length (CB1′–CB2), and posterior neurocranium height (Po–Ba), whereas sex affected all parameters, except for the occipital bone length (Ba–CB1) and sphenoid bone length (CB1′–CB2) (Table 4). The data were then compared between groups using the multiple comparisons test. For the male offspring, the animals in the HFDM group showed longer lengths for all variables, except for the sphenoid bone length (CB1′–CB2) and posterior neurocranium height (Po–Ba) (CM vs. HFDM; Po–N: $$p \leq 0.009$$; Po–E: $$p \leq 0.021$$; Ba–E: $p \leq 0.001$; So–E: $$p \leq 0.038$$; Ba–CB1: $$p \leq 0.025$$; Ba–So: $p \leq 0.001$). In contrast, there was no significant difference in any of the variables between the CF and HFDF groups (Figure 5A). ## 3.2.2. Changes in the Viscerocranium In the viscerocranium, there was a statistically significant interaction between the effects of food and sex on the palate length (Mu2–Iu). A simple main effects analysis showed that food had a statistically significant effect on the palate length (Mu2–Iu) and midface length (CB2–Iu), whereas sex affected all parameters (Table 4). The palate length (Mu2–Iu) was the only parameter among all of the cephalometric measurements that significantly increased in both the males and females. The midface length (CB2–Iu) was longer in the HFDM group compared with the CM group but not in the HFDF group compared with the CF group (Figure 5B). ## 3.2.3. Changes in the Mandible In the mandible, the interaction between food and sex did not affect any parameters. The simple main effects of food statistically affected the anterior corpus length (M1–Il), while sex affected all parameters in the mandible (Table 4). There was no significant difference in all variables among the CM, CF, HFDM, and HFDF groups (Figure 5C). ## 3.2.4. Changes in the Dental Morphology It was shown that the HFD did not affect any dental parameters. There were no significant differences between the CM, CF, HFDM, and HFDF groups for every parameter (Figure 6). ## 4. Discussion Balanced nutrition is essential for growth and development. This study investigated the effects of two-generation exposure to an HFD on the craniofacial growth and morphology of male and female rat offspring using cephalometric analyses. We found the effects of an HFD on craniofacial growth in the different patterns between male and female offspring. At the weaning age, the body weights of the rats in the HFDM and HFDF groups were heavier than their respective CM and CF counterparts. Nonetheless, the body weight of the rats in the HFDM group was continuously larger than that of the CM group throughout the experimental period. In contrast, the body weight of the rats in the HFDF group was not considerably different from the CF group. An HFD similarly affected the males’ neurocranial length more compared with females. The cephalometric analysis showed that the total skull length (Po–N), cranial vault (Po–E), total cranial base (Ba–E), anterior cranial base (So–E), occipital bone (Ba–CB1), and posterior cranial base (Ba–So) lengths of the rats in the HFDM group were significantly longer compared with the CM group. On the other hand, there was no significant difference between any neurocranial parameters for the rats in the HFDF and CF groups. Moreover, the HFD moderately affected the male offspring’s viscerocranium, while it only slightly affected the females. The midface (CB2–Iu) and palate lengths (Mu2–Iu) of the rats in the HFDM group were longer than in the CM group. Interestingly, the palate length (Mu2–Iu) of the rats in the HFDF group was similarly increased compared with those in the CF group. Finally, the effect of an HFD was not detected in any mandible or dental parameters. The results from our study emphasized the sexual dimorphism of an HFD on craniofacial morphology, which could be the result of sex hormones that influence bone growth and metabolism [27]. Androgens and estrogen enhance craniofacial bone growth, which is evident immediately after birth [27]. The effects of an HFD in this study prominently affected male offspring at ten weeks. The higher intake of fats and energy possibly increases lipid stores and stimulates rapid bone growth [7]. In addition, male hormones can massively stimulate bone extension [27]. As a result, males and females have different skeletal growth patterns [28]. Furthermore, estrogen has a protective effect against an HFD in females by reducing proinflammatory cytokines and maintaining insulin sensitivity during obesity [29]. Therefore, we hypothesized that the different characteristics of male and female sex hormones explained our findings. However, in this study, the mandible was not affected by an HFD in males or females. Mandibular growths are affected by various environmental factors, including postnatal masticatory functions [30]. Our results suggested that the environmental factors were more predominant compared with the effect of an HFD during mandibular development. It is important to highlight that a maternal HFD on offspring growth and development could be considerably amplified by a post-weaning HFD, influencing multiple generations [4,7,9,11,12]. Family environment is an important factor associated with obesity in children and adolescents [6]. Obese parents significantly increase the risk of obesity in children [3,6]. Therefore, after weaning, we challenged the offspring with an HFD to mimic the obesogenic environment, which mostly happened in the family. In the current study, the effect of two-generation exposure to an HFD was more considerable for the male than the female offspring. The body weight of the HFDM group was significantly increased compared with those in the CM group throughout the experiment. On the other hand, the body weight of rats in the HFDF group was larger than those in the CF group only at three weeks old. Previous studies reported that a two-generational HFD increased the body weight and post-weaning growth rates of both male and female offspring [2,4,12]. These results emphasized that both genetic and environmental factors played an essential role in offspring health. This embryonic craniofacial development involves several transformations and migrations of the ectoderm, mesoderm, and endoderm germ layers [31]. This complex could be affected by maternal conditions and environments because they start from an early stage after fertilization [32,33]. In brief, the embryonic ectoderm changes at the beginning of embryo development and finally forms the neural crest [32]. The neural crest is subsequently differentiated into pharyngeal arches and develops into most of the skull’s bones and cartilages [31,34]. Indeed, most anterior cranial neural crest cells develop into the frontal and nasal bones. In contrast, posterior cranial neural crest cells turn into pharyngeal arches and transform into the maxilla, mandible, middle ear, and a part of the neck [31]. In this study, an HFD appeared to affect each part of craniofacial morphology differently. In males, an HFD had a major effect on the neurocranium. The total skull (Po–N), cranial vault (Po–E), total cranial base (Ba–E), anterior cranial base (So–E), occipital bone (Ba–CB1), and posterior cranial base (Ba–So) lengths of rats in the HFDM group were longer than in the CM group. The minor effect of an HFD was shown in males’ viscerocranium. The midface (CB2–Iu) and palate lengths (Mu2–Iu) of rats in the HFDM group were longer than those in the CM group, while only the palate length (Mu2–Iu) was increased in rats in the HFDF group compared with those in CF. Finally, an HFD did not affect the mandibles and teeth in males or females. The different origins of each part of the skull presumably explain the different effects of an HFD on the neurocranium, viscerocranium, mandibles, and teeth. The increased neurocranial growth in the HFDM rats could be the combined effect of maternal and post-weaning HFD. First, maternal HFD was reported to affect the offspring’s bone and craniofacial growth [7,35]. Previous papers explained two possible underlying mechanisms [36,37,38,39,40]. An HFD during pregnancy alters placental gene expression and DNA methylation, increasing the transfer of nutrients across the placenta [36,38,40]. Moreover, the unbalanced maternal lipids during gestation and lactation impair fetal cells. Excessive fat intake during a specific period of pregnancy, as well as lactation, contributes to abnormal cell function and fat metabolism and increases the risk of metabolic diseases in offspring [36]. Second, a post-weaning HFD influenced craniofacial growth in offspring. Previous studies reported long-term consumption of HFD-induced craniofacial morphology changes in rodents [2,12,25,41]. D. Botero-González et al. demonstrated that a post-weaning obesogenic diet decreased the nasal and maxillary lengths in young adult rats [25]. In our study, an HFD did not affect the offspring’s nasal length. The palatal length of rats in the HFDM and HFDF groups increased compared with those in the CM and CF groups. Different types of obesogenic diets could be the reason for the different results. Furthermore, previous studies addressed craniofacial abnormalities in obese patients [41]. Correspondingly with our results, maxillary length increases in obese male and female adolescents [42]. Obesity potentially stimulated growth activity in both genders, resulting in larger craniofacial dimensions. Consequently, various craniofacial characteristics tend to be different in obese patients. In contrast to our study, obese patients tend to have a shorter upper face height, larger mandibles, and flatter and more concave profiles [41]. An HFD was reported to influence bones in offspring [7,9,43,44]. An HFD during pregnancy delays fetal skeletal development by suppressing fetal osteoblasts, resulting in decreased bone formation, volume, and mineral density at late gestation [7,9]. Contrastingly, offspring from HFD-fed dams had an increase in bone volume and osteoblast activity after weaning [10]. Higher fat contents in milk were suspected to be the fuel for bone development in offspring [10]. Corresponding to our findings, we speculate that the higher fat content in milk from dams fed an HFD increased the craniofacial growth in male offspring. Dental anthropology is determined by multifactorial effects, such as the genetic and environmental factors associated with the development of tooth size [45]. However, the most substantial effect that determines dental size is a specific gene [45,46,47]. In the current study, there was no statistical difference in tooth size between groups. These findings suggest that HFD consumption did not alter the gene sequence. However, a previous study reported that an HFD increased the labial groove and dentine thickness in aged rodents [46,48]. Therefore, detecting the effect of an HFD on teeth probably requires a longer study period and further analysis. One of the limitations of this study was the difficulty in separating the direct effect of a maternal HFD on offspring from other environmental and genetic factors. We must consider that our findings were from the effects of mother and offspring. This limitation encourages further studies to clarify these combined effects and their mechanisms. Furthermore, future studies can investigate serum lipid and associated factors coupled with body weight and blood sugar levels. This will allow for an understanding of the mechanisms of our results. Understanding the different patterns of craniofacial growth and the development of obese individuals will increase awareness among orthodontists, allowing them to produce the most appropriate orthodontic treatment plans for patients. ## 5. Conclusions In conclusion, the two-generation exposure to HFD affected craniofacial growth and development in a sex-specific manner in young adult rats. It was shown that maternal HFD combined with post-weaning HFD consumption significantly promoted neurocranium and viscerocranium growth in male offspring. In contrast, the mandible and dental morphologies were not affected by the HFD in males or females. 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--- title: 'The Global, Regional, and National Uterine Cancer Burden Attributable to High BMI from 1990 to 2019: A Systematic Analysis of the Global Burden of Disease Study 2019' authors: - Jingchun Liu - Haoyu Wang - Zhi Wang - Wuyue Han - Li Hong journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003834 doi: 10.3390/jcm12051874 license: CC BY 4.0 --- # The Global, Regional, and National Uterine Cancer Burden Attributable to High BMI from 1990 to 2019: A Systematic Analysis of the Global Burden of Disease Study 2019 ## Abstract Uterine cancer (UC) is the most common gynecologic malignancy, and high body mass index (BMI) is a poor prognostic factor for UC. However, the associated burden has not been fully assessed, which is crucial for women’s health management and the prevention and control of UC. Therefore, we utilized the Global Burden of Disease Study (GBD) 2019 to describe the global, regional, and national UC burden due to high BMI from 1990 to 2019. The data show that globally, women’s high BMI exposure is increasing annually, with most regions having higher rates of high BMI exposure than the global average. In 2019, 36,486 [$95\%$ uncertainty interval (UI): 25,131 to 49,165] UC deaths were attributed to high BMI globally, accounting for $39.81\%$ ($95\%$ UI: 27.64 to 52.67) of all UC deaths. The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years (DALY) rate (ASDR) for high BMI-associated UC remained stable globally from 1990 to 2019, with significant differences across regions. Higher ASDR and ASMR were found in higher socio-demographic index (SDI) regions, and lower SDI regions had the fastest estimated annual percentage changes (EAPCs) for both rates. Among all age groups, the fatal outcome of UC with high BMI occurs most frequently in women over 80 years old. ## 1. Introduction Uterine cancer (UC) is the most common gynecological malignancy [1]. It is estimated that about $7\%$ of all new cancers in women in the United States are UCs. Although most UCs are highly treatable with a good prognosis [2], the estimated mortality rate is still the sixth highest among female cancers whose disease burden cannot be ignored. Previous studies have estimated differences in the incidence, severity, or mortality of UC by age, race, and ethnicity [3,4,5,6,7]. Assessing the disease burden of UC due to other important risk factors is essential to guide disease interventions and improve public health. High body mass index (BMI)has been shown to be an important risk factor for UC with an association with higher all-cause mortality and disease recurrence [8,9,10]. However, due to the rising trend of high BMI in women worldwide, there is a need to strengthen health policies and management, which will benefit UC control and reduce the risk of the burden of other diseases [11,12]. The Global Burden of Disease Study (GBD) 2019 focuses on the burden of multiple diseases and injuries and incorporates the associated risk factors and the relative harms they cause. The Socio-demographic Index (SDI) is a composite indicator of the development status of countries or regions based on a combination of per capita income, education, and fertility rates [13]. In this study, we used GBD 2019 to provide a comprehensive analysis of the disease burden of UC due to high BMI from global, regional, and national levels, including risk factor exposure, disability-adjusted life years (DALYs), and deaths, with links to SDI, aiming to contribute to women’s health management, as well as prevention and control of UC. ## 2.1. Data Source We obtained the data for this study from the GBD 2019 public dataset (http://ghdx.healthdata.org/gbd-results-tool (accessed on 13 October 2022)). GBD 2019 focuses on 369 diseases and injury burdens and incorporates their associated risk factors and the relative harms they cause. We restricted our analysis to deaths and DALYs due to UC in total and attributable to high BMI, as well as summary exposure values (SEVs) of women with high BMI worldwide. Our study was grouped by age (5-year age groups from 20 to 79 years and 80+ years) and region. In GBD 2019, the 204 countries and territories in the study were classified into five levels based on the SDI, a composite indicator that assesses total fertility, education, and income attainment. They are also divided into 21 GBD regions based on geographical location. The statistical indicators used in this study on age, death, DALY, SEV, etc., are available for free by visiting GBD 2019. The $95\%$ uncertainty interval (UI) of data was obtained by accessing GBD 2019. ## 2.2. Standard Definitions In GBD 2019, UC is defined as C54–C54.3, C54.8–C54.9, Z85.42, and Z86.001 to match ICD10. Data for high BMI in GBD 2019 were obtained by updating and supplementing the GBD 2017. Criteria for high BMI were defined by mixed-effects modeling and data adjustment according to each country, year, age, and sex. *In* general, a high BMI for adults (ages 20+) was defined as BMI greater than 25 kg/m2 [14,15]. The SDI values divide all countries and regions into five levels, and the exact list can be found in previous studies [15]. ## 2.3. Statistical Analysis Death, the age-standardized mortality rate (ASMR), DALY, and age-standardized DALY rate (ASDR) were used to quantify the burden of uterine cancer attributable to high BMI worldwide. Population attribution fractions (PAFs) are used to assess the burden of disease attributable to a risk factor and are calculated as E/O × $100\%$, where E is the number of cases that can be attributed to the exposure and O is the total number of cases. Time trends in statistical indicators from 1990 to 2019 are measured by the estimated annual percentage change (EAPC), which is calculated as EAPC = 100 × (exp (β) − 1), with β representing the annual change in ln (age-standardized rate) and the $95\%$ confidence interval (CI) also derived from the model. Positive EAPC here represents an increasing trend, and negative EAPC represents a decreasing trend. Finally, Spearman’s correlation was used to test the association between the statistical indicators, SDI and EAPC. All statistical analysis and data visualization is performed with the software GraphPad Prism8 (Boston, MA, USA) or R (4.1.0) (Auckland, New Zealand). ## 2.4. Ethics Statement No ethical review was required for this study because only extensive pooled data without personal identifiers were used in the data analysis. ## 3.1. UC Deaths and ASMR Attributable to High BMI From 1990 to 2019, the PAF of UC deaths attributable to high BMI increased from $30.65\%$ ($95\%$ UI: 19.42 to 43.94) to $39.81\%$ ($95\%$ UI: 27.64 to 52.67) annually worldwide (Supplementary Table S1). Specifically, the number of UC deaths associated with high BMI increased from 56,130 ($95\%$ UI: 51,104 to 60,199) to 91,641 ($95\%$ UI: 82,389 to 101,502), and ASMR was relatively stable within the fluctuating range, developing from 0.82 ($95\%$ UI: 0.51 to 1.17) to 0.83 ($95\%$ UI. 0.57 to 1.12) (Figure 1A–C). The EAPC was 0.05 ($95\%$ CI: 0 to 0.09). At the SDI-regional level, the number of UC deaths attributable to high BMI and the proportion of total UC deaths has increased annually in all five regions. Deaths due to UC associated with high BMI occurred most frequently in High SDI and High-middle SDI areas, with 11,964 ($95\%$ UI: 8392 to 15,777) and 12,148 ($95\%$ UI: 8455 to 16,245) deaths in 2019, respectively (Figure 1B and Table 1). From 1990 to 2019, ASMR increased yearly in almost all SDI regions, reaching a range of 0.51–1.15 in 2019, except for High-middle SDI which decreased from 1.22 to 1.07 (Figure 1C). The same trend is reflected in the EAPC, which stands at −0.65 ($95\%$ CI: −0.56 to −0.75) in the High-middle SDI and ranges from 0.53 to 2.23 in the other regions. At the GBD-regional level, high BMI-associated UC deaths occurred mainly in High-income North America, Western Europe, and Eastern Europe (Figure 1D and Table 1). From 1990 to 2019, Central Asia, High-income Asia Pacific, and Eastern Europe showed a decreasing trend in ASMR, with EAPC ranging from −0.41 to −0.37. ASMR volatility was relatively stable or increasing in other regions, with Southeast Asia showing the fastest growth in ASMR (EAPC = 3.16; $95\%$ CI: 3.05 to 3.27). At the national level, the most deaths due to high BMI in UC were caused by the United States of America in both 1990 and 2019, followed by the Russian Federation and China (Supplementary Table S2). The highest ASMR was observed in American Samoa in 1990 (ASMR = 3.94, $95\%$ UI: 2.57 to 6.1) and 2019 (ASMR = 6.06, $95\%$ UI: 3.71 to 8.57) (Figure 2). During this period, Bangladesh had the lowest ASMR of 0.06 ($95\%$ UI: 0.01 to 0.18) in 1990 and 0.14 ($95\%$ UI: 0.06 to 0.34) in 2019. There were 162 countries with elevated ASMR out of the 204 countries and territories included in the analysis, and Equatorial Guinea showed the fastest increase with EAPC in ASMR of 6.84 ($95\%$ CI: 6.11 to 7.56). Among other countries and territories, the Republic of Korea experienced the largest decline with an EAPC in ASMR of −3.44 ($95\%$ CI: −4.29 to −2.58). In 2019, high BMI-related UC deaths were associated with age, peaking in the 80+ age group, followed by the 65–69 age group (Figure 3). Age-specific mortality rate increased with age globally and in all SDI level regions. Specifically, deaths occurred most frequently in the 80+ age group, with the majority occurring in the High SDI and High-middle SDI regions. Globally, the EAPC for age-specific mortality rate developed a W-shaped association with age, with values below 0 at ages 45–49 and 65–79, decreasing fastest at ages 60–69 and increasing fastest at ages 80+. At the SDI regional level, the EAPC for age-specific mortality rate in the High-middle SDI region was chronically below 0 until 2019. All other regions have positive values, with persistently higher values in the Low-middle SDI and Low SDI regions. ## 3.2. UC DLAYs and ASDR Attributable to High BMI From 1990 to 2019, the PAF of UC DALY cases attributable to high BMI increased from $30.00\%$ to $40.19\%$ worldwide (Supplementary Table S1). The number of high BMI-associated UC DALY cases increased from 444,333 ($95\%$ UI: 276,290 to 633,114) to 935,961 ($95\%$ UI: 642,880 to 1,255,462) (Figure 4A, B). The ASDR increased from 20.59 ($95\%$ UI: 12.82 to 29.38) in 1990 to 21.48 ($95\%$ UI: 14.75 to 28.83) in 2019, with an EAPC of 0.16 ($95\%$ CI: 0.11 to 0.21) (Table 1 and Figure 4C). At the SDI-regional level, the number and proportion of UC DALYs attributed to high HBI increased year on year for all five levels of SDI regions. In 2019, the high-middle SDI region contributed the most DALYs for high BMI-associated UC, although the corresponding ASDR showed a decreasing trend over three decades with an EAPC of −0.71 ($95\%$ CI: −0.82 to −0.6). All other regions showed an increasing trend in ASDR, and in particular, the fastest-growing ASDR was observed in the Low SDI region (EAPC = 2.24; $95\%$ CI: 2.15 to 2.34) (Figure 4C). Among all 21 GBD regions, the top three regions with the highest occurrence of UC DALY attributable to high BMI were High-income North America, Western Europe, and Eastern Europe (Figure 4D). In 1990, the highest ASDR belonged to Eastern Europe (ASDR = 59.35; $95\%$UI: 40.42 to 78.12), while in 2019, it was the Caribbean (ASDR = 65.75; $95\%$ UI: 44.11 to 90.18). From 1990 to 2019, the ASDR for Eastern Europe and Central Asia declined, with EAPCs of −0.42 ($95\%$ CI: −0.68 to −0.15) and −0.41 ($95\%$ CI: −0.58 to −0.25), respectively. The ASDR for Southern Latin America, Andean Latin America, and High-income Asia *Pacific is* relatively stable. Other regions are on an upward trend, with Southeast Asia showing the fastest growth with an EAPC in ASDR of 3.14 ($95\%$ CI: 2.97 to 3.3). At the national level, in 1990, the most DALY cases were found in Russian Federation, and in 2019 were contributed by the United States of America (Figure 5 and Supplementary Table S2). During the period, American Samoa and Bangladesh consistently occupied the highest and lowest ASDRs, with 108.2 ($95\%$ UI: 71.33 to 164.82) and 1.65 ($95\%$ UI: 0.26 to 4.76) in 1990, 3.83 ($95\%$ UI: 1.55 to 9.10) and 171.18 ($95\%$ UI: 106.68 to 237.06) in 2019, respectively. From 1990 to 2019, a total of 45 countries and territories had declining ASDRs, and 159 were stable or increasing. The Republic of Korea had the most significant ASDR decline (EAPC = −3.38; $95\%$ CI: −4.35 to −2.4), and Equatorial Guinea had the fastest ASDR increase (EAPC = 6.32; $95\%$ CI: 5.58 to 7.06). In 2019, the number of age-specific DALYs peaked at age 60–64 years globally, yet age-specific DALY rates showed a similar pattern to death, peaking at age 65–69 years (Figure 6). The age-specific DALY numbers and rates for all SDI regions were similar to the global trend with inverted V patterns. In addition, the EAPC in age-specific DALY rates showed similar trends to the EAPC in age-specific mortality rates. ## 3.3. The Changes in High BMI Exposure in Women The age-standardized SEV rate of high BMI among women increased globally, from 12.44 ($95\%$ UI: 9.05 to 17.05) in 1990 to 20.59 ($95\%$ UI: 16.66 to 25.75) per 100,000 persons in 2019. All SDI regions are in line with global average trends, while the high SDI region consistently shows the highest age-standardized SEV rate of high BMI (Figure 7). There is a total of 13 GBD regions with age-standardized SEV rates of high BMI among women consistently above the global average over the three decades, particularly in high-income North America and Southern Sub-Saharan Africa (Supplementary Figure S1). ## 3.4. Association of ASMR, ASDR of UC Attributable to High BMI with SDI A cross-sectional analysis between ASMR of high BMI-associated UC and SDI over 30 years in the GBD regions revealed that ASMR first increased slowly with SDI until it reached approximately 0.5, then increased rapidly, and decreased rapidly after SDI reached 0.7 (Figure 8A). Overall, in 2019, EAPC in ASMR of UC attributable to high BMI was negatively associated with SDI values (R = −0.506, $$p \leq 0.012$$), reaching the highest EAPC at approximately SDI of 0.53 and the lowest at 0.75 (Figure 8C). In the GBD region, the association between ASDR or its EAPC and SDI has a similar pattern to that of ASMR (Figure 8B,D). ## 4. Discussion Previous studies have described the overall burden of uterine cancer over 30 years [16]. In fact, excess body fat and high BMI have been implicated as important causes of most cancers [17,18]. Multiple studies have reported an association between increased BMI and UC risk [12,19,20,21,22] and a stronger association between BMI and risk of endometrioid adenocarcinoma [23,24]. Current genome-wide association studies (GWAS) suggest that high BMI is one of the most definitive risk factors for endometrial cancer and identified risk loci and basis for the risk stratification [25]. Additionally, studies have shown that obesity affects the mapping of dye to the sentinel lymph node in minimally invasive procedures suggesting an intervention for treatment [26]. Mechanistically, obesity is associated with high levels of circulating estrogens in the body, abnormal fatty acid metabolism, and long-term chronic inflammation of the microenvironment, which may promote the development of cancer cells [27,28,29,30]. Therefore, understanding the burden of UC attributable to high BMI and providing timely health surveillance and disease control for risk populations to reduce the disease burden on individuals and society is critical to the current prevention and control of UC worldwide. In this study, spatial and temporal trends in mortality and DALY attributable to high BMI in UC were estimated at the global, regional, and national levels. A series of analyses have shown that the global burden of UC attributable to high BMI is large and growing. From 1990 to 2019, the number of UC deaths associated with high BMI almost doubled, with the percentage increasing from $30.65\%$ to $39.81\%$. Meanwhile, the percentage of DALYs attributable to high BMI increased from $30.00\%$ to $40.19\%$. Moreover, over the past three decades, while high-middle SDI areas have the highest burden of high BMI-associated UC, low SDI areas show faster-increasing mortality and DALY rates. This is consistent with previous reports [31] and may reflect ongoing epidemiologic shifts, demographic changes, and disparities in UC prevention and health control. In conclusion, these results provide a more comprehensive and comparable estimate that may inform a fair and reasonable reduction in the global burden of UC, particularly high BMI-associated UC. Although the absolute burden of high BMI-associated UC increased from 1990 to 2019, the global ASMR (EAPC = 0.05, $95\%$ CI: 0 to 0.09) and ASDR (EAPC = 0.16, $95\%$, CI:0.11 to 0.21) were relatively stable. The ASMR and ASDR due to high BMI-associated UC decreased or remained relatively stable despite higher high BMI exposure in areas with higher SDI. Notably, however, these two rates remained significantly higher in areas with lower SDI. In addition, high BMI exposure and the associated disease burden of UC varied widely worldwide; high-income North America, Western Europe, and Eastern Europe consistently accounted for the highest-burden over three decades. At the national level, Equatorial Guinea, Uganda, and Lesotho showed a rapid increase in ASDR and ASMR. These results suggest that some progress may have been made in the control of high BMI-associated UC globally over the past three decades, and they are cautiously optimistic. However, the uneven distribution of the burden of high BMI-associated UC and disparities in increase around the world diminish the potential to progress and suggest the need to adapt UC control efforts to specific societal circumstances and health system needs, taking into account disease context, regional culture, and high BMI exposure, to accelerate efforts to control and address the burden of high BMI-associated UC and regional inequalities. From 1990 to 2019, the highest and fastest-growing rates of high BMI-associated UC mortality were concentrated in people over 80 years of age, probably due to the difficulty of treatment and health control caused by the decline in the body’s general condition with increasing age. Meanwhile, cancer control and care in older adults is complex, with a potentially blurred demarcation between reasonable treatment, over-treatment and under-treatment [32]. The highest DALY rates were concentrated among 65–69-years-olds adults, but the fastest increases were found among 25–29 and 55–59-year groups. This implies that the trend toward a younger burden of uterine cancer associated with high BMI is also a challenge that cannot be ignored. Previous studies have shown that low alcohol, reasonable physical activity, and having a college degree are associated with a healthy BMI in young women [33]. However, poor lifestyle habits, occupational stress, discordant emotional states, and major illnesses may lead to high BMI. All these suggest that reasonable guidance and improvement of life and health status will be meaningful in the prevention and treatment of uterine cancer in young women. The Research Aimed at Improving Both Mood and Weight (RAINBOW), which co-treats mood and obesity and has shown benefits in multiple trials, maybe a suitable model to follow [34,35]. Higher SDI regions still lead to age-specific high BMI-associated UC mortality and DALY rates. These data remind us that the burden of disease cannot be controlled in a one-size-fits-all idealistic manner, and the age of the population and the risks it may carry a need to be taken into account. GBD 2019 builds on the changing global cancer burden landscape and demonstrates the importance of social environment, population age, risk context, and other characteristics of cancer risk, which can be helpful for directions and strategies for disease risk control. Several limitations provide opportunities for future improvements to this GBD 2019-based study. First, the definition of GBD data needs to be clarified. For UC, data on nonmalignant tumors of the cervix in situ (ICD10: Z86.001) were included. This classification does not seem appropriate and is highly controversial, as it is usually assessed as precancerous of the cervix malignancy rather than UC, based on the location and pathological features of the lesion. Second, data for UC can be refined because it is a broad concept that includes many diseases. Providing more specific burden data for disease classification (e.g., endometrial cancer), clinical classification, and even molecular typing would help in further public health management. Third, the criteria for high BMI were defined as greater than 25 kg/m2 according to country, sex, age, and year, with 20 to 25 kg/m2 being used as the minimum detection limit. However, this crude assessment of results should be improved, and specific criteria should be listed to increase credibility and facilitate individual analysis. Another limitation that cannot be ignored is the lack of available or high-quality data in some areas, resulting in lower data accuracy and delayed availability, which may overestimate or underestimate the burden of disease in a given area or time. Differences in data availability and reliability among SDI regions, GBD regions, and countries can lead to wide variations in trends in disease burden estimates. Therefore, increased global normative surveillance of cancer and health is needed. The introduction and dissemination of new technologies or methods may help identify more women at higher risk of disease and establish screening [36]. In addition, this study, which continued through 2019, did not consider the association between changes in social environment or health management and UC attributable to high BMI during the COVID-19 pandemic, which may have a significant impact on the global pattern of disease burden. Assessment of these associations is critical for future work on the burden of UC because a potential lack of health control, poor diagnosis, and limited treatment may be detrimental to global efforts to reduce cancer burden [37,38,39,40]. In conclusion, a systematic analysis of UC attributable to high BMI in the GBD 2019 study provides comprehensive and comparable estimates of the burden of this disease. 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--- title: 'Middle Segment-Preserving Pancreatectomy to Avoid Pancreatic Insufficiency: Individual Patient Data Analysis of All Published Cases from 2003–2021' authors: - Thomas M. Pausch - Xinchun Liu - Josefine Dincher - Pietro Contin - Jiaqu Cui - Jishu Wei - Ulrike Heger - Matthias Lang - Masayuki Tanaka - Stephen Heap - Jörg Kaiser - Rosa Klotz - Pascal Probst - Yi Miao - Thilo Hackert journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003839 doi: 10.3390/jcm12052013 license: CC BY 4.0 --- # Middle Segment-Preserving Pancreatectomy to Avoid Pancreatic Insufficiency: Individual Patient Data Analysis of All Published Cases from 2003–2021 ## Abstract Middle segment-preserving pancreatectomy (MPP) can treat multilocular diseases in the pancreatic head and tail while avoiding impairments caused by total pancreatectomy (TP). We conducted a systematic literature review of MPP cases and collected individual patient data (IPD). MPP patients ($$n = 29$$) were analyzed and compared to a group of TP patients ($$n = 14$$) in terms of clinical baseline characteristics, intraoperative course, and postoperative outcomes. We also conducted a limited survival analysis following MPP. Pancreatic functionality was better preserved following MPP than TP, as new-onset diabetes and exocrine insufficiency each occurred in $29\%$ of MPP patients compared to near-ubiquitous prevalence among TP patients. Nevertheless, POPF Grade B occurred in $54\%$ of MPP patients, a complication avoidable with TP. Longer pancreatic remnants were a prognostic indicator for shorter and less eventful hospital stays with fewer complications, whereas complications of endocrine functionality were associated with older patients. Long-term survival prospects after MPP appeared strong (median up to 110 months), but survival was lower in cases with recurring malignancies and metastases (median < 40 months). This study demonstrates MPP is a feasible treatment alternative to TP for selected cases because it can avoid pancreoprivic impairments, but at the risk of perioperative morbidity. ## 1. Introduction Total pancreatectomy (TP) can be the standard surgical treatment for a range of pathologies, including cancer, chronic pancreatitis, and intraductal papillary mucinous neoplasia (IPMN) [1,2,3,4]. TP is also conducted to avoid high-risk pancreatoenteric anastomosis or as a rescue operation for partial pancreatectomy [5,6]. Compared to partial pancreatectomy, TP can benefit from the absence of postoperative pancreatic fistula (POPF) and subsequent secondary complications that can otherwise complicate the short-term postoperative course (e.g., erosional post pancreatectomy hemorrhage) [7]. Nevertheless, TP also has serious postoperative mortality that increases with the extent of associated vascular/multi-visceral resection [8,9]. Furthermore, over the long-term, TP can result in physical impairment and reduced quality of life (QOL) due to deficiencies of the endocrine and exocrine systems (e.g., diabetes mellitus, DM) [10,11,12]. Consequently, there is an unmet need and responsibility to consider saving unaffected pancreatic parenchyma to avoid the negative functional consequences that can occur after removing the whole pancreas. The time is ripe for such amendments, as the outcomes of pancreatic surgery are improving due to technological advancement (e.g., surgical instruments and techniques) and healthcare optimization (e.g., hospital centralization, patient-selection, perioperative and intensive care). New techniques include parenchyma-sparing resections of the pancreatic head [13] and body [14] as well as minimally invasive local excisions of small benign/premalignant lesions [15,16]. Such procedures can serve as components of middle-preserving pancreatectomy (MPP), or middle segment-preserving pancreatectomy (MSPP; hereafter MPP). This relatively new operation for the resection of multilocular diseases spares unaffected parenchyma along the pancreatic body (Figure 1). An initial publication reported two sequential operations for recurrent pancreatic carcinoma in 1999 [17] and the first one-stage procedure was reported in 2003 [18]. However, this procedure is still rare and lacks evidence as a viable alternative to TP. Our study aimed to collect and summarize the current literature on MPP in terms of its perioperative parameters and postoperative outcomes. By doing so, we intended to (i) provide a thorough description of all MPP operations published so far, and (ii) generate the highest quality evidence possible on its surgical and clinical outcomes, given the limitations for analyzing such a rare procedure. ## 2. Materials and Methods To achieve these aims we conducted a literature search for all MPP surgical cases published to date. As there have been no controlled trials for MPP, we requested complete individual patient data (IPD) from the original authors to generate a sample conducive to statistical analysis [19]. We included a comparative benchmark of TP patients curated from a database at a high-volume center for pancreatic surgery in order to enable a meaningful interpretation of the outcomes. The nature of case-study data is not amenable to standard meta-analysis or mixed-model techniques because reports mostly cover single individuals and contain neither repeated measurements within patients nor multiple treatment arms. Therefore, we effectively ignored clustering and treated every patient as an independent case sampled from a random population. The IPD approach has advantages over analyzing aggregate data by standardizing the methodology across studies while avoiding pitfalls that stem from selection or publication biases. Furthermore, the dataset can involve more outcome measurements than those reported in source publications. Thus, analyses may be more reliable than a meta-analysis of aggregate data [19]. The study protocol was registered with Prospero (CRD42018112324) and performed per PRISMA and MOOSE guidelines [20,21,22]. ## 2.1. Search Strategy and Eligibility Criteria The Web of Science and MEDLINE databases were systematically searched using OVID (Heidelberg University), PubMed, and Clarivate between 5 April 2018 and 31 January 2022, following the guidelines of Kalkum et al. [ 23]. The search terms used were “middle segment preserving pancreatectomy” or “middle preserving pancreatectomy” in the title or abstract, without any other limitations. Further articles were manually sourced from the reference lists of retrieved articles if they mentioned the above terms. The included studies were full-text reports of MPP surgeries and survival outcomes. The exclusion criteria were: (i) duplicate studies, (ii) reviews without original data, (iii) animal studies, (iv) absence of individual patient data, and (v) MPP performed in a two-stage procedure. Two-stage procedures were excluded because they represent sequential partial pancreatic resections (often in cases of recurrence). These contrast with the focal procedure, which attempts to remove synchronous multilocular diseases in one operation. Investigators TMP, JD, and XL independently screened all retrieved articles according to the eligibility criteria. Disagreements between reviewers were resolved by discussion until a consensus was found. The original authors were contacted for missing patient information, and articles were excluded from the analysis if none were provided. A comparative benchmark group of TP patients was selected from a homogenous single-center cohort. Thus, patients in the sample underwent relatively standardized procedures and the error attributable to variation in techniques across centers was limited. Patients for the TP group were extracted from Heidelberg University Hospital’s patient database of 244 patients who underwent TP between February 2002 and November 2020 due to benign multilocular pancreatic pathologies. Only patients with benign pathologies were selected in order to conservatively provide a benchmark with less oncological risk, thereby sharpening the contrast with MPP patients. Patients were selected from the database by retrospective assessment for the possibility of MPP by investigators TMP and JD based on careful examination of preoperative radiological images, intraoperative surgical evaluations, and postoperative histopathology results. This curation provided some approximation of patient matching and ensured that the samples were comparable. There were no criteria for minimum follow-up times for either the MPP or TP samples. ## 2.2. Quality Control and Risk of Bias IPD were manually checked for consistency and completeness by investigators TMP, JD, and XL, with disagreements resolved by consensus. The methodological quality of each included study was assessed by investigators TMP and PP using a risk of bias evaluation tool for case reports and series, adapted from the ‘Critical Appraisal Skills Program’ and the ‘Newcastle Ottawa Scale’ [24]. Investigators TMP and PP also considered the overall dataset in light of the 7 domains of the ROBINS-I tool [25]. ## 2.3. Extracted Data and Definitions The full extracted data terms are available in Supplementary Table S1. They can be broadly classified as (i) study-level data, (ii) patient baseline characteristics, (iii) surgical procedures performed, (iv) intra-operative outcomes, (v) postoperative course and complications, and (vi) survival information. Data were collected by investigators TMP, JD, and XL, with disagreements resolved by consensus. If the information was not provided in the primary source, classifications were made via correspondence with the original authors or the data was left missing if no information could be retrieved. Pathologies indicated for pancreatic resections can be highly diverse. Therefore, we arbitrarily classified them into 4 groups. The first included ‘multifocal primary pancreatic neoplasms’, such as pancreatic ductal adenocarcinoma and IPMN (neoplasia group). Importantly, this general definition of neoplasia covered any pathology associated with abnormal tissue growth, benign or malignant. The second group included ‘multifocal pancreatic lesions that have metastasized from other organs’, including renal cell carcinoma and colorectal cancer (metastatic group). The third group, ‘synchronous heterogeneous pancreatic diseases’, included those in which the pancreatic head and tail had different pathologies (synchronous group). The final group was ‘non-neoplastic pancreatic diseases’, primarily chronic pancreatitis. ## 2.4.1. Patient Baseline Characteristics Patient characteristics were summarized and reported descriptively, but statistical tests were used to determine if there were any potential confounding differences between MPP and TP samples (continuous variables: t-test; categorical variables: Chi-squared or Fisher’s exact tests). ## 2.4.2. Surgical Resection and Intraoperative Outcomes The intraoperative outcomes for MPP were summarized descriptively based on the specific procedures used during operations. Statistical models were untenable in this regard because the number of replicates under each procedure was not sufficient. However, we compared intraoperative outcomes between non-expanded pancreatic resections and multi-visceral resections with t-tests. We compared outcomes with the TP group by pooling all MPP operations together and using Type III ANOVAs, incorporating age, American Society of Anesthesiologists classification (ASA°) [26,27,28], and sex as patient-level covariates. These analyses were repeated using a reduced dataset that excluded multi-visceral resections from the MPP sample, since all TP operations were conducted around the pancreas and the extent of resection surgery can have significant associations with intraoperative outcomes [8,9]. Resections of the spleen, duodenum, and gallbladder were excluded from the definition of multi-visceral resection as these are part of standard pancreatic resection. ## 2.4.3. Postoperative Course The postoperative course for MPP patients was summarized descriptively and formally analyzed using logistic regression models for the effects of patient characteristics, surgical outcomes, and pathological dignity on binary event outcomes. A negative binomial generalized linear model (GLM) was used to analyze the length of stay because the Poisson model showed overdispersion. A full model containing all factors of interest could not be fitted for many of these models, so three reduced models (patient characteristics, surgical outcomes, pathological dignity) were fitted and compared to a null model with no factors using the corrected Akaike Information Criterion (AIC). Models were interpreted if they (i) provided equivalent or better explanatory power than the null model, (ii) satisfied model assumptions, and (iii) contained (borderline) significant effects from any component parameter based on a Wald test or the confidence interval. Postoperative outcomes for patients in the MPP and TP groups were compared using logistic regression models (negative binomial GLM for the length of stay), with the surgery group as the treatment of interest and age, ASA°, and sex as patient-level covariates. The main effect of surgery type and the confidence interval of its odd ratios were used to infer any differences in outcome between surgery groups. Models could not be fitted in comparisons where all patients in a group had the same outcome, so some comparisons were made descriptively. ## 2.4.4. Long-Term Follow-Up and Survival Robust models of survival analysis were untenable because of the wide variation in follow-up time, small sample size, and relatively few deaths observed. Therefore, our survival analysis for patients receiving MPP was based on summary descriptions of the patients who had died and univariate comparisons with those who survived. We used a reduced dataset to provide some control over the variation in follow-up times by excluding patients without an observed death who had less than 10 years of follow-up. We provided tentative survival estimates for MPP patients using Kaplan-Meier models. ## 3.1. Literature Review and Risk of Bias All of the included studies were case reports or small case series (Table 1). Of the 31 articles identified through the initial search, 17 articles with a total of 28 MPP patients were included in the final analysis (Figure 2). Of these articles, 11 were assessed to have a moderate risk of bias (Table A1) because the authors did not report the selection of patients included in the article (i.e., the study may have omitted other patients undergoing MPP at the same center). Other domains for risk of bias at the study level were assessed as negligible. We completed our analytical sampling with patients from our records. Here, we added 1 additional patient to the MPP group and formed a comparator group of 14 TP patients that had been evaluated as potential MPP candidates, bringing the IPD to 43 patients (29 MPP and 14 TP). We determined that risk of bias may exist at the sample level for $\frac{2}{7}$ domains of ROBINS-I [25]. Firstly, our samples may have carried serious risks of bias due to confounding because the patient characteristics (e.g., age, comorbidity, suspected histology) contributed to both the chosen intervention and surgical outcome. Furthermore, our TP sample represented non-independent homogeneous operations from a single center, whereas the MPP sample represented diverse and independent operations from multiple centers. Secondly, we also assessed a moderate risk of bias due to deviations from the intended interventions; the MPP sample contained different co-interventions and intra-operative technical variations, whereas procedures were more standardized in the TP group. We could partly account for these risks by including patient-level covariates in the analysis, but they were otherwise inherent limitations to a retrospective case study analysis with a curated comparator group. ## 3.2. Pre-Operative Baseline IPD for baseline variables are provided in Supplementary Tables S2 and S3 and a summary for the MPP and TP groups is provided in Table A2. A summary of the underlying pathologies in the pancreatic head and tail is provided in Table A2. Across all patients, the mean age at surgery was 61 years, with 24 females ($56\%$) and 19 males ($44\%$). ASA° was ≤2 for 27 patients ($63\%$) and >2 for 16 patients ($37\%$). Pre-existing diabetes mellitus was present in $\frac{8}{43}$ patients ($19\%$). There were no significant differences in the mean age or distributions of sex, ASA°, or pre-existing diabetes between groups (Table A2). The most common surgical indication was for pancreatic neoplasia, in both MPP ($\frac{12}{29}$; $41\%$) and TP ($\frac{8}{14}$; $57\%$) patients. Multiple synchronous pancreatic pathologies were also common among both MPP ($\frac{10}{29}$; $34\%$) and TP ($\frac{3}{14}$; $21\%$) patients. The remaining 3 ($2\%$) TP patients were indicated for non-neoplastic pathologies (mainly chronic pancreatitis), compared to 1 ($3\%$) MPP patient. There were 6 ($21\%$) MPP patients indicated for intra-pancreatic metastatic pathologies, but none from the TP group. This is because only patients with benign multilocular pancreatic pathologies were selected for the TP group and hence no patients were indicated for metastatic pathologies. The result was a borderline significant difference in the distribution of surgical indications between groups (Table A2). Relatedly, $\frac{19}{29}$ ($66\%$) MPP patients had a malignant pathology, whereas all 14 TP patients had a benign pathology (Fisher’s test: $p \leq 0.001$). ## 3.3. Surgical Resections and Intraoperative Outcomes Individual patient data for surgical procedures and intraoperative outcomes are provided in Supplementary Tables S4 and S5. The procedures are illustrated in Figure 1 and the intraoperative outcomes are summarized in Table 2. The intraoperative outcomes are compared between MPP and TP groups in Figure 3 and Table A4. ## 3.3.1. MPP Surgical Procedures The most common proximal MPP operation was pylorus-preserving pancreaticoduodenectomy (PPPD; Traverso-Longmire procedure; $\frac{12}{29}$; $41\%$). Other common procedures included pancreaticoduodenectomy (PD; Kausch-Whipple procedure; $\frac{7}{29}$; $24\%$), and subtotal stomach-preserving pancreaticoduodenectomy (SSSPD; $\frac{5}{29}$; $17\%$), 1 of the latter being laparoscopic. Parenchyma-sparing resections at the head occurred in $\frac{5}{29}$ ($17\%$) cases, including 2 inferior pancreatic head resections, 2 duodenum-preserving pancreatic head resections (including 1 Beger procedure), and 1 uncinate process resection. Head resections were coupled with spleen-preserving distal pancreatectomy or spleen-resecting procedures, which were used independently of the proximal procedure (Fisher’s test: $$p \leq 0.260$$). Most operations ($\frac{24}{26}$; $92\%$) used pancreaticojejunostomy for anastomosis, whereas 1 operation used reversed pancreaticogastrostomy and 1 operation did not use anastomosis (after uncinate process resection). Transection was typically achieved with a scalpel and sutures ($\frac{15}{21}$; $71\%$), with a stapler used in $\frac{6}{21}$ patients ($29\%$). Multi-visceral resections in addition to the pancreatic resection ($\frac{6}{29}$; $21\%$) included: superior mesenteric vein resection and reconstruction, right lobectomy of the liver, left hepatectomy due to single liver metastasis, and right hemicolectomy. There were also two metachronous and synchronous resections for extrapancreatic lesions, including a metastatic dermatofibrosarcoma protuberans (DFSP) in the right lung and a metastatic pheochromocytoma at a previous surgical site of left adrenalectomy. ## 3.3.2. MPP Intraoperative Outcomes The median operation time for MPP surgeries was 440 min (range: 250–670 min). Multi-visceral operations tended to run longer than operations restricted to the pancreas, although not significantly (t6.6 = 1.54, $$p \leq 0.169$$). Operations were significantly longer in older patients (Figure 3a, Table A4). There were 2 patients with statistically outlying amounts of blood loss at 5055 and 5500 mL. Median blood loss was 800 mL (range: 150–5500 mL), with no significant difference in blood lost between multi-visceral and pancreatic resections (t5.8 = 0.88, $$p \leq 0.414$$). Significantly more blood was lost in patients with ASA° > 2 (Figure 3b, Table A4). The remnant pancreas had a median length of 5.1 cm (range: 2.0–9.0 cm, $$n = 27$$) and a median of $33.8\%$ of the original volume (range: 15.0–$56.9\%$, $$n = 18$$). Patient variables had no significant association with remnant length (Table A4). We detected significantly longer pancreatic remnants when the resection was restricted to the pancreas and was not multi-visceral (t15.0 = 2.20, $$p \leq 0.044$$), but this pattern did not hold for remnant volume (t6.0 = 0.15, $$p \leq 0.885$$). ## 3.3.3. Comparison of Intraoperative Outcomes with TP Patients The mean log operation time was significantly longer in the MPP group than in the TP group (Figure 3a, Table A4), but blood loss did not significantly differ between surgery types (Figure 3b, Table A4). Remnant lengths ranged from 2.0 to 9.0 cm (Q1–Q3: 4.75–7.00 cm) and estimated unaffected parenchyma lengths ranged from 3.0 to 9.0 cm (Q1–Q3: 3.0–5.0 cm). There was no significant difference between the mean length of the remnant in MPP patients and the estimated unaffected parenchyma in TP patients (Figure 3c, Table A4). ## 3.4. Postoperative Course and Complications Individual patient data for the postoperative course are provided in Supplementary Tables S6 and S7. The observed frequencies for short- and intermediate-term complications in the MPP and TP groups are provided in Figure 4. Figure 5 summarizes the prognostic indicators for complications in the MPP group. The results of multi-model comparisons and the estimates of selected models are provided in Table A5, Table A6, Table A7 and Table A8. Comparisons between MPP and TP groups are available in Table A9. ## 3.4.1. MPP Postoperative Outcomes The median postoperative length of stay was 30 days (min, Q1, Q3, max = 5, 21, 50, 139 days, respectively). Hospital stays were significantly longer after prolonged operations and operations with greater amounts of blood loss (Figure 5a). Although $69\%$ of MPP patients experienced a postoperative event and $76\%$ experienced morbidity (Figure 4), most of the complications were of minor to intermediate severity. POPF occurred in more than half of the MPP patients, but all cases were POPF Grade B, and all patients recovered completely after interventional drainage placement. There were no subsequent life-threatening complications, no cases of organ failure, and no rescue operations were needed (i.e., no Grade C cases). Delayed gastric emptying occurred in $14\%$ of patients, but all cases were successfully managed with conservative treatment. Other complications occurred in $31\%$ of patients, including symptomatic pseudocyst, respiratory failure, early post-pancreatectomy hemorrhage (Type B PPH), splenic hematoma, peritoneal bleeding, liver abscess, cholangitis, pleural effusion, and superficial wound-healing disorder. Three patients ($10\%$) had recorded readmissions, all of whom were treated and cured for other complications (symptomatic pseudocyst, liver abscess, and cholangitis). Multi-model comparisons indicated that the surgical outcome provided notable explanatory power for an uneventful postoperative course, morbidity, POPF, and readmission (Table A5). Specifically, the odds of an uneventful course (borderline) improved with the length of the pancreatic remnant, and longer remnants were also (borderline) associated with lower rates of morbidity and POPF (Figure 5b–d). ## 3.4.2. MPP Postoperative Pancreatic Function Endocrine pancreatic insufficiency was reported in $44\%$ of patients, including also mild cases of impaired glucose tolerance and fasting glucose (Figure 4). New-onset diabetes mellitus occurred in 7 ($29\%$) patients who had no pre-existing condition, with $\frac{5}{7}$ ($71\%$) being insulin-dependent and $\frac{2}{7}$ ($29\%$) being non-insulin-dependent. Exocrine insufficiency was recorded in $\frac{8}{27}$ ($30\%$) patients and presented as steatorrhea after fatty food ($\frac{7}{8}$; $88\%$) and decreased fecal elastase (<50 μg/g; $\frac{1}{8}$; $13\%$). Multi-model analysis indicated that patient variables were informative for explaining the development of endocrine insufficiency and new-onset DM, but not exocrine insufficiency (Table A5 and Table A6). In particular, the odds of presenting with endocrine insufficiency or DM following MPP surgery increased with age (Figure 5e,f). The model for endocrine insufficiency also detected a borderline effect of ASA° because $\frac{10}{12}$ ($83\%$) patients with endocrine insufficiency had ASA° ≤ 2. In contrast, multi-model comparisons suggested that pathological dignity was informative for explaining exocrine insufficiency (Table A5). A post-hoc analysis revealed that these results were heavily influenced by patients with chronic pancreatitis (CP). Specifically, non-CP patients experienced only $6\%$ (0–$81\%$) the rate of exocrine insufficiency as CP patients (Fisher’s test: $$p \leq 0.015$$, Figure 5g). Sensitivity analyses that removed CP patients suggested that the surgical outcome model was informative, but no component factors had clear prognostic associations with exocrine insufficiency (Table A5 and Table A7). Finally, all patients with exocrine insufficiency received operations that resected or reduced the pancreatic head (6 PPPD; 1 PD; 1 DPPHR). ## 3.4.3. Comparison of Postoperative Course with TP Patients MPP patients had significantly longer postoperative stays than TP patients, but there were no significant differences in the likelihood of adverse events or morbidity between groups (Table A9). Although the overall incidence rates were similar, the rates for specific complications varied between groups (Figure 4, Table A9). On the one hand, readmissions, POPF, and DGE only occurred in the MPP group and were completely absent in the TP group. On the other hand, less than half of the MPP patients developed endocrine or exocrine pancreatic insufficiency, whereas both of these conditions were prevalent in the TP group. Moreover, few MPP patients suffered from manifest diabetes mellitus or insulin dependency. Of the data available, $\frac{1}{7}$ ($14\%$) MPP patients experienced a hypoglycemic event compared to $\frac{10}{10}$ TP patients (Fisher’s test: OR = 0.00–0.27, $p \leq 0.001$). MPP patients also displayed lower mean HbA1c (t18.06 = 2.13, $$p \leq 0.047$$) and fasting blood glucose (t8.04 = 13.07, $p \leq 0.001$) than TP patients. MPP patients were significantly less likely to experience exocrine insufficiency than TP patients (Table A9), but there was no significant difference in their presentation. The rate of steatorrhea did not differ (Fisher’s test: OR = 0.10–2.72, $$p \leq 0.480$$) between MPP ($\frac{7}{17}$; $41\%$) and TP ($\frac{8}{14}$; $57\%$) patients. Average weight loss was 4.00 ± 5.68 kg for MPP patients ($$n = 8$$) and 7.85 ± 8.56 kg for TP patients ($$n = 14$$), but this difference was not significant (t19.38 = 1.26, $$p \leq 0.221$$). Finally, patients in the MPP group were significantly less likely to present with other complications than those in the TP group (Figure 4, Table A9). ## 3.5. MPP Long-Term Follow-Up and Survival Analysis Median follow-up for the MPP group was 72 months (range: 5–228), in which 6 patients ($21\%$) died (Table A10). Malignancy was assessed in all 6 patients, with a metastatic stage present at the time of operation in 3 cases (renal cell cancer, DFSP, and rectal cancer). Of those that died, $\frac{4}{6}$ ($67\%$) patients died from tumor recurrence or progression to systemic metastases. Of the remaining 2 patients, one died from cerebral infarction and the other from malignant lymphoma. Of the $\frac{5}{29}$ MPP patients with an observed recurrence of malignancy, $\frac{4}{5}$ ($80\%$) patients died during follow-up. The majority of malignant cases survived over the follow-up period ($\frac{13}{19}$; $68\%$), although follow-up times ranged from 5 to 185 months. Kaplan-Meier estimates suggested that median survival among all MPP patients with malignant pathologies was 110 months ($95\%$ CI: 58—incalculable). One-year survival for malignant cases undergoing MPP was $94\%$ and three-year survival was $81\%$. To control for variation in follow-up times, we used a reduced dataset including only patients with survival follow-up extending to at least 10 years ($$n = 12$$). Univariate comparisons between those that died or survived indicated that survival may be associated with the recurrence of malignancy after surgery and pancreatic remnant length (Table 3). Specifically, those who experienced a recurrence were borderline more likely to die within 10 years, while patients with larger remnants were significantly more likely to survive than die within 10 years. There was no significant difference in survival between malignant and non-malignant cases. Within the reduced dataset, median survival for those with malignant pathologies at the time of surgery was estimated at 58 months, whereas it was estimated at 39 months for patients with recurrent malignancies. Patients with remnants smaller than the overall MPP median (<5.15 cm) were estimated to have a median survival of 36 months. Median survival across all 12 patients in the reduced dataset was estimated at 110 months. One-year survival within the reduced dataset was $92\%$ (CI: 77–100) and three-year survival was $75\%$ (CI: 54–100). ## 4. Discussion MPP is a novel and rare surgical technique that demands investigation. By compiling all published reports on the procedure, our dataset provides an early opportunity to study its potential risks and benefits. Although MPP procedures take longer on average than TP, it appears to be effective at sparing unaffected parenchyma that would otherwise be lost. This can have significant benefits for the postoperative course and long-term outcomes. Specifically, MPP is associated with severely reduced risks of functional endocrine and exocrine complications, including new-onset DM. That being said, MPP does not eliminate the risks of POPF or DGE as completely as TP. The long-term outcomes after MPP surgery appear promising, especially for patients with benign pathologies and large spared remnants. Survival for patients with malignant pathologies was conservatively estimated at 58 months, despite many of these patients being metastatic at the time of surgery. Overall, this systematic review and analysis suggest that MPP is a feasible alternative to TP in light of ongoing developments in pancreatic surgery. Furthermore, this early analysis provides reliable evidence for more dedicated clinical research efforts. However, we must stress that potential cases for MPP are still expected to be rare since our evaluation of 244 patients receiving TP for multilocular disease over 18 years revealed only 14 ($6\%$) patients suitable for MPP. This indicates that there is most often no alternative to TP. TP is the current standard of care for multilocular pancreatic pathologies (even if lesions spare the pancreatic body) because of its capacity to avoid POPF and other secondary complications in the short term. However, it comes with physical impairment, high mortality rates, and reduced QOL in the long term [10,11,12]. Major concerns include diabetes, with a systematic review finding that approximately $80\%$ of TP patients develop hypoglycemic episodes (with $40\%$ experiencing severe hypoglycemia), resulting in 0–$8\%$ mortality and 25–$45\%$ morbidity [10]. Pancreoprivic diabetes can complicate recovery and predispose patients to readmission, leading to treatment costs that can be triple those for patients with non-pancreatogenic diabetes [12]. Fortunately, the management of endocrine insufficiency after TP has improved over the past decades, leading to diabetes-specific outcomes that seem equivalent to other types of insulin-dependent diabetes [51]. Additionally, QOL impairment by exocrine insufficiency might be improved by modern pancreatic enzyme preparations [52]. However, endocrine and exocrine insufficiencies still seem to heavily impair QOL after TP [53,54,55]. The life-long burdens related to TP were illustrated in a recent study reporting that the psychosocial impact of diabetes, the need for insulin therapy, and the severity of exocrine insufficiency were all significantly greater after TP than after a Kausch-Whipple procedure [5]. Therefore, there are severe detriments to the complete removal of the parenchyma and a consequent need to critically evaluate the application of TP as a treatment or rescue operation in selected cases. Indeed, it has been recommended to use TP in non-oncological cases only when avoiding POPF and its related sequelae can overcome the drawbacks of life-long diabetes and exocrine insufficiency [5]. Functional complications of the endocrine and exocrine pancreatic systems are a ubiquitous concern for TP patients [10,11,12], and MPP represents a method with the potential to retain pancreatic functionality. The pre-operative rates of DM were equivalent between MPP and TP patients, implying a similar baseline quality of the pancreatic parenchyma between groups. Therefore, the subsequent difference in new-onset DM after surgery suggests that patients may be saved from postoperative diabetes by receiving MPP. Additionally, pancreoprivic diabetes may be more serious after TP, as potentially life-threatening hypoglycemic events were common among TP patients but rare among MPP patients. However, older patients were still more likely to experience functional complications than younger patients after MPP in terms of endocrine insufficiencies and new-onset diabetes, possibly due to the natural degradation of organ quality with age. Additionally, the risk of exocrine insufficiency may be greater for patients with chronic pancreatitis due to disease-related organ damage. The risk of exocrine insufficiency may also increase with the extent of resection of the pancreatic head. In total, however, the majority of patients were free of functional endocrine and exocrine complications after MPP surgery, whereas they were guaranteed after TP surgery. In contrast to TP, MPP carries the risks of typical complications of partial pancreatectomy, such as POPF and DGE. In this respect, remnant length was highlighted as an important prognostic factor following MPP. Specifically, longer pancreatic remnants were associated with shorter and less eventful hospital stays alongside decreased risks of morbidity and POPF. However, it is unclear whether saving more parenchyma necessarily translates into better clinical outcomes, as it may also be easier to preserve longer remnants in healthier patients with good baseline prognoses. Remarkably, our evidence emphasizes that larger pancreatic remnants are not associated with greater risk of developing POPF or other complications compared to smaller remnants. Overall, 6 MPP patients died during follow-up. All of these patients had malignant pathologies, half of whom were already in a metastatic stage at the time of surgery. Indeed, death was significantly associated with recurrence of malignancy or metastatic progression. The length of the pancreatic remnant was also highlighted as a significant prognostic factor, as patients with longer remnants were significantly more likely to survive for 10 years than those with smaller remnants. However, this retrospective study cannot determine whether leaving longer remnants contributes to survival or if longer remnants can be saved in patients with better survival prospects. Overall, survival outcomes of MPP were promising, with a median survival of 110 months in a dataset covering 10 years of follow-up and three-quarters of patients suffering from malignant diseases. However, the number of reported MPP cases was still too small for thorough survival analysis. Our analytical approach was limited by small sample sizes, but this was not a failure of study design. Indeed, the rarity of data and unmet need for synthesis was the issue being addressed by this research. Hence, our MPP sample included most, if not all, published and retrievable individual patient data available to date. This allowed us to establish the largest cohort of MPP patients possible for our analysis. In turn, our careful curation of a benchmark TP sample provided numerous control benefits at the cost of sample size and non-independence. Specifically, our sample benefited from limiting the error attributable to variation in techniques across centers. Furthermore, patients were carefully curated on the basis of whether they could have received MPP, thereby providing some approximation of patient matching and relevancy. Finally, the selection of TP patients with only benign cases produced a sample with less oncological risk for use as a healthier benchmark and to sharpen contrasts. Therefore, the small size and non-independence of the TP sample was not as serious a drawback as it appears since we were more interested in a reliable benchmark than in generalizing outcomes or effect measures to the general TP population. We highlight the limitations and biases inherent to our approach so that the results can be critically interpreted, but we also highlight that the analysis was designed to provide robust and reliable interpretations given the paucity of MPP data. Finally, compared to a meta-analysis of aggregate data, our IPD approach incorporated many outcome measurements whilst being more standardized and less impaired by selection or publication biases [19]. Nevertheless, we strongly recommend future research to improve upon our analytical methods as more MPP data becomes available. Our risk of bias analysis suggested that $65\%$ of retrieved papers had a moderate risk of bias because they did not report on previous experience with MPP intervention. However, given the rarity of this operation and the value of reporting its outcomes, it is probably safe to assume that the reported cases reflected the entire experience of the responsible clinics. Even if this was not the case, the risk of bias existed only in the domain of patients selected to report, and we did not assess any risk owing to the quality of outcome measurements, alternative causalities, lack of follow-up, or fidelity in reporting. ## 5. Conclusions This systematic review and IPD analysis suggest that MPP is a feasible alternative to TP. Perioperative and postoperative parameters were satisfactory, especially for younger patients and those with larger spared remnants. Furthermore, survival prognosis was satisfactory for those with benign disease and acceptable even for many with malignant diseases (providing there was no metastasis or recurrence). However, the number of reported cases was too low to make reliable survival estimates. In summation, despite some risk of short-term complications, MPP offers a resection technique that can spare pancreatic functionality and provide long-term benefits over TP. Therefore, it could be considered in rare and selected cases (e.g., young patients with large savable remnants, no pre-existing diabetes, and no organ damage from chronic pancreatitis). ## References 1. Rockey E.W.. **Total Pancreatectomy for Carcinoma**. *Ann. Surg.* (1943) **118** 603-611. 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--- title: Stromal Vascular Fraction Cells from Individuals Who Have Previously Undergone Radiotherapy Retain Their Pro-Wound Healing Properties authors: - Lucy V. Trevor - Kirsten Riches-Suman - Ajay L. Mahajan - M. Julie Thornton journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003870 doi: 10.3390/jcm12052052 license: CC BY 4.0 --- # Stromal Vascular Fraction Cells from Individuals Who Have Previously Undergone Radiotherapy Retain Their Pro-Wound Healing Properties ## Abstract Beneficial effects have been observed following the transplant of lipoaspirates containing adipose-derived stem cells into chronic wounds caused by oncologic radiotherapy. It is not yet certain whether adipose-derived stem cells are resistant to radiation exposure. Therefore, the aims of this study were to isolate stromal vascular fraction from human breast tissue exposed to radiotherapy and determine the presence of adipose-derived stem cells. Stromal vascular fraction from irradiated donor tissue was compared to commercially sourced pre-adipocytes. Immunocytochemistry was used to determine the presence of adipose-derived stem cell markers. Conditioned media from stromal vascular fraction isolated from irradiated donors was used as a treatment in a scratch wound assay of dermal fibroblasts also isolated from irradiated donors and compared to pre-adipocyte conditioned media and serum free control. This is the first report of human stromal vascular fraction being cultured from previously irradiated breast tissue. Stromal vascular fraction conditioned media from irradiated donors had a similar effect in increasing the migration of dermal fibroblasts from irradiated skin to pre-adipocyte conditioned media from healthy donors. Therefore, the ability of adipose-derived stem cells in the stromal vascular fraction to stimulate dermal fibroblasts in wound healing appears to be preserved following radiotherapy. This study demonstrates that stromal vascular fraction from irradiated patients is viable, functional and may have potential for regenerative medicine techniques following radiotherapy. ## 1. Introduction Curative, adjuvant, or palliative radiotherapy is commonly used to combat cancer [1]. In breast cancer, a standard adjuvant radiotherapy regimen consists of 15 fractions of 40 Gγ external beam. Whilst the therapeutic aim is to provide enough radiation damage to halt or regress tumour growth, it is inevitable that adjacent healthy tissue is also exposed to radiation. Skin reactions are common, with over $90\%$ of patients receiving radiotherapy reporting some dermal damage [2]. These reactions can be immediate—characterized by redness at the radiotherapy site—or prolonged in nature with dermal fibroblast (DF) dysfunction, hyper-inflammatory responses, fibrosis and damage to the underlying microcirculation [3]. Radiotherapy can be provided to breast cancer patients before or after mastectomy, and the impact of radiotherapy on success and satisfaction rates after subsequent reconstruction varies. For implant-based reconstruction, radiotherapy was associated with poor patient satisfaction irrespective of whether radiotherapy was applied prior to or after reconstruction. Similarly, prior, or post-reconstruction radiotherapy was associated with capsule contracture and an increased need for repeat surgery (reviewed in [4]). Interestingly, the degree of radiation-induced skin damage is negatively correlated with post-implant reconstructive complications [5]. For patients undergoing autologous tissue reconstruction with radiotherapy, patient satisfaction and quality of life are higher than for implant-based surgeries [6]. Given autologous implants use fat tissue from the stomach or back, it is possible that the improved outcomes in these patients are due to factors released from this adipose tissue. Far from being an inert insulation system and connective tissue, adipose is now considered a complex endocrine organ. Approximately one third of adipose tissue is comprised of mature adipocyte cells, with the remaining two thirds comprising a heterogeneous mixture of cells including fibroblasts, endothelial progenitor cells, pericytes, white and red blood cells, as well as mesenchymal stem cells. These cells together comprise what is termed the stromal vascular fraction (SVF; reviewed in [7]). The mesenchymal stem cell niche, termed adipose-derived stem or stromal cells (ASCs), were first identified in 2001 and were later isolated from human SVF [8,9]. Within the literature, the term ASC can be interchanged with preadipocytes [10]. They are present in SVF from white subcutaneous adipose tissue [11] and are reportedly more resistant to in vitro radiation exposure than bone marrow stem cells [12]. Thus, ASCs within human SVF could contribute to the observed beneficial impact of autologous breast reconstruction following radiotherapy. ASCs in culture are characterized by the expression of CD44, CD73, CD90 and CD105, with no expression of the hematopoietic marker CD45 (which is present in non-ASC SVF cells) [13,14]. ASCs secrete paracrine factors which can enhance wound healing in animal in vivo models [15] and ASC exosomes can promote DF migration in vitro [16]. The secretome contains multiple growth factors and adipokines including fibroblast growth factor 2 (FGF2), adiponectin and vascular endothelial growth factor (VEGF) [17,18,19]; all of which may promote the wound healing response. Despite the promise that human ASCs hold for improved surgical outcomes following radiotherapy, and their reported resistance to radiation-induced damage, there have been no studies performed to date that have isolated ASCs from the SVF of patients who have undergone radiotherapy. Thus, the aim of this project was to perfect an isolation procedure of SVF from the breast tissue of patients who have undergone prior radiotherapy; to successfully culture ASCs from this SVF, and to provide proof-of-concept data that assesses whether their secretome may be beneficial for wound healing. ## 2.1. Human Tissue Collection Human tissue was obtained via Ethical Tissue following ethical approval from Leeds (East) Research Ethics Committee. This was submitted 20 November 2017 with the ISAC reference number $\frac{17}{091.}$ Excess human tissue was obtained with informed consent from female patients undergoing reconstructive surgery following breast cancer, mastectomy/wide local excision and 40 Gy in 15 fractions of radiotherapy. Samples were transported on ice, at approximately 4–8 °C, and processed within 24 h. ## 2.2. SVF Isolation Methodology was developed for the isolation of SVF cells from breast tissue subcutaneous fat adapted from the literature [20,21]. Subcutaneous fat was rinsed with tissue washing solution (sterile PBS with 10 µL/mL primacin), minced, and approx. 15 mL fat was transferred to a 50 mL tube containing 15 mL preadipocyte growth media with 1 mg/mL collagenase. This was briefly vortexed and incubated at 37 °C for one hour with regular (5–10 min) agitation. Following this, 15 mL preadipocyte growth media (PromoCell preadipocyte basal medium supplemented with $5\%$ FBS, 4 µL/mL endothelial cell growth supplement, 10 ng/mL recombinant human epidermal growth factor, 1 µg/mL hydrocortisone, 90 µg/mL heparin and 2 µL/mL primacin) was added to the solution which was then passed through a cell strainer into a fresh 50 mL tube to remove undigested debris and centrifuged (600× g for 5 min). The floating fatty portion containing further undigested material and the supernatant was discarded and the pellet resuspended in 15 mL preadipocyte media. After further centrifugation (600× g for 5 min), the pellet was resuspended in 20 mL preadipocyte media and divided between two 75 cm2 flasks. After 24 h in a tissue culture incubator, adherent cells were washed thrice with PBS. Growth media was changed daily to ensure removal of red blood cells from the cultured cells. After 3–5 days the cells reached approximately $85\%$ confluency and were passaged using trypsin/EDTA, centrifuged (600× g for 5 min) and re-seeded at a 1:3 dilution. ## 2.3. Dermal Fibroblast (DF) Isolation The epidermis and deep dermis/subcutaneous fat were separated from the dermis which was diced into 5 mm2 pieces. This was placed papillary dermis-down in a sterile 100 mm2 tissue culture dish in fibroblast growth medium (DMEM with $10\%$ FBS, 2 µL/mL primacin and 10 µL/mL Glutamax). Tissue was incubated at 37 °C, in a humidified incubator with $5\%$ CO2 in air and medium was changed after seven days and then twice weekly thereafter, allowing DF time to explant. DF were cultured in this way up until passage 3, at which point they were transferred into preadipocyte media. Cell growth and morphology were not altered. This media change ensured the same type of growth media was used throughout all experimental procedures, including conditioned media (CM) supplementation; and thus, any experimental differences in cell behaviour were attributable to factors secreted by cells rather than a different growth media composition. ## 2.4. Preadipocyte Cell Culture Commercial preadipocytes (PromoCell) were resuspended in preadipocyte media and transferred to 75 cm2 flasks and routinely passaged using trypsin/EDTA as above. ## 2.5. Immunocytochemistry SVF cells and commercial preadipocytes were plated in 8-well chamber slides at a density of 5000 cells per well and grown in preadipocyte growth media until $70\%$ confluent. They were then washed in PBS and fixed in ice-cold methanol for 10 min at −20 °C. Cells were washed thrice in PBS (5 min per wash), blocked in PBS containing $10\%$ donkey serum (90 min) and incubated with primary antibodies diluted in PBS containing $1\%$ donkey serum. Primary antibodies were: CD10 ab951 Anti-CD10 antibody (56C6) 1:100, CD45 ab40763 Anti-CD45 antibody (EP322Y) 1:100, CD73 ab54217 Anti-CD73 antibody (7G2) 1:200, and CD105 ab114052 Anti-CD105 antibody (3A9) 1:200. These were incubated for 1 h at room temperature. Cells were subsequently washed thrice in PBS (5 min per wash) and incubated with secondary antibodies diluted in PBS containing $1\%$ donkey serum for one hour, protected from light. Secondary antibodies were: Alexa Fluor Donkey Anti-Mouse IgG and Alexa Fluor Donkey Anti-Rabbit IgG (versions for both that fluoresced at 594 or 488) 1:100. Finally, cells were washed four times with PBS and mounted using Vectashield® Mounting Media containing 4′,6-diamidino-2-phenylindole (DAPI). Random images were captured on a confocal microscope at ×250 magnification. ## 2.6. Collection of Conditioned Media SVF cells and commercial preadipocytes were plated into six-well plates at a density of 150,000 cells per well in preadipocyte media. After 48 h, cells were washed thrice in sterile PBS and maintained for 24 h in preadipocyte media containing no serum. Conditioned media (CM) was collected into sterile microcentrifuge tubes and centrifuged at 300× g for 5 min) before filtering through a 40 μm filter to remove cell debris. The resultant CM was stored at −20 °C until use. ## 2.7. Quantification of Paracrine Factors The concentration of FGF2, adiponectin and VEGF in CM was measured using commercial Quantikine ELISA kits as per manufacturers’ instructions (R&D Systems). FGF2 was mixed 1:1 with assay diluent RD1W during the assay (DFB50); adiponectin was mixed 1:2 (DRP300) and VEGF was mixed 1:4 (DVE00). Unknown sample concentrations were interpolated from a standard curve run on each experiment. ## 2.8. Scratch Wound Assay DF were seeded in triplicate at a density of 150,000 cells per well in six-well plates, in preadipocyte media. Once the cells reached $85\%$ confluency they were washed thrice in sterile PBS and incubated for 24 h in preadipocyte media containing no serum. A linear wound was made in the monolayer, cell debris removed by washing with PBS, and the cell-free scratch wounded area imaged as previously described [22]. Media was replaced with serum free preadipocyte media, or SVF CM or preadipocyte CM as described in Section 2.6. A CooLpix 4500 *Nikon camera* was used to take images at 0, 6, 24 and 48 h at fixed points, at ×40 magnification. The distance between the two wound edges (left and right) was measured at six fixed points per well using ImageJ software. The mean reduction in distance was calculated at each timepoint. ## 2.9. Statistical Analysis Concentrations of paracrine factors were analysed using unpaired t-tests. Scratch wound migration assays used a two-way ANOVA with repeated measures and post-hoc test using GraphPad Prism 8. $p \leq 0.05$ was considered statistically significant. n refers to the number of independent experiments performed. ## 3.1. Isolation of SVF Isolation of SVF from irradiated tissue (IR-SVF) has not been performed previously. The methodology described here was adapted from protocols on non-irradiated SVF isolation as described in the literature [20,21]. During the optimisation of the technique, several amendments were made. Collagenase concentrations ranging from 0.5–2.0 mg/mL were tested for the release of IR-SVF from minced tissue; however 0.5 mg/dL failed to release cells from tissue and 2.0 mg/mL caused cell apoptosis thus a concentration of 1.0 mg/mL was used in the successful protocol. Red blood cells are prevalent in IR-SVF pellets and so two techniques were used to remove them from the resultant cell culture. In the first technique, the pellet was washed with an ammonium-chloride-potassium buffer to cause red blood cell lysis [21], however this also caused lysis of other cells within the IR-SVF and successful cultures were not explanted. Thus, we removed this lysis step and instead removed red blood cell contaminants by washing cultured cells with PBS daily to remove them. DF were explanted from tissue in parallel and the complete successful protocol for matched cell isolation can be seen in Figure 1. ## 3.2. Characterisation of Adherent Cells from SVF as Preadipocytes The morphology of IR-SVF adherent cells was monitored across passages. At passage 0, there was an abundance of small, phase bright cells which were contaminating red blood cells; these were progressively removed during PBS washes as described previously. After 3–5 days, IR-SVF cells reached $85\%$ confluence and were passaged. Subsequent to this, IR-SVF cells grew quickly and required passaging every two days. Morphology was initially heterogeneous at lower passages but became more uniform and became consistently spindle-shaped by passage 3 (Figure 2a). SVF can contain a heterogenous mixture of cells including stromal cells, pericytes, endothelial cells, red and white blood cells and ASCs/preadipocytes [7]. IR-SVF cells at passage 3 underwent immunocytochemical analysis to verify their identity, using a panel of preadipocyte markers. These were compared with commercially available human preadipocytes at passage 4 (Promocell). Due to issues with the supply of fluorescently conjugated secondary antibodies, IR-SVF immunocytochemistry used a 594 nm (red) tag and preadipocytes used a 488 nm (green tag); however, the primary antibodies used in both instances were the same (Figure 2b). The percentage of cells expressing these markers was calculated by assessing 100 random cells across multiple fields of view (identified by DAPI-stained nuclei) per antibody, per cell type. As expected, $100\%$ of commercial preadipocytes stained positively for CD10, CD73 and CD105, and negatively for CD45. Only $58\%$ of IR-SVF stained positively for CD10, whereas $93\%$ were positive for CD73 and $100\%$ were positive for CD105. All were negative for CD45 (Figure 2c). Cumulatively, this demonstrates that a high proportion of cells within the IR-SVF are ASCs/preadipocytes. ## 3.3. Conditioned Media from IR-SVF Promotes Wound Healing In Vitro Preadipocytes are known to secrete numerous factors that can promote wound healing, including fibroblast growth factor 2 (FGF2), adiponectin and vascular endothelial growth factor (VEGF). Conditioned media (CM) from IR-SVF and commercial preadipocytes was collected and the concentration of these factors within CM was assessed using ELISA. The expression of both FGF2 and VEGF was comparable between preadipocytes and IR-SVF, however IR-SVF secreted significantly more adiponectin than preadipocytes (16.7 ± 0.45 ng/mL versus 14.0 ± 0.98 ng/mL); an increase of $20\%$ (Figure 3a). CM from IR-SVF and preadipocytes was used as a stimulus in DF migration assays to assess whether the secretion of paracrine factors by IR-SVF could still promote a wound healing response in vitro. CM from both IR-SVF and commercial preadipocytes promoted in vitro wound closure to a similar extent at all time points, with an increase in migration over control cells (treated with serum-free media only) visible as early as 6 h after treatment (Figure 3b,c). ## 4. Discussion To our knowledge, this is the first example in the literature of obtaining and culturing viable cells from the SVF of patients who have been exposed to radiotherapy. A large proportion of cells within the SVF were ASCs (as demonstrated by expression of ASC/preadipocyte surface markers), and the secretome of these cells was able to promote in vitro migration of dermal fibroblasts. Our isolation protocol was adapted from previous methods established for non-irradiated adipose tissue [20,21] but had some key changes to improve success rates. Sample centrifugation speeds are notoriously variable between and sometimes even within individual laboratories, and in our case, we used a speed of 600× g for 5 min. Initial studies on the isolation of adipocytes from lipoaspirates suggested a higher speed of ~1200× g for 3 min [23]; however speeds upwards of 900× g have been proven to cause up to three-fold as much adipocyte cell death as lower speeds [24]; hence 600× g was a logical compromise between centrifugal stress and cell yield. Collagenase concentration was carefully titrated to balance sufficient tissue digestion with maintenance of cell membrane integrity; with optimum results observed at a concentration of 1.0 mg/mL. Furthermore, red blood cell lysis with ammonium chloride potassium buffer was omitted [21] from the protocol as we observed this also caused lysis of other cell populations within IR-SVF. Following these amendments, we were able to isolate adherent cells from IR-SVF which proliferated readily in culture and became more homogenous in appearance through routine subculturing. Adherent cells from IR-SVF adapted an elongated spindle morphology typical of ASCs [25,26]. Analysis of cell surface markers demonstrated comparable positivity for CD73 and CD105 with commercial preadipocytes, as well as being CD45-negative. However, only half of IR-SVF cells were positive for CD10. Whilst CD10 has been found expressed in ASCs (reviewed in [27]), it is not a consensus as mesenchymal stem cells from human lipoaspirates were CD10 negative [28]. Thus, the absence of CD10 is not necessarily enough to conclude that ASCs only comprise up to half of the IR-SVF population. A further analysis of marker expression using Western blotting or flow cytometry would provide a more definitive characterization. Growth factors and chemokines are known to promote wound healing, and FGF2, adiponectin and VEGF have all had beneficial effects on in vitro wound healing assays [29,30,31]. We found that IR-SVF secreted each of these to a comparable level as commercial ASC/preadipocytes, and furthermore expressed $20\%$ more adiponectin. Whilst adiponectin was originally thought to be secreted exclusively by adipose cells, it is now recognized that it can be secreted by alternative cell types including muscle and vascular cells [32]; it is likely therefore that the modest increase in adiponectin secretion by IR-SVF represents a contribution from non-adipose-restricted tissue. The secretion of these chemokines by IR-SVF suggested that CM from IR-SVF might be able to promote migration in a scratch wound assay. Conditioned media from ASC has previously been demonstrated to promote DF migration in a scratch assay [16]. IR-SVF also promoted DF migration in our scratch assay which lends further credit to our argument that the cells we have isolated from IR-SVF are ASCs and moreover, that these ASCs retain their functionality and are resistant to catastrophic damage caused by radiotherapy. The observation that IR-SVF and PA-CM were equally able to induce migration despite a significant difference in adiponectin expression suggests that adiponectin is not critical for DF migration. The immunomodulation, anti-inflammatory and proangiogenic activity of SVF and ASCs are similar, however, SVF is easier and quicker to obtain as it does not require isolation of different types of cells, and therefore in a clinical setting can be applied immediately. However, there are varying techniques (enzymatic vs. non-enzymatic) for SVF isolation, hence a more standardised and accepted protocol for application is required. While many clinical studies have reported the use of mesenchymal stromal cells (MSCs) to be safe and feasible, some minor side effects have been conveyed. Long-term cell culture can result in accumulation of abnormalities and use of antibiotics in culture media can increase risk of contamination with mycoplasma, although fibrosis is the most common adverse event described [33]. Nonetheless, the assessment of the effectiveness of cell monotherapy for wound healing and choice of cell sources is a promising biomedical approach. The complications resulting in poor healing in tissue that has been exposed to radiation damage is not dissimilar to other chronic non-healing wounds such as diabetic foot ulcers (DFU). To assess the regenerative effect of any cell type, it needs to be administered as a monotherapy in the absence of others with potential therapeutic effects. For example, application of somatic cells to DFUs only stimulates healing, while MSCs can contribute to the restoration of angiogenesis [34]. The therapeutic effects of various cells and clinical studies where stem and somatic cell-based therapy was administered as a monotherapy is reviewed in [34]. While studies have shown ASCs exhibit superior wound healing properties to other applications, e.g., hyaluronic acid, skin grafts, etc. reviewed in [35], their isolation is not an easy procedure and still requires consolidated clinical practice. The culture of viable cells from SVF following exposure to radiation therapy is a novel finding. This valuable innovation is promising for the translation of ASC use into the clinic and reinforces the idea that mesenchymal stem cell populations may be resistant to radiation damage. This suggests that this tissue could still be a useful tool for promoting wound healing and surgical recovery in these patients. In vitro purification of these cells can be achieved in a matter of weeks, which again suggests a potential therapeutic application in patients, post-mastectomy. 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--- title: Effect of Localized Vibration Massage on Popliteal Blood Flow authors: - Devin Needs - Jonathan Blotter - Madison Cowan - Gilbert Fellingham - A. Wayne Johnson - Jeffrey Brent Feland journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003898 doi: 10.3390/jcm12052047 license: CC BY 4.0 --- # Effect of Localized Vibration Massage on Popliteal Blood Flow ## Abstract There is a broad scope of literature investigating whole-body vibration (WBV) effects on blood flow (BF). However, it is unclear how therapeutic localized vibrations alter BF. Low-frequency massage guns are advertised to enhance muscle recovery, which may be through BF changes; however, studies using these devices are lacking. Thus, the purpose of this study was to determine if popliteal artery BF increases from localized vibration to the calf. Twenty-six healthy, recreationally active university students (fourteen males, twelve females, mean age 22.3 years) participated. Each subject received eight therapeutic conditions randomized on different days with ultrasound blood flow measurements. The eight conditions combined either control, 30 Hz, 38 Hz, or 47 Hz for a duration of 5 or 10 min. BF measurements of mean blood velocity, arterial diameter, volume flow, and heart rate were measured. Using a cell means mixed model, we found that both control conditions resulted in decreased BF and that both 38 Hz and 47 Hz resulted in significant increases in volume flow and mean blood velocity, which remained elevated longer than the BF induced by 30 Hz. This study demonstrates localized vibrations at 38 Hz and 47 Hz significantly increase BF without affecting the heart rate and may support muscle recovery. ## 1. Introduction Over the last 20 years, whole-body vibrations (WBV) utilizing a vibrating platform with lower frequencies in the 20–50 Hz range have become a highly researched topic demonstrating beneficial musculoskeletal or physiological responses [1,2,3,4]. This treatment modality has been used both adjunctively with exercise or in rehabilitation. It has been investigated for its effect on muscle recovery [1,2,3], muscle oxygenation [4,5,6], muscle performance [7,8,9], and wound healing [10,11,12]. Despite the vast amounts of research on WBV application, much less is known about localized vibration effects at similar lower frequencies. In contrast, extensive work has been done on occupational hand–arm vibration syndrome studies at higher frequencies. These studies have shown detrimental effects to finger blood flow, particularly at frequencies greater than 63 Hz [13], which, in turn, have led to conflicting beliefs on the efficacy of localized vibrations as a therapeutic modality. Furthermore, little is known about the primary mechanisms through which vibrations affects the blood flow, but both the frequency and magnitude of vibrations appear to be important contributors to responses in the hand [13]. Whole-body vibration studies have generally shown resultant increases in the blood flow [4], both arterial [14,15,16,17,18] and cutaneous [4,19,20]. The results of these studies vary in the magnitude of response, which may be due to vibration parameters that can differ between studies, such as frequency, amplitude, duration, measurement site and depth (arterial vs. cutaneous), and types of vibration platforms (i.e., vertical vs. oscillating). Uniquely, oscillating vibration platforms using a low frequency (10–30 Hz) have more consistently reported increases in arterial blood flow compared to vertical platforms [4]. The frequency of a vibration has also been shown to influence the magnitude of blood flow responses [4,14,19,21]. For example, Lythgo et al., using standing WBV, demonstrated that the mean blood velocity in the femoral artery increased the most at 30 Hz when comparing 5 Hz increments between 5 and 30 Hz [14]. Meanwhile, Maloney-Hinds et al. reported that 50 Hz increased the skin blood flow more than 30 Hz while uniquely resting the arm on a vertical vibration platform as a form of localized vibration [21]. Thus, the use of vibration improves blood flow; however, the variability of vibration parameters (frequency, amplitude, and duration), along with WBV vs. localized vibrations, leaves an unclear picture as to the optimal combination for arterial vs. cutaneous blood flow responses. Local vibration treatments have recently gained popularity with the rise of percussion massage devices. These devices allow for the targeted treatment of specific soft tissue as compared to WBV, which affects the entire extremity. A study that surveyed health professionals reported that most respondents believed mechanical percussion would improve the local blood flow (54–$69\%$), followed by the enhancement of pre-exercise excitation ($37\%$) and improvement in the range of motion ($31\%$) [22]. Despite the popularity of these devices, there is a paucity of research utilizing massage guns to support claims that they enhance muscle recovery. Localized vibrations using a vibrating foam roller [23] and another study using a massage gun [24] showed an improved dorsiflexion range of motion in the ankle after treatment of the calf muscles. In other related research, hand and rolling massages offer limited treatment in comparison to local vibrations, as each involve applying pressure and friction to soft tissue. Hand and rolling massage have also been reported to increase the blood velocity [25,26] and skin temperature [27]. However, it is theorized that mechanical pressure can increase blood flow secondary to increasing arteriole pressure [28]. It is believed that local vibration therapy using a massage gun increases the arterial blood flow, but this has yet to be proven. Therefore, the purpose of this study was to examine the effect of frequency and duration of localized percussion massage of arterial blood flow in the lower leg. ## 2. Materials and Methods Subjects Twenty-six subjects (fourteen males, twelve females) were recruited from a university population and completed this study (mean age is 22.3 ± 2.3 years). Male subjects had a mean height of 182.6 ± 9.1 cm and average weight of 83.9 ± 18.7 kg. Female subjects had an average height of 168.4 ± 8.4 cm and average weight of 64.9 ± 10.0 kg. Inclusion criteria for the study required that subjects were recreationally active, described for this study as participating in at least 30 min of exercise 3x/week. Additionally, qualified subjects were required to be injury-free in the lower extremities over the past 3 months and without current complaints of lower extremity pain, discomfort, or soreness. Exclusion criteria consisted of a history of cardiovascular issues, peripheral vascular disorders, or taking any type of blood pressure medication. Qualified subjects were asked to avoid participating in a lower body exercise routine within the 4 h prior to each therapy visit and avoid consuming caffeine within 24 h of therapy. All qualified subjects signed an approved institutional IRB consent form (IRB2022-083) in accordance with the Declaration of Helsinki. Protocol This was a randomized crossover design. Subjects reported to the lab on 8 different days, with each visit separated by at least 24 h. Each subject underwent all therapeutic conditions and control conditions consisting of three frequencies (30 Hz, 38 Hz, and 47 Hz) and a control condition (C) for both a 5-min and 10-min duration in randomized order. Subjects began each session by having a 3-lead ECG connected to them to measure their heart rate. The ECG was directly linked with the GE Logiq S8 ultrasound unit (GE Healthcare, Chicago, IL, USA). Subjects lay prone on a treatment table for 10 min with their ankles placed on a small foam roller to allow the feet to hang relaxed and the knee to be mildly bent to allow the calf muscles to be relaxed without additional stretch caused by laying with the knee extended (see Figure 1). Baseline measurements of blood flow were then taken, followed by vibration therapy to the calf area using a Hypervolt percussion massage gun (Hyperice, Irvine, CA, USA) set to a predetermined frequency and time duration. The massage gun was swept smoothly at an even tempo of approximately two seconds (proximal–distal–proximal) over the gastrocnemius and soleus muscles, with no added pressure other than the weight of the device. For the control condition, the massage gun was off (no percussive vibration), but the head of the device was moved over the muscle belly similar to the vibration conditions. Post-therapy blood flow measurements were taken at 13 different time points: immediately after vibration was completed, then once per minute for 5 min, and, finally, another 7 measurements taken every 2 min until 19 min post-vibration. Measurements A GE Logiq S8 with pulse wave doppler ultrasound and a 9L transducer in vascular mode were used to measure the arterial blood flow in the popliteal artery below the knee. This is consistent with previous methods used for measuring arterial blood flow [14,16] and has been shown to be reliable [29]. The outcome measures included heart rate (bpm), mean blood velocity (cm/s), arterial diameter (cm), and volume flow (mL/min). Five cardiac cycles were used to determine the mean velocity and volume flow. All measures other than heart rate were normalized to the baseline value for that specific condition. This allowed for the comparison of conditions within the same subject. All participants completed the study within four weeks of starting. Hypervolt states the frequencies of the gun are 30 Hz at level 1, 40 Hz at level 2, and 53 Hz at level 3. Using an omega HHT41 digital stroboscope (Omega, Stamford, CT, USA), we determined the actual frequencies of the Hypervolt gun were 30 Hz, 38 Hz, and 47 Hz. We also verified that the Hypervolt massage gun head has a measured amplitude of 2.56 cm and weight of 1.14 kg. Statistical Analysis An initial statistical analysis was performed for the arterial diameter, volume flow (VF), and mean velocity (MV). This analysis revealed insignificant changes in the arterial diameter. Similarly, the heart rate measurements showed little change; thus, only MV and VF were used for further statistical analysis. The data for all 26 subjects was averaged at each time point to analyze the average effect of each condition. Using a cell means mixed model to appropriately account for both within-subject and between-subject variability, contrasts were created for a more detailed analysis. The condition effect was analyzed by comparing the pre- and post-vibration values for VF and MV, and the linear and quadratic recovery effects were analyzed. The effect of each condition requires a single test. Therefore, to analyze 8 conditions’ pre- to post-values for both VF and MV requires 16 tests. Multiple tests artificially increase the significance level (α) of the t-tests. Using a significance level (α) of 0.025, the original t-value was ±2.064. To compensate for the α inflation due to 16 tests, Bonferroni correction was used, resulting in a new t-value of ±2.99. Similarly, for the 4 conditions with significant condition effects (38 and 47 Hz at both 5 and 10 min), the linear and quadratic recovery effects were tested for both MV and VF, resulting in another 16-test analysis. The linear and quadratic effects for the 10-min control condition were not analyzed to avoid further alpha inflation and because there was no increase in the blood flow to analyze for return to the baseline. Thus, a t-value with an absolute value greater than 2.99 was used to determine the significance for all the results of the t-tests and to maintain an alpha level of 0.05. ## 3. Results Table 1 shows the t-values of the pre- and post-effects of the vibration, the linear effect, and quadratic effect of recovery for each variable and each condition. These results show that vibrations have a consistent effect pre- and post-vibration for MV and VF. It also clearly reveals that the control and 30 Hz 5-min conditions do not have a statistically significant effect on MV or VF. Interestingly, the control for 10 min only had a significant negative effect for MV, while 30 Hz for 10 min neared significance for both MV and VF. Finally, the t-tests showed that the conditions at 38 Hz and 47 Hz result in a significant increase of MV and VF for both the 5-min and 10-min conditions. Figure 2 and Figure 3 show the MV and VF responses, respectively, for all 8 conditions. Post-vibrations in these figures are represented as time 0 min. Figure 2 and Figure 3 show that MV and VF continue to increase for up to 3 min post-vibration. They also depict the trend that each variable gradually recovers toward its baseline over the remaining measured time periods. The t-tests revealed that there is a significant linear effect for all conditions of both VF and MV. Figure 4 and Figure 5 show the VF data with a linear best fit for the post-vibration data. Finally, the t-tests show that the quadratic recovery effect is not significant for any condition. ## 4. Discussion The objective of this work was to determine if and how much local vibrations, using a massage gun, increase arterial blood flow. The pre-post-analysis of VF and MV show a significant increase that is dependent on frequency and time, with greater blood flow at a higher frequency and longer durations. The VF increase for 38 Hz at 5 min and 10 min was $24\%$ and $32\%$, respectively. The 47 Hz conditions saw VF increases of $31\%$ for 5 min and $47\%$ for 10 min of vibrations. The data clearly show that VF and MV continue to increase for several minutes post-vibration using both 38 Hz and 47 Hz. For the 47 Hz 10-min condition, both VF and MV peaked at 3 min post-vibration, while the 47 Hz 5-min and 38 Hz 10-min conditions peaked at 2 min. Finally, the 38 Hz 5-min condition peaked at 1 min post-vibration. It is reasonable to assume that, with a larger sample size, this delayed effect would be more pronounced. While we only measured post-vibration blood flow for 19 min, Figure 4 and Figure 5 show that the high-frequency and duration conditions result in an elevated blood flow that demonstrates a longer return to baseline. This residual effect is important to consider for either recovery treatments after an activity or the application of pre-activity use in athletes who want their blood flow elevated in a particular muscle group prior to competition. Further observation of the linear return to baseline of each condition provides some interesting insights into the effects of frequency and duration. The effect of duration has a smaller impact than frequency on the slope of the blood flow return to baseline. This is particularly evident when comparing 30 Hz to 38 Hz as compared to 38 Hz vs. 47 Hz. The slope for the linear recovery of VF with 47 Hz for 10 min is −$1.7\%$/min and 47 Hz for 5 min is −$1.6\%$/min. For VF with 38 Hz, the slopes were −$1.6\%$/min and −$1.3\%$/min for 10 min and 5 min, respectively. Thus, the rate of VF recovery for these two frequencies is similar. Finally, for VF with 30 Hz, the slope for 10 min was −$1.1\%$/min and −$0.9\%$/min for 5 min. Therefore, within each frequency, the VF slopes are comparable between the 5-min and 10-min conditions. This also indicates that, as the frequency increases from 30 Hz to 38 Hz, so does the steepness of the slope, suggesting that, as the blood flow becomes more elevated, the blunting or recovery of the blood flow to baseline may occur at a faster rate. Future studies should carry out post-vibration blood flow measures longer to determine how the residual blood flow differs by frequency and time. Variations in the rate of return to the baseline could affect the practical application of localized vibration. These findings of increased blood flow at frequencies above 30 Hz are supported by Maloney-Hinds et al. [ 21], who investigated skin blood flow responses to the forearm. In their study, participants had their arm passively vibrated by resting the forearm on a WBV platform at 30 Hz and 50 Hz for 10 min. The blood flow was measured using a laser Doppler flow meter between each minute of vibration for 10 min and for 15 min post-vibration. Their study found that 30 Hz and 50 Hz vibrations both resulted in significant increases in the blood flow compared to baseline. Although not significant, their data showed responses at 50 Hz were continually higher than 30 Hz. Our data show 30 Hz did not significantly affect VF or MV pre-post-vibration, although 5 and 10 min demonstrated an average pre-post-increase in VF of $0\%$ and $18\%$, respectively. This increase at 30 Hz for 10 min is just below the significant t-value, and we postulate that, with a larger sample size, this may reach significance. Furthermore, the peak increase in VF for 30 Hz was $10\%$ and $38\%$ for 5- and 10-min conditions, respectively. This further supports our finding that longer condition durations, up to 10 min, increases VF. Future studies should observe the effect of even longer durations to determine if there is a duration ceiling. The control condition resulted in decreased VF, as subjects were at rest with very little stimulus, and this became significant at 10 min. This is likely because blood flow decreases in a muscle at rest. The weight of the massage gun exerted a pressure of 0.79 psi while using a flat, round massage head. This likely resulted in minimal tissue deformation and possibly did not exert enough pressure to induce an increase in blood flow responses. Heart rate measurements were collected to verify that any changes in blood flow were due to local vibration stimulation and not excitation of the cardiovascular system. The heart rate was averaged for each subject across the eight conditions. Only 4 out of 26 subjects demonstrated minimal increases of between 1 and 3 bpm, which is within the normal fluctuation range, while 22 subjects maintained or slightly decreased their average heart rate. These data indicate that vibrations of the calf muscles did not increase the heart rate. This is consistent with other studies that applied WBV and measured the blood flow and heart rate [16,18]. Similarly, the popliteal diameter was measured to determine if the vibrations caused arterial dilation. The diameter measurements were also averaged over the eight conditions for each subject, and only five subjects saw changes in the diameter over $2.5\%$ from pre- to post-vibration. These results were insignificant in our initial statistical analysis. This finding is consistent with a study by Kerschan-Schindl et al., where the systolic area of the popliteal artery reportedly was not significantly changed after WBV exercise [18]. Therefore, changes in the heart rate and popliteal diameter do not appear to have affected our results. The exact mechanisms of how vibrations cause increased blood flow are still unclear. The results presented here clearly indicate that local vibrations increase arterial blood flow. It is also evident that local vibrations result in a local increase of flow without raising the heart rate, meaning only local blood flow is being excited. Furthermore, the popliteal artery diameter is not significantly affected by vibrations, which implies the physiological response is more locally induced with mechanical stress. It is possible that the mechanical pressure of the therapeutic condition causes an increase in arterial pressure, which, when released, may increase the blood flow [26]. Furthermore, vibration stimulus may result in muscle contraction [30], which, in turn, causes vasoconstriction and increasing arterial back pressure [31]. It is understood that exercise results in the release of vasodilators and an increase in arterial blood flow [32]. Additionally, it has been shown that exercise with vasodilator blockage results in even higher arterial blood flow [32]. Future works could block hormone receptors with antihistamines and measure the blood flow response to determine if the hormone response is primarily responsible for vibrations increasing the blood flow. The results of this study are limited to healthy university-aged and recreationally active young adults. Any extrapolation of these results to a particular pathology or clinical population such as those with ischemia, diabetes, or musculotendinous injuries requires future investigations to establish efficacy in these populations. Thus, this intervention should not be used as treatment for medical pathological populations until further clinical evidence is provided. While little evidence exists for manual massage-related effects on blood flow and recovery, if increases in the blood flow were a significant factor, a recommendation for light exercise would produce even greater increases in blood flow. However, our results suggest that localized vibration therapy in healthy young active adults can potentially increase blood flow to a particular region or muscle group without the metabolic demands of normal exercise. Those using such devices should note our results are further limited to 5- and 10-min applications, and there is no evidence yet to suggest that increasing the duration will enhance the blood flow effects. For future studies, it is also noteworthy to mention that our study found anecdotal evidence that higher frequencies were often reported to be uncomfortable. ## 5. Conclusions This study demonstrates that, for healthy university-aged adults, localized percussion vibration using a massage gun increases VF and MV and that higher frequencies and longer durations of vibrations lead to greater increases in both. The data also revealed there is a time delay between the end of the vibration condition and the peak increase in VF and MV. This delay becomes longer with increasing the frequency and duration. Furthermore, we found a strong linear return to the baseline effect with similar VF rates for 38 Hz and 47 Hz and a lower rate for 30 Hz. We also concluded, increases seen in popliteal artery blood flow were not influenced by the heart rate and popliteal diameter. Future research is needed to determine the relationship between frequency and duration effects on blood flow when using massage guns. 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--- title: Differences in metabonomic profiles of abdominal subcutaneous adipose tissue in women with polycystic ovary syndrome authors: - Fangfang Di - Danfeng Gao - Lihua Yao - Runjie Zhang - Jin Qiu - Liwen Song journal: Frontiers in Endocrinology year: 2023 pmcid: PMC10003901 doi: 10.3389/fendo.2023.1077604 license: CC BY 4.0 --- # Differences in metabonomic profiles of abdominal subcutaneous adipose tissue in women with polycystic ovary syndrome ## Abstract ### Introduction Polycystic ovary syndrome (PCOS) is a complex endocrine disorder that often coexists with a metabolic disorder. Studies have demonstrated that the malfunction of adipose tissue, particularly abdominal adipose tissue, could exacerbate reproductive and metabolic problems in PCOS patients. Adipose tissue-secreted signaling mediators (e.g., lipids and metabolites) would then interact with other body organs, including the ovary, to maintain the systemic equilibrium. ### Methods In this study, we examined adipose samples from PCOS patients and unaffected individuals using a liquid chromatography–mass spectrometry-based metabonomics approach (LC–MS/MS). PCOS biomarkers were selected using multivariate statistical analysis. ### Results Our pathway analysis revealed that these differential metabolites could be engaged in inflammatory diseases and mitochondrial beta-oxidation. We further developed an in vitro PCOS cell model to examine the effects of hyperandrogenism on granulosa cells and related metabolic disorders. We noted that isoleucine recovered the promotive effect on cell apoptosis, inhibitory effect on cell proliferation, sex hormone secretion, and mitochondrial function induced by dehydroepiandrosterone. Our gas chromatography–mass spectrometry targeted analysis (GC–MS/MS) revealed that isoleucine was significantly decreased in PCOS patients. ### Discussion Based on these results, we speculate that metabolome alterations are vital in ameliorating PCOS symptoms. This may be a novel therapeutic target for PCOS treatment. Our study provides preliminary evidence that these findings will enhance our ability to accurately diagnose and intervene in PCOS. ## PRÉCIS Isoleucine demonstrated a high PCOS diagnostic ability and recovered promotive effect on cell apoptosis, inhibitory effect on cell proliferation, sex hormone secretion, and mitochondrial function induced by dehydroepiandrosterone in granulosa cells. ## Introduction Polycystic ovary syndrome (PCOS) is a complex endocrinopathy in women, affecting approximately $6\%$ to $21\%$ of women of reproductive age (1–3). It has been extensively investigated as it is considered the most prevalent form of ovarian disorder. PCOS has been identified as a multisystem disease and is no longer regarded merely as a disease of ovary. In addition to having a wide range of symptoms and indicators that make categorizing the illness challenging, patients with PCOS are also linked to a number of other conditions, such as menstrual irregularities and metabolic changes [4]. Therefore, the etiology of PCOS is not fully understood. Currently, suppressive or maintenance treatment including metformin, hormonal contraceptives, and orlistat are the first-line treatment for PCOS [5, 6]. The efficacy of these treatments has been limited by low sustainability and adherence. Therefore, it is necessary to search for new replacements to provide ideal treatment options for PCOS patients. Adiposity is one of the main symptoms of PCOS and is believed to be the main cause of increased metabolic risk [7]. Adipose tissue (AT) has significant endocrine and metabolic functions as is known as an organ for storing fat [8]. Extensive research has been done on the functions of subcutaneous AT in PCOS women [9, 10]. Beyond proteins, adipocytokines—which are released by AT—also involve lipids, extracellular vesicles, metabolites, and noncoding RNAs in the process whereby AT communicates with other body organs [11]. Particularly, mounting evidence indicates that adiponectin, an adipocytokine, has a critical role in female reproductive organs, where it promotes IGF-I-induced steroidogenesis in granulosa cells [12]. Although these adipose tissue secretions are essential to PCOS, a thorough explanation of the potential mechanisms is required. Therefore, identifying the adipokines, including metabolites secreted by AT and the characterization of their effects on PCOS, is of utmost importance. It is necessary to identify prospective biomarkers by adopting non-invasive methods and precise techniques to gain a better understanding of the pathomechanisms of PCOS. Metabonomics, a recently developed technology, describes dynamic changes and provides information for the discovery of active drivers on the metabolites present in physiological or pathological systems [13]. It has been widely applied in the diagnosis of a variety of disorders [14]. Recently, a research group analyzed several metabolomic studies concerning PCOS-affected women and contrasted them with data from healthy controls [15, 16]. Certain metabolites, such as fatty acids [17] and amino acids [10], have been recognized as biomarkers for the diagnosis of PCOS. It is possible to trace miniscule biochemical alterations in this endocrinopathy by employing metabonomics to investigate the pathophysiology of PCOS, which may aid in the diagnosis of the disorder. Uncertainty surrounds the function of the active metabolites released by AT in PCOS. To offer fresh perspectives on the part AT plays in the pathophysiology of PCOS, we conducted non-targeted metabonomics using biopsies obtained during surgery in women with or without PCOS. In contrast to conventional molecular genetic approaches, our current experimental methodology offers the theoretical benefit of a hypothesis-free technique to identify the dysregulated metabolites in AT of PCOS patients. In addition, we investigated the protective effect of metabolites on proliferation, apoptosis, and mitochondrial function in dehydroepiandrosterone (DHEA)-induced PCOS cell models. Our findings made clear the function of released metabolites related with AT in PCOS. The results of the present research offer a novel perspective on the potential therapeutic benefits and molecular activities in PCOS. ## Recruitment of patients A total of 16 women were enrolled in this study. Eight women suffered from PCOS, while the remaining eight were normal control (NC) women. The subjects’ average age and BMI were statistically identical (Table 1). The study was approved by the ethics committee of Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine. All patients provided informed consent. The *Rotterdam criteria* [18], which include polycystic ovaries, oligo- or anovulation, clinical and/or hyperandrogenism, and exclusion of other causes of hyperandrogenism like androgen-secreting tumors, non-classical congenital adrenal hyperplasia, hyperprolactinemia, and Cushing’s syndrome, were used to diagnose PCOS. When two or more of the three requirements were met, the diagnosis was deemed accurate. The women in the non-PCOS group had regular menstrual cycles every 26–34 days with no signs of hyperandrogenism. Additionally, none of the study participants had used any medications known to impact metabolic or hormonal characteristics within the 3 months prior to the study. **Table 1** | Unnamed: 0 | Control (n = 8) | PCOS (n = 8) | | --- | --- | --- | | Age (years) | 29.75 ± 3.37 | 28.6 ± 2.97 | | BMI (kg/m2) | 20.53 ± 2.71 | 21.14 ± 4.48 | | Basal FSH (IU/L) | 5.67 ± 2.23 | 6.58 ± 1.62 | | Basal LH (IU/L) | 6.79 ± 2.56 | 14.28 ± 4.32* | | Basal T0 (nmol/mL) | 1.64 ± 0.38 | 3.04 ± 1.05* | ## Sample preparation Subcutaneous fat of the abdomen (PCOS, 5; NC, 8) was sampled from women with tubal factor infertility using laparoscopy. Three patients dropped out of the trial. When performing the laparoscopy, all patients were fasting, and the surgeon removed 3–4 g of subcutaneous fat. Biopsies were immediately rinsed in cooled NaCl $0.9\%$ solution, segmented, and snap-frozen as previously reported [9, 18]. Until analysis, samples were kept frozen in liquid nitrogen (196°C). Around 20 mg of subcutaneous fat of the abdomen was added to 500 μl methanol solution (containing 5 μg/ml L-2-chlorophenylalanine as internal standard) and homogenized for 2 min. The supernatant was centrifuged at 13,000 rpm at 4°C for 10 min, and 200 μl was obtained. The same volume of serum was extracted from all samples and mixed evenly to prepare QC (quality control) samples. ## LC–MS/MS analysis The UHPLC system was coupled to Orbitrap/MS (Waters Corp., Milford, MA, USA), equipped with an electrospray ionization source, and operated in positive or negative ionization modes with a mass resolution of 70,000 and an m/z of 200. Using data correlation (dd-MS2, TopN = 10) MS/MS mode, the full-scan quality resolution was 17,500 when m/z was 200, and the scanning range was 100–1,500. The chromatographic conditions were as follows: sample size was 2 μl, column temperature was 25°C, flow rate was 0.35 ml/min, and mobile phases were $0.1\%$ formic acid aqueous solution and $0.1\%$ acetonitrile formic acid solution. The optimized chromatographic gradient was as follows: 0–2 min, $5\%$ in liquid B; 2–10 min, $5\%$–$95\%$ in liquid B; 10–15 min, $95\%$ in liquid B; 15–18 min, $5\%$ in liquid B. Data were obtained in centroid mode using Thermo Excalibur 2.2 software from Thermo Fisher Scientific, Massachusetts, USA. ## GC–MS/MS analysis Serum sample collection was referred to Yan et al. [ 19]. Shanghai Lu-Ming Biotech Company Limited (Shanghai, China) provided an experimental platform and assistance for the targeting amino acid metabolomics analysis. Briefly, a mixture of methanol/water (4:1 by volume) was used to collect 2 × 107 per sample. The sample was quickly stored in liquid nitrogen. Before testing on the machine, the sample was equilibrated to ambient temperature for 30 min. The sample was dispersed using the ultrasonic lysis method. It was then concentrated and centrifuged and then freeze-dried. Finally, a mixture of BSTFA and n-hexane (4:1 by volume) was added to the sample, vortexed vigorously for 2 min, and derivatized at 70°C for 60 min. These samples were analyzed by a gas chromatography system (Thermo Fisher Scientific TSQ 9000, USA). UPLC–ESI–MS/MS was utilized as the analytical method for the quantitative detection of targeted amino acid metabolites. ## Cell line culture A steroid-derived human granulosa-like tumor cell line (KGN cell line) was selected for this study because it retains the physiological properties of ovarian granulosa cells [20]. In the DMEM/F-12 medium including $10\%$ fetal bovine serum (FBS, Gibco), KGN cells were grown in a humid atmosphere at 37°C and $5\%$ CO2. The concentrations of metabolites used are listed in the legend. DHEA was added to the medium 4 h prior to metabolite treatment. ## Proliferation assays The effects of metabolites were assessed using the Cell Counting Kit-8 assay (CCK-8, Beyotime, China). KGN cells were reseeded in 96-well plates at 5,000 cells/well. Each well received 10 l of CCK-8 reagent. Cells were then incubated for 1 h at 37°C. Absorbance was measured at a wavelength of 450 nm using a microplate reader (Thermo Fisher Scientific, USA). Cells were assessed at 0, 24, and 48 h. ## Apoptosis analysis A flow cytometry study of the Annexin V-fluorescein isothiocyanate (FITC) against propidium iodide (PI) assay was used to identify apoptosis (BD Pharmingen, CA, USA). A total of 3 × 105 KGN cells were reseeded in each well of six-well plates. Cells were trypsinized, washed twice with cold phosphate-buffered saline for 15 min at room temperature, and used to incubate cells with 5 µl of Annexin v-FITC and 5 µl of PI each well. ## Measurement of hormones Serum samples extracted from KGN culture supernatants were tested in duplicate using testosterone (T0), estrogen (E2), and progesterone (P4) ELISA kits (CUSABIO, China) in accordance with the directions provided by the manufacturer. ## Measurement of ATP contents Using the appropriate kits, adenosine triphosphate (ATP) concentrations were assessed following the extraction and quantification of proteins from KGN (Beyotime, China). ## Statistical analysis Data were obtained using the Thermo Xcalibur 2.2 software (Thermo Scientific, SAN Jose, USA). Peak calibration and extraction were performed using the Compound Discovery Software (Thermo Fisher Scientific). Data tables were imported into Simca-P 13.0 for multivariate statistical analysis. Unsupervised principal component analysis (PCA) was used to assess the overall trend of separation between these samples. Differential metabolites were screened using partial least square, discrimination analysis (PLSDA). According to the PLSDA model, variables whose importance was greater than 1.0 in the projection (VIP) value were selected, and SPSS Statistics 18.0.0 was used for the two-tailed Student’s t test, and a p-value < 0.05 was considered statistically significant. Multiple test adjustments were made using Bonferroni correction. To identify these potential biomarkers, the accurate ion mass was entered into the Human Metabolome Database (HMDB), Metlin, MoNA, and MassBank databases to match accurate molecular weight and automatically search for MS1/MS2 fragment ions. Finally, to determine the structure of the compound, we used our internal standard metabolite library, matching the exact mass, fragment ion mass, and retention time. Furthermore, metabolic pathway enrichment analysis was performed using the KEGG database (https://www.metaboanalyst.ca/). The area under the receiver operating characteristic (ROC) curve, i.e., AUC, was used to evaluate the diagnostic ability of biomarkers. The metabolite interaction network analysis was conducted using the IPA online database. ## Identification and screening of differentially expressed metabolites Patients’ AT was drawn for metabonomics analysis to examine the metabolic profiles of the NC and PCOS groups. The findings of the PCA for the NC and PCOS groups (Figures 1A, B) revealed a pattern of aggregation within groups and segregation between groups. The plots of the PCOS group were very different from those of the NC group, according to the PLS-DA model, which revealed significant metabolite differences between the two groups (Figures 1C, D). Additionally, a continuing analysis of the PLS-DA model was carried out (Figures 1E, F). In the PCOS group, a total of 107 distinct metabolites were found (VIP >1, $p \leq 0.05$). **Figure 1:** *Identified metabolic profile in NC and PCOS. (A, B) PCA revealed a distinct metabolic profile in the PCOS group compared with the NC group. The X-axis and Y-axis represent the first and second principal components, respectively. (C, D) Statistical validation with perripening analysis of the corresponding OPLS–DA model of the NC and PCOS groups. (E, F) Perripening tests were obtained from LC–MS data of the NC and PCOS groups. The intercept values of the regression line and the Y-axis are R2 and Q2.* ## Enrichment analysis on differential metabolites Figure 2A illustrates the results as a volcano plot of all metabolites. Red and green colors were used to represent elevated and decreased metabolites, respectively. Figure 2B depicts a heat map of the various metabolites identified by LC–MS. The differential metabolites could be loosely divided into various super-classes as per the enriched metabolite set clustering analysis (Figure 2C), such as organic acids, fatty acyls, nucleic acids, and main classes such as amino acids and peptides (Figure 2D). The biomarker pathway enrichment analysis used the KEGG and MetaboAnalyst databases. According to Figures 2E, F, these differential metabolites were mainly enriched in inflammatory diseases, beta-oxidation, mitochondrial beta-oxidation, etc. It is well known that PCOS is an inflammatory, systemic, lifestyle endocrinopathy [21]. The mitochondrion is a vital organelle that regulates energy production necessary for cellular survival, and mitochondrial malfunction has been implicated as a possible pathogenesis-inducing factor for PCOS, according to a previous study (22–24). Consequently, the experiments confirmed that the altered metabolites might play important functions in PCOS. **Figure 2:** *Differentially expressed metabolites in PCOS. (A) The volcano map of all metabolites expressed in NC and PCOS groups. (B) Hierarchical clustering analysis was used to assess significantly regulated metabolites between NC and PCOS groups. Increased and decreased metabolites are depicted by red and blue, respectively. (C) Super chemical class metabolite sets of the differential metabolites. (D) Main chemical class metabolite sets of the differential metabolites. (E) Enriched diseases clustering analysis. (F) Enriched metabolic pathway clustering analysis.* ## The possible function of metabolites Research has shown that granulosa cell death may be the fundamental cause of follicular atresia. Granulosa cell proliferation and apoptosis determine the fate of a follicle [25]. The levels of plasma amino acids in PCOS women have been demonstrated to be significantly out of balance [26], given that L-tyrosine and L-leucine may recover regular menstrual cycle and ovulation in PCOS [27]. Hence, we chose amino acids such as DL-tryptophan, L-lysine, L-histidine, L-tyrosine, L-phenylalanine, and isoleucine as candidate metabolites to explore their potential biological roles. The ROC analysis uncovered that DL-tryptophan, L-lysine, L-histidine, L-tyrosine, L-phenylalanine, and isoleucine demonstrated a strong capacity for PCOS diagnosis, with AUC values of 0.900, 0.825, 0.900, 0.850, 0.925, and 0.925, respectively (Figures 3A–F). This suggested that the amino acids may assist in making a clinical diagnosis. Further studies need to be conducted to confirm the functions of the amino acids. The primary mechanism of follicular atresia in PCOS was found to be increase in granulosa cell apoptosis [28]. Cell viability assay (Figures 4A–F) was performed, which revealed that L-phenylalanine and isoleucine could significantly promote the proliferation of cells in cultured KGN (Figures 4E, F), and the two amino acids were chosen for an in-depth study. **Figure 3:** *ROC analysis of representative differentially expressed metabolites. The AUC of (A) DL-tryptophan, (B) L-lysine, (C) L-histidine, (D) L-tyrosine, (E) L-phenylalanine, and (F) isoleucine.* **Figure 4:** *The growth function of representative metabolites in granulosa cells. (A–F) CCK-8 assays were used to detect cell viability of KGN cells at different times using the same concentration of metabolites (10, 20, 50, or 100 μM). (G). Relative cell growth after treatment with DHEA (10−4 M) and L-phenylalanine (20 μM) was detected by the CCK-8 assay. (H). Relative cell growth after treatment with DHEA (10−4 M) and isoleucine (20 μM) was detected by the CCK-8 assay. *p < 0.05, ****p < 0.0001.* ## The effect of L-phenylalanine and isoleucine on KGN cell proliferation and apoptosis in the DHEA cell model KGN cells were pretreated with DHEA to imitate the pathophysiological state of PCOS and simulate the hyperandrogenic milieu in order to further investigate the physiological roles of the two amino acids [29]. L-Phenylalanine (Figure 4G) and isoleucine (Figure 4H) significantly reversed the growth inhibition of DHEA-treated KGN cells. To delve deeper into this finding, apoptosis of KGN cells was discovered using flow cytometry. Isoleucine significantly recovered the apoptosis of DHEA-treated KGN cells but not in the L-phenylalanine group (Figure 5). **Figure 5:** *Analysis of the cell apoptosis of KGN cells transfected with DHEA (10−4 M) and isoleucine (20 μM) or L-phenylalanine (20 μM). The early and late apoptosis rates of KGN cells were compared using PI and FITC. ***p < 0.001; ns, non-significant.* ## Isoleucine protected mitochondrial functions and sexual hormone disturbances of KGN after exposure to DHEA A creative pathway analysis was performed on various metabolites (IPA), which identified numerous linked signaling pathways, including the ones that have been shown to be closely related to PCOS such as pathways related to mitochondrial dysfunction, ROS, PI3K/AKT, MAPK, and Wnt signaling (Figure 6A). The mitochondrion is a crucial organelle that controls energy production required for cellular survival. According to earlier reports [22], PCOS pathogenesis could be exacerbated by mitochondrial dysfunction [23, 24]. After DHEA treatment, mitochondrial function indicator ATP level decreased markedly (Figure 6B), indicating the possibility of mitochondrial malfunction. Isoleucine replenishment reduced the DHEA-induced mitochondrial dysfunction (Figure 6B). Additionally, ELISA was used to measure the T0, E2, and P4 in each group. Compared with the control group, the DHEA group had higher T0, E2, and P4 concentrations. However, compared with the DHEA group, the levels of T0 and P4 but not E2 were suppressed in the DHEA+ isoleucine group (Figures 6C–E). Consistently, we deduced that DHEA could lead to mitochondrial dysfunction and sexual hormone disturbances in granulosa cells, which were ameliorated by isoleucine treatment. To further clarify the role of isoleucine in PCOS, we detected the levels of intracellular amino acids by GC–MS/MS-targeted amino acid metabolism analysis. Notably, the reduced level of isoleucine could be significantly detected in PCOS (Figure 7A). Taken together, these results indicated that isoleucine was the potential target for PCOS treatment. **Figure 6:** *The possible mechanism of isoleucine in granulosa cells. (A) Network and function analysis of differential metabolites using the IPA database. The yellow nodes represent the upregulated metabolites. The blue nodes represent the downregulated metabolites. CP represents the signaling pathway related to the changed metabolites. (B) Relative ATP level of KGN cells transfected with DHEA (10−4 M) and isoleucine (20 μM). Cell serum was collected for ELISA analysis of (C) T0, (D) P4, and (E) E2. *p < 0.05, **p < 0.01, ****p < 0.0001.* **Figure 7:** *GC–MS/MS-targeted amino acid metabolism analysis. (A) Histogram showing the concentration of isoleucine in the NC group and PCOS group. *p < 0.05.* ## Discussion The primary defect in PCOS appears to be an exaggerated androgen secretion by ovarian theca cells [30] and possibly by the adrenals, upon which several factors act, triggering the development of the PCOS phenotype. Among these factors, abdominal adiposity and/or obesity play a major role in many PCOS patients, in part because of the induction of insulin resistance and hyperinsulinemia. Furthermore, hyperinsulinemia facilitates androgen secretion in the ovaries and adrenals [31]. Abdominal AT has been identified as a better marker of metabolic health than body weight [32], and mouse models of PCOS suggest that AT plays a crucial role in the development of PCOS [33]. Most metabonomic studies comparing PCOS and normal control subjects have focused on analyses of plasma/serum or follicular fluid [34]. Secretion of metabolites from brown adipose tissue (BAT) has recently been studied by our research group in an untargeted manner [25]. We were interested in analyzing active metabolites in subcutaneous AT that may influence the PCOS phenotype. Possible reasons include the following: $60\%$ of PCOS-afflicted women are overweight or obese [7], and the bulk of these patients are classified as having abdominal obesity. A recent prevailing view has proven that hyperandrogenism favors accumulation of abdominal fat, thereby promoting insulin resistance (35–37), both of which are diagnostic indicators of PCOS. Thus, the AT is more relevant with PCOS. AT has been employed in prior research on the alteration of gene and protein expressions in PCOS [10, 31, 38]. To date, few studies have focused on the metabolic function of AT in paracrine. Thus, we employed the abdominal AT to investigate the connection of released metabolites and PCOS. Our study is an untargeted metabonomic study based on LC–MS. Altogether, 107 distinct metabolites were enriched. We discovered through pathway analysis that the different metabolites were mostly prevalent in the processes of beta-oxidation and mitochondrial beta-oxidation, among others, which are strongly related to PCOS (Figures 3E, F). Consequently, we verified that the distinct metabolites may have significant roles in PCOS. The main classes of differential metabolites include amino acids and peptides. According to prior research, considerable deviation in the plasma levels of amino acids was found in patients with PCOS [26]. Furthermore, L-tyrosine and L-leucine have been shown to restore a regular menstrual cycle and ovulation in PCOS rat models [27]. Hence, amino acids such as DL-tryptophan, L-lysine, L-histidine, L-tyrosine, L-phenylalanine, and isoleucine were chosen as prospective candidate metabolites to investigate their biological roles. The ROC analysis revealed that candidate amino acids showed a high PCOS diagnostic ability. This suggested that the amino acids may have diagnostic capacity in PCOS. Most follicle somatic cells are granulosa cells [39, 40]. Growing evidence suggests that functional alterations largely influence the growth, development, and maturation of follicles in granulosa cells [41, 42]. Studies have extensively screened the differentially expressed genes in the granulosa cells to investigate the regulatory mechanisms governing the development of PCOS, with significant enrichment in pathways associated with metabolism, steroidogenesis, inflammation, cell proliferation, and apoptosis [43]. Excessive apoptosis and delays in the proliferation of granulosa cells can lead to numerous cystic dilated follicles and atretic follicles in the ovarian cortex [44]. The ovaries eventually exhibit polycystic alterations in the absence of mature follicles and corpus luteum development [45]. Therefore, the malfunction of granulosa cells may account for abnormal folliculogenesis seen in PCOS [46]. Herein, we demonstrate that isoleucine has a therapeutic role in the proliferation/apoptosis process, mitochondrial function, and oxidative stress in granulosa cells. Isoleucine, an essential branched-chain amino acid with anomalous content, is directly correlated with the development of PCOS [10, 47, 48]. However, it remains to be ascertained how isoleucine affects PCOS. Our GC–MS/MS-targeted analysis revealed that isoleucine was significantly decreased in PCOS, suggesting that isoleucine was the potential target for PCOS treatment. Furthermore, we tested hormone levels in cell culture supernatant. Important steroid hormones including P4 and T0 are produced by granulosa cells in developing follicles. They aid in the formation of ovarian follicles; however, an excess of androgen causes the granulosa cells to undergo autophagy and death, which negatively impacts ovarian function [49]. Additionally, low levels of P4 can extend the life of dominant follicles [50], whereas high levels of P4 may eventually lead to dominant follicle atresia [43]. This study shows that in comparison with the DHEA group, the levels of T0 and P4 were significantly decreased by the addition of isoleucine. These results indicated that isoleucine may participate in regulating the production of hormones. When interpreting our findings, it is crucial to consider the limitations of our research. Samples of AT are difficult to obtain. Therefore, this study’s limitation was its limited sample size. Also, the need for more research in the relationship of high androgen and isoleucine is required. We hypothesized that isoleucine might regulate granulosa cell activity, including cell proliferation/apoptosis, sex hormone secretion, and mitochondrial malfunction of ovarian granulosa cells in PCOS induced by DHEA. Our study provides evidence that isoleucine is a promising candidate for PCOS therapy. However, more in vivo and in vitro investigations are required to learn more about the precise mechanism. ## Data availability statement The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors. ## Ethics statement The studies involving human participants were reviewed and approved by Shanghai Tongren Hospital, Shanghai Jiao Tong University School of Medicine. The patients/participants provided their written informed consent to participate in this study. ## Author contributions FD and LS designed the research. FD, LY, and DG performed the experiments. FD, JQ, and RZ analyzed the data. FD, RZ, and LS wrote the article. All authors contributed to manuscript revision, read, and approved the submitted version. ## Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. ## Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. ## References 1. Balen AH, Morley LC, Misso M, Franks S, Legro RS, Wijeyaratne CN. **The management of anovulatory infertility in women with polycystic ovary syndrome: An analysis of the evidence to support the development of global who guidance**. *Hum Reprod Update* (2016) **22** 687-708. DOI: 10.1093/humupd/dmw025 2. 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--- title: Are Patients with Axial Spondyloarthritis Who Were Breastfed Protected against the Development of Severe Disease? authors: - Sara Alonso - Ignacio Braña - Estefanía Pardo - Stefanie Burger - Pablo González del Pozo - Mercedes Alperi - Rubén Queiro journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003909 doi: 10.3390/jcm12051863 license: CC BY 4.0 --- # Are Patients with Axial Spondyloarthritis Who Were Breastfed Protected against the Development of Severe Disease? ## Abstract Background and aims: *Breastfeeding is* recognized as one of the most influential drivers of the gut microbiome. In turn, alterations in the gut microbiome may play a role in the development and severity of spondyloarthritis (SpA). We aimed to analyze different disease outcomes in patients with axial SpA (axSpA) based on the history of breastfeeding. Patients and methods: A random sample was selected from a large database of axSpA patients. Patients were divided based on history of breastfeeding and several disease outcomes were compared. Both groups were also compared based on disease severity. Adjusted linear and logistic regression statistical methods were used. Results: The study included 105 patients (46 women and 59 men), and the median age was 45 years (IQR: 16–72), and the mean age at diagnosis was 34.3 ± 10.9 years. Sixty-one patients ($58.1\%$) were breastfed, with a median duration of 4 (IQR: 1–24) months. After the fully adjusted model, BASDAI [−1.13 ($95\%$CI: −2.04, −0.23), $$p \leq 0.015$$] and ASDAS [−0.38 ($95\%$CI: −0.72, −0.04), $$p \leq 0.030$$] scores were significantly lower in breastfed patients. Forty-two percent had severe disease. In the adjusted logistic model for age, sex, disease duration, family history, HLA-B27, biologic therapy, smoking, and obesity, breastfeeding had a protective effect against the development of severe disease (OR 0.22, $95\%$CI: 0.08–0.57, $$p \leq 0.003$$). The selected sample size was sufficient to detect this difference with a statistical power of $87\%$ and a confidence level of $95\%$. Conclusion: Breastfeeding might exert a protective effect against severe disease in patients with axSpA. These data need further confirmation. ## 1. Introduction The spondyloarthritis (SpA) concept includes a group of entities with their own clinical-radiological characteristics and a genetic link through HLA-B27. Currently, this nosology family includes entities with inflammatory symptoms and signs that predominate in the axial skeleton, such as radiographic (also known as ankylosing spondylitis -AS-) and non-radiographic axial SpA (axSpA), as well as predominantly peripheral forms such as psoriatic arthritis, among others [1]. The pathogenesis of these entities is only partially known, and although the best-known element of genetic predisposition is HLA-B27, not all patients with SpA express this genetic biomarker [1]. The imbalance between the different species of bacteria, viruses and fungi that colonize the human intestine, a process called gut dysbiosis, seems to be at the origin of these conditions. Emerging evidence suggests that subclinical gut inflammation in patients with SpA, apparently driven by intestinal dysbiosis, is not the consequence of the systemic inflammatory process but rather an important pathophysiological event actively participating in the origin of the disease [2]. This breakdown of intestinal homeostasis is not only a key early step in the development of SpA, but is also associated with the degree of activity and severity of it [3]. Additionally, both the genetic background (HLA-B27) and the level of disease activity are likely to influence the composition of the gut microbiota of patients with SpA [4]. The potential of a hindering effect of NSAIDs on the achievement of treatment objectives in axSpA has also recently been hypothesized through a negative effect of these drugs on the intestinal microbiota of these patients [5]. The establishment of the gut microbiome during early life is a complex process with lasting implications for an individual’s health. Breastfeeding is recognized as one of the most influential drivers of gut microbiome composition during infancy, an effect on the health of individuals that may extend into the advanced stages of life. Differences in gut microbial communities between breast-fed and formula-fed infants have been consistently observed, and are hypothesized to partially mediate the relationships between breastfeeding and the decreased risk for numerous communicable and noncommunicable diseases in early life [6]. Thus, for example, among children with juvenile idiopathic arthritis (JIA), those breastfed for more than 6 months tend to show fewer joint deformities, less disease activity and better physical function [7]. Furthermore, breastfeeding could have potential preventive effects on the development of certain rheumatic diseases during adulthood. Indeed, one study reported that patients with AS had been breastfed less often than healthy controls. In families where children were breastfed, the patients with AS were less often breastfed than their healthy siblings. In addition, breastfeeding reduced the familial prevalence of AS. Therefore, a breastfeeding-induced protective effect on the occurrence of AS has been suggested [8]. Recently, breastfeeding has also been advocated to have a potential modifiable effect in reducing the risk of rheumatoid arthritis (RA) [9]. Despite this information, very little is known about the role of breastfeeding on disease outcomes in certain rheumatic conditions such as axSpA. In this study, we addressed the potential role of breastfeeding on various clinical outcomes in patients with axSpA. We also investigated whether having received breastfeeding could influence the severity of the disease. ## 2. Patients and Methods This was a retrospective longitudinal study of outpatients with axSpA fulfilling the ASAS criteria [10]. These patients were treated regularly and according to a standard follow-up protocol in a unit specifically dedicated to axSpA of a rheumatology service of a tertiary care hospital. The patients were informed of the purpose of the study and gave their informed consent to carry it out. The ethical standards of good clinical practice contained in the Declaration of Helsinki were followed at all times. Patients seen for the first time in this unit signed an informed consent that authorizes researchers to use the clinical, analytical and radiographic information collected during follow-up so that it can be used for future research purposes. The anonymity of the patients has been safeguarded at all times. The research protocol was reviewed by a clinical research ethics committee (CEIcPA-ref$\frac{2020}{22}$). *The* generic information collected refers to socio-demographic aspects, lifestyles, and previous medical history. Regarding axSpA, the following are collected: age at onset, symptom duration, family history of disease, comorbid factors (psychological dysfunction, osteoporosis, metabolic syndrome), axial and peripheral clinical manifestations, number of painful joints, number of inflamed joints, enthesitis, dactylitis, extra-articular manifestations (uveitis, psoriasis, inflammatory bowel disease), disease activity according to the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and the Ankylosing Spondylitis Disease Activity Score (ASDAS), physical function according to the Bath Ankylosing Spondylitis Functional Index (BASFI), structural damage (sacroiliitis, syndesmophytes, vertebral squaring), and the general disease impact according to the Assessment of SpondyloArthritis international Society-Health Index (ASAS HI) questionnaire. We have previously contrasted the validity and feasibility of these measures under routine clinical conditions [11,12]. Current and past medication in relation to SpA (non-steroidal anti-inflammatory drugs (NSAIDs), conventional disease-modifying antirheumatic drugs (DMARDs), biologic and targeted-specific DMARDs), and the pertinent analytical parameters (HLA-B27, rheumatoid factor (RF), antinuclear antibodies (ANA), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP)) are also collected. These patients are seen every 3 months when they start systemic therapy or when they have poor symptom control, or every 6 months when they progress satisfactorily, reaching treatment goals (ASDAS remission or low activity). The baseline and follow-up protocol were the same for all patients. The work procedures of this SpA unit are regularly audited and currently have the advanced quality seal awarded by the Spanish Society for Healthcare Quality. For the purposes of this study, patients were asked about their history of breastfeeding (whether or not they received it, and if so for approximately how long). Information on breastfeeding was only cross-checked with the patients’ mothers when the patients were uncertain how long they had been breastfeeding or whether they had received it. In this case, the patients were asked to cross-reference the requested information with their mothers. This part of the study was included in the information sent to the ethics committee for approval. Only patients with reliable information in this regard were included. This implied that if the patients could not provide this information with certainty because they did not remember and it was impossible to cross-reference this information with their mothers, they were not included in the study. Although this implies a certain inclusion bias, this only happened in five cases. The information to carry out this study was collected between 1 February and 30 June 2022. Furthermore, for the purposes of the study, a random sample of patients was chosen from the database of this monographic unit, selecting one out of every three consecutive patients from this database. ## 3. Statistical Analysis A descriptive statistical study of all the variables was made, using central and dispersion measures for the quantitative variables, as well as absolute and relative frequencies for the qualitative ones. The use of central tendency measures (mean or median) and their dispersion values was made based on the normality (or not) in the distribution of the data. Categorical variables were compared with a Fisher’s exact test and continuous variables with a Mann-Whitney U test, except for age at diagnosis, which followed a normal distribution and was compared with a Student’s t-test. To estimate the crude and adjusted effect of breastfeeding on disease outcomes, linear regressions were used, as when the outcome was a quantitative variable, or logistic in the case of categorical ones. To assess whether the age of onset of the disease was influenced by breastfeeding, the Welch two sample t-test was used. A Wilcoxon rank sum test with continuity correction was used to assess the crude effect of breastfeeding and its duration on the different disease outcomes (BASDAI, ASDAS, ASAS HI, structural damage). To estimate the potential independent effect of breastfeeding on the outcomes analyzed, a multiple linear regression adjusted for age, sex, disease duration, family history of SpA, HLA-B27, biological treatment, smoking, and obesity was performed. In addition, the crude and adjusted effect of breastfeeding on the severity of the disease was analyzed. For the purposes of this study, severe disease was defined as the combined outcome of BASDAI > 4 and/or ASDAS > 2.1 + BASFI > 4 + ASAS HI > 5, maintained for at least 6 months each year, during follow-up. Regarding the sample size, the number of randomly selected study subjects was sufficient to detect significant differences of two independent proportions (severe vs. non-severe disease), based on the history of breastfeeding, with a statistical power of $87\%$ and a confidence level of $95\%$. Statistical analyses were performed with R software version 4.0.2. ## 4. Results The study included 105 randomly selected patients from a larger database of axSpA, 46 women and 59 men, with a median age of 45 (IQR: 16–72) years, and a mean age at diagnosis of 34.3 ± 10.9 years. Sixty-one patients ($58.1\%$) had a history of breastfeeding, with a median duration of 4 (IQR: 1–24) months. Most patients presented radiographic axSpA (n: 63, $60\%$). Seventy-eight patients ($74.3\%$) were HLA-B27 positive. Fifty-nine percent of the patients were receiving biological therapies (mostly anti-TNFα) at the time of being included in the study. Most patients were reasonably well controlled with a median ASDAS score of 1.90 (IQR: 0–4.70). Table 1 shows the main characteristics of the study population, both overall and divided according to the history of breastfeeding. Having received breastfeeding did not influence the age of onset of the disease ($$p \leq 0.69$$). In the crude estimate, the history of breastfeeding was associated with lower BASDAI [−1.35 ($95\%$CI: −2.30, −0.40), $$p \leq 0.006$$], BASFI [−0.85 ($95\%$CI: −1.79, 0.10), $$p \leq 0.08$$], ASDAS [−0.47 ($95\%$CI: −0.82, −0.13), $$p \leq 0.008$$], and ASAS HI [−2.01 ($95\%$CI: −3.63, −0.38), $$p \leq 0.02$$] scores. After the fully adjusted model, BASDAI [−1.13 ($95\%$CI: −2.04, −0.23), $$p \leq 0.015$$] and ASDAS [−0.38 ($95\%$CI: −0.72, −0.04), $$p \leq 0.030$$] scores remained significantly lower in breastfed patients. After these adjusted models, there was a trend towards lower ASAS HI values [−1.43 ($95\%$CI: −2.98, 0,11), $$p \leq 0.07$$], but just bordering statistical significance. However, the duration of breastfeeding did not influence the above outcomes. There was no relationship between structural damage and breastfeeding. In fact, in the multivariate logistic regression model, the only factors associated with greater structural damage were disease duration [OR 1.10, $95\%$CI: 1.04–1.17, $$p \leq 0.003$$] and smoking [OR 4.23, $95\%$CI: 1.43–13.53, $$p \leq 0.011$$]. Of the 44 patients classified as severe disease, 26 had not been breastfed, while the rest had been (crude OR 0.30, $95\%$CI: 0.13–0.66, $$p \leq 0.004$$). In the adjusted logistic model for age, sex, disease duration, family history, HLA-B27, biologic therapy, smoking, and obesity, breastfeeding maintained a protective effect against the development of severe disease (OR 0.22, $95\%$CI: 0.08–0.57, $$p \leq 0.003$$). The other factors with an independent effect on severe disease were found to be male sex (OR 0.30, $95\%$CI: 0.11–0.79, $$p \leq 0.018$$), family history of disease (OR 0.36, $95\%$CI: 0.12–0.96, $p \leq 0.05$), and obesity (OR 4.1, $95\%$CI: 1.01–19.1, $p \leq 0.05$). There was a nonsignificant trend toward more severe disease among smokers (OR 2.43, $$p \leq 0.07$$). ## 5. Discussion In this study of a randomly selected population of patients with axSpA, it was observed that patients who were breastfed had significantly lower disease activity indices (BASDAI and ASDAS) and less severe disease. However, we did not detect differences in the age of onset of the disease in relation to breastfeeding or an association between the disease outcomes analyzed and the duration of breastfeeding. Nor did we detect a clear relationship between having been breastfed and structural damage, especially in the form of syndesmophytes development. After introducing the adjusted logistic regression models, it was shown that patients who were breastfed reduced the possibility of severe disease by $78\%$. In addition, the study sample randomly selected for this study had sufficient statistical power ($87\%$) to detect significant differences between the two groups based on the development of severe vs. non-severe disease. The benefits of breastfeeding are manifold, including the initial shaping of the gut microbiome in humans, with clear implications for the development and maturation of the immune system. Breast milk is a component of the maternal-mucosal immune system that aids in the development and regulation of both the infant’s innate and adaptive immunity. Furthermore, breast milk provides a host of anti-inflammatory, anti-infectious and tolerogenic products [6,13]. These benefits appear to be related to the ability to protect the individual from the development of communicable and non-communicable diseases later in life. Thus, the protective effect of breastfeeding on the future development of cardiovascular diseases, allergies, asthma, or diabetes, among others, has been reported [6,13]. Moreover, it has been hypothesized that individuals who receive breastfeeding could be protected from the future development of AS, while in the case of RA the data are more controversial [8,14]. In this sense, $58\%$ of our series had been breastfed, while the official rates of breastfeeding in Europe are around $70\%$, which supports this hypothesis [13]. On the other hand, infants with JIA who are breastfed appear to develop less severe disease than formula-fed infants with the same condition [7], so it is possible that the benefits of breastfeeding may not only refer to the possibility of protecting individuals from the development of certain rheumatic diseases, but also that these benefits can be extended to the natural evolution of the disease once it has already started. To the best of our knowledge, there are no studies that have analyzed activity and severity data in relation to a history of breastfeeding in patients with axSpA, and although breastfeeding did not appear to have a protective effect on the development of the disease in our population since both groups developed the disease at very similar ages, it does seem to be associated with a less active and less severe disease. It is also noteworthy that the protective effect against severe disease detected in our study was independent of the duration of lactation. Therefore, what seems important is breastfeeding itself, regardless of its duration. Our findings are in line with a meta-analysis conducted in patients with RA that suggested that breastfeeding was associated with a lower risk of RA, regardless of whether the breastfeeding time was longer or shorter [14]. It is difficult, in any case, to connect an event very early in an individual’s life, such as having been breastfed, with the development and evolution of a disease, such as axSpA, that will occur decades later and that is surely related to many other predisposing factors [15]. In any case, the connections between alterations in the gut microbiome and the development of SpA are strongly supported by many studies of the last decade [2,3,4,5,16], so it is tentative to speculate on the fact that the alterations in the intestinal microbiota involved in the development of SpA are gestated in a very early stage of life, and that, once developed, remain as a perennial dysbiosis imprint that under certain favorable circumstances (HLA-B27, a second hit phenomenon, etc.) lead to the development of clinically evident disease. Supporting this view, it has been shown that breastfed and bottle-fed rhesus macaque infants developed markedly different immune systems, which remained different 6 months after weaning when the animals began to receive identical diets. In particular, breastfed infants developed robust populations of memory T cells as well as T helper 17 (Th17) cells within the memory pool, whereas bottle-fed infants did not [17]. This last data is interesting, since Th17 cells seem to play an essential role in maintaining homeostasis and other barrier functions of the epithelium of the digestive mucosa [2,18]. The alternative hypothesis is that formula milks might contain products that promote an arthritogenic dysbiosis that, again, under favorable circumstances might lead to the development of clinically evident disease decades later. In any case, delving into the dysbiosis-disease connections that are at the base of the pathogenic theory of the gut-joint axis of SpA is beyond the objectives of this discussion. A notable fact extracted from the adjusted regression models of this study is that smoking was the most determining factor in relation to the adverse outcomes of the disease. Thus, smokers had, in a statistically significant way, an average of 1.56 points more in the BASDAI estimate, 1.59 points more in the BASFI score, 0.54 points more in the ASDAS, and 2.9 points more in the mean estimate of the ASAS HI. For its part, being a smoker increased the possibility of developing syndesmophytes more than fourfold. Moreover, there was a nonsignificant trend toward more severe disease among smokers. These findings are consistent with previous studies in this regard, and highlight the relevance of this modifiable risk factor in disease management strategies [19,20]. In addition, obesity has been linked with worse outcomes in axSpA. In a recent study, this modifiable comorbidity was significantly associated with worse quality of life, greater impairment of functional ability, and a trend toward worse disease activity [21]. Obesity has been associated with a higher reported BASDAI score, and being overweight or obese was associated with a higher degree of spinal stiffness and number of comorbidities compared to under/normal weight respondents [22]. In line with this, our obese patients had a more than fourfold greater likelihood of having severe disease. This data becomes especially important if we take into account that it has been hypothesized that prolonged breastfeeding constitutes a protective mechanism against obesity by affecting long-lasting physiological changes in liver-to-hypothalamus communication and hypothalamic metabolic regulation [23]. In that sense, we found a higher prevalence of obesity among non-breastfed patients. Therefore, a tentative thought is that part of the protective effects of breastfeeding on the development of axSpA and its severity is mediated by a positive effect of breastfeeding (especially prolonged) in the prevention of obesity in later stages of life. Obesity should therefore be considered as a modifiable risk factor for disease activity within axSpA management, and perhaps one of the best ways to combat this predictor of poor outcome is to promote prolonged breastfeeding. This study has certain weaknesses that we will comment on. First, it is a cross-sectional observation, although the patients were part of a larger cohort subjected to rigorous follow-up. Second, and despite careful questioning about the history of breastfeeding, a false recollection bias cannot be excluded. On the other hand, the sample size is relatively small, although this did not seem to affect the statistical power of the study in relation to the main outcomes, such as the difference in the proportion of patients with severe vs. non-severe disease after being breastfed. In addition, the structural damage was not estimated through a standard measure such as the mSASSS, but rather through the collection of information on variables such as the degree of sacroiliac involvement, vertebral squaring or syndesmophytes formation. The definition of severe disease is not standard, and this can be criticized, although this definition was based on a combined and sustained outcome at the time of the activity, the functional disability, and the global impact of the disease on the subjects. Among the strengths of the study, it is worth noting the detailed and standardized collection of information within a unit specifically dedicated to the study of axSpA patients and subject to periodic audits. We also highlight that the sample of patients was randomly extracted from a larger database, which reinforces the statistical reliability of the study. In addition, factors that are classically associated with worse outcomes in SpA, such as smoking and obesity [19,20,21,22,24], were also associated with worse clinical outcomes in our series, which contributes to reinforce the validity of our results. ## 6. Conclusions Our study shows that having received breastfeeding, regardless of its duration, is associated with better outcomes in patients with axSpA. Furthermore, breastfeeding seems to exert a certain protective effect against the development of more severe disease. In addition, this protective effect was maintained after the adjustment for several confounders. These data should be confirmed with larger prospective studies. ## References 1. Dougados M., Baeten D.. **Spondyloarthritis**. *Lancet* (2011) **377** 2127-2137. DOI: 10.1016/S0140-6736(11)60071-8 2. Rizzo A., Ferrante A., Guggino G., Ciccia F.. **Gut inflammation in spondyloarthritis**. *Best Pract. Res. Clin. Rheumatol.* (2017) **31** 863-876. 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--- title: High-Sensitivity C-Reactive Protein Modifies P-Wave Terminal Force in Lead V1-Associated Prognosis in Acute Ischemic Stroke or TIA Patients authors: - Yueyang Wu - Wei Lv - Jiejie Li - Xiaomeng Yang - Xia Meng - Zixiao Li - Yuesong Pan - Yong Jiang - Hongyi Yan - Xinying Huang - Liping Liu - Xingquan Zhao - Yilong Wang - Hao Li - Yongjun Wang journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003915 doi: 10.3390/jcm12052031 license: CC BY 4.0 --- # High-Sensitivity C-Reactive Protein Modifies P-Wave Terminal Force in Lead V1-Associated Prognosis in Acute Ischemic Stroke or TIA Patients ## Abstract Little is known about the role of high-sensitivity C-reactive protein (hsCRP) in the relationship between P-wave terminal force in lead V1 (PTFV1) and stroke prognosis. We aimed to investigate how hsCRP influences the effect of PTFV1 on ischemic stroke recurrence and mortality. In this study, patients enrolled in the Third China National Stroke Registry, which enrolled consecutive patients who had suffered an ischemic stroke or transient ischemic attack in China, were analyzed. After excluding patients with atrial fibrillation, 8271 patients with PTFV1 and hsCRP measurements were included in this analysis. Cox regression analyses were used to assess the association between PTFV1 and stroke prognosis according to different inflammation statuses stratified by an hsCRP level of 3 mg/L. A total of 216 ($2.6\%$) patients died, and 715 ($8.6\%$) patients experienced ischemic stroke recurrence within 1 year. In patients with hsCRP levels ≥ 3 mg/L, elevated PTFV1 was significantly associated with mortality (HR, 1.75; $95\%$ CI, 1.05–2.92; $$p \leq 0.03$$), while in those with hsCRP levels < 3 mg/L, such an association did not exist. In contrast, in patients with hsCRP levels < 3 mg/L and those with hsCRP levels ≥ 3 mg/L, elevated PTFV1 remained significantly associated with ischemic stroke recurrence. The predictive role of PTFV1 towards mortality but not ischemic stroke recurrence differed in terms of hsCRP levels. ## 1. Introduction Atrial cardiopathy is a term used to describe atrial structural and pathophysiologic changes that can precede atrial fibrillation (AF), which is known to be associated with an increased risk of ischemic stroke and mortality after stroke [1,2]. P-wave terminal force in lead V1 (PTFV1) is a well-investigated atrial cardiopathy marker applied to electrocardiography (ECG). It has been shown to be associated with the risk of incident ischemic stroke and mortality [3,4]. The production of a substrate for thrombus formation and subsequent embolization to the brain has been suggested to account for the risk of stroke correlated with PTFV1 [5]. More importantly, such an association persists even in the absence of AF, and a stronger association of PTFV1 with incident stroke than with incident AF has been revealed [5,6,7,8]. These findings suggest that PTFV1 plays a crucial role in the early screening for the risk of atrial-cardiopathy-related stroke. In contrast, limited data are available regarding the effect of PTFV1 on recurrent stroke in patients without AF. On the other hand, patients with a high inflammation burden have an increased risk of recurrent stroke and mortality after stroke [9,10,11]. Furthermore, inflammation has also been shown to be involved in a series of pathophysiological abnormalities that cause atrial cardiopathy to progress to stroke [12], such as endothelial dysfunction [13], impaired myocyte function, blood stasis [14], and myocardial remodeling [15]. High-sensitivity C-reactive protein (hsCRP) is a commonly used and accessible inflammatory marker, and whether the role of PTFV1 in recurrence and mortality after stroke varies according to hsCRP level is still unknown. The Third China National Stroke Registry (CNSR-III) enrolled patients with acute ischemic stroke and transient ischemic attack (TIA) in order to identify prognostic markers and promote the early evaluation and identification of high-risk patients [16]. We used the CNSR-III cohort to determine whether hsCRP levels affect PTFV1-associated ischemic stroke recurrence and mortality in patients with cerebrovascular disease but without AF. ## 2.1. The Study Design and Participants The CNSR-III was a nationwide, prospective registry developed between August 2015 and March 2018 that enrolled 15166 patients that had suffered ischemic stroke or TIA within seven days after symptom onset. The study included 201 hospitals in 26 provinces and municipalities in China. The prespecified biomarker substudy of the CNSR-III incorporated 171 study sites from which blood samples had been previously collected. Fasting blood samples were obtained within 24 h of admission. The CNSR-III was approved by the Ethics Committee at Beijing Tiantan Hospital and all participating centers. Informed consent was provided by all patients or their legally authorized representatives. The detailed study design and methods of the CNSR-III have been described previously [16]. ## 2.2. Baseline Data The baseline clinical data of patients enrolled in the CNSR-III were collected by trained research coordinators at each institute, and these data included age, sex, body mass index (calculated as weight in kilograms divided by height in meters squared, kg/m2), smoking habits, and medical history (stroke, TIA, diabetes, hypertension, dyslipidemia, coronary heart disease, and heart failure). The severity of stroke upon admission was measured using the National Institutes of Health Stroke Scale (NIHSS) score, and baseline leukocyte count as well as medication usage, e.g., antiplatelets, anticoagulants, antihypertensive agents, hypoglycemic agents, and lipid-lowering agents, were also recorded. ## 2.3. Sample Collection and Measurements of hsCRP The median time of sampling was 55 h (interquartile range, 27–96 h) after the onset of the index event. Serum and plasma specimens were extracted, transported through the cold chain, and subsequently stored at −80 °C in the core laboratory at Beijing Tiantan Hospital. All assays were performed centrally and blindly. The concentrations of plasma hsCRP were measured on Roche Cobas C701 analyzers. ## 2.4. Atrial Cardiopathy Marker Upon admission, each patient underwent a standard 12-lead ECG with a speed of 25 mm/s and calibration of 10 mm/mV. The ECG was digitalized and amplified to up to 5 times its original size. A well-trained cardiologist blinded to the clinical data of patients measured PTFV1 using digital calipers. The measurements were repeated thrice, and the average values were obtained for analysis. PTFV1 was defined as the duration (ms) times the absolute value of the depth (μV) of downward deflection (terminal portion). Previous studies have demonstrated excellent intra-rater correlations for manual measurements of PTFV1 [7]. To evaluate interrater reliability, a second well-trained cardiologist performed blinded measurements of a random sample of 200 ECGs. The interrater intraclass correlation coefficient was 0.78 ($95\%$ CI, 0.67–0.85). ## 2.5. Outcomes and Follow-Up The evaluated outcomes were all-cause mortality and ischemic stroke recurrence within 1 year. Patients were interviewed face-to-face at 3 months, while trained research coordinators contacted the patients at 6 months and 1 year. Death certificates were obtained either from the relevant hospitals or the local citizen registry. Ischemic stroke recurrence was confirmed through hospital visits. Suspected cases of ischemic stroke recurrence without hospitalization were judged by independent endpoint judgement committee. A detailed description of the follow-up procedure has been published previously [16]. ## 2.6. Statistical Analysis Continuous variables were reported as median with interquartile range and examined using the Mann–Whitney U test. Categorical variables were reported as frequency with percentage and analyzed using the chi-square test. The guidelines recommend the setting of an hsCRP level of 3 mg/L as a cutoff point for risk stratification of cardiovascular disease [17]. Therefore, we used an hsCRP cutoff of 3 mg/L to define elevated hsCRP levels. Increased PTFV1 was defined as > 5000 μV·ms according to a previous study [18]. The risk of outcomes was evaluated using Kaplan–Meier survival analysis with the log-rank test. Multivariable Cox proportional hazards models were used to assess the relationship between PTFV1 and outcomes. Models were adjusted for age, sex, NIHSS score, hypertension, diabetes mellitus, dyslipidemia, status as a current tobacco smoker, heart failure, coronary artery disease, stroke, TIA, medication (antiplatelets, anticoagulants, antihypertensive agents, hypoglycemic agents, and lipid-lowering agents), and baseline leukocyte count. A two-sided $p \leq 0.05$ was considered indicative of statistical significance. All data were analyzed using SAS statistical software, version 9.4 (SAS Institute, Inc., Cary, NC, USA). ## 3.1. Patient Characteristics After excluding patients with AF, a total of 8271 patients with both hsCRP and PTFV1 measurements were included in this analysis (Figure S1). Baseline characteristics were presented according to the PTFV1 threshold (Table 1). The median age of the participants was 62 years, and $68.6\%$ of patients were men. The median hsCRP level was 1.6 mg/L (interquartile range, 0.8–4.2 mg/L). Elevated PTFV1 was associated with older age and higher hsCRP levels, NIHSS scores, and BMI. Additionally, there was a higher prevalence of males; histories of stroke, diabetes, hypertension, coronary heart disease, and heart failure; the usage of anticoagulants and antihypertensive agents; and the nonuse of antiplatelet agents among those with PTFV1 > 5000 μV·ms. The baseline characteristics and clinical features of the included and excluded participants are presented in Table S1. The excluded patients tended to be older and had higher prevalence values in terms of histories of coronary heart disease and heart failure and the usage of anticoagulants, while they had lower prevalence of smoking, histories of diabetes and dyslipidemia, and the usage of antiplatelet agents, hypoglycemic agents, and lipid-lowering agents. We adjusted these factors in multivariable cox proportional hazards models. ## 3.2. Associations of PTFV1 with Mortality According to hsCRP Levels In total, 216 ($2.6\%$) participants died within 1 year. PTFV1 > 5000 μV·ms was significantly associated with mortality (adjusted HR, 1.58; $95\%$ CI, 1.01–2.47; $$p \leq 0.04$$) after adjustment. When classifying the patients according to their hsCRP levels, among patients with hsCRP levels ≥ 3 mg/L, elevated PTFV1 was significantly associated with mortality (adjusted HR, 1.75; $95\%$ CI, 1.05–2.92; $$p \leq 0.03$$); among those with hsCRP levels < 3 mg/L, such an association did not exist (adjusted HR, 1.00; $95\%$ CI, 0.39–2.56; $$p \leq 0.99$$) (Table 2). Figure 1 displays the cumulative incidence of mortality according to the hsCRP threshold. In those with hsCRP levels < 3 mg/L, PTFV1 > 5000 μV·ms was not associated with a higher cumulative incidence of mortality ($$p \leq 0.28$$). However, in those with hsCRP levels ≥ 3 mg/L, the cumulative incidence of mortality was significantly higher in the PTFV1 > 5000 μV·ms group ($$p \leq 0.0002$$). ## 3.3. Associations of PTFV1 with Ischemic Stroke Recurrence According to hsCRP Levels In total, 715 ($8.6\%$) participants experienced ischemic stroke recurrence within 1 year. Patients with PTFV1 > 5000 μV·ms had a significantly higher risk of ischemic stroke recurrence (adjusted HR, 1.86; $95\%$ CI, 1.42–2.44; $p \leq 0.0001$) after adjustment. In patients with hsCRP levels < 3 mg/L (adjusted HR, 1.95; $95\%$ CI, 1.35–2.82; $$p \leq 0.0004$$) and those with hsCRP levels ≥ 3 mg/L (adjusted HR, 1.74; $95\%$ CI, 1.18–2.56; $$p \leq 0.005$$), PTFV1 > 5000 μV·ms remained significantly associated with ischemic stroke recurrence (Table 3). Figure 2 displays the cumulative incidence of ischemic stroke recurrence according to the hsCRP threshold. In both patients with hsCRP levels < 3 mg/L ($p \leq 0.0001$) and those with hsCRP levels ≥ 3 mg/L ($$p \leq 0.003$$), PTFV1 > 5000 μV·ms was associated with a higher cumulative incidence of ischemic stroke recurrence. ## 3.4. Associations of hsCRP with Prognosis According to PTFV1 Threshold Patients with hsCRP levels ≥ 3 mg/L had a significantly higher risk of death (adjusted HR, 2.09; $95\%$ CI, 1.56–2.80; $p \leq 0.0001$) and ischemic stroke recurrence (adjusted HR, 1.24; $95\%$ CI, 1.06–1.45; $$p \leq 0.006$$) after adjustment (Tables S2 and S3). In patients with PTFV1 > 5000 μV·ms, an increased hsCRP level still showed a trend of a higher risk of death (adjusted HR, 2.75; $95\%$ CI, 0.91–8.29; $$p \leq 0.07$$) (Table S2), while no significant association was observed between increased hsCRP levels and ischemic stroke recurrence (adjusted HR, 0.92; $95\%$ CI, 0.53–1.62; $$p \leq 0.78$$) (Table S3). ## 4. Discussion In this study, we found that elevated PTFV1 was associated with a higher risk of death and ischemic stroke recurrence among patients who had suffered an acute ischemic stroke or TIA and in the absence of AF. Furthermore, a PTFV1-associated mortality risk was only observed among patients with high hsCRP levels. The association between PTFV1 and ischemic stroke recurrence was not influenced by hsCRP levels. AF is the primary cause of cardioembolism, accounting for $15\%$ to $24\%$ of ischemic strokes. A stroke resulting from AF is typically more severe, more likely to recur, and nearly twice as likely to be fatal as non-AF strokes [19]. Thrombus formation in patients with AF is caused by decreased LA appendage flow velocity, the activation of the coagulation cascade, and left atrial enlargement and fibrosis. Even short subclinical episodes of AF are linked to stroke, but the causal connection between AF and ischemic stroke remains indirect. Prior research has demonstrated that in older patients with vascular risk factors, a single brief episode of subclinical AF is linked to a higher risk of stroke [20]. Conversely, males with a low risk for stroke and clinically apparent AF do not face a significantly increased stroke risk [21]. These conflicting findings are insufficient with respect to establishing a definitive biological gradient between the burden of AF and the risk of stroke. It was reported that AF events were detected in only $8\%$ of stroke patients within 30 days prior to the onset of a stroke, while $16\%$ of stroke patients experienced their first AF event after the occurrence of stroke [22], suggesting that AF itself may not be the direct cause of stroke. Instead, it may be a risk indicator for embolic stroke due to underlying atrial dysfunction. Recent advancements in pathophysiology suggest that left atrial degeneration, including chamber dilation, remodeling, fibrosis, and damage to endothelial cells and cardiomyocytes, can cause thrombus generation and embolism, even in patients without AF. This condition is referred to as atrial cardiopathy, which describes the structural and functional disorders of the atrium that can precede AF [1]. The abnormal atrial tissue substrate results from aging and systemic vascular risk factors, which increase the risk of AF and thromboembolism. Once AF develops, it causes contractile dysfunction and stasis, leading to a greater risk of thromboembolism. Moreover, the arrhythmia causes the structural remodeling of the atrium, further worsening atrial cardiopathy and increasing the risk of thromboembolism. Autonomic changes and inflammation post-stroke may transiently increase AF risk after stroke [23]. Rather than considering AF as the sole cause of thromboembolic risk in patients with AF, it is more helpful to perceive both AF and thromboembolism as common manifestations of an underlying atrial cardiopathy. The driving force of thromboembolism is not merely the arrhythmia but also a host of underlying pathological tissue changes. Nonetheless, AF remains a crucial factor with respect to thromboembolic risk because the arrhythmia worsens both the tissue changes and left atrial contractile function. While no established criteria exist for diagnosing atrial cardiopathy, researchers have tried to identify biomarkers associated with stroke to detect the condition early. One crucial factor that connects atrial cardiopathy and AF with stroke is inflammation [12]. Patients with AF have increased levels of inflammatory markers such as CRP, tumor necrosis factor-α, and interleukin-2, -6, and -8 [14]. The Women’s Health Study demonstrated that in women without a history of cardiovascular disease, inflammatory biomarkers, including CRP, soluble intercellular adhesion molecule-1, and fibrinogen, were independently associated with an increased incidence of AF, even after controlling for traditional risk factors [24]. Among AF patients, CRP was positively correlated with stroke risk and related to stroke risk factors and prognosis (mortality and vascular events) [25]. Previous studies have suggested that there is a positive association between PTFV1 and sudden cardiac death, cardiovascular death [26], and all-cause death [4], independent of clinical cardiovascular risk factors. Our results proved the independent predictive role of PTFV1 with respect to mortality after stroke and further added evidence regarding the effect of hsCRP on it. We found that PTFV1 was associated with mortality only in those with elevated hsCRP levels. Many factors may account for the association between PTFV1 and mortality. First, PTFV1 reflects atrial changes, such as left atrial hypertrophy and interatrial conduction defects [27], and its increase has been associated with impaired left atrial function and possibly eventual mortality [28,29]. Second, a recent study confirmed an association between abnormal PTFV1 and left ventricular fibrosis determined via cardiac MRI [28]. In addition, PTFV1 has been suggested to be an early manifestation of left ventricular diastolic dysfunction [30], which is an independent predictor of mortality [31]. Third, PTFV1 was significantly associated with brain vascular injury and infarction [32], which might lead to an increased risk of mortality. On the other hand, inflammation has also been indicated to be involved in the dysfunction of the left atrium and left ventricle [12,33] and brain infarction [34,35]. Therefore, patients with elevated PTFV1 and hsCRP levels are likely to be exposed to greater abnormalities correlated with mortality. Furthermore, in view of hsCRP itself being a direct independent factor of mortality after stroke, through various mechanisms other than those aforementioned [36], hsCRP may play a more important role in predicting mortality than PTFV1. This might be one possible explanation for the absence of an association of PTFV1 with mortality in patients with elevated PTFV1 but low hsCRP levels found in our study. Furthermore, our findings expand the previous data on the relationship between PTFV1 and stroke in the absence of AF. Atrial thromboembolism caused by PTFV1 has been suggested to contribute to the incidence of stroke [5]. Although inflammation plays a role in not only thrombosis but also atherosclerotic plaque development and rupture [37], we found that PTFV1-associated ischemic stroke recurrence was not affected by hsCRP levels, suggesting a dominant role of PTFV1 in recurrent stroke. The results indicate that PTFV1 has a stronger association with recurrent stroke than with mortality, which could be partly explained by hsCRP being an overall indicator of poor prognosis, while PTFV1 was more specifically associated with the pathophysiology of ischemic stroke. Taken together, our findings, to some extent, indicated different mechanisms that lead to PTFV1’s ability to cause recurrent stroke and mortality and helped stratify the risk of recurrent stroke and mortality by incorporating hsCRP. The most clinically evident biomarker of atrial cardiopathy is AF. However, it seemed likely that atrial cardiopathy evolved long before AF became clinically evident. PTFV1 was significantly associated with the risk of AF [38,39]. Inflammation was shown to be involved in the inception, recurrence, and perpetuation of AF [40]. In addition, it contributed to promoting a prothrombotic AF state via endothelial dysfunction, platelet activation, and the increased expression of fibrinogen [14]. Inflammatory cells, such as lymphocytes, monocytes, and macrophages, are responsible for producing cytokines and chemokines, which can trigger thrombosis in AF. IL-6 has been found to stimulate the expression of tissue factor, fibrinogen, factor VIII, and von Willebrand factor, thereby promoting a pro-thrombotic state. IL-6 may also cause endothelial activation and endothelial cell damage, leading to platelet aggregation and increased sensitivity to thrombin [14]. Activated platelets can further promote and maintain the pro-thrombotic state while also increasing the levels of inflammatory biomarkers in patients with AF. In addition to these effects, altered endothelial function can also contribute to inflammation and thrombosis in AF. Endothelial activation leads to the rapid release of substances, such as von Willebrand factor and soluble P-selectin, onto the endothelial surface, which promote the attachment of rolling white blood cells to the endothelium and contribute to the development of a pro-inflammatory and pro-thrombotic environment [12]. It is possible that this inflammatory state contributes to the development of atrial cardiopathy, which leads to endothelial dysfunction [13] and atrial structural changes [15] and results in a greater state of inflammation. The underlying pathophysiology represented by these biomarkers may provide insight into atrial cardiopathy. We excluded patients with AF since the association between AF and stroke prognosis was clear. The current study focused on patients with manifestations of atrial cardiopathy before the occurrence of AF. This study has some limitations that should be considered when interpreting the results. First, the exclusion of patients with incomplete markers or AF might have introduced potential selection bias. Second, the manual measurement of PTFV1 rather than automated measurements might have limited the accuracy of the results. Nevertheless, the use of independent investigators for the blinded measurements enhanced the objectivity and reproducibility of the data. Third, this study was conducted in a Chinese population and may not be directly generalizable to other populations with different characteristics. Finally, although our findings suggest an association between PTFV1, hsCRP, and the prognosis of patients who have suffered an ischemic stroke or TIA, the observational nature of the study precludes our ability to infer a causal relationship. 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--- title: Inorganic Pyrophosphate Plasma Levels Are Decreased in Pseudoxanthoma Elasticum Patients and Heterozygous Carriers but Do Not Correlate with the Genotype or Phenotype authors: - Matthias Van Gils - Justin Depauw - Paul J. Coucke - Shari Aerts - Shana Verschuere - Lukas Nollet - Olivier M. Vanakker journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003929 doi: 10.3390/jcm12051893 license: CC BY 4.0 --- # Inorganic Pyrophosphate Plasma Levels Are Decreased in Pseudoxanthoma Elasticum Patients and Heterozygous Carriers but Do Not Correlate with the Genotype or Phenotype ## Abstract Pseudoxanthoma elasticum (PXE) is a rare ectopic calcification disorder affecting soft connective tissues that is caused by biallelic ABCC6 mutations. While the underlying pathomechanisms are incompletely understood, reduced circulatory levels of inorganic pyrophosphate (PPi)—a potent mineralization inhibitor—have been reported in PXE patients and were suggested to be useful as a disease biomarker. In this study, we explored the relation between PPi, the ABCC6 genotype and the PXE phenotype. For this, we optimized and validated a PPi measurement protocol with internal calibration that can be used in a clinical setting. An analysis of 78 PXE patients, 69 heterozygous carriers and 14 control samples revealed significant differences in the measured PPi levels between all three cohorts, although there was overlap between all groups. PXE patients had a ±$50\%$ reduction in PPi levels compared to controls. Similarly, we found a ±$28\%$ reduction in carriers. PPi levels were found to correlate with age in PXE patients and carriers, independent of the ABCC6 genotype. No correlations were found between PPi levels and the Phenodex scores. Our results suggest that other factors besides PPi are at play in ectopic mineralization, which limits the use of PPi as a predictive biomarker for severity and disease progression. ## 1. Introduction Ectopic mineralization—the pathologic deposition of calcium salts in soft tissues—is a complex process underlying a heterogenous group of disorders—both common (such as atherosclerosis, kidney disease and stroke) and orphan diseases—and is associated with significant morbidity and mortality. Evidence has emerged in recent years that ectopic mineralization arises out of a dynamic deregulation of several gene regulatory networks, proteins and metabolic alterations reflecting complex perturbations. A central mediator in these processes is inorganic pyrophosphate (PPi), a potent calcification inhibitor that acts by binding and coating crystal nucleation sites, thus halting ectopic mineralization formation [1]. PPi is produced by the conversion of extracellular ATP into adenosine monophosphate (AMP) and PPi by the ectonucleotidase enzyme ENPP1 [2]. Circulating PPi has a short half-life of ±30 min, in part due to hydrolyzation into pro-mineralizing phosphate (Pi) molecules by alkaline phosphatases (ALPL). In turn, ALPL activity is inhibited through adenosine release from AMP by CD73 [3]. Another important protein in the homeostasis of PPi was recently identified as ABCC6, an adenosine triphosphate (ATP)-binding transporter protein encoded by the ABCC6 gene. Biallelic pathogenic variants in ABCC6 are known to cause pseudoxanthoma elasticum (PXE), an autosomal recessive disorder in which the calcification and fragmentation of elastic fibers results in skin (papular lesions and increased skin laxity), eye (angioid streaks, choroidal neovascularization and hemorrhage) and cardiovascular symptoms (peripheral artery disease and stroke), though the severity is highly variable between patients [4,5,6]. In PXE families, heterozygous carriers of one ABCC6 pathogenic variant can present a partial PXE phenotype. While they do not develop skin lesions and PXE retinopathy is rare, they can present calcifications in the retina and abdominal organs and have an increased risk for cardio- and cerebrovascular complications [7,8,9,10,11]. Because of the predominant expression of ABCC6 in liver and kidney, PXE is considered a metabolic disorder driven by the absence of systemic substrates provided from the liver through ABCC6. The ABCC6 substrate remains elusive, but ABCC6—at least indirectly—regulates the release of ATP from hepatocytes into the circulation [12,13], thereby contributing to PPi production and mineralization homeostasis [3]. While ABCC6-mediated ATP release appears to be the main source of PPi, extracellular ATP may also be released by ANKH [14]. Decreased plasma levels of PPi are an important contributor to the ectopic mineralization in PXE. Significantly decreased PPi levels have been reported in PXE patients and Abcc6−/− rodent models [12,13,15]. Moreover, PPi deficiency is critical to the development of generalized arterial calcification of infancy (GACI), an ectopic calcification disorder with genetic and clinical overlap with PXE [16,17]. Furthermore, differential expressions and/or activities of ANKH, ALPLs and CD73 have been reported in PXE [13,15,18,19,20], leading to the consensus that a pro-mineralizing shift in the PPi/Pi balance is a significant driver of the PXE calcification phenotype. While many other factors can further negatively affect the mineralization homeostasis in PXE [3,21,22], recent studies using PPi supplementation in Abcc6−/− mice suggest that increasing PPi levels can help in preventing the progression of mineralization [23,24]. In this study, we demonstrated that PPi plasma levels are not only decreased in PXE patients but also in heterozygous carriers and may thus contribute to their partial phenotype. However, we could not find any correlation with the severity of the phenotype or with the ABCC6 genotype. Together with the observed overlap in PPi levels between patients, carriers and controls, this convinced us that PPi plasma levels are not a reliable biomarker for PXE. ## 2.1. Molecular and Clinical Evaluation For all patients, heterozygous carriers and controls, a molecular analysis of the ABCC6 gene was performed as previously described [11,25]. All ABCC6 variants were classified using the Sherloc classification of pathogenicity [26,27]. All patients had a histological diagnosis of PXE, and the disease severity was assessed using the PXE International Phenodex scoring system at the time of blood sampling for PPi measurement [28]. Scoring was performed for skin (S0–S3), eye (E0–E4), vasculature (V0–V3), cardiac (C0–C2) and gastrointestinal (G0–G1) symptoms. Data on putative confounders (i.e., smoking, hypertension, hypercholesterolemia, diabetes and obesity) were collected. Informed consent was obtained from all participants, and the tenets of the Declaration of Helsinki were followed. This study was approved by the ethical committee of the Ghent University Hospital. ## 2.2. Plasma PPi Analysis Fasting blood samples were collected from PXE patients, carriers and controls using 4 citrate BD-Vacutainers (363,083, BD) per sampling and stored on ice. The samples were immediately centrifuged at 1000× g for 10 min at 4 °C. Patient plasma was pooled, redistributed to Centrisart I MWCO 300,000 Da tubes (Item No. 13,279—E, Sartorius, Göttingen, Germany) and centrifuged at 2300× g for 30 min at 4 °C. Purified plasma was then collected, anonymized and stored at −80 °C. The plasma PPi content was determined using a two-step ATPase luminescence assay prepared on ice. For each plasma sample, 250 µL of ATP conversion mix (825 mU of ATP sulfurylase (M0394L, Bioké NV, Leiden, The Netherlands), 64 µM APS (SC-214506, Bio-Connect, Huissen, The Netherlands), 31 mM HEPES (pH = 7.4) and 104 µM Mg2Cl) was prepared. To 58 µL of plasma, 2 µL of 0 µM ATP and 20 µL of ATP conversion mix were added. PPi was enzymatically converted to ATP in a PCR machine (30 min at 37 °C and 10 min at 90 °C). *To* generate an internal calibration curve, 11 aliquots of 58 µL plasma samples were spiked with 2 µL of 0–50 µM ATP (in increments of 5 µM) and 20 µL of heat-inactivated ATP conversion mix. The 40 µL sample and calibration curve aliquots were distributed in pairs on a 96-well plate, and 10 µL of Bactiter-Glo was added to each well. After mixing for 2 min, the luminescence was measured using a Glomax (E7031, Promega, Leiden, The Netherlands). Linear calibration curves were established, and plasma PPi values were derived from the first-degree equations (Figure 1 and Supplementary Table S1). ## 2.3. Statistical Analysis A statistical analysis was performed via SPSS26 software (IBM, Chicago, IL, USA). The sample distribution was determined via Kolmogorov–Smirnov testing for normality, and subsequent analyses via (independent) t-testing, (repeated measures) ANOVA, chi-square (nominal variables) or their non-parametric counterparts were performed. The correlations between variables were first estimated using Pearson or Spearman analyses, depending on the variable distribution. Regression analyses were subsequently performed to estimate the predictive power of variables on particular dependents. The results were significant at p ≤ 0.05. ## 3.1. Demographic, Molecular and Clinical Characteristics of the Cohorts Samples from 78 Caucasian PXE probands, 69 carriers and 14 controls were analyzed. Table 1 shows the demographic characteristics of the patients, heterozygous carriers and the control cohort. Sex and age were normally distributed; no significant differences were found for these characteristics between the groups ($p \leq 0.05$). The molecular and clinical characteristics of the patient cohort are shown in Supplementary Table S2. In all but three patients, biallelic ABCC6 variants were identified. In total, 126 variants were pathogenic (class 5), 8 were likely pathogenic (class 4) and 19 were variants of unknown significance (class 3), with 12 and 1 of these identified as likely pathogenic (C3LP) and likely benign (C3LB), respectively. The characteristics of the carriers and controls are shown in Supplementary Table S3. In 44 and 6 carriers, respectively, a heterozygous ABCC6 pathogenic (class 5) or likely pathogenic (class 4) variant was found. In total, 19 carriers had a class 3 variant, of which 12 were C3LP variants. The effects of other confounding factors in our patient cohort were investigated. Notably, 8 patients were smokers; one patient had type II diabetes mellitus; no patients had untreated hypertension, but 5 patients were taking anti-hypertensive drugs and 3 patients and 23 patients had untreated and medication-controlled hypercholesterolemia, respectively. However, these confounders did not correlate with sex, age or the measured plasma PPi levels ($p \leq 0.05$) and were therefore considered non-informative (Table 2). The effects of putative confounding factors, i.e., smoking (yes/no), diabetes mellitus (no, type I or type II), hypertension (yes/no) and hypercholesterolemia (untreated/no or treated), were analyzed according to sex (female/male), PPi levels (µM) and age (years). Diabetes mellitus was diagnosed according to the WHO criteria (a fasting blood sugar level of 126 mg/dL, a 2 h oral glucose tolerance test result of 200 mg/dL and hemoglobin A1c of $6.5\%$ or higher). Hypertension was defined as a systolic and/or diastolic blood pressure higher than $\frac{140}{90}$ mmHg. Hypercholesterolemia was defined as a fasting low-density lipoprotein cholesterol (LDL-C) concentration > 115 mg/dL. No significant effects were identified (all $p \leq 0.05.$). ## 3.2. PPi Levels Were Reduced in Patients and Carriers Compared to Controls, Though Overlap between Biological Ranges Was Observed The distribution of the measured PPi values was normal for each cohort ($p \leq 0.05$), and the spread per cohort and sex is shown in Figure 2. While some overlap in PPi values was apparent, significant mean differences between all three cohorts were found ($p \leq 0.001$). Table 2 summarizes the measured plasma PPi levels (means ± SDs (µM)) of the PXE patients, heterozygous carriers and the control cohorts and per sex. The relative comparison between the cohorts—with the control cohort as a baseline—showed a significant mean reduction of ±$50\%$ in PPi levels in the PXE patients. Similarly, a significant ±$28\%$ reduction was observed for carriers. The PXE patient, heterozygous carrier and control sample cohorts are displayed according to sex (male/female) and as a group (total). The N represents the number of samples, age is mean ± SD (years) and PPi is mean ± SD (µM). Significant differences in PPi levels were found between the three cohorts (ANOVA after Bonferroni correction: PXE–heterozygous carrier, $p \leq 0.00001$; PXE–control, $p \leq 0.00001$; heterozygous carrier–control, $$p \leq 0.000083$$). Moreover, we looked at the fluctuation in PPi levels between yearly repeated samples in 14 PXE patients with two samples and 8 PXE patients with three samples (Supplementary Table S2). When comparing the three groups (sample 1: $$n = 22$$, sample 2: $$n = 22$$ and sample 3: $$n = 8$$; Figure 3), we noted that some patients appeared to have fluctuations in the measured plasma PPi levels, but overall no significant differences were found between the compared groups (repeated-measures ANOVA ($$n = 8$$/$\frac{8}{8}$): $F = 0.736$, $p \leq 0.05.$ Paired-samples t-test: samples 1–2: ($$n = 22$$/22), $p \leq 0.05$; samples 2–3 ($$n = 8$$/8), $$p \leq 0.527$$; samples 1–3: ($$n = 8$$/8), $p \leq 0.05$). ## 3.3. Plasma PPi Levels Correlated with Age in PXE but Not with Sex Next, we investigated whether sex or age were correlated with the measured PPi levels. First, we analyzed sex-based differences in each cohort, but no significant differences between men and women were found in patients, carriers or controls ($p \leq 0.05$; Table 2). Correlation analyses suggested that in patients and carriers PPi levels significantly increased with age ($p \leq 0.05$; Figure 4), but no such effect was observed in controls ($p \leq 0.05$; Figure 4). ## 3.4. Plasma PPi Levels Did Not Correlate with the ABCC6 Genotype To determine the correlations between the plasma PPi levels and the patient genotypes, the ABCC6 variants of the patient cohort were classified according to the Sherloc variant classification (Supplementary Table S2) [27]. We then categorized the patient cohort into six genotype groups, depending on the expected effect of each variant, i.e., variants likely resulting in erroneous mRNA products (deletions/frameshifts/splice site variants (D)), variants resulting in truncated/unstable proteins (nonsense (N)) and variants likely affecting protein function (missense (M)). Three patients with a single ABCC6 pathogenic variant were excluded from the analyses, resulting in 75 patients for a univariate analysis with correction for sex and age (Table 3). Stepwise analyses were performed with increased stringency for genotype inclusion: all C5-C3 variants ($$n = 75$$), C5-C3LP (likely pathogenic, excluding likely benign and unknown C3 variants; $$n = 71$$), C5-C4 ($$n = 40$$) and only C5 ($$n = 39$$). None of the generated models could explain the measured PPi levels. Comparable analyses for heterozygous carrier genotypes were performed without significant results ($p \leq 0.05$). Thus, we did not identify genotype–PPi correlations. ## 3.5. Plasma PPi Levels Did Not Correlate with the Phenodex Scores Regression analyses (Table 4) were performed on the Phenodex scores with respect to PPi, age and sex. For skin lesion severity, sex (i.e., being female; $$p \leq 0.045$$) was associated with higher scores. Ocular severity was only significantly predicted by age ($p \leq 0.001$). Given the low incidences of cardiovascular events in our cohort (V1: $$n = 9$$, V2: $$n = 4$$, V3: $$n = 3$$, C1: $$n = 2$$ and C2: $$n = 2$$), we first opted for a binary logistic regression (i.e., the absence/presence of a lesion). For the vascular outcome (absent: $$n = 64$$ and present: $$n = 14$$), sex was found to be non-informative, while age (but not PPi) significantly and inversely contributed ($p \leq 0.01$). For the cardiac outcome (absent: $$n = 75$$ and present: $$n = 3$$) sex, age and PPi were non-informative ($p \leq 0.05$). When performing ordinal logistic regressions, the severity of vascular lesions was only predicted by age ($p \leq 0.01$). As with the binary analysis, PPi and age did not contribute significantly to the cardiac Phenodex model ($p \leq 0.05$). ## 4. Discussion and Conclusions Since the initial reports that inorganic pyrophosphate is reduced, PPi has been demonstrated to play a pivotal role in the occurrence of ectopic mineralization in PXE [12,29]. Until recently, the human data published on the relation between ABCC6 and PPi had been at a relatively small scale due to the rarity of the disorder [15,19,29], and data on PPi levels in heterozygous carriers were not available. We observed a ±$50\%$ reduction in circulatory plasma PPi levels in our PXE patient cohort relative to healthy controls. Heterozygous carriers had a ±$28\%$ relative reduction in PPi levels between patients and controls. Despite some overlap, the mean PPi levels of all cohorts were significantly different. Thus, in general, PPi levels are directly dependent on the normal expression of both ABCC6 alleles. The patient PPi levels in our study are in line with earlier reports. Jansen et al. reported a relative reduction in plasma PPi of ±$60\%$ using CTAD-EDTA tubes [29]. Similarly, Sanchez-Tévar et al. noted significant relative reductions of ±$43\%$ (0.35 ± 0.15 µM) and ±$22\%$ (1.11 ± 0.26 µM) when measuring CTAD- and EDTA-based PPi samples of the same patients, respectively [15]. Lefthériotis et al. noted a similar $50\%$ reduction [19]. As we used a citrate-based assay, such differences in reduction—both relative and absolute—indicate that the anticoagulant may significantly impact the PPi signal readout, as exemplified by the difference found between CTAD and EDTA by Sanchez-Tévar et al. [ 15]. Such an effect of the anticoagulant was recently illustrated by Lundkvist et al., who showed that the amount of PPi detected depended on the anticoagulant used in the unfiltered plasma, with CTAD and heparin yielding higher concentrations compared to EDTA [30]. Moreover, we performed an internal calibration and noted that the readout values could vary between different samples despite having been spiked with equal amounts of ATP, indicating that unknown factors in the plasma can affect the readout and may be responsible for part of the variation between different studies (Supplementary Table S1). The value of an internal ATP standard to obtain reliable measurement results was also recently shown by Lundkvist et al. [ 30]. We cannot exclude that ethnic factors also affect PPi levels [31,32,33,34,35,36]. Though it remains a matter of debate which methodology measures the true and exact absolute PPi plasma levels, if any, the different available methods seem to be reliable to document the relative decreases in PPi plasma levels in PXE compared to controls. Indeed, our study reaffirmed that PPi is significantly reduced in PXE, though it is quite variable between patients. We observed in several PXE patients—in particular females—that their PPi levels were comparable to heterozygous carrier or control levels. This confirms that, at least in some patients, mechanisms independent of PPi must also play a role in PXE. A similar observation was made in Abcc6−/− mice in which PPi levels were increased by the global overexpression of ENPP1. Although plasma PPi was increased to the levels found in wild-type mice, the transgenic animals still suffered from small mineralization foci [37]. Mineralization in PXE develops progressively over time [38]. Moreover, tissue calcification, in particular vascular calcification, is a hallmark of aging [39,40]. We thus questioned if PPi levels were affected by age and found significant positive correlations between PPi levels and age in PXE patients and carriers but not in controls. The correlation with age in PXE patients was also noted by Lefthériotis et al., though this was only present in female patients [19]. This was in contrast to the PXE murine model, where no correlation between age and the quantified purinergic metabolites in the plasma of Abcc6−/− and wild-type mice was found, which could have been due to species-specific differences or the small number of analyzed samples [13]. We currently cannot explain the increase in PPi with age in PXE patients and heterozygous carriers, and it remains to be seen whether this correlation can be confirmed in larger independent cohorts. Besides the variable distribution, the plasma PPi levels did not correlate significantly with Phenodex score severity, similar to the findings of Lefthérotis et al. for cumulative Phenodex scores [19]. This indicates that a snapshot of the plasma PPi is not a reliable marker for the risk stratification of patients, nor does it seem to be a good surrogate end point to be used in clinical trials. It could be that the extracellular tissue content of PPi correlates more to disease severity than the circulatory levels. However, no reliable methods are currently available to measure tissue PPi content. Further, it is already known that PPi is only one of the many factors involved in the calcification process in PXE. Several other pathophysiological mediators and mechanisms—Fetuin-A, MGP, alkaline phosphatase, magnesium and DNA damage response activation—have been described as contributing to the ectopic calcification in PXE and may be explanations for why no significant correlations can be found with the PXE phenotype when the correlation analysis focuses only on one mediator [41,42,43,44,45,46]. Though recently a significant correlation was found with the calcification propensity time (T50), the results of this pilot study await further confirmation in larger independent study cohorts [45]. It may be that a good correlation with the complex PXE phenotype can only be achieved using a multivariable score, taking into account all of the abovementioned mediators. Finally, it cannot be fully excluded that if PPi plasma levels are followed prospectively over time a correlation with the disease progression may be present. This may, however, be challenging to document in view of the slowly progressive nature of the PXE phenotype and the important interfamilial variability. For this, a validated clinical biomarker would be an important asset. Because of the relatively broad range of PPi plasma levels in patients and carriers, we wondered if the nature of the ABCC6 variants would impact the PPi levels. However, we could not detect any effect of the ABCC6 genotype. Clearly, the regulation of circulatory PPi is much more complex than just ABCC6 activity and involves other (epi)genomic and environmental factors [3,47]. In conclusion, we confirmed decreased PPi levels in PXE patients and heterozygous carriers in an independent cohort, though in several patients the PPi levels were within the heterozygous carrier or control range. This suggests that other pathophysiological factors are at play in at least some patients, which limits the use of PPi as a diagnostic marker and as a predictive biomarker for disease severity and progression. Our results should be evaluated in other independent cohorts of different ethnicities and genetic backgrounds. Moreover, in common disorders such as chronic kidney disease and diabetes mellitus, in which vascular calcification is correlated with increased risk of cardiovascular complications, the predictive value of PPi plasma levels for these adverse events should be evaluated [48]. To this end, the measurement protocol that we have optimized can be used in clinical routines, as it has a turnaround time of 4 h from sampling to result. Further, samples can be temporarily stored at −80° after processing without affecting the measurement results, making batch analysis possible. The limitations of this study include that it is a cross-sectional study and that we did not observe a correlation with the mineralization load. However, we found that the Phenodex scoring grasped the actual symptoms of the patients—particularly for the ocular and cardiovascular features—better than a calcification score and considered it more appropriate to evaluate whether PPi levels could be used as a clinical biomarker. For the genotype correlations, a limitation is the limited available knowledge on the effect of ABCC6 missense variants. These variants were all considered together, though we cannot exclude that their functional effects may be different. Further, there is currently limited knowledge on the effects of the variants that are classified as class 3 variants of unknown significance, and therefore we cannot be completely sure about their implication in PXE [27]. 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--- title: Sex Differences in Delayed Hospitalization in Patients with Non-ST-Segment Elevation Myocardial Infarction Undergoing New-Generation Drug-Eluting Stent Implantation authors: - Yong Hoon Kim - Ae-Young Her - Seung-Woon Rha - Cheol Ung Choi - Byoung Geol Choi - Ji Bak Kim - Soohyung Park - Dong Oh Kang - Ji Young Park - Woong Gil Choi - Sang-Ho Park - Myung Ho Jeong journal: Journal of Clinical Medicine year: 2023 pmcid: PMC10003952 doi: 10.3390/jcm12051982 license: CC BY 4.0 --- # Sex Differences in Delayed Hospitalization in Patients with Non-ST-Segment Elevation Myocardial Infarction Undergoing New-Generation Drug-Eluting Stent Implantation ## Abstract We compared the effects of sex differences in delayed hospitalization (symptom-to-door time [SDT], ≥24 h) on major clinical outcomes in patients with non-ST-segment elevation myocardial infarction after new-generation drug-eluting stent implantation. A total of 4593 patients were classified into groups with ($$n = 1276$$) and without delayed hospitalization (SDT < 24 h, $$n = 3317$$). Thereafter, these two groups were subdivided into male and female groups. The primary clinical outcomes were major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, recurrent myocardial infarction, repeat coronary revascularization, and stroke. The secondary clinical outcome was stent thrombosis. After multivariable- and propensity score-adjusted analyses, in-hospital mortalities were similar between the male and female groups in both the SDT < 24 h and SDT ≥ 24 h groups. However, during a 3-year follow-up period, in the SDT < 24 h group, all-cause death ($$p \leq 0.013$$ and $$p \leq 0.005$$, respectively) and cardiac death (CD, $$p \leq 0.015$$ and $$p \leq 0.008$$, respectively) rates were significantly higher in the female group than those in the male group. This may be related to the lower all-cause death and CD rates ($$p \leq 0.022$$ and $$p \leq 0.012$$, respectively) in the SDT < 24 h group than in the SDT ≥ 24 h group among male patients. Other outcomes were similar between the male and female groups and between the SDT < 24 h and SDT ≥ 24 h groups. In this prospective cohort study, female patients showed higher 3-year mortality, especially in the SDT < 24 h, compared to male patients. ## 1. Introduction Acute myocardial infarction (AMI) occurs due to thrombus formation resulting from a rupture or erosion of vulnerable atherosclerotic plaques [1]. The contributing risk factors for plaque instability include atherosclerotic risk factors and other diverse factors [2,3]. The sudden imbalance between myocardial oxygen consumption and demand is also an important cause of myocardial infarction and is caused by coronary artery spasm, coronary embolism, coronary arteritis, anemia, hypotension, tachycardia, hypertrophic cardiomyopathy, and severe aortic stenosis [4]. Females have different characteristics compared to men. For example, they generally have smaller body surface area and smaller coronary arteries, and they have various sex hormone-mediated factors [5]. Previous [6] and recent [7] reports showed that females presenting with acute myocardial infarction had higher mortality rates than males. Many other results between the male and female sexes after acute coronary syndrome (ACS) [8,9] were not consistent, and definite causative factors contributing to poorer clinical outcomes in females have not been definitely identified. Old age and increased incidence of diabetes mellitus (DM), chronic heart failure (HF), hypertension prior to MI [10], underestimation of cardiovascular risk for females [11], and delayed presentation with more atypical symptoms were suggested for the explanation of poorer results in females [12]. One report showed that atypical symptoms were associated with pre-hospital delay in 1894 in patients with acute ACS [13]. In patients with ST-segment elevation myocardial infarction (STEMI), rapid reperfusion of the infarct-related artery (IRA) reduces the mortality rate, and the maximum time delay from STEMI diagnosis to reperfusion of the IRA is 120 min [14]. Recent research [15] showed that long-term mortality is strongly related to total ischemic time rather than door-to-balloon time (DBT), because DTB has reached its limit of effect. In patients with non-STEMI (NSTEMI), the current guideline [16] recommends that an early coronary angiography [CAG] and percutaneous coronary intervention [PCI] within 24 h of admission (early invasive) is preferred over a delayed invasive strategy that includes at least one high-risk criterion. However, the optimal timing of PCI in NSTEMI is debatable [17] and is yet to be fully evaluated. Similar to the findings of Eggers’s study [17], one study [18] showed that the major clinical outcomes were not significantly different between the early invasive and delayed invasive groups in patients with NSTEMI and complex lesions after new-generation DES implantation. However, Fox et al. [ 19] suggested that a routine invasive strategy reduces long-term rates of cardiovascular death or MI, and the largest absolute effect is seen in higher-risk patients. Furthermore, only a few studies [20,21] have investigated the long-term clinical outcomes in patients who had delayed hospitalization (symptom-to-door time [SDT] ≥ 24 h). Therefore, in this study, we compared the 3-year effects of sex differences in delayed hospitalization on major clinical outcomes in patients with NSTEMI after new-generation drug-eluting stent implantation. ## 2.1. Study Population This was a non-randomized, multicenter, prospective cohort study. From the Korea AMI Registry-National Institute of Health (KAMIR-NIH) [22], a total of 13,104 AMI patients were recruited from November 2011 to December 2015. KAMIR-NIH [22] is a nationwide, prospective, multicenter registry comprising 20 high-volume PCI centers in the Republic of Korea. Its website is http://www.kamir.or.kr (accessed on 1 November 2011). At the time of initial enrollment, only patients aged 18 and over were included. The exclusion criteria of this study were as follows: patients who did not undergo PCI ($$n = 1369$$, $10.4\%$); those who underwent plain old balloon angioplasty ($$n = 739$$, $5.6\%$); unsuccessful PCI ($$n = 152$$, $1.2\%$); coronary artery bypass graft (CABG, $$n = 44$$, $0.3\%$); or BMS, or first-generation (1G)-DES implantation ($$n = 708$$, $5.4\%$); those who had STEMI ($$n = 5365$$, $40.9\%$); or those who were lost to follow-up ($$n = 134$$, $1.0\%$) (Figure 1). Overall, 4593 patients with NSTEMI who underwent successful PCI using new-generation DES were enrolled and classified into SDT < 24 h ($$n = 3317$$, $72.2\%$) and SDT ≥ 24 h ($$n = 1276$$, $27.8\%$) groups, and these two groups were subdivided into male (group A [$$n = 2492$$] and group C [$$n = 849$$]) and female (group B [$$n = 825$$] and group D [$$n = 427$$]) subgroups (Figure 1). We described the types of DES new-generation that were used during the PCI within the footnotes of Table 1. This study was approved by the Ethics Committee of each participating center and the Chonnam National University Hospital Institutional Review Board Ethics Committee (CNUH-2011-172) according to the ethical guidelines of the 2004 Declaration of Helsinki. All 4593 patients included in the study provided written informed consent before enrollment. They finished their 3-year clinical follow-up through face-to-face interviews, phone calls, and chart reviews. From all participating PCI centers, the enrolled data were collected using a web-based system. Event adjudication processes have been described in a previous publication by KAMIR investigators [22]; event adjudication processes have been mentioned. ## 2.2. Percutaneous Coronary Intervention and Medical Treatment After conventional CAG via a transfemoral or transradial approach [23], 200–300 mg of aspirin, 300–600 mg of clopidogrel, 180 mg of ticagrelor, and 60 mg of prasugrel were prescribed as the loading doses before PCI. After PCI, 100 mg of aspirin was recommended for all patients, combined 75 mg of clopidogrel once daily, 90 mg of ticagrelor twice daily, or 5–10 mg of prasugrel once daily for a minimum of one year. The individual operators were able to choose the access site, revascularization strategy, and DES without any restrictions. ## 2.3. Study Definitions and Clinical Outcomes Based on current guidelines, NSTEMI was defined as the absence of persistent STE with increased cardiac biomarker levels in an appropriate clinical context [4,24]. In the IRA, successful PCI was defined as <$30\%$ residual stenosis and thrombolysis of MI flow grade 3. To obtain more precise results, a Global Registry of Acute Coronary Events (GRACE) risk score [25] was calculated for all study population. Patients with SDT ≥ 24 h were included in the delayed hospitalization group based on the findings of a recent report [20]. In our study, we defined the symptom onset time as the time of onset of the last sustained chest pain of the individual patients [26]. We also defined typical chest pain as substernal chest discomfort of characteristic quality and duration, triggered by exertion or emotional stress, and relieved by rest or nitroglycerin use [24]. Atypical chest pain was defined as chest pain that was inconsistent with the characteristics of typical chest pain. In this study, major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, recurrent MI (re-MI), any repeat coronary revascularization, and stroke were considered as the primary clinical outcome. Target lesion revascularization, target vessel revascularization (TVR), and non-TVR were included in the criteria for any repeat revascularization. The event rate of definite or probable stent thrombosis was considered as the secondary clinical outcome. When a definite non-cardiac cause was not approved, all-cause death was considered cardiac death (CD) [27]. In a previous report, we defined the definitions of re-MI, target lesion revascularization, TVR, and non-TVR [28]. We defined the definition of stroke according to the American Heart Association/American Stroke Association guidelines [29], such as an acute cerebrovascular event resulting in death or neurological deficit for >24 h or the presence of acute infarction demonstrated by brain imaging studies. By guidelines suggested by the Academic Research Consortium, ST was defined [30]. ## 2.4. Statistical Analyses We used the SPSS software version 20 (IBM, Armonk, NY, USA) to perform statistical analyses. For continuous variables, intergroup differences were evaluated using the unpaired t-test, and data were expressed as mean ± standard deviation or median (interquartile range). For categorical variables, intergroup differences were analyzed using the chi-square or Fisher’s exact test, and data were expressed as counts and percentages. Both in the groups with or without delayed hospitalization, univariate analyses were performed for all variables with the assumption that p value at <0.05 is a significant value. Subsequently, a multicollinearity test [31] was performed for the included variables to confirm non-collinearity among them (Table S1). Among the variables, variance inflation factor values were calculated to measure the degree of multicollinearity. A high correlation was suspected when the variance inflation factor value exceeds 5 [32]. Moreover, when the tolerance value was less than 0.1 [33] or the condition index was more than 10 [32], multicollinearity was suspected [33]. In this study, the following variables were included in the multivariable Cox regression analysis; age, left ventricular ejection fraction (LVEF), body mass index, diastolic blood pressure, DBT, cardiogenic shock, cardiopulmonary resuscitation (CPR) on admission, atypical chest pain, dyspnea, Q-wave, ST-segment depression, and T-wave inversion on electrocardiogram; Killip class II/III; non-PCI center; PCI center; hypertension; diabetes mellitus; previous heart failure; previous stroke; current smoker; levels of peak creatine kinase myocardial band (CK-MB); and blood glucose, serum creatinine, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol (Table S1). Moreover, to correct the confounding variables, a propensity score (PS)-adjusted analysis was performed using a logistic regression model. All baseline characteristics shown in Table 1 were included in the PS-adjusted analysis. The c-statistic for the PS-matched analysis in this study was 0.710. Using the nearest available pair-matching method in a 1:1 fashion, patients in the SDT ≥ 24 h group were matched to those in the SDT < 24 h group. The used caliper width was 0.01. Table S2 shows baseline characteristics between the male and female groups before and after PS-matched analysis. Various clinical outcomes were estimated using Kaplan–Meier curve analysis and long-rank was used to compare the group differences. A calculated p value at <0.05 is considered statistically significant. Table S3 shows the results of the collinearity test for MACCE between the <24 h and ≥24 h groups. ## 3.1. Baseline Characteristics Table 1, Tables S2, S4 and S5 show baseline characteristics. In both the SDT < 24 h and SDT ≥ 24 h groups, the mean values of body mass index, mean diameter of deployed stents, number of current smokers, prasugrel as a discharge medication, transradial approach, and use of intravascular ultrasound and optical coherence tomography were higher in the male group than in the female group. In contrast, the mean age, mean value of blood glucose, GRACE risk score, and number of patients with atypical chest pain who showed ST-segment depression and T-wave inversion on EKG, Killip classes II and III, hypertension, diabetes mellitus, previous history of heart failure and stroke, clopidogrel as a discharge medication, the left anterior descending coronary artery as a treated vessel, and a high GRACE risk score (>140) were higher in the female group. Figure S1 shows diverse causes of AMI. ## 3.2. Clinical Outcomes Table 2 and Table 3, Figure 2a–h show 3-year major clinical outcomes. After multivariable-adjusted analysis, in-hospital all-cause death rates were not significantly different between the male and female groups in both the SDT < 24 h (adjusted hazard ratio [aHR], 1.034; $$p \leq 0.913$$) and SDT ≥ 24 h (aHR, 1.218; $$p \leq 0.707$$) groups. Similarly, in-hospital CD rates were not significantly different between the male and female groups in both the SDT < 24 h (aHR, 1.324; $$p \leq 0.420$$) and SDT ≥ 24 h (aHR, 1.011; $$p \leq 0.984$$) groups. These results were confirmed by PS-adjusted analyses. During a 3-year follow-up period, in the < 24 h group, multivariable-adjusted analysis revealed that MACCE (aHR, 1.181; $95\%$ confidence interval [CI], 0.982–1.422; $$p \leq 0.098$$), non-CD (NCD, aHR, 1.226; $$p \leq 0.330$$), recurrent MI (aHR, 1.390; $$p \leq 0.112$$), any repeat revascularization (aHR, 1.038; $$p \leq 0.785$$), stroke (aHR, 1.562; $$p \leq 0.109$$), and ST (aHR, 1.561; $$p \leq 0.390$$) rates were not significantly different between the male and female groups. However, all-cause death (aHR, 1.392; $$p \leq 0.013$$) and CD (aHR, 1.520; $$p \leq 0.015$$) rates were significantly higher in the female group than in the male group. These results were confirmed by the PS-adjusted analysis. In the SDT ≥ 24 h group, after multivariable-adjusted and PS-adjusted analyses, MACCE ($$p \leq 0.927$$ and $$p \leq 0.561$$, respectively), all-cause death ($$p \leq 0.075$$ and $$p \leq 0.087$$, respectively), CD ($$p \leq 0.079$$ and $$p \leq 0.095$$, respectively), NCD ($$p \leq 0.522$$ and $$p \leq 0.245$$, respectively), recurrent MI ($$p \leq 0.772$$ and $$p \leq 0.746$$, respectively), any repeat revascularization ($$p \leq 0.132$$ and $$p \leq 0.101$$, respectively), stroke ($$p \leq 0.088$$ and $$p \leq 0.198$$, respectively), and ST ($$p \leq 0.655$$ and $$p \leq 0.758$$, respectively) rates were not significantly different between the male and female groups. In the total study population, after the multivariable-adjusted and PS-adjusted analyses, all-cause death ($$p \leq 0.001$$ and $$p \leq 0.002$$, respectively) and CD ($$p \leq 0.002$$ and $$p \leq 0.004$$, respectively) were significantly higher in the female group than in the male group. In Table 3, after multivariable-adjusted analysis, in-hospital all-cause death rates were not significantly different between the SDT < 24 h and SDT ≥ 24 h groups in both the male (aHR, 1.425; $$p \leq 0.327$$) and female (aHR, 1.143; $$p \leq 0.813$$) groups. Moreover, in-hospital CD rates were not significantly different between the SDT < 24 h and SDT ≥ 24 h groups in both the male (aHR, 2.036; $$p \leq 0.101$$) and SDT ≥ 24 h (aHR, 1.618; $$p \leq 0.432$$) groups. These results were confirmed by PS-adjusted analyses. During a 3-year follow-up period in the male group, the multivariable-adjusted analysis revealed that all-cause death (aHR, 1.450; $$p \leq 0.010$$) and CD (aHR, 1.542; $$p \leq 0.022$$) rates were significantly higher in the SDT ≥ 24 h group than those in the SDT < 24 h group. However, MACCE, NCD, recurrent MI, any repeat revascularization, stroke, and ST rates were not significantly different between the SDT < 24 h and SDT ≥ 24 h groups. These results were confirmed by the PS-adjusted analysis. In the female group, after multivariable-adjusted and PS-adjusted analyses, MACCE ($$p \leq 0.483$$ and $$p \leq 0.385$$, respectively), all-cause death ($$p \leq 0.225$$ and $$p \leq 0.362$$, respectively), CD ($$p \leq 0.205$$ and $$p \leq 0.216$$, respectively), NCD ($$p \leq 0.656$$ and $$p \leq 0.956$$, respectively), recurrent MI ($$p \leq 0.481$$ and $$p \leq 0.520$$, respectively), any repeat revascularization ($$p \leq 0.102$$ and $$p \leq 0.352$$, respectively), stroke ($$p \leq 0.086$$ and $$p \leq 0.093$$, respectively), and ST ($$p \leq 0.716$$ and $$p \leq 0.634$$, respectively) rates were not significantly different between the SDT < 24 h and SDT ≥ 24 h groups. In the total study population, after multivariable-adjusted and PS-adjusted analyses, all-cause death ($$p \leq 0.001$$ and $$p \leq 0.003$$, respectively) and CD ($$p \leq 0.002$$ and $$p \leq 0.003$$, respectively) were significantly higher in the SDT ≥ 24 h group than in the SDT < 24 h group. Table S6 shows the independent predictors of MACCE. Old age (≥65 years, $$p \leq 0.019$$ and $$p \leq 0.012$$, respectively), reduced LVEF (<$50\%$, $$p \leq 0.014$$ and $p \leq 0.001$, respectively), cardiogenic shock ($$p \leq 0.041$$ and $$p \leq 0.021$$, respectively), CPR on admission ($p \leq 0.001$ and $p \leq 0.001$, respectively), atypical chest pain ($p \leq 0.001$ and $p \leq 0.001$, respectively), EMS use ($$p \leq 0.030$$ and $$p \leq 0.039$$, respectively), and high GRACE risk scores (>140, $p \leq 0.001$ and $p \leq 0.001$, respectively) were common independent predictors of MACCE in both the SDT < 24 h and SDT ≥ 24 h groups. As shown in Table S7, old age ($p \leq 0.001$ and $p \leq 0.001$, respectively), reduced LVEF ($p \leq 0.001$ and $p \leq 0.001$, respectively), CPR on admission ($p \leq 0.001$ and $p \leq 0.001$, respectively), atypical chest pain ($p \leq 0.001$ and $p \leq 0.001$, respectively), and high GRACE risk scores ($$p \leq 0.004$$ and $p \leq 0.001$, respectively) were common independent predictors of all-cause death in both SDT < 24 h and SDT ≥ 24 h groups. Figures S2 and S3 show the results of subgroup analyses for MACCE and all-cause death in the SDT < 24 h and SDT ≥ 24 h groups using the Cox logistic regression model. In the SDT ≥ 24 h group, all subgroups, except for those showing significant p-for-interaction, demonstrated comparable MACCE and all-cause death rates between the male and female groups. In the SDT < 24 h group, however, the female group had a higher all-cause death rate compared with the male group in patients with young age (<65 years, $$p \leq 0.011$$) and hypertension ($$p \leq 0.026$$). ## 4. Discussion The main findings of this prospective observational study after multivariable- and PS-adjusted analyses were as follows: [1] in-hospital mortalities (all-cause death and CD) were not significantly different between the male and female groups in both the SDT < 24 h and SDT ≥ 24 h groups; [2] however, during a 3-year follow-up period in the SDT < 24 h group, all-cause death and CD rates were significantly higher in the female group than those in the male group; [3] furthermore, in the male group, all-cause death and CD rates were significantly lower in the SDT < 24 h group than those in the SDT ≥ 24 h group; [4] MACCE, non-CD, recurrent MI, any repeat revascularization, stroke, and ST rates were similar between the male and female groups and between SDT < 24 h and SDT ≥ 24 h groups; [5] old age, reduced LVEF, CPR on admission, atypical chest pain, and high GRACE risk scores were common independent predictors of MACCE and all-cause death in both the SDT < 24 h and SDT ≥ 24 h groups. The effects of delayed hospitalization on long-term clinical outcomes in patients with NSTEMI are not well-illuminated, and very limited data are available to date [20,21]. Additionally, the effects of sex differences in delayed hospitalization on long-term clinical outcomes in patients with NSTEMI who were confined to receiving new-generation drug-eluting stent implantation have not been reported. Materic et al. [ 7] reported that all-cause mortality was higher in females (adjusted odds ratio, 1.03; $95\%$ CI, 1.02–1.04; $p \leq 0.001$) than in males among 7,026,432 AMI hospitalizations between 2004 and 2015 in the National Inpatient Sample. In our study, in the SDT < 24 h group and total study population, all-cause death and CD were significantly higher in females than in males. In the SDT ≥ 24 h group, these mortalities were also numerically higher in the female group without reaching statistical significance compared with the male group (Table 2). In other words, regarding these results, we may consider that the long-term clinical outcome of the female with NSTEMI after new-generation PCI implantation could be worse than that of the male, regardless of SDT. In particular, the worse long-term clinical outcome was more obvious in the SDT < 24 h group than in the SDT ≥ 24 h group. Additionally, different clinical outcomes according to sex differences in our study were related to relatively low all-cause death and CD rates in the SDT < 24 h group compared to the SDT ≥ 24 h group in male patients (Table 3). It is suggested that females hospitalized with AMI have a higher chance of having worse outcomes than males [8,34]. Females with AMI are older at presentation, have more comorbidity, and present later and with more atypical symptoms [10,11,12,35]. In our study, both in the SDT < 24 h and SDT ≥ 24 h groups, the mean ages of the female group were significantly higher than those in the male group (70.9 ± 9.8 years vs. 61.0 ± 11.6 years; $p \leq 0.001$, 72.7 ± 9.2 years vs. 63.4 ± 11.9 years; $p \leq 0.001$, respectively, Table 1). In both the SDT < 24 h and SDT ≥ 24 h groups, the number of patients with hypertension ($p \leq 0.001$ and $p \leq 0.001$, respectively), DM (as the abbreviation ”DM” was introduced in the introduction section) ($p \leq 0.001$ and $$p \leq 0.005$$, respectively), high GRACE risk scores ($p \leq 0.001$ and $p \leq 0.001$, respectively), and the left anterior descending artery as a treated vessel ($$p \leq 0.012$$ and $$p \leq 0.002$$, respectively) was also significantly higher in the female group than in the male group (Table 1). Moreover, the number of patients with atypical chest pain was higher in the female group than in the male group ($18.1\%$ vs. $12.2\%$, $p \leq 0.001$, and $27.9\%$ vs. $20.8\%$, $$p \leq 0.006$$, respectively; Table 1). Old age and atypical chest pain were significant independent predictors of MACCE and all-cause death in both the SDT < 24 h and SDT ≥ 24 h groups (Tables S6 and S7). A recent report [36] (Seems like it could be omitted in the context) showed that females were more likely than males to have atypical symptoms and that women were less likely than males to recognize that their symptoms were due to AMI. Our results showed that all-cause death and CD rates in the female group were higher than those in the male group in the SDT < 24 h group. In patients with AMI, any delay from symptom onset to treatment is related to a further increase in infarct size and mortality [37] SDT and DBT make up the total ischemic time, and total ischemic time is suggested to be a better predictor of mortality and infarct size than DBT in patients with STEMI [15,38]. Foo et al. [ 39] showed that the impact of DBT reduction tends to be more significant when the SDT is longer than when it is shorter. In our study, DBT was not an independent predictor of MACCE in both the SDT < 24 h ($$p \leq 0.311$$) and SDT ≥ 24 h ($$p \leq 0.176$$) groups. Additionally, DBT was not an independent predictor of all-cause death in both the SDT < 24 h ($$p \leq 0.817$$) and SDT ≥ 24 h ($$p \leq 0.203$$) groups. This result is consistent with the previous results [20,40]. Hence, efforts to reduce delayed hospitalization may be important in reducing mortality in patients with NSTEMI [20]. In our study, although the mean DBT values between the male and female groups in both the SDT < 24 h and SDT ≥ 24 h groups were not significantly different (Table 1), in the male group, the 3-year all-cause death (aHR, 1.450; $$p \leq 0.010$$) and CD (aHR, 1.542; $$p \leq 0.022$$) rates were higher in the SDT ≥ 24 h group than in the SDT < 24 h group. Similarly, in the total study population, the 3-year all-cause death (aHR, 1.433; $$p \leq 0.001$$) and CD (aHR, 1.574; $$p \leq 0.002$$) rates were higher in the SDT ≥ 24 h group than in the SDT < 24 h group. However, in the SDT ≥ 24 h group, the 3-year primary and secondary clinical outcomes (Table 2) were not significantly different between the male and female patients. Regarding these results, as mentioned [20,37], SDT could be considered a more important factor than sex difference, even if female patients were older at presentation and had higher comorbidity and atypical chest pain. Prehospital delay is the total amount of time taken by patients to present to the emergency department following the onset of acute symptoms [13]. In a recent report [20], patients with NSTEMI and delayed hospitalization had a higher long-term all-cause mortality ($17.0\%$ vs. $10.5\%$; $p \leq 0.001$) than those without delayed hospitalization. Because they [20] included as many all-comers as possible, these data are valuable in showing the clinical importance of pre-hospital delay in patients with NSTEMI. However, approximately $15\%$ of this study population did not receive PCI or had unsuccessful PCI. Furthermore, patients who received bare-metal stents or first-generation DES were included. To date, second-generation (2G)-DES is the preferred revascularization option because it can reduce restenosis and mortality rates compared with 1G-DES during a long-term follow-up period [41]. In these areas, their research [20] has limitations in terms of reflecting the current real-world practice and demonstrating the long-term prognosis of NSTEMI patients. To overcome these limitations, we excluded patients who did not undergo PCI or who received bare-metal stents or first-generation DES, as shown in Figure 1. In our subgroup analysis, female patients in the SDT < 24 h group who were younger (<65 years) and hypertensive had a higher all-cause death rate than male patients (Figure S2). Champney et al. [ 42] demonstrated that for both STEMI and NSTEMI, the younger the patient’s age, the higher the mortality risk for women compared to males. Younger patients tend to have more risk factors, such as smoking, obesity, hypertension, dyslipidemia, and a family history of coronary artery disease [43]. In our study, in-hospital mortality, including all-cause death and CD, was not significantly different between the male and female groups in both the SDT < 24 h and SDT ≥ 24 h groups (Table 2). Despite this debate, Heer et al. [ 44] reported that there were no sex-related differences in in-hospital mortality among 48,215 patients undergoing PCI for NSTEMI between 2007 and the end of 2009. Another registry study [45] also showed that in-hospital mortality did not differ according to sex (adjusted odds ratio [OR], 0.92; $95\%$ CI, 0.57–1.48). As far as we know, no specific large-scale study exists, and we could not provide comparative results between our study and other studies. In addition, the population size was insufficient to conclude that the KAMIR-NIH data included 20 tertiary, high-volume university hospitals. Hence, we believe that our results may be the first to compare the long-term clinical outcomes between the SDT < 24 h and SDT ≥ 24 h groups in male and female patients after the successful implantation of new-generation DES and could provide valuable information to cardiologists. This study had some limitations. Delayed hospitalization was divided into three phases: patient decision, time to first medical contact, and transportation phases [46]. However, the time variables included in these phases were not included in the KAMIR-NIH data. Hence, information concerning transfers, distance to the nearest hospital, rural vs. urban residence, and the presence or absence of large differences between hospitals in the percentage of patients with delayed hospitalization were not available in the KAMIR-NIH data because these variables were not mandatory in this registry data. Hence, this information was not included in the analysis. This is a major shortcoming of the present study. Second, in this study, we defined delayed hospitalization as SDT ≥ 24 h. However, the clinical outcomes between the male and female groups in the SDT < 24 h and SDT ≥ 24 h groups can be altered according to different definitions of SDT [47]. Third, some subgroups had relatively small sample sizes; hence, their analyses may be underpowered to detect clinically meaningful differences. Fourth, there may have been some under-reported and/or missing data. Fifth, because of the limitations of the medical insurance system in the Republic of Korea, the use of fractional flow reserves to estimate intermediate lesions was low in this study (Table 1). Sixth, the 3-year follow-up period in this study was relatively short for estimating the long-term clinical outcomes. Finally, we believe that both delayed hospitalization and genetic factors [48] may have had negative effects, particularly in the female group. However, in this study, we did not take into account the aspect of genetic factors, so we were unable to fully evaluate their impact. This is other weak point of this study. ## 5. Conclusions In this nonrandomized, multicenter, prospective cohort study, in-hospital mortalities were similar between the male and female groups. In our study, females with NSTEMI are older at presentation, have more comorbidity, and present later and with more atypical symptoms, and these factors were independent predictors of mortality. This led to lower all-cause death and CD rates ($$p \leq 0.022$$ and $$p \leq 0.012$$, respectively) in the SDT < 24 h group than in the SDT ≥ 24 h group among male patients. Hence, female patients showed higher 3-year mortality, especially in the SDT < 24 h group and in the total study population, than male patients. However, further large-scale studies are required to confirm our results. ## References 1. 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