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Frontal fibrosing alopecia: A review of disease pathogenesis

Frontal fibrosing alopecia (FFA) is a primary patterned cicatricial alopecia that mostly affects postmenopausal women and causes frontotemporal hairline regression and eyebrow loss. Although the incidence of FFA has increased worldwide over the last decade, its etiology and pathology are still unclear. We cover the latest findings on its pathophysiology, including immunomodulation, neurogenic inflammation, and genetic regulation, to provide more alternatives for current clinical treatment. A persistent inflammatory response and immune privilege (IP) collapse develop and lead to epithelial hair follicle stem cells (eHFSCs) destruction and epithelial-mesenchymal transition (EMT) in the bulge area, which is the key process in FFA pathogenesis. Eventually, fibrous tissue replaces normal epithelial tissue and fills the entire hair follicle (HF). In addition, some familial reports and genome-wide association studies suggest a genetic susceptibility or epigenetic mechanism for the onset of FFA. The incidence of FFA increases sharply in postmenopausal women, and many FFA patients also suffer from female pattern hair loss in clinical observation, which suggests a potential association between FFA and steroid hormones. Sun exposure and topical allergens may also be triggers of FFA, but this conjecture has not been proven. More evidence and cohort studies are needed to help us understand the pathogenesis of this disease.

Introduction
Frontal fibrosing alopecia (FFA) is a type of primary lymphocytic cicatricial alopecia that leads to irreversible alopecia. In 1997, Kossard described FFA as an uncommon frontal variant of lichen planopilaris (LPP) (1). The incidence of this disease has increased worldwide since Kossard first described it in 1994 (2). Previously, the disease was usually reported in postmenopausal women. The average age of diagnosis of FFA is approximately 56 years. However, an increase in premenopausal women with FFA was observed in the same survey, and an earlier age of onset was found in some sporadic cases (3). With the advent of global aging, we need to improve our understanding of this cicatricial alopecia to address its potential threat to human health.
Frontal fibrosing alopecia (FFA) is a systemic skin disease with a variety of clinical manifestations and characterized by receding frontal and temporoparietal hairlines (3). The receding hairline of FFA has specific pattern characteristics and other common symptoms, such as facial papules due to vellus hair involvement. The alopecia region looks like a gleaming, atrophic, pale band of hair loss (4). Hairline recession is usually bilateral and symmetric, but some reports have described asymmetric forms. Frontal fibrosing alopecia has been classified into three clinical patterns based on frontal hairline recession (Figure 1 and Table 1) (5).
The slow progression of FFA results in inaccuracies in estimating the age of onset, leading to errors and interference in clinical retrospective analysis. Currently, there are few reports on the pathogenesis of FFA. We reviewed the current literature for immunomodulation, neurogenic inflammation, hormonal and metabolism, genetic and external factors to help clinicians better understand and explore the pathogenesis of this disease.

Immunomodulation
Many reports have revealed the role of immune cell and substance-mediated inflammatory responses in the pathogenesis of FFA (6). The current findings suggest that several major immune-mediated and inflammatory mechanisms are involved in the development of FFA/LPP.

Inflammation and immune privilege collapse
Histological findings in FFA show inflammatory cell infiltration around lesioned LPP hair follicles (HFs), especially near the bulge area and infundibulum (Figure 2), which is characterized by a rise in CD8 + cytotoxic T cells and plasmacytoid dendritic cells (6). Physiologically, epithelial hair follicle stem cells (eHFSCs) play an essential role in regulating the hair follicle cycle and entering the growth phase. HF immunity protects eHFSCs from potential autoimmune responses by downregulating the MHC class I and class II pathways (7,8). Anagen hair bulbs are one of the few immunologically privileged tissues in the mammalian body, with negative MHC class I pathways and an immunosuppressive microenvironment. Compared to normal HFs, the expression of key markers for bulge IP maintenance, TGFβ2 and CD200 expression is reduced, whereas the main indications of IP collapse are upregulated in Frontiers in Medicine 02 frontiersin.org inflammatory lesions of LPP HFs, such as MHC class I and II β2-microglobulin (6).
Moreover, LPP has shown a reduction in Ki-67 labeling and downregulation of keratin 15, a marker of hair follicle epithelial progenitor cells in the bulge area (9, 10). Previous studies have suggested that interferon-γ (IFN-γ) may play an essential role in inducing IP collapse in HF bulge area and the ensuing damage of eHFSCs caused by the immune system (6,11). This causes the entire follicle unit to become progressively fibrotic and unable to regenerate completely. However, it is unclear what triggers these inflammatory processes, and whether IP collapse is a major event before the inflammatory response or an extra reaction after the inflammatory response.

Epithelial-mesenchymal transition
Epithelial-mesenchymal transition (EMT) is considered a normal component of embryogenesis, tissue reconstruction and wound healing, but it also occurs in pathological processes, including epithelial cell malignant transformation, cancer metastasis, and other fibrosis-related illnesses (12, 13). The loss and destruction of eHFSCs alone is not sufficient to explain the typical appearance of associated scarring. In fact, when eHFSCs were selectively ablated in mice, the resulting hair loss was not accompanied by scarring (14). The EMT marker Snail1 is positive in the dermis of lesions in FFA, enhancing the idea that EMT is involved in the pathogenesis of FFA (15,16). Moreover, there are fibroblastoid cells within the lesional bulge epithelium and putative collagen filaments within the cytoplasm of bulge keratinocytes. Lesional FFA HFs show cells within the bulge epithelium that are abnormally positive for EMT markers, such as Snail1, Snail2, Zeb1 and TWIST1, mesenchymal markers, vimentin and fibronectin, and a cadherin switch (downregulation of E-cadherin and upregulation of N-cadherin) (17,18).  Peroxisome proliferator-activated receptor γ and mammalian target of rapamycin pathway peroxisome proliferator-activated receptor γ (PPAR-γ) is involved in lipid metabolism and the differentiation and maturation of sebocytes (19). The reduction of its activity causes fibrosis (10). Karnik and his colleagues first proposed the concept of PPAR-γ and lipid metabolism in the pathogenesis of LPP. By monitoring the genetic and metabolic levels of LPP patients, they observed disturbances in fatty acid metabolism and a decrease in peroxisome and cholesterol production, which likely contributed to the accumulation of proinflammatory lipids in the patient's hair follicles, ultimately leading to the infiltration of inflammatory cells in the bulge area (20). Previously, a new PPAR-γ modulator, N-acetyl-GED-0507-34-Levo (NAGED), was shown to not only reduce the invasion attack of inflammation on eminence but also partially restore the immune privilege of eminence (21). It also partially shows the effect of reversing the phenotype of EMT after induction of EMT in vitro (22,23). PPAR-γ plays such an extensive role in the pathogenesis of FFA that we have to dedicate more attention to it.
A previous study revealed that PPAR-γ signaling was critical for the survival of eHFSCs in mice, suggesting that the loss of this receptor targeted by the keratin 15 (K15) promoter in these stem cells leads to cicatricial alopecia-like manifestations (20). However, a gene expression investigation using laser capture microdissection revealed no significant differences in PPAR expression between lesional and non-lesional bulge epithelium in the same LPP patient, which suggests that we need to find some predisposing factors in the eHFSCs region or signals other than PPAR-γ (23).
Due to the unique role of PPAR-γ in fat metabolism and hair follicle growth, another pathway, the mammalian target of rapamycin (mTOR) signaling pathway, also plays a role in these two pathways. The mTOR signaling pathway plays various roles in the immune system and stem cell proliferation (24). Previous studies have revealed that mTOR signaling works as a modulator of PPAR-γ activity and lipid homeostasis. A possible mechanism for this regulatory effect on PPAR-γ is that mTOR plays a role in the maximal transcriptional activity of a subset of PPAR-γ genes (25). A recent study showed that the PPARγ/mTOR signaling pathway in microglia inhibits tumor necrosis factor-α (TNF-α) and interleukin-β (IL-β) expression (26). Moreover, immunohistochemical assessment of scalp samples from patients with FFA/LPP showed that the expression of all proteins of the mTOR signaling pathway was decreased in the lesional epidermis of patients (24). More studies are needed to determine how the mTOR and PPAR-γ pathways, alone or in combination, contribute to the pathogenesis of FFA.
The PPAR-γ pathway can also suppress EMT, another critical part of FFA pathogenesis. A previous study successfully modeled EMT using a group of EMT-promoting agents in healthy human eHFSCs in full-length HF organ culture ex vivo. In this model, PPAR-γ agonists have been found to inhibit or even reverse EMT to some extent (18,27) and have an antifibrotic effect in mouse models of systemic sclerosis by reducing transforming growth factor-β (TGF-β), which promotes the formation of collagen (28)(29)(30)(31). TGF-β has multiple functions, such as driving inflammation, fibrosis, and cell differentiation. A recent report indicated that PPAR-γ activation in TGF-β transgenic mice inhibits the TGFβ-STAT3 and TGFβ-EGR1 transcriptional activation pathways in some fibrotic diseases, providing strong support for the role of the PPAR-γ/TGF-β pathway in FFA (32).

Neurogenic inflammation
Psycho-emotional stress has been suggested as a trigger of follicle inflammation in FFA. It is worth noting that there have been reports of LPP/FFA development after hair transplantation (33), in which the Koebner phenomenon or the generation of a proinflammatory environment may impair the IP of hair follicles after transplantation. Experiments on mice have shown that stress stimulation can induce neurogenic inflammation around hair follicles, lead to an increase in mast cell degranulation, and produce inhibitive factors, such as substance P (SP) (34).
The role of neuropeptides in skin diseases has been demonstrated in many studies, and substantial evidence suggests that sensory neuropeptides play an essential role in the production and maintenance of the inflammatory cascade that causes chronic inflammation of the skin and some persistent symptoms in some diseases. Thus, calcitonin gene-related peptide (CGRP), which may be involved in lipid metabolism, has attracted the attention of some researchers (35). In many chronic inflammatory conditions, CGRP is elevated, and PPARγ is generally decreased (36, 37). Previous studies have shown that CGRP has immunosuppressive effects and helps protect eHFSCs from inflammatory factors such as INF-γ. However, in the same study, the upregulation of CGRP failed to restore IP of the HF (38).
In addition to PPAR-γ, SP induces the production and release of the proinflammatory cytokines IL-1, IL-6, and TNFα through the neurokinin (NK) 1 receptor signaling pathway. The upregulation of substance P expression around the bulge can mediate neurogenic inflammation and EMT. The expression of substance P was different between LPP/FFA lesional and non-lesional HFs (39). In general, LPP/FFA may have multiple pathogenic mechanisms associated with neurogenic inflammation, suggesting potential applications for new treatments.

Hormones and metabolism
Due to the age of onset of FFA, it is vital to explore the role of steroid hormones in the pathogenesis of FFA.
The mechanism of androgen action in hair loss has been previously described, while the exact mechanism of estrogen in hair growth and alopecia remains controversial. After menopause, circulating estrogen levels drop, and androgen levels rise. In the vast majority of reported cases, the onset of FFA occurs after menopause, but more recent cases of FFA have been reported in premenopausal women and men, prompting researchers to focus on the role of high androgen levels vs. estrogen in the pathogenesis (3). A recent retrospective study of 43 premenopausal women with FFA showed no abnormal sex hormone levels (40). Menopausal age, contraceptive history, and response to hormone replacement therapy were not significantly associated with the occurrence of FFA (41).
Many women with FFA also have female pattern hair loss (FPHL), and similarly, many men with FFA have male androgenetic alopecia (MAGA). A large retrospective study of 343 women and 12 men in Spain showed that 40% of affected women had concurrent FPHL and 67% of affected men had concurrent MAGA. FPHL/MAGA is a non-cicatricial alopecia disorder that is androgen-dependent in genetically susceptible individuals (42). Androgen deficiency was found in 32 of 168 FFA patients in a study specifically focused on hormonal and endocrine dysfunction (43). Dehydroepiandrosterone (DHEA) plays an essential role in androgen and estrogen biosynthesis, possesses the function of regulating PPAR and has also been found to have strong antifibrotic effects (44). Thus, downregulation of DHEA and androgens may lead to a profibrotic state of FFA. A study involving 30 female FFA patients and 34 healthy controls showed that DHEAS and androstenedione serum levels were significantly lower in FFA patients than in healthy controls (45). These studies raise the question of whether 5α reductase inhibitors are effective in treating FFA. The efficacy of 5α reductase inhibitors may be exaggerated due to the presence of FPHL/MAGA in many cases (46,47). Therefore, it is not clear whether and exactly how 5α reductase inhibitor therapy is beneficial to FFA.

Genetic
In previous studies, we could not establish a genetic link to FFA, although there were some reports of familial clustering in FFA patients. In 2019, Christos Tziotzios et al. conducted a genome-wide association study that found associations with FFA at four genomic loci: 2p22.2, 6P21.1, 8Q24.22, and 15Q2.1. Within loci 6P21.1 and 2p22.1, fine mapping showed associations with the HLA-B * 07:02 allele and a presumed casual missense variant in CYP1B1, encoding homologous heterospecifics and hormoneprocessing enzymes. CYP1B1 is a widely expressed gene that codes for the cytochrome P450 1B1 microsomal enzyme (also known as exogenous monooxygenase and aromatic hydrocarbon hydroxylase). This enzyme participates in the oxidative metabolism of estradiol and estrogen into the corresponding hydroxylated catechol estrogen. Therefore, it can be speculated that increased female exposure to CYP1B1 substrates may have an active role in the development of FFA (48).
Human leucocyte antigen (HLA) profiling of a familial cluster (7 FFA members and 4 unaffected members) and 7 sporadic cases revealed two susceptible haplotypes in familial cases (C * 17:01:01:02/B * 42:01:01 and C * 07:02:01:03/B * 07:02:01:01), and three unaffected family members also had the haplotype (49). This provides us with a possible pathogenesis theory, namely, the incidence of the disease in families may indicate exposure to a common environmental trigger, possibly enhanced by hereditary susceptibility.

Environmental factors
In the past 10-15 years, the incidence of FFA has increased year by year. It remains to be seen whether this increase is related to the improvement of the diagnosis level of dermatologists and the gradual increase in understanding of the disease. The rising incidence has suggested that FFA may be related to some exposure factors, similar to basic chronic diseases such as hypertension and diabetes. The relation of Frontal fibrosing alopecia (FFA) with environmental factors is still controversial. A recent multicentre case-control study used the odds ratio (OR) to express the effect size of different factors. It showed that FFA and formalin (OR 3.19), the use of ordinary (non-dermatological) facial soap (OR 2.09) and cream (OR 1.99), thyroid disease (OR 1.69), and alcohol scum nose (OR 2.08) are related. Smokers (OR 0.33) and anti-residue/cleaning shampoo users (OR 0.35) were negatively correlated with FFA, and FFA was not correlated with sunscreens use (50). This study reminds us to some extent that exogenous factors and the pathogenesis of FFA may have a mechanism that is still unclear.
Due to a proven correlation between LPP and light exposure, daylight exposure has also been speculated to be an environmental trigger for FFA. One hypothesis is that the light protection provided by many facial care products reduces the synthesis of the tryptophan light product 6-formylindolo [3,2-b] carbazole (FICZ), which is a potent endogenous ligand of AHR, from the photooxidation of the essential amino acid L-tryptophan. It shows proinflammatory effects at lower concentrations and anti-inflammatory effects at higher concentrations (51). However, there is no definitive evidence of a causal relationship between sunscreens or environmental factors and FFA. Relevant theories and hypotheses need to be proven by experiments and data.

Conclusion
Frontal fibrosing alopecia (FFA) is a type of primary cicatrical alopecia. At present, many studies have shown that FFA is associated with many autoimmune diseases, further illustrating the role of complex immune regulatory networks in the pathogenesis of the disease.
From a clinical and pathological point of view, FFA is a regional disease dominated by localized eHFSC pathology as previous study have previously described (5). However, from the perspective of pathogenesis and genomics, FFA is essentially a systematic, genetically driven disease entity, and some factors may only affect the progression rate of FFA lesions without changing the development and course of the disease (48). From a regional skin presentation perspective, it means that optimal disease management first requires early and decisive intervention at the local skin level. But at its core, systemic treatments may be more effective and more important than any other approach if we aim to stop the progression of these disfiguring hair disorders as soon as possible (17). Fibrosis is a common endpoint of many diseases, and the phenotype of fibrosis is irreversible with current treatments, so it is foreseeable that EMT is a key target for early and aggressive therapeutic intervention before eHFSC is completely damaged (18). How to reverse the immune response in the early stage of EMT, or develop a corresponding targeting carrier for PPARγ, so that the PPARγ inhibitors can accumulate around the hair follicle, will become the future treatment direction or strategy to help us integrate the recent FFA pathobiological insights and translate them into specific therapeutic benefits. Commonly, it is reported that FFA is related to thyroid disease and some other autoimmune diseases, such as scalp discoid lupus erythematosus, vitiligo, lichen planus, lichen planus pigmentosa, and Sjögren's syndrome (51).
Although the pathogenesis of FFA is complex and not completely clear at present, the incidence of FFA worldwide has been increasing over the past decade, and it is important to understand the pathogenesis of FFA to target the direction of future treatment. The results of the current study suggest that the complex interaction between immune-mediated neurogenic inflammation, genetics, hormones, and possible external stimuli provides strong evidence for the pathogenesis of FFA, and the lack of PPAR-γ plays a vital role in all stages of the disease. Genome-wide association analysis explains that FFA is an immune inflammatory disease with a genetic predisposition, which is driven by HLA-B * 07:02. The role of sex steroids and external stimuli in FFA is derived from clinical studies of disease behavior, and the potential influence of both on the pathogenesis of FFA is speculative. More extensive studies are needed to verify


Addition of oh8dG to Cardioplegia Attenuated Myocardial Oxidative Injury through the Inhibition of Sodium Bicarbonate Cotransporter Activity

The biomarker 8-hydroxy-2′-deoxyguanosine (oh8dG) is derived from oxidized nucleic acids or products of oxidant-mediated DNA damage. Enhanced sodium bicarbonate cotransporter (NBC) activity is caused by reactive oxygen species (ROS) production in ventricular myocytes. Thus, we hypothesized that cardioplegia-solution-mediated ROS generation may be involved in the regulation of NBC activity in cardiomyocytes and that oh8dG treatment may modulate ROS and associated NBC activity. Langendorff-free cardioplegia-arrested cardiac strips and cardiomyocytes were isolated to determine the NBC activity and effects of oh8dG on oxidative-stress-mediated cardiac damage markers. We first determined the histidine-tryptophan-ketoglutarate (HTK) solution mediated NBC activity in cardiac strips and cells. The oh8dG treatment attenuated NBC activity in the electroneutral or electrogenic form of NBC. Additionally, exposure to HTK solution induced ROS, whereas co-administration of oh8dG attenuated ROS-mediated NBC activity, reduced ROS levels, and decreased the expression of apoptotic markers and fibrosis-associated proteins in cardiac cells. The oh8dG-administrated cardiac tissues were also protected from enhanced HTK-induced damage markers, heat shock protein 60 and polyADP-ribose. Our results show that oh8dG has a protective role against myocardial oxidative damage and provides a useful treatment strategy for restoring cardiac function.

Introduction
To decrease primary graft failure and postoperative myocardial dysfunction, donor heart preservation is an important process during heart transplantation [1,2]. Extracted donor hearts are exposed to ischemia, which leads to the deletion of the adenosine triphosphate (ATP) stores that initiate anaerobic metabolism and intracellular acidosis [3,4]. Increased intracellular enhanced activity of the sodium-hydrogen exchanger (NHE) leads to sodium influx into myocardial cells [3,4]. After the transplantation procedure, reperfusion of the donor heart rapidly initiates the washout of hydrogen (H + ) to the interstitial space. It creates a huge gradient of H + , which leads to further sodium influx through NHE [5]. The influx of sodium leads to upregulation of the sodium-calcium exchanger (NCX) in reverse mode, which eventually results in the import of calcium into myocardial cells [5]. Intracellular calcium overload enhances myocardial cell death by increased reactive oxygen species (ROS) levels, hyper-contracture, and apoptosis [3][4][5]. To decrease ischemia-reperfusion injury, retrieved organs are generally preserved in cold (4 • C) organpreserving solutions [6]. One of the most frequently used organ-preserving solutions is the histidine-tryptophan-ketoglutarate (HTK) solution [7]. As antioxidants, histidine,

ROS Staining
Isolated cardiomyocytes, cardiac strips, and cardiac tissues were attached to poly-Llysine (P8920, Sigma-Aldrich)-coated coverslips for 15 min at room temperature. Next, 10 µM 2 , 7 -Dichlorofluorescin diacetate (DCFDA) was loaded for 15 min and then rinsed with 1× DPBS. Confocal images were obtained at 488 nm using a Zeiss LSM 700 confocal microscope (Fluo-view, Carl Zeiss, Oberkochen, Germany). Images were collected from five separate preparations of cardiac tissue, and the results are presented as the average from all experiments.

Cell Culture and DNA Transfection
Human HEK293T (H.T), lung fibroblast MRC5, lung adenocarcinoma A549 cells were purchased from ATCC (Washington, DC, USA). Cells were cultured in Dulbecco's Modified Eagle Medium containing 10% fetal bovine serum (FBS) and 100 U/mL penicillinstreptomycin antibiotics at 37 • C in 5% CO 2 /95% air. Human NBCe1-B (an electrogenic form of sodium bicarbonate cotransporter, encoded by SLC4A4) and NBCn1 (electroneutral form of sodium bicarbonate cotransporter, encoded by SLC4A7) clones were provided by Shmuel Muallem (National Institutes of Health, Bethesda, MD, USA). Plasmid DNAs (1 µg/µL) were mixed with 200 µL Jet Prime Buffer (B200225, Polyplus-transfection, Illkirch-Graffenstaden, France). Transfection reagent (4 mL) (21Y0910L1, Polyplus-transfection) was incubated with mixed Jet prime buffer and DNA for 10 min in the dark. Incubated DNAs were transferred into H.T-cultured plates, and all procedures were performed in accordance with the protocol of the manufacturer (Polyplus-transfection). MRC5 cells were used for determination of cell viability, and A549 cells were used for determination of native NBC activity. S0859 (18497, Cayman, Ann Arbor, MI, USA) was used for the specific inhibition of NBC activity.

Reverse Transcription-Polymerase Chain Reaction (RT-PCR)
Total RNA was extracted from the mouse cardiac tissues using the Hybrid-Ribo Ex extraction system (301-001, GeneAll, Seoul, Korea) in accordance with the instructions of the manufacturer. Isolated RNA was quantitated using the Spectrophotometer ND-1000 (Thermo Fisher Scientific), and cDNA was amplified using the TOPscript RT-PCR kit from Enzynomics (RT410S, Daejeon, Korea). The primers and PCR cycling protocol were as follows: mouse Bcl-2 (forward) GCA TCT TCT CCT TCC AGC CTG and (reverse) GAC GCT CTC CAC ACA CAT GAC; mouse p53 (forward) CAT GGC CAT CTA CAA GAA GTC and (reverse) GAA CAT CTC GAA GCG TTT ACG; denaturation at 95 • C (5 min), followed by 35 cycles of 95 • C (1 min), an annealing step (1 min), and an extension step at 72 • C (1 min). The final extension step was performed at 72 • C (10 min).

Transferase (TdT)-Mediated dUTP Nick End Labeling (TUNEL) Assay
Frozen cardiac tissues of mice were sectioned on a glass slide at a thickness of 10 µm. The TUNEL assay was performed in accordance with the protocol of the manufacturer, using a Transdetect In Situ Fluorescein TUNEL Cell Apoptosis Detection kit (FA201-02, TransGen Biotech Co., LTD, China). The slides were three times washed with 1× Dulbecco's phosphate-buffered saline (LB 001-02, DPBS, Kyungsan, Korea) for 10 min and fixed with 4% paraformaldehyde for 30 min at room temperature. The 1× labeling solution (FA201-02, TransGen Biotech Co., LTD, Beijing, China) was added to the surface of the glass slide with tissue attached and incubated at 37 • C in the dark for 1 h. The glass slides were rinsed with 1× DPBS and DAPI-included fluoromount-G (17984-24, Electron Microscopy Sciences, Hatfield, PA, USA) for 5 min. Confocal images were obtained at 358 nm using a Zeiss LSM 700 confocal microscope (Fluo-view, Carl Zeiss). Images were collected from five separate preparations of the cardiac tissues.

Immunostaining
Frozen cardiac tissues of mice were sectioned on the slide glass at a thickness of 10 µm. Slides were fixed with 4% paraformaldehyde or chilled methanol for 10 min. Heat shock protein 60 (ab46798, HSP60, Abcam) and poly (ADP-Ribose) (SM1398, PAR, ORIGENE, Rockville, MD, USA) antibodies were diluted at 1:100 and used to treat fixed samples for 24 h. Secondary antibodies tagged with FITC (for PAR, 1:200 dilution) and rhodamine (for HSP60, 1:200 dilution) were attached, and confocal images were obtained. Images were obtained using an LSM 700 Zeiss confocal microscope (Fluo-view, Carl Zeiss) at 488 nm (FITC), 530 nm (rhodamine), and 358 nm (DAPI for nucleus staining) and analyzed with ZEN software (ZEN 2009 light edition, Carl Zeiss). Images were collected from five separate preparations of cardiac tissue, and the results were averaged from all experiments.

MTT Assay
MRC5 cells were cultured in 96-well plates for 24 h and various dose of oh8dG was added for 1 h. Tetrazolium bromide (MTT; 298-93-1, Merck, Burlington, MA, USA) dye was mixed with 1 mL of PBS, and the cells were treated with 100 µL of MTT dye and incubated for 2 h in the dark. The medium was carefully aspirated from the plate and added 100 µL of DMSO, and the absorbance of sample was measured at 570 nm using a fluorescence microplate reader (VICTOR X3, PerkinElmer, Waltham, MA, USA).

Statistical Analysis
Experimental results are expressed as the mean ± standard error of the mean (SEM), and standard deviation (SD) was also represented. Experiment was performed more than three times and represented in figure legends. Differences between the mean values of the two samples were analyzed using the Student's t-test. Significance was determined by analysis of variance in each experiment (* p < 0.05, ** p < 0.01, and *** p < 0.001).

Treatment of oh8dG Attenuated HTK-Mediated ROS Level in Cardiac Strips and Isolated Cardiomyocytes
Cardioplegia-induced oxidative injury results in cardiomyocytes apoptosis [41,42].
To determine the anti-oxidative role of exogenous oh8dG, we measured ROS levels using DCFDA fluorescence in cardioplegia solution (HTK)-exposed cardiac strips. DCFDA fluorescence was enhanced in HTK-exposed cardiac strips for 1 h and attenuated by the administration of exogenous oh8dG (Figure 1a,b). The HTK-exposed cardiac strips for 2 h were exhausted of DCFDA fluorescence with or without oh8dG (Figure 1a,b). We also confirmed the anti-oxidative role of oh8dG in cardiomyocytes isolated from the mice. Isolated cardiomyocytes were easily damaged by HTK treatment. Thus, the exposure time of HTK was maintained within 30 min, similar to the experimental condition in cardiac strips, which is available in within 2 h. The improved DCFDA fluorescence in HTK-treated cardiomyocytes was attenuated by treatment with exogenous oh8dG (Figure 1c,d). To verify the toxicity of exogenous oh8dG, we performed an MTT assay (Supplementary Figure S1). There was no effect of oh8dG on cell viability. These results indicate that exogenous oh8dG attenuated HTK-mediated ROS levels in cardiac tissues and cells.

The Treatment of oh8dG Attenuated ROS-Mediated NBC Activities
To verify the role of NBC activity in response to ROS and the anti-oxidative effect of oh8dG, cells were transfected with two types of NBC, NBCe1-B, and NBCn1. NBC-transfected H293T cells were treated with oh8dG for 1 h, and the effective dose of oh8dG was determined. Both 10 and 100 µg/mL of oh8dG attenuated the NBC activities independently of the type of NBC, electrogenic and electroneutral (Figure 2a-d). Then, 100 µg/mL of oh8dG was suggested [28], and we also determined the working dose of oh8dG (100 µg/mL) to evaluate the role of oh8dG. We determined the ROSmodulated NBC activity. NBC-overexpressing cells were stimulated with H 2 O 2 with or without oh8dG. Treatment with H 2 O 2 induced two~three-fold high NBC activity in both NBCs, and the co-administration of oh8dG dramatically attenuated NBC activity (Figure 2e-h). We also confirmed the modulatory role of H 2 O 2 on NBC activity in native NBC-expressed A549 cells. NBC activity was enhanced by the treatment of H 2 O 2 , whereas H 2 O 2 -mediated NBC activity was attenuated by the presence of specific NBC inhibitor S0859 (Supplementary Figure S2). NBC activity was dose-dependently inhibited by the oh8dG treatment (Supplementary Figure S3). These results suggested that NBC activity was directly enhanced by treatment with ROS, and these enhanced activities were attenuated by exogenous oh8dG treatment. cells. NBC activity was enhanced by the treatment of H2O2, whereas H2O2-mediated NBC activity was attenuated by the presence of specific NBC inhibitor S0859 (Supplementary Figure S2). NBC activity was dose-dependently inhibited by the oh8dG treatment (Supplementary Figure S3). These results suggested that NBC activity was directly enhanced by treatment with ROS, and these enhanced activities were attenuated by exogenous oh8dG treatment.  Bars present mean ± SEM (n = 4~6 * p < 0.05, ** p < 0.01, and *** p < 0.001). The table represents mean and SD value. (c) DCFDA staining in isolated cardiomyocytes after cardiac arrest with cardioplegia solution (HTK) using Langendorff-free cardioplegia method for 1 min and 100 µg/mL oh8dG was treated for 10 min and 30 min on ice. The scale bar represents 20 µm. (d) Analysis of normalized intensity (total intensity/measuring area) of DCFDA. Bars present mean ± SEM (n = 10, *** p < 0.001). The table represents mean and SD value. *** p < 0.001). The table represents mean and SD value. (c) DCFDA staining in isolated cardiomyocytes after cardiac arrest with cardioplegia solution (HTK) using Langendorff-free cardioplegia method for 1 min and 100 μg/mL oh8dG was treated for 10 min and 30 min on ice. The scale bar represents 20 μm. (d) Analysis of normalized intensity (total intensity/measuring area) of DCFDA. Bars present mean ± SEM (n = 10, *** p < 0.001). The table represents mean and SD value.   . (g,h) The bars present mean ± SEM (n = 3~5, * p < 0.05, ** p < 0.01, and *** p < 0.001). The table represents mean and SD value.

HTK-Exposed Cardiac Tissues Enhanced NBC Activity, Attenuated by the Treatment of oh8dG
To verify the modulatory role of HTK-induced ROS in NBC activity in cardiac tissues, two types of NBC expression were determined. The left and right ventricles of the cardiac tissues were expressed in both NBCs (Figure 3a). Exposure to the HTK solution stimulated NBC activity in isolated cardiomyocytes (Figure 3b,c). Co-stimulation of HTK with oh8dG attenuated HTK-mediated NBC activity (Figure 3b,c). We then confirmed NBC activity in HTK-exposed isolated cardiac strips. oh8dG also attenuated NBC activity (Figure 3d,e). These results indicate that HTK exposure enhanced ROS production and enhanced NBC activity, which was attenuated by exogenous oh8dG administration.

HTK-Exposed Cardiac Tissues Enhanced NBC Activity, Attenuated by the Treatment of oh8dG
To verify the modulatory role of HTK-induced ROS in NBC activity in cardiac tissues, two types of NBC expression were determined. The left and right ventricles of the cardiac tissues were expressed in both NBCs (Figure 3a). Exposure to the HTK solution stimulated NBC activity in isolated cardiomyocytes (Figure 3b,c). Co-stimulation of HTK with oh8dG attenuated HTK-mediated NBC activity (Figure 3b,c). We then confirmed NBC activity in HTK-exposed isolated cardiac strips. oh8dG also attenuated NBC activity (Figure 3d,e). These results indicate that HTK exposure enhanced ROS production and enhanced NBC activity, which was attenuated by exogenous oh8dG administration. Figure 3. HTK-exposed cardiac tissues enhanced NBC activity, attenuated by the treatment of oh8dG. (a) Protein expression of NBCe1 and NBCn1 in left and right ventricle (LV and RV, respectively) cardiac strips of mice (n = 6). β-actin was used as the loading control. (b) NBC activity was assessed by measuring changes of pH i with or without pre-incubation of 100 µg/mL oh8dG for 1 h in cardiomyocytes on ice. HTK solution was treated for 5 min. (c) The bars present mean ± SEM (n = 3, * p < 0.05, and ** p < 0.01) in cardiomyocytes. The table represents mean and SD value. (d) NBC activity in cardiac strips during cardioplegia (HTK)-induced arrest for 1 min. After cardiac arrest, 100 µg/mL oh8dG was pre-incubated for 1 h. (e) The bars present mean ± SEM (n = 3, *** p < 0.001) in cardiac strips. The table represents mean and SD value.

Treatment of oh8dG Attenuated DNA Fragmentation and Expression of the Apoptotic Marker in HTK-Exposed Cardiac Tissues
Ischemia-reperfusion injury-mediated cellular apoptosis is mediated by caspase-3 activation [43] and, subsequently, induces DNA fragmentation [44]. Figure 4a shows an enhanced DAPI staining area that was observed in the HTK-treated cardiomyocytes. HTKmediated DNA fragmentation was reduced by exogenous oh8dG treatment (Figure 4a,b). The HTK-induced increase in the apoptotic marker Bcl-2, but not p-53, was reduced by oh8dG treatment (Figure 4c,d). The cardiac injury induces the fibrosis factor connective tissue growth factor (CTGF) [45,46]. The oh8dG treatment reduced the expression of CTGF (Figure 4e,f). Isolated cardiac strips were exposed to HTK during cardiac arrest. Thus, the inhibitory effect of oh8dG on CTGF expression was assessed using HTK-exposed cardiac strips as a control. These results indicated that HTK-mediated DNA fragmentation and expression of the apoptotic marker Bcl-2 were attenuated by exogenous oh8dG treatment, with a decrease in CTGF.

Treatment of oh8dG Attenuated HTK-Mediated Cardiac Destructive Signals
The exogenous oh8dG showed anti-oxidative and anti-apoptotic effects in cardiac tissues and cells. To verify the tissue-protective role of exogenous oh8dG in cardiac apoptotic death, we performed a TUNEL assay. The number of TUNEL-positive cardiac tissues was increased by HTK exposure in a time-dependent manner. The co-administration of oh8dG dramatically reduced the number of TUNEL-positive cells (Figure 5a,b). Cellular stress and apoptotic signals induce plasma membrane localization of the mitochondrial protein HSP60 [47]. In addition, PAR production is activated by DNA damage and stress [48]. HTK-exposed cardiac tissue showed enhanced membrane expression of HSP60 (Figure 5c). We verified the role of exogenous oh8dG in stress/injury-associated protein expression. Coadministration of oh8dG dramatically attenuated HTK-mediated HSP60/PAR expression (Figure 5c-e). These data indicate that the co-administration of HTK and exogenous oh8dG has a protective effect against HTK-associated cardiac destructive signals.    (b) Analysis of TUNEL positive cells (%) normalized by assessing total intensity/measuring area of FITC (green). Bars present mean ± SEM (n = 3, * p < 0.05). NS; not significant. The table represents mean and SD value. (c) Immunostaining of HSP60 (red), PAR (green), and nucleus (DAPI, blue) in cardiac strips of mice. I.R.HTK; immediately removed HTK (cardioplegia-induced arrest, 1 min).
The heart was treated with HTK solution for 2 h, and 100 µg/mL oh8dG was treated for 1 h and 2 h, respectively on ice. The scale bars represent 20 µm. Analysis of normalized intensity (total intensity/measuring area) of HSP60 (d) and PAR (e). Bars present mean ± SEM (n = 4, * p < 0.05, ** p < 0.01, and *** p < 0.001). The table represents mean and SD value.

Discussion
In the present study, we addressed that exposure to HTK solution in cardiac cells induced ROS and co-administration of exogenous oh8dG attenuated ROS-mediated NBC activity and reduced expression of apoptotic markers and fibrosis-associated protein CTGF. The exogenous oh8dG-administrated cardiac tissues were protected from the HTK-induced damage markers HSP60 and PAR. Our results addressed exogenous oh8dG as a protective supplement against potential HTK-solution-mediated oxidative damage. Thus, our observations in cardiac tissues are consistent with previous studies in various experimental systems showing the protective role of exogenous oh8dG against oxidative or inflammatory signals [21][22][23][24][25][26][27][28].
NBC activity is modulated by various cellular stimulants, such as ROS [18], acidic [49], hypoxia [50], and inflammatory cytokines [49]. Our previous study showed that HTKinduced arrest mediated more acidic intracellular circumstances through the involvement of sodium-potassium-chloride cotransporter Nkcc1 and chloride-bicarbonate exchanger Slc26a6 in the db/db diabetic mouse model's heart than in wild-type mice during reperfusion [38].
Although NBC is considered an intracellular pH regulator, it has not been revealed whether HTK is involved in the activity of NBCs. The present study showed that NBC activity was increased by HTK-mediated ROS generation. Enhanced NBC activity may mediate sodium and bicarbonate uptake and, subsequently, coordinate ion transport, such as calcium and chloride. We speculate that the accumulation of sodium and bicarbonate through enhanced NBC may mediate the activation of the chloride/bicarbonate exchanger (chloride influx and bicarbonate efflux) and NCX exchanger (calcium influx and sodium efflux). In addition, enhanced sodium and chloride may facilitate water influx to maintain cellular osmotic power ( Figure 6). Therefore, calcium overload, enhanced sodium/chloride level, and subsequent water intake occur in the cytosol of cardiomyocytes and, subsequently, induced cytotoxic edema and impaired cardiomyocytes' function. Similarly, it has been addressed that the angiotensin II-mediated modulation of NBC and pathological output of associated ion transporters in cardiopathies [51]. Although experimental limitations were revealed, our results provide new potential targets to maintain cardiac function after cardiac surgery or heart transplantation using the HTK solution. Modulation of NBC is essential, to protect the heart during the reperfusion period of cardiac surgery or transplantation, by decreasing ROS generation. idants 2022, 11, x FOR PEER REVIEW 13 of 17 Figure 6. Schematic model of enhanced NBC and its coordinated channels and transporters in HTKexposed cardiomyocytes and preserving effect of exogenous oh8dG. HTK-solution-exposed cardiac tissues produce oxidative signals. Oxidants enhance cardiac NBC activity through the involvement of ERK [51] and, subsequently, induce convergent involvement of NCX, CBE (SLC26A6), and aquaporin (AQP), which cause calcium overload and cyto-edema during reperfusion [16]. Cardiac calcium overload also mediates ROS generation [52]. Thus, the modulation of NBC activity may be a potential strategy against cardiac damage such as arrhythmic events or cardiac sudden death. The application of exogenous oh8dG may attenuate HTK-mediated NBC hyperactivity and the associated damage markers.
ROS-mediated NBC activities, including NBCn and NBCe, were attenuated by treatment with exogenous oh8dG. The signaling of oh8dG has been known in the inactivation of Ras in cancer cells [53]. Ras signaling is involved in migration in various cellular systems, such as vascular smooth muscle cells, endothelial cells, and several cancers [54][55][56][57]. In addition, NBCn is known to provide a migratory module in various cell types, such as vascular smooth muscle cells, breast cancers, and synoviocytes [49,58,59]. Currently, there is no direct evidence for an association between Ras and NBCn. In this regard, the proteinprotein network between NBCn and Ras signaling is an attractive and changeable issue for future studies.
The protective role of exogenous oh8dG in various inflammatory and oxidative stress-mediated diseases has been highlighted in different studies [21,23,[29][30][31][32][33]. Our results indicate that long-term exposure to HTK solution mediated the enhancement of tissue damage markers. Cardiac tissues should be maintained and protected from damage signals during cardioplegia exposure. The static hypothermic preservation method is a low-cost and standard method for heart transplantation [60]. HTK has been suggested as an effective cardiac preservation solution to regenerate cardiac function [61,62]; however, HTK could not fully protect against reperfusion injury during hypothermic organ preservation [63]. Since ROS generation is the main initiator of reperfusion injury, the addition of various ROS scavengers has been attempted in order to decrease reperfusion injury during heart transplantation [64][65][66]. However, the cardio-protective effect of decreasing ROS with ROS scavengers is insufficient. Since the generation of ROS and various ion transporters are involved in modulating pH during reperfusion, we thought that modulation of both ROS and ion channels is essential to decrease reperfusion injury. Therefore, Figure 6. Schematic model of enhanced NBC and its coordinated channels and transporters in HTKexposed cardiomyocytes and preserving effect of exogenous oh8dG. HTK-solution-exposed cardiac tissues produce oxidative signals. Oxidants enhance cardiac NBC activity through the involvement of ERK [51] and, subsequently, induce convergent involvement of NCX, CBE (SLC26A6), and aquaporin (AQP), which cause calcium overload and cyto-edema during reperfusion [16]. Cardiac calcium overload also mediates ROS generation [52]. Thus, the modulation of NBC activity may be a potential strategy against cardiac damage such as arrhythmic events or cardiac sudden death. The application of exogenous oh8dG may attenuate HTK-mediated NBC hyperactivity and the associated damage markers.
ROS-mediated NBC activities, including NBCn and NBCe, were attenuated by treatment with exogenous oh8dG. The signaling of oh8dG has been known in the inactivation of Ras in cancer cells [53]. Ras signaling is involved in migration in various cellular systems, such as vascular smooth muscle cells, endothelial cells, and several cancers [54][55][56][57]. In addition, NBCn is known to provide a migratory module in various cell types, such as vascular smooth muscle cells, breast cancers, and synoviocytes [49,58,59]. Currently, there is no direct evidence for an association between Ras and NBCn. In this regard, the protein-protein network between NBCn and Ras signaling is an attractive and changeable issue for future studies.
The protective role of exogenous oh8dG in various inflammatory and oxidative stressmediated diseases has been highlighted in different studies [21,23,[29][30][31][32][33]. Our results indicate that long-term exposure to HTK solution mediated the enhancement of tissue damage markers. Cardiac tissues should be maintained and protected from damage signals during cardioplegia exposure. The static hypothermic preservation method is a low-cost and standard method for heart transplantation [60]. HTK has been suggested as an effective cardiac preservation solution to regenerate cardiac function [61,62]; however, HTK could not fully protect against reperfusion injury during hypothermic organ preservation [63]. Since ROS generation is the main initiator of reperfusion injury, the addition of various ROS scavengers has been attempted in order to decrease reperfusion injury during heart transplantation [64][65][66]. However, the cardio-protective effect of decreasing ROS with ROS scavengers is insufficient. Since the generation of ROS and various ion transporters are involved in modulating pH during reperfusion, we thought that modulation of both ROS and ion channels is essential to decrease reperfusion injury. Therefore, the possibility of adding exogenous oh8dG, which leads to decreased ROS and modulation of NBC activity, to the preservation solution could be considered.
Our study has some experimental limitations. Cardiac function after reperfusion could not be evaluated because the Langendorff perfusion system was not used. We evaluated various cardiac injury markers to determine whether HTK leads to apoptosis during organ preservation. Although co-administration of exogenous oh8dG with HTK requires additional experiments on organ preservation for long-term exposure, the cardioprotective effect of exogenous oh8dG might provide improved beneficial effects to restore functional cardiac recovery during reperfusion.


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Effector-Memory B-Lymphocytes and Follicular Helper T-Lymphocytes as Central Players in the Immune Response in Vaccinated and Nonvaccinated Populations against SARS-CoV-2

Vaccines have been recognized as having a central role in controlling the COVID-19 pandemic; however, most vaccine development research is focused on IgG-induced antibodies. Here, we analyzed the generation of IgGs related to SARS-CoV-2 and the changes in B- and T-lymphocyte proportions following vaccination against COVID-19. We included samples from 69 volunteers inoculated with the Pfizer-BioNTech (BNT162b2), Astra Zeneca (AZD1222 Covishield), or Sputnik V (Gam-COVID-Vac) vaccines. IgGs related to SARS-CoV-2 increased after the first vaccine dose compared with the nonvaccinated group (Pfizer, p = 0.0001; Astra Zeneca, p < 0.0001; Sputnik V, p = 0.0089). The results of the flow cytometry analysis of B- and T-lymphocytes showed a higher proportion of effector-memory B-lymphocytes in both first and second doses when compared with the nonvaccinated subjects. FcRL4+ cells were increased in second-dose-vaccinated COVID-19(−) and recovered COVID-19(+) participants when compared with the nonvaccinated participants. COVID-19(−) participants showed a lower proportion of follicular helper T-lymphocytes (TFH) in the second dose when compared with the first-vaccine-dose and nonvaccinated subjects. In conclusion, after the first vaccine dose, immunization against SARS-CoV-2 induces IgG production, and this could be mediated by TFH and effector-memory B-lymphocytes. Our data can be used in the design of vaccine schedules to evaluate immuno-bridging from a cellular point of view.

Introduction
The coronavirus disease 2019  pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a newly emerged coronavirus [1]. To date, SARS-CoV-2 has caused over 200 million cases and around 5 million deaths worldwide. Vaccines represent the most efficient means to control the COVID-19 pandemic. Since the beginning of the pandemic, about 200 vaccines have entered the biopharmaceutical development process. The vaccination aim is to achieve a robust immune response against

Population Studied
A prospective cohort study was carried out including samples from 69 volunteers, of which 34 participants were not yet vaccinated, and 36 had already received the first vaccine dose. We followed up throughout the vaccination schedule, collecting 34 samples before vaccination, 54 samples after the first vaccine dose, and 43 samples after the second vaccine dose. The vaccinated participants were inoculated with the Pfizer-BioNTech (BNT162b2), Astra Zeneca (AZD1222 Covishield), or Sputnik V (Gam-COVID-Vac) vaccines. The interval between the first and second dose was one month for the Pfizer-BioNTech (BNT162b2) and Sputnik V (Gam-COVID-Vac) vaccines and two months for the Astra Zeneca (AZD1222 Covishield) vaccine. In addition, we considered the clinical history of COVID-19. Diagnosis of COVID was performed with clinical data and confirmed by rtPCR; all recovered COVID-19(+) patients coursed a mild-to-moderate illness. In addition, 14 days after the onset of infection, a second rtPCR was performed. The infection recovery occurred between three and four months before the blood sample collection. Patients with negative rtPCR test at this time were included in this study. The demographic characteristics of participants are shown in Table 1. Written informed consent was obtained from all participants before enrolling in the study and peripheral blood collection. The Science (CI-055-2021), Biosecurity (CB-056-2021), and Bioethics (CEI-2021/10/09) Committees from the Institute of Ophthalmology "Conde de Valenciana Foundation" approved this study.

Blood Sample Collection
A total of 10-12 mL of peripheral blood was obtained through venipuncture. Peripheral blood samples were collected before the first vaccine dose and 14 ± 5 days after the first and or second vaccine application ( Figure 1). To obtain the serum, one blood sample was allowed to clot for 10 min at room temperature and centrifuged at 3500 rpm (1000× g) for 7 min. Then, the serum was aliquoted and stored at −20 • C until the enzyme-linked immunosorbent assay (ELISA) was performed. Another blood sample was immediately used for complete blood count and flow cytometry analysis. 2021/10/09) Committees from the Institute of Ophthalmology "Conde de Valenciana Foundation" approved this study.

Blood Sample Collection
A total of 10-12 mL of peripheral blood was obtained through venipuncture. Peripheral blood samples were collected before the first vaccine dose and 14 ± 5 days after the first and or second vaccine application ( Figure 1). To obtain the serum, one blood sample was allowed to clot for 10 min at room temperature and centrifuged at 3500 rpm (1000× g) for 7 min. Then, the serum was aliquoted and stored at −20 °C until the enzymelinked immunosorbent assay (ELISA) was performed. Another blood sample was immediately used for complete blood count and flow cytometry analysis.

Detection of IgGs Related to SARS-CoV-2 by Enzyme-Linked Immunosorbent Assay (ELISA)
IgGs related to SARS-CoV-2 against the RBD domain of S protein were detected in the serum collected from vaccinated and nonvaccinated participants using an ELISA Kit UDITEST-V2G (IPN, Mexico City, Mexico), according to the manufacturer's instructions [13]. The optical density (OD) was measured at 450 nm in a Multiskan Ascent spectrophotometer (Thermo Scientific, Waltham, MA, USA). Each sample was run in duplicate, and the values were averaged.

Total Count of Neutrophils, Lymphocytes, and Neutrophil-Lymphocyte Ratio (NLR)
The total number of neutrophils and lymphocytes was obtained from the complete blood count data performed in an Automated Hematology Analyzer XS-1000i (Sysmex, Kobe, Japan). The neutrophil-lymphocyte ratio (NLR) was defined as the proportion of the absolute neutrophil count to absolute lymphocyte count.
CD4+ T-lymphocytes and CD19+ B-lymphocytes staining procedure and flow cytometry analysis. Briefly, 100 µL of complete blood was placed in a cytometric tube, and a viability staining for discriminated live or dead cells was performed by employing Ghost Violet 450 (#13-0863-T100, San Diego, CA, USA) from Tonbo bioscience, according to the manufacturer's instructions. Then, anti-CD19, anti-CD21, anti-CD27, and anti-FcRL4 MoAbs or anti-CD3, anti-CD4, anti-CD45RO, anti-CD45RA, anti-CCR7, and anti-CXCR5 MoAbs were added. The tubes were incubated at room temperature for 30 min. After the incubation, 1 mL of the BD FACS Lysing solution (BD, San José, CA, USA) was added and incubated at room temperature for 12 min, washed, and centrifuged. Finally, the cellular pellet was resuspended and fixed with 300 µL of the BD Stabilizing Fixative solution (San Jose, CA, USA).
Events were acquired with a BD FACSVerse (San Jose, CA, USA) cytometer using BD FACSuite software. First, the cells were gated in an FSC-A vs. Ghost Violet to exclude dead cells; later, in the FSC-A vs. FSC-H dot plot, we excluded doublets. Then, the lymphocyte region was selected using an FSC vs. SSC dot plot; 20,000 events were acquired from this population. Next, an SSC-A vs. CD3 followed by CD3 vs. CD4 or an SSC-A vs. CD19 dot plot was made. From the gated-CD3+CD4+ region, a CXCR5 vs. CCR7 plot was used to identify and quantify the TFH population. Additionally, from the gated-CD4 region, a CD45RO vs. CD45RA plot was used to identify and quantify the memory T-lymphocyte population. Conversely, from the gated-CD19 region, a CD27 vs. CD21 plot was used to identify and quantify the memory and effector-memory B-lymphocyte populations. In addition, from the populations mentioned above, the expression of FcRL4 was evaluated ( Figure 2). Positive and negative gates for each molecule were verified on the basis of "fluorescence-minus-one (FMO)" control (Supplementary Figure S1).

Statistical Analysis
For the parametric distribution, the Shapiro-Wilk test was used. Statistical analysis was performed using the Mann-Whitney test to compare between COVID-19(−) and recovered COVID-19(+) participants in nonvaccinated, vaccinated with the first dose, or vaccinated with the second dose. The Kruskal-Wallis test, followed by Dunn's multiple comparison test, was performed to compare groups before and throughout the vaccine schedule. The Wilcoxon test for paired samples or the Friedman test with Dunn's multiple comparisons was used for the longitudinal analysis throughout the follow-up of the vaccination schedule, when the participants had one or two vaccine doses, respectively.
All results are shown as the mean ± standard deviation (SD). Finally, random-effects generalized least-squares regression (GLS regression) was used to evaluate changes on the optical density (OD) after adjustment by TFH, memory B-lymphocytes or effector-memory B-lymphocytes, and COVID-19 background. Analyses were performed using the statistical program Graph Pad Prism 8 (GraphPad Software, La Jolla, CA, USA and Stata 15.1, Stata Corp., College Station, TX, USA). Values of p < 0.05 were considered statistically significant.

Statistical Analysis
For the parametric distribution, the Shapiro-Wilk test was used. Statistical analysis was performed using the Mann-Whitney test to compare between COVID-19(−) and recovered COVID19(+) participants in nonvaccinated, vaccinated with the first dose, or vaccinated with the second dose. The Kruskal-Wallis test, followed by Dunn's multiple comparison test, was performed to compare groups before and throughout the vaccine schedule. The Wilcoxon test for paired samples or the Friedman test with Dunn's multiple comparisons was used for the longitudinal analysis throughout the follow-up of the vaccination schedule, when the participants had one or two vaccine doses, respectively.
All results are shown as the mean ± standard deviation (SD). Finally, random-effects generalized least-squares regression (GLS regression) was used to evaluate changes on FSC-H dot plot, we excluded doublets. Lymphocyte region was selected using an FSC vs. SSC dot plot. SSC-A vs. CD19 dot plot or SSC-A vs. CD3 followed by CD3 vs. CD4 was made from lymphocyte region. From gated CD19 region, CD27 vs. CD21 plot was made to identify memory (CD21+CD27+) and effector-memory (CD21−CD27+) B-lymphocytes. In addition, expression of FcRL4 was evaluated with histogram from memory and effector-memory B-lymphocytes. On the other hand, from gated CD3, CD4 region, a CXCR5 vs. CCR7 and CD45RO vs. CD45RA plot was made to identify TFH (CCR7−CXCR5+) and memory (CD45RA−CD45RO+) T-lymphocytes, respectively. Analysis of samples from nonvaccinated, vaccinated with the first dose, and vaccinated with the second vaccine dose is shown.

Distinct Vaccine Platforms Induced Similar Production of Antibodies against SARS-CoV-2
First, we began by determining the IgG production against SARS-CoV-2 according to the vaccine platform. All analyzed vaccines significantly increased the optical density (OD) after the first dose compared with the nonvaccinated group (Pfizer p = 0.0001, Astra Zeneca p < 0.0001, and Sputnik V p = 0.0089) ( Figure 3A and Figure S2). Interestingly, with the first dose, we detected no significant differences in the OD between the distinct vaccine types. Based on these results, for the following analyses, we evaluated nonvaccinated, vaccinated with the first dose, and vaccinated with the second dose independently of the vaccine type. In addition, analysis with age stratification (subjects under 30 years and subjects over 30 years) was carried out, and no differences were detected in the vaccinated samples (Table S1, Supplementary Data). nonvaccinated, vaccinated with the first dose, and vaccinated with the second dose expected, in the participants with previous COVID-19, we detected an induction of I related to SARS-CoV-2 before the vaccine (OD mean = 0.8). Furthermore, the OD dete in recovered COVID-19(+) participants was significantly greater than in the particip naïve to COVID-19 in samples with the first (p < 0.0001) and second vaccine doses 0.0083). Interestingly, with the first vaccine dose, we detected a greater increase of the in both recovered COVID-19(+) and COVID-19(−) participants compared with nonvaccinated samples (p < 0.0001), whereas with the second vaccine dose, an increas the OD was detected only in the COVID-19(−) samples compared with the samples w the first dose (p < 0.0001) ( Figure 3B).   Table S2, Supplementary Data. A second analysis was performed considering COVID-19 history before immunization and determining immunization-induced IgG levels; we analyzed the OD in recovered COVID-19(+) and COVID-19(−) participants for each group of nonvaccinated, vaccinated with the first dose, and vaccinated with the second dose. As expected, in the participants with previous COVID-19, we detected an induction of IgGs related to SARS-CoV-2 before the vaccine (OD mean = 0.8). Furthermore, the OD detected in recovered COVID-19(+) participants was significantly greater than in the participants naïve to COVID-19 in samples with the first (p < 0.0001) and second vaccine doses (p = 0.0083). Interestingly, with the first vaccine dose, we detected a greater increase of the OD in both recovered COVID-19(+) and COVID-19(−) participants compared with the nonvaccinated samples (p < 0.0001), whereas with the second vaccine dose, an increase in the OD was detected only in the COVID-19(−) samples compared with the samples with the first dose (p < 0.0001) ( Figure 3B).

Immunization against SARS-CoV-2 Does Not Induce Differences in Total Neutrophils, Although a Decrease in Lymphocytes Is Detected
Neutrophils are a major component of the leukocyte population capable of releasing large amounts of reactive oxygen species and pro-inflammatory cytokines, and lymphocytes are an important part of the adaptive immune response against the virus. Therefore, we analyzed the total count of neutrophils and lymphocytes in COVID-19(−) and recovered COVID-19(+) participants in three groups: nonvaccinated, vaccinated with the first dose, and vaccinated with the second dose. All neutrophil and lymphocyte values were in the normal range defined by the hematic biometry ( Figure 4A,B). No differences in the total neutrophils were detected when comparing COVID-19(−) and recovered COVID-19(+) participants ( Figure 4A). On the other hand, the total lymphocytes were lower in the samples from those who had received the second vaccine dose; even in the COVID-19(−) participants, a significant difference was detected compared with the samples without vaccine (p = 0.0004) ( Figure 4B). have been investigated as independent predictors for the prognosis of systemic inflammatory diseases [14,15]. When we analyzed the NLR in the participants naïve to COVID-19, we detected a tendency to increase with the first vaccine dose compared with the nonvaccinated samples, and this tendency was maintained following the second vaccine dose. Meanwhile, in the recovered COVID-19(+) participants, the NLR decreased with the first vaccine dose; however, following the second vaccine dose, it returned to a value similar to that in the nonvaccinated samples ( Figure 4C).  Table S3, Supplementary Data.

Effector-Memory B-Lymphocytes Increase with First Vaccine Dose, but There Are No Differences with Second Vaccine Dose
Vaccines aim to generate protective antibodies in the long term; in this sense, the participation of B-lymphocytes is important. Therefore, we analyzed the proportions of total B-lymphocytes (CD19+), as well as memory B-lymphocytes (CD19+CD21+CD27+) and effector-memory B-lymphocytes (CD19+CD21−CD27+). A similar proportion of CD19+ B-lymphocytes was detected in the group of recovered COVID-19(+) participants. However, a lower percentage of CD19+ B-lymphocytes was detected in the samples with the second vaccine dose from the participants with COVID-19(−) compared with that in the nonvaccinated samples (p = 0.0189) and the samples with the first vaccine dose (p = 0.0097) ( Figure 5A).
Various inflammatory biomarkers, such as the neutrophil-lymphocyte ratio (NLR), have been investigated as independent predictors for the prognosis of systemic inflammatory diseases [14,15]. When we analyzed the NLR in the participants naïve to COVID-19, we detected a tendency to increase with the first vaccine dose compared with the nonvaccinated samples, and this tendency was maintained following the second vaccine dose. Meanwhile, in the recovered COVID-19(+) participants, the NLR decreased with the first vaccine dose; however, following the second vaccine dose, it returned to a value similar to that in the nonvaccinated samples ( Figure 4C).

Effector-Memory B-Lymphocytes Increase with First Vaccine Dose, but There Are No Differences with Second Vaccine Dose
Vaccines aim to generate protective antibodies in the long term; in this sense, the participation of B-lymphocytes is important. Therefore, we analyzed the proportions of total B-lymphocytes (CD19+), as well as memory B-lymphocytes (CD19+CD21+CD27+) and effector-memory B-lymphocytes (CD19+CD21−CD27+). A similar proportion of CD19+ B-lymphocytes was detected in the group of recovered COVID-19(+) participants. However, a lower percentage of CD19+ B-lymphocytes was detected in the samples with the second vaccine dose from the participants with COVID-19(−) compared with that in the nonvaccinated samples (p = 0.0189) and the samples with the first vaccine dose (p = 0.0097) ( Figure 5A).
In the case of memory B-lymphocytes (CD19+CD27+CD21+), a similar proportion of this population was detected between the COVID-19(−) and recovered COVID-19(+) participants. In addition, in the participants with COVID-19(−), a decrease was detected in the samples with the first and second vaccine dose compared with the nonvaccinated samples (p = 0.0166 and p = 0.0259, respectively). In contrast, the recovered COVID-19(+) participants ( Figure 5B) show only a tendency to decrease.
Finally, concerning the effector-memory B-lymphocytes (CD19+CD27+CD21−), a similar proportion was detected when comparing the COVID-19(−) and recovered COVID-19(+) participants in the same group (nonvaccinated, with the first vaccine dose, and with the second vaccine dose) and when comparing the samples from the second dose with the samples from the nonvaccinated. A higher proportion of effector-memory B-lymphocytes was detected in the samples with the first vaccine dose (in both COVID-19(−) and recovered COVID-19(+) participants) compared with that in the nonvaccinated samples (p = 0.0214 and p = 0.0265, respectively) and compared with the samples with the second vaccine dose (p = 0.0362 and p = 0.0457, respectively) ( Figure 5B). Moreover, we analyzed the samples considering age stratification, and no differences were found (Table S4, Supplementary Data).
Vaccines 2022, 10, 1761 8 of 18 5C). In the case of FcRL4+ B-lymphocytes with an effector-memory phenotype, a significant increase in this population was detected following the first and second vaccine doses when compared with the nonvaccinated sample from recovered COVID-19(+) participants (p < 0.0001 and p = 0.0037, respectively), and an increase in the second vaccine dose was detected when compared with the nonvaccinated samples from the COVID-19(−) participants (p = 0.035) ( Figure 5C).  Table S5, Supplementary Data.
We analyzed the expression of FcRL4 in both memory B-lymphocytes and effectormemory B-lymphocytes. In participants naïve to COVID-19, we detected a lower percentage of FcRL4+ memory B-lymphocytes in the first and second vaccine doses than the samples without vaccine (p = 0.239 and p = 0.0171, respectively). On the other hand, in participants with previous COVID-19, only a tendency to decrease was detected ( Figure 5C). In the case of FcRL4+ B-lymphocytes with an effector-memory phenotype, a significant increase in this population was detected following the first and second vaccine doses when compared with the nonvaccinated sample from recovered COVID-19(+) participants (p < 0.0001 and p = 0.0037, respectively), and an increase in the second vaccine dose was detected when compared with the nonvaccinated samples from the COVID-19(−) participants (p = 0.035) ( Figure 5C).

T-Lymphocytes and Follicular Helper T-Lymphocytes (TFH) Increase with First Dose of Vaccine against SARS-CoV-2 in COVID-19(−) Participants, and TFH Decreases with Second Dose
To effectively activate B-lymphocytes, interaction with T-lymphocytes, particularly the follicular helper T-lymphocytes (TFH), is required. We analyzed the proportions of T-lymphocytes, TFH, and memory T-lymphocytes.
When comparing the proportion of T-lymphocytes between the COVID-19(−) and recovered COVID-19(+) participants, no differences were detected in the variously vaccinated groups. However, an increase in this population was detected in the samples with the first and second vaccine doses compared with the samples from the nonvaccinated COVID-19(−) participants (p = 0.003 and p = 0.0246, respectively). Additionally, an increase in T-lymphocytes was detected in the samples with the second dose compared with the samples from the nonvaccinated recovered COVID-19(+) participants (p = 0.0168) ( Figure 6A).  Table S7, Supplementary Data.

Changes in Parameters by Longitudinal Analysis throughout Follow-Up of Vaccination Schedule
To analyze the immunological changes induced by the vaccine throughout the vaccination schedule, we performed a longitudinal analysis. We considered 14 participants with three samples (pre-vaccine sample and following the first and second vaccine doses) and 36 participants with two samples (10 with pre-vaccine and first vaccine dose samples, and 26 with first and second vaccine dose samples). Concerning the OD when analyzing the participants naïve to COVID-19, a significant increase in the OD wa detected with both vaccine doses (p < 0.0001). In contrast, in the recovered COVID-19(+ participants, this increase was only significant with the first vaccine dose (p = 0.0039) although there was an increase in the second dose (Figure 7). Concerning TFH, in the participants with a history of COVID-19, a similar proportion between the samples with the first vaccine dose and the samples from the nonvaccinated participants was detected, as well as a tendency to decrease the TFH from the recovered COVID-19(+) patients in the samples with the second vaccine dose compared with the samples from the nonvaccinated participants and the samples from the first-dose vaccinated participants ( Figure 6B). However, in the participants naïve to COVID-19, we detected a tendency for the proportion of TFH to increase in the first-dose vaccinated samples relative to the nonvaccinated samples. In contrast, in the samples with the second vaccine dose, a significant decrease was detected when comparing the samples with the first vaccine dose and the samples from the nonvaccinated participants (p < 0.0001 and p = 0.0018, respectively) ( Figure 6B). After adjustment by background of COVID-19 and effectormemory B lymphocytes, per unit of change on THF, we observed a significant decrement of 0.0357 (IC95%-0.0636; −0.0077, p = 0.012) on the OD. The average difference in the OD among those with and without COVID-19 background was 0.6347 (IC95% 0.3861; 0.8833, p < 0.001). No difference on the OD by effector-memory B-lymphocytes was noted. Finally, when analyzing the proportions of memory T-lymphocytes in both COVID-19(−) and recovered COVID-19(+) participants, no differences were found between the vaccinated and nonvaccinated samples ( Figure 6C). Furthermore, we analyzed the samples considering age stratification, and no differences were found (Table S6, Supplementary Data).

Changes in Parameters by Longitudinal Analysis throughout Follow-Up of Vaccination Schedule
To analyze the immunological changes induced by the vaccine throughout the vaccination schedule, we performed a longitudinal analysis. We considered 14 participants with three samples (pre-vaccine sample and following the first and second vaccine doses) and 36 participants with two samples (10 with pre-vaccine and first vaccine dose samples, and 26 with first and second vaccine dose samples). Concerning the OD, when analyzing the participants naïve to COVID-19, a significant increase in the OD was detected with both vaccine doses (p < 0.0001). In contrast, in the recovered COVID-19(+) participants, this increase was only significant with the first vaccine dose (p = 0.0039), although there was an increase in the second dose ( Figure 7).  Table S7, Supplementary Data.

Changes in Parameters by Longitudinal Analysis throughout Follow-Up of Vaccination Schedule
To analyze the immunological changes induced by the vaccine throughout the vaccination schedule, we performed a longitudinal analysis. We considered 14 participants with three samples (pre-vaccine sample and following the first and second vaccine doses) and 36 participants with two samples (10 with pre-vaccine and first vaccine dose samples, and 26 with first and second vaccine dose samples). Concerning the OD, when analyzing the participants naïve to COVID-19, a significant increase in the OD was detected with both vaccine doses (p < 0.0001). In contrast, in the recovered COVID-19(+) participants, this increase was only significant with the first vaccine dose (p = 0.0039), although there was an increase in the second dose ( Figure 7).   Table S8, Supplementary Data.
Regarding the total count of neutrophils and lymphocytes, no differences were detected throughout the follow-up during the vaccination scheme ( Figure 8A,B). Meanwhile, in the NLR, a tendency to increase was detected in the participants with COVID-19(−) with the first and second vaccine doses. Conversely, in the participants who recovered from COVID-19(+), a decrease with the first vaccine dose was detected (p = 0.0312), and with the second vaccine dose, the proportion was similar to pre-vaccinated subjects ( Figure 8C).
When analyzing the B-lymphocytes, a significant decrease was detected throughout the vaccination scheme in both COVID-19(−) (first vaccine dose, p = 0.0049; and second vaccine dose, p < 0.0001) and recovered COVID-19(+) (first vaccine dose, p = 0.0156; and second vaccine dose, p = 0.014) participants ( Figure 9A). Moreover, in COVID-19(−) participants, the memory of B-lymphocytes was decreased in the first vaccine dose (p = 0.0005), and no differences were detected with the second vaccine dose ( Figure 9B). In addition, in the effector-memory B-lymphocyte subpopulation, in both the COVID-19(−) and recovered COVID-19(+) participants, we detected a tendency to increase with the first vaccine dose, whereas, with the second vaccine dose, the percentages decrease to values similar to pre-vaccine proportions ( Figure 9B).
Regarding the total count of neutrophils and lymphocytes, no differences were detected throughout the follow-up during the vaccination scheme ( Figure 8A,B). Meanwhile, in the NLR, a tendency to increase was detected in the participants with COVID-19(−) with the first and second vaccine doses. Conversely, in the participants who recovered from COVID-19(+), a decrease with the first vaccine dose was detected (p = 0.0312), and with the second vaccine dose, the proportion was similar to pre-vaccinated subjects ( Figure 8C).  Figure 9A). Moreover, in COVID-19(−) participants, the memory of B-lymphocytes was decreased in the first vaccine dose (p = 0.0005), and no differences were detected with the second vaccine dose ( Figure 9B). In addition, in the effector-memory B-lymphocyte subpopulation, in both the COVID-19(−) and recovered COVID-19(+) participants, we detected a tendency to increase with the first vaccine dose, whereas, with the second vaccine dose, the percentages decrease to values similar to pre-vaccine proportions ( Figure 9B).
When analyzing memory B-lymphocytes, no changes in the FcRL4 expression were detected in the groups studied ( Figure 9C). Meanwhile, the proportion of effectormemory B-lymphocytes FcRL4+ in the COVID-19(−) significantly increased with the first (p = 0.0122) and second vaccine doses (p = 0.0029). In contrast, in the recovered COVID-19(+) participants, only a tendency to increase with the vaccine doses was detected ( Figure  9C). Finally, when analyzing the proportion of T-lymphocytes in COVID-19(−) participants, a significant increase was detected with the first vaccine dose (p = 0.0046), whereas in the recovered COVID-19(+) participants, a significant increase was detected with the first and second vaccine doses (p = 0.0078, and p = 0.0419, respectively) ( Figure  10A). In the case of TFH, in the participants naïve to COVID-19, a tendency to increase  Table S10, Supplementary Data. When analyzing memory B-lymphocytes, no changes in the FcRL4 expression were detected in the groups studied ( Figure 9C). Meanwhile, the proportion of effector-memory B-lymphocytes FcRL4+ in the COVID-19(−) significantly increased with the first (p = 0.0122) and second vaccine doses (p = 0.0029). In contrast, in the recovered COVID-19(+) participants, only a tendency to increase with the vaccine doses was detected ( Figure 9C).
Finally, when analyzing the proportion of T-lymphocytes in COVID-19(−) participants, a significant increase was detected with the first vaccine dose (p = 0.0046), whereas in the recovered COVID-19(+) participants, a significant increase was detected with the first and second vaccine doses (p = 0.0078, and p = 0.0419, respectively) ( Figure 10A). In the case of TFH, in the participants naïve to COVID-19, a tendency to increase with the first vaccine dose was detected, followed by a decrease with the second vaccine dose (p < 0.0001), whereas in the recovered COVID-19(+) participants, a tendency to decrease was detected with both the first and second vaccine doses ( Figure 10B). In COVID-19(−) participants, we detected a tendency for memory T-lymphocytes to increase following the first vaccine dose, followed by a significant decrease with the second vaccine dose (p = 0.0284), whereas in the recovered COVID-19(+) participants, a tendency to increase with both the first and second vaccine doses was detected ( Figure 10C).  Table S11, Supplementar Data.

Discussion
In recent years, the SARS-CoV-2 pandemic has had a meaningful impact on globa health. Severe COVID-19 is characterized by acute respiratory distress syndrome, multi organic failure, and even death [1,16], whereas long-term sequelae have been reported in the case of moderate disease [16]. This pandemic continues because of the high transmissibility, emergence of new variants, and presence of asymptomatic carriers Therefore, vaccination is the most viable strategy to prevent or diminish the disease. In the present study, we analyzed how different vaccine platforms induce short-and medium-term changes in the B-and T-lymphocyte populations, which might help explain effective immune response postvaccination.  Table S11, Supplementary Data.

Discussion
In recent years, the SARS-CoV-2 pandemic has had a meaningful impact on global health. Severe COVID-19 is characterized by acute respiratory distress syndrome, multiorganic failure, and even death [1,16], whereas long-term sequelae have been reported in the case of moderate disease [16]. This pandemic continues because of the high transmissibility, emergence of new variants, and presence of asymptomatic carriers. Therefore, vaccination is the most viable strategy to prevent or diminish the disease. In the present study, we analyzed how different vaccine platforms induce short-and medium-term changes in the B-and T-lymphocyte populations, which might help explain effective immune response postvaccination.
Progress in vaccine generation has resulted in several types of SARS-CoV-2 vaccines approved for emergency use [17,18]. Our study analyzed the immune response induced by Pfizer BNT162b2, which uses mRNA technology and a lipid nanoparticle delivery platform, and the Astra Zeneca AZD1222 and Gam-COVID-Vac (Sputnik V) vaccines that contain viral DNA within nonreplicant adenovirus vectors. They all encode the production of SARS-CoV-2 spike protein, which is the main target for neutralizing antibodies.
The development of adaptive immune response, encompassing neutralizing antibodies and B-and T-lymphocytes, is crucial to controlling and clearing viral infections. It has been reported that individuals infected with SARS-CoV-2 develop an antibody titer around 15 days after the symptoms onset [3]. It is well-known that the antibody titer diminishes over time [2,19]; as expected, the participants included in our study with a history of COVID-19 infection showed the presence of IgGs related to SARS-CoV-2 before vaccination. When analyzing the samples at the first vaccine dose, participants with previous SARS-CoV-2 infection might develop a more rapid and sustained response to a COVID-19 vaccine than individuals naïve to COVID-19 since they had increased antibodies in the serum. At the time of administration of the second vaccine dose, all participants naïve to COVID-19 showed a further increase in IgG related to SARS-CoV-2 at similar levels to those observed with the first dose in participants with primary infection. In contrast, in participants with a history of COVID-19, the OD was similar between vaccine doses, suggesting that both groups reached a plateau. Because the neutralizing capacity of the vaccine-induced antibodies has already been well-demonstrated [20], here, we determined the seroresponse to establish IgG production against SARS-CoV-2.
Several meta-analyses suggest that in COVID-19 patients, CD4+ and CD8+ absolute counts may be valuable biomarkers in the prognosis of disease severity and recovery [14,21,22]. Disease severity has been linked to the lymphocyte-to-neutrophil cell count ratio (NLR) [14,23]. In Mexico, Montiel-Cervantes et al. studied the NRL in patients with severe COVID-19 and compared it with those of healthy controls and convalescent patients. The authors concluded that the NLR is a useful biomarker of survival in severe COVID-19 [24]. The NLR parameter depends on the total count of neutrophils and lymphocytes, and when one of these increases or decreases, the NLR changes. In our study, the NLR increased within their normal range at the second vaccine dose in participants naïve to COVID-19 and participants with previous SARS-CoV-2 infection. A slightly lower count of lymphocytes, without clinical significance, could explain the change in the samples taken after the second vaccine dose. It is well-known that the reduction of immune cell counts in the peripheral blood during viral infection may be caused by virus-induced destruction of T-cells or the mobilization of immune cells to the sites of infection, such as the lungs or lymphatic nodules [25]. Thus, a similar phenomenon may happen in a controlled way in the case of immunization.
Immune responses mediated by CD4+ T-lymphocytes have been associated with controlling SARS-CoV-2 infection [19,22]. Here, we analyzed the changes in the proportions of CD4+ T-lymphocytes and the memory phenotype induced by vaccination against COVID-19 in participants naïve to COVID-19 and participants with a history of SARS-CoV-2 infection. Before vaccination, there were no differences in the percentages of CD4+ T-lymphocytes and CD45RO+ memory T-lymphocytes between participants naïve to COVID-19 and participants with a history of SARS-CoV-2 infection. After follow-up, throughout the vaccine schedule, both participants naïve to COVID-19 and participants with previous SARS-CoV-2 infection showed an increase in CD4+ T-lymphocytes following the first and second vaccine doses and maintained the percentage of this cell population, in contrast to that reported in infected participants who showed a decrease in this cell population [25]. Interestingly, both groups tended to increase the percentage of memory CD45RO+CD4+ T-lymphocytes. Memory T-lymphocytes can be divided into central memory and effector-memory types. Effector-memory T-lymphocytes patrol the periph-eral blood and tissues, whereas central memory T-lymphocytes target the lymphoid nodules [11,26]. These memory T-lymphocyte subsets live longer than effector T-lymphocytes, and access to secondary lymphoid tissues contributes to recall responses upon booster vaccination or future infection [26,27]. These results could be evidence of the generation of a robust immune response mediated by T-lymphocytes induced by the distinct vaccine platforms that may have implications for long-term protective immunity.
As mentioned above, virus-specific CD4+ T-lymphocytes may differentiate into multiple distinct phenotypes in response to SARS-CoV-2 infection. These include TFH as a critical component of the potent humoral immune response [28]. Interestingly, our study observed an increased frequency of TFH in participants naïve to COVID-19 after the first vaccine dose, possibly because the interaction with T-lymphocytes is required to develop efficient activation of B-lymphocytes. In contrast, this phenomenon was not wholly seen in the participants with a previous history of SARS-CoV-2 infection, possibly because they had memory B cells that could be activated by vaccination. Our results show the frequency of circulating TFH specific for SARS-CoV-2 generated during acute SARS-CoV-2 infection, which has been associated with reduced disease severity [29]. In contrast, after the second vaccine dose, a decrease in TFH was detected in both groups. In line with our findings, it has been reported that during COVID-19 infection, SARS-CoV-2-specific TFH decreases the CCR6 expression favoring homing to the mucosal airway [29], thus reducing their frequency in blood. One limitation of this study was not performing IL-21 analysis in serum samples; it has been shown that IL-21 promotes B and plasma cell development [30], as well as stimulates the differentiation of TFH. It is necessary to consider analyzing the IL-21 in serum samples in an intracellular manner after in vitro stimuli.
Although antibodies are a central component of vaccine efficacy, B-lymphocytes are fundamental to the adaptive immune system. In particular, the memory B-lymphocytes are studied as evidence of long-term immune protective immunization [31]. Our study analyzed the proportion of memory B-lymphocytes throughout the vaccine schedule; we detected no differences between participants naïve to COVID-19 and participants with a history of SARS-CoV-2 infection. However, both groups show a decrease in CD27+CD21+ B-lymphocytes after vaccination. The peripheral decrease in CD27+CD21+ B-lymphocytes could be explained by homing to lymphatic nodes to establish germinal centers [32].
After the first vaccine dose, the CD27+CD21− B-lymphocytes, considered effectormemory B-lymphocytes, significantly increased after the first vaccine dose, even in participants with a history of SARS-CoV-2 infection. The effector-memory B-lymphocytes are cells that can quickly and efficiently respond to an antigen recall and differentiate into plasmatic cells [32]; this population is increased due to immunization. However, after the second vaccine dose, the percentage of effector memory was similar to the percentage before immunization. This can be explained because, with the application of the second vaccine dose, part of the effector-memory B-lymphocytes differentiates to plasmatic cells.
We also analyzed the human Fc receptor-like 4 (FcRL4), a molecule member of the family homologous to FcγRI in one or more domains and whose expression is associated with memory B-lymphocytes [33]. Typically, FcRL4 is expressed in memory B-lymphocytes localized in the sub-epithelial regions of lymphoid tissues and tonsils [33]. In our study, we detected similar levels of the expression of FcRL4 in central memory B-lymphocytes. Meanwhile, in the case of effector-memory B-lymphocytes, the expression of FcRL4 increased throughout the vaccination schedule in both groups. Increased FcRL4+ B-lymphocytes have been reported in VIH [34] and rheumatoid arthritis [35,36]. Additionally, these B-lymphocytes are associated with an increase in pro-inflammatory cytokines, such as IL-6 [34]. It is important to point out that the function of FcRL4 has been associated with an enhanced response to the TLR9 and may function to switch B-lymphocyte responsiveness from adaptive BCR-mediated signaling to innate TLR-receptor signaling [33,34]. More studies are needed to determine if this signaling pathway is important in vaccines that use RNA or DNA.
Finally, because immune-bridging studies are currently based only on IgG evaluation, our findings can be used as additional evidence to demonstrate vaccine protective effects. After the second dose, the nonvaccinated subjects showed the same immunological changes observed in recovered COVID-19 patients after the first dose. Further studies analyzing the specificity against RBD inside the cell subsets studied here can be helpful to determine a minimal range of cells (TFH or FcRL4 B lymphocytes) needed to maintain an efficient memory immune response in response to antigen. Despite IgG evaluation helping to demonstrate vaccine efficacy, it is well-known that the levels will decrease over time. In contrast, assessing specific memory cells is vital to predicting the ability to respond to future infections [37,38]. Advances in this area are necessary in cases such as the development of vaccine schedules or booster dose schemes by regulatory authorities, and vaccination based on prioritization subjects such as healthcare staff, army, or vulnerable subjects; or based on public health when vaccine production and supply are insufficient.

Conclusions
In conclusion, immunization against SARS-CoV-2-independently of the vaccine platform-induces IgG production after the first vaccine dose. According to our data, the specific antibody production could result from the TFH-B-lymphocyte interaction. Following a second vaccine dose, both anti-SARS-CoV-2 antibodies and memory cells (Tand B-lymphocytes) were found in the systemic circulation, possibly to prevent subsequent infections ( Figure 11). In addition, the late-stage differentiation of effector-memory Blymphocytes to plasmatic cells was observed with the expression of FcRL4. Finally, because we did not observe differences between vaccines, the results obtained in this work can be used to expand the number of immunological studies to have more bases to perform immuno-bridging analysis during the evaluation and authorization of vaccine platforms. subsequent infections (Figure 11). In addition, the late-stage differentiation of effectormemory B-lymphocytes to plasmatic cells was observed with the expression of FcRL4. Finally, because we did not observe differences between vaccines, the results obtained in this work can be used to expand the number of immunological studies to have more bases to perform immuno-bridging analysis during the evaluation and authorization of vaccine platforms. Figure 11. Proposal model of T-and B-lymphocytes as central players after SARS-CoV-2 vaccination. (A) Immune response against SARS-CoV-2. Infected cells might be recognized and eliminated by NK cells, followed by recruitment of DCs. DCs become APCs and migrate to lymphatic node to present viral antigens to T-lymphocytes and generate an adaptive immune response composed by CD4+ T-lymphocytes. TFH interacts with B-lymphocytes to produce antibodies against the virus. (B) Immune response induced by vaccination. Vaccine induces production of high levels of S protein, and adjuvants enhance recruitment and differentiation of DCs into APCs. In COVID-19(−) subjects, APCs present the antigen to T-lymphocytes. TFH helps S Figure 11. Proposal model of T-and B-lymphocytes as central players after SARS-CoV-2 vaccination. (A) Immune response against SARS-CoV-2. Infected cells might be recognized and eliminated by NK cells, followed by recruitment of DCs. DCs become APCs and migrate to lymphatic node to present viral antigens to T-lymphocytes and generate an adaptive immune response composed by CD4+ Tlymphocytes. TFH interacts with B-lymphocytes to produce antibodies against the virus. (B) Immune response induced by vaccination. Vaccine induces production of high levels of S protein, and adjuvants enhance recruitment and differentiation of DCs into APCs. In COVID-19(−) subjects, APCs present the antigen to T-lymphocytes. TFH helps S protein-specific B-lymphocytes to differentiate into plasmatic cells and promote production of IgGs against S protein. In contrast, in recovered COVID-19(+) subjects, SARS-CoV-2 specific memory T-lymphocytes, and memory B-lymphocytes developed after infection, could be activated by vaccine application and quickly and efficiently respond to antigen recall. NK, natural killer cell; DC, dendritic cell; APC, antigen-presenting cell; TFH, follicular helper T-lymphocyte. Created using BioRender.com.