title: SARS-CoV-2 serology across scales: a framework for unbiased seroprevalence estimation incorporating antibody kinetics and epidemic recency

abstract: Serosurveys are a key resource for measuring SARS-CoV-2 cumulative incidence. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce adjusted estimates of seroprevalence from raw serosurvey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce adjusted seroprevalence estimates from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between reported and adjusted estimates of over two-fold in the results of some surveys, and provide a tool for practitioners to generate adjusted estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.


title: ADataViewer: Exploring Semantically Harmonized Alzheimer's Disease Cohort Datasets

abstract:
INTRODUCTIONCurrently, AD cohort datasets are difficult to find, lack across-cohort interoperability, and the content of the shared datasets often only becomes clear to third-party researchers once data access has been granted.

METHODSWe accessed and systematically investigated the content of 20 major AD cohort datasets on data-level. A medical professional and a data specialist manually curated and semantically harmonized the acquired datasets. We developed a platform that facilitates data exploration.

RESULTSWe present ADataViewer, an interactive platform that facilitates the exploration of 20 cohort datasets with respect to longitudinal follow-up, demographics, ethnoracial diversity, measured modalities, and statistical properties of individual variables. Additionally, we publish a variable mapping catalog harmonizing 1,196 variables across the 20 cohorts. The platform is available under https://adata.scai.fraunhofer.de/.

DISCUSSIONADataViewer supports robust data-driven research by transparently displaying cohort dataset content and suggesting datasets suited for discovery and validation studies based on selected variables of interest.

category: health informatics


title: Analytical performances of the COVISTIX and Panbio antigen rapid tests for SARS-CoV-2 detection in an unselected population (all commers)

abstract:
ImportanceA steady increase in acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases worldwide is causing some regions of the world to withstand a third or even fourth wave of contagion. Swift detection of SARS-CoV-2 infection is paramount for the containment of cases, prevention of sustained contagion; and most importantly, for the reduction of mortality.

ObjectiveTo evaluate the performance and validity of the COVISTIX rapid antigen test, for the detection of SARS-CoV-2 in an unselected population and compare it to Panbio rapid antigen test and RT-PCR.

DesignThis is comparative effectiveness study; samples were collected at two point-of-care facilities in Mexico City between May and August 2021.

ParticipantsRecruited individuals were probable COVID-19 cases, either symptomatic or asymptomatic persons that were at risk of infection due to close contact to SARS-CoV-2 positive cases.

Diagnostic interventionRT-PCR was used as gold standard for detection of SARS-CoV-2 in nasal and nasopharyngeal swabs, study subjects were tested in parallel either with the COVISTIX or with Panbio rapid antigen test.

Main outcomeDiagnostic performance of the COVISTIX assay is adequate in all commers since its accuracy parameters were not affected in samples collected after 7 days of symptom onset, and it detected almost 65% of samples with a Ct-value between 30 and 34.

ResultsFor the population tested with COVISTIX (n=783), specificity and sensitivity of the was 96.0% (CI95% 94.0-98.0) and 81% (CI95% 76.0-85.0), as for the Panbio (n=2202) population, was 99.0% (CI95%: 0.99-1.00) and 62% (CI%: 58.0-64.0%), respectively.

Conclusions and relevanceThe COVISTIX rapid antigen test shows a high performance in all comers, thus, this test is also adequate for testing patients who have passed the peak of viral shedding or for asymptomatic patients.

category: infectious diseases


title: Study of effect modifiers of genetically predicted CETP reduction

abstract:
Genetic variants in drug targets can be used to predict the effect of drugs. Here, we extend this principle to assess how sex and body mass index may modify the effect of a genetically predicted lower CETP levels on biomarkers and cardiovascular outcomes.

We found sex and BMI to be modifiers of the association between genetically predicted lower CETP and lipid biomarkers in UK Biobank participants. Female sex and lower BMI were associated with higher HDL-cholesterol and lower LDL-cholesterol for a same genetically predicted reduction in CETP concentration. We found that sex also modulated the effect of genetically lower CETP on cholesterol efflux capacity in samples from the Montreal Heart Institute Biobank. However, these modifying effects did not extend to sex-differences in cardiovascular outcomes in our data.

Our results provide insight on the clinical effects of CETP inhibitors in the presence of effect modification based on observational genetic data. The approach can support precision medicine applications and help assess the external validity of clinical trials.

category: genetic and genomic medicine


title: Y380Q novel mutation in receptor-binding domain of SARS-CoV-2 spike protein together with C379W interfere in the neutralizing antibodies interaction

abstract:
BackgroundThe emergence of SARS-CoV-2 variants is a current public health concern possibly impacting COVID-19 disease diagnosis, transmission patterns and vaccine effectiveness.

ObjectivesTo describe the SARS-CoV-2 lineages circulating early pandemic among samples with S gene dropout and characterize a novel mutation in receptor-binding domain (RBD) of viral spike protein.

Study designAdults and children older than 2 months with signs and symptoms of COVID-19 were prospectively enrolled from May to October 2020 in Porto Alegre, Brazil. All participants performed RT-PCR assays for diagnosing SARS-CoV-2, samples with S gene dropout and Ct < 30 (cycle threshold) were submitted to whole genome sequencing (WGS), and homology modeling and physicochemical properties analysis were performed.

Results484/1,557 participants tested positive for SARS-CoV-2. The S gene dropout was detected in 7.4% (36/484) as early as May, and a peak was observed in early August. WGS was performed in 8 samples. The B.1.1.28, B.1.91 and B.1.1.33 lineages were circulating in early pandemic. The RBD novel mutation (Y380Q) was found in one sample occurring simultaneously with C379W and V395A, and the B.1.91 lineage in the spike protein.

ConclusionMutations in the SARS-CoV-2 spike region were detected early in the COVID-19 pandemic in Southern Brazil, regarding the B.1.1.28, B.1.91 and B.1.1.33 lineages identified. The novel mutation (Y380Q) with C379W, modifies important RBD properties, which may interfere with the binding of neutralizing antibodies (CR3022, EY6A, H014, S304).

HighlightsO_LICharacterization of novel mutation (Y380Q) in RBD of SARS-CoV-2 spike protein
C_LIO_LIThe Y380Q and C379W modify important properties in the SARS-CoV-2 RBD region
C_LIO_LIThe RBD mutations may interfere with the binding of neutralizing antibodies
C_LIO_LIThe B.1.1.28, B.1.91 and B.1.1.33 lineages were circulating in early pandemic
C_LI


title: Adjuvant Testosterone Therapy in Chronic Heart Failure (ATTIC) - A Randomised Open-Label Trial

abstract:
IntroductionHeart failure is a major contributor to morbidity and mortality in the geriatric population, with no promising therapy currently available with considerable benefit. Testosterone therapy is an emerging viable treatment option given its beneficial effects, including improving cardiac functional capacity, alleviating symptoms, and low cost, amongst others.

MethodsWe have planned an open-label, parallel design, 1:1 randomized controlled trial which aims to recruit 160 adult males above the age of 60 diagnosed with chronic stable heart failure fulfilling the eligibility criteria. The participants will be randomized into two groups of 80 each. Both groups will receive standard recommended treatment regime of chronic stable heart failure and intervention arm participants will receive additional testosterone gel. All participants will be assessed at baseline, 4 weeks, 6 weeks and 12 weeks. The primary endpoints will assess the difference in functional capacity, frailty and quality of life at 3 months compared to baseline. The secondary endpoints will include the mean change from baseline at 3 months in cardiac remodelling using echocardiography, serum brain natriuretic peptide levels, the incidence of adverse drug reaction.

Statistical AnalysisThe data will be analysed with the help of SPSS software. Primary objectives of change in 6MWT, Frailty index and quality of life will be analysed using the student t-test. The statistical significance will be defined as p-value <0.05 and taking confidence level as 95%.

Ethical clearanceInstitutional Ethics Committee clearance taken via letter no AIIMS/IEC/20/847, dated 21/11/2020

category: geriatric medicine


title: Fundamental limits on inferring epidemic resurgence in real time

abstract:
We find that epidemic resurgence, defined as an upswing in the effective reproduction number (R) of the contagion from subcritical to supercritical values, is fundamentally difficult to detect in real time. Inherent latencies in pathogen transmission, coupled with smaller and intrinsically noisier case incidence across periods of subcritical spread, mean that resurgence cannot be reliably detected without significant delays of the order of the generation time of the disease, even when case reporting is perfect. In contrast, epidemic suppression (where R falls from supercritical to subcritical values) may be ascertained 5-10 times faster due to the naturally larger incidence at which control actions are generally applied. We prove that these innate limits on detecting resurgence only worsen when spatial or demographic heterogeneities are incorporated. Consequently, we argue that resurgence is more effectively handled proactively, potentially at the expense of false alarms. Timely responses to recrudescent infections or emerging variants of concern are more likely to be possible when policy is informed by a greater quality and diversity of surveillance data than by further optimisation of the statistical models used to process routine outbreak data.

Author summaryThe timely detection of epidemic resurgence (i.e., upcoming waves of infected cases) is crucial for informing public health policy, providing valuable signals for implementing interventions and identifying emerging pathogenic variants or important population-level behavioural shifts. Increases in epidemic transmissibility, parametrised by the time-varying reproduction number, R, commonly signify resurgence. While many studies have improved computational methods for inferring R from case data, to enhance real-time resurgence detection, few have examined what limits, if any, fundamentally restrict our ability to perform this inference. We apply optimal Bayesian detection algorithms and sensitivity tests and discover that resurgent (upward) R-changes are intrinsically more difficult to detect than equivalent downward changes indicating control. This asymmetry derives from the often lower and stochastically noisier case numbers that associate with resurgence, and induces detection delays on the order of the disease generation time. We prove these delays only worsen if spatial or demographic differences in transmissibility are modelled. As these fundamental limits exist even if case data are perfect, we conclude that designing integrated surveillance systems that fuse potentially timelier data sources (e.g., wastewater) may be more important than improving R-estimation methodology and deduce that there may be merit (subject to false alarm costs) in conservative resurgence response initiatives.


title: Fundamental limits on inferring epidemic resurgence in real time using effective reproduction numbers


title: BACTERIAL INFECTION AND ANTIBIOTIC RESISTANCE IN PATIENTS WITH HUMAN IMMUNODEFICIENCY VIRUS PRESENTING LOWER RESPIRATORY TRACT INFECTION IN NIGERIA

abstract: Lower Respiratory Tract Infection (LRTI) is associated with mortality and prolonged antibiotics use among HIV/AIDS patients. Sputum samples were collected from 134 HIV/AIDS patients with LRTI and productive cough, visiting University of Abuja Teaching Hospital, Nigeria, to determine the bacterial aetiologies and antibiotic resistance profile. Adequate for culture sputum samples were observed in only 119 subjects (75 females and 44 males) and cultured using standard procedure. Isolates were identified by biochemical method and 16SrRNA gene amplification, purification, sequencing and database nucleotide blast. Antibiotic susceptibility tests were performed and interpreted according to Clinical and Laboratory Standard Institute (CLSI) procedures. Bacteria associated LRTI was found in 20.2% of the patients and Klebsiella pneumonia (29.7%); Enterobacter cloacae (16.7%); Enterobacter hormaechei subsp. xiangfangensis (12.5%); Pseudomonas parafulva; Pseudomonas aeruginosa; Pseudomonas alcaliphila; Klebsiella aerogenes (8.3%); Comamonas testosteroni; Escherichia coli; Acinetobacter junii; Acinetobacter soli and Acinetobacter baumannii were implicated. Isolates show high resistance to amoxicillin-clavulanic acid at 94.1%, trimethoprim-sulfamethoxazole at 75.0% and cefotaxime at 70.0%. The Multiple Antibiotic Resistance (MAR) index of most isolates (62.5%) is within 0.3-0.8 in a range of 0.0 to 0.8. Isolates of the same species were found to have different MAR index in different patients. However, E. cloacae, E. hormaechei subsp. xiangfangensis, A. baumanni and 71.4% of K. pneumonia were Multi-drug Resistant (MDR). Interestingly, Gentamycin, Ciprofloxacin and Imipenem were effective against MDR isolates and showed significant negative correlation with MAR index. We propose that antibiotics with efficacy against MDR isolates could be used to down regulate the selective pressure of other antibiotics, and these MDR pathogens, including those rarely associated with human infection poses potential threat, similar to Methicillin Resistant Staphylococcus aureus (MRSA). Particularly, among the immunocompromised. Furthermore, HIV/AIDS patients present good metrics for profiling the burden and spread of antibiotic resistant bacteria in poor countries.


title: SARS-COV2 mutant-specific T cells and neutralizing antibodies after vaccination and up to 1 year after infection

abstract:
ObjectiveWe investigated blood samples from fully SARS-CoV2-vaccinated subjects and from previously positive tested patients up to one year after infection with SARS-CoV2, and compared short- and long-term T cell and antibody responses, with a special focus on the recently emerged delta variant (B.1.617.2).

Methods and ResultsIn 23 vaccinated subjects, we documented high anti-SARS-CoV2 spike protein receptor binding domain (RBD) antibody titers. Average virus neutralization by antibodies, assessed as inhibition of ACE2 binding to RBD, was 2.2-fold reduced for delta mutant vs. wild type (wt) RBD. The mean specific antibody titers were lower one year after natural infection than after vaccination; ACE2 binding to delta mutant vs. wt RBD was 1.65-fold reduced. In an additional group, omicron RBD binding was reduced compared to delta.

Specific CD4+ T cell responses were measured after stimulation with peptides pools from wt, alpha, beta, gamma, or delta variant SARS-CoV2 spike proteins by flow cytometric intracellular cytokine staining. There was no significant difference in cytokine production of IFN-{gamma}, TNF-, or IL-2 between vaccinated subjects. T cell responses to wt or mutant SARS-CoV2 spike were significantly weaker after natural occurring infections compared to those in vaccinated individuals.

ConclusionAntibody neutralisation of the delta mutant was reduced compared to wt, as assessed in a novel inhibition assay with a finger prick blood drop. Strong CD4 T cell responses were present against wt and mutant SARS-CoV2 variants, including the delta (B.1.617.2) strain, in fully vaccinated individuals, whereas they were partly weaker 1 year after natural infection. Hence, immune responses after vaccination are stronger compared to those after naturally occurring infection, pointing out the need of the vaccine to overcome the pandemic.

category: allergy and immunology


title: Antibody responses to BNT162b2 mRNA vaccine: infection-naive individuals with abdominal obesity warrant attention

abstract:
ObjectiveThe excess of visceral adipose tissue might hinder and delay the immune response. How people with abdominal obesity will respond to mRNA vaccines against SARS-CoV-2 is yet to be established. We evaluated SARS-CoV-2-specific antibody responses after the first and second dose of the BNT162b2 mRNA vaccine comparing the response of individuals affected by abdominal obesity (AO) to those without, discerning between individuals with or without prior infection.

MethodsIgG neutralizing antibodies against the Trimeric complex (IgG-TrimericS) were measured at four time points: at baseline, at day 21 after vaccine dose-1, at one month and three months after dose-2. Nucleocapsid antibodies were assessed to detect prior SARS-CoV-2 infection. Waist circumference was measured to determine abdominal obesity.

ResultsBetween the first and third month after vaccine dose-2, the drop in IgG-TrimericS levels was more remarkable in individuals with AO compared to those without AO (2.44 fold [95%CI: 2.22-2.63] vs 1.82 fold [95%CI: 1.69-1.92], respectively, p<0.001). Multiple linear regression confirmed this result even when adjusting for possible confounders (p<0.001).

ConclusionsOur findings highlight the need to extend the duration of serological monitoring of antibody levels in infection-naive individuals with abdominal obesity, a higher-risk population category in terms of possible weaker antibody response.

category: endocrinology


title: CHARACTERIZING AND MANAGING AN EPIDEMIC: A FIRST PRINCIPLES MODEL AND A CLOSED FORM SOLUTION TO THE KERMACK AND MCKENDRICK EQUATIONS

abstract: We derived a closed-form solution to the original epidemic equations formulated by Kermack and McKendrick in 1927 (1). The complete solution is validated using independently measured mobility data and accurate predictions of COVID-19 case dynamics in multiple countries. It replicates the observed phenomenology, quantitates pandemic dynamics, and provides simple analytical tools for policy makers. Of particular note, it projects that increased social containment measures shorten an epidemic and reduce the ultimate number of cases and deaths. In contrast, the widely used Susceptible-Infectious-Recovered (SIR) models, based on an approximation to Kermack and McKendricks original equations, project that strong containment measures delay the peak in daily infections, causing a longer epidemic. These projections contradict both the complete solution and the observed phenomenology in COVID-19 pandemic data. The closed-form solution elucidates that the two parameters classically used as constants in approximate SIR models cannot, in fact, be reasonably assumed to be constant in real epidemics. This prima facie failure forces the conclusion that the approximate SIR models should not be used to characterize or manage epidemics. As a replacement to the SIR models, the closed-form solution and the expressions derived from the solution form a complete set of analytical tools that can accurately diagnose the state of an epidemic and provide proper guidance for public health decision makers.

category: epidemiology


title: Place, cause and expectedness of death and relationship to the deceased are associated with poorer experiences of end-of-life care and challenges in early bereavement: Risk factors from an online survey of people bereaved during the COVID-19 pandemic

abstract:
ObjectivesTo identify clinical and demographic risk factors for sub-optimal end-of-life care and pandemic-related challenges prior to death and in early bereavement.

DesignOnline open national survey of adults bereaved in the UK from 16 March 2020-5 January 2021, recruited via media, social media, national associations and organisations.

SettingGeneral population, UK.

Participants711 participants, mean age 49.5 (SD 12.9, range 18-90). 395 (55.6%) had experienced the death of a parent, 152 (21.4%) a partner. 628 (88.6%) were female and 33 (4.7%) from a minority ethnic background. The mean age of the person who died was 72.2 (SD 16.1, range miscarriage to 102 years). 311 (43.8%) deaths were from confirmed/suspected COVID-19, and 410 (57.8%) deaths occurred in hospital.

Main outcome measuresEnd-of-life care experiences (six items, e.g. involvement in care decisions) and pandemic-related challenges before and after death (six items, e.g. unable to visit prior to death).

ResultsDeaths in hospital/care home increased the likelihood of: unable to visit prior to death, unable to say goodbye as wanted, limited contact in last days of life (all P<0.001). Deaths in hospice/at home increased the likelihood of: involved in care decisions (P<0.001), well supported by healthcare professionals (HCPs) after the death (P=0.003). Hospice deaths increased the likelihood of being given bereavement support information, which was least likely for care home deaths (P<0.001). Hospital deaths decreased the likelihood of knowing the contact details for the responsible care professional (P=0.001). Bereavement due to COVID-19 decreased the likelihood of: involvement in care decisions (P<0.001), feeling well supported by HCPs after the death (P<0.001), and increased the likelihood of: being unable to say goodbye (OR=0.348; 95% CI: 0.2 to 0.605), social isolation and loneliness (OR=0.439; 95% CI: 0.261 to 0.739), limited contact with relatives/friends (OR=0.465; 95% CI: 0.254 to 0.852). Expected deaths were associated with higher likelihood of feeling involved, informed, and well supported by HCPs (all P<0.001). The deceased being a partner or child increased the likelihood of knowing the contact details for the responsible care professional (P=0.001), being able to visit (P<0.001) and given bereavement support information (P<0.001). Being a bereaved partner strongly increased odds of social isolation and loneliness, e.g. OR = 0.092 (95% CI: 0.028 to 0.297) partner versus distant family member.

ConclusionsFour clear risk factors were found for poorer end-of-life care and pandemic-related challenges in bereavement: place, cause and expectedness of death, and relationship to the deceased.

O_TEXTBOXWhat is already known on this topic?O_LISince the start of the pandemic, over 20 million family members and friends have been bereaved due to COVID-19, with millions more bereaved due to other causes.
C_LIO_LIBereavement of any cause during the COVID-19 pandemic is associated with specific challenges, including limited access to people before their death, pressure on health and social care providers, quarantining due to infection or exposure, lockdowns and social distancing.
C_LIO_LIThere remains little evidence to inform optimal clinical practice, bereavement support and the policy response to COVID-19 as a mass bereavement event.
C_LI

What this study addsO_LIOur study highlights four risk factors for poorer end-of-life care and increased risk of pandemic-related challenges in early bereavement: place, cause and expectedness of death and relationship to the deceased.
C_LIO_LICOVID-19 deaths, hospital and care home deaths and unexpected deaths were generally associated with poorer outcomes, while being a partner of the person who died (regardless of cause) and bereavement due to COVID-19 increased the odds of experiencing social isolation and loneliness in bereavement.
C_LIO_LIThese factors should be taken into account in clinical practice, policy and bereavement support.
C_LI

C_TEXTBOX

category: palliative medicine


abstract:
ObjectiveTo describe trends of COVID-19 pediatric admissions number during the first 24 weeks of COVID-19 vaccination.

DesignA retrospective study was conducted in children (0-18 years), admitted in two pediatric hospitals of Rio de Janeiro city, between January 17 and July 3, 2021 with confirmed COVID-19 by reverse transcription polymerase chain reaction or serological tests. Trends of COVID-19 pediatric admissions number during the first 24 weeks of COVID-19 vaccination in Rio de Janeiro, Brazil and the pre-vaccine period were measured by linear regression.

ParticipantsChildren admitted in pediatric hospitals in Rio de Janeiro, city, Brazil

ResultsThe number of total admitted patients (with all diseases) were 5340 during the pre-vaccine period, being 94 (1.8%) of them with confirmed COVID-19, and 4182 children admitted during the vaccine period, with 86 confirmed COVID-19 patients (2.1 %) (p=0.29). Media of cases admitted per/week were 2.02 in pre-vaccine period and 3.6 during the first 24 weeks of COVID vaccination (p=0.009). One death was reported in the pre-vaccine period and four in the vaccine period (p=0.14). Trends of increase in the number of admitted cases were verified both in the pre-vaccine period as in the vaccine period, being more expressive in the last one.

ConclusionThere was trend of increase in number of children admitted with confirmed COVID-19 during the first 24 weeks of COVID-vaccination in Rio de Janeiro, city. Considering that few people were fully vaccinated, reducing of number of admitted children with confirmed COVID-19 was not verified.

category: pediatrics


title: A Machine Learning Approach to Identifying Delirium from Electronic Health Records

abstract:
BackgroundDespite the well-known impact of delirium on long-term clinical outcomes, identification of delirium in electronic health records (EHR) remains difficult due to inadequate assessment or documentation of delirium. The purpose of this research is to present a classification model that identifies delirium using retrospective EHR data. The classification model would support the additional identification of delirium cases otherwise undocumented during routine practice.

MethodsDelirium was confirmed with the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Age, sex, Elixhauser comorbidity index, drug exposures, and diagnoses were used as features to train the logistic regression and multi-layer perceptron models. The clinical notes from the EHR were parsed to supplement the features that were not recorded in the structured data. The model performance was evaluated with a 5-fold cross-validation area under the receiver operating characteristic curve (AUC).

ResultsSeventy-six patients (17 cases and 59 controls) with at least one CAM-ICU evaluation result during ICU stay from January 30, 2018 to February 20, 2018 were included in the model. The multi-layer perceptron model achieved the best performance in identifying delirium; mean AUC of 0.967 {+/-} 0.019. The mean positive predictive value (PPV), mean negative predicted value (NPV), mean sensitivity, and mean specificity of the MLP model were 0.9, 0.88, 0.56, and 0.95, respectively.

ConclusionA simple classification model showed a mean AUC over 0.95. This model promises to identify delirium cases with EHR data, thereby enable a sustainable infrastructure to build a retrospective cohort of delirium in the ICU. The cohort would be useful for the evaluation of long-term sequelae of delirium in ICU.

category: psychiatry and clinical psychology


title: A Comparative Study Between Nasopharyngeal/Oropharyngeal, Faecal and Saliva Viral Shedding In Ghanaian COVID-19 Patients attending KATH from October-December, 2020

abstract:
BackgroundDiagnostic testing for the current SARS-CoV-2 infections involves the collection and testing of invasive pharyngeal specimens by qualified Health workers. Though fully clad in personal protective equipment, the concern is that sampling in close proximity to the patient poses as a major health hazard. The present study sought to verify if saliva or faeces could become a possible surrogate for pharyngeal samples for SARS-CoV 2 testing in suspected Ghanaian COVID-19 patients.

ObjectivesTo ascertain if there is SARS-CoV 2 viral shedding in the saliva and faecal samples of Ghanaian COVID-19 patients, their sensitivity and specificity as compared to pharyngeal samples.

MethodFifty (50) recruited COVID-19 patients who have been confirmed via RT-PCR using their nasopharyngeal/oropharyngeal samples and twenty (20) SARS-CoV 2 negative suspected patients each provided some faecal and saliva sample for RT-PCR analysis for SARS-CoV 2.

ResultsForty-three (43) out of the fifty (50) COVID-19 patients recruited representing 86% tested positive for SARS-CoV 2 via their saliva sample whiles all their faecal samples tested positive for SARS-CoV 2 representing 100%. The sensitivity of saliva samples was 86% whiles the specificity was 100% but the sensitivity and specificity of the faecal samples were all 100%.

ConclusionThere is indeed viral shedding of SARS-CoV 2 in the saliva and faeces of Ghanaian COVID-19 patients just like their counterparts in other parts of the world. Saliva and faeces could possibly become an alternative sample to the current in place of the invasive pharyngeal samples for SARS-CoV 2 testing in resource limited settings. Further research to explore this possibility at different testing sites with larger sample size is recommended.

category: public and global health


title: Association between psychological factors related to pain and instrumental activities of daily living disability in older adults with knee osteoarthritis

abstract:
PurposeThe population of older adults with knee osteoarthritis (OA)-related disabilities is increasing globally. This study aimed to investigate the psychological factors associated with instrumental activities of daily living (IADL) disability in older adults with knee OA.

Materials and MethodsA cross-sectional study was conducted on 179 patients with knee OA aged [≥] 65 years. The six-item short form of the Pain Catastrophizing Scale (PCS-6), the four-item short form of the Pain Self-Efficacy Questionnaire (PSEQ-4), and the fifteen-item Geriatric Depression Scale (GDS-15) were used to assess psychological factors. IADL status was assessed using eight activity items. Participants were divided into IADL-disabled and non-disabled groups. Binary logistic regression analyses were performed with the IADL disability status as the dependent variable. The PCS-6, PSEQ-4, and GDS-15 tools were included as independent variables in the logistic regression model. Demographics, motor functions, and pain intensity were also included as confounders.

ResultsOf the total participants, 88 (49.1%) showed disability in conducting IADL. PSEQ-4 (odds ratio =0.90, 95%; confidence interval=0.82-0.99, p=0.02) was a significant independent variable among all psychological factors.

ConclusionOur study showed the importance of assessing self-efficacy using the PSEQ-4 in relation to IADL disability in older adults with knee OA.

category: rehabilitation medicine and physical therapy


title: Psychological factors associated with instrumental activities of daily living disability in older adults with knee osteoarthritis


title: Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a wearable neural interface

abstract: Prosthetics and orthotics have been recognized for decades as a potential means to restore hand function and independence to individuals living with impairment due to stroke. However, 75% of stroke survivors, caregivers, and health care professionals (HCP) believe current practices are insufficient, specifically calling out the upper extremity as an area where innovation is needed to develop highly usable prosthetics/orthotics for the stroke population. A promising method for controlling upper limb technologies is to infer movement intent non-invasively from surface electromyography (EMG) activity. While this approach has garnered significant attention in the literature, existing technologies are often limited to research settings and struggle to meet stated user needs. To address these limitations, we have developed the NeuroLife(R) EMG System, which consists of a wearable forearm sleeve with 150 embedded electrodes and associated hardware and software to record and decode surface EMG. Here, we demonstrate accurate decoding of 12 functional hand, wrist, and forearm movements, including multiple types of grasps from participants with varying levels of chronic impairment from stroke, with an overall accuracy of 77.1{+/-}5.6%. Importantly, we demonstrate the ability to decode a subset of 3 fundamental movements in individuals with severe hand impairment at 85.4{+/-}6.4% accuracy, highlighting the potential as a control mechanism for assistive technologies. Feedback from stroke survivors who tested the system indicates that the sleeves design meets various user needs, including being comfortable, portable, and lightweight. The sleeve is in a form factor such that it can be used at home without an expert technician and can be worn for multiple hours without discomfort. Taken together, the NeuroLife EMG System represents a platform technology to record and decode high-definition EMG for the eventual real-time control of assistive devices in a form factor designed to meet user needs.


title: Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface


title: COVID-19 Bimodal Clinical and Pathological Phenotypes

abstract:
BackgroundPatients with coronavirus disease-2019 (COVID-19) present varying clinical complications. Different viral load and host response related to genetic and immune background are probably the reasons for these differences. We aimed to sought clinical and pathological correlation that justifies the different clinical outcomes among COVID-19 autopsies cases.

MethodsMinimally invasive autopsy was performed on forty-seven confirmed COVID-19 patients from May-July, 2020. Electronic medical record of all patients was collected and a comprehensive histopathological evaluation was performed. Immunohistochemistry, immunofluorescence, special stain, western blotting and post-mortem real-time reverse transcriptase polymerase chain reaction on fresh lung tissue were performed.

ResultsWe show that 5/47 (10,6%) patients present a progressive decline in oxygenation index for acute respiratory distress syndrome (PaO2/FiO2 ratio), low compliance levels, interstitial fibrosis, high -SMA+ cells/protein expression, high collagens I/III deposition and NETs(P<0.05), named as fibrotic phenotype (N=5). Conversely, 10/47 (21,2%) patients demonstrated progressive increase in PaO2/FiO2 ratio, high pulmonary compliance levels, preserved elastic framework, increase thrombus formation and high platelets and D-dimer levels at admission (P<0.05), named as thrombotic phenotype. While 32/47 (68,1%) had a mixed phenotypes between both ones.

ConclusionsWe believe that categorization of patients based on these two phenotypes can be used to develop prognostic tools and potential therapies since the PaO2/FiO2 ratio variation and D-dimer levels correlate with the underlying fibrotic or thrombotic pathologic process, respectively; which may indicate possible clinical outcome of the patient.

category: respiratory medicine


title: Exploration of Alzheimer's Disease MRI Biomarkers Using APOE4 Carrier Status in the UK Biobank

abstract: Large-scale datasets enable novel strategies to refine and discover relations among biomarkers of disease. Here 30,863 individuals ages 44-82 from the UK Biobank were analyzed to explore MRI biomarkers associated with Alzheimers disease (AD) genetic risk as contrast to general effects of aging. Individuals homozygotic for the E4 variant of apolipoprotein E (APOE4) overlapped non-carriers in their 50s but demonstrated neurodegenerative effects on the hippocampal system beginning in the seventh decade (reduced hippocampal volume, entorhinal thickness, and hippocampal cingulum integrity). Phenome-wide exploration further nominated the posterior thalamic radiation (PTR) as having a strong effect, as well as multiple diffusion MRI (dMRI) and white matter measures consistent with vascular dysfunction. Effects on the hippocampal system and white matter could be dissociated in the homozygotic APOE4 carriers supporting separation between AD and cerebral amyloid angiopathy (CAA) patterns. These results suggest new ways to combine and interrogate measures of neurodegeneration.

category: neurology


title: Clinical and economic utility of a preterm birth predictor derived from an analysis of a large and diverse pregnancy cohort

abstract:
ObjectiveEvaluate clinical utility and cost effectiveness of identifying pregnancies at increased risk of preterm birth using a validated proteomic biomarker risk predictor to enable proactive intervention

Study DesignPregnancies at elevated risk ([≥] 15%) of preterm birth were identified in a cohort from TREETOP (NCT02787213), a study independent of biomarker development. In the screening arm, higher-risk subjects received simulated interventions based on published efficacy of multimodal treatment or care-management alone. Subjects in the non-screening arm received no interventions. Neonatal and maternal length of stay, neonatal mortality and morbidity and neonatal costs were compared between arms.

ResultsMultimodal/care-management modeled treatments predicted reductions in neonatal (30%/22%) and maternal (9.2%/8.5%) hospital stays, neonatal morbidity and mortality (41%/29%), and neonatal costs (34%/16%) for the screening vs. non-screening arm.

ConclusionModeled interventions applied to pregnancies identified as higher-risk by a proteomic biomarker risk predictor demonstrate clinically and economically meaningful improvements in neonatal and maternal outcomes.

category: obstetrics and gynecology


title: Detection of malignant peripheral nerve sheath tumors in patients with neurofibromatosis using aneuploidy and mutation identification in plasma

abstract:
Malignant peripheral nerve sheath tumors (MPNST) are the deadliest cancer that arises in individuals diagnosed with neurofibromatosis and account for nearly 5% of the 15,000 soft tissue sarcomas diagnosed in the United States each year. Comprised of neoplastic Schwann cells, primary risk factors for developing MPNST include existing plexiform neurofibromas (PN), prior radiotherapy treatment, and expansive germline mutations involving the entire NF1 gene and surrounding genes. PN develop in nearly 30-50% of patients with NF1 and most often grow rapidly in the first decade of life. One of the most important aspects of clinical care for NF1 patients is monitoring PN for signs of malignant transformation to MPNST that occurs in 10-15% of patients.

We perform aneuploidy analysis on ctDNA from 883 ostensibly healthy individuals and 28 patients with neurofibromas, including 7 patients with benign neurofibroma, 9 patients with PN and 12 patients with MPNST. Overall sensitivity for detecting MPNST using genome wide aneuploidy scoring was 33%, and analysis of sub-chromosomal copy number alterations (CNAs) improved sensitivity to 50% while retaining a high specificity of 97%. In addition, we performed mutation analysis on plasma cfDNA for a subset of patients and identified mutations in NF1, NF2, RB1, TP53BP2, and GOLGA2. Given the high throughput and relatively low sequencing coverage required by our assay, liquid biopsy represents a promising technology to identify incipient MPNST.

category: oncology


title: Common genetic alterations of SPOP-MATH domain in prostate cancer tissues and association with pathological tumor characteristic.

abstract: SPOP gene has a critical role in prostate cancer development and found high mutated in the prostate tumor through various populations. MATH domain represents an important site for SPOP-DNA linkage and other sensitive gene-gene interactions. To investigate the genetic alterations of the MATH domain of SPOP gene in prostate cancer biopsies and correlation with clinical and pathological parameters; DNA samples from 50 prostate cancer tissues were genotyped and confirmed by Sanger sequencing. The frequency and distribution of high frequent mutations were determined and correlated with the patients tumor characteristics. Among 50 samples 34 (68%) were carrying one or more common mutations. Novel frame shift deletion mutation: c.255delA (p.Leu86Phefs) was detected in eight patients (16%), in addition to five novel missense mutations with moderate frequency (6%) namely: c.209G>C (p.Arg70Pro), c.215A>C (p.Asn72Thr), c.334G>A (p.Glu112Lys), c.373T>C (p.Phe125Leu), and c.388G>A (p.Asp130Asn), All missense mutations located in MATH domain. The effects of novel mutations described in the MATH domain are uncertain. No significant differences between carriers and noncarriers of common mutations detected regarding Gleason score, prostate-specific antigen concentration PSA, and tumor stage [p > 0.05]. Clinical significance of mutations detected on prostate tumors progression can be investigated in future analysis. Our findings revealed novel SPOP alterations in prostate cancer tissues probably associated with cancer development.


title: Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.

abstract: The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole exome sequencing data of about 4,000 SARS-CoV-2-positive individuals were used to define an interpretable machine learning model for predicting COVID-19 severity. Firstly, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthly, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.


title: Longitudinal Analysis of the Determinants of Life Expectancy and Healthy Life Expectancy: A Causal Approach

abstract: Understanding the determinants of health is essential to designing effective strategies to advance economic growth, reduce disease and disability, and enhance quality of life. We undertake a comprehensive outlook on public health by incorporating three metrics - life expectancy (LE), healthy life expectancy (HLE), and the discrepancy between the two. We investigate the effects of various health and socio-economic factors on these metrics and employ causal machine learning and statistical methods such as propensity score matching, X-learners, and causal forests to calculate treatment effects. An increase in basic water services and public health expenditure significantly increased average LE, whereas high HIV prevalence rates and poverty rates reduced average LE. High GNI per capita and moderate BMI increased HLE while high HIV prevalence rates decreased HLE. High public health expenditure and high GNI per capita expand the gap between HLE and LE, whereas high HIV prevalence rates and moderate BMI diminish this gap. Results suggest that policymakers should utilize governmental resources to improve public health infrastructure rather than provide fiscal incentives to encourage private healthcare infrastructure. Additionally, more emphasis should be put on increasing educational levels of the general public by increasing educational expenditure and making educational institutions, public and private, more accountable.


title: Calibration of Two Validated SARS-CoV-2 Pseudovirus Neutralization Assays for COVID-19 Vaccine Evaluation

abstract: Vaccine-induced neutralizing antibodies (nAbs) are key biomarkers considered to be associated with vaccine efficacy. In United States Government-sponsored phase 3 efficacy trials of COVID-19 vaccines, nAbs are measured by two different validated pseudovirus-based SARS-CoV-2 neutralization assays, with each trial using one of the two assays. Here we describe and compare the nAb titers obtained in the two assays. We observe that one assay consistently yielded higher nAb titers than the other when both assays were performed on the World Health Organizations anti-SARS-CoV-2 immunoglobulin International Standard, COVID-19 convalescent sera, and mRNA-1273 vaccinee sera. To overcome the challenge this difference in readout poses in comparing/combining data from the two assays, we evaluate three calibration approaches and show that readouts from the two assays can be calibrated to a common scale. These results may aid decision-making based on data from these assays for the evaluation and licensure of new or adapted COVID-19 vaccines.


title: The evolutionary landscape of SARS-CoV-2 variant B.1.1.519 and its clinical impact in Mexico City

abstract: The SARS-CoV-2 pandemic is one of the most concerning health problems around the globe. We report the emergence of SARS-CoV-2 variant B.1.1.519 in Mexico City. This variant represented up to 90% of sequenced cases in February 2021. It is characterized by three amino acid changes in the spike protein: T478K, P681H, and T732A. We report the effective reproduction number of B.1.1.519 and present evidence of its geographical origin based on phylogenetic analysis. We also studied its evolution via haplotype analysis and identified the most recurrent haplotypes. Finally, we studied the clinical impact of B.1.1.519: patients infected with variant B.1.1.519 showed a highly significant adjusted odds ratio (aOR) increase of 1.85 over non-B.1.1.519 patients for developing a severe/critical outcome (P = 0.000296, 1.33-2.6 95% CI) and a 2.35-fold increase for hospitalization (P = 0.005, 1.32-4.34 95% CI). The continuous monitoring of this and other variants will be required to control the ongoing pandemic as it evolves.


title: Capturing population differences in rates of vascular aging using a deep learning electrocardiogram algorithm: a cross-sectional study

abstract:
BackgroundCardiovascular event rates increase with age in all populations. This is thought to be the result of multiple underlying molecular and cellular processes that lead to cumulative vascular damage. Apart from arterial stiffness based on pulse wave velocity there are few other non-invasive measures of this process of vascular aging. We have developed a potential biomarker of vascular aging using deep-learning to predict age from a standard 12-lead electrocardiogram (ECG). The difference between ECG predicted and chronological age ({delta}-age) can be interpreted as a measure of vascular aging.

MethodsWe use data collected in two cross-sectional studies of adults aged 40-69 years in Norway and Russia to test the hypothesis that mean levels of {delta}-age, derived from a deep-learning model trained on a US population, correspond to the known large differences in cardiovascular mortality between the two countries.

FindingsSubstantial differences were found in mean {delta}-age between populations: Russia-USA (+5{middle dot}2 years; 0{middle dot}7, 10 IQR) and Norway-USA (-2{middle dot}6 years; -7, 2 IQR). These differences were only marginally explained when accounting for differences in established cardiovascular disease risk factors.

Interpretation{delta}-age may be an important biomarker of fundamental differences in cardiovascular disease risk between populations as well as between individuals.

category: cardiovascular medicine


title: Machine Learning to Predict 10-year Cardiovascular Mortality from the Electrocardiogram: Analysis of the Third National Health and Nutrition Examination Survey (NHANES III)

abstract:
BackgroundThe value of the electrocardiogram (ECG) for predicting long-term cardiovascular outcomes is not well defined. Machine learning methods are well suited for analysis of highly correlated data such as that from the ECG.

MethodsUsing demographic, clinical, and 12-lead ECG data from the Third National Health and Nutrition Examination Survey (NHANES III), machine learning models were trained to predict 10-year cardiovascular mortality in ambulatory U.S. adults. Predictive performance of each model was assessed using area under receiver operating characteristic curve (AUROC), area under precision-recall curve (AUPRC), sensitivity, and specificity. These were compared to the 2013 American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE).

Results7,067 study participants (mean age: 59.2 {+/-} 13.4 years, female: 52.5%, white: 73.9%, black: 23.3%) were included. At 10 years of follow up, 338 (4.8%) had died from cardiac causes. Compared to the PCE (AUROC: 0.668, AUPRC: 0.125, sensitivity: 0.492, specificity: 0.859), machine learning models only required demographic and ECG data to achieve comparable performance: logistic regression (AUROC: 0.754, AUPRC: 0.141, sensitivity: 0.747, specificity: 0.759), neural network (AUROC: 0.764, AUPRC: 0.149, sensitivity: 0.722, specificity: 0.787), and ensemble model (AUROC: 0.695, AUPRC: 0.166, sensitivity: 0.468, specificity: 0.912). Additional clinical data did not improve the predictive performance of machine learning models. In variable importance analysis, important ECG features clustered in inferior and lateral leads.

ConclusionsMachine learning can be applied to demographic and ECG data to predict 10-year cardiovascular mortality in ambulatory adults, with potentially important implications for primary prevention.


title: Long-term air pollution exposure and diabetes risk in the elderly population.

abstract:
BackgroundType 2 diabetes is a major public health concern. Studies show that both genetics and environmental exposures play a significant role in developing the disease. We assessed the association between air pollution and first documented diabetes occurrence in a national U.S. cohort of older adults to estimate diabetes risk.

MethodsWe included all Medicare enrollees 65 years and older in the fee-for-service program, part A and part B, in the contiguous United States (2000-2016). Participants were followed annually until the first recorded diabetes diagnosis, end of enrollment, or death (264,869,458 person-years). We obtained annual estimates of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and warm-months ozone (O3) exposures from highly spatiotemporally resolved prediction models. We assessed the simultaneous effects of the pollutants on diabetes risk using survival analyses. We repeated the models in cohorts restricted to ZIP codes with air pollution levels not exceeding the national ambient air quality standards (NAAQS) during the study period.

ResultsWe identified 10,024,879 diabetes cases of 41,780,637 people (3.8% of person-years). The hazard ratio (HR) for first diabetes occurrence was 1.074 (95% CI 1.058; 1.089) for 5 {micro}g/m3 increase in PM2.5, 1.055 (95% CI 1.050; 1.060) for 5 ppb increase in NO2, and 0.999 (95% CI 0.993; 1.004) for 5 ppb increase in O3. Both for NO2 and PM2.5 there was evidence of non-linear exposure-response curves with stronger associations at lower levels (NO2 [≤] 40 ppb, PM2.5 [≤] 9 {micro}g/m3). Furthermore, associations remained in the restricted low-level cohorts. The O3-diabetes exposure-response relationship differed greatly between models and require further investigation.

ConclusionExposures to PM2.5 and NO2 are associated with increased diabetes risk, even when restricting the exposure to levels below the NAAQS set by the U.S. EPA.


title: Long-term air pollution exposure and diabetes risk in American older adults: a national cohort study.


title: A strategy to assess spillover risk of bat SARS-related coronaviruses in Southeast Asia

abstract:
Emerging diseases caused by coronaviruses of likely bat origin (e.g. SARS, MERS, SADS and COVID-19) have disrupted global health and economies for two decades.

Evidence suggests that some bat SARS-related coronaviruses (SARSr-CoVs) could infect people directly, and that their spillover is more frequent than previously recognized. Each zoonotic spillover of a novel virus represents an opportunity for evolutionary adaptation and further spread; therefore, quantifying the extent of this "hidden" spillover may help target prevention programs. We derive biologically realistic range distributions for known bat SARSr-CoV hosts and quantify their overlap with human populations. We then use probabilistic risk assessment and data on human-bat contact, human SARSr-CoV seroprevalence, and antibody duration to estimate that [~]400,000 people (median: [~]50,000) are infected with SARSr-CoVs annually in South and Southeast Asia. These data on the geography and scale of spillover can be used to target surveillance and prevention programs for potential future bat-CoV emergence.


title: INTESTINAL GLUCONEOGENESIS IS DOWNREGULATED IN PAEDIATRIC PATIENTS WITH COELIAC DISEASE

abstract:
ObjectiveUntreated coeliac disease (CD) patients have increased levels of blood glutamine and a lower duodenal expression of glutaminase (GLS). Intestinal gluconeogenesis (IGN) is a process through which glutamine is turned into glucose in the small intestine, for which GLS is crucial. Animal studies suggest impaired IGN may have long-term effects on metabolic control and be associated with development of type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). The aim of this study was to thoroughly investigate IGN at the gene expression level in children with untreated coeliac disease.

DesignQuantitative polymerase chain reaction (qPCR) was used to quantify expression of 11 target genes related to IGN using the delta-delta Ct method with three reference genes (GUSB, IPO8 and YWHAZ) in duodenal biopsies collected from 84 children with untreated coeliac disease and 58 disease controls.

ResultsSignificantly lower expression of nine target genes involved in IGN was seen in duodenal biopsies from CD patients compared with controls: FBP1, G6PC, GLS, GPT1, PCK1, PPARGC1A, SLC2A2, SLC5A1, and SLC6A19. No significant differences in expression were seen for G6PC3 and GOT1.

ConclusionChildren with untreated coeliac disease have lower expression of genes important for IGN. Further studies are warranted to disentangle whether this is a consequence of intestinal inflammation or due to an impaired metabolic pathway shared with other chronic metabolic diseases. Impaired IGN could be a mechanism behind the increased risk of NAFLD seen in CD patients.

SIGNIFICANCE OF THIS STUDYO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIGenome-wide association studies have shown an association between coeliac disease (CD) and glutaminase (GLS).
C_LIO_LIIntestinal gluconeogenesis (IGN) is a process with a recently described important function in energy homeostasis and metabolic disease. GLS is critical for IGN by enabling it to use glutamine, its main substrate.
C_LIO_LICD patients are at an increased risk of non-alcoholic fatty liver disease (NAFLD) as adults.
C_LI

What are the new findings?O_LINine genes involved in IGN are downregulated at the gene expression level in the small intestine of children with untreated CD, suggesting impairment of IGN.
C_LI

How might it impact on clinical practice in the foreseeable future?O_LIImpaired IGN might be a mechanism behind the increased risk of NAFLD seen in CD patients as adults.
C_LIO_LIEarly diagnosis and treatment of CD may restore IGN and prevent CD patients from NAFLD later in adulthood.
C_LI

category: gastroenterology


title: Brain white matter after pediatric mild traumatic brain injury: a diffusion tensor and neurite orientation and dispersion imaging study

abstract:
BackgroundPediatric mild traumatic brain injury (mTBI) affects millions of children annually. Diffusion tensor imaging (DTI) is sensitive to axonal injuries and white matter microstructure and has been used to characterize the brain changes associated with mild traumatic brain injury (mTBI). Neurite orientation dispersion and density imaging (NODDI) is a diffusion model that can provide additional insight beyond traditional DTI metrics, but has not been examined in pediatric mTBI. The goal of this study was to employ DTI and NODDI to gain added insight into white matter alterations in children with mTBI compared to children with mild orthopedic injury (OI).

MethodsChildren (mTBI n=320, OI n=176) aged 8-16.99 years (m 12.39 {+/-} 2.32 years) were recruited from emergency departments at five hospitals across Canada and underwent 3T MRI on average 11 days post-injury. DTI and NODDI metrics were calculated for seven major white matter tracts and compared between groups using univariate analysis of covariance controlling for age, sex, and scanner type. False discovery rate (FDR) was used to correct for multiple comparisons.

ResultsUnivariate analysis revealed no significant group main effects or interactions in DTI or NODDI metrics. Fractional anisotropy and neurite density index in all tracts exhibited a significant positive association with age and mean diffusivity in all tracts exhibited a significant negative association with age in the whole sample.

ConclusionsOverall, there were no differences between mTBI and OI groups in brain white matter microstructure from either DTI or NODDI in the seven tracts. This indicates that mTBI is associated with relatively minor white matter differences, if any, at the post-acute stage. Brain differences may evolve at later stages of injury, so longitudinal studies with long-term follow-up are needed.


title: Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health

abstract: Urinary metabolic profiling is a promising powerful tool to reflect dietary intake and can help understand metabolic alterations in response to diet quality. Here, we used 1H-NMR spectroscopy in a multi-country study in European children (1147 children from 6 different cohorts) and identified a common panel of 4 urinary metabolites (hippurate, N-methylnicotinic acid, urea and sucrose) that was predictive of Mediterranean diet adherence (KIDMED) and ultra-processed food (UPF) consumption and also had higher capacity in discriminating childrens diet quality than that of established sociodemographic determinants. Further, we showed that the identified metabolite panel also reflected the associations of these diet quality indicators with C-peptide, a stable and accurate marker of insulin resistance and future risk of metabolic disease. This methodology enables objective assessment of dietary patterns in European child populations, complementary to traditional questionary methods, and can be used in future studies to evaluate diet quality. Moreover, this knowledge can provide mechanistic evidence of common biological pathways that characterize healthy and unhealthy dietary patterns, and diet-related molecular alterations that could associate to metabolic disease.

category: nutrition


title: Asymptomatic SARS-CoV-2 infection and the demography of COVID-19

abstract: Asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19, but it is not yet clear how the proportion of asymptomatic infections varies by age and geographic location. Here we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate this question. Data were collected by multiple rounds of city-wide PCR test with detailed contact tracing, where each patient was monitored for symptoms through the whole course of infection. We find that the proportion of asymptomatic infections declines with age (coefficient =-0.006, P<0.01), falling from 56% in age group 0-9 years to 12% in age group >60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern together with the age distribution of overall cases can explain most of the geographic differences in reported asymptomatic proportions. Combined with demography and contact matrices from other countries worldwide, we estimate that a maximum of 22%-55% of SARS-CoV-2 infections would come from asymptomatic cases in an uncontrolled epidemic based on asymptomatic proportions in China. Our analysis suggests that flare-ups of COVID-19 are likely if only adults are vaccinated and that surveillance and possibly control measures among children will be still needed in the future to contain epidemic resurgence.


title: Reports of myocarditis and pericarditis following mRNA COVID-19 vaccines: A review of spontaneously reported data from the UK, Europe, and the US

abstract:
ObjectivesTo bring together spontaneously reported data from around the world to estimate the reporting rate in different countries and better understand the risk factors for myocarditis and pericarditis following exposure to COVID-19 mRNA vaccines.

DesignSystematic review of the literature and systematic review of spontaneously reported data from the United Kingdom (UK), United States (US), and European Union/European Economic Area (EU/EEA).

Data sourcesSpontaneously reported data for COVID-19 Vaccine Pfizer/BioNTech (Comirnaty) and COVID-19 Vaccine Moderna (Spikevax) were obtained using outputs from the UKs Yellow Card scheme (covering the period 09/12/2020 - 20/10/2021), the Vaccine Adverse Event Reporting System (VAERS; US; covering the period 23/08/2021 - 21/10/2021), and EudraVigilance (EU/EEA; covering the period 21/12/2020 - 21/10/2021). Systematic searches of PubMed and Embase literature databases were performed with a datalock point of 11 October 2021.

Eligibility criteriaAll publicly available spontaneous reporting data from the three regions of interest were included. Data on events labelled "Myocarditis" and "Pericarditis" were included. No restrictions on age or gender were applied. For the systematic literature review, all pharmacoepidemiological studies of observational design investigating myocarditis and pericarditis following mRNA COVID-19 vaccines identified by our search were included. No restrictions on language or date were applied. Pre-print manuscripts were included if no peer-reviewed version was available. Studies of non-observational design, case reports, and case series were excluded. Study quality was assessed using relevant Critical Appraisal Skills Programme (CASP) tools. All studies were considered of sufficient quality for inclusion.

Data extraction and synthesisOne researcher extracted data from spontaneous reporting systems and published pharmacoepidemiological studies. Spontaneously reported events of myocarditis and pericarditis were presented for each individual data source, and stratified by vaccine, age, sex, and dose where this information was available. Vaccination data were obtained to the same date, and reporting rates were calculated for the events of myocarditis and pericarditis for each population of interest. For published pharmacoepidemiological studies, the study design, participant characteristics, and study results were tabulated.

ResultsOverall, there were 435 reports of myocarditis and 327 reports of pericarditis reported to the UKs Yellow Card scheme up to 20 October 2021. To 21 October 2021, in the US, 1936 reports of myocarditis and 1271 reports of pericarditis had been submitted to VAERS; there had been 2924 reports of myocarditis and 1855 reports of pericarditis submitted to EudraVigilance to the same date. Most reports (73.3%) had been submitted following Comirnaty (Pfizer/BioNTech). Males represented 74.9% of reports of myocarditis and 56.9% of pericarditis overall (for US and EU/EEA populations only), and the majority of reports concerned vaccinees ages under 40 years. Reports were more frequent following the second dose of mRNA COVID-19 vaccine. Reporting rates of myocarditis and pericarditis were consistent between the data sources. Seven pharmacoepidemiological studies were included; results of these studies were largely consistent with results of our spontaneous report analyses.

ConclusionsThis study provides evidence that younger vaccinees more frequently report myocarditis and pericarditis following mRNA COVID-19 vaccines compared with older vaccinees. These events had mild clinical course followed by full recovery in most cases. Results from published literature supported the results of our analyses.

Strengths and Limitations of the StudyO_LIThis is the first study to bring together spontaneously reported data from the United Kingdom, United States, and Europe on myocarditis and pericarditis following mRNA COVID-19 vaccines.
C_LIO_LIResults from this study provide evidence on the frequency of reported events of myocarditis and pericarditis following mRNA vaccines in different age groups, and by sex and vaccine dose. Analyses of spontaneous reports were consolidated with results of published literature, identified by systematic review.
C_LIO_LIResults may have been influenced by biases including different vaccination policies in each region examined, and publicity on events of myocarditis and pericarditis following mRNA vaccines.
C_LIO_LIThe study relied on outputs from spontaneous reporting systems in which the level of detail differed between the systems examined; furthermore, it is not possible to estimate incidence rates using spontaneous reports due to the lack of data on the exposed population, and there is no unvaccinated comparison group.
C_LIO_LIThere is an urgent need for further pharmacoepidemiological studies to be conducted to provide more accurate estimates of the frequency, clinical course, long term outcome, effects of treatment and impact on quality of life, to address many of the limitations of spontaneous reporting.
C_LI

category: pharmacology and therapeutics


title: Reports of myocarditis and pericarditis following mRNA COVID-19 vaccines: A systematic review of spontaneously reported data from the UK, Europe, and the US and of the literature


title: Interplay between the Genetics of Personality Traits, severe Psychiatric Disorders, and COVID-19 Host Genetics in the Susceptibility to SARS-CoV-2 Infection

abstract:
BackgroundThe SARS-CoV-2 pandemic, with all its impacts on our way of life, is affecting our experiences and mental health. Notably, individuals with mental disorders have been reported to have a higher risk of contracting SARS-CoV-2. Personality traits could represent an important determinant of preventative health behavior and, therefore, the risk of contracting the virus.

AimsWe examined overlapping genetic underpinnings between major psychiatric disorders, personality traits, and susceptibility to SARS-CoV-2 infection.

MethodsLinkage disequilibrium score regression was used to explore the genetic correlations of COVID-19 susceptibility with psychiatric disorders and personality traits based on data from the largest available respective genome-wide association studies (GWAS). In two cohorts (the PsyCourse (n=1346) and the HeiDE (n=3266) study), polygenic risk scores were used to analyze if a genetic association between, psychiatric disorders, personality traits, and COVID-19 susceptibility exists in individual-level data.

ResultsWe observed no significant genetic correlations of COVID-19 susceptibility with psychiatric disorders. For personality traits, there was a significant genetic correlation for COVID-19 susceptibility with extraversion (p=1.47x10-5; rg=0.284). Yet, this was not reflected in individual-level data from the PsyCourse and HeiDE studies.

ConclusionsWe identified no significant correlation between genetic risk factors for severe psychiatric disorders and genetic risk for COVID-19 susceptibility. Among the personality traits, extraversion showed evidence for a positive genetic association with COVID-19 susceptibility, in one but not in another setting. Overall, these findings highlight a complex contribution of genetic and non-genetic components in the interaction between COVID-19 susceptibility and personality traits or mental disorders.

category: genetic and genomic medicine


title: Essential Indicators of Quality in Primary Care Settings: An Evidence-Based, Structured, Expert Approach

abstract:
Executive SummaryO_ST_ABSIntroductionC_ST_ABSPrimary health care has a central role in the workings of the health care system and health of the American public. Thus, a high-performing, high-quality primary care system is essential. As a result, measurement frameworks are needed to assess the quality of the infrastructure, workforce configurations, and processes available in primary care practices due to the complexity of primary care. As part of a larger project supported by AHRQ (grant no. 1 R01 HS 025982), our research team reports the use of an evidence-based approach to compile a targeted set of existing care measures. These measures are prioritized according to their overall contribution and value to primary care. Within this paper, we describe the process by which the performance measures were selected and present the final set of measures resulting from the process.

Defining Primary careThe study centers around general primary care settings, which have been defined as, "the provision of integrated, accessible health care services by clinicians who are accountable for addressing a large majority of personal health care needs, developing a sustained partnership with patients, and practicing in the context of family and community." (1)

Using PROMESWe adapted an evidence-based approach for measure development, The Productivity Measurement and Enhancement System, or ProMES, to select (modify, when appropriate) and rank existing primary care measures according to value to the primary care clinic. ProMES is a comprehensive performance measure development approach firmly grounded in motivational theory and performance measurement.(2, 3) Through a facilitated focus-group based process, these measures are defined, weighted, and prioritized to create indicators of both overall effectiveness and specific aspects of daily work. This alignment helps individuals and teams to focus their effort more clearly on the most important aspects of their work (i.e., clinical performance) resulting in greater productivity, reduced stress, and less waste of effort.(2, 3) We utilize the ProMES definition of productivity, which is how effectively an organization uses its resources to achieve its goals.

One unique feature of ProMES is the resulting measures include contingency curves, or non-linear functions that explicitly tie performance levels on a given measure to its contribution to the organizations values; in this way, the application of ProMES yields a more nuanced approach to prioritizing work than simple linear weights, while allowing direct comparison(s) between measure(s).

ResultsThe design team identified three fundamental objectives for delivery of high-quality primary care. The design team also selected sixteen performance indicators from the 44 pre-vetted measures that already exist in three different data sources for primary care. One indicator, Team 2 Day Post Discharge Contact Ratio, was selected as an indicator for both Objective 2 and 3. In addition, contingency curves were created for each of the indicators using the contingency functions developed by the design team.

O_LIObjective 1. Ensure patient has appropriate access to preventive, acute, or chronic health care services when needed.
- Indicators:
O_LINew Primary Care Patient Average Wait Time in Days
C_LIO_LIEstablished Primary Care Patient Average Wait Time in Days
C_LIO_LIAverage 3rd Next Available Appointment in PC Clinics
C_LIO_LITotal Inbound PC Secure Messages to Total Outbound PC Secure Messages (Ratio)
C_LIO_LIUrgent Care Utilization Rate
C_LI

C_LIO_LIObjective 2. Build a trusting, effective, sustained partnership between the health-care team, the patient, and his/her caregiver(s) towards shared goals.
- Indicators:
O_LIPatients Satisfaction Rating of Primary Care Provider
C_LIO_LITeam 2 Day Post Discharge Contact Ratio
C_LIO_LIPatient-Centered Medical Home Stress Discussed
C_LI

C_LIO_LIObjective 3. Deliver safe and effective care that comprehensively addresses a given patients particular ecological, biological, and/or psychosocial needs.
- Indicators:
O_LIAmbulatory Care Sensitive Conditions (ACSC) Hospitalizations Rate Per 1000 Patients
C_LIO_LIDiabetes Patients with HbA1c Poor Control
C_LIO_LIDiabetes Electronic Composite Measure
C_LIO_LIStatin Medication for Patients with Cardiovascular Disease
C_LIO_LIControlling High Blood Pressure
C_LIO_LIRenal Testing for Nephropathy
C_LIO_LIEffective Continuation Phase Treatment for depression
C_LIO_LIHospital-wide all cause 30-day Readmission Rate
C_LIO_LITeam 2 Day Post Discharge Contact Ratio
C_LI

C_LI

SummaryPerformance measures selected as part of our modified-ProMES process assist in the implementation of targeted care quality measures prioritized in accordance to their value in primary care. By deriving high-value metrics, organized by care objective with numerically assigned prioritization, we anticipate the results of this paper will apply to a diverse set of stakeholders, including but not limited to policy-makers, primary care clinicians, and administrators in healthcare organizations. Our design team of nationally recognized SMEs joined together in a national panel that consists of diverse stakeholder groups to collectively identify three primary care team objectives, 16 indicators of primary care quality, and 13 indicators which require modification and further work to address gaps which exist in the primary care performance measurement domain. Measures selected as part of this study aim were constructed independent of clinic size or configuration, so that clinics of many configurations (e.g., public vs. private, large vs. small, rural vs urban, team-based vs. traditional) could benefit from their use.

Our measure set provides an actionable catalogue of measures that can serve as a first step toward interoperability of electronic health record systems. Future work toward this goal should address both logistical considerations (e.g., data capture, common data/programming language) and lingering measurement challenges, such as the best way to operationalize these measures for teams working in complex and shifting situations (e.g., rotating team members).

Acronyms and Definitions

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/21262970v2_ufig1.gif" ALT="Figure 1">
View larger version (44K):
org.highwire.dtl.DTLVardef@1378895org.highwire.dtl.DTLVardef@e816d4org.highwire.dtl.DTLVardef@132dcaaorg.highwire.dtl.DTLVardef@35351b_HPS_FORMAT_FIGEXP  M_FIG C_FIG

category: health systems and quality improvement


title: Implicit, Intrinsic, Extrinsic, and Host Factors Attributing the Covid-19 Pandemic. Part 1- Intrinsic Factor Nitrous Oxide Emissions: A Systematic Analysis

abstract: Despite Nitrous oxide (N2O) being the most widely used anesthetics in dental and other medical applications, it is associated with global warming and stratospheric ozone destruction. With globalization, a larger amount of N2O emissions arearticulated especially from human activities (30%, 6.7 Tg N per year), which are primarily dominated by agriculture that is even above the emissions of all oceans (26%). The synthesis of N2O reflects the general chemistry and readily from a substrate Nitric oxide (NO) in the environment. The modeling of infectious disease dynamics covering common pathogen-transmission factors, for example intrinsic (or microbes nutrient supply) at a population level, is indeed imperative to curb the menace of any disease. Nonetheless, in areas where novel coronavirus disease (COVID-19) was at its worst, for example, Wuhan China, Mumbai India, Milan Italy, Washington USA etc., the reduction in N2O emissions was well noticed. Nonetheless, viruses exhibit greater mobility than humans and hijack nutrients including nitrogen to complete their epidemiological cycle all due to limited sequence space of viral genomes, the high probability of genetic drift, extremely large population sizes, the high mutation and recombination rates. In consequence of drastic fall in N2O emissions, lower human transport can not be an all alone contributor, but contrarily it may also be associated with coronavirus intrinsic factors. This prompted us to analyze freely accessible and large global data from two authenticated sources, the World Health Organization and World Bank. We hereby argue that intrinsic factor N2O emissions fueling the COVID-19 progression significantly. Entire predictions were found consistent with the recently observed shreds of evidence. These insights enhanced scientific ability to interrogate viral epidemiology and recommended a 7-points framework covering all-natural lifestyle and dietary supplements for COVID-19 prevention before the arrival of a front-line therapeutic(s) or preventable vaccine.

category: infectious diseases


title: Implicit, Intrinsic, Extrinsic (or Environmental), and Host Factors Attributing the Covid-19 Pandemic. Part 2- Implicit Factor Pesticide Use: A Systematic Analysis

abstract: Advances in our understanding of complex COVID-19 pandemic would allow us to effectively eliminate and eradicate SARS-COV2 virus. Although tremendous amount of research devoted to the robustness across its biology, diagnostics, vaccines and treatment has exploded in the past two years. However, still science do not have robust answers for causes, for example (i) What are the reasons of non-uniform global distribution of COVID-19? (ii) Why the United States, India, and Brazil, are the first-three most affected nations?, (iii) How did Bhutan, a nation sharing a boundary with China manage nearly 0.34% infections and 3 deaths from COVID-19? Nonetheless, the biomass bistribution of biosphere report suggest more than 1550-fold larger microbial biomass involving bacteria, fungi, archaea, protists and viruses is exist in comparision to all global human population in the biosphere. The rich microbiota act a first line of defence to invade pathogens and affect us both through the environment and microbiome. Unfortunately, a role of pathogen-transmission factors viz. implicit factors (competitive microflora) is still under represented. This study is an attempt from a gold standard correlation methodology using a large pesticide use global data. The non-specific pesticides kill both pests as well as protective microbiota, resulting a loss in rich biodiversity and allow easy pathogen entry to human. Entire predictions were found consistent with the recently observed evidences. These insights enhanced scientific ability to interrogate viral epidemiology and recommended to limit pesticide use for future pandemic prevention.


title: Low dose hydroxychloroquine prophylaxis for COVID-19 - a prospective study

abstract:
BackgroundSince the outbreak of COVID-19 pandemic, the world began a frantic search for possible prophylactic options. While trials on hydroxychloroquine (HCQ) prophylaxis are ongoing, concrete evidence is lacking. The study aimed to determine the relative efficacy of various doses of oral HCQ in prophylaxis and mitigating the severity of COVID-19 in healthcare workers.

MethodsThis was a prospective cohort with four arms (high, medium, low dose, and control) of HCQ prophylaxis, used by healthcare workers at a tertiary care center in India. Participants were grouped as per their opting for any one arm on a voluntary basis as per institute policy under the Government guidance. The outcomes studied were COVID-19 positivity by RT-PCR and its severity assessed by WHO COVID-19 severity scale.

ResultsTotal 486 participants were enrolled, of which 29 (6%) opted for low dose, 2 (<1%) medium dose, and none for high dose HCQ while 455 (93.6%) were in the control arm. Of the 164 participants who underwent RT-PCR, 96 (58.2%) tested positive. Out of these 96 positive cases, the majority of them (79 of 96 [82.3%]) were ambulatory and were managed conservatively at home. Only 17.7% (17 of 96) participants, all of them from the control group, required hospitalization with the mild-moderate disease. None of the participants had severe disease, COVID-related complications, ICU stay, or death. The difference in the outcome assessed amongst the various arms was statistically insignificant (p value >0.05).

ConclusionThis single-center study demonstrated that HCQ prophylaxis in healthcare workers does not cause a significant reduction in COVID-19 as well as mitigating its severity in those infected. At present, most of the trials have not shown any benefit. The debate continues to rage, should HCQ prophylaxis be given to healthcare workers for chemoprophylaxis?


title: SARS-CoV-2 infection fatality rates in India: systematic review, meta-analysis and model-based estimation

abstract:
IntroductionFervorous investigation and dialogue surrounding the true number of SARS-CoV-2 related deaths and implied infection fatality rates in India have been ongoing throughout the pandemic, and especially pronounced during the nations devastating second wave. We aim to synthesize the existing literature on the true SARS-CoV-2 excess deaths and infection fatality rates (IFR) in India, through a systematic search followed by viable meta-analysis. We then provide updated epidemiological model-based estimates of the wave 1, wave 2 and combined IFRs using an extension of the Susceptible-Exposed-Infected-Removed (SEIR) model, using data from April 1, 2020 to June 30, 2021.

MethodsFollowing PRISMA guidelines, the databases PubMed, Embase, Global Index Medicus, as well as BioRxiv, MedRxiv, and SSRN for preprints (accessed through iSearch), were searched on July 3, 2021 (with results verified through August 15, 2021). Altogether using a two-step approach, 4,765 initial citations were screened resulting in 37 citations included in the narrative review and 19 studies with 41 datapoints included in the quantitative synthesis. Using a random effects model with DerSimonian-Laird estimation, we meta-analyze IFR1 which is defined as the ratio of the total number of observed reported deaths divided by the total number of estimated infections and IFR2 (which accounts for death underreporting in the numerator of IFR1). For the latter, we provide lower and upper bounds based on the available range of estimates of death undercounting, often arising from an excess death calculation. The primary focus is to estimate pooled nationwide estimates of IFRs with the secondary goal of estimating pooled regional and state-specific estimates for SARS-CoV-2 related IFRs in India. We also try to stratify our empirical results across the first and the second wave. In tandem, we present updated SEIR model estimates of IFRs for waves 1, 2, and combined across the waves with observed case and death count data from April 1, 2020 to June 30, 2021.

ResultsFor India countrywide, underreporting factors (URF) for cases (sourced from serosurveys) range from 14.3-29.1 in the four nationwide serosurveys; URFs for deaths (sourced from excess deaths reports) range from 4.4-11.9 with cumulative excess deaths ranging from 1.79-4.9 million (as of June 2021). Nationwide pooled IFR1 and IFR2 estimates for India are 0.097% (95% confidence interval [CI]: 0.067 - 0.140) and 0.365% (95% CI: 0.264 - 0.504) to 0.485% (95% CI: 0.344 - 0.685), respectively, again noting that IFR2 changes as excess deaths estimates vary. Among the included studies in this meta-analysis, the IFR1 generally appear to decrease over time from the earliest study end date to the latest study end date (from 4 June 2020 to 6 July 2021, IFR1 changed from 0.199 to 0.055%), whereas a similar trend is not as readily evident for IFR2 due to the wide variation in excess death estimates (from 4 June 2020 to 6 July 2021, IFR2 ranged from (0.290-1.316) to (0.241-0.651) %).

Nationwide SEIR model-based combined estimates for IFR1 and IFR2 are 0.101% (95% CI: 0.097 - 0.116) and 0.367% (95% CI: 0.358 - 0.383), respectively, which largely reconcile with the empirical findings and concur with the lower end of the excess death estimates. An advantage of such epidemiological models is the ability to produce daily estimates with updated data with the disadvantages being that these estimates are subject to numerous assumptions, arduousness of validation and not directly using the available excess death data. Whether one uses empirical data or model-based estimation, it is evident that IFR2 is at least 3.6 times more than IFR1.

ConclusionWhen incorporating case and death underreporting, the meta-analyzed cumulative infection fatality rate in India varies from 0.36%-0.48%, with a case underreporting factor ranging from 25-30 and a death underreporting factor ranging from 4-12. This implies, by June 30, 2021, India may have seen nearly 900 million infections and 1.7-4.9 million deaths when the reported numbers stood at 30.4 million cases and 412 thousand deaths (covid19india.org) with an observed case fatality rate (CFR) of 1.35%. We reiterate the need for timely and disaggregated infection and fatality data to examine the burden of the virus by age and other demographics. Large degrees of nationwide and state-specific death undercounting reinforce the call to improve death reporting within India.

category: epidemiology


title: Emergence of SARS-CoV-2 Resistance with Monoclonal Antibody Therapy

abstract: Resistance mutations to monoclonal antibody (mAb) therapy has been reported, but in the non-immunosuppressed population, it is unclear if in vivo emergence of SARS-CoV-2 resistance mutations alters either viral replication dynamics or therapeutic efficacy. In ACTIV-2/A5401, non-hospitalized participants with symptomatic SARS-CoV-2 infection were randomized to bamlanivimab (700mg or 7000mg) or placebo. Treatment-emergent resistance mutations were significantly more likely detected after bamlanivimab 700mg treatment than placebo (7% of 111 vs 0% of 112 participants, P=0.003). There were no treatment-emergent resistance mutations among the 48 participants who received bamlanivimab 7000mg. Participants with emerging mAb resistant virus had significantly higher pre-treatment nasopharyngeal and anterior nasal viral load. Intensive respiratory tract viral sampling revealed the dynamic nature of SARS-CoV-2 evolution, with evidence of rapid and sustained viral rebound after emergence of resistance mutations, and worsened symptom severity. Participants with emerging bamlanivimab resistance often accumulated additional polymorphisms found in current variants of concern/interest and associated with immune escape. These results highlight the potential for rapid emergence of resistance during mAb monotherapy treatment, resulting in prolonged high level respiratory tract viral loads and clinical worsening. Careful virologic assessment should be prioritized during the development and clinical implementation of antiviral treatments for COVID-19.


title: Evaluation of commercially available high-throughput SARS-CoV-2 serological assays for serosurveillance and related applications

abstract: SARS-CoV-2 serosurveys can estimate cumulative incidence for monitoring epidemics but require characterization of employed serological assays performance to inform testing algorithm development and interpretation of results. We conducted a multi-laboratory evaluation of 21 commercial high-throughput SARS-CoV-2 serological assays using blinded panels of 1,000 highly-characterized blood-donor specimens. Assays demonstrated a range of sensitivities (96%-63%), specificities (99%-96%) and precision (IIC 0.55-0.99). Durability of antibody detection in longitudinal samples was dependent on assay format and immunoglobulin target, with anti-spike, direct, or total Ig assays demonstrating more stable, or increasing reactivity over time than anti-nucleocapsid, indirect, or IgG assays. Assays with high sensitivity, specificity and durable antibody detection are ideal for serosurveillance. Less sensitive assays demonstrating waning reactivity are appropriate for other applications, including characterizing antibody responses after infection and vaccination, and detection of anamnestic boosting by reinfections and vaccine breakthrough infections. Assay performance must be evaluated in the context of the intended use.


title: Antibody response to a fourth mRNA Covid-19 vaccine boost in weak responder kidney transplant recipients

abstract: The US FDA has recently authorized immunocompromised people to receive a third dose of mRNA Covid-19 vaccine following the two-doses regimen to further boost protection. Unfortunately, a non-negligible proportion of people treated with immunosuppressive drugs either do not respond or show only a weak response after a third boost and should, therefore, still be considered at risk of severe Covid-19. As of June 2021, we were granted the opportunity to offer a fourth vaccine dose to French solid organ transplant recipients who still showed a weak antibody response after the third dose. In this multicenter study, we demonstrate that that the protection conferred by a fourth dose is adequate for the majority of kidney transplant recipients.

category: transplantation


title: High viral SARS-CoV-2 load in placenta of patients with hypertensive disorders after COVID-19 during pregnancy

abstract:
IntroductionStudies described an increased frequency of hypertensive disorders of pregnancy after a COVID-19 episode. There is limited evidence about SARS-CoV-2 viral load in placenta. This study aimed to investigate the relationship between SARS-CoV-2 viral load in placenta and clinical development of HDP after COVID-19 throughout different periods of gestation.

MethodsThis was a case-control study in women with and without gestational hypertensive disorders (HDP) after SARS-CoV-2 infection diagnosed by RT-PCR during pregnancy. Patients were matched by gestational age at the moment of COVID-19 diagnosis. We performed an analysis of SARS-CoV-2 RNA levels in placenta.

ResultsA total of 28 women were enrolled. Sixteen patients were diagnosed with COVID-19 during the third trimester and the remaining twelve patients in the others trimesters. Ten placentas (35.7%) were positive for SARS-CoV-2, nine of them (90%) belonged to the HDP group versus one (10%) in control group (p=0.009). Those cases with the highest loads of viral RNA developed severe-preeclampsia.

ConclusionThe presence of SARS-CoV-2 was more frequent in placentas of patients with HDP after COVID-19. There seems to be a relationship between high viral load in the placenta and the development of hypertensive disorders. We found SARS-CoV-2 viral load in placenta after birth in mothers infected at the first half of pregnancy, but with negative nasopharyngeal RT-PCR at delivery. Our data suggest that SARS-CoV-2 infection during pregnancy could trigger gestational hypertensive disorders through placenta-related mechanisms.


title: Breast cancer risks associated with missense variants in breast cancer susceptibility genes

abstract:
BACKGROUNDProtein truncating variants in ATM, BRCA1, BRCA2, CHEK2 and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.

METHODSCombining 59,639 breast cancer cases and 53,165 controls, we sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1,146 training variants), BRCA1 (644), BRCA2 (1,425), CHEK2 (325) and PALB2 (472). We evaluated breast cancer risks according to five in-silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.

RESULTSThe most predictive in-silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1 and BRCA2, data were compatible with small subsets (approximately 7%, 2% and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.

CONCLUSIONSThese results will inform risk prediction models and the selection of candidate variants for functional assays, and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.


title: BCL11A intellectual developmental disorder: defining the clinical spectrum and genotype-phenotype correlations

abstract:
PurposeHeterozygous variants in BCL11A underlie an intellectual developmental disorder with persistence of fetal hemoglobin (BCL11A-IDD, a.k.a. Dias-Logan syndrome). We sought to delineate the genotypic and phenotypic spectrum of BCL11A-IDD.

MethodsWe performed an in-depth analysis of 42 patients with BCL11A-IDD ascertained through a collaborative network of clinical and research colleagues. We also reviewed 33 additional affected individuals previously reported in the literature or available through public repositories with clinical information.

ResultsMolecular and clinical data analysis of 75 patients with BCL11A-IDD identified 60 unique variants (30 frameshift, 7 missense, 6 splice-site, 17 stop-gain) and 8 unique CNVs (microdeletions involving BCL11A only). We redefined the most frequent manifestations of the condition: intellectual disability, hypotonia, behavioral abnormalities, postnatal microcephaly and autism spectrum disorder. Two thirds of patients have brain MRI abnormalities, and we identified a recurrent posterior fossa phenotype of vermian hypoplasia and/or small brainstem. Truncating BCL11A variants, particularly those affecting the long (BCL11A-L) and extra-long (-XL) isoforms, sparing the short (-S) isoform, were associated with increased severity.

ConclusionsWe expand the clinical delineation of BCL11A-IDD and identify a potential isoform-specific genotype-phenotype correlation. We show that BCL11A-IDD is associated with posterior fossa anomalies and highlight the differences between BCL11A-IDD and 2p16.1p15 microdeletion syndrome.


title: Social-economic drivers overwhelm climate in underlying the COVID-19 early growth rate

abstract:
Identifying the drivers underlying the spatial occurrence and spreading rate of COVID-19 can provide valuable information for their preventions and controls. Here, we examine how socio-economic and climate drivers affect the early growth rates of COVID-19 in China and the other countries, the former of which have consistently stricter quarantine during early epidemic and thus are used to enquire the influences of human interventions on trainsimissions. We find that the early growth rates of COVID-19 are higher in China than the other countries, which is consistent with previous reports. The global spread is mainly driven by the socio-economic factors such as GDP per capita, human movement and population density rather than climate. Among socio-economic factors, GDP per capita is most important showing negative relationships in China, while positive in the other countries. However, the predicability of early growth rates by socio-economic and climate variables is at least 1.6 times higher in Chinas provinces than the other countries, which is further supported by metapopulation network model. These findings collectively indicate that the stochasticity of transimission processes decrease upon strict quarantine measures such as travel restrictions.

Key findingsO_LIGDP per capita is most important in driving the spread of COVID-19, which shows negative relationships within China, while positive in the other countries.
C_LIO_LISocio-economic and climate factors are key in driving the early growth rate of COVID-19, while the former is more important.
C_LIO_LISocio-economic and climate features explain more variations of early growth rates in China due to the decreased stochasticity of transimission processes upon strict quarantine measures.
C_LI