A comprehensive knowledgebase of known and predicted human genetic variants associated with COVID-19 susceptibility and severity

Host genetic susceptibility is a key risk factor for severe illness associated with COVID-19. Despite numerous studies of COVID-19 host genetics, our knowledge of COVID-19-associated variants is still limited, and there is no resource comprising all the published variants and categorizing them based on their confidence level. Also, there are currently no computational tools available to predict novel COVID-19 severity variants. Therefore, we collated 820 host genetic variants reported to affect COVID-19 susceptibility by means of a systematic literature search and confidence evaluation, and obtained 196 high-confidence variants. We then developed the first machine learning classifier of severe COVID-19 variants to perform a genome-wide prediction of COVID-19 severity for 82,468,698 missense variants in the human genome. We further evaluated the classifier's predictions using feature importance analyses to investigate the biological properties of COVID-19 susceptibility variants, which identified conservation scores as the most impactful predictive features. The results of enrichment analyses revealed that genes carrying high-confidence COVID-19 susceptibility variants shared pathways, networks, diseases and biological functions, with the immune system and infectious disease being the most significant categories. Additionally, we investigated the pleiotropic effects of COVID-19-associated variants using phenome-wide association studies (PheWAS) in ~40,000 BioMe BioBank genotyped individuals, revealing pre-existing conditions that could serve to increase the risk of severe COVID-19 such as chronic liver disease and thromboembolism. Lastly, we generated a web-based interface for exploring, downloading and submitting genetic variants associated with COVID-19 susceptibility for use in both research and clinical settings (https://itanlab.shinyapps.io/COVID19webpage/). Taken together, our work provides the most comprehensive COVID-19 host genetics knowledgebase to date for the known and predicted genetic determinants of severe COVID-19, a resource that should further contribute to our understanding of the biology underlying COVID-19 susceptibility and facilitate the identification of individuals at high risk for severe COVID-19.Copyright © 2023 Elsevier Inc.

Immunotherapy: FAMILIAL CD45RA DEPLETED T CELLS TO TREAT SEVERE REFRACTORY INFECTIONS IN IMMUNOCOMPROMISED PATIENTS

Background & Aim: Immunocompromised patients are susceptible to high-risk opportunistic infections and malignant diseases. If available, most antiviral and antifungal drugs are quite toxic, relatively ineffective, and induce resistance in the long term. Methods, Results & Conclusion(s): We have previously demonstrated the safety of adoptive cell therapy for COVID-19 patients with CD45RA negative cells containing SARS-CoV-2-specific T cells from a donor, chosen based on HLA compatibility and cellular response to SARS-CoV-2 peptide pools. After finishing a Phase 2 randomized multicenter clinical trial (RELEASE, NCT04578210), we concluded that the infusion is safe, effective, accelerates lymphocyte recovery and shows hallmarks of an immune response. To use adoptive cell therapy to treat COVID-19 it would be necessary to develop a biobank of living drugs. For that, we examined the immune evolution performing a longitudinal analysis from previously SARS-CoV-2 infected and infection- naive individuals covering 21 months from infection. Cellular responses were maintained over time while humoral responses increased after vaccination but were gradually lost. Therefore, the best donors would be recovered individuals and two months after vaccination. We also evaluated the effect of dexamethasone (current standard of care treatment for COVID-19 and other infections involving lymphopenia) and Interleukin-15 (cytokine involved in T-cell maintenance and survival) on CD45RA negative. Dexamethasone did not alter cell functionality, proliferation or phenotype at a clinical-practice concentration, while interleukin-15 increased the memory T-cell and T-regulatory cell activation state, and interferon gamma release. Furthermore, we applied the adoptive passive transfer of CD45RA negative cells containing pathogen-specific memory T-cells to other infectious diseases characterized by sustained lymphopenia. We infused six immunocompromised patients with Cytomegalovirus, BK virus, Aspergillus, and Epstein-Barr virus lymphoproliferative disease. Patients experienced pathogen clearance, resolution of symptoms and lymphocyte increase. Transient microchimerism was detected in three patients. The use of CD45RA negative cells containing specific memory T cells of a third-party donor for treating severe pathogenic diseases in immunocompromised patients is feasible, safe, and effective, and has an advantage over other cell therapies such as lower costs and a less complex regulatory environment.Copyright © 2023 International Society for Cell & Gene Therapy

Ethical issues in the use of leftover samples and associated personal data obtained from diagnostic laboratories.

Diagnostic laboratories are an integral part of the research ecosystem in biomedical sciences. Among other roles, laboratories are a source of clinically-characterized samples for research or diagnostic validation studies. Particularly during the COVID-19 pandemic, this process was entered by laboratories with different experience in the ethical management of human samples. The objective of this document is to present the current ethical framework regarding the use of leftover samples in clinical laboratories. Leftover samples are defined as the residue of a sample that has been obtained and used for clinical purposes, and would otherwise be discarded. Secondary use of samples typically demands institutional ethical oversight and informed consent by the participants, although the latter requirement could be exempted when the harm risks are sufficiently small. However, ongoing discussions have proposed that minimal risk is an insufficient argument to allow the use of samples without consent. In this article, we discuss both positions, to finally suggest that laboratories anticipating the secondary use of samples should consider the adoption of broad informed consent, or even the implementation of organized biobanking, in order to achieve higher standards of ethical compliance which would enhance their capacity to fulfill their role in the production of knowledge.

AUTOPHAGY AND Acyl-CoA-BINDING PROTEIN INFLUENCE COVID-19 SEVERITY

Background: Autophagy, a cytosolic-structure degradation pathway, allows production of IL21 by CD4 T-cells and efficient cytolytic responses by CD8 T-cells. Autophagy is in part regulated by acyl-CoA-binding protein (ACBP) which has two functions. Intracellular ACBP favors autophagy, whereas secreted extracellular ACBP inhibits autophagy. Herein, we assessed whether autophagy and the ACBP pathway were associated with COVID-19 severity. Method(s): Through the BQC-19 Quebec biobank, somalogic proteomic analysis was performed on 5200 proteins in plasma samples collected between March 2020 and December 2021. Plasma from 903 patients (all data available) during the acute phase of COVID-19 were assessed. COVID-19 severity was stratified using WHO criteria. In vitro, ACBP intracellular levels, autophagy levels (LC3II) and IL21 production were assessed by flow in PBMCs after a 24h stimulation with IL6, phorbol myristate acetate (PMA)+ionomycin or lipopolysaccharide (LPS). Plasma levels of anti-SARS-CoV-2 (full spike protein or RBD) IgG were assessed by ELISA. Result(s): Median age of the cohort was 62 yo, 48% were female, 55% had comorbidities (see table). Increasing plasma levels of ACBP were found with severity (mild, moderate, severe and fatal groups having 5.3, 7.3, 9.5 and 10.6 RFU/50muL of plasma, respectively, p< 0.001 for all comparisons). Patients with comorbidities had higher plasma ACBP levels (7.4 vs 6.4 RFU/50muL, p< 0.001). Plasma ACBP levels were higher during the delta and omicron-variant periods (8.4 vs 6.8 RFU/50muL;p< 0.001). Plasma ACBP levels correlated with LC3II levels (r=0.51, P< 0.001) and IL6 (r=0.41, p< 0.001), but neither with markers IL1beta nor IL8. ACBP levels negatively correlated with IL21 levels (r=-0.27, p< 0.001), independently of age, sex, and severity. ACBP levels were not associated with levels of anti-SARS-CoV-2 IgG levels. In vitro, IL6 stimulation of healthy control PBMC induced extracellular ACBP release. Moreover, adding recombinant ACBP: 1) reduced autophagy in lymphocytes and monocytes upon polyclonal stimulation with PMA/ionomycin or LPS;2) reduced intracellular production of IL21 in T-cells after PMA/ ionomycin stimulation. Conclusion(s): Plasma ACBP levels were inversely linked with IL21 levels, suggesting that autophagy and IL21 allow control of SARS-CoV-2 infection, independently of the level of SARS-CoV-2 antibody secretion. ACBP is a targetable autophagy checkpoint and its extracellular inhibition may improve SARS-CoV-2 immune control. (Table Presented).

The Importance of Biobanking COVID-19 Samples

Collection and storage of biological specimens has been a longstanding method of conducting research all around the world. Biobanking has allowed for all types of viruses to be studied by a global network of researchers and thus enhanced and accelerated the research and development of diagnostic tests and vaccines. However, with the introduction of the novel coronavirus (COVID-19) leading to a pandemic, the challenges and gaps in biobanking became more apparent as the entire world struggled to address the pandemic. With strict measures in place to reduce transmission of the disease, the idea of virtual biobanking began to take root as a method for researchers to access data irrespective of their location. With a better understanding of the gaps and challenges faced by researchers in biobanking and virtual biobanking, it is likely that there will be a stronger and more robust response to epidemics and pandemics in the future. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Psychosocial predictors of COVID-19 infection in UK biobank (N = 104 201).

BACKGROUND: Since the outbreak of COVID-19, data on its psychosocial predictors are limited. We therefore aimed to explore psychosocial predictors of COVID-19 infection at the UK Biobank (UKB). METHODS: This was a prospective cohort study conducted among UKB participants. RESULTS: The sample size was N = 104 201, out of which 14 852 (14.3%) had a positive COVID-19 test. The whole sample analysis showed significant interactions between sex and several predictor variables. Among females, absence of college/university degree [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.45-1.66] and socioeconomic deprivation (OR 1.16 95% CI 1.11-1.21) were associated with higher odds of COVID-19 infection, while history of psychiatric consultation (OR 0.85 95% CI 0.77-0.94) with lower odds. Among males, absence of college/university degree (OR 1.56, 95% CI 1.45-1.68) and socioeconomic deprivation (OR 1.12, 95% CI 1.07-1.16) were associated with higher odds, while loneliness (OR 0.87, 95% CI 0.78-0.97), irritability (OR 0.91, 95% CI 0.83-0.99) and history of psychiatric consultation (OR 0.85, 95% CI 0.75-0.97) were associated with lower odds. CONCLUSION: Sociodemographic factors predicted the odds of COVID-19 infection equally among male and female participants, while psychological factors had differential impacts.

Changes in Juvenile Dermatomyositis after the Covid-19 Pandemic

Background. Prior research has shown that viruses may trigger JDM, although the degree to which COVID-19 may serve as a trigger for JDM remains unknown. We present two case reports of JDM occurring after COVID-19 infection. We also provide case numbers of new JDM diagnoses pre-and post-COVID-19 as well as an analysis of JDM population characteristics pre-and post-COVID-19. A 5year-old female developed upper respiratory infection (URI) symptoms and was diagnosed with COVID-19 in December of 2020. She developed Gottron's sign, heliotrope rash, and weakness resulting in admission in February of 2021. She had elevated CK, AST, ALT, LDH, and aldolase. Her CMAS (childhood myositis assessment scale) was 24. An MRI showed diffuse myositis. Myositis specific antibody (MSA) testing revealed a positive MJ antibody. She was diagnosed with JDM and started on steroids, methotrexate, hydroxychloroquine, and IVIG with improvement. The second patient was a 4year-old female who was diagnosed with COVID-19 in October 2020. In January 2021, she developed heliotrope rash and Gottron's papules. She developed decreased exercise tolerance in May 2021 found to have elevated Aldolase and LDH. Her CMAS was 34. An MRI showed diffuse myositis. MSA testing was significant for a positive P155/140 antibody. She was started on hydroxychloroquine, steroids, IVIG and methotrexate with improvement. Due to the aforementioned cases a retrospective analysis was performed assessing the characteristics of JDM pre-and post-COVID-19 at Lurie Children's Hospital. Methods. The Cure JM biorepository houses clinical data, laboratory data, and patient samples obtained at the onset of JDM. The following information was obtained from newly diagnosed JDM patients: MSA, DAS (disease activity score), flow cytometry results, vWF antigen, neopterin, CMAS, capillary end row loop(ERL), LDH, Aldolase, ESR, CRP, IgG, complements, ANA, and age at diagnosis. We identified 10 patients with a diagnosis of JDM from January 1st 2020 -July 1st 2021 who were designated as the post-COVID-19 group. This population was compared to a total of 51 patients diagnosed with JDM between Jan 1st 2010 and December 31st 2019 who were designated as the pre-COVID-19 group. Data analysis was performed using Welch T-testing. Research enrollment was impacted due to the COVID-19 pandemic. To better assess JDM rates, chart review and EMR reports were obtained to determine the total number of JDM diagnoses. Results. T-testing showed no significant change in DAS, ERL count, T or B cell flow cytometry, vWF antigen, CK, CMAS, CRP, Aldolase, LDH, IgG, complements or ANA titer between the pre-and post-COVID-19 JDM groups. The analysis showed a significant change in NK cell population with a decrease in the absolute NK cell number (pre 163, post 90.75. P value 0.03), and NK cell percentage (pre 6.6%, post 3.625%, P value 0.008). Both of the patients presented in this case report showed a low NK cell number (1% and 3% respectively). The total number of new JDM cases rose from an average of 6.3 cases per year to an average 9 cases per year from January 1st 2020 to December 31st 2021. Conclusion. This study provides two case reports of COVID-19 likely triggering JDM. This study also shows a modest increase in the number of new JDM cases since the onset of the pandemic. Interestingly, the NK cell population in the post-COVID-19 JDM patients were significantly decreased. NK cells have multiple roles in not only immune regulation, but also the immune response to viruses. This study suggests that NK cells play a role in the development of in virally mediated JDM, specifically in cases triggered by COVID-19. Future studies will be important to further delineate the function of NK cells in these patients. Markers of JDM disease severity, including DAS, Neopterin, CK, and CMAS, did not significantly change in our institution's JDM population after the onset of the COVID-19 pandemic.

WCN23-1206 Glomerulopathies Biobank in Uruguay. Description of the first 110 patients enrolled

Introduction: The incidence of glomerular diseases varies across different countries and criteria for kidney biopsy has changed over time. In Uruguay, glomerular diseases (GD) are a frequent cause of end stage kidney disease (ESKD) and renal replacement therapy with an annual incidence of 25.0 patients per million population according to data from the Uruguayan Dialysis Registry (UDR, year 2020). Since 1970, the Uruguayan Registry of Glomerulopathies has been recording the incidence, epidemiology and evolution of patients with GP in our country. In 2018, the Glomerulopathies Biobank (GB) began to operate including all patients with a native kidney biopsy performed at the Nephrology Department of the teaching hospital Hospital de Clinicas in Montevideo, Uruguay. The purpose of the BG is to record the phenotype (clinical and paraclinical) of patients with GD diagnosed by renal biopsy and at the same time store blood, urine, renal tissue and DNA samples. The aim of this report is to communicate the first 110 patients enrolled in the BG, which started in February 2018. Method(s): The BG protocol includes the collection of patronymic data, personal history, and clinical and paraclinical features of renal pathology. Plasma, urine and cell samples are stored for subsequent DNA extraction at the time of the kidney biopsy. In our country, all renal biopsies are performed by nephrologists. The Glomerular Biobank project is funded by the Nephrology Research Fund (School of Medicine, University of the Repubic) and was approved by the Ethics Committee of the Hospital de Clinicas and the Regulatory Verification Unit of the National Institute of Donation and Transplantation. The results are presented as mean and standard deviation (SD) for the continuous variables;and qualitative variables are described with percentages. Result(s): Patient recruitment began in February 2018 and we have recruited 110 patients. The mean age at the time of biopsy was 38.3+/-16.1 (min:16;max:78) years. Regarding sex distribution, the female sex slightly predominated (55.3%). Plasma creatinine was 2.1+/-1.45 mg/dL, proteinuria was 3.1+/-3.7 gr/dL and albuminaemia was 3.2+/-1.0 mg/dL. Microhaematuria was present in 61% of patients in the sediment study. Figure 1 shows the negative impact of the COVID 19 pandemic on the incidence of patients undergoing kidney biopsy. IgA nephropathy (13,8%)was the most frequent primary glomerular disease, followed by d focal and segmental glomerulosclerosis and membranous nephropathy. Consernig the glomerulopathies secondary to a systemic disease, the most frequent diagnosis was lupus nephritis (34,5%) followed by vasculitis, amyloidosis and diabetes. Conclusion(s): Having a prospective cohort of patients with glomerular disease, including reliable data and biological samples, will allow us to perform clinical and epidemiological analyses quickly and reliably in the future. The data and aliquots of biological material are available to any local nephrologist who proposes a hypothesis and has the approval of the corresponding ethics committee. The medium-term objective is to incorporate other national reference institutions in the care of patients with glomerular diseases. The data collected by the Glomerular Biobank will be a valuable input to the process of continuous improvement, and will serve as a basis for future nephrological research of excellence. No conflict of interestCopyright © 2023

Insights from a Rapidly Implemented COVID-19 Biobank Using Electronic Consent and Informatics Tools.

Biobanking during the COVID-19 pandemic presented unique challenges regarding patient enrollment, sample collection, and experimental analysis. This report details the ways in which we rapidly overcame those challenges to create a robust database of clinical information and patient samples while maintaining clinician and researcher safety. We developed a pipeline using REDCap (Research Electronic Data Capture) to coordinate electronic informed consent, sample collection, immunological assay execution, and data analysis for biobanking samples from patients with COVID-19. We then integrated immunological assay data with clinical data extracted from the electronic health record to link study parameters with clinical readouts. Of the 193 inpatients who participated in this study, 138 consented electronically and 56 provided paper consent. We collected and banked blood samples to measure circulating cytokines and chemokines, peripheral immune cell composition and activation status, anti-COVID-19 antibodies, and germline gene polymorphisms. In addition, we collected DNA and RNA from nasopharyngeal swabs to assess viral titer and microbiome composition by 16S sequencing. The rapid spread and contagious nature of COVID-19 required special considerations and innovative solutions to biobank samples quickly while protecting researchers and clinicians. Overall, this workflow and computational pipeline allowed for comprehensive immune profiling of 193 inpatients infected with COVID-19, as well as 89 outpatients, 157 patients receiving curbside COVID-19 testing, and 86 healthy controls. We describe a novel electronic framework for biobanking and analyzing patient samples during COVID-19, and present insights and strategies that can be applied more broadly to other biobank studies.

Biobanking: Paving Way For Medical Research

Biobank is a place where biosamples and associated data are collected and stored. The concept of biobanks may spark little excitement for most people. Biobanks are more developed in economically reach countries while it is a new for LMICs. As the advancement of science and technology, completion of human genome project, the treatment of patients are transformed from conventional to personalised. Human Genome project has advanced science through its application in microbiology, virology and pathology. In parallel to Human Genome project, Biobank has become a vital infrastructure for research, new drug discovery, it is also leading to the development of novel technologies, analytical tools and advancement of patient treatment through medical research. Biobanks are a key component of personalized medicine built on the three pillars of cancer research: proteomics, metabolomics, and epigenomics.lt has the potential to advance personalised medicine. Biobank aided in intense development in cancer research from the diagnostic, prognostic and therapeutic aspects. In recent pandemic Biobank have played and proved its role in fight against Covid-19 by allowing researches to study the disease and develop vaccines and treatment in short time. Without involvement of biobank and good quality of samples from patients infected with Covid-19, it would have been unachievable to sequence SARS-COV-2 virus and develop effective vaccines in record times.

No time for complacency: The CoVaRR-Net Biobank is an essential element of laboratory preparedness for infectious disease outbreaks.

The SARS-CoV-2 pandemic highlighted the need for rapid, collaborative, and population-centric research to define health impact, develop health care policies and establish reliable diagnostic and surveillance tests. Critical for these objectives were in-depth clinical data collected in standardized fashion and large numbers of various types of human samples prior and post-viral encounter. As the pandemic evolved with the emergence of new variants of concern (VOCs), access to samples and data from infected and vaccinated individuals were needed to monitor immune durability, the possibility of increased transmissibility and virulence, and vaccine protection against new and emerging VOCs. Therefore, essential to the pandemic response is a strong laboratory and data research component, supported by effective biobanking and data sharing. Critically important to the speed of the research response is the rapid access to biobanked samples. To address critical challenges brought to light by the pandemic, the Coronavirus Variants Rapid Response Network (CoVaRR-Net), funded by the Canadian Institutes of Health Research, was established to coordinate research efforts to provide rapid evidence-based responses to emerging VOCs. The purpose of this paper is to introduce the CoVaRR-Net Biobank and define its contribution to pandemic preparedness.

La pandémie de SRAS-CoV-2 a fait ressortir la nécessité de réaliser des recherches rapides, coopératives et populationnelles pour en définir les effets sur la santé, promulguer des politiques sanitaires et établir des tests diagnostiques et des tests de surveillance fiables. Pour réaliser ces objectifs, il était essentiel de colliger des données cliniques approfondies d'une manière standardisée et d'amasser un grand nombre de divers types d'échantillons humains avant et après le contact viral. Lorsque la pandémie a évolué par l'émergence de nouveaux variants préoccupants (VOC), il est devenu nécessaire d'accéder à des échantillons et à des données de personnes infectées et vaccinées pour surveiller la durabilité de l'immunité, la possibilité d'une transmissibilité et d'une virulence accrues et la protection conférée par les vaccins contre les VOC nouveaux et émergents. Ainsi, il est essentiel de disposer d'un vigoureux volet de recherches de laboratoire et de recherches à partir de données pour répondre à la pandémie, soutenu par une mise en biobanque et un partage des données efficaces. Pour assurer une réponse rapide par la recherche, il est tout aussi important d'accéder rapidement aux échantillons mis en biobanque. Afin de relever les défis cruciaux soulevés par la pandémie, le Coronavirus Variants Rapid Response Network (réseau de réponse rapide aux variants du coronavirus; CoVaRR-Net), financé par les Instituts de recherche en santé du Canada, a été créé pour coordonner les efforts de recherche afin de fournir des réponses rapides fondées sur des données probantes aux VOC en émergence. Le présent article vise à présenter la Biobanque CoVaRR-Net et à en définir la contribution à la préparation aux pandémies.

New Horizons: the value of UK Biobank to research on endocrine and metabolic disorders.

UK Biobank is an intensively characterized prospective study of 500 000 men and women, aged 40 to 69 years when recruited, between 2006 and 2010, from the general population of the United Kingdom. Established as an open-access resource for researchers worldwide to perform health research that is in the public interest, UK Biobank has collected (and continues to collect) a vast amount of data on genetic, physiological, lifestyle, and environmental factors, with prolonged follow-up of heath conditions through linkage to administrative electronic health records. The study has already demonstrated its unique value in enabling research into the determinants of common endocrine and metabolic diseases. The importance of UK Biobank, heralded as a flagship project for UK health research, will only increase over time as the number of incident disease events accrue, and the study is enhanced with additional data from blood assays (such as whole-genome sequencing, metabolomics, and proteomics), wearable technologies (including physical activity and cardiac monitors), and body imaging (magnetic resonance imaging and dual-energy X-ray absorptiometry). This unique research resource is likely to transform our understanding of the causes, diagnosis, and treatment of many endocrine and metabolic disorders.

Longitudinal analyses of depression, anxiety, and suicidal ideation highlight greater prevalence in the northern Dutch population during the COVID-19 lockdowns.

BACKGROUND: The pandemic of the coronavirus disease 2019 (COVID-19) has led to an increased burden on mental health. AIMS: To investigate the development of major depressive disorder (MDD), generalized anxiety disorder (GAD), and suicidal ideation in the Netherlands during the first fifteen months of the pandemic and three nation-wide lockdowns. METHOD: Participants of the Lifelines Cohort Study -a Dutch population-based sample-reported current symptoms of MDD and GAD, including suicidal ideation, according to DSM-IV criteria. Between March 2020 and June 2021, 36,106 participants (aged 18-96) filled out a total of 629,811 questionnaires across 23 time points. Trajectories over time were estimated using generalized additive models and analyzed in relation to age, sex, and lifetime history of MDD/GAD. RESULTS: We found non-linear trajectories for MDD and GAD with a higher number of symptoms and prevalence rates during periods of lockdown. The point prevalence of MDD and GAD peaked during the third hard lockdown at 2.88 % (95 % CI: 2.71 %-3.06 %) and 2.92 % (95 % CI: 2.76 %-3.08 %), respectively, in March 2021. Women, younger adults, and participants with a history of MDD/GAD reported significantly more symptoms. For suicidal ideation, we found a significant linear increase over time in younger participants. For example, 20-year-old participants reported 4.14× more suicidal ideation at the end of June 2021 compared to the start of the pandemic (4.64 % (CI: 3.09 %-6.96 %) versus 1.12 % (CI: 0.76 %-1.66 %)). LIMITATIONS: Our findings should be interpreted in relation to the societal context of the Netherlands and the public health response of the Dutch government during the pandemic, which may be different in other regions in the world. CONCLUSIONS: Our study showed greater prevalence of MDD and GAD during COVID-19 lockdowns and a continuing increase in suicidal thoughts among young adults suggesting that the pandemic and government enacted restrictions impacted mental health in the population. Our findings provide actionable insights on mental health in the population during the pandemic, which can guide policy makers and clinical care during future lockdowns and epi/pandemics.

Exploring the impact of selection bias in observational studies of COVID-19: a simulation study.

BACKGROUND: Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis. METHODS: We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. RESULTS: In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios. CONCLUSIONS: Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest.

A phenome-wide investigation of risk factors for severe COVID-19.

With the continued spread of COVID-19 globally, it is crucial to identify the potential risk or protective factors associated with COVID-19. Here, we performed genetic correlation analysis and Mendelian randomization analysis to examine genetic relationships between COVID-19 hospitalization and 405 health conditions and lifestyle factors in 456 422 participants from the UK Biobank. The genetic correlation analysis revealed 134 positive and 65 negative correlations, including those with intakes of a variety of dietary components. The MR analysis indicates that a set of body fat-related traits, maternal smoking around birth, basal metabolic rate, lymphocyte count, peripheral enthesopathies and allied syndromes, blood clots in the leg, and arthropathy are causal risk factors for severe COVID-19, while higher education attainment, physical activity, asthma, and never smoking status protect against the illness. Our findings have implications for risk stratification in patients with COVID-19 and the prevention of its severe outcomes.

Association of Social Isolation and Loneliness With Incident Heart Failure in a Population-Based Cohort Study.

BACKGROUND: Social isolation and loneliness have emerged as important risk factors for cardiovascular diseases, particularly during the coronavirus disease pandemic. However, it is unclear whether social isolation and loneliness had independent and joint associations with incident heart failure (HF). OBJECTIVES: This study sought to examine the association of social isolation, loneliness, and their combination with incident HF. METHODS: The UK Biobank study is a population-based cohort study. Social isolation and loneliness were assessed using self-reported questionnaires. HF cases were identified by linking hospital records and death registries. The weighted polygenic risk score associated with HF was calculated. RESULTS: Among the 464,773 participants (mean age: 56.5 ± 8.1 years, 45.3% male), 12,898 incident HF cases were documented during a median follow-up of 12.3 years. Social isolation (most vs least: adjusted HR: 1.17; 95% CI:1.11-1.23) and loneliness (yes vs no: adjusted HR: 1.19; 95% CI: 1.11-1.27) were significantly associated with an increased risk of incident HF. The association between an elevated risk of HF and social isolation was modified by loneliness (Pinteraction = 0.034). A gradient of association between social isolation and the risk of incident HF was found only among individuals without loneliness (Ptrend < 0.001), but not among those with loneliness (Ptrend = 0.829). These associations were independent of the genetic risk of HF. CONCLUSIONS: Social isolation and loneliness were independently associated with a higher likelihood of incident HF regardless of genetic risk. The association between social isolation and incident HF was potentially modified by loneliness status.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10-9 ) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10-8 ) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

An Overview of Biotechnological Applications in Ayurveda: Amalgamation of Modern Techniques and Science

Health systems and their trends are continually evolving with advanced research on new tools and techniques. Since every health system has its limitations, there is a requirement for the integration of different medical systems to better serve mankind. In this direction, a practitioner of modern medicine should take into consideration traditional medicine practices, while the traditional medicine practitioner should also integrate the beneficial strategies of modern medicine. In spite of different approaches, the aim of all these medical systems is the same, which is to serve mankind by treating various health problems. Although traditional medicine has the potential to treat a variety of diseases, its acceptance by the global community is less than that of modern medicine due to inadequate scientific validation of its therapeutic benefits. In recent years, many new diseases have emerged, perhaps due to changes in geography, environment, weather conditions, and soil composition. A complete treatment of such diseases is a challenge for all medical practitioners, whether belonging to modern or traditional medicine. Therefore, an in-depth multidisciplinary research is needed to find an effective therapeutic strategy by connecting modern and traditional medical systems with biomedical sciences. In this direction, biotechnology can play an important role in developing a diagnostic method and treatment protocol. The present review provides an overview of the available Ayurvedic treatment options and future possibilities in which biotechnology may assist as a service provider. Copyright © 2023 Bentham Science Publishers.

Cardiovascular Calcium Scoring by Deep Learning is Predictive of Mortality in Emergency Department Patients

Introduction: Computed tomography (CT) imaging is widely used in the emergency department (ED) setting. Calcifications of the coronary arteries, heart valves, and aorta are common incidental findings that may herald clinical or subclinical cardiovascular disease. Hypothesis: We sought to determine whether the quantitative burden of cardiovascular calcifications, as measured by a CT-based deep learning pipeline, would be predictive of short-term mortality in a diverse population of ED patients. Method(s): We conducted a prospective single-center cohort study nested in the Quebec COVID-19 Biobank from March 2020 to September 2021. For the purposes of this study, we enlisted adult patients presenting to the ED with cardiopulmonary symptoms who were tested for COVID-19 and underwent CT imaging of the chest. We used a deep learning model previously developed by our team to automate the quantitative scoring of coronary artery calcification (CAC), aortic valve calcification (AVC), mitral annular calcification (MAC), and thoracic aorta calcification (TAC) from the CT images. These calcium scores were categorized as sex-stratified tertiles plus a zero-score referent category. The primary outcome was all-cause mortality at 30 and 90 days adjusted for age, sex, and COVID-19 status using multivariable logistic regression. Result(s): The study sample consisted of 731 ED visits among 271 unique patients with a mean age of 66 years and 47% females. COVID-19 illness was the main diagnosis in 29% of ED visits. The prevalence of any quantifiable calcification was 51% for CAC, 33% for AVC, 23% for MAC, and 80% for TAC. The statistically significant adjusted odds ratios for mortality were 2.50 (1.08, 5.81) in the highest AVC tertile at 30 days, 2.73 (1.37 5.47) in the highest CAC tertile at 90 days, and 4.42 (1.01, 19.4) in the highest TAC tertile at 90 days. These odds ratio remained similar after further adjustment for past history of myocardial infarction or heart failure. Conclusion(s): High calcium scores in the coronary arteries, aortic valve, and thoracic aorta are associated with heightened 30-day mortality in ED patients. Deep learning quantification of calcium scores from clinical CT scans is an opportunistic approach for risk stratification.

Defining background shared antibody sequences between unrelated healthy individuals (public clonotypes) to support future studies on specific infectious disease related conditions

Background. Public clonotypes, antibodies against specific antigens in unrelated individuals that have genetic similarities, have been shown in a variety of infections, including SARS-CoV-2 and HIV. Likely, there are shared antibody responses between individuals for many infections. To explore antibody responses that would coincide with specific infectious diseases that may set off chronic illnesses, such as Multiple Sclerosis or Alzheimer's disease, defining the background shared clonotypes is needed to differentiate disease from normal background public clonotype responses. Methods. Heavy chain variable sequences were retrieved from public biorepositories (Bioproject PRJNA486667) composed of 43 healthy persons, and two groups of HIV infected persons;114 with broadly neutralizing antibodies and 91 without broadly neutralizing antibodies. We utilized the Immcantation package of software run on our SUNY Buffalo computational cluster. After PRESTo annotation, duplicate sequences were collapsed and sequences of only single counts were removed. Clonal groups were determined using ChangeO requiring IGHV, IGHJ, and CDR3 amino acid sequence to be perfectly matched. Figures and statistics were generated with immcantation, excel, and graphpad prism 8. Results. 244850 heavy chain sequences from 43 healthy controls were compared for exact matches to predicted germline variable segment and CDR3 amino acid sequence and identified 0.23% as public clonotypes. Comparison to 205 HIV + individuals (a total of 1.4 million comparative sequences) showed that 2.35% of heavy chain sequences were seen in more than one individual. Generally, public clonotypes had shorter CDR3s (peak of 9 amino acids). VH 3-9, 3-30 and 4-34 were the most commonly used variable segments in public clonotypes. Common exact match CDR3 sequences using a variety of variable sequences, including an 11 amino acid CDR3 sequence motif, were also discovered. Conclusion. This early work has identified several public clonotypes that are shared among subjects who are HIV positive and otherwise healthy people. Defining the sequences commonly seen between individuals can assist in specifying antibody responses specific to disease states from larger sequence databases.