COVID-19 Host Genetics Initiative Research Articles

Exome-wide association study for replication of rare variants affecting the severity of COVID-19 in the Russian population

BACKGROUND: Human genetics is one of the factors determining the severity of COVID-19 disease. Previously, a large-scale whole-genome association study of the COVID-19 HG project (COVID-19 Host Genetics Initiative, 2021) investigated the association of genetic variants at multiple loci with COVID-19 severity. The genetic variants that have the greatest impact on COVID-19 severity are expected to have a low frequency in the population. Therefore, the study of rare variants may provide additional insights into the pathogenesis of the disease and thus help in the development of prevention and treatment options. AIM: The aim is to perform a replication analysis in search of genes with enrichment for rare genetic variants in relation to the severity of COVID-19 disease. METHODS: In this study, the clinical exome of a Russian cohort of patients was sequenced based on the St. Petersburg State Budgetary Institution "City Hospital No. 40" and St. Petersburg State University. The study used biomaterial from patients hospitalised at "City Hospital No. 40" with a diagnosis of COVID-19 and healthy individuals included in the population control group. The severity of the course of COVID-19 was determined according to the results of lung computed tomography. The list of genes for subsequent replication was generated by a literature review. Replication analysis of genes associated with COVID-19 severity was performed using burden test methods. RESULTS: In total, 701 clinical exomes were sequenced: 263 severe COVID-19 and 438 healthy individuals. A literature review identified 18 genes associated with severe COVID-19 that were included in the replication analysis. The replication analysis did not identify any genes whose association with severe COVID-19 was confirmed in the study cohort. CONCLUSION: Replication analysis did not identify any genes for which a significant association between functional variant enrichment and COVID-19 severity was found. However, the results demonstrated that the direction of the correlation was consistent with findings from previous studies. The small size of the sample analysed is an obvious limitation of our study. Expanding the study cohort would increase the power of the tests and allow us to detect additional rare variants that influence the severity of COVID-19 progression

#736 The short-term and long-term impact of COVID-19 on the kidney disorders: an observational and Mendelian randomization study

Abstract Background and Aims The impact of “long COVID-19” on “short-term” or “long-term” influence on kidney function change remains unknown. We aimed to investigate the causal association between COVID-19 and subsequent kidney outcomes. Method 10121 participants exposed to COVID-19 were matched up to 3 unexposed controls by age, sex, Townsend deprive index and severity of COVID-19 from UK Biobank. Using conditional and time-varying Cox proportional hazard regression, we first investigated the association between the SARS-CoV-2 infection and incidence of acute kidney disorder and chronic kidney disease (CKD). One-sample mendelian randomization (MR) using polygenetic risk score (PRS) of COVID-19 as instrumental variable was performed. Then, we extended the finding with two-sample MR analyses using GWAS summary statistics from UKB as outcomes, and GWAS of COVID-19 severity, hospitalization and susceptibility from the COVID-19 Host Genetics Initiative (r7) database as exposures. Results In observational study, we observed time-varying effects of COVID-19 on the risk of acute kidney disorder incidence, with the highest hazard effect in the second week (HR 12.77, 95% CI: 5.93-27.70) and disappearing in the fourth week (HR 2.28, 95% CI: 0.75-6.93). In subgroup analysis, this time-varying effects were only found in patients with moderate and severe COVID-19, but not mild COVID-19 patients. No association was observed between SARS-CoV-2 infection and the risk of incident CKD. Subsequent individual-level MR showed that COVID-19 severity, hospitalization and susceptibility were significantly associated with increased risk of acute kidney disorder, but not CKD. Two-sample MR indicated that none of the COVID-19 phenotypes were associated with these two diseases nor other kidney traits. Conclusion COVID-19 had “short-term” effects on the risk of subsequent acute kidney disorder incidence, and the hazard effects were only observed in moderate or severe but not mild COVID-19 patients.

The causal relationship between COVID-19 and ten esophageal diseases: a study utilizing Mendelian randomization.

Clinical signs of dysphagia, pancreatic achalasia, and esophagitis have been reported in patients with COVID-19. However, the causal relationship between COVID-19 and esophageal diseases is not clear. Therefore, we utilized Mendelian randomization to explore the potential association between COVID-19 and esophageal diseases. The summary statistics for a Genome-wide association study (GWAS) were obtained from The COVID-19 Host Genetics Initiative, encompassing four types of COVID-19 as exposure: severe COVID-19, hospitalized COVID-19 versus ambulatory COVID-19, hospitalized COVID-19 versus uninfected, and confirmed COVID-19. Additionally, summary statistics for ten esophageal diseases as outcomes were sourced from the GWAS Catalog and FinnGen databases. Univariate Mendelian randomization (MR) analysis was utilized to thoroughly investigate and validate the potential causal association between COVID-19 and various esophageal conditions, including esophageal varices, Barrett's esophagus, esophagitis, esophageal obstruction, esophageal ulcer, esophageal perforation, gastroesophageal reflux, congenital esophageal malformations, benign esophageal tumors, and esophageal adenocarcinoma. An inverse variance-weighted (IVW) model was utilized for univariate Mendelian randomization (MR) analysis, which revealed that genetic liability in patients with confirmed COVID-19 was associated with esophageal obstruction (OR [95% CI]: 0.5275458 [0.2822400-0.9860563]; p-value = 0.0450699). Furthermore, a suggestive causal association was found between genetic liability and a reduced risk of benign esophageal tumors (OR [95% CI]: 0.2715453 [0.09368493-0.7870724]; p-value = 0.0163510), but with a suggestively increased risk of congenital esophageal malformations (OR [95% CI]: 6.959561 [1.1955828-40.51204]; p-value = 0.03086835). Additionally, genetic liability in hospitalized COVID-19 patients, compared to non-hospitalized COVID-19 patients, was suggestively associated with an increased risk of esophagitis (OR [95% CI]: 1.443859 [1.0890568-1.914252]; p-value = 0.01068201). The reliability of these causal findings is supported by Cochran's Q statistic and the MR-Egger intercept test. The results of this study suggest the existence of a causal relationship between COVID-19 and esophageal diseases, highlighting differing risk effects of COVID-19 on distinct esophageal conditions.

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10−8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10−8). A total of 113 variants were associated with survival at P-value < 1.0 × 10−5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways.

No causal association between atopic dermatitis and COVID-19 outcomes: A Mendelian randomization study.

Frequent hand washing and disinfection during the corona virus disease (COVID-19) pandemic may lead to skin-related disability. The causal relationship between atopic dermatitis (AD), the most common chronic, noninfectious, inflammatory skin disease, and COVID-19 remains unclear. We used Mendelian randomization (MR) to explore the causal inference of atopic dermatitis with COVID-19 outcomes. Genome-wide association study (GWAS) data for AD, consisting of 8383 cases and 236,162 controls of European ethnicity, were provided by the FinnGen database. The GWAS outcome data were derived from the COVID-19 Host Genetics Initiative and consisted of COVID-19 susceptibility (122,616 cases and 2,475,240 controls), hospitalization (32,519 cases and 2,062,805 controls), and very severe respiratory disease (13,769 cases and 1,072,442 controls). The inverse variance weighted with a fixed effects model (IVW (fe)) was used as the main statistical approach to assess the causality between AD and COVID-19 in this study. Several other analytical methods have also been used to complement or identify pleiotropy and heterogeneity. MR analysis showed no causality between AD and COVID-19 outcomes. The odds ratios (OR) were 1.00 (95% confidence interval (CI), 0.99-1.02) for susceptibility, 1.00 (95% CI, 0.96-1.04) for hospitalization, 0.97 (95% CI, 0.92-1.03) for very severe respiratory disease by the method of IVW (fe). In conclusion, we found no causal relationship between AD and COVID-19 outcomes. This study provides additional ideas for the exploration of the risk factors for COVID-19.

COVID-19 susceptibility, hospitalization, and severity and the risk of brain cortical structure: a mendelian randomization study.

Observational studies have reported structural changes in the brains of patients with COVID-19; it remains unclear whether these associations are causal. We evaluated the causal effects of COVID-19 susceptibility, hospitalization, and severity on cortical structures. Mendelian randomization (MR) study. Data on the different COVID-19 phenotypes were obtained from the latest large-scale genome-wide association study (GWAS) (R7) of the COVID-19 Host Genetics Initiative. Brain structure data, including cortical thickness (TH) and surface area (SA), were obtained from the ENIGMA Consortium. Additionally, we employed the round 5 dataset released in January 2021 as the validation cohort. The inverse-variance weighted (IVW) method was used as the primary analysis in MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. We performed enrichment analysis on the MR analyses that passed the sensitivity analysis filtering. After IVW and sensitivity analyses, we observed causal associations between COVID-19 susceptibility and rostral middle frontal SAw (P = 0.0308, β=-39.1236), cuneus THw (P = 0.0170, β=-0.0121), medial orbitofrontal THw (P = 0.0002, β = 0.0225), postcentral THw (P = 0.0217, β= -0.0106), temporal pole THw (P = 0.0077, β = 0.0359), medial orbitofrontal SAnw (P = 0.0106, β= -24.0397), medial orbitofrontal THnw (P = 0.0007, β = 0.0232), paracentral SAnw (P = 0.0483, β= -20.1442), rostral middle frontal SAnw (P = 0.0368, β= -81.9719), and temporal pole THnw (P = 0.0429, β = 0.0353). COVID-19 hospitalization had causal effects on medial orbitofrontal THw (P = 0.0053, β = 0.0063), postcentral THw (P = 0.0143, β= -0.0042), entorhinal THnw (P = 0.0142, β = 0.0142), medial orbitofrontal THnw (P = 0.0147, β = 0.0065), and paracentral SAnw (P = 0.0119, β= -7.9970). COVID-19 severity had causal effects on rostral middle frontal SAw (P = 0.0122, β=-11.8296), medial orbitofrontal THw (P = 0.0155, β = 0.0038), superior parietal THw (P = 0.0291, β= -0.0021), lingual SAnw (P = 0.0202, β=-11.5270), medial orbitofrontal THnw (P = 0.0290, β = 0.0039), paracentral SAnw (P = 0.0180, β= -5.7744), and pars triangularis SAnw (P = 0.0151, β=-5.4520). Our MR results demonstrate a causal relationship between different COVID-19 phenotypes and cortical structures.

Integration of risk variants from GWAS with SARS-CoV-2 RNA interactome prioritizes FUBP1 and RAB2A as risk genes for COVID-19

The role of host genetic factors in COVID-19 outcomes remains unclear despite various genome-wide association studies (GWAS). We annotate all significant variants and those variants in high LD (R2 > 0.8) from the COVID-19 host genetics initiative (HGI) and identify risk genes by recognizing genes intolerant nonsynonymous mutations in coding regions and genes associated with cis-expression quantitative trait loci (cis-eQTL) in non-coding regions. These genes are enriched in the immune response pathway and viral life cycle. It has been found that host RNA binding proteins (RBPs) participate in different phases of the SARS-CoV-2 life cycle. We collect 503 RBPs that interact with SARS-CoV-2 RNA concluded from in vitro studies. Combining risk genes from the HGI with RBPs, we identify two COVID-19 risk loci that regulate the expression levels of FUBP1 and RAB2A in the lung. Due to the risk allele, COVID-19 patients show downregulation of FUBP1 and upregulation of RAB2A. Using single-cell RNA sequencing data, we show that FUBP1 and RAB2A are expressed in SARS-CoV-2-infected upper respiratory tract epithelial cells. We further identify NC_000001.11:g.77984833C>A and NC_000008.11:g.60559280T>C as functional variants by surveying allele-specific transcription factor sites and cis-regulatory elements and performing motif analysis. To sum up, our research, which associates human genetics with expression levels of RBPs, identifies FUBP1 and RAB2A as two risk genes for COVID-19 and reveals the anti-viral role of FUBP1 and the pro-viral role of RAB2A in the infection of SARS-CoV-2.

Causal effects of dietary habits on COVID-19 susceptibility, hospitalisation and severity: a comprehensive Mendelian randomisation study.

This study aimed to investigate the causal effect of dietary habits on COVID-19 susceptibility, hospitalisation and severity. We used data from a large-scale diet dataset and the COVID-19 Host Genetics Initiative to estimate causal relationships using Mendelian randomisation. The inverse variance weighted (IVW) method was used as the main analysis. For COVID-19 susceptibility, IVW estimates indicated that milk (OR: 0·82; 95 % CI (0·68, 0·98); P = 0·032), unsalted peanut (OR: 0·53; 95 % CI (0·35, 0·82); P = 0·004), beef (OR: 0·59; 95 % CI (0·41, 0·84); P = 0·004), pork (OR: 0·63; 95 % CI (0·42, 0·93); P = 0·022) and processed meat (OR: 0·76; 95 % CI (0·63, 0·92); P = 0·005) were causally associated with reduced COVID-19 susceptibility, while coffee (OR: 1·23; 95 % CI (1·04, 1·45); P = 0·017) and tea (OR: 1·17; 95 % CI (1·05, 1·31); P = 0·006) were causally associated with increased risk. For COVID-19 hospitalisation, beef (OR: 0·51; 95 % CI (0·26, 0·98); P = 0·042) showed negative correlations, while tea (OR: 1·54; 95 % CI (1·16, 2·04); P = 0·003), dried fruit (OR: 2·08; 95 % CI (1·37, 3·15); P = 0·001) and red wine (OR: 2·35; 95 % CI (1·29, 4·27); P = 0·005) showed positive correlations. For COVID-19 severity, coffee (OR: 2·16; 95 % CI (1·25, 3·76); P = 0·006), dried fruit (OR: 1·98; 95 % CI (1·16, 3·37); P = 0·012) and red wine (OR: 2·84; 95 % CI (1·21, 6·68); P = 0·017) showed an increased risk. These findings were confirmed to be robust through sensitivity analyses. Our findings established a causal relationship between dietary habits and COVID-19 susceptibility, hospitalisation and severity.

Genetic Predisposition to Elevated Levels of Circulating ADAM17 Is Associated with the Risk of Severe COVID-19.

High levels of ADAM17 activity have emerged as an important mediator in severe COVID-19. This study aims to characterize eventual causal relationships between ADAM17 and COVID-19. Using Mendelian randomization analyses, we examined the causal effects of circulating ADAM17 on COVID-19 outcomes using summary statistics from large, genome-wide association studies of ADAM17 (up to 35,559 individuals) from the Icelandic Cancer Project and deCODE genetics, as well as critically ill COVID-19 patients (cases: 13,769; controls: 1,072,442), hospitalized COVID-19 patients (cases: 32,519; controls: 2,062,805) and reported SARS-CoV-2 infections (cases: 122,616; controls: 2,475,240) from the COVID-19 Host Genetics Initiative. The Mendelian randomization (MR) analyses demonstrated that a 1 standard deviation increase in genetically determined circulating ADAM17 (extracellular domain) was associated with an increased risk of developing critical ill COVID-19 (odds ratio [OR] = 1.26, 95% confidence interval [CI]:1.03-1.55). The multivariable MR analysis suggested a direct causal role of circulating ADAM17 (extracellular domain) in the risk of developing critical COVID-19 (OR = 1.09; 95% CI:1.01-1.17) when accounting for body mass index. No causal effect for the cytoplasmic domain of ADAM17 on COVID-19 was observed. Our results suggest that an increased genetic susceptibility to elevated levels of circulating ADAM17 (extracellular domain) is associated with a higher risk of suffering from severe COVID-19, strengthening the idea that the timely selective inhibition of ADAM17 could be a potential therapeutic target worthy of investigation.

Causal association of COVID-19 with brain structure changes: Findings from a non-overlapping 2-sample Mendelian randomization study

Recent cohort studies suggested that SARS-CoV-2 infection is associated with changes in brain structure. However, the potential causal relationship remains unclear. We performed a two-sample Mendelian randomization analysis to determine whether genetic susceptibility of COVID-19 is causally associated with changes in cortical and subcortical areas of the brain. This 2-sample MR (Mendelian Randomization) study is an instrumental variable analysis of data from the COVID-19 Host Genetics Initiative (HGI) meta-analyses round 5 excluding UK Biobank participants (COVID-19 infection, N = 1,348,701; COVID-19 severity, N = 1,557,411), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Global and regional cortical measures, N = 33,709; combined hemispheric subcortical volumes, N = 38,851), and UK Biobank (left/right subcortical volumes, N = 19,629). A replication analysis was performed on summary statistics from different COVID-19 GWAS study (COVID-19 infection, N = 80,932; COVID-19 severity, N = 72,733). We found that the genetic susceptibility of COVID-19 was not significantly associated with changes in brain structures, including cortical and subcortical brain structure. Similar results were observed for different (1) MR estimates, (2) COVID-19 GWAS summary statistics, and (3) definitions of COVID-19 infection and severity. This study suggests that the genetic susceptibility of COVID-19 is not causally associated with changes in cortical and subcortical brain structure.

The relationship between COVID-19, depressive disorder, and anxiety: a bidirectional Mendelian randomization study.

Previous clinical studies have found that negative mental states such as depression and anxiety are closely related to COVID-19 infection. We used Mendelian randomization (MR) to explore the relationship between depression, anxiety, and COVID-19 infection. Our data were based on publicly available GWAS databases. The COVID-19 samples were obtained from the COVID-19 Host Genetics Initiative (HGI). The depression samples were obtained from the Psychiatric Genomics Consortium (PGC). The anxiety samples were derived from the Finngen database. We used inverse-variance weighting (IVW) as the primary analysis method, with weighted median, MR Egger, and multivariate MRI adjustment. There was no causal effect of different COVID-19 infection statuses on depression and anxiety as determined by MR analysis. In addition, in the reverse MR analysis, we found a significant causal effect of anxiety on severe symptoms after COVID-19 infection. The results of the MR Egger regression, weighted median, and weighted mode methods were consistent with the IVW method. Based on sensitivity analyses, horizontal pleiotropy was unlikely to influence the final results. Our findings indicate that anxiety is a risk factor for severe symptoms following COVID-19 infection. However, the mechanism of interaction between the two needs further investigation.

Susceptibility and severity of COVID-19 and risk of psychiatric disorders in European populations: a Mendelian randomization study.

Observational studies have suggested that COVID-19 increases the prevalence of psychiatric disorders, but the results of such studies are inconsistent. This study aims to investigate the association between COVID-19 and the risk of psychiatric disorders using Mendelian randomization (MR) analysis. We used summary statistics from COVID-19 Host Genetics Initiative genome-wide association study (GWAS) of COVID-19 involving 2,586,691 participants from European ancestry. Genetic variations of five psychiatric disorders including autism spectrum disorder (ASD) (N = 46,351), bipolar disorder (BID) (N = 51,710), major depressive disorder (MDD) (N = 480,359), anxiety disorder (N = 83,566), and schizophrenia (SCZ) (N = 77,096) were extracted from several GWAS of European ancestry. The inverse-variance weighted (IVW) method as the main MR analysis conducted. We further performed sensitivity analyzes and heterogeneity analyzes as validation of primary MR results. The IVW analysis found that COVID-19 hospitalization phenotype was the risk factor for BID (OR = 1.320, 95% CI = 1.106-1.576, p = 0.002) and SCZ (OR = 1.096, 95% CI = 1.031-1.164, p = 0.002). Moreover, we detected a significant positive genetic correlation between COVID-19 severity and two psychiatric traits, BID (OR = 1.139, 95% CI = 1.033-1.256, p = 0.008) and SCZ (OR = 1.043, 95% CI = 1.005-1.082, p = 0.024). There was no evidence supporting the causal relationship between COVID-19 susceptibility and psychiatric disorders. Our results found that the COVID-19 hospitalization phenotype and COVID-19 severity phenotype might be the potential risks of BID and SCZ in European populations. Therefore, patients infected with SARS-CoV-2 should have enhanced monitoring of their mental status.

Alternative splicing in lung influences COVID-19 severity and respiratory diseases

Alternative splicing generates functional diversity in isoforms, impacting immune response to infection. Here, we evaluate the causal role of alternative splicing in COVID-19 severity and susceptibility by applying two-sample Mendelian randomization to cis-splicing quantitative trait loci and the results from COVID-19 Host Genetics Initiative. We identify that alternative splicing in lung, rather than total expression of OAS1, ATP11A, DPP9 and NPNT, is associated with COVID-19 severity. MUC1 and PMF1 splicing is associated with COVID-19 susceptibility. Colocalization analyses support a shared genetic mechanism between COVID-19 severity with idiopathic pulmonary fibrosis at the ATP11A and DPP9 loci, and with chronic obstructive lung diseases at the NPNT locus. Last, we show that ATP11A, DPP9, NPNT, and MUC1 are highly expressed in lung alveolar epithelial cells, both in COVID-19 uninfected and infected samples. These findings clarify the importance of alternative splicing in lung for COVID-19 and respiratory diseases, providing isoform-based targets for drug discovery.

The causal association between polycystic ovary syndrome and susceptibility and severity of COVID-19: a bidirectional Mendelian randomization study using genetic data.

Observational studies have reported an association between polycystic ovary syndrome (PCOS) and COVID-19, but a definitive causal relationship has not been established. This study aimed to assess this association using two-way two-sample Mendelian randomization (MR). A summary of PCOS characteristics was compiled using the PCOS summary statistics from the Apollo University of Cambridge Repository. COVID-19 susceptibility and severity statistics, including hospitalization and extremely severe disease, were obtained from genome-wide association studies from the COVID-19 Host Genetics Initiative. The primary analysis used the inverse variance-weighted method, supplemented by the weighted median, MR-Egger, and MR-PRESSO methods. The forward MR analysis showed no significant impact of PCOS on COVID-19 susceptibility, hospitalization, or severity (OR = 0.983, 1.011, 1.014; 95% CI = 0.958-1.008, 0.958-1.068, 0.934-1.101; and p = 0.173, 0.68, 0.733; respectively). Similarly, reverse MR analysis found no evidence supporting COVID-19 phenotypes as risk or protective factors for PCOS (OR = 1.041, 0.995, 0.944; 95% CI = 0.657-1.649, 0.85-1.164, 0.843-1.058; and p = 0.864, 0.945, 0.323; respectively). Consequently, no significant association between any COVID-19 phenotype and PCOS was established. This MR study suggested that PCOS is not a causal risk factor for the susceptibility and severity of COVID-19. The associations identified in previous observational studies might be attributable to the presence of comorbidities in the patients.

Mendelian randomization reveals no causal relationship between COVID-19 susceptibility, hospitalization, or severity and epilepsy.

Observational studies have shown an association between COVID-19 and epilepsy. However, causality remains unproven. This study aimed to investigate the causative effect of genetically predicted COVID-19 phenotypes on epilepsy risk using a two-sample Mendelian randomization (MR) analysis. We retrieved summary-level datasets for three COVID-19 phenotypes (COVID-19 susceptibility, COVID-19 hospitalization, and COVID-19 severity) and epilepsy from the genome-wide association studies conducted by the COVID-19 Host Genetics Initiative (COVID-19 HGI) and International League Against Epilepsy (ILAE) consortium, respectively. To analyze the final results, nine MR analytic methods were utilized. The inverse-variance weighted (IVW) method was chosen as the primary approach for data analysis to evaluate the potential causal effect. Other MR analytic methods (MR-Egger regression, weighted median estimator, mode based-estimator, and MR-PRESSO) were used as a supplement to IVW to ensure the robustness of the results. The IVW approach demonstrated no causal association between any genetically predicted COVID-19 phenotype and the risk of epilepsy [COVID-19 susceptibility: odds ratio (OR) = 0.99, 95% confidence interval (CI) = 0.86-1.14, p = 0.92; COVID-19 hospitalization: OR = 1.00, 95% CI = 0.96-1.04, p = 0.95; COVID-19 severity: OR = 0.99, 95% CI = 0.96-1.01, p = 0.25]. Other MR complementary methods revealed consistent results. Additionally, no evidence for heterogeneity and horizontal pleiotropy was found. This MR study revealed no genetically predicted causal relationship between COVID-19 phenotypes and epilepsy.

Biomarkers Associated With Severe COVID-19 Among Populations With High Cardiometabolic Risk

Cardiometabolic parameters are established risk factors for COVID-19 severity. The identification of causal or protective biomarkers for COVID-19 severity may facilitate the development of novel therapies. To identify protein biomarkers that promote or reduce COVID-19 severity and that mediate the association of cardiometabolic risk factors with COVID-19 severity. This genetic association study using 2-sample mendelian randomization (MR) was conducted in 2022 to investigate associations among cardiometabolic risk factors, circulating biomarkers, and COVID-19 hospitalization. Inputs for MR included genetic and proteomic data from 4147 participants with dysglycemia and cardiovascular risk factors collected through the Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Genome-wide association study summary statistics were obtained from (1) 3 additional independent plasma proteome studies, (2) genetic consortia for selected cardiometabolic risk factors (including body mass index [BMI], type 2 diabetes, type 1 diabetes, and systolic blood pressure; all n >10 000), and (3) the COVID-19 Host Genetics Initiative (n = 5773 hospitalized and 15 497 nonhospitalized case participants with COVID-19). Data analysis was performed in July 2022. Genetically determined concentrations of 235 circulating proteins assayed with a multiplex biomarker panel from the ORIGIN trial for the initial analysis. Hospitalization status of individuals from the COVID-19 Host Genetics Initiative with a positive COVID-19 test result. Among 235 biomarkers tested in samples totaling 22 101 individuals, MR analysis showed that higher kidney injury molecule-1 (KIM-1) levels reduced the likelihood of COVID-19 hospitalization (odds ratio [OR] per SD increase in KIM-1 levels, 0.86 [95% CI, 0.79-0.93]). A meta-analysis validated the protective association with no observed directional pleiotropy (OR per SD increase in KIM-1 levels, 0.91 [95% CI, 0.88-0.95]). Of the cardiometabolic risk factors studied, only BMI was associated with KIM-1 levels (0.17 SD increase in biomarker level per 1 kg/m2 [95% CI, 0.08-0.26]) and COVID-19 hospitalization (OR per 1-SD biomarker level, 1.33 [95% CI, 1.18-1.50]). Multivariable MR analysis also revealed that KIM-1 partially mitigated the association of BMI with COVID-19 hospitalization, reducing it by 10 percentage points (OR adjusted for KIM-1 level per 1 kg/m2, 1.23 [95% CI, 1.06-1.43]). In this genetic association study, KIM-1 was identified as a potential mitigator of COVID-19 severity, possibly attenuating the increased risk of COVID-19 hospitalization among individuals with high BMI. Further studies are required to better understand the underlying biological mechanisms.

Associations between polygenic risk score and covid-19 susceptibility and severity across ethnic groups: UK Biobank analysis

BackgroundCOVID-19 manifests with huge heterogeneity in susceptibility and severity outcomes. UK Black Asian and Minority Ethnic (BAME) groups have demonstrated disproportionate burdens. Some variability remains unexplained, suggesting potential genetic contribution. Polygenic Risk Scores (PRS) can determine genetic predisposition to disease based on Single Nucleotide Polymorphisms (SNPs) within the genome. COVID-19 PRS analyses within non-European samples are extremely limited. We applied a multi-ethnic PRS to a UK-based cohort to understand genetic contribution to COVID-19 variability.MethodsWe constructed two PRS for susceptibility and severity outcomes based on leading risk-variants from the COVID-19 Host Genetics Initiative. Scores were applied to 447,382 participants from the UK-Biobank. Associations with COVID-19 outcomes were assessed using binary logistic regression and discriminative power was validated using incremental area under receiver operating curve (ΔAUC). Variance explained was compared between ethnic groups via incremental pseudo-R2 (ΔR2).ResultsCompared to those at low genetic risk, those at high risk had a significantly greater risk of severe COVID-19 for White (odds ratio [OR] 1.57, 95% confidence interval [CI] 1.42–1.74), Asian (OR 2.88, 95% CI 1.63–5.09) and Black (OR 1.98, 95% CI 1.11–3.53) ethnic groups. Severity PRS performed best within Asian (ΔAUC 0.9%, ΔR2 0.98%) and Black (ΔAUC 0.6%, ΔR2 0.61%) cohorts. For susceptibility, higher genetic risk was significantly associated with COVID-19 infection risk for the White cohort (OR 1.31, 95% CI 1.26–1.36), but not for Black or Asian groups.ConclusionsSignificant associations between PRS and COVID-19 outcomes were elicited, establishing a genetic basis for variability in COVID-19. PRS showed utility in identifying high-risk individuals. The multi-ethnic approach allowed applicability of PRS to diverse populations, with the severity model performing well within Black and Asian cohorts. Further studies with larger sample sizes of non-White samples are required to increase statistical power and better assess impacts within BAME populations.

#6774 CAUSAL ASSOCIATION OF COVID-19 AND KIDNEY FUNCTION: A MENDELIAN RANDOMIZATION ANALYSIS

Abstract Background and Aims Previous observational studies suggest that there are potential relationships between COVID-19 and kidney functions. However, whether COVID-19 had causal effects on different kidney traits is currently unclear. We aimed to investigate the causal link between genetically determined COVID-19 and following kidney traits. Method We performed univariate Mendelian randomization (MR) studies using summary genome-wide association studies (GWAS) statistics of COVID-19 severity (n case/n control: 13,769/1,072,442 for European, n case/n control: 794/4862 for Asian), COVID-19 hospitalization (n case/n control: 32,519/2,062,805 for European, n case/n control:2882/31,200 for Asian) and COVID-19 susceptibility (n case/n control: 122,616/2,475,240 for European, n case/n control: 4459/36,121 for Asian) derived from THE COVID-19 Host Genetics Initiative (r7) as exposure. Phenotypic outcomes analyzed for Europeans included chronic kidney disease (CKD), creatinine-based estimated glomerular filtration rate, Cystatin C-based estimated glomerular filtration rate, Urine albumin-to-creatinine ratio, acute and chronic glomerulonephritis, membranous nephropathy, diabetic nephropathy, acute and chronic nephritic syndrome, acute renal failure, glomerular diseases and IgA nephropathy. While for Asians, outcomes including CKD, estimated glomerular filtration rate, serum creatinine, acute and chronic renal failure, diabetic nephropathy, IgA nephropathy, nephrotic syndrome, acute and chronic glomerulonephritis as well as membranous nephropathy were analyzed. The inverse variance weighted (IVW) MR with multiplicative random effects model was performed as primary analysis to evaluate the causal effects of COVID-19 on different kidney traits, and potential pleiotropy as well as heterogeneity was evaluated by using MR Egger and heterogeneity test, respectively. A series of sensitivity analyses, including weighted median MR, weighted mode MR, MR Pleiotropy Residual Sum and Outlier (MR PRESSO) were performed. In addition, the causal effects of COVID-19 on different kidney traits were validated by using additional GWAS summary data of critical COVID-19 (n case/n control: 5989/42891 for European, n case/n control: 274/366 for Asian) from GenOMICC database (r6) as exposure. After multiple corrections, a P value &amp;lt; 0.0036 for Europeans and P value &amp;lt; 0.0045 for Asians were considered as significant. Results IVW MR indicated that none of the COVID-19 phenotypes were associated with CKD (OR, 0.99: P = 0.16 for COVID-19 severity; OR, 0.99: P = 0.41 for COVID-19 hospitalization; OR, 0.95: P = 0.26 for COVID-19 susceptibility), nor other kidney traits for Europeans. As for Asian ancestry, consistent with the findings in Europeans, none of the COVID-19 phenotypes were associated with CKD (OR, 0.89: P = 0.16 for COVID-19 severity; OR, 0.93: P = 0.42 for COVID-19 hospitalization; OR, 0.95: P = 0.61 for COVID-19 susceptibility), nor other kidney traits as mentioned above. All sensitivity analyses also consistently indicated the absence of causal effects of COVID-19 severity, hospitalization and susceptibility on different kidney traits, neither in the European nor in the Asian population. Conclusion There is no significant evidence supporting the causal effects of genetically predicted COVID-19 phenotype on the following different kidney traits. More deeply explorations focused on the association between COVID-19 and kidney traits should be performed with more data would be available in the future.

Assessing the potential of polygenic scores to strengthen medical risk prediction models of COVID-19.

As findings on the epidemiological and genetic risk factors for coronavirus disease-19 (COVID-19) continue to accrue, their joint power and significance for prospective clinical applications remains virtually unexplored. Severity of symptoms in individuals affected by COVID-19 spans a broad spectrum, reflective of heterogeneous host susceptibilities across the population. Here, we assessed the utility of epidemiological risk factors to predict disease severity prospectively, and interrogated genetic information (polygenic scores) to evaluate whether they can provide further insights into symptom heterogeneity. A standard model was trained to predict severe COVID-19 based on principal component analysis and logistic regression based on information from eight known medical risk factors for COVID-19 measured before 2018. In UK Biobank participants of European ancestry, the model achieved a relatively high performance (area under the receiver operating characteristic curve ~90%). Polygenic scores for COVID-19 computed from summary statistics of the Covid19 Host Genetics Initiative displayed significant associations with COVID-19 in the UK Biobank (p-values as low as 3.96e-9, all with R2 under 1%), but were unable to robustly improve predictive performance of the non-genetic factors. However, error analysis of the non-genetic models suggested that affected individuals misclassified by the medical risk factors (predicted low risk but actual high risk) display a small but consistent increase in polygenic scores. Overall, the results indicate that simple models based on health-related epidemiological factors measured years before COVID-19 onset can achieve high predictive power. Associations between COVID-19 and genetic factors were statistically robust, but currently they have limited predictive power for translational settings. Despite that, the outcomes also suggest that severely affected cases with a medical history profile of low risk might be partly explained by polygenic factors, prompting development of boosted COVID-19 polygenic models based on new data and tools to aid risk-prediction.

Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity

BackgroundEpidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity. MethodsSummary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship. ResultsOur results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86–1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54–1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96–1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity. ConclusionsThis indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.