BIGwas: Single-command quality control and association testing for multi-cohort and biobank-scale GWAS/PheWAS data.

BACKGROUND: Genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) involving 1 million GWAS samples from dozens of population-based biobanks present a considerable computational challenge and are carried out by large scientific groups under great expenditure of time and personnel. Automating these processes requires highly efficient and scalable methods and software, but so far there is no workflow solution to easily process 1 million GWAS samples. RESULTS: Here we present BIGwas, a portable, fully automated quality control and association testing pipeline for large-scale binary and quantitative trait GWAS data provided by biobank resources. By using Nextflow workflow and Singularity software container technology, BIGwas performs resource-efficient and reproducible analyses on a local computer or any high-performance compute (HPC) system with just 1 command, with no need to manually install a software execution environment or various software packages. For a single-command GWAS analysis with 974,818 individuals and 92 million genetic markers, BIGwas takes ∼16 days on a small HPC system with only 7 compute nodes to perform a complete GWAS QC and association analysis protocol. Our dynamic parallelization approach enables shorter runtimes for large HPCs. CONCLUSIONS: Researchers without extensive bioinformatics knowledge and with few computer resources can use BIGwas to perform multi-cohort GWAS with 1 million GWAS samples and, if desired, use it to build their own (genome-wide) PheWAS resource. BIGwas is freely available for download from http://github.com/ikmb/gwas-qc and http://github.com/ikmb/gwas-assoc.

Detailed stratified GWAS analysis for severe COVID-19 in four European populations.

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.

The MUC5B Promoter Polymorphism Associates With Severe COVID-19 in the European Population.

Background: Diversity in response on exposure to severe acute respiratory syndrome coronavirus 2 may be related to the innate immune response in the elderly. The mucin MUC5B is an important component of the innate immune response and expression levels are associated with the MUC5B promoter polymorphism, rs35705950. The high expressing T-allele is a risk allele for the non-infectious aging lung disease idiopathic pulmonary fibrosis (IPF). We investigated if MUC5B rs35705950 associates with severe COVID-19. Methods: In this retrospective candidate gene case-control study we recruited 108 Dutch patients (69% male, median age 66 years, 77% white) requiring hospitalization for COVID-19 (22% ICU stay, 24% died). For validation, genotypes were obtained from the UK-Biobank (n = 436, 57% male, median age 70 years, 27% died), for replication data from the severe COVID-19 GWAS group from Italy (n = 835) and Spain (n = 775) was used, each with a control cohort (n = 356,735, n = 1,255, n = 950, respectively). MUC5B association analysis was performed including adjustment for age and sex. Results: The rs35705950 T-allele frequency was significantly lower in Dutch white patients (n = 83) than in controls (0.04 vs. 0.10; p = 0.02). This was validated in the UK biobank cohort (0.08 vs. 0.11; p = 0.001). While age and sex differed significantly between cases and control, comparable results were obtained with age and sex as confounding variables in a multivariate analysis. The association was replicated in the Italian (p = 0.04), and Spanish (p = 0.03) case-control cohorts. Meta-analysis showed a negative association for the T-allele with COVID-19 (OR = 0.75 (CI: 0.67-0.85); p = 6.63 × 10-6). Conclusions: This study shows that carriage of the T-allele of MUC5B rs35705950 confers protection from development of severe COVID-19. Because the T-allele is a known risk allele for IPF, this study provides further evidence for the existence of trade-offs between optimal mucin expression levels in the aging lung.

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality.

BackgroundThere is considerable variability in COVID-19 outcomes among younger adults, and some of this variation may be due to genetic predisposition.MethodsWe combined individual level data from 13,888 COVID-19 patients (n = 7185 hospitalized) from 17 cohorts in 9 countries to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. We next performed metaanalyses using FinnGen and the Columbia University COVID-19 Biobank.ResultsWe found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (HR, 1.4; 95% CI, 1.2-1.7). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (OR, 2.1; 95% CI, 1.6-2.6), venous thromboembolism (OR, 1.7; 95% CI, 1.2-2.4), and hepatic injury (OR, 1.5; 95% CI, 1.2-2.0). Risk allele carriers age 60 years and younger had higher odds of death or severe respiratory failure (OR, 2.7; 95% CI, 1.8-3.9) compared with those of more than 60 years (OR, 1.5; 95% CI, 1.2-1.8; interaction, P = 0.038). Among individuals 60 years and younger who died or experienced severe respiratory failure, 32.3% were risk-variant carriers compared with 13.9% of those not experiencing these outcomes. This risk variant improved the prediction of death or severe respiratory failure similarly to, or better than, most established clinical risk factors.ConclusionsThe major common COVID-19 genetic risk factor is associated with increased risks of morbidity and mortality, which are more pronounced among individuals 60 years or younger. The effect was similar in magnitude and more common than most established clinical risk factors, suggesting potential implications for future clinical risk management.

Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.

Genomewide Association Study of Severe Covid-19 with Respiratory Failure.

BACKGROUND: There is considerable variation in disease behavior among patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19). Genomewide association analysis may allow for the identification of potential genetic factors involved in the development of Covid-19. METHODS: We conducted a genomewide association study involving 1980 patients with Covid-19 and severe disease (defined as respiratory failure) at seven hospitals in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe. After quality control and the exclusion of population outliers, 835 patients and 1255 control participants from Italy and 775 patients and 950 control participants from Spain were included in the final analysis. In total, we analyzed 8,582,968 single-nucleotide polymorphisms and conducted a meta-analysis of the two case-control panels. RESULTS: We detected cross-replicating associations with rs11385942 at locus 3p21.31 and with rs657152 at locus 9q34.2, which were significant at the genomewide level (P<5×10-8) in the meta-analysis of the two case-control panels (odds ratio, 1.77; 95% confidence interval [CI], 1.48 to 2.11; P = 1.15×10-10; and odds ratio, 1.32; 95% CI, 1.20 to 1.47; P = 4.95×10-8, respectively). At locus 3p21.31, the association signal spanned the genes SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6 and XCR1. The association signal at locus 9q34.2 coincided with the ABO blood group locus; in this cohort, a blood-group-specific analysis showed a higher risk in blood group A than in other blood groups (odds ratio, 1.45; 95% CI, 1.20 to 1.75; P = 1.48×10-4) and a protective effect in blood group O as compared with other blood groups (odds ratio, 0.65; 95% CI, 0.53 to 0.79; P = 1.06×10-5). CONCLUSIONS: We identified a 3p21.31 gene cluster as a genetic susceptibility locus in patients with Covid-19 with respiratory failure and confirmed a potential involvement of the ABO blood-group system. (Funded by Stein Erik Hagen and others.).