Detailed stratified GWAS analysis for severe COVID-19 in four European populations
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Abstract
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.
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SciScore for 10.1101/2021.07.21.21260624: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: 5 Recruiting Centers and Ethics Committee Approval IDs: The project protocol involved the rapid recruitment of patient-participants and no additional project-related procedures (we primarily used material from clinically indicated venipunctures) and afforded anonymity, owing to the minimal dataset collected.
Consent: Differences in recruitment and consent procedures among the centers arose because some centers integrated the project into larger COVID-19 biobanking efforts, whereas other centers did not, and because there were differences in how local ethics committees provided guidance on the handling of anonymization or deidentification of data as well as consent procedures.Sex as a … SciScore for 10.1101/2021.07.21.21260624: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics IRB: 5 Recruiting Centers and Ethics Committee Approval IDs: The project protocol involved the rapid recruitment of patient-participants and no additional project-related procedures (we primarily used material from clinically indicated venipunctures) and afforded anonymity, owing to the minimal dataset collected.
Consent: Differences in recruitment and consent procedures among the centers arose because some centers integrated the project into larger COVID-19 biobanking efforts, whereas other centers did not, and because there were differences in how local ethics committees provided guidance on the handling of anonymization or deidentification of data as well as consent procedures.Sex as a biological variable Analysis of the Y-chromosome haplotypes: First, we produced high quality Y-chromosome genotypes by manually calling and visually inspecting Y-chromosome SNPs in the male fraction of the cohorts only. Randomization not detected. Blinding not detected. Power Analysis Sub-analyses in age groups of 20-40, 41-60, 61-80 and > 80 years were carried out, with the highest sample numbers and statistical power in the age groups of 41-60 and 61-80 years, such that only these are reported (Supplementary Table 1e). Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources Blood types A and AB were also analyzed combined as “A and AB”. ABsuggested: RRID:BDSC_203)Software and Algorithms Sentences Resources Association analysis of the 17q21.31 inversion: 17q21.31 inversion genotypes were imputed using IMPUTE v2.3.245, 46 from quality controlled SNP data (first and second analysis) based on experimentally-validated inversion genotypes from 109 individuals from the 1000 Genomes Project or from P-values (COVID-19 HGI A2/B2 release 5 data) using Fast and accurate P-value Imputation for genome-wide association study (FAPI) (Supplementary Methods). 1000 Genomes Projectsuggested: (1000 Genomes Project and AWS, RRID:SCR_008801)22 Candidate coding genes were selected based on their inclusion in the GWAS credible sets and/or if any of the variants had been identified as lead eQTL or sQTL. sQTLsuggested: (SQTL, RRID:SCR_000827)The analysis was carried out using hurdle modeling, implemented in the R package MAST.52 Finally, to check the effect of the 17q21.31 inversion on monocytes stimulated by infection-like conditions we also performed a differential expression analysis in the RNA-seq data from Quach et al.53 by imputing the inversion genotypes with IMPUTE v2.3.225 and quantifying gene and transcript expression differences with Kallisto v0.46.020 and QTLtools v1.154. IMPUTEsuggested: (IMPUTE, RRID:SCR_009245)Kallistosuggested: (kallisto, RRID:SCR_016582)QTLtoolssuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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