GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

• Authors: Erola Pairo-Castineira, MRC Centre for Inflammation Research; Konrad Rawlik, MRC Centre for Inflammation Research; Andrew D. Bretherick, MRC Centre for Inflammation Research; Ting Qi, Westlake University; Yang Wu, University of Queensland; Isar Nassiri, Wellcome Centre for Human Genetics; Glenn A. McConkey, University of Leeds; Marie Zechner, MRC Centre for Inflammation Research; Lucija Klaric, MRC Human Genetics Unit; Malak AlThgafi, Emory University
• Journal Title: Nature
• Volume: Volume 617, Number 7962
• Publisher: Nature | 2023-05-01, Pages 764-768
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1038/s41586-023-06034-3
• Subjects: Biology, Virology; Biology, Genetics
• Keywords: Humans; COVID-19; Critical Illness; Genetic Predisposition to Disease; Genome-Wide Association Study; Genotype; Phenotype; Genetic Variation; Whole Genome Sequencing; Transcriptome; Monocytes; rab GTP-Binding Proteins; Genotyping Techniques

Abstract

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).