• Media type: E-Article
  • Title: GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19
  • Contributor: Pairo-Castineira, Erola; Rawlik, Konrad; Bretherick, Andrew D.; Qi, Ting; Wu, Yang; Nassiri, Isar; McConkey, Glenn A.; Zechner, Marie; Klaric, Lucija; Griffiths, Fiona; Oosthuyzen, Wilna; Kousathanas, Athanasios; Richmond, Anne; Millar, Jonathan; Russell, Clark D.; Malinauskas, Tomas; Thwaites, Ryan; Morrice, Kirstie; Keating, Sean; Maslove, David; Nichol, Alistair; Semple, Malcolm G.; Knight, Julian; Shankar-Hari, Manu; [...]
  • imprint: Springer Science and Business Media LLC, 2023
  • Published in: Nature
  • Language: English
  • DOI: 10.1038/s41586-023-06034-3
  • ISSN: 0028-0836; 1476-4687
  • Keywords: Multidisciplinary
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown<jats:sup>1</jats:sup> to be highly efficient for discovery of genetic associations<jats:sup>2</jats:sup>. 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 group<jats:sup>3</jats:sup>. 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 (<jats:italic>JAK1</jats:italic>), monocyte–macrophage activation and endothelial permeability (<jats:italic>PDE4A</jats:italic>), immunometabolism (<jats:italic>SLC2A5</jats:italic> and <jats:italic>AK5</jats:italic>), and host factors required for viral entry and replication (<jats:italic>TMPRSS2</jats:italic> and <jats:italic>RAB2A</jats:italic>).</jats:p>