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

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Autores de IDIVAL

Autores ajenos al IDIVAL

  • Pairo-Castineira E
  • Rawlik K
  • Bretherick AD
  • Qi T
  • Wu Y
  • Nassiri I
  • McConkey GA
  • Zechner M
  • Klaric L
  • Griffiths F
  • Oosthuyzen W
  • Kousathanas A
  • Richmond A
  • Millar J
  • Russell CD
  • Malinauskas T
  • Thwaites R
  • Morrice K
  • Keating S
  • Maslove D
  • Nichol A
  • Semple MG
  • Knight J
  • Shankar-Hari M
  • Summers C
  • Hinds C
  • Horby P
  • Ling L
  • McAuley D
  • Montgomery H
  • Openshaw PJM
  • Begg C
  • Walsh T
  • Tenesa A
  • Flores C
  • Rojas-Martinez A
  • Lapunzina P
  • GenOMICC Investigators
  • SCOURGE Consortium
  • ISARICC Investigators
  • 23andMe COVID-19 Team
  • Yang J
  • Ponting CP
  • Wilson JF
  • Vitart V
  • Abedalthagafi M
  • Luchessi AD
  • Parra EJ
  • Cruz R
  • Carracedo A
  • Fawkes A
  • Murphy L
  • Rowan K
  • Pereira AC
  • Law A
  • Fairfax B
  • Hendry SC
  • Baillie JK



Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown(1) to be highly efficient for discovery of genetic associations(2). 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(3). 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).

© 2023. The Author(s).

Datos de la publicación

0028-0836, 1476-4687



Citas Recibidas en Web of Science: 38


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