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

Authors :
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
Riancho JA
Rojas-Martinez A
Lapunzina P
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
Source :
Nature [Nature] 2023 May; Vol. 617 (7962), pp. 764-768. Date of Electronic Publication: 2023 May 17.
Publication Year :
2023

Abstract

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown <superscript>1</superscript> to be highly efficient for discovery of genetic associations <superscript>2</superscript> . 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 <superscript>3</superscript> . 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).<br /> (© 2023. The Author(s).)

Details

Language :
English
ISSN :
1476-4687
Volume :
617
Issue :
7962
Database :
MEDLINE
Journal :
Nature
Publication Type :
Academic Journal
Accession number :
37198478
Full Text :
https://doi.org/10.1038/s41586-023-06034-3