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

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Title: 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
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
Item Type: Journal Article
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).
Issue Date: 25-May-2023
Date of Acceptance: 27-Mar-2023
URI: http://hdl.handle.net/10044/1/104327
DOI: 10.1038/s41586-023-06034-3
ISSN: 0028-0836
Publisher: Nature Research
Start Page: 764
End Page: 768
Journal / Book Title: Nature
Volume: 617
Issue: 7962
Copyright Statement: © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Publication Status: Published
Conference Place: England
Online Publication Date: 2023-05-17
Appears in Collections:Department of Metabolism, Digestion and Reproduction
Department of Surgery and Cancer
Department of Infectious Diseases
National Heart and Lung Institute
Faculty of Medicine
Imperial College London COVID-19



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