TY - JOUR
T1 - GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19
AU - GenOMICC Investigators
AU - Management, Laboratory and Data Team
AU - SCOURGE Consortium
AU - ISARICC Investigators
AU - Data Analysis Team
AU - Data Architecture Team
AU - Data Analysis and Management Team
AU - Project Administration Team
AU - Project Management Team
AU - The 23andMe COVID-19 Team
AU - Pairo-Castineira, Erola
AU - Rawlik, Konrad
AU - Bretherick, Andrew D.
AU - Qi, Ting
AU - Wu, Yang
AU - Nassiri, Isar
AU - McConkey, Glenn A.
AU - Zechner, Marie
AU - Klaric, Lucija
AU - Griffiths, Fiona
AU - Oosthuyzen, Wilna
AU - Kousathanas, Athanasios
AU - Richmond, Anne
AU - Millar, Jonathan
AU - Russell, Clark D.
AU - Malinauskas, Tomas
AU - Thwaites, Ryan
AU - Morrice, Kirstie
AU - Keating, Sean
AU - Maslove, David
AU - Nichol, Alistair
AU - Semple, Malcolm G.
AU - Knight, Julian
AU - Shankar-Hari, Manu
AU - Summers, Charlotte
AU - Hinds, Charles
AU - Horby, Peter
AU - Ling, Lowell
AU - McAuley, Danny
AU - Montgomery, Hugh
AU - Openshaw, Peter J.M.
AU - Begg, Colin
AU - Walsh, Timothy
AU - Tenesa, Albert
AU - Flores, Carlos
AU - Riancho, José A.
AU - Rojas-Martinez, Augusto
AU - Lapunzina, Pablo
AU - Clohisey, Sara
AU - Millar, Johnny
AU - Shankar-Hari, Manu
AU - Aitkin, Emma
AU - Aravindan, Latha
AU - Armstrong, Ruth
AU - Baillie, J. Kenneth
AU - Biggs, Heather
AU - Boz, Ceilia
AU - Brown, Adam
AU - Chikowore, Primmy
AU - Faulkner, Maria
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/5/25
Y1 - 2023/5/25
N2 - 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).
AB - 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).
UR - http://www.scopus.com/inward/record.url?scp=85160212509&partnerID=8YFLogxK
U2 - 10.1038/s41586-023-06034-3
DO - 10.1038/s41586-023-06034-3
M3 - Article
C2 - 37198478
AN - SCOPUS:85160212509
SN - 0028-0836
VL - 617
SP - 764
EP - 768
JO - Nature
JF - Nature
IS - 7962
ER -