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

Erola Pairo-CastineiraKonrad RawlikAndrew D BretherickTing QiYang WuIsar NassiriGlenn A McConkeyMarie ZechnerLucija KlarićFiona GriffithsWilna OosthuyzenAthanasios KousathanasAnne RichmondJonathan MillarClark D RussellTomas MalinauskasRyan S ThwaitesKirstie MorriceSean KeatingDavid MasloveAlistair NicholMalcolm Gracie SempleJulian KnightManu Shankar-HariCharlotte SummersCharles J HindsPeter HorbyLowell LingDaniel Francis McAuleyHugh E MontgomeryPeter J M OpenshawColin BeggTimothy WalshAlbert TenesaCarlos FloresJosé A RianchoAugusto Rojas-MartinezPablo Lapunzinanull nullnull nullnull nullnull nullJian YangChris Paul PontingJames F WilsonVeronique VitartMalak AbedalthagafiAndre D LuchessiEsteban J ParraRaquel CruzAngel CarracedoAngie FawkesLee MurphyKathryn M RowanAlexandre C PereiraAndrew LawBenjamin P FairfaxSara Clohisey HendryJohn Kenneth Baillie
Published in: Nature (2023)
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).
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