Critical illness in Covid-19 is an extreme and clinically homogeneous disease
phenotype, which we have previously shown1 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 critically ill patients can identify immunomodulatory therapies with strong beneficial effects in this group.3 Here, we provide an analysis of 24,202 critically ill cases comprising a combination of microarray genotype and whole genome sequence data from critically ill cases in the GenOMICC UK (11,440 cases) study, combined with other studies recruiting hospitalised patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and SCOURGE consortium (5,934 cases). To put these results in context of existing work, we conduct a meta-analysis of the new GenOMICC GWAS results with previously published data. We find 49 genome-wide significant associations. In order to explore the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression using a new monocyte TWAS model, as well as gene and protein expression using Mendelian randomisation. We identify potentially druggable targets in multiple systems including inflammatory signalling (JAK1), monocyte-macrophage activation (PDE4A), immunometabolism (SLC2A5, AK5), and host factors required for viral entry and replication (TMPRSS2, RAB2A).

Cite as

Pairo-Castineira, E., Rawlik, K., Bretherick, A., Qi, T., Wu, Y., Nassiri, I., McConkey, G., Zechner, M., Klaric, L., Griffiths, F., Oosthuyzen, W., Kousathanas, A., Richmond, A., Millar, J., Russell, C., Malinauskas, T., Thwaites, R., Morrice, K., Keating, S., Maslove, D., Nichol, A., Semple, M., Knight, J., Shankar-Hari, M., Summers, C., Hinds, C., Horby, P., Ling, L., McAuley, D., Montgomery, H., Openshaw, P., Begg, C., Walsh, T., Tenesa, A., Flores, C., Riancho, J., Rojas-Martinez, A., Lapunzina, P., Yang, J., Ponting, C., Wilson, J., Vitart, V., Abedalthagafi, M., Luchessi, A., Parra, E., Cruz, R., Carracedo, A., Fawkes, A., Murphy, L., Rowan, K., Pereira, A., Law, A., Fairfax, B., Clohisey, S. & Baillie, J. 2023, 'GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19', Nature, 617 , pp. 763-793 . https://doi.org/10.1038/s41586-023-06034-3

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Last updated: 03 May 2024
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