Kousathanas, Athanasios ORCID: 0000-0001-6265-6521, Pairo-Castineira, Erola ORCID: 0000-0002-2423-3090, Rawlik, Konrad ORCID: 0000-0002-0010-370X, Stuckey, Alex ORCID: 0000-0001-8636-737X, Odhams, Christopher ORCID: 0000-0003-2396-6150, Walker, Susan, Russell, Clark ORCID: 0000-0002-9873-8243, Malinauskas, Tomas, Millar, Jonathan ORCID: 0000-0002-4853-9377, Elliott, Katherine et al (show 52 more authors)
(2021)
Whole genome sequencing identifies multiple loci for critical illness caused by COVID-19.
[Preprint]
Abstract
Critical illness in COVID-19 is caused by inflammatory lung injury, mediated by the host immune system. We and others have shown that host genetic variation influences the development of illness requiring critical care 1 or hospitalisation 2;3;4 following SARS-Co-V2 infection. The GenOMICC (Genetics of Mortality in Critical Care) study recruits critically-ill cases and compares their genomes with population controls in order to find underlying disease mechanisms. Here, we use whole genome sequencing and statistical fine mapping in 7,491 critically-ill cases compared with 48,400 population controls to discover and replicate 22 independent variants that significantly predispose to life-threatening COVID-19. We identify 15 new independent associations with critical COVID-19, including variants within genes involved in interferon signalling ( IL10RB, PLSCR1 ), leucocyte differentiation ( BCL11A ), and blood type antigen secretor status ( FUT2 ). Using transcriptome-wide association and colocalisation to infer the effect of gene expression on disease severity, we find evidence implicating expression of multiple genes, including reduced expression of a membrane flippase ( ATP11A ), and increased mucin expression ( MUC1 ), in critical disease. We show that comparison between critically-ill cases and population controls is highly efficient for genetic association analysis and enables detection of therapeutically-relevant mechanisms of disease. Therapeutic predictions arising from these findings require testing in clinical trials.
Item Type: | Preprint |
---|---|
Uncontrolled Keywords: | GenOMICC Investigators, 23andMe, Covid-19 Human Genetics Initiative |
Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences |
Depositing User: | Symplectic Admin |
Date Deposited: | 22 Oct 2021 07:02 |
Last Modified: | 15 Aug 2024 13:49 |
DOI: | 10.1101/2021.09.02.21262965 |
Open Access URL: | http://10.0.4.77/2021.09.02.21262965 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3141191 |