1. Whole genome sequencing identifies multiple loci for critical illness caused by COVID-19
- Author
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Clark D Russell, Erola Pairo-Castineira, Malcolm G Semple, James F. Wilson, Jian Yang, andMe Investigators, Seán Keating, Yang Wu, Tala Zainy, Greg Elgar, Angie Fawkes, Lucija Klaric, Julian C. Knight, Paul Elliott, Richard H Scott, Charlotte Summers, David M. Maslove, Daniel F. McAuley, Marie Zechner, Sally Donovan, J Kenneth Baillie, Athanasios Kousathanas, Daniel Rhodes, Nicholas J. Parkinson, Veronique Vitart, Susan P. Walker, Peter Horby, Fiona Griffiths, Bo Wang, Peter J. M. Openshaw, Linda Todd, Andy Law, Sara Clohisey, Tom Fowler, Augusto Rendon, Alex Stuckey, Christopher A Odhams, Andrew D. Bretherick, Hugh Montgomery, Katherine S. Elliott, Shahla Salehi, Jonathan E Millar, Loukas Moutsianas, Charles J. Hinds, Kathy Rowan, Mark J. Caulfield, Fiona Maleady-Crowe, Timothy S. Walsh, Prabhu Arumugam, Georgia Chan, Lee Murphy, Afshan Siddiq, GenoMICC Investigators, Tomas Malinauskas, Konrad Rawlik, Kirstie Morrice, Chris P. Ponting, Alistair Nichol, Wilna Oosthuyzen, Manu Shankar-Hari, and Peter Goddard
- Subjects
Whole genome sequencing ,Genetics ,education.field_of_study ,Immune system ,Antigen ,Genetic variation ,Population ,Disease ,Biology ,Lung injury ,education ,Gene - 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 care1or hospitalisation2;3;4following 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.
- Published
- 2021
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