Crossfield, SSR orcid.org/0000-0001-7337-3527, Chaddock, NJM, Iles, MM orcid.org/0000-0002-2603-6509 et al. (2 more authors) (2022) Interplay between demographic, clinical and polygenic risk factors for severe COVID-19. International Journal of Epidemiology, 51 (5). pp. 1384-1395. ISSN 0300-5771
Abstract
Background
We aimed to identify clinical, socio-demographic and genetic risk factors for severe COVID-19 (hospitalization, critical care admission or death) in the general population.
Methods
In this observational study, we identified 9560 UK Biobank participants diagnosed with COVID-19 during 2020. A polygenic risk score (PRS) for severe COVID-19 was derived and optimized using publicly available European and trans-ethnic COVID-19 genome-wide summary statistics. We estimated the risk of hospital or critical care admission within 28 days or death within 100 days following COVID-19 diagnosis, and assessed associations with socio-demographic factors, immunosuppressant use and morbidities reported at UK Biobank enrolment (2006–2010) and the PRS. To improve biological understanding, pathway analysis was performed using genetic variants comprising the PRS.
Results
We included 9560 patients followed for a median of 61 (interquartile range = 34–88) days since COVID-19 diagnosis. The risk of severe COVID-19 increased with age and obesity, and was higher in men, current smokers, those living in socio-economically deprived areas, those with historic immunosuppressant use and individuals with morbidities and higher co-morbidity count. An optimized PRS, enriched for single-nucleotide polymorphisms in multiple immune-related pathways, including the ‘oligoadenylate synthetase antiviral response’ and ‘interleukin-10 signalling’ pathways, was associated with severe COVID-19 (adjusted odds ratio 1.32, 95% CI 1.11–1.58 for the highest compared with the lowest PRS quintile).
Conclusion
This study conducted in the pre-SARS-CoV-2-vaccination era, emphasizes the novel insights to be gained from using genetic data alongside commonly considered clinical and socio-demographic factors to develop greater biological understanding of severe COVID-19 outcomes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | COVID-19, polygenic risk score, epidemiology, risk prediction |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Discovery & Translational Science Dept (Leeds) |
Funding Information: | Funder Grant number MRC (Medical Research Council) Exception P.O. 4050781788 NIHR National Inst Health Research BRC NIHR National Inst Health Research NIHR202395 |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Jul 2022 14:12 |
Last Modified: | 25 Jun 2023 23:02 |
Status: | Published |
Publisher: | Oxford University Press |
Identification Number: | 10.1093/ije/dyac137 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188709 |