Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/27952
Title: Mapping the human genetic architecture of COVID-19
Authors: Karjalainen, J
Liao, RG
Neale, BM
Daly, M
Ganna, A
Pathak, GA
Andrews, SJ
Kanai, M
Veerapen, K
Fernandez-Cadenas, I
Nolan, C
Schulte, EC
Striano, P
Marttila, M
Minica, C
Marouli, E
Karim, MA
Wendt, FR
Savage, J
Sloofman, L
Butler-Laporte, G
Kim, HN
Kanoni, S
Okada, Y
Byun, J
Han, Y
Uddin, MJ
Smith, GD
Willer, CJ
Buxbaum, JD
Mehtonen, J
Finucane, H
Cordioli, M
Martin, AR
Zhou, W
Pasaniuc, B
Julienne, H
Aschard, H
Shi, H
Yengo, L
Polimanti, R
Ghoussaini, M
Schwartzentruber, J
Dunham, I
Chwialkowska, K
Francescatto, M
Trankiem, A
Balaconis, MK
Davis, L
Lee, S
Priest, J
Renieri, A
Sankaran, VG
van Heel, D
Deelen, P
Brent Richards, J
Nakanishi, T
Biesecker, L
Eric Kerchberger, V
Kenneth Baillie, J
Mari, F
Bernasconi, A
Ceri, S
Canakoglu, A
Wolford, B
Faucon, A
Dutta, AK
Schurmann, C
Harry, E
Birney, E
Nguyen, H
Nasir, J
Kaunisto, M
Solomonson, M
Dueker, N
Vadgama, N
Limou, S
Rahmouni, S
Mbarek, H
Darwish, D
Uddin, MM
Albertos, R
Pérez-Tur, J
Li, R
Folkersen, L
Moltke, I
Koelling, N
Teumer, A
Kousathanas, A
Utrilla, A
Verdugo, RA
Zárate, R
Medina-Gómez, C
Gómez-Cabrero, D
Carnero-Montoro, E
Cadilla, CL
Moreno-Estrada, A
Garmendia, A
Moya, L
Sedaghati-Khayat, B
Keywords: genetics;genome-wide association studies;SARS-CoV-2;viral infection
Issue Date: 8-Jul-2021
Publisher: Springer Nature
Citation: Niemi, K. et al for the COVID-19 Host Genetics Initiative (2021) 'Mapping the human genetic architecture of COVID-19', Nature, 600 (7889), pp. 472 - 477. doi: 10.1038/s41586-021-03767-x.
Abstract: Copyright © The Author(s) 2021. The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Description: Matters Arising to this article was published on 03 August 2022, available online at: https://doi.org/10.1038/s41586-022-04826-7 . A second Matters Arising to this article was published on 06 September 2023, available online at: https://doi.org/10.1038/s41586-023-06355-3 .
Data availability: Summary statistics generated by the COVID-19 HGI are available at https://www.covid19hg.org/results/r5/ and are available in the GWAS Catalog (study code GCST011074). The analyses described here include the freeze-5 data. COVID-19 HGI continues to regularly release new data freezes. Summary statistics for non-European ancestry samples are not currently available due to the small individual sample sizes of these groups, but results for lead variants of 13 loci are reported in Supplementary Table 3. Individual level data can be requested directly from contributing studies, listed in Supplementary Table 1. We used publicly available data from GTEx (https://gtexportal.org/home/), the Neale lab (https://www.nealelab.is/uk-biobank/), Finucane lab (https://www.finucanelab.org), the FinnGen Freeze 4 cohort (https://www.finngen.fi/en/access_results) and the eQTL catalogue release 3 (https://www.ebi.ac.uk/eqtl/).
Code availability: The code for summary statistics lift-over, the projection PCA pipeline including precomputed loadings and meta-analyses are available on GitHub (https://github.com/covid19-hg/) and the code for the Mendelian randomization and genetic correlation pipeline is available on GitHub at https://github.com/marcoralab/MRcovid.
Reporting summary: Further information on research design is available in the Nature Research Reporting Summary linked to this paper online at: https://www.nature.com/articles/s41586-021-03767-x#MOESM2 .
Supplementary information is available onlne at: https://www.nature.com/articles/s41586-021-03767-x#Sec24 .
Extended data figures and tables are available online at: https://www.nature.com/articles/s41586-021-03767-x#Sec23 .
URI: https://bura.brunel.ac.uk/handle/2438/27952
DOI: https://doi.org/10.1038/s41586-021-03767-x
ISSN: 0028-0836
Other Identifiers: ORCID iD: Claire M. Nolan https://orcid.org/0000-0001-9067-599X
Appears in Collections:Dept of Health Sciences Research Papers

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