Breedon, JR, Marshall, CR, Giovannoni, G, van Heel, DA, Akhtar, S, Anwar, M, Arciero, E, Asgar, O, Ashraf, S, Breen, G, Chung, R, Curtis, CJ, Chaudhary, S, Chowdhury, M, Colligan, G, Deloukas, P, Durham, C, Durrani, F, Eto, F, Finer, S et al, Garcia, AA, Griffiths, C, Harvey, J, Heng, T, Huang, QQ, Hurles, M, Hunt, KA, Hussain, S, Islam, K, Jacobs, BM, Khan, A, Khan, A, Lavery, C, Lee, SH, Lerner, R, MacArthur, D, Malawsky, D, Martin, H, Mason, D, Mazid, MB, McDermott, J, McSweeney, S, Miah, S, Munir, S, Newman, B, Owor, E, Qureshi, A, Rahman, S, Safa, N, Solly, J, Tahmasebi, F, Trembath, RC, Tricker, K, Uddin, N, van Heel, DA, Winckley, C, Wright, J, Dobson, R and Jacobs, BM (2023) Polygenic risk score prediction of multiple sclerosis in individuals of South Asian ancestry. Brain Communications, 5 (2).

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Abstract

Polygenic risk scores aggregate an individual’s burden of risk alleles to estimate overall genetic risk for a specific trait or disease. Polygenic risk scores derived from Genome-Wide Association Studies of European populations perform poorly for other ancestral groups. Given the potential for future clinical utility, underperformance of polygenic risk score prediction in South Asian populations has the potential to reinforce health inequalities. To determine whether European-derived polygenic risk scores underperform at Multiple Sclerosis prediction in a South Asian population compared with a European-ancestry cohort, we used data from two longitudinal genetic cohort studies: Genes & Health (2015-), a study of ∼50,000 British-Bangladeshi and British-Pakistani individuals, and UK Biobank (2006-), which is comprised of ∼500,000 predominantly White British individuals. We compared individuals with and without Multiple Sclerosis in both studies (Genes and Health: NCases=42, NControl=40,490; UK Biobank: NCases=2091, NControl=374,866). Polygenic risk scores were calculated using clumping-and-thresholding with risk allele effect sizes from the largest Multiple Sclerosis Genome-Wide Association Study to date. Scores were calculated with and without the Major Histocompatibility Complex region, the most influential locus in determining Multiple Sclerosis risk. Polygenic risk scire prediction was evaluated using Nagelkerke’s pseudo-R2 metric adjusted for case ascertainment, age, sex, and the first four genetic principal components. We found that, as expected, European-derived polygenic risk scores perform poorly in the Genes and Health cohort, explaining 1.1% (including the Major Histocompatibility Complex) and 1.5% (excluding the Major Histocompatibility Complex) of disease risk. In contrast, Multiple Sclerosis polygenic risk scores explained 4.8% (including the Major Histocompatibility Complex) and 2.8% (excluding the Major Histocompatibility Complex) of disease risk in European-ancestry UK Biobank participants. These findings suggest that polygenic risk score prediction of Multiple Sclerosis based on European Genome-Wide Association Study results is less accurate in a South Asian population. Genetic studies of ancestrally-diverse populations are required to ensure that polygenic risk scores can be useful across ancestries.

Item Type:	Article
Subjects:	Q Science > QH Natural history > QH301 Biology Q Science > QH Natural history > QH426 Genetics
Divisions:	Biological & Environmental Sciences (from Sep 19)
Publisher:	Oxford University Press (OUP)
SWORD Depositor:	A Symplectic
Date Deposited:	02 Mar 2023 12:49
Last Modified:	16 Mar 2023 11:45
DOI or ID number:	10.1093/braincomms/fcad041
URI:	https://researchonline.ljmu.ac.uk/id/eprint/19008

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