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Nat Genet DOI:10.1038/s41588-022-01054-7

Improving polygenic prediction in ancestrally diverse populations.

Publication TypeJournal Article
Year of Publication2022
AuthorsRuan, Y, Lin, Y-F, Feng, Y-CAnne, Chen, C-Y, Lam, M, Guo, Z, He, L, Sawa, A, Martin, AR, Qin, S, Huang, H, Ge, T
Corporate AuthorsStanley Global Asia Initiatives
JournalNat Genet
Date Published2022 May 05
ISSN1546-1718
Abstract

Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genome-wide association studies (GWAS) have been conducted predominantly in individuals of European descent, the limited transferability of PRS reduces their clinical value in non-European populations, and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although most remain underpowered. Here, we present a new PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage (CS) prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures, cross-population genetic overlaps and discovery GWAS sample sizes in simulations, and improves the prediction of quantitative traits and schizophrenia risk in non-European populations.

DOI10.1038/s41588-022-01054-7
Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/35513724?dopt=Abstract

Alternate JournalNat Genet
PubMed ID35513724
Grant ListU01MH109539 / / U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) /
R00MH117229 / / U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) /
K01DK114379 / / U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes & Digestive & Kidney Diseases) /
2017SHZDZX01 / / Science and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission) /
2017SHZDZX01 / / Science and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission) /
R00AG054573 / / U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) /