美国博德研究所Tian Ge等研究人员合作改进对不同祖先人群的多基因预测。相关论文于2022年5月5日在线发表在《自然—遗传学》杂志上。
Author: Ruan, Yunfeng, Lin, Yen-Feng, Feng, Yen-Chen Anne, Chen, Chia-Yen, Lam, Max, Guo, Zhenglin, He, Lin, Sawa, Akira, Martin, Alicia R., Qin, Shengying, Huang, Hailiang, Ge, Tian
Issue&Volume: 2022-05-05
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.
DOI: 10.1038/s41588-022-01054-7
Source: https://www.nature.com/articles/s41588-022-01054-7
Nature Genetics:《自然—遗传学》,创刊于1992年。隶属于施普林格·自然出版集团,最新IF:41.307
官方网址:https://www.nature.com/ng/
投稿链接:https://mts-ng.nature.com/cgi-bin/main.plex
本期文章:《自然—遗传学》:Online/在线发表