XPXP : Improving polygenic prediction by cross-population and cross-phenotype analysis

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

10 Scopus Citations
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Author(s)

  • Jiashun Xiao
  • Xianghong Hu
  • Xiang Wan
  • Gang Chen
  • Can Yang

Detail(s)

Original languageEnglish
Pages (from-to)1947-1955
Journal / PublicationBioinformatics
Volume38
Issue number7
Online published18 Jan 2022
Publication statusPublished - 1 Apr 2022
Externally publishedYes

Abstract

Motivation: As increasing sample sizes from genome-wide association studies (GWASs), polygenic risk scores (PRSs) have shown great potential in personalized medicine with disease risk prediction, prevention and treatment. However, the PRS constructed using European samples becomes less accurate when it is applied to individuals from non-European populations. It is an urgent task to improve the accuracy of PRSs in under-represented populations, such as African populations and East Asian populations. 
Results: In this article, we propose a cross-population and cross-phenotype (XPXP) method for construction of PRSs in under-represented populations. XPXP can construct accurate PRSs by leveraging biobank-scale datasets in European populations and multiple GWASs of genetically correlated phenotypes. XPXP also allows to incorporate population-specific and phenotype-specific effects, and thus further improves the accuracy of PRS. Through comprehensive simulation studies and real data analysis, we demonstrated that our XPXP outperformed existing PRS approaches. We showed that the height PRSs constructed by XPXP achieved 9% and 18% improvement over the runner-up method in terms of predicted R2 in East Asian and African populations, respectively. We also showed that XPXP substantially improved the stratification ability in identifying individuals at high genetic risk of type 2 diabetes.

Citation Format(s)

XPXP: Improving polygenic prediction by cross-population and cross-phenotype analysis. / Xiao, Jiashun; Cai, Mingxuan; Hu, Xianghong et al.
In: Bioinformatics, Vol. 38, No. 7, 01.04.2022, p. 1947-1955.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review