Cross-Ancestry Polygenic Prediction: Comparing Methods and Assessing Transferability Across Traits.

ABSTRACT: Accurate prediction of disease risk and other complex traits across different populations is essential for clinical and research purposes. However, genetic differences among ancestries, such as allelic frequencies and genetic architecture, can affect the performance of polygenic risk score (PGS) methods in cross-ancestry prediction. To address this issue, we conducted a formal test of seven polygenic prediction methods applicable across ancestries for five traits (BMI, standing height, LDL-, HDL- and total-cholesterol) from the UK Biobank dataset. We demonstrate that, GBLUP and PRS-CSx outperformed other methods for highly polygenic traits like height and BMI. In contrast, PRSice and PolyPred performed best for less polygenic traits like cholesterol, with PRS-CSx being comparable with larg

SUBMITTER: Momin MM 

PROVIDER: S-EPMC12820924 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature