Imputation disparities driven by recent selection and their impact on disease risk estimation in East and Southeast Asian populations

Abstract

Accurate genotype imputation is essential for large-scale genetic studies and precision medicine. While East Asian (EAS)-specific reference panels like ChinaMAP and CHN100k have been developed, most studies still rely on multi-ancestry panels like TOPMed due to the large sample size. However, their performance in underrepresented groups like Southeast Asians remains unclear. Using high-coverage whole-genome sequencing and SNP-array data from 8,316 Chinese and Thai individuals, we systematically evaluate six state-of-the-art reference panels for genotype imputation. Our results show that EAS-specific panels outperformed multi-ancestry panels for East and Southeast Asian populations. For example, ChinaMAP achieves a mean heterozygosity concordance rate above 0.90 without R² filtering, whereas TOPMed requires an R² threshold of 0.60-0.70 to achieve comparable results. Notably, we find that recent positive selection drives regional disparities in imputation accuracy, as illustrated by the olfactory receptor gene cluster. More importantly, our results indicate that the choice of reference panel and R² thresholds have a significant impact on polygenic risk score estimation for disease prediction. These findings provide valuable guidelines for improving genotype imputation in East and Southeast Asian populations and underscore the need for ancestrally diverse reference panels to support globally equitable genomic research.