AUTHOR=Hassanin Emadeldin , Lee Ko-Han , Hsieh Tzung-Chien , Aldisi Rana , Lee Yi-Lun , Bobbili Dheeraj , Krawitz Peter , May Patrick , Chen Chien-Yu , Maj Carlo TITLE=Trans-ancestry polygenic models for the prediction of LDL blood levels: an analysis of the United Kingdom Biobank and Taiwan Biobank JOURNAL=Frontiers in Genetics VOLUME=Volume 14 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1286561 DOI=10.3389/fgene.2023.1286561 ISSN=1664-8021 ABSTRACT=Polygenic risk scores (PRS) predictions often show bias toward the population of available genome-wide association studies, which is typically of European ancestry. This study aims to assess the performance differences of ancestry-specific PRS and test the implementation of multi-ancestry PRS to enhance the generalizability of low-density lipoprotein (LDL) cholesterol predictions in the East Asian population. In this study, we computed ancestry-specific and multi-ancestry PRS for LDL using data from the global lipid consortium while accounting for population-specific linkage disequilibrium patterns using PRS-CSx method in the UK Biobank dataset (n=423,596) and Taiwan Biobank dataset (TWB, n=68,978). Population-specific PRS better predicted LDL levels within the target population but multi-ancestry PRS were more generalizable. In the TWB dataset, covariate-adjusted R 2 values were 9.3% for ancestryspecific PRS, 6.7% for multi-ancestry PRS, and 4.5% for European-specific PRS. Similar trends (8.6%, 7.8%, 6.2%) were observed in the smaller East Asian population of the UK Biobank (n=1,480). Consistent with the R 2 values, PRS stratification in East Asians (TWB) effectively captured a heterogenous variability in LDL blood cholesterol levels across PRS strata. The mean difference in LDL levels between the lowest and highest East Asian-specific PRS (EAS_PRS) deciles was 0.82, compared to 0.59 for European-specific PRS (EUR_PRS) and 0.76 for multi-ancestry PRS. Notably, the mean LDL values in the top decile of multiancestry PRS were comparable to those of EAS_PRS (3.543 vs. 3.541, P=0.86). Our analysis of the PRS prediction model for LDL cholesterol further supports the issue of PRS generalizability across populations. Our targeted analysis of the East Asian (EAS) population revealed that integrating non-European genotyping data alongside powerful European-based GWAS can enhance the generalizability of LDL PRS.