Polygenic risk scores adaptation for Height in a Vietnamese population

Abstract

Genome-wide association studies (GWAS) with millions of genetic markers have proven to be useful for precision medicine applications as means of advanced calculation to provide a Polygenic risk score (PRS). However, the potential for interpretation and application of existing PRS models has limited transferability across ancestry groups due to the historical bias of GWAS toward European ancestry. Here we propose an adapted workflow to fine-tune the baseline PRS model to the dataset of target ancestry. We use the dataset of Vietnamese whole genomes from the 1KVG project and build a PRS model of height prediction for the Vietnamese population. Our best-fit model achieved an increase in R2 of 0.152 (according to 29.8%) compared to the null model, which only consists of the metadata.