# Transferability of polygenic risk scores for metabolic and cardiovascular traits in an underrepresented population

## TL;DR

This study evaluates how well genetic risk scores work in predicting metabolic and cardiovascular traits in Thai individuals, finding some promise but also limitations.

## Contribution

The study assesses the transferability of existing polygenic risk scores in an underrepresented Southeast Asian population.

## Key findings

- PRSs for type 2 diabetes and lipid traits showed strong predictive utility in Thai individuals.
- The best-performing CVD PRS showed an inverse association with disease risk.
- Reduced SNP retention and ancestry-related linkage disequilibrium differences affected PRS performance.

## Abstract

Polygenic risk scores (PRSs) are promising tools for genetic risk stratification, but their performance across ancestries remains uncertain. We evaluated 64 published PRSs for eight cardiometabolic traits in 4879 Thai individuals using imputed SNP-array data. Cross-sectional and six-year longitudinal analyses were performed to assess predictive performances. PRSs for type 2 diabetes (T2D) and lipid traits showed the strongest utility, with the best-performing LDL-C and TC scores explaining up to 9.8% and 7.8% of trait variance, respectively. The T2D PRS achieved an area under the curve (AUC) of 0.70 and consistently stratified disease risk over time. In contrast, PRSs for glycemic traits and cardiovascular disease (CVD) had weaker predictive value; notably, the best-performing CVD PRS showed an inverse association with disease risk. Reduced SNP retention and ancestry-related linkage disequilibrium differences contributed to variability. These findings highlight both the potential and current limitations of PRSs in underrepresented Southeast Asian populations.