Trans-ancestry polygenic models for the prediction of LDL blood levels: An analysis of the UK Biobank and Taiwan Biobank
Journal
Frontiers in Genetics
Journal Volume
14
Start Page
1286561
ISSN
1664-8021
Date Issued
2023
Author(s)
Emadeldin Hassanin
Ko-Han Lee
Tzung-Chien Hsieh
Rana Aldisi
Yi-Lun Lee
Dheeraj Bobbili
Peter Krawitz
Patrick May
Carlo Maj
Abstract
Polygenic risk score (PRS) predictions often show bias toward the population of
available genome-wide association studies (GWASs), which is typically of
European ancestry. This study aimed 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 (EAS) population. In this study, we computed
ancestry-specific and multi-ancestry PRSs for LDL using data obtained from
the Global Lipid Genetics Consortium, while accounting for populationspecific linkage disequilibrium patterns using the PRS-CSx method in the
United Kingdom Biobank dataset (UKB, n = 423,596) and Taiwan Biobank
dataset (TWB, n = 68,978). Population-specific PRSs were able to predict LDL
levels better within the target population, whereas multi-ancestry PRSs were more
generalizable. In the TWB dataset, covariate-adjusted R2 values were 9.3% for
ancestry-specific PRS, 6.7% for multi-ancestry PRS, and 4.5% for Europeanspecific PRS. Similar trends (8.6%, 7.8%, and 6.2%) were observed in the smaller
EAS population of the UKB (n = 1,480). Consistent with R2 values, PRS stratification
in EAS regions (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 EAS-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 multi-ancestry 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 EAS population
revealed that integrating non-European genotyping data with a powerful
European-based GWAS can enhance the generalizability of LDL PRS.
Subjects
polygenic risk score
East Asia
Taiwan Biobank
United Kingdom Biobank
LDL cholesterol
Publisher
Frontiers Media SA
Type
journal article