Unknown

Dataset Information

0

Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations.


ABSTRACT: Polygenic scores (PGS) have been widely used to predict disease risk using variants identified from genome-wide association studies (GWAS). To date, most GWAS have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European ancestry populations. Here, we derive a theoretical model of the relative accuracy (RA) of PGS across ancestries. We show through extensive simulations that the RA of PGS based on genome-wide significant SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of causal SNP effects and heritability. We find that LD and MAF differences between ancestries can explain between 70 and 80% of the loss of RA of European-based PGS in African ancestry for traits like body mass index and type 2 diabetes. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWAS are mostly shared across continents.

SUBMITTER: Wang Y 

PROVIDER: S-EPMC7395791 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations.

Wang Ying Y   Guo Jing J   Ni Guiyan G   Yang Jian J   Visscher Peter M PM   Yengo Loic L  

Nature communications 20200731 1


Polygenic scores (PGS) have been widely used to predict disease risk using variants identified from genome-wide association studies (GWAS). To date, most GWAS have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European ancestry populations. Here, we derive a theoretical model of the relative accuracy (RA) of PGS across ancestries. We show through extensive simulations that the RA of PGS based on genome-wide significant SNPs can be predicted a  ...[more]

Similar Datasets

| S-EPMC7067566 | biostudies-literature
| S-EPMC7041489 | biostudies-literature
| S-EPMC8445431 | biostudies-literature
| S-EPMC10802635 | biostudies-literature
| S-EPMC3605113 | biostudies-literature
| S-EPMC7642950 | biostudies-literature
| S-EPMC10284707 | biostudies-literature
| S-EPMC4734143 | biostudies-literature
| S-EPMC4596916 | biostudies-literature
| S-EPMC8418423 | biostudies-literature