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

Nat Commun. 2020 Jul 31;11(1):3865. doi: 10.1038/s41467-020-17719-y.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Africa / epidemiology
  • Aged
  • Alleles
  • Asia / epidemiology
  • Asthma / diagnosis
  • Asthma / epidemiology
  • Asthma / ethnology
  • Asthma / genetics*
  • Body Mass Index
  • Cholesterol / blood
  • Computer Simulation
  • Diabetes Mellitus, Type 2 / diagnosis
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / ethnology
  • Diabetes Mellitus, Type 2 / genetics*
  • Europe / epidemiology
  • Female
  • Gene Frequency
  • Genome-Wide Association Study
  • Humans
  • Hypertension / diagnosis
  • Hypertension / epidemiology
  • Hypertension / ethnology
  • Hypertension / genetics*
  • Linkage Disequilibrium
  • Male
  • Middle Aged
  • Models, Genetic*
  • Multifactorial Inheritance*
  • Polymorphism, Single Nucleotide*
  • Prognosis
  • Quantitative Trait, Heritable
  • Risk

Substances

  • Cholesterol