Improving polygenic prediction with genetically inferred ancestry.

Details

Serval ID
serval:BIB_DFFCB5547228
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Improving polygenic prediction with genetically inferred ancestry.
Journal
HGG advances
Author(s)
Naret O., Kutalik Z., Hodel F., Xu Z.M., Marques-Vidal P., Fellay J.
ISSN
2666-2477 (Electronic)
ISSN-L
2666-2477
Publication state
Published
Issued date
14/07/2022
Peer-reviewed
Oui
Volume
3
Number
3
Pages
100109
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Genome-wide association studies (GWASs) have demonstrated that most common diseases have a strong genetic component from many genetic variants each with a small effect size. GWAS summary statistics have allowed the construction of polygenic scores (PGSs) estimating part of the individual risk for common diseases. Here, we propose to improve PGS-based risk estimation by incorporating genetic ancestry derived from genome-wide genotyping data. Our method involves three cohorts: a base (or discovery) for association studies, a target for phenotype/risk prediction, and a map for ancestry mapping; successively, (1) it generates for each individual in the base and target cohorts a set of principal components based on the map cohort-called mapped PCs, (2) it associates in the base cohort the phenotype with the mapped-PCs, and (3) it uses the mapped PCs in the target cohort to generate a phenotypic predictor called the ancestry score. We evaluated the ancestry score by comparing a predictive model using a PGS with one combining a PGS and an ancestry score. First, we performed simulations and found that the ancestry score has a greater impact on traits that correlate with ancestry-specific variants. Second, we showed, using UK Biobank data, that the ancestry score improves genetic prediction for our nine phenotypes to very different degrees. Third, we performed simulations and found that the more heterogeneous the base and target cohorts, the more beneficial the ancestry score is. Finally, we validated our approach under realistic conditions with UK Biobank as the base cohort and Swiss individuals from the CoLaus|PsyCoLaus study as the target cohort.
Pubmed
Web of science
Open Access
Yes
Create date
20/05/2022 17:22
Last modification date
28/05/2022 6:35
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