| Title: | Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations |
| Journal: | Nature Communications |
| Published: | 31 Jul 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32737319/ |
| DOI: | https://doi.org/10.1038/s41467-020-17719-y |
| URL: | https://www.nature.com/articles/s41467-020-17719-y.pdf |
Publication 3673
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
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.6 Authors
- Ying Wang
- Jing Guo
- Guiyan Ni
- Jian Yang
- Peter M. Visscher
- Loic Yengo
1 Application
| Application ID | Title |
|---|---|
| 12505 | Dissecting the genetic basis of relationships between early-life and later-life events |
Enabling scientific discoveries that improve human health