Polygenic prediction via Bayesian regression and continuous shrinkage priors

Ge, Tian; Chen, Chia‐Yen; Ni, Yang; Feng, Yen‐Chen Anne; Smoller, Jordan W.

doi:10.1038/s41467-019-09718-5

articleNature CommunicationsApr 16, 2019GOLD OA

Polygenic prediction via Bayesian regression and continuous shrinkage priors

TGTian Ge CCChia‐Yen Chen YNYang Ni YAYen‐Chen Anne Feng JWJordan W. Smoller

Broad Institute · Massachusetts General Hospital · +2 more institutions

PubMed

Indexed incrossrefdoajpubmed

Abstract

Polygenic risk scores (PRS) have shown promise in predicting human complex traits and diseases. Here, we present PRS-CS, a polygenic prediction method that infers posterior effect sizes of single nucleotide polymorphisms (SNPs) using genome-wide association summary statistics and an external linkage disequilibrium (LD) reference panel. PRS-CS utilizes a high-dimensional Bayesian regression framework, and is distinct from previous work by placing a continuous shrinkage (CS) prior on SNP effect sizes, which is robust to varying genetic architectures, provides substantial computational advantages, and enables multivariate modeling of local LD patterns. Simulation studies using data from the UK Biobank show that…

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Keywords

Biobank
Linkage disequilibrium
Computer science
Bayesian probability
Regression
Prior probability
Single-nucleotide polymorphism
Multivariate statistics

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