Polygenic prediction via Bayesian regression and continuous shrinkage priors.

Nat Commun 2019 04 16;10(1):1776. Epub 2019 Apr 16.

Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.

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 PRS-CS outperforms existing methods across a wide range of genetic architectures, especially when the training sample size is large. We apply PRS-CS to predict six common complex diseases and six quantitative traits in the Partners HealthCare Biobank, and further demonstrate the improvement of PRS-CS in prediction accuracy over alternative methods.

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-019-09718-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467998PMC
April 2019
2 Reads

Publication Analysis

Top Keywords

continuous shrinkage
8
genetic architectures
8
polygenic prediction
8
bayesian regression
8
prs-cs
5
substantial computational
4
computational advantages
4
architectures substantial
4
alternative methods
4
robust varying
4
varying genetic
4
advantages enables
4
enables multivariate
4
patterns simulation
4
simulation studies
4
local patterns
4
modeling local
4
multivariate modeling
4
sizes robust
4
snp sizes
4

References

(Supplied by CrossRef)

N Chatterjee et al.
Nat. Rev. Genet. 2016

A Khera et al.
Nat. Genet. 2018

International Schizophrenia Consortium. et al.
Nature 2009

B Vilhjálmsson et al.
Am. J. Hum. Genet. 2015

Y Zhang et al.
Nat. Genet. 2018

C Hoggart et al.
PLoS Genet. 2008

G Los Campos De et al.
Genetics 2009

R Makowsky et al.
PLoS Genet. 2011

T Meuwissen et al.
Genetics 2001

S Xu et al.
Genetics 2003

Similar Publications