Modeling linkage disequilibrium increases accuracy of polygenic risk scores

, Schizophrenia Working Group of the Psychiatric Genomics Consorti (2015) Modeling linkage disequilibrium increases accuracy of polygenic risk scores. American Journal of Human Genetics, 97 (4). pp. 576-592. ISSN 0002-9297

[img]
Preview
PDF (final)
final.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (627kB)

Abstract

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Item Type:
Journal Article
Journal or Publication Title:
American Journal of Human Genetics
Additional Information:
This is the author’s version of a work that was accepted for publication in American Journal of Human Genetics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in American Journal of Human Genetics, 97, 4, 2015 DOI: 10.1016/j.ajhg.2015.09.001
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700/2716
Subjects:
ID Code:
80072
Deposited By:
Deposited On:
23 Jun 2016 12:48
Refereed?:
Yes
Published?:
Published
Last Modified:
19 Jun 2021 03:34