POLARIS: polygenic LD-adjusted risk score approach for set-based analysis of GWAS data

Baker, Emily, Schmidt, Karl Michael ORCID: https://orcid.org/0000-0002-0227-3024, Sims, Rebecca ORCID: https://orcid.org/0000-0002-3885-1199, O'Donovan, Michael C. ORCID: https://orcid.org/0000-0001-7073-2379, Williams, Julie ORCID: https://orcid.org/0000-0002-4069-0259, Holmans, Peter ORCID: https://orcid.org/0000-0003-0870-9412 and Escott-Price, Valentina ORCID: https://orcid.org/0000-0003-1784-5483 2018. POLARIS: polygenic LD-adjusted risk score approach for set-based analysis of GWAS data. Genetic Epidemiology 42 (4) , pp. 366-377. 10.1002/gepi.22117

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Abstract

Polygenic risk scores (PRSs) are a method to summarise the additive trait variance captured by a set of SNPs, and can increase the power of set-based analyses by leveraging public GWAS datasets. PRS aims to assess the genetic liability to some phenotype on the basis of polygenic risk for the same or di�erent phenotype estimated from independent data. We propose the application of PRSs as a set-based method with an additional component of adjustment for linkage disequilibrium (LD), with potential extension of the PRS approach to analyse biologically meaningful SNP sets. We call this method POLARIS: POlygenic Ld-Adjusted RIsk Score. POLARIS identi�es the LD-structure of SNPs using spectral decomposition of the SNP correlation matrix and replaces the individuals' SNP allele counts with LD-adjusted dosages. Using a raw genotype dataset together with SNP e�ect sizes from a second independent dataset, POLARIS can be used for set-based analysis. MAGMA is an alternative set-based approach employing principal component analysis to account for LD between markers in a raw genotype dataset. We used simulations, both with simple constructed and real LD-structure, to compare the power of these methods. POLARIS shows more power than MAGMA applied to the raw genotype dataset only, but less or comparable power to combined analysis of both datasets. POLARIS has the advantages that it produces a risk score per person per set using all available SNPs, and aims to increase power by leveraging the e�ect sizes from the discovery set in a self-contained test of association in the test dataset.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Advanced Research Computing @ Cardiff (ARCCA) Mathematics Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Additional Information:	With the GERAD Consortium
Publisher:	Wiley
ISSN:	0741-0395
Date of First Compliant Deposit:	2 February 2018
Date of Acceptance:	30 January 2018
Last Modified:	25 Oct 2024 01:05
URI:	https://orca.cardiff.ac.uk/id/eprint/108743

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