Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

Abstract:

:Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

journal_name

Nat Commun

journal_title

Nature communications

authors

Dadaev T,Saunders EJ,Newcombe PJ,Anokian E,Leongamornlert DA,Brook MN,Cieza-Borrella C,Mijuskovic M,Wakerell S,Olama AAA,Schumacher FR,Berndt SI,Benlloch S,Ahmed M,Goh C,Sheng X,Zhang Z,Muir K,Govindasami K,Lophatan

doi

10.1038/s41467-018-04109-8

subject

Has Abstract

pub_date

2018-06-11 00:00:00

pages

2256

issue

1

issn

2041-1723

pii

10.1038/s41467-018-04109-8

journal_volume

9

pub_type

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