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 4

SUBMITTER: Dadaev T 

PROVIDER: S-EPMC5995836 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature