@article{10902/15817,
year = {2018},
url = {http://hdl.handle.net/10902/15817},
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.},
publisher = {Nature Publishing Group},
publisher = {Nat Commun. 2018 Jun 11;9(1):2256},
title = {Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants},
author = {Dadaev, Tokhir and Saunders, Edward J. and Newcombe, Paul J. and Anokian, Ezequiel and Leongamornlert, Daniel A. and Brook, Mark N. and Cieza-Borrella, Clara and Mijuskovic, Martina and Wakerell, Sarah and Olama, Ali Amin Al and Schumacher, Fredrick R. and Berndt, Sonja I. and Benlloch, Sara and Ahmed, Mahbubl and Goh, Chee and Sheng, Xin and Zhang, Zhuo and Llorca Díaz, Francisco Javier and Dierssen Sotos, Trinidad and Gómez Acebo, Inés},
}