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Type: Journal article
Title: Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
Author: Dadaev, T.
Saunders, E.
Newcombe, P.
Anokian, E.
Leongamornlert, D.
Brook, M.
Cieza-Borrella, C.
Mijuskovic, M.
Wakerell, S.
Olama, A.
Schumacher, F.
Berndt, S.
Benlloch, S.
Ahmed, M.
Goh, C.
Sheng, X.
Zhang, Z.
Muir, K.
Govindasami, K.
Lophatananon, A.
et al.
Citation: Nature Communications, 2018; 9(1)
Publisher: Nature Publishing Group
Issue Date: 2018
ISSN: 2041-1723
Statement of
Tokhir Dadaev, Edward J. Saunders, Paul J. Newcombe, Ezequiel Anokian ... Lisa M Butler … Wayne D Tilley ... et al.
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.
Keywords: Molecular Sequence Annotation
Rights: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit licenses/by/4.0/.
RMID: 0030090574
DOI: 10.1038/s41467-018-04109-8
Appears in Collections:Medicine publications

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