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

• Verfasst von: Dadaev, Tokhir [VerfasserIn]
• Verfasst von: Brenner, Hermann [VerfasserIn]
• Verfasst von: Cuk, Katarina [VerfasserIn]
• Titel: Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
• Verf.angabe: Tokhir Dadaev, Hermann Brenner, Katarina Cuk [und 188 Weitere]
• Jahr: 2018
• Umfang: 19 S.
• Teil: volume:9
• Teil: year:2018
• Teil: extent:19
• Fussnoten: Published 11 June 2018 ; Gesehen am 27.06.2018
• Titel Quelle: Enthalten in: Nature Communications
• Ort Quelle: [London] : Nature Publishing Group UK, 2010
• Jahr Quelle: 2018
• Band/Heft Quelle: 9(2018) Artikel-Nummer 2256, 19 Seiten
• ISSN Quelle: 2041-1723
• DOI: doi:10.1038/s41467-018-04109-8
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1576906027

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., Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.