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dc.contributor.authorDadaev, Tokhires_ES
dc.contributor.authorSaunders, Edward J.es_ES
dc.contributor.authorNewcombe, Paul J.es_ES
dc.contributor.authorAnokian, Ezequieles_ES
dc.contributor.authorLeongamornlert, Daniel A.es_ES
dc.contributor.authorBrook, Mark N.es_ES
dc.contributor.authorCieza-Borrella, Claraes_ES
dc.contributor.authorMijuskovic, Martinaes_ES
dc.contributor.authorWakerell, Sarahes_ES
dc.contributor.authorOlama, Ali Amin Ales_ES
dc.contributor.authorSchumacher, Fredrick R.es_ES
dc.contributor.authorBerndt, Sonja I.es_ES
dc.contributor.authorBenlloch, Saraes_ES
dc.contributor.authorAhmed, Mahbubles_ES
dc.contributor.authorGoh, Cheees_ES
dc.contributor.authorSheng, Xines_ES
dc.contributor.authorZhang, Zhuoes_ES
dc.contributor.authorLlorca Díaz, Francisco Javier es_ES
dc.contributor.authorDierssen Sotos, Trinidad es_ES
dc.contributor.authorGómez Acebo, Inés es_ES
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2019-03-06T15:11:57Z
dc.date.available2019-03-06T15:11:57Z
dc.date.issued2018es_ES
dc.identifier.issn2041-1723es_ES
dc.identifier.urihttp://hdl.handle.net/10902/15817
dc.description.abstractProstate 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.es_ES
dc.format.extent19 p.es_ES
dc.language.isoenges_ES
dc.publisherNature Publishing Groupes_ES
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceNat Commun. 2018 Jun 11;9(1):2256es_ES
dc.titleFine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variantses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://dx.doi.org/10.1038/s41467-018-04109-8es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1038/s41467-018-04109-8es_ES
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution 4.0 International