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

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    Author
    Dadaev, T.
    Saunders, E.J.
    Newcombe, P.J.
    Date
    2018
    Journal
    Nature Communications
    Publisher
    Nature Publishing Group
    Type
    Article
    
    Metadata
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    See at
    https://dx.doi.org/10.1038/s41467-018-04109-8
    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. Copyright 2018 The Author(s).
    Keyword
    African Continental Ancestry Group
    Algorithms
    Bayes Theorem
    Chromosome Mapping
    European Continental Ancestry Group
    Genetic Predisposition to Disease
    Genome-Wide Association Study
    Humans
    Male
    Molecular Sequence Annotation
    prostate cancer
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    Identifier to cite or link to this item
    https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048420948&doi=10.1038%2fs41467-018-04109-8&partnerID=40&md5=575cc99635f00ccb89df4128325ecf20; http://hdl.handle.net/10713/9804
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41467-018-04109-8
    Scopus Count
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    UMB Open Access Articles 2018

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