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.
Original language | English |
---|---|
Article number | 2256 |
Journal | Nature Communications |
Volume | 9 |
Issue number | 1 |
ISSN | 2041-1723 |
DOIs | |
Publication status | Published - 2018 |
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- 10.1038/s41467-018-04109-8Licence: CC BY
- Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variantsFinal published version, 1.69 MBLicence: CC BY
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In: Nature Communications, Vol. 9, No. 1, 2256, 2018.
Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
AU - Dadaev, Tokhir
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AU - Ranu, Hardeep
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AU - Klarskov, Peter
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AU - Silva, Maria P.
AU - De Langhe, Sofie
AU - Thierens, Hubert
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AU - Mitkova, Atanaska
AU - Vlahova, Aleksandrina
AU - Dikov, Tihomir
AU - Christova, Svetlana
AU - Carracedo, Angel
AU - Bangma, Christopher
AU - Schroder, F. H.
AU - Cenee, Sylvie
AU - Tretarre, Brigitte
AU - Rebillard, Xavier
AU - Mulot, Claire
AU - Sanchez, Marie
AU - Adolfsson, Jan
AU - Stattin, Par
AU - Johansson, Jan Erik
AU - Cavalli-Bjoerkman, Carin
AU - Karlsson, Ami
AU - Broms, Michael
AU - Wu, Huihai
AU - Tillmans, Lori
AU - Riska, Shaun
AU - Freedman, Matthew
AU - Wiklund, Fredrik
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AU - Henderson, Brian E.
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AU - Haiman, Christopher A.
AU - Eeles, Rosalind A.
AU - Conti, David V.
AU - Kote-Jarai, Zsofia
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
U2 - 10.1038/s41467-018-04109-8
DO - 10.1038/s41467-018-04109-8
M3 - Journal article
C2 - 29892050
AN - SCOPUS:85048420948
SN - 2041-1723
VL - 9
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 2256
ER -