Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Ali Amin Al Olama, Tokhir Dadaev, Dennis J Hazelett, Qiuyan Li, Daniel Leongamornlert, Edward J Saunders, Sarah Stephens, Clara Cieza-Borrella, Ian Whitmore, Sara Benlloch Garcia, Graham G Giles, Melissa C Southey, Liesel Fitzgerald, Henrik Gronberg, Fredrik Wiklund, Markus Aly, Brian E Henderson, Fredrick Schumacher, Christopher A Haiman, Johanna SchleutkerTiina Wahlfors, Teuvo L Tammela, Børge G Nordestgaard, Tim J Key, Ruth C Travis, David E Neal, Jenny L Donovan, Freddie C Hamdy, Paul Pharoah, Nora Pashayan, Kay-Tee Khaw, Janet L Stanford, Stephen N Thibodeau, Shannon K Mcdonnell, Daniel J Schaid, Christiane Maier, Walther Vogel, Manuel Luedeke, Kathleen Herkommer, Adam S Kibel, Cezary Cybulski, Dominika Wokołorczyk, Wojciech Kluzniak, Lisa Cannon-Albright, Hermann Brenner, Katja Butterbach, Volker Arndt, Jong Y Park, Thomas Sellers, Hui-Yi Lin, PRACTICAL Consortium

48 Citations (Scopus)

Abstract

Genome-wide association studies (GWAS) have identified numerouscommon prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variationwas observed at 39 regions; 35 of which are nowdescribed by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-AsianGWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci nowexplain ~38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reportedGWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

Original languageEnglish
JournalHuman Molecular Genetics
Volume24
Issue number19
Pages (from-to)5589-602
Number of pages14
ISSN0964-6906
DOIs
Publication statusPublished - 1 Oct 2015

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