Title |
Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans
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Published in |
Human Molecular Genetics, May 2015
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DOI | 10.1093/hmg/ddv203 |
Pubmed ID | |
Authors |
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 Schleutker, Tiina 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, Chavdar Slavov, Radka Kaneva, Vanio Mitev, Jyotsna Batra, Judith A. Clements, Amanda Spurdle, Manuel R. Teixeira, Paula Paulo, Sofia Maia, Hardev Pandha, Agnieszka Michael, Andrzej Kierzek, Koveela Govindasami, Michelle Guy, Artitaya Lophatonanon, Kenneth Muir, Ana Viñuela, Andrew A. Brown, Mathew Freedman, David V. Conti, Douglas Easton, Gerhard A. Coetzee, Rosalind A. Eeles, Zsofia Kote-Jarai, Douglas F. Easton, Paul Pharoah, Kyriaki Michailidou, Manjeet K. Bolla, Qin Wang, Andrew Berchuck, Rosalind A. Eeles, Douglas F. Easton, Zsofia Kote-Jarai, Ali Amin Al Olama, Sara Benlloch, Georgia Chenevix-Trench, Antonis Antoniou, Lesley McGuffog, Fergus Couch, Ken Offit, Joe Dennis, Alison M. Dunning, Andrew Lee, Ed Dicks, Craig Luccarini, Javier Benitez, Anna Gonzalez-Neira, Jacques Simard, Daniel C. Tessier, Francois Bacot, Daniel Vincent, Sylvie LaBoissière, Frederic Robidoux, Stig E. Bojesen, Sune F. Nielsen, Borge G. Nordestgaard, Julie M. Cunningham, Sharon A. Windebank, Christopher A. Hilker, Jeffrey Meyer |
Abstract |
Genome-wide association studies (GWAS) have identified numerous common 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 variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, whilst the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed 2 association signals in Europeans that had been previously reported only in East-Asian GWAS.Based on statistical evidence and 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 now explain approximately 38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Montenegro | 1 | 17% |
United States | 1 | 17% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 67% |
Scientists | 2 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 2% |
United States | 2 | 1% |
Unknown | 180 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 24 | 13% |
Researcher | 19 | 10% |
Student > Master | 16 | 9% |
Professor | 15 | 8% |
Student > Doctoral Student | 14 | 8% |
Other | 41 | 22% |
Unknown | 56 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 51 | 28% |
Biochemistry, Genetics and Molecular Biology | 24 | 13% |
Agricultural and Biological Sciences | 22 | 12% |
Computer Science | 7 | 4% |
Business, Management and Accounting | 3 | 2% |
Other | 16 | 9% |
Unknown | 62 | 34% |