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


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.

SUBMITTER: Dadaev T 

PROVIDER: S-EPMC5995836 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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

Dadaev Tokhir T   Saunders Edward J EJ   Newcombe Paul J PJ   Anokian Ezequiel E   Leongamornlert Daniel A DA   Brook Mark N MN   Cieza-Borrella Clara C   Mijuskovic Martina M   Wakerell Sarah S   Olama Ali Amin Al AAA   Schumacher Fredrick R FR   Berndt Sonja I SI   Benlloch Sara S   Ahmed Mahbubl M   Goh Chee C   Sheng Xin X   Zhang Zhuo Z   Muir Kenneth K   Govindasami Koveela K   Lophatananon Artitaya A   Stevens Victoria L VL   Gapstur Susan M SM   Carter Brian D BD   Tangen Catherine M CM   Goodman Phyllis P   Thompson Ian M IM   Batra Jyotsna J   Chambers Suzanne S   Moya Leire L   Clements Judith J   Horvath Lisa L   Tilley Wayne W   Risbridger Gail G   Gronberg Henrik H   Aly Markus M   Nordström Tobias T   Pharoah Paul P   Pashayan Nora N   Schleutker Johanna J   Tammela Teuvo L J TLJ   Sipeky Csilla C   Auvinen Anssi A   Albanes Demetrius D   Weinstein Stephanie S   Wolk Alicja A   Hakansson Niclas N   West Catharine C   Dunning Alison M AM   Burnet Neil N   Mucci Lorelei L   Giovannucci Edward E   Andriole Gerald G   Cussenot Olivier O   Cancel-Tassin Géraldine G   Koutros Stella S   Freeman Laura E Beane LEB   Sorensen Karina Dalsgaard KD   Orntoft Torben Falck TF   Borre Michael M   Maehle Lovise L   Grindedal Eli Marie EM   Neal David E DE   Donovan Jenny L JL   Hamdy Freddie C FC   Martin Richard M RM   Travis Ruth C RC   Key Tim J TJ   Hamilton Robert J RJ   Fleshner Neil E NE   Finelli Antonio A   Ingles Sue Ann SA   Stern Mariana C MC   Rosenstein Barry B   Kerns Sarah S   Ostrer Harry H   Lu Yong-Jie YJ   Zhang Hong-Wei HW   Feng Ninghan N   Mao Xueying X   Guo Xin X   Wang Guomin G   Sun Zan Z   Giles Graham G GG   Southey Melissa C MC   MacInnis Robert J RJ   FitzGerald Liesel M LM   Kibel Adam S AS   Drake Bettina F BF   Vega Ana A   Gómez-Caamaño Antonio A   Fachal Laura L   Szulkin Robert R   Eklund Martin M   Kogevinas Manolis M   Llorca Javier J   Castaño-Vinyals Gemma G   Penney Kathryn L KL   Stampfer Meir M   Park Jong Y JY   Sellers Thomas A TA   Lin Hui-Yi HY   Stanford Janet L JL   Cybulski Cezary C   Wokolorczyk Dominika D   Lubinski Jan J   Ostrander Elaine A EA   Geybels Milan S MS   Nordestgaard Børge G BG   Nielsen Sune F SF   Weisher Maren M   Bisbjerg Rasmus R   Røder Martin Andreas MA   Iversen Peter P   Brenner Hermann H   Cuk Katarina K   Holleczek Bernd B   Maier Christiane C   Luedeke Manuel M   Schnoeller Thomas T   Kim Jeri J   Logothetis Christopher J CJ   John Esther M EM   Teixeira Manuel R MR   Paulo Paula P   Cardoso Marta M   Neuhausen Susan L SL   Steele Linda L   Ding Yuan Chun YC   De Ruyck Kim K   De Meerleer Gert G   Ost Piet P   Razack Azad A   Lim Jasmine J   Teo Soo-Hwang SH   Lin Daniel W DW   Newcomb Lisa F LF   Lessel Davor D   Gamulin Marija M   Kulis Tomislav T   Kaneva Radka R   Usmani Nawaid N   Slavov Chavdar C   Mitev Vanio V   Parliament Matthew M   Singhal Sandeep S   Claessens Frank F   Joniau Steven S   Van den Broeck Thomas T   Larkin Samantha S   Townsend Paul A PA   Aukim-Hastie Claire C   Gago-Dominguez Manuela M   Castelao Jose Esteban JE   Martinez Maria Elena ME   Roobol Monique J MJ   Jenster Guido G   van Schaik Ron H N RHN   Menegaux Florence F   Truong Thérèse T   Koudou Yves Akoli YA   Xu Jianfeng J   Khaw Kay-Tee KT   Cannon-Albright Lisa L   Pandha Hardev H   Michael Agnieszka A   Kierzek Andrzej A   Thibodeau Stephen N SN   McDonnell Shannon K SK   Schaid Daniel J DJ   Lindstrom Sara S   Turman Constance C   Ma Jing J   Hunter David J DJ   Riboli Elio E   Siddiq Afshan A   Canzian Federico F   Kolonel Laurence N LN   Le Marchand Loic L   Hoover Robert N RN   Machiela Mitchell J MJ   Kraft Peter P   Freedman Matthew M   Wiklund Fredrik F   Chanock Stephen S   Henderson Brian E BE   Easton Douglas F DF   Haiman Christopher A CA   Eeles Rosalind A RA   Conti David V DV   Kote-Jarai Zsofia Z  

Nature communications 20180611 1


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 t  ...[more]

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