Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.
Dadaev T., Saunders EJ., Newcombe PJ., Anokian E., Leongamornlert DA., Brook MN., Cieza-Borrella C., Mijuskovic M., Wakerell S., Olama AAA., Schumacher FR., Berndt SI., Benlloch S., Ahmed M., Goh C., Sheng X., Zhang Z., Muir K., Govindasami K., Lophatananon A., Stevens VL., Gapstur SM., Carter BD., Tangen CM., Goodman P., Thompson IM., Batra J., Chambers S., Moya L., Clements J., Horvath L., Tilley W., Risbridger G., Gronberg H., Aly M., Nordström T., Pharoah P., Pashayan N., Schleutker J., Tammela TLJ., Sipeky C., Auvinen A., Albanes D., Weinstein S., Wolk A., Hakansson N., West C., Dunning AM., Burnet N., Mucci L., Giovannucci E., Andriole G., Cussenot O., Cancel-Tassin G., Koutros S., Freeman LEB., Sorensen KD., Orntoft TF., Borre M., Maehle L., Grindedal EM., Neal DE., Donovan JL., Hamdy FC., Martin RM., Travis RC., Key TJ., Hamilton RJ., Fleshner NE., Finelli A., Ingles SA., Stern MC., Rosenstein B., Kerns S., Ostrer H., Lu Y-J., Zhang H-W., Feng N., Mao X., Guo X., Wang G., Sun Z., Giles GG., Southey MC., MacInnis RJ., FitzGerald LM., Kibel AS., Drake BF., Vega A., Gómez-Caamaño A., Fachal L., Szulkin R., Eklund M., Kogevinas M., Llorca J., Castaño-Vinyals G., Penney KL., Stampfer M., Park JY., Sellers TA., Lin H-Y., Stanford JL., Cybulski C., Wokolorczyk D., Lubinski J., Ostrander EA., Geybels MS., Nordestgaard BG., Nielsen SF., Weisher M., Bisbjerg R., Røder MA., Iversen P., Brenner H., Cuk K., Holleczek B., Maier C., Luedeke M., Schnoeller T., Kim J., Logothetis CJ., John EM., Teixeira MR., Paulo P., Cardoso M., Neuhausen SL., Steele L., Ding YC., De Ruyck K., De Meerleer G., Ost P., Razack A., Lim J., Teo S-H., Lin DW., Newcomb LF., Lessel D., Gamulin M., Kulis T., Kaneva R., Usmani N., Slavov C., Mitev V., Parliament M., Singhal S., Claessens F., Joniau S., Van den Broeck T., Larkin S., Townsend PA., Aukim-Hastie C., Gago-Dominguez M., Castelao JE., Martinez ME., Roobol MJ., Jenster G., van Schaik RHN., Menegaux F., Truong T., Koudou YA., Xu J., Khaw K-T., Cannon-Albright L., Pandha H., Michael A., Kierzek A., Thibodeau SN., McDonnell SK., Schaid DJ., Lindstrom S., Turman C., Ma J., Hunter DJ., Riboli E., Siddiq A., Canzian F., Kolonel LN., Le Marchand L., Hoover RN., Machiela MJ., Kraft P., PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium None., Freedman M., Wiklund F., Chanock S., Henderson BE., Easton DF., Haiman CA., Eeles RA., Conti DV., Kote-Jarai Z.
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.