Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Schumacher, Fredrick; Olama, Ali Amin Al; Berndt, Sonja I.; Benlloch, Sara; Ahmed, Mahbubl; Saunders, Ed; Dadaev, Tokhir; Leongamornlert, Daniel; Anokian, Ezequiel; Cieza-Borrella, Clara; Goh, Chee; Brook, Mark N.; Sheng, Xin; Fachal, Laura; Dennis, Joe; Tyrer, Jonathan P.; Muir, Kenneth; Lophatananon, Artitaya; Stevens, Victoria L.; Gapstur, Susan M.; Carter, Brian D.; Tangen, Catherine M.; Goodman, Phyllis J.; Thompson, Ian M.; Batra, Jyotsna; Chambers, Suzanne K.; Moya, Leire; Clements, Judith A.; Horvath, Lisa G.; Tilley, Wayne D.; Risbridger, Gail P.; Grönberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul D.P.; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L.J.; Sipeky, Csilla; Auvinen, Anssi; Albanês, Demetrius; Weinstein, Stephanie J.; Wolk, Alicja; Håkansson, Niclas; West, Catharine M L; Dunning, Alison M.; Burnet, N.G.; Mucci, Lorelei A.; Giovannucci, Edward; Andriole, Gerald L.; Cussenot, Olivier; Cancel‐Tassin, Géraldine; Koutros, Stella; Freeman, Laura E. Beane; Sørensen, Karina Dalsgaard; Ørntoft, Torben F.; Borre, Michael; Mæhle, Lovise; Grindedal, Eli Marie; Neal, David E.; Donovan, Jenny; Hamdy, Freddie C.; Martin, Richard M; Travis, Ruth C.; Key, Tim; Hamilton, Robert J.; Fleshner, Neil; Finelli, Antonio; Ingles, Sue A.; Stern, Mariana C.; Rosenstein, Barry S.; Kerns, Sarah L.; Ostrer, Harry; Lu, Yong; Zhang, Hong Wei; Feng, Na; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G.; Southey, Melissa C.; MacInnis, Robert J.; FitzGerald, Liesel M.; Kibel, Adam S.; Drake, Bettina F.; Vega, Ana; Gómez-Caamaño, Antonio; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño‐Vinyals, Gemma; Penney, Kathryn L.; Stampfer, Meir J.; Park, Jong Y.; Sellers, Thomas A.; Lin, Hui‐Yi; Stanford, Janet L.; Cybulski, Cezary; Wokołorczyk, Dominika; Lubiński, Jan; Ostrander, Elaine A.; Geybels, Milan S.; Nordestgaard, Børge G.; Nielsen, Sune F.; Weischer, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Ćuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J.; John, Esther M.; Teixeira, Manuel R.; Paulo, Paula; Neuhausen, Susan L.; Steele, Linda; Ding, Yuan Chun; Ruyck, Kim De; Meerleer, Gert De; Ost, Piet; Razack, Azad Hassan Abdul; Lim, Jasmine; Teo, Soo‐Hwang; Lin, Daniel W.; Newcomb, Lisa F.; Lessel, Davor; Gamulin, Marija; Kuliš, Tomislav; Kaneva, Radka; Usmani, Nawaid; Singhal, Sandeep K.; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Claessens, Frank; Joniau, Steven; Broeck, Thomas Van den; Larkin, Samantha; Townsend, Paul A.; Aukim-Hastie, Claire; Gago‐Dominguez, Manuela; Castelao, Jose E.; Martı́nez, Marı́a Elena; Roobol, Monique J.; Jenster, Guido; Schaik, Ron H.N. van; Ménégaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Thibodeau, Stephen N.; McDonnell, Shannon K.; Schaid, Daniel J.; Lindström, Sara; Turman, Constance; Ma, Jing; Hunter, David J.; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N.; Marchand, Loı̈c Le; Hoover, Robert N.; Machiela, Mitchell J.; Cui, Zuxi; Kraft, Peter; Amos, Christopher I.; Conti, David V.; Easton, Douglas F.; Wiklund, Fredrik; Chanock, Stephen J.; Henderson, Brian E.; Kóte-Jarai, Zsofia; Haiman, Christopher A.; Eeles, Rosalind

doi:10.1038/s41588-018-0142-8

Cited by 769 publications

(760 citation statements)

References 63 publications

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“…The risk region at 8q24 harbors multiple independent risk variants and is consistently recognized as the most significant PrCa risk region across ethnic populations. In our Latino men, it was associated with a 1.29-fold (95%CI: 1.19, 1.39) increased risk, which is similar to that reported in the largest European PrCa GWAS (OR = 1.23, 1.21, 1.25), 28 while larger than that reported in the AA PrCa GWAS (OR = 1.12, 95%CI: 1.07, 1.16). At 10q11.22, the risk variant rs10993994 has been consistently associated with PrCa risk across populations, [32][33][34] and is likely to be the putative causal variant within the region.…”

Section: Discussionsupporting

confidence: 85%

“…28,30 As found in previous studies in men of African ancestry, 16 directional consistency was also observed for the majority (>80%) of risk variants in Latinos, among which~30% were nominally statistically significant, suggesting that most of the known genetic susceptibility loci for PrCa generalize to the Latino population, which may not be surprising given their high degree of European ancestry. 28,30 As found in previous studies in men of African ancestry, 16 directional consistency was also observed for the majority (>80%) of risk variants in Latinos, among which~30% were nominally statistically significant, suggesting that most of the known genetic susceptibility loci for PrCa generalize to the Latino population, which may not be surprising given their high degree of European ancestry.…”

Section: Discussionsupporting

confidence: 82%

“…β m is the weight for SNP m. For an EURweighed PRS, weights were the conditional log ORs derived from men of European ancestry 28 ; for a Latino-weighted PRS, weights were the conditional log ORs obtained from metaanalyses in Latino men (Sets 1 and 2). The aggregate effect of the known risk alleles was examined using a weighted polygenetic risk score (PRS), PRS i = P C m = 1 β m g im , for each individual.…”

Section: Statistical Analysesmentioning

confidence: 99%

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A genome‐wide association study of prostate cancer in Latinos

Hopp

Ingles

et al. 2019

Intl Journal of Cancer

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Latinos represent <1% of samples analyzed to date in genome‐wide association studies of cancer. The clinical value of genetic information in guiding personalized medicine in populations of non‐European ancestry will require additional discovery and risk locus characterization efforts across populations. In the present study, we performed a GWAS of prostate cancer (PrCa) in 2,820 Latino PrCa cases and 5,293 controls to search for novel PrCa risk loci and to examine the generalizability of known PrCa risk loci in Latino men. We also conducted a genetic admixture‐mapping scan to identify PrCa risk alleles associated with local ancestry. Genome‐wide significant associations were observed with 84 variants all located at the known PrCa risk regions at 8q24 (128.484–128.548) and 10q11.22 (MSMB gene). In admixture mapping, we observed genome‐wide significant associations with local African ancestry at 8q24. Of the 162 established PrCa risk variants that are common in Latino men, 135 (83.3%) had effects that were directionally consistent as previously reported, among which 55 (34.0%) were statistically significant with p < 0.05. A polygenic risk model of the known PrCa risk variants showed that, compared to men with average risk (25th–75th percentile of the polygenic risk score distribution), men in the top 10% had a 3.19‐fold (95% CI: 2.65, 3.84) increased PrCa risk. In conclusion, we found that the known PrCa risk variants can effectively stratify PrCa risk in Latino men. Larger studies in Latino populations will be required to discover and characterize genetic risk variants for PrCa and improve risk stratification for this population.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionsupporting

confidence: 82%

Section: Statistical Analysesmentioning

confidence: 99%

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A genome‐wide association study of prostate cancer in Latinos

Hopp

Ingles

et al. 2019

Intl Journal of Cancer

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“…P + T and LDpred models were trained and tested using the LDpred software (version 1.0.6) . The summary statistics from RPACTICAL meta‐analysis and an LD reference panel of 503 European samples from 1000 Genomes (Phase 3 version 5) were used. We fitted various P + T and LDpred models in the training population (placebo arm) to identify the best models based on the highest C‐statistic.…”

Section: Methodsmentioning

confidence: 99%

“…In prostate cancer (PCa), PRS based on well‐established risk‐associated SNPs has been consistently demonstrated to be an effective tool for PCa risk stratification. Higher percentiles of PRS scores and higher observed PCa risk have been reported in many study populations . In this study, we investigated the validity performance of PRS based on the GPS methods (P + T and LDpred) and compared it with GRS in two independent populations from an existing clinical trial cohort.…”

Section: Introductionmentioning

confidence: 99%

Broad‐ and narrow‐sense validity performance of three polygenic risk score methods for prostate cancer risk assessment

Shi

Lin

et al. 2019

The Prostate

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Background Several polygenic risk score (PRS) methods are available for measuring the cumulative effect of multiple risk‐associated single nucleotide polymorphisms (SNPs). Their performance in predicting risk at the individual level has not been well studied. Methods We compared the performance of three PRS methods for prostate cancer risk assessment in a clinical trial cohort, including genetic risk score (GRS), pruning and thresholding (P + T), and linkage disequilibrium prediction (LDpred). Performance was evaluated for score deciles (broad‐sense validity) and score values (narrow‐sense validity). Results A training process was required to identify the best P + T model (397 SNPs) and LDpred model (3 011 362 SNPs). In contrast, GRS was directly calculated based on 110 established risk‐associated SNPs. For broad‐sense validity in the testing population, higher deciles were significantly associated with higher observed risk; Ptrend was 7.40 × 10−11, 7.64 × 10−13, and 7.51 × 10−10 for GRS, P + T, and LDpred, respectively. For narrow‐sense validity, the calibration slope (1 is best) was 1.03, 0.77, and 0.87, and mean bias score (0 is best) was 0.09, 0.21, and 0.10 for GRS, P + T, and LDpred, respectively. Conclusions The performance of GRS was better than P + T and LDpred. Fewer and well‐established SNPs of GRS also make it more feasible and interpretable for genetic testing at the individual level.

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Single-Nucleotide Polymorphism–Based Genetic Risk Score and Patient Age at Prostate Cancer Diagnosis

Labbate

et al. 2019

JAMA Netw Open

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IMPORTANCE Few studies have evaluated the association between a single-nucleotide polymorphism-based genetic risk score (GRS) and patient age at prostate cancer (PCa) diagnosis. OBJECTIVES To test the association between a GRS and patient age at PCa diagnosis and to compare the performance of a GRS with that of family history (FH) in PCa risk stratification. DESIGN, SETTING, AND PARTICIPANTS A cohort study of 3225 white men was conducted as a secondary analysis of the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) chemoprevention trial, a 4-year, randomized, double-blind, placebo-controlled multicenter study conducted from March 2003 to April 2009 to evaluate the safety and efficacy of dutasteride in reducing PCa events. Participants were confirmed to be cancer free by prostate biopsy (6-12 cores) within 6 months prior to the study and underwent 10 core biopsies every 2 years per protocol. The dates for performing data analysis were from July 2016 to October 2019. INTERVENTIONS A well-established, population-standardized GRS was calculated for each participant based on 110 known PCa risk-associated single-nucleotide polymorphisms, which is a relative risk compared with the general population. Men were classified into 3 GRS risk groups based on predetermined cutoff values: low (<0.50), average (0.50-1.49), and high (Ն1.50). MAIN OUTCOMES AND MEASURES Prostate cancer diagnosis-free survival among men of different risk groups. RESULTS Among 3225 men (median age, 63 years [interquartile range, 58-67 years]) in the study, 683 (21%) were classified as low risk, 1937 (60%) as average risk, and 605 (19%) as high risk based on GRS alone. In comparison, 2789 (86%) were classified as low or average risk and 436 (14%) as high risk based on FH alone. Men in higher GRS risk groups had a PCa diagnosis-free survival rate that was worse than that of those in the lower GRS risk group (χ 2 = 53.3; P < .001 for trend) and in participants with a negative FH of PCa (χ 2 = 45.5; P < .001 for trend). Combining GRS and FH further stratified overall genetic risk, indicating that 957 men (30%) were at high genetic risk (either high GRS or positive FH), 1667 men (52%) were at average genetic risk (average GRS and negative FH), and 601 men (19%) were at low genetic risk (low GRS and negative FH). The median PCa diagnosisfree survival was 74 years (95% CI, 73-75 years) for men at high genetic risk, 77 years (95% CI, 75 to >80 years) for men at average genetic risk, and more than 80 years (95% CI, >80 to >80 years) for men at low genetic risk. In contrast, the median PCa diagnosis-free survival was 73 years (95% CI, 71-76 years) for men with a positive FH and 77 years (95% CI, 76-79 years) for men with a negative FH.

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Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci

Cited by 769 publications

References 63 publications

A genome‐wide association study of prostate cancer in Latinos

A genome‐wide association study of prostate cancer in Latinos

Broad‐ and narrow‐sense validity performance of three polygenic risk score methods for prostate cancer risk assessment

Single-Nucleotide Polymorphism–Based Genetic Risk Score and Patient Age at Prostate Cancer Diagnosis

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