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17 results on '"Consortium, PRACTICAL"'

1. Association analyses identify 31 new risk loci for colorectal cancer susceptibility

Author

Law, PJ, Timofeeva, M, Fernandez-Rozadilla, C, Broderick, P, Studd, J, Fernandez-Tajes, J, Farrington, S, Svinti, V, Palles, C, Orlando, G, Sud, A, Holroyd, A, Penegar, S, Theodoratou, E, Vaughan-Shaw, P, Campbell, H, Zgaga, L, Hayward, C, Campbell, A, Harris, S, Deary, IJ, Starr, J, Gatcombe, L, Pinna, M, Briggs, S, Martin, L, Jaeger, E, Sharma-Oates, A, East, J, Leedham, S, Arnold, R, Johnstone, E, Wang, H, Kerr, D, Kerr, R, Maughan, T, Kaplan, R, Al-Tassan, N, Palin, K, Hänninen, UA, Cajuso, T, Tanskanen, T, Kondelin, J, Kaasinen, E, Sarin, A-P, Eriksson, JG, Rissanen, H, Knekt, P, Pukkala, E, Jousilahti, P, Salomaa, V, Ripatti, S, Palotie, A, Renkonen-Sinisalo, L, Lepistö, A, Böhm, J, Mecklin, J-P, Buchanan, DD, Win, A-K, Hopper, J, Jenkins, ME, Lindor, NM, Newcomb, PA, Gallinger, S, Duggan, D, Casey, G, Hoffmann, P, Nöthen, MM, Jöckel, K-H, Easton, DF, Pharoah, PDP, Peto, J, Canzian, F, Swerdlow, A, Eeles, RA, Kote-Jarai, Z, Muir, K, Pashayan, N, Consortium, Practical, Harkin, A, Allan, K, McQueen, J, Paul, J, Iveson, T, Saunders, M, Butterbach, K, Chang-Claude, J, Hoffmeister, M, Brenner, H, Kirac, I, Matošević, P, Hofer, P, Brezina, S, Gsur, A, Cheadle, JP, Aaltonen, LA, Tomlinson, I, Houlston, RS, Dunlop, MG, Law, Philip J [0000-0001-9663-4611], Timofeeva, Maria [0000-0002-2503-4253], Fernandez-Rozadilla, Ceres [0000-0001-7330-4804], Broderick, Peter [0000-0002-8348-5829], Studd, James [0000-0002-7157-754X], Farrington, Susan [0000-0001-5955-7389], Svinti, Victoria [0000-0001-9926-0416], Sud, Amit [0000-0002-6133-0164], Hayward, Caroline [0000-0002-9405-9550], Campbell, Archie [0000-0003-0198-5078], Martin, Lynn [0000-0003-3962-389X], East, James [0000-0001-8035-3700], Kaplan, Richard [0000-0002-0189-8348], Al-Tassan, Nada [0000-0001-9076-0334], Palin, Kimmo [0000-0002-4621-6128], Salomaa, Veikko [0000-0001-7563-5324], Buchanan, Daniel D [0000-0003-2225-6675], Win, Aung-Ko [0000-0002-2794-5261], Jenkins, Mark E [0000-0002-8964-6160], Easton, Douglas F [0000-0003-2444-3247], Pharoah, Paul DP [0000-0001-8494-732X], Eeles, Rosalind A [0000-0002-3698-6241], Muir, Kenneth [0000-0001-6429-988X], Pashayan, Nora [0000-0003-0843-2468], Harkin, Andrea [0000-0002-8831-7381], Paul, James [0000-0001-7367-5816], Hofer, Philipp [0000-0003-2550-6019], Brezina, Stefanie [0000-0001-5238-6900], Cheadle, Jeremy P [0000-0001-9453-8458], Tomlinson, Ian [0000-0003-3037-1470], Houlston, Richard S [0000-0002-5268-0242], and Apollo - University of Cambridge Repository

Subjects
Male, Science, Inheritance Patterns, cancer genetics, Datasets as Topic, colorectal cancer, Genome-wide association studies, Polymorphism, Single Nucleotide, Article, White People, Asian People, Risk Factors, Cancer genomics, Humans, Genetic Predisposition to Disease, lcsh:Science, Cancer genetics, neoplasms, cancer genomics, genomiikka, Middle Aged, Colorectal cancer, digestive system diseases, peräsuolisyöpä, syöpägeenit, Genetic Loci, Case-Control Studies, genome-wide association studies, lcsh:Q, syöpätaudit, Female, Colorectal Neoplasms, Genome-Wide Association Study
Abstract

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention., In colorectal cancer (CRC), finding loci associated with risk may give insight into disease aetiology. Here, the authors report a genome-wide association analysis in Europeans of 34,627 CRC cases and 71,379 controls, and find 31 new risk loci and 17 new risk SNPs at previously reported loci.

Published
2019

2. Abstract NG03: Multiethnic prostate cancer GWAS meta-analysis identifies novel variants, improves genetic risk prediction across populations, and informs biological mechanisms of prostate cancer

Author

Darst, Burcu F., primary, Moss, Lilit, additional, Saunders, Edward J., additional, Mancuso, Nicholas, additional, Sheng, Xin, additional, Chou, Alisha, additional, Dadaev, Tokhir, additional, Berndt, Sonja I., additional, Van Den Eeden, Stephen K., additional, Chanock, Stephen J., additional, Cook, Michael B., additional, Layne, Tracy M., additional, Albanes, Demetrius, additional, Nakagawa, Hidewaki, additional, Witte, John S., additional, Consortium, Practical, additional, Eeles, Rosalind A., additional, Kote-Jarai, Zsofia, additional, Conti, David V., additional, and Haiman, Christopher A., additional

Published
2021
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3. A polymorphism in the promoter of FRAS1 is a candidate SNP associated with metastatic prostate cancer

Author

Wang, Victoria, primary, Geybels, Milan S., additional, Jordahl, Kristina M., additional, Gerke, Travis, additional, Hamid, Anis, additional, Penney, Kathryn L., additional, Markt, Sarah C., additional, Freedman, Matthew, additional, Pomerantz, Mark, additional, Lee, Gwo‐Shu M., additional, Rana, Huma, additional, Börnigen, Daniela, additional, Rebbeck, Timothy R., additional, Huttenhower, Curtis, additional, Eeles, Ros A., additional, Stanford, Janet L., additional, Consortium, Practical, additional, Berndt, Sonja I., additional, Claessens, Frank, additional, Sørensen, Karina D., additional, Park, Jong Y., additional, Vega, Ana, additional, Usmani, Nawaid, additional, Mucci, Lorelei, additional, and Sweeney, Christopher J., additional

Published
2021
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4. The role of plasma microseminoprotein-beta in prostate cancer: an observational nested case-control and Mendelian randomization study in the European prospective investigation into cancer and nutrition

Author

Smith Byrne, K, Appleby, PN, Key, TJ, Holmes, MV, Fensom, GK, Agudo, A, Ardanaz, E, Boeing, H, Bueno-de-Mesquita, HB, Chirlaque, MD, Kaaks, R, Larrañaga, N, Palli, D, Perez-Cornago, A, Quirós, JR, Ricceri, F, Sánchez, MJ, Tagliabue, G, Tsilidis, KK, Tumino, R, Fortner, RT, Ferrari, P, Consortium, PRACTICAL, Riboli, E, Lilja, H, and Travis, RC

Subjects
Male, EPIC cohort, Mendelian randomization, microseminoprotein-beta, prospective study, prostate cancer, prostate-specific antigen, Biomarkers, Tumor, Case-Control Studies, Follow-Up Studies, Humans, Mendelian Randomization Analysis, Middle Aged, Nutritional Status, Prognosis, Prospective Studies, Prostatic Neoplasms, Prostatic Secretory Proteins, Risk Factors, Epidemiology, parasitic diseases, PRACTICAL Consortium, 1112 Oncology and Carcinogenesis, Oncology & Carcinogenesis, Nutrició, Nutrition, Tumor, Càncer de pròstata, Original Articles, Editor's Choice, Biomarkers
Abstract

BACKGROUND: Microseminoprotein-beta (MSP), a protein secreted by the prostate epithelium, may have a protective role in the development of prostate cancer. The only previous prospective study found a 2% reduced prostate cancer risk per unit increase in MSP. This work investigates the association of MSP with prostate cancer risk using observational and Mendelian randomization (MR) methods.PATIENTS AND METHODS: A nested case-control study was conducted with the European Prospective Investigation into Cancer and Nutrition (EPIC) with 1871 cases and 1871 matched controls. Conditional logistic regression analysis was used to investigate the association of pre-diagnostic circulating MSP with risk of incident prostate cancer overall and by tumour subtype. EPIC-derived estimates were combined with published data to calculate an MR estimate using two-sample inverse-variance method.RESULTS: Plasma MSP concentrations were inversely associated with prostate cancer risk after adjusting for total prostate-specific antigen concentration [odds ratio (OR) highest versus lowest fourth of MSP = 0.65, 95% confidence interval (CI) 0.51-0.84, Ptrend = 0.001]. No heterogeneity in this association was observed by tumour stage or histological grade. Plasma MSP concentrations were 66% lower in rs10993994 TT compared with CC homozygotes (per allele difference in MSP: 6.09 ng/ml, 95% CI 5.56-6.61, r2=0.42). MR analyses supported a potentially causal protective association of MSP with prostate cancer risk (OR per 1 ng/ml increase in MSP for MR: 0.96, 95% CI 0.95-0.97 versus EPIC observational: 0.98, 95% CI 0.97-0.99). Limitations include lack of complete tumour subtype information and more complete information on the biological function of MSP.CONCLUSIONS: In this large prospective European study and using MR analyses, men with high circulating MSP concentration have a lower risk of prostate cancer. MSP may play a causally protective role in prostate cancer.

Published
2020

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

Author

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, Consortium, Practical (Prostate Cancer Association Group To Investigate Cancer-Associated Alterations In The Genome), Freedman, M, Wiklund, F, Chanock, S, Henderson, BE, Easton, DF, Haiman, CA, Eeles, RA, Conti, DV, Kote-Jarai, Z, Dadaev, Tokhir [0000-0002-8268-0438], Leongamornlert, Daniel A [0000-0002-3486-3168], Brook, Mark N [0000-0002-8969-2378], Olama, Ali Amin Al [0000-0002-7178-3431], Schumacher, Fredrick R [0000-0002-3073-7463], Muir, Kenneth [0000-0001-6429-988X], Batra, Jyotsna [0000-0003-4646-6247], Nordström, Tobias [0000-0003-4915-7546], Pharoah, Paul [0000-0001-8494-732X], Pashayan, Nora [0000-0003-0843-2468], Schleutker, Johanna [0000-0002-1863-0305], Sipeky, Csilla [0000-0002-8853-4722], Wolk, Alicja [0000-0001-7387-6845], Cancel-Tassin, Géraldine [0000-0002-9583-6382], Sorensen, Karina Dalsgaard [0000-0002-4902-5490], Kerns, Sarah [0000-0002-6503-0011], Ostrer, Harry [0000-0002-2209-5376], Fachal, Laura [0000-0002-7256-9752], Kogevinas, Manolis [0000-0002-9605-0461], Nordestgaard, Børge G [0000-0002-1954-7220], Lim, Jasmine [0000-0002-7501-1834], Truong, Thérèse [0000-0002-2943-6786], Xu, Jianfeng [0000-0002-1343-8752], Easton, Douglas F [0000-0003-2444-3247], Eeles, Rosalind A [0000-0002-3698-6241], Apollo - University of Cambridge Repository, National Institutes of Health, Urology, and Clinical Chemistry

Subjects
Male, Risk, Science, GENETIC, Quantitative Trait Loci, Black People, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, urologic and male genital diseases, ANNOTATION, Polymorphism, Single Nucleotide, Article, White People, REGION, GENETIC ASSOCIATION, SDG 3 - Good Health and Well-being, MD Multidisciplinary, Medicine and Health Sciences, ELEMENTS, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, lcsh:Science, Medicinsk genetik, MODEL SELECTION, BAYESIAN FRAMEWORK, Cancer och onkologi, Science & Technology, Chromosome Mapping, Prostatic Neoplasms, Bayes Theorem, Molecular Sequence Annotation, ASSOCIATION, JOINT ANALYSIS, RISK LOCI, STATISTICS, Multidisciplinary Sciences, Cancer and Oncology, Multivariate Analysis, Science & Technology - Other Topics, lcsh:Q, Medical Genetics, Algorithms, VARIABLE-SELECTION, Genome-Wide Association Study
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., Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.

Published
2018

6. Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array

Author

Saunders, EJ, Dadaev, T, Leongamornlert, DA, Olama, AA, Benlloch, S, Giles, GG, Wiklund, F, Grönberg, H, Haiman, CA, Schleutker, J, Nordestgaard, BG, Travis, RC, Neal, D, Pasayan, N, Khaw, KT, Stanford, JL, Blot, WJ, Thibodeau, SN, Maier, C, Kibel, AS, Cybulski, C, Cannon-Albright, L, Brenner, H, Park, JY, Kaneva, R, Batra, J, Teixeira, MR, Pandha, H, Govindasami, K, Muir, K, Genetic Prostate Cancer Study Collaborators, UK, ProtecT Study Collaborators, UK, Consortium, PRACTICAL, Easton, DF, Eeles, RA, Kote-Jarai, Z, Khaw, Kay-Tee [0000-0002-8802-2903], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Male, Risk, DNA Repair, Genotype, BRCA1 Protein, Genes, BRCA2, Prostatic Neoplasms, Cell Cycle Proteins, DNA, urologic and male genital diseases, Polymorphism, Single Nucleotide, DNA-Binding Proteins, DNA Repair Enzymes, Case-Control Studies, Humans, Genetic Predisposition to Disease, Prospective Studies, Germ-Line Mutation, Genome-Wide Association Study
Abstract

BACKGROUND: Germline mutations within DNA-repair genes are implicated in susceptibility to multiple forms of cancer. For prostate cancer (PrCa), rare mutations in BRCA2 and BRCA1 give rise to moderately elevated risk, whereas two of ∼100 common, low-penetrance PrCa susceptibility variants identified so far by genome-wide association studies implicate RAD51B and RAD23B. METHODS: Genotype data from the iCOGS array were imputed to the 1000 genomes phase 3 reference panel for 21 780 PrCa cases and 21 727 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. We subsequently performed single variant, gene and pathway-level analyses using 81 303 SNPs within 20 Kb of a panel of 179 DNA-repair genes. RESULTS: Single SNP analyses identified only the previously reported association with RAD51B. Gene-level analyses using the SKAT-C test from the SNP-set (Sequence) Kernel Association Test (SKAT) identified a significant association with PrCa for MSH5. Pathway-level analyses suggested a possible role for the translesion synthesis pathway in PrCa risk and Homologous recombination/Fanconi Anaemia pathway for PrCa aggressiveness, even though after adjustment for multiple testing these did not remain significant. CONCLUSIONS: MSH5 is a novel candidate gene warranting additional follow-up as a prospective PrCa-risk locus. MSH5 has previously been reported as a pleiotropic susceptibility locus for lung, colorectal and serous ovarian cancers.

Published
2016

7. Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation

Author

Gusev, A, Shi, H, Kichaev, G, Pomerantz, M, Li, F, Long, HW, Ingles, SA, Kittles, RA, Strom, SS, Rybicki, BA, Nemesure, B, Isaacs, WB, Zheng, W, Pettaway, CA, Yeboah, ED, Tettey, Y, Biritwum, RB, Adjei, AA, Tay, E, Truelove, A, Niwa, S, Chokkalingam, AP, John, EM, Murphy, AB, Signorello, LB, Carpten, J, Leske, MC, Wu, S-Y, Hennis, AJM, Neslund-Dudas, C, Hsing, AW, Chu, L, Goodman, PJ, Klein, EA, Witte, JS, Casey, G, Kaggwa, S, Cook, MB, Stram, DO, Blot, WJ, Eeles, RA, Easton, D, Kote-Jarai, Z, Al Olama, AA, Benlloch, S, Muir, K, Giles, GG, Southey, MC, Fitzgerald, LM, Gronberg, H, Wiklund, F, Aly, M, Henderson, BE, Schleutker, J, Wahlfors, T, Tammela, TLJ, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, K-T, Stanford, JL, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Wokolorczyk, D, Kluzniak, W, Cannon-Albright, L, Teerlink, C, Brenner, H, Dieffenbach, AK, Arndt, V, Park, JY, Sellers, TA, Lin, H-Y, Slavov, C, Kaneva, R, Mitev, V, Batra, J, Spurdle, A, Clements, JA, Teixeira, MR, Pandha, H, Michael, A, Paulo, P, Maia, S, Kierzek, A, Conti, DV, Albanes, D, Berg, C, Berndt, SI, Campa, D, Crawford, ED, Diver, WR, Gapstur, SM, Gaziano, JM, Giovannucci, E, Hoover, R, Hunter, DJ, Johansson, M, Kraft, P, Le Marchand, L, Lindstrom, S, Navarro, C, Overvad, K, Riboli, E, Siddiq, A, Stevens, VL, Trichopoulos, D, Vineis, P, Yeager, M, Trynka, G, Raychaudhuri, S, Schumacher, FR, Price, AL, Freedman, ML, Haiman, CA, Pasaniuc, B, Cook, M, Guy, M, Govindasami, K, Leongamornlert, D, Sawyer, EJ, Wilkinson, R, Saunders, EJ, Tymrakiewicz, M, Dadaev, T, Morgan, A, Fisher, C, Hazel, S, Livni, N, Lophatananon, A, Pedersen, J, Hopper, JL, Adolfson, J, Stattin, P, Johansson, J-E, Cavalli-Bjoerkman, C, Karlsson, A, Broms, M, Auvinen, A, Kujala, P, Maeaettaenen, L, Murtola, T, Taari, K, Weischer, M, Nielsen, SF, Klarskov, P, Roder, A, Iversen, P, Wallinder, H, Gustafsson, S, Cox, A, Brown, P, George, A, Marsden, G, Lane, A, Davis, M, Tillmans, L, Riska, S, Wang, L, Rinckleb, A, Lubiski, J, Stegmaier, C, Pow-Sang, J, Park, H, Radlein, S, Rincon, M, Haley, J, Zachariah, B, Kachakova, D, Popov, E, Mitkova, A, Vlahova, A, Dikov, T, Christova, S, Heathcote, P, Wood, G, Malone, G, Saunders, P, Eckert, A, Yeadon, T, Kerr, K, Collins, A, Turner, M, Srinivasan, S, Kedda, M-A, Alexander, K, Omara, T, Wu, H, Henrique, R, Pinto, P, Santos, J, Barros-Silva, J, and Consortium, PRACTICAL

Subjects
urologic and male genital diseases
Abstract

Although genome-wide association studies have identified over 100 risk loci that explain ~33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Published
2016

8. Cross-cancer genome-wide analysis of lung, ovary, breast, prostate and colorectal cancer reveals novel pleiotropic associations

Author

Fehringer, Gordon, Kraft, Peter, Pharoah, Paul D, Eeles, Rosalind A, Chatterjee, Nilanjan, Schumacher, Fredrick R, Schildkraut, Joellen M, Lindstrom, Sara, Brennan, Paul, Bickeboller, Heike, Houlston, Richard S, Landi, Maria Teresa, Caporaso, Neil, Risch, Angela, Al Olama, Ali Amin, Berndt, Sonja I, Giovannucci, Edward L, Gronberg, Henrik, Kote-Jarai, Zsofia, Ma, Jing, Muir, Kenneth, Stampfer, Meir J, Stevens, Victoria L, Wiklund, Fredrik, Willett, Walter C, Goode, Ellen L, Permuth, Jennifer B, Risch, Harvey A, Reid, Brett M, Bezieau, Stephane, Brenner, Hermann, Chan, Andrew T, Chang-Claude, Jenny, Hudson, Thomas J, Kocarnik, Jonathan K, Newcomb, Polly A, Schoen, Robert E, Slattery, Martha L, White, Emily, Adank, Muriel A, Ahsan, Habibul, Aittomaki, Kristiina, Baglietto, Laura, Blomquist, Carl, Canzian, Federico, Czene, Kamila, dos-Santos-Silva, Isabel, Eliassen, A Heather, Figueroa, Jonine D, Flesch-Janys, Dieter, Fletcher, Olivia, Garcia-Closas, Montserrat, Gaudet, Mia M, Johnson, Nichola, Hall, Per, Hazra, Aditi, Hein, Rebecca, Hofman, Albert, Hopper, John L, Irwanto, Astrid, Johansson, Mattias, Kaaks, Rudolf, Kibriya, Muhammad G, Lichtner, Peter, Liu, Jianjun, Lund, Eiliv, Makalic, Enes, Meindl, Alfons, Muller-Myhsok, Bertram, Muranen, Taru A, Nevanlinna, Heli, Peeters, Petra H, Peto, Julian, Prentice, Ross L, Rahman, Nazneen, Sanchez, Maria Jose, Schmidt, Daniel F, Schmutzler, Rita K, Southey, Melissa C, Tamimi, Rulla, Travis, Ruth C, Turnbull, Clare, Uitterlinden, Andre G, Wang, Zhaoming, Whittemore, Alice S, Yang, Xiaohong R, Zheng, Wei, Buchanan, Daniel D, Casey, Graham, Conti, David V, Edlund, Christopher K, Gallinger, Steven, Haile, Robert W, Jenkins, Mark, Le Marchand, Loic, Li, Li, Lindor, Noralene M, Schmit, Stephanie L, Thibodeau, Stephen N, Woods, Michael O, Rafnar, Thorunn, Gudmundsson, Julius, Stacey, Simon N, Stefansson, Kari, Sulem, Patrick, Chen, Y Ann, Tyrer, Jonathan P, Christiani, David C, Wei, Yongyue, Shen, Hongbing, Hu, Zhibin, Shu, Xiao-Ou, Shiraishi, Kouya, Takahashi, Atsushi, Bosse, Yohan, Obeidat, Ma'en, Nickle, David, Timens, Wim, Freedman, Matthew L, Li, Qiyuan, Seminara, Daniela, Chanock, Stephen J, Gong, Jian, Peters, Ulrike, Gruber, Stephen B, Amos, Christopher I, Sellers, Thomas A, Easton, Douglas F, Hunter, David J, Haiman, Christopher A, Henderson, Brian E, Hung, Rayjean J, OCAC, Consortium, PRACTICAL, Res, Hereditary Breast Ovarian Canc, Transdisciplinary, Colorectal, Canc, African Amer Breast, Canc, African Ancestry Prostate, Medical Oncology, Epidemiology, Internal Medicine, Surgery, Guided Treatment in Optimal Selected Cancer Patients (GUTS), and Groningen Research Institute for Asthma and COPD (GRIAC)

Subjects
0301 basic medicine, Oncology, Male, medicine.medical_specialty, Cancer Research, Lung Neoplasms, SUSCEPTIBILITY LOCI, Genotype, IDENTIFIES 2, Colorectal cancer, Locus (genetics), Genome-wide association study, Breast Neoplasms, Article, 03 medical and health sciences, Prostate cancer, AFRICAN ANCESTRY, Breast cancer, SDG 3 - Good Health and Well-being, Internal medicine, medicine, Journal Article, AGGRESSIVE PROSTATE, Humans, GENETIC POLYMORPHISMS, Lung cancer, METAANALYSIS, Ovarian Neoplasms, business.industry, COMMON VARIANTS, Prostatic Neoplasms, CELL CARCINOMA, medicine.disease, RISK LOCI, 3. Good health, 030104 developmental biology, Expression quantitative trait loci, Adenocarcinoma, Female, business, Colorectal Neoplasms, GASTRIC-CANCER, Genome-Wide Association Study
Abstract

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103–14. ©2016 AACR.

Published
2016

9. Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci

Author

Al Olama, A.A., Benlloch, S., Antoniou, A.C., Giles, G.G., Severi, G., Neal, D.E., Hamdy, F.C., Donovan, J.L., Muir, K., Schleutker, J., Henderson, B.E., Haiman, C.A., Schumacher, F.R., Pashayan, N., Pharoah, P.D.P., Ostrander, E.A., Stanford, J.L., Batra, J., Clements, J.A., Chambers, S.K., Weischer, M., Nordestgaard, B.G., Ingles, S.A., Sorensen, K.D., Orntoft, T.F., Park, J.Y., Cybulski, C., Maier, C., Doerk, T., Dickinson, J.L., Cannon-Albright, L., Brenner, H., Rebbeck, T.R., Zeigler-Johnson, C., Habuchi, T., Thibodeau, S.N., Cooney, K.A., Chappuis, P.O., Hutter, P., Kaneva, R.P., Foulkes, W.D., Zeegers, M.P., Lu, Y-J., Zhang, H-W., Stephenson, R., Cox, A., Southey, M.C., Spurdle, A.B., FitzGerald, L., Leongamornlert, D., Saunders, E., Tymrakiewicz, M., Guy, M., Dadaev, T., Little, S.J., Govindasami, K., Sawyer, E., Wilkinson, R., Herkommer, K., Hopper, J.L., Lophatonanon, A., Rinckleb, A.E., Kote-Jarai, Z., Eeles, R.A., Easton, D.F., Surgeons, B.A.U., Collaborators, U.K.P.S., Consortium, PRACTICAL., Amin Al Olama, Ali [0000-0002-7178-3431], Antoniou, Antonis [0000-0001-9223-3116], Pharoah, Paul [0000-0001-8494-732X], Easton, Douglas [0000-0003-2444-3247], and Apollo - University of Cambridge Repository

Subjects
Adult, Aged, 80 and over, Male, Genotype, Genetic Variation, Prostatic Neoplasms, Middle Aged, urologic and male genital diseases, Risk Assessment, Risk Factors, Odds Ratio, Humans, Genetic Predisposition to Disease, Alleles, Aged, Genome-Wide Association Study
Abstract

BACKGROUND: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. METHODS: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. RESULTS: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2-5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). CONCLUSIONS: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. IMPACT: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.

Published
2015

10. Circulating Selenium and Prostate Cancer Risk: A Mendelian Randomization Analysis.

Author

Yarmolinsky, James, Bonilla, Carolina, Haycock, Philip C, Langdon, Ryan J Q, Lotta, Luca A, Langenberg, Claudia, Relton, Caroline L, Lewis, Sarah J, Evans, David M, Consortium, PRACTICAL, PRACTICAL Consortium, Davey Smith, George, and Martin, Richard M

Subjects
VITAMIN E, PHYSIOLOGICAL effects of selenium, PROSTATE cancer, TYPE 2 diabetes, CANCER genetics
Abstract

In the Selenium and Vitamin E Cancer Prevention Trial (SELECT), selenium supplementation (causing a median 114 μg/L increase in circulating selenium) did not lower overall prostate cancer risk, but increased risk of high-grade prostate cancer and type 2 diabetes. Mendelian randomization analysis uses genetic variants to proxy modifiable risk factors and can strengthen causal inference in observational studies. We constructed a genetic instrument comprising 11 single nucleotide polymorphisms robustly (P < 5 × 10-8) associated with circulating selenium in genome-wide association studies. In a Mendelian randomization analysis of 72 729 men in the PRACTICAL Consortium (44 825 case subjects, 27 904 control subjects), 114 μg/L higher genetically elevated circulating selenium was not associated with prostate cancer (odds ratio [OR] = 1.01, 95% confidence interval [CI] = 0.89 to 1.13). In concordance with findings from SELECT, selenium was weakly associated with advanced (including high-grade) prostate cancer (OR = 1.21, 95% CI = 0.98 to 1.49) and type 2 diabetes (OR = 1.18, 95% CI = 0.97 to 1.43; in a type 2 diabetes genome-wide association study meta-analysis with up to 49 266 case subjects and 249 906 control subjects). Our Mendelian randomization analyses do not support a role for selenium supplementation in prostate cancer prevention and suggest that supplementation could have adverse effects on risks of advanced prostate cancer and type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2018
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11. Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score

Author

Minh-Phuong, Huynh-Le, Roshan, Karunamuni, Chun Chieh, Fan, Lui, Asona, Wesley K, Thompson, Maria Elena, Martinez, Rosalind A, Eeles, Zsofia, Kote-Jarai, Kenneth R, Muir, Artitaya, Lophatananon, Johanna, Schleutker, Nora, Pashayan, Jyotsna, Batra, Henrik, Grönberg, David E, Neal, Børge G, Nordestgaard, Catherine M, Tangen, Robert J, MacInnis, Alicja, Wolk, Demetrius, Albanes, Christopher A, Haiman, Ruth C, Travis, William J, Blot, Janet L, Stanford, Lorelei A, Mucci, Catharine M L, West, Sune F, Nielsen, Adam S, Kibel, Olivier, Cussenot, Sonja I, Berndt, Stella, Koutros, Karina Dalsgaard, Sørensen, Cezary, Cybulski, Eli Marie, Grindedal, Florence, Menegaux, Jong Y, Park, Sue A, Ingles, Christiane, Maier, Robert J, Hamilton, Barry S, Rosenstein, Yong-Jie, Lu, Stephen, Watya, Ana, Vega, Manolis, Kogevinas, Fredrik, Wiklund, Kathryn L, Penney, Chad D, Huff, Manuel R, Teixeira, Luc, Multigner, Robin J, Leach, Hermann, Brenner, Esther M, John, Radka, Kaneva, Christopher J, Logothetis, Susan L, Neuhausen, Kim, De Ruyck, Piet, Ost, Azad, Razack, Lisa F, Newcomb, Jay H, Fowke, Marija, Gamulin, Aswin, Abraham, Frank, Claessens, Jose Esteban, Castelao, Paul A, Townsend, Dana C, Crawford, Gyorgy, Petrovics, Ron H N, van Schaik, Marie-Élise, Parent, Jennifer J, Hu, Wei, Zheng, Ian G, Mills, Ole A, Andreassen, Anders M, Dale, Tyler M, Seibert, collaborators, UKGPCS, BioResource), APCB (Australian Prostate Cancer, Investigators, NC-LA PCaP, Collaborators, IMPACT Study Steering Committee and, Investigators, Canary PASS, Committee, Profile Study Steering, Consortium, PRACTICAL, and Clinical Chemistry

Subjects
SELECTION, Male, Cancer Research, Urology, LASSO, Polymorphism, Single Nucleotide, Risk Assessment, Cancer screening, Cancer epidemiology, SDG 3 - Good Health and Well-being, Risk Factors, Humans, Genetic Predisposition to Disease, prostate cancer, multi-ancestry datasets, Cancer genetics, Early Detection of Cancer, Prostatic Neoplasms/diagnosis, Cancer och onkologi, Science & Technology, Manchester Cancer Research Centre, ResearchInstitutes_Networks_Beacons/mcrc, Prostatic Neoplasms, Urology & Nephrology, Prostate-Specific Antigen, Prostate-Specific Antigen/genetics, Oncology, Cancer and Oncology, Life Sciences & Biomedicine
Abstract

Background Prostate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets. Methods In total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry—the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured. Results The final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43–15.16] in ProtecT, 7.07 [6.58–7.60] in African ancestry, 10.31 [9.58–11.11] in Asian ancestry, and 11.18 [10.34–12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11–0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15–0.22) and 0.26 (0.19–0.33), respectively. Conclusions We demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

Published
2022

12. An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

Author

Wu, Lang, Yang, Yaohua, Guo, Xingyi, Shu, Xiao Ou, Cai, Qiuyin, Shu, Xiang, Li, Bingshan, Tao, Ran, Wu, Chong, Nikas, Jason B., Sun, Yanfa, Zhu, Jingjing, Roobol, Monique J., Giles, Graham G., Brenner, Hermann, John, Esther M., Clements, Judith, Grindedal, Eli Marie, Park, Jong Y., Stanford, Janet L., Kote-Jarai, Zsofia, Haiman, Christopher A., Eeles, Rosalind A., Zheng, Wei, Long, Jirong, Henderson, Brian E., Schumacher, Fredrick R., Easton, Douglas, Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth, Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Gapstur, Susan M., Stevens, Victoria L., Tangen, Catherine M., Batra, Jyotsna, Gronberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, Nordestgaard, Børge G., Li, Bingshan [0000-0003-2129-168X], Wu, Chong [0000-0002-8400-1785], Nikas, Jason B [0000-0001-9703-0422], Roobol, Monique J [0000-0001-6967-1708], Giles, Graham G [0000-0003-4946-9099], Park, Jong Y [0000-0002-6384-6447], Eeles, Rosalind A [0000-0002-3698-6241], Zheng, Wei [0000-0003-1226-070X], Apollo - University of Cambridge Repository, Hunter, DJ, consortium, PRACTICAL, Consortium, CRUK, Consortium, BPC3, Consortium, CAPS, Consortium, PEGASUS, and Urology

Subjects
0301 basic medicine, Male, General Physics and Astronomy, 02 engineering and technology, VARIANTS, urologic and male genital diseases, DISEASE, CRUK Consortium, Prostate cancer, BPC3 Consortium, Risk Factors, Epidemiology of cancer, GWAS, lcsh:Science, Cancer genetics, GENE-EXPRESSION, Genetics, Multidisciplinary, Methylation, 021001 nanoscience & nanotechnology, STATISTICS, Multidisciplinary Sciences, CpG site, DNA methylation, Science & Technology - Other Topics, 0210 nano-technology, SUSCEPTIBILITY LOCI, Science, Biology, Article, General Biochemistry, Genetics and Molecular Biology, PRACTICAL consortium, 03 medical and health sciences, Cancer epidemiology, SDG 3 - Good Health and Well-being, REVEALS, Genetic model, medicine, Biomarkers, Tumor, Humans, Genetic Predisposition to Disease, Gene, Genetic Association Studies, Genetic association, Science & Technology, Models, Genetic, MORTALITY, Prostatic Neoplasms, General Chemistry, DNA Methylation, medicine.disease, CAPS Consortium, 030104 developmental biology, TISSUE, ANTIGEN LEVEL, Case-Control Studies, lcsh:Q, CpG Islands, PEGASUS Consortium
Abstract

It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes., Genome wide association studies have identified multiple loci associated with risk of developing prostate cancer but the functional significance of many of these are unknown. Here, after generating models to predict methylation, the authors identify CpG methylation sites associated with prostate cancer.

Published
2021
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13. Performance of African-ancestry-specific polygenic hazard score varies according to local ancestry in 8q24

Author

Jennifer Cullen, Brandon A. Mahal, Maria Elena Martinez, Robin J. Leach, Brent S. Rose, Marie-Élise Parent, Catherine M. Tangen, Pascal Blanchet, Tyler M. Seibert, Jong Y. Park, Jennifer J. Hu, Geraldine Cancel-Tassin, Rosalind A. Eeles, Chun Chieh Fan, Esther M. John, Roshan Karunamuni, James L. Mohler, Jack A. Taylor, Melinda C. Aldrich, Artitaya Lophatananon, Luc Multigner, Ole A. Andreassen, Thérèse Truong, Marc Romana, Florence Menegaux, Ian M. Thompson, Laurent Brureau, Kenneth Muir, Olivier Cussenot, Dana C. Crawford, Adam S. Kibel, Gyorgy Petrovics, Asona Lui, Elizabeth T. H. Fontham, Bettina F. Drake, Jeannette T. Bensen, Ian G. Mills, William S. Bush, Hui-Yi Lin, Zsofia Kote-Jarai, Wesley K. Thompson, Maureen Sanderson, Anders M. Dale, Wei Zheng, Jay H. Fowke, Phyllis J. Goodman, William J. Blot, Minh-Phuong Huynh-Le, Collaborators, UKGPCS, Consortium, PRACTICAL, University of California [San Diego] (UC San Diego), University of California, The institute of cancer research [London], Centre de Recherche pour les Pathologies Prostatiques [Paris] (CeRePP), Sorbonne Université (SU), CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), CHU Pointe-à-Pitre/Abymes [Guadeloupe], Biologie Intégrée du Globule Rouge (BIGR (UMR_S_1134 / U1134)), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Université de Paris (UP), This study was funded in part by grants from the University of California (#C21CR2060), the United States National Institute of Health/National Institute of Biomedical Imaging and Bioengineering (#K08EB026503), the Research Council of Norway (#223273), KG Jebsen Stiftelsen, and South East Norway Health Authority., University of California (UC), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), and Institut National de la Transfusion Sanguine [Paris] (INTS)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Université Paris Cité (UPCité)

Subjects
Male, Multifactorial Inheritance, Cancer Research, Urology, Genetic genealogy, 030232 urology & nephrology, Black People, Single-nucleotide polymorphism, [SDV.CAN]Life Sciences [q-bio]/Cancer, Polymorphism, Single Nucleotide, Risk Assessment, White People, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Genotype, Genetic variation, Humans, Medicine, Genetic Predisposition to Disease, 1000 Genomes Project, Prostate cancer risk, Proportional hazards model, business.industry, Prostatic Neoplasms, 3. Good health, Oncology, Case-Control Studies, 030220 oncology & carcinogenesis, Relative risk, business, Chromosomes, Human, Pair 8, Demography
Abstract

Background We previously developed an African-ancestry-specific polygenic hazard score (PHS46+African) that substantially improved prostate cancer risk stratification in men with African ancestry. The model consists of 46 SNPs identified in Europeans and 3 SNPs from 8q24 shown to improve model performance in Africans. Herein, we used principal component (PC) analysis to uncover subpopulations of men with African ancestry for whom the utility of PHS46+African may differ. Materials and methods Genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Genetic variation in a window spanning 3 African-specific 8q24 SNPs was estimated using 93 PCs. A Cox proportional hazards framework was used to identify the pair of PCs most strongly associated with the performance of PHS46+African. A calibration factor (CF) was formulated using Cox coefficients to quantify the extent to which the performance of PHS46+African varies with PC. Results CF of PHS46+African was strongly associated with the first and twentieth PCs. Predicted CF ranged from 0.41 to 2.94, suggesting that PHS46+African may be up to 7 times more beneficial to some African men than others. The explained relative risk for PHS46+African varied from 3.6% to 9.9% for individuals with low and high CF values, respectively. By cross-referencing our data set with 1000 Genomes, we identified significant associations between continental and calibration groupings. Conclusion We identified PCs within 8q24 that were strongly associated with the performance of PHS46+African. Further research to improve the clinical utility of polygenic risk scores (or models) is needed to improve health outcomes for men of African ancestry.

Published
2021

14. Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer

Author

Minh-Phuong Huynh-Le, Nora Pashayan, Marija Gamulin, Jong Y. Park, Radka Kaneva, Frank Claessens, Kathryn L. Penney, Johanna Schleutker, Chun Chieh Fan, Ruth C. Travis, Lisa F. Newcomb, Olivier Cussenot, Ana Vega, Tyler M. Seibert, Janet L. Stanford, Ole A. Andreassen, Henrik Grönberg, Monique J. Roobol, Sue A. Ingles, Catharine M L West, Hermann Brenner, Freddie C. Hamdy, Karina Dalsgaard Sørensen, Manuela Gago-Dominguez, Zsofia Kote-Jarai, Roshan Karunamuni, Robert J. Hamilton, Manuel R. Teixeira, Esther M. John, Azad Hassan Abdul Razack, Barry S. Rosenstein, Stella Koutros, Eleanor I Walsh, Artitaya Lophatananon, Sonja I. Berndt, Richard M. Martin, Adam S. Kibel, Robert J. MacInnis, David E. Neal, Ian G. Mills, Athene Lane, Susan L. Neuhausen, Anders M. Dale, Wei Zheng, Rosalind A. Eeles, Alicja Wolk, Catherine M. Tangen, Emma L Turner, Wesley K. Thompson, Manolis Kogevinas, Christopher A. Haiman, Paul A. Townsend, Demetrius Albanes, Eli Marie Grindedal, Jyotsna Batra, Jenny L Donovan, Sune F. Nielsen, Fredrik Wiklund, Lorelei A. Mucci, Kenneth Muir, Børge G. Nordestgaard, Christopher J. Logothetis, Nawaid Usmani, Christiane Maier, Cezary Cybulski, collaborators, UKGPCS, BioResource), APCB BioResource (Australian Prostate Cancer, Collaborators, IMPACT Study Steering Committee and, Investigators, Canary PASS, Committee, Profile Study Steering, Consortium, PRACTICAL, and Urology

Subjects
Oncology, Male, Cancer Research, 030232 urology & nephrology, Prostatic Neoplasms/epidemiology, SUSCEPTIBILITY, Prostate cancer, 0302 clinical medicine, Risk Factors, Cancer screening, Training set, medicine.diagnostic_test, Manchester Cancer Research Centre, Hazard ratio, Middle Aged, Prognosis, 030220 oncology & carcinogenesis, Risk stratification, ICEP, Biomarkers, Tumor/genetics, prostate cancer, SNPs (PHS166 vs PHS46), Adult, medicine.medical_specialty, Urology, Single-nucleotide polymorphism, Risk Assessment, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Predictive Value of Tests, Internal medicine, Biopsy, Biomarkers, Tumor, medicine, Humans, Risk Assessment/methods, Aged, Models, Statistical, Proportional hazards model, business.industry, ResearchInstitutes_Networks_Beacons/mcrc, Prostatic Neoplasms, medicine.disease, business, Follow-Up Studies
Abstract

Background Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46). Materials and method 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy. Results 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer. Conclusions Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Published
2021

15. African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer

Author

Ian M. Thompson, Roshan Karunamuni, Elizabeth T.H. Fontham, Tyler M. Seibert, Jennifer J. Hu, Jong Y. Park, Phyllis J. Goodman, Ian G. Mills, Luc Multigner, James L. Mohler, Jack A. Taylor, Anders M. Dale, Wei Zheng, Chun Fan, Bettina F. Drake, Jeannette T. Bensen, Florence Menegaux, Supriya Srivastava, Laurent Brureau, Wesley K. Thompson, Hui Yi Lin, Jay H. Fowke, Maureen Sanderson, Zsofia Kote-Jarai, Rosalind A. Eeles, Geraldine Cancel-Tassin, William Blot, Minh-Phuong Huynh-Le, Catherine M. Tangen, Melinda C. Aldrich, Olivier Cussenot, Gyorgy Petrovics, Ole A. Andreassen, Thérèse Truong, Jennifer Cullen, Robin J. Leach, Esther M. John, Artitaya Lophatananon, Pascal Blanchet, Marc Romana, Kenneth Muir, William S. Bush, Marie-Élise Parent, Dana C. Crawford, Adam S. Kibel, University of California [San Diego] (UC San Diego), University of California (UC), Healthlytix [San Diego], The Royal Marsden, The institute of cancer research [London], University of Manchester [Manchester], University of Warwick [Coventry], Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Vanderbilt University School of Engineering [Nashville] (VUSE), GeneDx [Gaithersburg, MD, USA], Brigham & Women’s Hospital [Boston] (BWH), Harvard Medical School [Boston] (HMS), Washington University in Saint Louis (WUSTL), Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, H. Lee Moffitt Cancer Center and Research Institute, Louisiana State University (LSU), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), National Institute of Environmental Health Sciences [Durham] (NIEHS-NIH), National Institutes of Health [Bethesda] (NIH), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Biologie Intégrée du Globule Rouge (BIGR (UMR_S_1134 / U1134)), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Université Paris Cité (UPCité), The University of Texas at San Antonio (UTSA), Stanford University, Vanderbilt University [Nashville], Case Western Reserve University [Cleveland], eResearch Collaboratory [Quebec City], McGill University = Université McGill [Montréal, Canada], University of Miami Leonard M. Miller School of Medicine (UMMSM), School of Medicine, Dentistry and Biomedical Sciences [Belfast], Queen's University [Belfast] (QUB), University of Oslo (UiO), KG Jebsen Stiftelsen, National Institute of Biomedical Imaging and BioengineeringUnited States Department of Health and Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Biomedical Imaging and Bioengineering (NIBIB) [K08EB026503], Research Council of NorwayResearch Council of Norway [223273], South East Norway Health Authority, U.S. Department of DefenseUnited States Department of Defense [W81XWH-13-1-0391], Chard-Hutchinson, Xavier, collaborators, UKGPCS, Consortium, PRACTICAL, University of California, Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Santé et de la Recherche Médicale (INSERM)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université d'Angers (UA), and Institut National de la Transfusion Sanguine [Paris] (INTS)-Université de La Réunion (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pointe-à-Pitre/Abymes [Guadeloupe] -Université des Antilles (UA)-Université de Paris (UP)

Subjects
Male, Cancer Research, Multifactorial Inheritance, Genotyping Techniques, [SDV]Life Sciences [q-bio], Age at diagnosis, Genome-wide association study, Prostate cancer, 0302 clinical medicine, Genotype, genome wide association study, 0303 health sciences, education.field_of_study, genotypic ancestry, Age Factors, Middle Aged, prostate cancer, Hazard, [SDV] Life Sciences [q-bio], Oncology, 030220 oncology & carcinogenesis, polygenic risk, Genetic genealogy, Population, Black People, Single-nucleotide polymorphism, [SDV.CAN]Life Sciences [q-bio]/Cancer, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, [SDV.CAN] Life Sciences [q-bio]/Cancer, SDG 3 - Good Health and Well-being, medicine, genomics, Humans, Genetic Predisposition to Disease, education, Proportional Hazards Models, 030304 developmental biology, Genetic association, health disparities, Models, Genetic, Proportional hazards model, business.industry, African, Prostatic Neoplasms, medicine.disease, Case-Control Studies, business, Demography
Abstract

IntroductionPolygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46), showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify SNPs that might improve performance in this population.Material and MethodsAnonymized genotypic data were obtained from the PRACTICAL consortium for 6,253 men with African genetic ancestry. Ten iterations of a ten-fold cross-validation search were conducted, to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African were compared using the same cross-validated approach.ResultsThree SNPs (rs76229939, rs74421890, and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47 to 4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65 to 0.53).ConclusionsWe identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans and Asians. A strategy of building on established statistical models might benefit ancestral groups generally under-represented in genome-wide association studies.

Published
2021

16. The relationship between lipoprotein A and other lipids with prostate cancer risk: A multivariable Mendelian randomisation study

Author

Ioannidou, A, Watts, EL, Perez-Cornago, A, Platz, EA, Mills, IG, Key, TJ, Travis, RC, PRACTICAL consortium, CRUK, BPC3, CAPS, PEGASUS, Tsilidis, KK, Zuber, V, consortium, PRACTICAL, CRUK, BPC3, CAPS, and PEGASUS

Subjects
Male, BLOOD, Epidemiology, Physiology, Single Nucleotide Polymorphisms, Prostatic Neoplasms/epidemiology, Biochemistry, Medicine and Health Sciences, EPIDEMIOLOGY, 11 Medical and Health Sciences, Cholesterol, HDL/blood, CHOLESTEROL, Prostate Cancer, Cancer Risk Factors, Prostate Diseases, ASSOCIATION, Genomics, General Medicine, Apolipoproteins/blood, Lipids, Body Fluids, Blood, Cholesterol, LDL/blood, Oncology, Medicine, lipids (amino acids, peptides, and proteins), ICEP, Anatomy, Research Article, GENETICS, Urology, Lipoproteins, Lipoprotein(a)/blood, SDG 3 - Good Health and Well-being, General & Internal Medicine, Genetics, Genome-Wide Association Studies, Humans, SERIES LIPOPROTEIN, Lipids/blood, Cholesterol, HDL, Prostatic Neoplasms, Cancers and Neoplasms, Biology and Life Sciences, Proteins, Computational Biology, Human Genetics, Cholesterol, LDL, Mendelian Randomization Analysis, Genome Analysis, PREVENTION, United Kingdom, Genitourinary Tract Tumors, Apolipoproteins, PRACTICAL consortium, CRUK, BPC3, CAPS, PEGASUS, Medical Risk Factors, APOLIPOPROTEINS, Genome-Wide Association Study, Lipoprotein(a)
Abstract

Background Numerous epidemiological studies have investigated the role of blood lipids in prostate cancer (PCa) risk, though findings remain inconclusive to date. The ongoing research has mainly involved observational studies, which are often prone to confounding. This study aimed to identify the relationship between genetically predicted blood lipid concentrations and PCa. Methods and findings Data for low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (TG), apolipoprotein A (apoA) and B (apoB), lipoprotein A (Lp(a)), and PCa were acquired from genome-wide association studies in UK Biobank and the PRACTICAL consortium, respectively. We used a two-sample summary-level Mendelian randomisation (MR) approach with both univariable and multivariable (MVMR) models and utilised a variety of robust methods and sensitivity analyses to assess the possibility of MR assumptions violation. No association was observed between genetically predicted concentrations of HDL, TG, apoA and apoB, and PCa risk. Genetically predicted LDL concentration was positively associated with total PCa in the univariable analysis, but adjustment for HDL, TG, and Lp(a) led to a null association. Genetically predicted concentration of Lp(a) was associated with higher total PCa risk in the univariable (ORweighted median per standard deviation (SD) = 1.091; 95% CI 1.028 to 1.157; P = 0.004) and MVMR analyses after adjustment for the other lipid traits (ORIVW per SD = 1.068; 95% CI 1.005 to 1.134; P = 0.034). Genetically predicted Lp(a) was also associated with advanced (MVMR ORIVW per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055) and early age onset PCa (MVMR ORIVW per SD = 1.150; 95% CI 1.015,1.303; P = 0.028). Although multiple estimation methods were utilised to minimise the effect of pleiotropy, the presence of any unmeasured pleiotropy cannot be excluded and may limit our findings. Conclusions We observed that genetically predicted Lp(a) concentrations were associated with an increased PCa risk. Future studies are required to understand the underlying biological pathways of this finding, as it may inform PCa prevention through Lp(a)-lowering strategies., Anna Ioannidou and colleagues investigate the relationship between genetically predicted blood lipid concentrations and prostate cancer., Author summary Why was this study done? Prostate cancer (PCa) is geographically and clinically very heterogeneous, and, as a result, its risk factors may differ according to disease aggressiveness. The established PCa risk factors are mainly non-modifiable, which challenge PCa prevention efforts. Previous observational research has identified associations between blood lipids and PCa, though results remain inconclusive. The aim of this study was to identify evidence for any association between several blood lipids (i.e., LDL, HDL, TG, apoA, apoB, and Lp(a)) and total, advanced, as well as early age onset PCa. What did the researchers do and find? The researchers used genetic variants that are known to be associated with each of the blood lipids, to test whether they were associated with any of the 3 PCa outcomes. This Mendelian randomisation (MR) analysis can reduce the existence of confounding factors and reverse causation, given that genetic variants are randomly allocated and independently assorted during meiosis. MR provides complementary evidence to observational research. This study provided evidence for a positive association between genetically predicted lipoprotein A (Lp(a)) concentrations, but not with other lipids, and risk of total, advanced, and early age onset PCa. What do these findings mean? Elevated Lp(a) could play a potentially important role in increasing the risk of PCa. It remains, however, unclear whether Lp(a) is the causal factor, given that its pathophysiological mechanisms have not been well studied. These findings provide rationale for further Lp(a) research to understand its functionality and role in PCa, which could lead to repurposing lipid drugs for high-risk individuals that target Lp(a) directly and study their effectiveness against PCa.

Published
2022

17. Alcohol Intake and Alcohol-SNP Interactions Associated with Prostate Cancer Aggressiveness.

Author

Lin HY, Wang X, Tseng TS, Kao YH, Fang Z, Molina PE, Cheng CH, Berglund AE, Eeles RA, Muir KR, Pashayan N, Haiman CA, Brenner H, Consortium TP, and Park JY

Abstract

Excessive alcohol intake is a well-known modifiable risk factor for many cancers. It is still unclear whether genetic variants or single nucleotide polymorphisms (SNPs) can modify alcohol intake's impact on prostate cancer (PCa) aggressiveness. The objective is to test the alcohol-SNP interactions of the 7501 SNPs in the four pathways (angiogenesis, mitochondria, miRNA, and androgen metabolism-related pathways) associated with PCa aggressiveness. We evaluated the impacts of three excessive alcohol intake behaviors in 3306 PCa patients with European ancestry from the PCa Consortium. We tested the alcohol-SNP interactions using logistic models with the discovery-validation study design. All three excessive alcohol intake behaviors were not significantly associated with PCa aggressiveness. However, the interactions of excessive alcohol intake and three SNPs (rs13107662 [ CAMK2D , p = 6.2 × 10 -6 ], rs9907521 [ PRKCA, p = 7.1 × 10 -5 ], and rs11925452 [ ROBO1, p = 8.2 × 10 -4 ]) were significantly associated with PCa aggressiveness. These alcohol-SNP interactions revealed contrasting effects of excessive alcohol intake on PCa aggressiveness according to the genotypes in the identified SNPs. We identified PCa patients with the rs13107662 ( CAMK2D ) AA genotype, the rs11925452 ( ROBO1 ) AA genotype, and the rs9907521 ( PRKCA) AG genotype were more vulnerable to excessive alcohol intake for developing aggressive PCa. Our findings support that the impact of excessive alcohol intake on PCa aggressiveness was varied by the selected genetic profiles., Competing Interests: All authors disclosed no potential conflicts of interest.

Published
2021
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