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1. Cluster effect for SNP–SNP interaction pairs for predicting complex traits

Author

Lin, Hui-Yi, Mazumder, Harun, Sarkar, Indrani, Huang, Po-Yu, Eeles, Rosalind A., Kote-Jarai, Zsofia, Muir, Kenneth R., Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, Neal, David E., Nielsen, Sune F., Nordestgaard, Børge G., Grönberg, Henrik, Wiklund, Fredrik, MacInnis, Robert J., Haiman, Christopher A., Travis, Ruth C., Stanford, Janet L., Kibel, Adam S., Cybulski, Cezary, Khaw, Kay-Tee, Maier, Christiane, Thibodeau, Stephen N., Teixeira, Manuel R., Cannon-Albright, Lisa, Brenner, Hermann, Kaneva, Radka, Pandha, Hardev, and Park, Jong Y.

Published
2024
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2. Circulating free insulin-like growth factor-I and prostate cancer: a case-control study nested in the European prospective investigation into cancer and nutrition

Author

Cheng, Tuck Seng, Noor, Urwah, Watts, Eleanor, Pollak, Michael, Wang, Ye, McKay, James, Atkins, Joshua, Masala, Giovanna, Sánchez, Maria-Jose, Agudo, Antonio, Castilla, Jesús, Aune, Dagfinn, Colorado-Yohar, Sandra M., Manfredi, Luca, Gunter, Marc J., Pala, Valeria, Josefsson, Andreas, Key, Timothy J., Smith-Byrne, Karl, and Travis, Ruth C.

Published
2024
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4. Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers

Author

Smith-Byrne, Karl, Hedman, Åsa, Dimitriou, Marios, Desai, Trishna, Sokolov, Alexandr V., Schioth, Helgi B., Koprulu, Mine, Pietzner, Maik, Langenberg, Claudia, Atkins, Joshua, Penha, Ricardo Cortez, McKay, James, Brennan, Paul, Zhou, Sirui, Richards, Brent J., Yarmolinsky, James, Martin, Richard M., Borlido, Joana, Mu, Xinmeng J., Butterworth, Adam, Shen, Xia, Wilson, Jim, Assimes, Themistocles L., Hung, Rayjean J., Amos, Christopher, Purdue, Mark, Rothman, Nathaniel, Chanock, Stephen, Travis, Ruth C., Johansson, Mattias, and Mälarstig, Anders

Published
2024
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5. Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score

Author

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

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Cancer, Urologic Diseases, Prevention, Genetics, Good Health and Well Being, Male, Humans, Prostate-Specific Antigen, Prostatic Neoplasms, Early Detection of Cancer, Polymorphism, Single Nucleotide, Risk Factors, Risk Assessment, Genetic Predisposition to Disease, UKGPCS collaborators, APCB, NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Urology & Nephrology, Clinical sciences, Oncology and carcinogenesis
Abstract

BackgroundProstate 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.MethodsIn 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.ResultsThe 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.ConclusionsWe 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

6. Circulating inflammatory and immune response proteins and endometrial cancer risk: a nested case-control study and Mendelian randomization analyses

Author

Wang, Sabrina E., Viallon, Vivian, Lee, Matthew, Dimou, Niki, Hamilton, Fergus, Biessy, Carine, O'Mara, Tracy, Kyrgiou, Maria, Crosbie, Emma J., Truong, Therese, Severi, Gianluca, Kaaks, Rudolf, Fortner, Renée Turzanski, Schulze, Matthias B., Bendinelli, Benedetta, Sabina, Sieri, Tumino, Rosario, Sacerdote, Carlotta, Panico, Salvatore, Crous-Bou, Marta, Sánchez, Maria-Jose, Aizpurua, Amaia, Palacios, Daniel Rodriguez, Guevara, Marcela, Travis, Ruth C., Tsilidis, Konstantinos K., Heath, Alicia, Yarmolinsky, James, Rinaldi, Sabina, Gunter, Marc J., and Dossus, Laure

Published
2024
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8. Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics

Author

Desai, Trishna A., Hedman, Åsa K., Dimitriou, Marios, Koprulu, Mine, Figiel, Sandy, Yin, Wencheng, Johansson, Mattias, Watts, Eleanor L., Atkins, Joshua R., Sokolov, Aleksandr V., Schiöth, Helgi B., Gunter, Marc J., Tsilidis, Konstantinos K., Martin, Richard M., Pietzner, Maik, Langenberg, Claudia, Mills, Ian G., Lamb, Alastair D., Mälarstig, Anders, Key, Tim J., Travis, Ruth C., and Smith-Byrne, Karl

Published
2024
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9. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Landi, Maria Teresa, Stevens, Victoria, Wang, Ying, Albanes, Demetrios, Caporaso, Neil, Brennan, Paul, Amos, Christopher I., Shete, Sanjay, Hung, Rayjean J., Bickeböller, Heike, Risch, Angela, Houlston, Richard, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Wichmann, H-Erich, Christiani, David, Rennert, Gadi, Arnold, Susanne, Field, John K., Le Marchand, Loic, Melander, Olle, Brunnström, Hans, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A., Shen, Hongbing, Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Teare, M. Dawn, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Al Olama, Ali Amin, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanfrod, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Logothetis, Christopher J., John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Yarmolinsky, James, Robinson, Jamie W., Mariosa, Daniela, Karhunen, Ville, Huang, Jian, Dimou, Niki, Murphy, Neil, Burrows, Kimberley, Bouras, Emmanouil, Smith-Byrne, Karl, Lewis, Sarah J., Galesloot, Tessel E., Vermeulen, Sita, Martin, Paul, Hou, Lifang, Newcomb, Polly A., White, Emily, Wu, Anna H., Le Marchand, Loïc, Phipps, Amanda I., Buchanan, Daniel D., Zhao, Sizheng Steven, Gill, Dipender, Chanock, Stephen J., Purdue, Mark P., Davey Smith, George, Herzig, Karl-Heinz, Järvelin, Marjo-Riitta, Amos, Chris I., Dehghan, Abbas, Gunter, Marc J., Tsilidis, Kostas K., and Martin, Richard M.

Published
2024
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10. Genetically predicted circulating concentrations of micronutrients and risk of colorectal cancer among individuals of European descent: a Mendelian randomization study

Author

Tsilidis, Konstantinos K, Papadimitriou, Nikos, Dimou, Niki, Gill, Dipender, Lewis, Sarah J, Martin, Richard M, Murphy, Neil, Markozannes, Georgios, Zuber, Verena, Cross, Amanda J, Burrows, Kimberley, Lopez, David S, Key, Timothy J, Travis, Ruth C, Perez-Cornago, Aurora, Hunter, David J, van Duijnhoven, Fränzel JB, Albanes, Demetrius, Arndt, Volker, Berndt, Sonja I, Bézieau, Stéphane, Bishop, D Timothy, Boehm, Juergen, Brenner, Hermann, Burnett-Hartman, Andrea, Campbell, Peter T, Casey, Graham, Castellví-Bel, Sergi, Chan, Andrew T, Chang-Claude, Jenny, de la Chapelle, Albert, Figueiredo, Jane C, Gallinger, Steven J, Giles, Graham G, Goodman, Phyllis J, Gsur, Andrea, Hampe, Jochen, Hampel, Heather, Hoffmeister, Michael, Jenkins, Mark A, Keku, Temitope O, Kweon, Sun-Seog, Larsson, Susanna C, Le Marchand, Loic, Li, Christopher I, Li, Li, Lindblom, Annika, Martín, Vicente, Milne, Roger L, Moreno, Victor, Nan, Hongmei, Nassir, Rami, Newcomb, Polly A, Offit, Kenneth, Pharoah, Paul DP, Platz, Elizabeth A, Potter, John D, Qi, Lihong, Rennert, Gad, Sakoda, Lori C, Schafmayer, Clemens, Slattery, Martha L, Snetselaar, Linda, Schenk, Jeanette, Thibodeau, Stephen N, Ulrich, Cornelia M, Van Guelpen, Bethany, Harlid, Sophia, Visvanathan, Kala, Vodickova, Ludmila, Wang, Hansong, White, Emily, Wolk, Alicja, Woods, Michael O, Wu, Anna H, Zheng, Wei, Bueno-de-Mesquita, Bas, Boutron-Ruault, Marie-Christine, Hughes, David J, Jakszyn, Paula, Kühn, Tilman, Palli, Domenico, Riboli, Elio, Giovannucci, Edward L, Banbury, Barbara L, Gruber, Stephen B, Peters, Ulrike, Gunter, Marc J, and on behalf of GECCO, CORECT

Subjects
Complementary and Integrative Health, Digestive Diseases, Clinical Research, Clinical Trials and Supportive Activities, Cancer, Colo-Rectal Cancer, Prevention, Nutrition, Prevention of disease and conditions, and promotion of well-being, 3.3 Nutrition and chemoprevention, Case-Control Studies, Colorectal Neoplasms, Dietary Supplements, Genetic Predisposition to Disease, Humans, Mendelian Randomization Analysis, Micronutrients, Risk Factors, Selenium, Vitamin B 12, White People, Mendelian randomization, genes, nutrition, supplements, colorectal cancer, Engineering, Medical and Health Sciences, Nutrition & Dietetics
Abstract

BackgroundThe literature on associations of circulating concentrations of minerals and vitamins with risk of colorectal cancer is limited and inconsistent. Evidence from randomized controlled trials (RCTs) to support the efficacy of dietary modification or nutrient supplementation for colorectal cancer prevention is also limited.ObjectivesTo complement observational and RCT findings, we investigated associations of genetically predicted concentrations of 11 micronutrients (β-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B-6, vitamin B-12, and zinc) with colorectal cancer risk using Mendelian randomization (MR).MethodsTwo-sample MR was conducted using 58,221 individuals with colorectal cancer and 67,694 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. Inverse variance-weighted MR analyses were performed with sensitivity analyses to assess the impact of potential violations of MR assumptions.ResultsNominally significant associations were noted for genetically predicted iron concentration and higher risk of colon cancer [ORs per SD (ORSD): 1.08; 95% CI: 1.00, 1.17; P value = 0.05] and similarly for proximal colon cancer, and for vitamin B-12 concentration and higher risk of colorectal cancer (ORSD: 1.12; 95% CI: 1.03, 1.21; P value = 0.01) and similarly for colon cancer. A nominally significant association was also noted for genetically predicted selenium concentration and lower risk of colon cancer (ORSD: 0.98; 95% CI: 0.96, 1.00; P value = 0.05) and similarly for distal colon cancer. These associations were robust to sensitivity analyses. Nominally significant inverse associations were observed for zinc and risk of colorectal and distal colon cancers, but sensitivity analyses could not be performed. None of these findings survived correction for multiple testing. Genetically predicted concentrations of β-carotene, calcium, copper, folate, magnesium, phosphorus, and vitamin B-6 were not associated with disease risk.ConclusionsThese results suggest possible causal associations of circulating iron and vitamin B-12 (positively) and selenium (inversely) with risk of colon cancer.

Published
2021

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

Author

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

Subjects
UKGPCS collaborators, APCB BioResource, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Prevention, Urologic Diseases, Cancer, Prostate Cancer, Aging, Urology & Nephrology, Oncology and Carcinogenesis
Abstract

BackgroundPolygenic 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 method180 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.Results166 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.ConclusionsIncorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Published
2021

12. Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.

Author

Huynh-Le, Minh-Phuong, Fan, Chun Chieh, Karunamuni, Roshan, Thompson, Wesley K, Martinez, Maria Elena, Eeles, Rosalind A, Kote-Jarai, Zsofia, Muir, Kenneth, Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, Grönberg, Henrik, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Nielsen, Sune F, Nordestgaard, Børge G, Wiklund, Fredrik, Tangen, Catherine M, Giles, Graham G, Wolk, Alicja, Albanes, Demetrius, Travis, Ruth C, Blot, William J, Zheng, Wei, Sanderson, Maureen, Stanford, Janet L, Mucci, Lorelei A, West, Catharine ML, Kibel, Adam S, Cussenot, Olivier, Berndt, Sonja I, Koutros, Stella, Sørensen, Karina Dalsgaard, Cybulski, Cezary, Grindedal, Eli Marie, Menegaux, Florence, Khaw, Kay-Tee, Park, Jong Y, Ingles, Sue A, Maier, Christiane, Hamilton, Robert J, Thibodeau, Stephen N, Rosenstein, Barry S, Lu, Yong-Jie, Watya, Stephen, Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L, Huff, Chad, Teixeira, Manuel R, Multigner, Luc, Leach, Robin J, Cannon-Albright, Lisa, Brenner, Hermann, John, Esther M, Kaneva, Radka, Logothetis, Christopher J, Neuhausen, Susan L, De Ruyck, Kim, Pandha, Hardev, Razack, Azad, Newcomb, Lisa F, Fowke, Jay H, Gamulin, Marija, Usmani, Nawaid, Claessens, Frank, Gago-Dominguez, Manuela, Townsend, Paul A, Bush, William S, Roobol, Monique J, Parent, Marie-Élise, Hu, Jennifer J, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, UKGPCS collaborators, APCB (Australian Prostate Cancer BioResource), NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, and PRACTICAL Consortium

Subjects
UKGPCS collaborators, APCB, NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Humans, Prostatic Neoplasms, Neoplasm Invasiveness, Multivariate Analysis, Multifactorial Inheritance, Aged, Middle Aged, Ethnic Groups, Male, Self Report, Aging, Urologic Diseases, Cancer, Prostate Cancer
Abstract

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p

Published
2021

13. The effect of sample size on polygenic hazard models for prostate cancer

Author

Karunamuni, Roshan A, Huynh-Le, Minh-Phuong, Fan, Chun C, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, ZSofia, Amin Al Olama, Ali, Benlloch Garcia, Sara, Muir, Kenneth, Gronberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo LJ, Nordestgaard, Børge G, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Brenner, Hermann, Schöttker, Ben, Holleczek, Bernd, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, and Seibert, Tyler M

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Cancer, Aging, Urologic Diseases, Clinical Trials as Topic, Genome-Wide Association Study, Humans, Male, Models, Genetic, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Proportional Hazards Models, Prostatic Neoplasms, Sample Size, Australian Prostate Cancer BioResource, PRACTICAL Consortium, Genetics, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

Published
2020

14. A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

Author

Huynh-Le, Minh-Phuong, Fan, Chun Chieh, Karunamuni, Roshan, Walsh, Eleanor I, Turner, Emma L, Lane, J Athene, Martin, Richard M, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Parsons, J Kellogg, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Garcia, Sara Benlloch, Muir, Kenneth, Grönberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo LJ, Nordestgaard, Børge Grønne, Key, Timothy J, Travis, Ruth C, Pharoah, Paul DP, Pashayan, Nora, Khaw, Kay-Tee, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa A, Brenner, Hermann, Schöttker, Ben, Holleczek, Bernd, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar Kroumov, Kaneva, Radka P, Mitev, Vanio I, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda B, BioResource, for the Australian Prostate Cancer, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, and Consortium, for the PRACTICAL

Subjects
Biomedical and Clinical Sciences, Health Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Cancer, Prevention, Urologic Diseases, Good Health and Well Being, Aged, Early Detection of Cancer, Humans, Male, Middle Aged, Neoplasm Grading, Population Control, Prostatic Neoplasms, Australian Prostate Cancer BioResource, PRACTICAL Consortium, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundA polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.ResultsThe expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.ImpactPersonalized genetic risk assessments could inform prostate cancer screening decisions.

Published
2020

15. The associations of anthropometric, behavioural and sociodemographic factors with circulating concentrations of IGF‐I, IGF‐II, IGFBP‐1, IGFBP‐2 and IGFBP‐3 in a pooled analysis of 16,024 men from 22 studies

Author

Watts, Eleanor L, Perez‐Cornago, Aurora, Appleby, Paul N, Albanes, Demetrius, Ardanaz, Eva, Black, Amanda, Bueno‐de‐Mesquita, H Bas, Chan, June M, Chen, Chu, Chubb, SA Paul, Cook, Michael B, Deschasaux, Mélanie, Donovan, Jenny L, English, Dallas R, Flicker, Leon, Freedman, Neal D, Galan, Pilar, Giles, Graham G, Giovannucci, Edward L, Gunter, Marc J, Habel, Laurel A, Häggström, Christel, Haiman, Christopher, Hamdy, Freddie C, Hercberg, Serge, Holly, Jeff M, Huang, Jiaqi, Huang, Wen‐Yi, Johansson, Mattias, Kaaks, Rudolf, Kubo, Tatsuhiko, Lane, J Athene, Layne, Tracy M, Le Marchand, Loic, Martin, Richard M, Metter, E Jeffrey, Mikami, Kazuya, Milne, Roger L, Morris, Howard A, Mucci, Lorelei A, Neal, David E, Neuhouser, Marian L, Oliver, Steven E, Overvad, Kim, Ozasa, Kotaro, Pala, Valeria, Pernar, Claire H, Pollak, Michael, Rowlands, Mari‐Anne, Schaefer, Catherine A, Schenk, Jeannette M, Stattin, Pär, Tamakoshi, Akiko, Thysell, Elin, Touvier, Mathilde, Trichopoulou, Antonia, Tsilidis, Konstantinos K, Van Den Eeden, Stephen K, Weinstein, Stephanie J, Wilkens, Lynne, Yeap, Bu B, Key, Timothy J, Allen, Naomi E, and Travis, Ruth C

Subjects
Cancer, Aging, Urologic Diseases, Adult, Aged, Aged, 80 and over, Anthropometry, Biomarkers, Tumor, Cross-Sectional Studies, Humans, Insulin-Like Growth Factor Binding Proteins, Insulin-Like Growth Factor I, Insulin-Like Growth Factor II, Male, Middle Aged, Neoplasms, Prospective Studies, Young Adult, IGFs, IGFBPs, pooled analysis, correlates, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Insulin-like growth factors (IGFs) and insulin-like growth factor binding proteins (IGFBPs) have been implicated in the aetiology of several cancers. To better understand whether anthropometric, behavioural and sociodemographic factors may play a role in cancer risk via IGF signalling, we examined the cross-sectional associations of these exposures with circulating concentrations of IGFs (IGF-I and IGF-II) and IGFBPs (IGFBP-1, IGFBP-2 and IGFBP-3). The Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset includes individual participant data from 16,024 male controls (i.e. without prostate cancer) aged 22-89 years from 22 prospective studies. Geometric means of protein concentrations were estimated using analysis of variance, adjusted for relevant covariates. Older age was associated with higher concentrations of IGFBP-1 and IGFBP-2 and lower concentrations of IGF-I, IGF-II and IGFBP-3. Higher body mass index was associated with lower concentrations of IGFBP-1 and IGFBP-2. Taller height was associated with higher concentrations of IGF-I and IGFBP-3 and lower concentrations of IGFBP-1. Smokers had higher concentrations of IGFBP-1 and IGFBP-2 and lower concentrations of IGFBP-3 than nonsmokers. Higher alcohol consumption was associated with higher concentrations of IGF-II and lower concentrations of IGF-I and IGFBP-2. African Americans had lower concentrations of IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 and Hispanics had lower IGF-I, IGF-II and IGFBP-3 than non-Hispanic whites. These findings indicate that a range of anthropometric, behavioural and sociodemographic factors are associated with circulating concentrations of IGFs and IGFBPs in men, which will lead to a greater understanding of the mechanisms through which these factors influence cancer risk.

Published
2019

16. Anti-cancer therapy is associated with long-term epigenomic changes in childhood cancer survivors

Author

Robinson, Natassia, Casement, John, Gunter, Marc J., Huybrechts, Inge, Agudo, Antonio, Barranco, Miguel Rodríguez, Eichelmann, Fabian, Johnson, Theron, Kaaks, Rudolf, Pala, Valeria, Panico, Salvatore, Sandanger, Torkjel M., Schultze, Matthias B., Travis, Ruth C., Tumino, Rosario, Vineis, Paolo, Weiderpass, Elisabete, Skinner, Roderick, Sharp, Linda, McKay, Jill A, and Strathdee, Gordon

Published
2022
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17. Genetic overlap between autoimmune diseases and non‐Hodgkin lymphoma subtypes

Author

Din, Lennox, Sheikh, Mohammad, Kosaraju, Nikitha, Smedby, Karin Ekstrom, Bernatsky, Sasha, Berndt, Sonja I, Skibola, Christine F, Nieters, Alexandra, Wang, Sophia, McKay, James D, Cocco, Pierluigi, Maynadié, Marc, Foretová, Lenka, Staines, Anthony, Mack, Thomas M, de Sanjosé, Silvia, Vyse, Timothy J, Padyukov, Leonid, Monnereau, Alain, Arslan, Alan A, Moore, Amy, Brooks‐Wilson, Angela R, Novak, Anne J, Glimelius, Bengt, Birmann, Brenda M, Link, Brian K, Stewart, Carolyn, Vajdic, Claire M, Haioun, Corinne, Magnani, Corrado, Conti, David V, Cox, David G, Casabonne, Delphine, Albanes, Demetrius, Kane, Eleanor, Roman, Eve, Muzi, Giacomo, Salles, Gilles, Giles, Graham G, Adami, Hans‐Olov, Ghesquières, Hervé, De Vivo, Immaculata, Clavel, Jacqueline, Cerhan, James R, Spinelli, John J, Hofmann, Jonathan, Vijai, Joseph, Curtin, Karen, Costenbader, Karen H, Onel, Kenan, Offit, Kenneth, Teras, Lauren R, Morton, Lindsay, Conde, Lucia, Miligi, Lucia, Melbye, Mads, Ennas, Maria Grazia, Liebow, Mark, Purdue, Mark P, Glenn, Martha, Southey, Melissa C, Din, Morris, Rothman, Nathaniel, Camp, Nicola J, Doo, Nicole Wong, Becker, Nikolaus, Pradhan, Nisha, Bracci, Paige M, Boffetta, Paolo, Vineis, Paolo, Brennan, Paul, Kraft, Peter, Lan, Qing, Severson, Richard K, Vermeulen, Roel CH, Milne, Roger L, Kaaks, Rudolph, Travis, Ruth C, Weinstein, Stephanie J, Chanock, Stephen J, Ansell, Stephen M, Slager, Susan L, Zheng, Tongzhang, Zhang, Yawei, Benavente, Yolanda, Taub, Zachary, Madireddy, Lohith, Gourraud, Pierre‐Antoine, Oksenberg, Jorge R, Cozen, Wendy, Hjalgrim, Henrik, and Khankhanian, Pouya

Subjects
Biological Sciences, Genetics, Lymphoma, Arthritis, Neurodegenerative, Brain Disorders, Autoimmune Disease, Cancer, Human Genome, Rare Diseases, Hematology, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Alleles, Autoimmune Diseases, Female, Genetic Predisposition to Disease, HLA Antigens, Humans, Lymphoma, Non-Hodgkin, Male, Middle Aged, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Risk Factors, autoimmune disease, genome-wide association study, meta-analysis, non-Hodgkin lymphoma, Public Health and Health Services, Epidemiology
Abstract

Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.

Published
2019

18. Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry.

Author

Matejcic, Marco, Saunders, Edward J, Dadaev, Tokhir, Brook, Mark N, Wang, Kan, Sheng, Xin, Olama, Ali Amin Al, Schumacher, Fredrick R, Ingles, Sue A, Govindasami, Koveela, Benlloch, Sara, Berndt, Sonja I, Albanes, Demetrius, Koutros, Stella, Muir, Kenneth, Stevens, Victoria L, Gapstur, Susan M, Tangen, Catherine M, Batra, Jyotsna, Clements, Judith, Gronberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Wolk, Alicja, West, Catharine, Mucci, Lorelei, Kraft, Peter, Cancel-Tassin, Géraldine, Sorensen, Karina D, Maehle, Lovise, Grindedal, Eli M, Strom, Sara S, Neal, David E, Hamdy, Freddie C, Donovan, Jenny L, Travis, Ruth C, Hamilton, Robert J, Rosenstein, Barry, Lu, Yong-Jie, Giles, Graham G, Kibel, Adam S, Vega, Ana, Bensen, Jeanette T, Kogevinas, Manolis, Penney, Kathryn L, Park, Jong Y, Stanford, Janet L, Cybulski, Cezary, Nordestgaard, Børge G, Brenner, Hermann, Maier, Christiane, Kim, Jeri, Teixeira, Manuel R, Neuhausen, Susan L, De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F, Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A, Gago-Dominguez, Manuela, Roobol, Monique J, Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa A, Pandha, Hardev, Thibodeau, Stephen N, Schaid, Daniel J, PRACTICAL Consortium, Wiklund, Fredrik, Chanock, Stephen J, Easton, Douglas F, Eeles, Rosalind A, Kote-Jarai, Zsofia, Conti, David V, and Haiman, Christopher A

Subjects
PRACTICAL Consortium
Abstract

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Published
2019

19. A collaborative analysis of individual participant data from 19 prospective studies assesses circulating vitamin D and prostate cancer risk

Author

Travis, Ruth C, Perez-Cornago, Aurora, Appleby, Paul N, Albanes, Demetrius, Joshu, Corinne E, Lutsey, Pamela L, Mondul, Alison M, Platz, Elizabeth A, Weinstein, Stephanie J, Layne, Tracy M, Helzlsouer, Kathy J, Visvanathan, Kala, Palli, Domenico, Peeters, Petra H, Bueno-de-Mesquita, Bas, Trichopoulou, Antonia, Gunter, Marc J, Tsilidis, Konstantinos K, Sánchez, Maria-Jose, Olsen, Anja, Brenner, Hermann, Schöttker, Ben, Perna, Laura, Holleczek, Bernd, Knekt, Paul, Rissanen, Harri, Yeap, Bu B, Flicker, Leon, Almeida, Osvaldo P, Wong, Yuen Yee Elizabeth, Chan, June M, Giovannucci, Edward L, Stampfer, Meir J, Ursin, Giske, Gislefoss, Randi E, Bjørge, Tone, Meyer, Haakon E, Blomhoff, Rune, Tsugane, Shoichiro, Sawada, Norie, English, Dallas R, Eyles, Darryl W, Heath, Alicia K, Williamson, Elizabeth J, Manjer, Jonas, Malm, Johan, Almquist, Martin, Marchand, Loic Le, Haiman, Christopher A, Wilkens, Lynne R, Schenk, Jeannette M, Tangen, Cathy M, Black, Amanda, Cook, Michael B, Huang, Wen-Yi, Ziegler, Regina G, Martin, Richard M, Hamdy, Freddie C, Donovan, Jenny L, Neal, David E, Touvier, Mathilde, Hercberg, Serge, Galan, Pilar, Deschasaux, Mélanie, Key, Timothy J, and Allen, Naomi E

Subjects
Clinical Trials and Supportive Activities, Nutrition, Cancer, Prostate Cancer, Urologic Diseases, Prevention, Aging, Clinical Research, Aged, Case-Control Studies, Cross-Sectional Studies, Humans, Male, Middle Aged, Odds Ratio, Prospective Studies, Prostatic Neoplasms, Risk Assessment, Risk Factors, Vitamin D, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Previous prospective studies assessing the relationship between circulating concentrations of vitamin D and prostate cancer risk have shown inconclusive results, particularly for risk of aggressive disease. In this study, we examine the association between prediagnostic concentrations of 25-hydroxyvitamin D [25(OH)D] and 1,25-dihydroxyvitamin D [1,25(OH)2D] and the risk of prostate cancer overall and by tumor characteristics. Principal investigators of 19 prospective studies provided individual participant data on circulating 25(OH)D and 1,25(OH)2D for up to 13,462 men with incident prostate cancer and 20,261 control participants. ORs for prostate cancer by study-specific fifths of season-standardized vitamin D concentration were estimated using multivariable-adjusted conditional logistic regression. 25(OH)D concentration was positively associated with risk for total prostate cancer (multivariable-adjusted OR comparing highest vs. lowest study-specific fifth was 1.22; 95% confidence interval, 1.13-1.31; P trend < 0.001). However, this association varied by disease aggressiveness (P heterogeneity = 0.014); higher circulating 25(OH)D was associated with a higher risk of nonaggressive disease (OR per 80 percentile increase = 1.24, 1.13-1.36) but not with aggressive disease (defined as stage 4, metastases, or prostate cancer death, 0.95, 0.78-1.15). 1,25(OH)2D concentration was not associated with risk for prostate cancer overall or by tumor characteristics. The absence of an association of vitamin D with aggressive disease does not support the hypothesis that vitamin D deficiency increases prostate cancer risk. Rather, the association of high circulating 25(OH)D concentration with a higher risk of nonaggressive prostate cancer may be influenced by detection bias. SIGNIFICANCE: This international collaboration comprises the largest prospective study on blood vitamin D and prostate cancer risk and shows no association with aggressive disease but some evidence of a higher risk of nonaggressive disease.

Published
2019

20. Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer

Author

Mukama, Trasias, Fortner, Renée Turzanski, Katzke, Verena, Hynes, Lucas Cory, Petrera, Agnese, Hauck, Stefanie M., Johnson, Theron, Schulze, Matthias, Schiborn, Catarina, Rostgaard-Hansen, Agnetha Linn, Tjønneland, Anne, Overvad, Kim, Pérez, María José Sánchez, Crous-Bou, Marta, Chirlaque, María-Dolores, Amiano, Pilar, Ardanaz, Eva, Watts, Eleanor L., Travis, Ruth C., Sacerdote, Carlotta, Grioni, Sara, Masala, Giovanna, Signoriello, Simona, Tumino, Rosario, Gram, Inger T., Sandanger, Torkjel M., Sartor, Hanna, Lundin, Eva, Idahl, Annika, Heath, Alicia K., Dossus, Laure, Weiderpass, Elisabete, and Kaaks, Rudolf

Published
2022
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21. Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition

Author

Breeur, Marie, Ferrari, Pietro, Dossus, Laure, Jenab, Mazda, Johansson, Mattias, Rinaldi, Sabina, Travis, Ruth C., His, Mathilde, Key, Tim J., Schmidt, Julie A., Overvad, Kim, Tjønneland, Anne, Kyrø, Cecilie, Rothwell, Joseph A., Laouali, Nasser, Severi, Gianluca, Kaaks, Rudolf, Katzke, Verena, Schulze, Matthias B., Eichelmann, Fabian, Palli, Domenico, Grioni, Sara, Panico, Salvatore, Tumino, Rosario, Sacerdote, Carlotta, Bueno-de-Mesquita, Bas, Olsen, Karina Standahl, Sandanger, Torkjel Manning, Nøst, Therese Haugdahl, Quirós, J. Ramón, Bonet, Catalina, Barranco, Miguel Rodríguez, Chirlaque, María-Dolores, Ardanaz, Eva, Sandsveden, Malte, Manjer, Jonas, Vidman, Linda, Rentoft, Matilda, Muller, David, Tsilidis, Kostas, Heath, Alicia K., Keun, Hector, Adamski, Jerzy, Keski-Rahkonen, Pekka, Scalbert, Augustin, Gunter, Marc J., and Viallon, Vivian

Published
2022
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23. Circulating inflammatory biomarkers, adipokines and breast cancer risk—a case-control study nested within the EPIC cohort

Author

Cairat, Manon, Rinaldi, Sabina, Navionis, Anne-Sophie, Romieu, Isabelle, Biessy, Carine, Viallon, Vivian, Olsen, Anja, Tjønneland, Anne, Fournier, Agnès, Severi, Gianluca, Kvaskoff, Marina, Fortner, Renée T., Kaaks, Rudolf, Aleksandrova, Krasimira, Schulze, Matthias B., Masala, Giovanna, Tumino, Rosario, Sieri, Sabina, Grasso, Chiara, Mattiello, Amalia, Gram, Inger T., Olsen, Karina Standahl, Agudo, Antonio, Etxezarreta, Pilar Amiano, Sánchez, Maria-Jose, Santiuste, Carmen, Barricarte, Aurelio, Monninkhof, Evelyn, Hiensch, Anouk E., Muller, David, Merritt, Melissa A., Travis, Ruth C., Weiderpass, Elisabete, Gunter, Marc J., and Dossus, Laure

Published
2022
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25. Low Free Testosterone and Prostate Cancer Risk: A Collaborative Analysis of 20 Prospective Studies

Author

Watts, Eleanor L, Appleby, Paul N, Perez-Cornago, Aurora, Bueno-de-Mesquita, H Bas, Chan, June M, Chen, Chu, Cohn, Barbara A, Cook, Michael B, Flicker, Leon, Freedman, Neal D, Giles, Graham G, Giovannucci, Edward, Gislefoss, Randi E, Hankey, Graeme J, Kaaks, Rudolf, Knekt, Paul, Kolonel, Laurence N, Kubo, Tatsuhiko, Le Marchand, Loïc, Luben, Robert N, Luostarinen, Tapio, Männistö, Satu, Metter, E Jeffrey, Mikami, Kazuya, Milne, Roger L, Ozasa, Kotaro, Platz, Elizabeth A, Quirós, J Ramón, Rissanen, Harri, Sawada, Norie, Stampfer, Meir, Stanczyk, Frank Z, Stattin, Pär, Tamakoshi, Akiko, Tangen, Catherine M, Thompson, Ian M, Tsilidis, Konstantinos K, Tsugane, Shoichiro, Ursin, Giske, Vatten, Lars, Weiss, Noel S, Yeap, Bu B, Allen, Naomi E, Key, Timothy J, and Travis, Ruth C

Subjects
Cancer, Clinical Research, Prevention, Urologic Diseases, Prostate Cancer, Aging, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Biomarkers, Case-Control Studies, Down-Regulation, Humans, Male, Middle Aged, Neoplasm Grading, Prospective Studies, Prostatic Neoplasms, Protective Factors, Risk Assessment, Risk Factors, Testosterone, Time Factors, Androgens Pooled analysis, Prospective studies, Prostate cancer, Sex hormones, Epidemiology, Androgens, Pooled analysis, Clinical Sciences, Urology & Nephrology
Abstract

BackgroundExperimental and clinical evidence implicates testosterone in the aetiology of prostate cancer. Variation across the normal range of circulating free testosterone concentrations may not lead to changes in prostate biology, unless circulating concentrations are low. This may also apply to prostate cancer risk, but this has not been investigated in an epidemiological setting.ObjectiveTo examine whether men with low concentrations of circulating free testosterone have a reduced risk of prostate cancer.Design, setting, and participantsAnalysis of individual participant data from 20 prospective studies including 6933 prostate cancer cases, diagnosed on average 6.8 yr after blood collection, and 12 088 controls in the Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group.Outcome measurements and statistical analysisOdds ratios (ORs) of incident overall prostate cancer and subtypes by stage and grade, using conditional logistic regression, based on study-specific tenths of calculated free testosterone concentration.Results and limitationsMen in the lowest tenth of free testosterone concentration had a lower risk of overall prostate cancer (OR=0.77, 95% confidence interval [CI] 0.69-0.86; p

Published
2018

26. Prediction of acute myeloid leukaemia risk in healthy individuals.

Author

Abelson, Sagi, Collord, Grace, Ng, Stanley WK, Weissbrod, Omer, Mendelson Cohen, Netta, Niemeyer, Elisabeth, Barda, Noam, Zuzarte, Philip C, Heisler, Lawrence, Sundaravadanam, Yogi, Luben, Robert, Hayat, Shabina, Wang, Ting Ting, Zhao, Zhen, Cirlan, Iulia, Pugh, Trevor J, Soave, David, Ng, Karen, Latimer, Calli, Hardy, Claire, Raine, Keiran, Jones, David, Hoult, Diana, Britten, Abigail, McPherson, John D, Johansson, Mattias, Mbabaali, Faridah, Eagles, Jenna, Miller, Jessica K, Pasternack, Danielle, Timms, Lee, Krzyzanowski, Paul, Awadalla, Philip, Costa, Rui, Segal, Eran, Bratman, Scott V, Beer, Philip, Behjati, Sam, Martincorena, Inigo, Wang, Jean CY, Bowles, Kristian M, Quirós, J Ramón, Karakatsani, Anna, La Vecchia, Carlo, Trichopoulou, Antonia, Salamanca-Fernández, Elena, Huerta, José M, Barricarte, Aurelio, Travis, Ruth C, Tumino, Rosario, Masala, Giovanna, Boeing, Heiner, Panico, Salvatore, Kaaks, Rudolf, Krämer, Alwin, Sieri, Sabina, Riboli, Elio, Vineis, Paolo, Foll, Matthieu, McKay, James, Polidoro, Silvia, Sala, Núria, Khaw, Kay-Tee, Vermeulen, Roel, Campbell, Peter J, Papaemmanuil, Elli, Minden, Mark D, Tanay, Amos, Balicer, Ran D, Wareham, Nicholas J, Gerstung, Moritz, Dick, John E, Brennan, Paul, Vassiliou, George S, and Shlush, Liran I

Subjects
Humans, Disease Progression, Genetic Predisposition to Disease, Prevalence, Risk Assessment, Age Factors, Mutagenesis, Mutation, Models, Genetic, Adult, Aged, Middle Aged, Health, Female, Male, Leukemia, Myeloid, Acute, Electronic Health Records, Models, Genetic, Leukemia, Myeloid, Acute, General Science & Technology
Abstract

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure1. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion2,3. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)4-8. Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

Published
2018

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

Author

Schumacher, Fredrick R, Al Olama, Ali Amin, Berndt, Sonja I, Benlloch, Sara, Ahmed, Mahbubl, Saunders, Edward J, Dadaev, Tokhir, Leongamornlert, Daniel, Anokian, Ezequiel, Cieza-Borrella, Clara, Goh, Chee, Brook, Mark N, Sheng, Xin, Fachal, Laura, Dennis, Joe, Tyrer, Jonathan, 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, Moya, Leire, Clements, Judith, Horvath, Lisa, Tilley, Wayne, Risbridger, Gail P, Gronberg, Henrik, Aly, Markus, Nordström, Tobias, Pharoah, Paul, Pashayan, Nora, Schleutker, Johanna, Tammela, Teuvo LJ, Sipeky, Csilla, Auvinen, Anssi, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, Håkansson, Niclas, West, Catharine ML, Dunning, Alison M, Burnet, Neil, Mucci, Lorelei A, Giovannucci, Edward, Andriole, Gerald L, Cussenot, Olivier, Cancel-Tassin, Géraldine, Koutros, Stella, Beane Freeman, Laura E, Sorensen, Karina Dalsgaard, Orntoft, Torben Falck, Borre, Michael, Maehle, Lovise, Grindedal, Eli Marie, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Travis, Ruth C, Key, Tim J, Hamilton, Robert J, Fleshner, Neil E, Finelli, Antonio, Ingles, Sue Ann, Stern, Mariana C, Rosenstein, Barry S, Kerns, Sarah L, Ostrer, Harry, Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, 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, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Stanford, Janet L, and Cybulski, Cezary

Subjects
Cancer, Aging, Prostate Cancer, Genetics, Urologic Diseases, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Case-Control Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Risk, Profile Study, Australian Prostate Cancer BioResource, IMPACT Study, Canary PASS Investigators, Breast and Prostate Cancer Cohort Consortium, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, Cancer of the Prostate in Sweden, Prostate Cancer Genome-wide Association Study of Uncommon Susceptibility Loci, Genetic Associations and Mechanisms in Oncology (GAME-ON)/Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Published
2018

28. Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

Author

Seibert, Tyler M, Fan, Chun Chieh, Wang, Yunpeng, Zuber, Verena, Karunamuni, Roshan, Parsons, J Kellogg, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, ZSofia, Al Olama, Ali Amin, Garcia, Sara Benlloch, Muir, Kenneth, Grönberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo Lj, Nordestgaard, Børge G, Nielsen, Sune F, Weischer, Maren, Bisbjerg, Rasmus, Røder, M Andreas, Iversen, Peter, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Brenner, Hermann, Cuk, Katarina, Saum, Kai-Uwe, Park, Jong Y, Sellers, Thomas A, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Kierzek, Andrzej, Karow, David S, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, and PRACTICAL Consortium*

Subjects
PRACTICAL Consortium*, Humans, Prostatic Neoplasms, Kallikreins, Prostate-Specific Antigen, Disease-Free Survival, Risk Assessment, Survival Analysis, Cohort Studies, Predictive Value of Tests, Age of Onset, Genotype, Polymorphism, Single Nucleotide, Aged, Middle Aged, European Continental Ancestry Group, Male, Early Detection of Cancer, Outcome Assessment, Health Care, Polymorphism, Single Nucleotide, Outcome Assessment, Health Care, Aging, Urologic Diseases, Cancer, Genetic Testing, Prevention, Prostate Cancer, Genetics, 2.1 Biological and endogenous factors, General & Internal Medicine, Public Health and Health Services, Clinical Sciences
Abstract

ObjectivesTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DesignAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SettingMultiple institutions that were members of international PRACTICAL consortium.ParticipantsAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.Main outcome measuresPrediction with hazard score of age of onset of aggressive cancer in validation set.ResultsIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.ConclusionsPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Published
2018

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

Author

Dadaev, Tokhir, Saunders, Edward J, Newcombe, Paul J, Anokian, Ezequiel, Leongamornlert, Daniel A, Brook, Mark N, Cieza-Borrella, Clara, Mijuskovic, Martina, Wakerell, Sarah, Olama, Ali Amin Al, Schumacher, Fredrick R, Berndt, Sonja I, Benlloch, Sara, Ahmed, Mahbubl, Goh, Chee, Sheng, Xin, Zhang, Zhuo, Muir, Kenneth, Govindasami, Koveela, Lophatananon, Artitaya, Stevens, Victoria L, Gapstur, Susan M, Carter, Brian D, Tangen, Catherine M, Goodman, Phyllis, Thompson, Ian M, Batra, Jyotsna, Chambers, Suzanne, Moya, Leire, Clements, Judith, Horvath, Lisa, Tilley, Wayne, Risbridger, Gail, Gronberg, Henrik, Aly, Markus, Nordström, Tobias, Pharoah, Paul, Pashayan, Nora, Schleutker, Johanna, Tammela, Teuvo LJ, Sipeky, Csilla, Auvinen, Anssi, Albanes, Demetrius, Weinstein, Stephanie, Wolk, Alicja, Hakansson, Niclas, West, Catharine, Dunning, Alison M, Burnet, Neil, Mucci, Lorelei, Giovannucci, Edward, Andriole, Gerald, Cussenot, Olivier, Cancel-Tassin, Géraldine, Koutros, Stella, Freeman, Laura E Beane, Sorensen, Karina Dalsgaard, Orntoft, Torben Falck, Borre, Michael, Maehle, Lovise, Grindedal, Eli Marie, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Travis, Ruth C, Key, Tim J, Hamilton, Robert J, Fleshner, Neil E, Finelli, Antonio, Ingles, Sue Ann, Stern, Mariana C, Rosenstein, Barry, Kerns, Sarah, Ostrer, Harry, Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, 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, Fachal, Laura, Szulkin, Robert, Eklund, Martin, Kogevinas, Manolis, Llorca, Javier, Castaño-Vinyals, Gemma, Penney, Kathryn L, Stampfer, Meir, Park, Jong Y, and Sellers, Thomas A

Subjects
Genetics, Aging, Urologic Diseases, Prostate Cancer, Prevention, Human Genome, Cancer, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Algorithms, Bayes Theorem, Black People, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Molecular Sequence Annotation, Multivariate Analysis, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, Risk, White People, PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium
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.

Published
2018

30. Circulating sex hormones in relation to anthropometric, sociodemographic and behavioural factors in an international dataset of 12,300 men

Author

Watts, Eleanor L, Appleby, Paul N, Albanes, Demetrius, Black, Amanda, Chan, June M, Chen, Chu, Cirillo, Piera M, Cohn, Barbara A, Cook, Michael B, Donovan, Jenny L, Ferrucci, Luigi, Garland, Cedric F, Giles, Graham G, Goodman, Phyllis J, Habel, Laurel A, Haiman, Christopher A, Holly, Jeff MP, Hoover, Robert N, Kaaks, Rudolf, Knekt, Paul, Kolonel, Laurence N, Kubo, Tatsuhiko, Le Marchand, Loïc, Luostarinen, Tapio, MacInnis, Robert J, Mäenpää, Hanna O, Männistö, Satu, Metter, E Jeffrey, Milne, Roger L, Nomura, Abraham MY, Oliver, Steven E, Parsons, J Kellogg, Peeters, Petra H, Platz, Elizabeth A, Riboli, Elio, Ricceri, Fulvio, Rinaldi, Sabina, Rissanen, Harri, Sawada, Norie, Schaefer, Catherine A, Schenk, Jeannette M, Stanczyk, Frank Z, Stampfer, Meir, Stattin, Pär, Stenman, Ulf-Håkan, Tjønneland, Anne, Trichopoulou, Antonia, Thompson, Ian M, Tsugane, Shoichiro, Vatten, Lars, Whittemore, Alice S, Ziegler, Regina G, Allen, Naomi E, Key, Timothy J, and Travis, Ruth C

Subjects
Cancer, Aging, Estrogen, Good Health and Well Being, Adult, Anthropometry, Behavior, Datasets as Topic, Gonadal Steroid Hormones, Humans, Male, Social Class, Young Adult, General Science & Technology
Abstract

IntroductionSex hormones have been implicated in the etiology of a number of diseases. To better understand disease etiology and the mechanisms of disease-risk factor associations, this analysis aimed to investigate the associations of anthropometric, sociodemographic and behavioural factors with a range of circulating sex hormones and sex hormone-binding globulin.MethodsStatistical analyses of individual participant data from 12,330 male controls aged 25-85 years from 25 studies involved in the Endogenous Hormones Nutritional Biomarkers and Prostate Cancer Collaborative Group. Analysis of variance was used to estimate geometric means adjusted for study and relevant covariates.ResultsOlder age was associated with higher concentrations of sex hormone-binding globulin and dihydrotestosterone and lower concentrations of dehydroepiandrosterone sulfate, free testosterone, androstenedione, androstanediol glucuronide and free estradiol. Higher body mass index was associated with higher concentrations of free estradiol, androstanediol glucuronide, estradiol and estrone and lower concentrations of dihydrotestosterone, testosterone, sex hormone-binding globulin, free testosterone, androstenedione and dehydroepiandrosterone sulfate. Taller height was associated with lower concentrations of androstenedione, testosterone, free testosterone and sex hormone-binding globulin and higher concentrations of androstanediol glucuronide. Current smoking was associated with higher concentrations of androstenedione, sex hormone-binding globulin and testosterone. Alcohol consumption was associated with higher concentrations of dehydroepiandrosterone sulfate, androstenedione and androstanediol glucuronide. East Asians had lower concentrations of androstanediol glucuronide and African Americans had higher concentrations of estrogens. Education and marital status were modestly associated with a small number of hormones.ConclusionCirculating sex hormones in men are strongly associated with age and body mass index, and to a lesser extent with smoking status and alcohol consumption.

Published
2017

32. Cellular immune activity biomarker neopterin is associated hyperlipidemia: results from a large population-based study

Author

Chuang, Shu-Chun, Boeing, Heiner, Vollset, Stein Emil, Midttun, Øivind, Ueland, Per Magne, Bueno-de-Mesquita, Bas, Lajous, Martin, Fagherazzi, Guy, Boutron-Ruault, Marie-Christine, Kaaks, Rudolf, Küehn, Tilman, Pischon, Tobias, Drogan, Dagmar, Tjønneland, Anne, Overvad, Kim, Quirós, J Ramón, Agudo, Antonio, Molina-Montes, Esther, Dorronsoro, Miren, Huerta, José María, Barricarte, Aurelio, Khaw, Kay-Tee, Wareham, Nicholas J, Travis, Ruth C, Trichopoulou, Antonia, Lagiou, Pagona, Trichopoulos, Dimitrios, Masala, Giovanna, Agnoli, Claudia, Tumino, Rosario, Mattiello, Amalia, Peeters, Petra H, Weiderpass, Elisabete, Palmqvist, Richard, Ljuslinder, Ingrid, Gunter, Marc, Lu, Yunxia, Cross, Amanda J, Riboli, Elio, Vineis, Paolo, and Aleksandrova, Krasimira

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Cardiovascular, Nutrition, Aging, Clinical Research, Cell-mediated immunity, Metabolic syndrome, Neopterin, Clinical Sciences, Immunology, Clinical sciences
Abstract

BackgroundIncreased serum neopterin had been described in older age two decades ago. Neopterin is a biomarker of systemic adaptive immune activation that could be potentially implicated in metabolic syndrome (MetS). Measurements of waist circumference, triglycerides, high-density lipoprotein cholesterol (HDLC), systolic and diastolic blood pressure, glycated hemoglobin as components of MetS definition, and plasma total neopterin concentrations were performed in 594 participants recruited in the European Prospective Investigation into Cancer and Nutrition (EPIC).ResultsHigher total neopterin concentrations were associated with reduced HDLC (9.7 %, p

Published
2016

33. Dietary amino acids and risk of stroke subtypes : a prospective analysis of 356,000 participants in seven European countries

Author

Tong, Tammy Y. N., Clarke, Robert, Schmidt, Julie A., Huybrechts, Inge, Noor, Urwah, Forouhi, Nita G., Imamura, Fumiaki, Travis, Ruth C., Weiderpass, Elisabete, Aleksandrova, Krasimira, Dahm, Christina C., van der Schouw, Yvonne T., Overvad, Kim, Kyrø, Cecilie, Tjønneland, Anne, Kaaks, Rudolf, Katzke, Verena, Schiborn, Catarina, Schulze, Matthias B., Mayen-Chacon, Ana-Lucia, Masala, Giovanna, Sieri, Sabina, de Magistris, Maria Santucci, Tumino, Rosario, Sacerdote, Carlotta, Boer, Jolanda M. A., Verschuren, W. M. Monique, Brustad, Magritt, Nøst, Therese Haugdahl, Crous-Bou, Marta, Petrova, Dafina, Amiano, Pilar, Huerta, José María, Moreno-Iribas, Conchi, Engström, Gunnar, Melander, Olle, Johansson, Kristina, Lindvall, Kristina, Aglago, Elom K., Heath, Alicia K., Butterworth, Adam S., Danesh, John, Key, Timothy J., Tong, Tammy Y. N., Clarke, Robert, Schmidt, Julie A., Huybrechts, Inge, Noor, Urwah, Forouhi, Nita G., Imamura, Fumiaki, Travis, Ruth C., Weiderpass, Elisabete, Aleksandrova, Krasimira, Dahm, Christina C., van der Schouw, Yvonne T., Overvad, Kim, Kyrø, Cecilie, Tjønneland, Anne, Kaaks, Rudolf, Katzke, Verena, Schiborn, Catarina, Schulze, Matthias B., Mayen-Chacon, Ana-Lucia, Masala, Giovanna, Sieri, Sabina, de Magistris, Maria Santucci, Tumino, Rosario, Sacerdote, Carlotta, Boer, Jolanda M. A., Verschuren, W. M. Monique, Brustad, Magritt, Nøst, Therese Haugdahl, Crous-Bou, Marta, Petrova, Dafina, Amiano, Pilar, Huerta, José María, Moreno-Iribas, Conchi, Engström, Gunnar, Melander, Olle, Johansson, Kristina, Lindvall, Kristina, Aglago, Elom K., Heath, Alicia K., Butterworth, Adam S., Danesh, John, and Key, Timothy J.

Abstract

Purpose: Previously reported associations of protein-rich foods with stroke subtypes have prompted interest in the assessment of individual amino acids. We examined the associations of dietary amino acids with risks of ischaemic and haemorrhagic stroke in the EPIC study. Methods: We analysed data from 356,142 participants from seven European countries. Dietary intakes of 19 individual amino acids were assessed using validated country-specific dietary questionnaires, calibrated using additional 24-h dietary recalls. Multivariable-adjusted Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of ischaemic and haemorrhagic stroke in relation to the intake of each amino acid. The role of blood pressure as a potential mechanism was assessed in 267,642 (75%) participants. Results: After a median follow-up of 12.9 years, 4295 participants had an ischaemic stroke and 1375 participants had a haemorrhagic stroke. After correction for multiple testing, a higher intake of proline (as a percent of total protein) was associated with a 12% lower risk of ischaemic stroke (HR per 1 SD higher intake 0.88; 95% CI 0.82, 0.94). The association persisted after mutual adjustment for all other amino acids, systolic and diastolic blood pressure. The inverse associations of isoleucine, leucine, valine, phenylalanine, threonine, tryptophan, glutamic acid, serine and tyrosine with ischaemic stroke were each attenuated with adjustment for proline intake. For haemorrhagic stroke, no statistically significant associations were observed in the continuous analyses after correcting for multiple testing. Conclusion: Higher proline intake may be associated with a lower risk of ischaemic stroke, independent of other dietary amino acids and blood pressure.

Published
2024
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34. Observational and genetic associations between cardiorespiratory fitness and cancer : a UK Biobank and international consortia study

Author

Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M. L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., Brage, Soren, Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M. L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., and Brage, Soren

Abstract

Background: The association of fitness with cancer risk is not clear. Methods: We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of lung, colorectal, endometrial, breast, and prostate cancer in a subset of UK Biobank participants who completed a submaximal fitness test in 2009-12 (N = 72,572). We also investigated relationships using two-sample Mendelian randomisation (MR), odds ratios (ORs) were estimated using the inverse-variance weighted method. Results: After a median of 11 years of follow-up, 4290 cancers of interest were diagnosed. A 3.5 ml O2⋅min−1⋅kg−1 total-body mass increase in fitness (equivalent to 1 metabolic equivalent of task (MET), approximately 0.5 standard deviation (SD)) was associated with lower risks of endometrial (HR = 0.81, 95% CI: 0.73–0.89), colorectal (0.94, 0.90–0.99), and breast cancer (0.96, 0.92–0.99). In MR analyses, a 0.5 SD increase in genetically predicted O2⋅min−1⋅kg−1 fat-free mass was associated with a lower risk of breast cancer (OR = 0.92, 95% CI: 0.86–0.98). After adjusting for adiposity, both the observational and genetic associations were attenuated. Discussion: Higher fitness levels may reduce risks of endometrial, colorectal, and breast cancer, though relationships with adiposity are complex and may mediate these relationships. Increasing fitness, including via changes in body composition, may be an effective strategy for cancer prevention.

Published
2024
Full Text
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35. Observational and genetic associations between cardiorespiratory fitness and cancer:a UK Biobank and international consortia study

Author

Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, Van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., Brage, Soren, Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, Van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., and Brage, Soren

Abstract

Background: The association of fitness with cancer risk is not clear. Methods: We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of lung, colorectal, endometrial, breast, and prostate cancer in a subset of UK Biobank participants who completed a submaximal fitness test in 2009-12 (N = 72,572). We also investigated relationships using two-sample Mendelian randomisation (MR), odds ratios (ORs) were estimated using the inverse-variance weighted method.Results: After a median of 11 years of follow-up, 4290 cancers of interest were diagnosed. A 3.5 ml O2⋅min−1⋅kg−1 total-body mass increase in fitness (equivalent to 1 metabolic equivalent of task (MET), approximately 0.5 standard deviation (SD)) was associated with lower risks of endometrial (HR = 0.81, 95% CI: 0.73–0.89), colorectal (0.94, 0.90–0.99), and breast cancer (0.96, 0.92–0.99). In MR analyses, a 0.5 SD increase in genetically predicted O2⋅min−1⋅kg−1 fat-free mass was associated with a lower risk of breast cancer (OR = 0.92, 95% CI: 0.86–0.98). After adjusting for adiposity, both the observational and genetic associations were attenuated. Discussion: Higher fitness levels may reduce risks of endometrial, colorectal, and breast cancer, though relationships with adiposity are complex and may mediate these relationships. Increasing fitness, including via changes in body composition, may be an effective strategy for cancer prevention.

Published
2024

36. Dietary amino acids and risk of stroke subtypes: a prospective analysis of 356,000 participants in seven European countries

Author

Cardiovasculaire Epi Team 1, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiometabolic Health, Tong, Tammy Y.N., Clarke, Robert, Schmidt, Julie A., Huybrechts, Inge, Noor, Urwah, Forouhi, Nita G., Imamura, Fumiaki, Travis, Ruth C., Weiderpass, Elisabete, Aleksandrova, Krasimira, Dahm, Christina C., van der Schouw, Yvonne T., Overvad, Kim, Kyrø, Cecilie, Tjønneland, Anne, Kaaks, Rudolf, Katzke, Verena, Schiborn, Catarina, Schulze, Matthias B., Mayen-Chacon, Ana Lucia, Masala, Giovanna, Sieri, Sabina, de Magistris, Maria Santucci, Tumino, Rosario, Sacerdote, Carlotta, Boer, Jolanda M.A., Verschuren, W. M.Monique, Brustad, Magritt, Nøst, Therese Haugdahl, Crous-Bou, Marta, Petrova, Dafina, Amiano, Pilar, Huerta, José María, Moreno-Iribas, Conchi, Engström, Gunnar, Melander, Olle, Johansson, Kristina, Lindvall, Kristina, Aglago, Elom K., Heath, Alicia K., Butterworth, Adam S., Danesh, John, Key, Timothy J., Cardiovasculaire Epi Team 1, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiometabolic Health, Tong, Tammy Y.N., Clarke, Robert, Schmidt, Julie A., Huybrechts, Inge, Noor, Urwah, Forouhi, Nita G., Imamura, Fumiaki, Travis, Ruth C., Weiderpass, Elisabete, Aleksandrova, Krasimira, Dahm, Christina C., van der Schouw, Yvonne T., Overvad, Kim, Kyrø, Cecilie, Tjønneland, Anne, Kaaks, Rudolf, Katzke, Verena, Schiborn, Catarina, Schulze, Matthias B., Mayen-Chacon, Ana Lucia, Masala, Giovanna, Sieri, Sabina, de Magistris, Maria Santucci, Tumino, Rosario, Sacerdote, Carlotta, Boer, Jolanda M.A., Verschuren, W. M.Monique, Brustad, Magritt, Nøst, Therese Haugdahl, Crous-Bou, Marta, Petrova, Dafina, Amiano, Pilar, Huerta, José María, Moreno-Iribas, Conchi, Engström, Gunnar, Melander, Olle, Johansson, Kristina, Lindvall, Kristina, Aglago, Elom K., Heath, Alicia K., Butterworth, Adam S., Danesh, John, and Key, Timothy J.

Published
2024

37. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Yarmolinsky, James, primary, Robinson, Jamie W., additional, Mariosa, Daniela, additional, Karhunen, Ville, additional, Huang, Jian, additional, Dimou, Niki, additional, Murphy, Neil, additional, Burrows, Kimberley, additional, Bouras, Emmanouil, additional, Smith-Byrne, Karl, additional, Lewis, Sarah J., additional, Galesloot, Tessel E., additional, Kiemeney, Lambertus A., additional, Vermeulen, Sita, additional, Martin, Paul, additional, Albanes, Demetrius, additional, Hou, Lifang, additional, Newcomb, Polly A., additional, White, Emily, additional, Wolk, Alicja, additional, Wu, Anna H., additional, Le Marchand, Loïc, additional, Phipps, Amanda I., additional, Buchanan, Daniel D., additional, Zhao, Sizheng Steven, additional, Gill, Dipender, additional, Chanock, Stephen J., additional, Purdue, Mark P., additional, Davey Smith, George, additional, Brennan, Paul, additional, Herzig, Karl-Heinz, additional, Järvelin, Marjo-Riitta, additional, Amos, Chris I., additional, Hung, Rayjean J., additional, Dehghan, Abbas, additional, Johansson, Mattias, additional, Gunter, Marc J., additional, Tsilidis, Kostas K., additional, Martin, Richard M., additional, Landi, Maria Teresa, additional, Stevens, Victoria, additional, Wang, Ying, additional, Albanes, Demetrios, additional, Caporaso, Neil, additional, Amos, Christopher I., additional, Shete, Sanjay, additional, Bickeböller, Heike, additional, Risch, Angela, additional, Houlston, Richard, additional, Lam, Stephen, additional, Tardon, Adonina, additional, Chen, Chu, additional, Bojesen, Stig E., additional, Wichmann, H-Erich, additional, Christiani, David, additional, Rennert, Gadi, additional, Arnold, Susanne, additional, Field, John K., additional, Le Marchand, Loic, additional, Melander, Olle, additional, Brunnström, Hans, additional, Liu, Geoffrey, additional, Andrew, Angeline, additional, Shen, Hongbing, additional, Zienolddiny, Shan, additional, Grankvist, Kjell, additional, Johansson, Mikael, additional, Teare, M. Dawn, additional, Hong, Yun-Chul, additional, Yuan, Jian-Min, additional, Lazarus, Philip, additional, Schabath, Matthew B., additional, Aldrich, Melinda C., additional, Eeles, Rosalind A., additional, Haiman, Christopher A., additional, Kote-Jarai, Zsofia, additional, Schumacher, Fredrick R., additional, Benlloch, Sara, additional, Al Olama, Ali Amin, additional, Muir, Kenneth R., additional, Berndt, Sonja I., additional, Conti, David V., additional, Wiklund, Fredrik, additional, Chanock, Stephen, additional, Tangen, Catherine M., additional, Batra, Jyotsna, additional, Clements, Judith A., additional, Grönberg, Henrik, additional, Pashayan, Nora, additional, Schleutker, Johanna, additional, Weinstein, Stephanie J., additional, West, Catharine M.L., additional, Mucci, Lorelei A., additional, Cancel-Tassin, Géraldine, additional, Koutros, Stella, additional, Sørensen, Karina Dalsgaard, additional, Grindedal, Eli Marie, additional, Neal, David E., additional, Hamdy, Freddie C., additional, Donovan, Jenny L., additional, Travis, Ruth C., additional, Hamilton, Robert J., additional, Ingles, Sue Ann, additional, Rosenstein, Barry S., additional, Lu, Yong-Jie, additional, Giles, Graham G., additional, MacInnis, Robert J., additional, Kibel, Adam S., additional, Vega, Ana, additional, Kogevinas, Manolis, additional, Penney, Kathryn L., additional, Park, Jong Y., additional, Stanfrod, Janet L., additional, Cybulski, Cezary, additional, Nordestgaard, Børge G., additional, Nielsen, Sune F., additional, Brenner, Hermann, additional, Maier, Christiane, additional, Logothetis, Christopher J., additional, John, Esther M., additional, Teixeira, Manuel R., additional, Neuhausen, Susan L., additional, De Ruyck, Kim, additional, Razack, Azad, additional, Newcomb, Lisa F., additional, Lessel, Davor, additional, Kaneva, Radka, additional, Usmani, Nawaid, additional, Claessens, Frank, additional, Townsend, Paul A., additional, Castelao, Jose Esteban, additional, Roobol, Monique J., additional, Menegaux, Florence, additional, Khaw, Kay-Tee, additional, Cannon-Albright, Lisa, additional, Pandha, Hardev, additional, Thibodeau, Stephen N., additional, Hunter, David J., additional, Kraft, Peter, additional, Blot, William J., additional, and Riboli, Elio, additional

Published
2024
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38. Flavonoid and lignan intake and pancreatic cancer risk in the European prospective investigation into cancer and nutrition cohort

Author

Molina‐Montes, Esther, Sánchez, María‐José, Zamora‐Ros, Raul, Bueno‐de‐Mesquita, HB, Wark, Petra A, Obon‐Santacana, Mireia, Kühn, Tilman, Katzke, Verena, Travis, Ruth C, Ye, Weimin, Sund, Malin, Naccarati, Alessio, Mattiello, Amalia, Krogh, Vittorio, Martorana, Caterina, Masala, Giovanna, Amiano, Pilar, Huerta, José‐María, Barricarte, Aurelio, Quirós, José‐Ramón, Weiderpass, Elisabete, Åsli, Lene Angell, Skeie, Guri, Ericson, Ulrika, Sonestedt, Emily, Peeters, Petra H, Romieu, Isabelle, Scalbert, Augustin, Overvad, Kim, Clemens, Matthias, Boeing, Heiner, Trichopoulou, Antonia, Peppa, Eleni, Vidalis, Pavlos, Khaw, Kay‐Tee, Wareham, Nick, Olsen, Anja, Tjønneland, Anne, Boutroun‐Rualt, Marie‐Christine, Clavel‐Chapelon, Françoise, Cross, Amanda J, Lu, Yunxia, Riboli, Elio, and Duell, Eric J

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Digestive Diseases, Nutrition, Pancreatic Cancer, Rare Diseases, Complementary and Integrative Health, Cancer, Prevention, Cohort Studies, Diet, Diet Records, Europe, Female, Flavonoids, Humans, Life Style, Lignans, Male, Middle Aged, Pancreatic Neoplasms, Proportional Hazards Models, Prospective Studies, cohort, diet, flavonoids, lignans, pancreatic cancer, Oncology and Carcinogenesis, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

Despite the potential cancer preventive effects of flavonoids and lignans, their ability to reduce pancreatic cancer risk has not been demonstrated in epidemiological studies. Our aim was to examine the association between dietary intakes of flavonoids and lignans and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. A total of 865 exocrine pancreatic cancer cases occurred after 11.3 years of follow-up of 477,309 cohort members. Dietary flavonoid and lignan intake was estimated through validated dietary questionnaires and the US Department of Agriculture (USDA) and Phenol Explorer databases. Hazard ratios (HR) and 95% confidence intervals (CIs) were calculated using age, sex and center-stratified Cox proportional hazards models, adjusted for energy intake, body mass index (BMI), smoking, alcohol and diabetes status. Our results showed that neither overall dietary intake of flavonoids nor of lignans were associated with pancreatic cancer risk (multivariable-adjusted HR for a doubling of intake = 1.03, 95% CI: 0.95-1.11 and 1.02; 95% CI: 0.89-1.17, respectively). Statistically significant associations were also not observed by flavonoid subclasses. An inverse association between intake of flavanones and pancreatic cancer risk was apparent, without reaching statistical significance, in microscopically confirmed cases (HR for a doubling of intake = 0.96, 95% CI: 0.91-1.00). In conclusion, we did not observe an association between intake of flavonoids, flavonoid subclasses or lignans and pancreatic cancer risk in the EPIC cohort.

Published
2016

39. Comparison of abdominal adiposity and overall obesity in relation to risk of small intestinal cancer in a European Prospective Cohort

Author

Lu, Yunxia, Cross, Amanda J, Murphy, Neil, Freisling, Heinz, Travis, Ruth C, Ferrari, Pietro, Katzke, Verena A, Kaaks, Rudolf, Olsson, Åsa, Johansson, Ingegerd, Renström, Frida, Panico, Salvatore, Pala, Valeria, Palli, Domenico, Tumino, Rosario, Peeters, Petra H, Siersema, Peter D, Bueno-de-Mesquita, HB, Trichopoulou, Antonia, Klinaki, Eleni, Tsironis, Christos, Agudo, Antonio, Navarro, Carmen, Sánchez, María-José, Barricarte, Aurelio, Boutron-Ruault, Marie-Christine, Fagherazzi, Guy, Racine, Antoine, Weiderpass, Elisabete, Gunter, Marc J, and Riboli, Elio

Subjects
Biomedical and Clinical Sciences, Epidemiology, Public Health, Health Sciences, Nutrition and Dietetics, Obesity, Prevention, Nutrition, Cancer, Digestive Diseases, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Cardiovascular, Stroke, Adenocarcinoma, Adiposity, Adult, Aged, Body Height, Body Mass Index, Europe, Female, Humans, Intestinal Neoplasms, Male, Middle Aged, Proportional Hazards Models, Prospective Studies, Risk Factors, Waist Circumference, Waist-Hip Ratio, White People, Abdominal obesity, Small intestine, Oncology and Carcinogenesis, Public Health and Health Services, Oncology and carcinogenesis
Abstract

BackgroundThe etiology of small intestinal cancer (SIC) is largely unknown, and there are very few epidemiological studies published to date. No studies have investigated abdominal adiposity in relation to SIC.MethodsWe investigated overall obesity and abdominal adiposity in relation to SIC in the European Prospective Investigation into Cancer and Nutrition (EPIC), a large prospective cohort of approximately half a million men and women from ten European countries. Overall obesity and abdominal obesity were assessed by body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Multivariate Cox proportional hazards regression modeling was performed to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). Stratified analyses were conducted by sex, BMI, and smoking status.ResultsDuring an average of 13.9 years of follow-up, 131 incident cases of SIC (including 41 adenocarcinomas, 44 malignant carcinoid tumors, 15 sarcomas and 10 lymphomas, and 21 unknown histology) were identified. WC was positively associated with SIC in a crude model that also included BMI (HR per 5-cm increase = 1.20, 95 % CI 1.04, 1.39), but this association attenuated in the multivariable model (HR 1.18, 95 % CI 0.98, 1.42). However, the association between WC and SIC was strengthened when the analysis was restricted to adenocarcinoma of the small intestine (multivariable HR adjusted for BMI = 1.56, 95 % CI 1.11, 2.17). There were no other significant associations.ConclusionWC, rather than BMI, may be positively associated with adenocarcinomas but not carcinoid tumors of the small intestine.ImpactAbdominal obesity is a potential risk factor for adenocarcinoma in the small intestine.

Published
2016

40. A Meta-analysis of Individual Participant Data Reveals an Association between Circulating Levels of IGF-I and Prostate Cancer Risk

Author

Travis, Ruth C, Appleby, Paul N, Martin, Richard M, Holly, Jeff MP, Albanes, Demetrius, Black, Amanda, Bueno-de-Mesquita, HB As, Chan, June M, Chen, Chu, Chirlaque, Maria-Dolores, Cook, Michael B, Deschasaux, Mélanie, Donovan, Jenny L, Ferrucci, Luigi, Galan, Pilar, Giles, Graham G, Giovannucci, Edward L, Gunter, Marc J, Habel, Laurel A, Hamdy, Freddie C, Helzlsouer, Kathy J, Hercberg, Serge, Hoover, Robert N, Janssen, Joseph AMJL, Kaaks, Rudolf, Kubo, Tatsuhiko, Le Marchand, Loic, Metter, E Jeffrey, Mikami, Kazuya, Morris, Joan K, Neal, David E, Neuhouser, Marian L, Ozasa, Kotaro, Palli, Domenico, Platz, Elizabeth A, Pollak, Michael, Price, Alison J, Roobol, Monique J, Schaefer, Catherine, Schenk, Jeannette M, Severi, Gianluca, Stampfer, Meir J, Stattin, Pär, Tamakoshi, Akiko, Tangen, Catherine M, Touvier, Mathilde, Wald, Nicholas J, Weiss, Noel S, Ziegler, Regina G, Key, Timothy J, and Allen, Naomi E

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Cancer, Urologic Diseases, Aged, Humans, Insulin-Like Growth Factor I, Male, Middle Aged, Prostatic Neoplasms, Risk Factors, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

The role of insulin-like growth factors (IGF) in prostate cancer development is not fully understood. To investigate the association between circulating concentrations of IGFs (IGF-I, IGF-II, IGFBP-1, IGFBP-2, and IGFBP-3) and prostate cancer risk, we pooled individual participant data from 17 prospective and two cross-sectional studies, including up to 10,554 prostate cancer cases and 13,618 control participants. Conditional logistic regression was used to estimate the ORs for prostate cancer based on the study-specific fifth of each analyte. Overall, IGF-I, IGF-II, IGFBP-2, and IGFBP-3 concentrations were positively associated with prostate cancer risk (Ptrend all ≤ 0.005), and IGFBP-1 was inversely associated weakly with risk (Ptrend = 0.05). However, heterogeneity between the prospective and cross-sectional studies was evident (Pheterogeneity = 0.03), unless the analyses were restricted to prospective studies (with the exception of IGF-II, Pheterogeneity = 0.02). For prospective studies, the OR for men in the highest versus the lowest fifth of each analyte was 1.29 (95% confidence interval, 1.16-1.43) for IGF-I, 0.81 (0.68-0.96) for IGFBP-1, and 1.25 (1.12-1.40) for IGFBP-3. These associations did not differ significantly by time-to-diagnosis or tumor stage or grade. After mutual adjustment for each of the other analytes, only IGF-I remained associated with risk. Our collaborative study represents the largest pooled analysis of the relationship between prostate cancer risk and circulating concentrations of IGF-I, providing strong evidence that IGF-I is highly likely to be involved in prostate cancer development. Cancer Res; 76(8); 2288-300. ©2016 AACR.

Published
2016

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

Author

Gusev, Alexander, Shi, Huwenbo, Kichaev, Gleb, Pomerantz, Mark, Li, Fugen, Long, Henry W, Ingles, Sue A, Kittles, Rick A, Strom, Sara S, Rybicki, Benjamin A, Nemesure, Barbara, Isaacs, William B, Zheng, Wei, Pettaway, Curtis A, Yeboah, Edward D, Tettey, Yao, Biritwum, Richard B, Adjei, Andrew A, Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Chokkalingam, Anand P, John, Esther M, Murphy, Adam B, Signorello, Lisa B, Carpten, John, Leske, M Cristina, Wu, Suh-Yuh, Hennis, Anslem JM, Neslund-Dudas, Christine, Hsing, Ann W, Chu, Lisa, Goodman, Phyllis J, Klein, Eric A, Witte, John S, Casey, Graham, Kaggwa, Sam, Cook, Michael B, Stram, Daniel O, Blot, William J, Eeles, Rosalind A, Easton, Douglas, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G, Southey, Melissa C, Fitzgerald, Liesel M, Gronberg, Henrik, Wiklund, Fredrik, Aly, Markus, Henderson, Brian E, Schleutker, Johanna, Wahlfors, Tiina, Tammela, Teuvo LJ, Nordestgaard, Børge G, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Stanford, Janet L, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Teerlink, Craig, Brenner, Hermann, Dieffenbach, Aida K, Arndt, Volker, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Spurdle, Amanda, Clements, Judith A, Teixeira, Manuel R, Pandha, Hardev, Michael, Agnieszka, Paulo, Paula, Maia, Sofia, Kierzek, Andrzej, PRACTICAL consortium, Conti, David V, and Albanes, Demetrius

Subjects
PRACTICAL consortium, Cell Line, Tumor, Humans, Prostatic Neoplasms, Genetic Predisposition to Disease, Histones, Epigenesis, Genetic, Acetylation, Inheritance Patterns, Linkage Disequilibrium, Polymorphism, Single Nucleotide, African Americans, European Continental Ancestry Group, Male, Atlases as Topic, Genome-Wide Association Study, Genetic Loci, Cell Line, Tumor, Epigenesis, Genetic, Polymorphism, Single Nucleotide
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

42. Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry

Author

Figueroa, Jonine D, Middlebrooks, Candace D, Banday, A Rouf, Ye, Yuanqing, Garcia-Closas, Montserrat, Chatterjee, Nilanjan, Koutros, Stella, Kiemeney, Lambertus A, Rafnar, Thorunn, Bishop, Timothy, Furberg, Helena, Matullo, Giuseppe, Golka, Klaus, Gago-Dominguez, Manuela, Taylor, Jack A, Fletcher, Tony, Siddiq, Afshan, Cortessis, Victoria K, Kooperberg, Charles, Cussenot, Olivier, Benhamou, Simone, Prescott, Jennifer, Porru, Stefano, Dinney, Colin P, Malats, Núria, Baris, Dalsu, Purdue, Mark P, Jacobs, Eric J, Albanes, Demetrius, Wang, Zhaoming, Chung, Charles C, Vermeulen, Sita H, Aben, Katja K, Galesloot, Tessel E, Thorleifsson, Gudmar, Sulem, Patrick, Stefansson, Kari, Kiltie, Anne E, Harland, Mark, Teo, Mark, Offit, Kenneth, Vijai, Joseph, Bajorin, Dean, Kopp, Ryan, Fiorito, Giovanni, Guarrera, Simonetta, Sacerdote, Carlotta, Selinski, Silvia, Hengstler, Jan G, Gerullis, Holger, Ovsiannikov, Daniel, Blaszkewicz, Meinolf, Castelao, Jose Esteban, Calaza, Manuel, Martinez, Maria Elena, Cordeiro, Patricia, Xu, Zongli, Panduri, Vijayalakshmi, Kumar, Rajiv, Gurzau, Eugene, Koppova, Kvetoslava, Bueno-De-Mesquita, H Bas, Ljungberg, Börje, Clavel-Chapelon, Françoise, Weiderpass, Elisabete, Krogh, Vittorio, Dorronsoro, Miren, Travis, Ruth C, Tjønneland, Anne, Brennan, Paul, Chang-Claude, Jenny, Riboli, Elio, Conti, David, Stern, Marianna C, Pike, Malcolm C, Van Den Berg, David, Yuan, Jian-Min, Hohensee, Chancellor, Jeppson, Rebecca P, Cancel-Tassin, Geraldine, Roupret, Morgan, Comperat, Eva, Turman, Constance, De Vivo, Immaculata, Giovannucci, Edward, Hunter, David J, Kraft, Peter, Lindstrom, Sara, Carta, Angela, Pavanello, Sofia, Arici, Cecilia, Mastrangelo, Giuseppe, Kamat, Ashish M, Zhang, Liren, Gong, Yilei, Pu, Xia, Hutchinson, Amy, Burdett, Laurie, Wheeler, William A, and Karagas, Margaret R

Subjects
Cancer, Prevention, Human Genome, Genetics, Biotechnology, Urologic Diseases, Aetiology, 2.1 Biological and endogenous factors, Biomarkers, Tumor, Case-Control Studies, Chromosomes, Human, Pair 13, Chromosomes, Human, Pair 20, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Polymorphism, Single Nucleotide, Risk Factors, Urinary Bladder Neoplasms, White People, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.

Published
2016

43. Fine mapping of chromosome 5p15.33 based on a targeted deep sequencing and high density genotyping identifies novel lung cancer susceptibility loci

Author

Kachuri, Linda, Amos, Christopher I, McKay, James D, Johansson, Mattias, Vineis, Paolo, Bueno-de-Mesquita, H Bas, Boutron-Ruault, Marie-Christine, Johansson, Mikael, Quirós, J Ramón, Sieri, Sabina, Travis, Ruth C, Weiderpass, Elisabete, Le Marchand, Loic, Henderson, Brian E, Wilkens, Lynne, Goodman, Gary E, Chen, Chu, Doherty, Jennifer A, Christiani, David C, Wei, Yongyue, Su, Li, Tworoger, Shelley, Zhang, Xuehong, Kraft, Peter, Zaridze, David, Field, John K, Marcus, Michael W, Davies, Michael PA, Hyde, Russell, Caporaso, Neil E, Landi, Maria Teresa, Severi, Gianluca, Giles, Graham G, Liu, Geoffrey, McLaughlin, John R, Li, Yafang, Xiao, Xiangjun, Fehringer, Gord, Zong, Xuchen, Denroche, Robert E, Zuzarte, Philip C, McPherson, John D, Brennan, Paul, and Hung, Rayjean J

Subjects
Lung, Human Genome, Genetics, Cancer, Prevention, Lung Cancer, 2.1 Biological and endogenous factors, Aetiology, Case-Control Studies, Chromosome Mapping, Chromosomes, Human, Pair 5, Female, Genetic Loci, Genetic Predisposition to Disease, Genotyping Techniques, Humans, Lung Neoplasms, Male, Middle Aged, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Chromosome 5p15.33 has been identified as a lung cancer susceptibility locus, however the underlying causal mechanisms were not fully elucidated. Previous fine-mapping studies of this locus have relied on imputation or investigated a small number of known, common variants. This study represents a significant advance over previous research by investigating a large number of novel, rare variants, as well as their underlying mechanisms through telomere length. Variants for this fine-mapping study were identified through a targeted deep sequencing (average depth of coverage greater than 4000×) of 576 individuals. Subsequently, 4652 SNPs, including 1108 novel SNPs, were genotyped in 5164 cases and 5716 controls of European ancestry. After adjusting for known risk loci, rs2736100 and rs401681, we identified a new, independent lung cancer susceptibility variant in LPCAT1: rs139852726 (OR = 0.46, P = 4.73×10(-9)), and three new adenocarcinoma risk variants in TERT: rs61748181 (OR = 0.53, P = 2.64×10(-6)), rs112290073 (OR = 1.85, P = 1.27×10(-5)), rs138895564 (OR = 2.16, P = 2.06×10(-5); among young cases, OR = 3.77, P = 8.41×10(-4)). In addition, we found that rs139852726 (P = 1.44×10(-3)) was associated with telomere length in a sample of 922 healthy individuals. The gene-based SKAT-O analysis implicated TERT as the most relevant gene in the 5p15.33 region for adenocarcinoma (P = 7.84×10(-7)) and lung cancer (P = 2.37×10(-5)) risk. In this largest fine-mapping study to investigate a large number of rare and novel variants within 5p15.33, we identified novel lung and adenocarcinoma susceptibility loci with large effects and provided support for the role of telomere length as the potential underlying mechanism.

Published
2016

45. Dietary fat, fat subtypes and hepatocellular carcinoma in a large European cohort

Author

Duarte-Salles, Talita, Fedirko, Veronika, Stepien, Magdalena, Aleksandrova, Krasimira, Bamia, Christina, Lagiou, Pagona, Laursen, Anne Sofie Dam, Hansen, Louise, Overvad, Kim, Tjønneland, Anne, Boutron-Ruault, Marie-Christine, Fagherazzi, Guy, His, Mathilde, Boeing, Heiner, Katzke, Verena, Kühn, Tilman, Trichopoulou, Antonia, Valanou, Elissavet, Kritikou, Maria, Masala, Giovanna, Panico, Salvatore, Sieri, Sabina, Ricceri, Fulvio, Tumino, Rosario, Bueno-de-Mesquita, HB As, Peeters, Petra H, Hjartåker, Anette, Skeie, Guri, Weiderpass, Elisabete, Ardanaz, Eva, Bonet, Catalina, Chirlaque, Maria-Dolores, Dorronsoro, Miren, Quirós, J Ramón, Johansson, Ingegerd, Ohlsson, Bodil, Sjöberg, Klas, Wennberg, Maria, Khaw, Kay-Tee, Travis, Ruth C, Wareham, Nick, Ferrari, Pietro, Freisling, Heinz, Romieu, Isabelle, Cross, Amanda J, Gunter, Marc, Lu, Yunxia, and Jenab, Mazda

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Hepatitis, Infectious Diseases, Hepatitis - B, Liver Cancer, Prevention, Liver Disease, Cancer, Chronic Liver Disease and Cirrhosis, Rare Diseases, Nutrition, Digestive Diseases, Clinical Research, Emerging Infectious Diseases, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Good Health and Well Being, Adult, Aged, Carcinoma, Hepatocellular, Case-Control Studies, Diet, Dietary Fats, Europe, Feeding Behavior, Female, Humans, Incidence, Life Style, Liver Neoplasms, Male, Middle Aged, Nutritional Status, Prospective Studies, Risk, Risk Factors, Surveys and Questionnaires, Young Adult, European populations, cohort study, dietary fats, hepatocellular carcinoma, Oncology and Carcinogenesis, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

The role of amount and type of dietary fat consumption in the etiology of hepatocellular carcinoma (HCC) is poorly understood, despite suggestive biological plausibility. The associations of total fat, fat subtypes and fat sources with HCC incidence were investigated in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, which includes 191 incident HCC cases diagnosed between 1992 and 2010. Diet was assessed by country-specific, validated dietary questionnaires. A single 24-hr diet recall from a cohort subsample was used for measurement error calibration. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated from Cox proportional hazard models. Hepatitis B and C viruses (HBV/HCV) status and biomarkers of liver function were assessed separately in a nested case-control subset with available blood samples (HCC = 122). In multivariable calibrated models, there was a statistically significant inverse association between total fat intake and risk of HCC (per 10 g/day, HR = 0.80, 95% CI: 0.65-0.99), which was mainly driven by monounsaturated fats (per 5 g/day, HR = 0.71, 95% CI: 0.55-0.92) rather than polyunsaturated fats (per 5 g/day, HR = 0.92, 95% CI: 0.68-1.25). There was no association between saturated fats (HR = 1.08, 95% CI: 0.88-1.34) and HCC risk. The ratio of polyunsaturated/monounsaturated fats to saturated fats was not significantly associated with HCC risk (per 0.2 point, HR = 0.86, 95% CI: 0.73-1.01). Restriction of analyses to HBV/HCV free participants or adjustment for liver function did not substantially alter the findings. In this large prospective European cohort, higher consumption of monounsaturated fats is associated with lower HCC risk.

Published
2015

47. Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort

Author

His, Mathilde, Viallon, Vivian, Dossus, Laure, Schmidt, Julie A., Travis, Ruth C., Gunter, Marc J., Overvad, Kim, Kyrø, Cecilie, Tjønneland, Anne, Lécuyer, Lucie, Rothwell, Joseph A., Severi, Gianluca, Johnson, Theron, Katzke, Verena, Schulze, Matthias B., Masala, Giovanna, Sieri, Sabina, Panico, Salvatore, Tumino, Rosario, Macciotta, Alessandra, Boer, Jolanda M. A., Monninkhof, Evelyn M., Olsen, Karina Standahl, Nøst, Therese H., Sandanger, Torkjel M., Agudo, Antonio, Sánchez, Maria-Jose, Amiano, Pilar, Colorado-Yohar, Sandra M., Ardanaz, Eva, Vidman, Linda, Winkvist, Anna, Heath, Alicia K., Weiderpass, Elisabete, Huybrechts, Inge, and Rinaldi, Sabina

Published
2021
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48. Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition

Author

Kliemann, Nathalie, Viallon, Vivian, Murphy, Neil, Beeken, Rebecca J., Rothwell, Joseph A., Rinaldi, Sabina, Assi, Nada, van Roekel, Eline H., Schmidt, Julie A., Borch, Kristin Benjaminsen, Agnoli, Claudia, Rosendahl, Ann H., Sartor, Hanna, Huerta, José María, Tjønneland, Anne, Halkjær, Jytte, Bueno-de-Mesquita, Bas, Gicquiau, Audrey, Achaintre, David, Aleksandrova, Krasimira, Schulze, Matthias B., Heath, Alicia K., Tsilidis, Konstantinos K., Masala, Giovanna, Panico, Salvatore, Kaaks, Rudolf, Fortner, Renée T., Van Guelpen, Bethany, Dossus, Laure, Scalbert, Augustin, Keun, Hector C., Travis, Ruth C., Jenab, Mazda, Johansson, Mattias, Ferrari, Pietro, and Gunter, Marc J.

Published
2021
Full Text
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49. Carotenoids, retinol, tocopherols, and prostate cancer risk: pooled analysis of 15 studies 1–3

Author

Key, Timothy J, Appleby, Paul N, Travis, Ruth C, Albanes, Demetrius, Alberg, Anthony J, Barricarte, Aurelio, Black, Amanda, Boeing, Heiner, Bueno-de-Mesquita, H Bas, Chan, June M, Chen, Chu, Cook, Michael B, Donovan, Jenny L, Galan, Pilar, Gilbert, Rebecca, Giles, Graham G, Giovannucci, Edward, Goodman, Gary E, Goodman, Phyllis J, Gunter, Marc J, Hamdy, Freddie C, Heliövaara, Markku, Helzlsouer, Kathy J, Henderson, Brian E, Hercberg, Serge, Hoffman-Bolton, Judy, Hoover, Robert N, Johansson, Mattias, Khaw, Kay-Tee, King, Irena B, Knekt, Paul, Kolonel, Laurence N, Le Marchand, Loic, Männistö, Satu, Martin, Richard M, Meyer, Haakon E, Mondul, Alison M, Moy, Kristin A, Neal, David E, Neuhouser, Marian L, Palli, Domenico, Platz, Elizabeth A, Pouchieu, Camille, Rissanen, Harri, Schenk, Jeannette M, Severi, Gianluca, Stampfer, Meir J, Tjønneland, Anne, Touvier, Mathilde, Trichopoulou, Antonia, Weinstein, Stephanie J, Ziegler, Regina G, Zhou, Cindy Ke, Allen, Naomi E, Biomarkers, Endogenous Hormones Nutritional, and Group, Prostate Cancer Collaborative

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prevention, Urologic Diseases, Nutrition, Prostate Cancer, Cancer, Aging, Clinical Research, Adult, Biomarkers, Carotenoids, Case-Control Studies, Cohort Studies, Cross-Sectional Studies, Humans, Lycopene, Male, Meta-Analysis as Topic, Middle Aged, Neoplasm Grading, Neoplasm Staging, Observational Studies as Topic, Prospective Studies, Prostate, Prostatic Neoplasms, Risk Factors, Vitamin A, alpha-Tocopherol, prostate cancer, carotenoids, retinol, tocopherols, vitamin E, vitamin A, pooled analysis, nested case-control study, biomarkers, Endogenous Hormones Nutritional Biomarkers Prostate Cancer Collaborative Group, Engineering, Medical and Health Sciences, Nutrition & Dietetics, Clinical sciences, Nutrition and dietetics
Abstract

BackgroundIndividual studies have suggested that circulating carotenoids, retinol, or tocopherols may be associated with prostate cancer risk, but the studies have not been large enough to provide precise estimates of associations, particularly by stage and grade of disease.ObjectiveThe objective of this study was to conduct a pooled analysis of the associations of the concentrations of 7 carotenoids, retinol, α-tocopherol, and γ-tocopherol with risk of prostate cancer and to describe whether any associations differ by stage or grade of the disease or other factors.DesignPrincipal investigators of prospective studies provided individual participant data for prostate cancer cases and controls. Risk by study-specific fifths of each biomarker was estimated by using multivariable-adjusted conditional logistic regression in matched case-control sets.ResultsData were available for up to 11,239 cases (including 1654 advanced stage and 1741 aggressive) and 18,541 controls from 15 studies. Lycopene was not associated with overall risk of prostate cancer, but there was statistically significant heterogeneity by stage of disease, and the OR for aggressive disease for the highest compared with the lowest fifth of lycopene was 0.65 (95% CI: 0.46, 0.91; P-trend = 0.032). No other carotenoid was significantly associated with overall risk of prostate cancer or with risk of advanced-stage or aggressive disease. For retinol, the OR for the highest compared with the lowest fifth was 1.13 (95% CI: 1.04, 1.22; P-trend = 0.015). For α-tocopherol, the OR for the highest compared with the lowest fifth was 0.86 (95% CI: 0.78, 0.94; P-trend < 0.001), with significant heterogeneity by stage of disease; the OR for aggressive prostate cancer was 0.74 (95% CI: 0.59, 0.92; P-trend = 0.001). γ-Tocopherol was not associated with risk.ConclusionsOverall prostate cancer risk was positively associated with retinol and inversely associated with α-tocopherol, and risk of aggressive prostate cancer was inversely associated with lycopene and α-tocopherol. Whether these associations reflect causal relations is unclear.

Published
2015

50. Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions

Author

Han, Ying, Hazelett, Dennis J, Wiklund, Fredrik, Schumacher, Fredrick R, Stram, Daniel O, Berndt, Sonja I, Wang, Zhaoming, Rand, Kristin A, Hoover, Robert N, Machiela, Mitchell J, Yeager, Merideth, Burdette, Laurie, Chung, Charles C, Hutchinson, Amy, Yu, Kai, Xu, Jianfeng, Travis, Ruth C, Key, Timothy J, Siddiq, Afshan, Canzian, Federico, Takahashi, Atsushi, Kubo, Michiaki, Stanford, Janet L, Kolb, Suzanne, Gapstur, Susan M, Diver, W Ryan, Stevens, Victoria L, Strom, Sara S, Pettaway, Curtis A, Olama, Ali Amin Al, Kote-Jarai, Zsofia, Eeles, Rosalind A, Yeboah, Edward D, Tettey, Yao, Biritwum, Richard B, Adjei, Andrew A, Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Chokkalingam, Anand P, Isaacs, William B, Chen, Constance, Lindstrom, Sara, Le Marchand, Loic, Giovannucci, Edward L, Pomerantz, Mark, Long, Henry, Li, Fugen, Ma, Jing, Stampfer, Meir, John, Esther M, Ingles, Sue A, Kittles, Rick A, Murphy, Adam B, Blot, William J, Signorello, Lisa B, Zheng, Wei, Albanes, Demetrius, Virtamo, Jarmo, Weinstein, Stephanie, Nemesure, Barbara, Carpten, John, Leske, M Cristina, Wu, Suh-Yuh, Hennis, Anselm JM, Rybicki, Benjamin A, Neslund-Dudas, Christine, Hsing, Ann W, Chu, Lisa, Goodman, Phyllis J, Klein, Eric A, Zheng, S Lilly, Witte, John S, Casey, Graham, Riboli, Elio, Li, Qiyuan, Freedman, Matthew L, Hunter, David J, Gronberg, Henrik, Cook, Michael B, Nakagawa, Hidewaki, Kraft, Peter, Chanock, Stephen J, Easton, Douglas F, Henderson, Brian E, Coetzee, Gerhard A, Conti, David V, and Haiman, Christopher A

Subjects
Cancer, Human Genome, Biotechnology, Genetics, Urologic Diseases, Prostate Cancer, 2.1 Biological and endogenous factors, Aetiology, Asian People, Black People, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Hispanic or Latino, Humans, Linkage Disequilibrium, Male, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, White People, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.

Published
2015

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