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Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci
Fredrick R. Schumacher, Ali Amin Al Olama, Sonja I. Berndt, Sara Benlloch, Mahbubl Ahmed, Edward J. Saunders, Tokhir Dadaev, Daniel Leongamornlert, Ezequiel Anokian, Clara Cieza-Borrella, Chee Goh, Mark N. Brook, Xin Sheng, Laura Fachal, Joe Dennis, Jonathan P. Tyrer, Kenneth Muir, Artitaya Lophatananon, Victoria L. Stevens, Susan M. Gapstur, Brian D. Carter, Catherine M. Tangen, Phyllis J. Goodman, Ian M. Thompson, Jyotsna Batra, Suzanne K. Chambers, Leire Moya, Judith A. Clements, Lisa G. Horvath, Wayne D. Tilley, Gail P. Risbridger, Henrik Grönberg, Markus Aly, Tobias Nordström, Paul D.P. Pharoah, Nora Pashayan, Johanna Schleutker, Teuvo L.J. Tammela, Csilla Sipeky, Anssi Auvinen, Demetrius Albanes, Stephanie J. Weinstein, Alicja Wolk, Niclas Håkansson, Catharine West, Alison M. Dunning, N.G. Burnet, Lorelei A. Mucci, Edward Giovannucci, Gerald L. Andriole, Olivier Cussenot, Géraldine Cancel‐Tassin, Stella Koutros, Laura E. Beane Freeman, Karina D. Sørensen, Torben F. Ørntoft, Michael Borre, Lovise Mæhle, Eli Marie Grindedal, David E. Neal, Jenny Donovan, Freddie C. Hamdy, Richard M. Martin, Ruth C. Travis, Timothy J. Key, Robert J. Hamilton, Neil E. Fleshner, Antonio Finelli, Sue A. Ingles, Mariana C. Stern, Barry S. Rosenstein, Sarah L. Kerns, Harry Ostrer, Yong‐Jie Lu, Hong-Wei Zhang, Ninghan Feng, Xueying Mao, Xin Guo, Guomin Wang, Zan Sun, Graham G. Giles, Melissa C. Southey, Robert J. MacInnis, Liesel M. FitzGerald, Adam S. Kibel, Bettina F. Drake, Ana Vega, Antonio Gómez‐Caamaño, Robert Szulkin, Martin Eklund, Manolis Kogevinas, Javier Llorca, Gemma Castaño‐Vinyals, Kathryn L. Penney, Meir J. Stampfer, Jong Y. Park, Thomas A. Sellers, Hui‐Yi Lin, Janet L. Stanford, Cezary Cybulski, Dominika Wokołorczyk, Jan Lubiński, Elaine A. Ostrander, Milan S. Geybels, Børge G. Nordestgaard, Sune F. Nielsen, Maren Weischer, Rasmus Bisbjerg, Martin Andreas Røder, Peter Iversen, Hermann Brenner, Katarina Ćuk, Bernd Holleczek, Christiane Maier, Manuel Luedeke, Thomas Schnoeller, Jeri Kim, Christopher J. Logothetis, Esther M. John, Manuel R. Teixeira, Paula Paulo, Marta Cardoso, Susan L. Neuhausen, Linda Steele, Yuan Chun Ding, Kim De Ruyck, Gert De Meerleer, Piet Ost, Azad Hassan Abdul Razack, Jasmine Lim, Soo‐Hwang Teo, Daniel W. Lin, Lisa F. Newcomb, Davor Lessel, Marija Gamulin, Tomislav Kuliš, Radka Kaneva, Nawaid Usmani, Sandeep K. Singhal, Chavdar Slavov, Vanio Mitev, Matthew Parliament, Frank Claessens, Steven Joniau, Thomas Van den Broeck, Samantha Larkin, Paul A. Townsend, Claire Aukim-Hastie, Manuela Gago-Domínguez, Jose E. Castelao, Marı́a Elena Martı́nez, Monique J. Roobol, Guido Jenster, Ron H. N. van Schaik, F. Ménégaux, Thérèse Truong, Yves Akoli Koudou, Jianfeng Xu, Kay‐Tee Khaw, Lisa Cannon‐Albright, Hardev Pandha, Agnieszka Michael, Stephen N. Thibodeau, Shannon K. McDonnell, Daniel J. Schaid, Sara Lindström, Constance Turman, Jing Ma, David J. Hunter, Elio Ríboli, Afshan Siddiq, Federico Canzian, Laurence N. Kolonel, Loı̈c Le Marchand, Robert N. Hoover, Mitchell J. Machiela, Zuxi Cui, Peter Kraft, Christopher I. Amos, David V. Conti, Douglas F. Easton, Fredrik Wiklund, Stephen J. Chanock, Brian E. Henderson, Zsofia Kote‐Jarai, Christopher A. Haiman, Rosalind A. Eeles
Bibliographic record
VenueNature Genetics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of AlbertaPrincess Margaret Cancer Centre
FundersServicio Gallego de SaludCancer Council QueenslandCancer Council VictoriaMedical Research CouncilCanadian Institutes of Health ResearchNational Institutes of HealthWarwick Medical SchoolTurun Yliopistollinen KeskussairaalaDivision of Cancer Epidemiology and Genetics, National Cancer InstituteTampereen YliopistoNational Heart, Lung, and Blood InstitutePeter MacCallum Cancer CentreKarolinska InstitutetDOD Prostate Cancer Research ProgramCambridge University HospitalsQueensland University of TechnologyGriffith UniversityNational Cancer InstituteUniversity of BristolMonash Biomedicine Discovery Institute, Monash UniversityUniversity of OxfordUniversity of WarwickHarvard T.H. Chan School of Public HealthAarhus UniversitetshospitalNational Institute for Health and Care ResearchBreast Cancer Research FoundationUniversity of CambridgeUniversity College LondonUniversity of Southern CaliforniaCancer Research UKMonash UniversityAustralian Prostate Cancer ResearchTaysInstitut for Klinisk Medicin, Aarhus UniversitetProstate Cancer Foundation of AustraliaOvarian Cancer Research FundCase Western Reserve UniversityRoyal Marsden NHS Foundation TrustNational Cancer Research InstituteUppsala UniversitetProstate Cancer FoundationEuropean CommissionU.S. Department of DefenseTurun YliopistoAarhus UniversitetNational Health and Medical Research CouncilCancer Research Institute
KeywordsBiologyProstate cancerGeneticsCancerGenome-wide association studySingle-nucleotide polymorphismGenotypeGene
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.018
GPT teacher head0.361
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations1,010
Published2018
Admission routes2
Has abstractno