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Start Over Author "Collaborators, UKGPCS" Topic 030220 oncology & carcinogenesis
3 results on '"Collaborators, UKGPCS"'

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

Author

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

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

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

Published
2021
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2. Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer

Author

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

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

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

Published
2021
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3. African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer

Author

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

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

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

Published
2021
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