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Walsh T, Gulsuner S, Lee MK, Troester MA, Olshan AF, Earp HS, Perou CM, King MC. Inherited predisposition to breast cancer in the Carolina Breast Cancer Study. NPJ Breast Cancer 2021; 7:6. [PMID: 33479248 PMCID: PMC7820260 DOI: 10.1038/s41523-020-00214-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 12/17/2020] [Indexed: 11/09/2022] Open
Abstract
The Carolina Breast Cancer Study (CBCS) phases I-II was a case-control study of biological and social risk factors for invasive breast cancer that enrolled cases and controls between 1993 and 1999. Case selection was population-based and stratified by ancestry and age at diagnosis. Controls were matched to cases by age, self-identified race, and neighborhood of residence. Sequencing genomic DNA from 1370 cases and 1635 controls yielded odds ratios (with 95% confidence limits) for breast cancer of all subtypes of 26.7 (3.59, 189.1) for BRCA1, 8.8 (3.44, 22.48) for BRCA2, and 9.0 (2.06, 39.60) for PALB2; and for triple-negative breast cancer (TNBC) of 55.0 (7.01, 431.4) for BRCA1, 12.1 (4.18, 35.12) for BRCA2, and 10.8 (1.97, 59.11) for PALB2. Overall, 5.6% of patients carried a pathogenic variant in BRCA1, BRCA2, PALB2, or TP53, the four most highly penetrant breast cancer genes. Analysis of cases by tumor subtype revealed the expected association of TNBC versus other tumor subtypes with BRCA1, and suggested a significant association between TNBC versus other tumor subtypes with BRCA2 or PALB2 among African-American (AA) patients [2.95 (1.18, 7.37)], but not among European-American (EA) patients [0.62 (0.18, 2.09)]. AA patients with pathogenic variants in BRCA2 or PALB2 were 11 times more likely to be diagnosed with TNBC versus another tumor subtype than were EA patients with pathogenic variants in either of these genes (P = 0.001). If this pattern is confirmed in other comparisons of similarly ascertained AA and EA breast cancer patients, it could in part explain the higher prevalence of TNBC among AA breast cancer patients.
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Affiliation(s)
- Tom Walsh
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Suleyman Gulsuner
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Ming K Lee
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Melissa A Troester
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Andrew F Olshan
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - H Shelton Earp
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Charles M Perou
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Mary-Claire King
- Department of Medicine and Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA.
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2
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Rao JS, Zhang H, Kobetz E, Aldrich MC, Conway D. Predicting DNA methylation from genetic data lacking racial diversity using shared classified random effects. Genomics 2020; 113:1018-1028. [PMID: 33161089 DOI: 10.1016/j.ygeno.2020.10.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 09/24/2020] [Accepted: 10/30/2020] [Indexed: 10/23/2022]
Abstract
Public genomic repositories are notoriously lacking in racially and ethnically diverse samples. This limits the reaches of exploration and has in fact been one of the driving factors for the initiation of the All of Us project. Our particular focus here is to provide a model-based framework for accurately predicting DNA methylation from genetic data using racially sparse public repository data. Epigenetic alterations are of great interest in cancer research but public repository data is limited in the information it provides. However, genetic data is more plentiful. Our phenotype of interest is cervical cancer in The Cancer Genome Atlas (TCGA) repository. Being able to generate such predictions would nicely complement other work that has generated gene-level predictions of gene expression for normal samples. We develop a new prediction approach which uses shared random effects from a nested error mixed effects regression model. The sharing of random effects allows borrowing of strength across racial groups greatly improving predictive accuracy. Additionally, we show how to further borrow strength by combining data from different cancers in TCGA even though the focus of our predictions is DNA methylation in cervical cancer. We compare our methodology against other popular approaches including the elastic net shrinkage estimator and random forest prediction. Results are very encouraging with the shared classified random effects approach uniformly producing more accurate predictions - overall and for each racial group.
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Affiliation(s)
- J Sunil Rao
- University of Miami, FL, United States of America.
| | - Hang Zhang
- University of Miami, FL, United States of America
| | - Erin Kobetz
- University of Miami, FL, United States of America
| | - Melinda C Aldrich
- Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Douglas Conway
- Vanderbilt University Medical Center, Nashville, TN, United States of America
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3
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Badal S, Aiken W, Morrison B, Valentine H, Bryan S, Gachi A, Ragin C. Disparities in prostate cancer incidence and mortality rates: Solvable or not? Prostate 2020; 80:3-16. [PMID: 31702061 PMCID: PMC8378246 DOI: 10.1002/pros.23923] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 10/18/2019] [Indexed: 12/21/2022]
Abstract
Prostate cancer (PCa) is recognized as a disease possessing not only great variation in its geographic and racial distribution but also tremendous variation in its potential to cause morbidity and death and it, therefore, ought not to be considered a homogenous disease entity. Morbidity and death from PCa are disproportionately higher in men of African ancestry (MAA) who are generally observed to have more aggressive disease and worse outcomes following treatment compared to men of European ancestry (MEA). The higher rates of PCa among MAA relative to MEA appear to be multifactorial and related to inherent differences in biological aggressiveness; a continued lack of awareness of the disease and methods of prevention; a lower prevalence of screen-detected PCa; comparatively lower access to quality healthcare as well as systemic and institutionalized disparities in the administration of optimal care to MAA in developed countries such as the United States of America where high-quality care is available. Even when access to quality healthcare is assured in equal access settings, it appears that MAA still have worse outcomes after PCa treatment stage-for-stage and grade-for-grade compared to MEA, suggesting that, inherent racial, ethnic and biological differences are paramount in predicting poor outcomes. This review has explored the different contributing factors to the current disparities in PCa incidence and mortality rates with emphasis on the incongruence in how research has been conducted in understanding the disease towards developing therapies.
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Affiliation(s)
- Simone Badal
- Department of Basic Medical Sciences, Faculty of Medical Sciences, University of the West Indies, Kingston, Jamaica
| | - William Aiken
- Department of Surgery, Faculty of Medical Sciences, University of the West Indies, Kingston, Jamaica
| | - Belinda Morrison
- Department of Surgery, Faculty of Medical Sciences, University of the West Indies, Kingston, Jamaica
| | - Henkel Valentine
- Department of Basic Medical Sciences, Faculty of Medical Sciences, University of the West Indies, Kingston, Jamaica
| | - Sophia Bryan
- Department of Basic Medical Sciences, Faculty of Medical Sciences, University of the West Indies, Kingston, Jamaica
| | - Andrew Gachi
- Department of pathology, Aga Khan University Hospital, 3 Avenue, Parklands, Nairobi, Kenya
| | - Camille Ragin
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, PA, USA
- African Caribbean Cancer Consortium
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4
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Grant DJ, Manichaikul A, Alberg AJ, Bandera EV, Barnholtz‐Sloan J, Bondy M, Cote ML, Funkhouser E, Moorman PG, Peres LC, Peters ES, Schwartz AG, Terry PD, Wang X, Keku TO, Hoyo C, Berchuck A, Sandler DP, Taylor JA, O’Brien KM, Velez Edwards DR, Edwards TL, Beeghly‐Fadiel A, Wentzensen N, Pearce CL, Wu AH, Whittemore AS, McGuire V, Sieh W, Rothstein JH, Modugno F, Ness R, Moysich K, Rossing MA, Doherty JA, Sellers TA, Permuth‐Way JB, Monteiro AN, Levine DA, Setiawan VW, Haiman CA, LeMarchand L, Wilkens LR, Karlan BY, Menon U, Ramus S, Gayther S, Gentry‐Maharaj A, Terry KL, Cramer DW, Goode EL, Larson MC, Kaufmann SH, Cannioto R, Odunsi K, Etter JL, Huang R, Bernardini MQ, Tone AA, May T, Goodman MT, Thompson PJ, Carney ME, Tworoger SS, Poole EM, Lambrechts D, Vergote I, Vanderstichele A, Van Nieuwenhuysen E, Anton‐Culver H, Ziogas A, Brenton JD, Bjorge L, Salvensen HB, Kiemeney LA, Massuger LFAG, Pejovic T, Bruegl A, Moffitt M, Cook L, Le ND, Brooks‐Wilson A, Kelemen LE, Pharoah PD, Song H, Campbell I, Eccles D, DeFazio A, Kennedy CJ, Schildkraut JM. Evaluation of vitamin D biosynthesis and pathway target genes reveals UGT2A1/2 and EGFR polymorphisms associated with epithelial ovarian cancer in African American Women. Cancer Med 2019; 8:2503-2513. [PMID: 31001917 PMCID: PMC6536963 DOI: 10.1002/cam4.1996] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 12/03/2018] [Accepted: 01/08/2019] [Indexed: 02/02/2023] Open
Abstract
An association between genetic variants in the vitamin D receptor (VDR) gene and epithelial ovarian cancer (EOC) was previously reported in women of African ancestry (AA). We sought to examine associations between genetic variants in VDR and additional genes from vitamin D biosynthesis and pathway targets (EGFR, UGT1A, UGT2A1/2, UGT2B, CYP3A4/5, CYP2R1, CYP27B1, CYP24A1, CYP11A1, and GC). Genotyping was performed using the custom-designed 533,631 SNP Illumina OncoArray with imputation to the 1,000 Genomes Phase 3 v5 reference set in 755 EOC cases, including 537 high-grade serous (HGSOC), and 1,235 controls. All subjects are of African ancestry (AA). Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI). We further evaluated statistical significance of selected SNPs using the Bayesian False Discovery Probability (BFDP). A significant association with EOC was identified in the UGT2A1/2 region for the SNP rs10017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 1.2 × 10-6 , BFDP = 0.02); and an association with HGSOC was identified in the EGFR region for the SNP rs114972508 (per allele OR = 2.3, 95% CI = 1.6-3.4, P = 1.6 × 10-5 , BFDP = 0.29) and in the UGT2A1/2 region again for rs1017134 (per allele OR = 1.4, 95% CI = 1.2-1.7, P = 2.3 × 10-5 , BFDP = 0.23). Genetic variants in the EGFR and UGT2A1/2 may increase susceptibility of EOC in AA women. Future studies to validate these findings are warranted. Alterations in EGFR and UGT2A1/2 could perturb enzyme efficacy, proliferation in ovaries, impact and mark susceptibility to EOC.
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Affiliation(s)
- Delores J. Grant
- Department of Biological and Biomedical Sciences, Cancer Research ProgramJLC‐Biomedical/Biotechnology Research Institute, North Carolina Central UniversityDurhamNorth Carolina
| | - Ani Manichaikul
- Center for Public Health GenomicsUniversity of VirginiaCharlottesvilleVirginia
| | - Anthony J. Alberg
- Department of Epidemiology and Biostatistics, Arnold School of Public HealthUniversity of South CarolinaColumbiaSouth Carolina
| | - Elisa V. Bandera
- Department of Population ScienceRutgers Cancer Institute of New JerseyNew BrunswickNew Jersey
| | - Jill Barnholtz‐Sloan
- Case Comprehensive Cancer CenterCase Western Reserve University School of MedicineClevelandOhio
| | - Melissa Bondy
- Cancer Prevention and Population Sciences ProgramBaylor College of MedicineHoustonTexas
| | - Michele L. Cote
- Department of Oncology and the Karmanos Cancer Institute Population Studies and Disparities Research ProgramWayne State University School of MedicineDetroitMichigan
| | - Ellen Funkhouser
- Division of Preventive MedicineUniversity of Alabama at BirminghamBirminghamAlabama
| | - Patricia G. Moorman
- Department of Community and Family MedicineDuke University Medical CenterDurhamNorth Carolina
| | - Lauren C. Peres
- Center for Public Health GenomicsUniversity of VirginiaCharlottesvilleVirginia
| | - Edward S. Peters
- Epidemiology ProgramLouisiana State University Health Sciences Center School of Public HealthNew OrleansLouisisana
| | - Ann G. Schwartz
- Department of Oncology and the Karmanos Cancer Institute Population Studies and Disparities Research ProgramWayne State University School of MedicineDetroitMichigan
| | - Paul D. Terry
- Department of MedicineUniversity of Tennessee Medical Center – KnoxvilleKnoxvilleTennessee
| | - Xin‐Qun Wang
- Department of Public Health SciencesUniversity of VirginiaCharlottesvilleVirginia
| | - Temitope O. Keku
- Departments of Medicine and Nutrition, Division of Gastroenterology and HepatologyUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Cathrine Hoyo
- Department of Biological SciencesNorth Carolina State UniversityRaleighNorth Carolina
| | - Andrew Berchuck
- Department of Obstetrics and GynecologyDuke University Medical CenterDurhamNorth Carolina
| | - Dale P. Sandler
- Epidemiology Branch, Division of Intramural ResearchNational Institute of Environmental Health Sciences, National Institutes of HealthResearch Triangle ParkNorth Carolina
| | - Jack A. Taylor
- Epidemiology Branch, Division of Intramural ResearchNational Institute of Environmental Health Sciences, National Institutes of HealthResearch Triangle ParkNorth Carolina
| | - Katie M. O’Brien
- Epidemiology Branch, Division of Intramural ResearchNational Institute of Environmental Health Sciences, National Institutes of HealthResearch Triangle ParkNorth Carolina
| | - Digna R. Velez Edwards
- Vanderbilt Epidemiology Center, Center for Human Genetics Research, Department of Obstetrics and GynecologyVanderbilt University Medical CenterNashvilleTennessee
| | - Todd L. Edwards
- Division of Epidemiology, Center for Human Genetics Research, Department of MedicineVanderbilt University Medical CenterNashvilleTennessee
| | - Alicia Beeghly‐Fadiel
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology CenterInstitute for Medicine and Public Health, Vanderbilt University Medical CenterNashvilleTennessee
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and GeneticsNational Cancer InstituteBethesdaMaryland
| | - Celeste Leigh Pearce
- Department of EpidemiologyUniversity of Michigan School of Public HealthAnn ArborMichigan
- Department of Preventive Medicine, Keck School of MedicineUniversity of Southern California Norris Comprehensive Cancer CenterLos AngelesCalifornia
| | - Anna H. Wu
- Department of Preventive Medicine, Keck School of MedicineUniversity of Southern California Norris Comprehensive Cancer CenterLos AngelesCalifornia
| | - Alice S. Whittemore
- Department of Health Research and PolicyStanford University School of MedicineStanfordCalifornia
- Department of Biomedical Data ScienceStanford University School of MedicineStanfordCalifornia
| | - Valerie McGuire
- Department of Health Research and PolicyStanford University School of MedicineStanfordCalifornia
| | - Weiva Sieh
- Department of Population Health Science and PolicyIcahn School of Medicine at Mount SinaiNew YorkNew York
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Joseph H. Rothstein
- Department of Population Health Science and PolicyIcahn School of Medicine at Mount SinaiNew YorkNew York
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew York
| | - Francesmary Modugno
- Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive SciencesUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
- Department of EpidemiologyUniversity of Pittsburgh Graduate School of Public HealthPittsburghPennsylvania
- Ovarian Cancer Center of Excellence, Womens Cancer Research ProgramMagee‐Womens Research Institute and University of Pittsburgh Cancer InstitutePittsburghPennsylvania
| | - Roberta Ness
- The University of Texas School of Public HealthHoustonTexas
| | - Kirsten Moysich
- Department of Cancer Prevention and ControlRoswell Park Cancer InstituteBuffaloNew York
| | - Mary Anne Rossing
- Program in Epidemiology, Division of Public Health SciencesFred Hutchinson Cancer Research CenterSeattleWashington
- Department of EpidemiologyUniversity of WashingtonSeattleWashington
| | - Jennifer A. Doherty
- Department of Population Health SciencesHuntsman Cancer Institute, University of UtahSalt Lake City, Utah
| | | | | | | | - Douglas A. Levine
- Gynecology Service, Department of SurgeryMemorial Sloan Kettering Cancer CenterNew YorkNew York
- Gynecologic Oncology, Laura and Isaac Pearlmutter Cancer CenterNew York University Langone Medical CenterNew YorkNew York
| | | | - Christopher A. Haiman
- University of Southern California Norris Comprehensive Cancer CenterLos AngelesCalifornia
| | | | - Lynne R. Wilkens
- Cancer Epidemiology ProgramUniversity of Hawaii Cancer CenterHawaii
| | - Beth Y. Karlan
- Women's Cancer ProgramSamuel Oschin Comprehensive Cancer Institute, Cedars‐Sinai Medical CenterLos AngelesCalifornia
| | - Usha Menon
- MRC CTU at UCL, Institute of Clinical Trials and MethodologyUniversity College LondonLondonUK
| | - Susan Ramus
- School of Women's and Children's HealthUniversity of New South WalesNew South WalesAustralia
- The Kinghorn Cancer CentreGarvan Institute of Medical ResearchDarlinghurstNew South WalesAustralia
| | - Simon Gayther
- Center for Cancer Prevention and Translational GenomicsSamuel Oschin Comprehensive Cancer Institute, Cedars‐Sinai Medical CenterLos AngelesCalifornia
- Department of Biomedical SciencesCedars‐Sinai Medical CenterLos AngelesCalifornia
| | | | - Kathryn L. Terry
- Obstetrics and Gynecology Epidemiology CenterBrigham and Women's HospitalBostonMassachusetts
- Harvard T. H. Chan School of Public HealthBostonMassauchusetts
| | - Daniel W. Cramer
- Obstetrics and Gynecology Epidemiology CenterBrigham and Women's HospitalBostonMassachusetts
- Harvard T. H. Chan School of Public HealthBostonMassauchusetts
| | - Ellen L. Goode
- Department of Health Science Research, Division of EpidemiologyMayo ClinicRochesterMinnesota
| | - Melissa C. Larson
- Department of Health Science Research, Division of Biomedical Statistics and InformaticsMayo ClinicRochesterMinnesota
| | - Scott H. Kaufmann
- Departments of Medicine and PharmacologyMayo ClinicRochesterMinnesota
| | - Rikki Cannioto
- Cancer Pathology & Prevention, Division of Cancer Prevention and Population SciencesRoswell Park Cancer InstituteBuffaloNew York
| | - Kunle Odunsi
- Department of Gynecological OncologyRoswell Park Cancer InstituteBuffaloNew York
| | - John L. Etter
- Department of Cancer Prevention and ControlRoswell Park Cancer InstituteBuffaloNew York
| | - Ruea‐Yea Huang
- Center For ImmunotherapyRoswell Park Cancer InstituteBuffaloNew York
| | - Marcus Q. Bernardini
- Division of Gynecologic OncologyPrincess Margaret Hospital, University Health NetworkTorontoOntarioCanada
| | - Alicia A. Tone
- Division of Gynecologic OncologyPrincess Margaret Hospital, University Health NetworkTorontoOntarioCanada
| | - Taymaa May
- Division of Gynecologic OncologyPrincess Margaret Hospital, University Health NetworkTorontoOntarioCanada
| | - Marc T. Goodman
- Cancer Prevention and ControlSamuel Oschin Comprehensive Cancer Institute, Cedars‐Sinai Medical CenterLos AngelesCalifornia
- Department of Biomedical SciencesCommunity and Population Health Research Institute, Cedars‐Sinai Medical CenterLos AngelesCalifornia
| | - Pamela J. Thompson
- Cancer Prevention and ControlSamuel Oschin Comprehensive Cancer Institute, Cedars‐Sinai Medical CenterLos AngelesCalifornia
| | - Michael E. Carney
- Department of Obstetrics and GynecologyJohn A. Burns School of Medicine, University of HawaiiHonoluluHawaii
| | - Shelley S. Tworoger
- Channing Division of Network MedicineBrigham and Women's Hospital and Harvard Medical SchoolBostonMassachusetts
| | | | - Diether Lambrechts
- Vesalius Research Center, VIBLeuvenBelgium
- Laboratory for Translational Genetics, Department of OncologyUniversity of LeuvenBelgium
| | - Ignace Vergote
- Division of Gynecologic Oncology, Department of Obstetrics and Gynaecology and Leuven Cancer InstituteUniversity Hospitals LeuvenLeuvenBelgium
| | - Adriaan Vanderstichele
- Division of Gynecologic Oncology, Department of Obstetrics and Gynaecology and Leuven Cancer InstituteUniversity Hospitals LeuvenLeuvenBelgium
| | - Els Van Nieuwenhuysen
- Division of Gynecologic Oncology, Department of Obstetrics and Gynaecology and Leuven Cancer InstituteUniversity Hospitals LeuvenLeuvenBelgium
| | - Hoda Anton‐Culver
- Department of Epidemiology, Director of Genetic Epidemiology Research Institute, Center for Cancer Genetics Research & Prevention, School of MedicineUniversity of California IrvineIrvineCalifornia
| | - Argyrios Ziogas
- Department of EpidemiologyUniversity of California IrvineIrvineCalifornia
| | - James D. Brenton
- Cancer Research UK Cambridge InstituteUniversity of CambridgeCambridgeUK
| | - Line Bjorge
- Department of Gynecology and ObstetricsHaukeland University HospitalBergenNorway
- Centre for Cancer Biomarkers, Department of Clinical ScienceUniversity of BergenBergenNorway
| | - Helga B. Salvensen
- Department of Gynecology and ObstetricsHaukeland University HospitalBergenNorway
- Centre for Cancer Biomarkers, Department of Clinical ScienceUniversity of BergenBergenNorway
| | - Lambertus A. Kiemeney
- Radboud University Medical CenterRadboud Institute for Health SciencesNijmegenNetherlands
| | - Leon F. A. G. Massuger
- Department of Gynaecology, Radboud University Medical CenterRadboud Institute for Molecular Life sciencesNijmegenThe Netherlands
| | - Tanja Pejovic
- Department of Obstetrics & GynecologyOregon Health & Science UniversityPortlandOregon
- Knight Cancer Institute, Oregon Health & Science UniversityPortlandOregon
| | - Amanda Bruegl
- Department of Obstetrics & GynecologyOregon Health & Science UniversityPortlandOregon
- Knight Cancer Institute, Oregon Health & Science UniversityPortlandOregon
| | - Melissa Moffitt
- Department of Obstetrics & GynecologyOregon Health & Science UniversityPortlandOregon
- Knight Cancer Institute, Oregon Health & Science UniversityPortlandOregon
| | - Linda Cook
- Division of Epidemiology and Biostatistics, Department of Internal MedicineUniversity of New MexicoAlbuquerqueNew Mexico
| | - Nhu D. Le
- Cancer Control Research, British Columbia Cancer AgencyVancouverBritish ColumbiaCanada
| | - Angela Brooks‐Wilson
- Canada's Michael Smith Genome Sciences CentreBritish Columbia Cancer AgencyVancouverBritish ColumbiaCanada
- Department of Biomedical Physiology and KinesiologySimon Fraser UniversityBurnabyBritish ColumbiaCanada
| | - Linda E. Kelemen
- Hollings Cancer Center and Department of Public Health SciencesMedical University of South CarolinaCharlestonSouth Carolina
| | - Paul D.P. Pharoah
- Strangeways Research laboratory, Department of Oncology, Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
| | - Honglin Song
- Strangeways Research Laboratory, Department of OncologyUniversity of CambridgeCambridgeUK
| | - Ian Campbell
- Cancer Genetics Laboratory, Research DivisionPeter MacCallum Cancer CentreVictoriaAustralia
- Department of PathologyUniversity of MelbourneParkvilleVictoriaAustralia
| | - Diana Eccles
- Faculty of MedicineUniversity of SouthamptonSouthamptonUK
| | - Anna DeFazio
- Centre for Cancer ResearchThe Westmead Institute for Medical Research, The University of SydneySydneyNew South WalesAustralia
- Department of Gynaecological OncologyWestmead HospitalSydneyNew South WalesAustralia
| | - Catherine J. Kennedy
- Centre for Cancer ResearchThe Westmead Institute for Medical Research, The University of SydneySydneyNew South WalesAustralia
- Department of Gynaecological OncologyWestmead HospitalSydneyNew South WalesAustralia
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5
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Modeling Heterogeneity in the Genetic Architecture of Ethnically Diverse Groups Using Random Effect Interaction Models. Genetics 2019; 211:1395-1407. [PMID: 30796011 PMCID: PMC6456318 DOI: 10.1534/genetics.119.301909] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 01/24/2019] [Indexed: 01/08/2023] Open
Abstract
In humans, most genome-wide association studies have been conducted using data from Caucasians and many of the reported findings have not replicated in other populations. This lack of replication may be due to statistical issues (small sample sizes or confounding) or perhaps more fundamentally to differences in the genetic architecture of traits between ethnically diverse subpopulations. What aspects of the genetic architecture of traits vary between subpopulations and how can this be quantified? We consider studying effect heterogeneity using Bayesian random effect interaction models. The proposed methodology can be applied using shrinkage and variable selection methods, and produces useful information about effect heterogeneity in the form of whole-genome summaries (e.g., the proportions of variance of a complex trait explained by a set of SNPs and the average correlation of effects) as well as SNP-specific attributes. Using simulations, we show that the proposed methodology yields (nearly) unbiased estimates when the sample size is not too small relative to the number of SNPs used. Subsequently, we used the methodology for the analyses of four complex human traits (standing height, high-density lipoprotein, low-density lipoprotein, and serum urate levels) in European-Americans (EAs) and African-Americans (AAs). The estimated correlations of effects between the two subpopulations were well below unity for all the traits, ranging from 0.73 to 0.50. The extent of effect heterogeneity varied between traits and SNP sets. Height showed less differences in SNP effects between AAs and EAs whereas HDL, a trait highly influenced by lifestyle, exhibited a greater extent of effect heterogeneity. For all the traits, we observed substantial variability in effect heterogeneity across SNPs, suggesting that effect heterogeneity varies between regions of the genome.
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6
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Torres D, Lorenzo Bermejo J, Garcia Mesa K, Gilbert M, Briceño I, Pohl-Zeidler S, González Silos R, Boekstegers F, Plass C, Hamann U. Interaction between genetic ancestry and common breast cancer susceptibility variants in Colombian women. Int J Cancer 2019; 144:2181-2191. [PMID: 30485434 DOI: 10.1002/ijc.32023] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 11/05/2018] [Indexed: 01/31/2023]
Abstract
Latino women show lower incidences of breast cancer (BC) than non-Hispanic whites. Large-scale genetic association studies have identified variants robustly associated with BC risk in European women. We examine here the relevance of these variants to Colombian BC and possible interactions with genetic ancestry. Native American, European and African proportions were estimated for 1022 Colombian BC cases and 1023 controls. Logistic regression was applied to assess the association between 78 variants and BC risk and interactions between the variants and ancestry proportions. We constructed a multifactorial risk score combining established BC risk factors, associated risk variants and individual ancestry proportions. Each 1% increase in the Native American proportion translated into a 2.2% lower BC risk (95% CI: 1.4-2.9). Thirteen variants were associated with BC in Colombian women, with allele frequencies and risk effects partially different from European women. Ancestry proportions moderated the risk effects of two variants. The ability of Native American proportions to separate Colombian cases and controls (area-under-the-curve (AUC) = 0.61) was similar to the discriminative ability of family history of BC in first-degree female relatives (AUC = 0.58) or the combined effect of all 13 associated risk variants (AUC = 0.57). Our findings demonstrate ample potential for individualized BC prevention in Hispanic women taking advantage of individual Native American proportions, information on established susceptibility factors and recently identified common risk variants.
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Affiliation(s)
- Diana Torres
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute of Human Genetics, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Justo Lorenzo Bermejo
- Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
| | - Karen Garcia Mesa
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
| | - Michael Gilbert
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ignacio Briceño
- Institute of Human Genetics, Pontificia Universidad Javeriana, Bogota, Colombia.,Universidad de la Sabana, Bogota, Colombia
| | - Svenja Pohl-Zeidler
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rosa González Silos
- Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
| | - Felix Boekstegers
- Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
| | - Christoph Plass
- Division of Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Brinton LA, Awuah B, Nat Clegg-Lamptey J, Wiafe-Addai B, Ansong D, Nyarko KM, Wiafe S, Yarney J, Biritwum R, Brotzman M, Adjei AA, Adjei E, Aitpillah F, Edusei L, Dedey F, Nyante SJ, Oppong J, Osei-Bonsu E, Titiloye N, Vanderpuye V, Brew Abaidoo E, Arhin B, Boakye I, Frempong M, Ohene Oti N, Okyne V, Figueroa JD. Design considerations for identifying breast cancer risk factors in a population-based study in Africa. Int J Cancer 2017; 140:2667-2677. [PMID: 28295287 DOI: 10.1002/ijc.30688] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 01/30/2017] [Accepted: 02/08/2017] [Indexed: 02/04/2023]
Abstract
Although breast cancer is becoming more prevalent in Africa, few epidemiologic studies have been undertaken and appropriate methodologic approaches remain uncertain. We therefore conducted a population-based case-control study in Accra and Kumasi, Ghana, enrolling 2,202 women with lesions suspicious for breast cancer and 2,161 population controls. Biopsy tissue for cases prior to neoadjuvant therapy (if given), blood, saliva and fecal samples were sought for study subjects. Response rates, risk factor prevalences and odds ratios for established breast cancer risk factors were calculated. A total of 54.5% of the recruited cases were diagnosed with malignancies, 36.0% with benign conditions and 9.5% with indeterminate diagnoses. Response rates to interviews were 99.2% in cases and 91.9% in controls, with the vast majority of interviewed subjects providing saliva (97.9% in cases vs. 98.8% in controls) and blood (91.8% vs. 82.5%) samples; lower proportions (58.1% vs. 46.1%) provided fecal samples. While risk factor prevalences were unique as compared to women in other countries (e.g., less education, higher parity), cancer risk factors resembled patterns identified elsewhere (elevated risks associated with higher levels of education, familial histories of breast cancer, low parity and larger body sizes). Subjects with benign conditions were younger and exhibited higher socioeconomic profiles (e.g., higher education and lower parity) than those with malignancies, suggesting selective referral influences. While further defining breast cancer risk factors in Africa, this study showed that successful population-based interdisciplinary studies of cancer in Africa are possible but require close attention to diagnostic referral biases and standardized and documented approaches for high-quality data collection, including biospecimens.
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Affiliation(s)
- Louise A Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
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- Korle Bu Teaching Hospital, Accra, Ghana.,University of Ghana, Accra, Ghana
| | - Sarah J Nyante
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.,Currently at the University of North Carolina at Chapel Hill, Chapel Hill, NC
| | | | | | | | | | | | | | | | | | | | | | - Jonine D Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.,Currently at the Usher Institute of Population Health Sciences and Informatics, Edinburgh Cancer Research Centre, Edinburgh, Scotland
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8
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Keller BM, McCarthy AM, Chen J, Armstrong K, Conant EF, Domchek SM, Kontos D. Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography. BMC Cancer 2015; 15:143. [PMID: 25881232 PMCID: PMC4365961 DOI: 10.1186/s12885-015-1159-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 03/04/2015] [Indexed: 12/16/2022] Open
Abstract
Background Breast density and single-nucleotide polymorphisms (SNPs) have both been associated with breast cancer risk. To determine the extent to which these two breast cancer risk factors are associated, we investigate the association between a panel of validated SNPs related to breast cancer and quantitative measures of mammographic density in a cohort of Caucasian and African-American women. Methods In this IRB-approved, HIPAA-compliant study, we analyzed a screening population of 639 women (250 African American and 389 Caucasian) who were tested with a validated panel assay of 12 SNPs previously associated to breast cancer risk. Each woman underwent digital mammography as part of routine screening and all were interpreted as negative. Both absolute and percent estimates of area and volumetric density were quantified on a per-woman basis using validated software. Associations between the number of risk alleles in each SNP and the density measures were assessed through a race-stratified linear regression analysis, adjusted for age, BMI, and Gail lifetime risk. Results The majority of SNPs were not found to be associated with any measure of breast density. SNP rs3817198 (in LSP1) was significantly associated with both absolute area (p = 0.004) and volumetric (p = 0.019) breast density in Caucasian women. In African-American women, SNPs rs3803662 (in TNRC9/TOX3) and rs4973768 (in NEK10) were significantly associated with absolute (p = 0.042) and percent (p = 0.028) volume density respectively. Conclusions The majority of SNPs investigated in our study were not found to be significantly associated with breast density, even when accounting for age, BMI, and Gail risk, suggesting that these two different risk factors contain potentially independent information regarding a woman’s risk to develop breast cancer. Additionally, the few statistically significant associations between breast density and SNPs were different for Caucasian versus African American women. Larger prospective studies are warranted to validate our findings and determine potential implications for breast cancer risk assessment. Electronic supplementary material The online version of this article (doi:10.1186/s12885-015-1159-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Brad M Keller
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
| | - Anne Marie McCarthy
- Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Katrina Armstrong
- Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Emily F Conant
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
| | - Susan M Domchek
- Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Despina Kontos
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
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Assessing interactions of two loci (rs4242382 and rs10486567) in familial prostate cancer: statistical evaluation of epistasis. PLoS One 2014; 9:e89508. [PMID: 24586834 PMCID: PMC3934901 DOI: 10.1371/journal.pone.0089508] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2013] [Accepted: 01/21/2014] [Indexed: 12/02/2022] Open
Abstract
Understanding the impact of multiple genetic variants and their interactions on the disease penetrance of familial multiple prostate cancer is very relevant to the overall understanding of carcinogenesis. We assessed the joint effect of two loci on rs4242382 at 8q24 and rs10486567 at 7p15.2 to this end. We analyzed the data from a Finnish family-based genetic study, which was composed of 947 men including 228 cases in 75 families, to evaluate the respective effects of the two loci on the disease penetrance; in particular, the occurrence and number of prostate cancer cases within a family were utilized to evaluate the interactions between the two loci under the additive and multiplicative Poisson regression models. The risk alleles A at rs4242382 (OR = 1.14, 95% CI 1.08–1.19, P<0.0001) and a risk allele A at rs10486567 (OR = 1.06, 96%CI 1.01–1.11, P = 0.0208) were found to be associated with an increased risk of familial PrCa, especially with four or more cases within a family. A multiplicative model fitted the joint effect better than an additive model (likelihood ratio test X2 = 13.89, P<0.0001). The influence of the risk allele A at rs10486567 was higher in the presence of the risk allele A at rs4242382 (OR = 1.09 (1.01–1.18) vs. 1.01 (0.95–1.07)). Similar findings were observed in non-aggressive PrCa, but not in aggressive PrCa. We demonstrated that two loci (rs4242382 and rs10486567) are highly associated with familial multiple PrCa, and the gene-gene interaction or statistical epistasis was consistent with the Fisher's multiplicative model. These loci's association and epistasis were observed for non-aggressive but not for aggressive tumors. The proposed statistical model can be further developed to accommodate multi-loci interactions to provide further insights into epistasis.
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Park JM, Song KH, Lim JS, Kim JW, Sul CK. Is the Expression of Androgen Receptor Protein Associated With the Length of AC Repeats in the Type III 5-α Reductase Gene in Prostate Cancer Patients? Korean J Urol 2013; 54:404-8. [PMID: 23789051 PMCID: PMC3685642 DOI: 10.4111/kju.2013.54.6.404] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2013] [Accepted: 04/21/2013] [Indexed: 01/18/2023] Open
Abstract
Purpose Type III 5-α reductase (SRD5A3; steroid 5-α reductase 3) may be associated with the progression of prostate cancer (PCa). The aim of our study was to determine whether the length of AC repeats in the SRD5A3 gene is associated with the risk of PCa and the expression of androgen receptor (AR) protein in Korean men. Materials and Methods We compared the length of AC repeats in the short tandem repeat (STR) region of the SRD5A3 gene in 68 PCa patients and 81 control subjects by genotyping. A total of 55 patients in the PCa group underwent radical prostatectomy. We evaluated the expression of AR protein by using Western blotting and tested the association between the type of AC repeats in the SRD5A3 gene and AR protein expression and clinical and pathologic parameters. Results The short type of STR had less than 21 copies of AC repeats in the SRD5A3 gene. The SS type (short and short type) of STR of the SRD5A3 gene was 2.2 times as likely to occur in PCa patients as in controls (odds ratio, 2.21; 95% confidence interval, 1.14 to 4.31; p=0.019). However, AC repeats of the SRD5A3 gene were not associated with AR protein expression or clinical or pathologic parameters in PCa samples. Conclusions These results suggest that the short AC repeats of SRD5A3 polymorphism are associated with an increased risk of PCa. SRD5A3 polymorphism may contribute to a genetic predisposition for PCa.
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Affiliation(s)
- Jong Mok Park
- Department of Urology, Chungnam National University School of Medicine, Daejeon, Korea
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11
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Fejerman L, Stern MC, Ziv E, John EM, Torres-Mejia G, Hines LM, Wolff R, Wang W, Baumgartner KB, Giuliano AR, Slattery ML. Genetic ancestry modifies the association between genetic risk variants and breast cancer risk among Hispanic and non-Hispanic white women. Carcinogenesis 2013; 34:1787-93. [PMID: 23563089 DOI: 10.1093/carcin/bgt110] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Hispanic women in the USA have lower breast cancer incidence than non-Hispanic white (NHW) women. Genetic factors may contribute to this difference. Breast cancer genome-wide association studies (GWAS) conducted in women of European or Asian descent have identified multiple risk variants. We tested the association between 10 previously reported single nucleotide polymorphisms (SNPs) and risk of breast cancer in a sample of 4697 Hispanic and 3077 NHW women recruited as part of three population-based case-control studies of breast cancer. We used stratified logistic regression analyses to compare the associations with different genetic variants in NHWs and Hispanics classified by their proportion of Indigenous American (IA) ancestry. Five of 10 SNPs were statistically significantly associated with breast cancer risk. Three of the five significant variants (rs17157903-RELN, rs7696175-TLR1 and rs13387042-2q35) were associated with risk among Hispanics but not in NHWs. The odds ratio (OR) for the heterozygous at 2q35 was 0.75 [95% confidence interval (CI) = 0.50-1.15] for low IA ancestry and 1.38 (95% CI = 1.04-1.82) for high IA ancestry (P interaction 0.02). The ORs for association at RELN were 0.87 (95% CI = 0.59-1.29) and 1.69 (95% CI = 1.04-2.73), respectively (P interaction 0.03). At the TLR1 locus, the ORs for women homozygous for the rare allele were 0.74 (95% CI = 0.42-1.31) and 1.73 (95% CI = 1.19-2.52) (P interaction 0.03). Our results suggest that the proportion of IA ancestry modifies the magnitude and direction of the association of 3 of the 10 previously reported variants. Genetic ancestry should be considered when assessing risk in women of mixed descent and in studies designed to discover causal mutations.
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Affiliation(s)
- Laura Fejerman
- Department of Medicine, Division of General Internal Medicine, Institute for Human Genetics and Helen Diller Family Comprehensive Cancer Center, University of California-San Francisco, CA 94158, USA.
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12
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McCarthy AM, Armstrong K, Handorf E, Boghossian L, Jones M, Chen J, Demeter MB, McGuire E, Conant EF, Domchek SM. Incremental impact of breast cancer SNP panel on risk classification in a screening population of white and African American women. Breast Cancer Res Treat 2013; 138:889-98. [PMID: 23474973 DOI: 10.1007/s10549-013-2471-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2013] [Accepted: 02/26/2013] [Indexed: 11/25/2022]
Abstract
Breast cancer risk prediction remains imperfect, particularly among non-white populations. This study examines the impact of including single-nucleotide polymorphism (SNP) alleles in risk prediction for white and African American women undergoing screening mammogram. Using a prospective cohort study, standard risk information and buccal swabs were collected at the time of screening mammography. A 12 SNP panel was performed by deCODE genetics. Five-year and lifetime risks incorporating SNPs were calculated by multiplying estimated Breast Cancer Risk Assessment Tool (BCRAT) risk by the total genetic risk ratio. Concordance between the BCRAT and the combined model (BCRAT + SNPs) in identifying high-risk women was measured using the kappa statistic. SNP data were available for 810 women (39 % African American, 55 % white). The mean BCRAT 5-year risk was 1.71 % for whites and 1.18 % for African Americans. Mean genetic risk ratios were 1.09 in whites and 1.29 in African Americans. Among whites, three SNPs had higher frequencies, and among African Americans, seven SNPs had higher and four had lower high-risk allele frequencies than previously reported. Agreement between the BCRAT and the combined model was relatively low for identifying high-risk women (5-year κ = 0.54, lifetime κ = 0.36). Addition of SNPs had the greatest effect among African Americans, with 12.4 % identified as having high-5-year risk by BCRAT, but 33 % by the combined model. A greater proportion of African Americans were reclassified as having high-5-year risk than whites using the combined model (21 vs. 10 %). The addition of SNPs to the BCRAT reclassifies the high-risk status of some women undergoing screening mammography, particularly African Americans. Further research is needed to determine the clinical validity and utility of the SNP panel for use in breast cancer risk prediction, particularly among African Americans for whom these risk alleles have generally not been validated.
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Affiliation(s)
- Anne Marie McCarthy
- Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Room 1009, Philadelphia, PA 19104, USA.
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Batai K, Shah E, Murphy AB, Newsome J, Ruden M, Ahaghotu C, Kittles RA. Fine-mapping of IL16 gene and prostate cancer risk in African Americans. Cancer Epidemiol Biomarkers Prev 2012; 21:2059-68. [PMID: 22923025 DOI: 10.1158/1055-9965.epi-12-0707] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Prostate cancer is the most common type of cancer among men in the United States, and its incidence and mortality rates are disproportionate among ethnic groups. Although genome-wide association studies of European descents have identified candidate loci associated with prostate cancer risk, including a variant in IL16, replication studies in African Americans (AA) have been inconsistent. Here we explore single-nucleotide polymorphism (SNP) variation in IL16 in AAs and test for association with prostate cancer. METHODS Association tests were conducted for 2,257 genotyped and imputed SNPs spanning IL16 in 605 AA prostate cancer cases and controls from Washington, D.C. Eleven of them were also genotyped in a replication population of 1,093 AAs from Chicago. We tested for allelic association adjusting for age, global and local West African ancestry. RESULTS Analyses of genotyped and imputed SNPs revealed that a cluster of IL16 SNPs were significantly associated with prostate cancer risk. The strongest association was found at rs7175701 (P = 9.8 × 10(-8)). In the Chicago population, another SNP (rs11556218) was associated with prostate cancer risk (P = 0.01). In the pooled analysis, we identified three independent loci within IL16 that were associated with prostate cancer risk. SNP expression quantitative trait loci analyses revealed that rs7175701 is predicted to influence the expression of IL16 and other cancer-related genes. CONCLUSION Our study provides evidence that IL16 polymorphisms play a role in prostate cancer susceptibility among AAs. IMPACT Our findings are significant given that there has been limited focus on the role of IL16 genetic polymorphisms on prostate cancer risk in AAs.
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Affiliation(s)
- Ken Batai
- Institute of Human Genetics, College of Medicine, School of Public Health, University of Illinois at Chicago, Chicago, IL 60607-4067, USA
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