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Research Article

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

  • Fergus J. Couch equal contributor mail,

    equal contributor Contributed equally to this work with: Fergus J. Couch, Douglas F. Easton, Georgia Chenevix-Trench

    couch.fergus@mayo.edu (Fergus J Couch); Antonis@srl.cam.ac.uk (Antonis C Antoniou)

    Affiliation: Department of Laboratory Medicine and Pathology, and Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

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  • Xianshu Wang,

    Affiliation: Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, United States of America

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  • Lesley McGuffog,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Andrew Lee,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Curtis Olswold,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

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  • Karoline B. Kuchenbaecker,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Penny Soucy,

    Affiliation: Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Québec and Laval University, Québec City, Canada

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  • Zachary Fredericksen,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

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  • Daniel Barrowdale,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Joe Dennis,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Mia M. Gaudet,

    Affiliation: Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, United States of America

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  • Ed Dicks,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Matthew Kosel,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

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  • Sue Healey,

    Affiliation: Genetics Department, Queensland Institute of Medical Research, Brisbane, Australia

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  • Olga M. Sinilnikova,

    Affiliations: Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon–Centre Léon Bérard, Lyon, France, INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en Cancérologie de Lyon, Lyon, France

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  • Adam Lee,

    Affiliation: Department of Molecular Pharmacology and Experimental Therapeutics (MPET), Mayo Clinic, Rochester, Minnesota, United States of America

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  • François Bacot,

    Affiliation: Centre d'Innovation Génome Québec et Université McGill, Montreal, Canada

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  • Daniel Vincent,

    Affiliation: Centre d'Innovation Génome Québec et Université McGill, Montreal, Canada

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  • Frans B. L. Hogervorst,

    Affiliation: Family Cancer Clinic, Netherlands Cancer Institute, Amsterdam, The Netherlands

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  • Susan Peock,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Dominique Stoppa-Lyonnet,

    Affiliations: Institut Curie, Department of Tumour Biology, Paris, France, Institut Curie, INSERM U830, Paris, France, Université Paris Descartes, Sorbonne Paris Cité, Paris, France

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  • Anna Jakubowska,

    Affiliation: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

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  • kConFab Investigators,

    Affiliation: Kathleen Cuningham Consortium for Research into Familial Breast Cancer–Peter MacCallum Cancer Center, Melbourne, Australia

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  • Paolo Radice,

    Affiliations: Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy, IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy

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  • Rita Katharina Schmutzler,

    Affiliation: Centre of Familial Breast and Ovarian Cancer, Department of Gynaecology and Obstetrics and Centre for Integrated Oncology (CIO), Center for Molecular Medicine Cologne (CMMC), University Hospital of Cologne, Cologne, Germany

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  • SWE-BRCA,

    Affiliation: Department of Laboratory Medicine and Pathology, and Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

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  • Susan M. Domchek,

    Affiliation: Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

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  • Marion Piedmonte,

    Affiliation: Gynecologic Oncology Group Statistical and Data Center, Roswell Park Cancer Institute, Buffalo, New York, United States of America

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  • Christian F. Singer,

    Affiliation: Department of Obstetrics and Gynecology, and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria

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  • Eitan Friedman,

    Affiliation: Sheba Medical Center, Tel Aviv, Israel

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  • Mads Thomassen,

    Affiliation: Department of Clinical Genetics, Odense University Hospital, Odense, Denmark

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  • Ontario Cancer Genetics Network,

    Affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada

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  • Thomas V. O. Hansen,

    Affiliation: Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

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  • Susan L. Neuhausen,

    Affiliation: Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, United States of America

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  • Csilla I. Szabo,

    Affiliation: Center for Translational Cancer Research, Department of Biological Sciences, University of Delaware, Newark, Delaware, United States of America

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  • Ignacio Blanco,

    Affiliation: Genetic Counseling Unit, Hereditary Cancer Program, IDIBELL–Catalan Institute of Oncology, Barcelona, Spain

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  • Mark H. Greene,

    Affiliation: Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, United States of America

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  • Beth Y. Karlan,

    Affiliation: Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

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  • Judy Garber,

    Affiliation: Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America

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  • Catherine M. Phelan,

    Affiliation: Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida, United States of America

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  • Jeffrey N. Weitzel,

    Affiliation: Clinical Cancer Genetics (for the City of Hope Clinical Cancer Genetics Community Research Network), City of Hope, Duarte, California, United States of America

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  • Marco Montagna,

    Affiliation: Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto IOV–IRCCS, Padua, Italy

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  • Edith Olah,

    Affiliation: Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary

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  • Irene L. Andrulis,

    Affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada

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  • Andrew K. Godwin,

    Affiliation: Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas, United States of America

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  • Drakoulis Yannoukakos,

    Affiliation: Molecular Diagnostics Laboratory, IRRP, National Centre for Scientific Research Demokritos, Aghia Paraskevi Attikis, Athens, Greece

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  • David E. Goldgar,

    Affiliation: Department of Dermatology, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

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  • Trinidad Caldes,

    Affiliation: Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, Madrid, Spain

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  • Heli Nevanlinna,

    Affiliation: Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland

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  • Ana Osorio,

    Affiliation: Human Genetics Group, Spanish National Cancer Centre (CNIO), and Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain

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  • Mary Beth Terry,

    Affiliation: Department of Epidemiology, Columbia University, New York, New York, United States of America

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  • Mary B. Daly,

    Affiliation: Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America

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  • Elizabeth J. van Rensburg,

    Affiliation: Department of Genetics, University of Pretoria, Pretoria, South Africa

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  • Ute Hamann,

    Affiliation: Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany

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  • Susan J. Ramus,

    Affiliation: Department of Preventive Medicine, Keck School of Medicine, University of Southern California, California, United States of America

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  • Amanda Ewart Toland,

    Affiliation: Divison of Human Cancer Genetics, Departments of Internal Medicine and Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, United States of America

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  • Maria A. Caligo,

    Affiliation: Section of Genetic Oncology, Department of Laboratory Medicine, University of Pisa and University Hospital of Pisa, Pisa, Italy

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  • Olufunmilayo I. Olopade,

    Affiliation: Center for Clinical Cancer Genetics and Global Health, University of Chicago Medical Center, Chicago, Illinois, United States of America

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  • Nadine Tung,

    Affiliation: Department of Medical Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America

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  • Kathleen Claes,

    Affiliation: Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium

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  • Mary S. Beattie,

    Affiliation: Departments of Medicine, Epidemiology, and Biostatistics, University of California San Francisco, San Francisco, California, United States of America

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  • Melissa C. Southey,

    Affiliation: Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, Australia

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  • Evgeny N. Imyanitov,

    Affiliation: N. N. Petrov Institute of Oncology, St. Petersburg, Russia

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  • Marc Tischkowitz,

    Affiliation: Program in Cancer Genetics, Departments of Human Genetics and Oncology, McGill University, Montreal, Quebec, Canada

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  • Ramunas Janavicius,

    Affiliation: Vilnius University Hospital Santariskiu Clinics, Hematology, Oncology and Transfusion Medicine Center, Department of Molecular and Regenerative Medicine, Vilnius, Lithuania

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  • Esther M. John,

    Affiliation: Department of Epidemiology, Cancer Prevention Institute of California, Fremont, Califoria, United States of America

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  • Ava Kwong,

    Affiliation: The Hong Kong Hereditary Breast Cancer Family Registry, Cancer Genetics Center, Hong Kong Sanatorium and Hospital, Hong Kong, China

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  • Orland Diez,

    Affiliation: Oncogenetics Laboratory, University Hospital Vall d'Hebron and Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain

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  • Judith Balmaña,

    Affiliation: Department of Medical Oncology, University Hospital, Vall d'Hebron, Barcelona, Spain

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  • Rosa B. Barkardottir,

    Affiliation: Department of Pathology, Landspitali University Hospital and BMC, Faculty of Medicine, University of Iceland, Reykjavik, Iceland

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  • Banu K. Arun,

    Affiliation: Department of Breast Medical Oncology and Clinical Cancer Genetics, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America

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  • Gad Rennert,

    Affiliation: Clalit National Israeli Cancer Control Center and Department of Community Medicine and Epidemiology, Carmel Medical Center and B. Rappaport Faculty of Medicine, Haifa, Israel

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  • Soo-Hwang Teo,

    Affiliation: Cancer Research Initiatives Foundation, Sime Darby Medical Centre and University Malaya Cancer Research Institute, University of Malaya, Kuala Lumpur, Malaysia

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  • Patricia A. Ganz,

    Affiliation: UCLA Schools of Medicine and Public Health, Division of Cancer Prevention and Control Research, Jonsson Comprehensive Cancer Center, Los Angeles, California, United States of America

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  • Ian Campbell,

    Affiliation: VBCRC Cancer Genetics Laboratory, Peter MacCallum Cancer Centre, Melbourne, Australia

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  • Annemarie H. van der Hout,

    Affiliation: Department of Genetics, University Medical Center, Groningen University, Groningen, The Netherlands

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  • Carolien H. M. van Deurzen,

    Affiliation: Department of Pathology, Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, The Netherlands

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  • Caroline Seynaeve,

    Affiliation: Department of Medical Oncology, Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, The Netherlands

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  • Encarna B. Gómez Garcia,

    Affiliation: Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, MUMC, Maastricht, The Netherlands

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  • Flora E. van Leeuwen,

    Affiliation: Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands

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  • Hanne E. J. Meijers-Heijboer,

    Affiliation: Department of Clinical Genetics, VU University Medical Centre, Amsterdam, The Netherlands

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  • Johannes J. P. Gille,

    Affiliation: Department of Clinical Genetics, VU University Medical Centre, Amsterdam, The Netherlands

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  • Margreet G. E. M. Ausems,

    Affiliation: Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The Netherlands

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  • Marinus J. Blok,

    Affiliation: Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands

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  • Marjolijn J. L. Ligtenberg,

    Affiliation: Department of Human Genetics and Department of Pathology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

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  • Matti A. Rookus,

    Affiliation: Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands

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  • Peter Devilee,

    Affiliation: Department of Human Genetics and Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands

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  • Senno Verhoef,

    Affiliation: Family Cancer Clinic, Netherlands Cancer Institute, Amsterdam, The Netherlands

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  • Theo A. M. van Os,

    Affiliation: Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands

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  • Juul T. Wijnen,

    Affiliation: Department of Human Genetics and Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands

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  • HEBON,

    Affiliation: The Hereditary Breast and Ovarian Cancer Research Group Netherlands, Netherlands Cancer Institute, Amsterdam, The Netherlands

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  • EMBRACE,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Debra Frost,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Steve Ellis,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Elena Fineberg,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • Radka Platte,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

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  • D. Gareth Evans,

    Affiliation: Genetic Medicine, Manchester Academic Health Sciences Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom

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  • Louise Izatt,

    Affiliation: Clinical Genetics, Guy's and St. Thomas' NHS Foundation Trust, London, United Kingdom

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  • Rosalind A. Eeles,

    Affiliation: Oncogenetics Team, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, United Kingdom

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  • Julian Adlard,

    Affiliation: Yorkshire Regional Genetics Service, Leeds, United Kingdom

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  • Diana M. Eccles,

    Affiliation: University of Southampton Faculty of Medicine, Southampton University Hospitals NHS Trust, Southampton, United Kingdom

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  • Jackie Cook,

    Affiliation: Sheffield Clinical Genetics Service, Sheffield Children's Hospital, Sheffield, United Kingdom

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  • Carole Brewer,

    Affiliation: Department of Clinical Genetics, Royal Devon and Exeter Hospital, Exeter, United Kingdom

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  • Fiona Douglas,

    Affiliation: Institute of Genetic Medicine, Centre for Life, Newcastle Upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom

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  • Shirley Hodgson,

    Affiliation: Department of Clinical Genetics, St George's University of London, London, United Kingdom

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  • Patrick J. Morrison,

    Affiliation: Northern Ireland Regional Genetics Centre, Belfast Health and Social Care Trust, and Department of Medical Genetics, Queens University Belfast, Belfast, United Kingdom

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  • Lucy E. Side,

    Affiliation: North East Thames Regional Genetics Service, Great Ormond Street Hospital for Children NHS Trust and Institute for Womens Health, University College London, London, United Kingdom

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  • Alan Donaldson,

    Affiliation: Clinical Genetics Department, St Michael's Hospital, Bristol, United Kingdom

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  • Catherine Houghton,

    Affiliation: Cheshire and Merseyside Clinical Genetics Service, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom

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  • Mark T. Rogers,

    Affiliation: All Wales Medical Genetics Services, University Hospital of Wales, Cardiff, United Kingdom

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  • Huw Dorkins,

    Affiliation: North West Thames Regional Genetics Service, Kennedy-Galton Centre, Harrow, United Kingdom

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  • Jacqueline Eason,

    Affiliation: Nottingham Clinical Genetics Service, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom

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  • Helen Gregory,

    Affiliation: North of Scotland Regional Genetics Service, NHS Grampian and University of Aberdeen, Foresterhill, Aberdeen, United Kingdom

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  • Emma McCann,

    Affiliation: All Wales Medical Genetics Services, Glan Clwyd Hospital, Rhyl, United Kingdom

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  • Alex Murray,

    Affiliation: All Wales Medical Genetics Services, Singleton Hospital, Swansea, United Kingdom

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  • Alain Calender,

    Affiliation: Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon–Centre Léon Bérard, Lyon, France

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  • Agnès Hardouin,

    Affiliation: Centre François Baclesse, Caen, France

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  • Pascaline Berthet,

    Affiliation: Centre François Baclesse, Caen, France

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  • Capucine Delnatte,

    Affiliation: Centre René Gauducheau, Nantes, France

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  • Catherine Nogues,

    Affiliation: Oncogénétique Clinique, Hôpital René Huguenin/Institut Curie, Saint-Cloud, France

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  • Christine Lasset,

    Affiliations: Unité de Prévention et d'Epidémiologie Génétique, Centre Léon Bérard, Lyon, France, Université Lyon 1, CNRS UMR5558, Lyon, France

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  • Claude Houdayer,

    Affiliations: Institut Curie, Department of Tumour Biology, Paris, France, Université Paris Descartes, Sorbonne Paris Cité, Paris, France

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  • Dominique Leroux,

    Affiliations: Department of Genetics, Centre Hospitalier Universitaire de Grenoble, Grenoble, France, Institut Albert Bonniot, Université de Grenoble, Grenoble, France

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  • Etienne Rouleau,

    Affiliation: Laboratoire d'Oncogénétique, Hôpital René Huguenin, Institut Curie, Saint-Cloud, France

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  • Fabienne Prieur,

    Affiliation: Service de Génétique Clinique Chromosomique et Moléculaire, Centre Hospitalier Universitaire de St Etienne, St Etienne, France

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  • Francesca Damiola,

    Affiliation: INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en Cancérologie de Lyon, Lyon, France

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  • Hagay Sobol,

    Affiliation: Département Oncologie Génétique, Prévention et Dépistage, INSERM CIC-P9502, Institut Paoli-Calmettes/Université d'Aix-Marseille II, Marseille, France

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  • Isabelle Coupier,

    Affiliations: Unité d'Oncogénétique, CHU Arnaud de Villeneuve, Montpellier, France, Unité d'Oncogénétique, CRLCC Val d'Aurelle, Montpellier, France

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  • Laurence Venat-Bouvet,

    Affiliation: Department of Medical Oncology, Centre Hospitalier Universitaire Dupuytren, Limoges, France

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  • Laurent Castera,

    Affiliation: Institut Curie, Department of Tumour Biology, Paris, France

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  • Marion Gauthier-Villars,

    Affiliation: Institut Curie, Department of Tumour Biology, Paris, France

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  • Mélanie Léoné,

    Affiliation: Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon–Centre Léon Bérard, Lyon, France

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  • Pascal Pujol,

    Affiliations: Unité d'Oncogénétique, CHU Arnaud de Villeneuve, Montpellier, France, INSERM 896, CRCM Val d'Aurelle, Montpellier, France

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  • Sylvie Mazoyer,

    Affiliation: INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en Cancérologie de Lyon, Lyon, France

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  • Yves-Jean Bignon,

    Affiliation: Département d'Oncogénétique, Centre Jean Perrin, Université de Clermont-Ferrand, Clermont-Ferrand, France

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  • GEMO Study Collaborators,

    Affiliation: National Cancer Genetics Network, UNICANCER Genetic Group, Centre de Recherche en Cancérologie de Lyon and Institut Curie Paris, Paris, France

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  • Elżbieta Złowocka-Perłowska,

    Affiliation: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

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  • Jacek Gronwald,

    Affiliation: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

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  • Jan Lubinski,

    Affiliation: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

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  • Katarzyna Durda,

    Affiliation: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

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  • Katarzyna Jaworska,

    Affiliations: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland, Postgraduate School of Molecular Medicine, Warsaw Medical University, Warsaw, Poland

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  • Tomasz Huzarski,

    Affiliation: Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

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  • Amanda B. Spurdle,

    Affiliation: Genetics Department, Queensland Institute of Medical Research, Brisbane, Australia

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  • Alessandra Viel,

    Affiliation: Division of Experimental Oncology 1, Centro di Riferimento Oncologico, IRCCS, Aviano, Italy

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  • Bernard Peissel,

    Affiliation: Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy

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  • Bernardo Bonanni,

    Affiliation: Division of Cancer Prevention and Genetics, Istituto Europeo di Oncologia, Milan, Italy

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  • Giulia Melloni,

    Affiliation: Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy

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  • Laura Ottini,

    Affiliation: Department of Molecular Medicine, Sapienza University, Rome, Italy

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  • Laura Papi,

    Affiliation: Unit of Medical Genetics, Department of Clinical Physiopathology, University of Florence, Firenze, Italy

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  • Liliana Varesco,

    Affiliation: Unit of Hereditary Cancer, Department of Epidemiology, Prevention and Special Functions, IRCCS AOU San Martino–IST Istituto Nazionale per la Ricerca sul Cancro, Genoa, Italy

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  • Maria Grazia Tibiletti,

    Affiliation: UO Anatomia Patologica, Ospedale di Circolo-Università dell'Insubria, Varese, Italy

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  • Paolo Peterlongo,

    Affiliations: Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy, IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy

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  • Sara Volorio,

    Affiliation: IFOM, Fondazione Istituto FIRC di Oncologia Molecolare and Cogentech Cancer Genetic Test Laboratory, Milan, Italy

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  • Siranoush Manoukian,

    Affiliation: Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy

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  • Valeria Pensotti,

    Affiliation: IFOM, Fondazione Istituto FIRC di Oncologia Molecolare and Cogentech Cancer Genetic Test Laboratory, Milan, Italy

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  • Norbert Arnold,

    Affiliation: University Hospital of Schleswig-Holstein/University Kiel, Kiel, Germany

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  • Christoph Engel,

    Affiliation: Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany

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  • Helmut Deissler,

    Affiliation: University Hospital Ulm, Ulm, Germany

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  • Dorothea Gadzicki,

    Affiliation: Hannover Medical School, Hanover, Germany

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  • Andrea Gehrig,

    Affiliation: Institute of Human Genetics, University of Würzburg, Wurzburg, Germany

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  • Karin Kast,

    Affiliation: Department of Gynaecology and Obstetrics, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany

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  • Kerstin Rhiem,

    Affiliation: Centre of Familial Breast and Ovarian Cancer, Department of Gynaecology and Obstetrics and Centre for Integrated Oncology (CIO), Center for Molecular Medicine Cologne (CMMC), University Hospital of Cologne, Cologne, Germany

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  • Alfons Meindl,

    Affiliation: Department of Gynaecology and Obstetrics, Division of Tumor Genetics, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

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  • Dieter Niederacher,

    Affiliation: Department of Obstetrics and Gynaecology, University Medical Center Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany

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  • Nina Ditsch,

    Affiliation: Department of Gynaecology and Obstetrics, University of Munich, Munich, Germany

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  • Hansjoerg Plendl,

    Affiliation: Institute of Human Genetics, University Hospital of Schleswig-Holstein, University of Kiel, Kiel, Germany

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  • Sabine Preisler-Adams,

    Affiliation: Institute of Human Genetics, Münster, Germany

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  • Stefanie Engert,

    Affiliation: Department of Gynaecology and Obstetrics, Division of Tumor Genetics, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany

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  • Christian Sutter,

    Affiliation: Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany

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  • Raymonda Varon-Mateeva,

    Affiliation: Institute of Medical and Human Genetics, Berlin, Germany

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  • Barbara Wappenschmidt,

    Affiliation: Centre of Familial Breast and Ovarian Cancer, Department of Gynaecology and Obstetrics and Centre for Integrated Oncology (CIO), Center for Molecular Medicine Cologne (CMMC), University Hospital of Cologne, Cologne, Germany

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  • Bernhard H. F. Weber,

    Affiliation: Institute of Human Genetics, University of Regensburg, Regensburg, Germany

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  • Brita Arver,

    Affiliation: Department of Oncology and Pathology, Karolinska University Hospital, Stockholm, Sweden

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  • Marie Stenmark-Askmalm,

    Affiliation: Division of Clinical Genetics, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden

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  • Niklas Loman,

    Affiliation: Department of Oncology, Lund University Hospital, Lund, Sweden

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  • Richard Rosenquist,

    Affiliation: Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden

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  • Zakaria Einbeigi,

    Affiliation: Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden

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  • Katherine L. Nathanson,

    Affiliation: Abramson Cancer Center and Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

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  • Timothy R. Rebbeck,

    Affiliation: Abramson Cancer Center and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

    X
  • Stephanie V. Blank,

    Affiliation: NYU Women's Cancer Program, New York University School of Medicine, New York, New York, United States of America

    X
  • David E. Cohn,

    Affiliation: Ohio State University, Columbus Cancer Council, Columbus, Ohio, United States of America

    X
  • Gustavo C. Rodriguez,

    Affiliation: Division of Gynecologic Oncology, North Shore University Health System, University of Chicago, Evanston, Illinois, United States of America

    X
  • Laurie Small,

    Affiliation: Maine Medical Center, Maine Women's Surgery and Cancer Centre, Scarborough, Maine, United States of America

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  • Michael Friedlander,

    Affiliation: ANZ GOTG Coordinating Centre, Australia New Zealand GOG, Camperdown, Australia

    X
  • Victoria L. Bae-Jump,

    Affiliation: The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America

    X
  • Anneliese Fink-Retter,

    Affiliation: Department of Obstetrics and Gynecology, and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria

    X
  • Christine Rappaport,

    Affiliation: Department of Obstetrics and Gynecology, and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria

    X
  • Daphne Gschwantler-Kaulich,

    Affiliation: Department of Obstetrics and Gynecology, and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria

    X
  • Georg Pfeiler,

    Affiliation: Department of Obstetrics and Gynecology, and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria

    X
  • Muy-Kheng Tea,

    Affiliation: Department of Obstetrics and Gynecology, and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria

    X
  • Noralane M. Lindor,

    Affiliation: Department of Health Science Research, Mayo Clinic Arizona, Scottsdale, Arizona, United States of America

    X
  • Bella Kaufman,

    Affiliation: Sheba Medical Center, Tel Aviv, Israel

    X
  • Shani Shimon Paluch,

    Affiliation: Sheba Medical Center, Tel Aviv, Israel

    X
  • Yael Laitman,

    Affiliation: Sheba Medical Center, Tel Aviv, Israel

    X
  • Anne-Bine Skytte,

    Affiliation: Department of Clinical Genetics, Vejle Hospital, Vejle, Denmark

    X
  • Anne-Marie Gerdes,

    Affiliation: Department of Clincial Genetics, Rigshospitalet, København, Denmark

    X
  • Inge Sokilde Pedersen,

    Affiliation: Section of Molecular Diagnostics, Department of Clinical Biochemistry, Aalborg University Hospital, Aalborg, Denmark

    X
  • Sanne Traasdahl Moeller,

    Affiliation: Department of Clinical Genetics, Odense University Hospital, Odense, Denmark

    X
  • Torben A. Kruse,

    Affiliation: Department of Clinical Genetics, Odense University Hospital, Odense, Denmark

    X
  • Uffe Birk Jensen,

    Affiliation: Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark

    X
  • Joseph Vijai,

    Affiliation: Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America

    X
  • Kara Sarrel,

    Affiliation: Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America

    X
  • Mark Robson,

    Affiliation: Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America

    X
  • Noah Kauff,

    Affiliation: Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America

    X
  • Anna Marie Mulligan,

    Affiliations: Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada, Department of Laboratory Medicine, and the Keenan Research Centre of the Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Canada

    X
  • Gord Glendon,

    Affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada

    X
  • Hilmi Ozcelik,

    Affiliations: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada, Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada

    X
  • Bent Ejlertsen,

    Affiliation: Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

    X
  • Finn C. Nielsen,

    Affiliation: Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

    X
  • Lars Jønson,

    Affiliation: Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

    X
  • Mette K. Andersen,

    Affiliation: Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark

    X
  • Yuan Chun Ding,

    Affiliation: Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, United States of America

    X
  • Linda Steele,

    Affiliation: Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, United States of America

    X
  • Lenka Foretova,

    Affiliation: Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic

    X
  • Alex Teulé,

    Affiliation: Genetic Counseling Unit, Hereditary Cancer Program, IDIBELL–Catalan Institute of Oncology, Barcelona, Spain

    X
  • Conxi Lazaro,

    Affiliation: Molecular Diagnostic Unit, Hereditary Cancer Program, IDIBELL–Catalan Institute of Oncology, Barcelona, Spain

    X
  • Joan Brunet,

    Affiliation: Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI–Catalan Institute of Oncology, Girona, Spain

    X
  • Miquel Angel Pujana,

    Affiliation: Translational Research Laboratory, Breast Cancer and Systems Biology Unit, IDIBELL–Catalan Institute of Oncology, Barcelona, Spain

    X
  • Phuong L. Mai,

    Affiliation: Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, United States of America

    X
  • Jennifer T. Loud,

    Affiliation: Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, United States of America

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  • Christine Walsh,

    Affiliation: Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

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  • Jenny Lester,

    Affiliation: Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

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  • Sandra Orsulic,

    Affiliation: Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

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  • Steven A. Narod,

    Affiliation: Women's College Research Institute, University of Toronto, Toronto, Canada

    X
  • Josef Herzog,

    Affiliation: Clinical Cancer Genetics (for the City of Hope Clinical Cancer Genetics Community Research Network), City of Hope, Duarte, California, United States of America

    X
  • Sharon R. Sand,

    Affiliation: Clinical Cancer Genetics (for the City of Hope Clinical Cancer Genetics Community Research Network), City of Hope, Duarte, California, United States of America

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  • Silvia Tognazzo,

    Affiliation: Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto IOV–IRCCS, Padua, Italy

    X
  • Simona Agata,

    Affiliation: Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto IOV–IRCCS, Padua, Italy

    X
  • Tibor Vaszko,

    Affiliation: Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary

    X
  • Joellen Weaver,

    Affiliation: Biosample Repository, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America

    X
  • Alexandra V. Stavropoulou,

    Affiliation: Molecular Diagnostics Laboratory, IRRP, National Centre for Scientific Research Demokritos, Aghia Paraskevi Attikis, Athens, Greece

    X
  • Saundra S. Buys,

    Affiliation: Department of Internal Medicine, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, United States of America

    X
  • Atocha Romero,

    Affiliation: Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, Madrid, Spain

    X
  • Miguel de la Hoya,

    Affiliation: Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, Madrid, Spain

    X
  • Kristiina Aittomäki,

    Affiliation: Department of Clinical Genetics, Helsinki University Central Hospital, Helsinki, Finland

    X
  • Taru A. Muranen,

    Affiliation: Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland

    X
  • Mercedes Duran,

    Affiliation: Institute of Biology and Molecular Genetics, Universidad de Valladolid (IBGM–UVA), Valladolid, Spain

    X
  • Wendy K. Chung,

    Affiliation: Departments of Pediatrics and Medicine, Columbia University, New York, New York, United States of America

    X
  • Adriana Lasa,

    Affiliation: Genetics Service, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain

    X
  • Cecilia M. Dorfling,

    Affiliation: Department of Genetics, University of Pretoria, Pretoria, South Africa

    X
  • Alexander Miron,

    Affiliation: Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America

    X
  • BCFR,

    Affiliation: Breast Cancer Family Registry, Cancer Prevention Institute of California, Fremont, California, United States of America

    X
  • Javier Benitez,

    Affiliation: Human Genetics Group and Genotyping Unit, Spanish National Cancer Centre (CNIO), and Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain

    X
  • Leigha Senter,

    Affiliation: Divison of Human Genetics, Department of Internal Medicine, The Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, United States of America

    X
  • Dezheng Huo,

    Affiliation: Center for Clinical Cancer Genetics and Global Health, University of Chicago Medical Center, Chicago, Illinois, United States of America

    X
  • Salina B. Chan,

    Affiliation: Cancer Risk Program, Helen Diller Family Cancer Center, University of California San Francisco, San Francisco, California, United States of America

    X
  • Anna P. Sokolenko,

    Affiliation: N. N. Petrov Institute of Oncology, St. Petersburg, Russia

    X
  • Jocelyne Chiquette,

    Affiliation: Unité de Recherche en Santé des Populations, Centre des Maladies du Sein Deschênes-Fabia, Centre de Recherche FRSQ du Centre Hospitalier Affilié Universitaire de Québec, Québec, Canada

    X
  • Laima Tihomirova,

    Affiliation: Latvian Biomedical Research and Study Centre, Riga, Latvia

    X
  • Tara M. Friebel,

    Affiliation: University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

    X
  • Bjarni A. Agnarsson,

    Affiliation: Landspitali University Hospital and University of Iceland School of Medicine, Reykjavik, Iceland

    X
  • Karen H. Lu,

    Affiliation: Department of Breast Medical Oncology and Clinical Cancer Genetics, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America

    X
  • Flavio Lejbkowicz,

    Affiliation: Clalit National Israeli Cancer Control Center and Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel

    X
  • Paul A. James,

    Affiliation: Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Australia

    X
  • Per Hall,

    Affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    X
  • Alison M. Dunning,

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom

    X
  • Daniel Tessier,

    Affiliation: Centre d'Innovation Génome Québec et Université McGill, Montreal, Canada

    X
  • Julie Cunningham,

    Affiliation: Department of Laboratory Medicine and Pathology, and Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

    X
  • Susan L. Slager,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

    X
  • Chen Wang,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

    X
  • Steven Hart,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

    X
  • Kristen Stevens,

    Affiliation: Department of Laboratory Medicine and Pathology, and Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

    X
  • Jacques Simard,

    Affiliation: Cancer Genomics Laboratory, Centre Hospitalier Universitaire de Québec and Laval University, Québec City, Canada

    X
  • Tomi Pastinen,

    Affiliation: Department of Human Genetics, McGill University and Génome Québec Innovation Centre, McGill University, Montréal, Canada

    X
  • Vernon S. Pankratz,

    Affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America

    X
  • Kenneth Offit,

    Affiliation: Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America

    X
  • Douglas F. Easton equal contributor,

    equal contributor Contributed equally to this work with: Fergus J. Couch, Douglas F. Easton, Georgia Chenevix-Trench

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

    X
  • Georgia Chenevix-Trench equal contributor,

    equal contributor Contributed equally to this work with: Fergus J. Couch, Douglas F. Easton, Georgia Chenevix-Trench

    Affiliation: Genetics Department, Queensland Institute of Medical Research, Brisbane, Australia

    X
  • Antonis C. Antoniou mail,

    couch.fergus@mayo.edu (Fergus J Couch); Antonis@srl.cam.ac.uk (Antonis C Antoniou)

    Affiliation: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom

    X
  • on behalf of CIMBA
  • Published: March 27, 2013
  • DOI: 10.1371/journal.pgen.1003212

Abstract

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10−8, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10−8, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.4×10−8, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10−4). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.

Author Summary

BRCA1 mutation carriers have increased and variable risks of breast and ovarian cancer. To identify modifiers of breast and ovarian cancer risk in this population, a multi-stage GWAS of 14,351 BRCA1 mutation carriers was performed. Loci 1q32 and TCF7L2 at 10q25.3 were associated with breast cancer risk, and two loci at 4q32.2 and 17q21.31 were associated with ovarian cancer risk. The 4q32.3 ovarian cancer locus was not associated with ovarian cancer risk in the general population or in BRCA2 carriers and is the first indication of a BRCA1-specific risk locus for either breast or ovarian cancer. Furthermore, modeling the influence of these modifiers on cumulative risk of breast and ovarian cancer in BRCA1 mutation carriers for the first time showed that a wide range of individual absolute risks of each cancer can be estimated. These differences suggest that genetic risk modifiers may be incorporated into the clinical management of BRCA1 mutation carriers.

Introduction

Breast and ovarian cancer risk estimates for BRCA1 mutation carriers vary by the degree of family history of the disease, suggesting that other genetic factors modify cancer risks for this population [1][4]. Studies by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) have shown that a subset of common alleles influencing breast and ovarian cancer risk in the general population are also associated with cancer risk in BRCA1 mutation carriers [5][11]. In particular, the breast cancer associations were limited to loci associated with estrogen receptor (ER)-negative breast cancer in the general population (6q25.1, 12p11 and TOX3) [8][11].

To systematically search for loci associated with breast or ovarian cancer risk for BRCA1 carriers we previously conducted a two-stage genome-wide association study (GWAS) [12]. The initial stage involved analysis of 555,616 SNPs in 2383 BRCA1 mutation carriers (1,193 unaffected and 1,190 affected). After replication testing of 89 SNPs showing the strongest association, with 5,986 BRCA1 mutation carriers, a locus on 19p13 was shown to be associated with breast cancer risk for BRCA1 mutation carriers. The same locus was also associated with the risk of estrogen-receptor (ER) negative and triple negative (ER, Progesterone and HER2 negative) breast cancer in the general population [12], [13].

The Collaborative Oncological Gene-environment Study (COGS) consortium recently developed a 211,155 SNP custom genotyping array (iCOGS) in order to provide cost-effective genotyping of common and rare genetic variants to identify novel loci that explain the residual genetic variance of breast, ovarian and prostate cancers and fine-map known susceptibility loci. A total of 32,557 SNPs on the iCOGS array were selected on the basis of the BRCA1 GWAS for the purpose of identifying breast and ovarian cancer risk modifiers for BRCA1 mutation carriers. Genotype data from the iCOGS array were obtained for 11,705 samples from BRCA1 carriers and the 17 most promising SNPs were then genotyped in an additional 2,646 BRCA1 carriers. In this manuscript we report on the novel risk modifier loci identified by this multi-stage GWAS. No study has previously shown how the absolute risks of breast and ovarian cancer for BRCA1 mutation carriers vary by the combined effects of risk modifying loci. Here we use the results from this study, in combination with previously identified modifiers, to obtain absolute risks of developing breast and ovarian cancer for BRCA1 mutation carriers based on the joint distribution of all known genetic risk modifiers.

Materials and Methods

Ethics statement

All carriers participated in clinical or research studies at the host institutions, approved by local ethics committees.

Study subjects

BRCA1 mutation carriers were recruited by 45 study centers in 25 countries through CIMBA. The majority were recruited through cancer genetics clinics, and enrolled into national or regional studies. The remainder were identified by population-based sampling or community recruitment. Eligibility for CIMBA association studies was restricted to female carriers of pathogenic BRCA1 mutations age 18 years or older at recruitment. Information collected included year of birth, mutation description, self-reported ethnic ancestry, age at last follow-up, ages at breast or ovarian cancer diagnoses, and age at bilateral prophylactic mastectomy and oophorectomy. Information on tumour characteristics, including ER-status of the breast cancers, was also collected. Related individuals were identified through a unique family identifier. Women were included in the analysis if they carried mutations that were pathogenic according to generally recognized criteria.

GWAS stage 1 samples.

A total of 2,727 BRCA1 mutation carriers were genotyped on the Illumina Infinium 610K array (Figure 1). Of these 1,426 diagnosed with a first breast cancer under age 40 were considered “affected” in the breast cancer association analysis and 683 diagnosed with an ovarian cancer at any time were considered as “affected” in the ovarian cancer analysis. “Unaffected” in both analyses were over age 35 (Table S1) [12].

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Figure 1. Study design for selection of the SNPs and genotyping of BRCA1 samples.

GWAS data from 2,727 BRCA1 mutation carriers were analysed for associations with breast and ovarian cancer risk and 32,557 SNPs were selected for inclusion on the iCOGS array. A total of 11,705 BRCA1 samples (after quality control (QC) checks) were genotyped on the 31,812 BRCA1-GWAS SNPs from the iCOGS array that passed QC. Of these samples, 2,387 had been genotyped at the SNP selection stage and are referred to as “stage 1” samples, whereas 9,318 samples were unique to the iCOGS study (“Stage 2” samples). Next, 17 SNPs that exhibited the most significant associations with breast and ovarian cancer were selected for genotyping in a third stage involving an additional 2,646 BRCA1 samples (after QC).

doi:10.1371/journal.pgen.1003212.g001
Replication study samples.

All eligible BRCA1 carriers from CIMBA with sufficient DNA were genotyped, including those used in Stage 1. In total, 13,310 samples from 45 centers in 25 countries were genotyped using the iCOGS array (Table S2). Among the 13,310 samples, those that were genotyped in the GWAS stage 1 SNP selection stage are referred to as “stage 1” samples, and the remainder are “stage 2” samples. An additional 2,646 BRCA1 samples “stage 3” were genotyped on an iPLEX Mass Array of 17 SNPs from 12 loci selected after an interim analysis of iCOGS array data and were available for analysis after quality control (QC) (Figure 1). Carriers of pathogenic mutations in BRCA2 were drawn from a parallel GWAS of genetic modifiers for BRCA2 mutation carriers. BRCA2 mutation carriers were recruited from CIMBA through 47 studies which were largely the same as the studies that contributed to the BRCA1 GWAS with similar eligibility criteria. Samples from BRCA2 mutation carriers were also genotyped using the iCOGS array. Details of this experiment are described elsewhere [14]. A total of 8,211 samples were available for analysis after QC.

iCOGS SNP array

The iCOGS array was designed in a collaboration among the Breast Cancer Association Consortium (BCAC), Ovarian Cancer Association Consortium (OCAC), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) and CIMBA. The general aims for designing the iCOGS array were to replicate findings from GWAS for identifying variants associated with breast, ovarian or prostate cancer (including subtypes and SNPs potentially associated with disease outcome), to facilitate fine-mapping of regions of interest, and to genotype “candidate” SNPs of interest within the consortia, including rarer variants. Each consortium was given a share of the array: nominally 25% of the SNPs each for BCAC, PRACTICAL and OCAC; 17.5% for CIMBA; and 7.5% for SNPs of common interest between the consortia. The final design comprised 220,123 SNPs, of which 211,155 were successfully manufactured. A total of 32,557 SNPs on the iCOGS array were selected based on 8 separate analyses of stage 1 of the CIMBA BRCA1 GWAS that included 2,727 BRCA1 mutation carriers [12]. After imputation for all SNPs in HapMap Phase II (CEU) a total of 2,568,349 (imputation r2>0.30) were available for analysis. Markers were evaluated for associations with: (1) breast cancer; (2) ovarian cancer; (3) breast cancer restricted to Class 1 mutations (loss-of-function mutations expected to result in a reduced transcript or protein level due to nonsense-mediated RNA decay); (4) breast cancer restricted to Class 2 mutations (mutations likely to generate stable proteins with potential residual or dominant negative function); (5) breast cancer by tumor ER-status; (6) breast cancer restricted to BRCA1 185delAG mutation carriers; (7) breast cancer restricted to BRCA1 5382insC mutation carriers; and (8) breast cancer by contrasting the genotype distributions in BRCA1 mutation carriers, against the distribution in population-based controls. Analyses (1) and (2) were based on both imputed and observed genotypes, whereas the rest were based on only the observed genotypes. SNPs were ranked according to the 1 d.f. score-test for trend P-value (described below) and selected for inclusion based on nominal proportions of 61.5%, 20%, 2.5%, 2.5%, 2.5%, 0.5%, 0.5% and 10.0% for analyses (1) to (8). SNP duplications were not allowed and SNPs with a pairwise r2≥0.90 with a higher-ranking SNP were only allowed (up to a maximum of 2) if the P-value for association was <10−4 for analyses (1) and (2) and <10−5 for other analyses. SNPs with poor Illumina design scores were replaced by the SNP with the highest r2 (among SNPs with r2>0.80 based on HapMap data) that had a good quality design score. The analysis of associations with breast and ovarian cancer risks presented here included all 32,557 SNPs on iCOGS that were selected on the basis of the BRCA1 GWAS.

Genotyping and quality control

iCOGS genotyping.

Genotyping was performed at Mayo Clinic. Genotypes for samples genotyped on the iCOGS array were called using Illumina's GenCall algorithm (Text S1). A total of 13,510 samples were genotyped for 211,155 SNPs. The sample and SNP QC process is summarised in Table S3. Of the 13,510 samples, 578 did not fulfil eligibility criteria based on phenotypic data and were excluded. A step-wise QC process was applied to the remaining samples and SNPs. Samples were excluded due to inferred gender errors, low call rates (<95%), low or high heterozygosity and sample duplications (cryptic and intended). Of the 211,155 markers genotyped, 9,913 were excluded due to Y-chromosome origin, low call rates (<95%), monomorphic SNPs, or SNPs with Hardy-Weinberg equilibrium (HWE) P<10−7 under a country-stratified test statistic [15] (Table S3). SNPs that gave discordant genotypes among known sample duplicates were also excluded. Multi-dimensional scaling was used to exclude individuals of non-European ancestry. We selected 37,149 weakly correlated autosomal SNPs (pair-wise r2<0.10) to compute the genomic kinship between all pairs of BRCA1 carriers, along with 197 HapMap samples (CHB, JPT, YRI and CEU). These were converted to distances and subjected to multidimensional scaling (Figure S1). Using the first two components, we calculated the proportion of European ancestry for each individual [12] and excluded samples with >22% non-European ancestry (Figure S1). A total of 11,705 samples and 201,242 SNPs were available for analysis, including 31,812 SNPs selected by the BRCA1 GWAS. The genotyping cluster plots for all SNPs that demonstrated genome-wide significance level of association or are presented below, were checked manually for quality (Figure S2).

iPLEX analysis.

The most significant SNPs from 4 loci associated with ovarian cancer and 8 loci associated with breast cancer were selected (17 SNPs in total) for stage 3 genotyping. Genotyping using the iPLEX Mass Array platform was performed at Mayo Clinic. CIMBA QC procedures were applied. Samples that failed for ≥20% of the SNPs were excluded from the analysis. No SNPs failed HWE (P<0.01). The concordance among duplicates was ≥98%. Mutation carriers of self-reported non-European ancestry were excluded. A total of 2,646 BRCA1 samples were eligible for analysis after QC.

Statistical methods

The main analyses were focused on the evaluation of associations between each genotype and breast cancer or ovarian cancer risk separately. Analyses were carried out within a survival analysis framework. In the breast cancer analysis, the phenotype of each individual was defined by age at breast cancer diagnosis or age at last follow-up. Individuals were followed until the age of the first breast cancer diagnosis, ovarian cancer diagnosis, or bilateral prophylactic mastectomy, whichever occurred first; or last observation age. Mutation carriers censored at ovarian cancer diagnosis were considered unaffected. For the ovarian cancer analysis, the primary endpoint was the age at ovarian cancer diagnosis. Mutation carriers were followed until the age of ovarian cancer diagnosis, or risk-reducing salpingo-oophorectomy (RRSO) or age at last observation. In order to maximize the number of ovarian cancer cases, breast cancer was not considered as a censoring event in this analysis, and mutation carriers who developed ovarian cancer after a breast cancer diagnosis were considered as affected in the ovarian cancer analysis.

Association analysis.

The majority of mutation carriers were sampled through families seen in genetic clinics. The first tested individual in a family is usually someone diagnosed with cancer at a relatively young age. Such study designs tend to lead to an over-sampling of affected individuals, and standard analytical methods like Cox regression may lead to biased estimates of the risk ratios [16], [17]. To adjust for this potential bias the data were analyzed within a survival analysis framework, by modeling the retrospective likelihood of the observed genotypes conditional on the disease phenotypes. A detailed description of the retrospective likelihood approach has been published [17], [18]. The associations between genotype and breast cancer risk at both stages were assessed using the 1 d.f. score test statistic based on this retrospective likelihood [17], [18]. To allow for the non-independence among related individuals, we accounted for the correlation between the genotypes by estimating the kinship coefficient for each pair of individuals using the available genomic data [16], [19], [20] and by robust variance estimation based on reported family membership [21]. We chose to present P-values based on the kinship adjusted score test as it utilises the degree of relationship between individuals. A genome-wide level of significance of 5×10−8 was used [22]. These analyses were performed in R using the GenABEL [23] libraries and custom-written functions in FORTRAN and Python.

To estimate the magnitude of the associations (HRs), the effect of each SNP was modeled either as a per-allele HR (multiplicative model) or as genotype-specific HRs, and were estimated on the log-scale by maximizing the retrospective likelihood. The retrospective likelihood was fitted using the pedigree-analysis software MENDEL [17], [24]. As sample sizes varied substantially between contributing centers heterogeneity was examined at the country level. All analyses were stratified by country of residence and used calendar-year and cohort-specific breast cancer incidence rates for BRCA1 [25]. Countries with small number of mutation carriers were combined with neighbouring countries to ensure sufficiently large numbers within each stratum (Table S2). USA and Canada were further stratified by reported Ashkenazi Jewish (AJ) ancestry due to large numbers of AJ carriers. In stage 3 analysis involving several countries with small numbers of mutation carriers, we assumed only 3 large strata (Europe, Australia, USA/Canada). The combined iCOGS stage and stage 3 analysis was also stratified by stage of the experiment. The analysis of associations by breast cancer ER-status was carried out by an extension of the retrospective likelihood approach to model the simultaneous effect of each SNP on more than one tumor subtype [26] (Text S1).

Competing risk analysis.

The associations with breast and ovarian cancer risk simultaneously were assessed within a competing risk analysis framework [17] by estimating HRs simultaneously for breast and ovarian cancer risk. This analysis provides unbiased estimates of association with both diseases and more powerful tests of association in cases where an association exists between a variant and at least one of the diseases [17]. Each individual was assumed to be at risk of developing either breast or ovarian cancer, and the probabilities of developing each disease were assumed to be independent conditional on the underlying genotype. A different censoring process was used, whereby individuals were followed up to the age of the first breast or ovarian cancer diagnosis and were considered to have developed the corresponding disease. No follow-up was considered after the first cancer diagnosis. Individuals censored for breast cancer at the age of bilateral prophylactic mastectomy and for ovarian cancer at the age of RRSO were assumed to be unaffected for the corresponding disease. The remaining individuals were censored at the last observation age and were assumed to be unaffected for both diseases.

Imputation.

For the SNP selection process, the MACH software was used to impute non-genotyped SNPs based on the phased haplotypes from HapMap Phase II (CEU, release 22). The IMPUTE2 software [27] was used to impute non-genotyped SNPs for samples genotyped on the iCOGS array (stage 1 and 2 only), based on the 1,000 Genomes haplotypes (January 2012 version). Associations between each marker and cancer risk were assessed using a similar score test to that used for the observed SNPs, but based on the posterior genotype probabilities at each imputed marker for each individual. In all analyses, we considered only SNPs with imputation information/accuracy r2>0.30.

Absolute breast and ovarian cancer risks by combined SNP profile.

We estimated the absolute risk of developing breast and ovarian cancer based on the joint distribution of all SNPs that were significantly associated with risk for BRCA1 mutation carriers based on methods previously applied to BRCA2 carriers [28]. We assumed that the average, age-specific breast and ovarian cancer incidences for BRCA1 mutation carriers, over all modifying loci, agreed with published penetrance estimates for BRCA1 [25]. The model assumed independence among the modifying loci and we used only the SNP with the strongest evidence of association from each region. We used only loci identified through the BRCA1 GWAS that exhibited associations at a genome-wide significance level, and loci that were identified through population-based GWAS of breast or ovarian cancer risk, but were also associated with those risks for BRCA1 mutation carriers. For each SNP, we used the per-allele HR and minor allele frequencies estimated from the present study. Genotype frequencies were obtained under the assumption of HWE.

Results

Samples from 11,705 BRCA1 carriers from 45 centers in 25 countries yielded high-quality data for 201,242 SNPs on the iCOGS array. The array included 31,812 BRCA1 GWAS SNPs, which were analyzed here for their associations with breast and ovarian cancer risk for BRCA1 mutation carriers (Table S2). Of the 11,705 BRCA1 mutation carriers, 2,387 samples had also been genotyped for stage 1 of the GWAS and 9,318 were unique to the stage 2 iCOGS study.

Breast cancer associations

When restricting analysis to stage 2 samples (4,681 unaffected, 4,637 affected), there was little evidence of inflation in the association test-statistic (λ = 1.038; Figure S3). Combined analysis of stage 1 and 2 samples (5,784 unaffected, 5,920 affected) revealed 66 SNPs in 28 regions with P<10−4 (Figure S4). These included variants from three loci (19p13, 6q25.1, 12p11) previously associated with breast cancer risk for BRCA1 mutation carriers (Table 1). Further evaluation of 18 loci associated with breast cancer susceptibility in the general population found that only the TOX3, LSP1, 2q35 and RAD51L1 loci were significantly associated with breast cancer for BRCA1 carriers (Table 1, Table S4).

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Table 1. Associations with breast or ovarian cancer risk for loci previously reported to be associated with cancer risk for BRCA1 mutation carriers.

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After excluding SNPs from the known loci, there were 39 SNPs in 25 regions with P = 1.2×10−6–1.0×10−4. Twelve of these SNPs were genotyped by iPLEX in an additional 2,646 BRCA1 carriers (1,252 unaffected, 1,394 affected, “stage 3” samples, Table S5). There was additional evidence of association with breast cancer risk for four SNPs at two loci (P<0.01, Table 2). When all stages were combined, SNPs rs2290854 and rs6682208 (r2 = 0.84) at 1q32, near MDM4, had combined P-values of association with breast cancer risk of 1.4×10−7 and 4×10−7,respectively. SNPs rs11196174 and rs11196175 (r2 = 0.96) at 10q25.3 (in TCF7L2) had combined P-values of 7.5×10−7 and 1.2×10−6. Analysis within a competing risks framework, where associations with breast and ovarian cancer risks are evaluated simultaneously [17], revealed stronger associations with breast cancer risk for all 4 SNPs, but no associations with ovarian cancer (Table 3). In particular, we observed a genome-wide significant association between the minor allele of rs2290854 from 1q32 and breast cancer risk (per-allele HR: 1.14; 95%CI: 1.09–1.20; p = 2.7×10−8). Country-specific HR estimates for all SNPs are shown in Figure S5. Analyses stratified by BRCA1 mutation class revealed no significant evidence of a difference in the associations of any of the SNPs by the predicted functional consequences of BRCA1 mutations (Table S6). SNPs in the MDM4 and TCF7L2 loci were associated with breast cancer risk for both class1 and class2 mutation carriers.

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Table 2. Associations with breast and ovarian cancer risk for SNPs found to be associated with risk at all 3 stages of the experiment.

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Table 3. Analysis of associations with breast and ovarian cancer risk simultaneously (competing risks analysis) for SNPs found to be associated with breast or ovarian cancer.

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Both the 1q32 and 10q25.3 loci were primarily associated with ER-negative breast cancer for BRCA1 (rs2290854: ER-negative HR = 1.16, 95%CI: 1.10–1.22, P = 1.2×10−7; rs11196174: HR = 1.14, 95%CI: 1.07–1.20, P = 9.6×10−6), although the differences between the ER-negative and ER-positive HRs were not significant (Table S7). Given that ER-negative breast cancers in BRCA1 and BRCA2 mutation carriers are phenotypically similar [29], we also evaluated associations between these SNPs and ER-negative breast cancer in 8,211 BRCA2 mutation carriers. While the 10q25.3 SNPs were not associated with overall or ER-negative breast cancer risk for BRCA2 carriers, the 1q32 SNPs were associated with ER-negative (rs2290854 HR = 1.16, 95%CI:1.01–1.34, P = 0.033; rs6682208 HR = 1.19, 95%CI:1.04–1.35, P = 0.016), but not ER-positive breast cancer (rs2290854 P-diff = 0.006; rs6682208 P-diff = 0.001). Combining the BRCA1 and BRCA2 samples provided strong evidence of association with ER-negative breast cancer (rs2290854: P = 1.25×10−8; rs6682208: P = 2.5×10−7).

The iCOGS array included additional SNPs from the 1q32 region that were not chosen based on the BRCA1 GWAS. Of these non-BRCA1 GWAS SNPs, only SNP rs4951407 was more significantly associated with risk than the BRCA1-GWAS selected SNPs (P = 3.3×10−6, HR = 1.12, 95%CI:1.07–1.18, using stage 1 and stage 2 samples). The evidence of association with breast cancer risk was again stronger under the competing risks analysis (HR = 1.14, 95%CI: 1.08–1.20, P = 6.1×10−7). Backward multiple regression analysis, considering only the genotyped SNPs (P<0.01), revealed that the most parsimonious model included only rs4951407. SNPs from the 1000 Genomes Project, were imputed for the stage 1 and stage 2 samples (Figure S6). Only imputed SNP rs12404974, located between PIK3C2B and MDM4 (r2 = 0.77 with rs4951407), was more significantly associated with breast cancer (P = 2.7×10−6) than any of the genotyped SNPs. None of the genotyped or imputed SNPs from 10q25.3 provided P-values smaller than those for rs11196174 and rs11196175 (Figure S7).

Ovarian cancer associations

Analyses of associations with ovarian cancer risk using the stage 2 samples (8,054 unaffected, 1,264 affected) revealed no evidence of inflation in the association test-statistic (λ = 1.039, Figure S3). In the combined analysis of stage 1 and 2 samples (9866 unaffected, 1839 affected), 62 SNPs in 17 regions were associated with ovarian cancer risk for BRCA1 carriers at P<10−4 (Figure S3). These included SNPs in the 9p22 and 3q25 loci previously associated with ovarian cancer risk in both the general population and BRCA1 carriers [6], [7] (Table 1). Associations (P<0.01) with ovarian cancer risk were also observed for SNPs in three other known ovarian cancer susceptibility loci (8q24, 17q21, 19p13), but not 2q31 (Table 1). For all loci except 9p22, SNPs were identified that displayed smaller P-values of association than previously published results [5][7].

After excluding SNPs from known ovarian cancer susceptibility regions, there were 48 SNPs in 15 regions with P = 5×10−7 to 10−4. Five SNPs from four of these loci were genotyped in the stage 3 samples (2,204 unaffected, 442 with ovarian cancer). Three SNPs showed additional evidence of association with ovarian cancer risk (P<0.02, Table 2; Table S5). In the combined stage 1–3 analyses, SNPs rs17631303 and rs183211 (r2 = 0.68) on chromosome 17q21.31 had P-values for association of 1×10−8 and 3×10−8 respectively, and rs4691139 at 4q32.3 had a P-value of 3.4×10−8 (Table 2).

The minor alleles of rs17631303 (HR = 1.27, 95%CI:1.17–1.38) and rs183211 (HR = 1.25, 95%CI: 1.16–1.35) at 17q21.31 were associated with increased ovarian cancer risk (Table 2). Analysis of the associations within a competing risks framework, revealed no association with breast cancer risk (Table 3). The ovarian cancer effect size was maintained in the competing risk analysis but the significance of the association was slightly weaker (P = 2×10−6–1×10−5). This is expected because 663 ovarian cancer cases occurring after a primary breast cancer diagnosis were excluded for this analysis. The evidence of association was somewhat stronger under the genotype-specific model (2-df P = 1.6×10−9 and P = 2.6×10−9 for rs17631303 and rs183211 respectively in all samples combined) with larger HR estimates for the rare homozygote genotypes than those expected under a multiplicative model (Table 2).

Previous studies of the known common ovarian cancer susceptibility alleles found significant associations with ovarian cancer for both BRCA1 and BRCA2 carriers [6], [7]. Thus, we evaluated the associations between the 17q21.31 SNPs and ovarian cancer risk for BRCA2 carriers using iCOGS genotype data (7580 unaffected and 631 affected). Both rs17631303 and rs183211 were associated with ovarian cancer risk for BRCA2 carriers (P = 1.98×10−4 and 9.26×10−4), with similar magnitude and direction of association as for BRCA1 carriers. Combined analysis of BRCA1 and BRCA2 mutation carriers provided strong evidence of association (P = 2.80×10−10 and 2.01×10−9, Table 4).

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Table 4. Associations with SNPs at the novel 17q21 region with ovarian cancer risk for BRCA1 and BRCA2 mutation carriers.

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The combined analysis of stage 1 and 2 samples, and BRCA2 carriers, identified seven SNPs on the iCOGS array (pairwise r2 range: 0.68–1.00) from a 1.3 Mb (40.8–42.1 Mb, build 36.3) region of 17q21.31 that were strongly associated (P<1.27×10−9) with ovarian cancer risk (Table 4, Figure 2). Stepwise-regression analysis based on observed genotype data retained only one of the seven SNPs in the model, but it was not possible to distinguish between the SNPs. Imputation through the 1000 Genomes Project, revealed several SNPs in 17q21.31 with stronger associations (Figure 2, Table S8) than the most significant genotyped SNP in the combined BRCA1/2 analysis (rs169201, P = 6.24×10−11). The most significant SNP (rs140338099 (17-44034340), P = 3×10−12), located in MAPT, was highly correlated (r2 = 0.78) with rs169201 in NSF (Figure 2). This locus appears to be distinct from a previously identified ovarian cancer susceptibility locus located >1 Mb distal on 17q21 (spanning 43.3–44.3 Mb, build 36.3) [30]. None of the SNPs in the novel region were strongly correlated with any of the SNPs in the 43.3–44.3 Mb region (maximum r2 = 0.07, Figure S8). The most significantly associated SNP from the BRCA1 GWAS from the 43.3–44.3 Mb locus was rs11651753 (p = 4.6×10−4) (Table 1) (r2<0.023 with the seven most significant SNPs in the novel 17q21.31 region). An analysis of the joint associations of rs11651753 and rs17631303 from the two 17q21 loci with ovarian cancer risk for BRCA1 carriers (Stage 1 and 2 samples) revealed that both SNPs remained significant in the model (P-for inclusion = 0.001 for rs11651753, 1.2×10−6 for rs17631303), further suggesting that the two regions are independently associated with ovarian cancer for BRCA1 carriers.

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Figure 2. Mapping of the 17q21 locus.

Top 3 panels: P-values of association (−log10 scale) with ovarian cancer risk for genotyped and imputed SNPs (1000 Genomes Project CEU), by chromosome position (b.37) at the 17q21 region, for BRCA1, BRCA2 mutation carriers and combined. Results based on the kinship-adjusted score test statistic (1 d.f.). Fourth panel: Genes in the region spanning (43.4–44.9 Mb, b.37) and the location of the most significant genotyped SNPs (in red font) and imputed SNPs (in black font). Bottom panel: Pairwise r2 values for genotyped SNPs on iCOG array in the 17q21 region covering positions (43.4–44.9 Mb, b.37).

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The minor allele of rs4691139 at the novel 4q32.3 region was also associated with an increased ovarian cancer risk for BRCA1 carriers (per-allele HR = 1.20, 95%CI:1.17–1.38, Table 2), but was not associated with breast cancer risk (Table 3). No other SNPs from the 4q32.3 region on the iCOGS array were more significantly associated with ovarian cancer for BRCA1 carriers. Analysis of associations with variants identified through 1000 Genomes Project-based imputation of the Stage 1 and 2 samples, revealed 19 SNPs with stronger evidence of association (P = 5.4×10−7 to 1.1×10−6) than rs4691139 (Figure S9). All were highly correlated (pairwise r2>0.89) and the most significant (rs4588418) had r2 = 0.97 with rs4691139. There was no evidence for association between rs4691139 and ovarian cancer risk for BRCA2 carriers (HR = 1.08, 95%CI: 0.96–1.21, P = 0.22).

Absolute risks of developing breast and ovarian cancer

The current analyses suggest that 10 loci are now known to be associated with breast cancer risk for BRCA1 mutation carriers: 1q32, 10q25.3, 19p13, 6q25.1, 12p11, TOX3, 2q35, LSP1 and RAD51L1 all reported here and TERT [31]. Similarly, seven loci are associated with ovarian cancer risk for BRCA1 mutation carriers: 9p22, 8q24, 3q25, 17q21, 19p13, 17q21.31 and 4q32.3. Figure S10 shows the range of combined HRs at different percentiles of the combined genotype distribution, based on the single SNP HR and minor allele estimates from Table 1, Table 2, and Table S4 and for TERT from Bojesen et al [31] and assuming that all SNPs interact multiplicatively. Relative to BRCA1 mutation carriers at lowest risk, the median, 5th and 95th percentile breast cancer HRs were 3.40, 2.27, and 5.35 respectively. These translate to absolute risks of developing breast cancer by age 80 of 65%, 51% and 81% for those at median, 5th and 95th percentiles of the combined genotype distribution (Figure 3, Figure S10). Similarly, the median, 5th and 95th percentile combined HRs for ovarian cancer were 6.53, 3.75 and 11.12 respectively, relative to those at lowest ovarian cancer risk (Figure S10). These HRs translate to absolute risks of developing ovarian cancer of 44%, 28% and 63% by age 80 for the median, 5th and 95th percentile of the combined genotype distribution (Figure 3).

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Figure 3. Predicted breast and ovarian cancer absolute risks for BRCA1 mutation carriers at the 5th, 10th, 90th, and 95th percentiles of the combined SNP profile distributions.

The minimum, maximum and average risks are also shown. Predicted cancer risks are based on the associations of known breast or ovarian cancer susceptibility loci (identified through GWAS) with cancer risk for BRCA1 mutation carriers and loci identified through the present study. Breast cancer risks based on the associations with: 1q32, 10q25.3, 19p13, 6q25.1, 12p11, TOX3, 2q35, LSP1, RAD51L1 (based on HR and minor allele frequency estimates from Table 1, Table 2, and Table S4) and TERT [31]. Ovarian cancer risks based on the associations with: 9p22, 8q24, 3q25, 17q21, 19p13 (Table 1) and 17q21.31, 4q32.3 (Table 2). Only the top SNP from each region was chosen. Average breast and ovarian cancer risks were obtained from published data [25]. The methods for calculating the predicted risks have been described previously [28].

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Discussion

In this study we analyzed data from 11,705 BRCA1 mutation carriers from CIMBA who were genotyped using the iCOGS high-density custom array, which included 31,812 SNPs selected on the basis of a BRCA1 GWAS. This study forms the large-scale replication stage of the first GWAS of breast and ovarian cancer risk modifiers for BRCA1 mutation carriers. We have identified a novel locus at 1q32, containing the MDM4 oncogene, that is associated with breast cancer risk for BRCA1 mutation carriers (P<5×10−8). A separate locus at 10q23.5, containing the TCF7L2 gene, provided strong evidence of association with breast cancer risk for BRCA1 carriers but did not reach a GWAS level of significance. We have also identified two novel loci associated with ovarian cancer for BRCA1 mutation carriers at 17q21.31 and 4q32.2 (P<5×10−8). We further confirmed associations with loci previously shown to be associated with breast or ovarian cancer risk for BRCA1 mutation carriers. In most cases stronger associations were detected with either the same SNP reported previously (due to increased sample size) or other SNPs in the regions. Future fine mapping studies of these loci will aim to identify potentially causal variants for the observed associations.

Although the 10q25.3 locus did not reach the strict GWAS level of significance for association with breast cancer risk, the association was observed at all three independent stages of the experiment. Additional evidence for the involvement of this locus in breast cancer susceptibility comes from parallel studies of the Breast Cancer Association Consortium (BCAC). SNPs at 10q25.3 had also been independently selected for inclusion on the iCOGS array through population based GWAS of breast cancer. Analyses of those SNPs in BCAC iCOGS studies also found that SNPs at 10q25.3 were associated with breast cancer risk in the general population [32]. Thus, 10q25.3 is likely a breast cancer risk-modifying locus for BRCA1 mutation carriers. The most significant SNPs at 10q25.3 were located in TCF7L2, a transcription factor that plays a key role in the Wnt signaling pathway and in glucose homeostasis, and is expressed in normal and malignant breast tissue (The Cancer Genome Atlas (TCGA)). Variation in the TCF7L2 locus has previously been associated with Type 2 diabetes in a number of GWAS. The most significantly associated SNPs with Type 2 diabetes (rs7903146 and rs4506565) [22], [33] were also associated with breast cancer risk for BRCA1 mutation carriers in stage 1 and 2 analyses (p = 3.7×10−4 and p = 2.5×10−4 respectively); these SNPs were correlated with the most significant hit (rs11196174) for BRCA1 breast cancer (r2 = 0.40 and 0.37 based on stage 1 and 2 samples). This raises the possibility that variants in this locus influence breast cancer indirectly through effects on cellular metabolism.

We found that SNPs at 1q32 were primarily associated with ER-negative breast cancer risk for BRCA1 mutation carriers. There was also evidence of association with ER-negative breast cancer for BRCA2 mutation carriers. SNPs at the 1q32 region were independently selected for inclusion on iCOGS through GWAS of breast cancer in the general population by BCAC. In parallel analyses of iCOGS data by BCAC, 1q32 was found to be associated with ER-negative breast cancer [34] but not overall breast cancer risk [32]. Taken together, these results are in agreement with our findings and in line with the observation that the majority of BRCA1 breast cancers are ER-negative. However, they are not in agreement with a previous smaller candidate-gene study that found an association between a correlated SNP in MDM4 (r2>0.85) and overall breast cancer risk [35]. The 1q32 locus includes the MDM4 oncogene which plays a role in regulation of p53 and MDM2 and the apoptotic response to cell stress. MDM4 is expressed in breast tissue and is amplified and overexpressed along with LRRN2 and PIK3C2B in breast and other tumor types (TCGA) [36][38]. Although fine mapping will be necessary to identify the functionally relevant SNPs in this locus, we found evidence of cis-regulatory variation impacting MDM4 expression [39][41] (Text S1, Table S9, Figure S11), suggesting that common variation in the 1q32 locus may influence the risk of breast cancer through direct effects on MDM4 expression.

Several correlated SNPs at 17q21.31 from the iCOGS array provided strong evidence of association with ovarian cancer risk in both BRCA1 and BRCA2 mutation carriers. A subsequent analysis of these SNPs, which were selected through the BRCA1 GWAS, in case-control samples from the Ovarian Cancer Association Consortium (OCAC), revealed that the 17q21.31 locus is associated with ovarian cancer risk in the general population [Wey et al, personal communication]. Thus, 17q21.31 is likely a novel susceptibility locus for ovarian cancer in BRCA1 mutation carriers. The most significant associations at 17q21.31 were clustered in a large region of strong linkage disequilibrium which has previously been identified as a “17q21.31 inversion” (~900 kb long) consisting of two haplotypes (termed H1 and H2) [42]. The minor allele of rs2532348 (MAF = 0.21), which tags H2, was associated with increased ovarian cancer risk for BRCA1 mutation carriers (Table 4). The 1.3 Mb 17q21.31 locus contains 13 genes and several predicted pseudogenes (Figure 2), several of which are expressed in normal ovarian surface epithelium and ovarian adenocarcinoma [43]. Variation in this region has been associated with Parkinson's disease (MAPT, PLEKHM1, NSF, c17orf69) progressive supranuclear palsy (MAPT), celiac disease (WNT3), bone mineral density (CRHR1) (NHGRI GWAS catalog) and intracranial volume [44]. Of the top hits for these phenotypes, SNP rs199533 in NSF, previously associated with Parkinson's disease [45] and rs9915547 associated with intracranial volume [44] were strongly associated with ovarian cancer (P<10−9 in BRCA1/2 combined). Whether these phenotypes have shared causal variants in this locus remains to be elucidated. Further exploration of the functional relevance of the strongest hits in the 17q21.31 locus (P<10−8 in BRCA1/2 combined) provided evidence that cis-regulatory variation alters expression of several genes at 17q21, including PLEKHM1, c17orf69, ARHGAP27, MAPT, KANSL1 and WNT3 [39], [41] (Table S9, Figure S12), suggesting that ovarian cancer risk may be associated with altered expression of one or more genes in this region.

Our analyses revealed that a second novel locus at 4q32.3 was also associated with ovarian cancer risk for BRCA1 mutation carries (P<5×10−8). However, we found no evidence of association for these SNPs with ovarian cancer risk for BRCA2 mutation carriers using 8,211 CIMBA samples genotyped using the iCOGS array. Likewise, no evidence of association was found between rs4691139 at 4q32.3 and ovarian cancer risk in the general population based on data by OCAC data derived from 18,174 cases and 26,134 controls (odds ratio = 1.00, 95%CI:0.97–1.04, P = 0.76) [46]. The confidence intervals rule out a comparable effect to that found in BRCA1 carriers. Therefore, our findings may represent a BRCA1-specific association with ovarian cancer risk, the first of its kind. The 4q32.2 region contains several members of the TRIM (Tripartite motif containing) gene family, c4orf39 and TMEM192. TRIM60, c4orf39 and TMEM192 are expressed in normal ovarian epithelium and/or ovarian tumors (TCGA).

In summary, we have identified a novel locus at 1q32 associated with breast cancer risk for BRCA1 mutation carriers, which was also associated with ER-negative breast cancer for BRCA2 carriers and in the general population. A separate locus at 10q23.5 provided strong evidence of association with breast cancer risk for BRCA1 carriers. We have also identified 2 novel loci associated with ovarian cancer for BRCA1 mutation carriers. Of these, the 4q32.2 locus was associated with ovarian cancer risk for BRCA1 carriers but not for BRCA2 carriers or in the general population. Additional functional characterisation of the loci will further improve our understanding of the biology of breast and ovarian cancer development in BRCA1 carriers. Taken together with other identified genetic modifiers, 10 loci are now known to be associated with breast cancer risk for BRCA1 mutation carriers (1q32, 10q25.3, 19p13, 6q25.1, 12p11, TOX3, 2q35, LSP1, RAD51L1 and TERT and seven loci are known to be associated with ovarian cancer risk for BRCA1 mutation carriers (9p22, 8q24, 3q25, 17q21, 19p13 and 17q21.31, 4q32.3).

As BRCA1 mutations confer high breast and ovarian cancer risks, the results from the present study, taken together with other identified genetic modifiers, demonstrate for the first time that they can result in large differences in the absolute risk of developing breast or ovarian cancer for BRCA1 between genotypes. For example, the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are predicted to be 28–50% compared to 81–100% for the 5% at highest risk (Figure 3). Based on the distribution of ovarian cancer risk modifiers, the 5% of BRCA1 mutation carriers at lowest risk will have a lifetime risk of developing ovarian cancer of 28% or lower whereas the 5% at highest risk will have a lifetime risk of 63% or higher. Similarly, the breast cancer risk by age 40 is predicted to be 4–9% for the 5% of BRCA1 carriers at lowest risk compared to 20–49% for the 5% at highest risk, whereas the ovarian cancer risk at age 50 ranges from 3–7% for the 5% at lowest risk and from 18–47% for the 5% at highest risk. The risks at all ages for the 10% at highest or lowest risk of breast and ovarian cancer are predicted to be similar to those for the highest and lowest 5%. Thus, at least 20% of BRCA1 mutation carriers are predicted to have absolute risks of disease that are different from the average BRCA1 carriers. These large differences in cancer risks may have practical implications for the clinical management of BRCA1 mutation carriers, for example in deciding the timing of interventions. Such risks, in combination with other lifestyle and hormonal risk factors could be incorporated into cancer risk prediction algorithms for use by clinical genetics centers. These algorithms could then be used to inform the development of effective and consistent clinical recommendations for the clinical management of BRCA1 mutation carriers.

Supporting Information

Figure S1.

Multidimensional scaling of stage 1 and stage 2 (genotyped on iCOGS) samples. Panel A: Graphical representation of the first two components, for the BRCA1 carriers, for subgroups defined by the common 185delAG (c.68_69delAG) BRCA1 Jewish founder mutation, the 5382insC (c.5266dupC) Eastern European founder mutation and Hapap individuals (CEU: European; ASI: Includes CHB and JPT populations; YRI: African). Panel B: Red dots represent the samples with >22% non-European ancestry, excluded from the analysis.

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Figure S2.

Genotyping cluster plots in the BRCA1 samples for the key associated SNPs.

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Figure S3.

Quantile-quantile plot for the kinship adjusted score test statistic for stage 2 samples (1 degree of freedom χ2 trend test) for the associations with breast cancer (panel A) and ovarian cancer (panel B) risk for BRCA1 mutation carriers. The y = x line corresponds to the expected distribution, under the hypothesis of no inflation. Inflation was estimated using the values of the lowest 90% test statistics.

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Figure S4.

P-values (on −log10 scale) by chromosomal position, for the associations of 31,812 BRCA1 GWAS SNPs with breast (panel A) and ovarian (panel B) cancer risk for BRCA1 mutation carriers in the combined stage 1 and stage 2 samples. Blue lines correspond to a P-value of 10−5; red lines correspond to P-value 5×10−8.

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Figure S5.

Forest plots of the associations by country of residence of BRCA1 mutation carriers in the combined stage 1, stage 2 and stage 3 samples for SNPs found to be associated with breast and ovarian cancer risk for BRCA1 mutation carriers. Squares indicate the country specific, per-allele HR estimates for the SNPs. The area of the square is proportional to the inverse of the variance of the estimate. Horizontal lines indicate 95% confidence intervals. There was some evidence of heterogeneity in country-specific HR estimates for the rs2290854 and rs6682208 SNP (P = 0.04 and 0.02 respectively, Figure S3), but after accounting for opposite effects of these SNPs in Finland/Denmark, there was no evidence of heterogeneity. There was some evidence of heterogeneity in the country-specific HRs for rs17631303 (P-het = 0.004, df = 19) but this was no longer present after excluding one country (Poland, P-het = 0.12, df = 18), or when restricting analyses to Stage 1 and 2 samples only (P-het = 0.09, df = 19). There was no evidence of heterogeneity for correlated SNP rs183211 (P-het = 0.10). There was no evidence of hereterogeneity in the country-specific HRs for any of the other SNPs (P>0.68).

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Figure S6.

MDM4 regional association plot using BRCA1 stage 1 and stage 2 samples. P-values for association (−log10 scale) with breast cancer risk for BRCA1 mutation carriers for genotyped SNPs (diamond symbols ◊) and SNPs imputed from the 1000 genomes project data (square symbols □), by position (hg18) on chromosome 1. Red gradient represents r2 value with the most significant genotyped SNP rs4951407. The blue peaks represent recombination rate in the region.

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Figure S7.

TCF7L2 regional association plot using BRCA1 stage 1 and stage 2 samples. P-values for association (−log10 scale) with breast cancer risk for BRCA1 mutation carriers for genotyped SNPs (diamond symbols ◊) and SNPs imputed from the 1000 genomes project data (square symbols □), by position (hg18) on chromosome 1. Missing genotypes were replaced by imputed results. Red gradient represents r2 value with the most significant genotyped SNP rs11196174. The blue peaks represent recombination rate in the region.

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Figure S8.

Linkage disequilibrium patterns between the SNPs in the novel (17q21.31) and previously identified regions on 17q21. SNPs in the novel region are uncorrelated with SNPs in the 43.3–44.3 Mb region (positions according to hg build 36.3).

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Figure S9.

4q32.3 regional association plot using BRCA1 stage 1 and stage 2 samples. P-values for association (−log10 scale) with ovarian cancer risk for BRCA1 mutation carriers for genotyped SNPs (diamond symbols ◊) and imputed SNPs from the 1000 genomes project data (square symbols □), by position (hg18) on chromosome 1. Red gradient represents r2 value with the most significant genotyped SNP rs4691139. Blue peaks represent recombination rate in the region.

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Figure S10.

Combined Hazard Ratios (HR) for breast and ovarian cancer for BRCA1 mutation carriers. (A) HR for Breast Cancer based on 10 loci associated with breast cancer risk for BRCA1 mutation carriers. (B) Ovarian Cancer based on 7 loci associated with ovarian cancer risk for BRCA1 mutation carriers. All HRs computed relative to the lowest risk category. The Y-axes translate the combined HRs into absolute risks of developing breast or ovarian cancer by age 80. The absolute risks and HRs at different percentiles of the combined genotype distribution are also marked. The combined HRs were obtained under the assumption that the loci interact multiplicatively.

doi:10.1371/journal.pgen.1003212.s010

(PDF)

Figure S11.

Cis-eQTL and allelic expression (AE) analyses at MDM4 locus. A) Cis-eQTLs for SNPs at MDM4 locus using expression data from primary human osteoblasts (HOb). B) AE mapping for cis-regulatory variation in MDM4 locus using primary skin fibroblasts. Coordinates (hg18) for locus shown on top; blue tracks indicate the −log10(P value) of the association across all SNPs tested. The location of transcripts in this region is shown below.

doi:10.1371/journal.pgen.1003212.s011

(PDF)

Figure S12.

Cis-eQTL and allelic expression (AE) analyses at chr17q21.31 locus. (Upper panel) Cis-eQTLs for SNPs at c17orf69 locus using expression data from primary human osteoblasts. Allelic expression mapping for cis-regulatory variation in KANSL1 (middle panel) and WNT3 loci (lower panel) using a CEU population panel of lymphoblastoid cells. Coordinates (hg18) for loci are shown on top; blue tracks indicate the −log10(P value) of the association across all SNPs tested. The location of transcripts in these regions are shown.

doi:10.1371/journal.pgen.1003212.s012

(PDF)

Table S1.

Affected and unaffected BRCA1 mutation carriers by study country in the breast and ovarian cancer analysis used in SNP selection for the iCOGS array.

doi:10.1371/journal.pgen.1003212.s013

(DOCX)

Table S2.

Origin of BRCA1 samples by Country and Stage used in the current analysis.

doi:10.1371/journal.pgen.1003212.s014

(DOCX)

Table S3.

Sample and SNP quality control summary.

doi:10.1371/journal.pgen.1003212.s015

(DOCX)

Table S4.

Associations with breast cancer risk for BRCA1 mutation carriers, for known breast cancer susceptibility variants.

doi:10.1371/journal.pgen.1003212.s016

(DOCX)

Table S5.

Associations with BRCA1 breast or ovarian cancer risk for SNPs genotyped at stages 1, 2, and 3.

doi:10.1371/journal.pgen.1003212.s017

(DOCX)

Table S6.

Analysis of breast cancer associations by BRCA1 mutation class.

doi:10.1371/journal.pgen.1003212.s018

(DOCX)

Table S7.

Associations with Breast Cancer ER status in BRCA1 carriers for SNPs genotyped in stages 1–3.

doi:10.1371/journal.pgen.1003212.s019

(DOCX)

Table S8.

Imputed SNPs at the novel 17q21 region with P-values less than the most significant genotyped SNP (rs169201).

doi:10.1371/journal.pgen.1003212.s020

(DOCX)

Table S9.

SNPs associated (P<1×10−5) with local expression and Allelic Imbalance.

doi:10.1371/journal.pgen.1003212.s021

(DOCX)

Text S1.

Supplementary Methods.

doi:10.1371/journal.pgen.1003212.s022

(DOCX)

Acknowledgments

Antonis C. Antoniou is a Cancer Research–UK Senior Cancer Research Fellow. Douglas F. Easton is a Cancer Research UK Principal Research Fellow. Georgia Chenevix-Trench is an NHMRC Senior Principal Research Fellow.

iCOGS: CIMBA acknowledges the contributions of Kyriaki Michailidou, Jonathan Tyrer, and Ali Amin Al Olama to the iCOGS statistical analyses; Shahana Ahmed, Melanie J. Maranian, and Catherine S. Healey for their contributions to the iCOGS genotyping quality control process; and the staff of the genotyping unit in the Medical Genomics Facility at the Mayo Clinic under the supervision of Dr. Julie Cunningham.

Breast Cancer Family Registry (BCFR) Studies: Samples from the NC-BCFR were processed and distributed by the Coriell Institute for Medical Research. We wish to thank members and participants in the Breast Cancer Family Registry for their contributions to the study. The ABCFS would like to also thank Maggie Angelakos, Judi Maskiell, and Gillian Dite. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR.

Baltic Familial Breast Ovarian Cancer Consortium (BFBOCC): BFBOCC acknowledges Vilius Rudaitis and Laimonas Griškevičius. BFBOCC-LV acknowledges oncologists Janis Eglitis, Anna Krilova and Aivars Stengrevics.

BRCA-gene mutations and breast cancer in South African women (BMBSA): BMBSA thanks the families who contributed to the BMBSA study.

Beckman Research Institute of the City of Hope (BRICOH): BRICOH thanks Greg Wilhoite and Marie Pinto for their work in participant enrollment and biospecimen and data management.

Copenhagen Breast Cancer Study (CBCS): CBCS thanks the Danish Breast Cancer Cooperative Group (DBCG) for clinical data.

Spanish National Cancer Centre (CNIO): CNIO thanks Alicia Barroso, Rosario Alonso and Guillermo Pita for their assistance.

CONsorzio Studi ITaliani sui Tumori Ereditari Alla Mammella (CONSIT TEAM): CONSIT TEAM acknowledges Daniela Zaffaroni of the Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Monica Barile of Istituto Europeo di Oncologia (IEO), Milan, Riccardo Dolcetti of the Centro di Riferimento Oncologico (CRO) IRCCS, Aviano (PN), Maurizio Genuardi of University of Florence, Florence, Giuseppe Giannini of “La Sapienza” University, Rome, Adele Patrini of the Ospedale di Circolo-Università dell'Insubria, Varese, Antonella Savarese and Aline Martayain of the Istituto Nazionale Tumori Regina Elena (IRE), Rome and Stefania Tommasi of the Istituto Nazionale Tumori “Giovanni Paolo II”, Bari and the personnel of the CGT-lab at IFOM-IEO Campus, Milan, Italy.

Dana-Farber Cancer Institute (DFCI): DFCI thanks the study staff and participants.

The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON): HEBON recognizes Netherlands Cancer Institute, Amsterdam, NL: M.A. Rookus, F.B.L. Hogervorst, S. Verhoef, F.E. van Leeuwen, M.K. Schmidt, J. de Lange; Erasmus Medical Center, Rotterdam, NL: J.M. Collée, A.M.W. van den Ouweland, M.J. Hooning, C. Seynaeve; Leiden University Medical Center, NL: C.J. van Asperen, J.T. Wijnen, R.A. Tollenaar, P. Devilee, T.C.T.E.F. van Cronenburg; Radboud University Nijmegen Medical Center, NL: C.M. Kets, A.R. Mensenkamp; University Medical Center Utrecht, NL: M.G.E.M. Ausems, R.B. van der Luijt; Amsterdam Medical Center, NL: C.M. Aalfs, T.A.M. van Os; VU University Medical Center, Amsterdam, NL: J.J.P. Gille, Q. Waisfisz, H.E.J. Meijers-Heijboer; University Hospital Maastricht, NL: E.B. Gómez-Garcia, M.J. Blok; University Medical Center Groningen, NL: J.C. Oosterwijk, H. van der Hout, M.J. Mourits, G.H. de Bock.

Epidemiological study of BRCA1 & BRCA2 mutation carriers (EMBRACE): Douglas F. Easton is the PI of the study. EMBRACE acknowledges the Coordinating Centre, Cambridge: Susan Peock, Debra Frost, Steve Ellis, Elena Fineberg, Radka Platte. North of Scotland Regional Genetics Service, Aberdeen: Zosia Miedzybrodzka, Helen Gregory. Northern Ireland Regional Genetics Service, Belfast: Patrick Morrison, Lisa Jeffers. West Midlands Regional Clinical Genetics Service, Birmingham: Trevor Cole, Kai-ren Ong, Jonathan Hoffman. South West Regional Genetics Service, Bristol: Alan Donaldson, Margaret James. East Anglian Regional Genetics Service, Cambridge: Marc Tischkowitz, Joan Paterson, Amy Taylor. Medical Genetics Services for Wales, Cardiff: Alexandra Murray, Mark T. Rogers, Emma McCann. St James's Hospital, Dublin & National Centre for Medical Genetics, Dublin: M. John Kennedy, David Barton. South East of Scotland Regional Genetics Service, Edinburgh: Mary Porteous, Sarah Drummond. Peninsula Clinical Genetics Service, Exeter: Carole Brewer, Emma Kivuva, Anne Searle, Selina Goodman, Kathryn Hill. West of Scotland Regional Genetics Service, Glasgow: Rosemarie Davidson, Victoria Murday, Nicola Bradshaw, Lesley Snadden, Mark Longmuir, Catherine Watt, Sarah Gibson, Eshika Haque, Ed Tobias, Alexis Duncan. South East Thames Regional Genetics Service, Guy's Hospital London: Louise Izatt, Chris Jacobs, Caroline Langman. North West Thames Regional Genetics Service, Harrow: Huw Dorkins, Angela Brady, Athalie Melville, Kashmir Randhawa. Leicestershire Clinical Genetics Service, Leicester: Julian Barwell. Yorkshire Regional Genetics Service, Leeds: Julian Adlard, Gemma Serra-Feliu. Cheshire & Merseyside Clinical Genetics Service, Liverpool: Ian Ellis, Catherine Houghton. Manchester Regional Genetics Service, Manchester: D Gareth Evans, Fiona Lalloo, Jane Taylor. North East Thames Regional Genetics Service, NE Thames, London: Lucy Side, Alison Male, Cheryl Berlin. Nottingham Centre for Medical Genetics, Nottingham: Jacqueline Eason, Rebecca Collier. Northern Clinical Genetics Service, Newcastle: Fiona Douglas, Oonagh Claber, Irene Jobson. Oxford Regional Genetics Service, Oxford: Lisa Walker, Diane McLeod, Dorothy Halliday, Sarah Durell, Barbara Stayner. The Institute of Cancer Research and Royal Marsden NHS Foundation Trust: Rosalind A. Eeles, Susan Shanley, Nazneen Rahman, Richard Houlston, Astrid Stormorken, Elizabeth Bancroft, Elizabeth Page, Audrey Ardern-Jones, Kelly Kohut, Jennifer Wiggins, Elena Castro, Emma Killick, Sue Martin, Gillian Rea, Anjana Kulkarni. North Trent Clinical Genetics Service, Sheffield: Jackie Cook, Oliver Quarrell, Cathryn Bardsley. South West Thames Regional Genetics Service, London: Shirley Hodgson, Sheila Goff, Glen Brice, Lizzie Winchester, Charlotte Eddy, Vishakha Tripathi, Virginia Attard, Anna Lehmann. Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton: Diana Eccles, Anneke Lucassen, Gillian Crawford, Donna McBride, Sarah Smalley.

Fox Chase Cancer Canter (FCCC): FCCC thanks Dr. Betsy Bove for her technical support.

German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC): GC-HBOC thanks all family members who participated in this study, Wolfram Heinritz, Center Leipzig, and Dieter Schäfer, Center Frankfurt, for providing DNA samples and Juliane Köhler for excellent technical assistance.

Genetic Modifiers of Cancer Risk in BRCA1/2 Mutation Carriers (GEMO): GEMO thanks all the GEMO collaborating groups for their contribution to this study. GEMO Collaborating Centers are: Coordinating Centres, Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon - Centre Léon Bérard, & Equipe «Génétique du cancer du sein», Centre de Recherche en Cancérologie de Lyon: Olga Sinilnikova, Sylvie Mazoyer, Francesca Damiola, Laure Barjhoux, Carole Verny-Pierre, Sophie Giraud, Mélanie Léone; and Service de Génétique Oncologique, Institut Curie, Paris: Dominique Stoppa-Lyonnet, Marion Gauthier-Villars, Bruno Buecher, Claude Houdayer, Virginie Moncoutier, Muriel Belotti, Carole Tirapo, Antoine de Pauw. Institut Gustave Roussy, Villejuif: Brigitte Bressac-de-Paillerets, Olivier Caron. Centre Jean Perrin, Clermont–Ferrand: Yves-Jean Bignon, Nancy Uhrhammer. Centre Léon Bérard, Lyon: Christine Lasset, Valérie Bonadona, Sandrine Handallou. Centre François Baclesse, Caen: Agnès Hardouin, Pascaline Berthet. Institut Paoli Calmettes, Marseille: Hagay Sobol, Violaine Bourdon, Tetsuro Noguchi, Audrey Remenieras, François Eisinger. CHU Arnaud-de-Villeneuve, Montpellier: Isabelle Coupier, Pascal Pujol. Centre Oscar Lambret, Lille: Jean-Philippe Peyrat, Joëlle Fournier, Françoise Révillion, Philippe Vennin, Claude Adenis. Hôpital René Huguenin/Institut Curie, St Cloud: Etienne Rouleau, Rosette Lidereau, Liliane Demange, Catherine Nogues. Centre Paul Strauss, Strasbourg: Danièle Muller, Jean-Pierre Fricker. Institut Bergonié, Bordeaux: Emmanuelle Barouk-Simonet, Françoise Bonnet, Virginie Bubien, Nicolas Sevenet, Michel Longy. Institut Claudius Regaud, Toulouse: Christine Toulas, Rosine Guimbaud, Laurence Gladieff, Viviane Feillel. CHU Grenoble: Dominique Leroux, Hélène Dreyfus, Christine Rebischung, Magalie Peysselon. CHU Dijon: Fanny Coron, Laurence Faivre. CHU St-Etienne: Fabienne Prieur, Marine Lebrun, Caroline Kientz. Hôtel Dieu Centre Hospitalier, Chambéry: Sandra Fert Ferrer. Centre Antoine Lacassagne, Nice: Marc Frénay. CHU Limoges: Laurence Vénat-Bouvet. CHU Nantes: Capucine Delnatte. CHU Bretonneau, Tours: Isabelle Mortemousque. Groupe Hospitalier Pitié-Salpétrière, Paris: Florence Coulet, Chrystelle Colas, Florent Soubrier. CHU Vandoeuvre-les-Nancy : Johanna Sokolowska, Myriam Bronner. Creighton University, Omaha, USA: Henry T. Lynch, Carrie L. Snyder.

GFAST: G-FAST acknowledges the contribution of Bruce Poppe and Anne De Paepe and the technical support of Ilse Coene en Brecht Crombez.

Hospital Clinico San Carlos (HCSC): HCSC acknowledges Alicia Tosar for her technical assistance

Helsinki Breast Cancer Study (HEBCS): HEBCS thanks Carl Blomqvist, Kirsimari Aaltonen and RN Irja Erkkilä for their help with the HEBCS data and samples.

Study of Genetic Mutations in Breast and Ovarian Cancer patients in Hong Kong and Asia (HRBCP): HRBCP thanks Hong Kong Sanatoriuma and Hospital for their continual support.

Molecular Genetic Studies of Breast and Ovarian Cancer in Hungary (HUNBOCS): HUNBOCS thanks Hungarian Breast and Ovarian Cancer Study Group members (Janos Papp, Aniko Bozsik, Kristof Arvai, Judit Franko, Maria Balogh, Gabriella Varga, Judit Ferenczi, Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary) and the clinicians and patients for their contributions to this study.

INterdisciplinary HEalth Research Internal Team BReast CAncer susceptibility (INHERIT): INHERIT thanks Dr Martine Dumont, Martine Tranchant for sample management and skillful technical assistance. J.S. is Chairholder of the Canada Research Chair in Oncogenetics.

Kathleen Cuningham Consortium for Research into Familial Breast Cancer (kConFab): kConFab thanks Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study for their contributions to this resource, and the many families who contribute to kConFab.

Modifier Study of Quantitative Effects on Disease (MODSQUAD): MODSQUAD acknowledges ModSQuaD members Csilla Szabo and Zohra Ali-Kahn Catts (University of Delaware, Newark, USA); Lenka Foretova and Eva Machackova (Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic); and Michal Zikan, Petr Pohlreich and Zdenek Kleibl (Oncogynecologic Center and Department of Biochemistry and Experimental Oncology, First Faculty of Medicine, Charles University, Prague, Czech Republic).

National Israeli Cancer Control Center (NICCC): NICCC thanks the NICCC National Familial Cancer Consultation Service team led by Sara Dishon, the laboratory team led by Dr. Flavio Lejbkowicz, and the research field operations team led by Dr. Mila Pinchev.

Ontario Cancer Genetics Network (OCGN): OCGN thanks the study staff and participants.

The Ohio State University Comprehensive Cancer Center (OSUCCG): OSU CCG acknowledges Kevin Sweet, Caroline Craven and Michelle O'Connor who were instrumental in accrual of study participants, ascertainment of medical records and database management. Samples were processed by the OSU Human Genetics Sample Bank.

South East Asian Breast Cancer Association Study (SEABASS): SEABASS thanks Yip Cheng Har, Nur Aishah Mohd Taib, Phuah Sze Yee, Norhashimah Hassan and all the research nurses, research assistants and doctors involved in the MyBrCa Study for assistance in patient recruitment, data collection and sample preparation. In addition, we thank Philip Iau, Sng Jen-Hwei and Sharifah Nor Akmal for contributing samples from the Singapore Breast Cancer Study and the HUKM-HKL Study respectively.

Sheba Medical Centre (SMC): SMC acknowledges the assistance of the Meirav Comprehensice breast cancer center team at the Sheba Medical Center for assistance in this study.

Swedish Breast Cancer Study (SWE-BRCA): SWE-BRCA Acknowledges SWE-BRCA collaborators from Lund University and University Hospital: Åke Borg, Håkan Olsson, Helena Jernström, Karin Henriksson, Katja Harbst, Maria Soller, Niklas Loman, Ulf Kristoffersson; Gothenburg Sahlgrenska University Hospital: Anna Öfverholm, Margareta Nordling, Per Karlsson, Zakaria Einbeigi; Stockholm and Karolinska University Hospital: Anna von Wachenfeldt, Annelie Liljegren, Annika Lindblom, Brita Arver, Gisela Barbany Bustinza, Johanna Rantala; Umeå University Hospital: Beatrice Melin, Christina Edwinsdotter Ardnor, Monica Emanuelsson; Uppsala University: Hans Ehrencrona, Maritta Hellström Pigg, Richard Rosenquist; Linköping University Hospital: Marie Stenmark-Askmalm, Sigrun Liedgren.

The University of Chicago Center for Clinical Cancer Genetics and Global Health (UCHICAGO): UCHICAGO thanks Cecilia Zvocec, Qun Niu, physicians, genetic counselors, research nurses and staff of the Cancer Risk Clinic for their contributions to this resource, and the many families who contribute to our program. OIO is an ACS Clinical Research Professor.

University of California Los Angeles (UCLA): UCLA thanks Joyce Seldon MSGC and Lorna Kwan, MPH for assembling the data for this study.

University of California San Francisco (UCSF): UCSF thanks Ms. Salina Chan for her data management and the following genetic counselors for participant recruitment: Beth Crawford, Nicola Stewart, Julie Mak, and Kate Lamvik.

United Kingdom Familial Ovarian Cancer Registries (UKFOCR): UKFOCR thanks Paul Pharoah, Simon Gayther, Carole Pye, Patricia Harrington and Eva Wozniak for their contributions towards the UKFOCR.

Victorian Familial Cancer Trials Group (VFCTG): VFCTG thanks Sarah Sawyer and Rebecca Driessen for assembling this data and Ella Thompson for performing all DNA amplification.

Author Contributions

Conceived and designed the experiments: Fergus J Couch, Douglas F Easton, Georgia Chenevix-Trench, Kenneth Offit, Antonis C Antoniou. Performed the experiments: Fergus J Couch, Julie Cunningham, Xianshu Wang, Curtis Olswold, Matthew Kosel, Adam Lee, Mia M Gaudet, Kenneth Offit, François Bacot, Daniel Vincent, Daniel Tessier. Analyzed the data: Antonis C Antoniou, Karoline B Kuchenbaecker, Lesley McGuffog, Daniel Barrowdale, Andrew Lee, Joe Dennis, Ed Dicks, Vernon S Pankratz, Zachary Fredericksen, Curtis Olswold, Matthew Kosel. Contributed reagents/materials/analysis tools: Penny Soucy, Kristen Stevens, Jacques Simard, Tomi Pastinen, Sue Healey, Olga M Sinilnikova, Andrew Lee. Wrote the manuscript: Fergus J Couch, Douglas F Easton, Antonis C Antoniou. Collected data and samples and provided critical review of the manuscript: Fergus J Couch, Xianshu Wang, Lesley McGuffog, Curtis Olswold, Karoline B Kuchenbaecker, Penny Soucy, Zachary Fredericksen, Daniel Barrowdale, Joe Dennis, Mia M Gaudet, Ed Dicks, Matthew Kosel, Olga M Sinilnikova, François Bacot, Daniel Vincent, Frans BL Hogervorst, Susan Peock, Dominique Stoppa-Lyonnet, Anna Jakubowska, Paolo Radice, Rita Katharina Schmutzler, Susan M Domchek, Marion Piedmonte, Christian F Singer, Thomas v O Hansen, Susan L Neuhausen, Csilla I Szabo, Ignacio Blanco, Mark H Greene, Beth Y Karlan, Catherine M Phelan, Jeffrey N Weitzel, Marco Montagna, Edith Olah, Irene L Andrulis, Andrew K Godwin, Drakoulis Yannoukakos, David E Goldgar, Trinidad Caldes, Heli Nevanlinna, Ana Osorio, Mary Beth Terry, Mary B Daly, Elizabeth J van Rensburg, Ute Hamann, Susan J Ramus, Amanda Ewart Toland, Maria A Caligo, Olufunmilayo I Olopade, Nadine Tung, Kathleen Claes, Mary S Beattie, Melissa C Southey, Evgeny N Imyanitov, Ramunas Janavicius, Esther M John, Ava Kwong, Orland Diez, Rosa B Barkardottir, Banu K Arun, Gad Rennert, Soo-Hwang Teo, Patricia A Ganz, Annemarie H van der Hout, Carolien HM van Deurzen, Encarna B Gómez Garcia, Flora E van Leeuwen, Hanne EJ Meijers-Heijboer, Johannes JP Gille, Margreet GEM Ausems, Marinus J Blok, Marjolijn JL Ligtenberg, Matti A Rookus, Peter Devilee, Theo AM van Os, Juul T Wijnen, Debra Frost, Radka Platte, D Gareth Evans, Louise Izatt, Rosalind A Eeles, Julian Adlard, Diana M Eccles, Carole Brewer, Patrick J Morrison, Lucy E Side, Alan Donaldson, Mark T Rogers, Jacqueline Eason, Helen Gregory, Emma McCann, Alain Calender, Agnès Hardouin, Pascaline Berthet, Capucine Delnatte, Catherine Nogues, Dominique Leroux, Etienne Rouleau, Fabienne Prieur, Hagay Sobol, Laurence Venat-Bouvet, Laurent Castera, Marion Gauthier-Villars, Mélanie Léoné, Yves-Jean Bignon, Elżbieta Złowocka-Perłowska, Katarzyna Durda, Katarzyna Jaworska, Tomasz Huzarski, Alessandra Viel, Bernard Peissel, Bernardo Bonanni, Giulia Melloni, Laura Ottini, Laura Papi, Liliana Varesco, Maria Grazia Tibiletti, Valeria Pensotti, Norbert Arnold, Christoph Engel, Dorothea Gadzicki, Andrea Gehrig, Karin Kast, Kerstin Rhiem, Dieter Niederacher, Nina Ditsch, Hansjoerg Plendl, Sabine Preisler-Adams, Raymonda Varon-Mateeva, Barbara Wappenschmidt, Bernhard H F Weber, Brita Arver, Marie Stenmark-Askmalm, Richard Rosenquist, Zakaria Einbeigi, Katherine L Nathanson, Timothy R Rebbeck, Stephanie V Blank, David E Cohn, Gustavo C Rodriguez, Michael Friedlander, Victoria L Bae-Jump, Anneliese Fink-Retter, Christine Rappaport, Daphne Gschwantler Kaulich, Georg Pfeiler, Muy-Kheng Tea, Bella Kaufman, Shani Shimon Paluch, Yael Laitman, Anne-Marie Gerdes, Inge Sokilde Pedersen, Sanne Traasdahl Moeller, Torben A Kruse, Uffe Birk Jensen, Joseph Vijai, Mark Robson, Noah Kauff, Anna Marie Mulligan, Gord Glendon, Hilmi Ozcelik, Bent Ejlertsen, Finn C Nielsen, Lars Jønson, Mette K Andersen, Yuan Chun Ding, Lenka Foretova, Alex Teulé, Miquel Angel Pujana, Phuong L Mai, Jennifer T Loud, Sandra Orsulic, Steven A Narod, Josef Herzog, Sharon R Sand, Silvia Tognazzo, Simona Agata, Tibor Vaszko, Joellen Weaver, Alexandra V Stavropoulou, Saundra S Buys, Atocha Romero, Miguel de la Hoya, Kristiina Aittomäki, Taru A Muranen, Mercedes Duran, Wendy K Chung, Cecilia M Dorfling, Dezheng Huo, Salina B Chan, Anna P Sokolenko, Laima Tihomirova, Tara M Friebel, Bjarni A Agnarsson, Karen H Lu, Flavio Lejbkowicz, Paul A James, Per Hall, Alison M Dunning, Daniel Tessier, Susan L Slager, Jacques Simard, Tomi Pastinen, Vernon S Pankratz, Kenneth Offit, Douglas F Easton, Georgia Chenevix-Trench, Antonis C Antoniou, Andrew Lee, Adam Lee, Adriana Lasa, Alexander Miron, Caroline Seynaeve, Christian Sutter, Eitan Friedman, Elena Fineberg, Christine Lasset, Amanda B Spurdle, Anne-Bine Skytte, Alfons Meindl, Claude Houdayer, Fiona Douglas Francesca Damiola, Catherine Houghton, Alex Murray, Jan Lubinski, Conxi Lazaro, Christine Walsh, Chen Wang, Jenny Lester, Huw Dorkins, Helmut Deissler, Ian Campbell, Isabelle Coupier, Judith Balmaña, Joan Brunet, Javier Benitez, Jackie Cook, Jocelyne Chiquette, Judy Garber, Jacek Gronwald, Kara Sarrel, Kristen Stevens, Laurie Small, Leigha Senter, Linda Steele, Mads Thomassen, Marc Tischkowitz, Niklas Loman, Noralane M Lindor, Pascal Pujol, Paolo Peterlongo, Steve Ellis, Stefanie Engert, Sue Healey, Shirley Hodgson, Steven Hart, Sylvie Mazoyer, Siranoush, Manoukian, Senno Verhoef, Sara Volorio.

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