Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach

Guimin Gao; Fangyuan Zhao; Thomas U Ahearn; Kathryn L Lunetta; Melissa A Troester; Zhaohui Du; Temidayo O Ogundiran; Oladosu Ojengbede; William Blot; Katherine L Nathanson; Susan M Domchek; Barbara Nemesure; Anselm Hennis; Stefan Ambs; Julian McClellan; Mark Nie; Kimberly Bertrand; Gary Zirpoli; Song Yao; Andrew F Olshan; Jeannette T Bensen; Elisa V Bandera; Sarah Nyante; David V Conti; Michael F Press; Sue A Ingles; Esther M John; Leslie Bernstein; Jennifer J Hu; Sandra L Deming-Halverson; Stephen J Chanock; Regina G Ziegler; Jorge L Rodriguez-Gil; Lara E Sucheston-Campbell; Dale P Sandler; Jack A Taylor; Cari M Kitahara; Katie M O'Brien; Manjeet K Bolla; Joe Dennis; Alison M Dunning; Douglas F Easton; Kyriaki Michailidou; Paul D P Pharoah; Qin Wang; Jonine Figueroa; Richard Biritwum; Ernest Adjei; Seth Wiafe; GBHS Study Team; Christine B Ambrosone; Wei Zheng; Olufunmilayo I Olopade; Montserrat García-Closas; Julie R Palmer; Christopher A Haiman; Dezheng Huo

doi:10.1093/hmg/ddac102

Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach

Hum Mol Genet. 2022 Sep 10;31(18):3133-3143. doi: 10.1093/hmg/ddac102.

Authors

Guimin Gao¹, Fangyuan Zhao¹, Thomas U Ahearn², Kathryn L Lunetta³, Melissa A Troester⁴, Zhaohui Du⁵, Temidayo O Ogundiran⁶, Oladosu Ojengbede⁷, William Blot⁸, Katherine L Nathanson⁹, Susan M Domchek⁹, Barbara Nemesure¹⁰, Anselm Hennis^{10

11}, Stefan Ambs¹², Julian McClellan¹, Mark Nie¹, Kimberly Bertrand¹³, Gary Zirpoli¹³, Song Yao¹⁴, Andrew F Olshan⁴, Jeannette T Bensen⁴, Elisa V Bandera¹⁵, Sarah Nyante¹⁶, David V Conti¹⁷, Michael F Press¹⁸, Sue A Ingles¹⁷, Esther M John¹⁹, Leslie Bernstein²⁰, Jennifer J Hu²¹, Sandra L Deming-Halverson⁸, Stephen J Chanock², Regina G Ziegler², Jorge L Rodriguez-Gil²², Lara E Sucheston-Campbell²³, Dale P Sandler²⁴, Jack A Taylor²⁴, Cari M Kitahara²⁵, Katie M O'Brien²⁴, Manjeet K Bolla²⁶, Joe Dennis²⁶, Alison M Dunning²⁷, Douglas F Easton^{26

27}, Kyriaki Michailidou²⁸, Paul D P Pharoah^{26

27}, Qin Wang²⁶, Jonine Figueroa^{29

30}, Richard Biritwum³¹, Ernest Adjei³², Seth Wiafe³³; GBHS Study Team; Christine B Ambrosone¹⁴, Wei Zheng⁸, Olufunmilayo I Olopade³⁴, Montserrat García-Closas², Julie R Palmer¹³, Christopher A Haiman¹⁷, Dezheng Huo^{1

34}

Affiliations

¹ Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA.
² Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA.
³ Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA.
⁴ Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
⁵ Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
⁶ Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria.
⁷ Centre for Population & Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria.
⁸ Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
⁹ Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
¹⁰ Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA.
¹¹ University of the West Indies, Bridgetown, Bardados.
¹² Laboratory of Human Carcinogenesis, National Cancer Institute, Bethesda, MD 20892, USA.
¹³ Slone Epidemiology Center, Boston University, Boston, MA 02215, USA.
¹⁴ Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA.
¹⁵ Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA.
¹⁶ Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
¹⁷ Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
¹⁸ Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
¹⁹ Departments of Epidemiology & Population Health and of Medicine (Oncology) and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94304, USA.
²⁰ Biomarkers of Early Detection and Prevention, Department of Population Sciences, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA.
²¹ Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
²² Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, Bethesda, MD 20894, USA.
²³ Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH 43210, USA.
²⁴ Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA.
²⁵ Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
²⁶ Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK.
²⁷ Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK.
²⁸ Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia 2371, Cyprus.
²⁹ Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh EH16 5TJ, UK.
³⁰ Cancer Research UK Edinburgh Centre, Edinburgh EH4 2XR, UK.
³¹ University of Ghana, Accra, Ghana.
³² Komfo Anokye Teaching Hospital, Kumasi, Ghana.
³³ School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA.
³⁴ Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA.

Abstract

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms* / genetics
Female
Genetic Predisposition to Disease
Genome-Wide Association Study*
Humans
Multifactorial Inheritance / genetics
Receptors, Estrogen / genetics
Risk Factors

Substances

Receptors, Estrogen

Abstract

Publication types

MeSH terms

Substances

Grants and funding