• Anja Rudolph, Minsun Song, Mark N Brook, Roger L Milne, Nasim Mavaddat, Kyriaki Michailidou, Manjeet K Bolla, Qin Wang, Joe Dennis, Amber N Wilcox, John L Hopper, Melissa C Southey, Renske Keeman, Peter A Fasching, Matthias W Beckmann, Manuela Gago-Dominguez, Jose E Castelao, Pascal Guénel, Thérèse Truong, Stig E Bojesen, Henrik Flyger, Hermann Brenner, Volker Arndt, Hiltrud Brauch, Thomas Brüning, Arto Mannermaa, Veli-Matti Kosma, Diether Lambrechts, Machteld Keupers, Fergus J Couch, Celine Vachon, Graham G Giles, Robert J MacInnis, Jonine Figueroa, Louise Brinton, Kamila Czene, Judith S Brand, Marike Gabrielson, Keith Humphreys, Angela Cox, Simon S Cross, Alison M Dunning, Nick Orr, Anthony Swerdlow, Per Hall, PharoahPaul D PPDPDepartment of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK.Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK., Marjanka K Schmidt, Douglas F Easton, Nilanjan Chatterjee, Jenny Chang-Claude, and Montserrat García-Closas.
• Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
• Int J Epidemiol. 2018 Apr 1; 47 (2): 526-536.

BackgroundPolygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors.MethodsAnalyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status.ResultsThe strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests).ConclusionsThe combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.

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