TY - JOUR

T1 - Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium

AU - Rudolph, Anja

AU - Song, Minsun

AU - Brook, Mark N.

AU - Milne, Roger L.

AU - Mavaddat, Nasim

AU - Michailidou, Kyriaki

AU - Bolla, Manjeet K.

AU - Wang, Qin

AU - Dennis, Joe

AU - Wilcox, Amber N.

AU - Hopper, John L.

AU - Southey, Melissa C.

AU - Keeman, Renske

AU - Fasching, Peter A.

AU - Beckmann, Matthias W.

AU - Gago-Dominguez, Manuela

AU - Castelao, Jose E.

AU - Guénel, Pascal

AU - Truong, Thérèse

AU - Bojesen, Stig E.

AU - Flyger, Henrik

AU - Brenner, Hermann

AU - Arndt, Volker

AU - Brauch, Hiltrud

AU - Brüning, Thomas

AU - Mannermaa, Arto

AU - Kosma, Veli Matti

AU - Lambrechts, Diether

AU - Keupers, Machteld

AU - Couch, Fergus J.

AU - Vachon, Celine

AU - Giles, Graham G.

AU - MacInnis, Robert J.

AU - Figueroa, Jonine

AU - Brinton, Louise

AU - Czene, Kamila

AU - Brand, Judith S.

AU - Gabrielson, Marike

AU - Humphreys, Keith

AU - Cox, Angela

AU - Cross, Simon S.

AU - Dunning, Alison M.

AU - Orr, Nick

AU - Swerdlow, Anthony

AU - Hall, Per

AU - Pharoah, Paul D.P.

AU - Schmidt, Marjanka K.

AU - Easton, Douglas F.

AU - Chatterjee, Nilanjan

AU - Chang-Claude, Jenny

AU - García-Closas, Montserrat

PY - 2018

Y1 - 2018

N2 - Background: Polygenic 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. Methods: Analyses 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. Results: The 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). Conclusions: The 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.

AB - Background: Polygenic 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. Methods: Analyses 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. Results: The 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). Conclusions: The 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.

KW - Breast cancer

KW - Epidemiology

KW - Gene-environment interactions

KW - Genetic susceptibility

KW - Risk prediction

U2 - 10.1093/IJE/DYX242

DO - 10.1093/IJE/DYX242

M3 - Journal article

C2 - 29315403

AN - SCOPUS:85048267311

VL - 47

SP - 526

EP - 536

JO - International Journal of Epidemiology

JF - International Journal of Epidemiology

SN - 0300-5771

IS - 2

ER -