A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J Aronson, Paul L Auer, Annelie Augustinsson, Thaïs Baert, Laura E Beane Freeman, Heiko Becher, Matthias W Beckmann, Javier Benitez, Stig E BojesenHiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E Castelao, Stephen J Chanock, Georgia Chenevix-Trench, Emilie Cordina-Duverger, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A Heather Eliassen, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine D Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G Giles, Anna González-Neira, Felix Grassmann, Sune F Nielsen, Børge G Nordestgaard, CTS Consortium


BACKGROUND: Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.

METHODS: Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.

RESULTS: Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).

CONCLUSIONS: Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

TidsskriftBreast Cancer Research
Udgave nummer1
Sider (fra-til)93
StatusUdgivet - 9 aug. 2023


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