A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
Authors: Middha Pooja , Wang Xiaoliang , Behrens Sabine , Bolla Manjeet K. , Wang Qin , Dennis Joe , Michailidou Kyriaki , Ahearn Thomas U. , Andrulis Irene L. , Anton-Culver Hoda , Arndt Volker , Aronson Kristan J. , Auer Paul L. , Augustinsson Annelie , Baert Thaïs , Freeman Laura E. Beane , Becher Heiko , Beckmann Matthias W. , Benitez Javier , Bojesen Stig E. , Brauch Hiltrud , Brenner Hermann , Brooks-Wilson Angela , Campa Daniele , Canzian Federico , Carracedo Angel , Castelao Jose E. , Chanock Stephen J. , Chenevix-Trench Georgia ,   CTS Consortium, Cordina-Duverger Emilie , Couch Fergus J. , Cox Angela , Cross Simon S. , Czene Kamila , Dossus Laure , Dugué Pierre-Antoine , Eliassen A. Heather , Eriksson Mikael , Evans D. Gareth , Fasching Peter A. , Figueroa Jonine D. , Fletcher Olivia , Flyger Henrik , Gabrielson Marike , Gago-Dominguez Manuela , Giles Graham G. , González-Neira Anna , Grassmann Felix , Grundy Anne , Guénel Pascal , Haiman Christopher A. , Håkansson Niclas , Hall Per , Hamann Ute , Hankinson Susan E. , Harkness Elaine F. , Holleczek Bernd , Hoppe Reiner , Hopper John L. , Houlston Richard S. , Howell Anthony , Hunter David J. , Ingvar Christian ,   ABCTB Investigators,   kConFab Investigators, Isaksson Karolin , Jernström Helena , John Esther M. , Jones Michael E. , Kaaks Rudolf , Keeman Renske , Kitahara Cari M. , Ko Yon-Dschun , Koutros Stella , Kurian Allison W. , Lacey James V. , Lambrechts Diether , Larson Nicole L. , Larsson Susanna , Le Marchand Loic , Lejbkowicz Flavio , Li Shuai , Linet Martha , Lissowska Jolanta , Martinez Maria Elena , Maurer Tabea , Mulligan Anna Marie , Mulot Claire , Murphy Rachel A. , Newman William G. , Nielsen Sune F. , Nordestgaard Børge G. , Norman Aaron , O’Brien Katie M. , Olson Janet E. , Patel Alpa V. , Prentice Ross , Rees-Punia Erika , Rennert Gad , Rhenius Valerie , Ruddy Kathryn J. , Sandler Dale P. , Scott Christopher G. , Shah Mitul , Shu Xiao-Ou , Smeets Ann , Southey Melissa C. , Stone Jennifer , Tamimi Rulla M. , Taylor Jack A. , Teras Lauren R. , Tomczyk Katarzyna , Troester Melissa A. , Truong Thérèse , Vachon Celine M. , Wang Sophia S. , Weinberg Clarice R. , Wildiers Hans , Willett Walter , Winham Stacey J. , Wolk Alicja , Yang Xiaohong R. , Zamora M. Pilar , Zheng Wei , Ziogas Argyrios , Dunning Alison M. , Pharoah Paul D. P. , García-Closas Montserrat , Schmidt Marjanka K. , Kraft Peter , Milne Roger L. , Lindström Sara , Easton Douglas F. , Chang-Claude Jenny 
Published: August 2023

Abstract
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.