Post-GWAS gene-environment interplay in breast cancer: Results from the Breast and Prostate Cancer Cohort Consortium and a meta-analysis on 79 000 women

Myrto Barrdahl, Federico Canzian, Amit D. Joshi, Ruth C Travis, Jenny Chang-Claude, Paul L. Auer, Susan M. Gapstur, Mia M Gaudet, William Ryan Diver, Brian E Henderson, Christopher A Haiman, Fredrick R. Schumacher, Loïc Le Marchand, Christine D Berg, Stephen J Chanock, Robert N Hoover, Anja Rudolph, Regina G Ziegler, Graham G. Giles, Laura BagliettoGianluca Severi, Susan E Hankinson, Sara Lindström, Walter Willet, David J. Hunter, Julie E Buring, I-Min Lee, Shumin Zhang, Laure Dossus, David G. Cox, Kay-Tee Khaw, Eiliv Eylin Lund, Alessio Naccarati, Petra H. Peeters, J. Ramón Quirós, Elio B Riboli, Malin Sund, Dimitrios Trichopoulos, Ross L. Prentice, Peter Kraft, Rudolf J Kaaks, Daniele Campa

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27 Citations (Scopus)


We studied the interplay between 39 breast cancer (BC) risk SNPs and established BC risk (body mass index, height, age at menarche, parity, age at menopause, smoking, alcohol and family history of BC) and prognostic factors (TNMstage, tumor grade, tumor size, age at diagnosis, estrogenreceptor statusandprogesterone receptor status) as joint determinants of BC risk. We used a nested case-control design within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), with 16 285 BC cases and 19 376 controls. We performed stratified analyses for both the risk and prognostic factors, testing for heterogeneity for the risk factors, and case-case comparisons for differential associations of polymorphisms by subgroups of the prognostic factors. We analyzed multiplicative interactions between the SNPs and the risk factors. Finally, we also performed a meta-analysis of the interaction ORs from BPC3 and the Breast Cancer Association Consortium. After correction for multiple testing, no significant interaction between the SNPs and the established risk factors in the BPC3 study was found. The meta-analysis showed a suggestive interaction between smoking status and SLC4A7-rs4973768 (Pinteraction =8.84 3 10-4) which, although not significant after considering multiple comparison, has a plausible biological explanation. In conclusion, in this study of up to almost 79 000 women we can conclusively exclude any novel major interactions between genome-wide association studies hitsandthe epidemiologic risk factors takeninto consideration, butwepropose a suggestive interaction between smoking status and SLC4A7-rs4973768 that if further replicated could help our understanding in the etiology of BC.

Original languageEnglish
Pages (from-to)5260-5270
Number of pages11
JournalHuman Molecular Genetics
Issue number19
Publication statusPublished - 1 Oct 2014

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