Gaudet M.M.,Epidemiology Research Program |
Barrdahl M.,German Cancer Research Center |
Lindstrom S.,Harvard University |
Travis R.C.,University of Oxford |
And 35 more authors.
Breast Cancer Research and Treatment | Year: 2016
Current use of menopausal hormone therapy (MHT) has important implications for postmenopausal breast cancer risk, and observed associations might be modified by known breast cancer susceptibility loci. To provide the most comprehensive assessment of interactions of prospectively collected data on MHT and 17 confirmed susceptibility loci with invasive breast cancer risk, a nested case–control design among eight cohorts within the NCI Breast and Prostate Cancer Cohort Consortium was used. Based on data from 13,304 cases and 15,622 controls, multivariable-adjusted logistic regression analyses were used to estimate odds ratios (OR) and 95 % confidence intervals (CI). Effect modification of current and past use was evaluated on the multiplicative scale. P values <1.5 × 10−3 were considered statistically significant. The strongest evidence of effect modification was observed for current MHT by 9q31-rs865686. Compared to never users of MHT with the rs865686 GG genotype, the association between current MHT use and breast cancer risk for the TT genotype (OR 1.79, 95 % CI 1.43–2.24; Pinteraction = 1.2 × 10−4) was less than expected on the multiplicative scale. There are no biological implications of the sub-multiplicative interaction between MHT and rs865686. Menopausal hormone therapy is unlikely to have a strong interaction with the common genetic variants associated with invasive breast cancer. © 2016, Springer Science+Business Media New York. Source
Canzian F.,German Cancer Research Center |
Joshi A.D.,Harvard University |
Travis R.C.,University of Oxford |
Auer P.L.,Fred Hutchinson Cancer Research Center |
And 46 more authors.
Human Molecular Genetics | Year: 2014
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. © 2014. Published by Oxford University Press. Source