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Rudolph, Anja; Fasching, Peter A.; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K.; Wang, Qin; Thompson, Deborah; Czene, Kamila; Brand, Judith S.; Li, Jingmei; Scott, Christopher; Pankratz, V. Shane; Brandt, Kathleen; Hallberg, Emily; Olson, Janet E.; Lee, Adam; Beckmann, Matthias W.; Ekici, Arif B.; Haeberle, Lothar; Maskarinec, Gertraud; Le Marchand, Loic; Schumacher, Fredrick; Milne, Roger L.; Knight, Julia A.; Apicella, Carmel; Southey, Melissa C.; Kapuscinski, Miroslav K.; Hopper, John L.; Andrulis, Irene L.; Giles, Graham G. ... view all 40 authors View less authors (2015)
Publisher: BioMed Central
Journal: Breast Cancer Research : BCR
Languages: English
Types: Article
Subjects: Research Article, mammographic density, gene - environment interaction, single nucleotide polymorphism, Medizinische Fakultät, -, menopausal hormone therapy
ddc: ddc:610
Introduction Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density. Methods The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density. Results No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5? of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP?MHT?case-status <0.02). Conclusions The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0625-9) contains supplementary material, which is available to authorized users.
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