A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Rudolph, Anja; Fasching, Peter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet; Wang, Qin; Thompson, Deborah; Czene, Kamila; Brand, Judith; Li, Jingmei; Scott, Christopher; Pankratz, V.; Brandt, Kathleen; Hallberg, Emily; Olson, Janet; Lee, Adam; Beckmann, Matthias; Ekici, Arif; Haeberle, Lothar; Maskarinec, Gertraud; Le Marchand, Loic; Schumacher, Fredrick; Milne, Roger; Knight, Julia; Apicella, Carmel; Southey, Melissa; Kapuscinski, Miroslav; Hopper, John; Andrulis, Irene; Giles, Graham; Haiman, Christopher; Khaw, Kay-Tee; Luben, Robert; Hall, Per; Pharoah, Paul; Couch, Fergus; Easton, Douglas; dos-Santos-Silva, Isabel; Vachon, Celine; Chang-Claude, Jenny;
• Is Part Of: Breast cancer research. Volume 17:Issue 1(2015)
• Page Start: 1
• Page End: 12
• Publication Date: 2015-12
• Subjects: Breast -- Cancer -- Periodicals; 616.99449
• DOI: 10.1186/s13058-015-0625-9
• Languages: English
• ISSNs: 1465-542X

Abstract

Abstract 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 lowestP -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 andTNF ) and ten SNPs (AREG -rs10034692, PRDM6 -rs186749, ESR1 -rs12665607, ZNF365 -rs10995190, 8p11.23-rs7816345, LSP1 -rs3817198, IGF1 -rs703556, 12q24-rs1265507, TMEM184B -rs7289126, andSGSM3 -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 (unadjustedP int <0.0004) was observed with rs9358531 6.5kb 5′ ofPRL. Furthermore, three SNPs inPLCG2 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 (unadjustedP int <0.002), but solely among cases (unadjustedP int SNP×MHT×case-status <0.02). Conclusions The study identified potential interactions on mammographic density between current use of MHT and SNPs nearPRL and inPLCG2, 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.