Hormone metabolism pathway genes and mammographic density change after quitting estrogen and progestin combined hormone therapy in the California Teachers Study
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- 作者：Eunjung Lee ; Jianning Luo ; Yu-Chen Su ; Juan Pablo Lewinger…
- 刊名：Breast Cancer Research
- 出版年：2014
- 出版时间：December 2014
- 年：2014
- 卷：16
- 期：6
- 全文大小：474 KB
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- 出版者：BioMed Central
- ISSN：1465-5411
文摘
Introduction Mammographic density (MD) is a strong biomarker of breast cancer risk. MD increases after women start estrogen plus progestin therapy (EPT) and decreases after women quit EPT. A large interindividual variation in EPT-associated MD change has been observed, but few studies have investigated genetic predictors of the EPT-associated MD change. Here, we evaluate the association between polymorphisms in hormone metabolism pathway genes and MD changes when women quit EPT. Methods We collected mammograms before and after women quit EPT and genotyped 405 tagging single nucleotide polymorphisms (SNPs) in 30 hormone metabolism pathway genes in 284 non-Hispanic white participants of the California Teachers Study (CTS). Participants were ages 49 to 71?years at time of mammography taken after quitting EPT. We assessed percent MD using a computer-assisted method. MD change was calculated by subtracting MD of an ‘off-EPT-mammogram from MD of an ‘on-EPT-(that is baseline) mammogram. Linear regression analysis was used to investigate the SNP-MD change association, adjusting for the baseline ‘on-EPT-MD, age and BMI at time of baseline mammogram, and time interval and BMI change between the two mammograms. An overall pathway and gene-level summary was obtained using the adaptive rank truncated product (ARTP) test. We calculated -em class="a-plus-plus">P values adjusted for correlated tests (P ACT)-to account for multiple testing within a gene. Results The strongest associations were observed for rs7489119 in SLCO1B1, and rs5933863 in ARSC. SLCO1B1 and ARSC are involved in excretion and activation of estrogen metabolites of EPT, respectively. MD change after quitting was 4.2% smaller per minor allele of rs7489119 (P--.0008; P ACT--.018) and 1.9% larger per minor allele of rs5933863 (P--.013; P ACT--.025). These individual SNP associations did not reach statistical significance when we further used Bonferroni correction to consider the number of tested genes. The pathway level summary ARTP P value was not statistically significant. Conclusions Data from this longitudinal study of EPT quitters suggest that genetic variation in two hormone metabolism pathway genes, SLCO1B1 and ARSC, may be associated with change in MD after women stop using EPT. Larger longitudinal studies are needed to confirm our findings.