Lee Eunjung, Luo Jianning, Su Yu-Chen, Lewinger Juan Pablo, Schumacher Fredrick R, Van Den Berg David, Wu Anna H, Bernstein Leslie, Ursin Giske
Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, Los Angeles, CA, 90089, USA.
Department of Population Sciences, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
Breast Cancer Res. 2014 Dec 11;16(6):477. doi: 10.1186/s13058-014-0477-8.
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.
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 'P values adjusted for correlated tests (P(ACT))' to account for multiple testing within a gene.
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 = 0.0008; P(ACT) = 0.018) and 1.9% larger per minor allele of rs5933863 (P = 0.013; P(ACT) = 0.025). 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.
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.
乳腺钼靶密度(MD)是乳腺癌风险的一个强有力的生物标志物。女性开始雌激素加孕激素治疗(EPT)后MD会增加,而停止EPT后MD会降低。已观察到EPT相关的MD变化存在较大的个体间差异,但很少有研究调查EPT相关MD变化的遗传预测因素。在此,我们评估激素代谢途径基因多态性与女性停止EPT时MD变化之间的关联。
我们收集了女性停止EPT前后的乳腺钼靶片,并对加利福尼亚教师研究(CTS)的284名非西班牙裔白人参与者的30个激素代谢途径基因中的405个标签单核苷酸多态性(SNP)进行了基因分型。在停止EPT后进行乳腺钼靶检查时,参与者年龄在49至71岁之间。我们使用计算机辅助方法评估MD百分比。MD变化通过从“EPT治疗中”(即基线)乳腺钼靶片的MD中减去“停止EPT”乳腺钼靶片的MD来计算。使用线性回归分析来研究SNP与MD变化之间的关联,并对基线“EPT治疗中”的MD、基线乳腺钼靶检查时的年龄和体重指数(BMI)以及两次乳腺钼靶检查之间的时间间隔和BMI变化进行了调整。使用自适应秩截断乘积(ARTP)检验获得总体途径和基因水平的汇总结果。我们计算了“经相关检验调整的P值(P(ACT))”以考虑基因内的多重检验。
在溶质载体有机阴离子转运体家族1成员B1(SLCO1B1)中的rs7489119和雄激素硫酸酯酶(ARSC)中的rs5933863观察到最强的关联。SLCO1B1和ARSC分别参与EPT雌激素代谢物的排泄和激活。rs7489119的每个次要等位基因使停止治疗后的MD变化减少4.2%(P = 0.0008;P(ACT) = 0.018),rs5933863的每个次要等位基因使MD变化增加1.9%(P = 0.013;P(ACT) = 0.025)。当我们进一步使用Bonferroni校正来考虑测试基因数量时,这些单个SNP关联未达到统计学显著性。途径水平汇总的ARTP P值无统计学意义。
这项对停止EPT者的纵向研究数据表明,两个激素代谢途径基因SLCO1B1和ARSC中的基因变异可能与女性停止使用EPT后的MD变化有关。需要更大规模的纵向研究来证实我们的发现。