Breast and Bone Density: Impact of Colonic Environment

描述(由申请人提供)：女性一生中暴露于雌激素较多会增加患乳腺癌的风险。在肠道中，微生物区系在雌激素的新陈代谢中起着重要作用；因此，宿主细菌种群的个体差异可能是雌激素暴露和最终乳腺癌风险的决定因素。大肠微花将大豆异黄酮型大豆苷元转化为马酚是一种独特的肠道细菌种群的生物标志物。不考虑大豆摄入量，有能力产生马醇的女性的荷尔蒙特征与较低的乳腺癌风险有关。只有大约三分之一的人拥有尚未鉴定的能够产生马儿酚的细菌，从为期3天的大豆挑战后收集的尿样中可以很容易地确定马儿酚生产者的身份。我们假设，产生雌马素的女性累积接触雌激素的几率较低。我们建议研究雌马素产生状态与累积雌激素暴露的标记物(乳房和骨密度)、选定的类固醇激素和SHBG以及2-羟雌酮：16α-羟雌酮(2-OHE1：16α-OHE1)比率之间的关系。作为次要目标，我们将检查密度和雌激素指标之间的关联，并探索饮食和其他暴露对马匹生产者表型的影响。我们将从团体健康合作社(GHC)招募750名健康的绝经前志愿者，年龄在40-45岁之间，并在过去一年中进行过乳房X光检查。在GHC，根据美国放射乳房成像和数据报告系统(BI-RADS)将乳房X光检查分为密度类别。我们将在BI-RADS组中招募250名女性：1组和2组，3组和4组。我们将收集有关一般健康、人口统计、饮食摄入量、体力活动、生育史和风险因素的数据。在为期三天的大豆挑战之后，女性将在第四天收集第一次排空的尿液，用于马儿的分析。每名女性都将被归类为马术制作人或非制片人。其中150名女性还将被邀请到诊所就诊，用DEXA测量她们的髋骨和脊柱骨密度，并为类固醇激素分析提供血液样本，为2-OHE1和16α-OHE1分析提供现场尿样。将检查乳房密度、骨密度、类固醇激素、SHBG和2-OHEI：16α-OHE1之间的差异。此外，我们将独立于与这些测量相关的其他因素，评估等量排泄量是否可以预测乳房密度、骨密度、类固醇激素、SHBG和2-OHE 1：16CT-OHE 1的差异。如果等激素产生表型可以预测累积雌激素暴露/代谢的差异，它可能作为乳腺癌风险的早期标志。

DESCRIPTION (provided by applicant): Greater exposure to estrogen throughout a woman's lifetime increases her risk of developing breast cancer. In the gut, microflora play a significant role in the metabolism of estrogens; therefore, inter-individual differences in host bacterial populations may be a determinant of estrogen exposure and ultimately of breast cancer risk. Colonic microfloral conversion of the soy isoflavone daidzein to equol is a biomarker of a unique intestinal bacterial population. Irrespective of soy intake, women with the capacity to produce equol have hormonal profiles associated with a lower risk of breast cancer. Only about a third of individuals have the yet-to-be-identified bacteria capable of producing equol, and equol-producer status can be determined readily from a urine sample collected after a 3-day soy challenge. We postulate that women who are equol-producers have lower cumulative exposure to estrogens. We propose to examine relationships between equol-producer status and markers of cumulative estrogen exposure (breast and bone densities), selected steroid hormones and SHBG, and the 2-hydroxyestrone: 16alpha-hydroxyestrone (2-OHE1:16alpha-OHE 1) ratio. As secondary aims we will examine associations between the density and estrogen measures, and explore the impact of diet and other exposures on equol-producer phenotype. We will recruit 750 healthy, premenopausal volunteers from within Group Health Cooperative (GHC), aged 40-45 years, and who have had a screening mammogram in the past year. At GHC, mammograms are classified into categories of density according to the American College of Radiology Breast Imaging and Data Reporting System (BI-RADS). We will recruit 250 women each within BI-RADS Groups: 1 and 2 combined, 3, and 4. Data on general health, demographics, dietary intake, physical activity, reproductive history and risk factors will be collected. After a 3-day soy challenge, women will collect a first-void urine on the fourth day for analysis of equol. Each woman will be classified as an equol-producer or nonproducer. 150 of the women will also be invited for a clinic visit to have their hip and spine bone densities measured by DEXA, and to provide a blood sample for steroid hormone analysis and a spot urine for 2-OHE1 and 16alpha- OHE1 analysis. Differences in breast density, bone density, steroid hormones, SHBG, and 2-OHEI:16alpha-OHE1 by equol producer status will be examined. In addition, we will evaluate whether equol production predicts differences in breast density, bone density, steroid hormones, SHBG, and 2-OHE 1:16ct-OHE 1 independently of other factors associated with these measures. If equol-producer phenotype can predict differences in cumulative estrogen exposure / metabolism, it may serve as an early marker of breast cancer risk.