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过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代谢中起着重要作用;因此，宿主细菌种群的个体间差异可能是雌激素暴露和最终乳腺癌风险的决定因素。大豆异黄酮到雌马酚的结肠微菌群转化是独特的肠道细菌种群的生物标志物。不管大豆摄入量如何，有能力产生雌马酚的女性具有与乳腺癌风险较低相关的激素特征。只有大约三分之一的人具有能够产生雌马酚的尚未被鉴定的细菌，并且雌马酚生产者状态可以很容易地从3天大豆挑战后收集的尿液样本中确定。我们假设，生产雌马酚的女性累积暴露于雌激素的程度较低。我们建议检查雌马酚生产状态和累积雌激素暴露（乳房和骨密度），选定的类固醇激素和SHBG，以及2-羟基雌酮：16 α-羟基雌酮（2-OHE 1：16 α-OHE 1）比的标志物之间的关系。作为次要目标，我们将研究密度和雌激素措施之间的关联，并探讨饮食和其他暴露对雌马酚生产者表型的影响。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，在过去一年中接受过乳房X线检查。在GHC，乳房X线照片根据美国放射学会乳房成像和数据报告系统（BI-RADS）分为密度类别。我们将在BI-RADS组中招募250名女性：1和2合并，3和4。将收集关于一般健康、人口统计学、饮食摄入、体力活动、生殖史和风险因素的数据。在3天的大豆挑战后，女性将在第四天收集第一次排尿的尿液用于分析雌马酚。每个女性都将被归类为雌马酚生产者或非生产者。其中150名妇女还将被邀请到诊所就诊，通过DEXA测量她们的髋部和脊柱骨密度，并提供用于类固醇激素分析的血液样本和用于2-OHE 1和16 α-OHE 1分析的点尿。将通过雌马酚生产者状态检查乳房密度、骨密度、类固醇激素、SHBG和2-OHEI：16 α-OHE 1的差异。此外，我们还将评估雌马酚的产生是否能预测乳腺密度、骨密度、类固醇激素、SHBG和2-OHE 1：16 ct-OHE 1的差异，而不依赖于与这些指标相关的其他因素。如果雌马酚生产者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.