Metabolite Profiles and Mammographic Density in Premenopausal Women

绝经前女性的代谢物概况和乳房 X 光密度

基本信息

批准号：
10194422
负责人：
Adetunji T Toriola
金额：
$ 36.03万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10194422
关键词：
Address African American Age Amino Acids Biological Biological Markers Blood Blood specimen Breast Breast Cancer Prevention Breast Cancer Risk Factor Cancer Etiology Case-Control Studies Chemoprevention Coupled Data Development Diagnosis Disease Enrollment Ensure Etiology Fasting Future Health Incidence Lipids Malignant Neoplasms Mammographic Density Mammography Measures Mediating Modeling Molecular Molecular Weight Not Hispanic or Latino Nucleotides Obesity Participant Pathway interactions Performance Population Heterogeneity Premenopause Primary Prevention Questionnaires Race Reproducibility of Results Research Research Design Risk Source Surrogate Markers Techniques Time Tissues Translating Universities Validation Variant Washington Woman aged base biological systems breast density density follow-up innovation insight malignant breast neoplasm medical schools metabolome metabolomics novel novel strategies real world application recruit routine screening screening secondary analysis study population success tool young woman

项目摘要

ABSTRACT In 2019, approximately 268,600 women in the US will be diagnosed with breast cancer, making it the leading cause of cancer in women. About 25% of these cases occurred in premenopausal women. The annual incidence of breast cancer among women under age 50 has been increasing slowly since the mid-1990s, in contrast to what is observed in women aged over 50 years, where the incidence has remained stable over time. This persistent increase in the incidence among younger women indicates that new approaches to primary prevention in premenopausal women are needed. Mammographic breast density is one of the strongest risk factors for breast cancer, especially in premenopausal women, where an estimated 39% of breast cancer cases is attributable to having dense breasts. A decrease in breast density leads to a reduction in breast cancer incidence. Nevertheless, the molecular basis of mammographic breast density and the mechanisms through which dense breast increases breast cancer risk are poorly understood. A greater understanding of these mechanisms is crucial, and will uncover new biological pathways and actionable biomarkers that can be targeted to prevent breast cancer development. Metabolomics is a promising tool to provide novel insights into disease etiology, biological mechanisms, and pathways. Metabolomics has, however, not been applied to study mammographic breast density. Our pilot analyses show differences in metabolite levels between women with fatty breasts compared to women with dense breasts. Building on these novel findings, we will apply state-of-the art metabolomics platforms to 1) investigate the metabolome of mammographic breast density in premenopausal women; 2) quantify the variation in mammographic breast density explained by the metabolome; 3) determine whether the metabolome of mammographic breast density predicts breast cancer development in premenopausal women. Our overarching hypothesis is that we will leverage metabolomics to uncover the molecular mechanisms, biological pathways, as well as novel actionable biomarkers that are associated with mammographic breast density in premenopausal women. Our study population will consist of premenopausal women recruited during annual screening mammogram at the Joanne Knight Breast Health Center at the Washington University School of Medicine, St. Louis, MO. Mammographic breast density is quantitatively assessed using Volpara. Fasting blood samples are collected on the same day the women have their mammograms. The women also complete a questionnaire with detailed information on breast cancer risk factors and determinants of mammographic density. In conclusion, we will build on our exciting preliminary data to uncover novel, actionable biomarkers associated with mammographic breast density, and also breast cancer development in premenopausal women. These biomarkers could be targeted in breast cancer prevention in future studies.

抽象的 2019 年，美国约有 268,600 名女性将被诊断出患有乳腺癌，使其成为美国第一大癌症导致女性癌症的原因。其中约 25% 的病例发生在绝经前女性身上。每年一度的自20世纪90年代中期以来，50岁以下女性乳腺癌发病率一直在缓慢上升，与在 50 岁以上女性中观察到的情况相反，50 岁以上女性的发病率多年来一直保持稳定时间。年轻女性发病率的持续增加表明，新的治疗方法绝经前妇女需要进行初级预防。乳房X线摄影乳腺密度是其中之一乳腺癌的最强危险因素，尤其是绝经前女性，估计 39% 乳腺癌病例归因于乳房致密。乳腺密度的降低会导致乳腺密度的降低在乳腺癌的发病率中。尽管如此，乳房X线照相乳腺密度的分子基础和致密乳房增加乳腺癌风险的机制尚不清楚。一个更大的了解这些机制至关重要，并将揭示新的生物学途径和可操作的方法可以靶向预防乳腺癌发展的生物标志物。代谢组学是一个很有前途的工具为疾病病因学、生物学机制和途径提供新的见解。代谢组学有，然而，尚未应用于研究乳房X线照相乳腺密度。我们的试点分析显示了以下方面的差异脂肪乳房女性与致密乳房女性之间的代谢水平。在此基础上新颖的发现，我们将应用最先进的代谢组学平台来 1）研究绝经前妇女的乳房 X 光检查乳腺密度； 2) 量化乳腺X线摄影的变化由代谢组解释的密度； 3) 确定乳房X线摄影的代谢组是否有乳腺密度预测绝经前女性乳腺癌的发展。我们的总体假设是我们将利用代谢组学来揭示分子机制、生物途径以及新的可操作的方法与绝经前女性乳房 X 光检查乳腺密度相关的生物标志物。我们的研究人口将包括在乔安妮年度筛查乳房X光检查期间招募的绝经前妇女密苏里州圣路易斯华盛顿大学医学院奈特乳腺健康中心。乳腺X线摄影使用 Volpara 定量评估乳房密度。当天采集空腹血样妇女们接受了乳房X光检查。这些妇女还完成了一份包含详细信息的调查问卷乳腺癌危险因素和乳房X线照相密度的决定因素。总之，我们将在我们的基础上令人兴奋的初步数据揭示了与乳腺 X 线摄影相关的新颖、可操作的生物标志物密度，以及绝经前妇女乳腺癌的发展。这些生物标志物可以作为目标在未来的研究中预防乳腺癌。