Population-Based Reference Ranges for Estradiol and Estrone in Men

描述（由申请人提供）：雌二醇17？（E2）和雌酮（E1）-人类中两种最丰富的雌激素-在男性健康和疾病中的作用仍然知之甚少。虽然低和高E2水平都与男性的不良健康结果有关，但对E1和E2直接免疫测定准确性的担忧使现有数据的解释变得模糊。尽管E1在循环中与E2一样丰富，但人们对E1与男性结局的关系知之甚少。总E1和游离E2水平的参考限值对于临床决策至关重要。在缺乏严格推导的参考范围的情况下，将总和游离E1和E2水平划分为正常值、低值或高值充满了错误分类的重大风险。来自波士顿大学、心脏病研究（FHS）、欧洲男性衰老研究（EMAS）、男性骨质疏松性骨折研究（MrOS）、协和健康与男性衰老项目（CHAMP）、马约诊所、和疾病控制中心是生成参考限值的总和游离E1和E2水平的健康参考样本的年轻男子，FHS第三代（Gen 3）队列。我们还将生成年龄调整的参考限值（Z评分方法）。将使用液相色谱串联质谱法（LC-MS/MS）测量总E1和E2水平，并计算游离E1和E2。FHS Gen 3中生成的参考限值将应用于4个地理位置不同的队列中的男性- FHS Gen 3 + FHS后代队列（Gen 2）（FHS广泛样本）、EMAS、MrOS和CHAMP队列。我们将把总的和游离的E1和E2水平与糖尿病、心血管疾病、骨矿物质密度、身体功能和性症状联系起来，调整年龄、体重指数、腰围、血压、吸烟、血脂、葡萄糖、饮食和体育活动。我们将评估E1和E2水平的遗传性， 评估遗传效应对E1和E2水平个体间变异的贡献。基线总E1和游离E2以及E2和E1的纵向变化将与纵向随访期间不良结局的发生率相关（主要：死亡率、糖尿病、心血管疾病事件~次要：功能限制和残疾进展、骨质疏松症、非椎骨骨折）。将男性划分为E1和E2水平正常、低和高的人群的建议将以考虑其统计分布和结果与参考限值不同程度偏差的相关性为指导。该提案将促进我们对男性E1和E2水平作用的理解，并为执业医生解释E1和E2水平提供标准化框架。该项目具有很高的成本效益，因为它利用了四个特征良好的群组的现有成果数据。使用LC-MS/MS分析、标准校准品和基于社区的参考样本、4个地理上不同的验证队列的可用性以及跨学科的研究者团队将最大限度地提高成功的机会。

DESCRIPTION (provided by applicant): The role of estradiol 17¿ (E2) and estrone (E1) - the two most abundant estrogens in humans - in men's health and disease remains poorly understood. Although both low and high E2 levels have been associated with adverse health outcomes in men, concerns about the accuracy of direct immunoassays for E1 and E2 has clouded interpretation of available data. Even though E1 is as abundant in circulation as E2, little is known about the association of E1 with outcomes in men. Reference limits for total and free E1 and E2 levels are essential for clinical decision making. In the absence of rigorously-derived reference ranges, the partitioning of total and free E1 and E2 levels into normal, low, or high values has been fraught with substantial risk of misclassification. The objective of this collaboration among investigators from Boston University, the Framingham Heart Study (FHS), the European Male Aging Study (EMAS), the Osteoporotic Fractures in Men Study (MrOS), the Concord Health and Ageing in Men Project (CHAMP), the Mayo Clinic, and the Centers for Disease Control is to generate reference limits for total and free E1 and E2 levels in a healthy reference sample of young men in the FHS third generation (Gen 3) cohort. We also will generate age-adjusted reference limits (Z-score approach). Total E1 and E2 levels will be measured using liquid chromatography tandem mass spectrometry (LC-MS/MS) and free E1 and E2 will be calculated. Reference limits generated in FHS Gen 3 will be applied to men in 4 geographically distinct cohorts - FHS Gen 3 plus FHS Offspring cohort (Gen 2) (FHS broad sample), EMAS, MrOS, and CHAMP cohorts. We will relate total and free E1 and E2 levels to diabetes, cardiovascular disease, bone mineral density, physical function, and sexual symptoms, adjusting for age, body mass index, waist circumference, blood pressure, smoking, lipids, glucose, diet and physical activity. We will assess the heritability of E1 and E2 levels to evaluate the contribution of genetic effects on inter-individual variability in E1 and E2 levels. Baseline total and free E1 and E2 as well as longitudinal changes in E2 and E1 will be related to the incidence of adverse outcomes (primary: mortality, diabetes mellitus, cardiovascular disease events~ secondary: progression of functional limitations and disability, osteoporosis, nonvertebral fractures) during longitudinal follow-up. The recommendations for partitioning of men into those with normal, low and high E1 and E2 levels will be guided by considerations of their statistical distribution and the association of outcomes with varying degree of deviations from the reference limits. The proposal will advance our understanding of the role of E1 and E2 levels in men and provide a standardized framework for the interpretation of E1 and E2 levels by practicing physicians. The project is highly cost effective because it leverages existing outcomes data from four well characterized cohorts. The use of LC-MS/MS assay, a standard calibrator, and a community-based reference sample, the availability of 4 geographically distinct validation cohorts, and an inter-disciplinary team of investigators would maximize the chances of success.