Associations of Metabolomic Predictors of Fat Amount and Distribution with Ca

项目总结(见说明)： 值得注意的是，健康、经常运动的成年人显示出脂肪分布，内脏脂肪水平相对较低--无论他们的总体肥胖程度如何。MEC五个民族之间存在的肥胖水平和类型的异质性提供了一个独特的研究环境，以更好地了解BMI增加和脂肪分布变化的不良影响，包括其与癌症的关系。更具体地说，我们提出了一个普遍的观点：(I)脂肪沉积在不同的身体脂肪储存室具有不同的致癌风险；(Ii)瘦组织和脂肪组织的数量和身体分布在五个民族之间存在差异。 (3)身体脂肪的数量和分布对癌症的促进作用是通过相同的生物学机制实现的，但在MEC的五个族裔群体中，促进癌症的程度不同。在这一观点的背景下，我们建议测试这一假设，即脂肪分布的生物标记物是足够强大的疾病风险生物标记物，它们可以预测不同种族群体的疾病风险。目标： 目的1：开发、优化和验证一系列已定义的嵌套血浆代谢生物标记物谱，以反映整体体脂的相对和绝对脂肪分布。 目的：确定肥胖和体脂分布的全身性代谢组谱与先前开发的热量摄入代谢组谱(S)之间的异同和相互作用，以及膳食中常量营养素组成的类别间和类别内差异。 目的：在嵌套病例对照研究中，使用从MEC(乳房、结肠)和NHS(乳房)前瞻性收集的生物样本，检验这些体脂数量和分布的预测因素与癌症风险的关系。 目的4：将结果与其他项目的结果相结合，以便更好地了解潜在的生物学机制，并更好地预测肥胖表型和癌症风险。 这些数据将通过改进肥胖和癌症风险之间的联系的风险估计来改善公共健康。 这些数据将通过精炼肥胖和癌症之间联系的风险评估来改善公众健康。

PROJECT SUMMARY (See instructions): Notably, healthy, physically active adults display a fat distribution with a relatively low level of visceral adiposity - regardless of their overall adiposity. The heterogeneity in level and types of obesity that exists among the five ethnic groups in the MEC offers a unique research setting to better understand the ill effects of increases in BMI and shifts in distribution of fat, including its relationship to cancer. More specifically, we propose a general viewpoint in which: (i) Fat deposition in various body fat storage compartments carries different risks of cancer; (ii) Amount and body distribution of lean and fat tissue vary across the five ethnic groups and explain some of the observed ethnic differences in cancer risk (particularly for breast and colorectal cancer) observed in the MEC population; (iii) Body fat amount and distribution act on cancer promofion through the same biological mechanisms but to different extents in the five ethnic groups of the MEC. In the context of this view, we propose to test the hypothesis that biomarkers of fat distribution are sufficiently robust biomarkers of disease risk that they predict disease risk across ethnic groups. The Aims: Aim 1: To develop, optimize, and validate a defined series of nested plasma metabolomic biomarker profiles that reflect relative and absolute fat distribution in the context of overall body fat. Aim 2: To determine the similarities, differences, and interactions between the systemic metabolomic profiles of adiposity and body fat distribution and previously developed metabolomic profile(s) for caloric intake and dietary inter- and intra-class differences in macronutrient composition. Aim 3: To test the associations of these predictors of body fat amount and distribution with cancer risk in nested case-control studies using the prospectively collected biospecimens from the MEC (breast, colon) and the NHS (breast). Aim 4: To integrate results with those of the other projects in order to gain a better understanding of the underlying biology and better predict adiposity phenotypes and cancer risk. These data will improve public health by refining risk estimates of the links between adiposity and cancer risk. These data will improve public health by refining risk esfimates of the links between adiposity and cancer