Validated Biomarkers for Primary Macronutrient Balance

描述（由申请人提供）：本申请涉及广泛的挑战领域（03）生物标志物的发现和验证以及特定的挑战主题，03- es -101新的暴露评估方法的验证。在西方社会中，饮食宏量营养素的次优选择可以说是个人生活的主要环境压力因素。众所周知，准确评估大量人群的摄入量存在困难，这使得揭示这种相互关系的细节变得复杂。我们在NIEHS/NIH基因与环境倡议暴露生物学计划的生物反应指标部分的工作重点是开发特定类别脂肪（例如，饱和脂肪，反式脂肪，多不饱和脂肪）和碳水化合物（不同的血糖指数）的代谢组学特征，包括在护士健康研究I （NHS）中测试生物标志物，这是一个大的，特征明确的人群。饮食宏量营养素选择的一个独特但相关的组成部分是主要营养素在脂肪、碳水化合物和蛋白质之间的分布。一项名为OMNIHEART的研究独特地提供了生成和验证这些宏量营养素的生物标志物的能力。OMNIHEART是一项大型（164人）完全控制的喂养研究，其中每个人轮流进行3次饮食（每次6周）。我们目前的特定设计利用了现有的大型电子数据集（3500/2000人的血浆代谢组学/蛋白质组学），这些数据集是我们在NIH的其他支持下从NHS样本中生成的。提出的互惠设计是复杂的，但被选择是因为它最优地利用了这两种资源（NHS， OMNIHEART）。本研究的目的是生成初级宏量营养素平衡的有效剖面。目标是：目标1通过回顾性挖掘NHS内生成的现有数据集，确定主要宏量营养素组成对血浆代谢组和蛋白质组的影响；目标2：使用OMNIHEART的样本，验证主要宏量营养素组成对目标1中测定的血浆代谢组和蛋白质组的影响；目标3：确定主要宏量营养素组成对OMNIHEART中血浆代谢组和蛋白质组的影响；目标4：为了验证Aim 3中确定的血浆代谢组和蛋白质组的主要宏量营养素组成概况，并使用NHS Aim 5的现有数据：为了确定在护士健康研究中嵌套的先前病例对照研究中，对反映主要宏量营养素的资料的坚持程度可以预测II型糖尿病（A部分）和乳腺癌（B部分），拟议的研究直接响应RFA （RC1, 03-ES-101，新暴露评估方法的验证）和进一步的NIH关注健康和早期干预而不是晚期疾病的总体目标。该实验室完全有能力在两年内完成拟议的研究。

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (03) Biomarker Discovery and Validation and specific challenge topic, 03-ES-101 Validation of new exposure assessment methodologies Suboptimal dietary macronutrient choices are arguably the major environmental stressor in individuals living in Western societies. Unraveling the specifics of this inter-relationship has been complicated by the well known difficulty in accurately assessing intake in a large human population. Our work within the Biological Response Indicators component of the Exposure Biology Program of the NIEHS/NIH Genes and Environment Initiative has focused on the development of a metabolomic signature of class-specific fats (eg, saturated, trans, polyunsaturated) and carbohydrates (differing glycemic index), including testing the biomarkers within the Nurses' Health Study I (NHS), a large, well-characterized human population. A distinct, but related component of dietary macronutrient choice is the distribution of the major nutrient between fat, carbohydrate, and protein. One study, OMNIHEART, uniquely offers the ability to generate and validate biomarkers for these macronutrients. OMNIHEART was a large (164 people), completely controlled feeding study in which each individual was rotated through 3 diets (6 weeks each). Our current specific design takes advantage of existing large electronic datasets (plasma metabolomics/proteomics on 3500/2000 people) that we have generated/are generating from the NHS samples under other NIH support. The reciprocal design proposed is complex but was chosen because it optimally leverages both these two resources (NHS, OMNIHEART). The goal of this study is to generate validated profiles for primary macronutrient balance. The Aims are: Aim 1 To determine the effects of primary macronutrient composition on the plasma metabolome and proteome by retrospectively mining existing datasets generated within NHS Aim 2: To validate the effects of primary macronutrient composition on the plasma metabolome and proteome determined in Aim 1 using the samples from OMNIHEART Aim 3: To determine the effects of primary macronutrient composition on the plasma metabolome and proteome in OMNIHEART Aim 4: To validate the profiles of primary macronutrient composition on the plasma metabolome and proteome determined developed in Aim 3 with existing data from NHS Aim 5: To determine the extent to which adherence to profiles reflecting primary macronutrients predict type II diabetes (part A) and breast cancer (part B) in previously profiled case control studies nested within the Nurses' Health Study The proposed studies are directly responsive to the RFA (RC1, 03-ES-101, Validation of new exposure assessment methodologies) and further general NIH goals of focusing on health and early interventions rather than late stage disease. The proposed study is well within the capacity of the lab to complete within 2 years. PUBLIC HEALTH RELEVANCE: Suboptimal dietary macronutrient choices are arguably the major environmental stressor in individuals living in Western societies. We have been studying the effect of overall caloric intake on chronic disease. We now propose to identify biomarkers that can be used in epidemiological studies to best understand the role of differential intake of protein, fat, and carbohydrate in chronic disease.