Longitudinal Multi-Omic Profiles to Reveal Mechanisms of Obesity-Mediated Insulin Resistance

摘要 超重/肥胖是一种严重的流行病，困扰着大多数美国人，其中一些人会产生胰岛素 抵抗力(IR)，导致2型糖尿病(T2 DM)和心血管疾病的发生 疾病(CVD)。为什么有些人会在体重适度升高时出现胰岛素抵抗，这仍然是一个关键问题。 而其他人可以在保持胰岛素敏感(IS)的同时维持大量过量的体脂。先前的研究 使用GWA未能完全解释这一现象。然而，严格关注遗传学，却错过了 饮食和环境对细胞功能的复杂和终生影响。为了更全面地了解 在IR过程中，我们小组建议将前所未有的深度的纵向多组学战略应用于 利用人体模型发现与胰岛素抵抗发展相关的分子变化 体重增加，然后是体重下降。我们将测量生物分子(转录本、代谢物、蛋白质和 血液、脂肪组织和肌肉中的细胞因子)：1)比较IR和IS个体的基线；2)峰值体重 与基线和减肥后相比；3)比较那些经历了 与那些表现出相似体重增加的代谢耐受性的人相比，体重增加时代谢下降。我们 假设通过这种动态干预和纵向分析，我们可以阐明生物分子和 随着体重的增加和减少而改变的途径，特别是与IR唯一相关的途径 与体重或体重增加无关。这些只有我们的团队才能生成的高度新颖的数据将 显著扩展我们对表征和预测发育的生物分子和途径的理解 IR状态，为增强的风险分层(体重增加的不良反应)提供了新的标志 有可能对预防肥胖引起的代谢性疾病产生重大影响的治疗策略。

ABSTRACT Overweight/obesity is a significant epidemic afflicting a majority of Americans, some of whom develop insulin resistance (IR), which contributes to the development of type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). It remains a critical question why some individuals develop IR at modestly elevated body weight and others can sustain substantial amounts of excess body fat while remaining insulin sensitive (IS). Prior studies using GWAS have failed to fully explain this phenomenon. Focusing strictly on genetics, however, misses the complex and lifelong effects of diet and environment on cellular function. To gain a more complete picture of the IR process, our group proposes to apply a longitudinal multi-omic strategy of unprecedented depth for the discovery of molecular changes associated with the development of IR using a human model for experimental weight gain, followed by weight loss. We will measure biomolecules (transcripts, metabolites, proteins and cytokines) in blood, adipose tissue, and muscle: 1) at baseline comparing IR to IS Individuals; 2) at peak weight as compared to baseline and post weight loss; 3) compare changes in those individuals who experience metabolic decline with weight gain vs those who exhibit metabolic tolerance of similar weight gain. We hypothesize that through this dynamic intervention with longitudinal analysis we can elucidate biomolecules and pathways that change in response to weight gain and loss and specifically that uniquely associate with IR independent of weight or weight gain. These highly novel data that can be generated only by our group will significantly expand our understanding of biomolecules and pathways that characterize and predict development of the IR state, offering new markers for enhanced risk stratification (for adverse response to weight gain) and therapeutic strategies that have potential for a major impact on preventing obesity-induced metabolic disease.