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

纵向多组学分析揭示肥胖介导的胰岛素抵抗机制

基本信息

批准号：
9895799
负责人：
TRACEY MCLAUGHLIN
金额：
$ 62.83万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-04-01 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9895799
关键词：
Address Adipose tissue American Biochemical Pathway Biological Biopsy Blood Blood specimen Body Weight Body Weight decreased Body fat Cardiovascular Diseases Cell physiology Cells Characteristics Clinical Complex Data Development Diagnostic Diet Dietary Intervention Disease Environment Epidemic Exhibits Experimental Models Fatty acid glycerol esters Future Gene Proteins Genetic Genome Genomics Health Benefit Human Impairment Individual Infrastructure Insulin Insulin Resistance Intervention Knowledge Link Measurement Measures Mediating Metabolic Metabolic Diseases Metabolic dysfunction Modeling Molecular Molecular Profiling Monitor Morbidity - disease rate Muscle Non-Insulin-Dependent Diabetes Mellitus Obesity Overweight Paper Pathologic Pathway interactions Phenotype Population Portraits Prevalence Prevention Process Proteins Proteome Proteomics Public Health Publications Research Research Project Grants Resistance Process Risk Risk stratification Subgroup Technology Therapeutic Time Tissue Sample Tissues Transcript Weight Weight Gain cytokine experience gene environment interaction genome wide association study genomic profiles human model human subject longitudinal analysis metabolic phenotype metabolome metabolomics microbiome research multiple omics non-diabetic novel novel marker obesity development precision medicine predictive marker prevent protein metabolite recruit response subcutaneous tool transcriptome transcriptomics

Address Adipose tissue American Biochemical Pathway Biological Biopsy Blood Blood specimen Body Weight Body Weight decreased Body fat Cardiovascular Diseases Cell physiology Cells Characteristics Clinical Complex Data Development Diagnostic Diet Dietary Intervention Disease Environment Epidemic Exhibits Experimental Models Fatty acid glycerol esters Future Gene Proteins Genetic Genome Genomics Health Benefit Human Impairment Individual Infrastructure Insulin Insulin Resistance Intervention Knowledge Link Measurement Measures Mediating Metabolic Metabolic Diseases Metabolic dysfunction Modeling Molecular Molecular Profiling Monitor Morbidity - disease rate Muscle Non-Insulin-Dependent Diabetes Mellitus Obesity Overweight Paper Pathologic Pathway interactions Phenotype Population Portraits Prevalence Prevention Process Proteins Proteome Proteomics Public Health Publications Research Research Project Grants Resistance Process Risk Risk stratification Subgroup Technology Therapeutic Time Tissue Sample Tissues Transcript Weight Weight Gain cytokine experience gene environment interaction genome wide association study genomic profiles human model human subject longitudinal analysis metabolic phenotype metabolome metabolomics microbiome research multiple omics non-diabetic novel novel marker obesity development precision medicine predictive marker prevent protein metabolite recruit response subcutaneous tool transcriptome transcriptomics

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项目摘要

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.

抽象的超重/肥胖是大多数美国人的重要流行病，其中一些人发展阻力（IR），有助于2型糖尿病（T2DM）和心血管的发展疾病（CVD）。仍然是一个关键的问题，为什么有些人体重适度升高IR 其他人则可以维持大量的多余体内脂肪，同时保持胰岛素敏感（IS）。先前的研究使用GWAS未能完全解释这一现象。然而，严格关注遗传学，错过了饮食和环境对细胞功能的复杂和终身影响。为了获得更完整的图片 IR过程，我们的小组提议采用前所未有的深度的纵向多摩变策略使用人类模型进行实验发现与IR发展相关的分子变化体重增加，然后体重减轻。我们将测量生物分子（转录本，代谢物，蛋白质和细胞因子）在血液，脂肪组织和肌肉中：1）在基线时，将IR与个体进行了比较； 2）峰值重量与基线和减肥后相比； 3）比较那些经历的人的变化体重增加的代谢下降与表现出相似体重增加的代谢耐受性的人。我们假设通过纵向分析的这种动态干预，我们可以阐明生物分子和响应体重增加和损失的途径，尤其是与IR独特相关的途径独立于体重或体重增加。这些只有我们小组才能生成的高度新颖数据将显着扩展我们对表征和预测发展的生物分子和途径的理解 IR状态，为增强风险分层的新标记（为了减轻体重增加）和对预防肥胖引起的代谢疾病产生重大影响的治疗策略。