Novel Metabolic Predictors of Diabetes in American Indians

美洲印第安人糖尿病的新代谢预测因子

• 批准号: 9351506
• 负责人: Oliver Fiehn
• 金额: $ 73.23万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9351506
• 关键词: Acids; American Indians; Amino Acids; Analytical Chemistry; Betaine; Bioinformatics; Biological; Biological Assay; Biological Markers; Branched-Chain Amino Acids; Carbohydrates; Carnitine; Caucasians; Ceramides; Choline; Clinical; Cross-Sectional Studies; Data; Data Discovery; Development; Diabetes Mellitus; Emerging Technologies; Epidemiology; Ethnic group; European; Fasting; Food; General Population; Genetic; Goals; Heart; Human; Hydroxyl Radical; Individual; Insulin Resistance; Intervention; Life Style; Link; Lipids; Longitudinal cohort; Longitudinal cohort study; Lysophospholipids; Measures; Mediating; Mediation; Mediator of activation protein; Metabolic; Metabolic Diseases; Metabolic Marker; Metabolic Pathway; Metabolism; Methods; Minority Groups; Multivariate Analysis; Native Americans; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Participant; Pathology; Pathway interactions; Pharmacology; Phospholipids; Plasma; Prevalence; Prevention; Prevention strategy; Prognostic Marker; Regulation; Resources; Risk; Risk Factors; Sampling; Sphingomyelins; Testing; Time; Triglycerides; Visit; Work; acylcarnitine; cohort; combat; design; diabetes risk; fasting glucose; follow-up; genetic makeup; high risk population; interest; metabolic profile; metabolome; metabolomics; microbial; multidisciplinary; novel; pre-clinical; predictive marker; prognostic value; prospective; racial and ethnic; response; small molecule; specific biomarkers; statistics; trimethyloxamine

Project Summary American Indians (AIs) suffer disproportionately from type 2 diabetes (T2D). Discovery of novel mechanistic biomarkers is the key to identify at-risk individuals and to develop effective preventive strategies tailored to this high risk population. In response to PA-12-165, this project leverages the wealth of unique resources collected by the Strong Heart Study (SHS), the largest longitudinal cohort study of American Indians followed over 25 years, to identify sensitive and specific metabolic markers that are predictive of T2D risk at preclinical stages above and over standard clinical factors including obesity, fasting glucose and insulin resistance. Metabolomics is an emerging technology that can simultaneously identify and accurately quantify hundreds to thousands of metabolites in biofluids. Several metabolites, such as BCAAs, acylcarnitines, and lipids, have been associated with T2D, but these results were largely derived from cross-sectional studies in almost exclusively European Caucasians. However, given the genetic regulation of metabolism, metabolites identified in Caucasians may not be generalized to AIs who may have a different genetic make-up. In addition, cross- sectional analysis cannot capture the dynamic trajectory of metabolic changes over time. Moreover, most existing studies measured a list of pre-selected metabolites on a single platform, but given the complexity of the human metabolome and the substantial diversity of metabolites, no single analytical platform can detect all metabolites in a biological sample. We hypothesize that longitudinal changes in plasma metabolites predict T2D risk independent of fasting glucose, insulin resistance (IR) and obesity, and that metabolic profiles of T2D in AIs are similar to, but distinct from, those in Caucasians. Our goal here is to identify novel and sensitive T2D predictors that are specific to AIs beyond classical T2D indicators. To achieve this, we will repeatedly measure concentrations of over 500 metabolites, including BCAAs, carbohydrates, hydroxyl acids, lipids, as well as gut microbial-derived metabolites, in fasting plasma (~5 yr apart) from normoglycemic SHS participants followed >15 years. Putative metabolites will be replicated in an independent longitudinal sample of AIs followed for 10 years. To increase coverage, we will quantify metabolites concentrations on three complementary platforms. Each assay will be performed as a dual 'targeted' and 'untargeted' analyses to provide both hypothesis-driven quantitative data and discovery-driven semi-quantitative data of unidentified metabolites. Unknown compounds will be identified by well-established workflows. Multivariate analyses will be conducted to identify novel T2D predictors above and over standard clinical factors. Our multidisciplinary team consists of experts with complementary expertise in diabetes epidemiology, metabolomics, analytical chemistry, statistics and bioinformatics. Findings of this study will greatly advance our understanding of T2D pathology, and hold promise for reducing or eliminating T2D disparity in AIs, an ethnically important but traditionally understudied minority group suffering from alarmingly high rates of T2D and obesity.

项目摘要 美国印第安人（AIS）因2型糖尿病（T2D）而遭受不成比例的痛苦。发现新颖的机制 生物标志物是识别高危个人并制定量身定制的有效预防策略的关键 高风险人群。为了回应PA-12-165，该项目利用了收集的大量独特资源 通过强大的心脏研究（SHS），美国印第安人的最大纵向队列研究跟踪了25多个 多年，以确定在临床前阶段可预测T2D风险的敏感和特定的代谢标记 在标准的临床因素上方和超越，包括肥胖，禁食葡萄糖和胰岛素抵抗。 代谢组学是一种新兴技术，可以同时识别并准确地量化数百个 生物流体中成千上万的代谢产物。几种代谢物，例如BCAA，酰基肉碱和脂质，具有 与T2D相关，但这些结果在很大程度上源自 独家欧洲高加索人。但是，鉴于代谢的遗传调节，代谢物鉴定出来 在高加索人中，可能不会将可能具有不同基因构成的AIS推广。另外，交叉 截面分析无法捕获代谢变化随时间变化的动态轨迹。而且，大多数 现有研究测量了单个平台上预选的代谢物的列表，但考虑到复杂性 人类代谢组和代谢物的实质多样性，没有一个分析平台可以检测到所有 生物样品中的代谢产物。我们假设血浆代谢物的纵向变化预测 T2D风险独立于禁食葡萄糖，胰岛素抵抗（IR）和肥胖，以及T2D的代谢谱 在AIS中，AIS类似但与高加索人不同。我们的目标是确定新颖和敏感的T2D 超出经典T2D指标的AIS的预测因子。为了实现这一目标，我们将反复 测量500多种代谢物的浓度，包括BCAA，碳水化合物，羟基酸，脂质，AS 以及肠道微生物衍生的代谢产物，在距离正常血糖SHS的禁食等离子体（相距约5年）中 参与者遵循> 15年。假定的代谢物将在独立的纵向样本中复制 AIS随后十年。为了增加覆盖范围，我们将在三个 互补平台。每种测定将作为双重“有针对性”和“未靶向”分析进行。 提供假设驱动的定量数据和发现驱动的未识别的半定量数据 代谢物。未知的化合物将通过建立的工作流识别。多元分析将是 进行的旨在确定上述和超过标准临床因素的新型T2D预测因子。我们的多学科 团队由具有糖尿病流行病学，代谢组学，分析的互补专业知识的专家组成 化学，统计和生物信息学。这项研究的结果将大大提高我们对T2D的理解 病理学，并保持降低或消除AIS中T2D差异的希望，AIS是一个很重要的，但 传统上研究的少数群体遭受了令人震惊的T2D和肥胖率。