Metabolomic predictors of insulin resistance and diabetes

胰岛素抵抗和糖尿病的代谢组预测因子

• 批准号: 10363159
• 负责人: Clary B Clish
• 金额: $ 68.05万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10363159
• 关键词: Acids; Adenosine Monophosphate; African American; Amino Acids; Aromatic Amino Acids; Award; Base Sequence; Biochemical Markers; Biological Markers; Biological Models; Biology; Blood Chemical Analysis; Caucasians; Cells; Cleaved cell; Clinical; Clinical Trials; Collaborations; Communities; Complement; Cytosine; Data; Diabetes Mellitus; Diagnosis; Disease; Enzymes; Ethnic group; Etiology; Fatty acid glycerol esters; Framingham Heart Study; Funding; Future; Genes; Genetic; Glutamates; Glutamine; Glycosylated hemoglobin A; Goals; Health; Heterogeneity; High Prevalence; Human; Hyperglycemia; Imidazole; Incidence; Individual; Insulin; Insulin Resistance; Jackson Heart Study; Laboratories; Life Style; Lipids; Liver; Mass Spectrum Analysis; Mendelian randomization; Meta-Analysis; Metabolic; Metabolic Diseases; Metformin; Muscle; Names; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Pancreas; Participant; Pathway interactions; Phospholipids; Population; Predictive Value of Tests; Propionates; Proteins; Randomized; Recording of previous events; Resources; Risk; Risk Factors; Stratification; Taurine; Techniques; Testing; Time; Tissues; Triglycerides; Variant; Work; base; bioinformatics tool; causal variant; clinical risk; cohort; diabetes prevention program; diet and cancer; disorder risk; experimental study; fasting glucose; genetic architecture; genetic variant; genome wide association study; genome-wide; glucose tolerance; high risk; improved; loss of function; metabolome; metabolomics; multi-ethnic; n-pentanoic acid; new technology; novel; novel strategies; offspring; population based; preventive intervention; risk variant; solute; sphinganine; trait; uptake; whole genome; young adult

Project Summary/Abstract During prior funding periods we have identified and validated novel metabolite profiles of those destined to develop overt T2D. These metabolites were elevated up to 12 years before the onset of T2D in individuals who were initially glucose-tolerant; improved prediction of T2D beyond clinical risk factors and established biochemical markers; and have been validated by other groups. We have now extended our studies to participants in the Jackson Heart Study (JHS), an African American (AA) population with a high prevalence of T2D and its complications. We have also tested the predictive value of metabolites in a key clinical trial, the Diabetes Prevention Program (DPP). Our renewal will leverage critical advances made during the first 12 years of this award. Beyond the named metabolites that we have associated with incident T2D, our recent “whole metabolome” analyses of T2D and related traits in JHS have nominated hundreds of unknown compounds that are uncorrelated with existing biochemical markers for unambiguous identification. We will use novel, in-house mass spectrometry (MS) and bioinformatics tools to unambiguously identify these compounds. To complement the MS work, genome wide association studies (GWAS) and genetic correlation analyses of metabolites and proteins will be used to assign metabolite peaks to pathways (e.g., based on association with known metabolites or with enzymes or solute carriers) that inform their identity. Finally, fine mapping of metabolite-associated genetic variants, co- localization studies with established T2D-associated variants, and Mendelian Randomization experiments will be used to assess causality of metabolite-associated variants for T2D. Putative causal variants that emerge from these analyses will be validated in model systems, using techniques that are well established in our laboratory as well as novel approaches. In Specific Aim 1, we will establish the identity of unknown metabolite peaks that are associated with T2D and related traits, using state-of-the-art mass spectrometry, and informed by GWAS and genetic correlation analyses. In Specific Aim 2, we will refine the genetic architecture of metabolites associated with T2D and related traits (fasting glucose, insulin, lipids, HbA1c, and HOMA-IR) in multi-ethnic cohorts and test whether the likely causal variants are also risk variants for T2D and these same traits. In Specific Aim 3, we will functionally examine key metabolite-related variants in model systems. We will use both gain- and loss-of-function approaches to recapitulate metabolite profiles seen in humans and test for effects on key metabolic functions (e.g., insulin release) in metabolically active tissues (e.g., pancreas). Initial studies will focus on the novel T2D biomarker, ACY-1, a circulating enzyme most highly expressed by the liver which cleaves endogenous N- acetylated amino acids to their free circulating forms. All data from this multi-institutional collaboration will be made publicly available in real time for the entire scientific community.

项目概要/摘要 在之前的资助期间，我们已经确定并验证了那些注定要 在患有 T2D 的个体中，这些代谢物在发病前 12 年内就会升高。 最初对 T2D 的预测优于临床危险因素并建立 生化标记；并已得到其他小组的验证。 杰克逊心脏研究 (JHS) 的参与者是非裔美国人 (AA) 人群，其患病率很高 我们还在一项关键的临床试验中测试了代谢物的预测价值。 糖尿病预防计划（DPP）。 我们的续签将利用该奖项前 12 年取得的重要进展。 我们与 T2D 事件相关的代谢物，我们最近对 T2D 的“全代谢组”分析和 JHS 中的相关性状提名了数百种与现有不相关的未知化合物 我们将使用新颖的内部质谱 (MS) 和生化标记进行明确识别。 生物信息学工具可明确识别这些化合物，以补充全基因组范围内的 MS 工作。 关联研究（GWAS）以及代谢物和蛋白质的遗传相关分析将用于 将代谢物峰分配给途径（例如，基于与已知代谢物或酶或 最后，对代谢物相关的遗传变异进行精细定位，共同确定其身份。 已建立的 T2D 相关变异的本地化研究和孟德尔随机化实验将 用于评估 T2D 代谢物相关变异的因果关系。 这些分析的结果将在模型系统中得到验证，使用我们已经建立的技术 实验室以及新颖的方法。 在具体目标 1 中，我们将确定与 T2D 相关的未知代谢物峰的身份 相关性状，使用最先进的质谱分析，并通过 GWAS 和遗传相关性提供信息 在具体目标 2 中，我们将完善与 T2D 相关的代谢物的遗传结构和 多种族队列中的相关特征（空腹血糖、胰岛素、血脂、HbA1c 和 HOMA-IR），并测试是否 可能的因果变异也是 T2D 的风险变异，在特定目标 3 中，我们将从功能上考虑这些相同的特征。 检查模型系统中与关键代谢物相关的变体，我们将使用功能获得和功能丧失。 概括人类代谢物概况并测试对关键代谢功能影响的方法 （例如，胰岛素释放）在代谢活跃的组织（例如胰腺）中的初步研究将集中在新型 T2D 上。 生物标志物 ACY-1，一种在肝脏中表达最高的循环酶，可裂解内源性 N- 来自该多机构合作的所有数据都将被乙酰化氨基酸转化为游离循环形式。 向整个科学界实时公开。