Metabolomic predictors of insulin resistance and diabetes

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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.