Abstract
Metabolic diseases present particular difficulty for clinicians because they are often present for years before becoming clinically apparent. We investigated whether metabolite profiles can predict the development of diabetes in the Framingham Heart Study. Five branched-chain and aromatic amino acids had highly-significant associations with future diabetes, while a combination of three amino acids strongly predicted future diabetes by up to 12 years (>5-fold increased risk for individuals in top quartile). Our findings in over 1100 individuals underscore the potential importance of amino acid metabolism early in the pathogenesis of diabetes, and suggest that amino acid profiles could aid in diabetes risk assessment. In a “lipidomics” analysis from the same cohorts, we found that lipids of relatively lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. To explore potential mechanisms that modulate the distribution of plasma lipids, we also performed lipid profiling in the setting of perturbational experiments in MGH patients, including oral glucose tolerance testing, pharmacologic interventions such and acute exercise testing. Lipids associated with increased diabetes risk (particularly triacylglycerols or TAGs) fell in response to insulin action; in turn, these TAGs were elevated in the setting of insulin resistance. These studies identify a novel relationship between lipid acyl-chain content and diabetes risk, demonstrate how lipidomic profiling could also aid in clinical risk assessment beyond standard risk factors, and highlight enzymes including specific lipid elongases and desaturases for further exploration in the context of diabetes.