Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines, and other polar metabolites were profiled in baseline specimens using liquid chromatography-tandem mass spectrometry. Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly-significant associations with future diabetes: isoleucine, leucine, valine, tyrosine, and phenylalanine. A combination of three amino acids predicted future diabetes (>5-fold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings 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.
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