Elevated Metabolites Signal Diabetes Risk

Increased levels of amino acids in the blood can identify individuals at risk of developing diabetes mellitus type 2.

Amino acids, amines and other polar metabolites can be profiled in baseline blood specimens by liquid chromatography–tandem mass spectrometry (LC-MS), and correlated with disease progression.

A team led by scientists at Massachusetts General Hospital (MGH; Boston, MA, USA) recently found that the levels of five amino acids, identified by LC-MS, indicated increased diabetes risk in a general population. Out of 2,400 normoglycemic participants who entered the study in 1991 and 1995, 201 developed type 2 diabetes during the subsequent 12 years. Using the baseline blood samples, the research team measured levels of 61 metabolites in 189 participants who later developed diabetes and 189 diabetes free individuals, who were matched for age, sex, and diabetes risk factors.

The analysis found that elevations in five amino acids: isoleucine, leucine, valine, tyrosine, and phenylalanine, were significantly associated with the later development of type 2 diabetes and could also differentiate, among individuals with traditional risk factors such as obesity, and those most likely to actually develop diabetes. The investigators found that measuring combinations of several metabolites, as opposed to a single amino acid, improved risk prediction. Overall, in individuals closely matched for traditional risk factors for type 2 diabetes, those with the highest levels of the three most predictive amino acids had a four to five times greater risk of developing diabetes than did those with the lowest levels. These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment.

Thomas J. Wang, MD, the lead author of the study, said, "These findings could provide insight into metabolic pathways that are altered very early in the process leading to diabetes. They also raise the possibility that, in selected individuals, these measurements could identify those at highest risk of developing diabetes so that early preventive measures could be instituted." The study was published online on March 20, 2011, in Nature Medicine.

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