Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach

Abstract

Using a nontargeted metabolomics approach of 447 fasting plasma metabolites, we searched for novel molecular markers that arise before and after hyperglycemia in a large population-based cohort of 2,204 females (115 type 2 diabetic [T2D] case subjects, 192 individuals with impaired fasting glucose [IFG], and 1,897 control subjects) from TwinsUK. Forty-two metabolites from three major fuel sources (carbohydrates, lipids, and proteins) were found to significantly correlate with T2D after adjusting for multiple testing; of these, 22 were previously reported as associated with T2D or insulin resistance. Fourteen metabolites were found to be associated with IFG. Among the metabolites identified, the branched-chain keto-acid metabolite 3-methyl-2-oxovalerate was the strongest predictive biomarker for IFG after glucose (odds ratio [OR] 1.65 [95% CI 1.39-1.95], P = 8.46 × 10(-9)) and was moderately heritable (h(2) = 0.20). The association was replicated in an independent population (n = 720, OR 1.68 [ 1.34-2.11], P = 6.52 × 10(-6)) and validated in 189 twins with urine metabolomics taken at the same time as plasma (OR 1.87 [1.27-2.75], P = 1 × 10(-3)). Results confirm an important role for catabolism of branched-chain amino acids in T2D and IFG. In conclusion, this T2D-IFG biomarker study has surveyed the broadest panel of nontargeted metabolites to date, revealing both novel and known associated metabolites and providing potential novel targets for clinical prediction and a deeper understanding of causal mechanisms.

FIG. 1.

Metabolites associated with T2D case-control status (A) and with IFG control status (B). Each metabolite super-pathway is represented in a different color.

FIG. 2.

BCAA catabolism. The three BCAAs are first converted to BCKAs and eventually lead to the production of C3 and C5 acylcarnitines.