Metabolomics in diabetes, a review

Ann Med. 2016;48(1-2):89-102. doi: 10.3109/07853890.2015.1137630. Epub 2016 Jan 30.

Abstract

Metabolomics is a promising approach for the identification of chemical compounds that serve for early detection, diagnosis, prediction of therapeutic response and prognosis of disease. Moreover, metabolomics has shown to increase the diagnostic threshold and prediction of type 2 diabetes. Evidence suggests that branched-chain amino acids, acylcarnitines and aromatic amino acids may play an early role on insulin resistance, exposing defects on amino acid metabolism, β-oxidation, and tricarboxylic acid cycle. This review aims to provide a panoramic view of the metabolic shifts that antecede or follow type 2 diabetes. Key messages BCAAs, AAAs and acylcarnitines are strongly associated with early insulin resistance. Diabetes risk prediction has been improved when adding metabolomic markers of dysglycemia to standard clinical and biochemical factors.

Keywords: Acylcarnitines; aromatic amino acids; branched-chain amino acids; diabetes; dysglycemia; insulin resistance; mass spectrometry; metabolomics; nuclear magnetic resonance spectroscopy; obesity.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Amino Acids, Branched-Chain / blood
  • Animals
  • Biomarkers / metabolism*
  • Carnitine / analogs & derivatives
  • Carnitine / blood
  • Diabetes Mellitus, Type 2 / blood
  • Diabetes Mellitus, Type 2 / diagnosis
  • Diabetes Mellitus, Type 2 / metabolism*
  • Humans
  • Insulin Resistance / physiology
  • Metabolomics / methods
  • Obesity / blood
  • Obesity / complications
  • Predictive Value of Tests

Substances

  • Amino Acids, Branched-Chain
  • Biomarkers
  • acylcarnitine
  • Carnitine