Journal of Clinical Medicine · 2019 · 69 citations · 50 references
Life SciencesBiochemistryDiabetologyMetabolic RegulationMetabolomicsDiabetes MellitusDiabetes Mellitus BiochemistryMetabolite ExtractionMetabolite ProfilingMetabolomics Data AnalysisNuclear Magnetic Resonance MetabolomicsDisease Biomarker DiscoveryDisease Metabolite ProfilingMetabolic Signature DiscoveryMetabolomic Biomarker DiscoveryMetabolomic BiomarkersMultivariate Analysis Of Metabolite DataNuclear Magnetic Resonance Spectroscopy-based Metabolite ProfilingSerum Biomarkers
Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia associated with alterations in carbohydrate, lipid, and protein metabolism. The prognosis of T2DM patients is highly dependent on the development of complications, and therefore the identification of biomarkers of T2DM progression, with minimally invasive techniques, is a huge need. In the present study, we applied a 1H-Nuclear Magnetic Resonance (1H-NMR)-based metabolomic approach coupled with multivariate data analysis to identify serum metabolite profiles associated with T2DM development and progression. To perform this, we compared the serum metabolome of non-diabetic subjects, treatment-naïve non-complicated T2DM patients, and T2DM patients with complications in insulin monotherapy. Our analysis revealed a significant reduction of alanine, glutamine, glutamate, leucine, lysine, methionine, tyrosine, and phenylalanine in T2DM patients with respect to non-diabetic subjects. Moreover, isoleucine, leucine, lysine, tyrosine, and valine levels distinguished complicated patients from patients without complications. Overall, the metabolic pathway analysis suggested that branched-chain amino acid (BCAA) metabolism is significantly compromised in T2DM patients with complications, while perturbation in the metabolism of gluconeogenic amino acids other than BCAAs characterizes both early and advanced T2DM stages. In conclusion, we identified a metabolic serum signature associated with T2DM stages. These data could be integrated with clinical characteristics to build a composite T2DM/complications risk score to be validated in a prospective cohort.
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