Metabolite Biomarkers and Predictive Model Analysis for Patients with Type 2 Diabetes Mellitus With and Without Complications

Abstract

Objective: Understanding the pathogenesis of type 2 diabetes mellitus including the interaction between the inherent susceptibility, lifestyles, and environment is believed to cast hope to predict, prevent, and personalize cure for type 2 diabetes mellitus and its complications. To identify the differentially expressed metabolites as potential diabetes-associated metabolite biomarkers that identify individuals with and without diabetes. Methods: Sixty-four subjects were recruited to identify the systemic metabolic changes and biomarkers related to type 2 diabetes mellitus, and the related complications (ischemic heart disease and chronic kidney disease) using quadrupole time-of-flight liquid chromatography coupled to mass spectrometry. The top 5 biomarkers were identified, and the prediction accuracies for models developed by 4 algorithms were compared. Result: Tyrosine, tryptophan, glycerophospholipid, porphyrin and chlorophyll, sphingolipid metabolism, and glyco sylph ospha tidyl inosi tol-a nchor biosynthesis were the lipids and amino acid-related pathways differentially regulated in the type 2 diabetes mellitus patients compared to normal subjects and patients with complications. Hydroxyprolyl-leucine and N-palmitoyl threonine were higher in patients; 4,4ʹ- Thiob is-2- butan one, geran yl-hy droxy benzo ate, and Sesamex were higher in patients with chronic kidney disease complications; Asp Glu Trp, Trp Met Met were higher in patients with type 2 diabetes mellitus and ischemic heart disease compared to those normal subjects without risk. Random forest produced a consistently higher accuracy of more than 70% in the prediction for all the comparison groups. Pathways perturbated and biomarkers differentially regulated in individuals with risks or with the existing conditions of type 2 diabetes mellitus and its complications of ischemic heart disease and chronic kidney disease were identified using time-of-flight liquid chromatography coupled to mass spectrometry. Conclusion: Metabolomics is a new emerging field that provides comprehensive phenotypic information on the disease and drug response of a patient. It serves as a potential comprehensive therapeutic drug monitoring approach to be adopted in the near future for pharmaceutical care.