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

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 differ- entially 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 biomark- ers 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 devel- oped by 4 algorithms were compared.

Result: Tyrosine, tryptophan, glycerophospholipid, porphyrin and chlorophyll, sphingolipid metabo- lism, and glycosylphosphatidylinositol-anchor biosynthesis were the lipids and amino acid-related pathways differentially regulated in the type 2 diabetes mellitus patients compared to normal sub- jects and patients with complications. Hydroxyprolyl-leucine and N-palmitoyl threonine were higher in patients; 4,4ʹ-Thiobis-2-butanone, geranyl-hydroxybenzoate, 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 infor- mation on the disease and drug response of a patient. It serves as a potential comprehensive thera- peutic drug monitoring approach to be adopted in the near future for pharmaceutical care.

Cite this article as: Lay Kek T, Salleh Rofiee M, Abdul Ghani R, Aqmar Mohd Nor Hazalin N, Zaki Salleh M. Metabolite biomarkers and predictive model analysis for patients with type 2 diabetes mellitus with and without complications. Endocrinol Res Pract. 2023;27(3):135-147.