Metabolite biomarkers and predictive model analysis for patients with Type 2 Diabetes Mellitus with and without complications. Endocrinology Research and Practice, 27. pp. 135-147. ISSN 2822-6135 (2023)
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 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.
| Item Type: | Article |
|---|---|
| Keywords: | Type 2 Diabetes Mellitus (T2DM), LCMS-QTOF, Metabolomics, Ischemic Heart Diseases (IHD), Chronic Kidney Diseases (CKD) |
| Taxonomy: | By Niche > Genome > Human Genome By Niche > Genome > Human Genome Research |
| Local Content Hub: | Niche > Genome |
| Depositing User: | Hazrul Amir Tomyang (Puncak Alam) |
| Date Deposited: | 28 Aug 2025 01:52 |
| Last Modified: | 28 Aug 2025 01:52 |
| Related URLs: |
Actions (login required)
 |
View Item |