Discovery and comparison of serum biomarkers for diabetes mellitus and metabolic syndrome based on UPLC-Q-TOF/MS

Abstract

IntroductionDiabetes mellitus (DM) and metabolic syndrome (MetS) are systemic metabolic disorders, which have risk factors for diabetic cardiovascular and cerebral microvascular disease. It is very important to screen the metabolic biomarkers between DM and MetS patients, which can make patients benefit to a greater extent and prevent the occurrence of disease in advance. ObjectivesDiabetes mellitus (DM) and metabolic syndrome are a complex, chronic illness with a pronounced impact on the quality of life of many people. However, understanding the metabolic changes in patients and identifying high-risk individuals is crucial for prevention and disease management strategies. MethodsIn this study, a nontargeted metabolomics approach based on UPLC-Q-TOF/MS was used to find the differential metabolites in serum samples from patients with DM and MetS. ResultsMetabonomic analysis reveals metabolic differences between DM and HC with significant differences more than 60 metabolites. While, more than 65 metabolites have significant differences between MetS and HC. The independent disturbed pathway in the DM group was the FoxO signaling pathway. The independent disturbed pathways in the MetS group were the alpha-linolenic acid metabolism, glycerophospholipid metabolism and pyrimidine metabolism.The independent disturbed metabolites and the logistic regression result showed that betaine, alpha-linolenic acid, d-mannose, l-glutamine and methylmalonic acid can be used as a combinatorial biomarker to distinguish DM from healthy control. L-isoleucine, l-glutamine, PC(16:0/16:0), alpha-d-glucose, ketoisocaproic acid, d-mannose, uridine can be used as a combinatorial biomarker in MetS. ConclusionOur findings, on one hand, provide critical insight into the pathological mechanism of DM and MetS. On the other hand, supply a combinatorial biomarker to aid the diagnosis of diseases in clinical usage.