Discovery of metabolite profiles of metabolic syndrome using untargeted and targeted LC-MS based lipidomics approach

Abstract

Metabolic syndrome (MetS) is an important risk factor for type 2 diabetes, cardiovascular diseases and all-cause morbidity and mortality. Biomarkers can provide insight into the mechanism, facilitate early detection, and monitor progression of MetS and its response to therapeutic interventions. To identify potential biomarkers, we applied a non-targeted and targeted lipidomics method to characterize plasma metabolic profile in MetS patients. Metabolic profiling was performed on a non-target set (40 cases and 40 controls) on UHPLC-Q-TOF/MS and target set (80 MetS patients and 80 healthy controls) on UHPLC-Q-orbitrap MS. Using comprehensive screening and validation workflow, we identified a panel of three metabolites including PC(18:1/P-16:0), PC(o-22:3/22:3), PC(P-18:1/16:1). Our results indicated that the identified biomarkers may improve the risk prediction and provide a novel tool for monitoring of the progression of disease and response to treatment in MetS patients.

Keywords: Biomarkers; Lipidomics; Metabolic syndrome; Metabolomics.