biostudies-literatureUnknown12(6)Alsoud LOMetabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (<i>n</i> = 26), normoglycemic MetS patients (<i>n</i> = 30), and healthy (normoglycemic lean) subjects (<i>n</i> = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highMetabolites508https://www.ebi.ac.uk/biostudies/studies/S-EPMC9227428biostudies-literatureIdentification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS.PMC9227428Kasabri VSoares NCAl-Hroub HMAlzoubi KHSuyagh MSemreen MHEl-Huneidi WAlsoud LOBulatova NAbu-Irmaileh BBustanji YMousa MfalseIdentification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS.Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (<i>n</i> = 26), normoglycemic MetS patients (<i>n</i> = 30), and healthy (normoglycemic lean) subjects (<i>n</i> = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using high2022-01-01T00:00:00Z2022 Jun2025-04-05T13:34:16.943Z2025-04-05T13:34:16.943ZS-EPMC92274283573644110.3390/metabo12060508