A GC-MS-Based Urinary Metabolomic Profiling to Identify Potential Biomarkers of Metabolic Syndrome.

ABSTRACT: Metabolic syndrome (MetS) is a multifactorial condition characterized by central obesity, dyslipidemia, hypertension, and insulin resistance, increasing the risk of cardiovascular disease and type 2 diabetes. Despite its clinical significance, current diagnostic methods rely on invasive blood-based assessments. This study investigates the potential of urinary metabolomics as a noninvasive alternative for MetS diagnosis. Using gas chromatography-mass spectrometry (GC-MS), we analyzed urinary metabolites from 127 individuals classified into Normal, Borderline (BL), and MetS groups based on clinical diagnostic criteria. A total of 80 metabolites were identified, and partial least-squares discriminant analysis (PLS-DA) revealed distinct metabolic profiles between groups. Key metabolites, inclu

SUBMITTER: Pak J 

PROVIDER: S-EPMC12573147 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature