Integrated metabolomics reveals lipid mediators and food-associated chemicals associated with metabolic syndrome.

Background: Metabolic syndrome (MetS), a cluster of interrelated metabolic abnormalities, poses a major global health burden. However, its underlying molecular pathways and environmental triggers remain incompletely understood. Using an integrated metabolomics approach in a well-characterized Chinese cohort, this study aimed to comprehensively characterize metabolic perturbations associated with MetS and to explore potential mechanistic links with food-related chemical exposures. Methods: An integrated cross-platform metabolomics strategy was employed in a two-phase study design comprising independent discovery ( Results: Eight novel metabolite biomarkers significantly associated with MetS components were identified and validated, including the lipid mediator LPC (20:0) and the food-associated pesticide residue procymidone. Machine learning integration of these biomarkers produced optimized multi-metabolite panels that demonstrated superior diagnostic performance for distinguishing MetS (AUC = 0.791 ± 0.034) and its pre-clinical stages (AUC = 0.864 ± 0.023) from healthy controls. Mediation analysis revealed that LPC (20:0) statistically mediated the observed association between chromium exposure and MetS risk, and procymidone similarly mediated the association between mercury exposure and MetS risk, based on cross-sectional data and this finding requires functional validation. Conclusion: This study delineates a distinct metabolic signature of MetS. Pending external validation in independent populations, these findings suggest the potential for developing clinically useful diagnostic tools. Furthermore, it provides pioneering evidence that specific metabolites may bridge food-related chemical exposures to systemic metabolic dysregulation, offering an integrated pathophysiological perspective on the role of food in chronic disease.