Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts

Abstract

Background Metabolic syndrome (MetS) consists of risk factors (abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL–C), hypertension, hyperglycemia) for cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its risk factors to better understand the complex interplay of underlying signaling pathways. Methods We quantified serum samples of the KORA F4 study participants (N = 2,815) and analyzed 121 metabolites. Using multiple regression models adjusted for clinical and lifestyle covariates, we examined metabolites that have a Bonferroni significant MetS association, and replicated them in the SHIP-TREND-0 study (N = 988), and further analyzed for each of the five components of MetS. Database-based networks of the identified metabolites with interacting enzymes were also constructed. Results We identified and replicated 56 MetS-specific metabolites: 13 positively associated (e.g., Val, Leu/Ile, Phe and Tyr, sum of hexoses, 2 carnitines, and 6 lipids), and 43 negatively associated (e.g., Gly, Ser, and 40 lipids). Furthermore, most (89%) and least (23%) of the MetS-specific metabolites were separately associated with low HDL–C and hypertension among the components. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of the five components, indicating patients with MetS and each of the risk factors had lowered concentrations of lysoPC a C18:2 compared to corresponding healthy controls. Our metabolic networks clarified our observations by revealing impaired catabolisms of branched-chain and aromatic amino acids, as well as higher rates of Gly catabolism. Conclusion Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors and could help develop therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For example, higher levels of lysoPC a C18:2 may provide protection against MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.