Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts
Author:
Shi Mengya1, Han Siyu1, Klier Kristin2, Fobo Gisela3, Montrone Corinna3, Yu Shixiang1, Harada Makoto3, Henning Ann-Kristin4, Friedrich Nele4, Bahls Martin5, Dörr Marcus5, Nauck Matthias4, Völzke Henry4, Homuth Georg4, Grabe Hans J.2, Prehn Cornelia3, Adamski Jerzy3, Suhre Karsten6, Rathmann Wolfgang7, Ruepp Andreas3, Hertel Johannes2, Peters Annette3, Wang-Sattler Rui3
Affiliation:
1. Technical University of Munich (TUM) 2. University of Greifswald 3. Helmholtz Zentrum München, German Research Center for Environmental Health 4. University Medicine Greifswald 5. German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald 6. Weill Cornell Medicine - Qatar, Education City - Qatar Foundation 7. German Center for Diabetes Research (DZD)
Abstract
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.
Publisher
Research Square Platform LLC
Reference63 articles.
1. Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5. 2. Recent Progress in Metabolic Syndrome Research and Therapeutics;Kao T-W;Int J Mol Sci Multidisciplinary Digital Publishing Institute,2021 3. The Global Epidemic of the Metabolic Syndrome;Saklayen MG;Curr Hypertens Rep,2018 4. Metabolic Syndrome Pathophysiology and Predisposing Factors;Bovolini A;Int J Sports Med,2021 5. Overnutrition, ectopic lipid and the metabolic syndrome;Grundy SM;J Investig Med Off Publ Am Fed Clin Res,2016
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