AUTHOR=Jing Ziwei , Liu Liwei , Shi Yingying , Du Qiuzheng , Zhang Dingding , Zuo Lihua , Du Shuzhang , Sun Zhi , Zhang Xiaojian 

TITLE=Association of Coronary Artery Disease and Metabolic Syndrome: Usefulness of Serum Metabolomics Approach

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2021.692893

DOI=10.3389/fendo.2021.692893

ISSN=1664-2392

ABSTRACT=Introduction: Individuals with metabolic syndrome (MetS) are at increasing risk of coronary artery disease (CAD). We investigated the common metabolic perturbations of CAD and MetS via large-scale serum metabolomics to provide insight into potential associations.
Methods: A total of 492 participants, including 272 CAD, 55 MetS, and 165 healthy controls (HCs) were recruited in this study. Serum metabolomic profiles were determined by ultra high performance liquid chromatography-Q exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS). Multivariate statistics were applied to obtain the significant metabolites for CAD and MetS. Logistic regression were performed to investigate the association of significant metabolic perturbations with clinical cardiac risk factors, as well as the common perturbation of CAD and MetS. Finally, the ROC analysis were evaluated for the risk prediction values of common changed metabolites.
Results: 30 metabolites for CAD were identified and remained significant from the combinatorial variables of clinical risk factor, 26 metabolites for MetS were identified and 15 remained significant after adjustments of clinical risk factors. In the common metabolic signatures association analysis between CAD and MetS, 8 down-regulated metabolites, 1 up-regulated metabolite both in CAD and MetS, other 2 changed contrarily metabolites were observed. Finally, 9 metabolites with same change trend exhibited excellent risk prediction performance (86.4% for CAD and 90.9% for MetS) by receiver operating characteristic (ROC) analysis, further confirmed the association of the two diseases.
Conclusion: Large-scale serum metabolomics analysis might provide a new insight into the potential mechanisms underlying the common metabolic perturbations of CAD and MetS.