Identification of Serum Metabolomics Characteristics in Patients with Stable Angina Pectoris Using UHPLC-QE-MS

Author:

Zhou Yufei12ORCID,Zhou Chen12,Luo Gang12,Ren Wei23,Dong Li12,Liang Junjie12,Mao Linshen23,Liu Mengnan14ORCID,Dong Yanli12,Liang Pan23,Yang Sijin12ORCID

Affiliation:

1. National Traditional Chinese Medicine Clinical Research Base and Cardiovascular Medicine Department of the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, 646000 Sichuan, China

2. College of Integrated Traditional Chinese and Western Medicine, Southwest Medical University, Luzhou, 646000 Sichuan, China

3. National Traditional Chinese Medicine Clinical Research Base and Drug Research Center of the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, 646000 Sichuan, China

4. Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macao, 999078, China

Abstract

Background. Stable angina pectoris (SAP) is one of the main types of coronary heart disease (CHD). To improve treatment outcomes, more effective biomarkers are needed. Currently, studies on the metabolic characteristics of SAP are lacking. Here, we explored the serum metabolomic profile of SAP and identified potential biomarkers and related pathways to assist the clinical diagnosis and treatment of SAP. Method. Thirty patients with SAP patients and 30 healthy controls (CON) without stenosis were selected for this study. All patients underwent coronary angiography. The metabolites of the two groups’ serum samples were investigated using UHPLC-QE-MS. Changes in serum metabolic profile were evaluated using multivariate statistical analysis and pathway analysis. Result. OPLS-DA analysis identified significant differences in the serum metabolic profiles between patients with SAP and CON. Twenty-five differential metabolites were identified between patients from SAP and CON groups, including choline, creatine, L-arginine, beta-guanidinopropionic acid, isopalmitic acid, xanthine, LysoPC (18 : 1), and LysoPC (20 : 3). Pathway analysis found that these differential metabolites were involved in energy metabolism, oxidative stress, purine metabolism, and other metabolic pathways. Conclusion. By comparing the serum metabolic profiles of SAP patients with a control group, we identified 25 potential biomarkers that could improve the clinical diagnosis and treatment of SAP.

Funder

Sichuan Administration of Traditional Chinese Medicine

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

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