Comprehensive Metabolomic Characterization of Coronary Artery Diseases

医学 代谢组学 冠状动脉疾病 心肌梗塞 内科学 心脏病学 不稳定型心绞痛 曲线下面积 生物信息学 生物
作者
Yong Fan,Yong Li,Yan Chen,Yijing Zhao,Liwei Liu,Jin Li,Shi-Lei Wang,Raphael N. Alolga,Yin Yin,Xiangming Wang,Dongsheng Zhao,Jianhua Shen,Fanqi Meng,Xin Zhou,Hao Xu,Guoping He,Maode Lai,Ping Li,Wei Zhu,Lian‐Wen Qi
出处
期刊:Journal of the American College of Cardiology [Elsevier BV]
卷期号:68 (12): 1281-1293 被引量:221
标识
DOI:10.1016/j.jacc.2016.06.044
摘要

Pathogenesis and diagnostic biomarkers for diseases can be discovered by metabolomic profiling of human fluids. If the various types of coronary artery disease (CAD) can be accurately characterized by metabolomics, effective treatment may be targeted without using unnecessary therapies and resources.The authors studied disturbed metabolic pathways to assess the diagnostic value of metabolomics-based biomarkers in different types of CAD.A cohort of 2,324 patients from 4 independent centers was studied. Patients underwent coronary angiography for suspected CAD. Groups were divided as follows: normal coronary artery (NCA), nonobstructive coronary atherosclerosis (NOCA), stable angina (SA), unstable angina (UA), and acute myocardial infarction (AMI). Plasma metabolomic profiles were determined by liquid chromatography-quadrupole time-of-flight mass spectrometry and were analyzed by multivariate statistics.We made 12 cross-comparisons to and within CAD to characterize metabolic disturbances. We focused on comparisons of NOCA versus NCA, SA versus NOCA, UA versus SA, and AMI versus UA. Other comparisons were made, including SA versus NCA, UA versus NCA, AMI versus NCA, UA versus NOCA, AMI versus NOCA, AMI versus SA, significant CAD (SA/UA/AMI) versus nonsignificant CAD (NCA/NOCA), and acute coronary syndrome (UA/AMI) versus SA. A total of 89 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism, increased amino acid metabolism, increased short-chain acylcarnitines, decrease in tricarboxylic acid cycle, and less biosynthesis of primary bile acid. For differential diagnosis, 12 panels of specific metabolomics-based biomarkers provided areas under the curve of 0.938 to 0.996 in the discovery phase (n = 1,086), predictive values of 89.2% to 96.0% in the test phase (n = 933), and 85.3% to 96.4% in the 3-center external sets (n = 305).Plasma metabolomics are powerful for characterizing metabolic disturbances. Differences in small-molecule metabolites may reflect underlying CAD and serve as biomarkers for CAD progression.
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