Zhong Wei, Deng Qiaoting, Deng Xunwei, Zhong Zhixiong, Hou Jingyuan
Center for Cardiovascular Diseases, Meizhou People's Hospital (Huangtang Hospital), Meizhou Hospital Affiliated to Sun Yat-sen University, Meizhou, China.
Guangdong Provincial Engineering and Technology Research Center for Molecular Diagnostics of Cardiovascular Diseases, Meizhou, China.
Front Cardiovasc Med. 2021 May 20;8:616081. doi: 10.3389/fcvm.2021.616081. eCollection 2021.
Acute coronary syndrome (ACS) is the main cause of death and morbidity worldwide. The present study aims to investigate the altered metabolites in plasma from patients with ACS and sought to identify metabolic biomarkers for ACS. The plasma metabolomics profiles of 284 ACS patients and 130 controls were carried out based on an untargeted liquid chromatography coupled with tandem mass spectrometry (LC-MS) approach. Multivariate statistical methods, pathway enrichment analysis, and univariate receiver operating characteristic (ROC) curve analysis were performed. A total of 328 and 194 features were determined in positive and negative electrospray ionization mode in the LC-MS analysis, respectively. Twenty-eight metabolites were found to be differentially expressed, in ACS patients relative to controls ( < 0.05). Pathway analysis revealed that these metabolites are mainly involved in synthesis and degradation of ketone bodies, phenylalanine metabolism, and arginine and proline metabolism. Furthermore, a diagnostic model was constructed based on the metabolites identified and the areas under the curve (AUC) for 5-oxo-D-proline, creatinine, phosphatidylethanolamine lyso 16:0, and LPC (20:4) range from 0.764 to 0.844. The higher AUC value of 0.905 was obtained for the combined detection of phosphatidylethanolamine lyso 16:0 and LPC (20:4). Differential metabolic profiles may be useful for the effective diagnosis of ACS and may provide additional insight into the molecular mechanisms underlying ACS.
急性冠状动脉综合征（ACS）是全球范围内死亡和发病的主要原因。本研究旨在调查ACS患者血浆中代谢物的变化，并试图识别ACS的代谢生物标志物。基于非靶向液相色谱-串联质谱（LC-MS）方法，对284例ACS患者和130例对照者的血浆代谢组学图谱进行了分析。采用多变量统计方法、通路富集分析和单变量受试者工作特征（ROC）曲线分析。在LC-MS分析中，正、负离子电喷雾电离模式下分别确定了328个和194个特征峰。发现28种代谢物在ACS患者与对照者之间存在差异表达（<0.05）。通路分析表明，这些代谢物主要参与酮体的合成与降解、苯丙氨酸代谢以及精氨酸和脯氨酸代谢。此外，基于所鉴定的代谢物构建了诊断模型，5-氧代-D-脯氨酸、肌酐、溶血磷脂酰乙醇胺16:0和溶血磷脂酰胆碱（20:4）的曲线下面积（AUC）在0.764至0.844之间。溶血磷脂酰乙醇胺16:0和溶血磷脂酰胆碱（20:4）联合检测的AUC值更高，为0.905。差异代谢谱可能有助于ACS的有效诊断，并可能为ACS潜在的分子机制提供更多见解。
