Liu Chang, Zong Wen-Jing, Zhang Ai-Hua, Zhang Hua-Min, Luan Yi-Han, Sun Hui, Cao Hong-Xin, Wang Xi-Jun
Sino-America Chinmedomics Technology Collaboration Center, National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine Heping Road 24 Harbin China
China Academy of Chinese Medical Science Southern Street of Dongzhimen No. 16 Beijing 100700 China.
RSC Adv. 2018 Jan 2;8(2):647-654. doi: 10.1039/c7ra09353e.
Although many diagnostic tools have been developed for coronary heart disease (CHD), its diagnosis is still challenging. Lipids play an important role in diseases and a lipidomics approach could offer a platform to clarify the pathogenesis and pathologic changes of this disease. To the best of our knowledge, no lipidomics studies on serum have been attempted to improve the diagnosis and identify the potential biomarkers of CHD. The aim of this study was to investigate the distinctive lipid changes in serum samples of CHD patients and to identify candidate biomarkers for the reliable diagnosis of CHD using this platform. In this study, the serum lipid profiles of CHD patients were measured ultra-performance liquid chromatography-G2-Si-high definition mass spectrometry combined with multivariate data analysis. A MetaboAnalyst tool was used for the analysis of the receiver operating-characteristic, while the IPA software was applied for the pathway analysis. The obtained results inferred that 33 lipid molecular species involving 6 fatty acids, 21 glycerophospholipids and 6 sphingolipids have significant differences in the serum of CHD patients. Simultaneously, 4 upstream regulatory proteins related to lipid metabolism disorders of CHD were predicted. Ten lipids have high clinical diagnostic significance according to the receiver operating-characteristic curves. This research shows that the in-depth study of lipids in the serum contributes to the clinical diagnosis of CHD and interprets the occurrence and development of CHD.
尽管已经开发出许多用于冠心病(CHD)的诊断工具,但其诊断仍然具有挑战性。脂质在疾病中起着重要作用,脂质组学方法可以提供一个平台来阐明这种疾病的发病机制和病理变化。据我们所知,尚未尝试通过血清脂质组学研究来改善冠心病的诊断并确定其潜在生物标志物。本研究的目的是调查冠心病患者血清样本中独特的脂质变化,并使用该平台确定用于可靠诊断冠心病的候选生物标志物。在本研究中,采用超高效液相色谱-G2-Si-高清质谱联用多元数据分析方法测量冠心病患者的血清脂质谱。使用MetaboAnalyst工具进行受试者工作特征分析,同时应用IPA软件进行通路分析。所得结果推断,冠心病患者血清中涉及6种脂肪酸、21种甘油磷脂和6种鞘脂的33种脂质分子物种存在显著差异。同时,预测了4种与冠心病脂质代谢紊乱相关的上游调节蛋白。根据受试者工作特征曲线,有10种脂质具有较高的临床诊断意义。本研究表明,对血清脂质的深入研究有助于冠心病的临床诊断,并解释冠心病的发生和发展。