Lee Yeseung, Khan Adnan, Hong Seri, Jee Sun Ha, Park Youngja H
Metabolomics Laboratory, College of Pharmacy, Korea University, Sejong City, 30019, Korea.
Department of Epidemiology and Health Promotion and Institute of Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, 03722, Korea.
Mol Biosyst. 2017 May 30;13(6):1109-1120. doi: 10.1039/c6mb00732e.
Identifying changes in serum metabolites during cerebral ischemia is an important approach for early diagnosis of thrombotic stroke. Herein, we highlight novel biomarkers for early diagnosis of patients at high risk of thrombotic stroke using high resolution metabolomics (HRM). In this retrospective cohort study, serum samples obtained from patients at risk of thrombotic stroke (n = 62) and non-risk individuals (n = 348) were tested using HRM, coupled with LC-MS/MS, to discriminate between metabolic profiles of control and stroke risk patients. Multivariate analysis and orthogonal partial least square-discriminant analysis (OPLS-DA) were performed to determine the top 5% metabolites within 95% group identities, followed by filtering with p-value <0.05 and annotating significant metabolites using a Metlin database. Mapping identified features from Kyoto Encyclopedia of Genes and Genomes (KEGG) and Mummichog resulted in 341 significant features based on OPLS-DA with p-value <0.05. Among these 341 features, nine discriminated the thrombotic stroke risk group from the control group: low levels of N-acetyl-l-lysine, 5-aminopentanoate, cadaverine, 2-oxoglutarate, nicotinamide, l-valine, S-(2-methylpropionyl)-dihydrolipoamide-E and ubiquinone, and elevated levels of homocysteine sulfinic acid. Further analysis showed that these metabolite biomarkers are specifically related to stroke occurrence, and unrelated to other factors such as diabetes or smoking. Lower levels of lysine catabolites in thrombotic stroke risk patients, as compared to the control, supports targeting these compounds as novel biomarkers for early and non-invasive detection of a thrombotic stroke.
识别脑缺血期间血清代谢物的变化是血栓性中风早期诊断的重要方法。在此，我们利用高分辨率代谢组学（HRM）突出了用于血栓性中风高危患者早期诊断的新型生物标志物。在这项回顾性队列研究中，使用HRM结合液相色谱-串联质谱（LC-MS/MS）对从血栓性中风风险患者（n = 62）和非风险个体（n = 348）获得的血清样本进行检测，以区分对照组和中风风险患者的代谢谱。进行多变量分析和正交偏最小二乘判别分析（OPLS-DA）以确定95%组内一致性内的前5%代谢物，随后用p值<0.05进行筛选，并使用Metlin数据库注释显著代谢物。根据京都基因与基因组百科全书（KEGG）和Mummichog对识别出的特征进行映射，基于p值<0.05的OPLS-DA得出341个显著特征。在这341个特征中，有9个区分了血栓性中风风险组和对照组：N-乙酰-L-赖氨酸、5-氨基戊酸、尸胺、2-氧代戊二酸、烟酰胺、L-缬氨酸、S-（2-甲基丙酰基）-二氢硫辛酰胺-E和泛醌水平较低，以及高半胱氨酸亚磺酸水平升高。进一步分析表明，这些代谢物生物标志物与中风发生特异性相关，与糖尿病或吸烟等其他因素无关。与对照组相比，血栓性中风风险患者中赖氨酸分解代谢物水平较低，这支持将这些化合物作为血栓性中风早期和非侵入性检测的新型生物标志物。
