Korea Basic Science Institute, Seoul, 136-713, Korea.
Stroke. 2011 May;42(5):1282-8. doi: 10.1161/STROKEAHA.110.598789. Epub 2011 Apr 7.
Stroke is one of the leading causes of adult disability and death in developing countries. However, early diagnosis is difficult and no reliable biomarker is currently available. Thus, we applied a 1H-NMR metabolomics approach to investigate the altered metabolic pattern in plasma and urine from patients with cerebral infarctions and sought to identify metabolic biomarkers associated with stroke.
Metabolic profiles of plasma and urine from patients with cerebral infarctions, especially small vessel occlusion, were investigated using 1H-NMR spectroscopy coupled with multivariate statistical analysis, such as principal components analysis and orthogonal partial least-squares discriminant analysis.
Multivariate statistical analysis showed a significant separation between patients and healthy individuals. The plasma of stroke patients was characterized by the increased excretion of lactate, pyruvate, glycolate, and formate, and by the decreased excretion of glutamine and methanol; the urine of stroke patients was characterized by decreased levels of citrate, hippurate, and glycine. These metabolites detected from plasma and urine of patients with cerebral infarctions were associated with anaerobic glycolysis, folic acid deficiency, and hyperhomocysteinemia. Furthermore, the presence of cerebral infarction in the external validation model was predicted with high accuracy.
These data demonstrate that a metabolomics approach may be useful for the effective diagnosis of cerebral infarction and for the further understanding of stroke pathogenesis.
在发展中国家，中风是导致成年人残疾和死亡的主要原因之一。然而，早期诊断较为困难，目前也没有可靠的生物标志物。因此，我们采用 1H-NMR 代谢组学方法来研究脑梗死患者血浆和尿液中的代谢模式变化，并试图寻找与中风相关的代谢生物标志物。
采用 1H-NMR 光谱结合主成分分析和正交偏最小二乘判别分析等多变量统计分析方法，研究了脑梗死患者，特别是小血管闭塞患者的代谢谱。
多变量统计分析显示患者与健康个体之间存在明显分离。中风患者的血浆特征为乳酸、丙酮酸、乙醇酸和甲酸盐排泄增加，谷氨酰胺和甲醇排泄减少；中风患者的尿液特征为柠檬酸、马尿酸和甘氨酸水平降低。这些从脑梗死患者的血浆和尿液中检测到的代谢物与无氧糖酵解、叶酸缺乏和高同型半胱氨酸血症有关。此外，该模型对外部验证模型中脑梗死的存在具有较高的预测准确性。
这些数据表明代谢组学方法可能有助于有效地诊断脑梗死，并进一步了解中风的发病机制。
