Integrated Metabolomics Research Group, Seoul Center, Korea Basic Science Institute, Seoul, Republic of Korea.
Clin Exp Allergy. 2013 Apr;43(4):425-33. doi: 10.1111/cea.12089.
Asthma is a chronic inflammatory disease caused by complex interactions of genetic, epigenetic, and environmental factors. For this reason, new approaches are required to clarify the pathogenesis of asthma by systemic review.
We applied a (1)H-NMR metabolomics approach to investigate the altered metabolic pattern in sera from patients with asthma and sought to identify the mechanism underlying asthma and potential biomarkers.
A global profile of sera from patients with asthma (n = 39) and controls (n = 26) was generated using (1)H-NMR spectroscopy coupled with multivariate statistical analysis. Endogenous metabolites in serum were rapidly measured using the target-profiling procedure.
Multivariate statistical analysis showed a clear distinction between patients with asthma and healthy subjects. Sera of asthma patients were characterized by increased levels of methionine, glutamine, and histidine and by decreased levels of formate, methanol, acetate, choline, O-phosphocholine, arginine, and glucose. The metabolites detected in the sera of patients with asthma are involved in hypermethylation, response to hypoxia, and immune reaction. Furthermore, the levels of serum metabolites from patients with asthma correlated with asthma severity; in particular, lipid metabolism was altered in patients with lower forced expiratory volume in 1 s percentage (FEV(1)%) predicted values. In addition, potential biomarkers showed strong predictive power in ROC analysis, and the presence of asthma in external validation models was predicted with high accuracy (90.9% for asthma and 100% for control subjects).
CONCLUSION & CLINICAL RELEVANCE: These data showed that (1)H-NMR-based metabolite profiling of serum may be useful for the effective diagnosis of asthma and a further understanding of its pathogenesis.
哮喘是一种由遗传、表观遗传和环境因素复杂相互作用引起的慢性炎症性疾病。因此，需要新的方法通过系统综述来阐明哮喘的发病机制。
我们应用 1H-NMR 代谢组学方法研究哮喘患者血清中代谢模式的改变，并试图确定哮喘的发病机制和潜在的生物标志物。
采用 1H-NMR 光谱结合多变量统计分析技术，对哮喘患者（n=39）和对照者（n=26）的血清进行了全局谱分析。采用靶向分析程序快速测定血清中的内源性代谢物。
多变量统计分析显示哮喘患者与健康受试者之间有明显区别。哮喘患者的血清特征为蛋氨酸、谷氨酰胺和组氨酸水平升高，甲酸盐、甲醇、乙酸盐、胆碱、O-磷酸胆碱、精氨酸和葡萄糖水平降低。在哮喘患者血清中检测到的代谢物参与了过度甲基化、缺氧反应和免疫反应。此外，哮喘患者的血清代谢物水平与哮喘严重程度相关；特别是，在预测值较低的 1 秒用力呼气量（FEV1%）的患者中，脂质代谢发生改变。此外，潜在的生物标志物在 ROC 分析中具有很强的预测能力，并且在外部验证模型中可以准确地预测哮喘的存在（哮喘的准确率为 90.9%，对照组的准确率为 100%）。
这些数据表明，基于 1H-NMR 的血清代谢物谱分析可能有助于哮喘的有效诊断和发病机制的进一步理解。
