Shanghai Public Health Clinical Center Affiliated to Fudan University, China.
Acta Biochim Biophys Sin (Shanghai). 2010 Oct;42(10):688-98. doi: 10.1093/abbs/gmq078. Epub 2010 Sep 1.
This paper presents an liquid chromatography (LC)/mass spectrometry (MS)-based metabonomic platform that combined the discovery of differential metabolites through principal component analysis (PCA) with the verification by selective multiple reaction monitoring (MRM). These methods were applied to analyze plasma samples from liver disease patients and healthy donors. LC-MS raw data (about 1000 compounds), from the plasma of liver failure patients (n = 26) and healthy controls (n = 16), were analyzed through the PCA method and a pattern recognition profile that had significant difference between liver failure patients and healthy controls (P < 0.05) was established. The profile was verified in 165 clinical subjects. The specificity and sensitivity of this model in predicting liver failure were 94.3 and 100.0%, respectively. The differential ions with m/z of 414.5, 432.0, 520.5, and 775.0 were verified to be consistent with the results from PCA by MRM mode in 40 clinical samples, and were proved not to be caused by the medicines taken by patients through rat model experiments. The compound with m/z of 520.5 was identified to be 1-Linoleoylglycerophosphocholine or 1-Linoleoylphosphatidylcholine through exact mass measurements performed using Ion Trap-Time-of-Flight MS and METLIN Metabolite Database search. In all, it was the first time to integrate metabonomic study and MRM relative quantification of differential peaks in a large number of clinical samples. Thereafter, a rat model was used to exclude drug effects on the abundance of differential ion peaks. 1-Linoleoylglycerophosphocholine or 1-Linoleoylphosphatidylcholine, a potential biomarker, was identified. The LC/MS-based metabonomic platform could be a powerful tool for the metabonomic screening of plasma biomarkers.
本文提出了一种基于液相色谱(LC)/质谱(MS)的代谢组学平台,该平台结合了主成分分析(PCA)发现差异代谢物和选择性多重反应监测(MRM)验证的方法。这些方法应用于分析肝病患者和健康供体的血浆样本。通过 PCA 方法和具有显著差异的模式识别图谱对来自肝衰竭患者(n = 26)和健康对照者(n = 16)的血浆 LC-MS 原始数据(约 1000 种化合物)进行分析,建立了肝衰竭患者和健康对照者之间存在显著差异的图谱(P < 0.05)。该图谱在 165 例临床样本中得到验证。该模型预测肝衰竭的特异性和敏感性分别为 94.3%和 100.0%。通过 MRM 模式在 40 例临床样本中验证了质荷比为 414.5、432.0、520.5 和 775.0 的差异离子与 PCA 的结果一致,并通过大鼠模型实验证明这些差异离子不是由患者所服用的药物引起的。通过精确质量测量(Ion Trap-Time-of-Flight MS 和 METLIN 代谢物数据库搜索),质荷比为 520.5 的化合物被鉴定为 1-亚油酰甘油磷酸胆碱或 1-亚油酰基磷脂酰胆碱。总之,这是首次在大量临床样本中整合代谢组学研究和差异峰的 MRM 相对定量。此后,使用大鼠模型排除药物对差异离子峰丰度的影响。1-亚油酰甘油磷酸胆碱或 1-亚油酰基磷脂酰胆碱,一种潜在的生物标志物被鉴定出来。基于 LC/MS 的代谢组学平台可以成为一种强大的工具,用于代谢组学筛选血浆生物标志物。