Xiao Hong, Huang Jian-Hua, Zhang Xing-Wen, Ahmed Rida, Xie Qing-Ling, Li Bin, Zhu Yi-Ming, Cai Xiong, Peng Qing-Hua, Qin Yu-Hui, Huang Hui-Yong, Wang Wei
TCM and Ethnomedicine Innovation & Development Laboratory, Sino-Pakistan TCM Research Center, School of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, PR China.
TCM and Ethnomedicine Innovation & Development Laboratory, Sino-Pakistan TCM Research Center, School of Pharmacy, Hunan University of Chinese Medicine, Changsha, 410208, PR China; Hunan Provincial Key Laboratory of Diagnostics in Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, PR China.
Pancreatology. 2017 Jul-Aug;17(4):543-549. doi: 10.1016/j.pan.2017.04.015. Epub 2017 May 3.
Acute pancreatitis (AP) is defined as an acute inflammation of pancreas that may cause damage to other tissues and organs depending upon the severity of symptoms. The diagnosis of AP is usually made by detection of raised circulating pancreatic enzyme levels, but there are occasional false positive and false negative diagnoses and such tests are often normal in delayed presentations. More accurate biomarkers would help in such situations. In this study, the global metabolites' changes of AP patients (APP) were profiled by using gas chromatography-mass spectrometry (GC-MS). Multivariate pattern recognition techniques were used to establish the classification models to distinguish APP from healthy participants (HP). Some significant metabolites including 3-hydroxybutyric acid, phosphoric acid, glycerol, citric acid, d-galactose, d-mannose, d-glucose, hexadecanoic acid and serotonin were selected as potential biomarkers for helping clinical diagnosis of AP. Furthermore, the metabolite changes in APP with severe and mild symptoms were also analyzed. Based on the selected biomarkers, some relevant pathways were also identified. Our results suggested that GC-MS based serum metabolomics method can be used in the clinical diagnosis of AP by profiling potential biomarkers.
急性胰腺炎(AP)被定义为胰腺的急性炎症,根据症状的严重程度,可能会对其他组织和器官造成损害。AP的诊断通常通过检测循环中胰腺酶水平升高来进行,但偶尔会出现假阳性和假阴性诊断,并且在延迟就诊时此类检测结果通常正常。更准确的生物标志物将有助于应对此类情况。在本研究中,通过气相色谱-质谱联用(GC-MS)对AP患者(APP)的整体代谢物变化进行了分析。使用多变量模式识别技术建立分类模型,以区分APP和健康参与者(HP)。选择了一些重要的代谢物,包括3-羟基丁酸、磷酸、甘油、柠檬酸、d-半乳糖、d-甘露糖、d-葡萄糖、十六烷酸和血清素,作为有助于AP临床诊断的潜在生物标志物。此外,还分析了症状严重和轻微的APP中的代谢物变化。基于所选的生物标志物,还确定了一些相关途径。我们的结果表明,基于GC-MS的血清代谢组学方法可通过分析潜在生物标志物用于AP的临床诊断。