| Literature DB >> 28487129 |
Hong Xiao1, Jian-Hua Huang2, Xing-Wen Zhang3, Rida Ahmed4, Qing-Ling Xie1, Bin Li1, Yi-Ming Zhu5, Xiong Cai6, Qing-Hua Peng6, Yu-Hui Qin1, Hui-Yong Huang6, Wei Wang7.
Abstract
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.Entities:
Keywords: Acute pancreatitis; Biomarker discovery; Metabolomics; Pattern recognition
Year: 2017 PMID: 28487129 DOI: 10.1016/j.pan.2017.04.015
Source DB: PubMed Journal: Pancreatology ISSN: 1424-3903 Impact factor: 3.996