TY - JOUR
T1 - Novel biomarkers of hyperlipidemic acute pancreatitis
T2 - Metabolomic identification
AU - Zhao, Yan
AU - Jia, Wei
AU - Su, Mingming
AU - Qiu, Yunping
AU - Wang, Xingpeng
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012/10
Y1 - 2012/10
N2 - Background: Recognition of hypertriglyceridemia is critical for the diagnosis of hyperlipidemic pancreatitis (HLP) and the selection and evaluation of therapy. Objective: Investigate metabolic profiling technologies for identifying novel biomarkers and pathways activated in HLP. Methods: Blood and urine samples were obtained from 24 patients and 39 healthy people. A gas chromatography and mass spectrometry was employed to study the metabolic profile in HLP and healthy groups. Functional pathway trend analysis using multivariate statistical analysis was performed. Results: HLP patients could be precisely distinguished from the healthy controls. In the patient, levels of aconitate, citrate, hippurate, p-hydroxyphenylacetate and p-hydroxyphenylpopionic acid were decreased, while levels of tryptophan, tyrosine, tyramine,16-hexadecanoic acid, and 18-octadecanoic acid were increased. The change of energy metabolism-related mechanisms, fatty acid metabolism, gut microbiota metabolism, and metabolism of tyrosine could be used to distinguish HLP patients. Conclusions: Novel biomarkers could be identified by application of metabolomics. Metabolic profiling was useful for studies of pathogenesis of HLP.
AB - Background: Recognition of hypertriglyceridemia is critical for the diagnosis of hyperlipidemic pancreatitis (HLP) and the selection and evaluation of therapy. Objective: Investigate metabolic profiling technologies for identifying novel biomarkers and pathways activated in HLP. Methods: Blood and urine samples were obtained from 24 patients and 39 healthy people. A gas chromatography and mass spectrometry was employed to study the metabolic profile in HLP and healthy groups. Functional pathway trend analysis using multivariate statistical analysis was performed. Results: HLP patients could be precisely distinguished from the healthy controls. In the patient, levels of aconitate, citrate, hippurate, p-hydroxyphenylacetate and p-hydroxyphenylpopionic acid were decreased, while levels of tryptophan, tyrosine, tyramine,16-hexadecanoic acid, and 18-octadecanoic acid were increased. The change of energy metabolism-related mechanisms, fatty acid metabolism, gut microbiota metabolism, and metabolism of tyrosine could be used to distinguish HLP patients. Conclusions: Novel biomarkers could be identified by application of metabolomics. Metabolic profiling was useful for studies of pathogenesis of HLP.
KW - Blood
KW - Hyperlipidemic pancreatitis
KW - Metabolism
KW - Urine
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U2 - 10.5372/1905-7415.0605.119
DO - 10.5372/1905-7415.0605.119
M3 - Article
AN - SCOPUS:84874610222
VL - 6
SP - 765
EP - 769
JO - Asian Biomedicine
JF - Asian Biomedicine
SN - 1905-7415
IS - 5
ER -