ArticleTranslational gastroenterology and hepatology2024
Systematic metabolic profiling of mice with caerulein-induced acute pancreatitis.
Article in Translational gastroenterology and hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Acute pancreatitis (AP) is a complex inflammatory condition with rising incidence globally. Despite various known causes, early diagnosis remains challenging due to limitations in existing biomarkers. Metabolomics offers a promising avenue for identifying novel biomarkers and elucidating underlying pathophysiological mechanisms. Previous AP metabolomics studies primarily focused on analyzing serum, urine, and pancreatic tissues from patients or animal models. However, systematic metabolomics studies that analyze multiple tissues simultaneously are still lacking. The primary aim of our study is to obtain valuable clues to explore the pathophysiological mechanisms of AP and discover novel biomarkers to enable early detection. Methods: Using a mouse model of AP induced by cerulein, we conducted gas chromatography-mass spectrometry (GC-MS) metabolomic analysis on serum, pancreas, liver, spleen, colon, and kidney samples. Twelve male C57BL/6J mice were randomly divided into AP and control (CON) groups. Serum and tissue samples were collected, processed, and analyzed using established protocols. Multivariate statistical analysis was employed to identify differential metabolites and impacted metabolic pathways. Results: Distinct metabolic profiles were observed between AP and CON groups across multiple tissues. Elevated levels of ketone bodies, amino acids, citric acid, and lipids were noted, with significant differences in metabolite levels identified. Notably, 3-hydroxybutyric acid (3-HBA), branched-chain amino acids (BCAAs), phenylalanine, and L-lysine showed consistent alterations, suggesting their potential as early diagnostic biomarkers for AP. Pathway analysis revealed perturbations in several metabolic pathways, providing insights into the pathophysiological mechanisms underlying AP. Conclusions: Our study highlights the utility of metabolomics in identifying potential biomarkers for early diagnosis of AP and elucidating associated metabolic pathways. 3-HBA, BCAAs, phenylalanine and L-lysine emerge as promising biomarkers for further clinical validation. These findings contribute to a better understanding of AP pathophysiology and underscore the potential of metabolomics in precision medicine approaches for AP management.
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