Zhang K, Wang Y, Cui X, Wang W, Li Y. Features of Metabolite Changes in Disease Evolution in Cholecystolithiasis.
Dig Dis Sci 2024;
69:275-288. [PMID:
37943386 PMCID:
PMC10787879 DOI:
10.1007/s10620-023-08134-6]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 09/28/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND
Cholecystolithiasis is defined as a disease caused by complex and changeable factors. Advanced age, female sex, and a hypercaloric diet rich in carbohydrates and poor in fiber, together with obesity and genetic factors, are the main factors that may predispose people to choledocholithiasis. However, serum biomarkers for the rapid diagnosis of choledocholithiasis remain unclear.
AIMS
This study was designed to explore the pathogenesis of cholecystolithiasis and identify the possible metabolic and lipidomic biomarkers for the diagnosis of the disease.
METHODS
Using UHPLC-MS/MS and GC-MS, we detected the serum of 28 cholecystolithiasis patients and 19 controls. Statistical analysis of multiple variables included Principal Component Analysis (PCA). Visualization of differential metabolites was performed using volcano plots. The screened differential metabolites were further analyzed using clustering heatmaps. The quality of the model was assessed using random forests.
RESULTS
In this study, dramatically altered lipid homeostasis was detected in cholecystolithiasis group. In addition, the levels of short-chain fatty acids and amino acids were noticeably changed in patients with cholecystolithiasis. They detected higher levels of FFA.18.1, FFA.20.1, LPC16.0, and LPC20.1, but lower levels of 1-Methyl-L-histidine and 4-Hydroxyproline. In addition, glycine and L-Tyrosine were higher in choledocholithiasis group. Analyses of metabolic serum in affected patients have the potential to develop an integrated metabolite-based biomarker model that can facilitate the early diagnosis and treatment of the disease.
CONCLUSION
Our results highlight the value of integrating lipid, amino acid, and short-chain fatty acid to explore the pathophysiology of cholecystolithiasis disease, and consequently, improve clinical decision-making.
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