Ethanol-induced metabolomic differences in the Gut-Liver-Pancreas Axis

Significance of the Topic

The gastrointestinal–liver–pancreas axis plays a central role in nutrient processing and metabolic homeostasis. Chronic alcohol consumption disrupts this axis and contributes to liver disease, pancreatitis and systemic metabolic disorders. Untargeted high-resolution metabolomic profiling can reveal tissue-specific biochemical alterations induced by ethanol, providing insights into disease mechanisms and potential biomarkers.

Objectives and Study Overview

This investigation aimed to characterize ethanol-induced metabolomic changes in the gut, liver and pancreas of mice following an eight-week exposure to a 5 % ethanol diet. Key goals included:

• Profiling global metabolite and lipid alterations in each tissue.
• Determining tissue specificity of ethanol response.
• Identifying candidate metabolites with significant fold changes.

Methodology

Male C57BL/6 mice (n=8 per group) received a Lieber–DeCarli diet with or without 5 % ethanol for eight weeks. Post-mortem, gut, liver and pancreas samples were homogenized and lipophilic and polar metabolites extracted. Untargeted analysis was performed on an LCMS-9030 high-resolution quadrupole time-of-flight mass spectrometer in positive ion mode, employing both data-independent and data-dependent acquisition across m/z 100–1000. Quality control samples were interspersed to monitor retention time stability and signal reproducibility. Data processing and statistical analysis included:

• Peak detection and alignment using Analyze component detection algorithms.
• Filtering features present in ≥50 % of QCs with RSD < 30 %.
• Multivariate analysis (PCA) and volcano plots (fold change >2, p < 0.05, FDR correction) via MetaboAnalyst.

Použitá instrumentace

• Shimadzu LCMS-9030 HRMS Q-TOF system with electrospray ionization.
• Analyze component detection software for precursor ion selection.
• LabSolutions Insight for data preprocessing.
• MetaboAnalyst for multivariate statistics.
• MS/MS spectral libraries (in-house, Metlin, MassBank) for metabolite annotation.

Main Results and Discussion

PCA revealed that tissue type accounted for the greatest variance (58.9 % on PC1), with ethanol treatment contributing a smaller but clear separation within each tissue. Volcano plot analysis identified:

• Gut: 550 elevated and 385 reduced features. Notable upregulation of phosphatidylcholines, oleic acid ethyl ester; downregulation of lyso-phospholipids and glycerophosphoethanolamine.
• Liver: 290 increased and 233 decreased features. Significant accumulation of fatty acid ethyl esters (linoleic, docosahexaenoic, oleic) and N-acyltaurines.
• Pancreas: 108 elevated and 428 reduced features. Predominant decreases in monoacylglycerols (log2 fold change between –2 and –6).

Only three metabolites were common across all tissues, but these exhibited modest fold changes, underscoring highly tissue-specific ethanol effects.

Benefits and Practical Applications

These findings demonstrate the utility of untargeted HRMS metabolomics to uncover tissue-restricted metabolic signatures of chronic alcohol exposure. Potential applications include:

• Discovery of early biomarkers for alcohol-related organ injury.
• Informing targeted assay development for clinical research.
• Enhancing mechanistic understanding of organ-specific ethanol toxicity.

Future Trends and Potential Applications

Advances in multi-omics integration, single-cell metabolomics and spatially resolved mass spectrometry could further delineate cell-type responses within each organ. Translation to human cohorts and longitudinal sampling may enable personalized risk assessment and monitor recovery during abstinence or therapeutic intervention.

Conclusion

A comprehensive untargeted HRMS LC-MS/MS workflow has successfully mapped ethanol-induced metabolomic perturbations in the gut-liver-pancreas axis. Results highlight distinct biochemical responses in each organ, supporting targeted biomarker discovery and deeper insight into alcohol-driven pathophysiology.