Investigating The Relationship Between Off Target Pharmacology & The DMPK of Methapyrilene Using Lipidomics And MS Imaging

Significance of the Topic

The integration of metabolomics and lipidomics into drug safety assessment has transformed our ability to detect off-target pharmacology and understand hepatotoxicity. By profiling lipid and metabolite alterations, researchers can gain mechanistic insight into drug-induced toxicity, improve biomarker discovery, and enhance translational relevance in preclinical studies.

Objectives and Study Overview

This investigation examined the disposition and biological impact of methapyrilene—an antihistamine withdrawn for hepatotoxicity—in male Wistar rats. Key objectives were:

• Characterize toxicokinetics and metabolic fate after repeated oral dosing (0, 50, 150 mg/kg/day for 5 days).
• Identify perturbations in endogenous metabolites and lipids in biofluids and tissues.
• Map the spatial distribution of drug, metabolites, and dysregulated lipids in liver sections.
• Determine dose- and time-dependent trajectories in biochemical responses.

Methodology and Instrumentation

Eight male Wistar rats were assigned to three dose groups. Samples of urine, plasma, feces, and liver tissue were collected at 24, 72, and 120 hours post-dose and divided for multiple analyses.

• Toxicokinetics and metabolite identification: Reversed-phase UHPLC-MS/MS and LC-HRMS with MassMetaSite for structural elucidation.
• Discovery metabolomics and lipidomics: UHPLC-HRMS in positive and negative ESI modes; HILIC-MS/MS for quantitative lipid profiling.
• Urinary metabolomics: Reversed-phase UPLC-MS/MS (positive ESI) to monitor elimination profiles.
• Tissue imaging: DESI-MRM MS and DESI MS-QqQ to visualize localization of drug, metabolites, and lipids in liver sections.

Main Results and Discussion

Toxicokinetic analysis demonstrated rapid clearance of methapyrilene and its metabolites from plasma within 24 hours. A total of 24 drug-related metabolites were characterized, involving thiophene ring cleavage, demethylation, oxygenation, and both N- and O-glucuronidation pathways. Urinary data revealed shifting ratios of key metabolites (e.g., increases in M20 and decreases in M1), reflecting dose- and time-dependent biotransformation.
Lipidomic profiling uncovered significant dysregulation in multiple lipid classes—including triglycerides (TG), phosphatidylcholines (PC), sphingomyelins (SM), lysophosphatidylethanolamines (LPE), phosphatidylethanolamines (PE), free fatty acids (FFA), carnitines, and bile acids. Multivariate analysis highlighted distinct trajectories for the 50 and 150 mg/kg groups. DESI imaging mapped elevated bile acid and phosphatidylinositol (PI) signals with increasing dose, while PE and phosphatidylglycerol (PG) species localized differently between dose levels. Correlations between urinary metabolite elimination and lipid alterations suggest coordinated pharmacolipidodynamic effects.

Benefits and Practical Applications

The combined multi-omics and imaging approach provides:

• A comprehensive DMPK profile of methapyrilene, confirming known pathways and discovering novel glucuronide metabolites.
• Mechanistic insight into off-target lipid perturbations, aiding biomarker identification for hepatotoxicity.
• A platform that can be extended to other compounds for preclinical safety evaluation and regulatory submission support.

Future Trends and Potential Applications

Emerging directions include:

• Integration of spatial omics with artificial intelligence to predict toxicological outcomes based on molecular maps.
• Application to a broader range of xenobiotics, including biologics and novel small molecules.
• Development of in vitro liver models coupled with imaging lipidomics for high-throughput toxicology screening.

Conclusion

This study confirms established methapyrilene DMPK characteristics, uncovers new phase II metabolites, and links metabolite elimination profiles to endogenous lipid dysregulation. The combination of targeted assays, discovery analyses, and tissue imaging provides a robust framework for understanding drug-induced hepatic effects.

References

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