CYP3A4 and CYP2C19 genetic polymorphisms and myricetin interaction on tofacitinib metabolism

Zhize Ye1, Hailun Xia2, Jinyu Hu2

  • 1The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Shaoxing People's Hospital, Shaoxing, Zhejiang, China.

Insights

Genetic variations and myricetin significantly impact tofacitinib metabolism. This research provides crucial data for personalized rheumatoid arthritis treatment strategies.

Area of Science:

  • Pharmacology
  • Genetics
  • Drug Metabolism

Background:

  • Rheumatoid arthritis (RA) is a chronic autoimmune disease managed with drugs like tofacitinib.
  • Understanding tofacitinib metabolism is crucial for optimizing RA treatment.
  • Genetic variations in drug-metabolizing enzymes can alter drug efficacy and safety.

Purpose of the Study:

  • To investigate the impact of recombinant CYP2C19 and CYP3A4 variants on tofacitinib metabolism.
  • To analyze the in vitro interaction between tofacitinib and myricetin.
  • To provide data for precise tofacitinib application in RA patients.

Main Methods:

  • Utilized a recombinant human CYP2C19 and CYP3A4 system to assess tofacitinib metabolism.
  • Quantified the main metabolite, M9, using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS).
  • Performed in vitro inhibition assays with myricetin in rat and human liver microsomes, and specific CYP variants.

Main Results:

  • Eleven CYP2C19 variants significantly altered M9 levels compared to CYP2C19.1, with 10 showing decreases.
  • Eleven CYP3A4 variants significantly altered M9 levels compared to CYP3A4.1.
  • Myricetin exhibited non-competitive inhibition in RLM and HLM, competitive inhibition in CYP3A4.18, and mixed inhibition in CYP3A4.1 and CYP3A4.28.

Conclusions:

  • Gene polymorphisms in CYP2C19 and CYP3A4 significantly affect tofacitinib metabolism.
  • Myricetin interacts with tofacitinib metabolism through various inhibition mechanisms.
  • Findings support personalized tofacitinib dosing strategies based on genetic profiles and potential drug interactions.

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