Frontiers in Pharmacology (Mar 2024)

Effect of NAT2, GSTM1 and CYP2E1 genetic polymorphisms on plasma concentration of isoniazid and its metabolites in patients with tuberculosis, and the assessment of exposure-response relationships

  • Viktorija Ulanova,
  • Viktorija Ulanova,
  • Agnija Kivrane,
  • Agnija Kivrane,
  • Anda Viksna,
  • Anda Viksna,
  • Leonora Pahirko,
  • Lauma Freimane,
  • Darja Sadovska,
  • Darja Sadovska,
  • Iveta Ozere,
  • Iveta Ozere,
  • Andra Cirule,
  • Eduards Sevostjanovs,
  • Solveiga Grinberga,
  • Dace Bandere,
  • Renate Ranka,
  • Renate Ranka

DOI
https://doi.org/10.3389/fphar.2024.1332752
Journal volume & issue
Vol. 15

Abstract

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Objectives: Isoniazid is a key drug in the chemotherapy of tuberculosis (TB), however, interindividual variability in pharmacokinetic parameters and drug plasma levels may affect drug responses including drug induced hepatotoxicity. The current study investigated the relationships between isoniazid exposure and isoniazid metabolism-related genetic factors in the context of occurrence of drug induced hepatotoxicity and TB treatment outcomes.Methods: Demographic characteristics and clinical information were collected in a prospective TB cohort study in Latvia (N = 34). Time to sputum culture conversion (tSCC) was used as a treatment response marker. Blood plasma concentrations of isoniazid (INH) and its metabolites acetylisoniazid (AcINH) and isonicotinic acid (INA) were determined at three time points (pre-dose (0 h), 2 h and 6 h after drug intake) using liquid chromatography-tandem mass spectrometry. Genetic variations of three key INH-metabolizing enzymes (NAT2, CYP2E1, and GSTM1) were investigated by application PCR- and Next-generation sequencing-based methods. Depending on variables, group comparisons were performed by Student’s t-test, one-way ANOVA, Mann-Whitney-Wilcoxon, and Kruskal-Wallis tests. Pearson correlation coefficient was calculated for the pairs of normally distributed variables; model with rank transformations were used for non-normally distributed variables. Time-to-event analysis was performed to analyze the tSCC data. The cumulative probability of tSCC was obtained using Kaplan-Meier estimators. Cox proportional hazards models were fitted to estimate hazard rate ratios of successful tSCC.Results: High TB treatment success rate (94.1%) was achieved despite the variability in INH exposure. Clinical and demographic factors were not associated with either tSCC, hepatotoxicity, or INH pharmacokinetics parameters. Correlations between plasma concentrations of INH and its metabolites were NAT2 phenotype-dependent, while GSTM1 genetic variants did not showed any effects. CYP2E1*6 (T > A) allelic variant was associated with INH pharmacokinetic parameters. Decreased level of AcINH was associated with hepatotoxicity, while decreased values of INA/INH and AcINH/INH were associated with month two sputum culture positivity.Conclusion: Our findings suggest that CYP2E1, but not GSTM1, significantly affects the INH pharmacokinetics along with NAT2. AcINH plasma level could serve as a biomarker for INH-related hepatotoxicity, and the inclusion of INH metabolite screening in TB therapeutic drug monitoring could be beneficial in clinical studies for determination of optimal dosing strategies.

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