Importance of Clinical Pharmacogenetic-Pharmacokinetic Studies in Unravelling Determinants of Tuberculosis Treatment Outcomes: Findings and Implications in Latvia

Viktorija Igumnova, Agnija Kivrane, Anda Vīksna, Lauma Freimane, Darja Sadovska, Valentīna Čapligina, Leonora Pahirko, Iveta Ozere, Inga Norvaiša, Ineta Bogdanova, Alvils Krams, Andra Cīrule, Osvalds Pugovičs, Solveiga Grīnberga, Eduards Sevostjanovs, Dace Bandere, Renāte Ranka

Research output: Contribution to journalMeeting Abstractpeer-review


Background. Personalized medicine and therapeutic drug monitoring (TDM) strategies could be highly important to improve the effectiveness of anti-tuberculosis (anti-TB) therapy. Several drug-metabolizing enzymes exhibit genetic variations leading to deviations of plasma concentrations of anti-TB drugs,
however, associations between genetic polymorphisms, metabolic ratio and treatment outcome are not entirely clear.
Aim. The aim of this study was to determine the predictors of treatment outcome by kinetic measurements of isoniazid (INH) and its major metabolite etylisoniazid (AcINH) in blood plasma and genotyping analysis of two drug-metabolizing enzymes involved in the INH pharmacokinetic pathway.
Methods. Human DNA and plasma samples were obtained from TB patients (n=33) admitted to the Centre of Tuberculosis and Lung Diseases. Plasma levels of INH and AcINH were measured using Liquid Chromatography-Tandem Mass Spectrometry at 0, 2 h, and 6 h time points after medication administration. Patient N-acetyltransferase 2 (NAT2) phenotype (slow acetylator, SA; intermediate acetylator, IA) was assigned based on the obtained genotyping data using 7-SNP panel identification. Glutation-S-transferase M1 class (GSTM1) class null/plus genotype assay was carried out by a comparative duplex PCR. Timeto-event analysis was applied to analyse time to sputum culture conversion (tSCC) denoted by treatment success. In each NAT2 subgroup, Cox proportional hazards model was used to estimate hazard rate ratios of treatment success time adjusted for INH/AcINH metabolic ratio (MR).
Results. Treatment was successful in 21 patients, 12 were considered as censored. The median tSCC was 65, 65, 56 and 112 days for IA/null, SA/null, IA/plus and SA/plus genotypes, respectively. The mean MR (±SD) was 0.55±0.14, 2.59±0.96, 0.61±0.14 and 2.66±1.14 for genotype groups. No statistically significant differences between cumulative probability curves of tSCC were observed p=0.13). In the Cox model for SA genotype, global log-rank p=0.004 and concordance index was 0.76. The odds of SA/null carrier to achieve treatment success before SA/plus carrier was 5.65 (CI 1.09, 29.30), p=0.039; probability
of SA/null carrier to heal first was equal to 0.85. One unit increase of individual’s MR lowers the odds of achieving treatment success prior to the individual with one-unit lower MR (HR 0.36, (CI 0.16, 0.85), p=0.019); probability to heal first was 0.26.
Conclusion. Genotyping and TDM approach could be beneficial for implementation of personalised care for TB, and further research is needed to increase the level of evidence supporting dose adjustment strategies.
Acknowledgements. The authors declare the absence of conflict of interest. This study was supported by the Latvian Council of Science, project No. lzp-2020/1-0050.

Field of Science*

  • 3.1 Basic medicine

Publication Type*

  • 3.4. Other publications in conference proceedings (including local)


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