Influence of N-acetyltransferase 2 (NAT2) genotype/single nucleotide polymorphisms on clearance of isoniazid in tuberculosis patients: a systematic review of population pharmacokinetic models

Pharmacogenomic insights into tuberculosis treatment shows the NAT2 genetic variants linked to hepatotoxicity risk: a systematic review and meta-analysis

BACKGROUND

Tuberculosis (TB) patients undergoing anti-tuberculosis treatment often face serious adverse drug reactions, such as hepatotoxicity. Genetic variants of the N-acetyltransferase 2 (NAT2) gene have been linked to an increased risk of these toxic events.

OBJECTIVE

This study aims to provide a comprehensive evaluation of the evidence linking NAT2 genetic variants to anti-tuberculosis drug-related hepatotoxicity (ATDH).

METHOD

A comprehensive review and meta-analysis was performed by accessing databases such as PubMed, Scopus, and Web of Science. A total of 24 articles were incorporated into the dataset. Meta-analyses were conducted to gather estimates of the association between the slow acetlylators (SA) genotype and ATDH. The studies were stratified by ethnicity, regimen, genotyping methods, criteria for liver toxicity, and dosage. Also, meta-analysis for the specific SA type that was most likely responsible for the ATDH was also conducted.

RESULTS

The included studies showed individuals with a slow NAT2 acetylator had a significantly greater risk of experiencing hepatotoxicity ATDH (odds ratio [OR] 2.52 (95% CI: 1.95-3.27; p value < 0.001) compared to individuals with other types of acetylator (i.e., rapid and immediate). Among individuals with slow acetylator NAT2*5/7, NAT2*5/6, and NAT2*6/6 genotypes, there is a greater likelihood of association compared to other variations.

CONCLUSION

Our meta-analysis confirms a significant association between slow NAT2 acetylator and increased hepatotoxicity risk. The findings from the present underscore the potential of pharmacogenomic testing to improve TB treatment outcomes. By identifying patients with the slow acetylator NAT2 genotype, healthcare providers can predict an increased risk of anti-tuberculosis drug-induced hepatotoxicity. This allows for personalized treatment strategies, such as adjusting drug dosages or selecting alternative therapies, to minimize adverse effects and optimize efficacy.

Characteristics of isoniazid-induced psychosis: a systematic review of case reports and case series

PURPOSE

Isoniazid, a first-line antitubercular drug, is associated with nervous system adverse drug reactions such as seizures, peripheral neuropathy, and psychosis. This systematic review of case reports and case series aimed to characterize the demographic, social, and clinical factors associated with isoniazid-induced psychosis in patients with active tuberculosis (TB) and those who received isoniazid for latent TB infection (LTBI).

METHODS

We comprehensively searched the Embase, PubMed, and Scopus databases to identify relevant studies published between the date of inception of the database and June 2024.

RESULTS

A total of 28 studies, including 21 case reports and 7 case series involved 37 patients who developed isoniazid-induced psychosis. A higher frequency of isoniazid-induced psychosis was observed during the first 2 months of treatment, with a relatively early onset observed among patients aged 18 years or less. Delusions and/or hallucinations are the common symptoms of isoniazid-induced psychosis. Psychomotor disturbances, disorganized speech or formal thought disorder, disorganized or abnormal behaviour, and neuropsychiatric symptoms (sleep disturbances, hostility or aggression, confusion, affective symptoms, anxiety symptoms, and cognitive difficulties) were the other symptoms observed in the included studies. More than 80% of cases rechallenged with isoniazid resulted in the recurrence of psychotic symptoms.

CONCLUSION

Patients with TB and LTBI should be assessed for psychotic and neuropsychiatric symptoms during isoniazid therapy, mainly in the first 2 months. Further research is required to understand the impact of underlying risk factors, such as genetic predisposition and isoniazid pharmacokinetics, as well as the clinical utility and dosage recommendations of pyridoxine for managing isoniazid-induced psychosis.

Precision Medicine Strategies to Improve Isoniazid Therapy in Patients with Tuberculosis

Due to interindividual variability in drug metabolism and pharmacokinetics, traditional isoniazid fixed-dose regimens may lead to suboptimal or toxic isoniazid concentrations in the plasma of patients with tuberculosis, contributing to adverse drug reactions, therapeutic failure, or the development of drug resistance. Achieving precision therapy for isoniazid requires a multifaceted approach that could integrate various clinical and genomic factors to tailor the isoniazid dose to individual patient characteristics. This includes leveraging molecular diagnostics to perform the comprehensive profiling of host pharmacogenomics to determine how it affects isoniazid metabolism, such as its metabolism by N-acetyltransferase 2 (NAT2), and studying drug-resistant mutations in the Mycobacterium tuberculosis genome for enabling targeted therapy selection. Several other molecular signatures identified from the host pharmacogenomics as well as other omics-based approaches such as gut microbiome, epigenomic, proteomic, metabolomic, and lipidomic approaches have provided mechanistic explanations for isoniazid pharmacokinetic variability and/or adverse drug reactions and thereby may facilitate precision therapy of isoniazid, though further validations in larger and diverse populations with tuberculosis are required for clinical applications. Therapeutic drug monitoring and population pharmacokinetic approaches allow for the adjustment of isoniazid dosages based on patient-specific pharmacokinetic profiles, optimizing drug exposure while minimizing toxicity and the risk of resistance. Current evidence has shown that with the integration of the host pharmacogenomics-particularly NAT2 and Mycobacterium tuberculosis genomics data along with isoniazid pharmacokinetic concentrations in the blood and patient factors such as anthropometric measurements, comorbidities, and type and timing of food administered-precision therapy approaches in isoniazid therapy can be tailored to the specific characteristics of both the host and the pathogen for improving tuberculosis treatment outcomes.

Isoniazid-induced pancreatitis: A systematic review

BACKGROUND

Isoniazid-induced pancreatitis is a potentially serious adverse drug reaction, however, the frequency of its occurrence is unknown. We conducted a systematic review to explore this adverse drug reaction comprehensively.

METHODS

We performed an advanced search in PubMed, Web of Science, Scopus, Ovid, and Embase for studies that reported isoniazid-induced pancreatitis. From the extracted data of eligible cases, we performed a descriptive analysis and a methodological risk of bias assessment using a standardized tool.

RESULTS

We included 16 case reports from eight countries comprising 16 patients in our systematic review. Most of the isoniazid-induced pancreatitis cases were extrapulmonary tuberculosis cases. We found the mean age across all case reports was 36.7 years. In all the cases, discontinuation of isoniazid resulted in the resolution of pancreatitis.

CONCLUSIONS

We found the latency period for isoniazid-induced pancreatitis to be ranged from 12 to 45 days after initiation of isoniazid therapy. A low threshold for screening of pancreatitis by measuring pancreatic enzymes in patients on isoniazid presenting with acute abdominal pain is recommended. This would facilitate an early diagnosis and discontinuation of isoniazid, thus reducing the severity of pancreatitis and preventing the complications of pancreatitis.

Genetic Variation in CYP2D6, UGT1A4, SLC6A2 and SLCO1B1 Alters the Pharmacokinetics and Safety of Mirabegron

Mirabegron is a drug used in overactive bladder (OAB) treatment. Genetic variation in pharmacogenes might alter its pharmacokinetics, affecting its efficacy and safety. This research aimed to analyze the impact of genetic variation on mirabegron pharmacokinetics and safety. Volunteers from three bioequivalence trials (n = 79), treated with a single or a multiple dose of mirabegron 50 mg under fed or fasting conditions, were genotyped for 115 variants in pharmacogenes and their phenotypes were inferred. A statistical analysis was performed, searching for associations between genetics, pharmacokinetics and safety. CYP2D6 intermediate metabolizers showed a higher elimination half-life (t1/2) (univariate p-value (puv) = 0.018) and incidence of adverse reactions (ADRs) (puv = 0.008, multivariate p (pmv) = 0.010) than normal plus ultrarapid metabolizers. The UGT1A4 rs2011425 T/G genotype showed a higher t1/2 than the T/T genotype (puv = 0.002, pmv = 0.003). A lower dose/weight corrected area under the curve (AUC/DW) and higher clearance (CL/F) were observed in the SLC6A2 rs12708954 C/C genotype compared to the C/A genotype (puv = 0.015 and 0.016) and ADR incidence was higher when the SLCO1B1 function was decreased (puv = 0.007, pmv = 0.010). The lower elimination and higher ADR incidence when CYP2D6 activity is reduced suggest it might be a useful biomarker in mirabegron treatment. UGT1A4, SLC6A2 and SLCO1B1 might also be involved in mirabegron pharmacokinetics.

The synergy of artificial intelligence and personalized medicine for the enhanced diagnosis, treatment, and prevention of disease

INTRODUCTION

The completion of the Human Genome Project in 2003 marked the beginning of a transformative era in medicine. This milestone laid the foundation for personalized medicine, an innovative approach that customizes healthcare treatments.

CONTENT

Central to the advancement of personalized medicine is the understanding of genetic variations and their impact on drug responses. The integration of artificial intelligence (AI) into drug response trials has been pivotal in this domain. These technologies excel in handling large-scale genomic datasets and patient histories, significantly improving diagnostic accuracy, disease prediction and drug discovery. They are particularly effective in addressing complex diseases such as cancer and genetic disorders. Furthermore, the advent of wearable technology, when combined with AI, propels personalized medicine forward by offering real-time health monitoring, which is crucial for early disease detection and management.

SUMMARY

The integration of AI into personalized medicine represents a significant advancement in healthcare, promising more accurate diagnoses, effective treatment plans and innovative drug discoveries.

OUTLOOK

As technology continues to evolve, the role of AI in enhancing personalized medicine and transforming the healthcare landscape is expected to grow exponentially. This synergy between AI and healthcare holds great promise for the future, potentially revolutionizing the way healthcare is delivered and experienced.

Efficacy, safety, and pharmacokinetics of isoniazid affected by NAT2 polymorphisms in patients with tuberculosis: A systematic review

N-acetyltransferase 2 (NAT2) genetic polymorphisms might alter isoniazid metabolism leading to toxicity. We reviewed the impact of NAT2 genotype status on the pharmacokinetics, efficacy, and safety of isoniazid, a treatment for tuberculosis (TB). A systematic search for research articles published in Scopus, PubMed, and Embase until August 31, 2023, was conducted without filters or limits on the following search terms and Boolean operators: "isoniazid" AND "NAT2." Studies were selected if NAT2 phenotypes with pharmacokinetics or efficacy or safety of isoniazid in patients with TB were reported. Patient characteristics, NAT2 status, isoniazid pharmacokinetic parameters, early treatment failure, and the prevalence of drug-induced liver injury were extracted. If the data were given as a median, these values were standardized to the mean. Forty-one pharmacokinetics and 53 safety studies were included, but only one efficacy study was identified. The average maximum concentrations of isoniazid were expressed as supratherapeutic concentrations in adults (7.16 ± 4.85 μg/mL) and children (6.43 ± 3.87 μg/mL) in slow acetylators. The mean prevalence of drug-induced liver injury was 36.23 ± 19.84 in slow acetylators, which was significantly different from the intermediate (19.49 ± 18.20) and rapid (20.47 ± 20.68) acetylators. Subgroup analysis by continent showed that the highest mean drug-induced liver injury prevalence was in Asian slow acetylators (42.83 ± 27.61). The incidence of early treatment failure was decreased by genotype-guided isoniazid dosing in one study. Traditional weight-based dosing of isoniazid in most children and adults yielded therapeutic isoniazid levels (except for slow acetylators). Drug-induced liver injury was more commonly observed in slow acetylators. Genotype-guided dosing may prevent early treatment failure.

Model-Informed Precision Dosing of Isoniazid: Parametric Population Pharmacokinetics Model Repository

Introduction

Isoniazid (INH) is a crucial first-line anti tuberculosis (TB) drug used in adults and children. However, various factors can alter its pharmacokinetics (PK). This article aims to establish a population pharmacokinetic (popPK) models repository of INH to facilitate clinical use.

Methods

A literature search was conducted until August 23, 2022, using PubMed, Embase, and Web of Science databases. We excluded published popPK studies that did not provide full model parameters or used a non-parametric method. Monte Carlo simulation works was based on RxODE. The popPK models repository was established using R. Non-compartment analysis was based on IQnca.

Results

Fourteen studies included in the repository, with eleven studies conducted in adults, three studies in children, one in pregnant women. Two-compartment with allometric scaling models were commonly used as structural models. NAT2 acetylator phenotype significantly affecting the apparent clearance (CL). Moreover, postmenstrual age (PMA) influenced the CL in pediatric patients. Monte Carlo simulation results showed that the geometric mean ratio (95% Confidence Interval, CI) of PK parameters in most studies were within the acceptable range (50.00-200.00%), pregnant patients showed a lower exposure. After a standard treatment strategy, there was a notable exposure reduction in the patients with the NAT2 RA or nonSA (IA/RA) phenotype, resulting in a 59.5% decrease in AUC0-24 and 83.2% decrease in Cmax (Infants), and a 49.3% reduction in AUC0-24 and 73.5% reduction in Cmax (Adults).

Discussion

Body weight and NAT2 acetylator phenotype are the most significant factors affecting the exposure of INH. PMA is a crucial factor in the pediatric population. Clinicians should consider these factors when implementing model-informed precision dosing of INH. The popPK model repository for INH will aid in optimizing treatment and enhancing patient outcomes.

Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil

BACKGROUND

Tuberculosis (TB) treatment-related adverse drug reactions (TB-ADRs) can negatively affect adherence and treatment success rates.

METHODS

We developed prediction models for TB-ADRs, considering participants with drug-susceptible pulmonary TB who initiated standard TB therapy. TB-ADRs were determined by the physician attending the participant, assessing causality to TB drugs, the affected organ system, and grade. Potential baseline predictors of TB-ADR included concomitant medication (CM) use, human immunodeficiency virus (HIV) status, glycated hemoglobin (HbA1c), age, body mass index (BMI), sex, substance use, and TB drug metabolism variables (NAT2 acetylator profiles). The models were developed through bootstrapped backward selection. Cox regression was used to evaluate TB-ADR risk.

RESULTS

There were 156 TB-ADRs among 102 of the 945 (11%) participants included. Most TB-ADRs were hepatic (n = 82 [53%]), of moderate severity (grade 2; n = 121 [78%]), and occurred in NAT2 slow acetylators (n = 62 [61%]). The main prediction model included CM use, HbA1c, alcohol use, HIV seropositivity, BMI, and age, with robust performance (c-statistic = 0.79 [95% confidence interval {CI}, .74-.83) and fit (optimism-corrected slope and intercept of -0.09 and 0.94, respectively). An alternative model replacing BMI with NAT2 had similar performance. HIV seropositivity (hazard ratio [HR], 2.68 [95% CI, 1.75-4.09]) and CM use (HR, 5.26 [95% CI, 2.63-10.52]) increased TB-ADR risk.

CONCLUSIONS

The models, with clinical variables and with NAT2, were highly predictive of TB-ADRs.

Influence of N-acetyltransferase 2 polymorphisms and clinical variables on liver function profile of tuberculosis patients

BACKGROUND

Single nucleotide polymorphisms (SNPs) in the N-acetyltransferase 2 (NAT2) gene as well as several other clinical factors can contribute to the elevation of liver function test values in tuberculosis (TB) patients receiving antitubercular therapy (ATT).

RESEARCH DESIGN AND METHODS

A prospective study involving dynamic monitoring of the liver function tests among 130 TB patients from baseline to 98 days post ATT initiation was undertaken to assess the influence of pharmacogenomic and clinical variables on the elevation of liver function test values. Genomic DNA was extracted from serum samples for the assessment of NAT2 SNPs. Further, within this study population, we conducted a case control study to identify the odds of developing ATT-induced drug-induced liver injury (DILI) based on NAT2 SNPs, genotype and phenotype, and clinical variables.

RESULTS

NAT2 slow acetylators had higher mean [90%CI] liver function test values for 8-28 days post ATT and higher odds of developing DILI (OR: 2.73, 90%CI: 1.05-7.09) than intermediate acetylators/rapid acetylators.

CONCLUSION

The current study findings provide evidence for closer monitoring among TB patients with specific NAT2 SNPs, genotype and phenotype, and clinical variables, particularly between the period of more than a week to one-month post ATT initiation for better treatment outcomes.

Application of a physiologically based pharmacokinetic model to predict isoniazid disposition during pregnancy

Pregnancy can increase the risk of latent tuberculosis infection (LTBI) progression to tuberculosis (TB) disease. Isoniazid (INH) is the preferred preventative treatment for LTBI in pregnancy. INH is mainly cleared by N-acetyltransferase 2 (NAT2) but the pharmacokinetics (PK) of INH in different NAT2 phenotypes during pregnancy is not well characterized. To address this knowledge gap, we used physiologically based pharmacokinetic (PBPK) modeling to evaluate NAT2 phenotype-specific effects of pregnancy on INH disposition. A whole-body PBPK model for INH was developed and verified for non-pregnant NAT2 fast (FA), intermediate (IA), and slow (SA) acetylators. Model predictive performance was assessed using a drug-specific model acceptance criterion for mean plasma area under the curve (AUC) and peak plasma concentration (Cmax ), and the absolute average fold error (AAFE) for individual plasma concentrations. The verified model was extended to simulate INH disposition during pregnancy in NAT2 SA, IA, and FA populations. A sensitivity analysis was conducted using the verified PBPK model and known changes in INH disposition during pregnancy to determine whether NAT2 activity changes during pregnancy or other INH clearance pathways are altered. This analysis suggested that NAT2 activity is unchanged while other INH clearance pathways increase by ~80% during pregnancy. The model was applied to explore the effect of pregnancy on INH disposition in two ethnic populations with different NAT2 phenotype distributions and with high TB burden. Our PBPK model can be used to predict INH disposition during pregnancy in diverse populations and expanded to other drugs cleared by NAT2 during pregnancy.

Management of Polypharmacy and Potential Drug-Drug Interactions in Patients with Mycobacterial Infection: A 1-Year Experience of a Multidisciplinary Outpatient Clinic

In 2022, we opened an outpatient clinic for the management of polypharmacy and potential drug-drug interactions (pDDIs) in patients with mycobacterial infection (called GAP-MyTB). All patients who underwent a GAP-MyTB visit from March 2022 to March 2023 were included in this retrospective analysis. Fifty-two patients were included in the GAP-MyTB database. They were given 10.4 ± 3.7 drugs (2.8 ± 1.0 and 7.8 ± 3.9 were, respectively, antimycobacterial agents and co-medications). Overall, 262 pDDIs were identified and classified as red-flag (2%), orange-flag (72%), or yellow-flag (26%) types. The most frequent actions suggested after the GAP-MyTB assessment were to perform ECG (52%), therapeutic drug monitoring (TDM, 40%), and electrolyte monitoring (33%) among the diagnostic interventions and to reduce/stop proton pump inhibitors (37%), reduce/change statins (14%), and reduce anticholinergic burden (8%) among the pharmacologic interventions. The TDM of rifampicin revealed suboptimal exposure in 39% of patients that resulted in a TDM-guided dose increment (from 645 ± 101 to 793 ± 189 mg/day, p < 0.001). The high prevalence of polypharmacy and risk of pDDIs in patients with mycobacterial infection highlights the need for ongoing education on prescribing principles and the optimal management of individual patients. A multidisciplinary approach involving physicians and clinical pharmacologists could help achieve this goal.

EA, Udupa KS, Gota V, Mallayasamy S. Factors Influencing Pharmacokinetics of Tamoxifen in Breast Cancer Patients: A Systematic Review of Population Pharmacokinetic Models

BACKGROUND

Tamoxifen is useful in managing breast cancer and it is reported to have significant variability in its pharmacokinetics. This review aimed to summarize reported population pharmacokinetics studies of tamoxifen and to identify the factors affecting the pharmacokinetics of tamoxifen in adult breast cancer patients.

METHOD

A systematic search was undertaken in Scopus, Web of Science, and PubMed for papers published in the English language from inception to 20 August 2022. Studies were included in the review if the population pharmacokinetic modeling was based on non-linear mixed-effects modeling with a parametric approach for tamoxifen in breast cancer patients.

RESULTS

After initial selection, 671 records were taken for screening. A total of five studies were selected from Scopus, Web of Science, PubMed, and by manual searching. The majority of the studies were two-compartment models with first-order absorption and elimination to describe tamoxifen and its metabolites' disposition. The CYP2D6 phenotype and CYP3A4 genotype were the main covariates that affected the metabolism of tamoxifen and its metabolites. Other factors influencing the drug's pharmacokinetics included age, co-medication, BMI, medication adherence, CYP2B6, and CYP2C19 genotype.

CONCLUSION

The disposition of tamoxifen and its metabolites varies primarily due to the CYP2D6 phenotype and CYP3A4 genotype. However, other factors, such as anthropometric characteristics and menopausal status, should also be addressed when accounting for this variability. All these studies should be externally evaluated to assess their applicability in different populations and to use model-informed dosing in the clinical setting.