The Role of N-Acetyl Transferases on Isoniazid Resistance from Mycobacterium tuberculosis and Human: An In Silico Approach

Transforming Pharmacogenomics and CRISPR Gene Editing with the Power of Artificial Intelligence for Precision Medicine

Background: Advancements in pharmacogenomics, artificial intelligence (AI), and CRISPR gene-editing technology are revolutionizing precision medicine by enabling highly individualized therapeutic strategies. Artificial intelligence-driven computational techniques improve biomarker discovery and drug optimization while pharmacogenomics helps to identify genetic polymorphisms affecting medicine metabolism, efficacy, and toxicity. Genetically editing based on CRISPR presents a precise method for changing gene expression and repairing damaging mutations. This review explores the convergence of these three fields to enhance improved precision medicine. Method: A methodical study of the current literature was performed on the effects of pharmacogenomics on drug response variability, artificial intelligence, and CRISPR in predictive modeling and gene-editing applications. Results: Driven by artificial intelligence, pharmacogenomics allows clinicians to classify patients and select the appropriate medications depending on their DNA profiles. This reduces the side effect risk and increases the therapeutic efficacy. Precision genetic modifications made feasible by CRISPR technology improve therapy outcomes in oncology, metabolic illnesses, neurological diseases, and other fields. The integration of artificial intelligence streamlines genome-editing applications, lowers off-target effects, and increases CRISPR specificity. Notwithstanding these advances, issues including computational biases, moral dilemmas, and legal constraints still arise. Conclusions: The synergy of artificial intelligence, pharmacogenomics, and CRISPR alters precision medicine by letting customized therapeutic interventions. Clinically translating, however, hinges on resolving data privacy concerns, assuring equitable access, and strengthening legal systems. Future research should focus on refining CRISPR gene-editing technologies, enhancing AI-driven pharmacogenomics, and developing moral guidelines for applying these tools in individualized medicine going forward.

Determination of NAT2 Genotypes in a Cohort of Patients with Suspected TB in the State of Rio de Janeiro

The human N-acetyltransferase 2 enzyme, encoded by the NAT2 gene, plays an important role in the metabolism of isoniazid, the main drug used to treat tuberculosis. The interindividual variation in the response of patients to drug treatment for tuberculosis may be responsible for the occurrence of unfavorable outcomes. The presence of polymorphisms in genes associated with the metabolism and transport of drugs, receptors, and therapeutic targets has been identified as a major determinant of this variability. The objective of this study was to identify the genetic profile of NAT2 in the study population. Using the obtained genomic DNA followed by PCR amplification and sequencing, the frequency of nine SNPs as well as alleles associated with slow (47.9%), intermediate (38.7%), and fast acetylation phenotypes (11.3%), in addition to those whose phenotype has not yet been characterized (2.1%), was estimated. The NAT2*5B allele was identified more frequently (31.3%). The description of SNPs in pharmacogenes and the establishment of their relationship with the pharmacokinetics of an individual offer an individualized approach that allows us to reduce the unfavorable outcomes of a therapy, ensure better adherence to treatment, prevent the emergence of MDR strains, reduce the cost of treatment, and improve the quality of patients' lives.

NAT2 polymorphism and clinical factors that increased antituberculosis drug-induced hepatotoxicity

Aim: Hepatotoxicity is a known adverse effect of antituberculosis drugs. The NAT2 gene polymorphism has been associated with an increased risk of antituberculosis drug-induced hepatotoxicity (ATDIH). Materials and methods: This study investigates the association of NAT2 polymorphism and clinical risk factors that may contribute to the development of ATDIH. The authors sequenced the NAT2 region of 33 tuberculosis patients who developed ATDIH and 100 tuberculosis patients who did not develop ATDIH during tuberculosis treatment. NAT2 haplotypes were inferred and NAT2 acetylator status was predicted from the combination of the inferred haplotypes. Multiple logistic regression was performed to identify possible factors that are associated with ATDIH. Results: The TT genotype of NAT2*13A and the AA genotype of NAT2*6B were found to be substantially linked with the risk of ATDIH, with odds ratios of 3.09 (95% CI: 1.37-6.95) and 3.07 (95% CI: 1.23-7.69), respectively. NAT2 slow acetylators are 3.39-times more likely to develop ATDIH. Factors that were associated with ATDIH include underlying diabetes mellitus (adjusted odds ratio [AOR] 2.96; 95% CI: 1.05-8.37), pre-treatment serum bilirubin (AOR 1.09; 95% CI: 1.02-1.16) and NAT2 slow acetylator (AOR 3.77; 95% CI: 1.51-9.44). Conclusion: Underlying diabetes mellitus, having a higher baseline bilirubin and being a slow acetylator are identified as the risk factors associated with ATDIH among patients in Malaysia.

Phenylisoxazole-3/5-Carbaldehyde Isonicotinylhydrazone Derivatives: Synthesis, Characterization, and Antitubercular Activity

Eight new phenylisoxazole isoniazid derivatives, 3-(2′-fluorophenyl)isoxazole-5-carbaldehyde isonicotinylhydrazone (1), 3-(2′-methoxyphenyl)isoxazole-5-carbaldehyde isonicotinylhydrazone (2), 3-(2′-chlorophenyl)isoxazole-5-carbaldehyde isonicotinylhydrazone (3), 3-(3′-clorophenyl)isoxazole-5-carbaldehyde isonicotinylhydrazone (4), 3-(4′-bromophenyl)isoxazole-5-carbaldehyde isonicotinylhydrazone (5), 5-(4′-methoxiphenyl)isoxazole-3-carbaldehyde isonicotinylhydrazone (6), 5-(4′-methylphenyl)isoxazole-3-carbaldehyde isonicotinylhydrazone (7), and 5-(4′-clorophenyl)isoxazole-3-carbaldehyde isonicotinylhydrazone (8), have been synthesized and characterized by FT-IR, 1H-NMR, 13C-NMR, and mass spectral data. The 2D NMR (1H-1H NOESY) analysis of 1 and 2 confirmed that these compounds in acetone-d6 are in the trans(E) isomeric form. This evidence is supported by computational calculations which were performed for compounds 1–8, using DFT/B3LYP level with the 6-311++G(d,p) basis set. The in vitro antituberculous activity of all the synthesized compounds was determined against the Mycobacterium tuberculosis standard strains: sensitive H37Rv (ATCC-27294) and resistant TB DM97. All the compounds exhibited moderate bioactivity (MIC = 0.34–0.41 μM) with respect to the isoniazid drug (MIC = 0.91 μM) against the H37Rv sensitive strain. Compounds 6 (X = 4′-OCH3) and 7 (X = 4′-CH3) with MIC values of 12.41 and 13.06 μM, respectively, were about two times more cytotoxic, compared with isoniazid, against the resistant strain TB DM97.

Acetylator Status Among Newly Diagnosed and Recurrent Tuberculosis Patients from Kupang, Eastern Part of Indonesia

Purpose

N-acetyltransferase-2 enzyme in the liver, encoded by NAT2 gene, plays a central role in metabolizing tuberculosis (TB) drug isoniazid (INH). Low compliance of patients toward six-month TB therapy and internal host factors, ie comorbid diseases, immune status, and genetic profiles, are factors leading to treatment failure and recurrence of pulmonary TB infection. This study aimed to explore the NAT2 acetylator status among newly diagnosed and recurrent pulmonary TB patients in eastern part of Indonesia.

Patients and Methods

Archived DNA of TB patients (n=124) and healthy controls (n=124) were sequenced, and NAT2 acetylator status was determined, then categorized as fast, intermediate, or slow acetylators. Pulmonary TB patients who had no previous TB treatment history were designated as newly diagnosed pulmonary TB, whereas patients with a history of TB treatment were designated as recurrent pulmonary TB. The demographic, clinical, and microbiological data between pulmonary TB groups were compared, and acetylator status was described among groups.

Results

Male was more significantly prevalent in the recurrent pulmonary TB group (p=0.025), and anemia was more prevalent in new pulmonary TB (p=0.003). The acetylator status in pulmonary TB patients compared to healthy controls were rapid (33.9% vs 48.1%), intermediate (57.8% vs 33.0%), and slow acetylators (8.3% vs 18.9%), respectively. Interestingly, the rapid and intermediate acetylator were significantly more prevalent in pulmonary TB patients than in healthy controls (p=0.023, OR=2.58 (1.12–5.97). Furthermore, no differences were found in acetylator status between new and recurrent pulmonary (p=0.776).

Conclusion

Rapid and intermediate acetylators status predominated the pulmonary TB patients in Kupang, eastern part of Indonesia, postulating different genetic makeup in this area. As the pulmonary TB patients in Kupang exhibit more rapid acetylator phenotype, the acetylator status might be relevant to be checked before TB therapy for adjusting treatment dose to prevent drug resistances.

Development of a limited sampling strategy for the estimation of isoniazid exposure considering N-acetyltransferase 2 genotypes in Korean patients with tuberculosis

A limited sampling strategy (LSS) to estimate the exposure to isoniazid was developed considering N-acetyltransferase 2 (NAT2) genotypes in Korean patients with tuberculosis. The influence of the genotypes on the pharmacokinetics of isoniazid was also evaluated. A total of 33 participants participated in the study and received isoniazid 300 mg once daily. Evaluable participants consist of ten slow (SA), fourteen intermediate (IA) and six rapid acetylators (RA). As expected, isoniazid exposure was higher (mean AUC, 28.4 versus 7.6 mg*h/L) and systemic clearance lower (mean apparent clearance, 14.8 versus 50.6 L/h) in SAs than RAs. The formulas to estimate isoniazid exposure were constructed using one or more concentration-time points that correlate with the area under the concentration-time curve (AUC). The LSS using a formula of single concentration-time point at 4 h post dose (C₄) is applicable for all acetylators to the therapeutic drug monitoring (TDM) of isoniazid in patients with tuberculosis when evaluated using the Deming regression and Bland-Altman plot (AUC = 1.53 + 10.03*C₄, adjusted r² = 0.95, p < 0.001). Considering that SAs are more prone to adverse effects, pre-dose NAT2 genotyping would be valuable for optimal isoniazid dosing in conjunction with TDM.

Genetic characterization of N-acetyltransferase 2 variants in acquired multidrug-resistant tuberculosis in Indonesia

Background: Owing to the high resistance rate of tuberculosis (TB) to isoniazid, which is metabolized by N-acetyltransferase 2 (NAT2), we investigated the associations between NAT2 variants and multidrug-resistant (MDR)-TB. Materials & methods: The acetylator status based on NAT2 haplotypes of 128 patients with MDR-TB in Indonesia were compared with our published data from patients with anti-TB drug-induced liver injury (AT-DILI), TB and the general population. Results: NAT2*4 was more frequent in the MDR-TB group than in the AT-DILI group, TB controls and general controls. NAT2*4/*4 was significantly more frequent in patients with MDR-TB than in those with AT-DILI. NAT2*5B/7B, *6A/6A and *7B/*7B were detected at lower frequencies in patients with AT-DILI. Rapid acetylators were significantly more frequent in patients with MDR-TB than in those with AT-DILI. Conclusion: These results provide an initial data for optimizing TB treatment in the Indonesian population, and suggest that NAT2 genotyping may help to select appropriate treatment by predicting TB-treatment effect.

Benefits of Therapeutic Drug Monitoring of First Line Antituberculosis Drugs

Tuberculosis is an airborne infectious disease that remains a huge global health-related issue nowadays. Despite constant approvals of newly developed drugs, the use of first-line antituberculosis medicines seems reasonable in drug-susceptible Mycobacterium tuberculosis strains. Therapeutic drug monitoring presents a useful technique for the determination of plasma drug concentration to adjust appropriate dose regimes. In tuberculosis treatment, therapeutic drug monitoring is aiding clinicians in selecting an optimal therapeutic level, which is essential for the personalisation of therapy. This review is aimed at clarifying the use of therapeutic drug monitoring of the first-line antituberculosis drugs in routine clinical practice.