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GSTT1/GSTM1 Genotype and Anti-Tuberculosis Drug-Induced Hepatotoxicity in Peruvian Patients

Luis Jaramillo-Valverde
Kelly S. Levano
David D. Tarazona
Andres Vasquez-Dominguez
Anel Toledo-Nauto
Silvia Capristano
Cesar Sanchez
Eduardo Tarazona-Santos
Cesar Ugarte-Gil
5,6 and
Heinner Guio
Laboratorio de Biotecnología y Biología Molecular, Instituto Nacional de Salud, Lima 15046, Peru
School of Medicine, Universidad Continental, Lima 15046, Peru
INBIOMEDIC Research and Technological Center, Lima 15046, Peru
Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
School of Medicine, Universidad Peruana Cayetano Heredia, Lima 15102, Peru
School of Medicine, Universidad Cientifica del Sur, Lima 15067, Peru
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(19), 11028;
Submission received: 15 August 2022 / Revised: 9 September 2022 / Accepted: 13 September 2022 / Published: 20 September 2022
(This article belongs to the Special Issue Pharmacogenomics 2.0)


In Peru, 24,581 people were diagnosed with tuberculosis (TB) in 2020. Although TB treatments are effective, 3.4–13% are associated with significant adverse drug reactions (ADRs), with drug-induced liver injury (DILI) considered the most predominant. Among the first-line antituberculosis drugs, isoniazid (INH) is the main drug responsible for the appearance of DILI. In the liver, INH is metabolized by the enzymes N-acetyltransferase-2 (NAT2), cytochrome P450 2E1 (CYP2E1), and glutathione S-transferase (GST) with two isoforms, GSTT1 and GSTM1. Based on previous studies, we hypothesized that interactions between the GSTT1 and GSTM1 null genotypes induce DILI in TB patients. In this cross-sectional study of 377 participants who completed their anti-TB treatment, we genotyped by revealing the presence or absence of 215- and 480-bp bands of GSTM1 and GSTT1, respectively. We found that the prevalence of the GSTM1 genotype was 52.79% and 47.21% for presence and null, respectively, and for GSTT1 it was 69.76% and 30.24% for presence and null, respectively. Neither genotype was prevalent in the patients who developed DILI (n = 16). We did not confirm our hypothesis; however, we found that the combination of GSTM1 present genotype, GSTT1 null genotype, fast NAT2 acetylators, and CYP2E1 c1/c1 genotype had a significant risk for the development of ADR (OR 11; p = 0.017; 95% CI: (0.54–186.35)). We propose that the presence of the GSTM1 present genotype, GSTT1 null genotype, fast NAT2 acetylators, and CYP2E1 c1/c1 genotype in the Peruvian population could be considered a risk factor for the development of ADR due to therapeutic drug intake.

1. Introduction

At the liver level, isoniazid (INH) is acetylated by N-acetyltransferase-2 (NAT2) to acetylhydrazine, and then oxidized to toxic intermediates by the enzyme cytochrome P450 2E1 (CYP2E1) [1]. The enzymes NAT2 and glutathione S-transferase (GST) participate in the detoxification of these toxic compounds produced through acetylation and conjugation mechanisms, respectively. Some risk factors for adverse drug reactions (ADRs) have already been reported, such as coinfection with human immunodeficiency virus (HIV), hepatitis B and C, advanced age, and female gender [2,3]; however, they vary according to the genetic population characteristics of the people.
For this reason, it is necessary to study genetic factors and their consequences in treatment. In antituberculosis treatment, acetylation by NAT2, followed by oxidation by CYP2E1, is considered a candidate process for the generation of hydrazine, which is a reactive metabolite [4]. Some studies suggest that genetic polymorphisms in NAT2 and CYP2E1 are associated with ADRs [5]. However, other studies do not reach this conclusion [6,7].
The detoxification of INH metabolites is very important, and the enzymes GSTM1 and GSTT1 are essential in this process; this is because the enzyme GST catalyzes the conjugation of species with glutathione [8]. Glutathione undergoes nucleophilic attack and is catalyzed by GST, converting it to electrophilic substrates, reducing the reactivity in cellular macromolecules with potential toxic compounds [9]. Two highly polymorphic GST isoforms have been reported: on chromosome 1p13.3 the GTM1 gene encodes the GSTµ isoform and on chromosome 22q11.2 the GSTT1 gene encodes the GSTθ isoform [10]. It has been reported that the enzymatic activity loses its function when homozygous deletions are present in GSTM1 and GSTT1, causing the loss of glutathione [11].
The GSTM1 and GSTT1 null genotypes have been associated with the presence of ADRs in some studies; however, there is still no consensus on this. Previous studies revealed an association between the presence of ADRs and the null or deleted genotype of GSTM1 [12,13]; however, this association has been ruled out by more recent studies [14,15]. Similarly, few studies have reported an association between GSTT1 null genotypes and ADRs [15], while a few others find no statistically significant association [13,14,16]. Therefore, the role of the GST polymorphism in the development of ADRs remains unclear among diverse populations, and even more so among ethnic groups.
Individual and population behavior is influenced by genetic–environmental factors; therefore, in order to understand human genetic variations, it is important to study human genetic diversity through its geographic distribution [17]. That is the value of studying the American population with a pharmacogenomic approach due to the interethnic mixture [18]. For this reason, pharmacogenomics is aimed at understanding how pharmacological therapy is affected by our genetic diversity, identifying the genotype of an individual to predict their metabolism against different drugs, maximizing the probability of treatment success, and minimizing the presence of adverse reactions; this is framed as personalized medicine [19,20,21]. Although metabolic genotypes and phenotypes have been extensively studied in Caucasian and Asian populations, this information is still lacking in most Latin American populations. Only three investigations related to pharmacogenomics have analyzed native Peruvian samples [22,23,24]. With the high prevalence of tuberculosis (TB) in Peru, research is focusing on demonstrating the role of pharmacogenomics in the treatment of TB, starting with the determination of the genetic polymorphisms that affect the drugs INH and RIF and, in this way, affect efficient treatment and collaborate with the appearance of adverse effects. In the previous study, we reported NAT2 and CYP2E1 data in other populations of the American continent and the rest of the world [24].
The objective of this study is to determine the prevalence of, and evaluate the association between, the genetic polymorphisms of GSTM1 and GSTT1 and the presence of ADRs. The identification of genetic markers to predict the susceptibility to develop ADRs should serve to improve the management and control of TB. The current study is also important in terms of the great challenges in treating the high incidence of tuberculosis in our country. Peru is made up of diverse ethnic origins which lead to the presence of genetic heterogeneity [25]. To the best of our knowledge, this is the first study to identify GST gene polymorphisms as plausible risk factors in the development of anti-TB drug toxicity in the Peruvian population.

2. Results

No patient was excluded from the study. This cohort was predominantly male (55%). A total of 16 out of 377 participants (4.1%) were diagnosed with DILI, a mild ADR type with symptoms that included nausea and vomiting/gastric pain. Table 1 shows the frequency distribution of both biological and clinical variables.
The prevalence of GSTM1 genotypes in the study population was 52.79% and 47.21% for presence and null, respectively. In the case of GSTT1, the prevalence of genotypes was 69.76% and 30.24% for presence and null, respectively.
On the other hand, the GSTM1 and GSTT1 genotypes were not associated with DILI, and the allelic frequencies of both groups (with and without adverse reaction) were similar and were in Hardy–Weinberg equilibrium (p > 0.05), which suggests that these samples belonged to a population in genetic equilibrium. The chi-square test or, when necessary, Fisher’s exact test was used.
In Table 2, there is no association between the frequencies of genotypes and DILI. There is no evidence that the presence of variant genotypes of GSTM1, GSTT1, or their interaction, can become isolated risk or protective factors for developing ADRs during TB treatment (p > 0.05).
When the effects of combining GSTM1, GSTT1, and CYP2E1 genotypes and NAT2 acetylator status were examined, it was found that patients who were genotype present GSTM1, genotype null GSTT1, fast NAT2 acetylators, and had genotype CYP2E1 c1/c1 had a significant risk (OR = 11; p = 0.017) for the development of DILI compared to the most prevalent combination between GSTM1, GSTT1, NAT2 and CYP2E1 genotypes (Table 3).

3. Discussion

GST is an important component of phase II drug-metabolizing enzymes involved in the removal of toxic metabolites. There are several isoforms of the GST gene; the GSTM1 and GSTT1 genotypes are highly polymorphic among various ethnic groups, as well as within relatively homogeneous ethnic groups [26,27].
Our study in the Peruvian population analyzed the association between GSTM1/GSTT1 genotypes and hepatotoxicity induced by anti-TB drugs. Absence of GSTM1 and GSTT1 activity caused by homozygous null mutations or deletions has been implicated in liver injury due to lack of protection against oxidative species [28]. The frequencies of GSTM1 and GSTT1 homozygous null genotypes in this study were in agreement with other studies in the Brazilian population [6], demonstrating the consistency of our data.
In the total population, the GSTT1 present genotype was the most prevalent (69.76%), and there was no significant difference between patients with and without adverse reaction to TB, which is consistent with other reported studies [14,28]; however, a study conducted in Caucasians found a significant association between GSTT1 null genotypes and antituberculosis drug-induced hepatotoxicity (p = 0.03) [15].
The number of patients with null GSTM1 genotypes with adverse reactions was higher than that of patients with present genotype GSTM1 with adverse reaction; although we did not observe a significant association between null genotypes of GSTM1 and anti-TB DILI, as reported in a few other studies [14,29]. As we saw earlier, GSTM1 genotypes are highly polymorphic or variable between different ethnic groups, even within relatively homogeneous ethnic groups [26].
The combined deletion of the GSTM1 and GSTT1 gene has been reported in previous studies [30,31]. In the present study, the percentage of individuals with both GSTM1 and GSTT1 null mutations was higher in DILI total patients (6%); however, no statistically significant difference was found, in agreement with previous studies that did not find a significant association for GSTM1 null and GSTT1 null in Indian (p = 0.39) and Caucasian (p = 0.17) patients with the presence of anti-TB DILI [14,15].
This study is the first to our knowledge that examines the effects of combining GSTM1, GSTT1, and CYP2E1 genotypes, NAT2 acetylator status, and the presence of adverse reactions in the Peruvian population. This study found an interesting result: the present GSTM1 genotype, GSTT1 null genotype, fast NAT2 acetylators, and CYP2E1 c1/c1 genotype had a significant risk for the development of ADR and is suspected to be a risk factor for INH-induced hepatotoxicity.
Few studies have observed the relationship between GST genotypes and hepatotoxicity induced by antituberculosis drugs [12,15,32]. For example, Roy et al. (2001) have observed a significant association between the GSTM1 homozygous null genotype and anti-tuberculous drug-induced hepatotoxicity in Indian tuberculosis patients. Huang et al. (2007) have found similar results in a Chinese population. However, the presence of the GSTT1 homozygous null genotype was similar between cases and controls in both studies.
On the other hand, the same analysis in Spanish patients with TB showed an opposite effect; the homozygous null GSTT1 genotype was highly associated with anti-TB drug-induced hepatotoxicity, and no significant associations were found between the homozygous null GSTM1 genotype and hepatotoxicity [15]. This difference can be explained because concentrations of antituberculosis drugs and genetic polymorphisms vary significantly between populations and/or individuals [33].
In addition, the information obtained in the present study contributes to affirm that the allelic frequency of GSTM1 and GSTT1 is different according to the geographic location of the populations [34]. This reinforces the importance of pharmacogenomic studies in an ethnically diverse population such as Peru. Due to the controversy presented by the association between GSTM1GSTT1 polymorphisms and ADRs, three meta-analysis studies revealed that there is a significant risk of ADRs attributed only to the GSTM1 null genotype [28,35,36].
This discrepancy could be due to differences in the study designs of the compared projects, as well as in the ethnic origin of the populations studied; additionally, it could be attributed to several factors, such as different metabolism rate and disposition, ability to detoxify xenobiotics, susceptibility to certain diseases, socioeconomic status, and different acquired lifestyle. Furthermore, more studies with a larger population size are needed to confirm our findings [5].
This study also had the limitations of an observational study with tuberculosis patients attending a routine healthcare setting. Drug-related exposures recorded by the treating physician were analyzed. The incidence of hepatotoxicity induced by antituberculosis drugs is very low; however, our study was multicentered to better represent the population studied and to include as many cases of DILI as possible. Therefore, a prospective cohort study in TB patients with or without ADRs could confirm our findings.

4. Methods and Materials

Studied population and participants: Our study included 377 unrelated individuals, a subgroup of patients diagnosed with pulmonary tuberculosis between 2014 and 2015, recruited from health establishments of the Minister of Health (MINSA) located in Lima and Callao-Perú using previously collected data [24].
The inclusion criteria were patients: (i) with daily treatments of isoniazid, rifampicin, pyrazinamide and ethambutol for 2 months, followed by 4 months treatment of isoniazid and rifampicin, with drug dosages calculated according to bodyweight; (ii) with normal serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and bilirubin levels, no symptoms related to abnormal liver function (i.e., jaundice) prior to anti-TB drug treatment, and close monitoring of changes in liver function within 2 months of treatment; and (iii) with and without hepatotoxicity during drug treatment.
Patients with any of the following conditions were excluded from the study: (i) malnutrition; (ii) human immunodeficiency virus type 1 (HIV) infection; (iii) alcoholic liver disease or habitual drinking; (iv) hepatitis B or C infection, liver disease, systemic diseases and/or treatment with drugs other than the anti-TB drugs that can induce hepatotoxicity. All 377 participants (207 males and 170 females) completed their anti-TB treatment.
Patient Consent Statement: This study was approved by the Ethics in Research Committee of the Peruvian National Institute of Health (OI-087-13) and by Universidad Peruana Cayetano Heredia (SIDISI: 201091). Informed consent was obtained from all the participants.
Study design and data collection: This was a cross-sectional and observational study, with 377 tuberculosis patients, of both genders, aged between 15 and 50 years, which was the age group with the highest tuberculosis prevalence and the economically active one (possibility of infection by transport from one place to another) who lived in the study area [37].
We selected a subpopulation with the most prevalent sociodemographic characteristics of the general population. Our study was multicentered to better represent the population studied and to enroll as many DILI cases as possible.
Data collection sheet: This was designed to make it possible to collect sociodemographic characteristics, as well as clinical results, from medical records, in the studied population. The data collection sheet was accepted by the CIEI-INS. Two nurses, trained by the principal investigator, collected the information. The collected clinical records were analyzed by an epidemiologist and a biostatistician.
Blood Samples: After the survey questionnaire, peripheral blood samples (4 mL) were obtained from all 377 studied patients at baseline.
Laboratory methods: Genomic DNA was extracted from peripheral blood of all 377 participants using the genomic DNA extraction kit QIAamp DNA Blood Mini Kit (Qiagen, Germany) according to the manufacturer’s instructions. The selected genomic DNA regions for the analysis of each gene included GSTT1 and GSTM1 genes in 2 replicates. These regions were amplified by PCR using the Platinum Taq DNA polymerase kit (Invitrogen, USA) as described previously [15] with the following primers: 5′-GAACTCCCTGAAAAGCTAAAGC-3′ and 5′-GTTGGGCTCAAATATACGGTGG-3′ for the GSTM1 gene and the specific primers 5′-TTCCTTACTGGTCCTCACATCTC-3′ and 5′-TCACCGGATCATGGCCAGCA-3′ for the GSTT1 gene [15]. PCR was performed in a final volume of 25 mL, as follows: a 5-min denaturation at 94 °C, 30 cycles of 1 min at 94 °C, 1 min at 55 °C, and a final 5-min extension at 72 °C. The PCR products were revealed by the presence of bands using 1.5% agarose gel electrophoresis (gel prepared in 1X TAE buffer and stained with SYBR ® Safe DNA). The bands were 215 and 480 bp in size, depending on the GST genotype, designated as GSTM1 and GSTT1 marker bands, respectively. All electrophoresis reports included known positive and negative samples for both genes (Figure 1).
Measures and analysis: Presence of DILI (yes/no) was the outcome. This information was collected from the medical record of each patient and was diagnosed by a medical doctor. Liver profile is measured 2 months after starting treatment in all patients with sensitive tuberculosis in Peru [37]. Hepatotoxicity was defined as elevated aminotransferase levels and identified as being three times higher than before initiating TB treatment, with associated symptoms of hepatitis. Symptoms were considered as the occurrence of jaundice, nausea, vomiting, dyspepsia, and asthenia [38]. The reference values adopted were AST—36 UI/mL and ALT—32 UI/mL [39].
The GST genotype, exposure of interest, was classified as “wild and null”. The GST genotype is defined as the genetic information of the DNA fragments of the GSTT1 and GSTM1 genes to reduce the activity of potentially toxic compounds with cellular macromolecules. The other covariates were grouped into (1) demographics (gender and age), (2) alcohol consumption, (3) cholesterol, (4) hemoglobin, (5) glucose, and (6) body mass index (BMI). All the covariables were obtained from biological samples or at the time of interview of each patient.
NAT2 acetylator genotypes were classified as “slow, intermediate, and rapid,” and CYP2E1 genotypes were classified as “c1/c1, c1/c2, and c2/c2” in a previous study [29]. In this study, we found that rapid, intermediate, and slow NAT2 acetylators were 15%, 38%, and 47%, respectively, in the general population. Intermediate NAT2 acetylator is the least prevalent among patients with adverse reactions (p = 0.024). Finally, we found that the combination of intermediate NAT2 acetylators and CYP2E1 c1/c1 genotypes significantly protected (OR = 0.16; p = 0.049) against the development of DILI in our population [40].
Statistical analysis. A power of 92.6% was obtained when comparing the difference in the mean probability of the outcome variable between two categories of the independent variable (wild and null genotype). A ratio of 0.03 was assumed between wild and null genotypes and a probability of presence of RAFAs with wild and null genotypes, of 0.15 and 0.55, respectively, according to published data [5].
The chi–square test was used, or when necessary, Fisher’s exact test, to check the statistical significance of differences in the frequency distribution of variables and the Hardy–Weinberg equilibrium. Variables of interest had a normal distribution, so we calculated the median (interquartile), and used the Mann–Whitney test when it was necessary. Bivariate logistic regression analysis was performed, and the magnitude of the associations was expressed by the odds ratio (OR) as an estimate of relative risk, with a confidence interval of 95% regression. This strategy is correct when the prevalence of the disease or condition of interest being studied is small (ADRs: 3.4–13%), since the OR would give a value close to the prevalence ratio (PR) [41]. Data analysis was performed using Stata v15 (StataCorp, College Station, TX, USA) considering a statistical significance of p < 0.05.

5. Conclusions

We do not report evidence that the presence of variant genotypes of GSTM1, GSTT1, or their interaction, can become isolated risk or protective factors for developing ADRs during TB treatment. Although the present study is the first to examine the effects of combining GSTM1, GSTT1, and CYP2E1 genotypes, NAT2 acetylator status, and the presence of adverse reactions, finding an interesting result, the present GSTM1 genotype, GSTT1 null genotype, fast NAT2 acetylators, and CYP2E1 c1/c1 genotype had a significant risk for the development of ADR.
This is the first pharmacogenetic study carried out in a mestizo population where the ancestral component is greater than 50% native. The findings based on the type of phenotype (slow or fast metabolizer) in relation to its genetic polymorphism, show that the results are different from those found in other populations with a different ancestral component.

Author Contributions

Study design: L.J.-V., C.U.-G. and H.G. Performed the experiments: L.J.-V., A.V.-D. and A.T.-N. Analyzed the data: L.J.-V., K.S.L., D.D.T., S.C., A.V.-D., A.T.-N., C.S., E.T.-S., C.U.-G. and H.G. All authors have read and agreed to the published version of the manuscript.


This research was funded by Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica grant number EF033-235-2015. And the APC was funded by Universidad Continental.

Institutional Review Board Statement

Our study was approved by the Ethics in Research Committee of the Peruvian National Institute of Health and the Ethics Committee of the Universidad Peruana Cayetano Heredia. Written informed consent was obtained from all the participants.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Chamorro, J.G.; Castagnino, J.P.; Musella, R.M.; Nogueras, M.; Aranda, F.M.; Frías, A.; Visca, M.; Aidar, O.; Perés, S.; de Larrañaga, G.F. Sex, ethnicity, and slow acetylator profile are the major causes of hepatotoxicity induced by antituberculosis drugs. J. Gastroenterol. Hepatol. 2013, 28, 323–328. Available online: (accessed on 20 August 2019). [CrossRef] [PubMed]
  2. Possuelo, L.G.; Castelan, J.A.; de Brito, T.C.; Ribeiro, A.W.; Cafrune, P.I.; Picon, P.D.; Santos, A.R.; Teixeira, R.L.F.; Gregianini, T.S.; Hutz, M.H.; et al. Association of slow N-acetyltransferase 2 profile and anti-TB drug-induced hepatotoxicity in patients from Southern Brazil. Eur. J. Clin. Pharmacol. 2008, 64, 673–681. [Google Scholar] [CrossRef] [PubMed]
  3. Yimer, G.; Ueda, N.; Habtewold, A.; Amogne, W.; Suda, A.; Riedel, K.-D.; Burhenne, J.; Aderaye, G.; Lindquist, L.; Makonnen, E.; et al. Pharmacogenetic & pharmacokinetic biomarker for efavirenz based ARV and rifampicin based anti-TB drug induced liver injury in TB-HIV infected patients. PLoS ONE 2011, 6, e27810. [Google Scholar]
  4. Simon, T.; Becquemont, L.; Mary-Krause, M.; de Waziers, I.; Beaune, P.; Funck-Brentano, C.; Jaillon, P. Combined glutathione-S-transferase M1 and T1 genetic polymorphism and tacrine hepatotoxicity. Clin. Pharmacol. Ther. 2000, 67, 432–437. [Google Scholar] [CrossRef]
  5. Gupta, V.H.; Singh, M.; Amarapurkar, D.N.; Sasi, P.; Joshi, J.M.; Baijal, R.; Kumar, H.R.P.; Amarapurkar, A.D.; Joshi, K.; Wangikar, P.P. Association of GST null genotypes with anti-tuberculosis drug induced hepatotoxicity in Western Indian population. Ann. Hepatol. 2013, 12, 959–965. Available online: (accessed on 31 May 2022). [CrossRef]
  6. De Teixeira, R.L.F.; Morato, R.G.; Cabello, P.H.; Muniz, L.M.K.; Moreira, A.d.S.R.; Kritski, A.L.; Mello, F.C.Q.; Suffys, P.N.; de Miranda, A.B. Genetic polymorphisms of NAT2, CYP2E1 and GST enzymes and the occurrence of antituberculosis drug-induced hepatitis in Brazilian TB patients. Mem. Inst. Oswaldo Cruz. 2011, 106, 716–724. [Google Scholar] [CrossRef]
  7. Lv, X.; Tang, S.; Xia, Y.; Zhang, Y.; Wu, S.; Yang, Z.; Li, X.; Tu, D.; Chen, Y.; Deng, P.; et al. NAT2 genetic polymorphisms and anti-tuberculosis drug-induced hepatotoxicity in Chinese community population. Ann. Hepatol. 2012, 11, 700–707. [Google Scholar] [CrossRef]
  8. Strange, R.C.; Jones, P.W.; Fryer, A.A. Glutathione S-transferase: Genetics and role in toxicology. Toxicol. Lett. 2000, 112–113, 357–363. [Google Scholar] [CrossRef]
  9. Meister, A. Selective modification of glutathione metabolism. Science 1983, 220, 472–477. [Google Scholar] [CrossRef]
  10. Meyer, D.J.; Coles, B.; Pemble, S.E.; Gilmore, K.S.; Fraser, G.M.; Ketterer, B. Theta, a new class of glutathione transferases purified from rat and man. Biochem. J. 1991, 274, 409–414. [Google Scholar] [CrossRef]
  11. Pemble, S.; Schroeder, K.R.; Spencer, S.R.; Meyer, D.J.; Hallier, E.; Bolt, H.M.; Ketterer, B.; Taylor, J.B. Human glutathione S-transferase theta (GSTT1): cDNA cloning and the characterization of a genetic polymorphism. Biochem. J. 1994, 300 Pt 1, 271–276. [Google Scholar] [CrossRef] [Green Version]
  12. Roy, B.; Chowdhury, A.; Kundu, S.; Santra, A.; Dey, B.; Chakraborty, M.; Majumder, P.P. Increased risk of antituberculosis drug-induced hepatotoxicity in individuals with glutathione S-transferase M1 “null” mutation. J. Gastroenterol. Hepatol. 2001, 16, 1033–1037. [Google Scholar] [CrossRef] [PubMed]
  13. Huang, Y.-S.; Su, W.-J.; Huang, Y.-H.; Chen, C.-Y.; Chang, F.-Y.; Lin, H.-C.; Lee, S.D. Genetic polymorphisms of manganese superoxide dismutase, NAD(P)H:quinone oxidoreductase, glutathione S-transferase M1 and T1, and the susceptibility to drug-induced liver injury. J. Hepatol. 2007, 47, 128–134. [Google Scholar] [CrossRef] [PubMed]
  14. Chatterjee, S.; Lyle, N.; Mandal, A.; Kundu, S. GSTT1 and GSTM1 gene deletions are not associated with hepatotoxicity caused by antitubercular drugs. J. Clin. Pharm. Ther. 2010, 35, 465–470. [Google Scholar] [CrossRef]
  15. Leiro, V.; Fernández-Villar, A.; Valverde, D.; Constenla, L.; Vázquez, R.; Piñeiro, L.; González-Quintela, A. Influence of glutathione S-transferase M1 and T1 homozygous null mutations on the risk of antituberculosis drug-induced hepatotoxicity in a Caucasian population. Liver Int. 2008, 28, 835–839. [Google Scholar] [CrossRef] [PubMed]
  16. Tang, S.-W.; Lv, X.-Z.; Zhang, Y.; Wu, S.-S.; Yang, Z.-R.; Xia, Y.-Y.; Tu, D.-H.; Deng, P.-Y.; Ma, Y.; Chen, D.-F.; et al. CYP2E1, GSTM1 and GSTT1 genetic polymorphisms and susceptibility to antituberculosis drug-induced hepatotoxicity: A nested case-control study. J. Clin. Pharm. Ther. 2012, 37, 588–593. [Google Scholar] [CrossRef]
  17. Lu, Y.-F.; Goldstein, D.B.; Angrist, M.; Cavalleri, G. Personalized medicine and human genetic diversity. Cold Spring Harb. Perspect. Med. 2014, 4, a008581. Available online: (accessed on 1 August 2019). [CrossRef]
  18. Suarez-Kurtz, G.; Pena, S.D.J. Pharmacogenomics in the Americas: The impact of genetic admixture. Curr. Drug Targets 2006, 7, 1649–1658. [Google Scholar] [CrossRef]
  19. Guio, H.; Poterico, J.A.; Levano, K.S.; Cornejo-Olivas, M.; Mazzetti, P.; Manassero-Morales, G.; Ugarte-Gil, M.F.; Acevedo-Vásquez, E.; Dueñas-Roque, M.; Piscoya, A. Genetics and genomics in Peru: Clinical and research perspective. Mol. Genet. Genomic Med. 2018, 6, 873–886. Available online: (accessed on 1 August 2019). [CrossRef]
  20. Rohrer Vitek, C.R.; Nicholson, W.T.; Schultz, C.; Caraballo, P.J. Evaluation of the use of clinical decision support and online resources for pharmacogenomics education. Pharmacogenomics 2015, 16, 1595–1603. Available online: (accessed on 1 August 2019). [CrossRef]
  21. Weinshilboum, R.; Wang, L. Pharmacogenomics: Bench to bedside. Nat. Rev. Drug. Discov. 2004, 3, 739–748. Available online: (accessed on 1 August 2019). [CrossRef] [PubMed]
  22. Fuselli, S.; Gilman, R.H.; Chanock, S.J.; Bonatto, S.L.; De Stefano, G.; Evans, C.A.; Labuda, D.; Luiselli, D.; Salzano, F.M.; Soto, G.; et al. Analysis of nucleotide diversity of NAT2 coding region reveals homogeneity across Native American populations and high intra-population diversity. Pharm. J. 2007, 7, 144–152. Available online: (accessed on 15 April 2018). [CrossRef] [PubMed]
  23. Bisso-Machado, R.; Ramallo, V.; Paixão-Côrtes, V.R.; Acuña-Alonzo, V.; Demarchi, D.A.; Sandoval, J.R.S.; Granara, A.A.S.; Salzano, F.M.; Hünemeier, T.; Bortolini, M.C. NAT2 gene diversity and its evolutionary trajectory in the Americas. Pharm. J. 2016, 16, 559–565. Available online: (accessed on 12 March 2021). [CrossRef]
  24. Levano, K.S.; Jaramillo-Valverde, L.; Tarazona, D.D.; Sanchez, C.; Capristano, S.; Solari, L.; Mendoza-Ticona, A.; Soto, A.; Rojas, C.; Zegarra-Chapoñan, R.; et al. Allelic and Genotypic Frequencies of NAT2, CYP2E1 and AADAC genes in a cohort of Peruvian Tuberculosis Patients. bioRxiv 2021, 9, e1764. [Google Scholar] [CrossRef] [PubMed]
  25. Harris, D.N.; Song, W.; Shetty, A.C.; Levano, K.S.; Cáceres, O.; Padilla, C.; Borda, V.; Tarazona, D.; Trujillo, O.; Sanchez, C.; et al. Evolutionary genomic dynamics of Peruvians before, during, and after the Inca Empire. Proc. Natl. Acad. Sci. USA 2018, 115, E6526–E6535. Available online: (accessed on 27 February 2019). [CrossRef]
  26. Bolt, H.; Thier, R. Relevance of the Deletion Polymorphisms of the Glutathione S-Transferases GSTT1 and GSTM1 in Pharmacology and Toxicology. Curr. Drug. Metab. 2006, 7, 613–628. [Google Scholar] [CrossRef]
  27. Metabolic Gene Polymorphism Frequencies in Control Populations1|Cancer Epidemiology, Biomarkers & Prevention|American Association for Cancer Research. Available online: (accessed on 31 May 2022).
  28. Chanhom, N.; Udomsinprasert, W.; Chaikledkaew, U.S.A.; Mahasirimongkol, S.; Wattanapokayakit, S.; Jittikoon, J. GSTM1 and GSTT1 genetic polymorphisms and their association with antituberculosis drug-induced liver injury. Biomed Rep. 2020, 12, 153. Available online: (accessed on 25 July 2022). [CrossRef]
  29. Kim, S.H.; Kim, S.H.; Yoon, H.J.; Shin, D.H.; Park, S.S.; Kim, Y.S.; Jae-Seuk, P.; Young Koo, J. GSTT1 and GSTM1 null mutations and adverse reactions induced by antituberculosis drugs in Koreans. Tuberculosis 2010, 90, 39–43. [Google Scholar] [CrossRef]
  30. Voso, M.T.; D’Alo’, F.; Putzulu, R.; Mele, L.; Scardocci, A.; Chiusolo, P.; Latagliata, R.; Lo-Coco, F.; Rutella, S.; Pagano, L.; et al. Negative prognostic value of glutathione S-transferase (GSTM1 and GSTT1) deletions in adult acute myeloid leukemia. Blood 2002, 100, 2703–2707. Available online: (accessed on 31 May 2022). [CrossRef]
  31. Haase, D.; Binder, C.; Bünger, J.; Fonatsch, C.; Streubel, B.; Schnittger, S.; Griesinger, F.; Westphal, G.; Schoch, C.; Knopp, A.; et al. Increased risk for therapy-associated hematologic malignancies in patients with carcinoma of the breast and combined homozygous gene deletions of glutathione transferases M1 and T1. Leuk. Res. 2002, 26, 249–254. Available online: (accessed on 31 May 2022). [CrossRef]
  32. Huang, C.C.; Chien, W.P.; Wong, R.H.; Cheng, Y.W.; Chen, M.C.; Chou, M.C.; Lee, H. NAT2 Fast Acetylator Genotype is Associated with an Increased Risk of Colorectal Cancer in Taiwan. Dis. Colon. Rectum. 2007, 50, 981–989. [Google Scholar] [CrossRef]
  33. Guio, H.; Levano, K.S.; Sanchez, C.; Tarazona, D. The role of pharmacogenomics in the tuberculosis treatment regime. Rev. Peru Med. Exp. Salud. Publica 2015, 32, 794–800. [Google Scholar] [CrossRef]
  34. Shaikh, R.S.; Amir, M.; Masood, A.I.; Sohail, A.; Athar, H.U.R.; Siraj, S.; Ali, M.; Anjam, M.S. Frequency distribution of GSTM1 and GSTT1 null allele in Pakistani population and risk of disease incidence. Environ. Toxicol. Pharmacol. 2010, 30, 76–79. [Google Scholar] [CrossRef] [PubMed]
  35. Li, C.; Long, J.; Hu, X.; Zhou, Y. GSTM1 and GSTT1 genetic polymorphisms and risk of anti-tuberculosis drug-induced hepatotoxicity: An updated meta-analysis. Eur. J. Clin. Microbiol. Infect. Dis. 2013, 32, 859–868. [Google Scholar] [CrossRef] [PubMed]
  36. Tang, N.; Deng, R.; Wang, Y.; Lin, M.; Li, H.; Qiu, Y.; Hong, M.; Zhou, G. GSTM1 and GSTT1 null polymorphisms and susceptibility to anti-tuberculosis drug-induced liver injury: A meta-analysis. Int. J. Tuberc. Lung Dis. 2013, 17, 17–25. [Google Scholar] [CrossRef] [PubMed]
  37. MINSA. Norma Técnica de Salud Para la Atención Integral de las Personas Afectadas por Tuberculosis. 2013. Available online: (accessed on 21 November 2021).
  38. Ramappa, V.; Aithal, G.P. Hepatotoxicity Related to Anti-tuberculosis Drugs: Mechanisms and Management. J. Clin. Exp. Hepatol. 2013, 3, 37–49. Available online: (accessed on 12 October 2019). [CrossRef]
  39. Araujo-Mariz, C.; Militão de Albuquerque, M.F.P.; Lopes, E.P.; Ximenes, R.A.A.; Lacerda, H.R.; Miranda-Filho, D.B.; Lustosa-Martins, B.B.; Pastor, A.F.P.; Acioli-Santos, B. Hepatotoxicity during TB treatment in people with HIV/AIDS related to NAT2 polymorphisms in Pernambuco, Northeast Brazil. Ann. Hepatol. 2020, 19, 153–160. [Google Scholar] [CrossRef]
  40. Jaramillo-Valverde, L.; Levano, K.S.; Tarazona, D.D.; Capristano, S.; Zegarra-Chapoñan, R.; Sanchez, C.; Yufra-Picardo, V.M.; Tarazona-Santos, E.; Ugarte-Gil, C.; Guio, H. NAT2 and CYP2E1 polymorphisms and antituberculosis drug-induced hepatotoxicity in Peruvian patients. Mol. Genet. Genomic Med. 2022, 10, e1987. [Google Scholar] [CrossRef]
  41. Schiaffino, A.; Rodríguez, M.; Pasarín, M.I.; Regidor, E.; Borrell, C.; Fernández, E. ¿Odds ratio o razón de proporciones? Su utilización en estudios transversales. Gac. Sanit. 2003, 17, 70–74. [Google Scholar] [CrossRef]
Figure 1. PCR products revealed using 1.5% agarose gel electrophoresis. The bands were 215 and 480 bp in size, depending on the GST genotype, designated as GSTT1 (A) and GSTM1 (B). Samples are 1–11, 12 positive amplification sample and 13 negative amplification sample.
Figure 1. PCR products revealed using 1.5% agarose gel electrophoresis. The bands were 215 and 480 bp in size, depending on the GST genotype, designated as GSTT1 (A) and GSTM1 (B). Samples are 1–11, 12 positive amplification sample and 13 negative amplification sample.
Ijms 23 11028 g001
Table 1. Clinical and biological variables of adult patients diagnosed with sensitive pulmonary tuberculosis in Lima during the years 2014–2015.
Table 1. Clinical and biological variables of adult patients diagnosed with sensitive pulmonary tuberculosis in Lima during the years 2014–2015.
TotalAdverse Reaction (DILI)
Variables YesNop-Value
Female17045.09637.5016445.430.533 a
Age (years)--24.3 *(20.3–30.8) †24.2 *(20.9–29.6) †0.995 b
Alcohol consumption
Yes32887.001381.2531587.260.346 c
Cholesterol (mg/dL)--154.0 *(141.2–185.0) †169 *(149.0–189.0) †0.214 b
Hemoglobin (g/dL)--13.9 *(12.2–15.6) †13.6 *(12.4–14.9) †0.769 b
Glucose (mg/dL)--89.5 *(80.0–95.0) †83.1 *(77.9–91.1) †0.084 b
BMI (kg/m2)--21.1 *(19.7–22.5) †22 *(20.3–23.6) †0.182 b
GSTM1 genotype
Null17847.21105.6216894.380.160 c
GSTT1 genotype
Null11430.2465.2610894.740.346 c
Variables in black; * Median; † (Q1–Q3); BMI (Body mass index); GST (glutathione S-transferase); Statistically significant (p < 0.05); a chi-square test; b Mann–Whitney test; c Fisher’s exact test.
Table 2. Association of the null genotype GSTM1 and T1 with the risk of DILI in the Peruvian population.
Table 2. Association of the null genotype GSTM1 and T1 with the risk of DILI in the Peruvian population.
Adverse Reaction (DILI)
Yes = 16 (%)No = 361 (%)OR (CI 95%)p-Value
Present (M+)6 (3.02)193 (96.98)-
Null (M−)10 (5.62)168 (94.38)1.915 (0.61–6.54)0.211
Present (T+)10 (3.80)253 (96.20)-
Null (T−)6 (5.26)108 (94.74)1.406 (0.41–4.39)0.518
Both GSTM1 and T1 -
M+/T+13 (3.96)314 (96.04)
M+/T−7 (5.47)121 (94.53)1.397 (0.46–3.87)0.485
M−/T+3 (4.92)61 (95.08)1.188 (0.21–4.50)0.793
M−/T−3 (6.00)47 (96.00)1.542 (0.27–5.90)0.508
Variables in black; Data is represented as n (%); Statistically significant (p < 0.05); OR: odds ratio; CI: confidence intervals.
Table 3. Combined effects of NAT2, CYP2E1, and GST with the risk of DILI in the Peruvian population.
Table 3. Combined effects of NAT2, CYP2E1, and GST with the risk of DILI in the Peruvian population.
Adverse Reaction (DILI)
GSTM1GSTT1CYP2E1NAT2Yes = 16 (%)No = 361 (%)OR (IC 95%)p-Value
NullPresentC1/C1Slow3331 (0.12–8.02)1
PresentNullC1/C1Slow0200 (0–2.28)0.185
NullNullC1/C1Slow1150.73 (0.01–10.09)0.795
PresentPresentC1/C2 or C2/C2Slow0270 (0–1.67)0.124
NullPresentC1/C2 or C2/C2Slow0190 (0–2.4)0.196
PresentNullC1/C2 or C2/C2Slow0140 (0–3.31)0.265
NullNullC1/C2 or C2/C2Slow254.4 (0.28–47.68)0.126
PresentPresentC1/C1Intermediate0290 (0–1.55)0.111
NullPresentC1/C1Intermediate1340.32 (0.01–4.33)0.317
PresentNullC1/C1Intermediate0160 (0–2.86)0.234
NullNullC1/C1Intermediate0130 (0–3.58)0.283
PresentPresentC1/C2 or C2/C2Intermediate0150 (0–3.08)0.249
NullPresentC1/C2 or C2/C2Intermediate0210 (0–2.16)0.174
PresentNullC1/C2 or C2/C2Intermediate070 (0–7.04)0.428
NullNullC1/C2 or C2/C2Intermediate060 (0–8.36)0.463
PresentPresentC1/C1Rapid0140 (0–3.31)0.265
NullPresentC1/C1Rapid2102.2 (0.16–21.78)0.413
PresentNullC1/C1Rapid2211 (0.54–186.35)0.017
NullNullC1/C1Rapid060 (0–8.36)0.463
PresentPresentC1/C2 or C2/C2Rapid0100 (0–4.75)0.345
NullPresentC1/C2 or C2/C2Rapid133.67 (0.05–65.57)0.292
PresentNullC1/C2 or C2/C2Rapid125.5 (0.07–129.91)0.17
NullNullC1/C2 or C2/C2Rapid020 (0–28.51)0.671
Data are represented as n (%); Statistically significant (p < 0.05); OR: odds ratio; CI: confidence intervals.
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Jaramillo-Valverde, L.; Levano, K.S.; Tarazona, D.D.; Vasquez-Dominguez, A.; Toledo-Nauto, A.; Capristano, S.; Sanchez, C.; Tarazona-Santos, E.; Ugarte-Gil, C.; Guio, H. GSTT1/GSTM1 Genotype and Anti-Tuberculosis Drug-Induced Hepatotoxicity in Peruvian Patients. Int. J. Mol. Sci. 2022, 23, 11028.

AMA Style

Jaramillo-Valverde L, Levano KS, Tarazona DD, Vasquez-Dominguez A, Toledo-Nauto A, Capristano S, Sanchez C, Tarazona-Santos E, Ugarte-Gil C, Guio H. GSTT1/GSTM1 Genotype and Anti-Tuberculosis Drug-Induced Hepatotoxicity in Peruvian Patients. International Journal of Molecular Sciences. 2022; 23(19):11028.

Chicago/Turabian Style

Jaramillo-Valverde, Luis, Kelly S. Levano, David D. Tarazona, Andres Vasquez-Dominguez, Anel Toledo-Nauto, Silvia Capristano, Cesar Sanchez, Eduardo Tarazona-Santos, Cesar Ugarte-Gil, and Heinner Guio. 2022. "GSTT1/GSTM1 Genotype and Anti-Tuberculosis Drug-Induced Hepatotoxicity in Peruvian Patients" International Journal of Molecular Sciences 23, no. 19: 11028.

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