Dataset Information

Genetic Variations Associated with Anti-Tuberculosis Drug-Induced Liver Injury.

ABSTRACT: Purpose of this Review:In order to combat the development of drug resistance, the clinical treatment of tuberculosis requires the combined use of several anti-tuberculosis (anti-TB) drugs, including isoniazid and rifampicin. Combinational treatment approaches are suggested by the World Health Organization (WHO) and are widely accepted throughout the world. Unfortunately, a major side effect of the treatment is the development of anti-tuberculosis drug-induced liver injury (AT-DILI). Many factors contribute to isoniazid- and rifampicin-mediated AT-DILI and genetic variations are among the most common factors. The purpose of this review is to provide information on genetic variations associated with isoniazid- and rifampicin-mediated AT-DILI. Recent Findings:The genetic variations associated with AT-DILI have been identified in the genomic regions within or near genes encoding proteins in the following pathways: drug metabolizing enzymes (NAT2, CYP2E1, and GSTs), accumulation of bile acids, lipids, and heme metabolites (CYP7A1, BSEP, UGTs, and PXR), immune adaptation (HLAs and TNF-?), and oxidant challenge (TXNRD1, SOD1, BACH1, and MAFK). Summary:The information summarized in this review considers the genetic bases of risk factors contributing to AT-DILI and provides information that may help for future studies. Some of the implicated genetic variations can be used in the design of genetic tests and serve as biomarkers for the prediction of isoniazid- and rifampicin-mediated AT-DILI risk in personalized medicine.

SUBMITTER: Bao Y

PROVIDER: S-EPMC6241288 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Genetic Variations Associated with Anti-Tuberculosis Drug-Induced Liver Injury.

Bao Yifan Y Ma Xiaochao X Rasmussen Theodore P TP Zhong Xiao-Bo XB

Current pharmacology reports 20180315 3

<h4>Purpose of this review</h4>In order to combat the development of drug resistance, the clinical treatment of tuberculosis requires the combined use of several anti-tuberculosis (anti-TB) drugs, including isoniazid and rifampicin. Combinational treatment approaches are suggested by the World Health Organization (WHO) and are widely accepted throughout the world. Unfortunately, a major side effect of the treatment is the development of anti-tuberculosis drug-induced liver injury (AT-DILI). Many ...[more]

PMID: 30464886

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Project description:Background: Anti-tuberculosis drug-induced liver injury (ATB-DILI) is an adverse reaction with a high incidence and the greatest impact on tuberculosis treatment. However, there is a lack of effective biomarkers for the early prediction of ATB-DILI. Herein, this study uses UPLC‒MS/MS to reveal the plasma metabolic profile and lipid profile of ATB-DILI patients before drug administration and screen new biomarkers for predicting ATB-DILI. Methods: A total of 60 TB patients were enrolled, and plasma was collected before antituberculosis drug administration. The untargeted metabolomics and lipidomics analyses were performed using UPLC‒MS/MS, and the high-resolution mass spectrometer Q Exactive was used for data acquisition in both positive and negative ion modes. The random forest package of R software was used for data screening and model building. Results: A total of 60 TB patients, including 30 ATB-DILI patients and 30 non-ATB-DILI subjects, were enrolled. There were no significant differences between the ATB-DILI and control groups in age, sex, smoking, drinking or body mass index (p > 0.05). Twenty-two differential metabolites were selected. According to KEGG pathway analysis, 9 significantly enriched metabolic pathways were found, and both drug metabolism-other enzymes and niacin and nicotinamide metabolic pathways were found in both positive and negative ion models. A total of 7 differential lipid molecules were identified between the two groups. Ferroptosis and biosynthesis of unsaturated fatty acids were involved in the occurrence of ATB-DILI. Random forest analysis showed that the model built with the top 30 important variables had an area under the ROC curve of 0.79 (0.65-0.93) for the training set and 0.79 (0.55-1.00) for the validation set. Conclusion: This study demonstrated that potential markers for the early prediction of ATB-DILI can be found through plasma metabolomics and lipidomics. The random forest model showed good clinical predictive value for ATB-DILI.

Project description:BACKGROUND:Pregnane X receptor (PXR) regulates the expression of drug-metabolizing enzymes and transport enzymes. NF-?B not only plays a role in liver homeostasis and injury-healing processes by regulating inflammatory responses but may also regulate the transcription of PXR. Currently, genetic polymorphisms in PXR are associated with adverse drug effects. Because little is known about the association between NF-?B1 genetic polymorphisms and adverse drug reactions, we explored the association between PXR and NF-?B1 single nucleotide polymorphisms (SNPs) and susceptibility to anti-tuberculosis drug-induced liver injury (ATDILI). MATERIALS AND METHODS:A total of 746 tuberculosis patients (118 with ATDILI and 628 without ATDILI) were prospectively enrolled at West China Hospital between December 2014 and April 2018. Nine selected SNPs (rs3814055, rs13059232, rs7643645 and rs3732360 in PXR and rs78872571, rs4647992, rs60371688, rs1598861 and rs3774959 in NF-?B1) were genotyped with a custom-designed 2x48-plex SNP Scan TM Kit. The frequencies of the alleles, genotypes and genetic models of the variants were compared between patients with or without ATDILI, while joint effect analysis of the SNP-SNP interactions was performed using multiplicative and additive models. The odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) were calculated. RESULTS:The T allele of rs3814055 in PXR was associated with a decreased risk for ATDILI (OR 0.61; 95% CI: 0.42-0.89, p = 0.0098). The T alleles of rs78872571 and rs4647992 in NF-?B1 were significantly associated with an increased risk for ATDILI (OR 1.91; 95% CI: 1.06-3.43, p = 0.028 and OR 1.81; 1.06-3.10, p = 0.029, respectively). The allele, genotype and genetic model frequencies were similar in the two groups for the other six SNPs (all P>0.05). There were no multiplicative or additive interactions between the SNPs. CONCLUSION:Our study is the first to reveal that rs3814055 variants in PXR and rs78872571 and rs4647992 variants in NF-?B1 are associated with susceptibility to ATDILI caused by first-line anti-tuberculosis combination treatment in the Han Chinese population.

Project description:Although many genetic variants related to anti-tuberculosis drug induced liver injury (ATDILI) have been identified, the prediction and personalized treatment of ATDILI have failed to achieve, indicating there remains an area for further exploration. This study aimed to explore the influence of single nucleotide polymorphisms (SNPs) in Bradykinin receptor B2 (BDKRB2), Teneurin transmembrane protein 2 (TENM2), transforming growth factor beta 2 (TGFB2), and solute carrier family 2 member 13 (SLC2A13) on the risk of ATDILI.The subjects comprised 746 Chinese tuberculosis (TB) patients. Custom-by-design 2x48-Plex SNPscanTM kit was employed to genotype 28 selected SNPs. The associations of SNPs with ATDILI risk and clinical phenotypes were analyzed according to the distributions of allelic and genotypic frequencies and different genetic models. The odds ratio (OR) with corresponding 95% confidence interval (CI) was calculated.Among subjects with successfully genotyped, 107 participants suffered from ATDILI during follow-up. In BDKRB2, patients with rs79280755 G allele or rs117806152 C allele were more vulnerable to ATDILI (PBonferronicorrection = .002 and .03, respectively). Rs79280755 increased the risk of ATDILI significantly whether in additive (OR = 3.218, 95% CI: 1.686-6.139, PBonferroni correction = .003) or dominant model (PBonferroni correction = .003), as well as rs117806152 (Additive model: PBonferroni correction = .05; dominant model: PBonferroni correction = .03). For TENM2, rs80003210 G allele contributed to the decreased risk of ATDILI (PBonferroni correction = .02), while rs2617972 A allele conferred susceptibility to ATDILI (PBonferroni correction = .01). Regarding rs2617972, significant findings were also observed in both additive (OR = 3.203, 95% CI: 1.487-6.896, PBonferroni correction = .02) and dominant model (PBonferroni correction = .02). Moreover, rs79280755 and rs117806152 in BDKRB2 significantly affected some laboratory indicators. However, no meaningful SNPs were observed in TGFB2 and SLC2A13.Our study revealed that both BDKRB2 and TENM2 genetic polymorphisms were interrogated in relation to ATDILI susceptibility and some laboratory indicators in the Western Chinese Han population, shedding a new light on exploring novel biomarkers and targets for ATDILI.

Dataset Information

Genetic Variations Associated with Anti-Tuberculosis Drug-Induced Liver Injury.

Publications

Genetic Variations Associated with Anti-Tuberculosis Drug-Induced Liver Injury.

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