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Development of a prediction system for anti-tuberculosis drug-induced liver injury in Japanese patients.

ABSTRACT: Drug-induced liver injury (DILI) is a common adverse drug reaction in patients receiving antituberculosis (anti-TB) treatment. Among the anti-TB agents, isoniazid (INH) is the primary drug that causes hepatotoxicity in TB patients with DILI. Previous reports in several populations have consistently demonstrated an association between polymorphisms in the N-acetyltransferase 2 (NAT2) gene, which is responsible for INH hepatic metabolism, and a risk of DILI in TB patients. In this study, the genetic and baseline clinical data from 366 Japanese patients with TB (73 patients with DILI and 293 without DILI) were used to develop a system to predict DILI risk due to anti-TB agents. The distribution of the NAT2 acetylator status among the TB patients with DILI was 31 (42.5%), 29 (39.7%), and 13 (17.8%) for rapid, intermediate, and slow acetylators, respectively. A significant association was observed between NAT2 slow acetylators and DILI risk (odds ratio 4.32, 95% confidence interval 1.93-9.66, P value=5.56×10(-4)). A logistic regression model based on age and NAT2 genotype revealed that the area under the curve for the receiver-operating characteristic curve was 0.717. The findings demonstrated that slow NAT2 acetylator status is a significant predictor of the risk of DILI by anti-TB agents, and a personalized anti-TB treatment approach may aid in making treatment decisions and reducing the incidence of DILI.

SUBMITTER: Mushiroda T

PROVIDER: S-EPMC4917605 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Development of a prediction system for anti-tuberculosis drug-induced liver injury in Japanese patients.

Mushiroda Taisei T Yanai Hideki H Yoshiyama Takashi T Sasaki Yuka Y Okumura Masao M Ogata Hideo H Tokunaga Katsushi K

Human genome variation 20160623

Drug-induced liver injury (DILI) is a common adverse drug reaction in patients receiving antituberculosis (anti-TB) treatment. Among the anti-TB agents, isoniazid (INH) is the primary drug that causes hepatotoxicity in TB patients with DILI. Previous reports in several populations have consistently demonstrated an association between polymorphisms in the N-acetyltransferase 2 (NAT2) gene, which is responsible for INH hepatic metabolism, and a risk of DILI in TB patients. In this study, the genet ...[more]

PMID: 27340556

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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.

Dataset Information

Development of a prediction system for anti-tuberculosis drug-induced liver injury in Japanese patients.

Publications

Development of a prediction system for anti-tuberculosis drug-induced liver injury in Japanese patients.

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