Dataset Information

Association of genetic polymorphisms of CYP2E1, NAT2, GST and SLCO1B1 with the risk of anti-tuberculosis drug-induced liver injury: a systematic review and meta-analysis.

ABSTRACT: OBJECTIVES:The objective of this study was to investigate the association between genetic polymorphisms of N-acetyltransferase 2 (NAT2), cytochrome P450 2E1 (CYP2E1), glutathione S-transferase (GST) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) and the risk of anti-tuberculosis drug-induced liver injury (ATDILI). DESIGN:Systematic review and meta-analysis. DATA SOURCES:PubMed, Embase, Web of Science and Cochrane Reviews databases were searched through April 2019. ELIGIBILITY CRITERIA:We included case-control or cohort studies investigating an association between NAT2, CYP2E1, GST or SLCO1B1 polymorphisms and the ATDILI risk in patients with tuberculosis. DATA EXTRACTION AND SYNTHESIS:Three authors screened articles, extracted data and assessed study quality. The strength of association was evaluated for each gene using the pooled OR with a 95% CI based on the fixed-effects or random-effects model. Sensitivity analysis was performed to confirm the reliability and robustness of the results. RESULTS:Fifty-four studies were included in this analysis (n=26 for CYP2E1, n=35 for NAT2, n=19 for GST, n=4 for SLCO1B1). The risk of ATDILI was significantly increased with the following genotypes: CYP2E1 RsaI/PstI c1/c1 (OR=1.39, 95%?CI 1.06 to 1.83), NAT2 slow acetylator (OR=3.30, 95%?CI 2.65 to 4.11) and GSTM1 null (OR=1.30, 95%?CI 1.12 to 1.52). No significant association with ATDILI was found for the genetic polymorphisms of CYP2E1 DraI, GSTT1, GSTM1/GSTT1, SLCO1B1 388A>G and SLCO1B1 521T>C (p>0.05). CONCLUSIONS:ATDILI is more likely to occur in patients with NAT2 slow acetylator genotype, CYP2E1 RsaI/PstI c1/c1 genotype and GSTM1 null genotype. Close monitoring may be warranted for patients with these genotypes.

SUBMITTER: Yang S

PROVIDER: S-EPMC6688699 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of genetic polymorphisms of <i>CYP2E1, NAT2, GST</i> and <i>SLCO1B1</i> with the risk of anti-tuberculosis drug-induced liver injury: a systematic review and meta-analysis.

Yang Seungwon S Hwang Se Jung SJ Park Jung Yun JY Chung Eun Kyoung EK Lee Jangik I JI

BMJ open 20190801 8

<h4>Objectives</h4>The objective of this study was to investigate the association between genetic polymorphisms of N-acetyltransferase 2 (<i>NAT2)</i>, cytochrome P450 2E1 (<i>CYP2E1)</i>, glutathione S-transferase (<i>GST)</i> and solute carrier organic anion transporter family member 1B1 (<i>SLCO1B1)</i> and the risk of anti-tuberculosis drug-induced liver injury (ATDILI).<h4>Design</h4>Systematic review and meta-analysis.<h4>Data sources</h4>PubMed, Embase, Web of Science and Cochrane Reviews ...[more]

PMID: 31375612

Similar Datasets

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: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.

Dataset Information

Association of genetic polymorphisms of CYP2E1, NAT2, GST and SLCO1B1 with the risk of anti-tuberculosis drug-induced liver injury: a systematic review and meta-analysis.

Publications

Association of genetic polymorphisms of <i>CYP2E1, NAT2, GST</i> and <i>SLCO1B1</i> with the risk of anti-tuberculosis drug-induced liver injury: a systematic review and meta-analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets