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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

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.


Strengths and limitations of this study
 This is the first meta-analysis to evaluate the association between the risk of ATDILI and SLCO1B1 in TB patients.  2 3 . The currently recommended therapy for TB is highly effective, resulting in high cure rates if patients are adherent to therapy 4 . However, treatment adherence is often suboptimal in patients receiving the combination anti-TB therapy due to many adverse drug reactions, some of which are considered serious 5 . One of the common adverse drug reactions associated with anti-TB medications is anti-TB drug-induced liver injury (ATDILI) affecting 2-28% of TB patients 6 . ATDILI is primarily mild to moderate in severity; however, it is potentially serious and fatal, resulting in the treatment interruption and ultimately, treatment failure 7 8 . According to previous studies, common risk factors for the development of ATDILI include age, race, nutritional status, alcohol intake, cigarette smoking, and coinfection with HIV or hepatitis B or C virus 7 9 .
Recently, increasing evidence suggests an association between the risk of ATDILI and genetic polymorphisms of drug-metabolizing enzymes (DMEs) and drug transporters 10 11 . Reduced enzyme activity due to polymorphic genotypes of various DMEs including cytochrome P450 2E1 (CYP2E1), N-acetyltransferase 2 (NAT2), and glutathione S-transferase (GST) can result in the increased production and accumulation of toxic chemicals in the liver, leading to the development of ATDILI 12 . Previous meta-analyses indicated the association between the risk of ATDILI and the NAT2 slow acetylator, CYP2E1*1A, and GSTM1 null genotypes 10 13 . Since their publication, several case-control pharmacogenetic studies in TB patients were newly published with conflicting results regarding the association between the risk of ATDILI and genetic polymorphisms of various DMEs. Therefore, an updated meta-analysis has been warranted to confirm the association between the ATDILI risk and genetic polymorphisms of DMEs. In addition to DMEs, drug transporters have been emerging as a key determinant of the pharmacokinetics and pharmacodynamics of a drug 14 . Among various drug transporters, organic anion transporting polypeptide 1B1 (OATP1B1), encoded by SLCO1B1, is the major influx transporter responsible for hepatic uptake of RIF 15 . Although several studies have previously examined the association between SLCO1B1 polymorphisms and the risk of ATDILI, conflicting results have been reported regarding the effect of SLCO1B1 polymorphisms on ATDILI risk.
In our preliminary literature search, several polymorphic genes, including many DMEs, transporters, and other genes such as those involved in the immune system, were identified to have an association with the risk of ATDILI. Among these, sufficient, published information was available to conduct meta-analyses for CYP2E1, NAT2, GST, and SLCO1B1 genetic polymorphisms.

Objectives
This meta-analysis was to evaluate the association between the risk of ATDILI and genetic polymorphisms of CYP2E1, NAT2, GST, and SLCO1B1 in TB patients.

Methods
This study was in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist for reporting the study design, search strategy, methods,

Quality assessment and data extraction
The quality of included studies was assessed using the revised Little's recommendation based on the following criteria 16 17 . (1) scientific design; (2) definite inclusion of study population; (3) explicit information on study population; (4) explicit diagnostic criteria of ATDILI; (5) genetic detection method; (6) appropriate statistical analysis; and (7) logical discussion of study bias.
Studies with an overall score of ≥ 4 (range 0 to 7) were considered high quality and retained in the analysis. The following data were extracted from each study using a standardized extraction form: (1) name of the first author; (2) year of publication; (3) the polymorphic gene(s) and genotype(s) under investigation; (4) ethnicity; (5) sample size; (6) mean or median age; (7) sex distribution; (8) anti-TB drug regimens; (9) diagnostic criteria of ATDILI; (10) genotyping methods; (11) Hardy-Weinberg equilibrium (HWE) test results; and (12) the number of cases and controls for each polymorphic genotype.

Statistical analysis
The genotypes were analyzed based on the following genetic risk model:  otherwise, the fixed effects model was used. Heterogeneity of study outcomes among included studies was evaluated using Cochran's Q test (Q) and quantified using Higgin's I 2 test.
Significant heterogeneity was defined as the I 2 score of > 40% accompanied by P < 0.10 from the Cochran's Q test 18 . The strength of the association between the genetic polymorphisms and the risk of ATDILI was estimated using pooled ORs with the corresponding 95% CIs. The statistical significance of an OR was defined as P < 0.05 from the Z test. Subgroup analyses were performed to identify the source of heterogeneity and to investigate effects of the following covariates on the overall strength of the association between the genetic polymorphisms and the risk of ATDILI: ethnicity, the achievement of HWE, anti-TB drug regimen, the genotyping method used, and diagnostic criteria of ATDILI. In addition, sensitivity analyses were conducted to assess the robustness of the results. Publication bias was evaluated with a symmetrical funnel  (19 for GSTM1, 17 for GSTT1, and 11 for GSTM1/GSTT1), and 4 studies for SLCO1B1. Table 1 summarizes the characteristics of the included studies. Across the included studies, large variability in study population was observed in terms of ethnicity (Chinese, Japanese, Korean, Indian, Taiwanese, Brazilian, Caucasian, Iranian, Tunisian, and Turkish), age (mean or median age ranging from 27 to 70 years), and sex (the proportion of males ranging from 13% to 90%). Patients in our included studies received either monotherapy with INH or RIF or a combination therapy including a 4-drug regimen of INH, RIF, PZA, and EMB for the treatment of TB. ATDILI was defined as an elevated serum alanine aminotransferase (ALT) concentration by 1.5-to 5-fold or greater above the upper limit of normal (ULN) depending on the study. The quality score of the included studies was 5 or greater based on the revised Little's recommendation (Table 1) 16 17 . Genotype distribution, the achievement of HWE, and the genotyping method used in the included studies are summarized for each polymorphic gene in S1 to S4 Tables. Funnel plots for CYP2E1, NAT2, GST, and SLCO1B1 are provided in S5 Figure. None of the funnel plots were substantially asymmetrical.
In our primary analysis for the CYP2E1 DraI polymorphism with six studies including 233 cases and 1272 controls, no significant association was observed using the fixed-effects model between the risk of ATDILI and the DraI polymorphism (OR for the D/D genotype = 0.93, 95% CI 0.68-1.27, P = 0.64; I 2 = 0%, P heterogeneity = 0.51) ( Figure 2B). No subgroup analysis for the DraI polymorphism resulted in a significant association between the ATDILI risk and the DraI polymorphism (S6 Table).

NAT2
Overall, 34 studies with 1270 cases and 7234 controls were included in our primary analysis for the NAT2 polymorphism. Using the random-effects model, the pooled estimates of all included studies (n = 34) showed a significant association between the risk of ATDILI and the NAT2 polymorphism (OR for the slow acetylator genotype = 3.11, 95% CI 2.53-3.82, P < 0.00001; I 2 = 47%, P heterogeneity = 0.002) (Figure 3).
In the subgroup analysis based on ethnicity, anti-tuberculosis drug regimens, and  Table). Additionally, the association between the risk of ATDILI and the NAT2 slow acetylator genotype remained significant after excluding the studies where HWE was not achieved (S7 Table). Similarly, slow acetylators were at the significantly increased risk of ATDILI regardless of the genotyping method used (e.g., polymerase chain reaction-restriction fragment length polymorphism [PCR-RFLP], sequencing) (S7 Table).

GST
For the GSTM1 polymorphism, a total of 19 studies with 977 cases and 5119 controls were included in our primary analysis. Using the fixed-effects model, the pooled estimates of all included studies (n = 19) showed a significant association between the risk of ATDILI and the GSTM1 polymorphism (OR for the GSTM1 null genotype = 1.30, 95% CI 1.12-1.52, P = 0.0007; I 2 = 33%, P heterogeneity = 0.08) ( Figure 4A). In the subgroup analysis based on ethnicity and diagnostic criteria of ATDILI, the risk of ATDILI was significantly increased for the GSTM1 null genotype in Indians (OR = 1.68, 95% CI 1.30-2.19, P < 0.0001; I 2 = 36%, P heterogeneity = 0. 15) and in patients with ATDILI defined as a serum ALT concentration elevated by 2-fold or greater above the ULN (OR = 1.56, 95% CI 1.28-1.91, P < 0.0001; I 2 = 13%, P heterogeneity = 0.32) (S8 Table).
The risk of ATDILI was not significantly associated with the GSTT1 polymorphism (OR for the null genotype = 1.03, 95% CI 0.85-1.25, P = 0.76; I 2 = 16%, P heterogeneity = 0.26) or the  (Figures 4B and 4C). The associations of the GSTT1 and the GSTM1/GSTT1 genetic polymorphisms with the risk of ATDILI were not significant in any of the subgroups tested (S8 Table).

SLCO1B1
For the SLCO1B1 388A>G polymorphism, four studies with 279 cases and 837 controls were included in our primary analysis. Using the fixed-effects model, no significant association was observed between the risk of ATDILI and the SLCO1B1 388A>G polymorphism (OR for the AA genotype = 1.47, 95% CI 0.94-2.29, P = 0.09; I 2 = 0%, P heterogeneity = 0.72) ( Figure 5A). For the SLCO1B1 521T>C polymorphism, four studies with 310 cases and 901 controls were included in our primary analysis. Using the fixed-effects model, no significant association was found between the ATDILI risk and the SLCO1B1 521T>C polymorphism (OR for the CC genotype = 1.21, 95% CI 0.40-3.63, P = 0.74; I 2 = 0%, P heterogeneity = 0.56) ( Figure 5B). No significant association was observed between the risk of ATDILI and the SLCO1B1 polymorphisms (both 388A>G and 521T>C) in any of the tested subgroups based on ethnicity, anti-TB drug regimen, diagnostic criteria of ATDILI, and the genotyping method used (S9 Table).

Discussion
To our knowledge, our current study is a large-scale meta-analysis evaluating the association between the risk of ATDILI and genetic polymorphisms of SLCO1B1 as well as various DMEs including CYP2E1, NAT2, and GST to provide more updated, comprehensive, and compelling evidence. Compared with previous meta-analyses, our present study included a larger number Consistent with previous studies, our current study suggested a significantly increased risk of ATDILI in patients with the NAT2 slow acetylator genotype (OR = 3.11, 95% CI 2.53-3.82), the CYP2E1 RsaI/PstI c1/c1 genotype (OR = 1.39, 95% CI 1.06-1.83), and the GSTM1 null genotype (OR = 1.30, 95% CI 1.12-1.52) 10 13 19 . Among these genotypes, the risk of ATDILI was increased the most in patients with the NAT2 slow acetylator genotype. In contrast, no significant association was observed between the risk of ATDILI and the genetic polymorphisms of CYP2E1 DraI, GSTT1, GSTM1/GSTT1, SLCO1B1 388A>G, and SLCO1B1 521T>C. Caution needs to be exercised when interpreting this study finding because the lack of significant association between these polymorphisms and the risk of ATDILI might result from small sample sizes and the low frequency of ATDILI reported in patients with these genetic polymorphisms.
When evaluating the impacts of the CYP2E1 RsaI/PstI and DraI genetic polymorphisms on the risk of ATDILI in our study, patients with the RsaI/PstI c1/c1 genotype were 1.39-times more likely to develop ATDILI. Similarly, in a previous meta-analysis by Deng and colleagues, the risk of ATDILI was 1.4-times higher in patients with the RsaI/PstI c1/c1 genotype compared to other genotypes 20 . In the liver, INH is metabolized by NAT2 to acetylisoniazid which is consequently oxidized by CYP2E1 to reactive intermediates in the formation of hepatotoxins 21 22 . The increased inducibility or greater activity of CYP2E1 in patients with the CYP2E1 RsaI/PstI c1/c1 genotype may result in the production of more intermediate hepatotoxins, ultimately leading to the increased risk of ATDILI 21 22 . Our subgroup analysis showed a significantly increased risk of ATDILI in the CYP2E1 RsaI/PstI c1/c1 genotype carriers of East Asian and Indian ethnicity (S6 Table), suggesting a potential gene-ethnicity interaction in these ethnic populations due to genetic characteristics of the ethnicity or environmental factors in these populations 23 . In addition to ethnicity, combination anti-TB therapy was shown to significantly increase the risk of ATDILI in patients with the CYP2E1 RsaI/PstI c1/c1 genotype (S6 Table). This is consistent with previous study findings because hepatotoxicity commonly occurs with anti-TB drugs and thus, use of more than one hepatotoxic anti-TB medications increases the risk of ATDILI 7 . Moreover, patients with the CYP2E1 RsaI/PstI c1/c1 genotype were at a significantly increased risk of ATDILI when ATDILI was defined as serum ALT concentrations elevated > 2 times the ULN and when their genotype was determined by the PCR-RFLP or sequencing method. This may suggest more sensitive diagnostic criteria and genotyping method to identify patients at an increased risk of ATDILI as early in therapy as possible. However, caution needs to be exercised when applying this study finding in practice because of the potentially low specificity associated with the diagnostic criteria of ATDILI and genotyping method. Future studies are warranted to confirm our subgroup analysis results.
Similar to previous studies, our current study suggested a significantly increased risk of ATDILI in patients with the NAT2 slow acetylator genotype compared to those with intermediate/fast acetylator genotypes 10 19 . The risk of ATDILI in slow acetylators remained significantly increased in all tested subgroups regardless of ethnicity, the anti-TB drug regimen used, the achievement of HWE, diagnostic criteria of ATDILI, and the genotyping method used (S7 Table). Among the subgroups, the ATDILI risk appeared the highest in the West Asian According to previous studies, GST enzymes, particularly those coded by GSTM1 and GSTT1 loci, are associated with the risk of drug-induced hepatotoxicity 10 24 . Consistent with previous studies, our current study demonstrated a significantly increased risk of ATDILI in individuals with the GSTM1 null genotype compared to those with the non-null genotype; however, the risk of ATDILI was not affected by the GSTT1 or GSTM1/GSTT1 genetic polymorphisms. GSTs are important enzymes to detoxify various xenobiotics and play an essential role in INH metabolism by eliminating acetyldiazene ketene acetylonium ion (a possibly hepatotoxic free radical metabolite of INH) from the body through GSTM1. This may account for the significant association of the ATDILI risk with the GSTM1 genotype, but not with the GSTT1 or GSTM1/GSTT1 genotypes 10 24 . Our subgroup analysis showed a significantly increased risk of ATDILI in the GSTM1 null genotype carriers of Indian ethnicity (S8 Table), suggesting a potential gene-ethnicity interaction due to unknown genetic characteristics or environmental factors such as diet in Indian patients 23 . In addition, the risk of ATDILI was significantly increased in patients with the GSTM1 null genotype when ATDILI was defined as serum ALT concentrations elevated > 2 times the ULN (S8 Table). Based on this finding, serum ALT concentrations elevated > 2 times the ULN may be suggested as more sensitive diagnostic criteria of ATDILI; however, it may result in the false positive identification of ATDILI patients without clinical significance due to potentially low specificity. Considering this is a subgroup analysis result, caution is warranted in interpreting and applying this finding in practice until SLCO1B1 encodes organic anion transporting polypeptide 1B1 (OATP1B1) which is a major influx drug transporter responsible for the hepatic uptake of various endogenous and exogenous substances including RIF 25 . Previous studies showed significantly altered systemic exposure of RIF in carriers of the SLCO1B1 polymorphism 26 27 . To our knowledge, only four studies have been conducted to examine the association between the ATDILI risk and the SLCO1B1 genetic polymorphisms 11 25 28 29 . Various single nucleotide polymorphisms (SNPs) of SLCO1B1 were evaluated in these studies; however, SLCO1B1 388A>G (rs2306283) and 521T>C (rs4149056) were the only polymorphisms assessed in common 11 25 28 29 . Therefore, to maximize the sample size in our current meta-analysis, we examined the association between the risk of ATDILI and the polymorphic genotypes of SLCO1B1 388A>G and 521 T>C. Similar to each of the included studies, we did not find a significantly altered risk of ATDILI in patients with the SLCO1B1 388A>G and 521T>C genetic polymorphisms. However, caution should be exercised when interpreting and applying our study findings in practice due to the limited genetic risk model evaluated and a small sample size for the association between the ATDILI risk and the SLCO1B1 genetic polymorphisms.
In our study, significantly high heterogeneity between studies was observed for CYP2E1 RsaI/PstI (I 2 = 60%, P < 0.0001), NAT2 (I 2 = 47%, P = 0.002), and GSTM1/GSTT1 (I 2 = 59%, P = 0.006). The high heterogeneity between studies may be due to substantial differences in ethnicity, the achievement of HWE, anti-TB drug regimen, the genotyping method used, and diagnostic criteria of ATDILI among the studies included in our analysis. To address the relatively high heterogeneity, we performed sensitivity analyses using the leave-one-out method by deleting one study after each analysis followed by repeating the meta-analysis. Through the sensitivity analyses, outlier studies were identified as the major source of heterogeneity. After removing these outlier studies, heterogeneity was remarkably reduced (I 2 = 60% to 34% for CYP2E1 RsaI/PstI, I 2 = 47% to 32% for NAT2, I 2 = 33% to 0% for GSTM1, I 2 = 59% to 0% for GSTM1/GSTT1). The overall results for the association between the risk of ATDILI and genetic polymorphisms of these enzymes after excluding the outlier studies were not changed, indicating the robustness of our analysis result.
There are limitations to this study. First, due to the lack of information regarding other patient characteristics potentially associated with liver injuries, our estimated ORs were not adjusted based on the potential risk factor of drug-induced liver injuries such as age, alcohol consumption, cigarette smoking, and other lifestyle characteristics 7 9 . Second, our literature search limited to the articles published in English may lead to language bias. Third, the effect of anti-tuberculosis drug dosages on the risk of ATDILI could not be accounted for in our study because this information was not available in most of the included studies. In addition, a specific causative agent of ATDILI could not be identified in our analysis because most patients in our included studies received a combination regimen of anti-tuberculosis drugs. Lastly, only the limited number of genotypes were assessed for the association with the risk of ATDILI, particularly for SLCO1B1 genetic polymorphisms. Future studies are needed to comprehensively and adequately address the relationship between the ATDILI risk and various polymorphisms of the genes for drug-metabolizing enzymes and drug transporters by using different genetic risk models and including more polymorphic genotypes.
In conclusion, the risk of ATDILI during TB therapy was significantly increased in TB patients carrying NAT2 slow acetylator, CYP2E1 RsaI/PstI c1/c1, or GSTM1 null genotype.

Supporting information
Additional supporting information can be found in the online version of this article: S1     RsaI/PstI c1/c1 genotype compared to c1/c2 + c2/c2 genotypes and (B) DraI D/D genotype compared to D/C + C/C genotypes.

METHODS
Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number.
not applicable Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

Page 7-8
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

Page 7
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

Page 7
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

Page 7-8
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

Page 8
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.
Page 8

Risk of bias in individual studies
12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

RESULTS
Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.

Figure 1
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.

Page 8
Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12). Table 1 Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.

Page 8-13
Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. Page 8-13 Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Supplementar y Figure S5 Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]

60
ATDILI is more likely to occur in tuberculosis patients with NAT2 slow acetylator genotype, warranted for patients with these genotypes. 63 64 Strengths and limitations of this study 65  This is the first meta-analysis to evaluate the association between the risk of ATDILI 66 and SLCO1B1 in TB patients.      However, conflicting results have been reported regarding the association between the risk of 93 ATDILI and genetic polymorphisms of various DMEs in tuberculosis patients 9 12 13 . In addition 94 to DMEs, drug transporters have been emerging as a key determinant of the pharmacokinetics 95 and pharmacodynamics of a drug 14 . Among various drug transporters, organic anion and SLCO1B1 genetic polymorphisms on the ATDILI risk through meta-analysis.

106
Objectives 107 The objective of this meta-analysis was to evaluate the association between the risk of ATDILI 108 and genetic polymorphisms of CYP2E1, NAT2, GST, and SLCO1B1 in tuberculosis patients. conclusions (S1 Table). Three authors (SY, JP, and SH) independently conducted a literature 114 search, study selection, quality assessment, and data extraction. Any discrepancies were 115 adjudicated by corresponding authors (JIL and EKC). keywords and Medical Subject Heading (MeSH) terms: ("genetic polymorphism" or "NAT2" or 122 "CYP2E1" or "GST" or "SLCO1B1" or "drug-metabolizing enzymes" or "drug transporter") 123 AND ("anti-tuberculosis agents drug-induced liver injuries" or "hepatotoxicity"). The detailed 124 search strategies for each electronic database used in this analysis are presented in S2 Table. The  Quality assessment and data extraction 139 The quality of included studies was assessed using the revised Little's recommendation based on 140 the following criteria 16 17 : (1) (7) logical discussion of study bias.

143
Studies with an overall score of ≥ 4 (range 0 to 7) were considered high quality and retained in 144 the analysis.

145
The following data were extracted from each study using a standardized extraction form:

146
(1) name of the first author; (2)   the genetic polymorphisms and the risk of ATDILI was estimated using pooled odds ratios (ORs) 169 with the corresponding 95% confidence intervals (CIs). The statistical significance of an OR was 170 defined as P < 0.05 from the Z test.

171
Subgroup analysis was performed based on ethnicity, anti-TB drug regimen used, and the type of 172 study design. Sensitivity analysis was conducted to assess the robustness of the results and to 173 identify the source of heterogeneity using the leave-one-out method. In each analysis, one study 174 was deleted, and with the one study left out, the meta-analysis was performed; this process was 175 repeated until every study had been deleted from our included study pool for each tested  Patients and public were not involved in the design of this study.   Table). No significant 217 association was observed between the risk of ATDILI and the CYP2E1 RsaI/PstI c1/c1 genotype 218 when evaluating studies with the same study design only (i.e., either case-control studies or 219 cohort studies) (S9 Table). Overall, 35 studies with 1323 cases and 7319 controls were included in our primary analysis for 54%, P heterogeneity < 0.0001) (Figure 3). In the subgroup analysis based on ethnicity, anti-TB drug 230 regimens used, and study design, the risk of ATDILI was significantly increased in slow 231 acetylators compared to fast or intermediate acetylators in all subgroups (S10 Table).  Table). In the subgroup analyses by 240 study design, the estimated OR (95% CI, P-value; I 2 , P heterogeneity ) for the GSTM1 null genotype respectively (S11 Table). association between the risk of ATDILI and the GSTT1 and the GSTM1/GSTT1 polymorphisms 252 (S11 Table).  recessive, or additive genetic model (Table 2). Due to the lack of significant association between 261 the risk of ATDILI and the tested SLCO1B1 genetic polymorphisms in our primary meta-262 analysis, subgroup analyses were not performed for these genetic polymorphisms. polymorphisms. This high heterogeneity between studies may be due to substantial differences in 268 ethnicity, anti-TB drug regimen, the genotyping method used, study design, and diagnostic 269 criteria of ATDILI among the included studies (Table 1). Through the sensitivity analyses, outlier studies were identified as the major source of heterogeneity. After removing these outlier 271 studies, heterogeneity was substantially reduced (I 2 = 60% to 42% for CYP2E1 RsaI/PstI 23 , I 2 = 272 54% to 34% for NAT2 24 25 , I 2 = 59% to 0% for GSTM1/GSTT1 26 27 Table), 305 suggesting a potential gene-ethnicity interaction 33  null genotype (S11 Table). Considering the substantial difference in the GSTM1 null allele 351 frequency between Indians (29.6%) and East Asians (52.1%), a potential gene-ethnicity 352 interaction may exist based on their race, ethnicity, and body size as aforementioned 34 41  phenotype (e.g., NAT2*5B, *6A, and *7B all represent slow acetylator genotypes), and the 385 genetic model selection can be varied depending on the specific allelic variant 47 . Therefore, the 386 genetic models used in previous original and meta-analysis studies were adopted for these 387 polymorphic genes in our current study 9 18 19 . Future studies are needed to comprehensively and 388 adequately address the relationship between the ATDILI risk and various genetic polymorphisms 389 by using different genetic risk models and including more polymorphic genotypes.

Strengths and limitations of this study
 This is the first meta-analysis to evaluate the association between the risk of ATDILI and SLCO1B1 in patients with tuberculosis.
 We included most updated studies with the large sample sizes to better clarify the association of genetic polymorphisms with the risk of ATDILI.
Altered enzyme activity due to polymorphic genotypes of various DMEs including cytochrome P450 2E1 (CYP2E1), N-acetyltransferase 2 (NAT2), and glutathione S-transferase (GST) can result in the accumulation of toxic substances in the liver, leading to the development of ATDILI 11 . However, conflicting results have been reported regarding the association between the risk of ATDILI and genetic polymorphisms of various DMEs in patients with tuberculosis 9 12 13 . In addition to DMEs, drug transporters have been emerging as a key determinant of the pharmacokinetics and pharmacodynamics of a drug 14 . Among various drug transporters, organic Therefore, an updated meta-analysis has been warranted to confirm the association between the ATDILI risk and genetic polymorphisms of DMEs. In our preliminary literature search, several polymorphic genes, including many DMEs, transporters, and other genes such as those involved in the immune system, were identified to have an association with the risk of ATDILI. Among these, sufficient, published information was available to confirm the effect of CYP2E1, NAT2, GST, and SLCO1B1 genetic polymorphisms on the ATDILI risk through meta-analysis.

Objectives
The objective of this meta-analysis was to evaluate the association between the risk of ATDILI and genetic polymorphisms of CYP2E1, NAT2, GST, and SLCO1B1 in patients with tuberculosis.

Methods
This study was in compliance with the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) checklist for reporting the study design, search strategy, methods, results, and conclusions (S1 Table). Three authors (SY, JP, and SH) independently conducted a literature search, study selection, quality assessment, and data extraction. Any discrepancies were adjudicated by corresponding authors (JIL and EKC). and Medical Subject Heading (MeSH) terms: ("genetic polymorphism" or "NAT2" or "CYP2E1" or "GST" or "SLCO1B1" or "drug-metabolizing enzymes" or "drug transporter") AND ("antituberculosis agents drug-induced liver injuries" or "hepatotoxicity"). The detailed search strategies for each electronic database used in this analysis are presented in S2 Table. The reference lists in the selected reviews and meta-analyses were reviewed to ensure the inclusion of all relevant evidence in this analysis.

Study selection
Studies were considered eligible if they met all of the following inclusion criteria: (1)

Quality assessment and data extraction
The quality of included studies was assessed using the revised Little's recommendation based on the following criteria 16 17 : (1) scientific design; (2) definite inclusion of study population; (3) explicit information on study population; (4) explicit diagnostic criteria of ATDILI; (5) genetic detection method; (6) appropriate statistical analysis; and (7) logical discussion of study bias.
Studies with an overall score of ≥ 4 (range 0 to 7) were considered high quality and retained in the analysis.

Statistical analysis
The genotypes were analyzed based on the following proposed genetic risk model: and (6) SLCO1B1 388A>G and 521T>C polymorphisms. The genetic risk models for NAT2, CYP2E1, GSTM1, GSTT1, and GSTM1/GSTT1 have been studied in previous studies 9 18 19 . Based on these previous studies, the most clinically significant and plausible model for each polymorphic gene was selected. Due to the relative paucity of data suggesting the most clinically  22 . The strength of the association between the genetic polymorphisms and the risk of ATDILI was estimated using pooled odds ratios (ORs) with the corresponding 95% confidence intervals (CIs). The statistical significance of an OR was defined as P < 0.05 from the Z test.
Subgroup analysis was performed based on ethnicity, anti-tuberculosis drug regimen used, and the type of study design. Sensitivity analysis was conducted to assess the robustness of the results and to identify the source of heterogeneity using the leave-one-out method. In each analysis, one study was deleted, and with the one study left out, the meta-analysis was performed; this process was repeated until every study had been deleted from our included study pool for each tested polymorphic gene. Publication bias was evaluated with a symmetrical funnel plot. Statistical analyses were performed using Review Manager Software version 5.3 (Cochrane Collaboration, London, UK). Patients and public were not involved in the design of this study.

Study selection and characteristics
Overall  depending on the study. The quality score of the included studies was 6 or greater based on the revised Little's recommendation (Table 1, S3 Table) 16 17 . Genotype distribution and genotyping   Table). No significant association was observed between the risk of ATDILI and the CYP2E1 RsaI/PstI c1/c1 genotype when evaluating studies with the same study design only (i.e., either case-control studies or cohort studies) (S9 Table).
In our primary analysis for the CYP2E1 DraI polymorphism with six studies including 233 cases and 1272 controls, no significant association was observed using the fixed-effects model between the risk of ATDILI and the DraI polymorphism (OR for the D/D genotype = 0.93, 95% CI 0.68-1.27, P = 0.64; I 2 = 0%, P heterogeneity = 0.51) ( Figure 2B). 54%, P heterogeneity < 0.0001) (Figure 3). In the subgroup analysis based on ethnicity, antituberculosis drug regimens used, and study design, the risk of ATDILI was significantly increased in slow acetylators compared to fast or intermediate acetylators in all subgroups (S10 Table).

GST
For the GSTM1 polymorphism, a total of 19 studies with 977 cases and 5119 controls were included in our primary analysis. Using the fixed-effects model, the pooled estimates of all included studies (n = 19) showed a significant association between the risk of ATDILI and the GSTM1 polymorphism (OR for the GSTM1 null genotype = 1.30, 95% CI 1.12-1.52, P = 0.0007; I 2 = 33%, P heterogeneity = 0.08) ( Figure 4A). When studies were stratified for ethnicity, the risk of ATDILI was significantly increased for the GSTM1 null genotype in Indians (OR = 1.68, 95% CI 1.30-2.19, P < 0.0001; I 2 = 36%, P heterogeneity = 0.15) (S11 Table). In the subgroup analyses by study design, the estimated OR (95% CI, P-value; I 2 , P heterogeneity ) for the GSTM1 null genotype relative to the non-null genotype was 1.41 (1.04-1.93, P = 0.03; I 2 = 44%, P heterogeneity = 0.08) in cohort studies and 1.25 (1.01-1.55, P = 0.20; I 2 = 29%, P heterogeneity = 0.17) in case-control studies, respectively (S11 Table).  (Figures 4B and 4C). When studies were stratified for ethnicity, anti-tuberculosis drug regimens used, and study design, no subgroups showed significant association between the risk of ATDILI and the GSTT1 and the GSTM1/GSTT1 polymorphisms (S11 Table).

SLCO1B1
For the SLCO1B1 388A>G polymorphism, four studies with 302 cases and 913 controls were included in our primary analysis. Using the dominant, recessive, or additive genomic model, no significant association was observed between the risk of ATDILI and the SLCO1B1 388A>G polymorphism ( Table 2). For the SLCO1B1 521T>C polymorphism, four studies with 314 cases and 912 controls were included in our primary analysis. No significant association was found between the ATDILI risk and the SLCO1B1 521T>C polymorphism under the dominant, recessive, or additive genetic model (Table 2). Due to the lack of significant association between the risk of ATDILI and the tested SLCO1B1 genetic polymorphisms in our primary metaanalysis, subgroup analyses were not performed for these genetic polymorphisms.

Sensitivity analysis
Our primary analysis results showed significantly high heterogeneity between studies for polymorphisms. This high heterogeneity between studies may be due to substantial differences in  24 25 , I 2 = 59% to 0% for GSTM1/GSTT1 26 27 , and I 2 = 66 % to 0% for SLCO1B1 521T>C dominant genetic model 28 ). The overall results for the association between the risk of ATDILI and these genetic polymorphisms after excluding the outlier studies stayed the same as those from our primary analysis results.

Discussion
In this study, we conducted a large-scale meta-analysis evaluating the association between the risk of ATDILI and genetic polymorphisms of SLCO1B1 as well as various DMEs including CYP2E1, NAT2, and GST to provide more updated, comprehensive, and compelling evidence.
Compared with previous meta-analyses, our present study included a larger number of studies, which may sufficiently increase the statistical power compared to individual studies. However, a limited number of studies for the SLCO1B1 genetic polymorphisms were included (n = 4).
Consistently with previous studies, our current study suggested a significantly increased risk of  Table), suggesting a potential gene-ethnicity interaction 33  population might serve as a good control to estimate the effect of c1 allele on the risk of ATDILI; the rarity of this minor allele in other ethnicities could make it difficult to evaluate the association between the ATDILI risk and this genetic polymorphism 35 . In addition to ethnicity, combination anti-tuberculosis therapy was shown to significantly increase the risk of ATDILI in patients with the CYP2E1 RsaI/PstI c1/c1 genotype (S9 Table). This is consistent with previous study findings because hepatotoxicity commonly occurs with anti-tuberculosis drugs such as INH and RIF and thus, use of more than one hepatotoxic anti-tuberculosis medication increases the risk of ATDILI 7 .
In conclusion, the risk of ATDILI during tuberculosis therapy was significantly increased in patients with tuberculosis carrying NAT2 slow acetylator, CYP2E1 RsaI/PstI c1/c1, or GSTM1 null genotypes. Screening for these genetic polymorphisms, particularly for the NAT2 slow acetylator genotype, may be of great clinical benefit to identify patients at high risk for ATDILI and minimize the risk of ATDILI. Future studies are pertinent to develop dose and/or treatment adjustment strategies, to evaluate the feasibility and cost-effectiveness of the genetic screening test, and to assess the effect of more genetic polymorphisms on the risk of ATDILI for optimal prevention and management of ATDILI.

Competing interests
None declared