Genetic polymorphism and risk of anti-tuberculosis drug-induced liver injury (AT-DILI): a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Anti-tuberculosis (TB) drugs like isoniazid and rifampin can cause hepatotoxicity leading to treatment termination. Although Genome-wide association studies (GWAS) have identified variants linked to the risk of developing anti-tuberculosis drug-induced liver injury (AT-DILI), findings remain inconsistent. This study aimed to systematically summarise previous observational studies and assess the association between genetic polymorphisms and AT-DILI risk in adults. We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Libraries until January 10, 2023. The Newcastle-Ottawa Scale checklist was used to assess the methodological quality of the included studies. Pooled odds ratios (OR) with 95% confidence intervals (CIs) were employed using a random-effect model with the I 2 statistic to estimate the heterogeneity of results. Our study included 10 studies (n=3,322) of Asian ancestry. We identified genetic variants in drug-metabolizing enzymes, including NAT2, CYP2E1, and PXR, linked to AT-DILI risk. CYP2E1 C1/C1 and slow acetylators of NAT2*6A/6A, NAT26A/7B, NAT27B/7B, and NAT25B/7B genotypes were associated with increased risk, while rapid acetylators of NAT24/4 and NAT24/7B were linked to decreased risk. No significant association was found between CYP2E1B C1/C2, NAT2(*4/*6A, *4/*5B, *5B/*5B) and PXR with AT-DILI risk. This study revealed that NAT2 slow acetylator genotypes or CYP2E1 C1/C1 are causally linked to AT-DILI risk. The findings suggest that genetic variants in drug-metabolizing enzymes regulated by NAT2 and CYP2E1 are involved in developing drug-induced liver injury in users of anti-TB drugs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".