Association between TXNRD1 polymorphisms and anti-tuberculosis drug-induced hepatotoxicity in a prospective study
Bibliographic record
Abstract
Anti-tuberculosis drug-induced hepatotoxicity (ATDH) is a serious adverse reaction to anti-tuberculosis (TB) treatment. Thioredoxin reductase 1 (TXNRD1), encoded by the TXNRD1 gene, is an important enzyme involved in oxidant challenge. TXNRD1 plays a key role in regulating cell growth and transformation, and protects cells against oxidative damage. We investigated the association between TXNRD1 polymorphisms and ATDH susceptibility. In this prospective study, 280 newly diagnosed TB patients were followed-up for 3 months after beginning anti-TB therapy. Tag single-nucleotide polymorphisms (tag-SNPs) of TXNRD1 were selected using Haploview 4.2 based on the HapMap database of the Chinese Han in Beijing (CHB) panel. Genotyping was performed using the MassARRAY platform. Of the 280 patients enrolled in this study, 33 were lost to follow-up, 24 had ATDH, and 223 were free from ATDH. After adjusting for sex, age, smoking status, and body mass index, there were no significant differences in the allele and genotype frequency distributions of TXNRD1 SNPs between the ATDH and non-ATDH groups (all P > 0.05). The haplotype analysis showed that haplotype TCAGCC was associated with an increased risk of ATDH susceptibility [P = 0.024, OR (95%CI) = 6.273 (1.023-38.485)]. Further stratified analyses showed that the haplotype TCAGCC was associated with ATDH susceptibility in female subjects [P = 0.036, OR (95%CI) = 5.711 (0.917-35.560)] and non-smokers [P = 0.029, OR (95%CI) = 6.008 (0.971-37.158)]. Our results suggest that TXNRD1 variants may favor ATDH susceptibility in females and non-smokers. Further studies are required to verify this association.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".