<i>ABCB1</i>and<i>ABCC3</i>Gene Polymorphisms Are Associated with First-year Response to Methotrexate in Juvenile Idiopathic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Although methotrexate (MTX) is the most widely prescribed drug in juvenile idiopathic arthritis (JIA), 30% of patients fail to respond to it. To individualize treatment strategies, the genetic determinants of response to MTX should be identified. METHODS: A cohort of 287 patients with JIA treated with MTX was studied longitudinally over the first year of treatment. MTX response was defined as the American College of Rheumatology pediatric 70 criteria (ACRped70). We genotyped 21 single-nucleotide polymorphisms in 13 genes related to MTX polyglutamylation and to cellular MTX uptake and efflux. Potential associations between ACRped70 and genotypes were analyzed in a multivariate model and corrected for these 3 covariates: disease duration prior to MTX treatment, physician's global assessment of disease activity at baseline, and MTX dose at all study visits. RESULTS: MTX response was more often achieved by patients variant for the adenosine triphosphate-binding cassette transporter B1 (ABCB1) gene polymorphism rs1045642 (OR 3.80, 95% CI 1.70-8.47, p = 0.001) and patients variant for the ABCC3 gene polymorphism rs4793665 (OR 3.10, 95% CI 1.49-6.41, p = 0.002) than by patients with other genotypes. Patients variant for the solute carrier 19A1 (SLC19A1) gene polymorphism rs1051266 were less likely to respond to MTX (OR 0.25, 95% CI 0.09-0.72, p = 0.011). CONCLUSION: ABCB1 rs1045642, ABCC3 rs4793665, and SLC19A1 rs1051266 polymorphisms were associated with response to MTX in 287 patients with JIA studied longitudinally. Upon validation of our results in other JIA cohorts, these genetic determinants may help to individualize treatment strategies by predicting clinical response to MTX.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".