Association between <i>ABCG2</i> polymorphisms and allopurinol response in gout patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Recent studies suggest that single nucleotide polymorphisms in the adenosine triphosphate (ATP)-binding cassette subfamily G member 2 (ABCG2) gene, particularly rs2231142 and rs10011796, may influence individual responses to allopurinol. However, existing evidence remains inconclusive.Aim This systematic review and meta-analysis aimed to investigate the association between ABCG2 polymorphisms and allopurinol response in gout patients.Methods A comprehensive search of Scopus, PubMed, Web of Science, EBSCOhost, and the Clinical Pharmacogenomic Resource was conducted for observational studies up to May 2025. Two authors independently screened studies, extracted data, and assessed study quality using the Newcastle-Ottawa Scale. Pooled odds ratios with 95% confidence intervals were calculated using a random-effects model across codominant, dominant, and recessive genetic models. Statistical heterogeneity was evaluated using the I2 statistic, and sensitivity analyses were performed.Results Six studies met the inclusion criteria for the review, and five were included in the meta-analysis. A significant association was observed between rs2231142 with poor allopurinol response, but not rs10011796. Sensitivity analyses confirmed the robustness of the findings for rs2231142.Conclusion The findings suggest that ABCG2 rs2231142 influences allopurinol response. These results underscore the potential of rs2231142 as a predictive genetic marker for allopurinol efficacy and may inform the development of pharmacogenomic guidelines for gout management.This systematic review and meta-analysis was not registered in any protocol registry.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".