Pregnane X Receptor Polymorphisms and Risk of Inflammatory Bowel Disease: A Meta-Analysis
Bibliographic record
Abstract
Background: Pregnane X receptor (PXR) gene polymorphisms have been widely studied in terms of the association with inflammatory bowel disease (IBD), with inconsistent results.Objective: The present meta-analysis was performed to assess the association between PXR gene polymorphisms and the susceptibility of IBD, Crohn’s disease (CD), and ulcerative colitis (UC).Methods: PubMed, Wanfang, and CNKI databases were searched for eligible studies before November 1, 2016. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to calculate the various genetic models using either a fixed-effect or a random-effect model. The heterogeneity of the included studies was examined with Cochran Q and I2 statistics. Begg’s rank correlation test and Egger’s linear regression test were used to assess the publication bias.Results: A total of six studies with 4248 cases and 3853 controls were included in this meta-analysis. Three PXR gene polymorphisms were evaluated: rs1523127, rs2276707, and rs6785049. Our analyses of rs1523127, rs2276707, and rs6785049 suggested that PXR gene polymorphism had no obvious influence on the risk of IBD in Caucasians. Subgroup analyses based on disease type showed similar results.Conclusion: Our meta-analysis revealed that PXR gene polymorphism may not be significantly associated with IBD susceptibility. However, the number of original studies was limited and further studies with large samples are needed to verify the results.Abbreviations: PXR = pregnane X receptor, IBD = inflammatory bowel disease, CD = Crohn’s disease, UC = ulcerative colitis, ORs = pooled odds ratios, 95% CIs = 95% confidence intervals, NOS = Newcastle–Ottawa scale, HWE = Hardy–Weinberg equilibrium.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.051 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".