P1201 Association between Inflammatory Bowel Disease and Henoch-Schönlein purpura: A Bidirectional Two-Sample Mendelian Randomization Study
Bibliographic record
Abstract
Abstract Background Henoch-Schönlein purpura (HSP) is a systemic small-vessel vasculitis, and its association with inflammatory bowel disease (IBD) has been the focus of considerable research. Despite numerous studies, it remains uncertain whether and in which direction causal relationships exist between HSP and IBD. To reveal the causal association between HSP and IBD, we conducted a bidirectional two-sample Mendelian randomization analysis using publicly available genome-wide association study (GWAS) summary statistics. Methods We obtained summarized data for IBD, Crohn's disease (CD), ulcerative colitis (UC), and HSP from various GWAS. To estimate causality, we used inverse-variance weighted approaches. Additionally, we conducted several sensitivity analyses. In our causality estimates, we present odds ratios (ORs) and 95% confidence intervals (CIs). Results We found that CD (OR: 1.12, 95% CI: 1.00 to 1. 25, P < 0.05), but not UC (OR: 1.04, 95% CI: 0. 909 to 1.19, P > 0.05), had significant positive causal effects on HSP risk. However, the overall result of the MR study demonstrated that there was no causal link between genetic predisposition to IBD and an increased risk of HSP (OR: 1.10, 95% CI: 0.989 to 1.23, P > 0.05). Regarding the reverse directions, no significant causal associations were discovered. Conclusion It appears that CD and HSP are causally related, which could influence clinical decisions regarding the management of CD in patients diagnosed with HSP. However, neither overall IBD nor UC has a causal effect on HSP.
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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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".