TNFRSF1B Is Associated with ANCA in IBD
Bibliographic record
Abstract
The genetic basis of antineutrophil cytoplasmic antibody, an important biomarker of inflammatory bowel disease (IBD), has never been thoroughly examined on a genome-wide scale. In this study, we performed a 2-stage genome-wide association study (GWAS) on antineutrophil cytoplasmic antibody in IBD cases. In the 2959 IBD cases in the discovery stage, we observed an association between a variant in the gene TNFRSF1B with antineutrophil cytoplasmic antibody level (rs5745994, minor allele frequency = 0.028, beta = 18.12, 95% CI, 11.82-24.22, P = 1.89 × 10). This association was replicated in an independent cohort of 419 IBD cases (beta = 16.91, 95% CI, 6.13-27.69, P = 2.38 × 10). With a Q-value of 0.036, we performed a fixed-effect meta-analysis for the association of rs5745994 in both cohorts and observed a stronger association signal (beta = 17.81, 95% CI, 12.36-23.25, P = 8.97 × 10). TNFRSF1B gene codes for tumor necrosis factor (TNF) receptor 2 (TNFR2), thereby we examined the reported TNFRSF1B variant with serum TNFR2 level. We observed a negative association with serum TNFR2 level being 8.23 EU/mL in carriers and 9.12 EU/mL in noncarriers (P = 0.033). This finding indicates the functional role of identified TNFRSF1B variant in IBD serology and may be reflective of the underlying biological mechanisms that determine clinical expression and/or response to certain therapies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".