Role of Macrophage Migration Inhibitory Factor in Granulomatosis With Polyangiitis
Bibliographic record
Abstract
OBJECTIVE: To examine the association between macrophage migration inhibitory factor (MIF) promoter polymorphisms and granulomatosis with polyangiitis (GPA) in human subjects, and to assess the role of MIF in a murine model of granulomatous vasculitis. METHODS: promoter microsatellite (rs5844572). MIF promoter, CATT-length-dependent gene expression in response to β-glucan was assessed by gene reporter assays. In mouse studies, granulomatous disease was induced by injection of Candida albicans β-glucan into wild-type (WT) or Mif-knockout (Mif-KO) C57BL/6 mice and C57BL/6 mice transgenically overexpressing Mif in lung epithelium (Mif lung-Tg2.1). Mice were treated with a neutralizing anti-MIF antibody and analyzed for the density of pulmonary granulomas, expression of inflammatory chemokines, and frequency of mortality. RESULTS: The percentage of human subjects carrying >5 CATT repeats in each MIF allele (high genotypic MIF expressers) was 60.2% among patients with GPA and 53.9% among healthy controls (adjusted P = 0.049). In response to granulomatous stimulation, human MIF gene expression increased proportionally with CATT length. Mif lung-Tg2.1 mice exhibited more pulmonary granulomas than WT mice, which in turn showed more granulomas than Mif-KO mice. A significantly higher percentage of Mif lung-Tg2.1 mice, compared to Mif-KO or WT mice, died when injected with Candida albicans β-glucan, and treatment of these mice with an anti-MIF monoclonal antibody protected against a lethal outcome. Levels of MIF-dependent neutrophil/macrophage chemokines were elevated in the bronchoalveolar lavage fluid or plasma of Mif lung-Tg2.1 mice. CONCLUSION: Patients with GPA have an increased frequency of high MIF expression CATT alleles. Higher Mif expression increases the incidence of mortality and pulmonary granulomas in Mif lung-Tg2.1 mice, while anti-MIF treatment protects these mice against death. Blockade of MIF in high genotypic MIF expressers may therefore offer a selective pharmacologic therapy for GPA.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".