Lack of Association Between IRF5 Gene Polymorphisms and Biopsy-proven Giant Cell Arteritis
Bibliographic record
Abstract
OBJECTIVE: A novel association with a 100-kb region on chromosome 9 that contains the tumor necrosis factor receptor-associated factor 1 (TRAF1) and C5 genes has been observed in some autoimmune rheumatic diseases, in particular in rheumatoid arthritis. We analyzed the influence of 2 single-nucleotide polymorphisms (SNP) from the TRAF1/C5 region in susceptibility to giant cell arteritis (GCA). METHODS: We assessed 220 patients with biopsy-proven GCA and 410 matched controls. DNA from patients and controls was obtained from peripheral blood. Samples were genotyped for the rs10818488 and rs2900180 TRAF1/C5 gene polymorphisms by polymerase chain reaction, using a predesigned TaqMan allele discrimination assay. RESULTS: A genotyping rate of 95% was achieved in this series of GCA. No significant differences in the genotype distribution between GCA patients and controls were found for the 2 SNP. GCA patients exhibited a reduced frequency of TRAF1/C5 AA homozygosity (7.6%) compared to controls (12.7%) but the difference was only marginally significant (OR 0.58, 95% CI 0.30-1.11, p = 0.07). The frequency of minor allele T of TRAF1/C5 rs2900180 was also slightly reduced in patients (24.3%) compared to controls (27.8%) (p = 0.19). No significant differences were observed when patients were stratified according to the presence of specific clinical disease features. CONCLUSION: Our results showed no influence of rs10818488 and rs2900180 TRAF1/C5 gene polymorphisms in susceptibility to and clinical expression of GCA.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".