Influence of <i>IL2RA</i> rs2104286 Polymorphism in the Risk of Biopsy-proven Giant Cell Arteritis
Bibliographic record
Abstract
OBJECTIVE: To assess the influence of the IL2RA rs2104286 A>G polymorphism on susceptibility to and clinical spectrum of manifestations of biopsy-proven giant cell arteritis (GCA). METHODS: Our study included 318 patients with biopsy-proven GCA. DNA from patients and healthy controls was obtained from peripheral blood. Samples were genotyped for the IL2RA rs2104286 A>G polymorphism using a predesigned TaqMan allele discrimination assay and by PCR amplification. RESULTS: Although GCA patients showed a higher frequency of the minor allele homozygote of IL2RA rs2104286 (GG) compared to controls (5.1% vs 2.8%, respectively; p = 0.06, odds ratio 1.84, 95% confidence interval 0.91-3.70), the allele distribution showed no significant differences between GCA patients and controls. Stratification of GCA patients according to sex or polymyalgia rheumatica, jaw claudication, visual ischemic manifestations, or other severe ischemic complications did not yield significant differences in the allele or genotype frequencies of the IL2RA rs2104286 polymorphism. CONCLUSION: IL2RA rs2104286 polymorphism does not appear to be a genetic risk factor for susceptibility to biopsy-proven GCA. Also, this polymorphism does not seem to be implicated in the clinical expression of this vasculitis.
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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 | 0.002 |
| 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) | 0.002 | 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".