Meta‐analysis of genetic polymorphisms in granulomatosis with polyangiitis (Wegener's) reveals shared susceptibility loci with rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To examine the association of previously identified autoimmune disease susceptibility loci with granulomatosis with polyangiitis (Wegener's) (GPA), and to determine whether the genetic susceptibility profiles of other autoimmune diseases are associated with those of GPA. METHODS: Genetic data from 2 cohorts were meta-analyzed. Genotypes for 168 previously identified single-nucleotide polymorphisms (SNPs) associated with susceptibility to different autoimmune diseases were ascertained in a total of 880 patients with GPA and 1,969 control subjects of European descent. Single-marker associations were identified using additive logistic regression models. Associations of multiple SNPs with GPA were assessed using genetic risk scores based on susceptibility loci for Crohn's disease, type 1 diabetes, systemic lupus erythematosus, rheumatoid arthritis (RA), celiac disease, and ulcerative colitis. Adjustment for population substructure was performed in all analyses, using ancestry-informative markers and principal components analysis. RESULTS: Genetic polymorphisms in CTLA4 were significantly associated with GPA in the single-marker meta-analysis (odds ratio [OR] 0.79, 95% confidence interval [95% CI] 0.70-0.89, P = 9.8 × 10(-5) ). The genetic risk score for RA susceptibility markers was significantly associated with GPA (OR 1.05 per 1-unit increase in genetic risk score, 95% CI 1.02-1.08, P = 5.1 × 10(-5) ). CONCLUSION: RA and GPA may arise from a similar genetic predisposition. Aside from CTLA4, other loci previously found to be associated with common autoimmune diseases were not statistically significantly associated with GPA in this study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; both teacher heads agree on what is shown here.
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".