<i>PTPN22</i> R620W Polymorphism and ANCA Disease Risk in White Populations: A Metaanalysis
Bibliographic record
Abstract
OBJECTIVE: No clear consensus has been reached on the PTPN22 R620W polymorphism and anti-neutrophil cytoplasmic antibody (ANCA) disease, especially when stratified by ANCA specificity and disease phenotypes. METHODS: A metaanalysis was conducted on the PTPN22 R620W polymorphism across 4 studies in 1399 white patients with ANCA disease and 9934 normal control subjects. RESULTS: Overall, metaanalysis showed a statistically significant association between the A allele and ANCA disease in all subjects (OR 1.44, 95% CI 1.26-1.64, p < 0.00001), and stratification by disease category indicated the A allele was associated with granulomatosis with polyangiitis (Wegener's; GPA; OR 1.72, 95% CI 1.35-2.20, p < 0.0001) and microscopic polyangiitis (MPA; OR 1.53, 95% CI 1.08-2.15, p = 0.02) as compared to controls. However, when stratified by ANCA specificity, the association of the A allele was statistically evident among those with proteinase 3 (PR3) ANCA disease (OR 1.74, 95% CI 1.25-2.430, p = 0.001), with the same trend but not statistically associated with myeloperoxidase ANCA disease (OR 1.94, 95% CI 0.64-5.85, p = 0.24). The marked associations were also demonstrated between this allele with lung (OR 1.69, 95% CI 1.21-2.36, p = 0.002), ENT (OR 2.03, 95% CI 1.45-2.84, p < 0.0001), skin (OR 2.55, 95% CI 1.69-3.84, p < 0.0001), and peripheral neuropathy involvement (OR 2.12, 95% CI 1.39-3.22, p = 0.0005). CONCLUSION: The PTPN22 620W allele confers susceptibility to the occurrence and development of ANCA disease in whites, with specific evidence among subsets with GPA, MPA, and PR3 ANCA.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.038 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".