<i>PTPN22</i> R620W Polymorphism and ANCA Disease Risk in White Populations: A Metaanalysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it