Low Copy Number of the Fc-γ Receptor 3B Gene<i>FCGR3B</i>Is a Risk Factor for Primary Sjögren’s Syndrome
Bibliographic record
Abstract
OBJECTIVE: Immune complexes play an important role in the pathogenesis of primary Sjögren's syndrome (pSS). Crosslinking of the neutrophil-specific Fc-γ receptor 3b (FCGR3B) facilitates immune complex clearance, and copy number variation (CNV) of the FCGR3B gene is known to reduce the uptake, and potentially clearance, of circulating immune complexes. Our objective was to determine whether FCGR3B CNV is a risk factor for pSS. METHODS: This was a cross-sectional study of patients with established pSS (n = 174) and population-matched controls (n = 162). FCGR3B CNV was determined by a quantitative real-time polymerase chain reaction assay, using genomic DNA as template and Taqman chemistry. Reactions were performed as a duplex, with RNAse P as the reference gene. Clinical and serological data were analyzed for their association with FCGR3B copy number (CN). RESULTS: Low FCGR3B CN (< 2 copies) was a risk factor for pSS in this cohort (p = 0.016), and combined results from this and a previous study yielded an overall OR of 2.3 (95% CI 1.3, 3.9, p = 0.003). Among patients with pSS in our cohort, low FCGR3B CN was not associated with anti-Ro ± La autoantibodies, but was associated with lower rheumatoid factor titers (p = 0.001) and serum IgG levels (p = 0.031). CONCLUSION: We confirmed that, similarly to other systemic autoimmune diseases, FCGR3B CN is a genetic susceptibility factor for pSS. As in rheumatoid arthritis, the mechanism does not appear to be related to seropositivity for characteristic autoantibodies.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".