Soluble LILRA3, a Potential Natural Antiinflammatory Protein, Is Increased in Patients with Rheumatoid Arthritis and Is Tightly Regulated by Interleukin 10, Tumor Necrosis Factor-α, and Interferon-γ
Bibliographic record
Abstract
OBJECTIVE: Leukocyte immunoglobulin-like receptor A3 (LILRA3) belongs to a family of cell-surface receptors with inhibitory or activating functions. LILRA3 lacks transmembrane and cytoplasmic domains, suggesting that it may be secreted. LILRA3 has high homology to activating LILRA1 and A2, hence may act as a soluble agonist/antagonist to these receptors. Individuals lacking the LILRA3 gene have higher incidence of multiple sclerosis and Sjögren's syndrome, suggesting LILRA3 may be antiinflammatory. LILRA3 mRNA was detected in monocytes and mast cells but no protein expression has ever been described. Our aim was to examine LILRA3 protein expression in serum and synovial fluid of patients with rheumatoid arthritis (RA) and determine its in vitro regulation. METHODS: We developed a new ELISA to examine levels of LILRA3 in serum, synovial fluid, and/or culture supernatants from controls and patients with RA, degenerative arthritis, or gout. We used qRT-PCR and flow cytometry to determine the expression and cytokine-mediated regulation of LILRA3. RESULTS: LILRA3 protein is constitutively present in normal serum, with significantly higher concentrations in patients with RA. Serum LILRA3 concentrations from RA patients correlated with disease activity and levels in synovial fluid. Treatment of monocytes with interleukin 10 or interferon-gamma significantly upregulated while tumor necrosis factor-alpha significantly downregulated LILRA3 mRNA and protein expression. CONCLUSION: We show for the first time that LILRA3 is significantly increased in serum of patients with RA and is tightly regulated by key cytokines involved in pathogenesis of RA. These results suggest that LILRA3 may play a role in chronic inflammatory conditions such as RA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".