ZAP-70+ B Cell Subset Influences Response to B Cell Depletion Therapy and Early Repopulation in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To define the role of ZAP-70+ B cells (CD19+/ZAP-70+) as a biomarker of response to B cell depletion therapy (BCDT), their relationship with clinical outcome, and their behavior during repopulation of peripheral blood in patients with rheumatoid arthritis (RA). METHODS: Thirty-one patients with RA underwent BCDT and were followed for 12 months. Disease activity was assessed with the European League Against Rheumatism (EULAR) criteria. Cytofluorimetric analysis of peripheral blood B cell subsets at baseline and at 6- and 12-month intervals after BCDT was performed using surface markers (CD45, CD3, CD56, CD19, IgD, CD38, CD27) and intracellular ZAP-70. RESULTS: A moderate/good EULAR response was achieved in 66.6% of the RA cohort. The baseline percentage of CD19+/ZAP-70+ cells was lower in good responder patients (1.8% ± 1.7%) compared to poor responders (5.6% ± 4.9%; p = 0.02). A decrease of plasmablasts (IgD-CD27+CD38+) and pre-switch memory (IgD+CD27+) B cells occurred after BCDT. Recovery of B cells in peripheral blood after the first course of BCDT was characterized by the reappearance of B cell subtypes that showed a naive, activated phenotype, coupled with a decrease in memory cells. B cells carrying intracytoplasmic ZAP-70 increased significantly from the baseline value of 4.4% ± 4.5% to 12.4% ± 9.2% (p = 0.001) at the 6-month and to 9.4% ± 6.4% (p = 0.002) at the 12-month followup. CONCLUSION: Baseline percentage of CD19+/ZAP-70+ cells is associated with the clinical outcome after BCDT in patients with RA. Depletion of plasmablasts and pre-switch memory B cells and increase of CD19+/ZAP-70+ cells are features of the recovery of the B cell pool after BCDT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".