Dimethyl Fumarate Treatment Mediates an Anti-Inflammatory Shift in B Cell Subsets of Patients with Multiple Sclerosis
Bibliographic record
Abstract
The therapeutic mode of action of dimethyl fumarate (DMF), approved for treating patients with relapsing-remitting multiple sclerosis, is not fully understood. Recently, we and others demonstrated that Ab-independent functions of distinct B cell subsets are important in mediating multiple sclerosis (MS) relapsing disease activity. Our objective was to test whether and how DMF influences both the phenotype and functional responses of disease-implicated B cell subsets in patients with MS. High-quality PBMC were obtained from relapsing-remitting MS patients prior to and serially after initiation of DMF treatment. Multiparametric flow cytometry was used to monitor the phenotype and functional response-profiles of distinct B cell subsets. Total B cell counts decreased following DMF treatment, largely reflecting losses of circulating mature/differentiated (but not of immature transitional) B cells. Within the mature B cell pool, DMF had a greater impact on memory than naive B cells. In keeping with these in vivo effects, DMF treatment in vitro remarkably diminished mature (but not transitional B cell) survival, mediated by inducing apoptotic cell death. Although DMF treatment (both in vivo and in vitro) minimally impacted B cell IL-10 expression, it strongly reduced B cell expression of GM-CSF, IL-6, and TNF-α, resulting in a significant anti-inflammatory shift of B cell response profiles. The DMF-mediated decrease in B cell proinflammatory cytokine responses was further associated with reduced phosphorylation of STAT5/6 and NF-κB in surviving B cells. Together, these data implicate novel mechanisms by which DMF may modulate MS disease activity through shifting the balance between pro- and anti-inflammatory B cell responses.
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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 | 0.001 | 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 | 0.000 |
| 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 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".