Proinflammatory GM-CSF–producing B cells in multiple sclerosis and B cell depletion therapy
Bibliographic record
Abstract
B cells are not limited to producing protective antibodies; they also perform additional functions relevant to both health and disease. However, the relative contribution of functionally distinct B cell subsets in human disease, the signals that regulate the balance between such subsets, and which of these subsets underlie the benefits of B cell depletion therapy (BCDT) are only partially elucidated. We describe a proinflammatory, granulocyte macrophage-colony stimulating factor (GM-CSF)-expressing human memory B cell subset that is increased in frequency and more readily induced in multiple sclerosis (MS) patients compared to healthy controls. In vitro, GM-CSF-expressing B cells efficiently activated myeloid cells in a GM-CSF-dependent manner, and in vivo, BCDT resulted in a GM-CSF-dependent decrease in proinflammatory myeloid responses of MS patients. A signal transducer and activator of transcription 5 (STAT5)- and STAT6-dependent mechanism was required for B cell GM-CSF production and reciprocally regulated the generation of regulatory IL-10-expressing B cells. STAT5/6 signaling was enhanced in B cells of untreated MS patients compared with healthy controls, and B cells reemerging in patients after BCDT normalized their STAT5/6 signaling as well as their GM-CSF/IL-10 cytokine secretion ratios. The diminished proinflammatory myeloid cell responses observed after BCDT persisted even as new B cells reconstituted. These data implicate a proinflammatory B cell/myeloid cell axis in disease and underscore the rationale for selective targeting of distinct B cell populations in MS and other human autoimmune diseases.
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.
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 | 0.000 |
| 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 | 0.001 |
| 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 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".