An exploratory single-cell analysis of peripheral blood mononuclear cells from vedolizumab-treated Crohn’s disease patients identifies response-associated differences among the plasmacytoid dendritic cells and classical monocytes
Bibliographic record
Abstract
Background: Vedolizumab (VDZ) is a monoclonal antibody approved for the treatment of Crohn's disease (CD). Despite its efficacy, non-response to VDZ is common in clinical practice with no clear understanding of how it manifests. Here, we performed an exploratory study characterizing the cellular repertoire of responders and non-responders to VDZ during treatment. Methods: Peripheral blood mononuclear cells (PBMCs) were isolated from CD patients on VDZ treatment that were either steroid-free responder (N = 4) or non-responder (N = 4). Response was defined as ≥3 drop in Simple Endoscopic Score for Crohn's Disease (SES-CD) in combination with a ≥50% reduction in C-reactive protein (CRP) and fecal calprotectin and/or a ≥3 point drop in Harvey-Bradshaw Index (HBI). Single-cell repertoires were characterized using single-cell RNA-sequencing (scRNAseq) and mass cytometry by time of flight (CyTOF). Results: Non-responders to VDZ presented more T cells, but fewer myeloid cells, with plasmacytoid dendritic cells (pDCs) being the most notably lower among non-responders. At a transcriptional level we observed that T-cell expression of genes involved in for Toll-like receptor (TLR), NOD-like receptor (NLR), and mitogen-activated protein kinases (MAPK) signaling pathways were decreased among non-responders. Similarly, non-responder-derived classical monocytes presented lower expression of genes involved in cytokine-cytokine receptor signaling. Conclusions: Non-response to VDZ during treatment is associated with differences in abundance and expression among T and myeloid cells.
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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 | 0.001 |
| 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".