CD3+ immune cell endotypes are associated with PsA disease phenotype and response to advanced therapy: an integrated mass cytometry and proteomics cohort study
Bibliographic record
Abstract
OBJECTIVES: This study aims to identify circulating cellular immune cell endotypes in psoriatic arthritis (PsA), assess their association with treatment response, and explore key biological pathways linked to these immune profiles. METHODS: Using mass cytometry, we analysed CD3+ immune cell populations in patients with PsA initiating targeted therapies. Hierarchical clustering identified immune cell endotypes, and their associations with clinical features and treatment response were assessed using generalised estimating equation models. Proteomic profiling via an aptamer-based assay compared differentially expressed proteins across clusters, followed by pathway analysis. Imaging mass cytometry analysis was performed to characterise T cell subsets in synovial tissue samples. RESULTS: We analysed blood samples from 40 treatment periods involving 34 patients and identified 3 immune clusters (C); C1: 'memory CD4+ T cell endotype' - associated with higher sonographic musculoskeletal inflammation and peri-articular bone formation, and poorer response to therapy; C2: 'Nonclassical T cell endotype'-exhibited lowest levels of musculoskeletal inflammation; and C3: 'Terminal effector/Th1 cell endotype'-linked to higher sonographic peri-articular inflammation. The immune endotypes remained relatively stable 3 months posttreatment. The 'memory CD4+ T cell endotype' was characterised by deregulation of immune-related biological pathways, including several intracellular signalling pathways, the most notable being WNT signalling. CD4+ cells with memory and effector phenotypes were abundant in the synovial tissue sample from patients with PsA. CONCLUSIONS: Heterogeneity in circulating immune cell profiles is associated with PsA clinical features and therapeutic response. The results underscore the potential of immune cell phenotyping to improve prognosis in PsA, which could inform personalised treatment strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".