Synovial tissue atlas in juvenile idiopathic arthritis reveals pathogenic niches associated with disease severity
Bibliographic record
Abstract
Precision application of targeted therapies is urgently needed to improve long-term clinical outcomes for children affected by inflammatory arthritis, known as juvenile idiopathic arthritis (JIA). Progress has been hampered by our limited understanding of the cellular basis of inflammation in the target tissue of the disease, the synovial membrane. Here, we analyzed biopsies from the inflamed joints of treatment-naïve children with JIA, early in the course of their disease, using single-cell RNA sequencing, multiplexed immunofluorescence, and spatial transcriptomics to establish a cellular atlas of the JIA synovium. We identified distinct spatial tissue niches, composed of specific stromal and immune cell populations. In addition, we localized genes linked to arthritis severity and disease risk to effector cell populations, including tissue resident SPP1 + macrophages and fibrin-associated myeloid cells. Combined analyses of synovial fluid and peripheral blood from matched individuals revealed differences in cellular composition, signaling pathways, and transcriptional programs across these distinct anatomical compartments. Furthermore, our analysis revealed several pathogenic cell populations that are shared with adult-onset inflammatory arthritis, as well as age-associated differences in tissue vascularity, prominence of innate immunity, and enrichment of TGF-β–responsive stromal subsets that up-regulate expression of disease risk–associated genes. Overall, our findings demonstrate the need for age-specific analyses of synovial tissue pathology to guide targeted treatment strategies in JIA.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".