A cell atlas of human and mouse synovium from early and advanced stages of knee osteoarthritis: BHLHE40 regulates fibroblast activation
Bibliographic record
Abstract
Abstract Osteoarthritis (OA) is a destructive joint disease affecting multiple tissues, including synovium. Previous studies have identified some distinct fibroblast subtypes within synovium; however, the characterization of fibroblast subsets during distinct stages of knee (K)OA disease, and their contributions to the endogenous mechanisms that drive synovial fibrosis during KOA, are not well characterized. Here we profile synovium from early- (KL I) and advanced- (KL III/IV) stages of radiographic KOA. First, bulk-RNA sequencing of early- and advanced-staged KOA synovial tissue revealed transcriptomic differences between the two disease stages. Using single-nuclei RNA sequencing (snRNA-seq) and flow cytometry, we identified distinct fibroblast subsets and uncovered an endotypic shift in fibroblast subsets during KOA pathogenesis, transitioning from DPP4+ in early-stage to ITGB8+ in advanced-stages. SnRNA-seq of synovium from mice with experimental KOA revealed analogous populations of Dpp4+ and Itgb8+ fibroblasts in tissue from early and advanced model stages. Human advanced-stage KOA synovial tissue had stronger expression of matrisome-annotated genes compared to early-stage tissue. BHLHE40, a crucial transcriptional regulator of ECM related genes, was identified as upregulated in ITGB8+ fibroblasts compared to DPP4+ fibroblasts. Using primary human OA fibroblasts in vitro, and conditional knock out mice in vivo, we found that fibroblast-intrinsic loss of BHLHE40 increased fibrosis-related gene expression, enhanced fibroblast activation and induced severe synovial fibrosis in vivo. In contrast, overexpression of BHLHE40 in vitro was able to suppress TGF-β-induced fibroblast activation. Overall, this study provides a comprehensive cellular atlas of KOA synovium and has identified BHLHE40 as a crucial regulator of fibroblast-mediated synovial fibrosis.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".