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Distinct mural cells and fibroblasts drive fibrochondrogenesis in retrodiscal tissue following temporomandibular joint disc displacement
Wenlin Yuan, Yilin Chen, Ruojin Yan, Wei Liu, Chenyu Wang, Ying Wang, Qiaoli Dai, Wen Li, Mengqi Zhu, Xiao Chen, Jiejun Shi
Wenlin Yuan, Yilin Chen, Ruojin Yan, Wei Liu, Chenyu Wang, Ying Wang, Qiaoli Dai, Wen Li, Mengqi Zhu, Xiao Chen, Jiejun Shi
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Research Article Bone biology Cell biology

Distinct mural cells and fibroblasts drive fibrochondrogenesis in retrodiscal tissue following temporomandibular joint disc displacement

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Abstract

Adaptive remodeling of retrodiscal tissue following anterior disc displacement (ADD) of the temporomandibular joint (TMJ) has been recognized for decades, yet the underlying cellular dynamics and molecular mechanisms remain unclear. Using a porcine ADD model, this study investigated the cellular and molecular basis driving retrodiscal tissue adaptation. Histological staining revealed adaptive remodeling of retrodiscal tissue after ADD induction, with dense connective tissue and cartilaginous masses replacing loose connective tissue. Single-cell RNA-Seq captured pronounced fibroblast expansion during tissue remodeling, notably the FB2 subcluster with high developmental potential, and the emergence of a mural cell subcluster, MC4, associated with extracellular matrix (ECM) remodeling. CellChat analysis highlighted MC4-FB2 crosstalk via FGF2 and BMP5 signaling. The combination of pathway-aware multilayered hierarchical network (P-NET) and Seurat with drug database screening identified 5 promising compounds. Among them, zaprinast demonstrated the most robust effects by enhancing the remodeling capability of fibroblasts in vitro and alleviated TMJ deformation in vivo. Collectively, fibroblast activation is pivotal for early retrodiscal tissue adaptation after ADD, which is driven by MC4-derived FGF2/BMP5 signaling. Zaprinast treatment potentiates this remodeling process. These findings provide potentially new insights into the cellular basis of TMJ adaptation and identify potential therapeutic targets for ADD management.

Authors

Wenlin Yuan, Yilin Chen, Ruojin Yan, Wei Liu, Chenyu Wang, Ying Wang, Qiaoli Dai, Wen Li, Mengqi Zhu, Xiao Chen, Jiejun Shi

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