Defining subcellular synovial responses in TMJ osteoarthritis onset via mechanical stress and articular disk derangement models
Kazuhiro Shibusaka , Soichiro Negishi , Asuka Terashima , Miki Maemura , Hiroshi Yoshida , Masahiro Hosonuma , Nobuhiro Sakai , Young Kwan Kim , Yutaka Suzuki , Hiroyuki Okada , Fumiko Yano
International Journal of Oral Science ›› 2026, Vol. 18 ›› Issue (1) : 28
Temporomandibular joint osteoarthritis (TMJ-OA), the most common degenerative disease of the TMJ, is influenced by various adaptive, inflammatory, and mechanical stressors. In this study, we describe molecular alterations of the synovium of the articular disk in response to mechanical and inflammatory stimuli. Using an integrated transcriptomic approach combining subcellular spatial transcriptomics and single-cell RNA sequencing in murine models of mechanical stress and articular disk derangement, we characterized synovial changes associated with adipogenesis, fibrosis, and macrophage activation. In addition, cell type–and cluster–specific catabolic changes were observed under these stress conditions, suggesting potential contributions to TMJ-OA onset. These results provide a methodology-oriented resource for investigating the molecular pathology of TMJ disorders and may help guide future studies toward the development of targeted therapeutic strategies.
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
MacDonald, I. J., Huang, C. C., Liu, S. C., Lin, Y. Y. & Tang, C. H. Targeting CCN proteins in rheumatoid arthritis and osteoarthritis. Int. J. Mol. Sci. 22, 4340 (2021). |
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
|
| [40] |
|
| [41] |
|
| [42] |
|
| [43] |
|
| [44] |
|
| [45] |
|
| [46] |
|
| [47] |
|
| [48] |
|
| [49] |
|
| [50] |
|
| [51] |
|
| [52] |
|
| [53] |
|
| [54] |
|
| [55] |
|
| [56] |
|
| [57] |
|
| [58] |
|
| [59] |
|
| [60] |
|
| [61] |
|
| [62] |
|
| [63] |
|
| [64] |
|
| [65] |
|
| [66] |
|
| [67] |
|
| [68] |
|
| [69] |
|
| [70] |
|
| [71] |
|
| [72] |
|
| [73] |
|
| [74] |
|
| [75] |
|
| [76] |
|
| [77] |
|
| [78] |
|
| [79] |
|
| [80] |
Kaminow, B., Yunusov, D. & Dobin, A. STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data. bioRxiv https://doi.org/10.1101/2021.05.05.442755 (2021). |
| [81] |
|
| [82] |
Okada, H. et al. Advancing single cell technology: iSCseq drives living subcellular transcriptomic profiling in osteoimmune diversity. bioRxiv https://doi.org/10.1101/2022.09.05.506360 (2024). |
The Author(s)
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