Development of TMJ-OA mouse models

To replicate the pathological conditions of human TMJ-OA caused by MS and inflammation due to malocclusion9,10,11 and ADD,12,13,14 we used a modified MS mouse model15 and developed an original surgical ADD mouse model, respectively (Supplementary Fig. S1).

For the MS model, a metal plate was set on the posterior surface of the maxillary incisors of mice, positioned at a 45-degree angle to the palatal plane, to induce malocclusion using a custom-made mouth opener (Supplementary Fig. S1b–e). For the ADD model, the articular disk of the TMJ was surgically displaced anteriorly and double-tied to the zygomatic arch using 7-0 sutures (Supplementary Fig. S1f, g) to induce ADD and inflammation. There was no significant difference in the body weights of the model mice during the experimental period (at 8, 9, and 12 weeks of age) (Supplementary Fig. S1a, h, i). Micro-computed tomography (micro-CT) images of the mandibular condyle in ADD and MS model mice (Fig. 2a, b) revealed degenerative changes, with ADD model mice developing deformities comparable to those observed in patients with TMJ-OA,12,13,14 and MS model mice exhibiting structural and morphological changes characteristic of Angle’s Class II Division 2 malocclusion.11

Fig. 2

Subchondral bone loss in the MS and ADD models. a Representative 3D images of a mouse head, with the inset box indicating the TMJ showing the region of interests (ROI) in the condyle. The color-scale shows bone mineral density values. Scale bars, 1 mm. b Representative micro-CT images of the condyle at 12 weeks of age in the Ctrl and MS and ADD model groups, taken 3 weeks after induction. The black arrow indicates subchondral bone loss, the yellow arrow indicates osteophyte formation, and the white arrow indicates bone erosion. Temporal: temporal bone. Scale bars, 1 mm. c TRAP staining of the subchondral bone area of the condyle in the Ctrl, MS, and ADD model groups 3 weeks after induction. Lower panels show a higher magnification of the upper panels. Scale bars, 100 μm. d–j Quantitative analysis of the condyles in the Ctrl and MS and ADD model groups 3 weeks after induction. d BV/TV (%): bone volume fraction; e Tb.Th (µm): trabecular thickness; f TMD (mg/cm3): tissue mineral density; g Tb.N (1/mm): trabecular number; h Tb.Sp (µm): trabecular separation; i Oc. S/BS (%): osteoclast surface/bone surface; j Oc. N/BS (cell/mm2): osteoclast number/bone surface. All data are presented as mean ± SEM values. **P < 0.01, ***P < 0.001, ****P < 0.000 1 were compared between groups (n = 5 mice per group). Symbols represents individual mice

Condylar deformation and subchondral bone degradation in the TMJ-OA models

As the condyle of TMJ-OA patients shows subchondral bone loss16,17, we further investigated subchondral bone formation in the MS model, which may affect mechanical regulation of bone remodeling18,19 and the ADD model, which causes condyle growth and degradation (Fig. 2a, b). Tartrate-resistant acid phosphatase (TRAP) staining showed that osteoclast activity was significantly increased in the subchondral bone of the condyle in both MS and ADD models compared to the Ctrl (Fig. 2c). micro-CT analyses revealed that bone volume over total volume (BV/TV) were decreased the subchondral bone of the condyle in both the MS and ADD models compared to the Ctrl (Fig. 2d), trabecular thickness (Tb.Th) and tissue mineral density (TMD) were decreased the subchondral bone of the condyle in the ADD models compared to the Ctrl (Fig. 2e, f). Additionally, there were increases in trabecular number (Tb.N), trabecular separation/spacing (Tb.Sp), osteoclast surface/bone surface (Oc. S/BS), and osteoclast number/bone surface (Oc. N/BS) in the subchondral bone of the condyle in both the MS and ADD models compared to the Ctrl (Fig. 2g–j). These results indicate that MS and ADD-induced TMJ-OA lead to abnormally activated trabecular bone turnover and osteoclast activity.

Pathological changes in condylar and synovial tissues in TMJ-OA model mice

The histological changes in the model mice were investigated after 3 weeks using hematoxylin and eosin (H&E) and safranin O staining (Fig. 3a, b). Compared to the whole TMJ of control (Ctrl) mice, which had normal synovium and a round condyle, the MS model mice showed cartilage fibrillation in the superficial layer and adipogenic and fibrous changes in the posterior synovium of the articular disk. The ADD model mice displayed significant deformity of the condyle, with alterations in the extracellular matrix composition, including loss of proteoglycan in the superficial cartilage layer, and synovial hyperplasia throughout the entire disk (Fig. 3a, b).

Fig. 3

Pathological changes in the condyle and synovium of the TMJ-OA model mice. a Representative H&E staining image of the condyle at 3 weeks after induction surgery (scale bars = 1 mm). Inset boxes show the regions in the lower panels (scale bars = 100 μm). Black arrowheads indicate fibrillations, and blue arrowheads indicate areas of superficial bone erosion at the outer surface of the cortical bone. b Safranin O staining of the condyle at 3 weeks after induction surgery. Inset boxes show the regions in the lower panels. Red arrowheads indicate irregularities in the surface lamina. Black arrowheads indicate fibrillations in the superficial zone of cartilage in the ADD models. Yellow arrowheads indicate pre-hypertrophic chondrocytes in the MS model and hypertrophic chondrocytes in the ADD model. White arrowheads indicate hypocellularity in both the MS and ADD models. Orange arrowheads indicate the clustering of chondrocyte in the ADD models. Scale bars, 100 μm. c Measurement of the modified Mankin score for assessing cartilaginous degradation. d H&E staining of the synovium at 3 weeks after induction surgery. Inset boxes show the regions in the lower panels. Black arrowheads indicate increased thickening of synovial lining cells and enhanced infiltration of inflammatory cells. Red arrowheads indicate vascular invasion into the synovial lining cell layer. Yellow arrowheads indicate fibroblastic cells in the synovial mesenchyme. Scale bars, 100 μm. e Synovitis scores for assessing the severity of synovitis. f Representative H&E staining images of the MS model posterior synovium. The inset box indicates adipocytes, as shown in the enlarged H&E staining image. g mRNA levels of Pparg, Adipoq, Cebpa, Fabp3, and Fabp4 in the articular disk synovium in Ctrl and MS model mice 3 weeks after induction. Symbols represent individual mice; error bars show the mean ± SEM (n = 5 mice per group for c, e). **P < 0.01, ***P < 0.001, ****P < 0.000 1; one-way ANOVA followed by Dunnett’s post hoc test (for c, e) and Student’s unpaired two-tailed t-test (for g)

Safranin O staining revealed that the surface of the condyle in MS model mice was irregular and that the condyle contained hypertrophic cartilage layer chondrocytes. Degradative cartilaginous matrix and unlayered columnar chondrocytes and hypertrophic chondrocytes were observed in the condyles of ADD model mice (Fig. 3b). Furthermore, the Modified Mankin scores indicated that TMJ-OA development in both MS and ADD model condyles was significantly accelerated compared to that in Ctrl condyles (Fig. 3c).

We assessed extracellular matrix degradation and evaluated cartilage thickness in the condyle by dividing it into three regions: Posterior, Middle, and Anterior (Supplementary Fig. S2a, d). Cartilage thickness varied among the three regions, with the Middle and Posterior regions being thicker than the Anterior region. Notably, cartilage degeneration was most pronounced in the ADD model, particularly in the Middle and Posterior regions (Supplementary Fig. S2b, c, e, f). Additionally, hypertrophic chondrocytes were also increased in the Middle and Posterior regions (Supplementary Fig. S2c). In the MS model, significant differences were observed only in the Posterior region for the Safranin O-positive area and hypertrophic zone thickness (Supplementary Fig. S2b, f). Compared to the Ctrl synovium, adipose tissue was observed in the synovium of the TMJ articular disk in MS model mice, and significantly enlarged and hyperplastic fibrotic synovial lining cell layers were observed in the ADD synovium (Fig. 3d). The synovitis scores indicated that the severity of synovial hypertrophy was significantly increased in both the MS and ADD models (Fig. 3e). To confirm adipogenic differentiation in the articular disk synovium in the MS model, we examined the expression of adipogenic markers and observed that adipogenesis-associated genes were upregulated in the MS model compared to that in the Ctrl synovium (Fig. 3f, g).

These data indicate that mechanical and ADD-induced inflammatory stimuli to the TMJ lead to synovial hyperplasia and condylar cartilage degradation, contributing to the onset and progression of TMJ-OA. Furthermore, the histological changes observed throughout the TMJ suggest that the posterior synovium of the articular disk may play a pivotal role in disrupting TMJ homeostasis and initiating pathogenic degeneration during the early stages of disease.

Distinct mRNA expression profiles in Ctrl and MS and ADD model condyles

Next, we used RNA-seq analysis to comprehensively analyze the gene alterations in the articular disks, including the synovium, and mandibular condyles in our three TMJ models (Ctrl, MS, and ADD), three weeks after model establishment (Fig. 4a). Heatmaps based on genes, Gene Ontology terms, and pathways revealed that the gene expression patterns in the articular disk synovium and condyles (each group, n = 3) could clearly be divided into two tissue-specific groups, termed Condyle and Synovium (Supplementary Fig. S3). A Venn diagram of the number of differentially expressed genes (DEGs) between the Ctrl vs. MS and Ctrl vs. ADD group Condyle groups is shown in Fig. 4b.

Fig. 4

Comprehensive mRNA analysis of Ctrl, MS, and ADD group mandibular condyles. a Schematic representative image of the condyle and the synovium of the articular disk in the TMJ for bulk RNA-seq samples. b A Venn diagram showing the comparisons of DEGs among the Ctrl, MS, and ADD group condyles. c Heatmap of DEGs for the five common genes among the Ctrl, MS, and ADD group condyles. d Expression levels (TPM) of DEGs for the significantly downregulated common genes in the condyles of MS and ADD mice compared to the Ctrl group. Symbols represent individual mice; error bars show the mean ± SEM (n = 3 mice per group). **P < 0.01 and ***P < 0.001, one-way ANOVA followed by Dunnett’s post hoc test. e Volcano plots of DEGs between the Ctrl and MS group condyles. f Volcano plots of DEGs between the Ctrl and ADD group condyles. g IPA of the RNA-seq data from the Ctrl and ADD group condyles. The top 30 upregulated pathways are shown. P < 0.05 was considered as the significance threshold

Notably, comparing the Ctrl vs. MS and Ctrl vs. ADD group condyles showed that several genes related to cartilage homeostasis and OA were downregulated in the models (Fig. 4c, d). Normalized gene expression levels (in transcripts per million [TPM]) from the RNA-seq data showed that four of these genes—Cytl1,20,21,22,23Ankrd37,24Plec,25,26 and Mylk27—were significantly downregulated in both the MS and ADD condyles (Fig. 4d), as indicated by the volcano plots of the DEGs (Fig. 4e, f). Furthermore, the expression of Fetub,28 which mediates the NF-κB signaling pathway, and Ccn529, Wnt1 inducible signaling pathway protein 2 were significantly elevated in the ADD condyle group (Fig. 4f); in contrast, Pappa2,30 a regulator of insulin-like growth factor, was significantly downregulated (Supplementary Fig. S4a). Ingenuity pathway analysis (IPA) with terms and pathways based on the DEGs identified through each group comparison indicated upregulation of “Degradation of the extracellular matrix”, “Role of osteoclasts in rheumatoid arthritis signaling pathway”, and “Osteoarthritis pathway” in the ADD group as compared to the Ctrl group (Fig. 4g). In addition, the expression of degradation markers Ccl5, Ccn5, Mmp13, and Mmp9 was validated in the condyle tissues of the Ctrl, MS, and ADD groups using real-time RT-PCR (Supplementary Fig. S5).

Thus, RNA-seq analyses of the condyles suggest that the onset of TMJ-OA involves changes in gene expression profiles, characterized by the downregulation of cartilage homeostasis-related genes and the upregulation of factors associated with OA progression.

Distinct mRNA expression profiles in the articular disk synovium in the Ctrl and MS and ADD model groups

Comparisons of Ctrl vs. MS and Ctrl vs. ADD group articular disk synovium RNA-seq data revealed commonly upregulated genes related to pathogenesis-related cytokines and catabolic markers (Fig. 5a), as indicated by volcano plots of DEGs (Fig. 5b, c). IPA indicated upregulation of the “Pathogen induced cytokine storm signaling pathway” in the MS synovium in (Fig. 5d) and “Pulmonary fibrosis idiopathic signaling pathway” and “Role of osteoclasts in rheumatoid arthritis signaling pathway” in the ADD synovium (Fig. 5e) compared to the Ctrl group. To verify pathway alterations in the ADD synovium, we also conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, another method commonly used for pathway analyses and found that “Rheumatoid arthritism”, “HIF-1 signaling pathway”, and “NF-kappa B signaling pathway” were more enriched in the ADD synovium (Fig. 6a).

Fig. 5

Comprehensive mRNA analysis of the Ctrl, MS, and ADD group synovium. a A Venn diagram of the comparisons of DEGs among the Ctrl, MS, and ADD group synovium. b Volcano plots of DEGs between the Ctrl and MS group synovium. c Volcano plots of DEGs between the Ctrl and ADD group synovium. d IPA of RNA-seq data from the Ctrl and MS group synovium, showing the top 30 upregulated pathways. P < 0.05 was considered as the significance threshold. e IPA of the RNA-seq data from the Ctrl and ADD group synovium, showing the top 20 upregulated and downregulated pathways. P < 0.05 was considered as the significance threshold

Fig. 6

KEGG pathway enrichment and expression profiles of Mmps, volcano plot–derived DEGs, and fibroblastic marker DEGs in the Ctrl, MS, and ADD group synovium. a Histogram of KEGG pathway enrichment analysis from the Ctrl and ADD group synovium. b Heatmap of Mmps DEGs (left panel) and expression levels (TPM) of the DEGs (right panels) in the Ctrl, MS, and ADD group synovium. c Heatmap of DEGs (left panel) from the volcano plot in (Fig. 5c) and the expression levels (TPM) of the DEGs (right panels) in the Ctrl, MS, and ADD group synovium. d Heatmap of fibroblastic marker DEGs (left panel) and the expression levels (TPM) of the DEGs (right panels) in the Ctrl, MS, and ADD group synovium. Symbols represent individual mice; error bars show the mean ± SEM (n = 3 mice per group) *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.000 1; one-way ANOVA followed by Dunnett’s post hoc test

Since volcano plots of DEGs showed that Mmp3, 9, and 13 were upregulated in the ADD group and Mmp13 was commonly upregulated in the MS and ADD groups compared to the Ctrl group (Fig. 5b, c), we focused on matrix metalloproteinase expression in the synovium. TPM values from RNA-seq data for six genes—Mmp2, Mmp3, Mmp9, Mmp13, Mmp16, and Mmp19—were significantly increased in the ADD model synovium (Fig. 6b). Moreover, the expression of genes related to macrophages, inflammation, and bone remodeling, such as Ctsk,31,32Ccl21a,33Ccn5,29,34,35Cthrc1,36,37Cdh11,38 and Mdk,39 were significantly elevated in the synovium of ADD model mice (Fig. 6c). To further investigate both the similarities and differences in the spatial context of inflammatory and catabolic gene expression between the condylar cartilage and synovial tissue, we performed wide-scale spatial gene expression analysis using the Visium HD platform (10× Genomics), which enables transcriptome-wide profiling of approximately 20 000 genes without limitation to predefined target genes. The whole-transcriptome spatial map of our three TMJ models (Ctrl, MS, and ADD) revealed that M1 macrophage markers were expressed predominantly in the posterior synovial tissue of the articular disk, particularly in the superior lamina, in both the MS and ADD models. In addition, compared to the control, M1 macrophages extended deeper into the cartilage layers. This pattern was accompanied by a similar spatial distribution of Mmps markers, which were also observed spreading into the posterior-superior region of the articular disk and into the articular cartilage layers (Supplementary Fig. S6).

As synovitis promotes the production of pain neurotransmitters as well as synovial angiogenesis, which in turn accelerates inflammation and directly leads to synovial fibrosis at the later stage of OA40 we then focused on fibroblastic markers in the synovium. TPM values from RNA-seq data for six genes—Col1a1, Col3a1, Fn1, Lum, Dpt, and Fap—were significantly increased in the synovium of ADD model mice (Fig. 6d). Furthermore, the expression of the above markers (Fig. 6b–d) was validated in the synovial tissues of the Ctrl, MS, and ADD groups using real-time RT-PCR (Supplementary Fig. S7), supporting the gene expression trends observed in the RNA-seq analysis. In addition, TPM values and heatmaps from RNA-seq data for other catabolism-related gene families are shown in Supplementary Fig. S8.

Thus, our RNA-seq analyses suggested that cartilage homeostasis in MS and ADD model condyles was disrupted due to imbalances in collagen catabolism in the synovium in the MS model and severe synovial fibrosis in the ADD model. partly due to fibroblast proliferation and the disturbance of collagen synthesis and degradation by matrix metalloproteinases, ultimately leading to excessive collagen deposition in the extracellular matrix.

scRNA-seq identified key cell populations and crosstalk mechanisms in the mechanical and inflammatory stress TMJ models

To investigate the MS and ADD-induced inflammatory changes in the respective models of TMJ, we performed scRNA-seq on cells obtained from the articular disk, including the synovium, 3 weeks after model establishment (Fig. 7a). Following unsupervised graph clustering of the combined datasets of the Ctrl, MS, and ADD groups, uniform manifold approximation and projection (UMAP) of the scRNA-seq data analyzed using the scanpy package41 identified 17 cell types and 24 distinct cell clusters (labeled as clusters 0–23) (Fig. 7b, c) (Supplementary Fig. S9), taking into account the percentages of mitochondrial reads, ribosomal reads, and cell cycle phase (Supplementary Fig. S9a–c).

Fig. 7

scRNA-seq analysis of the Ctrl, MS, and ADD group articular disks. a Schematic overview of the scRNA-seq workflow. b UMAP plot with cell type annotation using CellAssign. c. UMAP plot showing the 0–23 clusters from a total of 9302 cells from articular disks from the Ctrl, MS, and ADD groups. d Streamline presentation based on the spliced/unspliced ratio of RNA using scVelo. e Feature plot on UMAP, showing the number of cells in the articular disks from the Ctrl, MS, and ADD groups. f Cumulative bar plot categorized by cell types. g Cumulative bar plot of the 0–23 clusters by CellAssign (upper panel) and by Ctrl, MS, and ADD groups (lower panel). h Dot plot of synovium-, fibroblast-, catabolism-, and inflammation-related gene expression across the 0–23 clusters

The differentiation pathway was examined based on the RNA-spliced/unspliced ratio using scVelo,42 which revealed that the clusters in the articular disk synovium predominantly comprised endothelial, fibroblast, and macrophage clusters (Fig. 7d). The 24 distinct cell clusters exhibited relatively conserved cell proportions, with all principal cell types distributed across the Ctrl, MS, and ADD-induced inflammatory conditions (Fig. 7e). A total of 9302 cells were captured, and the number of cells in the MS and ADD models was higher than that in the Ctrl condition; these differences might be due to the presence of hypertrophic tissues in the articular disks in the MS and ADD model mice (Fig. 7e).

Since adipogenesis-associated genes were upregulated in the synovium of the MS model compared to that in the Ctrl synovium (Fig. 3f, g), we also performed a dimensional reduction analysis (via UMAP) that included the adipocyte cell type (Supplementary Fig. S10). However, adipocytes represented only a small number of plots, labeled near the keratinocyte clusters (Supplementary Fig. S10a). We also verified the expression of the adipogenic marker Ppargc1a using in situ RNA expression analysis (Supplementary Fig. S11), and found that it was upregulated in the MS model synovium, which predominantly contained endothelial, pericyte, and osteoblastic cell populations, while the ADD model synovium predominantly contained fibroblast, keratinocyte, and macrophage cell populations (Fig. 7f). The 24 cell clusters were annotated and linked to the 17 cell types for comparison between the Ctrl, MS, and ADD model populations (Fig. 7g). Among the 24 distinct clusters, 11 clusters (1, 3, 4, 7, 8, 11, 15, 16, 19, 20 and 22) expressed fibroblastic markers such as Col1a1, Fos, Prg4, and Thy1, while 5 clusters (0, 2, 6, 14, and 18) expressed endothelial markers such as Clic5 and Ccl21a (Fig. 7h). Cluster 5 was primarily annotated as a macrophage cluster, while cluster 17 was annotated as a keratinocyte cluster (Fig. 7g). Indeed, matrix plots of gene expression revealed that cluster 2 was enriched for endothelial cell types, while cluster 17 was enriched for keratinocytes (Supplementary Fig. S9d). In addition, fibroblast, endothelial, and macrophage markers at the single-cell level were validated by gene expression in synovial tissues of the Ctrl, MS, and ADD groups using real-time RT-PCR, with Lum, Prox1, and Cd68 serving as respective markers (Supplementary Fig. S12).

Finally, we investigated cell-cell interactions among clusters 0–23 based on ligand-receptor expression levels using the CellChat platform.43 Regarding mechanosignal transduction, CellChat analysis of the scRNA-seq data showed that fibroblast clusters (1, 3, 4, 7, 8, 11, 15, 16, 19, 20, and 22) were predicted to interact with the endothelial clusters (0 and 2), macrophage cluster (5), and keratinocyte cluster (17), which was dominant in the ADD model (Supplementary Fig. S13a). Notably, Notch signaling in the endothelial clusters 0, 2, 6, 14, and 18 was conveyed from various clusters within the fibroblastic group (Supplementary Fig. S13a). Additionally, the macrophage-related clusters 5 and 12 were found to receive signals from 16 clusters, including endothelial, keratinocyte, and fibroblast clusters, with Cd36, Cd44, and Cd74 identified as a few of the predicted receptor molecules (Supplementary Fig. S14). In addition, the predictions derived from CellChat analysis of the scRNA-seq data were consistent with the spatial transcriptomic findings from the whole-transcriptome spatial maps of our three TMJ models (Ctrl, MS, and ADD) generated using the Visium HD platform. Notch signaling components (Supplementary Fig. S15a) and endothelial cell markers (Supplementary Fig. S15b) were predominantly expressed in the posterior synovial tissue of the articular disk—particularly in the superior lamina—in both the MS and ADD models, similar to the expression pattern observed for macrophage markers (Supplementary Fig. S6a). Interestingly, keratinocyte markers also exhibited a similar distribution, with marked expression in the posterior synovial tissue in the MS model, and deeper extension into the deep layers of the mandibular condylar cartilage in the ADD model, resembling the spatial patterns seen with M1 macrophages, MMPs, Notch signaling, and endothelial markers (Supplementary Fig. S15).

Collectively, these scRNA-seq data suggest that the identified endothelial, keratinocyte, and macrophage clusters in articular disk synovium might represent potential targets for modulating fibroblast crosstalk in the TMJ disease control.

Spatial transcriptomics revealed gene expression patterns corresponding to pathological changes in TMJ models

To further spatially validate the transcriptomic events, we first performed spatial transcriptome sequencing analysis using the Xenium platform (10x Genomics) (Fig. 8a). Specifically, we examined the spatial expression patterns in the posterior synovium, which exhibited severe pathological changes, across three representative images from the Ctrl, MS, and ADD groups (one image each) (Fig. 8b). To explore the transcriptome features in the synovium, we prepared a custom in situ gene expression profiling panel of 100 genes (Supplementary Fig. S16) (Xenium Custom Gene Expression panel ID: KEPGAC) based on the scRNA-seq data for the articular disk, including the posterior synovium, and performed in situ RNA expression analysis at a single-cell level using a pre-designed panel (ID: mMulti_v1) and the aforementioned custom panel. We obtained expression levels of 28 816, 37 503, and 31 187 cells from the Ctrl, MS, ADD group tissues, respectively. The expression of the signature genes was spatially localized in the regions corresponding to pathological features (Fig. 8c). Moreover, these histological and transcript features were consistent with the gene expression patterns and were further validated by single-cell, high-resolution spatial analysis.

Fig. 8

Spatial transcriptomics analysis of the Ctrl, MS, and ADD group posterior synovium. a Schematic overview of the spatial transcriptomics analysis (Xenium) workflow. b H&E staining of the whole TMJ (upper panel), with the inset box showing the H&E staining and the region of interest (ROI) in the Xenium spatial expression pattern images. c In situ gene expression profiling using Xenium for representative genes in the ROI from Ctrl, MS, and ADD group images. d Number of transcript counts for representative genes in the ROI from the Ctrl, MS, and ADD group images. Scale bars, 100 μm

To systematically validate the transcriptomic changes in the posterior synovium, we counted the number of detected transcripts in the region-of-interests (ROIs) of the posterior synovium. The expression levels of the signature gene transcripts in an ROI corresponded to the population of cell types annotated by the scRNA-seq analysis; for example, in the posterior synovium ROI in the ADD model, the number of transcripts for osteogenic markers, such as Spp1, Fos, and Grem1, and catabolic markers, such as Mmp3, Mmp13 and Cxcl14, were notably increased (Fig. 8d) as shown in the cell-type populations in Fig. 7f. These high resolution subcellular spatial transcriptomics data confirmed that the pathological features in the posterior synovium corresponded to the catabolic gene expression patterns.

Integration of scRNA-seq and subcellular spatial transcriptomics analysis results revealed dynamic cellular changes in TMJ pathology

As the subcellular spatial transcriptome analysis provided novel information regarding the in situ gene expression profiles in ROIs during pathological changes within the posterior synovium, spatial subcellular transcriptomics using the Xenium platform allowed single-cell resolution, even though the number of hybridization probes in the pre-designed and custom panels was limited. We then integrated the scRNA-seq data, consisting of 17 cell types and 24 cell clusters (Fig. 7b, c), with th