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. 2025 Nov 26;32(6):1652–1664. doi: 10.1111/odi.70154

Th17/IL‐17A Drives Alveolar Bone Loss via the JAK/STAT3‐RANKL Axis in the Periodontal Ligament

Die Lv 1, Jiuge Zhang 1, Yixin Zhang 1, Ying Zhou 1, Weideng Wei 1, Lisheng Zhang 1, Xiaoqiang Xia 1, Jiao Chen 1, Qianming Chen 1,2, Ping Zhang 1, Yuan Yue 1,3,✉, Xiaodong Feng 1,✉
PMCID: PMC13457682  PMID: 41299813

ABSTRACT

Objectives

Th17 cells play a critical role in alveolar bone loss, which is closely associated with osteoclast maturation during periodontitis. Previous studies have established that periodontal ligament cells (PDLCs) are a significant source of receptor activator of nuclear factor‐κB ligand (RANKL), a pivotal osteoclast‐inducing cytokine. However, the mechanisms by which IL‐17A promotes osteoclast activation via the PDL‐mediated pathways are poorly understood. This study investigates how IL‐17A promotes RANKL production in PDLCs and evaluates the therapeutic potential of targeting the JAK/STAT3 pathway in periodontitis.

Methods

A ligature‐induced periodontitis (LIP) model was established and alveolar bone loss was assessed using micro‐CT and TRAP staining. The molecular mechanisms were investigated using bioinformatic analysis, western blotting, and immunohistochemistry. The efficacy of anti‐IL‐17A (αIL‐17A) and tofacitinib in inhibiting alveolar bone loss was evaluated through intraperitoneal injection.

Results

RANKL was predominantly expressed in the PDL during periodontitis. IL‐17A enhanced osteoclast activity in RAW264.7 cells co‐cultured with PDLCs. IL‐17A upregulated RANKL expression in PDLCs through STAT3 activation. Tofacitinib significantly inhibited alveolar bone loss by suppressing Th17 cell differentiation and osteoclast activation.

Conclusions

IL‐17A promoted RANKL expression through JAK/STAT3 activation in PDLCs. Tofacitinib, a clinically available JAK inhibitor, significantly attenuated alveolar bone loss in periodontitis.

Keywords: alveolar bone loss, IL‐17A, periodontal ligament, periodontitis, RANKL, STAT3

1. Introduction

Periodontitis is a chronic inflammatory disease caused by oral microbial dysbiosis, which leads to periodontal immune damage and alveolar bone loss (Hajishengallis and Chavakis 2021; Sczepanik et al. 2020). It is one of the most prevalent oral diseases worldwide affecting more than 50% of adults to varying degrees (Nazir et al. 2020). A growing number of studies have shown that chronic periodontitis is strongly associated with systemic diseases (Beck et al. 2019; Graves et al. 2020; Priyamvara et al. 2020). While conventional therapies such as scaling and root planing manage most cases (Jonesn et al. 2023), refractory periodontitis—particularly in patients with systemic comorbidities—often progresses rapidly due to unresolved inflammation and excessive osteoclast activation (Jonesn et al. 2023; Shaddox and Walker 2010; Teughels et al. 2014). The pathogenesis of refractory periodontitis remains poorly understood and effective targeted therapeutic strategies are currently lacking, necessitating further investigation to elucidate its underlying mechanisms and identify novel pharmacological targets.

Single‐cell RNA sequencing (scRNA‐seq) studies have characterized immune cells involved in the pathogenesis of periodontitis, mostly in gingival tissues, thereby enhancing our understanding of the underlying mechanisms (Williams et al. 2021). The periodontal tissues consist of the gingiva, periodontal ligament, alveolar bone, and cementum. The periodontal ligament serves as a vital supportive component of the periodontal tissue, with periodontal ligament cells (PDLCs), key stromal cells at the bone‐resorptive interface; nevertheless, these investigations typically concentrate exclusively on gingival specimens, thereby restricting the scope of the conclusions that can be inferred (Buragaite‐Staponkiene et al. 2023; Shen et al. 2024; Williams et al. 2021). In periodontitis, the inflammatory response of the periodontal ligament produces receptor activator of nuclear factor‐κB (RANKL) (Tsukasaki et al. 2018), RANKL binds to the RANK receptor on osteoclast precursor cells, triggering NF‐κB and MAPK signaling pathways that drive their differentiation into mature osteoclasts (Andreev et al. 2020; Bae et al. 2023). However, the factors mediating RANKL production by PDLCs and the mechanisms underlying RANKL generation in these cells remain to be elucidated.

Recent research has underscored the crucial role of T helper 17 (Th17) cells and interleukin‐17A (IL‐17A) in the pathogenesis of periodontitis, promoting neutrophil recruitment and alveolar bone loss (Bunte and Beikler 2019; Gaffen and Moutsopoulos 2020; Moutsopoulos and Konkel 2018). Emerging evidence from other inflammatory studies demonstrates that pathogenic Th17 cells mediate tissue destruction by stimulating stromal cells through IL‐17A signaling to enhance osteoclastogenesis, thereby exacerbating inflammatory bone loss (Wang et al. 2017). This osteoclastogenic process is tightly regulated by TNF superfamily members, particularly the RANK and its ligand RANKL. PDLCs are a vital cellular source of RANKL in periodontitis. However, the specific mechanisms by which PDLCs mediate IL‐17A‐induced alveolar bone resorption in periodontitis remain unclear.

This study investigated the mechanism of action of IL‐17A in osteoclast activation during periodontitis. We aimed to provide novel insights into the pathogenesis of periodontitis and identify potential therapeutic targets. By combining in vitro and in vivo models, IL‐17A was found to activate the JAK/STAT3 signaling pathway in PDLCs, thereby upregulating the expression of RANKL, which drives osteoclastogenesis and subsequent alveolar bone loss. Furthermore, tofacitinib, a clinically approved JAK inhibitor, effectively suppresses IL‐17A‐induced RANKL production and mitigates pathological bone loss.

2. Materials and Methods

2.1. Animals

Female C57BL/6 mice, aged 8 weeks, were procured from Jiangsu Jicui Yaokang Biological Technology Co. Ltd., China. These mice were housed in a specific pathogen‐free environment with a controlled temperature range of 22°C–26°C and relative humidity of 40%–60%. Periodontitis was induced by placing a 5–0 silk ligature between the first and second maxillary molars (Marchesan et al. 2018). The experiments were divided into four groups: Group 1, a time course experiment with ligatures placed for 0 (Ctrl), 3, 6, 9, and 14 days (n = 5); Group 2, an IL‐17A intervention experiment consisting of control (Ctrl), periodontitis + isotype control (Perio), and periodontitis + anti‐IL‐17A (Perio + αIL‐17A) groups, with a 14‐day experimental period and αIL‐17A administered through intraperitoneal injection at 100 μg/mouse/day (n = 5); Group 3, a mechanistic exploration experiment including Ctrl, periodontitis + DMSO (Perio), periodontitis + tofacitinib (Perio + Tofa), Perio + αIL‐17A groups, with tofacitinib administered at 10 mg/kg and αIL‐17A at 100 μg/mouse/day for 6 days (n = 5), aimed at investigating the regulation of the RANKL signaling pathway; and Group 4, Tofacitinib efficacy exploration experiment comprising Ctrl, Perio, and Perio + Tofa groups, with a 14‐day experimental period (n = 5). Anesthesia was induced by an intraperitoneal injection of avertin, and mice that lost their ligatures were excluded from the analysis. At the endpoint, euthanasia was conducted with isoflurane anesthesia, followed by cervical dislocation. The maxillae were harvested for the assessment of bone loss via micro‐computed tomography (micro‐CT) and were also prepared for histological analysis and TRAP staining. The study protocol was approved by the Ethics Committee of the West China Hospital of Stomatology, Sichuan University (WCHSIRB‐D‐2024‐146).

2.2. Micro‐CT

Mouse maxilla specimens were fixed in 4% paraformaldehyde for 24 h, then subjected to μCT scanning using a Scanco μCT 45 system (90 kV, 80 μA, 10 μm resolution). Three‐dimensional reconstructions of the mouse maxilla samples were reconstructed, and bone loss was assessed by measuring the distance from the cemento‐enamel junction (CEJ) to the alveolar bone crest (ABC) on the distal side of the first molar on each of the buccal surfaces.

2.3. Immunohistochemistry

The paraffin sections were dewaxed in xylene and subsequently hydrated using an alcohol gradient. Next, the sections were heated in citrate buffer (pH 6.0) to facilitate antigen retrieval, after which they were blocked with 3% hydrogen peroxide. The sections were blocked with 10% goat serum, followed by incubation with primary antibodies against IL‐17A (1:1000, HUABIO, China), RANKL (1:500, Proteintech, China), and p‐STAT3 (1:200, CST, USA) at 4°C overnight. The assays were conducted using a universal SP kit and 3, 3′‐diaminobenzidine (DAB) color development kits (ZSGB‐BIO, China) in accordance with the manufacturer's instructions. Imaging was conducted using an SLIDEVIEW VS200 research‐grade whole slide scanner and quantitative analysis was performed using ImageJ software (version 1.52p).

2.4. PDLCs Primary Separation

Human third molars were obtained from three young, healthy adult patients (12–28 years old) undergoing molar extraction for orthodontic reasons at the West China Hospital of Stomatology, Sichuan University, Chengdu, China. Approval to conduct this study was granted by the Ethics Committee of the West China Hospital of Stomatology, Sichuan University, for research involving humans (WCHSIRB‐D‐2024‐048), and informed consent was obtained from the donors in accordance with the Declaration of Helsinki. PDLCs were separated from the middle third of the root surface and then enzymatically digested for 40 min at 37°C in a solution of 3 mg/mL collagenase I (Sigma, USA). The cells were cultured in DMEM/HIGH glucose medium (Hyclone, USA), supplemented with 10% fetal bovine serum (FBS, PAN, Germany) and 1% antibiotics (Hyclone, USA), at 37°C under 5% humidified CO2. PDLCs used in this study were between the fourth and seventh generations.

2.5. Osteoclast Induction

The RAW264.7 cells were kindly provided by Dr. Sun Yuezhang from the State Key Laboratory of Oral Diseases, Sichuan University. The RAW264.7 cells were cultured with DMEM/HIGH glucose medium containing 10% FBS in a 37°C, 5% CO2 incubator. RAW264.7 cells were seeded in a 24‐well plate at a density of 5 × 103 cells/well in the α‐MEM medium with different concentrations of RANKL (0–100 ng/mL, Sinobiological, China). The medium was replaced with fresh RANKL‐containing medium every 2–3 days. After culturing for 5 days, TRAP and cytoskeleton staining were performed. TRAP staining was conducted following the kit manufacturer's instructions (Solarbio, China).

2.6. Co‐Culturing PDLCs With RAW264.7 Macrophages

A transwell chamber was placed within a 24‐well plate that had been previously seeded with RAW264.7 cells. PDLCs were subsequently introduced into the upper chamber. Human M‐CSF recombinant protein (30 ng/mL, PeproTech, USA) and human RANKL recombinant protein (50 ng/mL, PeproTech, USA) were added to all groups, while human IL‐17A recombinant protein (20 ng/mL, PeproTech, USA) was added to the corresponding groups. Following a culture period of 7 days, the RAW264.7 cells were harvested for TRAP staining and cytoskeleton staining. The number of osteoclasts was quantified microscopically and defined as TRAP‐positive cells with three or more nuclei.

2.7. Immunofluorescence

In a sterile workbench, sterilized coverslips were placed in a six‐well plate. The cell suspension was added dropwise onto the coverslips. After treating with IL‐17A (20 ng/mL), tofacitinib (500 μM), and IL‐17A (20 ng/mL) + tofacitinib (500 μM) for 2 h, p‐STAT3 (Y705) staining was performed, and after 48 h of treatment, RANKL staining was performed. Cells were fixed with 4% paraformaldehyde and stained with primary antibodies against p‐STAT3 (1:200, CST, USA) and RANKL (1:500, proteintech China), using a secondary antibody labeled with 488 fluorescence (1:2000, Invitrogen, USA). Imaging was performed with an Olympus FV3000 confocal microscope. Fluorescence quantification analysis was performed using ImageJ software (version 1.52p).

2.8. Western Blot

PDLCs were stimulated with IL‐17A (20 ng/mL) for 48 h to detect RANKL expression and stimulated at 0, 0.5, 1, and 2 h to measure the levels of p‐STAT3. Total protein was extracted using RIPA lysis buffer (Beyotime, China). The extracted proteins from each sample were separated via 10% SDS‐PAGE and subsequently transferred to 0.2 μm PVDF membranes. The membranes were blocked using 5% skim milk and subsequently incubated overnight at 4°C with primary antibodies targeting p‐STAT3 (1:2000, CST, USA), STAT3 (1:2000, CST, USA), RANKL (1:1000, Proteintech, China) and β‐actin (1:3000, HUABIO, China). Subsequently, the membranes were treated with horseradish peroxidase (HRP)‐conjugated secondary antibodies specific to the primary antibodies (Zhongshan, China) for 2 h. Proteins were visualized using enhanced chemiluminescence reagents (Millipore, USA), and images were captured using an automated gel imaging system (Bio‐Rad, USA).

2.9. Quantitative Reverse Transcription Polymerase Chain Reaction

The cells were harvested for RNA extraction using an RNeasy Plus Mini Kit (Qiagen, Germany). In total, 500 ng RNA was used for reverse transcription with a PrimeScript RT reagent Kit (Takara, Japan). Polymerase chain reaction was performed using TB Green Premix Ex Taq II (Takara, Japan) on a QuantStudio 5 system (Thermo, USA), with GAPDH as the internal control. The primer sequences used are listed in Table S1.

2.10. Cytoskeleton Staining

The induced osteoclasts were fixed using 4% paraformaldehyde. Actin‐Tracker Red 555 (Beyotime Biotechnology, China) was prepared by diluting it in PBS containing 1% bovine serum albumin (BSA) and was incubated for half an hour at RT in the absence of light. Subsequently, DAPI (Solarbio, China) was applied to nuclei for staining for 2 min. Osteoclasts were quantified microscopically and defined as multinucleated cells containing three or more nuclei.

2.11. Flow Cytometry

Single‐cell suspensions were obtained from mouse gingival tissues. For intracellular cytokine staining, cells were stimulated with Phorbol 12‐myristate 13‐acetate (10 ng/mL), ionomycin (750 ng/mL), and Golgi‐Plug (1:1000 dilution) at 37°C for 4 h. Following this, cells were initially subjected to live viability and cell surface marker staining for 20 min at 4°C in the dark. Subsequently, cells were fixed using a fixation/permeabilization buffer in accordance with the manufacturer's guidelines (BD, USA). The stained cells were then analyzed with a Beckman CytoFLEX S flow cytometer (Beckman Coulter Life Science, USA), and data analysis was conducted using FlowJo software (version 10.8.1).

2.12. Bioinformatic Analysis

Single‐cell RNA sequencing data analysis: A previously published single‐cell RNA sequencing dataset, comprising five periodontal ligament biopsies from healthy individuals, was reanalyzed for this study (Pagella et al. 2021). Files downloaded from GEO (GSE 161267) accession viewer were extracted and imported into a Seurat object. Data quality control, integration, cell identification, and analysis were performed using the R package Seurat. Transcription factor binding site prediction: First, the transcription start site (TSS) of the target gene was identified using the NCBI Gene database, and the promoter region was defined as the sequence spanning 2000 bp upstream to 100 bp downstream of the TSS. The genomic sequence of this region was then extracted using the UCSC genome browser to preliminarily screen for transcription factors potentially interacting with the promoter (https://genome.ucsc.edu/). Next, the JASPAR database (https://jaspar.genereg.net/) was utilized to predict transcription factor binding sites. The JASPAR prediction was performed using default parameters, where the relative profile score threshold was adjusted to > 85% to prioritize high‐confidence binding sites.

2.13. Statistical Analysis

SPSS 26.0 was used for statistical analysis, and Graphpad Prism 8 was used for drawing. Data were expressed as mean ± SD. Data normality was assessed using the Shapiro–Wilk test. For two‐group comparisons, unpaired Student's t‐test was used, while one‐way ANOVA with Bonferroni correction was applied for multiple comparisons. A p‐value of < 0.05 was deemed statistically significant, with the following designations: *p < 0.05, **p < 0.01, and ***p < 0.001; ns, not significant.

3. Results

3.1. IL‐17A Is Implicated in the Exacerbation of Alveolar Bone Loss in Periodontitis

A ligature was placed between the first and second molars, which led to time‐dependent alveolar bone loss and osteoclast activation. At each time point, micro‐CT scans were used to obtain representative sagittal 3D and bi‐dimensional views of mouse maxillary molars, revealing a progressive increase in alveolar bone loss over time (Figure 1A,B). TRAP staining revealed an increase in osteoclast numbers in the ligature‐induced periodontitis (LIP) model group at various time points (Figure 1A,C). Osteoclast activation occurred predominantly during the early stages (Days 3–9). Our findings indicated that IL‐17A expression increased in the LIP model (Figure 1A,D). Flow cytometric analysis revealed a higher population of Th17 cells in gingival tissues in the LIP model (Figure S1A,B). Furthermore, treating mice with periodontitis using αIL‐17A significantly reduced alveolar bone loss (Figure 1E,F) and inhibited the recruitment of neutrophils (Figure S1C,D). Collectively, IL‐17A is significantly elevated in periodontitis, resulting in alveolar bone loss; therefore, targeting IL‐17A may represent an effective therapeutic strategy (Dutzan et al. 2018). However, the specific mechanisms underlying the regulation of alveolar bone loss by IL‐17A require further investigation.

FIGURE 1.

FIGURE 1

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Time course of alveolar bone loss, osteoclast activation and IL‐17A expression in LIP. (A) Representative sagittal 3D and bi‐dimensional views of the maxillary molars at 0, 3, 6, 9, and 14 days. The red arrows indicate the distances from the CEJ to ABC on the buccal side (n = 3). Scale bars: 0.5 mm. Representative TRAP‐stained sections at 0, 3, 6, 9, and 14 days (n = 3). Scale bars: 100 μm (upper panel) and 25 μm (lower panel). The red arrowheads mark osteoclasts. Representative IL‐17A immunohistochemically stained sections at 0, 3, 6, 9, and 14 days after insertion of ligature. Scale bars: 40 μm (upper panel) and 10 μm (lower panel). (B) Measurement of the distance from the CEJ to the ABC. (C) Quantitative analysis of the TRAP+ cells (osteoclast). (D) Quantitative analysis of IL‐17A+ cells. (E) Representative sagittal 3D and bi‐dimensional views of the maxillary molars treated with αIL‐17A (100 μg/day) for 14 days in control (Ctrl), periodontitis + isotype control (Perio) and periodontitis + αIL‐17A (Perio + αIL‐17A) (n = 3). Scale bars: 0.5 mm. (F) Measurement of the distance from the CEJ to the ABC on the buccal side. The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD. *p < 0.05, **p < 0.01, and ***p < 0.001; ns, no significant.

3.2. IL‐17A‐Induced RANKL Produced by PDLCs Drives Osteoclasts Activation

Given the established positive correlation between IL‐17A accumulation and osteoclast activation in periodontitis, the direct mechanistic link whereby IL‐17A regulates pathological osteoclast differentiation remains unclear. Immunohistochemical staining revealed that RANKL expression was significantly elevated during the 3–6‐day period in the LIP model, primarily in the periodontal ligament tissue (Figure 2A,B). We examined the expression of TNFSF11 (RANKL) in different cell types using scRNA‐seq data from human periodontal ligament samples. The results showed that mesenchymal cells were the main source of RANKL (Figure S2A,B). To validate these findings, we stimulated PDLCs with recombinant human IL‐17A, and western blotting indicated that IL‐17A significantly promoted RANKL expression (Figure 2C). RAW264.7 cells were exposed to escalating RANKL concentrations (0–100 ng/mL) for 5 days. Reverse transcription polymerase chain reaction and TRAP staining demonstrated that osteoclast activation increased in a concentration‐dependent manner with respect to RANKL levels (Figure S2C–H). Based on these findings, we selected an intermediate RANKL concentration (50 ng/mL) for subsequent experiments to achieve an optimal balance between osteoclastogenesis induction and experimental stability. Critical co‐culture experiments revealed that while IL‐17A alone minimally promoted osteoclast differentiation in RAW264.7 monocultures, its addition to hPDLCs‐RAW264.7 co‐cultures dramatically amplified osteoclastogenesis (Figure 2D–G), unequivocally establishing PDLC‐derived RANKL as the dominant effector of IL‐17A‐induced bone resorption.

FIGURE 2.

FIGURE 2

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RANKL expression response to IL‐17A in periodontal ligament contributes to osteoclastic differentiation of RAW264.7. (A) Representative immunohistochemical stained sections of RANKL in periodontal ligament sections at 0, 3, 6, 9, and 14 days. Scale bars: 40 μm (upper panel) and 10 μm (lower panel). (B) Quantitative analysis of the RANKL immunostaining intensity. (C) Western blot analysis of RANKL expression stimulated with 20 ng/mL IL‐17A for 48 h in PDLCs. (D) Schematic diagram of the PDLCs and RAW264.7 co‐culture system. (E) Representative TRAP stained and F‐Actin (red) immunofluorescence‐stained sections of RAW264.7 cells in the co‐culture system, all groups were supplemented with 30 ng/mL M‐CSF and 50 ng/mL RANKL. (F) Quantitative analysis of TRAP+ cells per well. (G) Quantitative analysis of osteoclasts per well. Scale bars: 10 μm. The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD. *p < 0.05, **p < 0.01, and ***p < 0.001; ns, no significant.

3.3. IL‐17A Mediated the Expression of RANKL via the JAK/STAT3 Pathway in PDLCs

The above results elucidated the regulatory function of IL‐17A in relation to RANKL. NF‐κB is a well‐known downstream signaling pathway of IL‐17A. We analyzed the UCSC database (https://genome.ucsc.edu/) to identify potential transcription factors that regulate RANKL. Interestingly, while NF‐κB was not identified, we discovered another promising molecule, STAT3, which may play a significant role in this regulatory process. Several studies have reported that the STAT3 signaling pathway is responsive to IL‐17A (Li et al. 2018; Qian et al. 2010; Samarpita et al. 2024; Wang et al. 2021). Next, we used the JASPAR database (https://jaspar.elixir.no/) to predict transcription factor‐binding sites in the promoter region of the TNFSF11 (RANKL). The prediction results indicated that there were 19 potential binding sites for STAT3 within the RANKL gene promoter region, with a set threshold of 8.5. The highest score for the predicted site was 1, indicating an important relationship between STAT3 and RANKL (Figure 3A; Table S2). Additionally, given the absence of clinically approved STAT3 inhibitors, we opted to use the clinically approved JAK inhibitor tofacitinib for subsequent experiments. Tofacitinib inhibits JAK activity, which in turn effectively obstructs the phosphorylation and activation of STAT3, consequently influencing the expression of its downstream target genes. To validate these findings, we treated PDLCs with human recombinant protein IL‐17A and detected the phosphorylation of STAT3 at tyrosine 705 in a time‐dependent manner (Figure 3B). Tofacitinib inhibited the phosphorylation of STAT3 (Figure 3C,D). Furthermore, tofacitinib counteracted the increase in RANKL induced by IL‐17A (Figure 3E,F). Taken together, these in vitro results indicated that IL‐17A modulates RANKL expression via activation of the JAK/STAT3 signaling pathway in human periodontal ligament cells.

FIGURE 3.

FIGURE 3

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IL‐17A mediates RANKL expression through the JAK/STAT3 pathway in PDLCs. (A) Schematic diagram of the promoter region upstream of the TNFSF11 transcription start site, highlighting enriched STAT3 binding motifs (predicted by JASPAR, MA0144.3). (B) Western blot analysis of p‐STAT3 levels in PDLCs treated with IL‐17A (20 ng/mL) for 0, 0.5, 1 and 2 h. (C) Representative immunofluorescence‐stained sections of p‐STAT3 expression in PDLCs treated with IL‐17A (20 ng/mL) or IL‐17A (20 ng/mL) + tofacitinib (500 nM) for 2 h. (D) Quantitative analysis of the p‐STAT3 immunostaining intensity. (E) Representative immunofluorescence‐stained sections of RANKL expression in PDLCs treated with IL‐17A (20 ng/mL) or IL‐17A (20 ng/mL) + tofacitinib (500 nM) for 48 h. (F) Quantitative analysis of the RANKL immunostaining intensity Scale bars: 20 μm. The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD. **p < 0.01.

3.4. Tofacitinib Alleviated Alveolar Bone Loss and Inflammation Through Inhibition Th17 Differentiation and Osteoclast Activation

We investigated the effect of tofacitinib on Th17 cell differentiation and osteoclast formation in vivo. The mice were treated with tofacitinib (10 mg/kg) or αIL‐17A (100 μg/mouse/day) for 6 days after the insertion of ligature (Figure 4A). Considering that the IL‐6 signaling pathway is a well‐established target of JAK inhibitors and plays a crucial role in Th17 cell differentiation, tofacitinib may also contribute to the suppression of Th17 cell differentiation. Notably, at 6 days post‐LIP, we detected significant upregulation of IL‐17A expression in the gingival, enhanced STAT3 phosphorylation at Y705 in the periodontal ligament, and a marked increase in RANKL levels, which coincided with extensive osteoclast activation. These effects were effectively suppressed by tofacitinib and αIL‐17A (Figure 4B–F). These results suggested that IL‐17A mediates the expression of RANKL in PDLCs through the activation of STAT3, thereby promoting osteoclast activation in vivo. Tofacitinib simultaneously inhibited the aforementioned processes, including Th17 cell differentiation and RANKL expression. Furthermore, quantitative analysis revealed no statistically significant alterations in alveolar bone morphology, which was attributable to the absence of measurable bone resorption in the experimental cohort at the 6‐day observational time point (Figure S3A,B). Additionally, we did not observe a significant increase in RANKL levels in the serum of mice (Figure S3C). We speculate that inflammation may primarily occur locally on the sixth day after the insertion of ligature. We further investigated the efficacy of tofacitinib in periodontitis. We administered tofacitinib (10 mg/kg) to the mice treated for 14 days (Figure 5A). Micro‐CT analysis demonstrated that tofacitinib treatment significantly reduced alveolar bone loss (Figure 5B,C). As osteoclast activation occurs at an early stage, we did not observe significant osteoclastic changes on Day 14 (Figure S4A,B). Interestingly, serum RANKL levels were elevated in LIP mice by Day 14, which were partially reversed by tofacitinib treatment (Figure S4C). This temporal shift implies progressive immune activation beyond the periodontal niche. Consistent with its anti‐inflammatory role, tofacitinib reduced MPO+ neutrophil infiltration (Figure 5D,E). These results demonstrated that tofacitinib exerts potent therapeutic effects against periodontitis, suggesting its potential as a novel therapeutic agent for periodontal disease management.

FIGURE 4.

FIGURE 4

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IL‐17A regulates RANKL through the STAT3 signaling pathway in vivo. (A) Schematic diagram of the experimental design for treating LIP with tofacitinib and αIL‐17A for 6 days. (B) Representative immunohistochemical stained sections of IL‐17A, p‐STAT3, and RANKL, as well as TRAP‐stained sections treated with αIL‐17A (100 μg/day) and tofacitinib (10 mg/kg) in the control (Ctrl), periodontitis + DMSO (Perio), periodontitis + tofacitinib (Perio + Tofa) and periodontitis + αIL‐17A (Perio + αIL‐17A) groups (n = 5). Scale bars: 10 μm (IHC staining) and 40 μm (TRAP staining). (C‐F) Quantitative analysis of IL‐17A, RANKL and p‐STAT3 staining intensity, and TRAP+ cells (osteoclasts). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD. **p < 0.01, and ***p < 0.001; ns, no significant.

FIGURE 5.

FIGURE 5

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Tofacitinib attenuates alveolar bone loss and inflammation in LIP. (A) Schematic diagram of the experimental design for treating LIP with tofacitinib for 14 days. (B) Representative sagittal 3D and bi‐dimensional views of maxillary molars treated with tofacitinib (10 mg/kg) in the control (Ctrl), periodontitis + DMSO (Perio), and periodontitis + tofacitinib (Perio + Tofa) groups (n = 4). Scale bars: 0.5 mm. (C) Measurement of the distance from the CEJ to the ABC on the buccal side. (D) Representative Hematoxylin and Eosin (H&E)‐stained and myeloperoxidase (MPO) immunohistochemically stained sections for tofacitinib treatment (n = 4). Scale bars: 40 μm. (E) Quantitative analysis of MPO+ cells. The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD. *p < 0.05, **p < 0.01, and ***p < 0.001.

4. Discussion

Previous research (Dutzan et al. 2018) and our recent findings (Zhou et al. 2024) have demonstrated elevated levels of IL‐17A and Th17 cells in periodontitis. IL‐17A exacerbates periodontal tissue damage and contributes to the progression of systemic diseases (Berry et al. 2022). Alveolar bone loss is a significant pathological alteration that is associated with periodontitis; however, the specific molecular mechanisms by which IL‐17A mediates alveolar bone loss are yet to be fully elucidated. In our study, we demonstrated that the gingival tissue produces a considerable quantity of IL‐17A, which subsequently diffuses into the underlying periodontal ligament. This process promotes the production of RANKL in PDLCs via the phosphorylation of STAT3 (Y705), thereby facilitating osteoclast formation. Furthermore, the clinically available JAK inhibitor tofacitinib was found to protect mice from alveolar bone loss during periodontitis (Figure 6).

FIGURE 6.

FIGURE 6

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Visualization illustrates the key cellular components and signaling pathways involved in the progression of osteoclast activation during periodontitis. It highlights the role of IL‐17A‐mediated regulation of RANKL expression in PDLCs and its potential therapeutic implications.

We used an LIP model to investigate the role of IL‐17A in the pathogenesis of periodontitis. Our findings revealed a significant increase in alveolar bone loss and osteoclast activity during the experimental phase of periodontitis compared to that in the control group. Specifically, a marked increase in the numbers of osteoclasts was observed primarily between Day 3 and 6, with these cells predominantly adhering to the surface of the alveolar bone. In contrast, the most pronounced changes in alveolar bone loss were observed on Day 14. Notably, osteoclasts have been detected prior to the onset of significant alveolar bone loss (Jang et al. 2024; Zhuang et al. 2019). The process of osteoclastogenesis involves the binding of these cells to the bone surface, where they secrete acids and enzymes that facilitate the demineralization of the bone matrix, thereby exacerbating alveolar bone loss (Andreev et al. 2020; Bae et al. 2023). Similarly, immunohistochemistry (IHC) data demonstrated a sustained increase in the number of IL‐17A‐positive cells in the gingival tissues during experimental periodontitis, which is consistent with the results of a previous study (Dutzan et al. 2017). IL‐17A exacerbates the inflammatory response in periodontal tissues by promoting the recruitment and activation of neutrophils, leading to bone resorption and destruction of periodontal tissues (Kim et al. 2023). Targeting IL‐17A resulted in effective relief of alveolar bone loss, and IL‐17A antibodies significantly reduced neutrophil recruitment and decreased the inflammatory response. However, the response to IL‐17A antibodies may vary among patients, and some individuals may be insensitive to this treatment, necessitating monitoring for potential suppression of the immune system or other adverse effects in a clinical setting (Berry et al. 2022; Wang et al. 2023). Therefore, the identification of new and reliable therapeutic targets is an urgent issue that needs to be addressed for the treatment of periodontitis.

Gingivitis is the initial stage of periodontitis and the epithelium serves as the primary barrier against invasion by pathogens and bacteria. When this barrier is compromised, inflammation progresses downward, ultimately resulting in alveolar bone loss (Curtis et al. 2020). The RANKL/osteoprotegerin (OPG) system is crucial for osteoclastogenesis, and RANKL expression levels are indicative of bone loss (Andreev et al. 2020). RANKL is primarily produced by osteoblasts, synovial fibroblasts, mesenchymal cells, T cells, and B cells. These cells participate in regulating the differentiation of osteoclasts and the process of bone resorption (El‐Masri et al. 2024; Ni et al. 2021; Yan et al. 2022). Based on the IHC results, we observed that RANKL levels significantly increased on the sixth day following LIP and were primarily localized in the periodontal ligament tissue. Single‐cell analysis also suggested that RANKL expression in periodontal ligament tissue primarily originates from mesenchymal cells. Therefore, we investigated the effect of IL‐17A on RANKL expression in PDLCs. Critical co‐culture experiments revealed that the addition of IL‐17A to hPDLCs‐RAW264.7 co‐cultures dramatically amplified osteoclastogenesis, unequivocally establishing PDLCs‐derived RANKL as the dominant effector of IL‐17A‐induced bone resorption. These findings support the notion that IL‐17A plays a crucial role in RANKL expression in PDLCs, thereby further promoting osteoclast activation.

The direct targeting of RANKL in clinical therapy (e.g., denosumab) can inhibit RANKL‐mediated bone resorption. However, long‐term use may lead to decreased bone mineral density and an increased risk of fracture (Zhang et al. 2020). RANKL also plays a significant role in immune regulation, and treatments targeting RANKL may adversely affect immune function, thereby increasing the risk of infection (Li et al. 2022). In patients with periodontal disease, the use of RANKL antibodies may elevate the risk of osteonecrosis, particularly in the jawbone, potentially resulting in tooth loss (Beth‐Tasdogan et al. 2022). Therefore, targeting RANKL in the context of periodontitis is undesirable. To further investigate the mechanism of RANKL production, we examined the transcriptional regulators that control RANKL expression. Bioinformatic analysis indicated that binding motifs for the STAT3 transcription factor were significantly enriched in the RANKL promoter region. Additionally, JAK/STAT3 activation in mesenchymal cells is essential for the induction of RANKL and the formation of osteoclasts (Sanpaolo et al. 2020). Furthermore, IL‐17A binding to sIL‐17AR has been shown to activate JAK tyrosine kinase and STAT transcription factors (Lu et al. 2023). Our findings revealed that IL‐17A stimulation of PDLCs significantly activated STAT3 and induced RANKL expression, whereas the JAK inhibitor tofacitinib reduced RANKL expression. In summary, STAT3 activation is crucial for osteoclastogenesis as it regulates RANKL expression within the IL‐17A‐activated signaling pathway. Thus, targeting the STAT3 signaling pathway may represent a promising strategy for the treatment of periodontitis.

Tofacitinib is a JAK inhibitor that modulates immune responses primarily by inhibiting the JAK–STAT signaling pathway. It has been approved for the treatment of rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis (Ogdie et al. 2020). Tofacitinib has demonstrated significant efficacy in the treatment of various diseases and has emerged as an important therapeutic option, in addition to traditional biologics. Compared with direct RANKL‐targeting therapies, JAK inhibitors demonstrate multi‐target anti‐inflammatory advantages in periodontitis treatment by suppressing pro‐inflammatory cytokines and modulating the RANKL/OPG equilibrium, thereby exerting the dual therapeutic effects of anti‐inflammation and osteogenic promotion. Their oral administration regimen provides superior convenience for long‐term disease management compared with injectable anti‐RANKL agents. Additionally, the established clinical applications of JAK inhibitors in inflammatory diseases may expedite their therapeutic repurposing for periodontitis through accelerated clinical adaptation pathways (Kang et al. 2019; Spalinger et al. 2021). STAT3 is a canonical downstream effector of the IL‐6 signaling pathway and serves as a key transcription factor during Th17 cell differentiation (Qin et al. 2024; Yamashita et al. 2011). We propose that tofacitinib mitigates alveolar bone loss via two mechanisms: inhibition of Th17 cell differentiation and suppression of RANKL expression. In vivo, we treated mice with periodontitis using tofacitinib (10 mg/kg) and observed significant inhibition of Th17 cell differentiation and osteoclast formation, and downregulation of RANKL expression. RANKL expression was significantly reduced after blocking IL‐17A in the LIP model. Compared to the untreated group, mice with periodontitis treated with tofacitinib exhibited a significant reduction in both alveolar bone loss and inflammatory response. Two cases documented within a single study have now demonstrated a reduction in periodontitis among osteoarthritis patients treated with JAK inhibitors, consistent with our findings (Kobayashi et al. 2019).

This study has several limitations. Firstly, the results were predominantly derived from animal models and in vitro experiments, which may not fully capture the complexity of human periodontitis. Future studies are needed to validate these results using clinical samples. Secondly, while our study demonstrated the efficacy of tofacitinib in suppressing the IL‐17A/STAT3/RANKL axis in periodontitis, several clinical limitations must be considered. The ORAL Surveillance study revealed that JAK inhibitors increase the risks of cardiovascular events, malignancies, and venous thromboembolism, particularly in elderly patients and those with cardiovascular comorbidities (Desai et al. 2021; Ingrassia et al. 2024; Winthrop and Cohen 2022). Additionally, they may elevate the risk of herpes zoster reactivation and opportunistic infections, and a reduced‐dose regimen or combination therapy with anti‐TNF agents is recommended for high‐risk populations. Future development should focus on targeted delivery systems and stimuli‐responsive platforms to minimize systemic exposure (Ireland et al. 2025; Winthrop and Cohen 2022). Despite their multi‐target advantages, the long‐term safety of JAK inhibitors requires further pharmacovigilance data.

5. Conclusion

Our research elucidated the longitudinal dynamics of periodontitis infection, indicating that pathogens, predominantly infiltrate from gingival tissue. This invasion initiates a cascade of inflammatory responses, resulting in substantial production of IL‐17A, which extends into the periodontal ligament tissue over time. IL‐17A facilitates the activation of STAT3 within periodontal ligament cells and stimulates the expression of RANKL. RANKL promotes the differentiation of mononuclear macrophages into osteoclasts, which subsequently exert direct effects on the neighboring alveolar bone, culminating in alveolar bone loss. Tofacitinib, a clinically available JAK inhibitor, presents as an innovative and promising therapeutic agent for periodontal disease, through its demonstrated ability to significantly attenuate alveolar bone loss.

Author Contributions

Die Lv: methodology, software, data curation, investigation, writing – original draft, formal analysis, conceptualization, validation, visualization. Jiuge Zhang: data curation, software, investigation, formal analysis. Yixin Zhang: methodology, software, formal analysis. Ying Zhou: methodology, software. Weideng Wei: methodology, data curation. Lisheng Zhang: methodology, visualization. Xiaoqiang Xia: conceptualization, methodology. Jiao Chen: conceptualization, methodology, validation. Qianming Chen: conceptualization, project administration. Ping Zhang: conceptualization, validation, project administration. Yuan Yue: conceptualization, writing – review and editing, project administration, resources, supervision. Xiaodong Feng: writing – review and editing, funding acquisition, conceptualization, resources, project administration, supervision.

Funding

This work was supported by the National Natural Science Foundation of China (NSFC) (grant nos. 82170971, 82373187, and 82001060), Sichuan Science and Technology Program (2025NSFJQ0062 and 2024YFFK0293), and Scientific Research Foundation, West China Hospital of Stomatology, Sichuan University (RD‐03‐202110).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Figure S1: Time course of alveolar bone loss, osteoclast activation and IL‐17A expression in LIP. (A, B) Flow cytometric analysis of IL‐17A+ cells within the CD4+ T cell population from gingival tissues for 14 days in the control (Ctrl) and periodontitis (Perio) groups (n = 3). (C) Representative H&E‐stained and MPO immunohistochemically stained sections treated with αIL‐17A (100 μg/day) in the control (Ctrl), periodontitis + isotype control (Perio) and periodontitis + αIL‐17A (Perio + αIL‐17A) groups (n = 3). Scale bars: 40 μm. (D) Quantitative analysis of MPO+ infiltrating cells. The p values were calculated by Student's t‐test (B) or one‐way ANOVA with Bonferroni post hoc test (D) and expressed as mean ± SD.

ODI-32-1652-s002.jpg (1.5MB, jpg)

Figure S2: RANKL expression response to IL‐17A in periodontal ligament contributes to osteoclastic differentiation of RAW264.7. (A, B) Single‐cell RNA sequencing analysis of TNFSF11/RANKL expression levels across distinct cell populations in periodontal ligament tissue. (C‐F) Relative mRNA expression levels of osteoclast markers (Acp5, Mmp9, Nfatc1, Ctsk) in RAW264.7 cells treated with 0–100 ng/mL RANKL for 5 days. (G) Representative TRAP‐stained sections of RAW264.7 cells treated with 0, 12.5, 25, 50, or 100 ng/mL RANKL for 5 days. (H) Quantitative analysis of the TRAP+ cells (osteoclast). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD.

ODI-32-1652-s004.jpg (1.7MB, jpg)

Figure S3: IL‐17A regulates RANKL through the STAT3 signaling pathway. (A) Representative sagittal 3D and bi‐dimensional views of maxillary molars treated with αIL‐17A (100 μg/day) and tofacitinib (10 mg/kg) in the control (Ctrl), periodontitis + DMSO (Perio), periodontitis +tofacitinib (Perio + Tofa), and periodontitis + αIL‐17A (Perio + αIL‐17A) groups at 6 days post‐treatment (n = 5). Scale bars: 0.5 mm. (B) Measurement of the distance from the CEJ to the ABC on the buccal side. (C) RANKL levels in serum measured by ELISA (n = 5). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD.

ODI-32-1652-s003.jpg (1.2MB, jpg)

Figure S4: Tofacitinib attenuates alveolar bone loss in LIP. (A) Representative TRAP‐stained sections treated with tofacitinib (10 mg/kg) in the control (Ctrl), periodontitis + DMSO (Perio), and periodontitis + tofacitinib (Perio + Tofa) groups following 14‐day treatment with tofacitinib (n = 4). Scale bars: 40 μm. (B) Quantitative analysis of the TRAP+ cells (osteoclast). (C) Serum RANKL levels measured by ELISA (n = 4). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD.

ODI-32-1652-s001.jpg (956.5KB, jpg)

Table S1: Primer sequences.

Table S2: Analysis of STAT3 binding sites in theTNFSF11/RANKL promoter by JASPAR database.

ODI-32-1652-s005.docx (33.9KB, docx)

Acknowledgments

This work was supported by the National Natural Science Foundation of China (NSFC) (grant nos. 82170971, 82373187, and 82001060), Sichuan Science and Technology Program (2025NSFJQ0062 and 2024YFFK0293), and Scientific Research Foundation, West China Hospital of Stomatology, Sichuan University (RD‐03‐202110). The authors thank Ning Ji (State Key Laboratory of Oral Diseases, Sichuan University) for assistance with the microscopic imaging.

Contributor Information

Yuan Yue, Email: hxkqyueyuan@163.com.

Xiaodong Feng, Email: xiaodongfeng@scu.edu.cn.

Data Availability Statement

This study reanalyzed the publicly available single‐cell RNA sequencing dataset GSE161267 from the Gene Expression Omnibus (GEO) database, originally published by Pagella et al. (iScience 24, 102405, 2021). Files downloaded from the GEO accession portal were extracted and imported into a Seurat object for secondary analysis. Since no new sequencing data were generated, data deposition in a public repository is not applicable.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1: Time course of alveolar bone loss, osteoclast activation and IL‐17A expression in LIP. (A, B) Flow cytometric analysis of IL‐17A+ cells within the CD4+ T cell population from gingival tissues for 14 days in the control (Ctrl) and periodontitis (Perio) groups (n = 3). (C) Representative H&E‐stained and MPO immunohistochemically stained sections treated with αIL‐17A (100 μg/day) in the control (Ctrl), periodontitis + isotype control (Perio) and periodontitis + αIL‐17A (Perio + αIL‐17A) groups (n = 3). Scale bars: 40 μm. (D) Quantitative analysis of MPO+ infiltrating cells. The p values were calculated by Student's t‐test (B) or one‐way ANOVA with Bonferroni post hoc test (D) and expressed as mean ± SD.

ODI-32-1652-s002.jpg (1.5MB, jpg)

Figure S2: RANKL expression response to IL‐17A in periodontal ligament contributes to osteoclastic differentiation of RAW264.7. (A, B) Single‐cell RNA sequencing analysis of TNFSF11/RANKL expression levels across distinct cell populations in periodontal ligament tissue. (C‐F) Relative mRNA expression levels of osteoclast markers (Acp5, Mmp9, Nfatc1, Ctsk) in RAW264.7 cells treated with 0–100 ng/mL RANKL for 5 days. (G) Representative TRAP‐stained sections of RAW264.7 cells treated with 0, 12.5, 25, 50, or 100 ng/mL RANKL for 5 days. (H) Quantitative analysis of the TRAP+ cells (osteoclast). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD.

ODI-32-1652-s004.jpg (1.7MB, jpg)

Figure S3: IL‐17A regulates RANKL through the STAT3 signaling pathway. (A) Representative sagittal 3D and bi‐dimensional views of maxillary molars treated with αIL‐17A (100 μg/day) and tofacitinib (10 mg/kg) in the control (Ctrl), periodontitis + DMSO (Perio), periodontitis +tofacitinib (Perio + Tofa), and periodontitis + αIL‐17A (Perio + αIL‐17A) groups at 6 days post‐treatment (n = 5). Scale bars: 0.5 mm. (B) Measurement of the distance from the CEJ to the ABC on the buccal side. (C) RANKL levels in serum measured by ELISA (n = 5). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD.

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Figure S4: Tofacitinib attenuates alveolar bone loss in LIP. (A) Representative TRAP‐stained sections treated with tofacitinib (10 mg/kg) in the control (Ctrl), periodontitis + DMSO (Perio), and periodontitis + tofacitinib (Perio + Tofa) groups following 14‐day treatment with tofacitinib (n = 4). Scale bars: 40 μm. (B) Quantitative analysis of the TRAP+ cells (osteoclast). (C) Serum RANKL levels measured by ELISA (n = 4). The p values were calculated by one‐way ANOVA with Bonferroni post hoc test and expressed as mean ± SD.

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Table S1: Primer sequences.

Table S2: Analysis of STAT3 binding sites in theTNFSF11/RANKL promoter by JASPAR database.

ODI-32-1652-s005.docx (33.9KB, docx)

Data Availability Statement

This study reanalyzed the publicly available single‐cell RNA sequencing dataset GSE161267 from the Gene Expression Omnibus (GEO) database, originally published by Pagella et al. (iScience 24, 102405, 2021). Files downloaded from the GEO accession portal were extracted and imported into a Seurat object for secondary analysis. Since no new sequencing data were generated, data deposition in a public repository is not applicable.

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