Anti‐Inflammatory Effects of Vicatia thibetica De Boiss. in Rheumatoid Arthritis and Associated Multi‐Pathway Modulation In Vivo

ABSTRACT

Vicatia thibetica de Boiss. (VTDB) is not only used as an important Tibetan medicine but is also consumed as a common wild vegetable. Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovial inflammation and progressive destruction of cartilage and bone. VTDB is recorded in the Four Medical Classics for treating “Huang‐Shui,” a condition resembling RA. To preliminarily investigate its potential therapeutic basis, VTDB and its polarity‐based fractions were evaluated for their effects against RA. The chemical constituents of VTDB‐TE were profiled using UHPLC‐Q‐Orbitrap MS/MS, and network pharmacology analysis predicted possible involvement of the PI3K/Akt and JAK2/STAT3 signaling pathways. Among the tested fractions, VTDB‐nBuOH exhibited the most pronounced pharmacological activity in the collagen‐induced arthritis (CIA) rat model. VTDB‐nBuOH treatment was associated with reduced paw swelling, lower serum levels of rheumatoid factor (RF) and C‐reactive protein (CRP), and improved synovial histopathology. The treatment was also associated with reduced levels of pro‐inflammatory cytokines and alterations in the levels of proteins associated with PI3K/Akt, JAK2/STAT3, and the downstream IKK/IκB/NF‐κB axis. Additionally, VTDB‐nBuOH treatment was associated with a shift in macrophage polarization markers toward an anti‐inflammatory M2‐like phenotype, suggesting a possible restoration of the M1/M2 balance within the joint microenvironment. 16S rRNA sequencing revealed VTDB‐nBuOH treatment‐associated changes in gut microbial composition, including enrichment of certain beneficial genera and reduction of some pathogenic taxa. Proteomic analysis also pointed to the PI3K/Akt pathway as a potential node of interest. Collectively, these correlative findings suggest that VTDB‐nBuOH may alleviate synovial inflammation and cartilage and bone damage through multi‐pathway modulation, though further mechanistic studies are needed to establish causality. VTDB‐nBuOH shows preliminary promise for further investigation as a potential candidate for RA treatment.

Vicatia thibetica de Boiss. (VTDB) extracts and fractions were screened for anti‐rheumatoid arthritis activity via UHPLC‐MS, network pharmacology, and CIA rat models. VTDB‐nBuOH stood out, regulating PI3K/Akt, JAK2/STAT3, macrophage polarization, and gut microbiota to relieve joint inflammation, with proteomics verifying its multi‐pathway regulatory effects.

1. Introduction

Vicatia thibetica de Boiss. (VTDB), belonging to the Apiaceae family, is not only used as an important Tibetan medicine in the Qinghai‐Tibet plateau area but is also commonly consumed as a wild vegetable by local communities [1]. It is regarded as one of the five root medicines (Polygonatum sibiricum, Asparagus cochinchinensis, Vicatia thibetica de Boiss., Oxybaphus himalaicus, and Tribulus terrestris) in Tibetan medicine, and it possesses multiple traditional functions of strengthening the spleen, promoting digestion, activating blood, removing stasis, relieving cough, and removing sputum [2]. Recent studies have reported that V. thibetica de Boiss has significant antibacterial and anti‐inflammatory activities [3]. Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease affecting about 1% of the global population, with its prevalence continuing to increase worldwide [4, 5]. In the early stages, serological markers such as anti‐citrullinated protein antibodies and rheumatoid factor (RF) are often detectable [6]. The synovium plays a central role in RA pathogenesis [7]. Aberrant activation and proliferation of fibroblast‐like synoviocytes and macrophage‐like synoviocytes both drive synovial inflammation and osteoclastogenesis [8, 9]. FLSs secrete matrix metalloproteinases, including MMP‐3 and MMP‐13, which degrade cartilage, while receptor activator of nuclear factor‐κB ligand is overexpressed to promote osteoclast differentiation and bone resorption [10, 11]. Taken together, these pathological processes result in synovial hyperplasia, pannus formation, and progressive joint destruction.

Macrophages are pivotal in shaping the inflammatory microenvironment. Classically activated M1 macrophages release pro‐inflammatory cytokines such as TNF‐α, IL‐1β, and IL‐6, thereby amplifying inflammation and enhancing osteoclast activity. In contrast, alternatively activated M2 macrophages produce IL‐4, IL‐10, and TGF‐β, supporting immune regulation and tissue repair [12, 13]. Imbalances in M1/M2 polarization perpetuate chronic inflammation and joint damage, highlighting macrophage regulation as a promising therapeutic target. In addition to local joint pathology, systemic immune regulation has attracted increasing attention, especially regarding the role of the gut microbiota. The gastrointestinal tract—the largest immune organ—hosts numerous immune cells and diverse microbial communities [14]. Many orally administered natural compounds have low bioavailability. They reach the colon intact and interact with the gut microbiota to influence host immunity. Mounting evidence indicates that dysbiosis disrupts mucosal integrity, provokes low‐grade inflammation, and initiates systemic immune responses, thereby contributing to RA development through the gut‐joint axis [15, 16].

Current RA therapies primarily aim to suppress inflammation and modulate immunity [17]. These include non‐steroidal anti‐inflammatory drugs, glucocorticoids, conventional synthetic disease‐modifying antirheumatic drugs, and biological DMARDs [18]. Nanomedicine‐based drug‐delivery strategies have also been investigated for inflammatory joint diseases, including RA [19]. While effective in alleviating symptoms and slowing disease progression, these treatments often fail to address the three main pathological features of RA: chronic inflammation, abnormal osteoclast activation, and disrupted immune balance. Moreover, long‐term use can cause adverse effects such as immunosuppression, gastrointestinal toxicity, bone marrow suppression, infections, and hepatic or renal impairment [20]. These limitations underscore the urgent need for natural compounds with multitarget actions and favorable safety profiles. Comparative evaluation of solvent extracts or fractions has been used as a practical strategy to prioritize potentially active plant‐derived preparations [21, 22, 23]. Integrated phytochemical, in silico, and in vivo approaches have also been applied to explore the bioactive constituents and potential pharmacological basis of medicinal plant extracts [24, 25, 26]. In addition to modern medicine, traditional Tibetan medicine (TTM) has long been used to prevent and treat RA‐like disorders. Notably, the prevalence of RA in Tibet is markedly higher than in other regions of China, reaching 4.86%, possibly related to unique geographic and lifestyle factors. Within TTM theory, RA corresponds to Grum‐Bu disease, which arises from imbalances among the three humors—Lung, mKhris‐pa, and Bad‐kan [27]. Recognizing its clinical significance, RA has been included in the national monitoring index system for key specialty development in TTM. VTDB, known as “Jawa” in TTM, has traditionally been prescribed to regulate the three humors and to treat conditions described as “Huang‐Shui” [28]. Based on this ethnopharmacological background, the present study investigated the pharmacological efficacy of VTDB extracts using a collagen‐induced arthritis (CIA) rat model and explored potential pathways associated with their effects. These findings provide a scientific basis for the development of VTDB as a multi‐target candidate in RA therapy.

2. Materials and Methods

2.1. Reagents and Antibodies

MTX tablets were purchased from Shanghai Xinyi Medicine Co., Ltd. (Shanghai, China; No. H31020644). Bovine type II collagen (BIIC, 20022) and Incomplete Freund's adjuvant (IFA, 7002) were obtained from Chondrex, Inc. (Woodinville, WA, USA). ELISA kits for cytokines and related factors were purchased from Xiamen Lun Changshuo Biotechnology Co., Ltd. (Xiamen, China). These kits included tumor necrosis factor‐α (TNF‐α, ED‐31063), interleukin‐1β (IL‐1β, ED‐73004), interleukin‐6 (IL‐6, ED‐30219), interleukin‐10 (IL‐10, ED‐30194), interleukin‐17 (IL‐17, ED‐30201), interferon‐γ (IFN‐γ, ED‐30173), macrophage colony‐stimulating factor (M‐CSF, ED‐30531), granulocyte‐macrophage colony‐stimulating factor (GM‐CSF, ED‐30579), immunoglobulin M (IgM, ED‐30629), immunoglobulin G (IgG, ED‐30626), and hypoxia‐inducible factor‐1α (HIF‐1α, ED‐30312). Biochemical detection kits for blood urea nitrogen (BUN), creatinine (CREA), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were obtained from Nanjing Jiancheng Bioengineering Institute (Nanjing, China; product nos. C013‐2‐1, C011‐2‐1, C009‐2‐1, and C010‐2‐1, respectively). Primary antibodies against phospho‐JAK2 (Tyr1008, No. AB30495‐050) and STAT3 (No. T55292) were obtained from Huaan Biotechnology Co., Ltd. (Hangzhou, China) and Proteintech Group (Wuhan, China), respectively.

2.2. Herbal Material and Extract Preparation

The roots of VTDB were collected from Zhangba Village, Nyingchi City, Tibet Autonomous Region, China. Prof. Guoyue Zhong at the Research Center for Traditional Chinese and Ethnic Medicine, Jiangxi University of Chinese Medicine, performed botanical authentication. A voucher specimen (No. VTDB2309) was deposited in the university herbarium. Dried roots were pulverized and extracted three times with 95% ethanol under reflux. The combined extracts were concentrated under reduced pressure to yield the total ethanol extract (VTDB‐TE, 22.7%). The crude extract was sequentially partitioned with petroleum ether, ethyl acetate, and n‐butanol, yielding four fractions based on polarity: VTDB‐PE (3.30%), VTDB‐EtOAc (0.50%), VTDB‐nBuOH (1.90%), and the aqueous residual fraction VTDB‐W (15.40%). According to the Chinese Materia Medica, the clinical oral dosage of VTDB is 3–9 g/day. Based on preliminary rat experiments, an equivalent crude‐drug dose of 3.6 g/kg was selected for the present study. Based on this dosage, the corresponding extract doses were VTDB‐TE, 0.84 g/kg; VTDB‐PE, 0.12 g/kg; VTDB‐EtOAc, 0.02 g/kg; VTDB‐nBuOH, 0.07 g/kg; and VTDB‐W, 0.57 g/kg. These doses were calculated to correspond to the same equivalent crude‐drug dose, enabling comparison of the pharmacological activities of VTDB‐TE and its polarity‐based fractions on an equivalent crude‐drug basis.

2.3. UHPLC‐Q‐Orbitrap MS/MS

Fifty milligram of VTDB was dissolved in 2 mL of methanol. The solution was sonicated for 30 min and then centrifuged at 10 000 × g for 10 min. The supernatant was filtered through a 0.22 µm membrane prior to analysis. Chromatographic separation was performed on a Vanquish UHPLC system (Thermo Fisher Scientific, Waltham, MA, USA). The system was equipped with a Phenomenex Kinetex C18 column (2.1 × 100 mm, 2.6 µm) and used 0.1% acetic acid in water (A) and isopropanol–acetonitrile (1:1, v/v, B) as mobile phases. Mass spectrometric analysis was performed using an Orbitrap Exploris 120 mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) equipped with an ESI source. The voltage was set to +3.8 kV for positive mode and −3.4 kV for negative mode, sheath and auxiliary gases were set to 50 and 15 arbitrary units, respectively, and the capillary temperature was maintained at 300°C. Full MS and MS/MS spectra were acquired at resolutions of 60 000 and 30 000, respectively, using stepped normalized collision energies (NCE) of 20, 30, and 40.

2.4. Network Pharmacology‐Based Target Prediction

VTDB‐TE constituents were putatively annotated based on UHPLC‐Q‐Orbitrap MS/MS data and MassBank database matching using MassLynx, and structural information was retrieved from PubChem. Compounds were selected via SwissADME (http://www.swissadme.ch) [29]. Corresponding targets were predicted using SwissTarget Prediction (http://www.swisstargetprediction.ch). RA‐related targets were obtained from GeneCards (https://www.genecards.org), TTD (http://db.idrblab.net/ttd), OMIM (https://omim.org), and DrugBank (https://www.drugbank.ca). Shared VTDB–RA targets were identified using Venny 2.1 (http://bioinfogp.cnb.csic.es/tools/venny/), and PPI networks were constructed with STRING (https://string‐db.org) and visualized in Cytoscape 3.9.1. Core targets were screened with the MCODE plugin, and GO and KEGG enrichment analyses were performed using DAVID (https://david.ncifcrf.gov/tools.jsp) with p < 0.05 [30].

2.5. Experimental Animals

Male Wistar rats (6–8 weeks old, 200 ± 20 g), of specific pathogen‐free (SPF) grade, were obtained from Hunan SJA Laboratory Animal Co., Ltd. (Changsha, China; License No. SCXK [Xiang] 2022‐0002). All animals were housed under standard laboratory conditions, including a temperature of 23°C ± 2°C and a 12‐h light/dark cycle, with ad libitum access to food and water. All experimental procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals and were approved by the Animal Care and Use Committee of Jiangxi University of Chinese Medicine (Approval No. JZLLSC20220867).

2.6. Induction of CIA and Drug Administration

Male Wistar rats were acclimated for 7 days before the induction of CIA. The induction followed a previously reported protocol with minor modifications [31]. CIA was induced by two intradermal injections of bovine type II collagen (1 mg/mL) emulsified in a ratio of 1:1 with IFA on ice, administered 7 days apart. For the primary immunization, 0.2 mL of the emulsion was administered at the tail base, followed by a booster injection of 0.1 mL on Day 7. Control rats received an equivalent volume of saline. Six days after the first immunization, arthritis severity was assessed by summing the swelling scores of all four paws. Based on these scores, rats were randomly assigned to eight groups (n = 8 per group): Control (0.5% CMC‐Na), CIA model (0.5% CMC‐Na), methotrexate (MTX, 0.5 mg/kg every 3 days), VTDB‐TE (0.84 g/kg), VTDB‐PE (0.12 g/kg), VTDB‐EtOAc (0.02 g/kg), VTDB‐nBuOH (0.07 g/kg), and VTDB‐W (0.57 g/kg). Treatments were administered orally for 28 consecutive days. Body weight, paw volume, ankle circumference, and arthritis index (AI; maximum score 8) were recorded every 4 days. On Day 28, rats were fasted overnight and then euthanized under isoflurane anesthesia (5% induction, 2% maintenance). Blood was collected from the abdominal aorta for serum biochemistry, and major organs were harvested for calculation of organ indices. Paw and joint tissues, as well as cecal contents, were collected for histopathological and microbiota analyses.

2.7. Histopathological Evaluation of Ankle Joints

Ankle joints were harvested from the same anatomical location in each rat and fixed in 4% paraformaldehyde. Three‐dimensional imaging of joint morphology and bone erosion was performed using a Quantum GX2 micro‐CT scanner (PerkinElmer, Hopkinton, MA, USA). Structural images were reconstructed and quantitatively analyzed using the Quantum GX2 analysis software. After micro‐CT scanning, the joints were decalcified in EDTA, embedded in paraffin, and sectioned for histological staining [32]. Hematoxylin and eosin (H&E) and Safranin O‐Fast Green stains were applied to assess pathological changes. A semi‐quantitative scoring system was used to evaluate synovial hyperplasia, inflammatory infiltration, and cartilage/bone destruction. Cartilage damage severity was further assessed using the Mankin scoring system [33].

2.8. Enzyme‐Linked Immunosorbent Assay (ELISA) and Serum Biochemistry

Serum levels of pro‐inflammatory cytokines, including TNF‐α, IL‐1β, IL‐6, and IL‐17, along with immunoglobulins (IgG and IgM) and bone metabolism markers (M‐CSF and GM‐CSF), were measured using commercial ELISA kits according to the manufacturers’ instructions. Absorbance was read at 450 nm, and concentrations were determined from standard curves. Concurrently, serum biochemical parameters, including ALT, AST, CREA, and BUN, were quantified using standard commercial kits.

2.9. Immunohistochemistry

Paraffin‐embedded tissue sections were deparaffinized in xylene and rehydrated through a graded ethanol series. Antigen retrieval was performed in citrate buffer (pH 6.0). Endogenous peroxidase activity was quenched with 3% hydrogen peroxide, and non‐specific binding was blocked with 5% goat serum at room temperature for 30 min. Sections were incubated overnight at 4°C with primary antibodies against TNF‐α (ABclonal, A0277, 1:100), IL‐6 (Affinity, DF6087, 1:100), MMP‐9 (ABclonal, A0289, 1:100), MMP‐13 (Abcam, ab219620, 1:500), IL‐1β (Bioss, bs‐0812R, 1:400), COX‐2 (ABclonal, A3560, 1:200), and RANKL (ABclonal, A13567, 1:100). After washing three times with PBS, the sections were incubated with HRP‐conjugated secondary antibodies at room temperature for 50 min. Immunoreactivity was detected using DAB substrate, and the sections were counterstained with hematoxylin. Finally, the sections were dehydrated through a graded ethanol series, mounted with mounting medium, and examined under a light microscope.

2.10. Immunofluorescence

Paraffin‐embedded sections were first deparaffinized and rehydrated. Then, antigen retrieval was performed using citrate buffer (pH 6.0). After blocking with 5% BSA for 1 h at room temperature, sections were incubated overnight at 4°C with primary antibodies: iNOS (Abcam, ab283655, 1:500), CD206 (CST, #24595, 1:200), and NF‐κB p65 (Abcam, ab16502, 1:400). After PBS washes, sections were incubated with Alexa Fluor 488‐conjugated goat anti‐rabbit IgG (Abcam, ab150077, 1:500) for 1 h at room temperature in the dark. Nuclei were counterstained with DAPI and mounted using antifade medium. Images were acquired using a confocal laser scanning microscope (FV3000, Olympus, Japan). Subsequently, five random fields per section were analyzed, and the positive staining area and mean fluorescence intensity were quantified using Image‐Pro Plus 6.0.

2.11. Western Blot Analysis

Synovial tissues from rat ankle joints were homogenized in SDS lysis buffer containing phosphatase inhibitors and PMSF. Protein concentrations were determined using a bicinchoninic acid (BCA) assay. Equal amounts of protein were denatured in reducing loading buffer, resolved by SDS–PAGE, and transferred onto polyvinylidene fluoride (PVDF) membranes. After blocking, membranes were incubated overnight at 4°C with primary antibodies against JAK2, p‐JAK2, STAT3, p‐STAT3, IKKα/β, IκBα, p‐IκBα, NF‐κB p65, p‐NF‐κB p65, PI3K, p‐PI3K, and Akt (all 1:1000). β‐actin (1:5000) was used as the loading control. After washing, membranes were incubated with horseradish peroxidase‐conjugated secondary antibodies, and immunoreactive bands were visualized using enhanced chemiluminescence and captured with a chemiluminescence imaging system. Band intensities were quantified using ImageJ software (version 1.53; National Institutes of Health, USA). Phosphorylated proteins were normalized to their corresponding total proteins where applicable, whereas total protein expression levels were normalized to β‐actin. All experiments were performed in triplicate.

2.12. DNA Extraction and 16S rRNA Gene Sequencing

Cecal contents were collected and stored at −80°C. Microbial DNA was extracted using the E.Z.N.A. Soil DNA Kit (Omega Biotek, USA). The V3–V4 region of the bacterial 16S rRNA gene was amplified with primers 338F and 806R on an ABI GeneAmp 9700 PCR thermocycler. PCR products were purified with the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, USA) and quantified using a Quantus Fluorometer. Sequencing was performed on the Illumina NovaSeq 6000 platform (2 × 250 bp; Novogene, Beijing, China). Raw reads were processed on the NovoMagic platform (https://magic‐plus.novogene.com). Alpha‐diversity (Chao1, Shannon) and beta‐diversity (PCoA, Bray–Curtis) were analyzed using QIIME2. Differential taxa were identified using LEfSe (p < 0.05).

2.13. Proteomics Analysis

Proteomic analysis was performed by Shanghai Biotree Biotech Co., Ltd. (Shanghai, China) using its standard workflow. Synovial tissues from the Control, Model, and VTDB‐nBuOH groups were homogenized and protein concentrations were measured by BCA assay. Equal amounts of protein were reduced, alkylated, digested with trypsin, desalted on C18 cartridges, and reconstituted for LC–MS/MS analysis. Peptides were separated on a PePSep C18 column (1.9 µm, 75 µm × 15 cm, Bruker, Germany) using a nano‐UPLC system coupled to a timsTOF Pro2 mass spectrometer (Bruker, Germany) with data‐independent acquisition (DIA‐PASEF). Raw data were processed with Spectronaut against the Rattus norvegicus UniProt database. Carbamidomethylation of cysteine was set as a fixed modification, and methionine oxidation and N‐terminal acetylation were set as variable modifications. Trypsin specificity allowed up to two missed cleavages. Peptide‐spectrum matches were filtered at a 1% false discovery rate, and differentially expressed proteins were defined by fold change ≤ 0.83 or ≥ 1.2 with p < 0.05 (Student's t‐test).

2.14. Statistical Analysis

All data are presented as mean ± standard deviation (SD). Statistical analyses and graphical visualizations were performed using GraphPad Prism 9.0 (GraphPad Software, USA). Data normality was assessed using the Shapiro–Wilk test before parametric analyses. Comparisons among multiple groups were performed using one‐way ANOVA followed by Tukey's multiple‐comparisons test, whereas comparisons between two groups were performed using an unpaired two‐tailed Student's t‐test. A p value < 0.05 was considered statistically significant.

3. Results

3.1. Chemical Profile of VTDB‐TE

In this study, the UHPLC‐Q‐Orbitrap MS/MS method was implemented to profile the chemical constituents of VTDB‐TE. Based on mass spectrometric information and database matching, a total of 224 natural small‐molecule compounds were putatively identified. The corresponding total ion chromatograms (TICs) are presented in Figure S1A,B, and detailed identification data are provided in Table S1.

3.2. Network Pharmacology Prediction of Potential Anti‐RA Targets and Pathways of VTDB‐TE

Absorption, distribution, metabolism, and excretion screening retained 204 compounds according to the predefined screening criteria. Target prediction yielded 1,311 potential compound‐associated targets, while public databases provided 7,028 RA‐related targets. Intersection analysis identified 755 overlapping targets between the predicted compound‐associated targets and RA‐related targets (Figure 1A), which were used to construct a protein‐protein interaction (PPI) network (Figure 1B).

FIGURE 1.

Network pharmacology analysis of VTDB‐TE associated with rheumatoid arthritis. (A) Venn diagram showing the overlap between predicted VTDB‐associated targets and RA‐related targets. (B) Network showing protein–protein interaction (PPI) network of overlapping targets. (C) Visualization showing the top 31 hub targets derived from the PPI network. (D) Gene Ontology (GO) enrichment analysis of overlapping targets. The top 10 significantly enriched terms in biological process (BP), cellular components (CC), and molecular functions (MF) are shown. Enriched terms mainly relate to immune regulation, inflammatory response, and cell signaling. (E) KEGG pathway enrichment analysis of overlapping targets. The top 10 enriched pathways are displayed. Dot size represents the number of target genes mapped to each pathway, and dot color indicated the statistical significance (Q value). Key RA‐associated genes are highlighted.

Core target clusters within this network were identified using the MCODE plugin in Cytoscape software, resulting in 31 core targets. Analysis of the core PPI network indicated that PIK3CA, PIK3CB, PIK3CG, PIK3R1, JAK2, and JAK1 exhibited relatively high network centrality (Figure 1C). To explore the potential biological functions of these targets, GO enrichment analysis was performed. This revealed predominant involvement in inflammation‐ and oxidative stress‐related biological processes, as well as molecular functions and cellular components associated with immune regulation (Figure 1D). KEGG pathway analysis further indicated significant enrichment in PI3K‐Akt, JAK‐STAT, chemokine, and cancer‐related signaling pathways (Figure 1E).

3.3. VTDB Ameliorates Symptoms in CIA Rats

We evaluated the therapeutic efficacy of VTDB total extract (VTDB‐TE) and its polarity‐based fractions (VTDB‐PE, VTDB‐EtOAc, VTDB‐nBuOH, VTDB‐W) against CIA (the experimental design and intervention protocol are shown in Figure 2A). The evaluation was based on measurements of paw volume, ankle circumference, arthritis scores, and body weight. Compared with the control group, CIA rats developed progressive joint swelling starting from Day 4 post‐immunization. From Day 12 to Day 24, all VTDB fractions except VTDB‐EtOAc consistently reduced paw swelling compared to CIA rats (Figure 2C,D; p < 0.05). VTDB‐TE showed effects comparable to MTX. Reductions in ankle circumference generally mirrored the changes in paw volume, supporting the anti‐edematous effect of VTDB‐TE and most of its fractions, with the exception of VTDB‐EtOAc (Figure 2F,G). Compared with the CIA model group, arthritis scores showed an overall downward trend after VTDB treatment, with VTDB‐TE and VTDB‐nBuOH exhibiting more pronounced improvement (Figure 2H–J). Importantly, VTDB‐TE did not adversely affect body weight gain. Rats treated with VTDB showed gradual recovery of body weight from Day 12 onward, and by Day 24, body weight was significantly higher than that in CIA rats (Figure 2L,M). Collectively, these results demonstrated that VTDB‐TE and most polarity‐based fractions suppressed joint swelling and inflammatory manifestations in CIA rats. Moreover, no obvious adverse effect on body weight gain was observed across the VTDB treatment groups.

FIGURE 2.

Therapeutic effects of VTDB and its solvent fractions on CIA rats. (A) Experimental design of the intervention protocol. (B) Time‐course of hind paw volume during the treatment period. (C–D) Hind paw volume on Days 12 and 24 of treatment. (E) Time‐course of ankle circumference during the treatment period. (F–G) Changes in ankle circumference on Days 12 and 24. (H) Arthritis index (AI) scores during the treatment period. (I–J) AI scores on Days 12 and 24. (K) Body weight trajectories during the treatment period. (L–M) Body weights on Days 12 and 24. Data are presented as mean ± SD, n = 8 per group. ### p < 0.001 versus Control, *p < 0.05, **p < 0.01, ***p < 0.001 versus Model. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, total extract of VTDB; VTDB‐PE, petroleum ether fraction of VTDB; VTDB‐EtOAc, ethyl acetate fraction of VTDB; VTDB‐nBuOH, n‐butanol fraction of VTDB; VTDB‐W, water fraction of VTDB; MTX, methotrexate.

3.4. VTDB Attenuates Joint Destruction and Bone Loss in Cia Rats

Joint morphology, micro‐CT, and histopathological analyses were performed to evaluate the protective effects of VTDB‐TE and its fractions separated based on polarity (VTDB‐PE, VTDB‐EtOAc, VTDB‐nBuOH, VTDB‐W) in CIA rats (Figure 3). CIA rats exhibited marked joint swelling, erythema, and deformity, whereas treatment with VTDB‐TE, VTDB‐PE, VTDB‐nBuOH, and VTDB‐W visibly improved joint appearance, with more evident improvement observed in the VTDB‐TE and VTDB‐nBuOH groups (Figure 3A). Micro‐CT analysis revealed severe subchondral bone erosion in CIA rats, characterized by irregular articular surfaces, trabecular disruption, narrowed joint spaces, and increased bone resorption (Figure 3B–C). Quantitative assessment showed decreased bone mineral density (BMD) (Figure 3H), bone volume fraction (BV/TV) (Figure 3I), trabecular thickness (Tb. Th) (Figure 3J), and trabecular number (Tb. N) (Figure 3K), and an elevated bone surface‐to‐volume ratio (BS/BV) (Figure 3L). VTDB treatment significantly mitigated these changes and preserved trabecular architecture, except for the VTDB‐EtOAc fraction (Figure 3H–L). Among the tested fractions, VTDB‐nBuOH showed relatively prominent overall protective effects (Figure 3H–O). Histopathological evaluation further confirmed these findings. H&E staining showed marked synovial hyperplasia and inflammatory cell infiltration in the ankle joints of CIA rats (Figure 3D,E), while Safranin O–Fast Green staining revealed cartilage structural damage, reduced matrix staining, and subchondral bone lesions (Figure 3F,G). VTDB‐TE, VTDB‐PE, VTDB‐nBuOH, and VTDB‐W alleviated synovial inflammation, preserved cartilage integrity, and reduced bone erosion to varying degrees, with more pronounced protection observed in the VTDB‐TE and VTDB‐nBuOH groups. Histological scoring further supported these findings, showing that VTDB‐TE exhibited efficacy comparable to methotrexate across synovial, cartilage, and bone‐related parameters, whereas VTDB‐EtOAc showed relatively weaker effects (Figure 3M–O). Overall, these findings demonstrate that VTDB and its active fractions substantially reduce joint inflammation and structural damage in CIA rats. Among the tested fractions, VTDB‐nBuOH showed more pronounced improvement in joint structural damage and inflammation. These effects likely result from modulation of inflammatory responses, cartilage protection, and preservation of bone remodeling homeostasis.

FIGURE 3.

Effects of VTDB and its solvent fractions on joint histopathology and damage in CIA rats. (A) Representative photographs of hind paw swelling. (B) Micro‐computed tomography (micro‐CT) images of ankle joints. (C) Enlarged views of micro‐CT scans highlighting joint morphology. (D, E) Hematoxylin and eosin (H&E) staining of ankle joint; (E) shows an enlarged view. (F, G) Safranin O–Fast Green staining of cartilage; (G) shows enlarged views. (H) Bone mineral density (BMD). (I) Bone volume fraction (BV/TV). (J) Trabecular thickness (Tb. Th). (K) Trabecular number (Tb. N). (L) Bone surface to volume ratio (BS/BV). (M) Bone destruction scores. (N) Inflammation scores. (O) Cartilage damage scores. Data are expressed as mean ± SD (n = 3 per group). ###p < 0.001 versus Control; *p < 0.05, **p < 0.01, ***p < 0.001 versus Model. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, total extract of VTDB; VTDB‐PE, petroleum ether fraction of VTDB; VTDB‐EtOAc, ethyl acetate fraction of VTDB; VTDB‐nBuOH, n‐butanol fraction of VTDB; VTDB‐W, water fraction of VTDB; MTX, methotrexate.

3.5. VTDB Improves Serum Biochemical Parameters and Modulates Systemic Immune and Inflammatory Responses in CIA Rats

CIA rats exhibited abnormalities in hepatorenal function‐related parameters, mainly characterized by an increased renal index and elevated serum ALT, BUN, and creatinine levels (Figure 4B–F). VTDB treatment improved these parameters to varying degrees, with more evident effects on ALT and creatinine levels (Figure 4C–F). In addition, CIA rats showed increased spleen and thymus indices (Figure 4G,H), accompanied by elevated serum IgG and IgM levels (Figure 4I,J), indicating persistent systemic immune activation. VTDB‐TE and VTDB‐PE showed relatively prominent regulatory effects on these immune‐related parameters, whereas VTDB‐EtOAc exhibited comparatively weaker activity (Figure 4G–J). Disease induction was further supported by elevated serum levels of RF (Figure 4K), C‐reactive protein (CRP; Figure 4L), and multiple pro‐inflammatory mediators, including TNF‐α (Figure 4M), IL‐1β (Figure 4N), IL‐6 (Figure 4O), IL‐17 (Figure 4P), HIF‐1α (Figure 4Q), IFN‐γ (Figure 4R), M‐CSF (Figure 4S), and GM‐CSF (Figure 4T). VTDB‐TE and its polarity‐based fractions reduced these inflammatory mediators to varying degrees, with VTDB‐TE and VTDB‐PE showing relatively prominent overall inhibitory effects, while VTDB‐EtOAc generally exhibited weaker activity (Figure 4M–T). Collectively, these results suggest that VTDB ameliorates renal function‐related abnormalities, attenuates systemic inflammation, and modulates immune responses in CIA rats, whereas VTDB‐EtOAc showed relatively weaker overall efficacy among the tested fractions.

FIGURE 4.

Effects of VTDB and its fractions on organ indices, biochemical parameters, immune function, and pro‐inflammatory cytokines in CIA rats.(A, B) Liver and kidney indices: Liver indices (A), kidney indices (B). (C–F) Serum biochemical parameters: alanine aminotransferase (ALT, C), aspartate aminotransferase (AST, D), blood urea nitrogen (BUN, E), and creatinine (Cr, F). (G, H) Spleen and thymus indices: Spleen indices (G), thymus indices (H); (I,J) Serum immunoglobulin levels: immunoglobulin G (IgG, I) and immunoglobulin M (IgM, J). (K, L) Serum rheumatoid factor (RF, K) and C‐reactive protein (CRP, L) levels. (M–T) Serum pro‐inflammatory cytokines: tumor necrosis factor‐α (TNF‐α, M), interleukin‐1β (IL‐1β, N), interleukin‐6 (IL‐6, O), interleukin‐17 (IL‐17, P), hypoxia‐inducible factor‐1α (HIF‐1α, Q), interferon‐γ (IFN‐γ, R), macrophage colony‐stimulating factor (M‐CSF, S), and granulocyte‐macrophage colony‐stimulating factor (GM‐CSF, T). Data are expressed as mean ± SD, n = 8 per group. *p < 0.05, **p < 0.01, ***p < 0.001 versus Model; #p < 0.05, ##p < 0.01, ###p < 0.001 versus Control. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, ethanol total extract; VTDB‐PE, petroleum ether fraction; VTDB‐EtOAc, ethyl acetate fraction; VTDB‐nBuOH, n‐butanol fraction; VTDB‐W, water fraction; MTX, methotrexate.

3.6. VTDB Regulates Macrophage Polarization and Reduces Synovial Inflammation in CIA Rats

Immunohistochemical staining of ankle joints confirmed elevated local inflammatory mediators in CIA rats. Compared with the control group, the model group showed markedly increased expression of TNF‐α (Figure 5A–I), IL‐1β (Figure 5B–J), IL‐6 (Figure 5C–K), COX‐2 (Figure 5D–L), RANKL (Figure 5E,M), MMP‐9 (Figure 5F–N), and MMP‐13 (Figure 5G–O). Treatment with VTDB‐TE and its polarity‐based fractions (VTDB‐PE, VTDB‐EtOAc, VTDB‐nBuOH, and VTDB‐W) reduced these inflammatory and joint destruction–related markers to different extents (Figure 5A–G,I–O), indicating effective suppression of synovial inflammation [34]. The persistence of synovitis in RA is strongly influenced by macrophage polarization, with M1 macrophages amplifying joint inflammation by releasing pro‐inflammatory cytokines and matrix metalloproteinases, while M2 macrophages promote the resolution of inflammation and tissue repair [35].

FIGURE 5.

VTDB and its fractions modulate synovial macrophage polarization to alleviate inflammation in CIA rats. (A–G) Immunohistochemical staining of synovial tissues showing inflammatory mediators: TNF‐α (A), IL‐1β (B), IL‐6 (C), cyclooxygenase‐2 (COX‐2, D), receptor activator of nuclear factor‐κB ligand (RANKL, E), matrix metalloproteinase‐9 (MMP‐9, F), and matrix metalloproteinase‐13 (MMP‐13, G). (H) Immunofluorescence images of macrophage polarization markers: inducible nitric oxide synthase (iNOS⁺, M1 marker, red) and CD206⁺ (M2 marker, green). (I–O) Quantitative analysis of positive staining areas for TNF‐α (I), IL‐1β (J), IL‐6 (K), COX‐2 (L), RANKL (M), MMP‐9 (N), and MMP‐13 (O). (P–Q) Semi‐quantitative analysis of fluorescence intensity for iNOS⁺ (P) and CD206⁺ (Q). Scale bar = 200 µm. Data are expressed as mean ± SD (n = 3). *p < 0.05, **p < 0.01, ***p < 0.001 versus Model; ##p < 0.01, ###p < 0.001 versus Control. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, total extract of VTDB; VTDB‐PE, petroleum ether fraction of VTDB; VTDB‐EtOAc, ethyl acetate fraction of VTDB; VTDB‐nBuOH, n‐butanol fraction of VTDB; VTDB‐W, water fraction of VTDB; MTX, methotrexate.

The observed reduction in inflammatory mediators following treatment with VTDB‐TE and its polarity‐based fractions suggested a shift in macrophage polarization. To further investigate this, immunofluorescence staining was performed. CIA rats displayed abundant iNOS‐positive M1 macrophages and reduced CD206‐positive M2 macrophages (Figure 5H,P,Q). Treatment with VTDB‐TE and its polarity‐based fractions significantly reversed this imbalance, decreasing M1 signals while enhancing M2 macrophage signals. The most pronounced effects were observed in the VTDB‐TE and VTDB‐nBuOH groups, whereas VTDB‐EtOAc exhibited comparatively weaker activity (Figure 5H,P,Q). Collectively, these findings indicate that VTDB‐TE and its polarity‐based fractions reduce the expression of pro‐inflammatory and joint destruction‐associated mediators in synovial tissues and are accompanied by changes in macrophage polarization markers, characterized by decreased M1‐associated iNOS signals and increased M2‐associated CD206 signals.

3.7. VTDB Attenuates Synovial Inflammation in CIA Rats, and Its Effects May Be Associated With Modulation of the JAK2/STAT3, NF‐κB, and PI3K/Akt Signaling Pathways

A schematic illustration of the signaling pathways associated with the effects of VTDB is shown in Figure 6A. Western blot analysis of ankle synovial tissues revealed that CIA rats exhibited increased p‐JAK2/JAK2, p‐STAT3/STAT3, IKKα/β, p‐IκBα/IκBα, p‐NF‐κB p65/NF‐κB p65, and p‐PI3K/PI3K levels, together with increased Akt expression, indicating activation of multiple pro‐inflammatory signaling pathways (Figure 6B–I). Treatment with VTDB‐TE and its polarity‐based fractions attenuated these changes to varying degrees, whereas VTDB‐EtOAc showed comparatively weaker inhibitory effects. Immunofluorescence staining further supported these findings, showing enhanced NF‐κB fluorescence in synovial tissues from CIA rats (Figure 6J,K). Treatment with VTDB‐TE and several polarity‐based fractions reduced NF‐κB fluorescence intensity, suggesting suppression of NF‐κB activation in synovial tissues. Collectively, these findings indicate that the attenuation of synovial inflammation by VTDB‐TE and its polarity‐based fractions in CIA rats is associated with modulation of the JAK2/STAT3, NF‐κB, and PI3K/Akt signaling pathways. Among the tested fractions, VTDB‐EtOAc showed the weakest modulatory effect.

FIGURE 6.

VTDB and its fractions inhibit synovial NF‐κB activation and modulate the JAK2/STAT3 and PI3K/Akt signaling pathways in CIA rats. (A) Schematic illustration of the signaling pathways associated with the effects of VTDB, including JAK2/STAT3, NF‐κB, and PI3K/Akt signaling. (B) Representative western blot bands of pathway‐related proteins in ankle synovial tissues. (C–J) Quantitative analysis of p‐JAK2/JAK2 (C), p‐STAT3/STAT3 (D), IKKα/β‐actin (E), p‐IκBα/IκBα (F), p‐NF‐κB p65/NF‐κB p65 (G), p‐PI3K/PI3K (H), Akt/β‐actin (I), and NF‐κB fluorescence intensity (J). (K) Representative immunofluorescence images of NF‐κB (red) with DAPI‐stained nuclei (blue) in synovial tissues. Data are expressed as mean ± SD (western blot, n = 8; immunofluorescence, n = 3). *p < 0.05, **p < 0.01, ***p < 0.001 versus Model; ##p < 0.01, ###p < 0.001 versus Control. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, total extract of VTDB; VTDB‐PE, petroleum ether fraction of VTDB; VTDB‐EtOAc, ethyl acetate fraction of VTDB; VTDB‐nBuOH, n‐butanol fraction of VTDB; VTDB‐W, water fraction of VTDB; MTX, methotrexate.

3.8. VTDB Modulates Gut Microbial Community Structure in CIA Rats

CIA rats exhibited abnormalities in gut microbiota α‐diversity, mainly characterized by reduced microbial richness, as reflected by significantly decreased Chao1 and Observed Features indices, while the Shannon index showed a downward trend (Figure 7A–C). VTDB treatment partially restored these α‐diversity indices, although most differences did not reach statistical significance. In addition, β‐diversity analysis revealed altered microbial community structure in CIA rats, with PCoA and NMDS plots showing a distinct clustering trend between the CIA and control groups (Figure 7D,E). Treatment with VTDB‐TE, VTDB‐PE, VTDB‐nBuOH, and VTDB‐W shifted the microbial profiles toward those of the control group, indicating partial restoration of gut microbial community structure. Collectively, these findings suggest that VTDB modulates gut microbial community structure in CIA rats, and this modulation may contribute to its anti‐inflammatory and immunoregulatory effects.

FIGURE 7.

Effects of VTDB and its fractions on gut microbiota diversity in CIA rats. (A–C) α‐diversity indices: Chao1 (A), Observed Features (B), Shannon index (C). (D, E) β‐diversity analysis using principal coordinates analysis (PCoA, D) and non‐metric multidimensional scaling (NMDS, E). Data are expressed as mean ± SD, n = 5. *p < 0.05 versus Control. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, total extract of VTDB; VTDB‐PE, petroleum ether fraction of VTDB; VTDB‐nBuOH, n‐butanol fraction of VTDB; VTDB‐W, water fraction of VTDB; MTX, methotrexate.

3.9. VTDB Modulates Gut Microbiota Composition at the Phylum and Genus Levels in CIA Rats

At the phylum level, Patescibacteria, Actinobacteriota, Bacteroidota, Firmicutes, and Proteobacteria were among the dominant taxa (Figure 8A). Hierarchical clustering showed that the control and VTDB‐nBuOH groups clustered closely, whereas MTX and VTDB‐PE formed another cluster, indicating distinct microbial modulation patterns among treatments (Figure 8A). Compared with the control group, CIA rats exhibited increased relative abundances of Patescibacteria (Figure 8B) and Actinobacteriota (Figure 8C), together with decreased abundances of Bacteroidota (Figure 8D) and Firmicutes (Figure 8E). VTDB‐TE and the tested fractions partially reversed these phylum‐level alterations to varying degrees, suggesting partial restoration of microbial homeostasis. At the genus level, the relative abundance profiles of the top 20 genera differed across groups (Figure 8F), and UPGMA clustering broadly reflected the phylum‐level patterns (Figure 8G). CIA rats were characterized by enrichment of Lachnospiraceae_NK4A136_group, Christensenellaceae_R‐7_group, Monoglobus, Methanosphaera, and Candidatus_Saccharimonas, along with depletion of Lactobacillus and Romboutsia (Figure 8H–N). VTDB‐TE and VTDB‐nBuOH significantly increased Lactobacillus abundance (Figure 8H), while several treatment groups also showed a trend toward recovery in Romboutsia abundance (Figure 8I). In addition, VTDB treatment reduced the abundances of Lachnospiraceae_NK4A136_group, Christensenellaceae_R‐7_group, Monoglobus, Methanosphaera, and Candidatus_Saccharimonas to varying degrees (Figure 8J–N). LEfSe and cladogram analyses further identified group‐associated microbial taxa across the different treatments (Figure 8O,P). Collectively, these findings suggest that VTDB reshapes gut microbial composition in CIA rats at both the phylum and genus levels, with VTDB‐nBuOH showing relatively prominent modulatory effects among the tested fractions.

FIGURE 8.

VTDB and its fractions modulate gut microbial composition in CIA rats (n = 5 per group). (A) Heatmap of the top 10 most abundant bacterial phyla. (B–E) Relative abundances of significantly altered phyla: Patescibacteria (B), Actinobacteriota (C), Bacteroidota (D), and Firmicutes (E). (F) Relative abundance of the top 20 abundant genera; (G) UPGMA clustering tree based on genus‐level profiles. (H–N) Relative abundances of key genera significantly affected by VTDB: Lactobacillus (H), Romboutsia (I), Lachnospiraceae_NK4A136_group (J), Christensenellaceae_R‐7_group (K), Monoglobus (L), Methanosphaera (M), and Candidatus_Saccharimonas(N). (O) LDA score plot showing taxa with significant differences identified by LEfSe analysis. (P) LEfSe‐generated cladogram from Kingdom to Species; node size represents relative abundance, and color indicates the enriched group; yellow nodes indicate taxa without significant differences. Data are expressed as mean ± SD (n = 5 per group). #p < 0.05, ##p < 0.01, ###p < 0.001 versus Control; *p < 0.05, **p < 0.01, ***p < 0.001 versus Model. Abbreviations: VTDB, V. thibetica de Boiss.; VTDB‐TE, total extract of VTDB; VTDB‐PE, petroleum ether fraction of VTDB; VTDB‐nBuOH, n‐butanol fraction of VTDB; VTDB‐W, water fraction of VTDB; MTX, methotrexate.

3.10. VTDB‐nBuOH Partially Restores the Altered Synovial Proteomic Profile in CIA Rats

To further explore the potential mechanisms underlying the effects of the active fraction VTDB‐nBuOH in rheumatoid arthritis, label‐free untargeted proteomic profiling was performed on synovial tissues from CIA rats. PCA showed a separation trend among the Control, Model, and VTDB‐nBuOH groups, with the VTDB‐nBuOH group located closer to the Control group and farther from the Model group, suggesting that VTDB‐nBuOH partially corrected the abnormal proteomic profile induced by CIA (Figure 9A).

FIGURE 9.

Proteomic profiling of VTDB‐nBuOH in ankle joints of CIA rats. (A) Principal component analysis (PCA) score plot illustrating overall proteomic variation; (B) Number of differentially expressed proteins (DEPs) across Control, Model, and VTDB‐nBuOH groups. (C) Venn diagram showing shared and unique DEPs among groups; (D–F) Volcano plots of DEPs between Model and Control (D), between VTDB‐nBuOH and Control (E), and between VTDB‐nBuOH and Model (F), red and blue dots indicate upregulated and downregulated proteins, respectively. (G–P) Representative DEPs between Control versus Model and Model versus VTDB‐nBuOH groups, including A0A0G2JWT4 (G, L), A0A8I5Y6E8 (H, M), A0A8I5ZYJ1 (I, N); A6HZ21 (J, O) and D3ZVM5 (K, P). (Q) Gene Ontology (GO) enrichment analysis of DEPs between Model and VTDB‐nBuOH groups, categorized into biological process, cellular component, and molecular function; (R) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEPs between Model and VTDB‐nBuOH groups; dot size represents the number of mapped DEPs, and color indicates statistical significance (p value); Data are presented as mean ± SD, n = 3 per group). Abbreviations: VTDB‐nBuOH, n‐butanol fraction of V. thibetica de Boiss.

Differential expression analysis further supported this finding. Consistent with the Control_vs_Model comparison, a large number of DEPs were also identified in the Model_vs_VTDB‐nBuOH comparison. Specifically, 538 proteins were upregulated and 365 were downregulated in the Control_vs_Model comparison, whereas 495 proteins were upregulated and 576 were downregulated in the Model_vs_VTDB‐nBuOH comparison (Figure 9B,D–F), indicating marked remodeling of the abnormal synovial proteomic profile after VTDB‐nBuOH treatment. Venn analysis further identified 12 DEPs common to all three pairwise comparisons (Figure 9C), suggesting that these proteins may represent key candidate molecules involved in the reversal of CIA‐associated proteomic abnormalities by VTDB‐nBuOH. Representative DEPs further supported this conclusion: compared with the Control group, A0A0G2JWT4, A0A8I5Y6E8, A6HZ21, and D3ZVM5 were downregulated in the Model group, whereas A0A8I5ZYJ1 was upregulated; these alterations were partially reversed after VTDB‐nBuOH treatment (Figure 9G–P).

To clarify the biological significance of these proteomic changes, GO and KEGG enrichment analyses were further performed on DEPs in the Model_vs_VTDB‐nBuOH comparison. These DEPs were mainly associated with metabolic processes, cytoplasmic and extracellular components, as well as protein‐ and drug‐binding functions (Figure 9Q), and were significantly enriched in ECM–receptor interaction, proteasome, focal adhesion, and PI3K–Akt signaling pathways (Figure 9R). Collectively, these results indicate that VTDB‐nBuOH partially restores the altered synovial proteomic profile in CIA rats and may exert its therapeutic effects through regulation of multiple pathways, including PI3K–Akt signaling.

4. Discussion

RA is a chronic autoimmune disease characterized by persistent synovial inflammation, pannus formation, and progressive joint destruction. The CIA rat model mimics key clinical and histopathological features of RA [36]. In this study, CIA rats exhibited paw swelling, synovial hyperplasia, cartilage erosion, and elevated serum RF and CRP, confirming successful model establishment [31]. Treatment with VTDB total extract (VTDB‐TE) and its polarity‐based fractions reduced paw swelling, improved synovial histology, lowered serum pro‐inflammatory cytokines (TNF‐α, IL‐1β, IL‐6, IL‐17, HIF‐1α, IFN‐γ), immunoglobulins (IgG, IgM), and hematopoietic growth factors (M‐CSF, GM‐CSF), and improved several hepatorenal function‐related parameters, particularly changes in the renal index and serum ALT and creatinine levels. Among the fractions, VTDB‐nBuOH exhibited the most pronounced therapeutic effects, whereas VTDB‐EtOAc showed limited activity. These results are consistent with previous studies reporting the anti‐inflammatory and immunomodulatory effects of VTDB.

Synovial inflammation in RA is driven by innate and adaptive immune cells, with M1 macrophages producing TNF‐α, IL‐1β, IL‐6, and iNOS, amplifying tissue damage [37, 38]. Matrix metalloproteinases (MMP‐9, MMP‐13) and RANKL promote osteoclast differentiation and cartilage/bone erosion. VTDB fractions markedly attenuated synovial inflammation, reducing TNF‐α, IL‐1β, IL‐6, and COX‐2 levels, as well as MMP‐9, MMP‐13, and RANKL expression. iNOS fluorescence decreased and CD206 fluorescence increased in several treatment groups, suggesting an association with a shift toward a more anti‐inflammatory macrophage phenotype. These findings indicate that VTDB modulates the pro‐inflammatory synovial environment and preserves joint structure. Similar effects have been reported in RA models [39]. The observed effects may be associated with interconnected signaling pathways that play a central role in RA pathogenesis. Pro‐inflammatory cytokines activate JAK2/STAT3, PI3K/Akt, and NF‐κB pathways, driving osteoclast differentiation and FLS proliferation [40]. Network pharmacology screening retained 204 candidate compounds and predicted 755 overlapping targets between compound‐associated and RA‐related target sets, with potential hub targets including PIK3CA/B/G, PIK3R1, and JAK1/2. KEGG enrichment analysis further suggested potential involvement of the PI3K‐Akt and JAK‐STAT signaling pathways.

Subsequent experimental findings were broadly consistent with these pathway predictions. VTDB‐nBuOH was associated with reduced phosphorylation of JAK2, STAT3, IκBα, NF‐κB p65, and PI3K, together with decreased IKKα and Akt expression, suggesting modulation of the NF‐κB, JAK2/STAT3, and PI3K/Akt‐related signaling pathways, which are closely associated with RA pathogenesis. Immunofluorescence staining further supported these findings, showing reduced NF‐κB fluorescence intensity in joint tissues after VTDB‐nBuOH treatment, consistent with attenuation of synovial inflammatory signaling. Among the tested fractions, VTDB‐nBuOH exhibited the most prominent modulatory effects on the aforementioned signaling pathways. In contrast, VTDB‐EtOAc showed comparatively weaker activity and was not prioritized in subsequent mechanistic analyses.

Gut microbiota dysbiosis has been associated with RA pathogenesis in the context of systemic inflammation [41, 42, 43]. Treatment with VTDB‐TE and its polarity‐based fractions (VTDB‐PE, VTDB‐nBuOH, VTDB‐W) partially restored gut microbial composition, with partial normalization of phylum‐ and genus‐level microbial alterations. Among the fractions, VTDB‐nBuOH showed relatively prominent modulatory effects on gut microbial composition. At the genus level, treatment enriched certain genera associated with gut microbial homeostasis, including Lactobacillus and Romboutsia, while reducing several taxa linked to CIA‐associated microbial alterations, such as Lachnospiraceae_NK4A136_group, Christensenellaceae_R‐7_group, Monoglobus, and Methanosphaera. These findings suggest a potential relationship between VTDB‐associated alterations in gut microbial composition and the attenuation of RA‐related inflammation, while the directionality and mechanistic contribution of these microbial changes remain to be further clarified [44, 45, 46, 47].

Proteomic analysis provides complementary system‐level information for interpreting the effects of VTDB‐nBuOH. In this study, this analysis showed that VTDB‐nBuOH partially restored the altered synovial proteomic profile in CIA rats. Venn analysis further identified 12 DEPs common to all three pairwise comparisons, suggesting that these proteins may represent key candidate molecules involved in the reversal of CIA‐associated proteomic abnormalities. Notably, KEGG enrichment analysis identified the PI3K–Akt signaling pathway as one of the significantly enriched pathways. This finding was consistent with the Western blot results showing treatment‐associated changes in p‐PI3K/PI3K and Akt expression, providing experimental support for this key proteomic finding.

In conclusion, VTDB and its polarity‐based fractions (VTDB‐PE, VTDB‐EtOAc, VTDB‐nBuOH, VTDB‐W) exert anti‐inflammatory and joint‐protective effects in CIA rats, accompanied by changes in macrophage polarization markers, modulation of JAK2/STAT3, NF‐κB, and PI3K/Akt‐related signaling, and partial restoration of gut microbial composition. Among these, VTDB‐nBuOH conferred the most pronounced therapeutic benefits, effectively alleviating inflammation, attenuating joint pathology, and partially restoring the altered synovial proteomic profile in CIA rats (Figure 10).

FIGURE 10.

Schematic diagram of Vicatia thibetica de Boiss.: in vivo anti‐inflammatory effects and associated multi‐pathway modulation in rheumatoid arthritis. The schematic was prepared using BioRender.com and Adobe Illustrator 2022 (version 26.0; Adobe Inc., San Jose, CA, USA).

Several limitations of the present study should be acknowledged. Although UHPLC‐Q‐Orbitrap MS/MS was used to characterize the overall chemical profile of VTDB‐TE, representative chemical markers were not quantitatively determined, and therefore further chemical standardization of VTDB preparations is warranted. In addition, because the present study was primarily designed to compare the pharmacological activities of VTDB‐TE and its polarity‐based fractions on an equivalent crude‐drug basis and to identify the major active fraction, dose‐response relationships of the individual fractions were not systematically evaluated. Moreover, the mechanistic findings were mainly based on in vivo observations and pathway‐associated changes, and the precise causal relationships and direct molecular targets remain to be established. Future studies should therefore establish validated marker‐based quantitative methods, further isolate and characterize the chemical constituents of the identified active fraction, systematically evaluate the dose‐response relationships of the active fraction and its representative bioactive constituents, and perform targeted experimental validation to clarify the underlying causal mechanisms and direct molecular targets.

The data generated in the present study are included in the figures of this article and Table S1 in the supplementary file.

Author Contributions

Mo‐Zi‐Li Adu: data curation, project administration, writing – original draft. Wei Jiang: methodology. Min Li: conceptualization. Bo‐Wei Xia: investigation. En Yuan: formal analysis. Yue‐Zhi Tan: validation. Wu‐Xin Yang: visualization, writing – review and editing. Guo‐Yue Zhong: supervision, funding acquisition. Qin‐Ge Ma: resources, writing –review and editing. Rong‐Rui Wei: supervision, writing – review and editing. All authors discussed and approved the final manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (82360682, 82360825), Hubei Provincial Natural Science Foundation (2026AFB780), Science and Technology Research Program of Hubei Provincial Department of Education (D20251703; B2025058), Doctoral Research Startup Fund of Wuhan Polytechnic University (2026RZ043, 2026RZ050), National and Provincial College Students' Innovation Training Program Projects of 2026 (202610496009X, S202610496045X), and Jiangxi Provincial Natural Science Foundation (20242BAB26172).

Ethics Statement

All experimental procedures involving animals were conducted in accordance with the Guide for the Care and Use of Laboratory Animals and were approved by the Animal Care and Use Committee of Jiangxi University of Chinese Medicine (approval no. JZLLSC20220867).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File: cbdv71805‐sup‐0001‐SuppMat.docx.

Data Availability Statement

The data presented in this study are available in the article and its supplementary information.