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Effectiveness of low-intensity exercise in mitigating active arthritis exacerbation in a mouse rheumatoid-arthritis model

ABSTRACT: Objective To investigate the effects of low-intensity exercise on active arthritis in a SKG mouse model of human rheumatoid arthritis (RA) pathology. Methods Twenty-four female SKG mice were divided into three groups: sedentary (control), AR (induced arthritis), and AREx (induced arthritis plus low-intensity exercise). Arthritis was induced via intraperitoneal administration of mannan. After a 2-week inflammation period, low-intensity treadmill exercise was performed only in the AREx group. Arthritis was assessed weekly during the rearing period. After 4 weeks of exercise, histological and bone morphometric analyses of the right ankle joint were performed. A histological analysis of the gastrocnemius muscle was also performed. Bulk mRNA sequencing was conducted on the left synovial membrane-fat pad (SM-FP) complex. Results The synovitis score showed no change; however, the arthritis score was significantly lower in the AREx group than in the AR group (p<0.05), indicating that low-intensity exercise suppressed arthritis exacerbation. The calcaneal and talar bone volumes decreased in the AR group, whereas the AREx group showed no significant change. In the SM-FP complex tissue, the gene expression of inflammatory cytokines decreased in the AREx group compared with the AR group, particularly the suppression of IL6/Jak/Stat3. Immunohistochemical analysis revealed significantly decreased expression of pro-inflammatory cytokines and increased expression of anti-inflammatory cytokines in the synovium of the AREx group compared with the AR group (p<0.05). Conclusion Low-intensity exercise therapy for active RA showed anti-inflammatory and suppressive effects on arthritis exacerbation in SKG mice, a mouse model of human RA pathology.

ORGANISM(S): Mus musculus

PROVIDER: GSE271058 | GEO | 2025/01/31

REPOSITORIES: GEO

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Project description:Purpose: The goals of this study were to study the transcriptome and TCR repertoire of naive CD4 T cells before the induction of arthritis in the SKG and wild-type (WT) mouse with eGFP-Nur77 as a reporter of antigen stimulation (SKGNur and WTNur). Methods: Bulk RNA sequencing was used to generate the mRNA profiles for the top 10% and bottom 10% of GFP expressing cells from three SKGNur and three WTNur BALB/c mice resulting in 12 samples overall (3 WT Low, 3 WT High, 3 SKG Low, 3 SKG High) using the Truseq Stranded mRNA kit followed by sequencing on a HiSeq 2500 sequencer. The sequence reads that passed quality filters were aligned with STAR and then analyzed with DESeq2. Results: We mapped about 38,000,000 million reads per sample to the mouse genome (mm10). The differential expression pairwise comparisons (WT Low v WT High, WT Low v SKG Low, SKG Low v SKG High, and WT High v SKG High) generated a collection of 991 differentially expressed genes with log2FC >1 and Benjamini-Hochberg adjusted p value < 0.05. Hierarchical clustering of differentially expressed genes uncovered six modules of gene expression which highlighted heterogeneity within the naive CD4 T cell compartment and transcriptional signatures associated with the SKG High samples. Methods: Single cell RNA gene expression and TCR sequencing libraries were generated for the top 10% and bottom 10% of GFP expressing cells from two SKGNur and two WTNur BALB/c mice resulting in 8 samples overall (2 WT Low, 2 WT High, 2 SKG Low, 2 SKG High) using the 5' 10x single cell 5"+V(D)J v1 kit and were sequenced on a NovaSeq 6000 sequencer. The reads were aligned using cellranger and analyzed using a combination of single cell tools including scanpy and scvelo. Results: We mapped about 785,000,000 sequence reads and about 379,000,000 sequence reads per sample for the gene expression and TCR libraries to the mouse genome (build mm10 with the addition of the eGFP transcript) and TCR reference (vdj GRCm38 v 3.1.0), respectively, using cellranger. We identified 31,054 transcripts across 101,869 cells and recovered paired TRA and TRB chains from more than 80% of cells. After filtering cells and genes by our quality control metrics, we identified 1119 highly variable genes which were used for PCA analysis to create a nearest neighbors graph for leiden clustering and UMAP projection. We identified 13 clusters that we collapsed into 9 cell sub-types. Within the cluster (T.4_Nr4a1) exclusively expressing our marker gene of interest, Nr4a1, we found that SKG High cells upregulated TCR signaling genes despite their impaired impaired TCR signaling ability due to a Zap70 mutation. Within the T.4Nr4a1 cluster we found two states of acute to chronic TCR signaling, marked by Egr2 and Tnfrsf9, and we used trajectory inference to uncover a continuum of cell states with these acute to chronic TCR signaling states as the endpoints. Interestingly, SKG High cells in the T.4 Nr4a1 cluster seemed arrested in the earlier more acute TCR signaling state suggesting they are unable to appropriately fully upregulate the chronic TCR signaling and more anergic cell state. We also uncovered TRBV restriction within the SKG High samples and specifically within the SKG High cells within the T.4 Nr4a1 cluster that seems to be driven by a failure of negative selection by endogenously expressed super antigens from MMTVs present in the BALB/c mouse. Thus the naive CD4 T cell compartment within the SKG High cells are poised to enter into a reactive immune response via both a unique transcriptomic and TCR repertoire which may underlie the mechanism of high arthritogenic potential of these cells.

Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000550. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis - Age Dependant This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000549. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Effectiveness of low-intensity exercise in mitigating active arthritis exacerbation in a mouse rheumatoid-arthritis model

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