The Immune Cell Landscape in Different Anatomical Structures of Knee in Osteoarthritis: A Gene Expression-Based Study

Innate Immunity and Synovitis: Key Players in Osteoarthritis Progression

Osteoarthritis (OA) is a chronic progressive disease of the joint. Although representing the most frequent cause of disability in the elderly, OA remains partly obscure in its pathogenic mechanisms and is still the orphan of resolutive therapies. The concept of what was once considered a "wear and tear" of articular cartilage is now that of an inflammation-related disease that affects over time the whole joint. The attention is increasingly focused on the synovium. Even from the earliest clinical stages, synovial inflammation (or synovitis) is a crucial factor involved in OA progression and a major player in pain onset. The release of inflammatory molecules in the synovium mediates disease progression and worsening of clinical features. The activation of synovial tissue-resident cells recalls innate immunity cells from the bloodstream, creating a proinflammatory milieu that fuels and maintains a damaging condition of low-grade inflammation in the joint. In such a context, cellular and molecular inflammatory behaviors in the synovium could be the primum movens of the structural and functional alterations of the whole joint. This paper focuses on and discusses the involvement of innate immunity cells in synovitis and their role in the progression of OA.

Gene expression and immune infiltration analysis comparing lesioned and preserved subchondral bone in osteoarthritis

Background

Osteoarthritis (OA) is a degenerative disease requiring additional research. This study compared gene expression and immune infiltration between lesioned and preserved subchondral bone. The results were validated using multiple tissue datasets and experiments.

Methods

Differentially expressed genes (DEGs) between the lesioned and preserved tibial plateaus of OA patients were identified in the GSE51588 dataset. Moreover, functional annotation and protein-protein interaction (PPI) network analyses were performed on the lesioned and preserved sides to explore potential therapeutic targets in OA subchondral bones. In addition, multiple tissues were used to screen coexpressed genes, and the expression levels of identified candidate DEGs in OA were measured by quantitative real-time polymerase chain reaction. Finally, an immune infiltration analysis was conducted.

Results

A total of 1,010 DEGs were identified, 423 upregulated and 587 downregulated. The biological process (BP) terms enriched in the upregulated genes included "skeletal system development", "sister chromatid cohesion", and "ossification". Pathways were enriched in "Wnt signaling pathway" and "proteoglycans in cancer". The BP terms enriched in the downregulated genes included "inflammatory response", "xenobiotic metabolic process", and "positive regulation of inflammatory response". The enriched pathways included "neuroactive ligand-receptor interaction" and "AMP-activated protein kinase signaling". JUN, tumor necrosis factor α, and interleukin-1β were the hub genes in the PPI network. Collagen XI A1 and leucine-rich repeat-containing 15 were screened from multiple datasets and experimentally validated. Immune infiltration analyses showed fewer infiltrating adipocytes and endothelial cells in the lesioned versus preserved samples.

Conclusion

Our findings provide valuable information for future studies on the pathogenic mechanism of OA and potential therapeutic and diagnostic targets.

Bioinformatics Analysis and Experimental Validation of Mitochondrial Autophagy Genes in Knee Osteoarthritis

Background

Mitochondrial autophagy is closely related to the pathogenesis of osteoarthritis, In order to explore the role of mitochondrial autophagy related genes in knee osteoarthritis (KOA) and its molecular mechanism.

Methods

KOA-related transcriptome data were extracted from the Gene Expression Omnibus (GEO) database. Differentially expressed mitochondrial autophagy gene (DEMGs) were screened in patients with KOA by differential expression analysis. The STRING website was used to construct a protein-protein interaction (PPI) network among DEMGs. Molecular complex detection (MCODE) method in Cytoscape software was performed to identify hub DEMGs. Support vector machine recursive feature elimination (SVM-RFE) method was used to construct the hub DEMG diagnosis model. Genes with diagnostic value were identified as biomarkers by plotting receiver operating characteristic (ROC) curves and Expression validation. CIBERSORT algorithm was used to calculate the proportion of 22 immune cells in each sample in the GSE114007 dataset. Finally, biomarker expression was verified by qPCR.

Results

A total of 15 DEMGs were obtained and enrichment analyses showed that these DEMG strains were mainly enriched in the mitophagy-animal, shigellosis, autophagy-animal and FoxO signal pathways. The PPI network unveiled 13 DEMGs with interactions. In addition, 8 hub DEMGs (ULK1, CALCOCO2, MAP1LC3B, BNIP3L, GABARAPL1, BNIP3, FKBP8 and FOXO3) were obtained for KOA. And 5 model DEMGs (BNIP3L, BNIP3, MAP1LC3B, ULK1 and FOXO3) were screened. The ROC curves revealed that BNIP3 and FOXO3 has strong diagnostic value in these models of DEMG. Immune-infiltration and correlation analysis showed that BNIP3 and FOXO3 were significantly correlated with three different immune cells, including primary B cells, M0 macrophage and M2 macrophage. The cartilage tissue samples qPCR verification results show that FOXO3 and BNIP3 were all down-regulated in KOA (p < 0.01), and the validation results are consistent with the above analysis.

Conclusion

BNIP3 and FOXO3 have been identified as biomarkers for the diagnosis of KOA, which might supply a new insight for the pathogenesis and treatment of KOA.

Targeting an inflammation-amplifying cell population can attenuate osteoarthritis-associated pain

BACKGROUND

Understanding of pain in osteoarthritis, its genesis, and perception is still in its early stages. Identification of precise ligand-receptor pairs that transduce pain and the cells and tissues in which they reside will elucidate new therapeutic approaches for pain management. Our recent studies had identified an inflammation-amplifying (Inf-A) cell population that is expanded in human OA cartilage and is distinctive in the expression of both IL1R1 and TNF-R2 receptors and active Jnk signaling cascade.

METHODS

In this study, we have tested the function of the cartilage-resident IL1R1+TNF-R2+ Inf-A cells in OA. We have identified that the IL1R1+TNF-R2+ Inf-A cells expand in aged mice as well as after anterior cruciate ligament tear upon tibia loading and OA initiation in mice. We targeted and modulated the Jnk signaling cascade in InfA through competitive inhibition of Jnk signaling in mice and human OA explants and tested the effects on joint structure and gait in mice.

RESULTS

Modulation of Jnk signaling led to attenuation of inflammatory cytokines CCL2 and CCL7 without showing any structural improvements in the joint architecture. Interestingly, Jnk inhibition and lowered CCL2 and 7 are sufficient to significantly improve the gait parameters in treated PTOA mice demonstrating reduced OA-associated pain. Consistent with the mice data, treatment with JNK inhibitor did not improve human OA cartilage explants.

CONCLUSION

These studies demonstrate that Inf-A, an articular-cartilage resident cell population, contributes to pain in OA via secretion of CCL2 and 7 and can be targeted via inhibition of Jnk signaling.

Classification of distinct osteoarthritis subtypes with different knee joint tissues by gene expression profiles

Aims

Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA.

Methods

First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to verify the effectiveness of markers.

Results

C1 subtype is mainly concentrated in the development of skeletal muscle organs, C2 lies in metabolic process and immune response, and C3 in pyroptosis and cell death process. Therefore, we divided OA into three subtypes: bone remodelling subtype (C1), immune metabolism subtype (C2), and cartilage degradation subtype (C3). The number of macrophage M0 and activated mast cells of C2 subtype was significantly higher than those of the other two subtypes. COL2A1 has significant differences in different subtypes. The expression of COL2A1 is related to age, and trafficking protein particle complex subunit 2 is related to the sex of OA patients.

Conclusion

This study linked different tissues with gene expression profiles, revealing different molecular subtypes of patients with knee OA. The relationship between clinical characteristics and OA-related genes was also studied, which provides a new concept for the diagnosis and treatment of OA.

Identification of cuproptosis-related subtypes, characterization of immune microenvironment infiltration, and development of a prognosis model for osteoarthritis

Background

Osteoarthritis (OA) is a prevalent chronic joint disease with an obscure underlying molecular signature. Cuproptosis plays a crucial role in various biological processes. However, the association between cuproptosis-mediated immune infifiltration and OA progression remains unexplored. Therefore, this study elucidates the pathological process and potential mechanisms underlying cuproptosis in OA by constructing a columnar line graph model and performing consensus clustering analysis.

Methods

Gene expression profifile datasets GSE12021, GSE32317, GSE55235, and GSE55457 of OA were obtained from the comprehensive gene expression database. Cuproptosis signature genes were screened by random forest (RF) and support vector machine (SVM). A nomogram was developed based on cuproptosis signature genes. A consensus clustering was used to distinguish OA patients into different cuproptosis patterns. To quantify the cuproptosis pattern, a principal component analysis was developed to generate the cuproptosis score for each sample. Single-sample gene set enrichment analysis (ssGSEA) was used to provide the abundance of immune cells in each sample and the relationship between these significant cuproptosis signature genes and immune cells.To quantify the cuproptosis pattern, a principal component analysis technique was developed to generate the cuproptosis score for each sample. Cuproptosis-related genes were extracted and subjected to differential expression analysis to construct a disease prediction model and confifirmed by RT-qPCR.

Results

Seven cuproptosis signature genes were screened (DBT, LIPT1, GLS, PDHB, FDX1, DLAT, and PDHA1) to predict the risk of OA disease. A column line graph model was developed based on these seven cuproptosis signature genes, which may assist patients based on decision curve analysis. A consensus clustering method was used to distinguish patients with disorder into two cuproptosis patterns (clusters A and B). To quantify the cuproptosis pattern, a principal component analysis technique was developed to generate the cuproptosis score for each sample. Furthermore, the OA characteristics of patients in cluster A were associated with the inflflammatory factors IL-1b, IL-17, IL-21, and IL-22, suggesting that the cuproptosis signature genes play a vital role in the development of OA.

Discussion

In this study, a risk prediction model based on cuproptosis signature genes was established for the fifirst time, and accurately predicted OA risk. In addition, patients with OA were classifified into two cuproptosis molecule subtypes (clusters A and B); cluster A was highly associated with Th17 immune responses, with higher IL-1b, IL-17, and IL-21 IL-22 expression levels, while cluster B had a higher correlation with cuproptosis. Our analysis will help facilitate future research related cuproptosis-associated OA immunotherapy. However, the specifific mechanisms remain to be elucidated.

Activated mast cells in periprosthetic joint infection-associated tissue

Background

Periprosthetic joint infection (PJI) is a devastating complication of total joint arthroplasty surgery. Increased densities of activated mast cells have been predicted to be present in PJI compared to non-infectious arthroplasty failure based on analysis of transcriptomic data, but their presence in PJI-associated periprosthetic tissues has not been visually confirmed.

Objective

This preliminary study investigated the presence and activation status of mast cells in periprosthetic tissues associated with PJI.

Methods

Periprosthetic tissues from five PJI cases and three arthroplasty failures due to instability and one due to stiffness were immunohistochemically stained using tryptase and microscopically evaluated to enumerate mast cells and evaluate overall activation status within tissue samples. Mast cell activation was evidenced by the release of tryptase into the extracellular space surrounding mast cells.

Results

Mast cells were found in all samples, with average cellular densities of 22 and 26 cells/mm2 tissue in PJI and uninfected samples, respectively (p, 0.6610). Apparent mast cell activation and degranulation was readily observed throughout each of the five PJI samples studied, but not in any of the uninfected samples studied.

Conclusion

While preliminary, these findings provide evidence for a role of mast cells in the immune response in PJI. Additional investigation of the role of mast cells during arthroplasty failure is warranted, providing a better understanding of underlying biology and informing potential diagnostic and treatment targets.

Revealing the immune cell subtype reconstitution profile in patients from the CLARITY study using deconvolution algorithms after cladribine tablets treatment

Immune Cell Deconvolution methods utilizing gene expression profiling to quantify immune cells in tissues and blood are an appealing alternative to flow cytometry. Our objective was to investigate the applicability of deconvolution approaches in clinical trial settings to better investigate the mode of action of drugs for autoimmune diseases. Popular deconvolution methods CIBERSORT and xCell were validated using gene expression from the publicly available GSE93777 dataset that has comprehensive matching flow cytometry. As shown in the online tool, ~ 50% of signatures show strong correlation (r > 0.5) with the remainder showing moderate correlation, or in a few cases, no correlation. Deconvolution methods were then applied to gene expression data from the phase III CLARITY study (NCT00213135) to evaluate the immune cell profile of relapsing multiple sclerosis patients treated with cladribine tablets. At 96 weeks after treatment, deconvolution scores showed the following changes vs placebo: naïve, mature, memory CD4⁺ and CD8⁺ T cells, non-class switched, and class switched memory B cells and plasmablasts were significantly reduced, naïve B cells and M2 macrophages were more abundant. Results confirm previously described changes in immune cell composition following cladribine tablets treatment and reveal immune homeostasis of pro- vs anti-inflammatory immune cell subtypes, potentially supporting long-term efficacy.

Comprehensive bulk and single-cell transcriptome profiling give useful insights into the characteristics of osteoarthritis associated synovial macrophages

Background

Osteoarthritis (OA) is a common chronic joint disease, but the association between molecular and cellular events and the pathogenic process of OA remains unclear.

Objective

The study aimed to identify key molecular and cellular events in the processes of immune infiltration of the synovium in OA and to provide potential diagnostic and therapeutic targets.

Methods

To identify the common differential expression genes and function analysis in OA, we compared the expression between normal and OA samples and analyzed the protein-protein interaction (PPI). Additionally, immune infiltration analysis was used to explore the differences in common immune cell types, and Gene Set Variation Analysis (GSVA) analysis was applied to analyze the status of pathways between OA and normal groups. Furthermore, the optimal diagnostic biomarkers for OA were identified by least absolute shrinkage and selection operator (LASSO) models. Finally, the key role of biomarkers in OA synovitis microenvironment was discussed through single cell and Scissor analysis.

Results

A total of 172 DEGs (differentially expressed genes) associated with osteoarticular synovitis were identified, and these genes mainly enriched eight functional categories. In addition, immune infiltration analysis found that four immune cell types, including Macrophage, B cell memory, B cell, and Mast cell were significantly correlated with OA, and LASSO analysis showed that Macrophage were the best diagnostic biomarkers of immune infiltration in OA. Furthermore, using scRNA-seq dataset, we also analyzed the cell communication patterns of Macrophage in the OA synovial inflammatory microenvironment and found that CCL, MIF, and TNF signaling pathways were the mainly cellular communication pathways. Finally, Scissor analysis identified a population of M2-like Macrophages with high expression of CD163 and LYVE1, which has strong anti-inflammatory ability and showed that the TNF gene may play an important role in the synovial microenvironment of OA.

Conclusion

Overall, Macrophage is the best diagnostic marker of immune infiltration in osteoarticular synovitis, and it can communicate with other cells mainly through CCL, TNF, and MIF signaling pathways in microenvironment. In addition, TNF gene may play an important role in the development of synovitis.

Development and validation of cuproptosis-related genes in synovitis during osteoarthritis progress

Osteoarthritis (OA) is one of the most common refractory degenerative joint diseases worldwide. Synovitis is believed to drive joint cartilage destruction during OA pathogenesis. Cuproptosis is a novel form of copper-induced cell death. However, few studies have examined the correlations between cuproptosis-related genes (CRGs), immune infiltration, and synovitis. Therefore, we analyzed CRGs in synovitis during OA. Microarray datasets (GSE55235, GSE55457, GSE12021, GSE82107 and GSE176308) were downloaded from the Gene Expression Omnibus database. Next, we conducted differential and subtype analyses of CRGs across synovitis. Immune infiltration and correlation analyses were performed to explore the association between CRGs and immune cell abundance in synovitis. Finally, single-cell RNA-seq profiling was performed using the GSE176308 dataset to investigate the expression of CRGs in the various cell clusters. We found that the expression of five CRGs (FDX1, LIPT1, PDHA1, PDHB, and CDKN2A) was significantly increased in the OA synovium. Moreover, abundant and various types of immune cells infiltrated the synovium during OA, which was correlated with the expression of CRGs. Additionally, single-cell RNA-seq profiling revealed that the cellular composition of the synovium was complex and that their proportions varied greatly as OA progressed. The expression of CRGs differed across various cell types in the OA synovium. The current study predicted that cuproptosis may be involved in the pathogenesis of synovitis. The five screened CRGs (FDX1, LIPT1, PDHA1, PDHB, and CDKN2A) could be explored as candidate biomarkers or therapeutic targets for OA synovitis.

Role of Mesenchymal Stem Cells and Their Paracrine Mediators in Macrophage Polarization: An Approach to Reduce Inflammation in Osteoarthritis

Osteoarthritis (OA) is a low-grade inflammatory disorder of the joints that causes deterioration of the cartilage, bone remodeling, formation of osteophytes, meniscal damage, and synovial inflammation (synovitis). The synovium is the primary site of inflammation in OA and is frequently characterized by hyperplasia of the synovial lining and infiltration of inflammatory cells, primarily macrophages. Macrophages play a crucial role in the early inflammatory response through the production of several inflammatory cytokines, chemokines, growth factors, and proteinases. These pro-inflammatory mediators are activators of numerous signaling pathways that trigger other cytokines to further recruit more macrophages to the joint, ultimately leading to pain and disease progression. Very few therapeutic alternatives are available for treating inflammation in OA due to the condition's low self-healing capacity and the lack of clear diagnostic biomarkers. In this review, we opted to explore the immunomodulatory properties of mesenchymal stem cells (MSCs) and their paracrine mediators-dependent as a therapeutic intervention for OA, with a primary focus on the practicality of polarizing macrophages as suppression of M1 macrophages and enhancement of M2 macrophages can significantly reduce OA symptoms.

Osteoarthritis: New Insight on Its Pathophysiology

Understanding of the basis of osteoarthritis (OA) has seen some interesting advancements in recent years. It has been observed that cartilage degeneration is preceded by subchondral bone lesions, suggesting a key role of this mechanism within the pathogenesis and progression of OA, as well as the formation of ectopic bone and osteophytes. Moreover, low-grade, chronic inflammation of the synovial lining has gained a central role in the definition of OA physiopathology, and central immunological mechanisms, innate but also adaptive, are now considered crucial in driving inflammation and tissue destruction. In addition, the role of neuroinflammation and central sensitization mechanisms as underlying causes of pain chronicity has been characterized. This has led to a renewed definition of OA, which is now intended as a complex multifactorial joint pathology caused by inflammatory and metabolic factors underlying joint damage. Since this evidence can directly affect the definition of the correct therapeutic approach to OA, an improved understanding of these pathophysiological mechanisms is fundamental. To this aim, this review provides an overview of the most updated evidence on OA pathogenesis; it presents the most recent insights on the pathophysiology of OA, describing the interplay between immunological and biochemical mechanisms proposed to drive inflammation and tissue destruction, as well as central sensitization mechanisms. Moreover, although the therapeutic implications consequent to the renewed definition of OA are beyond this review scope, some suggestions for intervention have been addressed.

Identification of Potential Therapeutic Target Genes in Osteoarthritis

Objective

Osteoarthritis (OA), also known as joint failure, is characterized by joint pain and, in severe cases, can lead to loss of joint function in patients. Immune-related genes and immune cell infiltration play a crucial role in OA development. We used bioinformatics approaches to detect potential diagnostic markers and available drugs for OA while initially exploring the immune mechanisms of OA.

Methods

The training set GSE55235 and validation set GSE51588 and GSE55457 were obtained from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified by the limma package. Gene set enrichment analysis (GSEA) was performed on the GSE55235 dataset using the cluster profiler package. At the same time, DEGs were analyzed by gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, protein-protein interaction (PPI) analysis was performed on the common DEGs of the three datasets using the STRING database. Proteins with direct linkage were identified as hub genes, and the relation of hub genes was subsequently analyzed using the GOSemSim package. Hub genes' expression profiles and diagnostic capabilities (ROC curves) were analyzed and validated using three datasets. In addition, we performed RT-qPCR to validate the levels of hub genes. The immune microenvironment was analyzed using the CIBERSORT package, and the relationship between hub genes and immune cells was evaluated. In addition, we used a linkage map (CMAP) database to identify available drug candidates. Finally, the GSEA of hub genes was used to decipher the potential pathways corresponding to hub genes.

Results

Three hub genes (CX3CR1, MYC, and TLR7) were identified. CX3CR1 and TLR7 were highly expressed in patients with OA, whereas the expression of MYC was low. The results of RT-qPCR validation were consistent with those obtained using datasets. Among these genes, CX3CR1 and TLR7 can be used as diagnostic markers. It was found that CX3CR1, MYC, and TLR7 affect the immune microenvironment of OA via different immune cells. In addition, we identified a potential drug for the treatment of OA. Altogether, CX3CR1, MYC, and TLR7 affect the immune response of OA through multiple pathways.

Conclusion

CX3CR1, MYC, and TLR7 are associated with various immune cells and are the potential diagnostic markers and therapeutic targets for OA.

Phenotype Diversity of Macrophages in Osteoarthritis: Implications for Development of Macrophage Modulating Therapies

Chronic inflammation is implicated in numerous human pathologies. In particular, low-grade inflammation is currently recognized as an important mechanism of osteoarthritis (OA), at least in some patients. Among the signs of the inflammatory process are elevated macrophage numbers detected in the OA synovium compared to healthy controls. High macrophage counts also correlate with clinical symptoms of the disease. Macrophages are central players in the development of chronic inflammation, pain, cartilage destruction, and bone remodeling. However, macrophages are also involved in tissue repair and remodeling, including cartilage. Therefore, reduction of macrophage content in the joints correlates with deleterious effects in OA models. Macrophage population is heterogeneous and dynamic, with phenotype transitions being induced by a variety of stimuli. In order to effectively use the macrophage inflammatory circuit for treatment of OA, it is important to understand macrophage heterogeneity and interactions with surrounding cells and tissues in the joint. In this review, we discuss functional phenotypes of macrophages and specific targeting approaches relevant for OA treatment development.

Single-Cell Profiles of Age-Related Osteoarthritis Uncover Underlying Heterogeneity Associated With Disease Progression

Objective: Osteoarthritis (OA) is the most common chronic degenerative joint disease, which represents the leading cause of age-related disability. Here, this study aimed to depict the intercellular heterogeneity of OA synovial tissues.

Methods: Single-cell RNA sequencing (scRNA-seq) data were preprocessed and quality controlled by the Seurat package. Cell cluster was presented and cell types were annotated based on the mRNA expression of corresponding marker genes by the SingleR package. Cell-cell communication was assessed among different cell types. After integrating the GSE55235 and GSE55457 datasets, differentially expressed genes were identified between OA and normal synovial tissues. Then, differentially expressed marker genes were overlapped and their biological functions were analyzed.

Results: Totally, five immune cell subpopulations were annotated in OA synovial tissues including macrophages, dendritic cells, T cells, monocytes and B cells. Pseudo-time analysis revealed the underlying evolution process in the inflammatory microenvironment of OA synovial tissue. There was close crosstalk between five cell types according to the ligand-receptor network. The genetic heterogeneity was investigated between OA and normal synovial tissues. Furthermore, functional annotation analysis showed the intercellular heterogeneity across immune cells in OA synovial tissues.

Conclusion: This study offered insights into the heterogeneity of OA, which provided in-depth understanding of the transcriptomic diversities within synovial tissue. This transcriptional heterogeneity may improve our understanding on OA pathogenesis and provide potential molecular therapeutic targets for OA.

Mast Cells Differentiated in Synovial Fluid and Resident in Osteophytes Exalt the Inflammatory Pathology of Osteoarthritis

Introduction: Osteophytes are a prominent feature of osteoarthritis (OA) joints and one of the clinical hallmarks of the disease progression. Research on osteophytes is fragmentary and modes of its contribution to OA pathology are obscure. Aim: To elucidate the role of osteophytes in OA pathology from a perspective of molecular and cellular events. Methods: RNA-seq of fully grown osteophytes, collected from tibial plateau of six OA patients revealed patterns corresponding to active extracellular matrix re-modulation and prominent participation of mast cells. Presence of mast cells was further confirmed by immunohistochemistry, performed on the sections of the osteophytes using anti-tryptase alpha/beta-1 and anti-FC epsilon RI antibodies and the related key up-regulated genes were validated by qRT-PCR. To test the role of OA synovial fluid (SF) in mast cell maturation as proposed by the authors, hematopoietic stem cells (HSCs) and ThP1 cells were cultured in a media supplemented with 10% SF samples, obtained from various grades of OA patients and were monitored using specific cell surface markers by flow cytometry. Proteomics analysis of SF samples was performed to detect additional markers specific to mast cells and inflammation that drive the cell differentiation and maturation. Results: Transcriptomics of osteophytes revealed a significant upregulation of mast cells specific genes such as chymase 1 (CMA1; 5-fold) carboxypeptidase A3 (CPA3; 4-fold), MS4A2/FCERI (FCERI; 4.2-fold) and interleukin 1 receptor-like 1 (IL1RL1; 2.5-fold) indicating their prominent involvement. (In IHC, anti-tryptase alpha/beta-1 and anti- FC epsilon RI-stained active mast cells were seen populated in cartilage, subchondral bone, and trabecular bone.) Based on these outcomes and previous learnings, the authors claim a possibility of mast cells invasion into osteophytes is mediated by SF and present in vitro cell differentiation assay results, wherein ThP1 and HSCs showed differentiation into HLA-DR+/CD206+ and FCERI+ phenotype, respectively, after exposing them to medium containing 10% SF for 9 days. Proteomics analysis of these SF samples showed an accumulation of mast cell-specific inflammatory proteins. Conclusions: RNA-seq analysis followed by IHC study on osteophyte samples showed a population of mast cells resident in them and may further accentuate inflammatory pathology of OA. Besides subchondral bone, the authors propose an alternative passage of mast cells invasion in osteophytes, wherein OA SF was found to be necessary and sufficient for maturation of mast cell precursor into effector cells.

Cell Interplay in Osteoarthritis

Osteoarthritis (OA) is a common chronic disease and a significant health concern that needs to be urgently solved. OA affects the cartilage and entire joint tissues, including the subchondral bone, synovium, and infrapatellar fat pads. The physiological and pathological changes in these tissues affect the occurrence and development of OA. Understanding complex crosstalk among different joint tissues and their roles in OA initiation and progression is critical in elucidating the pathogenic mechanism of OA. In this review, we begin with an overview of the role of chondrocytes, synovial cells (synovial fibroblasts and macrophages), mast cells, osteoblasts, osteoclasts, various stem cells, and engineered cells (induced pluripotent stem cells) in OA pathogenesis. Then, we discuss the various mechanisms by which these cells communicate, including paracrine signaling, local microenvironment, co-culture, extracellular vesicles (exosomes), and cell tissue engineering. We particularly focus on the therapeutic potential and clinical applications of stem cell-derived extracellular vesicles, which serve as modulators of cell-to-cell communication, in the field of regenerative medicine, such as cartilage repair. Finally, the challenges and limitations related to exosome-based treatment for OA are discussed. This article provides a comprehensive summary of key cells that might be targets of future therapies for OA.

Optimization of Lyophilized Hyperacute Serum (HAS) as a Regenerative Therapeutic in Osteoarthritis

Hyperacute serum (HAS) is a blood derivative product that promotes the proliferation of various cell types and controls inflammation in vitro. The aim of this study is to investigate the regenerative potential of different formulations of HAS, including lyophilized and hyaluronic acid combined versions, to obtain a stable and standardized therapeutic in osteoarthritis (OA), which may be able to overcome the variability limitations of platelet-rich plasma (PRP). Primary human osteoarthritic chondrocytes were used for testing cellular viability and gene expression of OA-related genes. Moreover, a co-culture of human explants of cartilage, bone and synovium under inflammatory conditions was used for investigating the inflammatory control capacities of the different therapeutics. In this study, one formulation of lyophilized HAS achieved the high cell viability rates of liquid HAS and PRP. Gene expression analysis showed that HAS induced higher Col1a1 expression than PRP. Cytokine quantification from supernatant fluids revealed that HAS treatment of inflamed co-cultures significantly reduced levels of IL-5, IL-15, IL-2, TNFα, IL-7 and IL-12. To conclude, lyophilized HAS is a stable and standardized therapeutic with high potential in joint regeneration.

Bone marrow derived mast cells injected into the osteoarthritic knee joints of mice induced by sodium monoiodoacetate enhanced spontaneous pain through activation of PAR2 and action of extracellular ATP

Conditions that resemble osteoarthritis (OA) were produced by injection of sodium monoiodoacetate (MIA) into the knee joints of mice. Bone marrow derived mast cells (BMMCs) injected into the OA knee joints enhanced spontaneous pain. Since no spontaneous pain was observed when BMMCs were injected into the knee joints of control mice that had not been treated with MIA, BMMCs should be activated within the OA knee joints and release some pain-inducible factors. Protease activated receptor-2 (PAR2) antagonist (FSLLRY-NH₂) almost abolished the pain-enhancing effects of BMMCs injected into the OA knee joints, suggesting that tryptase, a mast cell protease that is capable of activating PAR2, should be released from the injected BMMCs and enhance pain through activation of PAR2. When PAR2 agonist (SLIGKV-NH₂) instead of BMMCs was injected into the OA knee joints, it was also enhanced pain. Apyrase, an ATP degrading enzyme, injected into the OA knee joints before BMMCs suppressed the pain enhanced by BMMCs. We showed that purinoceptors (P2X4 and P2X7) were expressed in BMMCs and that extracellular ATP stimulated the release of tryptase from BMMCs. These observations suggest that ATP may stimulate degranulation of BMMCs and thereby enhanced pain. BMMCs injected into the OA knee joints stimulated expression of IL-1β, IL-6, TNF-α, CCL2, and MMP9 genes in the infrapatellar fat pads, and PAR2 antagonist suppressed the stimulatory effects of BMMCs. Our study suggests that intermittent pain frequently observed in OA knee joints may be due, at least partly, to mast cells through activation of PAR2 and action of ATP, and that intraarticular injection of BMMCs into the OA knee joints may provide a useful experimental system for investigating molecular mechanisms by which pain is induced in OA knee joints.

Communications Between Bone Marrow Macrophages and Bone Cells in Bone Remodeling

The mammalian skeleton is a metabolically active organ that continuously undergoes bone remodeling, a process of tightly coupled bone resorption and formation throughout life. Recent studies have expanded our knowledge about the interactions between cells within bone marrow in bone remodeling. Macrophages resident in bone (BMMs) can regulate bone metabolism via secreting numbers of cytokines and exosomes. This review summarizes the current understanding of factors, exosomes, and hormones that involved in the communications between BMMs and other bone cells including mensenchymal stem cells, osteoblasts, osteocytes, and so on. We also discuss the role of BMMs and potential therapeutic approaches targeting BMMs in bone remodeling related diseases such as osteoporosis, osteoarthritis, rheumatoid arthritis, and osteosarcoma.