Complement component C1q is produced by isolated articular chondrocytes

The role of O-GlcNAcylation in bone metabolic diseases

O-GlcNAcylation, as a post-translational modification, can modulate cellular activities such as kinase activity, transcription-translation, protein degradation, and insulin signaling by affecting the function of the protein substrate, including cellular localization of proteins, protein stability, and protein/protein interactions. Accumulating evidence suggests that dysregulation of O-GlcNAcylation is associated with disease progression such as cancer, neurodegeneration, and diabetes. Recent studies suggest that O-GlcNAcylation is also involved in the regulation of osteoblast, osteoclast and chondrocyte differentiation, which is closely related to the initiation and development of bone metabolic diseases such as osteoporosis, arthritis and osteosarcoma. However, the potential mechanisms by which O-GlcNAcylation regulates bone metabolism are not fully understood. In this paper, the literature related to the regulation of bone metabolism by O-GlcNAcylation was summarized to provide new potential therapeutic strategies for the treatment of orthopedic diseases such as arthritis and osteoporosis.

Hematopoiesis Revolves Around the Primordial Evolutional Rhythm of Purinergic Signaling and Innate Immunity - A Journey to the Developmental Roots

A cell's most significant existential task is to survive by ensuring proper metabolism, avoiding harmful stimuli, and adapting to changing environments. It explains why early evolutionary primordial signals and pathways remained active and regulate cell and tissue integrity. This requires energy supply and a balanced redox state. To meet these requirements, the universal intracellular energy transporter purine nucleotide-adenosine triphosphate (ATP) became an important signaling molecule and precursor of purinergic signaling after being released into extracellular space. Similarly, ancient proteins involved in intracellular metabolism gave rise to the third protein component (C3) of the complement cascade (ComC), a soluble arm of innate immunity. These pathways induce cytosol reactive oxygen (ROS) and reactive nitrogen species (RNS) that regulate the redox state of the cells. While low levels of ROS and RNS promote cell growth and differentiation, supra-physiological concentrations can lead to cell damage by pyroptosis. This balance explains the impact of purinergic signaling and innate immunity on cell metabolism, organogenesis, and tissue development. Subsequently, along with evolution, new regulatory cues emerge in the form of growth factors, cytokines, chemokines, and bioactive lipids. However, their expression is still modulated by both primordial signaling pathways. This review will focus on the data that purinergic signaling and innate immunity carry on their ancient developmental task in hematopoiesis and specification of hematopoietic stem/progenitor cells (HSPCs). Moreover, recent evidence shows both these regulatory pathways operate in a paracrine manner and inside HSPCs at the autocrine level.

The role of the complement system in disc degeneration and Modic changes

Disc degeneration and vertebral endplate bone marrow lesions called Modic changes are prevalent spinal pathologies found in chronic low back pain patients. Their pathomechanisms are complex and not fully understood. Recent studies have revealed that complement system proteins and interactors are dysregulated in disc degeneration and Modic changes. The complement system is part of the innate immune system and plays a critical role in tissue homeostasis. However, its dysregulation has also been associated with various pathological conditions such as rheumatoid arthritis and osteoarthritis. Here, we review the evidence for the involvement of the complement system in intervertebral disc degeneration and Modic changes. We found that only a handful of studies reported on complement factors in Modic changes and disc degeneration. Therefore, the level of evidence for the involvement of the complement system is currently low. Nevertheless, the complement system is tightly intertwined with processes known to occur during disc degeneration and Modic changes, such as increased cell death, autoantibody production, bacterial defense processes, neutrophil activation, and osteoclast formation, indicating a contribution of the complement system to these spinal pathologies. Based on these mechanisms, we propose a model how the complement system could contribute to the vicious cycle of tissue damage and chronic inflammation in disc degeneration and Modic changes. With this review, we aim to highlight a currently understudied but potentially important inflammatory pathomechanism of disc degeneration and Modic changes that may be a novel therapeutic target.

The Role of Innate Immunity in Osteoarthritis and the Connotation of "Immune-joint" Axis: A Narrative Review

Osteoarthritis (OA) is a degenerative disease that results in constriction of the joint space due to the gradual deterioration of cartilage, alterations in subchondral bone, and synovial membrane. Recently, scientists have found that OA involves lesions in the whole joint, in addition to joint wear and tear and cartilage damage. Osteoarthritis is often accompanied by a subclinical form of synovitis, which is a chronic, relatively low-grade inflammatory response mainly mediated by the innate immune system. The "immune-joint" axis refers to an interaction of an innate immune response with joint inflammation and the whole joint range. Previous studies have underestimated the role of the immune-joint axis in OA, and there is no related research. For this reason, this review aimed to evaluate the existing evidence on the influence of innate immune mechanisms on the pathogenesis of OA. The innate immune system is the body's first line of defense. When the innate immune system is triggered, it instantly activates the downstream inflammatory signal pathway, causing an inflammatory response, while also promoting immune cells to invade joint synovial tissue and accelerate the progression of OA. We have proposed the concept of the "immune-joint" axis and explored it from two aspects of Traditional Chinese Medicine (TCM) theory and modern medical research, such as the innate immunity and OA, macrophages and OA, complement and OA, and other cells and OA, to enrich the scientific connotation of the "immune-joint" axis.

Bioinformatics analysis of hub genes as osteoarthritis prognostic biomarkers

Osteoarthritis (OA) is a progressive cartilage degradation disease, concomitant with synovitis, osteophyte formation, and subchondral bone sclerosis. Over 37% of the elderly population is affected by OA, and the number of cases is increasing as the global population ages. Therefore, the objective of this study was to identify and analyze the hub genes of OA combining with comprehensive bioinformatics analysis tools to provide theoretical basis in further OA effective therapies. Two sample sets of GSE46750 contained 12 pairs OA synovial membrane and normal samples harvested from patients as well as GSE98918 including 12 OA and non-OA patients were downloaded from the Gene Expression Omnibus database (GEO) database. Differentially expressed genes (DEGs) were identified using Gene Expression Omnibus 2R (GEO2R), followed by functional enrichment analysis, protein-protein interaction networks construction. The hub genes were identified and evaluated. An OA rat model was constructed, hematoxylin and eosin staining, safranin O/fast green staining, cytokines concentrations of serum were used to verify the model. The hub genes expression level in the knee OA samples were verified using RT-qPCR. The top 20 significantly up-regulated and down-regulated DEGs were screened out from the two datasets, respectively. The top 18 GO terms and 10 KEGG pathways were enriched. Eight hub genes were identified, namely MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2. Among them, the hub genes were all up-regulated in in vivo OA rat model, compared with healthy controls. The eight hub genes identified (MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2) were shown to be associated with OA. These genes can serve as disease markers to discriminate OA patients from healthy controls.

Identification of circulating monocytes as producers of tuberculosis disease biomarker C1q

Tuberculosis (TB) is a prevalent disease causing an estimated 1.6 million deaths and 10.6 million new cases annually. Discriminating TB disease from differential diagnoses can be complex, particularly in the field. Increased levels of complement component C1q in serum have been identified as a specific and accessible biomarker for TB disease but the source of C1q in circulation has not been identified. Here, data and samples previously collected from human cohorts, a clinical trial and a non-human primate study were used to identify cells producing C1q in circulation. Cell subset frequencies were correlated with serum C1q levels and combined with single cell RNA sequencing and flow cytometry analyses. This identified monocytes as C1q producers in circulation, with a pronounced expression of C1q in classical and intermediate monocytes and variable expression in non-classical monocytes.

Identification of hub genes and regulatory networks in histologically unstable carotid atherosclerotic plaque by bioinformatics analysis

Objective

This study identified underlying genetic molecules associated with histologically unstable carotid atherosclerotic plaques through bioinformatics analysis that may be potential biomarkers and therapeutic targets.

Methods

Three transcriptome datasets (GSE41571, GSE120521 and E-MTAB-2055) and one non-coding RNA dataset (GSE111794) that met histological grouping criteria of unstable plaque were downloaded. The common differentially expressed genes (co-DEGs) of unstable plaques identified from three mRNA datasets were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG). A protein–protein interaction (PPI) network was constructed to present the interaction between co-DEGs and screen out hub genes. MiRNet database and GSE111794 dataset were used to identify the miRNAs targeting hub genes. Associated transcription factors (TFs) and drugs were also predicted. These predicted results were used to construct miRNA/TFs-hub gene and drug-hub gene regulatory networks.

Results

A total of 105 co-DEGs were identified, including 42 up-regulated genes and 63 down-regulated genes, which were mainly enriched in collagen-containing extracellular matrix, focal adhesion, actin filament bundle, chemokine signaling pathway and regulates of actin cytoskeleton. Ten hub genes (up-regulated: HCK, C1QC, CD14, FCER1G, LCP1 and RAC2; down-regulated: TPM1, MYH10, PLS3 and FMOD) were screened. HCK and RAC2 were involved in chemokine signaling pathway, MYH10 and RAC2 were involved in regulation of actin cytoskeleton. We also predicted 12 miRNAs, top5 TFs and 25 drugs targeting hub genes. In the miRNA/TF-hub gene regulatory network, PLS3 was the most connected hub genes and was targeted by six miRNAs and all five screened TFs. In the drug-hub gene regulatory network, HCK was targeted by 20 drugs including 10 inhibitors.

Conclusions

We screened 10 hub genes and predicted miRNAs and TFs targeting them. These molecules may play a crucial role in the progression of histologically unstable carotid plaques and serve as potential biomarkers and therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01257-1.

Comprehensive Genetic Analysis of Tuberculosis and Identification of Candidate Biomarkers

Purpose: The purpose of this study is to use the data in the GEO database to analyze, screen biomarkers that can diagnose tuberculosis, and verification of candidate biomarkers.

Materials and methods: GSE158767 dataset were used to process WGCNA analysis, differential gene analysis, Gene ontology and KEGG analysis, protein-protein network analysis and hub genes analysis. Based on our previous study, the intersect between WGCNA and differential gene analysis could be used as candidate biomarkers. Then, the enzyme-linked immunosorbent assay was used to validate candidate biomarkers, and receiver operating characteristic was used to assess diagnose ability of candidate biomarkers.

Results: A total of 412 differential genes were screened. And we obtained 105 overlapping genes between DEGs and WGCNA. GO and KEGG analysis showed that most of the differential genes were significantly enriched in innate immunity. A total of 15 hub genes were screened, and four of them were verified by Enzyme-linked immunosorbent assay. CCL5 performed well in distinguishing the healthy group from the TB group (AUC = 0.723). And CCL19 performed well in distinguishing the TB group from the ORD groups (AUC = 0.811).

Conclusion: CCL19, C1Qb, CCL5 and HLA-DMB may play important role in tuberculosis, which indicated four genes may become effective biomarkers and could be conveniently used to facilitate the individual tuberculosis diagnosis in Chinese people.

Identification and development of a novel 5-gene diagnostic model based on immune infiltration analysis of osteoarthritis

Background

Osteoarthritis (OA), which is due to the progressive loss and degeneration of articular cartilage, is the leading cause of disability worldwide. Therefore, it is of great significance to explore OA biomarkers for the prevention, diagnosis, and treatment of OA.

Methods and materials

The GSE129147, GSE57218, GSE51588, GSE117999, and GSE98918 datasets with normal and OA samples were downloaded from the Gene Expression Omnibus (GEO) database. The GSE117999 and GSE98918 datasets were integrated, and immune infiltration was evaluated. The differentially expressed genes (DEGs) were analyzed using the limma package in R, and weighted gene co-expression network analysis (WGCNA) was used to explore the co-expression genes and co-expression modules. The co-expression module genes were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and hub genes were identified by the degree, MNC, closeness, and MCC algorithms. The hub genes were used to construct a diagnostic model based on support vector machines.

Results

The Immune Score in the OA samples was significantly higher than in the normal samples, and a total of 2313 DEGs were identified. Through WGCNA, we found that the yellow module was significantly positively correlated with the OA samples and Immune Score and negatively correlated with the normal samples. The 142 DEGs of the yellow module were related to biological processes such as regulation of inflammatory response, positive regulation of inflammatory response, blood vessel morphogenesis, endothelial cell migration, and humoral immune response. The intersections of the genes obtained by the 4 algorithms resulted in 5 final hub genes, and the diagnostic model constructed with these 5 genes showed good performance in the training and validation cohorts.

Conclusions

The 5-gene diagnostic model can be used to diagnose OA and guide clinical decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03183-9.

Blockade of Fgfr1 with PD166866 Protects Cartilage from the Catabolic Effects Induced by Interleukin-1β: A Genome-Wide Expression Profiles Analysis

OBJECTIVE

Previously we showed that genetic deletion of Fgfr1 in chondrocytes protected mice from progression of osteoarthritis (OA). The aim of this study is to evaluate the effect of PD166866, a potent selective inhibitor of Fgfr1, on cartilage degeneration induced by interleukin-1β (IL-1β) and to clarify underlying global gene expression pattern.

DESIGN

Cartilage explants and primary rat chondrocytes were stimulated with IL-1β to establish an inflammatory OA in vitro model. The effects of PD166866 were determined by measuring the release of glycosaminoglycans (GAG) in cartilage explants and primary rat chondrocytes, and the underlying molecular mechanism was analyzed by microarray and RT-PCR analysis in primary chondrocytes.

RESULTS

In cartilage explants, PD166866 significantly counteracts IL-β stimulated GAG release. In addition, PD166866 impede IL-1β-stimulated nuclear translocation of p65 in rat chondrocytes. Based on microarray analysis, a total of 67 and 132 genes with more than 1.5-fold changes were identified in IL-1β-treated versus control and PD166866 cotreatment versus IL-1β treatment alone, respectively. Only 19 thereof were coregulated by IL-1β and PD166866 simultaneously. GO and KEGG pathway analysis showed that some pathways, including "cytokine-cytokine receptor interaction," "chemokine signaling pathway," and "complement and coagulation cascades," as well as some key genes like chemokines, complement, and matrix metalloproteinases may relevant for therapeutic application of Fgfr1 blockade in IL-1β-stimulated chondrocytes.

CONCLUSION

Our results clearly demonstrated that blockade of Fgfr1 with PD166866 could effectively suppress the catabolic effects induced by IL-1β, and elucidated whole genomic targets of Fgfr1 inhibition responsible for the therapeutic effects of Fgfr1 blockade against inflammatory OA.

Anti-Inflammatory Therapeutic Approaches to Prevent or Delay Post-Traumatic Osteoarthritis (PTOA) of the Knee Joint with a Focus on Sustained Delivery Approaches

Inflammation plays a central role in the pathogenesis of knee PTOA after knee trauma. While a comprehensive therapy capable of preventing or delaying post-traumatic osteoarthritis (PTOA) progression after knee joint injury does not yet clinically exist, current literature suggests that certain aspects of early post-traumatic pathology of the knee joint may be prevented or delayed by anti-inflammatory therapeutic interventions. We discuss multifaceted therapeutic approaches that may be capable of effectively reducing the continuous cycle of inflammation and concomitant processes that lead to cartilage degradation as well as those that can simultaneously promote intrinsic repair processes. Within this context, we focus on early disease prevention, the optimal timeframe of treatment and possible long-lasting sustained delivery local modes of treatments that could prevent knee joint-associated PTOA symptoms. Specifically, we identify anti-inflammatory candidates that are not only anti-inflammatory but also anti-degenerative, anti-apoptotic and pro-regenerative.

Proteomic Analysis of Synovial Fibroblasts and Articular Chondrocytes Co-Cultures Reveals Valuable VIP-Modulated Inflammatory and Degradative Proteins in Osteoarthritis

Osteoarthritis (OA) is the most common musculoskeletal disorder causing a great disability and a reduction in the quality of life. In OA, articular chondrocytes (AC) and synovial fibroblasts (SF) release innate-derived immune mediators that initiate and perpetuate inflammation, inducing cartilage extracellular matrix (ECM) degradation. Given the lack of therapies for the treatment of OA, in this study, we explore biomarkers that enable the development of new therapeutical approaches. We analyze the set of secreted proteins in AC and SF co-cultures by stable isotope labeling with amino acids (SILAC). We describe, for the first time, 115 proteins detected in SF-AC co-cultures stimulated by fibronectin fragments (Fn-fs). We also study the role of the vasoactive intestinal peptide (VIP) in this secretome, providing new proteins involved in the main events of OA, confirmed by ELISA and multiplex analyses. VIP decreases proteins involved in the inflammatory process (CHI3L1, PTX3), complement activation (C1r, C3), and cartilage ECM degradation (DCN, CTSB and MMP2), key events in the initiation and progression of OA. Our results support the anti-inflammatory and anti-catabolic properties of VIP in rheumatic diseases and provide potential new targets for OA treatment.

An Evidence-Based Systematic Review of Human Knee Post-Traumatic Osteoarthritis (PTOA): Timeline of Clinical Presentation and Disease Markers, Comparison of Knee Joint PTOA Models and Early Disease Implications

Understanding the causality of the post-traumatic osteoarthritis (PTOA) disease process of the knee joint is important for diagnosing early disease and developing new and effective preventions or treatments. The aim of this review was to provide detailed clinical data on inflammatory and other biomarkers obtained from patients after acute knee trauma in order to (i) present a timeline of events that occur in the acute, subacute, and chronic post-traumatic phases and in PTOA, and (ii) to identify key factors present in the synovial fluid, serum/plasma and urine, leading to PTOA of the knee in 23-50% of individuals who had acute knee trauma. In this context, we additionally discuss methods of simulating knee trauma and inflammation in in vivo, ex vivo articular cartilage explant and in vitro chondrocyte models, and answer whether these models are representative of the clinical inflammatory stages following knee trauma. Moreover, we compare the pro-inflammatory cytokine concentrations used in such models and demonstrate that, compared to concentrations in the synovial fluid after knee trauma, they are exceedingly high. We then used the Bradford Hill Framework to present evidence that TNF-α and IL-6 cytokines are causal factors, while IL-1β and IL-17 are credible factors in inducing knee PTOA disease progresssion. Lastly, we discuss beneficial infrastructure for future studies to dissect the role of local vs. systemic inflammation in PTOA progression with an emphasis on early disease.

Identification of Three Significant Genes Associated with Immune Cells Infiltration in Dysfunctional Adipose Tissue-Induced Insulin-Resistance of Obese Patients via Comprehensive Bioinformatics Analysis

BACKGROUND

Low-grade chronic inflammation in dysfunctional adipose tissue links obesity with insulin resistance through the activation of tissue-infiltrating immune cells. Numerous studies have reported on the pathogenesis of insulin-resistance. However, few studies focused on genes from genomic database. In this study, we would like to explore the correlation of genes and immune cells infiltration in adipose tissue via comprehensive bioinformatics analyses and experimental validation in mice and human adipose tissue.

METHODS

Gene Expression Omnibus (GEO) datasets (GSE27951, GSE55200, and GSE26637) of insulin-resistant individuals or type 2 diabetes patients and normal controls were downloaded to get differently expressed genes (DEGs), and GO and KEGG pathway analyses were performed. Subsequently, we integrated DEGs from three datasets and constructed commonly expressed DEGs' PPI net-works across datasets. Center regulating module of DEGs and hub genes were screened through MCODE and cytoHubba in Cytoscape. Three most significant hub genes were further analyzed by GSEA analysis. Moreover, we verified the predicted hub genes by performing RT qPCR analysis in animals and human samples. Besides, the relative fraction of 22 immune cell types in adipose tissue was detected by using the deconvolution algorithm of CIBERSORT (Cell Type Identification by Estimating Relative Subsets of RNA Transcripts). Furthermore, based on the significantly changed types of immune cells, we performed correlation analysis between hub genes and immune cells. And, we performed immunohistochemistry and immunofluorescence analysis to verify that the hub genes were associated with adipose tissue macrophages (ATM).

RESULTS

Thirty DEGs were commonly expressed across three datasets, most of which were upregulated. DEGs mainly participated in the process of multiple immune cells' infiltration. In protein-protein interaction network, we identified CSF1R, C1QC, and TYROBP as hub genes. GSEA analysis suggested high expression of the three hub genes was correlated with immune cells functional pathway's activation. Immune cell infiltration and correlation analysis revealed that there were significant positive correlations between TYROBP and M0 macrophages, CSF1R and M0 macrophages, Plasma cells, and CD8 T cells. Finally, hub genes were associated with ATMs infiltration by experimental verification.

CONCLUSIONS

This article revealed that CSF1R, C1QC, and TYROBP were potential hub genes associated with immune cells' infiltration and the function of proinflammation, especially adipose tissue macrophages, in the progression of obesity-induced diabetes or insulin-resistance.

Antibiotic Treatment Prior to Injury Improves Post-Traumatic Osteoarthritis Outcomes in Mice

Osteoarthritis (OA) is a painful and debilitating disease characterized by the chronic and progressive degradation of articular cartilage. Post-traumatic OA (PTOA) is a secondary form of OA that develops in ~50% of cases of severe articular injury. Inflammation and re-occurring injury have been implicated as contributing to the progression of PTOA after the initial injury. However, there is very little known about external factors prior to injury that could affect the risk of PTOA development. To examine how the gut microbiome affects PTOA development we used a chronic antibiotic treatment regimen starting at weaning for six weeks prior to ACL rupture, in mice. A six-weeks post-injury histological examination showed more robust cartilage staining on the antibiotic (AB)-treated mice than the untreated controls (VEH), suggesting slower disease progression in AB cohorts. Injured joints also showed an increase in the presence of anti-inflammatory M2 macrophages in the AB group. Molecularly, the phenotype correlated with a significantly lower expression of inflammatory genes Tlr5, Ccl8, Cxcl13, and Foxo6 in the injured joints of AB-treated animals. Our results indicate that a reduced state of inflammation at the time of injury and a lower expression of Wnt signaling modulatory protein, Rspo1, caused by AB treatment can slow down or improve PTOA outcomes.

Identification of Novel Targets of Knee Osteoarthritis Shared by Cartilage and Synovial Tissue

Arthritis is the leading cause of disability among adults, while osteoarthritis (OA) is the most common form of arthritis that results in cartilage loss. However, accumulating evidence suggests that the protective hyaline cartilage should not be the sole focus of OA treatment. Particularly, synovium also plays essential roles in OA’s initiation and progression and warrants serious consideration when battling against OA. Thus, biomarkers with similar OA-responsive expressions in cartilage and synovium should be the potential targets for OA treatment. On the other hand, molecules with a distinguished response during OA in cartilage and synovium should be ruled out as OA therapeutic(s) to avoid controversial effects in different tissues. Here, to pave the path for developing a new generation of OA therapeutics, two published transcriptome datasets of knee articular cartilage and synovium were analyzed in-depth. Genes with statistically significantly different expression in OA and healthy cartilage were compared with those in the synovium. Thirty-five genes with similar OA-responsive expression in both tissues were identified while recognizing three genes with opposite OA-responsive alteration trends in cartilage and synovium. These genes were clustered based on the currently available knowledge, and the potential impacts of these clusters in OA were explored.