Genome-wide expression profiles of subchondral bone in osteoarthritis. Arthritis Res Ther. 2013;15:R190. [PMID: 24229462 PMCID: PMC3979015 DOI: 10.1186/ar4380]

An Innovative Anoikis Signature With Inflammatory Infiltrates in Osteoarthritis

AIM

To explore the relationship between an innovative anoikis-related gene signature and inflammatory infiltrates in patients with osteoarthritis.

METHODS

Gene expression profiles (GSM1248759 and GSE200843) were curated from the Gene Expression Omnibus database, followed by the construction of a protein-protein interaction network. Functional and genomic enrichment analyses were conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The CIBERSORT method was employed to investigate immune cell infiltration differences between osteoarthritic and control tissues. Additionally, the ConsensusClusterPlus package in R software was utilized to identify distinct anoikis patterns (Cluster C1 and Cluster C2) and conduct molecular biological investigations.

RESULTS

Analysis revealed two distinct anoikis patterns (Cluster C1 and Cluster C2), with Cluster C2 patients exhibiting varying immune cell levels compared to Cluster C1 patients. Molecular investigations identified 84 DEGs enriched in specific pathways such as adipocytokine signaling, cytokine-cytokine receptor interaction, ECM-receptor interaction, and the PPAR signaling pathway. qPCR experiments confirmed the elevated expression levels of specific genes, including SOD2, MAPK14, CEACM3, LAMB3, COL13A1, TLR3, NOTCH3, and KLF12, in the IL-1β-induced group compared with the osteoarthritis group.

CONCLUSION

This study highlights the role of anoikis-related genes and immune infiltration differences in osteoarthritis, enhancing our understanding of its development.

Stage-Dependent Fibrotic Gene Profiling of WISP1-Mediated Fibrogenesis in Human Fibroblasts

Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease with unknown etiology, characterized by chronic inflammation and tissue scarring. Although, Pirfenidone and Nintedanib slow the disease progression, no currently available drugs or therapeutic interventions address the underlying cause, highlighting the unmet medical need. A matricellular protein, Wnt-1-induced secreted protein 1 (WISP1), also referred to as CCN4 (cellular communication network factor 4), is a secreted multi-modular protein implicated in multi-organ fibrosis. Although the precise mechanism of WISP1-mediated fibrosis remains unclear, emerging evidence indicates that WISP1 is profibrotic in nature. While WISP1-targeting therapy is applied in the clinic for fibrosis, detailed interrogation of WISP1-mediated fibrogenic molecular and biological pathways is lacking. Here, for the first time, using NanoString® technology, we identified a novel WISP1-associated profibrotic gene signature and molecular pathways potentially involved in the initiation and progression of fibrosis in primary human dermal and lung fibroblasts from both healthy individuals and IPF patients. Our data demonstrate that WISP1 is upregulated in IPF-lung fibroblasts as compared to healthy control. Furthermore, our results confirm that WISP1 is downstream of the transforming growth factor-β (TGFβ), and it induces fibroblast cell proliferation. Additionally, WISP1 induced IL6 and CCL2 in fibroblasts. We also developed a novel, combined TGFβ and WISP1 in vitro system to demonstrate a role for WISP1 in the progression of fibrosis. Overall, our findings uncover not only similarities but also striking differences in the molecular profile of WISP1 in human fibroblasts, both during the initiation and progression phases, as well as in disease-specific context.

Advances in the Regulation of Periostin for Osteoarthritic Cartilage Repair Applications

Emerging evidence indicates periostin (POSTN) is upregulated in patients with OA, and studies have shown that it can induce the activation of inflammatory cytokines and catabolic enzymes, making it a potential therapeutic target. Link N (LN) is a peptide fragment derived from the link protein and has been demonstrated as an anabolic-like factor and anti-catabolic and anti-inflammatory factors both in vitro and in vivo. This study aims to determine if LN can regulate POSTN expression and function in OA cartilage. Articular cartilage was recovered from donors undergoing total knee replacements to isolate chondrocytes and prepare osteochondral explants. Cells and explants were treated with POSTN and LN (1 and 100 μg) and measured for changes in POSTN expression and various matrix proteins, catabolic and proinflammatory factors, and signaling. To determine the effects of POSTN expression in vivo, a rabbit OA model was used. Immunoprecipitation and in silico modeling were used to determine peptide/POSTN interactions. Western blotting, PCR, and immunohistochemistry demonstrated that LN decreased POSTN expression both in vitro and in vivo. LN was also able to directly inhibit POSTN signaling in OA chondrocytes. In silico docking suggested the direct interaction of LN with POSTN at residues responsible for its oligomerization. Immunoprecipitation experiments confirmed the direct interaction of LN with POSTN and the destabilization of its oligomerization. This study demonstrates the ability of a peptide, LN, to suppress the overexpression and function of POSTN in OA cartilage.

Identification of hub genes through integrated single-cell and microarray transcriptome analysis in osteoarthritic meniscus

BACKGROUND

Osteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood.

METHOD

We analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform.

RESULT

After quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified.

CONCLUSION

This research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

A lactate metabolism-related gene signature to diagnose osteoarthritis based on machine learning combined with experimental validation

BACKGROUND

Lactate is gradually proved as the essential regulator in intercellular signal transduction, energy metabolism reprogramming, and histone modification. This study aims to clarify the diagnosis value of lactate metabolism-related genes in osteoarthritis (OA).

METHODS

Lactate metabolism-related genes were retrieved from the MSigDB. GSE51588 was downloaded from the Gene Expression Omnibus (GEO) as the training dataset. GSE114007, GSE117999, and GSE82107 datasets were adopted for external validation. Genomic difference detection, protein-protein interaction network analysis, LASSO, SVM-RFE, Boruta, and univariate logistic regression (LR) analyses were used for feature selection. Multivariate LR, Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB) were used to develop the multiple-gene diagnosis models. 12 control and 12 OA samples were collected from the local hospital for re-verification. The transfection assays were conducted to explore the regulatory ability of the gene to the apoptosis and vitality of chondrocytes.

RESULTS

Through the bioinformatical analyses and machine learning algorithms, SLC2A1 and NDUFB9 of the 273 lactate metabolism-related genes were identified as the significant diagnosis biomarkers. The LR, RF, SVM, and XGB models performed impressively in the cohorts (AUC > 0.7). The local clinical samples indicated that SLC2A1 and NDUFB9 were both down-regulated in the OA samples (both P < 0.05). The knockdown of NDUFB9 inhibited the viability and promoted the apoptosis of the CHON-001 cells treated with IL-1beta (both P < 0.05).

CONCLUSIONS

A lactate metabolism-related gene signature was constructed to diagnose OA, which was validated in multiple independent cohorts, local clinical samples, and cellular functional experiments.

ELIXCYTE®, an Allogenic Adipose-Derived Stem Cell Product, Mitigates Osteoarthritis by Reducing Inflammation and Preventing Cartilage Degradation In Vitro

Adipose-derived stem cells (ADSCs) comprise a promising therapy for osteoarthritis (OA). The therapeutic potential of ELIXCYTE®, an allogeneic human ADSC (hADSC) product, was demonstrated in a phase I/II OA clinical trial. However, the exact mechanism underlying such effects is not clear. Moreover, studies suggest that interleukin-11 (IL-11) has anti-inflammatory, tissue-regenerative, and immune-regulatory functions. Our aim was to unravel the mechanism associated with the therapeutic effects of ELIXCYTE® on OA and its relationship with IL-11. We cocultured ELIXCYTE® with normal human articular chondrocytes (NHACs) in synovial fluid obtained from individuals with OA (OA-SF) to investigate its effect on chondrocyte matrix synthesis and degradation and inflammation by assessing gene expression and cytokine levels. NHACs exposed to OA-SF exhibited increased MMP13 expression. However, coculturing ELIXCYTE® with chondrocytes in OA-SF reduced MMP13 expression in chondrocytes and downregulated PTGS2 and FGF2 expression in ELIXCYTE®. ELIXCYTE® treatment elevated anti-inflammatory cytokine (IL-1RA, IL-10, and IL-13) levels, and the reduction in MMP13 was positively correlated with IL-11 concentrations in OA-SF. These findings indicate that IL-11 in OA-SF might serve as a predictive biomarker for the ELIXCYTE® treatment response in OA, emphasizing the therapeutic potential of ELIXCYTE® to mitigate OA progression and provide insights into its immunomodulatory effects.

An overview of CCN4 (WISP1) role in human diseases

CCN4 (cellular communication network factor 4), a highly conserved, secreted cysteine-rich matricellular protein is emerging as a key player in the development and progression of numerous disease pathologies, including cancer, fibrosis, metabolic and inflammatory disorders. Over the past two decades, extensive research on CCN4 and its family members uncovered their diverse cellular mechanisms and biological functions, including but not limited to cell proliferation, migration, invasion, angiogenesis, wound healing, repair, and apoptosis. Recent studies have demonstrated that aberrant CCN4 expression and/or associated downstream signaling is key to a vast array of pathophysiological etiology, suggesting that CCN4 could be utilized not only as a non-invasive diagnostic or prognostic marker, but also as a promising therapeutic target. The cognate receptor of CCN4 remains elusive till date, which limits understanding of the mechanistic insights on CCN4 driven disease pathologies. However, as therapeutic agents directed against CCN4 begin to make their way into the clinic, that may start to change. Also, the pathophysiological significance of CCN4 remains underexplored, hence further research is needed to shed more light on its disease and/or tissue specific functions to better understand its clinical translational benefit. This review highlights the compelling evidence of overlapping and/or diverse functional and mechanisms regulated by CCN4, in addition to addressing the challenges, study limitations and knowledge gaps on CCN4 biology and its therapeutic potential.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies

OBJECTIVE

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.

DESIGN

We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.

RESULTS

Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.

CONCLUSIONS

Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Adenylate cyclase activates the cAMP signalling pathway to enhance platelet-rich plasma-treated Achilles tendon disease, a theoretical bioinformatics-based study

The effectiveness of platelet-rich plasma (PRP) for the treatment of Achilles tendon disorders still needs to be evaluated through a series of prospective studies, but genomic analysis can reveal the existence of complementary PRP treatment options. Based on the 96 platelet activation-related genes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we performed Gene Ontology functional enrichment analysis and KEGG enrichment analysis, pathway correlation analysis, and enrichment mapping to determine the enrichment results of the gene set enrichment analysis and found that the cAMP signalling pathway may be the key to enhancing the effectiveness of PRP treatment. The cAMP signalling pathway interacts with the Rap1 signalling pathway and cGMP-PKG signalling pathway to mediate the entire pathophysiological process of Achilles tendon disease. Moreover, ADCY1-9 may be the key to the activation of the cAMP signalling network. Further based on the data in the Gene Expression Omnibus database, it was found that ADCY4 and ADCY7 may be the players that play a major role, associated with the STAT4-ADCY4-LAMA5 axis and the GRbeta-ADCY7-SEMA3C axis, which is expected to be a complementary target for enhancing the efficacy of PRP in the treatment of Achilles tendon disease.

Integrated comparison of the mRNAome in cartilage, synovium, and macrophages in osteoarthritis

The precise molecular mechanisms associated with osteoarthritis (OA), the most common musculoskeletal disorder, are poorly understood. There are currently no effective treatments to prevent the initiation and progression of the disease. In recent years, the development of mRNAome has made it possible to identify new mechanisms and therapeutic targets. However, the differentially expressed genes screened by different microarrays are not completely the same. In order to avoid this shortcoming, we integrate the different genes from different tissues and data sets, and select the commonly expressed genes for further studies.

Systematic review of computed tomography parameters used for the assessment of subchondral bone in osteoarthritis

OBJECTIVE

To systematically review the published parameters for the assessment of subchondral bone in human osteoarthritis (OA) using computed tomography (CT) and gain an overview of current practices and standards.

DESIGN

A literature search of Medline, Embase and Cochrane Library databases was performed with search strategies tailored to each database (search from 2010 to January 2023). The search results were screened independently by two reviewers against pre-determined inclusion and exclusion criteria. Studies were deemed eligible if conducted in vivo/ex vivo in human adults (>18 years) using any type of CT to assess subchondral bone in OA. Extracted data from eligible studies were compiled in a qualitative summary and formal narrative synthesis.

RESULTS

This analysis included 202 studies. Four groups of CT modalities were identified to have been used for subchondral bone assessment in OA across nine anatomical locations. Subchondral bone parameters measuring similar features of OA were combined in six categories: (i) microstructure, (ii) bone adaptation, (iii) gross morphology (iv) mineralisation, (v) joint space, and (vi) mechanical properties.

CONCLUSIONS

Clinically meaningful parameter categories were identified as well as categories with the potential to become relevant in the clinical field. Furthermore, we stress the importance of quantification of parameters to improve their sensitivity and reliability for the evaluation of OA disease progression and the need for standardised measurement methods to improve their clinical value.

Revealing the impact of TOX3 on osteoarthritis: insights from bioinformatics

Osteoarthritis, a prevalent long-term condition of the joints, primarily impacts older individuals, resulting in discomfort, restrictions in mobility, and a decrease in overall well-being. Although Osteoarthritis is widely spread, there is a lack of successful interventions to stop the advancement of the condition. Numerous signaling pathways have been emphasized in recent research on Osteoarthritis, yet the diagnostic significance of numerous genes has not been investigated. To identify genes that were expressed differently in osteoarthritis, we utilized the Gene Expression Omnibus database. To identify marker genes, we built machine learning models including Least Absolute Shrinkage and Selection Operator and Random Forest. We categorized Osteoarthritis samples and performed immune cell infiltration analysis based on the expression patterns of these characteristic genes. Both the Least Absolute Shrinkage and Selection Operator and Random Forest models selected six marker genes (TOX3, ARG1, CST7, RERGL, COL11A1, NCRNA00185) out of a total of 17 differentially expressed genes. The osteoarthritis samples were categorized into two groups, namely a high expression group and a low expression group, based on the median levels of TOX3 expression. Comparative analysis of these groups identified 85 differentially expressed genes, showing notable enrichment in pathways related to lipid metabolism in the group with high expression. Analysis of immune cell infiltration revealed noticeable differences in immune profiles among the two groups. The group with high expression of TOX3 showed a notable increase in Mast cells and Type II IFN Response, whereas B cells, Cytolytic activity, Inflammation-promoting cells, NK cells, pDCs, T cell co-inhibition, Th1 cells, and Th2 cells were significantly decreased. We constructed a ceRNA network for TOX3, revealing 57 lncRNAs and 18 miRNAs involved in 57 lncRNA-miRNA interactions, and 18 miRNA-mRNA interactions with TOX3. Validation of TOX3 expression was confirmed using an external dataset (GSE29746), revealing a notable increase in Osteoarthritis samples. In conclusion, our study presents a comprehensive analysis identifying TOX3 as a potential feature gene in Osteoarthritis. The distinct immune profiles and involvement in fat metabolism pathways associated with TOX3 expression suggest its significance in Osteoarthritis pathogenesis. The study establishes a basis for comprehending the intricate correlation between characteristic genes and Osteoarthritis, as well as for the formulation of individualized therapeutic approaches.

COL3A1, COL5A1 and COL6A2 serve as potential molecular biomarkers for osteoarthritis based on weighted gene co‑expression network analysis bioinformatics analysis

Osteoarthritis (OA) is a non-inflammatory degenerative joint disease, characterized by joint pain and stiffness. The prevalence of OA increases with age. However, the relationship between biomarkers [collagen type III α1 (COL3A1), COL5A1, COL6A2, COL12A1] and OA remains unclear. The OA subchondral bone dataset GSE51588 was downloaded from the GEO database, and the differentially expressed genes (DEGs) were screened. Weighted gene co-expression network analysis was performed, and a protein-protein interaction network was constructed and further analyzed using Cytoscape and STRING. Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and then Gene Set Enrichment Analysis (GSEA) was used to formulate the molecular functions and pathways based on the results of GO and KEGG analyses. Comparative Toxicogenomics Database and TargetScan were used to identify the hub-gene-related diseases and the microRNAs that regulated the central hub genes. Immunohistochemical staining was performed to confirm the expression of related proteins in OA and non-OA tissue samples. A total of 1,679 DEGs were identified. GO analysis showed that the DEGs were primarily enriched in the process of 'immune system', 'extracellular region', 'secretory granule', 'collagen-containing extracellular matrix', 'ECM-receptor, glycosaminoglycan binding' and 'systemic lupus erythematosus'. The results of GSEA were similar to those of GO and KEGG enrichment terms for DEGs. A total of 25 important modules were generated, and two core gene clusters and seven core genes were obtained (COL6A2, COL5A2, COL12A1, COL5A1, COL6A1, LUM and COL3A1). Core genes were expressed differentially between OA subchondral bone and normal tissue samples. The expression levels of COL3A1, COL5A1 and COL6A2 in OA subchondral bone tissue were higher compared with those in normal tissues, but COL12A1 expression was not significantly increased; all stained markers were highly expressed in surrounding tissues of immunohistochemical staining. In conclusion, COL3A1, COL5A1 and COL6A2 may be potential molecular biomarkers for OA.

Mechanisms of tissue degeneration mediated by periostin in spinal degenerative diseases and their implications for pathology and diagnosis: a review

Periostin (POSTN) serves a dual role as both a matricellular protein and an extracellular matrix (ECM) protein and is widely expressed in various tissues and cells. As an ECM protein, POSTN binds to integrin receptors, transduces signals to cells, enabling cell activation. POSTN has been linked with various diseases, including atopic dermatitis, asthma, and the progression of multiple cancers. Recently, its association with orthopedic diseases, such as osteoporosis, osteoarthritis resulting from cartilage destruction, degenerative diseases of the intervertebral disks, and ligament degenerative diseases, has also become apparent. Furthermore, POSTN has been shown to be a valuable biomarker for understanding the pathophysiology of orthopedic diseases. In addition to serum POSTN, synovial fluid POSTN in joints has been reported to be useful as a biomarker. Risk factors for spinal degenerative diseases include aging, mechanical stress, trauma, genetic predisposition, obesity, and metabolic syndrome, but the cause of spinal degenerative diseases (SDDs) remains unclear. Studies on the pathophysiological effects of POSTN may significantly contribute toward the diagnosis and treatment of spinal degenerative diseases. Therefore, in this review, we aim to examine the mechanisms of tissue degeneration caused by mechanical and inflammatory stresses in the bones, cartilage, intervertebral disks, and ligaments, which are crucial components of the spine, with a focus on POSTN.

PSD95 as a New Potential Therapeutic Target of Osteoarthritis: A Study of the Identification of Hub Genes through Self-Contrast Model

Osteoarthritis (OA) is a worldwide joint disease. However, the precise mechanism causing OA remains unclear. Our primary aim was to identify vital biomarkers associated with the mechano-inflammatory aspect of OA, providing potential diagnostic and therapeutic targets for OA. Thirty OA patients who underwent total knee arthroplasty were recruited, and cartilage samples were obtained from both the lateral tibial plateau (LTP) and medial tibial plateau (MTP). GO and KEGG enrichment analyses were performed, and the protein-protein interaction (PPI) assessment was conducted for hub genes. The effect of PSD95 inhibition on cartilage degeneration was also conducted and analyzed. A total of 1247 upregulated and 244 downregulated DEGs were identified. Significant differences were observed between MTP and LTP in mechanical stress-related genes and activated sensory neurons based on a self-contrast model of human knee OA. Cluster analysis identified DLG4 as the hub gene. Cyclic loading stress increased PSD95 (encoded by DLG4) expression in LTP cartilage, and PSD95 inhibitors could alleviate OA progression. This study suggests that inhibiting PSD95 could be a potential therapeutic strategy for preventing articular cartilage degradation.

[Identification of Characteristic lncRNA Molecular Markers in Osteoarthritis by Integrating GEO Database and Machine Learning Strategies and Experimental Validation]

Objective

To screen for long non-coding RNA (lncRNA) molecular markers characteristic of osteoarthritis (OA) by utilizing the Gene Expression Omnibus (GEO) database combined with machine learning.

Methods

The samples of 185 OA patients and 76 healthy individuals as normal controls were included in the study. GEO datasets were screened for differentially expressed lncRNAs. Three algorithms, the least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF), were used to screen for candidate lncRNA models and receiver operating characteristic (ROC) curves were plotted to evaluate the models. We collected the peripheral blood samples of 30 clinical OA patients and 15 health controls and measured the immunoinflammatory indicators. RT-PCR was performed for quantitative analysis of the expression of lncRNA molecular markers in peripheral blood mononuclear cells (PBMC). Pearson analysis was performed to examine the correlation between lncRNA and indicators for inflammation of the immune system.

Results

A total of 14 key markers were identified with LASSO, 6 genes were identified with SVM-RFE, and 24 genes were identified with RF. Venn diagram was used to screen for overlapping genes identified with the three algorithms, showing HOTAIR, H19, MIR155 HG, and NKILA to be the overlapping genes. The ROC curves showed that these four lncRNAs all had an area under the curve ( AUC) greater than 0.7. The RT-PCR findings revealed relatively elevated expression of HOTAIR, H19, and MIR155HG and decreased expression of NKILA in the PBMC of OA patients compared with those of the normal group ( P<0.01). The results were consistent with the bioinformatics predictions. Pearson analysis showed that the candidate lncRNAs were correlated with clinical indicators for inflammation.

Conclusion

HOTAIR, H19, MIR155 HG, and NKILA can be used as molecular markers for the clinical diagnosis of OA and are correlate with clinical indicators of inflammation of the immune system.

Comprehensive analysis on subchondral bone marrow lesions of human osteoarthritis by integrating bulk and single-cell transcriptomes

OBJECTIVE

This study aims to demonstrate the cellular composition and underlying mechanisms in subchondral bone marrow lesions (BMLs) of knee osteoarthritis (OA).

METHODS

BMLs were assessed by MRI Osteoarthritis Knee Score (MOAKS)≥2. Bulk RNA-sequencing (bulk-seq) and BML-specific differentially expressed genes (DEGs) analysis were performed among subchondral bone samples (including OA-BML=3, paired OA-NBML=3; non-OA=3). The hub genes of BMLs were identified by verifying in independent datasets and multiple bioinformatic analyses. To further estimate cell-type composition of subchondral bone, we utilized two newly developed deconvolution algorithms (MuSiC, MCP-counter) in transcriptomic datasets, based on signatures from open-accessed single-cell RNA sequencing (scRNA-seq). Finally, competing endogenous RNA (ceRNA) and transcription factor (TF) networks were constructed through multiple predictive databases, and validated by public non-coding RNA profiles.

RESULTS

A total of 86 BML-specific DEGs (up 79, down 7) were identified. IL11 and VCAN were identified as core hub genes. The "has-miR-424-5p/lncRNA PVT1" was determined as crucial network, targeting IL11 and VCAN, respectively. More importantly, two deconvolution algorithms produced approximate estimations of cell-type composition, and the cluster of heterotopic-chondrocyte was discovered abundant in BMLs, and positively correlated with the expression of hub genes.

CONCLUSION

IL11 and VCAN were identified as the core hub genes of BMLs, and their molecular networks were determined as well. We profiled the characteristics of subchondral bone at single-cell level and determined that the heterotopic-chondrocyte was abundant in BMLs and was closely linked to IL11 and VCAN. Our study may provide new insights into the microenvironment and pathological molecular mechanism of BMLs, and could lead to novel therapeutic strategies.

Characterization of aberrant glycosylation associated with osteoarthritis based on integrated glycomics methods

BACKGROUND

Osteoarthritis (OA) is the most common form of arthritis, affecting millions of aging people. Investigation of abnormal glycosylation is essential for the understanding of pathological mechanisms of OA.

METHODS

The total protein was isolated from OA (n = 13) and control (n = 11) cartilages. Subsequently, glycosylation alterations of glycoproteins in OA cartilage were investigated by lectin microarrays and intact glycopeptides analysis. Finally, the expression of glycosyltransferases involved in the synthesis of altered glycosylation was assessed by qPCR and GEO database.

RESULTS

Our findings revealed that several glycopatterns, such as α-1,3/6 fucosylation and high-mannose type of N-glycans were altered in OA cartilages. Notably, over 27% of identified glycopeptides (109 glycopeptides derived from 47 glycoproteins mainly located in the extracellular region) disappeared or decreased in OA cartilages, which is related to the cartilage matrix degradation. Interestingly, the microheterogeneity of N-glycans on fibronectin and aggrecan core protein was observed in OA cartilage. Our results combined with GEO data indicated that the pro-inflammatory cytokines altered the expression of glycosyltransferases (ALG3, ALG5, MGAT4C, and MGAT5) which may contribute to the alterations in glycosylation.

CONCLUSION

Our study revealed the abnormal glycopatterns and heterogeneities of site-specific glycosylation associated with OA. To our knowledge, it is the first time that the heterogeneity of site-specific N-glycans was reported in OA cartilage. The results of gene expression analysis suggested that the expression of glycosyltransferases was impacted by pro-inflammatory cytokines, which may facilitate the degradation of protein and accelerate the process of OA. Our findings provide valuable information for the understanding of molecular mechanisms in the pathogenesis of OA.

Bioinformatics and system biology approach to identify potential common pathogenesis for COVID-19 infection and osteoarthritis

A growing of evidence has showed that patients with osteoarthritis (OA) had a higher coronavirus 2019 (COVID-19) infection rate and a poorer prognosis after infected it. Additionally, scientists have also discovered that COVID-19 infection might cause pathological changes in the musculoskeletal system. However, its mechanism is still not fully elucidated. This study aims to further explore the sharing pathogenesis of patients with both OA and COVID-19 infection and find candidate drugs. Gene expression profiles of OA (GSE51588) and COVID-19 (GSE147507) were obtained from the Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) for both OA and COVID-19 were identified and several hub genes were extracted from them. Then gene and pathway enrichment analysis of the DEGs were performed; protein-protein interaction (PPI) network, transcription factor (TF)-gene regulatory network, TF-miRNA regulatory network and gene-disease association network were constructed based on the DEGs and hub genes. Finally, we predicted several candidate molecular drugs related to hub genes using DSigDB database. The receiver operating characteristic curve (ROC) was applied to evaluate the accuracy of hub genes in the diagnosis of both OA and COVID-19. In total, 83 overlapping DEGs were identified and selected for subsequent analyses. CXCR4, EGR2, ENO1, FASN, GATA6, HIST1H3H, HIST1H4H, HIST1H4I, HIST1H4K, MTHFD2, PDK1, TUBA4A, TUBB1 and TUBB3 were screened out as hub genes, and some showed preferable values as diagnostic markers for both OA and COVID-19. Several candidate molecular drugs, which are related to the hug genes, were identified. These sharing pathways and hub genes may provide new ideas for further mechanistic studies and guide more individual-based effective treatments for OA patients with COVID-19 infection.

Periostin regulation and cartilage degradation early after anterior cruciate ligament reconstruction

OBJECTIVE AND DESIGN

The purpose of this study was to explore pathological processes during the first 4 weeks after anterior cruciate ligament reconstruction (ACLR).

SUBJECTS

Sixteen ACL-injured patients (8 females/8 males, mean age = 19.1, mean BMI = 28.6).

METHODS

Arthrocentesis was performed 1 and 4 weeks after ACLR. Proteins in the synovial fluid were identified using nanoLC-ESI-MS/MS. Differentially up- or down-regulated proteins were identified and quantified, and a pathway analysis was performed. All identified proteins were mapped into a protein-protein interaction (PPI) network, and networks of PPIs with a combined score > 0.9 were then visualized.

RESULTS

Seven pathways were upregulated after ACLR: PI3K-AKT signaling pathway, extracellular matrix (ECM)-receptor interaction, focal adhesion, protein digestion and absorption, ameobiasis, and platelet activation. Network analyses identified 8 proteins that were differentially upregulated with strong PPI interactions (periostin and 7 collagen-related proteins). Increases in periostin moderately correlated with increases in a synovial fluid biomarker of type II cartilage degradation (ρ = 0.51, p = 0.06).

CONCLUSION

Pro-inflammatory pathways and periostin were upregulated after ACLR. Periostin demonstrated strong network connections with markers of collagen breakdown, and future work is needed to determine whether periostin may offer a biomarker of early cartilage degradation after ACLR and/or play an active role in early post-traumatic osteoarthritis (PTOA) progression.

Molecular crosstalk between articular cartilage, meniscus, synovium, and subchondral bone in osteoarthritis

AIMS

Osteoarthritis (OA) is a common degenerative joint disease worldwide, which is characterized by articular cartilage lesions. With more understanding of the disease, OA is considered to be a disorder of the whole joint. However, molecular communication within and between tissues during the disease process is still unclear. In this study, we used transcriptome data to reveal crosstalk between different tissues in OA.

METHODS

We used four groups of transcription profiles acquired from the Gene Expression Omnibus database, including articular cartilage, meniscus, synovium, and subchondral bone, to screen differentially expressed genes during OA. Potential crosstalk between tissues was depicted by ligand-receptor pairs.

RESULTS

During OA, there were 626, 97, 1,060, and 2,330 differentially expressed genes in articular cartilage, meniscus, synovium, and subchondral bone, respectively. Gene Ontology enrichment revealed that these genes were enriched in extracellular matrix and structure organization, ossification, neutrophil degranulation, and activation at different degrees. Through ligand-receptor pairing and proteome of OA synovial fluid, we predicted ligand-receptor interactions and constructed a crosstalk atlas of the whole joint. Several interactions were reproduced by transwell experiment in chondrocytes and synovial cells, including TNC-NT5E, TNC-SDC4, FN1-ITGA5, and FN1-NT5E. After lipopolysaccharide (LPS) or interleukin (IL)-1β stimulation, the ligand expression of chondrocytes and synovial cells was upregulated, and corresponding receptors of co-culture cells were also upregulated.

CONCLUSION

Each tissue displayed a different expression pattern in transcriptome, demonstrating their specific roles in OA. We highlighted tissue molecular crosstalk through ligand-receptor pairs in OA pathophysiology, and generated a crosstalk atlas. Strategies to interfere with these candidate ligands and receptors may help to discover molecular targets for future OA therapy.Cite this article: Bone Joint Res 2022;11(12):862-872.

Serum periostin level is not sufficient to serve as a clinically applicable biomarker of osteoarthritis

BACKGROUND

Emerging knowledge has highlighted the role of periostin (POSTN) in osteoarthritis (OA) process; however, whether POSTN is suitable as a biomarker of OA remains unclear. This study aimed to investigate the potential value of POSTN as a biomarker of OA.

METHODS

Ten 6-month-old female Sprague-Dawley (SD) rats were used in this study. Five rats underwent ovariectomy (OVX) operation and the others were carried out sham operation. Thirty-two patients with OA and eighteen patients who had meniscus injuries or ligament injuries but with intact articular cartilages were recruited in this study from January to July 2019 at the Peking University International Hospital. We first detected the expression of POSTN in the cartilage of OVX induced OA rats and different compartments of the knee joint in patients with OA using immunohistochemistry. Besides, serum POSTN levels in patients with or without OA were examined using enzyme-linked immunosorbent assay (ELISA). The associations among serum POSTN levels, clinical symptoms, and radiological severity were assessed according to the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores and, Kellgren-Lawrence (KL) grading, respectively. Finally, multivariable cumulative link models were established to evaluate the validity of serum POSTN level as a predictor of knee OA.

RESULTS

The significantly higher POSTN expression was found in OVX-OA rats than Sham rats, while, the expression of POSTN was significantly higher in the torn cartilage of patients with OA. However, the serum POSTN level did not differ significantly between patients with and without OA. Additionally, we found no remarkable associations between serum POSTN level and WOMAC scores and KL grading. Subsequent analysis revealed that serum POSTN was not a significant predictor of OA.

CONCLUSION

Thus, although POSTN may be involved OA process and local POSTN is valuable in disease diagnosis and distinguishing of the severity of disease, its serum level is not sufficient to serve as a candidate biomarker of OA given the current analysis technology.

Identification of cellular heterogeneity and immunogenicity of chondrocytes via single-cell RNA sequencing technique in human osteoarthritis

Background: Osteoarthritis (OA) has placed a heavy burden to the economy and humanistics. To explore the biological functions and markers of chondrocytes contributes significantly to the accurate diagnosis and targeted treatment of OA.

Methods: We systematically analyzed the immunogenicity and biological function of varied chondrocytes at single cell resolution, and identified the chondrocyte subtypes and biomarkers involved in the development of OA, which are verified in the bulk sequencing cohort.

Results: Based on previous study, we defined eight subtypes of chondrocytes with different biological functions, finding out that effector chondrocytes (ECs) and fibrocartilage chondrocytes (FCs) may promote the development of OA. Compared with other chondrocytes, ECs and FCs show stronger immunogenicity. FCs mainly affects the degeneration of cartilage caused by fibrous degeneration, while ECs mainly exerts immune function and causes tissues inflammation. In addition, the canonical gene markers of EC and FC assist with the prediction of OA, which has been verified in Bulk RNA sequencing data from two GEO datasets.

Conclusion: In summary, this study provides a new perspective for the exploration of cellular heterogeneity and pathophysiology in OA and will make contribution to the accurate diagnosis and targeted treatment of OA.

Quantifying the Human Subchondral Trabecular Bone Microstructure in Osteoarthritis with Clinical CT

Osteoarthritis (OA) is characterized by critical alterations of the subchondral bone microstructure, besides the well-known cartilaginous changes. Clinical computed tomography (CT) detection of quantitative 3D microstructural subchondral bone parameters is applied to monitor changes of subchondral bone structure in different stages of human OA and is compared with micro-CT, the gold standard. Determination by clinical CT (287 µm resolution) of key microstructural parameters in tibial plateaus with mild-to-moderate and severe OA reveals strong correlations to micro-CT (35 µm), high inter- and intraobserver reliability, and small relative differences. In vivo, normal, mild-to-moderate, and severe OA are compared with clinical CT (331 µm). All approaches detect characteristic expanded trabecular structure in severe OA and fundamental microstructural correlations with clinical OA stage. Multivariate analyses at various in vivo and ex vivo imaging resolutions always reliably separate mild-to-moderate from severe OA (except mild-to-moderate OA from normal), revealing a striking similarity between 287 µm clinical and 35 µm micro-CT. Thus, accurate structural measurements using clinical CT with a resolution near the trabecular dimensions are possible. Clinical CT offers an opportunity to quantitatively monitor subchondral bone microstructure in clinical and experimental settings as an advanced tool of investigating OA and other diseases affecting bone architecture.

Comprehensive comparative analysis of histopathology and gene expression in subchondral bone between kashin-beck disease and primary osteoarthritis

Kashin-Beck disease (KBD) is an endemic, degenerative osteoarthropathy that exhibits some similar characteristics to osteoarthritis (OA) but with different etiologies and pathogeneses. In addition to cartilage damage, microstructural changes of bone were observed in KBD. This study aimed to comparatively demonstrate the general histopathological changes, transcriptomics, and differentially expressed miRNAs of subchondral bone between KBD and OA. Tibial plateau subchondral bone samples were collected from eighteen patients with KBD and eighteen patients with OA. Histopathological changes were examined by hematoxylin-eosin (HE) staining, safranin O-fast green staining, and picrosirius red staining. RNA sequencing and miRNA array analysis were performed to screen the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs), respectively. The subchondral bone samples of the tibial plateau of KBD and OA both showed increased thickness and sclerosis. A total of 179 DEGs and 124 DEMs were identified in subchondral bone between KBD and OA, which were involved in several vital GO terms and KEGG signaling pathways. Our results suggest that the pathological mechanisms of subchondral bone are different between KBD and OA, although they exhibit similar histopathological features. Integrated analysis revealed several genes such as ADAMTS14, SLC13A5, and CEACAM1, that may be crucial DEGs in subchondral bone between KBD and OA, suggesting that these genes could serve as potential differential diagnostic biomarkers for subchondral bone lesions in KBD and OA. These findings provide valuable information for further clarifying pathological changes in subchondral bone in KBD and OA.

Multi-omics molecular biomarkers and database of osteoarthritis

Osteoarthritis (OA) is the most common form of arthritis in the adult population and is a leading cause of disability. OA-related genetic loci may play an important role in clinical diagnosis and disease progression. With the rapid development of diverse technologies and omics methods, many OA-related public data sets have been accumulated. Here, we retrieved a diverse set of omics experimental results from 159 publications, including genome-wide association study, differentially expressed genes and differential methylation regions, and 2405 classified OA-related gene markers. Meanwhile, based on recent single-cell RNA-seq data from different joints, 5459 cell-type gene markers of joints were collected. The information has been integrated into an online database named OAomics and molecular biomarkers (OAOB). The database (http://ibi.zju.edu.cn/oaobdb/) provides a web server for OA marker genes, omics features and so on. To our knowledge, this is the first database of molecular biomarkers for OA.

Identification of mechanics-responsive osteocyte signature in osteoarthritis subchondral bone

Aims

Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA.

Methods

Gene expression profiles of OA subchondral bone were used to identify disease-relevant genes and signalling pathways. RNA-sequencing data of a bone loading model were used to identify the loading-responsive gene set. Weighted gene co-expression network analysis (WGCNA) was employed to develop the osteocyte mechanics-responsive gene signature.

Results

A group of 77 persistent genes that are highly relevant to extracellular matrix (ECM) biology and bone remodelling signalling were identified in OA subchondral lesions. A loading responsive gene set, including 446 principal genes, was highly enriched in OA medial tibial plateaus compared to lateral tibial plateaus. Of this gene set, a total of 223 genes were identified as the main contributors that were strongly associated with osteocyte functions and signalling pathways, such as ECM modelling, axon guidance, Hippo, Wnt, and transforming growth factor beta (TGF-β) signalling pathways. We limited the loading-responsive genes obtained via the osteocyte transcriptome signature to identify a subgroup of genes that are highly relevant to osteocytes, as the mechanics-responsive osteocyte signature in OA. Based on WGCNA, we found that this signature was highly co-expressed and identified three clusters, including early, late, and persistently responsive genes.

Conclusion

In this study, we identified the mechanics-responsive osteocyte signature in OA-lesioned subchondral bone.

Cite this article: Bone Joint Res 2022;11(6):362–370.

Elevation of α-1,3 fucosylation promotes the binding ability of TNFR1 to TNF-α and contributes to osteoarthritic cartilage destruction and apoptosis

Background

Osteoarthritis (OA) is the most common form of arthritis and is characterized by the degradation of articular cartilage and inflammation of the synovial membrane. Fucosylation is an important feature of protein N/O-glycosylation and is involved in a variety of pathological processes, including inflammation and cancer. However, whether fucosylation impacts the OA pathological process is unknown.

Methods

Total proteins were extracted from cartilage samples obtained from patients with OA (n = 11) and OA rabbit models at different time points (n = 12). OA-associated abnormal glycopatterns were evaluated by lectin microarrays and lectin blots. The expression of fucosyltransferases involved in the synthesis of α-1,3 fucosylation was assessed by semi-qPCR. The synthesis of α-1,3 fucosylation mediated by FUT10 was interrupted by the transfection of siRNA, and the effect of α-1,3 fucosylation on OA-associated events was assessed. Then, immunoprecipitation and lectin blotting were used to investigate the relationship between the α-1,3 fucosylation level of tumor necrosis factor receptor superfamily member 1A (TNFR1) and OA. Finally, a TNFR1 antibody microarray was fabricated to evaluate the effect of α-1,3 fucosylation on the ability of TNFR1 to bind to tumor necrosis factor-α (TNF-α).

Results

Elevated α-1,3 fucosylation was observed in cartilage from OA patients, rabbit models, and chondrocytes induced by TNF-α (fold change> 2, p< 0.01). Our results and the GEO database indicated that the overexpression of FUT10 contributed to this alteration. Silencing the expression of FUT10 impaired the ability of TNFR1 to bind to TNF-α, impeded activation of the NF-κB and P38/JNK-MAPK pathways, and eventually retarded extracellular matrix (ECM) degradation, senescence, and apoptosis in chondrocytes exposed to TNF-α.

Conclusion

The elevation of α-1,3 fucosylation is not only a characteristic of OA but also impacts the OA pathological process. Our work provides a new positive feedback loop of “inflammation conditions/TNF-α/FUT10/α-1,3 fucosylation of TNFR1/NF-κB and P38/JNK-MAPK pathways/proinflammatory processes” that contributes to ECM degradation and chondrocyte apoptosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-022-02776-z.

Leptin in Osteoarthritis and Rheumatoid Arthritis: Player or Bystander?

White adipose tissue (WAT) is a specialized tissue whose main function is lipid synthesis and triglyceride storage. It is now considered as an active organ secreting a plethora of hormones and cytokines namely adipokines. Discovered in 1994, leptin has emerged as a key molecule with pleiotropic functions. It is primarily recognized for its role in regulating energy homeostasis and food intake. Currently, further evidence suggests its potent role in reproduction, glucose metabolism, hematopoiesis, and interaction with the immune system. It is implicated in both innate and adaptive immunity, and it is reported to contribute, with other adipokines, in the cross-talking networks involved in the pathogenesis of chronic inflammation and immune-related diseases of the musculo-skeletal system such as osteoarthritis (OA) and rheumatoid arthritis (RA). In this review, we summarize the most recent findings concerning the involvement of leptin in immunity and inflammatory responses in OA and RA.

Gene expression analysis of subchondral bone, cartilage, and synovium in naturally occurring equine palmar/plantar osteochondral disease

Osteoarthritis (OA) is a disease of the entire joint but the relationship between pathological events in various joint tissues is poorly understood. We examined concurrent changes in bone, cartilage, and synovium in a naturally occurring equine model of joint degeneration. Joints (n = 64) were grossly assessed for palmar/plantar osteochondral disease (POD) in racehorses that required euthanasia for unrelated reasons and assigned a grade of 0 (n = 34), 1 (n = 17), 2 or 3 (n = 13) using a recognized grading scheme. Synovium, cartilage, and subchondral bone were collected for histological and gene expression analysis. Relations between POD grade, cartilage histological score, and gene expression levels were examined using one-way analysis of variance or Kruskal-Wallis test and Spearman's correlation coefficient with corrections for multiple comparisons. Cartilage histological score increased in joints with POD grade 1 (p = 0.002) and 2 or 3 (p < 0.001) compared to 0. At grade 1, expression of COL1A1, COL2A1, and MMP1 increased and BGN decreased in subchondral bone while expression of BGN and ACAN decreased in cartilage. These changes further progressed at grades 2 and 3. POD grades 2 and 3 were associated with decreased expression of osteoclast inhibitor OPG and increased markers of cartilage degeneration (MMP13, COL1A1). Expression of the vascular endothelial growth factor decreased with POD grade and negatively correlated with cartilage histological score. Synovium showed no histological or transcriptomic changes related to pathology grade. Cartilage degeneration in POD is likely to be secondary to remodeling of the subchondral bone. Limited activation of proinflammatory and catabolic genes and moderate synovial pathology suggests distinct molecular phenotype of POD compared with OA.

Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis

Background

A chronic progressive degenerative joint disease, such as osteoarthritis (OA) is positively related to age. The medical economy is facing a major burden, because of the high disability rate seen in patients with OA. Therefore, to prevent and treat OA, exploring the diagnostic biomarkers of OA will be of great significance.

Methods

Differentially expressed genes (DEGs) were obtained from the Gene Expression Omnibus database using the RobustRankAggreg R package, and a protein–protein interaction network was constructed. The module was obtained from Cytoscape, and the four algorithms of degree, MNC, closeness, and MCC in CytoHubba were used to identify the hub genes. A diagnostic model was constructed using Support Vector Machines (SVM), and the ability of the model to predict was evaluated by other cohorts.

Results

From normal and OA samples, 136 DEGs were identified, out of which 45 were downregulated in the normal group and 91 were upregulated in the OA group. These genes were associated with the extracellular matrix-receptor interactions, the PI3K-Akt signaling pathway, and the protein digestion and absorption pathway, as per a functional enrichment analysis. Finally, we identified the 7 hub genes (COL6A3, COL1A2, COL1A1, MMP2, COL3A1, POST, and FN1). These genes have important roles and are widely involved in the immune response, apoptosis, inflammation, and bone development. These 7 genes were used to construct a diagnostic model by SVM, and it performed well in different cohorts. Additionally, we verified the methylation expression of these hub genes.

Conclusions

The 7-genes signature can be used for the diagnosis of OA and can provide new ideas in the clinical decision-making for patients with OA.

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.

Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits ("endophenotypes"), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.

Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics

Background: Osteoarthritis (OA) is one of the main causes of disability in the elderly population, accompanied by a series of underlying pathologic changes, such as cartilage degradation, synovitis, subchondral bone sclerosis, and meniscus injury. The present study aimed to identify key genes, signaling pathways, and miRNAs in knee OA associated with the entire joint components, and to explain the potential mechanisms using computational analysis.

Methods: The differentially expressed genes (DEGs) in cartilage, synovium, subchondral bone, and meniscus were identified using the Gene Expression Omnibus 2R (GEO2R) analysis based on dataset from GSE43923, GSE12021, GSE98918, and GSE51588, respectively and visualized in Volcano Plot. Venn diagram analyses were performed to identify the overlapping DEGs (overlapping DEGs) that expressed in at least two types of tissues mentioned above. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, protein-protein interaction (PPI) analysis, and module analysis were conducted. Furthermore, qRT-PCR was performed to validate above results using our clinical specimens.

Results: As a result, a total of 236 overlapping DEGs were identified, of which 160 were upregulated and 76 were downregulated. Through enrichment analysis and constructing the PPI network and miRNA-mRNA network, knee OA-related key genes, such as HEY1, AHR, VEGFA, MYC, and CXCL12 were identified. Clinical validation by qRT-PCR experiments further supported above computational results. In addition, knee OA-related key miRNAs such as miR-101, miR-181a, miR-29, miR-9, and miR-221, and pathways such as Wnt signaling, HIF-1 signaling, PI3K-Akt signaling, and axon guidance pathways were also identified. Among above identified knee OA-related key genes, pathways and miRNAs, genes such as AHR, HEY1, MYC, GAP43, and PTN, pathways like axon guidance, and miRNAs such as miR-17, miR-21, miR-155, miR-185, and miR-1 are lack of research and worthy for future investigation.

Conclusion: The present informatic study for the first time provides insight to the potential therapeutic targets of knee OA by comprehensively analyzing the overlapping genes differentially expressed in multiple joint components and their relevant signaling pathways and interactive miRNAs.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Osteoarthritis: Current Molecular Biomarkers and the Way Forward

The ultimate hope of researchers and patients is a pathway to development of treatments for osteoarthritis to modify the disease process in addition to the symptoms. However, development of disease modifying drugs requires objective endpoints such as measures of joint structure, joint tissue homeostasis and/or joint survival-measures such as provided by imaging biomarkers, molecular biomarkers and joint replacement frequency, respectively. Although biomarkers supporting investigational drug use and drug approval include surrogate endpoints that may not necessarily reflect or directly correlate with the clinical outcome of interest, a formal biomarker qualification process currently exists that is a rigorous three stage process that yields biomarker approvals (or denials) for specific contexts of use. From a cost perspective, biochemical biomarkers are the 'ones to beat'; however, even well-validated biomarkers may not cross the translation gaps for eventual use in healthcare unless they offer an advantage in terms of cost per quality adjusted life year. This review summarizes the case FOR and AGAINST biomarkers in drug development and highlights the current data for a subset of biomarkers in the osteoarthritis research field informing on cartilage homeostasis, joint inflammation and altered subchondral bone remodeling.

PR11-364P22.2/ATF3 protein interaction mediates IL-1β-induced catabolic effects in cartilage tissue and chondrocytes

Osteoarthritis (OA) is a degenerative joint disease which lacks effective medical treatment due to ill-defined molecular mechanisms underlying the pathology. Inflammation is a key factor that induces and aggravates OA. Therefore, the current study aims to explore roles of the dysregulated long non-coding RNAs in the pro-inflammatory cytokine IL-1β-mediated catabolic effects in cartilage tissue and chondrocytes. We identified RP11-364P22.2 as dysregulated in OA patient-derived cartilage tissues and highly responsive to IL-1β stimulus. RNA pull-down coupled with mass spectrometry demonstrated that RP11-364P22.2 physically binds to activating transcription factor 3 (ATF3) and thus increases the protein stability and facilitates its nuclear translocation. Loss- and gain-of-function assays indicated that the interaction between RP11-364P22.2 and ATF3 is indispensable for the detrimental effects of IL-1β including growth inhibition, apoptosis induction as well as degradation of the key chondrocyte structural proteins of type II collage and Aggrecan and synthesis of the extracellular matrix-degrading enzyme MMP13 in chondrocytes. In vivo, depletion of the RP11-364P22.2 effector ATF3 drastically prevented OA development in the rats with surgical destabilization of the medial meniscus (DMM). These results highlight the important roles of lncRNAs in the pathogenesis of OA and indicate the RP11-364P22.2/ATF3 regulatory axis as a potential therapeutic target of inflammation-induced OA.

Analysis of spatial osteochondral heterogeneity in advanced knee osteoarthritis exposes influence of joint alignment

Osteoarthritis (OA) is considerably affected by joint alignment. Here, we investigate the patterns of spatial osteochondral heterogeneity in patients with advanced varus knee OA together with clinical data. We report strong correlations of osteochondral parameters within individual topographical patterns, highlighting their fundamental and location-dependent interactions in OA. We further identify site-specific effects of varus malalignment on the lesser loaded compartment and, conversely, an unresponsive overloaded compartment. Last, we trace compensatory mechanisms to the overloaded subarticular spongiosa in patients with additional high body weight. We therefore propose to consider and to determine axial alignment in clinical trials when selecting the location to assess structural changes in OA. Together, these findings broaden the scientific basis of therapeutic load redistribution and weight loss in varus knee OA.

Intra-articular silencing of periostin via nanoparticle-based siRNA ameliorates post-traumatic osteoarthritis in mice

OBJECTIVE

Recent evidence delineates an emerging role of Periostin (Postn) in osteoarthritis (OA) as its expression subsequent to knee injury is detrimental to the articular cartilage. We hypothesize that intra-articular knockdown of Postn in a murine model of post-traumatic OA would ameliorate OA.

METHODS

Post-traumatic OA was induced in 10-week-old male C57BL/6J mice (n=24) by destabilization of the medial meniscus (DMM) and analyzed 8-week post-surgery. Intra-articular Postn was inhibited by siRNA using a novel peptide-nucleotide polyplex. Cartilage degeneration (OARSI score) and synovitis were assessed histologically. Bone changes were measured by μCT. The effect and mechanism of Postn silencing were investigated in human chondrocytes treated with IL-1β with or without IKK2 inhibitor, SC-514.

RESULTS

Peptide-siRNA nanoplatform significantly abolished Postn expression. OARSI score was significantly less in mice receiving Postn siRNA (10.94±0.66) compared to both untreated (22.38±1.30,P=0.002) and scrambled siRNA (22.69±0.87,P=0.002) treatment. No differences were observed in synovitis. Subchondral bone sclerosis, BV/TV, vBMD, and heterotopic ossification were significantly low in Postn siRNA treatment. Immunostaining of cartilage revealed that Postn knockdown reduced the DMM-induced MMP-13 intensity, phosphorylation of p65, and immunoreactivity of aggrecan neoepitope, DIPEN. Postn knockdown also suppressed IL-1β-induced MMP-13 and ADAMTS-4 in chondrocytes. Mechanistically, Postn-induced MMP-13 was abrogated by SC-514 demonstrating a link between Postn and NF-κB.

CONCLUSION

Intra-articular delivery of Postn siRNA nanocomplex represents a promising clinical approach to mitigate the severity of joint degeneration and provides an unequivocal scientific rationale for longitudinal studies. Employing a cartilage-specific gene knockout strategy will further illuminate the functional role of Postn in OA.

Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis

BACKGROUND

Osteoarthritis (OA) is a worldwide musculoskeletal disorder. However, disease-modifying therapies for OA are not available. Here, we aimed to characterize the molecular signatures of OA and to identify novel therapeutic targets and strategies to improve the treatment of OA.

METHODS

We collected genome-wide transcriptome data performed on 132 OA and 74 normal human cartilage or synovium tissues from 7 independent datasets. Differential gene expression analysis and functional enrichment were performed to identify genes and pathways that were dysregulated in OA. The computational drug repurposing method was used to uncover drugs that could be repurposed to treat OA.

RESULTS

We identified several pathways associated with the development of OA, such as extracellular matrix organization, inflammation, bone development, and ossification. By protein-protein interaction (PPI) network analysis, we prioritized several hub genes, such as JUN, CDKN1A, VEGFA, and FOXO3. Moreover, we repurposed several FDA-approved drugs, such as cardiac glycosides, that could be used in the treatment of OA.

CONCLUSIONS

We proposed that the hub genes we identified would play a role in cartilage homeostasis and could be important diagnostic and therapeutic targets. Drugs such as cardiac glycosides provided new possibilities for the treatment of OA.

Periostin loss-of-function protects mice from post-traumatic and age-related osteoarthritis

Background

Elevated levels of periostin (Postn) in the cartilage and bone are associated with osteoarthritis (OA). However, it remains unknown whether Postn loss-of-function can delay or prevent the development of OA. In this study, we sought to better understand the role of Postn in OA development and assessed the functional impact of Postn deficiency on post-traumatic and age-related OA in mice.

Methods

The effects of Postn deficiency were studied in two murine experimental OA models using Postn^−/− (n = 32) and littermate wild-type (wt) mice (n = 36). Post-traumatic OA was induced by destabilization of the medial meniscus (DMM) in 10-week-old mice (n = 20); age-related OA was analyzed in 24-month-old mice (n = 13). Cartilage degeneration was assessed histologically using the OARSI scoring system, and synovitis was evaluated by measuring the synovial lining cell layer and the cells density in the synovial stroma. Bone changes were measured by μCT analysis. Serum levels of Postn were determined by ELISA. Expression of Postn and collagenase-3 (MMP-13) was measured by immunostaining. RNA-seq was performed on chondrocytes isolated from 21-day old Postn^−/− (n = 3) and wt mice (n = 3) to discover genes and pathways altered by Postn knockout.

Results

Postn^−/− mice exhibited significantly reduced cartilage degeneration and OARSI score relative to wt mice in post-traumatic OA after 8 weeks (maximum: 2.37 ± 0.74 vs. 4.00 ± 1.20, P = 0.011; summed: 9.31 ± 2.52 vs. 21.44 ± 6.01, P = 0.0002) and spontaneous OA (maximum: 1.93 ± 0.45 vs. 3.58 ± 1.16, P = 0.014; summed: 6.14 ± 1.57 vs. 11.50 ± 3.02, P = 0.003). Synovitis was significantly lower in Postn^−/− mice than wt only in the DMM model (1.88 ± 1.01 vs. 3.17 ± 0.63; P = 0.039). Postn^−/− mice also showed lower trabecular bone parameters such as BV/TV, vBMD, Tb.Th, and Tb.N and high Tb. Sp in both models. Postn^−/− mice had negligible levels of serum Postn compared with wt. Immunofluorescent studies of cartilage indicated that Postn^−/− mice expressed lower MMP-13 levels than wt mice. RNA-seq revealed that cell-cell-adhesion and cell-differentiation processes were enriched in Postn^−/− mice, while those related to cell-cycle and DNA-repair were enriched in wt mice.

Conclusions

Postn deficiency protects against DMM-induced post-traumatic and age-related spontaneous OA. RNA-seq findings warrant further investigations to better understand the mechanistic role of Postn and its potential as a therapeutic target in OA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02477-z.

Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration

Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.

RNA Sequencing Reveals Interacting Key Determinants of Osteoarthritis Acting in Subchondral Bone and Articular Cartilage: Identification of IL11 and CHADL as Attractive Treatment Targets

OBJECTIVE

To identify key determinants of the interactive pathophysiologic processes in subchondral bone and cartilage in osteoarthritis (OA).

METHODS

We performed RNA sequencing on macroscopically preserved and lesional OA subchondral bone from patients in the Research Arthritis and Articular Cartilage study who underwent joint replacement surgery due to OA (n = 24 sample pairs: 6 hips and 18 knees). Unsupervised hierarchical clustering and differential expression analyses were conducted. Results were combined with data on previously identified differentially expressed genes in cartilage (partly overlapping samples) as well as data on recently identified OA risk genes.

RESULTS

We identified 1,569 genes that were significantly differentially expressed between lesional and preserved subchondral bone, including CNTNAP2 (fold change [FC] 2.4, false discovery rate [FDR] 3.36 × 10^-5 ) and STMN2 (FC 9.6, FDR 2.36 × 10^-3 ). Among these 1,569 genes, 305 were also differentially expressed, and with the same direction of effect, in cartilage, including the recently recognized OA susceptibility genes IL11 and CHADL. Upon differential expression analysis with stratification for joint site, we identified 509 genes that were exclusively differentially expressed in subchondral bone of the knee, including KLF11 and WNT4. These genes that were differentially expressed exclusively in the knee were enriched for involvement in epigenetic processes, characterized by, e.g., HIST1H3J and HIST1H3H.

CONCLUSION

IL11 and CHADL were among the most consistently differentially expressed genes OA pathophysiology-related genes in both bone and cartilage. As these genes were recently also identified as robust OA risk genes, they classify as attractive therapeutic targets acting on 2 OA-relevant tissues.

OATargets: a knowledge base of genes associated with osteoarthritis joint damage in animals

OBJECTIVES

To collate the genes experimentally modulated in animal models of osteoarthritis (OA) and compare these data with OA transcriptomics data to identify potential therapeutic targets.

METHODS

PubMed searches were conducted to identify publications describing gene modulations in animal models. Analysed gene expression data were retrieved from the SkeletalVis database of analysed skeletal microarray and RNA-Seq expression data. A network diffusion approach was used to predict new genes associated with OA joint damage.

RESULTS

A total of 459 genes were identified as having been modulated in animal models of OA, with ageing and post-traumatic (surgical) models the most prominent. Ninety-eight of the 143 genes (69%) genetically modulated more than once had a consistent effect on OA joint damage severity. Several discrepancies between different studies were identified, providing lessons on interpretation of these data. We used the data collected along with OA gene expression data to expand existing annotations and prioritise the most promising therapeutic targets, which we validated using the latest reported associations. We constructed an online database OATargets to allow researchers to explore the collated data and integrate it with existing OA and skeletal gene expression data.

CONCLUSIONS

We present a comprehensive survey and online resource for understanding gene regulation of animal model OA pathogenesis.

Periostin Mediates Condylar Resorption via the NF-κB-ADAMTS5 Pathway

Although the up-regulation of periostin in osteoarthritic (OA) is found, its function on OA condyle caused by disc displacement is not clear. Our objective was to explore whether periostin has any effect on condylar resorption. We initially identified periostin-positive cells in temporomandibular joint osteoarthritic (TMJ-OA) cartilage. Furthermore, the vitro analysis confirmed that the expression of periostin in chondrocytes treated with a static pressure of 150 kpa and 200 kpa for 3 h by an in-house-designed pressure chamber. To explore the underlying mechanism, we found that periostin can induce IκBα phosphorylation and its subsequent degradation, leading to consequent p65 nuclear translocation and subsequent induction of ADAMTS5 expression, which is known to be detrimental to cartilage extracellular matrix production. Importantly, inhibiting NF-κB signaling, by BAY 11-7082 treatment, rescued periostin-induced ADAMTS5 up-regulation. This study elucidated the direct role of periostin in condylar resorption, which was found to occur via NF-κB-ADAMTS5 signaling. Inhibition of this pathway might provide a new strategy for TMJ-OA treatment.

Differential gene expression analysis reveals pathways important in early post-traumatic osteoarthritis in an equine model

Background

Post-traumatic osteoarthritis (PTOA) is a common and significant problem in equine athletes. It is a disease of the entire joint, with the synovium thought to be a key player in disease onset and progression due to its role in inflammation. The development of effective tools for early diagnosis and treatment of PTOA remains an elusive goal. Altered gene expression represents the earliest discernable disease-related change, and can provide valuable information about disease pathogenesis and identify potential therapeutic targets. However, there is limited work examining global gene expression changes in early disease. In this study, we quantified gene expression changes in the synovium of osteoarthritis-affected joints using an equine metacarpophalangeal joint (MCPJ) chip model of early PTOA. Synovial samples were collected arthroscopically from the MCPJ of 11 adult horses before (preOA) and after (OA) surgical induction of osteoarthritis and from sham-operated joints. After sequencing synovial RNA, Salmon was used to quasi-map reads and quantify transcript abundances. Differential expression analysis with the limma-trend method used a fold-change cutoff of log2(1.1). Functional annotation was performed with PANTHER at FDR < 0.05. Pathway and network analyses were performed in Reactome and STRING, respectively.

Results

RNA was sequenced from 28 samples (6 preOA, 11 OA, 11 sham). “Sham” and “preOA” were not different and were grouped. Three hundred ninety-seven genes were upregulated and 365 downregulated in OA synovium compared to unaffected. Gene ontology (GO) terms related to extracellular matrix (ECM) organization, angiogenesis, and cell signaling were overrepresented. There were 17 enriched pathways, involved in ECM turnover, protein metabolism, and growth factor signaling. Network analysis revealed clusters of differentially expressed genes involved in ECM organization, endothelial regulation, and cellular metabolism.

Conclusions

Enriched pathways and overrepresented GO terms reflected a state of high metabolic activity and tissue turnover in OA-affected tissue, suggesting that the synovium may retain the capacity to support healing and homeostasis in early disease. Limitations of this study include small sample size and capture of one point post-injury. Differentially expressed genes within key pathways may represent potential diagnostic markers or therapeutic targets for PTOA. Mechanistic validation of these findings is an important next step.

Osteoarthritis: Prognosis and emerging therapeutic approach for disease management

Osteoarthritis (OA), a disorder of joints, is prevalent in older age. The contemporary cure for OA is aimed to confer symptomatic relief, consisting of temporary pain and swelling relief. In this paper, we discuss various modalities responsible for the onset of OA and associated with its severity. Inhibition of chondrocytes receptors such as DDR2, SDF-1, Asporin, and CXCR4 by specific pharmacological inhibitors attenuates OA, a critical step for finding potential disease modifying drugs. We critically analyzed recent OA studies with an emphasis on intermediate target molecules for OA intervention. We also explored some novel and safe treatments for OA by considering disease prognosis crosstalk with cellular signaling pathways.

Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis

Osteoarthritis (OA) is a high prevalent musculoskeletal problem, which can cause severe pain, constitute a huge social and economic burden, and seriously damage the quality of life. This study was intended to identify genetic characteristics of subchondral bone in patients with OA and to elucidate the potential molecular mechanisms involved. Data of gene expression profiles (GSE51588), which contained 40 OA samples and 10 normal samples, was obtained from the Gene Expression Omnibus (GEO). The raw data were integrated to obtain differentially expressed genes (DEGs) and were further analyzed with bioinformatic analysis. The protein-protein interaction (PPI) networks were built and analyzed via Search Tool for the Retrieval of Interacting Genes (STRING). The significant modules and hub genes were identified via Cytoscape. Moreover, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis were performed. Totally 235 DEGs were differentially expressed in the subchondral bone from OA patients compared with those of normal individuals, of which 78 were upregulated and 157 were downregulated. Eight hub genes were identified, including DEFA4, ARG1, LTF, RETN, PGLYRP1, OLFM4, ORM1, and BPI. The enrichment analyses of the DEGs and significant modules indicated that DEGs were mainly involved in inflammatory response, extracellular space, RAGE receptor binding, and amoebiasis pathway. The present study provides a novel and in-depth understanding of pathogenesis of the OA subchondral bone at molecular level. DEFA4, ARG1, LTF, RETN, PGLYRP1, OLFM4, ORM1, and BPI may be the new candidate targets for diagnosis and therapies on patients with OA in the future.

Gene Expression Profiling Studies Using Microarray in Osteoarthritis: Genes in Common and Different Conditions

Osteoarthritis (OA), which is characterized mainly by cartilage degradation, is the most prevalent joint disorder worldwide. Although OA is identified as a major cause of joint pain, disability, and socioeconomic burden, the etiology of OA is still not clearly known. Recently, gene microarray analysis has become an efficient method for the research of complex diseases and has been employed to determine what genes and pathways are involved in the pathological process of OA. In this review, OA study results over the last decade are summarized for gene expression profiling of various tissues, such as cartilage, subchondral bone, and synovium in human OA and mouse OA models. Many differentially expressed genes, which mainly involve matrix metabolism, bone turnover, and inflammation pathways, were identified in diseased compared with "normal" tissues. Nevertheless, rare common genes were reported from studies using different tissue sources, microarray chips, and research designs. Thus, future novel and carefully designed microarray studies are required to elucidate underlying genetic mechanisms in the pathogenesis of OA as well as new directions for potential OA-targeted pharmaceutical therapies.