Study of Osteoarthritis-Related Hub Genes Based on Bioinformatics Analysis

The Envelope of Function: Revisiting the Theory With New Concepts-A Narrative Review

Musculoskeletal injuries are a complex multifactorial phenomenon, and several factors can contribute to their occurrence. This review aimed to discuss some relevant and often unexpected elements involved in musculoskeletal injuries and rehabilitation. One of the main factors discussed is the role of physiological adaptation to training in musculoskeletal injury susceptibility. This is probably the most modifiable factor in preventing and treating musculoskeletal injuries. Other factors discussed are the role of genetics in injury susceptibility; the effect of stressors and environmental factors and the way we deal with setbacks; anabolic steroid use as aesthetic and performance-enhancement drugs; nutrition, sleeping, and the imbalance between rest, energy intake, and training; anatomic and biomechanical factors; and the role of systemic disease. Moreover, the topic of unknown factors keeps an open door for future discoveries. This review highlights the importance of understanding the various factors contributing to musculoskeletal injuries and the need for an individualized approach to injury prevention and rehabilitation, from both a historical and a physiological point of view.

HSPB1 as an RNA-binding protein mediates the pathological process of osteoarthritis

Heat-shock protein beta1 (HSPB1) is a member of the small HSP family, downregulated in osteoarthritis (OA) chondrocytes and demonstrated the capacity to serve as an RNA-binding protein (RBP). This work aimed to explore the profile of HSPB1 bound RNA and reveal the potential regulation mechanism of HSPB1 in OA. In this work, we captured an unbiased HSPB1-RNA interaction map in Hela cells using the iRIP-seq. The results demonstrated that HSPB1 interacted with plentiful of mRNAs and genomic location toward the CDS region. Functional enrichment of HSPB1-related peaks showed the involvement in gene expression, translation initiation, cellular protein metabolic process, and nonsense-mediated decay. HOMER software analysis showed that HSPB1 bound peaks were over-represented in GAGGAG sequences. In addition, ABLIRC and CIMS algorithm indicated that HSPB1 bound to AU-rich motifs and the proportion of AU-rich peaks in 3' UTR were slightly higher than that in other regions. Moreover, HSPB1-binding targets analysis revealed several gens were associated with OA including EGFR, PLEC, COL5A1, and ROR2. The association of OA-related mRNAs to HSPB1 was additionally confirmed in OA tissues by the quantitative RIP-PCR experiments. Further experiment demonstrated the downregulation of HSPB1 in OA tissues. In conclusion, our current study confirmed HSPB1 as an RNA-binding protein and revealed its potential function in the pathological process of OA, providing a reliable insight to further investigate the molecular regulation mechanism of HSPB1 in OA.

Osteoarthritis related epigenetic variations in miRNA expression and DNA methylation

Osteoarthritis (OA) is chronic arthritis characterized by articular cartilage degradation. However, a comprehensive regulatory network for OA-related microRNAs and DNA methylation modifications has yet to be established. Thus, we aimed to identify epigenetic changes in microRNAs and DNA methylation and establish the regulatory network between miRNAs and DNA methylation. The mRNA, miRNA, and DNA methylation expression profiles of healthy or osteoarthritis articular cartilage samples were downloaded from Gene Expression Omnibus (GEO) database, including GSE169077, GSE175961, and GSE162484. The differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), and differentially methylated genes (DMGs) were analyzed by the online tool GEO2R. DAVID and STRING databases were applied for functional enrichment analysis and protein-protein interaction (PPI) network. Potential therapeutic compounds for the treatment of OA were identified by Connectivity map (CMap) analysis. A total of 1424 up-regulated DEGs, 1558 down-regulated DEGs, 5 DEMs with high expression, 6 DEMs with low expression, 1436 hypermethylated genes, and 455 hypomethylated genes were selected. A total of 136 up-regulated and 65 downregulated genes were identified by overlapping DEGs and DEMs predicted target genes which were enriched in apoptosis and circadian rhythm. A total of 39 hypomethylated and 117 hypermethylated genes were obtained by overlapping DEGs and DMGs, which were associated with ECM receptor interactions and cellular metabolic processes, cell connectivity, and transcription. Moreover, The PPI network showed COL5A1, COL6A1, LAMA4, T3GAL6A, and TP53 were the most connective proteins. After overlapping of DEGs, DMGs and DEMs predicted targeted genes, 4 up-regulated genes and 11 down-regulated genes were enriched in the Axon guidance pathway. The top ten genes ranked by PPI network connectivity degree in the up-regulated and downregulated overlapping genes of DEGs and DMGs were further analyzed by the CMap database, and nine chemicals were predicted as potential drugs for the treatment of OA. In conclusion, TP53, COL5A1, COL6A1, LAMA4, and ST3GAL6 may play important roles in OA genesis and development.

A comprehensive analysis of single-cell RNA transcriptome reveals unique SPP1+ chondrocytes in human osteoarthritis

Osteoarthritis (OA) has become the most common degenerative disease in the world, which brings a serious economic burden to society and the country. Although epidemiological studies have shown that the occurrence of osteoarthritis is associated with obesity, sex, and trauma, the biomolecular mechanisms for the development and progression of osteoarthritis remain ambiguous. Several studies have drawn a connection between SPP1 and osteoarthritis. SPP1 was first found to be highly expressed in osteoarthritic cartilage, and later more studies have shown that SPP1 is also highly expressed in subchondral bone and synovial in OA patients. However, the biological function of SPP1 remains unclear. Single-cell RNA sequencing (scRNA-seq) is a novel technique that reflects gene expression at the cellular level, making it better depict the state of different cells than ordinary transcriptome data. However, most of the existing chondrocyte scRNA-seq studies focus on the occurrence and development of OA chondrocytes and lack analysis of normal chondrocyte development. Therefore, to better understand the mechanism of OA, scRNA-seq analysis of a larger cell volume containing normal and osteoarthritic cartilage is of great importance. Our study identifies a unique cluster of chondrocytes characterized by high SPP1 expression. The metabolic and biological characteristics of these clusters were further investigated. Besides, in animal models, we found that the expression of SPP1 is spatially heterogeneous in cartilage. Overall, our work provides novel insight into the potential role of SPP1 in OA, which sheds light on understanding the role of SPP1 in OA, promoting the progress of the treatment and prevention in the field of OA.

Identification of CaMK4 as a sex-difference-related gene in knee osteoarthritis

Background

Osteoarthritis (OA) is a common degenerative joint disease with a higher prevalence in females than in males. Sex may be a key factor affecting the progression of OA. This study aimed to investigate critical sex-difference-related genes in patients with OA and confirm their potential roles in OA regulation.

Methods

OA datasets GSE12021, GSE55457, and GSE36700 were downloaded from the Gene Expression Omnibus database to screen OA-causing genes that are differentially expressed in the two sexes. Cytoscape was used to construct a protein-protein interaction network and determine hub genes. Synovial tissues of patients (male and female) with OA and female non-OA healthy controls were obtained to confirm the expression of hub genes and screen the key genes among them. Destabilization of the medial meniscus (DMM)-induced OA mice model was established to verify the screened key genes. Hematoxylin and eosin (HE) staining and Safranin O-fast green dye staining were employed to observe synovial inflammation and pathological cartilage status.

Results

The abovementioned three datasets were intersected to obtain 99 overlapping differentially expressed genes, of which 77 were upregulated and 22 were downregulated in female patients with OA. The hub genes screened were EGF, AQP4, CDC42, NTRK3, ERBB2, STAT1, and CaMK4. Among them, Ca2+/calmodulin-dependent protein kinase-4 (CaMK4) was identified as a key sex-related gene for OA. It was significantly higher in female OA patients than in the cases of male patients. Moreover, CaMK4 was significantly increased in female patients with OA compared with the female non-OA group. These results suggest that CaMK4 plays an important role in the progression of OA. OA mouse models demonstrated that CaMK4 expression in the mice knee joint synovial tissue elevated after DMM, with aggravated synovial inflammation and significant cartilage damage. Cartilage damage improved after intraperitoneal administration of the CaMK4 inhibitor KN-93.

Conclusions

CaMK4 is a key sex-related gene influencing the progression and pathogenesis of OA and may be considered as a new target for OA treatment.

Prediction and analysis of osteoarthritis hub genes with bioinformatics

Background

Osteoarthritis (OA) is the most common type of arthritis. OA can cause joint pain, stiffness, and loss of function. The pathogenesis of OA is not completely clear. Moreover, there is no effective treatment, and clinical management is limited to symptomatic relief or joint surgery. This study utilized bioinformatics to analyze normal and OA articular cartilage samples to find biomarkers and therapeutic targets for OA.

Methods

The GSE169077 gene chip dataset was downloaded from the public gene chip data platform of the National Biotechnology Information Center. The dataset included 6 samples of OA tissues and 5 samples of healthy cartilage tissues. Differentially expressed genes (DEGs) were screened using the R language "limma" function package under the threshold of log2[fold change (FC)] ≥2 and a P value <0.05. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways of the target genes were enriched and analyzed using the database for annotation, visualization, and integrated discovery (DAVID), and a protein-protein interaction (PPI) network was further constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database. The coexpression relationship of the genes in the module was visualized and screened with Cytoscape.

Results

A total of 27 DEGs were identified, including 9 downregulated genes and 18 upregulated genes. GO signal pathway enrichment analysis showed involvement in hypoxic response, fibrous collagen trimer, and extracellular matrix structural components. KEGG analysis demonstrated associations with protein digestion and absorption, extracellular matrix receptor interaction, and the peroxisome proliferator-activated receptor signal pathway, among several other pathways. A PPI network was obtained through STRING analysis, and the results were imported into Cytoscape software. The 27 DEGs were sequenced by the cytoHubba plug-in by various calculation methods, and 5 hub genes (COL1A1, COL1A2, POSTN, BMP1, and MMP13) were finally selected. These genes were analyzed by PPI again and annotated with GO and KEGG in different colors.

Conclusions

Bioinformatics technology effectively identified differential genes in the knee cartilage tissue of healthy controls and patients with OA, providing opportunities to further explore the mechanism and treatment of OA on a transcriptional level.

Proteomic profiling of extracellular vesicles in synovial fluid and plasma from Oligoarticular Juvenile Idiopathic Arthritis patients reveals novel immunopathogenic biomarkers

Introduction

New early low-invasive biomarkers are demanded for the management of Oligoarticular Juvenile Idiopathic Arthritis (OJIA), the most common chronic pediatric rheumatic disease in Western countries and a leading cause of disability. A deeper understanding of the molecular basis of OJIA pathophysiology is essential for identifying new biomarkers for earlier disease diagnosis and patient stratification and to guide targeted therapeutic intervention. Proteomic profiling of extracellular vesicles (EVs) released in biological fluids has recently emerged as a minimally invasive approach to elucidate adult arthritis pathogenic mechanisms and identify new biomarkers. However, EV-prot expression and potential as biomarkers in OJIA have not been explored. This study represents the first detailed longitudinal characterization of the EV-proteome in OJIA patients.

Methods

Fourty-five OJIA patients were recruited at disease onset and followed up for 24 months, and protein expression profiling was carried out by liquid chromatography-tandem mass spectrometry in EVs isolated from plasma (PL) and synovial fluid (SF) samples.

Results

We first compared the EV-proteome of SF vs paired PL and identified a panel of EV-prots whose expression was significantly deregulated in SF. Interaction network and GO enrichment analyses performed on deregulated EV-prots through STRING database and ShinyGO webserver revealed enrichment in processes related to cartilage/bone metabolism and inflammation, suggesting their role in OJIA pathogenesis and potential value as early molecular indicators of OJIA development. Comparative analysis of the EV-proteome in PL and SF from OJIA patients vs PL from age/gender-matched control children was then carried out. We detected altered expression of a panel of EV-prots able to differentiate new-onset OJIA patients from control children, potentially representing a disease-associated signature measurable at both the systemic and local levels with diagnostic potential. Deregulated EV-prots were significantly associated with biological processes related to innate immunity, antigen processing and presentation, and cytoskeleton organization. Finally, we ran WGCNA on the SF- and PL-derived EV-prot datasets and identified a few EV-prot modules associated with different clinical parameters stratifying OJIA patients in distinct subgroups.

Discussion

These data provide novel mechanistic insights into OJIA pathophysiology and an important contribution in the search of new candidate molecular biomarkers for the disease.

Contribution of MicroRNA-27b-3p to Synovial Fibrotic Responses in Knee Osteoarthritis

OBJECTIVE

Synovial fibrosis contributes to osteoarthritis (OA) pathology, but the underlying mechanisms remain unknown. We have observed increased microRNA-27b-3p (miR-27b-3p) levels in synovial fluid of patients with late-stage radiographic knee OA. Here, we investigated the contribution of miR-27b-3p to synovial fibrosis in patients with severe knee OA and in a mouse model of knee OA.

METHODS

We stained synovium sections obtained from patients with radiographic knee OA scored according to the Kellgren/Lawrence scale and mice that underwent destabilization of the medial meniscus (DMM) for miR-27b-3p using in situ hybridization. We examined the effects of intraarticular injection of miR-27b-3p mimic into naive mouse knee joints and intraarticular injection of a miR-27b-3p inhibitor into mouse knee joints after DMM. We performed transfection with miR-27b-3p mimic and miR-27b-3p inhibitor in human OA fibroblast-like synoviocytes (FLS) using reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) array, RNA sequencing, RT-qPCR, Western blotting, immunofluorescence, and migration assays.

RESULTS

We observed increased miR-27b-3p expression in the synovium from patients with knee OA and in mice with DMM-induced arthritis. Injection of the miR-27b-3p mimic in mouse knee joints induced a synovial fibrosis-like phenotype, increased synovitis scores, and increased COL1A1 and α-smooth muscle actin (α-SMA) expression. In the mouse model of DMM-induced arthritis, injection of the miR-27b-3p inhibitor decreased α-SMA but did not change COL1A1 expression levels or synovitis scores. Transfection with the miR-27b-3p mimic in human OA FLS induced profibrotic responses, including increased migration and expression of key extracellular matrix (ECM) genes, but transfection with the miR-27b-3p inhibitor had the opposite effects. RNA sequencing identified a PPARG/ADAMTS8 signaling axis regulated by miR-27b-3p in OA FLS. Human OA FLS transfected with miR-27b-3p mimic and then treated with the PPARG agonist rosiglitazone or with ADAMTS8 small interfering RNA exhibited altered expression of select ECM genes.

CONCLUSION

Our findings demonstrate that miR-27b-3p has a key role in ECM regulation associated with synovial fibrosis during OA.

Gene Expression Microarray Data Identify Hub Genes Involved in Osteoarthritis

The present study was performed to explore the underlying molecular mechanisms and screen hub genes of osteoarthritis (OA) via bioinformatics analysis. In total, twenty-five OA synovial tissue samples and 25 normal synovial tissue samples were derived from three datasets, namely, GSE55457, GSE55235, and GSE1919, and were used to identify the differentially expressed genes (DEGs) of OA by R language. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A Venn diagram was built to show the potential hub genes identified in all three datasets. The STRING database was used for constructing the protein–protein interaction (PPI) networks and submodules of DEGs. We identified 507 upregulated and 620 downregulated genes. Upregulated DEGs were significantly involved in immune response, MHC class II receptor activity, and presented in the extracellular region, while downregulated DEGs were mainly enriched in response to organic substances, extracellular region parts, and cadmium ion binding. Results of KEGG analysis indicated that the upregulated DEGs mainly existed in cell adhesion molecules (CAMs), while downregulated DEGs were significantly involved in the MAPK signaling pathway. A total of eighteen intersection genes were identified across the three datasets. These include Nell-1, ATF3, RhoB, STC1, and VEGFA. In addition, 10 hub genes including CXCL12, CXCL8, CCL20, and CCL4 were found in the PPI network and module construction. Identification of DEGs and hub genes associated with OA may be helpful for revealing the molecular mechanisms of OA and further promotes the development of relevant biomarkers and drug targets.

Identification and validation of pivotal genes related to age-related meniscus degeneration based on gene expression profiling analysis and in vivo and in vitro models detection

BACKGROUND

The componential and structural change in the meniscus with aging would increase the tissue vulnerability of the meniscus, which would induce meniscus tearing. Here, we investigated the molecular mechanism of age-related meniscus degeneration with gene expression profiling analysis, and validate pivotal genes in vivo and in vitro models.

METHODS

The GSE45233 dataset, including 6 elderly meniscus samples and 6 younger meniscus samples, was downloaded from the Gene Expression Omnibus (GEO) database. To screen the differential expression of mRNAs and identify the miRNAs targeting hub genes, we completed a series of bioinformatics analyses, including functional and pathway enrichment, protein-protein interaction network, hub genes screening, and construction of a lncRNA-miRNA-mRNA network. Furthermore, crucial genes were examined in human senescent menisci, mouse senescent meniscus tissues and mouse meniscus cells stimulated by IL-1β.

RESULTS

In total, the most significant 4 hub genes (RRM2, AURKB, CDK1, and TIMP1) and 5 miRNAs (hsa-miR-6810-5p, hsa-miR-4676-5p, hsa-miR-6877-5p, hsa-miR-8085, and hsa-miR-6133) that regulated such 4 hub genes, were finally identified. Moreover, these hub genes were decreased in meniscus cells in vitro and meniscus tissues in vivo, which indicated that hub genes were related to meniscus senescence and could serve as potential biomarkers for age-related meniscus tearing.

CONCLUSIONS

In short, the integrated analysis of gene expression profile, co-expression network, and models detection identified pivotal genes, which elucidated the possible molecular basis underlying the senescence meniscus and also provided prognosis clues for early-onset age-related meniscus tearing.

The role of circRNA derived from RUNX2 in the serum of osteoarthritis and its clinical value

Background

Circular RNA (circRNA) has been shown to affect the pathological process of osteoarthritis (OA) and is expected to become a potential marker for disease diagnosis. This study aimed to investigate the association between circRNA derived from the gene of runt‐related transcription factor 2 (RUNX2) and OA risk.

Methods

The expression profile of RUNX2‐derived circRNAs in serum of OA patients was detected. Then, the cytological localization of screened differential circRNAs was studied. Luciferase (LUC) reporter assay was used to identify the microRNA (miRNA) sponge capacity of the circRNAs. Bioinformatics analysis was used to construct the functional pathway of this circRNA‐miRNAs network. And then, the diagnostic value of RUNX2‐derived circRNAs in OA was evaluated.

Results

RUNX2‐derived hsa_circ_0005526 (circ_RUNX2) is significantly highly expressed in OA serum and mainly located in the cytoplasm within the cartilage cell by sponging multiple miRNAs (miR‐498, miR‐924, miR‐361‐3p, and miR‐665). Bioinformatics analysis showed ECM‐receptor interaction pathway ranked the most significant pathway of circ_RUNX2‐miRNAs regulatory network in KEGG database. The ROC curve showed that there may be good diagnostic value of serum circ_RUNX2 in OA.

Conclusion

RUNX2‐derived circ_RUNX2 may be involved in OA development via ECM‐receptor interaction pathways and may be used as potential clinical indicator of OA.

Biomarkers of Joint Damage in Osteoarthritis: Current Status and Future Directions

Osteoarthritis (OA) is a disease of the whole joint organ, characterized by the loss of cartilage, and structural changes in bone including the formation of osteophytes, causing disability and loss of function. It is also associated with systemic mediators and low-grade inflammation. Currently, there is negligible/no availability of specific biomarkers that can be used to facilitate the diagnosis and treatment of OA. The most unmet clinical need is, however, related to the monitoring of disease progression over a short period that can be used in clinical trials. In this review, the value of biomarkers identified over the past decade has been highlighted. These biomarkers are associated with the synthesis and breakdown of cartilage, including collagenous and noncollagenous biomarkers, inflammatory and anti-inflammatory biomarkers, expressed in the biological fluid such as serum, synovial fluid, and urine. Broad validation of novel and clinically applicable biomarkers and their involvement in the pathways are particularly needed for early-stage diagnosis, monitoring disease progression, and severity and examining new drugs to mitigate the effects of this highly prevalent and debilitating condition.