Identifying the hub genes and immune cell infiltration in synovial tissue between osteoarthritic and rheumatoid arthritic patients by bioinformatic approach

RGS1 Enhancer RNA Promotes Gene Transcription by Recruiting Transcription Factor FOXJ3 and Facilitates Osteoclastogenesis Through PLC-IP3R-dependent Ca2+ Response in Rheumatoid Arthritis

Recent evidence has highlighted the functions of enhancers in modulating transcriptional machinery and affecting the development of human diseases including rheumatoid arthritis (RA). Enhancer RNAs (eRNAs) are RNA molecules transcribed from active enhancer regions. This study investigates the specific function of eRNA in gene transcription and osteoclastogenesis in RA. Regulator of G protein signaling 1 (RGS1)-associated eRNA was highly activated in osteoclasts according to bioinformatics prediction. RGS1 mRNA was increased in mice with collagen-induced arthritis as well as in M-CSF/soluble RANKL-stimulated macrophages (derived from monocytes). This was ascribed to increased RGS1 eRNA activity. Silencing of 5'-eRNA blocked the binding between forkhead box J3 (FOXJ3) and the RGS1 promoter, thus suppressing RGS1 transcription. RGS1 accelerated osteoclastogenesis through PLC-IP3R-dependent Ca2+ response. Knockdown of either FOXJ3 or RGS1 ameliorated arthritis severity, improved pathological changes, and reduced osteoclastogenesis and bone erosion in vivo and in vitro. However, the effects of FOXJ3 silencing were negated by RGS1 overexpression. In conclusion, this study demonstrates that the RGS1 eRNA-driven transcriptional activation of the FOXJ3/RGS1 axis accelerates osteoclastogenesis through PLC-IP3R dependent Ca2+ response in RA. The finding may offer novel insights into the role of eRNA in gene transcription and osteoclastogenesis in RA.

Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis

Sarcopenia, a geriatric syndrome characterized by progressive loss of muscle mass and strength, and osteoarthritis, a common degenerative joint disease, are both prevalent in elderly individuals. However, the relationship and molecular mechanisms underlying these two diseases have not been fully elucidated. In this study, we screened microarray data from the Gene Expression Omnibus to identify associations between sarcopenia and osteoarthritis. We employed multiple statistical methods and bioinformatics tools to analyze the shared DEGs (differentially expressed genes). Additionally, we identified 8 hub genes through functional enrichment analysis, protein-protein interaction analysis, transcription factor-gene interaction network analysis, and TF-miRNA coregulatory network analysis. We also discovered potential shared pathways between the two diseases, such as transcriptional misregulation in cancer, the FOXO signalling pathway, and endometrial cancer. Furthermore, based on common DEGs, we found that strophanthidin may be an optimal drug for treating sarcopenia and osteoarthritis, as indicated by the Drug Signatures database. Immune infiltration analysis was also performed on the sarcopenia and osteoarthritis datasets. Finally, receiver operating characteristic (ROC) curves were plotted to verify the reliability of our results. Our findings provide a theoretical foundation for future research on the potential common pathogenesis and molecular mechanisms of sarcopenia and osteoarthritis.

Network Analysis of Osteoarthritis Progression Using a Steiner Minimal Tree Algorithm

Purpose

To provide a comprehensive analysis of associated genes with osteoarthritis (OA). Here, we reported a network analysis of OA progression by using a Steiner minimal tree algorithm.

Methods

We collected the OA-related genes through screening the publications in MEDLINE. We performed functional analysis to analyze the associated biochemical pathways of the OA-related genes. Pathway crosstalk analysis was constructed to explore interactions of the enriched pathways. Steiner minimal tree algorithm was used to analyze molecular pathway networks. The average clustering coefficient was compared with the corresponding values of the Osteoarthritis-specific network. The new finding RNA was compared with former single-cell RNA-seq analysis results.

Results

A gene set with 177 members reported to be significantly associated with Osteoarthritis was collected from 187 studies. Functional enrichment analysis revealed a specific related-OA gene including skeletal system development, cytokine-mediated signaling pathway, inflammatory response, cartilage development, and extracellular matrix organization. We performed a pathway crosstalk analysis among the 72 significantly enriched pathways. A total of 151 of the 177 genes in the Osteoarthritis gene set were included in the human interactome network. There were 31 genes in the former single-cell RNA-seq analysis results. The CLU, ENO1, SRRM1, UBC, HMGB1, NR3C1, NOTCH2NL, and CBX5 have significantly increased expression in seven molecularly defined populations of OA cartilage.

Conclusion

The Steiner tree-based approach finds new biological molecules associated with OA genes.

Overexpression of RAD54L attenuates osteoarthritis by suppressing the HIF-1α/VEGF signaling pathway: Bioinformatics analysis and experimental validation

Osteoarthritis (OA) is a widespread chronic, progressive, degenerative joint disease that causes pain and disability. Current treatments for OA have limited effectiveness and new biomarkers need to be identified. Bioinformatics analysis was conducted to explore differentially expressed genes and DNA repair/recombination protein 54 L (RAD54L) was selected. We firstly overexpressed RAD54L in interleukin-1β (IL-1β)-induced human articular chondrocytes or in OA rats to investigate its effect on OA. Chondrocyte viability and apoptotic rate were measured by Cell Counting Kit-8 and flow cytometry, respectively. Then we evaluated OA severity in vivo by Hematoxylin-eosin staining and Osteoarthritis Research Society International standards. The expression of inflammatory mediators was tested by enzyme-linked immunosorbent assay. Finally, western blot was performed to determine the relative expression level of hypoxia-inducible factors 1α (HIF-1α) and vascular endothelial growth factor (VEGF). Overexpression of RAD54L promoted cell viability and attenuated apoptosis in IL-1β-induced human chondrocytes. A lower Osteoarthritis Research Society International score and a remarkable alleviation of chondrocyte disordering and infiltration of inflammatory cells were found in cartilage tissues of OA rats after overexpressing RAD54L. The inflammatory response induced by OA was decreased by RAD54L overexpression in vitro and in vivo. In addition, RAD54L overexpression decreased the relative expression level of HIF-1α and VEGF. Overexpression of RAD54L could attenuate OA by suppressing the HIF-1α/VEGF signaling pathway, indicating that RAD54L may be a potential treatment target for OA.

Identification of novel potential drugs for the treatment and prevention of osteoarthritis

Objectives

Osteoarthritis (OA) is characterized by a high prevalence, poor prognosis, and a propensity to lead to disability. Despite the availability of standard therapies, they are associated with potential side effects and don't provide a complete cure for patients. Consequently, there is an urgent demand for the development of novel drugs.

Method

The gene expression profiles (GSE64394, GSE178557 and GSE215039) of normal and OA chondrocytes samples were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by the "LIMMA" R package. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were conducted using the R package clusterProfiler. A protein-protein (PPI) interaction network was performed to identify hub genes by using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. Small molecule compounds linked to OA were predicted through the NetworkAnalyst platform. Finally, molecular docking was conducted using AutoDock and Pymol software.

Results

We identified 98 DEGs primarily implicated in endochondral ossification, extracellular matrix degradation, and Wnt signaling pathways. 23 DEGs were closely associated with OA, and 10 hub genes were found to be potential drug targets for OA. Two new targeted compounds, tetrachlorodibenzodioxin (TCDD) and valproic acid (VPA), were screened. And they both exhibited strong binding affinity to their respective targets.

Conclusions

Reducing exposure to TCDD could be a crucial strategy in preventing OA, and VPA has gained recognition as a novel drug candidate for OA treatment.

Identification of immune-associated genes in vascular dementia by integrated bioinformatics and inflammatory infiltrates

Objective

Dysregulation of the immune system plays a vital role in the pathological process of vascular dementia, and this study aims to spot critical biomarkers and immune infiltrations in vascular dementia employing a bioinformatics approach.

Methods

We acquired gene expression profiles from the Gene Expression Database. The gene expression data were analyzed using the bioinformatics method to identify candidate immune-related central genes for the diagnosis of vascular dementia. and the diagnostic value of nomograms and Receiver Operating Characteristic (ROC) curves were evaluated. We also examined the role of the VaD hub genes. Using the database and potential therapeutic drugs, we predicted the miRNA and lncRNA controlling the Hub genes. Immune cell infiltration was initiated to examine immune cell dysregulation in vascular dementia.

Results

1321 immune genes were included in the combined immune dataset, and 2816 DEGs were examined in GSE122063. Twenty potential genes were found using differential gene analysis and co-expression network analysis. PPI network design and functional enrichment analysis were also done using the immune system as the main subject. To create the nomogram for evaluating the diagnostic value, four potential core genes were chosen by machine learning. All four putative center genes and nomograms have a solid diagnostic value (AUC ranged from 0.81 to 0.92). Their high confidence level became unquestionable by validating each of the four biomarkers using a different dataset. According to GeneMANIA and GSEA enrichment investigations, the pathophysiology of VaD is strongly related to inflammatory responses, drug reactions, and central nervous system degeneration. The data and Hub genes were used to construct a ceRNA network that includes three miRNAs, 90 lncRNA, and potential VaD therapeutics. Immune cells with varying dysregulation were also found.

Conclusion

Using bioinformatic techniques, our research identified four immune-related candidate core genes (HMOX1, EBI3, CYBB, and CCR5). Our study confirms the role of these Hub genes in the onset and progression of VaD at the level of immune infiltration. It predicts potential RNA regulatory pathways control VaD progression, which may provide ideas for treating clinical disease.

QbD-Based Fabrication of Biomimetic Hydroxyapatite Embedded Gelatin Nanoparticles for Localized Drug Delivery against Deteriorated Arthritic Joint Architecture

Biomaterials such as nanohydroxyapatite and gelatin are widely explored to improve damaged joint architecture associated with rheumatoid arthritis (RA). Besides joint damage, RA is associated with inflammation of joints and cartilage, which potentiates the need for both bone nucleation and therapeutic intervention. For such purpose, a modified nanoprecipitation method is used herein to fabricate tofacitinib (Tofa)-loaded nanohydroxyapatite (nHA) embedded gelatin (GLT) nanoparticles (NPs) (Tofa-nHA-GLT NPs). The quality by design (QbD) approach is chosen to assess the key parameters that determine the efficiency of the NPs, and are further optimized via Box-Behnken design of experiment. The particle size, polydispersity, zeta potential, and encapsulation efficiency (EE) of the prepared NPs are found to be 269 nm, 0.18, -20.5 mV, and 90.7%, respectively. Furthermore, the NPs have improved stability, skin permeability, and a sustained drug release pattern at pH 6.5 (arthritic joint pH). Moreover, rhodamine-B loaded nHA-GLT NPs demonstrates considerably higher cellular uptake by the murine-derived macrophages than free rhodamine-B solution. In vitro, cell-based experiments confirm the good cell biocompatibility with insignificant toxicity. Thus, QbD-based approach has successfully led to the development of Tofa-nHA-GLT NPs with the potential to target inflamed arthritic joint.

Identification and analysis of microplastics in human lower limb joints

Microplastics (MPs) have been detected in various human tissues, including the liver, placenta, and blood. However, studies about MPs in the human locomotor system are limited. This study evaluated the presence of MPs in the synovium of 45 patients undergoing hip or knee arthroplasty using micro-Fourier transform infrared spectroscopy, scanning electron microscopy, and Raman microscopy and investigated their association with clinical indicators and local cellular responses. A total of 343 MPs of nine common types were identified, with a mean abundance of 5.24 ± 2.07 particles/g and ranging from 1.16 to 10.77 particles/g. Although there was no clear correlation between MP abundance and demographics, MP abundance was higher in hip samples than in knee samples. In addition, a potential association was observed between MP abundance and specific clinical diagnoses. Transcriptomic analysis revealed that a three-fold increase in MP abundance corresponded to enhanced local cellular stress responses, particularly heat shock protein reactions. Our findings demonstrate the presence of MPs in human joints and suggest that further studies are needed to explore the intricate associations between MPs and anatomical location, clinical diagnosis, and local cellular responses.

Identification of Key Ubiquitination-Related Genes and Their Association with Immune Infiltration in Osteoarthritis Based on the mRNA-miRNA Network

Osteoarthritis (OA) is a prevalent degenerative joint disease that is closely associated with functions of ubiquitination and immune cells, yet the mechanism remains ambiguous. This study aimed to find core ubiquitination-related genes and their correlative immune infiltration in OA using weighted gene co-expression network analysis (WGCNA). The ubiquitination-related genes, datasets GSE55235 and GSE143514 were obtained from open databases. WGCNA got used to investigate key co-expressed genes. Then, we screened differentially expressed miRNAs by "limma" package in R, and constructed mRNA-miRNA network. We conducted function enrichment analysis on the identified genes. CIBERSORT was then utilized to analyze the relevance between immune infiltration and genes. Lastly, RT-qPCR was further used to verify the prediction of bioinformatics. A sum of 144 ubiquitination-related genes in OA were acquired. Enrichment analysis indicated that obtained genes obviously involved in mTOR pathway to regulate the OA development. GRB2 and SEH1L and L-arginine synergistically regulate the mTOR signaling pathway in OA. Moreover, GRB2 and SEH1L were remarkably bound up with immune cell infiltration. Additionally, GRB2 expression was upregulated and SEH1L level was downregulated in the OA development by RT-qPCR experiment. The present study identified GRB2 and SEH1L as key ubiquitination-related genes which were involved in immune infiltration in OA patients, thereby providing new drug targets for OA.

Long noncoding RNA H19 synergizes with STAT1 to regulate SNX10 in rheumatoid arthritis

Erosive destruction of joint structures is an important event in the rheumatoid arthritis (RA) development where fibroblast-like synoviocytes (FLS) represent the main effectors. The implication of long noncoding RNAs (lncRNAs) in RA has not been clearly established. Here, we sought to assess the function of lncRNA H19 in RA by assessing its contribution to the phenotype of FLS. H19 was overexpressed in RA-FLS, and H19 promoted RA-FLS proliferation, invasion as well as angiogenesis and reduced RA-FLS apoptosis. Moreover, H19 loss significantly alleviated joint redness and swelling and reduced inflammatory response, synovial hyperplasia and cartilage damage in arthritic mice induced by collagen. Mechanistically, H19 significantly increased the transcription of sorting nexin (SNX) 10 in RA-FLS by promoting STAT1 translocation into the nucleus. Overexpression of SNX10 or STAT1 mitigated the repressing effects of H19 loss on RA in mice. Our findings highlight that H19 upregulation may result in the development of FLS-mediated RA via the STAT1/SNX10 axis. H19 might serve as a possible therapeutic target for RA treatment.

Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis

Osteoarthritis (OA) is a major cause of pain, disability, and social burden in the elderly throughout the world. Although many studies focused on the molecular mechanism of OA, its etiology remains unclear. Therefore, more biomarkers need to be explored to help early diagnosis, clinical outcome measurement, and new therapeutic target development. Our study aimed to retrieve the potential hub genes of osteoarthritis (OA) by weighted gene co-expression network analysis (WGCNA) and assess their clinical utility for predicting OA. Here, we integrated WGCNA to identify novel OA susceptibility modules and hub genes. In this study, we first selected 477 and 834 DEGs in the GSE1919 and the GSE55235 databases, respectively, from the Gene Expression Omnibus (GEO) website. Genes with p-value<0.05 and | log2FC | > 1 were included in our analysis. Then, WGCNA was conducted to build a gene co-expression network, which filtered out the most relevant modules and screened out 23 overlapping WGCNA-derived hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses elucidated that these hub genes were associated with cell adhesion molecules pathway, leukocyte activation, and inflammatory response. In addition, we conducted the protein–protein interaction (PPI) network in 23 hub genes, and the top four upregulated hub genes were sorted out (CD4, SELL, ITGB2, and CD52). Moreover, our nomogram model showed good performance in predicting the risk of OA (C-index = 0.76), and this model proved to be efficient in diagnosis by ROC curves (AUC = 0.789). After that, a single-sample gene set enrichment (ssGSEA) analysis was performed to discover immune cell infiltration in OA. Finally, human primary synoviocytes and immunohistochemistry study of synovial tissues confirmed that those candidate genes were significantly upregulated in the OA groups compared with normal groups. We successfully constructed a co-expression network based on WGCNA and found out that OA-associated susceptibility modules and hub genes, which may provide further insight into the development of pre-symptomatic diagnosis, may contribute to understanding the molecular mechanism study of OA risk genes.

Bioinformatics-Led Discovery of Osteoarthritis Biomarkers and Inflammatory Infiltrates

The molecular mechanisms of osteoarthritis, the most common chronic disease, remain unexplained. This study aimed to use bioinformatic methods to identify the key biomarkers and immune infiltration in osteoarthritis. Gene expression profiles (GSE55235, GSE55457, GSE77298, and GSE82107) were selected from the Gene Expression Omnibus database. A protein-protein interaction network was created, and functional enrichment analysis and genomic enrichment analysis were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) databases. Immune cell infiltration between osteoarthritic tissues and control tissues was analyzed using the CIBERSORT method. Identify immune patterns using the ConsensusClusterPlus package in R software using a consistent clustering approach. Molecular biological investigations were performed to discover the important genes in cartilage cells. A total of 105 differentially expressed genes were identified. Differentially expressed genes were enriched in immunological response, chemokine-mediated signaling pathway, and inflammatory response revealed by the analysis of GO and KEGG databases. Two distinct immune patterns (ClusterA and ClusterB) were identified using the ConsensusClusterPlus. Cluster A patients had significantly lower resting dendritic cells, M2 macrophages, resting mast cells, activated natural killer cells and regulatory T cells than Cluster B patients. The expression levels of TCA1, TLR7, MMP9, CXCL10, CXCL13, HLA-DRA, and ADIPOQSPP1 were significantly higher in the IL-1β-induced group than in the osteoarthritis group in an in vitro qPCR experiment. Explaining the differences in immune infiltration between osteoarthritic tissues and normal tissues will contribute to the understanding of the development of osteoarthritis.