Decisive gene strategy on osteoarthritis: a comprehensive whole-literature based approach for conclusive gene targets.

BACKGROUND: Previous meta-analyses only examined the association between single or several gene polymorphisms and osteoarthritis (OA), whereas no studies have concluded that there are existing all gene loci that associate with OA. OBJECTIVE: To assess whether a definite conclusion of the association between the gene loci and OA can be drawn. METHODS: Decisive gene strategy (DGS), a literature-based approach, was used to search PubMed, Embase, and Cochrane databases for all meta-analyses that associated gene polymorphisms and OA. Trial Sequential Analysis (TSA) examined the sufficiency of the cumulative sample size. Finally, we assessed the importance of gene loci in OA based on whether there were enough sample sizes and the heterogeneity of the literatures with I2 value. RESULTS: After excluding 179 irrelevant publications, 80 meta-analysis papers were recruited. Among Caucasians, SMAD3 rs12901499 (OR = 1.20, 95% CI: 1.12-1.29) was a risk factor with validation of sufficient sample sizes through TSA model. Among Asians, there were 3 gene loci risk factors with validation of sufficient sample sizes through TSA model: ESR1 rs2228480, SMAD3 rs12901499, and MMP-1 rs1799750 (OR = 1.35, 95% CI: 1.08-1.69; OR = 1.34, 95% CI: 1.07-1.69; OR = 1.43, 95% CI: 1.18-1.74, respectively). Besides, 3 gene loci, DVWA rs7639618, GDF5 rs143383, and VDR rs7975232 (OR = 0.78, 95% CI: 0.67-0.90; OR = 0.74, 95% CI: 0.67-0.81; OR = 0.56, 95% CI: 0.35-0.90, respectively) were identified as protective factors through TSA model. CONCLUSIONS: We used DGS to identify conclusive gene loci associated with OA. These findings provide implications of precision medicine in OA and may potentially advance genetic therapy.

Similarities and differences between osteoarthritis and rheumatoid arthritis: insights from Mendelian randomization and transcriptome analysis.

BACKGROUND: Osteoarthritis (OA) and rheumatoid arthritis (RA) are often difficult to distinguish in the early stage of the disease. The purpose of this study was to explore the similarities and differences between the two diseases through Mendelian randomization (MR) and transcriptome analysis. METHODS: We first performed a correlation analysis of phenotypic data from genome-wide association studies (GWAS) of OA and RA. Then, we performed functional and pathway enrichment of differentially expressed genes in OA, RA, and normal patients. The infiltration of immune cells in arthritis was analyzed according to gene expression. Finally, MR analysis was performed with inflammatory cytokines and immune cells as exposures and arthritis as the outcome. The same and different key cytokines and immune cells were obtained by the two analysis methods. RESULTS: GWAS indicated that there was a genetic correlation between OA and RA. The common function of OA and RA is enriched in their response to cytokines, while the difference is enriched in lymphocyte activation. T cells are the main immune cells that differentiate between OA and RA. MR analysis further revealed that OA is associated with more protective cytokines, and most of the cytokines in RA are pathogenic. In addition, CCR7 on naive CD4 + T cell was positively correlated with OA. SSC-A on CD4 + T cell was negatively correlated with RA, while HLA DR on CD33- HLA DR + was positively correlated with RA. CONCLUSION: Our study demonstrated the similarities and differences of immune inflammation between OA and RA, allowing us to better understand these two diseases.

CCL4/CCR5 regulates chondrocyte biology and OA progression.

BACKGROUND: Osteoarthritis (OA) is a common musculoskeletal disorder characterized by chondrocyte apoptosis and extracellular matrix degradation. This study aimed to investigate the role of CCL4/CCR5 in regulating chondrocyte apoptosis and reactive oxygen species (ROS) levels in OA progression. METHODS: Bioinformatics analysis was employed to identify CCL4 as the target gene, following which primary chondrocytes were treated with varying concentrations of CCL4. Apoptosis rate of chondrocytes and ROS levels were assessed using flow cytometry. The mechanism by which CCL4 regulated the extracellular matrix was investigated through Western blot and Immunofluorescence analyses. Additionally, maraviroc, a CCR5 inhibitor, was administered to chondrocytes in order to explore the potential signaling pathway of CCL4/CCR5. RESULTS: Our study found that CCL4 was predominantly up-regulated among the top 10 hub genes identified in RNA-sequencing analysis. Validation through quantitative polymerase chain reaction (qPCR) confirmed elevated CCL4 expression in patients with Hip joint osteoarthritis, knee joint osteoarthritis, and facet joint osteoarthritis. The upregulation of CCL4 was associated with an increase in chondrocyte apoptosis and ROS levels. Mechanistically, CCL4, upon binding to its receptor CCR5, triggered the downstream phosphorylation of P65 in the nuclear factor-κB (NF-κB) signaling pathway. In vitro experiments demonstrated that treatment with maraviroc mitigated chondrocyte apoptosis, reduced intracellular ROS levels, and attenuated extracellular matrix degradation. CONCLUSION: The study highlights the critical role of CCL4/CCR5 in modulating chondrocyte apoptosis and ROS levels in OA progression. Targeting this pathway may offer promising therapeutic interventions for mitigating the pathogenic mechanisms associated with OA.

Small extracellular vesicles derived from synovial fibroblasts contain distinct miRNA profiles and contribute to chondrocyte damage in osteoarthritis.

BACKGROUND: Small extracellular vesicles (sEV) derived from synovial fibroblasts (SF) represent a novel molecular mechanism regulating cartilage erosion in osteoarthritis (OA). However, a comprehensive evaluation using disease relevant cells has not been undertaken. The aim of this study was to isolate and characterise sEV from OA SF and to look at their ability to regulate OA chondrocyte effector responses relevant to disease. Profiling of micro (mi) RNA signatures in sEV and parental OA SF cells was performed. METHODS: SF and chondrocytes were isolated from OA synovial membrane and cartilage respectively (n = 9). sEV were isolated from OA SF (± IL-1ß) conditioned media by ultracentrifugation and characterised using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Particle size was confirmed by nanoparticle tracking analysis (NTA). sEV regulation of OA chondrocyte and cartilage effector response was evaluated using qPCR, ELISA and sulphated glycosaminoglycan assay (sGAG). RNA-sequencing was used to establish miRNA signatures in isolated sEV from OA SF. RESULTS: OA SF derived sEV were readily taken up by OA chondrocytes, with increased expression of the catabolic gene MMP 13 (p < 0.01) and decreased expression of the anabolic genes aggrecan and COL2A1 (p < 0.01) observed. Treatment with sEV derived from IL-1ß stimulated OA SF significantly decreased expression of aggrecan and COL2A1 (p < 0.001) and increased SOX 9 gene expression (p < 0.05). OA chondrocytes cultured with sEV from either non-stimulated or IL-1ß treated OA SF, resulted in a significant increase in the secretion of IL-6, IL-8 and MMP-3 (p < 0.01). Cartilage explants cultured with sEV from SF (± IL-1ß) had a significant increase in the release of sGAG (p < 0.01). miRNA signatures differed between parental SF cells and isolated sEV. The recently identified osteoclastogenic regulator miR182, along with miR4472-2, miR1302-3, miR6720, miR6087 and miR4532 were enriched in sEV compared to parental cells, p < 0.01. Signatures were similar in sEVs derived from non-stimulated or IL-1ß stimulated SF. CONCLUSIONS: OA SF sEV regulate chondrocyte inflammatory and remodelling responses. OA SF sEV have unique signatures compared to parental cells which do not alter with IL-1ß stimulation. This study provides insight into a novel regulatory mechanism within the OA joint which could inform future targeted therapy.

Association between serum iron status and the risk of five bone and joint-related diseases: a Mendelian randomization analysis.

Background: According to reports, iron status has been associated with the risk of bone and joint-related diseases. However, the exact role of iron status in the development of these conditions remains uncertain. Method: We obtained genetic data on iron status, specifically serum iron, ferritin, transferrin saturation (TSAT), and transferrin, as well as data on five common bone and joint-related diseases (osteoarthritis, osteoporosis, rheumatoid arthritis [RA], ankylosing spondylitis [AS], and gout) from independent genome-wide association studies involving individuals of European ancestry. Our primary approach for causal estimation utilized the inverse variance weighted (IVW) method. To ensure the reliability of our findings, we applied complementary sensitivity analysis and conducted reverse causal analysis. Result: Using the IVW method, we revealed a positive causal relationship between ferritin levels and the risk of osteoarthritis (OR [95% CI], 1.0114 [1.0021-1.0207]). Besides, we identified a protective causal relationship between serum iron levels and TSAT levels in the risk of RA (OR [95% CI] values of serum iron and TSAT were 0.9987 [0.9973-0.9999] and 0.9977 [0.9966-0.9987], respectively). Furthermore, we found a positive causal relationship between serum iron levels and the risk of AS (OR [95% CI], 1.0015 [1.0005-1.0026]). Regarding gout, both serum iron and TSAT showed a positive causal relationship (OR [95% CI] values of 1.3357 [1.0915-1.6345] and 1.2316 [1.0666-1.4221] for serum iron and TSAT, respectively), while transferrin exhibited a protective causal relationship (OR [95% CI], 0.8563 [0.7802-0.9399]). Additionally, our reverse causal analysis revealed a negative correlation between RA and ferritin and TSAT levels (OR [95% CI] values of serum iron and TSAT were 0.0407 [0.0034-0.4814] and 0.0049 [0.0002-0.1454], respectively), along with a positive correlation with transferrin (OR [95% CI], 853.7592 [20.7108-35194.4325]). To ensure the validity of our findings, we replicated the results through sensitivity analysis during the validation process. Conclusion: Our study demonstrated a significant correlation between iron status and bone and joint-related diseases.

[Causality between atopic diseases and osteoarthritis:a Mendelian randomization study].

OBJECTIVE: To explore causal relationship between atopic diseases (asthma and atopic dermatitis) and osteoarthritis (OA) by using mendelian randomization(MR). METHODS: Asthma and atopic dermatitis as instrumental variables were selected, searched them through IEU database, and selected the latest data with a large number of cases and single nucleotide polymorphism (SNP). Data were collected and processed using R language, inverse varianceweighted (IVW) method was adopted as main MR Evaluation method. Single linear regression was performed to estimate causality based on pooled knee and hip data from genome-wide association studies (GWAS). The forest map was drawn to visualize the results, and gene pleiotropy and sensitivity were analyzed by scatter plot and funnel plot. At the same time, asthma, atopic dermatitis, body mass index (BMI), osteoporosis and OA were selected for multivariate MR Analysis to exclude the effect of horizontal pleiotropy on the results in GWAS data. RESULTS: Analysis of MR-IVW results showed asthma was positively correlated with causal effect of OA [OR=1.41, 95%CI(1.07, 1.85), P=0.02], multivariate Mendelian randomization (MVMR) adjusted for BMI and osteoporosis and a direct causal effect on OA was observed [OR=1.57, 95%CI(1.03, 2.39), P=0.03)]. MR Results of two samples of atopic dermatitis and OA were [OR=1.01, 95%CI(0.97, 1.04), P=0.76], and MVMR results were [OR=1.02, 95%CI(0.99, 1.05), P=0.25], indicating no clear causal relationship between two samples. CONCLUSION: Asthma could increase risk of OA, atopic dermatitis has no obvious relationship with OA, and the relationship between atopic diseases and OA still needs to be discussed.

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Construction of ferroptosis-related gene signatures for identifying potential biomarkers and immune cell infiltration in osteoarthritis.

Osteoarthritis (OA) is a comprehensive joint disorder. The specific genes that trigger OA and the strategies for its effective management are not fully understood. This study focuses on identifying key genes linked to iron metabolism that could influence both the diagnosis and therapeutic approaches for OA. Analysis of GEO microarray data and iron metabolism genes identified 15 ferroptosis-related DEGs, enriched in hypoxia and HIF-1 pathways. Ten key hub genes (ATM, GCLC, PSEN1, CYBB, ATG7, MAP1LC3B, PLIN2, GRN, APOC1, SIAH2) were identified. Through stepwise regression, we screened 4 out of the above 10 genes, namely, GCLC, GRN, APOC1, and SIAH2, to obtain the optimal model. AUROCs for diagnosis of OA for the four hub genes were 0.81 and 0.80 of training and validation sets, separately. According to immune infiltration results, OA was related to significantly increased memory B cells, M0 macrophages, regulatory T cells, and resting mast cells but decreased activated dendritic cells. The four hub genes showed a close relation to them. It is anticipated that this model will aid in diagnosing osteoarthritis by assessing the expression of specific genes in blood samples. Moreover, studying these hub genes may further elucidate the pathogenesis of osteoarthritis.

Targeting Fascin1 maintains chondrocytes phenotype and attenuates osteoarthritis development.

Osteoarthritis (OA) is the most common form of arthritic disease, and phenotypic modification of chondrocytes is an important mechanism that contributes to the loss of cartilage homeostasis. This study identified that Fascin actin-bundling protein 1 (FSCN1) plays a pivotal role in regulating chondrocytes phenotype and maintaining cartilage homeostasis. Proteome-wide screening revealed markedly upregulated FSCN1 protein expression in human OA cartilage. FSCN1 accumulation was confirmed in the superficial layer of OA cartilage from humans and mice, primarily in dedifferentiated-like chondrocytes, associated with enhanced actin stress fiber formation and upregulated type I and III collagens. FSCN1-inducible knockout mice exhibited delayed cartilage degeneration following experimental OA surgery. Mechanistically, FSCN1 promoted actin polymerization and disrupted the inhibition of Decorin on TGF-ß1, leading to excessive TGF-ß1 production and ALK1/Smad1/5 signaling activation, thus, accelerated chondrocyte dedifferentiation. Intra-articular injection of FSCN1-overexpressing adeno-associated virus exacerbated OA progression in mice, which was mitigated by an ALK1 inhibitor. Moreover, FSCN1 inhibitor NP-G2-044 effectively reduced extracellular matrix degradation in OA mice, cultured human OA chondrocytes, and cartilage explants by suppressing ALK1/Smad1/5 signaling. These findings suggest that targeting FSCN1 represents a promising therapeutic approach for OA.

METTL14-mediated lncRNA-FAS-AS1 promotes osteoarthritis progression by up-regulating ADAM8.

BACKGROUND: Osteoarthritis (OA) is a prevalent degenerative disease. We explored the role and regulatory mechanisms of lncRNA-FAS-AS1 in OA progression. METHODS: We exposed human immortalized chondrocytes to IL-1ß for 24 h to induce an OA cell model. The target molecule levels were assessed using western blot and quantitative real-time PCR (RT-qPCR). Cell viability and apoptosis were measured using CCK-8 and flow cytometry. The m6A modification of FAS-AS1 was determined using MeRIP. We examined the binding relationships between FAS-AS1, Fragile X mental retardation 1 (FMR1), and A disintegrin and metalloproteinase 8 (ADAM8) using RIP and RNA pull-down. The OA animal model was established by separating the medial collateral ligament and medial meniscus. Safranin-O staining and Mankin's scale were employed to evaluate pathological changes within the cartilage. RESULTS: FAS-AS1, METTL14, and ADAM8 were upregulated, and the JAK/STAT3 signaling pathway was activated in OA mice and IL-1ß-induced chondrocytes. FAS-AS1 knockdown inhibited extracellular matrix degradation in IL-1ß-induced chondrocytes; however, ADAM8 overexpression reversed this effect. FAS-AS1 maintained the stability of ADAM8 mRNA by recruiting FMR1. METTL14 knockdown repressed FAS-AS1 expression in an m6A-dependent manner. FAS-AS1 overexpression reversed the inhibitory effects of METTL14 knockdown on JAK/STAT3 signaling and cartilage damage in the OA model both in vitro and in vivo. CONCLUSION: METTL14-mediated FAS-AS1 promotes OA progression through the FMR1/ADAM8/JAK/STAT3 axis.

Identification of novel drug targets for osteoarthritis by integrating genetics and proteomes from blood.

BACKGROUND: Osteoarthritis (OA) is a degenerative osteoarticular disease, involving genetic predisposition. How the risk variants confer the risk of OA through their effects on proteins remains largely unknown. Therefore, we aimed to discover new and effective drug targets for OA and its subtypes. METHODS: A proteome-wide association study (PWAS) was performed based on OA and its subtypes genome-wide association studies (GWAS) summary datasets and the protein quantitative trait loci (pQTL) data. Subsequently, Mendelian randomization (MR) and colocalization analysis was conducted to estimate the associations between protein and OA risk. The replication analysis was performed in an independent dataset of human plasma pQTL data. RESULTS: The abundance of seven proteins was causally related to OA, two proteins to knee OA and six proteins to hip OA, respectively. We replicated 2 of these proteins using an independent pQTL dataset. With the further support of colocalization, and higher ECM1 level was causally associated with a higher risk of OA and hip OA. Higher PCSK1 level was causally associated with a lower risk of OA. And higher levels of ITIH1, EFEMP1, and ERLEC1 were associated with decreased risk of hip OA. CONCLUSION: Our study provides new insights into the genetic component of protein abundance in OA and a promising therapeutic target for future drug development.

METTL14 promotes chondrocyte ferroptosis in osteoarthritis via m6A modification of GPX4.

BACKGROUND: Ferroptosis is caused by iron-dependent peroxidation of membrane phospholipids and chondrocyte ferroptosis contributes to osteoarthritis (OA) progression. Glutathione peroxidase 4 (GPX4) plays a master role in blocking ferroptosis. N6-methyladenosine (m6A) is an epigenetic modification among mRNA post-transcriptional modifications. This study investigated the effect of methyltransferase-like 14 (METTL14), the key component of the m6A methyltransferase, on chondrocyte ferroptosis via m6A modification. METHODS: An OA rat model was established through an intra-articular injection of monosodium iodoacetate in the right knee. OA cartilages in rat models were used for gene expression analysis. Primary mouse chondrocytes or ADTC5 cells were stimulated with IL-1ß or erastin. The m6A RNA methylation quantification kit was used to measure m6A level. The effect of METTL14 and GPX4 on ECM degradation and ferroptosis was investigated through western blotting, fluorescence immunostaining, propidium iodide staining, and commercially available kits. The mechanism of METTL14 action was explored through MeRIP-qPCR assays. RESULTS: METTL14 and m6A expression was upregulated in osteoarthritic cartilages and IL-1ß-induced chondrocytes. METTL14 depletion repressed the IL-1ß or erastin-stimulated ECM degradation and ferroptosis in mouse chondrocytes. METTL14 inhibited GPX4 gene through m6A methylation modification. GPX4 knockdown reversed the si-METTL14-mediated protection in IL-1ß-induced chondrocytes. CONCLUSION: METTL14 depletion inhibits ferroptosis and ECM degradation by suppressing GPX4 mRNA m6A modification in injured chondrocytes.

TIPE2 gene transfer ameliorates aging-associated osteoarthritis in a progeria mouse model by reducing inflammation and cellular senescence.

Osteoarthritis (OA) pain is often associated with the expression of tumor necrosis factor alpha (TNF-α), suggesting that TNF-α is one of the main contributing factors that cause inflammation, pain, and OA pathology. Thus, inhibition of TNF-α could potentially improve OA symptoms and slow disease progression. Anti-TNF-α treatments with antibodies, however, require multiple treatments and cannot entirely block TNF-α. TNF-α-induced protein 8-like 2 (TIPE2) was found to regulate the immune system's homeostasis and inflammation through different mechanisms from anti-TNF-α therapies. With a single treatment of adeno-associated virus (AAV)-TIPE2 gene delivery in the accelerated aging Zmpste24-/- (Z24-/-) mouse model, we found differences in Safranin O staining intensity within the articular cartilage (AC) region of the knee between TIPE2-treated mice and control mice. The glycosaminoglycan content (orange-red) was degraded in the Z24-/- cartilage while shown to be restored in the TIPE2-treated Z24-/- cartilage. We also observed that chondrocytes in Z24-/- mice exhibited a variety of senescent-associated phenotypes. Treatment with TIPE2 decreased TNF-α-positive cells, ß-galactosidase (ß-gal) activity, and p16 expression seen in Z24-/- mice. Our study demonstrated that AAV-TIPE2 gene delivery effectively blocked TNF-α-induced inflammation and senescence, resulting in the prevention or delay of knee OA in our accelerated aging Z24-/- mouse model.

Transcriptome combined with single cell to explore hypoxia-related biomarkers in osteoarthritis.

Osteoarthritis (OA) is a prevalent degenerative condition among the elderly on a global scale. Research has demonstrated that hypoxia can promote chondrocyte apoptosis and autophagy leading to OA. Hence, it was vital to screen the hypoxia related biomarkers in OA. We introduced transcriptome data to screen out differentially expressed genes (DEGs) in GSE114007 and GSE57218 (OA samples vs control samples). We performed differential expression analysis in key annotated cell to obtain differentially expressed marker genes at the single-cell level (GSE169454). Venn diagram was executed to identify hypoxia related differentially expressed genes (HR-DEGs) associated with OA. Further, feature genes were obtained through the application of least absolute shrinkage and selection operator (LASSO) regression and the Random Forest (RF) algorithm. Receiver operating characteristic (ROC) and expression level analysis were used to identify hypoxia related biomarkers in OA. We further performed immune infiltration and gene set enrichment analysis (GSEA) based on hypoxia related biomarkers. Finally, we analyzed the expression of biomarkers in single-cell level. We identified 2351 DEGs associated with OA. At the single-cell level, 242 differentially expressed marker genes were obtained. 12 HR-DEGs were retained venn diagram. Subsequently, three hypoxia related biomarkers (ADM, DDIT3 and MAFF) were identified. Moreover, we got 15 significantly different immune cells. Finally, we found a lower expression of ADM, DDIT3 and MAFF in OA group compared to the control group in ECs. Overall, we obtained three hypoxia related biomarkers (ADM, DDIT3 and MAFF) associated with OA, which established a theoretical basis for addressing OA.

17ß-estradiol promotes the progression of temporomandibular joint osteoarthritis by regulating the FTO/IGF2BP1/m6A-NLRC5 axis.

BACKGROUND: Temporomandibular joint osteoarthritis (TMJOA) is a degenerative cartilage disease. 17ß-estradiol (E2) aggravates the pathological process of TMJOA; however, the mechanisms of its action have not been elucidated. Thus, we investigate the influence of E2 on the cellular biological behaviors of synoviocytes and the molecular mechanisms. METHODS: Primary fibroblast-like synoviocytes (FLSs) isolated from rats were treated with TNF-α to establish cell model, and phenotypes were evaluated using cell counting kit-8, EdU, Tanswell, enzyme-linked immunosorbent assay, and quantitative real-time PCR (qPCR). The underlying mechanism of E2, FTO-mediated NLRC5 m6A methylation, was assessed using microarray, methylated RNA immunoprecipitation, qPCR, and western blot. Moreover, TMJOA-like rat model was established by intra-articular injection of monosodium iodoacetate (MIA), and bone morphology and pathology were assessed using micro-CT and H&E staining. RESULTS: The results illustrated that E2 facilitated the proliferation, migration, invasion, and inflammation of TNF-α-treated FLSs. FTO expression was downregulated in TMJOA and was reduced by E2 in FLSs. Knockdown of FTO promoted m6A methylation of NLRC5 and enhanced NLRC5 stability by IGF2BP1 recognition. Moreover, E2 promoted TMJ pathology and condyle remodeling, and increased bone mineral density and trabecular bone volume fraction, which was rescued by NLRC5 knockdown. CONCLUSION: E2 promoted the progression of TMJOA.

FTO-overexpressing extracellular vesicles from BM-MSCs reverse cellular senescence and aging to ameliorate osteoarthritis by modulating METTL3/YTHDF2-mediated RNA m6A modifications.

Extracellular vesicles secreted by bone marrow mesenchymal stem cells (BM-MSCs) exert therapeutic effects in osteoarthritis (OA). As an important N6-Methyladenosine (m6A) demethylase, it is reported that fat mass and obesity-associated protein (FTO) involves in regulating OA progression. Here, we generated MSCs-derived FTO-overexpressing EVs (FTO-EVs) to investigate whether FTO-EVs could be used for the potential treatment of OA. Our experiments verify that FTO-EVs suppressed cellular senescence, aging, apoptosis, and enhanced cell autophagy in LPS-treated chondrocytes in vitro and monosodium iodoacetate (MIA)-treated mice tissues in vivo. Also, ROS scavenger NAC reversed LPS-induced detrimental effects in chondrocytes. Mechanical experiments illustrated that FTO-EVs induced m6A-demethylation in autophagy-associated genes (Atg5 and Atg7) and pro-apoptosis gene (BNIP3), subsequently inducing the upregulation of Atg5/Atg7 and downregulation of BNIP3 in a YTHDF2-dependent manner, and the effects of FTO-EVs on the expressions of Atg5/Atg7 and BNIP3 were all reversed by upregulating m6A methyltransferase METTL3. Furthermore, FTO-EVs-induced suppressing effects on LPS-treated chondrocytes senescence and aging were abolished by Atg5/Atg7 knockdown and BNIP3 overexpression. In conclusion, this study evidenced that BM-MSCs-derived FTO-EVs suppressed cellular senescence and apoptosis, and triggered protective autophagy to suppress OA development through demethylating m6A modifications, and the engineering FTO-EVs could be potentially used to treat OA in clinic.

Identification of HTRA1, DPT and MXRA5 as potential biomarkers associated with osteoarthritis progression and immune infiltration.

BACKGROUND: Our study aimed to identify potential specific biomarkers for osteoarthritis (OA) and assess their relationship with immune infiltration. METHODS: We utilized data from GSE117999, GSE51588, and GSE57218 as training sets, while GSE114007 served as a validation set, all obtained from the GEO database. First, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were performed to identify hub modules and potential functions of genes. We subsequently screened for potential OA biomarkers within the differentially expressed genes (DEGs) of the hub module using machine learning methods. The diagnostic accuracy of the candidate genes was validated. Additionally, single gene analysis and ssGSEA was performed. Then, we explored the relationship between biomarkers and immune cells. Lastly, we employed RT-PCR to validate our results. RESULTS: WGCNA results suggested that the blue module was the most associated with OA and was functionally associated with extracellular matrix (ECM)-related terms. Our analysis identified ALB, HTRA1, DPT, MXRA5, CILP, MPO, and PLAT as potential biomarkers. Notably, HTRA1, DPT, and MXRA5 consistently exhibited increased expression in OA across both training and validation cohorts, demonstrating robust diagnostic potential. The ssGSEA results revealed that abnormal infiltration of DCs, NK cells, Tfh, Th2, and Treg cells might contribute to OA progression. HTRA1, DPT, and MXRA5 showed significant correlation with immune cell infiltration. The RT-PCR results also confirmed these findings. CONCLUSIONS: HTRA1, DPT, and MXRA5 are promising biomarkers for OA. Their overexpression strongly correlates with OA progression and immune cell infiltration.

Integrated bioinformatic analysis of the molecular mechanisms between type 2 diabetes mellitus and osteoarthritis.

Type 2 diabetes mellitus (T2DM) is a metabolic syndrome that has been identified as an independent risk factor for osteoarthritis (OA) and may even trigger and exacerbate the progression of OA. However, the relationship between T2DM and OA is complex and has not yet been fully clarified by current research. In this study, we analyzed the potential mechanism of action between T2DM and OA by bioinformatics. Transcriptome sequencing data of T2DM (GSE25724) and OA (GSE55235) were downloaded from the gene expression omnibus. Differential expression analysis was performed for different subgroups to obtain differentially expressed genes. The protein-protein interaction network was constructed using overlapping genes and screened for hub targets. Then the enrichment analysis was performed separately for overlapping and hub targets. The GeneMANIA is used to predict functionally similar genes of hub genes. Differential expression analyses revealed that 184 genes are involved in both diseases together. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment results showed that the overlapping genes were mainly involved in the advanced glycation end products-receptor of advanced glycation end products signaling pathway, the NF-kappa B signaling pathway, the mitogen-activated protein kinases signaling pathway, and the interleukin-17 signaling pathway in diabetic complications. The functions of genes similar to the hub genes are focused on cell chemotaxis, positive regulation of cell migration, positive regulation of RNA polymerase II transcription, regulation of leukocyte migration, epithelial cell proliferation, and integrated stress response signaling. The transcription factor Jun and C-X-C motif chemokine 8 may play an important role in the inflammatory response caused by advanced glycation end products. This study improves our understanding of T2DM complicating OA and helps to stimulate more effective treatments.

PLCγ1 deficiency in chondrocytes accelerates the age-related changes in articular cartilage and subchondral bone.

Ageing is the most prominent risk for osteoarthritis (OA) development. This study aimed to investigate the role of phosphoinositide-specific phospholipase Cγ (PLCγ) 1, previously linked to OA progression, in regulating age-related changes in articular cartilage and subchondral bone. d-galactose (d-Gal) was employed to treat chondrocytes from rats and mice or injected intraperitoneally into C57BL/6 mice. RTCA, qPCR, Western blot and immunohistochemistry assays were used to evaluate cell proliferation, matrix synthesis, senescence genes and senescence-associated secretory phenotype, along with PLCγ1 expression. Subchondral bone morphology was assessed through micro-CT. In mice with chondrocyte-specific Plcg1 deficiency (Plcg1flox/flox; Col2a1-CreERT), articular cartilage and subchondral bone were examined over different survival periods. Our results showed that d-Gal induced chondrocyte senescence, expedited articular cartilage ageing and caused subchondral bone abnormalities. In d-Gal-induced chondrocytes, diminished PLCγ1 expression was observed, and its further inhibition by U73122 exacerbated chondrocyte senescence. Plcg1flox/flox; Col2a1-CreERT mice exhibited more pronounced age-related changes in articular cartilage and subchondral bone compared to Plcg1flox/flox mice. Therefore, not only does d-Gal induce senescence in chondrocytes and age-related changes in articular cartilage and subchondral bone, as well as diminished PLCγ1 expression, but PLCγ1 deficiency in chondrocytes may also accelerate age-related changes in articular cartilage and subchondral bone. PLCγ1 may be a promising therapeutic target for mitigating age-related changes in joint tissue.