Molecular Mechanisms Of Osteoarthritis Research Articles

Two Members of Vitamin-K-Dependent Proteins, Gla-Rich Protein (GRP) and Matrix Gla Protein (MGP), as Possible New Players in the Molecular Mechanism of Osteoarthritis.

Objectives: The pathophysiology of osteoarthritis is mainly unknown. Matrix Gla protein (MGP) and Gla-rich protein (GRP) are both vitamin-K-dependent mineralization inhibitors. In this study, we aimed to compare the levels of MGP and GRP in the synovial fluid of osteoarthritic (OA) and non-osteoarthritic (non-OA) knee joints. Materials and Methods: Two groups were formed, with one consisting of patients with OA and the other non-OA, serving as a control group. The non-OA group included individuals who had arthroscopic surgery for non-cartilage-related issues. In the OA group, all participants had undergone total knee arthroplasty because of grade 4 primary degenerative osteoarthritis. During the operation, at least 1 mL of knee synovial fluid was collected. The GRP and MGP levels in the synovial fluid were measured using an ELISA kit. Results: The mean age in the OA group (62.03 ± 11.53 years) was significantly higher than that in the non-OA group (47.70 ± 14.49 years; p = 0.0001). GRP levels were significantly higher in the OA group (419.61 ± 70.14 ng/mL) compared to the non-OA group (382.18 ± 62.34 ng/mL; p = 0.037). MGP levels were significantly higher in the OA group (67.76 ± 11.36 ng/mL) compared to the non-OA group (53.49 ± 18.28 ng/mL; p = 0.001). Calcium levels (Ca++) were also significantly higher in the OA group (12.89 ± 3.43 mg/dL) compared to the non-OA group (9.51 ± 2.15 mg/dL; p = 0.0001). There was a significantly positive correlation between MGP levels and age (p = 0.011, R = +0.335). Linear regression analysis was performed to determine the effect of age on MGP levels (p = 0.011, R-Square = 0.112). The dependent variable in this analysis was MGP (ng/mL), and age was the predictor. Conclusions: In conclusion, both GRP and MGP are potentially usable biomarkers in osteoarthritis. However, GRP seems to be more valuable because it is not associated with age. In the future, both proteins could provide important contributions to the diagnosis and treatment of osteoarthritis.

TPX2 upregulates MMP13 to promote the progression of lipopolysaccharide-induced osteoarthritis.

This study seeks to identify potential clinical biomarkers for osteoarthritis (OA) using bioinformatics and investigate OA mechanisms through cellular assays. Differentially Expressed Genes (DEGs) from GSE52042 (four OA samples, four control samples) were screened and analyzed with protein-protein interaction (PPI) analysis. Overlapping genes in GSE52042 and GSE206848 (seven OA samples, and seven control samples) were identified and evaluated using Gene Set Enrichment Analysis (GSEA) and clinical diagnostic value analysis to determine the hub gene. Finally, whether and how the hub gene impacts LPS-induced OA progression was explored by in vitro experiments, including Western blotting (WB), co-immunoprecipitation (Co-IP), flow cytometry, etc. Bioinformatics analysis of DEGs (142 up-regulated and 171 down-regulated) in GSE52042 identified two overlapping genes (U2AF2, TPX2) that exhibit significant clinical diagnostic value. These genes are up-regulated in OA samples from both GSE52042 and GSE206848 datasets. Notably, TPX2, which AUC = 0.873 was identified as the hub gene. In vitro experiments have demonstrated that silencing TPX2 can alleviate damage to chondrocytes induced by lipopolysaccharide (LPS). Furthermore, there is a protein interaction between TPX2 and MMP13 in OA. Excessive MMP13 can attenuate the effects of TPX2 knockdown on LPS-induced changes in OA protein expression, cell growth, and apoptosis. In conclusion, our findings shed light on the molecular mechanisms of OA and suggested TPX2 as a potential therapeutic target. TPX2 could promote the progression of LPS-induced OA by up-regulating the expression of MMP13, which provides some implications for clinical research.

Development and validation of biomarkers related to PANoptosis in osteoarthritis.

Osteoarthritis (OA) is a high-incidence disease of the orthopedic system. However, studies on the molecular mechanisms of OA and pyroptosis, apoptosis, and necroptosis (PANoptosis) at the transcriptome level remain scarce. Therefore, this study purposed to detect biomarkers in OA and explore their relationship to the immune microenvironment. OA-related expression data was sourced from the Gene Expression Omnibus (GEO) database. Subsequently, differentially expressed analysis and a Venn diagram were performed to obtain differentially expressed PANoptosis-related genes (DEPGs). Furthermore, the least absolute shrinkage and selection operator (LASSO), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and random forest (RF) were implemented to screen diagnostic genes. Receiver operating characteristic (ROC) curves were performed to verify the diagnostic ability of the diagnostic genes. Next, immune infiltration analysis was performed to find the relationships between differential immune cells (OA vs. normal) and diagnostic genes. Finally, drug prediction analysis was also carried out, and the expression of diagnostic genes was verified in external datasets. A total of 62 DEPGs were identified, which were enriched for regulating apoptotic signaling pathways, tumor necrosis factor (TNF) signaling pathways, and other related pathways. Three feature genes, nuclear factor-kappa-B inhibitor-alpha (NFKBIA), RING finger protein 34 (RNF34), and serine incorporator 3 (SERINC3) were obtained by intersecting genes obtained by the LASSO regression algorithm, SVM algorithm, and RF algorithm and showed excellent diagnostic efficacy with the Area under the curve (AUC) values of individual genes were all greater than 0.7, indicating that the model was more effective. Immuno-infiltration analysis showed that RNF34 was positively correlated with CD56dim natural killer cells, type 17 helper T cells, and NFKBIA was positively correlated with plasmacytoid dendritic cells. Additionally, 12 drugs were predicted by NFKBIA, such as gambogic acid and dioscin. In addition, NFKBIA and SERINC3 were significantly downregulated, and RNF34 was upregulated in OA samples. Three genes (NFKBIA, RNF34, and SERINC3) related to PANoptosis, were obtained by bioinformatics analysis, which would provide a new direction for the diagnosis and treatment of OA.

Elucidating the role of ubiquitination and deubiquitination in osteoarthritis progression.

Osteoarthritis is non-inflammatory degenerative joint arthritis, which exacerbates disability in elder persons. The molecular mechanisms of osteoarthritis are elusive. Ubiquitination, one type of post-translational modifications, has been demonstrated to accelerate or ameliorate the development and progression of osteoarthritis via targeting specific proteins for ubiquitination and determining protein stability and localization. Ubiquitination process can be reversed by a class of deubiquitinases via deubiquitination. In this review, we summarize the current knowledge regarding the multifaceted role of E3 ubiquitin ligases in the pathogenesis of osteoarthritis. We also describe the molecular insight of deubiquitinases into osteoarthritis processes. Moreover, we highlight the multiple compounds that target E3 ubiquitin ligases or deubiquitinases to influence osteoarthritis progression. We discuss the challenge and future perspectives via modulation of E3 ubiquitin ligases and deubiquitinases expression for enhancement of the therapeutic efficacy in osteoarthritis patients. We conclude that modulating ubiquitination and deubiquitination could alleviate the osteoarthritis pathogenesis to achieve the better treatment outcomes in osteoarthritis patients.

RNA-Seq Reveals the mRNAs, miRNAs, and lncRNAs Expression Profile of Knee Joint Synovial Tissue in Osteoarthritis Patients

Osteoarthritis (OA) is a chronic disease common in the elderly population and imposes significant health and economic burden. Total joint replacement is the only currently available treatment but does not prevent cartilage degeneration. The molecular mechanism of OA, especially the role of inflammation in disease progression, is incompletely understood. We collected knee joint synovial tissue samples of eight OA patients and two patients with popliteal cysts (controls), measured the expression levels of lncRNAs, miRNAs, and mRNAs in these tissues by RNA-seq, and identified differentially expressed genes (DEGs) and key pathways. In the OA group, 343 mRNAs, 270 lncRNAs, and 247 miRNAs were significantly upregulated, and 232 mRNAs, 109 lncRNAs, and 157 miRNAs were significantly downregulated. mRNAs potentially targeted by lncRNAs were predicted. Nineteen overlapped miRNAs were screened based on our sample data and GSE 143514 data. Pathway enrichment and functional annotation analyses showed that the inflammation-related transcripts CHST11, ALDH1A2, TREM1, IL-1β, IL-8, CCL5, LIF, miR-146a-5p, miR-335-5p, lncRNA GAS5, LINC02288, and LOC101928134 were differentially expressed. In this study, inflammation-related DEGs and non-coding RNAs were identified in synovial samples, suggesting that competing endogenous RNAs have a role in OA. TREM1, LIF, miR146-5a, and GAS5 were identified to be OA-related genes and potential regulatory pathways. This research helps elucidate the pathogenesis of OA and identify novel therapeutic targets for this disorder.

MiR-199a-5p Reduces Chondrocyte Hypertrophy and Attenuates Osteoarthritis Progression via the Indian Hedgehog Signal Pathway.

Osteoarthritis (OA), the most common type of arthritis, is an age-associated disease, characterized by the progressive degradation of articular cartilage, synovial inflammation, and degeneration of subchondral bone. Chondrocyte proliferation is regulated by the Indian hedgehog (IHH in humans, Ihh in animals) signaling molecule, which regulates hypertrophy and endochondral ossification in the development of the skeletal system. microRNAs (miRNAs, miRs) are a family of about 22-nucleotide endogenous non-coding RNAs, which negatively regulate gene expression. In this study, the expression level of IHH was upregulated in the damaged articular cartilage tissues among OA patients and OA cell cultures, while that of miR-199a-5p was the opposite. Further investigations demonstrated that miR-199a-5p could directly regulate IHH expression and reduce chondrocyte hypertrophy and matrix degradation via the IHH signal pathway in the primary human chondrocytes. The intra-articular injection of synthetic miR-199a-5p agomir attenuated OA symptoms in rats, including the alleviation of articular cartilage destruction, subchondral bone degradation, and synovial inflammation. The miR-199a-5p agomir could also inhibit the Ihh signaling pathway in vivo. This study might help in understanding the role of miR-199a-5p in the pathophysiology and molecular mechanisms of OA and indicate a potential novel therapeutic strategy for OA patients.

Identification of Key Diagnostic Markers and Immune Infiltration in Osteoarthritis.

Osteoarthritis (OA) is a worldwide chronic disease of the articulating joints. An increasing body of data demonstrates the immune system's involvement in osteoarthritis. The molecular mechanisms of OA are still unclear. This study aimed to search for OA immunerelated hub genes and determine appropriate diagnostic markers to help the detection and treatment of the disease. Gene expression data were downloaded from the GEO database. Firstly, we analyzed and identified the differentially expressed genes (DEGs) using R packages. Meanwhile, ssGSEA was used to determine the activation degree of immune-related genes (IRGs), and WGCNA analysis was applied to search for co-expressed gene modules associated with immune cells. Then, critical networks and hub genes were found in the PPI network. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analyzed the biological functions of genes. The ability of the hub genes to differentiate OA from controls was assessed by the area under the ROC curve. A miRNA and transcription factor (TF) regulatory network was constructed according to their relationship with hub genes. Finally, the validation of hub genes was carried out by qPCR. In total, 353 DEGs were identified in OA patients compared with controls, including 222 upregulated and 131 downregulated genes. WGCNA successfully identified 34 main functional modules involved in the pathogenesis of OA. The most crucial functional module involved in OA included 89 genes. 19 immune-related genes were obtained by overlapping DEGs with the darkgrey module. The String database was constructed using the protein-protein interaction (PPI) network of 19 target genes, and 7 hub genes were identified by MCODE. ROC curve showed that 7 hub genes were potential biomarkers of OA. The expression levels of hub genes were validated by qPCR, and the results were consistent with those from bioinformatic analyses. Immune-related hub genes, including TYROBP, ITGAM, ITGB2, C1QC, MARCO, C1QB, and TLR8, may play critical roles in OA development. ITGAM had the highest correction on immune cells.

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.

Иммуногенетические аспекты развития остеоартрита (обзор литературы)

Inflammation plays critical role in the onset and progression of osteoarthritis (OA), a joint disease affecting more than 10 % of the world's population. Exporing immunological mechanisms of osteoarthritis is essential. The present paper is a literature review of immunogenetic aspects of the pathogenesis of the disease. The study is aimed at analysis and summary of information concerning the immunogenetics and molecular mechanisms of osteoarthritis. Material and methods The original literature search was conducted on key resources including Scientific Electronic Library (www. elibrary.ru) and the National Library of Medicine (www.pubmed.org) with subsequent selection of articles, analysis and synthesis of information. Results and discussion Mutations in proinflammatory cytokine and receptor genes, metalloprotease genes, HLA genes and in the anti-inflammatory cytokine (IL-4) gene, polymorphisms in phospholipase and IL-2 genes are more common for OA patients than for healthy subjects. Epigenetic regulation in OA include a decreased methylation of the promoters of proinflammatory cytokine and metalloprotease genes and a decreased methylation of NF‑κB‑sensitive iNOS enhancer sites. OA patients show an increased activity of histone acetylases in the IL-6 promoter area. In contrast, the expression of anti-inflammatory cytokines is decreased due to the reduced activity of the SIRT1 deacetylase.

Proteomics Profiling of Human Synovial Fluid Suggests Increased Protein Interplay in Early-Osteoarthritis (OA) That Is Lost in Late-Stage OA

The underlying molecular mechanisms in osteoarthritis (OA) development are largely unknown. This study explores the proteome and the pairwise interplay of proteins in synovial fluid from patients with late-stage knee OA (arthroplasty), early knee OA (arthroscopy due to degenerative meniscal tear), and from deceased controls without knee OA. Synovial fluid samples were analyzed using state-of-the-art mass spectrometry with data-independent acquisition. The differential expression of the proteins detected was clustered and evaluated with data mining strategies and a multilevel model. Group-specific slopes of associations were estimated between expressions of each pair of identified proteins to assess the co-expression (i.e., interplay) between the proteins in each group. More proteins were increased in early-OA versus controls than late-stage OA versus controls. For most of these proteins, the fold changes between late-stage OA versus controls and early-stage OA versus controls were remarkably similar suggesting potential involvement in the OA process. Further, for the first time, this study illustrated distinct patterns in protein co-expression suggesting that the interplay between the protein machinery is increased in early-OA and lost in late-stage OA. Further efforts should focus on earlier stages of the disease than previously considered.

Insight into osteoarthritis through integrative analysis of metabolomics and transcriptomics

Lack of clinically specific biomarkers has impeded the diagnosis of osteoarthritis (OA) and limited understanding of pathogenesis for OA has also restrained the enhancement of therapeutic measures. In the study, plasma untargeted metabolomics of twelve OA patients and twenty healthy controls (HC) were analyzed by gas chromatography coupled with quadrupole time-of-flight mass spectrometry (GC/Q-TOF-MS). The differential metabolites (DMs) between OA and HC were evaluated by multivariate analysis and Bayes discriminant analysis was employed to discover potential diagnosis biomarkers. Meanwhile a transcriptomic dataset GSE55235 was downloaded from GEO database to explore the differentially expressed genes (DEGs) between OA and HC by R/Bioconductor project. Finally, an integrative analysis of DMs and DEGs was performed to investigate the possible molecular mechanisms of OA. As a result, a panel of three metabolites including succinic acid, xanthurenic acid and L-tryptophan was revealed to potentially act as biomarker for the diagnosis of OA. Furthermore, the integrated analysis of metabolomics and transcriptomics showed the top three enrichment in the T cell receptor signaling pathway, Fc epsilon RI (FcεRI) signaling pathway, and thermogenesis, explaining the inflammation, joint destruction and energy metabolism disorders in OA.

Identification and functional analysis of long non-coding RNAs in the synovial membrane of osteoarthritis patients.

Osteoarthritis (OA), the most common chronic joint disease in the elderly, has become a significant economic burden for families and societies worldwide. Although treatments are continually improving, current drugs only target joint pain, with no effective therapies modifying OA progression. Long noncoding RNAs (lncRNAs), which have received increasing attention in recent years, are abnormally expressed in OA cartilage. In the present study, weighted coexpression network analysis (WGCNA) was applied to identify modules related to certain OA clinical traits. In total, 4404 coding genes and 161 lncRNAs were differentially expressed based on two OA expression profile data sets and normal control samples. Subsequently, 11 independent modules were acquired, and the green module, with a total of 49 hub genes, was identified as the most relevant to OA. These hub genes were validated using the GSE12021 data set. There was only one lncRNA among the hub genes, namely, NONHSAG034351. Thus, we further explored the function of NONHSAG034351‐related genes in the network. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that NONHSAG034351‐associated genes are involved in the response to lipopolysaccharide, angiogenesis, tumour necrosis factor (TNF) signalling, and mitogen‐activated protein kinase (MAPK) signalling pathways. In conclusion, we identified modules through WGCNA related to OA clinical traits. NONHSAG034351, the only hub‐lncRNA, was downregulated in OA synovial tissue and might play a significant role in the pathological progression of this disease. Our findings have important clinical implications and could provide novel biomarkers that indicate the molecular mechanisms of OA and act as potential therapeutic targets.Significance of this studyLong noncoding RNAs (lncRNAs) have been reported to be abnormally expressed in osteoarthritis (OA), which is the most common chronic joint disease among the elderly. In the present study, we report the expression profiles of lncRNAs in OA and the identification of modules through WGCNA related to OA clinical traits. NONHSAG034351, the only hub‐lncRNA identified to be downregulated in the synovial tissue of OA patients, might play a significant role in the pathological progression of OA. Furthermore, our findings provide novel biomarkers associated with the molecular mechanisms underlying OA pathogenesis, thus implying potential therapeutic targets with important clinical implications.

Metabonomic-Transcriptome Integration Analysis on Osteoarthritis and Rheumatoid Arthritis.

Purpose This study is aimed at exploring the potential metabolite/gene biomarkers, as well as the differences between the molecular mechanisms, of osteoarthritis (OA) and rheumatoid arthritis (RA). Methods Transcriptome dataset GSE100786 was downloaded to explore the differentially expressed genes (DEGs) between OA samples and RA samples. Meanwhile, metabolomic dataset MTBLS564 was downloaded and preprocessed to obtain metabolites. Then, the principal component analysis (PCA) and linear models were used to reveal DEG-metabolite relations. Finally, metabolic pathway enrichment analysis was performed to investigate the differences between the molecular mechanisms of OA and RA. Results A total of 976 DEGs and 171 metabolites were explored between OA samples and RA samples. The PCA and linear module analysis investigated 186 DEG-metabolite interactions including Glycogenin 1- (GYG1-) asparagine_54, hedgehog acyltransferase- (HHAT-) glucose_70, and TNF receptor-associated factor 3- (TRAF3-) acetoacetate_35. Finally, the KEGG pathway analysis showed that these metabolites were mainly enriched in pathways like gap junction, phagosome, NF-kappa B, and IL-17 pathway. Conclusions Genes such as HHAT, GYG1, and TRAF3, as well as metabolites including glucose, asparagine, and acetoacetate, might be implicated in the pathogenesis of OA and RA. Metabolites like ethanol and tyrosine might participate differentially in OA and RA progression via the gap junction pathway and phagosome pathway, respectively. TRAF3-acetoacetate interaction may be involved in regulating inflammation in OA and RA by the NF-kappa B and IL-17 pathway.

MiRNA-103 promotes chondrocyte apoptosis by down-regulation of Sphingosine kinase-1 and ameliorates PI3K/AKT pathway in osteoarthritis.

Objectives: The aim of the present study was to determine the effects of miRNA-103 on chondrocyte apoptosis and molecular mechanisms in osteoarthritis (OA) progression. Methods: The cell proliferation, apoptosis, and recovery ability were measured by cell counting kit-8 (CCK-8), flow cytometry, and wound healing assays. The interaction of miRNA-103 and Sphingosine kinase-1 (SPHK1) were determined by using luciferase reporter assay. The expression of mRNA and proteins were measured by qRT-PCR and Western blot. OA rat model was established by surgery stimulation. Results: miRNA-103 expression was significantly increased in the cartilage of OA patients and surgery-induced OA rat models. miRNA-103 transfection into primary rat chondrocytes reduced SPHK1 expression, induced apoptosis, inhibited cell proliferation, and impeded scratch assay wound closure. Moreover, expression of total AKT, and p-AKT were significantly reduced in miRNA-103-overexpressing chondrocytes while SPHK1 up-regulation increased the expression of phosphatidylinsitol-3-kinase (PI3K) and p-AKT, and reversed the proliferation suppression induced by the miRNA-103 mimic. Conclusions: Our studies suggest that miRNA-103 contributes to chondrocyte apoptosis, promoting OA progression by down-regulation of PI3K/AKT pathway through the reduction in SPHK1 activity.

265 17BETA-ESTRADIOL-INDUCED UP-REGULATION OF TYPE II COLLAGEN EXPRESSION IS MEDIATED BY ER ALPHA/SP/SOX-9/P300 COMPLEX THROUGH COL2A1 PROMOTER/FIRST INTRON INTERACTIONS IN DIFFERENTIATED AND DEDIFFERENTIATED ARTICULAR CHONDROCYTES

Purpose: Type II collagen, encoded by COL2A1 gene, is a phenotypic marker of articular cartilage whose expression is strongly decreased during osteoarthritis (OA) process. Specific proteins (Sp) and Sox proteins have been previously characterized to be major regulators of this gene. Besides, the existence of a link between estrogen deprivation and osteoarthritis in postmenopausal women suggests that 17β-estradiol (17β-E2) may be a critical modulator of cartilaginous matrix homeostasis. The aim of present study was to investigate the molecular mechanisms regulating type II collagen gene expression under the effect of 17β-E2, and to characterize the genomic pathway via estrogen receptors (ER). Methods: Articular chondrocytes were isolated from 3-week old rabbits and incubated for 24 hours with increasing concentrations of 17β-E2 (0 to 10 nM). Nuclear proteins were extracted and submitted to gel retardation assays in order to determine Sp and Sox proteins binding activities on COL2A1 gene. In some experiments, relative expression of Sp1/Sp3 or Sox-9 was inhibited by siRNAs strategies. Moreover, chromatin immunoprecipitation was used to study protein-protein interactions on COL2A1 promoter and enhancer sequences. Results: We have previously shown that 17β-E2 could stimulate type II collagen neosynthesis, protein level and corresponding steady-state levels of COL2A1 mRNAs in primary and in vitro dedifferentiated rabbit articular chondrocytes. 17β-E2 action was mediated, in part, by an ERα/Sp transactivating effect on the -266/-63 bp region of COL2A1 proximal promoter. Our new data showed that 17β-E2 also increases the DNA-binding activities of Sp1/Sp3 and Soxs proteins to the first intron region including COL2A1 specific enhancer. In addition, Sp1, Sp3 and Sox-9 siRNAs prevented hERα66-induced transactivation of COL2A1, suggesting that these factors are required for COL2A1 up-regulation. Moreover, chromatin immunoprecipitation assays indicated that ERα physically interacts in vivo with Sp1, Sp3, Sox-9 and p300 transcription factors, on both COL2A1 promoter and enhancer sequences. Thus, considering that all these transcription factors are known to act in concert, we proposed that 17β-E2 in vivo effect could be mediated by a bridging complex, composed of ERα, Sp1, Sp3, Sox-9 and p300 transcription factors, which could establish a physical link between the two main cisregulatory regions of the gene, and consequently, may facilitate COL2A1 transcription process. Besides, this transcriptional activation of COL2A1 gene requires the ERα transactivation domains, AF-1 and AF-2, as demonstrated by using ERα mutants lacking these functional domains. Conclusions: Understanding the molecular basis for 17β-E2/ERα induction of COL2A1 transcription provides new insights into molecular mechanisms of OA and could be therefore attractive for some applications in the tissue engineering of cartilage.

218 GENOME-WIDE COMPARATIVE TRANSCRIPTOME ANALYSIS OF CARTILAGE FORMATION IN VIVO

Purpose: To explore the molecular mechanisms of osteoarthritis (OA) initiation and progression, global gene expression profiling was performed on cartilage from mice with surgically-induced OA. We used WT mice, and mice lacking ADAMTS-5 activity (ADAMTS-5 Dcat). By comparing the gene expression during OA in these mice we have distinguished early events leading to aggrecan degradation (pre-fibrillated changes) from the downstream progressive phases that follow loss of aggrecan. Methods: Mechanical instability was introduced into 10 week old male mouse knee joints by surgical destabilization of the medial meniscus (DMM). In this model focal degeneration, exemplified by loss of aggrecan in the non-calcified articular cartilage, occurs in the medial tibial plateau 2 weeks after surgery in WT mice. After 6 weeks, aggrecan loss had progressed and cartilage fibrillation was evident. In ADAMTS-5 Dcat mice aggrecan loss and cartilage erosion is significantly reduced. Noncalcified cartilage from the developing lesion in DMM or sham-operated joints at 1, 2 and 6 weeks post-surgery was harvested by laser microdissection. Chondrocyte total RNA was extracted and cRNA generated by linear amplification (MessageAmp, Ambion), labeled with Cy3/Cy5 and hybridized to 44k whole genome microarrays (Agilent). Data was validated by quantitative PCR of selected genes. Results: There was an early upregulation (1 week) in WT mice of cartilage hypertrophy markers, such as collagen X. However in the ADAMTS-5 Dcat mice, these were not upregulated until 6 weeks, suggesting that the hypertrophic response of chondrocytes is not an initiating event, but an event downstream of the onset of ADAMTS-5 activity and/or cartilage degeneration. Of particular interest was the upregulation of the inflammatory mediator Ptgs2 (Cox-2) early (1 and 2 weeks) in WT OA mice. Upregulation of Cox-2 was not seen in ADAMTS-5 Dcat mice. Dysregulation of several Bmps (eg Bmp7), inflammatory cytokines, Fgfs, members of the Wnt/b-catenin pathway were apparent in WT mice. Expression profiling also showed numerous changes in gene expression that followed the same pattern in both WT and ADAMTS-5 Dcat mice, and thus are likely to be independent of ADAMTS-5-mediated aggrecan degradation. These changes include upregulation of several cathepsins (eg cathepsin S), Bmps (eg Bmp7) lumican and fibronectin. Conclusions: This well controlled OA model combined with precise microdissection of cartilage from developing cartilage lesions and microarray technology provides new insights into gene expressed during the initiation and progression of OA. Furthermore the comparison of OA gene expression in WT, ADAMTS-5 Dcat and other mouse models will allow us to prioritize candidate genes for functional analysis.

217 GLOBAL GENE EXPRESSION PROFILING OF EARLY OSTEOARTHRITIS IN WILD-TYPE MICE AND MICE LACKING ADAMTS-5 ACTIVITY

Purpose: To explore the molecular mechanisms of osteoarthritis (OA) initiation and progression, global gene expression profiling was performed on cartilage from mice with surgically-induced OA. We used WT mice, and mice lacking ADAMTS-5 activity (ADAMTS-5 Dcat). By comparing the gene expression during OA in these mice we have distinguished early events leading to aggrecan degradation (pre-fibrillated changes) from the downstream progressive phases that follow loss of aggrecan. Methods: Mechanical instability was introduced into 10 week old male mouse knee joints by surgical destabilization of the medial meniscus (DMM). In this model focal degeneration, exemplified by loss of aggrecan in the non-calcified articular cartilage, occurs in the medial tibial plateau 2 weeks after surgery in WT mice. After 6 weeks, aggrecan loss had progressed and cartilage fibrillation was evident. In ADAMTS-5 Dcat mice aggrecan loss and cartilage erosion is significantly reduced. Noncalcified cartilage from the developing lesion in DMM or sham-operated joints at 1, 2 and 6 weeks post-surgery was harvested by laser microdissection. Chondrocyte total RNA was extracted and cRNA generated by linear amplification (MessageAmp, Ambion), labeled with Cy3/Cy5 and hybridized to 44k whole genome microarrays (Agilent). Data was validated by quantitative PCR of selected genes. Results: There was an early upregulation (1 week) in WT mice of cartilage hypertrophy markers, such as collagen X. However in the ADAMTS-5 Dcat mice, these were not upregulated until 6 weeks, suggesting that the hypertrophic response of chondrocytes is not an initiating event, but an event downstream of the onset of ADAMTS-5 activity and/or cartilage degeneration. Of particular interest was the upregulation of the inflammatory mediator Ptgs2 (Cox-2) early (1 and 2 weeks) in WT OA mice. Upregulation of Cox-2 was not seen in ADAMTS-5 Dcat mice. Dysregulation of several Bmps (eg Bmp7), inflammatory cytokines, Fgfs, members of the Wnt/b-catenin pathway were apparent in WT mice. Expression profiling also showed numerous changes in gene expression that followed the same pattern in both WT and ADAMTS-5 Dcat mice, and thus are likely to be independent of ADAMTS-5-mediated aggrecan degradation. These changes include upregulation of several cathepsins (eg cathepsin S), Bmps (eg Bmp7) lumican and fibronectin. Conclusions: This well controlled OA model combined with precise microdissection of cartilage from developing cartilage lesions and microarray technology provides new insights into gene expressed during the initiation and progression of OA. Furthermore the comparison of OA gene expression in WT, ADAMTS-5 Dcat and other mouse models will allow us to prioritize candidate genes for functional analysis.

Interleukin‐1β up‐regulation of Smad7 via NF‐κB activation in human chondrocytes

We have previously shown that interleukin-1beta (IL-1beta) impairs transforming growth factor beta (TGFbeta) signaling through TGFbeta receptor type II (TGFbetaRII) down-regulation and Smad7 up-regulation. This mechanism could account for the reduced responsiveness of osteoarthritic chondrocytes to TGFbeta and the cartilage breakdown linked to this disease. The aim of this study was to investigate the molecular mechanism underlying the IL-1beta-induced stimulation of Smad7 in human articular chondrocytes. Human articular chondrocytes were treated with IL-1beta in the presence of TGFbeta1, pyrrolidine dithiocarbamate (a repressor of the NF-kappaB pathway), or cycloheximide. Then, steady-state messenger RNA and protein levels were estimated by real-time reverse transcription-polymerase chain reaction and immunocytology. In addition, transient transfections of p65 expression vector or p65-targeted short hairpin RNA were performed to define the effect of NF-kappaB on Smad7 expression. TGFbetaRII overexpression restored the TGFbeta response of human articular chondrocytes. However, this effect was transient, implying that a secondary mechanism was responsible for the alteration of the TGFbeta response with long-term exposure to IL-1beta. Moreover, IL-1beta caused a late induction of the inhibitory Smad7. This effect was direct, since it did not require de novo synthesis. In addition, we established, by experiments with gain/loss of function, that the up-regulation of Smad7 by IL-1beta is mediated through the NF-kappaB pathway, especially the p65 subunit. These findings clarify the regulatory process of IL-1beta on Smad7 expression. Understanding the molecular basis of IL-1beta induction of Smad7 and the reduction of chondrocyte responsiveness to TGFbeta provides new insights into the molecular mechanisms of osteoarthritis and may facilitate the identification of novel approaches for its treatment.

Association analysis of single nucleotide polymorphisms in cartilage-specific collagen genes with knee and hip osteoarthritis in the Japanese population.

Osteoarthritis (OA) is one of the most common diseases in the elderly. Although its pathophysiology is complex and its molecular basis remains to be determined, much evidence suggests that OA has strong genetic determinants. To search for susceptibility loci of OA, we selected seven candidate genes encoding cartilage-specific collagens (type II, IX, X, and XI collagens) and performed association analysis for OA using single nucleotide polymorphisms (SNPs) in the coding region of these genes. Four hundred seventeen OA samples and 280 control samples were collected from the Japanese population, and 12 SNPs were genotyped. Our studies have identified two susceptibility loci of OA: COL2A1 and COL9A3. An SNP in COL9A3 showed significant association with knee OA (p = 0.002, odds ratio [OR] = 1.48). Haplotype analysis showed significant association between a specific haplotype of COL2A1 and hip OA (p = 0.024; OR = 1.30). Further analysis of these two genes will shed light on the molecular mechanisms of OA.