Objective To use a computational approach to investigate the cellular and extracellular matrix changes that occur with age in the knee joints of mice. Methods Knee joints from an inbred C57/BL1/6 (ICRFa) mouse colony were harvested at 3–30 months of age. Sections were stained with H&E, Safranin-O, Picro-sirius red and antibodies to matrix metalloproteinase-13 (MMP-13), nitrotyrosine, LC-3B, Bcl-2, and cleaved type II collagen used for immunohistochemistry. Based on this and other data from the literature, a computer simulation model was built using the Systems Biology Markup Language using an iterative approach of data analysis and modelling. Individual parameters were subsequently altered to assess their effect on the model. Results A progressive loss of cartilage matrix occurred with age. Nitrotyrosine, MMP-13 and activin receptor-like kinase-1 (ALK1) staining in cartilage increased with age with a concomitant decrease in LC-3B and Bcl-2. Stochastic simulations from the computational model showed a good agreement with these data, once transforming growth factor-β signalling via ALK1/ALK5 receptors was included. Oxidative stress and the interleukin 1 pathway were identified as key factors in driving the cartilage breakdown associated with ageing. Conclusions A progressive loss of cartilage matrix and cellularity occurs with age. This is accompanied with increased levels of oxidative stress, apoptosis and MMP-13 and a decrease in chondrocyte autophagy. These changes explain the marked predisposition of joints to develop osteoarthritis with age. Computational modelling provides useful insights into the underlying mechanisms involved in age-related changes in musculoskeletal tissues.

OBJECTIVE:To use a novel computational approach to examine the molecular pathways involved in cartilage breakdown and to use computer simulation to test possible interventions for reducing collagen release. METHODS:We constructed a computational model of the relevant molecular pathways using the Systems Biology Markup Language, a computer-readable format of a biochemical network. The model was constructed using our experimental data showing that interleukin-1 (IL-1) and oncostatin M (OSM) act synergistically to up-regulate collagenase protein levels and activity and initiate cartilage collagen breakdown. Simulations were performed using the COPASI software package. RESULTS:The model predicted that simulated inhibition of JNK or p38 MAPK, and overexpression of tissue inhibitor of metalloproteinases 3 (TIMP-3) led to a reduction in collagen release. Overexpression of TIMP-1 was much less effective than that of TIMP-3 and led to a delay, rather than a reduction, in collagen release. Simulated interventions of receptor antagonists and inhibition of JAK-1, the first kinase in the OSM pathway, were ineffective. So, importantly, the model predicts that it is more effective to intervene at targets that are downstream, such as the JNK pathway, rather than those that are close to the cytokine signal. In vitro experiments confirmed the effectiveness of JNK inhibition. CONCLUSION:Our study shows the value of computer modeling as a tool for examining possible interventions by which to reduce cartilage collagen breakdown. The model predicts that interventions that either prevent transcription or inhibit the activity of collagenases are promising strategies and should be investigated further in an experimental setting.

Purpose: The molecular mechanisms involved in age-related osteoarthritis are complex and as yet, the role of ageing in the process is not fully understood. Histochemical and Immunohistochemical data of knee joint cartilage taken from our aged mice colony, from 3 months to 30 months of age, indicate that many factors are involved. In order to increase our understanding of the primary mechanisms, we developed computer simulation models. Methods: Computer simulation models were constructed in a modular way and then integrated into one combined model, using the Systems Biology Markup Language. The models include components for autophagy, apoptosis, regulation of matrix degrading enzymes, accumulation of protein damage, accumulation of advanced glycation end products, the NFκB pathway, and TGFβ signalling. Due to the observed cellular heterogeneity, the models were simulated using a stochastic algorithm (Gillespie direct method) using software tools developed at Newcastle University and the COPASI biochemical network simulator. The models were calibrated against histochemical and immunohistochemical data from our aged mice colony at 3, 6, 12, 24 and 30 months of age. We also fitted the model to published kinetic data of signalling pathways. Different perturbations were made to the model and the model output was then compared to datasets not used in the model calibration. The perturbations were also used to test the importance of each of the components and their interactions. Results: The histochemical and immunohistochemical data showed many age-related changes including a decline in autophagy, an increase in apoptosis, and an increase in levels of oxidised proteins, matrix metalloproteinase-13 (MMP-13) level and collagen cleavage. In addition the ratio of the TGFβ type 1 receptors, ALK1 and ALK5, increases with age. However, there was considerable cell-cell variability in the measured outcomes. The model shows that the main source of this cellular heterogeneity is due to the stochastic nature of cellular damage, as most variability in the model output was seen in the levels of oxidised proteins and AGE products. There was also considerable variability in the time at which damage starts to accrue, and this accounts for the wide variability in the activation of matrix degrading enzymes. The model showed that negative feedback loops in the system are the main contributor to the age-related increase in the ALK1/ALK5 receptor and this also contributes to the age-related increase in MMP-13 and collagen degradation. Conclusions: Age-related changes in cartilage are caused by complex molecular mechanisms responding to different stress signals. There is both a gradual increase in damaged components and a dysregulation in signalling responses with age. Computer modelling is a complementary approach to assist with unravelling this complexity.

Objectives To investigate the effect of leptin on cartilage destruction. Methods Collagen release was assessed in bovine cartilage explant cultures, while collagenolytic and gelatinolytic activities in culture supernatants were determined by bioassay and gelatin zymography. The expression of matrix metalloproteinases (MMP) was analysed by real-time RT–PCR. Signalling pathway activation was studied by immunoblotting. Leptin levels in cultured osteoarthritic joint infrapatellar fat pad or peri-enthesal deposit supernatants were measured by immunoassay. Results Leptin, either alone or in synergy with IL-1, significantly induced collagen release from bovine cartilage by upregulating collagenolytic and gelatinolytic activity. In chondrocytes, leptin induced MMP1 and MMP13 expression with a concomitant activation of STAT1, STAT3, STAT5, MAPK (JNK, Erk, p38), Akt and NF-κB signalling pathways. Selective inhibitor blockade of PI3K, p38, Erk and Akt pathways significantly reduced MMP1 and MMP13 expression in chondrocytes, and reduced cartilage collagen release induced by leptin or leptin plus IL-1. JNK inhibition had no effect on leptin-induced MMP13 expression or leptin plus IL-1-induced cartilage collagen release. Conditioned media from cultured white adipose tissue (WAT) from osteoarthritis knee joint fat pads contained leptin, induced cartilage collagen release and increased MMP1 and MMP13 expression in chondrocytes; the latter being partly blocked with an anti-leptin antibody. Conclusions Leptin acts as a pro-inflammatory adipokine with a catabolic role on cartilage metabolism via the upregulation of proteolytic enzymes and acts synergistically with other pro-inflammatory stimuli. This suggests that the infrapatellar fat pad and other WAT in arthritic joints are local producers of leptin, which may contribute to the inflammatory and degenerative processes in cartilage catabolism, providing a mechanistic link between obesity and osteoarthritis.

Purpose: The aim of this study was to investigate age-related cartilage changes in the knee joints of mice. Cartilage degeneration is associated with cellular changes to chondrocytes, an increase in degradative stimuli and changes to the proteins of the extracellular matrix. It is not known to what extent these changes occur with age or if they are specific to diseased cartilage. Herein, we systematically investigated the changes that occur with age in mouse cartilage. Methods: C57/BL (ICRFa) mice have been selectively bred for longevity. Knee joints were collected (4 mice/group) at 3, 6, 12, 24, 30 months of age. Histology was performed with sections stained with hematoxylin & eosin (H&E), safranin O, Picro-sirius red and antibodies to cleaved type II collagen, MMP13, nitro-tyrosine (as a measure of oxidative stress), cleaved LC3B (as a measure of autophagy) and Bcl-2 /Bax (as a measure of apoptosis). Results: Our data indicate that a progressive degradation and loss of matrix occurs with age particularly in the load bearing area of cartilage. An increase in oxidative stress, MMP13 expression and type II collagen cleavage products occur with age with a concomitant decrease in autophagy and increase in apoptosis. Conclusions: This study demonstrates that many of the changes that occur in osteoarthritis are found in cartilage with increasing age. The increase in the level of oxidative stress, MMP-13 and type II collagen cleavage products explain the complete loss of cartilage tissue from load bearing regions of the joint in 30 month old mice joints. These changes explain the marked predisposition to osteoarthritis with increasing age.

Introduction: At present, there is no reliable tool for predicting disease outcome in patients with rheumatoid arthritis (RA). We previously demonstrated an association between specific baseline biomarkers/clinical measures including matrix metalloproteinase-3 (MMP-3) and 2-year radiographic progression in patients with RA. This study further evaluates the predictive capability of these baseline variables with outcome extended over 8-years.Methods: Fifty-eight of the original cohort (n = 118) had radiographic progression from baseline to mean 8.2-years determined using the van der Heijde modified Sharp method. The contribution of each predictor variable towards radiographic progression was assessed with univariate and multivariate analyses.Results: Traditional factors (including erythrocyte sedimentation rate, C-reactive protein, anti-cyclic citrullinated peptide (anti-CCP), and rheumatoid factor) and biomarkers of tissue destruction (including MMP-3, C-telopeptide of type II collagen, cartilage oligomeric matrix protein, and tissue inhibitor of metalloproteinase 1) measured at baseline were associated with radiographic progression at endpoint. Multivariate logistic regression identified anti-CCP seropositivity [OR 9.29, 95% CI: 2.29-37.64], baseline elevated MMP-3 [OR 8.25, 95% CI: 2.54-26.78] and baseline radiographic damage [OR 5.83, 95% CI: 1.88-18.10] as the strongest independent predictors of radiographic progression. A model incorporating these variables had a predictive accuracy of 0.87, assessed using the area under the receiver operating characteristic curve.Conclusion: In our cohort with onset of RA symptoms < 2-years, multivariate analysis identified anti-CCP status and baseline MMP-3 as the strongest independent predictors of radiographic disease outcome at 8.2-years. This finding suggests determination of baseline MMP-3, in conjunction with traditional serologic markers, may provide additional prognostic information for patients with RA. Furthermore, these findings highlight the importance of continued research into a broad range of biomarkers as potential predictors of joint damage.

The joint is a discrete unit that consists of cartilage, bone, tendon and ligaments. These tissues are all composed of an extracellular matrix made of collagens, proteoglycans and specialised glycoproteins that are actively synthesised, precisely assembled and subsequently degraded by the resident connective tissue cells. A balance is maintained between matrix synthesis and degradation in healthy adult tissues. Different classes of proteinases play a part in connective tissue turnover in which active proteinases can cleave matrix protein during resorption, although the proteinase that predominates varies between different tissues and diseases. The metalloproteinases are potent enzymes that, once activated, degrade connective tissue and are inhibited by tissue inhibitors of metalloproteinases (TIMPs); the balance between active matrix metalloproteinases and TIMPs determines, in many tissues, the extent of extracellular matrix degradation. The serine proteinases are involved in the initiation of activation cascades and some, such as elastase, can directly degrade the matrix. Cysteine proteinases are responsible for the breakdown of collagen in bone following the removal of the osteoid layer and the attachment of osteoclasts to the exposed bone surface. Various growth factors increase the synthesis of matrix and proteinase inhibitors, whereas cytokines (alone or in combination) can inhibit matrix synthesis and stimulate proteinase production and matrix destruction.

OBJECTIVE:Increasing evidence implicates serine proteinases in pathologic tissue turnover. The aim of this study was to assess the role of the transmembrane serine proteinase matriptase in cartilage destruction in osteoarthritis (OA). METHODS:Serine proteinase gene expression in femoral head cartilage obtained from either patients with hip OA or patients with fracture to the neck of the femur (NOF) was assessed using a low-density array. The effect of matriptase on collagen breakdown was determined in cartilage degradation models, while the effect on matrix metalloproteinase (MMP) expression was analyzed by real-time polymerase chain reaction. ProMMP processing was determined using sodium dodecyl sulfate-polyacrylamide gel electrophoresis/N-terminal sequencing, while its ability to activate proteinase-activated receptor 2 (PAR-2) was determined using a synovial perfusion assay in mice. RESULTS:Matriptase gene expression was significantly elevated in OA cartilage compared with NOF cartilage, and matriptase was immunolocalized to OA chondrocytes. We showed that matriptase activated proMMP-1 and processed proMMP-3 to its fully active form. Exogenous matriptase significantly enhanced cytokine-stimulated cartilage collagenolysis, while matriptase alone caused significant collagenolysis from OA cartilage, which was metalloproteinase-dependent. Matriptase also induced MMP-1, MMP-3, and MMP-13 gene expression. Synovial perfusion data confirmed that matriptase activates PAR-2, and we demonstrated that matriptase-dependent enhancement of collagenolysis from OA cartilage is blocked by PAR-2 inhibition. CONCLUSION:Elevated matriptase expression in OA and the ability of matriptase to activate selective proMMPs as well as induce collagenase expression make this serine proteinase a key initiator and inducer of cartilage destruction in OA. We propose that the indirect effects of matriptase are mediated by PAR-2, and a more detailed understanding of these mechanisms may highlight important new therapeutic targets for OA treatment.

The joint is a discrete unit that consists of cartilage, bone, tendon, and ligaments. Tendon consists of a matrix mainly made of collagen; bone consists of a mineralized collagen matrix; and cartilage is made up of collagens, proteoglycans, and specialized glycoproteins. Many studies have focused on single tissues of the joint, rather than regarding the joint as an organ made up of cartilage, bone, tendon, and muscle: future studies would benefit from an integrated approach....

Objective To investigate if statins prevent cartilage degradation and the production of collagenases and gelatinases in bovine nasal and human articular cartilage after proinflammatory cytokine stimulation. Methods In a cartilage degradation model, the effects of several statins were assessed by measuring proteoglycan degradation and collagen degradation, while collagenolytic and gelatinolytic activity in culture supernatants were determined by collagen bioassay and gelatin zymography. The production of matrix metalloproteinases (MMPs) in cartilage and chondrocytes were analysed by real-time reverse transcriptase PCR and immunoassay. Cytokine-induced signalling pathway activation was studied by immunoblotting. Results Simvastatin and mevastatin significantly inhibited interleukin 1 (IL-1)+oncostatin M (OSM)-induced collagen degradation; this was accompanied with a marked decrease in collagenase and gelatinase activity from bovine nasal cartilage. The cholesterol pathway intermediate mevalonic acid reversed the simvastatin-mediated protection of cartilage degradation, and the expression and production of collagenase (MMP-1 and MMP-13) and gelatinase (MMP-2 and MMP-9). Statins also significantly decreased MMP-1 and MMP-13 expression in human articular cartilage and chondrocytes stimulated with IL-1+OSM, and blocked the activation of critical proinflammatory signalling pathways required for MMP expression. The loss of the isoprenoid intermediate geranylgeranyl pyrophosphate due to statin treatment accounted for the inhibition of MMP expression and signalling pathway activation. Conclusions This study shows, for the first time, that lipophilic statins are able to block cartilage collagen breakdown induced by proinflammatory cytokines, by downregulating key cartilage-degrading enzymes. This demonstrates a possible therapeutic role for statins in acting as anti-inflammatory agents and in protecting cartilage from damage in joint diseases.

The assays described allow the activity of members of the matrix metalloproteinase (MMP) family that degrade collagen, gelatin and casein substrates to be measured. The protocols described include the preparation of radiolabeled substrates, methods for the separation of degraded product from undegraded substrate, and methods for the activation of MMPs. The advantages and disadvantages of these methods are discussed in relation to immunoassays that measure the amount of individual MMPs.