An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining.

Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology.

Prognostic model to predict the incidence of radiographic knee osteoarthritis.

OBJECTIVE: Early diagnosis of knee osteoarthritis (KOA) in asymptomatic stages is essential for the timely management of patients using preventative strategies. We develop and validate a prognostic model useful for predicting the incidence of radiographic KOA (rKOA) in non-radiographic osteoarthritic subjects and stratify individuals at high risk of developing the disease. METHODS: Subjects without radiographic signs of KOA according to the Kellgren and Lawrence (KL) classification scale (KL=0 in both knees) were enrolled in the OA initiative (OAI) cohort and the Prospective Cohort of A Coruña (PROCOAC). Prognostic models were developed to predict rKOA incidence during a 96-month follow-up period among OAI participants based on clinical variables and serum levels of the candidate protein biomarkers APOA1, APOA4, ZA2G and A2AP. The predictive capability of the biomarkers was assessed based on area under the curve (AUC), and internal validation was performed to correct for overfitting. A nomogram was plotted based on the regression parameters. Model performance was externally validated in the PROCOAC. RESULTS: 282 participants from the OAI were included in the development dataset. The model built with demographic, anthropometric and clinical data (age, sex, body mass index and WOMAC pain score) showed an AUC=0.702 for predicting rKOA incidence during the follow-up. The inclusion of ZA2G, A2AP and APOA1 data significantly improved the model's sensitivity and predictive performance (AUC=0.831). The simplest model, including only clinical covariates and ZA2G and A2AP serum levels, achieved an AUC=0.826. Both models were internally cross-validated. Predictive performance was externally validated in an independent dataset of 100 individuals from the PROCOAC (AUC=0.713). CONCLUSION: A novel prognostic model based on common clinical variables and protein biomarkers was developed and externally validated to predict rKOA incidence over a 96-month period in individuals without any radiographic signs of disease. The resulting nomogram is a useful tool for stratifying high-risk populations and could potentially lead to personalised medicine strategies for treating OA.

Identification of circulating autoantibodies to non-modified proteins associated with ACPA status in early rheumatoid arthritis.

OBJECTIVES: To discover autoantibodies to non-modified proteins associated with the presence/absence of anticitrullinated protein antibodies (ACPA) in rheumatoid arthritis (RA). METHODS: The autoantibody repertoire of 80 ACPA negative and 80 ACPA positive RA subjects from the Swedish population-based Epidemiological Investigation of RA (EIRA) cohort was screened using a suspension bead array built on protein fragments earlier described as autoimmunity targets. Four autoantibodies positive in the initial screening were validated in another set of EIRA samples containing 317 ACPA-positive, 302 ACPA-negative and 372 age- and sex-matched controls. The relationship between the four autoantibodies and lung abnormalities on high-resolution computed tomography (HRTC) was examined in 93 early RA patients from LURA cohort. Association between the autoantibodies, smoking and MHC class II alleles was assessed by logistic regression analysis. RESULTS: : Anti-ANOS1 and anti-MURC IgG levels were associated with ACPA-positive status (OR = 3.02; 95% CI 1.87-4.89; and OR = 1.86; 95% CI 1.16-2.97, respectively) and increased in ACPA-positive patients compared with controls. Anti-ANOS1 IgG was associated with smoking habit (OR = 2.11; 95% CI 1.22-3.69) and anti-MURC IgG with the presence of the MHC class II "shared-epitope" genes (OR = 1.95; 95% CI 1.11-3.46). Anti-TSPYL4 IgG was associated with ACPA-negative (OR = 0.41; 95% CI 0.19-0.89). Anti-TSPYL4 IgG and anti-MAP2K6 IgG levels were increased in the ACPA-negative patients compared with controls. Presence of anti-MAP2K6 IgG and anti-TSPYL4 IgG correlated negatively with HRCT-defined lung abnormalities. CONCLUSIONS: These four autoantibodies may be useful in diagnostics and in predicting clinical phenotypes of RA.

Exploring High-Throughput Immunoassays for Biomarker Validation in Rheumatic Diseases in the Context of the Human Proteome Project.

Rheumatic diseases are high prevalence pathologies with different etiology and evolution and low sensitivity in clinical diagnosis. Therefore, it is necessary to develop an early diagnosis method which allows personalized treatment, depending on the specific pathology. The biology/disease initiative, at Human Proteome Project, is an integrative approach to identify relevant proteins in the human proteome associated with pathologies. A previously reported literature data mining analysis, which identified proteins related to osteoarthritis (OA), rheumatoid arthritis (RA), and psoriatic arthritis (PSA) was used to establish a systematic prioritization of potential biomarkers candidates for further evaluation by functional proteomics studies. The aim was to study the protein profile of serum samples from patients with rheumatic diseases such as OA, RA, and PSA. To achieve this goal, customized antibody microarrays (containing 151 antibodies targeting 121 specific proteins) were used to identify biomarkers related to early and specific diagnosis in a screening of 960 serum samples (nondepleted) (OA, n = 480; RA, n = 192; PSA, n = 288). This functional proteomics screening has allowed the determination of a panel (30 serum proteins) as potential biomarkers for these rheumatic diseases, displaying receiver operating characteristics curves with area under the curve values of 80-90%.

Analysis of Endogenous Peptides Released from Osteoarthritic Cartilage Unravels Novel Pathogenic Markers.

Osteoarthritis (OA) is a pathology characterized by the loss of articular cartilage. In this study, we performed a peptidomic strategy to identify endogenous peptides (neopeptides) that are released from human osteoarthritic tissue, which may serve as disease markers. With this aim, secretomes of osteoarthritic and healthy articular cartilages obtained from knee and hip were analyzed by shotgun peptidomics. This discovery step led to the identification of 1175 different peptides, corresponding to 101 proteins, as products of the physiological or pathological turnover of cartilage extracellular matrix. Then, a targeted multiple reaction monitoring-mass spectrometry method was developed to quantify the panel of best marker candidates on a larger set of samples (n = 62). Statistical analyses were performed to evaluate the significance of the observed differences and the ability of the neopeptides to classify the tissue. Eight of them were differentially abundant in the media from wounded zones of OA cartilage compared with the healthy tissue (p < 0.05). Three neopeptides belonging to Clusterin and one from Cartilage Oligomeric Matrix Protein showed a disease-dependent decrease specifically in hip OA, whereas two from Prolargin (PRELP) and one from Cartilage Intermediate Layer Protein 1 were significantly increased in samples from knee OA. The release of one peptide from PRELP showed the best metrics for tissue classification (AUC = 0.834). The present study reveals specific neopeptides that are differentially released from knee or hip human osteoarthritic cartilage compared with healthy tissue. This evidences the intervention of characteristic pathogenic pathways in OA and provides a novel panel of peptidic candidates for biomarker development.

Screening and Validation of Novel Biomarkers in Osteoarticular Pathologies by Comprehensive Combination of Protein Array Technologies.

Osteoarthritis (OA) is one of the most prevalent articular diseases. The identification of proteins closely associated with the diagnosis, progression, prognosis, and treatment response is dramatically required for this pathology. In this work, differential serum protein profiles have been identified in OA and rheumatoid arthritis (RA) by antibody arrays containing 151 antibodies against 121 antigens in a cohort of 36 samples. Then the identified differential serum protein profiles have been validated in a larger cohort of 282 samples. The overall immunoreactivity is higher in the pathological situations in comparison with the controls. Several proteins have been identified as biomarker candidates for OA and RA. Most of these biomarker candidates are proteins related to inflammatory response, lipid metabolism, or bone and extracellular matrix formation, degradation, or remodeling.

Defining the proteomic landscape of rheumatoid arthritis: progress and prospective clinical applications.

INTRODUCTION: The heterogeneity of Rheumatoid Arthritis (RA) and the absence of clinical tests accurate enough to identify the early stages of this disease have hampered its management. Therefore, proteomics research is increasingly focused on the discovery of novel biological markers, which would not only be able make an early diagnosis, but also to gain insight into the different pathological mechanisms underlying the heterogeneity of RA and also to stratify patients, which is critical to enabling effective treatments. Areas covered: The proteomic approaches that have been utilised to provide knowledge about RA pathogenesis, and to identify biomarkers for RA diagnosis, prognosis, disease monitoring and prediction of response to therapy, are summarized. Expert commentary: Although each proteomic study is unique in its design, all of them have contributed to the understanding of RA pathogenesis and the discovery of promising biomarkers for patient stratification, which would improve clinical care of RA patients. Still, efforts need to be made to validate these findings and translate them into clinical practice.

Quantitative proteomic profiling of human articular cartilage degradation in osteoarthritis.

Osteoarthritis (OA) is the most common rheumatic pathology and is characterized primarily by articular cartilage degradation. Despite its high prevalence, there is no effective therapy to slow disease progression or regenerate the damaged tissue. Therefore, new diagnostic and monitoring tests for OA are urgently needed, which would also promote the development of alternative therapeutic strategies. In the present study, we have performed an iTRAQ-based quantitative proteomic analysis of secretomes from healthy human articular cartilage explants, comparing their protein profile to those from unwounded (early disease) and wounded (advanced disease) zones of osteoarthritic tissue. This strategy allowed us to identify a panel of 76 proteins that are distinctively released by the diseased tissue. Clustering analysis allowed the classification of proteins according to their different profile of release from cartilage. Among these proteins, the altered release of osteoprotegerin (decreased in OA) and periostin (increased in OA), both involved in bone remodelling processes, was verified in further analyses. Moreover, periostin was also increased in the synovial fluid of OA patients. Altogether, the present work provides a novel insight into the mechanisms of human cartilage degradation and a number of new cartilage-characteristic proteins with possible biomarker value for early diagnosis and prognosis of OA.

Analysis of autoantibody profiles in osteoarthritis using comprehensive protein array concepts.

Osteoarthritis (OA) is the most common rheumatic disease and one of the most disabling pathologies worldwide. To date, the diagnostic methods of OA are very limited, and there are no available medications capable of halting its characteristic cartilage degeneration. Therefore, there is a significant interest in new biomarkers useful for the early diagnosis, prognosis, and therapeutic monitoring. In the recent years, protein microarrays have emerged as a powerful proteomic tool to search for new biomarkers. In this study, we have used two concepts for generating protein arrays, antigen microarrays, and NAPPA (nucleic acid programmable protein arrays), to characterize differential autoantibody profiles in a set of 62 samples from OA, rheumatoid arthritis (RA), and healthy controls. An untargeted screen was performed on 3840 protein fragments spotted on planar antigen arrays, and 373 antigens were selected for validation on bead-based arrays. In the NAPPA approach, a targeted screening was performed on 80 preselected proteins. The autoantibody targeting CHST14 was validated by ELISA in the same set of patients. Altogether, nine and seven disease related autoantibody target candidates were identified, and this work demonstrates a combination of these two array concepts for biomarker discovery and their usefulness for characterizing disease-specific autoantibody profiles.

Pharmacoproteomic study of three different chondroitin sulfate compounds on intracellular and extracellular human chondrocyte proteomes.

Chondroitin sulfate (CS) is a symptomatic slow acting drug for osteoarthritis (OA) widely used for the treatment of this highly prevalent disease, characterized by articular cartilage degradation. However, little is known about its mechanism of action, and recent large scale clinical trials have reported variable results on OA symptoms. Herein, we aimed to study the modulations in the intracellular proteome and the secretome of human articular cartilage cells (chondrocytes) treated with three different CS compounds, with different origin or purity, by two complementary proteomic approaches. Osteoarthritic cells were treated with 200 µg/ml of each brand of CS. Quantitative proteomics experiments were carried out by the DIGE and stable isotope labeling with amino acids in cell culture (SILAC) techniques, followed by LC-MALDI-MS/MS analysis. The DIGE study, carried out on chondrocyte whole cell extracts, led to the detection of 46 spots that were differential between conditions in our study: 27 were modulated by CS1, 4 were modulated by CS2, and 15 were modulated by CS3. The SILAC experiment, carried out on the subset of chondrocyte-secreted proteins, allowed us to identify 104 different proteins. Most of them were extracellular matrix components, and 21 were modulated by CS1, 13 were modulated by CS2, and 9 were modulated by CS3. Each of the studied compounds induces a characteristic protein profile in OA chondrocytes. CS1 displayed the widest effect but increased the mitochondrial superoxide dismutase, the cartilage oligomeric matrix protein, and some catabolic or inflammatory factors like interstitial collagenase, stromelysin-1, and pentraxin-related protein. CS2 and CS3, on the other hand, increased a number of structural proteins, growth factors, and extracellular matrix proteins. Our study shows how, from the three CS compounds tested, CS1 induces the activation of inflammatory and catabolic pathways, whereas CS2 and CS3 induce an anti-inflammatory and anabolic response. The data presented emphasize the importance of employing high quality CS compounds, supported by controlled clinical trials, in the therapy of OA. Finally, the present work exemplifies the usefulness of proteomic approaches in pharmacological studies.

Association of the serological status of rheumatoid arthritis patients with two circulating protein biomarkers: A useful tool for precision medicine strategies.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation of the joints and presence of systemic autoantibodies, with a great clinical and molecular heterogeneity. Rheumatoid Factor (RF) and anti-citrullinated protein antibodies (ACPA) are routinely used for the diagnosis of RA. However, additional serological markers are needed to improve the clinical management of this disease, allowing for better patient stratification and the desirable application of precision medicine strategies. In the present study, we investigated those systemic molecular changes that are associated with the RF and ACPA status of RA patients. To achieve this objective, we followed a proteomic biomarker pipeline from the discovery phase to validation. First, we performed an iTRAQ-based quantitative proteomic experiment on serum samples from the RA cohort of the Hospital of Santiago de Compostela (CHUS). In this discovery phase, serum samples from the CHUS cohort were pooled according to their RF/ACPA status. Shotgun analysis revealed that, in comparison with the double negative group (RF-/ACPA-), the abundance of 12 proteins was altered in the RF+/ACPA+ pool, 16 in the RF+/ACPA- pool and 10 in the RF-/ACPA+ pool. Vitamin D binding protein and haptoglobin were the unique proteins increased in all the comparisons. For the verification phase, 80 samples from the same cohort were analyzed individually. To this end, we developed a Multiple Reaction Monitoring (MRM) method that was employed in a comprehensive targeted analysis with the aim of verifying the results obtained in the discovery phase. Thirty-one peptides belonging to 12 proteins associated with RF and/or ACPA status were quantified by MRM. In a final validation phase, the serum levels of alpha-1-acid glycoprotein 1 (A1AG1), haptoglobin (HPT) and retinol-binding protein 4 (RET4) were measured by immunoassays in the RA cohort of the Hospital of A Coruña (HUAC). The increase of two of these putative biomarkers in the double seropositive group was validated in 260 patients from this cohort (p = 0.009 A1AG1; p = 0.003 HPT). The increased level of A1AG1 showed association with RF rather than ACPA (p = 0.023), whereas HPT showed association with ACPA rather than RF (p = 0.013). Altogether, this study has allowed a further classification of the RA seropositive patients into two novel clusters: RF+A1AG+ and ACPA+HPT+. The determination of A1AG1 and HPT in serum would provide novel information useful for RA patient stratification, which could facilitate the effective implementation of personalized medicine in routine clinical practice.

Nucleic Acid Programmable Protein Arrays (NAPPA) for the Discovery of Autoantibodies in Osteoarthritis.

Since a decade, the nucleic acid protein programmable array (NAPPA) technology has provided researchers with a high-throughput proteomic technique for deciphering immune signatures and screening for biomarkers, among other applications. In osteoarthritis (OA), the activation of proinflammatory pathways of innate immunity due to cellular stress response and cartilage degradation is now considered to be one of the pathophysiological drivers of the disease, perpetuating the catabolic process and the inflammation of the joint. Therefore, the identification of immunosignatures in OA would allow to detect autoantibodies (AAbs) as a new source of disease-specific biomarkers. Herein, we describe a proteomic strategy combining NAPPA and in situ protein expression coupled with enzyme-linked immunoassays (ELISA) to search for novel serum AAbs in OA.

Serum Proteomic Profiling in Rheumatoid Arthritis by Antibody Suspension Bead Arrays.

The versatility of protein microarrays provides researchers with a wide variety of possibilities to address proteomic studies. Therefore, protein microarrays are becoming very useful tools to identify candidate biomarkers in human body fluids for disease states such as rheumatoid arthritis (RA). In RA serum, there is a high prevalence of rheumatoid factor (RF), which is an antibody with high specificity against Fc portion of IgG. The presence of RF, in particular RF-IgM, has the great potential to interfere with antibody-based immunoassays by nonspecifically binding capture antibodies. Because of this concern, we describe a procedure to reduce the interference of RF-IgM on RA serum protein profiling approaches based on multiplexed antibody suspension bead arrays.

Association of serum anti-centromere protein F antibodies with clinical response to infliximab in patients with rheumatoid arthritis: A prospective study.

BACKGROUND: One-third of rheumatoid arthritis (RA) patients demonstrate no clinical improvement after receiving tumor necrosis factor inhibitors (TNFi). The presence of serum autoantibodies is a hallmark in RA and may provide information on future response to treatment. The aim of this prospective study was to search for novel serum autoantibodies useful to predict clinical response to TNFi. METHODS: The autoantibody repertoire was profiled on RA patients treated with TNFi as a first line of biologic therapy (N = 185), who were recruited in three independent cohorts. The presence and levels of autoantibodies in serum at baseline were analysed in association with the clinical response after 24 weeks follow-up. A multiplex bead array built using antigens selected from an initial untargeted screening was employed to identify the autoantibodies on a discovery cohort (N = 50) and to verify and validate the results on verification (N = 61) and validation (N = 74) cohorts. Non-parametric tests, meta-analysis and Receiver Operating Curves (ROC) were performed in order to assess the clinical relevance of the observed findings. RESULTS: Novel autoantibodies were associated with the clinical response to TNFi, showing different reactivity profiles among the different TNFi. The baseline levels of IgG antibodies against Centromere protein F (CENPF), a protein related to cell proliferation, were significantly (p<0.05) increased in responders (N = 111) to infliximab (IFX) compared to non-responders (N = 44). The addition of anti-CENPF antibodies to demographic and clinical variables (age, sex, DAS28-ESR) resulted in the best model to discriminate responders, showing an area under the curve (AUC) of 0.756 (95% CI [0.639-0.874], p = 0.001). A further meta-analysis demonstrated the significant association of anti-CENPF levels with the patient's subsequent response to IFX, showing a standardized mean difference (SMD) of -0.65 (95% CI [-1.02;-0. 27], p = 0.018). CONCLUSIONS: Our study reveals for the first time the potential of circulating anti-CENPF antibodies to predict the clinical response to IFX before starting the treatment. This finding could be potentially useful to guide therapeutic decisions and may lead to further studies focusing on the role of CENPF on RA pathology.

Predictive modeling of therapeutic response to chondroitin sulfate/glucosamine hydrochloride in knee osteoarthritis.

BACKGROUND: In the present study, we explored potential protein biomarkers useful to predict the therapeutic response of knee osteoarthritis (KOA) patients treated with pharmaceutical grade Chondroitin sulfate/Glucosamine hydrochloride (CS+GH; Droglican, Bioiberica), in order to optimize therapeutic outcomes. METHODS: A shotgun proteomic analysis by iTRAQ labelling and liquid chromatography-mass spectrometry (LC-MS/MS) was performed using sera from 40 patients enrolled in the Multicentre Osteoarthritis interVEntion trial with Sysadoa (MOVES). The panel of proteins potentially useful to predict KOA patient's response was clinically validated in the whole MOVES cohort at baseline (n = 506) using commercially available enzyme-linked immunosorbent assays kits. Logistic regression models and receiver-operating-characteristics (ROC) curves were used to analyze the contribution of these proteins to our prediction models of symptomatic drug response in KOA. RESULTS: In the discovery phase of the study, a panel of six putative predictive biomarkers of response to CS+GH (APOA2, APOA4, APOH, ITIH1, C4BPa and ORM2) were identified by shotgun proteomics. Data are available via ProteomeXchange with identifier PXD012444. In the verification phase, the panel was verified in a larger set of KOA patients (n = 262). Finally, ITIH1 and ORM2 were qualified by a blind test in the whole MOVES cohort at baseline. The combination of these biomarkers with clinical variables predict the patients' response to CS+GH with a specificity of 79.5% and a sensitivity of 77.1%. CONCLUSIONS: Combining clinical and analytical parameters, we identified one biomarker that could accurately predict KOA patients' response to CS+GH treatment. Its use would allow an increase in response rates and safety for the patients suffering KOA.

Discovery of circulating proteins associated to knee radiographic osteoarthritis.

Currently there are no sufficiently sensitive biomarkers able to reflect changes in joint remodelling during osteoarthritis (OA). In this work, we took an affinity proteomic approach to profile serum samples for proteins that could serve as indicators for the diagnosis of radiographic knee OA. Antibody suspension bead arrays were applied to analyze serum samples from patients with OA (n = 273), control subjects (n = 76) and patients with rheumatoid arthritis (RA, n = 244). For verification, a focused bead array was built and applied to an independent set of serum samples from patients with OA (n = 188), control individuals (n = 83) and RA (n = 168) patients. A linear regression analysis adjusting for sex, age and body mass index (BMI) revealed that three proteins were significantly elevated (P < 0.05) in serum from OA patients compared to controls: C3, ITIH1 and S100A6. A panel consisting of these three proteins had an area under the curve of 0.82 for the classification of OA and control samples. Moreover, C3 and ITIH1 levels were also found to be significantly elevated (P < 0.05) in OA patients compared to RA patients. Upon validation in additional study sets, the alterations of these three candidate serum biomarker proteins could support the diagnosis of radiographic knee OA.

Multiplexed mass spectrometry monitoring of biomarker candidates for osteoarthritis.

The methods currently available for the diagnosis and monitoring of osteoarthritis (OA) are very limited and lack sensitivity. Being the most prevalent rheumatic disease, one of the most disabling pathologies worldwide and currently untreatable, there is a considerable interest pointed in the verification of specific biological markers for improving its diagnosis and disease progression studies. Considering the remarkable development of targeted proteomics methodologies in the frame of the Human Proteome Project, the aim of this work was to develop and apply a MRM-based method for the multiplexed analysis of a panel of 6 biomarker candidates for OA encoded by the Chromosome 16, and another 8 proteins identified in previous shotgun studies as related with this pathology, in specimens derived from the human joint and serum. The method, targeting 35 different peptides, was applied to samples from human articular chondrocytes, healthy and osteoarthritic cartilage, synovial fluid and serum. Subsequently, a verification analysis of the biomarker value of these proteins was performed by single point measurements on a set of 116 serum samples, leading to the identification of increased amounts of Haptoglobin and von Willebrand Factor in OA patients. Altogether, the present work provides a tool for the multiplexed monitoring of 14 biomarker candidates for OA, and verifies for the first time the increased amount of two of these circulating markers in patients diagnosed with this disease. SIGNIFICANCE: We have developed an MRM method for the identification and relative quantification of a panel of 14 protein biomarker candidates for osteoarthritis. This method has been applied to analyze human articular chondrocytes, articular cartilage, synovial fluid, and finally a collection of 116 serum samples from healthy controls and patients suffering different degrees of osteoarthritis, in order to verify the biomarker usefulness of the candidates. HPT and VWF were validated as increased in OA patients.

Secretome analysis of human articular chondrocytes unravels catabolic effects of nicotine on the joint.

PURPOSE: Osteoarthritis (OA) is a degenerative joint pathology characterized by articular cartilage degradation that lacks from efficient therapy. Since previous epidemiological data show a high controversy regarding the role of smoking in OA, we aimed to evaluate the effects of nicotine (the most physiologically active compound of tobacco) on the joint. EXPERIMENTAL DESIGN: Secretome analyses, based on metabolic labeling followed by LC-MALDI-TOF/TOF analysis, were carried out using an in vitro model of articular inflammation (primary human articular chondrocytes treated with interleukin-1ß), and also on osteoarthritic cells. ELISA and Western blot assays were performed to verify some of the results. RESULTS: Nineteen proteins were altered by nicotine in the model of articular inflammation, including several cytokines and proteases. We confirmed the increased secretion by nicotine of matrix metalloproteinase 1 and two proposed markers of OA, fibronectin, and chitinase 3-like protein 1. Finally, four components of the extracellular matrix of cartilage were decreased by nicotine in OA chondrocytes. CONCLUSIONS AND CLINICAL RELEVANCE: Our data contribute to a better understanding of the molecular mechanisms that are modulated by nicotine in cartilage cells, suggesting a negative effect of this drug on the joint.

NAPPA as a Real New Method for Protein Microarray Generation.

Nucleic Acid Programmable Protein Arrays (NAPPA) have emerged as a powerful and innovative technology for the screening of biomarkers and the study of protein-protein interactions, among others possible applications. The principal advantages are the high specificity and sensitivity that this platform offers. Moreover, compared to conventional protein microarrays, NAPPA technology avoids the necessity of protein purification, which is expensive and time-consuming, by substituting expression in situ with an in vitro transcription/translation kit. In summary, NAPPA arrays have been broadly employed in different studies improving knowledge about diseases and responses to treatments. Here, we review the principal advances and applications performed using this platform during the last years.

A pharmacoproteomic study confirms the synergistic effect of chondroitin sulfate and glucosamine.

Osteoarthritis (OA) is the most common age-related rheumatic disease. Chondrocytes play a primary role in mediating cartilage destruction and extracellular matrix (ECM) breakdown, which are main features of the OA joint. Quantitative proteomics technologies are demonstrating a very interesting power for studying the molecular effects of some drugs currently used to treat OA patients, such as chondroitin sulfate (CS) and glucosamine (GlcN). In this work, we employed the iTRAQ (isobaric tags for relative and absolute quantitation) technique to assess the effect of CS and GlcN, both alone and in combination, in modifying cartilage ECM metabolism by the analysis of OA chondrocytes secretome. 186 different proteins secreted by the treated OA chondrocytes were identified. 36 of them presented statistically significant differences (p ≤ 0.05) between untreated and treated samples: 32 were increased and 4 decreased. The synergistic chondroprotective effect of CS and GlcN, firstly reported by our group at the intracellular level, is now demonstrated also at the extracellular level.