Evolution and advancements in genomics and epigenomics in OA research: How far we have come.

OBJECTIVE: Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease. DESIGN: In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients. RESULTS: Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease. CONCLUSIONS: Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.

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.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.

OBJECTIVE: Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades. DESIGN: We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease. RESULTS: Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues. CONCLUSIONS: Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Proteomic profiling of human menisci from mild joint degeneration and end-stage osteoarthritis versus healthy controls.

Objective: To gain new insight into the molecular changes of the meniscus by comparing the proteome profiles of healthy controls with mild degeneration and end-stage osteoarthritis (OA). Method: We obtained tissue plugs from lateral and medial menisci of 37 individuals (central part of the posterior horn) classified as healthy (n â€‹= â€‹12), mild signs of joint damage (n â€‹= â€‹13) and end-stage OA (n â€‹= â€‹12). The protein profile was analysed by nano-liquid chromatography-mass spectrometry using data-independent acquisition and quantified by Spectronaut. Linear-mixed effects modelling was applied to extract the between-group comparisons. Results: A similar protein profile was observed for the mild group as compared to healthy controls while the most different group was end-stage OA mainly for the medial compartment. When a pattern of gradual change in protein levels from healthy to end-stage OA was required, a 42-proteins panel was identified, suggesting a potential role in OA development. The levels of QSOX1 were lower and G6PD higher in the mild group following the proposed protein abundance pattern. Qualitative protein changes suggest lower levels of CYTL1 as a potential biomarker of early joint degradation. Conclusion: For future targeted proteomic approaches, we propose a candidate panel of 42 proteins based on gradually altered meniscal posterior horn protein abundance patterns associated with joint degradation.

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.

A meta-analysis and a functional study support the influence of mtDNA variant m.16519C on the risk of rapid progression of knee osteoarthritis.

OBJECTIVES: To identify mitochondrial DNA (mtDNA) genetic variants associated with the risk of rapid progression of knee osteoarthritis (OA) and to characterise their functional significance using a cellular model of transmitochondrial cybrids. METHODS: Three prospective cohorts contributed participants. The osteoarthritis initiative (OAI) included 1095 subjects, the Cohort Hip and Cohort Knee included 373 and 326 came from the PROspective Cohort of Osteoarthritis from A Coruña. mtDNA variants were screened in an initial subset of 450 subjects from the OAI by in-depth sequencing of mtDNA. A meta-analysis of the three cohorts was performed. A model of cybrids was constructed to study the functional consequences of harbouring the risk mtDNA variant by assessing: mtDNA copy number, mitochondrial biosynthesis, mitochondrial fission and fusion, mitochondrial reactive oxygen species (ROS), oxidative stress, autophagy and a whole transcriptome analysis by RNA-sequencing. RESULTS: mtDNA variant m.16519C is over-represented in rapid progressors (combined OR 1.546; 95% CI 1.163 to 2.054; p=0.0027). Cybrids with this variant show increased mtDNA copy number and decreased mitochondrial biosynthesis; they produce higher amounts of mitochondrial ROS, are less resistant to oxidative stress, show a lower expression of the mitochondrial fission-related gene fission mitochondrial 1 and an impairment of autophagic flux. In addition, its presence modulates the transcriptome of cybrids, especially in terms of inflammation, where interleukin 6 emerges as one of the most differentially expressed genes. CONCLUSIONS: The presence of the mtDNA variant m.16519C increases the risk of rapid progression of knee OA. Among the most modulated biological processes associated with this variant, inflammation and negative regulation of cellular process stand out. The design of therapies based on the maintenance of mitochondrial function is recommended.

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%.

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.

Multi-laboratory experiment PME11 for the standardization of phosphoproteome analysis.

Global analysis of protein phosphorylation by mass spectrometry proteomic techniques has emerged in the last decades as a powerful tool in biological and biomedical research. However, there are several factors that make the global study of the phosphoproteome more challenging than measuring non-modified proteins. The low stoichiometry of the phosphorylated species and the need to retrieve residue specific information require particular attention on sample preparation, data acquisition and processing to ensure reproducibility, qualitative and quantitative robustness and ample phosphoproteome coverage in phosphoproteomic workflows. Aiming to investigate the effect of different variables in the performance of proteome wide phosphoprotein analysis protocols, ProteoRed-ISCIII and EuPA launched the Proteomics Multicentric Experiment 11 (PME11). A reference sample consisting of a yeast protein extract spiked in with different amounts of a phosphomix standard (Sigma/Merck) was distributed to 31 laboratories around the globe. Thirty-six datasets from 23 laboratories were analyzed. Our results indicate the suitability of the PME11 reference sample to benchmark and optimize phosphoproteomics strategies, weighing the influence of different factors, as well as to rank intra and inter laboratory performance.

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.

Targeted phospholipidomic analysis of synovial fluid as a tool for osteoarthritis deep phenotyping.

Objective: The aim of this study was to carry out a targeted phospholipidomic analysis on synovial fluid (SF) from patients with different grades of osteoarthritis (OA) and controls, in order to search for specific phospholipid profiles that may be useful for the deep phenotyping of this disease. Design: Multiple reaction monitoring-mass spectrometry (MRM/MS) was applied to explore the potential phospholipidomic differences in the SF of knee OA patients (n â€‹= â€‹15) (subclassified into early- and late-stage OA) and non-OA controls (n â€‹= â€‹4). Multivariate statistical analyses conducted by partial least squares discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA) were performed to identify significantly altered phospholipids in OA, characterize phospholipidomic profiles associated with the radiographic stage of the disease and describe potential endotypes at early stages. Results: Significant discrimination of phospholipid profiles between non-OA controls and the early- and late-stage OA groups were found by PLS-DA and HCA. Compared to SF from non-OA controls, OA patients showed higher levels of most quantified phospholipid species, including phosphatidylcholines (PC), phosphatidylserines and phosphatidylinositols. Furthermore, several PC species showed significant differences in abundance between the two OA subgroups and were negatively correlated with cartilage damage. Finally, two distinct endotypes of early-stage OA were identified based on the phospholipidomic profile of SF. Conclusions: Our data provides a novel insight into the phospholipid profiles of OA synovial fluid, revealing specific alterations associated with the radiographic stage of the disease. This targeted phospholipidomic profiling also facilitated the characterization of two different OA endotypes at early stages of the disease.

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.

Integrative Metabolic Pathway Analysis Reveals Novel Therapeutic Targets in Osteoarthritis.

In osteoarthritis (OA), impairment of cartilage regeneration can be related to a defective chondrogenic differentiation of mesenchymal stromal cells (MSCs). Therefore, understanding the proteomic- and metabolomic-associated molecular events during the chondrogenesis of MSCs could provide alternative targets for therapeutic intervention. Here, a SILAC-based proteomic analysis identified 43 proteins related with metabolic pathways whose abundance was significantly altered during the chondrogenesis of OA human bone marrow MSCs (hBMSCs). Then, the level and distribution of metabolites was analyzed in these cells and healthy controls by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), leading to the recognition of characteristic metabolomic profiles at the early stages of differentiation. Finally, integrative pathway analysis showed that UDP-glucuronic acid synthesis and amino sugar metabolism were downregulated in OA hBMSCs during chondrogenesis compared with healthy cells. Alterations in these metabolic pathways may disturb the production of hyaluronic acid (HA) and other relevant cartilage extracellular matrix (ECM) components. This work provides a novel integrative insight into the molecular alterations of osteoarthritic MSCs and potential therapeutic targets for OA drug development through the enhancement of chondrogenesis.

Mining the Proteome Associated with Rheumatic and Autoimmune Diseases.

A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders.

Discovery of an autoantibody signature for the early diagnosis of knee osteoarthritis: data from the Osteoarthritis Initiative.

OBJECTIVE: To find autoantibodies (AAbs) in serum that could be useful to predict incidence of radiographic knee osteoarthritis (KOA). DESIGN: A Nucleic-acid Programmable Protein Arrays (NAPPA) platform was used to screen AAbs against 2125 human proteins in sera at baseline from participants free of radiographic KOA belonging to the incidence and non-exposed subcohorts of the Osteoarthritis Initiative (OAI) who developed or not, radiographic KOA during a follow-up period of 96 months. NAPPA-ELISA were performed to analyse reactivity against methionine adenosyltransferase two beta (MAT2ß) and verify the results in 327 participants from the same subcohorts. The association of MAT2ß-AAb levels with KOA incidence was assessed by combining several robust biostatistics analysis (logistic regression, Receiver Operating Characteristic and Kaplan-Meier curves). The proposed prognostic model was replicated in samples from the progression subcohort of the OAI. RESULTS: In the screening phase, six AAbs were found significantly different at baseline in samples from incident compared with non-incident participants. In the verification phase, high levels of MAT2ß-AAb were significantly associated with the future incidence of KOA and with an earlier development of the disease. The incorporation of this AAb in a clinical model for the prognosis of incident radiographic KOA significantly improved the identification/classification of patients who will develop the disorder. The usefulness of the model to predict radiographic KOA was confirmed on a different OAI subcohort. CONCLUSIONS: The measurement of AAbs against MAT2ß in serum might be highly useful to improve the prediction of OA development, and also to estimate the time to incidence.

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.

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.

Platelet-rich plasma in osteoarthritis treatment: review of current evidence.

Platelet-rich plasma (PRP) is defined as a volume of plasma with a platelet concentration higher than the average in peripheral blood. Many basic, preclinical and even clinical case studies and trials report PRP's ability to improve musculoskeletal conditions including osteoarthritis, but paradoxically, just as many conclude it has no effect. The purpose of this narrative review is to discuss the available relevant evidence that supports the clinical use of PRP in osteoarthritis, highlighting those variables we perceive as critical. Here, recent systematic reviews and meta-analyses were used to identify the latest randomized controlled trials (RCTs) testing a PRP product as an intra-articular treatment for knee osteoarthritis, compared with an intra-articular control (mostly hyaluronic acid). Conclusions in the identified RCTs are examined and compared. In total, five recent meta-analyses and systematic reviews were found meeting the above criteria. A total of 19 individual trials were identified in the five reviews but only 9 were level of evidence I RCTs, and many had moderate or high risks of bias. At present, results from these RCTs seem to favor PRP use over other intra-articular treatments to improve pain scales in the short and medium term (6-12 months), but the overall level of evidence is low. As a result, clinical effectiveness of PRP for knee osteoarthritis treatment is still under debate. This is, prominently, the result of a lack of standardization of PRP products, scarceness of high quality RCTs not showing high risks of bias, and poor patient stratification for inclusion in the RCTs.