Proteomics profiling of human synovial fluid suggests increased protein interplay in early-osteoarthritis (OA) that is lost in late-stage OA

The Genetics and Functional Genomics of Osteoarthritis

Osteoarthritis is the most prevalent whole-joint degenerative disorder, and is characterized by the degradation of articular cartilage and the underlying bone structures. Almost 600 million people are affected by osteoarthritis worldwide. No curative treatments are available, and management strategies focus mostly on pain relief. Here, we provide a comprehensive overview of the available human genetic and functional genomics studies for osteoarthritis to date and delineate how these studies have helped shed light on disease etiopathology. We highlight genetic discoveries from genome-wide association studies and provide a detailed overview of molecular-level investigations in osteoarthritis tissues, including methylation-, transcriptomics-, and proteomics-level analyses. We review how functional genomics data from different molecular levels have helped to prioritize effector genes that can be used as drug targets or drug-repurposing opportunities. Finally, we discuss future directions with the potential to drive a step change in osteoarthritis research.

Exploring the Early Molecular Pathogenesis of Osteoarthritis Using Differential Network Analysis of Human Synovial Fluid

The molecular mechanisms that drive the onset and development of osteoarthritis (OA) remain largely unknown. In this exploratory study, we used a proteomic platform (SOMAscan assay) to measure the relative abundance of more than 6000 proteins in synovial fluid (SF) from knees of human donors with healthy or mildly degenerated tissues, and knees with late-stage OA from patients undergoing knee replacement surgery. Using a linear mixed effects model, we estimated the differential abundance of 6251 proteins between the three groups. We found 583 proteins upregulated in the late-stage OA, including MMP1, collagenase 3 and interleukin-6. Further, we selected 760 proteins (800 aptamers) based on absolute fold changes between the healthy and mild degeneration groups. To those, we applied Gaussian Graphical Models (GGMs) to analyze the conditional dependence of proteins and to identify key proteins and subnetworks involved in early OA pathogenesis. After regularization and stability selection, we identified 102 proteins involved in GGM networks. Notably, network complexity was lost in the protein graph for mild degeneration when compared to controls, suggesting a disruption in the regular protein interplay. Furthermore, among our main findings were several downregulated (in mild degeneration versus healthy) proteins with unique interactions in the healthy group, one of which, SLCO5A1, has not previously been associated with OA. Our results suggest that this protein is important for healthy joint function. Further, our data suggests that SF proteomics, combined with GGMs, can reveal novel insights into the molecular pathogenesis and identification of biomarker candidates for early-stage OA.

An osteoarthritis pathophysiological continuum revealed by molecular biomarkers

We aimed to identify serum biomarkers that predict knee osteoarthritis (OA) before the appearance of radiographic abnormalities in a cohort of 200 women. As few as six serum peptides, corresponding to six proteins, reached AUC 77% probability to distinguish those who developed OA from age-matched individuals who did not develop OA up to 8 years later. Prediction based on these blood biomarkers was superior to traditional prediction based on age and BMI (AUC 51%) or knee pain (AUC 57%). These results identify a prolonged molecular derangement of joint tissue before the onset of radiographic OA abnormalities consistent with an unresolved acute phase response. Among all 24 protein biomarkers predicting incident knee OA, the majority (58%) also predicted knee OA progression, revealing the existence of a pathophysiological "OA continuum" based on considerable similarity in the molecular pathophysiology of the progression to incident OA and the progression of established OA.

Differences in the Synovial Fluid Proteome of Septic and Aseptic Implant Failure

Implant loosening is a severe complication after total joint replacement. Here, differential diagnosis between septic and aseptic cases is crucial for further surgical treatment, but low-grade periprosthetic joint infections (PJIs) in particular remain a challenge. In this study, we analyzed the synovial fluid proteome of 21 patients undergoing revision surgery for septic (eight cases) or aseptic (thirteen cases) implant failure using LC-MS/MS to identify potential new biomarkers as future diagnostic tools. Staphylococci were found in four cases, Streptococci in two cases, Serratia marcescens and Cutibacterium acnes in one case. Proteomic analysis of the synovial fluid resulted in the identification of 515 different proteins based on at least two peptides. A statistical comparison revealed 37 differentially abundant proteins (p < 0.05), of which 17 proteins (46%) showed a higher abundance in the septic group. The proteins with the highest fold change included the known marker proteins c-reactive protein (7.57-fold) and the calprotectin components protein S100-A8 (4.41-fold) and protein S100-A9 (3.1-fold). However, the protein with the highest fold change was leucine-rich alpha-2-glycoprotein 1 (LRG1) (9.07-fold), a currently discussed new biomarker for inflammatory diseases. Elevated LRG1 levels could facilitate the diagnosis of PJI in the future, but their significance needs to be further investigated.

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.

Serum proteomic biomarkers diagnostic of knee osteoarthritis

OBJECTIVE

To better understand the pathogenesis of knee osteoarthritis (OA) through identification of serum diagnostics.

DESIGN

We conducted multiple reaction monitoring mass spectrometry analysis of 107 peptides in baseline sera of two cohorts: the Foundation for National Institutes of Health (NIH) (n = 596 Kellgren-Lawrence (KL) grade 1-3 knee OA participants); and the Johnston County Osteoarthritis Project (n = 127 multi-joint controls free of radiographic OA of the hands, hips, knees (bilateral KL=0), and spine). Data were split into (70%) training and (30%) testing sets. Diagnostic peptide and clinical data predictors were selected by random forest (RF); selection was based on association (p < 0.05) with OA status in multivariable logistic regression models. Model performance was based on area under the curve (AUC) of receiver operating characteristic (ROC) and precision-recall (PR) curves.

RESULTS

RF selected 23 peptides (19 proteins) and body mass index (BMI) as diagnostic of OA. BMI weakly diagnosed OA (ROC-AUC 0.57, PR-AUC 0.812) and only symptomatic OA cases. ACTG was the strongest univariable predictor (ROC-AUC 0.705, PR-AUC 0.897). The final model (8 serum peptides) was highly diagnostic (ROC-AUC 0.833, 95% confidence interval [CI] 0.751, 0.905; PR-AUC 0.929, 95% CI 0.876, 0.973) in the testing set and equally diagnostic of non-symptomatic and symptomatic cases (AUCs 0.830-0.835), and not significantly improved with addition of BMI. The STRING database predicted multiple high confidence interactions of the 19 diagnostic OA proteins.

CONCLUSIONS

No more than 8 serum protein biomarkers were required to discriminate knee OA from non-OA. These biomarkers lend strong support to the involvement and cross-talk of complement and coagulation pathways in the development of OA.

S100A12 is involved in the pathology of osteoarthritis by promoting M1 macrophage polarization via the NF-κB pathway

BACKGROUND

Osteoarthritis (OA) is a degenerative joint disease that affects millions worldwide. Synovitis and macrophage polarization are important factors in the development of OA. However, the specific components of synovial fluid (SF) responsible for promoting macrophage polarization remain unclear.

METHODS

Semi-quantitative antibody arrays were used to outline the proteome of SF. Differential expression analysis and GO/KEGG were performed on the obtained data. Immunohistochemistry and ELISA were used to investigate the relationship between SF S100A12 levels and synovitis levels in clinalclinical samples. In vitro cell experiments were conducted to investigate the effect of S100A12 on macrophage polarization. Public databases were utilized to predict and construct an S100A12-centered lncRNA-miRNA-mRNA competing endogenous RNA network, which was preliminarily validated using GEO datasets.

RESULTS

The study outlines the protein profile in OA and non-OA SF. The results showed that the S100A12 level was significantly increased in OA SF and inflammatory chondrocytes. The OA synovium had more severe synovitis and higher levels of S100A12 than non-OA synovium. Exogenous S100A12 upregulated the levels of M1 markers and phosphorylated p65 and promoted p65 nuclear translocation, while pretreatment with BAY 11-7082 reversed these changes. It was also discovered that LINC00894 was upregulated in OA and significantly correlated with S100A12, potentially regulating S100A12 expression by acting as a miRNA sponge.

CONCLUSIONS

This study demonstrated that S100A12 promotes M1 macrophage polarization through the NF-κB pathway, and found that LINC00894 has the potential to regulate the expression of S100A12 as a therapeutic approach.

A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression

Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative disease characterized by chronic pain and impaired jaw function. The complexity of TMJ OA has hindered the development of prognostic tools, posing a significant challenge in timely, patient-specific management. Addressing this gap, our research employs a comprehensive, multidimensional approach to advance TMJ OA prognostication. We conducted a prospective study with 106 subjects, 74 of whom were followed up after 2 to 3 y of conservative treatment. Central to our methodology is the development of an innovative, open-source predictive modeling framework, the Ensemble via Hierarchical Predictions through Nested cross-validation tool (EHPN). This framework synergistically integrates 18 feature selection, statistical, and machine learning methods to yield an accuracy of 0.87, with an area under the ROC curve of 0.72 and an F1 score of 0.82. Our study, beyond technical advancements, emphasizes the global impact of TMJ OA, recognizing its unique demographic occurrence. We highlight key factors influencing TMJ OA progression. Using SHAP analysis, we identified personalized prognostic predictors: lower values of headache, lower back pain, restless sleep, condyle high gray level-GL-run emphasis, articular fossa GL nonuniformity, and long-run low GL emphasis; and higher values of superior joint space, mouth opening, saliva Vascular-endothelium-growth-factor, Matrix-metalloproteinase-7, serum Epithelial-neutrophil-activating-peptide, and age indicate recovery likelihood. Our multidimensional and multimodal EHPN tool enhances clinicians' decision-making, offering a transformative translational infrastructure. The EHPN model stands as a significant contribution to precision medicine, offering a paradigm shift in the management of temporomandibular disorders and potentially influencing broader applications in personalized healthcare.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Small Joint Organoids 3D Bioprinting: Construction Strategy and Application

Osteoarthritis (OA) is a chronic disease that causes pain and disability in adults, affecting ≈300 million people worldwide. It is caused by damage to cartilage, including cellular inflammation and destruction of the extracellular matrix (ECM), leading to limited self-repairing ability due to the lack of blood vessels and nerves in the cartilage tissue. Organoid technology has emerged as a promising approach for cartilage repair, but constructing joint organoids with their complex structures and special mechanisms is still challenging. To overcome these boundaries, 3D bioprinting technology allows for the precise design of physiologically relevant joint organoids, including shape, structure, mechanical properties, cellular arrangement, and biological cues to mimic natural joint tissue. In this review, the authors will introduce the biological structure of joint tissues, summarize key procedures in 3D bioprinting for cartilage repair, and propose strategies for constructing joint organoids using 3D bioprinting. The authors also discuss the challenges of using joint organoids' approaches and perspectives on their future applications, opening opportunities to model joint tissues and response to joint disease treatment.

Analysis of joint protein expression profile in anterior disc displacement of TMJ with or without OA

OBJECTIVE

Anterior disc displacement (ADD) is a common clinical issue and may cause osteoarthritis (OA). However, the research of protein changes in synovial fluid as disease development marker and potential treatment clue is still insufficient.

MATERIALS AND METHODS

We conducted the high-resolution mass spectrometry (MS) of synovial fluid collected from 60 patients with normal disk position to ADD and ADD with osteoarthritis (OA). The proteins with significant changes among the 3 groups were analyzed by biological information and further validated by in primary rat condyle chondrocytes and OA animal model.

RESULTS

FGL2, THBS4, TNC, FN1, OMD etc. were significantly increased in ADD without OA (p < 0.05), which reflected the active extracellular matrix and collagen metabolism. FGFR1, FBLN2, GRB2 etc. were significantly increased in ADD with OA group (p < 0.05), which revealed an association with apoptosis and ferroptosis. Proteins such as P4HB, CBLN4, FHL1, VIM continuously increase in the whole disease progress (p < 0.05). Both the in vitro and in vivo results are consistent with protein changes detected in MS profile.

CONCLUSION

This study firstly provides the expression changes of proteins from normal disc condyle relationship toward ADD with OA, which can be selected and studied further as disease progress marker and potential treatment targets.

Elevated secretion of pro-collagen I-alpha and vascular endothelial growth factor as biomarkers of acetabular labrum degeneration and calcification in hip osteoarthritis: An explant study

Background

Hip osteoarthritis (OA) involves structural degeneration of different joint compartments, including femoral head cartilage, periarticular ligaments and the acetabular labrum. However, the molecular mechanisms underlying labrum degeneration in hip OA remain poorly understood.

Aim

To assess secretion of putative biomarkers for OA from explanted human labrum tissues under basal and inflammatory conditions and to determine whether these could differentiate between OA and calcification status compared to fracture controls.

Methods

Intact labrum specimens were collected from patients undergoing joint arthroplasty for primary hip OA (n ​= ​15, mean age 70) or non-OA femoral neck fracture (n ​= ​5, mean age 64). Tissues were dissected in equal-sized samples and explanted for one week. To mimic activation of inflammatory signaling by endogenous damage-associated molecular patterns (DAMP) tissue were stimulated with a toll-like receptor 4 (TLR4) agonist (1 ​μg/mL LPS). The involvement of transforming growth factor-beta (TGF-beta) signaling was evaluated by treatment with a TGF-beta type 1 receptor inhibitor (10 ​μM SB-505124). Secretion of aggrecan (ACAN), pro-collagen-I alpha (Pro-Col-Iα), cartilage oligomeric matrix protein (COMP), interleukin-6 (IL-6) and vascular endothelial growth factor (VEGF) was assessed by enzyme-linked immunosorbent assay (ELISA). Labrum calcification was evaluated by 3D whole mount fluorescent microscopy of ethyl cinnamate-based optically cleared tissues stained with Alcian blue/Alizarin red.

Results

Whole mount microscopy revealed non-OA fracture controls were non-calcified, whereas six OA labra (40%) were partially calcified or ossified. Basal secretion of Pro-Col-Iα and VEGF was increased four-fold in OA versus non-OA labra. Pro-Col-Iα levels were correlated with those of VEGF (r ​= ​0.65) and COMP (r ​= ​0.54). Stimulation of DAMP signaling through TLR4 affected secretion of IL-6, VEGF, COMP and Pro-Col-Iα, with distinct responses between non-OA and OA tissues. Inhibition of TGF-beta signaling specifically reduced elevated secretion of Pro-Col- Iα and VEGF in calcified OA labrum.

Conclusions

Secretion of the putative OA biomarkers Pro-Col-Iα and VEGF is elevated in degenerated human acetabular labrum and may serve as indicators of OA and calcification status. Secretion of both factors was partially regulated by TGF-beta signaling in calcified OA labrum tissues.The Translational potential of this article:Our findings suggest that a biomarker panel consisting of Pro-Col-Iα/VEGF/COMP may be valuable for assessing subradiographic labrum degeneration and calcification in hip OA. Targeting TGF-beta signaling may offer a means to reduce vascular invasion and fibrosis in acetabular labrum tissue.

Evaluating the causal effect of circulating proteome on the risk of osteoarthritis-related traits

OBJECTIVES

This study aims to identify circulating proteins that are causally associated with osteoarthritis (OA)-related traits through Mendelian randomisation (MR)-based analytical framework.

METHODS

Large-scale two-sample MR was employed to estimate the effects of thousands of plasma proteins on 12 OA-related traits. Additional analyses including Bayesian colocalisation, Steiger filtering analysis, assessment of protein-altering variants and mapping expression quantitative trait loci to protein quantitative trait loci were performed to investigate the reliability of the MR findings; protein-protein interaction, pathway enrichment analysis and evaluation of drug targets were conducted to deepen the understanding and identify potential therapeutic targets of OA.

RESULTS

Dozens of circulating proteins were identified to have putatively causal effects on OA-related traits, and a majority of these proteins were either drug targets or considered druggable.

CONCLUSIONS

Through MR analysis, we have identified numerous plasma proteins associated with OA-related traits, shedding light on protein-mediated mechanisms and offering promising therapeutic targets for OA.

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 ​= ​12), mild signs of joint damage (n ​= ​13) and end-stage OA (n ​= ​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.

TMT quantitative proteomics reveals key proteins relevant to microRNA-1-mediated regulation in osteoarthritis

Osteoarthritis (OA) is the second-commonest arthritis, but pathogenic and regulatory mechanisms underlying OA remain incompletely understood. Here, we aimed to identify the mechanisms associated with microRNA-1 (miR-1) treatment of OA in rodent OA models using a proteomic approach. First, N = 18 Sprague Dawley (SD) rats underwent sham surgery (n = 6) or ACL transection (n = 12), followed at an interval of one week by randomization of the ACL transection group to intra-articular administration of either 50 µL placebo (control group) or miR-1 agomir, a mimic of endogenous miR-1 (experimental group). After allowing for eight weeks of remodeling, articular cartilage tissue was harvested and immunohistochemically stained for the presence of MMP-13. Second, N = 30 Col2a1-cre-ERT2 /GFPf1/fl -RFP-miR-1 transgenic mice were randomized to intra-articular administration of either placebo (control group, N = 15) or tamoxifen, an inducer of miR-1 expression (experimental group, N = 15), before undergoing surgical disruption of the medial meniscus (DMM) after an interval of five days. After allowing for eight weeks of remodeling, articular cartilage tissue was harvested and underwent differential proteomic analysis. Specifically, tandem mass tagging (TMT) quantitative proteomic analysis was employed to identify inter-group differentially-expressed proteins (DEP), and selected DEPs were validated using real-time quantitative polymerase chain reaction (RT-qPCR) technology. Immunohistochemically-detected MMP-13 expression was significantly lower in the experimental rat group, and proteomic analyses of mouse tissue homogenate demonstrated that of 3526 identified proteins, 345 were differentially expressed (relative up- and down-regulation) in the experimental group. Proteins Fn1, P4ha1, P4ha2, Acan, F2, Col3a1, Fga, Rps29, Rpl34, and Fgg were the *top ten most-connected proteins, implying that miR-1 may regulate an expression network involving these proteins. Of these ten proteins, three were selected for further validation by RT-qPCR: the transcript of Fn1, known to be associated with OA, exhibited relative upregulation in the experimental group, whereas the transcripts of P4ha1 and Acan exhibited relative downregulation. These proteins may thus represent key miR-1 targets during OA-regulatory mechanisms, and may provide additional insights regarding therapeutic mechanisms of miR-1 in context of OA.

Culture-expanded mesenchymal stromal cell therapy: does it work in knee osteoarthritis? A pathway to clinical success

Osteoarthritis (OA) is a degenerative multifactorial disease with concomitant structural, inflammatory, and metabolic changes that fluctuate in a temporal and patient-specific manner. This complexity has contributed to refractory responses to various treatments. MSCs have shown promise as multimodal therapeutics in mitigating OA symptoms and disease progression. Here, we evaluated 15 randomized controlled clinical trials (RCTs) and 11 nonrandomized RCTs using culture-expanded MSCs in the treatment of knee OA, and we found net positive effects of MSCs on mitigating pain and symptoms (improving function in 12/15 RCTs relative to baseline and in 11/15 RCTs relative to control groups at study endpoints) and on cartilage protection and/or repair (18/21 clinical studies). We examined MSC dose, tissue of origin, and autologous vs. allogeneic origins as well as patient clinical phenotype, endotype, age, sex and level of OA severity as key parameters in parsing MSC clinical effectiveness. The relatively small sample size of 610 patients limited the drawing of definitive conclusions. Nonetheless, we noted trends toward moderate to higher doses of MSCs in select OA patient clinical phenotypes mitigating pain and leading to structural improvements or cartilage preservation. Evidence from preclinical studies is supportive of MSC anti-inflammatory and immunomodulatory effects, but additional investigations on immunomodulatory, chondroprotective and other clinical mechanisms of action are needed. We hypothesize that MSC basal immunomodulatory "fitness" correlates with OA treatment efficacy, but this hypothesis needs to be validated in future studies. We conclude with a roadmap articulating the need to match an OA patient subset defined by molecular endotype and clinical phenotype with basally immunomodulatory "fit" or engineered-to-be-fit-for-OA MSCs in well-designed, data-intensive clinical trials to advance the field.

The Diagnostic and Prognostic Value of Synovial Fluid Analysis in Joint Diseases

Liquid biopsy is an emergent test method for the diagnosis and prognosis in the clinic. Joint fluid, also known as synovial fluid, contains a variety of bioactive constituents that can be selectively detected and further evaluated in a convenient fashion. Therefore, synovial fluid analysis functions as a specific form of liquid biopsy and plays a vital role in numerous joint diseases. In spite of the component analysis of aspirated synovial fluid beingconsidered as the gold standard for diagnosis of joint infections, biopsy of joint fluid benefits the initial diagnosis and long-term prognosis of degenerative, inflammatory, autoimmune, traumatic, congenital, and even neoplastic joint diseases. The convenience and accuracy for disease evaluation are significantly elevated as a result of the combination of synovial fluid analysis and other novel clinical technologies. In this review, we shed light on the latent role of synovial fluid in the diagnosis and prognosis of articular diseases and proposed future prospects for relevant research in this field.

The impact of omics research on our understanding of osteoarthritis and future treatments

PURPOSE OF REVIEW

To review recent studies using 'Omics' approaches (genomics, proteomics, metabolomics, single cell analyses) in patient populations and animal models of osteoarthritis (OA), with the goal of identifying disease-modifying mechanisms that could serve as therapeutic and diagnostic targets.

RECENT FINDINGS

The number of genes, pathways and molecules with potential roles in OA pathogenesis has grown substantially over the last 18 months. Studies have expanded from their traditional focus on cartilage and gene expression to other joint tissues, proteins and metabolites. Single cell approaches provide unprecedented resolution and exciting insights into the heterogeneity of cellular activities in OA. Functional validation and investigation of underlying mechanisms in animal models of OA, in particular genetically engineered mice, link Omics findings to pathophysiology and potential therapeutic applications.

SUMMARY

Although great progress has been made in the use of Omics approaches to OA, in both animal models and patient samples, much work remains to be done. In addition to filling gaps in data sets not yet existing, integration of data from the various approaches, mechanistic investigations, and linkage of Omics data to patient stratification remain significant challenges.

Towards Precision Medicine for Osteoarthritis: Focus on the Synovial Fluid Proteome

Osteoarthritis (OA) is a joint degenerative disease that most affects old age. The study of proteomics in synovial fluid (SF) has the task of providing additional elements to diagnose and predict the progress of OA. This review aims to identify the most significant biomarkers in the study of OA and to stimulate their routine use. Some of the major components of the ECM, such as proteoglycan aggrecan and decorin, were found considerably reduced in OA. Some biomarkers have proved useful for staging the temporality of OA: Periostin was found to be increased in early OA, while CRTA1 and MMPs were found to be increased in late OA. In its natural attempt at tissue regeneration, Collagen III was found to be increased in early OA while decreased in late OA. Some molecules studied in other areas, such as ZHX3 (oncological marker), LYVE1, and VEGF (lymph and angiogenesis markers), also have been found to be altered in OA. It also has been recorded that alteration of the hormonal pathway, using a dosage of PPAR-γ and RETN, can influence the evolution of OA. IL-1, one of the most investigated biomarkers in OA-SF, is not as reliable as a target of OA in recent studies. The study of biomarkers in SF appears to be, in combination with the clinical and radiological aspects, an additional weapon to address the diagnosis and staging of OA. Therefore, it can guide us more appropriately towards the indication of arthroplasty in patients with OA.