Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers

Metabolic phenotypes reflect patient sex and injury status: A cross-sectional analysis of human synovial fluid

OBJECTIVE

Osteoarthritis is a heterogeneous disease. The objective was to compare differences in underlying cellular mechanisms and endogenous repair pathways between synovial fluid (SF) from male and female participants with different injuries to improve the current understanding of the pathophysiology of downstream post-traumatic osteoarthritis (PTOA).

DESIGN

SF from n = 33 knee arthroscopy patients between 18 and 70 years with no prior knee injuries was obtained pre-procedure and injury pathology assigned post-procedure. SF was extracted and analyzed via liquid chromatography-mass spectrometry metabolomic profiling to examine differences in metabolism between injury pathologies (ligament, meniscal, and combined ligament and meniscal) and patient sex. Samples were pooled and underwent secondary fragmentation to identify metabolites.

RESULTS

Different knee injuries uniquely altered SF metabolites and downstream pathways including amino acid, lipid, and inflammatory-associated metabolic pathways. Notably, sexual dimorphic metabolic phenotypes were examined between males and females and within injury pathology. Cervonyl carnitine and other identified metabolites differed in concentrations between sexes.

CONCLUSIONS

These results suggest that different injuries and patient sex are associated with distinct metabolic phenotypes. Considering these phenotypic associations, a greater understanding of metabolic mechanisms associated with specific injuries, sex, and PTOA development may yield data regarding how endogenous repair pathways differ between male and female injury types. Ongoing metabolomic analysis of SF in injured male and female patients can be performed to monitor PTOA development and progression.

Utilising Discriminant Function Analysis (DFA) for Classifying Osteoarthritis (OA) Patients and Volunteers Based on Biomarker Concentration

Osteoarthritis (OA) is a degenerative joint disease characterised by the breakdown of cartilage, causing pain, stiffness, and limited movement. Early diagnosis is crucial for effective management but remains challenging due to non-specific early symptoms. This study explores the application of Discriminant Function Analysis (DFA) to classify OA patients and healthy volunteers based on biomarker concentrations of Interleukin-6 (IL-6), Tumour necrosis factor-alpha (TNF-α), and Myeloperoxidase (MPO). DFA was employed to analyse biomarker data from 86 participants (58 patients, 28 volunteers) to evaluate the discriminatory power of these biomarkers in predicting OA. Significant differences were observed in MPO and TNF-α levels between groups, while IL-6 did not show a significant distinction. The iterative classification process improved model assumptions and classification accuracy, achieving a pre-classification accuracy of 71.8%, which adjusted to 57.1% post-classification. The results highlight DFA's potential in OA diagnosis, suggesting its utility in managing complex data and aiding personalised treatment strategies. The study underscores the need for larger sample sizes and additional biomarkers to enhance diagnostic robustness and provides a foundation for integrating DFA into clinical practice for early OA detection.

Metabolic Profiles of Encapsulated Chondrocytes Exposed to Short-Term Simulated Microgravity

The mechanism by which chondrocytes respond to reduced mechanical loading environments and the subsequent risk of developing osteoarthritis remains unclear. This is of particular concern for astronauts. In space the reduced joint loading forces during prolonged microgravity (10-6 g) exposure could lead to osteoarthritis (OA), compromising quality of life post-spaceflight. In this study, we encapsulated human chondrocytes in an agarose gel of similar stiffness to the pericellular matrix to mimic the cartilage microenvironment. We then exposed agarose-chondrocyte constructs to simulated microgravity (SM) using a rotating wall vessel (RWV) bioreactor to better assess the cartilage health risks associated with spaceflight. Global metabolomic profiling detected a total of 1205 metabolite features across all samples, with 497 significant metabolite features identified by ANOVA (FDR-corrected p-value < 0.05). Specific metabolic shifts detected in response to SM exposure resulted in clusters of co-regulated metabolites, as well as key metabolites identified by variable importance in projection scores. Microgravity-induced metabolic shifts in gel constructs and media were indicative of protein synthesis, energy metabolism, nucleotide metabolism, and oxidative catabolism. The microgravity associated-metabolic shifts were consistent with early osteoarthritic metabolomic profiles in human synovial fluid, which suggests that even short-term exposure to microgravity (or other reduced mechanical loading environments) may lead to the development of OA.

Unraveling the molecular landscape of osteoarthritis: A comprehensive review focused on the role of non-coding RNAs

Osteoarthritis (OA) poses a significant global health challenge, with its prevalence anticipated to increase in the coming years. This review delves into the emerging molecular biomarkers in OA pathology, focusing on the roles of various molecules such as metabolites, noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Advances in omics technologies have transformed biomarker identification, enabling comprehensive analyses of the complex pathways involved in OA pathogenesis. Notably, ncRNAs, especially miRNAs and lncRNAs, exhibit dysregulated expression patterns in OA, presenting promising opportunities for diagnosis and therapy. Additionally, the intricate interplay between epigenetic modifications and OA progression highlights the regulatory role of epigenetics in gene expression dynamics. Genome-wide association studies have pinpointed key genes undergoing epigenetic changes, providing insights into the inflammatory processes and chondrocyte hypertrophy typical of OA. Understanding the molecular landscape of OA, including biomarkers and epigenetic mechanisms, holds significant potential for developing innovative diagnostic tools and therapeutic strategies for OA management.

Osteochondral fluid transport in an ex vivo system

OBJECTIVE

Alterations to bone-to-cartilage fluid transport may contribute to the development of osteoarthritis (OA). Larger biological molecules in bone may transport from bone-to-cartilage (e.g., insulin, 5 kDa). However, many questions remain about fluid transport between these tissues. The objectives of this study were to (1) test for diffusion of 3 kDa molecular tracers from bone-to-cartilage and (2) assess potential differences in bone-to-cartilage fluid transport between different loading conditions.

DESIGN

Osteochondral cores extracted from bovine femurs (N = 10 femurs, 10 cores/femur) were subjected to either no-load (i.e., pure diffusion), pre-load only, or cyclic compression (5 ± 2% or 10 ± 2% strain) in a two-chamber bioreactor. The bone was placed into the bone compartment followed by a 3 kDa dextran tracer, and tracer concentrations in the cartilage compartment were measured every 5 min for 120 min. Tracer concentrations were analyzed for differences in beginning, peak, and equilibrium concentrations, loading effects, and time-to-peak tracer concentration.

RESULTS

Peak tracer concentration in the cartilage compartment was significantly higher compared to the beginning and equilibrium tracer concentrations. Cartilage-compartment tracer concentration and maximum fluorescent intensity were influenced by strain magnitude. No time-to-peak relationship was found between strain magnitudes and cartilage-compartment tracer concentration.

CONCLUSION

This study shows that bone-to-cartilage fluid transport occurs with 3 kDa dextran molecules. These are larger molecules to move between bone and cartilage than previously reported. Further, these results demonstrate the potential impact of cyclic compression on osteochondral fluid transport. Determining the baseline osteochondral fluid transport in healthy tissues is crucial to elucidating the mechanisms OA pathology.

Metabolomics in Osteoarthritis Knee: A Systematic Review of Literature

Introduction

Osteoarthritis (OA) is a common degenerative disorder of the synovial joints and is usually an age-related disease that occurs due to continuous wear and tear of the cartilage in the joints. Presently, there is no proven medical management to halt the progression of the disease in the early stages. The purpose of our systematic review is to analyze the possible metabolites and metabolic pathways that are specifically involved in OA pathogenesis and early treatment of the disease.

Materials and Methods

The articles were collected from PubMed, Cochrane, Google Scholar, Embase, and Scopus databases. "Knee", "Osteoarthritis", "Proteomics", "Lipidomics", "Metabolomics", "Metabolic Methods", and metabolic* were employed for finding the articles. Only original articles with human or animal OA models with healthy controls were included.

Results

From the initial screening, a total of 458 articles were identified from the 5 research databases. From these, 297 articles were selected in the end for screening, of which 53 papers were selected for full-text screening. Finally, 50 articles were taken for the review based on body fluid: 6 urine studies, 15 plasma studies, 16 synovial fluid studies, 11 serum studies, 4 joint tissue studies, and 1 fecal study. Many metabolites were found to be elevated in OA. Some of these metabolites can be used to stage the OA Three pathways that were found to be commonly involved are the TCA cycle, the glycolytic pathway, and the lipid metabolism.

Conclusion

All these studies showed a vast array of metabolites and metabolic pathways associated with OA. Metabolites like lysophospholipids, phospholipids, arginine, BCCA, and histidine were identified as potential biomarkers of OA but a definite association was not identified, Three pathways (glycolytic pathway, TCA cycle, and lipid metabolic pathways) have been found as highly significant in OA pathogenesis. These metabolic pathways could provide novel therapeutic targets for the prevention and progression of the disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43465-024-01169-5.

Causal association of genetically determined plasma metabolites with osteoarthritis: a two-sample Mendelian randomization study

Background

We aimed to elucidate the causal relationship between plasma metabolites and the vulnerability to Osteoarthritis (OA), encompassing both hip OA and knee OA.

Methods

We conducted a two-way two-sample Mendelian randomization (MR) analysis to investigate the association of 1,400 plasma metabolites with OA. The Inverse Variance Weighted (IVW) model served as the primary two-sample MR Analysis method, with supplementary analysis using the Weighted Median (WM) and MR Egger methods. To ensure the robustness of our findings, sensitivity analyses were performed, incorporating Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. To validate the identified metabolites, we utilized the Steiger test and linkage disequilibrium score regression.

Results

A total of 94 plasma metabolites were associated with osteoarthritis, with 60 associated with hip OA and 106 associated with knee OA. IVW analysis revealed that tryptophan levels showed the strongest positive association with hip OA (OR [95% CI]: 1.119 [1.024, 1.223]), while X-24757 levels exhibited the highest positive association with knee osteoarthritis (OR [95% CI]: 1.095 [1.032, 1.162]). Ethylparaben sulfate levels were found to have the greatest positive association with hip OA (OR [95% CI]: 1.118 [1.015, 1.231]). Notably, the plasma metabolite X-2475 showed a strong robust random effect across all three types of osteoarthritis. Metabolic pathway analysis revealed that the pathogenesis of osteoarthritis in the hip was mediated by acetylarginine, specifically in four important metabolic pathways: ethanol degradation (p = 0.044), amino sugar metabolism (p = 0.090), fatty acid biosynthesis (p = 0.095), and aspartate metabolism (p = 0.097816).

Conclusion

There is a significant association between tryptophan levels and the risk of hip OA, as well as X-24757 levels and the risk of knee osteoarthritis. Additionally, X-24757 levels are also linked to the risk of hip OA. Moreover, this study has identified four crucial metabolic pathways in hip osteoarthritis, which are all regulated by acetylarginine. These findings provide valuable insights into potential biomarkers for OA and highlight potential pathways for its prevention and clinical intervention.

Metabolomic Profiling and Characterization of a Novel 3D Culture System for Studying Chondrocyte Mechanotransduction

Articular chondrocytes synthesize and maintain the avascular and aneural articular cartilage. In vivo these cells are surrounded by a 3D pericellular matrix (PCM) containing predominantly collagen VI. The PCM protects chondrocytes and facilitates mechanotransduction, and PCM stiffness is critical in transmitting biomechanical signals to chondrocytes. Various culture systems with different hydrogels have been used to encapsulate chondrocytes for 3D culture, but many lack either the PCM or the in vivo stiffness of the cartilage matrix. Here, we demonstrate that primary chondrocytes cultured in alginate will form a pericellular matrix and display a phenotype similar to in vivo conditions. We found that primary human and bovine chondrocytes, when cultured in alginate beads with addition of sodium L-ascorbate for 7 days, had a pronounced PCM, retained their phenotype, and synthesized both collagens VI and II. This novel culture system enables alginate-encapsulated chondrocytes to develop a robust PCM thereby creating a model system to study mechanotransduction. We also observed distinct compression-induced changes in metabolomic profiles between the monolayer-agarose and alginate-released agarose-embedded chondrocytes indicating physiological changes in cell metabolism. Our data suggest that 3D preculture of chondrocytes in alginate before encapsulation in physiologically-stiff agarose leads to a pronounced development of pericellular matrix that is sustained in the presence of ascorbate. This novel model can be useful in studying the mechanism by which chondrocytes respond to cyclical compression and other types of loading simulating in vivo physiological conditions.

Starve a cold or feed a fever? Identifying cellular metabolic changes following infection and exposure to SARS-CoV-2

Viral infections induce major shifts in cellular metabolism elicited by active viral replication and antiviral responses. For the virus, harnessing cellular metabolism and evading changes that limit replication are essential for productive viral replication. In contrast, the cellular response to infection disrupts metabolic pathways to prevent viral replication and promote an antiviral state in the host cell and neighboring bystander cells. This competition between the virus and cell results in measurable shifts in cellular metabolism that differ depending on the virus, cell type, and extracellular environment. The resulting metabolic shifts can be observed and analyzed using global metabolic profiling techniques to identify pathways that are critical for either viral replication or cellular defense. SARS-CoV-2 is a respiratory virus that can exhibit broad tissue tropism and diverse, yet inconsistent, symptomatology. While the factors that determine the presentation and severity of SARS-CoV-2 infection remain unclear, metabolic syndromes are associated with more severe manifestations of SARS-CoV-2 disease. Despite these observations a critical knowledge gap remains between cellular metabolic responses and SARS-CoV-2 infection. Using a well-established untargeted metabolomics analysis workflow, we compared SARS-CoV-2 infection of human lung carcinoma cells. We identified significant changes in metabolic pathways that correlate with either productive or non-productive viral infection. This information is critical for characterizing the factors that contribute to SARS-CoV-2 replication that could be targeted for therapeutic interventions to limit viral disease.

Metabolomic profiles of cartilage and bone reflect tissue type, radiography-confirmed osteoarthritis, and spatial location within the joint

Osteoarthritis is the most common chronic joint disease, characterized by the abnormal remodeling of joint tissues including articular cartilage and subchondral bone. However, there are currently no therapeutic drug targets to slow the progression of disease because disease pathogenesis is largely unknown. Thus, the goals of this study were to identify metabolic differences between articular cartilage and subchondral bone, compare the metabolic shifts in osteoarthritic grade III and IV tissues, and spatially map metabolic shifts across regions of osteoarthritic hip joints. Articular cartilage and subchondral bone from 9 human femoral heads were obtained after total joint arthroplasty, homogenized and metabolites were extracted for liquid chromatography-mass spectrometry analysis. Metabolomic profiling revealed that distinct metabolic endotypes exist between osteoarthritic tissues, late-stage grades, and regions of the diseased joint. The pathways that contributed the most to these differences between tissues were associated with lipid and amino acid metabolism. Differences between grades were associated with nucleotide, lipid, and sugar metabolism. Specific metabolic pathways such as glycosaminoglycan degradation and amino acid metabolism, were spatially constrained to more superior regions of the femoral head. These results suggest that radiography-confirmed grades III and IV osteoarthritis are associated with distinct global metabolic and that metabolic shifts are not uniform across the joint. The results of this study enhance our understanding of osteoarthritis pathogenesis and may lead to potential drug targets to slow, halt, or reverse tissue damage in late stages of osteoarthritis.

Inflammation and Organic Cation Transporters Novel (OCTNs)

Inflammation is a physiological condition characterized by a complex interplay between different cells handled by metabolites and specific inflammatory-related molecules. In some pathological situations, inflammation persists underlying and worsening the pathological state. Over the years, two membrane transporters namely OCTN1 (SLC22A4) and OCTN2 (SLC22A5) have been shown to play specific roles in inflammation. These transporters form the OCTN subfamily within the larger SLC22 family. The link between these proteins and inflammation has been proposed based on their link to some chronic inflammatory diseases such as asthma, Crohn's disease (CD), and rheumatoid arthritis (RA). Moreover, the two transporters show the ability to mediate the transport of several compounds including carnitine, carnitine derivatives, acetylcholine, ergothioneine, and gut microbiota by-products, which have been specifically associated with inflammation for their anti- or proinflammatory action. Therefore, the absorption and distribution of these molecules rely on the presence of OCTN1 and OCTN2, whose expression is modulated by inflammatory cytokines and transcription factors typically activated by inflammation. In the present review, we wish to provide a state of the art on OCTN1 and OCTN2 transport function and regulation in relationships with inflammation and inflammatory diseases focusing on the metabolic signature collected in different body districts and gene polymorphisms related to inflammatory diseases.

Metabolic profiling of synovial fluid in human temporomandibular joint osteoarthritis

Introduction

Temporomandibular joint (TMJ) osteoarthritis (OA) is a common TMJ degenerative disease with an unclear mechanism. Synovial fluid (SF), an important component of TMJ, contains various proteins and metabolites that may directly contribute to OA. The present study aimed to investigate the influence of SF in TMJOA at the metabolite level.

Methods

Untargeted and widely targeted metabolic profiling were employed to identify metabolic changes in SF of 90 patients with different TMJOA grades according to TMJ magnetic resonance imaging.

Results

A total 1498 metabolites were detected. Most of the metabolites were amino acids and associated metabolites, benzene and substituted derivatives, and lipids. Among patients with mild, moderate and severe TMJOA, 164 gradually increasing and 176 gradually decreasing metabolites were identified, indicating that biosynthesis of cofactors, choline metabolism, mineral absorption and selenocompound metabolism are closely related to TMJOA grade. Combined metabolomics and clinical examination revealed 37 upregulated metabolites and 16 downregulated metabolites in patients with pain, of which 19 and 26 metabolites were positively and negatively correlated, respectively, with maximum interincisal opening. A model was constructed to diagnose TMJOA grade and nine biomarkers were identified. The identified metabolites are key to exploring the mechanism of TMJOA.

Discussion

In the present study, a metabolic profile was constructed and assessed using a much larger number of human SF samples from patients with TMJOA, and a model was established to contribute to the diagnosis of TMJOA grade. The findings expand our knowledge of metabolites in human SF of TMJOA patients, and provide an important basis for further research on the pathogenesis and treatment of TMJOA.

Comparative study of 1H-NMR metabolomic profile of canine synovial fluid in patients affected by four progressive stages of spontaneous osteoarthritis

The study aimed to assess the metabolomic profile of the synovial fluid (SF) of dogs affected by spontaneous osteoarthritis (OA) and compare any differences based on disease progression. Sixty client-owned dogs affected by spontaneous OA underwent clinical, radiographic, and cytologic evaluations to confirm the diagnosis. The affected joints were divided into four study groups based on the Kallgreen-Lawrence classification: OA1 (mild), OA2 (moderate), OA3 (severe), and OA4 (extremely severe/deforming). The osteoarthritic joint's SF was subjected to cytologic examination and 1H-NMR analysis. The metabolomic profiles of the study groups' SF samples were statistically compared using one-way ANOVA. Sixty osteoarthritic joints (45 stifles, 10 shoulders and 5 elbows) were included in the study. Fourteen, 28, and 18 joints were included in the OA1, OA2, and OA3 groups, respectively (0 joints in the OA4 group). Metabolomic analysis identified 48 metabolites, five of which were significantly different between study groups: Mannose and betaine were elevated in the OA1 group compared with the OA2 group, and the 2-hydroxyisobutyrate concentration decreased with OA progression; in contrast, isoleucine was less concentrated in mild vs. moderate OA, and lactate increased in severe OA. This study identified different 1H-NMR metabolomic profiles of canine SF in patients with progressive degrees of spontaneous OA, suggesting 1H-NMR metabolomic analysis as a potential alternative method for monitoring OA progression. In addition, the results suggest the therapeutic potentials of the metabolomic pathways that involve mannose, betaine, 2-hydroxyisobutyrate, isoleucine, and lactate.

Exploring molecular mechanisms of intra-articular changes in osteonecrosis of femoral head using DIA proteomics and bioinformatics

PURPOSE

This study is aimed to delve into the crucial proteins associated with hormonal osteonecrosis of the femoral head (ONFH) and its intra-articular lesions through data-independent acquisition (DIA) proteomics and bioinformatics analysis.

METHODS

We randomly selected samples from eligible ONFH patients and collected samples from the necrotic area of the femoral head and load-bearing cartilage. The control group comprised specimens from the same location in patients with femoral neck fractures. With DIA proteomics, we quantitatively and qualitatively tested both groups and analyzed the differentially expressed proteins (DEPs) between groups. Additionally, we enriched the analysis of DEP functions using gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways and verified the key proteins in ONFH through Western blot.

RESULTS

Proteomics experiment uncovered 937 common DEPs (422 upregulated and 515 downregulated) between the two groups. These DEPs mainly participate in biological processes such as hidden attributes, catalytic activity, molecular function regulators, and structural molecule activity, and in pathways such as starch and sucrose metabolism, ECM-receptor interaction, PI3K-Akt signaling, complement and coagulation cascades, IL-17 signaling, phagosome, transcriptional misregulation in cancers, and focal adhesion. Through protein-protein interaction network target gene analysis and Western blot validation, we identified C3, MMP9, APOE, MPO, LCN2, ELANE, HPX, LTF, and THBS1 as key proteins in ONFH.

CONCLUSIONS

With DIA proteomics and bioinformatics analysis, this study reveals the molecular mechanisms of intra-articular lesions in ONFH. A correlation in the necrotic area and load-bearing cartilage of ONFH at ARCO stages IIIB-IV as well as potential key regulatory proteins was identified. These findings will help more deeply understand the pathogenesis of ONFH and may provide important clues for seeking more effective treatment strategies.

Serum Metabolomic Alteration in Rats with Osteoarthritis Treated with Palm Tocotrienol-Rich Fraction Alone or in Combination with Glucosamine Sulphate

Osteoarthritis (OA) is a degenerative joint condition with limited disease-modifying treatments currently. Palm tocotrienol-rich fraction (TRF) has been previously shown to be effective against OA, but its mechanism of action remains elusive. This study aims to compare serum metabolomic alteration in Sprague-Dawley rats with monosodium iodoacetate (MIA)-induced OA which were treated with palm TRF, glucosamine sulphate, or a combination of both. This study was performed on thirty adult male rats, which were divided into normal control (n = 6) and OA groups (n = 24). The OA group received intra-articular injections of MIA and daily oral treatments of refined olive oil (vehicle, n = 6), palm TRF (100 mg/kg, n = 6), glucosamine sulphate (250 mg/kg, n = 6), or a combination of TRF and glucosamine (n = 6) for four weeks. Serum was collected at the study's conclusion for metabolomic analysis. The findings revealed that MIA-induced OA influences amino acid metabolism, leading to changes in metabolites associated with the biosynthesis of phenylalanine, tyrosine and tryptophan as well as alterations in the metabolism of phenylalanine, tryptophan, arginine and proline. Supplementation with glucosamine sulphate, TRF, or both effectively reversed these metabolic changes induced by OA. The amelioration of metabolic effects induced by OA is linked to the therapeutic effects of TRF and glucosamine. However, it remains unclear whether these effects are direct or indirect in nature.

Mass Spectrometry Analysis for Clinical Applications: A Review

Mass spectrometry (MS) has become an attractive analytical method in clinical analysis due to its comprehensive advantages of high sensitivity, high specificity and high throughput. Separation techniques coupled MS detection (e.g., LC-MS/MS) have shown unique advantages over immunoassay and have developed as golden criterion for many clinical applications. This review summarizes the characteristics and applications of MS, and emphasizes the high efficiency of MS in clinical research. In addition, this review also put forward further prospects for the future of mass spectrometry technology, including the introduction of miniature MS instruments, point-of-care detection and high-throughput analysis, to achieve better development of MS technology in various fields of clinical application. Moreover, as ambient ionization mass spectrometry (AIMS) requires little or no sample pretreatment and improves the flux of MS, this review also summarizes its potential applications in clinic.

Intra-articular delivery of an indoleamine 2,3-dioxygenase galectin-3 fusion protein for osteoarthritis treatment in male Lewis rats

OBJECTIVE

Osteoarthritis (OA) is driven by low-grade inflammation, and controlling local inflammation may offer symptomatic relief. Here, we developed an indoleamine 2,3-dioxygenase and galectin-3 fusion protein (IDO-Gal3), where IDO increases the production of local anti-inflammatory metabolites and Gal3 binds carbohydrates to extend IDO's joint residence time. In this study, we evaluated IDO-Gal3's ability to alter OA-associated inflammation and pain-related behaviors in a rat model of established knee OA.

METHODS

Joint residence was first evaluated with an analog Gal3 fusion protein (NanoLuc™ and Gal3, NL-Gal3) that produces luminescence from furimazine. OA was induced in male Lewis rats via a medial collateral ligament and medial meniscus transection (MCLT + MMT). At 8 weeks, NL or NL-Gal3 were injected intra-articularly (n = 8 per group), and bioluminescence was tracked for 4 weeks. Next, IDO-Gal3s's ability to modulate OA pain and inflammation was assessed. Again, OA was induced via MCLT + MMT in male Lewis rats, with IDO-Gal3 or saline injected into OA-affected knees at 8 weeks post-surgery (n = 7 per group). Gait and tactile sensitivity were then assessed weekly. At 12 weeks, intra-articular levels of IL6, CCL2, and CTXII were assessed.

RESULTS

The Gal3 fusion increased joint residence in OA and contralateral knees (p < 0.0001). In OA-affected animals, both saline and IDO-Gal3 improved tactile sensitivity (p = 0.008), but IDO-Gal3 also increased walking velocities (p ≤ 0.033) and improved vertical ground reaction forces (p ≤ 0.04). Finally, IDO-Gal3 decreased intra-articular IL6 levels within the OA-affected joint (p = 0.0025).

CONCLUSION

Intra-articular IDO-Gal3 delivery provided long-term modulation of joint inflammation and pain-related behaviors in rats with established OA.

Depletion of SNORA33 Abolishes ψ of 28S-U4966 and Affects the Ribosome Translational Apparatus

Eukaryotic ribosomes are complex molecular nanomachines translating genetic information from mRNAs into proteins. There is natural heterogeneity in ribosome composition. The pseudouridylation (ψ) of ribosomal RNAs (rRNAs) is one of the key sources of ribosome heterogeneity. Nevertheless, the functional consequences of ψ-based ribosome heterogeneity and its relevance for human disease are yet to be understood. Using HydraPsiSeq and a chronic disease model of non-osteoarthritic primary human articular chondrocytes exposed to osteoarthritic synovial fluid, we demonstrated that the disease microenvironment is capable of instigating site-specific changes in rRNA ψ profiles. To investigate one of the identified differential rRNA ψ sites (28S-ψ4966), we generated SNORA22 and SNORA33 KO SW1353 cell pools using LentiCRISPRv2/Cas9 and evaluated the ribosome translational capacity by 35S-Met/Cys incorporation, assessed the mode of translation initiation and ribosomal fidelity using dual luciferase reporters, and assessed cellular and ribosomal proteomes by LC-MS/MS. We uncovered that the depletion of SNORA33, but not SNORA22, reduced 28S-ψ4966 levels. The resulting loss of 28S-ψ4966 affected ribosomal protein composition and function and led to specific changes in the cellular proteome. Overall, our pioneering findings demonstrate that cells dynamically respond to disease-relevant changes in their environment by altering their rRNA pseudouridylation profiles, with consequences for ribosome function and the cellular proteome relevant to human disease.

Germ-Free C57BL/6 Mice Have Increased Bone Mass and Altered Matrix Properties but Not Decreased Bone Fracture Resistance

The gut microbiome impacts bone mass, which implies a disruption to bone homeostasis. However, it is not yet clear how the gut microbiome affects the regulation of bone mass and bone quality. We hypothesized that germ-free (GF) mice have increased bone mass and decreased bone toughness compared with conventionally housed mice. We tested this hypothesis using adult (20- to 21-week-old) C57BL/6J GF and conventionally raised female and male mice (n = 6-10/group). Trabecular microarchitecture and cortical geometry were measured from micro-CT of the femur distal metaphysis and cortical midshaft. Whole-femur strength and estimated material properties were measured using three-point bending and notched fracture toughness. Bone matrix properties were measured for the cortical femur by quantitative back-scattered electron imaging and nanoindentation, and, for the humerus, by Raman spectroscopy and fluorescent advanced glycation end product (fAGE) assay. Shifts in cortical tissue metabolism were measured from the contralateral humerus. GF mice had reduced bone resorption, increased trabecular bone microarchitecture, increased tissue strength and decreased whole-bone strength that was not explained by differences in bone size, increased tissue mineralization and fAGEs, and altered collagen structure that did not decrease fracture toughness. We observed several sex differences in GF mice, most notably for bone tissue metabolism. Male GF mice had a greater signature of amino acid metabolism, and female GF mice had a greater signature of lipid metabolism, exceeding the metabolic sex differences of the conventional mice. Together, these data demonstrate that the GF state in C57BL/6J mice alters bone mass and matrix properties but does not decrease bone fracture resistance. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Emerging molecular biomarkers in osteoarthritis pathology

Osteoarthritis (OA) is the most common form of arthritis resulting in joint discomfort and disability, culminating in decline in life quality. Attention has been drawn in recent years to disease-associated molecular biomarkers found in readily accessible biofluids due to low invasiveness of acquisition and their potential to detect early pathological molecular changes not observed with traditional imaging methodology. These biochemical markers of OA have been found in synovial fluid, blood, and urine. They include emerging molecular classes, such as metabolites and noncoding RNAs, as well as classical biomarkers, like inflammatory mediators and by-products of degradative processes involving articular cartilage. Although blood-based biomarkers tend to be most studied, the use of synovial fluid, a more isolated biofluid in the synovial joint, and urine as an excreted fluid containing OA biomarkers can offer valuable information on local and overall disease activity, respectively. Furthermore, larger clinical studies are required to determine relationships between biomarkers in different biofluids, and their impacts on patient measures of OA. This narrative review provides a concise overview of recent studies of OA using these four classes of biomarkers as potential biomarker for measuring disease incidence, staging, prognosis, and therapeutic intervention efficacy.

Metabolomic profiling to identify early urinary biomarkers and metabolic pathway alterations in autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of numerous fluid-filled cysts that lead to progressive loss of functional nephrons. Currently, there is an unmet need for diagnostic and prognostic indicators of early stages of the disease. Metabolites were extracted from the urine of patients with early-stage ADPKD (n = 48 study participants) and age- and sex-matched normal controls (n = 47) and analyzed by liquid chromatography-mass spectrometry. Orthogonal partial least squares-discriminant analysis was used to generate a global metabolomic profile of early ADPKD for the identification of metabolic pathway alterations and discriminatory metabolites as candidates of diagnostic and prognostic biomarkers. The global metabolomic profile exhibited alterations in steroid hormone biosynthesis and metabolism, fatty acid metabolism, pyruvate metabolism, amino acid metabolism, and the urea cycle. A panel of 46 metabolite features was identified as candidate diagnostic biomarkers. Notable putative identities of candidate diagnostic biomarkers for early detection include creatinine, cAMP, deoxycytidine monophosphate, various androgens (testosterone; 5-α-androstane-3,17,dione; trans-dehydroandrosterone), betaine aldehyde, phosphoric acid, choline, 18-hydroxycorticosterone, and cortisol. Metabolic pathways associated with variable rates of disease progression included steroid hormone biosynthesis and metabolism, vitamin D3 metabolism, fatty acid metabolism, the pentose phosphate pathway, tricarboxylic acid cycle, amino acid metabolism, sialic acid metabolism, and chondroitin sulfate and heparin sulfate degradation. A panel of 41 metabolite features was identified as candidate prognostic biomarkers. Notable putative identities of candidate prognostic biomarkers include ethanolamine, C20:4 anandamide phosphate, progesterone, various androgens (5-α-dihydrotestosterone, androsterone, etiocholanolone, and epiandrosterone), betaine aldehyde, inflammatory lipids (eicosapentaenoic acid, linoleic acid, and stearolic acid), and choline. Our exploratory data support metabolic reprogramming in early ADPKD and demonstrate the ability of liquid chromatography-mass spectrometry-based global metabolomic profiling to detect metabolic pathway alterations as new therapeutic targets and biomarkers for early diagnosis and tracking disease progression of ADPKD.NEW & NOTEWORTHY To our knowledge, this study is the first to generate urinary global metabolomic profiles from individuals with early-stage ADPKD with preserved renal function for biomarker discovery. The exploratory dataset reveals metabolic pathway alterations that may be responsible for early cystogenesis and rapid disease progression and may be potential therapeutic targets and pathway sources for candidate biomarkers. From these results, we generated a panel of candidate diagnostic and prognostic biomarkers of early-stage ADPKD for future validation.

Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study

BACKGROUND

Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases and is the leading cause of pain and disability in the aged population. However, the underlying biological mechanism has not been fully understood. This study aims to reveal the causal effect of circulation metabolites on OA susceptibility.

METHODS

A two-sample Mendelian Randomization (MR) analysis was performed to estimate the causality of GDMs on OA. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas 8 different OA phenotypes, including any-site OA (All OA), knee and/or hip OA (knee/hip OA), knee OA, hip OA, spine OA, finger and/or thumb OA (hand OA), finger OA, thumb OA, were set the outcomes. Inverse-variance weighted (IVW) was used for calculating causal estimates. Methods including weight mode, weight median, MR-egger, and MR-PRESSO were used for the sensitive analysis. Furthermore, metabolic pathway analysis was performed via the web-based Metaconflict 4.0. All statistical analyses were performed in R software.

RESULTS

In this MR analysis, a total of 235 causative associations between metabolites and different OA phenotypes were observed. After false discovery rate (FDR) correction and sensitive analysis, 9 robust causative associations between 7 metabolites (e.g., arginine, kynurenine, and isovalerylcarnitine) and 5 OA phenotypes were finally identified. Additionally, eleven significant metabolic pathways in 4 OA phenotypes were identified by metabolic pathway analysis.

CONCLUSION

The finding of our study suggested that identified metabolites and metabolic pathways can be considered useful circulating metabolic biomarkers for OA screening and prevention in clinical practice, and can also serve as candidate molecules for future mechanism exploration and drug target selection.

Intra-Articular Delivery of an Indoleamine 2,3-Dioxygenase Galectin-3 Fusion Protein for Osteoarthritis Treatment in Male Lewis Rats

Objective : Controlling joint inflammation can improve osteoarthritis (OA) symptoms; however, current treatments often fail to provide long-term effects. We have developed an indoleamine 2,3-dioxygenase and galectin-3 fusion protein (IDO-Gal3). IDO converts tryptophan to kynurenines, directing the local environment toward an anti-inflammatory state; Gal3 binds carbohydrates and extends IDO's joint residence time. In this study, we evaluated IDO-Gal3's ability to alter OA-associated inflammation and pain-related behaviors in a rat model of established knee OA. Methods : Joint residence was first evaluated with an analog Gal3 fusion protein (NanoLuc™ and Gal3, NL-Gal3) that produces luminescence from furimazine. OA was induced in male Lewis rats via a medial collateral ligament and medial meniscus transection (MCLT+MMT). At 8 weeks, NL or NL-Gal3 were injected intra-articularly (n=8 per group), and bioluminescence was tracked for 4 weeks. Next, IDO-Gal3's ability to modulate OA pain and inflammation was assessed. Again, OA was induced via MCLT+MMT in male Lewis rats, with IDO-Gal3 or saline injected into OA-affected knees at 8 weeks post-surgery (n=7 per group). Gait and tactile sensitivity were then assessed weekly. At 12 weeks, intra-articular levels of IL6, CCL2, and CTXII were assessed. Results : The Gal3 fusion increased joint residence in OA and contralateral knees (p<0.0001). In OA-affected animals, IDO-Gal3 improved tactile sensitivity (p=0.002), increased walking velocities (p≤0.033), and improved vertical ground reaction forces (p≤0.04). Finally, IDO-Gal3 decreased intra-articular IL6 levels within the OA-affected joint (p=0.0025). Conclusion : Intra-articular IDO-Gal3 delivery provided long-term modulation of joint inflammation and pain-related behaviors in rats with established OA.

Utilizing metabolomics to identify potential biomarkers and perturbed metabolic pathways in osteoarthritis: A systematic review

PURPOSE

Osteoarthritis (OA) is a joint disease that is clinically diagnosed using components of history, physical exam, and characteristic radiographic findings, such as joint space narrowing. Currently, there are no laboratory findings that are specific to a diagnosis of OA. The purpose of this systematic review is to evaluate the state of current studies of metabolomic biomarkers that can aid in the diagnosis and treatment of OA.

METHODS

Articles were gathered from PubMed and Web of Science using the search terms "osteoarthritis" and "biomarkers" and "metabolomics". Last search of databases took place December 3rd, 2022. Duplicates were manually screened, along with any other results that were not original journal articles. Only original reports involving populations with diagnosed primary or secondary OA (human participants) or surgically induced OA (animal participants) and a healthy control group for comparison were considered for inclusion. Metabolites and metabolic pathways reported in included articles were then manually extracted and evaluated for importance based on reported a priori p-values and/or area under the receiver-operator curve (AUC).

RESULTS

Of the 161 results that were returned in the database searches, 43 unique articles met the inclusion criteria. Articles were categorized based on body fluid analyzed: 6 studies on urine samples, 13 studies on plasma samples, 11 studies on synovial fluid (SF) samples, 11 studies on serum samples, 1 study on both synovial fluid and serum, and 1 study that involved both plasma and synovial fluid. To synthesize results, individual metabolites, as well as metabolic pathways that involve frequently reported metabolites, are presented for each study. Indications as to whether metabolite levels were increased or decreased are also included if this data was included in the original articles.

CONCLUSIONS

These studies clearly show that there are a wide range of metabolic pathways perturbed in OA. For this period, there was no consensus on a single metabolite, or panel of metabolites, that would be clinically useful in early diagnosis of OA or distinguishing OA from a healthy control. However, many common metabolic pathways were identified in the studies, including TCA cycle, fatty acid metabolism, amino acid metabolism (notably BCAA metabolism and tryptophan metabolism via kynurenine pathway), nucleotide metabolism, urea cycle, cartilage matrix components, and phospholipid metabolism. Future research is needed to define effective clinical biomarkers of osteoarthritis from metabolomic and other data.

Metabolomic Phenotypes Reflect Patient Sex and Injury Status: A Cross-Sectional Analysis of Human Synovial Fluid

Background

Post-traumatic osteoarthritis (PTOA) is caused by knee injuries like anterior cruciate ligament (ACL) injuries. Often, ACL injuries are accompanied by damage to other tissues and structures within the knee including the meniscus. Both are known to cause PTOA but underlying cellular mechanisms driving disease remain unknown. Aside from injury, patient sex is a prevalent risk factor associated with PTOA.

Hypothesis

Metabolic phenotypes of synovial fluid that differ by knee injury pathology and participant sex will be distinct from each other.

Study Design

A cross-sectional study.

Methods

Synovial fluid from n=33 knee arthroscopy patients between 18 and 70 years with no prior knee injuries was obtained pre-procedure and injury pathology assigned post-procedure. Synovial fluid was extracted and analyzed via liquid chromatography mass spectrometry metabolomic profiling to examine differences in metabolism between injury pathologies and participant sex. Additionally, samples were pooled and underwent fragmentation to identify metabolites.

Results

Metabolite profiles revealed that injury pathology phenotypes were distinct from each other where differences in endogenous repair pathways that are triggered post-injury were detected. Specifically, acute differences in metabolism mapped to amino acid metabolism, lipid-related oxidative metabolism, and inflammatory-associated pathways. Lastly, sexual dimorphic metabolic phenotypes were examined between male and female participants, and within injury pathology. Specifically, Cervonyl Carnitine and other identified metabolites differed in concentration between sexes.

Conclusions

The results of this study suggest that different injuries (e.g., ligament vs. meniscus), as well as sex are associated with distinct metabolic phenotypes. Considering these phenotypic associations, a greater understanding of metabolic mechanisms associated with specific injuries and PTOA development may yield data regarding how endogenous repair pathways differ between injury types. Furthermore, ongoing metabolomic analysis of synovial fluid in injured male and female patients can be performed to monitor PTOA development and progression.

Clinical Relevance

Extension of this work may potentially lead to the identification of biomarkers as well as drug targets that slow, stop, or reverse PTOA progression based on injury type and patient sex.

Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling

Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (n = 31), HC (healthy controls) group (n = 57) and non-OA group (n = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (18:0/22:6), p-cresol sulfate and so on, were identified as critical metabolites for the diagnosis of OA and HC and yielded an area under the curve (AUC) of 0.978. The other panel of unknown m/z 239.091, phosphatidylcholine (18:0/18:0) and phenylalanine were found to distinguish OA from non-OA and achieved an AUC of 0.888. These potential biomarkers are mainly involved in lipid metabolism, glucose metabolism and amino acid metabolism. It is expected to reveal new insight into OA pathogenesis from changed metabolic pathways.

Subchondral bone structure and synovial fluid metabolism are altered in injured and contralateral limbs 7 days after non-invasive joint injury in skeletally-mature C57BL/6 mice

OBJECTIVE

Post-traumatic osteoarthritis (PTOA) commonly develops after ACL injury, but early changes to the joint soon after injury are insufficiently understood. The objectives of this study were (1) evaluate the response of subchondral bone tissue modulus to joint injury and (2) identify which bone structural, material, and metabolic outcomes are local (i.e., injured joint only) or systemic (i.e., injured and contralateral-to-injured).

DESIGN

Female C57Bl∖6N mice (19 weeks at injury) underwent tibial compression overload to simulate ACL injury (n = 8) or a small pre-load (n = 8). Synovial fluid was harvested at euthanasia 7 days later for metabolomic profiling. Bone outcomes included epiphyseal and SCB microarchitecture, SCB nanoindentation modulus, SCB formation rate, and osteoclast number density.

RESULTS

Injury decreased epiphyseal bone volume fraction ([-5.29, -1.38%], P = 0.0016) and decreased SCB thickness for injured vs sham-injured limbs ([2.2, 31.4 μm], P = 0.017)). Epiphyseal bone loss commonly occurred for contralateral-to-injured limbs. There was not sufficient evidence to conclude that SCB modulus changes with injury. Metabolomic analyses revealed dysregulated synovial fluid metabolism with joint injury but that many metabolic pathways are shared between injured and contralateral-to-injured limbs.

CONCLUSION

This study demonstrates rapid changes to bone structure and synovial fluid metabolism after injury with the potential for influencing the progression to PTOA. These changes are often evidenced in the contralateral-to-injured limb, indicating that systemic musculoskeletal responses to joint injury should not be overlooked.

Correlations between metabolites in the synovial fluid and serum: A mouse injury study

Osteoarthritis occurs frequently after joint injury. Currently, osteoarthritis is diagnosed by radiographic changes that are typically found after the disease has progressed to multiple tissues. The primary objective was to compare potential metabolomic biomarkers of joint injury between synovial fluid and serum in a mouse model of posttraumatic osteoarthritis. The secondary objective was to gain insight into the pathophysiology of osteoarthritis by examining metabolomic profiles after joint injury. Twelve-week-old adult female C57BL/6 mice (n = 12) were randomly assigned to control, Day 1, or Day 8 postinjury groups. Randomly selected stifle joints were subjected to a single rapid compression. At Days 1 and 8 postinjury, serum was extracted before mice were euthanized for synovial fluid collection. Metabolomic profiling detected ~2500 metabolites across serum and synovial fluid. Of these, 179 were positively correlated and 51 were negatively correlated between synovial fluid and serum, indicating the potential for the development of metabolomic biomarkers. Synovial fluid captured injury-induced differences in metabolomic profiles at both Days 1 and 8 after injury whereas serum did not. However, synovial fluid and serum were distinct at both time points after injury. In synovial fluid, pathways of interest mapped to amino acid synthesis and degradation, bupropion degradation, and transfer RNA (tRNA) charging. In serum, pathways were amino acid synthesis and degradation, the phospholipase pathway, and nicotine degradation. These results provide a rich picture of the injury response at early time points after joint injury. Furthermore, the correlations between synovial fluid and serum metabolites suggest the potential to gain insight into intra-articular pathophysiology through analysis of serum metabolites.

Stage related metabolic profile of the synovial fluid in patients with acute flares of knee osteoarthritis

Background and aim

Osteoarthritis (OA) is the most common joint condition and the leading cause of pain and disability in elderly patients. Currently, there is no biomarker available for the early diagnosis of OA, and limited data is available regarding the molecular basis of progression for OA. For this reason, this study aimed to identify the metabolomic profile of early and late OA using high-performance liquid chromatography coupled with untargeted mass spectrometry (LC-MS).

Methods

31 patients with knee OA and joint effusion were enrolled. Based on Kellgren/Laurence scale, 12 patients were classified as early OA (eOA) and 19 as late OA (lOA). The synovial fluid (SF) was collected and characterized by untargeted LC-MS. Only the metabolites identified in more than 25% of each group were kept for further analysis. Principal component analysis (PCA) enabled the unsupervised clustering of the eOA and lOA groups. Further, for classification, the best three principal components (PCs) were used as input for two machine learning algorithms (random forest and naïve Bayes), which were trained to discriminate between the eOA and lOA groups.

Results

43 metabolites were identified in both eOA and lOA, but after selecting the metabolites present in at least 25% of the patients in each group, the metabolomics analysis yielded a panel of only nine metabolites: four metabolites related to phospholipids (phosphatidylcholine 20:0/18:2 and 18:0/20:2, sphingomyelin, and ceramide), three metabolites belonging to purine metabolites (inosine 5'-phosphate, adenosine thiamine diphosphate, and diadenosine 5',5'-diphosphate), one metabolite was a gonadal steroid hormone (estrone 3-sulfate), and one metabolite represented by heme, with all but ceramide (d18:1/20:0) being enriched in the lOA group. By using as features the best three PCs (PC2, PC8 and PC9), random forest and naïve Bayes machine learning algorithms yielded a classification accuracy of 0.81 and 0.78, respectively.

Conclusion

Our LC-MS analysis of SF from patients with eOA and lOA indicates stage-dependent differences, lOA being associated with a perturbed metabolome of phospholipids, purine metabolites, gonadal steroid hormones (estrone 3-sulfate) and a heme molecule. Specific questions need to be answered regarding the biosynthesis and function of these metabolites in osteoarthritic joints, with the aim of developing new relevant biomarkers and therapeutic strategies.

Metabolic Profiling of Serum for Osteoarthritis Biomarkers

Osteoarthritis is a prevalent aging disease in the world, and in recent years it has shown a trend toward younger age, which is becoming a major health problem in the world and seriously endangers the health of the elderly. However, the etiology and pathogenesis of osteoarthritis are still unclear, causing great trouble for treatment. To screen out candidate biomarkers that could be used for the identification of osteoarthritis and explore the pathogenesis of osteoarthritis, we performed an untargeted metabolomics analysis of nine New Zealand rabbit serum samples by LC-MS/MS, including three normal serum samples (control group) and six osteoarthritis serum samples (case group). Finally, 44 differential metabolites were identified, and the ROC analysis results indicated that a total of 36 differential metabolites could be used as candidate biomarkers. Further metabolic pathway enrichment analysis was performed on these differential metabolites, and we found that a total of 17 metabolic pathways were affected, which may provide directions for the study of osteoarthritis mechanisms.

Serum Metabolomic Signatures for Knee Cartilage Volume Loss over 10 Years in Community-Dwelling Older Adults

Osteoarthritis (OA) is the most prevalent joint disorder characterized by joint structural pathological changes with the loss of articular cartilage as its hallmark. Tools that can predict cartilage loss would help identify people at high risk, thus preventing OA development. The recent advance of the metabolomics provides a new avenue to systematically investigate metabolic alterations in disease and identify biomarkers for early diagnosis. Using a metabolomics approach, the current study aimed to identify serum metabolomic signatures for predicting knee cartilage volume loss over 10 years in the Tasmania Older Adult Cohort (TASOAC). Cartilage volume was measured in the medial, lateral, and patellar compartments of the knee by MRI at baseline and follow-up. Changes in cartilage volume over 10 years were calculated as percentage change per year. Fasting serum samples collected at 2.6-year follow-up were metabolomically profiled using the TMIC Prime Metabolomics Profiling Assay and pairwise metabolite ratios as the proxies of enzymatic reaction were calculated. Linear regression was used to identify metabolite ratio(s) associated with change in cartilage volume in each of the knee compartments with adjustment for age, sex, and BMI. The significance level was defined at α = 3.0 × 10−6 to control multiple testing. A total of 344 participants (51% females) were included in the study. The mean age was 62.83 ± 6.13 years and the mean BMI was 27.48 ± 4.41 kg/m2 at baseline. The average follow-up time was 10.84 ± 0.66 years. Cartilage volume was reduced by 1.34 ± 0.72%, 1.06 ± 0.58%, and 0.98 ± 0.46% per year in the medial, lateral, and patellar compartments, respectively. Our data showed that the increased ratios of hexadecenoylcarnitine (C16:1) to tetradecanoylcarnitine (C14) and C16:1 to dodecanoylcarnitine (C12) were associated with 0.12 ± 0.02% reduction per year in patellar cartilage volume (both p < 3.03 × 10−6). In conclusion, our data suggested that alteration of long chain fatty acid β-oxidation was involved in patellar cartilage loss. While confirmation is needed, the ratios of C16:1 to C14 and C12 might be used to predict long-term cartilage loss.

The cortical bone metabolome of C57BL / 6J mice is sexually dimorphic

Cortical bone quality, which is sexually dimorphic, depends on bone turnover and therefore on the activities of remodeling bone cells. However, sex differences in cortical bone metabolism are not yet defined. Adding to the uncertainty about cortical bone metabolism, the metabolomes of whole bone, isolated cortical bone without marrow, and bone marrow have not been compared. We hypothesized that the metabolome of isolated cortical bone would be distinct from that of bone marrow and would reveal sex differences. Metabolite profiles from liquid chromatography–mass spectrometry (LC‐MS) of whole bone, isolated cortical bone, and bone marrow were generated from humeri from 20‐week‐old female C57Bl/6J mice. The cortical bone metabolomes were then compared for 20‐week‐old female and male C57Bl/6J mice. Femurs from male and female mice were evaluated for flexural material properties and were then categorized into bone strength groups. The metabolome of isolated cortical bone was distinct from both whole bone and bone marrow. We also found sex differences in the isolated cortical bone metabolome. Based on metabolite pathway analysis, females had higher lipid metabolism, and males had higher amino acid metabolism. High‐strength bones, regardless of sex, had greater tryptophan and purine metabolism. For males, high‐strength bones had upregulated nucleotide metabolism, whereas lower‐strength bones had greater pentose phosphate pathway metabolism. Because the higher‐strength groups (females compared with males, high‐strength males compared with lower‐strength males) had higher serum type I collagen cross‐linked C‐telopeptide (CTX1)/procollagen type 1 N propeptide (P1NP), we estimate that the metabolomic signature of bone strength in our study at least partially reflects differences in bone turnover. These data provide novel insight into bone bioenergetics and the sexual dimorphic nature of bone material properties in C57Bl/6 mice. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Innovative in Silico Approaches for Characterization of Genes and Proteins

Bioinformatics is an amalgamation of biology, mathematics and computer science. It is a science which gathers the information from biology in terms of molecules and applies the informatic techniques to the gathered information for understanding and organizing the data in a useful manner. With the help of bioinformatics, the experimental data generated is stored in several databases available online like nucleotide database, protein databases, GENBANK and others. The data stored in these databases is used as reference for experimental evaluation and validation. Till now several online tools have been developed to analyze the genomic, transcriptomic, proteomics, epigenomics and metabolomics data. Some of them include Human Splicing Finder (HSF), Exonic Splicing Enhancer Mutation taster, and others. A number of SNPs are observed in the non-coding, intronic regions and play a role in the regulation of genes, which may or may not directly impose an effect on the protein expression. Many mutations are thought to influence the splicing mechanism by affecting the existing splice sites or creating a new sites. To predict the effect of mutation (SNP) on splicing mechanism/signal, HSF was developed. Thus, the tool is helpful in predicting the effect of mutations on splicing signals and can provide data even for better understanding of the intronic mutations that can be further validated experimentally. Additionally, rapid advancement in proteomics have steered researchers to organize the study of protein structure, function, relationships, and dynamics in space and time. Thus the effective integration of all of these technological interventions will eventually lead to steering up of next-generation systems biology, which will provide valuable biological insights in the field of research, diagnostic, therapeutic and development of personalized medicine.

High-Throughput Chinmedomics Strategy Discovers the Quality Markers and Mechanisms of Wutou Decoction Therapeutic for Rheumatoid Arthritis

Wutou decoction (WTD) is a traditional Chinese medicine prescription for the treatment of rheumatoid arthritis (RA), and this study systematically analyzed the metabolic mechanism and key pharmacodynamic components of WTD in RA rats by combining untargeted metabolomics and serum pharmacochemistry of traditional Chinese medicine to enrich the evidence of WTD quality markers (Q-markers) studies. WTD prevented synovial edema in RA rats and reduced tumor necrosis factor-alpha and interleukin 6 levels in rat serum, according to the results of an enzyme-linked immunosorbent examination and histopathological inspection. In model rats, pattern recognition and multivariate statistical analysis revealed 24 aberrant metabolites that disrupted linoleic acid metabolism, arachidonic acid metabolism, arginine and proline metabolism, etc. However, continued dosing of WTD for 28 days reversed 13 abnormal metabolites, which may be an important therapeutic mechanism from a metabolomic perspective. Importantly, 12 prototypical components and 16 metabolites from WTD were characterized in RA rat serum. The results of Pearson correlation analysis showed that aconitine, L-ephedrine, L-methylephedrine, quercetin, albiflorin, paeoniflorigenone, astragaline A, astragaloside II, glycyrrhetic acid, glycyrrhizic acid, licurazide, and isoliquiritigenin are the key pharmacological components that regulate the metabolism of RA rats, and they are identified as Q-markers. In sum, utilizing metabolomics and serum pharmacochemistry of traditional Chinese medicine, the metabolic mechanisms and Q-markers of WTD therapy in RA rats were revealed, providing a theoretical basis for the quality control investigation of WTD.

Fundamentals of OA. An initiative of Osteoarthritis and Cartilage. Obesity and metabolic factors in OA

OBJECTIVE

Obesity was once considered a risk factor for knee osteoarthritis (OA) primarily for biomechanical reasons. Here we provide an additional perspective by discussing how obesity also increases OA risk by altering metabolism and inflammation.

DESIGN

This narrative review is presented in four sections: 1) metabolic syndrome and OA, 2) metabolic biomarkers of OA, 3) evidence for dysregulated chondrocyte metabolism in OA, and 4) metabolic inflammation: joint tissue mediators and mechanisms.

RESULTS

Metabolic syndrome and its components are strongly associated with OA. However, evidence for a causal relationship is context dependent, varying by joint, gender, diagnostic criteria, and demographics, with additional environmental and genetic interactions yet to be fully defined. Importantly, some aspects of the etiology of obesity-induced OA appear to be distinct between men and women, especially regarding the role of adipose tissue. Metabolomic analyses of serum and synovial fluid have identified potential diagnostic biomarkers of knee OA and prognostic biomarkers of disease progression. Connecting these biomarkers to cellular pathophysiology will require future in vivo studies of joint tissue metabolism. Such studies will help reveal when a metabolic process or a metabolite itself is a causal factor in disease progression. Current evidence points towards impaired chondrocyte metabolic homeostasis and metabolic-immune dysregulation as likely factors connecting obesity to the increased risk of OA.

CONCLUSIONS

A deeper understanding of how obesity alters metabolic and inflammatory pathways in synovial joint tissues is expected to provide new therapeutic targets and an improved definition of "metabolic" and "obesity" OA phenotypes.

In vivo mechanotransduction: Effect of acute exercise on the metabolomic profiles of mouse synovial fluid

Objective

Exercise is known to induce beneficial effects in synovial joints. However, the mechanisms underlying these are unclear. Synovial joints experience repeated mechanical loading during exercise. These mechanical stimuli are transduced into biological responses through cellular mechanotransduction. Mechanotransduction in synovial joints is typically studied in tissues. However, synovial fluid directly contacts all components of the joint, and thus may produce a whole-joint picture of the mechanotransduction response to loading. The objective of this study was to determine if metabolic phenotypes are present in the synovial fluid after acute exercise as a first step to understanding the beneficial effects of exercise on the joint.

Material and methods

Mice underwent a single night of voluntary wheel running or standard housing and synovial fluid was harvested for global metabolomic profiling by LC-MS. Hierarchical unsupervised clustering, partial least squares discriminant, and pathway analysis provided insight into exercise-induced mechanotransduction.

Results

Acute exercise produced a distinct metabolic phenotype in synovial fluid. Mechanosensitive metabolites included coenzyme A derivatives, prostaglandin derivatives, phospholipid species, tryptophan, methionine, vitamin D3, fatty acids, and thiocholesterol. Enrichment analysis identified several pathways previously linked to exercise including amino acid metabolism, inflammatory pathways, citrulline-nitric oxide cycle, catecholamine biosynthesis, ubiquinol biosynthesis, and phospholipid metabolism.

Conclusion

To our knowledge, this is the first study to investigate metabolomic profiles of synovial fluid during in vivo mechanotransduction. These profiles indicate that exercise induced stress-response processes including both pro- and anti-inflammatory pathways. Further research will expand these results and define the relationship between the synovial fluid and the serum.

Effects of mechanical stimulation on metabolomic profiles of SW1353 chondrocytes: shear and compression

Mechanotransduction is a biological phenomenon where mechanical stimuli are converted to biochemical responses. A model system for studying mechanotransduction are the chondrocytes of articular cartilage. Breakdown of this tissue results in decreased mobility, increased pain, and reduced quality of life. Either disuse or overloading can disrupt cartilage homeostasis, but physiological cyclical loading promotes cartilage homeostasis. To model this, we exposed SW1353 cells to cyclical mechanical stimuli, shear and compression, for different durations of time (15 and 30 min). By utilizing liquid chromatography-mass spectroscopy (LC-MS), metabolomic profiles were generated detailing metabolite features and biological pathways that are altered in response to mechanical stimulation. In total, 1457 metabolite features were detected. Statistical analyses identified several pathways of interest. Taken together, differences between experimental groups were associated with inflammatory pathways, lipid metabolism, beta-oxidation, central energy metabolism, and amino acid production. These findings expand our understanding of chondrocyte mechanotransduction under varying loading conditions and time periods. This article has an associated First Person interview with the first author of the paper.

Compatibility of Achyranthes bidentata components in reducing inflammatory response through Arachidonic acid pathway for treatment of Osteoarthritis

Achyranthes bidentate is a common traditional Chinese medicine (TCM) used in treating osteoarthritis (OA). The compatibility between effective components has now become a breakthrough in understanding the mechanism of TCM. This study aimed at determining the optimal compatibility and possible mechanism of Achyranthes bidentate for OA treatment. Results showed that the adhesion score of the OA group is higher than NC group, and showed a trend of down-regulation in the intervention group. The CHI3L1 and IL-1β in joint fluid of the OA group was significantly increased compared to the sham operation group (NC group). Group G, I, and L exhibited significantly down-regulated CHI3L1, while groups C, F, I, K, and L exhibited reduced IL-1β. Joint adhesion, damage in cartilage, and synovial tissue was found in the OA model, cartilage tissue was found recovered in groups I, J, and L, and synovial tissue was recovered in group G, I, and L. Thus, group I and L were chosen for metabolite analysis, and indole-3-propionic acid was slightly up-regulated, while koeiginequinone A, prostaglandin H2, and 1-hydroxy-3-methoxy-10-methylacridonew were down-regulated in group I and L. According to functional analysis, the arachidonic acid (AA) metabolic pathway is enriched. Down-regulated expression of vital proteins in the AA metabolism pathway, such as PGE2 and COX2 in group I and L were verified. In conclusion, Hydroxyecdysone, Oleanolic acid, Achyranthes bidentata polysaccharide at a compatibility of 0.03-μg/mg, 2.0-μg/mg, 20.0-μg/mg or 0.03-μg/mg, 2.0-μg/mg, 10.0-μg/mg, respectively, may be the optimal compatibility of Achyranthes bidentate.

Analysis of Serum Metabolomics in Rats with Osteoarthritis by Mass Spectrometry

Osteoarthritis is a common multifactorial chronic disease that occurs in articular cartilage, subchondral bone, and periarticular tissue. The pathogenesis of OA is still unclear. To investigate the differences in serum metabolites between OA and the control group, liquid chromatography/mass spectrometry (LC/MS)-based metabolomics was used. To reveal the pathogenesis of OA, 12 SD male rats were randomly divided into control and OA groups using collagenase to induce OA for modeling, and serum was collected 7 days after modeling for testing. The OA group was distinguished from the control group by principal component analysis and orthogonal partial least squares-discriminant analysis, and six biomarkers were finally identified. These biomarkers were metabolized through tryptophan metabolism, glutamate metabolism, nitrogen metabolism, spermidine metabolism, and fatty acid metabolism pathways. The study identified metabolites that may be altered in OA, suggesting a role in OA through relevant metabolic pathways. Metabolomics, as an important tool for studying disease mechanisms, provides useful information for studying the metabolic mechanisms of OA.

Collagen type II: From biosynthesis to advanced biomaterials for cartilage engineering

Collagen type II is the major constituent of cartilage tissue. Yet, cartilage engineering approaches are primarily based on collagen type I devices that are associated with suboptimal functional therapeutic outcomes. Herein, we briefly describe cartilage's development and cellular and extracellular composition and organisation. We also provide an overview of collagen type II biosynthesis and purification protocols from tissues of terrestrial and marine species and recombinant systems. We then advocate the use of collagen type II as a building block in cartilage engineering approaches, based on safety, efficiency and efficacy data that have been derived over the years from numerous in vitro and in vivo studies.

Effects of long-term exercise and a high-fat diet on synovial fluid metabolomics and joint structural phenotypes in mice: an integrated network analysis

OBJECTIVE

To explore how systemic factors that modify knee osteoarthritis risk are connected to 'whole-joint' structural changes by evaluating the effects of high-fat diet and wheel running exercise on synovial fluid (SF) metabolomics.

METHODS

Male mice were fed a defined control or high-fat (60% kcal fat) diet from 6 to 52 weeks of age, and half the animals were housed with running wheels from 26 to 52 weeks of age (n = 9-13 per group). Joint tissue structure and osteoarthritis pathology were evaluated by histology and micro-computed tomography. Systemic metabolic and inflammatory changes were evaluated by body composition, glucose tolerance testing, and serum biomarkers. SF metabolites were analyzed by high performance-liquid chromatography mass spectrometry. We built correlation-based network models to evaluate the connectivity between systemic and local metabolic biomarkers and osteoarthritis structural pathology within each experimental group.

RESULTS

High-fat diet caused moderate osteoarthritis, including cartilage pathology, synovitis and increased subchondral bone density. In contrast, voluntary exercise had a negligible effect on these joint structure components. 1,412 SF metabolite features were detected, with high-fat sedentary mice being the most distinct. Diet and activity uniquely altered SF metabolites attributed to amino acids, lipids, and steroids. Notably, high-fat diet increased network connections to systemic biomarkers such as interleukin-1β and glucose intolerance. In contrast, exercise increased local joint-level network connections, especially among subchondral bone features and SF metabolites.

CONCLUSION

Network mapping showed that obesity strengthened SF metabolite links to blood glucose and inflammation, whereas exercise strengthened SF metabolite links to subchondral bone structure.

Soluble biological markers in osteoarthritis

In recent years, markers research has focused on the structural components of cartilage matrix. Specifically, a second generation of degradation markers has been developed against type II collagen neoepitopes generated by specific enzymes. A particular effort has been made to measure the degradation of minor collagens III and X of the cartilage matrix. However, because clinical data, including longitudinal controlled studies, are very scarce, it remains unclear whether they will be useful as an alternative to or in combination with current more established collagen biological markers to assess patients with osteoarthritis (OA). In addition, new approaches using high-throughput technologies allowed to detect new types of markers and improve the knowledge about the metabolic changes linked to OA. The relative advances coming from phenotype research are a first attempt to classify the heterogeneity of OA, and several markers could improve the phenotype characterization. These phenotypes could improve the selection of patients in clinical trials limiting the size of the studies by selecting patients with OA characteristics corresponding to the metabolic pathway targeted by the molecules evaluated. In addition, the inclusion of rapid progressors only in clinical trials would facilitate the demonstration of efficacy of the investigative drug to reduce joint degradation. The combination of selective biochemical markers appears as a promising and cost-effective approach to fulfill this unmet clinical need. Among the various potential roles of biomarkers in OA, their ability to monitor drug efficacy is probably one of the most important, in association with clinical and imaging parameters. Biochemical markers have the unique property to detect changes in joint tissue metabolism within a few weeks.

MicroRNA-183 attenuates osteoarthritic pain by inhibiting the TGFα-mediated CCL2/CCR2 signalling axis

AIMS

MicroRNA-183 (miR-183) is known to play important roles in osteoarthritis (OA) pain. The aims of this study were to explore the specific functions of miR-183 in OA pain and to investigate the underlying mechanisms.

METHODS

Clinical samples were collected from patients with OA, and a mouse model of OA pain was constructed by surgically induced destabilization of the medial meniscus (DMM). Reverse transcription quantitative polymerase chain reaction was employed to measure the expression of miR-183, transforming growth factor α (TGFα), C-C motif chemokine ligand 2 (CCL2), proinflammatory cytokines (interleukin (IL)-6, IL-1β, and tumour necrosis factor-α (TNF-α)), and pain-related factors (transient receptor potential vanilloid subtype-1 (TRPV1), voltage-gated sodium 1.3, 1.7, and 1.8 (Nav1.3, Nav1.7, and Nav1.8)). Expression of miR-183 in the dorsal root ganglia (DRG) of mice was evaluated by in situ hybridization. TGFα, CCL2, and C-C chemokine receptor type 2 (CCR2) levels were examined by immunoblot analysis and interaction between miR-183 and TGFα, determined by luciferase reporter assay. The extent of pain in mice was measured using a behavioural assay, and OA severity assessed by Safranin O and Fast Green staining. Immunofluorescent staining was conducted to examine the infiltration of macrophages in mouse DRG.

RESULTS

miR-183 was downregulated in tissue samples from patients and mice with OA. In DMM mice, overexpression of miR-183 inhibited the expression of proinflammatory cytokines (IL-6, IL-1β, TNF-α) and pain-related factors (TRPV1, Nav1.3, Nav1.7, Nav1.8) in DRG. OA pain was relieved by miR-183-mediated inhibition of macrophage infiltration, and dual luciferase reporter assay demonstrated that miR-183 directly targeted TGFα.

CONCLUSION

Our data demonstrate that miR-183 can ameliorate OA pain by inhibiting the TGFα-CCL2/CCR2 signalling axis, providing an excellent therapeutic target for OA treatment. Cite this article: Bone Joint Res 2021;10(8):548-557.

Mass Spectrometry-based Biomarkers for Knee Osteoarthritis: A Systematic Review

Introduction: Knee osteoarthritis (OA) is a joint disease, affecting multiple tissues in the joint. Early detection and intervention may delay OA development and avoid total knee arthroplasty. Specific biomarker profiles for early detection and guiding clinical decision-making of OA have not yet been identified. One technique that can contribute to the finding of this "OA biomarker" is mass spectrometry (MS), which offers the possibility to analyze different molecules in tissues or fluids. Several proteomic, lipidomic, metabolomic and other -omic approaches aim to identify these molecular profiles; however, variation in methods and techniques complicate the finding of promising candidate biomarkers.Areas covered: In this systematic review, we aim to provide an overview of molecules in OA knee patients. Possible biomarkers in several tissue types of OA and non-OA patients, as well as current limitations and possible future suggestions will be discussed.Expert opinion: According to this review, we do not believe one specific biomarker will function as predictive molecule for OA. Likely, a group of molecules will give insight in OA development and possible therapeutic targets. For clinical implementation of MS-analysis in clinical decision-making, standardized procedures, large cohort studies and sharing protocols and data is necessary.

A review of applications of metabolomics in osteoarthritis

Osteoarthritis (OA) represents the most prevalent and disabling arthritis worldwide due to its heterogeneous and progressive articular degradation. However, effective and timely diagnosis and fundamental treatment for this disorder are lacking. Metabolomics, a growing field in life science research in recent years, has the potential to detect many metabolites and thus explains the underlying pathophysiological processes. Hence, new specific metabolic markers and related metabolic pathways can be identified for OA. In this review, we aimed to provide an overview of studies related to the metabolomics of OA in animal models and humans to describe the metabolic changes and related pathways for OA. The present metabolomics studies reveal that the pathogenesis of OA may be significantly related to perturbations of amino acid metabolism. These altered amino acids (e.g., branched-chain amino acids, arginine, and alanine), as well as phospholipids, were identified as potential biomarkers to distinguish patients with OA from healthy individuals.

Metabolomics: A Scoping Review of Its Role as a Tool for Disease Biomarker Discovery in Selected Non-Communicable Diseases

Metabolomics is a branch of ‘omics’ sciences that utilises a couple of analytical tools for the identification of small molecules (metabolites) in a given sample. The overarching goal of metabolomics is to assess these metabolites quantitatively and qualitatively for their diagnostic, therapeutic, and prognostic potentials. Its use in various aspects of life has been documented. We have also published, howbeit in animal models, a few papers where metabolomic approaches were used in the study of metabolic disorders, such as metabolic syndrome, diabetes, and obesity. As the goal of every research is to benefit humankind, the purpose of this review is to provide insights into the applicability of metabolomics in medicine vis-à-vis its role in biomarker discovery for disease diagnosis and management. Here, important biomarkers with proven diagnostic and therapeutic relevance in the management of disease conditions, such as Alzheimer’s disease, dementia, Parkinson’s disease, inborn errors of metabolism (IEM), diabetic retinopathy, and cardiovascular disease, are noted. The paper also discusses a few reasons why most metabolomics-based laboratory discoveries are not readily translated to the clinic and how these could be addressed going forward.

The microbiome mediates epiphyseal bone loss and metabolomic changes after acute joint trauma in mice

OBJECTIVE

To compare the early responses to joint injury in conventional and germ-free mice.

DESIGN

Post-traumatic osteoarthritis (PTOA) was induced using a non-invasive anterior cruciate ligament rupture model in 20-week old germ-free (GF) and conventional C57BL/6 mice. Injury was induced in the left knees of n = 8 GF and n = 10 conventional mice. To examine the effects of injury, n = 5 GF and n = 9 conventional naïve control mice were used. Mice were euthanized 7 days post-injury, followed by synovial fluid recovery for global metabolomic profiling and analysis of epiphyseal trabecular bone by micro-computed tomography (μCT). Global metabolomic profiling assessed metabolic differences in the joint response to injury between GF and conventional mice. Magnitude of trabecular bone volume loss measured using μCT assessed early OA progression in GF and conventional mice.

RESULTS

μCT found that GF mice had significantly less trabecular bone loss compared to conventional mice, indicating that the GF status was protective against early OA changes in bone structure. Global metabolomic profiling showed that conventional mice had greater variability in their metabolic response to injury, and a more distinct joint metabolome compared to their corresponding controls. Furthermore, differences in the response to injury in GF compared to conventional mice were linked to mouse metabolic pathways that regulate inflammation associated with the innate immune system.

CONCLUSIONS

These results suggest that the gut microbiota promote the development of PTOA during the acute phase following joint trauma possibly through the regulation of the innate immune system.

A biolabel research based on metabonomics reveals the therapeutic potentials of Herba Lysimachiae in synovial diseases: The dual effects on synovial platelet aggregation by prostaglandin E1/E2

Previous research has demonstrated that Herba Lysimachiae (HL) exerts the dual effects on platelet aggregation in the synovium, which may contribute to its protection against synovial lesions under different situations. However, the mechanism is unclear. In the present experiment, a biolabel research based on metabonomics was used to mine the information about the intervention of HL on synovium at the metabolite level, which may help to analyze the regulation of HL on synovial platelet aggregation and its possible treatment in synovial diseases. Synovial metabolic profiling was analyzed using a Shimadzu Nexera UHPLC LC-30A system and an AB SCIEX Triple TOF 4600 mass spectrometer. Enzyme-linked immunosorbent assay (ELISA) was used to verify the biolabels analysis results in the healthy and osteoarthritis rats. Totally, thirteen common metabolites were differentially expressed after treating with HL, and implicated in 2 key pathways (arachidonic acid metabolism and glycerophospholipid metabolism). ELISA showed that HL regulated the expression of prostaglandins E1 and E2 in synovial tissues of the healthy and osteoarthritis rats. This study reveals that HL may regulate synovial platelet aggregation through prostaglandin E1/E2. Additionally, HL is suitable for treating synovial diseases, especially osteoarthritis, which may be associated with platelet aggregation, apoptosis, inflammation, angiogenesis, and carcinogenesis processes.

The Research Progress of Exosomes in Osteoarthritis, With Particular Emphasis on the Mediating Roles of miRNAs and lncRNAs

Osteoarthritis (OA) is a kind of degenerative disease, which is caused by many factors such as aging, obesity, strain, trauma, congenital joint abnormalities, joint deformities. Exosomes are mainly derived from the invagination of intracellular lysosomes, which are released into the extracellular matrix after fusion of the outer membrane of multi vesicles with the cell membrane. Exosomes mediate intercellular communication and regulate the biological activity of receptor cells by carrying non-coding RNA, long noncoding RNAs (lncRNAs), microRNAs (miRNAs), proteins and lipids. Evidences show that exosomes are involved in the pathogenesis of OA. In view of the important roles of exosomes in OA, this paper systematically reviewed the roles of exosomes in the pathogenesis of OA, including the roles of exosomes in OA diagnosis, the regulatory mechanisms of exosomes in the pathogenesis, and the intervention roles of exosomes in the treatment of OA. Reviewing the roles of exosomes in OA will help to clarify the pathogenesis of OA and explore new diagnostic biomarkers and therapeutic targets.