Dataset Information

Multi-Omic Temporal Landscape of Plasma and Synovial Fluid-Derived Extracellular Vesicles Using an Experimental Model of Equine Osteoarthritis.

ABSTRACT: Extracellular vesicles (EVs) contribute to osteoarthritis pathogenesis through their release into joint tissues and synovial fluid. Synovial fluid-derived EVs have the potential to be direct biomarkers in the causal pathway of disease but also enable understanding of their role in disease progression. Utilizing a temporal model of osteoarthritis, we defined the changes in matched synovial fluid and plasma-derived EV small non-coding RNA and protein cargo using sequencing and mass spectrometry. Data exploration included time series clustering, factor analysis and gene enrichment interrogation. Chondrocyte signalling was analysed using luciferase-based transcription factor activity assays. EV protein cargo appears to be more important during osteoarthritis progression than small non-coding RNAs. Cluster analysis revealed plasma-EVs represented a time-dependent response to osteoarthritis induction associated with supramolecular complexes. Clusters for synovial fluid-derived EVs were associated with initial osteoarthritis response and represented immune/inflammatory pathways. Factor analysis for plasma-derived EVs correlated with day post-induction and were primarily composed of proteins modulating lipid metabolism. Synovial fluid-derived EVs factors represented intermediate filament and supramolecular complexes reflecting tissue repair. There was a significant interaction between time and osteoarthritis for CRE, NFkB, SRE, SRF with a trend for osteoarthritis synovial fluid-derived EVs at later time points to have a more pronounced effect.

SUBMITTER: Anderson JR

PROVIDER: S-EPMC10573509 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Multi-Omic Temporal Landscape of Plasma and Synovial Fluid-Derived Extracellular Vesicles Using an Experimental Model of Equine Osteoarthritis.

Anderson James R JR Johnson Emily E Jenkins Rosalind R Jacobsen Stine S Green Daniel D Walters Marie M Bundgaard Louise L Hausmans Bas A C BAC van den Akker Guus G Welting Tim J M TJM Chabronova Alzbeta A Kharaz Yalda A YA Clarke Emily J EJ James Victoria V Peffers Mandy J MJ

International journal of molecular sciences 20231004 19

Extracellular vesicles (EVs) contribute to osteoarthritis pathogenesis through their release into joint tissues and synovial fluid. Synovial fluid-derived EVs have the potential to be direct biomarkers in the causal pathway of disease but also enable understanding of their role in disease progression. Utilizing a temporal model of osteoarthritis, we defined the changes in matched synovial fluid and plasma-derived EV small non-coding RNA and protein cargo using sequencing and mass spectrometry. D ...[more]

PMID: 37834337

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Project description:Osteoarthritis causes progressive joint deterioration, severe morbidity, and reduced mobility in both humans and horses. Currently, osteoarthritis is diagnosed at late stages through clinical examination and radiographic imaging, hence it is challenging to address and provide timely therapeutic interventions to slow disease progression or ameliorate symptoms. Extracellular vesicles are cell-derived vesicles that play a key role in cell-to-cell communication and are potential sources for specific composite biomarker panel discovery. We here used a multi-omics strategy combining proteomics and phospholipidomics in an integral approach to identify composite biomarkers associated to purified extracellular vesicles from synovial fluid of healthy, mildly and severely osteoarthritic equine joints. Although the number of extracellular vesicles was unaffected by osteoarthritis, proteome profiling of extracellular vesicles by mass spectrometry identified 40 differentially expressed proteins (non-adjusted p < 0.05) in osteoarthritic joints associated with 7 significant canonical pathways in osteoarthritis. Moreover, pathway analysis unveiled changes in disease and molecular functions during osteoarthritis development. Phospholipidome profiling by mass spectrometry showed a relative increase in sphingomyelin and a decrease in phosphatidylcholine, phosphatidylinositol, and phosphatidylserine in extracellular vesicles derived from osteoarthritic joints compared to healthy joints. Unsupervised data integration revealed positive correlations between the proteome and the phospholipidome. Comprehensive analysis showed that some phospholipids and their related proteins increased as the severity of osteoarthritis progressed, while others decreased or remained stable. Altogether our data show interrelationships between synovial fluid extracellular vesicle-associated phospholipids and proteins responding to osteoarthritis pathology and which could be explored as potential composite diagnostic biomarkers of disease.

Project description:BackgroundOsteoarthritis remains one of the greatest causes of morbidity and mortality in the equine population. The inability to detect pre-clinical changes in osteoarthritis has been a significant impediment to the development of effective therapies against this disease. Synovial fluid represents a potential source of disease-specific small non-coding RNAs (sncRNAs) that could aid in the understanding of the pathogenesis of osteoarthritis. We hypothesised that early stages of osteoarthritis would alter the expression of sncRNAs, facilitating the understanding of the underlying pathogenesis and potentially provide early biomarkers.MethodsSmall RNA sequencing was performed using synovial fluid from the metacarpophalangeal joints of both control and early osteoarthritic horses. A group of differentially expressed sncRNAs was selected for further validation through qRT-PCR using an independent cohort of synovial fluid samples from control and early osteoarthritic horses. Bioinformatic analysis was performed in order to identify putative targets of the differentially expressed microRNAs and to explore potential associations with specific biological processes.ResultsResults revealed 22 differentially expressed sncRNAs including 13 microRNAs; miR-10a, miR-223, let7a, miR-99a, miR-23b, miR-378, miR-143 (and six novel microRNAs), four small nuclear RNAs; U2, U5, U11, U12, three small nucleolar RNAs; U13, snoR38, snord96, and one small cajal body-specific RNA; scarna3. Five sncRNAs were validated; miR-223 was significantly reduced in early osteoarthritis and miR-23b, let-7a-2, snord96A and snord13 were significantly upregulated. Significant cellular actions deduced by the differentially expressed microRNAs included apoptosis (P < 0.0003), necrosis (P < 0.0009), autophagy (P < 0.0007) and inflammation (P < 0.00001). A conservatively filtered list of 57 messenger RNA targets was obtained; the top biological processes associated were regulation of cell population proliferation (P < 0.000001), cellular response to chemical stimulus (P < 0.000001) and cell surface receptor signalling pathway (P < 0.000001).ConclusionsSynovial fluid sncRNAs may be used as molecular biomarkers for early disease in equine osteoarthritic joints. The biological processes they regulate may play an important role in understanding early osteoarthritis pathogenesis. Characterising these dynamic molecular changes could provide novel insights on the process and mechanism of early osteoarthritis development and is critical for the development of new therapeutic approaches.

Dataset Information

Multi-Omic Temporal Landscape of Plasma and Synovial Fluid-Derived Extracellular Vesicles Using an Experimental Model of Equine Osteoarthritis.

Publications

Multi-Omic Temporal Landscape of Plasma and Synovial Fluid-Derived Extracellular Vesicles Using an Experimental Model of Equine Osteoarthritis.

Similar Datasets

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