Osteoarthritis (OA) is a chronic, degenerative condition of articular joints. The prevalence of OA is high in many mammalian populations, though our understanding of the disease is limited, with the initiating factors and the early phenotype of the disease being poorly characterised. Clinically, the early-stage of OA is rarely identified, precluding the identification and treatment of affected individuals. Consequently, in vitro models of OA typically reflect the later stages of the disease, and are rarely validated against the naturally-occurring disease. This project utilised tissue from a naturally-occurring canine disease (medial coronoid process disease) to characterise the transcriptome of early-stage OA, and inform different in vitro models, to try and refine the model conditions. Medial coronoid processes from affected dogs were removed and graded histologically, both manually and through the development of a semi-automated assessment. Early-stage OA was characterised by a decrease in the chondrocyte density, an increase in the thickness of the articular cartilage and a loss of proteoglycan. No histological changes in bone morphology were noted in early-stage OA. A transcriptomic approach was adopted, in which the transcriptome of earlystage canine OA was assessed in the coronoid process samples. The canine data generated were meta-analysed alongside published datasets from in vivo models of early-stage OA. These data were from rodent models of the disease. A panel of genes were identified as being associated with the early stage of the disease across multiple datasets. By immunoassay, synovial fluid was screened for pro-inflammatory cytokines and in affected canine joints, interleukin 8 was found to be increased. Three in vitro models (cytokine stimulation of monolayer cell cultures, cyclic compression of agarose embedded cells and impact loading of osteochondral cores) were refined through modification of their stimuli. An identified panel of differentially expressed genes were used to screen each model under different parameters. Hierarchical clustering analysis was used to cluster the panel of conditions so that those which most closely reflected the naturally occurring disease were selected for more detailed transcriptomic analysis by microarray. Chondrocytes and osteoblasts were stimulated with a range of cytokine conditions, using IL-1β and IL-8 based on use in the literature and immunoassay findings. Monolayers were stimulated for a range of times and conentrations with either a single stimulus or multiple cytokines in the medium. The cells responded differently to the cytokine stimulus, requiring different stimuli to most closely replicate the transcriptomic profile of the natural disease. Microarray profiling revealed that cytokine stimulation enriched genes associated with the extracellular matrix and the extracellular region in both cells types. For the cyclic compression model, cells were embedded in an agarose gel matrix and cyclically compressed for various time periods followed by various incubation periods after compression. Both chondrocytes and osteoblasts responded in a similar manner to the cyclic compression stimulus when a post loading incubation step was included to replicate the transcriptomic profile of the natural disease. Cyclic compression enriched gene clusters associated with response to oxidative stress and the extracellular matrix When osteochondral cores were harvested from joints and impacted to represent a traumatic injury, the model could not replicate the transcriptomic model of the natural disease, although increased sGAG release nitric oxide (NO) production was observed. Degradation of mRNA in both tissues was a feature of this model regardless of the loading condition, which precluded further analysis by microarray, but highlighted the significant limitations that were associated with this model. None of the three models tested could accurately reflect the transcriptomic changes of the early-stage OA phenotype in cartilage or bone. A unified model, combining cytokine stimulation with cyclic compression drove cells towards the diseased phenotype in bone. Inflammatory pathways were activated as well as the proteases MMP3 and MMP13. However, chondrocytes were seemingly unresponsive to the multifactorial model, and this will require further analysis. The chronic nature of OA makes it difficult to match in vitro models to the transcriptomic phenotype identified in naturally occurring OA, particularly with respect to the differential expression of structural genes which were identified in the naturally occurring disease but not the models. This work highlights the limitations of existing models, but proposes a validation process which can be used to direct invitro models towards the naturally occurring phenotype.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:735732 |
| Date | January 2017 |
| Creators | Johnson, Craig I. |
| Contributors | Clements, Dylan ; Argyle, David |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/28699 |
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