Risk factors for osteoarthritis include raised BMI and female gender. Whether these two factors influenced synovial gene expression was investigated using a triangulation and modelling strategy which generated 12 datasets of gene expression in synovial tissue from three knee pathologies with matching BMI groups, obese and overweight, and gender distributions. Intra-operative synovial biopsies were immersed in RNAlater at 4oC before storage at -80oC. Total RNA was extracted using RNAeasy with gDNA removal. Following RT- PCR and quality assessment, cDNA was applied to Affymetrix Clariom D microarray gene chips. Bioinformatics analyses were performed. Linear models were prepared in limma with gender and BMI factors incorporated sequentially for each pathology comparison, generating 12 models of probes differentially expressed at FDR p<0.05 and Bayes number, B>0. Data analysis of differently expressed genes utilized Ingenuity Pathway Analysis and Cytoscape with Cluego and Cytohubba plug-ins.Abstract
Introduction
Methodology
It is increasingly evident that synovium may play a larger role in the aetiology of osteoarthritis. We compared gene expression in whole tissue synovial biopsies from end-stage knee osteoarthritis and knee trauma patients with that of their paired explant cultures to determine how accurately cultured cells represent holistic synovial function. Synovial tissue biopsies were taken from 16 arthroplasty patients and 8 tibial plateau fracture patients with no osteoarthritis. Pairs of whole tissue fragments were either immediately immersed in RNAlater Stabilisation Solution at 4o C before transfer to -80o C storage until RNA extraction; or weighed, minced and cultured at 500mg tissues/5ml media in a humidified incubator at 37oC, 5% CO2. After sub-culturing total RNA was extracted using RNAeasy Plus Mini Kit with gDNA removal. Following RT-PCR and quality assessment, cDNA was applied to Affymetrix Clariom D microarray gene chips. Bioinformatics analyses were performed.Abstract
Introduction
Methodology
Articular cartilage degradation is a defining feature of osteoarthritis. Synovium is a reactive tissue with synovial villae, neoangiogenesis and intimal hyperplasia common to many joint pathologies. The consequences of cartilage debris in osteoarthritis impacting the synovial intima is not well understood. We analysed the immunohistology of synovium from 16 patients with osteoarthritis and 17 patients undergoing knee surgery for non-arthritic pathologies. This data was integrated with imaging and functional scores to correlate synovitis in osteoarthritis. Formalin-fixed paraffin embedded synovial biopsy sections were cut in serial sequence and processed for routine staining (H&E or CD3, CD68, CD20, Vimentin, vWF and PCNA IHC) using standardised Dako monoclonal mouse anti-human antibodies. Digital images scanned at x20 were evaluated for fragments of cartilage and aggregates of inflammatory cells. Clinical data (gender, BMI, KL grade, WOMAC & SF-12 scores) was aligned with histopathological data.Abstract
Introduction
Methodology
Synovitis impacts osteoarthritis symptomatology and progression. The transcription factors controlling synovial gene expression have not been described. This study analyses gene expression in synovium samples from 16 patients with osteoarthritis with 9 undergoing arthroscopic and 8 knee trauma surgery for non-arthritic pathologies. Intra-operative synovial biopsies were immersed in RNAlater at 4oC before storage at -80oC. Total RNA was extracted using RNAeasy. After purification, RT-PCR and quality assessment, cDNA was applied to Affymetrix Clariom D microarray gene chips. Bioinformatics analyses were performed. Linear models were prepared in limma with gender and BMI factors incorporated sequentially for each pathology comparison, generating 12 models of probes differentially expressed at FDR p<0.05 and Bayes number, B>0. Data analysis of differently expressed genes utilized Ingenuity Pathway Analysis and Cytoscape with Cluego and Cytohubba plug-ins.Abstract
Introduction
Methodology
