FRI0355 Microarray Analysis of Early and Late RA Human Synovial Fibroblasts Reveals A Unique Gene Expression Pattern in Early Disease
Authors: M. Juarez, T. Smallie, T. Tang, H. Adams, K. Raza, C.D. Buckley, A. Clark, A. Filer
Journal: Annals of the Rheumatic Diseases (2014)

<h3>Background</h3> Human synovial fibroblasts are implicated in rheumatoid arthritis (RA) pathogenesis at two levels: they promote cartilage and bone destruction and contribute to persistent joint inflammation. Significant damage to RA joints occurs within the first year of disease and thus early aggressive treatment is advocated. Special attention has been given to the "early window of opportunity" in the first 3 months of disease. Despite this, whereas much is known about synovial fibroblasts taken from very late disease at joint replacement, little is known about fibroblast biology in early RA. We hypothesised that by studying synovial fibroblasts from patients in this early window we would identify novel stromal biomarkers and therapeutic targets in very early disease. <h3>Objectives</h3> To describe the gene expression pattern of human synovial fibroblasts from patients with early RA of up to three months symptom duration and compare it to that of synovial fibroblasts from patients with longstanding RA. <h3>Methods</h3> Synovial tissue was obtained from patients with longstanding RA undergoing joint replacement (n=8, mean disease duration 20 years) or patients with synovitis of at least one joint and symptom duration of up to 3 months fulfilling 1987 criteria for RA by 18 months follow-up (n=14) via ultrasound guided synovial biopsy. Normal (n=8) and resolving arthritis (n=16) fibroblasts were used as controls. RNA was extracted and treated with the RNA clean and concentrator kit. Samples were hybridised onto Agilent Sure Print G3 8x60k v2 arrays. Scanned images were analysed with Agilent Feature Extraction Software. Partek Genomics Suite was used to analyse gene expression using a 1-way fixed model ANOVA to create pairwise contrasts with a corrected step-up p-value (False Discovery Rate by Benjamini) and a fold change for differences in gene expression. Age, gender and joint of origin were found to contribute to variance and thus included in the ANOVA model. Antibody status did not contribute to variance of the datasets and was thus excluded. <h3>Results</h3> 73 out of a total of 50,599 probes, detected differentially expressed transcripts between early and late RA (FDR&lt;0.05, fold change ±1.5). Some of the probes denoted protein coding genes whilst others denoted pseudogenes, small nuclear and long non-coding RNAs. To ascertain those genes that were uniquely differentially expressed between early and late RA, normal and resolving samples were compared to late RA samples. In total 13 probes were shared between this analysis and that of early and late RA, leaving 60 probes exclusively differentiating early RA. Of these, 27 were upregulated and 33 downregulated in early RA compared to late RA. Gene ontology revealed that 38.2% of the differentially expressed genes were involved in transcription regulation and 23.5% in RNA metabolic processes. Detailed analysis and validation of differentially expressed targets is ongoing. <h3>Conclusions</h3> We have identified a distinct gene expression pattern in synovial fibroblasts of patients with early RA. By analysing normal and resolving arthritis samples, we have been able to ensure that this pattern is unique to early RA fibroblasts and not due to non-specific joint inflammation. Ongoing in depth analysis and validation of targets will allow unravelling of modifiable disease mechanisms in early RA. <h3>Disclosure of Interest</h3> None declared <h3>DOI</h3> 10.1136/annrheumdis-2014-eular.3703