A6.07 Tissue- and cell-specific transcriptomes indicate systemic nature of ra and revealed combinations of protein biomarkers relevant for disease characterisation in serum

Background and objectives Clinical signs and symptoms, radiographic changes and routine laboratory tests have indispensable roles in diagnosis of rheumatoid arthritis (RA). Nevertheless, a high degree of heterogeneity between RA patients and increasing options of treatment require the identification of objective criteria relevant for diagnosis and therapeutic stratification of patients. This study focused on global approaches in dissecting inflammation in RA including transcriptome analyses of synovial tissue, blood and bone marrow monocytes and proteome analyses of selected molecules in serum from long-lasting and early RA. Materials and methods Gene-expression profiling of synovial tissues, blood and bone marrow monocytes of RA and osteoarthritis (OA) patients were performed by Affymetrix microarrays. Based on transcriptome data, 28 molecules were selected for protein analyses by ELISA and multiplex immunoassays in sera from patients with long-lasting RA (n = 17) and OA (n = 16), early RA (n = 10) and healthy donors (n = 14). Results Transcriptome analyses of synovial tissues from RA and OA patients showed the most prominent differences between these two diseases and identified more than 1000 differentially expressed genes. More subtle differences were disclosed by gene-expression profiling of blood and bone marrow monocytes from RA and OA with 300 and 150 differentially expressed genes, respectively. From RA tissue- and cell-specific transcriptomes 28 genes were selected for protein analyses in serum from RA and OA patients including: chemokines (CXCL13, CCL18), adhesion molecules (VCAM1, ICAM1, E- and P-Selectins), enzymes (MMP3, A1AT), alarmins (S100P and S1008/9) and the soluble form of cell surface molecules (CD14, CD163). Out of 28 markers only 16 reached statistical significance to discriminate long-lasting RA from OA. A combination of 5 markers was able to correctly classify long-lasting RA. However, the same combination of markers identified only one-third of early RA patients. Conclusions Tissue- and cell-specific transcriptomes demonstrated the systemic nature of RA. Proteome analyses of serum from long-lasting RA patients confirmed transcriptome data and showed that molecular patterns determined by the combination of inflammatory and cell-specific markers are required for disease stratification. In early RA transcriptome data outperformed proteome data suggesting that focus on transcriptional alterations is more sensitive approach for disease management of early RA.