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Background No single biomarker has yet been able to predict disease course in patients with rheumatoid arthritis (RA). However combinations of biomarkers and changes therein early during treatment may be predictive of later treatment response. Objectives Investigate correlations between early changes (Δ) in the validated multi-biomarker disease activity (MBDA) score and Δ in disease activity measurements – Disease Activity Score (DAS28-CRP), Clinical Disease Activity Index (CDAI), Simplified Disease Activity Index (SDAI) and C-reactive protein (CRP) – in early RA patients (the OPERA cohort). Methods In the randomized double-blinded OPERA trial, 180 treatment-naive patients were randomized to an adalimumab (ADA) group (oral methotrexate (MTX) in combination with ADA) or a placebo group (oral MTX and placebo-ADA). Intra-articular glucocorticoids were also injected into swollen joints (1). DAS28-CRP, CDAI, SDAI, and CRP were measured at baseline (BL) and at 3, 6 and 12 months. MBDA score, calculated based on serum concentrations of CRP, interleukin-6, chitinase-3-like protein 1, vascular endothelial growth factor A, matrix metalloproteinase 1 and 3, vascular cell adhesion molecule 1, epidermal growth factor, tumor necrosis factor receptor type I, serum amyloid A, leptin and resistin, with a range of 1–100, was determined retrospectively at the same time points on banked serum samples (2). Correlations between ΔMBDA scores and Δ disease activity measurements were analyzed by Spearman9s correlation coefficient. Results Patients had a median age of 55.2 (range: 18.7–86) years, disease duration of 84 (range: 42–214) days; 66% were female; 72% and 65% were RF and anti-CCP positive, respectively. At BL, median DAS28-CRP was 5.6 (3.3–8.6) and median MBDA score was 59 (12–90). MBDA scores were low ( 44) in 147 (82%) patients. There were no statistically significant correlations between BL MBDA score and other disease activity measurements at 3 or 6 months in the placebo or ADA groups. Median ΔMBDA scores from BL to 3 months (ΔMBDA score 0–3m ) and to 6 months (ΔMBDA score 0–6m ) were -16.5 and -20, respectively. Median ΔDAS28-CRP from BL to 6 months (ΔDAS28-CRP 0–6m ) and to 12 months (ΔDAS28-CRP 0–12m ) were -2.9 and -3.2, respectively. ΔMBDA score 0–3m and ΔDAS28-CRP 0–6m were significantly correlated in the placebo and ADA groups, as were ΔMBDA score 0–6m and ΔDAS28-CRP 0–12m . ΔMBDA score 0–3m also significantly correlated with ΔDAS28-CRP, ΔCDAI, ΔSDAI and ΔCRP from BL to 6 months and from BL to 12 months (Table 1). Conclusions In patients with early RA from the OPERA cohort, ΔMBDA score from BL to 3 or 6 months were correlated with longer-term ΔDAS28-CRP, ΔCDAI, ΔSDAI and ΔCRP. Correlations were generally similar between treatment groups. References Horslev-Petersen K, et al., Ann Rheum Dis 2014; 73:654–661 Hirata et al. Current Biomarker Findings 2015, 5:69–78 Disclosure of Interest C. H. Brahe: None declared, M. Ostergaard Grant/research support from: Abbvie, BMS, Boehringer-Ingelheim, Eli Lilly, Janssen, Merck, Pfizer, Roche, UCB, Celgene, Sanofi, Regeneron, Novartis, T.Jensen, J. Johansen: None declared, N. Defranoux: None declared, C.-C. Hwang: None declared, R. Bolce: None declared, E. Sasso: None declared, K. Horslev-Petersen: None declared, K. Steengaard-Pedersen Grant/research support from: Meda, Abbvie, Roche, Speakers bureau: UCB, Pfizer, P. Junker: None declared, T. Ellingsen: None declared, P. Ahlquist: None declared, H. Lindegaard Grant/research support from: Boehringer Ingelheim, A. Linauskas: None declared, A. Schlemmer Grant/research support from: Abbvie, Roche, MSD, M. Dam: None declared, I. Hansen: None declared, T. Lottenburger: None declared, C. Ammitzboll: None declared, A. Jorgensen: None declared, S. Krintel: None declared, J. Raun: None declared, M. Hetland: None declared

Background Response to anti-TNF therapy is highly variable in patients with rheumatoid arthritis (RA). Predictors of treatment response have been identified, but their ability to predict response in individual patients is poor (1). MicroRNAs (miRNAs) have been suggested to influence susceptibility to RA and disease severity (2). Objectives To identify predictive miRNAs associated with treatment response in 180 patients with RA (disease duration Methods Patients received methotrexate 7.5 mg weekly (increased to 20 mg/week within two months) in combination with adalimumab (n=89)/placebo-adalimumab (n=91) 40 mg subcutaneously every other week. If swollen joints were present, they were injected with triamcinolone. Treatment response after 1 year was assessed according to EULAR response (good vs. moderate/poor), DAS28(CRP) remission, and ACR/EULAR Boolean remission criteria. MiRNAs were purified from pretreatment whole blood. Expressions of miRNAs were determined using TaqMan® Human MicroRNA LDA, A Card v2.0 (Applied Biosystems). Raw Cycle threshold (Ct) values of each miRNA were pre-processed using quantile normalization. Interaction between miRNAs and treatment was tested for each miRNA, and potential predictive miRNAs (p-values Results In the adalimumab-group/placebo-group 82%/74% achieved EULAR good response, 74%/49% achieved DAS28(CRP) remission, and 48%/30% EULAR/ACR Boolean remission. After backwards elimination a low expression of miR-22 in the adalimumab group was associated with response using EULAR response (OR: 12.18, 95% CI: 2.30-140.45, p=0.01) and DAS28(CRP) remission (OR: 44.74, 95% CI: 5.99-736.18, p=0.001) as outcome parameters. Similarly, high expressions of miR-23b (OR: 0.48, 95% CI: 0.24-0.86, p=0.03) and miR-758 (OR: 0.20, 95% CI: 0.03-0.86, p=0.05) in the adalimumab group were associated with response using DAS28(CRP) remission as outcome parameter. A high expression of miR-629 in the adalimumab group (OR: 0.45, 95% CI: 0.23-0.82, p=0.01) was associated with response using ACR/EULAR remission. Conclusions We identified several miRNAs in whole blood from patients with early RA associated with treatment response to adalimumab. Validation studies are needed to assess the utility of these miRNAs as predictive biomarkers in patients with RA. References Prajapati R et al. Pharmacogenomics 2011;12:1571-85. Trenkmann M et al. Clin Rev Allergy Immunol 2010;39:10-9. Horslev-Petersen K et al. Arthritis Rheum 2011; 63 (Supplement 10): 394. Disclosure of Interest S. B. Krintel: None Declared, C. Dehlendorff: None Declared, M. Hetland: None Declared, K. Horslev-Petersen: None Declared, K. Andersen: None Declared, P. Junker: None Declared, J. Podenphant: None Declared, T. Ellingsen: None Declared, P. Ahlqvist: None Declared, H. Lindegaard Consultant for: MSD, Merck, Roche, A. Linauskas: None Declared, A. Schlemmer: None Declared, M. Dam: None Declared, I. Hansen: None Declared, H. C. Horn: None Declared, A. Jorgensen: None Declared, J. Raun: None Declared, C. Ammitzboll: None Declared, M. Ostergaard: None Declared, K. Stengaard-Pedersen: None Declared, J. Johansen: None Declared