AB0122 THE NORA PROJECT - PREDICTION OF THERAPY RESPONSE IN RHEUMATOID ARTHRITIS
Authors: L. Mathsson-Alm, I. Gehring, M. Poorafshar, J. Rönnelid, J. Askling, E. Haavardsholm, H. Berner Hammer
Journal: Annals of the Rheumatic Diseases (2021)

Background: Personalized medicine in Rheumatoid arthritis (RA) especially regarding therapy response is still in early stages. The Nordic RA (NORA) project is aiming to improve the prediction of therapy outcome by combining established serologic marker with new markers, genetic information and patient-derived data. Objectives: As an initial step in the project the aim was to select clinically characterized patient cohorts and evaluate if changes or patterns in serological markers could predict therapy response and/or disease progress. Methods: The ARCTIC ( A iming for R emission in rheumatoid arthritis: a randomised trial examining the benefit of ultrasound in a C linical TI ght C ontrol regimen) study [1] was designed to compare two tight control treatment strategies for early Rheumatoid arthritis and was used as a first cohort. Plasma samples (n=1622) from 224 RA patients from the ARCTIC study were included and taken at baseline and 3, 4, 6, 8, 10, 12, 14, 16, 20, and 24 months from trial start, and analyzed for the presence of EliA TM RF (IgM, IgA, IgG), anti-CCP (IgG, IgA) and anti-RA33 (IgM, IgA, IgG) autoantibodies, as well as Calprotectin using the EliA instrument platform (Phadia AB, Uppsala, Sweden). In addition, a custom-made multiplex chip (Thermo Fisher Scientific, Sweden) [2] was used for measurement of anti-IgG antibodies against RA-specific antigens (citrullinated, acetylated and carbamylated), and established CTD-markers (Connective Tissue Disease), e.g. Ro52/60 and dsDNA. The citrullinated peptides on the multiplex chip were both multiple as well as single citrullinated at different positions within the peptide sequence. Additionally, we included an ELISA to measure antibodies against native human collagen II [3]. Results: The different single assays in the baseline samples varied between 7 – 80% positive test results, e.g. anti-CCP IgG 80%. For some patients we could see changes in levels for anti-CCP, RF and anti-RA33 in the follow up samples, which varied from negative to more than 3-10xULN (Upper Limit of Normal). For anti-CCP IgG we found 9 patients (4%), who changed from negative to positive (patient 1-5) or from positive to negative (patient 6-8), while patient 9 had a peak at visit 6 (=12 months) and declined afterwards (figure 1). In addition, the above mentioned 9 patients showed clear changes in signal strength for the markers included on the multiplex chip and followed a similar pattern as the anti-CCP IgG signal. Different antibody patterns against single citrullinated peptides were observed and number of ACPA-positive peptides correlated with IgG anti-CCP levels. Figure 1. Anti-CCP IgG value normalised to cutoff (blue line) for patient 1 to 9. The heatmap visualizes the change over time in anti-CCP IgG signal with dark blue showing negative results and orange/red showing results &gt;5xULN. Anti-Collagen II antibodies (anti-CII) were detected in 15% of the baseline samples and in most cases declined over time. Two patients showed low baseline anti-CII levels that increased in the follow up samples. The changes in serological markers and the different reactivity patterns could possibly correlate with clinical outcome and define subgroups of patients with different response to therapy. Results could be repeated in RA patients from the NOR-VEAC [4] cohort. At baseline 73% of the 106 RA patients had a positive anti-CCP IgG result and 11 patients (10%) showed a significant change of anti-CCP IgG level over time. Conclusion: Different response patterns and changes in serological antibody levels over the first 24 months after RA diagnosis could possibly reveal subgroups of patients with different prognosis and response to treatment. Further evaluations in additional treatment cohorts and correlation with clinical data are ongoing. References: [1]Haavardsholm et al., BMJ 2016;354:i4205. [2]Hansson et al. Arthritis Research &amp; Therapy 2012, 14:R201. [3]Manivel et al Ann Rheum Dis. 2017 Sep;76(9):1529-1536. [4]Mjaavatten et al., Arthritis Research &amp; Therapy 2009, 11 :R146. Acknowledgements: The NORA project is a NordForsk funded project. Disclosure of Interests: Linda Mathsson-Alm Employee of: Employee of Thermo Fisher Scientific, Isabel Gehring Employee of: Employee of Thermo Fisher Scientific, Maryam Poorafshar Employee of: Employee of Thermo Fisher Scientific, Johan Rönnelid: None declared, Johan Askling Grant/research support from: Research grants from Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB, mainly in the context of safety monitoring (ARTIS), Espen Haavardsholm: None declared, Hilde Berner Hammer: None declared