SAT0003 ELEVATED BASELINE AND INCREASING AUTOANTIBODY LEVELS ARE ASSOCIATED WITH INCREASED RISK FOR IMMINENT ONSET OF INFLAMMATORY ARTHRITIS IN A PROSPECTIVELY STUDIED ANTI-CITRULLINATED PROTEIN ANTIBODY POSITIVE COHORT: THE TIP-RA COLLECTIVE
Authors: K. Deane, G. Firestein, D. Boyle, J. Buckner, E. A. James, S. Posso, W. Robinson, L. K. Moss, J. Seifert, R. Gilmore, S. Barzideh, N. Rao, F. Baribaud, S. Nagpal, A. Johnsen, V. M. Holers
Journal: Annals of the Rheumatic Diseases (2020)

Background: The Targeting Immune Responses for Prevention of RA (TIP-RA) Collaborative prospectively studies individuals at high risk for developing RA because of serum ACPA positivity in absence of baseline inflammatory arthritis (IA). Objectives: The objective of the analyses presented herein is to evaluate the role of baseline and changing levels of ACPA and rheumatoid factor (RF) in relationship to incident IA/RA. Methods: ACPA+ subjects and ACPA- controls were identified who did not have baseline historical or examination evidence of IA. ACPA+ was defined by serum elevation of anti-CCP3 ≥20 units (Inova). Subjects were evaluated annually or sooner if they had changes in joint symptoms. Factors including RFIgM and RFIgA (Inova) were also assessed, and relationships between autoantibody levels at baseline and over time and incident IA/RA were evaluated using t-tests, with paired testing where applicable. Results: Baseline characteristics of ACPA+ and ACPA- subjects are in Table 1. Sixteen of the 94 (17%) ACPA+ subjects developed IA/RA a mean of 518 days from the baseline visit; 14 of these met 2010 ACR/EULAR criteria for RA at the time of detection of IA. There was a trend for ACPA+ subjects who later developed IA/RA to have higher baseline levels of anti-CCP3 compared to those who did not develop IA/RA (Table 2). In addition, those who developed IA/RA had significantly higher mean levels of RFIgM and RFIgA compared to those who did not. While not statistically significant, in longitudinal analyses in the ACPA+ subjects with incident IA/RA, anti-CCP3 levels increased from baseline to identification of IA (mean [SD] of 119 [102] to 126 [100], p=0.42). Furthermore, RFIgM levels increased from 36 [49] at baseline to 43 [51] at the time of IA (p=0.31), and RFIgA levels increased from 16 [29] to 21 [31] (p=0.10). In contrast, in ACPA+ subjects who did not develop IA/RA, anti-CCP3 levels increased only slightly over follow-up of a mean of 712 days: 75 [75] to 80 [76], p=0.70 while the levels of RFIgM and RFIgA decreased slightly during the same follow-up: for RFIgM mean [SD] levels went from 9 [22] to 8 [19], p=0.74; for RFIgA, 5 [16] to 3 [12], p=0.67. Table 1. Baseline characteristics of ACPA+/- subjects ACPA-(n=162 ) ACPA+(n=94 ) p-value Age, mean 58 58 0.90 % Female 69 68 0.67 % Ever smoker 33 34 0.87 RF-IgM, mean (SD) 3.2 (10.0) 13.5 (30.2) &lt;0.01 RF-IgA, mean (SD) 0.3 (0.6) 6.5 (19.1) &lt;0.01 Table 2. Baseline characteristics of 16 ACPA+ subjects who developed incident IA/RA vs. 78 ACPA+ who did not Did not develop IA/RA (n=78) Developed IA/RA (n=16) p-value Days from baseline to IA/RA or follow-up, mean (SD) 712 (124) 518 (295) – % Meeting 2010 criteria at time of IA - 88 – CCP3, mean (SD) 74.5 (75.3) 119.1 (102.1) 0.05 RFIgM, mean (SD) 9 (22) 36 (49) &lt;0.01 RFIgA, mean (SD) 4 (16) 16 (29) 0.03 Conclusion: In this prospectively followed cohort of ACPA+ subjects, higher levels of RFIgM and RFIgA at baseline were significantly associated with development of IA/RA within the follow-up period. Furthermore, there was a trend for rising levels of anti-CCP3 and RFIgM and A to be associated with development of IA/RA. These finding support the use of higher and/or rising levels of autoantibodies as additional features to predict imminent onset of IA/RA in ACPA+ individuals as well as potentially to use as outcomes of success of preventive interventions. Furthermore, the trend of increasing levels of RFIgM and RFIgA over time in individuals who developed IA/RA suggests that targeting pathways of RF development may lead to preventive interventions in a subset of RA. References: None Disclosure of Interests: Kevin Deane Grant/research support from: Janssen, Consultant of: Inova, ThermoFisher, Janseen, BMS and Microdrop, Gary Firestein Grant/research support from: Lilly, Janssen, Abbvie, David Boyle: None declared, Jane Buckner Grant/research support from: Bristol-Myers Squibb, Janssen, Eddie A. James Grant/research support from: Janssen, Pfizer, Sanofi, Novartis, Sylvia Posso Grant/research support from: Janssen, William Robinson Grant/research support from: Janssen, Laurie K. Moss Grant/research support from: Janssen, Jennifer Seifert Grant/research support from: Janssen, Roger Gilmore Grant/research support from: Janssen, Saman Barzideh Grant/research support from: Janssen, Navin Rao Shareholder of: Janssen Pharmaceuticals, Employee of: Janssen Pharmaceuticals, Frederic Baribaud Shareholder of: Janssen Research &amp; Development, LLC, Employee of: Janssen Research &amp; Development, LLC, Sunil Nagpal Shareholder of: Janssen Pharmaceuticals, Employee of: Janssen Pharmaceuticals, Alyssa Johnsen Employee of: Janssen, V. Michael Holers Grant/research support from: Janssen, Celgene, and BMS