THU0033 ALTERATIONS IN THE PHENOTYPIC LANDSCAPE AND SPECIFICITY OF CD4+ T CELLS IN CCP+ AT RISK SUBJECTS BEFORE THE ONSET OF RHEUMATOID ARTHRITIS. (2nd June 2020)

• Record Type: Journal Article
• Authors: Rims, C.; Muir, V.; Deane, K.; Nagpal, S.; Rao, N.; Baribaud, F.; Vratsanos, G.; Holers, V. M.; Linsley, P.; James, E. A.; Buckner, J.
• Is Part Of: Annals of the rheumatic diseases. Volume 79(2020)Supplement 1
• Page Start: 230
• Page End: 230
• Publication Date: 2020-06-02
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2020-eular.1918
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: The "Targeting Immune Responses for Prevention of RA" (TIP-RA) collaboration studies individuals at high risk for developing rheumatoid arthritis (RA) because of serum anti-citrullinated protein antibody (ACPA) positivity in absence of arthritis at baseline, and is focused on defining how they transition from at-risk to classifiable disease. One potential mechanism is the expansion of antigen specific T cells that recognize self-antigens and acquisition of disease associated T cell phenotypes. ACPA emerge years prior to clinically apparent disease and subsequently increase in their titer and breadth of specificity. However, few studies have characterized T cells during this transition. Objectives: To identify features associated with progression to RA by examining the specificity and surface phenotype of CD4+ T cells in individuals from the TIP-RA cohort by HLA class II tetramer staining and multi-parameter flow cytometry. Methods: Tetramer staining and flow cytometry were performed on peripheral blood samples from a baseline visit from CCP3- controls (n=34), CCP3+ at-risk (n=26), CCP3+ positive individuals who transitioned in the near-term to RA (called "RA converters", n=4), and seropositive early-RA (n=21). Our staining panel allowed us to measure the frequencies of T cells specific for citrullinated alpha-enolase, aggrecan, cartilage intermediate layer protein (CILP), fibrinogen and vimentin. We then applied both supervised phenotyping and a cluster-based computational approach to compare the phenotypic landscape and specificity of antigen specific and total CD4+ T cells in each cohort. Results: We observed higher overall frequencies of T cells that recognize citrullinated epitopes in CCP3+ at-risk subjects than CCP- controls (p< 0.05). Among the individual specificities, elevated frequencies prior to disease onset were most prominent for CILP specific T cells. Supervised phenotypic analysis revealed an increase in CCR4+ CD4+ T cells in CCP3+ at risk subjects (p< 0.001) and a corresponding decrease in CXCR3+ CD4+ T cells that was most pronounced in RA converters and seropositive early-RA (p< 0.05). Cluster-based phenotypic analysis defined ten distinct phenotypic states present within all subjects. Each of these ten immunotypes contained T cells that recognize citrullinated epitopes. However, the predominant immunotype varied for different antigens. During progression, the frequencies of Ag specific T cells diminished when onset was imminent, but rebounded shortly after diagnosis. Concomitantly, Ag specific T cells with memory phenotypes were diminished, but subsequently reverted to TSCM, Th1, and Th1-17 like phenotypes. Conclusion: Our data show that disease associated changes in the antigen specificity of CD4+ T cells are present in CCP3+ at-risk subjects. Furthermore, the number of antigen specific T cells and their phenotype are perturbed before the onset of symptoms and development of classified RA. These findings support a continuum of immunologic changes that underlie risk and drive disease, motivating new approaches for early intervention. Acknowledgments: We gratefully acknowledge the Targeting Immune Responses for Prevention of Rheumatoid Arthritis (TIP-RA) for designing and executing this collaborative study Disclosure of Interests: Cliff Rims: None declared, Virginia Muir: None declared, Kevin Deane Grant/research support from: Janssen, Consultant of: Inova, ThermoFisher, Janseen, BMS and Microdrop, Sunil Nagpal Shareholder of: Janssen Pharmaceuticals, Employee of: Janssen Pharmaceuticals, Navin Rao Shareholder of: Janssen Pharmaceuticals, Employee of: Janssen Pharmaceuticals, Frederic Baribaud Shareholder of: Janssen Research & Development, LLC, Employee of: Janssen Research & Development, LLC, George Vratsanos Shareholder of: Janssen Pharmaceuticals, Employee of: Janssen Pharmaceuticals, V. Michael Holers Grant/research support from: Janssen, Celgene, and BMS, Peter Linsley Consultant of: BMS, Eddie A. James Grant/research support from: Janssen, Pfizer, Sanofi, Novartis, Jane Buckner Grant/research support from: Bristol-Myers Squibb, Janssen