Periodic Reporting for period 4 - RACE (Rheumatoid Arthritis Caught Early: investigating biological mechanisms preceding chronification of joint inflammation to identify patients prior to presentation of classic chronic arthritis)
Período documentado: 2022-04-01 hasta 2024-03-31
Overall aim.
Rheumatoid Arthritis (RA) causes long lasting disability. At the time of clinically evident arthritis and diagnosis, the disease is already persisting, requiring long-term suppressive treatment. The overarching aim is to prevent chronic arthritis and RA by inhibiting the evolving auto-immune response in a pre-arthritis phase. To achieve this ultimate aim, patients who will develop RA should be accurately recognized in the at-risk stage of clinically suspect arthralgia (CSA). Currently, identification of RA-patients before the classic presentation with clinically evident chronic arthritis is beyond the state of the art. This project therefore aimed to achieve this early recognition.
Impact for society.
The ability to identify patients with imminent RA in a disease phase in which chronicity is not yet established allows very early intervention and the ability to prevent the development of chronic RA. At present RA is an important cause of functional loss, work loss and associated with high costs for society by the long-term use of expensive treatment (biologics). Prevention of disease chronicity will likely reduce the level of RA-related work loss and prevent or diminish the long term need of expensive therapies.
The project.
The project will study RA-specific auto-immune responses at the cellular and humoral level as well as markers reflecting local and systemic inflammation. Serial data collected over time will be combined to reveal interactions between markers and time relationships. Additionally a prediction model identifying imminent RA will be developed. This project is based on recent work on progression from Clinically Suspect Arthralgia (CSA; the symptomatic phase preceding clinical arthritis) clinical arthritis and RA.
Rheumatoid Arthritis (RA) causes long lasting disability. At the time of clinically evident arthritis and diagnosis, the disease is already persisting, requiring long-term suppressive treatment. The overarching aim is to prevent chronic arthritis and RA by inhibiting the evolving auto-immune response in a pre-arthritis phase. To achieve this ultimate aim, patients who will develop RA should be accurately recognized in the at-risk stage of clinically suspect arthralgia (CSA). Currently, identification of RA-patients before the classic presentation with clinically evident chronic arthritis is beyond the state of the art. This project therefore aimed to achieve this early recognition.
Impact for society.
The ability to identify patients with imminent RA in a disease phase in which chronicity is not yet established allows very early intervention and the ability to prevent the development of chronic RA. At present RA is an important cause of functional loss, work loss and associated with high costs for society by the long-term use of expensive treatment (biologics). Prevention of disease chronicity will likely reduce the level of RA-related work loss and prevent or diminish the long term need of expensive therapies.
The project.
The project will study RA-specific auto-immune responses at the cellular and humoral level as well as markers reflecting local and systemic inflammation. Serial data collected over time will be combined to reveal interactions between markers and time relationships. Additionally a prediction model identifying imminent RA will be developed. This project is based on recent work on progression from Clinically Suspect Arthralgia (CSA; the symptomatic phase preceding clinical arthritis) clinical arthritis and RA.
During this project, worldwide the largest Clinically Suspect Arthralgia (CSA) cohort has been established; it now includes >900 patients with CSA that are longitudinally followed on the development of rheumatoid arthritis (RA). Using clinical, serological and imaging data several novel discoveries were made. Novel autoantibody characteristics were studied, among which aberrant ACPA-F(ab)glycosylation, this appeared not to be predictive for RA development in patients with CSA. However, anti-APAA antibodies were found predictive, independent of the known IgM RF and ACPA autoantibodies. Anti-CarP autoantibodies were not independently predictive. Many autoantibody characteristics (AntiCCP2, RF, antiCarp, Anti-APAA, and level and isotypes from all of these autoantbodies) and markers of systemic inflammation were studied in serial serum samples during progression from CSA to RA, and were shown completely stable. This suggests that changes in the systemic autoimmune response are not related to the final hit or final process of RA development. The imaging studies however discovered several new tissues that are inflamed in RA , that occur even before arthritis development and that progressed during RA development. The most specific novel feature is tenosynovitis at the level of small joints, which is also highly predictive of RA development. Other early inflammatory features are intermetatarsal bursitis in the forefeet and interossei tendinitis in the hands, that also occur very early after CSA onset. Hence these imaging studies deepened our understanding of the tissues inflamed in RA and increased the predictive accuracy in the at risk stage of CSA. Moreover, these data show that the concept of RA, which has always been considered as an exclusive disease of synovitis, should be changed. The finding that these tissues are inflamed before arthritis develops suggests that that RA development follows the outside-in hypothesis. It starts with changes in the systemic autoimmune response which mostly develop in the asymptomatic risk stage, before CSA onset. This is followed by local inflammation in periarticular structures, and finally intraarticular synovitis develops. Finally using all clinical, serological and clinical data, a risk stratification method for RA development was derived at the end of the project and this was validated in international cohort data.
This project was feasible, thanks to unique ‘pre-RA’ cohorts and cross-boundary work done with basic scientists, clinicians and engineers. The work has increased our understanding of time courses of RA development and has also resulted in a model for risk stratification that will be useful for clinical practice and that will support the design of future prevention trials by including homogeneous at risk patients.