Clinical Assessment for Rheumatologic Disease - Research and Advancement in Safety and Efficacy

ANCA Associated Vasculitis (AAV), Autoinflammatory Disease, Axial Spondylarthritis (axSpA), Connective Tissue Disease (CTD), Giant Cell Arteritis (GCA), Gout Arthritis, Idiopathic Inflammatory Myopathy (IIM), Polymyalgia Rheumatica (PMR), Psoriatic Arthritis (PsA), Rheumatic Diseases, Rheumatoid Arthritis (RA), Systemic Lupus Erthematosus (SLE), Systemic Sclerosis (SSc)

The CARe RAiSE project represents a pioneering translational initiative aimed at advancing precision medicine in the treatment of autoimmune rheumatic diseases. The primary objective is the development and implementation of an innovative cell-based ex vivo assay that enables individualized prediction of therapeutic response to disease-modifying antirheumatic drugs (DMARDs). By identifying the most effective treatment option for each patient, this approach seeks to enhance therapeutic efficacy, reduce time to clinical response, and minimize healthcare costs. Despite the availability of numerous DMARDs, clinical decision-making remains largely empirical due to considerable interindividual variability in treatment response. This frequently results in a prolonged trial-and-error process, placing a significant burden on patients and the healthcare system. CARe RAiSE aims to overcome this limitation by providing a functional diagnostic tool that can predict a patient's immunological response to specific DMARDs prior to treatment initiation. The assay is based on peripheral blood mononuclear cells (PBMCs) obtained from individual patients, enabling a physiologically relevant assessment of immune responsiveness to targeted therapies. Combining high-content imaging with homogeneous well-based cytokine and inflammasome activity assays, the platform allows for a detailed single-cell analysis of inflammatory pathways. These data are used to generate predictive signatures of treatment response, thereby facilitating a mechanistically informed and personalized therapeutic strategy. Through this approach, CARe RAiSE introduces a scientifically grounded, efficient, and patient-specific method for DMARD selection, with the potential to substantially improve patient outcomes and reduce the socioeconomic impact of autoimmune rheumatic diseases.

Study Overview and Work Packages This study aims to functionally characterize individual immune responses in patients with autoimmune and autoinflammatory rheumatic diseases using immunological and molecular approaches to develop predictive models of response to immunomodulatory therapies. The study follows a hybrid design with prospective-longitudinal and cross-sectional components and includes the following cohorts: Newly diagnosed cohort: Patients with treatment-naïve disease. Sampling at baseline (V0), follow-up at 6 and 12 weeks (V1/V2), with optional sampling at disease relapse (VRel) and after treatment adjustment (VTher). Cross-sectional cohort: Patients under ongoing immunomodulatory therapy. Single-timepoint sampling (Vc), with optional VRel and VTher. Healthy control cohort: Age- and sex-matched healthy individuals. Single-timepoint sampling equivalent to V0 (Vk). Work Package 1 - Patient Recruitment and Sample Collection Patients are recruited through the Rheumatology Outpatient Clinic at the University Hospital Bonn. Inclusion requires a confirmed diagnosis of an autoimmune or autoinflammatory rheumatic disease. Specifically, patients with the following conditions are eligible: Rheumatoid arthritis (RA) Psoriatic arthritis (PsA) Psoriasis (PSO) Axial spondyloarthritis (axSpA) Giant cell arteritis (GCA) Connective tissue diseases, including * Systemic lupus erythematosus (SLE) * Systemic sclerosis (SSc) * Mixed connective tissue disease (MCTD) * Idiopathic inflammatory myopathies (IIM) ANCA-associated vasculitides (AAV), including * Microscopic polyangiitis (MPA) * Granulomatosis with polyangiitis (GPA) * Eosinophilic granulomatosis with polyangiitis (EGPA) Autoinflammatory diseases, including gout (arthritis urica) At each visit, peripheral blood samples (EDTA, serum, PaxGene) are collected, accompanied by detailed clinical phenotyping (disease manifestations, activity scores) and standardized documentation of longitudinal disease trajectories. All samples are pseudonymized and stored in the central Biobank Bonn. Matched healthy controls are included for comparative analysis. Work Package 2 - Ex vivo Functional Immune Profiling and Immunophenotyping Peripheral blood mononuclear cells (PBMCs) are isolated from EDTA blood and subjected to a standardized, proprietary ex vivo assay to assess immunomodulatory effects of selected DMARDs (disease-modifying antirheumatic drugs). Functional immune responses are characterized based on TNF-α production, inflammasome activation, and cytokine secretion, assessed at defined timepoints. Cytokine concentrations are quantified via ELISA and multiplex immunoassays. Comprehensive flow cytometry-based immunophenotyping is performed to quantify relevant immune cell subsets and define activation states. In a subset of patients, total mRNA is extracted from PBMCs and analyzed via bulk transcriptomics to characterize gene expression patterns associated with immunoregulatory pathways. Key targets include cytokine and chemokine signatures, transcription factors, interferon-stimulated genes, and markers of immune cell activation and differentiation. In parallel, previously collected and ethically approved archived biospecimens (e.g., synovial fluid, synovial tissue, skin biopsies) are included for correlative studies. These comprise histopathological and immunohistochemical analyses, cytokine quantification, and immune cell profiling. PBMCs isolated from diagnostic synovial fluid samples will also undergo the ex vivo assay. The objective is to correlate structural and cellular features of inflamed tissues with molecular and functional immune profiles derived from peripheral blood. Work Package 3 - Correlation with Clinical Outcomes Predictive models derived from ex vivo assays will be evaluated against actual clinical outcomes. This includes longitudinal analysis of treatment response, disease progression, and adverse event profiles. The correlation of predicted versus observed responses will allow robust validation of assay performance in terms of sensitivity, specificity, and predictive value, with the goal of enabling personalized treatment selection in autoimmune and autoinflammatory rheumatic diseases.

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