Synovial Transcriptome Profiling for Predicting Biological Treatment Response in Rheumatoid Arthritis: A Feasibility study

ABSTRACT Introduction Disease-Modifying Anti-Rheumatic Drug (DMARD) treatment fails to achieve clinical remission in a substantial proportion of patients with rheumatoid arthritis (RA). Patient-derived synovial tissue (ST)-signatures, thought to determine this heterogeneity of treatment responses, can be studied by single-cell RNA sequencing (scRNA-seq). Study aims The first aim was to obtain viable ST from RA patients using wrist arthroscopy. The second aim was to identify patient-specific transcriptome signatures from the ST omics data that relate to clinical course and treatment responses in RA. Methods Radiocarpal and midcarpal synovectomy was performed using a standard set-up wrist arthroscopy. Single-cell suspensions of ST from affected wrists of two RA patients and a control subject were processed on the 10X Genomics Chromium Platform. Seurat was used for downstream analysis. Results In two RA patients and one non-inflammatory control, ST was successfully removed during wrist arthroscopy. No surgical complications occurred. For the RA patients and control, 17,176 and 7,884 high-quality cells were analyzed, respectively. Apart from enrichment of cell compartments in RA, including those of B- and plasma cells, T cell populations, NK cells, and macrophages, we observed interpatient variability that may influence the relationship between RA synovial signature and clinical phenotype, potentially also affecting treatment response and outcome. In-depth analysis of the prevailing cell-type abundance phenotype (CTAP) in the RA patients, as described previously, provided insights into the extent to which these CTAPs may be used to predict treatment responses. Conclusion In this feasibility study, we demonstrated that wrist arthroscopy successfully retrieves ST with good tissue viability, which may provide informative and high-quality transcriptomic data for predicting therapy response at an individual level.