PhDDespite a growing armamentarium of therapies available to treat rheumatoid arthritis (RA), predicting response to therapy remains a clinical challenge. Witnessed variability in treatment outcomes translates to a large unmet clinical need; with significant risk of disease progression, exposure to side effects and health economic burden. Clinical heterogeneity in RA is reflected at the tissue level as diseased synovium displays variation in both degree and organisation of immune cell infiltration. Transcriptomic analysis suggests that synovial cellular heterogeneity is mirrored by a diversification of molecular profiles which may affect response to therapy. B-cells play a critical role in the pathogenesis and propagation of RA. Treatment response to the B-cell depleting agent rituximab in RA is varied and clear predictors of response are yet to be elucidated. The first aim of this work was to develop a pathological scoring system for the rheumatoid synovium to determine ‘B-cell rich’ and ‘B-cell poor’ pathotypes and investigate whether these subgroups can predict clinical response. I establish that despite the degree of reduction in synovial B-cells following rituximab therapy, clinical response remains indeterminate. The second aim was to investigate whether a molecular signature associated with response to rituximab therapy. Critically, I demonstrate that an upregulation of genes associated with ectopic lymphoid structures (ELS) and those which orchestrate Th17/interleukin 17 (IL-17) pathways are associated with diminished response to rituximab. Furthermore, these genes can be utilised to create a model which has high sensitivity to predict response to rituximab. Finally, I investigate whether changes in synovial cellular infiltration and gene expression are associated with changes in ultrasound (US) synovial thickening (ST) and power doppler (PD) signal, demonstrating a key role of fibroblast and IL-17 associated genes. Synovium remains the site of insult in RA; this work enhances the notion that synovial biopsies may be pivotal stratification tools of the future
