|dc.description.abstract||Rheumatoid arthritis (RA) is a debilitating chronic inflammatory disease that affects millions of people worldwide. Disease pathogenesis involves the synovium, a thin membrane encapsulating the joint, mostly composed of cells resembling fibroblasts and macrophages. Th synovium proliferates and forms a pannus of inflamed tissue that persistently recruits immune cells, degrades collagen, and activates bone-resorbing osteoclasts. The infiltrating immune cells interact with the stromal tissue cells, leading to synovial hypertrophy, and ultimately to joint destruction. The cellular composition and molecular functions of stromal fibroblast cells in the synovium are relevant to understanding disease progression. With small quantities of patient tissues, the latest technologies allow us to assay transcriptomics genome-wide at high resolution. Transcriptomics analysis helps us determine the distinct functions of cellular populations in the synovium and reveal gene regulatory factors activated by cytokines elevated in the disease state. Further understanding of basic biology in these cells may reveal fibroblast-specific targets for the treatment of inflammatory diseases mediated by fibroblasts.
Here, we use computational analyses of bulk tissue and single cell transcriptomic data, and also genetics data, to advance understanding of mechanisms underlying RA. We integrate genome-wide association study (GWAS) results with gene expression data to understand which cell types express the genes that are associated with risk of developing disease. Next, we analyze transcriptomics data collected from synovial fibroblasts obtained from fresh tissue discarded during joint replacement surgery. Single-cell gene expression profiles reveals the cellular population structure of fibroblasts in the synovium. Within the sublining layer, RA patients have an overabundant fibroblast population negative for CD34 and positive for CD90. The heterogenous synovial cellular populations produce a mixture of signaling molecules that synergistically influence the positive feedback loop between local tissue cells and infiltrating immune cells. To understand the regulation of the synergistic response to tumor necrosis factor (TNF) and interleukin 17 (IL-17A), we use high resolution transcriptomics with time series, dose response, and gene silencing. Our analyses predict and our experiments validate that CUX1 is a key mediator for fibroblast expression of CXCL1, CXCL2, CXCL3. Understanding regulation of transcriptional response to inflammatory factors in synovial fibroblasts has implications for RA as well as other diseases involving chronic inflammation mediated by fibroblasts in connective tissues such as psoriasis. Our approaches for interrogating RA could be applied to these diseases.||