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Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes

UID: 11398

Publisher(s): synapse.org

Description
Description from Synapse.org

"Rheumatoid arthritis (RA) is a prototypical autoimmune disease that causes inflammation leading to cartilage and bone destruction in joints. Clinical challenges in RA include the empirical selection of drugs to treat patients, inadequate responders with incomplete disease remission, and lack of a cure. We profiled the full spectrum of cells in inflamed synovium from patients with RA with the goal of deconstructing the cell states and pathways characterizing pathogenic heterogeneity in RA. Our multicenter consortium effort used multi-modal CITE-seq, single-cell RNA-seq, and histology of synovial tissue from 79 donors to build a >314,000 single-cell RA synovial cell atlas with 77 cell states across T, B/plasma, natural killer, myeloid, stromal, and endothelial cells. We stratified tissue samples into six distinct cell-type abundance phenotypes (CTAPs) individually enriched for specific cell states. These CTAPs demonstrate the striking diversity of RA synovial inflammation, ranging from marked enrichment of T and B cells (CTAP-TB) to a mixture of myeloid, fibroblast, and endothelial cells largely lacking lymphocytes (CTAP-EFM). Disease-relevant cell states, cytokines, risk genes, histology, and serology metrics are associated with certain CTAPs, implicating pathological interactions. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying RA synovial phenotypes. This comprehensive RA synovial atlas and molecular, tissue-based stratification reveal new insights into RA pathology and heterogeneity, which could inform novel targeted-treatment approaches.

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Subject(s)
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Accession #: syn52297840

Access Restrictions
Free to All
Access Instructions
Download from Synapse.org to access. An interactive data browser is available to view all of the transcriptomics data for each of the manually curated cell clusters.
Associated Publications
Dataset Format(s)
Microsoft Excel, CSV, TSV, FASTQ, MTX, BAM, BAI, H5, RDS, TGZ
Data Catalog Record Updated
2024-10-23