bioRxivImmunology
Single Cell Transcriptomics And Flow Cytometry Reveal Disease-Associated Fibroblast Subsets In Rheumatoid Arthritis
F. Mizoguchi, K. Slowikowski, J. L. Marshall, K. Wei, D. A. Rao, S. K. Chang, H. N. Nguyen, E. H. Noss, J. D. Turner, B. E. Earp, P. E. Blazar, J. Wright, B. P. Simmons, L. T. Donlin, G. D. Kalliolias, S. M. Goodman, V. P. Bykerk, L. B. Ivashkiv, J. A. Lederer, N. Hacohen, P. A. Nigrovic, A. Filer, C. D. Buckley, S. Raychaudhuri, M. B. Brenner
Abstract
Fibroblasts mediate normal tissue matrix remodeling, but they can cause fibrosis or tissue destruction following chronic inflammation. In rheumatoid arthritis (RA), synovial fibroblasts expand, degrade cartilage, and drive joint inflammation. Little is known about fibroblast heterogeneity or if aberrations in fibroblast subsets relate to disease pathology. Here, we used an integrative strategy, including bulk transcriptomics on targeted subpopulations and unbiased single-cell transcriptomics, to analyze fibroblasts from synovial tissues. We identify 7 phenotypic fibroblast subsets with distinct surface protein phenotypes, and these collapsed into 3 subsets based on transcriptomics data. One subset expressing PDPN, THY1, but lacking CD34 was 3-fold expanded in RA relative to osteoarthritis (P=0.007); most of these cells expressed CDH11. The subsets were found to differ in expression of cytokines and matrix metalloproteinases, localization in synovial microanatomy, and in response to TNF. Our approach provides a template to identify pathogenic stromal cellular subsets in complex diseases.
- organism: human
- assay: scRNA-seq
- assay: flow cytometry
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: experimental assay
- approach: statistical model
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