Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patie...

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Published in:	Nature immunology Vol. 20; no. 7; pp. 928 - 942
Main Authors:	Zhang, Fan, Wei, Kevin, Slowikowski, Kamil, Fonseka, Chamith Y., Rao, Deepak A., Kelly, Stephen, Goodman, Susan M., Tabechian, Darren, Hughes, Laura B., Salomon-Escoto, Karen, Watts, Gerald F. M., Jonsson, A. Helena, Rangel-Moreno, Javier, Meednu, Nida, Rozo, Cristina, Apruzzese, William, Eisenhaure, Thomas M., Lieb, David J., Boyle, David L., Mandelin, Arthur M., Boyce, Brendan F., DiCarlo, Edward, Gravallese, Ellen M., Gregersen, Peter K., Moreland, Larry, Firestein, Gary S., Hacohen, Nir, Nusbaum, Chad, Lederer, James A., Perlman, Harris, Pitzalis, Costantino, Filer, Andrew, Holers, V. Michael, Bykerk, Vivian P., Donlin, Laura T., Anolik, Jennifer H., Brenner, Michael B., Raychaudhuri, Soumya
Format:	Journal Article
Language:	English
Published:	New York Nature Publishing Group US 01-07-2019 Nature Publishing Group
Subjects:	631/250/2502 631/250/256 631/250/38 692/699/249/1313 692/699/249/2510 Analysis Arthritis, Rheumatoid - genetics Arthritis, Rheumatoid - metabolism Arthritis, Rheumatoid - pathology Autoimmune diseases Autoimmunity - genetics B cells Biomarkers Biomedical and Life Sciences Biomedicine CD8 antigen CD90 antigen Cell activation Computational Biology - methods Correlation analysis Cross-Sectional Studies Cytokines - metabolism Fibroblasts Fibroblasts - metabolism Flow Cytometry Gene Expression Gene Expression Profiling - methods High-Throughput Nucleotide Sequencing Histocompatibility antigen HLA Histocompatibility Antigens Class II - genetics Histocompatibility Antigens Class II - immunology Humans Immunology Infectious Diseases Inflammation Interleukin 1 Interleukin 6 Leukocytes - immunology Leukocytes - metabolism Lymphocytes Lymphocytes B Lymphocytes T Monocytes Monocytes - immunology Monocytes - metabolism Osteoarthritis Pathogenesis Phenotypes Resource Rheumatoid arthritis Rheumatoid factor Ribonucleic acid RNA RNA sequencing Signal Transduction Single-Cell Analysis - methods Synovial Membrane - metabolism Synovial Membrane - pathology T cells T-Lymphocyte Subsets - immunology T-Lymphocyte Subsets - metabolism Transcriptome Transcriptomics Workflow
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Summary:	To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing (RNA-seq) and flow cytometry to T cells, B cells, monocytes, and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis (OA). Utilizing an integrated strategy based on canonical correlation analysis of 5,265 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics revealed cell states expanded in RA synovia: THY1(CD90) + HLA-DRA hi sublining fibroblasts, IL1B + pro-inflammatory monocytes, ITGAX + TBX21 + autoimmune-associated B cells and PDCD1 + peripheral helper T (T PH ) cells and follicular helper T (T FH ) cells. We defined distinct subsets of CD8 + T cells characterized by GZMK + , GZMB + , and GNLY + phenotypes. We mapped inflammatory mediators to their source cell populations; for example, we attributed IL6 expression to THY1 + HLA-DRA hi fibroblasts and IL1B production to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis. Defining cell types and their activation status in rheumatoid arthritis (RA) is critical to understanding this disease. Raychaudhuri and colleagues leverage several single-cell -omics approaches to define the cellular processes and pathways in the human RA joint.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Co-senior authors S.K., S.M.G., D.T., L.B.H., K.S.-E., A.M.M., D.L.B., J.H.A., V.P.B., V.M.H., A.F., C.P., H.P., G.S.F., L.M., P.K.G., W.A. and L.T.D. recruited patients and obtained synovial tissues. B.F.B., E.D. and E.M.G. performed histological assessment of tissues. K.W., D.A.R., G.F.M.W., and M.B.B. designed and implemented tissue processing and cell sorting pipeline. J.A.L. obtained mass cytometry data from samples. N.H., C.N., and T.M.E. obtained single cell RNA-seq data from samples. F.Z., K.S., C.Y.F., D.J.L. and S.R. conducted computational and statistical analysis. A.H.J., J.R.-M., N.M.P., and C.R., designed and performed validation experiments. K.S., F.Z., and J.R.M. implemented the website. J.A., S.L.B., C.D.B., J.H.B., J.D., J.M.G., M.G., L.B.I., E.A.J., J.A.J., J.K., Y.C.L., M.J.M., M.M., F.M., J.N., A.N., D.E.O., M.P., C.R., W.H.R., A.S., D.S., J.S., J.D.T., and P.J.U. contributed to the procurement and processing of samples, design of the AMP study. S.R., M.B.B., J.H.A., and L.T.D. supervised the research. F.Z., K.W., K.S, and S.R. generated figures and wrote the initial draft. K.S, C.Y.F. D.A.R, L.T.D., J.H.A, M.B.B. edited the draft, and all the authors participated in writing the final manuscript. AUTHOR CONTRIBUTIONS Co-first authors
ISSN:	1529-2908 1529-2916
DOI:	10.1038/s41590-019-0378-1