Defining Inflammatory Cell States in Rheumatoid Arthritis Joint Synovial Tissues by Integrating Single-cell Transcriptomics and Mass Cytometry
Chamith Y. Fonseka,
Deepak A. Rao,
Susan M. Goodman,
Laura B. Hughes,
Gerald F. M. Watts,
David J. Lieb,
David L. Boyle,
Arthur M. Mandelin,
Accelerating Medicines Partnership: RA Phase 1, AMP RA/SLE,
Brendan F. Boyce,
Ellen M. Gravallese,
Solbritt Rantapää Dahlqvist,
Gary S Firestein,
James A. Lederer,
V. Michael Holers,
Vivian P. Bykerk,
Laura T. Donlin,
Jennifer H. Anolik,
Michael B. Brenner,
Posted 20 Jun 2018
bioRxiv DOI: 10.1101/351130 (published DOI: 10.1038/s41590-019-0378-1)
Posted 20 Jun 2018
To define the cell populations in rheumatoid arthritis (RA) driving joint inflammation, we applied single-cell RNA-seq (scRNA-seq), mass cytometry, bulk RNA-seq, and flow cytometry to sorted T cells, B cells, monocytes, and fibroblasts from 51 synovial tissue RA and osteoarthritis (OA) patient samples. Utilizing an integrated computational strategy based on canonical correlation analysis to 5,452 scRNA-seq profiles, we identified 18 unique cell populations. Combining mass cytometry and transcriptomics together revealed cell states expanded in RA synovia: THY1+HLAhigh sublining fibroblasts (OR=33.8), IL1B+ pro-inflammatory monocytes (OR=7.8), CD11c+T-bet+ autoimmune-associated B cells (OR=5.7), and PD-1+ Tph/Tfh (OR=3.0). We also defined CD8+ T cell subsets characterized by GZMK+, GZMB+, and GNLY+ expression. Using bulk and single-cell data, we mapped inflammatory mediators to source cell populations, for example attributing IL6 production to THY1+HLAhigh fibroblasts and naive B cells, and ILB to pro-inflammatory monocytes. These populations are potentially key mediators of RA pathogenesis.
- Downloaded 4,341 times
- Download rankings, all-time:
- Site-wide: 2,411
- In immunology: 69
- Year to date:
- Site-wide: 25,594
- Since beginning of last month:
- Site-wide: 18,817
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!