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

Abstract

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-seq and flow cytometry to T cells, B cells, monocytes and fibroblasts from 51 samples of synovial tissue from patients with RA or osteoarthritis. 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 together 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 + T peripheral helper (Tph) and T follicular helper (Tfh). We defined distinct subsets of CD8 + T cells characterized by a GZMK + , GZMB + and GNLY + phenotype. 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.

Macrophages drive the inflammatory phase in experimental osteoarthritis

“…This observation was shown independently by another group that classified two subtypes of macrophages in OA (55). Furthermore, AMP characterized myeloid subpopulations from joint replacements and compared the transcriptional profile of macrophages from OA and RA patients (43). In particular, their OA macrophages exhibited increased expression of genes that were down-regulated in our data.…”

“…Figure 3D). This may indicate that OAassociated inflammation is distinct from that observed in RA (43). Therefore, these results suggest that synovial macrophages increase expression of genes associated with OA-specific inflammation and monocyte infiltration, while decreasing expression of genes associated with the tissue-resident phenotype.…”

“…Time course RNA-seq was visualized as the fold-change between the mean of each post-CIOA time point and day 0. Enrichment of marker genes from Zhang et al (43) were calculated using the hypergeometric distribution on the proportion of genes in each of the four k-means clusters compared to total expressed genes.…”

New Developments in Transcriptomic Analysis of Synovial Tissue

“…This was accompanied by reductions in synovial cellularity, joint damage, and leukocyte infiltration, highlighting that the changes observed were not solely due to a reduction in the number of cells within the synovium. Bulk-sequencing of sorted populations mirrored the findings of Zhang et al (41), with the largest differences being observed between the lining layer and sublining layer (45). Further similarities existed in the gene expression profile of these populations with the FAPα + CD90 + cells expressing higher levels of chemokines and cytokines, including IL-6, whereas the FAPα + CD90 − cells showed higher levels of RANKL and MMPs.…”

“…Within the NIH AMP consortium, the exploration of synovial fibroblast subsets was extended through a combined investigation of larger numbers of RA and OA samples using bulk and scRNA-seq, and flow and mass-cytometry. Zhang et al (41) used canonical correlation analysis to integrate this multimodal data from 51 RA and OA samples, facilitating a linked transcriptomic and proteomic analysis of single cells. In addition to defining the myeloid, T and B cell subpopulations present in the RA synovium, this study identified four synovial fibroblast populations: a CD55 + lining layer population and three sublining populations identified as CD34 + , HLA hi , or DKK3 + .…”