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Here, you can explore our single-cell RNA sequencing data to investigate the phenotypic spectrum of synovial tissue macrophage during development and resolution of rheumatoid arthritis (RA). Analyses were performed using the Seurat pipeline and custom scripts which are available upon request. In this web application we use a random subset of 8000 cells for faster computation. Further details can be found in our paper summarized below which you should cite if you use our data.

Distinct synovial tissue macrophage subsets regulate inflammation and remission in rheumatoid arthritis

Stefano Alivernini, Lucy MacDonald, Aziza Elmesmari, Samuel Finlay, Barbara Tolusso, Maria Rita Gigante, Luca Petricca, Clara Di Mario, Laura Bui, Simone Perniola, Moustafa Attar, Marco Gessi, Anna Laura Fedele, Sabarinadh Chilaka, Domenico Somma, Stephen Sansom, Andrew Filer, Charles McSharry, Neal L. Millar, Kristina Kirschner, Alessandra Nerviani, Myles J. Lewis, Costantino Pitzalis, Andrew R. Clark, Gianfranco Ferraccioli, Irina Udalova, Christopher D. Buckley, Elisa Gremese, Iain B. McInnes, Thomas D. Otto and Mariola Kurowska-Stolarska

Abstract

Immune-regulatory mechanisms of drug-free remission in rheumatoid arthritis (RA) are unknown. We hypothesised that synovial tissue macrophages (STM), which persist in remission, contribute to joint homeostasis. We used single-cell transcriptomics to profile 32000 STMs and identified phenotypic changes in patients with early/active RA, treatment-refractory/active RA and RA in sustained remission. Each clinical state was characterised by different frequencies of 9 discrete phenotypic clusters within 4 distinct STM subpopulations with diverse homeostatic, regulatory and inflammatory functions. This cellular atlas combined with deep-phenotypic, spatial and functional analyses of synovial biopsy FACS-sorted STMs revealed two STM subpopulations (MerTKpos/TREM2high and MerTKpos/LYVE1pos) with unique remission transcriptomic signatures enriched in negative-regulators of inflammation. These STMs were potent producers of inflammation-resolving lipid mediators and induced the repair response of synovial fibroblasts in vitro. A low proportion of MerTKpos STMs in remission was predictive of flare after treatment cessation. Therapeutic fostering of MerTKpos STM-subpopulations could therefore be a successful strategy for RA treatment.

The results are displayed in 2 sections
  • Clustering - Allows cluster visualization and exploration of top cluster markers.
  • Differential expression (DE) - Comparison of gene expression in macrophages from healthy, UPA, Naive RA, Resistant RA and Remission RA using parameters specified in our paper (i.e the first 12 Principal components and 0.5 as the clustering resolution).
Results
scRNAseq defines heterogeneity within MerTKpos /CD206pos and MerTK neg /CD206 neg STM populations. (a) UMAP of 9 STM clusters identified by scRNAseq analysis. (a-h) show data from Healthy (n=4), UPA (n=4), naïve-active RA (n=5), treatment- resistant RA (n=6) and RA in remission (n=6) in 5 independent experiments. (b) Heatmap of the top 20 differentially expressed genes per cluster. Top cluster markers and the total number of genes characterized each cluster are provided. (c) Violin plots represent log- normalized expression values of STM clusters’ markers with median marked by black dots while cluster identity by unique colour. (d) Relationship between clusters embedded in the top 3 Diffusion-map Components. (e) Hierarchical clustering of STMs. (f) MerTK expression in the 9 STM clusters. (g) Proposed classification of human STMs. (h) Split UMAP and dot plots of relative changes in the STM clusters between groups. Significant differences (*p less than 0.05) between the given condition and at least two other conditions in Two-way ANOVA with Tukey’s correction. Precise p-values in Supplementary Figure 3a which can be found in our paper .
Results     Results

Single gene DE visualization

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Dotplot for multiple gene DE visualization

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DE scatterplot

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DE table

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