Single-cell RNA-Seq analysis reveals cell subsets and gene signatures associated with rheumatoid arthritis disease activity

Abstract

Rheumatoid arthritis (RA) management leans toward achieving remission or low disease activity. In this study, we conducted single-cell RNA sequencing (scRNA-Seq) of peripheral blood mononuclear cells (PBMCs) from 36 individuals (18 patients with RA and 18 matched controls, accounting for age, sex, race, and ethnicity), to identify disease-relevant cell subsets and cell type-specific signatures associated with disease activity. Our analysis revealed 18 distinct PBMC subsets, including an IFN-induced transmembrane 3-overexpressing (IFITM3-overexpressing) IFN-activated monocyte subset. We observed an increase in CD4+ T effector memory cells in patients with moderate-high disease activity (DAS28-CRP ≥ 3.2) and a decrease in nonclassical monocytes in patients with low disease activity or remission (DAS28-CRP < 3.2). Pseudobulk analysis by cell type identified 168 differentially expressed genes between RA and matched controls, with a downregulation of proinflammatory genes in the γδ T cell subset, alteration of genes associated with RA predisposition in the IFN-activated subset, and nonclassical monocytes. Additionally, we identified a gene signature associated with moderate-high disease activity, characterized by upregulation of proinflammatory genes such as TNF, JUN, EGR1, IFIT2, MAFB, and G0S2 and downregulation of genes including HLA-DQB1, HLA-DRB5, and TNFSF13B. Notably, cell-cell communication analysis revealed an upregulation of signaling pathways, including VISTA, in both moderate-high and remission-low disease activity contexts. Our findings provide valuable insights into the systemic cellular and molecular mechanisms underlying RA disease activity.

Keywords: Autoimmunity; Immunology; Rheumatology.

Figure 1. Identification of 18 PBMCs cell subsets.

(A) UMAP embeddings and subset annotations of scRNA-Seq data set from patients with rheumatoid arthritis (n = 18) and healthy controls (n = 18) matched on age, sex, and ethnicity. (B) Normalized expression of the top 40 ranked genes in different cell subsets (Wilcoxon rank test, FDR ≤ 0.05). (C) Correlation heatmap of gene expression across cells subsets (Spearman correlation). CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.

Figure 2. Cell subsets and top marker genes identified in Wilcoxon rank sum.

(A) UMAP embedding for cell subsets in B cells, monocytes, CD4 T cells, CD8 T cells, and NK cells. (B) Dot plots of top ranking genes in each cell subset. CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.

Figure 3. Pseudobulk analysis between patients with RA and matched controls for each subsets.

(A) Single-cell UMAP of patients with RA and matched controls. (B) Differentially expressed genes between patients with RA and matched controls. (C) UpSet plots of upregulated and downregulated genes across different cell subsets. CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.

Figure 4. Functional analysis between RA and matched controls.

Pathways and overrepresentation analysis for each cell subtype (gene ratio > 0.15, FDR ≤ 0.05, 0.08 < base mean < 4). CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.

Figure 5. Cell proportion and cell density between patients with remission-low and moderate-high disease activity and matched controls.

(A) UMAP representation of cell subsets. (B) Compositional and density analysis between control patients with low and high disease activity. (C) Cell proportion analysis between controls and patients with RA with ow and high disease activity. Each point represents the cell subset proportion of each patient normalized to the total number of cells for that patient (Mann-Whitney U test, *P ≤ 0.05). CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.

Figure 6. Gene signature associated with disease activity and percentage of expression across cell subsets.

Gene expression heatmap between controls and RA with low and high disease activity and average expression across cell subtypes. CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.

Figure 7. Cell-cell communications between patients with remission-low and moderate-high disease activity and matched controls.

(A) Heatmap representing the relative number of interactions between RA and matched controls. (B) Bar plot illustrates statistically significant communication pathways based on the weight of interactions between patients with RA and controls. (C) Dot plot of the relative contribution of communication pathways based on weight of interactions between high and low disease activity compared with controls. (D) Heatmaps of the relative importance of cells as senders and receivers for the IFN-II, the VEGF, and the NT signaling pathway network in high and low disease activity. (E) Circle plots representing the relative importance of cells as senders and receivers for the VISTA signaling pathway network in high and low disease activity and overall. CD, cluster differentiation; IFIT, IFN-induced proteins with tetratricopeptide repeats; IFITM, IFN-induced transmembrane; Tem, T effector memory; TEMRA, terminally differentiated effector memory; RA, rheumatoid arthritis.