Physical inactivity exacerbates pathologic inflammatory signalling at the single cell level in patients with systemic lupus

Abstract

Background: Physical activity is an adjunctive therapy that improves symptoms in people living with systemic lupus erythematosus (SLE), yet the mechanisms underlying this benefit remain unclear.

Methods: We carried out a cohort study of 123 patients with SLE enrolled in the California Lupus Epidemiology Study (CLUES). The primary predictor variable was self-reported physical activity, which was measured using a previously validated instrument. We analyzed peripheral blood mononuclear cell (PBMC) single-cell RNA sequencing (scRNA-seq) data available from the cohort. From the scRNA-seq data, we compared immune cell frequencies, cell-specific gene expression, biological signalling pathways, and upstream cytokine activation states between physically active and inactive patients, adjusting for age, sex and race.

Findings: We found that physical activity influenced immune cell frequencies, with sedentary patients most notably demonstrating greater CD4+ T cell lymphopenia (P_adj = 0.028). Differential gene expression analysis identified a transcriptional signature of physical inactivity across five cell types. In CD4+ and CD8+ T cells, this signature was characterized by 686 and 445 differentially expressed genes (P_adj < 0.1). Gene set enrichment analysis demonstrated enrichment of proinflammatory genes in the TNF-α signalling through NF-kB, interferon-γ (IFN-γ), IL2/STAT5, and IL6/JAK/STAT3 signalling pathways. Computational prediction of upstream cytokine activation states suggested CD4+ T cells from physically inactive patients exhibited increased activation of TNF-α, IFN-γ, IL1Β, and other proinflammatory cytokines. Network analysis demonstrated interconnectivity of genes driving the proinflammatory state of sedentary patients. Findings were consistent in sensitivity analyses adjusting for corticosteroid treatment and physical function.

Interpretation: Taken together, our findings suggest a mechanistic explanation for the observed benefits of physical activity in patients with SLE. Specifically, we find that physical inactivity is associated with altered frequencies and transcriptional profiles of immune cell populations and may exacerbate pathologic inflammatory signalling via CD4+ and CD8+ T cells.

Funding: This work was supported by the US National Institutes of Health (NIH) (R01 AR069616, K23HL138461-01A1, K23AT011768) the US CDC (U01DP0670), and the CZ Biohub.

Keywords: Lifestyle behaviors; Physical activity; Rheumatoid arthritis; Single cell transcriptomics.

Fig. 1

Study overview. Patients with systemic lupus erythematosus (SLE) enrolled in the California Lupus Epidemiology Study (CLUES) were compared based on physical activity status (active versus sedentary). Single cell RNA sequencing of PBMCs was carried out to identify and profile immune cell populations. Cell frequencies, gene expression, biological pathways, and gene networks were compared between physically active and sedentary groups.

Fig. 2

scRNA-seq identifies differences in immune cell frequencies and gene expression based on physical inactivity. (A) UMAP plot of all single cells used in the study, coloured by the cell types. There are 11 cell types: CD4+ T cells and CD8+ T cells, B cells, classical and nonclassical monocytes (cM and ncM), natural killer cells (NK), plasmablasts (PB), conventional and plasmacytoid dendritic cells (cDC and pDC), proliferating lymphocytes (Prolif), and CD34 progenitors (Progen).(B) UMAP plots of single cells from physically inactive (left) and physically active (right) patients. (C) Box plots showing the proportion of the 4 significant cell types in the physically active (n = 81) and inactive (n = 42) groups (P-values, two-sided Mann–Whitney test with Benjamini-Hochberg correction). (D) UMAP plot showing the lymphoid subpopulations: CD4+ and CD8+ naïve T cells, CD4+ effector memory and regulatory T cells, GZMH+ and GZMK+ CD8+ T cells, mucosal-associated invariant CD8+ T cells (MAIT), CD56^bright and CD56^dim natural killer cells. (E) Box plots showing the proportion of the 4 significant lymphoid subtypes in the physically active (n = 81) and inactive (n = 42) groups. Boxes indicate the first and third quartiles, middle lines indicate the median value, and whiskers extend to 1.5 × the interquartile range below the first quartile and above the third quartile.

Fig. 3

Physical inactivity drives proinflammatory gene expression in T cells. (A) Bar plot showing the number of differentially expressed (DE) genes between the physically active (n = 81) and inactive (n = 42) groups at an adjusted P-value (Padj) < 0.1 for each of the 6 most abundant cell types. Data regarding more finely resolved cell subtypes are presented in Supplemental Figure S1. (B) Volcano plots of differential expression analysis in CD4+ T cells and CD8+ T cells. There were 686 and 445 DE genes (FDR <0.1) in CD4+ T cells and CD8+ T cells, respectively. A positive log₂(fold change) indicates that a gene is upregulated in physically inactive patients compared to active patients. (C) Dot plots showing Hallmark pathways that are statistically significantly associated with physical inactivity in CD4+ T cells and CD8+ T cells (FDR <0.1). (D, E) Bar plots showing the cytokines predicted by Ingenuity Pathway Analysis to be activated in (D) CD4+ T cells and (E) CD8+ T cells of physically inactive patients compared to active patients.

Fig. 4

A gene network drives proinflammatory signalling in CD4+ T cells. A gene-concept network plot of 4 immune-related Hallmark pathways in CD4+ T cells (TNF-α signalling via NF-kB, IFN-γ response, IL6 JAK STAT3 signalling, and IL2 STAT5 signalling pathways). The gene dots are coloured by the genes' log₂(fold change), and a positive and negative log₂(fold change) indicate that the gene is upregulated and downregulated in physically inactive patients, respectively.