Alterations in genes associated with cytosolic RNA sensing in whole blood are associated with coronary microvascular disease in SLE

Abstract

Systemic lupus erythematosus (SLE) patients are 90% women and over three times more likely to die of cardiovascular disease than women in the general population. Chest pain with no obstructive cardiac disease is associated with coronary microvascular disease (CMD), where narrowing of the small blood vessels can lead to ischemia, and frequently reported by SLE patients. Using whole blood RNA samples, we asked whether gene signatures discriminate SLE patients with coronary microvascular dysfunction (CMD) on cardiac MRI (n = 4) from those without (n = 7) and whether any signaling pathway is linked to the underlying pathobiology of SLE CMD. RNA-seq analysis revealed 143 differentially expressed (DE) genes between the SLE and healthy control (HC) groups, with virus defense and interferon (IFN) signaling being the key pathways identified as enriched in SLE as expected. We next conducted a comparative analysis of genes differentially expressed in SLE-CMD and SLE-non-CMD relative to HC samples. Our analysis highlighted differences in IFN signaling, RNA sensing and ADP-ribosylation pathways between SLE-CMD and SLE-non-CMD. This is the first study to investigate possible gene signatures associating with CMD in SLE, and our data strongly suggests that distinct molecular mechanisms underly vascular changes in CMD and non-CMD involvement in SLE.

Keywords: Coronary microvascular disease; Gene expression; Interferon; Systemic lupus erythematosus.

Fig. 1

DEG and pathway analysis of SLE vs HC whole blood transcriptomes. (A) Principal component analysis (PCA) of whole blood transcriptomes from SLE group (n = 11) and HC group (n = 10). (B) Volcano plots of the gene expression comparison between SLE and HC. The horizontal axis represents the log2 (fold change) and the vertical axis represents the − log10 (P-value). The red plots represent the selected DEGs with fold change ≥ 2 and p < 0.01. (C) GO terms enriched in SLE patients’ samples. Genes with P-values < 0.05 were selected as input and enriched terms with p_adj < 0.05 were selected.

Fig. 2

Unique gene differentially expressed in SLE–CMD and SLE–non-CMD whole blood samples using HC as reference group. (A, B) Venn diagram representing the unique or overlapping (A) upregulated or (B) downregulated genes in SLE–CMD and SLE–non-CMD when using HC as a reference group. SLE–CMD versus HC (a); SLE–non-CMD versus HC (b); DE genes were identified using DEseq2 v1.42.0 with p_adj < 0.1, log2FoldChange > 0.5 as up regulated gene cutoff, and log2FoldChang < 0.5 as down regulated gene cutoff. SLE–CMD (n = 4), SLE–non-CMD (n = 7), and HC (n = 10); (C) Go pathway analysis for SLE–CMD and SLE–non-CMD common genes. 60 common genes were used for this test with default filters of pvalueCutoff = 0.05, qvalueCutoff = 0.2, minGSSize = 10, maxGSSize = 500.

Fig. 3

Representative DE genes in pathway analysis. (A, B) Go pathway analysis for unique genes in (A) SLE–CMD and (B) SLE-non-CMD. Genes with p-values < 0.05 were selected as input and enriched terms with p_adj < 0.1 were selected. SLE–CMD (n = 4), SLE-non-CMD (n = 7), and HC (n = 10); (C) Heatmap of SLE–CMD unique genes in the enriched GO terms. Green: up regulated; Red: down regulated; (D) Heatmap of unique genes in SLE-non-CMD in the enriched GO terms. Green: up regulated; Red: down regulated.

Fig. 4

SLE–CMD unique gene signature related to RNA sensing and inflammation. (A, B) Dot plot of enrichment of RNA sensing related genes in SLE–CMD (A) and Dot plot of enrichment of inflammation related genes in SLE–CMD (B) (P_adj < 0.1, |log2FoldChange|> 0.5). SLE–CMD (n = 4), SLE-non-CMD (n = 7), and HC (n = 10).

Fig. 5

RIG-I and DHX58 expression were significantly increased in IFNα treated AC16 cells. (A, B) Bar plot of expression of RIG-I (A) and DHX58 (B) in IFNa treated Human Cardiomyocyte Cell line cells (n = 3). Statistical significance was determined by unpaired Student’s t-test, ****p < 0.0001.