Construction of competing endogenous RNA networks in systemic lupus erythematosus by integrated analysis

Abstract

Objective: Systemic lupus erythematosus (SLE) is a disease characterised by immune inflammation and damage to multiple organs. Recent investigations have linked competing endogenous RNAs (ceRNAs) to lupus. However, the exact mechanism through which the ceRNAs network affects SLE is still unclear. This study aims to investigate the regulatory functions of the ceRNAs network, which are important pathways that control the pathophysiological processes of SLE.

Methods: CircRNA microarray for our tested assays were derived from bone marrow samples from three healthy individuals and three SLE patients in our hospital. The other sequencing data of circRNA, miRNA and mRNA were obtained from Gene Expression Omnibus (GEO) datasets. Using the limma package of R program, the differential expression of mRNA and miRNA in the GEO database was discovered. Then predicted miRNA-mRNA and circRNA-miRNA were established using miRMap, miRanda, miRDB, TargetScan, and miTarBase. CircRNA-miRNA-mRNA ceRNA network was constructed using Cytoscape, and hub genes were screened using a protein-protein interaction network. Immune infiltration analysis of the hub gene was also performed by CIBERSORT and GSEA.

Results: 230 overlapped circRNAs, 86 DEmiRNAs and 2083 DEmRNAs were identified in SLE patients as compared to healthy controls. We constructed a circRNA-miRNA-mRNA ceRNAs network contained 11 overlapped circRNAs, 9 miRNAs and 51 mRNAs. ESR1 and SIRT1 were the most frequently associated protein-protein interactions in the PPI network. KEGG analysis showed that DEGs was enriched in FoxO signaling pathway as well as lipids and atherosclerosis. We constructed a novel circRNA-miRNA-mRNA ceRNA network (HSA circ 0000345- HSA miR-22-3-P-ESR1/SIRT1) that may have a major impact on SLE.

Conclusion: Through this bioinformatics and integrated analysis, we suggest a regulatory role for ceRNA network in the pathogenesis and treatment of SLE.

Keywords: bioinformatics analysis; competing endogenous RNAs; differentially expressed genes; enrichment analysis; systemic lupus erythematosus.

Figure 1

Identification of DEcircRNAs in SLE (A) Basic information of circRNA datasets. (B) Volcano plots for different expression of circRNAs of bone-marrow in SLE. (C) Heatmap plot showing the top 20 DEcircRNAs in our dataset. (D) Volcano plots for DEcircRNAs of GSE84655. (E) Heatmap plot showing the top 20 DEcircRNAs of GSE84655. (F,G) The Venn plots of DEcircRNAs of two datasets.

Figure 2

Determination of lupus-associated DEmRNAs and DEmiRNA. (A) Basic information of miRNAs and mRNA datasets. (B,C) Hotmap of the 20 top DEmiRNAs and DEmRNAs. (D,E) The Venn plots of predicted miRNAs based on DEmRNAs of GSE175839.

Figure 3

A flowchart of DEGs analysis.

Figure 4

Construction of CeRNAs networks (A) CircRNA(down)-miRNA(up)-mRNA(down) regulatory network (B) CircRNA(up)-miRNA(down)-mRNA(up) regulatory network.

Figure 5

GO term and KEGG pathways enrichment analysis (A) Biological process (BP), (B) cellular component (CC), (C) molecular function (MF) of the GO annotation (D) KEGG pathways of DEmRNA.

Figure 6

PPI network and hubgenes of targeted DEmRNAs in SLE (A) PPI network of DEmRNAs (B) The top 9 hubgenes analysed by Cytoscape.

Figure 7

Immune infiltration characteristics between SLE patients and controls. (A,B) GSEA analysis for SIRT1 and ESR1 in SLE group. (C) Infiltrating difference of immune cells between SLE patients and controls in the box plot. (D,E) Spearman correlation between immune cell subsets for SIRT1 and ESR1. The color of dots denotes the P value. The size of dots denotes the strength of correlation. (F) The relative percent of immune cell subsets in a bar plot. Statistical significance at the level of * <0.05, ** <0.01, and *** <0.001. SLE: Systemic lupus erythematosus; CON: Controls.