Circular RNA expression profile of systemic lupus erythematosus and its clinical significance as a potential novel biomarker

Abstract

Background: Circular RNAs (circRNAs) are a class of endogenous noncoding RNAs that are more abundant, specific, and highly organized than linear RNAs. Increasing evidence supports that circRNAs may serve as diagnostic biomarkers in many diseases, but their potential as biomarkers in systemic lupus erythematosus (SLE) remains unclear.

Objective: We investigated the critical circRNAs involved in SLE progression and explored their potential application as biomarkers in SLE.

Method: RNA sequencing was conducted on peripheral blood mononuclear cells (PBMCs) from 4 SLE patients and 4 healthy volunteers. CircRNA profile data were analyzed to identify differentially expressed circRNAs and visualized via R software. After screening, qPCR analysis of target circRNA expression was performed using PBMCs from 31 SLE patients and 35 healthy volunteers. Correlations between circRNA expression levels and the SLEDAI score were assessed via Spearman correlation analysis. Finally, the performance of circRNAs as biomarkers in SLE was examined by receiver operating characteristic curve analysis.

Results: The result identified six differentially expressed circRNAs between SLE patients and healthy controls: hsa_circ_0006689, hsa_circ_0070562, hsa_circ_0006117, hsa_circ_0007683, hsa_circ_0042519, and hsa_circ_0008647. The validation analysis showed differing relative expression levels of hsa_circ_0007683, hsa_circ_0042519, hsa_circ_0008647, and hsa_circ_0006689 between SLE patients and healthy volunteers (P < 0.05), and hsa_circ_0006689 expression in PBMCs correlated with the SLEDAI score (P < 0.05). Furthermore, addition of hsa_circ_0006689 expression increased the sensitivities of anti-dsDNA antibody and anti-Sm antibody levels for SLE diagnosis (from 29.03 to 61.30% and 32.26-71.00%, respectively).

Conclusion: Our results suggest hsa_circ_0006689 may be a useful circRNA biomarker for SLE diagnosis and prognosis.

Keywords: RNA sequencing; Systemic lupus erythematosus (SLE); circRNAs; hsa_circ_0006689.

Fig. 1

Volcano plot and heatmap of differentially expressed circRNAs between 4 SLE patients and 4 healthy volunteers (A) Heatmap analysis showed distinguishable circRNA expression profiles between the two groups. (B)The volcano plots displayed 195 down-regulated circRNAs and 167 up-regulated circRNAs (P values < 0.05, |log2(FC)| >1)

Fig. 2

Functional and pathway enrichment analyses from differentially expressed circRNAs in SLE patients. (A) Biological process GO analysis; (B) cell component GO analysis; and (C) molecular function GO analysis of differentially expressed circRNAs in SLE. (D) KEGG enrichment analysis of differentially expressed circRNAs in SLE.

Fig. 3

qPRC validation of the differential expression of circRNAs in PBMCs from SLE patients and healthy controls (HC). (A-D) Relative expression levels of differentially expressed circRNAs in SLE patients compared with healthy controls as determined by qPCR.

Fig. 4

Correlation of circRNAs expression and SLEDAI score. (A-F) Spearman correlation analysis showed that only the expression level of hsa_circ_0006689 in PBMCs was correlated with the SLEDAI score (P < 0.05)

Fig. 5

Sensitivity and specificity of different biomarkers for the diagnosis of SLE. ROC curve analysis was conducted, and AUC values were determined. (A) ROC curve analysis of hsa_circ_0006689 in the SLE and healthy control groups. (B) ROC curve analysis for the combination of hsa_circ_0006689 and other current diagnostic biomarkers in the SLE and healthy control groups