BACKGROUND: Recently, it was reported that circular RNAs (circRNAs) play the crucial role in many physiological and biological processes and can be used as biomarkers. However, the information about circRNAs in children with systemic lupus erythematosus (SLE) is limited. The aim of this study is to determine the expression of circRNAs in children with SLE and investigate the significance of circRNA for diagnosing SLE. METHODS: Microarray profile of circRNAs and mRNAs was performed for identifying the changes in expression of circRNAs and mRNAs between children with SLE and healthy children. Quantitative polymerase chain reaction (qPCR) was used to confirm the results. Spearman correlation test was performed to assess the correlation between circRNAs and clinical variables. The receiver operating characteristic (ROC) curve was calculated for evaluating the diagnostic value. RESULTS: A comparison between the children with SLE and healthy children revealed that 348 circRNAs and 1162 mRNAs were expressed differentially. The authors constructed a complex circRNA target network consisting of 307 matched circRNA-mRNA pairs for 124 differentially expressed circRNAs (74 circRNAs were upregulated, and 50 circRNAs were downregulated) and 142 differentially expressed mRNAs (83 mRNAs were upregulated, and 59 mRNAs were downregulated) by using gene co-expression network analysis. The competing for endogenous RNA (ceRNA) network includes 42 differentially expressed circRNAs, 41 differentially expressed mRNAs, and 71 predicted miRNAs. Among these SLE patients, we detected that the hsa_circ_0021372 and hsa_circ_0075699 levels are associated with C3 and C4 levels in children with SLE. The hsa_circ_0057762 level is positively associated with the SLEDAI-2K score. The ROC curves of circRNAs showed that the levels of hsa_circ_0057762 (AUC 0.804, 95% CI 0.607-1.0, P = 0.02) and hsa_circ_0003090 (AUC 0.848, 95% CI 0.688-1.0, P = 0.008) could differentiate the patients with SLE from the healthy controls. CONCLUSIONS: We firstly characterized the expression profiles of circRNA and mRNA in children with SLE and propose herein their possible roles in the pathogenesis of SLE. These results provide novel insight into the mechanisms of SLE pathogenesis, and circRNAs may serve as useful biomarkers for SLE.
BACKGROUND: Recently, it was reported that circular RNAs (circRNAs) play the crucial role in many physiological and biological processes and can be used as biomarkers. However, the information about circRNAs in children with systemic lupus erythematosus (SLE) is limited. The aim of this study is to determine the expression of circRNAs in children with SLE and investigate the significance of circRNA for diagnosing SLE. METHODS: Microarray profile of circRNAs and mRNAs was performed for identifying the changes in expression of circRNAs and mRNAs between children with SLE and healthy children. Quantitative polymerase chain reaction (qPCR) was used to confirm the results. Spearman correlation test was performed to assess the correlation between circRNAs and clinical variables. The receiver operating characteristic (ROC) curve was calculated for evaluating the diagnostic value. RESULTS: A comparison between the children with SLE and healthy children revealed that 348 circRNAs and 1162 mRNAs were expressed differentially. The authors constructed a complex circRNA target network consisting of 307 matched circRNA-mRNA pairs for 124 differentially expressed circRNAs (74 circRNAs were upregulated, and 50 circRNAs were downregulated) and 142 differentially expressed mRNAs (83 mRNAs were upregulated, and 59 mRNAs were downregulated) by using gene co-expression network analysis. The competing for endogenous RNA (ceRNA) network includes 42 differentially expressed circRNAs, 41 differentially expressed mRNAs, and 71 predicted miRNAs. Among these SLEpatients, we detected that the hsa_circ_0021372 and hsa_circ_0075699 levels are associated with C3 and C4 levels in children with SLE. The hsa_circ_0057762 level is positively associated with the SLEDAI-2K score. The ROC curves of circRNAs showed that the levels of hsa_circ_0057762 (AUC 0.804, 95% CI 0.607-1.0, P = 0.02) and hsa_circ_0003090 (AUC 0.848, 95% CI 0.688-1.0, P = 0.008) could differentiate the patients with SLE from the healthy controls. CONCLUSIONS: We firstly characterized the expression profiles of circRNA and mRNA in children with SLE and propose herein their possible roles in the pathogenesis of SLE. These results provide novel insight into the mechanisms of SLE pathogenesis, and circRNAs may serve as useful biomarkers for SLE.