Hsa_circRNA_405498 and hsa_circRNA_100033 serve as potential biomarkers for differential diagnosis of type 1 diabetes
Ziwei Zhang, Shuoming Luo, Zilin Xiao, Wenfeng Yin, Xiajie Shi, Hongzhi Chen, Zhiguo Xie, Zhenqi Liu, Xia Li, Zhiguang Zhou- Biochemistry (medical)
- Clinical Biochemistry
- Endocrinology
- Biochemistry
- Endocrinology, Diabetes and Metabolism
Abstract
Purpose
The role of circular RNAs (circRNAs) in type 1 diabetes (T1D) is largely unknown. We aimed to identify some circRNAs as differential diagnostic biomarkers for T1D to discriminate patients with latent autoimmune diabetes in adults (LADA), and type 2 diabetes (T2D).
Methods
The circRNA expression profiles were determined by Arraystar human circRNA microarray in T1D compared to controls (n = 6 each). The differentially expressed circRNAs were validated by RT-qPCR using a validation cohort with 20 T1D and 20 controls. The diagnostic performances of the candidate circRNAs and the clinical parameters were assessed using the logistic least absolute shrinkage and selection operator (LASSO) regression model in a larger cohort with 457 subjects including patients with T1D, T2D and LADA, and controls.
Results
We identified 110 differentially expressed circular transcripts (53 upregulated and 57 downregulated) in T1D patients compared with controls. Further analysis showed that the levels of hsa_circRNA_405498 and hsa_circRNA_100033 were significantly downregulated in T1D compared to controls (both P < 0.05). Moreover, the expression levels of these two circRNAs showed sequential downregulation from controls, patients with T2D, LADA, to T1D (P < 0.05). The area under the curve (AUC) of receiver operating characteristic (ROC) plots in logistic LASSO regression model showed high diagnostic accuracy for combination model with the two circRNAs and some clinical parameters in discriminating T1D from LADA (AUC = 0.915), T2D (AUC = 0.993), and controls (AUC = 0.992).
Conclusions
Our study demonstrated that hsa_circRNA_405498 and hsa_circRNA_100033 are promising novel differential diagnostic biomarkers for T1D.