Plasma-derived exosomal miRNA profiles associated with type 1 diabetes.

AIMS: Recently, exosomal miRNAs have been shown to play important roles in multiple diseases, including type 1 diabetes (T1D). To assess the biomarker potential of exosomal miRNAs for T1D, we measured the expression profiles of plasma-derived exosomal miRNAs in T1D and explored their potential functions by bioinformatic analysis. MATERIALS AND METHODS: In the discovery phase, exosome samples were isolated from plasma by size exclusion chromatography from 10 T1D patients and 10 sex- (p = 0.36), age- (p = 0.97), and body mass index-matched (p = 0.47) healthy control subjects. Exosomal miRNA expression profiles were measured using the Illumina NovaSeq 6000 platform. With verification by quantitative real-time PCR (qRT-PCR), we used multiple bioinformatics approaches to explore the potential biological functions of the identified differentially expressed miRNAs. The diagnostic signature of exosomal miRNAs was evaluated by least absolute shrinkage and selection operator (LASSO) regression and evaluated based on the area under the receiver operating characteristic curve (AUC). RESULTS: In total, 43 differentially expressed miRNAs, among which 34 were upregulated and 9 were downregulated, were identified in T1D. After correcting for multiple testing using false discovery rate, 11 identified exosomal miRNAs still showed statistical significance. Among the 5 selected miRNAs, 3 miRNAs (miR-103a-3p, miR-144-5p and miR-454-3p) were successfully validated by qRT-PCR. The biological analysis-enriched terms included protein autophosphorylation and the Hedgehog signalling pathway. The highest AUC of exosomal miRNA was 0.889 under the LASSO model. The expression levels of 5 selected exosomal miRNAs were correlated with multiple clinical characteristics such as fasting C-peptide and postprandial C-peptide. CONCLUSIONS: Our results indicated that plasma-derived exosomal miRNAs could serve as promising diagnostic biomarkers of T1D.

Hsa_circRNA_405498 and hsa_circRNA_100033 Serve as Potential Biomarkers for Differential Diagnosis of Type 1 Diabetes.

CONTEXT: The role of circular RNAs (circRNAs) in type 1 diabetes (T1D) is largely unknown. OBJECTIVE: We aimed to identify some circRNAs as differential diagnostic biomarkers for T1D to distinguish between 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 real-time quantitative polymerase chain reaction 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 individuals, 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 < .05). Moreover, the expression levels of these 2 circRNAs showed sequential downregulation from controls, patients with T2D, LADA, to T1D (P < .05). The area under the curve (AUC) of receiver operating characteristic plots in logistic LASSO regression model showed high diagnostic accuracy for combination model with the 2 circRNAs and some clinical parameters in distinguishing T1D from LADA (AUC = 0.915), T2D (AUC = 0.993), and controls (AUC = 0.992). CONCLUSION: Our study demonstrated that hsa_circRNA_405498 and hsa_circRNA_100033 are promising novel differential diagnostic biomarkers for T1D.