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.