Abstract

New strategies and biomarkers are needed in the early detection of β-cell damage in the progress of type 1 diabetes mellitus (T1DM). To explore whether serum microRNAs (miRNA) should be served as biomarkers for T1DM. The miRNA profile was established with miRNA microarray in discovery phase (six T1DM, six controls). A miRNA-based model for T1DM diagnosis was developed using logistic regression analysis in the training dataset (40 T1DM, 56 controls) and then validated with leave-one-out cross validation and another independent validation dataset (33 T1DM, 29 controls). Quantitative reverse transcription polymerase chain reaction was applied to confirm the differences of candidate miRNAs between T1DM and controls. Area under the receiver-operating characteristic (ROC) curve (AUC) was used to evaluate diagnostic accuracy. INS-1 cells, streptozotocin-treated mice (n = 4), and nonobese diabetic (NOD) mice (n = 12) were used to evaluate the association of miRNAs with β-cell damage. A miRNA -based model was established in the training dataset with high diagnostic accuracy for T1DM (AUC = 0.817) based on six candidate differential expressed miRNAs identified in discovery phase. The validation dataset showed the model's satisfactory diagnostic performance (AUC = 0.804). Secretions of miR-1225-5p and miR-320c were significantly increased in streptozotocin-treated mice and INS-1 cells. Noteworthy, the elevation of these two miRNAs was observed before glucose elevation in the progress of diabetes in NOD mice. Two miRNA biomarkers (miR-1225-5p and miR-320c) related to β-cell damage were identified in patients with recent-onset T1DM. The miRNA-based model established in this study exhibited a good performance in diagnosis of T1DM.

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