Context: New strategies and biomarkers are needed in the early detection of β-cell damage in the progress of type 1 diabetes mellitus (T1DM).
Objective: To explore whether serum microRNAs (miRNA) should be served as biomarkers for T1DM.
Design, settings, and patients: 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).
Main outcome measures: 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.
Results: 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.
Conclusions: 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.