Department of Endocrinology and Metabolism, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
J Clin Endocrinol Metab. 2018 Apr 1;103(4):1320-1329. doi: 10.1210/jc.2017-01417.
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.
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).
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.
在 1 型糖尿病（T1DM）的进展中，需要新的策略和生物标志物来早期检测β细胞损伤。
探讨血清 microRNAs（miRNA）是否可作为 T1DM 的生物标志物。
设计、地点和患者：在发现阶段（6 例 T1DM，6 例对照）使用 miRNA 微阵列建立 miRNA 图谱。使用逻辑回归分析在训练数据集（40 例 T1DM，56 例对照）中开发基于 miRNA 的 T1DM 诊断模型，然后使用留一法交叉验证和另一个独立验证数据集（33 例 T1DM，29 例对照）进行验证。
采用实时定量逆转录聚合酶链反应（qRT-PCR）证实 T1DM 与对照组之间候选 miRNA 的差异。接受者操作特征（ROC）曲线下面积（AUC）用于评估诊断准确性。使用 INS-1 细胞、链脲佐菌素处理的小鼠（n=4）和非肥胖型糖尿病（NOD）小鼠（n=12）评估 miRNA 与β细胞损伤的关系。
基于在发现阶段鉴定的 6 个候选差异表达 miRNA，在训练数据集中建立了具有高 T1DM 诊断准确性的 miRNA 模型（AUC=0.817）。验证数据集显示该模型具有令人满意的诊断性能（AUC=0.804）。miR-1225-5p 和 miR-320c 的分泌在链脲佐菌素处理的小鼠和 INS-1 细胞中显著增加。值得注意的是，在 NOD 小鼠糖尿病进展过程中葡萄糖升高之前，就观察到了这两种 miRNA 的升高。
在近期发生的 T1DM 患者中鉴定出与β细胞损伤相关的两个 miRNA 生物标志物（miR-1225-5p 和 miR-320c）。本研究中建立的基于 miRNA 的模型在 T1DM 诊断中表现出良好的性能。
