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J Clin Endocrinol Metab. 2018 Jan 23. doi: 10.1210/jc.2017-01417. [Epub ahead of print]

Two novel microRNA biomarkers related to β-cell damage and their potential values for early diagnosis of type 1 diabetes.

Liu L1,2,3, Yan J1,2, Xu H1,2, Zhu Y4, Liang H1,2, Pan W1,2, Yao B1,2, Han X4, Ye J5, Weng J1,2.

Author information

1
Department of Endocrinology and Metabolism, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
2
Guangdong Provincial Key Laboratory of Diabetology, Guangzhou, Guangdong, China.
3
Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
4
Key Laboratory of Human Functional Genomics of Jiangsu Province, Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, Jiangsu, China.
5
Antioxidant and Gene Regulation Lab, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA.

Abstract

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 should be served as biomarkers for T1DM.

Design, Settings and Patients:

The serum microRNA profile was established with microRNA microarray in discovery phase (6 T1DM, 6 controls). A microRNA-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 Measure(s):

Quantitative RT-PCR was applied to confirm the differences of candidate microRNAs between T1DM and controls. Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy. INS-1 cells, streptozocin-treated mice (n=4) and NOD mice (n=12) were used to evaluate the association of microRNAs with β-cell damage.

Results:

A microRNA-based model was established in the training dataset with high diagnostic accuracy for T1DM (AUC=0.817) based on six candidate differential expressed microRNAs 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 streptozocin-treated mice and INS-1 cells. Noteworthy, the elevation of these two microRNAs was observed before glucose elevation in the progress of diabetes in NOD mice.

Conclusions:

Two microRNA biomarkers (miR-1225-5p and miR-320c) related to β-cell damage were identified in recent-onset T1DM patients. The microRNA-based model established in this study exhibited a good performance in diagnosis of T1DM.

PMID:
29370422
DOI:
10.1210/jc.2017-01417

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