Serum miRNAs as potential biomarkers for early prediction of type 1 diabetes

Document Type

Conference Proceeding

Publication Date


Publication Title

FASEB Journal


Background The incidence of type 1 diabetes (T1D), a T cell-mediated beta cell destructive autoimmune disease, has been increasing about 3-4% annually for several decades. Individuals at risk for T1D are diagnosed at a late stage when the possibility for disease prevention is absent. Autoantibodies (AA) to islet antigens such as islet antigen (IA)-2, IA-2b, and glutamate decarboxylase (GAD65) appear earlier before T1D onset and are used for early T1D prediction. However, the appearance of islet AA marks a relatively late stage of the autoimmune process and therefore is not suitable for early disease intervention. More importantly AA lack causal relationship with the pathogenesis of T1D. Therefore, there is an urgent need for better (increased specificity/sensitivity) and earlier (predating autoantibodies) markers for the prediction of AA development. MicroRNAs (miRNAs) have emerged as an important regulatory factors in pancreatic β-cell development, homeostasis, function, and in a variety of immune cell development, differentiation and function. Our recent study showed that miRNAs regulate T1D development and serum miRNAs are potential biomarkers for T1D progression in mouse models. Our objective here is to identify specific serum miRNA biomarkers for earlier and better prediction of individuals at risk for T1D in human. Method We performed serum miRNA expressions profiles in 35 AA positive (IAA and ICA) non-T1D subjects and 40 AA negative relative subjects from the Diabetes Prevention Trial-Type 1 (DPT-1) cohort, using the TaqMan low-density arrays. miRNAs with changed expression level were further confirmed by a single TaqMan RT-PCR. Result 9 miRNAs (miR-146a, miR-561 and miR-548a-3p, miR-184 and miR-200a) were down-regulated and 2 miRNAs (miR-30c and miR-487a) are up-regulated in the serum of AA+ non-T1D subjects compared to that from AA- subjects (two-sample t-test P<0.05). In addition, a cluster of five miRNAs (miR-146a, miR-197, miR-193b, miR-574-3p, and miR-561) was identified to clearly separate AA+ subjects from AA- subjects with higher sensitivity and specificity ( LASSO logistic regression). miRNA target and pathway prediction analyses revealed that some of these miRNAs are related to immune function and beta-cell homeostasis and potentially involved in autoimmune processes. Conclusion We have identified distinct serum miRNA expressions profiles in AA+ subjects compared to AA- subjects. These serum miRNAs could serve as potential biomarkers for early prediction of autoimmune processes in individuals at risk for T1D, which need to be further confirmed in the future studies.



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