Background Islet cell death is a common feature of type 1 diabetes (T1D), including after islet cell transplantation, as well as of type 2 diabetes (T2D). As of today, we lack tools to quantitatively detect islet cell loss prior to the clinical onset of diabetes, or to predict the progression of established diabetes. Our preliminary data demonstrates that a signature of 20 different non-coding (nc) RNAs (including microRNAs) reflects beta cell death (RAPID: RNA-based Analysis for Prediction of Islet Death signature). Objectives 1)To identify a high-throughput platform for detection of ncRNAs/microRNAs 2)To validate the RAPID signature of 20 ncRNAs using this high-throughput platform 3)To test the suitability of these ncRNA biomarkers in predicting the progression to T1D Method Next Generation Sequencing (NGS) studies on developing human pancreas have led to the identification of specific ncRNAs that are found to be expressed specifically in the human pancreatic islets. We use combined FISH and immunostaining to confirm the localization of each miRNA in human islets. TaqMan-based real-time PCR on plasma from at-risk diabetic individuals and age/gender matched controls in a longitudinal study, is used to measure the abundance of specific ncRNAs in plasma-EDTA samples of individuals at risk of T1D. I will discuss the comparison of 2 different ultra-high-throughput TaqMan real-time PCR platforms that we use to analyze these samples and present the data demonstrating the suitability of these RNA-based biomarkers in predicting the progression to T1D. Results Present study has allowed us to validate a microRNA-based signature of islet cell death in diabetes. Using a cohort of kids at risk of T1D, we demonstrate the suitability and advantages of these ncRNA biomarkers over traditional / conventional antibody- and glucose-based detection. The development of an assay for early detection of islet injury and death has direct applications in clinical medicine. Hopefully, this study results will inform medical researchers as to how to predict the development of Type 1 diabetes, monitor response to interventions such as islet transplantation, vaccines and drugs that aim to retard beta cell loss or promote beta cell regeneration.


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