Objective
In this application, we are proposing to evaluate novel biomarkers of progression to clinical diabetes among subjects in early-stage type 1 diabetes. In addition, we will create one of the largest datasets of early-stage type 1 diabetes participants by combining several ongoing prospective cohorts and including continuous glucose monitoring data with C-peptide, autoantibody and demographic data to evaluate the most accurate and easily implemented tools for monitoring at risk individuals.
Background Rationale
Type 1 diabetes is one of the most prevalent severe chronic diseases of childhood. The high incidence, associated severe morbidity, mortality, and associated health care expenditures make type 1 diabetes a prime target for prevention. With the recent FDA approval of the first drug (teplizumab) to slow progression of early-stage type 1 diabetes, there is a critical need for accurate, efficient and easily utilized tools for monitoring at risk individuals in the clinical setting in order to recognize imminent transition to clinical type 1 diabetes and identify those eligible for preventative therapies. These studies are likely to contribute significantly to the prediction of type 1 diabetes and monitoring of early-stage type 1 diabetes. Determining accurate and easily implemented tools for monitoring at risk individuals is a prerequisite for the implementation of general population screening for early-stage type 1 diabetes.
Description of Project
This project will evaluate biomarkers for monitoring individuals in early-stage type 1 diabetes, including continuous glucose monitoring data. We will also incorporate demographic data, autoantibody levels and classic measurements of beta cell function (C-peptide) to identify the most accurate, easily implemented, and efficient tools for monitoring at risk individuals and translate these evidence-based models into clinical care. In addition, we will test a novel home-based measure of beta cell function in our ongoing Autoimmunity Screening for Kids (ASK) general population study. The subjects have been and will continue to be consented so that they can participate in future studies and be, as in our prior studies, partners in our research.
Anticipated Outcome
Among our large population of subjects with early-stage type 1 diabetes, we will identify novel biomarkers and tools for monitoring individuals at risk for clinical type 1 diabetes.
Relevance to T1D
Identification of accurate and easily implemented tools for monitoring at risk individuals will provide the basis for general population screening for early-stage type 1 diabetes. These tools will be critical in moving from current clinical research monitoring programs for early-stage type 1 diabetes to evidence-based clinical care models.