Background & Purpose

JDRF and Janssen’s Disease Interception Accelerator are soliciting applications to discover and develop candidate biomarkers of progression in the at-risk setting for type 1 diabetes (T1D). JDRF is committed and most interested in investigator-initiated proposals that focus on research with potential for clinical utility.

Validated biomarkers that detect risk, stage the disease, and predict its rate of progression in the at-risk setting for T1D are required to provide a framework for clinical trial design, benefit/risk decisions around interventions, and ultimately for the practice of predictive medicine to prevent symptomatic T1D. These biomarkers may include markers of beta cell stress, dysfunction, and damage, functional beta cell mass, autoimmune/inflammatory biomarkers, and/or biomarkers of impaired glucose and metabolic control. While progress has been made in identifying predictive markers for risk of T1D, there may be alternative molecular biomarkers (metabolites, proteomics, gene expression patterns, additional autoantibodies, etc.) that may prove to be expressed earlier, be more highly predictive, and/or more cost effective for detecting risk. Biomarkers that detect activation of innate immunity or of T cells specific for beta cells, islet inflammation or beta cell stress, dysfunction or damage may be demonstrated to serve this role. For prevention approaches to succeed it is also important to develop other biomarkers associated with progression that can be used both as prognostic biomarkers to design trials and tailor therapy and as predictive biomarkers of efficacy of preventive interventions to accelerate clinical development. Biomarkers that detect very early beta cell inflammation or beta cell stress, dysfunction or damage, beta cell specific autoimmune responses, dysglycemia, or insulin resistance may be demonstrated to serve this role. Non-invasive imaging biomarkers to detect islet inflammation and beta cell mass could prove critical for more accurate staging and monitoring progression, may help determine whether the disease can have a relapsing/remitting pattern, and may be used for assessing response to interventions. It is likely that a combination of biomarkers will be required to accurately stage and better predict rate of progression.