Type 1 diabetes (T1D) results from chronic autoimmune responses against pancreatic beta cells, leading to their virtually complete eradication and consequently loss of insulin secretion. There is an unmet need to discover novel biomarkers that better mark disease activity and beta cell destruction. Novel biomarkers could improve our ability to identify at-risk individuals before autoantibody conversion, for early intervention, and could help staging disease progression more precisely to facilitate risk stratification and better guide enrollment into trials. Our overall goal is to discover and validat circulating microRNAs (miRNAs) that can be exploited as novel biomarkers of islet autoimmunity. MiRNAs are small, non-coding RNA molecules that regulate gene expression in cells. MiRNAs regulate virtually all pathways, including those relevant to T1D, such as key functions of the immune system and pancreatic beta cells, their development and regeneration. MiRNAs are also present and remarkably stable in serum and plasma. Circulating miRNA biomarkers are reported in many conditions, both acute and chronic, but remain largely unexplored in T1D. This is a joint application from research groups at the Henry Ford Health System (HFHS) in Detroit and the University of Miami (UM). Each group has independently discovered associations of selected miRNAs with T1D. Our preliminary data involve large and well-characterized clinical cohorts from the Type 1 Diabetes TrialNet and the Diabetes Prevention Trial-Type 1 (DPT-1). Comparison of our data reveals that many of the miRNAs we independently found associated with islet autoimmunity and/or T1D were observed in both studies. This concordance provides compelling rationale to conduct further studies of circulating miRNAs in T1D, and gave us impetus to present this application, combining our complementary expertise and data, believing that this joint effort will be strongly synergistic and will powerfuly impact the discovery and validation of miRNA biomarkers for T1D. We propose the following aims: 1) Examine serum miRNAs as biomarkers of diabetes progression in two large data sets of progressors versus slow/non-progressors, both through cross-sectional and longitudinal analyses; 2) Examine the relationship of miRNA biomarkers to autoantibodies, in longitudinal studies of the TrialNet cohort, to determine if miRNAs identify a group or relatives destined to acquire autoantibodies and could serve as early biomarkers preceding autoantibody conversion; 3) Examine whether relatives with highly susceptible and protective HLA haplotypes have different patterns of circulating miRNAs, in relation to diabetes progression; 4) Construct composite predictive models incorporating multiple prognostic miRNAs and other biomarkers (genetic, immunological, metabolic) available from the parent studies. This multiple-PI proposal is led by experts in T1D, statistics, biomarker discovery and prediction studies in the DPT-1/TrialNet cohorts, biomarker data mining, and miRNA studies both at the preclinical and clinical levels.
Type 1 diabetes causes lifelong insulin-dependence, with increased morbidity and mortality from both acute and chronic complications. There is an unmet need for novel biomarkers that can improve disease prediction, including risk stratification and staging of disease progression, that would impact design of clinical trials and ultimately support the development of new therapies. This project aims at identifying circulating microRNAs that can be exploited as novel biomarkers in type 1 diabetes and develop new and more accurate composite predictive models.
