Summary:
Type 1 diabetes (T1D) is a metabolic disease currently without a cure that results in destruction of insulin-
producing ß cells of the pancreas via an autoimmune response. T1D treatment requires insulin administration
and greatly reduces life quality and expectancy. Development and persistence of islet autoimmunity (IA) can be
determined by circulating autoantibodies against islet proteins. However, novel biomarkers are needed to: 1)
better understand the mechanisms that trigger and drive IA; and 2) predict individual progression through the
stages of the disease. To identify new biomarkers, we have recently completed a plasma proteomics analysis
for The Environmental Determinants of Diabetes in the Young (TEDDY). This nested case-control study 1
(NCC1) included 401 children who developed IA (at median age of 21 months) and 94 children who progressed
to clinical T1D (at median age of 29 months), matched against controls. We identified 376 proteins as candidate
biomarkers; 83 of these proteins were validated as significant predictors of either IA or progression to T1D in
longitudinal analyses of 6,426 samples. We also identified panels of proteins that can predict, with high accuracy,
development of islet autoimmunity (AUC=0.918) and progression to T1D (AUC=0.871) 6 months prior to
seroconversion by machine learning analysis. Limitations of the TEDDY NCC1 included limited follow-up and
very young age (=6 years) of the participants. IA and progression to T1D can occur over a much broader age
range, and the cellular and systemic processes involved may differ in younger vs older children. In the next case
control study 2 (NCC2), TEDDY monitored individuals until 15 years of age, an additional 501 participants
developed IA (at median age of 89 months) and an additional 345 progressed to T1D (at median age of 108
months). Here we propose to perform a longitudinal analysis of the NCC2 samples with a highly multiplexed,
sensitive, and robust targeted proteomics analysis to simultaneously validate biomarkers identified in the NCC1
and to provide information about the biological processes regulated during disease development. More
specifically, we propose the following specific aims: (I) validate predictive biomarkers of islet autoimmunity; (II)
validate predictive biomarkers of progression to T1D; and (III) determine mechanisms underlying development
of IA and progression to T1D. To fulfill these aims we will perform a large-scale targeted proteomics analysis of
8 time points from 48 months pre-seroconversion to 12 months post-seroconversion of individuals that only
developed islet autoimmunity and individuals that developed clinical diabetes, paired with controls, totaling 6,400
samples. The results of this project should bring the field one step closer to developing clinical biomarkers and
associated assays that can predict all phases of T1D development in addition to identifying possible causes.
This knowledge gained will likely open opportunities to develop preventive interventions against T1D.
