Multi-omics integration to characterize genetic influences on metabotypes of type 1 diabetes progression

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PROJECT SUMMARY Type 1 diabetes (T1D) is a chronic, autoimmune disease that affects 1.4 million people in the U.S, and its incidence is increasing. The preclinical period of T1D is called islet autoimmunity (IA) and is characterized by the detection of autoantibodies to pancreatic islet cells. Genetic and non-genetic factors contribute to the risk of T1D, though factors affecting the progression from preclinical IA to symptomatic T1D remain unclear. Metabolomics and associated genetic loci controlling metabolite levels (mtQTLs) can be powerful tools for understanding disease pathophysiology that have been underutilized in T1D research. Genes encode enzymes, and the downstream effect of genetic variation on enzymatic activity is captured by ratios between metabolites participating in biochemical reactions. Although several studies have identified individual metabolites associated with risk of T1D (T1D metabotypes), functional understanding of these compounds remains elusive since metabolites reflect both genetic and environmental influences. Characterization of T1D metabotype ratios and related genetic drivers therefore promises to deliver new insights into progression to T1D. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is the largest prospective T1D study in the world, following 8,676 children in Finland, Germany, Sweden, and the U.S. for the development of IA and T1D. In this initiative, we will leverage TEDDY’s robust multi-omics repository to: 1) Identify ratios of T1D metabotypes associated with progression from IA to T1D; 2) Estimate T1D metabotype and ratio heritability to elucidate the genetic vs. environmental contribution to metabolite variation at the time of seroconversion to IA and from infancy to seroconversion; 3) Perform mtQTL mapping to identify the genotypes that affect T1D-associated or highly heritable metabotypes and ratios, and quantify the relationship between mtQTLs, T1D metabotypes and ratios, and progression to T1D in a mediation analysis. Our team is uniquely positioned to replicate results in the Diabetes Autoimmunity Study in the Young (DAISY), which follows 2,547 children in Colorado for T1D using similar study design, case definitions, and genetics and metabolomics technologies as TEDDY. Findings from these aims will provide critical data for a future application to refine and pinpoint environmental contributions to metabolomics changes in T1D using multi-omics approaches. Furthermore, this study improves on previous metabolomics studies in T1D by incorporating cutting-edge approaches that integrate metabolomics and genetics to elucidate underlying processes in disease progression. Our characterization of genetic influences on metabolomics disturbances at this stage of disease will lay a foundation for the ongoing search for strategies to prevent or delay T1D progression in high-risk populations.