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

> **NIH NIH R03** · UNIVERSITY OF COLORADO DENVER · 2020 · $155,500

## Abstract

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.

## Key facts

- **NIH application ID:** 10133276
- **Project number:** 1R03DK127472-01
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Randi Kay Johnson
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $155,500
- **Award type:** 1
- **Project period:** 2020-09-15 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10133276

## Citation

> US National Institutes of Health, RePORTER application 10133276, Multi-omics integration to characterize genetic influences on metabotypes of type 1 diabetes progression (1R03DK127472-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10133276. Licensed CC0.

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