Identifying cell-type specific genetic control of T1D risk variants in TEDDY

NIH RePORTER · NIH · R01 · $1,467,161 · view on reporter.nih.gov ↗

Abstract

Type 1 diabetes (T1D) is a complex disorder that arises from the action of multiple genetic and environmental risk factors with population cumulative risk approaching 1 in 300 children. The disease process for T1D consists of initiation of an immune attack targeted to insulin secreting beta cells in the islets, modifying, impairing, and (ultimately) destroying the beta cells. Genome- wide association studies (GWAS), performed by ourselves and others, identified more than 100 chromosomal loci where there is significant, replicated evidence of association with T1D. As shown by us in the Type 1 Diabetes Genetic Consortium ImmunoChip fine-mapping analysis, and other studies, ~ 98-99% of T1D credible set of SNPs are in the non-coding region of the genome and preferentially map in enhancer regions active in immune cells. The proposed study is an ancillary research project of the Environmental Determinants of Diabetes in the Young (TEDDY) study. TEDDY was designed to discover environmental triggers of T1D in a prospective cohort of newborns at genetic risk, followed multiple times per year with collection of samples for deep phenotypic and biomarker profiling. This project will utilize longitudinal samples and their rich demographic, genetic, and immune markers collected on TEDDY participants. We will use single-cell sequencing technology to monitor immune markers at the protein and transcription levels to generate profiles for different stages of islet autoimmunity. To gain a comprehensive understanding of the T1D risk genes that function in initiation and progression of islet autoimmunity, we propose to apply single-cell sequencing to map T1D risk variants that alter gene expression in circulating immune cells; we will use immune cell-surface markers for cell type identification and examine immune profiles at initiation and progression to T1D. To identify biological pathways, that T1D genes function in, we will construct a reference co-expression network and refine predicted gene-gene interactions with Bayesian networks.

Key facts

NIH application ID
10797290
Project number
1R01DK138367-01
Recipient
UNIVERSITY OF VIRGINIA
Principal Investigator
Suna Onengut
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$1,467,161
Award type
1
Project period
2024-02-01 → 2027-01-31