Type 1 diabetes (T1D) is a complex autoimmune disorder that arises from the action of multiple genetic and environmental risk factors and can affect up to 1 in 300 children. In 2001, the Type 1 Diabetes Genetics Consortium (T1DGC) was established with the goals of conducting large-scale genetic studies to identify regions in the genome that contribute to T1D risk and making available the assembled data and biospecimens to the broader scientific community. The T1DGC has been highly successful conducting the most robustly powered studies of T1D using (a) candidate genes, (b) variants in the MHC, (c) genome-wide linkage, and (d) genome-wide association scan (GWAS). From our GWAS meta-analysis of over 16,000 cases and controls, 18 newly identified loci were reported at genome-wide significance (P d 5 x 10-8), including replication evidence in an independent set of 4,267 cases, 4,463 controls and 2,319 families. This brought the total number of T1D loci to 42. We have now conducted follow-up genotyping of the novel 18 loci, and conducted dense SNP mapping (using the ImmunoChip) in all known T1D loci. We have discovered a single T1D candidate gene in the majority of these loci. The loci from GWAS discovered through analysis of common genetic variants explain less than 15% of the total genetic liability of T1D (after the 50% contributed by genes in the MHC). The residual genetic risk (""""""""missing heritability"""""""") may be due to rare variants that are found in coding regions of genes. These rare coding variants are likely to be functional with large effects on risk. Unlike common variants, DNA sequencing of these coding and regulatory regions is required for discovery of rare functional variants. The sequencing effort, even of the coding regions (the """"""""exome"""""""") is performed at significant cost. For testing association of T1D with rare variants, a genotyping array (the ExomeChip) has been designed from over 12,000 human exomes. This custom array will permit testing of rare variants by genotyping large numbers of samples at reduced cost. The ExomeChip contains ~200,000 non-synonymous, non-sense, and splice-site variants, as well as 100,000 variants for additional content (including MHC variants). The primary aims of this grant application are to discover novel genetic risk factors that contribute to risk of T1D by 1) conducting ExomeChip genotyping in a well-characterized collection of 2,500 T1DGC affected sib pair (ASP) families;2) performing analyses of the ExomeChip data (both single SNP and burden tests) in order to discover new genes whose functionally significant variants influence risk to T1D;and 3) replicating these novel results by targeted sequencing in ~7,000 T1D cases and ~7,000 controls. We will integrate existing data (HLA typing, ImmunoChip, CNV, ExomeChip) to provide a comprehensive analysis of rare, common, and structural variation associated with T1D risk. These findings should lead to novel pathways of etiology and avenues for T1D prediction, prevention and therapy.

Public Health Relevance

Type 1 diabetes (T1D) is a common autoimmune disease that results from pancreatic b cell destruction, mediated by both genetic and non-genetic factors. We discovered over 40 regions in the genome with significant associations with common genetic variants and have identified the most likely candidate genes. Despite this success, there remains genetic risk unresolved, likely due to rare variants found in coding regions of genes. We propose to use a custom genotyping array (the ExomeChip) to discover the genes and pathways involved in T1D risk due to rare variants, with an ultimate goal of developing novel avenues for T1D prediction, prevention and therapy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK096926-03
Application #
8668054
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Akolkar, Beena
Project Start
2012-07-01
Project End
2016-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Virginia
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
Robertson, Catherine C; Rich, Stephen S (2018) Genetics of type 1 diabetes. Curr Opin Genet Dev 50:7-16
Rich, Stephen S; Cefalu, William T (2016) The Impact of Precision Medicine in Diabetes: A Multidimensional Perspective. Diabetes Care 39:1854-1857
Onengut-Gumuscu, Suna; Chen, Wei-Min; Burren, Oliver et al. (2015) Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers. Nat Genet 47:381-6