eLifeGenetic & Genomic MedicinePeer-reviewed journal article
Polymorphisms in Intron 1 of HLA-DRA Differentially Associate with Type 1 Diabetes and Celiac Disease and Implicate Involvement of Complement System Genes C4A and C4B
Özkan AydemiriD, Jeffrey A. BaileyiD, Daniel AgardhiD, Åke LernmarkiD, Janelle Annette NobleiD, Agnes Andersson SvärdiD, Elizabeth P. BlankenhorniD, Hemang M. ParikhiD, Anette‐Gabriele ZiegleriD, Jorma ToppariiD, Beena AkolkariD, William HagopianiD, Marian J. RewersiD, John P. MordesiD, TEDDY Study Group
Abstract
Polymorphisms in genes in the human leukocyte antigen (HLA) class II region comprise the most important inherited risk factors for many autoimmune diseases including type 1 diabetes (T1D) and celiac disease (CD): both diseases are positively associated with the HLA-DR3 haplotype (DRB1*03:01-DQA1*05:01-DQB1*02:01). Studies of two different populations have recently documented that T1D susceptibility in HLA-DR3 homozygous individuals is stratified by a haplotype consisting of three single nucleotide polymorphisms ("tri-SNP") in intron 1 of the HLA-DRA gene. In this study, we use a large cohort from the longitudinal "The Environmental Determinants of Diabetes in the Young" (TEDDY) study to further refine the tri-SNP association with T1D and with autoantibody-defined T1D endotypes. We found that the tri-SNP association is primarily in subjects whose first-appearing T1D autoantibody is to insulin. In addition, we discovered that the tri-SNP is also associated with celiac disease (CD), and that the particular tri-SNP haplotype ("101") that is negatively associated with T1D risk is positively associated with risk for CD. The opposite effect of the tri-SNP haplotype on two DR3-associated diseases can enhance and refine current models of disease prediction based on genetic risk. Finally, we investigated possible functional differences between the individuals carrying high and low-risk tri-SNP haplotypes, and found that differences in complement system genes C4A and C4B may underlie the observed divergence in disease risk.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 0th percentile
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