[HTML][HTML] Genetics of type 1 diabetes: what's next?

F Pociot, B Akolkar, P Concannon, HA Erlich, C Julier… - Diabetes, 2010 - ncbi.nlm.nih.gov
F Pociot, B Akolkar, P Concannon, HA Erlich, C Julier, G Morahan, CR Nierras, JA Todd
Diabetes, 2010ncbi.nlm.nih.gov
The discovery of the association between HLA in the major histocompatibility complex
(MHC) on chromosome 6p21 with type 1 diabetes, but not with type 2 diabetes, suggested
that these disease entities were of different genetic background and pathogenesis. The
discovery that some individuals with diabetes had autoantibodies in their blood provided
additional evidence that type 1 diabetes had an autoimmune origin. Recently, increasing
knowledge of the genome, coupled with rapidly improving genotyping technology and …
The discovery of the association between HLA in the major histocompatibility complex (MHC) on chromosome 6p21 with type 1 diabetes, but not with type 2 diabetes, suggested that these disease entities were of different genetic background and pathogenesis. The discovery that some individuals with diabetes had autoantibodies in their blood provided additional evidence that type 1 diabetes had an autoimmune origin. Recently, increasing knowledge of the genome, coupled with rapidly improving genotyping technology and availability of increasingly large numbers of samples, has enabled statistically robust, systematic, genome-wide examinations for discovery of loci contributing to type 1 diabetes susceptibility, including within the MHC itself. Currently, there are over 50 non-HLA regions that significantly affect the risk for type 1 diabetes (http://www. t1dbase. org). Many of these regions contain interesting, but previously unrecognized, candidate genes. A few regions contain genes of unknown function or no known annotated genes, suggesting roles for long-distance gene regulatory effects, noncoding RNAs, or unknown mechanisms. Against a background of ever-improving knowledge of the genome, particularly its transcriptional regulation, and with massive advances in sequencing, specific genes, rather than regions that impinge upon type 1 diabetes risk, will be identified soon. Here we discuss follow-up strategies for genome-wide association (GWA) studies, causality of candidate genes, and genetic association in a bioinformatics approach with the anticipation that this knowledge will permit identification of the earliest events in type 1 diabetes etiology that could be targets for intervention or biomarkers for monitoring the effects and outcomes of potential therapeutic agents. The International Type 1 Diabetes Genetics Consortium (T1DGC) has established significant resources for the study of genetics of type 1 diabetes. These resources are available to the research community and provide a basis for future discovery in the transition from gene mapping to discovery of disease mechanisms.
The T1DGC (http://www. t1dgc. org) is an international research program established in 2002 whose primary aims are to 1) discover genes that modify risk of type 1 diabetes and 2) expand on existing genetic resources for type 1 diabetes research (1). Over the last 7 years, the T1DGC has assembled a collection of 4,000 type 1 diabetes affected sib-pair (ASP) families for genetic studies. In addition to building this resource, consortium members have provided access to large case-control collections for specific T1DGC genotyping studies. Building on these assets, four major research projects have been performed: an exhaustive examination of the HLA region by single nucleotide polymorphism (SNP) genotyping and high-resolution HLA typing; a detailed investigation of published candidate genes; a genome-wide linkage scan; and a GWA study and meta-analysis. Importantly, T1DGC data and bio-specimens used in these studies have been made available to the research community. The T1DGC continues to build on these resources to help identify the inherited events in the pathogenesis of type 1 diabetes. The etiology of human type 1 diabetes is still largely obscure, but it is recognized that both genetic and environmental factors are important in defining disease risk (2). This is supported by observations showing that the proband-wise concordance for monozygotic (MZ) twins is estimated to be 50%(compared with 8% for dizygotic [DZ] twins)(3). These MZ twins have the whole range of population genetic risk profiles for type 1 diabetes, and if they were all high-risk …
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