The past, present, and future of genetic associations in type 1 diabetes.
ABSTRACT Type 1 diabetes mellitus (T1DM) is an autoimmune disease affecting approximately one in 300 individuals in the United States. The majority of genetic research to date has focused on the heritability that predisposes to islet autoimmunity and T1DM. The evidence so far points to T1DM being a polygenic, common, complex disease with major susceptibility lying in the major histocompatibility complex (MHC) on chromosome 6 with other smaller effects seen in loci outside of the MHC. With recent advances in technology, novel means of exploring the human genome have given way to new information in the development of T1DM. The newest technologies, namely high-throughput polymorphism typing and sequencing, have led to a paradigm shift in studying common diseases such as T1DM. In this review we highlight the advances in genetic associations in T1DM in the last several decades and how they have led to a better understanding of T1DM pathogenesis.
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ABSTRACT: Identity-by-descent (IBD) mapping tests whether cases share more segments of IBD around a putative causal variant than do controls. These segments of IBD can be accurately detected from genome-wide SNP data. We investigate the power of IBD mapping relative to that of SNP association testing for genome-wide case-control SNP data. Our focus is particularly on rare variants, as these tend to be more recent and hence more likely to have recent shared ancestry. We simulate data from both large and small populations and find that the relative performance of IBD mapping and SNP association testing depends on population demographic history and the strength of selection against causal variants. We also present an IBD mapping analysis of a type 1 diabetes data set. In those data we find that we can detect association only with the HLA region using IBD mapping. Overall, our results suggest that IBD mapping may have higher power than association analysis of SNP data when multiple rare causal variants are clustered within a gene. However, for outbred populations, very large sample sizes may be required for genome-wide significance unless the causal variants have strong effects.Genetics 01/2012; 190(4):1521-31. DOI:10.1534/genetics.111.136937 · 4.87 Impact Factor
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ABSTRACT: Classical major histocompatibility complex (MHC) class I and II molecules present peptides to cognate T-cell receptors on the surface of T lymphocytes. The specificity with which T cells recognize peptide-MHC (pMHC) complexes has allowed for the utilization of recombinant, multimeric pMHC ligands for the study of minute antigen-specific T-cell populations. In type 1 diabetes (T1D), CD8+ cytotoxic T lymphocytes, in conjunction with CD4+ T helper cells, destroy the insulin-producing β cells within the pancreatic islets of Langerhans. Due to the importance of T cells in the progression of T1D, the ability to monitor and therapeutically target diabetogenic clonotypes of T cells provides a critical tool that could result in the amelioration of the disease. By administering pMHC multimers coupled to fluorophores, nanoparticles, or toxic moieties, researchers have demonstrated the ability to enumerate, track, and delete diabetogenic T-cell clonotypes that are, at least in part, responsible for insulitis; some studies even delay or prevent diabetes onset in the murine model of T1D. This paper will provide a brief overview of pMHC multimer usage in defining the role T-cell subsets play in T1D etiology and the therapeutic potential of pMHC for antigen-specific identification and modulation of diabetogenic T cells.Clinical and Developmental Immunology 05/2012; 2012:380289. DOI:10.1155/2012/380289 · 2.93 Impact Factor
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ABSTRACT: The landmark discovery of induced pluripotent stem cells (iPSCs) by Shinya Yamanaka has transformed regenerative biology. Previously, insights into the pathogenesis of chronic human diseases have been hindered by the inaccessibility of patient samples. However, scientists are now able to convert patient fibroblasts into iPSCs and differentiate them into disease-relevant cell types. This ability opens new avenues for investigating disease pathogenesis and designing novel treatments. In this review, we highlight the uses of human iPSCs to uncover the underlying causes and pathological consequences of diabetes and metabolic syndromes, multifactorial diseases whose etiologies have been difficult to unravel using traditional methodologies.Cell metabolism 09/2013; DOI:10.1016/j.cmet.2013.08.010 · 16.75 Impact Factor