Understanding type 1 diabetes through genetics: advances and prospects.
ABSTRACT Starting with early crucial discoveries of the role of the major histocompatibility complex, genetic studies have long had a role in understanding the biology of type 1 diabetes (T1D), which is one of the most heritable common diseases. Recent genome-wide association studies (GWASs) have given us a clearer picture of the allelic architecture of genetic susceptibility to T1D. Fine mapping and functional studies are gradually revealing the complex mechanisms whereby immune self-tolerance is lost, involving multiple aspects of adaptive immunity. The triggering of these events by dysregulation of the innate immune system has also been implicated by genetic evidence. Finally, genetic prediction of T1D risk is showing promise of use for preventive strategies.
SourceAvailable from: Aimée M Dudley[Show abstract] [Hide abstract]
ABSTRACT: Clinically relevant features of monogenic diseases, including severity of symptoms and age of onset, can vary widely in response to environmental differences as well as to the presence of genetic modifiers affecting the trait's penetrance and expressivity. While a better understanding of modifier loci could lead to treatments for Mendelian diseases, the rarity of individuals harboring both a disease causing allele and a modifying genotype hinders their study in human populations. We examined the genetic architecture of monogenic trait modifiers using a well-characterized yeast model of the human Mendelian disease classic galactosemia. Yeast strains with loss of function mutations in the yeast ortholog (GAL7) of the human disease gene (GALT) fail to grow in the presence of even small amounts of galactose due to accumulation of the same toxic intermediates that poison human cells. To isolate and individually genotype large numbers of the very rare (~0.1%) galactose-tolerant recombinant progeny from a cross between two gal7Δ parents, we developed a new method, called FACS-QTL. FACS-QTL improves upon the currently used approaches of bulk segregant analysis and extreme QTL mapping by requiring less genome engineering and strain manipulation as well as maintaining individual genotype information. Our results identified multiple distinct solutions by which the monogenic trait could be suppressed, including genetic and non-genetic mechanisms as well as frequent aneuploidy. Taken together, our results imply that the modifiers of monogenic traits are likely to be genetically complex and heterogeneous.Genetics 11/2014; 199(1). DOI:10.1534/genetics.114.170563 · 4.87 Impact Factor
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ABSTRACT: Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult.03/2015; 6(1):87-123. DOI:10.3390/genes6010087
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ABSTRACT: Pregnancy presents a unique physiological challenge that requires changes coordinated by placentally and non-placentally derived hormones to prepare the mother for the metabolic stress presented by fetal development and to ensure appropriate nutrient allocation between mother and fetus. Of particular importance is the maintenance of normal glucose metabolism during pregnancy. Here, we describe physiological changes in glucose metabolism during pregnancy and highlight new insights into these adaptations that have emerged over the past decade using novel methodologies, specifically genome-wide association studies (GWAS) and metabolomics. While GWAS have identified some novel associations with metabolic traits during pregnancy, the majority of the findings overlap with those observed in nonpregnant populations and individuals with type 2 diabetes (T2D). Metabolomics studies have provided new insight into key metabolites involved in gestational diabetes mellitus (GDM). Both of these approaches have suggested that a strong link exists between GDM and T2D. Most recently, a role of the gut microbiome in pregnancy has been observed, with changes in the microbiome during the third trimester having metabolic consequences for the mother. In this Perspectives in Diabetes article, we highlight how these new data have broadened our understanding of gestational metabolism, and emphasize the importance of future studies to elucidate differences between GDM and T2D. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.Diabetes 02/2015; 64(2):327-34. DOI:10.2337/db14-0877 · 8.47 Impact Factor