Type 2 diabetes (T2D) is one of the major causes of morbidity and mortality in the developed world. While environmental factors such as diet play a significant role, familial clustering indicates that there must be significant genetic susceptibility factors at work. For two decades we have been engaged in a large collaborative study entitled FUSION (Finland - United States Investigation of NIDDM), in which more than 30,000 individuals with diabetes (and suitable controls) from Finland are being studied, using careful phenotyping of diabetes and diabetes-associated quantitative traits, and genome-wide genetic linkage and association. Large numbers of additional samples are also now available from several collaborators around the world. We have developed and applied new high throughput genotyping approaches in the laboratory, which have allowed the collection of a massive amount of data from these Finnish diabetics and their families. Using the genome wide association study (GWAS) approach, we have now contributed to the identification of no less than 70 well-validated loci for T2D, and have identified >400 additional loci harboring variants that have important effects on obesity, fasting glucose, LDL and HDL cholesterol, triglycerides, proinsulin levels, blood pressure, and adult height. We are now investigating the functional basis of disease risk that arises from several of these variants. This analysis includes high throughput sequencing of these loci to identify common and rare alleles that may be driving the association, analysis of the relationship between gene expression and risk haplotypes, cell culture and biochemical assays, and mouse models. We have also embarked upon large scale whole exome and whole genome sequencing of diabetics and controls, to look for rare variants of large effect that contribute to disease risk. This includes an effort to identify the cause of rare Mendelian forms of the disease such as neonatal diabetes, congential hyperinsulinemia, and unmapped loci for Maturity Onset Diabetes of the Young (MODY). Confirmation of the effectiveness of this approach includes the recent identification of an autosomal dominant form of diabetes arising from a mutation in the Wolfram syndrome 1 gene. A major effort has been devoted to defining the epigenome of the human pancreatic islet, by mapping a variety of chromatin marks across the entire genome. This has enabled identification of enhancers and insulators, some of which harbor variants that influence the risk of T2D. Detailed investigation has led to the discovery of large regions of regulatory enhancers greater than >3kb in length we term stretch enhancers. Stretch enhancers have been demonstrated to correlate with gene expression in a tissue specific manner and are enriched in disease-associated variants. The newest component of the project involves the collection of skin, muscle, and adipose biopsies from individuals with normal glucose tolerance, impaired glucose tolerance, or early onset T2D. These are being analyzed for genotype and gene expression to identify correlates with disease. We have expanded the scope of the biopsy study to examine microRNA (miR) expression and isomiR detection by miR-seq as well as DNA methylation analysis. We are developing methods to investigate enhancer RNA (eRNA) sequencing to investigate the correlation with epigenetic analysis of histone methylation allowing the identification of active regulatory elements in frozen tissue. To fully characterize tissues in these glucose tolerance states we are examining the metabolome of these tissues investigating >250 metabolites by mass spectroscopy and their correlation with T2D associated variants, quantitative traits and gene expression. The skin biopsies are also being utilized to generate induced pluripotent stem cell lines (iPS), which in turn can be differentiated into tissues relevant to diabetes (including insulin producing cells), to study the relationships of disease risk alleles to cellular phenotype. With this kind of substantial progress, we are confident that the geneticist's nightmare (Jim Neel's description of the genetics of diabetes) may finally be coming to an end.

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Justice, Anne E (see original citation for additional authors) (2017) Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits. Nat Commun 8:14977
Scott, Robert A; Scott, Laura J; M├Ągi, Reedik et al. (2017) An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans. Diabetes 66:2888-2902
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