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type=\u0022text\/css\u0022 rel=\u0022stylesheet\u0022 href=\u0022\/\/d282kpwvnogo5m.cloudfront.net\/sites\/default\/files\/advagg_css\/css__ce2QY63WIanKyr8eSq7eavr1XQRRmFD6ZSmwpyJi8lM__zXwFqpqmxrZOXXcd_TpBQpjuELbmIP9wBR5UuTDWAO4__YJWWMMdfCJuAFm5cUEp88OsodhO3ZA-2lzRfoBsSlk4.css\u0022 media=\u0022all\u0022 \/\u003E\n\u003Clink rel=\u0027stylesheet\u0027 type=\u0027text\/css\u0027 href=\u0027\/sites\/all\/modules\/contrib\/panels\/plugins\/layouts\/onecol\/onecol.css\u0027 \/\u003E\u003C\/head\u003E\u003Cbody\u003E\u003Cdiv class=\u0022panels-ajax-tab-panel panels-ajax-tab-panel-sageoa-tab-art\u0022\u003E\u003Cdiv class=\u0022panel-display panel-1col clearfix\u0022 \u003E\n  \u003Cdiv class=\u0022panel-panel panel-col\u0022\u003E\n    \u003Cdiv\u003E\u003Cdiv class=\u0022panel-pane pane-highwire-markup\u0022 \u003E\n  \n      \n  \n  \u003Cdiv class=\u0022pane-content\u0022\u003E\n    \u003Cdiv class=\u0022highwire-markup\u0022\u003E\u003Cdiv xmlns=\u0022http:\/\/www.w3.org\/1999\/xhtml\u0022 id=\u0022content-block-markup\u0022 xmlns:xhtml=\u0022http:\/\/www.w3.org\/1999\/xhtml\u0022\u003E\u003Cdiv class=\u0022article fulltext-view \u0022\u003E\u003Cspan class=\u0022highwire-journal-article-marker-start\u0022\u003E\u003C\/span\u003E\u003Cdiv class=\u0022section abstract\u0022 id=\u0022abstract-1\u0022\u003E\u003Ch2\u003ESummary\u003C\/h2\u003E\n            \u003Cp id=\u0022p-1\u0022\u003ESignificant advancements in the knowledge of human genetics and type 2 diabetes (T2DM) have been made in the last 5 years. Researchers have now identified \u223c65 regions of the genome that influence diabetes [Morris AP et al. \u003Cem\u003ENat Genet\u003C\/em\u003E 2012]. Genetic studies have also become larger. These advances are virtually all tied to improvements in technology that now allow researchers to quickly sequence the genomes of thousands of individual patients and to analyze tens of millions of genetic variants. This article discussed the new biology being derived from genetic research and how it can impact research being conducted in nongenetic areas.\u003C\/p\u003E\n         \u003C\/div\u003E\u003Cul class=\u0022kwd-group\u0022\u003E\u003Cli class=\u0022kwd\u0022\u003EDiabetes Mellitus\u003C\/li\u003E\u003C\/ul\u003E\u003Cp id=\u0022p-2\u0022\u003ESignificant advancements in the knowledge of human genetics and type 2 diabetes (T2DM) have been made in the last 5 years. It was only in 2007 that one of the first genome-wide association studies (GWAS) for T2DM identified the first genetic polymorphism with a robust relationship to diabetes\u2014a common variant in the fat mass and obesity associated \u003Cem\u003EFTO\u003C\/em\u003E gene that predisposes individuals to diabetes through an effect on body mass index (BMI) [Frayling TM et al. \u003Cem\u003EScience\u003C\/em\u003E 2007]. Researchers have now identified \u223c65 regions of the genome that influence diabetes [Morris AP et al. \u003Cem\u003ENat Genet\u003C\/em\u003E 2012]. Genetic studies have also become larger. The 2007 study included \u223c39,000 participants, while current studies of BMI include up to 350,000. These advances are virtually all tied to improvements in technology that now allow researchers to quickly sequence the genomes of thousands of individual patients and to analyze tens of millions of genetic variants.\u003C\/p\u003E\u003Cp id=\u0022p-3\u0022\u003ETimothy Frayling, PhD, University of Exeter, Exeter, United Kingdom, discussed the new biology being derived from genetic research and how it can impact research being conducted in nongenetic areas.\u003C\/p\u003E\u003Cp id=\u0022p-4\u0022\u003EMost forms of diabetes do not follow strict patterns of inheritance through families; they tend to appear in clusters. Prof. Frayling\u0027s approach to genetic studies focuses on differences in allele frequency based on the principle that variant genes present more frequently in cases than in controls, thus variant status provides probability of disease status. However, he cautioned that it remains extremely difficult to identify a single causal risk factor to explain the huge variation in human beings and to sort out the effects of confounding factors.\u003C\/p\u003E\u003Cp id=\u0022p-5\u0022\u003EGeneticists have identified 32 polymorphisms that are robustly associated with normal variation in BMI, some of which overlap with the monogenic causes of severe obesity. Some of the common polymorphisms are located near genes such as \u003Cem\u003EPOMC, BDNF, SH2B1\u003C\/em\u003E, and \u003Cem\u003EMC4R\u003C\/em\u003E\u2014mutations known to cause severe appetite disorders and severe obesity in children [Speliotes EK et al. \u003Cem\u003ENat Genet\u003C\/em\u003E 2010]. However, the \u003Cem\u003EFTO\u003C\/em\u003E genotype still stands out as the having the largest influence on BMI and related metabolic traits, and dual-energy X-ray absorptiometry measures in children participating in the 2007 study [Frayling TM et al. \u003Cem\u003EScience\u003C\/em\u003E 2007] show that the \u003Cem\u003EFTO\u003C\/em\u003E effect is associated entirely with adiposity, as opposed to skeletal or lean tissue mass (\u003Ca id=\u0022xref-fig-1-1\u0022 class=\u0022xref-fig\u0022 href=\u0022#F1\u0022\u003EFigure 1\u003C\/a\u003E).\u003C\/p\u003E\u003Cdiv id=\u0022F1\u0022 class=\u0022fig pos-float  odd\u0022\u003E\u003Cdiv class=\u0022highwire-figure\u0022\u003E\u003Cdiv class=\u0022fig-inline-img-wrapper\u0022\u003E\u003Cdiv class=\u0022fig-inline-img\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F1.large.jpg?width=800\u0026amp;height=600\u0026amp;carousel=1\u0022 title=\u0022FTO: The Association is with Fat Mass Rather Than Lean Mass.\u0022 class=\u0022fragment-images colorbox-load\u0022 rel=\u0022gallery-fragment-images-2057428382\u0022 data-figure-caption=\u0022FTO: The Association is with Fat Mass Rather Than Lean Mass.\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003E\u003Cimg class=\u0022fragment-image\u0022 alt=\u0022Figure 1.\u0022 src=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F1.medium.gif\u0022\/\u003E\u003C\/a\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cul class=\u0022highwire-figure-links inline\u0022\u003E\u003Cli class=\u00220 first\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F1.large.jpg?download=true\u0022 class=\u0022highwire-figure-link highwire-figure-link-download\u0022 title=\u0022Download Figure 1.\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EDownload figure\u003C\/a\u003E\u003C\/li\u003E\u003Cli class=\u00221\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F1.large.jpg\u0022 class=\u0022highwire-figure-link highwire-figure-link-newtab\u0022 target=\u0022_blank\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EOpen in new tab\u003C\/a\u003E\u003C\/li\u003E\u003Cli class=\u00222 last\u0022\u003E\u003Ca href=\u0022\/highwire\/powerpoint\/13070\u0022 class=\u0022highwire-figure-link highwire-figure-link-ppt\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EDownload powerpoint\u003C\/a\u003E\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv class=\u0022fig-caption attrib\u0022\u003E\u003Cspan class=\u0022fig-label\u0022\u003EFigure 1.\u003C\/span\u003E \n            \u003Cp id=\u0022p-6\u0022 class=\u0022first-child\u0022\u003EFTO: The Association is with Fat Mass Rather Than Lean Mass.\u003C\/p\u003E\n         \u003Cq class=\u0022attrib\u0022 id=\u0022attrib-1\u0022\u003EALSPAC=Avon Longitudinal Study of Parents and Children; DEXA=dual-energy X-ray absorptiometry.\u003C\/q\u003E\u003Cq class=\u0022attrib\u0022 id=\u0022attrib-2\u0022\u003EReproduced with permission from TM Frayling, PhD.\u003C\/q\u003E\u003Cdiv class=\u0022sb-div caption-clear\u0022\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cp id=\u0022p-7\u0022\u003ELongitudinal studies have also informed today\u0027s knowledge of how the \u003Cem\u003EFTO\u003C\/em\u003E gene functions. Sovio et al. [\u003Cem\u003EPloS Genet\u003C\/em\u003E 2011] have shown that the minor (fat) allele in \u003Cem\u003EFTO\u003C\/em\u003E is associated with children emerging from their adiposity trough earlier than the major (thin) allele by the age of 7 years. Thus, after the age of 7 it is difficult to assess the effects of \u003Cem\u003EFTO\u003C\/em\u003E gene variants in humans because fatter individuals eat, behave, and metabolize differently than thinner individuals as a consequence of being more overweight. This association has also been documented in an animal study in which enhanced expression of \u003Cem\u003EFTO\u003C\/em\u003E led to increased food intake and obesity [Church C et al. \u003Cem\u003ENat Genet\u003C\/em\u003E 2010].\u003C\/p\u003E\u003Cp id=\u0022p-8\u0022\u003EInteractions between the \u003Cem\u003EFTO\u003C\/em\u003E gene and the environment have been the subject of several studies. It was recently shown that the \u003Cem\u003EFTO\u003C\/em\u003E genotype influences individual variation in BMI as well as mean BMI [Yang J et al. \u003Cem\u003ENature\u003C\/em\u003E 2012]. This concept, which indicates a possible increase in the strength of genetics in today\u0027s environment, was also seen in the results of a twin study that showed strong evidence that adiposity in preadolescent children born since the onset of the obesity epidemic is highly heritable, while environmental effects are small and divided approximately equally between shared and nonshared effects [Wardle J et al. \u003Cem\u003EAm J Clin Nutr\u003C\/em\u003E 2008]. After categorizing subjects as physically inactive or active, results from a meta-analysis of data from 45 studies of adults (n=218,166) and 9 studies of children and adolescents (n=19,268) showed \u003Cem\u003EFTO\u003C\/em\u003E had a weaker effect on the distribution of BMI in physically active individuals, suggesting that the genetic effects in a less obesogenic environment are stronger [Kilpel\u00e4inen TO et al. \u003Cem\u003EPLoS Med\u003C\/em\u003E 2011]. Another impact study focused on the interaction of sugar-sweetened beverages with the genetic predisposition to adiposity. The genetic association with BMI and adiposity was stronger among participants with higher intake of sugar-sweetened beverages than among those with lower intake [Qi Q et al. \u003Cem\u003EN Engl J Med\u003C\/em\u003E 2012]. \u201cThere is still much to learn about the \u003Cem\u003EFTO\u003C\/em\u003E gene, but the pieces are starting to come together,\u201d said Prof. Frayling.\u003C\/p\u003E\u003Cp id=\u0022p-9\u0022\u003EGenetic studies are also informing epidemiology. Since genes are randomly sorted during meiosis, genetic studies are analogous to a randomized controlled trial. It is generally accepted that testosterone levels in men are inversely associated with several recognized risk factors for T2DM (eg, obesity, central adiposity, and elevated levels of fasting plasma insulin and glucose). A relationship has also been indicated between T2DM and lower baseline levels of free testosterone and sex hormone-binding globulin (SHBG) in men [Tibblin G et al. \u003Cem\u003EDiabetes\u003C\/em\u003E 1996; Haffner SM et al. \u003Cem\u003EAm J Epidemiol\u003C\/em\u003E 1996] and reduced SHBG concentrations among women with polycystic ovary syndrome and hyperinsulinemia [Nestler JE et al. \u003Cem\u003EJ Clin Endocrinol\u003C\/em\u003E 1991; Stellato RK et al. \u003Cem\u003EDiabetes Care\u003C\/em\u003E 2000]. Using Mendelian randomization principles, Prof. Frayling\u0027s laboratory has shown that GWAS have shown genetic variants at the SHBG gene influence circulating SHBG levels and that there is a direct relationship between low SHBG levels and increased risk of T2DM. Prof. Frayling predicted that future Mendelian randomization experiments will be useful for predicting which epigenetic and gene expression factors casually influence T2DM.\u003C\/p\u003E\u003Cp id=\u0022p-10\u0022\u003EIncreased adiponectin levels have been shown to be associated with a lower risk of T2DM. Thus, the relationship between genetic variation at the adiponectin-encoding gene, \u003Cem\u003EADIPOQ\u003C\/em\u003E, and adiponectin levels, and subsequently its role in diabetes has been studied extensively. One study identified a novel association between a low-frequency single nucleotide polymorphism (SNP; rs17366653) and adiponectin levels, and showed that 7 SNPs exert independent effects on adiponectin levels, which explained 6% of adiponectin variation. No evidence of association with T2DM was found [Warren LL et al. \u003Cem\u003EDiabetes\u003C\/em\u003E 2012]. Large-scale and well-powered Mendelian randomization is recommended for future studies.\u003C\/p\u003E\u003Cp id=\u0022p-11\u0022\u003EProf. Frayling concluded with a description of an ongoing study comparing \u003Cem\u003EADIPOQ\u003C\/em\u003E gene splicing, metabolic profiles, and insulin resistance in individuals with lifelong genetically reduced adiponectin levels with a control population. Data for this study and others are and will be available on the Internet. Prof. Frayling reiterated that GWAS findings are important tools to understand the biology of diabetes and should be made freely available to all researchers (\u003Ca id=\u0022xref-fig-2-1\u0022 class=\u0022xref-fig\u0022 href=\u0022#F2\u0022\u003EFigure 2\u003C\/a\u003E).\u003C\/p\u003E\u003Cdiv id=\u0022F2\u0022 class=\u0022fig pos-float  odd\u0022\u003E\u003Cdiv class=\u0022highwire-figure\u0022\u003E\u003Cdiv class=\u0022fig-inline-img-wrapper\u0022\u003E\u003Cdiv class=\u0022fig-inline-img\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F2.large.jpg?width=800\u0026amp;height=600\u0026amp;carousel=1\u0022 title=\u0022Main Message: GWAS Findings Are Important Tools to Understand the Biology of Diabetes.\u0022 class=\u0022fragment-images colorbox-load\u0022 rel=\u0022gallery-fragment-images-2057428382\u0022 data-figure-caption=\u0022Main Message: GWAS Findings Are Important Tools to Understand the Biology of Diabetes.\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003E\u003Cimg class=\u0022fragment-image\u0022 alt=\u0022Figure 2.\u0022 src=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F2.medium.gif\u0022\/\u003E\u003C\/a\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cul class=\u0022highwire-figure-links inline\u0022\u003E\u003Cli class=\u00220 first\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F2.large.jpg?download=true\u0022 class=\u0022highwire-figure-link highwire-figure-link-download\u0022 title=\u0022Download Figure 2.\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EDownload figure\u003C\/a\u003E\u003C\/li\u003E\u003Cli class=\u00221\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/12\/16\/30\/F2.large.jpg\u0022 class=\u0022highwire-figure-link highwire-figure-link-newtab\u0022 target=\u0022_blank\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EOpen in new tab\u003C\/a\u003E\u003C\/li\u003E\u003Cli class=\u00222 last\u0022\u003E\u003Ca href=\u0022\/highwire\/powerpoint\/13072\u0022 class=\u0022highwire-figure-link highwire-figure-link-ppt\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EDownload powerpoint\u003C\/a\u003E\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv class=\u0022fig-caption attrib\u0022\u003E\u003Cspan class=\u0022fig-label\u0022\u003EFigure 2.\u003C\/span\u003E \n            \u003Cp id=\u0022p-12\u0022 class=\u0022first-child\u0022\u003EMain Message: GWAS Findings Are Important Tools to Understand the Biology of Diabetes.\u003C\/p\u003E\n         \u003Cq class=\u0022attrib\u0022 id=\u0022attrib-3\u0022\u003EDNA=deoxyribonucleic acid; FFA=free fatty acid; SHBG=sex hormone-binding globulin.\u003C\/q\u003E\u003Cq class=\u0022attrib\u0022 id=\u0022attrib-4\u0022\u003EReproduced with permission from TM Frayling, PhD.\u003C\/q\u003E\u003Cdiv class=\u0022sb-div caption-clear\u0022\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cul class=\u0022copyright-statement\u0022\u003E\u003Cli class=\u0022fn\u0022 id=\u0022copyright-statement-1\u0022\u003E\u00a9 2012 MD Conference Express\u00ae\u003C\/li\u003E\u003C\/ul\u003E\u003Cspan class=\u0022highwire-journal-article-marker-end\u0022\u003E\u003C\/span\u003E\u003C\/div\u003E\u003Cspan id=\u0022related-urls\u0022\u003E\u003C\/span\u003E\u003C\/div\u003E\u003Ca href=\u0022http:\/\/mdc.sagepub.com\/content\/12\/16\/30.abstract\u0022 class=\u0022hw-link hw-link-article-abstract\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EView Summary\u003C\/a\u003E\u003C\/div\u003E  \u003C\/div\u003E\n\n  \n  \u003C\/div\u003E\n\u003C\/div\u003E\n  \u003C\/div\u003E\n\u003C\/div\u003E\n\u003C\/div\u003E\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/mdc.sagepub.com\/sites\/all\/modules\/highwire\/highwire\/plugins\/highwire_markup_process\/js\/highwire_figures.js?nzn96p\u0022\u003E\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/mdc.sagepub.com\/sites\/all\/modules\/highwire\/highwire\/plugins\/highwire_markup_process\/js\/highwire_openurl.js?nzn96p\u0022\u003E\u003C\/script\u003E\n\u003C\/body\u003E\u003C\/html\u003E"}