{
"question": [
"How do genetic mutations in the insulin gene affect glucose metabolism?",
"What are the most common genetic loci associated with an increased risk of Type 2 diabetes?",
"How does genome-wide association studies (GWAS) help in identifying diabetes-related genes?",
"What is the role of the HLA region in the genetic predisposition to Type 1 diabetes?",
"How do genetic differences contribute to variations in diabetes prevalence among different populations?"
],
"answer": [
"Genetic mutations in the insulin gene can affect glucose metabolism by disrupting insulin secretion, insulin action, and insulin processing. For instance, mutations in genes like IGF2BP2, SLC30A8, and CDKN2A/CDKN2B can lead to a lower disposition index, affecting insulin secretion. Variants in genes like GCKR can influence fasting glucose levels, insulin levels, and triglyceride levels. Additionally, mutations in genes like TCF7L2, KCNJ11, and HHEX, which are involved in -cell metabolism, can affect glucose-sensing and insulin secretion. Furthermore, a variant of the MTNR1B gene can lead to a reduction of the early insulin response to glucose, affecting insulin secretion over time.",
"The most common genetic loci associated with an increased risk of Type 2 diabetes include TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEX.",
"Genome-wide association studies (GWAS) help in identifying diabetes-related genes by scanning the genomes of many people to find genetic variations associated with the disease. These studies have identified numerous risk loci, or regions of the genome, associated with type 2 diabetes. The identified loci contain genes that may influence the disease's pathophysiology. GWAS also help in understanding the genetic basis of inter-individual variation in glycemic traits, such as levels of glucose, insulin, and hemoglobin A1c. The insights gained from these studies can contribute to the development of novel strategies for patient care.",
"The HLA region on chromosome 6p21.3 plays a significant role in the genetic predisposition to Type 1 diabetes. This region contains the HLA class II genes (HLA-DRB1, DQB1, and DQA1), which are the most potent diabetes-predisposing genes in the entire genome. These genes encode the highly polymorphic antigen-presenting proteins that are central to susceptibility to Type 1 diabetes. Certain alleles of these genes, particularly HLA-DR3, DR4, and DQB1*0302, are associated with a higher risk of developing the disease. However, the exact mechanism by which these genes confer susceptibility to diabetes is not yet fully understood.",
"Genetic differences contribute to variations in diabetes prevalence among different populations through the presence of different risk alleles and allele frequencies. Certain genetic loci associated with type-2 diabetes (T2D) and obesity have been subject to recent selection pressures, leading to population-specific genetic risk factors. For instance, East Asians and sub-Saharan Africans show pronounced differentiation at T2D loci, suggesting natural selection at these loci. Similarly, South Asians and Europeans show an excess of obesity loci with evidence of recent positive selection. These genetic variations, combined with environmental and lifestyle factors, contribute to the different rates of diabetes prevalence among various populations."
],
"contexts": [
[
"\tNature 503, 290294 (2013). 33. Dimas, A. S. et al. Impact of type 2 diabetes susceptibility variants on\nquantitative glycemic traits reveals mechanistic heterogeneity. Diabetes 63,\n21582171 (2014). 34. Dupuis, J. et al. New genetic loci implicated in fasting glucose homeostasis and\ntheir impact on type 2 diabetes risk. Nat. Genet. 42, 105116 (2010). 35. Lotta, L. A. et al. Integrative genomic analysis implicates limited peripheral\nadipose storage capacity in the pathogenesis of human insulin resistance. Nat. Genet. 49, 1726 (2017). 36. Manning, A. K. et al.",
"\t\n\nGenes reviewed were categorized into three groups: genes affecting insulin secretion, genes affecting insulin resistance, and genes affecting mitochondria function.Findings from these studies are summarized in Tables 12.2-12.4.Polymorphisms of genes, such as plasminogen activator inhibitor type 1 (PAI-1) gene and forkhead box C2 (FOXC2) gene, studied in women with GDM (Leipold, Knoefl er, Gruber, Klein, et al., 2006;Pappa et al., 2011;Shaat et al., 2007) but not associated with T2DM (Carlsson, Groop, & Ridderstrle, 2005;Osawa et al., 2003) were not included in this review.",
"\t\n\nMost of the diabetes-associated SNPs were found in non-coding regions of the genome and are thus likely to affect gene regulation.In order to understand how these genes affect type 2 diabetes and how the SNPs associated with diabetes affect gene expression, we need to first understand the physiological processes that regulate the expression of these genes.We examined the expression patterns of these potential new diabetes-susceptibility genes to determine which are expressed in tissues important for the development of type 2 diabetes.This may also suggest the potential mechanism(s) by which alterations in these genes affect diabetes risk (e.g.insulin secretion versus insulin sensitivity).We also sought to determine whether any of these genes are regulated by conditions known to alter the expression of metabolically relevant genes.We examined the expression of these genes under fasting and non-fasting conditions (e.g. in response to insulin), which might be altered if they affect peripheral insulin sensitivity.Consumption of diets high in fats and sugars is associated with risk of developing type 2 diabetes [34] and many genes that are critical for -cell function are regulated by glucose [35].Thus, we also compared their expression in fasted mice consuming a normal chow diet or a diet high in fat and sugar, and examined the expression of these genes in mouse pancreatic islets cultured under low and high glucose concentrations.Here we show that most of the diabetesassociated genes are expressed in many metabolically relevant tissues and the expression levels of several of these genes were decreased by high fat feeding or were increased in the fed state in the brain.In addition, we found most of these genes are down-regulated by increased glucose concentrations in mouse islets.",
"\t\n\nThese studies provide valuable insights into the molecular circuitry of the beta cell and pinpoint pathways crucial for the maintenance of normal glucose homeostasis.Could (a more subtle) variation in the same genes inuence susceptibility to multifactorial T2D?In the case of glucokinase and the hepatocyte nuclear factor (HNF) genes (see Chapter 4), this does not seem to be so, although regions of linkage to T2D overlapping the HNF-1a and HNF-4a loci 35,36 hint at the possibility of variants in regulatory regions not yet scanned.",
"\t\n\nMutations in transcription factors have also been reported to contribute to the genetic risk for T2DM through various mechanisms: dysregulation of target genes involved in glucose or lipid metabolism (HNFs, PPARG , IPF -1 , IB1, TIEG2/KLF11 ), impaired -cell development and differentiation ( IPF -1 , NEUROD1 / 2, TIEG2/KLF11 ), and increased -cell apoptosis ( IB1 / MAPK8IP1 ).Deleterious mutations that signifi cantly impair the transactivation activity of these transcription factors can be responsible in some families for monogenic -like forms of diabetes with late age of onset, which may represent an intermediary phenotype between MODY and the most common forms of T2DM.This is the case for the TIEG2/KLF11 gene encoding the Kr ppel -like factor 11 (KLF11), an SP1 -like pancreas expressed transcription factor that is induced by the transforming growth factor (TGF ) and regulates cell growth in the exocrine pancreas.A common polymorphism (Q62R) in KLF11 was reported to be associated with polygenic T2DM developing in adulthood and to affect the function of KLF11 in vitro [99] .Insulin levels were found to be lower in carriers of the minor allele at Q62R [99] but attempts of replication in other populations only found a minor, or no detectable effect of the Q62R common variant on diabetes risk [100] .Sequencing of KLF11 gene in families enriched for earlyonset T2DM uncovered two missense mutations which segregated with diabetes in three pedigrees [99] , but proof of their causality was only based on in vitro experiments.These fi ndings suggest a role for the TGF - signaling pathway in pancreatic diseases affecting endocrine islets (diabetes) or exocrine cells (cancer) [101] .",
"\t\n\nIn studies where overt T2D has been the phenotype the majority of associated polymorphisms have encoded proteins known to be involved in -cell metabolism; for example TCF7L2, KCNJ11 and HHEX have shown robust association [170,171].This suggests that these genes could prove useful in predicting -cell preservation during the course of T2D.The glucokinase gene (GCK) coding for the initial glucose-sensing step in the -cell can have activating mutations causing hypoglycemia that might provide structural and functional models leading to drug targets for treating T2D [172].In the GoDARTs study, investigators examined the medication response of metformin and sulphonylurea based on the TCF7L2 variants mainly affecting the -cell.The carriers of the at risk 'T' allele responded less well to sulphonylurea therapy than metformin [173].Also it is of significant public health interest that in the Diabetes Prevention Program, lifestyle modifications were shown to reduce the risk of diabetes conferred by risk variants of TCF7L2 at rs7093146, and in placebo participants who carried the homozygous risk genotype (TT), there was 80% higher risk for developing diabetes compared to the lifestyle intervention group carrying the same risk genotypes [35].These findings could herald significant future progress in the field of T2D pharmacogenomics, possibly leading to the development and use of agents tailored on the basis of genotype.",
"\t\n\nImportantly, our findings demonstrate that more than 50% of the genes in which genetic variants have been known to increase risk of T2DM showed altered expression in different tissues.The perturbation was highest, as expected, in pancreatic islets, where eight genes i.e.HHEX, HNF1B, KCNQ1, NOTCH2, TCF7L2, THADA, TSPAN8 and WFS1, showed aberrant expression.All of these genetic loci, apart from the less studied TSPAN8, have been implicated in pathways primarily involved in insulin secretion, cell proliferation and regeneration [30].Of note, genetic variants in the THADA and WFS1 have recently been shown to impair glucagon-like peptide-1stimulated insulin secretion [31,32].Furthermore, many of these loci have also shown effects on insulin sensitivity [33].In line with this, five genes, i.e.HNF1B, IRS1, KCNJ11, NOTCH2 and WFS1, were also differentially expressed in skeletal muscle.Of all T2DM genes, IRS1 seems to have a clear effect on insulin sensitivity; the T2DM-associated allele was associated with decreased IRS1 protein expression as well as reduced phosphatidylinositol-3-kinase-activity and insulin-stimulated glucose uptake in humans [12].",
"\t\nThe intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis.However, the specific genes through which these regulatory variants act remain poorly characterized.We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and highdensity genotyping.We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations.At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5.At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1.At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis.Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci.\t\n\nThe intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis.However, the specific genes through which these regulatory variants act remain poorly characterized.We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and highdensity genotyping.We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations.At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5.At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1.At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis.Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci.",
"\t\n\nIn conclusion, our study in the DESIR prospective cohort shows that carriers of the GCKR-L446 variant have lower fasting glycemia and insulin resistance and are protected against the development of diabetes despite higher TG levels and a risk of dyslipidemia.This suggests, for the first time, a molecular mechanism by which these two components of the so-called metabolic syndrome can be dissociated.Based on rodent models, such as the adenoviral-mediated hepatic overexpression of GCK or GCKR in mice with diet-induced diabetes (5,19), more active GCKR may result in improved interaction with GCK, leading to more efficiently releasable pools of GCK enzyme, with subsequent beneficial effects on glucose metabolism but otherwise with a concomitant alteration of lipid profile.",
"\t\n\nAgainst this background, it is intriguing that we and others have found that a variant of the MTNR1B gene is associated with elevated plasma glucose levels, a reduction of the early insulin response to both oral and intravenous glucose, a faster deterioration of insulin secretion over time, and increased future risk of T2D (Bouatia-Naji et al., 2009;Lyssenko et al., 2009;Prokopenko et al., 2009).This association has subsequently been confirmed in other populations (Jonsson et al., 2013;Renstro m et al., 2015;Ro nn et al., 2009).Despite the very robust genetic association, a molecular understanding of why melatonin signaling is involved in the pathogenesis of T2D has still not been reached.To resolve this issue, we performed experimental studies in human islets, INS-1 832/13 b cells, and mice, as well as clinical studies in humans.We show that the rs10830963 risk variant of MTNR1B is an expression quantitative trait locus (eQTL) conferring increased expression of MTNR1B mRNA in human islets.Experiments in INS-1 832/13 b cells and Mt2 knockout mice (Mt2 / ) establish that melatonin signaling results in inhibition of insulin release.Translation to humans in a recallby-genotype study demonstrates that melatonin treatment inhibits insulin secretion in all subjects, but carriers of the risk variant are more sensitive to this inhibitory effect of melatonin.Together, these observations support a model in which a genetically determined increase in melatonin signaling underlies impaired insulin secretion, a pathogenetic hallmark of T2D.",
"\tChange in Body-Mass Index and Insulin Secretion and Action\n\nWe examined the effect of the genotyped DNA variants on changes in the BMI and insulin secretion (disposition index) and action over time in 2444 subjects from the Botnia study who did not have diabetes.At baseline, carriers of risk genotypes in the IGF2BP2 and SLC30A8 genes and at the CDKN2A/CDKN2B locus had a lower disposition index, which was maintained unchanged throughout the 8-year observation period (P<0.05) (Fig. 3H, 3I, and 3M in the Supplementary Appendix).",
"\t\n\nWhile the above findings show no evidence of association between relevant mitochondrial gene sets and T2D, these genes could still display causal associations with specific intermediate phenotypes linked to the disease.Support for this comes from reported mitochondrial dysfunction in insulin-resistant individuals [8].Therefore, we tested the same three gene sets described above for enrichment of associations with seven different glucose and insulin-related traits characteristic of T2D, using GWA metaanalyses of up to 46,186 non-diabetic individuals [37,38] (Soranzo N. et al., unpublished data).The quantitative traits analyzed include fasting levels of glucose and insulin, glucose and insulin levels 2 hours following a 75-gram oral glucose tolerance test, indices of b-cell function (HOMA-B) and insulin resistance (HOMA-IR) [49], and glycated hemoglobin levels (HbA 1C ), which reflect long-term plasma glucose concentrations (see Materials and Methods).",
"\t\n\nUsing the same data, the DIAGRAM investigators were also able to extend previous analyses which derive biological insights from the association effects of T2D-risk variants on related traits, such as body mass index, fasting glucose (in non-diabetic individuals), and indices of betacell function and insulin action [6, 27, 28].They were able to confirm: (1) partial, but not complete, overlap between variants that influence individual risk of T2D, and those that modulate physiological variation in fasting glucose amongst healthy individuals; (2) that the only signals which are driven by a primary effect on obesity are those at FTO and MC4R; and (3) that, whilst most risk loci operate via beta-cell dysfunction, a growing number (see Table 1) exert their T2D-risk effects through an obesity-independent deterioration in insulin sensitivity.This list of \"insulin resistance\" loci offers interesting insights into key players mediating the actions of insulin in peripheral tissues.In the case of the GRB14 locus for example, which emerged from GWAS in South Asians as well as Europeans [8], RNA expression data from fat confirms GRB14 as the strongest candidate transcript at the locus: its product is an adaptor protein that binds to the insulin receptor to inhibit tyrosine kinase signaling [29].",
"\t\n\naffected by genetic factors (5) with an estimated heritability of 0.53 (0.33-0.70) (6).These findings indicate that genetic factors exert substantial effects on GLP-1-induced insulin response and, as a consequence, may affect an individual's response to the GLP-1-based therapies.",
"\t\nAims/hypothesis: Impaired insulin secretion, insulin action, insulin-independent glucose effectiveness, glu-cose tolerance and the associated abnormalities in insulin and glucose metabolism phenotypes are precursors of type 2 diabetes.Genome-wide multipoint variance component linkage scans were carried out using 654 markers to identify quantitative trait loci for insulin sensitivity, acute insulin response to glucose, disposition index and glucose effectiveness training responses in whites and blacks in the HERITAGE Family Study.Methods: These phenotypes were obtained from an IVGTT with the minimal model.The distributions of insulin sensitivity, acute insulin response to glucose and disposition index training responses (posttraining minus baseline) were approximately normalised using a square-root transformation.All phenotypes were adjusted for the effects of age, BMI and their respective baseline values within sex and generation by race prior to linkage scans.Results: In blacks, a promising linkage with a maximum lod score of 3.1 on 19q (54-62 Mb) for glucose effectiveness training response was found.Six interesting linkages with lod scores of at least 1.0 were found for disposition index training response in whites.They included 1p (30 Mb), 3q (152 Mb),.Conclusions/ interpretation: Quantitative trait loci for 20 weeks of endurance exercise training responses in insulin action and glucose metabolism phenotypes were found on chromosome 19q as well as 6p and 7q, with nominal (6p, 7q) but consistent (6p) linkages across the races.Keywords Acute insulin response to glucose .Disposition index .Exercise training response .Glucose effectiveness .Insulin sensitivity .IVGTT .Minimal model .Quantitative trait loci Abbreviations AIR g : acute insulin response to glucose .DI: disposition index .GYS1: glycogen synthase 1 gene .LDB: location database .PPAR: peroxisome proliferatoractivated receptor .S I : insulin sensitivity .S G : glucose effectiveness P.An (*) .T. Rice .\t\n\nAims/hypothesis: Impaired insulin secretion, insulin action, insulin-independent glucose effectiveness, glu-cose tolerance and the associated abnormalities in insulin and glucose metabolism phenotypes are precursors of type 2 diabetes.Genome-wide multipoint variance component linkage scans were carried out using 654 markers to identify quantitative trait loci for insulin sensitivity, acute insulin response to glucose, disposition index and glucose effectiveness training responses in whites and blacks in the HERITAGE Family Study.Methods: These phenotypes were obtained from an IVGTT with the minimal model.The distributions of insulin sensitivity, acute insulin response to glucose and disposition index training responses (posttraining minus baseline) were approximately normalised using a square-root transformation.All phenotypes were adjusted for the effects of age, BMI and their respective baseline values within sex and generation by race prior to linkage scans.Results: In blacks, a promising linkage with a maximum lod score of 3.1 on 19q (54-62 Mb) for glucose effectiveness training response was found.Six interesting linkages with lod scores of at least 1.0 were found for disposition index training response in whites.They included 1p (30 Mb), 3q (152 Mb),.Conclusions/ interpretation: Quantitative trait loci for 20 weeks of endurance exercise training responses in insulin action and glucose metabolism phenotypes were found on chromosome 19q as well as 6p and 7q, with nominal (6p, 7q) but consistent (6p) linkages across the races.Keywords Acute insulin response to glucose .Disposition index .Exercise training response .Glucose effectiveness .Insulin sensitivity .IVGTT .Minimal model .Quantitative trait loci Abbreviations AIR g : acute insulin response to glucose .DI: disposition index .GYS1: glycogen synthase 1 gene .LDB: location database .PPAR: peroxisome proliferatoractivated receptor .S I : insulin sensitivity .S G : glucose effectiveness P.An (*) .T. Rice .",
"\t\n\nCell Metabolism 21, March 3, 2015 2015 Elsevier Inc. 359 Cell Metabolism Perspective ADCY5, which were primarily found to be associated with the variation of fasting glucose levels (Bouatia-Naji et al., 2009;Dupuis et al., 2010;Prokopenko et al., 2009), and GCKR, which was primarily found to be associated with the variation of fasting glucose levels, fasting insulin levels, and triglyceride levels (Saxena et al., 2007;Dupuis et al., 2010) (Figure 2).Interestingly, the overlap between loci influencing glucose-or insulin-related traits and T2D-susceptibility loci was unexpectedly limited (Dupuis et al., 2010).This result suggests that genes and related pathways that influence normal physiological levels of metabolic traits can be different from those leading to pathophysiological levels of metabolic traits that define T2D.A recent study strengthened this conclusion showing that the combination of established SNPs raising fasting glucose levels was significantly associated with the incidence of impaired fasting glucose levels over the 9-year follow-up of the study, but not with the risk of developing overt T2D (Vaxillaire et al., 2014).",
"\t\n\nPatients with established type 2 diabetes display both b-cell dysfunction and insulin resistance.To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity.We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures.We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses.Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes.The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity.The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia.ARAP1 constituted a third cluster characterized by defects in insulin processing.A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels.The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits.By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.",
"\t\n\nIn conclusion, having only considered subjects with a BMI less than 25 kg/m 2 provides strong evidence of the importance of the genetic effect of Gly972Arg on diabetes risk.Although its contribution to the overall risk in the general population could be minimal, this evidence supports the line of research seeking to clarify the role of IRS1 in lean patients with diabetes.Further studies of this genetic effect are needed to evaluate its potential interaction with other factors-especially with genetic variation, risk factor as obesity-that participate in the same metabolic pathway."
],
[
"\t\n\nFigure2| effect sizes of the 11 common variants confirmed to be involved in type 2 diabetes risk.The x axis gives the year that published evidence reached the levels of statistical confidence that are now accepted as necessary for genetic association studies.CDKAL1, CDK5 regulatory subunitassociated protein 1-like 1; CDKN2, cyclin-dependent kinase inhibitor 2A; FTO, fat mass and obesity-associated; HHEX, haematopoietically expressed homeobox; IDE, insulin-degrading enzyme; IGF2BP2, insulin-like growth factor 2 mRNA-binding protein 2; KCNJ11, potassium inwardly-rectifying channel, subfamily J, member 11; PPARG, peroxisome proliferator-activated receptor- gene; SLC30A8, solute carrier family 30 (zinc transporter), member 8; TCF2, transcription factor 2, hepatic; TCF7L2, transcription factor 7-like 2 (T-cell specific, HMg-box); WFS1, Wolfram syndrome 1.",
"\tCorrelation of the Susceptibility Loci with the Pathogenesis of T2D\n\nWith the large number of aforementioned genetic loci susceptible to T2D, the question pertains to how they participate in the pathogenesis of T2D.A great number of studies have suggested that genetic variants in or near KCNJ11, TCF7L2, WFS1, HNF1B, IGF2BP2, CDKN2A-CDKN2B, CDKAL1, SLC30A8, HHEX/IDE, KCNQ1, THADA, TSPAN8/LGR5, CDC123/CAMK1D, JAZF1, MTNR1B, DGKB/TMEM195, GCK, PROX1, ADCY5, SRR, CENTD2, ST6GAL1, HNF4A, KCNK16, FITM2-R3HDML-HNF4A, GLIS3, GRB14, ANK1, BCAR1, RASGRP1, and TMEM163 may confer T2D risk through impaired -cell function [16,24,44,68,[111][112][113][114], whereas PPAR, ADAMTS9, IRS1, GCKR, RBMS1/ITGB6, PTPRD, DUSP9, HMGA2, KLF14, GRB14, ANKRD55, and GRK5 have an impact on insulin action [21,24,115,116] (Tables 1, 2, and 3).FTO and MC4R, previously identified genes associated with obesity, appear to confer T2D risk through their primary effects on BMI, but recent GWAS have shown that their effects on T2D were independent of BMI, though FTO may have a small but detectable influence on T2D risk through insulin action [117,118].\t\n\nIn 2010, a meta-analysis of 21 genome-wide association studies performed by Dupuis and colleagues identified ADCY5, PROX1, GCK, GCKR, and DGKB/TMEM195 as new genetic loci for T2D susceptibility [22].Among these loci, DGKB/TMEM195, GCK, PROX1, and ADCY5 mainly affect -cell functions, whereas the locus mapped in GCKR shows a primary effect on insulin action [22].In the same year, another genome-wide association study by Qi and colleagues discovered new variants near RBMS1 and ITGB6 genes at 2q24, and these variants were found to affect glucose metabolism and insulin resistance [23].In addition, an expanded meta-analysis of existing GWAS by Voight and colleagues identified 12 new signals with a combined < 5 10 8 , including BCL11A, ZBED3, KLF14, TP53INP1, TLE4, CENTD2, HMGA2, HNF1A, PRC1, ZFAND6, DUSP9, and KCNQ1 [24].HNF1A was previously recognized as the causal gene of MODY3 [62] and also harbored the common variant (G319S) that contributes to early-onset T2D [63,64].DUSP9, mapped on chromosome X, encodes a member of the family of mitogen-activated protein kinase phosphatase 4, MKP4, which is important in cell cycle regulation and plays pivotal roles in regulating insulin action [65][66][67].",
"\t\n\nOne obvious locus to consider is TCF7L2 in the context of type 2 diabetes.Common genetic variation located within the gene encoding transcription factor 7 like 2 (TCF7L2) has been consistently reported to be strongly associated with the disease.Such reports range from 2006, when we first published the association [3], to the recent transethnic meta-analysis GWAS of type 2 diabetes [4].",
"\t\n\nTesting of these loci for association with T2D as a dichotomous trait in up to 40,655 cases and 87,022 nondiabetic controls demonstrated that the fasting glucose-raising alleles at seven loci (in or near ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 and the known T2D genes TCF7L2 and SLC30A8) are robustly associated (P < 5 10 8 ) with increased risk of T2D (Table 2).The association of a highly correlated SNP in ADCY5 with T2D in partially overlapping samples is reported by our companion manuscript 29 .We found less significant T2D associations (P < 5 10 3 ) for variants in or near CRY2, FADS1, GLIS3 and C2CD4B (Table 2).These data clearly show that loci with similar fasting glucose effect sizes may have very different T2D risk effects (see, for example, ADCY5 and MADD in Table 2).",
"\t\n\nDespite identification of many putative causative genetic variants, few have generated credible susceptibility variants for type 2 diabetes.Indeed, the most important finding using linkage studies is the discovery that the alteration of TCF7L2 (TCF-4) gene expression or function (33) disrupts pancreatic islet function and results in enhanced risk of type 2 diabetes.Candidate gene studies have also reported many type 2 diabetes-associated loci and the coding variants in the nuclear receptor peroxisome proliferator-activated receptor-g (34), the potassium channel KCNJ11 (34), WFS1 (35), and HNF1B (TCF2) (36) are among the few that have been replicated (Table 2).Recently, there have been great advances in the analysis of associated variants in GWA and replication studies due to highthroughput genotyping technologies, the International HapMap Project, and the Human Genome Project.Type 2 susceptibility loci such as JAZF1, CDC123-CAMK1D, TSPAN8-LGR5, THADA, ADAMTS9, NOTCH2, and ADCY5 (37,38) are among some of the established loci (Table 2).CDKN2A/B, CDKAL1, SLC30A8, IGF2BP2, HHEX/IDE, and FTO are other established susceptibility loci for diabetes (Table 2) (34,39,40).GWA studies have also identified the potassium voltage-gated channel KCNQ1 (32) as an associated gene variant for diabetes.A recent GWA study reporting a genetic variant with a strong association with insulin resistance, hyperinsulinemia, and type 2 diabetes, located adjacent to the insulin receptor substrate 1 (IRS1) gene, is the C allele of rs2943641 (41).Interestingly, the parental origin of the single nucleotide polymorphism is of importance because the allele that confers risk when paternally inherited is protected when maternally transmitted.GWA studies for glycemic traits have identified loci such as MTNR1B (42), GCK (glucokinase) (42), and GCKR (glucokinase receptor) (42); however, further investigation of genetic loci on glucose homeostasis and their impact on type 2 diabetes is needed.Indeed, a recent study by Soranzo et al. (42) using GWA studies identified ten genetic loci associated with HbA 1c .Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin may be associated with changes in levels of HbA 1c .",
"\t\n\nG enome-wide association studies (GWAS) have iden- tified several type 2 diabetes mellitus (T2DM) susceptibility loci including CDKAL1, CDKN2B, IGF2BP2, HHEX, SLC30A8, PKN2, LOC387761 (1)(2)(3)(4)(5), and KCNQ1, which was recently identified by similar GWAS approach in two independent Japanese samples (6,7).Although these associations have been well replicated in Japanese populations (8), the role of these loci in other East Asian populations remains less clear.For example, a study in China by Wu et al. (9) did not find significant associations between single-nucleotide polymorphisms (SNPs) in IGF2BP2 and SLC30A8 with T2DM, whereas an association between SNPs at the HHEX locus and T2DM was reported among Chinese living in Shanghai, but not among Chinese in Beijing.Another study in Hong Kong Chinese (10) also did not find an association with SNPs at the IGF2BP2 locus; however, they reported an association between T2DM with SNPs at the HHEX and SLC30A8 loci.",
"\t\n\nMinor susceptibility might operate in some populations from other genes, including insulin receptor substrate 1 ( IRS -1 ), adiponectin ( ACDC ) or ectonucleotide pyrophosphatase/phosphodiesterase 1 enzyme ( ENPP1 ) in a context of obesity or diabesity. In genome scans of diabetic families, loci for T2DM have been found at several sites, including chromosomes 1q, 2q ( NIDDM1 ), 2p, 3q, 12q, 11q, 10q and 20.NIDDM1 has been identifi ed as coding for calpain 10, a non -lysosomal cysteine protease with actions at the mitochondria and plasma membrane, and also in pancreatic -cell apoptosis. In 2007, fi ve large genome -wide association studies in European descent populations have identifi ed new potential T2DM genes, including the Wnt signaling related transcription factors TCF7L2 and HHEX , the zinc transporter ZnT8 ( SLC30A8 ), the CDK5 regulatory subunit -associated protein 1 -like 1 ( CDKAL1 ) and a regulatory protein for IGF2 ( IGF2BP2 ).A consensus of close to 20 confi rmed T2DMsusceptibility loci to date provided novel insights into the biology of T2DM and glucose homeostasis, but individually with a relatively small genetic effect.Importantly, these genes implicate several pathways involved in -cell development and function. Compared with clinical risk factors alone, the inclusion of common genetic variants (at least those identifi ed to date) associated with the risk of T2DM has a small effect on the ability to predict future development of T2DM.At the individual level, however, a combined genotype score based on 15 risk alleles confers a 5 -8 fold increased risk of developing T2DM.Identifying the subgroups of individuals at higher risk is important to target these subjects with more effective preventative measures.",
"\t\n\nTesting of these loci for association with T2D as a dichotomous trait in up to 40,655 cases and 87,022 nondiabetic controls demonstrated that the fasting glucose-raising alleles at seven loci (in or near ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 and the known T2D genes TCF7L2 and SLC30A8) are robustly associated (P < 5 10 8 ) with increased risk of T2D (Table 2).The association of a highly correlated SNP in ADCY5 with T2D in partially overlapping samples is reported by our companion manuscript 29 .We found less significant T2D associations (P < 5 10 3 ) for variants in or near CRY2, FADS1, GLIS3 and C2CD4B (Table 2).These data clearly show that loci with similar fasting glucose effect sizes may have very different T2D risk effects (see, for example, ADCY5 and MADD in Table 2).",
"\tType 2 Diabetes\n\nCommon variants in 11 genes were significantly associated with the risk of future type 2 diabetes in the MPP cohort, including TCF7L2 (odds ratio, 1.30; P = 9.510 13 ), PPARG (odds ratio, 1.20; P = 4.010 4 ), FTO (odds ratio, 1.14; P = 9.210 5 ), KCNJ11 (odds ratio, 1.13; P = 3.610 4 ), NOTCH2 (odds ratio, 1.13; P = 0.02), WFS1 (odds ratio, 1.12; P = 0.001), CDKAL1 (odds ratio, 1.11; P = 0.004), IGF2BP2 (odds ratio, 1.10; P = 0.008), SLC30A8 (odds ratio, 1.10; P = 0.008), JAZF1 (odds ratio, 1.08; P = 0.03), and HHEX (odds ratio, 1.07; P = 0.03) (Table 2).Although these findings could not be fully replicated in the smaller Botnia study, there was little heterogeneity between the studies with respect to the risk conferred by different genotypes.\t\n\nOf the 16 loci that have been associated with type 2 diabetes previously, [8][9][10][11][12][13][14][15] we showed that 11 -TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEXwere associated with an enhanced risk of future diabetes.Many of the variants that we genotyped appear to influence beta-cell function, possibly through effects on proliferation, regeneration, and apoptosis.There was a time-dependent increase in the BMI and a decrease in insulin sensitivity in the subjects from the Botnia study, an increase in insulin resistance that was reflected by an increase in insulin secretion.However, this increase was inadequate to compensate for the increase in insulin resistance in carriers with a high genetic risk, which resulted in a markedly impaired disposition index.Only variants in FTO were associated with an increased BMI.Both FTO and PPARG together with TCF7L2 and KCNJ11 predicted transition from impaired fasting glucose levels or impaired glucose tolerance to manifest diabetes, which suggests that a combination of increased obesity and insulin resistance with a deterioration in beta-cell function contribute to the manifestation of diabetes in these subjects.Collectively, our findings emphasize the critical role of inherited defects in beta-cell function for the development of type 2 diabetes.",
"\t\n\nTo date, more than 70 genes have been identified as involved in T2DM, primarily by association analysis [34].In addition, via GWAS arrays, more than 100 SNPs have been identified for T2DM [35].From the 50 novel loci associated with T2DM previously identified, more than 40 loci have been associated with T2DM-related traits, including fasting proinsulin, insulin and glucose (Table 1) [36][37][38][39].However, for T2DM-related traits, such as the HOMA index or pancreatic cell function, there are virtually no published data examining the relationship between these traits or the genotype and environment interactions.Clinical investigations of some loci have suggested that the genetic components of T2DM risk act preferentially through cell function [40].Among all 40 loci associated with T2DM-related traits, only transcription factor-7-like 2 (TCF7L2) was shown to clearly contribute to T2DM risk [41].Several studies in white European [42], Indian [43], Japanese [44], Mexican American [45] and West African [46] individuals have shown a strong association between TCF7L2 and T2DM.It is also noteworthy that these populations represent the major racial groups with a high prevalence of T2DM.In all populations, TCF7L2 showed a strong association, with the odds of developing T2DM increased by 30%-50% for each allele inherited.This finding indicates an approximately double odds ratio compared to most other diabetes susceptibility polymorphisms.TCF7L2 is a transcription factor involved in the Wnt signaling pathway that is ubiquitously expressed, and it has been observed that TCF7L2 risk alleles result in the overexpression of TCF7L2 in pancreatic cells.This overexpression causes reduced nutrient-induced insulin secretion, which results in a direct predisposition to T2DM as well as an indirect predisposition via an increase in hepatic glucose production [47].",
"\tCommon Variants\n\nThe development of GWAS spurred considerable progress identifying common variants [minor allele frequency (MAF)>0.05]associated with T2D (Table 1) and glycemic traits (Table 2).After early candidate gene and linkage studies identified common variants associated with T2D in PPARG, KCNJ11-ABCC8 and TCF7L2, the first five GWAS for T2D detected six additional loci, and by early 2008, GWAS and meta-analyses had identified 15 loci for T2D and G6PC2 as a locus for fasting glucose (10).Also in 2008, reports of the first non-European-based GWAS for T2D established KCNQ1 as a T2D locus with variants common in East Asians (MAF = 0.33) but low frequency in Europeans (MAF 0.01) (11,12).KCNQ1 risk variants showed similar effect sizes in both populations, demonstrating the role of allele frequency in power to detect loci (13).In 2010, a meta-analysis of European-ancestry individuals identified a second signal of T2D-associated variants near KCNQ1 that are not in marked linkage disequilibrium (LD) with the initial variants (r 2 < 0.05) and independent from them based on conditional analyses (14).By the end of 2011, further GWAS and meta-analyses in several populations had identified 55 loci for T2D (15,16).Also by 2011, GWAS had identified 32 total loci for one or more glycemic traits, including 17 for fasting glucose (15,17), 2 for fasting insulin (18), 5 for 2hGlu (19), 11 for HbA1c (20)(21)(22) and 9 for proinsulin, including 1 identified only in women (23).Incomplete overlap of loci between T2D and glycemic traits showed that not all effects on glucose levels in healthy individuals translate to the risk of T2D and vice versa.Based on the overlap between traits and the biological function of nearby genes, most identified T2D loci appeared to have a primary role in pancreatic islet -cell function, with far fewer impacting insulin resistance.",
"\t\n\nThe most replicated locus for susceptibility to T2D is TCF7L2, in which two intronic markers, rs12255372 and rs7903146, are associated with the disease across multiple, ethnically diverse populations [87][88][89][90][91][92][93][94][95][96][97][98][99][100].Because TCF7L2 is expressed in pancreatic -cells, and insulin secretion is reduced in individuals with the risk alleles at rs12255372 and rs7903146, carriers of these alleles may respond sub-optimally to sulfonylurea therapy due to decreased -cell function [101].A study involving 4469 participants from the Genetics of Diabetes Audit and Research Tayside (GoDARTs) provided evidence in support of this hypothesis by finding that individuals with the variant TT genotype at rs12255372 were less likely to respond to sulfonylurea treatment with a target HbA1c < 7% compared to carriers of the GG genotype (57% vs. 40%) [101].Further, individuals with the TT genotype were much less likely to achieve a target HbA1c of 7% within one year of initiating sulfonylurea treatment compared with carriers of the GG genotype [101].Similar results were observed with marker rs7903146.These results suggest that the TCF7L2 locus may not only affect susceptibility to T2D, but may also modulate response to sulfonylurea therapy; in both cases, the pathophysiology likely stems from impaired insulin secretion due to deteriorating -cell function.",
"\t\n\nThrough genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05).Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance.Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations.This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies.Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.",
"\tRESULTS-\n\nWe confirmed the associations of TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, and FTO with risk for type 2 diabetes, with odds ratios ranging from 1.13 to 1.35 (1.3 10 12 P unadjusted 0.016).In addition, the A allele of rs8050136 at FTO was associated with increased BMI in the control subjects (P unadjusted 0.008).However, we did not observe significant association of any genetic variants with surrogate measures of insulin secretion or insulin sensitivity indexes in a subset of 2,662 control subjects.Compared with subjects carrying zero, one, or two risk alleles, each additional risk allele was associated with 17% increased risk, and there was an up to 3.3-fold increased risk for type 2 diabetes in those carrying eight or more risk alleles.Despite most of the effect sizes being similar between Asians and Europeans in the metaanalyses, the ethnic differences in risk allele frequencies in most of these genes lead to variable attributable risks in these two populations.",
"\t\n\nRESULTS-We confirmed the association of all eight loci with type 2 diabetes with odds ratio (OR) ranging from 1.18 to 1.89 (P 1.6 10 3 to 4.6 10 34 ).The strongest association with the highest effect size was observed for TCF7L2 (OR 1.89 [95% CI 1.71-2.09],P 4.6 10 34 ).We also found significant association of PPARG and TCF7L2 with homeostasis model assessment of -cell function (P 6.9 10 8 and 3 10 4 , respectively), which looked consistent with recessive and under-dominant models, respectively.CONCLUSIONS-Our study replicates the association of wellestablished common variants with type 2 diabetes in Indians and shows larger effect size for most of them than those reported in Europeans.Diabetes 59:2068-2074, 2010 T ype 2 diabetes is a complex metabolic disorder with both genetic and environmental factors such as food habits and lifestyle contributing to its pathogenesis (1).Due to its complex etiology, the progress of discovery of genetic components for type 2 diabetes had been very slow until the advent of high throughput genome-wide association (GWA) studies (2).Until recently, only a few common variants in PPARG (3), KCNJ11 (4), and TCF7L2 (5) were shown to be associated with type 2 diabetes.With the advent of GWA studies, there are at least 20 loci identified today that are associated with the risk of type 2 diabetes (6).The first GWA study in the French population revealed SLC30A8 and HHEX as new loci for type 2 diabetes in addition to replicating the strong association with TCF7L2 (7).Further, GWA studies added several new genes including CDKAL1, CDKN2A, IGF2BP2, and FTO to the list of type 2 diabetes-associated loci and confirmed the associations for PPARG, KCNJ11,.\t\n\nOBJECTIVE-Common variants in PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 genes have been shown to be associated with type 2 diabetes in European populations by genome-wide association studies.We have studied the association of common variants in these eight genes with type 2 diabetes and related traits in Indians by combining the data from two independent case-control studies.",
"\t\n\nFG-associated loci from GWAS studies have also helped define the relationship between T2D and abnormal insulin processing and secretion in -cells.Among other glycemic trait analyses by the MAGIC, nine genome-wide significant loci were described for corrected insulin response (CIR), seven of which were previously associated with both T2D and other glycemic traits (MTNR1B, GCK, HHEX/ IDE, CDKAL1, CDKN2A/2B, ANK1, C2CD4A/B) (Prokopenko et al. 2014).Two other loci included G6PC2 associated with glycemic trait variability in nondiabetic individuals and the novel GRB10 association, which showed potential tissuespecific methylation and parental imprinting that might mask its association with T2D).Meta-analysis of GWA studies by MAGIC for fasting proinsulin levels adjusted for FI identified eight loci, of which four demonstrated that both proinsulin-raising (for TCF7L2, SLC30A8, and VPS13C/C2CD4A/B) and proinsulin-lowering alleles (for ARAP1) influenced T2D risk through a decrease in insulin secretion caused by distal or proximal impairment of proinsulin conversion, respectively (Strawbridge et al. 2011).Similarly, Dimas and colleagues described associations at the HHEX/IDE and MTNR1B loci with defects in early insulin secretion through reduced insulinogenic index for the T2D risk allele and showed that the T2D risk allele at ARAP1 was related to defects in the first steps of insulin production, through association with 32,33 split proinsulin (Dimas et al. 2014).",
"\tUnderstanding the biology of T2D-susceptibility loci\n\nThis analysis takes the number of independent loci showing genomewide significant associations with T2D beyond 35.For some, such as those at KCNJ11 and SLC30A8, the molecular mechanisms responsible for the susceptibility effect can be assigned with some confidence 42 .At others, the identities of the causal variants, the genes through which they act and the pathophysiological processes which they influence remain obscure.We used several approaches designed to link DIAGRAM+ and previously reported T2D association signals to biological insights relevant to T2D pathogenesis."
],
[
"\tGenome-Wide Association Study (GWAS). With the advent of GWAS, exploration of the genetic basis for T2D susceptibility has made significant breakthroughs.In 2007, the results of five genome-wide association studies were published.These studies increased the number of confirmed T2D susceptibility loci to nine (PPAR, KCNJ11, TCF7L2, CDKAL1, CDKN2A/B, IGF2BP2, HHEX/IDE, FTO, and SLC30A8) [13][14][15][16][17][18].Except for PPAR and FTO, which mainly affect insulin sensitivity, all the other genes may affect cell function, although the exact mechanisms remain largely unknown [16].HHEX, which is located on chromosome 10q, is a member of the homeobox family and encodes a transcription factor that maybe involved in Wnt signaling [58].Nevertheless, these studies established the utility of GWAS approach in elucidating complex genetic traits.",
"\t\n\nThe application of genome wide association studies (GWAS) has robustly revealed dozens of genetic contributors to T1D [23][24][25][26][27][28][29], the results of which have largely been independently replicated [30][31][32][33][34][35][36].The most recently reported meta-analysis of this trait identified in excess of forty loci [29], including 18 novel regions plus confirmation of a number of loci uncovered through crossdisease comparisons [34][35][36].As such, the risks conferred by these additional loci are relatively modest compared to the 'low-hanging fruit' described in the first studies and could only be ultimately uncovered when larger sample sizes were utilized.",
"\t\n\nBy contrast, knowledge of the genetic basis of diabetes is incomplete, despite Herculean efforts (8)(9)(10)(11)(12).Genome-wide association studies have accelerated the discovery of single-nucleotide polymorphisms (SNPs) at numerous loci.Comparison of the frequencies of these SNPs in case-control studies has enabled the calculation of the odds of their association with specific disease phenotypes.To date, genome-wide studies have added more than 4,000 SNPs involving some 200 diseases, including .30diabetes-related SNPs (diabetoSNPs).The analysis of dia-betoSNPs has intrinsic appeal as a tool for diabetes prediction, and could also yield potential clues to ethnic disparities in the susceptibility to type 2 diabetes.Because the diabetoSNPs individually confer modest effects, investigators have adopted an approach based on cumulative genetic risk score (GRS) at several loci to improve sensitivity (13)(14)(15)(16).Using available information on the relative odds of diabetes per risk allele (11,12), investigators can further calculate a weighted GRS.",
"\t\n\nGenomic variations and DNA profiling of those at risk for type 2 diabetes Despite many candidate gene studies and genome-wide linkage studies, very few susceptibility loci for type 2 diabetes have been identified until the recent emergence of genomic-wide association (GWA) data and large-scale replication studies (Table 2).Meta-analysis of GWA studies provides the unique opportunity to investigate the heterogeneity or consistency of genomic associations across diverse datasets and study populations.Recently, Voight et al. (32), using large-scale association analyses combining the data from eight GWA studies, identified 12 new susceptibility loci for type 2 diabetes.",
"\t\n\nBackground: Genome-wide association studies (GWAS) identify regions of the genome that are associated with particular traits, but do not typically identify specific causative genetic elements.For example, while a large number of single nucleotide polymorphisms associated with type 2 diabetes (T2D) and related traits have been identified by human GWAS, only a few genes have functional evidence to support or to rule out a role in cellular metabolism or dietary interactions.Here, we use a recently developed Drosophila model in which high-sucrose feeding induces phenotypes similar to T2D to assess orthologs of human GWAS-identified candidate genes for risk of T2D and related traits.Results: Disrupting orthologs of certain T2D candidate genes (HHEX, THADA, PPARG, KCNJ11) led to sucrose-dependent toxicity.Tissue-specific knockdown of the HHEX ortholog dHHEX (CG7056) directed metabolic defects and enhanced lethality; for example, fat-body-specific loss of dHHEX led to increased hemolymph glucose and reduced insulin sensitivity.",
"\tGenome-Wide Association Studies (GWAS)\n\nCompletion of the Human Genome Project in 2003 [44] led to subsequent advances in biomedical research.Since 2007, a new technology in the form of 'genome-wide chips' has facilitated remarkable progress in T2D genetic research with the first publication of five large GWA scans within the span of four months, showing that more than 500,000 SNP markers distributed across the genome [45][46][47][48][49].This approach has been successful in locating genes for other diseases besides T2D and obesity [40] namely, type 1 diabetes [50], prostate cancer [51], rheumatoid arthritis [52], Crohns disease [53,54], and cardiovascular disease [55] and is being applied to other complex disorders.Use of this 'hypothesis-free' approach involved in GWAS has opened new areas of biology to explore as discoveries of more than seventy entirely new T2D loci clearly suggest that associations are not limited to candidate genes and by applying GWAS and re-sequencing approaches, new genes involved in disease pathogenesis can be identified [56] (Table 1).",
"\t\n\nGenome-wide association studies (GWAS) have made a significant contribution to our current knowledge of the role(s) of genetic variation in population-level susceptibility to T1D (Mychaleckyj et al., 2010).",
"\t\n\nOver the past few years, genome-wide association studies (GWAS) have been extremely successful in detecting loci associated with complex disease traits such as obesity and T2D.GWAS is a hypothesis-free method where many genetic markers (usually more than one million single nucleotide polymorphisms [SNPs]) spread over the entire genome are tested for association with disease traits.This method differs from the traditional biologic candidate gene approach in that it is agnostic to prior biological knowledge about a specific gene's role in disease and is hence unbiased in this respect.This approach instead relies heavily on replication of association signals across multiple populations and generally requires very large sample sizes to overcome the power constraints inherent in conducting so many association tests [72].GWAS have confirmed the three previously identified signals for T2D which localize to transcription factor 7-like 2 (TCF7L2), peroxisome proliferative activated receptor, gamma (PPARG), and potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11), and identified many new susceptibility loci [73][74][75][76][77][78].More than 40 T2D loci have been discovered and replicated to date, most of which localize to genes that appear to influence beta-cell function [79].These findings highlight the role of inherited defects in beta-cell function rather than defects in genes causing insulin resistance in the etiology of T2D [80,81].",
"\tIntroduction\n\nGenome-wide association studies (GWAS) have identified approximately 80 loci robustly associated with predisposition to type 2 diabetes (T2D) [1][2][3] and a further 70 influencing a range of continuous glycemic traits [4][5][6][7][8][9][10] in non-diabetic subjects.There is substantial, though far from complete, overlap between these two sets of loci.Physiological studies in non-diabetic individuals indicate that most of these loci primarily influence insulin secretion rather than insulin sensitivity, highlighting a key role for the pancreatic islets of Langerhans in the mechanistic underpinnings of these association signals [11,12].These findings have motivated efforts to catalogue the epigenomic and transcriptional landscape of human islets and to apply these findings to deliver biological insights into disease pathogenesis.Recently, it has been shown, for example, that GWAS signals for T2D and fasting glucose show significant co-localization with islet enhancers [13,14].",
"\t\nIt has proven to be challenging to isolate the genes underlying the genetic components conferring susceptibility to type 1 and type 2 diabetes.Unlike previous approaches, 'genome-wide association studies' have extensively delivered on the promise of uncovering genetic determinants of complex diseases, with a number of novel disease-associated variants being largely replicated by independent groups.This review provides an overview of these recent breakthroughs in the context of type 1 and type 2 diabetes, and outlines strategies on how these findings will be applied to impact clinical care for these two highly prevalent disorders.",
"\t\n\nGenome-wide association studies (GWAS) have discovered germline genetic variation associated with type 2 diabetes risk (1)(2)(3)(4).One of the largest GWAS, involving DNA taken from individuals of European descent and conducted by the DIAGRAM (DIAbetes Genetics Replication And Meta-analysis) consortium, identified 65 loci associated with type 2 diabetes risk (1).However, for most of these loci, the precise identity of the affected gene and the molecular mechanisms underpinning the altered risk are not known.",
"\t\nGenome wide association studies (GWAS) have transformed the study of heritable factors influencing complex diseases such as type 2 diabetes (T2D), with the current tally of established risk loci approaching 70.Each of these loci has the potential to offer novel insights into the biology of this disease, and opportunities for clinical exploitation.However, the complexity of this condition has often frustrated efforts to achieve these functional and translational advances.This review describes progress made over the past year to expand genome wide association studies, to characterize the mechanisms through which diabetes risk loci operate, and to define the processes involved in diabetes predisposition.\t\n\nGenome wide association studies (GWAS) have transformed the study of heritable factors influencing complex diseases such as type 2 diabetes (T2D), with the current tally of established risk loci approaching 70.Each of these loci has the potential to offer novel insights into the biology of this disease, and opportunities for clinical exploitation.However, the complexity of this condition has often frustrated efforts to achieve these functional and translational advances.This review describes progress made over the past year to expand genome wide association studies, to characterize the mechanisms through which diabetes risk loci operate, and to define the processes involved in diabetes predisposition.",
"\t\nA new generation of genetic studies of diabetes is underway.Following from initial genome-wide association (GWA) studies, more recent approaches have used genotyping arrays of more densely spaced markers, imputation of ungenotyped variants based on improved reference haplotype panels, and sequencing of protein-coding exomes and whole genomes.Experimental and statistical advances make possible the identification of novel variants and loci contributing to trait variation and disease risk.Integration of sequence variants with functional analysis is critical to interpreting the consequences of identified variants.We briefly review these methods and technologies and describe how they will continue to expand our understanding of the genetic risk factors and underlying biology of diabetes.",
"\t\nGenome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c).At the end of 2011, established loci (P < 5 10 8 ) totaled 55 for T2D and 32 for glycemic traits.Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05]variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations.Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci.Established published loci now total 88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered.Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes.\t\n\nGenome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c).At the end of 2011, established loci (P < 5 10 8 ) totaled 55 for T2D and 32 for glycemic traits.Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05]variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations.Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci.Established published loci now total 88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered.Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes.",
"\t\n\nGenome-wide association (GWA) studies represent the single most effective technique for identifying genetic risk loci causing complex diseases.Since the publication of the first GWA studies for type 2 diabetes (T2D) in 2007, nearly 90 statistically robust risk loci have been identified.The T2D risk loci identified by GWA studies contained several genes that are targets of current diabetic therapies; however, the majority of genes in these loci had not previously been implicated in the pathophysiology of T2D.Mechanistic insights about the physiological role of T2D loci in the disease predisposition have been gained from investigation of their contribution into glycemic trait variability in nondiabetic individuals.Current efforts to identify the causative genetic mutations in these loci and the molecular mechanisms through which they exert their effects have the potential to make far-reaching contributions to our understanding of molecular basis of T2D and the development of novel strategies for patient care.\t\nGenome-wide association (GWA) studies represent the single most effective technique for identifying genetic risk loci causing complex diseases.Since the publication of the first GWA studies for type 2 diabetes (T2D) in 2007, nearly 90 statistically robust risk loci have been identified.The T2D risk loci identified by GWA studies contained several genes that are targets of current diabetic therapies; however, the majority of genes in these loci had not previously been implicated in the pathophysiology of T2D.Mechanistic insights about the physiological role of T2D loci in the disease predisposition have been gained from investigation of their contribution into glycemic trait variability in nondiabetic individuals.Current efforts to identify the causative genetic mutations in these loci and the molecular mechanisms through which they exert their effects have the potential to make far-reaching contributions to our understanding of molecular basis of T2D and the development of novel strategies for patient care. IntroductionType 2 diabetes (T2D) is a common, chronic disorder whose prevalence is increasing rapidly across the globe.Like other complex diseases, T2D represents a challenge for genetic studies aiming to uncover the underlying pathophysiological mechanisms.It is predicted that T2D will affect 592 million individuals by 2035 (Federation 2013) in developed and low-and middle-income countries.While the recent increase in T2D prevalence has been attributed to a sedentary \"westernized\"",
"\t\n\nFamily-based studies of the genetic determinants of type 2 diabetes and related precursor quantitative traits (QTs, e.g.plasma insulin and glucose levels) and GWA studies have now provided an abundance of evidence for potentially causative genes.These results have been drawn together onto a single map of the human genome sequence [86].The goal is to look for genomic locations where the presence of a potential underlying type 2 diabetes gene has been attested to repeatedly-diabetes genetic 'hot spots'.Such replication increases our confidence of the presence of an underlying gene.While GWA studies look for diabetes genes using a different approach to linkage analysis, the ultimate goal is the same-to find the genetic determinants of the disease.Therefore, the results of linkage and association must eventually match each other.The current analysis identifies multiple linkage locations that differ from those found in the recent GWA studies [87-89], and suggests the location of additional major type 2 diabetes susceptibility genes.",
"\tINTRODUCTION\n\nMultiple genome-wide association studies (GWASs) have correlated type 2 diabetes mellitus (T2DM) with genetic variants, yielding a large number of loci and associated gene products that are linked to the disease phenotype-often with little or no insight into the mechanism underlying that link (Hivert et al., 2014).The current challenge is to establish robust systems to systematically evaluate the role of these loci using disease-relevant cells.Previous studies have used patient samples, cell lines, or animal models to seek mechanistic insight but with significant limitations.Large variation is observed in primary patient samples, perhaps due to genetic heterogeneity, whereas animal models present major physiological and metabolic differences that hamper understanding of the precise function of human genes in T2DM.Therefore, a robust system to systematically evaluate the role of T2DM-associated genes using disease-relevant human cells will provide an important tool for diabetes research and spur the development of precision (allele-specific) therapies, exemplified by the use of sulfonylurea drugs to treat patients carrying certain KCNJ11 mutations (Gloyn et al., 2004)."
],
[
"\tB. HLA Genes\n\nEarly studies indicated that the HLA region on chromosome 6p21 (commonly termed IDDM1, for insulin-dependent diabetes mellitus locus) is a critical susceptibility locus for many human autoimmune diseases, including T1D (305,399).These initial findings revolutionized our understanding of T1D etiology in two ways, as stated by Nerup et al. (305) in conclusion of their 1974 report: 1) T1D is a distinct disease entity, corroborating histopathological evidence; and 2) an aberrant cellular immune response, potentially triggered by viral infection, instigates onset.Numerous new susceptibility loci have emerged since, but none of them matches the strong association found with the HLA region.It is unlikely that new loci will ever be discovered that confer such a dramatic risk to T1D development (96).In genetic studies, the odds ratio is the statistic used to calculate whether a single nucleotide polymorphism (SNP) given is associated with the disease.An odds ratio of one implies that the event is equally likely in both patient and control groups.Odds ratios of alleles predisposing to complex disorders are typically modest, often in the range of 1.2-1.3,and even the HLA region has a predicted value of only 6.8.This suggests that if genetic predisposition is indeed a dominant factor in T1D development, a vast amount of common SNPs are still waiting to be discovered (96,159).After several decades of continuous progress since the discovery of HLA association (for historical perspective, see Ref. 285), the class II genes remain the strongest genetic contributor (138,323,429,433,439).Several HLA class II genes are pivotal as their alleles were found to determine a susceptibility hierarchy ranging from protection to strongly at-risk (15,73,105,134,135,237,309,393).The DRB1*1501-DQA1*0102-DQB1*0602 haplotype, found in 20% of the population but only 1% of patients, confers dominant protection against T1D (134).At the susceptible end of this spectrum are individuals with the DR3/4-DQ8 heterozygous haplotype (DR3 is DRB1*03-DQB1*0201, DR4 is DRB1*04-DQB1*0302, DQ8 is DQA1*0301, DQB1*0302).It is important to note that only 30 -50% of patients with T1D have the DR3/4-DQ2/8 genotype.A study in the Denver, Colorado area (15) identified this high-risk haplotype in 2.4% of newborns and more than 20% of the children affected by T1D, and its presence marks a 55% risk of developing overt diabetes by age 12. DR3/4-DQ2/8 siblings who are HLA identical to a diabetic proband have a risk as high as 80% for persistent anti-islet autoantibodies and 60% for progression to diabetes by age 15 (15).",
"\t\n\nIt has been long established that approximately half of the genetic risk for T1D is conferred by the genomic region harboring the HLA class II genes (primarily HLA-DRB1, -DQA1 and -DQB1 genes), which encode the highly polymorphic antigen-presenting proteins.Other established loci prior to the application of GWAS are the genes encoding insulin (INS) [9][10][11][12], cytotoxic Tlymphocyte-associated protein 4 (CTLA4) [13][14][15][16], protein tyrosine phosphatase, non-receptor type 22 (PTPN22) gene [17,18], interleukin 2 receptor alpha (IL2RA) [19][20][21] and ubiquitinassociated and SH3 domain-containing protein A (UBASH3A) [22].",
"\tDiscussion\n\nThe study of the HLA region in type 1 diabetes is a model for the identification of the actual diseasepredisposing variants in complex diseases, as well as for determining when all the genetic factors in a region have been identified (17) .\tIntroduction\n\nIt long has been established that approximately half of the genetic risk for T1D is conferred by the genomic region harboring the human leukocyte antigen HLA class II genes (primarily HLA-DRB1, -DQA1 and -DQB1 genes), which encode the highly polymorphic antigen-presenting proteins.The greatest risk arises when both haplotypes are present in the same individual (1,2,3,4) .",
"\t\n\nStudies by Valdes et al. have reported that HLA class I alleles associate with age-of-onset of T1D (Valdes et al., 2012(Valdes et al., , 1999)).Several alleles in the HLA class I region (Table 2) appear to confer high risk, but this effect is modified when accounting for LD with class II haplotypes (Noble et al., 2002).The HLA-B*39:06 allele, for instance, has the strongest risk of T1D susceptibility with an odds ratio of 10.31, while HLA-B*57:01 appears to be highly protective with an OR of 0.19 even after considering the LD with DQ and DR (Noble et al., 2010).Notably, Mikk et al. suggested that B*39:06 can significantly improve the prognosis of T1D disease, especially in patients with the DRB1*04:04-DQA1*03:01-DQB1*03:02 class II haplotypes (Mikk et al., 2014).Therefore, it is important to account for LD when elucidating for genetic risk within the class I locus.\t\n\nAs such, the HLA-encoding region is the most strongly associated T1D locus (Mychaleckyj et al., 2010).However, the molecular understanding of how HLA contributes to T1D remains unclear due the large number of distinctive HLA alleles and unusual frequencies that make the overall mechanism difficult to interpret (Sanchez-Mazas and Meyer, 2014).This has raised new questions, particularly with respect to the approximation of genetic distances, and other significant statistics in population genetics studies (Buhler and Sanchez-Mazas, 2011;Sanchez-Mazas and Meyer, 2014).As such, improving our understanding of the basic biology of the HLA locus is an essential facet of research into the mechanisms and causes of T1D.",
"\t\n\nAssociation to T1D at the HLA Prior to the advent of genome-wide linkage scans, the role of the Human Leukocyte Antigen (HLA) gene region in immune regulation, and ready availability of serologic markers, led investigators to discover the association between certain HLA alleles and T1D in the early 1970s (33,130,158).The global importance of the HLA on T1D has since been confirmed in genome-wide scans for linkage: All such scans performed to date show a major locus at the HLA (28,32,36,78,119).The fraction of all genetic risk, which can be attributed to the contribution of HLA genes to T1D susceptibility, is about 44%, with a S of 3.4 (160).",
"\tGenetic association studies in type 1 diabetes\n\nThe first locus to be successfully associated with type 1 diabetes susceptibility was the HLA locus on chromosome 6p (94)(95)(96).HLA genes fall into two major classes, class I and class II [see Redondo et al. (20) for review of nomenclature].Other genes, many related to the immune system, are also located in the HLA region.Early studies indicated that the strongest associations were with class II genes and, in particular, the HLA-D genes (97) encoding DRb (HLA-DRB), DQa (HLA-DRA) and DQb (HLA-DQB).The focus was initially narrowed to the DR3 and DR4-containing chromosomes, which confer strong risk (see, e.g., Platz et al. (98) and Schober et al. (99); DR2 was found to be protective (98).These findings have been consistently reproducible, with very strong associated risks: 90% of patients carry a DR3-or DR4-containing haplotype compared with 20% of the general population (20), for an odds ratio of approximately (0.9 0.8)/ (0.1 0.2) 36.The odds ratio for compound heterozygotes carrying both DR3 and DR4 is even higher, estimated at approximately 75 (35% of patients vs. 2.4% of controls).\t\n\nSubsequent studies attempting to further localize the risk alleles have been complicated by long-range linkage disequilibrium, which can extend for 500 kb to over 1 Mb in the case of DR3 (104).Thus, an allele at one location in the HLA may show association with diabetes because of correlation with a causal allele elsewhere.For example, it seems likely that the HLA region contains additional alleles, outside the class II genes, that affect diabetes risk (105).However, linkage disequilibrium makes it difficult to localize these genes precisely (106).One approach is to compare individuals who are identical for the major associated haplotypes but differ at other regions in the HLA (107,108).By examining the HLA regions of such individuals in detail, it may be possible to eventually sort out the intricacies of the relationship between alleles in HLA and type 1 diabetes susceptibility.However, large numbers of patients will be needed to identify the few people in whom linkage disequilibrium has broken down, and these individuals will need to be extensively characterized, perhaps by complete resequencing, before definitive conclusions can be drawn.Once the relevant alleles are definitively identified, the next challenge will be to elucidate the mechanisms by which these alleles mod-ulate autoimmunity and lead to diabetes.Given the known function of class II genes in antigen presentation, a probable explanation is differing efficiency in presentation of either islet cell antigens or foreign peptides that mimic islet cell antigens.",
"\t\n\nGenetic, functional, structural, and animal model studies all indicate that the highly polymorphic HLA class II molecules, namely the DR and DQ - heterodimers, are central to susceptibility to type 1 diabetes (4,5).The genes encoding these proteins are located in the HLA region, which spans 4,000 kb of DNA on human chromosome 6p21.3.The HLA region comprises 200 genes, and 40% of the expressed genes are predicted to have immune re-sponse functions (6,7).In addition to the class II genes HLA-DRB1 and HLA-DQB1, any one (or more) of these MHC genes, including the other HLA genes, could contribute to the overall risk for type 1 diabetes.The exact mechanism(s) by which the HLA class II molecules confer susceptibility to immune-mediated destruction of the pancreatic islets is still not known in its entirety, but the binding of key peptides from autoantigens (preproinsulin, GAD, insulinoma-associated 2 antigen, and zinc transporter, ZnT8, so far identified) to HLA class II molecules in the thymus and in the periphery are likely to play an important role.Theoretically, targeting this process of antigen presentation and T-cell activation may be an effective therapeutic approach to preventing type 1 diabetes.In practice, HLA screening is used to identify people at risk for developing type 1 diabetes, for inclusion in, and exclusion from, clinical studies (8) and clinical trials (9).\t\n\nOther features of the HLA-type 1 diabetes association were also examined; however, only support for an HLA effect by age at diagnosis was found (15)(16)(17)(18).Presumably, the risk conferred by specific HLA class I and class II alleles and haplotypes reflects the specificity of peptide binding and presentation (19,20).New genomic knowledge will better define the naturally processed peptides from autoantigens in type 1 diabetes.Intriguingly, a decrease in high-risk HLA genetic contribution in new-onset cases over the last decades has been observed in several studies, suggesting a change in environmental impact on penetrance as the incidence of type 1 diabetes increases (21)(22)(23).",
"\t\n\nLinkage studies have demonstrated that the HLA re- gion, termed IDDM1, is the major genetic determinant of IDDM susceptibility (see, e.g., Davies et al. 1994).From affected-sib-pair HLA haplotype sharing data, Risch (1987) estimated that the HLA component of IDDM susceptibility (Xs for HLA) accounts for a 3.42- fold increased risk in siblings over the population prevalence, compared to an observed 15-fold increased risk in siblings due to all genetic factors (Xs).Under a multi- plicative model, Risch calculated that HLA contributes -44% to the genetic risk for IDDM.",
"\t\n\n1. Finding the region does not readily give you the gene or mechanism.More than 25 years ago, it was discovered that alleles at the human leukocyte antigen (HLA) class I HLA-B locus were associated with Type I diabetes, using case-control association studies [4850].HLA loci were candidates for predisposition to autoimmunity because HLA molecules have a critical role in the regulation of the immune response by binding and presenting foreign or selfantigens to T lymphocytes.Later studies showed that HLA class II loci, including HLA-DRB1, DQB1 and DQA1, were even more strongly associated with diabetes.As a result of several genome-wide linkage screens [61,62,73,83], it is now clear that the most potent diabetes-predisposing genes in the entire genome are located in the HLA region on chromosome 6p21.3(these HLA region susceptibility genes are now collectively referred to as IDDM1).However, because of the extensive degree of linkage disequilibrium among the various HLA loci, it has been difficult to determine which precise locus produces diabetes susceptibility (for review, see [92]).Many studies have shown that diabetics of European ancestry have higher frequencies of HLA-DR3 and DR4 (variants at DRB1).For example, 96 % of Cana-dian Type I diabetic children had at least one of these alleles, compared with 46 % of the general population [93].However, DR4 haplotypes in diabetics were found to have a higher frequency of DQB1*0302 at the nearby HLA-DQB1 locus than DR4 haplotypes in control subjects [51], which suggested that DQB1 rather than DRB1 might be the primary diabetes susceptibility locus.Similarly, several HLA haplotypes positively associated with Type I diabetes (including DR4-DQB1*0302) were found to encode an amino acid other than aspartate at position 57 of the DQB1 chain, again implying that DQB1 was the primary susceptibility locus [52].However, an elegant study showed that DR4 haplotypes encoding both DRB*0401 (a subtype of DR4) and DQB*0302 were more diabetogenic than DR4 haplotypes encoding only one of these [53] thus, DRB1 and DQB1 together could confer susceptibility.The HLA-DQA1 locus also appears to be involved in susceptibility [54,55].In addition to susceptibility alleles, there are also protective alleles.For example, DR2 haplotypes carrying DRB1*1501 and DQB1*0602 confer strong (apparently dominant) protection against diabetes.Because it is not yet known which antigens (presented with HLA to the immune system) are critical to initiating autoimmune diabetes, the mechanism by which HLA genes produce susceptibility to (or protection from) diabetes has not yet been established.One recent model is that susceptible HLA-DR and DQ molecules bind diabetogenic antigens with low affinity and allow escape from the thymus into the periphery of self-reactive T cells, while protective HLA molecules bind with high affinity, resulting in thymic negative selection of autoreactive T cells [94].This model could explain the dominant effect of protective alleles.It has also been suggested that, in addition to HLA, other genes within the HLA region are associated with Type I diabetes [9597], but these associations could be secondary to linkage disequilibrium with HLA [98101].Numerous linkage studies have also shown the existence of susceptibility genes in the HLA region.In 538 diabetic sibpairs, 54 % shared two HLA haplotypes and only 7.3 % shared zero haplotypes, both frequencies significantly different from the 25 % expected [102].From these data, one can estimate the increased risk to siblings of diabetics attributable to HLA region genes to be about 3.4 (HLA l sib = ratio of expected to observed sharing of zero haplotypes in siblings = 0.25/0.073= 3.4) [3].Because the total increase in risk to siblings is about 15 (see above), the HLA contribution to total familial clustering of diabetes is about 44 % (assuming that l sib values are multiplicative, 15/3.4 = 4.4, and 3.4/[3.4+ 4.4] = 44 %).In summary, it appears that the largest genetic contribution to Type I diabetes is through HLA-DRB, DQB and DQA alleles, which confer varying degrees of susceptibility or resistance.However, after more than 25 years of study, it is still not clear how and in which combinations the HLA genes produce their predisposing or protective effects.",
"\t\n\nIn humans, certain alleles of DR and DQ loci of the HLA region (human MHC) have been shown to be associated with, and linked to, IDDM (4).Recent studies indicated that up to 50% of IDDM susceptibility is determined by genes in the HLA region (5,6) and that genetic markers located as far as 20 centiMorgan (cM) away from the class II HLA region still show linkage with putative susceptibility genes (5).These data indicate the importance of MHC-linked genes-in the predisposi- tion to the disease.",
"\t\n\nFollowing decades of effort to unravel the \"enigma\" of T1D genetics, nearly 50 loci have (thus far) been associated with susceptibility to the disease (Fig. 3) (Cooper et al. 2008;Concannon et al. 2009;Pociot et al. 2010).Nevertheless, no single gene is in-and-of-itself either necessary or sufficient to predict the development of T1D.The first T1D susceptibility locus identified, the Human Leukocyte Antigen (HLA) complex, provides the greatest contribution (i.e., 60%) to the overall genetic susceptibility.There are three classes of HLA genes, with class II genes having the strongest association with T1D (Redondo et al. 2001).Because class II HLA genes encode for molecules that participate in antigen presentation, the effect of MHC allelic variability on T1D risk may, for example, be explained by differences in the presentation of b-cell antigens, either by promoting anti-self-reactivity or by the failure to impart regulated immune responses (Mallone et al. 2005).The great majority of T1D patients carry the HLA-DR3 or -DR4 class II antigens, with 30% being DR3/DR4 heterozygous.In Caucasians, the DR3/DR4 genotype confers the highest T1D risk, followed by DR4 and DR3 homozygosity, respectively.Conversely, the class II allele, DQB1 0602, in linkage disequilibrium with DR2, is associated with protection from the development of T1D and is found in ,1% of patients with T1D (Redondo et al. 2001).",
"\t\n\nThe major genetic risk factors are the HLA class II haplotypes HLA-DR3-DQ2 and HLA-DR4-DQ8 on chromosome 6 (REFS 49-51).The risk of develop ing celltargeted autoimmunity on the extended HLADRDQ haplotype is complicated by a large number of HLA-DRB1 alleles in humans.Specifically, on the HLA-DQ8 haplotype, HLA-DRB1*04:01 and HLA-DRB1*04:05 are associated with greater suscep tibility to T1DM than is HLA-DRB1*04:04, whereas HLA-DRB1*04:03 is protective [52][53][54] .These haplotypes are often associated with insulin autoantibodies 55 , but the extended haplotype HLA-DRB1*03:01-DQ2 (HLA-DQA1*05:01-DQB1*02:01) was associated with GAD65 autoantibody 55,56 .These genetic risk factors are common in western populations and have a low pene trance 57,58 , which might explain why many people do not develop islettargeted autoimmunity or T1DM despite having these T1DM risk factors.",
"\t\n\nOf the 49 T1D susceptibility region, the HLA association is the strongest with Odd Ratios (ORs) ranging from 0.02 to >11 for specific haplotypes (Noble and Erlich, 2012;Todd et al., 2010).This region contributes to about 50% of genetic susceptibility to T1D, specifically the HLA class II DR-DQ haplotypes (Erlich et al., 2008).Particularly, the DR4-DQ8 and DR3-DQ2 haplotype combinations are present in about 90% of children with T1D (Held et al., 1999;Tait and Boyle, 1986;Deschamps et al., 1980).A genotype containing both haplotypes (DR4-DQ8/DR3-DQ2) carries the highest risk of diabetes, and is commonly seen in 5% of early-onset disease (Gale and Gillespie, 2014).Other strong associations to T1D susceptibility come from polymorphisms in the insulin INS gene (OR = 3.5), the PTPN22 gene (OR = 3.8), the IL2RA and COBL genes (OR = 2.5; 2.4, respectively) (Gillespie, 2014;Pociot et al., 2010;Todd et al., 2010).The rest of the genomic regions that confer susceptibility to T1D have smaller effects with ORs between 8 Put together, the haplotype is the group of genes that a progeny inherits from one parent 1.1 and 1.9 (Gillespie, 2014;Todd et al., 2010).The names of the T1D susceptibility regions are listed in Table 1 along with the names of the disease associated SNPs and genes.T1D has also been shown to be associated with some other autoimmune conditions like Rheumatoid arthritis, Graves' disease and Malignant anaemia (Heras et al., 2010;Knip and Siljandera, 2008).Markers for these other diseases can be found within the susceptibility regions forT1D.The names of diseases that share T1D susceptibility regions are shown in Table 2.",
"\t\n\nIn the first case-control set, having conditioned on HLA-DQB1, HLA-DRB1 and HLA-B using allele HLA-A*02 as a reference, HLA-A*01, HLA-A*11 and HLA-A*31 were protective and HLA-A*24 was predisposing for type 1 diabetes; HLA-A*03 was more predisposing than HLA-A*11 and HLA-A*31 (Supplementary Table 4).Once these alleles were accounted for, there was no further detectable HLA-A effect in the case-control set (P 5 0.15).In the second case-control set, having conditioned on HLA-DRB1 and HLA-DQB1, both HLA-A*01 and HLA-A*11 were again more protective than HLA-A*02.HLA-A*24 was still the most predisposing for type 1 diabetes and may also be associated with an earlier age-at-diagnosis (P 5 0.01; Supplementary Tables 4 and 5).\t\n\nThe major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune.In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region [4][5][6][7][8][9][10][11] .Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear.Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods-recursive partitioning and regression-to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios .1.5;P combined 5 2.01 3 10 219 and 2.35 3 10 213 , respectively) in addition to the established associations of the MHC class II genes.Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples.Taken together with previous studies [4][5][6][7][8][10][11][12][13][14][15][16] , we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes.\t\nThe major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune.In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region [4][5][6][7][8][9][10][11] .Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear.Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods-recursive partitioning and regression-to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios .1.5;P combined 5 2.01 3 10 219 and 2.35 3 10 213 , respectively) in addition to the established associations of the MHC class II genes.Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples.Taken together with previous studies [4][5][6][7][8][10][11][12][13][14][15][16] , we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes.The MHC spans 4 megabases (Mb) and contains 149 genes, of which eight (the class II loci HLA-DRB1, HLA-DQB1, HLA-DQA1, HLA-DPB1, HLA-DPA1; the class I loci HLA-A, HLA-B and HLA-C) are the highly polymorphic immune response genes.There are many other candidate genes with common variants-any one of which or a combination thereof-that might also be involved in disease susceptibility.We studied 850 type-1-diabetes-affected sibling-pair (ASP) families from the United Kingdom and the United States and a first set of 2,049 type 1 diabetes patients and 1,912 controls from across Great Britain, in which we genotyped a combined total of 254 polymorphic MHC loci, including HLA-DQB1, HLA-DRB1, HLA-A and HLA-B (Table 1 and Supplementary Table 1).A second independent set of 1,050 type 1 diabetes cases and 1,125 controls was used for validation.After these analyses were completed, 1,475 additional single nucleotide polymorphisms (SNPs) in 1,964 of our type 1 diabetes cases and 2,923 controls became available as part of our collaboration with the Wellcome Trust Case Control Consortium (WTCCC) 17 (Table 1)."
],
[
"\t\n\nThe genetic influences on the prevalence of type 2 diabetes in the Asian population are mainly related to insulin secretion capacity [4] ; other genes involved in the risk of type 2 diabetes are not substantially different in other ethnic groups [5] .The most relevant genes contributing to ethnic differences are associated with insulin secretion capacity, and they are GLIS3 , PEPD , KCNK16 , HNF4A and KCNQ1 according to meta-analyses of genome-wide association studies [4,6] .The risk allele of the KCNQ1 polymorphism is associated with impairment of insulin secretion.KCNK16 and GLIS3 have been reported to be associated with decreased -cell function and -cell mass, leading to the prevalence of type 2 diabetes [4] .These genetic differences are related to the much lower insulin secretory capacity in Asians than Caucasians.The ancestral Asian diets consisted largely of complex carbohydrates with high fiber and very low fat content, and these people had very efficient insulin utilization.In Asians, the insulin secretion capacity has been consistently very low in early ages.However, eating patterns and lifestyles have changed rapidly over the last 20 years and insulin resistance has markedly increased.Therefore, the ethnic differences may be related not only to environmental factors such as eating patterns, physical activity, and stress, but also to genetic factors.Moreover, the interaction between genetic and environmental factors plays an important role in the prevalence of type 2 diabetes [7] .",
"\t\n\nAs described above, genetic studies of T2D in European populations have made significant progress in our understanding of T2D susceptibility.However, existing data can only provide partial explanation for the heritability of T2D.It is well known that discrepancies exist in allelic frequencies and effect sizes in different ethnic groups.It is, therefore, important to understand whether these variants are also applicable to other ethnic populations.Asians.Epidemiological studies have documented consistent increases in the prevalence of diabetes in Asia, especially in China, with diabetes prevalence having increased from 2.6% in 2000 to 9.7% in 2010 [69].However, our understanding of the genetic basis of T2D in East Asia remains limited.It is therefore imperative to identify specific genes associated with this disease in East Asians.",
"\t\n\nGenetic explorations in traditionally understudied populations have succeeded in identifying novel T2D variants in Mexican populations (6,14), as well as in East Asians (15), Greenlanders (16), and African Americans (8).In Mexico, T2D is one of the leading causes of death and has a prevalence twice that of non-Hispanic whites in the U.S. and is among the highest worldwide (17,18).Although different environmental and lifestyle risk factors in Mexico partially explain the increased prevalence of T2D, unique genetic influences also contribute (6,14).Here, we explored protein-coding variants present at higher frequency in people of Latino descent to shed further light on genetic risk factors for T2D in Mexico.We identified a novel T2D association with a protective, splice-acceptor variant that disrupts expression of IGF2 isoform 2, providing a clear hypothesis for future mechanism of action and therapeutic inquiries.",
"\t\n\nDespite heterogeneity across populations in risk allele frequency or effect size in type 2 diabetes genes, the combined effects of multiple genetic variants using genetic scores based on the number of risk alleles appear to be similar across different ethnic groups.Typically, each risk allele increment is associated with a 10-20% increased risk of type 2 diabetes (41,42).These data suggest that the overall contribution of the identified genetic loci to type 2 diabetes is similar between Caucasians and other ethnic groups, and that these loci do not appear to explain ethnic differences in diabetes risk.In predicting future risk of diabetes, the clinical utility of these cumulative genetic risk scores appears to be limited in either high-or low-risk populations.\tGENETIC SUSCEPTIBILITY AND GENE-ENVIRONMENT INTERACTIONS-\n\nThe recent advent of genome-wide association studies (GWAS) has led to major advances in the identification of common genetic variants contributing to diabetes susceptibility (40).To date, at least 40 genetic loci have been convincingly associated with type 2 diabetes, but these loci confer only a modest effect size and do not add to the clinical prediction of diabetes beyond traditional risk factors, such as obesity, physical inactivity, unhealthy diet, and family history of diabetes.Many diabetes genes recently discovered through GWAS in Caucasian populations have been replicated in Asians; however, there were significant interethnic differences in the location and frequency of these risk alleles.For example, common variants of the TCF7L2 gene that are significantly associated with diabetes risk are present in 20-30% of Caucasian populations but only 3-5% of Asians (41,42).Conversely, a variant in the KCNQ1 gene associated with a 20-30% increased risk of diabetes in several Asian populations (43,44) is common in East Asians, but rare in Caucasians.It is intriguing that most diabetes susceptibility loci that have been identified are related to impaired b-cell function, whereas only a few (e.g., peroxisome proliferator-activated receptor-g, insulin receptor substrate 1, IGF-1, and GCKR) are associated with insulin resistance or fasting insulin, which points toward b-cell dysfunction as a primary defect for diabetes pathogenesis.It should be noted that most of the single nucleotide polymorphisms uncovered may not be the actual causal variants, which need to be pinpointed through fine-mapping, sequencing, and functional studies.",
"\t\n\nIn addition to these environmental and lifestyle risk factors, genetic predisposition towards T2D may provide additional insights into the differences in T2D prevalence observed between populations in SSA.At present, there are around 100 loci for which there is robust (genome-wide significant) evidence of association with traits related to T2D, including obesity and fasting hyperglycaemia, identified in predominantly European and Asian populations.However, the relevance of many recent genomic findings to populations in SSA has not been systematically studied.Given the marked genomic diversity among populations in SSA, understanding the genomic basis of T2D, its complications, and its risk factors in populations of African descent is likely to provide additional insights into disease aetiology and potential therapeutic strategies [8,9].These observations highlight the need for epidemiological studies with the statistical resolution to reliably assess the burden and epidemiology of T2D and inform potential preventative and therapeutic strategies relevant to SSA.",
"\tII. Genetics of Type 2 Diabetes\n\nType 2 diabetes clearly represents a multifactorial disease, and several findings indicate that genetics is an important contributing factor.First, certain ethnic minorities and indigenous groups with low population admixture (e.g., Pima Indians, Micronesians and other Pacific Islanders, Australian Aborigines, and Mexican-Americans) show exceptionally high type 2 diabetes prevalence (up to 21% in Pima Indians) (10 -12).Second, type 2 diabetes clusters within families and first-degree relatives have, compared with the general population, an up to 3.5-fold higher risk to develop the disease (13,14).Finally, twin studies demonstrated a markedly higher concordance for type 2 diabetes in monozygotic compared with dizygotic twins (70 vs. 10%) (15).Type 2 diabetes does not follow simple Mendelian inheritance and, therefore, is considered a polygenic disease.According to the generally accepted common variant-common disease hypothesis (16), complex diseases, such as type 2 diabetes, are caused by the simultaneous occurrence of common DNA sequence variations (minor allele frequencies 5%) in many genes.Each of these DNA alterations is supposed to exert only moderate effects on the affected genes' function and/or expression, but in their sum, these variations confer an increased susceptibility toward the adverse environmental factors mentioned above.Single nucleotide polymorphisms (SNPs), exchanges of single base pairs, cover approximately 90% of the sequence variation within the human genome (SNP Fact Sheet of the Human Genome Project; available at http://www.ornl.gov/sci/techresources/Human_Genome/faq/snps.shtml) and are therefore regarded as the major determinants of the individual predisposition to complex diseases.Thus, strong efforts are currently ongoing to map and catalog these sequence variations (The International HapMap Project at http://www.hapmap.org/index.html.en).However, the less frequent copy number variations (due to deletion and/or duplication of DNA segments one kilobase to several megabases in size) and smaller DNA insertions, deletions, duplications, and inversions may also play a role.All of these findings initiated an intensive search for the genes, or better gene variants, responsible for the genetic predisposition to type 2 diabetes.",
"\t\n\nDespite comparatively limited cohort sizes, analyses of type 2 diabetes risk in Hispanic populations have driven diabetes gene discovery by leveraging high disease prevalence, population-specific haplotypic variation, and a private mutation spectrum.There is evidence that these findings are relevant across ancestry: effects of variation in Hispanic populations are significantly directionally consistent with analyses in European ancestry, even at fairly modest levels of significance (p < 0.01) [12, 42, 43].Furthermore, due to differential LD structure, inclusion of Hispanic populations in trans-ethnic fine mapping and meta-analyses provides an opportunity to narrow windows of association and localize causal alleles [12].",
"\t\n\nThe genetic structure of the Arab population and prevalence of consanguineous marriages predispose them to T2D risk.There is a requirement for carrying out genome analysis and association studies for identification of T2D risk genes so that at-risk individuals can be identified early and appropriate measures can be taken to prevent disease progression.Environmental factors also play a significant role in T2D development.Gene variants that are too rare to be picked up by GWAS may have relatively large effects on the risk of developing T2D.Moreover, variants which are considered to be rare across populations may be more common in a particular subpopulation [106].Recent advances in next-generation sequencing technologies allow vast amounts of genetic data to be analyzed and processed rapidly, thus substantially saving time and facilitating progress in genetic studies.\t\n\nAlthough initial GWAS were mainly carried out in European populations [30][31][32], more studies focused on other ethnic groups such as Hispanics [33], Asians [34,35], African-Americans [36], Asian-Americans [37] and Arabs [38], among others, are also coming up.A catalogue of all major GWAS is maintained by The National Human Genome Research Institute and can be accessed through their website [39].Meta-analysis and comparison of results of GWAS across populations can also help identify additional statistically significant genetic associations of relevance to T2D [40,41].Since obesity predisposes to T2D, the FTO gene vari-ant which affects BMI is also considered as a risk factor for T2D [42].Variants in other genes which influence glucose and insulin levels have also been investigated for their role in conferring susceptibility to diabetes, for example, glucose-raising genes such as MTNR1B, GCK, MADD and insulin-related genes such as GCKR, IGF1, IRS1 [27,43,44].Other than GWAS, case-control association studies in different ethnic groups have also helped identify haplotypes which may predispose to diabetes in the affected individuals [45,46].",
"\tGenetic Predisposition\n\nThe fact that type 2 diabetes is a genetic disease is well known to clinicians by how it occurs in families, and by there being ethnic populations who are particularly high risk.The genetic link was clearly shown more than two decades ago by a famous study of identical twins in the U.K. that found essentially a 100% concordance rate for this diseaseif one twin developed type 2 diabetes, then the other one invariably developed it (9).However, this kind of study provides no insight into how genetics act in the disease.Is there a defective gene that directly impairs the glucose homeostasis system?Alternatively, does it cause insulin resistance or some other defect that acts indirectly by exceeding the capacity of an otherwise normal glucose homeostasis system to compensate?Also, are there one or many genetic defects that predispose to this disease?",
"\tEvidence from population studies\n\nThe high prevalence of T2D in some populations, such as Nauruan Islanders and Pima Indians, is also consistent with a genetic aetiology.1011 Neel proposed the `thrifty genotype' hypothesis to explain the persistence at a high frequency of genotypes associated with adverse phenotypes in modern societies, on the basis that those same genes, by promoting ecient energy storage, had proved benecial in times of intermittent food supply. 12igration studies provide additional ammunition for the nature nurture debate.Individuals from the Indian subcontinent, for example, have high prevalence rates of T2D whether in urban India 13 or as migrants. 14Migrant populations do not, however, immediately acquire all of the environmental attributes of their new homes, so these eects may reect dietary and cultural as well as genetic factors.",
"\t\n\nGenome-wide association studies (GWAS) have made a significant contribution to our current knowledge of the role(s) of genetic variation in population-level susceptibility to T1D (Mychaleckyj et al., 2010).",
"\t\n\nAnother caveat is that most genome-wide association and prediction studies have been conducted in populations of European descent [44, 51, 52], and case-control and prospective genetic studies in African-American [57,58] or Asian [59-61] populations are still rare.It has been hypothesised that different risk alleles and allele frequencies in various ethnic groups could contribute to global differences in incidence rates of type 2 diabetes [62], but this needs to be corroborated in further studies.",
"\t\n\nWhilst the activities of the DIAGRAM consortium have focused on samples of European descent, the past year has seen considerable expansion of efforts to identify common variants influencing T2D-risk in other populations, including those of South and East Asian origin, and African-Americans.For example, Kooner and colleagues [8] completed a GWA metaanalysis in over 5500 T2D cases and 14,400 controls from the UK, Singapore, and Pakistan, all with origins in the Indian subcontinent.This analysis identified 6 novel association signals, including variants near the genes encoding the GRB14 adaptor protein and hepatocyte nuclear factor-4A, the latter already implicated in monogenic forms of diabetes [8].Equivalent efforts in East Asian subjects have been similarly productive, adding a further 8 loci to the global tally [9,10].Studies in individuals of African descent are of particular interest given their extensive genetic diversity, and during the past year the first large-scale association studies from African-American subjects have emerged [11,12].These studies have highlighted some of the particular challenges associated with genetic studies in African-descent populations (such as limited linkage disequilibrium, and genetic admixture) but did reveal a number of novel genome-wide significant signals, including those mapping near RND3 and BCL2.",
"\tDISCUSSION\n\nA number of genetic variants have recently been identified as associated with T2DM (1-6).Most of these variants were identified in GWASs in Europeans, but associations for many are consistent in other ethnic groups, including American Indians (18,19).However, some associations are heterogeneous across ethnic groups (5,6,20).In Pima Indians, for example, TCF7L2 variants, which are strongly associated in most ethnic groups, show little association with diabetes (20).In addition because of ethnic differences in allele frequencies, relative importance of different diabetessusceptibility alleles varies.For these reasons, GWASs in non-European populations might yield additional T2DM susceptibility variants.Indeed, studies in East Asians and South Asians have identified additional diabetes associations (4-6).",
"\t\n\nIf only a subset of type 2 diabetes susceptibility genes was required for the disease in any individual and the frequencies of these susceptibility genes were different in each population, linkage results would be variable.This might easily arise if hyperglycaemia was a collection of subtly different phenotypes, each resulting from different subsets of underlying genes.Heterogeneity for diabetes as a broad phenotype is already apparent in the distinct features of type 1 diabetes, type 2 diabetes and MODY/monogenic diabetes [114].The non-monogenic form of type 2 diabetes is likely to feature further levels of heterogeneity.Phenotypic heterogeneity may be largely independent of the ethnic background however, since there was a mixture of racial groups in all replication clusters (Tables 1 and 2).Even though association studies [88,115] suggest that there will be some differences in the frequency of individual type 2 diabetes genes between ethnic backgrounds, many type 2 diabetes genes may be shared between individuals of different continents of origin.",
"\t\nDifferent populations suffer from different rates of obesity and type-2 diabetes (T2D).Little is known about the genetic or adaptive component, if any, that underlies these differences.Given the cultural, geographic, and dietary variation that accumulated among humans over the last 60,000 years, we examined whether loci identified by genome-wide association studies for these traits have been subject to recent selection pressures.Using genomewide SNP data on 938 individuals in 53 populations from the Human Genome Diversity Panel, we compare population differentiation and haplotype patterns at these loci to the rest of the genome.Using an ''expanding window'' approach (100-1,600 kb) for the individual loci as well as the loci as ensembles, we find a high degree of differentiation for the ensemble of T2D loci.This differentiation is most pronounced for East Asians and sub-Saharan Africans, suggesting that these groups experienced natural selection at loci associated with T2D.Haplotype analysis suggests an excess of obesity loci with evidence of recent positive selection among South Asians and Europeans, compared to sub-Saharan Africans and Native Americans.We also identify individual loci that may have been subjected to natural selection, such as the T2D locus, HHEX, which displays both elevated differentiation and extended haplotype homozygosity in comparisons of East Asians with other groups.Our findings suggest that there is an evolutionary genetic basis for population differences in these traits, and we have identified potential group-specific genetic risk factors.\t\n\nDifferent populations suffer from different rates of obesity and type-2 diabetes (T2D).Little is known about the genetic or adaptive component, if any, that underlies these differences.Given the cultural, geographic, and dietary variation that accumulated among humans over the last 60,000 years, we examined whether loci identified by genome-wide association studies for these traits have been subject to recent selection pressures.Using genomewide SNP data on 938 individuals in 53 populations from the Human Genome Diversity Panel, we compare population differentiation and haplotype patterns at these loci to the rest of the genome.Using an ''expanding window'' approach (100-1,600 kb) for the individual loci as well as the loci as ensembles, we find a high degree of differentiation for the ensemble of T2D loci.This differentiation is most pronounced for East Asians and sub-Saharan Africans, suggesting that these groups experienced natural selection at loci associated with T2D.Haplotype analysis suggests an excess of obesity loci with evidence of recent positive selection among South Asians and Europeans, compared to sub-Saharan Africans and Native Americans.We also identify individual loci that may have been subjected to natural selection, such as the T2D locus, HHEX, which displays both elevated differentiation and extended haplotype homozygosity in comparisons of East Asians with other groups.Our findings suggest that there is an evolutionary genetic basis for population differences in these traits, and we have identified potential group-specific genetic risk factors.\t\n\nIn conclusion, our results have shown that genetic regions surrounding loci associated with T2D, and to a lesser extent, obesity, have been subject to unusually high levels of change in the last 50,000-100,000 years.Most notably, sub-Saharan Africans and East Asians appear to have undergone selection at T2D loci.Identifying specific targets of recent selection in the human genome can aid in determining population-specific risk variants, especially insofar as disease prevalence differs between populations (Ayodo et al. 2007).We anticipate that future studies will be at a finer scale at both the population, genetic, and phenotypic level, potentially further elucidating the genetic basis of obesity and T2D, and the population-specific genetic or non-genetic mechanisms that lead to different rates, types, and consequences of obesity and T2D."
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