Detailed physiologic characterization reveals diverse mechanisms for novel genetic Loci regulating glucose and insulin metabolism in humans

Contribution of genetic background and antiretroviral therapy to body fat changes in antiretroviral-naive HIV-infected adults

OBJECTIVES

To evaluate the association of host genetics with changes in limb or trunk fat in a group of antiretroviral therapy (ART)-naive HIV-infected patients prospectively followed up according to the initiation and the type of ART.

METHODS

Fifty single nucleotide polymorphisms (SNPs) in 26 genes, associated with obesity, insulin resistance, lipid metabolism or lipodystrophy in previously published genetic studies, were assessed in ART-naive HIV-infected Caucasian patients divided into three groups: 24 (27%) did not start ART, 29 (32.6%) received zidovudine or stavudine and 36 (40.4%) received neither zidovudine nor stavudine in their initial regimen. Patients underwent body fat measurements (using dual-energy X-ray absorptiometry) at baseline and Month 12. A multivariate model using backward stepwise elimination was used to assess the influence of SNPs and baseline levels of non-genetic covariates on changes in limb or trunk fat.

RESULTS

The baseline characteristics were: 73% men, 17% coinfected with hepatitis C virus and/or hepatitis B virus, median age 37 years, median CD4+ T cell count 228/mm(3), median HIV-RNA 5.2 log copies/mL, median plasma glucose 85 mg/dL, median plasma insulin 9.1 IU/mL, median limb fat 5.6 kg and median trunk fat 7.0 kg. There were no baseline differences among the three groups except for the CD4+ T cell count. The decrease in limb fat was greater in the no-ART group relative to the other two groups (P < 0.05). The multivariate model showed associations of rs1801278 in IRS1 (P = 0.029, OR = 0.13), baseline viral load (P = 0.006; OR = 4.453) and baseline glucose levels (P = 0.008, OR = 0.926) with loss of limb fat, and rs2228671 in LDLR (P = 0.012, OR = 0.108), rs405509 in APOE (P = 0.048, OR = 0.205), baseline viral load (P = 0.005, OR = 0.186) and baseline CD4+ T cell count (P = 0.01, OR = 1.008) with gain of trunk fat.

CONCLUSIONS

Specific polymorphisms in IRS1 (limb fat loss) and LDLR and APOE (trunk fat gain) were identified as independent markers of fat changes irrespective of the initiation of ART and the type of ART and deserve further validation.

Genetic variation in MTNR1B is associated with gestational diabetes mellitus and contributes only to the absolute level of beta cell compensation in Mexican Americans

AIMS/HYPOTHESIS

MTNR1B is a type 2 diabetes susceptibility locus associated with cross-sectional measures of insulin secretion. We hypothesised that variation in MTNR1B contributes to the absolute level of a diabetes-related trait, temporal rate of change in that trait, or both.

METHODS

We tested rs10830963 for association with cross-sectional diabetes-related traits in up to 1,383 individuals or with rate of change in the same phenotypes over a 3-5 year follow-up in up to 374 individuals from the family-based BetaGene study of Mexican Americans.

RESULTS

rs10830963 was associated cross-sectionally with fasting glucose (p = 0.0069), acute insulin response (AIR; p = 0.0013), disposition index (p = 0.00078), glucose effectiveness (p = 0.018) and gestational diabetes mellitus (OR 1.48; p = 0.012), but not with OGTT 30 min Δinsulin (the difference between the 30 min and fasting plasma insulin concentration) or 30 min insulin-based disposition index. rs10830963 was also associated with rate of change in fasting glucose (p = 0.043), OGTT 30 min Δinsulin (p = 0.01) and AIR (p = 0.037). There was no evidence for an association with the rate of change in beta cell compensation for insulin resistance.

CONCLUSIONS/INTERPRETATION

We conclude that variation in MTNR1B contributes to the absolute level of insulin secretion but not to differences in the temporal rate of change in insulin secretion. The observed association with the rate of change in insulin secretion reflects the natural physiological response to changes in underlying insulin sensitivity and is not a direct effect of the variant.

Polygenic type 2 diabetes prediction at the limit of common variant detection

Genome-wide association studies (GWAS) may have reached their limit of detecting common type 2 diabetes (T2D)-associated genetic variation. We evaluated the performance of current polygenic T2D prediction. Using data from the Framingham Offspring (FOS) and the Coronary Artery Risk Development in Young Adults (CARDIA) studies, we tested three hypotheses: 1) a 62-locus genotype risk score (GRSt) improves T2D prediction compared with previous less inclusive GRSt; 2) separate GRS for β-cell (GRSβ) and insulin resistance (GRSIR) independently predict T2D; and 3) the relationships between T2D and GRSt, GRSβ, or GRSIR do not differ between blacks and whites. Among 1,650 young white adults in CARDIA, 820 young black adults in CARDIA, and 3,471 white middle-aged adults in FOS, cumulative T2D incidence was 5.9%, 14.4%, and 12.9%, respectively, over 25 years. The 62-locus GRSt was significantly associated with incident T2D in all three groups. In FOS but not CARDIA, the 62-locus GRSt improved the model C statistic (0.698 and 0.726 for models without and with GRSt, respectively; P < 0.001) but did not materially improve risk reclassification in either study. Results were similar among blacks compared with whites. The GRSβ but not GRSIR predicted incident T2D among FOS and CARDIA whites. At the end of the era of common variant discovery for T2D, polygenic scores can predict T2D in whites and blacks but do not outperform clinical models. Further optimization of polygenic prediction may require novel analytic methods, including less common as well as functional variants.

Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity

Patients with established type 2 diabetes display both β-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.

The influence of rare genetic variation in SLC30A8 on diabetes incidence and β-cell function

CONTEXT/OBJECTIVE

The variant rs13266634 in SLC30A8, encoding a β-cell-specific zinc transporter, is associated with type 2 diabetes. We aimed to identify other variants in SLC30A8 that increase diabetes risk and impair β-cell function, and test whether zinc intake modifies this risk. DESIGN/OUTCOME: We sequenced exons in SLC30A8 in 380 Diabetes Prevention Program (DPP) participants and identified 44 novel variants, which were genotyped in 3445 DPP participants and tested for association with diabetes incidence and measures of insulin secretion and processing. We examined individual common variants and used gene burden tests to test 39 rare variants in aggregate.

RESULTS

We detected a near-nominal association between a rare-variant genotype risk score and diabetes risk. Five common variants were associated with the oral disposition index. Various methods aggregating rare variants demonstrated associations with changes in oral disposition index and insulinogenic index during year 1 of follow-up. We did not find a clear interaction of zinc intake with genotype on diabetes incidence.

CONCLUSIONS

Individual common and an aggregate of rare genetic variation in SLC30A8 are associated with measures of β-cell function in the DPP. Exploring rare variation may complement ongoing efforts to uncover the genetic influences that underlie complex diseases.

IG20/MADD plays a critical role in glucose-induced insulin secretion

Pancreatic β-cell dysfunction is a common feature of type 2 diabetes. Earlier, we had cloned IG20 cDNA from a human insulinoma and had shown that IG20/MADD can encode six different splice isoforms that are differentially expressed and have unique functions, but its role in β-cell function was unexplored. To investigate the role of IG20/MADD in β-cell function, we generated conditional knockout (KMA1ko) mice. Deletion of IG20/MADD in β-cells resulted in hyperglycemia and glucose intolerance associated with reduced and delayed glucose-induced insulin production. KMA1ko β-cells were able to process insulin normally but had increased insulin accumulation and showed a severe defect in glucose-induced insulin release. These findings indicated that IG20/MADD plays a critical role in glucose-induced insulin release from β-cells and that its functional disruption can cause type 2 diabetes. The clinical relevance of these findings is highlighted by recent reports of very strong association of the rs7944584 single nucleotide polymorphism (SNP) of IG20/MADD with fasting hyperglycemia/diabetes. Thus, IG20/MADD could be a therapeutic target for type 2 diabetes, particularly in those with the rs7944584 SNP.

Recent advances in the molecular genetics of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a complex disease in which both genetic and environmental factors interact in determining impaired β-cell insulin secretion and peripheral insulin resistance. Insulin resistance in muscle, liver and fat is a prominent feature of most patients with T2DM and obesity, resulting in a reduced response of these tissues to insulin. Considerable evidence has been accumulated to indicate that heredity is a major determinant of insulin resistance and T2DM. It is believed that, among individuals destined to develop T2DM, hyperinsulinemia is the mechanism by which the pancreatic β-cell initially compensates for deteriorating peripheral insulin sensitivity, thus ensuring normal glucose tolerance. Most of these people will develop T2DM when β-cells fail to compensate. Despite the progress achieved in this field in recent years, the genetic causes of insulin resistance and T2DM remain elusive. Candidate gene association, linkage and genome-wide association studies have highlighted the role of genetic factors in the development of T2DM. Using these strategies, a large number of variants have been identified in many of these genes, most of which may influence both hepatic and peripheral insulin resistance, adipogenesis and β-cell mass and function. Recently, a new gene has been identified by our research group, the HMGA1 gene, whose loss of function can greatly raise the risk of developing T2DM in humans and mice. Functional genetic variants of the HMGA1 gene have been associated with insulin resistance syndromes among white Europeans, Chinese individuals and Americans of Hispanic ancestry. These findings may represent new ways to improve or even prevent T2DM.

A central role for GRB10 in regulation of islet function in man

Variants in the growth factor receptor-bound protein 10 (GRB10) gene were in a GWAS meta-analysis associated with reduced glucose-stimulated insulin secretion and increased risk of type 2 diabetes (T2D) if inherited from the father, but inexplicably reduced fasting glucose when inherited from the mother. GRB10 is a negative regulator of insulin signaling and imprinted in a parent-of-origin fashion in different tissues. GRB10 knock-down in human pancreatic islets showed reduced insulin and glucagon secretion, which together with changes in insulin sensitivity may explain the paradoxical reduction of glucose despite a decrease in insulin secretion. Together, these findings suggest that tissue-specific methylation and possibly imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.

In this paper, we report the first large genome-wide association study in man for glucose-stimulated insulin secretion (GSIS) indices during an oral glucose tolerance test. We identify seven genetic loci and provide effects on GSIS for all previously reported glycemic traits and obesity genetic loci in a large-scale sample. We observe paradoxical effects of genetic variants in the growth factor receptor-bound protein 10 (GRB10) gene yielding both reduced GSIS and reduced fasting plasma glucose concentrations, specifically showing a parent-of-origin effect of GRB10 on lower fasting plasma glucose and enhanced insulin sensitivity for maternal and elevated glucose and decreased insulin sensitivity for paternal transmissions of the risk allele. We also observe tissue-specific differences in DNA methylation and allelic imbalance in expression of GRB10 in human pancreatic islets. We further disrupt GRB10 by shRNA in human islets, showing reduction of both insulin and glucagon expression and secretion. In conclusion, we provide evidence for complex regulation of GRB10 in human islets. Our data suggest that tissue-specific methylation and imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.

A rare SNP in pre-miR-34a is associated with increased levels of miR-34a in pancreatic beta cells

Changes in the levels of specific microRNAs (miRNAs) can reduce glucose-stimulated insulin secretion and increase beta-cell apoptosis, two causes of islet dysfunction and progression to type 2 diabetes. Studies have shown that single nucleotide polymorphisms (SNPs) within miRNA genes can affect their expression. We sought to determine whether miRNAs, with a known role in beta-cell function, possess SNPs within the pre-miRNA structure which can affect their expression. Using published literature and dbSNP, we aimed to identify miRNAs with a role in beta-cell function that also possess SNPs within the region encoding its pre-miRNA. Following transfection of plasmids, encoding the pre-miRNA and each allele of the SNP, miRNA expression was measured. Two rare SNPs located within the pre-miRNA structure of two miRNA genes important to beta-cell function (miR-34a and miR-96) were identified. Transfection of INS-1 and MIN6 cells with plasmids encoding pre-miR-34a and the minor allele of rs72631823 resulted in significantly (p < 0.05) higher miR-34a expression, compared to cells transfected with plasmids encoding the corresponding major allele. Similarly, higher levels were also observed upon transfection of HeLa cells. Transfection of MIN6 cells with plasmids encoding pre-miR-96 and each allele of rs41274239 resulted in no significant differences in miR-96 expression. A rare SNP in pre-miR-34a is associated with increased levels of mature miR-34a. Given that small changes in miR-34a levels have been shown to cause increased levels of beta-cell apoptosis this finding may be of interest to studies looking at determining the effect of rare variants on type 2 diabetes susceptibility.

Susceptibility to type 2 diabetes mellitus--from genes to prevention

Knowledge of the genetics of type 2 diabetes mellitus (T2DM) has evolved tremendously over the past few years. Following advances in technology and analytical approaches, collaborative case-control genome-wide association studies have revealed up to 65 loci credibly associated with T2DM. Prospective population studies have demonstrated that aggregated genetic risk scores, so-called because they sum the genetic risk attributed to each locus, can predict incident T2DM among individuals of various age ranges and diverse ethnic backgrounds. With each set of T2DM loci discovered, increasing the number of loci in these scores has improved their predictive ability, although a prediction plateau may already have been reached. The current literature shows that intensive lifestyle interventions are effective for preventing T2DM at any level of genetic risk and might be particularly efficacious among individuals with high genetic susceptibility. By contrast, counselling to inform patients about their personal T2DM genetic risk profiles does not seem to improve motivation or attitudes that lead to positive lifestyle behaviour changes. Future studies should investigate the role of genetics for both T2DM prediction and prevention in young populations in the hope of reducing disease burden for future generations.

Nutrigenetics: bridging two worlds to understand type 2 diabetes

The increasing global prevalence of type 2 diabetes mellitus (T2DM) is a major public health concern. Accumulating data provides strong evidence of the shared contribution of genetic and environmental factors to T2DM risk. Genome-wide association studies have hugely improved our understanding of the genetic basis of T2DM. However, it is obvious that genetics only partly account for an individuals' predisposition to T2DM. The dietary environment has changed remarkably over the last century. Examination of individual macronutrients and more recently of foods and dietary patterns is becoming increasingly important in terms of developing public health strategies. Nutrigenetics offers the potential to improve diet-related disease prevention and therapy, but is not without its own challenges. In this review we present evidence on the dietary environment and genetics as risk factors for T2DM and bridging the 2 disciplines we highlight some key gene-nutrient interactions.

Metabolic syndrome

Metabolic syndrome is not a disease per se, but is a term that highlights traits that may have an increased risk of disease, approximately 2-fold for cardiovascular disease and 5-fold or more for type 2 diabetes mellitus. Obesity and insulin resistance are believed to be at the core of most cases of metabolic syndrome, although further research is required to truly understand the pathophysiology behind the syndrome and the gene-environment interactions that increase susceptibility. The mainstay of treatment remains lifestyle changes with exercise and diet to induce weight loss and pharmacologic intervention to treat atherogenic dyslipidemia, hypertension, and hyperglycemia.

Differentiated human stem cells resemble fetal, not adult, β cells

Human pluripotent stem cells (hPSCs) have the potential to generate any human cell type, and one widely recognized goal is to make pancreatic β cells. To this end, comparisons between differentiated cell types produced in vitro and their in vivo counterparts are essential to validate hPSC-derived cells. Genome-wide transcriptional analysis of sorted insulin-expressing (INS(+)) cells derived from three independent hPSC lines, human fetal pancreata, and adult human islets points to two major conclusions: (i) Different hPSC lines produce highly similar INS(+) cells and (ii) hPSC-derived INS(+) (hPSC-INS(+)) cells more closely resemble human fetal β cells than adult β cells. This study provides a direct comparison of transcriptional programs between pure hPSC-INS(+) cells and true β cells and provides a catalog of genes whose manipulation may convert hPSC-INS(+) cells into functional β cells.

Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes

OBJECTIVE

Paralleling the rise of pediatric obesity, the prevalence of impaired glucose tolerance (IGT) and type 2 diabetes (T2D) is increasing among youth. In this study, we asked whether the co-occurrence of risk alleles in or near five genes modulating insulin secretion (TCF7L2 rs7903146, IGF2BP2 rs4402960, CDKAL1 rs7754840, HHEX rs1111875, and HNF1A rs1169288) is associated with a higher risk of IGT/T2D in obese children and adolescents.

RESEARCH DESIGN AND METHODS

We studied 714 obese subjects (290 boys and 424 girls; mean age 13.6 ± 3.1 years; mean z score BMI 2.2 ± 0.4) and evaluated the insulin secretion by using the oral minimal model and, in a subgroup of 37 subjects, the hyperglycemic clamp. Also, 203 subjects were followed up for a mean of 2.1 years.

RESULTS

We observed that the increase of risk alleles was associated with a progressive worsening of insulin secretion (P < 0.001) mainly due to an impairment of the dynamic phase of insulin secretion (P = 0.004); the higher the number of the risk alleles, the higher the chance of progression from normal glucose tolerance (NGT) to IGT/T2D (P = 0.022). Also, for those who were IGT at baseline, a higher risk score was associated with a lower odds to revert to NGT (P = 0.026).

CONCLUSIONS

Obese children and adolescents developing IGT/T2D have a higher genetic predisposition than those who do not show these diseases, and this predisposition is mainly related to gene variants modulating the early phase of insulin secretion. Although these data are very interesting, they need to be replicated in other cohorts.

HOMA and Matsuda indices of insulin sensitivity: poor correlation with minimal model-based estimates of insulin sensitivity in longitudinal settings

AIMS/HYPOTHESIS

Little is known about the performance of surrogates in assessing changes in insulin sensitivity over time. This report compared updated HOMA of insulin sensitivity (HOMA2-%S) and the Matsuda index from OGTTs with minimal model-based estimates of insulin sensitivity (SI) from frequently sampled IVGTTs (FSIGTs) in longitudinal settings and cross-sectional settings.

METHODS

Two longitudinal studies were used: one a natural observational study in which 338 individuals were followed for a median of 4 years; one a clinical treatment study in which 97 individuals received pioglitazone treatment and were followed for 1 year. Pairs of OGTTs and FSIGTs were performed at baseline and follow-up. Correlations were computed. Impact of measurement uncertainty was investigated through simulation studies.

RESULTS

Correlations between HOMA2-%S and SI from baseline or follow-up data were in the range reported previously (0.61-0.69). By contrast, correlations for changes over time were only 0.35-0.39. The corresponding correlations between the Matsuda index and SI were 0.66-0.72 for cross-sectional data and 0.40-0.48 for longitudinal change. Correlations for changes were significantly lower than the cross-sectional correlations in both studies (p < 0.03). Simulation results demonstrated that the reduced correlations for change were not explained by error propagation, supporting a real limitation of surrogates to fully capture longitudinal changes in insulin sensitivity.

CONCLUSIONS/INTERPRETATION

HOMA and Matsuda indices derived from cross-sectional data should be used cautiously in assessing longitudinal changes in insulin sensitivity.

Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits

Over the past 8 years, the genetics of complex traits have benefited from an unprecedented advancement in the identification of common variant loci for diseases such as type 2 diabetes (T2D). The ability to undertake genome-wide association studies in large population-based samples for quantitative glycaemic traits has permitted us to explore the hypothesis that models arising from studies in non-diabetic individuals may reflect mechanisms involved in the pathogenesis of diabetes. Amongst 88 T2D risk and 72 glycaemic trait loci, only 29 are shared and show disproportionate magnitudes of phenotypic effects. Important mechanistic insights have been gained regarding the physiological role of T2D loci in disease predisposition through the elucidation of their contribution to glycaemic trait variability. Further investigation is warranted to define causal variants within these loci, including functional characterisation of associated variants, to dissect their role in disease mechanisms and to enable clinical translation.

The architecture of risk for type 2 diabetes: understanding Asia in the context of global findings

The prevalence of Type 2 diabetes is rising rapidly in both developed and developing countries. Asia is developing as the epicentre of the escalating pandemic, reflecting rapid transitions in demography, migration, diet, and lifestyle patterns. The effective management of Type 2 diabetes in Asia may be complicated by differences in prevalence, risk factor profiles, genetic risk allele frequencies, and gene-environment interactions between different Asian countries, and between Asian and other continental populations. To reduce the worldwide burden of T2D, it will be important to understand the architecture of T2D susceptibility both within and between populations. This review will provide an overview of known genetic and nongenetic risk factors for T2D, placing the results from Asian studies in the context of broader global research. Given recent evidence from large-scale genetic studies of T2D, we place special emphasis on emerging knowledge about the genetic architecture of T2D and the potential contribution of genetic effects to population differences in risk.

A fasting insulin-raising allele at IGF1 locus is associated with circulating levels of IGF-1 and insulin sensitivity

Background

A meta-analysis of genome-wide data reported the discovery of the rs35767 polymorphism near IGF1 with genome-wide significant association with fasting insulin levels. However, it is unclear whether the effects of this polymorphism on fasting insulin are mediated by a reduced insulin sensitivity or impaired insulin clearance. We investigated the effects of the rs35767 polymorphism on circulating IGF-1 levels, insulin sensitivity, and insulin clearance.

Methodology/Principal Findings

Two samples of adult nondiabetic white Europeans were studied. In sample 1 (n=569), IGF-1 levels were lower in GG genotype carriers compared with A allele carriers (190±77 vs. 218±97 ng/ml, respectively; P=0.007 after adjusting for age, gender, and BMI). Insulin sensitivity assessed by euglycaemic-hyperinsulinemic clamp was lower in GG genotype carriers compared with A allele carriers (8.9±4.1 vs. 10.1±5.1 mg x Kg^-1 free fat mass x min^-1, respectively; P=0.03 after adjusting for age, gender, and BMI). The rs35767 polymorphism did not show significant association with insulin clearance. In sample 2 (n=859), IGF-1 levels were lower in GG genotype carriers compared with A allele carriers (155±60 vs. 164±63 ng/ml, respectively; P=0.02 after adjusting for age, gender, and BMI). Insulin sensitivity, as estimated by the HOMA index, was lower in GG genotype carriers compared with A allele carriers (2.8±2.2 vs. 2.5±1.3, respectively; P=0.03 after adjusting for age, gender, and BMI).

Conclusion/Significance

The rs35767 polymorphism near IGF1 was associated with circulating IGF-1 levels, and insulin sensitivity with carriers of the GG genotype exhibiting lower IGF-1 concentrations and insulin sensitivity as compared with subjects carrying the A allele.

Fatty Acid desaturase gene polymorphisms and metabolic measures in schizophrenia and bipolar patients taking antipsychotics

Atypical antipsychotics have become a common therapeutic option in both schizophrenia and bipolar disorder. However, these medications come with a high risk of metabolic side effects, particularly dyslipidemia and insulin resistance. Therefore, identification of patients who are at increased risk for metabolic side effects is of great importance. The genetics of fatty acid metabolism is one area of research that may help identify such patients. Therefore, in this present study, we aimed to determine the effect of one commonly studied genetic polymorphism from both fatty acid desaturase 1 (FADS1) and FADS2 gene on a surrogate measure of insulin resistance and lipid levels in a metabolically high-risk population of patients largely exposed to atypical antipsychotics. This study used a cross-sectional design, fasting blood draws, and genetic analysis to investigate associations between polymorphisms, haplotypes, and metabolic measures. A total of 320 subjects with schizophrenia (n = 226) or bipolar disorder (n = 94) were included in this study. The mean age of the population was 42.5 years and 45% were male. A significant association between FADS1 and FADS2 haplotypes was found with insulin resistance while controlling for confounders. Further investigation is required to replicate this finding.

Moving on from GWAS: functional studies on the G6PC2 gene implicated in the regulation of fasting blood glucose

Genome-wide association studies (GWAS) have shown that single-nucleotide polymorphisms (SNPs) in G6PC2 are the most important common determinants of variations in fasting blood glucose (FBG) levels. Molecular studies examining the functional impact of these SNPs on G6PC2 gene transcription and splicing suggest that they affect FBG by directly modulating G6PC2 expression. This conclusion is supported by studies on G6pc2 knockout (KO) mice showing that G6pc2 represents a negative regulator of basal glucose-stimulated insulin secretion that acts by hydrolyzing glucose-6-phosphate, thereby reducing glycolytic flux and opposing the action of glucokinase. Suppression of G6PC2 activity might, therefore, represent a novel therapy for lowering FBG and the risk of cardiovascular-associated mortality. GWAS and G6pc2 KO mouse studies also suggest that G6PC2 affects other aspects of beta cell function. The evolutionary benefit conferred by G6PC2 remains unclear, but it is unlikely to be related to its ability to modulate FBG.

Bridging the gap between genetic associations and molecular mechanisms for type 2 diabetes

Type 2 diabetes is a global pandemic for which there is currently no disease-modifying treatment. New and targeted therapeutics are greatly needed, but progress in identifying novel targets for therapeutic intervention is severely hampered by poor understanding of disease pathogenesis. Over the past 6 years, the success of genome-wide association studies has led to an unprecedented increase in the number of loci robustly associating with type 2 diabetes risk. Each of these signals offers the opportunity to uncover biological insights into disease pathogenesis, which, if harnessed effectively, hold the promise to deliver new pathways for therapeutic intervention, strategies for patient stratification, and potentially, biomarkers for identifying those at greatest risk of developing diabetes. We review the progress that has been made and the approaches being adopted and discuss the inherent challenges in moving from association signals, which largely map to poorly annotated sequence, to transcripts, mechanisms, and disease biology.

Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals

AIMS/HYPOTHESIS

Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies.

METHODS

We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR.

RESULTS

We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (RBJ [also known as DNAJC27], QPTCL: effect sizes -0.068 and -0.107 SD, respectively), HDL-cholesterol (SLC39A8: -0.065 SD, MTCH2: -0.039 SD), and diastolic BP (SLC39A8: -0.069 SD), and higher and lower levels of LDL- and total cholesterol (QPTCL: 0.041 and 0.042 SDs, respectively, FLJ35779 [also known as POC5]: -0.042 and -0.041 SDs, respectively) (all p < 2.4 × 10(-4)), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (GRB14: 0.069 SD) and lower fasting glucose levels (CPEB4: -0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (-0.005 SD), diastolic BP (-0.006 SD) and 2 h glucose (-0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (-0.015 SD) and higher triacylglycerol levels (0.014 SD) (all p < 2.9 × 10(-3)), independent of BMI and/or WHR.

CONCLUSIONS/INTERPRETATION

These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities.

Association of risk variants for type 2 diabetes and hyperglycemia with gestational diabetes

OBJECTIVE

The aim of this study was to investigate the association of risk variants for type 2 diabetes (T2D) and hyperglycemia with gestational diabetes (GDM).

DESIGN AND METHODS

Five hundred and thirty-three Finnish women who were diagnosed with GDM and 407 controls with normal glucose tolerance during the pregnancy were genotyped for 69 single-nucleotide polymorphisms (SNPs) which have been previously verified as susceptibility risk variants for T2D and hyperglycemia. All participants underwent an oral glucose tolerance test at the follow-up study after the index pregnancy.

RESULTS

Risk variants rs10830963 and rs1387153 of MTNR1B were significantly associated with GDM (odds ratio (OR)=1.62 (95% CI 1.34-1.96), P=4.5 × 10⁻⁷ and 1.38 (1.14-1.66), P=7.6 × 10⁻⁴ respectively). Both SNPs of MTNR1B were also significantly associated with elevated fasting glucose level and reduced insulin secretion at follow-up. Additionally, risk variants rs9939609 of FTO, rs2796441 of TLE1, rs560887 of G6PC2, rs780094 of GCKR, rs7903146 of TCF7L2 and rs11708067 of ADCY5 showed nominally significant associations with GDM (OR range from 1.25 to 1.30).

CONCLUSIONS

Our study suggests that GDM and T2D share a similar genetic background. Our findings also provide further evidence that risk variants of MTNR1B are associated with GDM by increasing fasting plasma glucose and decreasing insulin secretion.

Population genomics of cardiometabolic traits: design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies.

Systematic evaluation of validated type 2 diabetes and glycaemic trait loci for association with insulin clearance

AIMS/HYPOTHESIS

Insulin clearance is a highly heritable trait, for which few quantitative trait loci have been discovered. We sought to determine whether validated type 2 diabetes and/or glycaemic trait loci are associated with insulin clearance.

METHODS

Hyperinsulinaemic-euglycaemic clamps were performed in two Hispanic-American family cohorts totalling 1329 participants in 329 families. The Metabochip was used to fine-map about 50 previously identified loci for type 2 diabetes, fasting glucose, fasting insulin, 2 h glucose or HbA1c. This resulted in 17,930 variants, which were tested for association with clamp-derived insulin clearance via meta-analysis of the two cohorts.

RESULTS

In the meta-analysis, 38 variants located within seven loci demonstrated association with insulin clearance (p < 0.001). The top signals for each locus were rs10241087 (DGKB/TMEM195 [TMEM195 also known as AGMO]) (p = 4.4 × 10(-5)); chr1:217605433 (LYPLAL1) (p = 3.25 × 10(-4)); rs2380949 (GLIS3) (p = 3.4 × 10(-4)); rs55903902 (FADS1) (p = 5.6 × 10(-4)); rs849334 (JAZF1) (p = 6.4 × 10(-4)); rs35749 (IGF1) (p = 6.7 × 10(-4)); and rs9460557 (CDKAL1) (p = 6.8 × 10(-4)).

CONCLUSIONS/INTERPRETATION

While the majority of validated loci for type 2 diabetes and related traits do not appear to influence insulin clearance in Hispanics, several of these loci do show evidence of association with this trait. It is therefore possible that these loci could have pleiotropic effects on insulin secretion, insulin sensitivity and insulin clearance.

G6PC2: a negative regulator of basal glucose-stimulated insulin secretion

Elevated fasting blood glucose (FBG) is associated with increased risk for the development of type 2 diabetes and cardiovascular-associated mortality. Genome-wide association studies (GWAS) have linked polymorphisms in G6PC2 with variations in FBG and body fat, although not insulin sensitivity or glucose tolerance. G6PC2 encodes an islet-specific, endoplasmic reticulum-resident glucose-6-phosphatase catalytic subunit. A combination of in situ perfused pancreas, in vitro isolated islet, and in vivo analyses were used to explore the function of G6pc2 in mice. G6pc2 deletion had little effect on insulin sensitivity and glucose tolerance, whereas body fat was reduced in female G6pc2 knockout (KO) mice on both a chow and high-fat diet, observations that are all consistent with human GWAS data. G6pc2 deletion resulted in a leftward shift in the dose-response curve for glucose-stimulated insulin secretion (GSIS). As a consequence, under fasting conditions in which plasma insulin levels were identical, blood glucose levels were reduced in G6pc2 KO mice, again consistent with human GWAS data. Glucose-6-phosphatase activity was reduced, whereas basal cytoplasmic calcium levels were elevated in islets isolated from G6pc2 KO mice. These data suggest that G6pc2 represents a novel, negative regulator of basal GSIS that acts by hydrolyzing glucose-6-phosphate, thereby reducing glycolytic flux.

Aldosterone deficiency prevents high-fat-feeding-induced hyperglycaemia and adipocyte dysfunction in mice

AIMS/HYPOTHESIS

Obesity is associated with aldosterone excess, hypertension and the metabolic syndrome, but the relative contribution of aldosterone to obesity-related complications is debated. We previously demonstrated that aldosterone impairs insulin secretion, and that genetic aldosterone deficiency increases glucose-stimulated insulin secretion in vivo. We hypothesised that elimination of endogenous aldosterone would prevent obesity-induced insulin resistance and hyperglycaemia.

METHODS

Wild-type and aldosterone synthase-deficient (As (-/-)) mice were fed a high-fat (HF) or normal chow diet for 12 weeks. We assessed insulin sensitivity and insulin secretion using clamp methodology and circulating plasma adipokines, and examined adipose tissue via histology.

RESULTS

HF diet induced weight gain similarly in the two groups, but As (-/-) mice were protected from blood glucose elevation. HF diet impaired insulin sensitivity similarly in As (-/-) and wild-type mice, assessed by hyperinsulinaemic-euglycaemic clamps. Fasting and glucose-stimulated insulin were higher in HF-fed As (-/-) mice than in wild-type controls. Although there was no difference in insulin sensitivity during HF feeding in As (-/-) mice compared with wild-type controls, fat mass, adipocyte size and adiponectin increased, while adipose macrophage infiltration decreased. HF feeding significantly increased hepatic steatosis and triacylglycerol content in wild-type mice, which was attenuated in aldosterone-deficient mice.

CONCLUSIONS/INTERPRETATION

These studies demonstrate that obesity induces insulin resistance independently of aldosterone and adipose tissue inflammation, and suggest a novel role for aldosterone in promoting obesity-induced beta cell dysfunction, hepatic steatosis and adipose tissue inflammation.

Recent progress in the use of genetics to understand links between type 2 diabetes and related metabolic traits

Genome-wide association studies have identified genetic variants associated with increased risk of type 2 diabetes. The aim of this review is to highlight some of the insights into the mechanism underlying type 2 diabetes provided by genetic association studies.

Genetics of type 2 diabetes and potential clinical implications

Type 2 diabetes (T2DM) is a common complex metabolic disorder that has a strong genetic component. Recent advances in genome-wide association studies have revolutionized our knowledge regarding the genetics of T2DM. There are at least 64 common genetic variants that are strongly associated with T2DM. However, the pathophysiologic roles of these variants are mostly unknown and require further functional characterization. The variants identified so far have a small effect size and their added effect explains less than 10 % of the T2DM heritability. The current ongoing whole exome and whole genome studies of T2DM are focused on identifying functionally important rare variants that have a stronger effect. Through these efforts, we will have a better understanding of the genetic architecture of T2DM and its pathophysiology. The potential clinical applications of genetic studies of T2DM include risk prediction, identification of novel therapeutic targets, genetic prediction of efficacy and toxicity of anti-diabetic medications, and eventually optimization of patient care through personalized genomic medicine. We hope further research in genetics of T2DM could aid patient care and improve outcomes of T2DM patients.

Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion

Insulin secretion has a crucial role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5-5%) and rare (MAF < 0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip. We identified low-frequency coding variants associated with fasting proinsulin concentrations at the SGSM2 and MADD GWAS loci and three new genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1 and PAM. We also show that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs both nearby and megabases away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.

What will diabetes genomes tell us?

A 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.

Factor structure underlying components of allostatic load

Allostatic load is a commonly used metric of health risk based on the hypothesis that recurrent exposure to environmental demands (e.g., stress) engenders a progressive dysregulation of multiple physiological systems. Prominent indicators of response to environmental challenges, such as stress-related hormones, sympatho-vagal balance, or inflammatory cytokines, comprise primary allostatic mediators. Secondary mediators reflect ensuing biological alterations that accumulate over time and confer risk for clinical disease but overlap substantially with a second metric of health risk, the metabolic syndrome. Whether allostatic load mediators covary and thus warrant treatment as a unitary construct remains to be established and, in particular, the relation of allostatic load parameters to the metabolic syndrome requires elucidation. Here, we employ confirmatory factor analysis to test: 1) whether a single common factor underlies variation in physiological systems associated with allostatic load; and 2) whether allostatic load parameters continue to load on a single common factor if a second factor representing the metabolic syndrome is also modeled. Participants were 645 adults from Allegheny County, PA (30–54 years old, 82% non-Hispanic white, 52% female) who were free of confounding medications. Model fitting supported a single, second-order factor underlying variance in the allostatic load components available in this study (metabolic, inflammatory and vagal measures). Further, this common factor reflecting covariation among allostatic load components persisted when a latent factor representing metabolic syndrome facets was conjointly modeled. Overall, this study provides novel evidence that the modeled allostatic load components do share common variance as hypothesized. Moreover, the common variance suggests the existence of statistical coherence above and beyond that attributable to the metabolic syndrome.

Interactions between genetic background, insulin resistance and β-cell function

An interaction between genes and the environment is a critical component underlying the pathogenesis of the hyperglycaemia of type 2 diabetes. The development of more sophisticated techniques for studying gene variants and for analysing genetic data has led to the discovery of some 40 genes associated with type 2 diabetes. Most of these genes are related to changes in β-cell function, with a few associated with decreased insulin sensitivity and obesity. Interestingly, using quantitative traits based on continuous measures rather than dichotomous ones, it has become evident that not all genes associated with changes in fasting or post-prandial glucose are also associated with a diagnosis of type 2 diabetes. Identification of these gene variants has provided novel insights into the physiology and pathophysiology of the β-cell, including the identification of molecules involved in β-cell function that were not previously recognized as playing a role in this critical cell.

Potential of pluripotent stem cells for diabetes therapy

Diabetes mellitus type 1 (T1DM) and type 2 (T2DM) are common diseases. To date, it is widely accepted that all forms of DM lead to the loss of beta cells. Therefore, to avoid the debilitating comorbidities when glycemic control cannot be fully achieved, some would argue that beta cell replacement is the only way to cure the disease. Due to organ donor shortage, other cell sources for beta cell replacement strategies have to be employed. Pluripotent stem cells, including embryonic stem (ES) and induced pluripotent stem (iPS) cells offer a valuable alternative to provide the necessary cells to substitute organ transplants but also to serve as a model to study the onset and progression of the disease, resulting in better treatment regimens. This review will summarize recent progress in the establishment of pluripotent stem cells, their differentiation into the pancreatic lineage with a focus on two-dimensional (2D) and three-dimensional (3D) differentiation settings, the special role of iPS cells in the analysis of genetic predispositions to diabetes, and techniques that help to move current approaches to clinical applications. Particular attention, however, is also given to the long-term challenges that have to be addressed before ES or iPS cell-based therapies will become a broadly accepted treatment option.

Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program

Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats

Type 2 diabetes (T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate <3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D.

A tale of two glucose transporters: how GLUT2 re-emerged as a contender for glucose transport into the human beta cell

Finding novel causes for monogenic forms of diabetes is important as, alongside the clinical implications of such a discovery, it can identify critical proteins and pathways required for normal beta cell function in humans. It is increasingly apparent that there are significant differences between rodent and human islets. One example that has generated interest is the relative importance of the glucose transporter GLUT2 in rodent and human beta cells. The central role of GLUT2 in rodent beta cells is well established, but a number of studies have suggested that other glucose transporters, namely GLUT1 and GLUT3, may play an important role in facilitating glucose transport into human beta cells. In this issue of Diabetologia Sansbury et al (DOI: 10.1007/s00125-012-2595-0 ) report homozygous loss of function mutations in SLC2A2, which encodes GLUT2, as a rare cause of neonatal diabetes. Evidence for a beta cell defect in these subjects comes from very low birthweights, lack of endogenous insulin secretion and a requirement for insulin therapy. Neonatal diabetes is not a consistent feature of SLC2A2 mutations. It is only found in a small percentage of cases (~4%) and the diabetes largely resolves before 18 months of age. This discovery is significant as it suggests that GLUT2 plays an important role in human beta cells, but the interplay and relative roles of other transporters differ from those in rodents. This finding should encourage efforts to delineate the precise role of GLUT2 in the human beta cell at different developmental time points and is a further reminder of critical differences between human and rodent islets.

Genetic advances of type 2 diabetes in Chinese populations

In recent decades, the prevalence of type 2 diabetes in China has increased significantly, underscoring the importance of investigating the etiological mechanisms, including genetic determinants, of the disease in Chinese populations. Numerous loci conferring susceptibility to type 2 diabetes (T2D) have been identified worldwide, with most having been identified in European populations. In terms of ethnic heterogeneity in pathogenesis as well as disease predisposition, it is imperative to explore the specific genetic architecture of T2D in Han Chinese. Replication studies of European-derived susceptibility loci have been performed, validating 11 of 32 loci in Chinese populations. Genetic investigations into heritable traits related to glucose metabolism are expected to provide new insights into the pathogenesis of T2D, and such studies have already inferred some new susceptibility loci. Other than replication studies of European-derived loci, efforts have been made to identify specific susceptibility loci in Chinese populations using methods such as genome-wide association studies. These efforts have identified additional new loci for the disease. Genetic studies can facilitate the prediction of risk for T2D and also promote individualized anti-diabetic treatment. Despite many advances in the field of risk prediction and pharmacogenetics, the pace of clinical application of these findings is rather slow. As a result, more studies into the practical utility of these findings remain necessary.

Genetics of type 2 diabetes in European populations

Type 2 diabetes (T2D) has become a leading health problem throughout the world. It is caused by environmental and genetic factors, as well as interactions between the two. However, until very recently, the T2D susceptibility genes have been poorly understood. During the past 5 years, with the advent of genome-wide association studies (GWAS), a total of 58 T2D susceptibility loci have been associated with T2D risk at a genome-wide significance level (P < 5 × 10(-8) ), with evidence showing that most of these genetic variants influence pancreatic β-cell function. Most novel T2D susceptibility loci were identified through GWAS in European populations and later confirmed in other ethnic groups. Although the recent discovery of novel T2D susceptibility loci has contributed substantially to our understanding of the pathophysiology of the disease, the clinical utility of these loci in disease prediction and prognosis is limited. More studies using multi-ethnic meta-analysis, gene-environment interaction analysis, sequencing analysis, epigenetic analysis, and functional experiments are needed to identify new susceptibility T2D loci and causal variants, and to establish biological mechanisms.

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Through 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.

From genotype to human β cell phenotype and beyond

Polygenic type 2 diabetes mellitus (T2DM) is a multi-factorial disease due to the interplay between genes and the environment. Over the years, several genes/loci have been associated with this type of diabetes, with the majority of them being related to β cell dysfunction. In this review, the available information on how polymorphisms in T2DM-associated genes/loci do directly affect the properties of human islet cells are presented and discussed, including some clinical implications and the role of epigenetic mechanisms.

SLC2A2 mutations can cause neonatal diabetes, suggesting GLUT2 may have a role in human insulin secretion

AIMS

The gene SLC2A2 encodes GLUT2, which is found predominantly in pancreas, liver, kidney and intestine. In mice, GLUT2 is the major glucose transporter into pancreatic beta cells, and biallelic Slc2a2 inactivation causes lethal neonatal diabetes. The role of GLUT2 in human beta cells is controversial, and biallelic SLC2A2 mutations cause Fanconi-Bickel syndrome (FBS), with diabetes rarely reported. We investigated the potential role of GLUT2 in the neonatal period by testing whether SLC2A2 mutations can present with neonatal diabetes before the clinical features of FBS appear.

METHODS

We studied SLC2A2 in patients with transient neonatal diabetes mellitus (TNDM; n = 25) or permanent neonatal diabetes mellitus (PNDM; n = 79) in whom we had excluded the common genetic causes of neonatal diabetes, using a combined approach of sequencing and homozygosity mapping.

RESULTS

Of 104 patients, five (5%) were found to have homozygous SLC2A2 mutations, including four novel mutations (S203R, M376R, c.963+1G>A, F114LfsX16). Four out of five patients with SLC2A2 mutations presented with isolated diabetes and later developed features of FBS. Four out of five patients had TNDM (16% of our TNDM cohort of unknown aetiology). One patient with PNDM remains on insulin at 28 months.

CONCLUSIONS

SLC2A2 mutations are an autosomal recessive cause of neonatal diabetes that should be considered in consanguineous families or those with TNDM, after excluding common causes, even in the absence of features of FBS. The finding that patients with homozygous SLC2A2 mutations can have neonatal diabetes supports a role for GLUT2 in the human beta cell.

Pancreatic beta-cell function and type 2 diabetes risk: quantify the causal effect using a Mendelian randomization approach based on meta-analyses

The objective of the study is to quantify the causal effect of β-cell function on type 2 diabetes by minimizing residual confounding and reverse causation. We employed a Mendelian randomization (MR) approach using TCF7L2 variant rs7903146 as an instrument for lifelong levels of β-cell function. We first conducted two sets of meta-analyses to quantify the association of the TCF7L2 variant with the risk of type 2 diabetes among 55 436 cases and 106 020 controls from 66 studies by calculating pooled odds ratio (OR) and to quantify the associations with multiple direct or indirect measures of β-cell function among 35 052 non-diabetic individuals from 31 studies by calculating pooled mean difference. We further applied the method of MR to obtain the causal estimates for the effect of β-cell function on type 2 diabetes risk based on findings from the meta-analyses. The OR [95% confidence interval (CI)] was 0.87 (0.81-0.93) for each five unit increment in homeostasis model assessment of insulin secretion (HOMA-%B) (P = 3.0 × 10(-5)). In addition, for measures based on intravenous glucose tolerance test, ORs (95% CI) associated with type 2 diabetes risk were 0.24 (0.08-0.74) (P = 0.01) and 0.14 (0.04-0.48) (P = 0.002) for per 1 standard deviation increment in insulin sensitivity index and disposition index, respectively. Findings from the present study lend support to a causal role of pancreatic β-cell function itself in the etiology of type 2 diabetes.

Exercise training, genetics and type 2 diabetes-related phenotypes

Type 2 diabetes mellitus (T2DM) is at virtually pandemic levels world-wide. Diabetes has been referred to as 'a geneticist's nightmare'. However, dramatic advances in our understanding of the genetics of T2DM have occurred in the past 5 years. While endurance exercise training and increased habitual physical activity levels have consistently been shown to improve or be associated with improved T2DM-related phenotypes, there is substantial interindividual variation in these responses. There is some evidence that T2DM-related phenotype responses to exercise training are heritable, indicating that they might have a genetic basis. Genome-wide linkage studies have not identified specific chromosomal loci that could account for these differences, and no genome-wide association studies have been performed relative to T2DM-related phenotype responses to exercise training. From candidate gene studies, there are relatively strong and replicated data supporting a role for the PPARγ Pro12Ala variant in the interindividual differences in T2DM-related phenotype responses to training. This is a potentially important candidate locus because it affects T2DM susceptibility, has high biological plausibility and is the target for the primary pharmaceutical method for treating T2DM. Is it time to conduct a hypothesis-driven large-scale exercise training intervention trial based on PPARγ Pro12Ala genotype with T2DM-related phenotypes as the primary outcome measures, while also assessing potential mechanistic changes in skeletal muscle and adipose tissue? Or would it be more appropriate to propose a smaller trial to address the specific skeletal muscle and adipose tissue mechanisms affected by the interaction between the PPARγ Pro12Ala genotype and exercise training?

A systems genetics approach identifies genes and pathways for type 2 diabetes in human islets

Close to 50 genetic loci have been associated with type 2 diabetes (T2D), but they explain only 15% of the heritability. In an attempt to identify additional T2D genes, we analyzed global gene expression in human islets from 63 donors. Using 48 genes located near T2D risk variants, we identified gene coexpression and protein-protein interaction networks that were strongly associated with islet insulin secretion and HbA(1c). We integrated our data to form a rank list of putative T2D genes, of which CHL1, LRFN2, RASGRP1, and PPM1K were validated in INS-1 cells to influence insulin secretion, whereas GPR120 affected apoptosis in islets. Expression variation of the top 20 genes explained 24% of the variance in HbA(1c) with no claim of the direction. The data present a global map of genes associated with islet dysfunction and demonstrate the value of systems genetics for the identification of genes potentially involved in T2D.

The role of obesity-related genetic loci in insulin sensitivity

AIMS

Despite rapid advancements and many new diabetes susceptibility loci found in the past few years, few genetic variants associated with insulin sensitivity have been described, potentially attributable to the lack of larger cohorts examined with gold standard methods for insulin sensitivity assessment. There is a strong link between obesity and insulin sensitivity, and we hypothesized that known obesity susceptibility loci may act via effects on insulin sensitivity.

METHODS

A cohort of 71-year-old men without diabetes (Uppsala Longitudinal Study of Adult Men) underwent a euglycaemic-hyperinsulinaemic clamp and genotyping for genetic variants representing 32 loci recently reported to be associated with BMI (n = 926). The effect of these loci on the insulin sensitivity index (M/I ratio) was examined using linear regression. An in silico replication was performed in publically available data for the three top single-nucleotide polymorphisms from the Meta-Analyses of Glucose and Insulin-related traits Consortium analyses of homeostasis model assessment of insulin resistance (n = 37,037).

RESULTS

Three loci (SH2B1, MTCH2 and NEGR1) were associated with decreased insulin sensitivity at a nominal significance (P ≤ 0.05) after adjustment for BMI, but did not hold for multiple comparison correction. SH2B1 rs7359397 was also associated with homeostasis model assessment of insulin resistance in the Meta-Analyses of Glucose and Insulin-related traits Consortium data set (P = 3.9 × 10(-3)).

CONCLUSIONS

Our study supports earlier reports of SH2B1 to be of importance in insulin sensitivity and, in addition, suggests potential roles of NEGR1 and MTCH2.

Hyperglycemia and a common variant of GCKR are associated with the levels of eight amino acids in 9,369 Finnish men

We investigated the association of glycemia and 43 genetic risk variants for hyperglycemia/type 2 diabetes with amino acid levels in the population-based Metabolic Syndrome in Men (METSIM) Study, including 9,369 nondiabetic or newly diagnosed type 2 diabetic Finnish men. Plasma levels of eight amino acids were measured with proton nuclear magnetic resonance spectroscopy. Increasing fasting and 2-h plasma glucose levels were associated with increasing levels of several amino acids and decreasing levels of histidine and glutamine. Alanine, leucine, isoleucine, tyrosine, and glutamine predicted incident type 2 diabetes in a 4.7-year follow-up of the METSIM Study, and their effects were largely mediated by insulin resistance (except for glutamine). We also found significant correlations between insulin sensitivity (Matsuda insulin sensitivity index) and mRNA expression of genes regulating amino acid degradation in 200 subcutaneous adipose tissue samples. Only 1 of 43 risk single nucleotide polymorphisms for type 2 diabetes or hyperglycemia, the glucose-increasing major C allele of rs780094 of GCKR, was significantly associated with decreased levels of alanine and isoleucine and elevated levels of glutamine. In conclusion, the levels of branched-chain, aromatic amino acids and alanine increased and the levels of glutamine and histidine decreased with increasing glycemia, reflecting, at least in part, insulin resistance. Only one single nucleotide polymorphism regulating hyperglycemia was significantly associated with amino acid levels.

Exome sequencing and genetic testing for MODY

CONTEXT

Genetic testing for monogenic diabetes is important for patient care. Given the extensive genetic and clinical heterogeneity of diabetes, exome sequencing might provide additional diagnostic potential when standard Sanger sequencing-based diagnostics is inconclusive.

OBJECTIVE

The aim of the study was to examine the performance of exome sequencing for a molecular diagnosis of MODY in patients who have undergone conventional diagnostic sequencing of candidate genes with negative results.

RESEARCH DESIGN AND METHODS

We performed exome enrichment followed by high-throughput sequencing in nine patients with suspected MODY. They were Sanger sequencing-negative for mutations in the HNF1A, HNF4A, GCK, HNF1B and INS genes. We excluded common, non-coding and synonymous gene variants, and performed in-depth analysis on filtered sequence variants in a pre-defined set of 111 genes implicated in glucose metabolism.

RESULTS

On average, we obtained 45 X median coverage of the entire targeted exome and found 199 rare coding variants per individual. We identified 0-4 rare non-synonymous and nonsense variants per individual in our a priori list of 111 candidate genes. Three of the variants were considered pathogenic (in ABCC8, HNF4A and PPARG, respectively), thus exome sequencing led to a genetic diagnosis in at least three of the nine patients. Approximately 91% of known heterozygous SNPs in the target exomes were detected, but we also found low coverage in some key diabetes genes using our current exome sequencing approach. Novel variants in the genes ARAP1, GLIS3, MADD, NOTCH2 and WFS1 need further investigation to reveal their possible role in diabetes.

CONCLUSION

Our results demonstrate that exome sequencing can improve molecular diagnostics of MODY when used as a complement to Sanger sequencing. However, improvements will be needed, especially concerning coverage, before the full potential of exome sequencing can be realized.