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

Genome-wide association studies: findings at the major histocompatibility complex locus in psychosis

The major histocompatibility complex (MHC) is one of the most intensively investigated, genetically diverse regions of the genome. In its extended form, it encodes more than 400 genes critical to immunity but is also involved in many other functions. In 2009, three simultaneously published genome-wide association studies (GWAS) reported the first compelling evidence for involvement of the MHC in schizophrenia susceptibility. In this review, we describe the structure and function of the MHC, discuss some of the challenges for genetic analysis of the region, and provide an update on findings from GWAS studies before describing potential approaches to interpreting the role of the locus in schizophrenia etiology. The GWAS literature supports involvement of the MHC locus in schizophrenia susceptibility. Current evidence suggests that the MHC plays a more significant role in schizophrenia susceptibility than in other psychiatric disorders. Because of the substantial diversity at the locus, there are differences in the implicated risk variants between ancestral groups, as there are for many other disorders. This is somewhat different than the pattern emerging at other loci. The association findings presently capture large genomic regions, with at least some evidence to suggest that multiple signals may be involved. Based on notable successes in other disorders, we suggest approaches to refining association signals at the locus. Finally, we discuss that these genetic data may be used to understand how the MHC contributes to the complex etiology of schizophrenia.

Targeting the pancreatic β-cell to treat diabetes

Diabetes is a leading cause of morbidity and mortality worldwide, and predicted to affect over 500 million people by 2030. However, this growing burden of disease has not been met with a comparable expansion in therapeutic options. The appreciation of the pancreatic β-cell as a central player in the pathogenesis of both type 1 and type 2 diabetes has renewed focus on ways to improve glucose homeostasis by preserving, expanding and improving the function of this key cell type. Here, we provide an overview of the latest developments in this field, with an emphasis on the most promising strategies identified to date for treating diabetes by targeting the β-cell.

Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu

The Estonian Biobank cohort is a volunteer-based sample of the Estonian resident adult population (aged ≥18 years). The current number of participants-close to 52000--represents a large proportion, 5%, of the Estonian adult population, making it ideally suited to population-based studies. General practitioners (GPs) and medical personnel in the special recruitment offices have recruited participants throughout the country. At baseline, the GPs performed a standardized health examination of the participants, who also donated blood samples for DNA, white blood cells and plasma tests and filled out a 16-module questionnaire on health-related topics such as lifestyle, diet and clinical diagnoses described in WHO ICD-10. A significant part of the cohort has whole genome sequencing (100), genome-wide single nucleotide polymorphism (SNP) array data (20 000) and/or NMR metabolome data (11 000) available (http://www.geenivaramu.ee/for-scientists/data-release/). The data are continuously updated through periodical linking to national electronic databases and registries. A part of the cohort has been re-contacted for follow-up purposes and resampling, and targeted invitations are possible for specific purposes, for example people with a specific diagnosis. The Estonian Genome Center of the University of Tartu is actively collaborating with many universities, research institutes and consortia and encourages fellow scientists worldwide to co-initiate new academic or industrial joint projects with us.

Genetic insights into cardiometabolic risk factors

Many biochemical traits are recognised as risk factors, which contribute to or predict the development of disease. Only a few are in widespread use, usually to assist with treatment decisions and motivate behavioural change. The greatest effort has gone into evaluation of risk factors for cardiovascular disease and/or diabetes, with substantial overlap as 'cardiometabolic' risk. Over the past few years many genome-wide association studies (GWAS) have sought to account for variation in risk factors, with the expectation that identifying relevant polymorphisms would improve our understanding or prediction of disease; others have taken the direct approach of genomic case-control studies for the corresponding diseases. Large GWAS have been published for coronary heart disease and Type 2 diabetes, and also for associated biomarkers or risk factors including body mass index, lipids, C-reactive protein, urate, liver function tests, glucose and insulin. Results are not encouraging for personal risk prediction based on genotyping, mainly because known risk loci only account for a small proportion of risk. Overlap of allelic associations between disease and marker, as found for low density lipoprotein cholesterol and heart disease, supports a causal association, but in other cases genetic studies have cast doubt on accepted risk factors. Some loci show unexpected effects on multiple markers or diseases. An intriguing feature of risk factors is the blurring of categories shown by the correlation between them and the genetic overlap between diseases previously thought of as distinct. GWAS can provide insight into relationships between risk factors, biomarkers and diseases, with potential for new approaches to disease classification.

Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants

Type 2 diabetes affects over 300 million people, causing severe complications and premature death, yet the underlying molecular mechanisms are largely unknown. Pancreatic islet dysfunction is central for type 2 diabetes pathogenesis, and therefore understanding islet genome regulation could provide valuable mechanistic insights. We have now mapped and examined the function of human islet cis-regulatory networks. We identify genomic sequences that are targeted by islet transcription factors to drive islet-specific gene activity, and show that most such sequences reside in clusters of enhancers that form physical 3D chromatin domains. We find that sequence variants associated with type 2 diabetes and fasting glycemia are enriched in these clustered islet enhancers, and identify trait-associated variants that disrupt DNA-binding and islet enhancer activity. Our studies illustrate how islet transcription factors interact functionally with the epigenome, and provide systematic evidence that dysregulation of islet enhancers is relevant to the mechanisms underlying type 2 diabetes.

Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease

The large-scale genome-wide association studies conducted so far identified numerous allelic variants associated with type 2 diabetes (T2D), coronary heart disease (CHD) and related cardiometabolic traits. Many T2D- and some CHD-risk loci are also linked with metabolic traits that are hallmarks of insulin resistance (lipid profile, abdominal adiposity). Chromosome 9p21.3 and 2q36.3 are the most consistently replicated loci appearing to share genetic risk for both T2D and CHD. Although many glucose- or insulin-related trait variants are also linked with T2D risk, none of them is associated with CHD. Hence, while T2D and CHD are strongly clinically linked together, further ongoing analyses are needed to clarify the existence of a shared underlying genetic signature of these complex traits. The present review summarizes an updated picture of T2D-CHD genetics as of 2013, aiming to provide a platform for targeted studies dissecting the contribution of genetics to the phenotypic heterogeneity of T2D and CHD.

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 potential of novel biomarkers to improve risk prediction of type 2 diabetes

The incidence of type 2 diabetes can be reduced substantially by implementing preventive measures in high-risk individuals, but this requires prior knowledge of disease risk in the individual. Various diabetes risk models have been designed, and these have all included a similar combination of factors, such as age, sex, obesity, hypertension, lifestyle factors, family history of diabetes and metabolic traits. The accuracy of prediction models is often assessed by the area under the receiver operating characteristic curve (AROC) as a measure of discrimination, but AROCs should be complemented by measures of calibration and reclassification to estimate the incremental value of novel biomarkers. This review discusses the potential of novel biomarkers to improve model accuracy. The range of molecules that serve as potential predictors of type 2 diabetes includes genetic variants, RNA transcripts, peptides and proteins, lipids and small metabolites. Some of these biomarkers lead to a statistically significant increase of model accuracy, but their incremental value currently seems too small for routine clinical use. However, only a fraction of potentially relevant biomarkers have been assessed with regard to their predictive value. Moreover, serial measurements of biomarkers may help determine individual risk. In conclusion, current risk models provide valuable tools of risk estimation, but perform suboptimally in the prediction of individual diabetes risk. Novel biomarkers still fail to have a clinically applicable impact. However, more efficient use of biomarker data and technological advances in their measurement in clinical settings may allow the development of more accurate predictive models in the future.

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.

Genetic framework of type 2 diabetes mellitus

More than 100 genes associated with the risk of type 2 diabetes mellitus (T2DM) are now established. Most of them affect insulin secretion, adipogenesis and insulin resistance, but the exact molecular mechanisms determining their involvement in the pathogenesis of T2DM are not understood completely.

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.

Trans-ethnic fine mapping identifies a novel independent locus at the 3' end of CDKAL1 and novel variants of several susceptibility loci for type 2 diabetes in a Han Chinese population

AIMS/HYPOTHESIS

Candidate gene and genome-wide association studies have identified ∼60 susceptibility loci for type 2 diabetes. A majority of these loci have been discovered and tested only in European populations. The aim of this study was to assess the presence and extent of trans-ethnic effects of these loci in an East Asian population.

METHODS

A total of 9,335 unrelated Chinese Han individuals, including 4,535 with type 2 diabetes and 4,800 non-diabetic ethnically matched controls, were genotyped using the Illumina 200K Metabochip. We tested 50 established loci for type 2 diabetes and related traits (fasting glucose, fasting insulin, 2 h glucose). Disease association with the additive model of inheritance was analysed with logistic regression.

RESULTS

We found that 14 loci significantly transferred to the Chinese population, with two loci (p = 5.7 × 10(-12) for KCNQ1; p = 5.0 × 10(-8) for CDKN2A/B-CDKN2BAS) reaching independent genome-wide statistical significance. Five of these 14 loci had similar lead single-nucleotide polymorphisms (SNPs) as were found in the European studies while the other nine were different. Further stepwise conditional analysis identified a total of seven secondary signals and an independent novel locus at the 3' end of CDKAL1.

CONCLUSIONS/INTERPRETATION

These results suggest that many loci associated with type 2 diabetes are commonly shared between European and Chinese populations. Identification of population-specific SNPs may increase our understanding of the genetic architecture underlying type 2 diabetes in different ethnic populations.

Lipin-1 and lipin-3 together determine adiposity in vivo

The lipin protein family of phosphatidate phosphatases has an established role in triacylglycerol synthesis and storage. Physiological roles for lipin-1 and lipin-2 have been identified, but the role of lipin-3 has remained mysterious. Using lipin single- and double-knockout models we identified a cooperative relationship between lipin-3 and lipin-1 that influences adipogenesis in vitro and adiposity in vivo. Furthermore, natural genetic variations in Lpin1 and Lpin3 expression levels across 100 mouse strains correlate with adiposity. Analysis of PAP activity in additional metabolic tissues from lipin single- and double-knockout mice also revealed roles for lipin-1 and lipin-3 in spleen, kidney, and liver, for lipin-1 alone in heart and skeletal muscle, and for lipin-1 and lipin-2 in lung and brain. Our findings establish that lipin-1 and lipin-3 cooperate in vivo to determine adipose tissue PAP activity and adiposity, and may have implications in understanding the protection of lipin-1-deficient humans from overt lipodystrophy.

Association of serine racemase gene variants with type 2 diabetes in the Chinese Han population

A genome‐wide association study in the Chinese Han population has identified several novel genetic variants of the serine racemase (SRR) gene in type 2 diabetes. Our purpose was to systematically evaluate the contribution of SRR variants in the Chinese Han population. rs391300 and rs4523957 in SRR were genotyped respectively in the two independent populations. A meta‐analysis was used to estimate the effects of SRR in 21,305 Chinese Han individuals. Associations between single‐nucleotide polymorphisms and diabetes‐related phenotypes were analyzed among 2,615 newly diagnosed type 2 diabetes patients and 5,029 controls. Neither rs391300 nor rs4523957 were associated with type 2 diabetes in populations. Furthermore, meta‐analysis did not confirm an association between type 2 diabetes and SRR. In the controls, rs391300‐A and rs4523957‐G were associated with higher 30‐min plasma glucose in an oral glucose tolerance test. The present study did not confirm that SRR was associated with type 2 diabetes.

Clinical and genetic determinants of progression of type 2 diabetes: a DIRECT study

OBJECTIVE

To identify the clinical and genetic factors that explain why the rate of diabetes progression is highly variable between individuals following diagnosis of type 2 diabetes.

RESEARCH DESIGN AND METHODS

We studied 5,250 patients with type 2 diabetes using comprehensive electronic medical records in Tayside, Scotland, from 1992 onward. We investigated the association of clinical, biochemical, and genetic factors with the risk of progression of type 2 diabetes from diagnosis to the requirement of insulin treatment (defined as insulin treatment or HbA1c ≥8.5% [69 mmol/mol] treated with two or more noninsulin therapies).

RESULTS

Risk of progression was associated with both low and high BMI. In an analysis stratified by BMI and HbA1c at diagnosis, faster progression was independently associated with younger age at diagnosis, higher log triacylglyceride (TG) concentrations (hazard ratio [HR] 1.28 per mmol/L [95% CI 1.15-1.42]) and lower HDL concentrations (HR 0.70 per mmol/L [95% CI 0.55-0.87]). A high Genetic Risk Score derived from 61 diabetes risk variants was associated with a younger age at diagnosis and a younger age when starting insulin but was not associated with the progression rate from diabetes to the requirement of insulin treatment.

CONCLUSIONS

Increased TG and low HDL levels are independently associated with increased rate of progression of diabetes. The genetic factors that predispose to diabetes are different from those that cause rapid progression of diabetes, suggesting a difference in biological process that needs further investigation.

Centenarians as super-controls to assess the biological relevance of genetic risk factors for common age-related diseases: a proof of principle on type 2 diabetes

Genetic association studies of age-related, chronic human diseases often suffer from a lack of power to detect modest effects. Here we propose an alternative approach of including healthy centenarians as a more homogeneous and extreme control group. As a proof of principle we focused on type 2 diabetes (T2D) and assessed allelic/genotypic associations of 31 SNPs associated with T2D, diabetes complications and metabolic diseases and SNPs of genes relevant for telomere stability and age-related diseases. We hypothesized that the frequencies of risk variants are inversely correlated with decreasing health and longevity. We performed association analyses comparing diabetic patients and non-diabetic controls followed by association analyses with extreme phenotypic groups (T2D patients with complications and centenarians). Results drew attention to rs7903146 (TCF7L2 gene) that showed a constant increase in the frequencies of risk genotype (TT) from centenarians to diabetic patients who developed macro-complications and the strongest genotypic association was detected when diabetic patients were compared to centenarians (p_value = 9.066*10⁻⁷). We conclude that robust and biologically relevant associations can be obtained when extreme phenotypes, even with a small sample size, are compared.

PROX1 gene variant is associated with fasting glucose change after antihypertensive treatment

STUDY OBJECTIVE

To assess the relationship of the 33 single nucleotide polymorphisms (SNPs) previously associated with fasting glucose in Caucasians in genome-wide association studies (GWAS) with glucose response to antihypertensive drugs shown to increase risk for hyperglycemia and diabetes.

DESIGN

Randomized, multicenter clinical trial.

PATIENTS

A total of 456 Caucasian men and women with uncomplicated hypertension.

MEASUREMENTS AND MAIN RESULTS

The Pharmacogenomic Evaluation of Antihypertensives Responses study evaluated blood pressure and glucose response in uncomplicated hypertensive patients randomized to either atenolol or hydrochlorothiazide (HCTZ) monotherapy, followed by combination therapy with both agents. Association of these SNPs with atenolol- or HCTZ-induced glucose response was evaluated in 456 Caucasian patients using linear regression adjusting for age, sex, body mass index, baseline glucose, baseline insulin, and principal component for ancestry. The SNP rs340874 in the 5' region of PROX1 gene was significantly associated with atenolol-induced glucose change (p=0.0013). Participants harboring the C allele of this SNP had greater glucose elevation after approximately 9 weeks of atenolol monotherapy (β = +2.39 mg/dl per C allele), consistent with the direction of effect in fasting glucose GWAS, that showed the C allele is associated with higher fasting glucose.

CONCLUSION

These data suggest that PROX1 SNP rs340874, discovered in fasting glucose GWAS, may also be a pharmacogenetic risk factor for antihypertensive-induced hyperglycemia. β-blockers and thiazides may interact with genetic risk factors to increase risk for dysglycemia and diabetes.

Association of ketone body levels with hyperglycemia and type 2 diabetes in 9,398 Finnish men

We investigated the association of the levels of ketone bodies (KBs) with hyperglycemia and with 62 genetic risk variants regulating glucose levels or type 2 diabetes in the population-based Metabolic Syndrome in Men (METSIM) study, including 9,398 Finnish men without diabetes or newly diagnosed type 2 diabetes. Increasing fasting and 2-h plasma glucose levels were associated with elevated levels of acetoacetate (AcAc) and β-hydroxybutyrate (BHB). AcAc and BHB predicted an increase in the glucose area under the curve in an oral glucose tolerance test, and AcAc predicted the conversion to type 2 diabetes in a 5-year follow-up of the METSIM cohort. Impaired insulin secretion, but not insulin resistance, explained these findings. Of the 62 single nucleotide polymorphisms associated with the risk of type 2 diabetes or hyperglycemia, the glucose-increasing C allele of GCKR significantly associated with elevated levels of fasting BHB levels. Adipose tissue mRNA expression levels of genes involved in ketolysis were significantly associated with insulin sensitivity (Matsuda index). In conclusion, high levels of KBs predicted subsequent worsening of hyperglycemia, and a common variant of GCKR was significantly associated with BHB levels.

Mendelian randomization studies do not support a causal role for reduced circulating adiponectin levels in insulin resistance and type 2 diabetes

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

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.

Linkage of type 2 diabetes on chromosome 9p24 in Mexican Americans: additional evidence from the Veterans Administration Genetic Epidemiology Study (VAGES)

OBJECTIVE

Type 2 diabetes (T2DM) is a complex metabolic disease and is more prevalent in certain ethnic groups such as the Mexican Americans. The goal of our study was to perform a genome-wide linkage (GWL) analysis to localize T2DM susceptibility loci in Mexican Americans.

METHODS

We used the phenotypic and genotypic data from 1,122 Mexican-American individuals (307 families) who participated in the Veterans Administration Genetic Epidemiology Study (VAGES). GWL analysis was performed using the variance components approach. Data from 2 additional Mexican-American family studies, the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), were combined with the VAGES data to test for improved linkage evidence.

RESULTS

After adjusting for covariate effects, T2DM was found to be under significant genetic influences (h2 = 0.62, p = 2.7 × 10(-6)). The strongest evidence for linkage of T2DM occurred between markers D9S1871 and D9S2169 on chromosome 9p24.2-p24.1 (LOD = 1.8). Given that we previously reported suggestive evidence for linkage of T2DM at this region also in SAFDGS, we found the significant and increased linkage evidence (LOD = 4.3, empirical p = 1.0 × 10(-5), genome-wide p = 1.6 × 10(-3)) for T2DM at the same chromosomal region, when we performed a GWL analysis of the VAGES data combined with the SAFHS and SAFDGS data.

CONCLUSION

Significant T2DM linkage evidence was found on chromosome 9p24 in Mexican Americans. Importantly, the chromosomal region of interest in this study overlaps with several recent genome-wide association studies involving T2DM-related traits. Given its overlap with such findings and our own initial T2DM association findings in the 9p24 chromosomal region, high throughput sequencing of the linked chromosomal region could identify the potential causal T2DM genes.

Multilocus Genetic Risk Scores for Coronary Heart Disease Prediction

Objective—

Current guidelines do not support the use of genetic profiles in risk assessment of coronary heart disease (CHD). However, new single nucleotide polymorphisms associated with CHD and intermediate cardiovascular traits have recently been discovered. We aimed to compare several multilocus genetic risk score (MGRS) in terms of association with CHD and to evaluate clinical use.

Approach and Results—

We investigated 6 Swedish prospective cohort studies with 10 612 participants free of CHD at baseline. We developed 1 overall MGRS based on 395 single nucleotide polymorphisms reported as being associated with cardiovascular traits, 1 CHD-specific MGRS, including 46 single nucleotide polymorphisms, and 6 trait-specific MGRS for each established CHD risk factors. Both the overall and the CHD-specific MGRS were significantly associated with CHD risk (781 incident events; hazard ratios for fourth versus first quartile, 1.54 and 1.52; P <0.001) and improved risk classification beyond established risk factors (net reclassification improvement, 4.2% and 4.9%; P =0.006 and 0.017). Discrimination improvement was modest (C-index improvement, 0.004). A polygene MGRS performed worse than the CHD-specific MGRS. We estimate that 1 additional CHD event for every 318 people screened at intermediate risk could be saved by measuring the CHD-specific genetic score in addition to the established risk factors.

Conclusions—

Our results indicate that genetic information could be of some clinical value for prediction of CHD, although further studies are needed to address aspects, such as feasibility, ethics, and cost efficiency of genetic profiling in the primary prevention setting.

Identification of HKDC1 and BACE2 as genes influencing glycemic traits during pregnancy through genome-wide association studies

Maternal metabolism during pregnancy impacts the developing fetus, affecting offspring birth weight and adiposity. This has important implications for metabolic health later in life (e.g., offspring of mothers with pre-existing or gestational diabetes mellitus have an increased risk of metabolic disorders in childhood). To identify genetic loci associated with measures of maternal metabolism obtained during an oral glucose tolerance test at ∼28 weeks' gestation, we performed a genome-wide association study of 4,437 pregnant mothers of European (n = 1,367), Thai (n = 1,178), Afro-Caribbean (n = 1,075), and Hispanic (n = 817) ancestry, along with replication of top signals in three additional European ancestry cohorts. In addition to identifying associations with genes previously implicated with measures of glucose metabolism in nonpregnant populations, we identified two novel genome-wide significant associations: 2-h plasma glucose and HKDC1, and fasting C-peptide and BACE2. These results suggest that the genetic architecture underlying glucose metabolism may differ, in part, in pregnancy.

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.

Fast association tests for genes with FAST

Gene-based tests of association can increase the power of a genome-wide association study by aggregating multiple independent effects across a gene or locus into a single stronger signal. Recent gene-based tests have distinct approaches to selecting which variants to aggregate within a locus, modeling the effects of linkage disequilibrium, representing fractional allele counts from imputation, and managing permutation tests for p-values. Implementing these tests in a single, efficient framework has great practical value. Fast ASsociation Tests (Fast) addresses this need by implementing leading gene-based association tests together with conventional SNP-based univariate tests and providing a consolidated, easily interpreted report. Fast scales readily to genome-wide SNP data with millions of SNPs and tens of thousands of individuals, provides implementations that are orders of magnitude faster than original literature reports, and provides a unified framework for performing several gene based association tests concurrently and efficiently on the same data.

AVAILABILITY

https://bitbucket.org/baderlab/fast/downloads/FAST.tar.gz, with documentation at https://bitbucket.org/baderlab/fast/wiki/Home.

Advances in blood pressure genomics

The elucidation of genes implicated in Mendelian forms of hypertension demonstrates rare variants with substantial effects are responsible, and often these genes lie within pathways managing sodium homeostasis. More recently with advances in affordable high-throughput genotyping strategies, multiple common genetic variants with modest effects on blood pressure (<1 mmHg systolic) have been discovered in the population. In aggregate, these common variants explain <3% of the variance of blood pressure. Although these findings may offer new mechanistic insights into the biology of blood pressure, a key question is can these findings translate into patient benefit? It is timely to reflect on recent advances in genomics, and the use of new resources, such as the 1000 Genomes Project and the Encyclopedia of DNA Elements, to annotate likely causal variants, and their relevance to cardiovascular disease. In this review, we discuss the advances in relation to our knowledge of the genetic architecture of blood pressure, and whether gene discoveries might influence cardiovascular risk assessment, help to stratify patient response to medicine, or identify new biological pathways for novel therapeutic targets.

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.

PPARG2 Pro12Ala and ADAMTS9 rs4607103 as "insulin resistance loci" and "insulin secretion loci" in Italian individuals. The GENFIEV study and the Verona Newly Diagnosed Type 2 Diabetes Study (VNDS) 4

We investigated cross-sectionally whether the type 2 diabetes (T2DM) risk alleles of rs1801282 (PPARG2) and rs4607103 (ADAMTS9) were associated with T2DM and/or insulin sensitivity (IS) and beta cell function (βF) in Italians without and with newly diagnosed T2DM. In 676 nondiabetic subjects (336 NGR and 340 IGR) from the GENFIEV study and in 597 patients from the Verona Newly Diagnosed Type 2 Diabetes Study (VNDS), we (1) genotyped rs1801282 and rs4607103, (2) assessed βF by C-peptide/glucose modeling after OGTT, and (3) assessed IS by HOMA-IR in both studies and by euglycemic insulin clamp in VNDS only. Logistic, linear, and two-stage least squares regression analyses were used to test (a) genetic associations with T2DM and with pathophysiological phenotypes, (b) causal relationships of the latter ones with T2DM by a Mendelian randomization design. Both SNPs were associated with T2DM. The rs4607103 risk allele was associated to impaired βF (p < 0.01) in the GENFIEV study and in both cohorts combined. The rs1801282 genotype was associated with IS both in the GENFIEV study (p < 0.03) and in the VNDS (p < 0.03), whereas rs4607103 did so in the VNDS only (p = 0.01). In a Mendelian randomization design, both HOMA-IR (instrumental variables: rs1801282, rs4607103) and βF (instrumental variable: rs4607103) were related to T2DM (p < 0.03-0.01 and p < 0.03, respectively). PPARG2 and ADAMTS9 variants are both associated with T2DM and with insulin resistance, whereas only ADAMTS9 may be related to βF. Thus, at least in Italians, they may be considered bona fide "insulin resistance genes".

Reevaluation of fatty acid receptor 1 as a drug target for the stimulation of insulin secretion in humans

The role of free fatty acid receptor 1 (FFAR1/GPR40) in glucose homeostasis is still incompletely understood. Small receptor agonists stimulating insulin secretion are undergoing investigation for the treatment of type 2 diabetes. Surprisingly, genome-wide association studies did not discover diabetes risk variants in FFAR1. We reevaluated the role of FFAR1 in insulin secretion using a specific agonist, FFAR1-knockout mice and human islets. Nondiabetic individuals were metabolically phenotyped and genotyped. In vitro experiments indicated that palmitate and a specific FFAR1 agonist, TUG-469, stimulate glucose-induced insulin secretion through FFAR1. The proapoptotic effect of chronic exposure of β-cells to palmitate was independent of FFAR1. TUG-469 was protective, whereas inhibition of FFAR1 promoted apoptosis. In accordance with the proapoptotic effect of palmitate, in vivo cross-sectional observations demonstrated a negative association between fasting free fatty acids (NEFAs) and insulin secretion. Because NEFAs stimulate secretion through FFAR1, we examined the interaction of genetic variation in FFAR1 with NEFA and insulin secretion. The inverse association of NEFA and secretion was modulated by rs1573611 and became steeper for carriers of the minor allele. In conclusion, FFAR1 agonists support β-cell function, but variation in FFAR1 influences NEFA effects on insulin secretion and therefore could affect therapeutic efficacy of FFAR1 agonists.

Impact of variation at the FTO locus on milk fat yield in Holstein dairy cattle

This study explores the biological role of the Fat Mass and Obesity associated (FTO) gene locus on milk composition in German Holstein cattle. Since FTO controls energy homeostasis and expenditure and the FTO locus has repeatedly shown association with obesity in human studies, we tested FTO as a candidate gene in particular for milk fat yield, which represents a high amount of energy secreted during lactation. The study was performed on 2,402 bulls and 860 cows where dense milk composition data were available. Genetic information was taken from a 2 Mb region around FTO. Five SNPs and two haplotype blocks in a 725 kb region covering FTO and the neighboring genes RPGRIP1L, U6ATAC, and 5 S rRNA were associated with milk fat yield and also affected protein yield in the same direction. Interestingly, higher frequency SNP alleles and haplotypes within the FTO gene increased milk fat and protein yields by up to 2.8 and 2.2 kg per lactation, respectively, while the most frequent haplotype in the upstream block covering exon 1 of FTO to exon 15 of RPGRIP1L had opposite effects with lower fat and milk yield. Both haplotype blocks were also significant in cows. The loci accounted for about 1% of the corresponding trait variance in the population. The association signals not only provided evidence for at least two causative mutations in the FTO locus with a functional effect on milk but also milk protein yield. The pleiotropic effects suggest a biological function on the usage of energy resources and the control of energy balance rather than directly affecting fat and protein synthesis. The identified effect of the obesity gene locus on milk energy content suggests an impact on infant nutrition by breast feeding in humans.

Lipins, lipinopathies, and the modulation of cellular lipid storage and signaling

Members of the lipin protein family are phosphatidate phosphatase (PAP) enzymes, which catalyze the dephosphorylation of phosphatidic acid to diacylglycerol, the penultimate step in TAG synthesis. Lipins are unique among the glycerolipid biosynthetic enzymes in that they also promote fatty acid oxidation through their activity as co-regulators of gene expression by DNA-bound transcription factors. Lipin function has been evolutionarily conserved from a single ortholog in yeast to the mammalian family of three lipin proteins-lipin-1, lipin-2, and lipin-3. In mice and humans, the levels of lipin activity are a determinant of TAG storage in diverse cell types, and humans with deficiency in lipin-1 or lipin-2 have severe metabolic diseases. Recent work has highlighted the complex physiological interactions between members of the lipin protein family, which exhibit both overlapping and unique functions in specific tissues. The analysis of "lipinopathies" in mouse models and in humans has revealed an important role for lipin activity in the regulation of lipid intermediates (phosphatidate and diacylglycerol), which influence fundamental cellular processes including adipocyte and nerve cell differentiation, adipocyte lipolysis, and hepatic insulin signaling. The elucidation of lipin molecular and physiological functions could lead to novel approaches to modulate cellular lipid storage and metabolic disease.

New susceptibility loci in MYL2, C12orf51 and OAS1 associated with 1-h plasma glucose as predisposing risk factors for type 2 diabetes in the Korean population

Most recently, 1-h hyperglycemia has been recognized as an additional risk factor for type 2 diabetes. To date, previous genome-wide association studies for glycemic traits have a limited impact on the fasting state and 2-h plasma glucose level in an oral glucose challenge. To identify genetic susceptibility in different stages of glucose tolerance, we performed a meta-analysis for glycemic traits including 1-h plasma glucose (1-hPG) from 14 232 non-diabetic individuals in the Korean population. Newly implicated variants (MYL2, C12orf51 and OAS1) were found to be significantly associated with 1-hPG. We also demonstrated associations with gestational diabetes mellitus. Our results could provide additional insight into the genetic variation in the clinical range of glycemia.

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.

Lack of interaction of beta-cell-function-associated variants with hypertension on change in fasting glucose and diabetes risk: the Framingham Offspring Study

OBJECTIVE

To test whether pancreatic beta-cell genetic frailty and hypertension (HTN) interact in their associations with change over time in fasting glucose (ΔFG) or type 2 diabetes mellitus (T2D) risk.

METHODS AND RESULTS

We pooled data from 3471 Framingham Offspring Study participants into six ∼4-year periods (15 852 person-examinations; mean age 52; 54% women). We defined two genetic exposures reflecting beta-cell genetic risk burden: single nucleotide polymorphism (SNP) score counts of fasting glucose-associated and T2D-associated risk alleles at 16 and 33 putative beta-cell loci, respectively; and three HTN exposures: HTN versus no-HTN; treated versus untreated HTN; and five mutually exclusive antihypertensive categories (beta-blockers, thiazides, renin-angiotensin system agents, combinations, others) versus untreated HTN. We tested ∼4-year mean ΔFG or odds of T2D by per-risk allele score change and HTN category, seeking genetic score-by-HTN interaction. Genetic scores increased ∼4-year ΔFG (0.6  mg/dl per-risk allele; P = 8.9 × 10(-16)) and T2D-risk (∼17% per-risk allele; P = 2.1 × 10(-7)). As compared to no-HTN, HTN conferred higher ΔFG (2.6 versus 1.7 mg/dl; P < 0.0001) and T2D-risk [odds ratio (OR) = 2.9, 95% confidence interval (CI) 2.8-3.0; P < 0.0001]. As compared to untreated HTN, treated HTN conferred higher ΔFG (3.4 versus 3.0 mg/dl; P < 0.0001) and T2D-risk (OR = 1.4, 95% CI 1.3-1.5; P = 0.02). Beta-blockers (OR = 1.6, 95% CI 1.1-2.4), combinations (OR = 1.6, 95% CI 1.1-2.5), and others (OR = 2.0, 95% CI 1.4-2.9) increased T2D-risk (all P < 0.02). In joint models including interaction terms, all genetic score-by-HTN interaction terms were P value greater than 0.05. In joint models without interaction, fasting glucose-SNP or T2D-SNP genetic scores (both P < 0.001) and HTN (P < 0.0001) independently increased ΔFG or T2D-risk.

CONCLUSION

HTN, HTN treatment, and common fasting glucose-SNP genetic score/T2D-SNP genetic score independently predicted ΔFG and T2D incidence, but did not modify each other's association with ΔFG or T2D risk.

Resequencing and clinical associations of the 9p21.3 region: a comprehensive investigation in the Framingham heart study

BACKGROUND

9p21.3 is among the most strongly replicated regions for cardiovascular disease. There are few reports of sequencing the associated 9p21.3 interval. We set out to sequence the 9p21.3 region followed by a comprehensive study of genetic associations with clinical and subclinical cardiovascular disease and its risk factors, as well as with copy number variation and gene expression, in the Framingham Heart Study (FHS).

METHODS AND RESULTS

We sequenced 281 individuals (94 with myocardial infarction, 94 with high coronary artery calcium levels, and 93 control subjects free of elevated coronary artery calcium or myocardial infarction), followed by genotyping and association in >7000 additional FHS individuals. We assessed genetic associations with clinical and subclinical cardiovascular disease, risk factor phenotypes, and gene expression levels of the protein-coding genes CDKN2A and CDKN2B and the noncoding gene ANRIL in freshly harvested leukocytes and platelets. Within this large sample, we found strong associations of 9p21.3 variants with increased risk for myocardial infarction, higher coronary artery calcium levels, and larger abdominal aorta diameters and no evidence for association with traditional cardiovascular disease risk factors. No common protein-coding variation, variants in splice donor or acceptor sites, or copy number variation events were observed. By contrast, strong associations were observed between genetic variants and gene expression, particularly for a short isoform of ANRIL and for CDKN2B.

CONCLUSIONS

Our thorough genomic characterization of 9p21.3 suggests common variants likely account for observed disease associations and provides further support for the hypothesis that complex regulatory variation affecting ANRIL and CDKN2B gene expression may contribute to increased risk for clinically apparent and subclinical coronary artery disease and aortic disease.

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.

Association study of 25 type 2 diabetes related Loci with measures of obesity in Indian sib pairs

Obesity is an established risk factor for type 2 diabetes (T2D) and they are metabolically related through the mechanism of insulin resistance. In order to explore how common genetic variants associated with T2D correlate with body mass index (BMI), we examined the influence of 25 T2D associated loci on obesity risk. We used 5056 individuals (2528 sib-pairs) recruited in Indian Migration Study and conducted within sib-pair analysis for six obesity phenotypes. We found associations of variants in CXCR4 (rs932206) and HHEX (rs5015480) with higher body mass index (BMI) (β=0.13, p=0.001) and (β=0.09, p=0.002), respectively and weight (β=0.13, p=0.001) and (β=0.09, p=0.001), respectively. CXCR4 variant was also strongly associated with body fat (β=0.10, p=0.0004). In addition, we demonstrated associations of CXCR4 and HHEX with overweight/obesity (OR=1.6, p=0.003) and (OR=1.4, p=0.002), respectively, in 1333 sib-pairs (2666 individuals). We observed marginal evidence of associations between variants at six loci (TCF7L2, NGN3, FOXA2, LOC646279, FLJ39370 and THADA) and waist hip ratio (WHR), BMI and/or overweight which needs to be validated in larger set of samples. All the above findings were independent of daily energy consumption and physical activity level. The risk score estimates based on eight significant loci (including nominal associations) showed associations with WHR and body fat which were independent of BMI. In summary, we establish the role of T2D associated loci in influencing the measures of obesity in Indian population, suggesting common underlying pathophysiology across populations.

Regulation of insulin and type 1 insulin-like growth factor signaling and action by the Grb10/14 and SH2B1/B2 adaptor proteins

The effects of insulin and type 1 insulin-like growth factor (IGF-1) on metabolism, growth and survival are mediated by their association with specific receptor tyrosine kinases, which results in both receptor and substrate phosphorylation. Phosphotyrosine residues on receptors and substrates provide docking sites for signaling proteins containing SH2 (Src homology 2) domains, including molecular adaptors. This review focuses on the regulation of insulin/IGF-1 signaling and action by two adaptor families with a similar domain organization: the growth factor receptor-bound proteins Grb7/10/14 and the SH2B proteins. Both Grb10/14 and SH2B1/B2 associate with the activation loop of insulin/IGF-1 receptors through their SH2 domains, but association of Grb10/14 also involves their unique BPS domain. Consistent with Grb14 binding as a pseudosubstrate to the kinase active site, insulin/IGF-induced activation of receptors and downstream signaling pathways in cultured cells is inhibited by Grb10/14 adaptors, but is potentiated by SH2B1/B2 adaptors. Accordingly, Grb10 and Grb14 knockout mice show improved insulin/IGF sensitivity in vivo, and, for Grb10, overgrowth and increased skeketal muscle and pancreatic β-cell mass. Conversely, SH2B1-depleted mice display insulin and IGF-1 resistance, with peripheral depletion leading to reduced adiposity and neuronal depletion leading to obesity through associated leptin resistance. Grb10/14 and SH2B1 adaptors also modulate insulin/IGF-1 action by interacting with signaling components downstream of receptors and exert several tissue-specific effects. The identification of Grb10/14 and SH2B1 as physiological regulators of insulin signaling and action, together with observations that variants at their gene loci are associated with obesity and/or insulin resistance, highlight them as potential therapeutic targets for these conditions.

Finding genetic risk factors of gestational diabetes

Gestational diabetes mellitus (GDM) is a complex metabolic disorder of pregnancy that is suspected to have a strong genetic predisposition. It is associated with poor perinatal outcome, and both GDM women and their offspring are at increased risk of future development of type 2 diabetes mellitus (T2DM). During the past several years, there has been progress in finding the genetic risk factors of GDM in relation to T2DM. Some of the genetic variants that were proven to be significantly associated with T2DM are also genetic risk factors of GDM. Recently, a genome-wide association study of GDM was performed and reported that genetic variants in CDKAL1 and MTNR1B were associated with GDM at a genome-wide significance level. Current investigations using next-generation sequencing will improve our insight into the pathophysiology of GDM. It would be important to know whether genetic information revealed from these studies could improve our prediction of GDM and the future development of T2DM. We hope further research on the genetics of GDM would ultimately lead us to personalized genomic medicine and improved patient care.

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.