Variants in MTNR1B influence fasting glucose levels

Melatonin inhibits insulin secretion in rat insulinoma β-cells (INS-1) heterologously expressing the human melatonin receptor isoform MT2

Melatonin exerts some of its effects via G-protein-coupled membrane receptors. Two membrane receptor isoforms, MT1 and MT2, have been described. The MT1 receptor is known to inhibit second messenger cyclic adenosine monophosphate (cAMP) signaling through receptor-coupling to inhibitory G-proteins (G(i) ). Much less is known about the MT2 receptor, but it has also been implicated in signaling via G(i) -proteins. In rat pancreatic β-cells, it has recently been reported that the MT2 receptor plays an inhibitory role in the cyclic guanosine monophosphate (cGMP) pathway. This study addresses the signaling features of the constitutively expressed human recombinant MT2 receptor (hMT2) and its impact on insulin secretion, using a rat insulinoma β-cell line (INS-1). On the basis of a specific radioimmunoassay, insulin secretion was found to be more strongly reduced in the clones expressing hMT2 than in INS-1 controls, when incubated with 1 or 100 nm melatonin. Similarly, cAMP and cGMP levels, measured by specific enzyme-linked immunosorbent assays (ELISAs), were reduced to a greater extent in hMT2 clones after melatonin treatment. In hMT2-expressing cells, the inhibitory effect of melatonin on insulin secretion was blocked by pretreatment with pertussis toxin, demonstrating the coupling of the hMT2 to G(i) -proteins. These results indicate that functional hMT2 expression leads to the inhibition of cyclic nucleotide signaling and a reduction in insulin release. Because genetic variants of the hMT2 receptor are considered to be risk factors in the development of type 2 diabetes, our results are potentially significant in explaining and preventing the pathogenesis of this disease.

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes

OBJECTIVE

Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology.

RESEARCH DESIGN AND METHODS

We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates.

RESULTS

Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets.

CONCLUSIONS

We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

The Rotterdam Study: 2012 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.

PWD/PhJ and WSB/EiJ mice are resistant to diet-induced obesity but have abnormal insulin secretion

Recently, novel inbred mouse strains that are genetically distinct from the commonly used models have been developed from wild-caught mice. These wild-derived inbred strains have been included in many of the large-scale genomic projects, but their potential as models of altered obesity and diabetes susceptibility has not been assessed. We examined obesity and diabetes-related traits in response to high-fat feeding in two of these strains, PWD/PhJ (PWD) and WSB/EiJ (WSB), in comparison with C57BL/6J (B6). Young PWD mice displayed high fasting insulin levels, although they had normal insulin sensitivity. PWD mice subsequently developed a much milder and delayed-onset obesity compared with B6 mice but became as insulin resistant. PWD mice had a robust first-phase and increased second-phase glucose-stimulated insulin secretion in vivo, rendering them more glucose tolerant. WSB mice were remarkably resistant to diet-induced obesity and maintained very low fasting insulin throughout the study. WSB mice exhibited more rapid glucose clearance in response to an insulin challenge compared with B6 mice, consistent with their low percent body fat. Interestingly, in the absence of a measurable in vivo insulin secretion, glucose tolerance of WSB mice was better than B6 mice, likely due to their enhanced insulin sensitivity. Thus PWD and WSB are two obesity-resistant strains with unique insulin secretion phenotypes. PWD mice are an interesting model that dissociates hyperinsulinemia from obesity and insulin resistance, whereas WSB mice are a model of extraordinary resistance to a high-fat diet.

New type 2 diabetes risk genes provide new insights in insulin secretion mechanisms

Type 2 diabetes results from the inability of beta cells to increase insulin secretion sufficiently to compensate for insulin resistance. Insulin resistance is thought to result mainly from environmental factors, such as obesity. However, there is compelling evidence that the decline of both insulin sensitivity and insulin secretion have also a genetic component. Recent genome-wide association studies identified several novel risk genes for type 2 diabetes. The vast majority of these genes affect beta cell function by molecular mechanisms that remain unknown in detail. Nevertheless, we and others could show that a group of genes affect glucose-stimulated insulin secretion, a group incretin-stimulated insulin secretion (incretin sensitivity or secretion) and a group proinsulin-to-insulin conversion. The most important so far type 2 diabetes risk gene, TCF7L2, interferes with all three mechanisms. In addition to advancing knowledge in the pathophysiology of type 2 diabetes, the discovery of novel genetic determinants of diabetes susceptibility may help understanding of gene-environment, gene-therapy and gene-gene interactions. It was also hoped that it could make determination of the individual risk for type 2 diabetes feasible. However, the allelic relative risks of most genetic variants discovered so far are relatively low. Thus, at present, clinical criteria assess the risk for type 2 diabetes with greater sensitivity and specificity than the combination of all known genetic variants.

Fine mapping of five loci associated with low-density lipoprotein cholesterol detects variants that double the explained heritability

Complex trait genome-wide association studies (GWAS) provide an efficient strategy for evaluating large numbers of common variants in large numbers of individuals and for identifying trait-associated variants. Nevertheless, GWAS often leave much of the trait heritability unexplained. We hypothesized that some of this unexplained heritability might be due to common and rare variants that reside in GWAS identified loci but lack appropriate proxies in modern genotyping arrays. To assess this hypothesis, we re-examined 7 genes (APOE, APOC1, APOC2, SORT1, LDLR, APOB, and PCSK9) in 5 loci associated with low-density lipoprotein cholesterol (LDL-C) in multiple GWAS. For each gene, we first catalogued genetic variation by re-sequencing 256 Sardinian individuals with extreme LDL-C values. Next, we genotyped variants identified by us and by the 1000 Genomes Project (totaling 3,277 SNPs) in 5,524 volunteers. We found that in one locus (PCSK9) the GWAS signal could be explained by a previously described low-frequency variant and that in three loci (PCSK9, APOE, and LDLR) there were additional variants independently associated with LDL-C, including a novel and rare LDLR variant that seems specific to Sardinians. Overall, this more detailed assessment of SNP variation in these loci increased estimates of the heritability of LDL-C accounted for by these genes from 3.1% to 6.5%. All association signals and the heritability estimates were successfully confirmed in a sample of ∼10,000 Finnish and Norwegian individuals. Our results thus suggest that focusing on variants accessible via GWAS can lead to clear underestimates of the trait heritability explained by a set of loci. Further, our results suggest that, as prelude to large-scale sequencing efforts, targeted re-sequencing efforts paired with large-scale genotyping will increase estimates of complex trait heritability explained by known loci.

Despite the striking success of genome-wide association studies in identifying genetic loci associated with common complex traits and diseases, much of the heritable risk for these traits and diseases remains unexplained. A higher resolution investigation of the genome through sequencing studies is expected to clarify the sources of this missing heritability. As a preview of what we might learn in these more detailed assessments of genetic variation, we used sequencing to identify potentially interesting variants in seven genes associated with low-density lipoprotein cholesterol (LDL-C) in 256 Sardinian individuals with extreme LDL-C levels, followed by large scale genotyping in 5,524 individuals, to examine newly discovered and previously described variants. We found that a combination of common and rare variants in these loci contributes to variation in LDL-C levels, and also that the initial estimate of the heritability explained by these loci doubled. Importantly, our results include a Sardinian-specific rare variant, highlighting the need for sequencing studies in isolated populations. Our results provide insights about what extensive whole-genome sequencing efforts are likely to reveal for the understanding of the genetic architecture of complex traits.

Role of melatonin on diabetes-related metabolic disorders

Melatonin is a circulating hormone that is mainly released from the pineal gland. It is best known as a regulator of seasonal and circadian rhythms, its levels being high during the night and low during the day. Interestingly, insulin levels are also adapted to day/night changes through melatonin-dependent synchronization. This regulation may be explained by the inhibiting action of melatonin on insulin release, which is transmitted through both the pertussis-toxin-sensitive membrane receptors MT₁ and MT₂ and the second messengers 3’,5’-cyclic adenosine monophosphate, 3’,5’-cyclic guanosine monophosphate and inositol 1,4,5-trisphosphate. Melatonin may influence diabetes and associated metabolic disturbances not only by regulating insulin secretion, but also by providing protection against reactive oxygen species, since pancreatic β-cells are very susceptible to oxidative stress because they possess only low-antioxidative capacity. On the other hand, in several genetic association studies, single nucleotide polymorphysms of the human MT₂ receptor have been described as being causally linked to an elevated risk of developing type 2 diabetes. This suggests that these individuals may be more sensitive to the actions of melatonin, thereby leading to impaired insulin secretion. Therefore, blocking the melatonin-induced inhibition of insulin secretion may be a novel therapeutic avenue for type 2 diabetes.

Melatonin receptor 1 B polymorphisms associated with the risk of gestational diabetes mellitus

Backgrounds

Two SNPs in melatonin receptor 1B gene, rs10830963 and rs1387153 showed significant associations with fasting plasma glucose levels and the risk of Type 2 Diabetes Mellitus (T2DM) in previous studies. Since T2DM and gestational diabetes mellitus (GDM) share similar characteristics, we suspected that the two genetic polymorphisms in MTNR1B may be associated with GDM, and conducted association studies between the polymorphisms and the disease. Furthermore, we also examined genetic effects of the two polymorphisms with various diabetes-related phenotypes.

Methods

A total of 1,918 subjects (928 GDM patients and 990 controls) were used for the study. Two MTNR1B polymorphisms were genotyped using TaqMan assay. The allele distributions of SNPs were evaluated by x² models calculating odds ratios (ORs), 95% confidence intervals (CIs), and corresponding P values. Multiple regressions were used for association analyses of GDM-related traits. Finally, conditional analyses were also performed.

Results

We found significant associations between the two genetic variants and GDM, rs10830963, with a corrected P value of 0.0001, and rs1387153, with the corrected P value of 0.0008. In addition, we also found that the two SNPs were associated with various phenotypes such as homeostasis model assessment of beta-cell function and fasting glucose levels. Further conditional analyses results suggested that rs10830963 might be more likely functional in case/control analysis, although not clear in GDM-related phenotype analyses.

Conclusion

There have been studies that found associations between genetic variants of other genes and GDM, this is the first study that found significant associations between SNPs of MTNR1B and GDM. The genetic effects of two SNPs identified in this study would be helpful in understanding the insight of GDM and other diabetes-related disorders.

Type 2 diabetes and obesity: genomics and the clinic

Type 2 diabetes (T2D) and obesity represent major challenges for global public health. They are at the forefront of international efforts to identify the genetic variation contributing to complex disease susceptibility, and recent years have seen considerable success in identifying common risk-variants. Given the clinical impact of molecular diagnostics in rarer monogenic forms of these diseases, expectations have been high that genetic discoveries will transform the prospects for risk stratification, development of novel therapeutics and personalised medicine. However, so far, clinical translation has been limited. Difficulties in defining the alleles and transcripts mediating association effects have frustrated efforts to gain early biological insights, whilst the fact that variants identified account for only a modest proportion of observed familiarity has limited their value in guiding treatment of individual patients. Ongoing efforts to track causal variants through fine-mapping and to illuminate the biological mechanisms through which they act, as well as sequence-based discovery of lower-frequency alleles (of potentially larger effect), should provide welcome acceleration in the capacity for clinical translation. This review will summarise recent advances in identifying risk alleles for T2D and obesity, and existing contributions to understanding disease pathology. It will consider the progress made in translating genetic knowledge into clinical utility, the challenges remaining, and the realistic potential for further progress.

Association of genetic Loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children

OBJECTIVE

To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents.

RESEARCH DESIGN AND METHODS

A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9-16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose.

RESULTS

Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021-0.031) for each unit increase in the score.

CONCLUSIONS

Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.

Genetics of type 2 diabetes: pathophysiologic and clinical relevance

BACKGROUND

Recent genome-wide association studies enlarged our knowledge about the genetic background of type 2 diabetes.

AIMS

This review provides an overview of the role of these novel genetic findings for the pathophysiology, prediction and treatment of type 2 diabetes.

RESULTS

The genetic susceptibility to type 2 diabetes appears to be determined by many common variants in multiple gene loci with low effect sizes. Although at least 36 diabetes-associated genes were identified, only about 10% of the heritability of type 2 diabetes can be explained. Most of the discovered gene variants have been linked to beta-cell dysfunction rather than insulin resistance, which might challenge established thinking of type 2 diabetes as a predominant disorder of insulin action. Genetic data can lead to statistically significant, but not to clinically relevant contributions to risk prediction for type 2 diabetes. Nevertheless, preliminary evidence suggests interactions between genotypes and response to lifestyle changes or drug treatment.

CONCLUSIONS

Future studies need to target the issue of hidden heritability and to detect the causal gene variants within the identified gene loci. Improved understanding of the genetic contribution to type 2 diabetes may then help addressing the questions whether genotyping is useful to predict individual diabetes risk, identifies individual responsiveness to preventive and therapeutic interventions or at least allows for breaking down type 2 diabetes into smaller, clinically meaningful subtypes.

Identification of an imprinted master trans regulator at the KLF14 locus related to multiple metabolic phenotypes

Genome-wide association studies have identified many genetic variants associated with complex traits. However, at only a minority of loci have the molecular mechanisms mediating these associations been characterized. In parallel, whereas cis regulatory patterns of gene expression have been extensively explored, the identification of trans regulatory effects in humans has attracted less attention. Here we show that the type 2 diabetes and high-density lipoprotein cholesterol-associated cis-acting expression quantitative trait locus (eQTL) of the maternally expressed transcription factor KLF14 acts as a master trans regulator of adipose gene expression. Expression levels of genes regulated by this trans-eQTL are highly correlated with concurrently measured metabolic traits, and a subset of the trans-regulated genes harbor variants directly associated with metabolic phenotypes. This trans-eQTL network provides a mechanistic understanding of the effect of the KLF14 locus on metabolic disease risk and offers a potential model for other complex traits.

Relationship between MTNR1B (melatonin receptor 1B gene) polymorphism rs10830963 and glucose levels in overweight children and adolescents

AIMS

The G-allele of the single nucleotide polymorphism (SNP) rs10830963 in MTNR1B (melatonin receptor 1B gene) is associated with type 2 diabetes mellitus and glucose levels in adults. The aim of this study was to analyze whether there is an allele-dosage effect on glucose metabolism in overweight children and to explore if changes in glucose metabolism in a lifestyle intervention do also depend on genotype.

METHODS

We genotyped rs10830963 in 1118 overweight children and adolescents [mean age 10.7 yr, mean body mass index (BMI) 27.8 kg/m2]; 340 of these individuals completed a 1-yr lifestyle intervention (mean age 10.7 yr, mean BMI 27.9 kg/m2). The degree of overweight [BMI-SDS (standard deviation score)], fasting insulin, glucose, homeostasis model assessment for insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index (QUICKI) were measured before and after intervention.

RESULTS

We showed a significant relationship between rs10830963 and basal glucose levels [β:1.101, 95% confidence interval (CI) 0.316-1.886 mg/dL per risk allele; p = 0.006] by linear regression adjusted for age, age(2), and sex. There was no effect of the allele on insulin or indices of insulin resistance or sensitivity. After the 1-yr lifestyle intervention, we observed a significant reduction of BMI-SDS as well as an improvement of HOMA-IR and QUICKI, but no evidence for an association between rs10830963 genotype and changes of glucose levels.

CONCLUSIONS

The G-allele of rs10830693 in the MTNR1B gene was significantly related to glucose levels, while an impact of this genetic variant on the changes in glucose metabolism in children participating in a lifestyle intervention was not observable.

Circadian disruption and SCN control of energy metabolism

In this review we first present the anatomical pathways used by the suprachiasmatic nuclei to enforce its rhythmicity onto the body, especially its energy homeostatic system. The experimental data show that by activating the orexin system at the start of the active phase, the biological clock not only ensures that we wake up on time, but also that our glucose metabolism and cardiovascular system are prepared for increased activity. The drawback of such a highly integrated system, however, becomes visible when our daily lives are not fully synchronized with the environment. Thus, in addition to increased physical activity and decreased intake of high-energy food, also a well-lighted and fully resonating biological clock may help to withstand the increasing "diabetogenic" pressure of today's 24/7 society.

Distribution of melatonin receptors in murine pancreatic islets

Melatonin has multiple receptor-dependent and receptor-independent functions. At the cell membrane, melatonin interacts with its receptors MT1 and MT2, which are expressed in numerous tissues. Genome-wide association studies have recently shown that the MTNR1B/MT2 receptor may be involved in the pathogenesis of type 2 diabetes mellitus. In line with these findings, expression of melatonin receptors has been shown in mouse, rat, and human pancreatic islets. MT1 and MT2 are G-protein-coupled receptors and are proposed to exert inhibitory effects on insulin secretion. Here, we show by immunocytochemistry that these membrane melatonin receptors have distinct locations in the mouse islet. MT1 is expressed in α-cells while MT2 is located to the β-cells. These findings help to unravel the complex machinery underlying melatonin's role in the regulation of islet function.

The effect of genome-wide association scan quality control on imputation outcome for common variants

Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an input for imputing genotypes. This study aims to determine the effect of commonly applied QC steps on imputation outcomes. We performed several iterations of imputing SNPs across chromosome 22 in a dataset consisting of 3177 samples with Illumina 610 k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with the directly typed genotypes. In addition, we investigated the correlation between alternatively QCed data. We also applied a series of post-imputation QC steps balancing elimination of poorly imputed SNPs and information loss. We found that the difference between the unQCed data and the fully QCed data on imputation outcome was minimal. Our study shows that imputation of common variants is generally very accurate and robust to GWAS QC, which is not a major factor affecting imputation outcome. A minority of common-frequency SNPs with particular properties cannot be accurately imputed regardless of QC stringency. These findings may not generalise to the imputation of low frequency and rare variants.

Associations of common genetic variants with age-related changes in fasting and postload glucose: evidence from 18 years of follow-up of the Whitehall II cohort

OBJECTIVE

In the general, nondiabetic population, fasting glucose increases only slightly over time, whereas 2-h postload glucose shows a much steeper age-related rise. The reasons underlying these different age trajectories are unknown. We investigated whether common genetic variants associated with fasting and 2-h glucose contribute to age-related changes of these traits.

RESEARCH DESIGN AND METHODS

We studied 5,196 nondiabetic participants of the Whitehall II cohort (aged 40-78 years) attending up to four 5-yearly oral glucose tolerance tests. A genetic score was calculated separately for fasting and 2-h glucose, including 16 and 5 single nucleotide polymorphisms, respectively. Longitudinal modeling with age centered at 55 years was used to study the effects of each genotype and genetic score on fasting and 2-h glucose and their interactions with age, adjusting for sex and time-varying BMI.

RESULTS

The fasting glucose genetic score was significantly associated with fasting glucose with a 0.029 mmol/L (95% CI 0.023-0.034) difference (P = 2.76 × 10(-21)) per genetic score point, an association that remained constant over time (age interaction P = 0.17). Two-hour glucose levels differed by 0.076 mmol/L (0.047-0.105) per genetic score point (P = 3.1 × 10(-7)); notably, this effect became stronger with increasing age by 0.006 mmol/L (0.003-0.009) per genetic score point per year (age interaction P = 3.0 × 10(-5)), resulting in diverging age trajectories by genetic score.

CONCLUSIONS

Common genetic variants contribute to the age-related rise of 2-h glucose levels, whereas associations of variants for fasting glucose are constant over time, in line with stable age trajectories of fasting glucose.

A common polymorphism rs3781637 in MTNR1B is associated with type 2 diabetes and lipids levels in Han Chinese individuals

Background

Several studies have shown that common variants in the MTNR1B gene were associated with fasting glucose level and type 2 diabetes. The purpose of this study was to examine whether tagging single nucleotide polymorphisms (SNPs) in the MTNR1B region were associated with type 2 diabetes and related traits in a Han Chinese population.

Methods

We investigated the association of polymorphisms in the MTNR1B gene with type 2 diabetes by employing a case-control study design (1118 cases and 1161 controls). Three tagging SNPs (rs10830963, rs3781637, and rs1562444) with R²>0.8 and minor allele frequency>0.05 across the region of the MTNR1B gene were studied. Genotyping was performed by matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy using a MassARRAY platform.

Results

The polymorphism rs3781637 was associated with type 2 diabetes adjusted for age, sex and body mass index (BMI) in the additive model and recessive model (OR = 1.22, 95% CI 1.01-1.46, p = 0.038 and OR = 2.81, 95% CI 1.28-6.17, p = 0.01, respectively). In the non-diabetic controls, rs3781637 was nominally associated with plasma triglyceride, total cholesterol and low density lipoprotein cholesterol (LDL-C) levels in the recessive model (p = 0.018, 0.008 and 0.038, respectively). After adjustment for multiple comparisons, the associations of rs3781637 with total cholesterol and LDL-C remained significant in the recessive model (the empirical p = 0.024 and 0.045, respectively), but the association between rs3781637 and triglyceride became non-significant (the empirical p = 0.095). The associations of rs10830963 and rs1562444 with type 2 diabetes and related traits were not significant in the additive, dominant and recessive models.

Conclusions

The rs3781637 A/G polymorphism of the MTNR1B gene is associated with type 2 diabetes, plasma, total cholesterol and LDL-C levels in the Han Chinese population.

Melatonin stimulates glucagon secretion in vitro and in vivo

Recent investigations have demonstrated that melatonin influences carbohydrate metabolism mediated by insulin-inhibiting effects on pancreatic β-cells. This study evaluated whether melatonin has also an effect on pancreatic α-cells and glucagon expression as well as the glucagon secretion in vitro and in vivo. Glucagon-producing pancreatic α-cell line αTC1 clone 9 (αTC1.9) was used, which was characterized as an appropriate model with glucose responsiveness and expression of the melatonin receptors MT1 and MT2. The results demonstrate that melatonin incubation significantly enhanced the expression as well as the secretion of glucagon. These effects appeared to be more pronounced under hyperglycemic conditions compared to basal glucose concentrations. Notably, in vivo studies demonstrated that long-term oral melatonin administration led to significantly elevated plasma glucagon concentrations in Wistar rats. In contrast, plasma glucagon levels were found to be slightly decreased in type 2 diabetic Goto-Kakizaki rats. Moreover, investigations measuring the relative glucagon receptor mRNA expression showed marked differences in the liver of melatonin-substituted rats as well as in melatonin receptor knockout mice. In conclusion, these findings revealed evidence that melatonin influences pancreatic glucagon expression and secretion as well as the peripheral glucagon action.

Association study of type 2 diabetes genetic susceptibility variants and risk of pancreatic cancer: an analysis of PanScan-I data

OBJECTIVE

To examine associations between recently identified common type 2 diabetes (T2D) susceptibility genetic variants and pancreatic cancer risk.

METHODS

Using data on individuals of European ancestry from the Cancer Genetic Markers of Susceptibility PanScan-I study (1,763 pancreatic cancer cases and 1,802 controls), we tested associations for 37 T2D susceptibility variants with pancreatic cancer risk. Associations with pancreatic cancer were also tested for three composite T2D susceptibility measures, incorporating data on all 37 variants, and for ten additional variants related to T2D-related phenotypes, including fasting glucose and beta-cell function.

RESULTS

Of the 37 T2D risk alleles, two showed nominally significant positive associations with pancreatic cancer risk (FTO rs8050136 per-allele OR = 1.12; CI: 1.02-1.23; MTNR1B rs1387153 OR = 1.11; CI: 1.00-1.23) and one showed an inverse association (BCL11A rs243021 OR = 0.88; CI: 0.80-0.97). The composite T2D susceptibility measures were not associated with pancreatic cancer. The glucose-raising allele of MADD rs11039149 was associated with increased risk of pancreatic cancer (OR = 1.14; CI: 1.03-1.27).

CONCLUSIONS

Overall, these results do not provide strong evidence that common variants underling T2D or related phenotypes also affect pancreatic cancer risk; however, associations for FTO, MTNR1B, BCL11A, and MADD variants warrant further investigation in larger studies. Hypothesis-driven analyses of existing genome-wide genetic data can be cost-efficient and promising approaches for investigating genetic susceptibility to complex diseases.

Inherited destiny? Genetics and gestational diabetes mellitus

Despite years of investigation, very little is known about the genetic predisposition for gestational diabetes mellitus (GDM). However, the advent of genome-wide association and identification of loci contributing to susceptibility to type 2 diabetes mellitus has opened a small window into the genetics of GDM. More importantly, the study of the genetics of GDM has not only illuminated potential new biology underlying diabetes in pregnancy, but has also provided insights into fetal outcomes. Here, I review some of the insights into GDM and fetal outcomes gained through the study of both rare and common genetic variation. I also discuss whether recent testing of type 2 diabetes mellitus susceptibility loci in GDM case-control samples changes views of whether GDM is a distinct form of diabetes. Finally, I examine how the study of susceptibility loci can be used to influence clinical care, one of the great promises of the new era of human genome analysis.

Exposure to room light before bedtime suppresses melatonin onset and shortens melatonin duration in humans

CONTEXT

Millions of individuals habitually expose themselves to room light in the hours before bedtime, yet the effects of this behavior on melatonin signaling are not well recognized.

OBJECTIVE

We tested the hypothesis that exposure to room light in the late evening suppresses the onset of melatonin synthesis and shortens the duration of melatonin production.

DESIGN

In a retrospective analysis, we compared daily melatonin profiles in individuals living in room light (<200 lux) vs. dim light (<3 lux).

PATIENTS

Healthy volunteers (n = 116, 18-30 yr) were recruited from the general population to participate in one of two studies.

SETTING

Participants lived in a General Clinical Research Center for at least five consecutive days.

INTERVENTION

Individuals were exposed to room light or dim light in the 8 h preceding bedtime.

OUTCOME MEASURES

Melatonin duration, onset and offset, suppression, and phase angle of entrainment were determined.

RESULTS

Compared with dim light, exposure to room light before bedtime suppressed melatonin, resulting in a later melatonin onset in 99.0% of individuals and shortening melatonin duration by about 90 min. Also, exposure to room light during the usual hours of sleep suppressed melatonin by greater than 50% in most (85%) trials.

CONCLUSIONS

These findings indicate that room light exerts a profound suppressive effect on melatonin levels and shortens the body's internal representation of night duration. Hence, chronically exposing oneself to electrical lighting in the late evening disrupts melatonin signaling and could therefore potentially impact sleep, thermoregulation, blood pressure, and glucose homeostasis.

CUBN is a gene locus for albuminuria

Identification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10(-11)) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.

Mouse models and the interpretation of human GWAS in type 2 diabetes and obesity

Within the last 3 years, genome-wide association studies (GWAS) have had unprecedented success in identifying loci that are involved in common diseases. For example, more than 35 susceptibility loci have been identified for type 2 diabetes and 32 for obesity thus far. However, the causal gene and variant at a specific linkage disequilibrium block is often unclear. Using a combination of different mouse alleles, we can greatly facilitate the understanding of which candidate gene at a particular disease locus is associated with the disease in humans, and also provide functional analysis of variants through an allelic series, including analysis of hypomorph and hypermorph point mutations, and knockout and overexpression alleles. The phenotyping of these alleles for specific traits of interest, in combination with the functional analysis of the genetic variants, may reveal the molecular and cellular mechanism of action of these disease variants, and ultimately lead to the identification of novel therapeutic strategies for common human diseases. In this Commentary, we discuss the progress of GWAS in identifying common disease loci for metabolic disease, and the use of the mouse as a model to confirm candidate genes and provide mechanistic insights.

Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here, we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K single nucleotide polymorphisms (SNPs), from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness study. Outcomes included 12 indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. A total of 21 SNPs satisfied this criterion. The top finding indicated that a SNP in Meis homeobox 2 (MEIS2) mediated the effects of risperidone on hip circumference (q=0.004). The same SNP was also found to mediate risperidone's effect on waist circumference (q=0.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as in several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement, and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication.

Evaluation of four novel genetic variants affecting hemoglobin A1c levels in a population-based type 2 diabetes cohort (the HUNT2 study)

BACKGROUND

Chronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes.

METHODS

We genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the BNC2, SORCS1, GSC and WDR72 loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model.

RESULTS

No significant associations with HbA1c or glucose levels were found for the SORCS1, BNC2, GSC or WDR72 variants (all P-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the SORCS1 risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (P = 0.13) and 0.13 mmol/l (P = 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the WDR72 risk variant showed a borderline association with reduced HbA1c levels (β = -0.21, P = 0.06), and direction consistent with decreased glucose levels (β = -0.29, P = 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (β = 0.04, P = 0.38).

CONCLUSIONS

The four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the SORCS1 SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the SORCS1 locus, affect glycemic control in type 2 diabetes.

The genetics of obesity and the metabolic syndrome

In this review, we discuss the genetic architecture of obesity and the metabolic syndrome, highlighting recent advances in identifying genetic variants and loci responsible for a portion of the variation in components of the metabolic syndrome, namely, adiposity traits, serum HDL and triglycerides, blood pressure, and glycemic traits. We focus particularly on recent progress from large-scale genome-wide association studies (GWAS), by detailing their successes and how lessons learned can pave the way for future discovery. Results from recent GWAS coalesce with earlier work suggesting numerous interconnections between obesity and the metabolic syndrome, developed through several potentially pleiotropic effects. We detail recent work by way of a case study on the cadherin 13 gene and its relation with adiponectin in the HyperGEN and the Framingham Heart Studies, and its association with obesity and the metabolic syndrome. We provide also a gene network analysis of recent variants related to obesity and metabolic syndrome discovered through genome-wide association studies, and 4 gene networks based on searching the NCBI database.

AKT1 polymorphisms are associated with risk for metabolic syndrome

Converging lines of evidence suggest that AKT1 is a major mediator of the responses to insulin,insulin-like growth factor 1 (IGF1), and glucose. AKT1 also plays a key role in the regulation of both muscle cell hypertrophy and atrophy. We hypothesized that AKT1 variants may play a role in the endophenotypes that makeup metabolic syndrome. We studied a 12-kb region including the first exon of the AKT1 gene for association with metabolic syndrome-related phenotypes in four study populations [FAMUSS cohort (n = 574; age 23.7 ± 5.7 years), Strong Heart Study (SHS) (n = 2,134; age 55.5 ± 7.9 years), Dynamics of Health, Aging and Body Composition (Health ABC) (n = 3,075; age 73.6 ± 2.9 years), and Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE)(n = 175; age 40–65 years)]. We identified a three SNP haplotype that we call H1, which represents the ancestral alleles eles at the three loci and H2, which represents the derived alleles at the three loci. In young adult European Americans (FAMUSS), H1 was associated with higher fasting glucose levels in females. In middle age Native Americans (SHS), H1 carriers showed higher fasting insulin and HOMA in males, and higher BMI in females. Inolder African-American and European American subjects(Health ABC) H1 carriers showed a higher incidence of metabolic syndrome. Homozygotes for the H1 haplotype showed about twice the risk of metabolic syndrome in both males and females (p < 0.001). In middle-aged European Americans with insulin resistance (STRRIDE) studied by intravenous glucose tolerance test (IVGTT), H1 carriers showed increased insulin resistance due to the Sg component (p = 0.021). The 12-kb haplotype is a risk factor for metabolic syndrome and insulin resistance that needs to be explored in further populations.

Dorothy Hodgkin Lecture 2010. From hype to hope? A journey through the genetics of Type 2 diabetes

Recent advances in genetic analysis have enabled researchers to perform genome-wide surveys for common DNA sequence variants associated with risk of Type 2 diabetes and related traits. Over the past 4 years, these endeavours have extended the number of proven Type 2 diabetes-susceptibility loci from a handful to the current total of over 40. Each of these loci provides an opportunity to uncover insights into the biology of glucose regulation and the pathogenesis of Type 2 diabetes, insights which should support clinical translation to identify novel ways of treating and preventing disease. Here, I describe (i) progress in identification of diabetes-susceptibility loci; (ii) biological insights that have been gained in the relatively short period since these loci were discovered; and (iii) the challenges that need to be addressed if we are to maximize the translational benefits of this research.

The search for genetic risk factors of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is caused by complex interplay between multiple genetic and environmental factors. The three major approaches used to identify the genetic susceptibility include candidate gene approach, familial linkage analysis and genome- wide association analysis. Recent advance in genome-wide association studies have greatly improved our understanding of the pathophysiology of T2DM. As of the end of 2010, there are more than 40 confirmed T2DM-associated genetic loci. Most of the T2DM susceptibility genes were implicated in decreased β-cell function. However, these genetic variations have a modest effect and their combination only explains less than 10% of the T2DM heritability. With the advent of the next-generation sequencing technology, we will soon identify rare variants of larger effect as well as causal variants. These advances in understanding the genetics of T2DM will lead to the development of new therapeutic and preventive strategies and individualized medicine.

Genetics of Type 2 Diabetes

BACKGROUND

Type 2 diabetes (T2D) is a complex disorder that is affected by multiple genetic and environmental factors. Extensive efforts have been made to identify the disease-affecting genes to better understand the disease pathogenesis, find new targets for clinical therapy, and allow prediction of disease.

CONTENT

Our knowledge about the genes involved in disease pathogenesis has increased substantially in recent years, thanks to genomewide association studies and international collaborations joining efforts to collect the huge numbers of individuals needed to study complex diseases on a population level. We have summarized what we have learned so far about the genes that affect T2D risk and their functions. Although more than 40 loci associated with T2D or glycemic traits have been reported and reproduced, only a minor part of the genetic component of the disease has been explained, and the causative variants and affected genes are unknown for many of the loci.

SUMMARY

Great advances have recently occurred in our understanding of the genetics of T2D, but much remains to be learned about the disease etiology. The genetics of T2D has so far been driven by technology, and we now hope that next-generation sequencing will provide important information on rare variants with stronger effects. Even when variants are known, however, great effort will be required to discover how they affect disease risk.

Prospective influences of circadian clocks in adipose tissue and metabolism

Circadian rhythms make a critical contribution to endocrine functions that involve adipose tissue. These contributions are made at the systemic, organ and stem cell levels. The transcription factors and enzymes responsible for the maintenance of circadian rhythms in adipose depots and other peripheral tissues that are metabolically active have now been identified. Furthermore, the circadian regulation of glucose and lipid metabolism is well-established. Animal and human models provide strong evidence that disturbances in circadian pathways are associated with an increased risk of type 2 diabetes mellitus, obesity and their comorbidities. Thus, circadian mechanisms represent a novel putative target for therapy in patients with metabolic diseases.

Resequencing and analysis of variation in the TCF7L2 gene in African Americans suggests that SNP rs7903146 is the causal diabetes susceptibility variant

OBJECTIVE

Variation in the transcription factor 7-like 2 (TCF7L2) locus is associated with type 2 diabetes across multiple ethnicities. The aim of this study was to elucidate which variant in TCF7L2 confers diabetes susceptibility in African Americans.

RESEARCH DESIGN AND METHODS

Through the evaluation of tagging single nucleotide polymorphisms (SNPs), type 2 diabetes susceptibility was limited to a 4.3-kb interval, which contains the YRI (African) linkage disequilibrium (LD) block containing rs7903146. To better define the relationship between type 2 diabetes risk and genetic variation we resequenced this 4.3-kb region in 96 African American DNAs. Thirty-three novel and 13 known SNPs were identified: 20 with minor allele frequencies (MAF) >0.05 and 12 with MAF >0.10. These polymorphisms and the previously identified DG10S478 microsatellite were evaluated in African American type 2 diabetic cases (n = 1,033) and controls (n = 1,106).

RESULTS

Variants identified from direct sequencing and databases were genotyped or imputed. Fifteen SNPs showed association with type 2 diabetes (P < 0.05) with rs7903146 being the most significant (P = 6.32 × 10(-6)). Results of imputation, haplotype, and conditional analysis of SNPs were consistent with rs7903146 being the trait-defining SNP. Analysis of the DG10S478 microsatellite, which is outside the 4.3-kb LD block, revealed consistent association of risk allele 8 with type 2 diabetes (odds ratio [OR] = 1.33; P = 0.022) as reported in European populations; however, allele 16 (MAF = 0.016 cases and 0.032 controls) was strongly associated with reduced risk (OR = 0.39; P = 5.02 × 10(-5)) in contrast with previous studies.

CONCLUSIONS

In African Americans, these observations suggest that rs7903146 is the trait-defining polymorphism associated with type 2 diabetes risk. Collectively, these results support ethnic differences in type 2 diabetes associations.

Meta-analysis of gene-environment interaction: joint estimation of SNP and SNP × environment regression coefficients

INTRODUCTION

Genetic discoveries are validated through the meta-analysis of genome-wide association scans in large international consortia. Because environmental variables may interact with genetic factors, investigation of differing genetic effects for distinct levels of an environmental exposure in these large consortia may yield additional susceptibility loci undetected by main effects analysis. We describe a method of joint meta-analysis (JMA) of SNP and SNP by Environment (SNP × E) regression coefficients for use in gene-environment interaction studies.

METHODS

In testing SNP × E interactions, one approach uses a two degree of freedom test to identify genetic variants that influence the trait of interest. This approach detects both main and interaction effects between the trait and the SNP. We propose a method to jointly meta-analyze the SNP and SNP × E coefficients using multivariate generalized least squares. This approach provides confidence intervals of the two estimates, a joint significance test for SNP and SNP × E terms, and a test of homogeneity across samples.

RESULTS

We present a simulation study comparing this method to four other methods of meta-analysis and demonstrate that the JMA performs better than the others when both main and interaction effects are present. Additionally, we implemented our methods in a meta-analysis of the association between SNPs from the type 2 diabetes-associated gene PPARG and log-transformed fasting insulin levels and interaction by body mass index in a combined sample of 19,466 individuals from five cohorts.

Association of the rs10830963 polymorphism in MTNR1B with fasting glucose levels in Chinese children and adolescents

AIMS

We aimed to identify whether the risk G-allele was associated with fasting glucose level and other pre-diabetic and obesity-related phenotypes in Chinese children and adolescents.

METHODS

The rs10830963 polymorphism in MTNR1B was genotyped in 2,030 Chinese children and adolescents of two independent studies. Association with fasting glucose levels and risk of impaired fasting glucose (IFG) were initially tested. Subsequently we analyzed the association with fasting insulin, homeostasis model assessment for insulin resistance (HOMA-IR) and for beta cell function (HOMA-B), the quantitative insulin sensitivity check index (QUICK) and obesity-related phenotypes (BMI standard deviation score, waist circumference etc.).

RESULTS

The G-allele of rs10830963 was associated with increased fasting glucose level in Chinese children and adolescents (increase of 0.072 mmol/l per G-allele, 95% CI 0.034-0.111, p = 2.46 × 10(-4)). The G-allele was also associated with an increased risk of IFG (OR = 1.21, 95% CI 1.00-1.46, nominal p = 0.048). We found the glucose-raising G-allele was nominally associated with reduced HOMA-B. No association to other pre-diabetic or obesity-related phenotypes was detected.

CONCLUSIONS

The rs10830963 polymorphism in MTNR1B was associated with increased fasting glucose and risk of IFG in Chinese children and adolescents. The effect may result from reduced pancreatic beta cell function, but the mechanism awaits further studies.

Efficacy and safety of prolonged-release melatonin in insomnia patients with diabetes: a randomized, double-blind, crossover study

BACKGROUND

Diabetes is a major comorbidity in insomnia patients. The efficacy and safety of prolonged-release melatonin 2 mg in the treatment of glucose, lipid metabolism, and sleep was studied in 36 type 2 diabetic patients with insomnia (11 men, 25 women, age 46-77 years).

METHODS

In a randomized, double-blind, crossover study, the subjects were treated for 3 weeks (period 1) with prolonged-release melatonin or placebo, followed by a one-week washout period, and then crossed over for another 3 weeks (period 2) of treatment with the other preparation. All tablets were taken 2 hours before bedtime for a period of 3 weeks. In an extension period of 5 months, prolonged-release melatonin was given nightly to all patients in an open-label design. Sleep was objectively monitored in a subgroup of 22 patients using wrist actigraphy. Fasting glucose, fructosamine, insulin, C-peptide, triglycerides, total cholesterol, high-density and low-density lipoprotein cholesterol, and some antioxidants, as well as glycosylated hemoglobin (HbA1c) levels were measured at baseline and at the end of the study. All concomitant medications were continued throughout the study.

RESULTS

No significant changes in serum glucose, fructosamine, insulin, C-peptide, antioxidant levels or blood chemistry were observed after 3 weeks of prolonged-release melatonin treatment. Sleep efficiency, wake time after sleep onset, and number of awakenings improved significantly with prolonged-release melatonin as compared with placebo. Following 5 months of prolonged-release melatonin treatment, mean HbA1c (±standard deviation) was significantly lower than at baseline (9.13% ± 1.55% versus 8.47% ± 1.67%, respectively, P = 0.005).

CONCLUSION

Short-term use of prolonged-release melatonin improves sleep maintenance in type 2 diabetic patients with insomnia without affecting glucose and lipid metabolism. Long-term prolonged-release melatonin administration has a beneficial effect on HbA1c, suggesting improved glycemic control.

Genetic predisposition to long-term nondiabetic deteriorations in glucose homeostasis: Ten-year follow-up of the GLACIER study

OBJECTIVE

To assess whether recently discovered genetic loci associated with hyperglycemia also predict long-term changes in glycemic traits.

RESEARCH DESIGN AND METHODS

Sixteen fasting glucose-raising loci were genotyped in middle-aged adults from the Gene x Lifestyle interactions And Complex traits Involved in Elevated disease Risk (GLACIER) Study, a population-based prospective cohort study from northern Sweden. Genotypes were tested for association with baseline fasting and 2-h postchallenge glycemia (N = 16,330), and for changes in these glycemic traits during a 10-year follow-up period (N = 4,059).

RESULTS

Cross-sectional directionally consistent replication with fasting glucose concentrations was achieved for 12 of 16 variants; 10 variants were also associated with impaired fasting glucose (IFG) and 7 were independently associated with 2-h postchallenge glucose concentrations. In prospective analyses, the effect alleles at four loci (GCK rs4607517, ADRA2A rs10885122, DGKB-TMEM195 rs2191349, and G6PC2 rs560887) were nominally associated with worsening fasting glucose concentrations during 10-years of follow-up. MTNR1B rs10830963, which was predictive of elevated fasting glucose concentrations in cross-sectional analyses, was associated with a protective effect on postchallenge glucose concentrations during follow-up; however, this was only when baseline fasting and 2-h glucoses were adjusted for. An additive effect of multiple risk alleles on glycemic traits was observed: a weighted genetic risk score (80th vs. 20th centiles) was associated with a 0.16 mmol/l (P = 2.4 × 10⁻⁶) greater elevation in fasting glucose and a 64% (95% CI: 33-201%) higher risk of developing IFG during 10 years of follow-up.

CONCLUSIONS

Our findings imply that genetic profiling might facilitate the early detection of persons who are genetically susceptible to deteriorating glucose control; studies of incident type 2 diabetes and discrete cardiovascular end points will help establish whether the magnitude of these changes is clinically relevant.

Statistical issues in gene association studies

This chapter reviews statistical issues related to gene association studies. The goal is to review various aspects of study design and analysis for individuals who do not have an extensive statistical background. We will review statistical issues as they relate to both genome-wide and candidate gene studies. Topics reviewed include study design, power and sample size, data checking, statistical methods, population stratification, and multiple testing. We draw examples from the type 2 diabetes genetics literature to illustrate some of the issues discussed.

Association of a fasting glucose genetic risk score with subclinical atherosclerosis: The Atherosclerosis Risk in Communities (ARIC) study

OBJECTIVE

Elevated fasting glucose level is associated with increased carotid intima-media thickness (IMT), a measure of subclinical atherosclerosis. It is unclear if this association is causal. Using the principle of Mendelian randomization, we sought to explore the causal association between circulating glucose and IMT by examining the association of a genetic risk score with IMT.

RESEARCH DESIGN AND METHODS

The sample was drawn from the Atherosclerosis Risk in Communities (ARIC) study and included 7,260 nondiabetic Caucasian individuals with IMT measurements and relevant genotyping. Components of the fasting glucose genetic risk score (FGGRS) were selected from a fasting glucose genome-wide association study in ARIC. The score was created by combining five single nucleotide polymorphisms (SNPs) (rs780094 [GCKR], rs560887 [G6PC2], rs4607517 [GCK], rs13266634 [SLC30A8], and rs10830963 [MTNR1B]) and weighting each SNP by its strength of association with fasting glucose. IMT was measured through bilateral carotid ultrasound. Mean IMT was regressed on the FGGRS and on the component SNPs, individually.

RESULTS

The FGGRS was significantly associated (P = 0.009) with mean IMT. The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT. Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third.

CONCLUSIONS

The significant association of the FGGRS with IMT suggests a possible causal association of elevated fasting glucose with atherosclerosis, although it may be that these loci influence IMT through nonglucose pathways.

Genetics of type 2 diabetes: the GWAS era and future perspectives [Review]

Genome-wide association studies (GWAS) have facilitated a substantial and rapid rise in the number of confirmed genetic susceptibility variants for type 2 diabetes (T2D). Approximately 40 variants have been identified so far, many of which were discovered through GWAS. This success has led to widespread hope that the findings will translate into improved clinical care for the increasing numbers of patients with diabetes. Potential areas or clinical translation include risk prediction and subsequent disease prevention, pharmacogenetics, and the development of novel therapeutics. However, the genetic loci so far identified account for only a small fraction (approximately 10%) of the overall heritable risk for T2D. Uncovering the missing heritability is essential to the progress of T2D genetic studies and to the translation of genetic information into clinical practice.

The genetics of insulin resistance: Where's Waldo?

The physiologic hallmarks of type 2 diabetes are insulin resistance in hepatic and peripheral tissues and pancreatic β-cell dysfunction. Thus, genetic loci underlying susceptibility to type 2 diabetes are likely to map to one of these endophenotypes. Genome-wide association studies have now identified up to 38 susceptibility loci for type 2 diabetes and a number of other loci underlying variation in type 2 diabetes-related quantitative traits. The majority are of unknown biology or map to pancreatic β-cell dysfunction. A seemingly disproportionate minority map to insulin resistance. We briefly discuss the known insulin resistance loci identified from genome-wide association, and then discuss reasons why additional insulin resistance loci have not been identified. We present alternative views that may partly explain the apparent dearth of insulin resistance loci contributing to genetic susceptibility to type 2 diabetes, rather than focus on traditional issues such as study design and sampling, which have been addressed elsewhere.

Meta-analysis of sex-specific genome-wide association studies

Despite the success of genome-wide association studies, much of the genetic contribution to complex human traits is still unexplained. One potential source of genetic variation that may contribute to this "missing heritability" is that which differs in magnitude and/or direction between males and females, which could result from sexual dimorphism in gene expression. Such sex-differentiated effects are common in model organisms, and are becoming increasingly evident in human complex traits through large-scale male- and female-specific meta-analyses. In this article, we review the methodology for meta-analysis of sex-specific genome-wide association studies, and propose a sex-differentiated test of association with quantitative or dichotomous traits, which allows for heterogeneity of allelic effects between males and females. We perform detailed simulations to compare the power of the proposed sex-differentiated meta-analysis with the more traditional "sex-combined" approach, which is ambivalent to gender. The results of this study highlight only a small loss in power for the sex-differentiated meta-analysis when the allelic effects of the causal variant are the same in males and females. However, over a range of models of heterogeneity in allelic effects between genders, our sex-differentiated meta-analysis strategy offers substantial gains in power, and thus has the potential to discover novel loci contributing effects to complex human traits with existing genome-wide association data.

Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies

OBJECTIVE

Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin.

RESEARCH DESIGN AND METHODS

Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant.

RESULTS

Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele.

CONCLUSIONS

Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

Physiologic characterization of type 2 diabetes-related loci

For the past two decades, genetics has been widely explored as a tool for unraveling the pathogenesis of diabetes. Many risk alleles for type 2 diabetes and hyperglycemia have been detected in recent years through massive genome-wide association studies and evidence exists that most of these variants influence pancreatic β-cell function. However, risk alleles in five loci seem to have a primary impact on insulin sensitivity. Investigations of more detailed physiologic phenotypes, such as the insulin response to intravenous glucose or the incretion hormones, are now emerging and give indications of more specific pathologic mechanisms for diabetes-related risk variants. Such studies have shed light on the function of some loci but also underlined the complex nature of disease mechanism. In the future, sequencing-based discovery of low-frequency variants with higher impact on intermediate diabetes-related traits is a likely scenario and identification of new pathways involved in type 2 diabetes predisposition will offer opportunities for the development of novel therapeutic and preventative approaches.

Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways

OBJECTIVE

Glycated hemoglobin (HbA₁(c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA₁(c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA₁(c) levels.

RESEARCH DESIGN AND METHODS

We studied associations with HbA₁(c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA₁(c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.

RESULTS

Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10⁻²⁶), HFE (rs1800562/P = 2.6 × 10⁻²⁰), TMPRSS6 (rs855791/P = 2.7 × 10⁻¹⁴), ANK1 (rs4737009/P = 6.1 × 10⁻¹²), SPTA1 (rs2779116/P = 2.8 × 10⁻⁹) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10⁻⁹), and four known HbA₁(c) loci: HK1 (rs16926246/P = 3.1 × 10⁻⁵⁴), MTNR1B (rs1387153/P = 4.0 × 10⁻¹¹), GCK (rs1799884/P = 1.5 × 10⁻²⁰) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10⁻¹⁸). We show that associations with HbA₁(c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA₁(c)) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA₁(c).

CONCLUSIONS

GWAS identified 10 genetic loci reproducibly associated with HbA₁(c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA₁(c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA₁(c).

Combined effects of 19 common variations on type 2 diabetes in Chinese: results from two community-based studies

BACKGROUND

Many susceptible loci for type 2 diabetes mellitus (T2DM) have recently been identified from Caucasians through genome wide association studies (GWAS). We aimed to determine the association of 11 known loci with T2DM and impaired glucose regulation (IGR), individually and in combination, in Chinese.

METHODS/PRINCIPAL FINDINGS

Subjects were enrolled in: (1) a case-control study including 1825 subjects with T2DM, 1487 with IGR and 2200 with normal glucose regulation; and (2) a prospective cohort with 734 non-diabetic subjects at baseline. The latter was followed up for 3.5 years, in which 67 subjects developed T2DM. Nineteen single nucleotide polymorphisms (SNPs) were selected to replicate in both studies. We found that CDKAL1 (rs7756992), SLC30A8 (rs13266634, rs2466293), CDKN2A/2B (rs10811661) and KCNQ1 (rs2237892) were associated with T2DM with odds ratio from 1.21 to 1.35. In the prospective study, the fourth quartile of risk scores based on the combined effects of the risk alleles had 3.05 folds (95% CI, 1.31-7.12) higher risk for incident T2DM as compared with the first quartile, after adjustment for age, gender, body mass index and diabetes family history. This combined effect was confirmed in the case-control study after the same adjustments. The addition of the risk scores to the model of clinical risk factors modestly improved discrimination for T2DM by 1.6% in the case-control study and 2.9% in the prospective study.

CONCLUSIONS/SIGNIFICANCE

Our study provided further evidence for these GWAS derived SNPs as the genetic susceptible loci for T2DM in Chinese and extended this association to IGR.

Variants from GIPR, TCF7L2, DGKB, MADD, CRY2, GLIS3, PROX1, SLC30A8 and IGF1 are associated with glucose metabolism in the Chinese

Background

Recent meta-analysis of genome-wide association studies in European descent samples identified novel loci influencing glucose and insulin related traits. In the current study, we aimed to evaluate the association between these loci and traits related to glucose metabolism in the Chinese.

Methods/Principal Findings

We genotyped seventeen single nucleotide polymorphisms (SNPs) from fifteen loci including GIPR, ADCY5, TCF7L2, VPS13C, DGKB, MADD, ADRA2A, FADS1, CRY2, SLC2A2, GLIS3, PROX1, C2CD4B, SLC30A8 and IGF1 in 6,822 Shanghai Chinese Hans comprising 3,410 type 2 diabetic patients and 3,412 normal glucose regulation subjects. MADD rs7944584 showed strong association to type 2 diabetes (p = 3.5×10⁻⁶, empirical p = 0.0002) which was not observed in the European descent populations. SNPs from GIPR, TCF7L2, CRY2, GLIS3 and SLC30A8 were also associated with type 2 diabetes (p = 0.0487∼2.0×10⁻⁸). Further adjusting age, gender and BMI as confounders found PROX1 rs340874 was associated with type 2 diabetes (p = 0.0391). SNPs from DGKB, MADD and SLC30A8 were associated with fasting glucose while PROX1 rs340874 was significantly associated with OGTT 2-h glucose (p = 0.0392∼0.0014, adjusted for age, gender and BMI), the glucose-raising allele also showed association to lower insulin secretion. IGF1 rs35767 showed significant association to both fasting and 2-h insulin levels as well as insulin secretion and sensitivity indices (p = 0.0160∼0.0035, adjusted for age, gender and BMI).

Conclusions/Significance

Our results indicated that SNPs from GIPR, TCF7L2, DGKB, MADD, CRY2, GLIS3, PROX1, SLC30A8 and IGF1 were associated with traits related to glucose metabolism in the Chinese population.