Variants in MTNR1B influence fasting glucose levels

G-allele of intronic rs10830963 in MTNR1B confers increased risk of impaired fasting glycemia and type 2 diabetes through an impaired glucose-stimulated insulin release: studies involving 19,605 Europeans

OBJECTIVE

Genome-wide association studies have identified several variants within the MTNR1B locus that are associated with fasting plasma glucose (FPG) and type 2 diabetes. We refined the association signal by direct genotyping and examined for associations of the variant displaying the most independent effect on FPG with isolated impaired fasting glycemia (i-IFG), isolated impaired glucose tolerance (i-IGT), type 2 diabetes, and measures of insulin release and peripheral and hepatic insulin sensitivity.

RESEARCH DESIGN AND METHODS

We examined European-descent participants in the Inter99 study (n = 5,553), in a sample of young healthy Danes (n = 372), in Danish twins (n = 77 elderly and n = 97 young), in additional Danish type 2 diabetic patients (n = 1,626) and control subjects (n = 505), in the Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) study (n = 4,656), in the North Finland Birth Cohort 86 (n = 5,258), and in the Haguenau study (n = 1,461).

RESULTS

The MTNR1B intronic variant, rs10830963, carried most of the effect on FPG and showed the strongest association with FPG (combined P = 5.3 x 10(-31)) and type 2 diabetes. The rs10830963 G-allele increased the risk of i-IFG (odds ratio [OR] 1.64, P = 5.5 x 10(-11)) but not i-IGT. The G-allele was associated with a decreased insulin release after oral and intravenous glucose challenges (P < 0.01) but not after injection of tolbutamide. In elderly twins, the G-allele associated with hepatic insulin resistance (P = 0.017).

CONCLUSIONS

The G-allele of MTNR1B rs10830963 increases risk of type 2 diabetes through a state of i-IFG and not through i-IGT. The same allele associates with estimates of beta-cell dysfunction and hepatic insulin resistance.

A common variant in MTNR1B, encoding melatonin receptor 1B, is associated with type 2 diabetes and fasting plasma glucose in Han Chinese individuals

AIMS/HYPOTHESIS

Recently, three groups independently reported that variation in MTNR1B, the gene encoding melatonin receptor 1B, was associated with an increased risk of type 2 diabetes, increased fasting plasma glucose and impaired insulin secretion in populations of European ancestry. In the present study, we investigated whether a single MTNR1B polymorphism was associated with type 2 diabetes in Han Chinese individuals, to elucidate whether this is a cross-populational effect.

METHODS

The MTNR1B variant rs10830963 was genotyped in 1,165 type 2 diabetic patients and 1,105 normoglycaemic control individuals of southern Han Chinese ancestry who were residents of the metropolitan area of Shanghai. The risk of developing type 2 diabetes was calculated using a logistic regression model adjusted for age, sex and BMI. A possible association with fasting plasma glucose was analysed in the normoglycaemic control individuals using a multiple linear regression analysis with adjustments for age, sex and BMI.

RESULTS

The genetic variant rs10830963 was associated with an increased risk of type 2 diabetes in our Han Chinese cohort (OR 1.16, 95% CI 1.03-1.31, p = 0.015). As previously described, the risk variant was also associated with increased fasting plasma glucose, showing an increase of 0.068 mmol/l (95% CI 0.036-0.100, p = 4 x 10(-5)) per risk allele.

CONCLUSIONS/INTERPRETATION

A common variant in the MTNR1B gene is associated with an increased risk of type 2 diabetes and increased fasting plasma glucose in Han Chinese, suggesting an important role for this polymorphism in populations of different ethnic and environmental backgrounds.

Islet G protein-coupled receptors as potential targets for treatment of type 2 diabetes

Islet dysfunction - characterized by a combination of defective insulin secretion, inappropriately high glucagon secretion and reduced beta-cell mass - has a central role in the pathophysiology of type 2 diabetes. Several G protein-coupled receptors (GPCRs) expressed in islet beta-cells are known to be involved in the regulation of islet function, and therefore are potential therapeutic targets. This is evident from the recent success of glucagon-like peptide 1 (GLP1) mimetics and dipeptidyl peptidase 4 (DPP4) inhibitors, which promote activation of the GLP1 receptor to stimulate insulin secretion and inhibit glucagon secretion, and also have the potential to increase beta-cell mass. Other islet beta-cell GPCRs that are involved in the regulation of islet function include the glucose-dependent insulinotropic peptide (GIP) receptor, lipid GPCRs, pleiotropic peptide GPCRs and islet biogenic amine GPCRs. This Review summarizes islet GPCR expression, signalling and function, and highlights their potential as targets for the treatment of type 2 diabetes.

Human genetic variation and its contribution to complex traits

The last few years have seen extensive efforts to catalogue human genetic variation and correlate it with phenotypic differences. Most common SNPs have now been assessed in genome-wide studies for statistical associations with many complex traits, including many important common diseases. Although these studies have provided new biological insights, only a limited amount of the heritable component of any complex trait has been identified and it remains a challenge to elucidate the functional link between associated variants and phenotypic traits. Technological advances, such as the ability to detect rare and structural variants, and a clear understanding of the challenges in linking different types of variation with phenotype, will be essential for future progress.

Genome-wide association study for type 2 diabetes: clinical applications

PURPOSE OF REVIEW

Dissecting the genetics of complex polygenic diseases in which environmental factors interact with genetic variants in the predisposition to the disease has not been a trivial task and success has been limited. The purpose of this review is to provide insights into recent advances in genetics of type 2 diabetes.

RECENT FINDINGS

In the past year, together the consortia of several genome-wide association studies for type 2 diabetes have identified 19 common variants increasing susceptibility to disease. Most novel loci seem to influence the capacity of beta-cells to increase insulin secretion in response to increase in insulin resistance or body weight. Combined genetic information ultimately might aid in personalized prediction of disease risk; however, genetic tests cannot be offered yet to predict disease. The main reason is that the increased risk associated with each risk variant is small. We have only begun to explore the role of rare variants with stronger effects or copy number variations in the pathogenesis of type 2 diabetes.

SUMMARY

Rapid progress in the genetics of type 2 diabetes has significantly improved our understanding of disease pathogenesis and provided promising opportunities for drug discoveries over the coming years.

Genome-wide association studies in type 2 diabetes

Despite numerous candidate gene and linkage studies, the field of type 2 diabetes (T2D) genetics had until recently succeeded in identifying few genuine disease-susceptibility loci. The advent of genome-wide association (GWA) scans has transformed the situation, leading to an expansion in the number of established, robustly replicating T2D loci to almost 20. These novel findings offer unique insights into the pathogenesis of T2D and in the main point toward the etiologic importance of disorders of beta-cell development and function. All associated variants have common allele frequencies in the discovery populations, and exert modest to small effects on the risk of disease, characteristics that limit their prognostic and diagnostic potential. However, ongoing studies focusing on the role of copy number variation and targeting low-frequency polymorphisms should identify additional T2D susceptibility loci, some of which may have larger effect sizes and offer better individual prediction of disease risk.

Clinical translation of genetic predictors for type 2 diabetes

PURPOSE OF REVIEW

To highlight recent type 2 diabetes (T2D)-associated genetic discoveries and their potential for clinical application.

RECENT FINDINGS

The advent of genome-wide association screening has uncovered many loci newly associated with T2D. This review describes the techniques applied to discover novel T2D genes and compares their relative strengths, biases, and findings to date. The results of large-scale genome-wide association studies carried out since 2007 are summarized, and limitations of interpreting this preliminary data are offered. Recent studies exploring the clinical potential of these discoveries are reviewed, focusing on insights into T2D pathogenesis, risk prediction of future diabetes, and utility in guiding pharmacotherapy. The new T2D-associated loci have been implicated in beta-cell development and function, highlighting insulin secretion in the disease process. Preliminary risk prediction studies show that more loci are needed to improve T2D risk indices. Studies have also revealed that genes may play a role in the pharmacologic response to antidiabetic medications.

SUMMARY

Since 2007, genome-wide association studies have rapidly increased the number of T2D-associated loci. This review summarizes the history of genetic association studies, the results from the new genome-wide association studies, and the clinical application of these findings.

Obstructive sleep apnea and cardiovascular disease: a perspective and future directions

Data from animal and human studies provide a biological plausibility to the notion that obstructive sleep apnea activates pathways that lead to insulin resistance, atherosclerosis and hypertension. Sleep apnea thus activates the same pathways as does obesity. That obstructive sleep apnea is a risk factor for cardiovascular disease is supported by epidemiological association studies. Longitudinal cohort studies also provide evidence that patients with untreated severe sleep apnea have an increased rate of cardiovascular events. But these studies, while highly suggestive, do not provide the evidence needed to convince the skeptic. This would only be obtained by randomized treatment trials with hard cardiovascular endpoints such as cardiac events and deaths. While such studies are in the planning stages, they will be challenging. There are issues about randomizing individuals with severe sleep apnea and excessive sleepiness into no therapy, since they are at known increased risk for car crashes. Thus, lack of therapy puts others on the road at risk as well as the subject with sleep apnea. There is, moreover, the concern that treating obstructive sleep apnea in very obese individuals will have little impact, since any effect of therapy for OSA will be overwhelmed by the effects of obesity itself. Data from randomized treatment trials for cardiovascular endpoints will likely not be available for many years. In the interim, physicians need to consider how to treat such patients. It is proposed that given that CPAP treatment for obstructive sleep apnea is highly effective and essentially totally safe, and that the evidence is suggestive that sleep apnea is a risk factor for cardiovascular disease, then we propose all patients with severe sleep apnea should be treated to reduce cardiovascular risk.

Adverse metabolic and cardiovascular consequences of circadian misalignment

There is considerable epidemiological evidence that shift work is associated with increased risk for obesity, diabetes, and cardiovascular disease, perhaps the result of physiologic maladaptation to chronically sleeping and eating at abnormal circadian times. To begin to understand underlying mechanisms, we determined the effects of such misalignment between behavioral cycles (fasting/feeding and sleep/wake cycles) and endogenous circadian cycles on metabolic, autonomic, and endocrine predictors of obesity, diabetes, and cardiovascular risk. Ten adults (5 female) underwent a 10-day laboratory protocol, wherein subjects ate and slept at all phases of the circadian cycle-achieved by scheduling a recurring 28-h "day." Subjects ate 4 isocaloric meals each 28-h "day." For 8 days, plasma leptin, insulin, glucose, and cortisol were measured hourly, urinary catecholamines 2 hourly (totaling approximately 1,000 assays/subject), and blood pressure, heart rate, cardiac vagal modulation, oxygen consumption, respiratory exchange ratio, and polysomnographic sleep daily. Core body temperature was recorded continuously for 10 days to assess circadian phase. Circadian misalignment, when subjects ate and slept approximately 12 h out of phase from their habitual times, systematically decreased leptin (-17%, P < 0.001), increased glucose (+6%, P < 0.001) despite increased insulin (+22%, P = 0.006), completely reversed the daily cortisol rhythm (P < 0.001), increased mean arterial pressure (+3%, P = 0.001), and reduced sleep efficiency (-20%, P < 0.002). Notably, circadian misalignment caused 3 of 8 subjects (with sufficient available data) to exhibit postprandial glucose responses in the range typical of a prediabetic state. These findings demonstrate the adverse cardiometabolic implications of circadian misalignment, as occurs acutely with jet lag and chronically with shift work.

Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease

Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

The Rotterdam Study: 2010 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 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 close to a 1,000 research articles and reports (see www.epib.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.

Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion

Genome-wide association studies have shown that variation in MTNR1B (melatonin receptor 1B) is associated with insulin and glucose concentrations. Here we show that the risk genotype of this SNP predicts future type 2 diabetes (T2D) in two large prospective studies. Specifically, the risk genotype was associated with impairment of early insulin response to both oral and intravenous glucose and with faster deterioration of insulin secretion over time. We also show that the MTNR1B mRNA is expressed in human islets, and immunocytochemistry confirms that it is primarily localized in beta cells in islets. Nondiabetic individuals carrying the risk allele and individuals with T2D showed increased expression of the receptor in islets. Insulin release from clonal beta cells in response to glucose was inhibited in the presence of melatonin. These data suggest that the circulating hormone melatonin, which is predominantly released from the pineal gland in the brain, is involved in the pathogenesis of T2D. Given the increased expression of MTNR1B in individuals at risk of T2D, the pathogenic effects are likely exerted via a direct inhibitory effect on beta cells. In view of these results, blocking the melatonin ligand-receptor system could be a therapeutic avenue in T2D.

Genome-wide association analysis of metabolic traits in a birth cohort from a founder population

Genome-wide association studies (GWAS) of longitudinal birth cohorts enable joint investigation of environmental and genetic influences on complex traits. We report GWAS results for nine quantitative metabolic traits (triglycerides, high-density lipoprotein, low-density lipoprotein, glucose, insulin, C-reactive protein, body mass index, and systolic and diastolic blood pressure) in the Northern Finland Birth Cohort 1966 (NFBC1966), drawn from the most genetically isolated Finnish regions. We replicate most previously reported associations for these traits and identify nine new associations, several of which highlight genes with metabolic functions: high-density lipoprotein with NR1H3 (LXRA), low-density lipoprotein with AR and FADS1-FADS2, glucose with MTNR1B, and insulin with PANK1. Two of these new associations emerged after adjustment of results for body mass index. Gene-environment interaction analyses suggested additional associations, which will require validation in larger samples. The currently identified loci, together with quantified environmental exposures, explain little of the trait variation in NFBC1966. The association observed between low-density lipoprotein and an infrequent variant in AR suggests the potential of such a cohort for identifying associations with both common, low-impact and rarer, high-impact quantitative trait loci.

Genotype imputation

Genotype imputation is now an essential tool in the analysis of genome-wide association scans. This technique allows geneticists to accurately evaluate the evidence for association at genetic markers that are not directly genotyped. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of individual scans. Here, we review the history and theoretical underpinnings of the technique. To illustrate performance of the approach, we summarize results from several gene mapping studies. Finally, we preview the role of genotype imputation in an era when whole genome resequencing is becoming increasingly common.