Variants in MTNR1B influence fasting glucose levels

Gαi/o-coupled receptor signaling restricts pancreatic β-cell expansion

Gi-GPCRs, G protein-coupled receptors that signal via Gα proteins of the i/o class (Gαi/o), acutely regulate cellular behaviors widely in mammalian tissues, but their impact on the development and growth of these tissues is less clear. For example, Gi-GPCRs acutely regulate insulin release from pancreatic β cells, and variants in genes encoding several Gi-GPCRs--including the α-2a adrenergic receptor, ADRA2A--increase the risk of type 2 diabetes mellitus. However, type 2 diabetes also is associated with reduced total β-cell mass, and the role of Gi-GPCRs in establishing β-cell mass is unknown. Therefore, we asked whether Gi-GPCR signaling regulates β-cell mass. Here we show that Gi-GPCRs limit the proliferation of the insulin-producing pancreatic β cells and especially their expansion during the critical perinatal period. Increased Gi-GPCR activity in perinatal β cells decreased β-cell proliferation, reduced adult β-cell mass, and impaired glucose homeostasis. In contrast, Gi-GPCR inhibition enhanced perinatal β-cell proliferation, increased adult β-cell mass, and improved glucose homeostasis. Transcriptome analysis detected the expression of multiple Gi-GPCRs in developing and adult β cells, and gene-deletion experiments identified ADRA2A as a key Gi-GPCR regulator of β-cell replication. These studies link Gi-GPCR signaling to β-cell mass and diabetes risk and identify it as a potential target for therapies to protect and increase β-cell mass in patients with diabetes.

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

Understanding how FI and FG levels are regulated is important because their derangement is a feature of T2D. Despite recent success from GWAS in identifying regions of the genome influencing glycemic traits, collectively these loci explain only a small proportion of trait variance. Unlocking the biological mechanisms driving these associations has been challenging because the vast majority of variants map to non-coding sequence, and the genes through which they exert their impact are largely unknown. In the current study, we sought to increase our understanding of the physiological pathways influencing both traits using exome-array genotyping in up to 33,231 non-diabetic individuals to identify coding variants and consequently genes associated with either FG or FI levels. We identified novel association signals for both traits including the receptor for GLP-1 agonists which are a widely used therapy for T2D. Furthermore, we identified coding variants at several GWAS loci which point to the genes underlying these association signals. Importantly, we found that multiple coding variants in G6PC2 result in a loss of protein function and lower fasting glucose levels.

Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.

Circadian rhythms in anesthesia and critical care medicine: potential importance of circadian disruptions

The rotation of the earth and associated alternating cycles of light and dark--the basis of our circadian rhythms--are fundamental to human biology and culture. However, it was not until 1971 that researchers first began to describe the molecular mechanisms for the circadian system. During the past few years, groundbreaking research has revealed a multitude of circadian genes affecting a variety of clinical diseases, including diabetes, obesity, sepsis, cardiac ischemia, and sudden cardiac death. Anesthesiologists, in the operating room and intensive care units, manage these diseases on a daily basis as they significantly affect patient outcomes. Intriguingly, sedatives, anesthetics, and the intensive care unit environment have all been shown to disrupt the circadian system in patients. In the current review, we will discuss how newly acquired knowledge of circadian rhythms could lead to changes in clinical practice and new therapeutic concepts.

Genome-wide association study identifies two novel Loci with sex-specific effects for type 2 diabetes mellitus and glycemic traits in a korean population

BACKGROUND

Until recently, genome-wide association study (GWAS)-based findings have provided a substantial genetic contribution to type 2 diabetes mellitus (T2DM) or related glycemic traits. However, identification of allelic heterogeneity and population-specific genetic variants under consideration of potential confounding factors will be very valuable for clinical applicability. To identify novel susceptibility loci for T2DM and glycemic traits, we performed a two-stage genetic association study in a Korean population.

METHODS

We performed a logistic analysis for T2DM, and the first discovery GWAS was analyzed for 1,042 cases and 2,943 controls recruited from a population-based cohort (KARE, n=8,842). The second stage, de novo replication analysis, was performed in 1,216 cases and 1,352 controls selected from an independent population-based cohort (Health 2, n=8,500). A multiple linear regression analysis for glycemic traits was further performed in a total of 14,232 nondiabetic individuals consisting of 7,696 GWAS and 6,536 replication study participants. A meta-analysis was performed on the combined results using effect size and standard errors estimated for stage 1 and 2, respectively.

RESULTS

A combined meta-analysis for T2DM identified two new (rs11065756 and rs2074356) loci reaching genome-wide significance in CCDC63 and C12orf51 on the 12q24 region. In addition, these variants were significantly associated with fasting plasma glucose and homeostasis model assessment of β-cell function. Interestingly, two independent single nucleotide polymorphisms were associated with sex-specific stratification in this study.

CONCLUSION

Our study showed a strong association between T2DM and glycemic traits. We further observed that two novel loci with multiple diverse effects were highly specific to males. Taken together, these findings may provide additional insights into the clinical assessment or subclassification of disease risk in a Korean population.

Acute melatonin administration in humans impairs glucose tolerance in both the morning and evening

STUDY OBJECTIVES

To study the effect of melatonin administration on glucose metabolism in humans in the morning and evening.

DESIGN

Placebo-controlled, single-blind design.

SETTING

Laboratory assessments.

PARTICIPANTS

21 healthy women (24 ± 6 y; body mass index: 23.0 ± 3.3 kg/m(2)).

INTERVENTIONS

Glucose tolerance was assessed by oral glucose tolerance tests (OGTT; 75 g glucose) on 4 occasions: in the morning (9 AM), and evening (9 PM); each occurring 15 minutes after melatonin (5 mg) and placebo administration on 4 non-consecutive days.

MEASUREMENTS AND RESULTS

Melatonin administration impaired glucose tolerance. When administered in the morning, melatonin significantly increased the incremental area under the curve (AUC) and maximum concentration (Cmax) of plasma glucose following OGTT by 186% and 21%, respectively, as compared to placebo; while in the evening, melatonin significantly increased glucose AUC and Cmax by 54% and 27%, respectively. The effect of melatonin on the insulin response to the OGTT depended on the time of day (P < 0.05). In the morning, melatonin decreased glucose tolerance primarily by decreasing insulin release, while in the evening, by decreasing insulin sensitivity.

CONCLUSIONS

Acute melatonin administration in humans impairs glucose tolerance in both the morning and evening. When administering melatonin, the proximity to meal timing may need to be considered, particularly in those at risk for glucose intolerance.

Therapeutic effects of melatonin receptor agonists on sleep and comorbid disorders

Several melatonin receptors agonists (ramelteon, prolonged-release melatonin, agomelatine and tasimelteon) have recently become available for the treatment of insomnia, depression and circadian rhythms sleep-wake disorders. The efficacy and safety profiles of these compounds in the treatment of the indicated disorders are reviewed. Accumulating evidence indicates that sleep-wake disorders and co-existing medical conditions are mutually exacerbating. This understanding has now been incorporated into the new Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). Therefore, when evaluating the risk/benefit ratio of sleep drugs, it is pertinent to also evaluate their effects on wake and comorbid condition. Beneficial effects of melatonin receptor agonists on comorbid neurological, psychiatric, cardiovascular and metabolic symptomatology beyond sleep regulation are also described. The review underlines the beneficial value of enhancing physiological sleep in comorbid conditions.

Melatonin prevents mitochondrial dysfunction and insulin resistance in rat skeletal muscle

Melatonin has a number of beneficial metabolic actions and reduced levels of melatonin may contribute to type 2 diabetes. The present study investigated the metabolic pathways involved in the effects of melatonin on mitochondrial function and insulin resistance in rat skeletal muscle. The effect of melatonin was tested both in vitro in isolated rats skeletal muscle cells and in vivo using pinealectomized rats (PNX). Insulin resistance was induced in vitro by treating primary rat skeletal muscle cells with palmitic acid for 24 hr. Insulin-stimulated glucose uptake was reduced by palmitic acid followed by decreased phosphorylation of AKT which was prevented my melatonin. Palmitic acid reduced mitochondrial respiration, genes involved in mitochondrial biogenesis and the levels of tricarboxylic acid cycle intermediates whereas melatonin counteracted all these parameters in insulin-resistant cells. Melatonin treatment increases CAMKII and p-CREB but had no effect on p-AMPK. Silencing of CREB protein by siRNA reduced mitochondrial respiration mimicking the effect of palmitic acid and prevented melatonin-induced increase in p-AKT in palmitic acid-treated cells. PNX rats exhibited mild glucose intolerance, decreased energy expenditure and decreased p-AKT, mitochondrial respiration, and p-CREB and PGC-1 alpha levels in skeletal muscle which were restored by melatonin treatment in PNX rats. In summary, we showed that melatonin could prevent mitochondrial dysfunction and insulin resistance via activation of CREB-PGC-1 alpha pathway. Thus, the present work shows that melatonin play an important role in skeletal muscle mitochondrial function which could explain some of the beneficial effects of melatonin in insulin resistance states.

Genetic influences on the association between fetal growth and susceptibility to type 2 diabetes

The fetal insulin hypothesis proposes that low birth weight and susceptibility to type 2 diabetes (T2D) could both be two phenotypes of the same genotype. Insulin is a key growth factor in utero, and T2D is characterized by insulin resistance and/or beta-cell dysfunction. Therefore, genetic variants impacting on insulin secretion and action are likely to alter both fetal growth and susceptibility to T2D. There are three lines of evidence in support of this hypothesis. (1) Studies of rare monogenic diabetes have shown mutations in a single gene, such as GCK or KCNJ11, can cause diabetes by reducing insulin secretion, and these mutations are also associated with reduced birth weight. (2) Epidemiological studies have indicated that children born to fathers with diabetes are born smaller. As the father cannot influence the intrauterine environment, this association is likely to reflect genes inherited by the fetus from the father. (3) The most compelling evidence comes from recent genome-wide association studies. Variants in the CDKAL1 and HHEX-IDE genes that predispose to diabetes, if present in the fetus, are associated with reduced birth weight. These data provide evidence for a genetic contribution to the association between low birth weight and susceptibility to T2D. This genetic background is important to take into consideration when investigating the impact of environmental determinants and developing strategies for intervention and prevention.

Relationship between melatonin receptor 1B and insulin receptor substrate 1 polymorphisms with gestational diabetes mellitus: a systematic review and meta-analysis

Studies have investigated the relationship between genetic variants and risk of gestational diabetes mellitus (GDM). However, the results remain inconclusive. The aim of this study was to investigate the association of rs10830963 and rs1387153 variants in melatonin receptor 1B (MTNR1B) and rs1801278 variant in insulin receptor substrate 1 (IRS1) with GDM susceptibility. Electronic database of PubMed, Medline, Embase, and CNKI (China National Knowledge Infrastructure) were searched for relevant studies between 2005 and 2014. The odds ratio (OR) with its 95% confidence interval (CI) were employed to estimate the association. Total ten case-control studies, including 3428 GDM cases and 4637 healthy controls, met the inclusion criteria. Our results showed a significant association between the three genetic variants and GDM risk, rs10830963 with a P-value less than 0.0001, rs1387153 with a P-value of 0.0002, and rs1801278 with a P-value of 0.001. Furthermore, all the genetic models in these three polymorphisms were associated with increased risks of GDM as well (P< = 0.009). In conclusion, our study found that the genetic polymorphisms rs10830963 and rs1387153 in MTNR1B and rs1801278 in IRS1 were associated with an increased risk of developing GDM. However, further studies with gene-gene and gene-environmental interactions should be considered.

Genetic variation at glucose and insulin trait loci and response to glucose-insulin-potassium (GIK) therapy: the IMMEDIATE trial

The mechanistic effects of intravenous glucose, insulin and potassium (GIK) in cardiac ischemia are not well understood. We conducted a genetic sub-study of the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency care (IMMEDIATE) Trial to explore effects of common and rare glucose and insulin-related genetic loci on initial to 6-h and 6- to 12-h change in plasma glucose and potassium. We identified 27 NOTCH2/ADAM30 and 8 C2CD4B variants conferring a 40-57% increase in glucose during the first 6 h of infusion (P<5.96 × 10(-6)). Significant associations were also found for ABCB11 and SLC30A8 single-nucleotide polymorphisms (SNPs) and glucose responses, and an SEC61A2 SNP with a potassium response to GIK. These studies identify genetic factors that may impact the metabolic response to GIK, which could influence treatment benefits in the setting of acute coronary syndromes (ACS).

The pancreatic β cell: recent insights from human genetics

Diabetes mellitus is a metabolic disease characterised by relative or absolute pancreatic β cell dysfunction. Genetic variants implicated in disease risk can be identified by studying affected individuals. To understand the mechanisms driving genetic associations, variants must be translated through causative transcripts to biological insights. Studies into the genetic basis of Mendelian forms of diabetes have successfully identified genes involved in both β cell function and pancreatic development. For type 2 diabetes (T2D), genome-wide association studies (GWASs) are uncovering an ever-increasing number of susceptibility variants that exert their effect through β cell dysfunction, but translation to mechanistic understanding has in most cases been slow. Improved annotations of the islet genome and advances in whole-genome and -exome sequencing (WHS and WES) have facilitated recent progress.

The effects of light at night on circadian clocks and metabolism

Most organisms display endogenously produced ∼ 24-hour fluctuations in physiology and behavior, termed circadian rhythms. Circadian rhythms are driven by a transcriptional-translational feedback loop that is hierarchically expressed throughout the brain and body, with the suprachiasmatic nucleus of the hypothalamus serving as the master circadian oscillator at the top of the hierarchy. Appropriate circadian regulation is important for many homeostatic functions including energy regulation. Multiple genes involved in nutrient metabolism display rhythmic oscillations, and metabolically related hormones such as glucagon, insulin, ghrelin, leptin, and corticosterone are released in a circadian fashion. Mice harboring mutations in circadian clock genes alter feeding behavior, endocrine signaling, and dietary fat absorption. Moreover, misalignment between behavioral and molecular circadian clocks can result in obesity in both rodents and humans. Importantly, circadian rhythms are most potently synchronized to the external environment by light information and exposure to light at night potentially disrupts circadian system function. Since the advent of electric lights around the turn of the 20th century, exposure to artificial and irregular light schedules has become commonplace. The increase in exposure to light at night parallels the global increase in the prevalence of obesity and metabolic disorders. In this review, we propose that exposure to light at night alters metabolic function through disruption of the circadian system. We first provide an introduction to the circadian system, with a specific emphasis on the effects of light on circadian rhythms. Next we address interactions between the circadian system and metabolism. Finally, we review current experimental and epidemiological work directly associating exposure to light at night and metabolism.

Melatonin synthesis impairment as a new deleterious outcome of diabetes-derived hyperglycemia

Melatonin is a neurohormone that works as a nighttime signal for circadian integrity and health maintenance. It is crucial for energy metabolism regulation, and the diabetes effects on its synthesis are unresolved. Using diverse techniques that included pineal microdialysis and ultrahigh-performance liquid chromatography, the present data show a clear acute and sustained melatonin synthesis reduction in diabetic rats as a result of pineal metabolism impairment that is unrelated to cell death. Hyperglycemia is the main cause of several diabetic complications, and its consequences in terms of melatonin production were assessed. Here, we show that local high glucose (HG) concentration is acutely detrimental to pineal melatonin synthesis in rats both in vivo and in vitro. The clinically depressive action of high blood glucose concentration in melatonin levels was also observed in type 1 diabetes patients who presented a negative correlation between hyperglycemia and 6-sulfatoxymelatonin excretion. Additionally, high-mean-glycemia type 1 diabetes patients presented lower 6-sulfatoxymelatonin levels when compared to control subjects. Although further studies are needed to fully clarify the mechanisms, the present results provide evidence that high circulating glucose levels interfere with pineal melatonin production. Given the essential role played by melatonin as a powerful antioxidant and in the control of energy homeostasis, sleep and biological rhythms and knowing that optimal glycemic control is usually an issue for patients with diabetes, melatonin supplementation may be considered as an additional tool to the current treatment.

MTNR1B Genetic Variability Is Associated with Gestational Diabetes in Czech Women

The gene MTNR1B encodes a receptor for melatonin. Melatonin receptors are expressed in human β-cells, which implies that genetic variants might affect glucose tolerance. Meta-analysis confirmed that the rs10830963 shows the most robust association. The aim of the study was to assess the rs10830963 in Czech GDM patients and controls and to study relations between the SNP and biochemical as well as anthropometric characteristics. Our cohort consisted of 880 women; 458 were diagnosed with GDM, and 422 were normoglycemic controls without history of GDM. Despite similar BMI, the GDM group showed higher WHR, waist circumference, abdominal circumference, and total body fat content. The risk allele G was more frequent in the GDM group (38.3 versus 29.4% in controls, OR 1.49 CI95% [1.22; 1.82]; P OR = 0.0001). In spite of higher frequency, the G allele in the GDM group was not associated with any markers of glucose metabolism. In contrast, controls showed significant association of the allele G with FPG and with postchallenge glycemia during the oGTT. Frequency analysis indicates that rs10830963 is involved in gestational diabetes in Czech women. However, the association of the SNP with glucose metabolism, which is obvious in controls, is covert in women who have experienced GDM.

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

AIMS/HYPOTHESIS

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

METHODS

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

RESULTS

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

CONCLUSIONS/INTERPRETATION

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

Genetic association study with metabolic syndrome and metabolic-related traits in a cross-sectional sample and a 10-year longitudinal sample of chinese elderly population

Background

The metabolic syndrome (MetS) has been known as partly heritable, while the number of genetic studies on MetS and metabolic-related traits among Chinese elderly was limited.

Methods

A cross-sectional analysis was performed among 2 014 aged participants from September 2009 to June 2010 in Beijing, China. An additional longitudinal study was carried out among the same study population from 2001 to 2010. Biochemical profile and anthropometric parameters of all the participants were measured. The associations of 23 SNPs located within 17 candidate genes (MTHFR, PPARγ, LPL, INSIG, TCF7L2, FTO, KCNJ11, JAZF1, CDKN2A/B, ADIPOQ, WFS1, CDKAL1, IGF2BP2, KCNQ1, MTNR1B, IRS1, ACE) with overweight and obesity, diabetes, metabolic phenotypes, and MetS were examined in both studies.

Results

In this Chinese elderly population, prevalence of overweight, central obesity, diabetes, dyslipidemia, hypertension, and MetS were 48.3%, 71.0%, 32.4%, 75.7%, 68.3% and 54.5%, respectively. In the cross-sectional analyses, no SNP was found to be associated with MetS. Genotype TT of SNP rs4402960 within the gene IGF2BP2 was associated with overweight (odds ratio (OR)  = 0.479, 95% confidence interval (CI): 0.316-0.724, p = 0.001) and genotype CA of SNP rs1801131 within the gene MTHFR was associated with hypertension (OR = 1.560, 95% CI: 1.194–2.240, p = 0.001). However, these associations were not observed in the longitudinal analyses.

Conclusions

The associations of SNP rs4402960 with overweight as well as the association of SNP rs1801131 with hypertension were found to be statistically significant. No SNP was identified to be associated with MetS in our study with statistical significance.

Inhibitory G proteins and their receptors: emerging therapeutic targets for obesity and diabetes

The worldwide prevalence of obesity is steadily increasing, nearly doubling between 1980 and 2008. Obesity is often associated with insulin resistance, a major risk factor for type 2 diabetes mellitus (T2DM): a costly chronic disease and serious public health problem. The underlying cause of T2DM is a failure of the beta cells of the pancreas to continue to produce enough insulin to counteract insulin resistance. Most current T2DM therapeutics do not prevent continued loss of insulin secretion capacity, and those that do have the potential to preserve beta cell mass and function are not effective in all patients. Therefore, developing new methods for preventing and treating obesity and T2DM is very timely and of great significance. There is now considerable literature demonstrating a link between inhibitory guanine nucleotide-binding protein (G protein) and G protein-coupled receptor (GPCR) signaling in insulin-responsive tissues and the pathogenesis of obesity and T2DM. These studies are suggesting new and emerging therapeutic targets for these conditions. In this review, we will discuss inhibitory G proteins and GPCRs that have primary actions in the beta cell and other peripheral sites as therapeutic targets for obesity and T2DM, improving satiety, insulin resistance and/or beta cell biology.

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

Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

Metabolic profiling in diabetes

Metabolic profiling, or metabolomics, has developed into a mature science in recent years. It has major applications in the study of metabolic disorders. This review addresses issues relevant to the choice of the metabolomics platform, study design and data analysis in diabetes research, and presents recent advances using metabolomics in the identification of markers for altered metabolic pathways, biomarker discovery, challenge studies, metabolic markers of drug efficacy and off-target effects. The role of genetic variance and intermediate metabolic phenotypes and its relevance to diabetes research is also addressed.

Chronobiology and obesity: Interactions between circadian rhythms and energy regulation

Recent advances in the understanding of the molecular, genetic, neural, and physiologic basis for the generation and organization of circadian clocks in mammals have revealed profound bidirectional interactions between the circadian clock system and pathways critical for the regulation of metabolism and energy balance. The discovery that mice harboring a mutation in the core circadian gene circadian locomotor output cycles kaput (Clock) develop obesity and evidence of the metabolic syndrome represented a seminal moment for the field, clearly establishing a link between circadian rhythms, energy balance, and metabolism at the genetic level. Subsequent studies have characterized in great detail the depth and magnitude of the circadian clock's crucial role in regulating body weight and other metabolic processes. Dietary nutrients have been shown to influence circadian rhythms at both molecular and behavioral levels; and many nuclear hormone receptors, which bind nutrients as well as other circulating ligands, have been observed to exhibit robust circadian rhythms of expression in peripheral metabolic tissues. Furthermore, the daily timing of food intake has itself been shown to affect body weight regulation in mammals, likely through, at least in part, regulation of the temporal expression patterns of metabolic genes. Taken together, these and other related findings have transformed our understanding of the important role of time, on a 24-h scale, in the complex physiologic processes of energy balance and coordinated regulation of metabolism. This research has implications for human metabolic disease and may provide unique and novel insights into the development of new therapeutic strategies to control and combat the epidemic of obesity.

Melatonin, energy metabolism, and obesity: a review

Melatonin is an old and ubiquitous molecule in nature showing multiple mechanisms of action and functions in practically every living organism. In mammals, pineal melatonin functions as a hormone and a chronobiotic, playing a major role in the regulation of the circadian temporal internal order. The anti-obesogen and the weight-reducing effects of melatonin depend on several mechanisms and actions. Experimental evidence demonstrates that melatonin is necessary for the proper synthesis, secretion, and action of insulin. Melatonin acts by regulating GLUT4 expression and/or triggering, via its G-protein-coupled membrane receptors, the phosphorylation of the insulin receptor and its intracellular substrates mobilizing the insulin-signaling pathway. Melatonin is a powerful chronobiotic being responsible, in part, by the daily distribution of metabolic processes so that the activity/feeding phase of the day is associated with high insulin sensitivity, and the rest/fasting is synchronized to the insulin-resistant metabolic phase of the day. Furthermore, melatonin is responsible for the establishment of an adequate energy balance mainly by regulating energy flow to and from the stores and directly regulating the energy expenditure through the activation of brown adipose tissue and participating in the browning process of white adipose tissue. The reduction in melatonin production, as during aging, shift-work or illuminated environments during the night, induces insulin resistance, glucose intolerance, sleep disturbance, and metabolic circadian disorganization characterizing a state of chronodisruption leading to obesity. The available evidence supports the suggestion that melatonin replacement therapy might contribute to restore a more healthy state of the organism.

Genetics of type 2 diabetes: insights into the pathogenesis and its clinical application

With rapidly increasing prevalence, diabetes has become one of the major causes of mortality worldwide. According to the latest studies, genetic information makes substantial contributions towards the prediction of diabetes risk and individualized antidiabetic treatment. To date, approximately 70 susceptibility genes have been identified as being associated with type 2 diabetes (T2D) at a genome-wide significant level (P < 5 × 10⁻⁸). However, all the genetic loci identified so far account for only about 10% of the overall heritability of T2D. In addition, how these novel susceptibility loci correlate with the pathophysiology of the disease remains largely unknown. This review covers the major genetic studies on the risk of T2D based on ethnicity and briefly discusses the potential mechanisms and clinical utility of the genetic information underlying T2D.

Recent advances in the molecular genetics of type 2 diabetes mellitus

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

Search for genetic determinants of sulfonylurea efficacy in type 2 diabetic patients from China

AIMS/HYPOTHESIS

The aim of this study was to investigate whether genetic variance can influence the efficacy of glibenclamide in patients with type 2 diabetes.

METHODS

A total of 747 patients with type 2 diabetes was enrolled from the Xiaoke Pills Clinical Trial, which is a double-blind, randomised controlled trial. All the patients had been treated with glibenclamide for 48 weeks, with strict drug dose adjustment and data collection. Treatment failure was confirmed when patients reached the criteria for terminating their participation in the study (fasting blood glucose level ≥ 7.0 mmol/l on two consecutive tests 4 weeks after reaching the pre-set maximal dose or maximal tolerated dose). Using this cohort, we tested 44 single-nucleotide polymorphisms (SNPs) in 27 gene regions. The genes in our study were involved in the metabolism of sulfonylureas, islet beta cell function, insulin resistance and beta cell growth and differentiation. A logistic regression model was used to evaluate the relationship between genetic variants and treatment failure over a period of 48 weeks.

RESULTS

We found that no SNP reached the significance level of p < 0.00125 if Bonferroni correction was performed for multiple testing in the logistic regression model used in this pharmacogenetic study. Participants with the minor allele C of rs10811661 in CDKN2A/CDKN2B showed a significantly greater reduction in fasting blood glucose (TT vs TC vs CC: 9.3% (0-20.0%) vs 9.2% (0.9-20.5%) vs 12.7% (5.2-24.4%), p = 0.008) after the initial 4 weeks of treatment independent of age, sex and BMI. There was a significant difference in beta cell function among carriers of different genotypes of rs10811661.

CONCLUSIONS/INTERPRETATION

Our study demonstrated that the CDKN2A/CDKN2B gene may be nominally associated with the efficacy of glibenclamide, and that CDKN2A/CDKN2B is associated with beta cell function.

Does disruption of circadian rhythms contribute to beta-cell failure in type 2 diabetes?

Type 2 diabetes mellitus (T2DM) is a complex metabolic disease characterized by the loss of beta-cell secretory function and mass. The pathophysiology of beta-cell failure in T2DM involves a complex interaction between genetic susceptibilities and environmental risk factors. One environmental condition that is gaining greater appreciation as a risk factor for T2DM is the disruption of circadian rhythms (eg, shift-work and sleep loss). In recent years, circadian disruption has become increasingly prevalent in modern societies and consistently shown to augment T2DM susceptibility (partly mediated through its effects on pancreatic beta-cells). Since beta-cell failure is essential for development of T2DM, we will review current work from epidemiologic, clinical, and animal studies designed to gain insights into the molecular and physiological mechanisms underlying the predisposition to beta-cell failure associated with circadian disruption. Elucidating the role of circadian clocks in regulating beta-cell health will add to our understanding of T2DM pathophysiology and may contribute to the development of novel therapeutic and preventative approaches.

Nutrigenetics: bridging two worlds to understand type 2 diabetes

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

Interrogating causal pathways linking genetic variants, small molecule metabolites, and circulating lipids

BACKGROUND

Emerging technologies based on mass spectrometry or nuclear magnetic resonance enable the monitoring of hundreds of small metabolites from tissues or body fluids. Profiling of metabolites can help elucidate causal pathways linking established genetic variants to known disease risk factors such as blood lipid traits.

METHODS

We applied statistical methodology to dissect causal relationships between single nucleotide polymorphisms, metabolite concentrations, and serum lipid traits, focusing on 95 genetic loci reproducibly associated with the four main serum lipids (total-, low-density lipoprotein-, and high-density lipoprotein- cholesterol and triglycerides). The dataset used included 2,973 individuals from two independent population-based cohorts with data for 151 small molecule metabolites and four main serum lipids. Three statistical approaches, namely conditional analysis, Mendelian randomization, and structural equation modeling, were compared to investigate causal relationship at sets of a single nucleotide polymorphism, a metabolite, and a lipid trait associated with one another.

RESULTS

A subset of three lipid-associated loci (FADS1, GCKR, and LPA) have a statistically significant association with at least one main lipid and one metabolite concentration in our data, defining a total of 38 cross-associated sets of a single nucleotide polymorphism, a metabolite and a lipid trait. Structural equation modeling provided sufficient discrimination to indicate that the association of a single nucleotide polymorphism with a lipid trait was mediated through a metabolite at 15 of the 38 sets, and involving variants at the FADS1 and GCKR loci.

CONCLUSIONS

These data provide a framework for evaluating the causal role of components of the metabolome (or other intermediate factors) in mediating the association between established genetic variants and diseases or traits.

Physiological responses to food intake throughout the day

Circadian rhythms act to optimise many aspects of our biology and thereby ensure that physiological processes are occurring at the most appropriate time. The importance of this temporal control is demonstrated by the strong associations between circadian disruption, morbidity and disease pathology. There is now a wealth of evidence linking the circadian timing system to metabolic physiology and nutrition. Relationships between these processes are often reciprocal, such that the circadian system drives temporal changes in metabolic pathways and changes in metabolic/nutritional status alter core molecular components of circadian rhythms. Examples of metabolic rhythms include daily changes in glucose homeostasis, insulin sensitivity and postprandial response. Time of day alters lipid and glucose profiles following individual meals whereas, over a longer time scale, meal timing regulates adiposity and body weight; these changes may occur via the ability of timed feeding to synchronise local circadian rhythms in metabolically active tissues. Much of the work in this research field has utilised animal and cellular model systems. Although these studies are highly informative and persuasive, there is a largely unmet need to translate basic biological data to humans. The results of such translational studies may open up possibilities for using timed dietary manipulations to help restore circadian synchrony and downstream physiology. Given the large number of individuals with disrupted rhythms due to, for example, shift work, jet-lag, sleep disorders and blindness, such dietary manipulations could provide widespread improvements in health and also economic performance.

Circadian control of glucose metabolism

The incidence of obesity and type 2 diabetes mellitus (T2DM) has risen to epidemic proportions. The pathophysiology of T2DM is complex and involves insulin resistance, pancreatic β-cell dysfunction and visceral adiposity. It has been known for decades that a disruption of biological rhythms (which happens the most profoundly with shift work) increases the risk of developing obesity and T2DM. Recent evidence from basal studies has further sparked interest in the involvement of daily rhythms (and their disruption) in the development of obesity and T2DM. Most living organisms have molecular clocks in almost every tissue, which govern rhythmicity in many domains of physiology, such as rest/activity rhythms, feeding/fasting rhythms, and hormonal secretion. Here we present the latest research describing the specific role played by the molecular clock mechanism in the control of glucose metabolism and speculate on how disruption of these tissue clocks may lead to the disturbances in glucose homeostasis.

Genetic Testing and Type 2 Diabetes Risk Awareness

PURPOSE

The purpose of this study was to examine the motivational, attitudinal, and behavioral predictors of interest in genetic testing (GT) in those with and without awareness of their risk for type 2 diabetes (T2DM).

METHODS

A convenience sample of adults visiting emergency departments, libraries, or an online research registry was surveyed. Responses from adults without diabetes who reported 1 or more risk factors for T2DM (eg, family history, body mass index > 25) were included in the analyses (n = 265).

RESULTS

Participants were 37 ± 11 years old, white (54%), and female (69%), with some college education (53%) and an annual income below $25 000 (44%). Approximately half (52%) expressed interest in GT for T2DM. Individuals were stratified by perceived risk for T2DM (risk aware or risk unaware). Among the risk aware, younger age (P < .04) predicted greater interest in GT. Among the risk unaware, family history of T2DM (P < .008) and preference to know genetic risk (P < .0002) predicted interest in GT. Both groups identified the need for low-cost GT.

CONCLUSIONS

GT is an increasingly available and accurate tool to predict T2DM risk for patients. In this sample, GT was a salient tool for those with and without awareness of their T2DM risk. Financial accessibility is critical to use of this tool for both groups.

Interactions between sleep, circadian function, and glucose metabolism: implications for risk and severity of diabetes

Sleep disturbances, including sleep insufficiency and sleep fragmentation, have been linked to abnormal glucose metabolism and increased diabetes risk. Well-controlled laboratory studies have provided insights regarding the underlying mechanisms. Several large prospective studies suggest that these sleep disturbances are associated with an increased risk of incident diabetes. Obstructive sleep apnea, which combines sleep fragmentation and hypoxemia, is a major risk factor for insulin resistance and possibly diabetes. Whether glycemic control in type 2 diabetes patients can be improved by treating sleep apnea remains controversial. Recently, sleep disturbances during pregnancy and their relationship to gestational diabetes and hyperglycemia have received considerable attention owing to potential adverse effects on maternal and fetal health. Additionally, evidence from animal models has identified disruption of the circadian system as a putative risk factor for adverse metabolic outcomes. The purpose of this review is to provide an update on the current state of knowledge linking sleep disturbances, circadian dysfunction, and glucose metabolism. Experimental, prospective, and interventional studies are discussed.

Genetic modifiers of cognitive maintenance among older adults

Objective

Identify genetic factors associated with cognitive maintenance in late life and assess their association with gray matter (GM) volume in brain networks affected in aging.

Methods

We conducted a genome‐wide association study of ∼2.4 M markers to identify modifiers of cognitive trajectories in Caucasian participants (N = 7,328) from two population‐based cohorts of non‐demented elderly. Standardized measures of global cognitive function (z‐scores) over 10 and 6 years were calculated among participants and mixed model regression was used to determine subject‐specific cognitive slopes. “Cognitive maintenance” was defined as a change in slope of ≥ 0 and was compared with all cognitive decliners (slope < 0). In an independent cohort of cognitively normal older Caucasians adults (N = 122), top association findings were then used to create genetic scores to assess whether carrying more cognitive maintenance alleles was associated with greater GM volume in specific brain networks using voxel‐based morphometry.

Results

The most significant association was on chromosome 11 (rs7109806, P = 7.8 × 10⁻⁸) near RIC3. RIC3 modulates activity of α7 nicotinic acetylcholine receptors, which have been implicated in synaptic plasticity and beta‐amyloid binding. In the neuroimaging cohort, carrying more cognitive maintenance alleles was associated with greater volume in the right executive control network (RECN; P_FWE = 0.01).

Conclusions

These findings suggest that there may be genetic loci that promote healthy cognitive aging and that they may do so by conferring robustness to GM in the RECN. Future work is required to validate top candidate genes such as RIC3 for involvement in cognitive maintenance. Hum Brain Mapp 35:4556–4565, 2014. © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

CRY1 circadian gene variant interacts with carbohydrate intake for insulin resistance in two independent populations: Mediterranean and North American

Dysregulation in the circadian system induced by variants of clock genes has been associated with type 2 diabetes. Evidence for the role of cryptochromes, core components of the system, in regulating glucose homeostasis is not supported by CRY1 candidate gene association studies for diabetes and insulin resistance in human, suggesting possible dietary influences. The purpose of this study was to test for interactions between a CRY1 polymorphism, rs2287161, and carbohydrate intake on insulin resistance in two independent populations: a Mediterranean (n = 728) and an European origin North American population (n = 820). Linear regression interaction models were performed in two populations to test for gene-diet interactions on fasting insulin and glucose and two insulin-related traits, homeostasis model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI). In addition, fixed effects meta-analyses for these interactions were performed. Cohort-specific interaction analyses showed significant interactions between the CRY1 variant and dietary carbohydrates for insulin resistance in both populations (p < 0.05). Findings from the meta-analyses of carbohydrate-single nucleotide polymorphism interactions indicated that an increase in carbohydrate intake (% of energy intake) was associated with a significant increase in HOMA-IR (p = 0.011), fasting insulin (p = 0.007) and a decrease in QUICKI (p = 0.028), only among individuals homozygous for the minor C allele. This novel finding supports the link between the circadian system and glucose metabolism and suggests the importance this CRY1 locus in developing personalized nutrition programs aimed at reducing insulin resistance and diabetes risk.

BETASEQ: a powerful novel method to control type-I error inflation in partially sequenced data for rare variant association testing

SUMMARY

Despite its great capability to detect rare variant associations, next-generation sequencing is still prohibitively expensive when applied to large samples. In case-control studies, it is thus appealing to sequence only a subset of cases to discover variants and genotype the identified variants in controls and the remaining cases under the reasonable assumption that causal variants are usually enriched among cases. However, this approach leads to inflated type-I error if analyzed naively for rare variant association. Several methods have been proposed in recent literature to control type-I error at the cost of either excluding some sequenced cases or correcting the genotypes of discovered rare variants. All of these approaches thus suffer from certain extent of information loss and thus are underpowered. We propose a novel method (BETASEQ), which corrects inflation of type-I error by supplementing pseudo-variants while keeps the original sequence and genotype data intact. Extensive simulations and real data analysis demonstrate that, in most practical situations, BETASEQ leads to higher testing powers than existing approaches with guaranteed (controlled or conservative) type-I error.

AVAILABILITY AND IMPLEMENTATION

BETASEQ and associated R files, including documentation, examples, are available at http://www.unc.edu/~yunmli/betaseq

Genetic insights into cardiometabolic risk factors

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

Sleep duration does not mediate or modify association of common genetic variants with type 2 diabetes

AIMS/HYPOTHESIS

Short and long sleep duration are associated with increased risk of type 2 diabetes. We aimed to investigate whether genetic variants for fasting glucose or type 2 diabetes associate with short or long sleep duration and whether sleep duration modifies the association of genetic variants with these traits.

METHODS

We examined the cross-sectional relationship between self-reported habitual sleep duration and prevalence of type 2 diabetes in individuals of European descent participating in five studies included in the Candidate Gene Association Resource (CARe), totalling 1,474 cases and 8,323 controls. We tested for association of 16 fasting glucose-associated variants, 27 type 2 diabetes-associated variants and aggregate genetic risk scores with continuous and dichotomised (≤5 h or ≥9 h) sleep duration using regression models adjusted for age, sex and BMI. Finally, we tested whether a gene × behaviour interaction of variants with sleep duration had an impact on fasting glucose or type 2 diabetes risk.

RESULTS

Short sleep duration was significantly associated with type 2 diabetes in CARe (OR 1.32; 95% CI 1.08, 1.61; p = 0.008). Variants previously associated with fasting glucose or type 2 diabetes and genetic risk scores were not associated with sleep duration. Furthermore, no study-wide significant interaction was observed between sleep duration and these variants on glycaemic traits. Nominal interactions were observed for sleep duration and PPARG rs1801282, CRY2 rs7943320 and HNF1B rs4430796 in influencing risk of type 2 diabetes (p < 0.05).

CONCLUSIONS/INTERPRETATION

Our findings suggest that differences in habitual sleep duration do not mediate or modify the relationship between common variants underlying glycaemic traits (including in circadian rhythm genes) and diabetes.

Variants in glucose- and circadian rhythm-related genes affect the response of energy expenditure to weight-loss diets: the POUNDS LOST Trial

BACKGROUND

Circadian rhythm has been shown to be related to glucose metabolism and risk of diabetes, probably through effects on energy balance. Recent genome-wide association studies identified variants in circadian rhythm-related genes (CRY2 and MTNR1B) associated with glucose homeostasis.

OBJECTIVE

We tested whether CRY2 and MTNR1B genotypes affected changes in measures of energy expenditure in response to a weight-loss diet intervention in a 2-y randomized clinical trial, the POUNDS (Preventing Overweight Using Novel Dietary Strategies) LOST Trial.

DESIGN

The variants CRY2 rs11605924 (n = 721) and MTNR1B rs10830963 (n = 722) were genotyped in overweight or obese adults who were randomly assigned to 1 of 4 weight-loss diets that differed in their proportions of macronutrients. Respiratory quotient (RQ) and resting metabolic rate (RMR) were measured.

RESULTS

By 2 y of diet intervention, the A allele of CRY2 rs11605924 was significantly associated with a greater reduction in RQ (P = 0.03) and a greater increase in RMR and RMR/kg (both P = 0.04). The G allele of MTNR1B rs10830963 was significantly associated with a greater increase in RQ (P = 0.01) but was not related to changes in RMR and RMR/kg. In addition, we found significant gene-diet fat interactions for both CRY2 (P-interaction = 0.02) and MTNR1B (P-interaction < 0.001) in relation to 2-y changes in RQ.

CONCLUSIONS

Our data indicate that variants in the circadian-related genes CRY2 and MTNR1B may affect long-term changes in energy expenditure, and dietary fat intake may modify the genetic effects. This trial was registered at www.clinicaltrials.gov as NCT00072995.

Association of KCNQ1 and KLF14 polymorphisms and risk of type 2 diabetes mellitus: A global meta-analysis

rs151290 in KCNQ1 and rs972283 in KLF14 have been evaluated in terms of risk of type 2 diabetes mellitus (T2DM), but the results are inconsistent. We performed an meta-analysis to assess the contributions of rs151290 in KCNQ1 and rs972283 in KLF14 to risk of T2DM. We searched the worldwide literature published from 2008 to 2013 in MEDLINE via PubMed, EMBASE, Cochrane CENTRAL and Chinese databases. Two reviewers extracted data independently using a standardized protocol, and any discrepancies were resolved by a third reviewer. Fixed- and random-effects meta-analyses were performed to pool the odds ratios (ORs). Publication bias and heterogeneity were examined. A total of 11 articles were included in the meta-analysis: 6 studies with 6696 cases and 7151 controls investigated rs151290 in KCNQ1, and 5 studies with 50,552 cases and 106,535 controls investigated rs972283 in KLF14. We obtained highly significant ORs for the risk allele C for rs151290 and the risk allele G for rs972283. The population attributable risk percentage for rs151290 and rs972283 was 6.83% and 4.18%, respectively. The risk allele C of rs151290 in KCNQ1 and risk allele G of rs972283 in KLF14 were both associated with increased risk of T2DM in a global population.

Genetics of diabetes--are we missing the genes or the disease?

Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of diabetes is associated with long-term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Several pathogenic processes are involved in the development of diabetes. These range from autoimmune destruction of the beta-cells of the pancreas with consequent insulin deficiency to abnormalities that result in resistance to insulin action (American Diabetes Association, 2011). The vast majority of cases of diabetes fall into two broad categories. In type 1 diabetes (T1D), the cause is an absolute deficiency of insulin secretion, whereas in type 2 diabetes (T2D), the cause is a combination of resistance to insulin action and an inadequate compensatory insulin secretory response. However, the subdivision into two main categories represents a simplification of the real situation, and research during the recent years has shown that the disease is much more heterogeneous than a simple subdivision into two major subtypes assumes. Worldwide prevalence figures estimate that there are 280 million diabetic patients in 2011 and more than 500 million in 2030 (http://www.diabetesatlas.org/). In Europe, about 6-8% of the population suffer from diabetes, of them about 90% has T2D and 10% T1D, thereby making T2D to the fastest increasing disease in Europe and worldwide. This epidemic has been ascribed to a collision between the genes and the environment. While our knowledge about the genes is clearly better for T1D than for T2D given the strong contribution of variation in the HLA region to the risk of T1D, the opposite is the case for T2D, where our knowledge about the environmental triggers (obesity, lack of exercise) is much better than the understanding of the underlying genetic causes. This lack of knowledge about the underlying genetic causes of diabetes is often referred to as missing heritability (Manolio et al., 2009) which exceeds 80% for T2D but less than 25% for T1D. In the following review, we will discuss potential sources of this missing heritability which also includes the possibility that our definition of diabetes and its subgroups is imprecise and thereby making the identification of genetic causes difficult.

Overlap of genetic susceptibility to type 1 diabetes, type 2 diabetes, and latent autoimmune diabetes in adults

Despite the notion that there is a degree of commonality to the biological etiology of type 1 diabetes (T1D) and type 2 diabetes (T2D), the lack of overlap in the genetic factors underpinning each of them suggests very distinct mechanisms. A disorder considered to be at the "intersection" of these two diseases is "latent autoimmune diabetes in adults" (LADA). Interestingly, genetic signals from both T1D and T2D are also seen in LADA, including the key HLA and transcription factor 7-like 2 (TCF7L2) loci, but the magnitudes of these effects are more complex than just pointing to LADA as being a simple admixture of T1D and T2D. We review the current status of the understanding of the genetics of LADA and place it in the context of what is known about the genetics of its better-studied "cousins," T1D and T2D, especially with respect to the myriad of discoveries made over the last decade through genome-wide association studies.

Influence of melatonin receptor signalling on parameters involved in blood glucose regulation

The pineal hormone melatonin is known to influence insulin secretion via the G-protein-coupled receptor isoforms MT1 and MT2. The present study was aimed to further elucide the impact of melatonin on blood glucose regulation. To this end, mouse lines were used, in which one of the two or both melatonin receptors were deleted. In comparison with wild-type mice of the same age (8-12 months old), increased plasma insulin and melatonin levels and decreased blood glucose levels and body weights were detected in the MT1- and double-knockout lines. The elimination of melatonin receptor signalling also altered blood glucose concentrations, body weight and melatonin and insulin levels when comparing wild-type and receptor knockout mice of different ages (6 wk and 8-12 months old); such changes, however, were dependent on the type of receptor deleted. Furthermore, reverse transcription polymerase chain reaction results provided evidence that melatonin receptor deficiency has an impact on transcript levels of pancreatic islet hormones as well as on pancreatic and hepatic glucose transporters (Glut1 and 2). Under stimulated insulin secretion in the presence of melatonin in the rat insulinoma β-cells INS-1, the Glut1 transcript level was decreased. In conclusion, the present findings demonstrate that melatonin receptor knockout types affect blood glucose levels, body weight, plasma levels of melatonin and insulin, as well as pancreatic hormone and Glut1 expression in significantly different manners.

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

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

Unveiling the role of melatonin MT2 receptors in sleep, anxiety and other neuropsychiatric diseases: a novel target in psychopharmacology

BACKGROUND

Melatonin (MLT) is a pleiotropic neurohormone controlling many physiological processes and whose dysfunction may contribute to several different diseases, such as neurodegenerative diseases, circadian and mood disorders, insomnia, type 2 diabetes and pain. Melatonin is synthesized by the pineal gland during the night and acts through 2 G-protein coupled receptors (GPCRs), MT1 (MEL1a) and MT2 (MEL1b). Although a bulk of research has examined the physiopathological effects of MLT, few studies have investigated the selective role played by MT1 and MT2 receptors. Here we have reviewed current knowledge about the implications of MT2 receptors in brain functions.

METHODS

We searched PubMed, Web of Science, Scopus, Google Scholar and articles' reference lists for studies on MT2 receptor ligands in sleep, anxiety, neuropsychiatric diseases and psychopharmacology, including genetic studies on the MTNR1B gene, which encodes the melatonin MT2 receptor.

RESULTS

These studies demonstrate that MT2 receptors are involved in the pathophysiology and pharmacology of sleep disorders, anxiety, depression, Alzheimer disease and pain and that selective MT2 receptor agonists show hypnotic and anxiolytic properties.

LIMITATIONS

Studies examining the role of MT2 receptors in psychopharmacology are still limited.

CONCLUSION

The development of novel selective MT2 receptor ligands, together with further preclinical in vivo studies, may clarify the role of this receptor in brain function and psychopharmacology. The superfamily of GPCRs has proven to be among the most successful drug targets and, consequently, MT2 receptors have great potential for pioneer drug discovery in the treatment of mental diseases for which limited therapeutic targets are currently available.

Genetic susceptibility to type 2 diabetes and obesity: follow-up of findings from genome-wide association studies

Elucidating the underlying genetic variations influencing various complex diseases is one of the major challenges currently facing clinical genetic research. Although these variations are often difficult to uncover, approaches such as genome-wide association studies (GWASs) have been successful at finding statistically significant associations between specific genomic loci and disease susceptibility. GWAS has been especially successful in elucidating genetic variants that influence type 2 diabetes (T2D) and obesity/body mass index (BMI). Specifically, several GWASs have confirmed that a variant in transcription factor 7-like 2 (TCF7L2) confers risk for T2D, while a variant in fat mass and obesity-associated protein (FTO) confers risk for obesity/BMI; indeed both of these signals are considered the most statistically associated loci discovered for these respective traits to date. The discovery of these two key loci in this context has been invaluable for providing novel insight into mechanisms of heritability and disease pathogenesis. As follow-up studies of TCF7L2 and FTO have typically lead the way in how to follow up a GWAS discovery, we outline what has been learned from such investigations and how they have implications for the myriad of other loci that have been subsequently reported in this disease context.

Melatonin supplementation to treat the metabolic syndrome: a randomized controlled trial

BACKGROUND

Supplemental melatonin may ameliorate metabolic syndrome (MetS) components, but data from placebo-controlled trials are lacking.

METHODS

We conducted a double-blind, placebo-controlled, crossover, Phase II randomized pilot clinical trial to estimate the effects of melatonin supplementation on MetS components and the overall prevalence of MetS. We randomized 39 subjects with MetS to receive 8.0 mg oral melatonin or matching placebo nightly for 10 weeks. After a 6-week washout, subjects received the other treatment for 10 more weeks. We measured waist circumference, triglycerides, HDL cholesterol, fasting glucose, and blood pressure (BP) in each subject at the beginning and end of both 10-week treatment periods. The primary outcome was the mean 10-week change in each MetS component, and a secondary outcome was the proportion of subjects free from MetS, after melatonin versus placebo.

RESULTS

The mean 10-week change for most MetS components favored melatonin over placebo (except fasting glucose): waist circumference -0.9 vs. +1.0 cm (p = 0.15); triglycerides -66.3 vs. -4.2 mg/dL (p = 0.17); HDL cholesterol -0.2 vs. -1.1 mg/dL (p = 0.59); fasting glucose +0.3 vs. -3.1 mg/dL (p = 0.29); systolic BP -2.7 vs. +4.7 mmHg (p = 0.013); and diastolic BP -1.1 vs. +1.1 mmHg (p = 0.24). Freedom from MetS tended to be more common following melatonin versus placebo treatment (after the first 10 weeks, 35.3% vs. 15.0%, p = 0.25; after the second 10 weeks, 45.0% vs. 23.5%, p = 0.30). Melatonin was well-tolerated.

CONCLUSIONS

Melatonin supplementation modestly improved most individual MetS components compared with placebo, and tended to increase the proportion of subjects free from MetS after treatment.

TRIAL REGISTRATION

NCT01038921, clinicaltrials.gov.

Association of the ADIPOQ T45G polymorphism with insulin resistance and blood glucose: a meta-analysis

Results of published studies on the association of the ADIPOQ T45G polymorphism with insulin resistance (IR) and blood glucose are conflicting. In this study, we performed a meta-analysis to further investigate such an association. Articles that evaluate the effect of the T45G polymorphism on IR and blood glucose were identified from the PubMed and Embase databases. Five indices, including fasting blood glucose (FBG), fasting insulin (F-insulin), 2-h blood glucose (2-h BG), 2-h insulin, and homeostasis model assessment insulin resistance index (HOMA-IR), were used to assess the effects of the T45G polymorphism on IR and blood glucose under a dominant model. 24 articles involving 7630 subjects were included. Twenty-two studies on FBG, 17 on F-insulin, 20 on HOMA-IR, and 3 on 2-h BG were included. No study on 2-h insulin was found. This meta-analysis revealed no significant association between the ADIPOQ T45G polymorphism and IR and blood glucose in the overall population and subgroup subjects under a dominant model, regardless of whether FBG, F-insulin, 2-h BG, or HOMA-IR was used. The present meta-analysis indicated that the mutation allele may have no function in IR development. The ADIPOQ T45G polymorphism is not associated with IR and blood glucose.

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

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