A polymorphism within the G6PC2 gene is associated with fasting plasma glucose levels

Genetic variation of fasting glucose and changes in glycemia in response to 2-year weight-loss diet intervention: the POUNDS LOST trial

OBJECTIVE

Weight-loss intervention through diet modification has been widely used to improve obesity-related hyperglycemia; however, little is known about whether genetic variation modifies the intervention effect. We examined the interaction between weight-loss diets and genetic variation of fasting glucose on changes in glycemic traits in a dietary intervention trial.

RESEARCH DESIGN AND METHODS

The Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial is a randomized, controlled 2-year weight-loss trial. We assessed overall genetic variation of fasting glucose by calculating a genetic risk score (GRS) based on 14 fasting glucose-associated single nucleotide polymorphisms, and examined the progression in fasting glucose and insulin levels, and insulin resistance and insulin sensitivity in 733 adults from this trial.

RESULTS

The GRS was associated with 6-month changes in fasting glucose (P<0.001), fasting insulin (P=0.042), homeostasis model assessment of insulin resistance (HOMA-IR, P=0.009) and insulin sensitivity (HOMA-S, P=0.043). We observed significant interaction between the GRS and dietary fat on 6-month changes in fasting glucose, HOMA-IR and HOMA-S after multivariable adjustment (P-interaction=0.007, 0.045 and 0.028, respectively). After further adjustment for weight loss, the interaction remained significant on change in fasting glucose (P=0.015). In the high-fat diet group, participants in the highest GRS tertile showed increased fasting glucose, whereas participants in the lowest tertile showed decreased fasting glucose (P-trend <0.001); in contrast, the genetic association was not significant in the low-fat diet group (P-trend=0.087).

CONCLUSIONS

Our data suggest that participants with a higher genetic risk may benefit more by eating a low-fat diet to improve glucose metabolism.

Sorcin Links Pancreatic β-Cell Lipotoxicity to ER Ca2+ Stores

Preserving β-cell function during the development of obesity and insulin resistance would limit the worldwide epidemic of type 2 diabetes. Endoplasmic reticulum (ER) calcium (Ca(2+)) depletion induced by saturated free fatty acids and cytokines causes β-cell ER stress and apoptosis, but the molecular mechanisms behind these phenomena are still poorly understood. Here, we demonstrate that palmitate-induced sorcin downregulation and subsequent increases in glucose-6-phosphatase catalytic subunit-2 (G6PC2) levels contribute to lipotoxicity. Sorcin is a calcium sensor protein involved in maintaining ER Ca(2+) by inhibiting ryanodine receptor activity and playing a role in terminating Ca(2+)-induced Ca(2+) release. G6PC2, a genome-wide association study gene associated with fasting blood glucose, is a negative regulator of glucose-stimulated insulin secretion (GSIS). High-fat feeding in mice and chronic exposure of human islets to palmitate decreases endogenous sorcin expression while levels of G6PC2 mRNA increase. Sorcin-null mice are glucose intolerant, with markedly impaired GSIS and increased expression of G6pc2 Under high-fat diet, mice overexpressing sorcin in the β-cell display improved glucose tolerance, fasting blood glucose, and GSIS, whereas G6PC2 levels are decreased and cytosolic and ER Ca(2+) are increased in transgenic islets. Sorcin may thus provide a target for intervention in type 2 diabetes.

General Framework for Meta-Analysis of Haplotype Association Tests

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta‐analysis has emerged as the method of choice to combine results from multiple studies. Many meta‐analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta‐analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two‐stage meta‐analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta‐analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype‐specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type‐I error rate, and our approach is more powerful than inverse variance weighted meta‐analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose‐associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.

Recent progress in genetic and epigenetic research on type 2 diabetes

Type 2 diabetes (T2DM) is a common complex metabolic disorder that has a strong genetic predisposition. During the past decade, progress in genetic association studies has enabled the identification of at least 75 independent genetic loci for T2DM, thus allowing a better understanding of the genetic architecture of T2DM. International collaborations and large-scale meta-analyses of genome-wide association studies have made these achievements possible. However, whether the identified common variants are causal is largely unknown. In addition, the detailed mechanism of how these genetic variants exert their effect on the pathogenesis of T2DM requires further investigation. Currently, there are ongoing large-scale sequencing studies to identify rare, functional variants for T2DM. Environmental factors also have a crucial role in the development of T2DM. These could modulate gene expression via epigenetic mechanisms, including DNA methylation, histone modification and microRNA regulation. There is evidence that epigenetic changes are important in the development of T2DM. Recent studies have identified several DNA methylation markers of T2DM from peripheral blood and pancreatic islets. In this review, we will briefly summarize the recent progress in the genetic and epigenetic research on T2DM and discuss how environmental factors, genetics and epigenetics can interact in the pathogenesis of T2DM.

Lack of Prox1 Downregulation Disrupts the Expansion and Maturation of Postnatal Murine β-Cells

Transcription factor expression fluctuates during β-cell ontogeny, and disruptions in this pattern can affect the development or function of those cells. Here we uncovered that murine endocrine pancreatic progenitors express high levels of the homeodomain transcription factor Prox1, whereas both immature and mature β-cells scarcely express this protein. We also investigated if sustained Prox1 expression is incompatible with β-cell development or maintenance using transgenic mouse approaches. We discovered that Prox1 upregulation in mature β-cells has no functional consequences; in contrast, Prox1 overexpression in immature β-cells promotes acute fasting hyperglycemia. Using a combination of immunostaining and quantitative and comparative gene expression analyses, we determined that Prox1 upregulation reduces proliferation, impairs maturation, and enables apoptosis in postnatal β-cells. Also, we uncovered substantial deficiency in β-cells that overexpress Prox1 of the key regulator of β-cell maturation MafA, several MafA downstream targets required for glucose-stimulated insulin secretion, and genes encoding important components of FGF signaling. Moreover, knocking down PROX1 in human EndoC-βH1 β-cells caused increased expression of many of these same gene products. These and other results in our study indicate that reducing the expression of Prox1 is beneficial for the expansion and maturation of postnatal β-cells.

Genetic and clinical variables identify predictors for chronic kidney disease in type 2 diabetes

Type 2 diabetes and chronic kidney disease (CKD) may share common risk factors. Here we used a 3-stage procedure to discover novel predictors of CKD by repeatedly applying a stepwise selection based on the Akaike information criterion to subsamples of a prospective complete-case cohort of 2755 patients. This cohort encompassed 25 clinical variables and 36 genetic variants associated with type 2 diabetes, obesity, or fasting plasma glucose. We compared the performance of the clinical, genetic, and clinico-genomic models and used net reclassification improvement to evaluate the impact of top selected genetic variants to the clinico-genomic model. Associations of selected genetic variants with CKD were validated in 2 independent cohorts followed by meta-analyses. Among the top 6 single-nucleotide polymorphisms selected from clinico-genomic data, three (rs478333 of G6PC2, rs7754840 and rs7756992 of CDKAL1) contributed toward the improvement of prediction performance. The variant rs478333 was associated with rapid decline (over 4% per year) in estimated glomerular filtration rate. In a meta-analysis of 2 replication cohorts, the variants rs478333 and rs7754840 showed significant associations with CKD after adjustment for conventional risk factors. Thus, this novel 3-stage approach to a clinico-genomic data set identified 3 novel genetic predictors of CKD in type 2 diabetes. This method can be applied to similar data sets containing clinical and genetic variables to select predictors for clinical outcomes.

NIH working group report-using genomic information to guide weight management: From universal to precision treatment

OBJECTIVE

Precision medicine utilizes genomic and other data to optimize and personalize treatment. Although more than 2,500 genetic tests are currently available, largely for extreme and/or rare phenotypes, the question remains whether this approach can be used for the treatment of common, complex conditions like obesity, inflammation, and insulin resistance, which underlie a host of metabolic diseases.

METHODS

This review, developed from a Trans-NIH Conference titled "Genes, Behaviors, and Response to Weight Loss Interventions," provides an overview of the state of genetic and genomic research in the area of weight change and identifies key areas for future research.

RESULTS

Although many loci have been identified that are associated with cross-sectional measures of obesity/body size, relatively little is known regarding the genes/loci that influence dynamic measures of weight change over time. Although successful short-term weight loss has been achieved using many different strategies, sustainable weight loss has proven elusive for many, and there are important gaps in our understanding of energy balance regulation.

CONCLUSIONS

Elucidating the molecular basis of variability in weight change has the potential to improve treatment outcomes and inform innovative approaches that can simultaneously take into account information from genomic and other sources in devising individualized treatment plans.

Type 2 diabetes-related variants influence the risk of developing multiple myeloma: results from the IMMEnSE consortium

Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case-control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1rs2237892T allele or the CDKN2A-2Brs2383208G/G, IGF1rs35767T/T and MADDrs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32-2.13) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76-0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10(-) (06)). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348 and NOTCH2rs10923931 variants (Pinteraction=0.001 and 0.0004, respectively). Men carrying the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (ORM=0.71 and ORM=0.66 vs ORW=1.22 and ORW=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.

Genetic variation in insulin-induced kinase signaling

Individual differences in sensitivity to insulin contribute to disease susceptibility including diabetes and metabolic syndrome. Cellular responses to insulin are well studied. However, which steps in these response pathways differ across individuals remains largely unknown. Such knowledge is needed to guide more precise therapeutic interventions. Here, we studied insulin response and found extensive individual variation in the activation of key signaling factors, including ERK whose induction differs by more than 20-fold among our subjects. This variation in kinase activity is propagated to differences in downstream gene expression response to insulin. By genetic analysis, we identified cis-acting DNA variants that influence signaling response, which in turn affects downstream changes in gene expression and cellular phenotypes, such as protein translation and cell proliferation. These findings show that polymorphic differences in signal transduction contribute to individual variation in insulin response, and suggest kinase modulators as promising therapeutics for diseases characterized by insulin resistance.

Novel stable isotope analyses demonstrate significant rates of glucose cycling in mouse pancreatic islets

A polymorphism located in the G6PC2 gene, which encodes an islet-specific glucose-6-phosphatase catalytic subunit, is the most important common determinant of variations in fasting blood glucose (FBG) levels in humans. Studies of G6pc2 knockout (KO) mice suggest that G6pc2 represents a negative regulator of basal glucose-stimulated insulin secretion (GSIS) that acts by hydrolyzing glucose-6-phosphate (G6P), thereby reducing glycolytic flux. However, this conclusion conflicts with the very low estimates for the rate of glucose cycling in pancreatic islets, as assessed using radioisotopes. We have reassessed the rate of glucose cycling in pancreatic islets using a novel stable isotope method. The data show much higher levels of glucose cycling than previously reported. In 5 mmol/L glucose, islets from C57BL/6J chow-fed mice cycled ∼16% of net glucose uptake. The cycling rate was further increased at 11 mmol/L glucose. Similar cycling rates were observed using islets from high fat-fed mice. Importantly, glucose cycling was abolished in G6pc2 KO mouse islets, confirming that G6pc2 opposes the action of the glucose sensor glucokinase by hydrolyzing G6P. The demonstration of high rates of glucose cycling in pancreatic islets explains why G6pc2 deletion enhances GSIS and why variants in G6PC2 affect FBG in humans.

Association of LRP5, TCF7L2, and GCG variants and type 2 diabetes mellitus as well as fasting plasma glucose and lipid metabolism indexes

Recent data puts WNT signaling pathway in a pivotal role in regulating pancreas development as well as islet function, insulin production and secretion. The key effectors in the WNT signaling pathway are low-density lipoprotein receptor-related protein 5 (LRP5), transcription factor 7-like 2 (TCF7L2), and downstream-regulated glucagon (GCG). Our previous studies suggest that the WNT signaling pathway plays a significant role in risk of type 2 diabetes mellitus (T2DM) in Chinese population. The main purpose of the present study was to investigate the associations of single nucleotide polymorphisms (SNPs) in LRP5, TCF7L2 and glucagon (GCG) and quantitative traits in a healthy population. We used tag SNP to screen candidate SNPs for LRP5 and GCG; for TCF7L2, used the confirmed SNP rs11196218. A total of 1842 patients with T2DM and 7777 healthy controls underwent genotyping for the SNPs. We found a significant association of rs3758644 in LRP5 and fasting plasma glucose (p=0.006), and rs11196218 in TCF7L2 and triglycerides level (p=0.004). Among the SNPs in LRP5, TCF7L2, and GCG analyzed, only rs3758644 of LRP5 and rs11196218 of TCF7L2 were significantly associated with fasting plasma glucose and triglycerides index, respectively, in a healthy population.

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.

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.

Individualized medicine from prewomb to tomb

That each of us is truly biologically unique, extending to even monozygotic, "identical" twins, is not fully appreciated. Now that it is possible to perform a comprehensive "omic" assessment of an individual, including one's DNA and RNA sequence and at least some characterization of one's proteome, metabolome, microbiome, autoantibodies, and epigenome, it has become abundantly clear that each of us has truly one-of-a-kind biological content. Well beyond the allure of the matchless fingerprint or snowflake concept, these singular, individual data and information set up a remarkable and unprecedented opportunity to improve medical treatment and develop preventive strategies to preserve health.

The MafA transcription factor becomes essential to islet β-cells soon after birth

The large Maf transcription factors, MafA and MafB, are expressed with distinct spatial-temporal patterns in rodent islet cells. Analysis of Mafa(-/-) and pancreas-specific Mafa(∆panc) deletion mutant mice demonstrated a primary role for MafA in adult β-cell activity, different from the embryonic importance of MafB. Our interests here were to precisely define when MafA became functionally significant to β-cells, to determine how this was affected by the brief period of postnatal MafB production, and to identify genes regulated by MafA during this period. We found that islet cell organization, β-cell mass, and β-cell function were influenced by 3 weeks of age in Mafa(Δpanc) mice and compromised earlier in Mafa(Δpanc);Mafb(+/-) mice. A combination of genome-wide microarray profiling, electron microscopy, and metabolic assays were used to reveal mechanisms of MafA control. For example, β-cell replication was produced by actions on cyclin D2 regulation, while effects on granule docking affected first-phase insulin secretion. Moreover, notable differences in the genes regulated by embryonic MafB and postnatal MafA gene expression were found. These results not only clearly define why MafA is an essential transcriptional regulator of islet β-cells, but also why cell maturation involves coordinated actions with MafB.

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.

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.

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.

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.

Human cardiovascular disease IBC chip-wide association with weight loss and weight regain in the look AHEAD trial

BACKGROUND/AIMS

The present study identified genetic predictors of weight change during behavioral weight loss treatment.

METHODS

Participants were 3,899 overweight/obese individuals with type 2 diabetes from Look AHEAD, a randomized controlled trial to determine the effects of intensive lifestyle intervention (ILI), including weight loss and physical activity, relative to diabetes support and education, on cardiovascular outcomes. Analyses focused on associations of single nucleotide polymorphisms (SNPs) on the Illumina CARe iSelect (IBC) chip (minor allele frequency >5%; n = 31,959) with weight change at year 1 and year 4, and weight regain at year 4, among individuals who lost ≥ 3% at year 1.

RESULTS

Two novel regions of significant chip-wide association with year-1 weight loss in ILI were identified (p < 2.96E-06). ABCB11 rs484066 was associated with 1.16 kg higher weight per minor allele at year 1, whereas TNFRSF11A, or RANK, rs17069904 was associated with 1.70 kg lower weight per allele at year 1.

CONCLUSIONS

This study, the largest to date on genetic predictors of weight loss and regain, indicates that SNPs within ABCB11, related to bile salt transfer, and TNFRSF11A, implicated in adipose tissue physiology, predict the magnitude of weight loss during behavioral intervention. These results provide new insights into potential biological mechanisms and may ultimately inform weight loss treatment.

Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study

BACKGROUND

Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.

METHODS

As part of the 'Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.

RESULTS

Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 × 10-15), versus 3/9 in AA (p= 0.03 to 6 × 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.

CONCLUSIONS

Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.

Metabolic signaling in fuel-induced insulin secretion

The pancreatic islet β cell senses circulating levels of calorigenic nutrients to secrete insulin according to the needs of the organism. Altered insulin secretion is linked to various disorders such as diabetes, hypoglycemic states, and cardiometabolic diseases. Fuel stimuli, including glucose, free fatty acids, and amino acids, promote insulin granule exocytosis primarily via their metabolism in β cells and the production of key signaling metabolites. This paper reviews our current knowledge of the pathways involved in both positive and negative metabolic signaling for insulin secretion and assesses the role of established and candidate metabolic coupling factors, keeping recent developments in focus.

Large scale meta-analyses of fasting plasma glucose raising variants in GCK, GCKR, MTNR1B and G6PC2 and their impacts on type 2 diabetes mellitus risk

BACKGROUND

The evidence that the variants GCK rs1799884, GCKR rs780094, MTNR1B rs10830963 and G6PC2 rs560887, which are related to fasting plasma glucose levels, increase the risk of type 2 diabetes mellitus (T2DM) is contradictory. We therefore performed a meta-analysis to derive a more precise estimation of the association between these polymorphisms and T2DM.

METHODS

All the publications examining the associations of these variants with risk of T2DM were retrieved from the MEDLINE and EMBASE databases. Using the data from the retrieved articles, we computed summary estimates of the associations of the four variants with T2DM risk. We also examined the studies for heterogeneity, as well as for bias of the publications.

RESULTS

A total of 113,025 T2DM patients and 199,997 controls from 38 articles were included in the meta-analysis. Overall, the pooled results indicated that GCK (rs1799884), GCKR (rs780094) and MTNR1B (rs10830963) were significantly associated with T2DM susceptibility (OR, 1.04; 95%CI, 1.01-1.08; OR, 1.08; 95%CI, 1.05-1.12 and OR, 1.05; 95%CI, 1.02-1.08, respectively). After stratification by ethnicity, significant associations for the GCK, MTNR1B and G6PC2 variants were detected only in Caucasians (OR, 1.09; 95%CI, 1.02-1.16; OR, 1.10; 95%CI, 1.08-1.13 and OR, 0.97; 95%CI, 0.95-0.99, respectively), but not in Asians (OR, 1.02, 95% CI 0.98-1.05; OR, 1.01; 95%CI, 0.98-1.04 and OR, 1.12; 95%CI, 0.91-1.32, respectively).

CONCLUSIONS

Our meta-analyses demonstrated that GCKR rs780094 variant confers high cross-ethnicity risk for the development of T2DM, while significant associations between GCK, MTNR1B and G6PC2 variants and T2DM risk are limited to Caucasians.

Mapping I-A(g7) restricted epitopes in murine G6PC2

G6PC2, also known as islet-specific glucose 6-phosphatase catalytic subunit-related protein (IGRP), is a major target of autoreactive CD8(+) T cells in both diabetic human subjects and the non-obese diabetic (NOD) mouse. However, in contrast to the abundant literature regarding the CD8(+) response to this antigen, much less is known about the potential involvement of IGRP-reactive CD4(+) T cells in diabetogenesis. The single previous study that examined this question in NOD mice was based upon a candidate epitope approach and identified three I-A(g7)-restricted epitopes that each elicited spontaneous responses in these animals. However, given the known inaccuracies of MHC class II epitope prediction algorithms, we hypothesized that additional specificities might also be targeted. To address this issue, we immunized NOD mice with membranes from insect cells overexpressing full-length recombinant mouse IGRP and measured recall responses of purified CD4(+) T cells using a library of overlapping peptides encompassing the entire 355-aa primary sequence. Nine peptides representing 8 epitopes gave recall responses, only 1 of which corresponded to any of the previously reported sequences. In each case proliferation was blocked by a monoclonal antibody to I-A(g7), but not the appropriate isotype control. Consistent with a role in diabetogenesis, proliferative responses to 4 of the 9 peptides (3 epitopes) were also detected in CD4(+) T cells purified from the pancreatic draining lymph nodes of pre-diabetic female animals, but not from peripheral lymph nodes or spleens of the same animals. Intriguingly, one of the newly identified spontaneously reactive epitopes (P8 [IGRP(55-72)]) is highly conserved between mice and man, suggesting that it might also be a target of HLA-DQ8-restricted T cells in diabetic human subjects, an hypothesis that we are currently testing.

A SNP in G6PC2 predicts insulin secretion in type 1 diabetes

We investigated whether single nucleotide polymorphisms in genes related to glucose metabolism correlate with insulin secretion in type 1 diabetes patients. A cohort of 49 type 1 diabetes patients underwent serial mixed meal tolerance tests to assess insulin secretion. Patients were genotyped for SNPs related to glucose metabolism: CDKAL1 rs7754840, G6PC2 rs560887, HHEX rs1111875, KCNJ11 rs5215. Recently diagnosed patients (<100 days) homozygous for the G allele of G6PC2 had higher area under the curve C-peptide on mixed meal tolerance tests compared to non-homozygous patients (344.8 ± 203.2 vs. 167.9 ± 131.5, p = 0.04). Other SNPs did not correlate with insulin secretion in the new onset period. In a longitudinal survival analysis, homozygosity for the minor allele (A) in G6PC2 predicted more rapid loss of insulin secretion over time. A SNP in the beta cell gene G6PC2 may correlate with preserved insulin secretion in type 1 diabetes.

Multiple functional polymorphisms in the G6PC2 gene contribute to the association with higher fasting plasma glucose levels

AIMS/HYPOTHESIS

We previously identified the G6PC2 locus as a strong determinant of fasting plasma glucose (FPG) and showed that a common G6PC2 intronic single nucleotide polymorphism (SNP) (rs560887) and two common G6PC2 promoter SNPs (rs573225 and rs13431652) are highly associated with FPG. However, these promoter SNPs have complex effects on G6PC2 fusion gene expression, and our data suggested that only rs13431652 is a potentially causative SNP. Here we examine the effect of rs560887 on G6PC2 pre-mRNA splicing and the contribution of an additional common G6PC2 promoter SNP, rs2232316, to the association signal.

METHODS

Minigene analyses were used to characterise the effect of rs560887 on G6PC2 pre-mRNA splicing. Fusion gene and gel retardation analyses characterised the effect of rs2232316 on G6PC2 promoter activity and transcription factor binding. The genetic association of rs2232316 with FPG variation was assessed using regression adjusted for age, sex and BMI in 4,220 Europeans with normal FPG.

RESULTS

The rs560887-G allele was shown to enhance G6PC2 pre-mRNA splicing, whereas the rs2232316-A allele enhanced G6PC2 transcription by promoting Foxa2 binding. Genetic analyses provide evidence for association of the rs2232316-A allele with increased FPG (β = 0.04 mmol/l; p = 4.3 × 10(-3)) as part of the same signal as rs560887, rs573225 and rs13431652.

CONCLUSIONS/INTERPRETATION

As with rs13431652, the in situ functional data with rs560887 and rs2232316 are in accord with the putative function of G6PC2 in pancreatic islets, and suggest that all three are potentially causative SNPs that contribute to the association between G6PC2 and FPG.

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

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

Determinants of HbA1c in nondiabetic Dutch adults: genetic loci and clinical and lifestyle parameters, and their interactions in the Lifelines Cohort Study

OBJECTIVES

Glycated haemoglobin (HbA1c) is associated with cardiovascular disease risk in individuals without diabetes, and its use has been recommended for diagnosing diabetes. Therefore, it is important to gain further understanding of the determinants of HbA1c. The aim of this study was to investigate the effects of genetic loci and clinical and lifestyle parameters, and their interactions, on HbA1c in nondiabetic adults.

DESIGN

Population-based cohort study.

SETTING

Three northern provinces of the Netherlands.

SUBJECTS

A total of 2921 nondiabetic adults participating in the population-based LifeLines Cohort Study.

MEASUREMENTS

Body mass index (BMI), waist circumference, HbA1c, fasting plasma glucose (FPG) and erythrocyte indices were measured. Data on current smoking and alcohol consumption were collected through questionnaires. Genome-wide genotyping was performed, and 12 previously identified single-nucleotide polymorphisms (SNPs) were selected for replication and categorized as 'glycaemic' and 'nonglycaemic' SNPs according to their presumed mechanism(s) of action on HbA1c. Genetic risk scores (GRSs) were calculated as the sum of the weighted effect of HbA1c-increasing alleles.

RESULTS

Age, gender, BMI, FPG, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, current smoking and alcohol consumption were independent predictors of HbA1c, together explaining 26.2% of the variance in HbA1c, with FPG contributing 10.9%. We replicated three of the previously identified SNPs and the GRSs were also found to be independently associated with HbA1c. We found a smaller effect of the 'nonglycaemic GRS' in females compared with males and an attenuation of the effect of the GRS of all 12 SNPs with increasing BMI.

CONCLUSIONS

Our results suggest that a substantial portion of HbA1c is determined by nonglycaemic factors. This should be taken into account when considering the use of HbA1c as a diagnostic test for diabetes.

The utility of copy number variation (CNV) in studies of hypertension-related left ventricular hypertrophy (LVH): rationale, potential and challenges

The ultimate goal of human genetics is to understand the role of genome variation in elucidating human traits and diseases. Besides single nucleotide polymorphism (SNP), copy number variation (CNV), defined as gains or losses of a DNA segment larger than 1 kb, has recently emerged as an important tool in understanding heritable source of human genomic differences. It has been shown to contribute to genetic susceptibility of various common and complex diseases. Despite a handful of publications, its role in cardiovascular diseases remains largely unknown. Here, we deliberate on the currently available technologies for CNV detection. The possible utility and the potential roles of CNV in exploring the mechanisms of cardiac remodeling in hypertension will also be addressed. Finally, we discuss the challenges for investigations of CNV in cardiovascular diseases and its possible implications in diagnosis of hypertension-related left ventricular hypertrophy (LVH).

Association between the melatonin receptor 1B gene polymorphism on the risk of type 2 diabetes, impaired glucose regulation: a meta-analysis

Background

Melatonin receptor 1B (MTNR1B) belongs to the seven-transmembrane G protein-coupled receptor superfamily involved in insulin secretion, which has attracted considerable attention as a candidate gene for type 2 diabetes (T2D) since it was first identified as a loci associated with fasting plasma glucose level through genome wide association approach. The relationship between MTNR1B and T2D has been reported in various ethnic groups. The aim of this study was to consolidate and summarize published data on the potential of MTNR1B polymorphisms in T2D risk prediction.

Methods

PubMed, EMBASE, ISI web of science and the CNKI databases were systematically searched to identify relevant studies. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Heterogeneity and publication bias were also tested.

Results

A total of 23 studies involving 172,963 subjects for two common polymorphisms (rs10830963, rs1387153) on MTNR1B were included. An overall random effects per-allele OR of 1.05 (95% CI: 1.02–1.08; P<10⁻⁴) and 1.04 (95% CI: 0.98–1.10; P = 0.20) were found for the two variants respectively. Similar results were also observed using dominant or recessive genetic model. There was strong evidence of heterogeneity, which largely disappeared after stratification by ethnicity. Significant results were found in Caucasians when stratified by ethnicity; while no significant associations were observed in East Asians and South Asians. Besides, we found that the rs10830963 polymorphism is a risk factor associated with increased impaired glucose regulation susceptibility.

Conclusions

This meta-analysis demonstrated that the rs10830963 polymorphism is a risk factor for developing impaired glucose regulation and T2D.

A unified method for detecting secondary trait associations with rare variants: application to sequence data

Next-generation sequencing has made possible the detection of rare variant (RV) associations with quantitative traits (QT). Due to high sequencing cost, many studies can only sequence a modest number of selected samples with extreme QT. Therefore association testing in individual studies can be underpowered. Besides the primary trait, many clinically important secondary traits are often measured. It is highly beneficial if multiple studies can be jointly analyzed for detecting associations with commonly measured traits. However, analyzing secondary traits in selected samples can be biased if sample ascertainment is not properly modeled. Some methods exist for analyzing secondary traits in selected samples, where some burden tests can be implemented. However p-values can only be evaluated analytically via asymptotic approximations, which may not be accurate. Additionally, potentially more powerful sequence kernel association tests, variable selection-based methods, and burden tests that require permutations cannot be incorporated. To overcome these limitations, we developed a unified method for analyzing secondary trait associations with RVs (STAR) in selected samples, incorporating all RV tests. Statistical significance can be evaluated either through permutations or analytically. STAR makes it possible to apply more powerful RV tests to analyze secondary trait associations. It also enables jointly analyzing multiple cohorts ascertained under different study designs, which greatly boosts power. The performance of STAR and commonly used RV association tests were comprehensively evaluated using simulation studies. STAR was also implemented to analyze a dataset from the SardiNIA project where samples with extreme low-density lipoprotein levels were sequenced. A significant association between LDLR and systolic blood pressure was identified, which is supported by pharmacogenetic studies. In summary, for sequencing studies, STAR is an important tool for detecting secondary-trait RV associations.

Next-generation sequencing has greatly expanded our ability to identify missing heritability due to rare variants. In order to increase the power to detect associations, one desirable study design is to combine samples from multiple cohorts for mapping commonly measured traits. However, many current studies sequence selected samples (e.g. samples with extreme QT), which can bias the analysis of secondary traits, unless the sampling ascertainment mechanisms are properly adjusted. We developed a unified method for detecting secondary trait associations with rare variants (STAR) in selected and random samples, which can flexibly incorporate all rare variant association tests and allow joint analysis of multiple cohorts ascertained under different study designs. We demonstrate via simulations that STAR greatly boosts the power for detecting secondary trait associations. As an application of STAR, a dataset from the SardiNIA project was analyzed, where DNA samples from well-phenotyped individuals with extreme low-density lipoprotein levels were sequenced. LDLR was identified to be significantly associated with systolic blood pressure, which is supported by a previous pharmacogenetics study. In conclusion, STAR is an important tool for sequence-based association studies.

HbA1c-based diabetes diagnosis among patients with glucokinase mutation (GCK-MODY) is affected by a genetic variant of glucose-6-phosphatase (G6PC2)

AIMS

Genetic variation at the rs560887 locus of the glucose-6-phosphatase, catalytic 2 gene (G6PC2) is known to affect regulation of fasting glycaemia. We determined the rs560887 genotype of patients with monogenic diabetes and glucokinase gene mutations (GCK-MODY) and correlated the genotypes with HbA(1c) levels.

METHODS

Patients from families with GCK-MODY were recruited from two large cohorts from Poland (n = 128) and the Czech Republic (n = 154). Genotypes at the rs560887 polymorphic site in G6PC2 were examined using real-time quantitative polymerase chain reaction. The effect of rs560887 genotype on age at diagnosis of GCK-MODY and initial HbA(1c) levels were evaluated separately within both cohorts. Following that, a meta-analysis of rs560887 genotype-HbA(1c) associations of both Polish and Czech cohorts was performed to confirm homogeneity of findings and validate cohort-specific results.

RESULTS

GG homozygosity at rs560887 was associated with marginally elevated HbA(1c) levels (P = 0.07 in both cohorts). The effects observed in both groups were very homogeneous (Q = 0.18; P = 0.68). Meta-analysis showed that GG homozygosity at rs560887 was associated with mean HbA(1c) levels higher by 2.4 mmol/mol (0.24%), 95% CI 0.5-4.4 mmol/mol (0.05-0.44%) than in individuals with other genotypes. Additionally, meta-analysis of both cohorts showed that GG homozygous individuals had higher odds of reaching the 48 mmol/mol (6.5%) diagnostic threshold of diabetes; (odds ratio 1.90; 95% CI 1.07-3.36; P = 0.03). No such effects were observed for age at diagnosis of diabetes.

CONCLUSIONS

Variation at the rs560887 locus of G6PC2 is associated with worse glycated haemoglobin levels in individuals with GCK mutations; GG homozygotes are more likely to meet diagnostic criteria for diabetes based on HbA(1c) level.

A low frequency variant within the GWAS locus of MTNR1B affects fasting glucose concentrations: genetic risk is modulated by obesity

Two common variants (rs1387153, rs10830963) in MTNR1B have been reported to have independent effects on fasting blood glucose (FBG) levels with increased risk to type 2 diabetes (T2D) in recent genome-wide association studies (GWAS). In this investigation, we report the association of these two variants, and an additional variant (rs1374645) within the GWAS locus of MTNR1B with FBG, 2h glucose, insulin resistance (HOMA IR), β-cell function (HOMA B), and T2D in our sample of Asian Sikhs from India. Our cohort comprised 2222 subjects [1201 T2D, 1021 controls]. None of these SNPs was associated with T2D in this cohort. Our data also could not confirm association of rs1387153 and rs10830963 with FBG phenotype. However, upon stratifying data according to body mass index (BMI) (low ≤ 25 kg/m(2) and high > 25 kg/m(2)) in normoglycemic subjects (n = 1021), the rs1374645 revealed a strong association with low FBG levels in low BMI group (β = -0.073, p = 0.002, Bonferroni p = 0.01) compared to the high BMI group (β = 0.015, p = 0.50). We also detected a strong evidence of interaction between rs1374645 and BMI with respect to FBG levels (p = 0.002). Our data provide new information about the significant impact of another MTNR1B variant on FBG levels that appears to be modulated by BMI. Future confirmation on independent datasets and functional studies will be required to define the role of this variant in fasting glucose variation.

Maternal and offspring fasting glucose and type 2 diabetes-associated genetic variants and cognitive function at age 8: a Mendelian randomization study in the Avon Longitudinal Study of Parents and Children

Background

In observational epidemiological studies type 2 diabetes (T2D) and both low and high plasma concentrations of fasting glucose have been found to be associated with lower cognitive performance. These associations could be explained by confounding.

Methods

In this study we looked at the association between genetic variants, known to be robustly associated with fasting glucose and T2D risk, in the mother and her offspring to determine whether there is likely to be a causal link between early life exposure to glucose and child’s intelligence quotient (IQ) scores in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. We generated a fasting glucose (FGGRS) and a T2D (T2DGRS) genetic risk score and used them in a Mendelian randomization approach.

Results

We found a strong correlation between the FGGRS and fasting glucose plasma measurements that were available for a subset of children, but no association of either the maternal or the offspring FGGRS with child’s IQ was observed. In contrast, the maternal T2DGRS was positively associated with offspring IQ.

Conclusions

Maternal and offspring genetic variants which are associated with glucose levels are not associated with offspring IQ, suggesting that there is unlikely to be a causal link between glucose exposure in utero and IQ in childhood. Further exploration in even larger cohorts is required to exclude the possibility that our null findings were due to a lack of statistical power.

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

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

Genetic advances of type 2 diabetes in Chinese populations

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

Common genetic variants and central adiposity among Asian-Indians

Recent studies have identified common genetic variants that are unequivocally associated with central adiposity, BMI, and/or fasting plasma glucose among individuals of European descent. Our objective was to evaluate these associations in a population of Asian-Indians. We examined 16 single-nucleotide polymorphisms (SNPs) from loci previously linked to waist circumference, BMI, or fasting glucose in 1,129 Asian-Indians from New Delhi and Trivandrum. Trained medical staff measured waist circumference, height, and weight. Fasting plasma glucose was measured from collected blood specimens. Genotype-phenotype associations were evaluated using linear regression, with adjustments for age, gender, religion, and study region. For gene-environment interaction tests, total physical activity (PA) during the past 7 days was assessed by the International Physical Activity Questionnaire (IPAQ). The T allele at the FTO rs3751812 locus was associated with increased waist circumference (per allele effect of +1.58 cm, P(trend) = 0.0015) after Bonferroni adjustment for multiple testing (P(adj) = 0.04). We also found a nominally statistically significant FTO-PA interaction (P(interaction) = 0.008). Among participants with <81 metabolic equivalent (MET)-h/wk of PA, the rs3751812 variant was associated with increased waist size (+2.68 cm; 95% confidence interval (CI) = 1.24, 4.12), but not among those with 212+ MET-h/wk (-1.79 cm; 95% CI = -4.17, 0.58). No other variant had statistically significant associations, although statistical power was modest. In conclusion, we confirmed that an FTO variant associated with central adiposity in European populations is associated with central adiposity among Asian-Indians and corroborated prior reports indicating that high PA attenuates FTO-related genetic susceptibility to adiposity.

Novel Loci for metabolic networks and multi-tissue expression studies reveal genes for atherosclerosis

Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.

Fasting glucose GWAS candidate region analysis across ethnic groups in the Multiethnic Study of Atherosclerosis (MESA)

Genetic variants associated with fasting glucose in European ancestry populations are increasingly well understood. However, the nature of the associations between these single nucleotide polymorphisms (SNPs) and fasting glucose in other racial and ethnic groups is unclear. We sought to examine regions previously identified to be associated with fasting glucose in Caucasian genome-wide association studies (GWAS) across multiple ethnicities in the Multiethnic Study of Atherosclerosis (MESA). Nondiabetic MESA participants with fasting glucose measured at the baseline exam and with GWAS genotyping were included; 2,349 Caucasians, 664 individuals of Chinese descent, 1,366 African Americans, and 1,171 Hispanics. Genotype data were generated from the Affymetrix 6.0 array and imputation in IMPUTE. Fasting glucose was regressed on SNP dosage data in each ethnic group adjusting for age, gender, MESA study center, and ethnic-specific principal components. SNPs from the three gene regions with the strongest associations to fasting glucose in previous Caucasian GWAS (MTNR1B / GCK / G6PC2) were examined in depth. There was limited power to replicate associations in other ethnic groups due to smaller allele frequencies and limited sample size; SNP associations may also have differed across ethnic groups due to differing linkage disequilibrium patterns with causal variants. rs10830963 in MTNR1B and rs4607517 in GCK demonstrated consistent magnitude and direction of association with fasting glucose across ethnic groups, although the associations were often not nominally significant. In conclusion, certain SNPs in MTNR1B and GCK demonstrate consistent effects across four racial and ethnic groups, narrowing the putative region for these causal variants.

Genetic determinants of glucose homeostasis

Type 2 diabetes is a complex metabolic disorder characterised by varying degrees of impairment in insulin secretion and resistance to the action of insulin. Considerable progress has been made recently in understanding the genetic determinants of diabetes. A logical next step is to describe how these variants relate to the underlying pathophysiological processes that lead to diabetes as this may provide insights into pathways to disease. These quantitative traits are, of course, of direct interest in themselves and a growing literature is now emerging on the genetic determinants of insulin secretion and insulin resistance. This review article focuses on describing the complex associations between type 2 diabetes risk variants and quantitative glycaemic traits and the relationship between variants initially discovered in association studies of these traits and risk of type 2 diabetes.

Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.

A genome-wide association study identifies rs2000999 as a strong genetic determinant of circulating haptoglobin levels

Haptoglobin is an acute phase inflammatory marker. Its main function is to bind hemoglobin released from erythrocytes to aid its elimination, and thereby haptoglobin prevents the generation of reactive oxygen species in the blood. Haptoglobin levels have been repeatedly associated with a variety of inflammation-linked infectious and non-infectious diseases, including malaria, tuberculosis, human immunodeficiency virus, hepatitis C, diabetes, carotid atherosclerosis, and acute myocardial infarction. However, a comprehensive genetic assessment of the inter-individual variability of circulating haptoglobin levels has not been conducted so far.

We used a genome-wide association study initially conducted in 631 French children followed by a replication in three additional European sample sets and we identified a common single nucleotide polymorphism (SNP), rs2000999 located in the Haptoglobin gene (HP) as a strong genetic predictor of circulating Haptoglobin levels (P_overall = 8.1×10⁻⁵⁹), explaining 45.4% of its genetic variability (11.8% of Hp global variance). The functional relevance of rs2000999 was further demonstrated by its specific association with HP mRNA levels (β = 0.23±0.08, P = 0.007). Finally, SNP rs2000999 was associated with decreased total and low-density lipoprotein cholesterol in 8,789 European children (P_{total cholesterol} = 0.002 and P_LDL = 0.0008).

Given the central position of haptoglobin in many inflammation-related metabolic pathways, the relevance of rs2000999 genotyping when evaluating haptoglobin concentration should be further investigated in order to improve its diagnostic/therapeutic and/or prevention impact.

Genome-wide association study identifies multiple loci influencing human serum metabolite levels

Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10(-10)) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.

Type 2 Diabetes Genetics: Beyond GWAS

The global epidemic of type 2 diabetes mellitus (T2D) is one of the most challenging problems of the 21(st) century leading cause of and the fifth death worldwide. Substantial evidence suggests that T2D is a multifactorial disease with a strong genetic component. Recent genome-wide association studies (GWAS) have successfully identified and replicated nearly 75 susceptibility loci associated with T2D and related metabolic traits, mostly in Europeans, and some in African, and South Asian populations. The GWAS serve as a starting point for future genetic and functional studies since the mechanisms of action by which these associated loci influence disease is still unclear and it is difficult to predict potential implication of these findings in clinical settings. Despite extensive replication, no study has unequivocally demonstrated their clinical role in the disease management beyond progression to T2D from impaired glucose tolerance. However, these studies are revealing new molecular pathways underlying diabetes etiology, gene-environment interactions, epigenetic modifications, and gene function. This review highlights evolving progress made in the rapidly moving field of T2D genetics that is starting to unravel the pathophysiology of a complex phenotype and has potential to show clinical relevance in the near future.

A flexible likelihood framework for detecting associations with secondary phenotypes in genetic studies using selected samples: application to sequence data

For most complex trait association studies using next-generation sequencing, in addition to the primary phenotype of interest, many clinically important secondary traits are also available, which can be analyzed to map susceptibility genes. Owing to high sequencing costs, most studies use selected samples, and the sampling mechanisms of these studies can be complicated. When the primary and secondary traits are correlated, analyses of secondary phenotypes can cause spurious associations in selected samples and existing methods are inadequate to adjust for them. To address this problem, a likelihood-based method, MULTI-TRAIT-ASSOCIATION (MTA) was developed. MTA is flexible and can be applied to any study with known sampling mechanisms. It also allows efficient inferences of genetic parameters. To investigate the power of MTA and different study designs, extensive simulations were performed under rigorous population genetic and phenotypic models. It is demonstrated that there are great benefits for analyzing secondary phenotypes in selected samples. In particular, using case-control samples and samples with extreme primary phenotypes can be more powerful than analyzing random samples of equivalent size. One major challenge for sequence-based association studies is that most data sets are not of sufficient size to be adequately powered. By applying MTA, data sets ascertained under distinct mechanisms or targeted at different primary traits can be jointly analyzed to map common phenotypes and greatly increase power. The combined analysis can be performed using freely available data sets from public repositories, for example, dbGaP. In conclusion, MTA will have an important role in dissecting the etiology of complex traits.