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

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis

PURPOSE

To investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association.

METHODS

Our study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c.

RESULTS

With this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10-13), HbA1c (rg = 0.182, p = 4.14 × 10-6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10-6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER.

CONCLUSION

Our research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

Biochemical and metabolic characterization of a G6PC2 inhibitor

Three glucose-6-phosphatase catalytic subunits, that hydrolyze glucose-6-phosphate (G6P) to glucose and inorganic phosphate, have been identified, designated G6PC1-3, but only G6PC1 and G6PC2 have been implicated in the regulation of fasting blood glucose (FBG). Elevated FBG has been associated with multiple adverse clinical outcomes, including increased risk for type 2 diabetes and various cancers. Therefore, G6PC1 and G6PC2 inhibitors that lower FBG may be of prophylactic value for the prevention of multiple conditions. The studies described here characterize a G6PC2 inhibitor, designated VU0945627, previously identified as Compound 3. We show that VU0945627 preferentially inhibits human G6PC2 versus human G6PC1 but activates human G6PC3. VU0945627 is a mixed G6PC2 inhibitor, increasing the Km but reducing the Vmax for G6P hydrolysis. PyRx virtual docking to an AlphaFold2-derived G6PC2 structural model suggests VU0945627 binds two sites in human G6PC2. Mutation of residues in these sites reduces the inhibitory effect of VU0945627. VU0945627 does not inhibit mouse G6PC2 despite its 84% sequence identity with human G6PC2. Mutagenesis studies suggest this lack of inhibition of mouse G6PC2 is due, in part, to a change in residue 318 from histidine in human G6PC2 to proline in mouse G6PC2. Surprisingly, VU0945627 still inhibited glucose cycling in the mouse islet-derived βTC-3 cell line. Studies using intact mouse liver microsomes and PyRx docking suggest that this observation can be explained by an ability of VU0945627 to also inhibit the G6P transporter SLC37A4. These data will inform future computational modeling studies designed to identify G6PC isoform-specific inhibitors.

Identification of structural motifs critical for human G6PC2 function informed by sequence analysis and an AlphaFold2-predicted model

G6PC2 encodes a glucose-6-phosphatase (G6Pase) catalytic subunit, primarily expressed in pancreatic islet β cells, which modulates the sensitivity of insulin secretion to glucose and thereby regulates fasting blood glucose (FBG). Mutational analyses were conducted to validate an AlphaFold2 (AF2)-predicted structure of human G6PC2 in conjunction with a novel method to solubilize and purify human G6PC2 from a heterologous expression system. These analyses show that residues forming a predicted intramolecular disulfide bond are essential for G6PC2 expression and that residues forming part of a type 2 phosphatidic acid phosphatase (PAP2) motif are critical for enzyme activity. Additional mutagenesis shows that residues forming a predicted substrate cavity modulate enzyme activity and substrate specificity and residues forming a putative cholesterol recognition amino acid consensus (CRAC) motif influence protein expression or enzyme activity. This CRAC motif begins at residue 219, the site of a common G6PC2 non-synonymous single-nucleotide polymorphism (SNP), rs492594 (Val219Leu), though the functional impact of this SNP is disputed. In microsomal membrane preparations, the L219 variant has greater activity than the V219 variant, but this difference disappears when G6PC2 is purified in detergent micelles. We hypothesize that this was due to a differential association of the two variants with cholesterol. This concept was supported by the observation that the addition of cholesteryl hemi-succinate to the purified enzymes decreased the Vmax of the V219 and L219 variants ∼8-fold and ∼3 fold, respectively. We anticipate that these observations should support the rational development of G6PC2 inhibitors designed to lower FBG.

Shared Genetics between Age at Menarche and Type 2 Diabetes Mellitus: Genome-Wide Genetic Correlation Study

Background: Age at menarche (AAM) has been associated with type 2 diabetes mellitus (T2DM). However, little is known about their shared heritability. Methods: Our data comes from the Taiwan Biobank. Genome-wide association studies (GWASs) were conducted to identify single-nucleotide polymorphisms (SNPs) related to AAM-, T2DM-, and T2DM-related phenotypes, such as body fat percentage (BFP), fasting blood glucose (FBG), and hemoglobin A1C (HbA1C). Further, the conditional false discovery rate (cFDR) method was applied to examine the shared genetic signals. Results: Conditioning on AAM, Quantile-quantile plots showed an earlier departure from the diagonal line among SNPs associated with BFP and FBG, indicating pleiotropic enrichments among AAM and these traits. Further, the cFDR analysis found 39 independent pleiotropic loci that may underlie the AAM-T2DM association. Among them, FN3KRP rs1046896 (cFDR = 6.84 × 10-49), CDKAL1 rs2206734 (cFDR = 6.48 × 10-10), B3GNTL1 rs58431774 (cFDR = 2.95 × 10-10), G6PC2 rs1402837 (cFDR = 1.82 × 10-8), and KCNQ1 rs60808706 (cFDR = 9.49 × 10-8) were highlighted for their significant genetic enrichment. The protein-protein interaction analysis revealed a significantly enriched network among novel discovered genes that were mostly found to be involved in the insulin and glucagon signaling pathways. Conclusions: Our study highlights potential pleiotropic effects across AAM and T2DM. This may shed light on identifying the genetic causes of T2DM.

An Enhancer Within Abcb11 Regulates G6pc2 in C57BL/6 Mouse Pancreatic Islets

G6PC2 is predominantly expressed in pancreatic islet β-cells where it encodes a glucose-6-phosphatase catalytic subunit that modulates the sensitivity of insulin secretion to glucose by opposing the action of glucokinase, thereby regulating fasting blood glucose (FBG). Prior studies have shown that the G6pc2 promoter alone is unable to confer sustained islet-specific gene expression in mice, suggesting the existence of distal enhancers that regulate G6pc2 expression. Using information from both mice and humans and knowledge that single nucleotide polymorphisms (SNPs) both within and near G6PC2 are associated with variations in FBG in humans, we identified several putative enhancers 3' of G6pc2. One region, herein referred to as enhancer I, resides in the 25th intron of Abcb11 and binds multiple islet-enriched transcription factors. CRISPR-mediated deletion of enhancer I in C57BL/6 mice had selective effects on the expression of genes near the G6pc2 locus. In isolated islets, G6pc2 and Spc25 expression were reduced ∼50%, and Gm13613 expression was abolished, whereas Cers6 and nostrin expression were unaffected. This partial reduction in G6pc2 expression enhanced islet insulin secretion at basal glucose concentrations but did not affect FBG or glucose tolerance in vivo, consistent with the absence of a phenotype in G6pc2 heterozygous C57BL/6 mice.

ARTICLE HIGHLIGHTS

Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 hours

Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycemia, beta cell glucotoxicity, and ultimately type 2 diabetes (T2D). In this study, we sought to explore the effects of hyperglycemia on human pancreatic islet (HPI) gene expression by exposing HPIs from two donors to low (2.8mM) and high (15.0mM) glucose concentrations over 24 hours, assaying the transcriptome at seven time points using single-cell RNA sequencing (scRNA-seq). We modeled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Across all cell types, we identified 1,528 genes associated with time, 1,185 genes associated with glucose exposure, and 845 genes associated with interaction effects between time and glucose. We clustered differentially expressed genes across cell types and found 347 modules of genes with similar expression patterns across time and glucose conditions, including two beta cell modules enriched in genes associated with T2D. Finally, by integrating genomic features from this study and genetic summary statistics for T2D and related traits, we nominate 363 candidate effector genes that may underlie genetic associations for T2D and related traits.

Treatment of the Neutropenia Associated with GSD1b and G6PC3 Deficiency with SGLT2 Inhibitors

Glycogen storage disease type Ib (GSD1b) is due to a defect in the glucose-6-phosphate transporter (G6PT) of the endoplasmic reticulum, which is encoded by the SLC37A4 gene. This transporter allows the glucose-6-phosphate that is made in the cytosol to cross the endoplasmic reticulum (ER) membrane and be hydrolyzed by glucose-6-phosphatase (G6PC1), a membrane enzyme whose catalytic site faces the lumen of the ER. Logically, G6PT deficiency causes the same metabolic symptoms (hepatorenal glycogenosis, lactic acidosis, hypoglycemia) as deficiency in G6PC1 (GSD1a). Unlike GSD1a, GSD1b is accompanied by low neutrophil counts and impaired neutrophil function, which is also observed, independently of any metabolic problem, in G6PC3 deficiency. Neutrophil dysfunction is, in both diseases, due to the accumulation of 1,5-anhydroglucitol-6-phosphate (1,5-AG6P), a potent inhibitor of hexokinases, which is slowly formed in the cells from 1,5-anhydroglucitol (1,5-AG), a glucose analog that is normally present in blood. Healthy neutrophils prevent the accumulation of 1,5-AG6P due to its hydrolysis by G6PC3 following transport into the ER by G6PT. An understanding of this mechanism has led to a treatment aimed at lowering the concentration of 1,5-AG in blood by treating patients with inhibitors of SGLT2, which inhibits renal glucose reabsorption. The enhanced urinary excretion of glucose inhibits the 1,5-AG transporter, SGLT5, causing a substantial decrease in the concentration of this polyol in blood, an increase in neutrophil counts and function and a remarkable improvement in neutropenia-associated clinical signs and symptoms.

Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose

The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal (h² = 11%; standard error: 1%). The genetic correlation between different fasting times is > 0.77, suggesting that the genetic control of glucose is largely constant across fasting durations. Accounting for heritability differences between fasting times leads to a ~16% improvement in the discovery of genetic variants associated with glucose. Newly detected variants improve the prediction of fasting glucose and type 2 diabetes in independent samples. Finally, we meta-analysed summary statistics from genome-wide association studies of random and fasting glucose (N = 518,615) and identified 156 independent SNPs explaining 3% of fasting glucose variance. Altogether, our study demonstrates the utility of random glucose measures to improve the discovery of genetic variants associated with glucose homeostasis, even in fasting conditions.

Association of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) Gene Polymorphisms with Type 2 Diabetes among Malay Ethnics

Background  Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder, and the underlying causes remain unknown and have not been fully elucidated. Several candidate genes have been associated with T2DM in various populations with conflicting results. The variations found in glucokinase ( GCK ), glucokinase regulatory protein ( GCKR ), and glucose-6-phosphatase 2 ( G6PC2 ) genes were not well studied, particularly among Asians. Aims  The main objective of this study was to determine the candidate genetic polymorphisms of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) genes in T2DM among Malay ethnics. Methods  In this candidate gene association study, a total of 180 T2DM subjects and 180 control subjects were recruited to determine the genotypes using polymerase chain reaction-restriction fragment length polymorphism and Taqman probe assay methods. Genotype and allele frequencies in case and control samples were compared using the chi-squared test to determine a significant difference. Results  The body mass index, fasting blood glucose, hemoglobin A1c, systolic and diastolic blood pressure, and total cholesterol were significantly different ( p  < 0.05) between T2DM and control subjects. The genotypic and allelic frequencies of GCK (rs1799884), GCKR (rs780094), and G6PC2 (rs560887) gene polymorphisms were significantly different between T2DM and controls ( p  < 0.05). Conclusion  Hence, rs1799884 of GCK gene and rs780094 of GCKR gene and rs560887 of the G6PC2 gene are possible genetic biomarkers in T2DM development among Malay ethnics in Malaysia.

Common protein-coding variants influence the racing phenotype in galloping racehorse breeds

Selection for system-wide morphological, physiological, and metabolic adaptations has led to extreme athletic phenotypes among geographically diverse horse breeds. Here, we identify genes contributing to exercise adaptation in racehorses by applying genomics approaches for racing performance, an end-point athletic phenotype. Using an integrative genomics strategy to first combine population genomics results with skeletal muscle exercise and training transcriptomic data, followed by whole-genome resequencing of Asian horses, we identify protein-coding variants in genes of interest in galloping racehorse breeds (Arabian, Mongolian and Thoroughbred). A core set of genes, G6PC2, HDAC9, KTN1, MYLK2, NTM, SLC16A1 and SYNDIG1, with central roles in muscle, metabolism, and neurobiology, are key drivers of the racing phenotype. Although racing potential is a multifactorial trait, the genomic architecture shaping the common athletic phenotype in horse populations bred for racing provides evidence for the influence of protein-coding variants in fundamental exercise-relevant genes. Variation in these genes may therefore be exploited for genetic improvement of horse populations towards specific types of racing.

Additive genetic effect of GCKR, G6PC2, and SLC30A8 variants on fasting glucose levels and risk of type 2 diabetes

Impaired glucose tolerance is a major risk factor for type 2 diabetes (T2D) and several cardiometabolic disorders. To identify genetic loci underlying fasting glucose levels, we conducted an analysis of 9,232 individuals of European ancestry who at enrollment were either nondiabetic or had untreated type 2 diabetes. Multivariable linear mixed models were used to test for associations between fasting glucose and 7.9 million SNPs, with adjustment for age, body mass index (BMI), sex, significant principal components of the genotypes, and cryptic relatedness. Three previously discovered loci were genome-wide significant, with the lead SNPs being rs1260326, a missense variant in GCKR (p = 1.06×10⁻⁸); rs560887, an intronic variant in G6PC2 (p = 3.39×10⁻¹¹); and rs13266634, a missense variant in SLC30A8 (p = 4.28×10⁻¹⁰). Fine mapping, genome-wide conditional analysis, and functional annotation indicated that the three loci were independently associated with fasting glucose. Each copy of an alternate allele at any of these three SNPs was associated with a reduction of 0.012 mmol/L in fasting glucose levels (p = 8.0×10⁻²⁸), and this association was replicated in trans-ethnic analysis of 14,303 individuals (p = 2.2×10⁻¹⁶). The three SNPs were jointly associated with significantly reduced T2D risk, with an odds ratio (95% CI) of 0.93 (0.88, 0.98) per protective allele. Our findings implicate additive effects across pathophysiological pathways involved in type 2 diabetes, including glycolysis, gluconeogenesis, and insulin secretion. Since none of the individuals homozygous for the alternate alleles at all three loci has T2D, it might be possible to use a genetic predictor of fasting glucose levels to identify individuals at low vs. high risk of developing type 2 diabetes.

Type 2 Diabetes-Related Variants Influence the Risk of Developing Prostate Cancer: A Population-Based Case-Control Study and Meta-Analysis

In this study, we have evaluated whether 57 genome-wide association studies (GWAS)-identified common variants for type 2 diabetes (T2D) influence the risk of developing prostate cancer (PCa) in a population of 304 Caucasian PCa patients and 686 controls. The association of selected single nucleotide polymorphisms (SNPs) with the risk of PCa was validated through meta-analysis of our data with those from the UKBiobank and FinnGen cohorts, but also previously published genetic studies. We also evaluated whether T2D SNPs associated with PCa risk could influence host immune responses by analysing their correlation with absolute numbers of 91 blood-derived cell populations and circulating levels of 103 immunological proteins and 7 steroid hormones. We also investigated the correlation of the most interesting SNPs with cytokine levels after in vitro stimulation of whole blood, peripheral mononuclear cells (PBMCs), and monocyte-derived macrophages with LPS, PHA, Pam3Cys, and Staphylococcus Aureus. The meta-analysis of our data with those from six large cohorts confirmed that each copy of the FTO_rs9939609A, HNF1B_rs7501939T, HNF1B_rs757210T, HNF1B_rs4430796G, and JAZF1_rs10486567A alleles significantly decreased risk of developing PCa (p = 3.70 × 10^-5, p = 9.39 × 10^-54, p = 5.04 × 10^-54, p = 1.19 × 10^-71, and p = 1.66 × 10^-18, respectively). Although it was not statistically significant after correction for multiple testing, we also found that the NOTCH2_rs10923931T and RBMS1_rs7593730 SNPs associated with the risk of developing PCa (p = 8.49 × 10^-4 and 0.004). Interestingly, we found that the protective effect attributed to the HFN1B locus could be mediated by the SULT1A1 protein (p = 0.00030), an arylsulfotransferase that catalyzes the sulfate conjugation of many hormones, neurotransmitters, drugs, and xenobiotic compounds. In addition to these results, eQTL analysis revealed that the HNF1B_rs7501939, HNF1B_rs757210, HNF1B_rs4430796, NOTCH2_rs10923931, and RBMS1_rs7593730 SNPs influence the risk of PCa through the modulation of mRNA levels of their respective genes in whole blood and/or liver. These results confirm that functional TD2-related variants influence the risk of developing PCa, but also highlight the need of additional experiments to validate our functional results in a tumoral tissue context.

Mutations in G6PC2 gene with increased risk for development of type 2 diabetes: Understanding via computational approach

An increase in the fast blood glucose (FBG) levels has been linked to an increased risk of developing a chronic condition, type 2 diabetes (T2D). The mutation in the G6PC2 gene was identified to have a lead role in the modulation of FBG levels. The abnormal regulation of this enzyme influences glucose-stimulated insulin secretion (GSIS), which controls the insulin levels corresponding to the system's glucose level. This study focuses on the mutations at the G6PC2 gene, which cause the variation from normal expression levels and increase the risk of T2D. We examined the non-synonymous single nucleotide polymorphisms (nsSNPs) present in the G6PC2 and subjected them to pathogenicity, stability, residue conservation, and membrane simulation. The individual representation of surrounding amino acids in the mutant (I63T) model showed the loss of hydrophobic interactions compared to the native G6PC2. In addition, the trajectory results from the membrane simulation exhibited reduced stability, and the least compactness was identified for the I63T mutant model. Our study shed light on the structural and conformational changes at the transmembrane region due to the I63T mutation in G6PC2. Additionally, the Gibbs free energy landscape analysis against the two principal components showed structural differences and decreased the conformational stability of the I63T mutant model compared to the native. Like those presented in this study, dynamical simulations may indeed be crucial to comprehending the structural insights of G6PC2 mutations in cardiovascular-associated mortality and T2D.

Glucose-6-phosphatase catalytic subunit 2 negatively regulates glucose oxidation and insulin secretion in pancreatic β-cells

Elevated fasting blood glucose (FBG) is associated with increased risks of developing type 2 diabetes (T2D) and cardiovascular-associated mortality. G6PC2 is predominantly expressed in islets, encodes a glucose-6-phosphatase catalytic subunit that converts glucose-6-phosphate (G6P) to glucose, and has been linked with variations in FBG in genome-wide association studies. Deletion of G6pc2 in mice has been shown to lower FBG without affecting fasting plasma insulin levels in vivo. At 5 mM glucose, pancreatic islets from G6pc2 knockout (KO) mice exhibit no glucose cycling, increased glycolytic flux, and enhanced glucose-stimulated insulin secretion (GSIS). However, the broader effects of G6pc2 KO on β-cell metabolism and redox regulation are unknown. Here we used CRISPR/Cas9 gene editing and metabolic flux analysis in βTC3 cells, a murine pancreatic β-cell line, to examine the role of G6pc2 in regulating glycolytic and mitochondrial fluxes. We found that deletion of G6pc2 led to ∼60% increases in glycolytic and citric acid cycle (CAC) fluxes at both 5 and 11 mM glucose concentrations. Furthermore, intracellular insulin content and GSIS were enhanced by approximately two-fold, along with increased cytosolic redox potential and reductive carboxylation flux. Normalization of fluxes relative to net glucose uptake revealed upregulation in two NADPH-producing pathways in the CAC. These results demonstrate that G6pc2 regulates GSIS by modulating not only glycolysis but also, independently, citric acid cycle activity in β-cells. Overall, our findings implicate G6PC2 as a potential therapeutic target for enhancing insulin secretion and lowering FBG, which could benefit individuals with prediabetes, T2D, and obesity.

Nonsynonymous single-nucleotide polymorphisms in the G6PC2 gene affect protein expression, enzyme activity, and fasting blood glucose

G6PC2 encodes a glucose-6-phosphatase (G6Pase) catalytic subunit that modulates the sensitivity of insulin secretion to glucose and thereby regulates fasting blood glucose (FBG). A common single-nucleotide polymorphism (SNP) in G6PC2, rs560887 is an important determinant of human FBG variability. This SNP has a subtle effect on G6PC2 RNA splicing, which raises the question as to whether nonsynonymous SNPs with a major impact on G6PC2 stability or enzyme activity might have a broader disease/metabolic impact. Previous attempts to characterize such SNPs were limited by the very low inherent G6Pase activity and expression of G6PC2 protein in islet-derived cell lines. In this study, we describe the use of a plasmid vector that confers high G6PC2 protein expression in islet cells, allowing for a functional analysis of 22 nonsynonymous G6PC2 SNPs, 19 of which alter amino acids that are conserved in mouse G6PC2 and the human and mouse variants of the related G6PC1 isoform. We show that 16 of these SNPs markedly impair G6PC2 protein expression (>50% decrease). These SNPs have variable effects on the stability of human and mouse G6PC1, despite the high sequence homology between these isoforms. Four of the remaining six SNPs impaired G6PC2 enzyme activity. Electronic health record-derived phenotype analyses showed an association between high-impact SNPs and FBG, but not other diseases/metabolites. While homozygous G6pc2 deletion in mice increases the risk of hypoglycemia, these human data reveal no evidence that the beneficial use of partial G6PC2 inhibitors to lower FBG would be associated with unintended negative consequences.

Haplotypes of the genes (GCK and G6PC2) underlying the glucose/glucose-6-phosphate cycle are associated with pancreatic beta cell glucose sensitivity in patients with newly diagnosed type 2 diabetes from the VNDS study (VNDS 11)

BACKGROUND

Elevated fasting plasma glucose has been associated with increased risk for development of type 2 diabetes (T2D). The balance between glucokinase (GCK) and glucose-6-phosphate catalytic subunit 2 (G6PC2) activity are involved in glucose homeostasis through glycolytic flux, and subsequent insulin secretion.

AIM

In this study, we evaluated the association between the genetic variability of G6PC2 and GCK genes and T2D-related quantitative traits.

METHODS

In 794 drug-naïve, GADA-negative, newly diagnosed T2D patients (VNDS; NTC01526720) we performed: genotyping of 6 independent tag-SNPs within GCK gene and 5 tag-SNPs within G6PC2 gene; euglycaemic insulin clamp to assess insulin sensitivity; OGTT to estimate beta-cell function (derivative and proportional control; DC, PC) by mathematical modeling. Genetic association analysis has been conducted using Plink software.

RESULTS

Two SNPs within GCK gene (rs882019 and rs1303722) were associated to DC in opposite way (both p < 0.004). Two G6PC2 variants (rs13387347 and rs560887) were associated to both parameters of insulin secretion (DC and PC) and to fasting C-peptide levels (all p < 0.038). Moreover, subjects carrying the A allele of rs560887 showed higher values of 2h-plasma glucose (2hPG) (p = 0.033). Haplotype analysis revealed that GCK (AACAAA) haplotype was associated to decreased fasting C-peptide levels, whereas, the most frequent haplotype of G6PC2 (GGAAG) was associated with higher fasting C-peptide levels (p = 0.001), higher PC (β = 6.87, p = 0.022) and the lower 2hPG (p = 0.012).

CONCLUSION

Our findings confirmed the role of GCK and G6PC2 in regulating the pulsatility in insulin secretion thereby influencing insulin-signaling and leading to a gradual modulation in glucose levels in Italian patients with newly diagnosed T2D.

Genome-wide association study identifying novel variant for fasting insulin and allelic heterogeneity in known glycemic loci in Chilean adolescents: The Santiago Longitudinal Study

BACKGROUND

The genetic underpinnings of glycemic traits have been understudied in adolescent and Hispanic/Latino (H/L) populations in comparison to adults and populations of European ancestry.

OBJECTIVE

To identify genetic factors underlying glycemic traits in an adolescent H/L population.

METHODS

We conducted a genome-wide association study (GWAS) of fasting glucose (FG) and fasting insulin (FI) in H/L adolescents from the Santiago Longitudinal Study.

RESULTS

We identified one novel variant positioned in the CSMD1 gene on chromosome 8 (rs77465890, effect allele frequency = 0.10) that was associated with FI (β = -0.299, SE = 0.054, p = 2.72×10-8 ) and was only slightly attenuated after adjusting for body mass index z-scores (β = -0.252, SE = 0.047, p = 1.03×10-7 ). We demonstrated directionally consistent, but not statistically significant results in African and Hispanic adults of the Population Architecture Using Genomics and Epidemiology Consortium. We also identified secondary signals for two FG loci after conditioning on known variants, which demonstrate allelic heterogeneity in well-known glucose loci.

CONCLUSION

Our results exemplify the importance of including populations with diverse ancestral origin and adolescent participants in GWAS of glycemic traits to uncover novel risk loci and expand our understanding of disease aetiology.

Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches

Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.

Glucose metabolism-related gene polymorphisms as the risk predictors of type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a complex polygenic metabolic disease characterized by elevated blood glucose. Multiple environmental and genetic factors can increase the risk of T2DM and its complications, and genetic polymorphisms are no exception. This review is mainly focused on the related genes involved in glucose metabolic, including G6PC2, GCK, GCKR and OCT3. In this review, we have summarized the results reported globally and found that the genetic variants of GCK and OCT3 genes is a risk factor for T2DM while G6PC2 and GCKR genes are controversial in different ethnic groups. Hopefully, this summary could possibly help researchers and physicians understand the mechanism of T2DM so as to diagnose and even prevent T2DM at early time.

Mendelian Randomization Study: The Association Between Metabolic Pathways and Colorectal Cancer Risk

Background: The roles of obesity-related biomarkers and their molecular pathways in the development of postmenopausal colorectal cancer (CRC) have been inconclusive. We examined insulin resistance (IR) as a major hormonal pathway mediating the association between obesity and CRC risk in a Mendelian randomization (MR) framework.

Methods: We performed MR analysis using individual-level data of 11,078 non-Hispanic white postmenopausal women from our earlier genome-wide association study. We identified four independent single-nucleotide polymorphisms associated with fasting glucose (FG), three with fasting insulin (FI), and six with homeostatic model assessment–IR (HOMA-IR), which were not associated with obesity. We estimated hazard ratios (HRs) for CRC by adjusting for potential confounding factors plus genetic principal components.

Results: Overall, we observed no direct association between combined 13 IR genetic instruments and CRC risk (HR = 0.96, 95% confidence interval [CI]: 0.78–1.17). In phenotypic analysis, genetically raised HOMA-IR exhibited its effects on the increased risk and FG and FI on the reduced risk for CRC, but with a lack of statistical power. Subgroup analyses by physical activity level and dietary fat intake with combined phenotypes showed that genetically determined IR was associated with reduced CRC risk in both physical activity-stratified (single contributor: MTRR rs722025; HR = 0.12, 95% CI: 0.02–0.62) and high-fat diet subgroups (main contributor: G6PC2 rs560887; HR = 0.59, 95% CI: 0.37–0.94).

Conclusions: Complex evidence was observed for a potential causal association between IR and CRC risk. Our findings may provide an additional value of intervention trials to lower IR and reduce CRC risk.

G6PC2 confers protection against hypoglycemia upon ketogenic diet feeding and prolonged fasting

Objective

G6PC2 is predominantly expressed in pancreatic islet beta cells. G6PC2 hydrolyzes glucose-6-phosphate to glucose and inorganic phosphate, thereby creating a futile substrate cycle that opposes the action of glucokinase. This substrate cycle determines the sensitivity of glucose-stimulated insulin secretion to glucose and hence regulates fasting blood glucose (FBG) but not fasting plasma insulin (FPI) levels. Our objective was to explore the physiological benefit this cycle confers.

Methods

We investigated the response of wild type (WT) and G6pc2 knockout (KO) mice to changes in nutrition.

Results

Pancreatic G6pc2 expression was little changed by ketogenic diet feeding but was inhibited by 24 hr fasting and strongly induced by high fat feeding. When challenged with either a ketogenic diet or 24 hr fasting, blood glucose fell to 70 mg/dl or less in G6pc2 KO but not WT mice, suggesting that G6PC2 may have evolved, in part, to prevent hypoglycemia. Prolonged ketogenic diet feeding reduced the effect of G6pc2 deletion on FBG. The hyperglycemia associated with high fat feeding was partially blunted in G6pc2 KO mice, suggesting that under these conditions the presence of G6PC2 is detrimental. As expected, FPI changed but did not differ between WT and KO mice in response to fasting, ketogenic and high fat feeding.

Conclusions

Since elevated FBG levels are associated with increased risk for cardiovascular-associated mortality (CAM), these studies suggest that, while G6PC2 inhibitors would be useful for lowering FBG and the risk of CAM, partial inhibition will be important to avoid the risk of hypoglycemia.

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G6pc2 deletion lowers fasting blood glucose (FBG) in chow and high fat fed mice.

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Elevated FBG increases the risk of cardiovascular-associated mortality (CAM).

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G6pc2 deletion results in hypoglycemia in mice on a ketogenic diet.

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G6pc2 deletion results in hypoglycemia in mice following prolonged fasting.

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G6PC2 inhibitors may prevent CAM but increase risk of hypoglycemia.

Pancreatic islet beta cell-specific deletion of G6pc2 reduces fasting blood glucose

The G6PC1, G6PC2 and G6PC3 genes encode distinct glucose-6-phosphatase catalytic subunit (G6PC) isoforms. In mice, germline deletion of G6pc2 lowers fasting blood glucose (FBG) without affecting fasting plasma insulin (FPI) while, in isolated islets, glucose-6-phosphatase activity and glucose cycling are abolished and glucose-stimulated insulin secretion (GSIS) is enhanced at submaximal but not high glucose. These observations are all consistent with a model in which G6PC2 regulates the sensitivity of GSIS to glucose by opposing the action of glucokinase. G6PC2 is highly expressed in human and mouse islet beta cells however, various studies have shown trace G6PC2 expression in multiple tissues raising the possibility that G6PC2 also affects FBG through non-islet cell actions. Using real-time PCR we show here that expression of G6pc1 and/or G6pc3 are much greater than G6pc2 in peripheral tissues, whereas G6pc2 expression is much higher than G6pc3 in both pancreas and islets with G6pc1 expression not detected. In adult mice, beta cell-specific deletion of G6pc2 was sufficient to reduce FBG without changing FPI. In addition, electronic health record-derived phenotype analyses showed no association between G6PC2 expression and phenotypes clearly unrelated to islet function in humans. Finally, we show that germline G6pc2 deletion enhances glycolysis in mouse islets and that glucose cycling can also be detected in human islets. These observations are all consistent with a mechanism by which G6PC2 action in islets is sufficient to regulate the sensitivity of GSIS to glucose and hence influence FBG without affecting FPI.

Genome wide association study of 40 clinical measurements in eight dog breeds

The domestic dog represents an ideal model for identifying susceptibility genes, many of which are shared with humans. In this study, we investigated the genetic contribution to individual differences in 40 clinically important measurements by a genome-wide association study (GWAS) in a multinational cohort of 472 healthy dogs from eight breeds. Meta-analysis using the binary effects model after breed-specific GWAS, identified 13 genome-wide significant associations, three of them showed experimental-wide significant associations. We detected a signal at chromosome 13 for the serum concentration of alanine aminotransferase (ALT) in which we detected four breed-specific signals. A large proportion of the variance of ALT (18.1–47.7%) was explained by this locus. Similarly, a single SNP was also responsible for a large proportion of the variance (6.8–78.4%) for other measurements such as fructosamine, stress during physical exam, glucose, and morphometric measurements. The genetic contribution of single variant was much larger than in humans. These findings illustrate the importance of performing meta-analysis after breed-specific GWAS to reveal the genetic contribution to individual differences in clinically important measurements, which would lead to improvement of veterinary medicine.

Nutrient-Induced Metabolic Stress, Adaptation, Detoxification, and Toxicity in the Pancreatic β-Cell

Paraphrasing the Swiss physician and father of toxicology Paracelsus (1493-1541) on chemical agents used as therapeutics, "the dose makes the poison," it is now realized that this aptly applies to the calorigenic nutrients. The case here is the pancreatic islet β-cell presented with excessive levels of nutrients such as glucose, lipids, and amino acids. The short-term effects these nutrients exert on the β-cell are enhanced insulin biosynthesis and secretion and changes in glucose sensitivity. However, chronic fuel surfeit triggers additional compensatory and adaptive mechanisms by β-cells to cope with the increased insulin demand or to protect itself. When these mechanisms fail, toxicity due to the nutrient surplus ensues, leading to β-cell dysfunction, dedifferentiation, and apoptosis. The terms glucotoxicity, lipotoxicity, and glucolipotoxicity have been widely used, but there is some confusion as to what they mean precisely and which is most appropriate for a given situation. Here we address the gluco-, lipo-, and glucolipo-toxicities in β-cells by assessing the evidence both for and against each of them. We also discuss potential mechanisms and defend the view that many of the identified "toxic" effects of nutrient excess, which may also include amino acids, are in fact beneficial adaptive processes. In addition, candidate fuel-excess detoxification pathways are evaluated. Finally, we propose that a more general term should be used for the in vivo situation of overweight-associated type 2 diabetes reflecting both the adaptive and toxic processes to mixed calorigenic nutrients excess: "nutrient-induced metabolic stress" or, in brief, "nutri-stress."

General regression model: A "model-free" association test for quantitative traits allowing to test for the underlying genetic model

Most genome-wide association studies used genetic-model-based tests assuming an additive mode of inheritance, leading to underpowered association tests in case of departure from additivity. The general regression model (GRM) association test proposed by Fisher and Wilson in 1980 makes no assumption on the genetic model. Interestingly, it also allows formal testing of the underlying genetic model. We conducted a simulation study of quantitative traits to compare the power of the GRM test to the classical linear regression tests, the maximum of the three statistics (MAX), and the allele-based (allelic) tests. Simulations were performed on two samples sizes, using a large panel of genetic models, varying genetic models, minor allele frequencies, and the percentage of explained variance. In case of departure from additivity, the GRM was more powerful than the additive regression tests (power gain reaching 80%) and had similar power when the true model is additive. GRM was also as or more powerful than the MAX or allelic tests. The true simulated model was mostly retained by the GRM test. Application of GRM to HbA1c illustrates its gain in power. To conclude, GRM increases power to detect association for quantitative traits, allows determining the genetic model and is easily applicable.

Post genome-wide gene-environment interaction study: The effect of genetically driven insulin resistance on breast cancer risk using Mendelian randomization

PURPOSE

The role of insulin resistance (IR) in developing postmenopausal breast cancer has not been thoroughly resolved and may be confounded by lifestyle factors such as obesity. We examined whether genetically determined IR is causally associated with breast cancer risk.

METHODS

We conducted Mendelian randomization (MR) analyses using individual-level data from our previous meta-analysis of a genome-wide association study (GWAS) (n = 11,109 non-Hispanic white postmenopausal women). Four single-nucleotide polymorphisms were associated with fasting glucose (FG), 2 with fasting insulin (FI), and 6 with homeostatic model assessment-IR (HOMA-IR) but were not associated with obesity. We used this GWAS to employ hazard ratios (HRs) for breast cancer risk by adjusting for potential confounding factors.

RESULTS

No direct association was observed between comprising 12 IR genetic instruments and breast cancer risk (HR = 0.93, 95% CI: 0.76-1.14). In phenotype-specific analysis, genetically elevated FG was associated with reduced risk for breast cancer (main contributor of this MR-effect estimate: G6PC2 rs13431652; HR = 0.59, 95% CI: 0.35-0.99). Genetically driven FI and HOMA-IR were not significantly associated. Stratification analyses by body mass index, exercise, and dietary fat intake with combined phenotypes showed that genetically elevated IR was associated with greater breast cancer risk in overall obesity and inactive subgroups (single contributor: MTRR/LOC729506 rs13188458; HR = 2.21, 95% CI: 1.03-4.75).

CONCLUSIONS

We found complex evidence for causal association between IR and risk of breast cancer, which may support the potential value of intervention trials to lower IR and reduce breast cancer risk.

Noncoding Variations in the Gene Encoding Ceramide Synthase 6 are Associated with Type 2 Diabetes in a Large Indigenous Australian Pedigree

Type 2 diabetes (T2D) is a chronic disease that disproportionately affects Indigenous Australians. We have previously reported the localization of a novel T2D locus by linkage analysis to chromosome 2q24 in a large admixed Indigenous Australian pedigree (Busfield et al. (2002). American Journal of Human Genetics, 70, 349-357). Here we describe fine mapping of this region in this pedigree, with the identification of SNPs showing strong association with T2D: rs3845724 (diabetes p = 7 × 10-4), rs4668106 (diabetes p = 9 × 10-4) and rs529002 (plasma glucose p = 3 × 10-4). These associations were successfully replicated in an independent collection of Indigenous Australian T2D cases and controls. These SNPs all lie within the gene encoding ceramide synthase 6 (CERS6) and thus may regulate ceramide synthesis.

The Genetic Basis of Metabolic Disease

Recent developments in genetics and genomics are providing a detailed and systematic characterization of the genetic underpinnings of common metabolic diseases and traits, highlighting the inherent complexity within systems for homeostatic control and the many ways in which that control can fail. The genetic architecture underlying these common metabolic phenotypes is complex, with each trait influenced by hundreds of loci spanning a range of allele frequencies and effect sizes. Here, we review the growing appreciation of this complexity and how this has fostered the implementation of genome-scale approaches that deliver robust mechanistic inference and unveil new strategies for translational exploitation.

Association and Functional Analyses Revealed That PPP1R3B Plays an Important Role in the Regulation of Glycogen Content in the Pacific Oyster Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is one of the most important aquaculture species worldwide. Glycogen contributes greatly to the special taste and creamy white color of oysters. Previous genome-wide association studies (GWAS) identified several single nucleotide polymorphism (SNP) sites that were strongly related to glycogen content. Genes within 100 kb upstream and downstream of the associated SNPs were screened. One gene annotated as protein phosphatase 1 regulatory subunit 3B (PPP1R3B), which can promote glycogen synthesis together with protein phosphatase 1 catalytic subunit (PPP1C) in mammals, was selected as a candidate gene in this study. First, full-length CgPPP1R3B was cloned and its function was characterized. The gene expression profiles of CgPPP1R3B in different tissues and seasons showed a close relationship to glycogen content. RNA interference (RNAi) experiments of this gene in vivo showed that decreased CgPPP1R3B levels resulted in lower glycogen contents in the experimental group than in the control group. Co-immunoprecipitation (Co-IP) and yeast two-hybrid (Y2H) assays indicated that CgPPP1R3B can interact with CgPPP1C, glycogen synthase (CgGS) and glycogen phosphorylase (CgGP), thus participating in glycogen metabolism. Co-sedimentation analysis in vitro demonstrated that the CgPPP1R3B protein can bind to glycogen molecules directly, and these results indicated the conserved function of the CgPPP1R3B protein compared to that of mammals. In addition, thirteen SNPs were precisely mapped in this gene. Ten of the thirteen SNPs were confirmed to be significantly (p < 0.05) related to glycogen content in an independent wild population (n = 288). The CgPPP1R3B levels in oysters with high glycogen content were significantly higher than those of oysters with low glycogen content, and gene expression levels were significantly associated with various genotypes of four associated SNPs (p < 0.05). The data indicated that the associated SNPs may control glycogen content by regulating CgPPP1R3B expression. These results suggest that CgPPP1R3B is an important gene for glycogen metabolic regulation and that the associated SNPs of this gene are potential markers for oyster molecular breeding for increased glycogen content.

Metabolic fitness in relation to genetic variation and leukocyte DNA methylation

Metabolic syndrome (MetS) is a highly prevalent condition causing increased risk of several life-threatening diseases. MetS has a pronounced hereditary basis but is also influenced by environmental factors, partly through epigenetic mechanisms. In this study, the five phenotypes underlying MetS were incorporated into a continuous score for metabolic fitness (MF), and associations with both genotypic variation and leukocyte DNA methylation were investigated. Baseline MF phenotypes (waist circumference, blood pressure, blood glucose, serum triglycerides, and high-density lipoproteins) of 710 healthy Flemish adults were measured. After a 10 yr period, follow-up measures were derived from 618 of these subjects. Genotyping was performed for 65 preselected MF-related genetic variants. Next, full genetic predisposition scores (GPSs) were calculated, combining genotype scores of multiple genetic variants. Additionally, stepwise GPSs were constructed, including only the most predictive genetic variants for the different MF phenotypes. For a subset of 68 middle-aged men, global and gene-specific DNA methylation was investigated, and a biological pathway analysis was performed. The full GPSs were predictive for some baseline MF phenotypes, but not for changes over time. Only a limited number of genetic variants were significantly predictive individually. On the contrary, global and gene-specific DNA methylation was associated with changes in the MF phenotypes rather than with the baseline measures, indicating that effects of DNA methylation on MF are somewhat delayed. Furthermore, several biological pathways were associated with the MF phenotypes through gene promoter methylation. For CETP, G6PC2, MC4R, and TFAP2B both a genetic and epigenetic relationship was found with MF.

Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors

Measurements of fasting glucose (FG) or glycated hemoglobin A1c (HbA1c) are two clinically approved approaches commonly used to determine glycemia, both of which are influenced by genetic factors. Obtaining accurate measurements of FG or HbA1c is not without its challenges, though. Measuring glycated serum protein (GSP) offers an alternative approach for assessing glycemia. The aim of this study was to estimate the heritability of GSP and GSP expressed as a percentage of total serum albumin (%GA) using a variance component approach and localize genomic regions (QTLs) that harbor genes likely to influence GSP and %GA trait variation in a large extended multigenerational pedigree from Jiri, Nepal (n = 1,800). We also performed quantitative bivariate analyses to assess the relationship between GSP or %GA and several cardiometabolic traits. Additive genetic effects significantly influence variation in GSP and %GA levels (p values: 1.15 × 10^-5 and 3.39 × 10^-5, respectively). We localized a significant (LOD score = 3.18) and novel GSP QTL on chromosome 11q, which has been previously linked to type 2 diabetes. Two common (MAF > 0.4) SNPs within the chromosome 11 QTL were associated with GSP (adjusted pvalue < 5.87 × 10^-5): an intronic variant (rs10790184) in the DSCAML1 gene and a 3'UTR variant (rs8258) in the CEP164 gene. Significant positive correlations were observed between GSP or %GA and blood pressure, and lipid traits (p values: 0.0062 to 1.78 × 10^-9). A significant negative correlation was observed between %GA and HDL cholesterol (p = 1.12 × 10^-5). GSP is influenced by genetic factors and can be used to assess glycemia and diabetes risk. Thus, GSP measurements can facilitate glycemic studies when accurate FG and/or HbA1c measurements are difficult to obtain. GSP can also be measured from frozen blood (serum) samples, which allows the prospect of retrospective glycemic studies using archived samples.

Exposing the Causal Effect of C-Reactive Protein on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study

As a biomarker of inflammation, C-reactive protein (CRP) has attracted much attention due to its role in the incidence of type 2 diabetes mellitus (T2DM). Prospective studies have observed a positive correlation between the level of serum CRP and the incidence of T2DM. Recently, studies have reported that drugs for curing T2DM can also decrease the level of serum CRP. However, it is not yet clear whether high CRP levels cause T2DM. To evaluate this, we conducted a Mendelian randomization (MR) analysis using genetic variations as instrumental variables (IVs). Significantly associated single nucleotide polymorphisms (SNPs) of CRP were obtained from a genome-wide study and a replication study. Therein, 17,967 participants were utilized for the genome-wide association study (GWAS), and another 14,747 participants were utilized for the replication of identifying SNPs associated with CRP levels. The associations between SNPs and T2DM were from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium. After removing SNPs in linkage disequilibrium (LD) and T2DM-related SNPs, the four remaining CRP-related SNPs were deemed as IVs. To evaluate the pooled influence of these IVs on the risk of developing T2DM through CRP, the penalized robust inverse-variance weighted (IVW) method was carried out. The combined result (OR 1.114048; 95% CI 1.058656 to 1.172338; P = 0.024) showed that high levels of CRP significantly increase the risk of T2DM. In the subsequent analysis of the relationship between CRP and type 1 diabetes mellitus (T1DM), the pooled result (OR 1.017145; 95% CI 0.9066489 to 1.14225; P = 0.909) supported that CRP levels cannot determine the risk of developing T1DM.

Jointly Modelling Single Nucleotide Polymorphisms With Longitudinal and Time-to-Event Trait: An Application to Type 2 Diabetes and Fasting Plasma Glucose

In observational cohorts, longitudinal data are collected with repeated measurements at predetermined time points for many biomarkers, along with other variables measured at baseline. In these cohorts, time until a certain event of interest occurs is reported and very often, a relationship will be observed between some biomarker repeatedly measured over time and that event. Joint models were designed to efficiently estimate statistical parameters describing this relationship by combining a mixed model for the longitudinal biomarker trajectory and a survival model for the time until occurrence of the event, using a set of random effects to account for the relationship between the two types of data. In this paper, we discuss the implementation of joint models in genetic association studies. First, we check model consistency based on different simulation scenarios, by varying sample sizes, minor allele frequencies and number of repeated measurements. Second, using genotypes assayed with the Metabochip DNA arrays (Illumina) from about 4,500 individuals recruited in the French cohort D.E.S.I.R. (Data from an Epidemiological Study on the Insulin Resistance syndrome), we assess the feasibility of implementing the joint modelling approach in a real high-throughput genomic dataset. An alternative model approximating the joint model, called the Two-Step approach (TS), is also presented. Although the joint model shows more precise and less biased estimators than its alternative counterpart, the TS approach results in much reduced computational times, and could thus be used for testing millions of SNPs at the genome-wide scale.

Identification and functional analysis of glycemic trait loci in the China Health and Nutrition Survey

To identify genetic contributions to type 2 diabetes (T2D) and related glycemic traits (fasting glucose, fasting insulin, and HbA1c), we conducted genome-wide association analyses (GWAS) in up to 7,178 Chinese subjects from nine provinces in the China Health and Nutrition Survey (CHNS). We examined patterns of population structure within CHNS and found that allele frequencies differed across provinces, consistent with genetic drift and population substructure. We further validated 32 previously described T2D- and glycemic trait-loci, including G6PC2 and SIX3-SIX2 associated with fasting glucose. At G6PC2, we replicated a known fasting glucose-associated variant (rs34177044) and identified a second signal (rs2232326), a low-frequency (4%), probably damaging missense variant (S324P). A variant within the lead fasting glucose-associated signal at SIX3-SIX2 co-localized with pancreatic islet expression quantitative trait loci (eQTL) for SIX3, SIX2, and three noncoding transcripts. To identify variants functionally responsible for the fasting glucose association at SIX3-SIX2, we tested five candidate variants for allelic differences in regulatory function. The rs12712928-C allele, associated with higher fasting glucose and lower transcript expression level, showed lower transcriptional activity in reporter assays and increased binding to GABP compared to the rs12712928-G, suggesting that rs12712928-C contributes to elevated fasting glucose levels by disrupting an islet enhancer, resulting in reduced gene expression. Taken together, these analyses identified multiple loci associated with glycemic traits across China, and suggest a regulatory mechanism at the SIX3-SIX2 fasting glucose GWAS locus.

A common variant within the HNF1B gene is associated with overall survival of multiple myeloma patients: results from the IMMEnSE consortium and meta-analysis

Diabetogenic single nucleotide polymorphisms (SNPs) have recently been associated with multiple myeloma (MM) risk but their impact on overall survival (OS) of MM patients has not been analysed yet. In order to investigate the impact of 58 GWAS-identified variants for type 2 diabetes (T2D) on OS of patients with MM, we analysed genotyping data of 936 MM patients collected by the International Multiple Myeloma rESEarch (IMMENSE) consortium and an independent set of 700 MM patients recruited by the University Clinic of Heidelberg. A meta-analysis of the cox regression results of the two sets showed that rs7501939 located in the HNF1B gene negatively impacted OS (HRRec= 1.44, 95% CI = 1.18-1.76, P = 0.0001). The meta-analysis also showed a noteworthy gender-specific association of the SLC30A8rs13266634 SNP with OS. The presence of each additional copy of the minor allele at rs13266634 was associated with poor OS in men whereas no association was seen in women (HRMen-Add = 1.32, 95% CI 1.13-1.54, P = 0.0003). In conclusion, these data suggest that the HNF1Brs7501939 SNP confers poor OS in patients with MM and that a SNP in SLC30A8 affect OS in men.

Genetic aetiology of glycaemic traits: approaches and insights

Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.

Meta-analyses of the association of G6PC2 allele variants with elevated fasting glucose and type 2 diabetes

Objective

To collectively evaluate the association of glucose-6-phosphatase catalytic unit 2 (G6PC2) allele variants with elevated fasting glucose (FG) and type 2 diabetes (T2D).

Design

Meta-analysis

Data sources

PubMed, Web of Knowledge and Embase databases.

Study selection

Full text articles of studies that identified an association of G6PC2 with T2D and elevated FG.

Patient involvement

There was no T2D patient involvement in the analyses on the association of FG with G6PC2, there were T2D patients and non-diabetes patient involvement in the analyses on the association of T2D with G6PC2.

Statistical analysis

Random-effects meta-analyses were used to calculate the pool effect sizes. I² metric and H² tests were used to calculate the heterogeneity. Begg's funnel plot and Egger’s linear regression test were done to assess publication bias.

Results

Of the 423 studies identified, 21 were eligible and included. Data on three loci (rs560887, rs16856187 and rs573225) were available. The G allele at rs560887 in three ethnicities, the C allele at rs16856187 and the A allele at rs573225 all had a positive association with elevated FG. Per increment of G allele at rs560887 and A allele at rs573225 resulted in a FG 0.070 mmol/l and 0.075 mmol/l higher (ß (95% CI) = 0.070 (0.060, 0.079), p = 4.635e-50 and 0.075 (0.065, 0.085), p = 5.856e-48, respectively). With regard to the relationship of rs16856187 and FG, an increase of 0.152 (95% CI: 0.034–0.270; p = 0.011) and 0.317 (95% CI: 0.193–0.442, p = 6.046e-07) was found in the standardized mean difference (SMD) of FG for the AC and CC genotypes, respectively, when compared with the AA reference genotype. However, the G-allele of rs560887 in Caucasians under the additive model and the C-allele of rs16856187 under the allele and dominant models were associated with a decreased risk of T2D (OR (95% CI) = 0.964 (0.947, 0.981), p = 0.570e-4; OR (95% CI) = 0.892 (0.832, 0.956), p = 0.001; and OR (95% CI) = 0.923(0.892, 0.955), p = 5.301e-6, respectively).

Conclusions

Our meta-analyses demonstrate that all three allele variants of G6PC2 (rs560887, rs16856187 and rs573225) are associated with elevated FG, with two variants (rs560887 in the Caucasians subgroup and rs16856187 under the allele and dominant model) being associated with T2D as well. Further studies utilizing larger sample sizes and different ethnic populations are needed to extend and confirm these findings.

Is Type 2 Diabetes a Glycogen Storage Disease of Pancreatic β Cells?

Elevated plasma glucose leads to pancreatic β cell dysfunction and death in type 2 diabetes. Glycogen accumulation, due to impaired metabolism, contributes to this "glucotoxicity" via dysregulated biochemical pathways promoting β cell dysfunction. Here, we review emerging data, and re-examine published findings, on the role of glycogen in β cells in normoglycemia and in diabetes.

Human genetics as a model for target validation: finding new therapies for diabetes

Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are 'experiments of nature' that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck.

Genetically Driven Hyperglycemia Increases Risk of Coronary Artery Disease Separately From Type 2 Diabetes

OBJECTIVE

This study tested the hypothesis that genetically raised hyperglycemia increases coronary artery disease (CAD) risk separately from the risk conferred by type 2 diabetes as a whole.

RESEARCH DESIGN AND METHODS

We conducted a Mendelian randomization (MR) analysis using summary-level statistics from the largest published meta-analyses of genome-wide association studies (GWAS) for fasting glucose (FG) (n = 133,010 participants free of diabetes) and CAD (n = 63,746 case subjects and 130,681 control subjects) of predominantly European ancestry. FG-increasing variants associated with type 2 diabetes from the largest GWAS for type 2 diabetes were excluded. Variants with pleiotropic effects on other CAD risk factors (blood lipids, blood pressure, and obesity) were excluded using summary-level data from the largest published GWAS. Data from the Framingham Heart Study were used to validate the MR instrument and to build an FG genetic risk score (GRS).

RESULTS

In an instrumental variable analysis comprising 12 FG-raising variants, a 1 mmol/L increase in FG revealed an effect-size estimate of 1.43 CAD odds (95% CI 1.14-1.79). The association was preserved after excluding variants for heterogeneity and pleiotropic effects on other CAD risk factors (odds ratio [OR] 1.33 [95% CI 1.02-1.73]). The 12 FG-increasing variants did not significantly increase type 2 diabetes risk (OR 1.05 [95% CI 0.91-1.23]), and its prevalence was constant across FG GRS quintiles (P = 0.72).

CONCLUSIONS

Our data support that genetic predisposition to hyperglycemia raises the odds of CAD separately from type 2 diabetes and other CAD risk factors. These findings suggest that modulating glycemia may provide cardiovascular benefit.

Effects of G6pc2 deletion on body weight and cholesterol in mice

Genome-wide association study (GWAS) data have linked the G6PC2 gene to variations in fasting blood glucose (FBG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit that forms a substrate cycle with the beta cell glucose sensor glucokinase. This cycle modulates the glucose sensitivity of insulin secretion and hence FBG. GWAS data have not linked G6PC2 to variations in body weight but we previously reported that female C57BL/6J G6pc2-knockout (KO) mice were lighter than wild-type littermates on both a chow and high-fat diet. The purpose of this study was to compare the effects of G6pc2 deletion on FBG and body weight in both chow-fed and high-fat-fed mice on two other genetic backgrounds. FBG was reduced in G6pc2 KO mice largely independent of gender, genetic background or diet. In contrast, the effect of G6pc2 deletion on body weight was markedly influenced by these variables. Deletion of G6pc2 conferred a marked protection against diet-induced obesity in male mixed genetic background mice, whereas in 129SvEv mice deletion of G6pc2 had no effect on body weight. G6pc2 deletion also reduced plasma cholesterol levels in a manner dependent on gender, genetic background and diet. An association between G6PC2 and plasma cholesterol was also observed in humans through electronic health record-derived phenotype analyses. These observations suggest that the action of G6PC2 on FBG is largely independent of the influences of environment, modifier genes or epigenetic events, whereas the action of G6PC2 on body weight and cholesterol are influenced by unknown variables.

Susceptibility to type 2 diabetes may be modulated by haplotypes in G6PC2, a target of positive selection

BACKGROUND

The endoplasmic reticulum enzyme glucose-6-phosphatase catalyzes the common terminal reaction in the gluconeogenic/glycogenolytic pathways and plays a central role in glucose homeostasis. In most mammals, different G6PC subunits are encoded by three paralogous genes (G6PC, G6PC2, and G6PC3). Mutations in G6PC and G6PC3 are responsible for human mendelian diseases, whereas variants in G6PC2 are associated with fasting glucose (FG) levels.

RESULTS

We analyzed the evolutionary history of G6Pase genes. Results indicated that the three paralogs originated during early vertebrate evolution and that negative selection was the major force shaping diversity at these genes in mammals. Nonetheless, site-wise estimation of evolutionary rates at corresponding sites revealed weak correlations, suggesting that mammalian G6Pases have evolved different structural features over time. We also detected pervasive positive selection at mammalian G6PC2. Most selected residues localize in the C-terminal protein region, where several human variants associated with FG levels also map. This region was re-sequenced in ~560 subjects from Saudi Arabia, 185 of whom suffering from type 2 diabetes (T2D). The frequency of rare missense and nonsense variants was not significantly different in T2D and controls. Association analysis with two common missense variants (V219L and S342C) revealed a weak but significant association for both SNPs when analyses were conditioned on rs560887, previously identified in a GWAS for FG. Two haplotypes were significantly associated with T2D with an opposite effect direction.

CONCLUSIONS

We detected pervasive positive selection at mammalian G6PC2 genes and we suggest that distinct haplotypes at the G6PC2 locus modulate susceptibility to T2D.

Glycogen metabolism in the glucose-sensing and supply-driven β-cell

Glycogen metabolism in β-cells may affect downstream metabolic pathways controlling insulin release. We examined glycogen metabolism in human islets and in the rodent-derived INS-1 832/13 β-cells and found them to express the same isoforms of key enzymes required for glycogen metabolism. Our findings indicate that glycogenesis is insulin-independent but influenced by extracellular glucose concentrations. Levels of glycogen synthase decrease with increasing glucose concentrations, paralleling accumulation of glycogen. We did not find cAMP-elicited glycogenolysis and insulin secretion to be causally related. In conclusion, our results reveal regulated glycogen metabolism in human islets and insulin-secreting cells. Whether glycogen metabolism affects insulin secretion under physiological conditions remains to be determined.

G6PC2 Modulates the Effects of Dexamethasone on Fasting Blood Glucose and Glucose Tolerance

The glucose-6-phosphatase catalytic subunit 2 (G6PC2) gene encodes an islet-specific glucose-6-phosphatase catalytic subunit. G6PC2 forms a substrate cycle with glucokinase that determines the glucose sensitivity of insulin secretion. Consequently, deletion of G6pc2 lowers fasting blood glucose (FBG) without affecting fasting plasma insulin. Although chronic elevation of FBG is detrimental to health, glucocorticoids induce G6PC2 expression, suggesting that G6PC2 evolved to transiently modulate FBG under conditions of glucocorticoid-related stress. We show, using competition and mutagenesis experiments, that the synthetic glucocorticoid dexamethasone (Dex) induces G6PC2 promoter activity through a mechanism involving displacement of the islet-enriched transcription factor MafA by the glucocorticoid receptor. The induction of G6PC2 promoter activity by Dex is modulated by a single nucleotide polymorphism, previously linked to altered FBG in humans, that affects FOXA2 binding. A 5-day repeated injection paradigm was used to examine the chronic effect of Dex on FBG and glucose tolerance in wild-type (WT) and G6pc2 knockout mice. Acute Dex treatment only induces G6pc2 expression in 129SvEv but not C57BL/6J mice, but this chronic treatment induced G6pc2 expression in both. In 6-hour fasted C57BL/6J WT mice, Dex treatment lowered FBG and improved glucose tolerance, with G6pc2 deletion exacerbating the decrease in FBG and enhancing the improvement in glucose tolerance. In contrast, in 24-hour fasted C57BL/6J WT mice, Dex treatment raised FBG but still improved glucose tolerance, with G6pc2 deletion limiting the increase in FBG and enhancing the improvement in glucose tolerance. These observations demonstrate that G6pc2 modulates the complex effects of Dex on both FBG and glucose tolerance.

Evaluating the transferability of 15 European-derived fasting plasma glucose SNPs in Mexican children and adolescents

Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population.

Functional Analysis of Mouse G6pc1 Mutations Using a Novel In Situ Assay for Glucose-6-Phosphatase Activity and the Effect of Mutations in Conserved Human G6PC1/G6PC2 Amino Acids on G6PC2 Protein Expression

Elevated fasting blood glucose (FBG) has been associated with increased risk for development of type 2 diabetes. Single nucleotide polymorphisms (SNPs) in G6PC2 are the most important common determinants of variations in FBG in humans. Studies using G6pc2 knockout mice suggest that G6pc2 regulates the glucose sensitivity of insulin secretion. G6PC2 and the related G6PC1 and G6PC3 genes encode glucose-6-phosphatase catalytic subunits. This study describes a functional analysis of 22 non-synonymous G6PC2 SNPs, that alter amino acids that are conserved in human G6PC1, mouse G6pc1 and mouse G6pc2, with the goal of identifying variants that potentially affect G6PC2 activity/expression. Published data suggest strong conservation of catalytically important amino acids between all four proteins and the related G6PC3 isoform. Because human G6PC2 has very low glucose-6-phosphatase activity we used an indirect approach, examining the effect of these SNPs on mouse G6pc1 activity. Using a novel in situ functional assay for glucose-6-phosphatase activity we demonstrate that the amino acid changes associated with the human G6PC2 rs144254880 (Arg79Gln), rs149663725 (Gly114Arg) and rs2232326 (Ser324Pro) SNPs reduce mouse G6pc1 enzyme activity without affecting protein expression. The Arg79Gln variant alters an amino acid mutation of which, in G6PC1, has previously been shown to cause glycogen storage disease type 1a. We also demonstrate that the rs368382511 (Gly8Glu), rs138726309 (His177Tyr), rs2232323 (Tyr207Ser) rs374055555 (Arg293Trp), rs2232326 (Ser324Pro), rs137857125 (Pro313Leu) and rs2232327 (Pro340Leu) SNPs confer decreased G6PC2 protein expression. In summary, these studies identify multiple G6PC2 variants that have the potential to be associated with altered FBG in humans.

G6PC2 Modulates Fasting Blood Glucose In Male Mice in Response to Stress

The glucose-6-phosphatase catalytic 2 (G6PC2) gene is expressed specifically in pancreatic islet beta cells. Genome-wide association studies have shown that single nucleotide polymorphisms in the G6PC2 gene are associated with variations in fasting blood glucose (FBG) but not fasting plasma insulin. Molecular analyses examining the functional effects of these single nucleotide polymorphisms demonstrate that elevated G6PC2 expression is associated with elevated FBG. Studies in mice complement these genome-wide association data and show that deletion of the G6pc2 gene lowers FBG without affecting fasting plasma insulin. This suggests that, together with glucokinase, G6PC2 forms a substrate cycle that determines the glucose sensitivity of insulin secretion. Because genome-wide association studies and mouse studies demonstrate that elevated G6PC2 expression raises FBG and because chronically elevated FBG is detrimental to human health, increasing the risk of type 2 diabetes, it is unclear why G6PC2 evolved. We show here that the synthetic glucocorticoid dexamethasone strongly induces human G6PC2 promoter activity and endogenous G6PC2 expression in isolated human islets. Acute treatment with dexamethasone selectively induces endogenous G6pc2 expression in 129SvEv but not C57BL/6J mouse pancreas and isolated islets. The difference is due to a single nucleotide polymorphism in the C57BL/6J G6pc2 promoter that abolishes glucocorticoid receptor binding. In 6-hour fasted, nonstressed 129SvEv mice, deletion of G6pc2 lowers FBG. In response to the stress of repeated physical restraint, which is associated with elevated plasma glucocorticoid levels, G6pc2 gene expression is induced and the difference in FBG between wild-type and knockout mice is enhanced. These data suggest that G6PC2 may have evolved to modulate FBG in response to stress.

Improved Performance of Dynamic Measures of Insulin Response Over Surrogate Indices to Identify Genetic Contributors of Type 2 Diabetes: The GUARDIAN Consortium

Type 2 diabetes (T2D) is a heterogeneous disorder with contributions from peripheral insulin resistance and β-cell dysfunction. For minimization of phenotypic heterogeneity, quantitative intermediate phenotypes characterizing basal glucose homeostasis (insulin resistance and HOMA of insulin resistance [HOMAIR] and of β-cell function [HOMAB]) have shown promise in relatively large samples. We investigated the utility of dynamic measures of glucose homeostasis (insulin sensitivity [SI] and acute insulin response [AIRg]) evaluating T2D-susceptibility variants (n = 57) in Hispanic Americans from the GUARDIAN Consortium (n = 2,560). Basal and dynamic measures were genetically correlated (HOMAB-AIRg: ρG = 0.28-0.73; HOMAIR-SI: ρG = -0.73 to -0.83) with increased heritability for the dynamic measure AIRg Significant association of variants with dynamic measures (P < 8.77 × 10(-4)) was observed. A pattern of superior performance of AIRg was observed for well-established loci including MTNR1B (P = 9.46 × 10(-12)), KCNQ1 (P = 1.35 × 10(-4)), and TCF7L2 (P = 5.10 × 10(-4)) with study-wise statistical significance. Notably, significant association of MTNR1B with AIRg (P < 1.38 × 10(-9)) was observed in a population one-fourteenth the size of the initial discovery cohort. These observations suggest that basal and dynamic measures provide different views and levels of sensitivity to discrete elements of glucose homeostasis. Although more costly to obtain, dynamic measures yield significant results that could be considered physiologically "closer" to causal pathways and provide insight into the discrete mechanisms of action.

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.