Type 2 diabetes susceptibility gene TCF7L2 and its role in beta-cell function

Proteomic analysis of the effects of Girdin on Jiaogulan-treated type 2 diabetes patients

Jiaogulan (Gynostemma pentaphyllum) is a traditional herb with potential antidiabetic properties. This study investigated the underlying mechanisms of these properties by analysing plasma protein profiles in type 2 diabetes patients. A total of 42 participants were divided into three groups, each comprising 14 individuals: healthy controls (N), untreated type 2 diabetes patients (DM), and Jiaogulan-treated type 2 diabetes patients (DMJ). Proteomic analysis, integrated with bioinformatics and molecular docking, was conducted. This analysis identified 24 unique proteins in the healthy control group, 16 in the untreated diabetic group, and 19 in the Jiaogulan-treated group. Notably, the Jiaogulan-treated group exhibited statistically significant upregulation of proteins involved in insulin signalling, including CCDC88A (Girdin), with a p value of <0.05. This protein is a critical regulator of insulin sensitivity that interacts with the Akt and PI3K pathways. Furthermore, molecular docking analysis identified gypenoside, a bioactive compound from Jiaogulan, as a potential inhibitor of protein phosphatase 2A (PP2A), an important regulator of insulin signalling. PP2A inhibition preserves the phosphorylation of critical signalling molecules, such as Akt, facilitating glucose uptake and metabolism. These findings suggest that Jiaogulan may increase insulin sensitivity by modulating key proteins in the insulin signalling pathway, such as Girdin, and inhibiting PP2A activity. This inhibition might help maintain the phosphorylation of critical signalling molecules such as Akt, thereby promoting glucose uptake and metabolism. Ultimately, this research suggests that Jiaogulan has significant potential therapeutic benefits for individuals with type 2 diabetes.

Selected Genetic Characteristics of the Vietnamese Minority Living in the Czech Republic

The aim of this study was to analyse the allelic distribution of selected genes in the Czech and Vietnamese populations. We analysed samples from 94 Vietnamese volunteers and 2,859 Czech population-based subjects (2,559 from the Czechs post-MONICA and 300 volunteers from the South region of the Czech Republic). There were significant differences between the two populations for most, but not all, of the SNPs analysed. In particular, the prevalence of risk alleles in the analysed polymorphisms tended to be lower in the Vietnamese community compared to the Czech population, especially within the FTO (rs17817449; associated with obesity risk, P < 0.0001), TCF7L2 (rs7903146; linked to type 2 dia-betes, P < 0.0001) and ADH1B (rs1229984; related to alcohol consumption, P < 0.0001) genes. The genotype within the MCM6/LCT cluster (rs4988235) associated with lactase persistence was not present in the Vietnamese population. Slight genotype differences were detected for one HFE polymorphism (rs1799945 with P = 0.005; but not for rs1800562). Only the genotype frequencies within the MC4R and APOE genes were almost identical in both populations. We conclude that the Vietnamese population may have a lower genetic predisposition to the non-communicable diseases such as obesity or diabetes mellitus.

Understanding the Genetic Landscape of Gestational Diabetes: Insights into the Causes and Consequences of Elevated Glucose Levels in Pregnancy

Background/Objectives: During pregnancy, physiological changes in maternal circulating glucose levels and its metabolism are essential to meet maternal and fetal energy demands. Major changes in glucose metabolism occur throughout pregnancy and consist of higher insulin resistance and a compensatory increase in insulin secretion to maintain glucose homeostasis. For some women, this change is insufficient to maintain normoglycemia, leading to gestational diabetes mellitus (GDM), a condition characterized by maternal glucose intolerance and hyperglycaemia first diagnosed during the second or third trimester of pregnancy. GDM is diagnosed in approximately 14.0% of pregnancies globally, and it is often associated with short- and long-term adverse health outcomes in both mothers and offspring. Although recent studies have highlighted the role of genetic determinants in the development of GDM, research in this area is still lacking, hindering the development of prevention and treatment strategies. Methods: In this paper, we review recent advances in the understanding of genetic determinants of GDM and glycaemic traits during pregnancy. Results/Conclusions: Our review highlights the need for further collaborative efforts as well as larger and more diverse genotyped pregnancy cohorts to deepen our understanding of the genetic aetiology of GDM, address research gaps, and further improve diagnostic and treatment strategies.

Adaptive selection at G6PD and disparities in diabetes complications

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828 -T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828 -T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828 -T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles.

Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations

BACKGROUND

Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations.

METHODS

We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger's Z-test and further validated in a pediatric cohort without diabetes (aged 9-12 years old, n = 3866).

RESULTS

We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta - 0.08 SD, 95% CI [- 0.10-0.07], p = 6.50 × 10-32) and beta-cell dysfunction (Beta - 0.10 SD, 95% CI [- 0.12, - 0.08], p = 1.46 × 10-47) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06-0.10, p = 8.0 × 10-33). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02-1.62, p = 0.03).

CONCLUSIONS

We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.

T-cell factor 7L2 is a novel regulator of osteoblast functions that acts in part by modulation of hypoxia signaling

T-cell-like factor (TCF)7l2, a key effector of canonical Wnt signaling, is highly expressed in bone but nothing is known about its role in regulating osteoblast function. To test this, we generated mice with conditional disruption of Tcf7l2 gene in osteoblast lineages using Tcf7l2 floxed and Col1α2-Cre mice. Skeletal parameters were evaluated using heterozygous conditional knockdown (HCKD) mice since homozygous conditional knockout died during pregnancy or immediately after birth. At 5 wk of age, trabecular bone mass of long bones was reduced by 35% as measured by microcomputed tomography (μCT). Histology data showed a 42% reduction in femur trabecular bone mass caused by reduced bone formation. Knockdown of Tcf7l2 expression in osteoblasts decreased proliferation and differentiation by 20%-40%. Expression levels of genes (Hif1α, Vegf, and β-catenin) targeted by TCF7L2 were decreased by 50% in Tcf7l2-deficient osteoblasts and bones of HCKD mice. We found that the Hif1α gene promoter contained multiple putative TCF7L2 motifs and stabilization of HIF1α protein levels rescued expression of TCF7L2 target genes and alkaline phosphatase (ALP) activity in Tcf7l2-deficient osteoblasts. Furthermore, Tcf7l2 overexpression increased proliferation in the presence of canonical Wnt3a that was not affected by β-catenin inhibitor providing evidence for a noncanonical signaling in mediating TCF7L2 effects. Tcf7l2 expression was increased in response to mechanical strain (MS) in vitro and in vivo, and disruption of Tcf7l2 expression in osteoblasts reduced MS-induced ALP activity by 35%. We conclude that Tcf7l2, a mechanoresponsive gene, is an important regulator of osteoblast function acting, in part, via hypoxia signaling.NEW & NOTEWORTHY TCF7L2 is expressed by bone but it was not known whether TCF7L2 expression influenced bone development. By using a mouse model with conditional disruption of Tcf7l2 in osteoblast lineage cells, we have demonstrated for the first time, that TCF7L2 plays an important role in regulating osteoblasts via a noncanonical pathway.

A review on interplay between obesity, lipoprotein profile and nutrigenetics with selected candidate marker genes of type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus, a rapidly growing epidemic, and its frequently related complications demand global attention. The two factors commonly attributed to the epidemic are genetic factors and environmental factors. Studies indicate that the genetic makeup at an individual level and the environmental aspects influence the occurrence of the disease. However, there is insufficiency in understanding the mechanisms through which the gene mutations and environmental components individually lead to T2DM. Also, discrepancies have often been noted in the association of gene variants and type 2 diabetes when the gene factor is examined as a sole attribute to the disease.

STUDY

In this review initially, we have focused on the proposed ways through which CAPN10, FABP2, GLUT2, TCF7L2, and ENPP1 variants lead to T2DM along with the inconsistencies observed in the gene-disease association. The article also emphasizes on obesity, lipoprotein profile, and nutrition as environmental factors and how they lead to T2DM. Finally, the main objective is explored, the environment-gene-disease association i.e. the influence of each environmental factor on the aforementioned specific gene-T2DM relationship to understand if the disease-causing capability of the gene variants is exacerbated by environmental influences.

CONCLUSION

We found that environmental factors may influence the gene-disease relationship. Reciprocally, the genetic factors may alter the environment-disease relationship. To precisely conclude that the two factors act synergistically to lead to T2DM, more attention has to be paid to the combined influence of the genetic variants and environmental factors on T2DM occurrence instead of studying the influence of the factors separately.

Regulatory variants in TCF7L2 are associated with thoracic aortic aneurysm

Thoracic aortic aneurysm (TAA) is characterized by dilation of the aortic root or ascending/descending aorta. TAA is a heritable disease that can be potentially life threatening. While 10%-20% of TAA cases are caused by rare, pathogenic variants in single genes, the origin of the majority of TAA cases remains unknown. A previous study implicated common variants in FBN1 with TAA disease risk. Here, we report a genome-wide scan of 1,351 TAA-affected individuals and 18,295 control individuals from the Cardiovascular Health Improvement Project and Michigan Genomics Initiative at the University of Michigan. We identified a genome-wide significant association with TAA for variants within the third intron of TCF7L2 following replication with meta-analysis of four additional independent cohorts. Common variants in this locus are the strongest known genetic risk factor for type 2 diabetes. Although evidence indicates the presence of different causal variants for TAA and type 2 diabetes at this locus, we observed an opposite direction of effect. The genetic association for TAA colocalizes with an aortic eQTL of TCF7L2, suggesting a functional relationship. These analyses predict an association of higher expression of TCF7L2 with TAA disease risk. In vitro, we show that upregulation of TCF7L2 is associated with BCL2 repression promoting vascular smooth muscle cell apoptosis, a key driver of TAA disease.

Dietary Macronutrient Intake May Influence the Effects of TCF7L2 rs7901695 Genetic Variants on Glucose Homeostasis and Obesity-Related Parameters: A Cross-Sectional Population-Based Study

Transcription factor-7–like 2 (TCF7L2) is one of the most important susceptibility genes for type 2 diabetes mellitus (T2DM). The aim of our cross-sectional population-based study was to analyze whether daily macronutrient intake may influence the effects of the TCF7L2 rs7901695 genotype on glucose homeostasis and obesity-related parameters. We recruited 810 participants (47.5% men and 52.5% women), 18–79 years old (mean age, 42.1 (±14.5) years), who were genotyped for the common TCF7L2 rs7901695 single-nucleotide polymorphism (SNP), and anthropometric measurements, body composition, body fat distribution (visceral (VAT) and subcutaneous adipose tissue (SAT) content), blood glucose and insulin concentrations after fasting and during OGTTs, and HbA1c were assessed. The VAT/SAT ratio, HOMA-IR (homeostatic model assessment of insulin resistance), HOMA-B (homeostatic model assessment of β-cell function), and CIR30 (corrected insulin response) were calculated. The daily macronutrient intake was evaluated based on 3-day food-intake diaries. Daily physical activity was evaluated based on a validated questionnaire. We performed ANOVA or Kruskal–Wallis tests, and multivariate linear regression models were created to evaluate the effects of dietary macronutrient intake on glucose homeostasis and obesity-related parameters in carriers of the investigated genotypes. This study was registered at ClinicalTrials.gov as NCT03792685. The TT-genotype carriers stratified to the upper protein intake quantiles presented higher HbA1c levels than the CT- and CC-genotype participants in the same quantiles (p = 0.038 and p = 0.022, respectively). Moreover, we observed higher HOMA-IR (p = 0.014), as well as significantly higher blood glucose and insulin concentrations, during the OGTTs for those in the upper quantiles, when compared to subjects from the lower quantiles of protein intake, while the CC-genotype carriers presented significantly lower HbA1c (p = 0.033) and significantly higher CIR30 (p = 0.03). The linear regression models revealed that an increase in energy derived from proteins in TT carriers was associated with higher HbA1c levels (β = 0.37 (95% CI: 0.01–0.74, p = 0.05)), although, in general, carrying the TT genotype, but without considering protein intake, showed an opposite tendency—to lower HbA1c levels (β = −0.22 (95% CI: 0.47 to −0.01, p = 0.05). Among the subjects stratified to the lower quantile of carbohydrate intake, the TT-genotype individuals presented higher HbA1c (p = 0.041), and the CC-genotype subjects presented higher VAT (p = 0.033), lower SAT (p = 0.033), and higher VAT/SAT ratios (p = 0.034). In both the CC- and TT-genotype carriers, we noted higher VAT (p = 0.012 and p = 0.0006, respectively), lower SAT (p = 0.012 and p = 0.0006, respectively) and higher VAT/SAT ratios (p = 0.016 and p = 0.00062, respectively) when dietary fat provided more than 30% of total daily energy intake, without any differences in total body fat content. Our findings suggest that associations of the common TCF7L2 SNP with glucose homeostasis and obesity-related parameters may be dependent on daily macronutrient intake, which warrants further investigations in a larger population, as well as interventional studies.

Identifying Shared Risk Genes between Nonalcoholic Fatty Liver Disease and Metabolic Traits by Cross-Trait Association Analysis

Nonalcoholic fatty liver disease (NAFLD) generally co-occurs with metabolic disorders, but it is unclear which genes have a pleiotripic effect on NAFLD and metabolic traits. We performed a large-scale cross-trait association analysis to identify the overlapping genes between NAFLD and nine metabolic traits. Among all the metabolic traits, we found that obesity and type II diabetes are associated with NAFLD. Then, a multitrait association analysis among NAFLD, obesity and type II diabetes was conducted to improve the overall statistical power. We identified 792 significant variants by a cross-trait meta-analysis involving 100 pleiotripic genes. Moreover, we detected another two common genes by a genome-wide gene test. The results from the pathway enrichment analysis show that the 102 shared risk genes are enriched in cancer, diabetes, insulin secretion, and other related pathways. This study can help us understand the molecular mechanisms underlying comorbid NAFLD and metabolic disorders.

Robustness and lethality in multilayer biological molecular networks

Robustness is a prominent feature of most biological systems. Most previous related studies have been focused on homogeneous molecular networks. Here we propose a comprehensive framework for understanding how the interactions between genes, proteins and metabolites contribute to the determinants of robustness in a heterogeneous biological network. We integrate heterogeneous sources of data to construct a multilayer interaction network composed of a gene regulatory layer, a protein-protein interaction layer, and a metabolic layer. We design a simulated perturbation process to characterize the contribution of each gene to the overall system's robustness, and find that influential genes are enriched in essential and cancer genes. We show that the proposed mechanism predicts a higher vulnerability of the metabolic layer to perturbations applied to genes associated with metabolic diseases. Furthermore, we find that the real network is comparably or more robust than expected in multiple random realizations. Finally, we analytically derive the expected robustness of multilayer biological networks starting from the degree distributions within and between layers. These results provide insights into the non-trivial dynamics occurring in the cell after a genetic perturbation is applied, confirming the importance of including the coupling between different layers of interaction in models of complex biological systems.

Human embryonic stem cells as an in vitro model for studying developmental origins of type 2 diabetes

The developmental origins of health and diseases (DOHaD) is a concept stating that adverse intrauterine environments contribute to the health risks of offspring. Since the theory emerged more than 30 years ago, many epidemiological and animal studies have confirmed that in utero exposure to environmental insults, including hyperglycemia and chemicals, increased the risk of developing noncommunicable diseases (NCDs). These NCDs include metabolic syndrome, type 2 diabetes, and complications such as diabetic cardiomyopathy. Studying the effects of different environmental insults on early embryo development would aid in understanding the underlying mechanisms by which these insults promote NCD development. Embryonic stem cells (ESCs) have also been utilized by researchers to study the DOHaD. ESCs have pluripotent characteristics and can be differentiated into almost every cell lineage; therefore, they are excellent in vitro models for studying early developmental events. More importantly, human ESCs (hESCs) are the best alternative to human embryos for research because of ethical concerns. In this review, we will discuss different maternal conditions associated with DOHaD, focusing on the complications of maternal diabetes. Next, we will review the differentiation protocols developed to generate different cell lineages from hESCs. Additionally, we will review how hESCs are utilized as a model for research into the DOHaD. The effects of environmental insults on hESC differentiation and the possible involvement of epigenetic regulation will be discussed.

Regulation of epithelial-mesenchymal transition and organoid morphogenesis by a novel TGFβ-TCF7L2 isoform-specific signaling pathway

Alternative splicing contributes to diversification of gene function, yet consequences of splicing on functions of specific gene products is poorly understood. The major transcription factor TCF7L2 undergoes alternative splicing but the biological significance of TCF7L2 isoforms has remained largely to be elucidated. Here, we find that the TCF7L2 E-isoforms maintain, whereas the M and S isoforms disrupt morphogenesis of 3D-epithelial cell-derived organoids via regulation of epithelial-mesenchymal transition (EMT). Remarkably, TCF7L2E2 antagonizes, whereas TCF7L2M2/S2 promotes EMT-like effects in epithelial cells induced by transforming growth factor beta (TGFβ) signaling. In addition, we find TGFβ signaling reduces the proportion of TCF7L2E to TCF7L2M/S protein in cells undergoing EMT. We also find that TCF7L2 operates via TGFβ-Smad3 signaling to regulate EMT. Collectively, our findings unveil novel isoform-specific functions for the major transcription factor TCF7L2 and provide novel links between TCF7L2 and TGFβ signaling in the control of EMT-like responses and epithelial tissue morphogenesis.

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

Shared genetic architecture between metabolic traits and Alzheimer's disease: a large-scale genome-wide cross-trait analysis

A growing number of studies clearly demonstrate a substantial link between metabolic dysfunction and the risk of Alzheimer's disease (AD), especially glucose-related dysfunction; one hypothesis for this comorbidity is the presence of a common genetic etiology. We conducted a large-scale cross-trait GWAS to investigate the genetic overlap between AD and ten metabolic traits. Among all the metabolic traits, fasting glucose, fasting insulin and HDL were found to be genetically associated with AD. Local genetic covariance analysis found that 19q13 region had strong local genetic correlation between AD and T2D (P = 6.78 × 10- 22), LDL (P = 1.74 × 10- 253) and HDL (P = 7.94 × 10- 18). Cross-trait meta-analysis identified 4 loci that were associated with AD and fasting glucose, 3 loci that were associated with AD and fasting insulin, and 20 loci that were associated with AD and HDL (Pmeta < 1.6 × 10- 8, single trait P < 0.05). Functional analysis revealed that the shared genes are enriched in amyloid metabolic process, lipoprotein remodeling and other related biological pathways; also in pancreas, liver, blood and other tissues. Our work identifies common genetic architectures shared between AD and fasting glucose, fasting insulin and HDL, and sheds light on molecular mechanisms underlying the association between metabolic dysregulation and AD.

Effect of TCF7L2 polymorphism on pancreatic hormones after exenatide in type 2 diabetes

BACKGROUND

Glucagon-like peptide 1 (GLP-1) stimulates insulin secretion and reduces blood glucose in type 2 diabetes mellitus (T2DM). TCF7L2 rs7903146 polymorphism has been associated with decreased insulin secretion, reduced GLP-1 action, and possible impaired peripheral insulin sensitivity.

OBJECTIVES

To evaluate the postprandial pancreatic hormone response in patients with T2DM carriers of the TCF7L2 variant rs7903146 (CT/TT) compared with noncarriers of this variant (CC) after treatment with the GLP-1 agonist exenatide.

METHODS

Intervention study. Patients with T2DM (n = 162) were genotyped for the TCF7L2 rs7903146 single nucleotide polymorphism (SNP). Individuals with CT/TT and CC genotypes were compared regarding basal serum levels of glucose, glycosylated hemoglobin A1C (HbA1c), HDL, uric acid, insulin, and C-peptide. A subset of 56 individuals was evaluated during a 500-calorie mixed-meal test with measurements of glucose, insulin, proinsulin, C-peptide and glucagon before and after treatment with exenatide for 8 weeks.

RESULTS

Patients with genotypes CC and CT/TT presented similar glucose area under the curve (AUC) 0-180 min before treatment and a similar decrease after treatment (p < 0.001). Before exenatide, insulin levels at 30-120 min were higher in CT/TT versus CC subjects (p < 0.05). After treatment with exenatide, only CT/TT individuals demonstrated insulin reduction at 30-180 min during the meal test (p < 0.05). Patients with the CC genotype presented no differences in insulin concentrations before and after treatment. The areas under the glucagon curve between 0 and 180 min were similar before treatment and reduced after treatment in both groups (p < 0.001).

CONCLUSIONS

The presence of the TCF7L2 rs7903146 T allele in patients with T2DM was associated with increased secretion of insulin response to a mixed-meal test. Furthermore, after treatment with exenatide, only the carriers of the T allele showed significantly decreased postprandial plasma insulin peak levels comparing with non carriers.

Identification and characterization of differentially expressed genes in Type 2 Diabetes using in silico approach

Diabetes mellitus is clinically characterized by hyperglycemia. Though many studies have been done to understand the mechanism of Type 2 Diabetes (T2D), however, the complete network of diabetes and its associated disorders through polygenic involvement is still under debate. The present study designed to re-analyze publicly available T2D related microarray raw datasets present in GEO database and T2D genes information present in GWAS catalog for screening out differentially expressed genes (DEGs) and identify key hub genes associated with T2D. T2D related microarray data downloaded from Gene Expression Omnibus (GEO) database and re-analysis performed with in house R packages scripts for background correction, normalization and identification of DEGs in T2D. Also retrieved T2D related DEGs information from GWAS catalog. Both DEGs lists were grouped after removal of overlapping genes. These screened DEGs were utilized further for identification and characterization of key hub genes in T2D and its associated diseases using STRING, WebGestalt and Panther databases. Computational analysis reveal that out of 99 identified key hub gene candidates from 348 DEGs, only four genes (CCL2, ELMO1, VEGFA and TCF7L2) along with FOS playing key role in causing T2D and its associated disorders, like nephropathy, neuropathy, rheumatoid arthritis and cancer via p53 or Wnt signaling pathways. MIR-29, and MAZ_Q6 are identified potential target microRNA and TF along with probable drugs alprostadil, collagenase and dinoprostone for the key hub gene candidates. The results suggest that identified key DEGs may play promising roles in prevention of diabetes.

Coordinated Tcf7l2 regulation in a mouse model implicates Wnt signaling in fetal alcohol spectrum disorders

Mouse models of fetal alcohol spectrum disorders (FASD) have repeatedly identified genes with long-term changes in expression, DNA methylation, noncoding RNA, and histone modifications in response to neurodevelopmental alcohol exposure. Articulation of FASD is achieved via alcohol's effect on gene expression, likely involving epigenetic regulation. The list of genes affected is large and heterogeneous, depending on experimental protocol. We present reanalysis and synthesis of results highlighting the Wnt transcription factor 7 like 2 (Tcf7l2) gene as uniquely compatible with hippocampal DNA methylation, histone modifications, and gene expression changes in a coordinated response to neurodevelopmental alcohol exposure. We data-mined the literature for Tcf7l2 alterations in response to prenatal alcohol exposure. Four studies identified changes in brain Tcf7l2 expression in different FASD models. Further, we performed an in silico TCF7L2 binding site analysis for FASD mouse model data sets. Seven of these published gene lists were significantly enriched for TCF7L2 binding, indicating potential functional relationships. Finally, TCF7L2 is involved in regulation of hundreds of genes, with a role in brain development, myelination, and neuronal function. Tcf7l2 may be involved in neurological defects associated with alcohol exposure via dysregulation of many genes through Wnt signaling. Further functional work is warranted to validate this model for FASD.

Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates Type 2 Diabetes associated genes

Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p-values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study. We identified variants regulating gene expression (expression quantitative loci, eQTL) of HiCc pathway genes in islet samples. These eQTL genes showed higher levels of differential expression compared to non-eQTL genes in low, medium, and high glucose concentrations in rat islets. Among genes with highly significant eQTL evidence, NFATC4 belonged to four HiCc pathways. We asked if the expressions of T2D-associated candidate genes from GWAS and literature are regulated by Nfatc4 in rat islets. Extensive in vitro silencing of Nfatc4 in rat islet cells displayed reduced expression of 16, and increased expression of four putative downstream T2D genes. Overall, our approach uncovers the mechanistic connection of NFATC4 with downstream targets including a previously unknown one, TCF7L2, and establishes the HiCc pathways' relationship to T2D.

Impact of KCNQ1, CDKN2A/2B, CDKAL1, HHEX, MTNR1B, SLC30A8, TCF7L2, and UBE2E2 on risk of developing type 2 diabetes in Thai population

BACKGROUND

Several type 2 diabetes (T2D) susceptibility loci identified via genome-wide association studies were found to be replicated among various populations. However, the influence of these loci on T2D in Thai population is unknown. The aim of this study was to investigate the influence of eight single nucleotide polymorphisms (SNPs) reported in GWA studies on T2D and related quantitative traits in Thai population.

METHODS

Eight SNPs in or near the KCNQ1, CDKN2A/2B, SLC30A8, HHEX, CDKAL1, TCF7L2, MTNR1B, and UBE2E2 genes were genotyped. A case-control association study comprising 500 Thai patients with T2D and 500 ethnically-matched control subjects was conducted. Associations between SNPs and T2D were examined by logistic regression analysis. The impact of these SNPs on quantitative traits was examined by linear regression among case and control subjects.

RESULTS

Five SNPs in KCNQ1 (rs2237892), CDK2A/2B (rs108116610, SLC30A8 (rs13266634), TCF7L2 (rs7903146) and MTNR1B (rs1387153) were found to be marginally associated with risk of developing T2D, with odds ratios ranging from 1.43 to 2.02 (p = 0.047 to 3.0 × 10-4) with adjustments for age, sex, and body mass index. Interestingly, SNP rs13266634 of SLC30A8 gene reached statistical significance after correcting for multiple testing (p = 0.0003) (p < 0.006 after Bonferroni correction). However, no significant association was detected between HHEX (rs1111875), CDKAL1 (rs7756992), or UBE2E2 (rs7612463) and T2D. We also observed association between rs10811661 and both waist circumference and waist-hip ratio (p = 0.007 and p = 0.023, respectively). In addition, rs13266634 in SLC30A8 was associated with glycated hemoglobin (p = 0.018), and rs7903146 in TCF7L2 was associated with high-density lipoprotein cholesterol level (p = 0.023).

CONCLUSION

Of the eight genes included in our analysis, significant association was observed between KCNQ1, CDKN2A/2B, SLC30A8, TCF7L2, and MTNR1B loci and T2D in our Thai study population. Of these, CDKN2A/2B, SLC30A8, and TCF7L2 genes were also significantly associated with anthropometric, glycemic and lipid characteristics. Larger cohort studies and meta-analyses are needed to further confirm the effect of these variants in Thai population.

Screening of Polymorphisms of Transcription Factor 7-like 2 Gene in Polycystic Ovary Syndrome using Polymerase Chain Reaction-restriction Fragment Length Polymorphism Analysis

Background:

Polycystic ovary syndrome (PCOS) is a common endocrine disorder occurring in premenopausal women, with a prevalence rate of 5%–7%. It has been observed in multiple number of studies the coexistence between diabetes mellitus 2 and obesity with this endocrinopathic disorder. Transcription factor 7-like 2 (TCF7L2) gene is shown to be associated with insulin secretion.

Aim:

To screen whether the gene variant of TCF7L2 (formerly TCF4) gene is significantly associated and has susceptibilities with type 2 diabetes in PCOS. This study is essential to uncover diabetogenic association of the TCF7L2 gene variants with PCOS.

Design:

This was a hospital-based study.

Methods:

In this work, blood samples from 43 PCOS patients with age and sex similar to 43 control samples were collected, followed by isolation of DNA. Further genotyping of the TCF7L2 gene was carried out by performing polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).

Statistical Analysis:

Genotype frequencies of the TCF7L2 rs7903146 gene were checked by Hardy–Weinberg equilibrium of genotype in both PCOS and the control group, and also, the frequencies of the genotype were performed accordingly.

Results:

There was no significant allelic variation observed among the patient and the control samples. From the patient details, it was observed that women between the age group of 21 and 25 years are susceptible to PCOS.

Conclusion:

From the PCR-RFLP analysis, it can be stated that there are no expected gene polymorphisms seen in this study, unlike the study carried out on the Chinese population where they observed genotype variations CC, CT, and TT. From this study, we can conclude that TCF7L2 rs7903146 gene cannot be considered as the candidate gene for the occurrence of PCOS.

Changes in selective pressures associated with human population expansion may explain metabolic and immune related pathways enriched for signatures of positive selection

Background

The study of local adaptation processes is a very important research topic in the field of population genomics. There is a particular interest in the study of human populations because they underwent a process of rapid spatial expansion and faced important environmental changes that translated into changes in selective pressures. New mutations may have been selected for in the new environment and previously existing genetic variants may have become detrimental. Immune related genes may have been released from the selective pressure exerted by pathogens in the ancestral environment and new variants may have been positively selected due to pathogens present in the newly colonized habitat. Also, variants that had a selective advantage in past environments may have become deleterious in the modern world due to external stimuli including climatic, dietary and behavioral changes, which could explain the high prevalence of some polygenic diseases such as diabetes and obesity.

Results

We performed an enrichment analysis to identify gene sets enriched for signals of positive selection in humans. We used two genome scan methods, XPCLR and iHS to detect selection using a dense coverage of SNP markers combined with two gene set enrichment approaches. We identified immune related gene sets that could be involved in the protection against pathogens especially in the African population. We also identified the glycolysis & gluconeogenesis gene set, related to metabolism, which supports the thrifty genotype hypothesis invoked to explain the current high prevalence of diseases such as diabetes and obesity. Extending our analysis to the gene level, we found signals for 23 candidate genes linked to metabolic syndrome, 13 of which are new candidates for positive selection.

Conclusions

Our study provides a list of genes and gene sets associated with immunity and metabolic syndrome that are enriched for signals of positive selection in three human populations (Europeans, Africans and Asians). Our results highlight differences in the relative importance of pathogens as drivers of local adaptation in different continents and provide new insights into the evolution and high incidence of metabolic syndrome in modern human populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2783-2) contains supplementary material, which is available to authorized users.

Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network

Background

The future of medicine is moving towards the phase of precision medicine, with the goal to prevent and treat diseases by taking inter-individual variability into account. A large part of the variability lies in our genetic makeup. With the fast paced improvement of high-throughput methods for genome sequencing, a tremendous amount of genetics data have already been generated. The next hurdle for precision medicine is to have sufficient computational tools for analyzing large sets of data. Genome-Wide Association Studies (GWAS) have been the primary method to assess the relationship between single nucleotide polymorphisms (SNPs) and disease traits. While GWAS is sufficient in finding individual SNPs with strong main effects, it does not capture potential interactions among multiple SNPs. In many traits, a large proportion of variation remain unexplained by using main effects alone, leaving the door open for exploring the role of genetic interactions. However, identifying genetic interactions in large-scale genomics data poses a challenge even for modern computing.

Results

For this study, we present a new algorithm, Grammatical Evolution Bayesian Network (GEBN) that utilizes Bayesian Networks to identify interactions in the data, and at the same time, uses an evolutionary algorithm to reduce the computational cost associated with network optimization. GEBN excelled in simulation studies where the data contained main effects and interaction effects. We also applied GEBN to a Type 2 diabetes (T2D) dataset obtained from the Marshfield Personalized Medicine Research Project (PMRP). We were able to identify genetic interactions for T2D cases and controls and use information from those interactions to classify T2D samples. We obtained an average testing area under the curve (AUC) of 86.8 %. We also identified several interacting genes such as INADL and LPP that are known to be associated with T2D.

Conclusions

Developing the computational tools to explore genetic associations beyond main effects remains a critically important challenge in human genetics. Methods, such as GEBN, demonstrate the utility of considering genetic interactions, as they likely explain some of the missing heritability.

Wnt9a deficiency discloses a repressive role of Tcf7l2 on endocrine differentiation in the embryonic pancreas

Transcriptional and signaling networks establish complex cross-regulatory interactions that drive cellular differentiation during development. Using microarrays we identified the gene encoding the ligand Wnt9a as a candidate target of Neurogenin3, a basic helix-loop-helix transcription factor that functions as a master regulator of pancreatic endocrine differentiation. Here we show that Wnt9a is expressed in the embryonic pancreas and that its deficiency enhances activation of the endocrine transcriptional program and increases the number of endocrine cells at birth. We identify the gene encoding the endocrine transcription factor Nkx2-2 as one of the most upregulated genes in Wnt9a-ablated pancreases and associate its activation to reduced expression of the Wnt effector Tcf7l2. Accordingly, in vitro studies confirm that Tcf7l2 represses activation of Nkx2-2 by Neurogenin3 and inhibits Nkx2-2 expression in differentiated β-cells. Further, we report that Tcf7l2 protein levels decline upon initiation of endocrine differentiation in vivo, disclosing the downregulation of this factor in the developing endocrine compartment. These findings highlight the notion that modulation of signalling cues by lineage-promoting factors is pivotal for controlling differentiation programs.

Insights into the Genetic Susceptibility to Type 2 Diabetes from Genome-Wide Association Studies of Obesity-Related Traits

Obesity and type 2 diabetes (T2D) are common and complex metabolic diseases, which are caused by an interchange between environmental and genetic factors. Recently, a number of large-scale genome-wide association studies (GWAS) have improved our knowledge of the genetic architecture and biological mechanisms of these diseases. Currently, more than ~250 genetic loci have been found for monogenic, syndromic, or common forms of T2D and/or obesity-related traits. In this review, we discuss the implications of these GWAS for obesity and T2D, and investigate the overlap of loci for obesity-related traits and T2D, highlighting potential mechanisms that affect T2D susceptibility.

The association between the rs11196218A/G polymorphism of the TCF7L2 gene and type 2 diabetes in the Chinese Han population: a meta-analysis

Transcription factor 7-like 2 has been shown to be associated with type 2 diabetes mellitus in multiple ethnic groups in recent years. In the Chinese Han population in particular, numerous studies have evaluated the association between the rs11196218A/G polymorphism of the transcription factor 7-like 2 gene and type 2 diabetes mellitus. However, the results have been inconsistent, so we performed a meta-analysis to assess the association. Odds ratio and 95% confidence interval values were calculated using a random-effects model or a fixed-effects model based on heterogeneity analysis. The quality of the included studies was evaluated using the Newcastle-Ottawa Scale. Subgroup analyses were conducted based on conformity with Hardy-Weinberg equilibrium in the control group as well as on other variables, such as age, sex and body mass index. Sensitivity analysis was also performed to detect heterogeneity and to assess the stability of the results. In total, 10 case-control studies comprising 7,491 cases and 12,968 controls were included in this meta-analysis. The combined analysis indicated that the rs11196218A/G polymorphism was not associated with type 2 diabetes mellitus (G vs. A, OR=1.04, 95% CI=0.97-1.13, p=0.28). The subgroup analyses also did not show any association between the rs11196218A/G polymorphism and the risk of type 2 diabetes mellitus. Furthermore, the results of the subgroup analyses indicated that the absence of an association was not influenced by age, sex or body mass index. The results of the sensitivity analysis verified the reliability and stability of this meta-analysis. In conclusion, this study indicated that there is no significant association between the rs11196218A/G polymorphism and the risk of type 2 diabetes mellitus in the Chinese Han population.

Diabetes mellitus: The epidemic of the century

The epidemic nature of diabetes mellitus in different regions is reviewed. The Middle East and North Africa region has the highest prevalence of diabetes in adults (10.9%) whereas, the Western Pacific region has the highest number of adults diagnosed with diabetes and has countries with the highest prevalence of diabetes (37.5%). Different classes of diabetes mellitus, type 1, type 2, gestational diabetes and other types of diabetes mellitus are compared in terms of diagnostic criteria, etiology and genetics. The molecular genetics of diabetes received extensive attention in recent years by many prominent investigators and research groups in the biomedical field. A large array of mutations and single nucleotide polymorphisms in genes that play a role in the various steps and pathways involved in glucose metabolism and the development, control and function of pancreatic cells at various levels are reviewed. The major advances in the molecular understanding of diabetes in relation to the different types of diabetes in comparison to the previous understanding in this field are briefly reviewed here. Despite the accumulation of extensive data at the molecular and cellular levels, the mechanism of diabetes development and complications are still not fully understood. Definitely, more extensive research is needed in this field that will eventually reflect on the ultimate objective to improve diagnoses, therapy and minimize the chance of chronic complications development.

Glucose and the risk of hypertension in first-degree relatives of patients with type 2 diabetes

To test the hypothesis that plasma glucose (PG) levels is associated with the incidence of hypertension (HT) in nondiabetic and non-hypertensive first-degree relatives (FDR) of people with type 2 diabetes (T2D). A total of 1089 FDR without diabetes and/or HT of consecutive patients with T2D 30-70 years old were examined and followed for a mean (s.d.) of 6.9 (1.7) years for HT incidence. At baseline and through follow-up, participants underwent a standard 75 gm 2-h oral glucose tolerance test. HT was defined according to the criteria of the Seventh Report of Joint National Committee. We used Cox proportional hazard models to estimate hazard ratio for incident HT and plotted a receiver operating characteristic curve to assess discrimination. The PG levels at baseline were associated with incidence of HT, independently of age, gender, obesity and high cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, education and systolic blood pressure. Those with impaired glucose tolerance were 54% (hazard ratio 1.54; 95% confidence interval (CI) 1.33, 1.77) more likely to develop HT than those with normal glucose tolerance. Those with impaired fasting glucose were also 23% (hazard ratio 1.23; 95% CI 1.01, 1.50) more likely to develop HT. High PG levels were consistently associated with incident HT.

Differential methylation of TCF7L2 promoter in peripheral blood DNA in newly diagnosed, drug-naïve patients with type 2 diabetes

TCF7L2 is the susceptibility gene for Type 2 diabetes (T2D) with the largest effect on disease risk that has been discovered to date. However, the mechanisms by which TCF7L2 contributes to the disease remain largely elusive. In addition, epigenetic mechanisms, such as changes in DNA methylation patterns, might have a role in the pathophysiology of T2D. This study aimed to investigate the differences in terms of DNA methylation profile of TCF7L2 promoter gene between type 2 diabetic patients and age- and Body Mass Index (BMI)- matched controls. We included 93 type 2 diabetic patients that were recently diagnosed for T2D and exclusively on diet (without any pharmacological treatment). DNA was extracted from whole blood and DNA methylation was assessed using the Sequenom EpiTYPER system. Type 2 diabetic patients were more insulin resistant than their matched controls (mean HOMA IR 2.6 vs 1.8 in controls, P<0.001) and had a poorer beta-cell function (mean HOMA B 75.7 vs. 113.6 in controls, P<0.001). Results showed that 59% of the CpGs analyzed in TCF7L2 promoter had significant differences between type 2 diabetic patients and matched controls. In addition, fasting glucose, HOMA-B, HOMA-IR, total cholesterol and LDL-cholesterol correlated with methylation in specific CpG sites of TCF7L2 promoter. After adjustment by age, BMI, gender, physical inactivity, waist circumference, smoking status and diabetes status uniquely fasting glucose, total cholesterol and LDL-cholesterol remained significant. Taken together, newly diagnosed, drug-naïve type 2 diabetic patients display specific epigenetic changes at the TCF7L2 promoter as compared to age- and BMI-matched controls. Methylation in TCF7L2 promoter is further correlated with fasting glucose in peripheral blood DNA, which sheds new light on the role of epigenetic regulation of TCF7L2 in T2D.

Cross-sectional and longitudinal replication analyses of genome-wide association loci of type 2 diabetes in Han Chinese

This study aimed to examine genomic loci of type 2 diabetes (T2D) initially identified by genome-wide association studies in populations of European ancestry for their associations with T2D and quantitative glycemic traits, as well as their effects on longitudinal change in fasting plasma glucose (FPG) and T2D development, in the Chinese population. Single nucleotide polymorphisms (SNP) from 25 loci were genotyped in a large case-control sample of 10,001 subjects (5,338 T2D cases and 4,663 controls) and a prospective cohort of 1,881 Chinese. In the case-control sample, 8 SNPs in or near WFS1, CDKAL1, CDKN2A/2B, CDC123, HHEX, TCF7L2, KCNQ1, and MTNR1B were significantly associated with T2D (P<0.05). Thirteen SNPs were associated with quantitative glycemic traits. For example, the most significant SNP, rs10811661 near CDKN2A/2B (P = 1.11×10⁻⁸ for T2D), was also associated with 2-h glucose level of an oral glucose tolerance test (P = 9.11×10⁻³) and insulinogenic index (P = 2.71×10⁻²). In the cohort study, individuals carrying more risk alleles of the replicated SNPs had greater FPG increase and T2D incidence in a 7.5-year follow-up period, with each quartile increase in the number of risk alleles being associated with a 0.06 mmol/l greater increase in FPG (P = 0.03) and 19% higher odds of developing T2D (P = 0.058). Our study identified the associations of several established T2D-loci in Europeans with T2D and quantitative glycemic traits in the Chinese population. The prospective data also suggest their potential role in the risk prediction of T2D in the Chinese population.

Relationships between TCF7L2 genetic polymorphisms and polycystic ovary syndrome risk: a meta-analysis

OBJECTIVE

This meta-analysis was performed to evaluate the relationships between genetic polymorphisms in the TCF7L2 gene and polycystic ovary syndrome (PCOS) risk.

METHODS

The PubMed, Centralised Information Service for Complementary Medicine (CISCOM), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, Google Scholar, EBSCO, Cochrane Library, and Common Biorepository Model (CBM) databases were searched for relevant articles published before November 1st, 2013, without language restrictions. Meta-analysis was conducted using the STATA 12.0 software. The relationships were evaluated by calculating the pooled odds ratios (ORs) and their 95% confidence intervals (CIs). Seven case-control studies with a total 2458 PCOS patients and 5109 healthy subjects' met our inclusion criteria for qualitative data analysis. Two common polymorphisms (rs7903146 C→T and rs12255372 G→T) in the TCF7L2 gene were assessed.

RESULTS

The results of our meta-analysis suggested that TCF7L2 genetic polymorphisms might be strongly correlated with an increased risk of PCOS (allele model, OR=1.33, 95% CI=1.15-1.54, P<0.001; dominant model, OR=1.40, 95% CI=1.12-1.75, P=0.003), especially for the rs7903146 C→T polymorphism. A subgroup analysis was done to investigate the effect of ethnicity on an individual's risk of PCOS. Our results revealed positive significant correlations between TCF7L2 genetic polymorphisms and an increased risk of PCOS among Caucasians (allele model, OR=1.26, 95% CI=1.08-1.47, P=0.004; dominant model, OR=1.33, 95% CI=1.00-1.76, P=0.046) and Asians (allele model, OR=2.02, 95% CI=1.42-2.89, P<0.001; dominant model, OR=2.02, 95% CI=1.40-2.92, P<0.001), but not among Africans (all P<0.05).

CONCLUSIONS

Our findings provide convincing evidence that TCF7L2 genetic polymorphisms may contribute to susceptibility to PCOS, especially for the rs7903146 C→T polymorphism among Caucasians and Asians.

Parental history of type 2 diabetes, TCF7L2 variant and lower insulin secretion are associated with incident hypertension. Data from the DESIR and RISC cohorts

AIMS/HYPOTHESIS

The relationship between insulin secretion and the incidence of hypertension has not been well characterised. We hypothesised that both a parental history of diabetes and TCF7L2 rs7903146 polymorphism, which increases susceptibility to diabetes because of impaired beta cell function, are associated with incident hypertension. In a separate cohort, we assessed whether low insulin secretion is related to incident hypertension.

METHODS

Nine year incident hypertension was studied in 2,391 normotensive participants from the Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR) cohort. The relationship between insulin secretion and 3 year incident hypertension was investigated in 1,047 non-diabetic, normotensive individuals from the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) cohort. Insulin secretion during OGTT was expressed in relation to the degree of insulin resistance, as assessed by a hyperinsulinaemic-euglycaemic clamp.

RESULTS

In the DESIR cohort, a parental history of diabetes and the TCF7L2 at-risk variant were both associated with hypertension incidence at year 9, independently of waist circumference, BP, fasting glucose, insulin levels and HOMA-IR at inclusion (p = 0.02 for parental history, p = 0.006 for TCF7L2). In the RISC cohort, a lower insulin secretion rate during the OGTT at baseline was associated with both higher BP and a greater risk of hypertension at year 3. This inverse correlation between the insulin secretion rate and incident hypertension persisted after controlling for baseline insulin resistance, glycaemia and BP (p = 0.007).

CONCLUSIONS/INTERPRETATION

Parental history of diabetes, TCF7L2 rs7903146 polymorphism and a reduced insulin secretion rate were consistently associated with incident hypertension. A low insulin secretion rate might be a new risk factor for incident hypertension, beyond insulin resistance.

Importance of β-Catenin in glucose and energy homeostasis

In settings of increased insulin demand, failure to expand pancreatic β-cells mass leads to diabetes. Genome-wide scans of diabetic populations have uncovered several genes associated with susceptibility to type 2 diabetes and a number of them are part of the Wnt signaling. β-Catenin, a Wnt downstream effector participates in pancreatic development, however, little is known about its action in mature β-cells. Deletion of β-Catenin in Pdx1 pancreatic progenitors leads to a decreased β-cell mass and impaired glucose tolerance. Surprisingly, loss of β-catenin made these mice resistant to high fat diet because of their increased energy expenditure and insulin sensitivity due to hyperactivity. The complexity of this phenotype was also explained in part by ectopic expression of Cre recombinase in the hypothalamus. Our data implicates β-Catenin in the regulation of metabolism and energy homeostasis and suggest that Wnt signaling modulates the susceptibility to diabetes by acting on different tissues.

The involvement of the wnt signaling pathway and TCF7L2 in diabetes mellitus: The current understanding, dispute, and perspective

The Wnt signaling pathway was initially discovered for its role in tumorigenesis and the development of Drosophila and other eukaryotic organisms. The key effector of this pathway, the bipartite transcription factor β-cat/TCF, is formed by free β-catenin (β-cat) and a TCF protein, including TCF7L2. Extensive recent investigations have highlighted the role of the Wnt signaling pathway in metabolic homeostasis and its implication in diabetes and other metabolic diseases. Genome-wide association studies have shown that several key components of the Wnt signaling pathway are implicated in metabolic homeostasis and the development of type 2 diabetes (T2D). Despite controversial observations regarding the role of Wnt signaling in the development and function of pancreatic islets, the discovery of the association between certain single nucleotide polymorphisms of TCF7L2 and T2D susceptibility has fueled great efforts to explore the role of Wnt signaling in the function of pancreatic β-cells and glucose homeostasis. Here we have introduced our basic understanding of the canonical Wnt signaling pathway, summarized our current knowledge on its implication in metabolic homeostasis and T2D, discussed the work on TCF7L2 as a T2D susceptibility gene, and presented the controversial role of Wnt signaling and TCF7L2 in pancreatic islets as well as their potential metabolic function in other organs. We then expanded our view into the crosstalk among Wnt, insulin and FOXO signaling cascades, which further illustrates the complexity of the Wnt signaling pathway in metabolic homeostasis. Finally, we have presented our perspectives.

The role of the Wnt signaling pathway in incretin hormone production and function

Glucose metabolism is tightly controlled by multiple hormones and neurotransmitters in response to nutritional, environmental, and emotional changes. In addition to insulin and glucagon produced by pancreatic islets, two incretin hormones, namely glucagon-like peptide-1 (GLP-1) and gastric inhibitory polypeptide (GIP, also known as glucose-dependent insulinotropic peptide), also play important roles in blood glucose homeostasis. The incretin hormones mainly exert their regulatory effects via their corresponding receptors, which are expressed in pancreatic islets as well as many other extra-pancreatic organs. Recent studies have shown that the genes which encode these two incretin hormones can be regulated by the effectors of the Wnt signaling pathway, including TCF7L2, a transcription factor identified recently by extensive genome wide association studies as an important type 2 diabetes risk gene. Interestingly, TCF7L2 and β-catenin (β-cat), another effector of Wnt signaling pathway, may also mediate the function of the incretin hormones as well as the expression of their receptors in pancreatic β-cells. In this review, we have introduced the incretin hormones and the Wnt signaling pathway, summarized recent findings in the field, and provided our perspectives.

Effects of genetic susceptibility for type 2 diabetes on the evolution of glucose homeostasis traits before and after diabetes diagnosis: data from the D.E.S.I.R. Study

OBJECTIVE

To assess the impact of genetic susceptibility on evolution toward type 2 diabetes (T2D) by analyzing time trajectories of fasting glucose, glycated hemoglobin (HbA(1c)), insulin sensitivity (homeostasis model assessment [HOMA2%S]), and β-cell secretion (HOMA2%B) in a large nondiabetic cohort. We also examined whether baseline HbA(1c) modified the effect of genetic predisposition on the time trajectories.

RESEARCH DESIGN AND METHODS

Time trajectories were drawn in 4,744 participants from the French Data from an Epidemiological Study on the Insulin Resistance Syndrome (D.E.S.I.R.) cohort based on samples collected every 3 years over a 9-year follow-up. Trajectories were analyzed according to the TCF7L2 common variant, a family history of T2D, and a combination of at-risk alleles from nine T2D-associated genes.

RESULTS

There was a marked decrease in HOMA2%B in parallel to a steep increase in HbA(1c) over the 3 years before incident diabetes, which was not influenced by genetic predisposition when considered alone. However, after the onset of T2D, the TCF7L2 at-risk variant was associated with a greater decrease in HOMA2%B. There was a joint effect of a family history of T2D with the presence of the TCF7L2 risk allele with a greater rise in HbA(1c) conferred by the coexistence of a family history and the T risk allele. An HbA(1c) ≥5.7% at baseline was associated with a greater increase in both glycemia and HbA(1c) levels in the presence of a combination of diabetes at-risk alleles.

CONCLUSIONS

After incident T2D, TCF7L2 at-risk variants were associated with a faster decrease in β-cell function compared with those with the CC genotype. There was a joint effect of family history of T2D and TCF7L2 risk variant on the rise in glycemia and the decrease in insulin secretion at the end of follow-up, suggesting the joint influence of the combination of diabetes genetic predisposition with familial factors on the evolution of glycemia over time.

β-Cell failure in type 2 diabetes

Type 2 diabetic patients are insulin resistant as a result of obesity and a sedentary lifestyle. Nevertheless, it has been known for the past five decades that insulin response to nutrients is markedly diminished in type 2 diabetes. There is now a consensus that impaired glucose regulation cannot develop without insulin deficiency. First-phase insulin response to glucose is lost very early in the development of type 2 diabetes. Several prospective studies have shown that impaired insulin response to glucose is a predictor of future impaired glucose tolerance (IGT) and type 2 diabetes. Recently discovered type 2 diabetes-risk gene variants influence β-cell function, and might represent the molecular basis for the low insulin secretion that predicts future type 2 diabetes. We believe type 2 diabetes develops on the basis of normal but 'weak'β-cells unable to cope with excessive functional demands imposed by overnutrition and insulin resistance. Several laboratories have shown a reduction in β-cell mass in type 2 diabetes and IGT, whereas others have found modest reductions and most importantly, a large overlap between β-cell masses of diabetic and normoglycemic subjects. Therefore, at least initially, the β-cell dysfunction of type 2 diabetes seems more functional than structural. However, type 2 diabetes is a progressive disorder, and animal models of diabetes show β-cell apoptosis with prolonged hyperglycemia/hyperlipemia (glucolipotoxicity). β-Cells exposed in vitro to glucolipotoxic conditions show endoplasmic reticulum (ER) and oxidative stress. ER stress mechanisms might participate in the adaptation of β-cells to hyperglycemia, unless excessive. β-Cells are not deficient in anti-oxidant defense, thioredoxin playing a major role. Its inhibitor, thioredoxin-interacting protein (TXNIP), might be important in leading to β-cell apoptosis and type 2 diabetes. These topics are intensively investigated and might lead to novel therapeutic approaches. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2010.00094.x, 2011).

A validation study of type 2 diabetes-related variants of the TCF7L2, HHEX, KCNJ11, and ADIPOQ genes in one endogamous ethnic group of north India

The aim of this study was to validate the single nucleotide polymorphisms (SNPs) of four candidate genes (TCF7L2, HHEX, KCNJ11, and ADIPOQ) related to type 2 diabetes (T2D) in an endogamous population of north India; the Aggarwal population, having 18-clans. This endogamous population model was heavily supported by recent land mark work and we also verified the homogeneity of this population by clan-based stratification analysis. Two SNPs (rs4506565; rs7903146) in TCF7L2 were found to be significant (p-value = 0.00191; p-value = 0.00179, respectively), and odds ratios of 2.1 (dominant-model) and 2.0 (recessive-model) respectively, were obtained for this population. The TTT haplotype in the TCF7L2 gene was significantly associated with T2D. Waist-Hip ratio (WHR), systolic blood pressure (SBP), and age were significant covariates for increasing risk of T2D. Single-SNP, combined-SNPs and haplotype analysis provides clear evidence that the causal mutation is near to or within the significant haplotype (TTT) of the TCF7L2 gene. In spite of a culturally-learned sedentary lifestyle and fat-enriched dietary habits, WHR rather than body-mass-index emerged as a robust predictor of risk for T2D in this population.

Wnt signaling in pancreatic islets

The Wnt signaling pathway is critically important not only for stem cell amplification, differentiation, and migration, but also is important for organogenesis and the development of the body plan. Beta-catenin/TCF7L2-dependent Wnt signaling (the canonical pathway) is involved in pancreas development, islet function, and insulin production and secretion. The glucoincretin hormone glucagon-like peptide-1 and the chemokine stromal cell-derived factor-1 modulate canonical Wnt signaling in beta-cells which is obligatory for their mitogenic and cytoprotective actions. Genome-wide association studies have uncovered 19 gene loci that confer susceptibility for the development of type 2 diabetes. At least 14 of these diabetes risk alleles encode proteins that are implicated in islet growth and functioning. Seven of them are either components of, or known target genes for, Wnt signaling. The transcription factor TCF7L2 is particularly strongly associated with risk for diabetes and appears to be fundamentally important in both canonical Wnt signaling and beta-cell functioning. Experimental loss of TCF7L2 function in islets and polymorphisms in TCF7L2 alleles in humans impair glucose-stimulated insulin secretion, suggesting that perturbations in the Wnt signaling pathway may contribute substantially to the susceptibility for, and pathogenesis of, type 2 diabetes. This review focuses on considerations of the hormonal regulation of Wnt signaling in islets and implications for mutations in components of the Wnt signaling pathway as a source for risk-associated alleles for type 2 diabetes.

An automated reasoning framework for translational research

In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools. In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results.

Decreased TCF7L2 protein levels in type 2 diabetes mellitus correlate with downregulation of GIP- and GLP-1 receptors and impaired beta-cell function

Recent human genetics studies have revealed that common variants of the TCF7L2 (T-cell factor 7-like 2, formerly known as TCF4) gene are strongly associated with type 2 diabetes mellitus (T2DM). We have shown that TCF7L2 expression in the beta-cells is correlated with function and survival of the insulin-producing pancreatic beta-cell. In order to understand how variations in TCF7L2 influence diabetes progression, we investigated its mechanism of action in the beta-cell. We show robust differences in TCF7L2 expression between healthy controls and models of T2DM. While mRNA levels were approximately 2-fold increased in isolated islets from the diabetic db/db mouse, the Vancouver Diabetic Fatty (VDF) Zucker rat and the high fat/high sucrose diet-treated mouse compared with the non-diabetic controls, protein levels were decreased. A similar decrease was observed in pancreatic sections from patients with T2DM. In parallel, expression of the receptors for glucagon-like peptide 1 (GLP-1R) and glucose-dependent insulinotropic polypeptide (GIP-R) was decreased in islets from humans with T2DM as well as in isolated human islets treated with siRNA to TCF7L2 (siTCF7L2). Also, insulin secretion stimulated by glucose, GLP-1 and GIP, but not KCl or cyclic adenosine monophosphate (cAMP) was impaired in siTCF7L2-treated isolated human islets. Loss of TCF7L2 resulted in decreased GLP-1 and GIP-stimulated AKT phosphorylation, and AKT-mediated Foxo-1 phosphorylation and nuclear exclusion. Our findings suggest that beta-cell function and survival are regulated through an interplay between TCF7L2 and GLP-1R/GIP-R expression and signaling in T2DM.