Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0011849 (diabetes)
 277,896 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Variants in the TCF7L2 gene have been associated with type 2 diabetes mellitus (T2DM), but the causal variant(s) is still unknown. We studied the TCF7L2 messenger RNA (mRNA) expression in paired samples of visceral and subcutaneous adipose tissue from 49 subjects using quantitative real-time polymerase chain reaction and its relation to obesity and T2DM. All subjects were genotyped for the previously described TCF7L2 diabetes risk variants. Independent of age, sex, obesity, and diabetes status, we found >3-fold higher TCF7L2 mRNA expression in subcutaneous compared with visceral adipose tissue. There was no correlation between visceral and subcutaneous TCF7L2 expression. No differences in adipose tissue TCF7L2 mRNA expression levels were found between diabetic and nondiabetic subjects, or between lean and obese subjects (all Ps > .05). In addition, there was no association between TCF7L2 genetic variants and mRNA expression. Based on our data, TCF7L2 mRNA expression is fat-depot specific but does not seem to provide the mechanistic link explaining genetic association with T2DM.
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PMID:TCF7L2 gene expression in human visceral and subcutaneous adipose tissue is differentially regulated but not associated with type 2 diabetes mellitus. 1870 48

Type 2 diabetes is one of the fastest growing public health problems worldwide. Both environmental (e.g. physical activity, obesity, and diet) and genetic factors are involved in the development of type 2 diabetes. The associations between physical activity and diabetes risk have been assessed by a number of prospective studies and clinical trials. The results from these studies consistently indicate that the regular physical activity during occupation, commuting, leisure time or daily life reduces the risk of type 2 diabetes by 15-60%; and lifestyle intervention, including counselling for physical activity, nutrition, and body weight, can reduce the risk of type 2 diabetes by 40-60% among adults with impaired glucose tolerance and by about 20% among general individuals. In the past decade, studies using traditional linkage analysis and candidate-gene association approach have found dozens of genes harboring common variants that were related to the common-form type 2 diabetes. However, most reported associations are lack of reproducibility, except TCF7L2, PPARG, CAPN10, and KCNJ11. Since 2007, seven genome-wide association (GWA) studies emerged to generate a list of new diabetes genes. The genetic effects are largely of moderate size. These findings provide novel insight into the diabetes etiology and pave new avenue for predicting the disease risk using genetic information. In addition, data especially those from intervention trials display preliminary but promising evidence that the genetic variants might interact with physical activity in predisposing to type 2 diabetes. The gene-environment interactions merit extensive exploration in large, prospective studies.
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PMID:Genes, environment, and interactions in prevention of type 2 diabetes: a focus on physical activity and lifestyle changes. 1878 59

Interest in the importance of Wnt signaling in diabetes has risen after identification of the transcription factor TCF7L2, a component of this pathway, as a strong risk factor for type 2 diabetes. Here, we review emerging new evidence that Wnt signaling influences endocrine pancreas development and modulates mature beta-cell functions including insulin secretion, survival and proliferation. Alterations in Wnt signaling might also impact other metabolic tissues involved in the pathogenesis of diabetes, with TCF7L2 proposed to modulate adipogenesis and regulate GLP-1 production. Together, these studies point towards a role for Wnt signaling in the pathogenesis of type 2 diabetes, highlighting the importance of further investigation of this pathway to develop new therapies for this disease.
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PMID:Wnt signaling: relevance to beta-cell biology and diabetes. 1892 17

TCF7L2, HHEX and IDE on chromosome 10q23-25 reside within the linkage region for type 2 diabetes (T2D). Previous studies including ours have demonstrated that genetic polymorphisms in these three loci are associated with T2D, respectively. But, it is unclear whether TCF7L2, independently or interactively with HHEX and IDE, confer the susceptibility to T2D. In the present study, we first replicated genetic association study of the TCF7L2 gene in a Swedish cohort including 528 non-diabetic healthy controls and 243 T2D patients and then evaluated combining effect from common risk polymorphisms in TCF7L2-HHEX-IDE loci. T2D patients were diagnosed in the intermediate study time. To avoid influence from anti-diabetic treatment, baseline data in all T2D patients were used for analysis. We found that SNPs rs7901695, rs4506565, rs7903146 and rs12255372 in the TCF7L2 gene were strongly associated with T2D (p<0.004). In rs7903146, T2D patients carrying genotypes CT or TT had higher fasting plasma glucose (FPG) levels (p=0.042) and lower HOMA-beta index (p=0.015) and BMI (p=0.015) compared to the patients carrying CC genotype. Furthermore, the risk alleles from TCF7L2 rs7903146 polymorphism either with IDE rs2251101 polymorphism (p=0.0257, OR=1.398) or with HHEX rs1544210 polymorphism (p=0.0024, OR=1.514) were significantly associated with T2D. When risk alleles from three loci were combined, the association with T2D remained significant (p=0.0018, OR=1.506). The present study thus provides evidence that TCF7L2, as the main gene, together with HHEX and IDE loci have combining effects on genetic predisposition to T2D.
Exp Clin Endocrinol Diabetes 2009 Apr
PMID:Loci of TCF7L2, HHEX and IDE on chromosome 10q and the susceptibility of their genetic polymorphisms to type 2 diabetes. 1905 27

Several single nucleotide polymorphisms (SNPs) for type 2 diabetes mellitus (T2DM) risk have been identified by genome wide association studies (GWAS). The objective of the present study was to investigate the impact of these SNPs on T2DM intermediate phenotypes in order to clarify the physiological mechanisms through which they exert their effects on disease etiology. We analysed 23 SNPs in 9 T2DM genes (CDKAL1, CDKN2B, HHEX/IDE, IGF2BP2, KCNJ11, SLC30A8, TCF2, TCF7L2 and WFS1) in a maximum of 712 men and women from the Quebec Family Study. The participants underwent a 75 g oral glucose tolerance test (OGTT) and were measured for glucose, insulin and C-peptide levels. Indices of insulin sensitivity and insulin secretion were derived from fasting and OGTT measurements. We confirmed the significant associations of variants in CDKAL1, CDKN2B, HHEX/IDE, KCNJ11 and TCF7L2 with insulin secretion and also found associations of some of these variants with insulin sensitivity and glucose tolerance. IGF2BP2 and SLC30A8 SNPs were not associated with insulin secretion but were with insulin sensitivity and glucose tolerance (0.002 <or= P <or= 0.02). To examine the joint effects of these variants and their contribution to T2DM endophenotypes variance, stepwise regression models were used and the model R (2) was computed. The variance in the phenotypes explained by combinations of variants ranged from 2.0 to 8.5%. Diabetes-associated variants in CDKAL1, CDKN2B, HHEX/IDE, IGF2BP2, KCNJ11, SLC30A8 and TCF7L2 are associated with physiological alterations leading to T2DM, such as glucose intolerance, impaired insulin secretion or insulin resistance, supporting their role in the disease aetiology. These variants were found to account for 2.0-8.5% of the variance of T2DM-related traits.
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PMID:Association between insulin secretion, insulin sensitivity and type 2 diabetes susceptibility variants identified in genome-wide association studies. 1908 21

The Wnt pathway effector gene TCF7L2 has been linked to type II diabetes, making it important to study the role of Wnt signaling in diabetes pathogenesis. We examined the expression of multiple Wnt pathway components in pancreases from normal individuals and type II diabetic individuals. Multiple members of the Wnt signaling pathway, including TCF7L2, Wnt2b, beta-catenin, pGSK3beta, TCF3, cyclinD1, and c-myc, were undetectable or expressed at low levels in islets from nondiabetic individuals, but were also upregulated specifically in islets of type II diabetic patients. Culture of pancreatic tissue and islet isolation led to Wnt activation that was reversed by the Wnt antagonist sFRP, demonstrating that Wnt activation in that setting was due to soluble Wnt factors. These data support a model in which the Wnt pathway plays a dynamic role in the pathogenesis of type II diabetes and suggest manipulation of Wnt signaling as a new approach to beta-cell-directed diabetes therapy.
Exp Diabetes Res 2008
PMID:Islet specific Wnt activation in human type II diabetes. 1916 45

The success of genome-wide association studies (GWAS) to identify risk loci of complex diseases is now well-established. One persistent major hurdle is the cost of those studies, which make them beyond the reach of most research groups. Performing GWAS on pools of DNA samples may be an effective strategy to reduce the costs of these studies. In this study, we performed pooling-based GWAS with more than 550,000 SNPs in two case-control cohorts consisting of patients with Type II diabetes (T2DM) and with chronic rhinosinusitis (CRS). In the T2DM study, the results of the pooling experiment were compared to individual genotypes obtained from a previously published GWAS. TCF7L2 and HHEX SNPs associated with T2DM by the traditional GWAS were among the top ranked SNPs in the pooling experiment. This dataset was also used to refine the best strategy to correctly identify SNPs that will remain significant based on individual genotyping. In the CRS study, the top hits from the pooling-based GWAS located within ten kilobases of known genes were validated by individual genotyping of 1,536 SNPs. Forty-one percent (598 out of the 1,457 SNPs that passed quality control) were associated with CRS at a nominal P value of 0.05, confirming the potential of pooling-based GWAS to identify SNPs that differ in allele frequencies between two groups of subjects. Overall, our results demonstrate that a pooling experiment on high-density genotyping arrays can accurately determine the minor allelic frequency as compared to individual genotyping and produce a list of top ranked SNPs that captures genuine allelic differences between a group of cases and controls. The low cost associated with a pooling-based GWAS clearly justifies its use in screening for genetic determinants of complex diseases.
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PMID:Identification of susceptibility genes for complex diseases using pooling-based genome-wide association scans. 1918 12

Prediction of the disease status is one of the most important objectives of genetic studies. To select the genes with strong evidence of the association with type 2 diabetes mellitus, we validated the associations of the seven candidate loci extracted in our earlier study by genotyping the samples in two independent sample panels. However, except for KCNQ1, the association of none of the remaining seven loci was replicated. We then selected 11 genes, KCNQ1, TCF7L2, CDKAL1, CDKN2A/B, IGF2BP2, SLC30A8, HHEX, GCKR, HNF1B, KCNJ11 and PPARG, whose associations with diabetes have already been reported and replicated either in the literature or in this study in the Japanese population. As no evidence of the gene-gene interaction for any pair of the 11 loci was shown, we constructed a prediction model for the disease using the logistic regression analysis by incorporating the number of the risk alleles for the 11 genes, as well as age, sex and body mass index as independent variables. Cumulative risk assessment showed that the addition of one risk allele resulted in an average increase in the odds for the disease of 1.29 (95% CI=1.25-1.33, P=5.4 x 10(-53)). The area under the receiver operating characteristic curve, an estimate of the power of the prediction model, was 0.72, thereby indicating that our prediction model for type 2 diabetes may not be so useful but has some value. Incorporation of data from additional risk loci is most likely to increase the predictive power.
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PMID:Construction of a prediction model for type 2 diabetes mellitus in the Japanese population based on 11 genes with strong evidence of the association. 1924 72

This review focuses on current evidence for pharmacogenetics for the 3 commonly used drug classes in treating diabetes: metformin, sulphonylureas and thiazolidinediones. Currently, metformin pharmacogenetics is focussing on drug transport with the recent finding that variation in OCT transporters might affect metformin response. An aetiological approach has identified monogenic patients with diabetes due to TCF1 mutations who are particularly sensitive to the hypoglycaemic effects of sulphonylureas, and KCNJ11 or ABCC8 mutations in which sulphonylureas can be used in place of insulin treatment. In Type 2 diabetes sulphonylurea response has been shown to be associated with variants TCF7L2 associated with type 2 diabetes risk. For thiazolidinediones, focus has been on PPARgamma variants although with no consistent result. Genome wide association studies offer great potential to unravel what genetic factors influence response and side effects of diabetes therapies. Large numbers of well phenotyped patients for response and side effect as well as similarly sized similarly phenotyped replication cohorts are required. Establishing such cohorts is a priority in diabetes pharmacogenetics research.
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PMID:Pharmacogenetics and future strategies in treating hyperglycaemia in diabetes. 1927 54

Genetic variation can impact on efficacy and risk of adverse events to commonly used oral agents in -diabetes. Metformin is not metabolized and its mechanism of action remains debated; however, several cation transporters have been identified. Variation in these pharmacokinetic genes might influence metformin response. Conversely, although the cytochrome P450 system has been implicated in sulfonylurea response in some small studies, to date variants affecting pharmacodynamics, including those in ABCC8 (SUR1) and TCF7L2, are the most promising. For thiazolidinedione response, variants in PPARG or ADIPOQ (adiponectin) have been variably associated with response. With increasing well-phenotyped cohorts and new methods, including genome-wide association studies, the next few years offer great hope to use pharmacogenetics to unravel drug and disease mechanisms, as well as the possibility to individualize therapy by genotype.
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PMID:Pharmacogenetics in diabetes. 1932 63


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