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Transcription factor 7-like 2 polymorphism and context-specific risk of metabolic syndrome, type 2 diabetes, and dyslipidemia.

ABSTRACT: BACKGROUND:The transcription factor 7-like 2 gene (TCF7L2) is an element of the Wnt signaling pathway. There is lack of evidence if TCF7L2 has a functional role in lipid metabolism and regulation of the components constitutes the metabolic syndrome (MetSyn). The aims of this study were to evaluate whether the risk allele of TCF7L2 gene polymorphism is associated with dyslipidemia and MetSyn. MATERIALS AND METHODS:The MetSyn subjects were participated only based on the National Cholesterol Education Program - Third Adult Treatment Panel criteria. In this case-control study, the DNA from MetSyn patients without (n = 90) and with type 2 diabetes (T2D) (n = 94) were genotyped. RESULTS:The results show that the genotype-phenotype for CC, CT/TT of TCF7L2 gene polymorphism correlated with body mass index and waist circumference in MetSyn and MetSyn + T2D subjects (r = -0.949 and r = -0.963, respectively). The subjects that only possess MetSyn but are not diabetics show the 2 h postprandial glucose and fasting blood glucose, glycated hemoglobin significantly lower (P < 0.05) than those subjects have both abnormality. The level of triglyceride in CT/TT carriers in MetSyn was higher than CC carriers (P = 0.025). A comparison with the controls subjects, the frequencies of the T allele in the groups of MetSyn (46.66%) and MetSyn + T2D (47.34%) show significantly different (P < 0.05). The odds ratios for T allele in (MetSyn)/(normal), (MetSyn + T2D)/(normal), and in (MetSyn + T2D)/(MetSyn) were 3.59 (95% confidence interval [CI], 1.33-9.67, P = 0.0093), 3.76 (95% CI, 1.40-10.07, P = 0.0068), and 1.08 (95% CI: 0.55- 2.11, P = 0.834), respectively. CONCLUSION:The results revealed the important insights essential for the role of TCF7L2 that the T allele of TCF7L2 plays a significant role in the susceptibility to dyslipidemia, MetSyn, and T2D.

SUBMITTER: Palizban A

PROVIDER: S-EPMC5393097 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Transcription factor 7-like 2 polymorphism and context-specific risk of metabolic syndrome, type 2 diabetes, and dyslipidemia.

Palizban Abbasali A Rezaei Mahnaz M Khanahmad Hossein H Fazilati Mohammad M

Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences 20170315

<h4>Background</h4>The transcription factor 7-like 2 gene (TCF7L2) is an element of the Wnt signaling pathway. There is lack of evidence if TCF7L2 has a functional role in lipid metabolism and regulation of the components constitutes the metabolic syndrome (MetSyn). The aims of this study were to evaluate whether the risk allele of TCF7L2 gene polymorphism is associated with dyslipidemia and MetSyn.<h4>Materials and methods</h4>The MetSyn subjects were participated only based on the National Cho ...[more]

PMID: 28465699

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Project description:One of the goals of systems biology is the identification of regulatory mechanisms that govern an organism's response to external stimuli. Transcription factors have been hypothesized as a major contributor to an organism's response to various outside stimuli, and a great deal of work has been done to predict the set of transcription factors which regulate a given gene. Most of the current methods seek to identify possible binding sites from genomic sequence. Initial attempts at predicting transcription factors from genomic sequences suffered from the problem of false positives. Making the problem more difficult, it has also been shown that while predicted binding sites might be false positives, they can be shown to bind to their corresponding sequences in vitro. One method for rectifying this is through the use of phylogenetic analysis in which only regions which show high evolutionary conservation are analyzed. However such an approach may be too stringent because of the level of degeneracy shown in transcription factor binding site position weight matrices. Due to the degeneracy, there may be only a few bases that need to be conserved across species. Therefore, while a sequence may not show a high level of evolutionary conservation, these sequences may still show high affinity for the same transcription factor. In predicting transcription factor binding we explore the notion that "Co-expression implies co-regulation" [Allocco et al. BMC Bioinformatics 5:18, 2004]. With multiple genes requiring similar transcription factors binding sites, there exists a basis for eliminating false positives. This method allows for the selection of transcription factors binding sites that are active under a given experimental paradigm, thereby allowing us to indirectly incorporate the effects of chromosome and recognition site presentation upon transcription factor binding prediction. Rather than having to rationalize that a few transcription factors binding sites are over-represented in a cluster of genes, one can show that a few transcription factors are active in the cluster of genes that have been grouped together. Although the method focuses on predicting experiment-specific transcription factor binding sites, it is possible that if such a methodology were used in an iterative process where different experiments were analyzed, one could obtain a comprehensive set of transcription factors binding sites which regulate the various dynamic responses shown by biological systems under a variety of conditions hence building a more comprehensive model of transcriptional regulation.

Project description:PURPOSE:Serum immunoglobulins (Igs) play a critical role in modulating the immune response by neutralizing pathogens, although little is known about the effect of Igs in development of atherosclerotic cardiovascular disease (ASCVD). Elevated serum Immunoglobulin A (IgA) concentrations have been identified in previous studies in populations with obesity and hypertriglyceridemia, whereas variable concentrations of Immunoglobulin M (IgM) have been observed in the setting of dyslipidemia. METHODS:In this cross-sectional study, investigators examined the association of serum Ig concentrations with components of metabolic syndrome, including obesity, diabetes, and dyslipidemia. All consecutive adult patients aged 18?years or older discharged from two academic teaching hospitals with serum Immunoglobulin G (IgG) concentration measured during their admission were evaluated, with a total of 1809 individuals included and stratified into two groups: those with and those without dyslipidemia. RESULTS:Mean IgG concentration in individuals with and without dyslipidemia was 997?±?485?mg/dL and 1144?±?677?mg/dL, respectively (P?<? 0.0001). After controlling for confounders in the generalized linear model (GLM), the least square mean IgG concentration in individuals with and without dyslipidemia was 1095 and 1239?mg/dL, respectively (P?<? 0.0001). The mean IgA and IgM concentrations were not significantly different in individuals with and without dyslipidemia both before and after adjusting covariates. After controlling for confounding variables, all three serum Ig concentrations were not significantly different in individuals with and without diabetes. CONCLUSION:Dyslipidemia was associated with a lower mean serum IgG concentration. No association with any serum Ig was indentified in individuals with diabetes. Exploration of the association between alterations in serum Igs and metabolic syndrome and the role of alterations of Ig concentrations in disease progression represents an important step in identification of appropriate targeted treatment options for reducing cardiovascular risk.

Dataset Information

Transcription factor 7-like 2 polymorphism and context-specific risk of metabolic syndrome, type 2 diabetes, and dyslipidemia.

Publications

Transcription factor 7-like 2 polymorphism and context-specific risk of metabolic syndrome, type 2 diabetes, and dyslipidemia.

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