TCF7L2 rs7903146 polymorphism and diabetic nephropathy association is not independent of type 2 diabetes--a study in a south Indian population and meta-analysis

The genetic side of diabetic kidney disease: a review

BACKGROUND

Diabetic kidney disease (DKD) is one of the most common complications of diabetes, with approximately 30-40% of patients with type 1 diabetes mellitus and 20% of patients with type 2 diabetes mellitus eventually developing DKD. If DKD is not controlled in the early clinical stage and proteinuria develops, the disease will progress to end-stage renal disease. The pathogenesis of DKD remains largely unknown and is multifactorial, likely due to interactions between genetic and environmental factors. Familial clustering also supports a critical role of hereditary factors in DKD. The development of gene detection technology has promoted the exploration of DKD susceptibility genes in different cohorts of patients with diabetes. Identifying susceptibility genes can provide insights into the pathogenesis of DKD, as well as a basis for its clinical diagnosis and therapy.

RESULTS

Numerous candidate gene loci have been found to be associated with DKD, many of which play critical regulatory roles in the pathogenesis of this disease, including genes involved in glycol-metabolism, lipid metabolism, the renin-angiotensin-aldosterone system, inflammation and oxidative stress. In this review, we summarize the functions of several susceptibility genes involved in the development of DKD.

CONCLUSION

Based on our findings, we recommend that studying susceptibility gene polymorphisms can lead to a better understanding of the pathogenesis of DKD and could help prevent this disease or improve its outcomes.

Transcription factor 7-like 2 gene- smoking interaction on the risk of diabetic nephropathy in Chinese Han population

Objectives

To evaluate the relationship between transcription factor 7-like 2 (TCF7L2) gene polymorphism and diabetic nephropathy (DN) risk, as well as the effect of gene-environment interactions on DN risk in Chinese Han population.

Methods

The Hardy-Weinberg equilibrium (HWE) and the relationship between TCF7L2 gene single nucleotide polymorphism (SNPs) and DN susceptibility were evaluated by SNPStats. The interaction among four SNPs and environmental factors were tested by generalized multifactor dimensionality reduction (GMDR). The consistency of cross validation, accuracy of test balance and sign test were calculated to evaluate the interaction of each selection. The logistic regression was used to test the interaction between rs7903146 and current smoking by stratified analysis.

Results

Logistic regression analysis indicated that the DN risk of rs7903146-T allele carriers were obviously higher than that in CC genotype carriers (CT + TT versus CC), adjusted OR (95 %CI) = 1.64 (1.24–2.06). However, we also discovered that people with rs12255372, rs11196205 and rs290487 minor allele had non-significant difference risk of DN compared with people with major allele. The GMDR model found a significant two-locus model (p = 0.0100) including rs7903146 and current smoking, suggesting a potential gene–environment interaction between rs7903146 and current smoking. Compared with never smokers with rs7903146- CC genotype, current smokers with rs7903146- CT or TT genotype had the highest DN risk. After covariate adjustment, OR (95 %CI) was 2.15 (1.58–2.78).

Conclusions

We found a significant relationship of rs7903146-T alleles, and the interaction between rs7903146-T and current smoking with increased DN risk.

Potpourri: An Epistasis Test Prioritization Algorithm via Diverse SNP Selection

Genome-wide association studies (GWAS) explain a fraction of the underlying heritability of genetic diseases. Investigating epistatic interactions between two or more loci help to close this gap. Unfortunately, the sheer number of loci combinations to process and hypotheses prohibit the process both computationally and statistically. Epistasis test prioritization algorithms rank likely epistatic single nucleotide polymorphism (SNP) pairs to limit the number of tests. However, they still suffer from very low precision. It was shown in the literature that selecting SNPs that are individually correlated with the phenotype and also diverse with respect to genomic location leads to better phenotype prediction due to genetic complementation. Here, we propose that an algorithm that pairs SNPs from such diverse regions and ranks them can improve prediction power. We propose an epistasis test prioritization algorithm that optimizes a submodular set function to select a diverse and complementary set of genomic regions that span the underlying genome. The SNP pairs from these regions are then further ranked w.r.t. their co-coverage of the case cohort. We compare our algorithm with the state of the art on three GWAS and show that (1) we substantially improve precision (from 0.003 to 0.652) while maintaining the significance of selected pairs, (2) decrease the number of tests by 25-fold, and (3) decrease the runtime by 4-fold. We also show that promoting SNPs from regulatory/coding regions improves the performance (up to 0.8). Potpourri is available at http:/ciceklab.cs.bilkent.edu.tr/potpourri.

GenPop-An Online Tool to Analyze Human Population Genetic Data

GenPop is a web based online cross platform tool developed to help Geneticist and Epidemiologist to deal with association studies in analyzing human population genetic data. The tool features include descriptive analysis such as Hardy-Weinberg equilibrium test, chi-square p-value and analysis of single nucleotide polymorphisms (SNPs) with multiple inheritance models such as dominant, recessive, allelic, genotype, odd's ratio and relative risk at 95% confidence interval and analysis of multiple SNPs including haplotype frequencies and linkage disequilibrium for a pair of biallelic markers. This is a user-driven human population genetic data analysis tool that is easily scalable and acceptable with multiple implementations of different algorithms. GenPop has been developed using PHP, JavaScript and with PHPExcel library to analyse the genetic data for case control studies.

Associations of TCF7L2 gene polymorphisms with the risk of diabetic nephropathy: A case-control study

The aim of the study was to explore the correlation between rs7903146 and rs290487 polymorphisms in transcription factor 7-like 2 (TCF7L2) gene and diabetic nephropathy (DN) in Chinese Han population.Polymerase chain reaction-restriction fragment length polymorphism was used to determine genotypes of TCF7L2 polymorphisms in 90 patients with DN and 96 diabetes patients without DN. The linkage disequilibrium (LD) and haplotype analysis were performed with haploview software. Hardy-Weinberg equilibrium was assessed in the control group based on the genotype distributions of TCF7L2 polymorphisms. The genotype, allele, and haplotype distribution differences between the case and control groups were analyzed by chi-squared test, and odds ratio (OR) and 95% confidence interval (CI) were used to indicate the relative risk of DN.People carrying TT genotype of rs7903146 were more easily to be attacked by DN than CC genotype carriers (P = .02, OR = 4.26, 95% CI = 1.12-16.24). Meanwhile, T allele also showed 1.85 times risk to suffer from DN compared with C allele (OR = 1.85, 95% CI = 1.02-3.10). However, there was no significant difference in genotypes and alleles frequencies of rs290487 between 2 groups. The strong LD existed between the 2 single nucleotide polymorphisms and haplotype T-T (rs7903146-rs290487) increased the susceptibility to DN (OR = 2.63, 95% CI = 1.31-5.25).TCF7L2 rs7903146 polymorphism may be associated with the susceptibility to DN in Chinese Han population, but rs290487 is not. Additionally, haplotype is also a risk factor for DN.

The Susceptibility Genes in Diabetic Nephropathy

Background

Diabetes mellitus (DM) poses a severe threat to global public health. Diabetic nephropathy (DN) is one of the most common complications of diabetes and the leading cause of end-stage renal disease (ESRD). Approximately 30-40% of DM patients in the world progress to ESRD, which emphasizes the effect of genetic factors on DN. Family clustering also supports the important role of hereditary factors in DN and ESRD. Therefore, a large number of genetic studies have been carried out to identify susceptibility genes in different diabetic cohorts. Extensive susceptibility genes of DN and ESRD have not been identified until recently.

Summary and Key Messages

Some of these associated genes function as pivotal regulators in the pathogenesis of DN, such as those related to glycometabolism and lipid metabolism. However, the functions of most of these genes remain unclear. In this article, we review several susceptibility genes according to their genetic functions to make it easier to determine their exact effect on DN and to provide a better understanding of the advancements from genetic studies. However, several challenges associated with investigating the genetic factors of DN still exist. For instance, it is difficult to determine whether these variants affect the expression of the protein they encode or other cytokines. More efforts should be made to determine how these genes influence the progression of DN. In addition, many results could not be replicated among races, suggesting that the association between genetic polymorphisms and DN is race-specific. Therefore, large, well-designed studies involving more relevant variables and ethnic groups and more relevant functional studies are urgently needed. These studies may be beneficial and retard the progression of DN by early intervention, especially for patients who carry certain risk alleles or genotypes.

Meta-analysis of association between TCF7L2 polymorphism rs7903146 and type 2 diabetes mellitus

BACKGROUND

Large scale association studies have found a significant association between type 2 diabetes mellitus (T2DM) and transcription factor 7-like 2 (TCF7L2) polymorphism rs7903146. However, the quality of data varies greatly, as the studies report inconsistent results in different populations. Hence, we perform this meta-analysis to give a more convincing result.

METHODS

The articles, published from January 1st, 2000 to April 1st, 2017, were identified by searching in PubMed and Google Scholar. A total of 56628 participants (34232 cases and 22396 controls) were included in the meta-analysis. A total of 28 studies were divided into 4 subgroups: Caucasian (10 studies), East Asian (5 studies), South Asian (5 studies) and Others (8 studies). All the data analyses were analyzed by the R package meta.

RESULTS

The significant association was observed by using the dominant model (OR = 1.41, CI = 1.36 - 1.47, p < 0.0001), recessive model (OR = 1.58, CI = 1.48 - 1.69, p < 0.0001), additive model(CT vs CC) (OR = 1.34, CI = 1.28-1.39, p < 0.0001), additive model(TT vs CC) (OR = 1.81, CI = 1.69-1.94, p < 0.0001)and allele model (OR = 1.35, CI = 1.31-1.39, p < 0.0001).

CONCLUSION

The meta-analysis suggested that rs7903146 was significantly associated with T2DM in Caucasian, East Asian, South Asian and other ethnicities.

Association of the Transcription Factor 7 Like 2 (TCF7L2) Polymorphism With Diabetic Nephropathy Risk: A Meta-Analysis

It is assumed that genetic factors may participate in the development of diabetic nephropathy (DN). The association between TCF7L2 gene polymorphism and DN risk is still unclear. To evaluate the relationship, we performed this meta-analysis. Eligible relevant studies were searched and selected from PubMed, Embase, and ISI Web of Science. Summary effect estimates were derived using a random effects model, with attention to study quality and publication bias. Ethnical approval was not necessary, because this meta-analysis was based on published articles, and did not involve patient consent. A total of 7 studies were identified. Analysis of all studies indicated significant association between TCF7L2 gene polymorphism and DN risk (odds ratio [OR] = 1.31, 95% confidence interval (CI) = 1.10-1.56, Pheterogeneity < 0.00001, P = 0.002). Subgroup analysis showed similar results in Asian (OR = 1.33, 95% CI = 1.10-1.62, Pheterogeneity = 0.03, P = 0.004), in Caucasian (OR = 2.27, 95% CI = 1.78-2.90, Pheterogeneity = 0.17, P < 0.00001), in rs7903146 mutation (OR = 1.61, 95% CI = 1.25-2.07, Pheterogeneity < 0.00001, P = 0.0002), However, no association was observed in Negroid (OR = 1.10, 95% CI = 0.90-1.35, Pheterogeneity < 00001, P = 0.36). Our results suggest that TCF7L2 gene polymorphism may contribute to the risk of DN. However, more studies should be launched in the future.

Type 2 Diabetes Mellitus and the Association of Candidate Genes in Asian Indian Population from Hyderabad, India

INTRODUCTION

Genetic and environmental factors play an important role in susceptibility to type 2 diabetes mellitus (T2DM). Several genes have been implicated in the development of T2DM. Genetic variants of candidate genes are, therefore, prime targets for molecular analysis.

AIM

In this study, we have selected 3 candidate genes, namely, TCF7L2, SLC30A8, and IGF2, for assessing their association with T2DM in an Indian population.

MATERIALS AND METHODS

Five hundred individuals were enrolled in this case-control study- 250 T2DM patients and 250 healthy control individuals. Clinical characteristics were obtained for all subjects, and genotype analysis was performed by PCR-RFLP analysis.

RESULTS

Allele and genotyping frequencies, odds ratios, and 95% confidence intervals were calculated for 3 single nucleotide polymorphisms (SNPs), 1 each from TCF7L2 (rs7903146), SLC30A8 (rs13266634), and IGF2 (rs680) in T2DM patients. The rs7903146 and rs680 polymorphisms were found to be significantly associated with T2DM (p < 0.05), whereas the rs13266634 polymorphism was not (p > 0.05). The multifactor dimensionality reduction method identified the particular polymorphisms associated with an increased risk of disease.

CONCLUSION

The present study indicated that the gene-gene interaction model successfully predicted T2DM risk based on TCF7L2 and SLC30A8 polymorphisms. These results provide strong evidence of independent association between T2DM and the 3 SNPs analysed herein.

Association of TCF7L2 Polymorphism with Diabetic Nephropathy in the South Indian Population

The transcription factor 7-like 2 (TCF7L2) gene plays a significant role in the development of type 2 diabetes and diabetic nephropathy. The aim of this study was to investigate the association of TCF7L2 rs12255372 (G/T)polymorphism with type 2 diabetic nephropathy in the South Indian population. A total of 2102 subjects, 927 normal glucose tolerant (NGT) subjects, 598 type 2 diabetic subjects without nephropathy (DM), and 577 type 2 diabetic subjects with nephropathy (DN) were genotyped by MassARRAY. As compared to the NGT group, the odds ratio (adjusted for age, sex, BMI, HbA1c, and systolic BP) computed for the GT/TT genotype taking the GG genotype as reference was found to be 2.02 (95% CI: 1.16-3.51, p = 0.013) for DN and 1.94 (95% CI: 1.36-2.78, p = 0.0002) for DM. The genotype frequency was not significantly different between the DM and DN groups. In conclusion, the rs12255372 polymorphism in the TCF7L2 gene is associated with type 2 diabetes and DN but its association with DN is mediated through diabetes.

Validation of the association of TCF7L2 and SLC30A8 gene polymorphisms with post-transplant diabetes mellitus in Asian Indian population

The rs7903146 and rs13266634 polymorphisms in the TCF7L2 and SLC30A8 genes, respectively, have been reported to be associated with type 2 diabetes. However, little is known about the association of these polymorphisms with post-transplant diabetes mellitus (PTDM). To study this linkage, we determined a distribution of allele and genotype frequencies in Asian Indians. 42 PTDM and 98 non-PTDM subjects were recruited. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis was performed to detect for rs7903146 and rs13266634 polymorphisms. The clinical details and statistical analysis for PTDM and non-PTDM subjects were recorded. Our results observed higher frequencies of the minor alleles in rs7903146 and rs13266634 polymorphisms in the PTDM group compared to the non-PTDM subjects. The allele frequencies also found to be significantly associated with PTDM (rs7903146: T vs C: OR-2.6; (95%CI: 1.2-5.6); p = 0.01; rs13266634: T vs C: OR-2.0; (95%CI: 1.1-3.4); p = 0.01). These findings suggest that rs7903146 and rs13266634 polymorphisms are associated with PTDM in the Asian Indian population despite a relatively small study group.