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INTRODUCTION
Diabetes mellitus is a worldwide public health concern. This condition causes increased blood glucose level, lipid, carbohydrate, protein metabolism disturbance, and absolute or relative insulin deficiency. Type 2 diabetes mellitus (T2DM) is the most common metabolic disease in which genetic and environmental factors contribute to its development. In fact, this condition is the final stage of a chronic and progressive disorder resulting from insulin resistance, decreased pancreatic β-cell function, and increased glucose production by the liver. T2DM is currently diagnosed as a blood glucose level rate higher than normal or clinical manifestation of diabetes symptoms [1]. Studies have shown that insulin resistance develops a decade before T2DM clinically manifests [2]. Insulin resistance is a pathological condition in which the target cells, particularly muscle cells and adipose tissues, decrease their insulin response. Pancreatic β-cells increase insulin secretion to maintain glucose homeostasis [3].
Excess insulin secretion from pancreatic cells can control blood glucose in the early stages of T2DM. However, compensatory insulin is not enough to control the blood glucose level. Over time, patients show impaired glucose tolerance (IGT) and finally present with T2DM and β-cell deficiency [4]. All types of diabetes with IGT are insulin resistant. Insulin resistance is involved in pathogenic disorders, such as hypertension, dyslipidemia, T2DM, obesity, fatty liver disease, and cardiac diseases. These disorders combine to comprise metabolic syndromes (insulin-resistance syndromes) [5].
T2DM is a multifactorial, polygenic disease. Diverse genetic loci are involved in the susceptibility to this disease. Environmental factors, such as nutrition and physical activity, are also responsible for the T2DM phenotype [67]. Simultaneous T2DM incidence in identical twins is estimated to be 70% to 90% [89]. A higher risk of diabetes in infants is present if either parent suffers from T2DM. The risk increases to 40% in children if both parents are affected [10]. Insulin resistance appears by reduced glucose utilization in skeletal muscles. This condition is present in many non-diabetic, first-degree relatives of patients with T2DM [11].
Detection of genetic susceptibility to T2DM can be effective for prevention. Several genes are involved in the physiopathology of T2DM. Grant et al. [11] found that gene variants of transcription factor 7-like 2 (TCF7L2) showed strong associations with the risk of T2DM (combined odds ratio, 1.56; P=4.7) in subjects from Iceland, Denmark, and the United States.
The TCF7L2 gene has been shown to be the most important gene for diabetes susceptibility in European populations. In fact, each copy of the allele in the diabetes susceptibility gene increases the risk of diabetes 1.4- to 1.5-fold. The encoded TCF7L2 gene is a transcription factor and member of the Wnt signaling pathway [12]. High levels of this transcription factor have been reported in most human tissues, including the heart, lung, brain, liver, kidney, placenta, adipose tissues, and pancreatic β-cells [13].
Lyssenko et al. [14] found that single nucleotide polymorphisms (SNPs) rs12255372 and rs7903146 in TCF7L2 have strong associations with T2DM risk. Risk alleles of these genes are associated with dysfunction in pancreatic β-cells in all subjects [11]. The aim of this study was to evaluate the prevalence of SNPs and their relationship with the incidence of T2DM in the Iranian city of Jahrom. Findings were presented to health administrators and university authorities to help prevent T2DM as efficiently as possible.
METHODS
Patient characteristics
The number of participants selected for this cross-sectional study was determined using statistical methods. All subjects were selected using convenience sampling. The study group comprised 200 diabetic patients who were referred to clinics in Jahrom. The control population comprised 200 healthy individuals. All participants resided in the Persian-speaking region of Jahrom. Population demographics are highly homogenous in this area, and subjects in this study included just one ethnic group.
Age, sex, high density lipoprotein (HDL) level, low density lipoprotein (LDL) level, cholesterol, and fasting blood sugar (FBS) were measured and recorded in a questionnaire. A 5 mL blood sample was then collected in ethylenediaminetetraacetic acid tubes and stored at -20℃ for DNA extraction.
Biochemical analysis
Height and weight were measured to calculate body mass index (BMI). Blood samples were obtained after 12 hours of fasting. FBS and standard oral glucose tolerance tests were performed to diagnose T2DM.
Serum levels of HDL-cholesterol, total cholesterol (TC), and triglyceride (TG) were determined by standard methods and commercial kits (Pars Azmon, Tehran, Iran). LDL-cholesterol was calculated based on the Friedewald formula.
After 12 hours of fasting, 5 mL of venous blood was drawn from each of the subjects. Half of the blood sample was used for biochemical evaluation, and the other half for DNA extraction. DNA was extracted from nucleated blood cells, according to the DNA extraction kit (Sinagen Co., Tehran, Iran). DNA was quantified spectrophotometrically prior to being used in the polymerase chain reaction (PCR).
PCR was performed in PCR premix pipes, manufactured by Bioneer Co. (Daejeon, Korea). The reaction contained MgCl2 solution 1.5 µM, dNTP each 250 µM, and 0.2 µL (1 unit) Taq polymerase enzyme, DNA template 2.5 µL, 10 pmol primers each, and sterile water to 20 µL total reaction volume.
PCR was performed using a thermal cycler (Eppendorf, Hamburg, Germany). PCR cycling conditions included initial denaturation at 95℃ for 5 minutes, 35 cycles of denaturation at 95℃ for 30 seconds, annealing at 59℃ for 45 seconds, rs7903146 and rs1255372 polymorphisms at 55℃ for 40 seconds, extension at 72℃ for 30 seconds, and final extension at 72℃ for 5 minutes. Oligonucleotide primers were ordered from the Bioneer Co., based on the GenBank sequence database (National Centre for Biotechnology Information). Sequence of TCF7L2 gene containing two polymorphisms were investigated, using PCR amplification with specific primers rs7903146(C/T) F :5'-AAGAGAAGATTCCTTTTTAAATGGTG-3, R: 5'-CCTCATACGGCAATTAAATTATACA-3 and rs12255372(G/T) polymorphism F: 5'-CTGGAAACTAAGGCGTGAGG-3', R: 5'-GGGTCGATGTTGTTGAGCTT-3' F: 5'_GGTGGACTTGACTTTACTGG-3' and R: 5'_TAGAAGCAGCCTGGAGAA-3' was used. The final PCR product was analyzed on 2% agarose gel stained with ethidium bromide. To detect the rs7903146 (C/T) polymorphism, HpyCH4III restriction enzyme was used. SNP rs12255372 (G/T) could also be detected by Tsp509I restriction enzymes. In the presence of polymorphisms in 1 and 2 amplicons, the sequence of enzyme cutting sites could not be detected by restriction enzymes. Thus, a single band as large as the target amplicon existed in the presence of polymorphisms. A lack of polymorphism could be detected with more bands of specific weights.
PCR products were incubated for 24 hours at 37℃. Those with the allele-A of rs1255372 polymorphism were cut. Three bands of 143, 104, and 99 bp appeared, and uncut products (346 bp fragment) remained intact. PCR products with the G-allele of rs7903146 polymorphism were cut and two bands with lengths of 50 and 100 bp emerged. The 136 bp fragment remained intact in the uncut product. Digested products were then observed on agarose gel stained with 2% ethidium bromide.
Statistical analysis
SPSS version 11.5 was used for statistical analysis (SPSS Inc., Chicago, IL, USA). Variances between continuous variables (such as age) in diabetic and control groups were analyzed. The mean±standard error of age was shown. Relationships between different groups, genotypes, and TCF7L2 rs12255372 and rs7903146 polymorphism alleles were assessed by odds ratios with 95% confidence interval using a chi-square. P values of less than 0.05 were considered statistically significant.
RESULTS
Overall, 200 patients with T2DM and 200 healthy subjects were studied to determine TCF7L2 gene rs12255372 and rs7903146 polymorphisms. Subjects ranged from 35 to 75 years of age. No significant differences in demographic characteristics were observed between patient and control groups. Table 1 shows demographic characteristics of the two groups. Males accounted for 35.5% (n=71) and 31.5% (n=63) of the control and patient groups, respectively. The difference between groups was not statistically significant (P=0.397). Diabetic patients were slightly older (52.7±13.5 vs. 51.6±11.1, P=0.199). Neither age nor BMI significantly differed between groups. Clinical data and participant baseline characteristics are shown in Table 1.
TT mutant genotype distributions for both analyzed SNPs (rs12255372 and rs7903146) did not significantly differ between patients and controls (P≥0.05). T-allele frequency distributions for both analyzed SNPs were significantly different (P≤0.05) (Table 2). Finally, the association between biochemical parameters and TT+TG versus GG and TT+TC versus CC genotypes was evaluated. Table 3 shows that total cholesterol in rs12255372 (G/T) and LDL in rs7903146 (C/T) were the only significant differences observed between biochemical variables and genotypes.
DISCUSSION
Recognizing genes potentially underlying T2DM is necessary for the initial prevention of the disease. Type 2 diabetes is a complex disorder resulting from an interaction between genes and the environment. Genetic variations can insert minor or major impacts on T2DM. Intronic TCF7L2 variants are associated with T2DM. However, no specific mechanism exists demonstrating the relationship between T2DM and pathogenic genes. Although TCF7L2 has been extensively researched [11], little information about its biological role and susceptibility to diabetes is available. A study on three TCF7L2 variants (rs7903146, rs12255372, and rs4506565) was performed in India, and an association was detected between these three SNPs and T2DM [15].
These two SNPs have been shown to have strong correlations with T2DM in subjects from Iceland, Demark, and the United States [11]. A positive relationship between TCF7L2 variants and T2DM has also been demonstrated [16171819]. Four TCF7L2 genes (SNP rs11196205, rs7901695, rs12255372, and rs7903146) were investigated within a Japanese sample. A significant association was found between T2DM and these variants. Of all SNPs, rs12255372 showed the strongest association [20].
Additionally, Cauchi et al. [21] found a significant correlation between the rs7903146 polymorphism of TCF7L2 gene and T2DM risk in Morocco. However, studies performed in China [22], India [23], and the United Arab Emirates [24] found no significant association between this SNP in the TCF7L2 gene and T2DM. The current study found that rs12255372 (G/T) and rs7903146 (C/T) are not associated with T2DM in the sample recruited from Jahrom city.
The prevalence of rs12255372 (G/T) and rs7903146 (C/T) polymorphisms in the TCF7L2 gene varies by ethnicity. This variation is due to environmental and genetics factors.
Discrepancies and similarities between the current findings and previous research, differences in the selection of patients and controls in various studies, and demographic factors like ethnicity, race, and diet warrant consideration. These polymorphisms are not the only factors involved in diabetes occurrence.
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