Association between Single-Nucleotide Polymorphism of TCF7L2gene in Diabetes Mellitus Type 2 patients in Indonesia

Dyah Aryani Perwitasari¹, Imaniar Noor Faridah¹*, Ikrimah Nisa Utami², Rita Maliza³, Haafizah Dania¹, Lalu Muhammad Irham¹

¹Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy,

Universitas Ahmad Dahlan, Yogyakarta, Indonesia.

²Faculty of Medicine, Universitas Muhammadiyah Jakarta, Jakarta, Indonesia.

³Biology Department, Faculty of Mathematics and Natural Sciences,

Andalas University, Padang, West Sumatra, Indonesia.

*Corresponding Author E-mail: imaniar.faridah@pharm.uad.ac.id

ABSTRACT:

Background: Diabetes mellitus type-2 (DMT2), as one of chronic metabolic disease, still become a major concern in the world especially for low-middle income countries include Indonesia. The role of genetic has been known associated with the pathophysiology or treatment of DMT2, such as TCF7L2. Aim: The objective of current study is to find the association between TCF7L2gene in DMT2 Indonesian patients. Methods: This study enrolled 186 DMT2 patients and 30 health subjects. The treatment outcome was measured based on fasting blood glucose and hemoglobin A1C (HbA1C). Polymorphism of TCF7L2(rs7903146 (C > G/T)) was genotyped bypolymerase chain reaction (PCR). Results: The mean average of patients in this study is 60.47 years, and most of the patients using combination treatment (52.15%), however most of the DMT2 patients is in uncontrolled conditions. There are two genotypes TCF7L2 rs7903146 presented in this study, which are CC (wildtype) and CT (heterozygous mutant), however we could not find the TT (homozygous mutant). There are no significant association between blood glucose level-genotype variation and HbA1C-genotype variation (p value > 0.05). However, the proportion of heterozygous mutant-type in the uncontrolled group is higher than wild-type. Conclusion: The variations of TCF7L2 rs7903146 is not associated with DMT2 susceptibility in Indonesian populations. However, we present the higher proportion of the wildtypeTCF7L2 rs7903146 in DMT2 subjects. There is no association between treatment outcome and genotype variation in DMT2 subjects.

KEYWORDS: TCF7L2 gene, Diabetes mellitus, Indonesia, Variation, Polymorphism.

INTRODUCTION:

Diabetes is one of the chronic metabolic diseases with the increase of blood glucose level. This caused by the in effectivity of insulin due to the loss of sensitivity or less production of insulin. Insulin can change the glucose into the energy and has significant role in fat and protein metabolism. Blood glucose level and the proportion of glycosylated hemoglobin (HbA1c) can be used as the parameters to define the effectivity of treatment¹. The burden of diabetes mellitus (DM) is also rising in the world and become the major concern in the health care of world²^,³.

Globally, 9.3% of adult population in the world experienced diabetes in 2019, and it is predicted to reach 10.9% (around 700 million) in 2045⁴. Most of the countries with the highest population of diabetes are low-middle income countries, include India and Indonesia¹^,⁵^,⁶^,⁷. However, the faster rate of DM burden can be seen in Western Europe countries². The results of basic health survey conducted in Indonesia in 2007, 2013 and 2018 show the significant increase of diabetes prevalence⁸.

The future problem for the high prevalence of diabetes is macro-and microvascular complication. These complications may cause the higher cost on burden in the diabetes treatment⁹. The higher increase of diabetes-specific complications, such as, kidney failure and peripheral arterial diseases, goes along with the increase number of diabetes patients and longer duration of diabetes treatment¹⁰. Thus, appropriate treatment and effectivity monitoring must become the concern for decreasing the burden of diabetes. To get the better treatment results, some of the factors must be considered as the predictor of treatment success for DM, such as adherence, quality of life, environment and patients’ characteristics¹¹^,¹²^,¹³.

Genetic and environment have significant role in the pathophysiology of DM^14,15^,¹⁶. Genes also have influence in the success treatment in diabetes mellitus type-2 (DMT2) patients. Particular patients’ condition, like obesity, also was correlated with gene polymorphism in DM patients¹⁷. Other example, the mutation of Insulin Receptor Substrate (IRS) gene, may predicted the DM¹⁸. Considering the gene polymorphisms, can be one alternatives to reach the effective treatment by optimizing the choice and dose of medication¹⁹. In a large multiethnic cohort study revealed that solute carrier family 2, facilitated glucose transporter member 1(SLC2A2)gene, which encodedGlucose transporter 2(GLUT2), had significant association with diabetic patients treated by metformin which expressed by reduction of HbA1c percentage²⁰. Furthermore, according to the data from Genome Wide-Association Study (GWAS) revealed that the Fat mass- and obesity-associated (FTO), Transcription factor 7-like 2 (TCF7L2)and cyclin-dependent kinase inhibitor 2a (CDKN2A) were associated with body mass index (BMI), DMT2 and coronary heart disease^21,22. In some countries, TCF7L2gene showed strong association with DM incidence. In the precision medicine era, the association between genes variations and treatment effectivity may support the decrease of cost burden and increase the treatment effectivity^23–25.

The TCF7L2, based on GWAS analysis, is one of the genes with strong association with DMT2. TheTCF7L2regulated proclucagon gene (GCG), which finally influence the glucagon-like peptide 1 (GLP-1)²⁶^,²⁷. DMT2 patients with rs7903146 T allele carries, had low response to sulfonylurea, compared to the homozygous patients²⁸. The other previous study also showed that there were significant differences of HbA1C among DMT2 patients treated by glimepiride, glibenclamide or glipizide²⁹. So far, the result of the TCF7L2 variants still inconsistent. Previous studies conducted in Indonesia did not find significant association between TCF7L2polymorphism and DM. They did not find the TT genotype in the part of Jawa and Bali population^30,31. Therefore, the objective of current study is to find the association between TCF7L7gene inDMT2 Indonesian patients.

MATERIALS AND METHODS:

Patients and the Study Design:

This study was conducted in two different areas, which are Moewardi Hospital in Surakarta Solo, and Jetis I Public Health Center in Bantul, Yogyakarta, Indonesia. All DM patients, who diagnosed with DMT2 and using oral antidiabetic medication minimum 3 months, were included into the study as case group. The control group included 30 individuals who were healthy and did not consume oral antidiabetic or diagnosed of DM. However, there was no data for HbA1c and fasting blood glucose for control group. We categorized the treatment outcome, based on the normal range of fasting blood glucose and HbA1C. The DMT2 patients with high fasting blood glucose level and HbA1C, was defined as “uncontrolled”, and for the DMT2 patients with normal fasting blood glucose level and HbA1C, was defined as “controlled”. All participants provided written informed consent to the study. The ethical approval was obtained from the ethics committee of Universitas Ahmad Dahlan (UAD), No 011904040Yogyakarta, Indonesia.

Molecular Genotyping:

Blood samples were taken for genotyping and measurement of HbA1c and fasting blood glucose. Extraction of the DNA using FavorPrep Kit method™ (Favorgen Biotech, Taiwan) from 200μl whole blood sample. The quality of DNA was analyzed using gel electrophoresis (Bio-rad, USA) and ultraviolet–visible spectrophotometry. Polymorphism of TCF7L2 (rs7903146 (C>G/T)) was genotyped by polymerase chain reaction (PCR) – direct sequencing method using forward and reverse primers. The PCR was carried out under the followingconditions: Initial denaturation at 95°C for 3 minutes, followed by denaturation at 95°C for 1minutes, annealing at 58.3°C for 50 seconds, extensions at 72°C for 50 seconds and final extensions at 72°C for 10 minutes (35cycles). The product of the PCR was analyzed by using electrophoresis on a 1.5% agarose gel and 80 volts for 80 minutes (product size 210 bp). The products of PCR then were sent to 1st BASE Singapore forsequencing analysis. DNA sequences were edited by using the Bio-edit program. SNAP-gene version 6.0 programwas performed to identify the flanking region of TCF7L2 rs7903146 and SNP.

Statistical Analysis:

The continues variables were presented as mean+ standard deviation (mean+SD). Comparison of categorical variables between two groups was done by using ꭓ² test or Fisher’s exact test (if <80% of cells have expected count less than five). Comparison of continues variables between two groups was done by t-test or Mann Whitney test where applicable. The odds ratios were calculated using a logistic regression model. The statistical significance level was set at p-value < 0.05. Statistical analysis was performed using SAS 9.4.

RESULTS AND DISCUSSION:

Our study found that there were no significant association between the variants of TCF7L2rs7903146 and DMT2 in Indonesia population. Herein, we recruited 186DMT2 patients and 30 healthy subjects. Table 1 presents the characteristics of DMT2 patients. The mean average of patients in this study is 60.47 (SD: 10.67). Most of the patients had under senior high school as the last education (83.87%), married status (77.42%), working (65.59%) and using combination treatment (52.15%). The mean of blood glucose level and HbA1C of DMT2 patients are high, above the upper normal scale (156.95mg/dL; 8.24%, respectively).

In general, our study finds that, most of the DMT2 patients were in the uncontrolled conditions, based on the fasting blood glucose level and HbA1C. Since the antidiabetic was mostly given in combination to the DMT2 patients, the DMT2 strategy need to be improved. Previous study mentioned that in the low-middle income countries, the prevalence of non-communicable diseases increased, including DMT2. Most of the diabetic patients in these low-middle income countries was also female, with younger age was predominant. The education attainment and body mass index might predict the prevalence of diabetes ³². Our current study recruited older DMT2 patients, thus the mean age of subjects was 60.47 years old. Previous systematic review conducted in low-, middle-, and high- income countries presented that older DMT2 and male patients was predominant³³.

The electrophoregram analysis of DNA samplewas presented in Figure 1. There are two genotypes TCF7L2 rs7903146 presented in this study, which are CC (wildtype) and CT (heterozygous mutant), however we could not find the TT (homozygous mutant). Furthermore, Table 2 presents the genotype distribution of the wildtype and heterozygous mutant of TCF7L2rs7903146 gene in DMT2 patients and healthy people.

Figure 1 - Electrophoregram analysis of DNA sample (A) TCF7L2 rs7903146 gene sequencing CC genotype (Homodimer wildtype/normal); (B) TCF7L2 rs7903146 gene sequencing CT genotype (Heterodimer Mutan).

Table 1 - Characteristic of DMT2 patients (N = 186)

Characteristics		N	Proportion
Age, years old (mean :60.47, SD:10.67)	<60	83	44.62%
Age, years old (mean :60.47, SD:10.67)	>60	103	55.38%
Sex	Male	71	38.17%
Sex	Female	115	61.83%
Last education	Up to senior high school Higher than senior high school	156 30	83.87 16.13
Status	Married Not married	144 42	77.42 22.58
Working	Yes	122	65.59
Working	No	64	34.41
Anti-diabetes	Single	89	47.85
Anti-diabetes	Combination	97	52.15
Fasting Blood Glucose; mg/dl (Mean: 156.95; SD: 71.40)	Controlled Uncontrolled	78 108	41.94 58.06
HbA1C, % (Mean: 8.24; SD: 2.41)	Controlled Uncontrolled	33 153	17.74 82.26

SD = Standard Deviation; HbA1C = Hemoglobin A1C

Table 2 - Distribution of the genotype TCF7L2rs7903146 gene in DMT2 patients and healthy subjects

	DMT2 patients (N=186)	Normal (N=30)	P Value Hardy-Weinderg	Odds Ratio	95% CI	P Value Odds Ratio
Genotypes
Wild type (CC)	172 (92.47%)	26 (86.67%)	0.2872	1	0.162 – 1.731	0.2925
Heterozygous mutant (CT)	14 (7.53%)	4 (13.33%)	0.2872	0.529	0.162 – 1.731	0.2925

There are no significant differences of the distribution of wildtype and heterozygous mutant in both groups (P-value: 0.2872; OR: 0.529; CI 95%: 0.162-1.731). The proportion of wildtypeTCF7L2rs7903146in this population is 91.7% and the proportion of heterozygous mutant is 8.3%. The proportion of heterozygous mutant in healthy group is higher than heterozygous mutant in DMT2. However, it can be seen that the proportion of wildtypeTCF7L2rs7903146 in DMT2 subjects is higher than in the healthy subjects.

Previous study mentioned that DMT2 patients with TCF7L2, TT genotype had lower fasting blood glucose than DMT2 patients with CC genotype³⁴. The frequency of CT in healthy subjects is higher than the frequency of CT in DMT2 subjects. In Iraq, the G allele frequency was greater in DM subjects than in healthy subjects²⁷. Our study only finds two genotypes of CC and CT. In the other previous study, conducted in Iran, there were 3 genotypes of rs7903146 TCF7L2 gene, and CT genotype, TT genotype, or the dominant model were significantly associated with the risk of DMT2³⁵. In Han Chinese population, the CC genotype and the recessive model also might be associated with DMT2^36,37. In Saudi Arabia population the rs7903146 TCF7L2 did notassociate with DMT2 susceptibility³⁸. Based on the information from GTEx portal, the genotype frequency of our population in this study has the similar pattern with East Asia population, but with the higher frequency of heterozygous mutant. However, the contribution of the genetic variants to DMT2 in East Asia is still low³⁹.

To elucidate the gene expression in various tissue, we used GTEx Portal (http://www.gtexportal.org/home/) as the publicly available databases. As shown in figure2, the TCF7L2 gene had highly expressed in several tissues including the pancreas that related with DMT2. TCF7L2, which is located on 10q25.2-q25.3, plays significant role in β-cells function, with the mechanism of loss of insulin secretion. The loss of β-cells function could be defined by the T carrier as the risk allele. Thus, it was assumed that the T carriers have predisposed to develop DM³⁴. Our study presents that the wildtype was predominant in DMT2 patients and healthy subjects, even though the proportion of T carriers in healthy subjects is higher than in DMT2 patients.

The genotype frequency of TCF7L2rs7903146 in multiple continents including African, American, East Asia, European, and South Asianwere presented in Table III and figure 3. All these data were retrieved fromEnsembl(https://m.ensembl.org/Homo_sapiens).The East Asian population has the highest frequency of CC (95.6%) genotype of TCF7L2rs7903146 and the South Asia populations has the highest frequency of CT (42.1%) and TT (8.8%).

Table III - Genotype frequency of TCF7L2rs7903146 in some populations (GTEx Portal)

Populations	Frequency (%)
Populations	CC	CT	TT
African	55.2	37.5	7.3
American	59.1	34.9	6.1
East Asia	95.6	4.2	0.2
European	48.1	0.4	1.5
South Asia	49.1	42.1	8.8

Genotype frequency of multiple continents (African, American, East Asia, European and South Asia) were extracted from https://m.ensembl.org/Homo_sapiens

Further analysis related to the genotype association and DMT2 condition based on the fasting blood glucose level and HbA1Cwas shown in Table IV. The result implied that there is no significant association between blood glucose level-genotype variation and HbA1C-genotype variation (p value > 0.05). However, the proportion of heterozygous mutant type in the uncontrolled group is higher than heterozygous mutant in controlled group. In addition to that, the distribution of fasting blood glucose and HbA1C in the wildtype and heterozygous mutantare presented in Figure 4. The mean of HbA1C in heterozygous mutant is higher than wildtype,moreover, the number of uncontrolled patients with heterozygous mutant (92.86) is higher than the wildtype (81.40) ones. In the fasting blood glucose level, the mean and number of heterozygous mutant (78.57) in uncontrolled patients are higher than the wildtype (56.40).

A previous study, conducted in Germany, presented thatT allele of rs7903146 TCF7L2 more frequent in the DMT2 patients who failed of antidiabetic treatment than in control group⁴⁰.In Persian population, the TT and CT genotypes are more related to DMT2 risks than the CC genotype of TCF7L2 rs7903146 ⁴¹. This result is contradictive with our findings which presents that the CC genotype of TCF7L2 rs7903146 is more frequent in DMT2 patients with the uncontrolled blood glucose and HbA1C. The rs7903146 TCF7L2 was known as the predictor of sulphonylurea success treatment¹⁹.

Our study has limitation, due to the limited sample size in normal subjects, we suggest the future studies with larger sample size in Indonesia population. We also recommend the randomization, allocation and blinding to get the more representative results.We also did not consider the patients’ characteristics in this study.

CONCLUSION:

The variations of TCF7L2 rs7903146 is not associated with DMT2 susceptibility in Indonesian populations. However, we present the higher proportion of the wildtypeTCF7L2 rs7903146 in DMT2 subjects. There is no association between treatment outcome and genotype variation in DMT2 subjects.

ACKNOWLEDGEMENT:

We thank to LPPM Universitas Ahmad Dahlan for funding support.

CONFLICT OF INTERESTS:

All authors have no conflict of interest.

REFERENCES:

1. International Diabetes Federation. IDF Diabetes Atlas, 9th Edition.; 2019.

2. Khan MAB, Hashim MJ, King JK, Govender RD, Mustafa H, Al Kaabi J. Epidemiology of Type 2 Diabetes - Global Burden of Disease and Forecasted Trends. J Epidemiol Glob Health. 2020; 10(1): 107-111. doi:10.2991/jegh.k.191028.001

3. Chandramore K. Review on Dipeptidyl Peptidase IV Inhibitors as a Newer Target for Diabetes Mellitus Treatment. Asian J Pharm Res. 2017; 7(4): 230-238. doi:10.5958/2231-5691.2017.00036.3

4. Saeedi P, Petersohn I, Salpea P, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9(th) edition. Diabetes Res Clin Pract. 2019; 157: 107843. doi:10.1016/j.diabres.2019.107843

5. Raphael M, K V, GirishThunga, Rao K, N S. Utilization Pattern of Anti-Diabetic Drugs in Type 2 Diabetes Mellitus in Tertiary Care Hospital. Res J Pharm Technol. 2017; 10(7): 2063-2068. doi:10.5958/0974-360X.2017.00360.2

6. Perwitasari DA, Faridah IN, Supadmi W, et al. The Impact of Diabetes Distress on the Treatment Outcome. Res J Pharm Technol. 2019; 12(1): 223-226. doi:10.5958/0974-360X.2019.00041.6

7. Dewangan V, Pandey H. Pathophysiology and Management of Diabetes: A Review. Res J Pharmacol Pharmacodyn. 2017; 9(4): 219-222. doi:10.5958/2321-5836.2017.00039.8

8. Ministry of Health Republic of Indonesia. Indonesia Health Profile 2019.; 2020. https://pusdatin.kemkes.go.id/resources/download/pusdatin/profil-kesehatan-indonesia/Profil-Kesehatan-indonesia-2019.pdf

9. Harding JL, Pavkov ME, Magliano DJ, Shaw JE, Gregg EW. Global trends in diabetes complications : a review of current evidence. Diabetologia. 2019; 62: 3-16.

10. Dal Canto E, Ceriello A, Rydén L, et al. Diabetes as a cardiovascular risk factor: An overview of global trends of macro and micro vascular complications. Eur J Prev Cardiol. 2019; 26(2_suppl): 25-32. doi:10.1177/2047487319878371

11. S.K A, M VA. An Improvement in Patient Compliance in Diabetes Mellitus. Res J Pharm Technol. 2018; 11(2): 587-592. doi:10.5958/0974-360X.2018.00108.7

12. V G, Sahu SK, Susila C. Assess Quality of Life (QOL) and Glycemic Level among Type 2 Diabetic Patients in Global Hospital and Research Centre and its Units, Sirohi, Rajasthan. Asian J Nurs Educ Res. 2017; 7(4): 577-582. doi:10.5958/2349-2996.2017.00112.4

13. S J, Babu M. Knowledge of Diabetic Clients Regarding Self-care Practices in Management of type II Diabetes Mellitus at selected Rural Community of Bangalore, Karnataka. Asian J Nurs Educ Res. 2017; 7(1): 86-94. doi:10.5958/2349-2996.2017.00018.0

14. Kolb H, Martin S. Environmental/lifestyle factors in the pathogenesis and prevention of type 2 diabetes. BMC Med. 2017; 15(1). doi:10.1186/s12916-017-0901-x

15. Tremblay J, Hamet P. Environmental and genetic contributions to diabetes. Metabolism. 2019; 100S: 153952. doi:10.1016/j.metabol.2019.153952

16. Sheng T, Lu Y, Yang K, et al. Association Between Single Nucleotide Polymorphisms (SNPs) in the Promoter of Adiponectin Gene, Hypoadiponectinemia, and Diabetes. Res J Sci Technol. 2016; 8(1): 34-40. doi:10.5958/2349-2988.2016.00004.8

17. Ranjan S, Sharma PK. Association of Brain-Derived Neurotrophic factor (BDNF) gene SNP G196A with Type 2 Diabetes and Obesity: A Meta- Analysis. Res J Pharm Technol. 2017; 10(12): 4297-4305. doi:10.5958/0974-360X.2017.00787.9

18. Singh A, Singh S, Anbarasu A. In silico Evaluation of Non-Synonymous SNPs in IRS-1 Gene associated with type II Diabetes Mellitus. Res J Pharm Technol. 2018; 11(5): 1957-1961. doi:10.5958/0974-360X.2018.00363.3

19. Nasykhova YA, Tonyan ZN, Mikhailova AA, Danilova MM, Glotov AS. Pharmacogenetics of Type 2 Diabetes-Progress and Prospects. Int J Mol Sci. 2020; 21(18). doi:10.3390/ijms21186842

20. Zhou K, Yee SW, Seiser EL, et al. Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin. Nat Genet. 2016; 48(9): 1055-1059. doi:10.1038/ng.3632

21. Katsoulis K, Paschou SA, Hatzi E, Al. E. TCF7L2 gene variants predispose to the development of type 2 diabetes mellitus among individuals with metabolic syndrome. Hormones. 2018; 17: 359–365.

22. Assmann TS, Duarte GCK, Rheinheimer J, Crispim D. The TCF7L2 rs7903146 (C/T) polymorphism is associated with risk to type 2 diabetes mellitus in Southern-Brazil. Arq Bras Endocrinol Metab. 2014; 58(9): 918-925. doi:10.1590/0004-2730000003510

23. Ingelsson E, McCarthy MI. Human Genetics of Obesity and Type 2 Diabetes Mellitus: Past, Present, and Future. Circ Genomic Precis Med. 2018; 11(6): e002090. doi:10.1161/CIRCGEN.118.002090

24. Becker ML, Pearson ER, Tkáč I. Pharmacogenetics of oral antidiabetic drugs. Int J Endocrinol. 2013; 2013. doi:10.1155/2013/686315

25. Isakova J, Talaibekova E, Vinnikov D, Saadanov I, Aldasheva N. ADIPOQ, KCNJ11 and TCF7L2 polymorphisms in type 2 diabetes in Kyrgyz population: A case-control study. J Cell Mol Med. 2019; 23(2): 1628-1631. doi:10.1111/jcmm.14061

26. Grant SFA. The TCF7L2 Locus : A Genetic Window Into the Pathogenesis of Type 1 and Type 2 Diabetes. Diabetes Care. 2019; 42(September):1624-1629. doi:10.2337/dci19-0001

27. Ahmed NS, Hadi YA, Dhefer IH. Polymorphism Study of TCF7L2 gene and related to some biochemical parameters in DM2 females Iraqi patients. Res J Sci Technol. 2019; 11(1): 01-08. doi:10.5958/2349-2988.2019.00001.9

28. Pearson ER, Donnelly LA, Kimber C, et al. Brief Report : Variation in TCF7L2 Influences Therapeutic Response to Sulfonylureas. Diabetes. 2007; 56(August): 2178-2182. doi:10.2337/db07-0440.E.R.P.

29. Javorsky M, Babjaková E, I LK, et al. Association between TCF7L2 Genotype and Glycemic Control in Diabetic Patients Treated with Gliclazide. Int J Endocrinol. Published online 2013. doi:https://doi.org/10.1155/2013/374858

30. Saraswati MR, Suastika K, Malik SG, Sudoyo H. TCF7L2 gene polymorphisms rs12255372, rs7903146, rs10885406 and the association with type 2 diabetes in a population of Legian Village, Kuta, Bali. Indones J Biomed Sci. 2017; 11(2): 6-10.

31. Sahrani WA, Astuti I, Sadewa AH. Polymorphism of Transcription Factor 7-Like 2 Gene and HOMA-β Level of Individuals With and Without Type 2 Diabetes Mellitus Family History. Indones J Biotechnol. 2014; 19(2): 176. doi:10.22146/ijbiotech.9312

32. Seiglie JA, Marcus ME, Ebert C, et al. Diabetes Prevalence and Its Relationship With Education, Wealth, and BMI in 29 Low- and Middle-Income Countries. Diabetes Care. 2020; 43(4): 767-775. doi:10.2337/dc19-1782

33. Dagenais GR, Gerstein HC, Zhang X, et al. Variations in Diabetes Prevalence in Low-, Middle-, and High-Income Countries: Results From the Prospective Urban and Rural Epidemiological Study. Diabetes Care. 2016; 39(5): 780-787. doi:10.2337/dc15-2338

34. Dujic T, Bego T, Malenica M, et al. Effects of TCF7L2 rs7903146 variant on metformin response in patients with type 2 diabetes. Bosn J basic Med Sci. 2019; 19(4): 368-374. doi:10.17305/bjbms.2019.4181

35. Shokouhi S, Delpisheh A, Haghani K, Mahdizadeh M, Bakhtiyari S. Association of rs7903146, rs12255372, and rs290487 polymorphisms in TCF7L2 gene with type 2 diabetes in an Iranian Kurdish ethnic group. Clin Lab. 2014; 60(8): 1269-1276. doi:10.7754/clin.lab.2013.130809

36. Wang J, Li L, Zhang J, et al. Association of rs7903146 (IVS3C/T) and rs290487 (IVS3C/T) polymorphisms in TCF7L2 with type 2 diabetes in 9,619 Han Chinese population. PLoS One. 2013; 8(3): e59053. doi:10.1371/journal.pone.0059053

37. Chang YC, Chang TJ, Jiang YD, et al. Association study of the genetic polymorphisms of the transcription factor 7-like 2 (TCF7L2) gene and type 2 diabetes in the Chinese population. Diabetes. 2007; 56(10): 2631-2637. doi:10.2337/db07-0421

38. Acharya S, Al-Elq A, Al-Nafaie A, Muzaheed M, Al-Ali A. Type 2 diabetes mellitus susceptibility gene TCF7L2 is strongly associated with hyperglycemia in the Saudi Arabia Population of the eastern province of Saudi Arabia. Eur Rev Med Pharmacol Sci. 2015; 19(16): 3100-3106.

39. Luo Y, Wang H, Han X, et al. Meta-analysis of the association between SNPs in TCF7L2 and type 2 diabetes in East Asian population. Diabetes Res Clin Pract. 2009; 85(2): 139-146. doi:10.1016/j.diabres.2009.04.024

40. Holstein A, Hahn M, Korner A, Stumvoll M, Kovacs P. TCF7L2 and therapeutic response to sulfonylureas in patients with type 2 diabetes. BMC Med Genet. 2011; 12: 30. doi:10.1186/1471-2350-12-30

41. Palizban A, Nikpour M, Salehi R, Maracy MR. Association of a common variant in TCF7L2 gene with type 2 diabetes mellitus in a Persian population. Clin Exp Med. 2012; 12(2): 115-119. doi:10.1007/s10238-011-0144-7

Received on 21.12.2022 Modified on 12.01.2024

Research J. Pharm. and Tech 2024; 17(11):5485-5490.

DOI: 10.52711/0974-360X.2024.00839

	Wild-Type (CC) (N = 172 )	Heterozygous mutant (CT) (N = 14 )	Total	p-value
Fasting Blood Glucose Level				0.2215*
Controlled	75 (43.60)	3 (21.43)	78 (41.94)
Uncontrolled	97 (56.40)	11 (78.57)	108 (58.06)
HbA1C				0.5820*
Controlled	32 (18.60)	1 (7.14)	33 (17.74)
Uncontrolled	140 (81.40)	13 (92.86)	153 (81.26)