PPARɣ2, aldose reductase, and TCF7L2 gene polymorphisms: relation to diabetes mellitus

Abstract

Purpose

Diabetes mellitus (DM) is a growing global health concern. Genetic factors play a pivotal role in the development of diabetes. Therefore, the present work aimed to study the relation between peroxisome proliferator-activate receptors (PPARɣ2) (rs3856806), aldose reductase (AR) (rs759853), transcription factor 7 like 2 (TCF7L2) (rs7903146) gene polymorphism with diabetes in the Egyptian population.

Methods

The study included 260 diabetics and 120 healthy subjects. Genotyping was done using polymerase chain reaction-restriction fragment length polymorphism.

Results

Regression analysis revealed that PPARɣ2 TT, TCF7L2 TT were suggested to be independent risk predictors for T1DM and TCF7L2 TC, CC genotype were suggested to be independent protective factors against T1DM development. On the other hand, PPARɣ2 TT, AR TT genotypes were suggested to be independent risk predictors for T2DM susceptibility, and PPARɣ2 CT genotypes were suggested to be independent protective factors against T2DM development.

Conclusion

The present study revealed that PPARγ2 (rs3856806), TCF7L2 (rs7903146) and AR (rs759853) gene polymorphism may play an important role in the susceptibility of diabetes. Therefore, these polymorphisms may have a prognostic value for diabetes in the Egyptian population. Further work is required to confirm the role of these polymorphisms in diabetes.

Introduction

Diabetes mellitus, a major public health problem worldwide, is a chronic disease characterized by hyperglycemia. The global prevalence of diabetes is estimated at 451 million, which is predicted to rise to 693 million by 2045. A further almost half of all diabetic people remain undiagnosed due to the asymptomatic nature of this condition especially in type 2 diabetes mellitus [1]. Egypt is the nation with the ninth biggest population of diabetics in the world. According to International Diabetes Federation, there were 8.2 million diabetic patients in Egypt in 2017. It is expected that this number will increase up to 13.1 million by 2035 [2].

Diabetes is divided into two: type 1 diabetes mellitus “T1DM” and type 2 diabetes mellitus “T2DM”. T1DM is characterized by cellular mediated autoimmune destruction of pancreatic β cells leading to total insulin deficiency [3]. It represents about 10% of all diabetes and it affects all ages, but the majority are children less than 5 years old. The rate of T1DM is increasing by 2 to 5% per year globally [4]. T2DM is the most common type of diabetes that represents up to 95% of all diabetics. The pathogenesis of T2DM has two main abnormalities involving dysfunction of insulin production and insulin resistance, which cause the disability to adjust blood glucose concentration. Both types of diabetes are associated with hyperglycemia, oxidative stress, inflammation and macrovascular (stroke, coronary artery disease, atherosclerosis, and hypertension), and microvascular complications as nephropathy, neuropathy, and retinopathy [5].

Diabetes mellitus is a polygenic disease that clusters of genes along with their variants work together to cause the disease effectively. Many genes facilitated diabetes development such as insulin resistance genes; ATP-binding cassette subfamily C member 8 (ABCC8), and peroxisome proliferator-activates receptor-gamma (PPARϒ), that have a vital role in hypothalamic regulation, insulin signaling leading to diabetes [6]. Besides, PPARγ has an important role in the metabolism of lipid and glucose, insulin sensitivity, inflammation, stimulating adipogenesis, energy regulation, and fibrosis [7]. PPARɣ gene is located on chromosome 3p25.3. Many PPARɣ2 polymorphisms have been reported. The most common is Pro12Ala (rs1801282) which codes for proline at exon 2 instead of alanine that leads to reduced DNA-binding affinity and impaired transcriptional activity in target genes. This polymorphism has been associated with increased obesity, type 2 diabetes mellitus, coronary artery disease [8]. Another polymorphism is the silent mutation C161T (rs3856806) which codes for histidine amino acid at exon 6 is associated with decreased transcription of PPARγ [9]. Other candidate genes related to diabetes are angiotensin-converting enzyme, insulin receptor substrate 1 and 2, transcription factor 7-like 2 (TCF7L2) [10]. TCF7L2, transcription factor 7 like 2, is a member of the transcription factor family that participates in the regulation of insulin effect, secretion, and processing. Besides, it plays a pivotal role in the Wnt signaling pathway and the regulation of glucose metabolism in the gut, liver, skeletal muscle, pancreatic tissues, and brain [11]. TCF7L2 gene located on chromosome 10q25 has a vital role in pancreatic cancer, osteoarthritis, and diabetes [12]. Aldose reductase (AR) belongs to the aldo keto reductase superfamily that is found in many tissues such as the skeletal muscle tissue, lens, liver, kidney, and brain. It is the first enzyme in the polyol pathway which converts glucose to sorbitol causing accumulation of sorbitol within the cell. Sorbitol difficulty cross cell membranes and it accumulates in cells leading to osmotic stress and osmotic damage resulting in the development of diabetic complications. Human AR encoded by the AR gene located on the long arm of chromosome 7 at 7q35. Single nucleotide polymorphism of AR rs759853 causes changes in the expression of mRNA of the AR gene [13]. Several genetic polymorphisms are associated with the development of diabetes and its complications [14]. Identifying these polymorphisms leads to earlier prediction and prevention of the disease [15]. According to previous studies, PPARɣ2, AR, and TCF7L2 gene polymorphism may have a role in the development of diabetes mellitus that may help in the early prediction of the disease, however, few studies investigated this role. In addition, the results of these studies were inconsistent. Therefore, the current study focused on investigating whether the genetic polymorphisms of PPARɣ2 (rs3856806), AR (rs759853), and TCF7L2 (rs7903146) are associated with the risk of both type 1 and 2 diabetes susceptibility within the Egyptian population.

Materials and methods

The current study was conducted on 380 subjects classified into 120 type 1 diabetics (their age ranged from 20 to 55 years), 140 type 2 diabetic patients (their age ranged from 28 to 60 years), and 120 healthy subjects as the control group (based on clinical examination and laboratory investigations), their age ranges from 25 to 60 years. Diabetic patients were diagnosed based on the American Diabetes Association criteria. Diabetics were selected from the Clinics diabetes and endocrinology in Specialized Medical Hospital, Mansoura University. Informed consent was obtained from all participants. This study was ethically approved by Mansoura University Ethics Committee at the faculty of science (Sci-ch-ph -2020-28).

Inclusion criteria: Adults aged 20–60 years; male and female are included (healthy individuals, type 1 and 2 diabetic patients).

Exclusion criteria: Individuals who are younger than 20 years or older than 60 years, other types of diabetes such as gestational diabetes, Patients who had any evidence of other endocrinal diseases, liver or pancreatic diseases, heart, kidney diseases were excluded.

Clinical examination

This study was performed in the Clinical Pathology Department, Mansoura University. 8 ml of venous blood was withdrawn from each subject and divided into 4 ml was collected into 2 EDTA tubes for hemoglobin A1c (HbA1c) and DNA extraction. 4 ml was put in a plain tube, centrifuged and serum was used in FBG (fasting blood glucose), PPBG (postprandial blood glucose), lipid profile, and creatinine.

Biochemical investigations

FBG, PPBG, creatinine, and lipid profile were performed on automatic analyzer ADALTIS Pchem 1. HbA1c was done by biosystem kit for quantitative determination [16].

Estimated glomerular filtration rate (eGFR) was calculated from the simplified equation developed using data from the Modification of Diet in Renal Disease (MDRD) Study as follows [17]:

$$\mathrm{MDRD}\mathrm{equation}:\mathrm{eGFR}=186.3\mathrm{x}{\left({}_{\mathrm{Serum}\mathrm{creatinine}}\right)}^{-1.154}\mathrm{x}{\left(\mathrm{age}\right)}^{-0.203}\times 0.742\left[\mathrm{if},,\mathrm{female}\right]\times 1.212\left[\mathrm{if},,\mathrm{Black}\right]$$

Genotyping

DNA was extracted from whole EDTA blood samples using the Gene JET whole blood genomic DNA Purification Kits (Thermo Scientific, lot 00138029, Lithuania, EU). The gene polymorphism of rs3856806 PPARɣ2, rs759853 AR, and rs7903146 TCF7L2 were detected by PCR-RFLP “polymerase chain reaction-restriction fragment length polymorphism”. The following primers were used for the TCF7L2 gene [18]:

• forward primer 5’ CTGAACAATTAGAGAGCTAAGCACTTTTTAGGTA-3′

• and reverse primer 5’ TTTCACTATGTATTGTTGCCAGT CAGCAAACAC-3’

PCR reaction mixture contained 5 pmol of each primer in combination with Taq PCR Master Mix (Qiagen, Valencia, CA, USA). The PCR cycling conditions were: initial denaturation for 5 min at 94 °C, after that the PCR was carried out for 1 min for 35 cycles at 94 °C, for 1 min at 60 °C, for 1 min at 72 °C, and final cycle for 10 min at 72 °C (T-Gradient thermal cycler, Biometra, Germany). PCR products were digested with 10 U of RsaI (New England Biolabs, Hitchin, UK) at 37 °C for 2 h. The digested products were resolved on agarose gel electrophoresis 3.5% and visualized by UV transilluminator after staining with ethidium bromide to identify the different polymorphisms. TT genotype is represented at 266 bp, CC genotype at 233 and 33 bp. CT genotype is represented at 266, 233, and 33 bp.

For aldose reductase rs759853 gene polymorphism, the following primers [19] were used: forward 5’ TTC GCT TTC CCA CCA GAT AC’3; reverse 5 ‘CGC CGT TGT TGA GCA GGA GAC’3. The reaction mixture had initial denaturation for 2 min at 95 °C; followed by 35 cycles of denaturation for 1 min at 95 °C; annealing for 1 min at 66 °C; extension at 72 °C for 1 min and the final extension for 5 min at 72 °C. The amplified PCR products were subjected to enzyme digestion by BfaI (FspBI) restriction enzyme from Biolabs New England: incubate 10 μl of the PCR product; 18 μl of nuclease-free water; 2 μl of buffer tango and 1 μl of FspBI for 2 h at 37 °C. Followed by 3.5% agarose gel electrophoresis, and then stained with ethidium bromide to identify the different polymorphisms and visualized by UV transilluminator. CC genotype had 2 bands at 234 and 92 bp. CT genotype had 3 bands at 234, 175, 92 bp and a hidden band could not be seen (59 bp). TT genotype had 2 bands 175 and 92 bp and also a hidden band could not be seen because it is too small to appear on the gel (59 bp).

For PPARɣ2 C161T (rs3856806) genetic polymorphism, the following primers were used Forward primer [20]: 5’-CAAGACAACCTGCTACAAGC-3′.

and reverse primer: 5’-TTCTTGTAGATCTCCTGCAG-3’.

The reaction started with initial denaturation for 3 min at 94 °C; then, PCR of 32 cycles of denaturation for 45 s at 94 °C; annealing for 45 s at 57.7 °C and elongation for 60 s at 72 °C, then post-extension for 5 min at 72 °C. The restriction was carried out at 37 °C overnight using 8 U of Eco72I restriction enzyme, followed by agarose gel electrophoresis. The CC homozygote had 2 bands at 120 and 80 bp. The CT heterozygote had 3 fragments at 200; 120 and 80 bp. The TT homozygote produced 1 band at 200 bp.

Statistical analysis

The statistical calculations were done using SPSS Statistics for Windows (Released in 2011. Version 20.0. Armonk, NY: IBM Corp.). Data were presented and suitable analysis was done according to the type of data obtained for each parameter. Mean ± standard deviation (±SD) was used for the description of numerical data. Deviations from Hardy–Weinberg equilibrium expectations were determined using the chi-squared test. Odds ratio and 95% confidence interval were calculated for the association of the polymorphic genotype and allele with the risk of DR. Logistic and linear regression analyses were used for the prediction of risk factors. P is significant if <0.05 at confidence interval 95%.

Results

There were no significant differences in age and gender between diabetics and healthy. The control subjects were matched as regards age and gender. Higher concentrations of FBG, PPBG, HbA1c were significantly associated with diabetics when compared to the control group (P < 0.001 for each). HDL concentration was significantly lower in type 2 diabetics when compared to a healthy individual. Otherwise, no significant differences were found in creatinine level, lipid profile concentration, BMI, and eGFR between studied groups (P > 0.05 for each) Table 1.

Table 1.

The clinical attributes of the study participants

Parameter		Control N = 120	T1DM N = 120	T2DM N = 140	P1	P2
Age (years)		41.3 ± 9.6	40.6 ± 12.4	43.1 ± 7.1	0.625	0.084
gender	male	40 (33.3%)	54 (45%)	52 (37.1%)	0.064	0.521
	female	80 (66.7%)	66 (55%)	88 (62.9%)
FBG		95.1 ± 9.1	319.5 ± 152.4	231.2 ± 102.5	<0.001*	<0.001*
PPBG		135.4 ± 23.1	515.8 ± 341.7	283.4 ± 132.7	<0.001*	<0.001*
HbA1C (%)		5.3 ± 0.7	9.2 ± 1.7	8.4 ± 2.0	<0.001	<0.001
Creatinine (mg/dL)		0.9 ± 0.16	0.92 ± 0.18	.95 ± 0.290	0.363	0.093
TC (mg/dL)		199.8 ± 42.8	200.9 ± 39.4	190.2 ± 41.6	0.836	0.068
TG (mg/dL)		148.9 ± 55.6	134.7 ± 64.7	160.1 ± 71.2	0.069*	0.163*
HDL (mg/dL)		53.3 ± 9.1	52.7 ± 11.2	47.6 ± 10.5	0.649	<0.001
LDL (mg/dL)		118.3 ± 41.2	124.1 ± 37.6	110.9 ± 38.1	0.255	0.134
TC-HDL		3.8 ± 1.6	4.1 ± 2.1	4.1 ± 1.5	0.214*	0.120*
LDL-HDL		2.2 ± 1.1	2.4 ± 1.3	2.4 ± 1.2	0.199*	0.165*
eGFR ml/min/1.73m2		86.5 ± 19.5	88.5 ± 19.1	86.3 ± 19.1	0.423	0.933
BMI (kg/m2)		31.7 ± 6.7	32.1 ± 6.8	32.4 ± 6.9	0.646	0.409

T1DM: Type 1 diabetes mellitus. T2DM: Type 2 diabetes mellitus. FBG: Fasting blood glucose. PPBG: Postprandial blood glucose HbA1c: Hemoglobin A1c. TC: total cholesterol. TG: triglyceride HDL: high-density lipoprotein; LDL: low-density lipoprotein. N, number. eGFR: estimated glomerular filtration rate. BMI: Body mass index. P > 0.05 is considered non-significant, P < 0.05 is considered significant. P1: comparison between control and T1DM. P2: comparison between control and T2DM. Data are expressed as mean ± SD. t test was used for comparison (P); Man Whitney test was used for comparison (P*)

PPARɣ2 rs3856806, AR rs759853, TCF7L2 rs7903146 genotypes in control group were in Hardy–Weinberg equilibrium (P = 0.088, 0.144, 0.109; respectively). PPARɣ2 C allele showed a significantly lower proportion in type 1 diabetics when compared to the control group (P = 0.024), with a protective effect against T1DM development within healthy subjects (OR = 0.607). PPARɣ2 TT genotype and T allele showed a significantly higher proportion in the case compared to healthy control (P < 0.001, 0.024), with risk to develop T1DM within healthy subjects. AR CT, CT + TT genotypes showed a significantly higher proportion in type 1 diabetics when compared to the control group (P = 0.014, 0.017), with risk to develop T1DM within control subjects (OR = 1.516, 1.561). TCF7L2 TT and T allele showed a significantly higher proportion in the case when compared to the control group (P < 0.001), with risk to develop T1DM within healthy control subjects (OR = 3.433, 2.505; respectively). While, TCF7L2 TC, CC, TC + CC genotypes and C allele showed significantly lower proportion in type 1 diabetic patients when compared to the control group (P < 0.001), with a protective effect against T1DM development within healthy subjects (OR = 0.288, 0.294, 0.291, 0.399; respectively) Table 2.

Table 2.

Comparison of studied genotypes and alleles between control and type 1 diabetics

Genotypes and alleles	Control		T1DM		P	OR	95% CI
	N = 120		N = 120
	N	%	N	%
PPARɣ
CC	69	57.5	60	50	0.501	0.827	0.477	1.437
CT	51	42.5	30	25	0.435	0.784	0.426	1.444
TT	0	0	30	25	<0.001	–	–	–
CT + TT	51	42.5	60	50	0.501	1.208	0.696	2.098
C	189	78.8	150	62.5	0.024	0.607	0.394	0.937
T	51	21.3	90	37.5	0.024	1.646	1.067	2.541
AR
CC	75	62.5	54	45	0.117	0.641	0.368	1.117
CT	45	37.5	63	52.5	0.014	1.516	0.866	2.652
TT	0	0	3	.22	0.996	–	–	–
CT + TT	45	37.5	66	55.0	0.017	1.561	0.895	2.72
C	195	81.3	171	71.3	0.138	0.705	0.445	1.118
T	45	18.8	69	28.8	0.138	1.418	0.894	2.249
TCF7L2
TT	24	20	78	65	<0.001	3.433	1.885	6.252
TC	42	35	18	15	0.001	0.288	0.137	0.603
CC	54	45	24	20	<0.001	0.294	0.148	0.583
TC + CC	96	80	42	35	<0.001	0.291	0.16	0.53
T	90	37.5	174	72.5	<0.001	2.505	1.669	3.761
C	150	62.5	66	27.5	<0.001	0.399	0.266	0.599

T1DM: Type 1 diabetes mellitus. PPARɣ: Peroxisome proliferator–activated receptor gamma. AR: aldose reductase. TCF7L2: Transcription Factor 7-Like 2. P > 0.05 is considered non-significant, P < 0.05 is considered significant. OR, odds ratio; OR > 1 indicates increased occurrence of event. OR < 1 indicates decreased occurrence of event; CI, confidence interval. Logistic regression test was used

PPARɣ2 CT showed a significantly lower proportion in type 2 diabetics compared to the control group (P = 0.024), with a protective effect against T2DM development within healthy subjects (OR = 0.535). PPARɣ2 TT genotypes showed a significantly higher proportion in type 2 diabetics when compared to the control group (P = 0.022), with a risk to develop DM within healthy individuals. AR TT, CT + TT genotypes showed a significantly higher proportion in type 2 diabetic patients when compared to the control group (P = 0.039, 0.048), with the risk to develop T2DM within healthy individuals (OR CT + TT = 1.322). Otherwise, studied TCF7L2 SNPs showed no significant association with T2DM susceptibility within healthy subjects (P > 0.05 ((Table 3).

Table 3.

Comparison of studied genotypes and alleles between control and type 2 diabetics

Genotypes and alleles	Control N = 120		T2DM N = 140		P	OR	95% CI
	N	%	N	%
PPARɣ
CC	69	57.5	96	68.6	0.245	1.344	0.817	2.211
CT	51	42.5	26	18.6	0.024	0.535	0.311	0.922
TT	0	0	18	12.9	0.022	–	–	–
CT + TT	51	42.5	44	31.4	0.245	0.744	0.452	1.225
C	189	78.8	218	77.9	0.877	0.968	0.642	1.460
T	51	21.3	62	22.1	0.877	1.033	0.685	1.558
AR
CC	75	62.5	72	51.4	0.261	0.757	0.465	1.230
CT	45	37.5	54	38.6	0.589	1.148	0.695	1.896
TT	0	0	14	10	0.039	–	–	–
CT + TT	45	37.5	68	48.6	0.048	1.322	0.813	2.149
C	195	81.3	198	70.7	0.082	0.700	0.468	1.047
T	45	18.8	82	29.3	0.082	1.428	0.955	2.135
TCF7L2
TT	24	20	38	27.1	0.400	1.277	0.723	2.254
TC	42	35	46	32.9	0.494	0.798	0.418	1.523
CC	54	45	56	40	0.412	0.772	0.416	1.433
TC + CC	96	80	102	72.9	0.400	0.783	0.444	1.383
T	90	37.5	122	43.6	0.379	1.168	0.827	1.650
C	150	62.5	158	56.4	0.379	0.856	0.606	1.210

T2DM: Type 2 diabetes mellitus. PPARɣ: Peroxisome proliferator–activated receptor gamma. AR: aldose reductase. TCF7L2: Transcription Factor 7-Like 2. P > 0.05 is considered non-significant, P < 0.05 is considered significant. OR, odds ratio; OR > 1 indicates increased occurrence of event. OR < 1 indicates decreased occurrence of event; CI, confidence interval. Logistic regression test was used

Regression analysis was conducted for the prediction of both T1DM and T2DM using age, gender, creatinine, lipid profile, PPARɣ2, AR, TCF7L2 genotypes as covariates. According to T1DM PPARɣ2 rs3856806 TT, AR rs759853 CT, TCF7L2 rs7903146 TT genotypes were significantly associated with the risk of T1DM. In addition, TCF7L2 TC, CC genotypes were significantly associated with a decrease in the risk of T1DM in univariable analysis. However, taking significant covariates in univariable analysis into multivariable analysis revealed that PPARɣ2 rs3856806 TT, TCF7L2 rs7903146 TT were suggested to be independent risk predictors for T1DM susceptibility. On the other hand, TCF7L2 rs7903146 TC, CC genotype were suggested to be independent protective factors against DM development (Table 4). Regarding type 2 diabetics, PPARɣ2 rs3856806 TT, AR rs759853 TT genotypes were suggested to be independent risk predictors for T2DM susceptibility. Furthermore, the PPARɣ2 rs3856806 CT genotype was suggested to be an independent protective factor against T2DM development (Table 5).

Table 4.

Regression analysis for prediction of T1DM within healthy individual

Factors		Univariable				Multivariable
		p	OR	95% CI		p	OR		95% CI
Age		0.552	1.010	0.993	1.022
Gender		0.261	0.770	0.489	1.214
Creatinine		0.108	1.624	0.514	3.303
TG		0.980	1.009	0.999	1.013
TC/HDL		0.109	1.120	0.981	1.301
LDL/HDL		0.166	1.132	0.950	1.350
PPARɣ2	CC	0.417	0.756	0.566	1.473	0.387	0.509	0.127	1.350
	CT	0.439	0. 874	0.456	1.444	0.487	0.567	0.598	1.409
	TT	<0.001	–	–	–	<0.001	–	–	–
AR	CC	0.149	0.398	0.198	1.398	0.122	0.287	0.188	1.255
	CT	0.039	1.427	0.976	2. 563	0.056	1.546	0.875	2.654
	TT	0.994	–	–	–	0.890	–	–	–
TCF7L2	TT	0.017	1.808	1.112	2.939	0.003	1.504	1.192	1.849
	TC	0.045	0.560	0.318	0.986	0.043	0.355	0.263	0.817
	CC	0.028	0.548	0.320	0.938	0.031	0.628	0.214	0.989

TG: Triglyceride. TC: Total cholesterol. HDL: High-density lipoprotein. LDL: Low-density lipoprotein. PPARɣ: Peroxisome proliferator–activated receptor gamma. AR: aldose reductase. TCF7L2: Transcription Factor 7-Like 2. P < 0.05 is considered significant. OR, odds ratio; OR > 1 indicates increased occurrence of event. OR < 1 indicates decreased occurrence of event (protective exposure). CI, confidence interval. Logistic regression was used

Table 5.

Regression analysis for prediction of T2DM within healthy individual

Factors		Univariable				Multivariable
		p	OR	95% CI		p	OR		95% CI
Age		0.544	1.008	0.989	1.023
Gender		0.269	0.767	0. 497	1.216
Creatinine		0.109	1.729	0.486	3.299
TG		0.978	1.006	1.001	1.017
TC/HDL		0.111	1.121	0.979	1.297
LDL/HDL		0.159	1.129	0.946	1.345
TCF7L2	TT	0.410	1.198	0.487	1.298
	TC	0.329	0.698	0.387	1.476
	CC	0.429	0.487	0.198	1.398
PPARɣ2	CC	0.387	1.287	0.826	2.928	0.241	1.358	0.776	2.897
	CT	0.049	0.621	0.384	0.904	0.036	0.476	0.198	0.820
	TT	<0.001	–	–	–	<0.001	–	–	–
AR	CC	0.146	0.723	0.467	1.119	0.387	0.684	0.198	1.810
	CT	0.302	1.265	0.810	1.975	0.234	1.593	0.248	1.905
	TT	<0.001	–	–	–	<0.001	–	–	–

TG: Triglyceride. TC: Total cholesterol. HDL: High-density lipoprotein. LDL: Low-density lipoprotein. PPARɣ: Peroxisome proliferator–activated receptor gamma. AR: aldose reductase. TCF7L2: Transcription Factor 7-Like 2. P < 0.05 is considered significant. OR, odds ratio; OR > 1 indicates increased occurrence of event. OR < 1 indicates decreased occurrence of event (protective exposure). CI, confidence interval. Logistic regression was used

Discussion

Diabetes mellitus, a global public health concern, is one of the fastest-growing diseases in the world [21]. Diabetes is associated with serious complications affecting the patient’s health, productivity, and quality of life. In addition, these complications increase morbidity and mortality for diabetics. Diabetic complications include macrovascular complications, caused by damage to larger blood vessels, such as cardiovascular disease, and microvascular complications, caused by damage to small blood vessels, such as neuropathy, retinopathy, and nephropathy [22]. Diabetes caused about 4.6 million deaths every year. In addition, DM causes renal disease at the end-stage which requires dialysis or kidney transplantation and it is the main cause of diabetic retinopathy and blindness due to damage to the o retina [23]. Both genetic and environmental factors have a vital role in increasing the risk of the development of diabetes [24]. Single nucleotide polymorphisms (SNPs), the basis of complex diseases, are variations found at single bases within the DNA sequence of a genome. Identifying the SNPs responsible for the complex diseases development help in earlier diagnosis, prevention, and treatment of the disease [25]. Therefore, the present study aimed to investigate the relation between aldose reductase C106T (rs759853), TCF7L2 (rs7903146), and PPARɣ2 C161T (rs3856806) gene polymorphisms and the risk of type 1 and type 2 diabetes susceptibility in the Egyptian population.

The present study revealed that the studied groups are matched as regards age and gender. Higher concentrations of FBG, PPB, G, and HbA1c were significantly associated with diabetics than control subjects (p < 0.001). The concentration of HDL had significantly lower in type 2 diabetics than in healthy individuals (P < 0.001). No significant differences in creatinine level, BMI, eGFR, and lipid profile between diabetic groups when compared to the control group.

A similar study found that all diabetic patients had a significant increase in FBS, PPBG, and HbA1c (P = 0.001) compared to the control group [26]. Another study investigated a significant increase in serum creatinine, FBG, PPBG, and HbA1c levels in type 1 and type 2 diabetic patients when compared to the healthy subjects. These levels were higher in type 1 diabetics when compared to type 2 diabetics [27]. An Egyptian study carried on type 2 diabetics found that regarding GFR stages, 25.8% of the patients are of G1 (> 90) and 31.8% G2 (60–89) [28].

The present study indicated that carriers of TT genotype and T allele of PPARγ2 SNP were associated with increase the risk to develop T1DM, Furthermore, C allele carriers have a protective effect against the risk of T1DM susceptibility. Besides, PPARɣ2 TT genotypes had a risk to develop T2DM. While CT carriers have a protective effect against the risk of T2DM susceptibility within healthy individuals.

Similarly, TT genotype and T allele of rs3856806 PPARγ2 were associated with an increased risk of T2DM in the Chinese population [29, 30]. While T allele of PPARγ2 (rs3856806) reduced the risk of diabetes by 44% and it might be protective against type 2 diabetes [31]. Conversely, PPARγ2 (rs3856806) was no association with the type 2 diabetics West Bengal population in India [32]. A meta-analysis concluded that the T allele of PPARɣ2 was associated with increased risk of coronary heart disease [33], colorectal cancers [34], colonic adenomas [35], and ulcerative colitis [36].

Aldose reductase is an NADPH-dependent protein. It is the first enzyme in the polyol pathway. The activity of AR is elevated by hyperglycemia in the tissues of diabetics causing oxidative stress and inflammation [37].

Regarding AR C106T SNP (rs759853), the present study showed that CT, CT + TT genotypes carriers had a risk to develop T1DM within healthy controls. In addition, AR TT and CT + TT carriers had a risk of susceptibility of T2DM within healthy controls.

Similarly, AR gene polymorphism was associated with susceptibility to diabetes in the Egyptian population [38]. Another study found that the C allele of the AR polymorphism was significantly higher in type 2 diabetics than in control individuals [39]. In Japanese type 2 diabetics, the genotype distributions of the AR gene polymorphism were (68.5, 27.8, and 3.7%; respectively) for CC, CT, and TT in the diabetics, and (63.8, 33.8, 2.4%) for CC, CT, and TT in the control group. The C allele frequencies were 82.6% in the diabetics and 80.7% in healthy control [40].

TCF7L2, a transcription factor, is a member of the T cell family. It plays an important role in the WNT signaling pathway through regulating cell differentiation and proliferation [41]. TCF7L2 has a vital role in regulating glucose metabolism in the pancreas and liver [42].

The current study found that TC, CC, TC + CC genotypes, and C allele carriers of TCF7L2 (rs7903146) had a protective effect against T1DM development within healthy controls. TCF7L2 TT and T allele carriers had a risk to develop T1DM within healthy control subjects. While no significant association was detected between TCF7L2 SNP and T2DM susceptibility within the healthy individual.

Similarly, there was no association between rs7903146 SNP of TCF7L2 and susceptibility of type 2 diabetes in the Egyptian population [43], type 2 Euro-Brazilian diabetic patients [44], and type 2 diabetics in Jahrom city, Iran [45]. Conversely, the TCF7L2 gene was associated with the risk of T2DM development in different populations including the Egyptian population [46, 47], Sudanese and Turkish populations [48, 49], Chinese Han population [50], and Caucasian, East Asian, South Asian and other ethnicities [51]. On the other hand, T allele and TT genotype of TCF7L2 (rs7903146) were associated with a lower risk of type 2 diabetic Egyptian patients [52]. In the North Indian population and Cameroon population, [53, 54] carrier of T allele of TCF7L2 had a protective effect against diabetes.

According to logistic regression analysis, the present study revealed that AR rs759853 CT genotype was significantly associated with the risk of T1DM. Besides, PPARɣ2 rs3856806 TT, TCF7L2 rs7903146 TT, genotypes were suggested to be independent risk predictors for T1DM development. Moreover, TCF7L2 TC, CC genotype were suggested to be independent protective factors against T1DM development. On the other hand, PPARɣ2 rs3856806 TT, AR rs759853 TT genotypes were suggested to be independent risk predictors for T2DM susceptibility, and PPARɣ2 rs3856806 CT genotype were suggested to be independent protective factors against T2DM development.

Logistic analysis revealed that age or gender had no significant association with the risk of diabetes. While, higher FBG, HbA1c, triglyceride, total cholesterol, LDL, lower HDL, rs1801278 (GA + AA) were associated with the risk of T2DM development [55]. The differences between this study and previous studies could be related to the various data collection techniques, different sample sizes, different environmental factors. Besides, various ethnicity of the study cohorts, different characteristics of the populations, and different lifestyles lead to heterogeneity over different studies [56]. A limitation of this study is the small sample size. Hence, further studies on a larger number of diabetics evaluating different polymorphisms are needed to detect the genetic susceptibility to diabetes.

Conclusion

The present study revealed that PPARγ2 (rs3856806), TCF7L2 (rs7903146) and AR (rs759853) gene polymorphism may play an important role in the susceptibility of diabetes. Therefore, they provide a promising key for the prognosis of diabetes which enables early intervention. Further studies should be held on a larger scale with a larger sample size to reach optimal levels of knowledge about DM genetic factors hoping to limit its occurrence and prevention of its complications.

Declarations

Declaration of interest

The authors declared that there is no conflict of interest. The authors alone are responsible for the content and writing of this article.

Ethical approval

This study was ethically approved by Mansoura University Ethics Committee at the Faculty of Science (Sci-ch-ph -2020-28).

Informed consent

All the authors have read the manuscript and given their consent to Participate and Publish.