Glyoxalase I and Aldose Reductase Gene Polymorphisms and Susceptibility to Carotid Atherosclerosis in Type 2 Diabetes

Abstract

Aims: To investigate the association of polymorphisms of glyoxalase I (GLO1) A419C, GLO1 C-7T, and aldose reductase C-106T with type 2 diabetes and diabetic carotid atherosclerosis in a Chinese Han population. Methods: The study population included 362 patients with type 2 diabetes and 301 nondiabetic control subjects. Genetic analyses were performed using either the Taqman polymerase chain reaction or direct sequencing. All patients with diabetes underwent carotid ultrasonography to assess the intima-media thickness and the presence of atherosclerotic plaques. Results: There were no differences between the genotype frequencies of GLO1 A419C, GLO1 C-7T, and aldose reductase C-106T polymorphisms, in the control and diabetic groups. The value of mean carotid intima-media thickness and the prevalence of carotid atherosclerotic plaques were significantly increased in patients with type 2 diabetes with the GLO1-7CC genotype compared with those with the -7CT and TT genotypes (permutation p = 0.003 and 0.031, respectively). Multiple regression analysis showed that the GLO1-7CC genotype was an independent determinant of carotid intima-media thickness (β = 0.12, p = 0.014), but not an independent risk factor for carotid atherosclerotic plaques (odds ratio [OR] = 1.74, 95% CI 0.89-3.42, p = 0.10) in patients with type 2 diabetes.Conclusions: The GLO1 C-7T polymorphism is associated with carotid atherosclerosis in Chinese patients with type 2 diabetes.

Introduction

In patients with diabetes, the major cause of mortality and morbidity is cardiovascular disease (CVD), mainly due to markedly advanced atherosclerosis (Kannel et al., 1979). The risk of developing CVD escalates with an increasing number of conventional risk factors such as diabetes, hypertension, dyslipidemia, and smoking. However, these conventional factors cannot entirely account for the risk of CVD because atherosclerosis is a complex multifactorial disease with both genetic and environmental determinants (Lusis et al., 2004; Nabel, 2003). To date, many genetic polymorphisms have been found to have associations with atherosclerosis in both the general and diabetic populations (Humphries and Morgan, 2004; Wolff et al., 2005; Yamasaki et al., 2006).

The onset and progression of diabetic macrovascular complications have clear linkages to the accumulation of advanced glycation end products (AGEs) (Kilhovd et al., 1999; Brownlee, 2001), as confirmed by epidemiological studies. AGEs may be associated with atherosclerosis in many ways, including enhancement of endothelial dysfunction, elevation of vascular low-density lipoprotein (LDL) levels, increase in plaque destabilization, induction of neointimal hyperplasia, and inhibition of vascular repair after injury (Goldin et al., 2006; Huebschmann et al., 2006).

One of the most reactive precursors for AGE formation is methylglyoxal (MG), a reactive glycolysis-derived dicarbonyl metabolite. This compound also has a direct effect on the structure and function of blood vessels (Brownlee, 2001; Chang et al., 2005). Two enzymatic pathways are known to participate in MG catabolism. The first pathway is the glyoxalase system, which consists of glyoxalase I (GLO1) and glyoxalase II. This system converts MG to D-lactate via the intermediate (S)-D-lactoylglutathione, using reduced glutathione as a cofactor. The second pathway, the aldose reductase (ALR) pathway, can convert MG to acetol using NADPH as a cofactor (Chang et al., 2002). The activity and expression of these enzymatic pathways may be related to atherosclerosis risk in patients with diabetes, because both pathways are prevalent in cardiovascular tissues (Baba et al., 2009).

Experimental evidence shows that overexpression or inactivation of GLO1 and ALR may be related to AGE formation and vascular function (Shinohara et al., 1998; Ahmed et al., 2008; Baba et al., 2009). Polymorphisms in GLO1 A419C (rs2736654), GLO1 C-7T (rs1049346), and ALR C-106T (rs759853) alter the activity and expression of both enzymes and are associated with hemodialysis-related vascular complications, plasma coagulation factor XIII concentration, and diabetic microvascular complications, respectively (Yang et al., 2003; Gale et al., 2004; Kalousová et al., 2008). Thus, these polymorphisms may be potent determinants of atherosclerosis.

Carotid intima-media thickness (CIMT) and carotid atherosclerotic plaques (CAP) are quantitative measurements of carotid atherosclerosis and have significant predictive values for subsequent stroke and myocardial infarction (Salonen et al., 1991; O'Leary et al., 1999; Hollander et al., 2002). The measurement of CIMT and assessment of CAP by high-resolution ultrasound offers an experimental approach for studying the association between genetic predisposition and CVD. The aim of the present study was to evaluate whether GLO1 A419C, GLO1 C-7T, and ALR C-106T polymorphisms are associated with type 2 diabetes and diabetic carotid atherosclerosis in a Chinese Han popu1ation.

Materials and Methods

Subjects

A total of 362 unrelated Chinese Han patients with type 2 diabetes (169 men and 193 women, mean age 62.2 ± 10.3 years), being treated at Shanghai Jiao Tong University Affiliated First People's Hospital from 2007 to 2009, were enrolled in this study. Type 2 diabetes was diagnosed on the basis of WHO criteria. Exclusion criteria were current malignancy, history of ketoacidosis, positive for glutamic acid decarboxylase antibody, severe kidney or liver disease, a recent ischemic event, or corticosteroid use.

The control group consisted of 301 healthy Chinese volunteers (154 men and 147 women, mean age 60.0 ± 8.0 years) with no personal or family history of diabetes. The study protocol was designed according to the Declaration of Helsinki and was approved by the Ethics Committee of the Shanghai Jiao Tong University Affiliated First People's Hospital.

Laboratory analysis

The patients received a standard questionnaire containing questions regarding age, gender, height, weight, smoking history, age at diabetes onset, and duration and treatment of diabetes. Body mass index (BMI) was calculated as body weight in kilograms divided by height in square meters. Blood pressure (BP) was measured twice using a mercury sphygmomanometer, with participants in a seated position, after a 5-min rest. The mean of two readings was measured 1 min apart. Hypertension was defined as BP ≥140/90 mmHg and/or treatment with antihypertensive drugs.

Blood samples were drawn after overnight fasting to determine fasting plasma glucose (FPG), HbA1c, serum total cholesterol (TC), serum triglyceride (TG), serum high-density lipoprotein cholesterol (HDL-C), and serum LDL cholesterol (LDL-C) levels. FPG was measured by the hexokinase method, whereas TC, TG, HDL-C, and LDL-C were measured by enzymatic methods. HbA1c was measured by high-performance liquid chromatography.

Carotid ultrasonography

All patients with diabetes underwent carotid ultrasonography using an echotomographic system (HDI 5000, Philips ATL) with a 7.5 MHz probe. Both the near and far wall of the common carotid and internal and external carotids, as well as the carotid bifurcations on both sides, were evaluated online for the presence of atherosclerotic plaques. These were defined by a focal increase in thickness of 0.5 mm or 50% of the surrounding vessel wall (Mansia et al., 2007).

CIMT was measured in the far wall of the common carotid artery, 1 cm proximal to the carotid bulb, in a plaque-free region. Mean CIMT was calculated by averaging three measurements of CIMT at each of three scan planes (anterior, lateral, and posterior), from both the right and left common carotid arteries (a total of 18 measurements).

Genotyping of polymorphisms

Genomic DNA from peripheral blood was extracted using a commercially available kit (Qiagen) according to the manufacturer's instructions. The GLO1 A419C polymorphism and ALR C-106T polymorphism were genotyped by the Taqman polymerase chain reaction (PCR) method. The primers and probes are shown in Table 1. PCR was performed with a Rotorgene 6000 (Qiagen) under the following conditions: 45 cycles of 95°C for 10 s and 60°C for 60 s. GLO1 C-7T polymorphism was genotyped by PCR and direct sequencing. The primers are shown in Table 1. Amplification was performed with preheating at 95°C for 5 min, followed by denaturation at 95°C for 45 s, annealing at 60°C for 45 s, and extension at 72°C for 1 min for 30 cycles. The products were sequenced using a CEQ 8800 genetic analysis system (Beckman Coulter).

Table 1.

Primers and Probes Used for the Amplification of GLO1 and ALR Polymorphisms

SNP		Primers and probes
GLO1 A419C	Forward	ACATTGTAGCTATGTTTTCCTTCC
	Reverse	ACAGGCAAACTTACCGAATCC
	A-allele-specific probe	JUP-TGATGAGACCCAGAGTT-JUP
	C-allele-specific probe	MAR-TGATGCGACCCAGAGT-MAR
ALR C-106T	Forward	GCGAAGGAGCCTTCTGATT
	Reverse	GAAAGAATCCGCTGCCACT
	C-allele-specific probe	MAR-TTGCGCTGGGGGTGCCG-MAR
	T-allele-specific probe	JUP-TTGCGCTAGGGGTGCCGC-JUP
GLO1 C-7T	Forward	TGAGTTTGCCTCCTTTATGC
	Reverse	GATCGCCCCATCAAACAC

Statistical analyses

Descriptive data were expressed as means ± standard deviation and analyzed by a two-sample t-test or one-way analysis of variance. Variables without normal distribution (Serum TG and HbA1C) were expressed as medians with ranges and were analyzed after log or arctangent transformation. Categorical data were expressed as numbers and percentages and compared using the chi-squared test or Fisher exact test. Allele distribution was verified for Hardy-Weinberg equilibrium using the chi-square test. The haplotype analysis for two GLO1 gene polymorphisms was done using the SHEsis (Shi and He, 2008). Multiple linear regression and logistic regression analysis were used to evaluate the association between GLO1-7CC genotype and other risk factors with CIMT and CAP. A permutation test with 1000 permutations was applied to correct multiple comparisons using the SAS System (SAS Institute, Inc.). A two-tailed p-value <0.05 was considered statistically significant. Analyses, except the permutation test, were performed using the SPSS statistical package for Windows, version 13.0 (SPSS).

Results

Table 2 shows the basic characteristics of control subjects and patients with type 2 diabetes. There were no differences in gender, serum TC, or serum LDL-C between the two groups. The diabetic group had statistically higher values for age, BMI, BP, FPG, serum TG, serum HDL-C, and HbA1c compared with the control group. Genotypic frequencies of the three polymorphisms did not deviate from the Hardy-Weinberg equilibrium in either the control or the diabetic groups. There were also no differences in genotype or allele frequencies of these polymorphisms for the two groups. In addition, the analysis of haplotype distribution for the GLO1 gene polymorphisms was performed. There were just three haplotypes (C-A, T-A, T-C) in both groups characterized by frequency >5%. None of the haplotypes were associated with type 2 diabetes (Supplementary Table Sl; Supplementary Data are available online at www.liebertonline.com/gtmb).

Table 2.

Basic Characteristics of Control Subjects and Patients with Type 2 Diabetess

	Control subjects	Patients with diabetes	p
Number (M/F)	301 (154/147)	362 (169/193)	0.25
Age (y)	60.0 ± 8.0	62.2 ± 10.3	<0.01
BMI (kg/m²)	24.3 ± 2.3	25.0 ± 3.4	0.01
Hypertension, n (%)	57 (18.9)	228 (63)	<0.01
SBP (mmHg)	128.7 ± 15.6	133.0 ± 15.9	<0.01
DBP (mmHg)	75.8 ± 8.8	79.3 ± 8.9	<0.01
FPG (mmol/L)	4.9 ± 0.6	8.5 ± 2.9	<0.01
HbA1C (%)	5.2 (4.2-6.4)	8.7 (4.8-16.4)	<0.01
TC (mmol/L)	4.9 ± 0.9	5.0 ± 1.0	0.15
TG (mmol/L)	1.5 (0.4-13.0)	1.6 (0.5-7.8)	0.04
HDL-C(mmol/L)	1.3 ± 0.3	1.1 ± 0.2	<0.01
LDL-C(mmol/L)	2.8 ± 0.8	2.9 ± 0.8	0.10
GLO1 A419C genotype
AA, n (%)	237 (78.7)	285 (78.8)	0.97
AC, n (%)	62 (20.6)	74 (20.4)
CC, n (%)	2 (0.7)	3 (0.8)
A allele frequency	89.0	89.0	0.96
GLO1 C-7T genotype
CC, n (%)	54 (17.9)	67 (18.5)	0.93
CT, n (%)	128 (42.5)	157 (43.4)
TT, n (%)	119 (39.5)	138 (38.1)
C allele frequency	39.2	40.2	0.71
ALR C-106T genotype
CC, n (%)	203 (67.4)	242 (66.9)	0.93
CT, n (%)	88 (29.2)	106 (29.3)
TT, n (%)	10 (3.3)	14 (3.9)
C allele frequency	82.1	81.5	0.79

Data are expressed as mean ± standard deviation, median (range) or percentages.

BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; FPG, fasting plasma glucose; TC, total cholesterol; TG, triglycerides; HDL-C, high-density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol.

Clinical and biochemical characteristics of the patients with diabetes, grouped according to the genotypes of GLO1 A419C, GLO1 C-7T, and ALR C-106T polymorphisms, are shown in Table 3. Patients with the GLO1-7CC genotype had higher serum TG levels than those with the GLO1-7CT and TT genotype (p = 0.01, permutation p = 0.008). However, there were no other statistically significant differences between the respective genotypes of the three polymorphisms, including age, gender, duration of diabetes, BMI, BP, HbA1c, serum cholesterol, and treatment of diabetes or atherosclerosis.

Table 3.

Clinical and Biochemical Characteristics of Type 2 Diabetic Subjects According to GLO1 and ALR Polymorphisms

	GLO1 A419C				GLO1 C-7T				ALR C-106T
	AA	AC	CC	p	CC	CT	TT	p	CC	CT	TT	p
Number (M/F)	285 (139/146)	74 (28/46)	3 (2/1)	0.23	67 (36/31)	157 (77/80)	138 (56/82)	0.15	242 (124/118)	106 (40/66)	14 (5/9)	0.05
Age (y)	62.0 ± 10.3	62.0 ± 9.9	60.3 ± 12.7	0.96	62.8 ± 9.6	61.5 ± 10.4	62.0 ± 10.4	0.70	61.9 ± 10.4	62.1 ± 9.9	60.9 ± 9.7	0.92
Duration of diabetes (y)	11.8 ± 7.3	10.6 ± 6.7	9.0 ± 4.0	0.35	11.9 ± 7.3	11.3 ± 6.8	11.5 ± 7.4	0.87	11.4 ± 6.9	11.6 ± 7.9	12.0 ± 5.1	0.94
Smoking habit, n (%)	86 (30.1)	17 (23.0)	1 (33.3)	0.51	20 (29.9)	49 (31.2)	35 (25.4)	0.53	77 (31.8)	25 (23.6)	2 (14.3)	0.13
BMI (kg/m²)	25.0 ± 3.2	25.3 ± 4.0	21.6 ± 4.2	0.15	25.6 ± 3.4	24.6 ± 3.2	25.1 ± 3.6	0.12	24.9 ± 3.5	25.2 ± 3.2	25.9 ± 3.4	0.44
Hypertension, n (%)	184 (63.9)	41 (55.4)	3 (100%)	0.14	42 (62.7)	97 (61.8)	89 (64.5)	0.89	149 (61.6)	68 (64.2)	11 (78.6)	0.42
SBP (mmHg)	134.2 ± 15.3	135.1 ± 14.6	145.0 ± 18.0	0.45	135.1 ± 14.6	134.2 ± 15.7	134.7 ± 15.0	0.91	134.1 ± 14.6	135.5 ± 16.3	136.1 ± 15.7	0.67
DBP (mmHg)	79.6 ± 8.8	79.3 ± 8.7	85.0 ± 15.0	0.54	80.7 ± 8.7	79.8 ± 9.1	78.8 ± 8.5	0.34	79.6 ± 8.9	79.5 ± 8.7	80.4 ± 8.4	0.94
FPG (mmol/L)	8.5 ± 2.7	8.6 ± 3.3	8.5 ± 3.3	0.97	8.4 ± 2.5	8.5 ± 3.0	8.5 ± 2.8	0.98	8.5 ± 2.8	8.5 ± 2.9	9.3 ± 3.3	0.58
HbA1C (%)	8.7 (4.8-16.4)	8.8 (5.5-15.3)	7.6 (6.3-7.8)	0.33	8.7 (4.8-13.8)	8.8 (5.5-16.4)	8.6 (5.6-14.6)	0.98	8.7 (5.5-16.4)	8.7 (4.8-13.9)	9.2 (5.8-14.0)	0.44
TC (mmol/L)	4.9 ± 1.1	5.1 ± 0.9	5.6 ± 0.4	0.29	5.0 ± 1.1	5.0 ± 1.0	5.0 ± 1.0	0.93	4.9 ± 1.0	5.1 ± 1.0	5.1 ± 0.5	0.40
TG (mmol/L)	1.5 (0.5-7.8)	2.0 (0.5-6.2)	2.2 (0.9-2.6)	0.40	1.8 (0.6-7.7)	1.5 (0.5-5.4)	1.6 (0.5-7.8)	0.01	1.5 (0.5-7.8)	1.6 (0.5-6.3)	2.1 (1.2-7.7)	0.20
HDL-C (mmol/L)	1.1 ± 0.2	1.1 ± 0.2	1.3 ± 0.3	0.21	1.1 ± 0.2	1.1 ± 0.2	1.1 ± 0.3	0.36	1.1 ± 0.2	1.2 ± 0.3	1.1 ± 0.2	0.15
LDL-C (mmol/L)	2.9 ± 0.9	2.9 ± 0.7	3.3 ± 0.2	0.57	2.8 ± 0.9	2.9 ± 0.8	2.9 ± 0.8	0.73	2.8 ± 0.8	3.0 ± 0.8	2.8 ± 0.6	0.46
Diabetic medication
Insulin therapy, n (%)	103 (36.1)	22 (29.7)	1 (33.3)	0.70	27 (40.3)	53 (33.8)	46 (33.3)	0.58	82 (33.9)	38 (35.8)	6 (42.9)	0.75
Sulfonylurea n (%)	154 (54.0)	42 (56.8)	2 (66.7)	0.88	34 (50.7)	86 (54.8)	78 (56.5)	0.74	140 (57.9)	52 (49.1)	6 (42.9)	0.21
Metformin n (%)	105 (36.8)	28 (37.8)	1 (33.3)	0.95	26 (38.8)	58 (36.9)	50 (36.2)	0.94	87 (36.0)	43 (40.6)	4 (28.6)	0.57
Thiazolidinediones n (%)	40 (14.0)	12 (16.2)	0 (0)	0.82	11 (16.4)	20 (12.7)	21 (15.2)	0.72	37 (15.3)	12 (11.3)	3 (21.4)	0.48
Antidyslipidemic therapy, n (%)	82 (28.8)	27 (36.5)	1 (33.3)	0.50	24 (35.8)	44 (28.0)	42 (30.4)	0.51	69 (28.5)	34 (32.1)	7 (50.0)	0.22
Antiplatelet therapy, n (%)	84 (29.5)	17 (23.0)	1 (33.3)	0.66	16 (23.9)	49 (31.2)	37 (26.8)	0.49	70 (28.9)	29 (27.4)	3 (21.4)	0.84
Mean CIMT(mm)	0.69 ± 0.13	0.68 ± 0.12	0.60 ± 0.05	0.29	0.73 ± 0.14	0.68 ± 0.12	0.68 ± 0.13	0.01	0.69 ± 0.14	0.70 ± 0.12	0.67 ± 0.11	0.75
CAP, n (%)	156 (54.7)	36 (48.6)	2 (66.6)	0.55	44 (65.7)	85 (54.1)	65 (47.1)	0.04	128 (52.9)	58 (54.7)	8 (57.1)	0.92

Data are expressed as means ± standard deviation, median (range) or percentages.

CIMT, carotid intima-media thickness; CAP, carotid atherosclerotic plaques.

As shown in Table 3, the mean CIMT and the prevalence of CAP exhibited statistically significant differences among genotypes of GLO1 C-7T polymorphism in patients with diabetes (p = 0.01, 0.04, respectively). The differences remained significant in a permutation test (p = 0.002, 0.02, respectively). Patients with diabetes with the GLO1-7CC genotype had significantly higher mean CIMT values than did those with GLO1-7CT+TT genotypes (CC: 0.73 ± 0.14 mm vs. CT+TT: 0.68 ± 0.12 mm, p = 0.007, permutation p = 0.003). The prevalence of CAP was also increased in GLO1-7CC carriers (CC: 65.7% vs. CT+TT: 50.8%, p = 0.028, permutation p = 0.031). Multiple regression analysis showed that age (β = 0.29, p < 0.01), systolic BP (β = 0.13, p = 0.011), LDL-C (β = 0.13, p = 0.014), and GLO1-7CC genotype (β = 0.12, p = 0.014) were independent determinants of mean CIMT in patients with type 2 diabetes (Table 4). The GLO1-7CC genotype was also significantly associated with a risk of having carotid atherosclerotic plaques, as shown by the univariate logistic regression analysis (OR = 1.88, 95% CI 1.06-3.33, p = 0.03). However, this association was lost after adjustments were made for age, gender, BMI, BP, HbA1c, lipid profiles, and smoking status in the multivariate logistic regression model (OR = 1.74, 95% CI 0.89-3.42, p = 0.10). No differences were found between the values of mean CIMT and the prevalence of CAP for GLO1 A419C and ALR C-106T polymorphisms in patients with type 2 diabetes.

Table 4.

Association of GLO1 C-7T Polymorphism with Mean CIMT

	CIMT
	β	p
Age	0.29	<0.01
Female	−0.02	0.80
Smoking history	0.13	0.05
BMI	0.02	0.66
SBP	0.13	0.011
TG	−0.03	0.62
HDL-C	−0.06	0.30
LDL-C	0.13	0.014
HbA1c	0.07	0.19
GLO1-7CC genotype^a	0.12	0.014

CC was encoded as 1, CT/TT as 0.

Discussion

In diabetes, the accumulation of excess glucose drives several damage pathways and raises the MG concentration. In turn, MG perpetuates vascular injury responsible for long-term complications of diabetes, because it has the capacity to change the structure and function of proteins and accelerate oxidative damage directly or indirectly (Price and Knight, 2009). GLO1 and ALR, as the two main enzymes that participate in the catabolism of MG, are, therefore, expected to be important in controlling diabetic vascular complications.

Overexpression of GLO1 can reverse the hyperglycemia-induced AGE formation and angiogenesis deficit in endothelial cells (Shinohara et al., 1998; Ahmed et al., 2008). GLO1 overexpression can also ameliorate renal ischemia-reperfusion injury in rats (Kumagai et al., 2009). Miyata et al. (2001) reported a case of a Japanese woman under chronic hemodialysis who showed multiple cardiovascular complications despite the absence of significant risk factors but had a clear deficiency of GLO1 and unusually high levels of AGEs.

Polymorphisms in GLO1 A419C and C-7T may alter the expression and/or activity of GLO1. The A419C polymorphism places an alanine (CC) or glutamic acid (AA) residue at position 111 in the protein. In the case of glutamate substitution, the presence of an additional acidic charge from Glu111 results in a conformational change of the protein and decreased enzyme activity (Junaid et al., 2004). The C-7T polymorphism is located within the minimal promoter and approximates a DNA-dependent RNA polymerase site. The C allele is predicted to bind GC-binding factor, which is a transcription factor that represses transcription, leading to the reduction GLO1 expression compared with that of the T allele (Kageyama and Pastan, 1989; Gale et al., 2004).

The current study showed that the allele frequencies and haplotype distributions of the two GLO1 polymorphisms did not differ between diabetic and control groups. This result is consistent with most of the previous studies conducted in different populations (Kirk et al., 1985; Mimura et al., 1990). However, Degaffe et al. (2008) reported that the A allele for the A419C polymorphism is associated with type 2 diabetes in Zuni Indians. Unfortunately, the small sample size severely limited the generalization of their study. On the other hand, conflicting findings have been reported regarding the relationship of GLO1 polymorphisms and vascular damage. In healthy Caucasian pedigrees, a significant association was found between polymorphisms of A419C and C-7T and concentrations of plasminogen activator inhibitor-1 and factor XIII A2B2 complex. Both plasminogen activator inhibitor-1 and factor XIII are important factors in the development of coronary heart and diabetic vascular disease (Gale et al., 2004). Kalousová et al. (2008) demonstrated a higher prevalence of CVD and peripheral vascular disease as well as higher levels of serum AGE receptors in the CC genotype of the A419C polymorphism in Caucasian patients with hemodialysis. However, a recent study showed that these two polymorphisms are not associated with CIMT, ankle-arm index, prevalence of hypertension, or AGE concentration in two cohorts of Dutch individuals with normal glucose tolerance, impaired glucose tolerance, or type 2 diabetes (Engelen et al., 2009).

In the present study, the mean CIMT and the presence of CAP were significantly increased in patients with diabetes with the GLO1-7CC genotype compared with those with the -7CT and TT genotypes. The GLO1-7CC genotype was also an independent determinant of CIMT in patients with diabetes. Although there was a trend toward higher risk for CAP in the -7CC genotype, this was not significant after adjustments were made for other risk factors. These results suggested that this polymorphism is associated with carotid atherosclerosis in patients with type 2 diabetes. Although several studies have shown that A419C polymorphism is associated with an increased level of AGEs and vascular damage, no significant association with carotid atherosclerosis was found in patients with diabetes. The differences between the previous results and ours may be due to the discrepancies in allelic frequency between Chinese and European populations.

ALR is also an important enzyme in the MG metabolism. ALR activity prevents ischemic injury and mediates ischemic preconditioning in vivo (Shinmura et al., 2002; Kaiserova et al., 2008). They also showed that ALR-null mice had a higher abundance of AGEs in the heart and plasma than did wild-type mice. The differences between wild-type and ALR-null mouse tissues were evident even in the absence of diabetes. Atherosclerotic lesion formation in the apoE-null mouse was also enhanced by the deletion of the ALR gene (Baba et al., 2009).

ALR is not only involved in the MG catabolism, but it also participates in the metabolism of polyols. ALR activity increases in hyperglycemic conditions, which activates the polyol pathway and leads to an accumulation of sorbitol in the cell. Excess sorbitol may cause osmotic disturbances and other biochemical changes typically associated with diabetic microvascular complications (Greene et al., 1987; Wang et al., 2003). Therefore, it is unclear whether ALR activity is beneficial or harmful to cardiovascular tissues.

The reporter gene assay suggests that ALR expression was different among different alleles of ALR C-106T polymorphism (Yang et al., 2003). Hence, the relationship between ALR C-106T polymorphism and CAS can indirectly reflect the effect of the ALR gene on the cardiovascular system. In this study, neither the CIMT nor the presence of CAP was associated with ALR C-106T polymorphism in patients with type 2 diabetes, suggesting that ALR has no obvious effect on the progression of CVD. The results were consistent with those of a prospective study of patients with type 2 diabetes (So et al., 2008).

In conclusion, this study shows that only the GLO1 C-7T polymorphism, and not the GLO1 A419C and ALR C-106T polymorphisms, is associated with carotid atherosclerosis in Chinese patients with type 2 diabetes. Our findings may be helpful in predicting the progression of atherosclerosis and the need for intensive medical therapy for atherosclerosis in patients with type 2 diabetes.

Footnotes

Acknowledgments

This research was supported by grants from National Natural Science Foundation of China (No. 30700381) and Shanghai Municipal Science and Technology Commission (No. 74119638)

Disclosure Statement

No competing financial interests exist.

References

Ahmed

, Dobler

, Larkin

et al. 2008. Reversal of hyperglycemia-induced angiogenesis deficit of human endothelial cells by overexpression of glyoxalase 1 in vitro. Ann N Y Acad Sci, 1126:262-264.

Baba

, Barski

, Ahmed

et al. 2009. Reductive metabolism of AGE precursors: a metabolic route for preventing AGE accumulation in cardiovascular tissue. Diabetes, 58:2486-2497.

Brownlee

. 2001. Biochemistry and molecular cell biology of diabetic complications. Nature, 414:813-820.

Chang

, Paek

, Kim

et al. 2002. Substrate-induced up-regulation of aldose reductase by methylglyoxal, a reactive oxoaldehyde elevated in diabetes. Mol Pharmacol, 61:1184-1191.

Chang

, Wang

, Wu

. 2005. Methylglyoxal-induced nitric oxide and peroxynitrite production in vascular smooth muscle cells. Free Radic Biol Med, 38:286-293.

Degaffe

, Vander Jagt

, Bobelu

et al. 2008. Distribution of glyoxalase I polymorphism among Zuni Indians: the Zuni Kidney Project. J Diabetes Complications, 22:267-272.

Engelen

, Ferreira

, Brouwers

et al. 2009. Polymorphisms in glyoxalase 1 gene are not associated with vascular complications: the Hoorn and CoDAM studies. J Hypertens, 27:1399-1403.

Gale

, Futers

, Summers

. 2004. Common polymorphisms in the glyoxalase-1 gene and their association with pro-thrombotic factors. Diabetes Vasc Dis Res, 1:34-39.

Goldin

, Beckman

, Schmidt

et al. 2006. Advanced glycation end products: sparking the development of diabetic vascular injury. Circulation, 114:597-605.

10.

Greene

, Lattimer

, Sima

. 1987. Sorbitol, phosphoinositides, and sodium-potassium-ATPase in the pathogenesis of diabetic complications. N Engl J Med, 316:599-606.

11.

Hollander

, Bots

, Del Sol

et al. 2002. Carotid plaques increase the risk of stroke and subtypes of cerebral infarction in asymptomatic elderly: the Rotterdam study. Circulation, 105:2872-2877.

12.

Huebschmann

, Regensteiner

, Vlassara

et al. 2006. Diabetes and advanced glycoxidation end products. Diabetes Care, 29:1420-1432.

13.

Humphries

, Morgan

. 2004. Genetic risk factors for stroke and carotid atherosclerosis: insights into pathophysiology from candidate gene approaches. Lancet Neurol, 3:227-235.

14.

Junaid

, Kowal

, Barua

et al. 2004. Proteomic studies identified a single nucleotide polymorphism in glyoxalase I as autism susceptibility factor. Am J Med Genet A, 131:11-17.

15.

Kageyama

, Pastan

. 1989. Molecular cloning and characterization of a human DNA binding factor that represses transcription. Cell, 59:815-825.

16.

Kaiserova

, Tang

, Srivastava

et al. 2008. Role of nitric oxide in regulating aldose reductase activation in the ischemic heart. J Biol Chem, 283:9101-9112.

17.

Kalousová

, Germanová

, Jáchymová

et al. 2008. A419C (E111A) polymorphism of the glyoxalase I gene and vascular complications in chronic hemodialysis patient. Ann N Y Acad Sci, 1126:268-271.

18.

Kannel

, McGee

. 1979. Diabetes and glucose tolerance as risk factors for cardiovascular disease: the Framingham study. Diabetes Care, 2:120-126.

19.

Kilhovd

, Berg

, Birkeland

et al. 1999. Serum levels of advanced glycation end products are increased in patients with type 2 diabetes and coronary heart disease. Diabetes Care, 22:1543-1548.

20.

Kirk

, Ranford

, Serjeantson

et al. 1985. HLA, complement C2, C4, properdin factor B and glyoxalase types in South Indian diabetics. Diabetes Res Clin Pract, 1:41-47.

21.

Kumagai

, Nangaku

, Kojima

et al. 2009. Glyoxalase I overexpression ameliorates renal ischemia-reperfusion injury in rats. Am J Physiol Renal Physiol, 296:F912-F921.

22.

Lusis

, Fogelman

, Fonarow

. 2004. Genetic basis of atherosclerosis: part II: clinical implications. Circulation, 110:2066-2071.

23.

Mansia

, De Backer

, Dominiczak

et al. 2007. 2007 Guidelines for the management of arterial hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC) J Hypertens, 25:1105-1187.

24.

Mimura

, Kida

, Matsuura

et al. 1990. Immunogenetics of early-onset insulin-dependent diabetes mellitus among the Japanese: HLA, Gm, BF, GLO, and organ-specific autoantibodies—the J.D.S. study. Diabetes Res Clin Pract, 8:253-262.

25.

Miyata

, van Ypersele de Strihou

, Imasawa

et al. 2001. Glyoxalase I deficiency is associated with an unusual level of advanced glycation end products in a hemodialysis patient. Kidney Int, 60:2351-2359.

26.

Nabel EG (2003) Cardiovascular disease. N Engl J Med, 349:60-72.

27.

O'Leary

, Polak

, Kronmal

et al. 1999. Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. Cardiovascular Health Study Collaborative Research Group. N Engl J Med, 340:14-22.

28.

Price

, Knight

. 2009. Methylglyoxal: possible link between hyperglycaemia and immune suppression? Trends Endocrinol Metab, 20:312-317.

29.

Salonen

, Salonen

. 1991. Ultrasonographically assessed carotid morphology and the risk of coronary heart disease. Arterioscler Thromb, 11:1245-1249.

30.

Shi

, He

. 2003. SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res, 15:97-98.

31.

Shinmura

, Bolli

, Liu

et al. 2002. Aldose reductase is an obligatory mediator of the late phase of ischemic preconditioning. Circ Res, 91:240-246.

32.

Shinohara

, Thornalley

, Giardino

et al. 1998. Overexpression of glyoxalase-I in bovine endothelial cells inhibits intracellular advanced glycation endproduct formation and prevents hyperglycemia-induced increases in macromolecular endocytosis. J Clin Invest, 101:1142-1147.

33.

, Wang

, Ng

et al. 2008. Aldose reductase genotypes and cardiorenal complications: an 8-year prospective analysis of 1,074 type 2 diabetic patients. Diabetes Care, 31:2148-2153.

34.

Wang

, Ng

, Lee

et al. 2003. Phenotypic heterogeneity and associations of two aldose reductase gene polymorphisms with nephropathy and retinopathy in type 2 diabetes. Diabetes Care, 26:2410-2415.

35.

Wolff

, Braun

, Schlüter

et al. 2005. Endothelial nitric oxide synthase Glu(298) → Asp polymorphism, carotid atherosclerosis and intima-media thickness in a general population sample. Clin Sci (Lond), 109:475-481.

36.

Yamasaki

, Katakami

, Sakamoto

et al. 2006. Combination of multiple genetic risk factors is synergistically associated with carotid atherosclerosis in Japanese subjects with type 2 diabetes. Diabetes Care, 29:2445-2451.

37.

Yang

, Millward

, Demaine

. 2003. Functional differences between the susceptibility Z-2/C-106 and protective Z+2/T-106 promoter region polymorphisms of the aldose reductase gene may account for the association with diabetic microvascular complications. Biochim Biophys Acta, 1639:1-7.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB