Combination of Multiple Genetic Risk Factors Is Synergistically Associated With Carotid Atherosclerosis in Japanese Subjects With Type 2 Diabetes

The study enrolled type 2 diabetic subjects (n = 690, ≥50 years old) who visited the outpatient clinics of two participating hospitals (Osaka University Hospital and Juntendo University Hospital). The determination of type 2 diabetes was based on World Health Organization criteria. The patients’ characteristics are listed in Table 1. Smoking habit was evaluated as follows: value of 0 and 1 were assigned to subjects when the number of cigarettes per day × smoking years was <200 and ≥200, respectively.

The study protocol was approved by the committees on the ethics of human research of Osaka University Graduate School of Medicine and Juntendo University School of Medicine.

A series of ultrasonographic scannings of the carotid artery were performed using an echotomographic system (EUB-450; Hitachi Medico, Tokyo, Japan) with an electrical linear transducer (midfrequency of 7.5 MHz). All the images were photographed. The resolution limit of this system using 7.5 MHz was ∼0.1 mm. The conventional B-mode imaging of the extracranial common carotid artery, the carotid bulb, and the internal carotid artery in the neck was performed bilaterally from three different longitudinal projections (i.e., anterior-oblique, lateral, and posterior-oblique) as well as the transverse projection, as reported previously (11,12). The carotid IMT was measured as the distance from the leading edge of the first echogenic line to the leading edge of the second echogenic line (13). Three determinations of IMT were conducted at the site of the greatest thickness and at two points, 1 cm upstream and 1 cm downstream from the site of the greatest thickness. These three values were averaged. The greatest value among the six averaged IMT (three from the left and three from the right) was used as the representative value (average IMT) for each individual. Physicians conducted all scans and different physicians performed the determinations of IMT using the photographs. The physicians were unaware of the clinical characteristics of the subjects. The reproducibility of the IMT measurements was examined by conducting another scan 1 week later on eight subjects. The mean difference in IMT between these two determinations was 0.01 mm and the SD was 0.04 mm, demonstrating good reproducibility of repeated measurements.

Fasting blood was withdrawn for analyses of serum total cholesterol, serum HDL cholesterol, serum triglyceride, plasma glucose, and HbA_1c (A1C) levels by standard laboratory techniques. Blood pressure and BMIs were also measured. Examination for the occurrence of old myocardial infarction (major Q-QS changes) was performed based on the results of the resting 12-lead electrocardiogram and double Master two-step tests and the existence of previous symptoms of myocardial infarction (14).

With the use of PubMed, we selected 106 candidate gene SNPs that are potentially associated with atherosclerosis, diabetes, hypertension, dyslipidemia, or diabetic microangiopathy (Table 2). Of these 106 polymorphisms, we selected 40 common SNPs in which the frequency of the minor allele was ≥10% of sample population.

Venous blood was collected from each subject and genomic DNA was isolated with a DNA isolation kit (Qiagen). The genotypes of the SNPs in each subject were determined with a fluorescence- or colorimetry-based allele-specific DNA-primer probe assay system (Toyobo Gene Analysis) as described in detail by Yamada et al. (5).

The data are expressed as means ± SD, and all statistical tests were two-sided. The Student’s t test was applied to compare the average IMT of subjects with and without the SNP genotype or the SNP combination.

Genotypes of 40 common SNPs were classified into two categories by four ways, including the major allele’s dominant model, minor allele’s dominant model, major allele’s recessive model, and minor allele’s recessive model. Then, 16 SNP combination models consisting of one combination from each category for the two SNPs and the set of the other combinations were also built. In each model, the continuous data of two of the categories were compared by Student’s t test. The categorical data of the two categories were compared by Pearson’s χ² test. The data of age, systolic and diastolic blood pressure, and SNP combination as independent variables were also analyzed by multivariate regression analysis with the data of average IMT as a dependent variable. The association between SNP combination and the history of coronary heart disease was evaluated by the multiple logistic model.

Because the analyses were performed on the four models of 40 SNPs and 16 models of 780 SNP combinations, correction for multiple testing must be required. Bonferroni’s multiple comparison procedure was utilized for the correction and gave the corrected level of significance, 0.00031 [= 0.05/(40 × 4)] in the single SNP analyses and 4.01 × 10⁻⁶ [= 0.05/(₄₀C₂ × 16)] in the SNP combination analyses.

These statistical analyses were performed using the SAS statistical package (SAS/STAT 9.1; SAS Institute, Cary, NC).

The significance level for multiple comparisons was evaluated also by simulation. In a simulation, the virtual average IMT values following the normal distribution with the mean of 1.05 and the SD of 0.35 from the whole enrolled members’ population were randomly assigned to all members. Next, the population of the enrolled members was randomly divided between the group with the genotypes’ combination (18) and the group without it (646 or 644) by ₄₀C₂×16 patterns. The simulations in which the P value by Student’s t test under the threshold (3.5 × 10⁻⁶ or 2.7 × 10⁻⁹) was observed at least once were regarded as false positive. The ratio of the false positive to the whole simulations was regarded as the P value for the whole analyses.

In the single SNP analyses, no SNPs were found to be significantly associated with average IMT (mean [±SD] 1.06 ± 0.35 mm) by Bonferroni’s multiple comparison procedure in any model, whereas the P values of the Student’s t test were less than the uncorrected level of significance (0.05) in seven SNPs, including the ACE DD genotype (1.13 ± 0.43 vs. 1.04 ± 0.34 mm, P = 0.03284), CD18 1323 CC and CT genotypes (1.07 ± 0.36 vs. 0.93 ± 0.24 mm, P = 0.01768), factor XII 46CC genotype (1.13 ± 0.40 vs. 1.05 ± 0.34 mm, P = 0.04173), glycoprotein Ia 807 TT and CT genotypes (1.08 ± 0.39 vs. 1.01 ± 0.29 mm, P = 0.01179), LTA 252 GG genotype (1.15 ± 0.42 vs. 1.04 ± 0.33 mm, P = 0.00109), methylene-tetrahydrofolate reductase (MTHFR) 677 TT genotype (1.15 ± 0.45 vs. 1.04 ± 0.33 mm, P = 0.00220), and vascular endothelial growth factor −634 GG genotype (1.10 ± 0.40 vs. 1.03 ± 0.33 mm, P = 0.01829).

Next, to investigate the association between average IMT and the combinations of potential susceptible genes, we compared the average IMT data of two categories classified by the combinations of SNP genotypes with Student’s t test. In 780 combinations of SNPs, only two genotype combinations including LTA 252 GG–MTFHR 677 TT (P = 2.7 × 10⁻⁹) and ACE DD–LTA 252 GG (P = 3.5 × 10⁻⁶) were found to be associated with a significant (P = 2.7 × 10⁻⁹ and 3.5 × 10⁻⁶, respectively) increase in average IMT (1.54 ± 0.60 and 1.43 ± 0.58 mm, respectively) compared with those of the subjects without these combinations (1.04 ± 0.34 and 1.04 ± 0.34 mm, respectively).

The characteristics of the patients with and without these two genotype combinations are shown in Table 3. The diabetic subjects with the combination of ACE DD and LTA 252 GG showed significantly higher systolic and diastolic blood pressure than those without this combination. However, multivariate regression analysis demonstrated that the combination of ACE DD and LTA 252 GG is still the independent determinant of average IMT (partial regression coefficient = 0.344 mm, F = 18.53, P = 0.00002) after adjustment of systolic and diastolic blood pressure. A multiple logistic model demonstrated that this genotype combination is significantly responsible for a high frequency of history of coronary heart disease (odds ratio 3.11 [95% CI 1.16–8.38], P = 0.0247).

The diabetic patients with the combination of LTA 252 GG and MTHFR 677 TT showed a significantly higher age and diastolic blood pressure than those without this combination (Table 3). However, multivariate regression analysis demonstrated that the combination of LTA 252 GG and MTHFR 677 TT is still the independent determinant of average IMT after adjustment of age and diastolic blood pressure (partial regression coefficient = 0.438 mm, F = 29.91, P = 6.43 × 10⁻⁸). A multiple logistic model demonstrated that this genotype combination was not significantly responsible for a high frequency of history of coronary heart disease.

Additionally, the P value for the each combination of genotypes was empirically evaluated by the simulation for multiple comparisons. The simulation indicated that P value of 3.5 × 10⁻⁶ for ACE DD and LTA 252 GG combination corresponded to the P value of 2.8 × 10⁻² for the whole analysis, and P value of 2.7 × 10⁻⁹ for MTHFR 677 TT and LTA 252 GG combination was stricter than P value of 1.0 × 10⁻⁵ for the whole analysis.

In this study, we selected 106 candidate gene polymorphisms that may contribute to coronary heart disease, diabetes, and diabetes vascular complications. After genotyping of these candidate gene polymorphisms in all subjects, we found that 40 SNPs were relatively common (the frequency of the minor allele was ≥10%) in Japanese subjects with type 2 diabetes. Because multiple comparisons must be performed on these 40 SNPs in order to evaluate their association with carotid atherosclerosis, Bonferroni’s multiple comparison procedure was applied for statistical tests to control the family-wise type 1 error to <0.05.

In the single SNP analyses, we found that no single SNP genotypes were statistically significantly associated with carotid IMT after Bonferroni’s multiple comparison procedure. Although this procedure may be too strict to find out candidate SNP genotypes related to disease susceptibility, these results suggest the fact that any single candidate genotype is not critical in determining carotid IMT and that it is difficult to predict the risk of carotid atherosclerosis by simply diagnosing single SNP genotypes independently.

In the SNP combination analyses, two SNP combinations (MTHFR 677 TT genotype plus LTA 252 GG genotype and ACE DD genotype plus LTA 252 GG genotype) were found to be statistically (P < 4.01 × 10⁻⁶) significantly associated with carotid atherosclerosis in Japanese type 2 diabetic subjects after Bonferroni’s multiple comparison procedure.

LTA, formerly named tumor necrosis factor (TNF)-β, is structurally similar to TNF-α and plays a crucial role in the inflammatory response by inducing monocyte migration and lymphocyte activation (4). Furthermore, reduction of atherosclerotic lesions was observed in LTA knockout mice but not in TNF-α knockout mice, suggesting that LTA is more important in the progression of atherosclerosis (15). It is known that the A252G polymorphism in the LTA gene is to an amino acid–coding polymorphism, leading to an increase of C-reactive protein, vascular cell adhesion molecule (VCAM)-1, and selectin E (4), all of which are closely associated with the inflammatory process and the progression of atherosclerosis. However, the association between the LTA polymorphism and the progression of atherosclerosis has yet to be reported. Hyperhomocysteinemia is well known to be an independent risk factor for atherosclerosis, and MTHFR is an enzyme that is involved in the remethylation of homocysteine to methionine (16,17). The MTHFR 677 TT genotype results in a reduction of MTHFR activity and an increase in serum homocysteine level, and thus is possibly involved in the progression of atherosclerosis (18,19). In this study, we could not find that the LTA 252 GG genotype or the MTHFR 677 TT genotype was significantly associated with average IMT. These results indicate that a polymorphism of each genotype alone is not enough to lead to a substantial progression of atherosclerosis and that it is very important to examine both polymorphisms when we estimate whether each subject is predisposed to atherosclerosis.

It is known that the insertion/deletion (I/D) polymorphism of the ACE gene is associated with the level of circulating ACE and that the highest plasma ACE levels are found in subjects with the DD genotype (20). Although the ACE I/D polymorphism possibly influences blood pressure regulation (21) and is involved in the progression of atherosclerosis, it still remains controversial as to whether this SNP actually contributes to the progression of atherosclerosis (20–25). In this study, this SNP was found not to be responsible for an increase in average IMT, and this SNP also did not affect systolic and diastolic blood pressures (data not shown). However, the combination of the ACE DD genotype and the LTA 252 GG genotype contributed to a statistically significant increase in average IMT, and the subjects with this combination showed significantly higher systolic and diastolic blood pressure. Under age-, systolic blood pressure–, and diastolic blood pressure–matched conditions, this combination was still associated with an increase in average IMT. In addition, this combination was significantly related with a high frequency of history of old myocardial infarction in these subjects. Although it remains unknown as to how such a combination of these gene polymorphisms exerts synergistic effects on carotid atherosclerosis and blood pressure, these results indicate that these two genotypes synergistically contribute to the progression of carotid atherosclerosis and predisposition of coronary heart disease partially by elevated blood pressure and that it is very important to examine these polymorphisms when we estimate the predisposition of each subject to atherosclerosis and coronary heart disease.

This cross-sectional study has shown that two synergistic combinations of SNPs predispose subjects with type 2 diabetes to carotid atherosclerosis and that one of these combinations is associated with coronary heart disease. A long-term follow-up study will be required to further establish these combinations of SNPs as responsible for an increased risk of carotid and coronary atherosclerosis.

We are deeply indebted to Dr. Tadamitsu Kishimoto and Dr. Kouichi Yamanishi for their valuable suggestions. This work was partly supported by the Bio-Medical Cluster Project in Saito (northern part of Osaka prefecture), which is promoted by the Ministry of Education, Culture, Sports, Science and Technology, Japan.