Effects of the Renin-Angiotensin System Genes and Salt Sensitivity Genes on Blood Pressure and Atherosclerosis in the Total Population and Patients With Type 2 Diabetes

This study was conducted within the framework of the Rotterdam Study, an ongoing prospective population-based cohort study among subjects aged ≥55 years living in Ommoord, a suburb of Rotterdam, the Netherlands. The design of the study has been described elsewhere (12). Baseline data were collected between 1990 and 1993. The medical ethics committee of Erasmus University has approved the study, and written informed consent was obtained from all participants.

At the baseline examination, information concerning medical history, medication use, and smoking status was obtained. Height and weight were assessed, and BMI (in kg/m²) was calculated. At the research center, blood pressure was measured. Hypertension was defined as a systolic blood pressure level ≥160 mmHg and/or a diastolic blood pressure ≥100 mmHg and/or the use of antihypertensive medication. We included the following as antihypertensive medications: β-blockers, diuretics, and other antihypertensive medications (such as calcium antagonists and ACE inhibitors). Diabetes was defined as the use of glucose-lowering medication and/or random or postload serum glucose level ≥11.1 mmol/l (13). Total serum cholesterol and HDL cholesterol were determined. Pulse pressure was calculated as the following: systolic blood pressure minus diastolic blood pressure. Mean arterial pressure was calculated as the following: diastolic blood pressure plus one-third (systolic blood pressure minus diastolic blood pressure).

Carotid atherosclerosis was assessed by duplex scan ultrasonography of the carotid arteries, using a 7.5-MHz linear array transducer (Ultramark IV). Measurements of intima-media thickness (IMT) were performed offline from the still images recorded on videotape. Details about these measurements have been published previously (14). Results from a reproducibility study of IMT measurements have been published elsewhere (15).

Genomic DNA was isolated from blood samples using standard methods (16). The II, ID, and DD genotypes of the ACE gene were detected using the PCR technique according to the method of Lindpaintner et al. (17), with some modifications. We utilized TaqMan allelic discrimination Assays-By-Design (Applied Biosystems, Foster City, CA) for genotyping the AGT gene M235T, the AT1R gene C573T, the ADD1 gene G460T, the GNβ3 gene rs2301339 G/A, and the CYP3A5 gene A6986G polymorphisms.

Forward and reverse primer sequences were 5′-AGGTTTGCCTTACCTTGGAAGTG-3′ and 5′-GCTGTGACAGGATGGAAGACT-3′ for AGT. The minor groove-binding probes were 5′-CTGGCTCCCATCAGG-3′ (VIC) and 5′-CTGGCTCCCGTCAGG-3′ (FAM). We used the reverse-strand design for the AT1R gene polymorphism. Forward and reverse primer sequences were 5′-TGTGCTTTCCATTATGAGTCCCAAA-3′ and 5′-CAGAAAAGGAAACAGGAAACCCAGTATA-3′. The minor groove-binding probes were 5′-CTATCGGGAGGGTTG-3′ (VIC) and 5′-CTATCGGAAGGGTTG-3′ (FAM).

For ADD1, the forward and reverse primer sequences were 5′-GAGAAGACAAGATGGCTGAACTCT-3′ and 5′-GTCTTCGACTTGGGACTGCTT-3′. The minor groove-binding probes were 5′-CATTCTGCCCTTCCTC-3′ (VIC) and 5′-ATTCTGCCATTCCTC-3′ (FAM). For GNB3, the forward and reverse primer sequences were 5′-GGCAGGGCTGCTTCTCA-3′ and 5′-GCAAGCCGCTGCTCTCA-3′. The minor groove-binding probes were 5′-AAACCAAGGAAGGGACA-3′ (VIC) and 5′-ACCAAGGGAGGGACA-3′ (FAM). For CYP3A5, the forward and reverse primer sequences were 5′-CGAATGCTCTACTGTCATTTCTAACCA-3′ and 5′-TGAAGGGTAATGTGGTCCAAACAG-3′. The minor groove-binding probes were 5′-TTTTGTCTTTCAATATCTC-3′ (VIC) and 5′-TTTTGTCTTTCAGTATCTC-3′ (FAM).

The assays utilized 5 ng genomic DNA and 2-μl reaction volumes. The amplification and extension protocol was as follows: an initial activation step of 10 min at 95° preceded 40 cycles of denaturation at 95° for 15 s and annealing and extension at 50° for 60 s. Allele-specific fluorescence was then analyzed on an ABI PRISM 7900HT Sequence Detection System v2.1 (Applied Biosystems).

Hardy-Weinberg equilibrium was tested with the χ² test. Based on the biological pathway, the polymorphisms were defined in two groups: RAS genes and salt sensitivity genes. The genotypes considered at risk for increased blood pressure or atherosclerosis for the RAS genes or the salt sensitivity genes, respectively, were coded “1” in the analysis, whereas the genotypes not at risk were coded “0.”

Based on previous studies, we chose as risk alleles the D-allele for ACE I/D (18), the T-allele for AGT M235T (19), and the T-allele for AT1R (20) C573T polymorphism in the RAS pathway. For the salt sensitivity pathway, we chose as risk alleles the T-allele for G460T ADD1 (21), the G-allele for the GNβ3 rs2301339 G/A, and the A-allele for the CYP3A5 A6986G polymorphism (22). The risk allele for the GNβ3 rs2301339 G/A polymorphism was based on the results of a single gene in our study sample, which showed a higher systolic blood pressure in diabetic subjects with the GG genotype than in subjects with the AA genotype (147.1 vs. 142.1 mmHg).

The dominant genetic model was chosen in the RAS pathway based on previous studies for the ACE I/D (18) and the AGT M235T (19) polymorphisms and, in the salt-sensitive hypertension genes, on previous findings for the ADD1 (G460T) (21) and the CYP3A5 A6986G (22) polymorphisms. The rs2301339 G/A polymorphism of GNB3 is in linkage disequilibrium with the C825T polymorphism, which has been reported as being dominant (10). The C573T polymorphism of the AT1R is in linkage disequilibrium with a well-known polymorphism (A1166C), which was reported as dominant (23).

This approach resulted, for the RAS genes, in the following groups: ACE genotype: ID/DD = 1, II = 0; AGT genotype: MT/TT = 1, MM = 0; and AT1R genotype: CT/TT = 1, CC = 0. For the salt-sensitive combined group, genotypes were coded as follows: ADD1: GT/TT = 1, GG = 0; GNβ3: AG/GG = 1, AA = 0; and CYP3A5: GA/AA = 1, GG = 0. Then, to assess the combined effects of the three genotypes of the RAS genes, a variable was created that included the three polymorphisms, which resulted in a score ranging from 0 to 3. The latter number represents the total number of risk genotypes. A comparable procedure was used to assess the combined effects of risk genotypes of the three salt sensitivity genes. A variable was created using three genotypes of the salt sensitivity genes, which resulted in a score ranging from 0 to 3. The latter number represents the total number of risk genotypes. Furthermore, the same procedure was used to assess the combined effects of risk genotypes of both the three RAS genes and the three salt sensitivity genes. A variable was created using six genotypes of both the RAS and the salt sensitivity genes, which resulted in a score ranging from 0 to 6. The latter number represents the total number of risk genotypes.

When adding the genes together in a multiple gene scale, there are very few individuals who carry nonrisk genotypes. The population carries two or three risk genotypes for RAS genes and one or two risk genotypes for the salt sensitivity genes and three or four risk genotypes for the both RAS and salt sensitivity genes. Therefore, we have considered the reference group according to the most frequent risk genotype: for RAS genes, the group with two risk genotypes; for the salt sensitivity genes, the group with one risk genotype; and for both the RAS and the salt sensitivity genes, the group with four risk genotypes. For the both RAS and salt sensitivity genes, the number of individuals with zero risk genotype was very low; therefore, in our analysis we combined zero and one risk genotype together.

To investigate the associations between systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, and common carotid IMT with each combined genotype group, an ANCOVA was performed. All analyses were adjusted for age, sex, and blood pressure–lowering medication and additionally for BMI, total cholesterol, and smoking. The analysis on common carotid IMT also was adjusted for systolic and diastolic blood pressure. Interaction between the RAS genes and the salt sensitivity genes was modeled with an interaction term obtained from the product of main effects in relation to blood pressure values, hypertension, and common carotid IMT. Post hoc pairwise tests used a Bonferroni correction for multiple comparisons. Odds ratios with 95% CIs were calculated by logistic regression analyses, adjusted for sex and age. All analyses were performed using the SPSS for Windows software package, version 11.0 (SPSS, Chicago, IL).

Table 1 presents the baseline characteristics of the study population. In the total population of 7,983 participants (38.9% men), 36.1% were hypertensive patients, of whom 33.1% were on blood pressure–lowering drugs and 9.6% had diabetes. In diabetic patients (39.0% men), 54.3% were hypertensive, of whom 50.2% were on blood pressure–lowering drugs.

Genotype frequencies were in Hardy-Weinberg equilibrium. In the total population, with an increasing number of risk genotypes for the RAS genes, there was a significant increase in systolic blood pressure (P for trend = 0.01) and mean arterial pressure (P for trend = 0.02) (Table 2). With an increasing number of risk genotypes (0→3), systolic blood pressure increased by 2.5 mmHg and pulse pressure by 1 mmHg (Table 2). There was significantly lower systolic blood pressure (P = 0.02), mean arterial pressure (P = 0.04), and pulse pressure (P = 0.03) in carriers of one risk genotype compared with carries of two risk genotypes (Table 2). In diabetic patients, a significant increase was found with an increasing number of the RAS risk genotypes in systolic blood pressure (P for trend = 0.04) and pulse pressure (P for trend = 0.03). Diabetic patients with three risk genotypes had a 6.9 mmHg higher systolic blood pressure and a 6.0 mmHg higher pulse pressure than those who did not have any risk genotypes (Table 2). In diabetic patients, carriers of one risk genotype had a significantly lower systolic blood pressure (P = 0.03) and pulse pressure (P = 0.03) than those with two risk genotypes for the RAS genes (Table 2).

To examine whether antihypertensive medication is modifying the effect on blood pressure values across RAS, as well as salt sensitivity genes, we adjusted all the analyses for antihypertensive medication. No significant differences were observed in the frequency of antihypertensive medication among the group of RAS genes (P = 0.52), among the group of salt sensitivity genes (P = 0.75), and among the group in which RAS and salt sensitivity genes were combined (P = 0.20). Although many diabetic patients were treated with antihypertensive medication (50.2%), the frequencies of the RAS, salt sensitivity, and both the RAS and salt sensitivity genotypes were not statistically different among those with and without a treatment (P = 0.24, P = 0.84, and P = 0.89, respectively). After stratification by using different antihypertensive medications, the results remained unchanged (data not shown). In the total population, these frequencies were only different in combined RAS and salt sensitivity in those who were treated with β-blockers (P = 0.04) and, in salt sensitivity, in those who treated with diuretics (P = 0.05).

For the salt sensitivity genes, no associations were observed between an increasing number of risk genotypes and blood pressure values in the total population (Table 3). In diabetic patients, however, those who had three risk genotypes had a 9.0 mmHg higher systolic blood pressure than those who did not have any risk genotypes. This difference became statistically significant after further adjustment for putative risk factors (P = 0.05). Furthermore, diabetic patients who had three risk genotypes had a 13.1 mmHg significantly higher pulse pressure (P = 0.02, Table 2). Diabetic patients who carried three risk genotypes for the salt sensitivity genes had a significantly higher pulse pressure than those with one risk genotype (P = 0.01, Table 2).

For both RAS and salt sensitivity genes, no associations were observed between an increasing number of risk genotypes and blood pressure values in the total population and in the diabetic patients (Table 4). In diabetic patients, those who carried two risk genotypes had a 7 mmHg lower systolic blood pressure than those who carried four risk genotypes (P = 0.04, Table 4). Diabetic patients who had two risk genotypes had a 6.8 mmHg lower pulse pressure (P = 0.04), and those who had five risk genotypes had a 5.7 mmHg higher pulse pressure than those who had four risk genotypes (P = 0.01, Table 4).

In the total population, no significant associations were found between the risk of hypertension and the number of risk genotypes (Fig. 1). In diabetic patients, a threshold effect was observed in that the risk of hypertension in those without any risk genotypes was 0.2 (95% CI 0.1–0.7), with one risk genotype the risk was 1.0 (0.6–1.6), and with three the risk was 0.9 (0.6–1.3) lower than those with two risk genotypes of the RAS genes (P for trend = 0.46; Fig. 1A). Diabetic patients who carried every risk genotype had a 4.9 (1.4–17.6; P = 0.02) times higher risk of hypertension than those who did not carry any risk genotypes of the RAS genes (data not shown).

For the salt sensitivity genes, the risk of hypertension in diabetic patients (in those without any risk genotype) was 0.5 times (95% CI 0.2–1.3) lower and in those who had two risk genotypes was 1.1 times (0.7–1.5) higher than in those with one risk genotype (Fig. 1B). Diabetic patients who carried every risk genotype had a 1.9 (0.8–4.3; P = 0.14) times higher risk of hypertension than those who did not carry any risk genotypes of the salt sensitivity genes (data not shown). No such result was observed in the total population.

For both the RAS and the salt sensitivity genes in diabetic patients, the risk of hypertension in those with zero and one risk genotype was 0.3 (95% CI 0.1–1.4) and with two risk genotypes was 0.8 (0.4–0.4) lower than those with four risk genotypes. Furthermore, the risk of hypertension in those with three risk genotypes was 1.2 (0.8–1.7) higher and with five risk genotypes was 1.2 (0.7–2.1) higher than those with four risk genotypes (Fig. 1C).

In the total population, no significant associations were observed between mean common carotid IMT and the number of risk genotypes (Fig. 2). In contrast, in diabetic patients, there was a significant trend by increasing the number of risk genotypes for the RAS genes (P for trend = 0.01; Figs. 2A). Diabetic patients with three risk genotypes had a higher mean common carotid IMT compared with those with two risk genotypes for the RAS genes (mean difference = 0.04 mm, P = 0.02; Fig. 2A). Diabetic patients who carried every risk genotype had a higher mean common carotid IMT than those who did not carry any risk genotype for the RAS genes (mean difference = 0.05 mm, P = 0.24) (data not shown).

Figure 2B shows that diabetic patients who carried two risk genotypes for the salt sensitivity genes had a higher mean common carotid IMT compared with one risk genotype (mean difference = 0.03 mm, P = 0.04). These results remained after further adjustments. Diabetic patients who carried every risk genotype had a higher mean common carotid IMT than those who did not carry any risk genotype for the salt sensitivity genes (mean difference = 0.07 mm, P = 0.05) (data not shown). No significant association was found by including the interaction term of the RAS genes and salt sensitivity genes in relation to blood pressure values, hypertension, and common carotid IMT in both the total population and type 2 diabetic patients (data not shown). Figure 2C shows that diabetic patients who carried three risk genotypes for the both RAS and salt sensitivity genes had a lower mean common carotid IMT compared with four risk genotypes (mean difference 0.06 mm, P = 0.02).

In this population-based cohort study, we found that when studying three RAS and three salt sensitivity genes, most of the individuals in the population carried at least one or two risk genotypes and very few carried none at all. We found that among type 2 diabetic subjects, mean systolic blood pressure, pulse pressure, and risk of hypertension increased with the number of risk genotypes for the RAS genes and the salt sensitivity genes. Furthermore, we observed that mean common carotid IMT was increased in diabetic patients who had an increasing number of risk genotypes of the RAS genes.

To our knowledge, the present study is the first to study the combined effects of the RAS genes, as well as the salt sensitivity genes, in relation to blood pressure, pulse pressure, and common carotid IMT. Previous studies (24–27) on the effects of single genetic markers of the RAS or salt sensitivity on blood pressure have reported conflicting results. However, a single susceptibility gene is expected to exert only a small effect on the development of vascular complications. Studying multiple genes from a single pathway simultaneously will allow the discovery of more pronounced effects, particularly in high-risk subgroups such as patients with type 2 diabetes.

Several lines of evidence support the possibility that the RAS contributes to the etiology of vascular complications of diabetes (21). The ACE (I/D) polymorphism is one of the RAS gene polymorphisms that is associated with alterations in circulating ACE levels, that in the DD genotype being 50% higher than that in the II genotype (28). The association between ACE I/D-alleles and cardiovascular disease in diabetic patients has been examined in several studies (6,29). In the AGT gene, the T-allele of M235T polymorphism is associated with increased plasma AGT levels, hypertension, and carotid atherosclerosis (7). Furthermore, the AT1R C573T polymorphism has a protective effect against blood pressure–induced microalbuminuria in type 2 diabetes (8). These findings prompted us to investigate the role of RAS genes as a single pathway involved in complications of diabetes.

Moreover, salt sensitivity genes probably play a role in the development of cardiovascular complications, insulin resistance, and hypertension (30,31). It has been found that the ADD1 polymorphism leads to higher activity of the sodium-potassium pump and, hence, increases renal tubular sodium reabsorption, which increases the risk of salt-sensitive hypertension and cardiovascular disease (9,32). The GNβ3 gene enhances G protein activation and increases the activity of the sodium-proton exchanger (33,34). Furthermore, insulin action and effect on glucose transport partly depends on a G protein–sensitive mechanism (35). The CYP3A5 gene can mediate the metabolism of sodium transport in renal epithelia (36). Polymorphic renal expression of the CYP3A5*1 (37) may contribute to metabolized cortisol, which reduces insulin sensitivity and salt-sensitive hypertension (38). Therefore, it is reasonable to expect that in the salt sensitivity pathway multiple genes may be involved in complications of diabetes and act as a single pathway.

A large number of methodological problems still need to be overcome in studies on multiple genes. Even in a large study such as ours, problems arise with the number of individuals in the subcategories; for instance, in our study only 15 diabetic patients had no risk genotype for the RAS genes. To overcome this problem, we chose the reference group based on the largest number of individuals with either the RAS genes or the salt sensitivity genes or these two genes combined.

Complete evaluation of genetic interactions, for instance between three polymorphisms of the RAS genes presented in this study, would require comparisons of the 27 possible combinations of genotypes. Even large studies, such as the Rotterdam Study, do not allow the study of so many comparisons. To overcome this latter problem, the variation in the three polymorphisms was reduced to one variable. A key issue for this analysis is to identify which variants are the potential risk alleles. We have chosen the risk alleles based on previous studies for four polymorphisms (18–22), and for two polymorphisms we defined the risk allele based on the frequency observed in our study. The strategy of choosing the “risk” alleles and verification of risk profile using the same data are potentially dangerous and may lead to false-positive results. We tried to follow this approach for only two genes. Nevertheless, our results on risk profile should be considered with caution and need to be verified in other study populations.

The basis of our genetic model was a joint effect of different genetic sites, as recently described in studies on, for example, insulin resistance (39) and the interaction between genetic variants at different loci (40–42). Statistically, there are multiple ways to define the joint effects of genes. The risk profile was composed of the sum of the risk genotypes, which basically suggests an additive model underlying the joint effect of genes. It has been suggested that additive models may be of biological relevance (41). Another issue ignored in this type of analysis is that different alleles may have different effects; for example, the observed associations may differ across different alleles.

High systolic blood pressure is associated with vascular complications in patients with diabetes. Each 10-mmHg reduction in systolic blood pressure is associated with a 13% reduction in the risk of vascular complications (43). Furthermore, diabetic patients require two to three antihypertensive agents to achieve their targets (44,45). Our findings that the systolic blood pressure and risk of hypertension and atherosclerosis were increased with an increasing number of risk genotypes of the RAS risk and the salt sensitivity risk genotypes may have important clinical implications for therapeutic approaches or in the assessment of vascular complications of patients with type 2 diabetes, who are likely to receive several medications for diabetes. Although many diabetic patients were treated with antihypertensive medication (50.2%), the frequencies of the RAS genes and salt sensitivity genes were not statistically different among those who had a treatment.

Our findings are in line with the decreased incidence of complications that has been reported in several large clinical studies, when subjects with type 2 diabetes were treated with either ACE inhibitors (46) or angiotensin II receptor antagonists (47). Given the pronounced role of the RAS blockade in diabetes, hypertension (48–50), and the salt-sensitive type of hypertension (3–5,22), our findings are not unexpected from a medical perspective.

The results of the present study show the value of combining information of multiple genes in a single analysis of complex traits. Many of the negative results for single-locus studies of blood pressure or atherosclerosis in type 2 diabetes may have been due to the effect of multiple genes in a complex pathway. More powerful statistical methods are needed to explore the combined effects of more genetic variants on these traits. We suggest a combined effect of the RAS genes and a combined effect of the salt sensitivity genes on blood pressure and atherosclerosis in type 2 diabetes. Furthermore, our data show the importance of analyzing multiple genes in a biological pathway. An independent confirmation in another cohort can substantiate our conclusion.