# Gender Specific Association of RAS Gene Polymorphism with Essential Hypertension: A Case-Control Study

Authors: Kh. Dhanachandra Singh; Ajay Jajodia; Harpreet Kaur; Ritushree Kukreti; Muthusamy Karthikeyan
Journal: BioMed Research International
 (2014)

---

## Abstract

Renin-angiotensin system (RAS) polymorphisms have been studied as candidate risk factors for hypertension with inconsistent results, possibly due to heterogeneity among various genetic and environmental factors. A case-control association study was conducted to investigate a possible involvement of polymorphisms of three RAS genes:AGT M235T (rs699), ACE I/D (rs4340) and G2350A (rs4343), and AGTR1 A1166C (rs5186) in essential hypertensive patients. A total of 211 cases and 211 controls were recruited for this study. Genotyping was performed using PCR-RFLP method. The genotype and allele distribution of the M235T variant differed significantly in hypertensives and normotensives (OR-CI = 2.62 (1.24–5.76), P
=
0.006; OR-CI = 0.699 (0.518–0.943), P
=
0.018), respectively. When the samples were segregated based on sex, the 235TT genotype and T allele were predominant in the female patients (OR-CI = 5.68 (1.60-25.10), P
=
0.002; OR-CI = 0.522 (0.330–0.826), P
=
0.005) as compare to the male patients (OR-CI = 1.54 (1.24–5.76), P
=
0.34; OR-CI = 0.874 (0.330–0.826), P
=
0.506), respectively. For ACE DD variant, we found overrepresentation of “I”-allele (homozygous II and heterozygous ID) in unaffected males which suggest its protective role in studied population (OR-CI = 0.401 (0.224–0.718); P
=
0.0009). The M235T variant of the AGT is significantly associated with female hypertensives and ACE DD variant could be a risk allele for essential hypertension in south India.


---

## Body

## 1. Introduction

Human essential hypertension (EHT) is a multifactorial trait with a complex genetic basis. This complex disease is due to the consequence of an interaction between various environmental and genetic factors and it plays a major role in blood pressure (BP) variation [1]. It does not follow the Mendelian mode of transmission [2]. The genetic contribution is estimated to be between 30% and 40% of BP variation [3]. In recent years, a series of genes have been proposed to influence the mechanism of blood pressure. Some evidences of association between these genes had been reported [4–6] but on the contrary these associations were not always significant [7].More than 150 candidate genes have been implicated in the regulation of blood pressure that is linked to several pathways. Among these genes, RAS has significant direct involvement in the BP regulation as it is reported in several studies and most of the antihypertensive drugs are targeting this system. The genetic variation of RAS encoding genes, angiotensinogen (AGT), angiotensin-1-converting enzyme (ACE), and angiotensin II type 1 receptor (AGTR1), were associated with EHT and have been important genes for the association studies in various populations [8–10].AGT, the natural substrate of RAS, is synthesized in the liver and released into blood circulation. The potential role ofAGT gene in hypertension was originally explored by Jeunemaitre group through linkage and association study in the causation of human EHT in Utah and French populations [4].AGT variants have been shown to associate with serumAGT in black and white children, providing a potential mechanism for genetic associations [11, 12]. Among the identified major molecular variants ofAGT, M235T and T174 M variants had a significant association with hypertension [13]. But associations with these variants are found to be contradictory in different populations [14]. Two different meta-analyses in Chinese populations have also confirmed that T allele ofAGT M235T polymorphism is associated with essential hypertension [15, 16].ACE is a key zinc metalloenzyme of the RAS and is widely distributed in the kidney [17]. TheACE catalyzes the conversion of angiotensin I to the biologically active peptide, angiotensin II, which is involved in the control of fluid electrolyte balance and systemic blood pressure [18]. This polymorphism is characterized by the presence (insertion) or absence (deletion) of a 287 bp AluYa5 element inside intron 16. Although I/D polymorphism is located in intronic region of theACE gene, several investigators have found that the D allele is related to increased activity ofACE in serum. The highest serumACE activity was seen in the DD genotype while the lowest was seen in the II genotype [19]. Among theACE gene polymorphisms of exon 17, G2350A variant has the most significant effect on plasmaACE concentrations as it accounts for 19% of the total variance inACE plasma levels.ACE I/D is in linkage disequilibrium (LD) withACE G2350A and both the variants are associated with essential hypertension with contradictory result [20, 21]. Meta-analyses in different studies also found that DD genotype ofACE I/D polymorphism [22, 23] and AA genotype of ACE G2350A polymorphism are associated with essential hypertension [24].TheAGTR1, a receptor for angiotensin II, is a member of the G-protein-coupled receptor super family expressed in most tissues, where receptor activation leads to vasoconstriction, water retention, and vascular smooth muscle cell proliferation and hypertrophy [25, 26]. The polymorphism A1166C in the 3′ untranslated region of theAGTR1 gene was detected in study by Bonnardeaux et al., (1994) who also identified its association with hypertension [27]. Several recent findings and meta-analysis reported that it is associated with essential hypertension [28, 29]; however, conflicting results are also reported by few studies [30, 31].The goal of the present analysis is to assess the effect of a combination of variants at different loci of pathophysiological pathway of RAS genes in south Indian population. In this case-control study, we examined possible associations between polymorphisms of theAGT,ACE, andAGTR1 genes and hypertension in the south Indian population age between 30 and 70 years. We therefore determined the association betweenAGT M235T,ACE I/D,ACE G2350A, andAGTR1 A1166C polymorphisms in the study population.


## 2. Materials and Methods

### 2.1. Study Population

Blood sample (5 mL) were collected from patients (n
=
211) and control subjects (n
=
211) between the age of 30 and 70 years from the clinics after informed consent form was obtained from all the participating volunteers. Patients were diagnosed in accordance with JNC 7 guidelines [32] and hypertension was defined as systolic BP (SBP) of ≥140 mm Hg and/or diastolic BP (DBP) of ≥90 mm Hg or prior diagnosis of essential hypertension by a physician or current use of antihypertensive medication or individual having a history of hypertension. All the cases included in the study were of essential hypertension as diagnosed by the physician. Cases with secondary forms of hypertension, myocardial infarction, and cerebrovascular incidents or other systemic diseases and any major illness in last six month before the sample collection were excluded. Normotensive individuals (n
=
211) with SBP ≤ 120 mm Hg and DBP ≤ 80 mm Hg with matched age, sex, and location were selected as controls. Control individuals were also devoid of associated conditions like vascular diseases, diabetes, and other systemic diseases or under any medication and BMI of ≤25 kg/m2. This study was approved by Institutional Ethical Committee. Clinical data and family history were recorded in the questionnaire for all the participants. All the participants belonged to Dravidian ancestry living in Tamil Nadu, south India. All the patients’ samples were collected from the Outpatients Department of Government Hospitals of Tamil Nadu, south India. Control samples were also collected from the volunteers living in same place and origin. Genomic DNA was extracted using modified Miller’s protocol [33] and it was quantified spectrophotometrically by OD260/OD280 ratio. Genotyping was performed with PCR-RFLP and allele specific primer methods. Primer, restriction enzyme and PCR conditions are shown in Supplementary Table 1 in Supplementary Material available online at http://dx.doi.org/10.1155/2014/538053.


### 2.2. Statistical Analysis

Differences in theACE,AGTR1, andAGT genotype frequencies between the cases and controls were compared using chi-square statistics. The odds ratio (OR) and 95% confidence interval (CI) were used as a measure of the strength of the association between genotype frequencies. Statistical significance accepted level was P
<
0.05. The frequencies of the marker alleles were estimated by allele counting method and tested for Hardy-Weinberg equilibrium (HWE). All the statistical calculations were carried out using PLINK 1.07 [34] and STATA 11.0. Power of the study was calculated using PS-Power and sample size calculation [35].MDR (multidimensionality reduction) analysis was performed using MDR software [36] to determine the genotypic combination that may confer high or low risk for EHT and also to determine the single most predictive genetic (gene-gene/gene-environment) model for EHT. Briefly, the MDR was comprised of two steps. First, the best combination of multifactors was chosen. Second, the combinations of genotypes are classified into high- and low-risk groups [37]. Interaction analysis was performed in the open source MDR software package (v.2.0) available at http://www.epistasis.org/ [38].


## 2.1. Study Population

Blood sample (5 mL) were collected from patients (n
=
211) and control subjects (n
=
211) between the age of 30 and 70 years from the clinics after informed consent form was obtained from all the participating volunteers. Patients were diagnosed in accordance with JNC 7 guidelines [32] and hypertension was defined as systolic BP (SBP) of ≥140 mm Hg and/or diastolic BP (DBP) of ≥90 mm Hg or prior diagnosis of essential hypertension by a physician or current use of antihypertensive medication or individual having a history of hypertension. All the cases included in the study were of essential hypertension as diagnosed by the physician. Cases with secondary forms of hypertension, myocardial infarction, and cerebrovascular incidents or other systemic diseases and any major illness in last six month before the sample collection were excluded. Normotensive individuals (n
=
211) with SBP ≤ 120 mm Hg and DBP ≤ 80 mm Hg with matched age, sex, and location were selected as controls. Control individuals were also devoid of associated conditions like vascular diseases, diabetes, and other systemic diseases or under any medication and BMI of ≤25 kg/m2. This study was approved by Institutional Ethical Committee. Clinical data and family history were recorded in the questionnaire for all the participants. All the participants belonged to Dravidian ancestry living in Tamil Nadu, south India. All the patients’ samples were collected from the Outpatients Department of Government Hospitals of Tamil Nadu, south India. Control samples were also collected from the volunteers living in same place and origin. Genomic DNA was extracted using modified Miller’s protocol [33] and it was quantified spectrophotometrically by OD260/OD280 ratio. Genotyping was performed with PCR-RFLP and allele specific primer methods. Primer, restriction enzyme and PCR conditions are shown in Supplementary Table 1 in Supplementary Material available online at http://dx.doi.org/10.1155/2014/538053.


## 2.2. Statistical Analysis

Differences in theACE,AGTR1, andAGT genotype frequencies between the cases and controls were compared using chi-square statistics. The odds ratio (OR) and 95% confidence interval (CI) were used as a measure of the strength of the association between genotype frequencies. Statistical significance accepted level was P
<
0.05. The frequencies of the marker alleles were estimated by allele counting method and tested for Hardy-Weinberg equilibrium (HWE). All the statistical calculations were carried out using PLINK 1.07 [34] and STATA 11.0. Power of the study was calculated using PS-Power and sample size calculation [35].MDR (multidimensionality reduction) analysis was performed using MDR software [36] to determine the genotypic combination that may confer high or low risk for EHT and also to determine the single most predictive genetic (gene-gene/gene-environment) model for EHT. Briefly, the MDR was comprised of two steps. First, the best combination of multifactors was chosen. Second, the combinations of genotypes are classified into high- and low-risk groups [37]. Interaction analysis was performed in the open source MDR software package (v.2.0) available at http://www.epistasis.org/ [38].


## 3. Results

Association studies of genetic polymorphisms and trait for detecting the complex diseases remain controversial. However, the association study of allele and genotype frequencies of candidate genes with the unaffected and affected subjects to understand the genetic etiology of complex human traits remains an efficient method [39–41]. Taking this method into consideration, we determined the possible association of genetic polymorphisms of RAS genes with EHT with the south Indian subjects. To the best of our knowledge, few studies have been published in RAS gene polymorphisms with the genotype and allele based association study in Indian subjects. But, large number of studies has reported association between EHT andACE  [42–45] orAGT  [46–48] gene polymorphism but lack of haplotype based association of the RAS gene with the EHT in south Indian population. Probably this could be the first comprehensive reports on RAS gene polymorphisms with association study of genotype and haplotype in relation to EHT in south Indian subjects.A total of 422 subjects were recruited for this study, out of which 211 subjects were cases and 211 subjects were controls. Among the patients, 109 (51.66%) are males and 102 (48.34%) are females, whereas in control subjects 130 (61.61%) are males and 81 (38.99%) are females (Table1). The mean age of control subjects is  43.71
±
14.17 years for males and 43.90
±
13.57 years for females. The mean ages of male patients are 54.56
±
13.04 years and 54.37
±
12.25 years for females. The difference in the distribution of epidemiological features were found to be significant between cases and controls with respect to gender (χ² =  4.26; P
=
0.039).Table 1
Sample size, sex ratio, and basic characteristics (means, standard deviation) of study sample.
Cases (n)
Controls (n)
N
211
211
Male
109
130
Female
102
81
Age (years), male
54.56
±
13.04
43.71
±
14.17
Age (years), female
54.37
±
12.25
43.90
±
13.57
N: sample size.Genotype distributions of all four studied polymorphisms were compatible with HWE expectation in cases as well as in controls. Differences between cases and controls in allele/genotype frequency distributions that were observed forAGT M235T andACE I/D polymorphism (Tables 2 and 3) with T and D allele are more prevalent in cases than in controls except forACE I/D polymorphism in females. Genotype/allele distribution ofACE G2350A andAGTR1 A1166C polymorphisms was similar in both cases and controls (Tables 2 and 3).Table 2
Distributions of allele frequencies in cases and controls stratified gender wise.
Gene
Allele
Minor allele
Freq. minor allele case
Freq. minor allele control
χ
2
OR
P value
AGT M235T
M/T
M
0.254
0.327
5.527
0.699 (0.518–0.943)
0.018
*
Female
0.226
0.358
7.797
0.522 (0.330–0.826)
0.005
*
Male
0.280
0.308
0.443
0.874 (0.588–1.299)
0.506
ACE I/D
I/D
I
0.398
0.462
3.524
0.770 (0.586–1.012)
0.060
Female
0.441
0.420
0.169
1.091 (0.719–1.656)
0.681
Male
0.357
0.489
8.265
0.584 (0.404–0.844)
0.004
*
ACE G2350A
G/A
A
0.173
0.164
0.136
1.070 (0.746–1.535)
0.713
Female
0.172
0.210
0.866
0.780 (0.461–1.318)
0.352
Male
0.174
0.135
1.444
1.357 (0.824–2.236)
0.229
AGTR1 A1166C
A/C
C
0.384
0.401
0.244
0.933 (0.708–1.230)
0.622
Female
0.363
0.414
0.985
0.807 (0.529–1.233)
0.321
Male
0.404
0.392
0.064
1.049 (0.726–1.515)
0.800
χ
2: Chi-square with 1 degree of freedom; OR: odds ratio; *
P
<
0.05: statically significant (alpha value 0.05/4).Table 3
Distribution of genotype frequencies of RAS gene polymorphisms in patients and control subjects.
SNPs
Genotype
Case % (N
=
211)
Control % (N
=
211)
OR
95% CI
P value
AGT
M235T
MM
6.16
14.22
Ref
MT
38.39
36.97
2.40
1.11–5.37
0.016
TT
55.45
48.82
2.62
1.24–5.76
0.006
*
Male
MM
8.26
12.31
Ref
MT
39.45
36.92
1.59
0.59–4.52
0.320
TT
52.29
50.77
1.54
0.58–4.25
0.340
Female
MM
3.92
17.28
Ref
MT
37.25
37.04
4.43
1.21–20.09
0.011
TT
58.82
45.68
5.68
1.60–25.10
0.002
*
ACE
I/D
II
18.96
24.17
Ref
ID
41.71
44.08
1.21
0.71–2.07
0.467
DD
39.34
31.75
1.58
0.90–2.76
0.087
Male
II
17.43
23.08
Ref
ID
36.70
51.54
0.94
0.45–2.02
0.870
DD
45.87
25.38
2.39
1.09–5.27
0.020
Female
II
20.59
25.93
Ref
ID
47.06
32.10
1.85
0.80–4.28
0.117
DD
32.35
41.98
0.97
0.42–2.25
0.940
ACE
G2350A
GG
71.09
72.51
Ref
GA
23.22
22.27
1.06
0.65–1.73
0.793
AA
5.69
5.21
1.11
0.43–2.88
0.805
Male
GG
71.56
77.69
Ref
GA
22.02
17.69
1.51
0.42–5.66
0.472
AA
6.42
4.62
1.35
0.67–2.71
0.359
Female
GG
70.59
64.20
Ref
GA
24.51
29.63
0.75
0.37–1.54
0.400
AA
4.90
6.17
0.72
0.16–3.32
0.620
AGTR1
A1166C
AA
41.71
40.28
Ref
AC
39.81
39.34
0.98
0.62–1.53
0.917
CC
18.48
20.38
0.88
0.50–1.53
0.622
Male
AA
37.61
40.77
Ref
AC
44.04
40.00
1.03
0.47–2.24
0.540
CC
18.35
19.23
1.19
0.65–2.19
0.930
Female
AA
46.08
39.51
Ref
AC
35.29
38.27
0.79
0.39–1.61
0.484
CC
18.63
22.22
0.72
0.30–1.70
0.409
N: sample size; OR: odds ratio; CI: confidence interval; Ref: reference; *
P
<
0.05: statically significant.To test the association of RAS gene polymorphisms with hypertension, genotype odds ratio was calculated for all the variants reported in the table.


### 3.1.AGT M235T Polymorphism

The genotype distribution of M235T polymorphism was significantly different between case and control subjects. Taking the MM genotype of theAGT M235T polymorphism as a reference, association of the MT genotype was 2.40 (95% CI: 1.11–5.37) and TT genotype was 2.62 (95% CI: 1.24–5.76), indicating a dominant effect of the T on risk and T allele is highly associated with hypertension in our recessive model (Table 4). Allelic association does not withstand after multiple corrections (alpha value 0.05/4 = 0.013; Table 2). Furthermore, the samples were segregated for subgroup analysis on the basis of gender and T allele was associated with the female patients (OR: 0.522; 95% CI: 0.330–0.826) after applying the Bonferroni corrections (Tables 2 and 3).Table 4
Distribution of RAS gene polymorphisms (dominant and recessive model) in patient and control subjects.
SNPs
Model
TEST
Case (N)
Control (N)
OR
95% CI
P value
AGT M235T
MM + MT versus TT
DOM
94/117
108/103
0.766
0.513–1.144
0.173
MM versus MT + TT
REC
13/198
30/181
0.396
0.184–0.813
0.006
*
Male
MM + MT versus TT
DOM
52/57
64/66
0.941
0.547–1.616
0.814
MM versus MT + TT
REC
9/100
16/114
0.641
0.239–1.624
0.308
Female
MM + MT versus TT
DOM
42/60
44/37
0.589
0.313–1.106
0.077
MM versus MT + TT
REC
04/98
14/67
0.062
0.015–0.185
0.000
ACE I/D
II + ID versus DD
DOM
128/83
144/67
0.718
0.471–1.092
0.104
II versus ID + DD
REC
40/171
51/160
0.734
0.447–1.201
0.193
Male
II + ID versus DD
DOM
59/50
97/33
0.401
0.224–0 .718
0.0009
*
II versus ID + DD
REC
19/90
30/100
0.704
0.349–1.397
0.282
Female
II + ID versus DD
DOM
69/33
47/34
1.513
0.789–2.898
0.180
II versus ID + DD
REC
21/81
21/60
0.741
0.350–1.569
0.394
ACE G2350A
AA + AG versus GG
DOM
61/150
58/153
1.073
0.686–1.677
0.746
AA versus AG + GG
REC
12/199
11/200
1.096
0.432–2.813
0.830
Male
AA + AG versus GG
DOM
31/78
29/101
1.384
0.738–2.596
0.276
AA versus AG + GG
REC
7/102
6/124
1.418
0.394–0.273
0.540
Female
AA + AG versus GG
DOM
30/72
29/52
0.747
0.383–1.462
0.358
AA versus AG + GG
REC
05/97
05/76
0.784
0.174–0.542
0.707
A1166C
CC + CT versus TT
DOM
123/88
126/85
0.943
0.628–1.416
0.767
CC versus CT + TT
REC
39/172
43/168
0.886
0.530–1.477
0.623
Male
CC + CA versus AA
DOM
68/41
77/53
1.142
0.656–1.992
0.619
CC versus CA + AA
REC
20/89
25/105
0.944
0.464–1.903
0.862
Female
CC + CA versus AA
DOM
55/47
49/32
0.764
0.405–1.439
0.373
CC versus CA + AA
REC
19/83
18/63
0.801
0.365–1.767
0.548
DOM: dominant model; REC: recessive model;N: sample size; OR: odds ratio; CI: confidence interval; *
P
<
0.05: statically significant.


### 3.2.ACE I/D Polymorphism

Considering I/D polymorphism, the distribution of genotypes did not differ significantly between EHT patients and controls through a slight increase in the frequency of DD (39.34%) homozygous that was observed among patients as compared to controls (31.75%) (Table3). However, our results revealed overrepresentation of “I”-allele carriers (homozygous II and heterozygous ID) in male control subjects (Table 4) which suggests its protective role in studied population. This association was estimated as odds ratio of 0.401 with 95% CI 0.224–0.718 and withstand after multiple correction (Table 4).


### 3.3.ACE G2350A Polymorphism

The genotype distribution ofACE G2350A polymorphism did not differ significantly between EHT patients and control subjects, and the allele frequencies were in HWE in both groups (Tables 3 and 4).


### 3.4.AGTR1 A1166C Polymorphism

Genotyping frequencies of A1166C polymorphisms were identified for all the EHT patients and control subjects. Our result shows that there is no significant difference in genotype and allelic frequencies in EHT patients and controls. Furthermore, the allele frequencies are consistent with the HWE in both cases and controls (Tables2 and 3).


### 3.5. Analysis of Epistatic Interaction

To elaborate the findings of the analysis, MDR analysis was applied to detect and characterize high-order gene-gene and gene-environmental interactions in cases and controls. Figure1 illustrates the MDR interaction information analysis of all four polymorphisms studied gene, represented in the form of a dendrogram. The MDR analysis shows synergistic effect ofACE andAGT polymorphisms in the EHT patients. To improve the quality of analysis and identify the disease risk, we have carried out combination analysis and haplotype frequencies on the basis of the polymorphism pairs selected by MDR analysis. Similar analysis between gene-environmental interactions showed moderate synergistic effect of the markerAGT M235T andACE I/D with the sex in the development of EHT (Figure 1). Table 5
summarizes the results of the MDR analysis evaluated for all possible combinations of the polymorphisms studied for the risk of developing hypertension. It shows the best model with a combination of polymorphisms in order along with its prediction error and coefficient of variation (CV) consistency. Result reveals the interaction ofAGT M235T-ACE I/D polymorphisms as the overall best models with least prediction error of 0.39 and CV consistency of 10/10. High-risk (dark grey) and low-risk (light grey) genotypic combinations were determined based on the threshold value, which was 1.0 (211/211) for the present data. It was observed that TT genotype ofAGT M235T polymorphism when present in combination with DD genotype ofACE I/D polymorphism conferred a 2.5 times higher risk (56/22) for developing EHT (Figure 2).Table 5
Summary of MDR analysis. MDR analysis reveals that combination ofACE I/D and AGT M235T could be a high risk for the prevalence of the EHT.
Model
Training bal. acc. (%)
Testing bal. acc. (%)
Cross-validation consistency
Prediction error
Sex
0.550
0.528
08/10
0.450
I/D, M235T
0.613
0.595
10/10
0.387
I/D, M235T, and A1166C
0.655
0.569
6/10
0.345
I/D, M235T, A1166C, and sex
0.710
0.602
7/10
0.290Figure 1
Interaction dendrogram for the four polymorphisms of RAS gene modeled by the MDR method. A red or orange line indicates synergistic or nonadditive relationship yellow line, independency, or additivity.Figure 2
Distribution of high-risk (dark shaded) and low-risk (light shaded) genotypes among the markers studied. The summary of the distribution illustrates the hypertensives (left bars) and normotensives (right bars) for each genotype combination. Asterisk (*) indicates the significant difference between cases and control subjects.


## 3.1.AGT M235T Polymorphism

The genotype distribution of M235T polymorphism was significantly different between case and control subjects. Taking the MM genotype of theAGT M235T polymorphism as a reference, association of the MT genotype was 2.40 (95% CI: 1.11–5.37) and TT genotype was 2.62 (95% CI: 1.24–5.76), indicating a dominant effect of the T on risk and T allele is highly associated with hypertension in our recessive model (Table 4). Allelic association does not withstand after multiple corrections (alpha value 0.05/4 = 0.013; Table 2). Furthermore, the samples were segregated for subgroup analysis on the basis of gender and T allele was associated with the female patients (OR: 0.522; 95% CI: 0.330–0.826) after applying the Bonferroni corrections (Tables 2 and 3).Table 4
Distribution of RAS gene polymorphisms (dominant and recessive model) in patient and control subjects.
SNPs
Model
TEST
Case (N)
Control (N)
OR
95% CI
P value
AGT M235T
MM + MT versus TT
DOM
94/117
108/103
0.766
0.513–1.144
0.173
MM versus MT + TT
REC
13/198
30/181
0.396
0.184–0.813
0.006
*
Male
MM + MT versus TT
DOM
52/57
64/66
0.941
0.547–1.616
0.814
MM versus MT + TT
REC
9/100
16/114
0.641
0.239–1.624
0.308
Female
MM + MT versus TT
DOM
42/60
44/37
0.589
0.313–1.106
0.077
MM versus MT + TT
REC
04/98
14/67
0.062
0.015–0.185
0.000
ACE I/D
II + ID versus DD
DOM
128/83
144/67
0.718
0.471–1.092
0.104
II versus ID + DD
REC
40/171
51/160
0.734
0.447–1.201
0.193
Male
II + ID versus DD
DOM
59/50
97/33
0.401
0.224–0 .718
0.0009
*
II versus ID + DD
REC
19/90
30/100
0.704
0.349–1.397
0.282
Female
II + ID versus DD
DOM
69/33
47/34
1.513
0.789–2.898
0.180
II versus ID + DD
REC
21/81
21/60
0.741
0.350–1.569
0.394
ACE G2350A
AA + AG versus GG
DOM
61/150
58/153
1.073
0.686–1.677
0.746
AA versus AG + GG
REC
12/199
11/200
1.096
0.432–2.813
0.830
Male
AA + AG versus GG
DOM
31/78
29/101
1.384
0.738–2.596
0.276
AA versus AG + GG
REC
7/102
6/124
1.418
0.394–0.273
0.540
Female
AA + AG versus GG
DOM
30/72
29/52
0.747
0.383–1.462
0.358
AA versus AG + GG
REC
05/97
05/76
0.784
0.174–0.542
0.707
A1166C
CC + CT versus TT
DOM
123/88
126/85
0.943
0.628–1.416
0.767
CC versus CT + TT
REC
39/172
43/168
0.886
0.530–1.477
0.623
Male
CC + CA versus AA
DOM
68/41
77/53
1.142
0.656–1.992
0.619
CC versus CA + AA
REC
20/89
25/105
0.944
0.464–1.903
0.862
Female
CC + CA versus AA
DOM
55/47
49/32
0.764
0.405–1.439
0.373
CC versus CA + AA
REC
19/83
18/63
0.801
0.365–1.767
0.548
DOM: dominant model; REC: recessive model;N: sample size; OR: odds ratio; CI: confidence interval; *
P
<
0.05: statically significant.


## 3.2.ACE I/D Polymorphism

Considering I/D polymorphism, the distribution of genotypes did not differ significantly between EHT patients and controls through a slight increase in the frequency of DD (39.34%) homozygous that was observed among patients as compared to controls (31.75%) (Table3). However, our results revealed overrepresentation of “I”-allele carriers (homozygous II and heterozygous ID) in male control subjects (Table 4) which suggests its protective role in studied population. This association was estimated as odds ratio of 0.401 with 95% CI 0.224–0.718 and withstand after multiple correction (Table 4).


## 3.3.ACE G2350A Polymorphism

The genotype distribution ofACE G2350A polymorphism did not differ significantly between EHT patients and control subjects, and the allele frequencies were in HWE in both groups (Tables 3 and 4).


## 3.4.AGTR1 A1166C Polymorphism

Genotyping frequencies of A1166C polymorphisms were identified for all the EHT patients and control subjects. Our result shows that there is no significant difference in genotype and allelic frequencies in EHT patients and controls. Furthermore, the allele frequencies are consistent with the HWE in both cases and controls (Tables2 and 3).


## 3.5. Analysis of Epistatic Interaction

To elaborate the findings of the analysis, MDR analysis was applied to detect and characterize high-order gene-gene and gene-environmental interactions in cases and controls. Figure1 illustrates the MDR interaction information analysis of all four polymorphisms studied gene, represented in the form of a dendrogram. The MDR analysis shows synergistic effect ofACE andAGT polymorphisms in the EHT patients. To improve the quality of analysis and identify the disease risk, we have carried out combination analysis and haplotype frequencies on the basis of the polymorphism pairs selected by MDR analysis. Similar analysis between gene-environmental interactions showed moderate synergistic effect of the markerAGT M235T andACE I/D with the sex in the development of EHT (Figure 1). Table 5
summarizes the results of the MDR analysis evaluated for all possible combinations of the polymorphisms studied for the risk of developing hypertension. It shows the best model with a combination of polymorphisms in order along with its prediction error and coefficient of variation (CV) consistency. Result reveals the interaction ofAGT M235T-ACE I/D polymorphisms as the overall best models with least prediction error of 0.39 and CV consistency of 10/10. High-risk (dark grey) and low-risk (light grey) genotypic combinations were determined based on the threshold value, which was 1.0 (211/211) for the present data. It was observed that TT genotype ofAGT M235T polymorphism when present in combination with DD genotype ofACE I/D polymorphism conferred a 2.5 times higher risk (56/22) for developing EHT (Figure 2).Table 5
Summary of MDR analysis. MDR analysis reveals that combination ofACE I/D and AGT M235T could be a high risk for the prevalence of the EHT.
Model
Training bal. acc. (%)
Testing bal. acc. (%)
Cross-validation consistency
Prediction error
Sex
0.550
0.528
08/10
0.450
I/D, M235T
0.613
0.595
10/10
0.387
I/D, M235T, and A1166C
0.655
0.569
6/10
0.345
I/D, M235T, A1166C, and sex
0.710
0.602
7/10
0.290Figure 1
Interaction dendrogram for the four polymorphisms of RAS gene modeled by the MDR method. A red or orange line indicates synergistic or nonadditive relationship yellow line, independency, or additivity.Figure 2
Distribution of high-risk (dark shaded) and low-risk (light shaded) genotypes among the markers studied. The summary of the distribution illustrates the hypertensives (left bars) and normotensives (right bars) for each genotype combination. Asterisk (*) indicates the significant difference between cases and control subjects.


## 4. Genetic Power Test

We estimated the genetic power using the M235T polymorphism as an example; an 80% power should have to detect linkage between hypertension and T allele at type I error of 0.05 when the sample includes 211 cases and 211 controls. We also performed post hoc exploratory analyses to examine the relationships of the polymorphisms with cases and control subjects. Genetic power estimation showed that 211 cases and 211 controls had >80% power to detect linkage between M235T variant and hypertension in south Indian population.


## 5. Discussion

The renin-angiotensin system is a major endocrine/paracrine system that regulates blood pressure (BP) in our body [49], genes encoding components of this system have been strong candidates for the investigation of the genetic basis of essential hypertension and major targets for antihypertensive drugs [50]. However, previous studies in south India mainly focus on limited gene of RAS [47, 48, 51]; thus we carried out a case-control study to systemically investigate the association between polymorphisms in RAS genes and essential hypertension. The present study identifies gender specific genetic variants in RAS genes that may play crucial roles in BP regulation and susceptibility for hypertension. A significantly higher frequency of theAGT 235TT was observed in female patients when compared to the female controls.ACE DD was more prevalent in male patients when compared with male controls. So,AGT M235T was associated with EHT in females andACE I/D was associated with males in our study population. Association of T variant with the essential hypertension in our study has shown agreement with some studies.Jeunemaitre et al., 1992 [4], were the first to report the linkage of the molecular variants M235T with hypertension in the Caucasians. Subsequent studies among the UK/Chinese/Malaysian/south Indian supported the former finding [15, 40, 47, 48, 52] while a study of Germany/North India is inconsistent with the previous report  [47, 53]. The association studies in the Africans/African-Americans mostly found a negative association [54, 55], but the high frequency of T allele was observed in this population and it is associated with increase in plasma and mRNAAGT concentration [11, 55, 56].The frequency of the 235T variant (major allele in our study) was 0.746 for this study among cases and this frequency was similar to study already reported in Chinese (0.73) and Hong Kong Chinese (0.82) population [16, 57]. The frequency of 235T variant in the 1000 genome project was found to be 0.87 in Africans, 0.64 in Americans, and 0.84 in Asians but the frequency was deviated in Europeans with the frequency of 0.41 [58]. Several studies in south India has reported that the 235T frequencies are in the range of 0.56–0.81 in the patients [13, 59–61]. But in north India the frequency was reported to be 0.31 in the cases [44]. Prasad and colleague have performed a comparative study of north and south India in control subjects and 235T variant frequency was found to be 0.33 and 0.52, respectively [62]. These overall results show that 235T variant is predominantly present in south India compared to north India. Our study showed a higher OR 2.62 (95% CI, 1.24–5.76; P
=
0.006) compared to a recent meta-analysis [15] in Han Chinese population which reports high association betweenAGT M235T polymorphism and hypertension (OR = 1.54; 95% CI, 1.16–2.03; P
=
0.002). On the contrary, another meta-analysis of 126 studies by Sethi et al. (2003) has reported that odds ratio for hypertension was 1.19 (1.10 to 1.30) in TT individuals in white subjects and 1.60 (1.19 to 2.15) in Asian subjects and it was not associated with SBP or DBP [63]. Instead, M235T genotype was associated with a stepwise increase in angiotensinogen levels in white subjects and a corresponding increase in risk of hypertension in both White and Asian subjects [63]. In another meta-analysis, the frequencies of the AGT T allele were 80% in cases and 72% in controls. The pooled OR (with 95% CI) of TT versusMT + MM was 1.76 (1.44–2.16) (P
<
0.00001) with T versus M of 1.54 (1.31–1.81). The pooled OR of MM versus MT + TT was 0.67 (0.45–1.00) (P
=
0.05) [16].In this study, the significantly higher prevalence of 235T allele in female patients is in agreement with the previous report that the T allele was significantly more prevalent among female ETH than in control subjects [4]. In contrast, Freire et al. (1998) [64] found that theAGT M235T homozygous mutation genotype was significantly higher in males compared to females. Earlier studies have found that plasmaAGT levels in postmenopausal women are slightly higher [65] than in men [66]. Plasma angiotensinogen levels are more increased in M235T variant than the 235 M variant with administration of ethinyl estradiol (EE), a synthetic estrogen. TheAGT G (-6) variant is less transcriptionally active with lower levels ofAGT mRNA [16, 67] and a significant linkage disequilibrium between M235T and G-6A was also reported. These findings reveals that G-6A polymorphism, which is linked to nonfunctioning M235T, increased the plasmaAGT level via regulation ofAGT gene transcription and was involved in the pathogenesis of the predisposition to hypertension. Thus, sex hormones such as estrogen might bind to the core promoter region and enhance the transcription ofAGT gene. However, it is also can be hypothesized that estrogen may bind to the -6A variant more effectively andAGT gene expression could be more in this variant. Hence, the angiotensinogen promoter is directly controlled by estrogen [68, 69].The I/D allelic variant (intronic deletion of a 287 bp Alu sequence repetitive element, D allele) is one of the most intensively investigated genetic polymorphism in the field of hypertension and cardiovascular disease research [70, 71]. In the present study, dominant model ofACE gene in male (II + ID versus DD) is associated with EHT in south Indian and it was also observed that I allele has a protective role. Overrepresentation of D allele in male cases represents strong association in pathogenesis of hypertension in male. This is in accordance with the previous report by many studies [72–74]. Our study showed a lower OR 0.401 (95% CI 0.224–0.718; P
<
0.01) compared to a recent meta-analysis [22] in whole Chinese population which reports high association withACE DD polymorphism with hypertension (OR = 1.27; 95% CI 1.17–1.46; P
<
0.01). The D allele ofACE was initially suggested to be associated with increased levels of serumACE activity as compared with I variant [75, 76]. In contrast to this, Zee et al. (1992) has reported that “I” allele was associated with high blood pressure in an Australian population with strong evidence of familial hypertension [77]. In recent meta-analysis, the distribution of the D allele frequency was 0.45 for the EH group and 0.40 for the control group. The summary OR for the distribution frequency of D allele was 1.27 (5% CI 1.17–1.37). The heterogeneity among the 67 studies was also significant (P
<
0.00001,I(2) = 71.4%). There was a significant association between distribution frequency of the D allele and EH risk in Han, Kazakh, Tibetan, Zhuang, and unclassified nationalities (P
<
0.05). Contradictory result was observed in the national minorities, such as Mongolian, Uighur, Yi, Dongxiang, Yugu, Korean and Gamel, and theD allele; and EH risk was not significant (P
>
0.05) [22].The mechanism of the sex specific association with hypertension remains unclear. One notion is that estrogen protects against hypertension. Even though estrogen upregulates theAGT gene expression but it again acts as negative feedback mechanism in controlling renin secretion and then theACE secretion in RAS [78]. Sex differences exist in the regulation of arterial pressure and renal function by RAS. This may in part stem from a differential balance in the pressor and depressor arms of the RAS (Hilliard et al., 2013). In males, theACE/AngII/AGTR1 pathways are enhanced, whereas, in females, the balance is shifted towards theACE2/Ang(1-7)/MasR (Mas receptor) and angiotensin type 2 receptor (AT2R) pathways [79]. Studies reported that premenopausal women, as compared to age matched men, are protected from renal and cardiovascular disease, and this differential balance of the RAS between the sexes likely contributes [80, 81].There were some limitations in this study. First, the age and sex match case control was not available in the sample studied. Our approach is based on a sample with a relatively homogeneous genetic background, and therefore the results are unlikely to be affected by unmeasured confounding factors of population stratification. This study did not measure central obesity and psychiatric comorbidities, the major risk factor for hypertension. There are no measurements of plasma angiotensinogen levels or other markers of RAS activation available to correlate directly with the genetic polymorphisms investigated in this study.


## 6. Conclusion

In summary, the genotype distributions of theAGT M235T polymorphism influenced the risk of essential hypertension in south Indian women andACE DD is a risk in south Indian male population. MDR analysis reveals that if both TT and DD genotypes are present, prevalence of EHT is higher in the present study. The haplotype based MDR analysis suggests that we had adequate power to detect the functional relationship of the best factor model, increasing the risk of essential hypertension associated with combined genetic variations. This is the first report to evaluate the simultaneous association ofACE,AGTR1, andAGT gene polymorphisms in essential hypertension by haplotype based analyses and gender specific association in south India. Future studies are required to consider the joint effects of several candidate genes to dissect the genetic framework and gender specific association of essential hypertension.



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*Source: 538053-2014-04-17.xml*