Abstract
Aim
A case control study was designed to assess whether the prevalence of ACE gene polymorphism has any role in the development of CAD.
Methods
The study included unrelated 217 cases with CAD and 255 healthy controls. PCR was done using primers followed by agarose gel electrophoresis for study of different ACE gene polymorphisms. Multiple logistic regression analysis was carried out to find association between studied genotypes and lifestyle as well as biochemical risk factors.
Results
Both DD [OR: 2.16; 95%CI: (60.60–67.40)] and ID [OR: 1.48; 95%CI: (93.28–97.72)] genotypes of the ACE gene showed significant associations in the development of CAD. Coexistence of diabetes and hypertension found to be risk modifier of the disease. Tobacco intake in various forms elevates the risk of the disease among the cases with risk genotypes.
Conclusion
ID and DD genotypes of ACE gene came out to be predisposing factors for the CAD cases in our study population.
Keywords: ACE, Polymorphism, Allele, Case–control, Logistic regression
1. Introduction
The World Health Organization (WHO) reports that in the year 2005 cardiovascular diseases (CVD) caused 17.5 million (30%) of the 58 million deaths that occurred worldwide.1 It has been projected that by the year 2010, 60% of the world's patients with heart disease will be in India.2 Ischaemic heart disease (IHD), myocardial ischaemia (MI), is a disease resulting reduced blood supply to the heart muscle, usually due to coronary artery disease (atherosclerosis of the coronary arteries). Coronary artery disease (CAD) is a multifactorial disorder that is thought to result from an interaction between genetic background and environmental factors such as diet, smoking and physical activity.3 Major risk factors are sedentary lifestyle, cigarette/bidi smoking, alcohol intake hypertension, high Low Density Lipid (LDL) cholesterol, low High Density Lipid (HDL) cholesterol and diabetes mellitus. Other factors that influence CHD risk are obesity, family history of premature CHD, insulin resistance, hypertriglyceridaemia, small dense LDL particles, lipoprotein A, serum homocysteine and abnormalities in several coagulation factors. Interactions between genetic and environmental factors influence progression of pathological processes clinical characteristics of disease and susceptibility to therapeutic treatment.4 Genetic factors help in explaining the molecular basis of the disorder and in designing prevention and treatment of the disease. The renin–angiotensin system not only is essential in cardiovascular haemodynamics, but plays an important role in the development of CVD. Angiotensin I-converting enzyme (ACE) is a key component of both the renin–angiotensin–aldosterone system (RAAS) and the Kinin–kallikrein system.5 Angiotensin-converting enzyme is a zinc metallopeptidase that cleaves the C-terminal dipeptide (His–Leu) from angiotensin 1 and generates a vasoconstrictor, angiotensin II.6 Through protease activity it also inactivates bradykinin, a potent vasodilator. Due to its role in the RAAS, human vascular tone and blood salt/water balance have been maintained.7 Higher activity of RAAS results in vasoconstriction, salt water retention, endothelial dysfunction etc which is detrimental to normal physiology. The ACE gene maps to chromosome 17q23 spans 21 kb, and comprises 26 exons and 25 introns.8,9 The two major species of ACE mRNA (transcription encompassing exons 1–26, excluding exon 13) and a 3 kb testicular type ACE mRNA (transcription encompassing exons 13–26). Exon 26 encodes for the functionally important membrane anchoring domain of the ACE protein. The activity of ACE was strongly influenced by a quantitative trait locus which is in linkage disequilibrium with the Alu insertion/deletion (I/D) marker10–13 in intron 16. Polymorphism in intron 16 results in three genotypes – insertion homozygote (I/I), insertion/deletion heterozygote (I/D) and deletion homozygote (D/D).14 The differences in the degree of linkage disequilibrium between this quantitative trait locus and the I/D polymorphism are cited as a reason for the differences in the association of the polymorphism with CAD in different populations.15 The serum ACE levels are determined by the ACE polymorphism in the following order: DD > I/D > II.12 Association of ACE I/D polymorphism with essential hypertension, myocardial infarction, coronary heart disease, development of nephropathy in insulin and noninsulin dependent diabetes mellitus and diabetes mellitus have been reported.16–20 An insertion/deletion (I/D) polymorphism of the ACE gene has been proposed as a genetic marker of risk of coronary heart disease.17 This polymorphism has been recognized to be a major determinant of plasma ACE activity, with the highest values found in subjects homozygous for the D allele and the lowest in subjects homozygous for the I allele; ID heterozygotes show intermediate values.21 Several studies have shown that the DD genotype is associated with a higher risk for myocardial ischaemia (MI) and CAD.17 Some studies on the association between ACE genotypes and the risk of CAD have provided controversial results.18
To the best of our knowledge the study is the first to report on probable association of certain ACE polymorphisms as predisposing factors in the development of the CAD and their interactions with relevant biochemical and lifestyle factors in the general population of Eastern India.
2. Materials and methods
2.1. Choice of study cases
Two hundred and seventeen clinically diagnosed cases with coronary artery diseases were chosen from the outdoor of Cardiology Department of Ramakrishna Mission Seva Pratishthan. Two hundred and fifty-five age and sex matched medically diagnosed healthy controls were taken for the study which were negative for Treadmill test (TMT −ve). All the samples were diagnosed by biochemical tests and other medical tests like ECG, Echo, Treadmill test. After selection of the subjects, detailed history regarding their clinical, lifestyle habits and socioeconomic conditions were collected. Detailed status of the relevant biochemical parameters were noted from their recent investigations. All the study subjects were Bengali, Indian and belonged to the same ethnic group. The research protocol was approved by the ethical committee of the institution.
2.2. ACE polymorphism study
2–3 ml blood were collected from each individual in an EDTA vial. Genomic DNA was extracted from peripheral blood leukocytes by salting out method.22 Polymerase chain reaction (PCR) detection of the insertion/deletion polymorphism of the human angiotensin converting enzyme gene (DCP1) i.e. dipeptidyl carboxypeptidase 1 was done by specific primer sequences, sense oligo: 5′ CTGGAGACCACTCCCATCC1TTCT 3′and anti-sense oligo: 5′ GATGTGGCCATCACATTCGTCAGAT 3′. The DNA was amplified for 30 cycles with denaturation at 94 °C for 1 min, annealing at 58 °C for 1 min, and extension at 72 °C for 2 min by Applied Biosystems 2720 Thermal Cycler. Genotypes of all individuals were noted as DD: 190 bp; ID: 490 bp, 190 bp; II: 490 bp (Fig. 1).13 All samples with the DD genotype were rechecked with allele specific primers.13 All the results were checked twice in double blind method.
Fig. 1.
Patterns of studied ACE polymorphisms. Lane 1: DD genotype (190 bp). Lane 2, 4: II genotype (490 bp). Lane 3: 50 bp molecular weight marker (Bangalore Genei). Lane 5, 6: ID genotype (490 bp, 190 bp).
2.3. Statistical analysis
To test for significance of observed interactions, likelihood ratio tests were conducted using a chi-square test. The odd-ratios for different association models were calculated with 95% confidence interval and simultaneously p values were calculated. A value of p < 0.05 was considered as statistically significant. Extent of other risk factors was compared between cases and controls and across genotype levels. The stepwise multiple logistic regression analysis was performed with the SPSS Statistical Package (version 14) for the determination of the independent risk factors for CAD.
3. Results
The status of total serum cholesterol, HDL cholesterol, LDL cholesterol and serum triglycerides among the study subjects are shown in Table 1. Significant associations were found for these parameters in the development of CAD. Table 2 shows the different lifestyle as well as demographic characteristics of the subjects. 44.44% of the cases were found to be smokers which is much higher than that of the controls (19.21%). Smoking includes intake of both cigarette and bidi (a dry rolled temburni leaf containing fine tobacco dust). As expected intake of other forms of tobacco also found to have significant association with the CADs. Other form of tobacco includes catechu, zarda (flavoured tobacco) etc. Though the frequency of alcohol intake was higher among the cases than the control, it did not have any statistical impact on the disease. The observed data strongly correlates family history and the development of the disease. Coexistence of diabetes, obesity and hypertension also elevates the risk of the disease. No differences in age and sex were observed among the cases and controls. We did not find any association of educational and economic background of the subjects with the disease (data not shown). Table 3 shows the distribution of different ACE genotypes and the corresponding allele frequencies among the subjects. The frequencies were compatible with Hardy–Weinberg equilibrium. It was found that both the ID and DD genotypes impart statistically significant effect on the development of CAD (Table 4). The number of D allele carrying subjects was significantly higher in CADs. D allele was found to impart more risk of the disease in homozygous form than the ID genotype. The interactions among different polymorphisms of ACE and age, sex, diabetes, hypertension, family history, different forms of tobacco use, alcohol intake with the risks of CADs are summarized in Table 5. It was found that extensive smoking (>35 shots/week) and tobacco intake, diabetes, hypertension and family history of CAD were significantly associated with DD and ID genotypes respectively. In short, it was found from the stepwise logistic regression analysis that D allele of ACE gene was an independent risk factor for the CADs (OR: 1.44, 95%CI: 230.12–236.88, p < 0.05).
Table 1.
Distribution of biochemical risk factors among study subjects.
| Cases (N = 217) [Mean ± S.D] | p* | Control (N = 255) [Mean ± S.D] | |
|---|---|---|---|
| HDL (mg/dl) | 49.6 ± 3.2 | <0.02 | 66.2 ± 2.4 |
| LDL (mg/dl) | 143 ± 2.4 | <0.02 | 115 ± 3.4 |
| Serum cholesterol (mg/dl) | 188 ± 5.2 | <0.05 | 173.5 ± 3.5 |
| Serum triglyceride (mg/dl) | 157 ± 82.1 | <0.02 | 132.2 ± 2.4 |
HDL: High density lipoprotein; LDL: Low density lipoprotein.
*p: calculated as chi-square test.
S.D: Standard deviation.
Table 2.
Baseline patient characteristics.
| Cases (N = 217) | p* | Controls (N = 255) | |
|---|---|---|---|
| Age (Yrs) | |||
| Range | 29–81 | – | 18–66 |
| Average | 42.60 | 40.53 | |
| Gender (n, %) | |||
| Male | 119 (54.8) | – | 140 (54.90) |
| Female | 98 (45.16) | 115 (45.09) | |
| Lifestyle habits (%) | |||
| Cigarette smoking | 97 (44.7) | <0.01 | 49 (19.21) |
| Other tobacco habit | 129 (59.44) | <0.01 | 199 (78.03) |
| Alcohol intake | 89 (41.01) | NS | 36 (14.11) |
| Diabetes (%)a | 82 (37.78) | <0.001 | 32 (12.54) |
| Hypertension (%)b | 183 (84.61) | <0.01 | 23 (9.01) |
| Obesity | |||
| BMI (kg/m2)c <25(%) | 77 (35.90) | – | 141 (55.48) |
| BMI (kg/m2) >25(%) | 138 (64.10) | <0.01 | 114 (44.51) |
*p: calculated as chi-square test; NS: Non-significant.
Fasting blood glucose ≥120 mg/dl.
Systolic pressure >130 mm Hg; diastolic pressure >80 mm Hg.
Body mass index.
Table 3.
Distribution of ACE genotype and allele frequencies in the study.
| Genotype frequencies |
Allele frequencies |
||||
|---|---|---|---|---|---|
| ID | DD | II | D allele | I allele | |
| Case (n) | 0.474 | 0.235 | 0.29 | 0.47 H = 0.69 |
0.37 |
| Control (n) | 0.443 | 0.152 | 0.40 | 0.527 H = 1.29 |
0.62 |
H = Hardy–Weinberg equilibrium.
Table 4.
Distribution of ACE genotypes in the study subjects (overall).
| Genotype | Cases (n,%) | Control (n,%) | Crude OR (CI%) | p* |
|---|---|---|---|---|
| ID | 103 (47.46) | 113 (44.31) | 1.48 (93.28–97.72) | <0.99 |
| DD | 51 (23.5) | 39 (15.29) | 2.16 (60.60–67.40) | <0.95 |
| II | 33 (29.03) | 103 (40.39) | – | – |
| D allele | 205 (47.23) | 191 (38.2) | 1.44 (230.12–236.88) | <0.95 |
| I allele | 229 (52.76) | 309 (61.8) | – | – |
OR: odd ratio; CI: confidence interval; NS: non-significant.
*p-values obtained through chi-square analysis of the differential genotypes.
Table 5.
Association of ACE genotypes with other risk factors.
| Factors | ID |
DD |
II |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Case (n, %) | Control (n, %) | OR, 95%CI | pa | Case (n, %) | Control (n, %) | OR, 95%CI | pa | Case (n, %) | Control (n, %) | |
| Sex | ||||||||||
| Male | 58 (26.72) | 43 (16.86) | 1.83 | 0.29 | 23 (10.59) | 21 (8.2) | 0.901 | 0.759 | 32 (14.7) | 78 (30.5) |
| (1.063–3.170) | (0.46–1.754) | |||||||||
| Female | 50 (23.04) | 70 (27.45) | 28 (12.9) | 18 (7) | 31 (14.2) | 25 (9.8) | ||||
| Age (years) | ||||||||||
| ≤45 | 34 (15.66) | 41 (16.07) | 0.939 | 0.838 | 15 (6.91) | 13 (5.09) | 0.389 | 0.182 | 21 (9.67) | 41 (16.07) |
| (0.516–1.710) | (0.182–0.829) | |||||||||
| >45 | 69 (31.72) | 72 (28.23) | 36 (16.58) | 26 (10) | 42 (19.35) | 62 (24.31) | ||||
| Other tobacco intake | ||||||||||
| 2–3 s times/day | 78 (35.9) | 82 (32.15) | 1.81 | 0.007 | 12 (5.52) | 30 (11.7) | 3.191 | 0.001 | 32 (14.74) | 57 (22.35) |
| (0.862–3.8) | (1.59–6.3) | |||||||||
| Never | 25 (11.52) | 31 (12.15) | 39 (17.97) | 9 (3.52) | 31 (14.28) | 46 (18.03) | ||||
| Smoking | ||||||||||
| Never | 21 (9.67) | 37 (14.5) | 11 (5.06) | 26 (10.19) | 37 (17) | 52 (20.39) | ||||
| Ex-smokers | 35 (16.12) | 25 (2.74) | 0.42 | 0.088 | 12 (5.52) | 5 (1.96) | 0.23 | 0.091 | 17 (7.83) | 21 (8.23) |
| (0.81–0.99) | (0.09–0.56) | |||||||||
| ≤35 times/week | 31 (14.28) | 22 (8.62) | 0.57 | 0.41 | 10 (4.6) | 1 (0.34) | 0.80 | 0.088 | 6 (2.76) | 15 (5.88) |
| (0.153–2.147) | (1.017–3.62) | |||||||||
| >35 times/week | 32 (14.74) | 29 (11.37) | 1.38 | 0.003 | 18 (8.29) | 7 (2.74) | 1.27 | 0.004 | 3 (1.38) | 15 (5.88) |
| (0.057–1.31) | (0.147–1.563) | |||||||||
| Alcohol intake | ||||||||||
| Heavy | 24 (11.05) | 28 (10.98) | 0.232 | 0.049 | 4 (1.84) | 2 (0.78) | 0.336 | 0.246 | 4 (1.87) | 11 (4.31) |
| (0.054–0.993) | (0.053–2.122) | |||||||||
| Occasional | 46 (21.19) | 36 (14.11) | 0.132 | 0.3 | 15 (7) | 6 (2.3) | 0.171 | 0.4 | 21 (9.67) | 20 (7.9) |
| (0.057–0.305) | (0.069–0.423) | |||||||||
| Never | 33 (15.2) | 49 (19.21) | 32 (14.74) | 31 (12.15) | 45 (20.73) | 72 (28.23) | ||||
| Coexistence of diabetes | ||||||||||
| Yes | 59 (27.18) | 22 (8.62) | 1.3 | 0.001 | 23 (10.59) | 17 (6.66) | 1.67 | 0.008 | 21 (9.7) | 30 (11.78) |
| (1.153–2.610) | (0.313–1.409) | |||||||||
| Never | 44 (20.27) | 91 (35.68) | 28 (12.9) | 22 (8.6) | 42 (19.35) | 73 (28.62) | ||||
| Coexistence of high LDLC | ||||||||||
| Yes | 82 (37.78) | 87 (34.11) | 0.481 | 0.35 | 38 (17.5) | 10 (4) | 0.288 | 0.091 | 21 (10) | 21 (8.23) |
| (0.244–0.950) | (0.139–0.597) | |||||||||
| Never | 21 (9.67) | 26 (10) | 13 (6) | 29 (11) | 42 (19) | 92 (37) | ||||
| Family history of CAD | ||||||||||
| Yes | 81 (37) | 30 (11.76) | 1.9 | 0.001 | 9 (5) | 18 (7.05) | 1.6 | 0.001 | 10 (4.6) | 20 (8) |
| (0.006–0.045) | (0.008–0.044) | |||||||||
| No | 22 (10.13) | 83 (33) | 42 (19.35) | 21 (8.2) | 53 (24.42) | 83 (32.5) | ||||
| Coexistence of hypertension | ||||||||||
| Yes | 86 (39.63) | 23 (9) | 1.7 | 0.001 | 41 (18.89) | 7 (2.7) | 1.1 | 0.004 | 45 (20.73) | 15 (5.88) |
| (0.008–1.044) | (1.005–2.06) | |||||||||
| Never | 17 (7.83) | 90 (35.29) | 10 (4.6) | 32 (12.54) | 18 (8.29) | 88 (34.5) | ||||
OR: odd ratio; CI: confidence interval.
Calculated by χ2 analysis comparing genotype distributions among case and control subjects.
4. Discussion
There have been several studies that have investigated D allele frequency with coronary artery disease including one meta-analysis of 118 published studies23 which demonstrated a modest positive association between ACE-ID and CAD. The meta-analysis highlighted the heterogeneity of the reports and the lack of information from certain high risk groups such as East Indian. Reports of ACE-ID and CAD in Indians are limited to two previous reports one centred in Mumbai24 and the second in Singapore25 both of which were negative. Few have also investigated the modification of risk associated with various forms of tobacco and alcohol consumption and the gene–gene interactions between these polymorphisms among several population groups worldwide. To the best of our knowledge our study traces out the same correlations with the CAD cases of Eastern India for the first time. Our study shows similar results to two recent studies from Poland26 and Portugal27 in connection with ACE-D allele associated with CAD, hypertension, smoking, obesity, diabetes and dyslipidaemia in their local populations. Risk factors and as well as genetic factors also play an important role in the development of coronary artery disease. ACE gene is significantly up regulated in adipose tissue and it has been shown before that ACE-D allele is associated with increased obesity.28,29 In our study, the prevalence of CAD was significantly high among the obsessed individuals. As per smoking and alcohol intake is concerned our results partially support some of the previous works.30,31 It is a known fact that nicotine increases ACE gene expression resulting in increased plasma and tissue activity of angiotensin II.32 Higher levels of nicotine were found in tobacco from bidis (26.9 mg/gm) as compared to cigarettes available in Indian markets (15 mg/gm). Nicotine concentration in other forms of chewing tobacco was 3.4 mg/gm.33 We observed significant association of extensive smoking of cigarettes with the disease in comparison to the other forms of tobacco. Alcohol intake did not have any role on the disease development. Further stratification analysis showed significant association between smoking (>35 shots/week), other tobacco habits with ID and DD genotypes but no association was found in case of alcohol intake. Association of the DD genotype of the ACE gene and myocardial infarction (MI) and CAD has also been reported in numerous studies.17,34–36 Cambien et al first reported a significant association between the ACE DD genotype and an increased risk of myocardial infarction (MI) in Ireland and France.17 Higher frequency of DD genotypes has also been observed among Japanese CAD cases.37 Studies on the Indian population have shown contradictory results. Distribution of ACE polymorphism varies in different geographical regions and ethnic groups in India. I allele frequency was significantly higher (p < 0.05) in Dogras, Assamese and Kumaonese and the D allele was higher in Punjabis.38 The aim of our study was to look for the polymorphisms of ACE in the development of coronary artery disease in the general population of Eastern India. We found higher D allele frequency and DD [OR = 2.16, 95%CI = 60.60–67.40 (p < 0.95)] and ID [OR = 1.48, 95%CI = 93.28–97.72 (p < 0.99)] genotypes were significantly higher in the study cases as compared to the controls. Coexistence of diabetes and hypertension has been reported to be risk factor for the development of CAD.39 Both hypertension and diabetes were more significantly associated with ID and DD genotypes in our study. Family history of CHD has been well recognized in some studies.40,41 We have also observed significantly higher prevalence of ID and DD genotypes among the cases who had strong history of development of CAD in their first degree relatives than the controls. As expected, the LDL, HDL, serum cholesterol, serum triglyceride were found to have statistical correlations with the diseases at different significant levels. Some have agreed that high LDL cholesterol and low HDL cholesterol are independent risk factors for CVD31,42,43 and our study also supports it. In summary, ID and DD genotypes of ACE gene came out to be predisposing factors for the CAD cases in our study population. In spite of several precautions our study has certain limitations. Our study was hospital-based and could result in biased selection in place of random sampling. It has been suggested that studies with hospital controls can provide lower risk estimates, since diseases of controls could be associated with the polymorphisms under study. The insertion/deletion polymorphism of ACE gene, being a low-penetrance mutation may be in linkage disequilibrium with another functional variant and analysis of multiple genetic markers in the context of environmental factors is required to increase the probability of providing clinically useful information. But, the paper attempts to establish the sole role of the concerned polymorphism in developing CAD. On the other hand, inclusion of additional subjects would enhance this study especially in light of the heterogeneity of worldwide reports including two negative reports with East Indian subjects. Though 117 individuals are sufficient to represent a population status, the associations and the underlying mechanisms of lifestyle factors with the metabolic enzymes gene polymorphisms still need further study with large-scale (population-based) samples and modified designs.
Conflicts of interest
All authors have none to declare.
Acknowledgments
We are thankful to the Secretary, Ramakrishna Mission Seva Pratishthan for kind permission to carry out work. The authors alone are responsible for the content and writing of the paper.
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