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Hypertension. 2006;48:700-710
Published online before print August 28, 2006, doi: 10.1161/01.HYP.0000238124.91161.02
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(Hypertension. 2006;48:700.)
© 2006 American Heart Association, Inc.

Original Articles

Endothelial NO Synthase Gene Polymorphisms and Hypertension

A Meta-Analysis

Elias Zintzaras; Georgios Kitsios; Ioannis Stefanidis

From the Department of Biomathematics (E.Z., G.K.), and Department of Nephrology (I.S.), University of Thessaly School of Medicine, Larissa, Greece.

Correspondence to Elias Zintzaras, MSc, PhD, Head, Department of Biomathematics, University of Thessaly School of Medicine, Papakyriazi 22, 41222 Larissa, Greece. E-mail zintza{at}med.uth.gr


*    Abstract
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 *Abstract
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 down arrowResults
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Studies investigated the association between endothelial NO synthase gene polymorphisms and hypertension-reported contradicted or nonconclusive results. A meta-analysis of 35 genetic association studies that examined the relation between hypertension and the G894T, 4a/b, T786C, and G23T polymorphisms of the endothelial nitric oxide synthase gene was carried out. Subgroup analysis by ethnicity and potential sources of heterogeneity and bias were explored. The meta-analysis included genotype data on 7779/10 498, 2216/3222, 2491/3913, and 833/587 cases/controls for G894T, 4b/a, T786C, and G23T, respectively. For the 4b/a polymorphism, overall, the heterogeneity between studies was not significant (P=0.82), and the allele b was associated with a 15% decreased risk of hypertension relative to allele a (odds ratio: 0.85; 95% CI: 0.74 to 0.98). Overall and in whites, the recessive model for allele b produced significant results (odds ratios: 0.78; 95% CI: 0.68 to 0.90 and OR: 0.76 95% CI: 0.62 to 0.92, respectively), whereas the dominant model produced nonsignificant results. In studies involved East Asians and blacks, an association was not demonstrated. Regarding the G894T, T768C, and G23T polymorphisms, in no case (ie, overall, in whites, or in East Asians) was a statistically significant association and heterogeneity found. There was no substantial source of bias in the selected studies. In conclusion, there is evidence of association only between 4b/a polymorphism and hypertension; however, studies exploring combinations of the polymorphisms may help us better understand the genetics of hypertension.


Key Words: nitric oxide • polymorphism • meta-analysis


*    Introduction
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 up arrowAbstract
 *Introduction
down arrowMethods
 down arrowResults
 down arrowDiscussion
 down arrowReferences
 
Hypertension is a multifactorial disease involving both environmental and genetic components.1 Clinical and animal studies have suggested that an alteration in NO metabolism may be a contributing factor in the pathogenesis of hypertension.2–4 Thus, abnormalities in the activity of the enzyme endothelial NO synthase (eNOS) that synthesize NO in endothelial cells may lead to NO deficiency. The gene encoding eNOS is located on chromosome 7 (7q35-q36) and contains 26 exons with an entire length of 21kb. G894T (Glu298Asp in exon 7), intron 4 (4b/a), (T-786)C (T786C), and G23T are the most clinically relevant polymorphisms in the eNOS gene that have been described.5

The genetic association studies that examined whether the polymorphisms in the eNOS gene are associated with hypertension have provided controversial or inconclusive results, partly because each study involved few cases and few controls and, therefore, there was not enough information to demonstrate association. Furthermore, the interpretation is complicated by the fact that different populations, sampling strategies, genotyping procedures, and number of loci included in the analyses have been used. To shed some light on these contradictory results, as well as to decrease the uncertainty of the effect size of estimated risk, a meta-analysis6 of all of the available studies related the G894T (Glu298Asp), 4b/a, (T-786)C (T786C), and G23T polymorphisms and their associations with hypertension for various genetic contrasts was carried out. In addition, the heterogeneity between studies and the existence of potential bias were explored. Cumulative and recursive cumulative meta-analyses were also performed.


*    Methods
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 up arrowAbstract
 up arrowIntroduction
 *Methods
down arrowResults
 down arrowDiscussion
 down arrowReferences
 
Selection of Studies
All of the studies published before May 2006 were identified by extended computer based searches of PubMed and EMBASE databases. The following search criterion was used: ("eNOS" or "endothelial nitric oxide synthase" or "NOS3") and "polymorphism" and ("hypertension" or "blood pressure"). The retrieved studies were then read in their entirety to assess their appropriateness for inclusion in the meta-analysis. All of the references cited in the studies were also reviewed to identify additional published work not indexed by the PubMed and EMBASE databases. Case reports, editorials, and review articles were excluded. The search was restricted to articles in English.

Case–control studies that determined the distribution of G894T, 4b/a, T786C, and G23T genotypes in cases with essential hypertension and in a healthy/normotensive control group were eligible for inclusion in the meta-analysis. Case subjects were considered to be hypertensive if their systolic or diastolic blood pressure was ≥140 mm Hg or ≥90 mm Hg, respectively; were reported to have hypertension; or were on antihypertensive therapy. In studies with overlapping cases/controls, the most recent study, the largest in size study, or the study with more information on origin of cases/controls was included in the meta-analysis. Only studies in human subjects that have used validated genotyping methods were considered. Finally, genome scans were excluded because they investigate linkage.7,8

Data Extraction
From each study, the following information was abstracted: first author, journal, year of publication, ethnicity of the study population, demographics, clinical characteristics, matching, validity of the genotyping method, and the number of cases and controls for each G894T, 4b/a, T786C, and G23T genotype. The frequencies of the alleles and the genotypic distributions were extracted or calculated for both the cases and the controls. In addition, it was recorded whether the genotyping in each study was blinded to clinical status. When studies investigated >1 polymorphism, information on linkage disequilibrium and haplotype estimation was recorded.

Meta-Analysis
Before the main analysis, the significance of association for: (1) the allele contrast (G894T G versus T, 4b/a b versus a, T786C T versus C, and G23T G versus T), (2) the recessive (G894T GG versus GT+TT, 4b/a bb versus ba+aa, T786C TT versus TC+CC, and G23T GG versus GT+TT), and (3) dominant models (G894T GG+TG versus TT, 4b/a bb+ba versus aa, T786C TT+TC versus CC, and G23T GG+GT versus TT) were evaluated for each study separately. All of the associations were indicated as odds ratios (ORs) with the corresponding 95% CI. Based on the individual ORs, a pooled OR was estimated.

The heterogeneity between studies in terms of degree of association was tested using the Q-statistic, which is the weighted sum of squares deviations of the OR study estimates from the pooled estimate.8–10 When the ORs are homogeneous, Q follows a {chi}2 distribution with r-1 (r is the number of studies) degrees of freedom. If P<0.10, then the heterogeneity was considered significant. Heterogeneity was quantified with the I2 metric [I2=(Q–d.f.)/Q], which is independent of the number of studies in the meta-analysis.11 I2 takes values between 0% and 100% with higher values denoting greater degree of heterogeneity (I2=0% to 25%: no heterogeneity; I2=25% to 50%: moderate heterogeneity; I2=50% to 75%: large heterogeneity; I2=75% to 100%: extreme heterogeneity). The pooled OR was estimated using fixed effects (FEs; Mantel–Haenszel) and random effects (REs; DerSimonian and Laird) models.12 The calculation of pooled OR and Q used as weighting factor (wi) the inverse variance of {theta}i=lnOR (ie, wi=1/var[{theta}i]) of each study i. RE modeling assumes a genuine diversity in the results of various studies and incorporates to the calculations a between-study variance. Therefore, when there is heterogeneity between studies, the pooled OR was estimated using the RE model.

A cumulative and recursive cumulative meta-analysis was carried out for each polymorphism to evaluate the trend of RE OR for the genetic contrast under investigation in time.13,14 In cumulative meta-analysis, studies were chronologically ordered by publication year, then the pooled OR was obtained at the end of each year, that is, at each information step. In recursive cumulative meta-analysis, the relative change in pooled OR in each information step (OR in next year/OR in current year) was calculated. Thus, cumulative and recursive cumulative meta-analysis provide a framework for updating a genetic effect from all of the studies and a measure of how much the genetic effect changes as evidence accumulates.

A differential magnitude of effect in large versus small studies for the genetic contrast under investigation was checked using the Egger regression test for funnel plot asymmetry and the Begg–Mazumdar test, which is based on Kendall’s {tau}.15–18 Given that these tests are underpowered, they were always considered statistically significant for P<0.10 rather than for P<0.05.15,16

In addition to the main (or overall) analysis, which included all of the available data, subgroup analysis for each ethnicity was also performed. Ethnicity was categorized into 2 main groups: (1) white descents, and (2) East Asian descents.19 However, the consistency of genetic effects across these traditionally defined ethnicities does not necessarily mean that ethnicity-specific genetic effects are exactly the same. The distribution of the genotypes in the control group was tested for Hardy–Weinberg equilibrium (HWE; P≥0.05).7 Studies with controls not in HWE were subjected to a sensitivity analysis.20 In sensitivity analysis, the effect of excluding specific studies was examined. Analyses were performed using Meta-Analyst (Lau), StatsDirect (Microsoft Corp), and CVF90 with the Institute of Museum and Library Sciences library.21,22


*    Results
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 *Results
down arrowDiscussion
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Eligible Studies
The literature review identified 137 titles in PubMed and 120 in EMBASE that met the search criteria. The full articles of the retrieved studies were read to assess their appropriateness for meta-analysis according to the inclusion criteria. Data from 33 articles that investigated the association between any of the G894T, 4a/b, T786C, and G23T polymorphisms and hypertension met the inclusion criteria, and they were included in the meta-analysis. Figure 1 presents a flow chart of retrieved studies and studies excluded, with specification of reasons. Two articles1,23 provided data on 2 separate study ethnicities: whites and blacks. Thus, data were obtained from 35 studies. Data were extracted by 2 investigators (G.K. and I.S.), and disagreements were resolved after a discussion between the 3 authors. Twenty-one studies dealt with G894T,1,23–40 16 with 4a/b,1,25,27,28,35,36,41–49 7 with T786C,1,4,29,32,50,51 and 4 with G23T.24,25,52,53 Seven studies in 4a/b,1,25,27,28,35,36 4 studies in T786C,1,29,32 and 2 studies in G23T24,25 also investigated G894T. Two studies1 investigated 3 polymorphisms together: G894T, 4a/b, and T786C. The design in 24 studies was case–control,* in 7 studies was population-based cohort,4,29,31,36,43,45 and in 4 studies was cross-sectional.23,37,34,47 The studies were published between 1995 and 2006.


Figure 1
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  		Figure 1. Flow chart of retrieved studies and studies excluded, with specification of reasons.

For the determination of the genetic polymorphisms of G894T, T786C, and G23T, validated genotyping methods were used in all of the studies; namely, PCR and restriction of the PCR product with the enzyme corresponding to each polymorphism{dagger} or PCR with allele-specific probes.23,24,29,32,51,52 The polymorphism 4a/b was genotyped using electrophoretic differentiation.1,25,27,28,35,36,41–49 Five studies stated that the controls were age or sex matched.29,30,38,48,53 Studies were conducted in various populations of racial descent: 19 involved whites,{ddagger} 11 involved East Asians,§ 2 involved blacks,1,23 1 involved Turks,48 1 involved Arabs,40 and 1 was mixed.37 One study involved male cases,4 1 study involved female cases,46 and 2 studies24,33 provided data for males and females separately. A list of details abstracted from the studies included in the meta-analysis is provided in Tables 1 through 5DownDownDownDownDown.


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  		TABLE 1. Characteristics of Eligible Studies Considered in the Meta-Analysis


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  		TABLE 1. (Continued)


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  		TABLE 2. The Distribution of the G894T Genotype for Cases and Controls (in Parenthesis Are the Respective Percentages)


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  		TABLE 3. The Distribution of the 4b/a Genotypes for Cases and Controls (in Parenthesis Are the Respective Percentages)


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  		TABLE 4. The Distribution of the T786C Genotype for Cases and Controls (in Parenthesis Are the Respective Percentages)


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  		TABLE 5. The Distribution of the G23T Genotype for Cases and Controls (in Parenthesis Are the Respective Percentages)

Summary Statistics
Overall, the studies provided 7779/10 498 cases/controls for G894T, 2216/3222 cases/controls for 4b/a, 2491/3913 cases/controls for T786C, and 833/587 cases/controls for G23T. Eleven studies23,25,28,35,47,50 did not provide data for all of the genotypes separately: 5 studies23,25,28,35 provided data on G894T T-carriers and non–T-carriers, 4 studies25,28,35,47 provided data on 4b/a a-carriers and non–a-carriers, 1 study50 provided data on T786C C-carriers and non–C-carriers, and 1 study25 provided data on G23T T-carriers and non–T-carriers. Two studies provided data only for allele frequency.38,44 The genotype distributions and the allele frequencies are shown in Tables 2 through 5UpUpUp. The distribution of genotypes in the control group deviated from HWE in 1 study for G894T24 (Table 2); however, HWE deviation could not be tested for all of the studies.23,25,28,35,47,50 Because lack of HWE indicates possible genotyping errors and/or population stratification, a sensitivity analysis was, therefore, carried out excluding this study. In addition, articles where HWE could not be assessed were treated as studies that deviate from HWE in the sensitivity analysis. Although the majority of studies reviewed in this meta-analysis reported on >2 of the investigated polymorphisms, only 3 of them provided analyses of haplotypes.1,32 One study27 reported the existence of linkage disequilibrium between G894T and 4b/a, 1 study25 between 4b/a and G23T, and 2 studies between G894T and T786C,29,32 whereas, 1 study50 reported a lack of linkage disequilibrium between G894T and T786C.

Main Results, Subgroup, and Sensitivity Analyses
Table 6 and Figure 2 show the results for the association between the different polymorphisms and the risk of hypertension. For the G894T polymorphism and its relationship to hypertension, the allele contrast G versus T showed nonsignificant heterogeneity among studies (P=0.13; I2=29%) and the FE and RE pooled ORs were not significant, at 1.00 (95% CI: 0.95 to 1.06) and 1.01 (95% CI: 0.93 to 1.10), respectively. In subgroup analysis, the association was not significant for whites and East Asians. The recessive and dominant models for the effect of allele G produced the same overall pattern as the allele contrast. The recessive model for blacks also showed no association.


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  		TABLE 6. ORs and Heterogeneity Results for the Genetic Contrasts of G894T, 4b/a, T786C, and G23T eNOS Polymorphisms for Hypertension


Figure 2
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  		Figure 2. RE OR estimates with the corresponding 95% CI for the recessive models of (A) G894T allele G, (B) 4b/a allele b, (C) T786C allele T, and (D) G23T allele G and the risk of hypertension. The OR estimate of each study is marked with a {blacksquare}. The size of the square represents the weight that the corresponding study exerts in the meta-analysis. The CIs of pooled estimates are displayed as a horizontal line through the diamond; this line might be contained within the diamond if the confidence interval is narrow. The horizontal axis is plotted on a log scale.

For the 4b/a polymorphism, overall, the heterogeneity between studies was not significant (P=0.82; I2=0%), and the 4b/a allele b was associated with a 15% decreased risk of hypertension compared with the a allele (FE OR: 0.85; 95% CI: 0.74 to 0.98). In subgroup analysis, the association was marginally significant for whites (FE OR: 0.83; 95% CI: 0.69 to 0.99). Overall and in whites, the recessive model for allele b produced significant results (FE OR: 0.78; 95% CI: 0.68 to 0.90 and FE OR: 0.76; 95% CI: 0.62 to 0.92, respectively). However, for those studies involving East Asians, the RE pooled OR was not significant. The dominant model produced nonsignificant associations (P>0.05).

Regarding the relationship between the T768C polymorphism and hypertension, the heterogeneity between studies was not significant (P=0.39; I2=4%), and the analysis did not detect an association for the allele contrast T versus C (FE OR: 0.92; 95% CI: 0.82 to 1.02). However, there is a trend for association in whites (FE OR: 0.84; 95% CI: 0.70 to 1.01). The recessive and dominant models produced nonsignificant associations overall in whites and East Asians.

Finally, in no case (ie, overall or in whites) was a statistically significant association between the G23T polymorphism and the risk of developing hypertension for the contrasts under investigation found. In addition, there is no significant heterogeneity among studies (P=0.17; I2=44%). The sensitivity analysis did not alter the pattern of results in all of the polymorphisms and contrasts.

Potential Bias
None of the studies included in the meta-analysis stated that genotyping was performed blinded to clinical status. In cumulative meta-analysis for the recessive model, only 4b/a polymorphism showed evidence of an association as evidence accumulates (see Figure 3). In recursive cumulative meta-analysis for the recessive model, the relative change in OR for the G894T polymorphism fluctuated around the value of OR=1.0. The relative change in OR for 4b/a polymorphism showed a downward trend as evidence accumulates, whereas for T(–786)C and G23T it showed an increase (see Figure 4).


Figure 3
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  		Figure 3. Cumulative meta-analysis: the RE-pooled OR with the corresponding 95% CI at the end of each year; information step is shown.


Figure 4
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  		Figure 4. Recursive cumulative meta-analysis: the relative change in RE-pooled OR in each information step (OR in next year/OR in current year) is shown.

The Egger test and the Begg–Mazumdar test for the recessive model indicated that there is no differential magnitude of effect in large versus small studies for each polymorphism being investigated (P>0.10); however, for 4b/a polymorphism there is indication of an effect: the Begg–Mazumdar test showed a significant result (P=0.03), whereas the Egger test showed a marginal significance (P=0.09; see Figure 5).


Figure 5
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  		Figure 5. Funnel plot of SE against the log OR for 4b/a gene polymorphism.


*    Discussion
up arrowTop
 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 up arrowResults
 *Discussion
down arrowReferences
 
This meta-analysis examined the eNOS G894T, 4a/b, T786C, and G23T polymorphisms and their relationship to susceptibility for hypertension. The strength of the present analysis was based on the accumulation of published data giving greater information to detect significant differences. In the present study, the effect of allele frequency and the effects of the dominant and recessive models were estimated. In addition, the consistency of genetic effects across populations from different ethnicities was investigated. Main and subgroup analyses in whites and East Asians for the allele contrast; the recessive and dominant models for G894T, T786C, and G23T polymorphisms have produced nonsignificant results; and heterogeneity was ranging from none to high. There was consistency of genetic effects across different ethnicities, because they were not differentiated from the overall effect. However, the results for G23T were derived from a very small number of studies. Overall and in whites, significant results and lack of heterogeneity were observed for polymorphism 4b/a under a recessive model for allele b, conferring protection. In contrast, the association was not significant in East Asians, but the number of studies was small to draw safe conclusions. In all of the polymorphisms under investigation, the ORs for the allelic and dominant models were estimated based on fewer studies than the recessive model.

The overall lack of association between G894T, T786C, and G23T polymorphisms and hypertension and the discrepancy of results between whites and East Asians for 4b/a might be because of other unidentified functional mutations that exist in the eNOS gene that affect the susceptibility to hypertension.26 It has been reported that the polymorphisms might be in linkage disequilibrium, and interaction of the polymorphisms within haplotypes can be a major determinant of disease susceptibility rather than the individual polymorphism. Thus, individual eNOS genotypes might not be reliable markers of risk for developing hypertension. Then, a meta-analysis of eNOS haplotypes, combinations of polymorphisms, may provide more reliable information than single polymorphisms.54 Genome scans and genome search meta-analysis55 have provided evidence for genetic linkage in hypertension; however, none of the loci with suggestive linkage included the eNOS gene. Discrepant results could be because of other loci that may have an effect on the genetic susceptibility to hypertension that is also in linkage disequilibrium with the examined polymorphisms of eNOS gene. Although there is a strong genetic contribution to hypertension,4 other complex mechanisms1 and environmental interactions (eg, smoking) may play a role in the pathogenesis of hypertension.56 However, a meta-analysis of eNOS and ischemic heart disease involving >23 000 subjects57 showed that individuals homozygous for the Asp298 and intron-4a alleles of eNOS are at moderately increased risk of ischemic heart disease.

Sampling variability and stratification in case–control study design can be a possible confounding factor on the role of genetic markers. In addition, misclassification in case–control studies might exist, because selection of participants can be based on a limited number of blood pressure measurements. The strict selection criteria ensure a clear case and control definition for meta-analysis, because if the possibility for a case to be considered as a control is minimized, then, the estimation of risk is unbiased. Prevalence of essential hypertension rises gradually with age, and it is maximized in elderly individuals.58 In addition, age is independently associated with increased rates of hypertension. Thus, the absence of high blood pressure in young patients does not exclude the possibility of developing hypertension later. In many studies, young individuals were frequently included as controls. Therefore, a control group may include cases that are still at risk for developing hypertension. In the meta-analysis presented here, stratification because of ethnicity was taken into account, and the cases and controls were well defined with similar inclusion criteria, although they unavoidably cover a wide spectrum of disease in terms of duration, demographics, and other manifestations.

Perspectives
The present meta-analysis supported an association between hypertension and eNOS 4b/a polymorphism: the allele b under a recessive model provided evidence of protection, mainly when analysis was confined to whites. There was no detectable influence of the G894T, T786C, and G23T polymorphisms. The results of the present meta-analysis should be interpreted with some degree of caution, because the numbers of studies and participants were relatively small. Wide genome scans and family-based tests for association, together with large case–control studies that investigate combinations of the polymorphisms59 and gene–environment interaction,60 should be performed to make conclusive claims about the genetics of hypertension.


*    Acknowledgments
 
Disclosures

None.


*    Footnotes
 
*References 1, 24–28, 30, 32, 33, 35, 38–42, 44, 46, 48–53. Back

{dagger}References 1, 4, 25, 27, 28, 30, 31, 33, 35–40, 50, 53. Back

{ddagger}References 1, 4, 23, 24, 27, 30, 32–36, 38, 39, 42, 43, 46, 51–53. Back

§References 25, 26, 28, 29, 31, 41, 44, 45, 47, 49, 50. Back

Received April 9, 2006; first decision May 4, 2006; accepted July 17, 2006.


*    References
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 up arrowAbstract
 up arrowIntroduction
 up arrowMethods
 up arrowResults
 up arrowDiscussion
 *References
 

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