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The C825T Polymorphism of the G-Protein β3 Subunit Gene and Its Association with Hypertension and Stroke: An Updated Meta-Analysis

  • Lu Guo ,

    Contributed equally to this work with: Lu Guo, Li-Li Zhang, Bo Zheng

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

  • Li-Li Zhang ,

    Contributed equally to this work with: Lu Guo, Li-Li Zhang, Bo Zheng

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

  • Bo Zheng ,

    Contributed equally to this work with: Lu Guo, Li-Li Zhang, Bo Zheng

    Affiliation Department of Neurology, Southwest Hospital, Third Military Medical University, Shapingba District, Chongqing, PR China

  • Yun Liu,

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

  • Xiao-Jie Cao,

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

  • Yan Pi,

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

  • Bing-Hu Li,

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

  • Jing-Cheng Li

    lijingcheng11@yahoo.com.cn

    Affiliation Department of Neurology, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Yuzhong District, Chongqing, PR China

The C825T Polymorphism of the G-Protein β3 Subunit Gene and Its Association with Hypertension and Stroke: An Updated Meta-Analysis

  • Lu Guo, 
  • Li-Li Zhang, 
  • Bo Zheng, 
  • Yun Liu, 
  • Xiao-Jie Cao, 
  • Yan Pi, 
  • Bing-Hu Li, 
  • Jing-Cheng Li
PLOS
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Abstract

Objective

Several epidemiological studies have evaluated the association between the GNB3 C825T polymorphism and hypertension or stroke. The results of these studies were inconsistent; therefore, we performed a meta-analysis to clarify these discrepancies.

Methods

We systematically searched the PubMed, Embase, Web of Science, CNKI, and CBM databases, and manually searched reference lists of relevant papers, meeting abstracts, and relevant journals. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for dominant, recessive, and allelic models. A fixed or random effects model was separately adopted depending on study heterogeneity. Subgroup and sensitivity analyses were performed to detect study heterogeneity and examine result stability, respectively. Publication bias was tested using funnel plots, the Egger's regression test, and Begg's test.

Results

We screened 66 studies regarding hypertension and eight concerning stroke. A combined analysis showed that only the allelic model found a marginal association with hypertension (OR = 1.07, 95% CI = 1.01–1.13) and female gender (OR = 1.11, 95% CI = 0.99–1.24). However, no comparison models found an association with stroke (allelic model: OR = 1.11, 95% CI = 0.94–1.32; dominant model: OR = 1.16, 95% CI = 0.92–1.48; and recessive model: OR = 1.05, 95% CI = 0.97–1.14). Sensitivity analysis suggested that all models did not yield a relationship to hypertension or stroke among Asians. Besides, there was a lack of statistical association with hypertension in Caucasians, which maybe due to a small sample size. When we restricted the included studies to normal populations according to the Hardy–Weinberg equilibrium, no association was found.

Conclusions

There was no evidence indicating that the 825T allele or TT genotype was associated with hypertension or stroke in Asians or hypertension in Caucasians. However, further studies regarding Africans and other ethnicities are needed to identify further correlations.

Introduction

Hypertension is a major risk factor of stroke, cardiovascular disease, and end-stage renal disease and affects about 1 billion adults worldwide, including 3.8 million in Taiwan and 160 million in China [1]. Stroke is a primary contributor to long-term adult disability and the third most common cause of death in developed countries [2], [3]. Blood pressure-lowering therapies are viewed as protective measures against the risk of hypertension and stroke, but both genetic and lifestyle factors are likely involved in the development of these conditions.

Guanine nucleotide-binding proteins (G proteins) are key determinants of specific and temporal characteristics of many signaling processes and are expressed in all cells of the human body to primarily transduce signals from the cell surface into a cellular response. G proteins consist of α, β, and γ subunits and different genes encode for 18 α subunits, 5 β subunits, and 12 γ subunits, which enable the formation of highly variable heterotrimers [4]. Activation of a G protein-coupled receptor results in an exchange of guanosine triphosphate for guanosine diphosphate followed by dissociation of the α subunit from the βγ complex. Different α subunits can then regulate a large variety of intracellular signaling cascades. The α subunit and βγ complex then reassemble as a heterotrimer available for a new activation cycle [5]. Reportedly, the α, β, γ subunit composition of G proteins determine the receptor and effector specificities of particular heterotrimers. Thus, alterations in G protein signaling can cause multiple disorders and it is likely that functionally important genetic polymorphisms in genes that encode human G protein subunits can cause or contribute to various disease phenotypes.

The G protein beta polypeptide 3 (GNB3) gene encodes the Gβ3 subunit of heterotrimeric G proteins and is located on chromosome 12p13 and comprises 11 exons and 10 introns. A polymorphism (C825T, rs5433) was found to be associated with a shortened splice variant of the Gβ3 protein that gives rise to enhanced signal transduction via pertussis toxin-sensitive G proteins [6], [7]. The C825T polymorphism located in exon 10 is in close linkage disequilibrium with the A(-350)G promoter single nucleotide polymorphism (SNP) and the C1429T SNP and can serve as a marker for allele-specific GNB3 expression. However, differential G protein activities associated with the C825T SNP did not result from different transcript amounts associated with specific GNB3 genotypes [8].

Several epidemiological studies have shown an association between the GNB3 825T allele and other features of metabolic syndrome, including obesity, insulin resistance, changes in autonomic nervous function, and dyslipidemia. This polymorphism has also been identified in hypertension, stroke, Alzheimer’s disease, sudden death, tumor progression, and as a genetic marker for drug responses to diuretics, antidepressants, and the antihypertension medications sildenafil, clonidine, and sibutramine [9][12].

Recently, many groups have investigated the relationship between the GNB3 C825T polymorphism and hypertension or stroke; however, the results have been inconclusive. Therefore, we designed the present meta-analysis to better clarify the association between the GNB3 C825T polymorphism and hypertension or stroke.

Materials and Methods

Literature Search

This meta-analysis followed the PRISMA (preferred reporting items for systematic reviews and meta-analyses) criteria [13]. We comprehensively searched for related papers in the following electronic databases: PubMed (up to Nov 2012), Embase (1996 to Nov 2012), Web of Science (2003 to Nov 2012), CBM (China Biology Medicine, 1978 to Jul 2012) and CNKI (China National Knowledge Infrastructure, 1999 to Nov 2012) using various keywords, including “hypertension,” “stroke,” “cerebral hemorrhage,” “cerebrovascular disorder,” “cerebrovascular disease,” “mutation,” “variant,” “polymorphism,” “ischemic stroke,” “GNB3,” “G protein beta,” and “G-beta.” Then, we manually searched the relevant journals and co-authors listed in the included studies to find additional studies. Reference lists of all retrieved publications were also checked for missing information. Meeting abstracts, which were previously shown to influence meta-analytical results [14], were also scrutinized. All relevant articles were initially scanned on the basis of title, keywords, and abstract. If this was not possible, the full text was obtained for further evaluation. The literature retrieval was performed independently by three investigators (LG, LLZ, and BZ) and discrepancies were resolved by reaching a consensus among the investigators. If a consensus could not be established, a fourth reviewer (JCL) was consulted to resolve the discrepancy. The last database searches were performed on November 10, 2012.

Inclusion Criteria

Studies were screened that met the following criteria: (1) population-based or hospital-based case-control studies regarding the relationship between the GNB3 C825T polymorphism and essential hypertension or stroke; (2) sufficient data on genotypic and allelic frequencies to determine an odds ratio (OR) with a 95% confidence interval (CI). If multiple publications reported the same or overlapping data, the most recent or complete study or the largest population was included in this meta-analysis as described by Little et al. [15]; (3) to avoid local literature bias, publications in both Chinese and English were considered [16]; (4) studies with related clinical characteristics were limited to those using human subjects; (5) articles regarding cases compounded with other diseases, such as diabetes mellitus and myocardial infarction, were also included; and (6) if patient blood pressure was measured casually or ambulatory (24 h), the latter were used. Hypertension was defined as mean casual blood pressure ≥140/90 mmHg or mean ambulatory blood pressure >134/79 mmHg.

Data Extraction

Data were independently extracted from each study by three investigators (LG, LLZ, and BZ) following the above-mentioned inclusion criteria. Discordance was resolved by discussion or another reviewer (JCL) was consulted. The following data were collected from each of the selected studies: surname of the first author, year of publication, country of origin, population ethnicity, source of control, T allele frequency in controls, genotype variance in the cases and controls, and the Hardy–Weinberg equilibrium (HWE) using the χ2 test. A p-value of <0.05 for the HWE was considered statistically significant.

Quality Score Assessment

The quality of each selected study was assessed independently by the same three investigators according to the Newcastle–Ottawa Scale (NOS) (www.ohri.ca/programs/clinical_epidemiology/oxford.asp). Scores were based on the selection, comparability, and exposure (case-control studies) or outcome (cohort studies) of the studies. To avoid selection bias, studies of poor quality were not rejected in this meta-analysis.

Statistical Analysis

All statistical analyses were conducted using Stata statistical software ver. 11.0 (Stats Corp., College Station, TX, USA) and Review Manager ver. 5.0 (The Cochrane Collaboration, Oxford, UK). All tests were two-sided and a p-value <0.05 was considered statistically significant. The strength of association of the GNB3 C825T polymorphism with hypertension or stroke was measured by calculating summary ORs with corresponding 95% CIs for the dominant model (TT+CT vs. CC), recessive model (TT vs. CT+CC), and allelic model (T allele vs. C allele), respectively.

Heterogeneity between the studies was analyzed using the Cochran’s Q test and the I2 statistic (range, 0–100%) [17], [18]. If the results of the Q test was p<0.1 and the measure of I2 was >50%, indicating significant heterogeneity between studies, the ORs were pooled using a fixed effects Mantel–Haenszel method [19], otherwise the DerSimonian and Laird random effects model was adopted [20], [21]. A Galbraith plot was employed to detect potential sources of heterogeneity [22]. The pooled ORs were recalculated after removing outlier studies identified by the Galbraith plots. To further detect heterogeneity, subgroup analyses were performed using the status of the HWE (yes or no) or the control source.

Sensitivity analysis was conducted by limiting the meta-analysis to high quality studies (NOS score ≥8). We also performed the analyses a second time by limiting the studies according to the HWE and excluding those that included myocardial infarction, obesity, or diabetes mellitus in the cases or controls. Sensitivity analysis was performed to identify alterations in the overall significance of the estimate.

Cumulative meta-analysis was performed to identify the influence of the first published study on the subsequent publications concerning the relationship between the GNB3 C825T polymorphism and hypertension, and to estimate the combined estimate over time [23].

Publication bias was assessed using the Egger's regression test and Begg's test. The Egger’s test detects funnel plot asymmetry by determining whether the intercept deviates significantly from zero in a regression of the standardized effect estimates against their precision [24], [25]. These methods were based on plotting the estimate (logOR) against the corresponding standard error (SE).

Results

Study Selection and Characteristics

The present study met the PRISMA statement requirements (Appendix S1). Through comprehensive retrieval and evaluation, 66 studies (20,782 cases and 26,141 controls) regarding hypertension and eight studies (3,427 cases and 3,948 controls) regarding stroke met the inclusion criteria and were included in the final meta-analysis. Details of the included studies are presented in Tables 1 and 2 and the selection process is shown in Figure 1.

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Figure 1. A flow diagram of the literature search for associations between the GNB3 C825T polymorphism and hypertension (A) or stroke (B).

https://doi.org/10.1371/journal.pone.0065863.g001

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Table 1. The main characteristics of included studies regarding the association between the GNB3 C825T polymorphism and hypertension.

https://doi.org/10.1371/journal.pone.0065863.t001

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Table 2. The main characteristics of the included studies regarding association between the GNB3 C825T polymorphism and stroke.

https://doi.org/10.1371/journal.pone.0065863.t002

Of the 66 studies, eight compared males and females to assess an association between the GNB3 C825T polymorphism and hypertension. Among these articles, three publications [26][28] contained more than one independent population, and thus, we considered them as different studies that should be counted twice. Two studies [29], [30], which did not supply all of the required information regarding case or control genotypes were excluded from this meta-analysis. We only retrieved information on hypertensive patients and controls without diabetes mellitus from three studies [31][33]. Five studies [11], [12], [34][36] regarding the association of the GNB3 C825T polymorphism and ischemic stroke were identified while one [37] was regarding cerebral hemorrhage and the other two [38], [39] included ischemic stroke or cerebral hemorrhage cases.

All of the included studies were case-controlled in design. The main characteristics of the included studies are summarized in Tables 13. In all of the included studies, genotyping was analyzed via polymerase chain reaction and restriction fragment length polymorphisms. Stroke cases were evaluated by strict neurological examination: computed tomography, nuclear magnetic resonance imaging or both.

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Table 3. The association between the GNB3 C825T polymorphism and hypertension among males and females.

https://doi.org/10.1371/journal.pone.0065863.t003

Quantitative Synthesis

All models concerning the association of the GNB3 C825T polymorphism and hypertension or stroke were identified using the random effects model for I2>50%, which suggested significant heterogeneity. However, in most of the models, I2 was ≥70%, which indicated high heterogeneity [40], thus we pooled the ORs because of the significant results. The main results of this meta-analysis are presented in Tables 4 and 5. A significant overall association between the GNB3 C825T polymorphism and the risk of hypertension was only detected in the allelic model (OR = 1.07, 95% CI = 1.01–1.13). No evidence of significance was identified in the dominant model (OR = 1.08, 95% CI = 0.98–1.81) or the recessive model (OR = 1.05, 95% CI = 0.97–1.14). However, none of the comparison models found an association between the GNB3 C825T polymorphism and stroke (allelic model: OR = 1.11, 95% CI = 0.94–1.32; dominant model: OR = 1.16, 95% CI = 0.92–1.48; and recessive model: OR = 1.05, 95% CI = 0.97–1.14, respectively) (Figure 2). After excluding the outlier studies identified by the Galbraith plots, heterogeneity was effectively nonexistent or decreased and the pooled ORs were similar to those when the outlier studies regarding stroke cases were included; however, the association to hypertension was significant using the dominant model (OR = 1.05, 95% CI = 1.00–1.11). These results suggested that carriers of the T allele or TT genotype may have a higher risk of hypertension than non-carriers; however, the GNB3 C825T polymorphism was not a risk factor for stroke.

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Figure 2. A forest plot for (A) the allelic model (T allele vs. C allele), (B) the dominant model (GG+GA vs. AA), and (C) the recessive model (TT vs. CT+CC).

Random effects models were used with I2 values of 81, 76, and 71%. No evidence of association between the GNB3 C825T polymorphism and stroke were detected in the allelic model (OR = 1.11, 95% CI = 0.94–1.32), dominant model (OR = 1.16, 95% CI = 0.92–1.48), or recessive model (OR = 1.08, 95% CI = 0.84–1.38).

https://doi.org/10.1371/journal.pone.0065863.g002

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Table 4. The main results of meta-analysis of the association between the GNB3 C825T polymorphism and hypertension.

https://doi.org/10.1371/journal.pone.0065863.t004

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Table 5. The main results of meta-analysis of association between the GNB3 C825T polymorphism and stroke.

https://doi.org/10.1371/journal.pone.0065863.t005

We also performed a meta-analysis to detect any association between males and females; however, only the recessive model (OR = 1.35, 95% CI = 1.07) identified a risk of hypertension among females.

In the cumulative meta-analysis by year of publication, the ORs and 95% CIs became more stable (Figure 3). Study by Benjafield et al. [41] was the first publication to report a significant association between the GNB3 C825T polymorphism and hypertension and triggered the identification of subsequent related studies that tried to replicate the initial results. In the allelic, dominant, and recessive models, the study by Benjafield et al. [41] was the most influential and made the overall estimation more significant in the present cumulative meta-analysis. After the study by Dou et al. [42] was included, the overall estimation became more accurate for the larger sample size.

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Figure 3. A cumulative plot by publication year for (A) the allelic model, (B) the dominant model, and (C) the recessive model.

The ORs and associated 95% CIs became more stable over time. The study by Benjafield et al. [41] was the first report to show a significant association between the GNB3 C825T polymorphism and the risk of hypertension, and this study likely influenced the overall estimation.

https://doi.org/10.1371/journal.pone.0065863.g003

Subgroup Analysis

To further clarify heterogeneity among the studies, we performed subgroup analysis. Regarding the hypertension study population, the status of the HWE and the source of control had a critical role in heterogeneity (detailed data is presented in Table 4). Interestingly, only the allelic model, which was not consistent with the HWE, yielded a marginally significant risk of hypertension (OR = 1.18, 95% CI = 1.06–1.33), but no evidence of an association was found in the source of the control studies (controls were population-based or hospital-based).

Only one publication regarding Caucasians was screened in an analysis of the association between the GNB3 C825T polymorphism and stroke, and all of the control sources were population-based, thus we did not perform subgroup analysis by ethnicity. Similarly, there were only two studies regarding an African population and hypertension, further indicating that subgroup analysis by ethnicity was to be avoided.

Sensitivity Analysis

To further strengthen the confidence of the results of this meta-analysis, sensitivity analysis was conducted by limiting the included studies with NOS scores ≥8 or restricted analysis on hypertension populations according to the HWE and without other diseases or only included Asian and/or Caucasian populations. All comparative models found no association with hypertension, which suggested that the T allele or TT genotype may not be a risk factor for hypertension (detailed data is presented in Table 4). Importantly, the sensitivity analysis results were slightly out of agreement with those of the initial analysis; therefore, the results should be interpreted cautiously.

As to the association of stroke, when we restricted the analyses by limiting the included studies according to the HWE, the recalculated pooled OR values did not alter the initial results, suggesting that the TT genotype or T allele was not a risk factor of stroke (detailed data are presented in Table 5). Similarly, when we evaluated the ischemic stroke population or Asian population, no evidence of statistical association was obtained.

Publication Bias

Funnel plots were constructed and the Egger's test was performed to assess publication bias of the studies. Funnel plots should be symmetrical when no publication bias exists (Figures 4 and 5). Regarding the hypertension population, only the recessive model displayed an asymmetric funnel plot, while the Egger's regression test confirmed the presence of moderate publication bias (p = 0.043). No statistical evidence of publication bias was identified regarding the GNB3 C825T polymorphism and its association with stroke.

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Figure 4. Funnel plots for the GNB3 C825T polymorphism and its association with hypertension.

(A) the allelic model (T allele vs. C allele, p = 0.150), (B) the dominant model (TT+CT vs. CC, p = 0.565), and (C) the recessive model (TT vs. CT+CC, p = 0.043). The funnel plots should be symmetrical when no publication bias occurs; however, the funnel plot of the recessive model was asymmetrical (p = 0.043), suggesting publication bias. The other two were symmetrical (p = 0.150 and 0.565, respectively). SE, standard error; OR, odds ratio.

https://doi.org/10.1371/journal.pone.0065863.g004

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Figure 5. Funnel plots for the GNB3 C825T polymorphism and its association with stroke.

(A) the allelic model (T allele vs. C allele, p = 0.145), (B) the dominant model (TT+CT vs. CC, p = 0.281), and (C) the recessive model (TT vs. CT+CC, p = 0.116). The funnel plots should be symmetrical when no publication bias occurs. No evidence of publication bias was detected in the three models. SE, standard error; OR, odds ratio.

https://doi.org/10.1371/journal.pone.0065863.g005

Discussion

Stroke is a significant event that leads to increased mortality and morbidity and hypertensive individuals reportedly have a greater incidence of stroke than normotensive individuals. Genetic factors as well as obesity, high sodium intake, physical inactivity, low potassium diets, and alcohol consumption contribute to the occurrence of hypertension, and essential hypertension status may play a role in the etiology of stroke either through effects on blood pressure levels or through separate pathways [11], [43]. The established relationship between hypertension and stroke suggested that these disorders may have at least some genes in common. Recently, several studies reported that the GNB3 825T polymorphism was associated with an increased risk of hypertension, obesity, metabolic syndrome, atherosclerosis, and diabetes mellitus. Besides, the GNB3 825T allele was found to significantly increase the risk of clinical ischemic stroke in Caucasians, but not subclinical cerebral infarct [12], [44]. However, the present meta-analysis was designed to confirm the association between the GNB3 C825T polymorphism and essential hypertension or stroke.

Overall, our meta-analytical results showed that the GNB3 825T allele had a weak association with essential hypertension. However, after we restricted the studies according to the HWE and included only those without other diseases, such as diabetes and myocardial infarction, all of the compared models failed to identify an association between the GNB3 825T allele and hypertension. Similarly, when we performed sensitivity analysis with the inclusion criteria of “Asian” or “Caucasian,” no evidence of an association was obtained, which might be due to heterogeneity between the studies. Besides, the funnel plot was asymmetric in the recessive model for p = 0.043, so publication bias must also be considered. In addition, our results were consistent with those reported in previous studies [45], [46], but were slightly less discrepant with others [47], which might have resulted from the greater number of studies included in our meta-analysis. However, there were only two studies concerning an African population, thus a larger sample size is needed to further address the relationship between the GNB3 C825T polymorphism and essential hypertension in Africans.

Interestingly, the GNB3 C825T polymorphism was not associated with stroke. When we retrieved studies on ischemic stroke cases or limited the studies according to the HWE or an NOS score of ≥8, similar results were obtained, suggesting that our initial results were reliable and in line with most of the included studies. But, considering that most of the included stroke patients were Asian, our results cannot be directly used to extrapolate a correlation between the GNB3 c825T polymorphism and stroke in Caucasians, Africans, or other ethnicities.

In addition, we tested the T allele frequency in controls (hypertensive population) (Table 1), and found that there was statistical significance between Asian, Caucasian, and African groups (p = 0.0001). This result was in agreement with a previous study [48] that reported varied frequencies of the T allele among different ethnic groups, in which the highest rate occurred in Africans (T = 79%), followed by Asians (T = 46%), and then Caucasians (T = 33%). However, no statistical significance was found between males and females (p = 0.337). Therefore, it is likely that a higher T allele frequency is not necessarily indicative of an increased occurrence of hypertension.

Generally, the GNB3 825T allele was only slightly associated with an increased risk of essential hypertension compared to non-carriers. But, the GNB3 C825T polymorphism failed to contribute to the risk of stroke, thus it was clear that the polymorphism contributed to hypertension and stroke differently. Therefore, gene-gene interactions should be taken into consideration. Until now, >500 candidate genes for hypertension have been suggested from a variety of genetic studies, and this number continues to increase [1], but not all of these genes were associated with an increased risk of stroke. Distribution of the C825T genotypes varies greatly in different ethnicities and the frequency of the T allele is highest in Africans, lowest in Caucasians, and intermediate in Asians. However, the CC genotype is rare in Africans and the distribution of East Asian genotypes is roughly 25% TT, 50% TC, and 25% CC [4]. Thus, individuals from different ethnicities may develop cardiovascular disorders, such as hypertension or stroke, which more or less differ in pathogenesis/pathophysiology of a given disorder due to different genetic backgrounds. In our meta-analysis, individual studies on Africans, Asians, and other ethnicities were deficient; therefore, additional evidence regarding the correlation of the GNB3 C825T polymorphism with hypertension or stroke is required. The interactions between environmental and genetic factors constitute a key issue in the pathogenesis of hypertension and stroke. Most of the susceptibility genes for common diseases such as hypertension do not have a strong primary etiological role in disease predisposition, but rather code response elements to exogenous environmental factors. Therefore, a genetic marker may have only a modest affect on calculating risk in individuals who minimize exposure to environmental factors, but a major effect in individuals exposed to high-risk environment factors [49]. Young et al. [50] reported that latitude was an ecological factor that affected blood pressure via temperature and humidity. Likewise, GNB3 presents a number of functional alleles that influence hypertension susceptibility. Therefore, those populations that have a high prevalence of the GNB3 825T allele also have a higher prevalence of heat-adapted alleles at other SNPs. Physical inactivity, increased body mass, obesity, and smoking may also influence the risk of hypertension and stroke differently.

In addition to race, gender also seems to be an important risk factor for adverse cardiovascular events, such as hypertension and stroke. Suwazono et al. [51] reported that the 825T allele was an independent risk factor for hypertension in Japanese females, whereas Beige et al. [52] found that the T allele in males was associated with higher blood pressure. In our analysis, the GNB3 TT genotype was marginally associated with hypertension among females, and no evidence of an association with hypertension was found in males. In the cumulative meta-analysis, three models showed evidence of a non-association between GNB3 alleles and hypertension or stroke. Two primary causes may account for this discrepancy. First, females have dominant parasympathetic and subordinate sympathetic activities compared to males, and, secondly, estrogen plays an important role in gender-related differences in the autonomic nervous system [51]. Thus, it seems that different automatic functions between genders altered the association of the GNB3 825T allele with hypertension.

Some limitations of the present meta-analysis should be considered. Firstly, all of the included studies mostly involved Caucasians and Asians, thus studies on other ethnic populations are needed. Secondly, all of the included studies were case-controlled and all of the cases involved survivors of hypertension and stroke. Finally, the number of stroke cases were limited and had relatively weak statistical power to detect potential risks of the GNB3 C825T polymorphism. Thus, more population-based studies with large sample sizes are required. Despite these limitations, this meta-analysis was designed to overcome the limitations of individual studies, thus the results should be more reliable. Since the GNB3 C825T polymorphism appears to be a useful marker to predict the relative risk of diseases, such as hypertension and stroke, this meta-analysis is better suited in a preventive aspect to identify certain genotypes that will be most likely to benefit from pharmacological interventions.

In summary, the overall analysis of available evidence suggested that the GNB3 825T allele may be a good indicator of hypertension; however, it had no association with hypertension in Asians and Caucasians and there was lack of evidence to support an association with stroke in Asians. Therefore, multiethnic studies with much larger sample-sizes are required to better evaluate the association between the GNB3 C825T polymorphism and hypertension or stroke.

Supporting Information

Author Contributions

Conceived and designed the experiments: LG LLZ JCL. Analyzed the data: LG JCL LLZ. Wrote the paper: LG BZ. Literature search: LLZ YL XJC YP BHL. Title and abstract screening: XJC YL YP. Full text screening: LG LLZ BZ.

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