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Heterogeneous Effect of Two Selectin Gene Polymorphisms on Coronary Artery Disease Risk: A Meta-Analysis

  • Zhijun Wu,

    Affiliation Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

  • Yuqing Lou,

    Affiliation Department of Pulmonary, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China

  • Lin Lu,

    Affiliation Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

  • Yan Liu,

    Affiliation Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

  • Qiujing Chen,

    Affiliation Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

  • Xin Chen,

    Affiliation Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

  • Wei Jin

    jinwei_ivy@126.com

    Affiliation Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Heterogeneous Effect of Two Selectin Gene Polymorphisms on Coronary Artery Disease Risk: A Meta-Analysis

  • Zhijun Wu, 
  • Yuqing Lou, 
  • Lin Lu, 
  • Yan Liu, 
  • Qiujing Chen, 
  • Xin Chen, 
  • Wei Jin
PLOS
x

Correction

28 Feb 2014: The PLOS ONE Staff (2014) Correction: Heterogeneous Effect of Two Selectin Gene Polymorphisms on Coronary Artery Disease Risk: A Meta-Analysis. PLOS ONE 9(2): e91648. https://doi.org/10.1371/journal.pone.0091648 View correction

Abstract

Background

The selectins play important roles in the inflammatory process of coronary artery disease (CAD) and myocardial infarction (MI). Previous studies have shown ambiguous findings regarding a possible association between the selectin genes and CAD. The E-selectin Ser128Arg polymorphism and the P-selectin Thr715Pro polymorphism have been investigated widely but with inconsistent results. We performed a comprehensive meta-analysis to shed light on this issue.

Methods

Data were extracted by searches of MEDLINE, Embase, CNKI, Wanfang, Google Scholar, PORTA, GeNii, CiNii, J-STAGE, Nurimedia and Koreanstudies Information Service System [Kiss] up to October 2013, in which 10 studies on the Ser128Arg polymorphism with 3369 cases and 2577 controls and 10 studies on the Thr715Pro polymorphism with 5886 cases and 18345 controls. A random-effects model was used to calculate the combined odds ratios. The between-study heterogeneity and publication bias were addressed.

Results

The 128Arg carriers had a significant increased risk of CAD (allele comparison: P = 0.02, OR = 1.33, 95%CI 1.04–1.69, Pheterogeneity = 0.01); The 715Pro conferred a non-significant risk reduction relative to the 715Thr (allele comparison: P = 0.40, OR = 0.94, 95%CI 0.82–1.08, Pheterogeneity = 0.03).Subgroup analyses demonstrated that the 128Arg carriers had a significant increased risk of CAD among Asians (allele comparison: P = 0.001, OR = 2.07, 95%CI 1.33–3.24, Pheterogeneity = 0.77) but not among Caucasians (allele comparison: P = 0.33, OR = 1.13, 95%CI 0.88–1.45, Pheterogeneity = 0.08). Carrier status for the 715Pro was significantly associated with reduced risk of MI (allele comparison: P = 0.04, OR =  0.81, 95%CI 0.67–0.99, Pheterogeneity = 0.14). The asymmetric funnel plot and the Egger's test (P = 0.041) suggested the presence of publication bias for the Ser128Arg polymorphism.

Conclusion

Our results suggested there is an increase in the risk of CAD conferred by the Ser128Arg polymorphism and the thr715Pro polymorphism may be a protective factor of MI.

Introduction

It has been known for years that coronary artery disease (CAD) and myocardial infarction (MI) are the main killers in the world. The pathogenesis of CAD and MI involves important inflammatory components [1], [2]. One of the critical steps of inflammatory processes is the migration of leukocytes from the vessel wall to atherosclerosis lesion[3], which is strictly regulated by a variety of cell adhesion molecules and leukocyte-activating factors[4]. Leukocytes is captured from the blood stream and then rolled along the endothelial cell surface. The process is mediated by the selectins, a special family of three cell adhesion molecules: P-selectin, E-selectin and L-selectin. The three selectins have fundamental differences in their distribution, activation and expression. E-selectin is only expressed on the activated endothelium and recruits polymorphonuclear leukocytes, myeloid cells and T-lymphocytes to the inflammation sites[5]; P-selectin is expressed on the endothelial cells as well as platelets and instantly migrates to the plasma membrane when exposed to some free radicals, nitric oxide synthase inhibitors and other mediators[6]; L selectin is expressed on most types of leukocytes, as well as some neutrophils and myeloid cells [5] and serves as a homing receptor for lymphocytes to peripheral lymph nodes. L-selectin recruits cells to inflammation lesion like E-selectin.

Although the in vivo study has suggested that E-selectin and P-selectin exert similar effects of leukocyte adhesion on atherosclerosis lesions. The exact roles of E-selectin and P-selectin remain unclear. Estimates have placed genetic predisposition to be responsible for 40–60% of susceptibility to CAD [2], [7][9]. The single nuclear polymorphisms (SNPs) of adhesion molecules act independently of known risk factors of severe atherosclerosis [10]. Several polymorphisms of the selectin genes have been mentioned to contribute to the CAD incidence. For instance, an adenine to cytosine substitution at cDNA position 561, resulting in an amino acid exchange from serine (Ser) to arginine (Arg), in the epidermal growth factor (EGF) -like domain of E-selectin has profound effects on atherosclerosis. In additional, a Thr715Pro polymorphism located in front of the transmembrane domain of the P-selectin gene is associated with the susceptibility to CAD and MI. These two polymorphisms were the most investigated, but with conflicting results. It should be considered that the sample size in the previous studies was relatively small. Hence, the studies had low statistical power to detect modest associations of genotype with CAD. To shed some light on this divergence and maximize statistical power, we sought to evaluate the correlation of these two polymorphisms of the selectin genes with CAD by performing a comprehensive meta-analysis of available individual studies. Furthermore, the between-study heterogeneity and the publication bias were addressed.

Materials and Methods

Data Source and Search Strategy

We followed the guidelines of the 2009 preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement [11] when performed the literature search (Checklist S1). The search strategy was conducted by searching from PubMed/MEDLINE, Embase, China Nation Knowledge Infrastructure (CNKI) Platform and Wanfang electronic databases up to October 2013. In addition, five Japanese electronic databases (PORTA, GeNii, CiNii, J-STAGE and Google Scholar [Japanese]) as well as three Korean electronic databases (Nurimedia, Koreanstudies Information Service System [Kiss] and Google Scholar [Korean]) were also retrieved. The following medical subject heading (MeSH) terms and key words were used in the computer-based searches: ‘Ser128Arg’ or ‘A561C’, ‘E-selectin’ or ‘SELE’, ‘Thr715Pro’ or ‘rs6136’, ‘P-selectin’ or ‘SELP’ and ‘coronary artery disease’ or ‘acute coronary syndrome’ or ‘myocardial infarction’ or ‘atherosclerosis ’. We scanned the titles and abstracts of potentially appropriate articles followed by determining whether these studies conformed to our inclusion criteria. If the suitability of a study was uncertain, we scrutinized the full text for further estimation. We identified additional studies by screening the bibliographies of relevant studies and reviews. The related search function of Pubmed was also used.

Selection Criteria

All the studies conformed to the following criteria were potentially involved: (1) Studies followed case-control or cross-sectional design (studies without controls were excluded); (3) Studies providing adequate allele or genotype information on the examined polymorphisms; (4) Studies published in English journals or their supplements; (5) If multiple studies derived from a common population, only the study with the largest sample size was extracted to avoid overlapping data; (6) The genotype frequency amongst control must conform to Hardy-Weinberg equilibrium (HWE).

Standard definitions were used to diagnosis disease outcomes [12].CAD was defined as significant stenosis with ≥50% luminal obstruction in at least one or more major coronary vessel [13]. Acute coronary syndrome (ACS) was defined by unstable angina pectoris and fatal or non-fatal MI [14] and MI was defined by the World Health Organization (WHO) criteria [15].

Data Extraction

Two authors (Z.W. and Y.Lou.) independently extracted the relevant information from qualified studies by the standard data-collection protocol according to the inclusion criteria. The data were entered into separate databases in duplicate by the two authors. Any encountered inconsistencies were resolved at a consensus meeting. The following data was gathered based on different cohort: first author's name, publication year, ethnicity, geographic location, study design, population source, disease outcomes, matching variables, clinical characteristics (such as gender, age, body mass index [BMI], the percentage of hypertension [HTN], diabetes mellitus [DM], smoking status), the distribution of the Ser128Arg and Thr715Pro genotype in both patients and controls and conformity to genotype frequencies with HWE. Continuous variables were manifested as mean ± standard deviation (SD) or median (5th and 95th percentiles).

Statistical Analysis

Data management and processing were performed using Review Manager software release 5.0 (Oxford, England) and Stata 11.0 (Stata Corporation, College Station, Texas, USA). The combined odd ratios (ORs) corresponding to 95% confidence intervals (CIs) were calculated under the random-effects model using DerSimonian & Laird method. Considering the relatively low number of homozygote genotype, we only estimate the effect size of these two polymorphisms on CAD under the allelic and dominant models. The possibility of heterogeneity was assessed using Cochran's chi-square based Q statistic test [16] and index I2 statistic. A significant Q statistic test (P<0.10) indicated heterogeneity among studies. I2 = 100%×(Q−df)/Q, measures the proportion of the between-study variability due to heterogeneity rather than chance[17], [18]. Departure from HWE was examined via the chi-square test or Fisher's exact test on the basis of a Web program (http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl).

A univariate meta-regression was used to explore potential factors associated with the genetic heterogeneity. A cumulative meta-analysis might indicate the influence of the initial published research on subsequent studies and the evolution of the combined estimates with ascending date of publication. A sensitivity analysis was conducted using one-study removal approach to identify the influence of each study on the overall effect size [19]. The possibility of publication bias could be visual by an funnel plot [20] and then assessed by the Egger's and the Begg-Mazumdar test as well as the trim-and-fill method. All P values were 2-sided. P<0.05 was considered significant except the Q statistic test.

Result

Literature Search

A total of 395 relevant citations were reviewed based on our selection strategy. The stepwise selection process is shown in Figure 1. After sequent selection, a total of 19 articles (10 of the E-selectin Ser128Arg polymorphism and 9 of the P-selectin Thr715Pro polymorphism) with adequate information satisfied our inclusion criteria. The study by Morgan et al. [21] provided the genotype information of both the two polymorphism and regarded ACS as the disease endpoint. Because the population of the study by Volcik et al.[22] derived from two different ethnic backgrounds (Caucasian & African), we considered them as two independent studies and calculated the ORs separately. The Indian population of the study by Tripathi et al. [23] was regarded as an independent group because its lineage is miscellaneous and cannot simply be grouped as Asian or Caucasian [24][26]. In general, 15 studies were performed among Caucasians [21], [22], [27][39] and 2 among Asians [40], [41]. Most of the studies used a retrospective case-control design [21], [23], [27][34], [36][41] except 2 studies[22], [35].P-B controls were adopted in 8 studies[22], [27], [28], [30], [33][35], [37] and H-B in 10 studies[21], [23], [31], [32], [36], [38][42]. Cases and controls were matched in 8 studies [21], [23], [30], [32][35], [37]. CAD was employed as the disease endpoint in 12 of the studies [22], [23], [27][32], [37][39], [41], while MI was taken as the outcome in 5 studies [33][36], [40].

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Figure 1. Flowchart diagram illustrating search strategy and study selection.

https://doi.org/10.1371/journal.pone.0088152.g001

Data Synthesis

There were 10 studies with 3,369 CAD patients and 2,577 controls for the E-selectin Ser128Arg polymorphism and 10 studies with 5,886 cases and 18,345 controls for the P-selectin Thr715Pro polymorphism involved in our meta-analysis. The clinical characteristics of included studies are shown in Table 1. The allele and genotype frequencies of these two polymorphisms are listed in Table 2 and 3 respectively. All the studies conformed to HWE (PHWE>0.05).

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Table 2. The frequencies of the E-selectin Ser128Arg polymorphism among CAD and controls.

https://doi.org/10.1371/journal.pone.0088152.t002

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Table 3. The frequencies of the P-selectin Thr715Pro polymorphism among CAD and controls.

https://doi.org/10.1371/journal.pone.0088152.t003

The overall frequency of the E-selecitn 128Arg allele was 8.7% in cases and 7.7% in controls. The frequency of the 128Arg allele among Caucasians (9.0% cases & 9.0% controls) was moderately higher than that among Asians (6.5% cases & 3.3% controls). As for the P-selectin Thr715Pro polymorphism, most of the qualified studies were performed among Caucasians except one study (Volcik et al.[African] [22]). The 715Pro allele proportion in cases (9.7%) was similar to that in controls (9.3%).

Table 4 and 5 summarized the estimates of genotype data for allelic and dominant models in total and subgroup analysis. In the main analyses, the overall comparison of the E-selectin 128Arg allele relative to 128Ser yielded a significantly increased risk of CAD (allele comparison: P = 0.02, OR = 1.33, 95%CI 1.04–1.69, Pheterogeneity = 0.01; dominant model: P = 0.02, OR = 1.40, 95%CI 1.06–1.87, Pheterogeneity = 0.02) with remarkable heterogeneity(Figure 2a); No predominant association was observed for the P-selectin Thr715Pro polymorphism with CAD under the both allelic (P = 0.40, OR = 0.94, 95%CI 0.82–1.08, Pheterogeneity = 0.03) and dominant model(P = 0.22, OR = 0.92, 95%CI 0.82–1.05, Pheterogeneity = 0.10) (Figure 2b).

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Figure 2. Forest plots detailing the association of the E-selectin Ser128Arg polymorphism (Arg versus Ser, Figure 2a) and the P-selectin Thr715Pro polymorphism (Pro versus Thr, Figure 2b) with CAD using the allelic model in overall analysis.

https://doi.org/10.1371/journal.pone.0088152.g002

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Table 4. Summary estimates of the E-selectin Ser128Arg polymorphism with the CAD risk under the allelic and dominant models.

https://doi.org/10.1371/journal.pone.0088152.t004

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Table 5. Summary estimates of the P-selectin Thr715Pro polymorphism with the CAD risk under the allelic and dominant models.

https://doi.org/10.1371/journal.pone.0088152.t005

Sensitivity Analysis

Sensitivity analyses demonstrated that no single study influenced the heterogeneity and ORs when evaluating the association between the E-selectin Ser128Arg polymorphism and CAD in total analysis. As for the P-selectin Thr715Pro polymorphism, the study by Herrmann et al.[33] contributed to the observed heterogeneity in total analysis. The overall heterogeneity no longer existed (Pheterogeneity  = 0.21) after removing this study and the effect size did not change materially.

Cumulative Analysis and Publication Bias

Cumulative trends for allelic contrast of these two polymorphisms suggested there was not any distinct evidence for the first published study that triggered the ensuing replication of other studies that tried to replicate this initial result (data not shown).The funnel plot for the Ser128Arg polymorphism was distinct asymmetric for small negative studies. The Egger's (P = 0.041) and the Begg-Mazumdar (P = 0.016) test suggested a presence of publication bias. By using the trim and fill method, we found that if the publication bias was the sole source of the funnel plot asymmetry, 3 studies were needed to be symmetrical (Figure 3a). For the Thr715Pro polymorphism, the funnel plot analysis as well as the Egger's and the Begg-Mazumdar test reflected a low probability of publication bias under the allele comparison (P = 0.91 for Egger's test and P = 0.92 for Begg-Mazumdar test) (Figure 3b).

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Figure 3. Filled Begg's funnel plot for studies investigating the effect of the E-selectin Ser128Arg polymorphism on CAD (Figure 3a) and Begg's funnel plot analysis of the P-selectin Thr715Pro polymorphism with CAD risk (Figure 3b).

Red squares are missed studies due to publication bias in Figure 3a.

https://doi.org/10.1371/journal.pone.0088152.g003

Subgroup Analysis

To evaluate the possible factors that contributed to the majority of heterogeneity, we undertook a set of subgroup analyses. ORs generated for the Ser128Arg polymorphism were statistically significant among Asians (allele comparison: P = 0.001, OR = 2.07, 95%CI 1.33–3.24, Pheterogeneity = 0.77) but not among Caucasians (allele comparison: P = 0.33, OR = 1.13, 95%CI 0.88–1.45, Pheterogeneity = 0.08) (Figure 4); When data were stratified according to disease type, there was a significant association of the Ser128Arg polymorphism with CAD observed (allele comparison: P = 0.02, OR = 1.38, 95%CI 1.06–1.80, Pheterogeneity = 0.06; dominant model: P = 0.02, OR = 1.54, 95%CI 1.09–2.19, Pheterogeneity = 0.02); The 128Arg allele carriers had a marginal risk increase (42%) of CAD in matched studies under the dominant model (P = 0.05, 95%CI 0.80–2.51, Pheterogeneity = 0.08). Data were then stratified according to publication year. The out points of the publication year (2007 for the E-selectin Ser128Arg polymorphism & 2005 for the P-selectin Thr715Pro polymorphism) were chosen as the median. Risk increase in the studies published before 2007 (allele comparison: P = 0.004, OR = 1.68, 95%CI 1.18–2.40, Pheterogeneity = 0.16) was significantly different from that in the studies published in/after 2007(allele comparison: P = 0.53, OR = 1.07, 95%CI 0.86–1.34, Pheterogeneity = 0.18) (Table 4).

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Figure 4. ORs and 95%CI of individual studies and pooled data for the association between the E-selectin Ser128Arg polymorphism and CAD among Asians under the allele comparison (Arg versus Ser, Figure 4a) and under the dominant model (ArgArg+SerArg versus SerSer, Figure 4b).

https://doi.org/10.1371/journal.pone.0088152.g004

As for the P-selectin Thr715Pro polymorphism, the 715Pro carriers had a significant 19% risk reduction in MI group (allele comparison: P = 0.04, 95%CI 0.67–0.99, Pheterogeneity = 0.14) and a suggestive risk effect in CAD group (allele comparison: P = 0.65, OR = 1.04, 95%CI 0.87–1.25, Pheterogeneity = 0.26) (Figure 5). In addition, we observed a marginal association of the Thr715Pro polymorphism with CAD in matched studies (allele comparison: P = 0.09, OR = 0.87, 95%CI 0.74–1.02, Pheterogeneity = 0.10; dominant model: P = 0.06, OR = 0.86, 95%CI 0.74–1.01, Pheterogeneity = 0.19). However, there is a lack of dramatic association of the Thr715Pro polymorphism with CAD risk when data were categorized according to study design (prospective/retrospective), population source (P-B/H-B) and publication date (<2005/≥2005)(Table 5).

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Figure 5. Meta-analysis for the association between the P-selectin Thr715Pro polymorphism and MI under the allele comparison (Pro versus Thr, Figure 5a) and under the dominant model (ProPro+ThrPro versus ThrThr, Figure 5b).

https://doi.org/10.1371/journal.pone.0088152.g005

Meta-regression Analysis

A univariate meta-regression analysis was used to detect the effect of potential factors on genetic heterogeneity. Single covariates such as ethnicity, population source, case definition, study design, matching information, language, publication year and the baseline characteristics of total population were added in a series of univariate models. There was no evidence suggesting these factors were responsible for the between-study heterogeneity for both the E-selectin Ser128Arg polymorphism and the P-selectin Thr715Pro polymorphism.

Discussion

There has been growing interest in the role of cellular adhesion molecules in atherosclerosis. Among these, the selectins play essential roles in the first step in leukocyte recruitment and infiltration, which is vital in the key process of atherosclerosis[3]. The association between the SNPs of the selectin genes with CAD was previously confounding because of contradictory results produced by a range of relatively small individual studies. In addition, true variability across different population[43] and different genetic backgrounds[44] may be the other explanations. Meta-analysis is an ideal tool to identify the genuine association while addressing between-study heterogeneity. To clarify this issue, we performed a meta-analysis of publicly independent studies. To our best knowledge, this is the first meta-analysis appraising the relationship of the selectin genes with CAD risk. As a result, we detected that carrier status for the E-selectin 128Arg allele was significant associated with an increase of 33% in CAD risk with remarkable heterogeneity. We hypothesized the ethnicity may be a potential origin of between-study heterogeneity. The subgroup analysis suggested that the risk increase of the Ser128Arg polymorphism on CAD among Asians were dramatically larger than Caucasians. Although the minor allele frequency of the Ser128Arg polymorphism was slightly different between Asians and Caucasians, this inconsistence can be attributed to the pleiotropic effect of the Ser128Arg polymorphism due to various genetic ancestral backgrounds. Different linkage disequilibrium patterns due to different populations were likely to be another explanation. A SNP may be in close linkage with another nearby causal variant in one ethnic population but not in another. Ethnicity might be a source of between-study heterogeneity for the Ser128Arg polymorphism. However, we were unable to evaluate the influence of ethnicity on the CAD risk of the P-selectin 715Pro carriers, because most of the eligible studies concerning the Thr715Pro polymorphism were conducted among Caucasians. It is difficult to estimate the modest association in other racial descents unless examining a larger population. Constructing optimized databases and replicating the results of these two polymorphisms related to CAD in different populations may benefit to draw definitive conclusions.

As well as the obvious impact of ethnicity, distinct heterogeneity can be observed when comparing different disease types (e.g., CAD versus MI). Although both CAD and MI most commonly result from atherosclerotic occlusion of the coronary arteries and share many of the same inflammatory factors, the pathological manifestations of CAD and MI are quite different. Acute atherosclerotic plaque disruption with thrombosis, which compromises coronary blood flow, is the key process of MI[3]. Although some effects on leukocyte adhesion of the E- selectin and P-selectin are overlapping, these two members of the selectin family may partly differ in function. Besides the first adhesive cellular step, E-selectin also mediates the immune response of injured endothelial cells[45]. E- selectin binding to the sialylated Lewisx antigen (sLex) is regarded as the preliminary step of endothelial activation, damage or turnover and serves as a molecular marker for atherosclerosis [46].Reduction in the expression of E-selectin protects against atherosclerosis in apolipoprotein E-deficient mice [47]. We identified a strong susceptibility of the Ser128Arg polymorphism to disease outcome in CAD. Substitution of E-selectin EGF domain residue 128Ser with an arginine results in an alternation in E-selectin protein ligand binding specificity and an enhanced adherence of monocyte and neutrophil to the activated endothelium in vascular areas [40], [48]. The bound and activated leukocytes and the cytokine mediators exacerbate atherosclerosis progression. By contrast, the P-selectin Thr715Pro polymorphism exhibited as a significant protect factor of MI but not CAD. It is could be a likely explanation if the protective effect of the 715Pro allele was directed against thrombosis rather than atherosclerosis[33]. P-selectin is localized in storage granules of platelets and the Weibel-Palade bodies of endothelial cells. P-selectin can interact with P-selectin glycoprotein ligand 1(PSGL-1) expressed on leukocytes and triggers the synthesis of pro-coagulatory tissue factor and the subsequent release of tissue factor positive microparticles from leukocytes[49]. This is a key process of atherothrombosis. The Thr715Pro polymorphism, located 15 amino acids in front of the transmembrane domain, is a non-conservative amino acid exchange. The 715Pro impairs terminal glycosylation of P-selectin and has poor sensitivity of glycan-modifying Golgi enzymes, which then lead to affect the export of P-selectin on the cell surface and inefficient adhesion compared to the wild-type [50]. The less P-selectin molecules result in the generation of fewer platelet-monocyte aggregates. This could probably explain the protective effect of the Thr715Pro polymorphism on MI. However, the true functional significance of these two polymorphisms in vivo remains unclear. Further studies assessing the selectin proteins expression and regulation are required to clarify the problem.

Our study still has several limitations. First, only two of the most common SNPs of the selectin genes were investigated. We could not rule out the possible influence of other rare variations or uncommon SNPs that have not been extensively studied. Considering the effect of a SNP on a multi-factorial disease such as CAD is relatively weak, particular haplotypes involving the Ser128Arg polymorphism or another functional mutation in linkage disequilibrium may have more significance. Another problem should be cautiously considered. There was evidence for the publication bias of the E-selectin Ser128Arg polymorphism in the meta-analysis. This is said to occur when the chance of the publication of a smaller study increases if it shows a stronger effect [51]. By contrast, the small negative results tend to be rejected for publication. We cannot rule out the possibility of language bias and the influence of publication timing. It is likely that some unpublished studies and “grey” literature (articles in languages other than English) have not been included. Larger and well-design studies from different language databases are required to ascertain the robustness of our results.

In summary, our meta-analysis expanded previous individual studies by supporting the evidence that the E-selectin Ser128Arg polymorphism was associated with an increased risk of CAD while the P-selectin Thr715Pro polymorphism could be a protective factor of MI. We suggested that the members of selectin family appear to play heterogeneous roles at the development of atherosclerosis and therefore be new candidate targets for diagnostic purposes and therapeutic interventions in atherosclerosis.

Supporting Information

Checklist S1.

The PRISMA checklist for this meta-analysis.

https://doi.org/10.1371/journal.pone.0088152.s001

(DOC)

Acknowledgments

We really appreciate and thank Dr Kimura A for providing us useful data information on their studies and Furuta S and Liu SH for providing Japanese- and Korean- translation support.

Author Contributions

Conceived and designed the experiments: ZW Y. Lou LL WJ. Performed the experiments: ZW Y. Lou Y. Liu QC. Analyzed the data: ZW Y. Lou LL XC WJ. Contributed reagents/materials/analysis tools: ZW Y. Lou LL Y. Liu QC XC WJ. Wrote the paper: ZW Y. Lou.

References

  1. 1. Topol EJ, Smith J, Plow EF, Wang QK (2006) Genetic susceptibility to myocardial infarction and coronary artery disease. Hum Mol Genet 15 Spec No 2: R117–123.
  2. 2. Wu Z, Lou Y, Jin W, Liu Y, Lu L, et al. (2013) Relationship of the p22phox (CYBA) Gene Polymorphism C242T with Risk of Coronary Artery Disease: A Meta-Analysis. PLoS One 8: e70885.
  3. 3. Ross R (1999) Atherosclerosis–an inflammatory disease. N Engl J Med 340: 115–126.
  4. 4. Springer TA (1995) Traffic signals on endothelium for lymphocyte recirculation and leukocyte emigration. Annu Rev Physiol 57: 827–872.
  5. 5. Vestweber D, Blanks JE (1999) Mechanisms that regulate the function of the selectins and their ligands. Physiol Rev 79: 181–213.
  6. 6. Lefer DJ (2000) Pharmacology of selectin inhibitors in ischemia/reperfusion states. Annu Rev Pharmacol Toxicol 40: 283–294.
  7. 7. Roberts R, Stewart AF (2012) The genetics of coronary artery disease. Curr Opin Cardiol 27: 221–227.
  8. 8. Wu Z, Lou Y, Jin W, Liu Y, Lu L, et al. (2012) The Pro12Ala Polymorphism in the Peroxisome Proliferator-Activated Receptor Gamma-2 Gene (PPARgamma2) Is Associated with Increased Risk of Coronary Artery Disease: A Meta-Analysis. PLoS One 7: e53105.
  9. 9. Wu Z, Lou Y, Jin W, Liu Y, Lu L, et al. (2012) The C161T polymorphism in the peroxisome proliferator-activated receptor gamma gene (PPARgamma) is associated with risk of coronary artery disease: a meta-analysis. Mol Biol Rep.
  10. 10. Wenzel K, Ernst M, Rohde K, Baumann G, Speer A (1996) DNA polymorphisms in adhesion molecule genes–a new risk factor for early atherosclerosis. Hum Genet 97: 15–20.
  11. 11. Moher D, Liberati A, Tetzlaff J, Altman DG (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6: e1000097.
  12. 12. Vach W, Gerke O, Hoilund-Carlsen PF (2012) Three principles to define the success of a diagnostic study could be identified. J Clin Epidemiol 65: 293–300.
  13. 13. Wright RS, Anderson JL, Adams CD, Bridges CR, Casey DE Jr, et al. (2011) 2011 ACCF/AHA focused update incorporated into the ACC/AHA 2007 Guidelines for the Management of Patients with Unstable Angina/Non-ST-Elevation Myocardial Infarction: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines developed in collaboration with the American Academy of Family Physicians, Society for Cardiovascular Angiography and Interventions, and the Society of Thoracic Surgeons. J Am Coll Cardiol 57: e215–367.
  14. 14. Joensen AM, Jensen MK, Overvad K, Dethlefsen C, Schmidt E, et al. (2009) Predictive values of acute coronary syndrome discharge diagnoses differed in the Danish National Patient Registry. J Clin Epidemiol 62: 188–194.
  15. 15. Anderson JL, Adams CD, Antman EM, Bridges CR, Califf RM, et al. (2011) 2011 ACCF/AHA Focused Update Incorporated Into the ACC/AHA 2007 Guidelines for the Management of Patients With Unstable Angina/Non-ST-Elevation Myocardial Infarction: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Circulation 123: e426–579.
  16. 16. Lau J, Ioannidis JP, Schmid CH (1997) Quantitative synthesis in systematic reviews. Ann Intern Med 127: 820–826.
  17. 17. Higgins JP, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21: 1539–1558.
  18. 18. Higgins JP, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327: 557–560.
  19. 19. Biros E, Norman PE, Jones GT, van Rij AM, Yu G, et al. (2011) Meta-analysis of the association between single nucleotide polymorphisms in TGF-beta receptor genes and abdominal aortic aneurysm. Atherosclerosis 219: 218–223.
  20. 20. Egger M, Davey Smith G, Schneider M, Minder C (1997) Bias in meta-analysis detected by a simple, graphical test. BMJ 315: 629–634.
  21. 21. Morgan TM, Krumholz HM, Lifton RP, Spertus JA (2007) Nonvalidation of reported genetic risk factors for acute coronary syndrome in a large-scale replication study. Jama 297: 1551–1561.
  22. 22. Volcik KA, Ballantyne CM, Coresh J, Folsom AR, Wu KK, et al. (2006) P-selectin Thr715Pro polymorphism predicts P-selectin levels but not risk of incident coronary heart disease or ischemic stroke in a cohort of 14595 participants: the Atherosclerosis Risk in Communities Study. Atherosclerosis 186: 74–79.
  23. 23. Tripathi R, Singh PK, Tewari S, Tamhankar PM, Ramesh V, et al. (2009) Genetic predisposition of E-selectin gene (S128R) polymorphism in patients with coronary artery disease (CAD). Indian J Med Res 130: 423–427.
  24. 24. Reich D, Thangaraj K, Patterson N, Price AL, Singh L (2009) Reconstructing Indian population history. Nature 461: 489–494.
  25. 25. Quintana-Murci L, Chaix R, Wells RS, Behar DM, Sayar H, et al. (2004) Where west meets east: the complex mtDNA landscape of the southwest and Central Asian corridor. Am J Hum Genet 74: 827–845.
  26. 26. Palanichamy MG, Sun C, Agrawal S, Bandelt HJ, Kong QP, et al. (2004) Phylogeny of mitochondrial DNA macrohaplogroup N in India, based on complete sequencing: implications for the peopling of South Asia. Am J Hum Genet 75: 966–978.
  27. 27. Barbaux SC, Blankenberg S, Rupprecht HJ, Francomme C, Bickel C, et al. (2001) Association between P-selectin gene polymorphisms and soluble P-selectin levels and their relation to coronary artery disease. Arterioscler Thromb Vasc Biol 21: 1668–1673.
  28. 28. Bugert P, Vosberg M, Entelmann M, Jahn J, Katus HA, et al. (2004) Polymorphisms in the P-selectin (CD62P) and P-selectin glycoprotein ligand-1 (PSGL-1) genes and coronary heart disease. Clin Chem Lab Med 42: 997–1004.
  29. 29. Abu-Amero KK, Al-Mohanna F, Al-Boudari OM, Mohamed GH, Dzimiri N (2007) The interactive role of type 2 diabetes mellitus and E-selectin S128R mutation on susceptibility to coronary heart disease. BMC Med Genet 8: 35.
  30. 30. Carter AM, Anagnostopoulou K, Mansfield MW, Grant PJ (2003) Soluble P-selectin levels, P-selectin polymorphisms and cardiovascular disease. J Thromb Haemost 1: 1718–1723.
  31. 31. Endler G, Exner M, Raith M, Marculescu R, Mannhalter C, et al. (2003) The E-selectin S128R polymorphism is not a risk factor for coronary artery disease in patients with diabetes mellitus type 2. Thromb Res 112: 47–50.
  32. 32. Ghazouani L, Abboud N, Khalifa SB, Perret C, Nicaud V, et al. (2011) Contribution of SELP and PSGL-1 genotypes and haplotypes to the presence of coronary heart disease in Tunisians. Mol Biol Rep 38: 495–501.
  33. 33. Herrmann SM, Ricard S, Nicaud V, Mallet C, Evans A, et al. (1998) The P-selectin gene is highly polymorphic: reduced frequency of the Pro715 allele carriers in patients with myocardial infarction. Hum Mol Genet 7: 1277–1284.
  34. 34. Kee F, Morrison C, Evans AE, McCrum E, McMaster D, et al. (2000) Polymorphisms of the P-selectin gene and risk of myocardial infarction in men and women in the ECTIM extension study. Etude cas-temoin de l'infarctus myocarde. Heart 84: 548–552.
  35. 35. Rosner SA, Ridker PM, Zee RY, Cook NR (2005) Interaction between inflammation-related gene polymorphisms and cigarette smoking on the risk of myocardial infarction in the Physician's Health Study. Hum Genet 118: 287–294.
  36. 36. Sakowicz A, Fendler W, Lelonek M, Pietrucha T (2010) Genetic variability and the risk of myocardial infarction in Poles under 45 years of age. Arch Med Sci 6: 160–167.
  37. 37. Wenzel K, Blackburn A, Ernst M, Affeldt M, Hanke R, et al. (1997) Relationship of polymorphisms in the renin-angiotensin system and in E-selectin of patients with early severe coronary heart disease. J Mol Med (Berl) 75: 57–61.
  38. 38. Ye SQ, Usher D, Virgil D, Zhang LQ, Yochim SE, et al. (1999) A PstI polymorphism detects the mutation of serine128 to arginine in CD 62E gene - a risk factor for coronary artery disease. J Biomed Sci 6: 18–21.
  39. 39. Zak I, Sarecka B, Krauze J (2008) Synergistic effects between 561A>C and 98G>T polymorphisms of E-selectin gene and hypercholesterolemia in determining the susceptibility to coronary artery disease. Heart Vessels 23: 257–263.
  40. 40. Yoshida M, Takano Y, Sasaoka T, Izumi T, Kimura A (2003) E-selectin polymorphism associated with myocardial infarction causes enhanced leukocyte-endothelial interactions under flow conditions. Arterioscler Thromb Vasc Biol 23: 783–788.
  41. 41. Li Y, Wei YS, Wang M, Zhang PA, Jiang XJ, et al. (2005) Association between the Ser128Arg variant of the E-selectin and risk of coronary artery disease in the central China. Int J Cardiol 103: 33–36.
  42. 42. Abu-Amero KK, Al-Boudari OM, Mohamed GH, Dzimiri N (2006) E-selectin S128R polymorphism and severe coronary artery disease in Arabs. BMC Med Genet 7: 52.
  43. 43. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN (2003) Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 33: 177–182.
  44. 44. Salanti G, Sanderson S, Higgins JP (2005) Obstacles and opportunities in meta-analysis of genetic association studies. Genet Med 7: 13–20.
  45. 45. Haller H (1997) Endothelial function. General considerations. Drugs 53 Suppl 11–10.
  46. 46. Hwang SJ, Ballantyne CM, Sharrett AR, Smith LC, Davis CE, et al. (1997) Circulating adhesion molecules VCAM-1, ICAM-1, and E-selectin in carotid atherosclerosis and incident coronary heart disease cases: the Atherosclerosis Risk In Communities (ARIC) study. Circulation 96: 4219–4225.
  47. 47. Collins RG, Velji R, Guevara NV, Hicks MJ, Chan L, et al. (2000) P-Selectin or intercellular adhesion molecule (ICAM)-1 deficiency substantially protects against atherosclerosis in apolipoprotein E-deficient mice. J Exp Med 191: 189–194.
  48. 48. Revelle BM, Scott D, Beck PJ (1996) Single amino acid residues in the E- and P-selectin epidermal growth factor domains can determine carbohydrate binding specificity. J Biol Chem 271: 16160–16170.
  49. 49. Andre P, Hartwell D, Hrachovinova I, Saffaripour S, Wagner DD (2000) Pro-coagulant state resulting from high levels of soluble P-selectin in blood. Proc Natl Acad Sci U S A 97: 13835–13840.
  50. 50. Subramanian H, Gambaryan S, Panzer S, Gremmel T, Walter U, et al. (2012) The Thr715Pro variant impairs terminal glycosylation of P-selectin. Thromb Haemost 108: 963–972.
  51. 51. Rucker G, Schwarzer G, Carpenter J (2008) Arcsine test for publication bias in meta-analyses with binary outcomes. Stat Med 27: 746–763.