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A polymorphism with coronary artery disease: A meta-analysis
Thrombosis Research 131 (2013) e77–e84
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Regular Article
Association of the CCR5Δ32 polymorphism and its ligand RANTES-403 G/A polymorphism with coronary artery disease: A meta-analysis Lihan Wang, Xinyang Hu, Shoude Zhang, Xin Xu, Jianan Wang ⁎ Cardiovascular key lab of Zhejiang Province, the second affiliated hospital, school of medicine, Zhejiang University, Hangzhou 310009, China
a r t i c l e
i n f o
Article history: Received 11 June 2012 Received in revised form 17 July 2012 Accepted 27 July 2012 Available online 9 January 2013 Keywords: CCR5Δ32 RANTES-403 G/A Gene polymorphism Coronary artery disease Meta-analysis
a b s t r a c t Introduction: To explore the relationship between polymorphisms in the RANTES and CCR5 genes and the risk of coronary artery disease (CAD). Materials and Methods: We conducted a meta-analysis on two genetic variants (RANTES-403 G/A and CCR5Δ32). Publication bias was tested by the Egger's regression test and Begg's test. Sensitivity analysis and subgroup analyses were performed to explore the heterogeneity among studies. Results: No significant association of RANTES-403 G/A polymorphism and CAD risk was observed (dominant model: RR = 1.02, 95%CI = 0.90-1.06; recessive model: RR = 1.27, 95%CI = 0.90-1.80). However, after excluding the study conducted by Yangsoo et al., the pooled relative ratio (RR) in the dominant model suggested that the RANTES-403 G/A polymorphism was positively associated with CAD risk. The subgroup analyses found that a positive relationship between the polymorphism and CAD risk was restricted to the Caucasian population. A meta-analysis of studies on the CCR5Δ32 polymorphism showed no significant association with CAD risk both in dominant (RR=1.05, 95%CI =0.92-1.21) and recessive (RR =1.27, 95%CI= 0.90-1.80) models. Moreover, no association was identified in the subgroup analyses. Conclusions: The RANTES-403 G/A polymorphism is not associated with CAD risk, but does most likely increase CAD risk in Caucasians. Moreover, no relationship between the CCR5Δ32 polymorphism and risk of CAD was found. © 2012 Published by Elsevier Ltd.
Introduction Coronary artery disease (CAD) is the leading risk factor for death and disability in the world [1]. The underlying pathology of CAD has been recognized as atherosclerosis, which is a chronic inflammatory lesion affecting large and medium elastic and muscular arteries [2]. Chemokines and their receptors have been increasingly recognized as key mediators in the pathology of atherosclerosis [3]. Among these mediators, Regulated upon Activation, Normal T-cell Expressed, and secreted (RANTES), also known as Chemokine (C-C motif) ligand 5 (CCL5), is a critical regulator in this process. RANTES belongs to the C-C motif chemokine family and is mainly produced by CD8+ T cells, epithelial cells, fibroblasts, and platelets. In atherosclerotic plaques, RANTES expression is up-regulated [4–6]. CCR5 is one of the receptors of RANTES and belongs to the super family of the seven-transmembrane G-protein coupled receptors (GPCRs). It is predominantly expressed on T cells, macrophages, dendritic cells, and microglia. Importantly, studies have found that inflammatory leukocytes are recruited into the endothelium upon RANTES-CCR5 interaction and mediate the process of atherosclerosis. Increasingly evidence has shown that the down-regulation of RANTES or CCR5 can reduce the incidence of atherosclerotic lesions ⁎ Corresponding author at: Postal: 310009. Tel./fax: +86 571 13805786328. E-mail address: [email protected] (J. Wang). 0049-3848/$ – see front matter © 2012 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.thromres.2012.07.024
[7–9] and can improve the prognosis of patients with myocardial infarction [10–12]. Interestingly, some gene mutations affect the expression of CCR5 and RANTES, among which the CCR5Δ32 polymorphism and RANTES-403 G/A polymorphism are the most commonly studied. The CCR5Δ32 polymorphism is defined by a 32 bp deletion that leads to a truncated nonfunctional receptor [13]. This abnormal receptor is eliminated from the cell surface in homozygous individuals and down-regulated by 20%–30% in heterozygous patients [14]. Furthermore, according to some epidemiological studies, the CCR5Δ32 polymorphism reduces the risk of CAD [15–18]. RANTES-403 G/A refers to a transition (G > A) in the promoter region of the RANTES gene, which enhances the transcriptional activity [19] and increases the risk of CAD [6]. However, the relationship between these mutations and the risk of developing CAD has not been replicated in other studies [18,20–22]. To help clarify the inconsistent findings, we conducted a meta-analysis of the published genetic association studies of these two polymorphisms and the risk of CAD. Materials and methods Search strategy and inclusion criteria We sought genetic association studies published before February 2012 on CAD and the Δ32 variant in the CCR5 gene or -403 G/A
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variant in the RANTES gene. We systematically searched Pubmed, Embase, Web of Science, and a reference list of relevant papers using the term “CCR5”, “RANTES”, or “CCL5” paired with “coronary artery disease”, “coronary heart disease”, “atherosclerosis”, “ischemic heart disease”, “myocardial infarction”, and “genetic variant” or “polymorphism”, respectively. We also manually screened the reference lists of the retrieved articles to identify other relevant publications. The inclusion criteria were (1) studies on the relationship between the CCR5Δ32 polymorphism, RANTES-403 G/A polymorphism, and CAD; (2) published case–control studies; (3) cohort studies; (4) studies published as full-length articles in English; (5)and studies with sufficient data for estimating a relative ratio (RR) with 95% confidence interval (CI). Data extraction Two investigators independently extracted data (Wang and Zhang) and discrepancies were resolved by group discussion. For each study, the following information was extracted: name of the first author, year of publication, ethnic origin of the studied population, number in case (exposed) and control (unexposed) groups, genotype and allele distributions, male percentage, mean ages in case (exposed) and control (unexposed) groups, genotyping method, and Hardy-Weinberg equilibrium in case and control groups. If multiple published reports from the same study population were available, we included only the one with the largest sample size and complete data. Statistical analysis The Hardy-Weinberg equilibrium (HWE) was tested by the X 2 test. The strength of association was estimated as RR and 95% confidence intervals (CIs). For both polymorphisms, the statistical analysis was performed under both the dominant (Δ32, wt/Δ32 + Δ32/Δ32 vs. wt/wt; -403 G/A, GA + AA vs. GG) genetic model and recessive (Δ32, Δ32/Δ32 vs. wt/Δ32 + wt/wt; -403 G/A, AA vs. GA + GG) genetic model. The RRs were pooled through a random effects model, using the M-H heterogeneity approach when heterogeneity existed among these studies. Otherwise, a fixed effects model was adopted. Heterogeneity between studies was assessed by the Q-test an I 2 statistic, where p b 0.10 and I 2 > 50% indicated evidence of heterogeneity. In order to investigate the probable source of heterogeneity, a subgroup analysis were performed according to ethnicity, mean age level, sample size for patients (>300, 200–300, and b 200), and status of HWE (yes or no). Sensitivity analysis was performed by excluding each individual study at a time from the total and reanalyzing the remainder to examine the influence of one study on the overall summary estimate. Publication bias was assessed with funnel plots, the Egger regression test, and Begg's test. Data of the meta-analysis were analysed using Stata software (version 10.0; Stata Corporation, College Station, TX). All P values were for a two-sided analysis and values of P b 0.05 were considered statistically significant. Results Study characteristics The study selection process is detailed in Fig. 1. Based on our preliminary search criteria, a total of 18 publications were eligible. Among these articles, three publications were excluded for the absence of sufficient data for estimating RR and 95%CI. A total of 15 studies with 17 separate association studies were included in the final meta-analysis, including 6123 cases (patients with CAD) and 4241 controls. All studies were case–control in design. For the CCR5Δ32 polymorphism, 10 studies were available (7 Caucasian, 3 non-Caucasian), including 4537 cases (patients with CAD) and 3039 controls. Four studies considered the
Fig. 1. Flow diagram of the article selection process for CCR5Δ32 polymorphism, RANTES-403 G/A polymorphism, and CAD risk.
CCR5Δ32 polymorphism to be a protective factor for CAD, but three studies suggested there was no association between the CCR5Δ32 polymorphism and a risk of developing CAD. Furthermore three studies found an association of the CCR5Δ32 polymorphism and an increased the risk of CAD. For the RANTES-403 G/A, seven studies were available (4 Caucasian, 3 non-Caucasian), including 4577 cases (patients with CAD) and 2055 controls. Table 1 shows the main characteristics of these studies. Meta-analysis results The relationship between CCR5Δ32 and CAD A random effects model was used under a dominant genetic model because of statistical heterogeneity across the studies (I 2 = 65.8%; P = 0.002) (Table 2). Under a recessive genetic model, the fixed effects model was adopted, as no heterogeneity was observed among the studies (I2 = 34.6%; P= 0.164). Under this model, three studies had zero patients with the GG genotypes among case and control subjects, and therefore they were excluded from the analysis. When all 10 studies were pooled into the meta-analysis, there was no evidence of an association between the CCR5Δ32 polymorphism and CAD risk (for the dominant model: the pooled RR was 1.05, 95%CI: 0.81-1.34, I2 = 65.8%, P= 0.002; for the recessive model: the pooled RR was 0.84, 95%CI: 0.38-1.88, I 2 = 34.6%, P= 0.164). For further assessment, we performed a subgroup analysis to investigate the source of the heterogeneity. The results suggested that ethnicity, mean age level, and patient sample size were associated with heterogeneity. In the dominant genetic model, the sensitivity analysis found no evidence of any individual study having excessive influence on the pooled effect and between-study heterogeneity. Overall, the Egger's regression test and Begg's test demonstrated that no statistically significant publication bias (dominant model: p = 0.858 in Begg's test, p =0.416 in Egger's regression test; recessive model: p = 1.000 in Begg's test, p = 0.775 in Egger's regression test) was present in any of the dominant and recessive models. The relationship between RANTES-403 G/A polymorphism and CAD risk We chose a random effects model to investigate the relationship between the RANTES-403 G/A polymorphism and CAD risk under the dominant and recessive genetic models (dominant model: I2 = 72.4%, p = 0.001; recessive model: I2 = 52.4%, p = 0.050) (Table 3). When all seven studies were pooled into the meta-analysis, there was no evidence of an association between the RANTES-403 G/A polymorphism
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Table 1 Main characteristics of the studies included in the meta-analysis. Reference
Year
Ethnicity
Subjects, n Cases/ controls
Ten studies for the CCR5Δ32 polymorphism J . Petrkova [38] 2005 Caucasian
80/247
Mean age, y Cases/ controls
Genotyping method
End point of assessment
Gender component in Cases/ controls(%male)
Test for HWE
b55/NA
PCR-SSP
MI
100/100
1.758 0.185 0.021 0.884 30.456 0.000 1.589 0.207 0.491 0.484 0.196 0.658 0.011 0.915 19.042 0.000 0.631 0.427 0.006 0.939
Neha [39]
2011
South Asian
230/300
49.97/44.93
PCR
MI
85/85.2
Carmela [15]
2008
Caucasian
133/(136 + 123)
b45/(b45/>100)
PCR
MI
NA/(NA/NA)
P Gonza [16]
2001
Caucasian
(214 + 96)/360
(45/65)/42
PCR
MI
(NA/NA)NA
Jennifer [17]
2005
Caucasian
232/459
60.6/60.3
Taqman
CAD
0/0 (all female)
Stavros [40]
2005
Caucasian
210/165
63.7/63.2
PCR
CAD
77.6/76.4
S. Sharda [20]
2006
South Asian
197/199
47.31/44.58
PCR
CAD
84.26/81.40
Zeynep [41]
2009
West Asian
146/202
56.38/54.2
PCR
MI
60.4/59.4
Csaba [18]
2000
Caucasian
318/320
57.6/58.9
PCR
CAD
76.1/75
Eleonora [6]
2003
Caucasian
2694/530
63.8/56.9
PCR
CAD
73.9/51.3
Seven studies for the RANTES-403 G/A polymorphism Eleonora [6] 2003 Caucasian 2694/530
63.8/56.9
RFLP
CAD
73.9/51.3
Konstantina [42]
2008
Caucasian
192/149
64/62
RFLP
CAD
89.1/71.1
Sungha [43]
2007
East Asian
170/170
62.2/62.6
RFLP
MI
67.059/75.882
Csaba [18]
2000
Caucasian
318/320
57.6/58.9
RFLP
CAD
76.1/75
Javad [32]
2011
West Asian
191/128
NA/NA
RFLP
CAD
60.4/68.5
Irina [22]
2011
Caucasian
467/337
SSP
MI
Yangsoo [44]
2007
East Asian
553/416
RU:56.6/43.6 CZ:55.0/35.7 54.8/53.8
Taqman
CAD
RU: 83.41/62.14 CZ: 68.44/44.16 100/100
and CAD risk (dominant model: RR= 1.02, 95%CI =0.90-1.16; recessive model: RR= 1.12, 95%CI= 0.79-1.60). However, when we performed a sub-group analysis by ethnicity, there was a weak association between the RANTES-403 G/A polymorphism and CAD risk using the dominant genetic model, and the heterogeneity was removed (Caucasian: RR=1.16, 95%CI: 1.05-1.27, P= 0.379; non-Caucasian: RR =0.98, 95%CI: 0.81-0.95; P=0.770). We also performed a subgroup analysis by sample size for patients and HWE; however, these variables were Table 2 Meta-analysis of the effect of the CCR5Δ32 polymorphism on the risk of CAD and subgroup analysis under a dominant model. Study group
Overall Subgroup analysis 1.ethnicity Caucasian non-Caucasian 2.Sample size for patients >300 200-300 b200 3.Mean age level >50 b50 4.HWE yes no
Study
Sample size
RR (95%CI)
P
(n)
(case/controls)
10
4537/3039
1.05(0.81-1.34)
0.002
7 3
3964/2338 573/701
0.94(0.83-1.07) 2.07(1.39-3.08)
0.036 0.472
3 3 4
3309/1208 672/924 556/907
0.96(0.77-1.20) 1.26(0.68-2.32) 1.04(0.78-1.04)
0.157 0.084 0.001
5 4
3587/1675 774/1075
1.08(0.94-1.23) 0.70(0.48-1.02)
0.201 0.000
7 3
3940/2258 597/781
1.05(0.83-1.34) 0.78(0.33-1.84)
0.088 0.000
X2 p
4.799 0.028 9.427 0.002 1.519 0.218 1.135 0.287 0.804 0.370 0.022 0.883 0.659 0.417
not found to be an important source of heterogeneity. The sensitivity analysis suggested that after excluding the article conducted by Yangsoo et al., the between-study heterogeneity was removed in the dominant genetic model (dominant model: I2 =33.9%, P=0.182). Furthermore, the result of pooled RR was reversed after excluding this article from the dominant model (dominant model: RR=1.10, 95%CI=1.01-1.19). In the recessive genetic model, the heterogeneity was also removed after excluding the study conducted by “Konstantina Vogiatzi”. There was no statistical evidence of a publication bias (dominant model: p = 0.368 in Begg's test, p = 0.431 in Egger's regression test; recessive model: p =0.548 in Begg's test, p = 0.613 in Egger's regression test) among the studies using Egger's regression test and Begg's test in any of the dominant and recessive models. Discussion Several epidemiological studies have suggested a link between CCR5 and RANTES genetic variants and the risk of developing CAD. However, due to the small sample size and insufficient power of previous studies, these findings have yielded inconsistent results. This study is the first meta-analysis that has systematically reviewed the genetic effect of CCR5 and its ligand RANTES on the risk of CAD. We focused on two major gene variants, CCR5Δ32 and RANTES-403 G/A, and provided the most comprehensive assessment of these polymorphisms to date (Figs. 2–7). In this meta-analysis, we included a total of 10 publications regarding the CCR5Δ32 polymorphism and the risk of CAD, which provided a total of 4537 patients and 3041 controls. The primary pooled
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Table 3 Results of the meta-analysis for the RANTES-403 G/A polymorphism and subgroup analysis under dominant and recessive models. Study group
Overall 1.ethnicity Caucasian non-Caucasian 2.Sample size for patient >200 b200 3.HWE yes no
Study
Sample size
Dominant
Dominant
Recessive
Recessive
(n)
(case/control)
RR(95%CI)
P
RR(95%CI)
p
7
4631/2055
1.05(0.92-1.21)
0.000
1.12(0.79-1.60)
0.050
4 3
3671/1336 906/719
1.14(1.04-1.25) 0.88(0.81-0.95)
0.506 0.770
1.54(0.79-2.97) 0.90(0.62-1.31)
0.053 0.225
4 3
4086/1609 545/446
1.05(0.86-1.28) 0.99(0.86-1.12)
0.000 0.362
1.02(0.76-1.36) 1.76(0.48-6.48)
0.254 0.012
5 2
2940/679 1691/1376
0.96(0.85-1.09) 1.18(1.04-1.32)
0.057 0.685
RRs showed that CAD risk was not related to the CCR5Δ32 polymorphism. However, because of the high heterogeneity under the dominant model, were not able to determine a definitive conclusion. Therefore, we conducted a subgroup analysis to identify the source of the heterogeneity. Because ethnicity and population composition may strongly influence the prevalence of a gene polymorphism, we first performed a subgroup analysis by ethnicity to explore the source of heterogeneity. These results showed that heterogeneity was only removed in the non-caucasian group. However, due to the obvious ethnicity differences in this group, the results were unclear, and suggested that race bias may not affect the prevalence of the CCR5 Δ32 polymorphism. CAD has a complex etiology and pathophysiology generated by the combined effects of genes and environmental factors. Among them, age is one of the more important factors. Therefore, we performed a subgroup analysis by mean age level. The heterogeneity of CCR5Δ32 was removed in the group with a mean age over 50 years. Some studies have suggested that the CCR5Δ32 genotype increases in older people [23,24], but in our meta-analysis it seems that age as a “genes and environment factor” is a source of heterogeneity in CCR5Δ32. However, in the population group with a mean age over 50 years, the pooled effect also suggested no relationship between the CCR5Δ32 polymorphism and CAD risk. Considering that the quality of studies may influence the result, we further performed subgourp analyses by HWE and sample size. We failed to remove the heterogeneity by excluding three articles that
1.08(0.74-1.57) 2.49 (0.22-28.14))
0.129 0.018
deviated from the HWE; however, when we performed the subgroup analysis by sample size, we found that heterogeneity still existed when the sample size was small, but was removed as the sample size increased. This result suggested that the sample size for patients may be a factor that partly contributes to heterogeneity. Some studies have indicated the existence of a phenomenon known as “winner's curse” [25], but in this meta-analysis, no relationship between CCR5Δ32 and CAD risk was found regardless of the sample size. However, a recent study demonstrated that the CCR5Δ32 polymorphism influenced the risk of cardiovascular disease among patients with rheumatoid arthritis (RA) [26]. This suggests that other diseases patients suffered from may affect the relationship between the CCR5Δ32 polymorphism and risk of CAD. Therefore, other diseases may be important source of heterogeneity. However, lack of raw data limited us to perform subgroup analyses. We also performed a meta-analysis to explore the association between the RANTES-403 G/A polymorphism and CAD risk. A total of seven studies containing 4577 patients and 2050 controls were included. Our meta-analysis did not find an association between the RANTES-403 G/A polymorphism and CAD risk. However, according to the result of the sensitivity analysis, after excluding the study conducted by “Yangsoo”, the pooled effect and between-study heterogeneity were reversed in the dominant model. The findings suggested that RANTES-403 G/A is positively associated with CAD risk. Based on the influence of population composition, we performed a subgroup analysis by ethnicity. However, unlike the CCR5Δ32 polymorphism,
Fig. 2. Meta-analysis of studies of the CCR5Δ32 polymorphism in the dominant model.
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Fig. 3. Meta-analysis of the studies of the CCR5Δ32 polymorphism in the recessive model.
the pooled RRs in the dominant genetic model suggested a positive association between the RANTES-403 G/A polymorphism and CAD risk in the Caucasian population, whereby the heterogeneity is removed. However, in the non-Caucasian group, the pooled RR suggested a negative association between the RANTES-403 G/A polymorphism and risk of CAD. Because only three studies were included in the non-Caucasian studies and significant ethnic differences existed (two studies were conducted in East Asia and one study was conducted in South Asia), this result was unclear. According to the subgroup analysis by ethnicity, we found that the RANTES-403 G/A polymorphism increases the incidence of CAD in the Caucasian population. It has been reported that a higher frequency of this A allele occurs in individuals of African descent compared to Caucasian subjects [19]. In addition, the frequency of the A allele in the Caucasian population (case group: mean=0.208, range=0.192-0.284; control group: mean=0.180, range=0.1640.225) was significantly lower than that in the non-Caucasian population (case group: mean=0.337, range=0.233-0.367; control group: mean= 0.360, range=0.230-0.422). Such heterogeneous genetic backgrounds
might be, in part, responsible for the heterogeneity of effect on the disease across the ethnicity. However, given the limited numbers of studies, additional studies are needed to fully understand the relationship between ethinicity and this gene polymorphism. We also performed a subgroup analysis by HWE and patient sample size, and neither variable was found to be important sources of heterogeneity. However, when we eliminated the study conducted by Yangsoo et al., the,heterogeneity disappeared in the subgroup of studies with a sample size over 200. Moreover, a positive relationship between RANTES-403 G/A and CAD risk was also found. Interestingly, a study have shown the RANTES-403 G/A polymorphism increased the risk of rheumatoid arthritis (RA) which is a a complex autoimmune polygenic disease associated with accelerated atherosclerosis [27,28]. So it is likely that RANTES-403 G/A polymorphism may increase the risk of CAD via affecting immune system. It is worthy to note that the genotyping method of the study conducted by Yangsoo et al. was Taqman-PCR, while the others were PCR-RFLP (five studies) and PCR-SSP (one study). Several studies have
Fig. 4. Meta-analysis of the RANTES-403 G/A polymorphism in the dominant model.
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Fig. 5. Meta-analysis of the RANTES-403 G/A polymorphism in the recessive model.
suggested that the genotyping method will influence analyses of gene polymorphisms, and no genotyping method is 100% accurate [29,30]. Our meta-analysis also suggested that the genotyping method may affect the result, and therefore further improvements in existing genotyping technologies as well as the development of new methods are necessary. As mentioned above, CAD is a complex etiology generated by the combined effect of environmental risk factors, and other variants in these two described genes as well as other genes in the chemokine superfamily may have important genetic effects on CAD risk [18,31]. A comprehensive study concerning the multiple loci will help us to clarify the role of chemokines in CAD. In vitro studies using transient transfections of the human mast cell line HMC-1 and T cell line Jurkat with reporter vectors driven by ether the mutant or wild-type RANTES promoter have shown up to an 8-fold higher constitutive transcriptional activity of the mutant promoter [19]. Moreover, a comparison of RANTES
mRNA expression in patients with different RANTES-403 G/A polymorphisms has shown that patients carrying the AA genotype RANTES mRNA expression had a 1.74-fold increase in expression compared to patients carrying the GG genotype and a 1.51-fold increase in expression compared to patients carrying GA genotype [32]. Furthermore, several recent studies have shown that the RANTES-403 G/A polymorphism is related to a high level of circulating RANTES [33], and higher RANTES serum level increases CAD risk [34,35]. However, not all studies have concluded the same result [36,37]. Therefore, a comprehensive metaanalysis concerning RANTES serum levels, which would provide a more reliable result about the links between RANTES and CAD risk, are necessary. Some limitations should be considered in our meta-analysis. First, heterogeneity is a potential problem when interpreting the results of a meta-analysis. Medication data, angiographic data, and other conventional CAD risk factors should be considered as probable causes
Fig. 6. Subgroup analysis of RANTES-403 G/A polymorphism by ethnicity in the dominant model.
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Fig. 7. Sensitivity analysis of studies of the RANTES-403 G/A polymorphism in the dominant model.
for heterogeneity of the included studies. However, the lack of all individual raw data from previous studies has restricted further adjustments of the associated results by other co-variants, including age, obesity, cigarette smoking, and other lifestyle choices. Incomplete information may attenuate the power of our meta-analysis. Second, most studies have been conducted in Caucasian populations and the number of studies regarding other ethnicities is limited. Therefore, the race bias has been underestimated. Third, the conclusions from the RANTES-403 G/A polymorphism were only obtained in a dominant genetic model. Nevertheless, our meta-analysis provides pooled data on a substantial number of cases and controls for a better understanding of the association between the CCR5Δ32 polymorphism and CAD risk. Moreover, we have also provided a understanding of the association between the RANTES-403 G/A polymorphism and CAD risk. In summary, our meta-analysis of 15 studies found no evidence for an association between the CCR5Δ32 polymorphism and CAD risk or the RANTES-403 G/A polymorphism and CAD risk. However, the RANTES-403 G/A polymorphism was found to be associated with an increased risk of developing CAD in the Causcasian population. Furthermore, different genotyping methods may affect the results of these studies. Studies with a larger sample size and multi-ethnic patient population, particularly Asian and African patients, are needed in the future. Conflict of interest statement None. Acknowledgement We thank Medjaden Bioscience Limited for assisting in the preparation of this manuscript. References [1] Sanz J, Fayad ZA. Imaging of atherosclerotic cardiovascular disease. Nature 2008;451:953-7. [2] Libby P, Theroux P. Pathophysiology of coronary artery disease. Circulation 2005;111:3481-8. [3] Weber C, Noels H. Atherosclerosis: current pathogenesis and therapeutic options. Nat Med 2011;17:1410-22. [4] Pattison JM, Nelson PJ, Huie P, Sibley RK, Krensky AM. RANTES chemokine expression in transplant-associated accelerated atherosclerosis. J Heart Lung Transplant 1996;15:1194-9. [5] Reape TJ, Groot PH. Chemokines and atherosclerosis. Atherosclerosis 1999;147: 213-25.
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Involvement of polymorphisms in the chemokine system in the susceptibility for coronary artery disease (CAD). Coincidence of elevated Lp(a) and MCP-1–2518 G/G genotype in CAD patients. Atherosclerosis 2001;158:233-9. [19] Nickel RG, Casolaro V, Wahn U, Beyer K, Barnes KC, Plunkett BS, et al. Atopic dermatitis is associated with a functional mutation in the promoter of the C-C chemokine RANTES. J Immunol 2000;164:1612-6. [20] Sharda S, Gilmour A, Harris V, Singh VP, Sinha N, Tewari S, et al. Chemokine receptor 5 (CCR5) deletion polymorphism in North Indian patients with coronary artery disease. Int J Cardiol 2008;124:254-8. [21] Ghilardi G, Biondi ML, Turri O, Pateri F, d'Eril GM, Scorza R. Genetic control of chemokines in severe human internal carotid artery stenosis. Cytokine 2008;41: 24-8. [22] Tereshchenko IP, Petrkova J, Voevoda MI, Taborsky M, Navratilova Z, Romaschenko AG, et al. CCL5/RANTES gene polymorphisms in Slavonic patients with myocardial infarction. 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Thrombosis Research journal homepage: www.elsevier.com/locate/thromres
Regular Article
Association of the CCR5Δ32 polymorphism and its ligand RANTES-403 G/A polymorphism with coronary artery disease: A meta-analysis Lihan Wang, Xinyang Hu, Shoude Zhang, Xin Xu, Jianan Wang ⁎ Cardiovascular key lab of Zhejiang Province, the second affiliated hospital, school of medicine, Zhejiang University, Hangzhou 310009, China
a r t i c l e
i n f o
Article history: Received 11 June 2012 Received in revised form 17 July 2012 Accepted 27 July 2012 Available online 9 January 2013 Keywords: CCR5Δ32 RANTES-403 G/A Gene polymorphism Coronary artery disease Meta-analysis
a b s t r a c t Introduction: To explore the relationship between polymorphisms in the RANTES and CCR5 genes and the risk of coronary artery disease (CAD). Materials and Methods: We conducted a meta-analysis on two genetic variants (RANTES-403 G/A and CCR5Δ32). Publication bias was tested by the Egger's regression test and Begg's test. Sensitivity analysis and subgroup analyses were performed to explore the heterogeneity among studies. Results: No significant association of RANTES-403 G/A polymorphism and CAD risk was observed (dominant model: RR = 1.02, 95%CI = 0.90-1.06; recessive model: RR = 1.27, 95%CI = 0.90-1.80). However, after excluding the study conducted by Yangsoo et al., the pooled relative ratio (RR) in the dominant model suggested that the RANTES-403 G/A polymorphism was positively associated with CAD risk. The subgroup analyses found that a positive relationship between the polymorphism and CAD risk was restricted to the Caucasian population. A meta-analysis of studies on the CCR5Δ32 polymorphism showed no significant association with CAD risk both in dominant (RR=1.05, 95%CI =0.92-1.21) and recessive (RR =1.27, 95%CI= 0.90-1.80) models. Moreover, no association was identified in the subgroup analyses. Conclusions: The RANTES-403 G/A polymorphism is not associated with CAD risk, but does most likely increase CAD risk in Caucasians. Moreover, no relationship between the CCR5Δ32 polymorphism and risk of CAD was found. © 2012 Published by Elsevier Ltd.
Introduction Coronary artery disease (CAD) is the leading risk factor for death and disability in the world [1]. The underlying pathology of CAD has been recognized as atherosclerosis, which is a chronic inflammatory lesion affecting large and medium elastic and muscular arteries [2]. Chemokines and their receptors have been increasingly recognized as key mediators in the pathology of atherosclerosis [3]. Among these mediators, Regulated upon Activation, Normal T-cell Expressed, and secreted (RANTES), also known as Chemokine (C-C motif) ligand 5 (CCL5), is a critical regulator in this process. RANTES belongs to the C-C motif chemokine family and is mainly produced by CD8+ T cells, epithelial cells, fibroblasts, and platelets. In atherosclerotic plaques, RANTES expression is up-regulated [4–6]. CCR5 is one of the receptors of RANTES and belongs to the super family of the seven-transmembrane G-protein coupled receptors (GPCRs). It is predominantly expressed on T cells, macrophages, dendritic cells, and microglia. Importantly, studies have found that inflammatory leukocytes are recruited into the endothelium upon RANTES-CCR5 interaction and mediate the process of atherosclerosis. Increasingly evidence has shown that the down-regulation of RANTES or CCR5 can reduce the incidence of atherosclerotic lesions ⁎ Corresponding author at: Postal: 310009. Tel./fax: +86 571 13805786328. E-mail address: [email protected] (J. Wang). 0049-3848/$ – see front matter © 2012 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.thromres.2012.07.024
[7–9] and can improve the prognosis of patients with myocardial infarction [10–12]. Interestingly, some gene mutations affect the expression of CCR5 and RANTES, among which the CCR5Δ32 polymorphism and RANTES-403 G/A polymorphism are the most commonly studied. The CCR5Δ32 polymorphism is defined by a 32 bp deletion that leads to a truncated nonfunctional receptor [13]. This abnormal receptor is eliminated from the cell surface in homozygous individuals and down-regulated by 20%–30% in heterozygous patients [14]. Furthermore, according to some epidemiological studies, the CCR5Δ32 polymorphism reduces the risk of CAD [15–18]. RANTES-403 G/A refers to a transition (G > A) in the promoter region of the RANTES gene, which enhances the transcriptional activity [19] and increases the risk of CAD [6]. However, the relationship between these mutations and the risk of developing CAD has not been replicated in other studies [18,20–22]. To help clarify the inconsistent findings, we conducted a meta-analysis of the published genetic association studies of these two polymorphisms and the risk of CAD. Materials and methods Search strategy and inclusion criteria We sought genetic association studies published before February 2012 on CAD and the Δ32 variant in the CCR5 gene or -403 G/A
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variant in the RANTES gene. We systematically searched Pubmed, Embase, Web of Science, and a reference list of relevant papers using the term “CCR5”, “RANTES”, or “CCL5” paired with “coronary artery disease”, “coronary heart disease”, “atherosclerosis”, “ischemic heart disease”, “myocardial infarction”, and “genetic variant” or “polymorphism”, respectively. We also manually screened the reference lists of the retrieved articles to identify other relevant publications. The inclusion criteria were (1) studies on the relationship between the CCR5Δ32 polymorphism, RANTES-403 G/A polymorphism, and CAD; (2) published case–control studies; (3) cohort studies; (4) studies published as full-length articles in English; (5)and studies with sufficient data for estimating a relative ratio (RR) with 95% confidence interval (CI). Data extraction Two investigators independently extracted data (Wang and Zhang) and discrepancies were resolved by group discussion. For each study, the following information was extracted: name of the first author, year of publication, ethnic origin of the studied population, number in case (exposed) and control (unexposed) groups, genotype and allele distributions, male percentage, mean ages in case (exposed) and control (unexposed) groups, genotyping method, and Hardy-Weinberg equilibrium in case and control groups. If multiple published reports from the same study population were available, we included only the one with the largest sample size and complete data. Statistical analysis The Hardy-Weinberg equilibrium (HWE) was tested by the X 2 test. The strength of association was estimated as RR and 95% confidence intervals (CIs). For both polymorphisms, the statistical analysis was performed under both the dominant (Δ32, wt/Δ32 + Δ32/Δ32 vs. wt/wt; -403 G/A, GA + AA vs. GG) genetic model and recessive (Δ32, Δ32/Δ32 vs. wt/Δ32 + wt/wt; -403 G/A, AA vs. GA + GG) genetic model. The RRs were pooled through a random effects model, using the M-H heterogeneity approach when heterogeneity existed among these studies. Otherwise, a fixed effects model was adopted. Heterogeneity between studies was assessed by the Q-test an I 2 statistic, where p b 0.10 and I 2 > 50% indicated evidence of heterogeneity. In order to investigate the probable source of heterogeneity, a subgroup analysis were performed according to ethnicity, mean age level, sample size for patients (>300, 200–300, and b 200), and status of HWE (yes or no). Sensitivity analysis was performed by excluding each individual study at a time from the total and reanalyzing the remainder to examine the influence of one study on the overall summary estimate. Publication bias was assessed with funnel plots, the Egger regression test, and Begg's test. Data of the meta-analysis were analysed using Stata software (version 10.0; Stata Corporation, College Station, TX). All P values were for a two-sided analysis and values of P b 0.05 were considered statistically significant. Results Study characteristics The study selection process is detailed in Fig. 1. Based on our preliminary search criteria, a total of 18 publications were eligible. Among these articles, three publications were excluded for the absence of sufficient data for estimating RR and 95%CI. A total of 15 studies with 17 separate association studies were included in the final meta-analysis, including 6123 cases (patients with CAD) and 4241 controls. All studies were case–control in design. For the CCR5Δ32 polymorphism, 10 studies were available (7 Caucasian, 3 non-Caucasian), including 4537 cases (patients with CAD) and 3039 controls. Four studies considered the
Fig. 1. Flow diagram of the article selection process for CCR5Δ32 polymorphism, RANTES-403 G/A polymorphism, and CAD risk.
CCR5Δ32 polymorphism to be a protective factor for CAD, but three studies suggested there was no association between the CCR5Δ32 polymorphism and a risk of developing CAD. Furthermore three studies found an association of the CCR5Δ32 polymorphism and an increased the risk of CAD. For the RANTES-403 G/A, seven studies were available (4 Caucasian, 3 non-Caucasian), including 4577 cases (patients with CAD) and 2055 controls. Table 1 shows the main characteristics of these studies. Meta-analysis results The relationship between CCR5Δ32 and CAD A random effects model was used under a dominant genetic model because of statistical heterogeneity across the studies (I 2 = 65.8%; P = 0.002) (Table 2). Under a recessive genetic model, the fixed effects model was adopted, as no heterogeneity was observed among the studies (I2 = 34.6%; P= 0.164). Under this model, three studies had zero patients with the GG genotypes among case and control subjects, and therefore they were excluded from the analysis. When all 10 studies were pooled into the meta-analysis, there was no evidence of an association between the CCR5Δ32 polymorphism and CAD risk (for the dominant model: the pooled RR was 1.05, 95%CI: 0.81-1.34, I2 = 65.8%, P= 0.002; for the recessive model: the pooled RR was 0.84, 95%CI: 0.38-1.88, I 2 = 34.6%, P= 0.164). For further assessment, we performed a subgroup analysis to investigate the source of the heterogeneity. The results suggested that ethnicity, mean age level, and patient sample size were associated with heterogeneity. In the dominant genetic model, the sensitivity analysis found no evidence of any individual study having excessive influence on the pooled effect and between-study heterogeneity. Overall, the Egger's regression test and Begg's test demonstrated that no statistically significant publication bias (dominant model: p = 0.858 in Begg's test, p =0.416 in Egger's regression test; recessive model: p = 1.000 in Begg's test, p = 0.775 in Egger's regression test) was present in any of the dominant and recessive models. The relationship between RANTES-403 G/A polymorphism and CAD risk We chose a random effects model to investigate the relationship between the RANTES-403 G/A polymorphism and CAD risk under the dominant and recessive genetic models (dominant model: I2 = 72.4%, p = 0.001; recessive model: I2 = 52.4%, p = 0.050) (Table 3). When all seven studies were pooled into the meta-analysis, there was no evidence of an association between the RANTES-403 G/A polymorphism
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Table 1 Main characteristics of the studies included in the meta-analysis. Reference
Year
Ethnicity
Subjects, n Cases/ controls
Ten studies for the CCR5Δ32 polymorphism J . Petrkova [38] 2005 Caucasian
80/247
Mean age, y Cases/ controls
Genotyping method
End point of assessment
Gender component in Cases/ controls(%male)
Test for HWE
b55/NA
PCR-SSP
MI
100/100
1.758 0.185 0.021 0.884 30.456 0.000 1.589 0.207 0.491 0.484 0.196 0.658 0.011 0.915 19.042 0.000 0.631 0.427 0.006 0.939
Neha [39]
2011
South Asian
230/300
49.97/44.93
PCR
MI
85/85.2
Carmela [15]
2008
Caucasian
133/(136 + 123)
b45/(b45/>100)
PCR
MI
NA/(NA/NA)
P Gonza [16]
2001
Caucasian
(214 + 96)/360
(45/65)/42
PCR
MI
(NA/NA)NA
Jennifer [17]
2005
Caucasian
232/459
60.6/60.3
Taqman
CAD
0/0 (all female)
Stavros [40]
2005
Caucasian
210/165
63.7/63.2
PCR
CAD
77.6/76.4
S. Sharda [20]
2006
South Asian
197/199
47.31/44.58
PCR
CAD
84.26/81.40
Zeynep [41]
2009
West Asian
146/202
56.38/54.2
PCR
MI
60.4/59.4
Csaba [18]
2000
Caucasian
318/320
57.6/58.9
PCR
CAD
76.1/75
Eleonora [6]
2003
Caucasian
2694/530
63.8/56.9
PCR
CAD
73.9/51.3
Seven studies for the RANTES-403 G/A polymorphism Eleonora [6] 2003 Caucasian 2694/530
63.8/56.9
RFLP
CAD
73.9/51.3
Konstantina [42]
2008
Caucasian
192/149
64/62
RFLP
CAD
89.1/71.1
Sungha [43]
2007
East Asian
170/170
62.2/62.6
RFLP
MI
67.059/75.882
Csaba [18]
2000
Caucasian
318/320
57.6/58.9
RFLP
CAD
76.1/75
Javad [32]
2011
West Asian
191/128
NA/NA
RFLP
CAD
60.4/68.5
Irina [22]
2011
Caucasian
467/337
SSP
MI
Yangsoo [44]
2007
East Asian
553/416
RU:56.6/43.6 CZ:55.0/35.7 54.8/53.8
Taqman
CAD
RU: 83.41/62.14 CZ: 68.44/44.16 100/100
and CAD risk (dominant model: RR= 1.02, 95%CI =0.90-1.16; recessive model: RR= 1.12, 95%CI= 0.79-1.60). However, when we performed a sub-group analysis by ethnicity, there was a weak association between the RANTES-403 G/A polymorphism and CAD risk using the dominant genetic model, and the heterogeneity was removed (Caucasian: RR=1.16, 95%CI: 1.05-1.27, P= 0.379; non-Caucasian: RR =0.98, 95%CI: 0.81-0.95; P=0.770). We also performed a subgroup analysis by sample size for patients and HWE; however, these variables were Table 2 Meta-analysis of the effect of the CCR5Δ32 polymorphism on the risk of CAD and subgroup analysis under a dominant model. Study group
Overall Subgroup analysis 1.ethnicity Caucasian non-Caucasian 2.Sample size for patients >300 200-300 b200 3.Mean age level >50 b50 4.HWE yes no
Study
Sample size
RR (95%CI)
P
(n)
(case/controls)
10
4537/3039
1.05(0.81-1.34)
0.002
7 3
3964/2338 573/701
0.94(0.83-1.07) 2.07(1.39-3.08)
0.036 0.472
3 3 4
3309/1208 672/924 556/907
0.96(0.77-1.20) 1.26(0.68-2.32) 1.04(0.78-1.04)
0.157 0.084 0.001
5 4
3587/1675 774/1075
1.08(0.94-1.23) 0.70(0.48-1.02)
0.201 0.000
7 3
3940/2258 597/781
1.05(0.83-1.34) 0.78(0.33-1.84)
0.088 0.000
X2 p
4.799 0.028 9.427 0.002 1.519 0.218 1.135 0.287 0.804 0.370 0.022 0.883 0.659 0.417
not found to be an important source of heterogeneity. The sensitivity analysis suggested that after excluding the article conducted by Yangsoo et al., the between-study heterogeneity was removed in the dominant genetic model (dominant model: I2 =33.9%, P=0.182). Furthermore, the result of pooled RR was reversed after excluding this article from the dominant model (dominant model: RR=1.10, 95%CI=1.01-1.19). In the recessive genetic model, the heterogeneity was also removed after excluding the study conducted by “Konstantina Vogiatzi”. There was no statistical evidence of a publication bias (dominant model: p = 0.368 in Begg's test, p = 0.431 in Egger's regression test; recessive model: p =0.548 in Begg's test, p = 0.613 in Egger's regression test) among the studies using Egger's regression test and Begg's test in any of the dominant and recessive models. Discussion Several epidemiological studies have suggested a link between CCR5 and RANTES genetic variants and the risk of developing CAD. However, due to the small sample size and insufficient power of previous studies, these findings have yielded inconsistent results. This study is the first meta-analysis that has systematically reviewed the genetic effect of CCR5 and its ligand RANTES on the risk of CAD. We focused on two major gene variants, CCR5Δ32 and RANTES-403 G/A, and provided the most comprehensive assessment of these polymorphisms to date (Figs. 2–7). In this meta-analysis, we included a total of 10 publications regarding the CCR5Δ32 polymorphism and the risk of CAD, which provided a total of 4537 patients and 3041 controls. The primary pooled
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Table 3 Results of the meta-analysis for the RANTES-403 G/A polymorphism and subgroup analysis under dominant and recessive models. Study group
Overall 1.ethnicity Caucasian non-Caucasian 2.Sample size for patient >200 b200 3.HWE yes no
Study
Sample size
Dominant
Dominant
Recessive
Recessive
(n)
(case/control)
RR(95%CI)
P
RR(95%CI)
p
7
4631/2055
1.05(0.92-1.21)
0.000
1.12(0.79-1.60)
0.050
4 3
3671/1336 906/719
1.14(1.04-1.25) 0.88(0.81-0.95)
0.506 0.770
1.54(0.79-2.97) 0.90(0.62-1.31)
0.053 0.225
4 3
4086/1609 545/446
1.05(0.86-1.28) 0.99(0.86-1.12)
0.000 0.362
1.02(0.76-1.36) 1.76(0.48-6.48)
0.254 0.012
5 2
2940/679 1691/1376
0.96(0.85-1.09) 1.18(1.04-1.32)
0.057 0.685
RRs showed that CAD risk was not related to the CCR5Δ32 polymorphism. However, because of the high heterogeneity under the dominant model, were not able to determine a definitive conclusion. Therefore, we conducted a subgroup analysis to identify the source of the heterogeneity. Because ethnicity and population composition may strongly influence the prevalence of a gene polymorphism, we first performed a subgroup analysis by ethnicity to explore the source of heterogeneity. These results showed that heterogeneity was only removed in the non-caucasian group. However, due to the obvious ethnicity differences in this group, the results were unclear, and suggested that race bias may not affect the prevalence of the CCR5 Δ32 polymorphism. CAD has a complex etiology and pathophysiology generated by the combined effects of genes and environmental factors. Among them, age is one of the more important factors. Therefore, we performed a subgroup analysis by mean age level. The heterogeneity of CCR5Δ32 was removed in the group with a mean age over 50 years. Some studies have suggested that the CCR5Δ32 genotype increases in older people [23,24], but in our meta-analysis it seems that age as a “genes and environment factor” is a source of heterogeneity in CCR5Δ32. However, in the population group with a mean age over 50 years, the pooled effect also suggested no relationship between the CCR5Δ32 polymorphism and CAD risk. Considering that the quality of studies may influence the result, we further performed subgourp analyses by HWE and sample size. We failed to remove the heterogeneity by excluding three articles that
1.08(0.74-1.57) 2.49 (0.22-28.14))
0.129 0.018
deviated from the HWE; however, when we performed the subgroup analysis by sample size, we found that heterogeneity still existed when the sample size was small, but was removed as the sample size increased. This result suggested that the sample size for patients may be a factor that partly contributes to heterogeneity. Some studies have indicated the existence of a phenomenon known as “winner's curse” [25], but in this meta-analysis, no relationship between CCR5Δ32 and CAD risk was found regardless of the sample size. However, a recent study demonstrated that the CCR5Δ32 polymorphism influenced the risk of cardiovascular disease among patients with rheumatoid arthritis (RA) [26]. This suggests that other diseases patients suffered from may affect the relationship between the CCR5Δ32 polymorphism and risk of CAD. Therefore, other diseases may be important source of heterogeneity. However, lack of raw data limited us to perform subgroup analyses. We also performed a meta-analysis to explore the association between the RANTES-403 G/A polymorphism and CAD risk. A total of seven studies containing 4577 patients and 2050 controls were included. Our meta-analysis did not find an association between the RANTES-403 G/A polymorphism and CAD risk. However, according to the result of the sensitivity analysis, after excluding the study conducted by “Yangsoo”, the pooled effect and between-study heterogeneity were reversed in the dominant model. The findings suggested that RANTES-403 G/A is positively associated with CAD risk. Based on the influence of population composition, we performed a subgroup analysis by ethnicity. However, unlike the CCR5Δ32 polymorphism,
Fig. 2. Meta-analysis of studies of the CCR5Δ32 polymorphism in the dominant model.
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Fig. 3. Meta-analysis of the studies of the CCR5Δ32 polymorphism in the recessive model.
the pooled RRs in the dominant genetic model suggested a positive association between the RANTES-403 G/A polymorphism and CAD risk in the Caucasian population, whereby the heterogeneity is removed. However, in the non-Caucasian group, the pooled RR suggested a negative association between the RANTES-403 G/A polymorphism and risk of CAD. Because only three studies were included in the non-Caucasian studies and significant ethnic differences existed (two studies were conducted in East Asia and one study was conducted in South Asia), this result was unclear. According to the subgroup analysis by ethnicity, we found that the RANTES-403 G/A polymorphism increases the incidence of CAD in the Caucasian population. It has been reported that a higher frequency of this A allele occurs in individuals of African descent compared to Caucasian subjects [19]. In addition, the frequency of the A allele in the Caucasian population (case group: mean=0.208, range=0.192-0.284; control group: mean=0.180, range=0.1640.225) was significantly lower than that in the non-Caucasian population (case group: mean=0.337, range=0.233-0.367; control group: mean= 0.360, range=0.230-0.422). Such heterogeneous genetic backgrounds
might be, in part, responsible for the heterogeneity of effect on the disease across the ethnicity. However, given the limited numbers of studies, additional studies are needed to fully understand the relationship between ethinicity and this gene polymorphism. We also performed a subgroup analysis by HWE and patient sample size, and neither variable was found to be important sources of heterogeneity. However, when we eliminated the study conducted by Yangsoo et al., the,heterogeneity disappeared in the subgroup of studies with a sample size over 200. Moreover, a positive relationship between RANTES-403 G/A and CAD risk was also found. Interestingly, a study have shown the RANTES-403 G/A polymorphism increased the risk of rheumatoid arthritis (RA) which is a a complex autoimmune polygenic disease associated with accelerated atherosclerosis [27,28]. So it is likely that RANTES-403 G/A polymorphism may increase the risk of CAD via affecting immune system. It is worthy to note that the genotyping method of the study conducted by Yangsoo et al. was Taqman-PCR, while the others were PCR-RFLP (five studies) and PCR-SSP (one study). Several studies have
Fig. 4. Meta-analysis of the RANTES-403 G/A polymorphism in the dominant model.
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Fig. 5. Meta-analysis of the RANTES-403 G/A polymorphism in the recessive model.
suggested that the genotyping method will influence analyses of gene polymorphisms, and no genotyping method is 100% accurate [29,30]. Our meta-analysis also suggested that the genotyping method may affect the result, and therefore further improvements in existing genotyping technologies as well as the development of new methods are necessary. As mentioned above, CAD is a complex etiology generated by the combined effect of environmental risk factors, and other variants in these two described genes as well as other genes in the chemokine superfamily may have important genetic effects on CAD risk [18,31]. A comprehensive study concerning the multiple loci will help us to clarify the role of chemokines in CAD. In vitro studies using transient transfections of the human mast cell line HMC-1 and T cell line Jurkat with reporter vectors driven by ether the mutant or wild-type RANTES promoter have shown up to an 8-fold higher constitutive transcriptional activity of the mutant promoter [19]. Moreover, a comparison of RANTES
mRNA expression in patients with different RANTES-403 G/A polymorphisms has shown that patients carrying the AA genotype RANTES mRNA expression had a 1.74-fold increase in expression compared to patients carrying the GG genotype and a 1.51-fold increase in expression compared to patients carrying GA genotype [32]. Furthermore, several recent studies have shown that the RANTES-403 G/A polymorphism is related to a high level of circulating RANTES [33], and higher RANTES serum level increases CAD risk [34,35]. However, not all studies have concluded the same result [36,37]. Therefore, a comprehensive metaanalysis concerning RANTES serum levels, which would provide a more reliable result about the links between RANTES and CAD risk, are necessary. Some limitations should be considered in our meta-analysis. First, heterogeneity is a potential problem when interpreting the results of a meta-analysis. Medication data, angiographic data, and other conventional CAD risk factors should be considered as probable causes
Fig. 6. Subgroup analysis of RANTES-403 G/A polymorphism by ethnicity in the dominant model.
L. Wang et al. / Thrombosis Research 131 (2013) e77–e84
Fig. 7. Sensitivity analysis of studies of the RANTES-403 G/A polymorphism in the dominant model.
for heterogeneity of the included studies. However, the lack of all individual raw data from previous studies has restricted further adjustments of the associated results by other co-variants, including age, obesity, cigarette smoking, and other lifestyle choices. Incomplete information may attenuate the power of our meta-analysis. Second, most studies have been conducted in Caucasian populations and the number of studies regarding other ethnicities is limited. Therefore, the race bias has been underestimated. Third, the conclusions from the RANTES-403 G/A polymorphism were only obtained in a dominant genetic model. Nevertheless, our meta-analysis provides pooled data on a substantial number of cases and controls for a better understanding of the association between the CCR5Δ32 polymorphism and CAD risk. Moreover, we have also provided a understanding of the association between the RANTES-403 G/A polymorphism and CAD risk. In summary, our meta-analysis of 15 studies found no evidence for an association between the CCR5Δ32 polymorphism and CAD risk or the RANTES-403 G/A polymorphism and CAD risk. However, the RANTES-403 G/A polymorphism was found to be associated with an increased risk of developing CAD in the Causcasian population. Furthermore, different genotyping methods may affect the results of these studies. Studies with a larger sample size and multi-ethnic patient population, particularly Asian and African patients, are needed in the future. Conflict of interest statement None. Acknowledgement We thank Medjaden Bioscience Limited for assisting in the preparation of this manuscript. References [1] Sanz J, Fayad ZA. Imaging of atherosclerotic cardiovascular disease. Nature 2008;451:953-7. [2] Libby P, Theroux P. Pathophysiology of coronary artery disease. Circulation 2005;111:3481-8. [3] Weber C, Noels H. Atherosclerosis: current pathogenesis and therapeutic options. Nat Med 2011;17:1410-22. [4] Pattison JM, Nelson PJ, Huie P, Sibley RK, Krensky AM. RANTES chemokine expression in transplant-associated accelerated atherosclerosis. J Heart Lung Transplant 1996;15:1194-9. [5] Reape TJ, Groot PH. Chemokines and atherosclerosis. Atherosclerosis 1999;147: 213-25.
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