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. 2015 Feb 15;8(2):1715–1725.

Association between phosphodiesterase 4D (PDE4D) SNP 87 and ischemic stroke: a meta-analysis

Wenzhao Liang 1,*, Dezhi Zhang 2,*, Jing Mang 1, Jinting He 1, Hongyu Liu 1, Yankun Shao 1, Fanglei Han 3, Zhongxin Xu 1
PMCID: PMC4402747  PMID: 25932100

Abstract

Background and purpose: Data on the association between PDE4D SNP 87 and the risk of ischemic stroke are contentious and debatable. The present meta-analysis was undertaken to systematically summarize the possible association. Methods: Based on comprehensive search of PubMed, Embase, and CNKI databases, we identified 18 eligible articles examining the relationship between PDE4D SNP 87 and ischemic stroke risk. We evaluated the strength of relationship using odds ratios (ORs) with 95% confidence intervals (CIs). Results: In the overall analysis, PDE4D SNP 87 was not found to have effects on the risk of ischemic stroke. The null association persisted in the subgroup analyses according to ethnicity and sample size. Conclusions: Our meta-analysis suggests that PDE4D SNP 87 may not represent an independent risk factor for ischemic stroke development.

Keywords: PDE4D, SNP, ischemic stroke, risk

Introduction

Stroke is a leading cause of death and disability with a high prevalence among old and very old people worldwide [1,2]. There are two subtypes of stroke: hemorrhagic stroke and ischemic stroke [3]. Ischemic stroke characterized by a sudden decrease in blood flow to one or more central nervous system areas constitutes 80% of all strokes. Ischemic stroke is a highly complex disease composed of various heterogeneous disorders attributable to both genetic and environmental factors [4,5]. Experimental evidence demonstrates that genetics should be responsible for a large part of stroke risk [6]. However, the investigations fail to identify candidate genetic factors for the aggressive disease.

Several previous studies of an Icelandic population used a genome-wide approach highlighted the implication of single nucleotide polymorphisms (SNPs) and haplotypes in the 5-lipoxygenase-activating protein (ALOX5AP or FLAP) and phosphodiesterase 4D (PDE4D) genes in ischemic stroke [7,8]. PDE4D located on chromosomal region 5q12 is a very large gene that spans 1.5 Mb and consists of 8 splice variants, 22 exons, and several hundred SNPs [9]. PDE4D belongs to the large superfamily of cyclic nucleotide phosphodiesterases and has been reported to be involved in inflammation [10], cell proliferation [11], and migration [12] that could consequently result in ischemic stroke. A growing body of replicated reports has sought to challenge the preconceived findings of the Icelandic study in diverse populations, showing conflicting results [13-17]. The relatively small studies using participants of different ethnic backgrounds and different analytical methods may be the major sources of the controversy.

Among the numerous SNPs (SNP 26, 45, 56, 83, 87, and 89) of PDE4D gene, SNP 87 (rs2910829) has been extensively investigated in ischemic stroke community [18-21]. However, the efforts did not confirm the susceptibility role of SNP 87 in ischemic stroke. In this study, we hypothetized that SNP 87 was associated with the onset of ischemic stroke. To test this hypothesis, we performed a meta-analysis to re-evaluate the association between SNP 87 and ischemic stroke.

Materials and methods

Identification and eligibility of relevant studies

The genetic association studies concerning the association of SNP 87 and ischemic stroke risk published before March 2014 were identified by comprehensively searching PubMed, Embase and CNKI (China National Knowledge Infrastructure) databases. The following search terms were used: (polymorphism) OR (polymorphisms) AND (phosphodiesterase 4D) OR (PDE4D) OR (SNP 87) OR (rs2910829) AND (ischemic stroke). We reviewed the abstracts of the retrieved studies to examine their appropriateness for inclusion in the meta-analysis. Then, the full texts of the articles were screened in order to check their eligibility for the present study. Finally, all the reference lists of the eligible articles and the journals known to publish articles relevant to the current topic were systematically reviewed to identify additional published articles. The case-control studies provided the genotype distribution of SNP 87 in ischemic stroke risk were eligible for inclusion in the meta-analysis. For studies used the same series of cases, the latest or the largest study was considered. Review articles, comment letters, case reports were excluded from this meta-analysis.

Data extraction

Two reviewers independently gathered the data from each eligible study and reached a consensus on all items. The information required to be collected was: first author, journal, year of publication, study country, ethnicity, gender and mean age of the cases, sample sizes of the cases and controls, genotyping methods and genotype frequencies of SNP87.

Statistical analysis

STATA software (version 12.0) was used for all statistical analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the association of SNP 87 and ischemic stroke risk.

A chi-square-based Q test was used to measure between-study heterogeneity. Statistical significance was defined at P < 0.10. In addition, I2 statistic was calculated to quantify the proportion of the total variation across studies due to heterogeneity (I2 = 0%-25%: no heterogeneity; I2 = 25-50%: moderate heterogeneity; I2 = 50-75%: large heterogeneity; I2 = 75-100%: extreme heterogeneity) [22]. The ORs were pooled using the fixed effects model (the Mantel-Haenszel method) [23] when the P value is above 0.10, and the random effects model (the DerSimonian and Laird method) [24] if P < 0.10. Subgroup analyses by ethnicity (Asian or Caucasian) and sample size (500-1000, < 500, > 1000) were performed to further identify heterogeneity.

Hardy-Weinberg equilibrium (HWE) of the control groups were checked by a Chi-square test. A P-value < 0.10 was considered significant. Sensitivity analysis was carried out to identify the study modifying the summary ORs. Begg’s funnel plots and Egger’s test [25] were used to determine publication bias among the studies included in this meta-analysis. A two-sided P value < 0.10 was considered significant.

Results

Characteristics of studies

A flow diagram of the study selection process for the meta-analysis of SNP 87 and ischemic stroke is described in Figure 1. The original search provided 223 records. After eliminating duplications, 187 records remained. Of these, 161 were discarded after reviewing the abstracts. The full texts of the remaining 26 studies were examined in detail and 8 articles were further excluded according to the criteria for inclusion. Therefore, we identified 18 records [13-21,26-34] with 8,363 cases and 12,223 control subjects for the final meta-analysis, including 7 records for Caucasian descent, and 11 records for Asian descent. All 18 articles were based on a case-control design. The main information and genotype frequencies for SNP 87 for ischemic stroke cases and controls in each of the studies included are summarized in Table 1.

Figure 1.

Figure 1

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Flow chart for primary selection in this meta-analysis.

Table 1.

Main characteristics of all studies included in the meta-analysis

First author Year Population Gender Mean age Genotyping method Sample size Cases Controls HWE
Cases Controls CC CT TT CC CT TT
Gretarsdottir 2003 Caucasian NR NR RT-PCR 642 583 148 315 179 156 290 137 0.921
Bevan 2005 Caucasian F/M 65 ± 12.5 PCR 726 923 154 360 212 214 464 245 0.842
Lohmussaar 2005 Caucasian F/M 65 ± 18.2 MALDI-TOF 598 728 128 296 174 146 366 216 0.688
Saleheen 2005 Asian F/M 62.4 ± 12.4 PCR 170 203 76 57 37 86 78 39 0.007
Woo 2006 Caucasian F/M 69 TaqMan 352 268 80 175 97 58 134 76 0.941
Kuhlenbaumer 2006 Caucasian F/M 66.9 ± 14.6 RT-PCR 1014 1564 216 505 293 353 759 452 0.313
Staton 2006 Caucasian F/M 67.3 ± 11.7 NR 151 164 45 72 34 36 72 56 0.164
Lin 2007 Asian NR NR NR 180 210 120 52 8 149 54 7 0.447
Lovkvist 2008 Caucasian F/M 73.6 RT-PCR 929 394 187 473 269 72 208 114 0.177
Xue 2009 Asian F/M 60.8 ± 9.2 PCR-RFLP 424 887 12 119 293 26 257 604 0.832
Matsushita 2009 Asian F/M 69.6 NR 1092 3847 826 248 18 2840 950 57 0.025
Sun 2009 Asian F/M 73.2 ± 9.4 RT-PCR 646 761 439 182 25 539 202 20 0.837
Hsieh 2009 Asian F/M 70 ± 11 DS 108 280 71 31 6 187 81 12 0.398
Li 2010 Asian F/M 63.88 ± 7.36 PCR-RFLP 371 371 170 117 84 160 141 70 < 0.10
Kalita 2011 Asian F/M 61 PCR 148 188 51 77 20 72 92 24 0.520
Zhang 2012 Asian F/M 59.9 PCR 226 220 157 58 11 129 78 13 0.791
He 2012 Asian F/M 61 ± 10 PCR-RFLP 400 400 276 108 16 286 103 11 0.640
He 2013 Asian F/M 36.5 ± 6.4 PCR-RFLP 186 232 84 82 20 168 58 6 0.712
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F: female; M: male; PCR: polymerase chain reaction; PCR-RFLP: PCR-restriction fragment length polymorphism; RT-PCR: real-time PCR; MALDI-TOF: matrix-assisted laser desorption/ionization time-of-flight; DS: direct sequencing; HWE: Hardy-Weinberg equilibrium.

Quantitative synthesis

Table 2 summarizes for each of the studies the P value for heterogeneity and ORs with 95% CIs for the association between SNP 87 and ischemic stroke risk assuming the homozygote and heterozygote genotypes, the dominant, recessive and allele genetic models. The pooled effect estimates among all studies showed that none of the genetic models were significantly associated with an increased or decreased risk of ischemic stroke. However, a tend to increase ischemic stroke risk was indicated under all of the contrast models, and the tendency was more pronounced under the homozygote genotypes (TT vs.CC, OR, 1.05, 95% CI, 0.97-1.14, fixed-effects), the recessive model (TT vs. CT + CC, OR, 1.05, 95% CI, 0.98-1.13, fixed-effects), and the allele model (T vs. C, OR, 1.03, 95% CI, 0.97-1.09, random-effects). Meanwhile, neither the stratified analyses according to ethnicity nor according to sample size did we find the association of SNP 87 and ischemic stroke was significant (Table 2; Figures 2, 3, 4, 5 and 6).

Table 2.

Meta-analysis results for PDE4D SNP 87 and ischemic stroke risk

Variables (studies) TT vs. CC TT + CT vs. CC TT vs. CT + CC T vs. C CT vs. CC
OR (95% CI) P h I2 OR (95% CI) P h I2 OR (95% CI) P h I2 OR (95% CI) P h I2 OR (95% CI) P h I2
Total (18) 1.05 (0.97, 1.14) 0.292 13.5% 1.01 (0.96, 1.06) 0.293 13.5% 1.05 (0.98, 1.13) 0.417 3.2% 1.03 (0.97, 1.09) 0.015 47.1% 1.00 (0.95, 1.06) 0.425 2.5%
Ethnicity
Caucasian (7) 1.02 (0.92, 1.12) 0.732 0.0% 1.01 (0.94, 1.07) 0.987 0.0% 1.02 (0.93, 1.12) 0.498 0.0% 1.01 (0.96, 1.06) 0.695 0.0% 1.01 (0.93, 1.09) 0.995 0.0%
Asian (11) 1.11 (0.97, 1.28) 0.125 34.2% 1.02 (0.94, 1.10) 0.045 46.3% 1.13 (0.99, 1.28) 0.366 8.2% 1.07 (0.95, 1.21) 0.002 64.0% 1.00 (0.91, 1.09) 0.080 40.3%
Sample size
500-1000 (5) 1.06 (0.94, 1.20) 0.582 0.0% 1.02 (0.95, 1.10) 0.911 0.0% 1.08 (0.96, 1.21) 0.616 0.0% 1.03 (0.97, 1.10) 0.669 0.0% 1.02 (0.93, 1.11) 0.952 0.0%
< 500 (11) 1.05 (0.92, 1.20) 0.081 40.1% 1.02 (0.94, 1.11) 0.067 42.4% 1.05 (0.93, 1.19) 0.158 30.3% 1.05 (0.93, 1.19) 0.002 64.5% 1.01 (0.91, 1.13) 0.118 35.1%
> 1000 (2) 1.03 (0.87, 1.23) 0.847 0.0% 0.98 (0.89, 1.08) 0.369 0.0% 1.01 (0.86, 1.18) 0.708 0.0% 0.99 (0.91, 1.07) 0.393 0.0% 0.97 (0.88, 1.08) 0.322 0.0%
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Ph: p value of heterogeneity test; I2: heterogeneity (%); CI: confidence interval; OR, odds ratio.

Figure 2.

Figure 2

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Forest plot of ischemic stroke risk associated with PDE4D SNP 87 stratified by ethnicity under TT vs. CC model. The boxes and horizontal lines represent the OR and the corresponding 95% CI. The area of the boxes indicates the weight (inverse of the variance). The diamond corresponds to the summary OR and 95% CI.

Figure 3.

Figure 3

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Forest plot of ischemic stroke risk associated with PDE4D SNP 87 stratified by ethnicity under TT + CT vs. CC model. The boxes and horizontal lines represent the OR and the corresponding 95% CI. The area of the boxes indicates the weight (inverse of the variance). The diamond corresponds to the summary OR and 95% CI.

Figure 4.

Figure 4

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Forest plot of ischemic stroke risk associated with PDE4D SNP 87 stratified by ethnicity under TT vs. CT + CC model. The boxes and horizontal lines represent the OR and the corresponding 95% CI. The area of the boxes indicates the weight (inverse of the variance). The diamond corresponds to the summary OR and 95% CI.

Figure 5.

Figure 5

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Forest plot of ischemic stroke risk associated with PDE4D SNP 87 stratified by ethnicity under T vs. C model. The boxes and horizontal lines represent the OR and the corresponding 95% CI. The area of the boxes indicates the weight (inverse of the variance). The diamond corresponds to the summary OR and 95% CI.

Figure 6.

Figure 6

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Forest plot of ischemic stroke risk associated with PDE4D SNP 87 stratified by ethnicity under CT vs. CC model. The boxes and horizontal lines represent the OR and the corresponding 95% CI. The area of the boxes indicates the weight (inverse of the variance). The diamond corresponds to the summary OR and 95% CI.

Test of heterogeneity and sensitivity analysis

No significant heterogeneity was detected under all genetic models except for the allele model (P = 0.015, I2 = 47.1) (Table 2). Subgroup analyses and sensitivity analyses together identified the study by He et al. [34] was the source of the moderate heterogeneity. Excluding this study obviously diminished the heterogeneity and increased the homogeneity among the remaining studies (P = 0.816, I2 = 0.0%). Nonetheless, the corresponding pooled ORs were not quantitatively altered by removing any single study.

Publication bias

Both Begg’s funnel plots and Egger’s test were performed to determine the publication bias of the studies included in this meta-analysis. The shapes of the funnel plot did not indicate obvious asymmetry under any genetic model (Figure 7), and the statistical evidence of Egger’s test suggested no significant publication bias in the meta-analysis (TT vs. CC: P = 0.905).

Figure 7.

Figure 7

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Begg’s funnel plot for PDE4D SNP 87. Log OR is plotted versus standard error of Log OR for each included study. Each circle dot represents a separate study for the indicated association between PDE4D SNP 87 and ischemic stroke risk under TT vs. CC model.

Discussion

PDE4D selectively degrading cyclic AMP that has effects on the vasculature and nervous system has been implicated to play a pivotal role in the etiology of stroke [18,35]. Since the first study addressing the associations of PDE4D SNPs and ischemic stroke risk was reported [18], an increasing body of research has been subsequently published to assess how the PDE4D gene SNPs, especially SNP 87, act in the progress of ischemic stroke [19-21,31-34]. The investigations failed to reach a consensus on the association between PDE4D SNP 87 and the risk of ischemic stroke due to the small sample sizes. This promoted us to conduct the current meta-analysis, in an attempt to assess the controversial association through pooling the data supplied by the eligible studies.

This meta-analysis examined all the available data on the association between PDE4D SNP 87 and ischemic stroke risk, including a total of 8,363 cases and 12,223 control subjects. Although the pooled results showed that SNP 87 was not associated with the risk of ischemic stroke, the trend to an increased risk of developing ischemic stroke was observed. The stratified analyses based on ethnicity and sample size did not suggest any statistical evidence for a significant association.

By comparing the results of the meta-analyses published before and the present study, we found an implication of great interest. The initial meta-analysis published in 2008 investigating six SNPs (SNP 26, 45, 56, 83, 87, and 89) of PDE4D gene suggested that no SNPs examined in PDE4D showed a robust and reproducible association to ischemic stroke [36]. Similar results were observed in a following meta-analysis by Domingues-Montanari and the co-authors [37]. Later, two studies based on 7 datasets and 13 datasets respectively revealed a significant association between PDE4D SNP 83 and ischemic stroke, but not SNP 87 [38,39]. Taken together, a uniformly non-significant association was indicated in the four meta-analyses. However, we could draw an interesting conclusion from the five meta-analyses that the more studies were included, the higher risk of developing ischemic stroke was indicated in the results. This implies that the modification effects of SNP 87 are necessary to be further validated in future larger studies.

Heterogeneity is an important index to evaluate the quality of a meta-analysis. Despite some differences in certain aspects such as study designs, inclusion criteria for participants, sample sizes, and ethnic backgrounds, we only observed moderate between-study heterogeneity for the allele model, but not for the rest of four genetic models. In addition, when we deleted the study resulting in the heterogeneity, no significant alternation occurred in the corresponding ORs with 95% CIs, suggesting our results were statistically reliable.

Some limitations need to be considered when interpreting the results. To start with, although we have included all available data on the association of SNP 87 and ischemic stroke, the sample size does not appear to be sufficiently large enough to detect the potential relationship. Moreover, ischemic stroke is a multifactorial disease that is caused by the interplay of genetic and environmental factors, but we are unable to assess the effects of gene-environment interaction on ischemic stroke on account of lacking related data. Finally, only the published data were considered in this meta-analysis, and the unpublished or the ongoing studies were not included, which may have introduced selection bias.

In conclusion, we found from this meta-analysis that SNP 87 of PDE4D gene was not an independent risk factor for ischemic stroke risk. Further larger rigorous genetic association studies that take gene-gene and gene-environment interaction into consideration are needed to provide conclusive evidence for the association between PDE4D SNP 87 and ischemic stroke.

Disclosure of conflict of interest

None.

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