Figures
Abstract
Several published articles investigated the relationship between VEGF receptor gene polymorphisms and stroke, but they failed to reach the same conclusion. This meta-analysis was performed to identify the relationships between VEGF receptor gene and the risk of stroke. The PubMed, Embase, China National Knowledge Infrastructure (CNKI) database, Wanfang Chinese database, and VIP Chinese database were systemically searched. Data was extracted by two independent reviewers. The pooled odds ratio (OR) with 95% confidence interval (CI) were calculated. 5 case-control studies with a total of 2904 patients with stroke and 2824 control subjects were included, including 2904 cases and 2824 controls for -604T>C, 2733 cases and 2663 controls for +1192C>T, and 2733 cases and 2663 controls for +1719A>T. Under the dominant and recessive models, respectively, the overall ORs and 95% CIs of -604 C were 0.749, 0.493–1.138 (P = 0.176) and 0.819, 0.544–1.234 (P = 0.340); the overall ORs and 95% CIs of +1192 T were 1.148, 0.876–1.504 (P = 0.318) and 1.611, 1.004–2.586 (P = 0.048); the overall ORs and 95% CIs of +1719 T were 1.227, 0.932–1.615 (P = 0.146) and 1.139, 1.015–1.279 (P = 0.027). Our finding indicates that +1192C>T and +1719A>T may be associated with the risk of stroke, but not -604T>C.
Citation: Qiu S, Wu T, Wang P, Li J, Li Q, Du J (2016) The Association between VEGFR Gene Polymorphisms and Stroke: A Meta-Analysis. PLoS ONE 11(3): e0151371. https://doi.org/10.1371/journal.pone.0151371
Editor: Masaru Katoh, National Cancer Center, JAPAN
Received: December 2, 2015; Accepted: February 27, 2016; Published: March 16, 2016
Copyright: © 2016 Qiu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The authors have no support or funding to report.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Stroke is one of the most complex diseases with diverse etiologies. It is well established that genetic and environmental backgrounds play a crucial role in the pathogenesis of stroke[1]. Environmental factors, such as smoking, hypertension and diabetes mellitus may contribute to the development of stroke. Currently, several candidate genes have been linked to stroke in genome-wide association studies, but the contribution of susceptibility genes to stroke is still obscure[2].
Vascular endothelial growth factor (VEGF) plays an important role in the maintenance of endothelial integrity, endothelial survival and the physiological function of endothelium. Emerging evidence suggests that polymorphism of the VEGF gene may be associated with the risk of stroke and other cerebral vascular disease[3–6]. The bioactivity of VEGF is mediated by two receptor tyrosine kinases, VEGF receptor-1 (VEGFR1, also called Flt-1) and VEGF receptor-2 (VEGFR2, also called kinase insert domain-containing receptor, KDR). Of the two VEGFR isoforms, KDR is the main receptor and plays a pivotal role in endothelial integrity and function[7, 8]. Several single nucleotide polymorphisms (SNPs) of KDR were found in the promoter region and coding region. Three of them were believed to affect the activity of VEGF-KDR signaling pathway and investigated the most frequently: +1192C>T (rs2305948), +1719A>T (rs1870377) and -604T>C (rs2071559).+1192C>T and +1719A>T are both found in exon regions of VEGF receptor-2 and lead to amino acid substitutions that reduce the binding affinity of VEGF to VEGF receptor-2. -604T>C is located in the promoter region and leads to decreased promoter activity.
Many genetic association studies have been carried out to assess the relationship of these three variants with stroke. However, the findings of them remain controversial. Up to now, no meta-analysis has been performed to investigate this relationship. Therefore, we conduct this meta-analysis to deal with these contradictory results and assess whether VEGF receptor-2 polymorphisms contribute to the risk of stroke.
2. Methods
2.1 Search strategy
Publication search was performed for the potential eligible articles in English and Chinese in the following database: (1) Medline in PubMed searching engine; (2) Embase database; (3) Chinese National Knowledge Infrastructure (CNKI); (4) Wanfang Chinese database; (5) VIP Chinese database. The latest data for searching articles was November 1st, 2015. The key words for article searching were: [“vascular endothelial growth factors receptor” or “vasculotropin receptor” or “VEGFR”] and [“stroke” or “cerebral infarction” or “cerebrovascular disorders”] and [“single nucleotide polymorphism” or “SNP” or “polymorphism” or “mutation” or “genetics” or “variant”]. Publication language was restricted to English and Chinese, and the subjects were not limited in our search. We also performed a manual search of the reference lists of retrieved articles for additional potential studies.
2.2 Inclusion criteria
The inclusion criteria for the gene association studies in this meta-analysis were as follows: (1) independently published case-control studies explored the association between VEGF receptor gene polymorphisms and stroke; (2) with genotype or allelic distributions provided; (3) with data in any of the three polymorphisms, and sufficient data available to calculate an odd ratio (OR) with its 95% confidential interval (CI); (4) if the authors published two or more studies using the same subjects, the most recent publication or the publication with the largest sample size was include. No limitations were placed on race, ethnicity, or geography area.
2.3 Data extraction
Relevant data were systematically extracted from the included studies by two authors using a standardized form, and reached a consensus on all items. The researchers collected the following data: the first author’s name, publication year, countries and ethnicities of participants, sample size, and genotyping method.
2.4 Quality score assessment
To determine the methodological quality of the included studies, we used the Newcastle-Ottawa scale (NOS)[9] to judge the quality of these case-control studies. The NOS ranges from zero to nine stars, and a score ≥ 7 was considered to be of high quality. Two authors assessed the quality of included studies independently, and all disagreements were resolved by discussion.
2.5 Evaluation of statistic association
The association between -604T>C, +1192C>T, and +1719A>T polymorphisms and the risk of stroke was tested by calculating OR and 95% CI. The dominant and recessive models were applied for the genotype comparison. Heterogeneity between studies was estimated by Cochran’s χ2 based Q-statistic test[10] and I2 test. The heterogeneity was considered to be statistically significant at P≤0.1 or I2 >50%. When the P value was >0.1 and I2 ≤50%, the pooled OR was calculated by fixed-effects model, otherwise, the random-effects was applied. Pooled ORs were calculated by the method of Mantel-Haenszel and DerSimonian-Laird, respectively. 95% CI was estimated by Woolf’s method. Publication bias was explored using funnel plots and Egger’s regression test (P<0.05 indicated statistical significance)[11]. Hardy-Weinberg equilibrium (HWE) of the genotype distribution of controls was conducted by Pearson’s χ2 test. Sensitivity analysis was performed by limiting the meta-analysis to case-control studies with high quality (NOS score ≥ 7). All statistic tests were conducted by Stata 11.0 software.
3. Results
3.1 Included studies
Fig 1 showed the process of retrieving eligible studies. Initially, our highly sensitive search strategy identified 216 articles. After reviewed the titles and abstracts of all articles, 192 articles were excluded. After systematically reading full texts, we excluded another 19 articles. Finally, 5 case-control studies with a total of 2904 patients with stroke and 2824 control subjects met our inclusion criteria for qualitative data analysis[12–16]. Table 1 summarized the characteristics of the studies included in the meta-analysis. 5 studies with 2904 cases and 2824 controls for -604T>C, 3 studies with 2733 cases and 2663 controls for +1192C>T and 3 studies with 2733 cases and 2663 controls for +1719A>T were selected eventually. Table 2 showed the studies that have provided the distribution of VEGF receptor-2 genotype and allele among stroke patients and controls. The NOS results showed that the average score was 7.8, which indicated that the methodological quality of included studies was generally good.
3.2 Association of VEGFR2 polymorphisms and stroke
The minor allele and major allele were compared in the dominant and recessive models. The overall ORs and 95% CIs of -604 C were 0.749, 0.493–1.138 (P = 0.176) and 0.819, 0.544–1.234 (P = 0.340) compared with T in the dominant and recessive models, respectively (Fig 2). The overall ORs and 95% CIs of +1192 T were 1.148, 0.876–1.504 (P = 0.318) and 1.611, 1.004–2.586 (P = 0.048) compared with C in the dominant and recessive models, respectively (Fig 3). The overall ORs and 95% CIs of +1719 T were 1.227, 0.932–1.615 (P = 0.146) and 1.139, 1.015–1.279 (P = 0.027) compared with A in the dominant and recessive models, respectively (Fig 4) (Table 3).
a Dominant model. b Recessive model.
a Dominant model. b Recessive model.
a Dominant model. b Recessive model.
3.3 Sensitivity analysis
Sensitivity analysis was performed to assess the stability of results. Sensitivity analysis of the summary odds ratio coefficients on the relationships of the three SNPs and the risk of stroke is computed by omitting each study in turn(Figs 5–7). Furthermore, by limiting the meta-analysis to case-control studies with high quality (NOS score ≥ 7), the sensitivity analysis was conducted in another way. As a result, we omitted one study[16] in the comparison of -604T>C. However, the corresponding ORs were not substantially altered in comparisons, indicating that our results were relatively robust. The results of sensitivity analysis were shown in Table 4.
a Dominant model. b Recessive model.
a Dominant model. b Recessive model.
a Dominant model. b Recessive model.
3.4 Publication bias
We performed Funnel plot and Egger’s linear regression test to detect publication bias. The shape of funnel plot looks symmetrical for all the comparison models, and the Egger’s test was used to provide statistical evidence of publication funnel plot symmetry. No obvious evidence of publication bias was revealed by the results (Figs 8–10) (Table 5).
a Dominant model. b Recessive model.
a Dominant model. b Recessive model.
a Dominant model. b Recessive model.
4. Discussion
We conducted the meta-analysis to investigate the relationship between the three SNPs of VEGF receptor-2 gene and stroke risk. To our knowledge, this is the first time. The main finding was that +1192 T and +1719 T may confer risk of stroke in the recessive model. However, our data revealed no association between -604T>C polymorphisms and stroke risk.
VEGF receptor-2, also called KDR, is the main receptor for VEGF. VEGF-KDR signaling pathway plays a critical role in the development of vascular disease by impacting survival, proliferation, and migration of endothelial cell[17]. Animal researches have shown that deficiency of VEGF receptor-2 gene could result in abnormal blood vessels and defective development of endothelial cell[18]. Evidence suggests that all the three SNPs of VEGF receptor-2, -604T>C, +1192C>T, and +1719A>T, have a significant association with the development of coronary heart disease[19].
It remains debatable how the VEGF signaling pathway affect the pathogenesis of stroke. Evidences support the involvement of angiogenesis in stroke. Vascular endothelial growth factors (VEGF) have important roles in the development and function of the circulation system, which have been shown to participate in atherosclerosis and angiogenesis[5]. On the one hand, several studies suggest that increased VEGF signaling aggravates atherosclerosis through neovascularization and inflammation in atheromatous plaques. Increased density of microvessels within the plaque contributes to the growth and destabilization of the plaque, resulting in the narrowing and occlusion of large cerebral arteries[20, 21]. On the other hand, the lack of sufficient VEGF signaling could result in endothelial dysfunction, vascular degeneration, and formation of weak, thin walled vasculature, which can reduce vessel compliance and increase the risk of spontaneous vessel wall rupture[22, 23]. VEGF receptor-2 is the main receptor for VEGF. To investigate whether the polymorphisms of VEGF receptor-2 are associated with the risk of stroke, may contribute to the study of the mechanisms of stroke.
Although there are plenty of studies investigating the relationship between the three SNPs of VEGFR2 and stroke risk, their results were inconsistent or even contradictory. That is the reason we conduct this meta-analysis. In our results, we found two of the three SNPs might be associated with stroke risk, which was not gained by any of the original articles. We postulate that the sample size of the original articles is relatively small and not sufficient enough to get a conclusive result. In the present meta-analysis, +1192C>T and +1719A>T SNPs were associated with the risk of stroke, but not -604T>C. These results may be attributed to the different locations of the three SNPs in the VEGF receptor-2 gene. SNP +1192C>T is located in exon 7 and +1719A>T is located in exon 11, which lead to amino acid substitutions, Val297Ile and Gln472His, respectively, and reduce binding affinity of VEGF to VEGF receptor-2. However, -604T>C is located in the promoter region of VEGF receptor-2 gene, which may lead to a decreased expression of VEGF receptor-2. It is obscure whether the amount or the binding affinity of VEGF receptor-2 plays a more important role in the VEGF-KDR pathway. Nevertheless our finding suggested that the binding affinity of VEGF receptor-2 affected by +1192C>T and +1719A>T might play a more critical role in the function of VEGF.
In addition, genotype distributions of controls in all studies were consistent with HWE. Sensitivity analysis was also performed, and it didn’t have significant impact on the combined ORs. In the present studies, Funnel plot and Egger’s linear regression test were conducted, but no publication bias was found. This made the results of this meta-analysis more reliable to some extent.
However, there remained some limitations in this meta-analysis. First, the number of studies enrolled in this meta-analysis was relatively small, which makes it hard to perform subgroup analysis and the analysis of different stroke subtypes. Second, all included articles were published in English or Chinese. Therefore, studies issued in other languages might be missed. Third, although the genotyping methods in all studies were the same, other factors like age, sex might lead to bias, which would need further investigation.
In conclusion, our study suggests that +1192 T and +1719 T in the VEGF receptor-2 gene may be associated with an increased risk of stroke. No association with stroke risk is identified in -604T>C polymorphisms. Due to the limitations mentioned above, further researches are required to confirm the findings.
Supporting Information
S2 Checklist. meta-analysis-on-genetic-association-studies-form.
https://doi.org/10.1371/journal.pone.0151371.s003
(DOCX)
Acknowledgments
The authors would like to acknowledge the reviewers for their helpful comments on this article.
Author Contributions
Conceived and designed the experiments: PW JL JD. Analyzed the data: SQ TW. Contributed reagents/materials/analysis tools: QL. Wrote the paper: SQ TW.
References
- 1. Bevan S, Traylor M, Adib-Samii P, Malik R, Paul NL, Jackson C, et al. Genetic heritability of ischemic stroke and the contribution of previously reported candidate gene and genomewide associations. Stroke; a journal of cerebral circulation. 2012;43(12):3161–7. pmid:23042660.
- 2. Dichgans M, Markus HS. Genetic association studies in stroke: methodological issues and proposed standard criteria. Stroke; a journal of cerebral circulation. 2005;36(9):2027–31. pmid:16051898.
- 3. Kim OJ, Hong SH, Oh SH, Kim TG, Min KT, Oh D, et al. Association between VEGF polymorphisms and homocysteine levels in patients with ischemic stroke and silent brain infarction. Stroke; a journal of cerebral circulation. 2011;42(9):2393–402. pmid:21737794
- 4. Fontanella M, Gallone S, Panciani PP, Garbossa D, Stefini R, Latronico N, et al. Vascular endothelial growth factor gene polymorphisms and intracranial aneurysms. Acta Neurochirurgica. 2013;155(8):1511–5. pmid:23728502
- 5. Greenberg DA, Jin K. Vascular endothelial growth factors (VEGFs) and stroke. Cellular and molecular life sciences: CMLS. 2013;70(10):1753–61. pmid:23475070; PubMed Central PMCID: PMC3634892.
- 6. Park YS, Jeon YJ, Kim HS, Chae KY, Oh SH, Han IB, et al. The role of VEGF and KDR polymorphisms in moyamoya disease and collateral revascularization. PloS one. 2012;7(10):e47158. Epub 2012/10/19. pmid:23077562; PubMed Central PMCID: PMCPmc3470587.
- 7. Li B, Ogasawara AK, Yang R, Wei W, He GW, Zioncheck TF, et al. KDR (VEGF receptor 2) is the major mediator for the hypotensive effect of VEGF. Hypertension. 2002;39(6):1095–100. pmid:12052848.
- 8. Koch S, Claesson-Welsh L. Signal transduction by vascular endothelial growth factor receptors. Cold Spring Harb Perspect Med. 2012;2(7):a006502. pmid:22762016; PubMed Central PMCID: PMC3385940.
- 9.
GA Wells, B Shea, D O'Connell, J Peterson, V Welch, M Losos, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://wwwohrica/programs/clinical_epidemiology/oxfordasp.
- 10. Colditz GA, Burdick E, Mosteller F. Heterogeneity in meta-analysis of data from epidemiologic studies: a commentary. American journal of epidemiology. 1995;142(4):371–82. pmid:7625401.
- 11. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. Bmj. 1997;315(7109):629–34. pmid:9310563; PubMed Central PMCID: PMC2127453.
- 12. Zhang W, Sun K, Zhen Y, Wang D, Wang Y, Chen J, et al. VEGF receptor-2 variants are associated with susceptibility to stroke and recurrence. Stroke; a journal of cerebral circulation. 2009;40(8):2720–6. Epub 2009/06/13. pmid:19520980.
- 13. Oh SH, Min KT, Jeon YJ, Kim MH, Moon JS, Kim HS, et al. Association between kinase insert domain-containing receptor gene polymorphism and haplotypes and ischemic stroke. Journal of the neurological sciences. 2011;308(1–2):62–6. Epub 2011/06/28. pmid:21705026.
- 14. Han IB, Kim OJ, Ropper AE, Kim HS, Cho YK, Teng YD, et al. Association between kinase insert domain-containing receptor gene polymorphisms and silent brain infarction: a Korean study. Journal of the neurological sciences. 2012;318(1–2):85–9. Epub 2012/04/24. pmid:22520092.
- 15. Shen X. VEGFR-2 gene promoter region polymorphism and atherosclerosis susceptibility to ischemic stroke relevance: Soochow University; 2014.
- 16. Zhang H, LI G, Su F, Pu Y, Liu T. Gene polymorphisms and plasma concentration of vascular endothelial growth factor receptors and risk for TIA. Chinese Journal of Trauma and Disability Medicine. 2014;(12):47–.
- 17. Liang X, Xu F, Li X, Ma C, Zhang Y, Xu W. VEGF signal system: the application of antiangiogenesis. Curr Med Chem. 2014;21(7):894–910. pmid:24059233.
- 18. Shalaby F, Rossant J, Yamaguchi TP, Gertsenstein M, Wu XF, Breitman ML, et al. Failure of blood-island formation and vasculogenesis in Flk-1-deficient mice. Nature. 1995;376(6535):62–6. pmid:7596435.
- 19. Wang Y, Zheng Y, Zhang W, Yu H, Lou K, Zhang Y, et al. Polymorphisms of KDR gene are associated with coronary heart disease. J Am Coll Cardiol. 2007;50(8):760–7. pmid:17707181.
- 20. Moulton KS. Angiogenesis in atherosclerosis: gathering evidence beyond speculation. Curr Opin Lipidol. 2006;17(5):548–55. pmid:16960504.
- 21. Celletti FL, Waugh JM, Amabile PG, Brendolan A, Hilfiker PR, Dake MD. Vascular endothelial growth factor enhances atherosclerotic plaque progression. Nat Med. 2001;7(4):425–9. pmid:11283668.
- 22. Qureshi AI, Tuhrim S, Broderick JP, Batjer HH, Hondo H, Hanley DF. Spontaneous intracerebral hemorrhage. The New England journal of medicine. 2001;344(19):1450–60. pmid:11346811.
- 23. Greenberg DA, Jin K. From angiogenesis to neuropathology. Nature. 2005;438(7070):954–9. pmid:16355213.