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 » Introduction
 » Material and Methods
 » Results
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Table of Contents    
BRIEF REPORT
Year : 2011  |  Volume : 59  |  Issue : 3  |  Page : 408-412

The functional SNP rs4376531 in the ARHGEF gene is a risk factor for the atherothrombotic stroke in Han Chinese


1 Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
2 Department of Emergency Medicine, The People's Hospital of Anshun, Guizhou Province, China

Date of Submission20-Feb-2011
Date of Decision29-Mar-2011
Date of Acceptance06-May-2011
Date of Web Publication7-Jul-2011

Correspondence Address:
Li He
Department of Neurology, West China Hospital, Sichuan University Chengdu
China
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Source of Support: Sichuan Project of Science and Technology Support (No. 2010SZ0086) and the Department of Health of Guizhou Province (No. 2003008), Conflict of Interest: None


DOI: 10.4103/0028-3886.82755

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 » Abstract 

The gene encoding RhoA guanine nucleotide exchange factor 10(ARHGEF10) has been reported to be a risk factor for atherothrombotic stroke (AS) in Japanese. The single-nucleotide polymorphism (SNP) rs4376531 in intron 16 on ARHGEF10 is associated with AS and may play a role in the disease pathology. In order to explore the nature of this association in greater detail and in a new ethnic group, we carried out a case-control study to determine whether the rs4376531 polymorphism in ARHGEF10 is a risk factor of AS in Han Chinese people. This study was carried out to assay the frequency of genotypes and alleles of SNP rs4376531 in ARHGEF10 in patients with ischemic stroke and healthy controls using the polymerase chain reaction and the restriction fragment length polymorphism (PCR-RFLP) technique. A total of 383 individuals with AS in West China Hospital and 214 unrelated healthy controls were recruited. The frequencies of the G allele and GG genotype of the rs4376531 polymorphism were higher in the patients with AS than in control individuals: frequency of G, 91.0% vs 83.4%, P<0.001; GG, 82.2% vs 67.8%, P<0.001. After adjusting for sex, age, and multiple cardiovascular risk factors, the homozygous GG genotype for this variant was associated with a higher risk of AS, with an adjusted odds ratio of 4.99 (95% CI, 2.55-7.81, P< 0.001). Our findings suggest that the rs4376531 polymorphism in the ARHGEF10 gene is a risk factor for AS in the Han Chinese population.


Keywords: ARHGEF10, atherothrombotic stroke, rs4376531, single-nucleotide polymorphism


How to cite this article:
Yin YY, Zhang B, Zhou MK, Guo J, Lei L, He XH, Xu YM, He L. The functional SNP rs4376531 in the ARHGEF gene is a risk factor for the atherothrombotic stroke in Han Chinese. Neurol India 2011;59:408-12

How to cite this URL:
Yin YY, Zhang B, Zhou MK, Guo J, Lei L, He XH, Xu YM, He L. The functional SNP rs4376531 in the ARHGEF gene is a risk factor for the atherothrombotic stroke in Han Chinese. Neurol India [serial online] 2011 [cited 2021 Sep 24];59:408-12. Available from: https://www.neurologyindia.com/text.asp?2011/59/3/408/82755



 » Introduction Top


Stroke among the elderly population has become a leading cause of mortality and morbidity. [1] Stroke is not only associated with high incidence and fatality rate, but is also associated with enormous economic burden, especially in developing countries like China. [2] The high risk of stroke in people with conventional risk factors such as hypertension, diabetes mellitus, dyslipidemia, and unhealthy behaviors such as smoking and excessive drinking has been well established. In addition, the role of genetic factors has also been established. [3],[4] To date, many candidate genes have been studied for a potential role in stroke, particularly ischemic stroke, including STRK1, PDE4D, [5],[6],[7] ALOX5AP, [6] AGTRL1, [8] MTHFR, [9] NINJ2, [10] and ARHGEF10. [11] However, the findings are inconclusive about the association of these candidate genes with the risk of stroke. Thus, there is a need for further studies in regard to genes contribution to the risk of stroke.

ARHGEF is a member of the Rho-specific guanine nucleotide exchange factor family, widely expressed in the human. [12] It can activate RhoA by enhancing the activity of RhoGTPases, and the effector of RhoA-Rho-kinase plays a major role in the process of atherosclerotic cerebral infarction. [13] Two studies have linked mutations in the ARHGEF gene family with diabetes mellitus. [14],[15] In addition, a recent study found that a newly functional single-nucleotide polymorphism rs4376531 (G>C transition) located in intron 16 of the ARHGEF10 may be related to the risk of atherothrombotic stroke (AS) in the Japanese population. [11] To date, genetic studies on the association between the ARHGEF10 gene and AS have not been published for other populations. We carried out a case-control study in a Han Chinese population to determine whether the allele frequencies of this SNP are significantly different between patients with AS and healthy controls.


 » Material and Methods Top


Subjects

The study period was between April and November 2009 and both the patients with ischemic stroke and case-controls were recruited from among inpatients of West China Hospital, Sichuan University, located in Sichuan province. This study was approved by the ethics committee of Sichuan University and written informed consent was obtained from all participants. Diagnosis of AS was established in all the patients by a physician-based clinical evaluation and investigations such as computed tomography (CT), magnetic resonance (MRI), cerebral angiography, and carotid ultrasonography. Patients with hemorrhagic cerebral infarction, subarachnoid hemorrhage, cerebral vascular malformation, moyamoya disease, and aneurysm rupture were excluded. Patients with cardioembolism and stroke of undetermined etiology were also excluded. [16] These patients were excluded owing to the low genetic effects and less proportions in the number as indicated in the study from Japan. [11] The control participants were confirmed to have no stroke by clinical examination and reported no history of stroke or other neurological disease; all controls came from the southwest of China.

Data on cardiovascular risk factors were in all the patients. Hypertension was defined as the use of antihypertensive medication, a systolic blood pressure ≥140 mmHg, or a diastolic blood pressure ≥90 mmHg. Diabetes mellitus was self-reported or defined as the use of medication and/or a fasting blood glucose level >7 mmol/L. Hypercholesterolemia was diagnosed when participants told us that they have had a history of high total cholesterol level. History of smoking and alcohol drinking were also self-reported.

Genotyping of rs4376531

Genomic DNA was extracted from venous blood leukocytes using a standard phenol-chloroform method. The polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) technique was used to assay the genotypes of the SNP rs4376531. A 298-bp fragment of the rs4376531 polymorphism was amplified by the following primer pair: R, 5'ATCCACACGGGAACATTTACAG3'; F, 5'GAGGCAAAGTCAGAGAGGGTAAT 3'. Reactions were set up in 96-well plates and amplified using the following program in an applied biosystems PCR thermocycler: an initial denaturation at 94°C for 5 min, followed by 34 cycles of denaturation at 94°C for 30 s, annealing at 56°C for 30 s, and extension at 72°C for 30 s. A final extension step was performed at 72°C for 5 min. The PCR products were digested with restriction endonuclease BtscI (New England Biolabs, Beijing, China) at 37°C overnight. Digestion products were separated on 3% agarose gels and stained with ethidium bromide. When results were ambiguous, the amplification and digestion were repeated. In the end, definitive results were obtained for all patient and control samples. To validate the genotyping results for the rs4376531 polymorphism, PCR product of each genotype of sample was selected for direct sequencing using an automated sequencer (ABI Prism3730, Invitrogen Biotechnology, Shanghai, China). The samples to be sequenced were selected by an investigator different from the one who performed the initial genotyping reaction.

Statistical analysis

SPSS 13.0 (SPSS Inc., Chicago, USA) was used to analyze the data in this study. Values for ordinal variables were represented by the mean ± standard deviation (SD), and categorical variables were expressed as percentages. The Student's t-test was used to compare values for ordinal variables between case and control subjects, while categorical variables were compared using the chi-square test. The deviation of the allele from Hardy-Weinberg equilibrium and differences in the genotype and allele frequencies between the ischemic stoke patients and the control individuals were also evaluated with the chi-square test. The latent impacts of sex, age, and classic cardiovascular risk factors on the relatives of ischemic stroke with SNP rs4376531 were determined using multiple logistic regression. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were computed to estimate the risk of ischemic stroke in the presence of the rs4376531 polymorphism. Given the case-control design, the threshold for a significant P value was set at 0.05 (two-sided).


 » Results Top


A total of 383 patients with ischemic stroke and 214 healthy controls were recruited. The power is 0.99 for this sample size to derive the allele G of this SNP association with the ischemic disease. The comparison of clinical data between patients and controls is presented in [Table 1]. The mean age (±SD) was 62.94±13.43 for patients and 51.76±9.93 for control subjects (P<0.001). The gender distribution was similar for both the patient group (59.3% men) and control group (58.2% men) (P=0.802). As expected, the conventional risk factors for cardiovascular disease, such as hypertension, coronary heart disease and diabetes, were present at higher frequencies in the patient group, but hypercholesterolemia and smoking were not different between patients and controls (P=0.230 and P=0.372, respectively).
Table 1: Comparison of clinical data between ischemic stroke patients and health controls

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We analyzed the frequency of the SNP variant with a G>C transition (rs4376531) in the patients with AS and controls. There is a BtscI restriction site in the G allele of the rs4376531 polymorphism, whereas there is no such site in the wild-type C allele. Genotype distributions for the rs4376531 polymorphism were in accordance with Hardy-Weinberg equilibrium (P=0.189>0.05 and P=0.068>0.05 in patient-cohort and control-cohort, respectively). The differences in genotype and allele frequencies between patients with AS and control individuals is shown in [Table 2]. The frequency of the homozygous genotype (GG) was higher in the patients (82.2%) than in the controls (67.8%) [P<0.001, OR 2.20, 95% CI 1.50-3.25], while the heterozygous genotype of GC was higher in the controls [P<0.001]. After adjusting for sex, age, and multiple cardiovascular risk factors, the GG genotype was associated with a significantly higher risk of ischemic stroke (adjusted OR 4.99, 95% CI 2.80-8.88, P<0.001) [Table 3].
Table 2: Allele and genotype frequencies of SNP rs4376531 in the ARHGEF10 gene

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Table 3: Analysis of multiple logistic regression models describing the GG genotype of SNP rs4376531 in ARHGEF10

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 » Discussion Top


Our data suggest that the homozygous genotype (GG) for the rs4376531 SNP in intron 16 of ARHGEF10 is a risk factor for AS in a southeastern Han Chinese population, and this may be a dominant hereditary model, which adds to the known association reported in Japanese. Interestingly, the allele and genotype frequencies were different from those reported in the Japanese study, however, similar to the data of the HapMap in the Han Chinese in Beijing. [17] An explanation may be that the allele and genotype frequencies differ for different ethnic populations, and the different experimental method may also be responsible for this. Genotyping studies in other populations are needed in order to address this question. We speculate that the rs4376531 SNP of ARHGEF10, which was determined through fine mapping, may be specific to Asian populations. This hypothesis should be tested in studies in other parts of Asia.

ARHGEF10 is a member of the subfamily of guanine nucleotide exchange factors (GEFs); the N-terminal region contains tandem Dbl homology (DH) and pleckstrin homology (PH) domains, and the C-terminal region contains putative transmembrane domains. [18],[19] The DH domain is a catalytic domain, while the PH domain helps to modulate protein conformation and subcellular localization, both of which enhance the exchange of GTP with GDP on the target Rho GTPase. [20] The function of ARHGEF10 remains largely unknown except for its association with slowed nerve conduction in peripheral nerves. [12] It is known that ARHGEF10 can activate RhoA, and many studies have examined the function of the RhoA/Rho-Kinase, for instance in vascular smooth muscle cell (VSMC) contraction, actin cytoskeleton organization, cell adhesion, cell motility, and cytokinesis. [13],[21],[22],[23] Moreover, Rho-kinase can accelerate inflammation/oxidative stress, thrombus formation, and fibrosis, and it can reduce endothelial nitric oxide synthase. [24] All of these processes are involved in arteriosclerosis.

It is possible to propose a direct link between the rs4376531 SNP in the ARHGEF10 and arteriosclerosis. Matsushita et al. used functional assays to verify that ARHGEF10 can activate RhoA and found that the susceptible allele G of the SNP rs4376531 may affect the binding affinity of the Sp1 transcriptional factor, which in turn may increase transcription of the ARHGEF10 gene, leading to high expression of RhoA. [11] In this way, allele G of the SNP rs4376531 may activate the Rho/Rho-kinase pathway in the pathogenesis of arteriosclerosis. This suggests that it may be possible to treat AS patients with the homozygous genotype GG for this polymorphism in ARHGEF10 by using an inhibitor of Rho-activated kinase such as fasudil or Y27632. [25]

Some limitations in this study must be mentioned. First, the small sample size and hospital-based study design mean that our population may not be representative of the overall population in mainland China. Secondly, in the control cohort, all the participants are the healthy candidates for the routine physical examination every year, so some individuals with hypertension, even CHD were recruited. This maybe affect the results, and if this effect was excluded consideration of some same pathology between CHD and AS, the difference between the AS and control group maybe more obvious. In addition, the two groups were not well matched by age, and there may be a bias although we corrected it by statistics. Lastly, our study was limited to AS-related stroke and did not include other subtypes of ischemic stroke. Further research examining the association of the rs4376531 polymorphism in ARHGEF10 with other subtypes of ischemic stroke is needed.

The association of this polymorphism in ARHFEG10 with AS may allow for more effective prevention of the disease, since genetic identification of susceptible individuals may allow them to modify the lifestyle behaviors that place them at higher risk.


 » Acknowledgements Top


Yan-Ying Yin and Bo Zhang contributed equally to this work. This study was supported by the Sichuan Project of Science and Technology Support (No. 2010SZ0086) and the Department of Health of Guizhou Province (No. 2003008). We would like to thank all subjects who took part in this study.

 
 » References Top

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4.Brass LM, Isaacsohn JL, Merikangas KR, Robinette CD. A study of twins and stroke. Stroke 1992;23:221-3.  Back to cited text no. 4
    
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9.Kohara K, Fujisawa M, Ando F, Tabara Y, Niino N, Miki T, et al. MTHFR gene Polymorphism as a risk factor for silent brain infarcts and white matter lesions in the Japanese general population: The NILS-LSA Study. Stroke 2003;34:1130-5.  Back to cited text no. 9
    
10.Ikram MA, Seshadri S, Bis JC, Fornage M, DeStefano AL, Aulchenko YS, et al. Genomewide association studies of stroke. N Engl J Med 2009;360:1718-28.  Back to cited text no. 10
    
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12.Verhoeven K, De Jonghe P, Van de Putte T, Nelis E, Zwijsen A, Verpoorten N, et al. Slowed conduction and thin myelination of peripheral nerves associated with mutant rho guanine-nucleotide Exchange Factor 10. Am J Hum Genet 2003;73:926-32.  Back to cited text no. 12
    
13.Shimokawa H, Takeshita A. Rho-Kinase is an important therapeutic target in cardiovascular medicine. Arterioscler Thromb Vasc Biol 2005;25:1767-75.  Back to cited text no. 13
    
14.Kovacs P, Stumvoll M, Bogardus C, Hanson RL, Baier LJ. A functional Tyr1306Cys variant in LARG is associated with increased insulin action in vivo. Diabetes 2006;55:1497-503.  Back to cited text no. 14
    
15.Fu M, Sabra MM, Damcott C, Pollin TI, Ma L, Ott S, et al. Evidence that Rho guanine nucleotide exchange factor 11 (ARHGEF11) on 1q21 is a type 2 diabetes susceptibility gene in the Old Order Amish. Diabetes 2007;56:1363-8.  Back to cited text no. 15
    
16.Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke 1993;24:35-41.  Back to cited text no. 16
    
17.Available from: http://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=4376531). [Last accessed on 2010 May 01].  Back to cited text no. 17
    
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20.Schmidt A, Hall A. Guanine nucleotide exchange factors for Rho GTPases: turning on the switch. Genes Dev 2002;16:1587-609.  Back to cited text no. 20
    
21.Li R, Zheng Y. Residues of the Rho family GTPases Rho and Cdc42 that specify sensitivity to Dbl-like guanine nucleotide exchange factors biochem. J Biol Chem 1997;272: 4671-9.  Back to cited text no. 21
    
22.Uehata M, Ishizaki T, Satoh H, Ono T, Kawahara T, Morishita T, et al. Calcium sensitization of smooth muscle mediated by a Rho-associated protein kinase in hypertension. Nature 1997;389:991-3.  Back to cited text no. 22
    
23.Miller AL, Bement WM. Regulation of cytokinesis by Rho GTPase flux. Nature Cell Biol 2008;11:71-7.  Back to cited text no. 23
    
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    Tables

  [Table 1], [Table 2], [Table 3]

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