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. 2016 May 1;20(5):223–228. doi: 10.1089/gtmb.2015.0205

Interaction Between CYP4F2 rs2108622 and CPY4A11 rs9333025 Variants Is Significantly Correlated with Susceptibility to Ischemic Stroke and 20-Hydroxyeicosatetraenoic Acid Level

Duanxiu Liao 1, Xingyang Yi 1,✉, Biao Zhang 1, Qiang Zhou 2, Jing Lin 2
PMCID: PMC4876528  PMID: 26959478

Abstract

Aims: To investigate the association of four variants of two CYP ω-hydroxylase genes and 20-hydroxyeicosatetraenoic acid (HETE) levels with ischemic stroke (IS) and whether gene–gene interactions between these genes increase the risk of IS. Methods: Three hundred ninety-six patients with IS and 378 controls were genotyped for rs2269231, rs9333025, rs2108622, and rs3093135. Gene–gene interactions were analyzed using generalized multifactor dimensionality reduction (GMDR) methods. The 20-HETE levels was measured in 218 IS patients and 126 controls. Results: The frequency of the GG genotype of rs9333025 was significantly higher in IS patients than in controls (p < 0.001). The GMDR analysis showed a significant gene–gene interaction between rs9333025 and rs2108622 (p = 0.0116). This gene–gene interaction predicted a significantly higher risk of IS in individuals carrying the genotypes of rs9333025 GG and rs2108622 GG (odds ratio = 1.92, 95% confidence interval = 1.12–4.26, p = 0.007). The plasma levels of 20-HETE were significantly higher in IS patients than in controls, and IS patients carrying the genotype combination of rs9333025 GG and rs2108622 GG had higher 20-HETE levels than IS patients with other combinations of the two variants. Conclusion: CYP4A1l rs9333025 GG and CYP4F2 rs2108622 GG two-loci interaction significantly increases the risk for IS and an elevated 20-HETE level.

Introduction

Stroke has emerged as a leading cause of mortality worldwide and become a major public health problem (Feigin, 2005; Domingues-Montanari et al., 2008; Jiang et al., 2006). Ischemic stroke (IS) has generally been considered a heterogeneous and multifactorial disorder caused by both conventional environmental risk factors and genetic factors (Dichgans, 2007). Genetic predisposition has been suggested to significantly participate in the pathogenesis of IS (Guo et al., 2010). Therefore, a detailed understanding of genetic factors involved in IS could provide valuable insights into the pathogenesis of potential prevention and treatment strategies for IS (Goldstein et al., 2006).

Many genetic studies related to IS have been conducted in the last decade (Guo et al., 2010; Chehaibi et al., 2014; Das et al., 2014; Jin et al., 2014; Williams et al., 2014). Indeed, IS appears to be a disease that does not follow a simple Mendelian pattern of inheritance involving a single gene, suggesting that single-locus analysis may not be sufficient to investigate the genetic risk factors of IS (Guo et al., 2010). In addition, single-locus analysis may fail to detect significant variants for which individual effects could be below the threshold of detection but may exert significant influence on the pathogenesis of IS through synergistic interactions with other loci variants (Culverhouse et al., 2002). Thus, the search for gene variants linked to IS risk could be significantly enhanced by thorough investigation of gene–gene interactions using alternative analytical methods, such as the generalized multifactor dimensionality reduction (GMDR) approach (Lou et al., 2007).

Arachidonic acid (AA) is generally metabolized by the cyclooxygenases, lipoxygenases, and/or cytochrome P450 (CYP) epoxygenases (Calder, 2009). AA can also be metabolized by CYP ω-hydroxylase to form 20-hydroxyeicosatetraenoic acid (20-HETE), a potent vasoconstrictor (Powell et al., 1998; Lasker et al., 2000). 20-HETE plays an important role in the autoregulation of cerebral blood flow and systemic blood pressure (BP) (Gebremedhin et al., 2000), and blockade of the synthesis or vasoconstrictor actions of 20-HETE reduces infarct size in a middle cerebral artery occlusion model of IS (Omura et al., 2006). Because the CYP4A11 and CYP4F2 genes encode CYP ω-hydroxylase, any genetic variants in these two genes may be associated with the risk of IS. For instance, polymorphisms in CYP4F2 (Fava et al., 2008; Fu et al., 2008b; Deng et al., 2010; Munshi et al., 2012) and CYP4A11 C-296T (Ding et al., 2010) have been reported to be associated with an increased risk of IS.

Despite recent publications focused on the role of AA-metabolizing enzymes in IS pathogenesis, no study on the potential effects of gene–gene interactions of the encoding CYP ω-hydroxylase genes on IS risk has been reported. Because CYP genes encode for enzymes that compensate for or interact with each other in AA metabolism, studying combinations of genetic variants of CYP genes may yield significant discoveries toward elucidating the pathogenesis of IS. The present study aimed to investigate variations in CYP genes encoding CYP ω-hydroxylase and their potential synergistic effects on IS as well as to explore potential gene–gene interactions in relation to IS susceptibility and the 20-HETE level.

Materials and Methods

Study populations

The Ethics Committee of the People's Hospital of Deyang City and the Third Affiliated Hospital of Wenzhou Medical College reviewed and approved this study. All patients or their family members provided written informed consent before enrollment.

The study population was composed of 396 IS patients and 378 controls. Patients who were admitted to the abovementioned two hospitals suffering from their first IS were consecutively recruited between August 2010 and March 2013. Inclusion criteria were as follows: (1) age ≥18 years old; (2) diagnosis of IS based on both clinical findings and the results of a neurological examination using computed tomography or magnetic resonance imaging; and (3) IS-related atherothrombotic (n = 260) and small artery disease (n = 136) according to the TOAST classification system (Han et al., 2006). The exclusion criteria were as follows: (1) cardiogenic cerebral embolism or any cerebral infarction caused by other factors or unknown causes; (2) family history of apoplexy or a history of strokes; and (3) cerebral hemorrhage.

The control subjects were selected from outpatients with no history or family history (genetically related IS) of stroke, as confirmed by medical history, and physical and laboratory examinations at our medical centers.

The following data regarding vascular risk factors for each individual were collected: age, gender, hypertension, diabetes mellitus (DM), cigarette smoking status, alcohol intake, total plasma cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C). Hypertension was defined as the mean of three independent measures of BP ≥140/90 mmHg or the use of antihypertensive drugs. DM was diagnosed by any one or a combination of fasting glucose level >7.8 mM, >11.1 mM 2 h after oral glucose challenge, and the use of hypoglycemic drugs.

Genotyping

The single-nucleotide polymorphisms (SNPs) of the CYP4A11 and CYP4F2 genes encoding CYP ω-hydroxylase were selected from the NCBI database (http://ncbi.nlm.nih.gov/SNP), according to the following criteria: (1) the SNPs had been examined in previous studies and shown to have a potential association with stroke (Fava et al., 2008; Fu et al., 2008b; Deng et al., 2010; Ding et al., 2010; Munshi et al., 2012); (2) the SNPs have a minor allele frequency (MAF) >0.05; (3) the SNPs lead to amino acid changes; and (4) the SNPs are functional. Four TagSNPs with a MAF ≥0.05 were found in the human HapMap project database (http://hapmap.org), including CYP4A1l rs2269231 and rs9333025 and CYP4F2 rs2108622 and rs3093135.

Whole blood (3 mL) was drawn from an arm vein into a sterile tube containing ethylenediaminetetraacetic acid and stored at −80°C until genotype analysis was performed. Genomic DNA was extracted from peripheral blood using a modified phenol/chloroform method and purified using the UNIQ-10 kit (Sangon Biotech Co., Ltd., Shanghai, China).

Genotypes of four variants were examined using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) methods (Aggarwal et al., 2011; Chi et al., 2014). In brief, each SNP-containing gene possessed a specific genotype, with two amplification primers and one extension primer (Table 1). The reaction mixture was desalted by adding 6 mg of cation exchange resin (Sequenom, Inc., San Diego, CA), mixed, and resuspended in 25 μl pure water. Once the primer extension reaction was completed, the samples were spotted onto a 384-well spectroCHIP (Sequenom, Inc.) using a MassARRAY Nanodispenser (Sequenom, Inc.) and genotyped using a MALDI-TOF mass spectrometer (Sequenom, Inc.). Genotype calling was performed in real time with MassARRAY RT software version 3.0.0.4 and analyzed using the MassARRAY Typer software version 3.4 (Sequenom, Inc.).

Table 1.

Amplification and Extension Primers Used in This Study

SNPs Forward primer and reverse primer (5′→3′) Extension primer (5′→3′)
CYP4A1l (rs2269231) F:CGTTGGATGGGATAATGAGAGGAAGTTGC AAGGGAGAAAATCGAACTTTGTG
  R:ACGTTGGATGGTAGATTACATCAGATTCC  
CYP4A1l (rs9333025) F:ACGTTGGATGACACTGATTTCCCTCAAGGT CATTTCCCTCAAGGTCATAAA
  R:ACGTTGGATGCTGAAGTAAATGATTCTATG  
CYP4F2 (rs2108622) F:ATCAACCCGTTCCCACCT CCTAATCAATGAAGCA
  R:ACATTGTGCTCCCAGACG  
CYP4F2 (rs3093135) F:ACGTTGGATGCTGCGGAATTTTGGGATGGG  
  R: ACGTTGGATGACCCACCCTTGGTTTTTCTC GAGGAGCATTGAGGAC
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SNPs, single-nucleotide polymorphisms; F, forward primer; R, reverse primer.

Measurement of plasma 20-HETE level

Plasma CYP450 metabolite 20-HETE levels were measured using a stable isotope dilution gas chromatography/mass spectrometry in 218 IS patients and 126 controls, as described previously (Ward et al., 2011).

Statistical analyses

Based on a suggested sample size requirement for detecting gene–gene interaction (Wang and Zhao, 2003), we expected that our sample size of >360 patients and >360 controls would sufficiently provide 80% power at the 5% significance level calculated using three genetic models: the additive model, the dominant model, and the recessive model.

All statistical analyses were performed using SPSS 16.0 (SPSS, Inc., Chicago, IL). The χ2 test was used to analyze the deviation of Hardy–Weinberg equilibrium for genotype frequencies. Discrete variables were compared using χ2 tests, or if expected cell frequencies were small, Fisher's exact tests were conducted. Continuous variables were compared between IS patients and controls using Student's t-tests. The 20-HETE levels among the different genotypes of the four variants were compared with analysis of variance (ANOVA) followed by the Student–Newman–Keuls test. The Bonferroni test was applied next for comparisons after ANOVA. A p value of <0.05 was considered statistically significant.

Gene–gene interactions were investigated using the statistical software GMDR Beta program version 0.7 (www.healthsystem.virginia.edu/internet/addiction-genomics/Software) and multiple logistic regression. The variables entered into the model included age, gender, cigarette smoking, body–mass index, diabetes, hypertension, hyperlipidemia, rs2269231, rs9333025, rs2108622, rs3093135, and the interactive variable of rs9333025 and rs2108622. The relative risk of genotype and prevalence of cerebral infarction were expressed with odds ratios (ORs) and 95% confidence intervals (CIs).

Results

Clinical characteristics of the subjects

The demographic characteristics of the study subjects, which were also included in our previous study (Chi et al., 2014), are presented in Table 2. The IS patients had a higher prevalence of risk factors for stroke, including a history of hypertension (p < 0.001) or diabetes (p = 0.032). However, differences in other conventional risk factors, including smoking, alcohol intake, body–mass index, and levels of LDL-C, TC, and TG, did not reach statistical significance between the two groups (p > 0.05).

Table 2.

Comparisons of Clinical Characteristics and 20-Hydroxyeicosatetraenoic Acid Level Between the Ischemic Stroke and Control Groups

Characteristics Stroke patients (n = 396) Controls (n = 378) p value
Men, n (%) 235 (59.34) 222 (58.73) 0.924
Age, years 68.79 ± 11.11 64.98 ± 10.29 <0.001
Hypertension, n (%) 302 (76.26) 99 (26.19) <0.001
Diabetes mellitus, n (%) 138 (34.85) 97 (25.66) 0.032
Cigarette smoking, n (%) 165 (41.67) 159 (42.06) 0.942
Body–mass index, kg/m2 24.10 ± 2.33 23.90 ± 2.62 0.221
Alcohol intake, n (%) 184 (46.46) 170 (44.97) 0.694
TG, mM 1.96 ± 1.12 1.83 ± 1.02 0.182
TC, mM 5.54 ± 1.36 5.36 ± 1.21 0.061
LDL, mM 3.15 ± 1.27 2.99 ± 1.19 0.376
20-HETE (pM) 1711 ± 162 1465 ± 123 <0.001
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Data shared with our previous study (Chi et al., 2014).

HETE, hydroxyeicosatetraenoic acid; TC, total cholesterol; LDL, low-density lipoprotein; TG, triglycerides.

Single-locus analysis

The genotype distributions of the four variants in this study were consistent with the Hardy–Weinberg Equilibrium model (p > 0.05). Genotype distributions for IS patients and controls are shown in Table 3. The frequency of the GG genotype for rs9333025 was significantly higher in IS patients than in controls (p < 0.001). However, no significant differences were observed in genotype distributions for rs2269231, rs2108622, and rs3093135 between the two groups (p > 0.05).

Table 3.

Comparison of Genotypes Between the Ischemic Stroke and Control Groups (n, %)

Genotype Stroke patients (n = 396) Controls (n = 378) p value
rs2269231
 AA 78 (19.7) 66 (17.5)  
 AT 217 (54.8) 206 (54.5)  
 TT 101 (25.5) 106 (28.0) 0.362
rs9333025
 AA 7 (1.8) 17 (4.5)  
 AG 90 (22.7) 113 (29.9)  
 GG 299 (75.5) 248 (65.6) <0.001
rs2108622
 GG 209 (52.8) 186 (49.2)  
 GA 155 (39.1) 155 (41.0)  
 AA 32 (8.1) 37 (9.8) 0.293
rs3093135
 TT 331 (83.6) 314 (83.1)  
 AT 58 (14.6) 58 (15.3)  
 AA 7 (1.8) 6 (1.6) 0.999
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Gene–gene interactions

High-order interactions were investigated for IS using the GMDR method, and significant high-order interactions were detected (Table 4). With covariable adjustments, the best model for IS included the interaction between rs9333025 and rs2108622, which scored 10/10 for cross-validation consistency and 9 for sign test (p = 0.0116). Furthermore, significant interactions among the earlier two-loci models were confirmed by a permutation test (p = 0.0246). A one-locus model was also computed for each variant, yielding a minimum p = 0.9468, suggesting that their contribution to stroke risk was due to the synergistic action of the two genes and likely not to the additive effects of both loci.

Table 4.

Comparison of the Best Models, Prediction Accuracies, Cross-Validation Consistencies, and p Values Identified by Generalized Multifactor Dimensionality Reduction

Best modela Training balanced accuracy Testing balanced accuracy Cross-validation consistency Sign test (p)
1 0.6145 0.4868 9/10 5 (0.9468)
1,2 0.6336 0.5822 10/10 9 (0.0116)
1,2,3 0.5724 0.4736 7/10 2 (0.9326)
1,2,3,4 0.6012 0.4546 6/10 2 (0.9287)
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a

rs9333025, rs2108622, rs2269231, and rs3093135 are denoted as 1–4, respectively.

Logistic regression analysis

The relative risks of nine combinations of genotypes of rs9333025 and rs2108622 were considered as interactive variables. Logistic regression analysis indicated that the gene–gene interaction of rs9333025 GG and rs2108622 GG predicted a significantly higher risk of IS (adjusted for age, hypertension, DM; OR = 1.92, 95% CI = 1.12–4.26, p = 0.007; Table 5). There were no statistically significant interactions between the other genetic variant combinations.

Table 5.

Multiple Regression Analysis of the Major Risk Factors for Cerebral Infarction

Risk factor Wald OR 95% CI p value
Age 5.23 1.46 1.01–1.99 0.026
Hypertension 13.32 6.12 2.32–10.68 0.000
Diabetes mellitus 1.46 0.98 0.54–1.42 0.236
rs9333025 GG 2.66 1.26 0.92–1.88 0.062
Interactive variablea 7.88 1.92 1.12–4.26 0.007
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a

rs9333025 GG and rs2108622 GG.

OR, odds ratio; CI, confidence interval.

20-HETE level and its association with genotype distribution

Plasma 20-HETE levels of IS patients were significantly higher than those of the controls (Table 2). There were no significant associations between the 20-HETE level and any one of the four variant genotype distributions (all p > 0.05; Table 6). However, stratified analyses based on different genotype combinations of rs9333025 and rs2108622 revealed that IS patients carrying the genotype combination of rs9333025 GG and rs2108622 GG had a higher 20-HETE level than those carrying other combinations of the two variants (1802 ± 176 vs.1612 ± 141 pM, p < 0.001; Table 6).

Table 6.

Association of 20-Hydroxyeicosatetraenoic Acid Levels with Genotype Distribution in Patients

  20-HETE (pM) p value
rs2269231
 AA (n = 43) 1673 ± 156  
 AT (n = 119) 1686 ± 161  
 TT (n = 56) 1701 ± 178 0.768
rs9333025
 AA (n = 4) 1694 ± 159  
 AG (n = 49) 1725 ± 172  
 GG (n = 165) 1708 ± 168 0.694
rs2108622
 GG (n = 115) 1726 ± 182  
 GA (n = 85) 1697 ± 167  
 AA (n = 18) 1711 ± 172 0.465
rs3093135
 TT (n = 182) 1679 ± 146  
 AT (n = 31) 1687 ± 164  
 AA (n = 5) 1693 ± 156 0.823
Genetic combination of rs9333025 GG and rs2108622 GG
 Yes (n = 94) 1802 ± 176 <0.001
 No (n = 124) 1612 ± 141  
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Discussion

The present study showed that the variation of rs9333025, but not rs2269231, rs2108622, and rs3093135, differed significantly between IS patients and controls with a single-locus analytical approach. Our results were consistent with those of previous studies (Fu et al., 2008a; Ding et al., 2010; Liang et al., 2014), but contradicted the findings of some other studies (Fava et al., 2008; Fu et al., 2008b; Ward et al., 2008; Deng et al., 2010; Munshi et al., 2012). For instance, Ward et al. (2008) reported that a single polymorphism in the CYP4F2 gene, but not the CYP4A11 gene, is associated with increased 20-HETE secretion and BP. A population study suggested that the V433M polymorphism in CYP4F2 may increase the risk of IS in male subjects (Fava et al., 2008), and the G allele of rs2108622 is associated with IS in Japanese men (Fu et al., 2008b). One study in south India also found an association between 1347 G/A polymorphism and stroke (Munshi et al., 2012). There are a number of potential explanations for the differences between our results and those of others. First, racial differences exist among the investigations. Second, IS etiology can be complicated, and it is highly likely that the progression to IS requires several variations, each with minor and or potentially undetectable individual effects (Schork et al., 2009). Therefore, a linkage analysis, which is used to investigate single-gene disorders, seems unsuitable for genetic studies on IS.

A GMDR approach has been used to identify genetic IS risk factors (Liu et al., 2009; Yi et al., 2013) and also was used in the present study. GMDR analysis can reveal interesting synergistic effects of gene variant–gene variant interaction. Specifically, the risk for IS was noted to be increased by 1.92-fold in individuals carrying both the rs9333025 GG and rs2108622 GG genotypes, indicating that the interaction between rs9333025 and rs2108622 variants plays a key role in the genetic predisposition to IS. Our findings add to the evidence that interactions between genes with individually marginal effects may significantly increase the risk of common and complex diseases, such as IS.

However, the nature of the two-gene variant interaction between rs9333025 and rs2108622 remains unclear. One possible explanation is that these two genes participate in AA metabolism. The CYP4A11 and CYP4F2 genes encode CYP ω-hydroxylase, which is primarily responsible for metabolizing AA into 20-HETE, a potent vasoconstrictor (Powell et al., 1998; Lasker et al., 2000). In the current study, we found that the 20-HETE level of IS patients was significantly higher compared with that of the controls, and IS patients carrying the genotype combination of rs9333025 GG and rs2108622 GG had a higher 20-HETE level than those with other combinations of the two variants. The results indicated that rs9333025 GG and rs2108622 GG two-loci interaction can increase capability to metabolize AA, resulting in increased 20-HETE production. 20-HETE constricts cerebral arteries and regulates cerebral vascular tone (Lange et al., 1997; Gebremedhin et al., 2000) by activating intracellular signaling pathways, including protein kinase C (PKC), which are involved in apoptosis and cell death (Sun et al., 1999; Randriamboavonjy et al., 2003). 20-HETE also depolarizes vascular smooth muscle cells through inhibition of the large-conductance Ca2+-sensitive K+ channel and Na+, K+-ATPase activity together with an increase in Ca2+ influx through L-type Ca2+ channels (Gladden et al., 1998; Cheng et al., 2008). Finally, 20-HETE promotes the formation of oxygen radicals (Guo et al., 2007). Accumulating evidence indicates that 20-HETE is involved in endothelial dysfunction (Singh et al., 2007), which is closely linked to cardiovascular events (Corrado et al., 2008). Inhibition of the synthesis of 20-HETE has been shown to reverse the decrease in cerebral blood flow following subarachnoid hemorrhage and to reduce infarct size following transient cerebral ischemia (Takeuchi et al., 2005; Tanaka et al., 2007). All of these previous observations suggest a potential molecular mechanism by which a two-factor interaction influences the development of IS.

Limitations

The present study, however, focused only on four variants of two CYP ω-hydroxylase genes and the interactions among them in a small localized population; our results cannot represent those for a full spectrum of the Chinese population. Thus, our findings need to be confirmed in large sample size and multicenter studies. Our results indicated that IS patients carrying the combination of rs9333025 GG and rs2108622 GG had a higher 20-HETE level than those with combinations of one of the two variants and others. However, we did not obtain direct experimental evidence linking the elevated 20-HETE level and rs9333025 GG/rs2108622 GG genetic combination of CYP4A and CYP4F genes. Thus, the present results will need to be validated in further studies. Although this study examined the role of several known important CYP450 ω-hydroxylase genes, other known and unknown genes were not captured. Thus, future studies involving a larger set of genetic variants should be conducted to elucidate the full extent of gene–gene interaction effects on IS pathogenesis.

Summary

To the best of our knowledge, the present study is the first to identify an interaction between rs9333025 and rs2108622 gene variants in IS patients. Specifically, we discovered that this gene–gene interaction of rs9333025 GG and rs2108622 GG two loci confers a significant increase in the risk for IS and 20-HETE level in the Chinese population. Such double-loci variant analytical approaches may provide further insight into the complex pathogenesis of IS. However, our conclusion may need to be confirmed in multicenter studies with a larger sample size, as well as in animal studies, before it is specific and efficiently used for predicting the risk of IS in humans.

Acknowledgments

This study was supported by the Scientific Research Foundation of Sichuan Provincial Health Department (Grant No. 140025) and Deyang City Science and Technology Research Foundation (Grant No. 2014SZ035).

Author Contributions

D.L. contributed to the study design and literature. X.Y. contributed to data interpretation and writing. B.Z. contributed to data analysis and data collection. Q.Z. contributed to data collection and figures. J.L. contributed to data collection. All authors reviewed and approved the article.

Author Disclosure Statement

No competing financial interests exist.

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