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Research Article

Association of CYP2C19*2 with hyperlipidemia in patients with the wild-type CYP2C9

Published: July 28, 2017
Genet.Mol.Res. 16(3): gmr16039737
DOI: 10.4238/gmr16039737

Abstract

Arachidonic acids are metabolized by cytochromes P450 (CYP450) to epoxyeicosatrienoic acids (EETs). EETs have many cardiovascular protective effects such as vasodilation, anti-hypertension, anti-inflammation, lipid-lowering effects, and favorable effects on glucose homeostasis. This study aimed to investigate whether gene polymorphism of cytochrome P450 CYP2C9 and CYP2C19 are related to the risk of hypertension, hyperlipidemia, and diabetes mellitus. Four hundred and eighty patients were enrolled, and single nucleotide polymorphisms for CYP2C9 and CYP2C19 were genotyped. The percentages of patients with hypertension, hyperlipidemia, and diabetes mellitus with CYP2C9 *1/*2, *1/*3, and wild-type (CYP2C9 *1/*1) were similar, and the chi-square (χ2) analysis showed no statistically significant differences between each genotype. Further, no statistically significant differences were observed for the percentages of patients with hypertension, hyperlipidemia, and diabetes mellitus between CYP2C19 genotypes. Subgroup analysis showed that among patients with the wild-type CYP2C9 genotype (CYP2C9*1/*1, N = 297), patients with CYP2C19*1/*2 and *2/*2 genotypes have a significantly higher percentage of hyperlipidemia than those with CYP2C19 *1/*1, *1/*17, and *17/*17 genotypes. Binary logistic regression analysis also suggested that among patients with the wild-type CYP2C9 genotype, the CYP2C19*2 allele was associated with risk of hyperlipidemia (P = 0.027, odds ratio = 2.036; 95% confidence interval = 1.09-3.82). General linear model analysis showed that among our general research population, both CYP2C9 and CYP2C19 had no effect on hyperlipidemia independently, but the interaction between CYP2C9 and CYP2C19 and hyperlipidemia was statistically significant (F = 2.682, P = 0.031). Our study suggests that the association of CYP2C19*2 with hyperlipidemia was specific among patients with the wild-type CYP2C9.

Introduction

Arachidonic acid, a fatty acid in cell membranes, is metabolized by CYP450s to epoxyeicosatrienoic acid (EET). EETs serve as endothelial-derived hyperpolarizing factors (EDHF) and have numerous cardiovascular protective effects such as vasodilation, antihypertension, anti-atherosclerosis, and anti-inflammation effects (Fleming, 2001). EETs have also been shown to have a lipid-lowering effect. Zhang et al. (2009) showed that prevention of the degradation of EETs with a soluble epoxide hydrolase inhibitor caused reduction of serum lipid levels in a mouse model. Recently, a new study also suggested that EETs exert favorable effects on glucose homeostasis, either by enhancing pancreatic islet cell function or by increasing insulin sensitivity in peripheral tissues (Luther and Brown, 2016). CYP2C9 is one of the predominant epoxygenases abundantly expressed in the endothelium (Imig, 2012). The role of the CYP2C9 enzyme in the metabolism of warfarin and its gene polymorphism is well known and is highly associated with warfarin dose. The wild-type CYP2C9*1 allele is associated with normal enzyme activity, and two common allelic variants, CYP2C9*2 and CYP2C9*3, are associated with reduced enzyme activity. CYP2C19 is another type of cytochrome P450 expressed in human endothelial cells and catalyzes the biosynthesis of EETs from arachidonic acid. CYP2C19 gene variants, mainly CYP2C19*2, which is a loss-offunction allele, and CYP2C19*17, which is a gain-of-function allele, are well known to affect the efficacy of clopidogrel therapy (Hulot et al., 2006). Because EETs are metabolized by CYP2C9 and CYP2C19, it is reasonable to suspect that patients with reduced enzyme activity variants of CYP2C9 and CYP2C19 are more likely to develop hypertension, hyperlipidemia, or diabetes mellitus due to less EET production. This study aimed to investigate the association between CYP2C9 and CYP2C19 polymorphisms and risk of hypertension, hyperlipidemia, and diabetes mellitus in our patient population.

Materials and Methods

Subjects

A total of 480 patients were included in this study, and a consent form was signed by every patient. This study was approved and monitored by the Copernicus Group Institutional Review Boards. This study was in compliance with the Declaration of Helsinki.

Genotyping

We used the magnetic bead-based method for concentrating DNA, which was obtained from buccal swab leukocytes by using QiangenQiaCube instrument and MagMAXTM DNA Multi-sample kits. CYP2C9*1, *2, and *3 were genotyped in 480 patients. CYP2C19*1, *2, and *17 were genotyped in 453 patients.

Study outcome definition

Hyperlipidemia is defined as fasting total cholesterol ≥200 mg/dL, and/or fasting low-density lipoprotein cholesterol ≥160 mg/dL and/or fasting triglycerides ≥150 mg/dL. Diabetes mellitus was diagnosed if the fasting plasma glucose concentration was ≥126 mg/ dL at two different time points or hemoglobin A1c ≥ 6.5%. Hypertension was defined as systolic blood pressure ≥140 mmHg and diastolic blood pressure ≥90 mmHg or treatment with antihypertensive medication.

Statistics

SPSS 16 was used for statistical analysis. Data are reported as means ± standard error and P < 0.05 was considered to be statistically significant. One-way analysis of variance and Crosstabs distribution with the chi-square (χ2) analysis were performed to evaluate the differences between data. Binary logistic regression was used to evaluate the association of CYP2C9 and CYP2C19 gene polymorphism and diseases. A univariate general linear model was used to test for a potential interaction between CYP2C9 and CYP2C19 and hyperlipidemia.

Results

CYP2C9 and CYP2C19 allele frequency distribution

The allele frequency distribution of CYP2C9 and CYP2C19 in our patient population is presented in Table 1. The allele frequency of the wild-type allele is 79.5% for CYP2C9(*1) and 63.0% for CYP2C19(*1). One-way analysis of variance showed no significant age difference between patients with CYP2C9*1/*1, *1/*2, and *1/*3. Further, no significant age difference in patients was noted among each genotype of CYP2C19.

  Allele N (%) Genotype N (%) Age (years)
CYP2C9 1 763 (79.5) *1/*1 297 (61.9) 70.6 ± 12.8
  2 129 (13.4) *1/*2 111 (23.1) 70.1 ± 13.3
  3 68 (7.1) *1/*3 58 (12.1) 74.5 ± 12.3
        *2/*2 6 (1.2) 82.0 ± 4.8
        *2/*3 6 (1.2) 83.3 ± 9.4
        *3/*3 2 (0.4) 73.0 ± 11.3
CYP2C19 1 571 (63.0) *1/*1 182 (40.2) 72.1 ± 11.9
  2 152 (16.8) *1/*2 87 (19.2) 71.3 ± 12.8
  17 183 (20.2) *2/*2 15 (3.3) 71.9 ± 11.6
        *1/*17 120 (26.5) 70.7 ± 14.8
        *2/*17 35 (7.7) 68.9 ± 14.0
        *17/*17 14(3.1) 72.4 ± 12.7

Table 1: Age Distribution Among study population

CYP2C19 variants and diseases

For CYP2C19, because CYP2C19*2 is a loss-of-function allele and CYP2C19*17 is a gain-of-function allele, we divided patients into three groups: wild-type, patients with the CYP2C19*2 allele, and patients with the CYP2C19*17 allele. The percentages of patients with hypertension, hyperlipidemia, and diabetes mellitus in each group were similar, and the χ2 analysis revealed no statistically significant difference between each group (Table 2). To further explore whether CYP2C19 gene polymorphism played a role in the development of hypertension, hyperlipidemia, and diabetes mellitus, binary logistic regression analysis was also used to detect the association between gene polymorphism and the three diseases. The analysis also suggested that there was no association of the CYP2C19 gene polymorphism with risk of hypertension, hyperlipidemia, and diabetes mellitus (Table 3).

Theoretically, both CYP2C9 and CYP2C19 can affect EET production, which will subsequently affect the risk of related diseases. To avoid interaction or confounding effect between gene polymorphism from these two genes, the relationship between the CYP2C19 gene polymorphism and diseases was then analyzed only among patients with the CYP2C9 wild-type (CYP2C9 *1/*1). In the wild-type CYP2C9 patients, the χ2 analysis showed that patients with the CYP2C19*2 allele had a significantly higher percentage of hyperlipidemia than patients in the wild-type or CYP2C19*17 allele group (χ2 = 7.831, P = 0.02; Table 4). We also divided patients into two groups, those with *2 (*1/*2, *2/*2) genotypes and those without *2 (*1/*1, *17/*17, *1/*17) genotypes. Patients with the CYP2C19*2 allele had a significantly higher percentage of hyperlipidemia than those without the *2 allele (χ2 =7.62, P = 0.0057). Binary logistic regression analysis also suggested that CYP2C19*2 was significantly associated with hyperlipidemia (P = 0.027; odds ratio = 2.036; 95% confidence interval = 1.09-3.82) in patients with the wild-type CYP2C9. No differences in the incidence of hypertension and diabetes mellitus were noted among these three groups in patients with the wild-type CYP2C9.

CYP2C9 variants and diseases

For CYP2C9, there were not enough cases for patients with *2/*2, *2/*3, and *3/*3; hence, we compared differences only between *1/*1, *1/*2, and *1/*3. The percentages of patients with hypertension, hyperlipidemia, and diabetes mellitus in the wild-type, *1/*2, and *1/*3 CYP2C9 groups were similar, and the χ2 analysis showed no significant statistical differences between each genotype (Table 5). Binary logistic regression analysis also showed that the CYP2C9 gene polymorphism was not associated with the risk of hypertension, hyperlipidemia, and diabetes mellitus (Table 3).

Subgroup analysis among patients in the wild-type CYP2C19 group showed a similar result, wherein no significant differences were found for the risk of hypertension, hyperlipidemia, and diabetes mellitus among patients in the wild-type, *1/*2, and *1/*3 CYP2C9 groups.

Interaction between CYP2C19 and CYP2C9 and hyperlipidemia

A univariate general linear model was used to investigate the interaction between CYP2C9 and CYP2C19 and hyperlipidemia. In our general study population, both CYP2C9 and CYP2C19 had no effect on hyperlipidemia independently (F = 0.839, P = 0.523 for CYP2C9 and F = 1.850, P = 0.102 for CYP2C19), but the interaction between CYP2C9 and CYP2C19 and hyperlipidemia was statistically significant (F = 2.682, P = 0.031).

Discussion

In this study, we hypothesized that polymorphism in CYP2C9 and CYP2C19 affects enzyme activity, causes lower EET levels in endothelial cells, and then increases the risk of hypertension, hyperlipidemia, and diabetes mellitus in patients with the CYP2C9 and CYP2C19 variants. Our results suggest the association between CYP2C19*2 allele and risk of hyperlipidemia among patients with the wild-type CYP2C9 variants. Previous studies showed controversial results for the association between CYP2C9 and CYP2C19 gene polymorphism and the development of hypertension, hyperlipidemia, and diabetes mellitus. Regarding hypertension, Yu et al. (2004) showed that the allelic frequency of CYP2C9*3 in patients with hypertension was significantly higher than in healthy controls in a Chinese population. Caucasian patients with secondary renal diseases had less favorable blood pressure with CYP2C9 variant alleles (*2 and *3) (Joy et al., 2009). However, Dreisbach et al. (2005) showed that CYP2C9*2 and *3 are not associated with increased risk of hypertension in the African American population. For the CYP2C19 gene polymorphism, only one study on the association between CYP2C19 and hypertension showed that CYP2C19*2 variants did not have any association with hypertension in a Korean population (Shin et al., 2012). Concerning diabetes mellitus, CYP2C9*2, *3, and CYP2C19*2 have been shown to have no association with diabetes mellitus (Semiz et al., 2010; Weise et al., 2010), which is consistent with our results. One study even showed that individuals with the CYP2C19*2 variant seem to protect against metabolic syndrome (Gaio et al., 2014). Regarding hyperlipidemia, the study by Luo et al. (2005) suggested an association of CYP2C9*3 with hyperlipidemia in the female Chinese population. There are no reports on the relationship between CYP2C19 variants and hyperlipidemia. To the best of our knowledge, our study is the first to show an association between CYP2C19 variants and hyperlipidemia.

Several genes in the CYP450 system are involved in EET metabolisms, such as CYP2C9, CYP2C19, CYP2C8, and CYP2J2 (King et al., 2005). Thus, it is possible that gene polymorphism of a single gene, such as CYP2C9 or CYP2C19, is not enough to determine the level of EET biosynthesis. It is more likely that the combined effect of genetic variants of several genes in the CYP450 system determines the level of EET biosynthesis. Lundblad et al. (2005) showed that CYP2C8*3/*3/CYP2C9*2/*2 exhibited a 34% (P < 0.05) decreased EET biosynthesis compared to other CYP2C8/CYP2C9 haplotypes, whereas there were no significant differences between the CYP2C9 variants. In our study, patients with a combination of CYP2C9*1/*1 and CYP2C19*1/*2 or *2/*2 have significantly higher risk of hyperlipidemia than patients with other genotypes of CYP2C19. Individuals with CYP2C19*17, which is a gain-of-function allele, should theoretically have more EETs and lower risk of related diseases. However, there is no report to show that CYP2C19*17 is a protective factor for risk of hypertension, hyperlipidemia, and diabetes mellitus and our results also did not support this theory. Thus, this is indirect evidence to support that one gene in the CYP450 system is not enough to determine the level of EET biosynthesis. Our results used general linear model analysis to show that among our entire research population, both CYP2C9 and CYP2C19 have no effect on hyperlipidemia independently, but the interaction between CYP2C9 and CYP2C19 gene polymorphism and hyperlipidemia is statistically significant. Therefore, future studies should focus more on research regarding gene polymorphism combination effect or interactions for several related genes.

In summary, our study showed that the association of CYP2C19*2 with hyperlipidemia is specific for patients with wild-type CYP2C9 genotypes.

Conflicts of interest

The authors declare no conflict of interest.

About the Authors

Corresponding Author

K. Khalighi

Easton Cardiovascular Associates, Easton, PA, USA

Email:

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