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Association of CYP2C8, CYP2C9 and CYP2J2 gene polymorphisms with myocardial infarction in South Indian population
Pharmacological Reports 67 (2015) 97–101
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Original research article
Association of CYP2C8, CYP2C9 and CYP2J2 gene polymorphisms with myocardial infarction in South Indian population Annan Sudarsan Arun Kumar a,*, Srinivasamurthy Suresh Kumar a, Gurusamy Umamaheswaran a, Ramasamy Kesavan a, Jayaraman Balachandar b, Chandrasekaran Adithan a a Pharmacogenomics Laboratory, Department of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India b Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India
A R T I C L E I N F O
Article history: Received 5 June 2014 Received in revised form 9 July 2014 Accepted 11 August 2014 Available online 11 September 2014 Keywords: CYP2C8 CYP2C9 CYP2J2 Myocardial infarction Indian
A B S T R A C T
Background: Cardiovascular diseases (CVDs) are the major cause of mortality and morbidity worldwide. Myocardial infarction (MI) is a complex multi-factorial, polygenic disorder arising from an interaction between genetic makeup of individuals and various environmental factors. CYP2C8, CYP2C9 and CYP2J2 gene involved in the metabolism of arachidonic acid, generates epoxyeicosatrienoic acids (EETs) that mediate dilation of coronary arteries improving post-ischemic cardiac contractile function, reduce vascular inflammation, and increase intravascular fibrinolysis. The study is aimed at analyzing the association of CYP2C8, CYP2C9 and CYP2J2 gene polymorphisms and MI risk in the South Indian population. Methods: This retrospective study consisted of 287 MI patients, 279 risk control patients and 321 healthy individuals. Blood samples were collected from all the subjects and DNA was isolated using standard phenol–chloroform method. Polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) and real time-polymerase chain reaction (RT-PCR) methods were used for genotyping. To test the potential independent association between polymorphisms and the risk of MI, Multiple-logistic regression analysis was performed. Results: Our findings displayed a significant association between CYP2J2*7 (p = 0.04; OR = 2.0) polymorphism and MI while comparing cases with to risk controls. We did not observe any association of CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3 with MI. Conclusion: Our results suggest that individuals with any conventional risk factor for MI along with CYP2J2*7 variant allele may be predisposed to risk of MI in South Indian population. ß 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
Introduction Cardiovascular diseases (CVDs) are the major cause of mortality and morbidity worldwide [1]. CVDs are the outcome of numerous risk factors like age, body mass index (BMI), smoking, alcohol intake, hypertension, diabetes mellitus, hypercholesterolemia, less physical activity, tobacco use, stress, low intake of fruits, vegetables and raised waist to hip ratio. Worldwide, heart attacks are the leading cause of death among men and women. World
* Corresponding author. E-mail address: [email protected] (A.S. Arun Kumar).
health organization reported 17.3 million cardiovascular deaths in 2008, out of which 7.3 million was due to heart attack. It is estimated that there may be 23.3 million deaths due to heart diseases by 2030 [2]. Nitric oxide (NO) also known as endothelium derived relaxing factor (EDRF) produced by the vascular endothelial cells, is a key molecule which regulates vascular tone. In addition, the arachidonic acid metabolites, epoxyeicosatrienoic acids (EETs) also known as endothelium derived hyperpolarizing factor (EDHF) formed by drug metabolizing enzymes CYP2C8, CYP2C9, CYP2J2 isoforms in human endothelial cells, plays vital physiological roles in maintenance of vascular tone (vasodilatation), NOS3 regulation, vascular smooth muscle migration and fibrinolysis [3–6]. Drug metabolizing enzymes (DMEs) are a
http://dx.doi.org/10.1016/j.pharep.2014.08.010 1734-1140/ß 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
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diverse group of proteins which metabolizes vast array of xenobiotic compounds such as drugs, environmental pollutants, and endogenous compounds. Polymorphisms in CYP2C9 are analyzed to determine the clearance of drugs such as ibuprofen, indomethacin, flurbiprofencelecoxib, valdecoxib, etc. CYP2C8 also plays a vital role along with CYP2C9 for the clearance of ibuprofen [7]. It is also shown that CYP2C9 and CYP2C8 are inhibited by danazol, nicardipine, ketoconazole and lansoprazole. There is also evidence that sulfamethoxazole inhibit the enzyme activities of CYP2C9 and trimethoprim inhibit the enzyme activities of CYP2C8 [8]. The activity of CYP2J2 is reduced by more than 90% by drugs such as ketoconazole, lansoprazole, loratadine, miconazole, danazole, nicardipine and verapamil [9]. As all these drugs are commonly used for ailments such as myalgia, gastritis, etc., they also have important effect on activities of these enzymes. In humans CYP2C and CYP2J gene families are expressed in the endothelium, myocardium, and kidney. Vasodilatation, antihypertension, pro-angiogenesis, anti-atherosclerosis are some of the cardiovascular effects of CYP epoxygenases and EETs [10]. From previous reports it is evident that CYP2C8, and CYP2C9 genes are highly polymorphic in nature and their allelic variant frequencies differs based on ethnicity [11]. Human Cytochrome P450 [CYP] Allele Nomenclature Committee has so far described 14 variant alleles for CYP2C8 gene among which CYP2C8*2 (I269F) and CYP2C8*3 (R139K, K399R) has shown to decrease paclitaxel 60 -hydroxylase activity [12]. CYP2C8 metabolizes arachidonic acid to biologically active EETs (11,12EET and 14,15-EET) and therefore influences the circulating levels of EETs [13]. Thus allelic variants of CYP2C8 could produce an influencing pathological and physiological change in humans [14]. Human Cytochrome P450 [CYP] Allele Nomenclature Committee has so far described 58 variant alleles for CYP2C9 gene among which CYP2C9*2 and CYP2C9*3 are the most common polymorphisms [15]. Both these variants are associated with decreased metabolism of CYP2C9 substrates [16]. CYP2J2 metabolizes arachidonic acid primarly to 11,12-EET. This eicosanoid by inhibiting endothelial nuclear factor-B, possesses a potential antiinflammatory effect. EETs, such as 5,6-, 8,9-, and 14,15-EET, influence important vasodilatation functions effected via the mechanism of smooth muscle cell relaxation. Reports also suggest that EETs possess various other properties such as antioxidant, antiapoptotic, antimigratory and antithrombotic [17]. CYP2C8, CYP2C9 and CYP2J2 genes are involved in the pathogenesis of acute myocardial infarction (AMI) and therefore can be considered as candidate genes for MI [17,18]. The current study was designed out of our curiosity to find the association of these candidate CYP genes and the risk of MI among South Indian population. To the authors knowledge, the current study was the first study to evaluate the role of the allelic variants of CYP genes in patients with common cardiovascular diseases such as MI and hypertension. Literature surveys also showed that there are no studies done to evaluate the risk assessment of CYP2C8, CYP2C9, and CYP2J2 on MI patients in an Indian population. Thus the aim of the present study is to find the influence of
interethnic differences and the risk modifying effects of CYP2C8, CYP2C9 and CYP2J2 alleles on MI risk in Indian population. Methods Subjects The retrospective study consisted of three groups. Group1 comprised of 287 MI patients (MI diagnosis was based on World Health Organization criteria), group2 comprised of 279 risk control patients who had one of the conventional risk factor for coronary heart disease (hypertension) and group3 comprised of 321 healthy individuals. All the study subjects were interviewed using standardized questionnaire to know about the status of their lifestyle, smoking, alcohol and drug intake. The study subjects were aged between 25 and 75 years of either gender and unrelated ethnic Tamilians recruited from inpatients and out patients ward of Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER) Hospital, Pondicherry, India. Subjects were selected from families who were residing in South India for at least three generations and spoke Tamil as their mother tongue. The Institute Human Ethics Committee approval was obtained for the study. The study procedure was explained in detail and written informed consent was obtained from all the volunteers. Genotyping Volunteers were requested for 5 mL of blood and were collected from antecubital vein in polypropylene tubes containing 100 mL of 10% ethylene diamine tetra acetic acid (EDTA) as anticoagulant. The plasma was separated by centrifugation and was used for lipid profile analysis. Standard phenol–chloroform method was used to extract the genomic DNA from the peripheral leukocytes. After extraction, DNA was diluted to a concentration of 50 ng/mL and was stored at 20 8C. All the subjects were genotyped for CYP2C8*2 and CYP2C9*2 alleles by polymerase chain reaction– restriction fragment length polymorphism method (PCR-RFLP). Amplification was checked on 1% agarose gel. 8% or 12% polyacrylamide gels were used to identify electrophoresed enzyme-digested products. The details of the primers used for amplification, enzymes used for RFLP analysis and their band patterns are given in Table 1. Genotyping of CYP2C8*3, CYP2C9*3 and CYP2J2*7 was performed by real-time PCR allelic discrimination method (Applied Biosystems, Foster City, CA, USA). The thermocycler, kits for amplification and allelic discrimination were obtained from Applied Biosystems, Foster City, CA, USA. The assay ids for CYP2C8*3, CYP2C9*3 and CYP2J2*7 were C__25625782_20, C__27104892_10 and C__9581699_80, respectively. Statistical analysis Statistical Package for Social Sciences (SPSS windows version 16) was used for analyzing the genotype data. The demographic details with continuous variables were compared by Student ‘t’ test
Table 1 Primers and restriction enzymes used for genotyping of CYP2C8*2 and CYP2C9*2 alleles by PCR-RFLP method. Gene
SNP
Primers
Product Size (bp)
Annealing Temperature (8C)
Restriction enzyme
Major allele (1)
Minor allele (2)
CYP2C8
805A > T
167
56.9
Mbo I
69, 65, 33
98, 69
CYP2C9
430C > T
F – 50 AAAGTAAAAGAACACCAAGC30 R – 50 AAAATCCTTAGTAAATTACA30 F – 50 TACAAATACAATGAAAATATCATG30 R – 50 CTAACAACCAGACTCATAATG30
690
53.0
Ava II
521, 169
690
F – Forward; R – Reverse; bp – base pairs. (1) Band patterns observed under ultra violet light in the presence of wild type allele. (2) Band pattern observed under ultra violet light in the presence of variant allele.
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and dichotomous variables were compared by Chi-square test for the study groups (cases, risk controls and healthy controls). Fisher’s exact test was used to compare the differences in genotype and allele frequencies. Logistic regression analysis was performed to adjust the confounding factors namely age, gender, BMI, alcohol, smoking, diabetic status, total cholesterol, triglycerides, low density lipoproteins, high density lipoproteins and to estimate the risk of MI. Adjusted odds ratio (OR) with 95% confidence interval (CI) was analyzed keeping low risk genotype as the reference groups. The OR of 1 was set as reference for the normal type genotype. HAPLOVIEW Software version 4.1 was used for analyzing the haplotype structures prevailing in the study population. A p < 0.05 was considered statistically significant.
Results Table 2 shows the crude and adjusted OR of CYP2J2*7, CYP2C8*2, CYP2C8*3, CYP2C9*2, CYP2C9*3 polymorphisms and MI compared between cases, risk controls and healthy controls. It also shows the genotype and allele frequencies of CYP genes in the South Indian population. There was a significant difference observed in the distribution of CYP2J2*7 GT + TT genotype between the cases and the risk controls (p = 0.03). The crude odds ratio (OR) showed 1.9 fold risk for MI. After adjusting for the confounding factors, the risk for MI was increased to 2.0 folds (adjusted OR = 2.0), significantly (p = 0.04). Significant difference was also observed in the distribution of CYP2J2*7 T allele when compared between the cases and the risk controls (p = 0.02). Other polymorphisms did not show a significant association with MI when comparing cases and risk controls with crude OR and after adjusting for confounding factors. While comparing cases with healthy controls, the crude OR for CYP2C9*2 showed 2.4 fold risk for MI with a p value of 0.04; but after adjusting for confounding factors the significance was not observed. Even though the other polymorphisms showed a risk for MI after adjusting for confounding factors, the p values was not significant. We also constructed and compared the haplotype structure (HS) for four polymorphisms CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), CYP2C8*3 (rs10509681) and CYP2C8*2
99
(rs11572103) among cases, risk controls and healthy controls. The HS with frequency greater than 1% is given in Table 3. Although the HS2 showed a 1.3 fold risk for MI while comparing cases and controls, the p value was not significant (data not shown). The demographic details of the subjects are same as described previously and given in Table 4 [19]. All the polymorphisms were in Hardy-Weinberg equilibrium, except CYP2C8*3 and CYP2J2*7 among cases and healthy controls respectively.
Discussion EETs are synthesized by many isoforms of CYP enzymes but have organ-specific expression [20]. These EETs are termed as EDHF which are partly formed by CYP2C8, CYP2C9, and CYP2J in human endothelial cells [12,21,22]. In addition to common risk factors like hypertension, obesity, hypercholesterolemia, diabetes mellitus, alcohol usage and cigarette smoking for coronary artery disease, an individual’s genetic makeup should be taken into account for evaluating the disease susceptibility. This is the first study to analyze the association of allelic variants of CYP2C8, CYP2C9, and CYP2J2 with MI in South Indian population. We found that CYP2J2*7 T allele frequency was higher in MI patients than in controls in South Indians and the analysis also showed that the variant allele may be a risk factor for MI susceptibility which were consistent with previous report [23,24]. The variant allele of CYP2J2*7 will prevent the binding of Sp1 transcription factor to the promoter region which leads to the decreased promoter activity. The normal type CYP2J2 promoter was twice active than the variant CYP2J2*7 allele and had reduced EET activities [17]. EETs activate smooth muscle potassium channels leading hyperpolarization and vascular relaxation. However, there are also reports that provide lack of association of CYP2J2*7 polymorphism with coronary artery disease (CAD) in different ethnics. A large cross-sectional study in LURIC cohort did not confirm CYP2J2 polymorphism as a risk factor for CAD or MI [25]. Whereas a study conducted in African-American suggested that CYP2J2 polymorphism may be an important risk factor for coronary heart disease [26]. A study conducted in a total of
Table 2 Association between CYP2J2*7, CYP2C8*2, CYP2C8*3, CYP2C9*2, CYP2C9*3 polymorphisms and AMI compared between cases, risk controls and healthy controls. Gene & SNP
Genotype
Cases
Risk controls
CYP2J2*7 76G > T rs890293
GG GT + TT G T
251 36 536 38
(87.5) (12.5) (93.4) (6.6)
260 19 538 20
(93.2) (6.8) (96.4) (3.6)
CYP2C8*2 805A > T rs11572103
AA AT + TT A T
278 9 565 9
(96.9) (3.1) (98.4) (1.6)
269 10 548 10
(96.4) (3.6) (98.2) (1.8)
CYP2C8*3 1196A > G rs10509681
AA AG + GG A G
268 19 555 19
(93.4) (6.6) (96.7) (3.3)
260 19 539 19
(93.2) (6.8) (96.6) (3.4)
CYP2C9*2 430C > T rs1799853
CC CT + TT C T
268 19 554 20
(93.4) (6.6) (96.5) (3.5)
261 18 540 18
(93.5) (6.5) (96.8) (3.2)
CYP2C9*3 1075A > C rs1057910
AA AC + CC A C
240 47 529 49
(83.6) (16.4) (92.2) (8.5)
236 43 511 47
(84.6) (15.4) (91.6) (8.4)
OR (95% CI)
p Value
OR (95% CI) adjusted
p Value
1.9 (1.0–3.5)
0.03
2.0 (1.0–4.1)
0.04
1.9 (1.0–3.3)
0.02
0.8 (0.3–2.1)
0.9
0.8 (0.3–2.1)
0.8
0.9 (0.5–1.8)
0.9
0.9 (0.5–1.8)
0.9
1.0 (0.5–2.0)
0.9
1.0 (0.5–2.0)
0.9
1.0 (0.6–1.6)
0.8
1.0 (0.6–1.5)
0.9
0.9 (0.3–2.8)
1.5 (0.5–4.5)
1.2 (0.4–3.6)
1.2 (0.7–2.1)
0.9
0.4
0.7
0.5
Healthy control 286 35 606 36
(89.1) (10.9) (94.4) (5.6)
310 11 631 11
(96.6) (3.4) (98.3) (1.7)
304 17 625 17
(94.7) (5.3) (97.4) (2.6)
312 9 633 9
(97.2) (2.8) (98.6) (1.4)
275 46 593 49
(85.7) (14.3) (92.4) (7.6)
OR (95% CI)
p Value
OR (95% CI) adjusted
p Value
1.1 (0.7–1.9)
0.6
1.7 (0.8–3.6)
0.2
1.1 (0.7–1.9)
0.5
0.9 (0.3–2.2)
0.8
1.5 (0.3–7.4)
0.6
0.9 (0.3–2.2)
0.8
1.2 (0.6–2.4)
0.6
1.0 (0.3–3.9)
0.9
1.2 (0.6–2.4)
0.6
2.4 (1.0–5.5)
0.04
3.3 (0.7–15.6)
0.1
2.5 (1.1–5.6)
0.02
1.1 (0.7–1.8)
0.5
1.3 (0.6–2.8)
0.4
1.1 (0.7–1.6)
0.6
Covariates included in the regression analysis were age, gender, BMI, alcohol, smoking, diabetic status, total cholesterol, triglycerides, low density lipoproteins and high density lipoproteins. OR (95% CI): odds ratio (95% confidence interval); OR (95% CI) adjusted: odds ratio obtained after performing logistic regression analysis.
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Table 3 Haplotype structure and frequencies of rs1799853, rs1057910, rs10509681 and rs11572103 among cases, risk controls and healthy controls. Haplotype
rs1799853
rs1057910
rs10509681
rs11572103
Cases (n = 465)
Risk controls (n = 275)
HS1 HS2 HS3 HS4 HS5 HS6
C C Tc C C Tc
A Cc A A A A
A A Gc A Gc A
A A A Tc A A
397 38 10 7 6 –
239 18 9 5 – –
(85.3) (8.2) (2.1) (1.4) (1.3)
(86.6) (6.7) (3.3) (1.8)
OR (95% CI)
p Valuea
1.3 (0.7–2.3) 0.7 (0.3–1.7) 0.9 (0.3–2.7) – –
0.4 0.4 0.7 – –
Healthy controls (n = 356) 317 23 – – 6 4
(89.0) (6.4)
(1.7) (1.1)
OR (95% CI)
p Valueb
1.3 (0.8–2.3) – – 0.8 (0.3–2.5) –
0.3 – – 0.7 –
HS, haplotype structure. a p Value – compared between risk control and cases. b p Value – compared between healthy control and cases. c Variant allele in each of the haplotype structure.
1344 cases and 1267 ethnically and geographically matched controls suggested that there exist no association between CYP2J2 and cardiovascular risk [27]. Similarly, another study evaluated for a potential correlation of the CYP2J2 polymorphism and a history of myocardial infarction reported lack of association [28]. In the present study, we have observed risk of MI while comparing cases with risk controls but not with healthy controls. This shows that CYP2J2*7 confounds risk for MI in the presence of conventional risk factors for MI. Here the risk controls subjects were having one of the conventional risk factor (hypertension) for MI. However, the individual role of CYP2J2*7 polymorphism in predisposing to MI in the absence of conventional risk factors such as hypertension, hypercholesterolemia, diabetes, etc., is still questionable. Therefore, large prospective studies need to validate the present findings. We also investigated the effect of CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3, however our results showed lack of association with MI risk. Several studies have demonstrated that CYP2C polymorphism affects the metabolism of arachidonic acid. Variant allele of CYP2C8*3 decreased the metabolite (11,12- and 14,15-EET) with a turnover of only 35–40% when compared with the normal CYP2C8*1 allele. Furthermore, there are reports that show a 34% decrease in the synthesis of EET in liver samples analyzed for homozygous mutant genotype of CYP2C8*3 [12]. One of the reasons for non association may be the age of control groups who were significantly younger than the cases. In line with our findings, several studies show contradictory reports of association between polymorphisms and CVDs. A study in Caucasian population
reported lack of association between MI and the variant alleles of CYP2C8 and CYP2C9 genes [23]. A clinical study done in Swedish population suggests that CYP2C8 and CYP2C9 gene polymorphisms may be a contributing factor in the pathogenesis of MI. The study reported that, carriers of the rare allelic variants of CYP2C8*3, CYP2C9*2, and CYP2C9*3 has shown to have an increased risk of AMI [18]. Ludwigshafen Risk and Cardiovascular Health (LURIC) study concluded that there is no cardiovascular risk associated with variant alleles of CYP2C8 and CYP2C9 [29]. A cohort study conducted in 2210 men and 3534 women reported that CYP2C9 alleles were associated with an increased risk of MI in women but not in men [30]. The variations of CYP2C8 and CYP2C9 genes were also analyzed for risk of hypertension in an African American population and the results also suggested lack of association [31]. Association of CYP2C8 and CYP2C9 variants with a modest increase in risk of AMI was observed in female Swedish descents [18]. A study conducted in Caucasian population revealed that men carrying variant genotypes of CYP2C9*3 or CYP2C9*2 showed a protective effect with an OR of 0.56 (95% CI: 0.33–0.95; p = 0.03) for the risk of MI [32]. Our previous report also suggests that there exist an ethnic difference between the South Indian population and other major ethnic groups, namely African, European, Chinese, and Japanese [11]. Thus the ethnicity may play a major role in the development and occurrence of a disease. The main limitation of the study was the numbers of female subjects among the MI cases were significantly lower when compared to the risk controls and
Table 4 Demographic detail of study subjects. Parameter
AMI cases (n = 287)
Risk controls (n = 279)
Healthy controls (n = 321)
p Valuea
p Valueb
Sex M/F (numbers) Age (years) BMI (kg/m2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg)
255/32 51.4 0.6 24.03 0.2 122.3 1.1 80.4 0.9
116/163 49.6 0.5 24.24 0.3 144.4 1.1 91.2 0.6
132/189 44.5 0.5 22.2 0.2 117.7 0.5 77.1 0.3
<0.001 NS NS <0.001 <0.001
<0.001 <0.001 <0.001 <0.01 <0.05
Diabetes mellitus N (%) Diabetic Non Diabetic
108 (37.6) 179 (62.4)
60 (21.5) 219 (78.5)
– –
<0.001
Alcohol users N (%) Current Never
132 (45.9) 155 (54.1)
58 (20.8) 221 (79.2)
63 (19.6) 258 (80.4)
<0.001
<0.001
Smokers N (%) Current Never Total cholesterol (mg/dL) Triglycerides (mg/dL) HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)
141 (49.1) 146 (50.9) 189.8 2.5 150.9 3.4 39.2 0.5 120.4 2.1
44 (15.8) 235 (84.2) 191.2 2.3 141.9 4.0 40.4 0.4 122.2 1.9
23 (7.2) 298 (92.8) 160.1 2.2 105.7 2.8 36.5 0.6 102.6 1.7
<0.001 NS <0.05 NS NS
<0.001 <0.001 <0.001 <0.05 <0.001
BMI, body mass index; HDL, high density lipoprotein; LDL, low density lipoprotein. Values are mean SEM and numbers. a p Value – compared between risk control and cases. b p Value – compared between healthy control and cases.
–
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healthy control groups, which may be one of the reasons for lack of association. In general, a single SNP cannot be attributed to the risk of a complex disorder. The observed results may be due to the interaction of variant alleles. Hence constructing haplotype structures may help in predicting disease association. In our study although the OR predicted risk for MI with the constructed HS CCAA, the p value did not show any significance. Conclusion In conclusion, the present study suggests that individuals who are carriers of CYP2J2*7 variant allele and having any one of the conventional risk factor for MI may be predisposed to risk of MI in South Indian population. Further, large scale studies have to be conducted to predict the genetic risk susceptibility of complex disorders like MI.
[12]
[13] [14]
[15]
[16]
[17]
[18]
[19]
Conflict of interest [20]
None declared. [21]
Acknowledgments This work was supported by Department of Science and Technology (DST), Government of India, Grant no. 95996. We thank all the subjects who participated in the study.
[22]
[23]
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Original research article
Association of CYP2C8, CYP2C9 and CYP2J2 gene polymorphisms with myocardial infarction in South Indian population Annan Sudarsan Arun Kumar a,*, Srinivasamurthy Suresh Kumar a, Gurusamy Umamaheswaran a, Ramasamy Kesavan a, Jayaraman Balachandar b, Chandrasekaran Adithan a a Pharmacogenomics Laboratory, Department of Pharmacology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India b Department of Cardiology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India
A R T I C L E I N F O
Article history: Received 5 June 2014 Received in revised form 9 July 2014 Accepted 11 August 2014 Available online 11 September 2014 Keywords: CYP2C8 CYP2C9 CYP2J2 Myocardial infarction Indian
A B S T R A C T
Background: Cardiovascular diseases (CVDs) are the major cause of mortality and morbidity worldwide. Myocardial infarction (MI) is a complex multi-factorial, polygenic disorder arising from an interaction between genetic makeup of individuals and various environmental factors. CYP2C8, CYP2C9 and CYP2J2 gene involved in the metabolism of arachidonic acid, generates epoxyeicosatrienoic acids (EETs) that mediate dilation of coronary arteries improving post-ischemic cardiac contractile function, reduce vascular inflammation, and increase intravascular fibrinolysis. The study is aimed at analyzing the association of CYP2C8, CYP2C9 and CYP2J2 gene polymorphisms and MI risk in the South Indian population. Methods: This retrospective study consisted of 287 MI patients, 279 risk control patients and 321 healthy individuals. Blood samples were collected from all the subjects and DNA was isolated using standard phenol–chloroform method. Polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) and real time-polymerase chain reaction (RT-PCR) methods were used for genotyping. To test the potential independent association between polymorphisms and the risk of MI, Multiple-logistic regression analysis was performed. Results: Our findings displayed a significant association between CYP2J2*7 (p = 0.04; OR = 2.0) polymorphism and MI while comparing cases with to risk controls. We did not observe any association of CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3 with MI. Conclusion: Our results suggest that individuals with any conventional risk factor for MI along with CYP2J2*7 variant allele may be predisposed to risk of MI in South Indian population. ß 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
Introduction Cardiovascular diseases (CVDs) are the major cause of mortality and morbidity worldwide [1]. CVDs are the outcome of numerous risk factors like age, body mass index (BMI), smoking, alcohol intake, hypertension, diabetes mellitus, hypercholesterolemia, less physical activity, tobacco use, stress, low intake of fruits, vegetables and raised waist to hip ratio. Worldwide, heart attacks are the leading cause of death among men and women. World
* Corresponding author. E-mail address: [email protected] (A.S. Arun Kumar).
health organization reported 17.3 million cardiovascular deaths in 2008, out of which 7.3 million was due to heart attack. It is estimated that there may be 23.3 million deaths due to heart diseases by 2030 [2]. Nitric oxide (NO) also known as endothelium derived relaxing factor (EDRF) produced by the vascular endothelial cells, is a key molecule which regulates vascular tone. In addition, the arachidonic acid metabolites, epoxyeicosatrienoic acids (EETs) also known as endothelium derived hyperpolarizing factor (EDHF) formed by drug metabolizing enzymes CYP2C8, CYP2C9, CYP2J2 isoforms in human endothelial cells, plays vital physiological roles in maintenance of vascular tone (vasodilatation), NOS3 regulation, vascular smooth muscle migration and fibrinolysis [3–6]. Drug metabolizing enzymes (DMEs) are a
http://dx.doi.org/10.1016/j.pharep.2014.08.010 1734-1140/ß 2014 Institute of Pharmacology, Polish Academy of Sciences. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
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diverse group of proteins which metabolizes vast array of xenobiotic compounds such as drugs, environmental pollutants, and endogenous compounds. Polymorphisms in CYP2C9 are analyzed to determine the clearance of drugs such as ibuprofen, indomethacin, flurbiprofencelecoxib, valdecoxib, etc. CYP2C8 also plays a vital role along with CYP2C9 for the clearance of ibuprofen [7]. It is also shown that CYP2C9 and CYP2C8 are inhibited by danazol, nicardipine, ketoconazole and lansoprazole. There is also evidence that sulfamethoxazole inhibit the enzyme activities of CYP2C9 and trimethoprim inhibit the enzyme activities of CYP2C8 [8]. The activity of CYP2J2 is reduced by more than 90% by drugs such as ketoconazole, lansoprazole, loratadine, miconazole, danazole, nicardipine and verapamil [9]. As all these drugs are commonly used for ailments such as myalgia, gastritis, etc., they also have important effect on activities of these enzymes. In humans CYP2C and CYP2J gene families are expressed in the endothelium, myocardium, and kidney. Vasodilatation, antihypertension, pro-angiogenesis, anti-atherosclerosis are some of the cardiovascular effects of CYP epoxygenases and EETs [10]. From previous reports it is evident that CYP2C8, and CYP2C9 genes are highly polymorphic in nature and their allelic variant frequencies differs based on ethnicity [11]. Human Cytochrome P450 [CYP] Allele Nomenclature Committee has so far described 14 variant alleles for CYP2C8 gene among which CYP2C8*2 (I269F) and CYP2C8*3 (R139K, K399R) has shown to decrease paclitaxel 60 -hydroxylase activity [12]. CYP2C8 metabolizes arachidonic acid to biologically active EETs (11,12EET and 14,15-EET) and therefore influences the circulating levels of EETs [13]. Thus allelic variants of CYP2C8 could produce an influencing pathological and physiological change in humans [14]. Human Cytochrome P450 [CYP] Allele Nomenclature Committee has so far described 58 variant alleles for CYP2C9 gene among which CYP2C9*2 and CYP2C9*3 are the most common polymorphisms [15]. Both these variants are associated with decreased metabolism of CYP2C9 substrates [16]. CYP2J2 metabolizes arachidonic acid primarly to 11,12-EET. This eicosanoid by inhibiting endothelial nuclear factor-B, possesses a potential antiinflammatory effect. EETs, such as 5,6-, 8,9-, and 14,15-EET, influence important vasodilatation functions effected via the mechanism of smooth muscle cell relaxation. Reports also suggest that EETs possess various other properties such as antioxidant, antiapoptotic, antimigratory and antithrombotic [17]. CYP2C8, CYP2C9 and CYP2J2 genes are involved in the pathogenesis of acute myocardial infarction (AMI) and therefore can be considered as candidate genes for MI [17,18]. The current study was designed out of our curiosity to find the association of these candidate CYP genes and the risk of MI among South Indian population. To the authors knowledge, the current study was the first study to evaluate the role of the allelic variants of CYP genes in patients with common cardiovascular diseases such as MI and hypertension. Literature surveys also showed that there are no studies done to evaluate the risk assessment of CYP2C8, CYP2C9, and CYP2J2 on MI patients in an Indian population. Thus the aim of the present study is to find the influence of
interethnic differences and the risk modifying effects of CYP2C8, CYP2C9 and CYP2J2 alleles on MI risk in Indian population. Methods Subjects The retrospective study consisted of three groups. Group1 comprised of 287 MI patients (MI diagnosis was based on World Health Organization criteria), group2 comprised of 279 risk control patients who had one of the conventional risk factor for coronary heart disease (hypertension) and group3 comprised of 321 healthy individuals. All the study subjects were interviewed using standardized questionnaire to know about the status of their lifestyle, smoking, alcohol and drug intake. The study subjects were aged between 25 and 75 years of either gender and unrelated ethnic Tamilians recruited from inpatients and out patients ward of Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER) Hospital, Pondicherry, India. Subjects were selected from families who were residing in South India for at least three generations and spoke Tamil as their mother tongue. The Institute Human Ethics Committee approval was obtained for the study. The study procedure was explained in detail and written informed consent was obtained from all the volunteers. Genotyping Volunteers were requested for 5 mL of blood and were collected from antecubital vein in polypropylene tubes containing 100 mL of 10% ethylene diamine tetra acetic acid (EDTA) as anticoagulant. The plasma was separated by centrifugation and was used for lipid profile analysis. Standard phenol–chloroform method was used to extract the genomic DNA from the peripheral leukocytes. After extraction, DNA was diluted to a concentration of 50 ng/mL and was stored at 20 8C. All the subjects were genotyped for CYP2C8*2 and CYP2C9*2 alleles by polymerase chain reaction– restriction fragment length polymorphism method (PCR-RFLP). Amplification was checked on 1% agarose gel. 8% or 12% polyacrylamide gels were used to identify electrophoresed enzyme-digested products. The details of the primers used for amplification, enzymes used for RFLP analysis and their band patterns are given in Table 1. Genotyping of CYP2C8*3, CYP2C9*3 and CYP2J2*7 was performed by real-time PCR allelic discrimination method (Applied Biosystems, Foster City, CA, USA). The thermocycler, kits for amplification and allelic discrimination were obtained from Applied Biosystems, Foster City, CA, USA. The assay ids for CYP2C8*3, CYP2C9*3 and CYP2J2*7 were C__25625782_20, C__27104892_10 and C__9581699_80, respectively. Statistical analysis Statistical Package for Social Sciences (SPSS windows version 16) was used for analyzing the genotype data. The demographic details with continuous variables were compared by Student ‘t’ test
Table 1 Primers and restriction enzymes used for genotyping of CYP2C8*2 and CYP2C9*2 alleles by PCR-RFLP method. Gene
SNP
Primers
Product Size (bp)
Annealing Temperature (8C)
Restriction enzyme
Major allele (1)
Minor allele (2)
CYP2C8
805A > T
167
56.9
Mbo I
69, 65, 33
98, 69
CYP2C9
430C > T
F – 50 AAAGTAAAAGAACACCAAGC30 R – 50 AAAATCCTTAGTAAATTACA30 F – 50 TACAAATACAATGAAAATATCATG30 R – 50 CTAACAACCAGACTCATAATG30
690
53.0
Ava II
521, 169
690
F – Forward; R – Reverse; bp – base pairs. (1) Band patterns observed under ultra violet light in the presence of wild type allele. (2) Band pattern observed under ultra violet light in the presence of variant allele.
A.S. Arun Kumar et al. / Pharmacological Reports 67 (2015) 97–101
and dichotomous variables were compared by Chi-square test for the study groups (cases, risk controls and healthy controls). Fisher’s exact test was used to compare the differences in genotype and allele frequencies. Logistic regression analysis was performed to adjust the confounding factors namely age, gender, BMI, alcohol, smoking, diabetic status, total cholesterol, triglycerides, low density lipoproteins, high density lipoproteins and to estimate the risk of MI. Adjusted odds ratio (OR) with 95% confidence interval (CI) was analyzed keeping low risk genotype as the reference groups. The OR of 1 was set as reference for the normal type genotype. HAPLOVIEW Software version 4.1 was used for analyzing the haplotype structures prevailing in the study population. A p < 0.05 was considered statistically significant.
Results Table 2 shows the crude and adjusted OR of CYP2J2*7, CYP2C8*2, CYP2C8*3, CYP2C9*2, CYP2C9*3 polymorphisms and MI compared between cases, risk controls and healthy controls. It also shows the genotype and allele frequencies of CYP genes in the South Indian population. There was a significant difference observed in the distribution of CYP2J2*7 GT + TT genotype between the cases and the risk controls (p = 0.03). The crude odds ratio (OR) showed 1.9 fold risk for MI. After adjusting for the confounding factors, the risk for MI was increased to 2.0 folds (adjusted OR = 2.0), significantly (p = 0.04). Significant difference was also observed in the distribution of CYP2J2*7 T allele when compared between the cases and the risk controls (p = 0.02). Other polymorphisms did not show a significant association with MI when comparing cases and risk controls with crude OR and after adjusting for confounding factors. While comparing cases with healthy controls, the crude OR for CYP2C9*2 showed 2.4 fold risk for MI with a p value of 0.04; but after adjusting for confounding factors the significance was not observed. Even though the other polymorphisms showed a risk for MI after adjusting for confounding factors, the p values was not significant. We also constructed and compared the haplotype structure (HS) for four polymorphisms CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), CYP2C8*3 (rs10509681) and CYP2C8*2
99
(rs11572103) among cases, risk controls and healthy controls. The HS with frequency greater than 1% is given in Table 3. Although the HS2 showed a 1.3 fold risk for MI while comparing cases and controls, the p value was not significant (data not shown). The demographic details of the subjects are same as described previously and given in Table 4 [19]. All the polymorphisms were in Hardy-Weinberg equilibrium, except CYP2C8*3 and CYP2J2*7 among cases and healthy controls respectively.
Discussion EETs are synthesized by many isoforms of CYP enzymes but have organ-specific expression [20]. These EETs are termed as EDHF which are partly formed by CYP2C8, CYP2C9, and CYP2J in human endothelial cells [12,21,22]. In addition to common risk factors like hypertension, obesity, hypercholesterolemia, diabetes mellitus, alcohol usage and cigarette smoking for coronary artery disease, an individual’s genetic makeup should be taken into account for evaluating the disease susceptibility. This is the first study to analyze the association of allelic variants of CYP2C8, CYP2C9, and CYP2J2 with MI in South Indian population. We found that CYP2J2*7 T allele frequency was higher in MI patients than in controls in South Indians and the analysis also showed that the variant allele may be a risk factor for MI susceptibility which were consistent with previous report [23,24]. The variant allele of CYP2J2*7 will prevent the binding of Sp1 transcription factor to the promoter region which leads to the decreased promoter activity. The normal type CYP2J2 promoter was twice active than the variant CYP2J2*7 allele and had reduced EET activities [17]. EETs activate smooth muscle potassium channels leading hyperpolarization and vascular relaxation. However, there are also reports that provide lack of association of CYP2J2*7 polymorphism with coronary artery disease (CAD) in different ethnics. A large cross-sectional study in LURIC cohort did not confirm CYP2J2 polymorphism as a risk factor for CAD or MI [25]. Whereas a study conducted in African-American suggested that CYP2J2 polymorphism may be an important risk factor for coronary heart disease [26]. A study conducted in a total of
Table 2 Association between CYP2J2*7, CYP2C8*2, CYP2C8*3, CYP2C9*2, CYP2C9*3 polymorphisms and AMI compared between cases, risk controls and healthy controls. Gene & SNP
Genotype
Cases
Risk controls
CYP2J2*7 76G > T rs890293
GG GT + TT G T
251 36 536 38
(87.5) (12.5) (93.4) (6.6)
260 19 538 20
(93.2) (6.8) (96.4) (3.6)
CYP2C8*2 805A > T rs11572103
AA AT + TT A T
278 9 565 9
(96.9) (3.1) (98.4) (1.6)
269 10 548 10
(96.4) (3.6) (98.2) (1.8)
CYP2C8*3 1196A > G rs10509681
AA AG + GG A G
268 19 555 19
(93.4) (6.6) (96.7) (3.3)
260 19 539 19
(93.2) (6.8) (96.6) (3.4)
CYP2C9*2 430C > T rs1799853
CC CT + TT C T
268 19 554 20
(93.4) (6.6) (96.5) (3.5)
261 18 540 18
(93.5) (6.5) (96.8) (3.2)
CYP2C9*3 1075A > C rs1057910
AA AC + CC A C
240 47 529 49
(83.6) (16.4) (92.2) (8.5)
236 43 511 47
(84.6) (15.4) (91.6) (8.4)
OR (95% CI)
p Value
OR (95% CI) adjusted
p Value
1.9 (1.0–3.5)
0.03
2.0 (1.0–4.1)
0.04
1.9 (1.0–3.3)
0.02
0.8 (0.3–2.1)
0.9
0.8 (0.3–2.1)
0.8
0.9 (0.5–1.8)
0.9
0.9 (0.5–1.8)
0.9
1.0 (0.5–2.0)
0.9
1.0 (0.5–2.0)
0.9
1.0 (0.6–1.6)
0.8
1.0 (0.6–1.5)
0.9
0.9 (0.3–2.8)
1.5 (0.5–4.5)
1.2 (0.4–3.6)
1.2 (0.7–2.1)
0.9
0.4
0.7
0.5
Healthy control 286 35 606 36
(89.1) (10.9) (94.4) (5.6)
310 11 631 11
(96.6) (3.4) (98.3) (1.7)
304 17 625 17
(94.7) (5.3) (97.4) (2.6)
312 9 633 9
(97.2) (2.8) (98.6) (1.4)
275 46 593 49
(85.7) (14.3) (92.4) (7.6)
OR (95% CI)
p Value
OR (95% CI) adjusted
p Value
1.1 (0.7–1.9)
0.6
1.7 (0.8–3.6)
0.2
1.1 (0.7–1.9)
0.5
0.9 (0.3–2.2)
0.8
1.5 (0.3–7.4)
0.6
0.9 (0.3–2.2)
0.8
1.2 (0.6–2.4)
0.6
1.0 (0.3–3.9)
0.9
1.2 (0.6–2.4)
0.6
2.4 (1.0–5.5)
0.04
3.3 (0.7–15.6)
0.1
2.5 (1.1–5.6)
0.02
1.1 (0.7–1.8)
0.5
1.3 (0.6–2.8)
0.4
1.1 (0.7–1.6)
0.6
Covariates included in the regression analysis were age, gender, BMI, alcohol, smoking, diabetic status, total cholesterol, triglycerides, low density lipoproteins and high density lipoproteins. OR (95% CI): odds ratio (95% confidence interval); OR (95% CI) adjusted: odds ratio obtained after performing logistic regression analysis.
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Table 3 Haplotype structure and frequencies of rs1799853, rs1057910, rs10509681 and rs11572103 among cases, risk controls and healthy controls. Haplotype
rs1799853
rs1057910
rs10509681
rs11572103
Cases (n = 465)
Risk controls (n = 275)
HS1 HS2 HS3 HS4 HS5 HS6
C C Tc C C Tc
A Cc A A A A
A A Gc A Gc A
A A A Tc A A
397 38 10 7 6 –
239 18 9 5 – –
(85.3) (8.2) (2.1) (1.4) (1.3)
(86.6) (6.7) (3.3) (1.8)
OR (95% CI)
p Valuea
1.3 (0.7–2.3) 0.7 (0.3–1.7) 0.9 (0.3–2.7) – –
0.4 0.4 0.7 – –
Healthy controls (n = 356) 317 23 – – 6 4
(89.0) (6.4)
(1.7) (1.1)
OR (95% CI)
p Valueb
1.3 (0.8–2.3) – – 0.8 (0.3–2.5) –
0.3 – – 0.7 –
HS, haplotype structure. a p Value – compared between risk control and cases. b p Value – compared between healthy control and cases. c Variant allele in each of the haplotype structure.
1344 cases and 1267 ethnically and geographically matched controls suggested that there exist no association between CYP2J2 and cardiovascular risk [27]. Similarly, another study evaluated for a potential correlation of the CYP2J2 polymorphism and a history of myocardial infarction reported lack of association [28]. In the present study, we have observed risk of MI while comparing cases with risk controls but not with healthy controls. This shows that CYP2J2*7 confounds risk for MI in the presence of conventional risk factors for MI. Here the risk controls subjects were having one of the conventional risk factor (hypertension) for MI. However, the individual role of CYP2J2*7 polymorphism in predisposing to MI in the absence of conventional risk factors such as hypertension, hypercholesterolemia, diabetes, etc., is still questionable. Therefore, large prospective studies need to validate the present findings. We also investigated the effect of CYP2C8*2, CYP2C8*3, CYP2C9*2 and CYP2C9*3, however our results showed lack of association with MI risk. Several studies have demonstrated that CYP2C polymorphism affects the metabolism of arachidonic acid. Variant allele of CYP2C8*3 decreased the metabolite (11,12- and 14,15-EET) with a turnover of only 35–40% when compared with the normal CYP2C8*1 allele. Furthermore, there are reports that show a 34% decrease in the synthesis of EET in liver samples analyzed for homozygous mutant genotype of CYP2C8*3 [12]. One of the reasons for non association may be the age of control groups who were significantly younger than the cases. In line with our findings, several studies show contradictory reports of association between polymorphisms and CVDs. A study in Caucasian population
reported lack of association between MI and the variant alleles of CYP2C8 and CYP2C9 genes [23]. A clinical study done in Swedish population suggests that CYP2C8 and CYP2C9 gene polymorphisms may be a contributing factor in the pathogenesis of MI. The study reported that, carriers of the rare allelic variants of CYP2C8*3, CYP2C9*2, and CYP2C9*3 has shown to have an increased risk of AMI [18]. Ludwigshafen Risk and Cardiovascular Health (LURIC) study concluded that there is no cardiovascular risk associated with variant alleles of CYP2C8 and CYP2C9 [29]. A cohort study conducted in 2210 men and 3534 women reported that CYP2C9 alleles were associated with an increased risk of MI in women but not in men [30]. The variations of CYP2C8 and CYP2C9 genes were also analyzed for risk of hypertension in an African American population and the results also suggested lack of association [31]. Association of CYP2C8 and CYP2C9 variants with a modest increase in risk of AMI was observed in female Swedish descents [18]. A study conducted in Caucasian population revealed that men carrying variant genotypes of CYP2C9*3 or CYP2C9*2 showed a protective effect with an OR of 0.56 (95% CI: 0.33–0.95; p = 0.03) for the risk of MI [32]. Our previous report also suggests that there exist an ethnic difference between the South Indian population and other major ethnic groups, namely African, European, Chinese, and Japanese [11]. Thus the ethnicity may play a major role in the development and occurrence of a disease. The main limitation of the study was the numbers of female subjects among the MI cases were significantly lower when compared to the risk controls and
Table 4 Demographic detail of study subjects. Parameter
AMI cases (n = 287)
Risk controls (n = 279)
Healthy controls (n = 321)
p Valuea
p Valueb
Sex M/F (numbers) Age (years) BMI (kg/m2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg)
255/32 51.4 0.6 24.03 0.2 122.3 1.1 80.4 0.9
116/163 49.6 0.5 24.24 0.3 144.4 1.1 91.2 0.6
132/189 44.5 0.5 22.2 0.2 117.7 0.5 77.1 0.3
<0.001 NS NS <0.001 <0.001
<0.001 <0.001 <0.001 <0.01 <0.05
Diabetes mellitus N (%) Diabetic Non Diabetic
108 (37.6) 179 (62.4)
60 (21.5) 219 (78.5)
– –
<0.001
Alcohol users N (%) Current Never
132 (45.9) 155 (54.1)
58 (20.8) 221 (79.2)
63 (19.6) 258 (80.4)
<0.001
<0.001
Smokers N (%) Current Never Total cholesterol (mg/dL) Triglycerides (mg/dL) HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)
141 (49.1) 146 (50.9) 189.8 2.5 150.9 3.4 39.2 0.5 120.4 2.1
44 (15.8) 235 (84.2) 191.2 2.3 141.9 4.0 40.4 0.4 122.2 1.9
23 (7.2) 298 (92.8) 160.1 2.2 105.7 2.8 36.5 0.6 102.6 1.7
<0.001 NS <0.05 NS NS
<0.001 <0.001 <0.001 <0.05 <0.001
BMI, body mass index; HDL, high density lipoprotein; LDL, low density lipoprotein. Values are mean SEM and numbers. a p Value – compared between risk control and cases. b p Value – compared between healthy control and cases.
–
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healthy control groups, which may be one of the reasons for lack of association. In general, a single SNP cannot be attributed to the risk of a complex disorder. The observed results may be due to the interaction of variant alleles. Hence constructing haplotype structures may help in predicting disease association. In our study although the OR predicted risk for MI with the constructed HS CCAA, the p value did not show any significance. Conclusion In conclusion, the present study suggests that individuals who are carriers of CYP2J2*7 variant allele and having any one of the conventional risk factor for MI may be predisposed to risk of MI in South Indian population. Further, large scale studies have to be conducted to predict the genetic risk susceptibility of complex disorders like MI.
[12]
[13] [14]
[15]
[16]
[17]
[18]
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Conflict of interest [20]
None declared. [21]
Acknowledgments This work was supported by Department of Science and Technology (DST), Government of India, Grant no. 95996. We thank all the subjects who participated in the study.
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