Abstract

Background:

The cytochrome P450 (CYP) epoxygenase pathway produces arachidonic acid metabolites that are vasoactive, that affect renal sodium handling, and that have been proposed to play a mechanistic role in hypertension. Multiple single nucleotide polymorphisms (SNP) in CYP2C8, 2C9, 2J2 and soluble epoxide hydrolase (sEH) have been identified, many of which have altered functional activity in vitro. We performed a case-control study to determine the prevalence of epoxygenase-related SNP in African American individuals and to evaluate whether these SNP are associated with increased risk of hypertension.

Methods:

Normotensive African American individuals (N = 107) and African American patients with hypertension (N = 108) were recruited. DNA was extracted from a venous blood sample and genotyped for CYP2C8*2,*3, CYP2C9*2-*5,*8,*11, CYP2J2 *2-*7, L50L, R49S, V113M, N124S, sEH R287Q, and sEH 403Rins variant alleles by allelic discrimination using real-time polymerase chain reaction. Genotype and allele frequencies were calculated and associations with hypertension were estimated using unconditional logistic regression, adjusting for age and sex.

Results:

No association was found between any of the variant alleles and hypertension. We did find that only the CYP2C8*3and CYP2C9*2 alleles were in strong linkage disequilibrium in both the hypertensive and healthy African American groups, a finding that was reported previously in healthy individuals of white ethnicity.

Conclusions:

These results suggest that these epoxygenase-related SNP are not associated with increased risk of hypertension in the African American population. There was significant linkage disequilibrium between CYP2C8*3 and CYP2C9*2 alleles that was not associated with hypertension. Am J Hypertens 2005;18:1276–1281 © 2005 American Journal of Hypertension, Ltd.

Arachidonic acid metabolism through the cyclooxygenase pathway, which yields prostaglandins, and the lipoxygenase pathway, which produces leukotrienes, have been well characterized.1–5 However, arachidonic acid is also metabolized by cytochrome P450 (CYP) pathways that result in the formation of novel metabolites. These metabolites have vasoactive properties and potent effects on renal salt and water transport. Moreover, these metabolites have been proposed to play a mechanistic role in hypertension.1–5 The so-called “P450 cascade” is comprised of epoxidation (epoxygenase pathway), allylic oxidation, and ω-hydroxylation. The epoxygenase pathway involves human CYP2C isozymes such as CYP2C8, CYP2C9, CYP2C19, and CYP2J2, all of which synthesize epoxyeicosatrienoic acids (EET) metabolites.1–5 The EET are further metabolized by soluble epoxide hydrolase (sEH) to their corresponding dihydroxy metabolites, the DHET, which have vasoconstrictor or vasodilator properties depending on the vascular bed.

The epoxide metabolites have been implicated in both animal and human studies of hypertension. For example, 11,12-epoxyeicosatrienoic acid (11,12-EET), the putative endothelium-derived hyperpolarizing factor (EDHF), is formed directly by CYP2C9 and CYP2C8, and hydrolyzed by sEH to 11,12-DHET.6–8,9 These metabolites have also been shown to have potent effects on renal salt and water transport,10 and a tenfold higher urinary excretion of 11,12-DHET and 14,15-DHET has been observed in pregnancy-induced hypertension compared with values in pregnant control subjects.11 In animal models, the spontaneously hypertensive (SHR) rat has been shown to exhibit increased CYP2J expression and twofold higher levels of 14,15-EET and 11,12-EET compared with the normotensive Wistar-Kyoto rats.12 The SHR rats have also been shown to have abnormal pressure natriuresis, which is corrected by inhibitors of EET and 20-HETE production.13 In addition, EET have been shown to inhibit L-type cardiac calcium channels reconstituted from porcine coronary arteries.14

These pathways have been postulated to be mechanistically involved in the control of blood pressure and the initiation of essential hypertension in human beings.1–5,11

Therefore, genetic control maybe important because several of the enzymes discussed above have polymorphisms that are frequent and that cause functional effects in vitro.15–19 The aim of the present study was to determine whether these polymorphisms are associated with hypertension in African American individuals by using a case-control approach. We determined the frequency of CYP2C8*2,*3, CYP C9*2-*5,*8,*11, CYP2J2*2-*7, V113M, N124S, sEH 403Rins, and sEH R287Q variant alleles in normotensive and hypertensive African Americans.

Methods

Clinical Protocol

Normotensive (N = 107) and hypertensive African Americans (N = 108) recruited from the New Orleans metropolitan area were seen in the Tulane–Louisiana State University Charity Hospital General Clinical Research Center in New Orleans. Informed consent approved by the Tulane Institutional Review Board was obtained from all subjects. A medical history and three manual blood pressure measurements were then taken 5 min apart, and venous blood was obtained for DNA isolation. Hypertension was defined as the average of three blood pressure measurements >140/90 or as current use of antihypertensive medication. Subjects with a history of renal or cardiovascular disease were excluded. All subjects had normal serum creatinine on screening with a comprehensive laboratory profile.

Genotyping

DNA was isolated from peripheral blood mononuclear cells using standard DNA isolation kits. The alleles for all SNP were genotyped at the Functional Genomics Laboratory, University of Washington (Seattle, WA). We followed a previously published protocol by Higashi et al20 to genotype CYP2C9*3,*4,*5 and *11. For genotyping CYP2J2*7, CYP2J2 R49S, CYP2J2 V113M and CYP2J2 N124S we ordered Custom Taqman SNP assays or assays-by-design from Applied Biosystems (Foster City, CA), in which we sent a 500–base pairs region surrounding the SNP site of interest via the File Builder program that we downloaded from the company's website. These assays-by-design were run according to Applied Biosystems’ protocol using 10 ng of genomic DNA in an 11-μL reaction.

For the SNP CYP2C8*2, CYP2C8*3, CYP2C9*2, CYP2C9*8, sEH-Q, and sEH-RR we developed Taqman 5′-nuclease assays to genotype the alleles. The primers and probes were chosen using Primer Express software, version 1.5 (Applied Biosystems, Foster City, CA) following standardized guidelines recommended by the manufacturer. All primers and probes are listed in Table 1.

Table 1

Oligonucleotide primers and probes for genotyping assays

Allele Specific primers and probes Allele Specific primers and probes 
CYP2C8*2 (exon 5) SP: 5′-TTg CTC TTA CAC gAA gTT ACA TTA ggg A-3′ CYP2J2 V113M SP: 5′-CCC TTA TCC ACA Tgg ACC AAA ACT T-3′ 
 AP: 5′-CgA TgA ATC ACA AAA Tgg ACA AgA A-3′  AP: 5′-TCg TTg gCC AAg AAA CTT ACC A-3′ 
 WT: 5′-FAM-TTC CTg ATC AAA Atg-MGB-3′  WT: 5′-VIC-ACC gCC CCg TgA CC-MGB-3′ 
 MUT: 5′-VIC-TTC CTg TTC AAA Atg-MGB-3′  MUT: 5′-FAM-CCg CCC CAT gAC C-MGB-3′ 
CYP2C8*3 (exon 3) SP: 5′-ATT Agg AAT CAT TTC CAg CAA Tgg AA-3′ CYP2J2 N124S SP: 5′-CCC TTA TCC ACA Tgg ACC AAA ACT T-3′ 
 AP: 5′-CAA CTC CTC CAC AAg gCA gTg A-3′  AP: 5′-CAA CAT CAA ACA CTC ACC TTT CgT T-3′ 
 WT: 5′-FAM-ATg CTC CTC TTC C-MGB-3′  WT: 5′-VIC-CTT TAA gAA AAA Tgg TAA gTT T-MGB-3′ 
 MUT: 5′-VIC-AAT gCT CTT CTT CC-MGB-3′  MUT: 5′-FAM-AAg AAA AgT ggT AAg TTT-MGB-3′ 
CYP2C8*3 (exon 8) SP: 5′-TCC ACT ACT TCT CCT CAC TTC Tgg ACT-3′ CYP2J2*2 (exon 3) SP: 5′-TTC CCA ggA TTg ATT ATg TCA AgT G-3′ 
 AP: 5′-gCC ATT CTT ATC TAg AAA gTg gCC A-3′  AP: 5′-gTC TCT CAC CTC TgT CAT ATg CAA Tg-3′ 
 WT: 5′-FAM-Agg AAA TTC TTT gTC ATC AT-MGB-3′  WT: 5′-FAM-TCA CTC TgA CAg CAC T-MGB-3′ 
 MUT: 5′-VIC-Agg AAA TTC TCT gTC ATC-MGB-3′  MUT: 5′-VIC-TCA CTC Tgg CAg CAC-MGB-3′ 
CYP2C9*2 (exon 3) SP: 5′-gAA TTg TTT TCA gCA ATg gAA AgA AA-3′ CYP2J2*3 (exon 3) SP: 5′-TTC CCA ggA TTg ATT ATg TCA AgT G-3′ 
 AP: 5′-gTA Agg TCA gTg ATA Tgg AgT Agg gTC A-3′  AP: 5′-gTC TCT CAC CTC TgT CAT ATg CAA Tg-3′ 
 WT: 5′-FAM-TgA ACA Cgg TCC TC-MGB-3′  WT: 5′-FAM-TgA ATg CgT TCC TC-MGB-3′ 
 MUT: 5′-TET-TgA ACA CAg TCC TCA-MGB-3′  MUT: 5′-VIC-CTg AAT gCT TTC CTC T-MGB-3′ 
CYP2C9*8 (exon 3) SP: 5′-gAA TTg TTT TCA gCA ATg gAA AgA AA-3′ CYP2J2*4 (exon 4) SP: 5′-gAg ACA AAT CCA TCA gAA ggA TCC A-3′ 
 AP: 5′-gTA Agg TCA gTg ATA Tgg AgT Agg gTC A-3′  AP: 5′-CAT gTC TTT gAA gCC TCC AAg TAT gT-3′ 
 WT: 5′-FAM-CAA ggC AgC ggg CTT CCT CT-TAMRA-3′  WT: 5′-FAM-TCC AAT ATC ATT TgC TCC A-MGB-3′ 
 MUT: 5′-TET-CAC AAg gCA gTg ggC TTC CTC TT-TAMRA-3′  MUT: 5′-VIC-TCC AAT ATC AAT TgC TCC A-MGB-3′ 
sEH-RR SP: 5′-ggA gTg gCT gAg gCT gAA C-3′ CYP2J2*6 (exon 8) SP: 5′-TgC TgC TTT CTC TAg ggT ACC AT-3′ 
 AP: 5′-CTT gCT CTg AAg Agg CTT TTg A-3′  AP: 5′-ggg Tgg CCC ACT CTg T-3′ 
 WT: 5′-FAM-Tgg AAC AgA ACC TgA gTC ggA CTT TC-TAMRA-3′  WT: 5′-VIC-CCT gAC CAA TTT gAC-MGB-3′ 
 MUT: 5′-TET-CAg AAC CTg AgT CgT Cgg ACT TTC A-TAMRA-3′  MUT: 5′-FAM-TCC TgA CCT ATT TgA C-MGB-3′ 
sEH-Q SP: 5′-ATC CCT gCT CTg gCC CA-3′ CYP2J2*7 (G-50T) SP: 5′-CAg CgC CTg gCA TCT TC-3′ 
 AP: 5′-ggA ggA gCA gAT gAC TCT CCA TA-3′  AP: 5′-CCA gCA ggC gAC ggT-3′ 
 WT: 5′-FAM-ATg TCC ATA gCT Agg ACC Cgg TAA CCT g-TAMRA-3′  WT: 5′-VIC-CCC gCC TCg CTC C-MGB-3′ 
 MUT: 5′-TET-CAg gTT ACC Agg TCC TAg CTA Tgg ACA T-TAMRA-3′  MUT: 5′-FAM-CCC gCC TAg CTC C-MGB-3′ 
CYP2J2 R49S SP: 5′-Cgg CgC CCA AAg AAC TAC-3′   
 AP: 5′-ACA Agg AAg AAg TTg CCA Agg A-3′   
 WT: 5′-VIC-CTg gCg CCT gCC CT-MGB-3′   
 MUT: 5′-FAM-CCT ggA gCC TgC CCT-MGB-3′   
Allele Specific primers and probes Allele Specific primers and probes 
CYP2C8*2 (exon 5) SP: 5′-TTg CTC TTA CAC gAA gTT ACA TTA ggg A-3′ CYP2J2 V113M SP: 5′-CCC TTA TCC ACA Tgg ACC AAA ACT T-3′ 
 AP: 5′-CgA TgA ATC ACA AAA Tgg ACA AgA A-3′  AP: 5′-TCg TTg gCC AAg AAA CTT ACC A-3′ 
 WT: 5′-FAM-TTC CTg ATC AAA Atg-MGB-3′  WT: 5′-VIC-ACC gCC CCg TgA CC-MGB-3′ 
 MUT: 5′-VIC-TTC CTg TTC AAA Atg-MGB-3′  MUT: 5′-FAM-CCg CCC CAT gAC C-MGB-3′ 
CYP2C8*3 (exon 3) SP: 5′-ATT Agg AAT CAT TTC CAg CAA Tgg AA-3′ CYP2J2 N124S SP: 5′-CCC TTA TCC ACA Tgg ACC AAA ACT T-3′ 
 AP: 5′-CAA CTC CTC CAC AAg gCA gTg A-3′  AP: 5′-CAA CAT CAA ACA CTC ACC TTT CgT T-3′ 
 WT: 5′-FAM-ATg CTC CTC TTC C-MGB-3′  WT: 5′-VIC-CTT TAA gAA AAA Tgg TAA gTT T-MGB-3′ 
 MUT: 5′-VIC-AAT gCT CTT CTT CC-MGB-3′  MUT: 5′-FAM-AAg AAA AgT ggT AAg TTT-MGB-3′ 
CYP2C8*3 (exon 8) SP: 5′-TCC ACT ACT TCT CCT CAC TTC Tgg ACT-3′ CYP2J2*2 (exon 3) SP: 5′-TTC CCA ggA TTg ATT ATg TCA AgT G-3′ 
 AP: 5′-gCC ATT CTT ATC TAg AAA gTg gCC A-3′  AP: 5′-gTC TCT CAC CTC TgT CAT ATg CAA Tg-3′ 
 WT: 5′-FAM-Agg AAA TTC TTT gTC ATC AT-MGB-3′  WT: 5′-FAM-TCA CTC TgA CAg CAC T-MGB-3′ 
 MUT: 5′-VIC-Agg AAA TTC TCT gTC ATC-MGB-3′  MUT: 5′-VIC-TCA CTC Tgg CAg CAC-MGB-3′ 
CYP2C9*2 (exon 3) SP: 5′-gAA TTg TTT TCA gCA ATg gAA AgA AA-3′ CYP2J2*3 (exon 3) SP: 5′-TTC CCA ggA TTg ATT ATg TCA AgT G-3′ 
 AP: 5′-gTA Agg TCA gTg ATA Tgg AgT Agg gTC A-3′  AP: 5′-gTC TCT CAC CTC TgT CAT ATg CAA Tg-3′ 
 WT: 5′-FAM-TgA ACA Cgg TCC TC-MGB-3′  WT: 5′-FAM-TgA ATg CgT TCC TC-MGB-3′ 
 MUT: 5′-TET-TgA ACA CAg TCC TCA-MGB-3′  MUT: 5′-VIC-CTg AAT gCT TTC CTC T-MGB-3′ 
CYP2C9*8 (exon 3) SP: 5′-gAA TTg TTT TCA gCA ATg gAA AgA AA-3′ CYP2J2*4 (exon 4) SP: 5′-gAg ACA AAT CCA TCA gAA ggA TCC A-3′ 
 AP: 5′-gTA Agg TCA gTg ATA Tgg AgT Agg gTC A-3′  AP: 5′-CAT gTC TTT gAA gCC TCC AAg TAT gT-3′ 
 WT: 5′-FAM-CAA ggC AgC ggg CTT CCT CT-TAMRA-3′  WT: 5′-FAM-TCC AAT ATC ATT TgC TCC A-MGB-3′ 
 MUT: 5′-TET-CAC AAg gCA gTg ggC TTC CTC TT-TAMRA-3′  MUT: 5′-VIC-TCC AAT ATC AAT TgC TCC A-MGB-3′ 
sEH-RR SP: 5′-ggA gTg gCT gAg gCT gAA C-3′ CYP2J2*6 (exon 8) SP: 5′-TgC TgC TTT CTC TAg ggT ACC AT-3′ 
 AP: 5′-CTT gCT CTg AAg Agg CTT TTg A-3′  AP: 5′-ggg Tgg CCC ACT CTg T-3′ 
 WT: 5′-FAM-Tgg AAC AgA ACC TgA gTC ggA CTT TC-TAMRA-3′  WT: 5′-VIC-CCT gAC CAA TTT gAC-MGB-3′ 
 MUT: 5′-TET-CAg AAC CTg AgT CgT Cgg ACT TTC A-TAMRA-3′  MUT: 5′-FAM-TCC TgA CCT ATT TgA C-MGB-3′ 
sEH-Q SP: 5′-ATC CCT gCT CTg gCC CA-3′ CYP2J2*7 (G-50T) SP: 5′-CAg CgC CTg gCA TCT TC-3′ 
 AP: 5′-ggA ggA gCA gAT gAC TCT CCA TA-3′  AP: 5′-CCA gCA ggC gAC ggT-3′ 
 WT: 5′-FAM-ATg TCC ATA gCT Agg ACC Cgg TAA CCT g-TAMRA-3′  WT: 5′-VIC-CCC gCC TCg CTC C-MGB-3′ 
 MUT: 5′-TET-CAg gTT ACC Agg TCC TAg CTA Tgg ACA T-TAMRA-3′  MUT: 5′-FAM-CCC gCC TAg CTC C-MGB-3′ 
CYP2J2 R49S SP: 5′-Cgg CgC CCA AAg AAC TAC-3′   
 AP: 5′-ACA Agg AAg AAg TTg CCA Agg A-3′   
 WT: 5′-VIC-CTg gCg CCT gCC CT-MGB-3′   
 MUT: 5′-FAM-CCT ggA gCC TgC CCT-MGB-3′   

AP = antisense primer; FAM = 6-carboxy-fluorescein; MGB = Minor Groove Binder; MUT = mutant allele; SP = sense primer; TAMRA = 6-carboxy-tetramethyl-rhodamine; TET = tetrachloro-6-carboxy-fluorescein; VIC = chemical name not yet released; WT = wild-type allele.

All assays were run on 96-well plates, each containing genotyping controls consisting of four wells with homozygous wild-type control samples, four wells holding heterozygote control samples, four wells holding homozygous mutant control samples, where available, and four wells representing no template controls (no DNA samples). The other 80 wells per plate contained the samples to be genotyped. The plates were then run on either a DNA Engine Tetrad PTC-225 (MJ Research, Alameda, CA) or an Eppendorf Mastercycler (Brinkman, Westbury, NY) thermocycler using optimized polymerase chain reaction parameters. We performed an end-point analysis on the 7700 Sequence Detection System (Applied Biosystems, Foster City, CA). The samples were genotyped according to where they clustered in reference to the controls. For each SNP, a random 10% of samples were repeated using TaqMan-based assays, and an additional 5% of the samples were verified using direct DNA sequencing. All results were concordant.

Statistical Analysis

The χ2 goodness of fit test was used to evaluate significant deviation in the genotype distribution from Hardy-Weinberg equilibrium. Because more individuals of younger age were recruited among the control subjects than among the case subjects, unconditional logistic regression was performed, adjusting for age and sex as covariates, to obtain genotypic odds ratios (OR) and 95% confidence intervals (CI). A dominant genetic model (homozygotes + heterozygotes versus wild types) was assumed. Likelihood ratio tests comparing models with and without interaction terms were used to assess for evidence of interaction between SNP. All statistical analyses were performed using Intercooled Stata software, version 8.2 (Stata Corp., College Station, TX).

Linkage disequilibrium (LD) between pairs of SNP among cases and controls combined was calculated using the expectation-maximization (EM) algorithm,21 which estimates the pairwise haplotype frequencies from genotype data in unrelated individuals. The LD is expressed as r2 (also sometimes denoted Δ2), and takes a value of 1 if only two haplotypes are present.22

Results

The African American study population was comparable in terms of gender but the mean age of the hypertensive subjects was 10 years older than healthy control subjects. Demographic data are shown Table 2. Genotype frequencies were in Hardy-Weinberg equilibrium both in healthy and in hypertensive African Americans except for the CYP2J2*7 promoter polymorphism (P= .02). Genotype and allele frequencies for epoxygenase variants are shown in Table 3. There were no significant differences in allele frequencies between healthy and hypertensive African Americans for any of the SNP examined. After adjusting for age and sex, there was still no association observed with hypertension; the odds ratios are shown in Table 4. There was significant linkage disequilibrium between CYP2C9*2 and CYP2C8*3 in African Americans (r2 = 0.86). The remaining 18 variant alleles were not in linkage disequilibrium and therefore showed no evidence of co-inheritance. The CYP 2J2*2-*6, R49S, and V113M alleles (newly described) were not detected in the healthy and hypertensive African Americans. No significant interactions were observed.

Table 3

Genotype and allele frequencies of epoxygenase polymorphisms in hypertensive (HTN) and normotensive (C) African American subjects

CYP Group N Wild type Heterozygote Homozygote Allele (%) frequency 
2C8*2 107 76 29 15 
 HTN 108 74 31 17 
2C8*3 107 100 3.3 
 HTN 108 101 3.2 
2C9*2 107 100 3.3 
 HTN 108 101 3.2 
2C9*3 107 102 2.3 
 HTN 108 102 2.8 
2C9*4 107 107 
 HTN 108 108 
2C9*5 107 106 0.47 
 HTN 108 105 1.9 
2C9*8 107 103 1.9 
 HTN 108 100 4.2 
2C9*11 107 104 1.4 
 HTN 108 105 1.4 
2J2*2-*6 102 102 
 HTN 94 94 
2J2 R49S 102 102 
2J2 V113M  102 102 
2J2 L50L  102 99 1.5 
 HTN 94 94 
  94 94 
  94 86 4.3 
2J2*7 102 83 15 11 
 HTN 94 78 15 9.0 
2J2 N124S 102 101 0.49 
 HTN 93 92 0.54 
sEH R287Q 106 91 13 8.0 
 HTN 108 94 14 6.5 
R403 ins 106 101 2.4 
 HTN 108 104 1.9 
CYP Group N Wild type Heterozygote Homozygote Allele (%) frequency 
2C8*2 107 76 29 15 
 HTN 108 74 31 17 
2C8*3 107 100 3.3 
 HTN 108 101 3.2 
2C9*2 107 100 3.3 
 HTN 108 101 3.2 
2C9*3 107 102 2.3 
 HTN 108 102 2.8 
2C9*4 107 107 
 HTN 108 108 
2C9*5 107 106 0.47 
 HTN 108 105 1.9 
2C9*8 107 103 1.9 
 HTN 108 100 4.2 
2C9*11 107 104 1.4 
 HTN 108 105 1.4 
2J2*2-*6 102 102 
 HTN 94 94 
2J2 R49S 102 102 
2J2 V113M  102 102 
2J2 L50L  102 99 1.5 
 HTN 94 94 
  94 94 
  94 86 4.3 
2J2*7 102 83 15 11 
 HTN 94 78 15 9.0 
2J2 N124S 102 101 0.49 
 HTN 93 92 0.54 
sEH R287Q 106 91 13 8.0 
 HTN 108 94 14 6.5 
R403 ins 106 101 2.4 
 HTN 108 104 1.9 
Table 2

Demographics characteristics of study subjects

Characteristic Hypertensive Normotensive P value 
N 108 107  
Age (mean ± SD) 48.7 ± 11.3 37.4 ± 10.3 <.001 
Gender (% female) 57.4 46.7 .12 
Weight (lb) 202.9 ± 45.7 182 ± 47.5 <.001 
Characteristic Hypertensive Normotensive P value 
N 108 107  
Age (mean ± SD) 48.7 ± 11.3 37.4 ± 10.3 <.001 
Gender (% female) 57.4 46.7 .12 
Weight (lb) 202.9 ± 45.7 182 ± 47.5 <.001 
Table 4

Age- and sex-adjusted risk of hypertension (defined as ≥140/90 mm Hg), associated with epoxygenase single-nucleotide polymorphisms among African American subjects

Epoxygenase polymorphism OR (95% CI) P value 
CYP2C8*2 1.24 (0.62–2.47) .54 
2C8*3 0.49 (0.14–1.71) .27 
CYP2C9*2 0.48 (0.14–1.67) .25 
2C9*3 0.83 (0.19–3.63) .81 
2C9*4 n/a  
2C9*5 2.59 (0.25–27.35) .43 
2C9*8 1.32 (0.31–5.54) .71 
2C9*11 1.06 (0.19–5.98) .94 
CYP2J2*2-*6 n/a  
2J2 R49S n/a  
2J2 V113M n/a  
2J2 L50L 1.92 (0.46–8.07) .37 
CYP2J2*7 0.83 (0.36–1.92) .66 
2J2 N124S 0.50 (0.02–15.08) .69 
sEH R287Q 1.04 (0.42–2.56) .94 
R403 ins 0.60 (0.12–3.01) .54 
Epoxygenase polymorphism OR (95% CI) P value 
CYP2C8*2 1.24 (0.62–2.47) .54 
2C8*3 0.49 (0.14–1.71) .27 
CYP2C9*2 0.48 (0.14–1.67) .25 
2C9*3 0.83 (0.19–3.63) .81 
2C9*4 n/a  
2C9*5 2.59 (0.25–27.35) .43 
2C9*8 1.32 (0.31–5.54) .71 
2C9*11 1.06 (0.19–5.98) .94 
CYP2J2*2-*6 n/a  
2J2 R49S n/a  
2J2 V113M n/a  
2J2 L50L 1.92 (0.46–8.07) .37 
CYP2J2*7 0.83 (0.36–1.92) .66 
2J2 N124S 0.50 (0.02–15.08) .69 
sEH R287Q 1.04 (0.42–2.56) .94 
R403 ins 0.60 (0.12–3.01) .54 

CI = confidence interval; OR = odds ratio.

*Dominant models (homozygotes &plus; heterozygotes v wild type) adjusted for age and sex.

Discussion

The CYP arachidonate pathway has been proposed to play a mechanistic role in hypertension, based on accumulated biochemical data from human and animal studies.23–30 Several variant alleles of CYP2C8, 2C9, 2J2, and sEH, which have been shown to exhibit reduced functional activity in vitro and represent relatively common polymorphisms, provide the opportunity to test the significance of this pathway in patients with hypertension. This is the first report of the CYP alleles including newly described CYP2C9*8and *11 and CYP2J2 R49S, CYP2J2 V113M, and CYP2J2 N124S in African Americans with hypertension. Our results suggest that these variant alleles alone are not associated with increased risk for hypertension in the African Americans. The lack of association of CYP2C8*3 and CYP2J2*7 variant alleles with hypertension in African Americans has recently been reported by King et al.31

Possible confounding factors are the fact that our healthy subjects were younger and may not yet have developed hypertension, although this is addressed using age as a covariate in the logistic regression analysis. We have shown that only the CYP2C9*2 and CYP2C8*3 variant alleles are in linkage disequilibrium in the African Americans although the concurrence of these two alleles is not associated with hypertension. This is similar to the results previously reported in individuals of white ethnicity.32 Among the reported CYP2J2 alleles, only the CYP2J2*7 allele was detected with any degree of frequency. There did not appear to be any interaction between these variant alleles and hypertension, but these findings do not exclude the possibility that these variant alleles may interact with variant alleles of other major physiologic pathways such nitric oxide synthetase or the cyclooxygenase pathways.

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Author notes

*
This work was supported by the following: National Institutes of Health (NIH) Center of Biomedical Research Excellence (COBRE) grant National Center Research Resources (NCRR) 1P20RR17659-01 through the Tulane Hypertension and Renal Center of Excellence and the GCRC NIH/NCRR grant RR05096 through the Tulane–Louisiana State University Charity Hospital General Clinical Research Center; NIH GM068797 (to A.E.R.) and 5 P42 ES 04696-14 (to F.M.F.); and by the UW NIEHS–sponsored Center for Ecogenetics and Environmental Health grant NIEHS P30ES07033.