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Recently, it was suggested that arginase (ARG)1 plays an important role in atherogenesis. However, because of its complex functions depending on vascular cell type, its impact on atherogenesis remains unclear.
To evaluate the association between ARG1 polymorphisms and phenotypes related to atherosclerosis.
Among 10 ARG1 polymorphisms selected from databases, 4 single‐nucleotide polymorphisms (rs2781666; rs2781667; rs2781668; rs17599586) were tested for association with myocardial infarction (MI) in a case–control study (350 cases vs 581 controls), and with common carotid artery (CCA) intima–media thickness (CCA‐IMT) in an independent sample of 963 subjects (Etude du Vieillissement Artériel (EVA) study).
The genotype distribution of the rs2781666 G/T polymorphism differed significantly between MI cases and controls (p=0.005), and the risk of MI was consistently increased for both GT heterozygotes (OR (95% CI) 1.5 (1.1 to 2.0)) and TT homozygotes (OR (95% CI) 2.2 (1.1 to 4.4)). In the EVA study, the rs2781666 polymorphism was also associated with an increase in CCA‐IMT (p=0.010), a surrogate marker of MI.
The ARG1 rs2781666 polymorphism was consistently associated with MI and an increased CCA‐IMT. These findings reinforce the hypothesis of a significant role of ARG1 in vascular pathophysiology.
The aetiology of coronary artery disease (CAD) is complex, and results from interactions between environmental risk factors and individual genetic predispositions. As the overall genetic contribution to CAD has been estimated to range from 20% to 60%,1 it is essential to establish the genetic basis of CAD to understand the pathophysiology of this disease.
Some very recent studies support a role for arginase (ARG)1 in the initiation, development and complications of CAD.2,3,4,5,6 In hepatocytes, as a partner of the urea cycle, ARG1 catalyses the synthesis of l‐ornithine and urea from l‐arginine, but the ARG1 gene (ARG1) has also been shown to be expressed in various cell types. Teupser et al2 designated ARG1, located on 6q23, as a candidate gene that might modulate individual susceptibility to atherosclerosis. In that study, subtractive suppression hybridisation was used to screen for genes that were differentially expressed in macrophages obtained from two strains of rabbits with genetically determined high and low predisposition to atherosclerosis. ARG1 was shown to be expressed at higher levels in macrophages with low atherosclerotic response than in those with high atherosclerotic response, and the level of expression was correlated with increased enzymatic activity. These results suggested a protective role for ARG1 overexpression in the development of atherosclerosis. Consistent with these findings, Thomas et al7 showed evidence for a decreased ARG1 gene expression in foam cells compared with non‐foamy cells obtained from rabbits. Both studies were of particular interest because ARG1 was identified as a candidate gene following strategies without any preconceptions about the genes potentially involved in atherogenesis. Nevertheless, other studies suggested that ARG1 overexpression might be deleterious. Notably, it has been proposed that enhanced ARG expression and/or activity may contribute to endothelial dysfunction in various cardiovascular disorders including atherosclerosis.3,6,8 Finally, the role of ARG1 in atherogenesis may result from conflicting actions in the different vascular cell types.
In this context, we attempted to approach the putative role of ARG1 in humans by evaluating its potential implication in clinical manifestations of CAD. First, we searched for associations between ARG1 polymorphisms and myocardial infarction (MI) in a case–control study (350 cases and 581 controls).9 Second, in the longitudinal Etude du Vieillissement Artériel (EVA) study (n=963), we examined whether genetic variations in ARG1 were associated with common carotid artery (CCA) intima–media thickness (CCA‐IMT), considered as an indicator of generalised atherosclerosis.10,11,12,13
A sample of 350 cases of MI was drawn from the European Action on Secondary Prevention by Intervention to Reduce Events (EUROASPIRE) study.14 Patients were enrolled from hospitals of the Urban Community of Lille (Northern France) during the two EUROASPIRE surveys conducted in 1995–6 and in 1999–2000, respectively. Both surveys were conducted in two stages. In the first stage, consecutive patients with an established MI were retrospectively identified from hospital admission lists, diagnostic registers, hospital discharge lists or other sources. In the second stage, patients were contacted at least 6 months after their initial hospitalisation to participate in the EUROASPIRE study. About 30% of subjects selected in the first stage did not participate in the second stage, and the reasons for not participating were: refusal to participate or no response (43.5%), dead or not contacted (47.5%) and other reasons (9.0%). There was no significant difference by gender between participants and non‐participants (79.5% vs 75.7% males, respectively). The non‐participants were slightly older than the participants (mean (SD) 60.5 (9.5) vs 58.2 (9.7) years, respectively). Of the 350 selected patients with MI, 18.6% had had a coronary bypass graft and 36.3% had had a percutaneous transluminal coronary angioplasty. For all subjects, the major cardiovascular risk factors were collected.
The control group comprised subjects recruited within the framework of the World Health Organization MONICA (Multinational monitoring of trends and determinants of cardiovascular disease) project. Subjects were randomly sampled from the electoral rolls of the Urban Community of Lille between 1995 and 1997.9 The overall response rate was 73.4%. No significant difference by gender (50.3% vs 50.7% males, respectively) and age (mean (SD) 51.3 (8.4) vs 52.2 (8.7) years, respectively) could be detected between participants and non‐participants. Information about personal habits, medical history and drug intake was obtained using a standardised questionnaire. Subjects with a history or symptoms of CAD were excluded from this population‐based sample, which was representative of the general population, and 585 controls, matched by age and gender to the MI cases from the EUROASPIRE study, were selected.
For both cases and controls, hypertension was defined by a systolic blood pressure (SBP) 140 mm Hg and/or a diastolic blood pressure (DBP) 90 mm Hg and/or by use of antihypertensive drugs. SBP and DBP were measured twice, with an interval of at least 5 min, in a sitting position, after resting for at least 5–10 min. A mercury sphygmomanometer was used for controls, and digital electronic tensiometers were used for cases. About 40% of cases and 23% of controls were under antihypertensive treatment. Subjects were considered as diabetic or hypercholesterolaemic if they used antidiabetic or hypolipemiant drugs, respectively, and/or if the disease(s) was reported during the survey. Only subjects with fully available phenotypic and genetic data were considered for further analyses (350 cases and 581 controls).
The EVA study15 is a longitudinal study on vascular ageing and cognitive decline, composed of subjects aged from 59 to 71 years who were recruited from the city of Nantes (Western France), starting from the electoral rolls. Subjects were contacted both through the mail and, to a lesser extent, through information campaigns. When a subject was recruited, his or her spouse was systematically asked to participate in the study if he or she was in the required age range. The EVA cohort is composed of volunteers who differ slightly from the general population aged 60–70 years in several respects. In all, 14% of the EVA participants have had 12 years of schooling, as compared with 7% of the general population; they also have a higher socioeconomic status. Overall, the proportion of men (41.1%) is similar to that in the general population aged 60–70 years (39.9%). During the baseline visit (January 1992–July 1993), subjects had high‐resolution ultrasound examinations of the CCAs, including measurements of CCA‐IMT at sites free of plaques.15 The mean of four right and left CCA‐IMT measurements was used in the analysis. In the EVA study, hypertension was defined by an SBP140 mm Hg and/or a DBP90 mm Hg, and/or by antihypertensive treatment. SBP and DBP were measured twice, with an interval of at least 5 min, in a sitting position, after at least 5–10 min of rest, using a digital electronic tensiometer. In the EVA study, about 25% of subjects took antihypertensive drugs. Diabetes was defined by the use of antidiabetic drugs and/or a fasting plasma glucose level 7 mmol/l; hypercholesterolaemia was defined by the use of hypolipemiant drugs and/or a fasting plasma cholesterol level 6.2 mmol/l. Subjects with missing data were excluded from the statistical analyses. The population sample was composed of 963 subjects.
All study protocols were approved by the local ethics committees, and written informed consent was obtained from all subjects. Table 11 shows the main phenotypic characteristics of the participants of the MI case–control study and the EVA study.
By combining data from the National Center for Biotechnology Information/single‐nucleotide polymorphism (SNP; http://www.ncbi.nlm.nih.gov/SNP) and the HapMap project (http://www.hapmap.org) databases, a total of 10 SNPs spaced throughout the ARG1 gene were chosen on the basis of their location and/or putative functionality (fig 11).). Three SNPs, named rs2781659, rs2781665 and rs2781666, were located within the 5′ promoter sequence. Interestingly, rs2781665 and rs2781666 were putative binding sequences for transcription factors. A similar argument guided the selection of rs2781667 and rs2781668, located in intron 1. The SNPs rs115444111 and rs1063493 were selected because they encoded non‐synonymous substitutions in the peptide sequence (Gly→Glu and Gln→Glu, respectively). Finally, three polymorphisms, rs2297637, rs17599586 and rs1803151, permitted coverage of the 3′ region of the ARG1 gene. Moreover, in the HapMap database, rs2781668 and rs17599586 were defined as tag SNPs for other polymorphisms (rs2781668 for rs2246012; rs17599586 for rs3850245 and rs17657829).
The Hardy–Weinberg equilibrium was tested separately in controls from the MI core‐control study and in the EVA study. In the MI case–control study, genotype distributions between cases and controls were compared using Pearson's χ2 test. The associations of the different SNPs with the risk of MI were assessed by multiple logistic regression analyses. In the EVA study, CCA‐IMT means were compared between genotypes by an analysis of covariance that used a general linear model (General Linear Model procedure, type III test). The tests were performed assuming an allele–dose effect after the goodness of fit of the model had been evaluated by the likelihood ratio test. All the tests were adjusted for age, gender, body mass index, hypercholesterolaemia, hypertension, diabetes and smoking habits. For smoking habits, the subjects were classified as non‐smokers and ever smokers. These analyses were carried out with the SAS release V.8.2 software. The pairwise linkage disequilibrium (LD) was estimated using the standard definition of r2. The haplotype frequencies were estimated by using a stochastic‐EM algorithm implemented in the THESIAS software (freely available from http://www.genecanvas.org).16 The difference between estimated haplotype frequencies in MI cases and controls was evaluated by a likelihood ratio test. In the present work, four polymorphisms were selected for association studies. To take multiple testing into account, the Bonferroni correction was applied and a level of significance of p<0.013 was retained.
The 10 ARG1 SNPs were genotyped in a randomly selected subgroup of 186 subjects participating in the EVA study, allowing to determine allele frequencies (supplementary table 11,, available at http://jmg.bmj.com/supplemental) and pairwise LD (fig 11).). The data obtained enabled the selection of the most relevant ARG1 SNPs for association studies. As their minor allele frequencies were found to be <5%, rs11544411, rs1063493, rs2297637 and rs1803151 were excluded from the analyses. Among the remaining polymorphisms, rs2781659, rs2781665 and rs2781667, were in complete LD (r2=1), indicating that any one of these three SNPs could reflect the same haplotype block of ARG1. Among these three SNPs, we selected rs2781667, because it potentially introduced a binding site for nuclear factor κB, a feature that would be of importance in CAD. The remaining rs2781666, rs2781668 and rs17599586 polymorphisms were independant (0.03r20.56 for rs2781666, 0.02r20.56 for rs2781668 and 0.02r20.17 for rs17588586). Hence, the ARG1 SNPs selected were rs2781666, rs2781667, rs2781668 and rs17599586.
The four selected ARG1 SNPs were characterised in the 350 MI cases and in the 581 controls. Genotype distributions fulfilled the Hardy–Weinberg equilibrium. Associations between the ARG1 SNPs and MI were assessed by comparing the genotype distributions between MI cases and controls (table 22).
No significant difference in genotype distributions could be observed for rs2781667, rs2781668 and rs17599586. Conversely, genotypes carrying the minor rs2781666 T allele were statistically more common in MI cases than in controls (p=0.005). Assuming an allele–dose effect, the logistic regression analysis showed that the rs2781666 T allele was associated with a significantly increased risk of MI (OR (95% CI) 1.5 (1.2 to 1.9); p=0.001). The increase in the risk of MI could be observed both in rs2781666 GT heterozygotes (OR (95% CI) 1.5 (1.1 to 2.0)) and in rs2781666 TT homozygotes (OR (95% CI) 2.2 (1.1 to 4.4)). Our results suggested that significant associations of ARG1 polymorphisms with MI were restricted to rs2781666. However, taking LD into account, the impact of rs2781666 could be, at least partly, modulated by the three other SNPs. In order to define the independent effect of each polymorphism on MI, we performed a haplotype analysis (table 33).
As a consequence of LD, of the 16 theoretical haplotypes predicted by the 4 SNPs, only 4 could be observed with a frequency above 5%. The most common GCCC haplotype, which was composed of the common rs2781666 G, rs2781667 C, rs2781668 C and 17599586 C alleles, respectively, was considered as the reference haplotype. The haplotype distribution was statistically different between MI cases and controls (p=0.005). The difference could be mainly explained by the frequency of the TTCC haplotype (9.4% in MI vs 5.5% in controls, p=0.001). As a consequence, compared with subjects carrying the GCCC reference haplotype, the risk of MI in patients with the TTCC haplotype was estimated at 1.8 (95% CI 1.1 to 2.7; p=0.008) after adjustment for covariates. These results suggested that the effect of rs2781666 on the risk of MI was independent of rs2781668 and rs17599586. Unfortunately, because the TCCC haplotype was not represented in our samples, we were unable to estimate whether the impact of rs2781666 was independent or not of rs2781667.
In order to support the previous findings in an independent study, we tested the association of the four selected ARG1 SNPs with CCA‐IMT, a surrogate marker of MI.12 In the EVA study, the genotype distributions of the four SNPs fulfilled the Hardy–Weinberg distribution (table 44).
Regarding the rs2781666 polymorphism, the mean CCA‐IMT was significantly different between the three groups of genotypes after adjustment for covariates (p=0.010), and the difference was mainly due to the increased CCA‐IMT measured in the rs2781666 TT homozygotes (p=0.002). No significant association of ARG1 rs2781667 and rs17599586 with CCA‐IMT was detected. Moreover, the comparison of the mean CCA‐IMT between the rs2781668 genotypes did not reach statistical significance, and the trend could be attributable to the high degree of LD between rs2781666 and rs2781668.
Consistent with its association with the risk of MI, these data suggested that rs2781666 was associated with an increased CCA‐IMT. Haplotype analysis did not allow us to identify one or more specific ARG1 haplotypes associated with the phenotype (data not shown).
In this study, we present the first evidence that genetic variations in ARG1 may have an impact on atherosclerosis in humans. In the French population, of the 10 SNPs selected from databases, 4 were considered as relevant for association studies, and one of them, the rs2781666 polymorphism, was unambiguously associated with an allele–dose‐dependent increased risk of MI and a consistently increased CCA‐IMT. Interestingly, CCA‐IMT has been proposed as a reliable marker for both the presence and the degree of atherosclerosis,10,17 and prospective studies have shown a positive association between increased CCA‐IMT and the risk of MI.12,13 Results from two independent epidemiological studies consistently showed that an increase of 0.16 mm in CCA‐IMT was associated with a 43% increase in the risk of MI.12,18 Hence, results obtained in the EVA study were consistent with those obtained in the MI case–control study and reinforce the possible role for ARG1 in atherogenesis. As a limitation of the MI case–control study, when comparing genotype frequencies between cases and controls, we could not take into account the ancestry or ethnic origin of the subjects because we could not collect these data in France. However, to avoid a potential bias, MI cases and controls were recruited from the same geographical area—that is, the Urban Community of Lille (Northern France).
Pathophysiological hypotheses strongly argue for a significant role of ARG1 in atherogenesis. Both in animals and humans, the expression of ARG1 was detected in various cell types in the vascular wall, in addition to the liver, where ARG1 participates in the urea cycle. In animal models, constitutive ARG activity and immunoreactivity were observed in endothelial cells8,19 and vascular smooth muscle cells (VSMC).20,21 Mori et al22 showed that ARG1 expression was induced by lipopolysaccharide stimulation in rat macrophages. ARG1 is also expressed and is functionally active in human endothelial cells.23 However, alterations in the expression of ARG1 in the vascular wall cells may have complex effects on the atherogenesis according to cell types. It is generally admitted that ARG is a key regulator of nitric oxide (NO) signalling, counteracting NO synthase (NOS) activity by limiting their shared substrate. On the one hand, ARG1 overexpression may be deleterious in endothelial cells, in leading to decreased NO production by the endothelial NOS.19,24 Consistent with this, ARG1 knockdown was shown to enhance NOS activity and restore the endothelial NO signalling in ageing rat vessels.25 On the other hand, ARG1 overexpression might be atheroprotective in macrophages and VSMC, in causing decreased peroxynitrite production by the inducible NOS.26
Importantly, ornithine, the primary metabolite of the ARG pathway, may itself play an important part in atherogenesis. Ornithine feeds into the synthesis of L‐proline, and thus is a precursor of collagen biosynthesis.27 In addition, ornithine is involved in the formation of polyamines that play an important role in the mitogenic response of VSMC.4,28 Thus, various metabolites of ornithine play an important part in the matrix and cellular composition of the atherosclerotic plaque, a critical feature for plaque vulnerability.28,29 Therefore, although the contribution of ARG expression to atherosclerosis in each of the vascular cell types is still unknown, quantitative variations in ARG expression and/or activity seem to modulate the overall susceptibility to the disease.
Significant and consistent associations of ARG1 polymorphisms were restricted to the rs2781666 SNP, which was associated with an increased risk of MI and an enhanced CCA‐IMT. We propose that these results could be related to the previously described deleterious effect of ARG1 overexpression, at least in endothelial cells.19,24 As the rs2781666 polymorphism is located in the promoter region of the gene, it might modify ARG1 expression. In silico, an analysis of the putative functionality of this SNP using Genomatix/Matinspector30 suggested that the rs2781666 minor allele could generate a binding site for the X‐box binding protein 1, the aryl hydrocarbon receptor nuclear translocator and the tumour suppressor p53. Among these factors, p53 was of particular interest because it is activated in the atherosclerotic plaque. It regulates growth arrest, senescence and apoptosis of VSMC, and promotes apoptosis in macrophages.31,32,33 Thus, binding of p53 might lead to ARG1 overexpression, potentially promoting both MI and thickening of intima‐media. Nevertheless, functional experiments in various cell types will be needed to verify this hypothesis. Moreover, the possibility that the ARG1 rs2781666 polymorphism may be in LD with another functional polymorphism located in the ARG1 locus or in another gene nearby cannot be excluded.
In conclusion, our findings suggest that genetic variations in ARG1 may predispose to MI and intermediate phenotypes, and reinforce our interest in studies focusing on the role of ARG1 in vascular pathophysiology.
JD was supported by the Conseil Régional Nord–Pas‐de‐Calais and the Institut National de la Santé et de la Recherche Médicale (Inserm). We thank Dr RJ Pierce for his critical reading of the manuscript. The EUROASPIRE study was supported by an educational grant to the European Society of Cardiology by Merck, Sharp and Dohme‐Chibret Co. The WHO‐MONICA population study developed in Northern France was supported by grants from the Conseil Régional du Nord–Pas‐de‐Calais, the Fondation pour la Recherche Médicale, ONIVINS, the Parke‐Davis Laboratory, the Mutuelle Générale de l'Education Nationale, the Réseau National de Santé Publique, the Direction Générale de la Santé, Inserm, the Institut Pasteur de Lille, the Université de Lille 2, and the Unité d'Evaluation du Centre Hospitalier et Universitaire de Lille. The EVA study was organised with an agreement between Inserm and the Merck, Sharp and Dohme‐Chibret Co. It is also supported by EISAI Co (France).
ARG - arginase
CAD - coronary artery disease
CCA - common carotid artery
CCA‐IMT - CCA intima–media thickness
DBP - diastolic blood pressure
EUROASPIRE - European Action on Secondary Prevention by Intervention to Reduce Events
EVA - Etude du Vieillissement Artériel
LD - linkage disequilibrium
MI - myocardial infarction
NO - nitric oxide
NOS - NO synthase
SBP - systolic blood pressure
SNP - single‐nucleotide polymorphism
VSMC - vascular smooth muscle cells