Cytokine Polymorphisms Associated With Carotid Intima-Media Thickness in Stroke Patients
Background and Purpose— Carotid intima-media thickness (IMT) reflects generalized atherosclerosis and is predictive of future vascular events. Evidence exists that carotid IMT is heritable, and genetic studies can provide clues in the pathogenesis of atherosclerosis.
Methods— We recruited 470 white ischemic stroke patients, measured common carotid artery (CCA) IMT, and analyzed 54 polymorphisms with suspected roles in atherosclerosis.
Results— Among the polymorphisms tested, the angiotensin-converting enzyme insertion/deletion, osteopontin (OPN) T-443C, monocyte chemoattractant protein-1 (MCP-1) G-927C, and MCP-1 A-2578G polymorphisms were associated with CCA–IMT in age-gender–adjusted analysis. In multivariate analysis, the association between the OPN and MCP-1 polymorphisms remained significant. The OPN-443C allele was associated with increased IMT in the dominant model (0.053 mm for the TC and CC genotypes; P=0.001). The MCP-1-927C allele was associated with increased IMT in the additive model (0.040 mm for each C allele; P=0.001), and the MCP-1-2578 G allele was associated with decreased IMT in the recessive model (0.088 mm for the GG genotype; P=0.002).
Conclusions— The OPN and MCP-1 genes, coding for 2 cytokines with known roles in atherosclerosis, may contribute to increased carotid IMT and warrant further study.
Measuring carotid intima-media thickness (IMT) is a powerful technique for studying atherosclerosis. IMT is determined by visualizing the carotid arteries with high-resolution ultrasound, then analyzing the images by computer to accurately measure the thickness. Increased carotid IMT is a marker of generalized atherosclerosis and is associated with future myocardial infarction and stroke.1,2 Familial epidemiological studies suggest that increased IMT is under genetic influence with heritability estimates of 30% to 40%.3 There have been relatively few candidate gene studies, and further work is needed to identify genetic factors contributing to IMT.4 Studying the genetics of IMT can help better understand the pathophysiology of atherosclerosis in stroke patients.
We sought to explore the genetics of carotid IMT in brain infarction (BI) patients from the GENétique de l’Infarctus Cérébral (GENIC) study. This analysis included all polymorphisms tested in the GENIC study. The genes all had potential roles in vascular pathology, including inflammation, hypertension, coagulation, and lipid metabolism (Table 1⇓), many of which had not been analyzed previously with IMT.
Patients (n=510) were consecutively recruited from 12 different French neurological centers with the following criteria: (1) clinical symptoms of BI, (2) no hemorrhage on computed tomography, (3) BI proven by MRI, (4) 18 to 85 years of age, and (5) both parents of white origin. Patients were included within 1 week of the qualifying BI. All etiologic subtypes of BI were included for this analysis. Patients with a previous cardiovascular or cerebrovascular history were still eligible. There were 510 age-matched controls without BI, but they were not used for this analysis.
Data Collection and Risk Factor Definition
Demographic characteristics and risk factors were recorded with a questionnaire. Hypertension was defined as a previous history of hypertension treatment. Smoking was coded as never, previous, and current smoker. Subjects were classified as diabetic if treated previously for type 1 or type 2 diabetes mellitus. Use of lipid-lowering drugs was assessed. A positive cardiovascular history was defined as past myocardial infarction, angioplasty, coronary artery bypass surgery, or lower-limb arterial disease. History of previous stroke or transient ischemic attacks was recorded.
All subjects underwent carotid ultrasound to measure carotid IMT and for the presence of plaques. Operators (who were all certified before the study) visualized the common carotid arteries (CCAs), and IMT was electronically measured on a segment without plaques. We also recorded internal carotid artery and carotid bifurcation for the purpose of plaque detection, but by protocol, we used only CCA-IMT measurements for this analysis. There was a much higher incidence of plaques at the carotid bifurcation and internal carotid artery, which therefore precluded an accurate IMT measurement. Further details have been published previously.2
Data analyses were based on 470 BI cases for whom a good-quality CCA-IMT measurement was available. All analyses were adjusted for age and gender. We studied the association between CCA-IMT and several risk factors using the analysis of covariance (ANCOVA). The risk factors associated with CCA-IMT (P<0.05) were implemented in a stepwise multiple regression analysis with an entry and removal values set to 0.05. The risk factors that remained in the stepwise regression model were subsequently used to adjust the relationships between CCA-IMT and polymorphisms. We excluded the 29 polymorphisms with the less common allele frequency of <10% because there was very little power to detect significant associations (Table 1⇑). We compared the mean CCA-IMT between genotypes for the 54 remaining polymorphisms using ANCOVA adjusted for age and gender (ie, assuming no particular genetic model). The polymorphisms with a significant difference in mean CCA-IMT between genotypes were further explored in additive, dominant, and recessive genetic models using linear regression analysis. We used the Akaike Information Criterion (AIC) to select the best-fitting multivariate genetic model; the model with the lowest AIC score was the best fitting. Sensitivity analysis restricted to the 371 cases free of previous cardiovascular events was conducted using the best-fitting multivariate genetic model for the 3 identified polymorphisms. We performed haplotype analysis on the monocyte chemoattractant protein-1 (MCP-1) variants to better characterize their significant associations with CCA-IMT. These polymorphisms were in complete negative linkage disequilibrium (D′ value=−1) and generated 6 combined genotypes and 3 haplotypes (AG, AC, and GG). We analyzed the relationship between CCA-IMT and haplotypes in the same manner as for the individual polymorphisms. The AC and GG haplotypes were each studied as biallelic polymorphisms by reference to AG-AG carriers and were entered together in genetic models. AC and GG were coded in no particular genetic model as 2 unordered variables (2 df), in additive genetic model as 2 ordered variables (1 df), in dominant genetic model as 2 dummy variables (contrasting the effect of heterozygotes and homozygotes to noncarriers), and in recessive genetic model as 2 dummy variables (contrasting the effect of homozygotes to heterozygotes and noncarriers).
Because of the exploratory nature and the small sample size of this study, and because polymorphisms on the same gene were not independent, we did not adjust for multiple comparisons. However, acknowledging the contest of multiple testing, we used as statistical criteria value, a nominal P value cutoff of 0.01. Data were analyzed using the SAS package release 9.1 (SAS Institute).
Table 2 shows the relationships between CCA-IMT and several characteristics in age-gender–adjusted analysis. Increased age, male gender, hypertension, higher total and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher blood pressure values, and cardiovascular history were associated with increased CCA-IMT (P<0.05). In stepwise multiple regression analysis, CCA-IMT remained associated with age (P<0.0001), male gender (P<0.0001), systolic blood pressure (P=0.0005), low-density lipoprotein cholesterol (P=0.022), and cardiovascular history (P=0.013).
Of the 54 polymorphisms tested, there were significant differences in CCA-IMT between the genotypes of osteopontin (OPN) T-443C, MCP-1 G-927C and MCP-1 A-2578G (referred to as A-2518G in other reports; Figure). We also noted a small trend toward a higher mean CCA-IMT for homozygotes of angiotensin-converting enzyme deletion (ACE D; age-gender–adjusted mean±SE; 0.814±0.011) compared with carriers of ACE insertion (ACE I; age-gender–adjusted mean±SE; 0.787±0.008; P=0.044). In addition, there was no correlation between plasma ACE and CCA-IMT (Pearson coefficient correlation 0.06; P=0.17).
OPN T-443C Polymorphism
Patients with the TT genotype had lower mean CCA-IMT compared with C allele carriers (Figure). The –443C allele effect for increased IMT was significant in additive and dominant genetic models with a lowest AIC score for the dominant genetic model (Table 3). The adjusted mean±SE of CCA-IMT was 0.757±0.014 in carriers of TT genotype and 0.817±0.008 in carriers of TC or CC genotypes. The C allele dominant effect remained significant in sensitivity analysis restricted to incident cases without previous cardiovascular history (adjusted regression coefficient 0.048; P=0.004).
As shown in the Figure, homozygotes of -2578G had a lower mean CCA-IMT compared with -2578 A allele carriers. In multivariate analysis, the -2578G allele effect for reduced IMT was only significant in the recessive model. In addition, a G-927C variant in complete negative linkage disequilibrium with A-2578G was significantly associated with CCA-IMT in the recessive and additive genetic models (Figure; Table 3). The additive genetic model was the best-fitting multivariate genetic model. CCA-IMT increased by 0.036 mm for each C allele present. The recessive effect of -2578G and the additive effect of -927C were slightly attenuated after excluding cases with cardiovascular history (MCP-1 G-927C: adjusted regression coefficient −0.085; P=0.007; MCP-1 G-927C: adjusted regression coefficient 0.033; P=0.015).
The respective frequencies of the (-2578/-927) AG, AC, and GG haplotypes were 58.2%, 19.6%, and 22.1%; the GC haplotype was not observed. By reference to AG (the most frequent haplotype), AC was associated with the thickest CCA-IMT (age-gender–adjusted P=0.012), with adjusted mean values of 0.869 mm, 0.774 mm, and 0.760 mm in homozygotes, heterozygotes, and noncarriers, respectively. Conversely, GG was associated with the thinnest CCA-IMT (age-gender–adjusted P=0.038), with adjusted mean values of 0.750 mm, 0.824 mm, and 0.829 mm in homozygotes, heterozygotes, and noncarriers, respectively. The AC and GG haplotypes fit best in the recessive genetic model (P<0.009 computed in multivariate linear regression).
After adjusting for appropriate covariates, there were significant associations with CCA-IMT and 2 genes: OPN and MCP-1. Interestingly, these are both proinflammatory cytokines with important roles in atherosclerosis by directing leukocytes to vascular endothelium.5,6 There is little previous knowledge how these polymorphisms affect atherosclerotic phenotypes.
Monocyte Chemoattractant Protein-1
These results suggest associations of the MCP-1-927C and -2578A alleles with increased CCA-IMT. The alleles were significant in multivariate recessive genetic models (P<0.005). These variants reside in the promoter region of the MCP-1 gene and could potentially affect MCP-1 transcription and expression. The 2 polymorphisms were in complete linkage disequilibrium, so the actual disease-causing locus could reside nearby. In haplotype analysis, AC was associated with the thickest and CG with the thinnest IMT in recessive model (P<0.009). The haplotype analysis did not improve the strength of the association.
MCP-1 is a powerful attractant of monocytes and T cells with well-known roles in atherosclerosis. MCP-1 is synthesized by multiple cells involved in atherosclerosis, including endothelial cells, smooth muscle cells, fibroblasts, and macrophages.7 In the early stages of atherogenesis, MCP-1 is the primary chemokine recruiting monocytes into the arterial subendothelium.8 MCP-1 protein and mRNA are highly expressed in atherosclerotic vessels but not normal vessels.7,9–12 In addition, a study demonstrated that mice lacking MCP-1 have attenuated atherogenesis and arterial monocyte accumulation.13
There have been very few reports of MCP-1 A-2578G in atherosclerosis10,14–16 and none on G-927C. Tabara et al found no association of A-2578G with carotid IMT in a Japanese patients.15 Alonso-Villaverde reported that -2578G was associated with increased progression of carotid IMT in HIV-infected patients,10 and Szalai found that -2578G was associated with presence of severe coronary artery disease.14 Although we observed a protective effect of the G allele on IMT, this discrepancy could be explained by different patient populations, by chance, or inadequate sample sizes. In addition, A-2578G could be protective or harmful depending on the disease state.17
There was a strong association of the OPN-443C allele with increased IMT in dominant model remaining significant in multivariate analysis (P<0.001). The polymorphism resides in the promoter region of the OPN gene and is a common variant because allelic frequencies are roughly equal in the general population. The OPN T-443C polymorphism is in a binding site for the MYT1 zinc finger, but it is currently unknown how it affects OPN transcription or plasma levels.18 This polymorphism is relatively unstudied in atherosclerosis.
OPN is a multifunctional protein expressed by many cell types, with roles in atherosclerosis, cell-mediated immunity, and macrophage recruitment and activation.19 In early stages of atherosclerosis, OPN attracts inflammatory cells, promotes the release of proteinolytic enzymes, and stimulates smooth muscle cell proliferation.20–22 Plasma OPN is increased in severe coronary artery disease,23 and there are high concentrations of OPN in the intima from carotid endarterectomy specimens.24 In later stages of atherosclerosis, macrophages synthesize OPN at high levels, which may limit further calcification.25
The ACE D allele was not significantly associated with higher IMT after adjusting for age and sex. Although ACE D was strongly associated with elevated plasma ACE (P=0.001),26 there was no correlation between plasma ACE and IMT. Therefore, we cannot confirm a positive association between the ACE D allele and increased IMT, as described in some other reports.27 Future studies of ACE I/D should include plasma ACE measurements.
Although measuring IMT was part of the original design of the GENIC study and the genes were prespecified, there were several limitations to this analysis. This study included only white ischemic BI patients, and there could be different results in other populations. The GENIC controls were not included in the analysis or a replication study because they were age- and location-matched selected inpatients, and including them could risk selection bias. In addition, the GENIC controls were admitted with various non-neurological diseases and were therefore a heterogenous group with different vascular risk factors. The main limitation of the present study is the lack of adequate statistical power to detect associations, especially when testing 54 polymorphisms. Therefore, we could not consider gene–gene and gene–environment interactions. Because of the exploratory nature and the small sample size of the present study and because polymorphisms on the same gene are not independent, we did not adjust for multiple testing. Even if we used a more stringent criteria for declaring statistical significance, we caution that we could not exclude the possibility that the positive findings were attributable to chance. For these reasons, the present results should be considered hypothesis generating and be replicated in further larger studies, preferably from a community prospective population.
In this exploratory study, there were strong associations with the MCP-1 and OPN genes and CCA-IMT in these patients. These genes have important roles in atherosclerosis, and it has been suggested that blockade of both molecules could synergistically inhibit atherosclerosis.25 We did not measure transcriptional activity or protein concentrations, and these results should be replicated in further large population-based studies.
Assistance Publique Hôpitaux of Paris held legal responsibility for this study (P930902). The institutions and investigators in the GENIC (Étude du profil GENétique de l’Infarctus Cérébral) study are listed on our website: http://www.ccr.jussieu.fr/GENIC/Welcome. html.
Sources of Funding
This study was supported by grants-in-aid from the Fondation CNP pour la Santé, Caisse Nationale d’Assurance Maladie des Travailleurs Salariés (3AM001), Institut National de la Santé et de la Recherche Médicale (INSERM), Programme Hospitalier de Recherche Clinique of the French Ministry of Health (AOA9402), and Sanofi-Synthelabo and Bristol-Myers Squibb Laboratories. This study was supported by INSERM and Assistance Publique-Hôpitaux de Paris at the Clinical Investigation Centre of Saint-Antoine University Hospital. Dr Brenner is supported in part by the William M. Feinberg Memorial Fellowship through the Sarver Heart Center, University of Arizona. This study was also supported in part by a research grant from the Bundesministerium for Education, Science and Technology to Stefan-Martin Brand-Herrmann in the context of the BioProfile-Project “Innovations in treatment concepts for the metabolic syndrome” (BMBF 0313040C).
Stefan-Martin Brand-Herrmann, Klaus Schmidt-Petersen, and Jacqueline Schönfelder are participants in the grant of the Deutsche Forschungsgemeinschaft: “Graduierten-Kolleg 754, Myokardiale Genexpression und Funktion, Myokardhypertrophie.” SOS-ATTAQUE CEREBRALE Association supported the work on this article.
- Received November 10, 2005.
- Revision received March 1, 2006.
- Accepted March 15, 2006.
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