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(Stroke. 2004;35:e65.)
© 2004 American Heart Association, Inc.
Research Reports |
From the National Heart, Lung and Blood Institutes Framingham Heart Study, Framingham, Mass (C.S.F., M.G.L., D.C., P.A.W., R.B.D., C.J.O.); National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Md (C.S.F., C.J.O.); Departments of Neurology and Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, Mass (M.G.L., P.A.W.); Department of Internal Medicine, Boston Medical Center, Boston, Mass (D.F.); Roche Genetics, Basel, Switzerland (K.L.); Department of Radiology, Brigham and Womens Hospital, Harvard Medical School, Boston, Mass (J.F.P.); Department of Mathematics, Boston University, Boston, Mass (R.B.D.); Royal North Shore Hospital, Sydney University, Australia (G.H.T.); and Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston, Mass (C.J.O.).
Correspondence to Christopher J. ODonnell, 73 Mt Wayte Ave, Suite 2, Framingham, MA 01702. E-mail chris{at}fram.nhlbi.nih.gov
| Abstract |
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Methods Here, 867 men and 911 women (mean age, 57 years) in the Framingham offspring cohort underwent B-mode carotid ultrasonography to determine the mean internal (ICA) and common carotid artery (CCA) IMT. Age-, sex-, and multivariable-adjusted linear regression was used to estimate the association of the following variants with log-transformed CCA and ICA IMT: factor V Leiden, factor VII Arg/Gln, fibrinogen HindIII ß-148, plasminogen activator inhibitor-1 4G/5G, and the glycoprotein IIIa PlA2 polymorphism.
Results Mean ICA IMT was 0.58 mm; mean CCA IMT was 0.60 mm. There were no differences in ICA or CCA IMT by genotype for any of the candidate genes in unadjusted, age- or sex-adjusted, and multivariable-adjusted models.
Conclusions There is no evidence for an association between well-studied polymorphisms in the hemostatic factor genes and carotid IMT. Whether other common genetic variants in hemostatic factor genes are associated with subclinical atherosclerosis remains to be determined.
Key Words: coagulation epidemiology genetics risk factors
| Introduction |
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| Methods |
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Each examination included an extensive cardiovascular disease assessment, 12-lead ECG, and blood testing. Measured covariates for the present study were assessed at the time of carotid ultrasonography.
Subjects underwent ultrasonography according to a standard protocol.1 Imaging was conducted by a single trained sonographer using a Toshiba SSH-140A imaging unit with a high-resolution 7.5-MHz transducer for the common carotid artery (CCA) and a 5.0-MHz transducer for the internal carotid artery (ICA).
Measurements were made by a single trained sonographer blinded to all clinical information and overread by 1 of the investigators (J.F.P.). Based on 25 replicate readings by 2 separate readers, correlation coefficients for the mean and maximum ICA were 0.83 and 0.84, respectively.
A number of previously described polymorphisms in several of the genes coding for hemostatic factors were characterized using previously published assay conditions. The factor V Leiden mutation (1691G
A) was genotyped according to standard protocol. Briefly, factor V Leiden results from a G-to-A substitution at nucleotide position 1691. A polymerase chain reaction (PCR)based restriction fragment length polymorphism analysis was used, and genomic DNA was isolated from whole blood. The sequences of sense and antisense primers were 5'tgcccagtgcttaaacaagacca3' and 5'tgttatcacactggtgctaa3', respectively. The 4G/5G polymorphism of PAI-1 (1-BP DEL/INS 4G/5G) arises from an insertion/deletion of a guanidine (4 or 5 repeats) at position 675 in the PAI-1 promoter. We used a PCR-based analysis to detect the polymorphism. We amplified the region around the 4G/5G polymorphism. The sequences of the sense primer and antisense primer were 5'ggggcacagagagagtctggacac3' and 5'cggccgcctccgatgatac3', respectively. DNA was amplified with PCR. Samples were size fractionated on a polyacrylamide sequencing gel, and the PCR results were scored in a blinded fashion. Genotyping methods have been described previously for the fibrinogen HindIII ß-148 polymorphism (-148C
T),9 glycoprotein IIIa PlA2 polymorphism (1565T
C),10 and factor VII (10828G
A) polymorphism.11 The frequency of genotyping failures ranged from 2.3% (glycoprotein IIIa PlA2 polymorphism) to 2.9% (plasminogen activator inhibitor-1 4G/5G).
Descriptive statistics using means, medians, and standard deviations were performed on all variables when appropriate. The
2 test was used to compare observed genotype frequencies with their estimates under Hardy-Weinberg equilibrium. To reduce nonnormality of distributions, CCA and ICA IMTs were log transformed. Multivariate linear regression, taking into account correlations among family members, was performed with SAS PROC MIXED.12 The general model was run first, and those with significant tests of trend were fit for additive, recessive, and dominant models. To accommodate multiple testing with 5 genes, we used a value of P<0.01 as a Bonferroni-adjusted test of significance. Multivariable analyses included adjustment for age, sex, systolic blood pressure, hypertension treatment, tobacco use (yes/no), total and high-density lipoprotein cholesterol, log triglycerides, diabetes, body mass index, and prevalent cardiovascular disease.
We calculated power to detect genetic effects in the context of a general model that uses 2 parameters to represent differences in genotype-specific means (ie, means µ1, µ2, and µ3). Assuming that measured covariates explain 20% of the overall variance (sex and age accounted for 17% of variance for ICA and 29% for CCA IMT), with a sample size of 1750 and 1% significance level, 80% power is attained for any genetic polymorphism that contributes at least 0.63% of the variance. For example, consider a diallelic gene with allele frequencies of 0.90 and 0.10 (genotype frequencies, 0.81, 0.18, 0.01); if genotype-specific means differed as 0.0, 0.19, and 0.38 SD units, the polymorphism would contribute 0.65% of total variance, and expected power would exceed 80%.
| Results |
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Using 1 randomly selected sibling per nuclear family, we estimated allele frequencies and tested Hardy-Weinberg equilibrium for each gene. Allele frequencies for factor V Leiden, factor VII Arg/Gln, fibrinogen HindIII ß-148, plasminogen activator inhibitor-1 4G/5G, and glycoprotein IIIa PlA2 polymorphisms were 0.02, 0.15, 0.19, 0.47, and 0.15, respectively, for the rarer allele. Each of the polymorphisms was in Hardy-Weinberg equilibrium (all P>0.15).
Baseline characteristics are presented in Table 1. Unadjusted CCA and ICA IMTs by genotype for the different polymorphisms are shown in Table 2.
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In unadjusted and age- plus sex-adjusted analyses, there were no differences in CCA IMT or ICA IMT across the 3 genotypes for any of the allelic variants of hemostatic factor pathway genes. In further age-, sex-, and multivariable-adjusted models, there continued to be no significant differences across genotypes.
| Discussion |
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Our results are consistent with those of several other studies. In studies that have examined the association between hemostatic factor genes and carotid IMT,1315 there was no association between carotid IMT and the platelet glycoprotein IIb/IIIa PlA2 polymorphism,13 factor VII Arg/Gln polymorphism,15 or Arg/Gln polymorphism of the factor V Leiden gene.14
Our study has advantages over prior studies. We had a large sample size and an unselected sample of subjects. Furthermore, our study does not exclude the possibility that other genetic variants in these genes or other genes coding for additional elements of the hemostatic cascade may be associated with carotid IMT.
Although the present investigation failed to show an association between the polymorphisms examined and carotid IMT, it may still be of interest to explore more fully the possible association of carotid IMT with genetic variance by studying additional genetic variants in genes coding for hemostatic factors. In addition, it may be of interest to use other modalities to assess subclinical atherosclerosis such as electron beam CT and cardiac MRI that may add complementary information on IMT phenotype assessment.
| Acknowledgments |
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Received October 23, 2003; accepted November 19, 2003.
| References |
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