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From the Unitat d’Hemostàsia i Trombosi (J.M.S., J.C.S., A.B., J.F.), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Southwest Foundation for Biomedical Research (L.A., J.B.), San Antonio, Tex; and Centre National de Genotypage (M.L.), Evry, France.
Correspondence to Dr José Manuel Soria, Unitat d’Hemostàsia i Trombosi, Hospital de la Santa Creu i Sant Pau, C/Sant Antoni M Claret 167, 08025, Barcelona, Spain. E-mail jsoria@hsp.santpau.es
Abstract
Background— Fibrinogen levels are a widely accepted risk factor for cardiovascular disease, but the extent of the genetic component is unknown.
Materials and Results— To search for these genes, we conducted a genome-wide scan using 21 Spanish families from the Genetic Analysis of Idiopathic Thrombophila (GAIT) Project. Two loci were detected: 1 on chromosome 12 and another on chromosome 14. There are no cardiovascular-related candidate genes on chromosome 14, which implies that this locus represents a novel cardiovascular risk factor. Importantly, the locus on chromosome 12 contains the hepatocyte nuclear factors (TCF1), a candidate gene involved in the hepatocyte-specific transcription of the fibrinogen -chain and ?-chain genes. Three polymorphisms in TCF1 showed significant association with fibrinogen levels, supporting the implication of TCF1 in the determination of this phenotype.
Conclusions— Two loci, 1 on chromosome 12 (most likely the TCF1) and another on chromosome 14, are important determinants of fibrinogen levels in Spanish families. These data should help define the relationship between fibrinogen levels and the risk of cardiovascular disease.
Fibrinogen level is a risk factor for cardiovascular disease, but most of the genetic components are unknown. In a genome-wide linkage scan, 2 loci were detected: 1 on chromosome 12 (most likely the TCF1) and another on chromosome 14, which are important determinants of fibrinogen levels in Spanish families.
Key Words: thrombosis ? quantitative trait locus ? GAIT Project ? fibrinogen and TCF1 gene
Introduction
Fibrinogen is the precursor of fibrin. Its level influences platelet aggregation, blood viscosity, and endothelial cell injury, mechanisms that play a role in atherosclerosis and arterial and venous thrombosis.1,2 Among the components of the coagulation system, elevated fibrinogen has been associated most consistently with cardiovascular disorders such as myocardial infarction and stroke3–6 or venous thrombosis.7 In addition, fibrinogen levels are associated with unstable and stable coronary artery disease and coronary complications after interventions.8 Similar results have been obtained for progression of peripheral disease and for total mortality related to coronary disease.9 Moreover, there is strong evidence indicating that increased fibrinogen clusters with other cardiovascular risk factors, including hypertension, diabetes, and smoking.10 Thus, it is obvious that fibrinogen is an important factor in determining cardiovascular risk.
See page 1100
The fibrinogen molecule is a glycoprotein containing 2 copies of each of 3 polypeptide chains (, ?, and ) encoded by 3 distinct genes (FGA, FGB, and FGG) located on the long arm of chromosome 4 at position q23–32.11 Recently, as part of the Genetic Analysis of Idiopathic Thrombophila (GAIT) Project, we quantified the genetic contribution to susceptibility of thrombosis and related phenotypes in the Spanish population.12,13 Of the quantitative risk factors studied, fibrinogen levels had a heritability of 34%,12 indicating that genetic factors have an important effect on the quantitative variation in this phenotype. It has been reported that a proportion of this variation can be explained by polymorphisms in the fibrinogen genes,14,15 especially in the fibrinogen ?-chain gene, which regulates the limiting step in fibrinogen synthesis.16 In these studies, Humphries et al14,15 reported that between 5% and 9% of fibrinogen variability could be explained by the ?-chain polymorphisms, whereas 4.2% was determined by the fibrinogen -chain gene. Therefore, it appears that polymorphisms in the genes encoding fibrinogen chains do not explain the total variance of circulating levels of fibrinogen. Thus, other genetic factors are likely involved in the quantitative variation of this phenotype.
However, the relationship between fibrinogen gene polymorphisms and disease is not clear.17 Positive findings were reported between the G allele of the -455 G/A polymorphism in the fibrinogen ?-chain gene and coronary artery disease.18 Also, the -455 G/A polymorphism has been related to the progression of atheroma, but it was the A allele that was associated with deleterious effects.19 In contrast, 2 large studies failed to establish an association between fibrinogen genotypes and disease.20–22
Here we present the results of a comprehensive genome-wide scan designed to identify genes that influence variation in fibrinogen levels and susceptibility to thrombosis.
Materials and Methods
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
Enrollment of Family Members and Phenotyping
The recruitment, sampling, and phenotyping used in the GAIT Project have been extensively described in previous publications.12,23 Briefly, our sample included 398 individuals belonging to 3- to 5-generation extended pedigrees. The participants ranged in age from <1 year to 88 years and included approximately equal numbers of males and females. Twelve families were selected through a proband with idiopathic thrombophilia, and 9 families were randomly selected without regard to phenotype. Fibrinogen was measured by the von Clauss method,24 with thrombin from BioMerieux (Marcy-l’Etoile) in the STA automated coagulometer (Boehringer Mannheim). Information regarding fibrinogen levels by pedigree is shown in Table 1.
TABLE 1. Distribution of Examined Individuals by Pedigree With Fibrinogen Levels Information
All procedures were approved by the institutional review board of the Hospital de la Santa Creu i Sant Pau (Barcelona). Adults gave informed consent for themselves and for their minor children.
Genotypes
Genome Scan
DNA was extracted using a standard protocol.25 The genome scan used 363 highly informative microsatellite DNA markers, spaced at a density of 9.5 cM. The average heterozygosity of these DNA markers was 0.79. Microsatellites consisted primarily of the ABI-Prism genotyping set MD-10. In a few instances, nearby Genethon markers were substituted for LMS II markers to improve robustness of the scan. The polymerase chain reaction products were analyzed on the PE 310, PE 377, and PE 3700 automated sequencers, and they were genotyped using PE Genotyper software. Information on microsatellite markers can be found in the public-accessible genomic database (http://www.gdb.org).
The genotypic data were entered into a database and analyzed for discrepancies (ie, violations of Mendelian inheritance) using the program INFER (PEDSYS).26 Mistypings were either corrected or excluded from the analysis.
Single Nucleotide Polymorphisms
We genotyped 10 single nucleotide polymorphisms (SNPs): 6 located in introns and 4 in the coding regions (cSNPs) in the hepatocyte nuclear factor 1 (TCF1) gene using the SNP Genotyping Assys-on-Demand products from Applied Biosystems following the recommendations of the provider. Information on the intonic SNPs and the cSNPs can be found in the public-accessible Entrez Single Nucleotide Polymorphism SNP Database (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Snp). Table 2 contains information about these 10 SNPs. The haplotypes with the SNPs detected in TCF1 gene (Table 3) were generated with the MERLIN program.27
TABLE 2. SNP Information and Association (P value) With the Fibrinogen Levels
TABLE 3. Haplotype Information and Association (P value) With the Fibrinogen Levels
Linkage Analysis
Standard multipoint variance component linkage methods, as implemented in the computer program SOLAR, were used for the genome scan.28 Previous studies suggested that these methods may be vulnerable to deviations from multivariate normality, giving inflated logarithm of odds (LOD) scores if the distribution of the trait presents high levels of kurtosis.29 However, levels of fibrinogen in the GAIT individuals exhibited a kurtosis of 0.42, which does not affect the distribution of LOD scores. Thus, the standard nominal P values for LOD scores are appropriate for the fibrinogen linkage screen.30
Allelic frequencies were estimated from the GAIT sample, and marker maps for multipoint analyses were obtained from ABI-Prism and from the Marshfield Medical Research Organization. Because 12 of the families in the GAIT Project were ascertained through thrombophilic probands, all analyses included an ascertainment correction achieved by conditioning the likelihood of these pedigrees on the likelihoods of their respective probands.31 To control the multiple testing effect, genome-wide P values were calculated using the method of Feingold et al.32
Combined Linkage/Disequilibrium Analysis
Association of each SNP or haplotype in TCF1 gene with fibrinogen plasma levels was tested by means of a quantitative trait association. Analysis was performed using the measured genotype approach33 by testing for genotype-specific differences in the means of traits while allowing for the nonindependence among family members. These analyses were performed using SOLAR.28 To assess linkage and association simultaneously,34,35 an extension of the variance component-based linkage test was performed by simultaneously incorporating the genotype-specific means of the measured genotype test.
Exclusion Linkage Analysis
We performed an exclusion linkage analysis for the genomic area containing the structural fibrinogen genes. In a variance component framework, we can exclude linkage at a locus explaining a fixed amount of genetic variance. If comparing the model with a quantitative trait locus (QTL) explaining this fixed amount of variance with a null model without a QTL effect, we obtain a LOD score less than –2, and we can exclude linkage of that magnitude at that locus. We performed this strategy for different values of genetic variance explained for the fibrinogen locus, ranging from 0.05 to 0.5.
Genetic Nomenclature
We used gene symbols recommended by the Human Genome Organization gene nomenclature committee.36
Results
In the GAIT sample, the mean fibrinogen plasma level in males was 2.97 g/L, with an SD of 0.69. Females exhibited significantly higher plasma levels, averaging 0.29g/L more than males. Using appropriate age- and sex-specific fibrinogen thresholds, none of the GAIT participants had a fibrinogen deficiency. Levels of fibrinogen increased significantly with age in both sexes. Age and sex accounted for 7.03% of the variation in fibrinogen levels.
The heritability of fibrinogen levels was 0.34 (P=0.0017), demonstrating that genes play an important role in the determination of plasma levels (34% of phenotypic variability). Moreover, the proportion of the residual phenotypic variability accounted for by shared household effects was 0.16 (P=0.004) for fibrinogen levels. This suggests that environmental factors shared among members of a household, such as diet, also influence variation in fibrinogen levels. Smoking and oral contraceptive use, the most common environmental factors in our sample, were also investigated as potential covariates for fibrinogen but were not significant in these analyses.
Multipoint variance component methods were used to assess linkage between autosomal markers and quantitative values of fibrinogen. Age and sex were used as covariates in all of the analyses. Their effects were estimated simultaneously with the genetic effects.
The results of the genome scan for QTLs influencing fibrinogen levels are shown in Figure 1. The linkage analyses revealed strong evidence of QTLs influencing fibrinogen levels on chromosomes 14 (LOD 3.12; nominal P=7.5x10–5; genome-wide P=0.03) and suggestive evidence on chromosome 12 (LOD 2.1; nominal P=0.00094; genome-wide P=0.4). Additionally, another linkage signal (LOD 1.95; nominal P=0.0014) was observed on chromosome 1: an LOD of 1.5 (nominal P=0.0042) on chromosome 17, and an LOD of 0.7 (nominal P=0.034) on chromosome 4. The highest LOD scores observed in this genome scan (3.12 on chromosome 14q11) occurred in the interval flanked by markers D14S72-D14S50 (Figure 2). This linkage signal strongly suggests that a gene in this region influences plasma levels of fibrinogen.
Figure 1. Results from the autosomal multipoint genome scan. LOD scales are shown for all autosomes on which the maximum LOD score exceeds 1. Hatch marks along the length of the chromosome indicate the positions of genotyped DNA markers. Fib indicates fibrinogen.
Figure 2. Linkage results on chromosome 14.
In addition, on chromosome 12, the peak LOD score occurred between markers D12S79 and D12S1718 in the region that maps to 12q24 (Figure 3). Because in this region, the human TCF1 gene, a biologically plausible candidate gene, has been mapped,37 we genotyped 10 polymorphisms in the GAIT sample located across this gene (6 in noncoding regions and 4 in coding regions). The measured genotype association analysis revealed significant association with 3 of the SNPs and fibrinogen levels (Table 2), supporting the presence of a QTL in the region of TCF1 gene. Under the assumption that these 3 SNPs affect the fibrinogen levels, we calculated that these mutation accounts for 5% of the variance in fibrinogen levels in this population.
Figure 3. Linkage results on chromosome 12.
To determine whether the SNP4 marker, which showed the most significant association, could be the QTL underlying our linkage signal, we performed a conditional linkage analysis that simultaneously accounted for association with the SNP4 mutation. However, in linkage analyses conditional on this polymorphism, significant evidence of linkage remained (LOD 1.98), suggesting that this variant is either in disequilibrium with another functional site or is only 1 of a group of functional SNPs.
In addition, the 10 SNPs considered in TCF1 gene in the GAIT sample generated 18 haplotypes (Table 3). In the measured genotype association analysis, 2 of them (haplotypes 15 and 16) showed an association with fibrinogen levels (P=0.03 and P=0.03, respectively), but their statistical significance disappeared when corrected for multiple testing.
It is worth noting that the region on chromosome 4 that contains the fibrinogen chain structural genes showed weak evidence of linkage (LOD <1.0). In a subsequent exclusion linkage analysis at the fibrinogen locus, we can exclude a large effect for this locus (>0.49), but we cannot exclude an effect smaller than that. It seems safe to conclude that this analysis showed that the effect of the fibrinogen locus in determination of fibrinogen levels, if any, should be small in this population.
Discussion
A major challenge for biology in the genomic era is to find and map the QTLs for variation in medically important complex traits such as cardiovascular disease. Usually, it is extremely difficult to find these QTLs when the study focuses directly on the disease status (disease or no disease). Then, intermediate risk factors can be analyzed in the genetic search because they tend to be more proximal to gene action and thus provide less attenuated genetic signals than when a discrete clinical end point such as disease is analyzed. Also, risk or susceptibility to disease is primarily a quantitative process that reflects an unobservable continuous liability. Quantitative risk factors preserve the essential continuous nature of the liability relationship and thus contain additional genetic information that disease state by itself lacks.38
One of these intermediate risk factors is fibrinogen level, which is widely recognized as an independent risk factor for cardiovascular disease.39 The published data are remarkably strong and consistent, despite the diverse populations studied, the variable length of follow-up, different definitions of end points, and various analytical methods applied.39,40 Heritability estimates range from 28% in families41 to 44% in a twin study,42 which is similar to our estimate.12
In recent years, several polymorphisms have been identified in the fibrinogen chain genes that determine in part the levels of fibrinogen in the general population.15 However, the influence of these polymorphisms on plasma fibrinogen levels is relatively small in individuals of healthy families.14,15 So the need to localize new genes influencing fibrinogen levels is evident.
Our results represent a comprehensive genome-wide scan undertaken to identify chromosome regions containing genes that influence variation in susceptibility to thrombotic disease and its intermediate phenotypes, such as fibrinogen. It is worth noting that in the multipoint genetic analysis, the region on chromosome 4 that contains the fibrinogen chain structural genes (FGA, FGB, and FGG) showed little evidence of linkage to fibrinogen (LOD <1; Figure 1).
Failure to detect a significant QTL at the fibrinogen locus might be attributable to 2 possibilities. First, there is not a QTL in this region, and second, it has a small effect in the Spanish population, and our study does not have enough power to detect such small effects. The power to detect a single QTL that explains 5% of the variation of a phenotype in the GAIT sample is 10%. Because we cannot rule out a possible small effect of the fibrinogen structural genes on fibrinogen levels on the basis of our linkage exclusion analysis, we believe that the second option is the most likely.
In addition, this observation agrees with previous studies reporting that the influence of polymorphic variations in fibrinogen genes on fibrinogen levels is weak,43,44 and our results suggest that fibrinogen chain loci (and their polymorphisms) have a weak effect on fibrinogen levels.
Recently, no significant results were reported from a genome scan for fibrinogen in the Framingham Heart Study.44 However, our genome scan revealed 2 regions: 1 that showed strong evidence of linkage on chromosome 14 and another that showed suggestive evidence of linkage on chromosome 12, with variation of fibrinogen levels.
In our study, there are no hemostasis-related candidate genes in the region of the linkage signal on chromosome 14 that might influence fibrinogen levels. However, there may be many novel genes involved in other processes (ie, in blood vessel development or in blood cell function) that could play important roles in modifying the phenotypic variability of this trait.
It is important to note that in the region of chromosome 12, there is a biologically plausible candidate gene that might influence fibrinogen plasma levels. The peak LOD score occurred between markers D12S79 and D12S1718 in a region 12q24.21 (Figure 3), where the TCF1 gene that encodes the hepatocyte nuclear factor 1 (HNF1), is mapped.37 The HNF1 binds to a sequence required for hepatocyte-specific transcription of the gene for the ?-chain of fibrinogen and also interacts with homologous sequences required for optimal promoter function of the genes for the - and ?-chains of fibrinogen.45,46 Thus, TCF1 is an obvious candidate gene to explain the observed linkage to the fibrinogen plasma levels.
Among the 10 SNPs analyzed, 3 showed significant association with fibrinogen levels (Table 2), supporting the hypothesis that fibrinogen level is genetically influenced by the TCF1 locus. However, none of the haplotypes built with the 10 SNPs within this gene was associated with fibrinogen levels after adjustment for multiple testing. This might be because we have not yet identified the functional variants that are responsible for the observed effects. Thus, it is clear that these 3 polymorphisms cannot account for the observed linkage of variation in fibrinogen levels to the region of the TCF1 gene. In fact, they can only account for a small portion of the observed linkage signal. Moreover, the residual linkage signal (LOD 1.98) in the combined linkage/disequilibrium analysis,23 which simultaneously allowed for association between the SNP4 and fibrinogen levels, indicated that there must be 1 additional polymorphisms in the region influencing fibrinogen levels.
We are currently in the process of resequencing the TCF1 gene and surrounding regulatory and conserved regions to catalog the full extent of genetic variation present in this population and identify the functional polymorphisms responsible for the observed linkage signal.
There remains substantial residual genetic variation in fibrinogen levels even after taking into account the effects of these SNPs. This indicates that there are other QTLs that influence fibrinogen level, as suggested by the highly significant linkage signal on chromosome 14. This result supports our previous observation that multiple QTLs of varying effects will be involved in determining variation in hemostasis-related phenotypes.12,13
Although we do not have information about the functional role of these SNPs, on the basis of these results, the most likely possibility is that they are in linkage disequilibrium with another putative functional polymorphism of the TCF1 gene, which might affect transcription activity of the HNF1 -molecule or its expression. The next step will be to catalog the complete array of DNA sequence variation within the TCF1 gene through DNA resequencing. Because variation within noncoding regions may influence the regulation of transcription and other genetic functions, DNA resequencing should not be limited to the exons of the gene but should include 5' and 3' regulatory regions as well as introns.
In addition, further studies should also include fine mapping of the linkage region on chromosome 14. Also, any gene identified should be exhaustively dissected by resequencing strategies to identify its allelic architecture.
We believe that our approach should encourage future studies to use a whole genome scan, rather than the more limited approach on the basis of candidate genes. The genome scan with family studies is a powerful tool to identify (a priori) unexpected genes and maximizes the possibility to identify QTLs that influence complex important traits.
In conclusion, using a genome-wide scan, we identified an unsuspected gene (TCF-1) and another unknown QTL on chromosome 14 that influence interindividual variation in fibrinogen levels. Identification of genes that influence fibrinogen levels should lead to a better understanding of the etiology of cardiovascular disease. Ultimately, the results of these studies may provide clues for developing new diagnostic and treatment therapies for the prevention of disease.
Acknowledgments
This study was partially supported by grants HL70751 from the US National Institutes of Health, FIS 02/0375 from the Fondo Investigación Sanitaria SAF2002-03449, partially supported by FEDER funds (Spanish Ministry of Science and Technology), RED C03/01 from the Fondo Investigación Sanitaria, and from Fundació "La Caixa" and Fundació d’Investigació Sant Pau. J.M.S. was supported by FIS 99/3048 and A.B. by FIS 01/A046, both from the Fondo Investigación Sanitaria (Spanish Ministry of Health). This project was made possible in part by the genome scan performed by the Centre National de Génotypage (Evry, France).
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