Objective: Fibrinogen levels and fibrinogen clot structure have been implicated in the pathogenesis of vascular disease. We examined fibrinogen levels and variation in fibrinogen genes (fibrinogen γ (FGG), α (FGA) and β (FGB)), which have been associated with fibrin clot structure and fibrinogen levels, in relation to cerebral small vessel disease (SVD).
Methods and results: This study was performed as part of the Rotterdam Scan Study, a population based study in 1077 elderly patients undergoing cerebral MRI. Plasma fibrinogen levels and haplotypes were determined. We examined the association between fibrinogen levels and haplotype with silent brain infarcts and white matter lesions using logistic regression models. We constructed seven haplotypes (frequency >0.01) that describe the total common variation in the FGG and FGA genes. Haplotype 2 (GATAGTG) was associated with the presence of silent brain infarcts compared with the most frequent haplotype (GGTGGTA) (OR 1.41, 95% CI 1.03 to 1.94). Haplotype 3 (GGCGATA) was associated with periventricular white matter lesions in the highest tertile of the distribution (OR 1.40, 95% CI 1.01 to 1.92). No association was found between plasma fibrinogen levels and SVD.
Conclusions: Our study provides evidence for an association of common variation in the FGG and FGA genes with cerebral SVD. It is possible that the structure of the fibrin clot rather than plasma fibrinogen levels plays a role in the pathogenesis of cerebral SVD.
Statistics from Altmetric.com
Silent brain infarcts and cerebral white matter lesions are commonly detected on brain imaging in the elderly. Both result from small vessel disease (SVD) and have been associated with an increased risk of stroke and dementia.1 The pathogenesis of SVD is incompletely understood. Established risk factors are age and hypertension, although inflammatory, haemostatic and endothelial factors have also been implicated in the development of SVD.2 3
Fibrinogen has both inflammatory and haemostatic properties, and higher plasma levels have been associated with an increased risk of coronary artery disease, ischaemic stroke and dementia.4 5 Also, there is increasing evidence that altered structure of the fibrin clot may be involved in the pathogenesis of atherosclerosis and thrombotic disease.6 Genetic and environmental influences contribute to the variation in plasma fibrinogen concentration and fibrin clot structure. Fibrinogen is primarily synthesised by hepatocytes and consists of two symmetric sets of three chains (Aα, Bβ and γ), encoded by three separate genes, fibrinogen α (FGA), fibrinogen β (FGB) and fibrinogen γ (FGG), clustered on chromosome 4. The FGB gene is thought to be involved in determining fibrinogen plasma levels while the FGA and FGG genes are believed to play a role in regulating fibrin clot structure.7
We hypothesised a role for both fibrinogen plasma levels and clot structure in the pathogenesis of SVD. Therefore, we investigated the association between levels of fibrinogen in plasma and the presence of SVD, including silent brain infarcts and periventricular and subcortical white matter lesions, on MRI of the brain. In addition, we investigated the association between common variations in FGG, FGA and FGB genes, which are associated with fibrin clot structure and fibrinogen levels, and SVD. We performed the study as part of the Rotterdam Scan Study, a population based imaging study among those aged between 60 and 90 years.
The Rotterdam Scan Study was designed to study causes and consequences of brain changes in the elderly.8 In 1995–1996, participants aged 60–90 years were randomly selected in strata of age (5 years) and sex from two large ongoing population based studies, the Zoetermeer Study and the Rotterdam Study.9 A total of 1077 non-demented elderly subjects participated in the study (overall response 63%). The medical ethics committee of Erasmus Medical Centre approved the study and all participants gave informed consent.
Measurement of fibrinogen levels
Plasma concentrations of fibrinogen were determined in citrated plasma that was stored at –80°C. Prior to measurement, plasma samples were thawed at 37°C for 10 min. The method used was based on the Von Clauss10 clotting rate assay (Fibrinogen-C kit; Instrumentation Laboratory, Breda, The Netherlands) and performed on an Automated Coagulation Laboratory (ACL 300; Instrumentation Laboratory).
We obtained information on the following variables by interview and physical examination in 1995–1996: systolic blood pressure, diastolic blood pressure, body mass index, smoking and carotid intima thickness as a measure of carotid atherosclerosis.11 12
Single nucleotide polymorphisms selection and genotyping
The Seattle Single Nucleotide Polymorphisms (SNPs) programme for Genomic Applications has identified various SNPs in the FGG and FGA genes and the common haplotypes can be identified by haplotype tagging SNPs. By genotyping seven haplotype tagging SNPs, we were able to infer haplotypes and describe the common variation across the FGG and FGA genes. The length (total number of SNPs known to date) of the FGG and FGA genes are 8.6 kb (64 SNPs) and 7.6 kb (44 SNPs), respectively. We genotyped in the FGG and FGA genes the FGG 5836 G>A (rs2066860, intron 7), FGG 7874 G>A (rs2066861, intron 8), FGG 9340 T>C (rs1049636, intron 9), FGA 2224 G>A (rs2070011, exon 1), FGA 3655 G>A (rs2070014, intron 2), FGA 3807 T>C (rs2070016, intron 2) and the FGA 6534 A>G (rs6050, exon 5) polymorphisms that tag haplotypes covering the total common variation in the FGG and FGA genes. In addition, we genotyped the functional −148 C>T polymorphism (rs1800787) in the FGB gene that has been shown to directly affect FGB promoter activity.13 The FGB gene has a length of 8.1 kb and to date 75 SNPs have been identified. All polymorphisms have been described at http://www.ncbi.nlm.nih.gov/SNP.
DNA was isolated using standard procedures and genotyping was performed using baseline samples stored at −80°C. Genotypes were determined in 2 ng genomic DNA with the Taqman allelic discrimination assay (Applied Biosystems, Foster City, California, USA). Primer and probe sequences were designed using the SNP assay by design service of Applied Biosystems. Reactions were performed with the Taqman Prism 7900HT 384 wells format in 2 μl of reaction volume.
Haplotype alleles present in the population were inferred by means of the haplo.em function of the program Haplo Stats (http://cran.r-project.org/web/packages/haplo.stats/index.html), which computes maximum likelihood estimates of haplotype probabilities.14 15 Information on all SNPs was available for 899 persons.
Outcome measures on MRI
All participants underwent MRI of the brain in 1995–1996. Axial T1 weighted, T2 weighted and proton density scans on 1.5 T MRI scanners (for participants from Zoetermeer: MR Gyroscan, Philips, Best, the Netherlands and for participants from Rotterdam: MR VISION, Siemens, Erlangen, Germany) were made. Slice thickness was 5 or 6 mm, with an interslice gap of 20%.
Infarcts were defined as focal hyperintensities on T2 weighted images, 3 mm in size or larger. Proton density scans were used to distinguish infarcts from dilated perivascular spaces. Lesions in the white matter also had to have corresponding prominent hypointensities on T1 weighted images in order to distinguish them from cerebral white matter lesions. A history of stroke and transient ischaemic attack was obtained by self-report, and by checking medical records in all 1077 participants. An experienced neurologist (PJK) subsequently reviewed the medical history and scans and categorised the infarcts as silent or symptomatic. Silent brain infarcts were defined as evidence of one or more infarcts on MRI, without a history of a (corresponding) stroke or transient ischaemic attack. Participants with both symptomatic and silent infarcts were categorised in the symptomatic infarct group.
White matter lesions were considered present if visible as hyperintense on proton density and T2 weighted images, without prominent hypointensity on T1 weighted scans. Two raters independently scored periventricular and subcortical located white matter lesions. Both intra-reader and inter-reader studies (n = 100) showed good to excellent agreement (κ = 0.79–0.90, r = 0.88–0.95). A detailed description of the scoring method has been reported previously.16 Briefly, severity of periventricular white matter lesions was rated semiquantitatively at three regions (grade 0–9). A total volume of subcortical white matter lesions was based on the approximate number and size of the lesions in the frontal, parietal, occipital and temporal lobes (volume range 0–29.5 ml).
Because of the skewed distribution of fibrinogen levels, we used log transformed fibrinogen in the analyses. We examined the association of levels of fibrinogen with the presence of silent brain infarcts and periventricular and subcortical white matter lesions (third tertile versus the lower tertile of the distribution) by means of logistic regression models, adjusted for age and sex. Only for the analyses on silent brain infarcts did we exclude persons with symptomatic brain infarcts. We examined the associations per standard deviation (SD) increase in log transformed fibrinogen and in quartiles using the lowest quartile as the reference category. In addition, we adjusted for cardiovascular factors, including systolic and diastolic blood pressure, body mass index, current smoking and carotid intima thickness.
Hardy–Weinberg equilibrium of fibrinogen polymorphisms was tested using χ2 tests. We examined the association of the −148 C>T FGB promoter polymorphism with the presence of silent brain infarcts and periventricular and subcortical white matter lesions (third tertile versus the lower tertile of the distribution) by means of logistic regression models, using the CC genotype as the reference category. To test the associations of haplotypes of the FGG and FGA genes with levels of fibrinogen, silent brain infarcts and white matter lesions, we used the program Haplo Stats (http://cran.r-project.org/web/packages/haplo.stats/index.html).14 15 17 The probability for each haplotype pair in each individual was assigned and then an individual’s phenotype was directly modelled as a function of each inferred haplotype pair, weighed by their estimated probability, to account for haplotype ambiguity. The association between fibrinogen haplotypes and fibrinogen levels, silent brain infarction and white matter lesions was examined by means of the haplo.glm function of Haplo Stats.14 This approach is based on generalised linear model, and computes the regression of a trait on haplotypes and other covariates. In these analyses the most frequent haplotype was used as the reference category. It is important to note that in this type of analysis, haplotypes rather than subjects are used as the exposure. We adjusted for age and sex, and additionally for cardiovascular factors. As plasma fibrinogen levels are an important determinant of clot structure we repeated the analyses adjusting for plasma fibrinogen. An interaction between fibrinogen levels and clot structure on disease risk has been suggested. Therefore, we repeated the analyses stratifying on high levels (above the median) and low levels (below the median) of fibrinogen.
We identified 213 persons (mean age 75.5 (SD 7.0) years, 58.0% female) with silent brain infarcts on brain MRI, most of which had lacunar infarcts (n = 198), 358 persons (mean age 76.2 (SD 7.3) , 54.0% female) with subcortical white matter lesions and 327 (mean age 76.7 (SD 7.1) years, 56.0% female) with periventricular white matter lesions. The baseline characteristics of the total study population are shown in table 1.
Table 2 shows the constructed haplotypes and their frequencies in our population
Levels of log transformed fibrinogen were not associated with silent brain infarcts or white matter lesions on MRI (table 3).
This did not change after additional adjustment for cardiovascular factors or when only lacunar infarcts (n = 198) were analysed. All individual polymorphisms were in Hardy–Weinberg equilibrium.
No significant association was found between the −148 C>T FGB polymorphism and SVD. Compared with the CC genotype (reference), the age and sex adjusted odds ratio (OR) (95% confidence (CI)) for the presence of silent brain infarcts for the CT genotype was 1.36 (0.96 to 1.92) and 1.30 (0.61 to 2.78) for the TT genotype (p for trend 0.10). The age and sex adjusted OR (95% CI) for periventricular white matter lesions was 1.03 (0.75 to 1.42) for the CT genotype and 1.26 (0.64 to 2.48) for the TT genotype (p for trend 0.60). The age and sex adjusted OR (95% CI) for subcortical white matter lesions was 1.12 (0.82 to 1.53) for the CT genotype and 0.74 (0.36 to 1.50) for the TT genotype (p for trend 0.99). These estimates did not change after additional adjustments for cardiovascular factors. The −148 C>T FGB polymorphism was not associated with fibrinogen levels in our population. The age and sex adjusted mean of log transformed fibrinogen (95% CI) was 1.33 (1.31 to 1.35) for the CC genotype, 1.34 (1.31 to 1.37) for the CT genotype and 1.37 (1.30 to 1.44) for the TT genotype.
Haplotype reconstruction of the FGG and FGA genes resulted in 26 haplotypes, but only seven haplotypes had a frequency of >0.01 in our population. We disregarded 19 rare haplotypes with a frequency <1%, adding up to a total frequency of 3.8%. Haplotype alleles were coded as haplotype numbers 1 to 7 in order of decreasing frequency in the population (coding from 5836 G>A, 7874 G>A, 9340 T>C, 2224 G>A, 3655 G>A, 3807 T>C, 6534 A>G, haplotype 1 = G-G-T-G-G-T-A, haplotype 2 = G-A-T-A-G-T-G, haplotype 3 = G-G-C-G-A-T-A, haplotype 4 = G-G-T-G-G-C-A, haplotype 5 = G-G-C-A-G-T-A, haplotype 6 = A-G-T-G-G-T-A and haplotype 7 = G-G-T-A-G-T-G). Haplotype analyses were based on 899 participants for whom information on all SNPs was available.
Compared with haplotype 1, haplotype 2 was associated with a higher prevalence of silent brain infarcts and haplotype 3 was associated with more periventricular white matter lesions in the highest tertile of the distribution (table 4).
Additional adjustment for cardiovascular factors did not markedly change the associations. If anything, they got stronger (OR (95% CI) for silent brain infarcts (haplotype 2) 1.48 (1.08 to 2.03) and for periventricular white matter lesions (haplotype 3) 1.42 (1.02 to 1.96)). Analysing lacunar infarcts only (n = 198) gave similar results.
No association was found between haplotypes and plasma levels of fibrinogen, and adjustment for plasma fibrinogen did not change the estimates. Stratifying on high and low plasma fibrinogen also did not change the associations.
In this study, common variation in the FGG and FGA genes was associated with the presence of silent brain infarcts and periventricular white matter lesions on brain MRI. No associations were found between levels of fibrinogen or the −148 C>T FGB promoter polymorphism and silent brain infarcts or white matter lesions. Haplotypes of the FGG, FGA and FGB genes were not associated with fibrinogen levels.
Although an association between plasma fibrinogen levels and SVD has been suggested,18 we were not able to confirm this finding. In addition, no association was found between the −148 C>T FGB promoter polymorphism and SVD. This is in contrast with a previous study by Martiskainen et al that reported an association between the −455 G>A FGB promoter polymorphism, which is in perfect linkage disequilibrium (r2 = 1) with the −148 C>T polymorphism, and lacunar infarction.19 However, no fibrinogen levels were available in this study. Also, the study by Martiskainen et al included only stroke patients while the Rotterdam Scan Study is population based, which may account for differences in results. Several other studies focused on the possible association between the −148 C>T polymorphism and ischaemic stroke, and their results were inconclusive.20–22 It should be noted that in our population the −148 C>T FGB polymorphism was not significantly associated with fibrinogen levels. In an elderly population such as ours, the effects of the −148 C>T polymorphism on fibrinogen levels may be attenuated. Recently, such a decrease in raising effect on fibrinogen levels was shown for the −455 G>A polymorphism.23
To date, no study has examined common genetic variation in FGG and FGA in relation to cerebrovascular disease. However, common variation in these genes has been associated with other manifestations of vascular disease, independent of fibrinogen levels. Recently, Uitte de Willige et al studied haplotypes that describe the common variation in the FGG, FGA and FGB genes in relation to the risk of deep venous thrombosis.25 The haplotype of FGG (FGG-H2), tagged by 7874 G>A (rs2066861) and comparable with haplotype 2 in our study, was associated with an increased risk of deep venous thrombosis. A study by Mannila et al reported an association between haplotypes containing FGG SNP 9340 T>C (rs1049636; in their study named 1299+79 T>C), that tags haplotype 3 in our study, and FGA SNP 2224 (rs2070011; in their study named −58 G>A), that tags haplotype 2 in our study, and the risk of myocardial infarction.24 Several studies have examined individual polymorphisms in the FGG and FGA genes and vascular disease risk. The 6534 A>G (rs6050; also referred to as Thr312Ala) polymorphism in the FGA gene has been associated with venous thromboembolism, pulmonary embolism and post-stroke mortality among patients with atrial fibrillation.26 27
Although not associated with fibrinogen levels, there is evidence that variation in the FGA and FGG genes has functional implications. Uitte de Willige et al reported that the FGG-H2 was associated with reduced levels of fibrinogen γ′ (and a reduced γ′/γ ratio), a product of alternative splicing of the FGG gene. It is not clear how this reduced ratio influences fibrin formation and degradation. Several studies have provided evidence for a role of plasma fibrinogen γ′ in disease risk.28 29 Recently, Mannila et al showed that the FGA 2224G>A SNP constitutes an independent determinant of fibrin clot porosity and is involved in epistatic interactions on plasma fibrinogen concentration.30
Also, evidence for a functional role of the FGA 6534 A>G SNP exists. This SNP occurs in a region important for FXIII dependent cross linking processes and may affect fibrin clot structure or stiffness. It is not clear how this increase in clot stiffness leads to a tendency to embolise. Perhaps stiffer clots are more brittle, leading to an increased tendency to fragmentise under conditions of blood flow.7 31 Interestingly, the FGA SNP 2224 G>A in the study by Mannila et al and the FGG-H2 haplotype in the study by Uitte de Willige et al are in strong linkage disequilibrium with the 6534 A>G polymorphism.
In our study, common variation in the FGG and FGA genes was associated with silent brain infarcts and periventricular white matter lesions, but not with subcortical white matter lesions. It has previously been suggested that different pathophysiological mechanisms may underlie periventricular and subcortical white matter lesions.32 33 For example, atrial fibrillation has been found to be predominantly related to periventricular white matter lesions.34 A possible explanation for this may be that periventricular white matter is an arterial border zone and therefore more vulnerable while the subcortical white matter is better vascularised.35
In conclusion, in this population based imaging study, we found that common variation in the FGG and FGA genes of fibrinogen was associated with SVD on brain MRI. As this is the first report, our study needs to be replicated. Also, more functional studies need to be performed to elucidate the mechanism through which these genes influence the risk of vascular disease. Our findings suggest that mechanisms related to fibrin clot structure are involved in the pathogenesis of SVD rather than plasma concentration of fibrinogen.
Funding: This study was supported by the Netherlands Organisation for Scientific Research (NWO grant 904-61093). The Rotterdam Study is supported by the Erasmus Medical Centre and Erasmus University Rotterdam, The Netherlands Organisation for Scientific Research (NWO), the Netherlands Organisation for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry of Health, Welfare and Sports, The European Commission (DG XII), and the Municipality of Rotterdam.
Competing interests: None.
Ethics approval: The medical ethics committee of Erasmus Medical Centre approved the study.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.