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. Author manuscript; available in PMC: 2015 May 1.
Published in final edited form as: Arterioscler Thromb Vasc Biol. 2014 Feb 27;34(5):1093–1101. doi: 10.1161/ATVBAHA.113.302088

Genome-Wide Association Study for Circulating Tissue Plasminogen Activator (tPA) Levels and Functional Follow-up Implicates Endothelial STXBP5 and STX2

Jie Huang 1,2,*, Jennifer E Huffman 3,*, Munekazu Yamkauchi 4, Stella Trompet 5,6, Folkert W Asselbergs 7,8,9, Maria Sabater-Lleal 10, David-Alexandre Trégouët 11,12, Wei-Min Chen 13, Nicholas L Smith 14,15,16, Marcus E Kleber 17,18, So-Youn Shin 19,20, Diane M Becker 21, Weihong Tang 22, Abbas Dehghan 23,24, Andrew D Johnson 1,2, Vinh Truong 11,12, Lasse Folkersen 10, Qiong Yang 25, Tiphaine Oudot-Mellakh 11, Brendan M Buckley 26, Jason H Moore 27,28, Frances MK Williams 29, Harry Campbell 30, Günther Silbernagel 31, Veronique Vitart 3, Igor Rudan 30, Geoffrey H Tofler 32, Gerjan J Navis 33, Anita DeStefano 25, Alan F Wright 3, Ming-Huei Chen 25, Anton JM de Craen 6, Bradford B Worrall 13, Alicja R Rudnicka 34, Ann Rumley 35, Ebony B Bookman 36, Bruce M Psaty 14,15,37,38, Fang Chen 13, Keith L Keene 39, Oscar H Franco 23,24, Bernhard O Böhm 40,41, Andre G Uitterlinden 24,42, Angela M Carter 43, J Wouter Jukema 5,44,45, Naveed Sattar 46, Joshua C Bis 37, Mohammad A Ikram 23,47,48; the CHARGE consortium Neurology Working Group, Michèle M Sale 49, Barbara McKnight 14, Myriam Fornage 50, Ian Ford 51, Kent Taylor 52, P Eline Slagboom 24,53, Wendy L McArdle 54, Fang-Chi Hsu 55, Anders Franco-Cereceda 56, Alison H Goodall 57, Lisa R Yanek 21, Karen L Furie 58, Mary Cushman 59,60, Albert Hofman 23,24, Jacqueline CM Witteman 23,24, Aaron R Folsom 22, Saonli Basu 61, Nena Matijevic 62, Wiek H van Gilst 63, James F Wilson 30, Rudi GJ Westendorp 6,24, Sekar Kathiresan 64,65,66,67, Muredach P Reilly 68; the CARDIoGRAM Consortium, Russell P Tracy 60, Ozren Polasek 69, Bernhard R Winkelmann 70, Peter J Grant 42, Hans L Hillege 63, Francois Cambien 11,12, David J Stott 35, Gordon D Lowe 35, Timothy D Spector 29, James B Meigs 71,72, Winfried Marz 18,73,74, Per Eriksson 10, Lewis C Becker 21, Pierre-Emmanuel Morange 75, Nicole Soranzo 19,29, Scott M Williams 27, Caroline Hayward 3, Pim van der Harst 63, Anders Hamsten 10, Charles J Lowenstein 4, David P Strachan 34,**, Christopher J O'Donnell 1,2,64,**; the CHARGE Consortium Hemostatic Factor Working Group
PMCID: PMC4009733  NIHMSID: NIHMS567609  PMID: 24578379

Abstract

Objective

Tissue plasminogen activator (tPA), a serine protease, catalyzes the conversion of plasminogen to plasmin, the major enzyme responsible for endogenous fibrinolysis. In some populations, elevated plasma levels of tPA have been associated with myocardial infarction and other cardiovascular diseases (CVD). We conducted a meta-analysis of genome-wide association studies (GWAS) to identify novel correlates of circulating levels of tPA.

Approach and Results

Fourteen cohort studies with tPA measures (N=26,929) contributed to the meta-analysis. Three loci were significantly associated with circulating tPA levels (P <5.0×10−8). The first locus is on 6q24.3, with the lead SNP (rs9399599, P=2.9×10−14) within STXBP5. The second locus is on 8p11.21. The lead SNP (rs3136739, P=1.3×10−9) is intronic to POLB and less than 200kb away from the tPA encoding gene PLAT. We identified a non-synonymous SNP (rs2020921) in modest LD with rs3136739 (r2 = 0.50) within exon 5 of PLAT (P=2.0×10−8). The third locus is on 12q24.33, with the lead SNP (rs7301826, P=1.0×10−9) within intron 7 of STX2. We further found evidence for association of lead SNPs in STXBP5 and STX2 with expression levels of the respective transcripts. In in vitro cell studies, silencing STXBP5 decreased release of tPA from vascular endothelial cells, while silencing of STX2 increased tPA release. Through an in-silico lookup, we found no associations of the three lead SNPs with coronary artery disease or stroke.

Conclusions

We identified three loci associated with circulating tPA levels, the PLAT region, STXBP5 and STX2. Our functional studies implicate a novel role for STXBP5 and STX2 in regulating tPA release.

Keywords: tissue plasminogen activator, genome-wide association study, meta-analysis, cardiovascular disease risk, fibrinolysis, hemostasis

INTRODUCTION

Tissue plasminogen activator (tPA) is a glycoprotein produced mainly by vascular endothelial cells that catalyzes the conversion of plasminogen to plasmin, the major enzyme responsible for endogenous fibrinolysis and an important regulatory element in thrombosis. Circulating tPA is implicated in the progression and incidence of clinically apparent atherothrombotic cardiovascular diseases (CVD), such as myocardial infarction and stroke, and is associated, in some studies, with advanced atherosclerosis.1–11 Recombinant tPA is approved for use in patients with acute myocardial infarction and is the only drug approved by the U.S. Food and Drug Administration for treatment of acute ischemic stroke.5, 7

The estimated heritability for circulating tPA level is as high as 0.67, based on family and twin studies, providing substantial evidence of genetic influences on circulating levels.12–14 Little is known about the genetic predictors of circulating tPA. Several genetic polymorphisms within the PLAT gene locus have been identified, including the well-studied 311bp Alu-repeat insertion/deletion polymorphism (rs4646972).15 In some cohorts, this Alu-repeat polymorphism has been associated with levels of circulating tPA and with CVD risk, although this finding was not seen in all cohorts studied.4, 16, 17 Circulating levels of tPA are also associated with common polymorphisms in genes contained in the renin-angiotensin and bradykinin systems.18, 19

To date, there has not been a genome-wide association study (GWAS) on this circulating biomarker. We conducted a meta-analysis of 14 studies that had both tPA measurement and genome-wide genotype data in order to identify common variants that are associated with the variation in circulating levels of tPA antigen. Our study included a total of 26,929 participants who were enrolled in 14 cohorts of European ancestry with genome-wide markers. For replication, we evaluated the lead SNPs in an independent sample. We sought evidence for biological function for the lead SNPs within each locus, using human gene expression databases and RNA silencing studies in endothelial cells. We further sought to identify evidence for a role, if any, of the associated genetic variants with thrombosis-related clinical end points including apparent coronary artery disease (CAD) and stroke.

MATERIALS AND METHODS

Detailed Materials and Methods are available in the online-only Supplement.

RESULTS

Cohort Characteristics

The characteristics of a total of 26,929 participants in the 14 discovery cohorts are summarized in Supplemental Table I. The average age ranged from 45.2 years to 76.7 years. The percentage of males ranged from 38.5% to 75.3%, except for the largely female Twins UK, in which males comprised 4.8%. The BMI was similar across the cohorts, with a range of 26.1 kg/m2 to 27.9 kg/m2. The mean tPA level ranged from 5.06 ng/ml to 11.01 ng/ml.

Results of Primary GWAS

The P value results of our discovery meta-analysis for the 2,455,857 meta-analyzed SNPs are presented in Figure 1. A total of three loci reached genome-wide significance threshold of 5×10−8 (Table 1). For the first locus, we identified multiple SNPs (n=61) of genome-wide significance in the 6q24.3 region that harbors the STXBP5 gene.20 The SNP rs9399599 (within intron 26 of STXBP5) has the smallest P value of 2.9×10−14. Allele T (frequency =0.54) is the risk allele, with an effect size (se) of 0.032 (0.004). As the trait was natural-logarithm transformed, this translates to an increase of 1.033 ng/ml of tPA per copy of the risk allele. The regional plot demonstrates that all significant SNPs in the region are in high LD with the lead SNP (Supplemental Figure I, Plot A). The second locus includes 7 SNPs reaching the genome-wide significance threshold; six of these SNPs lie within POLB while another one lies within PLAT, the gene that encodes tPA. The lead SNP (rs3136739, P=1.3×10−9) resides within intron 3 of POLB. The SNP within PLAT is a non-synonymous SNP (rs2020921, P = 2.0×10−8) within exon 5 of PLAT with the minor allele causing a tryptophan to be substituted for an arginine. Based on the 1000 Genomes project European data, these two SNPs are in LD (r2 = 0.5). After re-analysis of Chromosome 8 conditioning on rs3136739, rs2020921 had a P-value of 2.1×10−4 and was the only SNP with a P-value < 1×10−3 within the 1.6 Mb region containing these two SNPs, suggesting there are two separate signals.

Figure 1. Manhattan plot showing the association P-values for the meta-analyzed SNPs in the discovery cohorts.

Figure 1

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X-axis organized by chromosome and base pair positions. Y-axis shows the -log10 of the association P-values. The horizontal dotted line marks the threshold for genome-wide significance (P =5.0×10−8).

Table 1.

Association results for four SNPs within the three significant loci with circulating levels of tPA antigen

SNP Chr Position Gene Effect
Allele
(freq)		 β, se
(ln-trans)		 GM ratio*
(95%CI)		 P-value PHet**
rs9399599 (lead SNP) 6 147744992 STXBP5 intron 26 T -> A (0.54) 0.032, 0.004 1.032 (1.024–1.041) 2.9×10−14 0.61
rs2020921 (nsSNP) 8 42164122 PLAT exon 5 G -> A (0.95) 0.067, 0.012 1.069(1.045–1.095) 2.0×10-8 0.15
rs3136739 (lead SNP) 8 42324237 POLB intron 3 A -> G (0.95) 0.063, 0.010 1.065 (1.043–1.087) 1.3×10-9 0.33
rs7301826 (lead SNP) 12 129857054 STX2 intron 7 C -> T (0.43) 0.027, 0.004 1.027 (1.018–1.036) 1.0×10-9 0.49
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*

per-allele proportionate increase in geometric mean tPA

**

P value for heterogeneity test

The third genome-wide locus includes a total of 33 SNPs lying within STX2 in the 12q24.33 region. The lead SNP (rs7301826, P=1.0×10−9) resides within intron 7 of STX2. Regional plots for these three loci are shown in Supplemental Figure I. Summary statistics of the three lead SNPs and the cis-acting SNP within PLAT in each individual GWAS are shown in Supplemental Table III. For all four SNPs in these three loci, there was no evidence for heterogeneity across studies (P>0.05) (Table 1). The individual and combined effect of the three top SNPs in explaining phenotypic variance was assessed in the largest contributing study (B58C). The proportion of variance in log-transformed tPA explained by the top three loci combined was 0.75%. This comprised 0.29% variance explained by rs9399599 alone, 0.16% variance explained by rs7301826 alone, and 0.28% variance explained by rs3136739 alone.

To test for replication, genotyping was conducted in 4,487 participants from PREVEND. In the PREVEND replication cohort, none of the 3 SNPs was associated with tPA (P<0.05). The effect sizes were smaller: −0.001, 0.017, 0.002 compared with 0.032, 0.063, 0.027, respectively, for the 3 lead SNPs within STXBP5, POLB-PLAT, and STX2. After combined meta-analysis of these results with the data from the fourteen discovery cohorts, the combined meta-analysis P values for association for the four genome-wide associated SNPs (rs9399599, rs2020921, rs3136739, and rs7301826) each remained genome-wide significant (P < 5.0× ×10−8).

Association with Gene Expression

All three lead SNPs and their proxies were searched against three large eQTL sources as described in the online detailed materials and methods. eQTL results provided expression association evidence for STXBP5 and STX2, but not for the chromosome 8 locus (Table 2). SNP rs7739314 (P < 3.1×10−12), located ~500 bp 3’ of STXBP5, was modestly associated with STXBP5 expression in lymphocytes (P < 1.6×10−3), CD4+ lymphocytes (P < 1.7×10−4), and liver (P < 0.03), though this was not the strongest eSNP for STXBP5 in these respective tissues. Three perfect proxy SNPs (r2=1.0) for the lead STX2 SNP (rs7301826) were strongly associated with expression of STX2 in a wide range of blood cells and other tissues. In every case, the strongest eSNP for STX2 was the same or a perfect proxy for the strongest SNP associated with circulating tPA level, indicating a high degree of concordance between the eQTL and association signals. tPA SNPs at the STX2 and STXBP5 loci were not significantly associated with expression of any other genes at those loci.

Table 2.

eQTL for two loci with proximal gene expression in human cells and tissues.

Index SNP Proxy eSNP†(tPA P, r2) eQTL Tissue eQTL P Strongest
eSNP†† 		Strongest eSNP
(eQTL P, tPA P, r2†)
rs9399599 in STXBP5 rs7739314 (3.1×10−12, 0.97) CD4+ lymphocytes NA rs694625 1.4×10−4, 0.02, 0.17
Lymphocytes 1.6×10−3 rs620715 3.5×10−4, 2.4×10−8, 0.90
Liver 0.03 rs1765028 7.8×10−6,4.4×10−6,0.44
rs7301826 in STX2 rs10848205 (1.5×10−6, 1.0) Monocytes 3.8×10−274 Same as proxy
rs10773819 (1.4×10−6 ,1.0) Lymphocytes 7.5×10−92 Same as proxy
Monocytes 1.5×10−80 rs1106369 7.1×10−91,1.5×10−6,1.0
PBMC 1.4×10−25
Macrophage 1.8×10−24 rs1106369 2.3×10−28, 1.5×10−6,1.0
CD4+ lymphocytes 2.9×10−20 Same as proxy
Leukocytes 2.7×10−10 Same as proxy
Liver 9.0×10−6 Same as proxy
Mammary artery 4.9×10−3 Same as proxy
rs2001483 (1.8×10−6, 1.0) Liver 2.7×10−5 Same as proxy
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All sentinel SNPs and their proxies were searched against eQTL sources as described in the online detailed materials and methods.

†

Proxy SNP is the measured SNP in highest LD with the index SNPLD measured in correlation R-square, based on HapMap2 CEU data.

††

Strongest eSNP is the one with the best eQTL P-value, for the same tissue and transcript as for the lead proxy eSNP.

Results of Gene Silencing for STXBP5 and STX2 in Human Endothelial Cells

The proteins encoded by STX2 and STXBP5 are expressed in three types of vascular endothelial cells (HAEC, HUVEC, and HDMVEC) (Figure 2B–D). Silencing of STX2 and STXBP5 decreased expression of STX2 and STXBP5 proteins, respectively, in each of the three endothelial cell types (Figure 2B–D). Silencing STXBP5 significantly decreased release of tPA, while silencing STX2 significantly increased tPA release, in both resting and histamine-stimulated vascular endothelial cells (Figure 2A). SNP specific effects were not evaluated in the current experiments.

Figure 2. Effect of gene silencing on tPA release.

Figure 2

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Endothelial cells were transfected with oligonucleotides to silence STXBP5 or STX2, and then treated with histamine to induce tPA release. Levels of tPA in the media were measured by ELISA. (A) Silencing STXBP5 decreases tPA release, whereas silencing STX2 increases tPA release. (B–D) Silencing of STX2 or STXBP5 decreases target protein expression in human umbilical vein endothelial cells (HUVEC) (B), human aortic endothelial cells (HAEC) (C), and human dermal microvascular endothelial cells (HDMVEC) (D). Each panel includes a 3 by 3 matrix of western blot images for the 3 proteins (STX2, STXBP5, beta-actin) after 3 gene silencing approaches (siControl for control scrambled oligonucleotide, siSTX2 for siRNA directed against STX2, and siSTXBP5 for siRNA directed against STXBP5).

Association with CAD and Stroke

In a recently updated meta-analysis (based on 13 observational cohort studies and 5494 cases of CAD), a 1SD increase in tPA-antigen, adjusted for conventional cardiovascular risk factors, was associated with an odds ratio of incident CAD of 1.13 (95%CI 1.06, 1.21).11 Since the genetic influences that we detected on tPA levels together accounted for less than 1% of phenotypic variance, and individual SNPs were associated with differences in untransformed tPA levels of less than 0.2SD, comparing homozygotes to heterozygotes, it is inherently unlikely that any of these variants would impact greatly on CAD risk, and an in silico look-up in previously published GWAS meta-analyses confirms this (Supplemental Table IV). The upper confidence limits in this table exclude clinically or epidemiologically important associations of the three top SNPs with cardiovascular disease, defined as either CAD or stroke.

Findings for Previously Implicated Genes

We examined for evidence of association of SNPs within a 20kb region of the cis-locus, PLAT, as well as SNPs within ACE, AGT, AGTR1, BDKRB2, and SERPINE1.21, 22 For a total of 204 SNPs, 32 SNPs within ACE, AGT, BGKRB2, PLAT, SERPINE1 have a P value <0.05 (Supplemental Table V). However, only three SNPs in PLAT (lead rs2020921, P=5.1×10−8) and five SNPs in SERPINE1 (lead SNP rs2227667, P=2.2×10−5) remained significant after adjusting for the multiple testing (multiple testing threshold P<2.5×10−4). Given the correlation of SNPs within these two loci due to residual LD, the associations for each of the eight SNPs within these two loci are robust, extending evidence from the prior literature for the existence of a genetic association with plasma levels of tPA.

DISCUSSION

In a large GWAS study of over 27,000 research participants of European ancestry, we discovered a total of three loci that have not been previously reported to be associated with circulating tPA level at a genome-wide significant threshold. This is the first GWAS study that identifies a non-synonymous SNP within PLAT that reaches genome-wide significant threshold. eQTL examination provided strong functional evidence for associated SNPs in STXBP5 and STX2, and further studies in human endothelial cells directly implicate these two genes in expression, production and release of tPA protein.

Prior candidate gene studies have not consistently noted the presence of associations between SNPs in the PLAT gene and circulating levels of tPA, and several studies have found no such association.17, 23 The current study substantially extends and strengthens the prior hypothesis of a cis-association between SNPs in PLAT and circulating levels of tPA by providing evidence for a strong and genome-wide significant association of SNPs within the PLAT locus. We identify an association with a non-synonymous SNP rs2020921 within PLAT, suggesting a functional variant, and separately with SNPs in POLB, raising the hypothesis of an independent genetic determination of tPA in this locus. These findings suggest that the cis-associations are complex and may have been missed because previous mapping studies focused on mapping a narrow genomic region and were conducted in relatively smaller samples. There is little known about the functional consequences of the non-synonymous PLAT mutation and prediction software provides conflicting predictions of its effect (PolyPhen-2: neutral, SIFT: deleterious) therefore future functional experiments are warranted.

The associations of variants within STXBP5 and STX2 with circulating levels of tPA are novel findings. Syntaxins are members of a family of membrane integrated SNARE (Soluble NSF Attachment Protein Receptor) proteins that participate in exocytosis.24 Syntaxin 4 plays a role in exocytosis of Weibel-Palade bodies in endothelial cells.25 Our functional studies reveal that STXBP5 and STX2 play a role in endothelial release of tPA. Our cell culture studies strongly support a role for these two genes in regulating endothelial cell tPA expression, production and release. While these studies provide novel evidence derived from an unbiased GWAS for the role of STXBP5 and STX2 in regulation of tPA at the endothelial cell level, further studies are clearly warranted to examine how manipulation of the specific SNPs rather than silencing the whole gene affects the dynamics of circulating tPA level at the cellular and model organism level.

SNPs in the STXBP5 and STX2 loci were also reported to be associated with circulating levels of vWF in a recent study by the CHARGE Consortium.26 Based on the 1000 Genomes data, there is moderate to strong correlation of the lead SNP associated with vWF26 and the lead SNP we report to be associated with tPA for STXBP5 (rs9390459, r2=0.97, D'=1.0) and for STX2 (rs79789987, r2=0.63, D'=1.0). Although tPA and vWF share associations with common variants at the STXBP5 and STX2 loci, these relatively weak genetic associations are not a major explanation for the phenotypic correlation between these haemostatic risk factors. Both plasma components were measured in the British 1958 birth cohort (B58C), and a highly significant (p<10−22) correlation (r=0.13) remained between log-transformed tPA and log-transformed vWF levels, after adjustment for the top SNPs at STXBP5 (rs9399599) and STX2 (rs7301826). The association of identical syntaxin-coding genes with various circulating hemostatic factor levels may provide an opportunity for further investigations on these newly identified mechanisms by which these circulating hemostatic factors are implicated in thrombotic cardiovascular and metabolic diseases.

Our study was motivated in part in order to better understand the mechanism by which endogenous tPA may be implicated in clinically apparent cardiovascular disease outcomes. Our lead SNP rs9399599 in the STXBP5 locus is associated with circulating levels of vWF26 and with risk of venous thrombosis.27 While elevated plasma level of vWF is a predictor of venous thrombosis, the available evidence suggests that the level of tPA is not associated with venous thrombosis.28 Another non-synonymous SNP rs1039084 within STXBP5 has a less significant association with vWF (P =1.0×10−9) than the lead SNP in our study, but rs1039084 has a stronger association than rs9399599 with vWF in a subgroup of CHD patients.29 For the STX2 locus, the SNP rs7978987 has been previously reported to be associated with vWF levels26 and with an increased risk of arterial thrombosis.29 The P value for association of this SNP with tPA is 4.5×10−9, similar to that of the lead SNP rs7301826 (P = 4.1×10−9). Two other SNPs within STX2 (rs1236 and rs11061158) were also previously reported to be associated with CHD.29 The former is genome-wide significant and the latter is marginally significant in our study (P = 1.9×10−9 and 0.048 respectively). None of the three lead SNPs in PLAT/POLB, STXBP5 or STX2 was found to be associated with CAD or stroke based on an in-silico examination of results from a large sample for CD and a moderate sized sample for stroke. However, the key function of tPA in the coagulation system and the importance of coagulation to the cardiovascular system have been well established, and the novel genes identified in our study merit further study of their potential role as intermediaries in the pathophysiology of atherothrombotic CVD.

The replication of previously reported findings for associations between genetic variation in SERPINE1 and PLAT with circulating tPA levels was able to act as a “positive control” for this study and extends the evidence for the existence of a genetic association in these genes with plasma levels of tPA.

We note several potential study limitations. First, samples in our study are of European ancestry; therefore, our findings may not be generalizable to populations of different ethnicity. Second, the replication sample size is quite small, with an 80% power to detect an association at the 5% significance level. Although not particularly weak, there was still inadequate power to provide strong evidence for replication of small effects detected in the discovery study. We therefore included biological validation that includes in vitro cell studies. Third, due to the low frequency of the lead SNPs within the POLB-PLAT locus, we are not able to use a traditional LD mapping approach to refine the association signals. The lead SNP within POLB (rs3136739) is in perfect LD (r2=1) with the non-synonymous SNP (rs2020921) within exon 5 of PLAT, based on the HapMap2 genotype data. However, rs3136739 has a missing rate of 10% in the HapMap2 data. Even with the most recent available 1000 genomes genotype data, however, it remains difficult to fully characterize the haplotype structure for SNPs with low minor allele frequency (~5%) based on pair-wise LD. Forth, although it is impossible to rule out that the association of the non-synonymous mutation with circulating tPA levels is simply a confounder introduced by altered antibody binding during the tPA measurement procedure, it is unlikely after investigating all information available to us at this time. Finally, there may be distinct roles for genetic variation in regulating circulating levels in healthy individuals compared with elevated levels in individuals in whom thrombolytic activity is induced. While there is no evidence of heterogeneity of effect by cohort, our results cannot exclude the possibility of meaningful differences in effects of genetic variation on circulating levels in the overall population versus subgroups of individuals with increased thrombolytic activity.

In conclusion, by analyzing a total of 26,929 participants from 14 discovery cohorts across the United States and Europe, we provide genome-wide evidence of association of SNPs in the STXBP5, PLAT and STX2 loci with circulating levels of tPA antigen. While our analyses do not provide evidence for association of these SNPs with clinically apparent CAD or stroke, we do provide functional evidence in endothelial cells for a novel regulatory role of STXBP5 and STX2 on tPA availability. The strong eQTL result for STX2 in a wide range of tissues supports the hypothesis that associated alleles may modulate tPA levels via a functional effect on gene expression.

Supplementary Material

Materials and Methods
Supplemental Material

SIGNIFICANCE.

Tissue plasminogen activator (tPA) catalyzes the conversion of plasminogen to plasmin, the major enzyme responsible for endogenous fibrinolysis. In some but not all studies, elevated plasma levels of tPA have been associated with coronary artery disease (CAD) and other cardiovascular diseases. Through a genome-wide association study approach we provide evidence of association of genetic variants in the STXBP5, PLAT and STX2 loci with circulating levels of tPA antigen. While our analyses do not provide supportive evidence for association of these SNPs with clinical CAD or stroke, we do provide additional functional evidence for a novel regulatory role of STXBP5 and STX2 on tPA availability in endothelial cells. Results from gene expression studies in various tissues support the hypothesis that associated alleles may modulate circulating tPA levels via a functional effect on gene expression. Our findings provide new insights into tPA biology and avenues for future research for the prevention and treatment of thrombosis.

ACKNOWLEDGEMENTS

The authors acknowledge the essential role of the CHARGE (Cohorts for Heart and Aging Research in Genome Epidemiology) Consortium in providing a collaboration protocol and data sharing resource for this project. The authors fully acknowledge the thousands of study participants who volunteered their time to help advance science and the scores of research staff and scientists who have made this research possible. ARIC would like to thank the staff and participants of the ARIC study for their important contributions. B58C acknowledges use of phenotype and genotype data from the British 1958 Birth Cohort DNA collection. CROATIA-Vis would like to acknowledge the invaluable contributions of the recruitment team (including those from the Institute of Anthropological Research in Zagreb) in Vis, the administrative teams in Croatia and Edinburgh and the people of Vis. Genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh. The Framingham Heart Study would like to acknowledge that the analyses presented here reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. ORCADES acknowledges the invaluable contributions of Lorraine Anderson, the research nurses in Orkney, and the administrative team in Edinburgh. Twins UK acknowledges essential contribution of Peter Grant and Angela Carter from the Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, UK for measurements of clotting factors phenotypes. Folkert W. Asselbergs is supported by UCL Hospitals NIHR Biomedical Research Centre.

Sources of Funding: ARIC The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C).

ASAP (Advanced Study of Aortic Pathology): This work was supported by the Swedish Research Council [12660]; the Stockholm County Council [20090077the Swedish Heart-Lung Foundation [20090541], the European Commission [FAD, Health F2 2008 200647]; a donation by Fredrik Lundberg. B58C (British 1958 Birth Cohort) was funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02. (http://www.b58cgene.sgul.ac.uk/). Genotyping for the B58C-WTCCC subset was funded by the Wellcome Trust grant 076113/B/04/Z. The B58C-T1DGC genotyping utilized resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), National Human Genome Research Institute (NHGRI), National Institute of Child Health and Human Development (NICHD), and Juvenile Diabetes Research Foundation International (JDRF) and supported by U01 DK062418. B58C-T1DGC GWAS data were deposited by the Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research (CIMR), University of Cambridge, which is funded by Juvenile Diabetes Research Foundation International, the Wellcome Trust and the National Institute for Health Research Cambridge Biomedical Research Centre; the CIMR is in receipt of a Wellcome Trust Strategic Award (079895). The B58C-GABRIEL genotyping was supported by a contract from the European Commission Framework Programme 6 (018996) and grants from the French Ministry of Research. Cardiogenics was funded by the European Union 6th Framework Programme (LSHM-CT-2006-037593). The CHS research was supported by NHLBI contractsHHSN268201200036C, N01HC85239, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL105756 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. DNA handling and genotyping at Cedars-Sinai Medical Center was supported in part by the National Center for Research Resources, grant UL1RR033176, and is now at the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124; in addition to the National Institute of Diabetes and Digestive and Kidney Disease grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The CROATIA-Vis study in the Croatian island of Vis was supported through the grants from the Medical Research Council UK and Ministry of Science, Education and Sport of the Republic of Croatia (number 108-1080315-0302) and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). The Framingham Heart Study was partially supported by NHLBI's Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc., for genotyping services (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. Partial investigator support was provided by National Institute of Diabetes and Digestive and Kidney Diseases K24 DK080140 (JB Meigs). GeneSTAR: This research was supported by grants 1U01 HL072518 and R01 HL59684 from the National Institutes of Health, Bethesda, Maryland, and the Johns Hopkins University School of Medicine General Clinical Research Center, National Institutes of Health Grant M01 RR00052. PROCARDIS was supported by the Swedish Research Council (8691), the Knut and Alice Wallenberg Foundation, the Swedish Heart-Lung Foundation, the Torsten and Ragnar Söderberg Foundation, the Strategic Cardiovascular Program of Karolinska Institutet and Stockholm County Council, the Foundation for Strategic Research and the Stockholm County Council. Maria Sabater-Lleal is a recipient of a Marie Curie Intra European Fellowship within the 7th Framework Programme of the European Union (PIEF-GA-2009-252361). LURIC has received funding from the 6th Framework Program (integrated project Bloodomics, grant LSHM-CT-2004-503485) and from the 7th Framework Program (Atheroremo, grant agreement number 201668 and RiskyCAD, grant agreement number 305739) of the European Union.

The MARTHA project was supported by a grant from the Program Hospitalier de Recherche Clinique. TOM was supported by a grant from the Fondation pour la Recherche Médicale. Statistical analyses in MARTHA benefit from the C2BIG computing centre funded by the Fondation pour la Recherche Médicale, La Région Ile de France (CODDIM) and the Genomic Network of the Pierre and Marie Curie University (Paris 06). ORCADES: DNA extractions were performed at the Wellcome Trust Clinical Research Facility in Edinburgh, UK. ORCADES was supported by the Chief Scientist Office of the Scottish Government, the Royal Society and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). PREVEND genetics is supported by the Dutch Kidney Foundation (Grant E033), The Netherlands Heart Foundation (Grant 2006B140, 2006T003), National Institutes of Health (grant LM010098, HL65234, HL67466, RR018787) and the EU project grant GENECURE (FP-6 LSHM CT 2006 037697). Pim van der Harst is supported by the NWO VENI grant 91676170 and the Dutch Inter University Cardiology Institute Netherlands (ICIN). Folkert W. Asselbergs is supported by a clinical fellowship from the Netherlands Organisation for Health Research and Development (ZonMw grant 90700342). PROSPER was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. Prof. Dr. Jukema is an established clinical investigator of the Netherlands Heart Foundation (grant 2001 D 032). Support for genotyping of the PROSPER/PHASE study was provided by the seventh framework program of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). Measurement of plasma tPA was funded by the Scottish Executive Chief Scientist Office, Health Services Research Committee grant number CZG/4/306. The Rotterdam Study is supported by the Erasmus Medical Center and Erasmus University Rotterdam; the Netherlands Organization for Scientific Research (NWO); the Netherlands Organization for Health Research and Development (ZonMw); the Research Institute for Diseases in the Elderly (RIDE); the Netherlands Heart Foundation; the Ministry of Education, Culture and Science; the Ministry of Health Welfare and Sports; the European Commission; and the Municipality of Rotterdam. Support for genotyping was provided by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) project nr. 050-060-810. Jacqueline Witteman is supported by NWO grant (vici, 918-76-619). Abbas Dehghan is supported by NWO grant (veni, 916.12.154) and the EUR Fellowship. The Twins UK study was funded by the Wellcome Trust; European Community's Sixth and Seventh Framework Programmes (FP-6/2005-2008) LIFE SCIENCES & HEALTH (Ref 005268 Genetic regulation of the end stage clotting process that leads to thrombotic stroke: The EuroClot Consortium and (FP7/2007-2013), ENGAGE project HEALTH-F4-2007-201413 and the FP-5 GenomEUtwin Project (QLG2-CT-2002-01254). The study also receives support from the Dept of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's & St Thomas' NHS Foundation Trust in partnership with King's College London. Timothy D. Spector is an NIHR Senior Investigator. The project also received support from a Biotechnology and Biological Sciences Research Council (BBSRC) project grant. (G20234). The authors acknowledge the funding and support of the National Eye Institute via an NIH/CIDR genotyping project (PI: Terri Young). SYS is supported by a Post-Doctoral Research Fellowship from the Oak Foundation. University of Rochester: This research was supported by grants from the NIH (P01 HL56091, R01 HL074061, R01 HL78635, P01 HL65608), AHA (EIG 0140210N), and the Paul N. Yu Professorship to CJL. Supported by grants from the AHA (0835446N) to MY. The GWAS component of the VISP study was supported by the National Human Genome Research Institute (NHGRI), Grant U01 HG005160 (PI Michele Sale & Bradford Worrall), as part of the Genomics and Randomized Trials Network (GARNET). Genotyping services were provided by the Johns Hopkins University Center for Inherited Disease Research (CIDR), which is fully funded through a federal contract from the National Institutes of Health to the Johns Hopkins University. Assistance with data cleaning was provided by the GARNET Coordinating Center (U01 HG005157; PI Bruce S Weir). Study recruitment and collection of datasets for the VISP clinical trial were supported by an investigator-initiated research grant (R01 NS34447; PI James Toole) from the United States Public Health Service, National Institute of Neurological Disorders and Stroke of the National Institutes of Health, Bethesda, Maryland. In addition to funding sources noted above, the CHARGE Consortium Neurology Working Group was supported by U01 HL096917 and R01-HL093029 for ARIC; by NHLBI contracts N01-HC-35129, N01 HC-15103, N01-HC-75150, N01-HC-45133, and AG-023629, AG-15928, AG-20098, and AG-027058 from the NIA, for CHS: and by NINDS and NIA grants NS17950, AG08122, and AG033193 for FHS.

O.H.F received a research grant from Pfizer. B.M.P received a research grant from the NIH. D.J.S has received a research grant from the Scottish Executive and an honourarium from Boehringer Ingelheim for consultancy. R.P.T. has received NIH grants to measure coagulation factors.

Nonstandard Abbreviations and Acronyms

CAD

Coronary artery disease

CVD

Cardiovascular disease

eQTL

Expression quantitative trait locus

eSNP

Expression single nucleotide polymorphism

GWAS

Genome-wide association study

LD

Linkage disequilibrium

MI

Myocardial infarction

SNP

Single nucleotide polymorphism

tPA

Tissue plasminogen activator

vWF

Von Willebrand factor

Footnotes

Disclosures: No other authors have conflicts of interest to disclose.

Writing Group: J.H., S.T., F.W.A., M.S-L., D.T., J.E.H., A.D.J., N.L.S., S.M.W., C.H., P.v.d.H., A.H. C.J.L, D.P.S. (co-chair), C.J.O. (co-chair)

REFERENCES

  • 1.Steins MB, Padro T, Li CX, Mesters RM, Ostermann H, Hammel D, Scheld HH, Berdel WE, Kienast J. Overexpression of tissue-type plasminogen activator in atherosclerotic human coronary arteries. Atherosclerosis. 1999;145:173–180. doi: 10.1016/s0021-9150(99)00030-1. [DOI] [PubMed] [Google Scholar]
  • 2.Wiman B, Andersson T, Hallqvist J, Reuterwall C, Ahlbom A, deFaire U. Plasma levels of tissue plasminogen activator/plasminogen activator inhibitor-1 complex and von willebrand factor are significant risk markers for recurrent myocardial infarction in the stockholm heart epidemiology program (sheep) study. Arterioscler Thromb Vasc Biol. 2000;20:2019–2023. doi: 10.1161/01.atv.20.8.2019. [DOI] [PubMed] [Google Scholar]
  • 3.Jansson JH, Olofsson BO, Nilsson TK. Predictive value of tissue plasminogen activator mass concentration on long-term mortality in patients with coronary artery disease. A 7-year follow-up. Circulation. 1993;88:2030–2034. doi: 10.1161/01.cir.88.5.2030. [DOI] [PubMed] [Google Scholar]
  • 4.van der Bom JG, de Knijff P, Haverkate F, Bots ML, Meijer P, de Jong PT, Hofman A, Kluft C, Grobbee DE. Tissue plasminogen activator and risk of myocardial infarction. The rotterdam study. Circulation. 1997;95:2623–2627. doi: 10.1161/01.cir.95.12.2623. [DOI] [PubMed] [Google Scholar]
  • 5.Caplan LR. Tissue plasminogen activator for acute ischemic stroke. N Engl J Med. 1999;341:1240–1241. doi: 10.1056/NEJM199910143411618. [DOI] [PubMed] [Google Scholar]
  • 6.Mills JD, Mansfield MW, Grant PJ. Tissue plasminogen activator, fibrin d-dimer, and insulin resistance in the relatives of patients with premature coronary artery disease. Arterioscler Thromb Vasc Biol. 2002;22:704–709. doi: 10.1161/hq0402.105902. [DOI] [PubMed] [Google Scholar]
  • 7.Bruno A. Tissue-plasminogen activator for acute ischaemic stroke. Lancet. 1997;349:503–504. doi: 10.1016/S0140-6736(05)61216-0. [DOI] [PubMed] [Google Scholar]
  • 8.Smith FB, Lee AJ, Rumley A, Fowkes FG, Lowe GD. Tissue-plasminogen activator, plasminogen activator inhibitor and risk of peripheral arterial disease. Atherosclerosis. 1995;115:35–43. doi: 10.1016/0021-9150(94)05498-8. [DOI] [PubMed] [Google Scholar]
  • 9.Cimminiello C. Tissue-type plasminogen activator and risk of myocardial infarction. Lancet. 1993;342:48–49. doi: 10.1016/0140-6736(93)91909-6. [DOI] [PubMed] [Google Scholar]
  • 10.Lowe GD, Danesh J, Lewington S, Walker M, Lennon L, Thomson A, Rumley A, Whincup PH. Tissue plasminogen activator antigen and coronary heart disease. Prospective study and meta-analysis. Eur Heart J. 2004;25:252–259. doi: 10.1016/j.ehj.2003.11.004. [DOI] [PubMed] [Google Scholar]
  • 11.Willeit P, Thompson A, Aspelund T, Rumley A, Eiriksdottir G, Lowe G, Gudnason V, Di Angelantonio E. Hemostatic factors and risk of coronary heart disease in general populations: New prospective study and updated meta-analyses. PLoS One. 2013;8:e55175. doi: 10.1371/journal.pone.0055175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.de Lange M, Snieder H, Ariens RA, Spector TD, Grant PJ. The genetics of haemostasis: A twin study. Lancet. 2001;357:101–105. doi: 10.1016/S0140-6736(00)03541-8. [DOI] [PubMed] [Google Scholar]
  • 13.Freeman MS, Mansfield MW, Barrett JH, Grant PJ. Genetic contribution to circulating levels of hemostatic factors in healthy families with effects of known genetic polymorphisms on heritability. Arterioscler Thromb Vasc Biol. 2002;22:506–510. doi: 10.1161/hq0302.104906. [DOI] [PubMed] [Google Scholar]
  • 14.de Lange M, de Geus EJ, Kluft C, Meijer P, van Doornen LJ, Boomsma DI, Snieder H. Genetic influences on fibrinogen, tissue plasminogen activator-antigen and von willebrand factor in males and females. Thromb Haemost. 2006;95:414–419. doi: 10.1160/TH05-09-0596. [DOI] [PubMed] [Google Scholar]
  • 15.Ladenvall P, Wall U, Jern S, Jern C. Eight single-nucleotide polymorphisms (snps) at the human tissue-type plasminogen activator (t-pa) locus. J Hum Genet. 2001;46:737–738. doi: 10.1007/PL00010919. [DOI] [PubMed] [Google Scholar]
  • 16.Ludwig M, Wohn KD, Schleuning WD, Olek K. Allelic dimorphism in the human tissue-type plasminogen activator (tpa) gene as a result of an alu insertion/deletion event. Hum Genet. 1992;88:388–392. doi: 10.1007/BF00215671. [DOI] [PubMed] [Google Scholar]
  • 17.Kathiresan S, Yang Q, Larson MG, Camargo AL, Tofler GH, Hirschhorn JN, Gabriel SB, O'Donnell CJ. Common genetic variation in five thrombosis genes and relations to plasma hemostatic protein level and cardiovascular disease risk. Arterioscler Thromb Vasc Biol. 2006;26:1405–1412. doi: 10.1161/01.ATV.0000222011.13026.25. [DOI] [PubMed] [Google Scholar]
  • 18.Asselbergs FW, Williams SM, Hebert PR, Coffey CS, Hillege HL, Navis G, Vaughan DE, van Gilst WH, Moore JH. The gender-specific role of polymorphisms from the fibrinolytic, renin-angiotensin, and bradykinin systems in determining plasma t-pa and pai-1 levels. Thromb Haemost. 2006;96:471–477. [PubMed] [Google Scholar]
  • 19.Brown NJ, Gainer JV, Murphey LJ, Vaughan DE. Bradykinin stimulates tissue plasminogen activator release from human forearm vasculature through b(2) receptor-dependent, no synthase-independent, and cyclooxygenase-independent pathway. Circulation. 2000;102:2190–2196. doi: 10.1161/01.cir.102.18.2190. [DOI] [PubMed] [Google Scholar]
  • 20.Fujita Y, Shirataki H, Sakisaka T, Asakura T, Ohya T, Kotani H, Yokoyama S, Nishioka H, Matsuura Y, Mizoguchi A, Scheller RH, Takai Y. Tomosyn: A syntaxin-1-binding protein that forms a novel complex in the neurotransmitter release process. Neuron. 1998;20:905–915. doi: 10.1016/s0896-6273(00)80472-9. [DOI] [PubMed] [Google Scholar]
  • 21.Asselbergs FW, Pattin K, Snieder H, Hillege HL, van Gilst WH, Moore JH. Genetic architecture of tissue-type plasminogen activator and plasminogen activator inhibitor-1. Semin Thromb Hemost. 2008;34:562–568. doi: 10.1055/s-0028-1103367. [DOI] [PubMed] [Google Scholar]
  • 22.Huang J, Sabater-Lleal M, Asselbergs FW, Tregouet D, Shin SY, Ding J, Baumert J, Oudot-Mellakh T, Folkersen L, Johnson AD, Smith NL, Williams SM, Ikram MA, Kleber ME, Becker DM, Truong V, Mychaleckyj JC, Tang W, Yang Q, Sennblad B, Moore JH, Williams FM, Dehghan A, Silbernagel G, Schrijvers EM, Smith S, Karakas M, Tofler GH, Silveira A, Navis GJ, Lohman K, Chen MH, Peters A, Goel A, Hopewell JC, Chambers JC, Saleheen D, Lundmark P, Psaty BM, Strawbridge RJ, Boehm BO, Carter AM, Meisinger C, Peden JF, Bis JC, McKnight B, Öhrvik J, Taylor K, Franzosi MG, Seedorf U, Collins R, Franco-Cereceda A, Syvänen AC, Goodall AH, Yanek LR, Cushman M, Müller-Nurasyid M, Folsom AR, Basu S, Matijevic N, van Gilst WH, Kooner JS, Hofman A, Danesh J, Clarke R, Meigs JB, Kathiresan S, Reilly MP, Klopp N, Harris TB, Winkelmann BR, Grant PJ, Hillege HL, Watkins H, Spector TD, Becker LC, Tracy RP, März W, Uitterlinden AG, Eriksson P, Cambien F, Morange PE, Koenig W, Soranzo N, van der Harst P, Liu Y, O'Donnell CJ, Hamsten A, Consortium D, Consortium C, Consortium CD, Consortium C. Genome-wide association study for circulating levels of pai-1 provides novel insights into its regulation. Blood. 2012;120:4873–4881. doi: 10.1182/blood-2012-06-436188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Ladenvall P, Nilsson S, Jood K, Rosengren A, Blomstrand C, Jern C. Genetic variation at the human tissue-type plasminogen activator (tpa) locus: Haplotypes and analysis of association to plasma levels of tpa. Eur J Hum Genet. 2003;11:603–610. doi: 10.1038/sj.ejhg.5201011. [DOI] [PubMed] [Google Scholar]
  • 24.Barrett JC, Clayton DG, Concannon P, Akolkar B, Cooper JD, Erlich HA, Julier C, Morahan G, Nerup J, Nierras C, Plagnol V, Pociot F, Schuilenburg H, Smyth DJ, Stevens H, Todd JA, Walker NM, Rich SS. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet. 2009;41:703–707. doi: 10.1038/ng.381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Strachan DP, Rudnicka AR, Power C, Shepherd P, Fuller E, Davis A, Gibb I, Kumari M, Rumley A, Macfarlane GJ, Rahi J, Rodgers B, Stansfeld S. Lifecourse influences on health among british adults: Effects of region of residence in childhood and adulthood. Int J Epidemiol. 2007;36:522–531. doi: 10.1093/ije/dyl309. [DOI] [PubMed] [Google Scholar]
  • 26.Smith NL, Chen MH, Dehghan A, Strachan DP, Basu S, Soranzo N, Hayward C, Rudan I, Sabater-Lleal M, Bis JC, de Maat MP, Rumley A, Kong X, Yang Q, Williams FM, Vitart V, Campbell H, Malarstig A, Wiggins KL, Van Duijn CM, McArdle WL, Pankow JS, Johnson AD, Silveira A, McKnight B, Uitterlinden AG, Aleksic N, Meigs JB, Peters A, Koenig W, Cushman M, Kathiresan S, Rotter JI, Bovill EG, Hofman A, Boerwinkle E, Tofler GH, Peden JF, Psaty BM, Leebeek F, Folsom AR, Larson MG, Spector TD, Wright AF, Wilson JF, Hamsten A, Lumley T, Witteman JC, Tang W, O'Donnell CJ. Novel associations of multiple genetic loci with plasma levels of factor vii, factor viii, and von willebrand factor: The charge (cohorts for heart and aging research in genome epidemiology) consortium. Circulation. 2010;121:1382–1392. doi: 10.1161/CIRCULATIONAHA.109.869156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Smith NL, Rice KM, Bovill EG, Cushman M, Bis JC, McKnight B, Lumley T, Glazer NL, van Hylckama Vlieg A, Tang W, Dehghan A, Strachan DP, O'Donnell CJ, Rotter JI, Heckbert SR, Psaty BM, Rosendaal FR. Genetic variation associated with plasma von willebrand factor levels and the risk of incident venous thrombosis. Blood. 2011;117:6007–6011. doi: 10.1182/blood-2010-10-315473. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Folsom AR, Cushman M, Heckbert SR, Rosamond WD, Aleksic N. Prospective study of fibrinolytic markers and venous thromboembolism. J Clin Epidemiol. 2003;56:598–603. doi: 10.1016/s0895-4356(03)00052-0. [DOI] [PubMed] [Google Scholar]
  • 29.van Loon JE, Leebeek FW, Deckers JW, Dippel DW, Poldermans D, Strachan DP, Tang W, O'Donnell CJ, Smith NL, de Maat MP. Effect of genetic variations in syntaxin-binding protein-5 and syntaxin-2 on von willebrand factor concentration and cardiovascular risk. Circ Cardiovasc Genet. 2010;3:507–512. doi: 10.1161/CIRCGENETICS.110.957407. [DOI] [PMC free article] [PubMed] [Google Scholar]

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Supplementary Materials

Materials and Methods
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