Genetic determinants of tissue factor pathway inhibitor plasma levels

Dennis, Jessica; Kassam, Irfahan; Morange, Pierre‐Emmanuel; Trégouët, David‐Alexandre; Gagnon, France

doi:10.1160/th14-12-1043

Cited by 12 publications

(17 citation statements)

References 70 publications

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“…This is supported by Th− patients having a significantly higher TFPI/TF ratio, and indeed by the absence of a thrombosis history in all individuals with a ratio >0.7. The reasons behind some BS patients having a relatively low level of MP-associated TFPI compared to MP-associated TF are unclear, but could include differential synthesis of TF and TFPI by activated monocytes24, TFPI degradation by leukocyte-derived serine proteases and/or reactive oxygen species4546 and the influence of genetic variants of TFPI on plasma levels47.…”

Section: Discussionmentioning

confidence: 99%

A low balance between microparticles expressing tissue factor pathway inhibitor and tissue factor is associated with thrombosis in Behçet’s Syndrome

Khan

Ambrose

Ahnström

et al. 2016

Sci Rep

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Thrombosis is common in Behçet’s Syndrome (BS), and there is a need for better biomarkers for risk assessment. As microparticles expressing Tissue Factor (TF) can contribute to thrombosis in preclinical models, we investigated whether plasma microparticles expressing Tissue Factor (TF) are increased in BS. We compared blood plasma from 72 healthy controls with that from 88 BS patients (21 with a history of thrombosis (Th+) and 67 without (Th−). Using flow cytometry, we found that the total plasma MP numbers were increased in BS compared to HC, as were MPs expressing TF and Tissue Factor Pathway Inhibitor (TFPI) (all p < 0.0001). Amongst BS patients, the Th+ group had increased total and TF positive MP numbers (both p ≤ 0.0002) compared to the Th- group, but had a lower proportion of TFPI positive MPs (p < 0.05). Consequently, the ratio of TFPI positive to TF positive MP counts (TFPI/TF) was significantly lower in Th+ versus Th− BS patients (p = 0.0002), and no patient with a TFPI/TF MP ratio >0.7 had a history of clinical thrombosis. We conclude that TF-expressing MP are increased in BS and that an imbalance between microparticulate TF and TFPI may predispose to thrombosis.

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Section: Discussionmentioning

confidence: 99%

A low balance between microparticles expressing tissue factor pathway inhibitor and tissue factor is associated with thrombosis in Behçet’s Syndrome

Khan

Ambrose

Ahnström

et al. 2016

Sci Rep

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“…Previous candidate gene studies of TFPI plasma levels have focused on hemostatic‐ and lipid‐related genes (reviewed in Dennis et al., ). Increasingly, however, genes with no previously known roles in clotting are being implicated in VTE (Antoni et al., ), arterial thrombosis, and thrombosis‐related phenotypes (Antoni et al., ; Morange et al., ; Rocanin‐Arjo et al., ).…”

Section: Discussionmentioning

confidence: 99%

“…Up to 52% of the variability in TFPI plasma levels is attributable to genetics (Almasy et al., ; Bladbjerg et al., ; Dennis et al., ; Warren et al., ), but few genes have been implicated. Most studies have been of candidate coagulation genes ( TFPI , PROS1 , F5 ), yet variants in these genes explained little of TFPI plasma level variability (Dennis, Kassam, Morange, Tregouet, & Gagnon, ), and in vitro and mouse models suggested that genes outside of the hemostatic pathway may be important (Lupu, Zhu, Popescu, Wren, & Lupu, ; Sanchez‐Solana, Motwani, Li, Eswaran, & Kumar, ). Genome‐wide linkage studies of TFPI plasma levels have been reported (Almasy et al., ; Dennis et al., ), and fine mapping of the most significant linkage signal identified three SNPs 25.1 Mb upstream of TFPI associated with TFPI plasma level variability and VTE risk (Dennis et al., ).…”

Section: Introductionmentioning

confidence: 99%

Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels

et al. 2017

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Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome-wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French-Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis-driven (HD) GWAS approach that prioritized single nucleotide polymorphisms (SNPs) in (1) hemostasis pathway genes, and (2) vascular endothelial cell (EC) regulatory regions, which are among the highest expressers of TFPI. Our GWAS identified 131 SNPs with suggestive evidence of association (P-value < 5 × 10 ), but no SNPs reached the genome-wide threshold for statistical significance. Hemostasis pathway genes were not enriched for TFPI plasma level associated SNPs (global hypothesis test P-value = 0.147), but EC regulatory regions contained more TFPI plasma level associated SNPs than expected by chance (global hypothesis test P-value = 0.046). We therefore stratified our genome-wide SNPs, prioritizing those in EC regulatory regions via stratified false discovery rate (sFDR) control, and reranked the SNPs by q-value. The minimum q-value was 0.27, and the top-ranked SNPs did not show association evidence in the MARTHA replication sample of 1,033 unrelated VTE cases. Although this study did not result in new loci for TFPI, our work lays out a strategy to utilize epigenomic data in prioritization schemes for future GWAS studies.

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“…While it is possible that it is a false positive, it could also have a population specific effect or an interaction with environmental factor(s). Interestingly, the expression of TFPI (Tissue Factor Pathway Inhibitor) has been linked to risk of thrombosis and heart disease previously (52) and a coding SNP in this region (rs7586970 or TFPI N221S within 500 KB) has been shown to be associated with total plasma TFPI levels (53). The unweighted and weighted pvalues for the crossover SNPs along with the association results from some independent studies are summarized in Table 2.…”

Section: Gwas Of Coronary Artery Disease (Cad): Summary Data On Coronmentioning

confidence: 99%

A Regression-based Framework for Scalable Pathway-guided Search in Genome-wide Association Studies

Biswas

Pal

Bhattacharjee

2017

Preprint

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Traditional unbiased genome-wide association studies (GWAS) have successfully identified thousands of loci associated with various complex diseases but there is evidence to suggest that many variants were missed at stringent genome-wide thresholds. Fortunately, there is a rapidly increasing amount of prior knowledge in publicly available genomic datasets and biological databases that can be harnessed to enhance the power of discovering SNPs/Genes from existing or new GWAS datasets. For most diseases, many of the identified loci tend to cluster into a few specific biological pathways/networks. From the point of view of disease etiology, such clustering is generally to be expected. This phenomenon can be exploited to conduct a more powerful genome-wide scan that is tailored to identify loci that are interconnected in pathways. We propose a scalable regression-based analytical framework to enable such a pathway-guided GWAS and demonstrate that it provides significant gains in power to detect disease associated SNPs. Our method requires two inputs, namely a) genome-wide summary level data (e.g., SNP p-values) and b) a grouping of genes into biologically meaningful categories (e.g., a database of pathways). It automatically adjusts the input p-values by incorporating the knowledge derived adaptively from the data and the pathways specified. The method involves a regularized logistic regression analysis to derive priors of each SNP and then re-weights the p-values of SNPs so as to maximize overall power of making discoveries. It increases the power to discover SNPs co-clustering into some of these pathways, while maintaining the global type-1 error (FWER) at the desired level. We used whole-genome simulations and summary data from real GWA studies of psoriasis, SLE, coronary artery disease and type-2 diabetes to illustrate the power improvement achieved by pathway-guided search. Our pipeline implemented as an R package can flexibly handle large number of prior annotations possibly derived from multiple databases.peer-reviewed)

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Genetic determinants of tissue factor pathway inhibitor plasma levels

Cited by 12 publications

References 70 publications

A low balance between microparticles expressing tissue factor pathway inhibitor and tissue factor is associated with thrombosis in Behçet’s Syndrome

A low balance between microparticles expressing tissue factor pathway inhibitor and tissue factor is associated with thrombosis in Behçet’s Syndrome

Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels

A Regression-based Framework for Scalable Pathway-guided Search in Genome-wide Association Studies

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