A Multitrait Genetic Study of Hemostatic Factors and Hemorrhagic Transformation after Stroke Treatment

BACKGROUND: Thrombolytic recombinant tissue plasminogen activator (r-tPA) treatment is the only pharmacologic intervention available in the ischemic stroke acute phase. This treatment is associated with an increased risk of intracerebral hemorrhages, known as hemorrhagic transformations (HTs), which worsen the patient\u27s prognosis. OBJECTIVES: to investigate the association between genetically determined natural hemostatic factors\u27 levels and increased risk of HT after r-tPA treatment. METHODS: Using data from genome-wide association studies on the risk of HT after r-tPA treatment and data on 7 hemostatic factors (factor [F]VII, FVIII, von Willebrand factor [VWF], FXI, fibrinogen, plasminogen activator inhibitor-1, and tissue plasminogen activator), we performed local and global genetic correlation estimation multitrait analyses and colocalization and 2-sample Mendelian randomization analyses between hemostatic factors and HT. RESULTS: Local correlations identified a genomic region on chromosome 16 with shared covariance: fibrinogen-HT, P = 2.45 × 10 CONCLUSION: We identified 4 shared loci between hemostatic factors and HT after r-tPA treatment, suggesting common regulatory mechanisms between fibrinogen and VWF levels and HT. Further research to determine a possible mediating effect of fibrinogen on HT risk is needed

Genetic analysis of the anticoagulant proteins Antithrombin, Protein C and Protein S

Curs 2019-2020Cardiovascular diseases (CVDs) are the number one case of dead globally according to the World Health Organisation (WHO) ahead of cancer and respiratory diseases. Most of CVDs are caused by a combination of genetic, environmental and lifestyle factors and therefore are considered complex diseases. Alterations in the coagulation cascade are strongly related to these diseases and can cause severe problems in the circulatory system that might lead to death, through the formation of thrombus that prevent blood from flowing. We focused this study on the identification of genetic markers in general population that are associated with some proteins of the coagulation cascade. To do this, in association with the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, we meta-analysed summary statistics from multiple Genome Wide Association Studies (GWAS). GWAS test for association in millions of genetic positions against a phenotypic trait in thousands of individuals. In our case, three of the most important anticoagulant blood proteins were measured, Antithrombin (AT), Protein C (PC) and Protein S (PS). These three proteins have been studied before in smaller samples sizes. Our meta-analysis involved more participants from different ancestries, increasing the power from previous studies. AT was analysed in 27,783 individuals (25,095 from European (EU) ancestry and 2,688 from African-American (AA) ancestry), PC in 19,285 individuals (16,597 from EU and 2,688 from AA) and PS was divided in two smaller phenotypes, PST and PSF, analysed in 6,257 and 4,006 individuals, respectively. Multiple independent loci that have been identified previously were detected in our meta-analyses, including the coding genes for our three proteins, SERPINC1 (AT), PROC (PC) and PROS1 (PS), but we identified some novel associations, too. For AT, a genomic region containing SNX17 and GCKR genes in EU population (best SNP rs4665972, trans-ethnic p-value = 4.41·10-16, EU p-value = 1.26·10-16), BAZ1B also in EU population (best SNP rs13244268, trans-ethnic p-value = 4.006·10-9, EU p-value = 6.00·10-9) and another genomic region containing TXNL4B and HP in AA population (best SNP rs5471, trans-ethnic p-value = 4.374·10-26, AA p-value = 7.76·10-25) were novel associations; for PC, most of the identified variants were already known or in high Linkage Disequilibrium with known variants, but we identified a novel variant in EU population, rs150070344, at SPG11 gene with a p-value of 4.07·10-8. For PS, we found a novel association at ORM1 gene for both phenotypes, PST and PSF (best SNP rs150611042, PST p-value = 1.03·10-15, PSF p-value = 1.16·10-19). In conclusion, the use of larger sample sizes has allowed the detection of new associated variants. Furthermore, we have been able to observe the already known differences that exist between the linkage disequilibrium blocks of two different populations, in our case EU and AA. The application of conditional analysis on these results will allow to know more details about the causal variants. This study has been done in the Genomics of Complex Diseases Group, led by José Manuel Soria, within the Research Institute of Hospital Sant Pau, and using international genetic data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.Director/a: Serrat Jurado, Josep Mari

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Background Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 x 10(-9) obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits

Arterioscler Thromb Vasc Biol

BACKGROUND: Antithrombin, PC (protein C), and PS (protein S) are circulating natural anticoagulant proteins that regulate hemostasis and of which partial deficiencies are causes of venous thromboembolism. Previous genetic association studies involving antithrombin, PC, and PS were limited by modest sample sizes or by being restricted to candidate genes. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, we meta-analyzed across ancestries the results from 10 genome-wide association studies of plasma levels of antithrombin, PC, PS free, and PS total. METHODS: Study participants were of European and African ancestries, and genotype data were imputed to TOPMed, a dense multiancestry reference panel. Each of the 10 studies conducted a genome-wide association studies for each phenotype and summary results were meta-analyzed, stratified by ancestry. Analysis of AT included 25 243 European ancestry and 2688 African ancestry participants, PC analysis included 16 597 European ancestry and 2688 African ancestry participants, PSF and PST analysis included 4113 and 6409 European ancestry participants. We also conducted transcriptome-wide association analyses and multiphenotype analysis to discover additional associations. Novel genome-wide association studies and transcriptome-wide association analyses findings were validated by in vitro functional experiments. Mendelian randomization was performed to assess the causal relationship between these proteins and cardiovascular outcomes. RESULTS: Genome-wide association studies meta-analyses identified 4 newly associated loci: 3 with antithrombin levels (GCKR, BAZ1B, and HP-TXNL4B) and 1 with PS levels (ORM1-ORM2). transcriptome-wide association analyses identified 3 newly associated genes: 1 with antithrombin level (FCGRT), 1 with PC (GOLM2), and 1 with PS (MYL7). In addition, we replicated 7 independent loci reported in previous studies. Functional experiments provided evidence for the involvement of GCKR, SNX17, and HP genes in antithrombin regulation. CONCLUSIONS: The use of larger sample sizes, diverse populations, and a denser imputation reference panel allowed the detection of 7 novel genomic loci associated with plasma antithrombin, PC, and PS levels

FGL1 as a modulator of plasma D-dimer levels: exome-wide marker analysis of plasma tPA, PAI-1 and D-dimer

BACKGROUND: Use of targeted exome-arrays with common, rare variants and functionally enriched variation has led to discovery of new genes contributing to population variation in risk factors. Plasminogen activator-inhibitor 1 (PAI-1), tissue plasminogen activator (tPA), and the plasma product D-dimer are important components of the fibrinolytic system. There have been few large-scale genome-wide or exome-wide studies of PAI-1, tPA and D-dimer. OBJECTIVES: We sought to discover new genetic loci contributing to variation in these traits using an exome-array approach. METHODS: Cohort level analyses and fixed effects meta-analyses of PAI-1 (n = 15,603), tPA (n = 6,876) and D-dimer (n = 19,306) from 12 cohorts of European ancestry with diverse study design were conducted, including single-variant analyses and gene-based burden testing. RESULTS: Five variants located in NME7, FGL1 and the fibrinogen locus, all associated with D-dimer levels, achieved genome-wide significance (P < 5 × 10(-8) ). Replication was sought for these 5 variants, as well as 45 well-imputed variants with P < 1 × 10(-4) in the discovery using an independent cohort. Replication was observed for 3 out of the 5 significant associations, including a novel and uncommon (0.013 allele frequency) coding variant p.Trp256Leu in FGL1 (Fibrinogen-Like-1) with increased plasma D-dimer levels. Additionally, a candidate-gene approach revealed a suggestive association for a coding variant (rs143202684-C) in SERPINB2, and suggestive associations with consistent effect in the replication analysis include an intronic variant (rs11057830-A) in SCARB1 associated with increased D-dimer levels. CONCLUSION: This work provides new evidence for a role of FGL1 in hemostasis

Multi‐phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

BackgroundMulti-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes.ObjectivesTo discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events.MethodsSummary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85&nbsp;×&nbsp;10-9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n&nbsp;=&nbsp;27).ResultsAcross the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes.ConclusionsThe discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits

A genetic association study of circulating coagulation Factor VIII and von Willebrand Factor levels

Coagulation Factor VIII (FVIII) and its carrier protein von Willebrand factor (VWF) are critical to coagulation and platelet aggregation. We leveraged whole genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program along with TOPMed-based imputation of genotypes in additional samples to identify genetic associations with circulating FVIII and VWF levels in a single variant meta-analysis including up to 45,289 participants. Gene-based aggregate tests were implemented in TOPMed. We identified three candidate causal genes and tested their functional effect on FVIII release from human liver endothelial cells (HLECs) and VWF release from human umbilical vein endothelial cells (HUVECs). Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P&lt;5×10-9) at seven new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and one for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multi-phenotype analysis of FVIII and VWF identified another three new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, while silencing of B3GNT2, CD36, and PDIA3 decreased release of VWF by HVECs. Mendelian randomization supports causal association of higher FVIII and VWF with increased risk of thrombotic outcomes. Seven new loci were identified for FVIII and one for VWF, with evidence supporting causal associations of FVIII and VWF with thrombotic outcomes. B3GNT2, CD36, and PDIA3 modulate the release of FVIII and/or VWF in vitro

Multi-phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Background: Multi-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes. Objectives: To discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events. Methods: Summary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10−9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27). Results: Across the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes. Conclusions: The discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits