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]), wereThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Genome-wide association studies (GWAS) have identified dozens of loci underlying the variability of plasma levels for individual hemostatic traits. [1][2][3][4][5][6][7][8] Further, GWAS for venous thromboembolism (VTE), 9,10 coronary artery disease (CAD) [11][12][13] and ischemic stroke (IS), 11,14 have discovered 34, 169, and 20 genetic risk loci associated with these cardiovascular (CV) events, respectively.Results from GWAS indicate that several of these hemostatic traits are genetically correlated with each other, sharing genetic loci that regulate their plasma levels. 1,[4][5][6][7][8] There are also shared genetic loci between hemostatic traits and CV events, again suggesting common regulators and possibly a causal pathway between the hemostatic trait and the CV event. 4,[7][8][9]12,14 The common regulatory loci between traits-even if the traits are not causally associated with each other-can be used to advance discovery of novel genetic loci common to the traits. This discovery can be accomplished with multiphenotype methods that incorporate summary statistics from several GWAS, increasing the statistical power to detect loci affecting two or more phenotypes by increasing the effective sample size. [15][16][17] In the present study, we used summary statistics of published GWAS from 7 hemostatic traits (FVII, FVIII, VWF, FXI, fibrinogen, PAI-1, tPA), and 3 CV events (VTE, CAD, IS) to calculate their genetic correlations and to conduct multi-phenotype meta-analyses to detect new genetic loci not previously known to be associated with these phenotypes.

Objective: Antithrombin, protein C (PC) and protein S (PS) 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 (GWAS) of plasma levels of antithrombin, PC, PS free and PS total. Approach and Results: Study participants were of European and African ancestries and genotype data were imputed to TOPMed, a dense multi-ancestry reference panel. Each of 10 studies conducted a GWAS for each phenotype and summary results were meta-analyzed, stratified by ancestry. We also conducted transcriptome-wide association analyses and multi-phenotype analysis to discover additional associations. Novel GWAS findings were validated by in vitro functional experiments. Mendelian randomization was performed to assess the causal relationship between these proteins and cardiovascular outcomes. GWAS meta-analyses identified 4 newly associated loci: 3 with antithrombin levels (GCKR, BAZ1B, and HP-TXNL4B) and 1 with PS levels (ORM1-ORM2). TWAS 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. Conclusion: 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.

Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three (SERPINA1, ZFP36L2, and TLR10) signals contain predicted deleterious missense variants. Two loci, SOCS3 and HPN, each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits (FGG;FGB;FGA), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.

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.

Major depessive disorder (MDD), bipolar disorder (BD) and schizophrenia (SCZ) are accompanied by an increased risk of cardiovascular diseases including venous thromboembolism (VTE). Reasons for this are complex, and include obesity, smoking and use of hormone and psychotropic medications. Genetic studies increasingly provide evidence of shared genetic risk of psychiatric and cardiometabolic illness. This study aimed to determine whether genetic predisposition to MDD, BD or SCZ was associated with an increased risk of VTE. Genetic correlations using the largest genome-wide genetic meta-analyses summary statistics for MDD, BD and SCZ (Psychiatric Genetics Consortium) and a recent genome-wide genetic meta-analysis of VTE (INVENT consortium) demonstrated a positive association between VTE and MDD but not BD or SCZ. The same summary statistics were used to construct polygenic risk scores for MDD, BD and SCZ in UK Biobank participants of self-reported white British ancestry. These were assessed for impact on self-reported VTE risk (10786 cases, 285124 controls), using logistic regression, in sex-specific and sex-combined analyses. We identified significant positive associations between polygenic risk for MDD and risk of VTE in men, women and sex-combined analyses, independent of known risk factors. Secondary analyses demonstrated that this association was not driven by those with lifetime experience of mental illness. Meta-analyses of individual data from six additional independent cohorts replicated the sex-combined association. This report provides evidence for shared biological mechanisms leading to MDD and VTE, and suggests that, in the absence of genetic data, family history for MDD might be considered when assessing risk of VTE.