BACKGROUND:Idiopathic venous thromboembolism (VTE) occurs in the absence of provoking factors, limiting the efficacy of current risk stratification. In parallel, the lack of integration between transcriptomic data and established risk factors prevents the identification of individuals with a high baseline predisposition. OBJECTIVES:We aimed to improve risk stratification of idiopathic VTE beyond traditional clinical models by developing a similarity-based risk score that integrates transcriptomic profiles with conventional risk factors. METHODS:We analyzed 790 individuals from the Genetic Analysis of Idiopathic Thrombophilia 2 familial study, including 70 participants with prior idiopathic VTE. Whole-blood RNA sequencing, known genetic variants, and clinical variables were integrated using supervised machine learning models (Elastic Net and XGBoost). Predictive gene expression features were evaluated through enrichment analyses. A unified similarity score combining both models was developed to identify control individuals who shared transcriptomic and clinical profiles with VTE cases. RESULTS:In both models, von Willebrand factor abundance was the strongest predictor of VTE, followed by clinical factors (body mass index, ABO alleles, and age) and expression of 494 genes, including STS, FAM13A, GPRIN1, FLVCR2, FAM177B, and several long noncoding RNAs not previously linked to thrombosis. Known thrombosis-associated genes such as UQCRC2 and PRKRA were also identified. Significant enrichment was observed for cardiomyopathic Kyoto Encyclopedia of Genes and Genomes pathways and renal Human Protein Atlas terms. Similarity-based risk score construction improved classification, with 74% of VTE cases and 23% of controls assigned to the risk zone. CONCLUSION:Multivariate integration via machine learning enhances VTE risk stratification, identifying novel transcriptomic signatures and lncRNA biomarkers that offer new strategies for VTE personalized prevention.

BACKGROUND:Venous thromboembolism (VTE) includes deep vein thrombosis (DVT) and pulmonary embolism (PE), the latter of which often originates from DVT and can be fatal. OBJECTIVES:The aim of this study was to identify causal genetic factors that alter risk of PE among those with a presumed DVT. METHODS:Using a case-only design of VTE, we conducted meta-analyses of genome-wide association studies (GWASs) in the International Network Against Venous Thrombosis Consortium. Among participants diagnosed with VTE, each study identified those who had a clinically reported PE, with or without a clinically reported DVT; those remaining had isolated DVT. Logistic regression models (PE as outcome compared with isolated DVT) were used for variant discovery and replication analyses. A polygenic risk score was created from the GWAS findings. Transcriptome-wide association study analyses were conducted using the GWAS discovery estimates. RESULTS:Our discovery and replication analyses included 126 316 individuals with a VTE across 29 studies: 54 389 who had a PE and the remaining 71 927 who had an isolated DVT. Five variants reached genome-wide significance (P < 5 × 10-8) in discovery, 4 of which replicated: F5 rs6025 (factor V Leiden), odds ratio (OR) 0.66; FGG rs2066864, OR 1.08; F11 rs4253417, OR 1.07; and SLC12A2-DT rs3749748, OR 0.92. Each 1 SD increase in the polygenic risk score was associated with risk (OR: 1.05; 95% CI: 1.003-1.094). Transcriptome-wide association study analysis identified genetic associations with FGG, SLC12A2-DT, and CDHR4 transcripts. CONCLUSION:Although the overall risk for VTE is strongly heritable, our findings support the hypothesis that PE in the setting of a presumed DVT is regulated by genetics, although the overall effect appears modest.

Coagulation factor V (FV) is a key protein in maintaining the hemostatic balance, with abnormal plasma levels associated with both thrombotic and hemorrhagic conditions. We propose a comprehensive bioinformatic analysis integrating large-scale proteogenomics and transcriptomic data from original and public data sets. We identify a biological fingerprint of 26 new proteins and loci involved in the regulation of plasma FV levels. Furthermore, the messenger RNA expression levels of 10 of these components demonstrate strong correlation in the liver. In addition, we provide experimental evidence for the involvement of one of the newly identified players (CLEC4M) in the clearance of FV. This work opens new avenues for a better understanding of the physiological processes involved in thrombotic and bleeding disorders.

Background Elevated coagulation factor (F) IX activity is associated with an increased risk of cardiovascular diseases, including venous thromboembolism. However, a genome-wide association study for FIX activity remains to be performed. Objectives We aimed to identify genetic loci associated with FIX activity. Methods We conducted a meta-analysis of genome-wide association studies across 2 population-based cohorts (N = 9628), followed by conditional and joint analyses and replication analyses (N = 1894). Using the identified variants, we explored genetic associations between FIX activity and both hemostatic and metabolic phenotypes and conducted Mendelian randomization analysis to investigate potential causal effects on cardiovascular diseases. Results We identified 10 genomic loci associated with FIX activity: AHCTF1, GCKR, KNG, HRG, HRG-AS1, F12, ABO, and F9, of which F12 and ABO were replicated at a Bonferroni-corrected significance, and GCKR and F9 reached nominal significance. Structural modeling of the F9 missense variant revealed its proximity to a critical cleavage site, providing mechanistic insight into FIX regulation. A polygenic score based on 10 genomic loci was associated with hemostatic phenotypes (activated partial thromboplastin time and FVIII, FXI, and FXII activity) and metabolic phenotypes (triglycerides, γ-glutamyl transferase, and low-density lipoprotein cholesterol levels). Mendelian randomization analyses suggested potential detrimental effects of FIX activity on venous thromboembolism. Conclusion Our findings enhance understanding of biological mechanisms regulating FIX activity and provide evidence for a causal role of FIX activity in the etiology of these cardiovascular conditions.

PurposeWe developed a predictive model to assess the risk of major bleeding (MB) within 6 months of primary venous thromboembolism (VTE) in cancer patients receiving anticoagulant treatment. We also sought to describe the prevalence and incidence of VTE in cancer patients, and to describe clinical characteristics at baseline and bleeding events during follow-up in patients receiving anticoagulants.MethodsThis observational, retrospective, and multicenter study used natural language processing and machine learning (ML), to analyze unstructured clinical data from electronic health records from nine Spanish hospitals between 2014 and 2018. All adult cancer patients with VTE receiving anticoagulants were included. Both clinically- and ML-driven feature selection was performed to identify MB predictors. Logistic regression (LR), decision tree (DT), and random forest (RF) algorithms were used to train predictive models, which were validated in a hold-out dataset and compared to the previously developed CAT-BLEED score.ResultsOf the 2,893,108 cancer patients screened, in-hospital VTE prevalence was 5.8% and the annual incidence ranged from 2.7 to 3.9%. We identified 21,227 patients with active cancer and VTE receiving anticoagulants (53.9% men, median age of 70 years). MB events after VTE diagnosis occurred in 10.9% of patients within the first six months. MB predictors included: hemoglobin, metastasis, age, platelets, leukocytes, and serum creatinine. The LR, DT, and RF models had AUC-ROC (95% confidence interval) values of 0.60 (0.55, 0.65), 0.60 (0.55, 0.65), and 0.61 (0.56, 0.66), respectively. These models outperformed the CAT-BLEED score with values of 0.53 (0.48, 0.59).ConclusionsOur study shows encouraging results in identifying anticoagulated patients with cancer-associated VTE who are at high risk of MB.

Background Association between global platelet function and the risk of venous thromboembolic disease (VTE) has been proposed, though the mechanisms do not involve increased platelet aggregation. However, platelet adhesiveness has not been systematically explored in VTE patients. Objectives To evaluate platelet adhesive functions in VTE patients. Methods Platelet adhesion was evaluated by using whole blood samples from VTE patients, selected based on short closure times on the PFA-100 (n = 54), and matched healthy individuals (n = 57) in: (i) the PFA-100, (ii) a cone plate analyzer (CPA), on a plastic surface, (iii) microfluidic devices, with two- and three-dimensional evaluation, and (iv) membrane glycoprotein analysis. Intraplatelet signaling was evaluated in isolated collagen type I (Col-I) activated platelets and platelets adhered on Col-I or von Willebrand factor (VWF) coated coverslips under flow. VWF antigen and ADAMTS-13 activity were measured in plasma samples. Results PFA-100 closure times remained significantly shorter in patients. The CPA test showed a significant increase in the platelet aggregates size when using blood from VTE patients. Platelet adhesion on Col-I revealed a higher area covered by platelets and increased aggregate volume when exposed to samples from VTE patients. Protein P-ZAP70/SYK72 showed a phosphorylation level significantly increased in patients' platelets. Plasma VWF was significantly elevated in VTE patients. Conclusions Platelets from VTE patients exhibit a proadhesive phenotype under flow conditions potentially related to the shortened occlusion times with the PFA-100. This enhanced adhesiveness may be explained by higher intraplatelet ZAP70/SYK72 phosphorylation and increased plasma VWF in patients. Therefore, primary hemostasis plays a significant role in the pathophysiology of VTE.

ABSTRACT: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 3 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. Mendelian randomization was also performed to provide evidence for causal associations of FVIII and VWF with thrombotic outcomes. We identified associations (P < 5 × 10-9) at 7 new loci for FVIII (ST3GAL4, CLEC4M, B3GNT2, ASGR1, F12, KNG1, and TREM1/NCR2) and 1 for VWF (B3GNT2). VWF, ABO, and STAB2 were associated with FVIII and VWF in gene-based analyses. Multiphenotype analysis of FVIII and VWF identified another 3 new loci, including PDIA3. Silencing of B3GNT2 and the previously reported CD36 gene decreased release of FVIII by HLECs, whereas 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 1 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.

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 percentage points higher in African populations. Three signals (SERPINA1, ZFP36L2, and TLR10) contain predicted deleterious missense variants. Two loci, SOCS3 and HPN, each harbor two conditionally distinct, non-coding variants. The gene region encoding the fibrinogen protein chain subunits (FGG;FGB;FGA), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common in African ancestry populations but extremely rare in Europeans (MAFAFR=0.180; MAFEUR=0.008). 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.

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations ( BAZ2B and DDIAS ). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP . Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

Background Factor V (FV) is a key molecular player in the coagulation cascade. FV plasma levels have been associated with several human diseases, including thrombosis, bleeding, and diabetic complications. So far, 2 genes have been robustly found through genome‐wide association analyses to contribute to the inter‐individual variability of plasma FV levels: structural F5 gene and PLXDC2. Methods and Results The authors used the underestimated Brown‐Forsythe methodology implemented in the QuickTest software to search for non‐additive genetic effects that could contribute to the inter‐individual variability of FV plasma activity. QUICKTEST was applied to 4 independent genome‐wide association studies studies (LURIC [Ludwigshafen RIsk and Cardiovascular Health Study], MARTHA [Marseille Thrombosis Association], MEGA [Multiple Environmental and Genetic Assessment], and RETROVE [Riesgo de Enfermedad Tromboembolica Venosa]) totaling 4505 participants of European ancestry with measured FV plasma levels. Results obtained in the 4 cohorts were meta‐analyzed using a fixed‐effect model. Additional analyses involved exploring haplotype and gene×gene interactions in downstream investigations. A genome‐wide significant signal at the PSKH2 locus on chr8q21.3 with lead variant rs75463553 with no evidence for heterogeneity across cohorts was observed ( P =0.518). Although rs75463553 did not show an association with mean FV levels ( P =0.49), it demonstrated a robust significant ( P =3.38x10 −9 ) association with the variance of FV plasma levels. Further analyses confirmed the reported association of PSKH2 with neutrophil biology and revealed that rs75463553 likely interacts with two loci, GRIN2A and POM121L12 , known for their involvement in smoking biology. Conclusions This comprehensive approach identifies the role of PSKH2 as a novel molecular player in the genetic regulation of FV, shedding light on the contribution of neutrophils to FV biology.

Venous thromboembolism (VTE) is a common disease with high heritability. However, only a small portion of the genetic variance of VTE can be explained by known genetic risk factors. Neutrophil extracellular traps (NETs) have been associated with prothrombotic activity. Therefore, the genetic basis of NETs could reveal novel risk factors for VTE. A recent genome-wide association study of plasma cell-free DNA (cfDNA) levels in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT-2) Project showed a significant associated locus near ORM1. We aimed to further explore this candidate region by next-generation sequencing, copy number variation (CNV) quantification, and expression analysis using an extreme phenotype sampling design involving 80 individuals from the GAIT-2 Project. The RETROVE study with 400 VTE cases and 400 controls was used to replicate the results. A total of 105 genetic variants and a multiallelic CNV (mCNV) spanning ORM1 were identified in GAIT-2. Of these, 17 independent common variants, a region of 22 rare variants, and the mCNV were significantly associated with cfDNA levels. In addition, eight of these common variants and the mCNV influenced ORM1 expression. The association of the mCNV and cfDNA levels was replicated in RETROVE (p-value = 1.19 × 10-6). Additional associations between the mCNV and thrombin generation parameters were identified. Our results reveal that increased mCNV dosages in ORM1 decreased gene expression and upregulated cfDNA levels. Therefore, the mCNV in ORM1 appears to be a novel marker for cfDNA levels, which could contribute to VTE risk.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with an increased risk of cardiovascular diseases, including venous thromboembolism (VTE). The reasons for this are complex and include obesity, smoking, and use of hormones and psychotropic medications. Genetic studies have increasingly provided evidence of the shared genetic risk of psychiatric and cardiometabolic illnesses. This study aimed to determine whether a genetic predisposition to MDD, BD, or SCZ is associated with an increased risk of VTE. Genetic correlations using the largest genomewide 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 (10 786 cases, 285 124 controls), using logistic regression, in sex-specific and sex-combined analyses. We identified significant positive associations between polygenic risk for MDD and the risk of VTE in men, women, and sex-combined analyses, independent of the 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 6 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, a family history of MDD might be considered when assessing the risk of VTE.

AIMS:Direct oral anticoagulants (DOAC) are progressively replacing vitamin K antagonists in the prevention of thromboembolism in patients with atrial fibrillation. However, their real-world clinical outcomes appear to be contradictory, with some studies reporting fewer and others reporting higher complications than the pivotal randomized controlled trials. We present the results of a clinical model for the management of DOACs in real clinical practice and provide a review of the literature.METHODS:The MACACOD project is an ongoing, observational, prospective, single-center study with unselected patients that focuses on rigorous DOAC selection, an educational visit, laboratory measurements, and strict follow-up.RESULTS:A total of 1,259 patients were included. The composite incidence of major complications was 4.93% py in the whole cohort vs 4.49% py in the edoxaban cohort. The rate of all-cause mortality was 6.11% py for all DOACs vs 5.12% py for edoxaban. There weren't differences across sex or between Edoxaban reduced or standard doses. However, there were differences across ages, with a higher incidence of major bleeding complications in patients >85 years (5.13% py vs 1.69% py in <75 years).CONCLUSIONS:We observed an incidence of serious complications of 4.93% py, in which severe bleeding predominated (3.65% py). Considering our results, more specialized attention seems necessary to reduce the incidence of severe complications and also a more critical view of the literature. Considering our results, and our indirect comparison with many real-world studies, more specialized attention seems necessary to reduce the incidence of severe complications in AF patients receiving DOACs.

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 antithrombin 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.

Background and Aims: Increased serum levels of homocysteine (Hcy) are a risk factor for cardiovascular diseases, including atherosclerosis. However, the precise mechanisms by which Hcy contributes to this condition remain elusive. microRNAs influence the expression of several genes related to atherosclerosis. Interestingly, miR-30d-5p was found to be up-regulated in the plasma of patients with hyperhomocysteinemia (HHcy) and venous thrombosis. Moreover, TIMP3 gene was a predicted target for miR-30d-5p.

The platelet antibodies that cause pseudothrombocytopenia (PTCP) act only in vitro and do not produce clinical bleeding. Most studies on PTCP have focused on improving differential diagnosis with true thrombocytopenia but studies on the characteristics of patients with PTCP are limited. In this study, we aimed to evaluate the clinical and biological characteristics of 192 patients with PTCP. In addition to general variables, we evaluated automated and microscopic platelet counts, platelet clumps, platelet diameters, immature platelet fraction (IPF), and platelet antibodies. Adult women accounted for the largest subgroup of patients (n=82; 42.7%) and 67 patients (34.9%) were grouped into families. Forty-four patients (22.9%) had one or more associated autoimmune disorders (ADs); 39 relatives of these patients (19.8%) had ADs and 45 relatives (23.4%) had immune thrombocytopenia (ITP) or unspecified thrombocytopenia. Platelet cryptantibodies and/or autoantibodies were positive in 56 patients (30.1%). Most patients (n=169; 80%) had automated platelet counts >80×109/L. In all patients, microscopic platelet counts were ≥150×109/L. The platelet clump index (% increase in microscopic platelet count compared to automatic count) ranged from 30 to >7000%. Platelet diameters and IPF parameters were significantly greater in the PTCP versus healthy controls (p<0.001). A total of 17 patients (8.8%) had had previous ITP or the PTCP evolved into ITP. Our data suggest that PTCP should be considered a situation of autoimmunity; the assessment of platelet clumps has a high diagnostic value; the close association between ITP and PTCP suggests that these conditions could be different phases of the same process.

BACKGROUND:Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. METHODS:We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. RESULTS:In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. CONCLUSIONS:Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

ABSTRACT Venous thromboembolism (VTE) is a complex disease with environmental and genetic determinants. We present new cross-ancestry meta-analyzed genome-wide association study (GWAS) results from 30 studies, with replication of novel loci and their characterization through in silico genomic interrogations. In our initial genetic discovery effort that included 55,330 participants with VTE (47,822 European, 6,320 African, and 1,188 Hispanic ancestry), we identified 48 novel associations of which 34 replicated after correction for multiple testing. In our combined discovery-replication analysis (81,669 VTE participants) and ancestry-stratified meta-analyses (European, African and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein QTL Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 novel GWAS loci provided insights to biological pathways contributing to VTE, indicating that some loci may contribute to VTE through well-characterized coagulation pathways while others provide new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. In summary, these findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of antithrombosis treatments with reduced risk of bleeds.

e18744 Background: Evidence regarding the clinical predictors of bleeding risk in patients with cancer and venous thromboembolism (VTE) is lacking. Our aim was to develop a predictive model to assess the risk of major bleeding (MB) in anticoagulant-treated patients with active cancer during the first 6 months following VTE diagnosis. Methods: Observational, retrospective, and multicenter study based on the secondary analysis of unstructured clinical data in electronic health records (EHRs). Using the EHRead technology, based on Natural Language Processing (NLP) and machine learning (ML), data were collected from EHRs from 9 Spanish hospitals between 2014 and 2018. The study population comprised all adult cancer patients with a diagnosis of VTE under anticoagulant treatment and no history of MB. This population was downsampled to prevent bias and class imbalance. A total of 94 patient characteristics were explored, and Random Forest (RF) feature selection was performed to identify the most relevant predictors. Multiple algorithms were used to train different prediction models, which were subsequently validated in a hold-out dataset. The model with the best performance metrics (i.e., ROC-AUC) was selected as the final model. Results: Among a source population of 2,893,208 patients, 21,227 anticoagulant-treated patients with VTE and active cancer were identified from EHRs. Of these, 53.9% men, with a median age (Q1, Q3) of 70 (59,80) years. The median duration of follow up across all patients was 0.7 (0.11, 2.03) years. During the study period, estimated in-hospital prevalence of cancer-related VTE was 5.8 %. The most common type of VTE at baseline was deep vein thrombosis (68.2 % of patients), followed by pulmonary embolism (28.4%). The most frequent primary cancers were colorectal (10.1%) and lung cancer (8.5 %). Of all trained and validated models, the RF approach yielded the best performance, with a ROC-AUC = 0.7. The following predictors of MB were identified: hemoglobin levels, presence of metastasis, patient’s age, platelet count, leukocyte count, and serum creatinine levels. Conclusions: This is the first multicenter study to use NLP to extract the unstructured information from EHRs to develop a predictive model for MB in anticoagulated cancer patients with VTE. These results may improve the prevention and management of bleeding in these patients.