Identification of a Whole Blood Signature for Venous Thromboembolism

Venous thromboembolism (VTE), comprised of deep vein thrombosis and pulmonary embolism, is a common health problem both in the United States and worldwide, with significant associated morbidity and mortality. Despite multiple known genetic and situational risk factors, an estimated 30% of all events remain classified as idiopathic, demonstrating a significant knowledge gap in the pathophysiology VTE. While platelets are well established as an essential contributor to thrombus formation and there has been recent interest in the role of neutrophil extracellular traps, specific cell types and pathways involved in the pathogenesis of VTE remain uncertain. In this study, our primary aims were to define a unique transcriptional signature for VTE and to identify the types of cells and specific pathways involved in development of VTE. Whole blood was collected in PAX gene tubes and RNA sequencing for coding mRNA was performed in an unbiased manner in 201 patients with prevalent VTE as well as 43 healthy controls. We used a bioinformatics approach to develop a unique signature for VTE by identifying differentially expressed genes, developing cell-type modules, and ascertaining pathways driving differentially expressed transcripts. We performed additional analyses on subgroups of patients with idiopathic VTE, patients with incident VTE, and VTE patients matched to healthy controls by age and sex. We went on to use machine learning methods to learn models that best differentiate VTE patients from healthy controls and validated it on a left out test set within our VTE population. Genes specific to neutrophils, erythrocytes, and platelets, in that order, were most significantly upregulated in patients with VTE compared to healthy controls. Genes related to T-cells were downregulated. Pathway analysis revealed upregulated neutrophil activation and degranulation, erythrocyte differentiation and homeostasis, and platelet degranulation. A gene signature of 217 transcripts was outstanding at differentiating patients with VTE versus healthy controls (AUC 0.94). Following adjustment for age, sex, and race/ethnicity our genetic signature remained significantly robust at differentiating patients with VTE versus controls (AUC 0.83). Our expression signature remained stable across patients with idiopathic VTE (AUC 0.93), and in patients who went on to develop future VTE events (AUC 0.95). In summary, we have demonstrated a whole blood transcriptional signature for prevalent and i