Unsupervised clustering of venous thromboembolism patients by clinical features at presentation identifies novel endotypes that improve prognostic stratification

Abstract

Background: Individuals with acute venous thromboembolism (VTE) constitute a heterogeneous group of patients with diverse clinical characteristics and outcome.

Objectives: To identify endotypes of individuals with acute VTE based on clinical characteristics at presentation through unsupervised cluster analysis and to evaluate their molecular proteomic profile and clinical outcome.

Methods: Data from 591 individuals from the Genotyping and Molecular phenotyping of Venous thromboembolism (GMP-VTE) project were explored. Hierarchical clustering was applied to 58 variables to define VTE endotypes. Clinical characteristics, three-year incidence of thromboembolic events or death, and acute-phase plasma proteomics were assessed.

Results: Four endotypes were identified, exhibiting different patterns of clinical characteristics and clinical course. Endotype 1 (n = 300), comprising older individuals with comorbidities, had the highest incidence of thromboembolic events or death (HR [95 % CI]: 3.76 [1.96-7.19]), followed by endotype 4 (n = 127) (HR [95 % CI]: 2.55 [1.26-5.16]), characterised by men with history of VTE and provoking risk factors, and endotype 3 (n = 57) (HR [95 % CI]: 1.57 [0.63-3.87]), composed of young women with provoking risk factors, vs. reference endotype 2 (n = 107). The reference endotype was constituted by individuals diagnosed with PE without comorbidities, who had the lowest incidence of the investigated endpoint. Differentially expressed proteins associated with the endotypes were related to distinct biological processes, supporting differences in molecular pathophysiology. The endotypes had superior prognostic ability compared to existing risk stratifications such as provoked vs unprovoked VTE and D-dimer levels.

Conclusion: Four endotypes of VTE were identified by unsupervised phenotype-based clustering that diverge in clinical outcome and plasmatic protein signature. This approach might support the future development of individualized treatment in VTE.

Keywords: Cluster analysis; Coagulation; Proteomics; Recurrence; Venous thrombosis.