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Discovery of novel plasma biomarkers for future incident venous thromboembolism by untargeted synchronous precursor selection mass spectrometry proteomics
Author(s) -
Jensen S. B.,
Hindberg K.,
Solomon T.,
Smith E. N.,
Lapek J. D.,
Gonzalez D. J.,
Latysheva N.,
Frazer K. A.,
Brækkan S. K.,
Hansen J.B.
Publication year - 2018
Publication title -
journal of thrombosis and haemostasis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.947
H-Index - 178
eISSN - 1538-7836
pISSN - 1538-7933
DOI - 10.1111/jth.14220
Subject(s) - proteomics , mass spectrometry , venous thromboembolism , selection (genetic algorithm) , chemistry , computational biology , medicine , chromatography , computer science , biology , biochemistry , thrombosis , artificial intelligence , gene
Essentials Discovery of predictive biomarkers of venous thromboembolism (VTE) may aid risk stratification. A case‐control study where plasma was sampled before the occurrence of VTE was established. We generated untargeted plasma proteomic profiles of 200 individuals by use of mass spectrometry. Assessment of the biomarker potential of 501 proteins yielded 46 biomarker candidates.Abstract Background Prophylactic anticoagulant treatment may substantially reduce the incidence of venous thromboembolism ( VTE ) but entails considerable risk of severe bleeding. Identification of individuals at high risk of VTE through the use of predictive biomarkers is desirable in order to achieve a favorable benefit‐to‐harm ratio. Objective We aimed to identify predictive protein biomarker candidates of VTE . Methods We performed a case‐control study of 200 individuals that participated in the Tromsø Study, a population‐based cohort, where blood samples were collected before the VTE events occurred. Untargeted tandem mass tag‐synchronous precursor selection‐mass spectrometry ( TMT ‐ SPS ‐ MS 3)‐based proteomic profiling was used to study the plasma proteomes of each individual. Results Of the 501 proteins detected in a sufficient number of samples to allow multivariate analysis, 46 proteins were associated with VTE case–control status with P ‐values below the 0.05 significance threshold. The strongest predictive biomarker candidates, assessed by statistical significance, were transthyretin, vitamin K‐dependent protein Z and protein/nucleic acid deglycase DJ ‐1. Conclusions Our untargeted approach of plasma proteome profiling revealed novel predictive biomarker candidates of VTE and confirmed previously reported candidates, thereby providing conceptual support for the validity of the study. A larger nested case–control study will be conducted to validate our findings.