Deep vein thrombosis exhibits characteristic serum and vein wall metabolic phenotypes in the inferior vena cava ligation mouse model
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Deep vein thrombosis (DVT) is a major health problem, responsible for significant morbidity and mortality, and imposes a heavy economic burden to healthcare systems (1). Although most events resolve without complication through spontaneous lysis and recanalization, DVT can be complicated with life-threatening pulmonary embolism (2), while approximately one third of DVT patients develop post-thrombotic syndrome with swelling, pain, skin changes and/or venous ulceration (3).Treatment with anticoagulation prevents further thrombus extension, protects from pulmonary embolism and reduces the risk of chronic lower limb complications. Importantly, unnecessary treatment can result in bleeding. Therefore, accurate and reliable DVT diagnosis is essential. Currently, diagnosis relies on subjective clinical examination and ultrasound imaging (4). A number of biological markers have been investigated with variable results. D-dimer, the most widely used biomarker, is sensitive but lacks specificity (5, 6). Ongoing research efforts target the utility of alternative blood diagnostic biomarkers able to accurately diagnose DVT, guide length and type of treatment, and potentially identify patients who may benefit from more aggressive therapies than standard anticoagulation. New molecular technologies and methods have entered the scientific arena, offering the opportunity to revisit this important clinical need. Metabolic profiling has emerged as a new approach to investigate complex metabolic disease and enable precision medicine. Metabolomics is the comprehensive and systematic identification of the small molecules present in differential abundance in biofluids and are affected by various factors such as diet, lifestyle, genetics, disease, environmental factors and medications. Metabolic profiling approaches to characterizing the metabolome can be either targeted or untargeted. In targeted approaches specific metabolites, representative of suspected biological pathways, are analysed in each sample. Non-targeted analysis simultaneously screens multiple small molecules for alterations in their levels within biofluids. This latter approach can identify novel, unrecognised metabolites and pathways, elucidating the pathophysiology of the disease, and highlighting potential biomarkers, biomarker signatures and/or therapeutic targets. Omics studies, specifically the non-targeted approaches have allowed us to go from hypothesis led to hypothesis generating studies.
Metabolomics employs high-throughput analytical platforms (both nuclear magnetic resonance [NMR] spectroscopy and ultra-performance liquid chromatography-mass spectrometry [UPLC-MS]) coupled with statistical modelling to identify metabolites, which are differentially present in the context of health and disease. This provides a platform to screen for candidate biomarkers for DVT diagnosis (7). NMR is a non-destructive, robust and quantitative method that provides information on molecular structure, but lacks sensitivity. MS is more sensitive, but requires pre-separation with a chromatographic method and ionisation of the sample. The combination of NMR and MS provides complimentary and accurate information on metabolites. Metabolomics has been shown to have utility in vascular disease and metabolic changes have previously been identified, at tissue level, between varicose and non-varicose vein, carotid and femoral atherosclerosis, and stable and unstable carotid plaques (8, 9). Recently, NMR spectrometry was used to identify metabolic changes of DVT in animals of different ages (10).
This study aims to elucidate the DVT-specific metabolite profile in a murine experimental model.
Metabolomics employs high-throughput analytical platforms (both nuclear magnetic resonance [NMR] spectroscopy and ultra-performance liquid chromatography-mass spectrometry [UPLC-MS]) coupled with statistical modelling to identify metabolites, which are differentially present in the context of health and disease. This provides a platform to screen for candidate biomarkers for DVT diagnosis (7). NMR is a non-destructive, robust and quantitative method that provides information on molecular structure, but lacks sensitivity. MS is more sensitive, but requires pre-separation with a chromatographic method and ionisation of the sample. The combination of NMR and MS provides complimentary and accurate information on metabolites. Metabolomics has been shown to have utility in vascular disease and metabolic changes have previously been identified, at tissue level, between varicose and non-varicose vein, carotid and femoral atherosclerosis, and stable and unstable carotid plaques (8, 9). Recently, NMR spectrometry was used to identify metabolic changes of DVT in animals of different ages (10).
This study aims to elucidate the DVT-specific metabolite profile in a murine experimental model.
Date Issued
2018-05-01
Date Acceptance
2018-01-30
Citation
European Journal of Vascular and Endovascular Surgery, 2018, 55 (5), pp.703-713
ISSN
1078-5884
Publisher
Elsevier
Start Page
703
End Page
713
Journal / Book Title
European Journal of Vascular and Endovascular Surgery
Volume
55
Issue
5
Copyright Statement
© 2018 European Society for Vascular Surgery. Published by Elsevier Ltd. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects
Science & Technology
Life Sciences & Biomedicine
Surgery
Peripheral Vascular Disease
Cardiovascular System & Cardiology
Deep vein thrombosis
Venous thromboembolism
Metabolomics
Metabolic profiling
Animal model
Biomarkers
PALADE BODY EXOCYTOSIS
VENOUS THROMBOSIS
ENDOTHELIAL-CELLS
TISSUE FACTOR
D-DIMER
CERAMIDE
ACYLCARNITINES
THROMBOEMBOLISM
ADENOSINE
SPHINGOLIPIDS
Science & Technology
Life Sciences & Biomedicine
Surgery
Animal model
Biomarkers
Deep vein thrombosis
Metabolic profiling
Metabolomics
Venous thromboembolism
Acetylcarnitine
Adenosine
Animals
Biomarkers
Chromatography, Liquid
Disease Models, Animal
Energy Metabolism
Magnetic Resonance Spectroscopy
Metabolomics
Mice
Sphingomyelins
Statistics as Topic
Succinic Acid
Vena Cava, Inferior
Venous Thrombosis
Vena Cava, Inferior
Animals
Mice
Venous Thrombosis
Disease Models, Animal
Succinic Acid
Sphingomyelins
Acetylcarnitine
Adenosine
Chromatography, Liquid
Magnetic Resonance Spectroscopy
Energy Metabolism
Statistics as Topic
Metabolomics
Biomarkers
Cardiovascular System & Hematology
1103 Clinical Sciences
1102 Cardiorespiratory Medicine and Haematology
Publication Status
Published
Date Publish Online
2018-03-08