Deep Vein Thrombosis Metabolomic Profiling by 1H NMR
ISTH Academy. Quintero M. Jul 9, 2019; 264479; PB1288 Topic: Biomarkers of Thrombosis & Hemostasis
Melissa Quintero
Melissa Quintero
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Deep Vein Thrombosis Metabolomic Profiling by 1H NMR

M. Quintero1,2, S. Montalvao1, S. Huber1, I. Macedo Toni1, B. de Moraes Martinelli1, L. Tasic2, J.M. Bizzacchi1
1Hemocentro UNICAMP, University of Campinas, Campinas, Brazil, 2University of Campinas (UNICAMP), Organic Chemistry, Campinas, Brazil

Main Topic: Diagnostics and OMICs
Category: Biomarkers of Thrombosis & Hemostasis

Background: Metabolomics is an emerging field of research used to describe 'the complete set of metabolites/low-molecular-weight intermediates, which are context dependent, varying according to the physiology, developmental or pathological state of the cell, tissue, organ or organism. It is currently used for diagnosis and biomarker screening.
Aims: The aim of this study was used the metabolomics to identify metabolic alterations in patients with spontaneous and provoked deep venous thrombosis (DVT).
Methods: Using liquid-state 1H-NMR data acquisition combined with chemometrics analysis, we evaluated twenty serum samples of DVT patients, spontaneous (median age of 47 years; 6 female/4 male) and provoked (median age of 33 years; 10 female), who were attended at the outpatient clinic of Hemocentro at Unicamp-Brazil from 2013 to 2017. All had a confirmation of the diagnosis of proximal and / or distal lower limbs by ultrasound with Doppler. The exclusion criteria were the presence of cancer, renal, hepatic or inflammatory disease, smoking and alcoholism. The collected time after the first DVT acute episode was maximum of 2 years. Patients with only one episode of thrombosis were used. The control group (median age of 41 years; 5 female/5male) come from the functional staff of the Hemocentro. The exclusion criteria were the same as for patients. Multivariate analysis pointed to slight differential metabolic profiles among spontaneous and provoked DVT and healthy control patients.
Results: Number of different discriminatory metabolites were identified, many of which are linked to energy, lipid or amino acids metabolism. Aromatic amino acids were discriminatory for thrombosis. The observed metabolic differences might indicate suggestive alterations for inflammatory processes.
Conclusions: To have a better understanding of the metabolic alterations potentially involved in the venous thrombosis pathways and to clarify the role of some anticoagulants in metabolism, a high number of patients and additional analysis are being performed.
FAPESP 2018/18624-4 and 2016/14172-6

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