LORENZO, Hadrien; RAZZAQ, Misbah; ODEBER, Jacob; MORANGE, Pierre-Emmanuel; SARACCO, Jérôme; TRÉGOUËT, David-Alexandre; THIÉBAUT, Rodolphe

doi:10.1109/CBMS.2019.00094

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LORENZO, Hadrien
Vaccine Research Institute [Créteil, France] [VRI]

RAZZAQ, Misbah
Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]

ODEBER, Jacob
KTH Royal Institute of Technology [Stockholm] [KTH]

Langue

Communication dans un congrès

Ce document a été publié dans

CBMS 2019 - 32nd IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2019-06-05, Cordoba. p. 453-458

IEEE

Résumé en anglais

The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains a relevant strategy to disentangle pathophysiological mechanisms underlying the risk of venous thrombosis (VT). As part of the MARseille THrombosis Association Study (MARTHA), we measured whole blood DNA methylation levels, plasma levels of 300 proteins, 3 thrombin generation biomarkers (endogeneous thrombin potential, peak and lagtime), clinical and genetic data in 700 patients with VT. The application of a novel high-dimensional multi-levels statistical methodology we recently developed, the data driven sparse Partial Least Square method (ddsPLS), on the MARTHA datasets enabled us 1/ to confirm the role of a known mutation of the variability of endogenous thrombin potential and peak, 2/ to identify a new signature of 7 proteins strongly associated with lagtime.< Réduire

Mots clés en anglais

Multi-Omics

High Dimensional Data

Missing Data

SVD

Partial Least Square

Variable Selection

Multi-Block Analysis

Machine Learning

Thrombine Generation

URI

https://oskar-bordeaux.fr/handle/20.500.12278/192603

DOI

http://dx.doi.org/10.1109/CBMS.2019.00094

Project ANR

Medical Genomics - ANR-10-LABX-0013

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251