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Born 27/01/1973 in Le Mans (France), I was recruited at INSERM (French National Institute for Medical Research) as a research associate 2nd class in 1999 just after completing my PhD in statistical genetics. From 2000 to 2014, I have been working at the department of Cardiovascular Genomics (subsequently referred to as INSERM UMR_S 525 & UMR_S 937) of the Pitié-Salpêtrière Hospital (Paris). In 2004, I was promoted research associate 1st class and obtained in 2005 my « qualification to conduct research » that enables me to supervise PhD students. So far I have supervised 9 PhD students and 16 post-doctoral (or equivalent) fellows
I was promoted Research Director 2nd class (INSERM DR2) in December 2009 and Reseach Director 1st class (INSERM DR1) in December 2018.
Research career
My research career started with the development of statistical methods to analyze family data as well as genetic polymorphisms in the context of candidate association studies. I then turned to the development and the application of statistical tools for the analysis of high-throughput microarray data as part of genome-wide association and expression projects. As former head of the genomics department of the Institute of Cardiometabolism and Nutrition (IHU-ICAN) and of the biostatistics and bioinformatics group of the Post-Genomic Platform of the Pitié-Salpêtrière Hospital, I got solid expertise in the generation and analysis of next-generation sequenced data (eg. whole-exome, RNA-sequencing, miRNA-sequencing, Chip-Sequencing). I partner with the GENMED Laboratory of Excellence on Medical Genomics to coordinate several genomics projects relying on whole exome/genome sequencing and high-throughput DNA arrays.
In parallel to these statistical and bioinformatics developments, I am participating in the design and the analysis of several epidemiological studies aiming at identifying susceptibility genes for cardiovascular diseases, my favorite diseases being venous thromboembolism (VTE) and pulmonary arterial hypertension. I am joint coordinator of the French EOVT, FARIVE, MARTHA, MARFAST and PILGRIM studies aimed at identifying genetic factors for VTE. Within the F-CRIN supported INNVOTE network that assembled all French clinician working in the field of VTE, I am responsible of the research programs on VTE genomics. I am an active convener of the International Network of Venous Thrombosis (INVENT) consortium and participate in international collaborative efforts on cardiovascular diseases including CHARGE, Cardiogenics, Cardomics, CADgenomics and MORGAM. More recently, my interests have turned to epigenetics as novel mechanisms contributing to the inter-individual susceptibility to human diseases with strong emphasis on the latest approaches on DNA methylation, microRNA and proteomic profiling towards the identification of novel molecular biomarkers for thrombosis.
Functions
From 2014 to 2018, I headed the department of Genomics and Pathophysiology of Cardiovascular Diseases within the INSERM UMR_S 1166 at the ICAN Institute for Cardiometabolism and Nutrition on the Pitié-Salpêtrière Campus (Paris). My team was composed of clinicians, molecular and cellular biologists, epidemiologists, statistical geneticists and bioinformaticians. Together, our aims were to : – identify novel genes and novel genetic variations associated with the susceptibility to cardiovascular diseases, both common or rare ; – to characterize their fonctional roles ; – to identify novel pathophysiological mechanisms with the ultimate goal to achieve a better clinical managment of patients. Our research program was built on the application of high-throughput microarray and next-generation sequencing technologies in human collections and on experimental invesstigations on identified variants/genes. Main diseases of interest were cardiomyopathies, arrhythmias , arterial and venous thrombosis.
By the end of 2018, I decided to move to Bordeaux and joined the Bordeaux Population Research Center (https://www.bordeaux-population-health.center/en/) to focus my research program on the application of machine learning and artificial intelligence based methods for cardiovascular precision medicine.
