Date : 09/03/2012

Laboratory
Genes and blood pressure - Genetic mechanisms of aldosterone-related disorders
U970, INSERM
Paris Cardiovascular Research Center - PARCC
Hôpital Européen Georges Pompidou- HEGP
56, rue Leblanc
75015 Paris
Website
Main discipline : Systems Biology
Lab director : Maria-Christina Zennaro

PhD Supervisor
Maria-Christina Zennaro
email : Cet e-mail est protégé contre les robots collecteurs de mails, votre navigateur doit accepter le Javascript pour le voir
phone: +33 1 53 98 80 42

Subjects
1.: primary aldosteronism
2.: molecular genetics
3.: functional genomics

Tools and Methodologies
1.: bioinformatics
2.: high throughput genetics and genomics
3.: integrated data analysis

Summary of lab's interests
Our group explores the genetic mechanisms underlying diseases related to aldosterone, either with loss-of-function (pseudohypoaldosteronism type 1), or with gain-of-function (primary aldosteronism) leading to hypertension. An original interdisciplinary approach combines complementary expertise from a large clinical database and adrenal biobank, to genetic, molecular and cellular experiments integrated through bioinformatic studies.

Summary of project
Aim of this project will be to investigate the genetic and the somatic genomic determinants of primary aldosteronism, the most common and treateble from of secondary hypertension. Through the use of GWAS, miRNome, SNParray and transcriptome data we will develop new model systems for PAL physiopathological investigations and for testing novel therapeutic approaches. Results obtained through this program may have substantial impact also for diagnosis and treatment of essential hypertension in the general population. The project will be conducted in collaboration with the group of A. Benecke (http://seg.ihes.fr).

Interdisciplinarity of the project
The project consists in the integrated bioinformatic analysis of existing data coming from multiple platforms and their translation into a physiopathological model and identification of biomarkers translatable to clinical practice. For this purpose, the applicants should have background in mathematics/bioinformatics and strong interest in systems biology.