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Carlo Rivolta


European network for genetic-epidemiological studies: building a method to dissect complex genetic traits, using essential hypertension as a disease model

Domaine: Cooperation Health

Acronyme: Hypergenes

Durée: 01.01.2008 – 31.06.2011

Budget total: 10.210.000 EUR

Budget UNIL: 1.929.000 EUR


Carlo Rivolta, Département de génétique médicale, CHUV



The project is focused on the definition of a comprehensive genetic epidemiological model of complex traits like Essential Hypertension (EH) and intermediate phenotypes of hypertension dependent/associated Target Organ Damages (TOD).

To identify the common genetic variants relevant for the pathogenesis of EH and TODs, we will perform a Whole Genome Association (WGA) study of 4.000 subjects recruited from historical well-characterized European cohorts. Genotyping will be done with the Illumina Human 1M BeadChip. Well-established multi-variate techniques and innovative genomic analyses through machine learning techniques will be used for the WGA investigations.

Using machine learning approach we aim at developing a disease model of EH integrating the available information on EH and TOD with relevant validated pathways and genetic/environmental information to mimic the clinician's recognition pattern of EH/TOD and their causes in an individual patient.

Our statistical design is with two samples run in parallel, each with 1,000 cases and 1,000 controls, followed by a replication/joint analysis. This design is more powerful than replication alone and allows also a formal testing of the potential heterogeneity of findings compared to a single step (one large sample) design.

The results represent the source to build a customized and inexpensive genetic diagnostic chip that can be validated in our existing cohorts (n=12,000 subjects). HYPERGENES is in the unique position to propose a ground-breaking project, improving the methodology of genetic epidemiology of chronic complex diseases that have a high prevalence among EU populations. Designing a comprehensive genetic epidemiological model of complex traits will also help us to translate genetic findings into improved diagnostic accuracy and new strategies for early detection, prevention and eventually personalised treatment of a complex trait. The ultimate goal will be to promote the quality of life of EU populations. 

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Carlo Rivolta

CH-1015 Lausanne  - Suisse  -  Tél. +41 21 693 47 50  -  Fax  +41 21 693 55 83