Objective
The theme of this proposal is to develop methodologies that integrate functional genomic tools and genetic strategies to address major unresolved questions concerning the molecular basis of common diseases using coronary artery disease (CAD) as an example. Progress in functional genomics technologies have dramatically increased the density of gene expression datasets providing information on the expression of individual genes and gene networks at the levels of transcription, translation, protein abundance and activity, and metabolic processes. They will impact prevalent human complex disorders by providing new information for disease prevention and treatment. Risk factors of CAD represent dominant causes of premature death and disability. Owing to the complexity of CAD, our understanding of the pathophysiological processes involved is limited.
In this programme implemented by international investigators and SMEs we shall use functional genomics technologies (metabonomics, proteomics and transcriptomics) to generate a comprehensive and multidimensional description of well-defined states of CAD in selected clinical cohorts and animal models, which will be used as a platform for studying the causes of CAD. We will initially test the power of high- density functional genomic datasets in separating patients from probands and disease models from controls. Subsequent genetic studies will test the inheritance of both classical morphological, biochemical and hormonal phenotypes and quantitative traits derived from functional genomics datasets.
This multidisciplinary strategy will ultimately:
i) define novel disease causative biomarkers associated with or predicting disease onset and progression and
ii) provide genetic and genomic information for identifying the underlying genes.
This information will form a basis for more rational and effective strategies for CAD prevention and treatment. The methodologies that are developed will have wide application to other diseases.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomics
- natural sciencesbiological sciencesgeneticsgenomes
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Call for proposal
FP6-2005-LIFESCIHEALTH-7
See other projects for this call
Funding Scheme
STREP - Specific Targeted Research ProjectCoordinator
OXFORD
United Kingdom