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Quantitative pathway analysis of natural variation.. (PANACEA)
Quantitative pathway analysis of natural variation in complex disease signaling in C. elegans
(PANACEA)
Date du début: 1 janv. 2009,
Date de fin: 31 mars 2013
PROJET
TERMINÉ
Complex human diseases account for 60% of the deaths in Europe. The genetic variation – that is the genetic make-up of all alleles at all loci - of complex disease pathways determines individual disease susceptibility and treatment prospects. Because humans are genetically diverse the EC prioritizes research which leads to a better understanding of the natural variation in genetic pathways underlying complex diseases. But for ethical reasons there is insufficient statistical power to identify these genetic mechanisms in large human populations. Therefore the extent and importance of natural variation in disease signaling pathways of complex human diseases remains largely unknown. PANACEA will investigate the influence of natural variation in genetic pathways in the worm Caenorhabditis elegans. C. elegans is an important model for the identification and characterization of genes associated with cancer in humans. Therefore PANACEA focuses on cancer signaling pathways as a prototypical example of a complex disease. The project will address two pivotal quations: i) how natural genetic variation affects complex disease signaling pathways, and ii) whether we can predict the effect of the natural genetic variation on these pathways. We will collect, store and analyse high-throughput genomic and proteomic data in genetically highly diverse populations. In conjunction with cellular developmental data we will construct a systems biology model aiming to describe and understand the effect of natural variation on cancer signaling pathways. The outcomes will provide i) an extensive data base of novel candidate genes and their genetic variation, and ii) a comprehensive systems biology analysis of how this genetic variation affects cancer development. PANACEA advances the FP6 projects ESBIC-D, CASIMIR and EURATools by providing new data and insights which will strongly benefit the field of systems biology in human health research in the EU.
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