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Modeling Disease through Cell Reprogramming: a Translational Approach to the Pathogenesis of Syndromes Caused by Symmetrical Gene Dosage Imbalances (DISEASEAVATARS)
Date du début: 1 sept. 2014, Date de fin: 31 août 2019 PROJET  TERMINÉ 

The fundamental limitation in our ability to dissect human diseases is the scarce availability of human tissues at relevant disease stages, which is particularly salient for neural disorders. Somatic cell reprogramming is overcoming this limitation through the derivation of patient-specific induced pluripotent stem cells (iPSC) that can be differentiated into disease-relevant cell-types. Despite these tantalizing possibilities, there are critical issues to be addressed in order to secure iPSC-modeling as a robust platform for the interrogation of disease aetiology and the development of new therapies. These concern the taming of human genetic variation, the identification of differentiation stages in which to uncover and validate phenotypes, and finally their translational into drug discovery assays. This project confronts these challenges focusing on the paradigmatic case of two rare but uniquely informative disorders caused by symmetric gene dosage imbalances at 7q11.23: Williams Beuren Syndrome and the subset of autism spectrum disorders associated to 7q11.23 microduplication. The hallmark of WBS is a unique behavioral-cognitive profile characterized by hypersociability and intellectual disability in the face of comparatively well-preserved language abilities. Hence, the striking symmetry in genotype and phenotype between WBS and 7dupASD points to the 7q11.23 cluster as a surprisingly small subset of dosage-sensitive genes affecting social behaviour and cognition. We build on a large panel of iPSC lines that we already reprogrammed from a unique cohort of WBS and 7dupASD patients and whose characterization points to specific derangements at the level of transcriptional/epigenetic control, protein synthesis and synaptic dysfunction. Through the integration of transcriptomic and epigenomic profiling with targeted mass spectrometry and gene network prediction we propose an innovative drug discovery pipeline for the identification of new therapeutic leads.



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