GENETICS OF T1D

Using gene to phenotype studies to identify type 1 diabetes genes and their functions

Coordinatore	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE    more  Organization address address: The Old Schools, Trinity Lane city: CAMBRIDGE postcode: CB2 1TN contact info Titolo: Ms. Nome: Renata Cognome: Schaeffer Email: send email Telefono: +44 1223 335743 Fax: +44 1223 332988
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	50˙000 €
EC contributo	50˙000 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2010-RG
Funding Scheme	MC-IRG
Anno di inizio	2011
Periodo (anno-mese-giorno)	2011-03-01   -   2013-02-28

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE  Organization address address: The Old Schools, Trinity Lane city: CAMBRIDGE postcode: CB2 1TN contact info Titolo: Ms. Nome: Renata Cognome: Schaeffer Email: send email Telefono: +44 1223 335743 Fax: +44 1223 332988	UK (CAMBRIDGE)	coordinator	50˙000.00

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 Obiettivo del progetto (Objective)

'Following the recent explosion of GWAS publications, we now have a much better grasp of the common genetic basis of many human complex traits. This dramatic development of genotyping and analytic technologies has allowed to characterize many novel variants associated with human disease. Nevertheless, the identification of these disease-associated loci hasn’t yet translated into a better understanding of the exact nature of the defects causing the pathologic manifestations. In the current research project, we propose to assess the physiological role of the risk variants on relevant phenotypes to identify functional the causal genes associated with type 1 diabetes (T1D) pathogenesis. To address this issue, we will develop highly sensitive and reproducible assays to measure the impact of the different genotypes on the selected phenotypes. By using this quantitative approach, we expect not only to be able to reduce the complexity inherent to the disease phenotype, but also to have the power and sensitivity to detect the important but quantitative physiological effects of common susceptibility alleles of low phenotypic penetrance.

In this study we will develop highly sensitive molecular assays, and will take advantage of the core flow cytometry facilities to characterize the cell surface, cytokine production and signaling profile of immune subsets in individuals carrying specific risk alleles. Importantly, we will take advantage of our core genotyping and clinical databases to assess the impact of disease-associated genotypes on these quantitative phenotypes. By integrating the phenotyping data with a high throughput genotyping database in a large sample of individuals, we expect to translate the current knowledge of the genetic risk, into a more physiologically relevant context, in order to narrow down on the actual causal genes contributing to the etiology of human diseases.'