Scientific and Technological Objectives
Find genes responsible for EH and TOD, using a whole genome association/entropy-based approach
Develop an integrated disease model, taking the environment into account, using an advanced bioinformatics approach
Test the predictive ability of the model to identify individuals at risk.
To identify the common genetic variants (e.g. SNPs, haplotypes) relevant for the pathogenesis of EH and EH-associated TODs in a case-control study of 4.000 subjects recruited from historical European cohorts, using whole genome association techniques. The European cohorts have already been well characterised and well defined for EH, TOD as well as for environmental risk factors and/or confounders like ethnicity, diet, smoking habits and others.
To design and implement a set of computational tools to run such a complex project. These tools can support the deployment of the knowledge management needed to support the analysis and data mining related to the genetic, clinical and environment data across different populations.
To develop a comprehensive Biomedical Information Infrastructure (BII) to store molecular, clinical, and environmental data that will help to build a comprehensive model of disease.
To develop new methods, new protocols and new standards for genomic association analysis and related issues (power, replication, stratification), gene annotation and molecular pathways. 3
To develop and test a set of specialised Decision Support Systems (DSS) tools combining multiple relevant information sources (genetic, clinical and environmental).
To create a “Web-Based Portal” to allow access to the BII in order to allow dissemination of knowledge.
To develop a simple, inexpensive genetic diagnostic chip, that can be validated in our existing wellcharacterized cohorts.
To strengthen the existing clinician-basic scientist collaborative network on the genetic mechanisms of EH. Thorough interdisciplinary efforts will facilitate common access and sharing of all available medical, clinical, environmental, biological and genetic information, ultimately leading to increased productivity at the different levels.
To generate educational tools to support professional training on genetics and genomics of complex traits, favouring mobility of PhD students, post-docs as well as joint PhD programs on two sites. This mechanism will be used not solely as an instrument to tighten the cooperation among research groups, but also to promote an ad hoc European PhD programme in "Advanced Genomics, Bioinformatics and Biostatistical Methods for Complex and Multifactorial Diseases".
To implement successful dissemination actions through participation in scientific meetings, in teaching tutorial sessions, encouraging publication of project results in high-impact scientific journals and providing an interactive and scalable feedback mechanism serving the research community.