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Projekt
A genome-wide phenotype-overlapping approach for the identification of shared disease loci
Antragsteller
Professor Dr. Andre Franke
Fachliche Zuordnung
Humangenetik
Förderung
Förderung von 2010 bis 2013
Projektkennung
Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 162103175
Diseases have historically been defined using organ structures. However, recent genetic discoveries indicate that such a definition may not be appropriate in elucidating the genetic pathology, since one disease gene can predispose to several diseases. We and others could already show an overlap of susceptibility variants among diseases. Hence, analyzing diseases that are likely to share etiological pathways may improve our future ability to develop effective therapies for them. Recently, many genome-wide association studies (GWAS) have been carried out to identify unknown genetic factors for single diseases. However, the joint and meta analysis of such data will most likely lead to the identification of novel shared susceptibility loci for the diseases under study. We have already published a proof-of-principle study. Nevertheless, a systematic approach is missing so far. The applicants have readily available genome-wide data sets for more than 14 distinct, mostly inflammatory barrier diseases (>14000 patients, >8800 controls) at their disposal. Within the project described below, the applicants will use established and novel analytical approaches to identify novel shared loci and systematically follow them up. We pursue the following objectives with our study:1. Detection and mapping of novel general inflammation genes2. Definition of signature etiologies for disease groups3. Potential redefinition of disease groups along general inflammation genesThe applicants’ access to further, independent large case-control cohorts for all diseases under study guarantees a fast validation, replication, and further follow-up within the project. The pursuit of the project and the rapid publication of results with little or no outside interference are ensured by a letter of collaboration that has been signed by all data-providing scientists.
DFG-Verfahren
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