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CL XI Epidemiology

Summary

The CL XI is built around the popgen biobank and will run populations-based studies within the framework of the stringent (and audited) popgen data protection concept. The CL XI will take further its current approaches to epidemiological study design and environmental exposure assessment for co-operations within the Cluster, focusing on the analysis of gene-gene and gene-environment interactions. With the envisaged collection of new samples and data the CL XI will predominantly collaborate with RAs I, II, VI and CL VII. In detail, the CL XI will facilitate family-based prospective studies through the enrollment of all first-degree relatives of patients with inflammatory barrier disease who already participate in popgen. Crohn`s disease will be the most promising target endpoint because of its strong attributable genetic risk component and young age of onset. Family-based prospective studies will allow a more efficient identification of the genetic and environmental trigger factors. Furthermore, the CL XI aims at providing the methodological expertise for a more in-depth characterization of relevant environmental exposures which will be driven by projects from various Cluster RAs. To this end, biomaterial obtained from core popgen populations will be analyzed in greater detail than has hitherto been the case through the generation of metabolomic profiles and through the combination of biomedical and environmental information.

Contribution to the Scientific Discourse

Creating a framework for assessment of genetic and environmental data in collaboration with the clinical partners represent the main task of this CL. It will provide: (1) methodological development and implementation for in-depth data/biomaterial collection to study environmental exposure, (2) recruitment of first-degree relatives (kindred cohort) of patients with inflammatory diseases already under study in the Popgen program, (3) a structure for long-term follow-up of these family-based cohorts for disease incidence and early disease risk markers and (4) methodological expertise in statistical algorithms for the molecular-epidemiological analysis of gene-gene and gene-environment interactions in inflammatory diseases.

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