Research - K.G. Jebsen Center for Genetic Epidemiology
Our Research
The overall aim of the K.G. Jebsen Center for Genetic Epidemiology is to better understand human health and disease by studying genomic variation in populations. The center will primarily work on the translational axis between population-based and laboratory-based research.
The center formalize collaborations between four strong local research groups and a world leading team of international collaborators at the interface of medicine, epidemiology, genetics, applied statistics, bioinformatics and system biology. We have deliberately chosen to establish work packages across the research groups’ individual expertise to accentuate the integrative component of the center. We believe that high-impact out-of-the-box discoveries is fostered in the interface of multidisciplinary teams working together towards a greater goal of improved human health guided by a clinical mindset.
Our main data resource is genome-wide genotype data on ~70,000 individuals from The Nord-Trøndelag Health Study (HUNT) enriched with phenotype information form a wide range of national registries.
Norway's 11-digits unique-personal identification number allows for assessment of a comprehensive health history for our participants utilizing registries such as: The Norwegian Patient Registry, the diagnostic registries at the hospitals of Levanger and Namsos, the database at the Norwegian Health Economics Administration (HELFO), the Cause of Death Registry, and the Norwegian Prescription Database.
Genome-Wide Association Study
Conducting Genome-Wide Association Study-scans on selected phenotypes using HUNT data.
Transcriptomics
Revealing genetic variants predictive of individual variation in cell type composition and cell type-specific gene expression.
Pharmacogenomics
Focusing on how genetic differences among individuals cause varied response to the same drug.
Mendelian Randomization
Using genetic instruments to provide unbiased evidence on causal effects of modifiable exposure.
Bioinformatics
Developing a pipeline for analyzing and integrating single cell and tissue transcriptomics data.
Metabolomics
The systematic study of metabolites, which are intermediates and end-products of all metabolic activities in our cells.
Network Biology
Developing new mathematical and computational methods to leverage knowledge from molecular networks in the identification of genetic variation associated with disease.
Ethical, Legal and Social Issues
Developing and improving procedures to respect the autonomy and promote the well-being of participants.