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.
We use genetic variation to provide informed bioinformatics prioritization of novel genes for functional follow-up. We investigate a wide range of disease information curated in close collaboration with our extensive network of clinical experts. Our reaerach will focus particulary on identifying inactivating mutations as they provide a unique opportunity to study functional consequence of mutations. In a separate effort, we will start with a limited number of likely functional mutations of unknown function and screen these for association with the widest possible range of disease and health outcomes found in Norway’s comprehensive health registries. We plan to coordinate collaborations with other large-scale studies to improve power, and collaborate with leading international experts for functional follow-up of our results.
We also use genetic epidemiology analysis to investigate modifiable causes of disease using a wide range of Mendelian randomization approaches. Finally, we will utilize inactivating mutations to systematically evaluate the efficiency and safety for licensed pharmaceutical treatments.
The center formalize collaborations between four strong local research groups and a world leading team of international collaborators at the interface of epidemiology, genetics, 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. HUNT is a comprehensive population based health study with personal and family histories on ~120,000 people from Nord-Trøndelag county, Norway, collected during three intensive studies HUNT 1-3 spanning three decades. Data was collected from self-reported questionnaires, clinical examinations, urine and non-fasting venous blood samples (HUNT 2 and 3) constituting ~7,000 variables from ~220,000 screening events. HUNT Biobank, which holds the biological material from HUNT, was appointed the "European Research Biobank of the Year" in 2013 by the European Society of Biorepositories and Biobanks. Genome-wide genotype data on ~70,000 individuals from HUNT 2 and 3 will be available for research in January 2016 through efforts coordinated and funded by Hveem, Holmen, Abecasis and Willer. The genotyping chip (HumanCoreExome, Illumina Inc) contains ~250k GWAS markers and ~250k exome variants which allows for concurrent evaluation of much of the coding variants while simultaneously allowing for imputation of much of the rest of the genome. Genotyping and data processing are currently being conducted at NTNU by the research groups of Hveem and Sætrom. We expect additional data sources to be added over the center period.
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. Computer resources. HUNT Cloud is a computer solution aimed at researchers within the HUNT community making available scalable storage and analysis for sensitive genomics data. HUNT Cloud currently holds 120,000 Norwegian samples from the large cohorts of HUNT, Tromsø and National Institute of Public Health.