Center for Diabetes Research is an interdisciplinary research center that integrates clinical investigations with large-scale genetic analyses and different model systems. The center collaborates with various groups at the University of Bergen and Haukeland University Hospital in an effort to find new diabetes genes and map new mechanisms involved in diabetes development. The main aim is to develop new diagnostic tools that can be tested in population-based registries and biobanks before being used in clinical practice, thus facilitating individualized diabetes care.
The center has six principal investigators: (1) Professor Pål R. Njølstad, MD PhD; (2) Professor Helge Ræder, MD PhD; (3) Professor Simona Chera, PhD; (4) Professor Anders Molven, PhD; (5) Professor Stefan Johansson, PhD; Professor Valeriya Lyssenko, MD PhD.
The groups work together to:
1. Find new genetic risk factors for diabetes and its complications
2. Reveal novel disease mechanisms in diabetes development
3. Develop and implement improved targeted treatment of diabetes
We are located at the Children and Youth Hospital building, block 2, 6th floor, Haukelandsbakken 15, 5021 Bergen, Norway.
Publications from the Center for Diabetes Research can be found here.
We thank the Kristian Gerhard Jebsen Foundation (KGJ) for supporting important diabetes research in Bergen. We also thank the University of Bergen (UoB), Helse Vest, The Research Council of Norway (RCN), the Trond Mohn foundation (former BFS), Novo Nordisk Fonden and the European Research Council (ERC).
Most recent publications
- ProHap enables human proteomic database generation accounting for population diversity
- Multi-ancestry GWAS of severe pregnancy nausea and vomiting identifies risk loci associated with appetite, insulin signaling, and brain plasticity
- Clinical utility of novel diabetes subgroups in predicting vascular complications and mortality: up to 25 years of follow-up of the HUNT Study
- Rare copy number variant analysis in case-control studies using snp array data: a scalable and automated data analysis pipeline
- Genetic associations of neuropathic pain and sensory profile in a deeply phenotyped neuropathy cohort