Genome-Wide Association Study (GWAS)

K.G. JEBSEN CENTER FOR GENETIC EPIDEMIOLOGY

Genome-Wide Association Study (GWAS)

The impact on medical care from genome-wide association studies can be substantial, laying the groundwork for implementing personalized medicine, based on studies of genetic variation on a population level. 

Great improvements have been made in the cost and efficiency of genome-wide scans and other innovative technologies, using such tools to provide patients with individualized information about their risk of developing certain diseases and to tailor prevention programs to each person's unique genetic makeup.

When a person reaches a disease endpoint, GWAS-based approaches may be used to select the treatments most likely to be effective. Since most inactivating mutations are rare due to negative natural selection, statistical power remains a challenge. To address this, we are well placed to coordinate collaborations with other large-scale studies, and we plan to do reciprocal look-up and meta-analyze results with studies of similar size to improve power. We will also participate in a range of consortia focused on discovery for a wide variety of traits. 

Our group run a large project called ALL-IN  where we look at a wide range of diseases. This is done in close collaboration with clinicians and researchers who specialize in the different areas. Look below for more details and contact information. 

ALL-IN

Contact: John-Anker Zwart, MD, PhD, FORMI/UIO

 

  • Cognitive impairment
  • Common psychiatric conditions
  • Eating disorders
  • Epilepsy
  • Headache and migraine
  • Surgical treatment of neck and back disorders
  • Neurodegenerative diseases
  • Pain conditions
  • Parkinsons disease
  • Sleep conditions
  • Cerebrovascular disease
  • Brain tumour

Group Leaders

Group Leaders

Lecture: Comprehensive benchmarking of integrated polygenic and conventional risk factor models for cardiovascular traits in the HUNT-study.

Lecture: Comprehensive benchmarking of integrated polygenic and conventional risk factor models for cardiovascular traits in the HUNT-study

Sequencing 10.000s of human genomes

Lecture: Sequencing 10.000s of human genomes

Understanding the biological basis of cardiovascular disease through genetics

Lecture: Understanding the biological basis of cardiovascular disease through genetics