The VIKING Study: The Västerbotten Imputation databanK of Near-complete Genomes - a stratified medicines initiative for genetically complex diseases

Dnr:

SNIC 2016/1-386

Type:

SNAC Medium

Principal Investigator:

Paul Franks

Affiliation:

Lunds universitet

Start Date:

2016-10-01

End Date:

2017-10-01

Primary Classification:

30107: Medicinsk genetik

Secondary Classification:

30205: Endokrinologi och diabetes

Tertiary Classification:

30302: Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi

Webpage:

http://www.ludc.med.lu.se/research-units/genetic-and-molecular-epidemiology-game/

Allocation

Abstract

People´s susceptibility to environmental risk factors and response to therapies varies. Some of us will smoke, drink, eat, and sunbath excessively yet never develop lung cancer, liver disease, obesity, or melanoma, whilst others will succumb early in life to these morbidities. Drug efficacy and side effects also varies considerably. Sensitivity to environmental risk factors, response to drug therapies, and occurrence of disease are heritable (segregating within families). Although most chronic diseases such as diabetes, heart disease and cancer have strong genetic bases, carrying risk alleles does not guarantee disease. Nevertheless, genetic factors raise sensitivity to environmental risk factors and interfere with the way medicines work. Harnessing this information may help clinicians quickly and efficiently identify the best therapy for a patient, without needing to embark on an expensive and sometimes harmful process of trial and error until a tolerable and effective treatment is found. The VIKING Study is the first attempt to use sophisticated genomic and bioinformatic methods to impute 15 million gene variants in ~50,000 northern Swedes and combine this with biomedical and demographic data from the Umeå Medical Biobank, and with disease and prescription drug registries. This expansive cohort will be used to study interactions between genotypes, lifestyle factors, and drug therapies to identify genetic biomarkers that can be used in stratified medical interventions.