EVITA-eVitenskap

The Norwegian biobanks contain a wealth of information that can lead to new and improved diagnostics and treatments of disease. Specifically, the biological samples stored in the biobanks contain information about individuals' genetic and epigenetic varia tion. Coupled with personal and environmental data such as those collected from questionnaires or patient records, these samples can reveal the molecular mechanisms that underlie human traits and diseases. Studies using high throughput methods have succe ssfully used biobank samples to identify single nucleotide polymorphisms (SNPs) associated with diseases such as type 2 diabetes, abnormal heart rhythm, and lung cancer. As the studies have managed to capture only part of the heritable variation, however, new studies have started to collect data on complete genetic variations and individual gene expression differences (www.1000genomes.org, tinyurl.com/3yy3hp6). Combined with other biobank "omics" data such as protein, metabolite, and epigenetic variation, these new and detailed data may identify and explain the "missing" heritable variation. For biobanks - which should make all data derived from their biological samples available for future studies - storage, access, and integration of data from differen t high throughput analyses are becoming a major challenge. Another major challenge facing biobank-based population studies is to develop down-stream analysis methods that can use available data to identify the biological mechanisms underlying disease-asso ciated variation. The goal of this project is to develop methods that address these two challenges by storing, accessing, and integrating biobank "omics" data, and analysing such data within a hypothesis-driven framework. We will focus especially on met hods that identify and explain disease-associated variation affecting gene regulation.