The Genome of Europe project is at the forefront of science and will -for the first time- bring together a large and comprehensive genetic dataset of DNA variation across all major groups of citizens living in Europe. GoE represents a unique collaboration across >30 countries to gather genetic information from their citizens as a reference database and make that accessible for medical and basic research. It is a very important first step to start using genetic information in health care and prevention, in particular in personalized or precision medicine and prevention.
So far, several genetic datasets have been available to scientists but these were relatively small and biased towards in particular inhabitants of the USA and UK. While the current GoE project is funded to collect at least 100,000 genomes of European citizens, the GoE database is expected to grow to >500,000 reference genomes as part of the 1 million genomes initiative (https://digital-strategy.ec.europa.eu/en/policies/1-million-genomes). The GoE project promotes scientific excellence by bringing together the major genetic groups, bio-informaticians, ELSI experts, and sequencing centers across Europe (>50 institutes and >200 scientists) which will collaborate in creating the GoE database for the coming 4 years.
Several ground breaking pilot projects are embedded that will use the genetic data as collected within GoE, such as the calibration of the polygenic risk scores (PRS) to local genetic variation. PRS are now widely investigated and also touted to move precision medicine and prevention forward, especially for the most common diseases of our greying society such as cancer, dementia, diabetes, osteoporosis and osteoarthritis, and cardiovascular diseases. The large and diverse GoE dataset will allow such PRS to be implemented across European population subgroups that differ in their genetic background. Examples include the application of PRS in breast cancer screening programs based on mammography, cardiovascular screening programs using genetically determined cholesterol levels, and use of pharmacogenetic information to select and optimize medication.