Biobanks - Future of Predictive Genomics

Complexity and Data Requirements of Biobanks

Disease Risks and Pharmacological Possibilities

Dataset must contain genomic data on enough people to achieve statistical relevance

Genetic and non-genetic medical conditions must be taken into account

Predictive genomics holds tremendous promise, but realizing that promise has been a fitful process. A dataset that can properly inform medical providers about a person’s disease risks and pharmacological possibilities has to contain genomic data on enough people to achieve statistical relevance and information about those people’s other medically relevant statistics, including those that are not genetically determined. This is the premise of a biobank, and the biobanks in Finland and Estonia are already revealing just how much can be learned when whole countries put in the resources necessary to use genomic information to its fullest potential.

Finland and Estonia – Examples of Successful Biobanks

Finland and Estonia are both highly developed countries with small, relatively homogenous populations and universal healthcare. Combined with their advanced health-records systems and robust understanding of informed consent, both countries were ideal testbeds for demonstrating the benefits of a thorough biobanking system. FinnGen, the Finnish biobank, and its Estonia counterpart collected both genomic and medical information from sizable fractions of each country’s population—roughly 10% of Finland and 20% of Estonia—and combined it with medical test results and other medical records available through their respective healthcare systems to create comprehensive databases of each participant’s health information.

Genome-Wide Association Studies

In Finland, this information is used as part of genome-wide association studies (GWAS) to identify gene variants of interest for various health conditions, including breast cancer, using Thermo Fisher Scientific GWA Arrays specifically designed for FinnGen’s research. This information, in turn, can be used to assign polygenic risk scores (PRSs) based on variants of concern present in a person’s genome and to act accordingly, such as performing direct medical tests more often on especially susceptible people.

Helping Doctors with Diagnosis & Choosing Treatments

In Estonia, this work is being used to help develop a tool to aid doctors with diagnosis and especially with choosing treatments for complex conditions like depression. Personalized genetic information may yet spare more Estonians from the difficult and sometimes life-threatening process of trial and error currently needed to find the right medication for conditions like these.

Webinar: Predictive Genomics Insights from Experts

In this webinar, Dr. Aarno Palotie of the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki and Dr. Andres Metspalu of the Estonian Genome Center ad the University of Tartu discuss their countries’ respective biobanks: what tools were used to collect genomic information, what other medical information they encompass, and how they have already been used to assist with medical practice.