Interview Questions for Kári Stefánsson, CEO of deCODE Genetics
1. Focus on Ongoing Projects:
Can you share details about a current project at deCODE that excites you the most, whether in multiomics or another area of research? What specific findings or innovations do you think will have the biggest impact on clinical practice in the near future?
Our general approach to the study of human health and disease has been to focus the biological foundations of human diversity. Human diversity begins with the diversity in the sequence of nucleotides in the genome but the environment makes significant contributions to it, not only through the selection component of evolution but also by interacting with the genomes of individuals from their conceptions to their deaths. Recently we have been putting emphasis on the study of interactions of variants in the sequence of the genome with other variants in the sequence (epistasis) as well as with environmental factors. It has proven difficult to document these interactions that are inevitable in part because of lack of power. We have however found a way that makes it easier at least for some categories of interactions and it goes as follows: Usually when people are searching for variants in the sequence that correlate with quantitative traits they look for variants that correlate with the mean. If instead of that you look for variants that correlate with variance in the quantitative trait (some with the allele have low value and others have high value) it inevitably means that the variant is interacting with something else, either another variant or a component of the environment. This approach has allowed us to find variants in the genome that interact with components of food that through the interaction influence risk of diseases. We have, for example, found a variant in the sequence that interacts with a diet item that is called oily fish in the UK biobank in such a way that if you carry the minor allele it leads to elevation in cholesterol but does not affect it if you are a non-carrier. We have also found a variant in an other gene that interacts with alcohol in such a way that if you are a carrier your level of non-HDL cholesterol and hence your risk of coronary artery disease is inversely correlated with your alcohol consumption. I believe that our ability to map in detail the interactions between the genome and environment (food and othe lifestyle) is going to have a major impact on clinical practice in the near future. It is going to allow us to use the sequence of our genomes to craft a personal lifestyle that is good for our health.
2. Addressing Current Challenges:
deCODE’s work in population genetics has been groundbreaking, but translating population-level insights into individual treatments can be complex. What is one specific challenge you’re addressing in this area, and what solutions or methodologies are you exploring to overcome it?
I do not disagree with the opinion that it is a formidable task to translate insights from population level genetics into individual treatments. However there are no other types of insights that offer more opportunities to do so. When we find an association of a variant in the sequence of a gene that affects the risk of a disease and we can determine whether the risk allele is a gain or a loss of function the gene product is a reasonable candidate for a drug target. When we find a target in this way and we combine the genetics with proteomics and/or transcriptomic it almost invariably comes with biomarkers of target engagement, pharmacodynamic effect, and disease progression that can become a biomarker of regression upon treatment. We have already discovered such targets that are engaged by compounds that are now in clinical development. The limiting resource in this work is access to large enough amount of sequence data to allow for the discovery of very rare variants and access to sequence data from other populations than the ones of European descent. We are relentlessly sequencing genomes from extremely well phenotyped populations and we have begun sequencing large number of African genomes.
3. Data Scalability and Clinical Translation:
deCODE has access to one of the most comprehensive genetic databases. How are you leveraging this vast amount of data to accelerate the clinical translation of genetic research into real-world healthcare? Are there any specific tools or frameworks you’re developing to ensure scalability and practical implementation in clinical settings?
We are participating in an attempt to use all of the genetic data we have generated on Icelanders that includes insight into genotypes of the entire nation and whole genome sequence of a large proportion of the nation in the implementation of precision medicine. This could be looked upon as a clinical trial of the translation of genetic reserch into real-world healthcare.
4. Future Visionary Direction:
Looking ahead 5-10 years, which emerging technologies or methodologies in genetic research are you most excited about, and how do you see them shaping the future of precision medicine?
The amount of genetic data that will be available in 5 to 10 years will dramatically change the nature of the field. The application of artificial intelegence (AI) to the analysis of data on sequences of millions of genomes, and of transcriptomics and proteomics data from tens of millions of serial samples with focus on multimodal analysis will be a game changer. Furthermore, AI analysis of clinical images will allow for the discovery of much more phenotypic details from both normal tissues and tissues undergoing pathogenesis of diseases. All of this is going to lead to avalanches of discoveries and much more accurate understanding of the contribution of genetics versus environment (lifestyle) in the pathogenesis of diseases and maintenance of health. I also expect that within this time frame the application of multiomic understanding of disease and health will have made it into the delivery of healthcare. The most effective way to accomplish this will be through aps that allow the individual to download all of the information available on their own healthcare (electronic medical records, data from wearable devices etc) and provides the option to buy genomic sequencing and transcriptomics and proteomics measurements. This would be accompanied by analytical software to turn these data into risk assessments. This would not only allow for the application of genetics to healthcare but empower the individual to become her or his own primary healthcare provider. The data generated thorough this type of healthcare would allow for much more specific genetic research into both heath and disease.
