Polygenic risk scores (PRS), put simply, look at gene variants across the human genome in order to determine an individual's risk of getting a disease, from different types of cancer to type II diabetes. PRS could complement current risk prediction models and lead to a more accurate risk prediction. However, for PRS to become a useful clinical instrument, transparent ways to assess their performance and careful communication of disease risks to individuals are key. In episode 22 of We’re doomed we’re saved, Andreas Horchler and Louise von Stechow speak to two PRS researchers, who contributed to the international and interdisciplinary, EU-funded INTERVENE project. Brooke Wolford, a Postdoctoral Fellow in the HUNT Center for Molecular and Clinical Epidemiology at the Norwegian University of Science and Technology and Kristi Läll, a researcher in statistical genetics at Institute of Genomics, University of Tartu, share their expertise on PRSs and discuss the potential of PRSs in the clinic and pinpoint strategies for addressing biases in PRS. Listen to Learn more about IINTERVENE here: https://www.interveneproject.eu/ Content and Editing: Louise von Stechow and Andreas Horchler Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast. Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow Image: Acton Crawford via Unsplash References: PRS background and clinical implications 1. https://www.statnews.com/2019/04/30/als-polygenic-analysis/ 2. https://www.nature.com/articles/s41591-021-01549-6 3. https://pubmed.ncbi.nlm.nih.gov/32423490/ 4. https://www.acmg.net/PDFLibrary/Clinical-Application-Polygenic-Risk-Scores.pdf 5. https://www.nature.com/articles/s41588-018-0183-z 6. https://www.nature.com/articles/s41467-020-19966-5 7. https://www.nature.com/articles/s41436-018-0406-9 8. https://www.nature.com/articles/s41436-020-0884-4 9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10681845/ 10. https://pubmed.ncbi.nlm.nih.gov/33009504/ 11. https://pubmed.ncbi.nlm.nih.gov/26392438/ 12. https://pubmed.ncbi.nlm.nih.gov/30309464/ 13. https://www.helsinki.fi/en/news/genes/personal-genetic-risk-motivates-positive-changes-health-behaviour-study-shows 14. https://pubmed.ncbi.nlm.nih.gov/32709988/ 15. https://www.nature.com/articles/d42473-019-00270-w 16. https://www.nature.com/articles/s41698-021-00176-1 17. https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(23)00156-0/fulltext 18. https://hpi.de/digital-health-cluster/pressemitteilungen/2021/intervene-verbesserte-krankheitspraevention-durch-einsatz-von-ki-und-genomik.html 19. https://www.myadlm.org/science-and-research/clinical-chemistry/clinical-chemistry-podcasts/2023/polygenic-risk-scores_genomes-to-risk-prediction 20. https://pubmed.ncbi.nlm.nih.gov/32722720/ 21. https://pubmed.ncbi.nlm.nih.gov/31322649/ 22. https://www.medrxiv.org/content/10.1101/2020.09.18.20197137v1 23. https://www.sciencedirect.com/science/article/pii/S0002929718302362 24. https://pubmed.ncbi.nlm.nih.gov/35130028/ 25. https://www.ebi.ac.uk/gwas/ 26. https://pubmed.ncbi.nlm.nih.gov/35896674/ Risks and ethical implications 27. https://www.nature.com/articles/s41588-019-0379-x 28. https://www.nature.com/articles/s41576-023-00637-2 29. https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1098439/full 30. https://www.nature.com/articles/s41591-024-02796-z?fromPaywallRec=true 31. https://www.nature.com/articles/s43856-021-00028-w 32. https://www.eesc.europa.eu/en/news-media/news/artificial-intelligence-eu-law-should-set-safe-boundaries-high-risk-applications-says-eesc#:~:text=The%20European%20Commission%20
Polygenic risk scores (PRS), put simply, look at gene variants across the human genome in order to determine an individual's risk of getting a disease, from different types of cancer to type II diabetes. PRS could complement current risk prediction models and lead to a more accurate risk prediction. However, for PRS to become a useful clinical instrument, transparent ways to assess their performance and careful communication of disease risks to individuals are key. In episode 22 of We’re doomed we’re saved, Andreas Horchler and Louise von Stechow speak to two PRS researchers, who contributed to the international and interdisciplinary, EU-funded INTERVENE project. Brooke Wolford, a Postdoctoral Fellow in the HUNT Center for Molecular and Clinical Epidemiology at the Norwegian University of Science and Technology and Kristi Läll, a researcher in statistical genetics at Institute of Genomics, University of Tartu, share their expertise on PRSs and discuss the potential of PRSs in the clinic and pinpoint strategies for addressing biases in PRS. Listen to Learn more about IINTERVENE here: https://www.interveneproject.eu/
Content and Editing: Louise von Stechow and Andreas Horchler
Disclaimer: Louise von Stechow & Andreas Horchler and their guests express their personal opinions, which are founded on research on the respective topics, but do not claim to give medical, investment or even life advice in the podcast.
Learn more about the future of biotech in our podcasts and keynotes. Contact us here: scientific communication: https://science-tales.com/ Podcasts: https://www.podcon.de/ Keynotes: https://www.zukunftsinstitut.de/louise-von-stechow
Image: Acton Crawford via Unsplash
References: PRS background and clinical implications