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Making invisible risk, visible

10 November 2020
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3
min read
Aerial view of people scattered across a green park, partially covered by the shadow of a large structure—evoking unseen patterns in population data and reflecting Genomics’ work in uncovering hidden genetic risks through polygenic analysis.

The world is at an inflection point for genetically powered risk prediction. Better technology, bigger data availability and declining costs of genotyping have all been critical driving forces to unlock our understanding of polygenic variation, and bring it out of theory into clinical practice.

This type of genetic variation is often the biggest single predictor of an individual’s health risk for common diseases. The use of Polygenic Risk Scores that measure this variation in the clinic will surpass the applications of genetics that we have seen to date – moving from an era of Genomic Medicine, where genetics can help to diagnose and help treat rare diseases, to one of Genomic Prevention, where common diseases can be preemptively managed at population scales.

The use of Polygenic Risk Scores that measure this variation in the clinic will surpass the applications of genetics that we have seen to date.

In a world with broken, ‘sick-care’ systems overwhelmed by both chronic and infectious disease burdens, healthcare systems everywhere need to undergo a sustainable transition to a long-term model that delivers cost-effective, equitable care. Polygenic Risk Scores have the potential to seed that transition. They have the potential to transform healthcare from a system of diagnosis and treatment to one of risk prediction and prevention.

We see a future where we can predict and prevent disease before it occurs and to deliver more personalized and precise healthcare interventions to the right patients at the right time.

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