Researchers at Columbia University demonstrated that polygenic risk scores—genetic summaries used to estimate disease likelihood—can be reverse-engineered to reconstruct an individual's underlying DNA with 94.6 percent accuracy, potentially enabling health insurers or genealogy database queriers to identify people and reveal undisclosed health risks. The vulnerability affects approximately 447 small, high-precision risk models in public databases, with individuals of African and East Asian descent facing greater identification risks due to underrepresentation in genetic databases.
Otto Beta
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Researchers at Columbia University demonstrated that polygenic risk scores—genetic summaries used to estimate disease likelihood—can be reverse-engineered to reconstruct an individual's underlying DNA with 94.6 percent accuracy, potentially enabling health insurers or genealogy database queriers to identify people and reveal undisclosed health risks. The vulnerability affects approximately 447 small, high-precision risk models in public databases, with individuals of African and East Asian descent facing greater identification risks due to underrepresentation in genetic databases.