Unlocking Genetic Profiles with a Programmable DNA‐Powered Decoding Circuit
Abstract: Human genetic architecture provides remarkable insights into disease risk prediction and personalized medication. Advances in genomics have boosted the fine‐mapping of disease‐associated genetic variants across human genome. In healthcare practice, interpreting intricate genetic profiles into actionable medical decisions can improve health outcomes but remains challenging. Here an intelligent genetic decoder is engineered with programmable DNA computation to automate clinical analyses and interpretations. The DNA‐based decoder recognizes multiplex genetic information by one‐pot ligase‐dependent reactions and interprets implicit genetic profiles into explicit decision reports. It is shown that the DNA decoder implements intended computation on genetic profiles and outputs a corresponding answer within hours. Effectiveness in 30 human genomic samples is validated and it is shown that it achieves desirable performance on the interpretation of CYP2C19 genetic profiles into drug responses, with accuracy equivalent to that of Sanger sequencing. Circuit modules of the DNA decoder can also be readily reprogrammed to interpret another pharmacogenetics genes, provide drug dosing recommendations, and implement reliable molecular calculation of polygenic risk score (PRS) and PRS‐informed cancer risk assessment. The DNA‐powered intelligent decoder provides a general solution to the translation of complex genetic profiles into actionable healthcare decisions and will facilitate personalized healthcare in primary care.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Unlocking Genetic Profiles with a Programmable DNA‐Powered Decoding Circuit ; day:28 ; month:04 ; year:2023 ; extent:13
Advanced science ; (28.04.2023) (gesamt 13)
- Creator
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Liu, Junlan
Zhang, Chao
Song, Jinxing
Zhang, Qing
Zhang, Rongjun
Zhang, Mingzhi
Han, Da
Tan, Weihong
- DOI
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10.1002/advs.202206343
- URN
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urn:nbn:de:101:1-2023042915073938091310
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:45 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Liu, Junlan
- Zhang, Chao
- Song, Jinxing
- Zhang, Qing
- Zhang, Rongjun
- Zhang, Mingzhi
- Han, Da
- Tan, Weihong
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