Towards precision prevention: Technologies for identifying healthy individuals with high risk of disease
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Author(s) • • • • • • • • •
Nagel, Zachary D.
Brenner, David J.
Begley, Thomas J.
Sobol, Robert W.
Bielas, Jason H.
Stambrook, Peter J.
Wei, Qingyi
Hu, Jennifer J.
Terry, Mary Beth
Dilworth, Caroline
Date Issued
April 2017
Journal
Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis
Publisher
Elsevier BV
Citation
Nagel, Zachary D. et al. “Towards Precision Prevention: Technologies for Identifying Healthy Individuals with High Risk of Disease.” Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis 800–802 (August 2017): 14–28 © 2017 Elsevier B.V.
Version
Author's final manuscript
Abstract
The rise of advanced technologies for characterizing human populations at the molecular level, from sequence to function, is shifting disease prevention paradigms toward personalized strategies. Because minimization of adverse outcomes is a key driver for treatment decisions for diseased populations, developing personalized therapy strategies represent an important dimension of both precision medicine and personalized prevention. In this commentary, we highlight recently developed enabling technologies in the field of DNA damage, DNA repair, and mutagenesis. We propose that omics approaches and functional assays can be integrated into population studies that fuse basic, translational and clinical research with commercial expertise in order to accelerate personalized prevention and treatment of cancer and other diseases linked to aberrant responses to DNA damage. This collaborative approach is generally applicable to efforts to develop data-driven, individualized prevention and treatment strategies for other diseases. We also recommend strategies for maximizing the use of biological samples for epidemiological studies, and for applying emerging technologies to clinical applications. Keywords: DNA damage; Comet; H2AX; Host cell reactivation; DNA repair; DNA damage response; Precision medicine
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/J.MRFMMM.2017.03.007