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Identification of individuals by trait prediction using whole-genome sequencing data

Item Type:Article
Title:Identification of individuals by trait prediction using whole-genome sequencing data
Creators Name:Lippert, C. and Sabatini, R. and Maher, M.C. and Kang, E.Y. and Lee, S. and Arikan, O. and Harley, A. and Bernal, A. and Garst, P. and Lavrenko, V. and Yocum, K. and Wong, T. and Zhu, M. and Yang, W.Y. and Chang, C. and Lu, T. and Lee, C.W.H. and Hicks, B. and Ramakrishnan, S. and Tang, H. and Xie, C. and Piper, J. and Brewerton, S. and Turpaz, Y. and Telenti, A. and Roby, R.K. and Och, F.J. and Venter, J.C.
Abstract:Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.
Keywords:Genomic Privacy, Genome Sequencing, DNA Phenotyping, Phenotype Prediction, Reidentification
Source:Proceedings of the National Academy of Sciences of the United States of America
ISSN:0027-8424
Publisher:National Academy of Sciences (U.S.A.)
Volume:114
Number:38
Page Range:10166-10171
Date:19 September 2017
Additional Information:Erratum in: PNAS 114(41): E8800.
Official Publication:https://doi.org/10.1073/pnas.1711125114
PubMed:View item in PubMed

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