Dataset Information

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

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.

SUBMITTER: Lippert C

PROVIDER: S-EPMC5617305 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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

Lippert Christoph C Sabatini Riccardo R Maher M Cyrus MC Kang Eun Yong EY Lee Seunghak S Arikan Okan O Harley Alena A Bernal Axel A Garst Peter P Lavrenko Victor V Yocum Ken K Wong Theodore T Zhu Mingfu M Yang Wen-Yun WY Chang Chris C Lu Tim T Lee Charlie W H CWH Hicks Barry B Ramakrishnan Smriti S Tang Haibao H Xie Chao C Piper Jason J Brewerton Suzanne S Turpaz Yaron Y Telenti Amalio A Roby Rhonda K RK Och Franz J FJ Venter J Craig JC

Proceedings of the National Academy of Sciences of the United States of America 20170905 38

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 demogr ...[more]

PMID: 28874526

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Dataset Information

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

Publications

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

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