Identification of individuals by trait prediction using whole-genome sequencing data.
Proc Natl Acad Sci U S A
; 114(38): 10166-10171, 2017 09 19.
Article
em En
| MEDLINE
| ID: mdl-28874526
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Fenótipo
/
Impressões Digitais de DNA
/
Confidencialidade
/
Sequenciamento Completo do Genoma
/
Modelos Genéticos
Tipo de estudo:
Diagnostic_studies
/
Etiology_studies
/
Incidence_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article