Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores

Paige, Brooks; Bell, James; Bellet, Aurelien; Gascón, Adrià; Ezer, Daphne

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1089/cmb.2020.0445

Titre :

Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores

Auteur(s) :

Paige, Brooks [Auteur]
Bell, James [Auteur]
Bellet, Aurelien [Auteur]

Machine Learning in Information Networks [MAGNET]
Gascón, Adrià [Auteur]
Ezer, Daphne [Auteur]

Titre de la revue :

Journal of Computational Biology

Pagination :

435-451

Éditeur :

Mary Ann Liebert

Date de publication :

2021

ISSN :

1066-5277

Mot(s)-clé(s) en anglais :

genetic risk scores
genomic privacy
GWAS
long-term privacy
reconstruction attack

Discipline(s) HAL :

Informatique [cs]/Apprentissage [cs.LG]
Statistiques [stat]/Machine Learning [stat.ML]

Résumé en anglais : [en]

Some organizations such as 23andMe and the UK Biobank have large genomic databases that they re-use for multiple different genome-wide association studies. Even research studies that compile smaller genomic databases often ...
Lire la suite >Some organizations such as 23andMe and the UK Biobank have large genomic databases that they re-use for multiple different genome-wide association studies. Even research studies that compile smaller genomic databases often utilize these databases to investigate many related traits. It is common for the study to report a genetic risk score (GRS) model for each trait within the publication. Here, we show that under some circumstances, these GRS models can be used to recover the genetic variants of individuals in these genomic databases—a reconstruction attack. In particular, if two GRS models are trained by using a largely overlapping set of participants, it is often possible to determine the genotype for each of the individuals who were used to train one GRS model, but not the other. We demonstrate this theoretically and experimentally by analyzing the Cornell Dog Genome database. The accuracy of our reconstruction attack depends on how accurately we can estimate the rate of co-occurrence of pairs of single nucleotide polymorphisms within the private database, so if this aggregate information is ever released, it would drastically reduce the security of a private genomic database. Caution should be applied when using the same database for multiple analysis, especially when a small number of individuals are included or excluded from one part of the study.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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