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Privacy-preserving genomic testing in the clinic: a model using HIV treatment.

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author McLaren Paul J, Raisaro Jean Louis, Aouri Manel, Rotger Margalida, Ayday Erman, Bartha István, Delgado Maria B, Vallet Yannick, Günthard Huldrych F, Cavassini Matthias, Furrer Hansjakob, Doco-Lecompte Thanh, Marzolini Catia, Schmid Patrick, Di Benedetto Caroline, Decosterd Laurent A, Fellay Jacques, Hubaux Jean-Pierre, Telenti Amalio,
Project Swiss HIV Cohort Study (SHCS)
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Original article (peer-reviewed)

Journal Genetics in medicine : official journal of the American College of Medical Genetics
Volume (Issue) 18(8)
Page(s) 814 - 22
Title of proceedings Genetics in medicine : official journal of the American College of Medical Genetics
DOI 10.1038/gim.2015.167

Open Access

Type of Open Access Repository (Green Open Access)


The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics. We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers. A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%. The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.Genet Med 18 8, 814-822.