Browsing by Author "Raisaro, J. L."
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Item Open Access Privacy threats and practical solutions for genetic risk tests(IEEE, 2015) Barman, L.; Elgraini, M.-T.; Raisaro, J. L.; Hubaux, J. -P.; Ayday, ErmanRecently, several solutions have been proposed to address the complex challenge of protecting individuals' genetic data during personalized medicine tests. In this short paper, we analyze different privacy threats and propose simple countermeasures for the generic architecture mainly used in the literature. In particular, we present and evaluate a new practical solution against a critical attack of a malicious medical center trying to actively infer raw genetic information of patients. © 2015 IEEE.Item Open Access Privacy-preserving genomic testing in the clinic: a model using HIV treatment(Nature Publishing Group, 2016) Mclaren, P. J.; Raisaro, J. L.; Aouri, M.; Rotger, M.; Ayday, E.; Bartha, I.; Delgado, M. B.; Vallet, Y.; Günthard, H. F.; Cavassini, M.; Furrer, H.; Doco-Lecompte, T.; Marzolini, C.; Schmid, P.; Di Benedetto, C.; Decosterd, L. A.; Fellay, J.; Hubaux, Jean-Pierre; Telenti A.Purpose: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.Methods: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.Results: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%.Conclusions: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.