1. bookVolume 2019 (2019): Issue 1 (January 2019)
Journal Details
License
Format
Journal
First Published
16 Apr 2015
Publication timeframe
4 times per year
Languages
English
access type Open Access

Privacy-Preserving Similar Patient Queries for Combined Biomedical Data

Published Online: 24 Dec 2018
Page range: 47 - 67
Received: 31 May 2018
Accepted: 16 Sep 2018
Journal Details
License
Format
Journal
First Published
16 Apr 2015
Publication timeframe
4 times per year
Languages
English

The decreasing costs of molecular profiling have fueled the biomedical research community with a plethora of new types of biomedical data, enabling a breakthrough towards more precise and personalized medicine. Naturally, the increasing availability of data also enables physicians to compare patients’ data and treatments easily and to find similar patients in order to propose the optimal therapy. Such similar patient queries (SPQs) are of utmost importance to medical practice and will be relied upon in future health information exchange systems. While privacy-preserving solutions have been previously studied, those are limited to genomic data, ignoring the different newly available types of biomedical data.

Keywords

[1] Shirley E. Poduslo, Rong Huang, Jie Huang, and Sierra M. Smith. Genome screen of late-onset alzheimer’s extended pedigrees identifies trpc4ap by haplotype analysis. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 150B(1):50–55, 2009.Search in Google Scholar

[2] Andrew P Feinberg and M Daniele Fallin. Epigenetics at the crossroads of genes and the environment. JAMA, 314:1129–1130, 2015.Search in Google Scholar

[3] Peter A Jones and Stephen B Baylin. The epigenomics of cancer. Cell, 128:683–692, 2007.Search in Google Scholar

[4] Irfan A Qureshi and Mark F Mehler. Advances in epigenetics and epigenomics for neurodegenerative diseases. Current neurology and neuroscience reports, 11:464–473, 2011.Search in Google Scholar

[5] Manel Esteller and James G. Herman. Cancer as an epigenetic disease: Dna methylation and chromatin alterations in human tumours. The Journal of Pathology, 196(1):1–7, 2002.Search in Google Scholar

[6] Jun Lu, Gad Getz, Eric A Miska, Ezequiel Alvarez-Saavedra, Justin Lamb, David Peck, Alejandro Sweet-Cordero, Benjamin L Ebert, Raymond H Mak, Adolfo A Ferrando, et al. Microrna expression profiles classify human cancers. nature, 435(7043):834–838, 2005.Search in Google Scholar

[7] Mohamed Hamed, Christian Spaniol, Alexander Zapp, and Volkhard Helms. Integrative network-based approach identifies key genetic elements in breast invasive carcinoma. BMC Genomics, 16(5), 2015.Search in Google Scholar

[8] Nora K. Speicher and Nico Pfeifer. Towards multiple kernel principal component analysis for integrative analysis of tumor samples. ArXiv e-prints, January 2017.Search in Google Scholar

[9] Nora K. Speicher and Nico Pfeifer. Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery. Bioinformatics, 31(12):i268, 2015.Search in Google Scholar

[10] Anthony A Philippakis, Danielle R Azzariti, Sergi Beltran, Anthony J Brookes, Catherine A Brownstein, Michael Brudno, Han G Brunner, Orion J Buske, Knox Carey, Cassie Doll, et al. The matchmaker exchange: a platform for rare disease gene discovery. Human mutation, 36(10):915–921, 2015.Search in Google Scholar

[11] Zhen Lin, Art B Owen, and Russ B Altman. Genomic research and human subject privacy. Science, pages 183–183, 2004.Search in Google Scholar

[12] Erman Ayday, Emiliano De Cristofaro, Jean-Pierre Hubaux, and Gene Tsudik. Whole genome sequencing: Revolutionary medicine or privacy nightmare? Computer, pages 58–66, 2015.Search in Google Scholar

[13] Muhammad Naveed, Erman Ayday, Ellen W Clayton, Jacques Fellay, Carl A Gunter, Jean-Pierre Hubaux, Bradley A Malin, and XiaoFeng Wang. Privacy in the genomic era. ACM Computing Surveys (CSUR), 48:6, 2015.Search in Google Scholar

[14] Yaniv Erlich and Arvind Narayanan. Routes for breaching and protecting genetic privacy. Nature Reviews Genetics, 15:409–421, 2014.Search in Google Scholar

[15] Mathias Humbert, Kévin Huguenin, Joachim Hugonot, Erman Ayday, and Jean-Pierre Hubaux. De-anonymizing genomic databases using phenotypic traits. Proceedings on Privacy Enhancing Technologies, 2015(2):99–114, 2015.Search in Google Scholar

[16] Michael Backes, Pascal Berrang, Mathias Humbert, Xiaoyu Shen, and Verena Wolf. Simulating the large-scale erosion of genomic privacy over time. IEEE/ACM transactions on computational biology and bioinformatics, 2018.Search in Google Scholar

[17] Eric E Schadt, Sangsoon Woo, and Ke Hao. Bayesian method to predict individual SNP genotypes from gene expression data. Nature genetics, 44:603–608, 2012.Search in Google Scholar

[18] Michael Backes, Pascal Berrang, Anne Hecksteden, Mathias Humbert, Andreas Keller, and Tim Meyer. Privacy in epigenetics: Temporal linkability of MicroRNA expression profiles. In Proceedings of the 25th USENIX Security Symposium, 2016.Search in Google Scholar

[19] Michael Backes, Pascal Berrang, Mathias Humbert, and Praveen Manoharan. Membership privacy in MicroRNA-based studies. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pages 319–330. ACM, 2016.Search in Google Scholar

[20] Michael Backes, Pascal Berrang, Matthias Bieg, Roland Eils, Carl Herrmann, Mathias Humbert, and Irina Lehmann. Identifying personal dna methylation profiles by genotype inference. In Security and Privacy (SP), 2017 IEEE Symposium on, pages 957–976. IEEE, 2017.Search in Google Scholar

[21] Pascal Berrang, Mathias Humbert, Yang Zhang, Irina Lehmann, Roland Eils, and Michael Backes. Dissecting privacy risks in biomedical data. In Proceedings of the 3rd IEEE European Symposium on Security and Privacy (Euro S&P). IEEE, 2018.Search in Google Scholar

[22] Xiao Shaun Wang, Yan Huang, Yongan Zhao, Haixu Tang, XiaoFeng Wang, and Diyue Bu. Efficient genome-wide, privacy-preserving similar patient query based on private edit distance. In Proceedings of the 22Nd ACM SIGSAC Conference on Computer and Communications Security, CCS ‘15, pages 492–503, New York, NY, USA, 2015. ACM.Search in Google Scholar

[23] Gilad Asharov, Shai Halevi, Yehuda Lindell, and Tal Rabin. Privacy-preserving search of similar patients in genomic data. Cryptology ePrint Archive, Report 2017/144, 2017. http://eprint.iacr.org/2017/144.Search in Google Scholar

[24] Muhammad Naveed, Shashank Agrawal, Manoj Prabhakaran, XiaoFeng Wang, Erman Ayday, Jean-Pierre Hubaux, and Carl Gunter. Controlled functional encryption. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS ‘14, pages 1280–1291, New York, NY, USA, 2014. ACM.Search in Google Scholar

[25] Yadong Yang, Edward Ruiz-Narvaez, Peter Kraft, and Hannia Campos. Effect of apolipoprotein e genotype and saturated fat intake on plasma lipids and myocardial infarction in the central valley of costa rica. Human Biology, 79(6):637–647, 2017/06/23 2007.Search in Google Scholar

[26] María J Artiga, María J Bullido, Isabel Sastre, María Recuero, Miguel A García, Jesús Aldudo, Jesús Vázquez, and Fernando Valdivieso. Allelic polymorphisms in the transcriptional regulatory region of apolipoprotein e gene. FEBS Letters, 421(2):105–108, 1998.Search in Google Scholar

[27] Gerwin Roks, Marc Cruts, Jeanine J. Houwing-Duistermaat, Bart Dermaut, Sally Serneels, Louis M. Havekes, Albert Hofman, Monique M. B. Breteler, Christine Van Broeckhoven, and Cornelia M van Duijn. Effect of the apoe-491a/t promoter polymorphism on apolipoprotein e levels and risk of alzheimer disease: The rotterdam study. American Journal of Medical Genetics, 114(5):570–573, 2002.Search in Google Scholar

[28] Simon M. Laws, Eugene Hone, Sam Gandy, and Ralph N. Martins. Expanding the association between the apoe gene and the risk of alzheimer’s disease: possible roles for apoe promoter polymorphisms and alterations in apoe transcription. Journal of Neurochemistry, 84(6):1215–1236, 2003.Search in Google Scholar

[29] June E. Eichner, S. Terence Dunn, Ghazala Perveen, David M. Thompson, Kenneth E. Stewart, and Berrit C. Stroehla. Apolipoprotein e polymorphism and cardiovascular disease: A huge review. American Journal of Epidemiology, 155(6):487, 2002.Search in Google Scholar

[30] Anna Danielsson, Szilárd Nemes, Magnus Tisell, Birgitta Lannering, Claes Nordborg, Magnus Sabel, and Helena Carén. Methped: a dna methylation classifier tool for the identification of pediatric brain tumor subtypes. Clinical Epigenetics, 7(1):62, 2015.Search in Google Scholar

[31] Dario Catalano and Dario Fiore. Using linearly-homomorphic encryption to evaluate degree-2 functions on encrypted data. In Proceedings of the 22Nd ACM SIGSAC Conference on Computer and Communications Security, CCS ‘15, pages 1518–1529, New York, NY, USA, 2015. ACM.Search in Google Scholar

[32] Ancestry. https://www.ancestry.com/dna/. Accessed: 2017-07-25.Search in Google Scholar

[33] 23andme. https://www.23andme.com/en-int/ancestry/. Accessed: 2017-07-25.Search in Google Scholar

[34] John Quackenbush. Computational genetics: computational analysis of microarray data. Nature reviews genetics, 2(6):418, 2001.Search in Google Scholar

[35] Bo Wang, Aziz M Mezlini, Feyyaz Demir, Marc Fiume, Zhuowen Tu, Michael Brudno, Benjamin Haibe-Kains, and Anna Goldenberg. Similarity network fusion for aggregating data types on a genomic scale. Nature methods, 11(3):333–337, 2014.Search in Google Scholar

[36] Burkhard Morgenstern, Bingyao Zhu, Sebastian Horwege, and Chris André Leimeister. Estimating evolutionary distances between genomic sequences from spaced-word matches. Algorithms for Molecular Biology, 10(1):5, Feb 2015.Search in Google Scholar

[37] Jianchao Yao, Chunqi Chang, Mari L. Salmi, Yeung Sam Hung, Ann Loraine, and Stanley J. Roux. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient. BMC Bioinformatics, 9(1):288, Jun 2008.Search in Google Scholar

[38] Michael B. Eisen, Paul T. Spellman, Patrick O. Brown, and David Botstein. Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences, 95(25):14863–14868, 1998.Search in Google Scholar

[39] dbSNP. https://www.ncbi.nlm.nih.gov/SNP/.Search in Google Scholar

[40] Raphael Bost, Raluca Ada Popa, Stephen Tu, and Shafi Goldwasser. Machine learning classification over encrypted data. In 22nd Network and Distributed System Security Symposium (NDSS’ 15), 2015.Search in Google Scholar

[41] Paul J McLaren, Jean Louis Raisaro, Manel Aouri, Margalida Rotger, Erman Ayday, István Bartha, Maria B Delgado, Yannick Vallet, Huldrych F Günthard, Matthias Cavassini, et al. Privacy-preserving genomic testing in the clinic: a model using HIV treatment. Genetics in Medicine, 2016.Search in Google Scholar

[42] George Danezis and Emiliano De Cristofaro. Fast and private genomic testing for disease susceptibility. In Proceedings of the 13th Workshop on Privacy in the Electronic Society, pages 31–34. ACM, 2014.Search in Google Scholar

[43] Whitfield Diffie and Martin E. Hellman. New directions in cryptography. IEEE Trans. Inf. Theor., 22(6):644–654, September 2006.Search in Google Scholar

[44] Pascal Paillier. Public-key cryptosystems based on composite degree residuosity classes. In Proceedings of the 17th International Conference on Theory and Application of Cryptographic Techniques, EUROCRYPT’99, pages 223–238, Berlin, Heidelberg, 1999. Springer-Verlag.Search in Google Scholar

[45] Florian Kerschbaum and Orestis Terzidis. Filtering for private collaborative benchmarking. In Günter Müller, editor, Emerging Trends in Information and Communication Security, pages 409–422, Berlin, Heidelberg, 2006. SpringerSearch in Google Scholar

[46] Personal genomes project (PGP) platform. https://my.pgphms.org.Search in Google Scholar

[47] Gene expression omnibus (GEO). https://www.ncbi.nlm.nih.gov/geo/.Search in Google Scholar

[48] Sally R. Lambert, Hendrik Witt, Volker Hovestadt, Manuela Zucknick, Marcel Kool, Danita M. Pearson, Andrey Korshunov, Marina Ryzhova, Koichi Ichimura, Nada Jabado, Adam M. Fontebasso, Peter Lichter, Stefan M. Pfister, V. Peter Collins, and David T. W. Jones. Differential expression and methylation of brain developmental genes define location-specific subsets of pilocytic astrocytoma. Acta Neuropathologica, 126(2):291–301, Aug 2013.Search in Google Scholar

[49] Petra Leidinger, Valentina Galata, Christina Backes, Cord Stähler, Stefanie Rheinheimer, Hanno Huwer, Eckart Meese, and Andreas Keller. Longitudinal study on circulating mirnas in patients after lung cancer resection. In Oncotarget, 2015.Search in Google Scholar

[50] Christine Jost, Ha Lam, Alexander Maximov, and Ben J. M. Smeets. Encryption performance improvements of the paillier cryptosystem. IACR Cryptology ePrint Archive, 2015:864, 2015.Search in Google Scholar

[51] Cynthia Dwork, Aaron Roth, et al. The algorithmic foundations of differential privacy. Foundations and Trends® in Theoretical Computer Science, 9(3–4):211–407, 2014.Search in Google Scholar

[52] Ivan Damgård, Mads Jurik, and Jesper Buus Nielsen. A generalization of paillier’s public-key system with applications to electronic voting. International Journal of Information Security, 9(6):371–385, 2010.Search in Google Scholar

[53] Amos Fiat and Adi Shamir. How to prove yourself: Practical solutions to identification and signature problems. In Andrew M. Odlyzko, editor, Advances in Cryptology — CRYPTO’ 86, pages 186–194, Berlin, Heidelberg, 1987. Springer Berlin Heidelberg.Search in Google Scholar

[54] Md Momin Al Aziz, Dima Alhadidi, and Noman Mohammed. Secure approximation of edit distance on genomic data. BMC Medical Genomics, 10(2):41, Jul 2017.Search in Google Scholar

[55] Yan Huang, David Evans, and Jonathan Katz. Private set intersection: Are garbled circuits better than custom protocols? In NDSS. The Internet Society, 2012.Search in Google Scholar

[56] Bristena Oprisanu and Emilliano De Cristofaro. Anonimme: Bringing anonymity to the matchmaker exchange platform for rare disease gene discovery. bioRxiv, 2018.Search in Google Scholar

[57] Per Hallgren, Claudio Orlandi, and Andrei Sabelfeld. Privatepool: Privacy-preserving ridesharing. In 2017 IEEE 30th Computer Security Foundations Symposium (CSF), pages 276–291, Aug 2017.Search in Google Scholar

[58] Ge Zhong, Ian Goldberg, and Urs Hengartner. Louis, lester and pierre: Three protocols for location privacy. In Nikita Borisov and Philippe Golle, editors, Privacy Enhancing Technologies, pages 62–76, Berlin, Heidelberg, 2007. Springer Berlin Heidelberg.Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo