Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States
Open accessAbstract
Accessing and integrating human genomic data with phenotypes are important for biomedical research. Making genomic data accessible for research purposes, however, must be handled carefully to avoid leakage of sensitive individual information to unauthorized parties and improper use of data. In this article, we focus on data sharing within the scope of data accessibility for research. Current common practices to gain biomedical data access are strictly rule based, without a clear and quantitative measurement of the risk of privacy breaches. In addition, several types of studies require privacy‐preserving linkage of genotype and phenotype information across different locations (e.g., genotypes stored in a sequencing facility and phenotypes stored in an electronic health record) to accelerate discoveries. The computer science community has developed a spectrum of techniques for data privacy and confidentiality protection, many of which have yet to be tested on real‐world problems. In this article, we discuss clinical, technical, and ethical aspects of genome data privacy and confidentiality in the United States, as well as potential solutions for privacy‐preserving genotype–phenotype linkage in biomedical research.
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Technical advancements of differential privacy allow organisations to share publicly a dataset while keeping information about individuals secret and can ensure provable privacy protection on sensitive data such as genomic data.
“Technical advancements of this kind, which allow organisations to share publicly a dataset while keeping information about individuals secret (preventing re-identification), and can ensure provable privacy protection on sensitive data, such as genomic data (Wang et al. 2017).”
From The ethics of algorithms: key problems and solutions (2022) · cites this paper as Wang et al. 2017
A growing scholarship on differential privacy is providing new privacy protection methods for organisations looking to protect users' privacy while keeping good model quality and manageable software costs, striking a balance between utility and privacy.
“Finally, a growing scholarship on differential privacy is providing new privacy protection methods for organisations looking to protect their users' privacy while also keeping good model quality, as well as manageable software costs and complexity, striking a balance between utility and privacy (Abadi et al. 2016;Wang et al. 2017;Xian et al. 2017).”
From The ethics of algorithms: key problems and solutions (2022) · cites this paper as Wang et al. 2017
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- Authors
- Wang, S., Jiang, X., Singh, S., Marmor, R., Bonomi, L., Fox, D., Dow, M., & Ohno‐Machado, L.
- Affiliations
- University of California San Diego (US)
- University of San Diego (US)
- Department of Biomedical Informatics University of California San Diego La Jolla California
- Corresponding author
- Wang, Shuang
- Venue
- Annals of the New York Academy of Sciences
- Publisher
- Wiley
- Published
- 2016-09-28
- Volume
- 1387
- Issue
- 1
- Pages
- 73-83
- ISSN
- 0077-8923 (ISSN-L)
- 1749-6632
- PMC
- PMC5266631
- OpenAlex
- W2523884223
- Cited by
- 78
- References
- 90
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 9 · 2023: 6 · 2022: 7 · 2021: 10 · 2020: 7 · 2019: 10 · 2018: 6 · 2017: 6
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annals of the New York Academy of Sciences (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- SSRN Electronic Journal (submittedVersion)
- Funders
- National Institutes of Health (U54HL108460, R00HG008175, UL1TR001442, T15LM011271, R00LM011392, R21LM012060)
- Patient-Centered Outcomes Research Institute (CDRN‐1306‐04819)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Physical Sciences › Computer Science › Information Systems › Thoreau and American Literature
- Keywords
- genomic data sharing, privacy violations, data access control, electronic health records, research data access, United States
- MeSH terms
- Humans, Informed Consent, Medical Record Linkage, Risk Management, United States, Computer Security, Computational Biology, Genomics, Genetic Privacy, Data Mining
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