PubMed · 8435593
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
J Clarke, P J Harkin. 1993-01-02. Electronic communication.. https://doi.org/10.1136/bmj.306.6869.64
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
MOTIVATION: Rare diseases affect millions of people worldwide, yet their genomic foundations remain poorly understood due to limited patient data and strict privacy regulations, such as the General Data Protection Regulation (GDPR) (https://gdpr.eu/tag/gdpr/) in March 2025. These restrictions can hinder the collaborative analysis of genomic data necessary for uncovering disease-causing variants. RESULTS: We present PRISM, a novel privacy-preserving framework based on fully homomorphic encryption (FHE) that facilitates rare disease variant analysis across multiple institutions without exposing sensitive genomic information. To address the challenges of centralized trust, PRISM is built upon a Threshold FHE scheme. This approach decentralizes key management across participating institutions and ensures no single entity can unilaterally decrypt sensitive data. Our method filters disease-causing variants under recessive, dominant, and de novo inheritance models entirely on encrypted data. We propose two algorithmic variants: a multiplication-intensive (MUL-IN) approach and an addition-intensive (ADD-IN) approach. The ADD-IN algorithms minimize the number of costly multiplication operations, enabling up to a 17× improvement in runtime for recessive/dominant filtering and 22× for de novo filtering, compared to MUL-IN methods. While ADD-IN produces larger ciphertexts, efficient parallelization via SIMD and multithreading allows it to handle millions of variants in reasonable time. To the best of our knowledge, this is the first study that utilizes FHE for privacy-preserving rare disease analysis across multiple inheritance models, demonstrating its practicality and scalability in a single-cloud setting. AVAILABILITY AND IMPLEMENTATION: The source code and the data used in this work can be found in https://github.com/mdppml/PRISM.git.
MOTIVATION: The affordability of genome sequencing and the widespread availability of genomic data have opened up new medical possibilities. Nevertheless, they also raise significant concerns regarding privacy due to the sensitive information they encompass. These privacy implications act as barriers to medical research and data availability. Researchers have proposed privacy-preserving techniques to address this, with cryptography-based methods showing the most promise. However, existing cryptography-based designs lack (i) interoperability, (ii) scalability, (iii) a high degree of privacy (i.e. compromise one to have the other), or (iv) multiparty analyses support (as most existing schemes process genomic information of each party individually). Overcoming these limitations is essential to unlocking the full potential of genomic data while ensuring privacy and data utility. Further research and development are needed to advance privacy-preserving techniques in genomics, focusing on achieving interoperability and scalability, preserving data utility, and enabling secure multiparty computation. RESULTS: This study aims to overcome the limitations of current cryptography-based techniques by employing a multi-key homomorphic encryption scheme. By utilizing this scheme, we have developed a comprehensive protocol capable of conducting diverse genomic analyses. Our protocol facilitates interoperability among individual genome processing and enables multiparty tests, analyses of genomic databases, and operations involving multiple databases. Consequently, our approach represents an innovative advancement in secure genomic data processing, offering enhanced protection and privacy measures. AVAILABILITY AND IMPLEMENTATION: All associated code and documentation are available at https://github.com/farahpoor/smkhe.
Our objectives were to review and analyze the laws in the 50 states, the District of Columbia, and Puerto Rico that regulate the acquisition, storage, and use of public health data and to offer proposals for reform of the laws on public health information privacy. Virtually all states reported some statutory protection for governmentally maintained health data for public health information in general (49 states), communicable diseases (42 states), and sexually transmitted diseases (43 states). State statutes permitted disclosure of data for statistical purposes (42 states), contact tracing (39 states), epidemiologic investigations (22 states), and subpoena or court order (14 states). The survey revealed significant problems that affect both the development of fair and effective public health information systems and the protection of privacy. Statutes may be silent about the degree of privacy protection afforded, confer weaker privacy protection to certain kinds of information, or grant health officials broad discretion to disseminate personal information. Our proposals for law reform are based on a meeting of experts at the Carter Presidential Center under the auspices of the Centers for Disease Control and Prevention and the Council of State and Territorial Epidemiologists: (1) an independent data protection commission should be established, (2) health authorities should justify the collection of personally identifiable information, (3) subjects should be given basic information about data practices, (4) data should be held and used in accordance with fair information practices, (5) legally binding privacy and security assurances should attach to identifiable health information with significant penalties for breach of these assurances, (6) disclosure of data should be made only for purposes consistent with the original collection, and (7) secondary uses beyond those originally intended by the data collector should be permitted only with informed consent.