Privacy-preserving biological age prediction over federated human methylation data using fully homomorphic encryption.

ABSTRACT: DNA methylation data play a crucial role in estimating chronological age in mammals, offering real-time insights into an individual's aging process. The epigenetic pacemaker (EPM) model allows inference of the biological age as deviations from the population trend. Given the sensitivity of this data, it is essential to safeguard both inputs and outputs of the EPM model. A privacy-preserving approach for EPM computation utilizing fully homomorphic encryption was recently introduced. However, this method has limitations, including having high communication complexity and being impractical for large data sets. The current work presents a new privacy-preserving protocol for EPM computation, analytically improving both privacy and complexity. Notably, we employ a single server for the secure co

SUBMITTER: Goldenberg M 

PROVIDER: S-EPMC11529865 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature