Private Epigenetic Pacemaker Detector Using Homomorphic Encryption

The epigenetic pacemaker (EPM) model uses DNA methylation data to predict human epigenetic age. The methylation values are collected from different individuals and are considered to be of medical importance. Sharing these data publicly among labs and other third parties for model calculation purposes may violate the privacy of personal medical records. The use of standard encryption approaches can prevent the exposure of these personal records to third parties when at rest, but running computations on the data requires decrypting it first, and thus exposing the entire data to the computing party. This work proposes computing EPM while limiting data exposure by employing cryptographic secure computing techniques including homomorphic encryption. Our protocol has rigorous privacy guarantees against passive computationally bounded adversaries in the two-server model. Our results show good correlation with low accuracy error between the model with and without encryption. These results can serve as a pilot for data security measures integrated in vast medical applications where personal privacy is imperative. 1