Blatt M[+], Gusev A[+], Polyakov Y[+], Goldwasser S[+]. Proceedings of the National Academy of Sciences. 2020
Homomorphic encryption (HE) is an exciting technique by which certain mathematical operations can be performed on encrypted data without requiring decryption. In this work, we developed an HE algorithm to perform efficient statistical tests for Genome-Wide Association Studies (GWAS) and subsequent polygenic risk prediction (PRS). As a proof of principle, we applied this algorithm to a real GWAS of 25,000 individuals and showed that it is highly accurate while outperforming previous approaches that require interactive, multi-party computation. This approach paves the way for multi-center GWAS collaboration without requiring sensitive data sharing, as well as crowd-sourced studies where participant data is entirely secure.
The method and code has been made publicly available and an eprint is available here.
Disclosure: A Gusev has consulted for Duality Technologies.