I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies

Genome-wide Association Studies (GWASes) identify genomic variations that are statistically associated with a trait, such as disease, in group of individuals. Unfortunately, careless sharing GWAS statistics might give rise to privacy attacks. Several works attempted reconcile secure processing privacy-preserving releases GWASes. However, we highlight these approaches remain vulnerable if GWASes utilize overlapping sets individuals and variations. In conditions, show even when relying on state-of-the-art techniques for protecting releases, an adversary could reconstruct the up 28.6% participants, released 92.3% would enable membership inference We introduce I-GWAS, novel framework securely computes results multiple possibly interdependent I-GWAS continuously noise-free new genomes become available.