medRxivGenetic & Genomic MedicinePreprint
Genomic privacy risks in GWAS summary statistics
Abstract
The rapid advancement in sequencing technologies has exponentially increased the availability of genomic data, heightening concerns about data privacy. Despite the perceived safety of publicly accessible genome-wide association study (GWAS) summary statistics, we demonstrate that their combination with less sensitive high-dimensional phenotype data can lead to significant leakage of confidential genomic information. By transforming a linear regression model into linear programming constraints, we scrutinize the potential for genomic data recovery using GWAS summary statistics. We found that an effective phenotype-to-sample size ratio above 0.85 could enable full genotype recovery, and that above 0.16 was sufficient to enable individual identification. Certain non-European populations are especially vulnerable. The results stress the urgent need for stronger privacy protections in genomic research while maintaining data utility.
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Evaluating anonymized genome re-identification using polygenic predictions and its implications for data privacy
Théo Cavinato, Robin J. Hofmeister, Zoltán Kutalik·Nature CommunicationsPeer-reviewed·Oct 25, 2026
- Safeguarding Privacy in Genome Research: A Comprehensive Framework for Authors
Maryam Ghasemian, Lynette Hammond Gerido, Erman Ayday·bioRxiv·Sep 20, 2024
- Sharing GWAS summary statistics results in more citations: evidence from the GWAS catalog
Guillermo Reales, Chris Wallace·bioRxiv·Sep 27, 2022
- SECRET-GWAS: Confidential Computing for Population-Scale GWAS
Jonah Rosenblum, Juechu Dong, Satish Narayanasamy·bioRxiv·Apr 24, 2024
- Dissecting the genetics of complex traits using summary association statistics
Bogdan Pasaniuc, Alkes L Price·bioRxiv·Sep 1, 2016
- Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores
Brooks Paige, James Bell, … Daphne Ezer·Journal of Computational BiologyPeer-reviewed·Jan 5, 2021