TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation

Meng Yang, Chuwen Zhang,Xiaoji Wang,Xingmin Liu, Shisen Li, Jianye Huang,Zhimin Feng,Xiaohui Sun,Fang Chen, Shuang Yang,Ming Ni,Lin Li,Yanan Cao,Feng Mu

Cell Systems(2022)

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摘要
The statistical power of genome-wide association studies (GWASs) is affected by the effective sample size. However, the privacy and security concerns associated with individual-level genotype data pose great challenges for cross-institutional cooperation. The full-process cryptographic solutions are in demand but have not been covered, especially the essential principal-component analysis (PCA). Here, we present TrustGWAS, a complete solution for secure, large-scale GWAS, recapitulating gold standard results against PLINK without compromising privacy and supporting basic PLINK steps including quality control, linkage disequilibrium pruning, PCA, chi-square test, Cochran-Armitage trend test, covariate-supported logistic regression and linear regression, and their sequential combinations. TrustGWAS leverages pseudorandom number perturbations for PCA and multiparty scheme of multi-key homomorphic encryption for all other modules. TrustGWAS can evaluate 100,000 individuals with 1 million variants and complete QC-LD-PCA-regression workflow within 50 h. We further successfully discover gene loci associated with fasting blood glucose, consistent with the findings of the ChinaMAP project.
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关键词
TrustGWAS,multi-key homomorphic encryption,GWAS,CKKS,privacy-preserving computation,pseudorandom number,genome privacy
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