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

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

作者机构：BGI Shenzhen MGI Shenzhen 518083 Peoples R China Univ Copenhagen Dept Biol DK-2200 Copenhagen Denmark Shanghai Jiao Tong Univ Ruijin HospRes Unit Clin & Basic Res Metab Dis Chinese Acad Med SciSch MedNatl Clin Res Ctr Me Dept Endocrine & Metab DisShanghai Inst Endocrin Shanghai 200025 Peoples R China SJTU Inst Translat Med Natl Ctr Translat Med Shanghai Shanghai 200240 Peoples R China BGI Shenzhen Shenzhen 518083 Peoples R China BGI Shenzen MGI QingDao Qingdao 266000 Peoples R China SJTU BGI Innovat Res Ctr Shanghai Peoples R China 

出 版 物：《CELL SYSTEMS》 (Cell Syst.)

年 卷 期：2022年第13卷第9期

页      面：752-+页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 071009[理学-细胞生物学] 09[农学] 0901[农学-作物学] 090102[农学-作物遗传育种] 

基　　金：Ministry of Science and Technology of the People's Republic of China [SQ2020YFF0426292] National Key R&D Program of China [2020YFA0112800, 2020YFA0112801] CAMS Innovation Fund for Medical Sciences [2020-12M-5-002] 

主　　题：TrustGWAS multi-key homomorphic encryption GWAS CKKS privacy-preserving computation pseudorandom number genome privacy 

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-PCAregression workflow within 50 h. We further successfully discover gene loci associated with fasting blood glucose, consistent with the findings of the ChinaMAP project.