Alzheimer's disease target and drug discovery by leveraging multiomics and electronic health data.

Abstract

Despite prolific genomic data from individuals with Alzheimer's disease (AD), translation into treatments has lagged. Here we applied Mendelian randomization to multiple AD genome-wide association studies and functional multiomics datasets to nominate druggable targets, identifying 19 targets for individuals of European ancestry and 7 for African ancestry. This included epoxide hydrolase 2 (EPHX2), for which we identified a protective missense variant (p.Arg287Gln). Experiments in induced pluripotent stem cell-derived neurons and cerebral organoids from patients with AD validated the protective role of p.Arg287Gln via reduced levels of EPHX2 and phosphorylated tau (pTau-181). Pharmacological inhibition of EPHX2 improved cognitive performance in the 5xFAD mouse model of AD. Finally, by leveraging electronic health data from 111,680 patients with mild cognitive impairment, we identified 12 drugs associated with reduced AD incidence, including trazodone (targeting ADRA1A) and baclofen (targeting GABBR1). Thus, integrating multiomics data, functional validation and electronic health data identifies new approaches for treating AD.