A Network‐based Deep Learning Framework Translates GWAS and Multi‐Omics Findings to Pathobiology and Drug Repurposing for Alzheimer’s Disease

Human genome sequencing studies have identified numerous loci associated with complex diseases, including Alzheimer’s disease (AD). However, translating human genetic and genomic findings (i.e., genome‐wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge. Today, artificial intelligence and deep learning approaches that identify new risk genes and drug targets from human genome sequencing findings are enabling a more complete mechanistic understanding of disease biology. This is facilitating more rapid development of targeted therapeutic interventions for AD.