Alzheimer’s disease (AD) is a highly genetic disease with complex causes. In this study, we aimed to identify genetic risk factors for AD and develop a risk prediction model. People with AD benefit more from early intervention before obvious symptoms appear. Whole-genome sequencing data, proteomic data, and magnetic resonance imaging (MRI) data provide different information about AD. Genetic data from healthy subjects and patients can help identify genetic risk factors for AD. Proteomic data can directly reveal the cause of AD and help discover potential drug targets. MRI can inform future development of AD. Therefore, the integration of whole-genome sequencing data, proteomic data, and MRI has great potential to facilitate the development of risk prediction models to facilitate early screening and intervention of disease.
