This three-year project aims to develop computational methods for integrating brain imaging, high throughput sequencing, electronic health records, and biological knowledge to study complex brain disorders. The project focuses on two main aspects:
1. Early detection and disease progression: Brain changes precede clinical symptoms by years or decades in complex brain disorders. Brain imaging, detecting signs like atrophy, offers early diagnostic potential distinguishing dementia from normal aging.
2. Genetic architecture and cognitive impairment: Beyond correlations, the study investigates direct and indirect impacts on cognitive decline, enhancing understanding of genetic underpinnings in brain disorders.
By leveraging AI algorithms and biomedical software on large-scale biobank data, the research aims to advance early diagnosis, prevention, and treatment of complex brain diseases.