This three-year project aims to develop computational and informatics methods for integrative analysis of brain imaging data, high throughput sequencing data, electronic health record data, and rich biological knowledge, with applications to various complex brain disorders. There are two major aspects in this project. First, in the study of complex brain disorders, evidence has shown that the brain changes years or even decades before the earliest clinical symptoms emerge. This may provide essential information regarding disease progression, as the earliest signs of disease may occur in the brain and can be measured before noticeable symptoms developed. Brain imaging has provided promising evidence to help differentiate dementia from normal aging and discover disease-sensitive signs like brain atrophy, to facilitate early diagnosis of complex brain disorders. Second, while most existing studies are focused on discovering correlations among the above-mentioned data, our research is focused on examining their direct and indirect effects on the progression of cognitive impairment, which helps us understanding the genetic architecture underlying complex brain disorders. We are working on both aspects and developing cutting-edge artificial intelligence algorithms and biomedical software for the analysis of large-scale biobank data, this effort will contribute to earlier diagnosis, prevention and treatment of complex brain diseases.
