Enhancing Alzheimer’s Research with AI and Informatics: Strategies for Mining Brain Imaging Genomics Data

COEX 

Alzheimer’s disease (AD) is a major public health crisis, affecting millions worldwide, with a substantial social and economic burden. Effective strategies are urgently needed to discover new AD genes for disease modeling and drug development. Studying AD genetics using multimodal imaging and multi-omics data is becoming a rapidly growing field with distinct advantages in power over categorical diagnosis under imaging and omics traits as well as in capturing new insights into disease mechanism and heterogeneity from genetic determinants to omics-level molecular signatures, to brain imaging biomarkers, and to AD outcomes. In this talk, we will discuss AI and informatics strategies for discovering AD risk and protective genes through analyzing multidimensional genetics, omics, imaging and outcome data from landmark and local AD biobanks. We show that the wide availability of these rich biobank data, coupled with advances in trustworthy AI and informatics, provides enormous opportunities to contribute significantly to gene discovery in AD and to impact the development of new diagnostic, therapeutic and preventative approaches.