This study uses large-scale longitudinal brain MRI, lifestyle, and genomic data to predict individual trajectories of brain aging. We will also use cohort data to virtually simulate changes in lifestyle factors, such as physical activity, social participation, and sleep, and estimate their preventive effects. Based on these findings, we will visualize future brain states using digital twins, with the goal of developing personalized strategies to prevent brain aging.