Project summary (16 lines): The brain constantly communicates with the rest of the body through a complex network of nerves, hormones, and immune cells. Brain-body communication is crucial for maintaining homeostasis and overall health. This communication can be affected by aging, as some parts of the brain shrink, some nerve cells lose their connections, and some blood vessels become clogged [1]. These changes can impair the brain’s ability to send and receive signals to and from the body, resulting in cognitive decline and physical deterioration. Therefore, studying how aging affects brain-body communication is essential for finding ways to prevent or treat age-related conditions and to promote healthy aging. Meanwhile, brain-body communication during aging is a complex and dynamic process that varies among individuals. To unlock the potential for personalized interventions, a deep comprehension at the individual level is paramount. Yet, comprehensive exploration of cellular-level brain-body communication in individuals has remained challenging due to a dearth of suitable tools and model systems. My proposal seeks to introduce an interdisciplinary approach, integrating an innovative single-whole-organism single-cell sequencing platform and cutting-edge machine learning methodologies, to construct aging trajectories. This innovation aims to elucidate age-induced alterations in brain-body communication at the individual resolution, enabling a profound understanding of these dynamics in complex organisms.