A brain health framework with application to the study of neurodegeneration.

Abstract

An all-encompassing framework seems necessary for understanding brain health in the context of neurodegeneration, particularly due to Alzheimer's disease (AD). We argue that current views, dominated by the amyloid-beta hypothesis, oversimplify the complexity of brain degeneration. We propose a multi-scale, multi-entity approach, treating the brain as a complex system composed of interacting subsystems across various scales, from the nanoscale (genes and proteins) to the macroscale (cognition) and beyond. By redefining brain health through mathematical complexity, we emphasize the importance of integrating diverse biological, environmental, and lifestyle factors to account for the heterogeneity in AD presentations. This framework suggests that failures at different levels of brain function can lead to cascading effects that influence neurodegenerative trajectories. Additionally, it calls for a shift toward personalized treatment approaches that target multiple yet specific pathological mechanisms affecting an individual. We propose computational models as essential tools for simulating and testing these complex interactions. Through this framework, we aim to provide a deeper understanding of neurodegeneration, and advocate for more comprehensive and multi-factorial approaches in both research and clinical practice to advance the treatment of brain health disorders such as AD.