Variations of global brain asymmetry are associated with aging and related diseases.

Lateralization is a hallmark of brain organization, yet the structural basis underlying this phenomenon remains a critical, unresolved question in cognitive and systems neuroscience. In this study, we applied multivariate machine learning techniques to investigate variations of global brain asymmetry and their associations with cognitive functions, aging, and aging-related diseases, using large-scale datasets. Our findings revealed substantial and previously unknown structural differences between the hemispheres, and established key associations between structural asymmetries and lateralized functions. At the population level, we identified unique aging trajectories of hemispheric differences and uncovered diagnosis-specific variations in patients with Alzheimer's and Parkinson's disease, and in APOE ε4 carriers at genetic risk. Notably, we identified a "left hemi-aging" pattern that challenges the conventional "right hemi-aging" model. Together, these results advance our understanding of functional lateralization in the human brain and highlight the potential of global brain asymmetry as a biomarker for brain aging and related diseases.