Brain aging shows nonlinear transitions, suggesting a midlife “critical window” for metabolic intervention
Abstract
Understanding the key drivers of brain aging is essential for effective prevention and treatment of neurodegenerative diseases. Here, we integrate human brain and physiological data to investigate underlying mechanisms. Functional MRI analyses across four large datasets (totaling 19,300 participants) show that brain networks not only destabilize throughout the lifetime but do so along a nonlinear trajectory, with consistent temporal “landmarks” of brain aging starting in midlife (40s). Comparison of metabolic, vascular, and inflammatory biomarkers implicate dysregulated glucose homeostasis as the driver mechanism for these transitions. Correlation between the brain’s regionally heterogeneous patterns of aging and gene expression further supports these findings, selectively implicating GLUT4 (insulin-dependent glucose transporter) and APOE (lipid transport protein). Notably, MCT2 (a neuronal, but not glial, ketone transporter) emerges as a potential counteracting factor by facilitating neurons’ energy uptake independently of insulin. Consistent with these results, an interventional study of 101 participants shows that ketones exhibit robust effects in restabilizing brain networks, maximized from ages 40 to 60, suggesting a midlife “critical window” for early metabolic intervention.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (10)
Botond B. Antal
Department of Biomedical Engineering
Helena van Nieuwenhuizen
Laufer Center for Physical and Quantitative Biology
Anthony G. Chesebro
Department of Biomedical Engineering
Helmut H. Strey
Department of Biomedical Engineering
David T. Jones
Department of Neurology
Kieran Clarke
Department of Physiology, Anatomy, and Genetics
Corey Weistuch
Department of Medical Physics
Eva-Maria Ratai
Athinoula A. Martinos Center for Biomedical Imaging
Ken A. Dill
Laufer Center for Physical and Quantitative Biology
Lilianne R. Mujica-Parodi
Department of Biomedical Engineering