Persistent metabolic youth in the aging female brain

Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults (n = 205) to define their metabolic brain age....

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Detalles Bibliográficos
Autores principales: Goyal, Manu S., Blazey, Tyler M., Su, Yi, Couture, Lars E., Durbin, Tony J., Bateman, Randall J., Benzinger, Tammie L.-S., Morris, John C., Raichle, Marcus E., Vlassenko, Andrei G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Biological Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386682/
https://www.ncbi.nlm.nih.gov/pubmed/30718410
http://dx.doi.org/10.1073/pnas.1815917116
Descripción
Sumario:Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults (n = 205) to define their metabolic brain age. We find that throughout the adult life span the female brain has a persistently lower metabolic brain age—relative to their chronological age—compared with the male brain. The persistence of relatively younger metabolic brain age in females throughout adulthood suggests that development might in part influence sex differences in brain aging. Our results also demonstrate that trajectories of natural brain aging vary significantly among individuals and provide a method to measure this.

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