Brain aging patterns in a large and diverse cohort of 49,482 individuals.
Pubmed ID: 39147830
Pubmed Central ID: PMC11483219
Journal: Nature medicine
Publication Date: Oct. 1, 2024
Affiliation: ['Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.', 'Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD, USA.', 'Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, Baltimore, MD, USA.']
MeSH Terms: Humans, Male, Adult, Female, Aged, Aged, 80 and over, Cohort Studies, Aging, Middle Aged, Life Style, Magnetic Resonance Imaging, Brain, Atrophy
Grants: R01 MH123550, R01 AG066650, U01 AG068057, RF1 AG054409, P30 AG072979, R01 MH112847, HHSN271201600059C, S10 OD032285, R01 AG067103, R01 AG034161, P30 AG066546, R01 AG058533, R01 AG083865, ZIA AG000513, R01 AG085571, P30 AG028747, P01 AG003991, U24 NS130411, P01 AG026276, U19 AG033655, U24 AG074855, HHSN271201300284P, R01 AG054073, R56 AG064088, R01 AG080821
Authors: Völzke H, Yaffe K, Fan Y, Launer LJ, Davatzikos C, Erus G, Heckbert SR, Albert MS, Evans MK, Zonderman AB, Grabe HJ, Ferrucci L, Yang Z, An Y, Srinivasan D, Abdulkadir A, Nasrallah IM, Wen J, Mamourian E, Wolk DA, Resnick SM, Shou H, Govindarajan ST, Melhem R, Cui Y, Parmpi P, Wittfeld K, Bülow R, Frenzel S, Tosun D, Bilgel M, Yi D, Marcus DS, LaMontagne P, Benzinger TLS, Austin TR, Waldstein SR, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Toga AW, O'Bryant S, Chakravarty MM, Villeneuve S, Johnson SC, Morris JC, Nick Bryan R, Shinohara RT, Habes M, Lalousis PA, Koutsouleris N
Cite As: Yang Z, Wen J, Erus G, Govindarajan ST, Melhem R, Mamourian E, Cui Y, Srinivasan D, Abdulkadir A, Parmpi P, Wittfeld K, Grabe HJ, Bülow R, Frenzel S, Tosun D, Bilgel M, An Y, Yi D, Marcus DS, LaMontagne P, Benzinger TLS, Heckbert SR, Austin TR, Waldstein SR, Evans MK, Zonderman AB, Launer LJ, Sotiras A, Espeland MA, Masters CL, Maruff P, Fripp J, Toga AW, O'Bryant S, Chakravarty MM, Villeneuve S, Johnson SC, Morris JC, Albert MS, Yaffe K, Völzke H, Ferrucci L, Nick Bryan R, Shinohara RT, Fan Y, Habes M, Lalousis PA, Koutsouleris N, Wolk DA, Resnick SM, Shou H, Nasrallah IM, Davatzikos C. Brain aging patterns in a large and diverse cohort of 49,482 individuals. Nat Med 2024 Oct;30(10):3015-3026. Epub 2024 Aug 15.
Studies:
Abstract
Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.