TY - JOUR
T1 - Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer's disease neuropathology
AU - Antoniades, Mathilde
AU - Srinivasan, Dhivya
AU - Wen, Junhao
AU - Erus, Guray
AU - Abdulkadir, Ahmed
AU - Mamourian, Elizabeth
AU - Melhem, Randa
AU - Hwang, Gyujoon
AU - Cui, Yuhan
AU - Govindarajan, Sindhuja Tirumalai
AU - Chen, Andrew A.
AU - Zhou, Zhen
AU - Yang, Zhijian
AU - Chen, Jiong
AU - Pomponio, Raymond
AU - Sotardi, Susan
AU - An, Yang
AU - Bilgel, Murat
AU - LaMontagne, Pamela
AU - Singh, Ashish
AU - Benzinger, Tammie
AU - Beason-Held, Lori
AU - Marcus, Daniel S.
AU - Yaffe, Kristine
AU - Launer, Lenore
AU - Morris, John C.
AU - Tosun, Duygu
AU - Ferrucci, Luigi
AU - Bryan, R. Nick
AU - Resnick, Susan M.
AU - Habes, Mohamad
AU - Wolk, David
AU - Fan, Yong
AU - Nasrallah, Ilya M.
AU - Shou, Haochang
AU - Davatzikos, Christos
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/11
Y1 - 2024/11
N2 - Background: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD). Methods: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42–85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Findings: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. Interpretation: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. Funding: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.
AB - Background: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer's disease (AD). Methods: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42–85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer's Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Findings: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. Interpretation: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. Funding: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.
KW - Ageing
KW - Alzheimer's disease
KW - Brain age
KW - Cognition
KW - Multimodal
UR - https://www.scopus.com/pages/publications/85206914012
UR - https://www.scopus.com/pages/publications/85206914012#tab=citedBy
U2 - 10.1016/j.ebiom.2024.105399
DO - 10.1016/j.ebiom.2024.105399
M3 - Article
C2 - 39437659
AN - SCOPUS:85206914012
SN - 2352-3964
VL - 109
JO - EBioMedicine
JF - EBioMedicine
M1 - 105399
ER -