Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease
NeuroImage, ISSN: 1053-8119, Vol: 256, Page: 119228
2022
- 28Citations
- 81Usage
- 85Captures
- 1Mentions
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- Citations28
- Citation Indexes28
- CrossRef28
- Usage81
- Downloads73
- Abstract Views8
- Captures85
- Readers85
- 85
- Mentions1
- News Mentions1
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Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease.
Neuroimage. 2022 Apr 19;:119228. Authors: Millar PR, Luckett PH, Gordon BA, Benzinger TL, Schindler SE, Fagan AM, Cruchaga C, Bateman RJ, Allegri R, Jucker M, Lee JH, Mori H, Salloway SP, Yakushev I, Morris JC, Ances BM, Dominantly Inherited Alzheimer Network PubMed: 35452806 Submit Comment
Article Description
“Brain-predicted age” quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18–89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S1053811922003524; http://dx.doi.org/10.1016/j.neuroimage.2022.119228; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85129731315&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/35452806; https://linkinghub.elsevier.com/retrieve/pii/S1053811922003524; https://digitalcommons.wustl.edu/oa_4/1601; https://digitalcommons.wustl.edu/cgi/viewcontent.cgi?article=2599&context=oa_4; https://dx.doi.org/10.1016/j.neuroimage.2022.119228
Elsevier BV
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