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Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

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dc.contributor.author Millar, Peter R.
dc.contributor.author Gordon, Brian A.
dc.contributor.author Luckett, Patrick H.
dc.contributor.author Benzinger, Tammie L.S.
dc.contributor.author Cruchaga, Carlos
dc.contributor.author Fagan, Anne M.
dc.contributor.author Hassenstab, Jason
dc.contributor.author Perrin, Richard J.
dc.contributor.author Schindler, Suzanne E.
dc.contributor.author Allegri, Ricardo Francisco
dc.contributor.author Day, Gregory S.
dc.contributor.author Farlow, Martin R.
dc.contributor.author Mori, Hiroshi
dc.contributor.author Nübling, Georg
dc.contributor.author Dominantly Inherited Alzheimer Network
dc.contributor.author Bateman, Randall J.
dc.contributor.author Morris, John C.
dc.contributor.author Ances, Beau M.
dc.date.accessioned 2023-08-30T14:39:56Z
dc.date.available 2023-08-30T14:39:56Z
dc.date.issued 2023-01-06
dc.identifier.citation Millar, P.R., Gordon, B.A., Luckett, P.H., Benzinger, T.L.S., Cruchaga, C., Fagan, A.M., Hassenstab, J., Perrin, R.J., Schindler, S.E., Allegri, R.F., Day, G.S., Farlow, M.R., Mori, H., Nübling, G., Dominantly Inherited Alzheimer Network, Bateman, R.J., Morris, J.C., Ances, B.M., 2023. Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study. Elife 12, e81869. https://doi.org/10.7554/eLife.81869 es_ES
dc.identifier.uri https://doi.org/10.7554/eLife.81869
dc.identifier.uri https://repositorio.fleni.org.ar/xmlui/handle/123456789/817
dc.description.abstract Background: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. es_ES
dc.language.iso eng es_ES
dc.publisher eLife Sciences Publications es_ES
dc.rights info:eu-repo/semantics/openAccess
dc.subject Alzheimer Disease es_ES
dc.subject Enfermedad de Alzheimer es_ES
dc.subject Amyloid beta-Peptides es_ES
dc.subject Péptidos beta-Amiloides es_ES
dc.subject Cognitive Dysfunction es_ES
dc.subject Disfunción Cognitiva es_ES
dc.subject Magnetic Resonance Imaging es_ES
dc.subject Imagen por Resonancia Magnética es_ES
dc.title Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study es_ES
dc.type info:eu-repo/semantics/article es_ES
dc.type info:eu-repo/semantics/publishedVersion
dc.description.fil Fil: Allegri, Ricardo Francisco. Fleni. Departamento de Neurología. Servicio de Neurología Cognitiva, Neuropsicología y Neuropsiquiatría. Centro de Memoria y Envejecimiento; Argentina.
dc.relation.ispartofVOLUME 12
dc.relation.ispartofCOUNTRY Reino Unido
dc.relation.ispartofCITY Cambridge
dc.relation.ispartofTITLE eLife
dc.relation.ispartofISSN 2050-084X
dc.type.snrd info:ar-repo/semantics/artículo es_ES

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