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Integration of neuroimaging signatures of aging and Alzheimer's with fluid biomarkers.

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Τίτλος: Integration of neuroimaging signatures of aging and Alzheimer's with fluid biomarkers.
Συγγραφείς: Gonzales MM; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA.; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA., Ho NH; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Wang DH; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Rashid T; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Brandigampala SR; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Dong M; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Martinez D; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Charisis S; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA., Hohman TJ; Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Seshadri S; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA., Davatzikos C; Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Maestre G; Departments of Neurosciences and Human Genetics, University of Texas Rio Valley Grande, Brownsville, Texas, USA., Kautz TF; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA., LaRoche A; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA., Young VM; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; School of Social and Behavioral Sciences, Arizona State University, Tempe, Arizona, USA., Sullivan AC; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA., Yaffe K; Departments of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA., Toledo JB; Nantz National Alzheimer Center, Stanley Appel Department of Neurology, Houston Methodist Hospital, Houston, Texas, USA., Habes M; The Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center, San Antonio, Texas, USA.; Neuroimage Analytics Laboratory (NAL) and the Biggs Institute Neuroimaging Core (BINC), Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio, Texas, USA.
Συλλογικό Έργο: Alzheimer's Disease Neuroimaging InitiativeHABS‐HD Study Team
Πηγή: Alzheimer's & dementia : the journal of the Alzheimer's Association [Alzheimers Dement] 2026 Oct; Vol. 22 (10), pp. e71889.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: John Wiley & Sons, Ltd Country of Publication: United States NLM ID: 101231978 Publication Model: Print Cited Medium: Internet ISSN: 1552-5279 (Electronic) Linking ISSN: 15525260 NLM ISO Abbreviation: Alzheimers Dement Subsets: MEDLINE
Imprint Name(s): Publication: 2020- : Hoboken, NJ : John Wiley & Sons, Ltd.
Original Publication: Orlando, FL : Elsevier, Inc.
Ιατρικοί όροι (MeSH): Alzheimer Disease*/diagnostic imaging , Alzheimer Disease*/blood , Alzheimer Disease*/pathology , Biomarkers*/blood , Aging*/pathology , Neuroimaging*/methods , Brain*/pathology , Brain*/diagnostic imaging, tau Proteins/blood ; Neurofilament Proteins/blood ; Humans ; Female ; Male ; Disease Progression ; Machine Learning ; Magnetic Resonance Imaging ; Aged ; Aged, 80 and over ; Atrophy
Περίληψη: Introduction: Machine learning algorithms applied to neuroimaging may aid diagnosis and disease monitoring. This study aimed to derive neuroimaging signatures of brain aging (Spatial Pattern of Atrophy for Recognition-Brain Age [SPARE-BA]) and Alzheimer's disease (SPARE-AD) in a diverse sample and to examine their associations with plasma biomarkers, diagnosis, and disease progression.
Methods: SPARE-BA and SPARE-AD were calculated using T1-images from 1297 participants without dementia. Associations between neuroimaging signatures and plasma biomarkers were assessed with partial correlations. Logistic regression and cox proportional hazard models evaluated diagnostic accuracy and clinical progression.
Results: SPARE-AD displayed the strongest association with plasma phosphorylated tau 217, whereas SPARE-BA correlated most strongly with plasma neurofilament light. The combination of neuroimaging signatures with plasma biomarkers achieved the highest diagnostic discriminability and strongest associations with clinical progression.
Discussion: Neuroimaging signatures of aging and Alzheimer's disease display distinct associations with plasma biomarkers. Neuroimaging signatures combined with plasma biomarkers may improve the detection and prediction of cognitive impairment.
(© 2026 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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Grant Information: R01AG085571 R01AG077472 P30AG094848 P30AG066546 R01AG083865 R01AG080821 R01AG059421 United States AG NIA NIH HHS; United States ALZ Alzheimer's Association; Texas Alzheimer's Research and Care Consortium Investigator Grant Program; Texas Council on Alzheimer's Disease and Related Disorders; T32AG021890 DKR Texas Alzheimer's Initiative
Contributed Indexing: Keywords: Alzheimer's disease; cognitive impairment; diagnosis; machine learning; neuroimaging; plasma biomarkers; prognosis
Substance Nomenclature: 0 (Biomarkers)
0 (tau Proteins)
0 (Neurofilament Proteins)
0 (neurofilament protein L)
Entry Date(s): Date Created: 20261017 Date Completed: 20261017 Latest Revision: 20261017
Update Code: 20261018
DOI: 10.1002/alz.71889
PMID: 42888952
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1552-5279
DOI:10.1002/alz.71889