Year: 2026
Type: article
Abstract: We developed a machine learning framework grounded in a computational model of brain function and FDG-PET imaging to predict Alzheimer’s disease (AD)-type tau across AD and related disorders (ADRD). The model was trained on 1088 research participants spanning normal aging and ADRD with FDG-PET and flortaucipir-PET (FTP-PET). Validation was conducted in: (1) a longitudinal subset of the training cohort ( n = 215), (2) Alzheimer’s Disease Neuroimaging Initiative ( n = 295), and (3) a heretogeneous clinical cohort ( n = 264; n = 28 with FTP-PET). Results showed that the model accurately predicted FTP-PET when applied at the participant-level ( R 2 ~ 0.34-0.71). It performed well in clinical scenarios, including classification of low versus high tau stages (79–95% accuracy) and prediction of tau in a heterogeneous clinical cohort without FTP-PET. These findings advance the understanding of the relationship between neurodegeneration and AD-type tau and provide a framework for estimating AD-type tau across ADRD.
Source: Nature Communications
Authors: Nick Corriveau-Lecavalier, Gemeng Zhang, Hugo Botha, Leland R. Barnard, Heather J. Wiste, Ellen Dicks, Venkatsampath R. Gogineni, Jeyeon Lee, Irene Sintini, Matthew L. Senjem, Christopher G. Schwarz, Petrice M. Cogswell, Derek R. Johnson, Jeffrey L. Gunter, Michael G. Kamykowski, Jonathan Graff-Radford, Vijay K. Ramanan, Julie A. Fields, Mary M. Machulda, Nikki H. Stricker, Bradley F. Boeve, Val J. Lowe, Kejal Kantarci, David S. Knopman, Jennifer L. Whitwell, Keith A. Josephs, Ronald C. Petersen, Clifford R. Jack, David T. Jones, or the Alzheimer’s Disease Neuroimaging Initiative
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $6,990
Funders: Foundation for the National Institutes of Health, Alzheimer's Association, Eli Lilly and Company, Pfizer, Biogen, F. Hoffmann-La Roche, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, GHR Foundation, Elsie and Marvin Dekelboum Family Foundation, Hanyang University, National Research Foundation of Korea, Eisai, Servier, H. Lundbeck A/S, Ministry of Science and ICT, South Korea, IXICO, National Institutes of Health, Genentech, Canadian Institutes of Health Research, National Institute on Aging, National Institute on Deafness and Other Communication Disorders, National Institute of Neurological Disorders and Stroke
Awards: G2487430503, G2512709480, G2796059794, G3108094803, G3158883161, Alzheimers Disease Patient Registry, G4079001475, G5235017436, G5367426553, G612749012, G6256152478, ADRC Consortium for Clarity in ADRD Research Through Imaging, Brain Aging and Alzheimer's Biomarker Classification Using Amyloid PET, tau PET, and Neurodegeneration on MRI: Developing the ATN system, Assessment of hyperphosphorylated tau PET binding in primary progressive aphasia, G9000338148, Disease pathways in the population determined by amyloid, tau, and neurodegeneration imaging biomarkers, The neurobiology of two distinct subtypes of neurodegenerative apraxia of speech: phenotypes of Alzheimer disease related 4-repeat tauopathies, Alzheimer's Disease Neuroimaging Initiative (ADNI4), Molecular and structural imaging in atypical Alzheimer's disease: a longitudinal study, Mayo Alzheimer's Disease Research Center, Longitudinal multi-modality imaging in non-fluent/agrammatic primary progressive aphasia, Mayo Alzheimer's Disease Research Center
OpenAlex ID: W7215991262