Authors
Michael Tran Duong, Penn Medicine
Sandhitsu R. Das, University of Pennsylvania Perelman School of Medicine
Xueying Lyu, School of Engineering and Applied Science
Long Xie, Penn Medicine
Hayley Richardson, University of Pennsylvania Perelman School of Medicine
Sharon X. Xie, University of Pennsylvania Perelman School of Medicine
Paul A. Yushkevich, Penn Medicine
Michael Weiner, University of California, San Francisco
Paul Aisen, University of California, San Diego
Ronald Petersen, Mayo Clinic
Clifford R. Jack, Mayo Clinic
William Jagust, University of California, Berkeley
John Q. Trojanowki, University of Pennsylvania
Arthur W. Toga, University of Southern California
Laurel Beckett, University of California, Davis
Robert C. Green, Harvard Medical School
Andrew J. Saykin, Indiana University Bloomington
John C. Morris, Washington University in St. Louis
Leslie M. Shaw, University of Pennsylvania
Enchi Liu, Janssen Alzheimer Immunotherapy
Tom Montine, University of Washington
Ronald G. Thomas, University of California, San Diego
Michael Donohue, University of California, San Diego
Sarah Walter, University of California, San Diego
Devon Gessert, University of California, San Diego
Tamie Sather, University of California, San Diego
Gustavo Jimenez-Maggiora, University of California, San Diego
Danielle Harvey, University of California, Davis
Matthew Bernstein, Mayo Clinic
Nick Fox, University of London
Publication Date
12-1-2022
Journal
Nature Communications
URL with Digital Object Identifier
10.1038/s41467-022-28941-1
Abstract
Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.
