Resumen
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.
| Idioma original | English (US) |
|---|---|
| Número de artículo | 1495 |
| Publicación | Nature communications |
| Volumen | 13 |
| N.º | 1 |
| DOI | |
| Estado | Published - dic 2022 |
| Publicado de forma externa | Sí |
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Chemistry(all)
- Biochemistry, Genetics and Molecular Biology(all)
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En: Nature communications, Vol. 13, N.º 1, 1495, 12.2022.
Resultado de la investigación: Article › revisión exhaustiva
}
TY - JOUR
T1 - Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease
AU - Alzheimer’S Disease Neuroimaging Initiative (Adni)
AU - Duong, Michael Tran
AU - Das, Sandhitsu R.
AU - Lyu, Xueying
AU - Xie, Long
AU - Richardson, Hayley
AU - Xie, Sharon X.
AU - Yushkevich, Paul A.
AU - Weiner, Michael
AU - Aisen, Paul
AU - Petersen, Ronald
AU - Jack, Clifford R.
AU - Jagust, William
AU - Trojanowki, John Q.
AU - Toga, Arthur W.
AU - Beckett, Laurel
AU - Green, Robert C.
AU - Saykin, Andrew J.
AU - Morris, John C.
AU - Shaw, Leslie M.
AU - Liu, Enchi
AU - Montine, Tom
AU - Thomas, Ronald G.
AU - Donohue, Michael
AU - Walter, Sarah
AU - Gessert, Devon
AU - Sather, Tamie
AU - Jimenez-Maggiora, Gustavo
AU - Harvey, Danielle
AU - Bernstein, Matthew
AU - Fox, Nick
AU - Thompson, Paul
AU - Schuff, Norbert
AU - DeCarli, Charles
AU - Borowski, Bret
AU - Gunter, Jeff
AU - Senjem, Matt
AU - Vemuri, Prashanthi
AU - Jones, David
AU - Kantarci, Kejal
AU - Ward, Chad
AU - Koeppe, Robert A.
AU - Foster, Norm
AU - Reiman, Eric M.
AU - Chen, Kewei
AU - Mathis, Chet
AU - Landau, Susan
AU - Cairns, Nigel J.
AU - Householder, Erin
AU - Taylor-Reinwald, Lisa
AU - Cerbone, Brittany
N1 - Funding Information: This work presented in this manuscript was funded by the University of Pennsylvania Alzheimer’s Disease Core Center grant (National Institute on Aging P30 AG072979). The authors thank our lab members for helpful discussions and the ADNI/HABS investigators, staff, participants and families for their support. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A listing of ADNI consortium investigators can be found at the end of the article. Data collection and sharing for the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was funded by the National Institutes of Health (NIH U01 AG024904) and the Department of Defense (DOD ADNI award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering and through generous contributions from the following: AbbVie; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The ADNI grantee organization is the Northern California Institute for Research and Education and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California. Additional data used in the preparation of this article were obtained from the Harvard Aging Brain Study (HABS—P01AG036694; https://habs.mgh.harvard.edu). HABS was launched in 2010, funded by the National Institute on Aging. and is led by principal investigators R.A.S., MD and K.A.J., MD at Massachusetts General Hospital/Harvard Medical School in Boston, MA. Funding Information: This work presented in this manuscript was funded by the University of Pennsylvania Alzheimer’s Disease Core Center grant (National Institute on Aging P30 AG072979). The authors thank our lab members for helpful discussions and the ADNI/HABS investigators, staff, participants and families for their support. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database ( adni.loni.usc.edu ). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A listing of ADNI consortium investigators can be found at the end of the article. Data collection and sharing for the Alzheimer’s Disease Neuroimaging Initiative (ADNI) was funded by the National Institutes of Health (NIH U01 AG024904) and the Department of Defense (DOD ADNI award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering and through generous contributions from the following: AbbVie; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The ADNI grantee organization is the Northern California Institute for Research and Education and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for NeuroImaging at the University of Southern California. Additional data used in the preparation of this article were obtained from the Harvard Aging Brain Study (HABS—P01AG036694; https://habs.mgh.harvard.edu ). HABS was launched in 2010, funded by the National Institute on Aging. and is led by principal investigators R.A.S., MD and K.A.J., MD at Massachusetts General Hospital/Harvard Medical School in Boston, MA. Publisher Copyright: © 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85126850679&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85126850679&partnerID=8YFLogxK
U2 - 10.1038/s41467-022-28941-1
DO - 10.1038/s41467-022-28941-1
M3 - Article
C2 - 35314672
AN - SCOPUS:85126850679
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 1495
ER -