Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Alzheimer’S Disease Neuroimaging Initiative (Adni)

doi:10.1038/s41467-022-28941-1

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Alzheimer’S Disease Neuroimaging Initiative (Adni)

Neurology

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

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 (N_M) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/N_M clusters with differing limbic and cortical patterns. The canonical group was defined as the T/N_M 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/N_M mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD.

Original language	English (US)
Article number	1495
Journal	Nature communications
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41467-022-28941-1
State	Published - Dec 2022

Funding

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. 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.

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

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title = "Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer{\textquoteright}s disease",

abstract = "Alzheimer{\textquoteright}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{\textquoteright}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.",

author = "{Alzheimer{\textquoteright}S Disease Neuroimaging Initiative (Adni)} and Duong, {Michael Tran} and Das, {Sandhitsu R.} and Xueying Lyu and Long Xie and Hayley Richardson and Xie, {Sharon X.} and Yushkevich, {Paul A.} and Michael Weiner and Paul Aisen and Ronald Petersen and Jack, {Clifford R.} and William Jagust and Trojanowki, {John Q.} and Toga, {Arthur W.} and Laurel Beckett and Green, {Robert C.} and Saykin, {Andrew J.} and Morris, {John C.} and Shaw, {Leslie M.} and Enchi Liu and Tom Montine and Thomas, {Ronald G.} and Michael Donohue and Sarah Walter and Devon Gessert and Tamie Sather and Gustavo Jimenez-Maggiora and Danielle Harvey and Matthew Bernstein and Nick Fox and Paul Thompson and Norbert Schuff and Charles DeCarli and Bret Borowski and Jeff Gunter and Matt Senjem and Prashanthi Vemuri and David Jones and Kejal Kantarci and Chad Ward and Koeppe, {Robert A.} and Norm Foster and Reiman, {Eric M.} and Kewei Chen and Chet Mathis and Susan Landau and Cairns, {Nigel J.} and Erin Householder and Lisa Taylor-Reinwald and Mesulam, {Marek Marsel}",

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doi = "10.1038/s41467-022-28941-1",

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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 - Mesulam, Marek Marsel

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.

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Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Abstract

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