Metabolic brain networks in aging and preclinical Alzheimer's disease
Abstract
Metabolic brain networks can provide insight into the network processes underlying progression from healthy aging to Alzheimer's disease. We explore the effect of two Alzheimer's disease risk factors, amyloid-β and ApoE ε4 genotype, on metabolic brain networks in cognitively normal older adults (N = 64, ages 69–89) compared to young adults (N = 17, ages 20–30) and patients with Alzheimer's disease (N = 22, ages 69–89). Subjects underwent MRI and PET imaging of metabolism (FDG) and amyloid-β (PIB). Normal older adults were divided into four subgroups based on amyloid-β and ApoE genotype. Metabolic brain networks were constructed cross-sectionally by computing pairwise correlations of metabolism across subjects within each group for 80 regions of interest. We found widespread elevated metabolic correlations and desegregation of metabolic brain networks in normal aging compared to youth and Alzheimer's disease, suggesting that normal aging leads to widespread loss of independent metabolic function across the brain. Amyloid-β and the combination of ApoE ε4 led to less extensive elevated metabolic correlations compared to other normal older adults, as well as a metabolic brain network more similar to youth and Alzheimer's disease. This could reflect early progression towards Alzheimer's disease in these individuals. Altered metabolic brain networks ofmore »
- Authors:
-
[1];
- University of California Berkeley, Berkeley, CA (United States). Helen Wills Neuroscience Institute
- University of California Berkeley, Berkeley, CA (United States). Helen Wills Neuroscience Institute; Leibniz Institute for Neurobiology, Magdeburg (Germany); Otto-von-Guericke University, Magdeburg (Germany). Clinic for Radiology and Nuclear Medicine
- University of California Berkeley, Berkeley, CA (United States). Helen Wills Neuroscience Institute; University of California San Francisco, San Francisco, CA (United States). Memory and Aging Center
- University of California Berkeley, Berkeley, CA (United States). Helen Wills Neuroscience Institute; Lawrence Berkeley National Laboratory, Berkeley, CA (United States). Division of Molecular Biophysics and Integrated Bioimaging
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1623708
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- NeuroImage: Clinical
- Additional Journal Information:
- Journal Volume: 17; Journal Issue: C; Journal ID: ISSN 2213-1582
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- Neurosciences & Neurology
Citation Formats
Arnemann, Katelyn L., Stöber, Franziska, Narayan, Sharada, Rabinovici, Gil D., and Jagust, William J. Metabolic brain networks in aging and preclinical Alzheimer's disease. United States: N. p., 2018.
Web. doi:10.1016/j.nicl.2017.12.037.
Arnemann, Katelyn L., Stöber, Franziska, Narayan, Sharada, Rabinovici, Gil D., & Jagust, William J. Metabolic brain networks in aging and preclinical Alzheimer's disease. United States. https://doi.org/10.1016/j.nicl.2017.12.037
Arnemann, Katelyn L., Stöber, Franziska, Narayan, Sharada, Rabinovici, Gil D., and Jagust, William J. Mon .
"Metabolic brain networks in aging and preclinical Alzheimer's disease". United States. https://doi.org/10.1016/j.nicl.2017.12.037. https://www.osti.gov/servlets/purl/1623708.
@article{osti_1623708,
title = {Metabolic brain networks in aging and preclinical Alzheimer's disease},
author = {Arnemann, Katelyn L. and Stöber, Franziska and Narayan, Sharada and Rabinovici, Gil D. and Jagust, William J.},
abstractNote = {Metabolic brain networks can provide insight into the network processes underlying progression from healthy aging to Alzheimer's disease. We explore the effect of two Alzheimer's disease risk factors, amyloid-β and ApoE ε4 genotype, on metabolic brain networks in cognitively normal older adults (N = 64, ages 69–89) compared to young adults (N = 17, ages 20–30) and patients with Alzheimer's disease (N = 22, ages 69–89). Subjects underwent MRI and PET imaging of metabolism (FDG) and amyloid-β (PIB). Normal older adults were divided into four subgroups based on amyloid-β and ApoE genotype. Metabolic brain networks were constructed cross-sectionally by computing pairwise correlations of metabolism across subjects within each group for 80 regions of interest. We found widespread elevated metabolic correlations and desegregation of metabolic brain networks in normal aging compared to youth and Alzheimer's disease, suggesting that normal aging leads to widespread loss of independent metabolic function across the brain. Amyloid-β and the combination of ApoE ε4 led to less extensive elevated metabolic correlations compared to other normal older adults, as well as a metabolic brain network more similar to youth and Alzheimer's disease. This could reflect early progression towards Alzheimer's disease in these individuals. Altered metabolic brain networks of older adults and those at the highest risk for progression to Alzheimer's disease open up novel lines of inquiry into the metabolic and network processes that underlie normal aging and Alzheimer's disease.},
doi = {10.1016/j.nicl.2017.12.037},
journal = {NeuroImage: Clinical},
number = C,
volume = 17,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2018},
month = {Mon Jan 01 00:00:00 EST 2018}
}
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β-Amyloid is Associated with Aberrant Metabolic Connectivity in Subjects with Mild Cognitive Impairment
journal, April 2014
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Neuronal activity regulates the regional vulnerability to amyloid-β deposition
journal, May 2011
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[18F]FDG PET signal is driven by astroglial glutamate transport
journal, January 2017
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Emerging concepts for the dynamical organization of resting-state activity in the brain
journal, December 2010
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The economy of brain network organization
journal, April 2012
- Bullmore, Ed; Sporns, Olaf
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From The Cover: Aging reduces neural specialization in ventral visual cortex
journal, August 2004
- Park, D. C.; Polk, T. A.; Park, R.
- Proceedings of the National Academy of Sciences, Vol. 101, Issue 35
Adaptive reconfiguration of fractal small-world human brain functional networks
journal, December 2006
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- Proceedings of the National Academy of Sciences, Vol. 103, Issue 51
Apolipoprotein E ε4 is associated with disease-specific effects on brain atrophy in Alzheimer's disease and frontotemporal dementia
journal, January 2009
- Agosta, Federica; Vossel, Keith A.; Miller, Bruce L.
- Proceedings of the National Academy of Sciences, Vol. 106, Issue 6
Spatial correlation between brain aerobic glycolysis and amyloid-β (Aβ) deposition
journal, September 2010
- Vlassenko, Andrei G.; Vaishnavi, S. Neil; Couture, Lars
- Proceedings of the National Academy of Sciences, Vol. 107, Issue 41
Genetic dissection of Alzheimer disease, a heterogeneous disorder.
journal, September 1995
- Schellenberg, G. D.
- Proceedings of the National Academy of Sciences, Vol. 92, Issue 19
Metabolic Brain Covariant Networks as Revealed by FDG-PET with Reference to Resting-State fMRI Networks
journal, October 2012
- Di, Xin; Biswal, and Alzheimer's Disease Neu, Bharat B.
- Brain Connectivity, Vol. 2, Issue 5
Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer's disease
journal, December 2007
- Chetelat, G.; Desgranges, B.; Landeau, B.
- Brain, Vol. 131, Issue 1
Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden
journal, April 2011
- Drzezga, Alexander; Becker, J. Alex; Van Dijk, Koene R. A.
- Brain, Vol. 134, Issue 6
Existing Pittsburgh Compound-B positron emission tomography thresholds are too high: statistical and pathological evaluation
journal, May 2015
- Villeneuve, Sylvia; Rabinovici, Gil D.; Cohn-Sheehy, Brendan I.
- Brain, Vol. 138, Issue 7
Regional brain hypometabolism is unrelated to regional amyloid plaque burden
journal, September 2015
- Altmann, Andre; Ng, Bernard; Landau, Susan M.
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