Beta‐amyloid deposition and the aging brain
Open accessAbstract
A central issue in cognitive neuroscience of aging research is pinpointing precise neural mechanisms that determine cognitive outcome in late adulthood as well as identifying early markers of less successful cognitive aging. One promising biomarker is beta amyloid (Abeta) deposition. Several new radiotracers have been developed that bind to fibrillar Abeta providing sensitive estimates of amyloid deposition in various brain regions. Abeta imaging has been primarily used to study patients with Alzheimer's Disease (AD) and individuals with Mild Cognitive Impairment (MCI); however, there is now building data on Abeta deposition in healthy controls that suggest at least 20% and perhaps as much as a third of healthy older adults show significant deposition. Considerable evidence suggests amyloid deposition precedes declines in cognition and may be the initiator in a cascade of events that indirectly leads to age-related cognitive decline. We review studies of Abeta deposition imaging in AD, MCI, and normal adults, its cognitive consequences, and the role of genetic risk and cognitive reserve.
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AD is not driven by a single pathological process but by complex interactions among neurons and glial cells-including astrocytes, microglia, and oligodendrocytes-that contribute to synaptic dysfunction, neuroinflammation, white matter injury, and neuronal loss.
“AD is not driven by a single pathological process but rather by complex interactions among neurons and glial cells—including astrocytes, microglia, and oligodendrocytes—that contribute to synaptic dysfunction, neuroinflammation, white matter injury, and neuronal loss.”
From Diffusion MRI reveals amyloid plaque–associated cellular signatures through spatial transcriptomic integration (2026) · cites this paper as [3]
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Rolstad, S., Nordlund, A., Eckerström, C., Gustavsson, M. H., Zetterberg, H., & Wallin, A. (2009) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000203130 · Cited by 34 · see citing works
Jagust, W. J. (2009) · Current Opinion in Neurology · doi:10.1097/wco.0b013e32832d93c7 · Cited by 23 · see citing works
Amyloid + Activation = Alzheimer's?
Jagust, W. J. (2009) · Neuron · doi:10.1016/j.neuron.2009.07.008 · Cited by 15 · see citing works
POSTPARTUM THROMBOSIS OF A DEVELOPMENTAL VENOUS ANOMALY
Prasad, S., Hurst, R. W., & Kasner, S. E. (2009) · Neurology · doi:10.1212/01.wnl.0000338623.26818.5f · Cited by 9 · see citing works
IMAGING β-AMYLOID BURDEN IN AGING AND DEMENTIA
Linazasoro, G. (2008) · Neurology · doi:10.1212/01.wnl.0000318046.06992.24 · Cited by 7 · see citing works
Use of eINDs for evaluation of multiple related PET amyloid plaque imaging agents.
Skovronsky, D. (2008) · PubMed · Cited by 5 · see citing works
Rosenberg, P. B., Zhou, Y., Kumar, A., Ravert, H. T., Brašić, J. R., Ye, W., Alexander, M., Dannals, R. F., Galecki, J., Lyketsos, C. G., et al. (2008) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2008.05.874 · Cited by 2 · see citing works
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Flagged first, then by citations
Research works printed but not linked: 3
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- Raz N Kennedy KM 2009 A systems approach to age-related change: Neuroanatomical changes, their modifiers, and cognitive correlates Jagust W D’Esposito M Imaging the aging brain Ch 4 43 70 Oxford UP NYC
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Cited by
Sorted by citations
Lee, J., & Kim, H.-J. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.931536 · Cited by 310 · see citing works
Risk Factors for β-Amyloid Deposition in Healthy Aging: Vascular and Genetic Effects
Rodrigue, K. M., Rieck, J. R., Kennedy, K. M., Devous, M. D., Diaz-Arrastia, R., & Park, D. C. (2013) · JAMA Neurology · doi:10.1001/jamaneurol.2013.1342 · Cited by 249 · see citing works
Self-citationSchilling, T., & Eder, C. (2011) · Journal of Cellular Physiology · doi:10.1002/jcp.22675 · Cited by 117 · see citing works
Vision function abnormalities in Alzheimer disease
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LILRB2-mediated TREM2 signaling inhibition suppresses microglia functions
Zhao, P., Xu, Y., Jiang, L.-L., Fan, X., Ku, Z., Li, L., Liu, X., Deng, M., Arase, H., Zhu, J.-J., et al. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00550-y · Cited by 54 · see citing works
Han, X., Hu, R., Ping, X., Chen, J., Liu, J., Liu, Z., Jin, X., Gao, X., Lin, M., Zhao, Y., et al. (2026) · Alzheimer's & Dementia · doi:10.1002/alz.71908
Frontotemporal dementia: does structural MRI-based clustering match clinical syndromes?
Singh-Reilly, N., Sintini, I., Ali, F., Duffy, J. R., Clark, H. M., Utianski, R. L., Meade, G., Machulda, M. M., Satoh, R., Lowe, V. J., et al. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1771092
- Authors
- Rodrigue, K. M., Kennedy, K. M., & Park, D. C.
- Affiliations
- The University of Texas at Dallas (US)
- Corresponding author
- Park, Denise C.
- Venue
- Neuropsychology Review
- Published
- 2009-11-12
- Volume
- 19
- Issue
- 4
- Pages
- 436-450
- ISSN
- 1040-7308 (ISSN-L)
- 1573-6660
- PMC
- PMC2844114
- OpenAlex
- W2065971926
- Cited by
- 230
- References
- 86
- Citations by year
- 2026: 11 · 2025: 19 · 2024: 16 · 2023: 20 · 2022: 31 · 2021: 23 · 2020: 21 · 2019: 15 · 2018: 6 · 2017: 9 · 2016: 9 · 2015: 8 · 2014: 10 · 2013: 10 · 2012: 9
- FWCI
- 0.92
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Neuropsychology Review (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (RF1AG006265, R01AG006265, R37AG006265, AG-006265-23)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
- Keywords
- amyloid-beta deposition, cognitive aging, amyloid imaging, Alzheimer's disease, mild cognitive impairment, healthy older adults, radioactive tracers, genetic risk, cognitive reserve, age-related cognitive decline, biomarkers
- MeSH terms
- Aging, Brain, Cognition Disorders, Humans, Models, Neurological, Amyloid beta-Peptides, Genetic Predisposition to Disease, Plaque, Amyloid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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