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Local and distant relationships between amyloid, tau and neurodegeneration in Alzheimer's Disease
Open accessAbstract
The relationships between β-amyloid (Aβ), tau and neurodegeneration within Alzheimer's Disease pathogenesis are not fully understood. To explore these associations in vivo, we evaluated 30 Aβ PET-positive patients (mean ± sd age 62.4 ± 8.3) with mild probable AD and 12 Aβ PET-negative healthy controls (HC) (mean ± sd age 77.3 ± 6.9) as comparison. All participants underwent 3 T MRI, 11C-PiB (Aβ) PET and 18F-AV1451 (tau) PET. Multimodal correlation analyses were run at both voxel- and region-of-interest levels. 11C-PiB retention in AD showed the most diffuse uptake pattern throughout association neocortex, whereas 18F-AV1451 and gray matter volume reduction (GMR) showed a progressive predilection for posterior cortices (p<0.05 Family-Wise Error-[FWE]-corrected). Voxel-level analysis identified negative correlations between 18F-AV1451 and gray matter peaking in medial and infero-occipital regions (p<0.01 False Discovery Rate-[FDR]-corrected). 18F-AV1451 and 11C-PiB were positively correlated in right parietal and medial/inferior occipital regions (p<0.001 uncorrected). 11C-PiB did not correlate with GMR at the voxel-level. Regionally, 18F-AV1451 was largely associated with local/adjacent GMR whereas frontal 11C-PiB correlated with GMR in posterior regions. These findings suggest that, in mild AD, tau aggregation drives local neurodegeneration, whereas the relationships between Aβ and neurodegeneration are not region specific and may be mediated by the interaction between Aβ and tau.
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“The occurrence of NFTs correlates well with spatial patterns of neuronal loss and is related to the degree of cognitive deficits [3,4].”
From Diffusion tensor imaging reveals whole-brain microstructural changes in the P301L mouse model of tauopathy. (2020) · cites this paper as [3]
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McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Alzheimer's disease: the amyloid cascade hypothesis
Hardy, J. A., & Higgins, G. A. (1992) · Science · doi:10.1126/science.1566067 · Cited by 7,484
Classification of primary progressive aphasia and its variants
Gorno-Tempini, M. L., Hillis, A. E., Weintraub, S., Kertesz, A., Mendez, M., Cappa, S. F., Ogar, J. M., Rohrer, J. D., Black, S., Boeve, B. F., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e31821103e6 · Cited by 5,141
Self-citationQuerfurth, H. W., & LaFerla, F. M. (2010) · New England Journal of Medicine · doi:10.1056/nejmra0909142 · Cited by 4,569
Jack, C. R., Knopman, D. S., Jagust, W. J., Petersen, R. C., Weiner, M. W., Aisen, P. S., Shaw, L. M., Vemuri, P., Wiste, H. J., Weigand, S. D., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(12)70291-0 · Cited by 4,396
Self-citationBrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics
Xia, M., Wang, J., & He, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068910 · Cited by 4,106
Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria
Dubois, B., Feldman, H. H., Jacova, C., Hampel, H., Molinuevo, J. L., Blennow, K., DeKosky, S. T., Gauthier, S., Selkoe, D., Bateman, R., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70090-0 · Cited by 3,321
Self-citationBraak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H., & Del Tredici, K. (2006) · Acta Neuropathologica · doi:10.1007/s00401-006-0127-z · Cited by 3,172
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Laforce, R. J., Soucy, J., Sellami, L., Dallaire‐Théroux, C., Brunet, F., Bergeron, D., Miller, B. L., & Ossenkoppele, R. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.06.2855 · Cited by 88
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Lin, L., Hua, F., Salinas, C. A., Young, C. L., Bussière, T., Apgar, J. F., Burke, J. M., Muralidharan, K. K., Rajagovindan, R., & Nestorov, I. A. (2022) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12759 · Cited by 21
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Uddin, M. S., Sumsuzzman, D. M., Jeandet, P., Behl, T., Rauf, A., Amran, M. S., & Ashraf, G. M. (2021) · Neurochemical Research · doi:10.1007/s11064-021-03325-x · Cited by 23
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Condello, C., Merz, G. E., Aoyagi, A., DeGrado, W. F., & Prusiner, S. B. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2655-9_16 · Cited by 18
Provost, K., Joie, R. L., Strom, A., Iaccarino, L., Edwards, L., Mellinger, T. J., Pham, J. Q., Baker, S. L., Miller, B. L., Jagust, W. J., et al. (2021) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x211001216 · Cited by 17
Self-citationHypometabolic mismatch with atrophy and tau pathology in mixed Alzheimer’s and Lewy body disease
Duong, M. T., Das, S. R., Khandelwal, P., Lyu, X., Xie, L., McGrew, E., Dehghani, N., McMillan, C. T., Lee, E. B., Shaw, L. M. J., et al. (2024) · Brain · doi:10.1093/brain/awae352 · Cited by 17
Meyer, P., McSweeney, M., Gonneaud, J., & Villeneuve, S. (2019) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2019.05.001 · Cited by 20
Disease stage–specific atrophy markers in Alzheimer's disease
Baumeister, H., Gellersen, H. M., Polk, S. E., Lattmann, R., Wuestefeld, A., Wisse, L. E. M., Glenn, T. W., Yakupov, R., Stark, M., Kleineidam, L., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70482 · Cited by 20
Moguilner, S., Herzog, R. A., Perl, Y. S., Medel, V., Cruzat, J., Coronel, C., Kringelbach, M. L., Deco, G., Ibáñez, A. M., & Tagliazucchi, E. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01449-0 · Cited by 15
Initiative, A. D. N., González‐Escamilla, G., Miederer, I., Grothe, M. J., Schreckenberger, M., Muthuraman, M., & Groppa, S. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00247-9 · Cited by 16
Differences in topological progression profile among neurodegenerative diseases from imaging data
Garbarino, S., Lorenzi, M., Oxtoby, N. P., Vinke, E. J., Marinescu, R. V., Eshaghi, A., Ikram, M. A., Niessen, W. J., Ciccarelli, O., Barkhof, F., et al. (2019) · eLife · doi:10.7554/elife.49298 · Cited by 16
Montandon, M., Herrmann, F. R., Garibotto, V., Rodriguez, C. K., Haller, S., & Giannakopoulos, P. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.12.002 · Cited by 15
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Hu, Y., Zhu, T., & Zhang, W. (2024) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2024.1344920 · Cited by 16
Hagihara, H., & Miyakawa, T. (2024) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyae047 · Cited by 16
Zilioli, A., Pancaldi, B., Baumeister, H., Busi, G., Misirocchi, F., Mutti, C., Florindo, I., Morelli, N., Mohanty, R., Berron, D., et al. (2024) · Brain Imaging and Behavior · doi:10.1007/s11682-024-00952-0 · Cited by 14
Network interdigitations of Tau and amyloid‐beta deposits define cognitive levels in aging
Kim, C. M., Montal, V., Diez, I. P., Orwig, W., Initiative, A. D. N., & Sepulcre, J. (2021) · Human Brain Mapping · doi:10.1002/hbm.25350 · Cited by 13
Raoufi, S., Salavati, Z., Komaki, A., Shahidi, ., & Zarei, M. (2023) · Metabolic Brain Disease · doi:10.1007/s11011-023-01168-9 · Cited by 14
Anderson, A. J., & Lin, F. V. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101788 · Cited by 13
Mapping the association between tau-PET and Aβ-amyloid-PET using deep learning
Ruwanpathirana, G. P., Williams, R. C., Masters, C. L., Rowe, C. C., Johnston, L. A., & Davey, C. E. (2022) · Scientific Reports · doi:10.1038/s41598-022-18963-6 · Cited by 13
Longitudinal associations between β-amyloid and cortical thickness in mild cognitive impairment
Mak, E., Zhang, L., Tan, C. H., Reilhac, A., Shim, H. Y., Wen, M. O. Q., Wong, Z. X., Chong, E. J. Y., Xu, X., Stephenson, M. C., et al. (2023) · Brain Communications · doi:10.1093/braincomms/fcad192 · Cited by 13
Zhou, Z., Wang, Q., Liu, L., Wang, Q., Zhang, X., Li, C., Liu, J., Wei, Y., Gao, J. H., Fu, L., et al. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01690-1 · Cited by 10
Tau polygenic risk scoring: a cost-effective aid for prognostic counseling in Alzheimer’s disease
Ramanan, V. K., Heckman, M. G., Lesnick, T. G., Przybelski, S. A., Cahn, E. J., Kosel, M., Murray, M. E., Mielke, M. M., Botha, H., Graff‐Radford, J., et al. (2022) · Acta Neuropathologica · doi:10.1007/s00401-022-02419-2 · Cited by 10
Hays, C. C., Zlatar, Z. Z., Meloy, M. J., Osuna, J., Liu, T. T., Galasko, D. R., & Wierenga, C. E. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-190504 · Cited by 12
Drenthen, G. S., Backes, W. H., Freeze, W. M., Jacobs, H. I. L., Verheggen, I. C. M., van Boxtel, M. P. J., Hoff, E. I., Verhey, F. R., & Jansen, J. F. A. (2022) · Journal of Alzheimer’s Disease · doi:10.3233/jad-220175 · Cited by 10
Ziontz, J., Harrison, T. M., Fonseca, C. S., Giorgio, J., Han, F., Lee, J., Jagust, W. J., & Initiative, A. D. N. (2024) · Human Brain Mapping · doi:10.1002/hbm.70083 · Cited by 10
Self-citationClear‐headed into old age: Resilience and resistance against brain aging—A PET imaging perspective
Hoenig, M. C., & Drzezga, A. E. (2022) · Journal of Neurochemistry · doi:10.1111/jnc.15598 · Cited by 9
Marcotte, C., Potvin, O., Collins, D. L., Rheault, S., & Duchesne, S. (2019) · Scientific Reports · doi:10.1038/s41598-019-49914-3 · Cited by 8
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Li, B., He, D., Li, X., & Guo, X. (2022) · Ageing and Neurodegenerative Diseases · doi:10.20517/and.2022.14 · Cited by 11
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Grao‐Cruces, E., Claro, C., la Paz, S. M., & Nóbrega, C. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24032944 · Cited by 15
Metadata
- Authors
- Iaccarino, L., Tammewar, G., Ayakta, N., Baker, S. L., Bejanin, A., Boxer, A. L., Gorno-Tempini, M. L., Janabi, M., Kramer, J. H., Lazaris, A., Lockhart, S. N., Miller, B. L., Miller, Z. A., O'Neil, J. P., Ossenkoppele, R., Rosen, H. J., Schonhaut, D. R., Jagust, W. J., & Rabinovici, G. D.
- Affiliations
- Vita-Salute San Raffaele University (IT)
- University of California, San Francisco (US)
- Lawrence Berkeley National Laboratory (US)
- University of California, Berkeley (US)
- Corresponding author
- Iaccarino, Leonardo
- ORCID
- Venue
- NeuroImage: Clinical
- Publisher
- Elsevier BV
- Published
- 2018
- Volume
- 17
- Pages
- 452-464
- ISSN
- 2213-1582 (ISSN-L)
- PMC
- PMC5684433
- OpenAlex
- W2756641284
- Cited by
- 165
- References
- 85
- Citations by year
- 2026: 10 · 2025: 13 · 2024: 22 · 2023: 18 · 2022: 22 · 2021: 18 · 2020: 20 · 2019: 25 · 2018: 17
- FWCI
- 12.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- NeuroImage Clinical (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- University of California
- FP7 People: Marie-Curie Actions (628812)
- National Institutes of Health (K23-AG048291, R01-AG038791, U01-AG045390, U54-NS092089)
- Tau Consortium
- National Institute on Aging (F32-AG050389, P50-AG023501, R01-AG034570, R01-AG045611)
- John Douglas French Alzheimer's Foundation
- National Institute of Neurological Disorders and Stroke (R01-NS050915)
- Ministero dell’Istruzione, dell’Università e della Ricerca
- Alzheimer's Association
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, amyloid-beta, tau protein, neurodegeneration, 11C-PiB PET, gray matter volume reduction
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Brain, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Amyloid beta-Peptides, tau Proteins, Positron-Emission Tomography
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