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Imaging the evolution and pathophysiology of Alzheimer disease
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Technologies for imaging the pathophysiology of Alzheimer disease (AD) now permit studies of the relationships between the two major proteins deposited in this disease - amyloid-β (Aβ) and tau - and their effects on measures of neurodegeneration and cognition in humans. Deposition of Aβ in the medial parietal cortex appears to be the first stage in the development of AD, although tau aggregates in the medial temporal lobe (MTL) precede Aβ deposition in cognitively healthy older people. Whether aggregation of tau in the MTL is the first stage in AD or a fairly benign phenomenon that may be transformed and spread in the presence of Aβ is a major unresolved question. Despite a strong link between Aβ and tau, the relationship between Aβ and neurodegeneration is weak; rather, it is tau that is associated with brain atrophy and hypometabolism, which, in turn, are related to cognition. Although there is support for an interaction between Aβ and tau resulting in neurodegeneration that leads to dementia, the unknown nature of this interaction, the strikingly different patterns of brain Aβ and tau deposition and the appearance of neurodegeneration in the absence of Aβ and tau are challenges to this model that ultimately must be explained.
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“These and other studies 13,24,133,134 strongly support the concept of AD as being an amyloid-provoked, or facilitated, tauopathy, although there is also evidence that both pathologies act in synergy 135 .”
From The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics (2022) · cites this paper as [13]
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Citations
Cites
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Amyloid oligomers exacerbate tau pathology in a mouse model of tauopathy
Selenica, M.-L. B., Brownlow, M., Jimenez, J. P., Lee, D. C., Pena, G., Dickey, C. A., Gordon, M. N., & Morgan, D. (2013) · Neurodegenerative Diseases · doi:10.1159/000337230 · Cited by 10,359
Sleep Drives Metabolite Clearance from the Adult Brain
Xie, L., Kang, H., Xu, Q., Chen, M. J., Liao, Y., Thiyagarajan, M., O’Donnell, J., Christensen, D. J., Nicholson, C., Iliff, J. J., et al. (2013) · Science · doi:10.1126/science.1241224 · Cited by 5,411
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
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B
Klunk, W. E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D. P., Bergström, M., Savitcheva, I., Huang, G., Estrada, S., et al. (2004) · Annals of Neurology · doi:10.1002/ana.20009 · Cited by 4,496
Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R., Hill, R., Hansen, L. A., & Katzman, R. (1991) · Annals of Neurology · doi:10.1002/ana.410300410 · Cited by 4,397
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-citationWhat is cognitive reserve? Theory and research application of the reserve concept
STERN, Y. (2002) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617702813248 · Cited by 3,951
Clinical and biomarker changes in dominantly inherited Alzheimer's disease
Bateman, R. J., Xiong, C., Benzinger, T. L. S., Fagan, A. M., Goate, A., Fox, N. C., Marcus, D. S., Cairns, N. J., Xie, X., Blazey, T. M., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1202753 · Cited by 3,814
Cited by
Sorted by citations
Items 101–200 of 610
Rodríguez, M. H., Arciniega-Martínez, I. M., García-Marín, I. D., Correa‐Basurto, J., & Rosales‐Hernández, M. C. (2020) · Molecular Neurobiology · doi:10.1007/s12035-020-02009-x · Cited by 51
Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer’s Disease
Rani, S., Dhar, S. B., Khajuria, A., Gupta, D., Jaiswal, P. K., Singla, N., Kaur, M., Singh, G., & Barnwal, R. P. (2023) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-023-01330-y · Cited by 48
Sang, Z., Song, Q., Cao, Z., Deng, Y., Tan, Z., & Zhang, L. (2021) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2021.113310 · Cited by 46
What’s the cut-point?: a systematic investigation of tau PET thresholding methods
Weigand, A. J., Maaß, A., Eglit, G. L., & Bondi, M. W. (2022) · Alzheimer s Research & Therapy · doi:10.1186/s13195-022-00986-w · Cited by 49
Pezzoli, S., Giorgio, J., Martersteck, A., Dobyns, L., Harrison, T. M., & Jagust, W. J. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13438 · Cited by 42
Self-citationGut Microbiota: Critical Controller and Intervention Target in Brain Aging and Cognitive Impairment
Li, H., Ni, J., & Qing, H. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.671142 · Cited by 44
Mieling, M., Meier, H., & Bunzeck, N. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105393 · Cited by 42
Association of Presynaptic Loss with Alzheimer's Disease and Cognitive Decline
Lan, G., Cai, Y. Q., Li, A., Liu, Z., Ma, S., Guo, T., & Initiative, A. D. N. (2022) · Annals of Neurology · doi:10.1002/ana.26492 · Cited by 42
Cassady, K. E., Adams, J. N., Chen, X., Maaß, A., Harrison, T. M., Landau, S. M., Baker, S. L., & Jagust, W. J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab122 · Cited by 46
Self-citationNavigating Early Alzheimer's Diagnosis: A Comprehensive Review of Diagnostic Innovations
Juganavar, A., Joshi, A., & Shegekar, T. (2023) · Cureus · doi:10.7759/cureus.44937 · Cited by 47
Influence of human gut microbiome on the healthy and the neurodegenerative aging
Borrego-Ruiz, A., & Borrego, J. J. (2024) · Experimental Gerontology · doi:10.1016/j.exger.2024.112497 · Cited by 43
Pereira, J. B., Harrison, T. M., Joie, R. L., Baker, S. L., & Jagust, W. J. (2020) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04669-x · Cited by 40
Self-citationGiorgio, J., Jagust, W. J., Baker, S. L., Landau, S. M., Peter Tiňo, B., Kourtzi, Z., & Initiative, A. D. N. (2022) · Nature Communications · doi:10.1038/s41467-022-28795-7 · Cited by 40
Self-citationOn the design of convolutional neural networks for automatic detection of Alzheimer's diseasePreprint
Liu, S., Yadav, C., Fernandez‐Granda, C., & Razavian, N. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.03740 · Cited by 41
Neurodegenerative Microbially-Shaped Diseases: Oxidative Stress Meets Neuroinflammation
Silva, D. F., Empadinhas, N., Cardoso, S. M., & Esteves, A. R. (2022) · Antioxidants · doi:10.3390/antiox11112141 · Cited by 44
Trajectories and contributing factors of neural compensation in healthy and pathological aging
Bunzeck, N., Steiger, T. K., Krämer, U. M., Luedtke, K., Marshall, L., Obleser, J., & Tune, S. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105489 · Cited by 43
Kazemeini, S., Nadeem-Tariq, A., Shih, R., Rafanan, J., Ghani, N., & Vida, T. A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252111720 · Cited by 41
Wang, M., Feng, L.-R., Li, Z., Ma, K., Chang, K.-W., Chen, X., Yang, P., Ji, S., Ma, Y., Han, H., et al. (2021) · Journal of Neuroinflammation · doi:10.1186/s12974-021-02166-3 · Cited by 37
Yang, A., Du, L., Gao, W., Liu, B., Chen, Y., Wang, Y., Liu, X., Lv, K., Zhang, W., Xia, H., et al. (2022) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims-22-7 · Cited by 38
Duffy, I. R., Boyle, A. J., & Vasdev, N. (2019) · Molecular Imaging · doi:10.1177/1536012119869070 · Cited by 38
Brain metabolic signatures across the Alzheimer’s disease spectrum
Sala, A., Caprioglio, C., Santangelo, R., Vanoli, E. G., Iannaccone, S., Magnani, G., & Perani, D. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04559-2 · Cited by 37
Llibre‐Guerra, J. J., Li, Y., Schindler, S. E., Gordon, B. A., Fagan, A. M., Morris, J. C., Benzinger, T. L. S., Hassenstab, J. J., Wang, G., Allegri, R., et al. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.17126 · Cited by 40
Devous, M. D., Fleisher, A., Pontecorvo, M. J., Lu, M., Siderowf, A. D., Navitsky, M. A., Kennedy, I. A., Southekal, S. S., Harris, T. S., & Mintun, M. A. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-200808 · Cited by 38
A Machine Learning–Based Approach to Discrimination of Tauopathies Using [ 18F ] PM‐PBB3 PET Images
Endo, H., Tagai, K., Ono, M., Ikoma, Y., Oyama, A., Matsuoka, K., Kokubo, N., Hirata, K., Sano, Y., Oya, M., et al. (2022) · Movement Disorders · doi:10.1002/mds.29173 · Cited by 36
Li, B., Chen, Y., Zhou, Y., Feng, X., Gu, G., Han, S., Cheng, N., Sun, Y., Zhang, Y., Cheng, J., et al. (2023) · Neural Regeneration Research · doi:10.4103/1673-5374.385839 · Cited by 42
Functional connectome through the human life span
Sun, L., Zhao, T., Liang, X., Xia, M., Li, Q., Liao, X., Gong, G., Wang, Q., Pang, C., Yu, Q., et al. (2024) · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition · doi:10.58530/2024/1294 · Cited by 42
Heo, Y., Kim, K., Kim, J., Jang, J., & Park, C. B. (2020) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.0c02349 · Cited by 36
Xu, Y., Zhao, M.-N., Zhou, D., Zheng, T., & Zhang, H. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.111360 · Cited by 38
Defective Autophagy and Mitophagy in Alzheimer’s Disease: Mechanisms and Translational Implications
Chen, J., He, H., Ye, Q., Feng, F., Wang, W., Gu, Y., Han, R., & Xie, C. (2021) · Molecular Neurobiology · doi:10.1007/s12035-021-02487-7 · Cited by 37
Sayed, N. S. E., Kandil, E. A., & Ghoneum, M. H. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.666502 · Cited by 38
Shi, L., Yu, X., Li, H., Wu, G.-S., & Luo, H. (2023) · Experimental Gerontology · doi:10.1016/j.exger.2023.112145 · Cited by 35
Yu, M., Risacher, S. L., Nho, K. T., Wen, Q., Oblak, A. L., Unverzagt, F. W., Apostolova, L. G., Farlow, M. R., Brosch, J. R., Clark, D. G., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113691 · Cited by 36
Neuroimaging biomarkers and CSF sTREM2 levels in Alzheimer’s disease: a longitudinal study
Nabizadeh, F., Seyedmirzaei, H., & Karami, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-66211-w · Cited by 36
A golden age of muscarinic acetylcholine receptor modulation in neurological diseases
Tobin, A. B. (2024) · Nature Reviews Drug Discovery · doi:10.1038/s41573-024-01007-1 · Cited by 38
Diagnosis and treatment of cognitive impairment
Arnim, C. A. F. V., Bartsch, T., Jacobs, A. H., Holbrook, J. A., Bergmann, P., Zieschang, T., Polidori, M. C., & Dodel, R. C. (2019) · Zeitschrift für Gerontologie und Geriatrie · doi:10.1007/s00391-019-01560-0 · Cited by 36
Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology
Han, F., Lee, J., Chen, X., Ziontz, J., Ward, T. J., Landau, S. M., Baker, S. L., Harrison, T. M., Jagust, W. J., & Initiative, A. D. N. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14296 · Cited by 42
Self-citationAdams, J. N., Maaß, A., Berron, D., Harrison, T. M., Baker, S. L., Thomas, W. P., Stanfill, M., & Jagust, W. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2504-20.2021 · Cited by 34
Self-citationSang, Z., Song, Q., Cao, Z., Deng, Y., & Zhang, L. (2021) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.1080/14756366.2021.1993845 · Cited by 33
Reelin reverts biochemical, physiological and cognitive alterations in mouse models of Tauopathy
Rossi, D., Gruart, A., Contreras-Murillo, G., Muhaisen, A., Ávila, J., Delgado-García, J. M., Pujadas, L., & Soriano, E. (2020) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101743 · Cited by 30
Mokarizadeh, N., Karimi, P., Erfani, M., Sadigh‐Eteghad, S., Maroufi, N. F., & Rashtchizadeh, N. (2020) · International Immunopharmacology · doi:10.1016/j.intimp.2020.106300 · Cited by 35
Wang, K., Shi, J., Zhou, Y. M., He, Y., Mi, J., Yang, J. L., Liu, S., Tang, X., Liu, W., Tan, Z., et al. (2021) · Bioorganic Chemistry · doi:10.1016/j.bioorg.2021.104879 · Cited by 32
Du, J., Li, A., Shi, D., Chen, X., Wang, Q., Liu, Z., Sun, K., Guo, T., & Initiative, A. D. N. (2023) · Neurology · doi:10.1212/wnl.0000000000207369 · Cited by 35
The neuroprotective and neural circuit mechanisms of acupoint stimulation for cognitive impairment
Zhang, Z., Chen, L., Guo, Y., Li, D., Zhang, J., Liu, L., Fan, W., Guo, T., Qin, S., Zhao, Y., et al. (2023) · Chinese Medicine · doi:10.1186/s13020-023-00707-x · Cited by 33
Royse, S. K., Cohen, A. D., Snitz, B. E., & Rosano, C. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.685957 · Cited by 31
Relationship between tau, neuroinflammation and atrophy in Alzheimer's disease: The NIMROD study
Su, L., Surendranathan, A., Huang, Y., Bevan-Jones, W. R., Passamonti, L., Hong, Y. T., Arnold, R. J., Rodríguez, P. V., Wang, Y., Mak, E., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.10.006 · Cited by 32
Baez-Lugo, S., Deza-Araujo, Y. I., Maradan, C., Collette, F., Antoine Lutz, A., Marchant, N. L., Chételat, G., Vuilleumier, P. O., Klimecki, O., Arenaza‐Urquijo, E. M., et al. (2023) · Nature Aging · doi:10.1038/s43587-022-00341-6 · Cited by 31
Tissot, C., Servaes, S., Lussier, F. Z., Ferrari‐Souza, J. P., Therriault, J., Ferreira, P. C. L., Bezgin, G., Bellaver, B., Leffa, D. T., Mathotaarachchi, S. S., et al. (2022) · Journal of Nuclear Medicine · doi:10.2967/jnumed.122.264434 · Cited by 30
Alzheimer's disease: Potential pathogenesis and imaging findings
Zhang, Y., Zhang, C., Liu, J., & Shao, H. (2023) · Open Research (University of Surrey) · doi:10.1002/viw.20230025 · Cited by 33
Association between periodontitis and Alzheimer's disease: A narrative review
Seyedmoalemi, M., & Saied‐Moallemi, Z. (2025) · IBRO Neuroscience Reports · doi:10.1016/j.ibneur.2024.12.004 · Cited by 29
The role of magnetic fields in neurodegenerative diseases
Riancho, J., de la Torre, J. R. S., Paz‐Fajardo, L., Limia, C., Santurtún, A., Cifra, M., Kourtidis, K., & Fdez-Arróyabe, P. (2020) · International Journal of Biometeorology · doi:10.1007/s00484-020-01896-y · Cited by 29
Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease
Dang, M., Chen, Q., Zhao, X. B., Chen, K., Li, X., Zhang, J., Lu, J., Ai, L., Chen, Y., & Zhang, Z. (2022) · Human Brain Mapping · doi:10.1002/hbm.26043 · Cited by 31
Lu, J., Zhang, Z., Wu, P., Liang, X., Zhang, H., Hong, J., Clement, C., Yen, T., Ding, S., Wang, M., et al. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103416 · Cited by 31
Ourry, V., Binette, A. P., St‐Onge, F., Strikwerda‐Brown, C., Chagnot, A., Poirier, J., Breitner, J. C. S., Arenaza‐Urquijo, E. M., Rabin, J. S., Buckley, R. F., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.09.003 · Cited by 30
Alzheimer’s Disease: From Amyloid to Autoimmune Hypothesis
Arshavsky, Y. I. (2020) · The Neuroscientist · doi:10.1177/1073858420908189 · Cited by 28
Aghili, M., Tabarestani, S., & Adjouadi, M. (2022) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2022.109582 · Cited by 31
Engineering NIR-II luminescent lanthanide nanoprobes for imaging brain diseases in vivo
Du, Y., Ni, S., Ma, Q., Song, X., & Yang, H. (2023) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2023.215401 · Cited by 29
Role of Mitochondrial Dysfunction in the Pathology of Amyloid-β
Huang, Z., Yan, Q., Wang, Y., Zou, Q., Li, J., Liu, Z., & Cai, Z. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200519 · Cited by 28
Sayed, N. S. E., Kandil, E. A., & Ghoneum, M. H. (2021) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2021/5525306 · Cited by 31
RetractedJansen, M. G., Geerligs, L., Claassen, J. A. H. R., Overdorp, E. J., Brazil, I. A., Kessels, R. P. C., & Oosterman, J. M. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.723728 · Cited by 28
Multimodal data integration via mediation analysis with high‐dimensional exposures and mediators
Zhao, Y., Li, L., & Initiative, A. D. N. (2022) · Human Brain Mapping · doi:10.1002/hbm.25800 · Cited by 25
Cucurbituril-Oriented Nanoplatforms in Biomedical Applications
Cheng, G., Luo, J., Liu, Y., Chen, X., Wu, Z., & Chen, T. (2020) · ACS Applied Bio Materials · doi:10.1021/acsabm.0c01061 · Cited by 29
Morphological integration of the human brain across adolescence and adulthood
Nadig, A., Seidlitz, J., McDermott, C. L., Liu, S., Bethlehem, R. A. I., Moore, T. M., Mallard, T. T., CLASEN, L. S., Blumenthal, J. D., Lalonde, F., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2023860118 · Cited by 27
Tufail, A. B., Ma, Y., Kaabar, M. K. A., Rehman, A. U., Khan, R., & Cheikhrouhou, O. (2021) · Mathematics · doi:10.3390/math9233101 · Cited by 28
Hojjati, S. H., Abbas Babajani-feremi, A., & Initiative, T. A. D. N. (2022) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2021.769982 · Cited by 28
Martini, A. C., Gross, T. J., Head, E., & Mapstone, M. E. (2022) · Neuron · doi:10.1016/j.neuron.2022.04.001 · Cited by 26
Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology
Gouilly, D., Rafiq, M., Nogueira, L., Salabert, A., Payoux, P., Péran, P., & Pariente, J. (2023) · Revue Neurologique · doi:10.1016/j.neurol.2022.12.006 · Cited by 31
End-to-end automatic pathology localization for Alzheimer’s disease diagnosis using structural MRI
Cao, G., Zhang, M., Wang, Y., Zhang, J., Han, Y., Xu, X., Huang, J., & Kang, G. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107110 · Cited by 28
FDG‐PET markers of heterogeneity and different risk of progression in amnestic MCI
Caminiti, S., Francesco, S. D., Tondo, G., Galli, A., Redolfi, A., & Perani, D. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.13385 · Cited by 27
Multi-Target-Directed Cinnamic Acid Hybrids Targeting Alzheimer’s Disease
Drakontaeidi, A., & Pontiki, E. A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25010582 · Cited by 28
The Effects of Amyloid and Tau on Functional Network Connectivity in Older Populations
Wales, R. M., & Leung, H.-C. (2021) · Brain Connectivity · doi:10.1089/brain.2020.0902 · Cited by 26
Takamiya, A., Casteele, T. V., Koole, M. J. B., Winter, F. D., Bouckaert, F., den Stock, J. V., Sunaert, S. G., Dupont, P. J., Vandenberghe, R. R., Laere, K. V., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-95206-0 · Cited by 27
Yu, Z., Si, X., Chen, Y., Chao, Y., Lin, C., Li, S., Zhang, X., Ming, D., & Li, Q. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab407 · Cited by 26
Qu, Y., Shi, L., Liu, Y., Huang, L., Luo, H., & Wu, G.-S. (2022) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2022/8878923 · Cited by 26
Wan, C., Liu, X.-Q., Chen, M., Ma, H., Wu, G.-L., Qiao, L., Cai, Y.-F., & Zhang, S. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-03889-y · Cited by 27
Hrybouski, S., Das, S. R., Xie, L., Wisse, L. E. M., Kelley, M., Lane, J., Sherin, M., DiCalogero, M., Nasrallah, I. M., Detre, J. A., et al. (2023) · Brain Communications · doi:10.1093/braincomms/fcad245 · Cited by 38
Ren, J., Wang, Q., Hong, H., & Tang, C. (2025) · Microorganisms · doi:10.3390/microorganisms13081956 · Cited by 28
Ryou, M., Chen, X., Cai, M., Wang, H., Jung, M. E., Metzger, D. B., Mallet, R. T., & Shi, X. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.674688 · Cited by 26
Wang, T., Yan, S., Shan, Y., Xue, H., Xing, Y., Bi, S., Chen, Z., Xi, H., Qi, Z., Tang, Y., et al. (2025) · Radiology · doi:10.1148/radiol.241463 · Cited by 24
Content-specific vulnerability of recent episodic memories in Alzheimer's disease
Grande, X., Berron, D., Maaß, A., Bainbridge, W. A., & Düzel, E. (2021) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2021.107976 · Cited by 27
Nonaka, H., Mino, T., Sakamoto, S., Oh, J. H., Watanabe, Y., Ishikawa, M., Tsushima, A., Amaike, K., Kiyonaka, S., Tamura, T., et al. (2022) · Chem · doi:10.1016/j.chempr.2022.11.005 · Cited by 24
Tau accumulation and atrophy predict amyloid independent cognitive decline in aging
Fonseca, C. S., Baker, S. L., Dobyns, L., Janabi, M., Jagust, W. J., & Harrison, T. M. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13654 · Cited by 25
Self-citationMourer, T., Ghalid, M. E., d’Enfert, C., & Bachellier‐Bassi, S. (2021) · Research in Microbiology · doi:10.1016/j.resmic.2021.103813 · Cited by 25
Xiao, G., Chen, Q., & Zhang, X. (2021) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2021.10.008 · Cited by 25
Optimizing quantification of MK6240 tau PET in unimpaired older adults
Harrison, T. M., Ward, T. J., Murphy, A., Baker, S. L., Dominguez, P. A., Koeppe, R. A., Vemuri, P., Lockhart, S. N., Jung, Y., Harvey, D. J., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119761 · Cited by 25
Self-citationLiu, W., Yu, Y., Zang, J., Liu, Y., Li, F.-R., Zhang, L., Guo, R., Kong, L., Ma, L.-Y., & Li, X. (2024) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.4c00109 · Cited by 23
Air pollution: a latent key driving force of dementia
Mohammadzadeh, M., Khoshakhlagh, A. H., & Grafman, J. H. (2024) · BMC Public Health · doi:10.1186/s12889-024-19918-4 · Cited by 26
Yuan, L., Sun, S., Pan, X., Zheng, L., Li, Y., Yang, J., & Wu, C. (2019) · Neurochemistry International · doi:10.1016/j.neuint.2019.104586 · Cited by 23
Hojjati, S. H., Feiz, F., Ozoria, S., Razlighi, Q. R., & Initiative, F. T. A. D. N. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-210419 · Cited by 22
Bhawal, R. P., Fu, Q., Anderson, E. T., Gibson, G. E., & Zhang, S. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222413188 · Cited by 24
Liu, X., Guo, L., Duan, B., Wu, J., & Wang, E. (2022) · NeuroToxicology · doi:10.1016/j.neuro.2022.08.003 · Cited by 23
Qin, J., Guan, Y., Li, Z., Guo, X., Zhang, M., Wang, D., & Tang, J. (2022) · Journal of Materials Chemistry B · doi:10.1039/d2tb01499h · Cited by 23
Kim, S. H., Choi, K. Y., Park, Y., McLean, C., Park, J., Lee, J. H., Lee, K., Kim, B. C., Huh, Y. H., Lee, K. H., et al. (2021) · Cells · doi:10.3390/cells10102697 · Cited by 23
MicroRNAs in the pathophysiology of Alzheimer’s disease and Parkinson's disease: an overview
Khezri, M. R., Yousefi, K., Zolbanin, N. M., & Ghasemnejad‐Berenji, M. (2022) · Molecular Neurobiology · doi:10.1007/s12035-022-02727-4 · Cited by 22
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Adams, J. N., Harrison, T. M., Maass, A., Baker, S. L., & Jagust, W. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1601-21.2021 · Cited by 22
Self-citationMi, J., He, Y., Yang, J., Zhou, Y., Zhu, G., Wu, A., Liu, W., & Sang, Z. (2022) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/j.bmcl.2022.128574 · Cited by 22
Wu, D., Chen, J., Luo, K., Li, H., Liu, T., Li, L., Dai, Z., Li, Y., Zhao, Y., & Fu, X. (2022) · Bioorganic Chemistry · doi:10.1016/j.bioorg.2022.105760 · Cited by 21
Zhao, H., Sun, M., Zhang, Y., Kong, W., Fan, L., Wang, K., Xu, Q., Chen, B., Dong, J., Shi, Y., et al. (2023) · Aging and Disease · doi:10.14336/ad.2023.0516 · Cited by 22
Šprung, J., Warner, D. O., Knopman, D. S., Petersen, R. C., Mielke, M. M., Jack, C. R., Lowe, V. J., Martin, D. P., Hanson, A. C., Schroeder, D. R., et al. (2020) · British Journal of Anaesthesia · doi:10.1016/j.bja.2020.01.015 · Cited by 20
Lu, M., Tan, L., Zhou, X., Yang, Z., Zhu, Q. C., Chen, J., Luo, H., & Wu, G.-S. (2020) · Biogerontology · doi:10.1007/s10522-020-09884-w · Cited by 21
Ramos‐Miguel, A., Jones, A. A., Petyuk, V., Barakauskas, V., Barr, A. M., Leurgans, S. E., Jager, P. L. D., Casaletto, K. B., Schneider, J. A., Bennett, D. A., et al. (2021) · Acta Neuropathologica · doi:10.1007/s00401-021-02282-7 · Cited by 20
Metadata
- Authors
- Jagust, W.
- Affiliations
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Jagust, William
- ORCID
- Jagust, William
- Venue
- Nature Reviews Neuroscience
- Published
- 2018-09-28
- Volume
- 19
- Issue
- 11
- Pages
- 687-700
- ISSN
- 1471-003X (ISSN-L)
- 1471-0048
- PMC
- PMC7032048
- OpenAlex
- W2894357926
- Cited by
- 604
- References
- 213
- Citations by year
- 2026: 73 · 2025: 85 · 2024: 89 · 2023: 94 · 2022: 76 · 2021: 85 · 2020: 58 · 2019: 40 · 2018: 2
- FWCI
- 7.13
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature reviews. Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (R01AG045611, R01AG062542, P01AG019724, R01AG034570)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, amyloid-beta, tau protein, neurodegeneration, brain atrophy, hypometabolism, medial parietal cortex, medial temporal lobe, cognitive decline, dementia, disease progression
- MeSH terms
- Aging, Alzheimer Disease, Brain, Humans, Amyloid beta-Peptides, tau Proteins, Disease Progression, Multimodal Imaging
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