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Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Open accessAbstract
Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of beta-amyloid (Abeta) peptide, ultimately leading to formation of Abeta plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain beta-amyloidosis are reductions in CSF Abeta(42) and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.
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“Studies of non-demented elderly cohorts overall report approximately 20–40% are PIB-positive [67, 68, 71–78].”
From Brain aging, Alzheimer's disease, and mitochondria (2011) · cites this paper as [76]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These investigations have established that volumetric decline occurs initially in medial temporal lobe grey matter, following tau protein deposition, and is closely correlated to cognitive decline.”
From White matter microstructural abnormality precedes cortical volumetric decline in Alzheimer’s disease: evidence from data-driven disease progression modelling (2022) · cites this paper as Jack Jr. et al 2010
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“On the regional level, abnormality is evident in medial temporal lobe areas first (hippocampus and entorhinal cortex), then in lateral temporal lobe areas (mid-temporal gyrus and fusiform gyrus) and finally in frontal lobe areas (Jack Jr. et al 2010, Young et al 2014).”
From White matter microstructural abnormality precedes cortical volumetric decline in Alzheimer’s disease: evidence from data-driven disease progression modelling (2022) · cites this paper as Jack Jr. et al 2010
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“because measures of all biomarkers studied to date have considerable overlap with those found other types of dementia (as well the cognitively normal elderly population), it remains difficult to determine whether or not cognitive impairment is due to AD or another more dominant and concurrent process.”
From Accuracy of the Clinical Diagnosis of Alzheimer Disease at National Institute on Aging Alzheimer Disease Centers, 2005–2010 (2012) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“it is Tau pathology and synapse loss that temporally correlate with cognitive impairment and precede overt neurodegeneration (Jack et al., 2010; Scheff et al., 2006; Spires-Jones and Hyman, 2014”
From Changes in the Synaptic Proteome in Tauopathy and Rescue of Tau-Induced Synapse Loss by C1q Antibodies (2018) · cites this paper as Jack et al., 2010
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“Amyloid accumulation probably starts many years before the onset of symptoms,2,26,27 and initiation of anti-amyloid treatment only after dementia develops may be too late to affect the clinical course of the disease.28”
From Two Phase 3 Trials of Bapineuzumab in Mild-to-Moderate Alzheimer's Disease (2014) · cites this paper as [26]
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“Firstly, cognitive decline is more closely correlated to neurodegeneration than tau accumulation (Jack Jr. et al 2010).”
From White matter microstructural abnormality precedes cortical volumetric decline in Alzheimer’s disease: evidence from data-driven disease progression modelling (2022) · cites this paper as Jack Jr. et al 2010
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“Alzheimer’s disease (AD) is characterized by deposition of hallmark pathological peptides and neurodegeneration that progress across partially overlapping neuroanatomical and temporal axes1,2.”
From Integrated multimodal cell atlas of Alzheimer’s disease (2024) · cites this paper as [2]
In the citing paper
“Autosomal dominant mutations to the MAPT (tau) gene lead to neuronal tangle pathology and frontotemporal dementia but not to amyloid plaques 122,123 , suggesting that tau pathology does not induce Aβ pathology.”
From The amyloid hypothesis in Alzheimer disease: new insights from new therapeutics (2022) · cites this paper as [123]
In the citing paper
“Amyloid plaques appear a decade or two before clinical symptoms of AD, but it is tau pathology and synapse loss that correlate best with cognitive impairment during disease progression (Jack et al., 2010).”
From Microglia in Alzheimer’s disease (2018) · cites this paper as Jack et al., 2010
In the citing paper
“Extensive biomarker and imaging studies indicate that amyloid-β aggregation is the earliest pathological event in Alzheimer’s disease, followed at a later stage by pathological changes of tau aggregation extending beyond the limbic system to the neocortex, which correlates with brain atrophy and cognitive decline2,3.”
From Interplay between innate immunity and Alzheimer disease: APOE and TREM2 in the spotlight (2018) · cites this paper as [2]
In the citing paper
“Their timeline states that in individuals who develop AD, Aβ plaque deposition and reduced CSF Aβ occur first. Next, CSF tau levels rise. These changes manifest years before clinical signs or symptoms develop. Later on hippocampal atrophy appears, followed shortly thereafter by memory decline and eventually dementia. Full progression from Aβ changes to clinical decline takes approximately 10 to 20”
From The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives (2014) · cites this paper as [205]
In the citing paper
“Plaque formation rates also vary over time [217]. After a period of rapid accumulation, plaque deposition gradually slows and by the time symptoms manifest plaque deposition is essentially done [20, 205, 218].”
From The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives (2014) · cites this paper as [205]
In the citing paper
“data argue symptoms generally manifest only after plaques stop forming (Figure 5) [205, 216, 217].”
From The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives (2014) · cites this paper as [205]
In the citing paper
“As people meeting preclinical AD criteria may remain cognitively stable for many years [205, 214], these trials will take a long time to complete.”
From The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives (2014) · cites this paper as [205]
In the citing paper
“The new AD biological framework and the model of pathologic AD biomarkers from Jack and colleagues 18 conceptualize a progressive sequence of measurable biochemical, neurophysiological, and neuroanatomical alterations that can be detected years before psychometrically and clinically noticeable deterioration in cognition, behavior, and function.”
From The Alzheimer’s Disease Clinical Spectrum (2019) · cites this paper as [18]
In the citing paper
“The neuropathological changes that are quintessential for AD diagnosis—namely, the development of amyloid plaques and tau tangles—are considered to develop years before onset of the cognitive changes that characterize AD dementia [26].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [26]
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Citations
Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
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
Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., Roses, A. D., Haines, J. L., & Pericak-Vance, M. A. (1993) · Science · doi:10.1126/science.8346443 · Cited by 9,429
Mild cognitive impairment as a diagnostic entity
Petersen, R. C. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01388.x · Cited by 7,864
Self-citationImaging 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
Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70178-3 · Cited by 4,411
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
Interplay between Cortical Spreading Depolarization and Seizures
Kramer, D. R., Fujii, T., Ohiorhenuan, I. E., & Liu, C. Y. (2017) · Stereotactic and Functional Neurosurgery · doi:10.1159/000452841 · Cited by 3,721
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Items 1,001–1,077 of 1,077
Preclinical AD Workgroup staging: Pathological correlates and potential challenges
Jicha, G. A., Abner, E. L., Schmitt, F. A., Kryscio, R. J., Riley, K. P., Cooper, G. E., Stiles, N., Mendiondo, M. S., Smith, C. D., Van Eldik, L. J., et al. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.02.018 · Cited by 71
Emerging β-amyloid pathology and accelerated cortical atrophy
Mattsson, N., Insel, P. S., Nosheny, R., Tosun, D., Trojanowski, J. Q., Shaw, L. M., Jack, C. R., Donohue, M. C., & Weiner, M. W. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.446 · Cited by 71
Self-citationState of the science on brain insulin resistance and cognitive decline due to Alzheimer's disease
Rhea, E. M., Leclerc, M., Yassine, H. N., Capuano, A. W., Tong, H., Petyuk, V. A., Macauley, S. L., Fioramonti, X., Carmichael, O., Calon, F., et al. (2023) · Aging and disease · doi:10.14336/ad.2023.0814 · Cited by 70
Early diagnosis of Alzheimer's disease from elevated olfactory mucosal miR-206 level.
Moon, J., Lee, S.-T., Kong, I. G., Byun, J.-I., Sunwoo, J.-S., Shin, J.-W., Shim, J.-Y., Park, J.-H., Jeon, D., Jung, K.-H., et al. (2016) · Scientific Reports · doi:10.1038/srep20364 · Cited by 69
The application of cerebrospinal fluid biomarkers in early diagnosis of Alzheimer disease
Blennow, K., & Zetterberg, H. (2013) · Medical Clinics of North America · doi:10.1016/j.mcna.2012.12.012 · Cited by 69
Knopman, D. S., Jack, C. R., Wiste, H. J., Weigand, S. D., Vemuri, P., Lowe, V. J., Kantarci, K., Gunter, J. L., Senjem, M. L., Mielke, M. M., et al. (2013) · JAMA Neurology · doi:10.1001/jamaneurol.2013.182 · Cited by 68
Self-citationLongitudinal trajectories of everyday function by diagnostic status
Farias, S. T., Chou, E., Harvey, D. J., Mungas, D., Reed, B., DeCarli, C., Park, L. Q., & Beckett, L. (2013) · Psychology and Aging · doi:10.1037/a0034069 · Cited by 68
Marinescu, R. V., Oxtoby, N. P., Young, A. L., Bron, E. E., Toga, A. W., Weiner, M. W., Barkhof, F., Fox, N. C., Eshaghi, A., Toni, T., et al. (2021) · Machine Learning for Biomedical Imaging · doi:10.59275/j.melba.2021-2dcc · Cited by 68
Self-citationWojdała, A. L., Bellomo, G., Gaetani, L., Toja, A., Chipi, E., Shan, D., Chiasserini, D., & Parnetti, L. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106356 · Cited by 70
Hippocampal Deficits in Amyloid-β-Related Rodent Models of Alzheimer’s Disease
Vyas, Y., Montgomery, J. M., & Cheyne, J. E. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00266 · Cited by 66
Lloret, M.-A., Cervera-Ferri, A., Nepomuceno, M., Monllor, P., Esteve, D., & Lloret, A. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21031168 · Cited by 68
Watanabe, Y., Kitamura, K., Nakamura, K., Sanpei, K., Wakasugi, M., Yokoseki, A., Onodera, O., Ikeuchi, T., Kuwano, R., Momotsu, T., et al. (2016) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000442585 · Cited by 65
Boeve, B., Bove, J., Brannelly, P., Brushaber, D., Coppola, G., Dever, R., Dheel, C., Dickerson, B., Dickinson, S., Faber, K., et al. (2020) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.06.4947 · Cited by 61
Self-citationAlliance for aging research AD biomarkers work group: structural MRI
Jack, C. R. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.09.011 · Cited by 64
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Alexopoulos, P., Kriett, L., Haller, B., Klupp, E., Gray, K., Grimmer, T., Laskaris, N., Förster, S., Perneczky, R., Kurz, A., et al. (2014) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2014.03.006 · Cited by 62
Olde Rikkert, M. G. M., Verhey, F. R., Blesa, R., von Arnim, C. A. F., Bongers, A., Harrison, J., Sijben, J., Scarpini, E., Vandewoude, M. F. J., Vellas, B., et al. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-141305 · Cited by 61
Criteria for the neuropathological diagnosis of dementing disorders: routes out of the swamp?
Jellinger, K. A. (2009) · Acta Neuropathologica · doi:10.1007/s00401-008-0466-z · Cited by 60
Hafkemeijer, A., Möller, C., Dopper, E. G. P., Jiskoot, L. C., van den Berg-Huysmans, A. A., van Swieten, J. C., van der Flier, W. M., Vrenken, H., Pijnenburg, Y. A. L., Barkhof, F., et al. (2016) · Journal of Alzheimer’s Disease · doi:10.3233/jad-150695 · Cited by 57
Role of Family History for Alzheimer Biomarker Abnormalities in the Adult Children Study
Xiong, C. (2011) · Archives of Neurology · doi:10.1001/archneurol.2011.208 · Cited by 56
Mental retirement and health selection: Analyses from the U.S. Health and Retirement Study
Clouston, S. A. P., & Denier, N. (2017) · Social Science & Medicine · doi:10.1016/j.socscimed.2017.01.019 · Cited by 56
Effects of ApoE4 and maternal history of dementia on hippocampal atrophy
Andrawis, J. P., Hwang, K. S., Green, A. E., Kotlerman, J., Elashoff, D., Morra, J. H., Cummings, J. L., Toga, A. W., Thompson, P. M., & Apostolova, L. G. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.07.020 · Cited by 54
Longitudinal relationships among biomarkers for Alzheimer disease in the Adult Children Study
Xiong, C., Jasielec, M. S., Weng, H., Fagan, A. M., Benzinger, T. L. S., Head, D., Hassenstab, J., Grant, E., Sutphen, C. L., Buckles, V., et al. (2016) · Neurology · doi:10.1212/wnl.0000000000002593 · Cited by 54
Damian, M., Hausner, L., Jekel, K., Richter, M., Froelich, L., Almkvist, O., Boada, M., Bullock, R., De Deyn, P. P., Frisoni, G. B., et al. (2013) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000348354 · Cited by 53
Is sleep disruption a risk factor for Alzheimer's disease?
Macedo, A. C., Balouch, S., & Tabet, N. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-161287 · Cited by 49
Tau-directed approaches for the treatment of Alzheimer’s disease: focus on leuco-methylthioninium
Seripa, D., Solfrizzi, V., Imbimbo, B. P., Daniele, A., Santamato, A., Lozupone, M., Zuliani, G., Greco, A., Logroscino, G., & Panza, F. (2016) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2016.1140039 · Cited by 50
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Scholey, A. (2018) · Proceedings of The Nutrition Society · doi:10.1017/s0029665117004025 · Cited by 49
Regulation of microglial physiology by the microbiota
Cook, J., & Prinz, M. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2125739 · Cited by 49
Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification
Hett, K., Ta, V.-T., Catheline, G., Tourdias, T., Manjón, J. V., Coupé, P., Initiative, A. D. N., Weiner, M. W., Aisen, P., Petersen, R., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-49970-9 · Cited by 49
Self-citationThe Role of Amyloid-Beta and Tau in the Early Pathogenesis of Alzheimer’s Disease
Yin, X., Qiu, Y., Zhao, C., Zhou, Z., Bao, J., & Qian, W. (2021) · Medical Science Monitor · doi:10.12659/msm.933084 · Cited by 48
Tauopathy contributes to synaptic and cognitive deficits in a murine model for Alzheimer’s disease
Stancu, I., Ris, L., Vasconcelos, B., Marinangeli, C., Goeminne, L., Laporte, V., Haylani, L. E., Couturier, J., Schakman, O., Gailly, P., et al. (2014) · The FASEB Journal · doi:10.1096/fj.13-246702 · Cited by 48
NPT088 reduces both amyloid‐β and tau pathologies in transgenic mice
Levenson, J. M., Schroeter, S., Carroll, J. C., Cullen, V., Asp, E., Proschitsky, M., Chung, C. H. ‐., Gilead, S., Nadeem, M., Dodiya, H. B., et al. (2016) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1016/j.trci.2016.06.004 · Cited by 47
Mosconi, L., Glodzik, L., Mistur, R., McHugh, P., Rich, K. E., Javier, E., Williams, S., Pirraglia, E., De Santi, S., Mehta, P. D., et al. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.07.011 · Cited by 46
Comparative pathobiology of β-amyloid and the unique susceptibility of humans to Alzheimer's disease
Rosen, R. F., Tomidokoro, Y., Farberg, A. S., Dooyema, J., Ciliax, B., Preuss, T. M., Neubert, T. A., Ghiso, J. A., LeVine, H., & Walker, L. C. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.04.019 · Cited by 46
Predicting Reduction of Cerebrospinal Fluid β-Amyloid 42 in Cognitively Healthy Controls
Mattsson, N., Insel, P. S., Donohue, M., Jagust, W., Sperling, R., Aisen, P., & Weiner, M. W. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2014.4530 · Cited by 45
Self-citationSilva, A. R. T., Grinberg, L. T., Farfel, J. M., Diniz, B. S., Lima, L. A., Silva, P. J. S., Ferretti, R. E. L., Rocha, R. M., Filho, W. J., Carraro, D. M., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048751 · Cited by 40
Hippocampal synaptic and neural network deficits in young mice carrying the humanAPOE 4 gene
Sun, G., He, Y., Ma, X. K., Li, S., Chen, D., Gao, M., Qiu, S., Yin, J., Shi, J., & Wu, J. (2017) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.12720 · Cited by 42
Biomarkers in frontotemporal lobar degenerations—Progress and challenges
Hu, W. T., Trojanowski, J. Q., & Shaw, L. M. (2011) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2011.04.012 · Cited by 42
Self-citationAbramowski, D., Rabe, S., Upadhaya, A. R., Reichwald, J., Danner, S., Staab, D., Capetillo-Zarate, E., Yamaguchi, H., Saido, T. C., Wiederhold, K.-H., et al. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.4586-11.2012 · Cited by 41
Nakaya, M., Sato, N., Matsuda, H., Maikusa, N., Shigemoto, Y., Sone, D., Yamao, T., Ogawa, M., Kimura, Y., Chiba, E., et al. (2022) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12356 · Cited by 41
Individualized atrophy scores predict dementia onset in familial frontotemporal lobar degeneration
Staffaroni, A. M., Cobigo, Y., Goh, S. M., Kornak, J., Bajorek, L., Chiang, K., Appleby, B., Bove, J., Bordelon, Y., Brannelly, P., et al. (2020) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.04.007 · Cited by 40
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Cain, A., Taga, M., McCabe, C., Green, G., Hekselman, I., White, C. C., Lee, D. I., Gaur, P., Rozenblatt-Rosen, O., Zhang, F., et al. (2020) · doi:10.1101/2020.12.22.424084 · Cited by 143
Machauer, R., Lueoend, R., Hurth, K., Veenstra, S. J., Rueeger, H., Voegtle, M., Tintelnot-Blomley, M., Rondeau, J.-M., Jacobson, L. H., Laue, G., et al. (2021) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.1c01300 · Cited by 40
Functional network segregation is associated with attenuated tau spreading in Alzheimer's disease
Steward, A., Biel, D., Brendel, M., Dewenter, A., Roemer, S., Rubinski, A., Luan, Y., Dichgans, M., Ewers, M., Franzmeier, N., et al. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.12867 · Cited by 39
Chaudhry, A., & Rizig, M. (2021) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2020.117270 · Cited by 37
Davtyan, H., Hovakimyan, A., Kiani Shabestari, S., Antonyan, T., Coburn, M. A., Zagorski, K., Chailyan, G., Petrushina, I., Svystun, O., Danhash, E., et al. (2019) · Alzheimer's Research & Therapy · doi:10.1186/s13195-019-0556-2 · Cited by 37
Charting a path toward combination therapy for Alzheimer’s disease
Stephenson, D., Perry, D., Bens, C., Bain, L. J., Berry, D., Krams, M., Sperling, R., Dilts, D., Luthman, J., Hanna, D., et al. (2015) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2015.995168 · Cited by 37
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Rafii, M. S., & Aisen, P. S. (2019) · CNS Drugs · doi:10.1007/s40263-018-0598-1 · Cited by 36
Self-citationGossye, H., Van Broeckhoven, C., & Engelborghs, S. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00757 · Cited by 34
Staging Neurodegenerative Disorders: Structural, Regional, Biomarker, and Functional Progressions
Archer, T., Kostrzewa, R. M., Beninger, R. J., & Palomo, T. (2011) · Neurotoxicity Research · doi:10.1007/s12640-010-9190-2 · Cited by 34
Jagust, W. J., Koeppe, R. A., Rabinovici, G. D., Villemagne, V. L., Harrison, T. M., Landau, S. M., & Initiative, T. A. D. N. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.14165 · Cited by 34
Self-citationAlzheimer’s disease: From basic science to precision medicine approach
Forloni, G. (2020) · BMJ Neurology Open · doi:10.1136/bmjno-2020-000079 · Cited by 33
Human APOE genotype affects intraneuronal A 1-42 accumulation in a lentiviral gene transfer model
Zhao, W., Dumanis, S. B., Tamboli, I. Y., Rodriguez, G. A., Jo LaDu, M., Moussa, C. E. H., & William Rebeck, G. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddt525 · Cited by 32
Progress Update: Fluid and Imaging Biomarkers in Alzheimer’s Disease
Sutphen, C. L., Fagan, A. M., & Holtzman, D. M. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.07.031 · Cited by 31
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Stone, D. B., Ryman, S. G., Hartman, A. P., Wertz, C. J., Vakhtin, A. A., & Initiative, A. D. N. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.711579 · Cited by 28
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Zimmer, J. A., Shcherbinin, S., Devous, M. D., Bragg, S. M., Selzler, K. J., Wessels, A. M., Shering, C., Mullen, J., Landry, J., Andersen, S. W., et al. (2021) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12123 · Cited by 27
Hudd, F., Shiel, A., Harris, M., Bowdler, P., McCann, B., Tsivos, D., Wearn, A., Knight, M., Kauppinen, R., Coulthard, E., et al. (2019) · Journal of Alzheimer's Disease · doi:10.3233/jad-180879 · Cited by 26
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Babapour Mofrad, R., & van der Flier, W. M. (2019) · Nature Reviews Neurology · doi:10.1038/s41582-018-0115-7 · Cited by 24
Tracking the earliest pathologic changes in Alzheimer disease
Landau, S. M., & Frosch, M. P. (2014) · Neurology · doi:10.1212/wnl.0000000000000392 · Cited by 20
Facilitating the use of the target product profile in academic research: a systematic review
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Devanarayan, V., Charil, A., Horie, K., Doherty, T., Llano, D. A., Andreozzi, E., Sachdev, P., Ye, Y., Murali, L. K., Zhou, J., et al. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.14411 · Cited by 19
Heneghan, A., Deng, F., Wells, K., Ritchie, K., Muniz-Terrera, G., Ritchie, C. W., Lawlor, B., & Naci, L. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-220267 · Cited by 18
Long-term levels of LDL-C and cognitive function: the CARDIA study
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Metabolites Associated with Early Cognitive Changes Implicated in Alzheimer’s Disease
Darst, B. F., Huo, Z., Jonaitis, E. M., Koscik, R. L., Clark, L. R., Lu, Q., Kremen, W. S., Franz, C. E., Rana, B., Lyons, M. J., et al. (2021) · Journal of Alzheimer’s Disease · doi:10.3233/jad-200176 · Cited by 16
A review of neuroimaging-based data-driven approach for Alzheimer’s disease heterogeneity analysis
Liu, L., Sun, S., Kang, W., Wu, S., & Lin, L. (2024) · Reviews in the Neurosciences · doi:10.1515/revneuro-2023-0033 · Cited by 16
Oxtoby, N. P., Shand, C., Cash, D. M., Alexander, D. C., & Barkhof, F. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.660581 · Cited by 14
Cognitive Reserve in Midlife is not Associated with Amyloid-β Deposition in Late-Life
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Self-citationHarrison, T. M., & Bookheimer, S. Y. (2016) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2015.09.003 · Cited by 12
Proteomic clusters underlie heterogeneity in preclinical Alzheimer’s disease progression
Wisch, J. K., Butt, O. H., Gordon, B. A., Schindler, S. E., Fagan, A. M., Henson, R. L., Yang, C., Boerwinkle, A. H., Benzinger, T. L. S., Holtzman, D. M., et al. (2023) · Brain · doi:10.1093/brain/awac484 · Cited by 11
Backwaters and rapids on the amyloid river
Burns, J. M., & Swerdlow, R. H. (2013) · Neurology · doi:10.1212/wnl.0b013e3182840d14 · Cited by 5
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Abrol, A., Calhoun, V. D., & Initiative, T. A. D. N. (2025) · Human Brain Mapping · doi:10.1002/hbm.70391 · Cited by 3
Zhong, J., Li, M., Dai, Z., & Wan, J. (2025) · Neurochemistry International · doi:10.1016/j.neuint.2025.106049 · Cited by 3
Parker, C., Weston, P., Zhang, H., Oxtoby, N., & Initiative, T. A. D. N. (2022) · doi:10.1101/2022.07.12.499784 · Cited by 2
Kasahara, H., Ikeda, M., Makioka, K., Nakamura, T., Takahashi, R., Kawarabayashi, T., Sanada, E., Suto, T., Higuchi, T., Tsushima, Y., et al. (2025) · Journal of Alzheimer’s Disease · doi:10.1177/13872877251316516
Metadata
- Authors
- Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q.
- Affiliations
- Mayo Clinic (US)
- University of California, Berkeley (US)
- University of Pennsylvania (US)
- University of California San Diego (US)
- University of California, San Francisco (US)
- Corresponding author
- Jack, Clifford R
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2010-01
- Volume
- 9
- Issue
- 1
- Pages
- 119-128
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC2819840
- OpenAlex
- W2167840686
- Cited by
- 4,806
- References
- 119
- Citations by year
- 2026: 273 · 2025: 317 · 2024: 278 · 2023: 259 · 2022: 308 · 2021: 321 · 2020: 359 · 2019: 303 · 2018: 267 · 2017: 283 · 2016: 265 · 2015: 273 · 2014: 335 · 2013: 337 · 2012: 301
- FWCI
- 127.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (AG11378)
- National Institute on Aging
- 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, amyloid PET, tau protein, brain atrophy, FDG-PET, synaptic dysfunction, neurodegeneration, disease stage, biomarkers, cognitive decline
- MeSH terms
- Aging, Alzheimer Disease, Brain, Cognition Disorders, Humans, Magnetic Resonance Imaging, Models, Neurological, Time Factors, Signal Transduction, Biomarkers, Amyloid beta-Peptides, tau Proteins, Disease Progression, Positron-Emission Tomography, Apolipoprotein E4, Plaque, Amyloid
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