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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
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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“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
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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“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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In the citing paper
“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
Cited by
Sorted by citations
Items 601–700 of 1,077
The role of innate immunity in Alzheimer's disease
Ennerfelt, H. E., & Lukens, J. R. (2020) · Immunological Reviews · doi:10.1111/imr.12896 · Cited by 124
Biological heterogeneity in ADNI amnestic mild cognitive impairment
Nettiksimmons, J., DeCarli, C. S., Landau, S. M., Beckett, L. A., & Initiative, A. D. N. (2014) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2013.09.003 · Cited by 124
Amyloid burden and metabolic function in early-onset Alzheimer’s disease: parietal lobe involvement.
Ossenkoppele, R., Zwan, M. D., Tolboom, N., van Assema, D. M. E., Adriaanse, S. F., Kloet, R. W., Boellaard, R., Windhorst, A. D., Barkhof, F., Lammertsma, A. A., et al. (2012) · Brain · doi:10.1093/brain/aws113 · Cited by 123
Alzheimer’s disease due to loss of function: A new synthesis of the available data
Kepp, K. P. (2016) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2016.06.004 · Cited by 123
Baldeiras, I., Santana, I. J., Leitão, M. J., Gens, H., Pascoal, R., Tábuas‐Pereira, M., Beato-Coelho, J., Duro, D., Almeida, M. R., & Oliveira, C. R. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0362-2 · Cited by 123
Benatar, M. G., & Wuu, J. (2012) · Neurology · doi:10.1212/wnl.0b013e31826e9b1d · Cited by 123
Sérot, J., Zmudka, J., & Jouanny, P. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-111964 · Cited by 123
Apathy correlates with prefrontal amyloid deposition in Alzheimer's disease
Mori, T., Shimada, H., Shinotoh, H., Hirano, S., Eguchi, Y., Yamada, M., Fukuhara, R., Tanimukai, S., Zhang, M.-R., Kuwabara, S., et al. (2014) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2013-306110 · Cited by 122
Parker, T. D., Slattery, C. F., Zhang, J., Nicholas, J. M., Paterson, R. W., Foulkes, A. J. M., Malone, I. B., Thomas, D. L., Modat, M., Cash, D. M., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.24056 · Cited by 122
Developing therapeutic approaches to tau, selected kinases, and related neuronal protein targets
Lee, V. M.-Y., Brunden, K. R., Hutton, M., & Trojanowski, J. Q. (2011) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a006437 · Cited by 122
Self-citationZhang, S., Han, D., Tan, X., Feng, J., Guo, Y., & Ding, Y. (2012) · International Journal of Clinical Practice · doi:10.1111/j.1742-1241.2011.02845.x · Cited by 123
Maier, F. C., Wehrl, H. F., Schmid, A. M., Mannheim, J. G., Wiehr, S., Lerdkrai, C., Calaminus, C., Stahlschmidt, A., Ye, L., Burnet, M. W. M., et al. (2014) · Nature Medicine · doi:10.1038/nm.3734 · Cited by 122
Biomarkers in Alzheimer's disease drug development
Cummings, J. L. (2011) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2010.06.004 · Cited by 122
Spatial patterns of brain amyloid- burden and atrophy rate associations in mild cognitive impairment
Tosun, D., Schuff, N. W., Mathis, C. A., Jagust, W., Weiner, M. W., & Initiative, A. D. N. (2011) · Brain · doi:10.1093/brain/awr044 · Cited by 122
Self-citationWhitwell, J. L., Graff‐Radford, J., Tosakulwong, N., Weigand, S. D., Machulda, M. M., Senjem, M. L., Spychalla, A. J., Vemuri, P., Jones, D. T., Drubach, D. A., et al. (2018) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.02.020 · Cited by 122
Self-citationEarly diagnosis and treatment of Alzheimer’s disease: new definitions and challenges
Pais, M. V., Martinez, L. D., Ribeiro, O. G., Loureiro, J. C., Fernandez, R., Valiengo, L. D. C. L., Canineu, P. R., Stella, F., Talib, L. L., Radanovic, M., et al. (2020) · Brazilian Journal of Psychiatry · doi:10.1590/1516-4446-2019-0735 · Cited by 124
Autophagy–lysosomal-associated neuronal death in neurodegenerative disease
Nixon, R. A. (2024) · Acta Neuropathologica · doi:10.1007/s00401-024-02799-7 · Cited by 126
Tracking neuroinflammation in Alzheimer’s disease: the role of positron emission tomography imaging
Zimmer, E. R., Leuzy, A., Benedet, A. L., Breitner, J., Gauthier, S., & Rosa-Neto, P. (2014) · Journal of Neuroinflammation · doi:10.1186/1742-2094-11-120 · Cited by 121
Kim, H. Y., Kim, H. V., Jo, S., Lee, C. J., Choi, S. Y., Kim, D. J., & Kim, Y. S. (2015) · Nature Communications · doi:10.1038/ncomms9997 · Cited by 122
Byun, M. S., Kim, S. E., Park, J., Yi, D., Choe, Y. M., Sohn, B. K., Choi, H. J., Baek, H., Han, J., Woo, J. I., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142756 · Cited by 121
J-ADNI Study Group, Yamane, T., Ishii, K., Sakata, M., Ikari, Y., Nishio, T., Ishii, K., Kato, T., Ito, K., & Senda, M. (2016) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-016-3591-2 · Cited by 121
Detectable Neuropsychological Differences in Early Preclinical Alzheimer’s Disease: A Meta-Analysis
Han, S. D., Nguyen, C. P., Stricker, N. H., & Nation, D. A. (2017) · Neuropsychology Review · doi:10.1007/s11065-017-9345-5 · Cited by 121
Alzheimer's disease and automatic speech analysis: A review
Pulido, M. L. B., Hernández, J. B. A., Ballester, M. Á. F., González, C. M. T., Mekyska, J., & Smékal, Z. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113213 · Cited by 120
Concordance Between Cerebrospinal Fluid Biomarkers and [11C]PIB PET in a Memory Clinic Cohort
Zwan, M. D., van Harten, A. C., Ossenkoppele, R., Bouwman, F. H., Teunissen, C. E., Adriaanse, S. F., Lammertsma, A. A., Scheltens, P., van Berckel, B. N. M., & van der Flier, W. M. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-132561 · Cited by 120
de Waal, H., Stam, C. J., Lansbergen, M. M., Wieggers, R. L., Kamphuis, P. J. G. H., Scheltens, P., Maestú, F., & van Straaten, E. C. W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0086558 · Cited by 120
Pereira, J. B., Westman, E., & Hansson, O. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.06.002 · Cited by 120
Neurovascular and immune mechanisms that regulate postoperative delirium superimposed on dementia
Wang, P., Velagapudi, R., Kong, C., Rodriguiz, R. M., Wetsel, W. C., Yang, T., Berger, M., Gelbard, H. A., Colton, C. A., & Terrando, N. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12064 · Cited by 120
Identifying incipient dementia individuals using machine learning and amyloid imaging
Mathotaarachchi, S., Pascoal, T. A., Shin, M., Benedet, A. L., Kang, M. S., Beaudry, T., Fonov, V. S., Gauthier, S., & Rosa-Neto, P. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.06.027 · Cited by 118
Aguilar, C., Westman, E., Muehlboeck, J., Mecocci, P., Vellas, B. J., Tsolaki, M., Kłoszewska, I., Soininen, H. S., Lovestone, S., Spenger, C., et al. (2013) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2012.11.005 · Cited by 118
Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer’s disease
Tetreault, A. M., Phan, T. X., Orlando, D., Lyu, I., Kang, H., Landman, B. A., Darby, R. R., & Initiative, O. B. O. A. D. N. (2020) · Brain · doi:10.1093/brain/awaa058 · Cited by 118
Data-driven modelling of neurodegenerative disease progression: thinking outside the black box
Young, A. L., Oxtoby, N. P., Garbarino, S., Fox, N. C., Barkhof, F., Schott, J. M., & Alexander, D. C. (2024) · Nature reviews. Neuroscience · doi:10.1038/s41583-023-00779-6 · Cited by 120
Predicting Aggressive Decline in Mild Cognitive Impairment
Tosto, G., Zimmerman, M. E., Carmichael, O. T., & Brickman, A. M. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.667 · Cited by 118
Huijbers, W., Vannini, P., Sperling, R. A., Pennartz, C. M. A., Cabeza, R. E. L., & Daselaar, S. M. (2012) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2012.08.021 · Cited by 118
In vivo characterization of the early states of the amyloid-beta network
Sepulcre, J., Sabuncu, M. R., Becker, A., Sperling, R., & Johnson, K. A. (2013) · Brain · doi:10.1093/brain/awt146 · Cited by 117
Multi-modal cross-attention network for Alzheimer’s disease diagnosis with multi-modality data
Zhang, J., He, X., Liu, Y., Cai, Q., Chen, H., & Qing, L. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107050 · Cited by 117
Infection, systemic inflammation, and Alzheimer's disease
Lim, S., Rodríguez‐Ortiz, C. J., & Kitazawa, M. (2015) · Microbes and Infection · doi:10.1016/j.micinf.2015.04.004 · Cited by 117
Yau, W. W., Tudorascu, D., McDade, E., Ikonomović, S., James, J. A., Minhas, D. S., Mowrey, W. B., Sheu, L. K., Snitz, B. E., Weissfeld, L. A., et al. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00135-0 · Cited by 117
Teipel, S. J., Grothe, M. J., Zhou, J. H., Sepulcre, J., Dyrba, M., Sorg, C., & Babiloni, C. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000995 · Cited by 117
Dhiman, K., Blennow, K., Zetterberg, H., Martins, R. N., & Gupta, V. B. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03040-5 · Cited by 117
Dendritic Spines in Alzheimer’s Disease: How the Actin Cytoskeleton Contributes to Synaptic Failure
Pelucchi, S., Stringhi, R., & Marcello, E. E. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21030908 · Cited by 117
Medina‐Sánchez, M., Miserere, S., Morales‐Narváez, E., & Merkoçi, A. (2013) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2013.10.069 · Cited by 117
Ansart, M., Epelbaum, S., Bassignana, G., Bône, A., Bottani, S., Cattai, T., Couronné, R., Faouzi, J., Koval, I., Louis, M., et al. (2021) · Medical Image Analysis · doi:10.1016/j.media.2020.101848 · Cited by 116
Dementia and mild cognitive impairment in adults with intellectual disability: Issues of diagnosis
Krinsky‐McHale, S. J., & Silverman, W. P. (2013) · Developmental Disabilities Research Reviews · doi:10.1002/ddrr.1126 · Cited by 116
Soldan, A., Pettigrew, C. A., Lu, Y., Wang, M., Selnes, O. A., Albert, M., Brown, T., Ratnanather, J. T., Laurent Younes, B., & Miller, M. I. (2015) · Human Brain Mapping · doi:10.1002/hbm.22810 · Cited by 116
Nguyen, T. T. X., Tchetgen, E. J. T., Kawachi, I. I., Gilman, S. E., Walter, S., Liu, S. Y., Manly, J. J., & Glymour, M. M. (2015) · Annals of Epidemiology · doi:10.1016/j.annepidem.2015.10.006 · Cited by 116
Burnham, S. C., Faux, N. G., Wilson, W. J., Laws, S. M., Ames, D. J., Bedő, J., Bush, A. I., Doecke, J. D., Ellis, K. A., Head, R. J., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.40 · Cited by 116
Meta-analysis of functional network alterations in Alzheimer's disease: Toward a network biomarker
Jacobs, H. I. L., Raduà, J., Lückmann, H. C., & Sack, A. T. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.03.009 · Cited by 116
Verfaillie, S. C. J., Adriaanse, S. M., Binnewijzend, M. A. A., Benedictus, M. R., Ossenkoppele, R., Wattjes, M. P., Pijnenburg, Y. A. L., van der Flier, W. M., Lammertsma, A. A., Kuijer, J. P. A., et al. (2015) · European Radiology · doi:10.1007/s00330-015-3696-1 · Cited by 116
Nabers, A., Ollesch, J., Schartner, J., Kötting, C., Genius, J., Hafermann, H., Klafki, H., Gerwert, K. B., & Wiltfang, J. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04286 · Cited by 116
Song, Q., Song, H., Xu, J., Huang, J., Meng, H., Gu, X. Q., Chen, J., Zheng, G., Chen, H., & Gao, X. (2016) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.6b00781 · Cited by 116
Cardiovascular risk factors and accelerated cognitive decline in midlife
Yaffe, K. S., Bahorik, A. L., Hoang, T. D. M., Forrester, S., Jacobs, D. R., Lewis, C. E., Lloyd‐Jones, D. M., Sidney, S., & Reis, J. P. (2020) · Neurology · doi:10.1212/wnl.0000000000010078 · Cited by 118
Irwin, D. J., McMillan, C. T., Toledo, J. B., Arnold, S. E., Shaw, L. M., Wang, L.-S., Van Deerlin, V., Lee, V. M.-Y., Trojanowski, J. Q., & Grossman, M. (2012) · Archives of Neurology · doi:10.1001/archneurol.2012.26 · Cited by 116
Self-citationThe therapeutics of Alzheimer's disease: Where we stand and where we are heading
Selkoe, D. J. (2013) · Annals of Neurology · doi:10.1002/ana.24001 · Cited by 116
Patient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy
Brown, J. A., Deng, J., Neuhaus, J. M., Sible, I. J., Sias, A. C., Lee, S. E., Kornak, J., Marx, G. A., Karydas, A. M., Spina, S., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.037 · Cited by 116
Brain foods - the role of diet in brain performance and health
Ekstrand, B., Scheers, N., Rasmussen, M. K., Young, J. F., Ross, A. B., & Landberg, R. (2020) · Nutrition Reviews · doi:10.1093/nutrit/nuaa091 · Cited by 115
Progress in Alzheimer’s disease
Galimberti, D., & Scarpini, E. A. (2011) · Journal of Neurology · doi:10.1007/s00415-011-6145-3 · Cited by 114
Chronic kidney disease is associated with dementia independent of cerebral small-vessel disease
Miwa, K., Tanaka, M. R., Okazaki, S., Furukado, S., Yagita, Y., Sakaguchi, M., Mochizuki, H., & Kitagawa, K. (2014) · Neurology · doi:10.1212/wnl.0000000000000251 · Cited by 114
Functional Disintegration of the Default Mode Network in Prodromal Alzheimer’s Disease
Dillen, K. N. H., Jacobs, H. I. L., Kukolja, J., Richter, N., von Reutern, B., Onur, O. A., Langen, K., & Fink, G. R. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161120 · Cited by 114
Cerebral white matter free water
Maillard, P., Fletcher, E. M., Singh, B., Martinez, O., Johnson, D. K., Olichney, J., Farias, S. T., & DeCarli, C. S. (2019) · Neurology · doi:10.1212/wnl.0000000000007449 · Cited by 114
Parnetti, L., Chiasserini, D., Eusebi, P., Giannandrea, D., Bellomo, G., Carlo, C. D., Padiglioni, C., Mastrocola, S., Lisetti, V., & Calabresi, P. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-111349 · Cited by 114
Forlenza, O. V., Radanovic, M., Talib, L. L., Aprahamian, I., Diniz, B. S., Zetterberg, H., & Gattaz, W. F. (2015) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2015.09.003 · Cited by 114
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Nyström, S., Psonka-Antonczyk, K. M., Ellingsen, P. G., Johansson, L. B. G., Reitan, N. K., Handrick, S., Prokop, S., Heppner, F. L., Wegenast‐Braun, B. M., Jucker, M., et al. (2013) · ACS Chemical Biology · doi:10.1021/cb4000376 · Cited by 114
Takeda, S., Commins, C., DeVos, S. L., Nobuhara, C. K., Wegmann, S., Roe, A. D., Costantino, I., Fan, Z., Nicholls, S. B., Sherman, A. E., et al. (2016) · Annals of Neurology · doi:10.1002/ana.24716 · Cited by 113
Agosta, F., Dalla Libera, D., Spinelli, E. G., Finardi, A., Canu, E., Bergami, A., Bocchio Chiavetto, L., Baronio, M., Comi, G., Martino, G., et al. (2014) · Annals of Neurology · doi:10.1002/ana.24235 · Cited by 113
Alzheimer's disease including focal presentations
Villain, N., & Dubois, B. (2019) · Seminars in Neurology · doi:10.1055/s-0039-1681041 · Cited by 113
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Meyer, P.-F., Tremblay-Mercier, J., Leoutsakos, J., Madjar, C., Lafaille-Maignan, M.-É., Savard, M., Rosa-Neto, P., Poirier, J., Etienne, P., Breitner, J., et al. (2019) · Neurology · doi:10.1212/wnl.0000000000007232 · Cited by 113
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Cabral, C., Morgado, P. M., Costa, D. C., & Silveira, M. (2015) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2015.01.003 · Cited by 113
Oh, H., Madison, C. M., Baker, S. L., Rabinovici, G. D., & Jagust, W. J. (2016) · Brain · doi:10.1093/brain/aww108 · Cited by 113
Self-citationOlsen, R. K., Yeung, L., Noly‐Gandon, A., D’Angelo, M. C., Kacollja, A., Smith, V. M., Ryan, J. D., & Barense, M. D. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.04.025 · Cited by 113
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Pan, X., Phan, T.-L., Adel, M., Fossati, C., Gaidon, T., Wojak, J., & Guedj, É. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.3022591 · Cited by 113
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Tosto, G., Zimmerman, M. E., Hamilton, J. L., Carmichael, O. T., Brickman, A. M., & Initiative, A. D. N. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.05.014 · Cited by 112
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Exalto, L. G., Biessels, G. J., Karter, A. J., Huang, E. S., Quesenberry, C. P., & Whitmer, R. A. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-132570 · Cited by 112
Toussaint, P., Perlbarg, V., Bellec, P., Désarnaud, S., Lacomblez, L., Doyon, J., Habert, M., & Benali, H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.091 · Cited by 112
Bemelmans, S. A. S. A., Tromp, K., Bunnik, E. M., Milne, R., Badger, S. J., Brayne, C., Schermer, M., & Richard, E. (2016) · Alzheimer s Research & Therapy · doi:10.1186/s13195-016-0212-z · Cited by 112
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Cunha, J. P., Proença, R. P., Dias‐Santos, A., de Almeida, R. M., Águas, H., Alves, M., Papoila, A. L., Louro, C., & Castanheira-Dinis, A. (2017) · Graefe s Archive for Clinical and Experimental Ophthalmology · doi:10.1007/s00417-017-3715-9 · Cited by 112
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Savica, R., Boeve, B. F., & Mielke, M. M. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2017.4243 · Cited by 112
Meyer, P. T., Hellwig, S., Amtage, F., Rottenburger, C., Sahm, U., Reuland, P., Weber, W., & Hüll, M. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.110.083683 · Cited by 112
Automated MRI measures predict progression to Alzheimer's disease
Desikan, R. S., Cabral, H., Settecase, F., Hess, C. P., Dillon, W. P., Glastonbury, C. M., Weiner, M. W., Schmansky, N. J., Salat, D. H., & Fischl, B. R. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.023 · Cited by 112
Self-citationFortea, J., Sala‐Llonch, R., Bartrés‐Faz, D., Lladó, A., Solé‐Padullés, C., Bosch, B., Antonell, A., Olives, J., Sánchez‐Valle, R., Molinuevo, J. L., et al. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.02.017 · Cited by 112
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Ossenkoppele, R., van der Flier, W. M., Zwan, M. D., Adriaanse, S. F., Boellaard, R., Windhorst, A. D., Barkhof, F., Lammertsma, A. A., Scheltens, P., & van Berckel, B. N. M. (2013) · Neurology · doi:10.1212/wnl.0b013e31827f0889 · Cited by 112
Laurent Younes, B., Albert, M., & Miller, M. I. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.04.009 · Cited by 111
Harada, R., Okamura, N., Furumoto, S., Tago, T., Maruyama, M., Higuchi, M., Yoshikawa, T., Arai, H., Iwata, R., Kudo, Y., et al. (2012) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-012-2261-2 · Cited by 111
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Kimura, Y., Ichise, M., Ito, H., Shimada, H., Ikoma, Y., Seki, C., Takano, H., Kitamura, S., Shinotoh, H., Kawamura, K., et al. (2015) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.160127 · Cited by 111
Ritchie, K. A., Ropacki, M. T., Albala, B., Harrison, J., Kaye, J. A., Kramer, J. H., RANDOLPH, C. C., & Ritchie, C. W. (2016) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2016.07.154 · Cited by 111
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Liu, B., Teschemacher, A. G., & Kasparov, S. (2017) · Glia · doi:10.1002/glia.23136 · Cited by 111
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Guo, S., Xu, K., Zhao, R., Gotz, D., Hongyuan Zha, B., & Cao, N. (2017) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2017.2745320 · Cited by 111
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Sharma, N., Kolekar, M. H., Jha, K., & Kumar, Y. (2018) · IRBM · doi:10.1016/j.irbm.2018.11.007 · Cited by 111
Chong, J. R., Ashton, N. J., Karikari, T. K., Tanaka, T., Schöll, M., Zetterberg, H., Blennow, K., Chen, C., & Lai, M. K. P. (2021) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2021-327370 · Cited by 111
Fišar, Z. (2022) · Biomolecules · doi:10.3390/biom12111676 · Cited by 113
Caselli, R. J., & Reiman, E. M. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-129026 · Cited by 111
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Snyder, P. J., Jackson, C. E., Petersen, R. C., Khachaturian, A. S., Kaye, J. A., Albert, M., & Weıntraub, S. (2011) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2011.03.009 · Cited by 111
Self-citationCharacterizing dementia with Lewy bodies by means of diffusion tensor imaging
Watson, R., Blamire, A. M., Colloby, S. J., Wood, J., Barber, R., He, J., & O'Brien, J. T. (2012) · Neurology · doi:10.1212/wnl.0b013e318266fc51 · Cited by 111
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Villemagne, V. L., Doré, V., Bourgeat, P., Burnham, S. C., Laws, S., Salvado, O., Masters, C. L., & Rowe, C. C. (2017) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2016.09.006 · Cited by 110
Sex-specific genetic predictors of Alzheimer’s disease biomarkers
(ADNI), A. D. N. I., Deming, Y., The Alzheimer Disease Genetics Consortium (ADGC), Dumitrescu, L., Barnes, L. L., Thambisetty, M., Kunkle, B., Gifford, K. A., Bush, W. S., Chibnik, L. B., et al. (2018) · Acta Neuropathologica · doi:10.1007/s00401-018-1881-4 · Cited by 110
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Jagust, W. (2016) · Brain · doi:10.1093/brain/awv326 · Cited by 110
Self-citationAlzheimer's disease: Pathogenesis and prevention
Braak, H., & Tredici, K. D. (2012) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2012.01.011 · Cited by 110
APOE-related biomarker profiles in non-pathological aging and early phases of Alzheimer's disease
Reinvang, I., Espeseth, T., & Westlye, L. T. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.05.006 · Cited by 109
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Farrell, M. E., Kennedy, K. M., Rodrigue, K. M., Wig, G. S., Bischof, G. N., Rieck, J. R., Chen, X., Festini, S. B., Devous, M. D., & Park, D. C. (2017) · JAMA Neurology · doi:10.1001/jamaneurol.2017.0892 · Cited by 109
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Samanta, S. (2020) · Archives of Physiology and Biochemistry · doi:10.1080/13813455.2020.1770799 · Cited by 109
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Gonneaud, J., Baria, A. T., Binette, A. P., Gordon, B. A., Chhatwal, J. P., Cruchaga, C., Jucker, M., Levin, J., Salloway, S., Farlow, M. R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25492-9 · Cited by 109
Self-citation
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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