The DOI matches its Crossref record; 121 of the 121 references it cites were found in a registry or an index.
Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers
Open accessAbstract
In 2010, we put forward a hypothetical model of the major biomarkers of Alzheimer's disease (AD). The model was received with interest because we described the temporal evolution of AD biomarkers in relation to each other and to the onset and progression of clinical symptoms. Since then, evidence has accumulated that supports the major assumptions of this model. Evidence has also appeared that challenges some of our assumptions, which has allowed us to modify our original model. Refinements to our model include indexing of individuals by time rather than clinical symptom severity; incorporation of interindividual variability in cognitive impairment associated with progression of AD pathophysiology; modifications of the specific temporal ordering of some biomarkers; and recognition that the two major proteinopathies underlying AD biomarker changes, amyloid β (Aβ) and tau, might be initiated independently in sporadic AD, in which we hypothesise that an incident Aβ pathophysiology can accelerate antecedent limbic and brainstem tauopathy.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We believe that A+T−(N)+ represents evidence of comorbidity, that is, A+T− represents Alzheimer’s pathologic change while in the A+T− context, (N) + represents evidence of non-AD neurodegeneration/neuronal injury [152] and thus A+T−(N)− and A+T−(N)+ indicate meaningfully different pathologic states [153].”
From NIA‐AA Research Framework: Toward a biological definition of Alzheimer's disease (2018) · cites this paper as [153]
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
“However, the integration of white matter changes within standard biomarker models of the pathological cascade in Alzheimer’s disease remains missing (Jack et al., 2013).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Jack et al., 2013
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
“This should be seen in the context that b-amyloid markers do become abnormal up to 20 years before clinical symptoms become overt [114], and because expression of apoE in the brain mediates clearance of amyloid-b peptides [89], a clearance that is impaired in Alzheimer disease [90].”
From Plasma levels of apolipoprotein E, APOE genotype and risk of dementia and ischemic heart disease: A review (2016) · cites this paper as [114]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“robust evidence indicates that cerebral Aβ accumulation is one of the earliest mechanistic alterations of the whole pathophysiological dynamic of AD (104–107).”
From The β-Secretase BACE1 in Alzheimer’s Disease (2021) · cites this paper as [107]
In the citing paper
“Models of AD pathophysiology theorize a temporal sequence where disruptions in amyloid-β (Aβ) production and/or clearance initiate a biological cascade that leads to Aβ plaque formation that spreads throughout the cortex followed by tauopathy, neuronal dysfunction and death, and ultimately dementia2,3.”
From Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study (2018) · cites this paper as [3]
In the citing paper
“A hypothetical model of dynamic biomarkers has been proposed to explain the pathophysiological process of Alzheimer's disease 142 , in which Aβ deposition occurs independently and accelerates tauopathy, which then leads to neurodegeneration detectable on magnetic resonance imaging (MRI) and positron emission tomography (PET) before cognitive symptoms become manifest.”
From Mental health care for older adults: recent advances and new directions in clinical practice and research (2022) · cites this paper as [142]
In the citing paper
“Accumulation of aggregated amyloid-β (Aβ) in the brain is believed to be the first pathological mechanism of Alzheimer’s disease (AD)1.”
From Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity (2017) · cites this paper as [1]
In the citing paper
“The temporal sequence of Aβ accumulation preceding neurodegeneration confirms the most acknowledged hypothetical model on the development of AD1.”
From Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity (2017) · cites this paper as [1]
In the citing paper
“However, CSF and positron emission tomography longitudinal studies support the hypothetical pathophysiological model of AD for which amyloidosis proceeds, either promoting or being permissive to the spreading of tau pathology that is likely to drive disease clinical evolution (104–107).”
From The β-Secretase BACE1 in Alzheimer’s Disease (2021) · cites this paper as [107]
In the citing paper
“Accumulation of amyloid in the brain is believed to be the first sign of the disease and can precede a clinical diagnosis of dementia by up to 20 years [1, 4, 5].”
From Duration of preclinical, prodromal, and dementia stages of Alzheimer's disease in relation to age, sex, and APOE genotype (2019) · cites this paper as [5]
In the citing paper
“Since tau and phospho-tau are considered to be markers of downstream neurodegeneration in AD (Jack et al., 2013), this suggests that apathy is associated with core AD neurodegenerative processes.”
From Neuropsychiatric symptoms in Alzheimer's disease: what might be associated brain circuits? (2015) · cites this paper as Jack et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70299-6 · Cited by 4,806
Self-citationGoate, A., Chartier-Harlin, M.-C., Mullan, M., Brown, J., Crawford, F., Fidani, L., Giuffra, L., Haynes, A., Irving, N., James, L., et al. (1991) · Nature · doi:10.1038/349704a0 · Cited by 4,659
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
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
Self-citationGreicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308627101 · Cited by 3,684
Association of missense and 5′-splice-site mutations in tau with the inherited dementia FTDP-17
Hutton, M., Lendon, C. L., Rizzu, P., Baker, M., Froelich, S., Houlden, H., Pickering-Brown, S., Chakraverty, S., Isaacs, A., Grover, A., et al. (1998) · Nature · doi:10.1038/31508 · Cited by 3,498
Self-citationStern, Y. (2009) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2009.03.004 · Cited by 2,943
Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.5062-08.2009 · Cited by 2,862
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
Seeley, W. W., Crawford, R. K., Zhou, J., Miller, B. L., & Greicius, M. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.024 · Cited by 2,350
Research works printed but not linked: 2
- DeCarli, 1992, Postmortem regional neurofibrillary tangle densities, but not senile plaque densities, are related to regional cerebral metabolic rates for glucose during life in Alzheimer's disease, Neurodegeneration, 1, 113
- Bateman R. Dominantly inherited Alzheimer network clinical trials: a model for prevention trials. Alzheimer's Association International Conference; Paris, France; July 16–21, 2011. S680.
Cited by
Sorted by citations
Items 301–304 of 304
Sheng, J., Zhu, H., Zhou, R., Zhang, Q., Wang, J., & Ying, Z. (2025) · Brain Research · doi:10.1016/j.brainres.2025.149691 · Cited by 4
Zhong, J., Li, M., Dai, Z., & Wan, J. (2025) · Neurochemistry International · doi:10.1016/j.neuint.2025.106049 · Cited by 3
Disrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis
Al-Amin, M. M., Grandjean, J., Klohs, J., & Kim, J. (2020) · doi:10.1101/2020.04.27.064634 · Cited by 2
Park, J. H., Kim, B., Al‐Amin, M. M., Tate, M. D., Sharify, A. D., John, S. K., Karahan, H., Lu, H., Dabin, L. C., & Kim, J. (2026) · Alzheimer's & Dementia · doi:10.1002/alz.71742
Metadata
- Authors
- 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., Lesnick, T. G., Pankratz, V. S., Donohue, M. C., & Trojanowski, J. Q.
- Affiliations
- Mayo Clinic (US)
- University of California, Berkeley (US)
- University of California, San Francisco (US)
- University of California San Diego (US)
- University of Pennsylvania (US)
- Corresponding author
- Jack, Clifford R
- ORCID
- Venue
- The Lancet Neurology
- Publisher
- Elsevier BV
- Published
- 2013-02
- Volume
- 12
- Issue
- 2
- Pages
- 207-216
- ISSN
- 1474-4422 (ISSN-L)
- PMC
- PMC3622225
- OpenAlex
- W1993571512
- Cited by
- 4,396
- References
- 121
- Citations by year
- 2026: 265 · 2025: 339 · 2024: 376 · 2023: 352 · 2022: 360 · 2021: 428 · 2020: 395 · 2019: 365 · 2018: 313 · 2017: 309 · 2016: 262 · 2015: 292 · 2014: 228 · 2013: 106
- FWCI
- 209.74
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Lancet Neurology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (AG11378)
- 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, biomarkers, pathophysiological model, amyloid-beta, tau protein, interindividual variability, cognitive impairment, sporadic Alzheimer's disease, disease progression
- MeSH terms
- Alzheimer Disease, Cognition Disorders, Humans, Models, Biological, Biomarkers, Amyloid beta-Peptides, tau Proteins, Nonlinear Dynamics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
