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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.
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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 measuredIn 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
“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
“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
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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
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