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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A+T−(N)− and A+T−(N)+ indicate meaningfully different pathologic states.
“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]
In “Our Original Model – Lancet Neurology 2010” (page not available), the paper distinguishes amyloid biomarkers from biomarkers of neurodegeneration, supporting the idea that an abnormal (N) marker adds information. It does not examine A+T−(N)− versus A+T−(N)+ or establish that these two profiles indicate meaningfully different pathologic states. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe integration of white matter changes within standard biomarker models of the pathological cascade in Alzheimer's disease remains missing.
“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
In “Our Original Model – Lancet Neurology 2010” (page unavailable), the paper lists the biomarkers in its original and updated models without identifying white matter changes as a separate component. That supports the omission in this model, but the paper does not establish that white matter changes remain absent from standard biomarker models generally. (LLM, conf=0.78)
Experimental — accuracy not yet measuredβ-amyloid markers become abnormal up to 20 years before clinical symptoms become overt.
“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]
In “Our Original Model,” the paper places CSF Aβ42 and amyloid PET abnormalities before clinical symptoms. Its “Recent evidence concerning the order in which biomarkers become abnormal” section reports that CSF Aβ42 was fully abnormal 5–10 years or more before dementia diagnosis and describes a protracted asymptomatic period, but it does not establish the claimed 20-year interval. (LLM, conf=0.86)
Experimental — accuracy not yet measuredModels of AD pathophysiology theorize a temporal sequence where disruptions in 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 dementia.
“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]
A hypothetical model proposes that Aβ deposition occurs independently and accelerates tauopathy, which then leads to neurodegeneration detectable on MRI and PET before cognitive symptoms become manifest.
“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]
Accumulation of aggregated Aβ in the brain is believed to be the first pathological mechanism of Alzheimer's disease.
“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]
The temporal sequence of Aβ accumulation preceding neurodegeneration confirms the most acknowledged hypothetical model on the development of AD.
“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]
Robust evidence indicates that cerebral Aβ accumulation is one of the earliest mechanistic alterations in AD pathophysiology.
“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]
CSF and PET longitudinal studies support a model in which amyloidosis promotes or permits tau pathology spreading that likely drives clinical evolution.
“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]
Amyloid accumulation in the brain is thought to be the earliest sign of Alzheimer's disease and may begin up to 20 years before a clinical dementia diagnosis.
“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 <i>APOE</i> genotype (2019) · cites this paper as [5]
Apathy in Alzheimer's disease is associated with core Alzheimer's disease neurodegenerative processes.
“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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- [62]Thurfjell L Lundqvist R Villemagne VL Rowe CC A data-derived Aβ biomarker model computed using longitudinal PiB data from AIBL Alzheimer’s Association International Conference 2012 Vancouver, British Columbia, Canada Alzheimer’s Associaton 2012
- [81]Donohue M Aisen PS Dartigues J Jacqmin-Gadda H Gamst A Le Gogg M Validating Alzheimer’s pathological cascade by merging ADNI with PAQUID Alzheimer’s Assoication International Conference 2012 Vancouver, British Columbia, Canada Alzheimer’s Association 2012
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- 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 · 2012: 1
- 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
- Health Sciences › Medicine › Physiology › 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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