The probabilistic model of Alzheimer disease : the amyloid hypothesis revised
(2022) In Nature Reviews Neuroscience 23(1). p.53-66- Abstract
The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological... (More)
The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.
(Less)
- author
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Nature Reviews Neuroscience
- volume
- 23
- issue
- 1
- pages
- 53 - 66
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:34815562
- scopus:85119834657
- ISSN
- 1471-003X
- DOI
- 10.1038/s41583-021-00533-w
- language
- English
- LU publication?
- yes
- id
- 0fdc9e99-2091-4db3-899d-a40558628939
- date added to LUP
- 2021-12-15 08:54:58
- date last changed
- 2024-04-06 15:11:59
@article{0fdc9e99-2091-4db3-899d-a40558628939,
abstract = {{<p>The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.</p>}},
author = {{Frisoni, Giovanni B. and Altomare, Daniele and Thal, Dietmar Rudolf and Ribaldi, Federica and van der Kant, Rik and Ossenkoppele, Rik and Blennow, Kaj and Cummings, Jeffrey and van Duijn, Cornelia and Nilsson, Peter M. and Dietrich, Pierre Yves and Scheltens, Philip and Dubois, Bruno}},
issn = {{1471-003X}},
language = {{eng}},
number = {{1}},
pages = {{53--66}},
publisher = {{Nature Publishing Group}},
series = {{Nature Reviews Neuroscience}},
title = {{The probabilistic model of Alzheimer disease : the amyloid hypothesis revised}},
url = {{http://dx.doi.org/10.1038/s41583-021-00533-w}},
doi = {{10.1038/s41583-021-00533-w}},
volume = {{23}},
year = {{2022}},
}