Comment on “ApoE-Directed Therapeutics Rapidly Clear β-Amyloid and Reverse Deficits in AD Mouse Models”
Abstract
Cramer et al . (Reports, 23 March 2012, p. 1503; published online 9 February 2012) reported that bexarotene rapidly reduces β-amyloid (Aβ) levels and plaque burden in two mouse models of Aβ deposition in Alzheimer’s disease (AD). We now report that, although bexarotene reduces soluble Aβ 40 levels in one of the mouse models, the drug has no impact on plaque burden in three strains that exhibit Aβ amyloidosis.
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Treatment with LXR/RXR agonists increases levels of ABCA1 and APOE and decreases amyloid deposition in APP overexpressing cells and mice.
“Several studies demonstrated that treatment of LXR/RXR agonists increase the levels of ABCA1 and APOE and decrease amyloid deposition in APP overexpressing cells and mice [73-77].”
From MicroRNAs in brain cholesterol metabolism and their implications for Alzheimer's disease (2016) · cites this paper as [77]
The effects of bexarotene have been variable in most follow-up studies.
“the effects of bexarotene have been variable in most follow-up studies (13, 14, 15, 16)”
From Nuclear SphK2/S1P signaling is a key regulator of ApoE production and Aβ uptake in astrocytes (2024) · cites this paper as [16]
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RNA-sequencing reveals transcriptional up-regulation of Trem2 in response to bexarotene treatment
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Some Candidate Drugs for Pharmacotherapy of Alzheimer’s Disease
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Lack of support for bexarotene as a treatment for Alzheimer's disease
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Retinoic acid receptor-targeted drugs in neurodegenerative disease
Clark, J. N., Whiting, A., & McCaffery, P. J. A. (2020) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1080/17425255.2020.1811232 · Cited by 30 · see citing works
Targretin Improves Cognitive and Biological Markers in a Patient with Alzheimer’s Disease
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The novel function of bexarotene for neurological diseases
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Bexarotene Does Not Clear Amyloid Beta Plaques but Delays Fibril Growth: Molecular Mechanisms
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Improving the predictive value of interventional animal models data
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New Hope from an Old Drug: Fighting Alzheimer's Disease with the Cancer Drug Bexarotene (Targretin)?
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Nuclear Localization of Apolipoprotein E4: A New Trick for an Old Protein
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- Authors
- Veeraraghavalu, K., Zhang, C., Miller, S., Hefendehl, J. K., Rajapaksha, T. W., Ulrich, J., Jucker, M., Holtzman, D. M., Tanzi, R. E., Vassar, R., & Sisodia, S. S.
- Affiliations
- University of Chicago (US)
- Harvard University (US)
- German Center for Neurodegenerative Diseases (DE)
- Northwestern University (US)
- Washington University in St. Louis (US)
- Corresponding author
- Veeraraghavalu, Karthikeyan
- Zhang, Can
- Miller, Sean
- Hefendehl, Jasmin K.
- Rajapaksha, Tharinda W.
- Ulrich, Jason
- Jucker, Mathias
- Holtzman, David M.
- Tanzi, Rudolph E.
- Vassar, Robert
- Sisodia, Sangram S.
- ORCID
- Venue
- Science
- Published
- 2013-05-24
- Volume
- 340
- Issue
- 6135
- Pages
- 924-924
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W3150015993
- Cited by
- 133
- References
- 9
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 4 · 2022: 2 · 2021: 7 · 2020: 9 · 2019: 9 · 2018: 8 · 2017: 12 · 2016: 16 · 2015: 21 · 2014: 29 · 2013: 12
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- DZNE Pub (submittedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- bexarotene, apolipoprotein E, amyloid-beta, Alzheimer's disease, amyloid plaques, Aβ40, amyloidosis, mouse model
- MeSH terms
- Alzheimer Disease, Animals, Apolipoproteins E, Brain, Male, Tetrahydronaphthalenes, Amyloid beta-Peptides
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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.
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