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Toward more predictive genetic mouse models of Alzheimer’s disease
Open accessAbstract
Genetic mouse models for Alzheimer's disease (AD) have been widely used to understand aspects of the biology of the disease, but have had limited success in translating these findings to the clinic. In this review, we discuss the benefits and limitations of existing genetic models and recent advances in technologies (including high throughput sequencing and genome editing) that promise more predictive models. We summarize widely used biomarkers and behavioral tests for mouse models of AD and highlight best practices that will maximize translatability of preclinical findings.
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“traditional models created by incorporating a highly penetrant mutation in APP, PSEN1, or PSEN2 onto a single inbred background strain have largely failed to yield successful results in human clinical trials [286, 287]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [286]
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Metadata
- Authors
- Onos, K. D., Sukoff Rizzo, S. J., Howell, G. R., & Sasner, M.
- Affiliations
- Jackson Laboratory (US)
- Tufts University (US)
- Corresponding author
- Howell, Gareth R.
- Sasner, Michael
- Venue
- Brain Research Bulletin
- Publisher
- Elsevier BV
- Published
- 2016-04
- Volume
- 122
- Pages
- 1-11
- ISSN
- 0361-9230 (ISSN-L)
- PMC
- PMC4843786
- OpenAlex
- W2207047877
- Cited by
- 156
- References
- 85
- Citations by year
- 2026: 6 · 2025: 10 · 2024: 14 · 2023: 10 · 2022: 11 · 2021: 11 · 2020: 23 · 2019: 21 · 2018: 20 · 2017: 20 · 2016: 10
- FWCI
- 2.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Brain Research Bulletin (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (RF1AG051496)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (T32HD007065)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, genetic mouse models, translational research, next-generation sequencing, genome editing, biomarkers, behavioral tests, preclinical models
- MeSH terms
- Alzheimer Disease, Animals, Disease Models, Animal, Genetic Testing, Biomarkers, Mice
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 ›
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