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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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Cites
Improving bioscience research reporting: The ARRIVE guidelines for reporting animal research
Kilkenny, C., Browne, W. J., Cuthill, I. C., Emerson, M., & Altman, D. G. (2010) · Journal of Pharmacology and Pharmacotherapeutics · doi:10.4103/0976-500x.72351 · Cited by 6,277
Iliff, J. J., Wang, M., Liao, Y., Plogg, B. A., Peng, W., Gundersen, G. A., Benveniste, H., Vates, G. E., Deane, R., Goldman, S. A., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003748 · Cited by 5,824
Sleep Drives Metabolite Clearance from the Adult Brain
Xie, L., Kang, H., Xu, Q., Chen, M. J., Liao, Y., Thiyagarajan, M., O’Donnell, J., Christensen, D. J., Nicholson, C., Iliff, J. J., et al. (2013) · Science · doi:10.1126/science.1241224 · Cited by 5,411
CRISPR-Cas systems for editing, regulating and targeting genomes
Sander, J. D., & Joung, J. K. (2014) · Nature Biotechnology · doi:10.1038/nbt.2842 · Cited by 3,153
TREM2 Variants in Alzheimer's Disease
Guerreiro, R., Wojtas, A., Bras, J., Carrasquillo, M., Rogaeva, E., Majounie, E., Cruchaga, C., Sassi, C., Kauwe, J. S. K., Younkin, S., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1211851 · Cited by 3,020
Development, maintenance and disruption of the blood-brain barrier
Obermeier, B., Daneman, R., & Ransohoff, R. M. (2013) · Nature Medicine · doi:10.1038/nm.3407 · Cited by 2,452
The glymphatic system: a beginner's guide
Jessen, N. A., Munk, A. S. F., Lundgaard, I., & Nedergaard, M. (2015) · Neurochemical Research · doi:10.1007/s11064-015-1581-6 · Cited by 2,075
Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database
Bertram, L., McQueen, M. B., Mullin, K., Blacker, D., & Tanzi, R. E. (2007) · Nature Genetics · doi:10.1038/ng1934 · Cited by 1,857
TREM2 Lipid Sensing Sustains the Microglial Response in an Alzheimer’s Disease Model
Wang, Y., Cella, M., Mallinson, K., Ulrich, J. D., Young, K. L., Robinette, M. L., Gilfillan, S., Krishnan, G. M., Sudhakar, S., Zinselmeyer, B. H., et al. (2015) · Cell · doi:10.1016/j.cell.2015.01.049 · Cited by 1,736
Single App knock-in mouse models of Alzheimer’s disease
Saito, T., Matsuba, Y., Mihira, N., Takano, J., Nilsson, P., Itohara, S., Iwata, N., & Saido, T. C. (2014) · Nature Neuroscience · doi:10.1038/nn.3697 · Cited by 1,366
Research works printed but not linked: 1
- Benitez, 2013, TREM2 and neurodegenerative disease, N. Engl. J. Med., 369, 1567
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Rizzo, S. J. S. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3661-8_17 · Cited by 7
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Rai, S. P., Bascuñana, P., Brackhan, M., Krohn, M., Möhle, L., Paarmann, K., & Pahnke, J. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200675 · Cited by 7
Marshall, J. P. S., Huynh, K., Lancaster, G. I., Ng, J., Collins, J. M., Pernes, G., Liang, A., Featherby, T. J., Mellet, N. A., Drew, B. G., et al. (2024) · iScience · doi:10.1016/j.isci.2024.108800 · Cited by 8
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O’Connell, K. M. S., Ouellette, A. R., Neuner, S. M., Dunn, A. R., & Kaczorowski, C. C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/657122
Sobrinho, C. M. F., Knackfuss, F. B., Souza, P. C. S., Torres, T. M., Ramos, A. A., Dias, L. P. B., Ferreira, J. B. P., & Pires, I. M. F. (2020) · Arquivo Brasileiro de Medicina Veterinária e Zootecnia · doi:10.1590/1678-4162-10935
McKeever, P. M. (2018) · TSpace (University of Toronto)
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Kasza, Á. (2018) · SZTE Repository of Dissertations (University of Szeged) · doi:10.14232/phd.9743
Yan, R. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.738448428.793577747
Webber, C. (2020) · New Oxford Textbook of Psychiatry · doi:10.1093/med/9780198713005.003.0016
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Pires, I. M. F., Ferreira, J. B. P., Dias, L. P. B., Sobrinho, C. M. F., Ramos, A. A., Souza, P. C. S., Torres, T. M., & Knackfuss, F. B. (2025) · Animal Reproduction · doi:10.1590/1984-3143-ar2025-0013
Rizzo, S. J. S. (2025) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2025.103138
Tseng, Y.-L., Lu, P.-C., Lee, C.-C., He, R.-Y., Huang, Y.-A., Tseng, Y.-C., Cheng, T.-J. R., Huang, J. J.-T., & Fang, J.-M. (2024) · Figshare · doi:10.6084/m9.figshare.26584962
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Silverman, J. L., Haouchine, O. Y., Roy, D., & Monsen, E. R. (2026) · Current topics in behavioral neurosciences · doi:10.1007/7854_2026_617
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
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