A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease
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Abstract
Background: Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes. Results: This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of the 5xFAD mouse, a widely used amyloid pathology model, and three mouse models based on LOAD genetics carrying APOE4 and TREM2*R47H alleles demonstrated overlaps with distinct human AD modules that, in turn, were functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq showed strong correlation between gene expression changes independent of experimental platform. Conclusions: Taken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models.
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These modules were grouped into five consensus clusters and annotated using Reactome, representing conserved AD-related molecular signatures across cohorts and brain regions.
“These modules were grouped into five consensus clusters and annotated using Reactome, representing conserved AD‐related molecular signatures across cohorts and brain regions. 37 , 41 , 51”
From Unique transcriptomic alterations in 5XFAD;PS19 mouse model identify glial lipid dysregulation and coordinated microglial–oligodendrocyte responses (2026) · cites this paper as [41]
The direction of the changes correlated with gene expression changes observed in human AD based on the AMP-AD modules.
“The direction of the changes correlated with gene expression changes observed in human AD based on the AMP-AD modules (Preuss et al., 2020).”
From Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer’s Disease-Relevant Phenotypes in Mice (2022) · cites this paper as Preuss et al., 2020
Transcriptomic analyses of brain tissue from LOAD1.Plcg2M28L or LOAD1.Mthfr677C>T mice revealed increased alignment to brain transcriptomes from human patients with AD compared to B6 or LOAD1 controls.
“Transcriptomic analyses of the brain tissue from LOAD1.Plcg2M28L or LOAD1.Mthfr677C > T mice revealed increased alignment to brain transcriptomes from human patients with AD compared to B6 or LOAD1 controls (Preuss et al., 2020).”
From Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer’s Disease-Relevant Phenotypes in Mice (2022) · cites this paper as Preuss et al., 2020
The Results section describes comparing brain transcriptomes from APOE4 KI, Trem2*R47H, and combined-variant mice with human AD co-expression modules, including comparisons with B6 controls. Searches for LOAD1.Plcg2M28L and LOAD1.Mthfr677C>T found no passage reporting analyses of those mice or their increased alignment relative to B6 or LOAD1 controls. No page numbers were available in our copy. (LLM, conf=0.76)
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Cites
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“This panel consists of 760 genes identified by the Accelerating Medicines Partnership Alzheimer’s Disease Project Consortium as LOAD relevant genes (29).”
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“The direction of the changes correlated with gene expression changes observed in human AD based on the AMP-AD modules (Preuss et al., 2020).”
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- Authors
- the MODEL-AD Consortium, Preuss, C., Pandey, R., Piazza, E., Fine, A., Uyar, A., Perumal, T., Garceau, D., Kotredes, K. P., Williams, H., Mangravite, L. M., Lamb, B. T., Oblak, A. L., Howell, G. R., Sasner, M., Logsdon, B. A., & Carter, G. W.
- Affiliations
- Jackson Laboratory (US)
- Nanostring Technologies (United States) (US)
- Sage Bionetworks (US)
- Indiana University School of Medicine (US)
- Corresponding author
- Carter, Gregory W.
- ORCID
- Venue
- Molecular Neurodegeneration
- Published
- 2020-11-10
- Volume
- 15
- Issue
- 1
- Pages
- 67-67
- ISSN
- 1750-1326 (ISSN-L)
- PMC
- PMC7656729
- OpenAlex
- W3104184392
- Cited by
- 63
- References
- 10
- Citations by year
- 2026: 12 · 2025: 3 · 2024: 10 · 2023: 9 · 2022: 16 · 2021: 11 · 2020: 2
- FWCI
- 5.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Molecular Neurodegeneration (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion, cc-by)
- IUScholarWorks (Indiana University) (submittedVersion, cc-by)
- Funders
- National Institute on Aging (U54 AG 054354)
- Topics
- Health Sciences › Medicine › Physiology › 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
- late-onset Alzheimer's disease, mouse models of Alzheimer's disease, gene co-expression modules, human brain transcriptome, 5xFAD mice, APOE ε4, amyloid pathology
- MeSH terms
- Alzheimer Disease, Animals, Brain, Disease Models, Animal, Microglia, Mice, Gene Regulatory Networks, Transcriptome
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