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A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease

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 h...

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Detalles Bibliográficos
Autores principales: Preuss, Christoph, Pandey, Ravi, Piazza, Erin, Fine, Alexander, Uyar, Asli, Perumal, Thanneer, Garceau, Dylan, Kotredes, Kevin P., Williams, Harriet, Mangravite, Lara M., Lamb, Bruce T., Oblak, Adrian L., Howell, Gareth R., Sasner, Michael, Logsdon, Benjamin A., Carter, Gregory W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7656729/
https://www.ncbi.nlm.nih.gov/pubmed/33172468
http://dx.doi.org/10.1186/s13024-020-00412-5
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: Supplementary information accompanies this paper at 10.1186/s13024-020-00412-5.