Scientific DataNeurosciencePeer-reviewed journal article
Systematic Phenotyping and Characterization of the 5xFAD mouse model of Alzheimer's Disease
Stefânia ForneriD, Shimako KawauchiiD, Gabriela Balderrama-GutierreziD, Enikö A. KramáriD, Dina P. MatheosiD, Jimmy Phan, Dominic I. JavonilloiD, Kristine M. TraniD, Edna E. Hingco, Celia da Cunha, Narges RezaieiD, Joshua A. AlcantaraiD, David Baglietto‐VargasiD, Camden S. JanseniD, Jonathan C. Neumann, Marcelo A. WoodiD, Grant R. MacGregoriD, Ali MortazaviiD, Andrea J. TenneriD, Frank M. LaFerlaiD, Kim N. GreeniD
Abstract
Mouse models of human diseases are invaluable tools for studying pathogenic mechanisms and testing interventions and therapeutics. For disorders such as Alzheimers disease in which numerous models are being generated, a challenging first step is to identify the most appropriate model and age to effectively evaluate new therapeutic approaches. Here we conducted a detailed phenotypic characterization of the 5xFAD model on a congenic C57BL/6J strain background, across its lifespan - including a seldomly analyzed 18-month old time point to provide temporally correlated phenotyping of this model and a template for characterization of new models of LOAD as they are generated. This comprehensive analysis included quantification of plaque burden, A{beta} biochemical levels, and neuropathology, neurophysiological measurements and behavioral and cognitive assessments, and evaluation of microglia, astrocytes, and neurons. Analysis of transcriptional changes was conducted using bulk-tissue generated RNA-seq data from microdissected cortices and hippocampi as a function of aging, which can be explored at the UCI Mouse Explorer and AD Knowledge Portal. This deep-phenotyping pipeline identified novel aspects of age-related pathology in the 5xFAD model.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 502
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