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Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease

Mouse models of human diseases are invaluable tools for studying pathogenic mechanisms and testing interventions and therapeutics. For disorders such as Alzheimer’s disease in which numerous models are being generated, a challenging first step is to identify the most appropriate model and age to eff...

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Autores principales: Forner, Stefania, Kawauchi, Shimako, Balderrama-Gutierrez, Gabriela, Kramár, Enikö A., Matheos, Dina P., Phan, Jimmy, Javonillo, Dominic I., Tran, Kristine M., Hingco, Edna, da Cunha, Celia, Rezaie, Narges, Alcantara, Joshua A., Baglietto-Vargas, David, Jansen, Camden, Neumann, Jonathan, Wood, Marcelo A., MacGregor, Grant R., Mortazavi, Ali, Tenner, Andrea J., LaFerla, Frank M., Green, Kim N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519958/
https://www.ncbi.nlm.nih.gov/pubmed/34654824
http://dx.doi.org/10.1038/s41597-021-01054-y
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author Forner, Stefania
Kawauchi, Shimako
Balderrama-Gutierrez, Gabriela
Kramár, Enikö A.
Matheos, Dina P.
Phan, Jimmy
Javonillo, Dominic I.
Tran, Kristine M.
Hingco, Edna
da Cunha, Celia
Rezaie, Narges
Alcantara, Joshua A.
Baglietto-Vargas, David
Jansen, Camden
Neumann, Jonathan
Wood, Marcelo A.
MacGregor, Grant R.
Mortazavi, Ali
Tenner, Andrea J.
LaFerla, Frank M.
Green, Kim N.
author_facet Forner, Stefania
Kawauchi, Shimako
Balderrama-Gutierrez, Gabriela
Kramár, Enikö A.
Matheos, Dina P.
Phan, Jimmy
Javonillo, Dominic I.
Tran, Kristine M.
Hingco, Edna
da Cunha, Celia
Rezaie, Narges
Alcantara, Joshua A.
Baglietto-Vargas, David
Jansen, Camden
Neumann, Jonathan
Wood, Marcelo A.
MacGregor, Grant R.
Mortazavi, Ali
Tenner, Andrea J.
LaFerla, Frank M.
Green, Kim N.
author_sort Forner, Stefania
collection PubMed
description Mouse models of human diseases are invaluable tools for studying pathogenic mechanisms and testing interventions and therapeutics. For disorders such as Alzheimer’s 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/6 J 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, Aβ 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 MODEL-AD Explorer and AD Knowledge Portal. This deep-phenotyping pipeline identified novel aspects of age-related pathology in the 5xFAD model.
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spelling pubmed-85199582021-10-29 Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease Forner, Stefania Kawauchi, Shimako Balderrama-Gutierrez, Gabriela Kramár, Enikö A. Matheos, Dina P. Phan, Jimmy Javonillo, Dominic I. Tran, Kristine M. Hingco, Edna da Cunha, Celia Rezaie, Narges Alcantara, Joshua A. Baglietto-Vargas, David Jansen, Camden Neumann, Jonathan Wood, Marcelo A. MacGregor, Grant R. Mortazavi, Ali Tenner, Andrea J. LaFerla, Frank M. Green, Kim N. Sci Data Data Descriptor Mouse models of human diseases are invaluable tools for studying pathogenic mechanisms and testing interventions and therapeutics. For disorders such as Alzheimer’s 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/6 J 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, Aβ 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 MODEL-AD Explorer and AD Knowledge Portal. This deep-phenotyping pipeline identified novel aspects of age-related pathology in the 5xFAD model. Nature Publishing Group UK 2021-10-15 /pmc/articles/PMC8519958/ /pubmed/34654824 http://dx.doi.org/10.1038/s41597-021-01054-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Forner, Stefania
Kawauchi, Shimako
Balderrama-Gutierrez, Gabriela
Kramár, Enikö A.
Matheos, Dina P.
Phan, Jimmy
Javonillo, Dominic I.
Tran, Kristine M.
Hingco, Edna
da Cunha, Celia
Rezaie, Narges
Alcantara, Joshua A.
Baglietto-Vargas, David
Jansen, Camden
Neumann, Jonathan
Wood, Marcelo A.
MacGregor, Grant R.
Mortazavi, Ali
Tenner, Andrea J.
LaFerla, Frank M.
Green, Kim N.
Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease
title Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease
title_full Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease
title_fullStr Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease
title_full_unstemmed Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease
title_short Systematic phenotyping and characterization of the 5xFAD mouse model of Alzheimer’s disease
title_sort systematic phenotyping and characterization of the 5xfad mouse model of alzheimer’s disease
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519958/
https://www.ncbi.nlm.nih.gov/pubmed/34654824
http://dx.doi.org/10.1038/s41597-021-01054-y
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