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Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model

Alzheimer’s disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell an...

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Autores principales: Gurdon, Brianna, Yates, Sharon C., Csucs, Gergely, Groeneboom, Nicolaas E., Hadad, Niran, Telpoukhovskaia, Maria, Ouellette, Andrew, Ouellette, Tionna, O’Connell, Kristen, Singh, Surjeet, Murdy, Tom, Merchant, Erin, Bjerke, Ingvild, Kleven, Heidi, Schlegel, Ulrike, Leergaard, Trygve B., Puchades, Maja A., Bjaalie, Jan G., Kaczorowski, Catherine C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002670/
https://www.ncbi.nlm.nih.gov/pubmed/36909528
http://dx.doi.org/10.1101/2023.02.27.530226
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author Gurdon, Brianna
Yates, Sharon C.
Csucs, Gergely
Groeneboom, Nicolaas E.
Hadad, Niran
Telpoukhovskaia, Maria
Ouellette, Andrew
Ouellette, Tionna
O’Connell, Kristen
Singh, Surjeet
Murdy, Tom
Merchant, Erin
Bjerke, Ingvild
Kleven, Heidi
Schlegel, Ulrike
Leergaard, Trygve B.
Puchades, Maja A.
Bjaalie, Jan G.
Kaczorowski, Catherine C.
author_facet Gurdon, Brianna
Yates, Sharon C.
Csucs, Gergely
Groeneboom, Nicolaas E.
Hadad, Niran
Telpoukhovskaia, Maria
Ouellette, Andrew
Ouellette, Tionna
O’Connell, Kristen
Singh, Surjeet
Murdy, Tom
Merchant, Erin
Bjerke, Ingvild
Kleven, Heidi
Schlegel, Ulrike
Leergaard, Trygve B.
Puchades, Maja A.
Bjaalie, Jan G.
Kaczorowski, Catherine C.
author_sort Gurdon, Brianna
collection PubMed
description Alzheimer’s disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell and pathology composition of 6- and 14-month-old AD-BXD mouse brains using the semi-automated workflow (QUINT); which we expanded to allow for nonlinear refinement of brain atlas-registration, and quality control assessment of atlas-registration and brain section integrity. Near global age-related increases in microglia, astrocyte, and amyloid-beta accumulation were measured, while regional variation in neuron load existed among strains. Furthermore, hippocampal immunohistochemistry analyses were combined with bulk RNA-sequencing results to demonstrate the relationship between cell composition and gene expression. Overall, the additional functionality of the QUINT workflow delivers a highly effective method for registering and quantifying cell and pathology changes in diverse disease models.
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spelling pubmed-100026702023-03-11 Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model Gurdon, Brianna Yates, Sharon C. Csucs, Gergely Groeneboom, Nicolaas E. Hadad, Niran Telpoukhovskaia, Maria Ouellette, Andrew Ouellette, Tionna O’Connell, Kristen Singh, Surjeet Murdy, Tom Merchant, Erin Bjerke, Ingvild Kleven, Heidi Schlegel, Ulrike Leergaard, Trygve B. Puchades, Maja A. Bjaalie, Jan G. Kaczorowski, Catherine C. bioRxiv Article Alzheimer’s disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell and pathology composition of 6- and 14-month-old AD-BXD mouse brains using the semi-automated workflow (QUINT); which we expanded to allow for nonlinear refinement of brain atlas-registration, and quality control assessment of atlas-registration and brain section integrity. Near global age-related increases in microglia, astrocyte, and amyloid-beta accumulation were measured, while regional variation in neuron load existed among strains. Furthermore, hippocampal immunohistochemistry analyses were combined with bulk RNA-sequencing results to demonstrate the relationship between cell composition and gene expression. Overall, the additional functionality of the QUINT workflow delivers a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. Cold Spring Harbor Laboratory 2023-02-28 /pmc/articles/PMC10002670/ /pubmed/36909528 http://dx.doi.org/10.1101/2023.02.27.530226 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Gurdon, Brianna
Yates, Sharon C.
Csucs, Gergely
Groeneboom, Nicolaas E.
Hadad, Niran
Telpoukhovskaia, Maria
Ouellette, Andrew
Ouellette, Tionna
O’Connell, Kristen
Singh, Surjeet
Murdy, Tom
Merchant, Erin
Bjerke, Ingvild
Kleven, Heidi
Schlegel, Ulrike
Leergaard, Trygve B.
Puchades, Maja A.
Bjaalie, Jan G.
Kaczorowski, Catherine C.
Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
title Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
title_full Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
title_fullStr Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
title_full_unstemmed Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
title_short Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model
title_sort detecting the effect of genetic diversity on brain composition in an alzheimer’s disease mouse model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002670/
https://www.ncbi.nlm.nih.gov/pubmed/36909528
http://dx.doi.org/10.1101/2023.02.27.530226
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