Genetically Engineered Mouse Models for Alzheimer Disease and Frontotemporal Dementia: New Insights from Single-Cell and Spatial Transcriptomics.

Am J Pathol

Department of Physiology and Biophysics, Center for Neurodegeneration and Regeneration, Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, California; Neuromedicine PhD Program, Programs in Biomedical and Biological Sciences (PIBBS), Keck School of Medicine, University of Southern California, Los Angeles, California; Neuroscience Graduate Program, University of Southern California, Los Angeles, California. Electronic address:

Published: December 2024

AI Article Synopsis

  • Neurodegenerative diseases like Alzheimer’s, Parkinson’s, and Huntington’s are linked to protein aggregation, prompting research on genetically engineered animal models to study these conditions and test treatments.
  • The article emphasizes mouse models of Alzheimer’s and frontotemporal dementia, highlighting those that have contributed significantly to understanding these diseases.
  • Recent findings from advanced techniques, like single-cell transcriptomics, are summarized, noting the limitations of current models but expressing optimism for their role in advancing research.

Article Abstract

Neurodegenerative diseases, including Alzheimer disease, frontotemporal dementia, Parkinson disease, Huntington disease, and amyotrophic lateral sclerosis, are often casually linked to protein aggregation and inclusion. As the origins of those proteinopathies have been biochemically traced and genetically mapped, genetically engineered animal models carrying the specific mutations or variants are widely used for investigating the etiology of these diseases, as well as for testing potential therapeutics. This article focuses on the mouse models of Alzheimer disease and closely related frontotemporal dementia, particularly the ones that have provided most valuable knowledge, or are in a trajectory of doing so. More importantly, some of the major findings from these models are summarized, based on the recent single-cell transcriptomics, multiomics, and spatial transcriptomics studies. While no model is perfect, it is hoped that the new insights from these models and the practical use of these models will continue to help to establish a path forward.

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Source
http://dx.doi.org/10.1016/j.ajpath.2024.11.006DOI Listing

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