Related Experiment Video
Updated: Jul 7, 2026

08:08
A Technique for Serial Collection of Cerebrospinal Fluid from the Cisterna Magna in Mouse
Published on: November 10, 2008
Amyloid precursor protein increases cortical neuron size in transgenic mice
Esther S Oh1, Alena V Savonenko, Julie F King
1Department of Medicine, The Johns Hopkins University School of Medicine, 558 Ross Research Building, Baltimore, MD 21205, USA.
Neurobiology of Aging
|February 29, 2008
Summary
Overexpressing amyloid precursor protein (APP) in mice, even the wild-type, caused cortical neurons to grow larger. This suggests APP may have neurotrophic effects and could explain why some Alzheimer's models don't lose neurons.
Area of Science:
- Neuroscience
- Genetics
- Molecular Biology
Background:
- Alzheimer's disease (AD) pathogenesis involves beta-amyloid, derived from amyloid precursor protein (APP).
- Neuronal loss is a hallmark of AD, but some transgenic models show no significant cell death.
Purpose of the Study:
- To investigate the effect of amyloid precursor protein (APP) transgene expression on cortical neuron size.
- To determine if APP overexpression influences neuronal hypertrophy in transgenic mouse models of Alzheimer's disease.
Main Methods:
- Measuring cortical neuron volumes (in cubic micrometers) in transgenic mice.
- Utilizing mouse models expressing familial AD Swedish mutation (APPswe), with or without mutated presenilin1 (PS1dE9), and wild-type APP (APPwt).
Main Results:
- Overexpression of APPswe and APPwt led to a higher proportion of medium-sized neurons.
- A corresponding decrease in the percentage of small-sized neurons was observed with APPswe and APPwt overexpression.
- PS1dE9 mutation alone did not affect neuronal size distribution.
Conclusions:
- Overexpression of either mutant (APPswe) or wild-type APP is sufficient to cause cortical neuron hypertrophy.
- This APP-induced hypertrophy suggests a potential neurotrophic effect.
- APP overexpression may contribute to the absence of neuronal loss in certain transgenic AD models.
