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Pathological Aspects of Neuronal Hyperploidization in Alzheimer's Disease Evidenced by Computer Simulation
Estíbaliz Barrio-Alonso1, Bérénice Fontana1, Manuel Valero2
1Department of Molecular, Cellular, and Developmental Neurobiology, Cajal Institute, CSIC, Madrid, Spain.
Frontiers in Genetics
|April 16, 2020
Summary
Neuronal hyperploidy (NH), a cell cycle reactivation in neurons, is linked to Alzheimer's disease (AD). Our study shows NH causes synaptic dysfunction and network disruption, suggesting it's a key factor in AD pathogenesis.
Area of Science:
- Neuroscience
- Cell Biology
- Pathology
Background:
- Terminally differentiated neurons can reactivate the cell cycle, leading to hyperploidy.
- This neuronal hyperploidy (NH) is observed in Alzheimer's disease (AD) and may contribute to its development.
- The precise impact of NH on brain function and its role in AD remain unclear.
Purpose of the Study:
- To investigate the functional consequences of neuronal hyperploidy (NH) in a more physiologically relevant context.
- To explore the relationship between NH, synaptic function, and network integrity in Alzheimer's disease (AD).
Main Methods:
- Development of an in vitro system to induce cell cycle reentry in a subset of differentiated neurons, mimicking in vivo conditions.
- Analysis of synaptic function and morphological changes in hyperploid neurons.
- In silico modeling to test the hypothesis of network perturbation by hyperploid neurons.
Main Results:
- Neuronal hyperploidy (NH) correlates with synaptic dysfunction and morphological alterations in affected neurons.
- Membrane depolarization was found to facilitate the survival of hyperploid neurons.
- Hyperploid neurons, when integrated into neural networks, can disrupt normal network function.
Conclusions:
- Neuronal hyperploidy (NH) is a significant pathological process in Alzheimer's disease (AD).
- The survival of hyperploid neurons in active neural networks contributes to network dysfunction.
- NH represents a relevant target for understanding and potentially treating AD.
Keywords:
SV40 large T antigenneural network modelingneurite retractionneuron hypertrophyneuronal cell cycle reentryoscillatory patternssynaptic dysfunctionsynaptic firing rate
