Mechanisms of hyperexcitability in Alzheimer's disease hiPSC-derived neurons and cerebral organoids vs. isogenic control
- The Scripps Research Institute, United States
- Scintillon Institute, United States
Abstract
Human Alzheimer's disease (AD) brains and transgenic AD mouse models manifest hyperexcitability. This aberrant electrical activity is caused by synaptic dysfunction that represents the major pathophysiological correlate of cognitive decline. However, the underlying mechanism for this excessive excitability remains incompletely understood. To investigate the basis for the hyperactivity, we performed electrophysiological and immunofluorescence studies on hiPSC-derived cerebrocortical neuronal cultures and cerebral organoids bearing AD-related mutations in presenilin 1 or amyloid precursor protein vs. isogenic gene corrected controls. In the AD hiPSC-derived neurons/organoids, we found increased excitatory bursting activity, which could be explained in part by a decrease in neurite length. AD hiPSC-derived neurons also displayed increased sodium current density and increased excitatory and decreased inhibitory synaptic activity. Our findings establish hiPSC-derived AD neuronal cultures and organoids as a relevant model of early AD pathophysiology and provide mechanistic insight into the observed hyperexcitability.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
National Institutes of Health (P01 HD29587)
- Stuart A Lipton
National Institute of Neurological Disorders and Stroke (Core grant P30 NS076411)
- Stuart A Lipton
National Institutes of Health (DP1 DA041722)
- Stuart A Lipton
National Institutes of Health (R01 NS086890)
- Stuart A Lipton
National Institutes of Health (R01 AG056259)
- Stuart A Lipton
National Institutes of Health (RF1 AG057409)
- Stuart A Lipton
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Ghatak et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 9,823
- views
-
- 1,351
- downloads
-
- 162
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Mechanisms of hyperexcitability in Alzheimer's disease hiPSC-derived neurons and cerebral organoids vs. isogenic control
eLife 8:e50333.
https://doi.org/10.7554/eLife.50333
Further reading
-
- Neuroscience
Combining electrophysiological, anatomical and functional brain maps reveals networks of beta neural activity that align with dopamine uptake.
-
- Neuroscience
During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally-driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event's track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.
