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Neuronal Hyperactivity in Neurons Derived from Individuals with Grey Matter Heterotopia

GSE220673 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2025/01/02 Platform GPL20301Platform GPL30882
Summary
Periventricular heterotopia (PH), the most common form of grey matter heterotopia, represents a cortical malformation that is often associated with developmental delay and drug-resistant seizures1,2. The detailed neurophysiological underpinnings of PH symptoms in humans remain, however, elusive. Human cerebral organoids (hCOs) derived from patients with causative mutations in FAT4 or DCHS1 exhibit key features of PH3, but neuronal activity in these 3D models has not yet been investigated. Here, using silicon probe recordings, we detected exaggerated spontaneous spike activity in FAT4 and DCHS1 hCOs, suggesting functional changes in neuronal networks. Patch-clamp recordings revealed a decreased spike threshold exclusively for DCHS1 neurons, which presumably results from an enhanced density of somatic voltage-gated sodium channels. Furthermore, single-cell morphological reconstructions and immunostainings demonstrated greater morphological complexity of neurons and synaptic alterations, rather than an imbalance of excitatory-inhibitory neuron number, as contributing to the hyperactivity observed in FAT4 and DCHS1 hCOs. The morphological phenotype was rescued by an expression of wild-type DCHS1 in DCHS1 neurons. In addition, transcriptome and proteome analyses uncovered changes in GO terms associated with neuronal morphology and synaptic function. Overall, we provide detailed new insights into cellular alterations likely contributing to the emergence of symptoms in grey matter heterotopia.
Published in
Neuronal hyperactivity in neurons derived from individuals with gray matter heterotopia
Di Matteo F, Bonrath R, Pravata V et al. · Nature communications 2025 · PMID 39966398 · doi:10.1038/s41467-025-56998-1
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Also filed as BioProject PRJNA910960 and SRA study SRP412417. Searching any of these in the dataset finder brings you back here.

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