Minimum embedding dimension analysis uncovers reduced network complexity during neuronal differentiation in autism spectrum disorder
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA514983 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8439270.fastq.gz | Fastqsanger.gz | |||
| SRR8439271.fastq.gz | Fastqsanger.gz | |||
| SRR8439272.fastq.gz | Fastqsanger.gz | |||
| SRR8439263.fastq.gz | Fastqsanger.gz | |||
| SRR8439273.fastq.gz | Fastqsanger.gz |
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Project description:Background: Neuronal activity can be modeled as a nonlinear dynamical system to yield novel measures of neuronal state and dysfunction. We hypothesized that electrical activity during neuronal differentiation would be marked by a reduction in dynamical complexity in autism spectrum disorder (ASD). Methods: Electrical activity of induced pluripotent stem cell (iPSC)-derived neurons from ASD patients and controls were recorded using a multielectrode array (MEA). Minimum embedding dimension (MED) analysis was performed to characterize the complexity present in the electrical recordings of the neuronal cultures during differentiation. Gene expression changes with respect to the MED were analyzed, and gene ontology analysis and the BrainSpan Atlas were used to identify gene enrichments in specific biological pathways, brain regions, and developmental stages. Results: We found that the MED showed a statistically significant deficit in the ASD samples, suggesting that, compared to controls, network complexity is reduced in ASD during neuronal differentiation. MED was correlated to clinical endpoints such as nonverbal intelligence and was associated with 53 differentially expressed genes. These differentially expressed genes were overrepresented in ASD gene lists and pathways related to neurodevelopment, cell morphology, and cell migration. Spatiotemporal analysis also showed a prenatal temporal enrichment in cortical and deep brain structures. Conclusion: Reduced network complexity in ASD was observed by MED analysis during neuronal differentiation, indicating deficits in integrated and synchronized firing. The results present nonlinear dynamical analysis of iPSC-derived neuronal electrical recordings as a new paradigm for the investigation of aberrant brain activity in neurodevelopmental disorders.
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