ArticleJournal of neurodevelopmental disorders2022
Characterization of cell-cell communication in autistic brains with single-cell transcriptomes.
Article in Journal of neurodevelopmental disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Hidden causal inference delineates dynamic lncRNA regulation in autism spectrum disorder.Briefings in bioinformatics · 2026Article
- Identifying condition-related cell-cell communication events using supervised tensor analysis.American journal of human genetics · 2026Article
- Integrative multi-omics and machine learning analysis identifies candidate biomarkers associated with mitochondrial quality control in major depressive disorder.Frontiers in psychiatry · 2026Article
- Single-Nucleus Transcriptomics of the Nucleus Accumbens Reveals Cell-Type-Specific Dysregulation in Adolescent Macaques with Depressive-Like Behaviors.Neuroscience bulletin · 2025Article
- Molecular and network disruptions in neurodevelopment uncovered by single cell transcriptomics analysis ofHeliyon · 2024Article
- Context-aware deconvolution of cell-cell communication with Tensor-cell2cell.Nature communications · 2022Article
- Expression and structural analysis of human neuroligin 2 and neuroligin 3 implicated in autism spectrum disorders.Frontiers in endocrinology · 2022Article
- Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on Autism Spectrum Disorder Neuroimaging.Disease markers · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAutism spectrum disorder is a neurodevelopmental disorder, affecting 1-2% of children. Studies have revealed genetic and cellular abnormalities in the brains of affected individuals, leading to both regional and distal cell communication deficits.
methodsRecent application of single-cell technologies, especially single-cell transcriptomics, has significantly expanded our understanding of brain cell heterogeneity and further demonstrated that multiple cell types and brain layers or regions are perturbed in autism. The underlying high-dimensional single-cell data provides opportunities for multilevel computational analysis that collectively can better deconvolute the molecular and cellular events altered in autism. Here, we apply advanced computation and pattern recognition approaches on single-cell RNA-seq data to infer and compare inter-cell-type signaling communications in autism brains and controls.
resultsOur results indicate that at a global level, there are cell-cell communication differences in autism in comparison with controls, largely involving neurons as both signaling senders and receivers, but glia also contribute to the communication disruption. Although the magnitude of changes is moderate, we find that excitatory and inhibitor neurons are involved in multiple intercellular signaling that exhibits increased strengths in autism, such as NRXN and CNTN signaling. Not all genes in the intercellular signaling pathways show differential expression, but genes in the affected pathways are enriched for axon guidance, synapse organization, neuron migration, and other critical cellular functions. Furthermore, those genes are highly connected to and enriched for genes previously associated with autism risks.
conclusionsOverall, our proof-of-principle computational study using single-cell data uncovers key intercellular signaling pathways that are potentially disrupted in the autism brains, suggesting that more studies examining cross-cell type effects can be valuable for understanding autism pathogenesis.
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