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<p>Brain development is guided by dynamic gene expression programs that vary across brain regions and developmental stages. Although numerous risk genes for neuropsychiatric disorders have been identified, the spatiotemporal contexts in which they act remain unclear. Here we show the spatiotemporal expression patterns of genome-wide risk gene sets across 15 neuropsychiatric traits, including autism, attention deficit hyperactive disorder, obsessive compulsive disorder, major depression, bipolar disorder, schizophrenia, epilepsy, Alzheimer’s disease and Parkinson’s disease, using bulk and single-cell transcriptomic data from the human brain. We identify trait-specific spatiotemporal enrichment patterns, allowing a classification of disorders into prenatally and postnatally enriched groups that align with known ages of disease onset. Integration with brain imaging datasets and gene co-expression network analysis further identifies synaptic development and function, as well as RNA processing during early brain development, in neuropsychiatric risk. These findings provide a systems-level framework linking genetic risk to neurodevelopmental and neuroanatomical contexts.</p>

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Spatiotemporal brain transcriptomics reveal risk gene hot-spots in major neuropsychiatric disorders

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月13日

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  • Weiqing Liu,
  • Tomomi Shimogori

摘要

Brain development is guided by dynamic gene expression programs that vary across brain regions and developmental stages. Although numerous risk genes for neuropsychiatric disorders have been identified, the spatiotemporal contexts in which they act remain unclear. Here we show the spatiotemporal expression patterns of genome-wide risk gene sets across 15 neuropsychiatric traits, including autism, attention deficit hyperactive disorder, obsessive compulsive disorder, major depression, bipolar disorder, schizophrenia, epilepsy, Alzheimer’s disease and Parkinson’s disease, using bulk and single-cell transcriptomic data from the human brain. We identify trait-specific spatiotemporal enrichment patterns, allowing a classification of disorders into prenatally and postnatally enriched groups that align with known ages of disease onset. Integration with brain imaging datasets and gene co-expression network analysis further identifies synaptic development and function, as well as RNA processing during early brain development, in neuropsychiatric risk. These findings provide a systems-level framework linking genetic risk to neurodevelopmental and neuroanatomical contexts.