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<p>Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder with complex molecular etiology. Since genetic causes account for less than 50% of ASD cases, novel approaches are required to overcome the challenges of characterizing genes and molecular pathways linking risk alleles to phenotype. Here we use RNA-sequencing, 3-dimensional protein-centric chromatin conformation (Hi-ChIP), and whole genome DNA methylation sequencing approaches to investigate hippocampal tissue from an ASD mouse model (<i>Cntnap2</i> knockout [<i>Cntnap2</i> KO]) to determine if multi-omic data integration improves the resolution of key molecular pathways contributing to the complex ASD phenotype. Each -omic dataset individually identified disruptions in numerous genes and pathways, providing broad ASD-related insights, such as 1) 699 downregulated genes with an enrichment of neuronal ontological terms; 2) unique chromatin interactions in <i>Cntnap2</i> KO mice; and 3) that&#xa0;most differentially methylated genes (1220/1659) have a neuronal function. The multi-omic data integration reduced the heterogeneity and refined the data to 43 genes with links to ASD (<i>e.g</i>., <i>Zbtb18, Cttnbp2, Gabbr2</i>). A pathways analysis of these 43 genes identified one gene ontological term: regulation of neuronal synaptic plasticity. These findings are consistent with large scale gene expression studies of human ASD postmortem brain tissue, suggesting that multi-omic data integration can be used to achieve a greater resolution of the heterogeneous ASD molecular etiology.</p>

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Multi-omic data integration improves the resolution of the molecular etiology of autism in a mouse model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月25日

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  • Carolina D. Alberca,
  • Kwangmoon Park,
  • Ligia A. Papale,
  • Andy Madrid,
  • Phillip E. Bergmann,
  • Sündüz Keleş,
  • Reid S. Alisch

摘要

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder with complex molecular etiology. Since genetic causes account for less than 50% of ASD cases, novel approaches are required to overcome the challenges of characterizing genes and molecular pathways linking risk alleles to phenotype. Here we use RNA-sequencing, 3-dimensional protein-centric chromatin conformation (Hi-ChIP), and whole genome DNA methylation sequencing approaches to investigate hippocampal tissue from an ASD mouse model (Cntnap2 knockout [Cntnap2 KO]) to determine if multi-omic data integration improves the resolution of key molecular pathways contributing to the complex ASD phenotype. Each -omic dataset individually identified disruptions in numerous genes and pathways, providing broad ASD-related insights, such as 1) 699 downregulated genes with an enrichment of neuronal ontological terms; 2) unique chromatin interactions in Cntnap2 KO mice; and 3) that most differentially methylated genes (1220/1659) have a neuronal function. The multi-omic data integration reduced the heterogeneity and refined the data to 43 genes with links to ASD (e.g., Zbtb18, Cttnbp2, Gabbr2). A pathways analysis of these 43 genes identified one gene ontological term: regulation of neuronal synaptic plasticity. These findings are consistent with large scale gene expression studies of human ASD postmortem brain tissue, suggesting that multi-omic data integration can be used to achieve a greater resolution of the heterogeneous ASD molecular etiology.