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<p>Autism spectrum disorder (ASD), a disorder with heterogeneous etiology, is characterized by abnormal behavioral responses to sensory inputs. However, there is still limited understanding of how brain and epigenetic factors, along with behavioral abnormality, contribute to ASD. After completing Adolescent-Adult Sensory Profile, a self-report questinnaire, 34 individuals with ASD and 72 controls underwent neuroimaging scans to measure brain structural (cortical and subcortical volume) and functional (thalamo-cortical resting-state functional connectivity) characteristics. For epigenetic measures, we computed DNA methylation values of the oxytocin receptor and arginine vasopressin receptor (AVPR) genes from the participants’ saliva. When sensory-related behavior was the default baseline, a machine learning algorithm demonstrated that the <i>neuroimaging-epigenetic model</i> outperformed the <i>neuroimaging model</i> or the <i>epigenetic model</i>. Thalamo-cortical hyperconnectivity and AVPR 1A epigenetic modification were found to be significant contributing factors in these models. By integrating neuroimaging and epigenetic biomarkers with behaviors, a more precise diagnosis of ASD can be achieved.</p><p></p>

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Dissecting the heterogeneity of autism spectrum disorder with sensory behavior, brain, and epigenetic factors

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月1日

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  • Yongjeon Cheong,
  • Jihyun Bae,
  • Seonkyoung Lee,
  • Jihyeong Ro,
  • Hidehiko Okazawa,
  • Hirotaka Kosaka,
  • Minyoung Jung

摘要

Autism spectrum disorder (ASD), a disorder with heterogeneous etiology, is characterized by abnormal behavioral responses to sensory inputs. However, there is still limited understanding of how brain and epigenetic factors, along with behavioral abnormality, contribute to ASD. After completing Adolescent-Adult Sensory Profile, a self-report questinnaire, 34 individuals with ASD and 72 controls underwent neuroimaging scans to measure brain structural (cortical and subcortical volume) and functional (thalamo-cortical resting-state functional connectivity) characteristics. For epigenetic measures, we computed DNA methylation values of the oxytocin receptor and arginine vasopressin receptor (AVPR) genes from the participants’ saliva. When sensory-related behavior was the default baseline, a machine learning algorithm demonstrated that the neuroimaging-epigenetic model outperformed the neuroimaging model or the epigenetic model. Thalamo-cortical hyperconnectivity and AVPR 1A epigenetic modification were found to be significant contributing factors in these models. By integrating neuroimaging and epigenetic biomarkers with behaviors, a more precise diagnosis of ASD can be achieved.