Yale School of Medicine, New Haven, CT, USA.
Icahn School of Medicine at Mount Sinai, New York, NY, USA.
J Autism Dev Disord. 2023 Sep;53(9):3636-3647. doi: 10.1007/s10803-022-05620-0. Epub 2022 Jun 25.
Autism (ASD) and schizophrenia spectrum disorders (SCZ) are neurodevelopmental conditions with overlapping and interrelated symptoms. A network analysis approach that represents clinical conditions as a set of "nodes" (symptoms) connected by "edges" (relations among symptoms) was used to compare symptom organization in the two conditions. Gaussian graphical models were estimated using Bayesian methods to model separate symptom networks for adults with confirmed ASD or SCZ diagnoses. Though overall symptom organization differed by diagnostic group, both symptom networks demonstrated high centrality of social communication difficulties. Autism-relevant restricted and repetitive behaviors and schizophrenia-related cognitive-perceptual symptoms were uniquely central to the ASD and SCZ networks, respectively. Results offer recommendations to improve differential diagnosis and highlight potential treatment targets in ASD and SCZ.
自闭症（ASD）和精神分裂症谱系障碍（SCZ）是具有重叠和相互关联症状的神经发育障碍。一种将临床状况表示为一组“节点”（症状）通过“边缘”（症状之间的关系）连接的网络分析方法，用于比较两种情况下的症状组织。使用贝叶斯方法估计高斯图形模型，以对确诊为 ASD 或 SCZ 诊断的成年人的单独症状网络进行建模。尽管整体症状组织因诊断组而异，但两个症状网络均表现出社交沟通困难的高度中心性。自闭症相关的受限和重复行为以及精神分裂症相关的认知知觉症状分别是 ASD 和 SCZ 网络的独特中心。研究结果为改善鉴别诊断提供了建议，并强调了 ASD 和 SCZ 中的潜在治疗靶点。
