School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China.
Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao 066004, China.
Cereb Cortex. 2023 Jun 8;33(12):7311-7321. doi: 10.1093/cercor/bhad040.
Autism spectrum disorder (ASD) is characterized by highly structural heterogeneity. However, most previous studies analyzed between-group differences through a structural covariance network constructed based on the ASD group level, ignoring the effect of between-individual differences. We constructed the gray matter volume-based individual differential structural covariance network (IDSCN) using T1-weighted images of 207 children (ASD/healthy controls: 105/102). We analyzed structural heterogeneity of ASD and differences among ASD subtypes obtained by a K-means clustering analysis based on evidently different covariance edges relative to healthy controls. The relationship between the distortion coefficients (DCs) calculated at the whole-brain, intra- and interhemispheric levels and the clinical symptoms of ASD subtypes was then examined. Compared with the control group, ASD showed significantly altered structural covariance edges mainly involved in the frontal and subcortical regions. Given the IDSCN of ASD, we obtained 2 subtypes, and the positive DCs of the 2 ASD subtypes were significantly different. Intra- and interhemispheric positive and negative DCs can predict the severity of repetitive stereotyped behaviors in ASD subtypes 1 and 2, respectively. These findings highlight the crucial role of frontal and subcortical regions in the heterogeneity of ASD and the necessity of studying ASD from the perspective of individual differences.
自闭症谱系障碍（ASD）的特征是高度结构异质性。然而，大多数先前的研究通过基于 ASD 组水平构建的结构协方差网络分析组间差异，忽略了个体间差异的影响。我们使用 207 名儿童（ASD/健康对照组：105/102）的 T1 加权图像构建了基于灰质体积的个体差异结构协方差网络（IDSCN）。我们基于与健康对照组相比明显不同的协方差边缘，对 K-均值聚类分析获得的 ASD 亚型进行了结构异质性分析。然后，我们检查了在全脑、半球内和半球间水平计算的失真系数（DC）与 ASD 亚型的临床症状之间的关系。与对照组相比，ASD 表现出明显改变的结构协方差边缘，主要涉及额叶和皮质下区域。基于 ASD 的 IDSCN，我们得到了 2 个亚型，这 2 个 ASD 亚型的正 DC 显著不同。2 个 ASD 亚型的半球内和半球间的正和负 DC 可以分别预测亚型 1 和 2 中重复刻板行为的严重程度。这些发现强调了额叶和皮质下区域在 ASD 异质性中的关键作用，以及从个体差异的角度研究 ASD 的必要性。
