The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
MOE Key Lab for Neuro Information, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China.
Mol Autism. 2023 Oct 30;14(1):41. doi: 10.1186/s13229-023-00573-2.
There has been increasing evidence for atypical white matter (WM) microstructure in autistic people, but findings have been divergent. The development of autistic people in early childhood is clouded by the concurrently rapid brain growth, which might lead to the inconsistent findings of atypical WM microstructure in autism. Here, we aimed to reveal the developmental nature of autistic children and delineate atypical WM microstructure throughout early childhood while taking developmental considerations into account.
In this study, diffusion tensor imaging was acquired from two independent cohorts, containing 91 autistic children and 100 typically developing children (TDC), aged 4-7 years. Developmental prediction modeling using support vector regression based on TDC participants was conducted to estimate the WM atypical development index of autistic children. Then, subgroups of autistic children were identified by using the k-means clustering method and were compared to each other on the basis of demographic information, WM atypical development index, and autistic trait by using two-sample t-test. Relationship of the WM atypical development index with age was estimated by using partial correlation. Furthermore, we performed threshold-free cluster enhancement-based two-sample t-test for the group comparison in WM microstructures of each subgroup of autistic children with the rematched subsets of TDC.
We clustered autistic children into two subgroups according to WM atypical development index. The two subgroups exhibited distinct developmental stages and age-dependent diversity. WM atypical development index was found negatively associated with age. Moreover, an inverse pattern of atypical WM microstructures and different clinical manifestations in the two stages, with subgroup 1 showing overgrowth with low level of autistic traits and subgroup 2 exhibiting delayed maturation with high level of autistic traits, were revealed.
This study illustrated age-dependent heterogeneity in early childhood autistic children and delineated developmental stage-specific difference that ranged from an overgrowth pattern to a delayed pattern. Trial registration This study has been registered at ClinicalTrials.gov (Identifier: NCT02807766) on June 21, 2016 ( https://clinicaltrials.gov/ct2/show/NCT02807766 ).
越来越多的证据表明自闭症患者存在非典型的脑白质（WM）微观结构，但研究结果存在差异。自闭症患者在幼儿期的发展受到大脑快速发育的影响，这可能导致自闭症患者 WM 微观结构的非典型性发现不一致。在这里，我们旨在揭示自闭症儿童的发育本质，并在考虑到发育因素的情况下，描绘整个幼儿期非典型 WM 微观结构的发展情况。
本研究对两个独立队列（包含 91 名自闭症儿童和 100 名正常发育儿童（TDC））进行了弥散张量成像。基于 TDC 参与者的支持向量回归进行发展预测建模，以估计自闭症儿童的 WM 非典型发育指数。然后，使用 K-均值聚类方法对自闭症儿童进行分组，并根据人口统计学信息、WM 非典型发育指数和自闭症特征，使用两样本 t 检验对各组进行比较。使用偏相关估计 WM 非典型发育指数与年龄的关系。此外，我们对每个自闭症儿童亚组的 WM 微观结构进行了基于无阈值聚类增强的两样本 t 检验，同时对重新匹配的 TDC 子集中的亚组进行了比较。
我们根据 WM 非典型发育指数将自闭症儿童分为两个亚组。这两个亚组表现出不同的发育阶段和年龄相关的多样性。WM 非典型发育指数与年龄呈负相关。此外，我们还发现两个阶段存在相反的 WM 微观结构异常模式和不同的临床表现，其中亚组 1 表现为过度生长和低水平自闭症特征，亚组 2 表现为发育迟缓与高水平自闭症特征。
本研究表明，自闭症儿童在幼儿期存在年龄相关的异质性，并描绘了从过度生长模式到发育迟缓模式的发育阶段特异性差异。
本研究已于 2016 年 6 月 21 日在 ClinicalTrials.gov（标识符：NCT02807766）注册（https://clinicaltrials.gov/ct2/show/NCT02807766）。
