Rosamund Stone Zander Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
J Child Neurol. 2024 May;39(5-6):178-189. doi: 10.1177/08830738241248685. Epub 2024 May 15.
Abnormalities in white matter development may influence development of autism spectrum disorder in tuberous sclerosis complex (TSC). Our goals for this study were as follows: (1) use data from a longitudinal neuroimaging study of tuberous sclerosis complex (TACERN) to develop optimized linear mixed effects models for analyzing longitudinal, repeated diffusion tensor imaging metrics (fractional anisotropy, mean diffusivity) pertaining to select white matter tracts, in relation to positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months, and (2) perform an exploratory analysis using optimized models applied to all white matter tracts from these data. Eligible participants (3-12 months) underwent brain magnetic resonance imaging (MRI) at repeated time points from ages 3 to 36 months. Positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months was used. Linear mixed effects models were fine-tuned separately for fractional anisotropy values (using fractional anisotropy corpus callosum as test outcome) and mean diffusivity values (using mean diffusivity right posterior limb internal capsule as test outcome). Fixed effects included participant age, within-participant longitudinal age, and autism spectrum disorder diagnosis. Analysis included data from n = 78. After selecting separate optimal models for fractional anisotropy and mean diffusivity values, we applied these models to fractional anisotropy and mean diffusivity of all 27 white matter tracts. Fractional anisotropy corpus callosum was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = 0.0093, = .0612), and mean diffusivity right inferior cerebellar peduncle was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = -0.00002071, = .0445), though these findings were not statistically significant after multiple comparisons correction. These optimized linear mixed effects models possibly implicate corpus callosum and cerebellar pathology in development of autism spectrum disorder in tuberous sclerosis complex, but future studies are needed to replicate these findings and explore contributors of heterogeneity in these models.
脑白质发育异常可能会影响结节性硬化症(TSC)患者自闭症谱系障碍的发展。本研究的目的如下:(1)利用 TSC 的纵向神经影像学研究(TACERN)的数据,开发优化的线性混合效应模型,分析与 36 个月时自闭症诊断观察量表第二版(ADOS-2)阳性分类相关的、针对特定白质束的纵向重复扩散张量成像指标(各向异性分数、平均弥散度);(2)利用这些数据中所有白质束的优化模型进行探索性分析。符合条件的参与者(3-12 个月)在 3 至 36 个月期间进行了多次脑磁共振成像(MRI)。36 个月时的自闭症诊断观察量表第二版阳性分类被用作结果。分别对各向异性分数值(以胼胝体各向异性分数为测试结果)和平均弥散度值(以右侧后内囊体平均弥散度为测试结果)进行精细调整线性混合效应模型。固定效应包括参与者年龄、参与者内纵向年龄和自闭症谱系障碍诊断。分析纳入了 n=78 名参与者的数据。在为各向异性分数和平均弥散度值选择了单独的最佳模型后,我们将这些模型应用于所有 27 个白质束的各向异性分数和平均弥散度。胼胝体各向异性分数与自闭症诊断观察量表第二版阳性分类相关(系数=0.0093,=0.0612),而右侧小脑下脚平均弥散度与自闭症诊断观察量表第二版阳性分类相关(系数=-0.00002071,=0.0445),但在多次比较校正后,这些发现没有统计学意义。这些优化的线性混合效应模型可能提示胼胝体和小脑病理学与结节性硬化症自闭症谱系障碍的发展有关,但需要进一步的研究来复制这些发现,并探讨这些模型中异质性的贡献因素。