PDF(Pubmed)
Abstract：
Background: 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. Methods: 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. Results: 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, P = .0612), and mean diffusivity right inferior cerebellar peduncle was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = -0.00002071, P = .0445), though these findings were not statistically significant after multiple comparisons correction. Conclusion: 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.
摘要：
背景：白质发育异常可能影响结节性硬化症（TSC）中自闭症谱系障碍的发展。本研究的目标如下：（1）使用结节性硬化症（TACERN）的纵向神经影像学研究数据来开发优化的线性混合效应模型，以分析纵向，重复扩散张量成像度量(分数各向异性，平均扩散率)与选定的白质区域有关，关于36个月时的阳性自闭症诊断观察时间表-第二版分类，（2）使用应用于这些数据的所有白质束的优化模型进行探索性分析。方法：符合条件的参与者（3-12个月）在3至36个月的重复时间点接受了脑磁共振成像（MRI）。使用36个月时的阳性自闭症诊断观察时间表-第二版分类。线性混合效应模型分别针对各向异性分数值（使用各向异性分数作为测试结果）和平均扩散率值（使用平均扩散率右后肢内囊作为测试结果）进行了微调。固定效应包括参与者年龄，参与者内纵向年龄，和自闭症谱系障碍的诊断。结果:分析包括来自n=78的数据。在为分数各向异性和平均扩散率值选择单独的最佳模型后，我们将这些模型应用于所有27个白质束的分数各向异性和平均扩散率。call体各向异性分数与自闭症诊断观察量表第二版分类有关（系数=0.0093，P=.0612），和平均扩散率右小脑下脚与自闭症诊断观察时间表-第二版分类有关（系数=-0.00002071，P=.0445），尽管这些发现在多重比较校正后没有统计学意义.结论：这些优化的线性混合效应模型可能暗示call体和小脑病理参与结节性硬化症自闭症谱系障碍的发展。但未来的研究需要重复这些发现,并探索这些模型中异质性的贡献者.
