PDF(Pubmed)
Abstract：
OBJECTIVE: Spinal muscular atrophy (SMA) is one of the most common monogenic neuromuscular diseases, and the pathogenesis mechanisms, especially the brain network topological properties, remain unknown. This study aimed to use individual-level morphological brain network analysis to explore the brain neural network mechanisms in SMA.
METHODS: Individual-level gray matter (GM) networks were constructed by estimating the interregional similarity of GM volume distribution using both Kullback-Leibler divergence-based similarity (KLDs) and Jesen-Shannon divergence-based similarity (JSDs) measurements based on Automated Anatomical Labeling 116 and Hammersmith 83 atlases for 38 individuals with SMA types 2 and 3 and 38 age- and sex-matched healthy controls (HCs). The topological properties were analyzed by the graph theory approach and compared between groups by a nonparametric permutation test. Additionally, correlation analysis was used to assess the associations between altered topological metrics and clinical characteristics.
RESULTS: Compared with HCs, although global network topology remained preserved in individuals with SMA, brain regions with altered nodal properties mainly involved the right olfactory gyrus, right insula, bilateral parahippocampal gyrus, right amygdala, right thalamus, left superior temporal gyrus, left cerebellar lobule IV-V, bilateral cerebellar lobule VI, right cerebellar lobule VII, and vermis VII and IX. Further correlation analysis showed that the nodal degree of the right cerebellar lobule VII was positively correlated with the disease duration, and the right amygdala was negatively correlated with the Hammersmith Functional Motor Scale Expanded (HFMSE) scores.
CONCLUSIONS: Our findings demonstrated that topological reorganization may prioritize global properties over nodal properties, and disrupted topological properties in the cortical-limbic-cerebellum circuit in SMA may help to further understand the network pathogenesis underlying SMA.
METHODS: Individual-level gray matter (GM) networks were constructed by estimating the interregional similarity of GM volume distribution using both Kullback-Leibler divergence-based similarity (KLDs) and Jesen-Shannon divergence-based similarity (JSDs) measurements based on Automated Anatomical Labeling 116 and Hammersmith 83 atlases for 38 individuals with SMA types 2 and 3 and 38 age- and sex-matched healthy controls (HCs). The topological properties were analyzed by the graph theory approach and compared between groups by a nonparametric permutation test. Additionally, correlation analysis was used to assess the associations between altered topological metrics and clinical characteristics.
RESULTS: Compared with HCs, although global network topology remained preserved in individuals with SMA, brain regions with altered nodal properties mainly involved the right olfactory gyrus, right insula, bilateral parahippocampal gyrus, right amygdala, right thalamus, left superior temporal gyrus, left cerebellar lobule IV-V, bilateral cerebellar lobule VI, right cerebellar lobule VII, and vermis VII and IX. Further correlation analysis showed that the nodal degree of the right cerebellar lobule VII was positively correlated with the disease duration, and the right amygdala was negatively correlated with the Hammersmith Functional Motor Scale Expanded (HFMSE) scores.
CONCLUSIONS: Our findings demonstrated that topological reorganization may prioritize global properties over nodal properties, and disrupted topological properties in the cortical-limbic-cerebellum circuit in SMA may help to further understand the network pathogenesis underlying SMA.
摘要：
目的：脊髓性肌萎缩症（SMA）是最常见的单基因神经肌肉疾病之一，和发病机制，特别是大脑网络拓扑特性，仍然未知。本研究旨在使用个体水平的形态学脑网络分析来探索SMA中的脑神经网络机制。
方法：通过使用基于Kullback-Leibler散度的相似性（KLDs）和基于Jesen-Shannon散度的相似性（JSDs）测量来估计GM体积分布的区域间相似性来构建个体水平灰质（GM）网络。基于自动解剖标记116和Hammersmith83地图集，对38个SMA2型和3型与健康和性别（38个通过图论方法分析了拓扑特性，并通过非参数置换检验在组之间进行了比较。此外,相关分析用于评估改变的拓扑指标与临床特征之间的关联.
结果：与HC相比，尽管全局网络拓扑仍然保留在具有SMA的个体中，结节性质改变的大脑区域主要涉及右嗅觉回，右岛，双侧海马旁回，右杏仁核,右丘脑,左颞上回,左小脑小叶IV-V,双侧小脑小叶VI，右小脑小叶VII,和VermisVII和IX。进一步的相关分析显示右侧小脑小叶VII的结节程度与病程呈正相关,右侧杏仁核与Hammersmith功能运动量表（HFMSE）评分呈负相关。
结论：我们的研究结果表明，拓扑重组可能优先考虑全局属性而不是节点属性，SMA中皮质-边缘-小脑回路的拓扑特性中断可能有助于进一步了解SMA背后的网络发病机制。
方法：通过使用基于Kullback-Leibler散度的相似性（KLDs）和基于Jesen-Shannon散度的相似性（JSDs）测量来估计GM体积分布的区域间相似性来构建个体水平灰质（GM）网络。基于自动解剖标记116和Hammersmith83地图集，对38个SMA2型和3型与健康和性别（38个通过图论方法分析了拓扑特性，并通过非参数置换检验在组之间进行了比较。此外,相关分析用于评估改变的拓扑指标与临床特征之间的关联.
结果：与HC相比，尽管全局网络拓扑仍然保留在具有SMA的个体中，结节性质改变的大脑区域主要涉及右嗅觉回，右岛，双侧海马旁回，右杏仁核,右丘脑,左颞上回,左小脑小叶IV-V,双侧小脑小叶VI，右小脑小叶VII,和VermisVII和IX。进一步的相关分析显示右侧小脑小叶VII的结节程度与病程呈正相关,右侧杏仁核与Hammersmith功能运动量表（HFMSE）评分呈负相关。
结论：我们的研究结果表明，拓扑重组可能优先考虑全局属性而不是节点属性，SMA中皮质-边缘-小脑回路的拓扑特性中断可能有助于进一步了解SMA背后的网络发病机制。
