Seoul National University Hospital, Seoul, Republic of Korea.
Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
Brain. 2020 Feb 1;143(2):684-700. doi: 10.1093/brain/awaa001.
Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.
脑结构协变网络反映了不同脑区形态的协变,被认为反映了脑发育和成熟的共同轨迹。对强迫症(OCD)的结构协变网络进行大规模研究可能为这种神经发育障碍的病理生理学提供线索。使用来自 37 个数据集的 1616 名 OCD 患者和 1463 名健康对照者的 T1 加权 MRI 扫描,我们计算了个体的脑结构协变网络(使用 33 个皮质表面区域、33 个皮质厚度值和 6 个皮质下体积的双侧平均值),其中边缘权重与两个脑形态特征之间的相似性成正比,即与健康对照者的偏差(即 z 分数转换)。使用网络分离(聚类和模块性)、网络集成(全局效率)及其平衡(小世界性)的度量来描述全局网络,并评估其社区成员资格。使用介数、接近度和特征向量中心性的度量对区域网络进行枢纽分析。使用元分析方法整合 37 个数据集的个体网络测量值。这些网络测量值在 K=0.10-0.25 范围内跨 37 个数据集进行汇总,使用元分析方法整合在 37 个数据集上。与健康对照组相比,在全局水平上,OCD 的结构协变网络表现出较低的聚类(P<0.0001)、较低的模块性(P<0.0001)和较低的小世界性(P=0.017)。检测社区成员资格强调了 OCD 中网络分离程度较低。在区域水平上,OCD 的尾状核和丘脑体积以及旁中央皮质表面积的中心性(秩转换)值较低,表明脑枢纽的分布发生了改变。扣带和眶额皮质以及其他脑区的中心性与 OCD 疾病持续时间相关,表明这些脑区与疾病的慢性程度关系更大。总之,这项迄今为止最大的 OCD 脑结构协变研究的发现表明,OCD 中结构协变网络的组织更为分散,脑枢纽发生重组。分离的发现表明 OCD 中可能存在脑形态学改变的特征,而枢纽的发现表明 OCD 与脑发育和成熟轨迹的改变有关,特别是在扣带和眶额区域。