Structural Covariance Reveals Alterations in Control and Salience Network Integrity in Chronic Schizophrenia
Structural Covariance Reveals Alterations in Control and Salience Network Integrity in Chronic Schizophrenia
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DOI：
10.1093/cercor/bhz064
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发表时间：
2019-12-01
期刊：
影响因子：
3.7
通讯作者：
Anticevic, Alan
中科院分区：
文献类型：
--
作者：
Spreng, R. Nathan;DuPre, Elizabeth;Anticevic, Alan
精神分裂症（SCZ）被认为是一种分布式大脑连接障碍。虽然已经取得了进展，描绘大规模的功能网络在SCZ，很少有人知道这些网络的灰质完整性的改变。我们使用了多变量的方法来确定的显着性，默认，运动，视觉，额顶控制，和背侧注意网络的结构协方差。我们导出了反映给定网络的每个结构图像中的协方差的个体分数。对SCZ患者和健康对照的发现（n=90）和复制（n=74）样品中的结构图像进行基于种子的多变量分析。我们首先验证了所有网络的模式，与完善的功能连接报告一致。接下来，在两个SCZ样本中，我们发现额顶叶控制和显着性网络的结构完整性可靠且稳健地降低，但默认，背侧注意，运动和感觉网络没有降低。有效的探索性分析未能确定与症状的关系。这些研究结果提供了证据，选择性结构下降的联想网络在SCZ。这种下降可能与最近发现的功能障碍，在联想网络，提供更敏感的多模态网络水平的探头SCZ。缺乏症状的影响表明，确定的障碍可能是SCZ的特征型标记。
Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n=90) and replication (n=74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ.