Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity.
Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity.
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DOI：
10.1001/jamapsychiatry.2015.0071
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发表时间：
2015-06
期刊：
影响因子：
25.8
通讯作者：
Pizzagalli, Diego A.
中科院分区：
文献类型：
--
作者：
Kaiser, Roselinde H.;Andrews-Hanna, Jessica R.;Wager, Tor D.;Pizzagalli, Diego A.
重度抑郁症（MDD）与大规模脑网络之间的通信失衡有关，这反映在静息态功能连接（rsFC）异常上。然而，鉴于研究方法和结果各异，确定MDD中网络功能障碍的一致模式一直很困难。
通过对rsFC研究的首次荟萃分析来研究MDD中的网络功能障碍。
从电子数据库（PubMed、Web of Science、EMBASE）中检索比较MDD患者与健康个体的基于种子体素的rsFC研究（2014年6月30日之前发表），并联系作者获取额外数据。
荟萃分析纳入了来自25篇出版物的27个数据集（556名成年/青少年MDD患者；518名对照）。
提取了感兴趣种子区域的坐标以及组间效应。根据种子在先验功能网络中的位置将其分类为“种子网络”。对组间效应的多级核密度分析确定了在哪些脑系统中MDD与每个种子网络存在超连接（正连接增加或负连接减少）或低连接（负连接增加或正连接减少）。
MDD的特征是额顶网络（FN）内的低连接，额顶网络是一组参与注意力的认知控制和情绪调节的区域，以及额顶系统与参与关注外部环境的背侧注意网络（DAN）的顶叶区域之间的低连接。MDD还与默认网络（DN）内的超连接有关，默认网络被认为支持内部导向和自我参照的思维，以及FN控制系统与DN区域之间的超连接。最后，MDD组在参与处理情绪或显著性的神经系统与可能介导此类功能自上而下调节的中线皮质区域之间表现出低连接。
额顶控制系统内连接减少，以及控制系统与参与内部或外部注意力的网络之间连接失衡，可能反映了以忽视外部世界为代价偏向内部思维的抑郁倾向。同时，参与认知控制的神经系统与支持显著性或情绪处理的神经系统之间连接改变可能与情绪调节缺陷有关。这些发现为一种神经认知模型提供了实证基础，在该模型中网络功能障碍是抑郁症核心认知和情感异常的基础。
Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. To investigate network dysfunction in MDD through the first meta-analysis of rsFC studies. Seed-based voxel-wise rsFC studies comparing MDD with healthy individuals (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web-of-Science, EMBASE), and authors contacted for additional data. Twenty-seven datasets from 25 publications (556 MDD adults/teens; 518 controls) were included in the meta-analysis. Coordinates of seed regions-of-interest and between-group effects were extracted. Seeds were categorized into “seed-networks” by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive, or reduced negative, connectivity) or hypoconnectivity (increased negative, or reduced positive, connectivity) with each seed-network. MDD was characterized by hypoconnectivity within the frontoparietal network (FN), a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network (DAN) involved in attending to the external environment. MDD was also associated with hyperconnectivity within the default network (DN), a network believed to support internally-oriented and self-referential thought, and hyperconnectivity between FN control systems and regions of DN. Finally, MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. Reduced connectivity within frontoparietal control systems, and imbalanced connectivity between control systems and networks involved in internal- or external-attention, may reflect depressive biases towards internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.
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