Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Neuroimaging Center at the Technische Universität München, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Department of Psychiatry, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Neuroimaging Center at the Technische Universität München, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Biol Psychiatry. 2019 Apr 1;85(7):573-583. doi: 10.1016/j.biopsych.2018.12.003. Epub 2018 Dec 11.
This study investigated characteristic large-scale brain changes in schizophrenia. Numerous imaging studies have demonstrated brain changes in schizophrenia, particularly aberrant intrinsic functional connectivity (iFC) of ongoing brain activity, measured by resting-state functional magnetic resonance imaging, and aberrant gray matter volume (GMV) of distributed brain regions, measured by structural magnetic resonance imaging. It is unclear, however, which iFC changes are specific to schizophrenia compared with those of other disorders and whether such specific iFC changes converge with GMV changes. To address this question of specific substantial dysconnectivity in schizophrenia, we performed a transdiagnostic multimodal meta-analysis of resting-state functional and structural magnetic resonance imaging studies in schizophrenia and other psychiatric disorders.
Multiple databases were searched up to June 2017 for whole-brain seed-based iFC studies and voxel-based morphometry studies in schizophrenia, major depressive disorder, bipolar disorder, addiction, and anxiety. Coordinate-based meta-analyses were performed to detect 1) schizophrenia-specific hyperconnectivity or hypoconnectivity of intrinsic brain networks (compared with hyperconnectivity or hypoconnectivity of each other disorder both separately and combined across comparisons) and 2) the overlap between dysconnectivity and GMV changes (via multimodal conjunction analysis).
For iFC meta-analysis, 173 publications comprising 4962 patients and 4575 control subjects were included, and for GMV meta-analysis, 127 publications comprising 6311 patients and 6745 control subjects were included. Disorder-specific iFC dysconnectivity in schizophrenia (consistent across comparisons with other disorders) was found for limbic, frontoparietal executive, default mode, and salience networks. Disorder-specific dysconnectivity and GMV reductions converged in insula, lateral postcentral cortex, striatum, and thalamus.
Results demonstrated specific substantial dysconnectivity in schizophrenia in insula, lateral postcentral cortex, striatum, and thalamus. Data suggest that these regions are characteristic targets of schizophrenia.
本研究旨在探讨精神分裂症的特征性大脑大范围变化。大量影像学研究表明，精神分裂症患者的大脑存在变化，尤其是静息态功能磁共振成像（rs-fMRI）测量的大脑活动固有功能连接（iFC）异常，以及结构磁共振成像（MRI）测量的分布脑区的灰质体积（GMV）异常。然而，尚不清楚与其他疾病相比，哪些 iFC 变化是精神分裂症特有的，以及这些特有的 iFC 变化是否与 GMV 变化相重合。为了明确精神分裂症患者是否存在特定的实质性连接异常，我们对精神分裂症及其他精神疾病的 rs-fMRI 和结构 MRI 研究进行了跨诊断的多模态荟萃分析。
我们检索了多个数据库，以获取截止到 2017 年 6 月的精神分裂症、重性抑郁障碍、双相情感障碍、成瘾和焦虑症的全脑种子 iFC 研究和基于体素形态计量学研究。采用基于坐标的荟萃分析来检测 1）与每个其他疾病的异常连接（无论是单独比较还是综合比较）相比，精神分裂症特有的内在脑网络的过度连接或连接不足，以及 2）连接异常与 GMV 变化之间的重叠（通过多模态联合分析）。
在 iFC 荟萃分析中，纳入了 173 项研究，共包含 4962 例患者和 4575 例对照，在 GMV 荟萃分析中，纳入了 127 项研究，共包含 6311 例患者和 6745 例对照。在精神分裂症中发现了与其他疾病比较具有一致性的，特定的、特有的 iFC 连接异常，包括边缘、额顶叶执行、默认模式和突显网络。特定的连接异常和 GMV 减少在脑岛、外侧后中央皮层、纹状体和丘脑上是一致的。
研究结果表明，在脑岛、外侧后中央皮层、纹状体和丘脑上存在精神分裂症的特定的、实质性的连接异常。数据表明这些区域是精神分裂症的特征性靶点。
