The Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China; Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan.
The Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China; Ministry of Education Frontiers Center for Brain Science, Institutes of Brain Science and Human Phenome Institute, Fudan University, Shanghai, China.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 May;5(5):542-553. doi: 10.1016/j.bpsc.2020.01.010. Epub 2020 Feb 10.
Mental disorders are typically defined as distinct diagnostic entities, but similar patterns of clinical and cognitive impairments are frequently found across diagnostic groups. We investigated whether these transdiagnostic deficits result from common neural substrates across disorders or various illness-specific mechanisms, or a combination of both.
Functional magnetic resonance imaging data were collected from clinically stable patients with major depressive disorder (n = 53), bipolar disorder (n = 78), or schizophrenia (n = 100) and matched healthy control subjects (n = 109) using a single scanner. Group comparisons were conducted to identify transdiagnostic and illness-specific features, and possible confounding effects of medication were considered. A multivariate approach with cross-validation was used to associate dysconnectivity features with shared cognitive deficits.
Transdiagnostic dysconnectivities were identified within somatomotor (Cohen's d = 0.50-0.58) and salience (Cohen's d = 0.52-0.58) networks and between subcortical-limbic (Cohen's d = 0.55-0.69) and subcortical-dorsal attention (Cohen's d = 0.56-0.61) networks. The executive control network was found to be illness-specifically disconnected from the prefrontal-limbic-pallidal circuit in major depressive disorder (Cohen's d = 0.57-0.58), prefronto-striato-parietal circuit in bipolar disorder (Cohen's d = 0.48-0.53), and default mode network in schizophrenia (Cohen's d = 0.47-0.56). Working memory deficits were associated with a linear combination of 11 transdiagnostic and 5 illness-specific dysconnectivities (r = .322, p= 9.7 × 10, n = 340). The associations of the identified dysconnectivities with medication dosage were nonsignificant.
Disconnectivity in the somatomotor network was a common transdiagnostic profile, while there were illness-specific patterns in different parts of the prefrontal cortex for different disorders. These findings suggest that prominent psychiatric disorders share common impairments, possibly linked to perception and motor output, as well as unique dysconnectivity profiles that hypothetically mediate the more distinctive features of the disorder-specific psychopathology.
精神障碍通常被定义为不同的诊断实体，但在不同的诊断组中经常发现相似的临床和认知障碍模式。我们研究了这些跨诊断缺陷是源于跨疾病的共同神经基础，还是各种特定疾病的机制，还是两者的组合。
使用单台扫描仪从患有重度抑郁症（n=53）、双相情感障碍（n=78）或精神分裂症（n=100）的临床稳定患者和匹配的健康对照者（n=109）中收集功能磁共振成像数据。进行组间比较以确定跨诊断和疾病特异性特征，并考虑药物治疗的可能混杂影响。使用具有交叉验证的多变量方法将功能连接不良与共享认知缺陷相关联。
在躯体运动（Cohen's d=0.50-0.58）和突显（Cohen's d=0.52-0.58）网络内以及皮质下-边缘（Cohen's d=0.55-0.69）和皮质下-背侧注意力（Cohen's d=0.56-0.61）网络之间确定了跨诊断功能连接不良。发现执行控制网络与重度抑郁症中的前额叶-边缘-苍白球回路（Cohen's d=0.57-0.58）、双相情感障碍中的前额叶-纹状体-顶叶回路（Cohen's d=0.48-0.53）和精神分裂症中的默认模式网络（Cohen's d=0.47-0.56）特异性断开连接。工作记忆缺陷与 11 个跨诊断和 5 个疾病特异性功能连接不良的线性组合相关（r=0.322，p=9.7×10，n=340）。鉴定出的功能连接不良与药物剂量之间的关联不显著。
躯体运动网络中的功能连接不良是一种常见的跨诊断特征，而不同疾病的前额叶皮层的不同部位则存在疾病特异性模式。这些发现表明，突出的精神障碍具有共同的缺陷，可能与感知和运动输出有关，以及假设介导疾病特异性精神病理学更独特特征的独特功能连接不良模式。
