He Hao, Yu Qingbao, Du Yuhui, Vergara Victor, Victor Teresa A, Drevets Wayne C, Savitz Jonathan B, Jiang Tianzi, Sui Jing, Calhoun Vince D
The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA; Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, NM, USA.
The Mind Research Network & Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, USA.
J Affect Disord. 2016 Jan 15;190:483-493. doi: 10.1016/j.jad.2015.10.042. Epub 2015 Oct 31.
Differentiating bipolar disorder (BD) from major depressive disorder (MDD) often poses a major clinical challenge, and optimal clinical care can be hindered by misdiagnoses. This study investigated the differences between BD and MDD in resting-state functional network connectivity (FNC) using a data-driven image analysis method.
In this study, fMRI data were collected from unmedicated subjects including 13 BD, 40 MDD and 33 healthy controls (HC). The FNC was calculated between functional brain networks derived from fMRI using group independent component analysis (ICA). Group comparisons were performed on connectivity strengths and other graph measures of FNC matrices.
Statistical tests showed that, compared to MDD, the FNC in BD was characterized by more closely connected and more efficient topological structures as assessed by graph theory. The differences were found at both the whole-brain-level and the functional-network-level in prefrontal networks located in the dorsolateral/ventrolateral prefrontal cortex (DLPFC, VLPFC) and anterior cingulate cortex (ACC). Furthermore, interconnected structures in these networks in both patient groups were negatively associated with symptom severity on depression rating scales.
As patients were unmedicated, the sample sizes were relatively small, although they were comparable to those in previous fMRI studies comparing BD and MDD.
Our results suggest that the differences in FNC of the PFC reflect distinct pathophysiological mechanisms in BD and MDD. Such findings ultimately may elucidate the neural pathways in which distinct functional changes can give rise to the clinical differences observed between these syndromes.
区分双相情感障碍(BD)和重度抑郁症(MDD)常常是一项重大的临床挑战,误诊可能会阻碍最佳临床护理。本研究使用数据驱动的图像分析方法,调查了BD和MDD在静息态功能网络连通性(FNC)方面的差异。
在本研究中,收集了未接受药物治疗的受试者的功能磁共振成像(fMRI)数据,包括13名BD患者、40名MDD患者和33名健康对照(HC)。使用组独立成分分析(ICA)从fMRI得出的功能性脑网络之间计算FNC。对FNC矩阵的连通性强度和其他图形指标进行组间比较。
统计测试表明,与MDD相比,通过图论评估,BD中的FNC具有更紧密连接和更高效的拓扑结构。在位于背外侧/腹外侧前额叶皮层(DLPFC、VLPFC)和前扣带回皮层(ACC)的前额叶网络的全脑水平和功能网络水平均发现了差异。此外,两个患者组中这些网络中的相互连接结构与抑郁评定量表上的症状严重程度呈负相关。
由于患者未接受药物治疗,样本量相对较小,尽管与之前比较BD和MDD的fMRI研究中的样本量相当。
我们的结果表明,前额叶皮层FNC的差异反映了BD和MDD中不同的病理生理机制。这些发现最终可能阐明神经通路,其中不同的功能变化可能导致这些综合征之间观察到的临床差异。