He Mengxin, Cheng Yuqi, Chu Zhaosong, Wang Xin, Xu Jinlei, Lu Yi, Shen Zonglin, Xu Xiufeng
Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Yunnan Clinical Research Center for Mental Disorders, Kunming, China.
Front Psychiatry. 2022 Apr 14;13:816191. doi: 10.3389/fpsyt.2022.816191. eCollection 2022.
The efficacy and prognosis of major depressive disorder (MDD) are limited by its heterogeneity. MDD with melancholic features is an important subtype of MDD. The present study aimed to reveal the white matter (WM) network changes in melancholic depression.
Twenty-three first-onset, untreated melancholic MDD, 59 non-melancholic MDD patients and 63 health controls underwent diffusion tensor imaging (DTI) scans. WM network analysis based on graph theory and support vector machine (SVM) were used for image data analysis.
Compared with HC, small-worldness was reduced and abnormal node attributes were in the right orbital inferior frontal gyrus, left orbital superior frontal gyrus, right caudate nucleus, right orbital superior frontal gyrus, right orbital middle frontal gyrus, left rectus gyrus, and left median cingulate and paracingulate gyrus of MDD patients. Compared with non-melancholic MDD, small-worldness was reduced and abnormal node attributes were in right orbital inferior frontal gyrus, left orbital superior frontal gyrus and right caudate nucleus of melancholic MDD. For correlation analysis, the 7th item score of the HRSD-17 (work and interest) was positively associated with increased node betweenness centrality (aBC) values in right orbital inferior frontal gyrus, while negatively associated with the decreased aBC in left orbital superior frontal gyrus. SVM analysis results showed that abnormal aBC in right orbital inferior frontal gyrus and left orbital superior frontal gyrus showed the highest accuracy of 81.0% (69/83), the sensitivity of 66.3%, and specificity of 85.2% for discriminating MDD patients with or without melancholic features.
There is a significant difference in WM network changes between MDD patients with and without melancholic features.
重度抑郁症(MDD)的疗效和预后受其异质性限制。伴有抑郁特征的MDD是MDD的一种重要亚型。本研究旨在揭示抑郁性抑郁症的白质(WM)网络变化。
23例首发、未治疗的抑郁性MDD患者、59例非抑郁性MDD患者和63名健康对照者接受了扩散张量成像(DTI)扫描。基于图论和支持向量机(SVM)的WM网络分析用于图像数据分析。
与健康对照相比,MDD患者的小世界特性降低,异常节点属性位于右侧眶额下回、左侧眶额上回、右侧尾状核、右侧眶额上回、右侧眶额中回、左侧直回以及左侧中央扣带回和旁扣带回。与非抑郁性MDD相比,抑郁性MDD的小世界特性降低,异常节点属性位于右侧眶额下回、左侧眶额上回和右侧尾状核。对于相关性分析,HRSD-17(工作和兴趣)的第7项得分与右侧眶额下回节点介数中心性(aBC)值增加呈正相关,而与左侧眶额上回aBC降低呈负相关。SVM分析结果表明,右侧眶额下回和左侧眶额上回的异常aBC对区分有无抑郁特征的MDD患者具有最高准确率81.0%(69/83)、敏感度66.3%和特异度85.2%。
伴有和不伴有抑郁特征的MDD患者在WM网络变化方面存在显著差异。