Gao Yujun, Guo Xin, Zhong Yi, Liu Xiaoxin, Tian Shanshan, Deng Jiahui, Lin Xiao, Bao Yanpin, Lu Lin, Wang Gaohua
Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430000, China.
Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, Peking University, Beijing 100191, China; National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Peking University, Beijing 100191, China.
J Affect Disord. 2023 Jul 1;332:136-142. doi: 10.1016/j.jad.2023.03.080. Epub 2023 Mar 28.
Gaining insight into abnormal functional brain network homogeneity (NH) has the potential to aid efforts to target or otherwise study major depressive disorder (MDD). The NH of the dorsal attention network (DAN) in first-episode treatment-naive MDD patients, however, has yet to be studied. As such, the present study was developed to explore the NH of the DAN in order to determine the ability of this parameter to differentiate between MDD patients and healthy control (HC) individuals.
This study included 73 patients with first-episode treatment-naive MDD and 73 age-, gender-, and educational level-matched healthy controls. All participants completed the attentional network test (ANT), Hamilton Rating Scale for Depression (HRSD), and resting-state functional magnetic resonance imaging (rs-fMRI) analyses. A group independent component analysis (ICA) was used to identify the DAN and to compute the NH of the DAN in patients with MDD. Spearman's rank correlation analyses were used to explore relationships between significant NH abnormalities in MDD patients, clinical parameters, and executive control reaction time.
Relative to HCs, patients exhibited reduced NH in the left supramarginal gyrus (SMG). Support vector machine (SVM) analyses and receiver operating characteristic curves indicated that the NH of the left SMG could be used to differentiate between HCs and MDD patients with respective accuracy, specificity, sensitivity, and AUC values of 92.47 %, 91.78 %, 93.15 %, and 65.39 %. A significant positive correlation was observed between the left SMG NH values and HRSD scores among MDD patients.
These results suggest that NH changes in the DAN may offer value as a neuroimaging biomarker capable of differentiating between MDD patients and healthy individuals.
深入了解异常的大脑功能网络同质性（NH）有助于针对重度抑郁症（MDD）进行靶向治疗或开展其他相关研究。然而，首发未治疗的MDD患者背侧注意网络（DAN）的NH尚未得到研究。因此，本研究旨在探索DAN的NH，以确定该参数区分MDD患者与健康对照（HC）个体的能力。
本研究纳入73例首发未治疗的MDD患者和73名年龄、性别及教育水平相匹配的健康对照。所有参与者均完成了注意网络测试（ANT）、汉密尔顿抑郁评定量表（HRSD）以及静息态功能磁共振成像（rs-fMRI）分析。采用组独立成分分析（ICA）识别DAN，并计算MDD患者DAN的NH。采用Spearman等级相关分析探讨MDD患者显著的NH异常、临床参数与执行控制反应时间之间的关系。
与HC相比，患者左侧缘上回（SMG）的NH降低。支持向量机（SVM）分析及受试者工作特征曲线表明，左侧SMG的NH可用于区分HC和MDD患者，其准确度、特异性、敏感性及曲线下面积（AUC）值分别为92.47%、91.78%、93.15%和65.39%。MDD患者中，左侧SMG的NH值与HRSD评分之间存在显著正相关。
这些结果表明，DAN的NH变化可能作为一种神经影像生物标志物，有助于区分MDD患者与健康个体。
