重性抑郁障碍
神经影像学
哈姆德
焦虑
心理学
萧条(经济学)
汉密尔顿焦虑量表
楔前
汉密尔顿抑郁量表
内科学
精神科
临床心理学
医学
认知
宏观经济学
经济
作者
Songhao Hu,Li Zhu,Xiangyang Zhang
标识
DOI:10.3389/fpsyt.2025.1589040
摘要
Background Anxious depression (AD) is a clinically significant subtype of major depressive disorder (MDD) characterized by prominent anxiety symptoms. Emerging neuroimaging evidence shows that AD patients have significantly altered brain structure. This study aimed to identify reliable neuroimaging biomarkers for AD in a Chinese cohort. Methods Participants were recruited from the REST-meta-MDD project, including 178 MDD patients and 89 healthy controls. MDD patients were stratified into 89 patients with AD and 89 with non-anxious depression (NAD). Voxel-based morphometry (VBM) was used to quantify gray matter volume (GMV) using T1-weighted images. Depressive and anxiety symptoms were assessed using the Hamilton Depression Rating Scale (HAMD-17) and the Hamilton Anxiety Rating Scale (HAMA-14). Structural covariance (SC) analysis was employed to investigate coordinated morphological changes across brain regions. Additionally, a support vector regression (SVR) model was constructed to predict anxiety severity in MDD patients, with external validation performed in an independent dataset. Results In AD patients, significant increases in GMV were observed in the right precuneus (PCUN) and right superior parietal gyrus (SPG). Reduced SC was also found between the right PCUN and left anterior cingulate gyrus (ACG), as well as between the right PCUN and right angular gyrus (ANG). Additionally, SVR analysis demonstrated that the right PCUN GMV could effectively predict MDD patients’ HAMA-14 scores ( r = 0.477, MSE = 73.865), validated in an independent external dataset (r = 0.368, MSE = 100.961). Conclusions This study’s findings indicate that brain structural abnormalities may be a crucial pathophysiological basis for AD.
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