Abstract
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.