BACKGROUND:Structural brain deficits associated with generalized anxiety disorder (GAD), panic disorder (PD), and obsessive-compulsive disorder (OCD) have been documented, but their integration within a unified framework remains unexplored. This study investigates, in anxiety and anxiety-related disorders, whether they share neurophysiological bases, whether structural changes (SCs) are linked to common genes, whether shared SCs co-occur with similar functional brain impairments, and whether brain morphometry can serve as biomarkers for diagnosis and treatment prediction.
METHODS:Participants included 100 individuals with GAD, 58 with PD, 45 with OCD, and 85 healthy controls, all drug-free. Structural and resting-state functional magnetic resonance imaging scans and clinical assessments were conducted before and after 4 weeks of paroxetine monotherapy. Analyses included voxel-based and surface-based morphometry; functional connectivity (FC) and Granger causality analysis (GCA) with shared SCs as regions of interest; associations between clinical assessments and neuroimaging metrics; associations between gene expression profiles and SCs; and machine learning.
RESULTS:Cingulate atrophy (CA) emerged as a common SC, with disorder-specific atrophy in gray matter volume (GMV) and cortical surface. Transcriptome-neuroimaging correlations identified shared genetic associations with GMV alterations, with negatively correlated genes enriched in neurodevelopment and cellular growth regulation (ND-CGR). Cingulate GMV was positively correlated with cognitive performance in GAD and PD patients. FC and GCA showed CA disrupted networks governing emotional regulation and cognitive control, characterized by overactive top-down influence and reduced bottom-up feedback. Machine learning demonstrated strong performance in classification and treatment response prediction, with cingulate morphometry contributing significantly.
CONCLUSIONS:CA is a shared neural substrate in GAD, PD, and OCD, linked to genetic disruptions in ND-CGR, cognitive impairments, and functional brain deficits. Cingulate morphometry holds promise as a biomarker for diagnosis and treatment response in these conditions.