Heterogeneous lifespan development of functional networks in major depression and its association with clinical and gene expression profiles

Motivation: Depression is a heterogeneous disorder linked to abnormal development of functional networks across the lifespan. However, neurodevelopmental heterogeneity in depression is not well understood. Goal(s): To investigate heterogeneous neurodevelopmental functional networks abnormalities in depression and their associations with clinical and gene expression profiles. Approach: We assessed brain age gap in depression using machine learning, identified divergent developmental trajectories of network topography, and conducted multivariate analyses of topography with clinical symptoms and gene expressions. Results: Depression-related brain age gaps were primarily associated with abnormal topography of ventral attention and sensorimotor networks, revealing two distinct developmental trajectories linked to specific clinical and gene expression profiles. Impact: Our results highlight the heterogeneity of neurodevelopment in depression and suggest potential underlying molecular mechanisms, providing deeper insights into the disorder's progression and supporting the identification of biomarkers for precise diagnosis and treatment.