Adolescent major depressive disorder (MDD) has been associated with cortical structural abnormalities. However, whether these structural changes correlate with gene expression profiles remains unclear. Here, we investigated the cortical similarity network alterations and the associated transcriptional patterns in adolescents with MDD using a novel Morphometric Inverse Divergence (MIND) network model.

Using structural images from 174 adolescents with MDD and 82 healthy controls (HCs), we constructed individual MIND networks based on multiple morphological features. We compared regional MIND between groups and developed machine learning models to assess the potential of MIND for distinguishing patients from HCs. Spatial associations between MIND differences and gene expression profiles were assessed using partial least squares regression, followed by gene enrichment analyses to identify associated biological pathways, cell types, and developmental trajectories.

Regional MIND abnormalities in adolescent MDD patients were primarily located in the orbitofrontal cortex, as well as in sensorimotor and visual network regions. Using MIND features, the optimal machine learning model achieved a high area under the curve (AUC) of 0.824 and generalized well to the external independent dataset (AUC = 0.724). MIND changes were associated with gene expression related to synaptic signaling, neurodevelopment, metabolism, and specific cell types. Developmental trajectory analysis suggested distinct, region-specific susceptibility windows for adolescent MDD.

By linking MIND network alterations and transcriptional expression profiles, this study provides new insights into the neural basis and associated molecular mechanisms underlying adolescent MDD and underscores the diagnostic potential of MIND.

Major depressive disorder (MDD) tends to emerge during adolescence; however, neurobiological research in adolescents has lagged behind that in adults. This study aimed to characterize gray matter (GM) structural alterations in adolescents with MDD using comprehensive morphological analyses.

This study included 93 adolescent MDD patients and 77 healthy controls. Voxel-based morphometry (VBM), deformation-based morphometry (DBM), and surface-based morphometry (SBM) methods were used to analyze GM morphological alterations in adolescent MDD patients. Sex-by-group and age-by-group interactions, as well as the relationships between altered GM structure and clinical characteristics were also analyzed.

Whole-brain VBM and DBM analyses revealed GM atrophy in the left thalamus and bilateral midbrain in adolescent MDD patients. Whole-brain SBM analysis revealed that adolescent MDD patients, relative to controls, showed decreased thickness in the left postcentral gyrus and left precentral gyrus; increased thickness in the bilateral superior temporal gyrus, left parahippocampal gyrus and right lateral orbitofrontal gyrus; and decreased fractal dimension in the right lateral occipital gyrus. A significant sex-by-group interaction effect was found in the fractal dimension of the left lateral occipital gyrus. The volume of the left thalamus and the thickness of the left superior temporal gyrus were correlated with the duration of disease in adolescent MDD patients.

This study suggested that adolescent MDD had GM morphological abnormalities in the frontal-limbic, subcortical, perceptual network and midbrain regions, with some morphological abnormalities associated with disease duration and sex differences. These findings provide new insight into the neuroanatomical substrates underlying adolescent MDD.