Structural Connectome Architecture Shapes Cortical Atrophy in Major Depressive Disorder: A Chinese DIRECT Consortium...

Cortical morphological alterations are evident in major depressive disorder (MDD), yet the underlying neurobiological processes that contribute to their characteristic spatial pattern remain unclear.

Large-scale, multisite structural magnetic resonance imaging data from a homogeneous Chinese cohort of 1442 patients with MDD and 1277 healthy control participants were used to calculate cortical morphological measures, which were compared between groups to determine cortical morphological alterations in MDD. A connectome constraint model was then used to examine whether the structural connectome shapes MDD-related cortical morphological alterations, followed by performance of a network diffusion model to identify the epicenters.

Group comparisons demonstrated a broadly distributed cortical thickness (CT) reduction in MDD, with the prefrontal cortex affected more prominently. Based on the normative structural connectome, we derived the estimated CT alteration of each brain node according to its connected neighbors and found a strong spatial correlation between the empirical and estimated CT alterations, indicating structural connectome constraint on cortical atrophy in MDD. Concurrently, we identified the left lateral prefrontal cortex as the putative epicenter of cortical atrophy. Moreover, analyses across first-episode, early-stage, and chronic MDD subgroups revealed reduced connectome constraint with increasing illness duration. Additionally, our results were robust against several methodological variations and were largely reproducible in the cross-ethnic ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) cohort of 1902 patients with MDD and 7658 control participants.

These findings represent a substantial advance in our understanding of the network-based spread of cortical atrophy in MDD and highlight the prospect of the left prefrontal cortex as a key target for early interventions.