Large-Scale Hypoconnectivity Between Resting-State Functional Networks in Unmedicated Adolescent Major Depressive Disorder

Abstract

Major depressive disorder (MDD) often emerges during adolescence, a critical period of brain development. Recent resting-state fMRI studies of adults suggest that MDD is associated with abnormalities within and between resting-state networks (RSNs). Here we tested whether adolescent MDD is characterized by abnormalities in interactions among RSNs. Participants were 55 unmedicated adolescents diagnosed with MDD and 56 matched healthy controls. Functional connectivity was mapped using resting-state fMRI. We used the network-based statistic (NBS) to compare large-scale connectivity between groups and also compared the groups on graph metrics. We further assessed whether group differences identified using nodes defined from functionally defined RSNs were also evident when using anatomically defined nodes. In addition, we examined relations between network abnormalities and depression severity and duration. Finally, we compared intranetwork connectivity between groups and assessed the replication of previously reported MDD-related abnormalities in connectivity. The NBS indicated that, compared with controls, depressed adolescents exhibited reduced connectivity (p<0.024, corrected) between a specific set of RSNs, including components of the attention, central executive, salience, and default mode networks. The NBS did not identify group differences in network connectivity when using anatomically defined nodes. Longer duration of depression was significantly correlated with reduced connectivity in this set of network interactions (p=0.020, corrected), specifically with reduced connectivity between components of the dorsal attention network. The dorsal attention network was also characterized by reduced intranetwork connectivity in the MDD group. Finally, we replicated previously reported abnormal connectivity in individuals with MDD. In summary, adolescents with MDD show hypoconnectivity between large-scale brain networks compared with healthy controls. Given that connectivity among these networks typically increases during adolescent neurodevelopment, these results suggest that adolescent depression is associated with abnormalities in neural systems that are still developing during this critical period.

Figure 1

Resting-state networks (RSNs) and processing pipeline. (a) 17-network solution RSNs used as nodes in the network analyses by Yeo et al (2011). Multiple views of each hemisphere of cortical renderings of the 17-network solution RSNs by Yeo et al (2011). Each color represents a different 17-network solution RSN. See Table 1 for RSN functional labels. (b) (1) T1-weighted (T1w) and echo planar fMRI images (EPIs) were acquired using an MRI system. (2) T1w and EPI images were preprocessed, including normalization to MNI space. (3) Time courses were extracted from each RSN (nodes), and functional connectivity was assessed for all pairs of RSNs (edges). (4) This resulted in a 17 × 17 correlation matrix for each participant. (5) These correlation matrices were used in subsequent network analyses using the network-based statistic (NBS) and graph theory.

Figure 2

Results of the network-based statistic (NBS). Schemaball representation of reduced connectivity between resting-state networks (RSNs) in the MDD compared with the CTL group. Network colors and numbers (associated with a given node represented as a square) correspond with those presented in Figure 1. Red lines indicate reduced connectivity in the MDD vs CTL group between the given networks identified using NBS. All results controlled for age, gender, and levels of intelligence. See Table 2 for network labels and Table 3 for details on results from the NBS.