Abnormal functional connectivity as neural biological substrate of trait and state characteristics in major depressive disorder.

OBJECTIVE: Major depressive disorder (MDD) is a neuropsychiatric disorder associated with functional dysconnectivity in emotion regulation system. State characteristics which measure the current presence of depressive symptoms, and trait characteristics which indicate the long-term vulnerability to depression are two important features of MDD. However, the relationships between trait and state characteristics of MDD and functional connectivity (FC) within the emotion regulation system still remain unclear. METHODS: This study aims to examine the neural biological mechanisms of trait characteristics measured by the Affective Neuroscience Personality Scale (ANPS) and state anhedonia measured by the Snaith-Hamilton Pleasure Scale (SHAPS) in MDD. Sixty-three patients with MDD and 63 well-matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. A spatial pairwise clustering and the network-based analysis approaches were adopted to identify the abnormal FC networks. Support vector regression was utilized to predict the trait and state characteristics based on abnormal FCs. RESULTS: Four disrupted subnetworks mainly involving the prefrontal-limbic-striatum system were observed in MDD. Importantly, the abnormal FC between the left amygdala (AMYG)/hippocampus (HIP) and right AMYG/HIP could predict the SADNESS scores of ANPS (trait characteristics) in MDD. While the aberrant FC between the medial prefrontal cortex (mPFC)/anterior cingulate gyrus (ACC) and AMYG/parahippocampal gyrus could predict the state anhedonia scores (state characteristics). CONCLUSIONS: The present findings give first insights into the neural biological basis underlying the trait and state characteristics associated with functional dysconnectivity within the emotion regulation system in MDD.