Characterizing Unipolar and Bipolar Depression by Alterations in Inflammatory Mediators and the Prefrontal-Limbic Structural Network

Abstract

Objective. The prefrontal-limbic system is closely associated with emotion processing in both unipolar depression (UD) and bipolar depression (BD). Evidence for this link is derived mostly from task-fMRI studies, with limited support from structural findings. Therefore, this study explores the differences in the emotional circuit in these two disorders on a structural, large-scale network basis, coupled with the highly noted inflammatory and growth factors. Methods. In this study, 31 BD patients, 37 UD patients, and 61 age-, sex-, and education-matched healthy controls (HCs) underwent diffusion-weighted imaging (DWI) scanning and serum cytokine sampling. The study compared cytokine levels and prefrontal-limbic network alterations among the three groups and explored potential biological and neurobiological markers to distinguish the two disorders using graph theory, network-based statistics (NBS), and logistic regression. Results. Compared to BD patients, UD patients showed greater s-100β protein levels, higher efficiency of the right amygdala, and significantly elevated prefrontal-cingulate-amygdala subnetwork intensity. Importantly, the altered prefrontal-cingulate-amygdala subnetwork, nodal efficiency of the right amygdala, IL-8, IL-17, and s-100β levels were risk factors for the diagnosis of UD, whereas anxiety symptoms tended to closely correlate with BD. Moreover, binary logistic regression manifested these factors achieved an area under the curve (AUC) of the receiver operating characteristics (ROC) of 0.949, with 0.875 sensitivity and 0.938 specificity in UD vs. BD classification. Conclusions. These findings narrow the gap in the structural network of emotional circuits in bipolar and unipolar depression, pointing to distinct emotion-processing mechanisms in both disorders.