Aberrant Dynamic Network Connectivity Changes in Comorbid Depression and Overweight/Obesity: Insights From the Triple Network Model

Abstract

The interaction between major depressive disorder (MDD) and overweight/obesity has received considerable attention owing to its widespread occurrence and the intricate biopsychological implications involved. Despite extensive research, the neural mechanisms underlying these comorbid conditions, particularly in terms of functional network connectivity (FNC), are still not well understood. This study aimed to clarify these mechanisms by utilizing resting-state functional magnetic resonance imaging (rs-fMRI) to examine both static and dynamic FNC. We analyzed data from 57 patients with both MDD and overweight/obesity (MDD-OW), 57 MDD patients of normal weight (MDD-NW), and 44 healthy controls, using techniques such as independent component analysis, sliding window analysis, K-means clustering, and graph theory. In contrast to static FNC, which showed no significant differences, dynamic FNC analysis identified four consistent states across all participants. Both MDD groups demonstrated reduced flexibility in functional coordination among these states and decreased nodal characteristics within the salience network. Notably, the MDD-OW group displayed enhanced dynamic FNC between the default mode network (DMN) and the executive control network (ECN) during certain states, which was inversely associated with the severity of depressive symptoms. These results highlight the importance of altered dynamic connectivity patterns in individuals with MDD and concurrent overweight/obesity, especially between the DMN and ECN, suggesting their potential utility as biomarkers for depressive states. This research contributes to our understanding of how comorbid overweight/obesity affects brain network dynamics in depressive disorders and provides a basis for targeted therapeutic strategies.