Neural Network Dysregulation in Female Abdominal Obesity: Distinct Functional Connectivity in Different Appetite...

This study investigated the neural mechanisms underlying appetite dysregulation in female subjects with abdominal obesity (AO) by identifying functional connectivity (FC) and network-level differences between moderate appetite (MA) and strong appetite (SA) subtypes.

A total of 60 women with AO (30 MA, 30 SA) and 30 healthy controls (HCs) underwent resting-state fMRI. Independent component analysis was used to identify and examine FC within and functional network connectivity (FNC) between key resting-state networks, including those involved in cognitive and visual processing. Network alterations and correlations with obesity-related indicators were evaluated.

Compared to HCs, both groups showed reduced FC in the default mode network (DMN) and visual network (VN), with SA additionally exhibiting decreased FC in the frontoparietal network (FPN) and lower angular gyrus FC than MA (p < 0.05, FDR-corrected). MA displayed increased DMN-left FPN (FPN_L) FNC (p < 0.001), while SA showed negative correlations between FC and BMI/appetite visual analog scale (VAS) scores in FPN and with body weight/BMI/appetite VAS in VN (p < 0.05). In HCs, DMN-FPN_L FNC positively correlated with BMI, a pattern that was not observed in MA.

Distinct brain network patterns characterize appetite subtypes in AO. SA showed more pronounced FC reductions in networks previously linked to self-regulation and visual processing, which may contribute to appetite dysregulation based on correlations with obesity indicators. In contrast, MA exhibited increased DMN-FPN_L FNC, potentially reflecting adaptive internetwork interactions.