Work

Neuroimaging study on brain structural network topological properties affected by obesity in children and adolescents

Year: 2025

Type: article

Abstract: To examine alterations in the topological properties of brain structural networks in obese adolescents through graph theory analysis. A total of 86 obese adolescents admitted to the Department of Child Health Care at the Children's Hospital of Nanjing Medical University from January 2023 to April 2024 were prospectively enrolled. This cohort included 60 patients in the simple obesity group (Simple OB), 26 patients in the obese group with metabolic syndrome (MS), and 24 healthy volunteers in the control group (CON). All participants underwent DTI scans of the head, anthropometric assessments, and blood tests. Using graph theory, a whole-brain structural network was constructed, and global and nodal topological properties were calculated. Modular analysis was also conducted, and the differences among the three groups were compared using one-way ANOVA. Post-hoc corrections were applied after ANOVA. (1) There were no significant differences in gender, age or fasting blood glucose (FBG) among the three groups. However, there were significant differences in body height(p < 0.001), body weight (p < 0.001), BMI (p < 0.001), Waist circumference (p = 0.006), DBP (p = 0.005), systolic blood pressure (SBP) (p = 0.004), HDL-C (p = 0.002) among the three groups. Compared with the CON group, there were significant differences in TBF (p < 0.001), TG (p < 0.001), TC (p = 0.029), ALT (p < 0.001), AST (p = 0.020), FINS (p = 0.019) between the OB group and the MS group. (2) The small-world attribute (σ), characteristic path length (Lp) and global efficiency (Eg) did not differ significantly among the three groups (p > 0.05). However, the clustering coefficient (Cp) and local efficiency (Eloc) varied among the three groups, with both Cp and Eloc values being lower in the OB group than in the CON group(p = 0.039 and 0.041 respectively). Node level analysis revealed differences in node properties in the left frontal lobe, right insula, right anterior central gyrus, left anterior cingulate gyrus, left anterior cuneus and bilateral occipital lobes. The modular analysis revealed that the connection strength between the Association and Limbic modules in the OB group was significantly higher than that in the CON group (p = 0.033). (3) The Eloc was negatively correlated with TBF(β = - 0.227, p = 0.036), The modularity was negatively correlated with FINS (β = - 0.293, p = 0.006). Adolescent obesity results in aberrant topological properties of brain's structural network, leading to abnormalities in brain regions associated with self-awareness, cognitive control, emotional regulation and sensorimotor functions in adolescents with obesity. At the level of the brain's structural network, these findings may provide insights into the underlying neural mechanisms of obesity and offer imaging evidence to support clinical interventions. • For the first time in an obese adolescent population in China, this study systematically reveals abnormalities in the topological properties of brain structural networks using graph theory analysis, filling a research gap in this field within the Chinese population. • Innovatively, obese adolescents were categorized into a simple obesity group and a metabolic syndrome group, and compared with a healthy control group, thereby delineating brain network differences under varying metabolic states and enhancing the clinical discriminative power of the findings. • The study found that the local efficiency (Eloc) and clustering coefficient (Cp) of brain structural networks were significantly reduced in obese adolescents, indicating impaired white matter integrity in local information integration and providing new neuroimaging evidence for obesity-related cognitive impairment. • Modularity analysis revealed enhanced connectivity within the association-limbic system in the obese group, suggesting possible dysregulation of neural modulation or compensatory functional reorganization, offering a new perspective for understanding the interaction between emotion and cognition in obese adolescents. • This is the first report of a significant negative correlation between local efficiency and body fat percentage, as well as between modularity properties and fasting insulin levels, strengthening the quantitative association between metabolic indicators and brain network structure and suggesting potential biomarkers for early intervention. • Methodologically, the study integrates DTI with graph theory analysis and employs multiple metrics (global/nodal/modular) to comprehensively assess brain networks, enhancing the systematicity and reproducibility of the research and providing a standardized analytical framework for subsequent studies of a similar nature.

Source: Brain Research Bulletin

DOI: 10.1016/j.brainresbull.2025.111573

Authors: Xin Wang, Qian Li, Ruizhu Wang, Fei Yang, Yanli Xi, Ming Yang

Institutions: Second Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing Children's Hospital

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,280