Topological organization of the brain network in patients with primary angle-closure glaucoma through graph theory analysis

Abstract

Abstract Purpose Primary angle-closure glaucoma (PACG) is an irreversible blinding eye disease. Previous neuroimaging studies have reported abnormal brain function changes in PACG patients, but the potential association of PACG with changes in brain functional networks remains unknown. This study aims to investigate the impact of PACG on brain networks, with the goal of enhancing understanding of its neurobiological mechanisms for improved diagnosis and treatment through the application of graph theory analysis. Method A cohort comprising 44 PACG patients and 44 healthy controls was recruited for the study. Functional brain networks were constructed based on fMRI data utilizing the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was conducted to assess global metrics, nodal metrics, modular organization, and network-based statistics(NBS), facilitating a comparative analysis between PACG patients and the control group. Result The global metrics( including small world and network efficiency) did not reveal significant differences between the two groups. However, PACG patients showed increased nodal metrics (including centrality and efficiency) in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, alongside decreased values in the right temporal superior gyrus region compared with health controls. Moreover, Module 5 demonstrated significant differences in intra-module connectivity, while significant variations in inter-module connectivity were observed between Module 1 and Module 7, as well as Module 1 and Module 8. Notably, the NBS analysis revealed a significantly modified network when comparing the PACG and HC groups. Conclusion the study suggests that PACG patients exhibit differences in nodal metrics and modularity of functional brain networks, with changes observed mainly in prefrontal, occipital, and temporal lobes, as well as cerebellar regions. However, global metrics analysis indicates that the global connectivity patterns of the entire brain network remain unchanged in PACG patients. These findings may serve as potential biomarkers for early diagnosis and differential diagnosis of PACG, and interventions targeting brain regions with high degree centrality and nodal efficiency may help to optimize therapeutic strategies.