Disrupted Topological Organization of White Matter Network in Angelman Syndrome

Abstract

Background: Angelman syndrome (AS) is a genetic disorder that affects neurodevelopment. The investigation of changes in the brain white matter network, which would contribute to a better understanding of the pathogenesis of AS brain, was lacking.

Purpose: To investigate both local and global alterations of white matter in patients with AS.

Study type: Prospective.

Subjects: A total of 29 AS patients (6.6 ± 1.4 years, 15 [52%] females) and 19 age-matched healthy controls (HC) (7.0 ± 1.5 years, 10 [53%] females).

Field strength/sequence: A 3-T, three-dimensional (3D) T1-weighted imaging by using gradient-echo-based sequence, single shell diffusion tensor imaging by using spin-echo-based echo-planar imaging.

Assessment: Network metrics including global efficiency (E_g ), local efficiency (E_loc ), small world coefficient (Swc), rich-club coefficient (Φ), and nodal degree (ND) were estimated from diffusion MR (dMR) data. Connections among highly connected (hub) regions and less connected (peripheral) regions were also assessed. Correlation between the topological parameters and age for each group was also calculated to assess the development of the brain.

Statistical tests: Linear regression model, permutation test. P values estimated from the regression model for each brain region were adjusted by false discovery rate (FDR) correction.

Results: AS patients showed significantly lower E_g and higher swc compared to HC. Φ_n significantly increased at higher k-levels in AS patients. In addition, the connections among hub regions and peripheral regions were significantly interrupted in AS patients.

Data conclusion: The AS brain showed diminished connectivity, reflected by reduced network efficiency compared to HC. Compared to densely connected regions, less connected regions were more vulnerable in AS.

Evidence level: 2 TECHNICAL EFFICACY: Stage 3.

Keywords: Angelman syndrome; diffusion MRI; network analysis.