D-076 | Exploring the impact of ageing on brain structural connectivity: A graph theory approach on a local population sample

D-076 | Exploring the impact of ageing on brain structural connectivity: A graph theory approach on a local population sample 150 150 SAN 2024 Annual Meeting

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Author: Mariana Nahir Vallejo-Azar | Email: mvallejoazar@unaj.edu.ar


Mariana Nahir Vallejo-Azar, Julieta Laura Rodríguez Valdivia, Juana Irene Murray,  Tomás Picone, Juan Ignacio Navarro, Victoria Sosa Espinosa, María Agustina Lago,  Paula Natalia Gonzalez, Mariana Bendersky1°2°

Unidad de Estudios en Neurociencias y Sistemas complejos (ENyS, CONICET- UNAJ- Hospital SAMIC El Cruce)
Facultad de medicina, UBA

In recent years, studies have explored brain connectivity across different life stages. This study aimed to analyze changes in the global topology of the structural connectivity network with age in a local population. Structural MRI of 150 healthy volunteers (51 males and 99 females, age: 43.87±16.21 years) were acquired in a 3T scanner. Weighted connectivity matrices and topological measures were obtained using fiber number. Biological ages of subjects were assessed. A combined approach using Diffusion Weighted Imaging (DWI) and graph theory was applied. Linear models evaluated the effects of age and sex on the measures. Participants were divided into 10-year age intervals, and a Kruskal-Wallis test investigated differences among these groups. This method identified age intervals where topology is influenced by age. Most topological measures showed a significant decline with advancing age, except for path length, which increased. A notable impact on network topology was observed starting at age 61. The age interval of 71-90 years exhibited characteristics similar to those of the 61-70 years interval. The density of connections remained stable, likely due to high variability within each interval. Additionally, sex did not influence topological measures or ageing. Connectivity weighted by the number of fibers was sensitive to age-related changes, with ageing linked to a network with less efficiency, slower communication, greater vulnerability to injuries, and reduced redundanc

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