From the reward network to whole-brain metrics: structural connectivity in adolescents and young adults according to body mass index and genetic risk of obesity

Background: Obesity is a multifactorial condition. Genetic variants, such as the fat mass and obesity related gene (FTO)polymorphism, may increase the vulnerability of developing obesity by disrupting dopamine signaling within the reward network. Yet, the association of obesity, genetic risk of obes...

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Detalles Bibliográficos
Autores: Prunell Castañé, Anna, Beyer, Frauke, Witte, Veronica, Sánchez-Garre, Consuelo, Hernan, Imma, Caldú i Ferrús, Xavier, Jurado, Ma. Ángeles (María Ángeles), Garolera i Freixa, Maite
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2024
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/225315
Acceso en línea:https://hdl.handle.net/2445/225315
Access Level:acceso abierto
Palabra clave:Joves
Obesitat en els adolescents
Obesitat
Pes corporal
Cervell
Youth
Obesity in adolescence
Obesity
Body weight
Brain
Descripción
Sumario:Background: Obesity is a multifactorial condition. Genetic variants, such as the fat mass and obesity related gene (FTO)polymorphism, may increase the vulnerability of developing obesity by disrupting dopamine signaling within the reward network. Yet, the association of obesity, genetic risk of obesity, and structural connectivity of the reward network in adolescents and young adults remains unexplored. We investigate, in adolescents and young adults, the structural connectivity differences in the reward network and at the whole-brain level according to body mass index (BMI) and the FTO rs9939609 polymorphism. Methods: One hundred thirty-two adolescents and young adults (age range: [10, 21] years, BMI z-score range: [−1.76, 2.69]) were included. Genetic risk of obesity was determined by the presence of the FTO A allele. Whole-brain and reward network structural connectivity were analyzed using graph metrics. Hierarchical linear regression was applied to test the association between BMI-z, genetic risk of obesity, and structural connectivity. Results: Higher BMI-z was associated with higher (B = 0.76, 95% CI = [0.30, 1.21], P = 0.0015) and lower (B = −0.003, 95% CI = [−0.006, −0.00005], P = 0.048) connectivity strength for fractional anisotropy at the whole-brain level and of the reward network, respectively. The FTO polymorphism was not associated with structural connectivity nor with BMI-z. Conclusions: We provide evidence that, in healthy adolescents and young adults, higher BMI-z is associated with higher connectivity at the whole-brain level and lower connectivity of the reward network. We did not find the FTO polymorphism to correlate with structural connectivity. Future longitudinal studies with larger sample sizes are needed to assess how genetic determinants of obesity change brain structural connectivity and behavior.