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Pediatrics

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

International Journal of Obesity volume 48, pages 567–574 (2024)Cite this article

Subjects

Abstract

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.

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Fig. 1: Reconstruction of the reward network using R’s package brainconn.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors thank Isabel García-García and Jonatan Ottino-González their support. The authors also thank all the participants that made this project possible. We acknowledge the Centres de Recerca de Catalunya (CERCA) Program/Generalitat de Catalunya, the Institute of Neurosciences, the Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), the Consorci Sanitari de Terrassa, and the Hospital de Terrassa. We acknowledge the following funding sources, which were not involved in the study conceptualization, interpretation or writing: APC received a Ph.D. scholarship from the Spanish Ministry of Science, Innovation and Universities (PRE2019-087430). MAJ and MG received Grants from the Spanish Ministry of Economy, Industry and Competitiveness (PSI2017- 86536-C2-1-R and PSI2017-86536-C2-2-R, respectively), funded by MCIN/AEI/https://doi.org/10.13039/501100011033 and the European Regional Development Fund (ERDF). MAJ, MG, XC and APC have additionally received funding from the Departament d’Innovació, Universitats i Empresa, Generalitat de Catalunya (2021SGR0801).

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Authors and Affiliations

  1. Departament de Psicologia Clínica i Psicobiologia, Facultat de Psicologia, Universitat de Barcelona, Passeig de la Vall d’Hebron, 171, 08035, Barcelona, Spain

    Anna Prunell-Castañé, Xavier Caldú & María Ángeles Jurado

  2. Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain

    Anna Prunell-Castañé, Xavier Caldú & María Ángeles Jurado

  3. Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain

    Anna Prunell-Castañé, Xavier Caldú & María Ángeles Jurado

  4. Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany

    Frauke Beyer & Veronica Witte

  5. Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

    Frauke Beyer & Veronica Witte

  6. Pediatric Endocrinology Unit, Hospital de Terrassa, Consorci Sanitari de Terrassa, Terrassa, Barcelona, Spain

    Consuelo Sánchez Garre

  7. Molecular Genetics Unit, Consorci Sanitari de Terrassa, Terrassa, Spain

    Imma Hernán

  8. Brain, Cognition and Behavior: Clinical Research, Consorci Sanitari de Terrassa, Terrassa, Barcelona, Spain

    Maite Garolera

  9. Neuropsychology Unit, Hospital de Terrassa, Consorci Sanitari de Terrassa, Terrassa, Barcelona, Spain

    Maite Garolera

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  1. Anna Prunell-Castañé
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Contributions

APC, MAJ, MG, FB, and VW contributed to study design and conception. APC, IH, CSG, XC participated in data acquisition. APC performed the analyses. APC, MAJ, and FB contributed to results interpretation. APC wrote the original manuscript. All authors critically reviewed the manuscript, approved its final version for publishing, and agreed to be accountable for all aspects of such work.

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Correspondence to María Ángeles Jurado.

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Prunell-Castañé, A., Beyer, F., Witte, V. et al. 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. Int J Obes 48, 567–574 (2024). https://doi.org/10.1038/s41366-023-01451-w

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