Poster No:
1311
Submission Type:
Abstract Submission
Authors:
Diandra Brkic1, Fabio Mainardi2, Jonas Hauser3, Sean Deoni4
Institutions:
1Nestlé Institute of Health Sciences, Lausanne, Vaud, 2Nestlé Institute of Health Sciences, Lausanne, Switzerland, 3Brain Health Department, Nestlé Institute of Health Sciences, Lausanne, Switzerland, 44. Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI
First Author:
Co-Author(s):
Fabio Mainardi
Nestlé Institute of Health Sciences
Lausanne, Switzerland
Jonas Hauser
Brain Health Department, Nestlé Institute of Health Sciences
Lausanne, Switzerland
Sean Deoni
4. Department of Pediatrics, Warren Alpert Medical School at Brown University
Providence, RI
Introduction:
School-age period, typically from 2 to 15 years old, is a critical phase in child development that significantly impacts cognition, learning, behaviour, and social-emotional development. This age is characterized by heightened sensitivity, making it a crucial time for shaping and nurturing a child's overall growth and well-being. From a brain development perspective, it is also a pivotal period characterized by significant reorganization. For instance, there is a remarkable restructuring of synaptic plasticity, and notable changes in the structural and functional networks, associated with learning (Dean et al., 2015). Although numerous studies have investigated the impact of the environment, socioeconomic status (SES), and genes on neurodevelopment, there is a huge knowledge gap regarding the specific influence of nutrition on cortical changes, particularly in this age range (Saavedra & Prentice, 2023). In this study, we have assessed how nutrition shapes brain myelination and white matter network organisation, and how this affects cognition and learning skills in a large cohort of school-age children (Brown University RESONANCE cohort).
Methods:
A large sample (N=282) of school-age children (mean age 7.5 y.o.), from the Brown University RESONANCE cohort, was included in this study. All participants had morphological and structural brain measures (Water fraction myelination and fractional anisotropy, FA), full cognitive (WPPSI, WASI) and learning (AAB) assessments, and dietary intake (ASA-24h recall questionnaire) completed. Specifically we investigated how dietary intake affects both myelination and structural connectivity, linked to learning and cognitive skills. In order to capture this relationship in a data driven fashion, we performed a series of mediation models (Rijnhart et al., 2021). This allowed us to assess the indirect effects and shed light on the underlying pathways between important nutrients for, cognition and learning, mediated by brain structure and morphology, while controlling for age and parental education.
Results:
Four different mediation analyses were performed to explore the causal relationship between 64 nutrients and 35 food groups and cognitive and learning performance, with myelination and FA, as mediating factors. Mediation models identified the most significant nutrients contributing to cognitive and learning skills outcomes, via myelination and structural connectivity. Specifically, the models were: a) nutrition, myelination, cognition; b) nutrition, myelination, learning (reading); c) nutrition, FA (DTI), cognition; d) nutrition, FA (DTI), learning. Each of the models provided a set of most important essential nutrients (e.g. iron, vit B) affecting both learning and cognition, in different related brain networks and ROIs. Importantly we found consistency across all models, defining how dietary intake affects both learning and cognition, via correlated brain measures
Conclusions:
To the best of our knowledge this is the first study offering a deeper understanding of the intricate interplay between nutrition, brain development and structural changes, and cognitive and learning outcomes. Our results provide a unique perspective on which nutrients may support learning and cognition in school age children. In addition, it assesses how this relationship is mediated by myelination rate and structural efficiency in learning-related brain areas. In short, this study emphasizes the significance of considering the impact of nutrition on child development. It highlights the need to incorporate nutrition as a crucial factor when studying key determinants influencing brain development, learning, and cognitive abilities in school age. By recognizing the role of nutrition in shaping these domains, we can better understand the multifaceted factors that contribute to optimal brain development and promote effective strategies for fostering learning and cognition in children.
Higher Cognitive Functions:
Higher Cognitive Functions Other
Language:
Reading and Writing
Lifespan Development:
Normal Brain Development: Fetus to Adolescence 1
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 2
Keywords:
Cognition
Development
Language
Learning
MRI
Myelin
STRUCTURAL MRI
Tractography
White Matter
1|2Indicates the priority used for review
Provide references using author date format
References
Dean, D. C., O’Muircheartaigh, J., Dirks, H., Waskiewicz, N., Walker, L., Doernberg, E., Piryatinsky, I., & Deoni, S. C. L. (2015). Characterizing longitudinal white matter development during early childhood. Brain Structure and Function, 220(4), 1921–1933. doi: 10.1007/s00429-014-0763-3
Rijnhart, J. J. M., Lamp, S. J., Valente, M. J., MacKinnon, D. P., Twisk, J. W. R., & Heymans, M. W. (2021). Mediation analysis methods used in observational research: A scoping review and recommendations. BMC Medical Research Methodology, 21(1), 226. doi: 10.1186/s12874-021-01426-3
Saavedra, J. M., & Prentice, A. M. (2023). Nutrition in school-age children: A rationale for revisiting priorities. Nutrition Reviews, 81(7), 823–843. doi: 10.1093/nutrit/nuac089