Associations between Early Life Nutrient Intakes and Brain Maturation Show Developmental Dynamics from Infancy to Toddlerhood: A Neuroimaging Observation Study

Nora Schneider; Fabio Mainardi; Sanja Budisavljevic; Maryann Rolands; Sean Deoni

doi:10.1016/j.tjnut.2023.01.017

Associations between Early Life Nutrient Intakes and Brain Maturation Show Developmental Dynamics from Infancy to Toddlerhood: A Neuroimaging Observation Study

J Nutr. 2023 Mar;153(3):897-908. doi: 10.1016/j.tjnut.2023.01.017. Epub 2023 Jan 13.

Authors

Nora Schneider¹, Fabio Mainardi², Sanja Budisavljevic³, Maryann Rolands⁴, Sean Deoni⁵

Affiliations

¹ Brain Health Department, Nestlé Institute of Health Sciences, Société des Produits Nestlé SA, Vers-Chez-les-Blanc, Lausanne, Switzerland. Electronic address: nora.schneider@rdls.nestle.com.
² Applied Data Analytics Group, Nestlé Institute of Health Sciences, Société des Produits Nestlé SA, Vers-Chez-les-Blanc, Lausanne, Switzerland.
³ Brain Health Department, Nestlé Institute of Health Sciences, Société des Produits Nestlé SA, Vers-Chez-les-Blanc, Lausanne, Switzerland.
⁴ Nutrition Science Group, Nestlé Institute of Health Sciences, Société des Produits Nestlé SA, Vers-Chez-les-Blanc, Lausanne, Switzerland.
⁵ Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, RI, USA; Department of Radiology, Warren Alpert Medical School at Brown University, Providence, RI, USA; Spinn Neuroscience, Seattle, WA, USA.

Abstract

Background: Myelin imaging has increasingly been applied to study the impact of nutrition on brain development in recent years. Although individual dynamics for nutrient intakes and myelin trajectories previously have been investigated across childhood, the longitudinal interaction between both remains unclear in typically developed children.

Objectives: The objective of this work was to explore the developmental dynamics of nutrient-myelin interactions from infancy to early childhood using myelin imaging as a marker for brain maturation.

Methods: Brain neuroimaging (1 scan per child) and dietary nutrient intake data were analyzed for 88 nutrients from 293 children (127 female, 62% White) from a longitudinal cohort study in the United States. A sliding window approach was used to investigate correlations between nutrient intakes and brain myelination over a continuous set of age windows. Image processing techniques (Sobel-filter vertical edge detection) were applied to determine age windows with unique association profiles, providing novel insight into how these relationships change with child age.

Results: We identified 3 nutrient-myelin windows covering the age range of 1-5 y: window 1 from 6 to 20 mo with 60% positive nutrient correlations, window 2 from 20 to 30 mo with 20% positive correlations, and window 3 from 30 to 60 mo with 37% positive correlations. The windows are aligned with reported myelin and white matter dynamics that change in the first 5 y from fast and steep (window 1) to continued but slower growth (window 3), with window 2 possibly representing the inflection period.

Conclusions: To our knowledge, this is the first study in typically developing children demonstrating the developmental dynamics between early life nutrient intakes and brain maturation in toddlerhood. The knowledge can be applied for identifying targeted and brain-stage-appropriate nutritional interventions for this critical stage of brain development.

Keywords: MRI; brain development; dynamics; myelination; nutrition; toddlers.

Publication types

Observational Study
Research Support, N.I.H., Extramural

MeSH terms

Brain / diagnostic imaging
Child
Child, Preschool
Diet*
Eating*
Female
Humans
Infant
Longitudinal Studies
Neuroimaging
United States

Grants and funding

UG3 OD023313/OD/NIH HHS/United States