A Role for Data Science in Precision Nutrition and Early Brain Development

• Published in: Frontiers in psychiatry Vol. 13; p. 892259
• Main Authors: Morton, Sarah U, Leyshon, Brian J, Tamilia, Eleonora, Vyas, Rutvi, Sisitsky, Michaela, Ladha, Imran, Lasekan, John B, Kuchan, Matthew J, Grant, P Ellen, Ou, Yangming
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 23.06.2022
• Subjects: brain development; data science; magnetic resonance image; neonate; nutrition; Psychiatry; brain development; magnetic resonance image; nutrition; neonate; data science
• ISSN: 1664-0640; 1664-0640
• DOI: 10.3389/fpsyt.2022.892259

Multimodal brain magnetic resonance imaging (MRI) can provide biomarkers of early influences on neurodevelopment such as nutrition, environmental and genetic factors. As the exposure to early influences can be separated from neurodevelopmental outcomes by many months or years, MRI markers can serve as an important intermediate outcome in multivariate analyses of neurodevelopmental determinants. Key to the success of such work are recent advances in data science as well as the growth of relevant data resources. Multimodal MRI assessment of neurodevelopment can be supplemented with other biomarkers of neurodevelopment such as electroencephalograms, magnetoencephalogram, and non-imaging biomarkers. This review focuses on how maternal nutrition impacts infant brain development, with three purposes: (1) to summarize the current knowledge about how nutrition in stages of pregnancy and breastfeeding impact infant brain development; (2) to discuss multimodal MRI and other measures of early neurodevelopment; and (3) to discuss potential opportunities for data science and artificial intelligence to advance precision nutrition. We hope this review can facilitate the collaborative march toward precision nutrition during pregnancy and the first year of life.