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

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259898/
https://www.ncbi.nlm.nih.gov/pubmed/35815018
http://dx.doi.org/10.3389/fpsyt.2022.892259
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author 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
author_facet 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
author_sort Morton, Sarah U.
collection PubMed
description 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.
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spelling pubmed-92598982022-07-08 A Role for Data Science in Precision Nutrition and Early Brain Development 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 Front Psychiatry Psychiatry 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. Frontiers Media S.A. 2022-06-23 /pmc/articles/PMC9259898/ /pubmed/35815018 http://dx.doi.org/10.3389/fpsyt.2022.892259 Text en Copyright © 2022 Morton, Leyshon, Tamilia, Vyas, Sisitsky, Ladha, Lasekan, Kuchan, Grant and Ou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
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
A Role for Data Science in Precision Nutrition and Early Brain Development
title A Role for Data Science in Precision Nutrition and Early Brain Development
title_full A Role for Data Science in Precision Nutrition and Early Brain Development
title_fullStr A Role for Data Science in Precision Nutrition and Early Brain Development
title_full_unstemmed A Role for Data Science in Precision Nutrition and Early Brain Development
title_short A Role for Data Science in Precision Nutrition and Early Brain Development
title_sort role for data science in precision nutrition and early brain development
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9259898/
https://www.ncbi.nlm.nih.gov/pubmed/35815018
http://dx.doi.org/10.3389/fpsyt.2022.892259
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