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Advances in Fetal and Neonatal Neuroimaging and Everyday Exposures

Overview
Journal Pediatr Res
Specialties Biology
Pediatrics
Date 2024 Jun 14
PMID 38877283
Authors
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Abstract

The complex, tightly regulated process of prenatal brain development may be adversely affected by "everyday exposures" such as stress and environmental pollutants. Researchers are only just beginning to understand the neural sequelae of such exposures, with advances in fetal and neonatal neuroimaging elucidating structural, microstructural, and functional correlates in the developing brain. This narrative review discusses the wide-ranging literature investigating the influence of parental stress on fetal and neonatal brain development as well as emerging literature assessing the impact of exposure to environmental toxicants such as lead and air pollution. These 'everyday exposures' can co-occur with other stressors such as social and financial deprivation, and therefore we include a brief discussion of neuroimaging studies assessing the effect of social disadvantage. Increased exposure to prenatal stressors is associated with alterations in the brain structure, microstructure and function, with some evidence these associations are moderated by factors such as infant sex. However, most studies examine only single exposures and the literature on the relationship between in utero exposure to pollutants and fetal or neonatal brain development is sparse. Large cohort studies are required that include evaluation of multiple co-occurring exposures in order to fully characterize their impact on early brain development. IMPACT: Increased prenatal exposure to parental stress and is associated with altered functional, macro and microstructural fetal and neonatal brain development. Exposure to air pollution and lead may also alter brain development in the fetal and neonatal period. Further research is needed to investigate the effect of multiple co-occurring exposures, including stress, environmental toxicants, and socioeconomic deprivation on early brain development.

Citing Articles

Machine-learning based prediction of future outcome using multimodal MRI during early childhood.

Ouyang M, Whitehead M, Mohapatra S, Zhu T, Huang H Semin Fetal Neonatal Med. 2024; 29(2-3):101561.

PMID: 39528363 PMC: 11654837. DOI: 10.1016/j.siny.2024.101561.

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