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Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale

Martin G Frasch1, Silvia M Lobmaier2, Tamara Stampalija3

  • 1Department of Obstetrics and Gynecology, University of Washington, Seattle, USA.

Neuroscience and Biobehavioral Reviews
|June 3, 2018
PubMed

Insights

Prenatal stress (PS) affects fetal programming, impacting neurodevelopment. This study proposes a multi-scale approach to find non-invasive biomarkers for predicting and monitoring PS effects on children.

Area of Science:

  • Neuroscience
  • Developmental Biology
  • Psychiatry

Background:

  • Prenatal stress (PS) significantly influences early postnatal behavioral and cognitive development.
  • This 'fetal programming' is mediated by the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS).

Purpose of the Study:

  • To develop a multi-scale, multi-species framework for identifying early, non-invasive prenatal and postnatal biomarkers of PS.
  • To reveal mechanistic links between maternal stress and physiological changes across multiple scales.

Main Methods:

  • Utilizing a multi-scale approach encompassing brain epigenome, metabolome, microbiome, and ANS activity.
  • Gauging ANS activity through advanced, non-invasively obtainable properties of fetal heart rate fluctuations.
  • Employing machine learning for data synthesis and biomarker identification/validation across animal models and human cohorts.

Main Results:

  • The proposed framework integrates data across diverse physiological scales to understand PS impacts.
  • Identified potential non-invasive biomarkers for predicting neurodevelopmental trajectories affected by PS.
  • Established a foundation for evaluating therapeutic interventions targeting PS-induced alterations.

Conclusions:

  • A multi-scale, multi-species approach is crucial for comprehensive PS research.
  • Non-invasive biomarkers derived from this framework can predict and monitor neurodevelopmental outcomes.
  • This research is essential for designing effective interventions for PS-affected pregnancies.

Keywords:
ANSEpigeneticsGuinea pigHRVHumanMachine learningMicrobiomeOmicsRatSheep

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