Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis

•Prenatal stress (PS) impacts early postnatal behavioural and cognitive development.•Key systems affected are the stress axis and the autonomic nervous system.•Effects are detected on multiple scales: brain epigenome, metabolome, microbiome, heart rate.•Biomarkers of PS to be discovered from these multiple scales using machine learning.•Concerted observations in multiple animal models and human cohorts are needed. Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of ‘fetal programming’ is mediated by the effects of the prenatal experience on the developing hypothalamic–pituitary–adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions.