Maternal–fetal stress and DNA methylation signatures in neonatal saliva: an epigenome-wide association study

Background Maternal stress before, during and after pregnancy has profound effects on the development and lifelong function of the infant’s neurocognitive development. We hypothesized that the programming of the central nervous system (CNS), hypothalamic–pituitary–adrenal (HPA) axis and autonomic nervous system (ANS) induced by prenatal stress (PS) is reflected in electrophysiological and epigenetic biomarkers. In this study, we aimed to find noninvasive epigenetic biomarkers of PS in the newborn salivary DNA. Results A total of 728 pregnant women were screened for stress exposure using Cohen Perceived Stress Scale (PSS), 164 women were enrolled, and 114 dyads were analyzed. Prenatal Distress Questionnaire (PDQ) was also administered to assess specific pregnancy worries. Transabdominal fetal electrocardiograms (taECG) were recorded to derive coupling between maternal and fetal heart rates resulting in a ‘Fetal Stress Index’ (FSI). Upon delivery, we collected maternal hair strands for cortisol measurements and newborn’s saliva for epigenetic analyses. DNA was extracted from saliva samples, and DNA methylation was measured using EPIC BeadChip array (850 k CpG sites). Linear regression was used to identify associations between PSS/PDQ/FSI/Cortisol and DNA methylation. We found epigenome-wide significant associations for 5 CpG with PDQ and cortisol at FDR < 5%. Three CpGs were annotated to genes (Illumina Gene annotation file): YAP1 , TOMM20 and CSMD1 , and two CpGs were located approximately lay at 50 kb from SSBP4 and SCAMP1 . In addition, two differentiated methylation regions (DMR) related to maternal stress measures PDQ and cortisol were found: DAXX and ARL4D . Conclusions Genes annotated to these CpGs were found to be involved in secretion and transportation, nuclear signaling, Hippo signaling pathways, apoptosis, intracellular trafficking and neuronal signaling. Moreover, some CpGs are annotated to genes related to autism, post-traumatic stress disorder (PTSD) and schizophrenia. However, our results should be viewed as hypothesis generating until replicated in a larger sample. Early assessment of such noninvasive PS biomarkers will allow timelier detection of babies at risk and a more effective allocation of resources for early intervention programs to improve child development. A biomarker-guided early intervention strategy is the first step in the prevention of future health problems, reducing their personal and societal impact.