Prenatal stress is associated with child behavioral outcomes increasing susceptibility for psychiatric disorders in later life. Altered fetal brain development might partly mediate this association, as some studies suggest. With this study, we investigated the relation between prenatal stress, child’s brain structure and behavioral problems. The association between self-reported maternal pregnancy-related anxiety (PRAQ-R2 questionnaire, second and third trimester) and brain gray matter volume was probed in 27 4-year-old children (13 female). Voxel based morphometry was applied with an age-matched template in SPM for the whole-brain analyses, and amygdala volume was assessed with manual segmentation. Possible pre- and postnatal confounders, such as maternal depression and anxiety among others, were controlled for. Child behavioral problems were assessed with the Strength and Difficulties Questionnaire by maternal report. We found a significant interaction effect of pregnancy-related anxiety and child’s sex on child’s amygdala volume, i.e., higher pregnancy-related anxiety in the second trimester was related to significantly greater left relative amygdala volume in girls compared to boys. Further exploratory analyses yielded that both maternal pregnancy-related anxiety and child’s amygdala volume are related to child emotional and behavioral difficulties: While higher pregnancy-related anxiety was associated with more emotional symptoms, peer relationship problems and overall child difficulties, greater left amygdala volume was related to less of these child difficulties and might partly mediate sex-specific associations between pregnancy-related anxiety and child behavioral difficulties. Our data suggest that maternal prenatal distress leads to sexually dimorphic structural changes in the offspring’s limbic system and that these changes are also linked to behavioral difficulties. Our results provide further support for the notion that prenatal stress impacts child development.

Psychiatric disease susceptibility partly originates prenatally and is shaped by an interplay of genetic and environmental risk factors. A recent study has provided preliminary evidence that an offspring polygenic risk score for major depressive disorder (PRS-MDD), based on European ancestry, interacts with prenatal maternal depressive symptoms (GxE) on neonatal right amygdalar (US and Asian cohort) and hippocampal volumes (Asian cohort). However, to date, this GxE interplay has only been addressed by one study and is yet unknown for a European ancestry sample. We investigated in 105 Finnish mother–infant dyads (44 female, 11–54 days old) how offspring PRS-MDD interacts with prenatal maternal depressive symptoms (Edinburgh Postnatal Depression Scale, gestational weeks 14, 24, 34) on infant amygdalar and hippocampal volumes. We found a GxE effect on right amygdalar volumes, significant in the main analysis, but nonsignificant after multiple comparison correction and some of the control analyses, whose direction paralleled the US cohort findings. Additional exploratory analyses suggested a sex-specific GxE effect on right hippocampal volumes. Our study is the first to provide support, though statistically weak, for an interplay of offspring PRS-MDD and prenatal maternal depressive symptoms on infant limbic brain volumes in a cohort matched to the PRS-MDD discovery sample.

Highlights Assessed relation of maternal prenatal distress to amygdalae and hippocampi volumes. Newborn amygdalar volumes negatively related to maternal prenatal distress in males. No association between maternal prenatal distress and newborn hippocampal volumes. Prenatal maternal distress seems to affect newborn brain in a sex-dependent way.

The gross anatomy of the infant brain at term is fairly similar to that of the adult brain, but structures are immature, and the brain undergoes rapid growth during the first 2 years of life. Neonate magnetic resonance (MR) images have different contrasts compared to adult images, and automated segmentation of brain magnetic resonance imaging (MRI) can thus be considered challenging as less software options are available. Despite this, most anatomical regions are identifiable and thus amenable to manual segmentation. In the current study, we developed a protocol for segmenting the amygdala and hippocampus in T2-weighted neonatal MR images. The participants were 31 healthy infants between 2 and 5 weeks of age. Intra-rater reliability was measured in 12 randomly selected MR images, where 6 MR images were segmented at 1-month intervals between the delineations, and another 6 MR images at 6-month intervals. The protocol was also tested by two independent raters in 20 randomly selected T2-weighted images, and finally with T1 images. Intraclass correlation coefficient (ICC) and Dice similarity coefficient (DSC) for intra-rater, inter-rater, and T1 vs. T2 comparisons were computed. Moreover, manual segmentations were compared to automated segmentations performed by iBEAT toolbox in 10 T2-weighted MR images. The intra-rater reliability was high ICC ≥ 0.91, DSC ≥ 0.89, the inter-rater reliabilities were satisfactory ICC ≥ 0.90, DSC ≥ 0.75 for hippocampus and DSC ≥ 0.52 for amygdalae. Segmentations for T1 vs. T2-weighted images showed high consistency ICC ≥ 0.90, DSC ≥ 0.74. The manual and iBEAT segmentations showed no agreement, DSC ≥ 0.39. In conclusion, there is a clear need to improve and develop the procedures for automated segmentation of infant brain MR images.