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Predictions of children’s emotionality from evolutionary and epigenetic hypotheses

Hill, J., Pickles, A., Wright, N., Braithwaite, E. and Sharp, H. (2019) Predictions of children’s emotionality from evolutionary and epigenetic hypotheses. Scientific Reports, 9. 2519. ISSN 2045-2322

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To link to this item DOI: 10.1038/s41598-019-39513-7

Abstract/Summary

Sex-dependent effects of mismatched prenatal-postnatal maternal conditions are predicted by combining two evolutionary hypotheses: that foetal conditions provide a forecast of likely postnatal environments (Predictive Adaptive Response), and that the female foetus is better adapted than the male to maternal adversity (Trivers-Willard hypothesis). Animal studies have implicated glucocorticoid mechanisms modifiable by effects of postnatal tactile stimulation on glucocorticoid receptor gene expression. In this study we examined behavioural predictions in humans based on these evolutionary and epigenetic models. Mothers in a general population cohort provided self-reported anxiety scores at 20 weeks pregnancy, and at 9 weeks, 14 months and 3.5 years postpartum, and frequency of infant stroking at 9 weeks. Mothers and teachers reported child symptoms at 7 years. SEM models with maximum-likelihood estimates made use of data from 887 participants. There was a three-way interaction between prenatal and postnatal anxiety and maternal stroking in the prediction of irritability, seen only in girls. This arose because lower maternal stroking was associated with higher irritability, only in the mismatched, low-high and high-low maternal anxiety groups. We provide evidence that mechanisms likely to have evolved well before the emergence of humans, contribute to the development of children’s emotionality and risk for depression.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology
Faculty of Life Sciences > School of Psychology and Clinical Language Sciences > Psychopathology and Affective Neuroscience
ID Code:81970
Publisher:Nature Publishing Group

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