Abstract

To detect Postpartum depression (PPD) among mothers in early, easy, and accurate way is required. In this study, we aimed to examine whether biomarkers taken during the perinatal period can predict a risk of PPD, in addition to subjective scale scores. A longitudinal survey of 24 mothers was conducted at 6 and 9 months of gestation (T1&T2) and 1 month postpartum (T3). Psychological state was measured by EPDS, GHQ, and CES-D. Sleep quality, which has a profound influence on postpartum psychological state, was measured by PSQI. Values of 10 biomarkers was measured: blood cortisol, adrenaline, noradrenaline, dopamine, IgA, urinary free cortisol, adrenaline, noradrenaline, dopamine, and breast milk IgA. Correlation was analyzed between psychological scale scores and biomarker values at each time point in the survey. The result showed moderately significant correlations between EPDS scores at T3 and urinary dopamine at T3 (r=0.53, p=0.024), and between GHQ scores at T3 and breast milk IgA at T3 (r=-0.61, p=0.020). Some moderately significant correlations between biomarkers in different time points were found, which were seen between blood adrenaline at T2 and urinary adrenaline at T3 (r=0.52, p=0.034), and between urinary cortisol at T2 and urinary noradrenaline at T3 (r=0.55, p=0.023). These findings demonstrated that autonomic nervous system biomarkers and IgA in breast milk reflects mothers’ psychological state, which could be a tool to predict PPD. Furthermore, it was suggested that biomarkers at 9 months of gestation could detect PPD indirectly, by predicting the value of biomarkers at 1 month postpartum.

Key words: Psychological status, stress, biomarkers, postpartum depression.