Genetic and environmental factors predict multivariate trajectories of maternal distress after birth

Background: Maternal distress influences her own wellbeing and shapes her offspring’s psychosocial adjustment and neurodevelopment across childhood. The aim of this study was to analyze multivariate trajectories of maternal postpartum distress using a latent class modeling approach and to find genetic and psychosocial factors that predict membership within a given group (latent class). Methods: Maternal self-reports of depressive symptoms, parenting stress, general stress, and marital stress were measured at regular intervals during the first six years postpartum in 261 mothers participating in the Maternal Adversity, Vulnerability and Neurodevelopment Study. Genetic risk was determined by calculating a polygenic risk score for Major Depressive Disorder (MDD-PRS). Additionally, we assessed maternal history of early life adversity (mELA), educational level, and prenatal symptoms of depression as psychosocial risk factors. Using Latent Gold® Software, we identified latent classes of mothers based on their 1) average levels of distress and 2) change in distress over time. Results: We identified four latent classes based on average levels of distress and found that class membership probability was influenced by an interaction between MDD-PRS and prenatal depressive symptoms (WaldInteraction(3)=13.19, p=0.004; WaldMDD-PRS(3)=6.02, p=0.11; WaldDepression(3)=41.96; p<0.001), mELA (Wald(3)=8.64, p=0.035), and educational level (Wald(3)=11.61, p=0.009). Furthermore, we found five classes of mothers with distinct across- time trajectories, which were associated with mELA (Wald(3)=12.67, p=0.013). Conclusions: Our findings might become relevant in the clinical setting, e.g. for identifying pregnant women at risk for distress in the postpartum based on her prenatal symptoms of depression and genetic risk, mELA, and educational level.