Maternal Antenatal Depression Is Associated With Metabolic Alterations That Predict Birth Outcomes and Child Neurodevelopment and Mental Health

Background: Evidence regarding metabolic alterations associated with maternal antenatal depression (AD) is limited, and their role as potential biomarkers that improve the prediction of AD and adverse childbirth, neurodevelopmental, and mental health outcomes remains unexplored. Methods: In a cohort of 331 mother-child dyads, we studied associations between AD (a history of medical register diagnoses and/or a Center for Epidemiological Studies Depression Scale score during pregnancy ≥ 20) and 95 metabolic measures analyzed 3 times during pregnancy. We tested whether the AD-related metabolic measures increased variance explained in AD over its risk factors and in childbirth, neurodevelopmental, and mental health outcomes over AD. We replicated the findings in a cohort of 416 mother-child dyads. Results: Elastic net regression identified 15 metabolic measures that collectively explained 25% (p < .0001) of the variance in AD, including amino and fatty acids, glucose, inflammation, and lipids. These metabolic measures increased the variance explained in AD over its risk factors (32.3%, p < .0001 vs. 12.6%, p = .004) and in child gestational age (9.0%, p < .0001 vs. 0.7%, p = .34), birth weight (9.0%, p = .03 vs. 0.7%, p = .33), developmental milestones at the age of 2.3 to 5.7 years (21.0%, p = .002 vs. 11.6%, p < .001), and any mental or behavioral disorder by the age of 13.1 to 16.8 years (25.2%, p = .03 vs. 5.0%, p = .11) over AD, child sex, and age. These findings were replicated in the independent cohort. Conclusions: AD was associated with alterations in 15 metabolic measures, which collectively improved the prediction of AD over its risk factors and birth, neurodevelopmental, and mental health outcomes in children over AD. These metabolic measures may become biomarkers that can be used to identify at-risk mothers and children for personalized interventions.