Women’s Health
Metabolomic markers associated with antenatal depression Priscilla Kay Clayton* Priscilla Clayton Clayton Clayton Clayton Clayton Clayton Clayton Clayton Clayton Clayton priscilla.clayton@nih.gov
Background: Maternal depression affects up to 20% of pregnancies and is associated with adverse maternal and offspring outcomes. Several studies link antenatal depression to alterations in metabolites such as amino acids, lipids, and energy metabolism. However, few studies have examined these patterns during pregnancy.
Methods: We leveraged samples from the Pregnancy Outcomes, Maternal and Infant Study (PrOMIS) to examine metabolomic differences in 298 pregnant women. We assessed depression using the Patient Health Questionnaire-9 (score ≥10) and conducted targeted metabolomic profiling using liquid chromatography–mass spectrometry. We randomly partitioned the dataset into a training set (n=198) and an independent testing set (n=100). In the training set, we screened candidate metabolites using univariate logistic regression (p<0.05), followed by Elastic Net regularized logistic regression for the best model. We constructed receiver operating characteristic (ROC) curves to evaluate predictive performance.
Results: A total of 43 metabolites were significantly associated with depression (p<0.05), of which 17 were retained in the final model. Five metabolites were negatively associated (alloisoleucine, glutathione, pyruvic acid, PC P-34:0, palmitoyl-EA), while 12 were positively associated (R-3-hydroxy myristic acid, carnosine, PC O-38:5, glutamine, tridecylic acid, threonine, CAR 8:0; OH, N1,N8-diacetylspermidine, methionine, 3R-hydroxypalmitic acid, 2-aminoheptanoic acid, CAR DC6:0). ROC analyses yielded area under the curve (AUC) values of 0.81 (training), 0.73 (testing), and 0.78 (overall), adjusting for maternal age, pre-pregnancy BMI, gestational age, parity, and access to basic needs.
Conclusion: We identified metabolic signatures associated with antenatal depression, highlighting potential biomarkers and pathways such as amino acid, nitrogen, and anabolic metabolism. Future research should validate these findings in larger samples to establish clinical utility and potential for risk stratification.