Late-Pregnancy Immune and Kynurenine Signatures Predict Postpartum Depression and Brain Morphology
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: ABSTRACT Background Pregnancy involves profound immune adaptations that may contribute to the development of postpartum depression (PPD); however, the relevant biomarkers and critical time window remain unclear. Therefore, we investigated whether third-trimester and postpartum cytokines and kynurenine pathway (KP) metabolites predict PPD and whether these biological signatures are related to postpartum brain morphology. Methods Circulating cytokines and KP metabolites were assessed in 140 pregnant women during the third trimester and postpartum. Partial least squares (PLS) regression models were used to identify multivariate biological profiles predictive of PPD, followed by classification and regression tree (CART) analyses to evaluate predictive performance. In a neuroimaging subsample (n=61), voxel-based morphometry examined associations among PPD status, significant PLS-derived components, selected individual biomarkers, and postpartum grey matter volume. Results A third-trimester cytokine signature including 21 cytokines significantly predicted PPD with high specificity. A third-trimester KP profile, driven primarily by the kynurenic acid/quinolinic acid ratio, also predicted PPD, and the combination of cytokine and KP components improved overall predictive performance to 93.3%. Postpartum biomarkers showed substantially weaker associations with PPD. The cytokine component was differentially associated with postpartum grey matter volume according to PPD status, with opposite associations observed in occipital regions between women who did and did not develop PPD. KP measures also showed distinct associations within sensorimotor regions based on PPD status Conclusions Late pregnancy immune-inflammatory alterations are associated with subsequent PPD and postpartum brain morphology, supporting the potential utility of pregnancy-derived biological signatures for identifying women at increased risk for PPD.
Source: medRxiv
Authors: Yasmin A. Harrington, Ha Kyung Shin, Chiara Milano, Massimo C. Mauri, Alessandra Marano, Eleonora Maggioni, Letizia Squarcina, Emma Tassi, Paolo Enrico, Nicola Persico, Giorgio Conte, Elisa M.T Melloni, Elena Agnoletto, Sara Spadini, Cristina Lorenzi, Sofia Nasini, Stefano Dall’Acqua, Stefano Comai, Sara Poletti, Massimo Origoni, Paolo Brambilla, Francesco Benedetti, Milano PPDINFLAME Study Group
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: Ministero della Salute
Awards: G3105255457, G8830289886
OpenAlex ID: W7220731903