2026 ECNP Congress

PS02-2183

Third trimester inflammatory signature predicts peripartum depression and reveals divergent brain-immune relationships

Yasmin Harrington — C. Milano, E.M.T. Melloni, E. Agnoletto, A. Ferro, D. Iraci, S. Spadini, C. Lorenzi, P. Brambilla, S. Poletti, F. Benedetti · IRCCS San Raffaele Hospital, Psychiatry and Clinical Psychobiology Unit- Division of Neuroscience, Milan, Italy

2026 ECNP Congress

Introduction

Peripartum depression (PPD) affects roughly 17% of women worldwide and has a significant burden on both maternal health and child development [1]. Increasing evidence links immune dysregulation to mood disorders [2], yet reliable inflammatory predictors of PPD remain limited. Pregnancy and the postpartum period are associated with dynamic changes in brain structure, particularly grey matter volume (GMV) [3]. However, to date, the relationship between inflammation and brain morphology in PPD has not been explored.

Aims

We aimed to examine whether inflammatory markers measured during the third trimester and at 6 weeks postpartum predict the development of PPD and to investigate their association with postpartum GMV.

Methods

140 pregnant women were recruited from the Department of Obstetrics and Gynaecology of IRCCS San Raffaele Hospital and the Policlinico of Milan. Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS) with a cutoff score of ≥11 indicating probable PPD. Blood samples were collected during the third trimester and 6 weeks postpartum and analysed using a Luminex Bio-Plex Pro Human Cytokine 48-Plex immunoassay. Partial least squares regression (PLS) was applied to third trimester and postpartum inflammatory markers in separate models to identify multivariate profiles predictive of PPD status. Model performance was evaluated using a 7-fold cross-validation, and variable importance in projection (VIP) scores were used to identify contributing markers. Structural MRI data were acquired for a subsample of 61 women at postpartum on a 3.0 Tesla scanner and processed using Computational Anatomy Toolbox (CAT12) for SPM12. Voxel-based morphometry (VBM) was used to examine interactions between the PLS-derived inflammatory component and PPD status on GMV. Further, significant clusters from the VBM analysis were extracted using MarsBaR and entered into a post-hoc moderation model using PROCESS in SPSS. All analyses included age, recruitment center, number of previous pregnancies, and gestational week at blood sampling as covariates; neuroimaging analyses additionally controlled for total intracranial volume and days from delivery to MRI.

Results

The PLS model using third trimester markers as predictors showed a significant overall effect with one significant component explaining 6.7% of variance by exploiting 50% of variance in predictors (b=0.086, R2X = 0.449; R2Y = 0.067). 21 inflammatory markers significantly contributed to the component. In contrast, the model based on postpartum markers was not significant.The VBM analysis identified a significant interaction between the inflammatory component and PPD status in a cluster of 877 voxels encompassing the left occipital pole, calcarine cortex, and inferior, middle, and superior occipital gyri (pFWE=0.031). The post-hoc moderation analysis confirmed this interaction (β=−0.0091, p<.001) and conditional effects indicated a positive association between inflammation and GMV in non-PPD women (β=0.0032, SE=0.0010, p=.0029), and a negative association in PPD women (β=−0.0060, SE=0.0013, p<.001).

Discussion

These findings suggest that a multivariate inflammatory signature during late pregnancy predicts PPD risk and exhibits opposing associations with brain structure depending on PPD status. This pattern may reflect distinct neuroimmune mechanisms underlying vulnerability versus resilience. Integrating immunological and neuroimaging approaches may improve early identification and inform targeted interventions for PPD.

References

  1. Wang, Z.; Liu, J.; Shuai, H.; Cai, Z.; Fu, X.; Liu, Y.; Xiao, X.; Zhang, W.; Krabbendam, E.; Liu, S.; et al. Mapping Global Prevalence of Depression among Postpartum Women. Transl. Psychiatry 2021, 11, 543.
  2. Silva-Fernandes, A., Conde, A., Marques, M., Caparros-Gonzalez, R.A., Fransson, E., Mesquita, A.R., Figueiredo, B. and Skalkidou, A., 2024. Inflammatory biomarkers and perinatal depression: a systematic review. Plos one, 19(5), p.e0280612.
  3. Hoekzema, E., Barba-Müller, E., Pozzobon, C., Picado, M., Lucco, F., García-García, D., Soliva, J. C., Tobeña, A., Desco, M., Crone, E. A., Ballesteros, A., Carmona, S., & Vilarroya, O. (2017). Pregnancy leads to long-lasting changes in human brain structure. Nature Neuroscience, 20(2), 287-296.