2026 ECNP Congress

PS01-1097

Kynurenine pathway metabolites and grey matter volumes in peripartum depression: a voxel-based-morphometry study

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

2026 ECNP Congress

Background

Pregnancy and the postpartum period are high-risk windows for mood disturbances. Peripartum depression (PPD) is a depressive episode during pregnancy or after birth [1], affecting about 17% of women worldwide [2]. Its aetiology is multifactorial, involving psychological, social, and biological factors. Pregnancy is associated with significant hormonal and immune changes, including increased inflammation, which activates the kynurenine pathway (KP), shifting tryptophan (TRP) metabolism toward neuroactive metabolites influencing mood regulation [3]. Key KP markers include: kynurenic acid (KYNA), a neuroprotective metabolite; kynurenine-to-tryptophan ratio (KYN/TRP), indexing TRP degradation; kynurenic acid-to-quinolinic acid ratio (KYNA/QA), reflecting neuroprotective/neurotoxic balance; and kynurenic acid-to-kynurenine ratio (KYNA/KYN), indicating pathway activation toward KYNA production. Pregnancy has also been associated with mostly transient reductions in grey matter volumes (GMv) [4], suggesting that these neuroinflammatory and metabolic shifts may have structural brain correlates. Despite its relevance, the KP’s role in PPD remains unclear; clarifying its alterations may identify biomarkers or therapeutic targets.

Methods

We enrolled 61 pregnant women receiving prenatal care at San Raffaele Hospital and the Policlinico of Milan. Postpartum depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS) [5], and KP metabolites were measured in blood samples collected in the third trimester through mass spectrometry. Participants underwent 3T MRI with T1-weighted imaging. Voxel-based morphometry (VBM) analyses used the standard CAT12 pipeline in SPM12, including total intracranial volume extraction (TIV). Interaction terms (KP metabolite × PPD status) were included in the general linear model to test whether associations with GMv differed by group, covaring for age, hospital, TIV, days from delivery to MRI, and gestational week at blood sampling. Post-hoc analyses were performed in each group using STATISTICA software, with cluster-wise GMv extracted through the MarsBaR toolbox.

Results

EPDS identified 15 women with PPD and 46 healthy controls. Significant KP metabolite × PPD status interactions on GMv were found for: KYN (pFWE=0.007, k=1267, right superior frontal gyrus); KYNA (pFWE=0.009, k=1199, left angular gyrus); KYN/TRP (pFWE<0.001, k=2226, right superior frontal gyrus); KYNA/KYN in three clusters (cluster 1: pFWE=0.006, k=1296, right postcentral gyrus; cluster 2: pFWE=0.016, k=1037, right superior frontal gyrus; cluster 3: pFWE=0.040, k=810, left angular gyrus); and KYNA/QA (pFWE=0.013, k=1094, right precentral gyrus).

Post-hoc analyses showed KYN and KYN/TRP were negatively associated with frontal GM volumes (r=−0.53, p=0.044 and r=−0.53, p=0.043), while KYNA was positively associated with GM volumes exclusively in PPD women (r=0.66, p=0.008). Positive associations with GM volumes were likewise restricted to PPD women for KYNA/KYN (cluster 1: r=0.68, p=0.005; cluster 2: r=0.60, p=0.019; cluster 3: r=0.60, p=0.018) and KYNA/QA (r=0.62, p=0.014).

Conclusions

Relationships between KP metabolites and GMv were found exclusively in women who developed depressive symptoms, with increased conversion of TRP in KYN showing a detrimental effect, while production of KYNA exerted a positive effect. This finding suggests a biological relationship between TRP metabolites and brain structures specific to patients who develop PPD, thereby contributing to the biological and pathophysiological characterisation of perinatal affective disorders.

References

  1. Stewart, D. E., & Vigod, S. (2016). Postpartum depression. New England Journal of Medicine, 375(22), 2177-2186. https://doi.org/10.1056/NEJMcp1607649
  2. 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.
  3. Dantzer, R. (2016). Role of the kynurenine metabolism pathway in inflammation-induced depression: preclinical approaches. Inflammation-associated depression: Evidence, mechanisms and implications, 117-138. https://doi.org/10.1007/7854_2016_6
  4. 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. https://doi.org/10.1038/nn.4458
  5. Cox, J.L., Holden, J.M., Sagovsky, R., 1987. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br. J. Psychiatry. 150, 782-786. https://doi.org/10.1192/bjp.150.6.782.