ArticlebioRxiv : the preprint server for biology2025
Perinatal Shifts in Fecal-Derived Metabolites and Associations with Postpartum Depression.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors.
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Abstract
Introduction: Research on maternal depression is largely limited to static, blood-derived biomarkers in the postpartum period and mechanistic targets derived from populations outside the physiological contexts of pregnancy and postpartum, resulting in critical gaps in understanding context-specific mechanisms underlying this debilitating condition. Objectives: To examine temporal shifts in the maternal gut metabolome and associations between pregnancy-specific shifts and postpartum depression (PPD). Methods: We applied untargeted metabolomics (UPLC-MS/MS) to fecal samples collected from participants (N= 25) enrolled in the Maternal and Infant NutriTion (MINT) study. Random forest analysis was used to identify key pathways and metabolites contributing to temporal shifts. Fold change analysis and paired t-tests were used to quantify the magnitude and significance of metabolite changes. Associations between pregnancy-specific changes and PPD (Edinburgh Postnatal Depression Scale at 6 weeks) were identified using Pearson's correlation. Results: Lipid, amino acid, and xenobiotic metabolism emerged as core pathways driving temporal changes in the maternal gut metabolome. The most pronounced shifts occurred from 35 weeks gestation to postpartum, with 55 metabolites significantly altered compared to 24 from 24- to 35 weeks gestation and 26 from 24 weeks gestation to postpartum. Of the 29 metabolites associated with PPD; 68.9% were metabolic intermediates, primarily involved in lipid and amino acid metabolism (58.6%). Conclusions: This study provides some of the first evidence of temporal shifts in the maternal gut metabolome and associations with PPD, highlighting the importance of lipid and amino acid metabolism and laying the groundwork for future multi-omics research.
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