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Host–gut microbial metabolic crosstalk in postpartum depression: A multiomics insight linking blood metabolites to epigenetic modulation
Jan 10, 2026Journal of affective disorders
How Gut Bacteria Affect Postpartum Depression
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Abstract
New research shows that the bacteria in our gut and their byproducts may play a role in postpartum depression (PPD). However, we still don't fully understand how these factors influence the body's metabolism.
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BACKGROUND: Recent studies suggest a link among the gut microbiota, its metabolites, and postpartum depression (PPD); however, the specific effects on host metabolism remain unclear.
METHODS: A two-sample Mendelian randomization (MR) analysis was conducted using Genome-wide association study (GWAS) summary statistics on the gut microbiota and PPD. Two-step MR identified potential blood metabolites. Metabolic genes were retrieved from GeneCards. Summary data-based MR (SMR) methods integrate PPD GWAS data with blood expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) to identify key blood metabolic genes and regulatory regions linked to PPD risk. Colocalization analysis investigated interactions between host metabolic gene expression and the gut microbiota using fecal microbial quantitative trait loci (mbQTLs).
RESULTS: A two-sample MR analysis revealed that class Clostridia (OR = 1.174 95% CI = 1.002-1.376 P = 0.047), order Bifidobacteriales (OR = 1.365, 95% CI: 1.073-1.735, P = 0.029), family Bifidobacteriaceae (OR = 1.365, 95% CI: 1.077-1.729, P = 0.027), genus Eggerthella (OR = 1.126 95% CI = 1.024-1.238 P = 0.014), genus Prevotella7 (OR = 1.111, 95% CI: 1.012-1.22, P = 0.026), and genus RuminococcaceaeUCG011 (OR = 1.094 95% CI = 1.009-1.185 P = 0.029) were positively correlated with PPD risk, whereas phylum Verrucomicrobia (OR = 0.881; 95% CI: 0.783-0.991; P = 0.036) had protective effects. HDL was identified as a key intermediary between Bifidobacteriales and PPD. Integrating eQTL and mQTL data, SMR revealed seven blood tissue genes (RAF1, KHK, SLC3A1, FAM3B, ALDH7A1, FDXR, and GATM) as potential causal genes for PPD and implicated specific DNA methylation sites in their regulation. Colocalization analysis revealed that FDXR, RAF1, GATM, and SLC3A1 are involved in gene-microbiota interactions.
CONCLUSION: This multiomics study revealed that host metabolic genes linked to PPD are regulated through DNA methylation and metabolite-mediated host-microbiota interactions. These findings establish a foundation for future functional studies to develop mechanism-based therapeutic and preventive strategies targeting the gut-brain-metabolite axis in PPD.
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