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A 112-pair sub-cohort underwent multi-omics analyses: meconium microbiota profiling via 16S rRNA sequencing and cord blood tryptophan metabolite quantification via liquid chromatography\u2013tandem mass spectrometry. Least absolute shrinkage and selection operator (LASSO) regression, mediation analyses, and XGBoost modeling were applied.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Prenatal depression alone was a significant risk factor for ISD (fully adjusted OR\u2009=\u20091.53, 95% CI: 1.04\u20132.25), with a stronger effect in female infants (OR\u2009=\u20092.11, p\u2009=\u2009.022). Cord blood cortisol partially mediated this link (Average Causal Mediation Effect\u2009=\u2009\u20137.47, 95% CI: [\u201314.82, \u20130.12], p\u2009=\u2009.048). Prenatal anxiety correlated with reduced meconium microbial alpha-diversity, lower Bifidobacterium abundance, and decreased 3-HAA\/serotonin levels, which were associated with sleep disturbance; serial mediation confirmed the gut microbiota-tryptophan metabolism pathway. The XGBoost predictive model achieved an AUC of 0.727, with microbial diversity, Streptococcus abundance, dopamine, and 3-HAA as top contributors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study identifies distinct mediating pathways for depression and anxiety, providing targets for personalized infant sleep health interventions.<\/jats:p>\n                    <jats:p>Statement of Significance This study reveals that prenatal depression and anxiety impair infant sleep through distinct biological pathways. Depression was associated with elevated fetal cortisol (HPA axis), while anxiety may influence the neonatal gut microbiome and its production of sleep-regulating tryptophan metabolites. These findings contribute to a novel dual-pathway model that helps clarify previously unresolved mechanistic questions. By integrating these biomarkers into a machine learning model, we offer a translational tool for early risk prediction. The work bridges a critical gap between epidemiological observation and biological mechanism, paving the way for personalized interventions\u2014targeting stress hormones for depression or gut health for anxiety\u2014to improve infant neurodevelopmental outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/sleep\/zsag171","type":"journal-article","created":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T20:05:03Z","timestamp":1782590703000},"source":"Crossref","is-referenced-by-count":1,"title":["Differential effects of prenatal depression and anxiety on infant sleep: dual-pathway mechanisms involving the hypothalamic\u2013pituitary\u2013adrenal axis and the gut-brain axis"],"prefix":"10.1093","volume":"49","author":[{"given":"Can","family":"Liu","sequence":"first","affiliation":[{"name":"School of Public Health, Ningxia Medical University , Yinchuan, Ningxia 750004 ,","place":["China"]},{"name":"Ningxia Key Laboratory of Environmental Factors and Chronic Disease 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