ArticleGenes2024
Disentangling the Genetic Landscape of Peripartum Depression: A Multi-Polygenic Machine Learning Approach on an Italian Sample.
Article in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- State-of-the-art treatment of postpartum bipolar disorder.Current opinion in psychiatry · 2026Review
- Peripartum Depression Pharmacotherapies Targeting GABA-Glutamate Neurotransmission.Journal of clinical medicine · 2025Review
- Sex-Specific Inflammatory Profiles Affect Neuropsychiatric Issues in COVID-19 Survivors.Biomolecules · 2025Article
- A method for predicting postpartum depression via an ensemble neural network model.Frontiers in public health · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
backgroundThe genetic determinants of peripartum depression (PPD) are not fully understood. Using a multi-polygenic score approach, we characterized the relationship between genome-wide information and the history of PPD in patients with mood disorders, with the hypothesis that multiple polygenic risk scores (PRSs) could potentially influence the development of PPD.
methodsWe calculated 341 PRSs for 178 parous mood disorder inpatients affected by major depressive disorder (MDD) or bipolar disorder (BD) with (
resultsThe PLS linear regression in the whole sample defined a model explaining 27.12% of the variance in the presence of PPD history, 56.73% of variance among MDD, and 42.96% of variance in BD. Our findings highlight that multiple genetic factors related to circadian rhythms, inflammation, and psychiatric diagnoses are top contributors to the prediction of PPD. Specifically, in MDD, the top contributing PRS was monocyte count, while in BD, it was chronotype, with PRSs for inflammation and psychiatric diagnoses significantly contributing to both groups.
conclusionsThese results confirm previous literature about the immune system dysregulation in postpartum mood disorders, and shed light on which genetic factors are involved in the pathophysiology of PPD.
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