Evidence map›Paper›PMID 41140460›Full record

ArticleEClinicalMedicine2025

Identification and validation of postpartum depression subtypes: a population-based cohort study.

Anna E Bauer, Piotr Jaholkowski, Yi Lu, Jerry Guintivano, Laurie J Hannigan, Elizabeth C Corfield, Martin Tesli, Ole A Andreassen, Yun Li, Ted Reichborn-Kjennerud and 4 more

Abstract read
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Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Anna E BauerDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Piotr JaholkowskiInstitute of Psychiatry and Neurology, University of Oslo, Oslo, Norway.
Yi LuDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Jerry GuintivanoDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Laurie J HanniganNic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway.
Elizabeth C CorfieldNic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway.
Martin TesliDepartment of Mental Health and Suicide, Norwegian Institute of Public Health, Oslo, Norway.
Ole A AndreassenCentre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
Yun LiDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Ted Reichborn-KjennerudDepartment of Genetics, Environment, and Mental Health, Norwegian Institute of Public Health, Oslo, Norway.
Patrick F SullivanDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Samantha Meltzer-BrodyDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Alexandra HavdahlNic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway.
Helga AskPsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway.

Funding

Beyond GWAS: High Throughput Functional Genomics & Epigenome Editing to Elucidate the Effects of Genetic Associations for SchizophreniaR01MH125236 · NIMH · DUKE UNIVERSITY · PI CRAWFORD, GREGORY E, GERSBACH, CHARLES A. · 2021 to 2025
$8.1M
A Trans-Nordic Study of Extreme Major DepressionR01MH123724 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PATRICK F SULLIVAN, Lu Yi · 2020 to 2026
$4.7M
Disentangling the Epidemiologic and Genetic Heterogeneity of Postpartum Depression to Predict Risk and PrognosisK01MH120352 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BAUER, ANNA ELIZABETH · 2019 to 2023
$761k
NIMH NIH HHS K01 MH120352NIMH NIH HHS R01 MH123724NIMH NIH HHS R01 MH125236
6 · The paper itself

Abstract

Background: Postpartum depression (PPD) affects 18% of postpartum women globally. PPD is a heterogeneous condition with diverse presentations, which may differ in underlying etiology, potential outcomes, and optimal treatment. This study aimed to identify and validate PPD subtypes using comprehensive phenotypic and genetic data from a large, nationwide cohort. Methods: In this population-based cohort study, we used data from the Norwegian Mother, Father, and Child Cohort Study and Medical Birth Registry of Norway (MoBa), and applied unsupervised clustering (Uniform Manifold Approximation and Projection [UMAP] + Density-Based Spatial Clustering of Applications with Noise [DBSCAN]) to identify PPD subtypes among 7859 women with PPD (training set n = 5239). All pregnant women in Norway were eligible to enroll in MoBa between Jun 1, 1999 and Dec 31, 2008. Among women with their first recorded pregnancies in MoBa, they were considered to have clinically significant PPD if they scored ≥8 on the 6-item version of the Edinburgh Postnatal Depression Scale (EPDS) (equivalent to ≥11 on the full EPDS) administered at six months after birth. Input variables included psychiatric symptom severity, psychiatric history, trauma history, pain, and substance use. We then characterized clusters and tested associations with perinatal-relevant auxiliary variables and polygenic scores (PGS) for eight psychiatric and neurodevelopmental conditions. Findings were validated in a reserved test set (n = 2620). Findings: Nine clusters were identified in the training set (n = 5239), with seven replicating in the independent test set (n = 2620). Clusters were differentiated by symptom severity, onset timing, trauma history, and pain during pregnancy. In the training set, the cluster with the most severe symptoms was characterized by depression + trauma and comprised 28% [1483/5239] of training sample. This cluster showed marked socioeconomic adversity and elevated genetic risk for psychiatric conditions compared to other clusters (ADHD PGS OR 1.19, 95% CI 1.12-1.28; major depression PGS OR 1.15, 95% CI 1.07-1.23; PTSD PGS OR 1.09, 95% CI 1.02-1.17). In the test set, this cluster also comprised 28% [729/2620] and showed consistent associations with ADHD (OR 1.23, 95% CI 1.12-1.35), major depression (OR 1.09, 95% CI 0.99-1.20), and PTSD (OR 1.17, 95% CI 1.06-1.29). Conversely, the mild PPD cluster (10% [498/5239] of training sample) showed a protective profile (ADHD PGS OR 0.81, 95% CI 0.73-0.90; major depression PGS OR 0.85, 95% CI 0.77-0.94). In the test set, it represented 10% (263/2620), with consistent protective associations for ADHD (OR 0.84, 95% CI 0.72-0.96) and major depression (OR 0.77, 95% CI 0.67-0.89). Two early-onset clusters demonstrated distinct profiles despite similar symptom severity. The cluster characterized as early-onset PPD + pain (6% of training set [310/5239] and 7% of test set [178/2620]) had the highest prevalence of somatic conditions, including migraines (19% [58/310] training; 15% [26/178] test), nausea (47% [144/310] training; 53% [94/178] test), prenatal hospitalization (41% [128/310] training; 35% [62/178] test), and birth by caesarean section (10% [31/310] training; 8% [14/178] test), whereas the cluster characterized as early-onset PPD + anger (6% [307/5239] of training sample; 6% [158/2620] of test sample) showed many fewer physical health burdens. The clusters in the training and testing set had moderate to high concordance (ARI = 0.76 [95% CI 0.74, 0.77], FMI = 0.79 [95% CI 0.77, 0.81]). Interpretation: This study identifies clinically relevant PPD subtypes with distinct genetic and obstetric profiles, highlighting the importance of trauma-informed care, pain management, and holistic obstetric approaches in PPD prevention and treatment. Limitations of this study include reliance on self-reported data, lack of diversity in the genetically homogeneous Norwegian sample, and genetic analyses subject to power constraints, which may limit generalizability and reduce precision of results. Despite these limitations, identification of reproducible subtypes with different risk factors and outcomes provides a framework for developing targeted interventions and advancing precision psychiatry in maternal mental health. Funding: National Institute of Mental Health; National Institute of Child Health and Human Development; MRC Integrative Epidemiology Unit, University of Bristol; European Research Council; Marie Skłodowska-Curie Actions; South-Eastern Norway Regional Health Authority; Research Council of Norway; NordForsk; European Union Horizon 2020; Novo Nordisk Foundation.

Indexed as

Cluster analysisFather and child cohort studyPerinatal psychiatryPolygenic riskPostpartum depressionThe Norwegian mother

Identifiers

PMID41140460
PMCPMC12546979

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