Evidence map›Paper›PMID 42039520›Full record

ArticlebioRxiv : the preprint server for biology2026

The PMADS Project: A Longitudinal Multimodal Cohort Study to Understand Risk for Perinatal Mood and Anxiety Disorders.

Noemí Rubau-Apa, Caroline Hayes, Ashley Francisco, Sage Rush, Hudah Rana, Mahima Islam, Lily Hunter, Laura Pritschet, Taylor Salo, Suneeta Senapati and 25 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

35 authors.

Noemí Rubau-ApaTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Caroline HayesTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Ashley FranciscoTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Sage RushDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Hudah RanaTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Mahima IslamTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Lily HunterTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Laura PritschetTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Taylor SaloDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Suneeta SenapatiDepartment of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA, USA.
Liisa HantsooDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Deepak IndrakantiDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Emily M BeydlerDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Erica B BallerDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Ran BarzilayDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Monica E CalkinsDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Matthew CieslakDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
John A DetreDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Sammy DhaliwalTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Mark A ElliottDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Hao HuangDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Arielle S KellerDepartment of Psychological Sciences, University of Connecticut, Storrs, Connecticut, USA.
C Brock KirwanMindCORE, University of Pennsylvania, Philadelphia, PA, USA.
Rachel KishtonTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.
Tyler M MooreDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Sara L KornfieldPenn Center for Women's Behavioral Wellness, University of Pennsylvania, Philadelphia, PA, USA.
J Cobb ScottDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Manuel TasoDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
M Dylan TisdallDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Arastoo VossoughDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Lauren K WhiteDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Kelly ZafmanDepartment of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA, USA.
Daniel H WolfDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
David R RoalfDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Sheila ShanmuganTranslational Reproductive Neuropsychiatry and Data Science (TReNDS) Lab, Philadelphia, PA, USA.ORCID 0000-0001-7633-163X

Funding

Using person-specific networks to uncover sex differences in vulnerability to internalizing disordersDP5OD036142 · OD · UNIVERSITY OF PENNSYLVANIA · PI Sheila Shanmugan · 2023 to 2026
$2.0M
Depression as a disease of network disruption: learning from multiple sclerosisK23MH133118 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Erica Berlin Baller · 2023 to 2026
$780k
Elucidating the role of endocrine aging as a risk factor for Alzheimer's DiseaseK00AG079790 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Laura Pritschet · 2024 to 2026
$228k
NIA NIH HHS K00 AG079790NIH HHS DP5 OD036142NIMH NIH HHS K23 MH133118NIMH NIH HHS L40 MH124104
6 · The paper itself

Abstract

Background: Perinatal mood and anxiety disorders (PMADs) are among the most common and consequential complications of pregnancy. The perinatal period is also characterized by profound hormonal fluctuations and large-scale brain plasticity. However, the mechanisms linking these neurobiological changes to psychiatric risk are poorly understood. Prospective, clinically informed studies are needed to identify quantitative biomarkers and clarify pathways linking perinatal neurobiology to PMADs risk. Methods: This report describes the design of a prospective, longitudinal cohort study integrating multimodal neuroimaging, biofluid sampling, and deep clinical phenotyping to enable precision characterization of neurobiological trajectories of PMADs risk. Twenty-five individuals at elevated risk for PMADs will be recruited prior to conception and followed across six in-person timepoints spanning the menstrual cycle, pregnancy, and early postpartum, with additional remote follow-ups through the first postpartum year. Data collection includes high-resolution structural MRI, functional brain mapping using multi-echo resting-state fMRI, diffusion MRI, arterial spin labeling, ultra-high field MR-based techniques for measuring glutamate (GluCEST and Discussion: This cohort study establishes a longitudinal, multimodal framework for investigating neurobiological changes across the transition to pregnancy in individuals at elevated risk for PMADs. By anchoring pregnancy-related brain changes to preconception and menstrual cycle-related variability within the same individuals, this study is designed to evaluate associations between preconception hormone sensitivity, pregnancy-induced neuroplasticity, and PMADs risk. The resulting dataset will provide a deeply phenotyped longitudinal resource for investigating brain-behavior relationships across the perinatal period. Findings are expected to inform future larger-scale studies aimed at advancing mechanistic understanding of PMADs, improving individualized risk stratification, and supporting development of personalized preventive and neuromodulatory interventions.

Indexed as

brain plasticityneuroimagingperinatal depressionperinatal mood and anxiety disorderspostpartum depressionprecision functional mappingpreconceptionpregnancypremenstrual mood disorders

Identifiers

PMID42039520
PMCPMC13104829

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.