Evidence map›Paper›PMID 40778264›Full record

ArticleFrontiers in cell and developmental biology2025

Extracellular vesicles as prospective biological indicators for midgestational placental complications in the mouse.

Elaine Lee, Parinaz Kazemi, Shiva Shafiei, Sarah Yull, Mansuba Rana, Nadim Tawil, Laura Montermini, Janusz Rak, Daniel Dufort

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

9 authors.

Elaine Lee *Division of Experimental Medicine, McGill University, Montreal, QC, Canada.
Parinaz Kazemi *Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
Shiva ShafieiChild Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
Sarah YullDivision of Experimental Medicine, McGill University, Montreal, QC, Canada.
Mansuba RanaDivision of Experimental Medicine, McGill University, Montreal, QC, Canada.
Nadim TawilChild Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
Laura MonterminiChild Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.
Janusz RakDivision of Experimental Medicine, McGill University, Montreal, QC, Canada.
Daniel DufortDivision of Experimental Medicine, McGill University, Montreal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Placental dysfunction is often associated with reproductive complications such as preeclampsia, intrauterine growth restriction (IUGR), and preterm birth. Currently, the early diagnosis and intervention of these pathologies remain challenging due to the invasive nature of placental tissue sampling. Liquid biopsies of extracellular vesicles (EVs) released from the placenta have emerged as a prospective minimally invasive diagnostic strategy that could provide insight into the maternal-fetal interface because of the active role EVs play in mediating placental development and function. However, the lack of information on EVs directly from placenta at disease onset has questioned the representativeness of placental EVs as pathological indicators. To address these concerns, this study assessed the accuracy with which tissue-derived D10.5 placental EVs could identify phenotypes exhibited by a reproductively challenged Nodal conditional knockout mouse model at mid-gestation. Method: Implantation sites from female mice with a uterine-specific knockdown of the Nodal gene were examined from D8.5 to D14.5 utilizing histological analysis, Western blotting, and RT-qPCR to characterize their mid-gestational phenotypes. Placental EVs were then isolated from D10.5 placenta using enzymatic digestion, differential centrifugation, filtration, and size-exclusion chromatography. The final EV fractions were concentrated and validated with size analysis, canonical protein markers, and morphology assessment. Differential expression analysis across the EV samples was performed using proteomics and miRNA-Seq. Functional enrichment analysis of dysregulated EV factors was then completed using several gene ontology databases along with a literature review to determine whether placental EVs could indicate the reproductive abnormalities presented by the mutant mice. Results: Uterine-specific deletion of Nodal resulted in IUGR and fetal loss in mutant dams. Decidualization and placentation defects were observed, including thinner decidual and placental tissues, impaired angiogenesis, and an altered junctional zone within the maternal-fetal interface. Bioinformatics analysis of EV cargo identified 31 differentially expressed proteins and 10 miRNAs specifically linked to placental development, oxidative stress, angiogenesis, and immunomodulation. Notably, 15 of these proteins and six of these miRNAs have been previously associated with pregnancy complications, further supporting the prospects of placental EVs as biomarkers for various placental diseases. Conclusion: These findings suggest that placental EVs can reflect compromised placental function and could serve as pathological indicators for the early detection of pregnancy complications. Their potential diagnostic utility could improve maternal and neonatal health outcomes by enabling earlier intervention and monitoring of high-risk pregnancies.

Indexed as

EVsexosomesmiRNAsNodalplacentapregnancyproteomics

Identifiers

PMID40778264
PMCPMC12329223

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.