Evidence map›Paper›PMID 39607297›Full record

ArticleActa obstetricia et gynecologica Scandinavica2025

A novel multiple marker microarray analyzer and methodology to predict major obstetric syndromes using surface markers of circulating extracellular vesicles from maternal plasma.

Malene Møller Jørgensen, Rikke Bæk, Jenni K Sloth, Rami Sammour, Adi Sharabi-Nov, Manu Vatish, Hamutal Meiri, Marei Sammar

Abstract read
In one paragraph

Article in Acta obstetricia et gynecologica Scandinavica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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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

8 authors.

Malene Møller JørgensenDepartment of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0003-1381-3863
Rikke BækDepartment of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark.
Jenni K SlothDepartment of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark.
Rami SammourDepartment of Obstetrics and Gynecology, Maternal and Fetal Medicine Unit, Bnai-Zion University Medical Center, Haifa, Israel.
Adi Sharabi-NovDepartment of Statistics, Tel Hai Academic College, Tel Hai and Ziv Medical Center, Safed, Israel.
Manu VatishNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.ORCID 0000-0002-6012-2574
Hamutal MeiriTeleMarpe Ltd, Tel Aviv, Israel.ORCID 0000-0002-2272-5139
Marei SammarProf. Ephraim Katzir Department of Biotechnology Engineering, Braude College of Engineering, St, Karmiel, Israel.

Funding

Braude College of Engineering, Research Collaboration ProgramCOST Action STSM-CA16113
6 · The paper itself

Abstract

introductionPlacental-derived extracellular vesicles (EVs) are nano-organelles that facilitate intercellular communication between the feto-placental unit and the mother. We evaluated a novel Multiple Microarray analyzer for identifying surface markers on plasma EVs that predict preterm delivery and preeclampsia compared to term delivery controls. MATERIAL AND

methodsIn this prospective exploratory cohort study pregnant women between 24 and 40 gestational weeks with preterm delivery (n = 16), preeclampsia (n = 19), and matched term delivery controls (n = 15) were recruited from Bnai Zion Medical Center, Haifa, Israel. Plasma samples were tested using a multiple microarray analyzer. Glass slides with 17 antibodies against EV surface receptors - were incubated with raw plasma samples, detected by biotinylated secondary antibodies specific to EVs or placental EVs (PEVs), and labeled with cyanine 5-streptavidin. PBS and whole human IgG served as controls. The fluorescent signal ratio to negative controls was log 2 transformed and analyzed for sensitivity and specificity using the area under the receiver operating characteristics curves (AUROC). Best pair ratios of general EVs/PEVs were used for univariate analysis, and top pairs were combined for multivariate analysis. Results were validated by comparison with EVs purified using standard procedures.

resultsHeatmaps differentiated surface profiles of preeclampsia, preterm delivery, and term delivery receptors on total EVs and PEVs. Similar results were obtained with enriched EVs and EVs from raw plasma. Univariate analyses identified markers predicting preterm delivery and preeclampsia over term delivery controls with AUC >0.6 and sensitivity >50% at 80% specificity. Combining the best markers in a multivariate model, preeclampsia prediction over term delivery had an AUC of 0.89 (95% CI: 0.72-1.0) with 90% sensitivity and 90% specificity, marked by inflammation (TNF RII), relaxation (placenta protein 13 (PP13)), and immune-modulation (LFA1) receptors. Preterm delivery prediction over term delivery had an AUC of 0.97 (0.94-1.0), 84% sensitivity, and 90% specificity, marked by cell adhesion (ICAM), immune suppression, and general EV markers (CD81, CD82, and Alix). Preeclampsia prediction over preterm delivery had an AUC of 0.91 (0.79-0.99) with 80% sensitivity and 90% specificity with markers for complement activation (C1q) and autoimmunity markers.

conclusionsThe new, robust EV Multi-Array analyzer and methodology offer a simple, fast diagnostic tool that reveals novel surface markers for major obstetric syndromes.

Indexed as

BiomarkersExtracellular VesiclesPre-EclampsiaAdultCase-Control StudiesFemaleHumansIsraelMicroarray AnalysisPlacentaPredictive Value of TestsPregnancyPremature BirthProspective StudiesSensitivity and SpecificityBiomarkersdifferential diagnosisextracellular vesiclesimmunodiagnosticsmicro arrayspreeclampsiapreterm deliverysurface markers

Identifiers

PMID39607297
PMCPMC11683545

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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.