Evidence map›Paper›PMID 40057749›Full record

ArticleBMC pregnancy and childbirth2025

First trimester circulating miR-208b-3p and miR-26a-1-3p are relevant to the prediction of gestational hypertension.

Andrée-Anne Clément, Cécilia Légaré, Véronique Desgagné, Kathrine Thibeault, Frédérique White, Michelle S Scott, Pierre-Étienne Jacques, William D Fraser, Patrice Perron, Renée Guérin and 3 more

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

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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

13 authors.

Andrée-Anne ClémentDepartment of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, Québec, Canada.
Cécilia LégaréRNA Institute, College of Arts and Sciences, University at Albany-SUNY, Albany, NY, USA.
Véronique DesgagnéDepartment of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, Québec, Canada.
Kathrine ThibeaultDepartment of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, Québec, Canada.
Frédérique WhiteDepartment of biology, Faculty of Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Michelle S ScottDepartment of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, Québec, Canada.
Pierre-Étienne JacquesDepartment of biology, Faculty of Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada.
William D FraserDepartment of Obstetrics and Gynecology, Faculty of Medecine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Patrice PerronCentre de Recherche du Centre hospitalier universitaire de Sherbrooke (CR-CHUS), Sherbrooke, Québec, Canada.
Renée GuérinDepartment of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, Québec, Canada.
Marie-France HivertDepartment of Medicine, Faculty of Medecine and Health Sciences, Université de Sherbrooke, Sherbrooke, Québec, Canada.
Anne-Marie CôtéCentre de Recherche du Centre hospitalier universitaire de Sherbrooke (CR-CHUS), Sherbrooke, Québec, Canada.
Luigi BouchardDepartment of Biochemistry and Functional Genomics, Faculty of Medicine and Health Sciences (FMHS), Université de Sherbrooke, Sherbrooke, Québec, Canada. Luigi.Bouchard@USherbrooke.ca.

Funding

CIHR #MOP 115071Fonds de Recherche du Québec - Santé #20697
6 · The paper itself

Abstract

backgroundGestational hypertension (GH) is linked to an increased risk of cardiometabolic diseases for both mother and child, but we lack reliable biomarkers to identify high-risk women early in pregnancy. MicroRNAs (miRNAs) are small non-coding RNA that have emerged as promising biomarkers for pregnancy complications. We thus aimed to identify first trimester circulating miRNAs associated with GH and to build a miRNA-based algorithm to predict GH incidence.

methodsWe quantified miRNAs using next-generation sequencing in plasma samples collected at first trimester of pregnancy in Gen3G (N = 413, including 28 GH cases) and 3D (N = 281, including 21 GH cases) prospective birth cohorts. MiRNAs associated with GH in Gen3G (identified using DESeq2, p-value < 0.05) and replicated in 3D were included in a stepwise logistic regression model to estimate the probability of developing GH based on the miRNAs (normalized z-score counts) and maternal characteristics that contribute most to the model.

resultsWe identified 28 miRNAs associated with the onset of GH later in pregnancy (p < 0.05) in the Gen3G cohort. Among these, three were replicated in the 3D cohort (similar fold change and p < 0.1) and were included in stepwise logistic regression models with GH-related risk factors. When combined with first trimester mean arterial pressure (MAP), miR-208b-3p and miR-26a-1-3p achieve an AUC of 0.803 (95%CI: 0.512-0.895) in Gen3G and 0.709 (95%CI: 0.588-0.829) in 3D. The addition of miR-208b-3p, and miR-26a-1-3p to the model significantly improves the prediction performance over that of MAP alone (p = 0.03). We then proposed low and high-risk thresholds, which could help identify women at very low risk of GH and those who could benefit from prevention monitoring throughout their pregnancy.

conclusionThe combination of circulating miR-208b-3p and miR-26a-1-3p with first trimester MAP offers good performance as early predictors of GH. Interestingly, these miRNAs target pathways related to the cardiovascular system and could thus be relevant to the pathophysiology of GH. These miRNAs thus provide a novel avenue to identify women at risk and could lead to even more adequate obstetrical care to reduce the risk of complications associated with GH.

Indexed as

Hypertension, Pregnancy-InducedMicroRNAsPregnancy Trimester, FirstAdultBiomarkersFemaleHumansPredictive Value of TestsPregnancyProspective StudiesBiomarkersMicroRNAsMIRN208 microRNA, humanMIRN26 microRNA, humanHuman diseasesMicroRNA (miRNA)Non-coding RNAsNon-invasive biomarkersPregnancy-induced hypertensionRibo-hormones

Identifiers

PMID40057749
PMCPMC11889763

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.