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First-trimester predictive models for adverse pregnancy outcomes-a base for implementation of strategies to prevent cardiovascular disease development

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023698%3A_____%2F24%3AN0000009" target="_blank" >RIV/00023698:_____/24:N0000009 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11120/24:43927533

  • Result on the web

    <a href="https://pubmed.ncbi.nlm.nih.gov/39296937/" target="_blank" >https://pubmed.ncbi.nlm.nih.gov/39296937/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3389/fcell.2024.1461547" target="_blank" >10.3389/fcell.2024.1461547</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    First-trimester predictive models for adverse pregnancy outcomes-a base for implementation of strategies to prevent cardiovascular disease development

  • Original language description

    Introduction This study aimed to establish efficient, cost-effective, and early predictive models for adverse pregnancy outcomes based on the combinations of a minimum number of miRNA biomarkers, whose altered expression was observed in specific pregnancy-related complications and selected maternal clinical characteristics.Methods This retrospective study included singleton pregnancies with gestational hypertension (GH, n = 83), preeclampsia (PE, n = 66), HELLP syndrome (n = 14), fetal growth restriction (FGR, n = 82), small for gestational age (SGA, n = 37), gestational diabetes mellitus (GDM, n = 121), preterm birth in the absence of other complications (n = 106), late miscarriage (n = 34), stillbirth (n = 24), and 80 normal term pregnancies. MiRNA gene expression profiling was performed on the whole peripheral venous blood samples collected between 10 and 13 weeks of gestation using real-time reverse transcription polymerase chain reaction (RT-PCR).Results Most pregnancies with adverse outcomes were identified using the proposed approach (the combinations of selected miRNAs and appropriate maternal clinical characteristics) (GH, 69.88%; PE, 83.33%; HELLP, 92.86%; FGR, 73.17%; SGA, 81.08%; GDM on therapy, 89.47%; and late miscarriage, 84.85%). In the case of stillbirth, no addition of maternal clinical characteristics to the predictive model was necessary because a high detection rate was achieved by a combination of miRNA biomarkers only [91.67% cases at 10.0% false positive rate (FPR)].Conclusion The proposed models based on the combinations of selected cardiovascular disease-associated miRNAs and maternal clinical variables have a high predictive potential for identifying women at increased risk of adverse pregnancy outcomes; this can be incorporated into routine first-trimester screening programs. Preventive programs can be initiated based on these models to lower cardiovascular risk and prevent the development of metabolic/cardiovascular/cerebrovascular diseases because timely implementation of beneficial lifestyle strategies may reverse the dysregulation of miRNAs maintaining and controlling the cardiovascular system.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30214 - Obstetrics and gynaecology

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY

  • ISSN

    2296-634X

  • e-ISSN

    2296-634X

  • Volume of the periodical

    12

  • Issue of the periodical within the volume

    1461547

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    13

  • Pages from-to

  • UT code for WoS article

    001314635800001

  • EID of the result in the Scopus database

    2-s2.0-85204207374