AUTHOR=Awoyemi Toluwalase , Zhang Wei , Rahbar Maryam , Cribbs Adam , Logenthiran Prasanna , Jiang Shuhan , Collett Gavin , Cerdeira Ana Sofia , Vatish Manu 

TITLE=A cross-sectional analysis of syncytiotrophoblast membrane extracellular vesicles–derived transcriptomic biomarkers in early-onset preeclampsia

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1291642

DOI=10.3389/fcvm.2023.1291642

ISSN=2297-055X

ABSTRACT=<sec><title>Background</title><p>Preeclampsia (PE) is a pregnancy-specific hypertensive disorder affecting 2%–8% of pregnancies worldwide. Biomarker(s) for the disorder exists, but while these have excellent negative predictive value, their positive predictive value is poor. Extracellular vesicles released by the placenta into the maternal circulation, syncytiotrophoblast membrane extracellular vesicles (STB-EVs), have been identified as being involved in PE with the potential to act as liquid biopsies.</p></sec><sec><title>Objective</title><p>The objective of this study was to identify the difference in the transcriptome of placenta and STB-EVs between preeclampsia and normal pregnancy (NP) and mechanistic pathways.</p></sec><sec><title>Methods/study design</title><p>We performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (<italic>n</italic> = 6) and NP (<italic>n</italic> = 6), followed by bioinformatic analysis to identify targets that could be used in the future for EV-based diagnostic tests for preeclampsia. Some of the identified biomarkers were validated with real-time polymerase chain reactions.</p></sec><sec><title>Results</title><p>Our analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of <italic>FLNB</italic>, <italic>COL17A1</italic>, <italic>SLC45A4</italic>, <italic>LEP</italic>, <italic>HTRA4</italic>, <italic>PAPP-A2</italic>, <italic>EBI3</italic>, <italic>HSD17B1</italic>, <italic>FSTL3</italic>, <italic>INHBA</italic>, <italic>SIGLEC6</italic>, and <italic>CGB3</italic>. Our analysis also identified interesting mechanistic processes via an <italic>in silico</italic> prediction of STB-EV-based mechanistic pathways.</p></sec><sec><title>Conclusions</title><p>In this study, using comprehensive profiling of differentially expressed/carried genes of three linked sample subtypes in PE, we identified potential biomarkers and mechanistic gene pathways that may be important in the pathophysiology of PE and could be further explored in future studies.</p></sec>