Dataset Information

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

ABSTRACT:

Background

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.

Objective

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.

Methods/study design

We performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (n = 6) and NP (n = 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.

Results

Our analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP-A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3. Our analysis also identified interesting mechanistic processes via an in silico prediction of STB-EV-based mechanistic pathways.

Conclusions

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.

SUBMITTER: Awoyemi T

PROVIDER: S-EPMC10720444 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

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

Awoyemi Toluwalase T Zhang Wei W Rahbar Maryam M Cribbs Adam A Logenthiran Prasanna P Jiang Shuhan S Collett Gavin G Cerdeira Ana Sofia AS Vatish Manu M

Frontiers in cardiovascular medicine 20231130

<h4>Background</h4>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.<h4>Ob ...[more]

PMID: 38099221

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Project description:Preeclampsia (PE), defined as new-onset hypertension and multi-organ systemic complication during pregnancy, is the leading cause of maternal and neonatal mortality and morbidity. With extracellular vesicles research progresses, current data refers to the possibility that ferroptosis may play a role in exosomal effects. Evidence has suggested that ferroptosis may contribute to the pathogenesis of preeclampsia by bioinformatics analyses. The purpose of the current study is to identify the potential ferroptosis-related genes in syncytiotrophoblast-derived extracellular vesicles (STB-EVs) of preeclampsia using bioinformatics analyses. Clinical characteristics and gene expression data of all samples were obtained from the NCBI GEO database. The differentially expressed mRNAs (DE-mRNAs) in STB-EVs of preeclampsia were screened and then were intersected with ferroptosis genes. Functional and pathway enrichment analyses of ferroptosis-related DE-mRNAs in STB-EVs were performed. Ferroptosis-related hub genes in STB-EVs were identified by Cytoscape plugin CytoHubba with a Degree algorithm using a protein-protein interaction network built constructed from the STRING database. The predictive performance of ferroptosis-related hub genes was determined by a univariate analysis of receiver operating characteristic (ROC). The miRNA-hub gene regulatory network was constructed using the miRwalk database. A total of 1976 DE-mRNAs in STB-EVs were identified and the most enriched item identified by gene set enrichment analysis was signaling by G Protein-Coupled Receptors (normalized enrichment score = 1.238). These DE-mRNAs obtained 26 ferroptosis-related DE-mRNAs. Ferroptosis-related DE-mRNAs of gene ontology terms and Encyclopedia of Genes and Genomes pathway enrichment analysis were enriched significantly in response to oxidative stress and ferroptosis. Five hub genes (ALB, NOX4, CDKN2A, TXNRD1, and CAV1) were found in the constructed protein-protein interaction network with ferroptosis-related DE-mRNAs and the areas under the ROC curves for ALB, NOX4, CDKN2A, TXNRD1, and CAV1 were 0.938 (CI: 0.815-1.000), 0.833 (CI: 0.612-1.000), 0.875 (CI: 0.704-1.000), 0.958 (CI: 0.862-1.000), and 0.854 (CI: 0.652-1.000) in univariate analysis of ROC. We constructed a regulatory network of miRNA-hub gene and the findings demonstrate that hsa-miR-26b-5p, hsa-miR-192-5p, hsa-miR-124-3p, hsa-miR-492, hsa-miR-34a-5p and hsa-miR-155-5p could regulate most hub genes. In this study, we identified several central genes closely related to ferroptosis in STB-EVs (ALB, NOX4, CDKN2A, TXNRD1, and CAV1) that are potential biomarkers related to ferroptosis in preeclampsia. Our findings will provide evidence for the involvement of ferroptosis in preeclampsia and improve the understanding of ferroptosis-related molecular pathways in the pathogenesis of preeclampsia.

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Dataset Information

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

Background

Objective

Methods/study design

Results

Conclusions

Publications

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

Similar Datasets

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