ArticleFrontiers in pediatrics2023
Identification of miRNAs in extracellular vesicles as potential diagnostic markers for pediatric epilepsy and drug-resistant epilepsy via bioinformatics analysis.
Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- The Role of MicroRNAs in the Pathogenesis and as Biomarkers for Pediatric Epilepsy: A Systematic Review.Molecular diagnosis & therapy · 2025Pooled it
- Status Epilepticus Alters the Function of Brain-Derived Extracellular Vesicles.Journal of extracellular vesicles · 2026Article
- Comprehensive High-Depth Proteomic Analysis of Plasma Extracellular Vesicle-Containing Preparations in CDKL5 Deficiency Disorder.Biomedicines · 2026Article
- Exosomal microRNA signatures in youth at clinical high risk for bipolar disorder.Frontiers in psychiatry · 2025Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Pediatric epilepsy (PE) is a common neurological disease. However, many challenges regarding the clinical diagnosis and treatment of PE and drug-resistant epilepsy (DRE) remain unsettled. Our study aimed to identify potential miRNA biomarkers in children with epilepsy and drug-resistant epilepsy by scrutinizing differential miRNA expression profiles. Methods: In this study, miRNA expression profiles in plasma extracellular vesicles (EV) of normal controls, children with drug-effective epilepsy (DEE), and children with DRE were obtained. In addition, differential analysis, transcription factor (TF) enrichment analysis, Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and target gene prediction were used to identify specifically expressed miRNAs and their potential mechanisms of action. Potential diagnostic markers for DRE were identified using machine learning algorithms, and their diagnostic efficiency was assessed by the receiver operating characteristic curve (ROC). Results: The hsa-miR-1307-3p, hsa-miR-196a-5p, hsa-miR-199a-3p, and hsa-miR-21-5p were identified as diagnostic markers for PE, with values of area under curve (AUC) 0.780, 0.840, 0.832, and 0.816, respectively. In addition, the logistic regression model incorporating these four miRNAs had an AUC value of 0.940, and its target gene enrichment analysis highlighted that these miRNAs were primarily enriched in the PI3K-Akt, MAPK signaling pathways, and cell cycle. Furthermore, hsa-miR-99a-5p, hsa-miR-532-5p, hsa-miR-181d-5p, and hsa-miR-181a-5p showed good performance in differentiating children with DRE from those with DEE, with AUC values of 0.737 (0.534-0.940), 0.737 (0.523-0.952), 0.788 (0.592-0.985), and 0.788 (0.603-0.974), respectively. Conclusion: This study characterized the expression profile of miRNAs in plasma EVs of children with epilepsy and identified miRNAs that can be used for the diagnosis of DRE.
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