通过生物信息学分析鉴定细胞外囊泡中的微小RNA作为小儿癫痫和耐药性癫痫的潜在诊断标志物。

Identification of miRNAs in extracellular vesicles as potential diagnostic markers for pediatric epilepsy and drug-resistant epilepsy via bioinformatics analysis.

作者信息

Ruan Yucai, Deng Xuhui, Liu Jun, Xiao Xiaobing, Yang Zhi

机构信息

Department of Pediatrics, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, China.

Department of Neurology, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, China.

出版信息

Front Pediatr. 2023 Jul 3;11:1199780. doi: 10.3389/fped.2023.1199780. eCollection 2023.

DOI:10.3389/fped.2023.1199780

PMID:37469680

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10352456/

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.

摘要

背景

小儿癫痫（PE）是一种常见的神经系统疾病。然而，关于小儿癫痫和耐药性癫痫（DRE）的临床诊断与治疗仍存在许多未解决的挑战。我们的研究旨在通过仔细研究差异微小RNA（miRNA）表达谱，确定癫痫和耐药性癫痫患儿潜在的miRNA生物标志物。

方法

在本研究中，获取了正常对照组、药物有效癫痫（DEE）患儿和DRE患儿血浆细胞外囊泡（EV）中的miRNA表达谱。此外，使用差异分析、转录因子（TF）富集分析、基因本体（GO）分析和京都基因与基因组百科全书（KEGG）富集分析以及靶基因预测，以鉴定特异性表达的miRNA及其潜在作用机制。使用机器学习算法确定DRE的潜在诊断标志物，并通过受试者工作特征曲线（ROC）评估其诊断效率。

结果

hsa-miR-1307-3p、hsa-miR-196a-5p、hsa-miR-199a-3p和hsa-miR-21-5p被确定为PE的诊断标志物，曲线下面积（AUC）值分别为0.780、0.840、0.832和0.816。此外，纳入这四种miRNA的逻辑回归模型的AUC值为0.940，其靶基因富集分析表明，这些miRNA主要富集于PI3K-Akt、MAPK信号通路和细胞周期。此外，hsa-miR-99a-5p、hsa-miR-532-5p、hsa-miR-181d-5p和hsa-miR-181a-5p在区分DRE患儿和DEE患儿方面表现良好，AUC值分别为0.737（0.534 - 0.940）、0.737（0.523 - 0.952）、0.788（0.592 - 0.985）和0.788（0.603 - 0.974）。