Identification and Validation of a Dysregulated miRNA-Associated mRNA Network in Temporal Lobe Epilepsy

• Published in: BioMed research international Vol. 2021; pp. 4118216 - 12
• Main Authors: Li, Xing, Han, Yunli, Li, Dejun, Yuan, Hai, Huang, Shiqin, Chen, Xiaolan, Qin, Yuanhan
• Format: Journal Article
• Language: English
• Published: United States Hindawi 2021; Hindawi Limited
• Subjects: Annotations; Bioinformatics; Biomarkers; China; Computational Biology - methods; Convulsions & seizures; Data Mining - methods; Datasets; Encyclopedias; Ephrin-A5 - genetics; Epilepsy; Epilepsy, Temporal Lobe - genetics; Epilepsy, Temporal Lobe - metabolism; Gene expression; Gene Expression - genetics; Gene Expression Profiling - methods; Gene Expression Regulation - genetics; Gene Expression Regulation, Neoplastic - genetics; Gene Ontology; Gene Regulatory Networks - genetics; Genes; Genetic engineering; Genomes; Humans; MicroRNAs; MicroRNAs - genetics; miRNA; Molecular Sequence Annotation; Network analysis; Neurotransmitters; Pathogenesis; Patients; Polymerase chain reaction; Protein interaction; Protein Interaction Maps - genetics; Protein Kinase C beta - genetics; Proteins; Regulatory sequences; Reverse transcription; RNA, Messenger - genetics; Software; Temporal lobe; Transcriptome - genetics; China
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2021/4118216

Objectives. This study is aimed at exploring the relationships between miRNAs and mRNAs and to characterize their biological functions in temporal lobe epilepsy (TLE). Methods. Novel clinical significant miRNAs and target genes and their potential underlying mechanisms have been discovered and explored by mining miRNAs and mRNA expression data of TLE patients using various bioinformatics methods. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the bioinformatic analysis results. Results. A total of 6 dysregulated miRNAs and 442 differentially expressed genes (DEGs) related to TLE were obtained from GEO database (GSE114701 and GSE127871 datasets). A protein-protein interaction (PPI) network containing the 442 DEGs was established. mRNA response elements from the 6 dysregulated miRNAs were predicted using the miRDB and TargetScan bioinformatic tools. By merging the identified targets of the dysregulated miRNAs and the 247 downregulated DEGs, a miRNA-mRNA network was constructed revealing the interaction of miR-484 with eight mRNAs (ABLIM2, CEP170B, CTD-3193O13.9, EFNA5, GAP43, PRKCB, FXYD7, and NCAN). A weighted correlation network analysis (WGCNA) based on the eight genes was established and demonstrated that these mRNAs, except FXYD7 and NCAN, were hub genes in the network. Gene Oncology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that the six hub genes were mainly involved in cellular-related biological functions and the neurotransmitter synapse pathway. The differences in expression levels of the miR-484 and the three hub genes (CTD-3193O13.9, EFNA5, and PRKCB) observed experimentally in TLE patients compared to those of healthy controls were consistent with the WGCNA prediction. Conclusion. Our study suggests that understanding the miRNA-mRNA interactions will provide insights into the epilepsy pathogenesis. In addition, our results indicate that miR-484 may be a promising novel biomarker for TLE.