Insight into the mechanism of DNA methylation and miRNA-mRNA regulatory network in ischemic stroke

Ming-Xi Zhu; Tian-Yang Zhao; Yan Li; Ming-Xi Zhu; Tian-Yang Zhao; Yan Li

doi:10.3934/mbe.2023450

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 6: 10264-10283. doi: 10.3934/mbe.2023450

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Insight into the mechanism of DNA methylation and miRNA-mRNA regulatory network in ischemic stroke

1.
Department of Anatomy, School of Basic Medicine and Life Science, Hainan Medical University, 3 College Road, Hainan 571199, China
2.
Department of Anesthesia, The 4th Affiliated Hospital of Harbin Medical University, 37 Yiyuan Street, Harbin 150001, China

† The authors contributed equally to this work.
Academic Editor: Binh P. Nguyen

Received: 12 January 2023 Revised: 01 March 2023 Accepted: 06 March 2023 Published: 31 March 2023

Background
Epigenetic changes, such as DNA methylation and miRNA-target gene mechanisms, have recently emerged as key provokers in Ischemic stroke (IS) onset. However, cellular and molecular events harboring these epigenetic alterations are poorly understood. Therefore, the present study aimed to explore the potential biomarkers and therapeutic targets for IS.
Methods
miRNAs, mRNAs and DNA methylation datasets of IS were derived from the GEO database and normalized by PCA sample analysis. Differentially expressed genes (DEGs) were identified, and GO and KEGG enrichment analyses were performed. The overlapped genes were utilized to construct a protein-protein interaction network (PPI). Meanwhile, differentially expressed mRNAs and miRNAs interaction pairs were obtained from the miRDB, TargetScan, miRanda, miRMap and miTarBase databases. We constructed differential miRNA-target gene regulatory networks based on mRNA-miRNA interactions.
Results
A total of 27 up-regulated and 15 down-regulated differential miRNAs were identified. Dataset analysis identified 1053 and 132 up-regulated and 1294 and 9068 down-regulated differentially expressed genes in the GSE16561 and GSE140275 datasets, respectively. Moreover, 9301 hypermethylated and 3356 hypomethylated differentially methylated sites were also identified. Moreover, DEGs were enriched in terms related to translation, peptide biosynthesis, gene expression, autophagy, Th1 and Th2 cell differentiation, primary immunodeficiency, oxidative phosphorylation and T cell receptor signaling pathway. MRPS9, MRPL22, MRPL32 and RPS15 were identified as hub genes. Finally, a differential miRNA-target gene regulatory network was constructed.
Conclusions
RPS15, along with hsa-miR-363-3p and hsa-miR-320e have been identified in the differential DNA methylation protein interaction network and miRNA-target gene regulatory network, respectively. These findings strongly posit the differentially expressed miRNAs as potential biomarkers to improve ischemic stroke diagnosis and prognosis.
- ischemic stroke,
- DNA methylation,
- miRNA-target,
- regulatory network,
- PPI
Citation: Ming-Xi Zhu, Tian-Yang Zhao, Yan Li. Insight into the mechanism of DNA methylation and miRNA-mRNA regulatory network in ischemic stroke[J]. Mathematical Biosciences and Engineering, 2023, 20(6): 10264-10283. doi: 10.3934/mbe.2023450

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Abstract

Background

Epigenetic changes, such as DNA methylation and miRNA-target gene mechanisms, have recently emerged as key provokers in Ischemic stroke (IS) onset. However, cellular and molecular events harboring these epigenetic alterations are poorly understood. Therefore, the present study aimed to explore the potential biomarkers and therapeutic targets for IS.

Methods

miRNAs, mRNAs and DNA methylation datasets of IS were derived from the GEO database and normalized by PCA sample analysis. Differentially expressed genes (DEGs) were identified, and GO and KEGG enrichment analyses were performed. The overlapped genes were utilized to construct a protein-protein interaction network (PPI). Meanwhile, differentially expressed mRNAs and miRNAs interaction pairs were obtained from the miRDB, TargetScan, miRanda, miRMap and miTarBase databases. We constructed differential miRNA-target gene regulatory networks based on mRNA-miRNA interactions.

Results

A total of 27 up-regulated and 15 down-regulated differential miRNAs were identified. Dataset analysis identified 1053 and 132 up-regulated and 1294 and 9068 down-regulated differentially expressed genes in the GSE16561 and GSE140275 datasets, respectively. Moreover, 9301 hypermethylated and 3356 hypomethylated differentially methylated sites were also identified. Moreover, DEGs were enriched in terms related to translation, peptide biosynthesis, gene expression, autophagy, Th1 and Th2 cell differentiation, primary immunodeficiency, oxidative phosphorylation and T cell receptor signaling pathway. MRPS9, MRPL22, MRPL32 and RPS15 were identified as hub genes. Finally, a differential miRNA-target gene regulatory network was constructed.

Conclusions

RPS15, along with hsa-miR-363-3p and hsa-miR-320e have been identified in the differential DNA methylation protein interaction network and miRNA-target gene regulatory network, respectively. These findings strongly posit the differentially expressed miRNAs as potential biomarkers to improve ischemic stroke diagnosis and prognosis.

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