Screening for Regulatory Network of miRNA-Inflammation, Oxidative Stress and Prognosis-Related mRNA in Acute Myocardial Infarction: An in silico and Validation Study

Xunli Yin; Xuebing Wang; Shiai Wang; Youwei Xia; Huihui Chen; Ling Yin; Keqing Hu

doi:10.2147/IJGM.S354359

Screening for Regulatory Network of miRNA-Inflammation, Oxidative Stress and Prognosis-Related mRNA in Acute Myocardial Infarction: An in silico and Validation Study

Int J Gen Med. 2022 Feb 18:15:1715-1731. doi: 10.2147/IJGM.S354359. eCollection 2022.

Authors

Xunli Yin¹, Xuebing Wang¹, Shiai Wang¹, Youwei Xia², Huihui Chen¹, Ling Yin³, Keqing Hu⁴

Affiliations

¹ Department of Cardiovascular Medicine, The Seventh People's Hospital of Jinan, Jinan, 250100, People's Republic of China.
² Department of Critical Care Medicine, The Seventh People's Hospital of Jinan, Jinan, 250100, People's Republic of China.
³ Department of Conduit Room, The Seventh People's Hospital of Jinan, Jinan, 250100, People's Republic of China.
⁴ Cardiovascular Department, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, People's Republic of China.

Abstract

Background: Acute myocardial infarction (AMI), which commonly leads to heart failure, is among the leading causes of mortality worldwide. The aim of this study was to find potential regulatory network for miRNA-inflammation, oxidative stress and prognosis-related mRNA to uncover molecular mechanisms of AMI.

Methods: The expression profiles of miRNA and mRNA in the blood samples from AMI patients were downloaded from the Gene Expression Omnibus (GEO) dataset for differential expression analysis. Weighted gene co-expression network analysis (WGCNA) was used to further identify important mRNAs. The negatively regulatory network construction of miRNA-inflammation, oxidative stress and prognosis-related mRNAs was performed, followed by protein-protein interaction (PPI) and functional analysis of mRNAs.

Results: A total of three pairs of negatively regulatory network of miRNA-inflammation and prognosis-related mRNAs (hsa-miR-636/hsa-miR-491-3p/hsa-miR-188-5p/hsa-miR-188-3p-AQP9, hsa-miR-518a-3p-C5AR1 and hsa-miR-509-3-5p/hsa-miR-127-5p-PLAUR), two pairs of negatively regulatory network of miRNA-oxidative stress and prognosis-related mRNAs (hsa-miR-604-TLR4 and hsa-miR-139-5p-CXCL1) and three pairs of negatively regulatory network of miRNA-inflammation, oxidative stress and prognosis-related mRNA (hsa-miR-634/hsa-miR-591-TLR2, hsa-miR-938-NFKBIA and hsa-miR-520h/hsa-miR-450b-3p-ADM) were identified. In the KEGG analysis, some signaling pathways were identified, such as complement and coagulation cascades, pathogenic Escherichia coli infection, chemokine signaling pathway and cytokine-cytokine receptor interaction and Toll-like receptor signaling pathway.

Conclusion: Identified negatively regulatory network of miRNA-inflammation/oxidative stress and prognosis-related mRNA may be involved in the process of AMI. Those inflammation/oxidative stress and prognosis-related mRNAs may be diagnostic and prognostic biomarkers for AMI.

Keywords: acute myocardial infarction; inflammation; mRNAs; miRNAs; oxidative stress; prognosis.