Deep Learning-Based Medical Data Association Rules to Explore the Connectivity and Regulation Mechanism of miRNA-mRNA Network in Myocarditis

Abstract

Acute, chronic myocarditis as myocardial localized or diffuse inflammation lesions is usually involving cardiac function in patients with severe adverse outcomes such as heart failure, sudden death, and no unified, but its pathogenesis clinical is mainly composed of a number of factors including infection and autoimmune defects, such as physical and chemical factors; therefore, it is of great significance to explore the regulation mechanism of myocarditis-related miRNA network connectivity and temperament for in-depth understanding of the pathogenesis of myocarditis and the direction of targeted therapy. Based on this, this study explored the miRNA network related to the pathogenesis of myocarditis through deep learning medical data association rules and analyzed its specific mechanism. The results showed that 39 upregulated miRNAs, 88 downregulated miRNAs, 109 upregulated differentially expressed miRNAs, and 589 downregulated mRNAs were obtained by data association through GSE126677 and GSE4172 databases. GO enrichment and KRGG enrichment analysis showed that the differentially expressed mRNAs were involved in the regulation of a variety of biological processes, cellular components, and molecular functions. At the same time, the miRNA with differentially expressed miRNAs and their corresponding mRNAs were connected to further clarify the specific molecular mechanism of the pathological changes of myocarditis by constructing miRNA-mRNA network. It provides effective potential molecular targets for subsequent treatment and diagnosis.