Integration of bioinformatics and identification of the role of m6A genes in NAFLD

Abstract

Non-alcoholic fatty liver disease (NAFLD) is prevalent worldwide and seriously affects health. M6A methylation is crucial in its pathogenesis. In this study, a thorough analysis of three gene expression datasets identified nine key differentially expressed genes DEGs associated with m6A methylation in NAFLD that are involved in important biological processes. Subsequently, functional enrichment analysis, weighted gene co-expression network analysis (WGCNA), gene set variation analysis (GSVA) and immune infiltration analysis were conducted to explore the molecular mechanism and gene expression patterns. The LASSO risk model contains a total of 5 m6A-related differentially expressed genes (m6A-RDEGs)(RBM15, IGF2BP2, EIF3B, YTHDC1, WTAP), and the diagnostic model based on these key genes has high accuracy. Among them, YTHDC1 and WTAP are used as prominent biomarkers. In addition, an interaction network between mRNA and miRNA, RNA-binding protein (RBP), transcription factor (TF) and drugs is also constructed. Finally, the animal model of NAFLD was successfully established and validated by RT-qPCR and western blot. This study provides a valuable tool for clinical diagnosis and drives the progress of NAFLD research.