Molecular characterization of m6A RNA methylation regulators with features of immune dysregulation in IgA nephropathy.

ABSTRACT

The role of RNA N6-methyladenosine (m6A) modification in immunity is being elucidated. This study aimed to explore the potential association between m6A regulators and the immune microenvironment in IgA nephropathy (IgAN). The expression profiles of 24 m6A regulators in 107 IgAN patients were obtained from the Gene Expression Omnibus (GEO) database. The least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis were utilized to construct a model for distinguishing IgAN from control samples. Based on the expression levels of m6A regulators, unsupervised clustering was used to identify m6A-induced molecular clusters in IgAN. Gene set enrichment analysis (GSEA) and immunocyte infiltration among different clusters were examined. The gene modules with the highest correlation for each of the three clusters were identified by weighted gene co-expression network analysis (WGCNA). A model containing 10 m6A regulators was developed using LASSO and logistic regression analyses. Three molecular clusters were determined using consensus clustering of 24 m6A regulators. A decrease in the expression level of YTHDF2 in IgAN samples was significantly negatively correlated with an increase in resting natural killer (NK) cell infiltration and was positively correlated with the abundance of M2 macrophage infiltration. The risk scores calculated by the nomogram were significantly higher for cluster-3, and the expression levels of m6A regulators in this cluster were generally low. Immunocyte infiltration and pathway enrichment results for cluster-3 differed significantly from those for the other two clusters. Finally, the expression of YTHDF2 was significantly decreased in IgAN based on immunohistochemical staining. This study demonstrated that m6A methylation regulators play a significant role in the regulation of the immune microenvironment in IgAN. Based on m6A regulator expression patterns, IgAN can be classified into multiple subtypes, which might provide additional insights into novel therapeutic methods for IgAN.