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Background Dilated cardiomyopathy (DCM) is a prevalent condition with diverse etiologies, including viral infection, autoimmune response, and genetic factors. Despite the crucial role of energy metabolism in cardiac function, therapeutic targets for key genes in DCM’s energy metabolism remain scarce. Methods Our study employed the GSE79962 and GSE42955 datasets from the Gene Expression Omnibus (GEO) database for myocardial tissue sample collection and target gene identification via differential gene expression screening. Using various R packages, GSEA software, and the STRING database, we conducted data analysis, gene set enrichment, and protein-protein interaction predictions. The least absolute shrinkage and selection operator (LASSO) and Support Vector Machine (SVM) algorithms aided in feature gene selection, while the predictive model’s efficiency was evaluated via the receiver operating characteristic (ROC) curve analysis. We used the non-negative matrix factorization (NMF) method for molecular typing and the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm for predicting immune cell infiltration. Results The DLAT and LDHA genes may regulate the immune microenvironment of DCM by influencing activated dendritic cells, activated mast cells, and M0 macrophages, respectively. The BPGM, DLAT, PGM2, ADH1A, ADH1C, LDHA , and PFKM genes may regulate m6A methylation in DCM by affecting the ZC3H13, ALKBH5, RBMX, HNRNPC, METTL3 , and YTHDC1 genes. Further regulatory mechanism analysis suggested that PFKM, DLAT, PKLR, PGM2, LDHA, BPGM, ADH1A , and ADH1C could be involved in the development of cardiomyopathy by regulating the Toll-like receptor signaling pathway. Conclusions PFKM, DLAT, PKLR, PGM2, LDHA, BPGM, ADH1A , and ADH1C may serve as potential targets for guiding the diagnosis, treatment, and follow-up of DCM.

ABSTRACT. Previous research has focused on revealing the functions of each individual gene and/or pathway in idiopathic dilated cardiomyopathy (DCM) or ischemic cardiomyopathy (IC). However, the common or specific pathways of the initiation and processes of DCM and IC are still unclear. Here, we attempted to uncover the critical genes and potential molecular networks that play important roles in DCM and IC progression commonly or specifically. The transcriptional profiles from normal and DCM or IC patient samples were analyzed and compared using bioinformatic methods. Initially, the normal and DCM or IC sample data were processed and the most notable differentially expressed genes (DEGs) from DCM or IC were identified. By comparing the DEGs from DCM with those from IC, the DCM-and IC-specific DEGs were identified. The gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated the significance of multiple biological processes as well as signaling pathways that affect heart function and DCM or IC progression. Protein-protein interaction network analysis identified the relationships between different genes, and some important genes such as MYC and FN1 were found to be hubs, which master each individual module of DCM-specific and ICspecific DEGs, respectively. We discovered commonalities and differences of gene expression profiles and molecular pathways between different cardiomyopathies. The gene discovery and molecular signature analysis in this study could offer insights into disease mechanisms and also identify markers useful for diagnostic, prognostic, and therapeutic purposes.