Predicting diagnostic immune-related gene biomarkers in the development of heart failure after acute myocardial infarction: Bioinformatics based approaches

Objective: Post-myocardial infarction(MI) heart failure (HF) is regarded as a public health concern; however, effective biomarkers for predicting HF are still lacking. This study aimed to identy novel biomarkers for forecasting long-term HFin AMI patients. Methods: : The GSE59867 dataset was downloaded from the Gene Expression Omnibus (GEO) database, and then differentially expressed genes (DEGs) were identified with the criteria of p-value0.5. Protein-protein interaction (PPI) network was constructed by STRING software,and then Molecular Complex Detection (MCODE) plugin and CytoHubba plugin in Cytoscape software were applied to identify potential hub genes. Moreover, immune-related genes (IRGs) were downloaded from ImmPort database. The intersection between hub genes and IRGs was regarded as potential immune-related hub genes. Finally, these genes were further assessed for expression levels and predictive ability of long-term HF. Results: : A total of 200 DEGs were identified between the non-HF and HF groups, including 84 upregulated genes and 116 downregulated genes. Ten hub genes, including IL1B, CD28, CXCL8, IL2RA, KLRC4-KLRK1, CXCR5, CD40LG, FOS, TIMP1, GPR29, were further screened out by STRING, MCODE and CytoHubba. Among them, seven immune-related hub genes were filtered. Finally, we found that four genes were significantly changed between the HF and non-HF patients and all showed a predictive ability of the long-term HF, including CD28, CXCR5, FOS, IL2RA. In addition, functional enrichment analysis showed immune system process was enriched in the process of HF, including lymphocyte proliferation, T cell proliferation, lymphocyte proflieration, and IL-17 signaling pathway. Conclusion: We successfully identified four immune-related hub genes that were significantly changed between the HF and non-HF patients and all showed a predictive ability of the long-term HF, which could provide novel insights for the rationale of the development of HF.