Identification of immune-related genes for the diagnosis of ischemic heart failure based on bioinformatics

The role of immune cells in the pathogenesis of ischemic heart failure (IHF) is well-established. However, identifying key genes in patients with IHF remains a challenge. We obtained two IHF datasets from the GEO database (GSE76701 and GSE21610), and identified four potential diagnostic candidate genes for IHF by using bioinformatics and machine learning algorithms, namely RNASE2, MFAP4, CHRDL1, and KCNN3. We constructed nomogram and validated the diagnostic value of these genes on additional GEO datasets (GSE57338). The results showed that these four genes had high diagnostic value (area under the curve value of 0.961). Furthermore, our immune infiltration analysis revealed the presence of three dysregulated immune cells in IHF, namely macrophages M2, monocytes, and T cells gamma delta. We also explored the potential molecular mechanisms of IHF. These findings provide new insights into the pathogenesis, diagnosis, and treatment of IHF.