Comprehensive Analysis of Metabolic Reprogramming-Associated Key Genes and Immune Microenvironment in Heart Failure with Preserved Ejection Fraction
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Background
Heart failure with preserved ejection fraction (HFpEF) represents a profoundly heterogeneous cardiovascular condition; characterized by intricate molecular pathways that have not yet been fully elucidated. This study seeks to uncover metabolic reprogramming-associated key genes (Key Genes) linked to HFpEF, investigate their functional significance and influence on the immune microenvironment, and establish a robust early diagnostic framework.
Methods
We obtained datasets GSE194151 and GSE180065 from the GEO database. In order to counteract batch effects, metabolic reprogramming-related differentially expressed genes (MRRDEGs) were identified by differential expression analysis using the sva R package. Enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomics (KEGG) elucidated the associated biological functions and pathways. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to examine biological differences within subgroups using risk assessment. Single sample gene set enrichment analysis (ssGSEA) was used to measure immune cell infiltration. Protein-protein interaction networks (PPI Networks), mRNA-TF, mRNA-RBP, and mRNA-miRNA interaction networks were used to investigate multilevel regulatory mechanisms. A diagnostic model for HFpEF, constructed using logistic regression, SVM, and LASSO, was validated through ROC analysis and external datasets.
Results
In total, 34 MRRDEGs were identified, significantly enriched in processes like fatty acid metabolism and circadian rhythm regulation. A diagnostic model comprising five Key Genes( Hnrnpd , Hpcal1 , Hadha , Hspd1 , and Naa10 ) showed strong performance, with Hspd1 achieving an Area Under Curve (AUC) > 0.9. The validation using GSE180065 and HFpEF_2020 confirmed the reliability of the model. Immune analysis revealed significant enrichment of Activated CD4 T cells, type 2 T helper cells, and macrophages in the high-risk groups, correlating with specific Key Genes (p < 0.05). GSEA and GSVA linked high-risk groups to TGF-β signaling and fatty acid oxidation. PPI and regulatory network analyses further underscored the functional importance of Key Genes.
Conclusion
Our study systematically identified metabolic reprogramming-related Key Genes and their associations with immune microenvironment changes in HFpEF. These findings reveal the potential mechanisms underlying HFpEF and offer a high-performance diagnostic model, providing novel insights and therapeutic targets for molecular studies and immunotherapy in HFpEF.
