System analysis based on the necroptosis-related genes in heart failure

Abstract

Abstract Background: Heart failure(HF) is an emerging epidemic clinical syndrome that remains a leading cause of global morbidity and mortality. This study aimed to determine necroptosis' role in HF using bioinformatics analyses. Methods: A total of 3 datasets, including myocardial tissues samples from 225 HF patients and 26 normal people, were acquired from the Gene Expression Omnibus (GEO). Necroptosis-related differentially expressed genes (NRDEGs) in HF were determined. A prediction model based on three NRDEGs were constructed to assess the risk of HF. Then, consensus clustering, protein-protein interactions (PPI), and identifying the top 10 hub genes were performed. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were carried out. Investigations were conducted into immune infiltration. Furthermore, the eight NRDEGs’ mRNA expression level was validated in blood samples by quantitative real time-PCR (RT-qPCR). Results: A total of eight NRDEGs, namely FLOT1, DAPK1, KLHDC10, FLOT2, FAS, UCHL1, TNFAIP3, HSPA5, were excavated and further verified by RT-qPCR in blood samples. The expression levels of TNFAIP3 and HSPA5 were lower in HF, consistent with bioinformatics analysis. The correlation analysis revealed the regulatory network between 51 NRGs. The HF risk prediction model constructed of FLOT2, FAS and FLOT1 has relatively good accuracy and reliability. The 10-hub-genes associated with necroptosis might be significantly related to HF. Among10-hub-genes, STIP1, TGFBR2, and HSPD1 might be potential markers to indicate the early stage or progression of HF. The GSEA clarified nine relevant enrichment pathways. Conclusion: Our research supplies new information and views for investigating the underlying necroptosis-related mechanism and possible treatments of HF.