Combined analysis of single-cell transcriptomics and clinical data for the prognosis of di-lated cardiomyopathy
Objective This study aimed to delve into the molecular mechanisms underlying dilated cardiomyopathy(DCM)by analyzing multiple transcriptomic and single-cell datasets,and to identify potential therapeutic targets.Method(1)Data acquisition and preprocessing:Multiple transcriptomic and single-cell datasets were obtained from the GEO database,and batch effects were removed using the SVA package.(2)Differential gene analysis:PCA and differential analysis were performed to identify key genes associated with DCM.(3)Functional enrichment analysis:GO and KEGG enrichment analy-ses were conducted to explore the biological functions of these genes.(4)Key gene screening:Consensus clustering,LASSO,and random forest algorithms were employed to screen for key genes from the differential genes.(5)Causal relationship analysis:Mendelian randomization analysis was performed to verify the causal relationship between key genes and DCM.(6)Cell type analysis:Single-cell data analysis was used to determine the expression of key genes in different cell types.Result(1)A total of 788 key genes associated with DCM were identified.(2)GO and KEGG analyses revealed that these genes played important roles in multiple biological pathways.(3)Three key genes,FGFR3,RTKN2,and SLC9A3R1,were screened out.(4)Mendelian randomization analysis confirmed the causal relationship between SLC9A3R1 and DCM.(5)Single-cell data analysis showed that SLC9A3R1 was highly expressed in cardiomyocytes.Conclusion Through multi-omics analysis,this study has deeply explored the molecular mechanisms of DCM.SLC9A3R1,as a newly discovered key gene,may play a crucial role in the pathogenesis of DCM and holds promise as a novel therapeutic target.These findings provide new insights and directions for the diagnosis and treatment of DCM.