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Integrative analyses of biomarkers and pathways for heart failure
1Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Insights
Researchers identified 315 differentially expressed genes in heart failure (HF) patients, revealing potential molecular mechanisms and new therapeutic targets. Key genes like BBS9 and NPPA were highlighted, offering hope for improved HF diagnosis and treatment.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Heart failure (HF) poses a significant global health and economic burden.
- Despite progress, the underlying molecular mechanisms of HF remain incompletely understood.
Purpose of the Study:
- To identify differentially expressed genes (DEGs) in heart failure.
- To elucidate the molecular mechanisms and potential therapeutic targets for HF using bioinformatics analysis.
Main Methods:
- Retrieved and merged microarray data (GSE76701, GSE21610, GSE8331) from the Gene Expression Omnibus (GEO) database.
- Identified DEGs and performed functional enrichment analysis (GO, KEGG, GSEA, DO).
- Constructed a protein-protein interaction (PPI) network and utilized the Comparative Toxicogenomics Database (CTD).
Main Results:
- Identified 315 DEGs in 38 HF patients compared to 16 controls, with 278 upregulated and 37 downregulated.
- Enrichment analysis revealed significant involvement of BMP signaling, extracellular matrix, and related pathways.
- Identified BBS9, CHRD, BMP4, MYH6, NPPA, and CCL5 as central genes in PPI networks.
Conclusions:
- Enriched pathways and GO terms suggest key molecular mechanisms in HF pathogenesis.
- Identified potential novel therapeutic targets including EIF1AY, RPS4Y1, USP9Y, KDM5D, DDX3Y, NPPA, HBB, TSIX, LOC28556, and XIST.
- Findings support the development of advanced prediction, diagnosis, and treatment strategies for heart failure.
Background:
Heart failure (HF) is the most common potential cause of death, causing a huge health and economic burden all over the world. So far, some impressive progress has been made in the study of pathogenesis. However, the underlying molecular mechanisms leading to this disease remain to be fully elucidated.
Methods:
The microarray data sets of GSE76701, GSE21610 and GSE8331 were retrieved from the gene expression comprehensive database (GEO). After merging all microarray data and adjusting batch effects, differentially expressed genes (DEG) were determined. Functional enrichment analysis was performed based on Gene Ontology (GO) resources, Kyoto Encyclopedia of Genes and Genomes (KEGG) resources, gene set enrichment analysis (GSEA), response pathway database and Disease Ontology (DO). Protein protein interaction (PPI) network was constructed using string database. Combined with the above important bioinformatics information, the potential key genes were selected. The comparative toxicological genomics database (CTD) is used to explore the interaction between potential key genes and HF.
Results:
We identified 38 patients with heart failure and 16 normal controls. There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes. Pathway enrichment analysis showed that most DEGs were significantly enriched in BMP signal pathway, transmembrane receptor protein serine/threonine kinase signal pathway, extracellular matrix, basement membrane, glycosaminoglycan binding, sulfur compound binding and so on. Similarly, GSEA enrichment analysis showed that DEGs were mainly enriched in extracellular matrix and extracellular matrix related proteins. BBS9, CHRD, BMP4, MYH6, NPPA and CCL5 are central genes in PPI networks and modules.
Conclusions:
The enrichment pathway of DEGs and GO may reveal the molecular mechanism of HF. Among them, target genes EIF1AY, RPS4Y1, USP9Y, KDM5D, DDX3Y, NPPA, HBB, TSIX, LOC28556 and XIST are expected to become new targets for heart failure. Our findings provide potential biomarkers or therapeutic targets for the further study of heart failure and contribute to the development of advanced prediction, diagnosis and treatment strategies.
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