Integrative analyses of biomarkers and pathways for heart failure
Abstract 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 t...
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| Format: | Article |
| Language: | English |
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BMC
2022-03-01
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| Series: | BMC Medical Genomics |
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| Online Access: | https://doi.org/10.1186/s12920-022-01221-z |
| _version_ | 1811272044583583744 |
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| author | Shaowei Fan Yuanhui Hu |
| author_facet | Shaowei Fan Yuanhui Hu |
| author_sort | Shaowei Fan |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-12T22:33:18Z |
| format | Article |
| id | doaj.art-b9b68c7372864d34a77b67e23fa4b997 |
| institution | Directory Open Access Journal |
| issn | 1755-8794 |
| language | English |
| last_indexed | 2024-04-12T22:33:18Z |
| publishDate | 2022-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Genomics |
| spelling | doaj.art-b9b68c7372864d34a77b67e23fa4b9972022-12-22T03:13:56ZengBMCBMC Medical Genomics1755-87942022-03-0115111810.1186/s12920-022-01221-zIntegrative analyses of biomarkers and pathways for heart failureShaowei Fan0Yuanhui Hu1Guang’anmen Hospital, China Academy of Chinese Medical SciencesGuang’anmen Hospital, China Academy of Chinese Medical SciencesAbstract 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.https://doi.org/10.1186/s12920-022-01221-zPotential key genesHeart failureBioinformaticsGene expression synthesisBiomarkers |
| spellingShingle | Shaowei Fan Yuanhui Hu Integrative analyses of biomarkers and pathways for heart failure BMC Medical Genomics Potential key genes Heart failure Bioinformatics Gene expression synthesis Biomarkers |
| title | Integrative analyses of biomarkers and pathways for heart failure |
| title_full | Integrative analyses of biomarkers and pathways for heart failure |
| title_fullStr | Integrative analyses of biomarkers and pathways for heart failure |
| title_full_unstemmed | Integrative analyses of biomarkers and pathways for heart failure |
| title_short | Integrative analyses of biomarkers and pathways for heart failure |
| title_sort | integrative analyses of biomarkers and pathways for heart failure |
| topic | Potential key genes Heart failure Bioinformatics Gene expression synthesis Biomarkers |
| url | https://doi.org/10.1186/s12920-022-01221-z |
| work_keys_str_mv | AT shaoweifan integrativeanalysesofbiomarkersandpathwaysforheartfailure AT yuanhuihu integrativeanalysesofbiomarkersandpathwaysforheartfailure |