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pmid:35346191

Integrative analyses of biomarkers and pathways for heart failure.

Shaowei Fan · Yuanhui Hu

BMC medical genomics · 2022 doi:10.1186/s12920-022-01221-z

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:35346191
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science-record
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sha256:a5ad14dd98621f733191f96f79e8648a6dca7f0b5428fa89c5424686479d7e5b
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
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2026-11-01T18:14:08Z
updated_at
2026-11-01T22:48:44Z
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paper object · 10 fields
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title
Integrative analyses of biomarkers and pathways for heart failure.
doi
10.1186/s12920-022-01221-z
pmid
35346191
authors array · 2 items
[0]
Shaowei Fan
[1]
Yuanhui Hu
journal
BMC medical genomics
year
2022
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.
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In this study, we used the limma R package (version 3.6.3; https://www.r-project.org/) [12]. The DEGs between HF samples and healthy samples were determined by the threshold standard of |log2 (FC)|> 1 and p.adj < 0.05.
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sections[5] "Identification of DEGs between HF and healthy samples" paragraph 2
quote
In this study, we used the limma R package (version 3.6.3; https://www.r-project.org/) [12]. The DEGs between HF samples and healthy samples were determined by the threshold standard of |log2 (FC)|> 1 and p.adj < 0.05.
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The datasets analysed during the current study are available in the GEO Database repository, GSE76701 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76701. GSE21610 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610. GSE8331 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8331.
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The datasets analysed during the current study are available in the GEO Database repository, GSE76701 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76701. GSE21610 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610. GSE8331 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8331.
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There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes.
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There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes.
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There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes.
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Gene expression analysis in non-failing and failing myocardium pre and post pulsatile and non-pulsatile VAD support
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The datasets analysed during the current study are available in the GEO Database repository, GSE76701 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76701. GSE21610 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610. GSE8331 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8331.
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In this study, we used the limma R package (version 3.6.3; https://www.r-project.org/) [12]. The DEGs between HF samples and healthy samples were determined by the threshold standard of |log2 (FC)|> 1 and p.adj < 0.05.
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remain to be fully elucidated. METHODS: The microarray data sets of GSE76701, GSE21610 and GSE8331
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key genes and HF. RESULTS: We identified 38 patients with heart failure and 16 normal controls. There
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evidence array · 1 item
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In this study, we used the limma R package (version 3.6.3; https://www.r-project.org/) [12]. The DEGs between HF samples and healthy samples were determined by the threshold standard of |log2 (FC)|> 1 and p.adj < 0.05.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35346191", "kind": "science-record", "revision": 5, "content_hash": "sha256:a5ad14dd98621f733191f96f79e8648a6dca7f0b5428fa89c5424686479d7e5b", "created_at": "2026-11-01T18:14:08Z", "updated_at": "2026-11-01T22:48:44Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative analyses of biomarkers and pathways for heart failure.", "doi": "10.1186/s12920-022-01221-z", "pmid": "35346191", "authors": ["Shaowei Fan", "Yuanhui Hu"], "journal": "BMC medical genomics", "year": 2022, "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.\nMETHODS: 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.\nRESULTS: 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.\nCONCLUSIONS: 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.", "claims": [{"id": "claim-method", "statement": "In this study, we used the limma R package (version 3.6.3; https://www.r-project.org/) [12]. The DEGs between HF samples and healthy samples were determined by the threshold standard of |log2 (FC)|> 1 and p.adj < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35346191", "locator": "sections[5] \"Identification of DEGs between HF and healthy samples\" paragraph 2", "quote": "In this study, we used the limma R package (version 3.6.3; https://www.r-project.org/) [12]. The DEGs between HF samples and healthy samples were determined by the threshold standard of |log2 (FC)|> 1 and p.adj < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analysed during the current study are available in the GEO Database repository, GSE76701 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76701. GSE21610 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610. GSE8331 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8331.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35346191", "locator": "sections[26] \"notes\" paragraph 1", "quote": "The datasets analysed during the current study are available in the GEO Database repository, GSE76701 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76701. GSE21610 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610. GSE8331 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8331."}], "state": "complete"}, {"id": "claim-target-result", "statement": "There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35346191", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35346191"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE21610"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE21610"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35346191", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-022-01221-z", "sha256": "sha256:2628ff85b3e731eca8ac719a20925957ab762e30472c69c6bc1eba4eaf8df185", "bytes": 37836, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-022-01221-z", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8962515", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE21610", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE21610", "version": null, "note": "The datasets analysed during the current study are available in the GEO Database repository, GSE76701 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76701. 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