Identifying cellular senescence associated genes involved in the progression of end-stage renal disease as new biomarkers.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37553608", "kind": "science-record", "revision": 4, "content_hash": "sha256:58c8f848f9cba9019222ba67e3a99fae0fe45d0f528907f9593c12f451ef07c4", "created_at": "2026-11-01T19:02:20Z", "updated_at": "2026-11-01T22:52:28Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identifying cellular senescence associated genes involved in the progression of end-stage renal disease as new biomarkers.", "doi": "10.1186/s12882-023-03285-0", "pmid": "37553608", "authors": ["Yu-Jia Xi", "Qiang Guo", "Ran Zhang", "Guo-Sheng Duan", "Sheng-Xiao Zhang"], "journal": "BMC nephrology", "year": 2023, "abstract": "BACKGROUND: Cellular senescence plays an essential role in the development and progression of end-stage renal disease (ESRD). However, the detailed mechanisms phenomenon remains unclear.\nMETHODS: The mRNA expression profiling dataset GSE37171 was taken from the Gene Expression Omnibus (GEO) database. The cell senescence-associated hub genes were selected by applying protein-protein interaction (PPI), followed by correlation analysis, gene interaction analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. We next explored the relationships of hub genes with miRNAs, TFs, and diseases. The absolute abundance of eight immune cells and two stromal cells were calculated by MCPcount and the correlation of hub genes with these ten cells was analyzed. Lasso was used to selecting for trait genes. ROC curves and DCA decision curves were used to assess the accuracy and predictive power of the trait genes.\nRESULTS: A total of 65 cellular senescence signature genes were identified among patients and controls. The PPI network screened out ten hub genes. GO and KEGG indicated that ten hub genes were associated with ESRD progression. Transcription factor gene interactions and common regulatory networks of miRNAs were also identified in the datasets. The hub genes were significantly correlated with immune cells and stromal cells. Then the lasso model was constructed to screen out the five most relevant signature genes (FOS, FOXO3, SIRT1, TP53, SMARCA4). The area under the ROC curve (AUC) showed that these five characteristic genes have good resolving power for the diagnostic model.\nCONCLUSIONS: Our findings suggested that cellular senescence-associated genes played an important role in the development of ESRD and immune regulation.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) were screened using the “limma” package in the R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37553608", "locator": "sections[4] \"Differential expression analysis\" paragraph 2", "quote": "Differentially expressed genes (DEGs) were screened using the “limma” package in the R package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse37171) without any relevant permissions required to access the information from the database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37553608", "locator": "sections[28] \"notes\" paragraph 1", "quote": "The datasets presented in this study can be found in the GEO database (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse37171) without any relevant permissions required to access the information from the database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "After pre-processing the cohort in the GSE37171 dataset, 3910 DEGs (788 up-regulated and 3122 down-regulated genes) for advanced kidney disease were screened by a critical threshold (adj. p-value < 0.05 and | logFC |> 0.585).", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "After pre-processing the cohort in the GSE37171 dataset, 3910 DEGs (788 up-regulated and 3122 down-regulated genes) for advanced kidney disease were screened by a critical threshold (adj. p-value < 0.05 and | logFC |> 0.585)."}, "evidence": [{"asset": "source:pmid:37553608", "locator": "sections[13] \"Screening of DEGs associated with cellular senescence and GSEA enrichment analysis\" paragraph 2", "quote": "After pre-processing the cohort in the GSE37171 dataset, 3910 DEGs (788 up-regulated and 3122 down-regulated genes) for advanced kidney disease were screened by a critical threshold (adj. p-value < 0.05 and | logFC |> 0.585)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "After pre-processing the cohort in the GSE37171 dataset, 3910 DEGs (788 up-regulated and 3122 down-regulated genes) for advanced kidney disease were screened by a critical threshold (adj. p-value < 0.05 and | logFC |> 0.585).", "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:37553608"], "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:GSE37171"], "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:GSE37171"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37553608", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12882-023-03285-0", "sha256": 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