Comprehensive analysis of gene signatures associated with aging in human aortic dissection.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38828294", "kind": "science-record", "revision": 4, "content_hash": "sha256:9013bc96ba5cd9c9b4869eae9d001f37c98ebbe161908b9d39896e0ac6788bb5", "created_at": "2026-11-01T19:20:47Z", "updated_at": "2026-11-01T22:11:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of gene signatures associated with aging in human aortic dissection.", "doi": "10.1016/j.heliyon.2024.e31298", "pmid": "38828294", "authors": ["Jingyi Yan", "Xuerui Tan"], "journal": "Heliyon", "year": 2024, "abstract": "Background: Aortic dissection (AD) is a lethal aortic disease with limited effective therapeutic strategies. Aging increases the risk of AD, yet the underlying mechanisms remain unclear. This study aims to analyze the association of aging-related genes (Args) and AD using bioinformatic analysis. This helps provide novel insights into AD pathogenesis and contributes to developing novel therapeutic strategies.\nMethods: mRNA (GSE52093, GSE153434), miRNA (GSE98770) and single-cell RNA-sequencing (scRNA-seq, GSE213740) datasets of AD were downloaded from GEO database. Args were downloaded from Aging Atlas database. Differentially-expressed Args were determined by intersecting Args and differentially-expressed mRNAs of two mRNA datasets. Cytoscape was used to identify hub genes and construct hub gene regulatory networks related to miRNAs. Seurat and clusterProfiler R package were used for investigating expression patterns of hub genes at single-cell level, and functional analysis, respectively. To validate the cellular expression pattern of hub genes, the same analysis was applied to our own scRNA-seq data. Drugs targeting hub Args were determined using the DGIdb database.\nResults: HGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD. miR-221-3p was predicted to interact with ESR1. A decreased ESR1 expression in smooth muscle cell subpopulation 4 (SMC4) was observed in AD versus normal aortic tissues, which was validated by sequencing 197,605 aortic cells from 13 AD patients. Additionally, upregulated genes of SMC4 in AD tissues were enriched in the \"cellular senescence\" pathway. These data indicated that decreased ESR1 might promote SMC4 aging during AD formation. Eleven existing drugs targeting hub genes were identified, including ruxolitinib and filgrastim, which are associated with AD.\nConclusions: By sequencing transcriptomic data, this study revealed aging-related hub genes and regulatory network involved in AD formation. Additionally, this study proposed a noteworthy hypothesis that downregulated ESR1 may exacerbate AD by promoting SMC aging, which requires further investigation.", "claims": [{"id": "claim-method", "statement": "Differentially-expressed mRNAs (DEMs) were identified via the online tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/). The cutoff value for DEMs in the GSE52093 dataset was set to an adjusted P < 0.05 and |logFC|≥1, while an adjusted P < 0.05 and |logFC|≥1 were the criteria for DEMs in the GSE153434 dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38828294", "locator": "sections[4] \"Identification of differentially-expressed aging-related genes in AD\" paragraph 2", "quote": "Differentially-expressed mRNAs (DEMs) were identified via the online tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/). The cutoff value for DEMs in the GSE52093 dataset was set to an adjusted P < 0.05 and |logFC|≥1, while an adjusted P < 0.05 and |logFC|≥1 were the criteria for DEMs in the GSE153434 dataset."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The single-cell RNA sequencing data of 13 AD patients is available from the corresponding author upon reasonable request, and the rest transcriptomic data of AD analyzed in this study are available from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38828294", "locator": "sections[27] \"Data availability statement\" paragraph 2", "quote": "The single-cell RNA sequencing data of 13 AD patients is available from the corresponding author upon reasonable request, and the rest transcriptomic data of AD analyzed in this study are available from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "HGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38828294", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "HGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "HGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD.", "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:38828294"], "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. 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Conclusions: By sequencing transcriptomic data, this study revealed aging-related hub", "(PPI) construction. Analysis of single-cell RNA-sequencing data of AD The quality criteria for online s", "es using the 10 × Genomics Single Cell 3ʹ v3 RNA-seq kit. The libraries were finally sequenced on"], "order_basis": "paper_text_order:529", "id": "assay:1"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["A (GSE98770) and single-cell RNA-sequencing (scRNA-seq, GSE213740) datasets of AD were downloaded f", "es, the same analysis was applied to our own scRNA-seq data. Drugs targeting hub Args were determin", "g data of AD The quality criteria for online scRNA-seq data are: Cells with UMIs≤500, nGene≤250 or", "nline single-cell data, we also analyzed our scRNA-seq data from 13 patients with AD undergoing aor"], "order_basis": "paper_text_order:545", "id": "assay:2"}, {"role": "data_generation", "definition_id": "clinical_cohort", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["we also analyzed our scRNA-seq data from 13 patients with AD undergoing aortic replacement surgery. 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