A role of inflammaging in aortic aneurysm: new insights from bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37744379", "kind": "science-record", "revision": 5, "content_hash": "sha256:ec6048b7bdfc74e1098cd8e7026326b848eac5b987065d23849c3c2fcd4d26b3", "created_at": "2026-11-01T19:02:35Z", "updated_at": "2026-11-01T22:52:46Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A role of inflammaging in aortic aneurysm: new insights from bioinformatics analysis.", "doi": "10.3389/fimmu.2023.1260688", "pmid": "37744379", "authors": ["Shilin Wang", "Hao Liu", "Peiwen Yang", "Zhiwen Wang", "Ping Ye", "Jiahong Xia", "Shu Chen"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Introduction: Aortic aneurysms (AA) are prevalent worldwide with a notable absence of drug therapies. Thus, identifying potential drug targets is of utmost importance. AA often presents in the elderly, coupled with consistently raised serum inflammatory markers. Given that ageing and inflammation are pivotal processes linked to the evolution of AA, we have identified key genes involved in the inflammaging process of AA development through various bioinformatics methods, thereby providing potential molecular targets for further investigation.\nMethods: The transcriptome data of AA was procured from the datasets GSE140947, GSE7084, and GSE47472, sourced from the NCBI GEO database, whilst gene data of ageing and inflammation were obtained from the GeneCards Database. To identify key genes, differentially expressed analysis using the \"Limma\" package and WGCNA were implemented. Protein-protein intersection (PPI) analysis and machine learning (ML) algorithms were employed for the screening of potential biomarkers, followed by an assessment of the diagnostic value. Following the acquisition of the hub inflammaging and AA-related differentially expressed genes (IADEGs), the TFs-mRNAs-miRNAs regulatory network was established. The CIBERSORT algorithm was utilized to investigate immune cell infiltration in AA. The correlation of hub IADEGs with infiltrating immunocytes was also evaluated. Lastly, wet laboratory experiments were carried out to confirm the expression of hub IADEGs.\nResults: 342 and 715 AA-related DEGs (ADEGs) recognized from GSE140947 and GSE7084 datasets were procured by intersecting the results of \"Limma\" and WGCNA analyses. After 83 IADEGs were obtained, PPI analysis and ML algorithms pinpointed 7 and 5 hub IADEGs candidates respectively, and 6 of them demonstrated a high diagnostic value. Immune cell infiltration outcomes unveiled immune dysregulation in AA. In the wet laboratory experiments, 3 hub IADEGs, including BLNK, HLA-DRA, and HLA-DQB1, finally exhibited an expression trend in line with the bioinformatics analysis result.\nDiscussion: Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA.", "claims": [{"id": "claim-method", "statement": "To identify key genes, differentially expressed analysis using the “Limma” package and WGCNA were implemented.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37744379", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "To identify key genes, differentially expressed analysis using the “Limma” package and WGCNA were implemented."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original codes used for the analyses presented in the study are publicly available. This data can be found here: https://github.com/wangshilin2000/Source-code-for-figure-2-6-1260688-.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37744379", "locator": "sections[33] \"Data availability statement\" paragraph 2", "quote": "The original codes used for the analyses presented in the study are publicly available. This data can be found here: https://github.com/wangshilin2000/Source-code-for-figure-2-6-1260688-."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37744379", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA.", "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:37744379"], "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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The expression level of genes in qPCR was calculated by Student’s T−test using Gra", "Gs was validated in human aorta tissue using qPCR ( Figure 7A ). In comparison with normal aor", "e. (A) Relative mRNA levels were detected by qPCR. (B) Representative western blot (WB) analys"], "order_basis": "paper_text_order:3186", "id": "assay:1"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["rease. To further validate at protein level, western blotting (WB) and IHC were employed ( Figures 7B, C )", "ls were detected by qPCR. (B) Representative western blot (WB) analysis (left) and quantification (rig"], "order_basis": "paper_text_order:7131", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["protein level in the human aorta tissue. (C) Immunohistochemical staining of 6 hub IADEGs in aorta sections o", "at protein level, western blotting (WB) and IHC were employed ( Figures 7B, C ). The finding"], "order_basis": "paper_text_order:7158", "id": "assay:3"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["To identify key genes, differentially expressed analysis using the “Limma” package and WGCNA were implemented."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}