Weighted Gene Co-Expression Network Analysis Reveals Key Genes and Potential Drugs in Abdominal Aortic Aneurysm.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34068179", "kind": "science-record", "revision": 6, "content_hash": "sha256:b8bc42c1f5025e5cb2c4d06e30477dbe92c9955f5ae1a830116289d6ed6a2e02", "created_at": "2026-11-01T15:41:37Z", "updated_at": "2026-11-01T21:25:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Weighted Gene Co-Expression Network Analysis Reveals Key Genes and Potential Drugs in Abdominal Aortic Aneurysm.", "doi": "10.3390/biomedicines9050546", "pmid": "34068179", "authors": ["Ke-Jia Kan", "Feng Guo", "Lei Zhu", "Prama Pallavi", "Martin Sigl", "Michael Keese"], "journal": "Biomedicines", "year": 2021, "abstract": "Abdominal aortic aneurysm (AAA) is a prevalent aortic disease that causes high mortality due to asymptomatic gradual expansion and sudden rupture. The underlying molecular mechanisms and effective pharmaceutical therapy for preventing AAA progression have not been fully identified. In this study, we identified the key modules and hub genes involved in AAA growth from the GSE17901 dataset in the Gene Expression Omnibus (GEO) database through the weighted gene co-expression network analysis (WGCNA). Key genes were further selected and validated in the mouse dataset (GSE12591) and human datasets (GSE7084, GSE47472, and GSE57691). Finally, we predicted drug candidates targeting key genes using the Drug-Gene Interaction database. Overall, we identified key modules enriched in the mitotic cell cycle, GTPase activity, and several metabolic processes. Seven key genes (CCR5, ADCY5, ADCY3, ACACB, LPIN1, ACSL1, UCP3) related to AAA progression were identified. A total of 35 drugs/compounds targeting the key genes were predicted, which may have the potential to prevent AAA progression.", "claims": [{"id": "claim-method", "statement": "To define the statistical significance of differences between the two groups, we performed analysis using a non-parametric test or t-test based on data distribution characteristics.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34068179", "locator": "sections[10] \"2.8. 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