Identifying miRNA Modules and Related Pathways of Chronic Obstructive Pulmonary Disease Associated Emphysema by Weighted Gene Co-Expression Network Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34815668", "kind": "science-record", "revision": 4, "content_hash": "sha256:e7d95c225020906d5c642f34c913aa7ea70828189f7f850e5b8f9b6768d4afe2", "created_at": "2026-11-01T17:36:31Z", "updated_at": "2026-11-01T22:05:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identifying miRNA Modules and Related Pathways of Chronic Obstructive Pulmonary Disease Associated Emphysema by Weighted Gene Co-Expression Network Analysis.", "doi": "10.2147/COPD.S325300", "pmid": "34815668", "authors": ["Jing An", "Ting Yang", "Jiajia Dong", "Zenglin Liao", "Chun Wan", "Yongchun Shen", "Lei Chen"], "journal": "International journal of chronic obstructive pulmonary disease", "year": 2021, "abstract": "BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous chronic inflammatory disease characterized by progressive airflow limitation that causes high morbidity and mortality. MicroRNA, a short-chain noncoding RNA, regulates gene expression at the transcriptional level. microRNA modules with a role in the pathogenesis of COPD may serve as COPD biomarkers.\nMETHODS: We downloaded the GSE33336 microarray data set from the Gene Expression Omnibus (GEO) database, the data are derived from 29 lung samples of patients with emphysema undergoing curative resection for lung cancer. We used weighted gene co-expression network analysis (WGCNA) to construct co-expression modules and detect trait-related microRNA modules. We used the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to predict the biological function of the interest modules, and we screened out candidate hub microRNAs based on their module membership (MM) value and top proteins on the results of the protein-protein interaction (PPI) network.\nRESULTS: Three microRNA modules (royal blue, light yellow and grey60) were highly associated with COPD. Axon guidance, proteoglycans in cancer and mitogen-activated protein kinases (MAPK) signaling pathway were common pathways in these three modules. Keratin18 (KRT18) was the top protein in our study. miR-452, miR-149, miR-133a, miR-181a and miR-421 in hub microRNAs may play a role in COPD.\nCONCLUSION: These findings provide evidence for the role of miRNAs in COPD and identify biomarker candidates.", "claims": [{"id": "claim-method", "statement": "We used weighted gene co-expression network analysis (WGCNA) to construct co-expression modules and detect trait-related microRNA modules.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34815668", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We used weighted gene co-expression network analysis (WGCNA) to construct co-expression modules and detect trait-related microRNA modules."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during and/or analyzed during the current study are available in the Gene Expression Omnibus (GEO) datasets (http://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34815668", "locator": "sections[18] \"Data Sharing Statement\" paragraph 2", "quote": "The datasets generated during and/or analyzed during the current study are available in the Gene Expression Omnibus (GEO) datasets (http://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "WGCNA identified three COPD-associated miRNA modules—royal blue, light yellow, and grey60—and implicated miR-452, miR-149, miR-133a, miR-181a, and miR-421 as candidate hub miRNAs.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34815668", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Three microRNA modules (royal blue, light yellow and grey60) were highly associated with COPD."}, {"asset": "source:pmid:34815668", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "miR-452, miR-149, miR-133a, miR-181a and miR-421 in hub microRNAs may play a role in COPD."}, {"asset": "source:pmid:34815668", "locator": "sections[12] \"Association of miRNA Co-Expression Modules with Clinical Traits\" paragraph 2", "quote": "miRNAs clustered in the royal blue module had the strongest negative correlation with the predicted FEV1 (correlation, −0.41; p-value, 0.02), miRNAs clustered in the light yellow module had the strongest positive correlation with the moderate COPD status (correlation, 0.46; p-value, 0.008), miRNAs clustered in the grey60 module had the strongest negative correlation with the smoking pack years (correlation, −0.61; p-value, 3e-04)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "WGCNA identified three COPD-associated miRNA modules—royal blue, light yellow, and grey60—and implicated miR-452, miR-149, miR-133a, miR-181a, and miR-421 as candidate hub miRNAs.", "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:34815668"], "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:GSE33336"], "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:GSE33336"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34815668", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/COPD.S325300", "sha256": "sha256:46f31a8f7f4b0940c0ee78f26439d070a04b45e8a2484912a4dc240000360a19", "bytes": 29817, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/COPD.S325300", "version": null, "note": "Full article fetched from PMC; 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