Pyroptosis-Related Genes as Diagnostic Markers in Chronic Obstructive Pulmonary Disease and Its Correlation with Immune Infiltration.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38957709", "kind": "science-record", "revision": 2, "content_hash": "sha256:0349ee1de7373ee8ed4ca03fef27025dc46ae4e4a466fa6c4c0e5e06f4d36afc", "created_at": "2026-11-01T20:29:02Z", "updated_at": "2026-11-01T21:33:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Pyroptosis-Related Genes as Diagnostic Markers in Chronic Obstructive Pulmonary Disease and Its Correlation with Immune Infiltration.", "doi": "10.2147/COPD.S438686", "pmid": "38957709", "authors": ["Hong-Mei Shu", "Chang-Qing Lin", "Bei He", "Wang Wang", "Ling Wang", "Ting Wu", "Hai-Juan He", "Hui-Juan Wang", "He-Ping Zhou", "Guo-Zheng Ding"], "journal": "International journal of chronic obstructive pulmonary disease", "year": 2024, "abstract": "Background: Chronic obstructive pulmonary disease (COPD) stands as a predominant cause of global morbidity and mortality. This study aims to elucidate the relationship between pyroptosis-related genes (PRGs) and COPD diagnosis in the context of immune infiltration, ultimately proposing a PRG-based diagnostic model for predicting COPD outcomes.\nMethods: Clinical data and PRGs of COPD patients were sourced from the GEO database. The \"ConsensusClusterPlus\" package was employed to generate molecular subtypes derived from PRGs that were identified through differential expression analysis and LASSO Cox analysis. A diagnostic signature including eight genes (CASP4, CASP5, ELANE, GPX4, NLRP1, GSDME, NOD1and IL18) was also constructed. Immune cell infiltration calculated by the ESTIMATE score, Stroma scores and Immune scores were also compared on the basis of pyroptosis-related molecular subtypes and the risk signature. We finally used qRT - PCR to detect the expression levels of eight genes in COPD patient and normal.\nResults: The diagnostic model, anchored on eight PRGs, underwent validation with an independent experimental cohort. The area under the receiver operating characteristic (ROC) curves (AUC) for the diagnostic model showcased values of 0.809, 0.765, and 0.956 for the GSE76925, GSE8545, and GSE5058 datasets, respectively. Distinct expression patterns and clinical attributes of PRGs were observed between the comparative groups, with functional analysis underscoring a disparity in immune-related functions between them.\nConclusion: In this study, we developed a potential as diagnostic biomarkers for COPD and have a significant role in modulating the immune response. Such insights pave the way for novel diagnostic and therapeutic strategies for COPD.", "claims": [{"id": "claim-method", "statement": "Regarding the method of genetic identification, we performed univariate logistic regression analysis on the PRGs in GSE76925, selecting genes associated with COPD diagnosis based on a significance level of p<0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38957709", "locator": "sections[13] \"Statistical Analysis\" paragraph 2", "quote": "Regarding the method of genetic identification, we performed univariate logistic regression analysis on the PRGs in GSE76925, selecting genes associated with COPD diagnosis based on a significance level of p<0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are openly available in GEO. We used three databases: GSE76925 (doi:10.1038/srep44232), GSE8545 (doi:10.1378/chest.07-2245), and GSE5058 (doi:10.1164/rccm.200705-795OC).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38957709", "locator": "sections[28] \"Data Sharing Statement\" paragraph 2", "quote": "The data that support the findings of this study are openly available in GEO. We used three databases: GSE76925 (doi:10.1038/srep44232), GSE8545 (doi:10.1378/chest.07-2245), and GSE5058 (doi:10.1164/rccm.200705-795OC)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The eight-PRG diagnostic model achieved AUC values of 0.809, 0.765, and 0.956 in the GSE76925, GSE8545, and GSE5058 datasets, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38957709", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The area under the receiver operating characteristic (ROC) curves (AUC) for the diagnostic model showcased values of 0.809, 0.765, and 0.956 for the GSE76925, GSE8545, and GSE5058 datasets, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The eight-PRG diagnostic model achieved AUC values of 0.809, 0.765, and 0.956 in the GSE76925, GSE8545, and GSE5058 datasets, respectively.", "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:38957709"], "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:GSE5058"], "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:GSE5058"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38957709", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/COPD.S438686", "sha256": "sha256:3697bee1e3dca39f9a9af415b9e8736ff65adcb458f765fdd55e9e42084ef1d5", "bytes": 56356, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/COPD.S438686", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11217143", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE5058", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE5058", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE5058", "version": null, "note": "The data that support the findings of this study are openly available in GEO. 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We used three databases: GSE76925 (doi:10.1038/srep44232), GSE8545 (doi:10.1378/chest.07-2245), and GSE5058 (doi:10.1164/rccm.200705-795OC).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data that support the findings of this study are openly available in GEO. 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