Bioinformatics analysis and identification of genes associated with pyroptosis and immune cells in chronic obstructive pulmonary disease

Bioinformatics analysis and identification of genes associated with pyroptosis and immune cells in chronic obstructive pulmonary disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Bioinformatics analysis and identification of genes associated with pyroptosis and immune cells in chronic obstructive pulmonary disease Zhu Zeng, Yun-Ling Huang, Juan Chen, Qian Yuan, Zeng-Tao Sun, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8757376/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract The progression of chronic obstructive pulmonary disease (COPD), a ruinous chronic inflammatory lung disease, is associated with pyroptosis and inflammation. This study aimed toexplore the relationship between feature genes related to pyroptosis and immune cells in COPD using bioinformatics methods, and RNA sequencing datasets (GSE76925 and GSE56766) were retrieved from the Gene Expression Omnibus database. Pyroptosis-related genes (PRGs) were searchedusing the Gene card database, GOBP-PYROPTOSIS, REACTOME-PYROPTOSIS pathway, and a previous study. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to ascertainthe key modules associated with differential immune cells authenticated by adopting single-sample Gene Set Enrichment Analysis. Differentially expressed genes(DEGs) were identified using the limma package. Feature genes were identified using the least absolute shrinkage and selection operator (LASSO) algorithm in conjunction with the support vector machine-recursive feature elimination (SVM-RFE) algorithm, and the Receiver Operating Characteristic curves were painted with the aim of validating the diagnostic performance of feature genes. Four pyroptosis-immune cell-related genes (ADORA3, APOE, HMGB1, and ELANE) were identified. Additionally, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to explore the functions of the feature genes, showing that ADORA3 and APOE were primarily involved in immune-related pathways. Finally, a competing endogenous RNA (ceRNA) network was established. Pyroptosis plays an important role in the development of chronic obstructive pulmonary disease. In this study, four key genes (ADORA3, APOE, HMGB1, and ELANE) related to pyroptosis and immune cells in chronic obstructive pulmonary disease were detected by bioinformatic fractionation and validated in clinical experiments, which provides new ideas for the diagnosis and treatment of this disease. Health sciences/Biomarkers Biological sciences/Computational biology and bioinformatics Health sciences/Diseases Biological sciences/Genetics Biological sciences/Immunology chronic obstructive pulmonary disease pyroptosis immune cell feature gene machine learning algorithm Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementarytable1.xlsx Supplementarytable2.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers invited by journal 06 May, 2026 Editor assigned by journal 08 Apr, 2026 Editor invited by journal 26 Feb, 2026 Submission checks completed at journal 25 Feb, 2026 First submitted to journal 25 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8757376","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":638922374,"identity":"a9a108d4-df01-4a9c-b24e-b40be5ddbc44","order_by":0,"name":"Zhu Zeng","email":"","orcid":"","institution":"Chengdu University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zhu","middleName":"","lastName":"Zeng","suffix":""},{"id":638922375,"identity":"146ea0c1-e178-4c07-94a4-5da96afe2028","order_by":1,"name":"Yun-Ling 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This study aimed toexplore the relationship between feature genes related to pyroptosis and immune cells in COPD using bioinformatics methods, and RNA sequencing datasets (GSE76925 and GSE56766) were retrieved from the Gene Expression Omnibus database. Pyroptosis-related genes (PRGs) were searchedusing the Gene card database, GOBP-PYROPTOSIS, REACTOME-PYROPTOSIS pathway, and a previous study. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to ascertainthe key modules associated with differential immune cells authenticated by adopting single-sample Gene Set Enrichment Analysis. Differentially expressed genes(DEGs) were identified using the limma package. 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