The role of angiogenesis-related genes in sepsis-induced acute respiratory distress syndrome

The role of angiogenesis-related genes in sepsis-induced acute respiratory distress syndrome | 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 Research Article The role of angiogenesis-related genes in sepsis-induced acute respiratory distress syndrome Jixiu Fan, Qi Guo, Jifang Liang, Jin Huo, Shulan Wu, Tong Wang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4733659/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Acute respiratory distress syndrome (ARDS) is a major lung injury disease, and the most common cause is sepsis. Angiogenesis is vital in the process of diseaseoccurrence. Several angiogenesis related pathways have been identified to play an important role in ARDS. Hence, it was vital to screen the angiogenesis-related biomarkers for the treatment of sepsis-induced ARDS (SI-ARDS). Methods We introduced transcriptome data to filter differentially expressed genes (DEGs) in SI-ARDS. Venn diagram was executed to identify angiogenesis-related differentially expressed genes (AR-DEGs). Pearson correlation was utilised to obtain AR-DEGs highly correlated with SI-ARDS. PPI network was executed to gain core genes. Further, least absolute shrinkage and selection operator (LASSO) regression was implemented to retain biomarkers. Receiver operating characteristic (ROC) curves were conducted to estimate diagnostic model. The immune infltration circumstance was analyzed by ssGSEA algorithms. The miRNAs-transcription factor (TFs) and ceRNA network were predicted via miRTarBase, miRNet and AnimalTFDB database, respectively. Results We identified 108 DEGs associated with SI-ARDS. Then, 22 AR-DEGs highly correlated with SI-ARDS were obtainedpearson correlation. Subsequently, 6 angiogenesis-related biomarkers were identified, including LTF , OLFM4 , CEACAM8 , MME , BPI , and TFPI . Moreover, we got six significantly differential immune cells in ARDS samples induced by sepsis, among which neutrophils and MDSC infiltration had the highest correlation with TFPI , MME . Finally, the constructed ceRNA regulatory network was composed of 87 nodes and 192 edges. Some potential TFs targeting angiogenesis-related biomarkers were identified, including CEBPE and DCH1. Conclusion Overall, we obtained six angiogenesis-related biomarkers ( LTF , OLFM4 , CEACAM8 , MME , BPI , TFPI ) associated with SI-ARDS, which laid a theoretical foundation for the treatment of SI-ARDS. sepsis-induced acute respiratory distress syndrome Biomarkers Bioinformatics Machine learning Immune cells Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1.xlsx SupplementaryTableS2.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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-4733659","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":331562095,"identity":"d4769a5f-a578-4588-8edc-68bb0f52b87b","order_by":0,"name":"Jixiu Fan","email":"","orcid":"","institution":"Third Hospital of Shanxi Medical University，Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences，Tongji Shanxi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jixiu","middleName":"","lastName":"Fan","suffix":""},{"id":331562096,"identity":"590d470c-c008-4b8e-b7d0-0300d1ad50a3","order_by":1,"name":"Qi 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syndrome","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sepsis-induced acute respiratory distress syndrome, Biomarkers, Bioinformatics, Machine learning, Immune cells","lastPublishedDoi":"10.21203/rs.3.rs-4733659/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4733659/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAcute respiratory distress syndrome (ARDS) is a major lung injury disease, and the most common cause is sepsis. Angiogenesis is vital in the process of diseaseoccurrence. Several angiogenesis related pathways have been identified to play an important role in ARDS. Hence, it was vital to screen the angiogenesis-related biomarkers for the treatment of sepsis-induced ARDS (SI-ARDS).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe introduced transcriptome data to filter differentially expressed genes (DEGs) in SI-ARDS. Venn diagram was executed to identify angiogenesis-related differentially expressed genes (AR-DEGs). Pearson correlation was utilised to obtain AR-DEGs highly correlated with SI-ARDS. PPI network was executed to gain core genes. Further, least absolute shrinkage and selection operator (LASSO) regression was implemented to retain biomarkers. Receiver operating characteristic (ROC) curves were conducted to estimate diagnostic model. The immune infltration circumstance was analyzed by ssGSEA algorithms. The miRNAs-transcription factor (TFs) and ceRNA network were predicted via miRTarBase, miRNet and AnimalTFDB database, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe identified 108 DEGs associated with SI-ARDS. Then, 22 AR-DEGs highly correlated with SI-ARDS were obtainedpearson correlation. Subsequently, 6 angiogenesis-related biomarkers were identified, including \u003cem\u003eLTF\u003c/em\u003e, \u003cem\u003eOLFM4\u003c/em\u003e, \u003cem\u003eCEACAM8\u003c/em\u003e, \u003cem\u003eMME\u003c/em\u003e, \u003cem\u003eBPI\u003c/em\u003e, and \u003cem\u003eTFPI\u003c/em\u003e. Moreover, we got six significantly differential immune cells in ARDS samples induced by sepsis, among which neutrophils and MDSC infiltration had the highest correlation with \u003cem\u003eTFPI\u003c/em\u003e, \u003cem\u003eMME\u003c/em\u003e. Finally, the constructed ceRNA regulatory network was composed of 87 nodes and 192 edges. Some potential TFs targeting angiogenesis-related biomarkers were identified, including CEBPE and DCH1.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOverall, we obtained six angiogenesis-related biomarkers (\u003cem\u003eLTF\u003c/em\u003e, \u003cem\u003eOLFM4\u003c/em\u003e, \u003cem\u003eCEACAM8\u003c/em\u003e, \u003cem\u003eMME\u003c/em\u003e, \u003cem\u003eBPI\u003c/em\u003e, \u003cem\u003eTFPI\u003c/em\u003e) associated with SI-ARDS, which laid a theoretical foundation for the treatment of SI-ARDS.\u003c/p\u003e","manuscriptTitle":"The role of angiogenesis-related genes in sepsis-induced acute respiratory distress syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-10 04:24:11","doi":"10.21203/rs.3.rs-4733659/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"42638679-a876-4a7b-b395-baf853a7ae08","owner":[],"postedDate":"August 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-28T18:17:58+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-10 04:24:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4733659","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4733659","identity":"rs-4733659","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}