A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues | 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 A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues Sundeep Khosla, Dominik Saul, Robyn Laura Kosinsky, Elizabeth Atkinson, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1034608/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Aug, 2022 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Although cellular senescence is increasingly recognized as driving multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification, particularly in bulk or single cell RNA-sequencing (scRNA-seq) data remains challenging. Here, we generated a novel gene set (SenMayo) and first validated its enrichment in bone biopsies from two aged human cohorts. SenMayo also identified senescent cells in aged murine brain tissue, demonstrating applicability across tissues and species. For direct validation, we demonstrated significant reductions in SenMayo in bone following genetic clearance of senescent cells in mice, with similar findings in adipose tissue from humans in a pilot study of pharmacological senescent cell clearance. In direct comparisons, SenMayo outperformed all six existing senescence/SASP gene sets in identifying senescent cells across tissues and in demonstrating responses to senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from publicly available human and murine bone marrow/bone scRNA-seq data and identified monocytic and osteolineage cells, respectively, as showing the highest levels of senescence/SASP genes. Using pseudotime and cellular communication patterns, we found senescent hematopoietic and mesenchymal cells communicated with other cells through common pathways, including the Macrophage Migration Inhibitory Factor (MIF) pathway, which has been implicated not only in inflammation but also in immune evasion, an important property of senescent cells. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Moreover, using this senescence panel, we were able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways associated with these cells, which may be particularly useful for evolving efforts to map senescent cells (e.g., SenNet). In addition, SenMayo represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs. bone senescence SASP gene set aging Full Text Additional Declarations Yes there is potential Competing Interest. Patents on senolytic drugs and their uses and on SASP biomarkers are held by Mayo Clinic and the University of Minnesota. This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and was conducted in compliance with Mayo Clinic Conflict of Interest policies. Supplementary Files SenMayomanuscriptallsupplementaryfigures.pdf Supplementary Figures Cite Share Download PDF Status: Published Journal Publication published 16 Aug, 2022 Read the published version in Nature Communications → 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-1034608","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":69296358,"identity":"a61fe97c-2d02-4b8c-ba71-c21879aa9ae5","order_by":0,"name":"Sundeep 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This research has been reviewed by the Mayo Clinic Conflict of Interest Review Board and was conducted in compliance with Mayo Clinic Conflict of Interest policies.","formattedTitle":"A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1034608/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"bone, senescence, SASP, gene set, aging","lastPublishedDoi":"10.21203/rs.3.rs-1034608/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1034608/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Although cellular senescence is increasingly recognized as driving multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification, particularly in bulk or single cell RNA-sequencing (scRNA-seq) data remains challenging. Here, we generated a novel gene set (SenMayo) and first validated its enrichment in bone biopsies from two aged human cohorts. SenMayo also identified senescent cells in aged murine brain tissue, demonstrating applicability across tissues and species. For direct validation, we demonstrated significant reductions in SenMayo in bone following genetic clearance of senescent cells in mice, with similar findings in adipose tissue from humans in a pilot study of pharmacological senescent cell clearance. In direct comparisons, SenMayo outperformed all six existing senescence/SASP gene sets in identifying senescent cells across tissues and in demonstrating responses to senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from publicly available human and murine bone marrow/bone scRNA-seq data and identified monocytic and osteolineage cells, respectively, as showing the highest levels of senescence/SASP genes. Using pseudotime and cellular communication patterns, we found senescent hematopoietic and mesenchymal cells communicated with other cells through common pathways, including the Macrophage Migration Inhibitory Factor (MIF) pathway, which has been implicated not only in inflammation but also in immune evasion, an important property of senescent cells. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Moreover, using this senescence panel, we were able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways associated with these cells, which may be particularly useful for evolving efforts to map senescent cells (e.g., SenNet). 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