Machine learning predicts lifespan and underlying causes of death in aging C. elegans

Machine learning predicts lifespan and underlying causes of death in aging C. elegans | 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 Machine learning predicts lifespan and underlying causes of death in aging C. elegans Marina Ezcurra, Carina Kern, Petru Manescu, Matt Cuffaro, Catherine Au, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4131896/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 Senescence (aging) leads to senescent pathology that causes death, and genes control aging by determining such pathology. Here we investigate how senescent pathology mediates the effect of genotype on lifespan in C. elegans by means of a data-driven approach, using machine learning (ML). To achieve this we gathered extensive data on how diverse determinants of lifespan (sex, nutrition, genotype) affect patterns of age-related pathology. Our findings show that different life-extending treatments result in distinct patterns of suppression of senescent pathology. By analysing the differential effects on pathology and lifespan, our ML models were able to predict >70% of lifespan variation. Extent of pathology in the pharynx and intestine were the most important predictors of lifespan, arguing that elderly C. elegans die in part due to late-life disease in these organs. Notably, the mid-life pathogenetic burst characteristic of hermaphrodite senescence is absent from males. Biological sciences/Physiology/Ageing Biological sciences/Computational biology and bioinformatics/Machine learning Age-related disease aging C. elegans lifespan machine learning reproductive death Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Supplementaryfile1.xlsx Supplementaryinformation.pdf 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. 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-4131896","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":298313205,"identity":"cc670580-0755-4194-9f68-fde9b2fa306e","order_by":0,"name":"Marina 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