An in-silico approach to elucidate the pathways leading to primary osteoporosis: age-related vs. postmenopausal

An in-silico approach to elucidate the pathways leading to primary osteoporosis: age-related vs. postmenopausal | 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 An in-silico approach to elucidate the pathways leading to primary osteoporosis: age-related vs. postmenopausal Rocío Ruiz-Lozano, José Luis Calvo-Gallego, Peter Pivonka, Michelle McDonald, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3432139/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 May, 2024 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted 8 You are reading this latest preprint version Abstract Numerical models of bone remodelling have traditionally been used to simulate bone loss in postmenopausal women and the response to drug treatments. These models simulate the menopausal estrogen decline by altering certain signalling pathways. However, they overlook the simultaneous effect that ageing can have on bone cells function and thus on bone loss. Considering ageing and estrogen decline together is important for designing osteoporosis treatments that can counteract one of the two factors.A previously developed bone remodelling model was adapted to consider the effect of ageing through: (1) decreased TGF-beta content within bone matrix; (2) increased sclerostin production by non-skeletal cells. Estrogen deficiency is simulated in three different ways: (a) increased RANKL expression; (b) decreased OPG production; (c) increased responsiveness of osteoclasts to RANKL. The effect of ageing was validated using clinical BMD data of vertebral trabecular bone from males. The joint effect of ageing and estrogen deficiency was validated using the corresponding clinical data in women.In ageing, the effect of increased sclerostin production is more important than the decrease in TGF-beta. The three mechanisms used to simulate the effect of estrogen deficiency yielded almost identical responses. The results show that early menopause leads to lower density in the fifth decade, but after the sixth decade density is almost independent of the age at menopause on average. Osteoporosis treatment with denosumab was also simulated, concluding that the treatment proves more necessary after 10 years since menopause or after age 60. Age-related osteoporosis postmenopausal osteoporosis TGF-β estrogen deficiency RANKL-RANK-OPG signalling pathway Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.pdf Cite Share Download PDF Status: Published Journal Publication published 03 May, 2024 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted Editorial decision: Revision requested 18 Mar, 2024 Reviews received at journal 18 Mar, 2024 Reviewers agreed at journal 10 Feb, 2024 Reviewers agreed at journal 05 Jan, 2024 Reviewers invited by journal 27 Oct, 2023 Editor assigned by journal 11 Oct, 2023 Submission checks completed at journal 11 Oct, 2023 First submitted to journal 11 Oct, 2023 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. 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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-3432139","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277100289,"identity":"84c7ee82-1e7b-48f6-ab9c-8fff16209e14","order_by":0,"name":"Rocío Ruiz-Lozano","email":"","orcid":"","institution":"University of Seville","correspondingAuthor":false,"prefix":"","firstName":"Rocío","middleName":"","lastName":"Ruiz-Lozano","suffix":""},{"id":277100292,"identity":"e3107839-83d0-41f0-87f9-32f2b691010d","order_by":1,"name":"José Luis Calvo-Gallego","email":"","orcid":"","institution":"University of 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