Improvements in blood and fitness tracker biomarkers in a longitudinal real-world cohort of digital health platform users | 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 Improvements in blood and fitness tracker biomarkers in a longitudinal real-world cohort of digital health platform users Nimisha Schneider, Paul Fabian, Michelle Cawley, Bartek Nogal, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4850246/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 Digital health technologies offer new opportunities for personalized health management and disease prevention. We examined the use of a digital health platform (DHP) in a retrospective, long-term longitudinal study of over 20,000 users. The DHP evaluates a user’s individual biological profile, consisting of blood biomarkers, polygenic risk scores (PGS), and fitness tracker data, and provides personalized lifestyle interventions based on knowledge about nutrition, supplement, exercise and recovery collected from over 7,000 clinical studies. Here, we show improvement in suboptimal levels of key blood biomarkers that are sustained or increased in the long-term with DHP use. We additionally show correlation of biomarker improvement with specific sleep and activity patterns in users. Lastly, we find significant correlations between polygenic risk and both baseline levels and longitudinal change in biomarkers, including low-density lipoprotein cholesterol (LDL-c), suggesting that genetic predisposition for a negative trait (e.g., elevated LDL-c) could make it more difficult to improve that trait. This longitudinal, integrated biomarker dataset highlights the potential of digital health tools in fostering improvements in health-related biomarkers through personalized data analytics and targeted behavioral interventions. Health sciences/Health care Health sciences/Health care/Disease prevention/Lifestyle modification Full Text Additional Declarations There is a conflict of interest All authors are full time employees of InsideTracker and hold stock options but declare no non-financial competing interests. Author GB also holds InsideTracker shares. Supplementary Files npjdmsupplementarydata072024.pdf Supplementary Data npjdmsupplementarydata072024.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. 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