A multi-omics integration approach relying on circulating factors does not discern endotypes in childhood type 1 diabetes.

A multi-omics integration approach relying on circulating factors does not discern endotypes in childhood type 1 diabetes. | 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 Brief Communication A multi-omics integration approach relying on circulating factors does not discern endotypes in childhood type 1 diabetes. Alessandra Petrelli, Valentina Codazzi, Nicola Baldoni, Giulia Scotti, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4213232/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 May, 2025 Read the published version in Communications Medicine → Version 1 posted You are reading this latest preprint version Abstract Type 1 Diabetes (T1D) exhibits considerable heterogeneity, impacting prediction, prevention, diagnosis, and treatment. Precision medicine aims to tailor treatments using 'endotypes'—subtypes of disease with distinct pathophysiological mechanisms. However, proposed endotypes often lack mechanistic associations with clinical outcomes, remaining elusive in T1D. This study introduces a new approach leveraging the multi-omics factor analysis (MOFA) strategy to explore endotypes through data integration. Analyzing data from 146 new-onset pediatric T1D patients, including circulating immunome, transcriptome, and serum metabolic hormones, we identify 12 factors explaining variability across the three data sets. Notably, no clustering or direct association of these factors with clinical parameters, genetic predisposition and disease outcome are found, suggesting that a combination of clinical phenotypes is responsible for the differences across patients. These findings challenge the assumption that T1D heterogeneity reflects diverse developmental mechanisms, contributing significantly to the endotype discussion and impacting clinical trial design. Health sciences/Diseases/Endocrine system and metabolic diseases/Diabetes/Type 1 diabetes Health sciences/Health care/Paediatrics Biological sciences/Computational biology and bioinformatics/Data integration Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SUPPLEMENTARYMATERIAL.pdf Supplemental material Cite Share Download PDF Status: Published Journal Publication published 27 May, 2025 Read the published version in Communications Medicine → 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. 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