Development and Application of Brain Tissue Based Multi-omics Profile Scores for Alzheimer's Disease

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Development and Application of Brain Tissue Based Multi-omics Profile Scores for Alzheimer's Disease | 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 Development and Application of Brain Tissue Based Multi-omics Profile Scores for Alzheimer's Disease Timur Tug, Donghai Liang, Sven Teschke, Youran Tan, Marla Gearing, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9438710/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract BACKGROUND Advances in omics technologies, such as epigenomics and metabolomics, provide novel insights into the biological mechanisms underlying Alzheimer's disease (AD). However, little is known how different omics layers interact and jointly relate to AD neuropathology. METHODS We performed a comprehensive single- and multi-omics analysis integrating genome-wide DNA methylation and high-resolution metabolomics data from 157 frontal cortex samples. We developed novel single and multi-omics profile scores (PS) for AD pathology, using a combination of machine learning, regression, and pathway analysis. RESULTS For the ABC score (Amyloid, Braak, CERAD) the PS of DNAm outperformed metabolomics-based PS (median R²: 0.11 vs. 0.04). Combining both omics layers with the best-performing multi-omics PS yielded a partial R² of 0.15 for the ABC score independent of age, sex, race and socioeconomic factors. DNAm-specific pathways highlighted redox balance, immune activation, synaptic signaling, and lipid biosynthesis, whereas metabolomics-specific pathways emphasized inflammatory, hormonal, lipid, and energy metabolism. Notably, both omics layers converged on lipid metabolism and signal transduction as shared biological systems implicated in AD neuropathology. CONCLUSIONS Despite limited gains in predictive accuracy, integrative pathway and network analyses of DNAm and metabolomics PS converged on lipid metabolism and signal transduction, underscoring shared biological mechanisms and the value of multi-omics approaches for biological insight rather than prediction alone. Alzheimer’s disease multi-omics profile scores DNA methylation metabolomics neuropathology machine learning Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementfiles.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 14 May, 2026 Reviews received at journal 13 May, 2026 Reviews received at journal 30 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers agreed at journal 18 Apr, 2026 Reviewers invited by journal 18 Apr, 2026 Editor assigned by journal 17 Apr, 2026 Submission checks completed at journal 17 Apr, 2026 First submitted to journal 16 Apr, 2026 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. 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