Identification of genomic biomarkers of liver toxicity risk using Formal Concept Analysis on UK Biobank data

Identification of genomic biomarkers of liver toxicity risk using Formal Concept Analysis on UK Biobank data | 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 Identification of genomic biomarkers of liver toxicity risk using Formal Concept Analysis on UK Biobank data Federico Goodsaid, Anna Shteto, Jawad Boulahfa, Adrien Etcheto, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7105178/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Oct, 2025 Read the published version in The Pharmacogenomics Journal → Version 1 posted 10 You are reading this latest preprint version Abstract Predictive safety biomarkers for drug-induced liver injury (DILI) are critically needed to enhance patient risk stratification and minimize adverse outcomes. This study aims to identify genomic markers associated with increased mortality in toxic liver disease, using the KEM® (Knowledge Extraction and Management) explainable Artificial Intelligence platform. From 225 participants diagnosed with toxic liver disease within the UK Biobank cohort, data were consolidated, including survival outcomes, clinical phenotypes, comorbidities, and 36394 genomic single nucleotide polymorphisms (SNPs) focusing on liver-related pathways. Fifteen SNPs were found to be significantly associated with increased mortality risk, notably rs73158145 in the PRKAG2 gene. Predictive models built on these selected SNPs achieved a mean accuracy of 85%, outperforming models without pre-selection (68.9% accuracy). Further validation in independent cohorts is planned to confirm these biomarkers’ clinical relevance. Health sciences/Biomarkers/Predictive markers Biological sciences/Computational biology and bioinformatics/Predictive medicine liver toxicity genomics biomarkers pi3k uk biobank database Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Full Text Additional Declarations Table 1 is available in the Supplementary Files section. There is NO conflict of interest to disclose. Supplementary Files TPJ202500197ManuscriptTables.pdf Table 1 TPJ202500197ManuscriptAppendix.pdf Appendix A Kaplan-Meier plots stratified by clinical risk factors Cite Share Download PDF Status: Published Journal Publication published 28 Oct, 2025 Read the published version in The Pharmacogenomics Journal → Version 1 posted Editorial decision: revise 18 Aug, 2025 Review # 2 received at journal 14 Aug, 2025 Reviewer # 2 agreed at journal 11 Aug, 2025 Review # 1 received at journal 02 Aug, 2025 Reviewer # 1 agreed at journal 02 Aug, 2025 Reviewers invited by journal 15 Jul, 2025 Submission checks completed at journal 15 Jul, 2025 First submitted to journal 14 Jul, 2025 Unknown event 14 Jul, 2025 Editor assigned by journal 11 Jul, 2025 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-7105178","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":485886237,"identity":"8bad8041-c0ef-4f4b-a21a-dedc12cf7b6a","order_by":0,"name":"Federico 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