Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq 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 Technical Report Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data Martin Zhang, Kangcheng Hou, Bogdan Pasaniuc, Alkes L. Price, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-933790/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Sep, 2022 Read the published version in Nature Genetics → Version 1 posted You are reading this latest preprint version Abstract Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution; scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N=341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states; subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region; and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes. Molecular Genetics Bioinformatics Computational Biology gene expression single-cell Disease Relevance Score single-cell RNA-sequencing Full Text Additional Declarations There is NO Competing Interest. Supplementary Files papersupp.pdf Supplementary materials supptables16324518751.xlsx Supplementary Tables Cite Share Download PDF Status: Published Journal Publication published 01 Sep, 2022 Read the published version in Nature Genetics → 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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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-933790","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Technical Report","associatedPublications":[],"authors":[{"id":55587539,"identity":"2b9823aa-8540-475c-96ac-f820851bf651","order_by":0,"name":"Martin Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABI0lEQVRIie2RMUvDQBTHX4iky8WsFyLtV7hQSClF+lUihcvi4EcoCHYJuPZDONykFRxODjqlZL2hixRuqtBJDGTwcupkoh0d7geP+8O7H+/BA7BY/iHOtXm4LndtAvlsuLrSvxSPHqd80SgoOU5xF/4aH+rtYBTcvb1Uqy2MehuFq6cJBL1L0r7YKQ2XSMWPy9eHoV8oGOdZEuYqgzDfdygoiRAWDpOb+8i5EUA4dQniOsiuKVqpiZgyWaiwapRSuXGtlelvCqTigpW5h/1GkdTZmSm4UxmOcy5mTHpJ5BcCEamc3RnPEC7UVZsS3xaxfK/FOSuFXmwl+qSk8Lznk36wmLFWZQ4n2CSc6plzQN8d1Pa9YaBPczAp4EaxWCwWyw8+ADikaysPt3/mAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0006-2466","institution":"Harvard University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Zhang","suffix":""},{"id":55587540,"identity":"d15b6fa2-50cb-41b7-9664-4c5ef8fd8cc8","order_by":1,"name":"Kangcheng Hou","email":"","orcid":"","institution":"University of California, Los Angeles","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kangcheng","middleName":"","lastName":"Hou","suffix":""},{"id":55587541,"identity":"5a005257-2bd7-4e15-9a36-e4c918b0b4a0","order_by":2,"name":"Bogdan Pasaniuc","email":"","orcid":"","institution":"UCLA","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bogdan","middleName":"","lastName":"Pasaniuc","suffix":""},{"id":55587542,"identity":"ee5a69ac-7ffb-4710-8f93-7704c5974b39","order_by":3,"name":"Alkes L. 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