Single-subject network analysis of FDOPA PET in Parkinson’s disease and Psychosis spectrum

Single-subject network analysis of FDOPA PET in Parkinson’s disease and Psychosis spectrum | 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 Single-subject network analysis of FDOPA PET in Parkinson’s disease and Psychosis spectrum Mario Severino This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6126927/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 Greater understanding of individual biological differences is essential for developing more targeted treatment approaches to complex brain disorders. Traditional analysis methods in molecular imaging studies have primarily focused on quantifying tracer binding in specific brain regions, often neglecting inter-regional functional relationships. In this study, we propose a statistical framework that combines molecular imaging data with perturbation covariance analysis to construct single-subject networks and investigate individual patterns of molecular alterations. This framework was tested on [18F]-DOPA PET imaging as marker of the brain dopamine system in patients with Parkinson's Disease (PD) and schizophrenia to evaluate its ability to classify patients and characterize their disease severity. Our results show that single-subject networks effectively capture molecular alterations, differentiate individuals with heterogeneous conditions, and account for within-group variability. Moreover, the approach successfully distinguishes between preclinical and clinical stages of psychosis and identifies the corresponding molecular connectivity changes in response to antipsychotic medications. Mapping molecular imaging networks presents a new and powerful method for characterizing individualized disease trajectories as well as for evaluating treatment effectiveness in future research. PET FDOPA Parkinson’s Disease Schizophrenia Network Analysis Molecular Connectivity Full Text Additional Declarations The authors declare no competing interests. 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-6126927","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":422190866,"identity":"6fb896ae-5ad4-471c-8a6f-b1293fe65969","order_by":0,"name":"Mario Severino","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0008-8361-6228","institution":"University of Padua","correspondingAuthor":true,"prefix":"","firstName":"Mario","middleName":"","lastName":"Severino","suffix":""}],"badges":[],"createdAt":"2025-02-28 08:56:35","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6126927/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6126927/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77591874,"identity":"60376fd9-f3d9-4bc9-85e5-6231043679f8","added_by":"auto","created_at":"2025-03-03 11:27:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1134850,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptMarioSeverino.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6126927/v1_covered_4ec27917-5d22-4fb9-8c8a-bfb4c2d7a025.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eSingle-subject network analysis of FDOPA PET in Parkinson’s disease and Psychosis spectrum\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PET, FDOPA, Parkinson’s Disease, Schizophrenia, Network Analysis, Molecular Connectivity","lastPublishedDoi":"10.21203/rs.3.rs-6126927/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6126927/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGreater understanding of individual biological differences is essential for developing more targeted treatment approaches to complex brain disorders. 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