Spatiotemporal and progression heterogeneity of Parkinson’s disease leveraging multimodal data

Spatiotemporal and progression heterogeneity of Parkinson’s disease leveraging multimodal 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 Spatiotemporal and progression heterogeneity of Parkinson’s disease leveraging multimodal data Zhining Li, Pei Lu, Hongyu Bi, Yumeng Liu, Dixia Cong, Can Li, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8989360/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Parkinson’s disease (PD) is a clinically and biologically heterogeneous neurodegenerative disorder with divergent progression trajectories. Conventional longitudinal cohorts often lack the temporal resolution required for comprehensive disease progression modeling. This study leverages multimodal biomarkers to systematically identify and characterize interpretable PD subtypes with distinct temporal progression patterns. A cohort of 147 participants (107 PD, 40 healthy controls) underwent comprehensive multimodal assessments, including clinical evaluations, quantitative gait analysis, and neuroimaging. Biomarkers demonstrating monotonic associations with disease progression and significant group differences were selected, adjusted for covariates, and normalized. The subtype and stage inference (SuStaIn) model was applied to delineate progression subtypes, which were externally validated. Analysis revealed three reproducible PD subtypes: gait-predominant, intermediate motor, and cognitive-predominant, each defined by unique progression trajectories. Subtype classification exhibited high confidence and generalizability. The gait-predominant subtype showed early impairments in step length, gait speed, and turning, with late cognitive decline. The intermediate motor subtype featured early deterioration in axial and appendicular metrics alongside intermediate structural changes. The cognitive-predominant subtype displayed early cerebellar/brainstem involvement, rapid cognitive decline, and severe multimodal deficits, reflecting a malignant phenotype with the highest disease burden. These findings demonstrate biologically grounded divergence in PD progression, offering a scalable framework for individualized staging, mechanistic stratification, and precision-medicine trial design. Health sciences/Biomarkers Biological sciences/Computational biology and bioinformatics Health sciences/Diseases Health sciences/Neurology Biological sciences/Neuroscience Parkinson’s disease Multimodal Disease progression Gait analysis Cognitive decline Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 07 May, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers invited by journal 03 Mar, 2026 Editor assigned by journal 03 Mar, 2026 Submission checks completed at journal 02 Mar, 2026 First submitted to journal 27 Feb, 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. 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-8989360","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":601425939,"identity":"eb534e50-c46b-41d1-806f-c886937b70a9","order_by":0,"name":"Zhining Li","email":"","orcid":"","institution":"The Second Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Zhining","middleName":"","lastName":"Li","suffix":""},{"id":601425940,"identity":"4e3380fe-71d6-4044-be9c-23a1dfa54cc3","order_by":1,"name":"Pei Lu","email":"","orcid":"","institution":"Xuzhou Medical 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Conventional longitudinal cohorts often lack the temporal resolution required for comprehensive disease progression modeling. This study leverages multimodal biomarkers to systematically identify and characterize interpretable PD subtypes with distinct temporal progression patterns. A cohort of 147 participants (107 PD, 40 healthy controls) underwent comprehensive multimodal assessments, including clinical evaluations, quantitative gait analysis, and neuroimaging. Biomarkers demonstrating monotonic associations with disease progression and significant group differences were selected, adjusted for covariates, and normalized. The subtype and stage inference (SuStaIn) model was applied to delineate progression subtypes, which were externally validated. Analysis revealed three reproducible PD subtypes: gait-predominant, intermediate motor, and cognitive-predominant, each defined by unique progression trajectories. Subtype classification exhibited high confidence and generalizability. The gait-predominant subtype showed early impairments in step length, gait speed, and turning, with late cognitive decline. The intermediate motor subtype featured early deterioration in axial and appendicular metrics alongside intermediate structural changes. The cognitive-predominant subtype displayed early cerebellar/brainstem involvement, rapid cognitive decline, and severe multimodal deficits, reflecting a malignant phenotype with the highest disease burden. 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