{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T03:41:20Z","timestamp":1792813280660,"version":"4.5.0"},"reference-count":28,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T00:00:00Z","timestamp":1792713600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T00:00:00Z","timestamp":1792713600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82574697"],"award-info":[{"award-number":["82574697"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["movementdisorders.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Movement Disorders"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Motor progression in Parkinson's disease (PD) is highly heterogeneous, limiting prognosis and the efficiency of clinical trials that require accurate risk stratification. Traditional modeling approaches assume a single average trajectory and fail to capture meaningful divergence, whereas the biological determinants of trajectory\u2010defined subtypes remain unclear. Multivariate proteomic biomarkers may improve early identification of rapid progressors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>We aimed to (1) delineate distinct motor progression subtypes in early PD using longitudinal Movement Disorder Society\u2013Unified Parkinson's Disease Rating Scale (MDS\u2010UPDRS) III scores and (2) identify cerebrospinal fluid (CSF) proteomic signatures that discriminate rapid from slow progressors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed 5\u2010year longitudinal data from 396 Parkinson's Progression Markers Initiative (PPMI) participants with early PD. Motor progression trajectories were derived using latent class trajectory modeling (LCTM) of repeated MDS\u2010UPDRS III scores. CSF proteomics from 78 Olink samples were used for biomarker discovery, with least absolute shrinkage and selection operator (LASSO)\u2013based feature selection followed by multivariable logistic regression. Validation was performed in 184 SOMAscan\u2010profiled samples.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>LCTM identified distinct motor progression subtypes in early PD. Differential CSF protein expression across these trajectories highlighted candidate markers of rapid decline. A seven\u2010protein signature (CCL27, CXCL9, NEFL, SERPINE1, GH1, TYMP, KLK1) exhibited good discriminative performance for distinguishing rapid from slow progressors (area under the curve [AUC]\u2009=\u20090.908). In an independent cohort, the combined model showed consistent directional effects and achieved the highest accuracy (AUC\u2009=\u20090.796).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrating trajectory modeling with CSF proteomics identified a concise seven\u2010protein signature associated with early PD progression, which showed reproducible patterns across two PPMI cohorts. This approach may support improved risk stratification in PD. \u00a9 2026 International Parkinson and Movement Disorder Society.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mds.70589","type":"journal-article","created":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T03:07:40Z","timestamp":1792811260000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Latent Class Trajectory Modeling Identifies Cerebrospinal Fluid Protein Signatures Associated with Motor Progression in Parkinson's Disease: Evidence from the Parkinson's Progression Markers Initiative Cohort"],"prefix":"10.1002","author":[{"given":"Shunyao","family":"Qi","sequence":"first","affiliation":[{"name":"Institute of Medicinal Plant Development (IMPLAD) Chinese Academy of Medical Sciences and Peking Union Medical College  Beijing 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