{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T19:54:59Z","timestamp":1785354899054,"version":"3.55.0"},"reference-count":48,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T00:00:00Z","timestamp":1621468800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["606650"],"award-info":[{"award-number":["606650"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["movementdisorders.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Movement Disorders"],"published-print":{"date-parts":[[2021,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Potential therapeutic targets and clinical trials for Huntington\u02bcs disease have grown immensely in the last decade. However, to improve clinical trial outcomes, there is a need to better characterize profiles of signs and symptoms across different epochs of the disease to improve selection of participants.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>The objective of the present study was to best distinguish longitudinal trajectories across different Huntington\u02bcs disease progression groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Clinical and morphometric imaging data from 1082 participants across IMAGE\u2010HD, TRACK\u2010HD, and PREDICT\u2010HD studies were combined, with longitudinal times ranging between 1 and 10\u2009years. Participants were classified into 4 groups using CAG and age product. Using multivariate linear mixed modeling, 63 combinations of markers were tested for their sensitivity in differentiating CAG and age product groups. Next, multivariate linear mixed modeling was applied to define the best combination of markers to track progression across individual CAG and age product groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Putamen and caudate volumes, individually and\/or combined, were identified as the best variables to both differentiate CAG and age product groups and track progression within them. The model using only caudate volume best described advanced disease progression in the combined data set. Contrary to expectations, combining clinical markers and volumetric measures did not improve tracking longitudinal progression.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Monitoring volumetric changes throughout a trial (alongside primary and secondary clinical end points) may provide a more comprehensive understanding of improvements in functional outcomes and help to improve the design of clinical trials. Alternatively, our results suggest that imaging deserves consideration as an end point in clinical trials because of the prospect of greater sensitivity. \u00a9 2021 International Parkinson and Movement Disorder Society<\/jats:p><\/jats:sec>","DOI":"10.1002\/mds.28650","type":"journal-article","created":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T06:14:41Z","timestamp":1621491281000},"page":"2282-2292","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Tracking Huntington\u02bcs Disease Progression Using Motor, Functional, Cognitive, and Imaging Markers"],"prefix":"10.1002","volume":"36","author":[{"given":"Pubu M.","family":"Abeyasinghe","sequence":"first","affiliation":[{"name":"School of Psychological Sciences and Turner Institute for Brain and Mental Health Monash University  Melbourne Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey 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