4.6 Article

Tracking Huntington's Disease Progression Using Motor, Functional, Cognitive, and Imaging Markers

期刊

MOVEMENT DISORDERS
卷 36, 期 10, 页码 2282-2292

出版社

WILEY
DOI: 10.1002/mds.28650

关键词

Huntingtonʼ s disease; symptom profiles; statistical modeling; tracking disease progression

资金

  1. CHDI Foundation [A-3433]
  2. National Health and Medical Research Council Australia [606650]
  3. Australian Research Council [DE170100128, DP200100757]
  4. National Health and Medical Research Council [APP1194910]
  5. MRC [UKDRI-1008/2] Funding Source: UKRI
  6. Australian Research Council [DP200100757, DE170100128] Funding Source: Australian Research Council

向作者/读者索取更多资源

Potential therapeutic targets and clinical trials for Huntington's disease have expanded significantly in the last decade. This study aimed to distinguish longitudinal trajectories across different progression groups of Huntington's disease by combining clinical and morphometric imaging data. Putamen and caudate volumes were identified as key variables for differentiation and tracking disease progression within different groups. Monitoring volumetric changes alongside clinical end points may offer a more comprehensive understanding of functional outcomes and help refine the design of clinical trials.
Background Potential therapeutic targets and clinical trials for Huntington's 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. Objective The objective of the present study was to best distinguish longitudinal trajectories across different Huntington's disease progression groups. Methods Clinical and morphometric imaging data from 1082 participants across IMAGE-HD, TRACK-HD, and PREDICT-HD studies were combined, with longitudinal times ranging between 1 and 10 years. 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. Results 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. Conclusions 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. (c) 2021 International Parkinson and Movement Disorder Society

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