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

被引:16
作者
Abeyasinghe, Pubu M. [1 ,2 ]
Long, Jeffrey D. [3 ,4 ]
Razi, Adeel [1 ,2 ,5 ,6 ]
Pustina, Dorian [7 ]
Paulsen, Jane S. [8 ]
Tabrizi, Sarah J. [9 ,10 ]
Poudel, Govinda R. [11 ]
Georgiou-Karistianis, Nellie [1 ,2 ]
机构
[1] Monash Univ, Sch Psychol Sci, Melbourne, Vic, Australia
[2] Monash Univ, Turner Inst Brain & Mental Hlth, Melbourne, Vic, Australia
[3] Univ Iowa, Dept Psychiat, Carver Coll Med, Iowa City, IA 52242 USA
[4] Univ Iowa, Coll Publ Hlth, Dept Biostat, Iowa City, IA USA
[5] Monash Univ, Monash Biomed Imaging, Clayton, Vic, Australia
[6] Wellcome Ctr Human Neuroimaging, UCL, London, England
[7] CHDI Management CHDI Fdn, Princeton, NJ USA
[8] Univ Wisconsin, Dept Neurol, Madison, WI 53706 USA
[9] Dementia Res Inst UCL, UCL Queen Sq Inst Neurol, UCL Dept Neurodegenerat Dis, London, England
[10] Dementia Res Inst UCL, UCL Queen Sq Inst Neurol, Huntingtons Dis Ctr, London, England
[11] Australian Catholic Univ, Mary MacKillop Inst Hlth Res, Melbourne, Vic, Australia
基金
英国医学研究理事会; 澳大利亚研究理事会;
关键词
Huntingtonʼ s disease; symptom profiles; statistical modeling; tracking disease progression; CLINICAL-TRIALS; PREMANIFEST; HD; ONSET; PREDICTION; BIOMARKERS; DIAGNOSIS;
D O I
10.1002/mds.28650
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
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
引用
收藏
页码:2282 / 2292
页数:11
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