Tracking Huntingtonʼs disease progression using motor, functional, cognitive, and imaging markers

Journal article

Abeyasinghe, Pubu M., Long, Jeffrey D., Razi, Adeel, Pustina, Dorian, Paulsen, Jane S., Tabrizi, Sarah J., Poudel, Govinda R. and Georgiou-Karistianis, Nellie. (2021). Tracking Huntingtonʼs disease progression using motor, functional, cognitive, and imaging markers. Movement Disorders. 36(10), pp. 2282-2292. https://doi.org/10.1002/mds.28650
AuthorsAbeyasinghe, Pubu M., Long, Jeffrey D., Razi, Adeel, Pustina, Dorian, Paulsen, Jane S., Tabrizi, Sarah J., Poudel, Govinda R. and Georgiou-Karistianis, Nellie
Abstract

Background
Potential therapeutic targets and clinical trials for Huntingtonʼs 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 Huntingtonʼs 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. © 2021 International Parkinson and Movement Disorder Society

KeywordsHuntingtonʼs disease; symptom profiles; statistical modeling; tracking disease progression
Year2021
JournalMovement Disorders
Journal citation36 (10), pp. 2282-2292
PublisherJohn Wiley & Sons, Inc.
ISSN0885-3185
Digital Object Identifier (DOI)https://doi.org/10.1002/mds.28650
Scopus EID2-s2.0-85105984769
Research or scholarlyResearch
Page range2282-2292
FunderAustralian Research Council (ARC)
National Health and Medical Research Council (NHMRC)
Publisher's version
License
All rights reserved
File Access Level
Controlled
Output statusPublished
Publication dates
Online20 May 2021
Publication process dates
Accepted27 Apr 2021
Deposited07 Nov 2021
ARC Funded ResearchThis output has been funded, wholly or partially, under the Australian Research Council Act 2001
Grant IDARC/DE170100128
ARC/DP200100757
NHMRC/1194910
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The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: Applications in neuroscience and neuroinformatics research
Goscinski, Wojtek J., McIntosh, Paul, Felzmann, Ulrich, Maksimenko, Anton, Hall, Christopher J., Gureyev, Timur, Thompson, Darren, Janke, Andrew, Galloway, Graham, Killeen, Neil E. B., Raniga, Parnesh, Kaluza, Owen, Ng, Amanda, Poudel, Govinda, Barnes, David G., Nguyen, Toan, Bonnington, Paul and Egan, Gary F.. (2014). The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: Applications in neuroscience and neuroinformatics research. Frontiers in Neuroinformatics. 8(March), pp. 1 - 13. https://doi.org/10.3389/fninf.2014.00030
Functional magnetic resonance imaging of working memory in Huntington's disease: Cross-sectional data from the IMAGE-HD study
Georgiou-Karistianis, Nellie, Stout, Julie C., Domínguez, Juan F., Carron, Sarah P., Ando, Ayaka, Churchyard, Andrew, Chua, Phyllis, Bohanna, India, Dymowski, Alicia R., Poudel, Govinda and Egan, Gary F.. (2014). Functional magnetic resonance imaging of working memory in Huntington's disease: Cross-sectional data from the IMAGE-HD study. Human Brain Mapping. 35(5), pp. 1847 - 1864. https://doi.org/10.1002/hbm.22296
Voxel-ICA for reconstruction of source signal time-series and orientation in EEG and MEG
Jonmohamadi, Yaqub, Poudel, Govinda, Innes, Carrie and Jones, Richard. (2014). Voxel-ICA for reconstruction of source signal time-series and orientation in EEG and MEG. Australasian Physical and Engineering Sciences in Medicine. 37(2), pp. 457 - 464. https://doi.org/10.1007/s13246-014-0265-x
Multi-modal neuroimaging in premanifest and early Huntington's disease : 18 month longitudinal data from the IMAGE-HD study
Domínguez D, Juan F., Egan, Gary F., Gray, Marcus A., Poudel, Govinda R., Churchyard, Andrew, Chua, Phyllis, Stout, Julie C. and Georgiou-Karistianis, Nellie. (2013). Multi-modal neuroimaging in premanifest and early Huntington's disease : 18 month longitudinal data from the IMAGE-HD study. PLoS ONE. 8(9), pp. 1-10. https://doi.org/10.1371/journal.pone.0074131
Functional and connectivity changes during working memory in Huntington's disease : 18 month longitudinal data from the IMAGE-HD study
Georgiou-Karistianis, Nellie, Poudel, Govinda R., Domínguez D, Juan F., Langmaid, Rebecca, Gray, Marcus A., Churchyard, Andrew, Chua, Phyllis, Borowsky, Beth, Egan, Gary F. and Stout, Julie C.. (2013). Functional and connectivity changes during working memory in Huntington's disease : 18 month longitudinal data from the IMAGE-HD study. Brain and Cognition. 83(1), pp. 80-91. https://doi.org/10.1016/j.bandc.2013.07.004
Efficient and regular patterns of nighttime sleep are related to increased vulnerability to microsleeps following a single night of sleep restriction
Innes, Carrie R. H., Poudel, Govinda R. and Jones, Richard D.. (2013). Efficient and regular patterns of nighttime sleep are related to increased vulnerability to microsleeps following a single night of sleep restriction. Chronobiology International. 30(9), pp. 1187-1196. https://doi.org/10.3109/07420528.2013.810222
Distinct neural correlates of time-on-task and transient errors during a visuomotor tracking task after sleep restriction
Poudel, Govinda R., Innes, Carrie R. H. and Jones, Richard D.. (2013). Distinct neural correlates of time-on-task and transient errors during a visuomotor tracking task after sleep restriction. NeuroImage. 77, pp. 105-113. https://doi.org/10.1016/j.neuroimage.2013.03.054
Time-Varying Functional Connectivity for Understanding the Neural Basis of Behavioral Microsleeps
J Toppi, L Astolfi, GR Poudel, F Babiloni, L Macchiusi, D Mattia, S Salinari and RD Jones. (2012). Time-Varying Functional Connectivity for Understanding the Neural Basis of Behavioral Microsleeps. 34th Annual International Conference of the IEEE EMBS. IEEE, Institute of Electrical and Electronics Engineers. pp. 4708-4711 https://doi.org/10.1109/EMBC.2012.6347018
Performance of Beamformers on EEG Source Reconstruction
Yaqub Jon Mohamadi, Govinda Poudel, Carrie R H Innes and Richard Jones. (2012). Performance of Beamformers on EEG Source Reconstruction. 34th Annual International Conference of the IEEE EMBS. IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2012.6346476
Cerebral perfusion differences between drowsy and nondrowsy individuals after acute sleep restriction
Poudel, Govinda R., Innes, Carrie R. H. and Jones, Richard D.. (2012). Cerebral perfusion differences between drowsy and nondrowsy individuals after acute sleep restriction. Sleep. 35(8), pp. 1085-1096. https://doi.org/10.5665/sleep.1994