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Brain Age as a New Measure of Disease Stratification in Huntington's Disease

27 Pages Posted: 19 Jul 2023

See all articles by Pubu M. Abeyasinghe

Pubu M. Abeyasinghe

Monash University - Turner Institute for Brain and Mental Health

James H. Cole

University College London - UCL Centre for Medical Imaging

Adeel Razi

Monash University - Turner Institute for Brain and Mental Health

Govinda Poudel

New Zealand Brain Research Institute - Christchurch Neurotechnology Research Programme

Jane S. Paulsen

University of Wisconsin - Madison - Department of Neurology

Sarah J. Tabrizi

University College London - UCL Huntington's Disease Centre

Jeffrey D. Long

University of Iowa - Department of Psychiatry

Nellie Georgiou-Karistianis

Monash University - Turner Institute for Brain and Mental Health

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Abstract

Background: Extensive knowledge about Huntington’s disease (HD) has been generated over the last two decades, yet no disease modifying treatment exists. One contributing factor is the need for proper methods to characterise and define states of progression for therapeutics. Therefore, the objective of the present study was to calculate the brain’s biological age (so-called brain age) and utilize it as the basis of a data-driven clustering method to characterise states of progression in HD. Brain age has the potential for this type of stratification, as somatic expansion increases with age, which is thought to ultimately affect brain volumes. This approach may help define stratified treatment populations for clinical interventions and identify the optimal time for interventions to obtain the highest efficiency.

Methods: T1-weighted MRI and clinical data from 953 participants, across PREDICT-HD, TRACK-HD and IMAGE-HD cohorts, were combined, including longitudinal measurements ranging between 1 and 10 years. Brain age for all participants was calculated and classified into 4 groups, using CAG and age product (CAP) score for the initial analysis. Next, unsupervised longitudinal k-means clustering was performed using brain-predicted age difference (brain-PAD: the difference between brain-predicted age and the chronological age) to identify heterogeneous states of progression across the disease spectrum.

Findings: At baseline, brain age and chronological age of HD participants were significantly different compared to controls, and the difference increased as a function of progression state. Brain-PAD was associated with disease severity captured by the CAP groups. Five states of progression were identified using statistical methods, resulting in substantive differences between the baseline and longitudinal progression of brain-PAD.

Interpretation: Our findings demonstrate that brain-PAD has the potential to capture states of progression and might enhance other prognostic approaches. Hence, brain-PAD is proposed as a potential measure for participant stratification and might contribute to the selection of individuals for future clinical trials in HD.

Funding: IMAGE-HD was supported by CHDI Foundation research agreement A–3433 and the National Health and Medical Research Council Australia grant 606650. AR is funded by the Australian Research Council (Refs: DE170100128 and DP200100757) and National Health and Medical Research Council (Ref: APP1194910). IMAGE-HD data used in this work was generously provided by the participants and made available by Prof. Nellie Georgiou-Kartistianis (N.G- K), Principal Investigator. TRACK-HD data used in this work was generously provided by the participants in the TRACK-HD study was made available by Prof. Sarah Tabrizi, Principal Investigator, University College London. PREDICT-HD data used in this work was generously provided by the participants in PREDICT-HD study and made available by the PREDICT-HD investigators and coordinators of the Huntington Study Group, Prof. Jane S. Paulsen, Principal Investigator (PREDICT-HD work was funded by the National Institute of Neurological Diseases and Stroke of the NIH (grants #NS082089; #NS040068, #NS103475, #NS105509) and CHDI.

Declaration of Interest: None.

Ethical Approval: PREDICT-HD procedures were approved by institutional review boards at each site (32 sites across the United States, Canada, Australia, and Europe). TRACK-HD was approved by the local ethics committees at each study site in the Netherlands, UK, France, and Canada. IMAGE-HD was approved by the Monash University and Melbourne Health Human Research Ethics Committees as a single site study in Melbourne, Australia. For all three studies, each participant provided written informed consent.

Keywords: Huntington's Disease, brain age, states of progression, statistical modelling, tracking disease progression

Suggested Citation

Abeyasinghe, Pubu M. and Cole, James H. and Razi, Adeel and Poudel, Govinda and Paulsen, Jane S. and Tabrizi, Sarah J. and Long, Jeffrey D. and Georgiou-Karistianis, Nellie, Brain Age as a New Measure of Disease Stratification in Huntington's Disease. Available at SSRN: https://ssrn.com/abstract=4513720 or http://dx.doi.org/10.2139/ssrn.4513720

Pubu M. Abeyasinghe

Monash University - Turner Institute for Brain and Mental Health ( email )

James H. Cole

University College London - UCL Centre for Medical Imaging ( email )

Adeel Razi

Monash University - Turner Institute for Brain and Mental Health ( email )

Govinda Poudel

New Zealand Brain Research Institute - Christchurch Neurotechnology Research Programme ( email )

Jane S. Paulsen

University of Wisconsin - Madison - Department of Neurology ( email )

Sarah J. Tabrizi

University College London - UCL Huntington's Disease Centre ( email )

Jeffrey D. Long

University of Iowa - Department of Psychiatry ( email )

Nellie Georgiou-Karistianis (Contact Author)

Monash University - Turner Institute for Brain and Mental Health ( email )