Journal article
Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease
Neurology. Genetics, Vol.7(5), pp.e617-e617
10/01/2021
DOI: 10.1212/NXG.0000000000000617
PMCID: PMC8515202
PMID: 34660889
Abstract
Background and Objectives
Longitudinal measurements of brain atrophy using structural MRI (sMRI) can provide powerful markers for tracking disease progression in neurodegenerative diseases. In this study, we use a disease progression model to learn individual-level disease times and hence reveal a new timeline of sMRI changes in Huntington disease (HD).
Methods
We use data from the 2 largest cohort imaging studies in HD-284 participants from TRACK-HD (100 control, 104 premanifest, and 80 manifest) and 159 participants from PREDICT-HD (36 control and 128 premanifest)-to train and test the model. We longitudinally register T1-weighted sMRI scans from 3 consecutive time points to reduce intraindividual variability and calculate regional brain volumes using an automated segmentation tool with rigorous manual quality control.
Results
Our model reveals, for the first time, the relative magnitude and timescale of subcortical and cortical atrophy changes in HD. We find that the largest (similar to 20% average change in magnitude) and earliest (similar to 2 years before average abnormality) changes occur in the subcortex (pallidum, putamen, and caudate), followed by a cascade of changes across other subcortical and cortical regions over a period of similar to 11 years. We also show that sMRI, when combined with our disease progression model, provides improved prediction of onset over the current best method (root mean square error = 4.5 years and maximum error = 7.9 years vs root mean square error = 6.6 years and maximum error = 18.2 years).
Discussion
Our findings support the use of disease progression modeling to reveal new information from sMRI, which can potentially inform imaging marker selection for clinical trials.
Details
- Title: Subtitle
- Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease
- Creators
- Peter A. Wijeratne - University College LondonSara Garbarino - University of GenoaSarah Gregory - UCL, Dept Neurodegenerat Dis, Queen Sq Inst Neurol, Huntingtons Dis Res Ctr, London, EnglandEileanoir B. Johnson - UCL, Dept Neurodegenerat Dis, Queen Sq Inst Neurol, Huntingtons Dis Res Ctr, London, EnglandRachael Scahill - UCL, Dept Neurodegenerat Dis, Queen Sq Inst Neurol, Huntingtons Dis Res Ctr, London, EnglandJane S. Paulsen - University of IowaSarah J. Tabrizi - UCL, Dept Neurodegenerat Dis, Queen Sq Inst Neurol, Huntingtons Dis Res Ctr, London, EnglandMarco Lorenzi - Univ Cote dAzur, INRIA, Epione Res Project, Valbonne, FranceDaniel C. Alexander - University College LondonPREDICT-HD InvestigatorsTRACK-HD investigators
- Resource Type
- Journal article
- Publication Details
- Neurology. Genetics, Vol.7(5), pp.e617-e617
- DOI
- 10.1212/NXG.0000000000000617
- PMID
- 34660889
- PMCID
- PMC8515202
- NLM abbreviation
- Neurol Genet
- ISSN
- 2376-7839
- eISSN
- 2376-7839
- Publisher
- Lippincott Williams & Wilkins
- Number of pages
- 11
- Grant note
- ANR-15-IDEX-01 / L'Agence Nationale de la Recherche under Investissements d'Avenir UCA JEDI through the project "AtroProDem: A data-driven model of mechanistic brain Atrophy Propagation in Dementia"; French National Research Agency (ANR) MR/T027770/1 / MRC Skills Development Fellowship; UK Research & Innovation (UKRI); Medical Research Council UK (MRC) NIHR UCLH Biomedical Research Centre French government, through the UCA JEDI ANR-15-IDEX-01; ANR-19-P3IA-0002 / French government, through the 3IA Cote d'Azur Investments in the Future project 200181/Z/15/Z / Wellcome Trust; European Commission 666992 / European Union's Horizon 2020 research and innovation programme
- Language
- English
- Date published
- 10/01/2021
- Academic Unit
- Psychiatry; Psychological and Brain Sciences
- Record Identifier
- 9984383308202771
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