Journal article
Concurrent Cross-Sectional and Longitudinal Analyses of Multivariate White Matter Profiles and Clinical Functioning in Pre-Diagnosis Huntington Disease
Journal of Huntington's disease, Vol.8(2), pp.199-219
04/30/2019
DOI: 10.3233/JHD-180332
PMID: 30932891
Abstract
Background: Gray matter (GM) atrophy in the striatum and across the brain is a consistently reported feature of the Huntington Disease (HD) prodrome. More recently, widespread prodromal white matter (WM) degradation has also been detected. However, longitudinal WM studies are limited and conflicting, and most analyses comparing WM and clinical functioning have also been cross-sectional.
Objective: We simultaneously assessed changes in WM and cognitive and motor functioning at various prodromal HD stages.
Methods: Data from 1,336 (1,047 prodromal, 289 control) PREDICT-HD participants were analyzed (3,700 sessions). MRI images were used to create GM, WM, and cerebrospinal fluid probability maps. Using source-based morphometry, independent component analysis was applied to WM probability maps to extract covarying spatial patterns and their subject profiles. WM profiles were analyzed in two sets of linear mixed model (LMM) analyses: one to compare WM profiles across groups cross-sectionally and longitudinally, and one to concurrently compare WM profiles and clinical variables cross-sectionally and longitudinally within each group.
Results: Findings illustrate widespread prodromal changes in GM-adjacent-WM, with premotor, supplementary motor, middle frontal and striatal changes early in the prodrome that subsequently extend sub-gyrally with progression. Motor functioning agreed most with WM until the near-onset prodromal stage, when Stroop interference was the best WM indicator. Across groups, Trail-Making Test part A outperformed other cognitive variables in its similarity to WM, particularly cross-sectionally.
Conclusions: Results suggest that distinct regions coincide with cognitive compared to motor functioning. Furthermore, at different prodromal stages, distinct regions appear to align best with clinical functioning. Thus, the informativeness of clinical measures may vary according to the type of data available (cross-sectional or longitudinal) as well as age and CAG-number.
Details
- Title: Subtitle
- Concurrent Cross-Sectional and Longitudinal Analyses of Multivariate White Matter Profiles and Clinical Functioning in Pre-Diagnosis Huntington Disease
- Creators
- Jennifer A Ciarochi - Neuroscience Institute, Georgia State University, Atlanta, GA, USAHans J Johnson - Department of Electrical and Computer Engineering, 1402 Seamans Center for the Engineering Arts and Science, The University of Iowa, Iowa City, IA, USAVince D Calhoun - The Mind Research Network, Albuquerque, NM, USA, Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USAJingyu Liu - The Mind Research Network, Albuquerque, NM, USAFlor A Espinoza - The Mind Research Network, Albuquerque, NM, USAHenry J Bockholt - The Mind Research Network, Albuquerque, NM, USAMaria Misiura - Department of Psychology, Georgia State University, Atlanta, GA, USAArvind Caprihan - The Mind Research Network, Albuquerque, NM, USASergey Plis - The Mind Research Network, Albuquerque, NM, USAJane S Paulsen - Department of Psychiatry, Iowa Mental Health Clinical Research Center, University of Iowa, IA, USA, Departments of Neurology and Psychology, University of Iowa, IA, USAJessica A Turner - Neuroscience Institute, Georgia State University, Atlanta, GA, USA, Department of Psychology, Georgia State University, Atlanta, GA, USAPREDICT-HD Investigators and Coordinators of the Huntington Study Group (Institution)
- Resource Type
- Journal article
- Publication Details
- Journal of Huntington's disease, Vol.8(2), pp.199-219
- DOI
- 10.3233/JHD-180332
- PMID
- 30932891
- ISSN
- 1879-6397
- eISSN
- 1879-6400
- Language
- English
- Date published
- 04/30/2019
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Psychiatry; Psychological and Brain Sciences; The Iowa Institute for Biomedical Imaging; The Iowa Initiative for Artificial Intelligence; Iowa Informatics Initiative
- Record Identifier
- 9984083268202771
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