Journal article
Multivariate clustering of progression profiles reveals different depression patterns in prodromal Huntington disease
Neuropsychology, Vol.29(6), pp.949-960
11/2015
DOI: 10.1037/neu0000199
PMCID: PMC4640959
PMID: 26011117
Abstract
Although Huntington disease (HD) is caused by an autosomal dominant mutation, its phenotypic presentation differs widely. Variability in clinical phenotypes of HD may reflect the existence of disease subtypes. This hypothesis was tested in prodromal participants from the longitudinal Neurobiological Predictors of Huntington Disease (PREDICT-HD) study.
We performed clustering using longitudinal data assessing motor, cognitive, and depression symptoms. Using data from 521 participants with 2,716 data points, we fit growth mixture models (GMM) that identify groups based on multivariate trajectories.
In various GMM, different phases of disease progression were partitioned by progression trajectories of motor and cognitive signs, and by overall level of depression symptoms. More progressed motor signs were accompanied by more progressed cognitive signs, but not always by higher levels of depressive symptoms. In several models, there were at least 2 groups with similar trajectories for motor and cognitive signs that showed different levels for depression symptoms-one with a very low level of depression and the other with a higher level of depression.
Findings indicate that at least intermediate HD progression might be associated with different levels of depression. Depression is one of the few symptoms that is treatable in HD and has implications for clinical care. Identification of potential depression subtypes may also help to select appropriate patients for clinical trials.
Details
- Title: Subtitle
- Multivariate clustering of progression profiles reveals different depression patterns in prodromal Huntington disease
- Creators
- Ji-in Kim - Department of PsychiatryJeffrey D Long - Department of PsychiatryJames A Mills - Department of PsychiatryElizabeth McCusker - Department of NeurologyJane S Paulsen - Department of Psychiatry
- Contributors
- Hans J Johnson (Contributor) - University of Iowa, Electrical and Computer Engineering
- Resource Type
- Journal article
- Publication Details
- Neuropsychology, Vol.29(6), pp.949-960
- Publisher
- United States
- DOI
- 10.1037/neu0000199
- PMID
- 26011117
- PMCID
- PMC4640959
- ISSN
- 0894-4105
- eISSN
- 1931-1559
- Grant note
- MR/L010305/1 / Medical Research Council R01 NS040068 / NINDS NIH HHS 5R01NS040068 / NINDS NIH HHS R01 NS054893 / NINDS NIH HHS 2 UL1 TR000442-06 / NCATS NIH HHS 5R01NS054893 / NINDS NIH HHS UL1 TR000442 / NCATS NIH HHS
- Language
- English
- Date published
- 11/2015
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Psychiatry; Psychological and Brain Sciences; Biostatistics; The Iowa Institute for Biomedical Imaging; The Iowa Initiative for Artificial Intelligence; Iowa Informatics Initiative
- Record Identifier
- 9984070478402771
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