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Multivariate clustering of progression profiles reveals different depression patterns in prodromal Huntington disease.
Published Web Location
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640959/No data is associated with this publication.
Abstract
Objective
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.Method
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.Results
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.Conclusions
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.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.