Dataset Information

The Clinical Picture of Psychosis in Manifest Huntington's Disease: A Comprehensive Analysis of the Enroll-HD Database.

ABSTRACT: Background: Psychotic symptoms have been under-investigated in Huntington's disease (HD) and research is needed in order to elucidate the characteristics linked to the unique phenotype of HD patients presenting with psychosis. Objective: To evaluate the frequency and factors associated with psychosis in HD. Methods: Cross-sectional study including manifest individuals with HD from the Enroll-HD database. Both conventional statistical analysis (Stepwise Binary Logistic Regression) and five machine learning algorithms [Least Absolute Shrinkage and Selection Operator (LASSO); Elastic Net; Support Vector Machines (SVM); Random Forest; and class-weighted SVM] were used to describe factors associated with psychosis in manifest HD patients. Results: Approximately 11% of patients with HD presented history of psychosis. Logistic regression analysis indicated that younger age at HD clinical diagnosis, lower number of CAG repeats, history of [alcohol use disorders, depression, violent/aggressive behavior and perseverative/obsessive behavior], lower total functional capacity score, and longer time to complete trail making test-B were associated with psychosis. All machine learning algorithms were significant (chi-square p < 0.05) and capable of distinguishing individual HD patients with history of psychosis from those without a history of psychosis with prediction accuracy around 71-73%. The most relevant variables were similar to those found in the conventional analyses. Conclusions: Psychiatric and behavioral symptoms as well as poorer cognitive performance were related to psychosis in HD. In addition, psychosis was associated with lower number of CAG repeats and younger age at clinical diagnosis of HD, suggesting that these patients may represent a unique phenotype in the HD spectrum.

SUBMITTER: Rocha NP

PROVIDER: S-EPMC6232301 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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The Clinical Picture of Psychosis in Manifest Huntington's Disease: A Comprehensive Analysis of the Enroll-HD Database.

Rocha Natalia P NP Mwangi Benson B Gutierrez Candano Carlos A CA Sampaio Cristina C Furr Stimming Erin E Teixeira Antonio L AL

Frontiers in neurology 20181106

Background: Psychotic symptoms have been under-investigated in Huntington's disease (HD) and research is needed in order to elucidate the characteristics linked to the unique phenotype of HD patients presenting with psychosis. Objective: To evaluate the frequency and factors associated with psychosis in HD. Methods: Cross-sectional study including manifest individuals with HD from the Enroll-HD database. Both conventional statistical analysis (Stepwise Binary Logistic Regres ...[more]

PMID: 30459704

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Project description:Although the association between cytosine-adenine-guanine (CAG) repeat length and age at onset of Huntington's disease is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counselling. We compared various measures for tracking progression and predicting conversion to manifest Huntington's disease.In this prospective observational study, we assessed the ability of 40 measures in five domains (motor, cognitive, psychiatric, functional, and imaging) to predict time to motor diagnosis of Huntington's disease, accounting for CAG repeat length, age, and the interaction of CAG repeat length and age. Eligible participants were individuals from the PREDICT-HD study (from 33 centres in six countries [USA, Canada, Germany, Australia, Spain, UK]) with the gene mutation for Huntington's disease but without a motor diagnosis (a rating below 4 on the diagnostic confidence level from the 15-item motor assessment of the Unified Huntington's Disease Rating Scale). Participants were followed up between September, 2002, and July, 2014. We used joint modelling of longitudinal and survival data to examine the extent to which baseline and change of measures analysed separately was predictive of CAG-adjusted age at motor diagnosis.1078 individuals with a CAG expansion were included in this analysis. Participants were followed up for a mean of 5·1 years (SD 3·3, range 0·0-12·0). 225 (21%) of these participants received a motor diagnosis of Huntington's disease during the study. 37 of 40 cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors were in the motor, imaging, and cognitive domains: an increase of one SD in total motor score (motor domain) increased the risk of a motor diagnosis by 3·07 times (95% CI 2·26-4·16), a reduction of one SD in putamen volume (imaging domain) increased risk by 3·32 times (2·37-4·65), and a reduction of one SD in Stroop word score (cognitive domain) increased risk by 2·32 times (1·88-2·87).Prediction of diagnosis of Huntington's disease can be improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest Huntington's disease should inform discussions about guidelines for diagnosis, prognosis, and counselling, and might be useful in guiding the selection of participants and outcome measures for clinical trials.US National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.

Project description:BackgroundThe study of complex neurodegenerative diseases is moving away from hypothesis-driven biological methods toward large scale multimodal approaches, requiring standardized collaborative efforts. Enroll-HD exemplifies such an integrated clinical research platform, designed and implemented to meet the research and clinical needs of Huntington's disease (HD). The aim of this study was to describe the unique organization of Enroll-HD and report baseline data analyses of its core study.MethodsThe Enroll-HD platform incorporates electronic data capture, biosampling, and a longitudinal observational study spanning four continents (ClinicalTrials.gov Identifier: NCT01574053). The primary study population includes HD gene expansion carriers (HDGECs; CAG expansion ≥36), subdivided into manifest/premanifest HD. The control population consists of genotype-negative first-degree relatives and family controls not genetically related. The study includes 10 core clinical assessments covering motor, cognitive, and behavioral domains.ResultsThis data set comprises 1,534 participants (HDGEC = 1,071; controls = 463). Participant retention was high; 42 participants prematurely withdrew from the study. Mean ± standard deviation SD CAG repeat size was 43.5 ± 3.5 for HDGECs and 19.8 ± 3.4 for controls. Motor and behavioral assessments identified numerical differences between controls and HDGECs (manifest > premanifest > controls). Functional and independence assessments were generally similar for the premanifest and control groups with overlap in range of scores obtained. For the majority of cognitive tests, there were large differences between participants with manifest HD and all other groups.ConclusionsThese first data from the Enroll-HD clinical research platform demonstrate the maturity and potential of the platform in collecting high-quality, clinically relevant data. Future data sets will be substantially larger as the platform expands longitudinally and regionally.

Project description:BACKGROUND: Huntington's disease (HD) is a fatal progressive neurodegenerative disorder caused by the expansion of the polyglutamine repeat region in the huntingtin gene. Although the disease is triggered by the mutation of a single gene, intensive research has linked numerous other genes to its pathogenesis. To obtain a systematic overview of these genes, which may serve as therapeutic targets, CHDI Foundation has recently established the HD Research Crossroads database. With currently over 800 cataloged genes, this web-based resource constitutes the most extensive curation of genes relevant to HD. It provides us with an unprecedented opportunity to survey molecular mechanisms involved in HD in a holistic manner. METHODS: To gain a synoptic view of therapeutic targets for HD, we have carried out a variety of bioinformatical and statistical analyses to scrutinize the functional association of genes curated in the HD Research Crossroads database. In particular, enrichment analyses were performed with respect to Gene Ontology categories, KEGG signaling pathways, and Pfam protein families. For selected processes, we also analyzed differential expression, using published microarray data. Additionally, we generated a candidate set of novel genetic modifiers of HD by combining information from the HD Research Crossroads database with previous genome-wide linkage studies. RESULTS: Our analyses led to a comprehensive identification of molecular mechanisms associated with HD. Remarkably, we not only recovered processes and pathways, which have frequently been linked to HD (such as cytotoxicity, apoptosis, and calcium signaling), but also found strong indications for other potentially disease-relevant mechanisms that have been less intensively studied in the context of HD (such as the cell cycle and RNA splicing, as well as Wnt and ErbB signaling). For follow-up studies, we provide a regularly updated compendium of molecular mechanism, that are associated with HD, at http://hdtt.sysbiolab.eu Additionally, we derived a candidate set of 24 novel genetic modifiers, including histone deacetylase 3 (HDAC3), metabotropic glutamate receptor 1 (GRM1), CDK5 regulatory subunit 2 (CDK5R2), and coactivator 1ß of the peroxisome proliferator-activated receptor gamma (PPARGC1B). CONCLUSIONS: The results of our study give us an intriguing picture of the molecular complexity of HD. Our analyses can be seen as a first step towards a comprehensive list of biological processes, molecular functions, and pathways involved in HD, and may provide a basis for the development of more holistic disease models and new therapeutics.

Dataset Information

The Clinical Picture of Psychosis in Manifest Huntington's Disease: A Comprehensive Analysis of the Enroll-HD Database.

Publications

The Clinical Picture of Psychosis in Manifest Huntington's Disease: A Comprehensive Analysis of the Enroll-HD Database.

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