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Data Analytics from Enroll-HD, a Global Clinical Research Platform for Huntington's Disease
Georg B Landwehrmeyer1,2, Cheryl J Fitzer-Attas2, Joseph D Giuliano2
1Department of Neurology University of Ulm Ulm Germany.
Insights
Enroll-HD, a global Huntington's disease (HD) research platform, collected baseline data from 1,534 participants. Findings show distinct differences in motor, behavioral, and cognitive assessments between HD gene expansion carriers and controls.
Area of Science:
- Neuroscience and Genetics
- Clinical Research Methodology
- Neurodegenerative Disease Studies
Background:
- Complex neurodegenerative diseases necessitate large-scale, multimodal research approaches.
- Enroll-HD is an integrated clinical research platform designed for Huntington's disease (HD).
- This study describes the organization of Enroll-HD and presents baseline data.
Purpose of the Study:
- To describe the unique organization of the Enroll-HD platform.
- To report baseline data analyses from the Enroll-HD core study.
- To establish a foundation for future longitudinal and regional data collection.
Main Methods:
- Utilized electronic data capture and biosampling across four continents.
- Included HD gene expansion carriers (HDGECs) and control groups (genotype-negative relatives, unrelated family controls).
- Employed 10 core clinical assessments covering motor, cognitive, and behavioral domains.
Main Results:
- Data from 1,534 participants (1,071 HDGECs, 463 controls) were analyzed.
- Significant differences observed in motor and behavioral assessments across manifest HD, premanifest HD, and controls.
- Large cognitive differences were noted between manifest HD participants and all other groups.
Conclusions:
- The Enroll-HD platform demonstrates maturity in collecting high-quality, clinically relevant data.
- Baseline data highlight the platform's potential for advancing HD research.
- Future data sets are expected to be larger as the platform expands globally.
Background:
The 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.
Methods:
The 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.
Results:
This 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.
Conclusions:
These 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.