Huntington's Disease Biobank: Advancing Remote Monitoring and Deep Phenotyping

This observational study aims to identify novel biomarkers of disease onset and progression in Huntington's disease by integrating remote monitoring with fluid biomarkers. Using video-based computer vision and mobile app-based cognitive assessments combined with machine learning algorithms, we aim to develop markers that can be used by Huntington's disease patients at home. Using machine learning to analyze videos of movement will capture the movements with an accuracy that will be as good as seeing an expert neurologist. These individualized markers can be followed over time to evaluate symptoms onset and change. The study will track disease progression and correlate these digital markers with changes in plasma and cerebrospinal fluid. The ultimate goal is to advance biomarker discovery and therapeutic development for Huntington's disease. The study includes one in-person visit per year. A remote visit via Zoom or Facetime (15 min) every three months to record videos of movement. We can also share cutting-edge wristbands and a mobile phone app.