Multi-Modal Digital Monitoring of Disease Symptoms Huntington's Disease

Overview

The objective of the study is to validate the use of wearable sensors and digital health technologies for monitoring disease activity in Huntington's Disease (HD). Healthy subjects, as well as subjects with documented diagnosis of HD will be screened and recruited at University of Rochester Medical Center and Vanderbilt University Medical Center to participate in this 12-month observational study. There will be a total of 5 visits every approximately 3 months. In each study visit, participants will complete several Patient Reported Outcomes (PROs), Clinical Reported Outcomes, complete a series of Digital Assessments (Speech, Cognitive, Motor, and Finger Tapping). Participants will be provided with a pendant, wrist, and ankle sensors to monitor their daily physical activities for 7 days after each study visit. Participants will also be provided with a tablet to complete digital assessments (Speech, Cognitive, Motor, and Finger Tapping) on monthly basis at home.

HD is a devastating inherited neurological disorder that causes progressive nerve degeneration in the brain. HD is characterized by multifaceted symptomatology including motor, cognitive, and psychiatric symptoms, which begin insidiously and progress over many years. The principal means of measuring gross motor and speech impairment in HD is the Unified Huntington's Disease Rating Scale (UHDRS). Although valuable, the scale is subjective and categorical and requires significant training to administer correctly. Quantitative motor (Q-motor) tests have helped reduce subjectivity and improve sensitivity of motor assessments in HD. Q-Motor assessments have demonstrated utility in tracking longitudinal progression of motor impairment and as a supplemental measure in clinical trials. Likewise, force-sensitive insoles, video motion analysis systems, and pressure-sensitive walking mats have been utilized to objectively measure impaired gait in HD. However, these gait-measuring technologies and Q-Motor assessments must be administered in clinic by trained personnel. Similarly, the Montreal Cognitive assessment (MoCA) and Mini-mental State Examination, are often used to measure cognitive decline. However, these tests need to be administered by trained professionals and have limited ability to detect subtle changes in cognitive performance over time. Furthermore, measures are conducted infrequently, typically in a clinic setting, and may not be an accurate representation of an individual's true cognitive status. There is currently no cure which can halt, slow or reverse the progression of the disease. The key challenge in development of new therapeutics in HD and other neurological disorders is that the current way of assessing the disease is largely subjective and requires in-person, in-clinic assessments. Digital measures, like the proposed solution can provide objective, real-world assessments of how individuals are functioning. Wearable sensors and digital health technologies that can detect motor, speech, and cognitive abnormalities can provide insight into the phase of clinical disease onset. Given that gene positive premanifest stage of HD can take up to several years before the onset of symptomatic disease, the subtle changes in these biomarkers in the early stage of HD provide an opportune window to apply disease-modifying treatment that could potentially slow down or prevent the progression of the disease Thus, a system that can objectively, sensitively, and frequently monitor multiple clinical domains (motor, speech and cognitive function) is necessary to understand the pattern of evolving motor, speech and cognitive abnormalities in individuals with prodromal HD, and for identification of endpoint measures for therapeutic trials. This observational study will follow participants over 12 months. Healthy subjects, as well as subjects with documented diagnosis of HD will be screened and recruited at University of Rochester Medical Center and Vanderbilt University Medical Center. In addition to standard clinical assessments, the study will leverage BioDigit HD to collect wearable and digital health data from participants in at the study site and their home environments. A key objective of the project is to measure changes in disease symptoms using patient reported outcomes (PROs), clinical reported outcomes, and digital measures in individuals with HD.