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Using wearable wireless technology to understand the natural history of adrenomyeloneuropathy in both clinic and home settings: 1-year follow-up in the CYGNET study

C. Bergner, W. Koehler, J. Bonkowsky, C. Stephen, F. Eichler, L. Glenn, M. Engelen (Leipzig, Germany)

Meeting: 2023 International Congress

Abstract Number: 1752

Keywords: Familial neurodegenerative diseases, Gait disorders: Clinical features, Spasticity: Clinical features

Category: Technology

Objective: To assess the feasibility of using wearable wireless motion sensors to quantify disease progression in men with adrenomyeloneuropathy (AMN) enrolled in the CYGNET natural history study.

Background: AMN is an inherited, progressive neurodegenerative disease resulting from pathogenic variants in ABCD1. Characterized by spastic paraparesis and sensory ataxia with adulthood onset, AMN leads to loss of mobility, incontinence, pain, and sexual dysfunction. Phenotypic and visit-to-visit variability confound efforts to understand the natural history. Use of technology to allow frequent home-based assessments of mobility and physical activity levels would offer a window into real-world function and help to elucidate disease progression over time. Wearable activity monitors allow passive and continuous data collection, while minimizing patient burden.

Method: The ongoing CYGNET study (NCT05008874) is a prospective, multicenter, observational investigation of disease progression over ≥2 years in adult men with AMN and an Expanded Disability Status Score of 1–6.5. Regular in-clinic and at-home gait and balance assessments are performed, including timed functional tasks (TFTs) and postural body sway parameters, using wearable wireless motion sensors. Activity levels are monitored using passive data collection via an actigraph watch. Here, we report compliance with use of the wearable device and characterize the study population on derived outcomes over 1 year of follow-up.

Results: Baseline characteristics will be presented for all enrolled patients (N = 65). We have previously reported that in-clinic baseline mobility measures (TFTs) gathered in a subset of these patients using wireless motion sensors correlate with those gathered via standard operator assessments, with correlation coefficients of 0.746 (Timed Up-and-Go) to 0.998 (2-Minute Walk Test). Wear compliance data will be presented, as well as exploratory measures including activity levels and sleep parameters derived from actimeter data.

Conclusion: Assessment of patient activity and function will help us to better understand the natural history and impact of AMN. When evaluating potential therapeutic options for AMN in the future, these findings will help inform clinical trial design.

To cite this abstract in AMA style:

C. Bergner, W. Koehler, J. Bonkowsky, C. Stephen, F. Eichler, L. Glenn, M. Engelen. Using wearable wireless technology to understand the natural history of adrenomyeloneuropathy in both clinic and home settings: 1-year follow-up in the CYGNET study [abstract]. Mov Disord. 2023; 38 (suppl 1). https://www.mdsabstracts.org/abstract/using-wearable-wireless-technology-to-understand-the-natural-history-of-adrenomyeloneuropathy-in-both-clinic-and-home-settings-1-year-follow-up-in-the-cygnet-study/. Accessed May 19, 2025.
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