To quantify change in symptoms over time using home-based gait and mobility assessments from a prospective natural history study of patients with adrenomyeloneuropathy (AMN).

AMN is a rare neurodegenerative disorder of the brain and spinal cord affecting adults with mutations in the ABCD1 gene. Quantification of AMN disease progression is challenging, owing to phenotypic and disease progression variability. One solution to address this is to measure traditional functional motor tasks more frequently using wireless motion sensors during clinic and remote visits. Here, we assess the feasibility and test-retest reliability of motion sensors over 1 year, and relate it to standard in-clinic measurements.

CYGNET (NCT05008874) is an ongoing prospective, multicenter, observational study that will enroll up to 80 male patients with AMN and follow them for ≥2 years with annual clinic visits and quarterly remote visits. Gait and balance assessments include postural body sway parameters and traditional functional motor tasks. In clinic, standard methods are used to calculate time and distance. Wireless motion sensors enable quantification of the temporal–spatial components of gait assessments both in the clinic and at home.

Over 50 patients between 18–69 years of age with Expanded Disability Status Score 1-6.5 have been enrolled. Correlation between wireless sensor and operator-assessed mobility measures collected at baseline clinic visit ranged from 0.746 (Timed Up-and-Go) to 0.998 (2-Minute Walk Test). In-clinic and home data collected over 1 year utilizing wireless technology will be presented for the first 20 patients enrolled.

Use of wireless motion sensors can provide an objective and sensitive assessment of gait, stability, balance and functional abilities of an individual both in their natural and the clinical environment. These data will help inform the design of future clinical trials evaluating potential therapeutics, including gene therapy for AMN.

Funding: This study was sponsored by SwanBio Therapeutics.