Inertial sensing of step kinematics in ambulatory patients with ALS and related motor neuron diseases

Spinal cord neurone loss and foot placement changes in a rat knock-in model of amyotrophic lateral sclerosis Type 8

Amyotrophic lateral sclerosis is an age-dependent cell type-selective degenerative disease. Genetic studies indicate that amyotrophic lateral sclerosis is part of a spectrum of disorders, ranging from spinal muscular atrophy to frontotemporal dementia that share common pathological mechanisms. Amyotrophic lateral sclerosis Type 8 is a familial disease caused by mis-sense mutations in VAPB. VAPB is localized to the cytoplasmic surface of the endoplasmic reticulum, where it serves as a docking point for cytoplasmic proteins and mediates inter-organelle interactions with the endoplasmic reticulum membrane. A gene knock-in model of amyotrophic lateral sclerosis Type 8 based on the VapBP56S mutation and VapB gene deletion has been generated in rats. These animals display a range of age-dependent phenotypes distinct from those previously reported in mouse models of amyotrophic lateral sclerosis Type 8. A loss of motor neurones in VapBP56S/+ and VapBP56S/P56S animals is indicated by a reduction in the number of large choline acetyl transferase-staining cells in the spinal cord. VapB-/- animals exhibit a relative increase in cytoplasmic TDP-43 levels compared with the nucleus, but no large protein aggregates. Concomitant with these spinal cord pathologies VapBP56S/+ , VapBP56S/P56S and VapB-/- animals exhibit age-dependent changes in paw placement and exerted pressures when traversing a CatWalk apparatus, consistent with a somatosensory dysfunction. Extramotor dysfunction is reported in half the cases of motor neurone disease, and this is the first indication of an associated sensory dysfunction in a rodent model of amyotrophic lateral sclerosis. Different rodent models may offer complementary experimental platforms with which to understand the human disease.

The use of digital outcome measures in clinical trials in rare neurological diseases: a systematic literature review

Developing drugs for rare diseases is challenging, and the precision and objectivity of outcome measures is critical to this process. In recent years, a number of technologies have increasingly been used for remote monitoring of patient health. We report a systematic literature review that aims to summarize the current state of progress with regard to the use of digital outcome measures for real-life motor function assessment of patients with rare neurological diseases. Our search of published literature identified 3826 records, of which 139 were included across 27 different diseases. This review shows that use of digital outcome measures for motor function outside a clinical setting is feasible and employed in a broad range of diseases, although we found few outcome measures that have been robustly validated and adopted as endpoints in clinical trials. Future research should focus on validation of devices, variables, and algorithms to allow for regulatory qualification and widespread adoption.

A systematic review of digital technology to evaluate motor function and disease progression in motor neuron disease

Amyotrophic lateral sclerosis (ALS) is the most common subtype of motor neuron disease (MND). The current gold-standard measure of progression is the ALS Functional Rating Scale-Revised (ALS-FRS(R)), a clinician-administered questionnaire providing a composite score on physical functioning. Technology offers a potential alternative for assessing motor progression in both a clinical and research capacity that is more sensitive to detecting smaller changes in function. We reviewed studies evaluating the utility and suitability of these devices to evaluate motor function and disease progression in people with MND (pwMND). We systematically searched Google Scholar, PubMed and EMBASE applying no language or date restrictions. We extracted information on devices used and additional assessments undertaken. Twenty studies, involving 1275 (median 28 and ranging 6-584) pwMND, were included. Sensor type included accelerometers (n = 9), activity monitors (n = 4), smartphone apps (n = 4), gait (n = 3), kinetic sensors (n = 3), electrical impedance myography (n = 1) and dynamometers (n = 2). Seventeen (85%) of studies used the ALS-FRS(R) to evaluate concurrent validity. Participant feedback on device utility was generally positive, where evaluated in 25% of studies. All studies showed initial feasibility, warranting larger longitudinal studies to compare device sensitivity and validity beyond ALS-FRS(R). Risk of bias in the included studies was high, with a large amount of information to determine study quality unclear. Measurement of motor pathology and progression using technology is an emerging, and promising, area of MND research. Further well-powered longitudinal validation studies are needed.

Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia

With disease-modifying approaches under evaluation in ataxia-telangiectasia and other ataxias, there is a need for objective and reliable biomarkers of free-living motor function. In this study, we test the hypothesis that metrics derived from a single wrist sensor worn at home provide accurate, reliable, and interpretable information about neurological disease severity in children with A-T.

A total of 15 children with A-T and 15 age- and sex-matched controls wore a sensor with a triaxial accelerometer on their dominant wrist for 1 week at home. Activity intensity measures, derived from the sensor data, were compared with in-person neurological evaluation on the Brief Ataxia Rating Scale (BARS) and performance on a validated computer mouse task.

Children with A-T were inactive the same proportion of each day as controls but produced more low intensity movements (p < 0.01; Cohen’s d = 1.48) and fewer high intensity movements (p < 0.001; Cohen’s d = 1.71). The range of activity intensities was markedly reduced in A-T compared to controls (p < 0.0001; Cohen’s d = 2.72). The activity metrics correlated strongly with arm, gait, and total clinical severity (r: 0.71–0.87; p < 0.0001), correlated with specific computer task motor features (r: 0.67–0.92; p < 0.01), demonstrated high reliability (r: 0.86–0.93; p < 0.00001), and were not significantly influenced by age in the healthy control group.

Motor activity metrics from a single, inexpensive wrist sensor during free-living behavior provide accurate and reliable information about diagnosis, neurological disease severity, and motor performance. These low-burden measurements are applicable independent of ambulatory status and are potential digital behavioral biomarkers in A-T.