This repository contains the R code for the human studies analysis described in:
McKinnon, S., Qiang, Z., Keerie, A., Wells, T., Shaw, P. J., Alix, J. J. P., & Mead, R. J. (2025). Maximizing the translational potential of neurophysiology in amyotrophic lateral sclerosis: a study on compound muscle action potentials. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 26(3–4), 322–330. https://doi.org/10.1080/21678421.2024.2448540
Abstract
Mouse models of amyotrophic lateral sclerosis (ALS) enable testing of novel therapeutic interventions. However, treatments that have extended survival in mice have often failed to translate into human benefit in clinical trials. Compound muscle action potentials (CMAPs) are a simple neurophysiological test that measures the summation of muscle fiber depolarization in response to maximal stimulation of the innervating nerve. CMAPs can be measured in both mice and humans and decline with motor axon loss in ALS, making them a potential translational read-out of disease progression. We assessed the translational potential of CMAPs and ascertained time points when human and mouse data aligned most closely. We extracted data from 18 human studies and compared with results generated from SOD1G93A and control mice at different ages across different muscles. The relative CMAP amplitude difference between SOD1G93A and control mice in tibialis anterior (TA) and gastrocnemius muscles at 70 days of age was most similar to the relative difference between baseline ALS patient CMAP measurements and healthy controls in the abductor pollicis brevis (APB) muscle. We also found that the relative decline in SOD1G93A TA CMAP amplitude between 70 and 140 days was similar to that observed in 12 month human longitudinal studies in APB. Our findings suggest CMAP amplitudes can provide a “translational window”, from which to make comparisons between the SOD1G93A model and human ALS patients. CMAPs are easy to perform and can help determine the most clinically relevant starting/end points for preclinical studies and provide a basis for predicting potential clinical effect sizes.
18 September 2023