A precision medicine approach to identify walking phenotypes and rehabilitation targets after injury

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Walking phenotypes are different between people, to the point that we can recognize people by the way they walk. Despite these evident individual differences, researchers will obtain averages across a specific population, such as healthy individuals or individuals with walking impairments due to musculoskeletal or neurological injury, to derive group-level descriptors of walking function. These averages, which eliminate important between-individual differences, inform rehabilitation research studies that prescribe the same intervention for all participants. Precision Medicine is an innovative approach put forth by the NIH to consider individual patients’ biological, environmental, and lifestyle differences to inform the prescription of treatment. Despite the stronghold and success that precision medicine has had in pharmaco-genomics and oncology, it has yet to be implemented to fine-tune interventions for walking behaviors. Our goal is to identify individual- specific walking phenotypes and their underlying joint and muscle level impairments to effectively guide clinical decision-making long-term. To achieve this goal, we will use data analysis pipelines that use machine learning to leverage the wealth of clinical and laboratory data used to characterize function after injury. This approach will allow us to identify the specific muscles and joints responsible for each walking phenotype, which can serve as rehabilitation intervention targets. Our KL2 funded project took the first step in this direction: using stroke survivors as a model of pathological walking behavior, we identified four distinct walking phenotypes, which point at deficits in either walking speed, balance, propulsion, or shock absorption. What remains to be determined are the individual joints and muscles responsible for these distinctive walking phenotypes (Aim 1), whether these impairments can be detected early after injury to develop treatment strategies in the early stages (Aim 2), and whether clinical measures within the International Classification of Functioning, Disability, and Health, can be used to draw inference on mechanisms of impairment (Aim 3), allowing easy implementation of our findings in clinical settings. We will achieve these aims via secondary analyses of longitudinal data collected as part of our KL2 project to identify the joint and muscle impairments that characterize each walking phenotype. We will harness our results in an R01 proposal to assess the effects of generalized vs. phenotype-specific prescription of walking interventions, using the intervention targets identified here. Identification of individualized intervention targets could improve the efficacy of walking interventions and more generally improve mobility, and associated participation, health, and well-being, all aligned with the NIH mission.