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Updated: Feb 13, 2026

Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
Published on: July 6, 2022
COMPREHENSIVE ANALYSIS OF MURINE GAIT DURING SKELETAL MATURATION
Cameron X Villarreal1, Amanda Thayer2, Jeremy A Hampton1
1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN.
None:
Gait is a highly coordinated motor behavior that integrates musculoskeletal and neuromotor control. Analysis of gait parameters is widely used in murine studies as functional biomarkers of locomotor development and disease progression. However, there has yet to be a comprehensive characterization of how gait matures during the rapid growth preceding skeletal maturity, an age range often used in preclinical gait studies. We analyzed gait longitudinally in healthy C57BL/6J mice from 6 to 16 weeks of age, timed to the onsets of sexual and skeletal maturity, respectively. More than 30 gait parameters were quantified weekly and organized into functional groupings reflecting growth, stride, coordination, paw placement, propulsion, and parameter variability. Through a combination of univariate and multivariate analyses, we identified robust age- and sex-based differences across these functional groupings of individual gait parameters. Univariate analysis revealed that many age-associated parameters exhibit a ramp-to-plateau trajectory in the 6- to 16-week age range, with many individual gait parameters plateauing within 8-10 weeks of age. Through multivariate analysis, we identified significant age- and sex-effects on principal components that aligned to functional groupings of gait parameters. Together, these results demonstrate that functional groupings of gait parameters tend to plateau at different phases of skeletal maturation and are differentially impacted by sex, also highlighting the importance of interpreting both univariate and multivariate analysis in longitudinal and comprehensive gait analysis. Understanding these patterns of gait maturation can inform better murine gait study design and more nuanced data analysis that considers potential interactions with age and sex effects.
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