Locomotor analysis identifies early compensatory changes during disease progression and subgroup classification in a mouse model of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis is a motoneuron degenerative disease that is challenging to diagnose and presents with considerable variability in survival. Early identification and enhanced understanding of symptomatic patterns could aid in diagnosis and provide an avenue for monitoring disease progression. Use of the mSOD1G93A mouse model provides control of the confounding environmental factors and genetic heterogeneity seen in amyotrophic lateral sclerosis patients, while investigating underlying disease-induced changes. In the present study, we performed a longitudinal behavioral assessment paradigm and identified an early hindlimb symptom, resembling the common gait abnormality foot drop, along with an accompanying forelimb compensatory mechanism in the mSOD1G93A mouse. Following these initial changes, mSOD1 mice displayed a temporary hindlimb compensatory mechanism resembling an exaggerated steppage gait. As the disease progressed, these compensatory mechanisms were not sufficient to sustain fundamental locomotor parameters and more severe deficits appeared. We next applied these initial findings to investigate the inherent variability in B6SJL mSOD1G93A survival. We identified four behavioral variables that, when combined in a cluster analysis, identified two subpopulations with different disease progression rates: a fast progression group and a slow progression group. This behavioral assessment paradigm, with its analytical approaches, provides a method for monitoring disease progression and detecting mSOD1 subgroups with different disease severities. This affords researchers an opportunity to search for genetic modifiers or other factors that likely enhance or slow disease progression. Such factors are possible therapeutic targets with the potential to slow disease progression and provide insight into the underlying pathology and disease mechanisms.

Identification of B6SJL mSOD1(G93A) mouse subgroups with different disease progression rates.

Disease progression rates among patients with amyotrophic lateral sclerosis (ALS) vary greatly. Although the majority of affected individuals survive 3-5 years following diagnosis, some subgroups experience a more rapidly progressing form, surviving less than 1 year, and other subgroups experience slowly progressing forms, surviving nearly 50 years. Genetic heterogeneity and environmental factors pose significant barriers in investigating patient progression rates. Similar to the case for humans, variation in survival within the mSOD1 mouse has been well documented, but different progression rates have not been investigated. The present study identifies two subgroups of B6SJL mSOD1(G93A) mice with different disease progression rates, a fast progression group (FPG) and slow progression group, as evidenced by differences in the rate of motor function decline. In addition, increased disease-associated gene expression within the FPG facial motor nucleus confirmed the presence of a more severe phenotype. We hypothesize that a more severe disease phenotype could be the result of 1) an earlier onset of axonal disconnection with a consistent degeneration rate or 2) a more severe or accelerated degenerative process. We performed a facial nerve transection axotomy in both mSOD1 subgroups prior to disease onset as a method to standardize the axonal disconnection. Instead of leading to comparable gene expression in both subgroups, this standardization did not eliminate the severe phenotype in the FPG facial nucleus, suggesting that the FPG phenotype is the result of a more severe or accelerated degenerative process. We theorize that these mSOD1 subgroups are representative of the rapid and slow disease phenotypes often experienced in ALS.

The need for speed in rodent locomotion analyses.

Locomotion analysis is now widely used across many animal species to understand the motor defects in disease, functional recovery following neural injury, and the effectiveness of various treatments. More recently, rodent locomotion analysis has become an increasingly popular method in a diverse range of research. Speed is an inseparable aspect of locomotion that is still not fully understood, and its effects are often not properly incorporated while analyzing data. In this hybrid manuscript, we accomplish three things: (1) review the interaction between speed and locomotion variables in rodent studies, (2) comprehensively analyze the relationship between speed and 162 locomotion variables in a group of 16 wild-type mice using the CatWalk gait analysis system, and (3) develop and test a statistical method in which locomotion variables are analyzed and reported in the context of speed. Notable results include the following: (1) over 90% of variables, reported by CatWalk, were dependent on speed with an average R(2) value of 0.624, (2) most variables were related to speed in a nonlinear manner, (3) current methods of controlling for speed are insufficient, and (4) the linear mixed model is an appropriate and effective statistical method for locomotion analyses that is inclusive of speed-dependent relationships. Given the pervasive dependency of locomotion variables on speed, we maintain that valid conclusions from locomotion analyses cannot be made unless they are analyzed and reported within the context of speed.