Toni Ahtoniemi, Ph.D. Charles River Discovery Research Services

Suggested guidelines on a novel way of translating central nervous system disease from mouse to men.

Fine motor skills, such as finger-tapping rhythm and rate, are applied for early diagnosis of many diseases, such as Huntington’s disease. Similarly, functional motor recovery has been assayed with stroke patients to quantify movement smoothness in patients recovering from stroke (Rohrer et al., 2002).

The same readouts cannot be used for mice, but what if there was a tool to analyze fine motor skill characteristics for a model of central nervous system disease (CNS)? Recently, researchers have been experimenting with a novel, automated, high-precision, kinematic movement analysis system that can be utilized to detect subtle phenotype changes, with earlier and more sensitive detection compared to traditional movement analysis (Zörner et al., 2010). The system provides a more comprehensive study of fine motor performance and motor deficits than previous methods, which is necessary to fully model the aspects of human CNS disease in preclinical models.

In kinematic analysis, movements of relevant body parts, such as limb joints, trunk and tail, are recorded using a high-speed camera from the bottom and sides simultaneously. This allows correlation of all body parts so that one can establish a complete profile of the animal’s motor abilities. Kinematic analysis applies not only to the study of fine motor defect development in rodent models of CNS and other motor impairment diseases, but also may offer a sensitive tool to investigate efficacy of therapeutic approaches or to study subtle motor skill changes, similar to how human CNS disease is studied.

If you plan on using this system…

  1. Know your model well. Kinematic movement can be used to detect subtle phenotype changes, with earlier and more sensitive detection compared to traditional movement analysis. However, choosing the right time points will be critical in achieving the best outcome, which is why it is important to take the model specifics into account, especially the age and disease progression of the phenotype, as parameters differ from model to model.
  2. Take note of speed and direction. A kinematic gait analysis allows you to correlate all body parts so that one can establish a complete profile of the animal’s motor abilities. By examining the speed and direction of movement, you add value to the simultaneous analysis of various limb joints, body parts, and joint angles as well as coordination.
  3. Carefully select your markers. The higher sensitivity of these tests makes it possible to detect even the most subtle changes in preclinical models that otherwise may not show a phenotype detectable using gross motor assays. However, the selection of markers will depend on the model and will vary from model to model.
  4. Choose the right time to test. Kinematic analysis offers advantages in behavioral pharmacology in that the higher sensitivity of the system widens the therapeutic window of opportunity for pharmacological testing. The higher throughput and automation also makes it possible to use the system as a sensitive screening tool. But selecting the correct time to test after dosing is critical because different compounds have different pharmacokinetic properties for absorption, distribution, metabolism, and excretion. So knowing the properties of a compound and the time when maximum concentrations are reached in the system or brain is vital for seeing the effects.

Toni Ahtoniemi, who obtained his Ph.D. in 2008 on CNS-related disease models, is a project manager with Charles River Discovery Research Services, based in Finland. This article was adapted from a post on Charles River’s scientific blog, Eureka.

Rohrer B, Fasoli S, Krebs HI, Hughes R, Volpe B, Frontera WR, Stein J, Hogan N. Movement smoothness changes during stroke recovery. The Journal of Neuroscience, 2002 Sep 15;22(18):8297-304.
Zörner B, Filli L, Starkey ML, Gonzenbach R, Kasper H, Röthlisberger M, Bolliger M, Schwab ME. Profiling locomotor recovery: comprehensive quantification of impairments after CNS damage in rodents. Nature Methods, 2010 Sep;7(9):701-8.

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