A. Zimprich, M.A. Östereicher, L. Becker, P. Dirscherl, L. Ernst, H. Fuchs, V. Gailus-Durner, L, Garrett, F. Giesert, L. Glasl, A. Hummel, J. Rozman, M. Hrabeˇ de Angelis, D. Vogt-Weisenhorn, W. Wurst, S.M. Hölterb,
Institute of Developmental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
Journal of Neuroscience Methods
Background: Generation and phenotyping of mutant mouse models continues to increase along with the search for the most efficient phenotyping tests. Here we asked if a combination of different locomotor tests is necessary for comprehensive locomotor phenotyping, or if a large data set from an automated gait analysis with the CatWalk system would suffice.
New method: First we endeavored to meaningfully reduce the large CatWalk data set by Principal Com-ponent Analysis (PCA) to decide on the most relevant parameters. We analyzed the influence of sex, body weight, genetic background and age. Then a combination of different locomotor tests was analyzed to investigate the possibility of redundancy between tests.
Result: The extracted 10 components describe 80% of the total variance in the CatWalk, characterizing different aspects of gait. With these, effects of CatWalk version, sex, body weight, age and genetic back-ground were detected. In addition, the PCA on a combination of locomotor tests suggests that these are independent without significant redundancy in their locomotor measures.
Comparison with existing methods: The PCA has permitted the refinement of the highly dimensional Cat- Walk (and other tests) data set for the extraction of individual component scores and subsequent analysis.
BIOSEB Instruments Used:
Aron Test or Four Plates Test (LE830),Grip strength test (BIO-GS3),Rotarod (BX-ROD)