Locomotor activity as an effective measure of the severity of inflammatory arthritis in a mouse model

Author:

Doucet Mélina R.,Laevski Angela M.,Doiron Jérémie A.,Boudreau Luc H.ORCID,Surette Marc E.ORCID

Abstract

Objective Mouse models are valuable in preclinical studies of inflammatory arthritis. However, current methods for measuring disease severity or responses to treatment are not optimal. In this study a smart cage system using multiple sensors to measure locomotor activity was evaluated in the K/BxN serum transfer model of inflammatory arthritis. Methods Arthritis was induced in C57BL/6 mice with injections of K/BxN serum. Clinical index and ankle thickness were measured for 14 days. Locomotor activity was measured in smart cages for 23 h periods on Days 0, 7, and 13. The same measurements were taken in mice consuming diets supplemented or not with fish oil to evaluate a preventative treatment. Results Initiation, peak and resolution phases of disease could be measured with the smart cages. Locomotor activity including speed, travel distance, number of active movements and rear movements were all significantly lower on Days 7–8 of illness (peak) compared to Days 0 and 13–14 (resolution) (one-way repeated measures analyses, p<0.05). The clinical index and ankle thickness measurements did not capture differences between dietary groups. Significantly increased activity was measured in most of the locomotor parameters in the fish oil group compared to the control mice at both Days 8 and 14 (2-way repeated measures ANOVA, p<0.05). Conclusion The measurement of locomotor activity provided a more detailed evaluation of the impact of inflammatory arthritis on animal well-being and mobility than that provided by measuring clinical index and ankle thickness, and could be a valuable tool in preclinical studies of inflammatory arthritis.

Funder

Canadian Institutes of Health Research

Natural Sciences and Engineering Research Council of Canada

New Brunswick Innovation Foundation

Publisher

Public Library of Science (PLoS)

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