02 Feb 2007

Measuring behavior in experimental animals is a labor-intensive, imperfect science, and one upon which AD researchers depend heavily. With the advent of more and more mouse models, behavioral testing will only gain in importance for both research and preclinical testing. So what if you could get all the behavioral data you need without taking your mice out of their cages? That’s the idea behind home-cage-based behavioral analysis, a kind of constant surveillance of mice where they live. In this week’s PNAS, Susan Lindquist and colleagues at the Whitehead Institute in Cambridge, Massachusetts, show how they developed and applied such a system to two models of neurodegenerative disease.

Their results illustrate how, when used carefully, automated behavioral analysis can reveal both new phenotypes and early signs of disease. Working with mouse models of prion and Huntington diseases, the researchers detected telltale behavioral differences weeks or months before obvious disease onset. They also observed behaviors in each mouse model that are reminiscent of human disease, but were unknown before in lab animals. With the wealth of data gleaned from the analysis, they constructed behavioral arrays that track changes over time, and allow for early diagnosis of disease.

To get to automated behavior assessment, first author Andrew Steele and colleagues viewed hours of videotapes of frolicking mice, manually classifying behaviors and defining the body movements typical of each. They then used that information to train computer software to recognize 19 behaviors from walking, resting, and eating, to sniffing, rearing, and jumping.

Next, they collected and analyzed 24-hour chunks of video of Huntington disease mice or prion-infected mice in their cages. The HD model has well-characterized motor defects and, as expected, the mice spent less time doing things that required grip strength and coordination, like hanging or jumping. But the researchers also saw new behaviors; for example, the mice rested for shorter periods of time and woke up more often. The differences were statistically significant by 6 weeks of age, long before obvious disease onset at 9-10 weeks. This phenotype is also seen in people with HD, who often suffer sleep disturbances. In another novel activity, the mice showed a steady increase in grooming behavior, which might mimic the psychological problems seen in people with HD. From this, the researchers concluded that the mice might be a better model of HD than previously thought.

In the prion-infected mice, resting abnormalities were also the first changes seen; they appeared months before overt disease onset. The prion mice showed some new phenotypes, too, the most dramatic of which was hyperactivity with more sniffing, rearing, and jumping. Both strains of mice exhibited some of the behaviors only in the light or dark phase, showing the value of 24-hour monitoring.

Taking a systems approach to behavioral analysis, the researchers combined the data on 19 behaviors into a global phenotype for each disease. From this, they constructed diagnostic rules, which distinguished between sick and well mice much earlier than do standard tests. The advantages of the system are many, the authors write. Tests can be done in high-throughput mode with less stress on the animals, and conditions also vary less. In addition, animals can be watched at night, when mice are more active. The measurements prove to be highly sensitive, which should reduce the number of animals needed.

That’s not to say this method is the end-all of mouse behavioral studies, the authors stress. “High-resolution automated mouse behavior analysis will never replace the cleverly designed, highly specific behavioral tests used to assess particular physical or behavioral deficits,” they write. But, they add, the approach will be useful for testing therapeutics on these mouse models, and for guiding the choice of more detailed behavioral studies in other models.—Pat McCaffrey

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