Journal Article

Selective striatal neuronal loss in a YAC128 mouse model of Huntington disease

Elizabeth J. Slow, Jeremy van Raamsdonk, Daniel Rogers, Sarah H. Coleman, Rona K. Graham, Yu Deng, Rosemary Oh, Nagat Bissada, Sazzad M. Hossain, Yu-Zhou Yang, Xiao-Jiang Li, Elizabeth M. Simpson, Claire-Anne Gutekunst, Blair R. Leavitt and Michael R. Hayden

in Human Molecular Genetics

Volume 12, issue 13, pages 1555-1567
Published in print July 2003 | ISSN: 0964-6906
Published online July 2003 | e-ISSN: 1460-2083 | DOI:
Selective striatal neuronal loss in a YAC128 mouse model of Huntington disease

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An expanded CAG repeat is the underlying genetic defect in Huntington disease, a disorder characterized by motor, psychiatric and cognitive deficits and striatal atrophy associated with neuronal loss. An accurate animal model of this disease is crucial for elucidation of the underlying natural history of the illness and also for testing experimental therapeutics. We established a new yeast artificial chromosome (YAC) mouse model of HD with the entire human HD gene containing 128 CAG repeats (YAC128) which develops motor abnormalities and age-dependent brain atrophy including cortical and striatal atrophy associated with striatal neuronal loss. YAC128 mice exhibit initial hyperactivity, followed by the onset of a motor deficit and finally hypokinesis. The motor deficit in the YAC128 mice is highly correlated with striatal neuronal loss, providing a structural correlate for the behavioral changes. The natural history of HD-related changes in the YAC128 mice has been defined, demonstrating the presence of huntingtin inclusions after the onset of behavior and neuropathological changes. The HD-related phenotypes of the YAC128 mice show phenotypic uniformity with low inter-animal variability present, which together with the age-dependent striatal neurodegeneration make it an ideal mouse model for the assessment of neuroprotective and other therapeutic interventions.

Journal Article.  8731 words.  Illustrated.

Subjects: Genetics and Genomics

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