Cross-species translation of the Morris maze for Alzheimer’s disease
Katherine L. Possin, … , Joel H. Kramer, Steven Finkbeiner
Katherine L. Possin, … , Joel H. Kramer, Steven Finkbeiner
Published January 19, 2016
Citation Information: J Clin Invest. 2016;126(2):779-783. https://doi.org/10.1172/JCI78464.
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Concise Communication Neuroscience

Cross-species translation of the Morris maze for Alzheimer’s disease

Abstract

Analogous behavioral assays are needed across animal models and human patients to improve translational research. Here, we examined the extent to which performance in the Morris water maze — the most frequently used behavioral assay of spatial learning and memory in rodents — translates to humans. We designed a virtual version of the assay for human subjects that includes the visible-target training, hidden-target learning, and probe trials that are typically administered in the mouse version. We compared transgenic mice that express human amyloid precursor protein (hAPP) and patients with mild cognitive impairment due to Alzheimer’s disease (MCI-AD) to evaluate the sensitivity of performance measures in detecting deficits. Patients performed normally during visible-target training, while hAPP mice showed procedural learning deficits. In hidden-target learning and probe trials, hAPP mice and MCI-AD patients showed similar deficits in learning and remembering the target location. In addition, we have provided recommendations for selecting performance measures and sample sizes to make these assays sensitive to learning and memory deficits in humans with MCI-AD and in mouse models. Together, our results demonstrate that with careful study design and analysis, the Morris maze is a sensitive assay for detecting AD-relevant impairments across species.

Authors

Katherine L. Possin, Pascal E. Sanchez, Clifford Anderson-Bergman, Roland Fernandez, Geoffrey A. Kerchner, Erica T. Johnson, Allyson Davis, Iris Lo, Nicholas T. Bott, Thomas Kiely, Michelle C. Fenesy, Bruce L. Miller, Joel H. Kramer, Steven Finkbeiner

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