University of Cambridge > Talks.cam > CamBRAIN Virtual Journal Club > A Fully Automated Behavioural Phenotyping of APP Knock-In Azheimer's Disease Mouse Model

A Fully Automated Behavioural Phenotyping of APP Knock-In Azheimer's Disease Mouse Model

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  • UserNeha Ramu, University of Cambridge
  • ClockWednesday 05 May 2021, 16:00-17:00
  • HouseZoom.

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Introduction: Alzheimer’s Disease (AD) is a debilitating neurodegenerative disease that places an immense burden on patients and public healthcare systems. One of the genes associated with AD is the amyloid precursor protein (APP) gene, mutations of which result in overproduction of Aβ42, forming amyloid plaques. Current diagnostic processes cannot detect these plaques before extensive neurodegeneration has already occurred, thus developing early diagnostic tools is essential. Aim: To study the efficacy of the Smart Kage, a novel technology that automates behavioural phenotyping of mouse models, for application in early diagnosis of AD. Methods: We assessed the APP -NL-G-F mouse model by carrying out behavioural phenotyping. We subjected our control (12 wildtype mice) and test (2 known APP -NL-G-F, 6 blinded) cohorts to the novel object recognition (NOR), object in place (OIP) and T maze task. All tasks were incorporated and fully automated by the Smart Kage to increase the efficiency of behavioural testing and to continuously monitor progression of mice phenotypes. Results: In the object recognition tasks, the control cohort showed no significant difference (NOR: p = 0.31, OIP : p = 0.41) in the average time spent on the objects in the familiarisation phases, nor did the known APP mice (NOR: p = 0.67, OIP : p = 1.00). However, in the test phases, control mice spent significantly more time on the novel/swapped object/s (NOR: p = 0.01, OIP : p = 0.04) whereas the known APP again showed no significant difference (NOR: p = 1.00, OIP : p = 0.53). In the T maze task, the control cohort showed a high average percentage correct alternation (77%) and rate of learning over testing days, whereas there was high variation between the two known APP mice. At this 6 month interim, we are not unblinded to the test cohort, thus we currently have observational results. The Smart Kage data has been collected and will be analysed in due course. Conclusion: The APP -NL-G-F mice show AD-like memory impairments in spatial and non-spatial recognition memory, but the working memory assessment was inconclusive. Whilst further investigations with larger sample sizes are required before the Smart Kage data can contribute towards developing an early diagnostic tool, we have gained very promising insights towards automating behavioural phenotyping of mouse models.

This talk is part of the CamBRAIN Virtual Journal Club series.

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