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      Using mice to model Alzheimer's dementia: an overview of the clinical disease and the preclinical behavioral changes in 10 mouse models

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          Abstract

          The goal of this review is to discuss how behavioral tests in mice relate to the pathological and neuropsychological features seen in human Alzheimer's disease (AD), and present a comprehensive analysis of the temporal progression of behavioral impairments in commonly used AD mouse models that contain mutations in amyloid precursor protein (APP). We begin with a brief overview of the neuropathological changes seen in the AD brain and an outline of some of the clinical neuropsychological assessments used to measure cognitive deficits associated with the disease. This is followed by a critical assessment of behavioral tasks that are used in AD mice to model the cognitive changes seen in the human disease. Behavioral tests discussed include spatial memory tests [Morris water maze (MWM), radial arm water maze (RAWM), Barnes maze], associative learning tasks (passive avoidance, fear conditioning), alternation tasks (Y-Maze/T-Maze), recognition memory tasks (Novel Object Recognition), attentional tasks (3 and 5 choice serial reaction time), set-shifting tasks, and reversal learning tasks. We discuss the strengths and weaknesses of each of these behavioral tasks, and how they may correlate with clinical assessments in humans. Finally, the temporal progression of both cognitive and non-cognitive deficits in 10 AD mouse models (PDAPP, TG2576, APP23, TgCRND8, J20, APP/PS1, TG2576 + PS1 (M146L), APP/PS1 KI, 5×FAD, and 3×Tg-AD) are discussed in detail. Mouse models of AD and the behavioral tasks used in conjunction with those models are immensely important in contributing to our knowledge of disease progression and are a useful tool to study AD pathophysiology and the resulting cognitive deficits. However, investigators need to be aware of the potential weaknesses of the available preclinical models in terms of their ability to model cognitive changes observed in human AD. It is our hope that this review will assist investigators in selecting an appropriate mouse model, and accompanying behavioral paradigms to investigate different aspects of AD pathology and disease progression.

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          Most cited references294

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          National Institute on Aging-Alzheimer's Association guidelines for the neuropathologic assessment of Alzheimer's disease: a practical approach.

          We present a practical guide for the implementation of recently revised National Institute on Aging-Alzheimer's Association guidelines for the neuropathologic assessment of Alzheimer's disease (AD). Major revisions from previous consensus criteria are: (1) recognition that AD neuropathologic changes may occur in the apparent absence of cognitive impairment, (2) an "ABC" score for AD neuropathologic change that incorporates histopathologic assessments of amyloid β deposits (A), staging of neurofibrillary tangles (B), and scoring of neuritic plaques (C), and (3) more detailed approaches for assessing commonly co-morbid conditions such as Lewy body disease, vascular brain injury, hippocampal sclerosis, and TAR DNA binding protein (TDP)-43 immunoreactive inclusions. Recommendations also are made for the minimum sampling of brain, preferred staining methods with acceptable alternatives, reporting of results, and clinico-pathologic correlations.
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            Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer's disease.

            We studied the accumulation of neurofibrillary tangles (NFTs) and senile plaques (SPs) in 10 Alzheimer's disease patients who had been examined during life. We counted NFTs and SPs in 13 cytoarchitectural regions representing limbic, primary sensory, and association cortices, and in subcortical neurotransmitter-specific areas. The degree of neuropathologic change was compared with the severity of dementia, as assessed by the Blessed Dementia Scale and duration of illness. We found that (1) the severity of dementia was positively related to the number of NFTs in neocortex, but not to the degree of SP deposition; (2) NFTs accumulate in a consistent pattern reflecting hierarchic vulnerability of individual cytoarchitectural fields; (3) NFTs appeared in the entorhinal cortex, CA1/subiculum field of the hippocampal formation, and the amygdala early in the disease process; and (4) the degree of SP deposition was also related to a hierarchic vulnerability of certain brain areas to accumulate SPs, but the pattern of SP distribution was different from that of NFT.
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              Animal models of neuropsychiatric disorders.

              Modeling of human neuropsychiatric disorders in animals is extremely challenging given the subjective nature of many symptoms, the lack of biomarkers and objective diagnostic tests, and the early state of the relevant neurobiology and genetics. Nonetheless, progress in understanding pathophysiology and in treatment development would benefit greatly from improved animal models. Here we review the current state of animal models of mental illness, with a focus on schizophrenia, depression and bipolar disorder. We argue for areas of focus that might increase the likelihood of creating more useful models, at least for some disorders, and for explicit guidelines when animal models are reported.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                16 March 2014
                23 April 2014
                2014
                : 5
                : 88
                Affiliations
                [1] 1Sanders-Brown Center on Aging, University of Kentucky Lexington, KY, USA
                [2] 2Division of Neuropathology, Department of Pathology and Laboratory Medicine, University of Kentucky Lexington, KY, USA
                [3] 3Department of Neurology, University of Kentucky Lexington, KY, USA
                [4] 4Department of Anatomy and Neurobiology, University of Kentucky Lexington, KY, USA
                Author notes

                Edited by: Shin Murakami, Touro University-California, USA

                Reviewed by: James C. Vickers, University of Tasmania, Australia; Danna Zimmer, University of Maryland Medical School, USA

                *Correspondence: Linda J. Van Eldik, Sanders-Brown Center on Aging, 800 S. Limestone, Lexington, KY 40536-0230, USA e-mail: linda.vaneldik@ 123456uky.edu

                This article was submitted to Genetics of Aging, a section of the journal Frontiers in Genetics.

                Article
                10.3389/fgene.2014.00088
                4005958
                24795750
                ac9c4af2-c0f6-4b42-9655-419ce6dfe2a5
                Copyright © 2014 Webster, Bachstetter, Nelson, Schmitt and Van Eldik.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 February 2014
                : 01 April 2014
                Page count
                Figures: 1, Tables: 4, Equations: 0, References: 365, Pages: 23, Words: 23054
                Categories
                Genetics
                Review Article

                Genetics
                alzheimer's disease,mouse models,neuropsychological assessment,behavior,cognition,app mice,app/ps1 mice,3×tg-ad mice

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