Transgenic Mouse Models of Alzheimer’s Disease: Behavioral Testing and Considerations

Kathryn J. Bryan; Hyoung-gon Lee; George Perry; Mark A. Smith; Gemma Casadesus

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Buccafusco JJ, editor. Methods of Behavior Analysis in Neuroscience. 2nd edition. Boca Raton (FL): CRC Press/Taylor & Francis; 2009.

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Methods of Behavior Analysis in Neuroscience. 2nd edition.

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Chapter 1Transgenic Mouse Models of Alzheimer’s Disease: Behavioral Testing and Considerations

Kathryn J. Bryan, Hyoung-gon Lee, George Perry, Mark A. Smith, and Gemma Casadesus.

1.1. INTRODUCTION

One hundred years ago, the German psychiatrist and neuropathologist Alois Alzheimer gave a lecture in which he identified a disease of the cerebral cortex [1] that would ultimately bear his name: Alzheimer’s disease (AD). In individuals with this condition, the cerebral cortex is thinner than normal and senile plaques, along with neurofibrillary tangles (NFTs), are found in the brain [2]. In the early 1980s, the biochemical characterization of senile plaques in patients with Down’s syndrome and AD led to the identification of amyloid-β (Aβ) peptide as a major component. Thereafter, it was determined that Aβ is a product of the Aβ protein precursor (APP). The importance of Aβ/APP in the pathogenesis of AD is evidenced by the fact that genetic mutations in the APP gene invariably cause AD in cases with the early onset familial form of the disease [3–5]. The relationship between APP and Aβ caused the research community to respond with quick enthusiasm for Aβ and laid the foundation for the amyloid cascade hypothesis [4,6]. The amyloid cascade hypothesis states that mutations in APP (or other genes) lead to an increase in Aβ and that this then leads to disease. While the original hypothesis [6] posited Aβ fibrils as the major mediator of the disease, a more recent incarnation of the hypothesis [4] proposes smaller oligomeric forms of Aβ as key. In both cases, Aβ is viewed as being important in mediating the neuronal and synaptic toxicity that leads to the deterioration of cognition [7]. Likewise, a steady influx of research began to elucidate the role of NFTs and their principal protein component, phosphorylated tau, in the brain and how these pathological entities related to the symptomatology of AD [8]. While the pathological significance of Aβ and NFTs in disease, as well as their interaction is still under much discussion [9,10], the majority of investigators in the field are convinced that they play fundamental roles in the onset and progression of AD. That said, other theories of AD, unrelated to NFTs and Aβ deposits, are also being actively pursued (for review see [11–15]). Nevertheless, the development of transgenic mouse models of AD over the last decade has primarily focused on the pathological markers (NFTs and senile plaques), and such transgenic models have become promising tools to decipher the mechanistic importance of tau phosphorylation and Aβ deposits, as well their relationship between each other and the other pathological changes.

While seemingly obvious, it is important to remember that the validity of a mouse model of disease is tightly linked to the ability of the animal to mimic the signs of the disease—in the case of AD, cognitive decline. The aim of this review is to discuss cognitive function in transgenic mouse models focused predominantly on Aβ and tau models and, thereafter, the validity of these models to study AD and the mechanistic questions that have arisen based on their behavioral phenotype [16,17].

1.2. BEHAVIORAL TESTS

The most predominant and striking sign in an AD patient is the progressive decline in cognition, primarily due to loss of neurons and synapses in the hippocampal formation and related areas [18]. As such, a “must have” feature of a valid AD-transgenic model is the ability of the model to accurately reflect the behavioral changes observed in human AD patients. To accurately interpret behavioral results from transgenic mouse models of AD, it is important to intimately understand the behavioral tasks that are most often used to test cognitive changes in mice, as well as what each cognitive test is actually measuring. When examining cognition in animals, behavioral tasks are typically divided into either associative or operant learning tasks. Associative learning tasks use cues in the environment to condition a specific response in the animal. Operant learning tasks require the animal to make a particular response to a specific stimulus in order to receive an outcome. Cognitive tasks are further divided into groups by the type of memory being tested. The following are some of the most often used tasks to determine cognitive changes in mouse models, transgenic or otherwise.

1.2.1. Spatial Memory Tasks

1.2.1.1. The Morris Water Maze

The Morris water maze (MWM) is a particularly sensitive task to examine age-related/AD-like deficits because it is highly specific for hippocampal function, one of the first and most affected brain regions in AD [18]. As a result, the MWM test is one of the most common behavioral tasks used to determine hippocampal spatial memory deficits [19]. The test consists of placing the rodent in a circular tank filled with cloudy water, which is used to motivate the animal to escape the water by swimming to a hidden platform located right below the water’s surface. Over several days the rodent learns to find the hidden platform by using spatial cues, such as posters or taped objects strategically placed on the walls outside of the water maze, in the testing room. Distance swam, latency to reach the platform, and swim speed, most often recorded on video, are common measures of this test. The capacity of the animal to retrieve and retain learned information or the flexibility to purge and relearn new strategies can be determined using a probe trial and reversal trial. In the probe trial the platform is taken out and the animals are allowed to swim in the pool. Time spent in the region that previously contained the platform, crossings over the platform area, and time to reach the platform location are measured. The reversal trial is identical to the training trials, but in this case, the platform is switched to the opposite region of the pool, testing the cognitive flexibility of the animal that is necessary to relearn a new location. A cued version of this task, rendering the platform visible, can also be used to measure nonspatial strategies as well as visual acuity [20]. Variations include the radial arm water maze (RAWM) or plus-shaped water maze [21].

One desirable aspect of this task is that the motivating stimulus, i.e., escaping the water, does not require the food or water deprivation that is common in other spatial memory tasks. However, it has certain limitations as well, one of which is the fact that the various components of memory, i.e., reference and working memories, cannot be tested simultaneously.

1.2.1.2. Radial Arm Maze

One task that can accommodate simultaneous measurement of memory components and has also been widely used to study spatial memory performance in rodents is the radial arm maze (RAM). This maze consists of 8–17 equally spaced arms radiating from a central platform, which the rodent has to enter in order to attain a food or water reward placed in some of the arms. In this task, the animals guide themselves using spatial cues around the room, with the goal to enter each arm only once to receive the maximum amount of food or water rewards in the shortest period of time and with the least amount of effort. This maze requires the use of working memory to retain information that is important for a short time (within trial information), as well as the use of reference memory to retain the general rules of the task across days. Specifically, the animal must be able to remember which arms were baited as well as which it already entered (working memory), but it also must know to avoid non-baited arms across trials (reference memory), all of which takes place by being able to successfully encode spatial information. However, while this task permits the examination of both reference and working memory, major limitations are the use of food or water deprivation in this task, as well as the presence of odor confounds [22–24].

1.2.1.3. Radial Arm Water Maze

A relatively new spatial memory task, the RAWM, has been designed to eliminate the limitations of the above-mentioned tasks by combining the positive aspects of the MWM and RAM. The difference between the MWM and RAWM is that performance in the RAWM entails finding a platform that is submerged in water located in one of several arms (6–8) in the water bath, compared to the classic MWM which only has an open swim field. This makes the task a bit more difficult, but forces the animal to use spatial cues and working memory (keeping track of the arms it has already visited) to remember where the platform is located. Several variations of this task, using different numbers of platforms and platform location organization, have been used to examine spatial memory differences after pharmacological treatment [25,26] and differences across species [27], gender [28], and, importantly, models of AD [24,29].

1.2.2. Contextual Memory

1.2.2.1. Fear Conditioning

Freezing response, defined as a complete lack of movement, is the innate response of rodents to fear. In a fear conditioning paradigm, the animal is placed in a box containing a grid that delivers a mild aversive stimulus for two minutes. In the box, the animal is presented with a tone (usually 80 dB) (conditioned stimulus) that is paired with a mild shock (unconditioned stimulus) at the end of the trial with the result that the tone elicits the freezing response. Repeated exposures are sometimes necessary depending on the strain used or the interval time between the tone and the shock. Some researchers use trace fear conditioning, which increases the time gap between the tone and the shock in order to investigate prefrontal cortical activity. Here, the animal is taken out of the box and returned 24 hr later to evaluate its learned aversion for an environment associated with a mild aversive stimulus (context-dependent fear) by measuring freezing behavior in the absence of tone or aversive stimulus. Cue-dependent fear can be measured by placing the animal in a new box that is different in color, shape, etc., and presenting it with the tone as it explores the new environment; freezing behavior associated with the tone is measured.

Fear conditioning is a widely used test to measure hippocampal-dependent associative learning. This test is thought to be sensitive to emotion-associated learning and therefore is a useful measure of amygdalar–hippocampal communication. Many of the transgenic mouse models of AD display impairments in fear and anxiety, which is primarily a function of the amygdala. The hippocampal function used in fear conditioning may be different from learning in a spatial task [30–32].

1.2.2.2. Passive-Avoidance Learning

In the passive-avoidance learning task, the animal must learn to avoid a mild aversive stimulus, in this case darkness, by remaining in the well-lit side of a two-chamber apparatus and not entering the dark where it receives the aversive stimulus. Note that since rodents innately gravitate to darkness, the animal has to suppress this tendency through pairing the negative stimulus with the desired compartment. Animals that do not remember the aversive stimulus will cross over earlier than animals that remember. Dependent measures include the median step-through latency (latency to cross into the unsafe side) and the percentage of animals from each experimental group that cross the threshold within an allocated time [20,33,34].

1.2.3. Working Memory/Novelty/Activity

1.2.3.1. Y-Maze

This test is based on the innate preference of mice to alternate arms when exploring a new environment. Various modifications are available with different levels of difficulty and different demands on specific types of cognition. One version that is particularly popular for the study of cognitive changes in AD transgenic models is the spontaneous alternation version of the Y-maze. In this instance, test animals are placed in a Y-shaped maze for 6–8 min and the number of arms entered, as well as the sequence of entries, is recorded and a score is calculated to determine alternation rate (degree of arm entries without repetitions). A high alternation rate is indicative of sustained cognition as the animals must remember which arm was entered last to not reenter it [35].

A short-term memory version can also be carried out in which one arm of the Y-maze is blocked and the subject is allowed to explore the two arms for 15–30 min. The animal is then removed from the maze for a few minutes or up to several hours, depending on the experimental manipulation, and then placed back into the maze, this time with all arms open, to explore for 5 min. Animals with preserved cognitive function will remember the previously blocked arm and will enter that one first on the second trial. This test can also be repeated a week after the last trial with a delay time of only 2 min between the trials in order to test long-term memory and the time it takes the animal to relearn the task. Typically measured parameters include the first arm entered, amount of time spent in each arm, and total number of arm entries [35].

1.2.3.2. T-Maze

T-maze tasks are incredibly well characterized and are widely used for cognitive behavioral testing in both mice and rats. Animals are started at the base of the T and allowed to choose one of the goal arms abutting the other end of the stem. If two trials are given in quick succession, on the second trial the rodent tends to choose the arm not visited before, reflecting memory of the first choice. This is called “spontaneous alternation.” This tendency can be reinforced by making the animal hungry and rewarding it with a preferred food if it alternates. Both spontaneous and rewarded alternations are very sensitive to dysfunction of the hippocampus, and hence are sensitive to AD-like symptoms, but other brain structures are also involved. Each trial should be completed in less than 2 min, but the total number of trials required will vary according to statistical and scientific requirements [36].

1.2.3.3. Object Recognition

The object recognition test is based on the natural tendency of rodents to investigate a novel object instead of a familiar one, as well as their innate tendency to restart exploring when they are presented with a novel environment. The choice to explore the novel object, as well as the reactivation of exploration after object displacement, reflects the use of learning and recognition memory processes. The available object-recognition tasks to test cognition in rodents use different numbers of available objects and environments in which the animals are tested, as well as types of configuration aimed to test spatial recognition and novelty, among other things. One particular object recognition task that is sensitive to age-related deficits is very suitable to test AD-related deficits [37–39]. In this task, a rodent is placed in a circular open field filled with different objects (i.e., various plastic toys of different sizes and shapes) for 6 min. After a series of trials, during which the animal has habituated to the configuration and properties of the different objects, some of the objects are switched from one location to another to assess spatial recognition. Subsequently, some of the objects are replaced with new ones to evaluate novel object recognition. The time spent exploring the open field (movement/inactivity) as well as number of times and length of time inspecting each object over the different trials is calculated.

1.2.3.4. Open Field

The open field locomotion test is used primarily to examine motor function by means of measuring spontaneous activity in an open field. The circular or square open fields vary in size depending on the experiment and are divided into distinct quadrants or sections. The animal is placed in the open field and the movements of the animal are either videotaped or monitored by automated computer programs. Rearing, line crosses, cleaning, general movement, number of lines crossed, preference for particular sections, and/or fecal movements can all be calculated to examine behavior and anxiety [40,41].

1.3. TRANSGENIC MOUSE MODELS OF ALZHEIMER’S DISEASE

1.3.1. Amyloid-β Transgenic Mouse Models

The first transgenic mouse model of AD, PDGF promoter expressing amyloid precursor protein (PDAPP), was developed in 1995 by Games et al. [42] and displays increased human Aβ_1–40 and Aβ_1–42 that are 5–14 times higher than endogenous mouse Aβ. The PDGF-driven mouse human amyloid precusor displays synaptic loss; reductions in size of the hippocampus, fornix, and corpus callosum; and memory loss that is comparable to that of human AD patients [43]. PDAPP mice older than 6 mo have been tested in the MWM, open field, radial arm maze, operant bar pressing, and visual object recognition tasks and have significant memory impairments on all tasks compared to age matched controls [29,44–46]. For instance, when tested in the MWM, PDAPP mice have significantly higher swim latencies in finding the platform than controls. During open field trials and visual object recognition tasks, PDAPP mice tend to exhibit high levels of motor activity and revisit already explored areas or objects more often than control animals. PDAPP mice have further been tested in an associative learning task—the fear conditioning task—which relies on the ability of the animal to associate an auditory cue with a foot shock. After training, however, both PDAPP and control animals display the same amount of freezing response after the auditory cue is given, as well as when reexposed to the same training context [47]. There are no studies to date that have examined how PDAPP mice perform if the context is altered (to context B). A better indicator of cognitive deficits involving the hippocampus compared to the auditory cue, which is primarily driven by the amygdala, would be to perform this test in an altered context, such as a dark room with a berry-scented odor, after initial training. No studies to date have explored different contexts.

The deficits in cognition in the older PDAPP mice correlate with increased Aβ and reductions in the hippocampus/brain ratio. However, in many cases, the same cognitive deficits are also found in young (3–4 mo) animals in which Aβ deposits, or hippocampal formation reduction, are not yet apparent [43]. As such, these results tend to not support the amyloid cascade hypothesis; however, the three types of mice, C57Bl/6, DBA/2J, and Swiss-Webster, that are used to produce a PDAPP mouse, are not the same for each study [43]. This aspect will be further discussed, but it is important to mention that this is a recurring problem in all transgenic mouse models of AD. Another potential reason is that PDAPP mice tend to have lower body temperatures, which may result in varying degrees of hypothermia during the MWM task, which can produce amnesia in animals [48 50]. Although there are many theories as to why young PDAPP mice perform like older PDAPP mice, the reason for the inconsistencies in the literature is still unknown.

Shortly after the PDAPP mouse was developed, another human mutant APP transgenic mouse model, which over-expresses the Swedish double mutant form of APP695, was introduced as the Tg2576 mouse [51]. Tg2576 mice are similar to the PDAPP mouse in that they exhibit five times the level of endogenous murine APP in the brain and, after 11 mo, develop plaque-like deposits of Aβ_1–40 and Aβ_1–42/43 in the frontal, temporal, and entorhinal cortices; hippocampus; presubiculum; and cerebellum. Unlike the PDAPP mice, Tg2576 mice do not have significant synaptic loss or reductions in hippocampal size. Tg2576 mice have been tested in many of the same tasks as the PDAPP mice. For example, mice at 2, 6, 9, and 12 mo of age have been tested in the MWM. In this regard, after 10 mo of age, this transgenic mouse line demonstrates poor spatial memory retention and is unable to find a visible platform after 2 and 4 days of training compared to controls [43,52]. Tg2576 mice also tend to explore the familiar arm of the Y-maze more than controls. As with the PDAPP mice, Tg2576 mice are not always cognitively impaired. King and Arendash [53] did not see cognitive deficits in the MWM task in young or old animals, but did find that the Tg2576 mice had sensorimotor deficits during the visual cue trials. However, many studies that did not find a difference in cognition between Tg2576 mice and controls did find a significant decline in memory if they eliminated animals that showed visual and/or motor deficits [43,54,55].

Tg2576 mice have also been tested in a variety of Pavlovian tasks, such as fear conditioning. Older mice first trained in a salient context (context A) were then divided into subgroups, one of which was again tested in context A and the other in a novel context (context B). Based on the context-shift theory, normal animals perform well when trained and tested in the same context, but show a decline in memory when tested in the new context if they acquired the memory for the original training cues [56]. Conversely, Tg2576 mice performed well in both contexts, unaffected by the change in cues, most likely because they were unable to remember the cues from the original training context. Although, Tg2576 mice did not distinguish between contextual cues, they were able to learn the fear response when trained with a specific cue, such as a sound or light. These results are consistent with the PDAPP mice [57].

The accumulation of Aβ_1–42 is dependent upon the cleavage of the β-secretase and the γ-secretase enzymes. Individual enzymes known as presenilins are involved in γ-secretase enzyme activity, and mutations in presenilins often lead to Aβ_1–42 accumulation as found in AD patients [58]. The first mouse model to examine the role of presenilin 1 (PS1) was produced by Shen et al. [59]. The PS1 knockout mice were deficient in PS1; however, they quickly died after birth. Massive neuronal loss and hemorrhages were found in the brain. Today there are a few types of PS1 and PS2 transgenic mouse models that survive after birth. All of the models that lack the PS1 or PS2 gene demonstrate cognitive decline on the MWM and on object recognition tasks, but compared to the Tg2576 animals, they are not severely impaired. In animals that over-express human PS1, high levels of Aβ_1–42 were found, but without accompanying plaque-like accumulations or behavioral alterations [43,60].

The first multiple gene transgenic mouse model of AD was developed to alter both the presenilins and the accumulation of human APP, today known as APP+PS1. Compared to the Tg2576 animals, the APP+PS1 has levels of Aβ_1–40 five times higher by 6 mo of age [61]. Young and old APP+PS1 mice have been tested in the Y-maze, elevated plus maze, MWM, and RAWM. Both young and old animals display deficits in the spontaneous alternation version of the Y-maze task, with fewer alternations between arms on the Y-maze. However, in the other behavioral tests, young animals tend to perform as well as controls, but by 15–17 mo of age, the APP+PS1 animals showed spatial deficits in the MWM and RAWM, and increased activity in an open-field test. This was one of the first transgenic mouse models that showed a strong positive correlation between Aβ_1–42 development and cognitive decline [61–63].

A second multi-gene PS1/APP mouse model, known as the PSAPP mouse, was developed from a different mutation in human PS1 (A246E) and was crossed with the Tg2576 mouse. Aβ_1–42 and plaque loads occurred as early as 7 mo, earlier than in the Tg2576 mice. PSAPP mice perform similarly to the Tg2576 mice in a cued fear conditioning paradigm. Notably, PSAPP mice perform well at this test if they are given a cue, but are unable to distinguish altered contexts between training and testing, suggesting a hippocampal deficit. During spatial MWM testing, PSAPP mice have longer latencies to find the hidden platform, which is significantly correlated with the levels of insoluble hippocampal Aβ_1–42. [64]

The CRND8 transgenic mouse is derived from an APP Swedish mutation and V717F mice. Plaque formation develops in the hippocampus and cortex around 9 wk of age. They differ from the PDAPP and Tg2576 mice in that they have dense core deposits and dystrophic neurites without hippocampal volume decreases. In an MWM test, CRND8 mice perform worse than controls when tested after plaques have developed [65]. Hyde et al. [66] confirmed that Aβ production occurs prior to the formation of plaques, and therefore animals at the pre-plaque, early/mid-plaque stage, and late-plaque stage were tested in the MWM. Pre-plaque animals perform as well as controls; however, both early/mid-plaque and late-plaque animals have deficits in swim time. Further, early/mid-plaque animals perform well on the probe trial, while the late-plaque animals do not [66].

A more recent transgenic mouse model is the PDGF-APP_{Sw, Ind} mouse, which expresses the Swedish and Indiana APP mutations with increased BrdU and immature neuronal markers in the dentate gyrus and subventricular zone [67]. This increased neurogenesis is also found in the brains of patients with AD. While neurogenesis in AD may be a result of increased injured neurons or the loss of neurons, the PDGF-APP_{Sw, Ind}, however, do not display neuronal loss, indicating that another mechanism is responsible for the neurogenesis [68].

1.3.2. Tau Transgenic Mouse Models

Tau, a microtubule protein, is modified in AD, resulting in neuronal degeneration. Tau transgenic mouse models have been designed to model the NFT pathology often observed in AD. Early over-expressing tau transgenic mouse models demonstrate motor deficits and cell loss in the spinal cord; however, they did not develop “true” NFTs. Recently, a new tau transgenic mouse, P301S, was developed that demonstrates progressive NFT formation and neuronal loss [69], and NFT formation is found in the spinal cord, brainstem, cerebellum, diencephalon, and basal telencephalon when the expression of FTDP-17–associated mutation P301L is increased under the mouse prion promoter (JNPL3 line). Significantly, increased NFTs are correlated with a decline in MWM performance [70]. Other mouse models using the P301S FTDP-17–associated mutation, which show human tau is expressed in the spinal cord and hippocampus under the mouse Thy1.2 promoter, have phosphorylated tau, but do not have NFTs [71].

The rTg(tauP301L) 4510 mouse expresses the P301L mutation in tau associated with frontotemporal dementia and develops NFTs in the neocortex and hippocampus, which is consistent with other tau transgenic mice. When tested in the MWM, cognitive decline can be seen as early as 4 mo of age in the rTg(tauP301L) 4510 mice and this memory deficit is also accompanied by neuronal loss [72]. The development of the P301S mouse allows researchers to examine the effect of Aβ on NFT formation. Injections of Aβ_1–42 into the hippocampus of P301L mice leads to increased NFT numbers in the amygdala and hippocampus [73]. The best model for AD, however, combines amyloid and tau pathology by crossing the APP, PS1, and P301L genes. The result is the 3xTg-AD mouse model, which develops amyloid plaques that quickly develop first in the neocortex and then spread to the hippocampus, and then develops NFT in the hippocampus shortly after the appearance of amyloid pathology. The 3xTg-AD mice display long-term potentiation deficits and precede plaque and tangle formation. A reduction in plaques and tangles occurs in response to immunotherapy treatment with Aβ antibodies [74]. Cognitive testing of both male and female 3xTg-AD using the MWM and passive-avoidance tests displayed impairments by females and males by 4.5 mo of age. There were no differences between controls and 3xTg-AD on the object recognition task [75].

1.4. CONCERNS WITH TRANSGENIC MOUSE MODELS OF ALZHEIMER’S DISEASE

Transgenic mouse models allow us to examine the mechanisms involved in the development of diseases such as AD. However, because of the large discrepancy in the behavioral findings observed across the now plentiful number of AD mouse models, a simple question that arises is whether we are really any closer today to determining what these mechanisms are than when the first PDAPP mouse was produced. The majority of AD research is carried out using animal models that have increased Aβ levels compared to controls, and while Aβ pathology is mimicked in these models, many other factors associated with AD pathology are not. For instance, as described above, many of the transgenic models, such as the Tg2576 and PS1+APP mice, do not have neuronal loss or larger ventricles, as would be expected in a true model of AD [51,54]. We also cannot disregard the many AD mouse models that have increases in Aβ or APP, but do not demonstrate cognitive deficits [43,48,54,60]. Inconsistencies in the literature could be due to differences in the behavioral protocols, type of tests that were conducted, age of the animals, the genetic background the transgenic animals were designed on, timing, sleep cycle of the animals, etc. Researchers often use a standard behavioral protocol, but the age of the animals, environmental cues, changes in researchers during the study, timing, techniques, handling, and time of day are difficult to keep constant from one lab to another. Any and all of these factors can affect behavioral outcomes. Likewise, the background of animals used for the transgenic mouse AD-model design influences how the animals will perform on various behavioral tasks [76]. For instance, Pugh et al. [76] found differences in learning of the passive avoidance task and MWM in two strains of mice (FVB/N and C57BL6/J) that are often used to engineer transgenic mouse lines. This information is an important factor when designing experiments and evaluating cognition testing. A lack of behavioral differences should not preclude the manipulated target from playing a role in the disease.

Another argument that further complicates the use of animal models based solely on APP and/or tau mutations is that other mechanisms may be at play [77]. In this regard, the possibility that Aβ production and tau hyperphosphorylation are compensatory responses to other pathogenic mechanisms such as cell cycle dysregulation or oxidative stress has not been excluded [13,78]. For example, oxidative stress as measured by 8-hydroxyguanosine (8OHG) and nitrotyrosine adduct formation, precedes Aβ deposition by decades in Down’s syndrome and AD patients [79–83]. Moreover, the pathological lesions in the brains of patients with AD are associated with decreased oxidative markers compared to histologically unaffected but vulnerable neurons [16]. Similarly, in Down’s syndrome, 8OHG immunoreactivity increases significantly in the teens and twenties, while Aβ burden only increases after age 30 [79]. Tau accumulation may also be an indicator of an oxidative imbalance. Oxidative stress and attendant modifications of tau byproducts of oxidative stress include Hydroxy-2,3-nonenal (4-HNE) and other cytotoxic carbonyls, which may enable neurons modified by tau and neurofilament proteins to survive for decades [83].

Mechanistic questions aside, the fact that studying AD via the use of mouse models carrying specific familial mutations to pathological entities of the disease (Aβ, tau hyperphosphorylation) may only provide a partial view rather than a complete picture of this disease [16]. As such, some stereological studies have suggested that there may be little or no neuronal loss during “normal” aging, even though the number of plaques is increased [84]. This observation parallels that observed in many of the transgenic mouse models. Importantly, like their human counterparts, these mice show evidence of oxidative stress that precedes the Aβ deposits [85,86]. Also, due to the fact that Aβ may be an end product of an underlying cause of AD, researchers using transgenic AD models may ultimately be examining a later stage of AD, when cognitive decline is seen. Nevertheless, some reports of neuronal loss in various transgenic AD models argue that Aβ is a bioactive substance. Furthermore, because these models are based on mutations associated with early onset AD, careful evaluation is needed to determine whether they provide a compelling analogy to sporadic AD in humans, which comprises 95% of the cases. To address this issue, perhaps, animal models of aging rather than mutation-specific models may afford a more accurate picture of how all of these pathogenic entities interact for the development and progression of AD [87,88].

In conclusion, the development of transgenic models of AD may provide tools to achieve an understanding of pathogenic mechanisms and develop new therapies. The efforts in this respect with regard to AD have been monumental, with several transgenic lines being available to researchers (Table 1.1). However, the validity of these models is overwhelmingly based on the ability of over-expression of APP and tau mutations to cause the pathological inclusions observed in the AD brain (plaques and NFTs); however, work is still needed to transfer this validity to other events-associated AD pathology. As such, AD transgenic mice differ in the timing and level of Aβ, PS1/2, and tau accumulation, and not all of the animals demonstrate neuronal cell loss, or hippocampal atrophy and ventricular enlargement. More importantly, cognitive decline is not always correlated with Aβ deposits or NFT formation. AD pathogenesis is likely a syndrome rather than a disease of specific mutations. Therefore, full validation of an AD model will only be recognized when features of AD beyond tau and Aβ are incorporated in the models.

TABLE 1.1

Transgenic Mouse Models of Alzheimer’s Disease

REFERENCES

1.: Alzheimer A. Uber eine eigenartige Erkrankung der Hirnrinde. Allg Zeitschr Psychiatr. 1907;64:146–148.
2.: Smith MA. Alzheimer disease. Int Rev Neurobiol. 1998;42:1–54. [PubMed: 9476170]
3.: Glenner GG, Wong CW. Alzheimer’s disease and Down’s syndrome: Sharing of a unique cerebrovascular amyloid fibril protein. Biochem Biophys Res Commun. 1984;122:1131–1135. [PubMed: 6236805]
4.: Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: Progress and problems on the road to therapeutics. Science. 2002;297:353–356. [PubMed: 12130773]
5.: Knowles RB, Gomez-Isla T, Hyman BT. Aβ associated neurophil changes: Correlation with neuronal loss and dementia. J Neuropathol Exp Neurol. 1998;57:1122–1130. [PubMed: 9862634]
6.: Hardy JA, Higgins GA. Alzheimer’s disease: The amyloid cascade hypothesis. Science. 1992;256:184–185. [PubMed: 1566067]
7.: Walsh DM, Selkoe DJ. Oligomers on the brain: The emerging role of soluble protein aggregates in neurodegeneration. Protein Pept Lett. 2004;11:213–228. [PubMed: 15182223]
8.: Tiraboschi P, Sabbagh MN, Hansen LA, et al. Alzheimer disease without neocortical neurofibrillary tangles: ”A second look” Neurology. 2004;62:1141–1147. [PubMed: 15079014]
9.: Arriagada PV, Growdon JH, Hedley-Whyte ET, Hyman BT. Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology. 1992;42:631–639. [PubMed: 1549228]
10.: Roberson ED, Scearce-Levie K, Palop JJ, et al. Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer’s disease mouse model. Science. 2007;316:750–754. [PubMed: 17478722]
11.: Raina AK, Zhu X, Smith MA. Alzheimer’s disease and the cell cycle. Acta Neurobiol. Exp. (Wars). 2004;64:107–112. [PubMed: 15190685]
12.: Casadesus G, Atwood CS, Zhu X, et al. Evidence for the role of gonadotropin hormones in the development of Alzheimer disease. Cell Mol Life Sci. 2005;62:293–298. [PubMed: 15723165]
13.: Zhu X, Raina AK, Perry G, Smith MA. Alzheimer’s disease: The two-hit hypothesis. Lancet Neurol. 2004;3:219–226. [PubMed: 15039034]
14.: Smith MA, Rottkamp CA, Nunomura A, Raina AK, Perry G. Oxidative stress in Alzheimer’s disease. Biochim. Biophys. Acta. 2000;1502:139–144. [PubMed: 10899439]
15.: Sayre LM, Perry G, Atwood CS, Smith MA. The role of metals in neurodegenerative diseases. Cell. Mol. Biol. (Noisy-le-grand). 2000;46:731–741. [PubMed: 10875436]
16.: Castellani RJ, Lee HG, Zhu X, et al. Neuropathology of Alzheimer disease: Pathognomonic but not pathogenic. Acta Neuropathol (Berl). 2006;111:503–509. [PubMed: 16718346]
17.: Berg L, McKeel DW Jr, Miller JP, Baty J, Morris JC. Neuropathological indexes of Alzheimer’s disease in demented and nondemented persons aged 80 years and older. Arch Neurol. 1993;50:349–358. [PubMed: 8460956]
18.: West MJ. Regionally specific loss of neurons in the aging human hippocampus. Neurobiol. Aging. 1993;14:287–293. [PubMed: 8367010]
19.: Morris R. Developments of a water-maze procedure for studying spatial learning in the rat. J. Neurosci. Methods. 1984;11:47–60. [PubMed: 6471907]
20.: Lawlor PA, Bland RJ, Das P, et al. Novel rat Alzheimer’s disease models based on AAV-mediated gene transfer to selectively increase hippocampal Aβ levels. Mol. Neurodegener. 2007;2:11. [PMC free article: PMC1906777] [PubMed: 17559680]
21.: Vloeberghs E, Van Dam D, D’Hooge R, Staufenbiel M, De Deyn PP. APP23 mice display working memory impairment in the plus-shaped water maze. Neurosci Lett. 2006;407:6–10. [PubMed: 16959424]
22.: de Toledo-Morrell L, Morrell F, Fleming S. Age-dependent deficits in spatial memory are related to impaired hippocampal kindling. Behav Neurosci. 1984;98:902–907. [PubMed: 6091704]
23.: Ikegami S. Behavioral impairment in radial-arm maze learning and acetylcholine content of the hippocampus and cerebral cortex in aged mice. Behav Brain Res. 1994;65:103–111. [PubMed: 7880448]
24.: Morgan D, Diamond DM, Gottschall PE, et al. A beta peptide vaccination prevents memory loss in an animal model of Alzheimer’s disease. Nature. 2000;408:982–985. [PubMed: 11140686]
25.: Shear DA, Dong J, Haik-Creguer KL, et al. Chronic administration of quinolinic acid in the rat striatum causes spatial learning deficits in a radial arm water maze task. Exp Neurol. 1998;150:305–311. [PubMed: 9527900]
26.: Bimonte HA, Denenberg VH. Estradiol facilitates performance as working memory load increases. Psychoneuroendocrinology. 1999;24:161–173. [PubMed: 10101725]
27.: Hyde LA, Hoplight BJ, Denenberg VH. Water version of the radial-arm maze: Learning in three inbred strains of mice. Brain Res. 1998;785:236–244. [PubMed: 9518631]
28.: Bimonte HA, Hyde LA, Hoplight BJ, Denenberg VH. In two species, females exhibit superior working memory and inferior reference memory on the water radial-arm maze. Physiol Behav. 2000;70:311–317. [PubMed: 11006429]
29.: Arendash GW, Gordon MN, Diamond DM, et al. Behavioral assessment of Alzheimer’s transgenic mice following long-term Abeta vaccination: Task specificity and correlations between Abeta deposition and spatial memory. DNA Cell Biol. 2001;20:737–744. [PubMed: 11788052]
30.: Fanselow MS. Conditioned and unconditional components of post-shock freezing. Pavlov J Biol Sci. 1980;15:177–182. [PubMed: 7208128]
31.: Fanselow MS, Tighe TJ. Contextual conditioning with massed versus distributed unconditional stimuli in the absence of explicit conditional stimuli. J Exp Psychol Anim Behav Process. 1988;14:187–199. [PubMed: 3367103]
32.: Hamann S, Monarch ES, Goldstein FC. Impaired fear conditioning in Alzheimer’s disease. Neuropsychologia. 2002;40:1187–1195. [PubMed: 11931922]
33.: Senechal Y, Kelly PH, Dev KK. Amyloid precursor protein knockout mice show age-dependent deficits in passive avoidance learning. Behav Brain Res. 2008;186:126–132. [PubMed: 17884188]
34.: McGaugh JL. Time-dependent processes in memory storage. Science. 1966;153:1351–1358. [PubMed: 5917768]
35.: Jackson LL. V.T.E. on an elevated maze. J Comp Psychol. 1943;36:99–107.
36.: Deacon RM, Rawlins JN. T-maze alternation in the rodent. Nature protocols. 2006;1:7–12. [PubMed: 17406205]
37.: Shukitt-Hale B, Casadesus G, Cantuti-Castelvetri I, Joseph JA. Effect of age on object exploration, habituation, and response to spatial and nonspatial change. Behav Neurosci. 2001;115:1059–1064. [PubMed: 11584918]
38.: Casadesus G, Shukitt-Hale B, Cantuti-Castelvetri I, Rabin BM, Joseph JA. The effects of heavy particle irradiation on exploration and response to environmental change. Adv Space Res. 2004;33:1340–1346. [PubMed: 15803625]
39.: Janus C, Pearson J, McLaurin J, et al. A beta peptide immunization reduces behavioural impairment and plaques in a model of Alzheimer’s disease. Nature. 2000;408:979–982. [PubMed: 11140685]
40.: Hall CS. Emotional behavior in the rat: Defecation and urination as measures of individual differences in emotionality. J Comp Psychol. 1934;18:385–403.
41.: Hrnkova M, Zilka N, Minichova Z, Koson P, Novak M. Neurodegeneration caused by expression of human truncated tau leads to progressive neurobehavioural impairment in transgenic rats. Brain Res. 2007;1130:206–213. [PubMed: 17169350]
42.: Games D, Adams D, Alessandrini R, et al. Alzheimer-type neuropathology in transgenic mice overexpressing V717F beta-amyloid precursor protein. Nature. 1995;373:523–527. [PubMed: 7845465]
43.: Kobayashi DT, Chen KS. Behavioral phenotypes of amyloid-based genetically modified mouse models of Alzheimer’s disease. Genes, Brain, and Behavior. 2005;4:173–196. [PubMed: 15810905]
44.: Chen G, Chen KS, Knox J, et al. A learning deficit related to age and beta-amyloid plaques in a mouse model of Alzheimer’s disease. Nature. 2000;408:975–979. [PubMed: 11140684]
45.: Dodart JC, Meziane H, Mathis C, et al. Behavioral disturbances in transgenic mice overexpressing the V717F beta-amyloid precursor protein. Behav Neurosci. 1999;113:982–990. [PubMed: 10571480]
46.: Morgan D. Learning and memory deficits in APP transgenic mouse models of amyloid deposition. Neurochem Res. 2003;28:1029–1034. [PubMed: 12737527]
47.: Gerlai R, Fitch T, Bales KR, Gitter BD. Behavioral impairment of APP(V717F) mice in fear conditioning: Is it only cognition. Behav Brain Res. 2002;136:503–509. [PubMed: 12429413]
48.: Justice A, Motter R. Behavioral characterization of PDAPP transgenic Alzheimer mice. Soc. Neurosci. Abstr. 1997;23:1637.
49.: Rauch TM, Welch DI, Gallego L. Hypothermia impairs performance in the Morris water maze. Physiol Behav. 1989;46:315–320. [PubMed: 2602474]
50.: Richardson R, Riccio DC, Morilak D. Anterograde memory loss induced by hypothermia in rats. Behav Neural Biol. 1983;37:76–88. [PubMed: 6882343]
51.: Hsiao K, Chapman P, Nilsen S, et al. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science. 1996;274:99–102. [PubMed: 8810256]
52.: Takeuchi A, Irizarry MC, Duff K, et al. Age-related amyloid beta deposition in transgenic mice overexpressing both Alzheimer mutant presenilin 1 and amyloid beta precursor protein Swedish mutant is not associated with global neuronal loss. Am J Pathol. 2000;157:331–339. [PMC free article: PMC1850215] [PubMed: 10880403]
53.: King DL, Arendash GW. Behavioral characterization of the Tg2576 transgenic model of Alzheimer’s disease through 19 months. Physiol Behav. 2002;75:627–642. [PubMed: 12020728]
54.: Arendash GW, King DL. Intra- and intertask relationships in a behavioral test battery given to Tg2576 transgenic mice and controls. Physiol Behav. 2002;75:643–652. [PubMed: 12020729]
55.: Westerman MA, Cooper-Blacketer D, Mariash A, et al. The relationship between Abeta and memory in the Tg2576 mouse model of Alzheimer’s disease. J Neurosci. 2002;22:1858–1867. [PMC free article: PMC6758862] [PubMed: 11880515]
56.: Riccio DC, Richardson R, Ebner DL. Memory retrieval deficits based upon altered contextual cues: A paradox. Psychol Bull. 1984;96:152–165. [PubMed: 6463163]
57.: Corcoran KA, Lu Y, Turner RS, Maren S. Overexpression of hAPPswe impairs rewarded alternation and contextual fear conditioning in a transgenic mouse model of Alzheimer’s disease. Learn Mem. 2002;9:243–252. [PMC free article: PMC187133] [PubMed: 12359834]
58.: Brunkan AL, Goate AM. Presenilin function and gamma-secretase activity. J Neurochem. 2005;93:769–792. [PubMed: 15857382]
59.: Shen J, Bronson RT, Chen DF, et al. Skeletal and CNS defects in Presenilin-1-deficient mice. Cell. 1997;89:629–639. [PubMed: 9160754]
60.: Spires TL, Hyman BT. Transgenic models of Alzheimer’s disease: Learning from animals. NeuroRx. 2005;2:423–437. [PMC free article: PMC1144486] [PubMed: 16389306]
61.: Holcomb L, Gordon MN, McGowan E, et al. Accelerated Alzheimer-type phenotype in transgenic mice carrying both mutant amyloid precursor protein and presenilin 1 transgenes. Nat Med. 1998;4:97–100. [PubMed: 9427614]
62.: Holcomb LA, Gordon MN, Jantzen P, et al. Behavioral changes in transgenic mice expressing both amyloid precursor protein and presenilin-1 mutations: Lack of association with amyloid deposits. Behav Genet. 1999;29:177–185. [PubMed: 10547924]
63.: Arendash GW, King DL, Gordon MN, et al. Progressive, age-related behavioral impairments in transgenic mice carrying both mutant amyloid precursor protein and presenilin-1 transgenes. Brain Res. 2001;891:42–53. [PubMed: 11164808]
64.: Dineley KT, Xia X, Bui D, Sweatt JD, Zheng H. Accelerated plaque accumulation, associative learning deficits, and up-regulation of alpha 7 nicotinic receptor protein in transgenic mice co-expressing mutant human presenilin 1 and amyloid precursor proteins. J Biol Chem. 2002;277:22768–22780. [PubMed: 11912199]
65.: Chishti MA, Yang DS, Janus C, et al. Early-onset amyloid deposition and cognitive deficits in transgenic mice expressing a double mutant form of amyloid precursor protein 695. J Biol Chem. 2001;276:21562–21570. [PubMed: 11279122]
66.: Hyde LA, Kazdoba TM, Grilli M, et al. Age-progressing cognitive impairments and neuropathology in transgenic CRND8 mice. Behav Brain Res. 2005;160:344–355. [PubMed: 15863231]
67.: Jin K, Galvan V, Xie L, et al. Enhanced neurogenesis in Alzheimer’s disease transgenic (PDGF-APPSw, Ind) mice. Proc Natl Acad Sci U S A. 2004;101:13363–13367. [PMC free article: PMC516572] [PubMed: 15340159]
68.: Casadesus G, Zhu X, Lee HG, et al. Neurogenesis in Alzheimer’s disease: Compensation, crisis, or chaos? In: Janigro D, editor. The cell cycle in the central nervous system. Totowa: Humana Press; 2006. pp. 359–370.
69.: Gotz J, Chen F, Barmettler R, Nitsch RM. Tau filament formation in transgenic mice expressing P301L tau. J Biol Chem. 2001;276:529–534. [PubMed: 11013246]
70.: Ramsden M, Kotilinek L, Forster C, et al. Age-dependent neurofibrillary tangle formation, neuron loss, and memory impairment in a mouse model of human tauopathy (P301L). J Neurosci. 2005;25:10637–10647. [PMC free article: PMC6725849] [PubMed: 16291936]
71.: Allen B, Ingram E, Takao M, et al. Abundant tau filaments and nonapoptotic neurodegeneration in transgenic mice expressing human P301S tau protein. J Neurosci. 2002;22:9340–9351. [PMC free article: PMC6758022] [PubMed: 12417659]
72.: Gotz J, Chen F, van Dorpe J, Nitsch RM. Formation of neurofibrillary tangles in P301l tau transgenic mice induced by Abeta 42 fibrils. Science. 2001;293:1491–1495. [PubMed: 11520988]
73.: Oddo S, Caccamo A, Kitazawa M, Tseng BP, LaFerla FM. Amyloid deposition precedes tangle formation in a triple transgenic model of Alzheimer’s disease. Neurobiol. Aging. 2003;24:1063–1070. [PubMed: 14643377]
74.: Oddo S, Caccamo A, Shepherd JD, et al. Triple-transgenic model of Alzheimer’s disease with plaques and tangles: Intracellular Abeta and synaptic dysfunction. Neuron. 2003;39:409–421. [PubMed: 12895417]
75.: Clinton LK, Billings LM, Green KN, et al. Age-dependent sexual dimorphism in cognition and stress response in the 3xTg-AD mice. Neurobiol Dis. 2007;28:76–82. [PMC free article: PMC2756084] [PubMed: 17659878]
76.: Pugh PL, Ahmed SF, Smith MI, Upton N, Hunter AJ. A behavioural characterisation of the FVB/N mouse strain. Behav Brain Res. 2004;155:283–289. [PubMed: 15364488]
77.: Lee HG, Casadesus G, Zhu X, et al. Challenging the amyloid cascade hypothesis: Senile plaques and amyloid-beta as protective adaptations to Alzheimer disease. Ann N Y Acad Sci. 2004;1019:1–4. [PubMed: 15246983]
78.: Nunomura A, Perry G, Pappolla MA, et al. RNA oxidation is a prominent feature of vulnerable neurons in Alzheimer’s disease. J Neurosci. 1999;19:1959–1964. [PMC free article: PMC6782583] [PubMed: 10066249]
79.: Nunomura A, Perry G, Pappolla MA, et al. Neuronal oxidative stress precedes amyloid-beta deposition in Down syndrome. J Neuropathol Exp Neurol. 2000;59:1011–1017. [PubMed: 11089579]
80.: Nunomura A, Perry G, Aliev G, et al. Oxidative damage is the earliest event in Alzheimer disease. J Neuropathol Exp Neurol. 2001;60:759–767. [PubMed: 11487050]
81.: Nunomura A, Chiba S, Lippa CF, et al. Neuronal RNA oxidation is a prominent feature of familial Alzheimer’s disease. Neurobiol Dis. 2004;17:108–113. [PubMed: 15350971]
82.: Odetti P, Angelini G, Dapino D, et al. Early glycoxidation damage in brains from Down’s syndrome. Biochem Biophys Res Commun. 1998;243:849–851. [PubMed: 9501012]
83.: Long JM, Mouton PR, Jucker M, Ingram DK. What counts in brain aging? Design-based stereological analysis of cell number. J Gerontol A Biol Sci Med Sci. 1999;54:B407–B417. [PubMed: 10568523]
84.: Calhoun ME, Wiederhold KH, Abramowski D, et al. Neuron loss in APP transgenic mice. Nature. 1998;395:755–756. [PubMed: 9796810]
85.: Morsch R, Simon W, Coleman PD. Neurons may live for decades with neurofibrillary tangles. J Neuropathol Exp Neurol. 1999;58:188–197. [PubMed: 10029101]
86.: Smith MA, Hirai K, Hsiao K, et al. Amyloid-beta deposition in Alzheimer transgenic mice is associated with oxidative stress. J Neurochem. 1998;70:2212–2215. [PubMed: 9572310]
87.: Wei X, Zhang Y, Zhou J. Alzheimer’s disease-related gene expression in the brain of senescence accelerated mouse. Neurosci Lett. 1999;268:139–142. [PubMed: 10406024]
88.: Butterfield DA, Poon HF. The senescence-accelerated prone mouse (SAMP8): A model of age-related cognitive decline with relevance to alterations of the gene expression and protein abnormalities in Alzheimer’s disease. Exp Gerontol. 2005;40:774–783. [PubMed: 16026957]
89.: King DL, Arendash GW, Crawford F, et al. Progressive and gender-dependent cognitive impairment in the APP(SW) transgenic mouse model for Alzheimer’s disease. Behav Brain Res. 1999;103:145–162. [PubMed: 10513583]

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Bryan KJ, Lee H, Perry G, et al. Transgenic Mouse Models of Alzheimer’s Disease: Behavioral Testing and Considerations. In: Buccafusco JJ, editor. Methods of Behavior Analysis in Neuroscience. 2nd edition. Boca Raton (FL): CRC Press/Taylor & Francis; 2009. Chapter 1.

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INTRODUCTION
BEHAVIORAL TESTS
TRANSGENIC MOUSE MODELS OF ALZHEIMER’S DISEASE
CONCERNS WITH TRANSGENIC MOUSE MODELS OF ALZHEIMER’S DISEASE
REFERENCES

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