Introduction

The identification of the Aβ peptide as a major component of amyloid deposited in brain vessels and subsequently of parenchymal plaques in the brains of Alzheimer’s victims [1] led to a focus on this molecule as a key element in the pathophysiology of Alzheimer’s disease (AD). Subsequent work found that some mutations causing the disease occurred in the amyloid precursor protein (APP) that is processed, in some circumstances, into the Aβ peptide [2]. Ultimately, all mutations causing AD have been demonstrated to result in overproduction of the long variant of the Aβ peptide [3]. Thus the pathology, genetics, and the in vitro neurotoxicity of the Aβ peptide has led to a focus on the aggregation and accumulation of this material as a prime target for therapies designed to treat AD.

As for other disorders, development of animal models to understand amyloid pathology became an important research goal. Our lab and many others attempted to mimic the AD condition in rodent brain by direct injections of the peptide [4, 5]. These efforts were largely unsatisfactory. Similarly, a number of other research groups attempted to create transgenic models overexpressing various forms of the APP gene. After many failures to create models that deposit amyloid in a manner similar to AD, and after a couple of retracted claims, the first APP transgenic mouse that deposited amyloid in a manner similar to AD was developed [6]. Because of the platelet-derived growth-factor promoter used, this mouse is referred to as the PDAPP mouse. Shortly thereafter, other APP transgenic mice were successfully developed with amyloid pathology similar to AD: the Tg2576 mouse of Hsiao [7] and the APP23 mouse of Novartis [8]. In a variety of informative ways, these mice have been crossed with other genetically modified mice. One of these was the presenilin-1 (PS1) mouse of Duff [9]. The presenilin gene codes for a critical component of the gamma secretase complex, which determines the length of the Aβ peptide during processing of the APP. Mutations of this gene can also cause early-onset AD in humans. Our group and several others found that crosses between the PS1 mice and the APP mice resulted in accelerated amyloid pathology as the mice age [10]. This chapter focuses on the behavioral abnormalities in the APP transgenic models. It is important to recognize that these are not models of AD, as they lack the tau pathology and the neuron loss found consistently in the human disorder. However, the mouse models mimic in considerable detail the amyloid deposition found in the human disease, and they are all largely similar, irrespective of the mutations used or the promoters employed.

Memory Deficits Correlate with Aβ Load

The first to demonstrate that APP transgenic mice had both amyloid deposits as well as memory deficits was Hsiao et al. [7]. They demonstrated deficits in a reference-memory version of the open-pool water maze [11], with the deficits first appearing at an age when the amyloid plaques started to appear (10 to 11 months). A number of studies have now found within-age-group correlations between spatial-navigation performance in various forms of the water maze and one or more measures of amyloid load in several different APP lines [12–20]. In some sense, given the perception that rodent memory-assessment methods have some imprecision and that the number of mice included in such studies is typically small (less than 20), the correlation was surprising and argued for an intimate relationship between amyloid load measures and memory dysfunction. This led to the somewhat comforting conclusion that the amyloid plaques and attendant disruptions of neuronal architecture with dystrophic neurites and activation of proinflammatory states of glial cells were responsible for the memory loss. However, even these studies were not always consistent regarding the pool of Aβ that correlated best with memory loss.

There are several domains in which amyloid loads can be measured. The pathologist examines amyloid histologically and identifies two major forms. One form is fibrillar aggregates, stained by Congo red or Thioflavine S, that form compacted amyloid plaques (associated with dystrophic neurites) in the parenchyma or amyloid angiopathy in the vasculature. A second, more widely spread form of Aβ is stained only immunohistochemically and is referred to as diffuse deposits. The neurochemist views Aβ content from the perspective of solubility in different reagents. There are water-soluble fractions, detergent-soluble fractions, and water-insoluble fractions (typically dissolved in concentrated formic acid or guanidinium solutions). Most often, these are analyzed by sandwich enzyme-linked immunosorbent assays (ELISA). A third domain is that of the physical chemist, who views the Aβ peptide from the perspective of its secondary and tertiary structure. There are many forms of Aβ: monomers, multimers varying from 2mers to 20mers that are collectively called oligomers, protofibrillar forms in which Aβ is aggregated in a beta-pleated sheet structure, and finally mature 6- to 9-nm fibrils, which are the forms thought to form the amyloid plaques. One of the great unanswered questions in Alzheimer research is how these different fractions relate to each other. As a further level of complexity, there are two major C-terminal length variants of Aβ ending at amino acid 40 or 42. These appear to be distributed differently, with vascular amyloid deposits being primarily of the Aβ 40 form and diffuse Aβ ending primarily at amino acid 42 [21, 22]. The final common path of mutations causing early-onset AD in humans is to increase the amount of the long form of Aβ [3]. In general, the more-hydrophobic Aβ42 variant is more prone to forming aggregates.

The studies correlating memory loss with amyloid increases used a variety of indices for amyloid load. Often, only one of several measurements of amyloid load correlated with behavior, and this was not always the same measure or even in the same brain regions (hippocampus versus cortex). Undermining the association between congophilic amyloid plaques and memory disruption was the increasing number of observations of memory dysfunction in mice that either never developed amyloid pathology [23–28] or exhibited some form of memory disruption prior to the appearance of amyloid deposits [15, 26, 29–32]. In many instances, the severity of the memory deficits worsened as mice grew older [30, 33, 34]. However, the worsening of memory function as mice aged was not linearly related to the increasing amount of Aβ in the brain [15, 17]. Intriguingly, not all reports find memory dysfunction in transgenic rodents that overexpress APP. For example, Savonenko et al. [35] were unable to detect changes in two APP mouse lines that deposit amyloid, and Ruiz-Opazo [36] found that transgenic rats expressing APP actually had protection from age-associated memory deficits.

Although the transgenic mice are very similar genetically, there are large variations in the extent to which they overproduce Aβ. In our APP+PS1 model, we find roughly a two-fold range of amyloid load in mice of the same age and gender. In the PDAPP mouse line, some transgenic mice never deposit amyloid. These large variations permit identification of correlations with behavior within an age group. If the amyloid loads were uniform, correlations within age groups would be nearly impossible. However, it is likely that whatever factors are accounting for this variation in amyloid load, they are affecting all of the pools of Aβ similarly. Thus mice with a high level of soluble Aβ when young are likely destined to have high levels of deposited Aβ as they age. So too, all pools of Aβ are likely to covary within individual members of an age cohort; those mice with the highest levels of deposited Aβ are likely to have higher levels of soluble Aβ, insoluble Aβ, oligomeric Aβ, etc. In this sense, a correlation with one pool need not indicate that it is the one causing the memory disruption; indeed, it may be acting as a surrogate for other, more difficult to measure pools. At the moment, there is some evidence that an oligomeric pool of Aβ may be most closely related to the degeneration in AD [37]. However, this pool has been notoriously ephemeral; reliable assays have not been widely adopted, and the oligomers appear to rapidly convert to other forms. It is not certain that different investigators are studying the same entity when each refers to oligomeric pools. At the recent Alzheimer Conference (2004), Karen Ashe presented impressive data supporting an oligomeric form of Aβ (referred to as Aβ*) as being most closely related to memory loss in younger Tg2576 transgenic mice. The reader is advised to monitor progress in this area critically and with some caution, but the data collected thus far is consistent with this hypothesis. For example, some forms of fibrillar Aβ may not be apparent by traditional methods. Richardson et al. [31] found extracellular Aβ fibrils in memory-deficient APP mice well before the appearance of histologically identifiable deposits.

In summary, memory dysfunction is a very consistent part of the APP mouse phenotype. Correlations with amyloid load suggest that this plays a causal role in the memory disruption. However, when examined across age groups, the correlation breaks down, with old mice having much more amyloid than predicted by their memory deficits. Still, given the potential for ceiling effects in the behavioral tests and the likelihood that amyloid effects on memory may be nonlinear and exhibit saturation, these data alone are not sufficient to rule out observable amyloid pools as the major factor in the memory impairments developed by the transgenic mice.

Interventions Improving Memory in APP Transgenic Mice

A number of approaches have been proposed to reduce Aβ loads in AD patients and, in many instances, these are first being tested in the APP transgenic mouse models of amyloid deposition (Table 10.1). If the hypothesis that amyloid causes memory loss is to hold merit, then amyloid-reducing treatments should also protect the mice from memory disruptions. To a large extent, this outcome has been demonstrated, although the Aβ pool responsible for the benefits is not clear.

TABLE 10.1

Therapeutic Interventions Improving Memory Performance of APP Transgenic Mice

In 1999, Schenk et al. [38] found that vaccines against the Aβ peptide dramatically reduced the amyloid loads in PDPP transgenic mice. Our research group, believing that inflammation was a contributing factor in the disease, attempted to show that the microglial activation associated with such immunization would worsen the memory, not protect it. Within weeks of the publication, we were vaccinating our APP+PS1 mice against Aβ at an age prior to the onset of spatial-navigation-memory dysfunction. We tested mice at an age before the onset of memory loss in the working-memory version of the radial arm water-maze task. We found all mice capable of robust learning of platform location, even those vaccinated against Aβ. However, when tested several months later, we found that the mice given control inoculations had lost the ability to remember platform location, but the anti-Aβ-vaccinated mice could ultimately learn as well as the nontransgenic littermate controls [39]. Similar data were collected in parallel by the Toronto group using a different APP mouse model (CRND8 [40]). Thus this surprisingly effective treatment not only reduced amyloid loads, but also protected mice from memory deficits.

Subsequent studies transitioned from the active immunization protocols used by Schenk et al. [38] to passive immunization with anti-Aβ monoclonal antibodies. Dodart et al. [41] and Kotilinek et al. [42] both observed reversal of memory deficits in APP transgenic mice using different antibodies and different models. However, the striking feature of both studies was the rapidity of the reversal; as little as a single dose of antibody reversed the hole-board deficits in PDAPP mice, and three injections reversed water-maze deficits in Tg2576 mice. In neither circumstance was the measurable form of Aβ load reduced by these treatments. These data are some of the strongest evidence for considering small, difficult-to-measure soluble pools — rapidly affected by antibodies — as being the form of Aβ most proximally linked to memory dysfunction in the APP transgenic mice.

Some genetic manipulations have been found to modify the mnemonic dysfunction of APP transgenic mice. One of the first observations was that by Raber et al. [43]. Using the J9 APP mouse, they crossed these mice with transgenic mice expressing hApoE3 or hApoE4 on an mApoE-null background. They found that the ApoE3 protein was capable of reversing the memory deficits in the J9 mice but that the ApoE4 gene could not. These results suggest that ApoE3 can counteract the memory-disrupting action of Aβ, while the E4 variant, linked to increased risk for AD, cannot. Another genetic manipulation found to completely eliminate both amyloid production and memory loss was a knockout of the BACE1 gene [44]. BACE1 is a protease mediating the APP cleavage at the N-terminal of Aβ. Alternative APP processing by another enzyme, alpha secretase, precludes Aβ formation. One concern in the transgenic field was that APP overexpression, not just Aβ overproduction, was responsible for the memory problems in the mice. The Tg2576 mice raised on the BACE1-null background failed to develop memory loss. Moreover, electrophysiological abnormalities in these mice were avoided. Thus, APP overexpression alone is not responsible for these aspects of the APP mouse phenotype.

Another genetic manipulation impacting cognitive performance in transgenic mice involves the RAGE (Receptor for Advanced Glycation Endproducts) protein, a receptor binding a number of modified proteins that also binds Aβ. APP mice overexpressing RAGE in neurons develop memory deficits at a younger age than unmodified APP mice. APP mice expressing a dominant-negative form of RAGE are protected from memory loss [45]. It is unclear to what extent these manipulations also modified Aβ accumulation in these mice. RAGE has been proposed to transport Aβ from blood into brain [46], possibly modifying brain Aβ content.

Drugs have also been found to reverse or prevent the memory dysfunctions in APP transgenic mouse models. Ginkgo biloba, an herbal agent often promoted as a remedy for age-associated memory loss and AD, but with minimal support in the human literature [47], was found to prevent memory loss in Tg2576 mice when administered from 8 to 14 months of age [48]. Surprisingly, this was associated with increased protein carbonyl formation but no changes in amyloid loads measured by ELISA. A drug with demonstrated benefits for AD patients (memantine) also alleviates memory deficits after 3 weeks of treatment in APP+PS1 mice [49]. Treatment with antiCD40L antibodies, previously demonstrated to reduce Aβ deposition [50], also protects APP+PS1 transgenic mice from memory impairments [51]. Another treatment argued to reduce Aβ (melatonin [52, 53]) also prevents memory disruptions in the APP695 mouse when administered from 5 to 9 months of age [54]. Most recently, a remarkable delayed effect was observed with the phosphodiesterase-inhibitor rolipram [55]. In this study, APP+PS1 mice were treated for 3 weeks with the agent when the mice were 3 months of age and the first amyloid deposits were appearing. Even though the drug was discontinued for at least 2 months, when tested at 6 to 7 months of age, mice receiving the drug scored significantly better than mice given vehicle treatments on contextual fear conditioning, radial arm water maze, and open-pool water-maze tasks. The treatment also reversed long-term potentiation (LTP) deficits and increased cyclic AMP response-element binding protein (CREB) phosphorylation at 7 to 8 months. No changes in ELISA-measured Aβ were found at 7 to 8 months. Taken at face value, these data argue for a permanent rearrangement of the brain’s response to Aβ caused by this agent. Estrogen replacement to ovariectomized mice also improved memory in APP+PS1 mice, but the treatment produced similar effects in nontransgenic mice as well as transgenic animals [56], demonstrating no selectivity of estrogen for the amyloid-depositing mice.

In summary, a number of manipulations impact the memory phenotype of APP transgenic mice. Most importantly, the BACE-null APP mouse is protected from memory loss, verifying that it is the Aβ overproduction associated with the transgenes that is responsible for the impairments. Although some of these manipulations are directed at reducing amyloid, many of the successful treatments have no apparent action on amyloid accumulation (at least in the pools measured). This implies that (a) there is a chain of events associated with amyloid-induced memory deficits in APP mice and (b) interventions may be directed either at the amyloid deposits themselves or at downstream events in the process, leading to consolidations that are otherwise disrupted by the presence of Aβ. Thus in AD, as in other chronic degenerative diseases (e.g., heart disease), there will be multiple therapeutic targets to improve memory functions. In fact, the combined efficacy of donepezil and memantine in AD cases is the first step in a graded series of improvements in managing the disease [57].

Mechanisms of Aβ-Associated Memory Impairment in Transgenic Mice

Although the APP transgenic mouse is a reasonable model for amyloid deposition, the absence of significant neuron loss implies that it is not a good model for AD [58–62]. Thus, one major contribution to the dramatic cognitive declines observed in AD cases is not present in these murine models. Still, the memory impairments are a consistent feature of the APP mouse phenotype and, to a large extent, have similar characteristics, applying primarily to hippocampus-mediated tasks. Assuming that the mechanism(s) causing memory impairment in APP mice contribute to at least early mnemonic changes found in AD cases, an understanding of these mechanisms is likely to suggest additional therapeutic targets.

An obvious correlate of memory function to examine in APP transgenic mice is long-term potentiation (LTP), a form of synaptic plasticity often argued to underlie learning. Unfortunately, the phenotypic changes in synaptic transmission in APP transgenic mice have not been as uniform as the changes in memory function (Table 10.2). The first study examining LTP in the Tg2576 mice found normal synaptic transmission in 14- to 17-month-old mice but reduced hippocampal LTP [63]. Noting that many ex vivo hippocampal slices from APP mice died unless kynurenic acid was included during slice preparation, the researchers also measured LTP in vivo and found a similar reduction in APP transgenic mice. When APP mice were combined with nontransgenic mice, there was a correlation between T-maze performance and the extent of LTP. However, when evaluating the same mice, Fitzjohn et al. [64] found normal paired pulse and long-term potentiation but impaired synaptic transmission at 18 months. In 27- to 28-month-old PDAPP mice, Larson et al. [65] found results similar to those described by Fitzjohn et al. [64], with impaired synaptic activity but with LTP maintained. Similar observations were made by Hsia et al. [26] and Roder et al. [66] in 12- and 18-month-old APP23 mice and by Harris-Cerruti et al. [67]. Perhaps most atypical was the report by Jolas et al. [68]. They found that LTP was increased in slices from 5-month-old CRND8 APP mice relative to nontransgenic animals but that field potential slopes declined. Dewachter et al. [69] found an LTP deficit in an APP mouse that was rescued when the mice were bred onto a targeted PS1-null condition. However, the memory deficits in this mouse were not rescued by the PS1-null condition, arguing that something more than LTP changes were involved in the memory dysfunction. Trinchese et al. [17] found LTP deficits in APP+PS1 mice at 3 months when plaques were first appearing. The extent of the LTP deficit progressed as the mice aged, in parallel with reductions in working memory on the radial arm water maze. In a slightly different APP+PS1 mouse, Gureviciene et al. [70] found normal LTP induction and maintenance for 60 min in vitro. Yet, when potentiating the perforant path in vivo, they found more-rapid decay of the potentiation when measured 24 h later. Although a simple summary of these disparate results is not straight forward, it seems likely that APP mice have some disruption of normal synaptic physiology. It may be hard to measure LTP in the same manner if baseline parameters are not consistent in transgenic and nontransgenic mice. The two in vivo studies appear to consistently identify reductions in LTP, and a more rapid decay of a potentiated synapse would appear consistent with the behavioral literature. Still, this is an area requiring more effort before reaching consensus.

TABLE 10.2

Electrophysiological Plasticity in APP Transgenic Mice

As mentioned above, neuron loss is not a significant feature for the APP transgenic mouse phenotype. However, another possibility is that there is synapse loss, argued to be the best pathological correlate of cognitive decline in AD [71]. Here the data are mixed. Initial results suggested loss of synaptophysin fluorescence in the APP mice [6, 72], often in the absence of detectable amyloid deposits [26, 27]. In some instances, it is possible that these changes were associated with reduced volumes of the corresponding structures [12, 73, 74]. Other studies failed to find reductions in synaptophysin staining [58–61] or even increases in synaptophysin staining [12, 75]. Some of the differences may be attributable to different mouse lines or the brain regions studied. Thus far, most studies finding deficits used fluorescence detection, while those not finding differences used peroxidase reaction product for detection. Furthermore, given the enrichment of synaptophysin in the dystrophic neurites surrounding plaques [21], determining how each study in plaque-bearing mice dealt with these sources of synaptophysin reactivity is an important consideration. It is likely that there is some structural loss of presynaptic markers in select regions of the transgenic mice, but this loss is likely modest.

Perhaps more important than structural changes are functional changes in synaptic markers. Several years back, our group compared the gene-expression profiles of memory-deficient 16- to 18-month-old APP+PS1 mice to nontransgenic littermates in both plaque-bearing regions (hippocampus, cortex) and plaque-free regions (cerebellum, brain stem) using both microarrays and real-time PCR (polymerase chain reaction) [76]. We used several criteria (size of difference, statistical significance, selectivity for plaque-bearing regions) to identify a small number of genes (fewer than 50) that were modified only in the plaque-bearing regions of transgenic animals. Many of these were associated with inflammation in the vicinity of the plaques, and some were associated with the transgene itself, but several were unexpected findings and had been previously linked to learning and memory. One category included immediate early genes such as arc and zif 264. Down-regulation of these genes causes consolidation failures in rodent models of memory or synaptic plasticity (referenced in Dickey et al. [77]). Others were postsynaptic proteins, such as the NMDA (N-methyl-D-aspartate) receptor subunit NR2B. PSD-95 (Post Synaptic Density Marker-95), or calmodulin kinase II-, is also linked to neural plasticity. In general, the RNA content for a number of presynaptic markers, including synaptophysin, remained stable. A similar pattern of changes, with deficiencies of postsynaptic markers (debrin, fractin) and stability of presynaptic markers (synaptophysin), was observed by Calon et al. [78] in 16- to 18-month-old Tg2576 mice. For the immediate early genes, our group subsequently identified that the basal level of expression was unaffected in the transgenic animals but that the induction caused by exposure to a novel environment was suppressed [77]. Palop et al. [79] observed a similar reduction in the immediate early gene c-fos in the J20 APP transgenic mouse line. This marker and reductions in the calcium-regulated protein calbindin were significantly correlated with Aβ1–42 levels and memory impairment in these mice.

We also found that sodium potassium ATPase, the enzyme using 40% of the brain’s ATP, was decreased at both the message level and by enzymatic assay in plaque-bearing regions [80]. When evaluated immunohistochemically, there was a paucity of immunoreactivity for the enzyme in a penumbral region surrounding each Congo red-stained deposit. Given the overlap of this zone with the location of the swollen neurites, we speculated (“wildly” so, to some reviewers) that a local loss of ionic homeostasis might lead to osmotic imbalance in the vicinity of the plaques, leading to swelling of the neural processes. This might also alter the electrotonic properties of the dendrites associated with these processes, leading to impaired transmission of postsynaptic potentials. Clearly, further efforts will be needed to test this hypothesis, but 30% reductions in the activity of this critical enzyme are likely to have significant impact on neural function.

Conclusions

The APP transgenic mice are a very good model of the amyloid deposition found in Alzheimer dementias. The patterns of deposition, regional distribution, and even the anatomical localization of the short and long variants mimic the human disease. The APP mouse phenotype also consistently includes progressive memory impairment. This phenotype appears to be due to Aβ accumulation and not overexpression of APP, as the BACE1-null background, which overproduces APP but not Aβ, rescues the memory phenotype. Still, none of the readily measurable pools of Aβ seem to correlate linearly with this memory loss, suggesting that an occult pool, possibly oligomeric, is more directly linked to the memory deficits.

A number of manipulations, most notably immunotherapies, have been found to regulate the memory phenotype. Not all successful manipulations modify Aβ levels (at least detectable forms of Aβ). This argues that there are steps in memory processing downstream from the site of Aβ action where interventions can be targeted. It is plausible that even treatments targeted at Aβ might have their greatest effect at downstream sites, e.g., reduced inflammation, independent of Aβ reductions. It is likely that AD, like many other degenerative disorders, will be managed through multiple treatment modalities. An overnight cure seems unlikely.

The mechanisms mediating these memory deficiencies are not clear. Given that we cannot identify a pool of Aβ that is intimately linked to the memory impairments, it is difficult to identify targets for this Aβ pool and their impact on downstream effectors. A number of candidates have been identified, but at the moment these can only be viewed as associated with the memory disruptions. Causal linkages will be difficult to prove.

With respect to AD, the value of the APP transgenic models is to screen drug candidates proposed to act on the human disease by reducing amyloid. It is less certain whether agents protecting from memory loss in the APP mice, independent of their influence on Aβ effects, will translate into the human condition. This will depend upon the extent to which failing memories in AD are due to amyloid-associated changes in neural processing versus structural loss of neurons and synapses.

Acknowledgments

The author has received support from AG 15490, AG 18478, and NS 48335 from the National Institutes of Health (NIH). The author also wishes to thank Karen Hsiao Ashe and Karen Duff for early access to their transgenic mice.

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