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The study of Alzheimer’s disease (AD) pathogenesis requires the use of animal models that develop some amount of amyloid pathology in the brain. Aged canines (beagles) naturally accumulate human-type amyloid β-peptide (Aβ) and develop parallel declines in cognitive function. However, the type and quantity of biochemically extracted Aβ in brain and cerebrospinal fluid (CSF), its link to aging and similarity to human aging, has not been examined systematically. Thirty beagles, aged 4.5–15.7 years, were studied. Aβ40 and Aβ42 were measured in CSF by ELISA, and from SDS and formic acid extracted prefrontal cortex. A sample of the contralateral hemisphere, used to assess immunohistochemical amyloid load, was used for comparison. In the brain, increases in Aβ42 were detected at a younger age, prior to increases in Aβ40, and were correlated with an increased amyloid load. In the CSF, Aβ42 decreased with age while Aβ40 levels remained constant. The CSF Aβ42/40 ratio was also a good predictor of the amount of Aβ in the brain. The amount of soluble oligomers in CSF was inversely related to brain extractable Aβ, whereas oligomers in the brain were correlated with SDS soluble Aβ42. These findings indicate that the Aβ in the brain of the aged canine exhibits patterns that mirror Aβ deposited in the human brain. These parallels support the idea that the aged canine is a useful intermediate between transgenic mice and humans for studying the development of amyloid pathology, and is a potentially useful model for the refinement of therapeutic interventions.
Alzheimer’s disease (AD) is a progressive and gradual decline in cognitive function accompanied by extensive neurodegeneration. It is the pattern of this neurodegeneration within the brain, the loss of specific populations of neurons and synapses, which distinguishes the clinical presentation of AD from other, less common, forms of dementia. Within the brain itself, the hallmark signs of AD include both extracellular deposition of the amyloid-β peptide (Aβ) and the intracellular accumulation of an abnormally phosphorylated form of the microtubule associated protein tau. Abnormal tau, found in neurofibrillary tangles, is also found in a number of other neurodegenerative diseases. These other diseases, the broader class of tauopathies, do not feature Aβ deposits as a primary feature of pathology, indicating that Aβ deposition is relatively specific to AD .
The Aβ peptide, derived from the larger amyloid-β precursor protein (APP), was first identified more than 25 years ago [2–4]. APP is sequentially cleaved by two membrane-bound endoprotease activities, β- and γ-secretase. β-secretase (primarily BACE1 in the brain ) first cleaves APP to release an amino terminal derivative, sAPPβ. A fragment of 99 amino acids (CTFβ, which begins with the N-terminal aspartyl residue of Aβ) remains membrane bound, and is in turn rapidly cleaved by γ-secretase to generate Aβ. Cleavage by γ-secretase occurs within the membrane, and is relatively unselective, resulting in the production of a population of heterogenous peptides. The most common form of Aβ, 40 amino acids long (Aβ40), is the most abundant (~80–90%), followed by a more hydrophobic 42 amino acid form (Aβ42, ~5–10%) .
The issue of how much Aβ contributes directly to neurodegeneration has been a topic of debate for some years. It is currently believed that the toxic form of the peptide may be a higher molecular weight, oligomeric form that can readily diffuse within the brain and either directly damage neurons or interfere with their normal function [7, 8]. Oligomers form readily from the Aβ42 peptide, less well so from the more abundant Aβ40 [9, 10], suggesting that the C-terminus is critical for oligomer formation to occur. Aβ dimers isolated from AD brain and CSF disrupt synaptic function [11, 12]. Just how oligomeric Aβ causes these effects has yet to be determined, although both receptor-mediated effects as well as direct interactions with the membrane bilayer are possibilities [13, 14].
Alzheimer’s disease is specific to humans – even our most closely related primate relatives do not develop anything that can be considered to be bona fide AD. Hence, much of our understanding of how Aβ pathology develops has been driven by studies in animal models. Although there is no model that captures all the hallmarks of AD, we are able to routinely model Aβ deposition. The study of AD pathogenesis in animal models is primarily focused on transgenic mice over expressing human mutant APP at high levels, typically under the control of a heterologous promoter , and insights from these models have been indispensible for our understanding of amyloid deposition in vivo [16–18]. Even though over expression of APP is not an absolute requirement for the development of amyloid pathology [19, 20], the introduction of some combination of familial AD mutations into APP or presenilin 1 (or both) does appear essential for the development of robust Aβ deposition. Although nonhuman primates (NHPs) have near identical APP sequence to humans, and are our closest evolutionary cousins, they develop surprisingly little AD-like neuropathology with age. While older NHPs typically show small amounts of amyloid deposition, this is quite modest compared to cases of AD [21–23], and is far less than that of the aged canine. True neurofibrillary tangle pathology is not a typical feature of pathology in NHPs , although chimpanzees  and baboons  may be an exception.
Aged canines also develop substantial amyloid deposition with age. Unlike aged NHPs, which may require several decades, canines develop pathology at a much younger age . Aged canines (beagles) naturally accumulate human-type Aβ [27, 28] with age [29, 30] and this parallels a decline in cognitive function [31, 32]. Aβ42 accumulation within diffuse plaques in the brain correlates with more severe learning and memory deficits in aged canines [31–33]. The quantity of deposited Aβ is often comparable to AD cases, and a substantial proportion is highly insoluble . This suggests that the amyloid in the aged canine quantitatively overlaps with the amount of amyloid in human disease. Thus, canines may represent a useful intermediate between genetically modified mouse models and AD. In this regard it is worth noting that immunization with fibrillar Aβ in aged canines may be a better parallel to human trials with this therapeutic approach than preclinical mouse models [34, 35].
In spite of significant progress in understanding the development of amyloid pathology in the brain of the aged dog, we still know very little about the interplay between the amount of Aβ in the brain and the levels of soluble oligomers in both the brain and CSF, and their link to age. This is an interesting question, since CSF Aβ42 continues to undergo extensive evaluation as a potential biomarker of AD and the development of amyloid pathology in the brain . From the perspective of a useful preclinical model, determining whether or not CSF Aβ levels predict brain levels would establish a biomarker for the selection of “at risk” animals for use in the development of novel therapeutics.
Thirty beagles, ranging in age from 4.5 – 15.7 years, were included in the study. All animals were from the colony at the Lovelace Respiratory Research Institute (Albuquerque, NM), and were housed either singly or in pairs in kennel buildings with indoor/outdoor runs measuring 91 cm × 600 cm. Animals were fed Wayne Mini Lab Dog Diet 8759 dog food once daily (Teklad Pioneer Lab Diets, Madison, WI) and water was available at all times. All dogs received regular veterinary care.
Animals were anesthetized with sodium pentobarbital (Nembutal) in accordance with approved IACUC protocols. The brains were removed and alternating 0.5 cm coronal sections were frozen at −80°C or fixed in 4% paraformaldehyde at 4°C for 72 hours. The fixed tissue was then transferred to phosphate buffered saline (pH 7.4, with 0.02% sodium azide) and stored at 4°C. Aβ was detected using a rabbit polyclonal antibody, designated anti-Aβ42, raised against a synthetic Aβ peptide containing amino acids 1 through 42 . Fifty μm vibratome sections were taken from the dorsolateral prefrontal cortex and pretreated for 4 minutes with 90% formic acid (FA) prior to overnight incubation at room temperature in anti-Aβ 42 (1:500) in Tris-saline with 2.0% bovine serum albumin and 0.1% Triton X-100. Bound antibody was detected using a biotinylated anti-rabbit ABC peroxidase kit and visualized with DAB substrate (Vector Labs, Burlingame, CA).
To determine Aβ load, five semi-random fields from each section (2 sections in total from each animal) were digitized and the cross-sectional area occupied by Aβ quantified using gray scale thresholding as described previously . Briefly, a random region within a random 10X field with Aβ deposition was centered and digitized at 20X. Additional fields were semi-randomly selected by moving laterally by one field. A Sony high-resolution CCD video camera (XC-77) and the built-in video capture capabilities of a Macintosh 8100/80AV were used to digitize images. All sections from a given region were captured sequentially during one session and were analyzed blind with respect to age. Files were saved as gray scale (256 level) images that were subsequently binarized with a cutoff value of 110. This eliminates the background along with some faint Aβ immunoreactivity, and is hence a conservative estimate of the actual amount . Public domain image analysis software (NIH Image 1.55) was used to calculate the percentage area occupied by Aβ.
Frozen tissue samples were directly homogenized in 70% formic acid (FA; 1.0 ml / 150 mg of tissue), with complete protease inhibitor cocktail (PIC; Roche). Samples were centrifuged at 100,000 × g for 1 hour, and the aqueous layer collected, aliquoted and frozen at −80°C. For the assay [20, 37, 38], samples were initially neutralized by a 1:20 dilution in TP buffer (1 M Tris base, 0.5 M Na2HPO4), followed by a further dilution as needed (but at least 1:1) in capture buffer [0.02 M sodium phosphate buffer (pH = 7), 0.4 M NaCl, 2 mM EDTA, 0.4% Block Ace (Serotec), 0.2% bovine serum albumin, 0.05% CHAPS, and 0.05% sodium azide]. CSF samples were diluted in capture buffer, as necessary. Standard curves of either synthetic Aβ40 or Aβ42 were prepared in the same buffer as the samples. All samples and standards were run at least in duplicate on Ab3160 coated ELISA plates, followed by detection with either HRP conjugated BA27 (for Aβ40) or BCO5 (for Aβ42). Aβ values were determined by comparison to the appropriate standard curve. An additional subset of samples (N=14) across a range of ages were extracted first in 2% SDS (+PIC), centrifuged for 30 minutes at 20,000 × g, and the supernatant collected and frozen. The resulting pellet was then extracted in 70% FA, as described above.
PBS soluble fractions were tested for total protein concentration by the BCA protein assay and diluted with double-distilled water to a standardized concentration. 7.6 μg of total protein was spotted onto a nitrocellulose membrane (Protran BA83, 0.2 μm pore size). Samples were dried and then blocked (10% Non-Fat Milk in Low-Tween TBS, pH 7.6 (20 mM Tris, 137 mM NaCl, 0.001% Tween 20) for 1 hour at room temperature. After blocking, the blot was washed in Low-Tween TBS, pH 7.6 (20 mM Tris, 137 mM NaCl, 0.001% Tween 20) three times for 5 minutes each. The blot was then incubated in anti-oligomer antibody (A11-1:2000 ) in 5% Milk- Low Tween TBS overnight at 4°C. After washing the blot 3 times for 5 minutes each, the blot was transferred into goat-anti-rabbit IgG (Jackson Immuno Research), diluted 1:12000 in Low-Tween TBS. Secondary antibody incubation was for 1 hour at room temperature. After the final 3 washes (5 min each), the blot was exposed to ECL reagent (Amersham) for 1 minute, exposed to film and the film developed. The film was scanned and pixel density was determined using Scion Imaging Software (Version: Beta 4.0.2). Experiments were repeated twice and the average densities used in data analyses.
For additional comparison, SDS extracts were run on 10–20% SDS-PAGE gels, transferred to nitrocellulose, and blotted with 1 μg/ml of 6E10 (which will detect fragments of the amyloid-β precursor protein that contain Aβ, as well as Aβ oligomers). Analyses were performed on the A11 signal since this represents “total oligomers”, and since it cannot be determined which bands should be summed for a comparable measure with 6E10.
SPSSR® for Windows was used to test for effects of age, and to determine the significance of all correlations and regression analyses.
In the brain, both Aβ40 (p<0.001) and Aβ42 (p<0.001) increased exponentially with age (Fig. 1A), as did the Aβ42 load (p<0.001) as determined by immunohistochemical analysis (Fig. 1B). Immunohistochemical Aβ42 load and total Aβ42 determined by ELISA were significantly correlated with each other (R2=0.23, p<0.01). Aβ42 deposition began at a slightly earlier age (7.6 years) as compared to Aβ40 (8.1 years), based on examination of the x-intercept data. The extractable Aβ in younger animals was primarily Aβ42, with Aβ40 appearing only in the older subjects, similar to what has been observed in humans. To examine this point further, animals were grouped into three age groups of approximately equal width (aged 4 to 8 years, N = 8; aged 8 to 12 years, N = 9; aged 12 to 16 years, N = 13); this illustrates that Aβ42 is much more prominent in middle aged (ranging from 8–12 years of age) canines, with Aβ40 appearing in substantial quantities only in later years (Fig. 1C). This is also reflected in the ratio of Aβ42/Aβ40, which tended to decrease with age in the brain (p<0.04; Fig. 1D). As with a previous report in canine brain, there are a small number of individual aged dogs (>10 years) that show low levels of Aβ .
In CSF, Aβ40 remained remarkably stable with age while Aβ42 decreased slightly (Fig. 2A). We expressed the Aβ42 data as a percentage of the total, a common method of examining Aβ in biological fluids that better controls for individual variability. The percentage (or ratio) of Aβ42 undergoes a linear decrease with increasing age (p<0.001; Fig. 2B). Lower percentages of CSF Aβ42 were correlated with larger amounts of formic acid extractable Aβ42 in the brain (p<0.001), as well as brain Aβ40 (p<0.005; Fig. 2C). Similarly, higher prefrontal immunohistochemical Aβ42 loads were correlated with lower CSF Aβ42 percentages (p<0.05; Fig. 2D).
Finally, we performed an examination of A11 positive oligomers in the brain and CSF within a subset of the subjects (Fig. 3A). As expected, 6E10 immunblots run for comparison purposes displayed bands corresponding to full length APP, possible fragments of APP, and various oligomeric species of Aβ. Brain A11 immunoreactivity did not correlate with the total amount of either Aβ40 or Aβ42 (data not shown). However, although the number of subjects that overlapped on this measure was small, A11 immunoreactivity against soluble oligomers did correlate with SDS extractable Aβ42 (R2=0.68, p<0.02) (Fig. 3B). In the CSF, A11 immunoreactivity was inversely correlated with both Aβ40 (R2=0.24, p<0.05) and Aβ42 (R2=0.26, p<0.04) in the prefrontal cortex, indicating that as the total amount of brain Aβ increases, the amount of soluble oligomers in the CSF decreases (Fig. 3C).
Formic acid extractable Aβ40 and Aβ42 increases in the brain with age in canines, and parallels similar changes in immunohistochemically detectable Aβ. In contrast, in the CSF, Aβ42 decreased with age while Aβ40 showed little change. Decreasing Aβ42 in the CSF is consistent with the concept of a “peripheral pool effect”: as Aβ is deposited in brain, soluble CSF pools decrease . The association between brain and CSF Aβ is similar to that observed for both AD patients [41–44] and transgenic mice . Brain extractable Aβ from younger animals was almost exclusively Aβ42, with Aβ40 appearing later. This extends earlier immunohistochemical studies in the canine showing that Aβ40 accumulation occurs at later ages than Aβ42, paralleling observations in human brain [33, 45].
As the proportion of Aβ42 in the CSF decreased, brain Aβ accumulation increased. The percentage of Aβ42 in the CSF was not only able to predict the amount of formic acid soluble Aβ42 in the brain, but also formic acid extractable Aβ40, as determined by ELISA. Also, the amount of Aβ42 measured as a percentage of occupied cortical area, determined by immunohistochemical techniques using a different antibody, was strongly related to the percentage of Aβ42 in the CSF. It is not surprising that the percentage of Aβ42 in the CSF is able to predict not only Aβ42 in the brain, but also Aβ40, since there is a high degree of correlation between the amounts of each peptide in the brain. Although CSF Aβ has yet to fulfill its potential as a biomarker of AD, these data suggest another possible use: measures of Aβ derived from CSF samples may be useful for predicting the levels of Aβ in brain as well as the extent of plaque formation in animal models of amyloid deposition. This measure could be particularly useful for selecting animals with extensive amounts of pre-existing Aβ pathology to use in targeted intervention studies aimed at reducing Aβ levels (e.g., immunization, statin therapy, nonsteroidal anti-inflammatories, etc.) and to potentially monitor the effects of ongoing treatments. This is particularly important in animal model research, since in vivo imaging of Aβ is expensive and usually impractical for most studies and investigators. Also, at least in the case of the most widely studied amyloid imaging agent, Pittsburg Compound B, amyloid deposited in the brain of species other than humans does not image nearly as well, likely due to differences in the interaction between the dye and the proportion of high affinity binding sites on the amyloid fibrils in vivo [46–48]. Since there is a current lack of good in vivo imaging agents that can assess the amount of Aβ in the brain from non-humans, CSF Aβ42 may prove a useful tool that behaves similarly across all species.
We have previously shown that Aβ in diffuse deposits is correlated with cognitive test error scores [32, 33]. For example, visual reversal learning scores, a measure of frontal function correlates with the prefrontal cortex Aβ load . Cognitive impairment in humans is associated with a decline in the level of Aβ42 in the CSF [43, 49], with an increase in the amount of brain extractable Aβ40 and Aβ42 , and with some aspects of plaque pathology . A similar relationship is seen between FA extractable Aβ and water maze performance in Tg2576 mice . It would thus seem that extracted Aβ is a functionally relevant measure that reflects soluble species of Aβ in addition to the accumulation of insoluble Aβ detected by immunohistochemistry. It will be interesting to see whether or not CSF Aβ42 is able to predict aspects of cognitive function in the aging beagle.
Finally, the amount of soluble oligomers in CSF was inversely related to brain extractable Aβ, whereas oligomers in the brain were correlated with SDS soluble Aβ42. It is now widely believed that soluble oligomeric forms of Aβ are responsible for the biological, and neurotoxic, effects of the peptide [7, 8]. Oligomeric Aβ species, which can exist at concentrations in the pM range in the CSF or brain interstitial fluid , are orders of magnitude more neurotoxic than either monomeric or fibrillar Aβ . It is also likely that soluble oligomeric Aβ pools exist in equilibrium with other forms of Aβ in the brain; for example, neuritic plaques and other amyloid deposits may serve as stable reservoirs . It is possible that the decrease in CSF soluble A11 positive oligomers in canine CSF relates to the exponential increase in the amount of insoluble Aβ deposited in the brain; this is a similar argument to that proposed above to account for the decreasing proportion of Aβ42 in the CSF. We also observed in a small subset of animals that A11 immunoreactivity in the brain is related to the amount of SDS soluble Aβ42. SDS-stable Aβ oligomers with size corresponding to a dimer have been isolated from AD brain and CSF, and have been put forward as likely candidates for the major form of toxic Aβ [11, 12]. However, A11 positive prefibrillar oligomers did not increase with age or with AD whereas fibrillar oligomers were higher in AD tissue  suggesting that future studies to measure the latter pool of oligomers would be interesting in the canine model.
The canine has proven to be a useful model for preclinical drug development due to similarities with humans in terms of absorption, toxicity and other pharmacokinetics. This contrasts to that of drugs developed in rodents and subsequently translated to the human . Several recent potential AD therapeutic agents, with a heavy reliance on preclinical data developed in transgenic mouse models of Aβ deposition, have ultimately failed in clinical trials. In light of this lack of success, it may be justified to include a complementary animal model in addition to mice in order to bolster the justification for proceeding into human trials. The present findings combined with previous data suggest that the aged canine provides a useful intermediate between transgenic mice and humans for the development of AD therapeutic interventions, particularly those aimed at reducing brain Aβ.
All work was conducted with prior IACUC approval, and was performed in accordance with USDA and PHS guidelines. The authors were supported by grants from the National Institutes of Health (M.P.M.: NS058382, AG005119; E.H.: AG032550, AG031764) and the Alzheimer’s Association (IIRG-03-5673). The authors thank Takeda Industries and Dr. Steven G. Younkin for providing the original antibodies used in this study, and Drs. Carl W. Cotman and Todd E. Golde for helpful advice.
The authors declare no financial conflict of interest.