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Human Molecular Genetics, 2003, Vol. 12, No. 22 2949-2956
DOI: 10.1093/hmg/ddg322
© 2003 Oxford University Press

Genetic background regulates ß-amyloid precursor protein processing and ß-amyloid deposition in the mouse

Emily J.H. Lehman1,2, Laura Shapiro Kulnane1,2, Yuan Gao1,2, Michelle C. Petriello1,2, Karen M. Pimpis1,2, Linda Younkin3, Georgia Dolios4, Rong Wang4, Steven G. Younkin3 and Bruce T. Lamb1,2,*

1Departments of Genetics and Neurosciences, Case Western Reserve University, Cleveland, Ohio 44106, USA, 2Center for Human Genetics, University Memory and Aging Center and Ireland Cancer Center, University Hospitals of Cleveland, Cleveland, OH 44106, USA, 3Center for Neuroscience, Mayo Foundation for Medical Education and Research, Jacksonville, FL 32224, USA and 4Department of Human Genetics, Mount Sinai School of Medicine, New York, NY 10029, USA

Received June 27, 2003; Revised September 4, 2003; Accepted September 15, 2003


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Alzheimer's disease (AD) is a multigenic neurodegenerative disorder characterized by distinct neuropathological hallmarks including deposits of the ß-amyloid (Aß) peptide. Aß is a 39- to 43-amino acid peptide derived from the proteolytic processing of the amyloid precursor protein (APP). While increasing evidence suggests that altered APP processing and Aß metabolism is a common feature of AD, the relationship between the levels of Aß and various APP products and the onset of AD remains unclear. We have undertaken a screen to characterize genetic factors that modify APP processing, Aß metabolism and Aß deposition in a genomic-based yeast artificial chromosome (YAC) transgenic mouse model of AD. A mutant human APP YAC transgene was transferred to three inbred mouse strains. Despite similar levels of holo-APP expression in the congenic strains, the levels of APP C-terminal fragments as well as brain and plasma Aß in young animals varied by genetic background. Furthermore, we demonstrate that age-dependent Aß deposition in the APP YAC transgenic model is dramatically altered depending on the congenic strain examined. These studies demonstrate that APP processing, Aß metabolism and Aß deposition are regulated by genetic background and that analysis of these phenotypes in mice should provide new insights into the factors that regulate AD pathogenesis.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Alzheimer's disease (AD), the most common cause of dementia in the elderly, is characterized by distinct neuropathological hallmarks, including extracellular deposits of the amyloid ß (Aß) peptide (1). Genetic studies demonstrate that AD is a heterogeneous, multigenic disorder with several distinct etiologies (2) including: dosage imbalance for chromosome 21 as occurs in Down syndrome (DS); mutations in the amyloid precursor protein (APP) gene on chromosome 21, the presenilin 1 (PS1) gene on chromosome 14 and the presenilin 2 (PS2) gene on chromosome 1 in early-onset FAD; and inheritance of distinct apolipoprotein E (ApoE) gene alleles on chromosomes 19 in late-onset FAD. Current data suggests that these four AD genes account for less than 30% of genetic risk for AD (2). Recently, numerous studies have provided evidence that many of the genetic forms of AD share common pathogenic mechanisms that involve alterations in Aß metabolism (3).

Aß is a 39- to 43-amino acid peptide derived from the proteolytic processing of APP (4). APP, a type-I integral membrane protein, matures through the constitutive secretory pathway and is processed by several different proteases (5). First, {alpha}-secretase cleavage of APP within the Aß sequence generates a C-terminal fragment (CTF{alpha}) that prevents the formation of Aß. A competing pathway results in ß-secretase cleavage at the N-terminus of Aß and generation of a separate C-terminal fragment (CTFß), which is subsequently processed by {gamma}-secretase to generate Aß of either 40 (Aß40) or 42 (Aß42) amino acids in length. However, at present the exact relationship between the levels of Aß and the various APP processing products and the deposition of Aß remains poorly defined.

Our laboratory has initiated a screen to characterize genetic factors that modify APP processing, Aß metabolism and Aß deposition in a transgenic mouse model of AD. Previously, we generated and characterized the genomic-based APP transgenic mouse line R1.40, containing several copies of a yeast artificial chromosome (YAC) with the entire human APP gene harboring the Swedish FAD mutation (6–9).

In the current manuscript, we generated mouse strains containing the R1.40 transgene in defined genetic backgrounds by repeated backcrossing to three inbred mouse strains. Despite similar levels of holo-APP expression in the three strains, the levels of brain APP CTFs as well as brain and plasma Aß40 and Aß42 in young animals varied depending upon genetic background. In addition, the congenic strains exhibited dramatic alterations in the age of onset of Aß deposition. These studies demonstrate that Aß metabolism and deposition are under genetic control in mice and that altered APP processing and Aß metabolism in young animals may have implications for later development of AD-like neuropathology.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Generation of R1.40 congenic strains of defined genetic background
We have focused on developing a genomic-based mouse model of AD, through the introduction of complete copies of human AD genes into the germline of mice (6–10). Transgenic line R1.40 contains the entire human APP gene carried on a YAC with the K670N/M671L mutation (6,11). We have demonstrated that line R1.40 develops extracellular Aß deposits and associated neuropathology that closely resembles those alterations observed in human AD (7–9). In the process of analyzing patterns of Aß deposition in R1.40 mice, we observed extensive variation between transgenic animals at the same age (data not shown) indicating the presence of stochastic and/or genetic factors that impact Aß deposition.

To characterize genetic modifiers of APP processing, Aß metabolism and Aß deposition and neuropathology in mice, the R1.40 YAC transgene was transferred into three different genetic backgrounds by repeated backcrossing to the inbred mouse strains C57BL/6J, DBA/2J and 129S1/SvImJ and selection for the R1.40 transgene at each generation. The animals described in the current study were backcrossed to the tenth generation to C57BL/6J [abbreviated B6-R1.40, official designation B6.Cg-Tg(APP)R1.40Lmb], the tenth generation to DBA/2J [abbreviated D2-R1.40, official designation D2.Cg-Tg(APP)R1.40Lm] and the fifth generation to 129S1/SvImJ [abbreviated 129S1-R1.40, official designation 129S1.Cg-Tg(APP)R1.40Lmb]. On average, animals at the fifth generation back-cross are 94% identical to the inbred line (termed incipient congenic), while animals at the tenth generation backcross are 99.8% identical to the inbred line (termed certified congenic) (12). The integrity and copy number of the transgene in the three congenic strains was confirmed by Southern blotting (data not shown).

Analysis of holo-APP and APP CTFs
In initial experiments designed to examine the effect of genetic background on APP processing, brain extracts from hemizygous B6-R1.40, D2-R1.40 and 129S1-R1.40 transgenic mice were analyzed by western blot analysis for various APP products. Steady-state levels of brain holo-APP and APP CTFs were determined at 4 weeks of age (Fig. 1 and Table 1). No significant differences in the fold increase in total APP expression (mouse+human) over endogenous C57BL/6J App was observed in the three sets of samples, suggesting that the levels of brain holo-APP are approximately equal in the three congenic strains. By contrast, the relative steady-state levels of the APP CTFs (8), expressed as the ratio of CTFß/(CTFß+CTF{alpha}) was significantly lower in the 129S1-R1.40 brain extracts compared with either the B6-R1.40 or D2-R1.40 extracts (Fig. 1 and Table 1). Analysis of (B6x129S1)F1-R1.40 brain extracts, revealed an indistinguishable CTF ratio when compared with the B6-R1.40 parental strain. These results suggest that the gene alleles responsible for the lower CTF ratio observed in the 129S1-R1.40 congenics are recessive to the ‘high’ B6 alleles. On the other hand, analysis of the (D2x129S1)F1-R1.40 brain extracts revealed a CTF ratio indistinguishable from the 129S1-R1.40 parental strain (Fig. 1), suggesting that the alleles responsible for the lower CTF ratio observed in the 129S1-R1.40 congenics is dominant to the ‘high’ DBA alleles. These data demonstrate that there is altered production and turnover of APP CTFs dependent upon genetic loci in the different mouse backgrounds.



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  		Figure 1. APP processing in the different R1.40 congenic strains. (A–C) Whole brain protein extracts (24 ml of 1% CHAPS with protease inhibitors per gram of tissue) were prepared from 4-week-old hemizygous B6-R1.40, D2-R1.40 and 129S1-R1.40 APP YAC transgenic mice. 25 µg of total protein was loaded onto 4–12% gradient acrylamide gels followed by western blotting with APP C-terminal antibody 369. Shown on the right is the approximate size in kDa. (B) Levels of total holo-APP (mouse+human) were analyzed in six animals (three male and three female) for each congenic strain by western blot and quantified relative to endogenous mouse App in a single C57BL/6J non-transgenic animal as described previously (8). Error bars represent standard error. No sex differences were observed in any of the samples. In addition, no significant differences in the levels of total holo-APP (mouse+human) were detected between the three congenic strains. (C) Relative levels of the APP CTFs [CTFß/CTF(ß+{alpha})] were determined for the three congenic strains and two F1s [129S1-R1.40, n=13; B6-R1.40, n=17; D2-R1.40, n=16; (B6x129S1)F1-R1.40, n=10; (D2x129S1)F1-R1.40, n=10]. Error bars represent standard error. In all three congenic strains, females exhibited higher CTF ratios than males, but this only reached statistical significance in the B6-R1.40 animals (P-value=0.016). Statistical comparison of different strain values was calculated by ANOVA with P-values of: 0.003 (129S1-R1.40 versus B6-R1.40), 0.023 (129S1-R1.40 versus D2-R1.40), 0.011 [129S1-R1.40 versus (B6x129S1)F1-R1.40] and 0.005 [D2-R1.40 versus (D2x129S1)F1-R1.40].

 

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  		Table 1. APP Processing and Aß metabolism in R1.40 congenic strains
 
Analysis of Aß metabolism
To further examine the effects of genetic background on APP processing, the levels of the two major isoforms of Aß (Aß40 and Aß42) in brain extracts and plasma from 4-week-old hemizygous B6-R1.40, D2-R1.40 and 129S1-R1.40 congenics were determined by ELISA. Pairwise comparisons revealed B6-R1.40 animals with the highest levels of both brain and plasma Aß40 and Aß42, 129S1-R1.40 animals with intermediate levels and D2-R1.40 animals with the lowest levels (Fig. 2 and Table 1). The statistically significant differences in steady-state levels of Aß between D2-R1.40 and B6-R1.40 animals were maintained at both 21 and 60 days of age (Fig. 3). Immunoprecipitation/mass spectrometry analysis of brain Aß from the 129S1-R1.40, B6-R1.40 and D2-R1.40 congenics revealed no significant differences in the identity of the Aß species produced (data not shown). These novel results suggest that the altered steady-state level of Aß in young animals is under the control of unique genetic loci in the R1.40 congenic strains.



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  		Figure 2. Aß metabolism in the different R1.40 congenic strains. Formic acid extracted brain homogenates (A and B) and plasma samples (C and D) from 12 mice (six male and six female) were run on Aß40 (A and C) and Aß42 (B and D) ELISAs with Aß standards and expressed as either pmol Aß/g brain tissue (brain extracts) or pM Aß (plasma). Error bars represent standard error. The only significant sex differences were a slight increase in brain Aß40 in males compared to females (P-value=0.02) and an increase in plasma Aß42 in females compared with males (P-value=0.003) in the D2-R1.40 animals. There was no statistically significant difference in the Aß42/Aß40 ratios in the samples examined (data not shown). Statistical comparison of different strain values was calculated by ANOVA (with Sidak correction for multiple comparisons) with P-values of: <0.001 (brain Aß40, B6-R1.40 versus D2-R1.40); 0.047 (brain Aß40, B6-R1.40 versus 129S1-R1.40); 0.009 (brain Aß40, 129S1-R1.40 versus D2-R1.40); <0.001 (brain Aß42, B6-R1.40 versus D2-R1.40); 0.028 (brain Aß42, B6-R1.40 versus 129S1-R1.40); 0.029 (brain Aß42, 129S1-R1.40 versus D2-R1.40); <0.001 (plasma Aß40, B6-R1.40 versus D2.R1.40); <0.001 (plasma Aß40, B6-R.140 versus 129S1-R1.40); 0.021 (plasma Aß42, B6-R1.40 versus D2-R1.40); and 0.027 (plasma Aß42, 129S1-R1.40 versus D2-R1.40).

 


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  		Figure 3. Aß metabolism in the different R1.40 congenic strains at different ages. Guanidine–HCl-extracted brain homogenates from four male B6-R1.40 and D2-R1.40 mice at 21 (only three D2-R1.40 animals were assayed at this timepoint), 28 and 60 days of age were run on Aß40 ELISAs with Aß standards and expressed as pmol Aß/g brain tissue (brain extracts). Error bars represent standard error. Statistical comparison of the different strain values was calculated by ANOVA (with Sidak correction for multiple comparisons) with P-values of: <0.001 (21 days); 0.002 (28 days); and 0.001 (60 days).

 
To gain further insight into genetic differences that result in high Aß levels in the B6-R1.40 strain and low Aß levels in the D2-R1.40 strain, four-week-old hemizygous (B6xD2) F1-R1.40 and (B6xD2)F2-R1.40 transgenic mice were generated and analyzed for the levels of brain Aß40 and Aß42 by ELISA (Fig. 4). The levels of brain Aß peptides in the (B6xD2) F1s were not significantly different from the B6-R1.40 parental strain, but were significantly different from the D2-R1.40 parental strain. These results demonstrate that the gene alleles controlling the ‘high’ levels of brain Aß in young B6-R1.40 congenics are dominant over the ‘low’ D2-R1.40 alleles. In addition, the levels of brain Aß40 and Aß42 in the F2 population varied across both parental and F1 Aß values and were strongly correlated within the F2 population (r=0.9, P<0.0001, two-tailed Pearson test), suggesting that the same genetic factors regulate both Aß peptides.



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  		Figure 4. Aß metabolism in the D2-R1.40 and B6-R1.40 congenic strains and (B6xD2)F1-R1.40s and (B6xD2)F2-R1.40s. Formic acid extracted brain samples from 4-week-old hemizygous B6-R1.40 congenic mice (B6, n=12, six male and six female), D2-R1.40 congenic mice (DBA, n=12, six male and six female), (B6xD2)F1-R1.40s (F1, n=15, seven male and eight female) and (B6xD2)F2-R1.40s (F2, n=40, 20 male and 20 female) were prepared. Brain samples were run on Aß40 (A) and Aß42 (B) ELISAs with Aß standards and expressed as pmol Aß/g brain tissue. Horizontal bars represent the means for each group. No significant sex differences were observed in either the F1 or F2 populations. Statistical comparison of different strain values was calculated by ANOVA (with Sidak correction for multiple comparisons) with P-values of: <0.001 (Aß40, B6-R1.40 versus D2-R1.40); 0.0007 [Aß40, (B6xD2)F1-R1.40 versus D2-R1.40]; <0.001 (Aß42, B6-R1.40 versus D2-R1.40); 0.014 [Aß42, (B6xD2)F1-R1.40 versus D2-R1.40].

 
Finally, correlational analysis of steady-state APP CTF ratios and Aß levels on individual animals where both measurements were obtained (B6-R1.40, n=7; D2-R1.40, n=6; 129S1-R1.40, n=9) revealed no significant correlation between these two biochemical measurements (data not shown). This is consistent with our previous observations that revealed that steady-state APP CTF ratios are not predictive for the levels of Aß in different brains regions of R1.40 transgenic mice in a mixed B6-129S1 background or in different brain regions of Tg2576, a cDNA-based APP transgenic mouse model in a mixed B6-SJL background (8).

Analysis of Aß deposition
To examine whether the altered steady-state levels of Aß in young congenics is correlated with altered Aß deposition later in life, aging studies of homozygous B6-R1.40, D2-R1.40 and (B6xD2)F1-R1.40 animals were conducted. While no Aß deposition was observed in any animals at 5 months of age (data not shown), all homozygous 13.5-month-old B6-R1.40 animals (n=4) exhibited Aß deposition in parietal cortex (Fig. 5B). By contrast, no Aß deposition was observed in 13.5-month-old homozygous D2-R1.40 animals (n=3; Fig. 5A). The 13.5-month-old homozygous (B6xD2)F1-R1.40 animals (n=3) also exhibited Aß deposition in parietal cortex (Fig. 5C), indicating dominance for B6 ‘depositing’ alleles over D2 ‘non-depositing’ alleles. This difference in Aß deposition was maintained at 17 months of age (data not shown) and by 20 months of age B6-R1.40 homozygous animals exhibited substantial Aß deposition in the frontal (Fig. 5H) and parietal cortex (Fig. 5E; n=3), while D2-R1.40 animals at the same age still lacked Aß deposition (Fig. 5G and D) (n=3). (B6xD2)F1-R1.40 animals (n=3) at 20 months of age also exhibited Aß deposition in frontal (Fig. 5I) and parietal cortex (Fig. 5F), further suggesting dominance of the B6 ‘depositing’ alleles. These results suggest that the alterations in Aß deposition in B6-R1.40 and D2-R1.40 congenic strains reflect the action of modifier loci. These results also demonstrate that elevated steady-state levels of Aß in young B6-R1.40 animals may be correlated with an earlier age of Aß deposition. This is the first demonstration that both Aß metabolism and Aß deposition are modified dependent upon genetic background in the mouse.



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  		Figure 5. Aß Deposition in D2-R1.40 and B6-R1.40 congenic strains and (B6xD2)F1-R1.40s. Absence of Aß deposition in parietal cortex of 13.5-month-old homozygous D2-R1.40 congenic (A) and in parietal cortex (D) and frontal cortex (G) of a 20-month-old homozygous D2-R1.40 congenic. Aß deposition in parietal cortex of a 13.5-month-old homozygous B6-R1.40 congenic (B). Multiple Aß deposits in the parietal cortex (E) and frontal cortex (H) of a 20-month-old B6-R1.40 congenic. Aß deposition in parietal cortex of a 13.5-month-old homozygous (B6xD2)F1-R1.40 congenic (C) and in the parietal cortex (F) and frontal cortex (I) of a 20-month-old (B6xD2)F1-R1.40 congenic . Staining was performed as described previously using Aß monoclonal antibody 6E10. Nearly identical staining was observed in at least three separate age- and sex-matched animals from each genotype and no Aß staining was observed on any sections (n>40 for each animal) from the D2-R1.40 congenics. Sections are 10 µm thick. Scale bar, 500 µm.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
The generation of Aß via the proteolytic processing of APP and its subsequent deposition into senile plaques is thought to be central to AD pathogenesis (3). However, the relationship between the levels of Aß and the various APP processing products generated over the lifespan of humans and the onset of AD remains quite obscure. For example, the levels of Aß measured in plasma or fibroblasts from human subjects do not consistently predict whether or when AD will develop (13,14). In addition, the increase in Aß secretion caused by individual FAD mutations does not necessarily correlate with age of onset within FAD pedigrees (15–17). This is probably due to numerous confounding environmental and genetic factors inherent in human population-based aging studies. Consistent with this hypothesis, considerable variation in the duration, severity, symptoms, age of onset and clinical/neuropathological correlations of AD has been observed in multiple studies (18–22). Notably, even within families containing the same early-onset FAD mutation, substantial variation in symptoms, age of onset, pathology, duration and penetrance is exhibited (23–25) suggesting the presence of modifier loci for Aß metabolism and AD in these families. Given the difficulties in identifying the factors that modulate risk for developing AD in humans we have turned to the mouse as a genetically defined and tractable model system to gain insight into the relationship between Aß metabolism and AD pathogenesis.

In the current studies we have focused on examining the effects of defined genetic backgrounds and environment on APP processing, Aß metabolism and Aß deposition in a transgenic mouse model of AD. We previously generated and characterized mouse line R1.40, a genomic-based APP transgenic model that exhibits numerous AD phenotypes (6–10). In this report, using the R1.40 line in defined inbred mouse strains, we show that APP processing, Aß metabolism and Aß deposition are modified dependent upon genetic background in the mouse and that alterations in steady-state levels of Aß in young animals may impact the onset of Aß deposition later in life. These congenic transgenic mouse strains now provide a unique resource to characterize gender-specific, environmental-specific as well as spatial and temporal alterations in APP processing, Aß metabolism and Aß deposition. In addition, the congenic strains will enable genetic mapping studies to identify genes responsible for alterations in both in vivo Aß metabolism and Aß deposition.

Our results demonstrate that genetic background impacts several steps leading from APP processing to Aß metabolism and Aß deposition. First, the choice between {alpha}- and ß-secretase cleavage in APP processing was significantly different as measured by ratios of steady-state CTF{alpha} and CTFß in the three congenic lines. Furthermore, the levels of Aß40 and Aß42 in both brain and plasma varied among the congenic lines with highest levels in the B6-R1.40 line, lowest levels in the D2-R1.40 line and intermediate levels in the 129S1-R1.40 line. Importantly, these alterations in APP processing occurred despite equivalent levels of holo-APP. Surprisingly, the relative steady-state levels of APP CTFs was not correlated with the levels of Aß in the congenic lines, suggesting that these two biochemical measurements are regulated independently. Genetic analysis of Aß40 and Aß42 levels in (B6xD2) F1-R1.40 revealed that the B6 ‘high’ alleles were dominant over the ‘low’ D2 alleles. Finally, the B6-R1.40 and (B6xD2) F1-R1.40 lines, which demonstrated elevated levels of Aß compared to D2-R1.40 animals at young ages, exhibited enhanced Aß deposition when compared to age-matched D2-R1.40 animals.

Our results further suggest that in the B6-R1.40 and D2-R1.40 genetic backgrounds, the levels of steady-state brain and plasma Aß in very young animals may be correlated with the presence of Aß deposition at 13.5, 17 and 20 months of age. B6-R1.40 animals first exhibit Aß deposition by 13.5 months of age while D2-R1.40 animals remain free of Aß deposition until at least 20 months of age. This difference of 6.5 months (or more) in the onset of Aß pathology represents an age of onset delay of at least 48% (6.5 months/13.5 months). If a lifespan-corrected, proportional delay were observed in humans, the average age of onset of Aß pathology would be delayed ~30 years, drastically reducing the rates of AD pathology observed in human populations (26,27). Identification of the mouse genes responsible for the delay in Aß deposition observed in these mouse strains may thus prove critical in efforts to identify factors that delay the age of onset of AD in human populations. Furthermore, these studies have important implications for the study of human AD in that the levels of Aß in very young individuals may be correlated with the age of onset of AD pathology. This hypothesis will need to be examined in greater detail using a large population of animals in which the levels of plasma Aß are measured in each animal at a variety of ages and correlated with Aß deposition in the same animals at an older age. This type of longitudinal study in a large group of F2 animals will help determine whether the genetic factors that regulate Aß metabolism and Aß deposition in these strains are the same or different and thus provide insight into the relationship between the levels of Aß throughout aging and eventual Aß deposition.

This study also has profound implications for the study of the various transgenic mouse models of AD which are largely maintained on hybrid genetic backgrounds (28–32). Our data demonstrate that significant phenotypic alterations in Aß metabolism and deposition are conferred by genetic background. Phenotypic variability due to genetic background has been suggested in other APP transgenic mouse models (33–35), but has yet to be formally addressed experimentally. For example, the PD-APP transgenic model of AD, which is derived from a hybrid background that includes the C56BL/6J and DBA/2J inbred strains examined here, exhibits extensive variability in Aß deposition dependent upon the parent of origin of the transgene (35). The results presented here suggest that interpretation of biochemical, pathological and behavioral data generated in the various transgenic models on mixed genetic backgrounds is likely to be substantially complicated by various genetic factors segregating uniquely in the progeny of these models.

In summary, our results demonstrate that APP processing, Aß metabolism and Aß deposition are genetically modified quantitative traits in the mouse which offer the opportunity for genetic analysis to identify novel genes involved in APP processing and Aß deposition. Such studies will provide a more complete understanding of the relationship between alterations in Aß metabolism and APP processing in young animals and the eventual deposition of Aß in aged animals. Intriguingly, our recent studies demonstrate that the levels of various APP processing products (including APP CTFs and Aß) in different brains regions of R1.40 transgenic mice are not predictive for later development of Aß deposition (8), suggesting the presence of additional regional and or age-related factors that modulate the pattern of Aß deposition. Finally, these studies complement ongoing human studies using plasma Aß as a quantitative trait in late-onset AD (36), although the mouse studies offer the distinct advantages of defined breeding strategies to help identify numerous quantitative traits, measurement of both brain and plasma Aß and various APP products at a variety of ages, as well as the complete genomic DNA sequence of the relevant polymorphic strains. Identification of genes involved in Aß metabolism and Aß deposition in the mouse will likely lead to unique targets for therapeutic intervention in AD.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Animals
R1.40 YAC transgenic animals were previously described (6). Congenic strains were generated by consecutive backcrossing onto one of the following inbred strains (from The Jackson Laboratory, Bar Harbor, ME): B6 (stock number 000664), D2 (stock number 000671) and 129S1 (stock number 002448). Typically transgene positive males were crossed with inbred females, but at least one cross of transgene-positive females with inbred males was made in each series to ensure the inclusion of the inbred Y chromosome. Transgene hemizygosity/homozygosity was determined by fluorescent in situ hybridization (37) and integrity of the transgene was determined by Southern blot analysis with human APP and Alu repetitive element probes (6). We observed the expected Mendelian ratios of control, hemizygous and homozygous animals with repeated back-crossing as well as with intercrossing hemizygotes, demonstrating that the transgene does not alter survival to weaning (data not shown). To generate hemizygous (B6xD2)F1-R1.40 animals, homozygous D2-R1.40 males were crossed with non-transgenic B6 females and the reciprocal cross of homozygous B6-R1.40 males to non-transgenic D2 females was also undertaken. Hemizygous (B6xD2)F2-R1.40 animals were generated by crossing a homozygous (B6xD2)F1-R1.40 male with a non-transgenic B6D2F1 (Jackson Laboratory stock number 100006) female. Homozygous (B6xD2)F1-R1.40 animals were generated by mating homozygous D2-R1.40 males to homozygous B6-R1.40 females. All mice were housed in ventilated microisolator cages on a 12 hour light/dark cycle, were allowed food (Purina 5021) and water ad libitum and were specific pathogen free.

Tissue procurement
Plasma was obtained from the orbital sinus. Both plasma and brain tissue were immediately frozen after procurement on dry ice before storage at -80°C. For neuropathological analysis of older animals, brains were sagitally bisected with half of the brain frozen and half immersion fixed in 4% paraformaldehyde in phosphate buffered saline for immunohistochemistry.

Western blot analysis
Analysis of the steady-state levels of holo-APP and APP CTFs was performed on brain extracts from 4-week-old hemizygous congenic strains and F1s as described previously (8) using polyclonal antibody 369 (kindly provided by Sam Gandy, Thomas Jefferson University, Philadelphia, PA, USA), which is specific to the C-terminus of APP. For CTF ratios, the intensity of CTFß/(CTFß+CTF{alpha}) was determined. Each sample was analyzed in triplicate and an average CTF ratio was determined. The identity of the CTFß and CTF{alpha} bands was further assessed by western blotting with various C- and N-terminal Aß and APP antibodies with CTF specific epitopes (data not shown). For quantification of holo-APP levels, western blots were analyzed on a Fluor-S Max imaging machine (BioRad, Hercules, CA, USA). Each gel contained serial dilutions of a single C57BL/6J non-transgenic brain extract of a known protein concentration, to which all congenic samples were compared. Images generated by the Fluor-S Max were analyzed with the Quantity One (BioRad) program and intensities for the holo-APP bands were determined for each lane. The Prism (Graph Pad Software, San Diego, CA, USA) statistical program was then utilized to generate a linear regression analysis of the serially diluted standard sample; all unknowns were fit to that line and a value for each sample was given relative to the standard curve of endogenous C57BL/6J App. All samples were analyzed in triplicate and an average determined.

Brain and plasma Aß40 and Aß42 ELISA
For measurement of strain differences in levels of Aß, frozen brain tissue was Dounce homogenized in 70% formic acid (150 mg/ml) as previously described (38,39). Homogenates were spun at 100 000 g for 1 h and supernatants neutralized by 20x dilution in 1 M Tris. Homogenates were subjected to an ELISA with capture monoclonal antibody BNT77 (specific to Aß 17–28) and monoclonal detection antibodies BA27 for Aß40 and BC05 for Aß42. Comparison to a curve of standard peptides yielded the pmole Aß/g of brain tissue and pM (for plasma) results reported. For determination of levels of Aß40 at various ages, a commercially available ELISA was utilized (Biosource International, Camarillo, CA, USA). Frozen brains were homogenized in 5 M guanidine HCl/50 mM Tris (125 mg/ml) using a Powergen homogenizer (Fisher, Pittsburgh, PA, USA). Homogenates were mixed gently at room temperature for 3–4 h, diluted 10-fold with Biosource sample/standard diluent containing 1x protease inhibitors (Calbiochem, San Diego, CA, USA) and spun at 16 000 g for 20 min at 4°C. Samples were further diluted 3-fold with sample/standard diluent [containing AEBSF (Sigma, St Louis, MO, USA) protease inhibitor at 1 mM] and the ELISA was carried out as prescribed by the manufacturer. The plate was read using a fluorometric plate reader (Perkin/Elmer, Wellesley, MA, USA). Sample values were compared to a standard curve and pmole/g values calculated.

Immunoprecipitation/mass spectrometry
Immunoprecipitation/mass spectrometry analysis of Aß peptides was performed as described (40). Formic acid extracts of mouse brain were neutralized with 2 M Tris to a final pH of 8 in the presence of protease inhibitors. Synthetic Aß12-28 was added as an internal standard. Aß peptides were immunoprecipitated with monoclonal antibodies 4G8 or 6E10 (Signet Laboratories, Dedham, MA, USA) using protein A/G-plus agarose beads. Peptides were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS, Voyager-DE STR Biospectrometry workstation, Applied Biosystems, Foster City, CA, USA). Relative peak intensities of Aß peptides to the internal standard were used for quantification.

Immunohistochemistry
Brains were embedded in paraffin and 10 µm brain sections were processed for immunohistochemistry as described (9). Monoclonal antibody 6E10 to Aß 1–17 (Signet Laboratories, Dedham, MA, USA) and the amyloid-specific dye Thioflavine-S were utilized to visualize Aß deposits in brain sections.

Statistics
Comparisons between groups of animals were made using analysis of variance (ANOVA). The Sidak post-hoc correction for multiple testing was applied when necessary after testing for homogeneity of variance (SPSS 10 for Macintosh, Chicago, IL, USA). Correlations between Aß40 and Aß42 or between brain and plasma Aß levels were evaluated using the Pearson correlation test (Prism). All P-values reported refer to ANOVA testing except in the case of correlation analysis.


   ACKNOWLEDGEMENTS
 
We thank S. Gandy for the generous gift of the 369 antibody. This work was supported by NIH Grant AG14451, an Alzheimer's Association grant and an American Health Assistance Foundation grant to B.T. Lamb as well as support from the University Alzheimer Center (AG08012) and the Ireland Cancer Center (CA43703). E.J.H.L. was supported in part by NIH training grant GM08613. This work was also supported by NIH grant AG10491 to R.W.


   FOOTNOTES
 
* To whom correspondence should be addressed at: Department of Genetics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106-4955, USA. Tel: +1 2163682979; Fax: +1 2163683432; Email: btl{at}po.cwru.edu Back


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 ABSTRACT
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 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
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