Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Jul 1.
Published in final edited form as: Neurol Res. 2021 Mar 10;43(7):570–581. doi: 10.1080/01616412.2021.1893566

Early loss of cerebellar Purkinje cells in human and a transgenic mouse model of Alzheimer's disease

Kiran Chaudhari a, Linshu Wang a, Jonas Kruse a, Winters Ali a, Nathalie Sumien a, Ritu Shetty a, Jude Prah a, Ran Liu a, Jiong Shi b, Michael Forster a, Shao-Hua Yang a,*
PMCID: PMC8169538  NIHMSID: NIHMS1679225  PMID: 33688799

Abstract

The cerebellum’s involvement in AD has been under-appreciated by historically labeling as a normal control in AD research. We determined the involvement of the cerebellum in AD progression. Postmortem human and APPswe/PSEN1dE9 mice cerebellums were used to assess the cerebellar Purkinje cells (PC) by immunohistochemistry. The locomotor and spatial cognitive functions were assessed in 4 to 5-month old APPswe/PSEN1dE9 mice. Aβ plaque and APP processing were determined in APPswe/PSEN1dE9 mice at different age groups by immunohistochemistry and Western blot. We observed loss of cerebellar PC in mild cognitive impairment and AD patients compared with cognitively normal controls. A strong trend towards PC loss was found in AD mice as early as 5 months. Impairment of balance beam and rotorod performance, but no spatial learning and memory dysfunction, was observed in AD mice at 4-5 months. Aβ plaque in the cerebral cortex was evidenced in AD mice at 2 months and dramatically increased at 6 months. Less and smaller Aβ plaques were observed in the cerebellum than in the cerebrum of AD mice. Similar intracellular APP staining was observed in the cerebellum and cerebrum of AD mice at 2 to 10 months. Similar expression of full-length APP and C-terminal fragments were indicated in the cerebrum and cerebellum of AD mice during aging. In summary, our study in post-mortem human brains and transgenic AD mice provided neuropathological and functional evidence that cerebellar dysfunction may occur at the early stage of AD and likely independent of Aβ plaque.

Keywords: APP/PSEN1, Cerebellum, Purkinje cell, Cognition, balance function, Aβ

Introduction

The human brain is characterized by the evolutionally expanded cerebrum and remarkable cognitive capacity [1], whereas the cerebellum is considered a more archaic brain structure for motor coordination. Accordingly, research of Alzheimer’s disease (AD) has been exclusively focused on the cognition, especially the hippocampus and cerebral cortex [2]. Although neuropathology and functional cerebellar changes have been observed in AD patients back to 1980s [3,4], the cerebellum’s involvement in AD has been under-appreciated. Indeed, both tau aggregation and Aβ plaques, two hallmarks of AD, are occasionally observed in the cerebellum at late stages in AD patients and transgenic AD mouse models [5-9]. Further, the cerebellar atrophy was only observed at the late stage of AD [10]. Nonetheless, brain atrophy in different regions does not always follow β-amyloid or tau deposit pattern [11]. The accumulation of Aβ plaques in the brain does not correlate with cognitive impairments. While tangles correlate strongly with cognitive decline and neuronal and synapse loss, mutations in tau cause frontotemporal dementia, not AD [12].

There has been growing interest in using non-cognitive functional changes such as sensory and motor dysfunction as potential predictors of AD [13]. Concurrently, there is increasing evidence that the cerebellum may be affected in AD at early stages [14,15]. Buschman et al. support the notion that the motor decline starts earlier than the cognitive decline during the disease progression in AD [16]. Balance and gait impairments are frequent in Mild Cognitive Impairment (MCI) and AD patients [17,18]. Loss of cerebellar Purkinje cell has been observed in both familial and sporadic AD patients [19,20]. However, the research on the cerebellum’s functional relevance in AD is still in its infancy, and the contribution of the cerebellum to AD pathophysiology is unclear. We aimed to determine the cerebellum’s involvement in post-mortem human AD brains and cerebellum-essential motor function in a transgenic AD model in the current study. Our study provided both neuropathological and functional evidence that the cerebellum could be involved in the early AD stage.

Material and Methods

Human cerebellum samples

Postmortem human cerebellar cortex was obtained from the Banner Sun Health Research Institute Brain and Body Donation Program (BBDP) [21]. The BBDP has obtained the Institutional Review Board's approval for these and all other aspects of the Program, including the informed consent and protocol. Written informed consent was obtained from all subjects (or guardians of subjects) participating in the study (consent for research). The median post-mortem interval, defined as the time elapsing between death and the start of organ removal, for all autopsied subjects, was 3.0 hours. All subjects were recruited from the Arizona Alzheimer’s Disease Center (ADC) Clinical Core. Clinical and neuropsychological assessments were performed annually according to the National Alzheimer’s Coordinating Center protocol. Subjects designated as “cognitively normal” (CN) have no cognitively based limitations in daily living activities and a Clinical Dementia Rating (CDR) score of 0. The diagnosis of MCI was given according to published consensus criteria and a CDR of 0.5. A diagnosis of probable AD by the National Institute of Neurological Disorders and Stroke (NINDS) criteria was given to subjects with a CDR score of ≥1.0 and a neuropsychological profile showing disproportionately severe impairment of learning and delayed recall. The cerebellar specimen from 6 subjects per group for CN, MCI, and AD was used for this experiment.

Transgenic AD mice

The procurement, housing, breeding, and animal protocol were approved by the University of North Texas Health Science Center Institutional Animal Care and Use Committee. Two-month age female C57BL/6J (Stock No: 000664 ∣ Black6) and B6.Cg-Tg(APPswe, PSEN1dE9)85Dbo/Mmjax (MMRRC Stock No: 34832-JAX ∣ APP/PS1) male mice were purchased from the Jackson Laboratory for breeding and maintaining heterozygous APPswe/PSEN1dE9 mice and wild type littermates. All mice were housed in clear polycarbonate cages at 23 ± 1 °C under a 12-hour light/dark cycle and fed ad libitum diet and water. Same-gender APPswe/PSEN1dE9 and wild type littermates were housed together. Mice were euthanized and perfused with cold saline to remove blood. Brains were then dissected for analysis using Western blot and immunohistochemistry.

Immunohistochemistry

For post-mortem human brains, the cerebellum was separated from the brainstem by severing the cerebellar peduncles. Each hemicerebellum was sliced into 4–5 segments in the parasagittal plane. Large (about 3.5 × 5 cm) tissue blocks of the cerebellum, following cryoprotection in 2% dimethyl sulfoxide/20% glycerol, were sectioned at 40 μm on a sledge-type freezing microtome. Pre-cut free-floating 40 μm sections were stored in 0.1 mol/L phosphate buffer with 0.1% sodium azide, in a refrigerator at 4 °C. For studying Purkinje cells, sections were washed in 1X phosphate-buffered saline with Tween-20 (PBST) solution 3 times (10 minutes each), followed by treatment 3% hydrogen peroxide to for 15 minutes. They were washed with distilled water twice (10 minutes each) and with PBST 3 times (10 minutes each). 3% goat serum (#G9023, Sigma Aldrich, St. Louis, MO) were used to block the nonspecific antibody binding for 1 hour at room temperature. After the blocking, sections were washed with PBST 3 times (10 minutes each). The primary antibody, mouse anti-Calbindin D28K (D-4) monoclonal antibody (CALB1, 1:200, #sc-365360, Santa Cruz Biotechnology, Dallas, TX), was used at 4 °C overnight. After washing with PBST, sections were stained with the goat anti-mouse IgG (H+L) secondary antibody, HRP conjugate (1:200, #31430, Thermo Fisher Scientific, Rockford, IL) for 1 hour at room temperature. DAB (3, 3 -diaminobenzidine) peroxidase substrate (#SK-4100, Vector Laboratories, Burlingame, CA) was used for staining in 100 seconds. Hematoxylin (#SLBP6178V, Sigma Aldrich, St. Louis, MO) was used to counter-stain sections in 30 seconds. The staining sections were then coded, and Calbindin-positive Purkinje cells were counted by a person blinded to group assignment in three 4X objective fields in each case. Images with lobules from every slice were collected on microscopy. The number of Purkinje cells from the middle layer of cortex was counted and data were analyzed with one-way ANOVA with a Tukey’s multiple comparison test.

Paraffin-embedded sagittal section brain slides of APPswe/PSEN1dE9 mice and littermates were de-paraffinized in xylene for 10 minutes, and subsequently hydrated in 100% ethanol for 10 minutes, and 95%, 70% and 50% ethanol for 5 minutes each. Antigen retrieval was performed by heating the slides in freshly prepared in sodium citrate buffer (10 mM Citric Acid, 0.05% Tween 20, pH 6.0) for 30 minutes. After 1 hour blocking with SuperBlock™ Blocking Buffer (#37515, Thermo Scientific), sections were incubated with primary antibody overnight (Calbindin D1I4Q: XP® Rabbit mAb 1:1000 dilutions; #13176; β3-Tubulin D71G9: XP® Rabbit mAb #5568β3, 1:100 dilutions from Cell Signaling Technology; Aldolase C Antibody H-11: sc-271593, 1:100 dilutions, from Santa Cruz Biotechnology; Mouse IgG, catalog # 803001, 6E10, 1:200 dilutions, from BioLegend). After washing 3 times with PBS (with 0.05% Tween-20, 10 minutes each), Alexa Fluor conjugated secondary antibody (Thermo Fisher Scientific) was used for fluorescent staining [22]. The stained sections were coded, and the morphological quantification and analysis of Purkinje cell number, cell body perimeter, primary and secondary dendritic branches were carried out using ~25 images per group (20X magnification) covering all cerebellar lobes by a person blinded to group assignment using the scale and manual tracing of each cell in ImageJ software. Similarly, 6E10 plaques were quantified by manual tracing around all the visible plaques from 20X magnification images covering the whole cortex and cerebellum. The area for each plaque was calculated by Image J.

Western Blot assessment

The mouse brain tissues were homogenized on ice in RIPA buffer (50 mM of Tris. HCL, pH 7.4, 150 mM NaCl, 1 mM EDTA, 1%Triton X) along with protease and phosphatase inhibitors (1:100). Protein assay was conducted using reagent Pierce 660 nm (Thermo Fisher Scientific) to determine the samples' protein content. The samples were resolved on 4-20% Mini-PROTEAN® TGX™ Precast Gels (LSR/Bio-Rad, Hercules, CA, USA) and transferred to Amersham™ Protran™ 0.1 μm NC-nitrocellulose blotting membrane (GE Healthcare Life Science, Pittsburgh, PA, USA). The membranes were incubated overnight in primary antibodies (Mouse IgG, catalog # 803001, 6E10, 1:2000 dilutions, from BioLegend; BACE1 Rabbit Polyclonal IgG # PA1-757, 1:1000 dilutions, from Thermo Fisher Scientific; GAPDH Antibody 6C5, Mouse mAb #sc-3223, 1:5000 dilutions; β-Actin Antibody C4, Mouse mAb #sc-47778, 1:2000 dilutions, from Santa Cruz Biotechnology) followed by secondary antibody (Jackson ImmunoReseach Laboratories). The chemiluminescence signal was detected using the UVP Biospectrum 500 imaging system and normalized to actin for each sample.

Mouse behavior assessment

Body weights were measured daily for 5 days/week. Values expressed are an average of 5-day measurements. The behavioral tests were conducted in the following order: open field exploration (locomotor activity), balance in elevated bridge walk (balance beam test), coordinated running (rotorod test), spatial learning, and memory using the Morris water maze test. Spontaneous locomotor activity was measured using a Digiscan apparatus (Omnitech Electronics Inc. Columbus, OH, USA, model RXYZCM-16) as described previously [23]. A bridge walking test was conducted as described previously [23]. Accelerated rotorod test was used to measure motor learning and maximum running performance, as described previously using a motor-driven treadmill (Omnitech Electronics, Model # AIO411RRT525M) [23]. Morris water maze test was used to assess spatial learning and memory as described previously [24].

Statistical Analysis

All data were presented as mean ± S.E.M. One-way ANOVA determined the significance of differences among groups with one independent variable with a Tukey’s multiple comparisons test for planned comparisons between groups when significance was detected. Repeated measure ANOVA is used to assess the performance of mice over time in repeated testing. Two-way ANOVA determined the significance of differences among groups where two independent variables were presented. P-value <0.05 (*) was considered significant. The mice's functional performance on the behavioral tests was assessed using two-way ANOVA with genotype and sex as factors. Unpaired t-test was used to compare the wild type and APPswe/PSEN1dE9 mice as between-group factors. The α level was set at 0.05 for all analyses. The software used for the analyses was Graph Pad Prism V.7 (GraphPad Software, Inc. CA, USA).

Results

Cerebellar Purkinje cells impairment in AD patients and APPswe/PSEN1dE9 mice

We obtained post-mortem cerebellum samples of MCI, AD, and age-matched CN controls from the Banner Sun Health Research Institute Brain and Body Donation Program. The average age was 89, 88.8, and 79.7 years old in CN, MCI, and AD, respectively. The average cerebellar amyloid score was 0, 0, and 1 in CN, MCI, and AD groups, respectively. Calbindin immunohistochemistry demonstrated a significant loss of cerebellar Purkinje cells in MCI and AD patients as compared to the age-matched CN (Figure 1).

Figure 1. Loss of cerebellar PCs in MCI and AD patients.

Figure 1.

Open in a new tab

A. Representative images of Calbindin D28K stained PCs in the cerebellum of cognitively normal (CN), mild cognitive impairment (MCI), and Alzheimer’s disease (AD) patients (co-stained with hematoxylin) B. Quantitative analysis of Calbindin D28K positive PC demonstrated a significant loss of PCs in MCI and AD patients. *p<0.05 compared to CN, ** p<0.01 compared to CN, # p<0.05 compared to AD patients (n=6 each group).

We determined the cerebellar Purkinje cells in the APPswe/PSEN1dE9 mouse model. When stained with Calbindin and DAPI, a trend in Purkinje cell loss (−18.82 %) at 5-month age compared to wild type and further loss (−8.69%) 8.5 months when compared to 5 month AD mice. (Figure 2A & 2B, WT 5-month n=3, AD 5 month n=5, AD 8.5 month n=4). When co-stained with Aldolase C and β3-tubulin, a strong trend of cerebellar Purkinje cell loss (−37.11%) was observed in 5 months old APPswe/PSEN1dE9 mice when compared with age-matched wild type littermates (Supplementary Figure S1A & 1B, WT n=4 for WT, n=5 for AD, p=0.06). Furthermore, the Purkinje cells in APPswe/PSEN1dE9 mice had significantly smaller soma size than wild type littermates (Supplementary Figure S1C p<0.05). No difference in the length of neurite branches per cell was founded between transgenic AD mice and wild-type littermates (Supplementary Figure S1D).

Figure 2. Loss of cerebellar PCs at the age of 5 and 8.5 months in APPswe/PSEN1dE9 mice.

Figure 2.

Open in a new tab

A. Representative fluorescent microscopic images (20X magnification, scale bar 100 μm) of cerebellar PCs stained with Calbindin (red) and DAPI (blue) in 5 and 8.5-month-old wild type (WT) and APPswe/PSEN1dE9 (AD) mice; B. Quantitative analysis of PC in the cerebellum of APPswe/PSEN1dE9 (AD) and WT. WT 5-month: n=3; AD 5-month: n=5; WT 8.5-month: n=4; and AD 8.5-month: n=4.

Impairment of cerebellum-essential motor coordination in 4 months old APPswe/PSEN1dE9 mice

The bodyweight of female mice was significantly lower than that of males (29.63 +/− 0.503 g for male wild-type, 31.88 +/− 1.122 g for male AD, 24.35 +/− 0.867 g for female wild-type, 26.03 +/− 0.941 g for female AD, male vs. female p<0.05). In the same gender, no difference in body weight of APPswe/PSEN1dE9 mice and wild type littermates were observed. No difference in spontaneous locomotor activity was observed in transgenic AD mice and wild type mice, evidenced by the total travel distance, ambulatory vertical activity count (Figure 3A, & 3B). However, wild type females spent less time in the center zone compared to genotype matched males. (Figure 3C).

Figure 3. APPswe/PSEN1dE9 mice exhibited impaired balance and coordinated running performance at 4 months as compared to wild type littermates.

Figure 3.

Open in a new tab

A & B & C. Spontaneous locomotor activity in travel distance (A), vertical activity (B), and center time (C) of male and female AD and WT mice in the open field performance. D & E. Session wise (D) and average (E) latency to fall in bridge walk performance demonstrated an impaired balance function in both male and female AD mice as compared with WT littermates at 4 months of age. F & G & H. Session wise (F), learning index (average latency to fall in session 2-4) (G), and maximum performance (average latency to fall in session 6 and 7) (H) in rotorod performance demonstrated impairment of coordinated running performance in male and female AD mice as compared with WT littermates at 4 months of age. Male WT: n=12; Male AD: n=9; Female WT: n=14; Female AD: n=10 for bridge walk test. Male WT: n=12; Male AD: n=9; Female WT: n=8; Female AD: n=4 for coordinated running performance. * p<0.05 compared to sex-matched WT.

The bridge-walking task (referenced in literature as “elevated path” or “balance beam”) is sensitive to loss of balance and motor coordination independently of other functions such as muscle strength and endurance. This assessment yields a measurement (latency for them to fall) that is relatively insensitive to practice and yields highly reliable results in individual mice. Session wise (Figure 3D) and averaging of the scores (Figure 3E) on all test days yields a graded sensitivity indicating impaired performance in both male and female APPswe/PSEN1dE9 mice at 4 months as compared the sex-matched wild type littermates.

In the coordinated running test done over 7 sessions, we used repeated measure analysis across the session, sex, and genotype. In between-subject analysis provided significant genotype (p=0) effect but no significant sex (p=0.849) effect. Further, the within-subject analysis showed a significant session (p=0) effect indicating that all mice improved performance across sessions until they reach the plateau by the 7th session. There was no session X sex interaction. However, session X genotype interaction suggested that the mice from different genotypes learned over session at different rates. In the absence of the sex effect, we could have combined the data to observe the overall genotype effect. Both males and females APPswe/PSEN1dE9 mice demonstrated poorer performance as compared to sex-matched wild-type littermates (Figure 3F) (p<0.05). Two composite outcomes in terms of learning index (average of session 2-4, Figure 3G) and maximum performance (average of session 6-7, Figure 3H) were calculated. The learning index of both male and female APPswe/PSEN1dE9 mice was significantly (male, p=0.0003; female, p<0.0274) lower than that of sex-matched wild type littermates (Figure 3G) (p<0.05). Male APPswe/PSEN1dE9 mice had significantly (p=0.0003) reduced maximum performance than sex-matched wild type littermates while female APPswe/PSEN1dE9 mice had a trend (p=0.1169) of reduced maximum performance composite measure than female wild type littermates. The non-significant outcome in females could be due to the smaller sample size (WT, n=8; AD, n=4) and low power. (WT n=8, AD n=4) (Figure 3H).

APPswe/PSEN1dE9 did not exhibit impaired spatial learning and memory at 4.5-month old

Morris water testing is a well-established test to assess the hippocampus and cortex's spatial learning and memory function. Repeated measure analysis was performed across 9 sessions, sex, and genotype (Figure 4A). The within-subject analysis showed a significant effect of the session (p=0), indicating that the mice learned to find the hidden platform over the session. However, we did not observe session X sex or session X genotype interaction, indicating that the learning over sessions was irrespective of sex and genotype. Further, between subject analysis indicated no main effect of sex (p=0.445) or genotype (p=0.209). The performance between APPswe/PSEN1dE9 and wild type littermates did not vary. When used the composite measures of learning index (average for session 2-4) (Figure 4B) and maximum performance (average for session 8-9) (Figure 4C), no impairment was observed in learning or maximum performance in APPswe/PSEN1dE9 mice as compared with sex-matched wild type littermates. No main effect of sex (p=0.928) or genotype (p=0.06) was observed in the learning index. Similarly, no main effect of sex (p=0.837) or genotype (p=0.546) was observed in maximum performance. The mice were further probed for the delayed memory in session 10 in terms of time spent in the target quadrant (Figure 4D). No delayed memory impairment was observed in APPswe/PSEN1dE9 mice compared with sex-matched wild-type littermates at 4.5 months.

Figure 4. APPswe/PSEN1dE9 mice did not exhibit impaired Morris water maze spatial learning and memory at 4.5 months as compared to wild type littermates.

Figure 4.

Open in a new tab

A. Path-length as a function of trials during spatial learning of Morris water maze test in male and female AD and WT mice. B. Learning index of male and female AD and WT mice measured as average path length across session 2-4 in water maze performance. C. Maximum performance measured as average path length (cm) across session 7-9 in the Morris water maze task for spatial learning assessment in male and female AD and WT mice. D. Delayed spatial memory measured as percent time spent in the target quadrant of the escape platform. Male WT: n= 12; Male AD: n= 8; Female WT: n=7; Female AD: n=3.

The cerebellum had less Aβ plaques but similar intracellular full-length APP and c-terminal fragment expression as the cerebral cortex in APPswe/PSEN1dE9 mice

As predicted, our immunohistochemistry study demonstrated that the cerebral cortex started to develop small Aβ plaques as early as 2 months while the cerebellum started to develop Aβ plaques around 6 months. Interestingly, even in the absence of extracellular Aβ plaque at 2 months, extensive intracellular 6E10 positive signals were observed in the granule and Purkinje cells (Figure 5A) in the cerebellum. Our Western blot analysis identified a similar pattern of full-length APP (~100 kDa), c99/c83 fragments (~20-25 kDa), and Aβ40/42 (~4 kDa) expression in the cortex and cerebellum of different aged transgenic AD mice. A comparable amount of full-length APP was found in the cortex and cerebellum across all ages. Increases of c99/c83 and Aβ40/42 expression were observed in the cortex and the cerebellum of 8.5 and 10 months APPswe/PSEn1dE9 mice (Figure 5B). A quantitative Western blot analysis demonstrated no difference in the expression of full-length APP, C99/C83, and BACE1 between the cerebral cortex and cerebellum in 5 months APPswe/PSEn1dE9 mice (Figure 5C & 5D). The Aβ plaques in the cerebellum were more uniform, and while those in the cortex were more irregular in shape and intensities (Figure 6A). When quantified, the plaques were consistently less in number and smaller in size in the cerebellum than in the same mouse's cerebral cortex at 5 months and 8.5 months (Figure 6B & 6C).

Figure 5. APPswe/PSEN1dE9 mice exhibited age-associated accumulation of extracellular Aβ plaque intracellular APP fragments in the cerebral cortex and cerebellum.

Figure 5.

Open in a new tab

A. Representative fluorescent microscopy (63X magnification, scale bar 50 μm) of 6E10 (green), β3Tubulin (red), and DAPI (blue) staining in the cerebral cortex and cerebellum in WT and APPswe/PSEN1dE9 (AD) mice at 2, 6 and 8.5 months. Accumulation of Aβ plaque in the cerebral cortex was evidenced in AD mice as early as 2 months and dramatically increased at 6 and 10 months. On the other hand, Aβ plaque in the cerebellum was observed in AD mice only at 10 months. Strong intracellular 6E10 staining was observed the cerebral pyramidal neuron, cerebellar granular neurons and PC in the AD mice as early as 2 months. B. Representative Western blots of full-length APP (APP-FL), c99/c83 and Aβ40/42 probed with 6E10 antibody in the cerebral cortex and cerebellum of AD and WT mice at 2, 6, 8.5 and 10 months of age. Similar expression patterns of full-length APP and CTF were observed in the cerebral cortex and cerebellum of AD mice at the age of 2, 6, 8.5, and 10 months. C and D. Representative and quantitative analysis of Western blots of APP-FL, C99/83, BACE1, and GAPDH in the cerebral cortex and cerebellum of 5-month old transgenic AD mice and WT littermates. No significant difference in full-length APP, C99/C83, and BACE1 expression was observed in AD and WT mice. n=6 each group.

Figure 6. Age-associated accumulation of extracellular Aβ plaque in the cerebral cortex and cerebellum of APPswe/PSEN1dE9 mice.

Figure 6.

Open in a new tab

A. Representative fluorescent microscopy (20X magnification, scale bar 100 μm) of 6E10 (green), and DAPI (blue) staining in the cerebral cortex and cerebellum of 5 and 8.5-month-old APPswe/PSEN1dE9 mice. B. Quantification of Aβ plaques counts indicates less plaques in the cerebellum compared to cerebral cortex at 5 and 8.5 months. C. Quantification of plaques sizes in the cerebral cortex and cerebellum of 5- and 8.5-month-old APPswe/PSEN1dE9 mice; 5-month: n=4; 8.5-month: n=5. * p<0.05 compared to age matched cortex; # p<0.05 compared to 5-month cortex.

Discussion

There is increasing evidence to indicate that the cerebellum has a broader range of functions beyond movement control [25,26]. The cerebellum represents only 10% of total brain mass, yet contains 80% of all neurons [27]. Cerebellar volume loss as much as 12.7% have been reported in AD patients [28]. Although the cerebellar volume loss occurs faster in AD when compared to normal aging as well as MCI, the rate of volume shrinkage is slower than that of the cerebrum, indicating that the loss of function could be related to network influence from cerebral connections [10]. Loss of Purkinje cells and a marked decrease in dendritic density were observed in the cerebellum even without typical neuritic plaques in AD patients [31]. Significant fewer cerebellar Purkinje cells were observed in AD patients compared with age-matched controls. Furthermore, familial AD patients at the average age of 55 years had fewer Purkinje cells than sporadic AD patients [20]. There is growing indications that motor dysfunction may occur early during the preclinical stage of AD [16,32]. A longitudinal cohort study with annually repeated evaluations over 10 years demonstrated that MCI patients also had impaired motor function, including gait and balance, and that the degree of impairment of lower extremity function was related to the risk of AD [33]. We observed a significant loss of cerebellar Purkinje cells in both MCI and AD patients in the current study. Our study indicated that loss of Purkinje cells could occur at the early stage of AD as there were significantly fewer Purkinje cells in MCI patients than controls. In addition to Purkinje cell loss, the impaired function of existing cerebellar Purkinje cells in transgenic AD mice has been reported to lose large-amplitude miniature inhibitory postsynaptic currents [34].

Significant motor function impairment has been observed in different transgenic AD mouse models. In Tg2576 transgenic AD mice, balance beam (bridge walking) dysfunction is the only behavioral deficit in young adults, significantly earlier than any other behavioral deficit [35,36]. APP23 transgenic mice exhibited motor coordination deficits on the rotorod test by 3 months of age, before Aβ plaque accumulation [37]. The study by Kuwabara et al. (2014) indicated the loss of motor function in rotorod performance and the number of slips from the balance beam starting as early as 3 months [38]. Motor coordination deficit and impairment of cerebellar long-term depression (LTD) induction have been found to precede Aβ accumulation in the cerebellum of APPswe/PS1dE9 transgenic mice at the age of 5-6 and 6-8 months, respectively [38]. Significant motor coordination and balance deficits and the cerebellar circuitry dysfunction were observed in 2-month-old TgCRND8 AD mice [39]. Significant bridge walking and rotorod performance deficit has been observed in 5XFAD transgenic mice at 10-12 months [40]. In the current study, we observed significant loss of cerebellum-essential function in 2 independent behavior tests, bridge walking and coordinated running, as early as 4 months in both male and female APPswe/PSEN1dE9 mice, providing further evidence that the cerebellum might be involved at the early stages of AD, even precede cognitive impairment.

The APPswe/PSEN1dE9 AD model's behavior change has been well-characterized at different age groups, especially in the cognitive domain. The deficit of contextual memory has been indicated as early as 6 months of age, evidenced by freezing behavior in fear-conditioning tests [41]. The deficit of Morris water maze performance has been observed at 12, but not 7, months of age [42]. We assessed the spatial learning and memory function in the APPswe/PSEN1dE9 mice after the balance/coordination test and observed no significant water maze performance deficit. Session wise assessment indicated that both the transgenic AD mice and wild type littermates learned over the session to find the hidden platform. When tested the mice for delayed memory after a 1-week break, the target quadrant's time was equal in APPswe/PSEN1dE9 mice and wild type littermates at a 4.5-month age.

The early motor function loss and coordination deficit were not observed unequivocally in transgenic AD mouse models [46]. In 5XFAD mice, significant impairment in Y-maze task was observed at the age of 4-5 months with normal motor function and exploratory activity as measured by the number of arms entered during the test [47]. Motor dysfunction was not observed in 9-month-old Tg2576 mice [48] and APPswe/PSEN1-L166P [34] even in the presence of cerebellar Aβ accumulation and alterations of the intrinsic excitability of Purkinje cell. Ferguson et al. (2013) conducted longitudinal behavioral tests in APPswe/PSEN1dE9 starting at 7 months and found lower rotorod performance at the age of 7, 9, 10, and 11 months although did not reach statistical significance [49]. We speculated that the inconsistent findings of motor and coordination deficits in transgenic AD mouse models could be partially due to the variation of the behavioral test protocols [34,48-52]. In the current study, we used an accelerated rotorod protocol at speeds up to 75 rpm. We conducted 4 trials/sessions; 2 sessions per day at a 2-hour intersession interval, and 7 or more sessions until the mouse performance reached a plateau. For bridge walking test, our paradigm used 4 different sizes and shapes which is more sensitive to assess balance function. Thus, our rotorod and bridge walking tests have enabled us to detect subtle change of cerebellum-associated balance dysfunction in transgenic AD mice.

It is plausible that the inconsistent observation of the cerebellum-essential function impairment in different transgenic AD mouse models may be partially due to the different promoters used in the transgenic AD mouse models. In our transgenic AD mouse model, the APPswe/PSEN1dE9 genes were directed to neurons by the mouse prion promoter. Consistent to previous studies, we observed Aβ deposits in the cerebral cortex as early as 2-month age and grows dramatically over 10-month age [53]. The APPswe/PSEN1dE9 mice showed few Aβ deposits in the cerebellum at 6 months of age, and the number and size of cerebellar deposits increase during aging [8,38]. However, APPswe/PSEN1dE9 exhibited cerebellar dysfunction and abnormal Purkinje cell activity before plaque deposition in the cerebellum similar to that observed in Familial Alzheimer’s disease [20,54]. Even without Aβ plaques in the cerebellum of 2-month old APPswe/PSEN1dE9 mice, a large amount of intracellular 6E10-immunoreactive proteins were observed in the cerebellar granular cells and Purkinje cells, indicating that the APPswe/PSEN1dE9 transgenes were indeed expressed both in the cerebrum and cerebellum of this transgenic AD model. The lack of Aβ plaques in the cerebellum, the early onset of cerebellum-essential functions deficit, and the decrease of cerebellar Purkinje cells in MCI and AD patients provide further evidence that the early onset cerebellum impairment was likely independent of extracellular Aβ plaque accumulation. We also observed smaller PC soma size in APP/PSEN1 mice at 5-months age which could correlate with loss of cerebellum function. We speculate that the smaller size of PC at this early age might be indicative starts of PC degeneration earlier than the accumulation of plaques and could be due to intracellular accumulation of APP fragments. It will be interesting to understand if the PCs are undergoing degeneration by apoptosis, autophagy or any other mechanism. There are previous reports indicating involvement of ER stress, higher intracellular Calcium on intracellular APP fragment processing via ubiquitin proteasome pathway as well as higher APP fragments leading to endosomal abnormalities [55,56]. Any of these mechanism could be responsible for loss of PC function by activating apoptotic pathway before actual loss of PC cells.

It could be possible that soluble Aβ oligomers may contribute to the cerebellum dysfunction in AD [57-59]. The existence of intracellular Aβ has been reported in neurons in the cerebrum, cerebellum, and spinal cord of individuals with or without AD neuropathology since the 1980s [60,61]. Intracellular Aβ has also been reported in many transgenic AD mouse models [61]. APP processing occurs at the cell surface and in the trans-Golgi network [62-64]. Furthermore, intracellular accumulation of C99 C-terminal fragments, but not the amyloid β, has been found to be the main contributor to neurodegeneration associated with AD [65-67]. The 6E10 antibody identifies full-length APP and C-terminal fragments with amino acid residues 1-16 of β-amyloid. Our immunoblot analysis further identified an equivalent expression of full-length APP, C99/C83 fragments as well as Aβ40/42 in the cerebral cortex and cerebellum during aging in the APPswe/PSEN1dE9 mice. Further, a similar level of BACE1 expression was observed in both brain regions. Our study suggests intracellular APP processing may play an important role in the cerebellar dysfunction at the early stages of AD.

In summary, our study in post-mortem human cerebellum and transgenic AD mice provided strong pilot evidence of neuropathology and neurofunction that cerebellar dysfunction might be involved in AD. The loss of Purkinje cells in MCI patients and the observed deficit of the cerebellum-essential balance/coordinative function in transgenic AD mice at 4 months of age indicated that cerebellar impairment may occur at early stage of AD, may even before cognitive deficit. Furthermore, our study suggested that cerebellar impairment in AD is likely independent of extracellular Aβ plaque accumulation but associated with intracellular APP processing.

The current study is limited in smaller sample size in both human and transgenic AD mice. Nonetheless, given that AD research has been historically focusing on the cerebrum and Aβ plaque/Tau with no effective therapy been discovered so far. The role of cerebellum in AD has been underappreciated. Our study warrants in depth and widespread research on the cerebellum beyond Aβ plaque. The early cerebellum-essential sign/symptom at the early stage of MCI and underlying mechanism, if establish, could provide guidance for early intervention and novel therapeutic target for the treatment of AD.

Supplementary Material

Supplementary Figure 1

Figure 1. Structural loss of cerebellar PCs at the age of 5 months in APPswe/PSEN1dE9 mice. A. Representative fluorescent microscopic images (20X magnification, scale bar 100 μm) of cerebellar PCs stained with Aldolase C (green) and β3 Tubulin (red) in AD and wild type mice (WT). B. Quantitative analysis of PCs count, C. Perimeter (μM) of PCs. D. Primary dendritic branches length (μM) of cerebellar PCs in AD and WT mice. AD: n=5 mice; WT: n=4 mice; * p<0.05 compared to WT.

Acknowledgments

This work was partly supported by National Institutes of Health grants R01NS088596 (SY) and R01NS109583 (SY), William and Ella Owens Medical Research Foundation (SY), and American Heart Association Grant 17POST33670981 (KC).

Footnotes

Conflict of Interest/Disclosure Statement

The authors have no conflict of interest to report.

References:

  • 1.Rakic P. Evolution of the neocortex: a perspective from developmental biology. Nat Rev Neurosci. 2009. October;10(10):724–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Cipres-Flores FJ, Segura-Uribe JJ, Orozco-Suarez S, et al. Beta-blockers and salbutamol limited emotional memory disturbance and damage induced by orchiectomy in the rat hippocampus. Life Sci. 2019. May 1;224:128–137. [DOI] [PubMed] [Google Scholar]
  • 3.Pro JD, Smith CH, Sumi SM. Presenile Alzheimer disease: amyloid plaques in the cerebellum. Neurology. 1980. August;30(8):820–5. [DOI] [PubMed] [Google Scholar]
  • 4.Braak H, Braak E, Bohl J, et al. Alzheimer's disease: amyloid plaques in the cerebellum. J Neurol Sci. 1989. November;93(2-3):277–87. [DOI] [PubMed] [Google Scholar]
  • 5.Brettschneider J, Del Tredici K, Lee VM, et al. Spreading of pathology in neurodegenerative diseases: a focus on human studies. Nat Rev Neurosci. 2015. February;16(2):109–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Catafau AM, Bullich S, Seibyl JP, et al. Cerebellar Amyloid-beta Plaques: How Frequent Are They, and Do They Influence 18F-Florbetaben SUV Ratios? J Nucl Med. 2016. November;57(11):1740–1745. [DOI] [PubMed] [Google Scholar]
  • 7.Aso E, Lomoio S, Lopez-Gonzalez I, et al. Amyloid generation and dysfunctional immunoproteasome activation with disease progression in animal model of familial Alzheimer's disease. Brain Pathol. 2012. September;22(5):636–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Lomoio S, Lopez-Gonzalez I, Aso E, et al. Cerebellar amyloid-beta plaques: disturbed cortical circuitry in AbetaPP/PS1 transgenic mice as a model of familial Alzheimer's disease. J Alzheimers Dis. 2012;31(2):285–300. [DOI] [PubMed] [Google Scholar]
  • 9.Xiong H, Callaghan D, Wodzinska J, et al. Biochemical and behavioral characterization of the double transgenic mouse model (APPswe/PS1dE9) of Alzheimer's disease. Neurosci Bull. 2011. August;27(4):221–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Tabatabaei-Jafari H, Walsh E, Shaw ME, et al. The cerebellum shrinks faster than normal ageing in Alzheimer's disease but not in mild cognitive impairment. Hum Brain Mapp. 2017. June;38(6):3141–3150. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Sluimer JD, van der Flier WM, Karas GB, et al. Accelerating regional atrophy rates in the progression from normal aging to Alzheimer's disease. Eur Radiol. 2009. December;19(12):2826–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Spires-Jones TL, Hyman BT. The intersection of amyloid beta and tau at synapses in Alzheimer's disease. Neuron. 2014. May 21;82(4):756–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Albers MW, Gilmore GC, Kaye J, et al. At the interface of sensory and motor dysfunctions and Alzheimer's disease. Alzheimers Dement. 2015. January;11(1):70–98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Schmahmann JD. Cerebellum in Alzheimer's disease and frontotemporal dementia: not a silent bystander. Brain. 2016. May;139(Pt 5):1314–8. [DOI] [PubMed] [Google Scholar]
  • 15.Jacobs HIL, Hopkins DA, Mayrhofer HC, et al. The cerebellum in Alzheimer's disease: evaluating its role in cognitive decline. Brain. 2017. July 28. [DOI] [PubMed] [Google Scholar]
  • 16.Buchman AS, Bennett DA. Loss of motor function in preclinical Alzheimer's disease. Expert Rev Neurother. 2011. May;11(5):665–76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Mazoteras Munoz V, Abellan van Kan G, Cantet C, et al. Gait and balance impairments in Alzheimer disease patients. Alzheimer Dis Assoc Disord. 2010. Jan-Mar;24(1):79–84. [DOI] [PubMed] [Google Scholar]
  • 18.Muir SW, Speechley M, Wells J, et al. Gait assessment in mild cognitive impairment and Alzheimer's disease: the effect of dual-task challenges across the cognitive spectrum. Gait Posture. 2012. January;35(1):96–100. [DOI] [PubMed] [Google Scholar]
  • 19.Fukutani Y, Cairns NJ, Rossor MN, et al. Purkinje cell loss and astrocytosis in the cerebellum in familial and sporadic Alzheimer's disease. Neurosci Lett. 1996. August 16;214(1):33–6. [DOI] [PubMed] [Google Scholar]
  • 20.Sepulveda-Falla D, Barrera-Ocampo A, Hagel C, et al. Familial Alzheimer's disease-associated presenilin-1 alters cerebellar activity and calcium homeostasis. J Clin Invest. 2014. April;124(4):1552–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Beach TG, Adler CH, Sue LI, et al. Arizona Study of Aging and Neurodegenerative Disorders and Brain and Body Donation Program. Neuropathology. 2015. August;35(4):354–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Li W, Poteet E, Xie L, et al. Regulation of matrix metalloproteinase 2 by oligomeric amyloid beta protein. Brain Res. 2011. April 28;1387:141–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Chaudhari K, Wong JM, Vann PH, et al. Exercise, but not antioxidants, reversed ApoE4-associated motor impairments in adult GFAP-ApoE mice. Behav Brain Res. 2016. May 15;305:37–45. [DOI] [PubMed] [Google Scholar]
  • 24.Chaudhari Kiran WJM, Vann Philip H. , Sumien Nathalie Exercise training and antioxidant supplementation independently improve cognitive function in adult male and female GFAP-APOE mice. Journal of Sport and Health Science. 2014;3(3):196–205. [Google Scholar]
  • 25.Buckner RL. The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron. 2013. October 30;80(3):807–15. [DOI] [PubMed] [Google Scholar]
  • 26.Strick PL, Dum RP, Fiez JA. Cerebellum and nonmotor function. Annu Rev Neurosci. 2009;32:413–34. [DOI] [PubMed] [Google Scholar]
  • 27.Azevedo FA, Carvalho LR, Grinberg LT, et al. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain. J Comp Neurol. 2009. April 10;513(5):532–41. [DOI] [PubMed] [Google Scholar]
  • 28.Andersen K, Andersen BB, Pakkenberg B. Stereological quantification of the cerebellum in patients with Alzheimer's disease. Neurobiol Aging. 2012. January;33(1):197 e11–20. [DOI] [PubMed] [Google Scholar]
  • 29.Woodruff-Pak DS, Foy MR, Akopian GG, et al. Differential effects and rates of normal aging in cerebellum and hippocampus. Proc Natl Acad Sci U S A. 2010. January 26;107(4):1624–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Vogel RW, Ewers M, Ross C, et al. Age-related impairment in the 250-millisecond delay eyeblink classical conditioning procedure in C57BL/6 mice. Learn Mem. 2002. Sep-Oct;9(5):321–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Mavroudis I, Petridis F, Kazis D, et al. Purkinje Cells Pathology in Alzheimer's Disease. Am J Alzheimers Dis Other Demen. 2019. Nov-Dec;34(7-8):439–449. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Pettersson AF, Engardt M, Wahlund LO. Activity level and balance in subjects with mild Alzheimer's disease. Dement Geriatr Cogn Disord. 2002;13(4):213–6. [DOI] [PubMed] [Google Scholar]
  • 33.Aggarwal NT, Wilson RS, Beck TL, et al. Motor dysfunction in mild cognitive impairment and the risk of incident Alzheimer disease. Arch Neurol. 2006. December;63(12):1763–9. [DOI] [PubMed] [Google Scholar]
  • 34.Hoxha E, Boda E, Montarolo F, et al. Excitability and synaptic alterations in the cerebellum of APP/PS1 mice. PLoS One. 2012;7(4):e34726. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.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. February 09;891(1-2):42–53. [DOI] [PubMed] [Google Scholar]
  • 36.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. November;20(11):737–44. [DOI] [PubMed] [Google Scholar]
  • 37.Van Dam D, D'Hooge R, Staufenbiel M, et al. Age-dependent cognitive decline in the APP23 model precedes amyloid deposition. Eur J Neurosci. 2003. January;17(2):388–96. [DOI] [PubMed] [Google Scholar]
  • 38.Kuwabara Y, Ishizeki M, Watamura N, et al. Impairments of long-term depression induction and motor coordination precede Abeta accumulation in the cerebellum of APPswe/PS1dE9 double transgenic mice. J Neurochem. 2014. August;130(3):432–43. [DOI] [PubMed] [Google Scholar]
  • 39.Russo R, Cattaneo F, Lippiello P, et al. Motor coordination and synaptic plasticity deficits are associated with increased cerebellar activity of NADPH oxidase, CAMKII, and PKC at preplaque stage in the TgCRND8 mouse model of Alzheimer's disease. Neurobiol Aging. 2018. August;68:123–133. [DOI] [PubMed] [Google Scholar]
  • 40.Ewers M, Morgan DG, Gordon MN, et al. Associative and motor learning in 12-month-old transgenic APP+PS1 mice. Neurobiol Aging. 2006. August;27(8):1118–28. [DOI] [PubMed] [Google Scholar]
  • 41.Kilgore M, Miller CA, Fass DM, et al. Inhibitors of class 1 histone deacetylases reverse contextual memory deficits in a mouse model of Alzheimer's disease. Neuropsychopharmacology. 2010. March;35(4):870–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Volianskis A, Kostner R, Molgaard M, et al. Episodic memory deficits are not related to altered glutamatergic synaptic transmission and plasticity in the CA1 hippocampus of the APPswe/PS1deltaE9-deleted transgenic mice model of ss-amyloidosis. Neurobiol Aging. 2010. July;31(7):1173–87. [DOI] [PubMed] [Google Scholar]
  • 43.Schmahmann JD. The cerebellum and cognition. Neurosci Lett. 2019. January 1;688:62–75. [DOI] [PubMed] [Google Scholar]
  • 44.Taillade M, Sauzeon H, Arvind Pala P, et al. Age-related wayfinding differences in real large-scale environments: detrimental motor control effects during spatial learning are mediated by executive decline? PLoS One. 2013;8(7):e67193. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Wang X, Wang QM, Meng Z, et al. Gait disorder as a predictor of spatial learning and memory impairment in aged mice. PeerJ. 2017;5:e2854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Wagner JM, Sichler ME, Schleicher EM, et al. Analysis of Motor Function in the Tg4-42 Mouse Model of Alzheimer's Disease. Front Behav Neurosci. 2019;13:107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Oakley H, Cole SL, Logan S, et al. Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer's disease mutations: potential factors in amyloid plaque formation. J Neurosci. 2006. October 4;26(40):10129–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Dineley KT, Xia X, Bui D, et al. 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. June 21;277(25):22768–80. [DOI] [PubMed] [Google Scholar]
  • 49.Ferguson SA, Sarkar S, Schmued LC. Longitudinal behavioral changes in the APP/PS1 transgenic Alzheimer's disease model. Behav Brain Res. 2013. April 1;242:125–34. [DOI] [PubMed] [Google Scholar]
  • 50.Fine JM, Renner DB, Forsberg AC, et al. Intranasal deferoxamine engages multiple pathways to decrease memory loss in the APP/PS1 model of amyloid accumulation. Neurosci Lett. 2015. January 1;584:362–7. [DOI] [PubMed] [Google Scholar]
  • 51.Lalonde R, Kim HD, Fukuchi K. Exploratory activity, anxiety, and motor coordination in bigenic APPswe + PS1/DeltaE9 mice. Neurosci Lett. 2004. October 14;369(2):156–61. [DOI] [PubMed] [Google Scholar]
  • 52.Xu J, Wang K, Yuan Y, et al. A Novel Peroxidase Mimics and Ameliorates Alzheimer's Disease-Related Pathology and Cognitive Decline in Mice. Int J Mol Sci. 2018. October 24;19(11). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Jackson HM, Soto I, Graham LC, et al. Clustering of transcriptional profiles identifies changes to insulin signaling as an early event in a mouse model of Alzheimer's disease. BMC Genomics. 2013. November 25;14:831. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Thal DR, Rub U, Orantes M, et al. Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology. 2002. June 25;58(12):1791–800. [DOI] [PubMed] [Google Scholar]
  • 55.Jin LW, Shie FS, Maezawa I, et al. Intracellular accumulation of amyloidogenic fragments of amyloid-beta precursor protein in neurons with Niemann-Pick type C defects is associated with endosomal abnormalities. Am J Pathol. 2004. March;164(3):975–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Jung ES, Hong H, Kim C, et al. Acute ER stress regulates amyloid precursor protein processing through ubiquitin-dependent degradation. Sci Rep. 2015. March 5;5:8805. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Cullen WK, Suh YH, Anwyl R, et al. Block of LTP in rat hippocampus in vivo by beta-amyloid precursor protein fragments. Neuroreport. 1997. October 20;8(15):3213–7. [DOI] [PubMed] [Google Scholar]
  • 58.Mavroudis I. Cerebellar pathology in Alzheimer's disease. Hell J Nucl Med. 2019. Jan-Apr;22 Suppl:174–179. [PubMed] [Google Scholar]
  • 59.Wang HW, Pasternak JF, Kuo H, et al. Soluble oligomers of beta amyloid (1-42) inhibit long-term potentiation but not long-term depression in rat dentate gyrus. Brain Res. 2002. January 11;924(2):133–40. [DOI] [PubMed] [Google Scholar]
  • 60.Grundke-Iqbal I, Iqbal K, George L, et al. Amyloid protein and neurofibrillary tangles coexist in the same neuron in Alzheimer disease. Proc Natl Acad Sci U S A. 1989. April;86(8):2853–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.LaFerla FM, Green KN, Oddo S. Intracellular amyloid-beta in Alzheimer's disease. Nat Rev Neurosci. 2007. July;8(7):499–509. [DOI] [PubMed] [Google Scholar]
  • 62.Greenfield JP, Tsai J, Gouras GK, et al. Endoplasmic reticulum and trans-Golgi network generate distinct populations of Alzheimer beta-amyloid peptides. Proc Natl Acad Sci U S A. 1999. January 19;96(2):742–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Choy RW, Cheng Z, Schekman R. Amyloid precursor protein (APP) traffics from the cell surface via endosomes for amyloid beta (Abeta) production in the trans-Golgi network. Proc Natl Acad Sci U S A. 2012. July 24;109(30):E2077–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.O'Brien RJ, Wong PC. Amyloid precursor protein processing and Alzheimer's disease. Annu Rev Neurosci. 2011;34:185–204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Devi L, Ohno M. Mitochondrial dysfunction and accumulation of the beta-secretase-cleaved C-terminal fragment of APP in Alzheimer's disease transgenic mice. Neurobiol Dis. 2012. January;45(1):417–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Lauritzen I, Pardossi-Piquard R, Bauer C, et al. The beta-secretase-derived C-terminal fragment of betaAPP, C99, but not Abeta, is a key contributor to early intraneuronal lesions in triple-transgenic mouse hippocampus. J Neurosci. 2012. November 14;32(46):16243–1655a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Lauritzen I, Pardossi-Piquard R, Bourgeois A, et al. Intraneuronal aggregation of the beta-CTF fragment of APP (C99) induces Abeta-independent lysosomal-autophagic pathology. Acta Neuropathol. 2016. August;132(2):257–76. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure 1

Figure 1. Structural loss of cerebellar PCs at the age of 5 months in APPswe/PSEN1dE9 mice. A. Representative fluorescent microscopic images (20X magnification, scale bar 100 μm) of cerebellar PCs stained with Aldolase C (green) and β3 Tubulin (red) in AD and wild type mice (WT). B. Quantitative analysis of PCs count, C. Perimeter (μM) of PCs. D. Primary dendritic branches length (μM) of cerebellar PCs in AD and WT mice. AD: n=5 mice; WT: n=4 mice; * p<0.05 compared to WT.

NIHMS1679225-supplement-Supplementary_Figure_1.tif (1.8MB, tif)

RESOURCES