Evaluation of oxidative stress in the brain of a transgenic mouse model of Alzheimer disease by in vivo electron paramagnetic resonance imaging

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Evaluation of oxidative stress in the brain of a transgenic mouse model of Alzheimer’s disease by in vivo electron paramagnetic resonance imaging Akihiro Matsumura, Miho C Emoto, Syuuichirou Suzuki, Naotoshi Iwahara, Shin Hisahara, Jun Kawamata, Hiromi Suzuki, Ayano Yamauchi, Hideo Sato-Akaba, Hirotada G Fujii, Shun Shimohama

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Free Radical Biology and Medicine

Received date: 3 February 2015 Revised date: 4 April 2015 Accepted date: 12 April 2015 Cite this article as: Akihiro Matsumura, Miho C Emoto, Syuuichirou Suzuki, Naotoshi Iwahara, Shin Hisahara, Jun Kawamata, Hiromi Suzuki, Ayano Yamauchi, Hideo Sato-Akaba, Hirotada G Fujii, Shun Shimohama, Evaluation of oxidative stress in the brain of a transgenic mouse model of Alzheimer’s disease by in vivo electron paramagnetic resonance imaging, Free Radical Biology and Medicine, http://dx.doi.org/10.1016/j.freeradbiomed.2015.04.013 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Title: Evaluation of oxidative stress in the brain of a transgenic mouse model of Alzheimer’s disease by in vivo electron paramagnetic resonance imaging

Authors and affiliation: Akihiro Matsumuraa, Miho C Emotob (equal contribution), Syuuichirou Suzukia, Naotoshi Iwaharaa, Shin Hisaharaa, Jun Kawamataa, Hiromi Suzukia, Ayano Yamauchia, Hideo SatoAkabac, Hirotada G Fujiib and Shun Shimohamaa

a

Department of Neurology, School of Medicine, Sapporo Medical University, South 1, West 16, Chuo-

ku, Sapporo 060-8543, Japan b

Center for Medical Education, Sapporo Medical University, South 1, West 16, Chuo-ku, Sapporo 060-

8543, Japan c

Department of Systems Innovation, Graduate School of Engineering Science, Osaka University,

Toyonaka, Osaka 560-8531, Japan

E-mail address: [email protected] (Akihiro Matsumura)

Corresponding author with complete address for mailing proofs: Dr. Shun Shimohama, Department of Neurology, School of Medicine, Sapporo Medical University, South 1, West 16, Chuo-ku, Sapporo 060-8543, Japan Tel: +81-11-611-2111 Fax: +81-11-622-7668 E-mail address: [email protected]

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Abstract Alzheimer’s disease (AD) is a neurodegenerative disease clinically characterized by progressive cognitive dysfunction. Deposition of amyloid-β (Aβ) peptides is the most important pathophysiological hallmark of AD. Oxidative stress induced by reactive oxygen species (ROS) is prominent in AD, and several reports suggest the relationship between the change in redox status and AD pathology containing progressive Aβ deposition, the activation of glial cells and mitochondrial dysfunction. Therefore, we examined immunohistochemical analysis using a transgenic mouse model of AD (APdE9), and evaluated the activity of superoxide dismutase (SOD) in the brain tissue homogenates of APdE9 mice in vitro. Together with those analysis, in vivo changes in redox status with age in both wild-type (WT) and APdE9 mouse brains were measured noninvasively by three-dimensional (3D) electron paramagnetic resonance (EPR) imaging using nitroxide [3-methoxycarbonyl-2,2,5,5-tetramethyl-pyrrolidine-1-yloxy (MCP)] as a redox-sensitive probe. Both methods found the similar change in redox status with age, and in particular a significant change in redox status in the hippocampus was observed by EPR imaging noninvasively between APdE9 mice and age-matched WT mice from 9 months until 18 months of age. EPR imaging clearly visualized the accelerated change in redox status of APdE9 mouse brain compared with WT. The evaluation of the redox status in the brain of AD model rodents by EPR imaging should be useful for diagnostic study of AD.

Key words: Alzheimer’s disease; Hippocampus; EPR; Imaging; ROS; redox status; oxidative stress; Microglia; Astrocytes; Amyloid-β.

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Introduction Alzheimer’s disease (AD) is the most common form of dementia in the elderly. This is a neurodegenerative disease clinically characterized by progressive cognitive dysfunction. The pathology of AD is characterized by extracellular senile plaques consisting of fibrillar amyloid-β (Aβ) peptides, followed by the formation of neurofibrillary tangles and loss of synapses and neurons. In particular, deposition of Aβ is considered to be the most important pathophysiological hallmark of AD, according to the amyloid cascade hypothesis [1]. Additionally, accumulation of activated microglia and astrocytes in and around senile plaques has been demonstrated in autopsied brains from AD patients, and considered to represent immune responses in AD [2-7]. Microglia are macrophage-like resident immune cells in the central nervous system (CNS). Previous studies using AD models suggested the involvement of microglia in Aβ clearance [8-11]. On the other hand, several types of activated microglia have been shown to release inflammatory cytokines and reactive oxidative species (ROS), resulting in CNS injury [2, 12]. The brain is especially vulnerable to oxidative stress because of its high oxygen consumption rate, high levels of polyunsaturated fatty acids, and not particularly enriched in antioxidant defense enzymes. It has long been hypothesized that oxidative stress induced in AD brains plays an important role in the pathogenesis of AD [13-17], and several markers of oxidative stress have been evaluated in autopsied brains from AD patients [18]. In AD pathology, Aβ peptide produced in the AD brain activates microglia and astrocytes. Some of these activated cells are proinflammatory and cytotoxic subtype (e.g., classical activation state (M1) of microglia), and produce both ROS and proinflammatory cytokines (Fig. 1). Additionally, mitochondrial dysfunction is also suggested to cause oxidative stress in AD [193

22]. Under oxidative stress, ROS activate amyloid precursor protein processing enzymes; β- and γsecretase, accelerating the production of Aβ in AD [16, 23]. Therefore, the vicious spiral of Aβ increase and oxidative stress induction may progress in the brain of AD patients. Under these conditions, elucidating the relationship between AD pathology and ROS generation under oxidative stress may contribute not only to clarify the detailed mechanisms for the development of AD but also to develop new therapeutic strategies for AD patients. ROS (including superoxide radicals, hydroxyl radicals, and singlet oxygen) and nitric oxide (NO) are generated during normal cellular metabolism. Under pathological conditions, production of ROS and NO is augmented, but their short half-lives make it extremely difficult to measure these radicals quantitatively either in in vitro or in vivo system. To overcome this problem, molecules that are modified by interactions with ROS in the biological system have been investigated as biomarkers of oxidative stress. DNA, lipids, proteins and carbohydrates are examples of such molecules that can be modified by excess ROS in vivo. Several biomarkers of oxidative stress have been developed, and many reported studies on AD utilized these biomarkers. However, none of these methods can be used to examine and monitor the effects of ROS in the brain of AD model mice noninvasively, repeatedly and for prolonged periods. Different from the above methods, the electron paramagnetic resonance (EPR)/spin probe technique is suitable for the examination of free radical reactions in vivo in experimental disease animal models, as demonstrated in many reports [24-27]. Nitroxide spin probes are redox-active compounds that can be oxidized or reduced by the biological reactions in cells. Tissue redox status and oxidative stress accompanying generation of hydroxyl radicals [28, 29] and superoxide radicals [30, 31] enhance the 4

conversion of the paramagnetic nitroxide to the corresponding diamagnetic hydroxylamine. Therefore, monitoring the rate of transformation of nitroxide to the corresponding diamagnetic probe by EPR imaging provides in vivo assessment of redox status in experimental animals. Such redox mapping based on redox-sensitive nitroxide spin probes used in EPR imaging has been reported in several rodent models of experimental diseases [29, 31, 32]. In the present study, we used a transgenic mouse model of AD, APdE9, and the wild-type littermates, and followed the deposition of Aβ and the activation of microglia and astrocytes in the brain from 3 to 18 months of age. Simultaneous with these immunehistochemical studies, first we evaluated the level of oxidative stress of brain tissues in vitro by measuring the change in the activity of antioxidant enzyme, superoxide dismutase (SOD). In parallel with this in vitro assay, we followed the changes in redox status in the brain from 3 to 18 months of age in both transgenic and wild-type mice, using three-dimensional (3D) EPR imaging combined with a redox-sensitive nitroxide probe.

Materials and methods Animals All the animal studies were approved by the Animal Care and Use Committee of Sapporo Medical University, and all procedures were carried out in accordance with the institutional guidelines. Male and female APPswe/PS1dE9 (APdE9) transgenic (Tg) mice and wild-type littermates (WT mice) were used in this study. The APdE9 founder mice were purchased from Jackson Laboratory, USA. All mice used in this study were bred by mating male APdE9 mice with female C57BL6/J mice in the animal facilities

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at Sapporo Medical University. The mice were maintained at 25°C with a 12-h light/dark cycle and provided food and water ad libitum. For details about APdE9 mice, refer to the web site of Jackson Laboratory [strain B6.Cg-Tg (APPswe, PSEN1dE9) 85Dbo/J; stock number 005864; http://jaxmice.jax.org/]. These hemizygous APdE9 mice express chimeric mouse/human amyloid precursor protein APPswe (mouse APP695 harboring a human Aβ domain with mutations K595N and M596L linked to Swedish familial AD pedigrees) and human mutated presenilin 1-dE9 (deletion of exon 9). These mutations are associated with early-onset AD and secretion of human Aβ. Brain tissue preparation Three, 6, 9, 12 and 18 month-old APdE9 mice (5 mice per group for each time point) were deeply anesthetized by intraperitoneal injection of pentobarbital sodium (50 mg/kg). Then, the brain was quickly removed and hemisected in the midsagittal plane. One hemisphere was postfixed for 2 days in 4% paraformaldehyde, and subsequently transferred to 10% sucrose followed by 20% sucrose in 10 mM phosphate-buffered saline (PBS) at 4°C for immunohistochemical and histological studies. The other hemisphere was frozen in liquid nitrogen after dissecting the cerebellum, and stored at -80°C. Immunohistochemistry Immunohistochemical analyses were performed as described previously [11]. The hemi-brain of an APdE9 mouse was cut into 20-µm thick slices using a cryostat, and collected in 10 mM PBS containing 0.1% sodium azide at 4°C. Four free floating brain sections containing the hippocampus at intervals of 400 µm were picked up and incubated for 3 days at 4°C with the following primary antibodies: mouse monoclonal anti-Aβ antibody (1:5,000; clone 6E10, Covance, Princeton, NJ, USA), rabbit polyclonal 6

anti-ionized calcium binding adaptor molecule 1 (Iba1) antibody (1:5,000; Wako Chemical, Osaka, Japan) for microglia, and mouse monoclonal anti-glial fibrillary acidic protein (GFAP) antibody (1:5,000; Millipore, Billerica, MA, USA) for astrocytes. After several washes with 10 mM PBS containing 0.3% Triton X-100 (PBS-T), sections were incubated appropriately with biotinylated antimouse or anti-rabbit immunoglobulin (Ig)G antibody (1:2,000; Vector Laboratories, Burlingame, CA, USA) for 2 h at room temperature. The sections were then incubated with avidin peroxidase (1:4,000; ABC Elite Kit, Vector Laboratories, Burlingame, CA, USA) for 1 h at room temperature. All the sections were washed several times with PBS-T between incubations, and labeling was visualized by incubating with 3,3’-diaminobenzidine (DAB) and nickel ammonium, which yielded a dark blue color [33]. We observed the immunostained sections of APdE9 mice under a light microscope. Triple immunofluorescent staining was performed and observed under a confocal microscope. Two hemi-brain sections of an APdE9 mouse at an interval of 800 µm was incubated with rabbit polyclonal anti-Iba1 antibody (1:5,000) and mouse monoclonal anti-GFAP antibody (1:5,000) for 3 days at 4°C. Then, the sections were probed with anti-mouse IgG antibody conjugated with Alexa Fluor 488 and anti-rabbit IgG antibody conjugated with Alexa Fluor 594 (each diluted 1:2,000) for 2 h at room temperature. The brain sections were further incubated with 1-fluoro-2,5-bis (3-carboxy-4hydroxystyryl) benzene (FSB, 1:10,000; Dojindo Laboratories, Kumamoto, Japan) for 30 min, to stain amyloid. Fluorescence was observed under a laser scanning confocal microscope (LSM510 Meta; Carl Zeiss, Jena, Germany). Quantification of amyloid plaque burden, microglia and astrocytes of the hippocampus In APdE9 mice, DAB-labeled sections stained by anti-Aβ, anti-Iba1 and anti-GFAP antibodies were 7

analyzed by measuring the percentage of positively stained area in a microscopic field using ImageJ software, as described previously [11]. Then, we compared the mean percentage of Aβ-, Iba1- and GFAP-positive areas among age groups. All images were binarized with the same threshold for each antibody signal using Adobe Photoshop CS6 software, and the percentage of positively stained area was measured. Measurement of superoxide dismutase activity The activity of SOD in brain tissue homogenates were evaluated using a spectrophotometric assay according to the previously reported method [34]. The superoxide generating reaction was initiated by the addition of xanthine oxidase (Roche Diagnostics, Indianapolis, IN, USA) to the reaction mixture (50mM phosphate buffer, pH 7.4) containing hypoxanthine (0.5 mM, Dojindo Laboratories, Kumamoto, Japan), and the amount of superoxide generated was quantitated by the reduction of cytochrome c (20 M, Sigma, St Louis, MO, USA) at 550 nm. The activity of SOD was calculated by the definition that one unit inhibits the rate of reduction of cytochrome c by 50%. In vivo EPR imaging EPR images of mouse heads were obtained using a custom-made 750-MHz CW-EPR imager. A main static magnetic field of 27 mT was generated with permanent magnets (Hitachi Metals, Ltd., Tokyo, Japan). Three sets of coils for magnetic field gradients and field scanning were driven by bipolar power supplies (PBX20-10, Kikusui Electronics Corp., Yokohama, Japan). As previously described [35], the sequence for field scanning consisted of three ramp changes, and the minimum scanning time was 50 ms. Data acquisition was controlled with an in-house program in LabVIEW software (National Instruments Inc., TX, USA). Image reconstruction from EPR spectra was based on the method of 8

filtered back-projection and was performed using a PowerMac G5 computer [36]. 3D EPR images were obtained by the single-stage filtered back-projection algorithm. This method does not go through twodimensional (slice-selective) images in the process of 3D image reconstruction. Thus, slice-selective 2D images in this study were generated from the reconstructed 3D image data sets. The estimated spatial resolution of EPR images in this study was approximately 1.0 mm [35]. In vivo EPR imaging of WT and APdE9 mouse heads APdE9 mice at the ages of 3 (n = 5), 6 (n = 8), 9 (n = 6), 12 (n = 6) and 18 months (n = 5), and WT mice at the ages of 3 (n = 5), 6 (n = 8), 9 (n = 6), 12 (n = 8) and 18 months (n = 6) were used in in vivo EPR imaging experiments. The blood-brain barrier-permeable nitroxide MCP [3-methoxycarbonyl2,2,5,5-tetramethyl-pyrrolidine-1-yloxy (Fig. 4B); Kyoto-Spinlabo Co., Ltd., Kyoto, Japan] was used as a redox-sensitive imaging probe. Both APdE9 and WT mice were anesthetized by inhalation of 1.5% isoflurane in air at 250 mL/min. The tail vein was cannulated with a 27-G needle for injection of the probe. MCP (1.5 µmol/g body weight) in PBS was injected via the tail vein over approximately 15 s. The body temperature of mice was maintained at 37 ± 0.5 °C during the EPR imaging experiments. Calculation of nitroxide reduction rate constants and their mapping The rate constant of the nitroxide reduction reaction for each pixel of the two-dimensional (2D) EPR image was calculated using a custom-written program in LabVIEW software (National Instruments, Austin, TX, USA) as reported previously [32]. Briefly, 2D slice images were obtained from the reconstructed 3D data, and the time-course of the signal intensity at each pixel was extracted. Semilogarithmic plot of the time course of the EPR signal intensity of MCP was used for calculation of rate constant. The rate constant of MCP was evaluated for each pixel using six temporal 2D slice images and 9

mapped in 2D format. The region of interest (ROI) was chosen in the map obtained, and averaged rate constant of MCP in the selected ROI was calculated using a custom-written program in Matlab software (The MathWorks Inc., Natick, MA, USA). MRI of mouse heads MRI of mouse heads were obtained using an MRmini scanner (MR Technology, Tsukuba, Japan), which consists of a 0.5 Tesla permanent magnet and a solenoid MRI coil. MRI was obtained using a spin-echo multi-slice T1-weighted sequence with the following parameters: repetition time = 450 ms, echo time = 12 ms, FOV = 40 mm, matrix = 256×128, number of excitations = 3, slice thickness = 1.2 mm, space =0.1 mm. Co-registration of EPR images and MRI Before EPR imaging, anatomical MRI images of the mouse head were obtained. In this study, the sagittal image of the middle of the mouse head was used for co-registration. The nitroxide distribution and its half-life map were obtained by EPR imaging, and each map was co-registered to the sagittal MRI of the mouse head. EPR and MRI coils with identical dimensions (22 mm inner diameter and 30 mm long) and a common mouse bed were used. To adjust the EPR and MRI images, a position marker, triarylmethyl probe oxo63 or nitroxide compound, was used for both modalities [32]. Statistics The percentage of positively stained area in the brain of APdE9 mice, and the values obtained from EPR imaging in APdE9 mice and WT mice are presented as mean ± SEM. The differences between groups were analyzed by Student’s t-test or ANOVA followed by post hoc comparison with TukeyKramer HSD test. The JMP statistical program (SAS Institute, Cary, NC, USA) was used for data 10

analysis.

Results Immunohistochemical and quantitative analysis of photomicroscopic images of immunostained brain sections of APdE9 mice Immunofluorescent images triple-stained for Aβ, microglia and astrocytes were obtained for two brain sections containing the hippocampus at an interval of 800 µm for each APdE9 mouse (Fig. 2A-E). In APdE9 mice, Aβ deposition stained by FSB increased with age, and microglia labeled by anti-Iba1 antibody were closely associated with Aβ deposits, while astrocytes labeled by anti-GFAP antibody accumulated around the Aβ deposition sites. Based on the following evidence: (1) microglia were closely associated with Aβ deposits (Fig. 2A-E) and (2) microglia internalized Aβ as in our previous in vitro study [8], we speculate that activated microglia phagocytose Aβ deposit in APdE9 mice. For each APdE9 mouse, four brain sections containing the hippocampus at intervals of 400 µm were immunostained for Aβ, microglia and astrocyte, and the photomicrographs are shown in Fig. 2F-Y. Deposition of Aβ in the hippocampus increased with age (Fig. 2F-J). However, there was no Aβ deposition in the midbrain (Fig. 2 K-O). In addition, the immunereactivity of microglia and astrocytes increased with age until 12 months of age and remained high at 18 months (Fig. 2P-Y). Using the photomicroscopic images of Aβ (Fig. 2 F-J), Iba1 (Fig. 2 P-T) and GFAP immunostaining (Fig. 2 U-Y), the percentage of positively stained area in a high power microscopic field of the hippocampus (area surrounded by red square) was calculated as described previously [11]. The Aβ burden increased in a time-dependent manner drastically at 12 months of age, and Aβ-immunostained area was significantly 11

elevated at 12 and 18 months compared to 3, 6 and 9 months (Fig. 2g1). As shown in Fig. 2g2 and 2g3, both Iba1- and GFAP-positive areas increased significantly from 9 months and reached a maximum at 12 months of age. These glial responses continued along with increase in Aβ deposition until 12 months of age, and remained elevated at 18 months. These phenomena may be associated with the progression of AD-like pathology in APdE9 mice. Evaluation of redox status in WT and APdE9 mice by in vitro biochemical assay and in vivo EPR imaging SOD is one of the key enzymes involved in cellular protection against damage induced by ROSinduced oxidative stress. The level of oxidative stress in AD-model mouse brain was evaluated by measuring the activity of SOD in brain homogenates prepared from the cerebral cortex of 3-, 9-, 12-, and 18-month-old APdE9 mice. After 9-months, a significant decrease in the activity of SOD was observed in the brains of APdE9 mice compared to that in 3-month-old mouse brain (Fig. 3). Next, the change in the redox status in vivo was followed with EPR imaging method by measuring the balance between oxidants and antioxidants noninvasively. To evaluate the redox status in WT and APdE9 mice, the redox-sensitive nitroxide imaging probe MCP (Fig. 4B) was used. The rate of reduction reaction of MCP obtained by EPR imaging was used as an index of in vivo redox status. Immediately after MCP was intravenously injected into WT and APdE9 mice, serial 3D EPR images were acquired every 30s. From these 3D EPR image data sets, slice-selective 2D images of mouse heads were generated. The sagittal (x-y plane) 2D EPR images of the WT mouse heads are shown in Fig. 4C. In order to analyze the MCP reduction kinetics in both WT and APdE9 mouse brains, rate constants of 12

MCP reduction at each pixel of the 2D image were calculated using the temporal changes in EPR signal intensity data. The pixel-based MCP reduction rates were computed and the corresponding image (socalled “redox map”) for WT mouse head reconstructed in the sagittal direction is displayed in Fig. 4D. The redox map was superimposed onto the MRI of the same WT mouse head (Fig. 4E) obtained before EPR experiments. The co-registered image (Fig. 4F) clearly showed location-specific distribution of MCP reduction rate in the WT mouse head. Change in redox status in the hippocampus with age in WT and APdE9 mice The redox map of APdE9 mouse head was obtained by the same methods as described above for WT mouse. Figures 5A and B show the co-registered images for 9 month-old WT and APdE9 mice, respectively. As shown in Fig. 2, although Aβ was accumulated in the hippocampus, there was no Aβ deposition in the midbrain of APdE9 mice. From these results, the midbrain was chosen as reference tissue that showed little or no effect from Aβ deposition. Two ROIs were selected, one in the hippocampus and the other in the midbrain, based on the anatomical map of MRI. In Fig. 5, the ROI in the hippocampus (ROI-1; 6 x 4 pixels) is indicated by a blue outlined square, and the ROI in the midbrain (ROI-2; 6 x 6 pixels) by a yellow outlined square. The averaged rate constants in both ROI (ROI-1 and ROI-2) were calculated for WT and APdE9 mice. The MCP reduction rate constant in the hippocampus (ROI-1) was not significantly different between WT and age-matched APdE9 mice (at least 5 mice used in each group, data not shown). In order to normalize the individual difference in each WT and age-matched APdE9 mouse, the ratio of MCP reduction rate constant in the hippocampus to that in the midbrain was newly defined as RRHM. 13

RRHM = rate constant in hippocampus / rate constant in midbrain RRHM was calculated in each WT and APdE9 mouse, and the changes in RRHM with age are shown in Fig. 6. In WT mice, RRHM did not change significantly until 18 months of age, although there was an apparent slight increase until 12 months of age followed by a decline at 18 months (Fig. 6A). Mean RRHM in APdE9 mice (Fig. 6B) did not show apparent increase, in contrast to WT mice. In Fig. 7, mean RRHM were compared between age-matched WT and APdE9 mice. There was no significant difference in mean RRHM between age-matched WT and APdE9 mice at 3 and 6 months of age (Fig. 7A and B). However, RRHM of APdE9 mice were significantly lower than those of agematched WT mice at 9, 12 and 18 months of age (Fig. 7C-E). Decreased RRHM indicated that reduction of the redox-sensitive nitroxide probe MCP in the hippocampus was slower in APdE9 mice than in WT mice. These results suggest that APdE9 mice began to show change in redox status in the hippocampus compared to age-matched WT mice from 9 months of age, and this significant change in redox status continued until 18 months of age. Based on our previous report [35], these results strongly indicate more prominent oxidative stress in the hippocampus of APdE9 mice compared to age-matched WT mice, causing a shift in redox status in the hippocampus of APdE9 mice detected by EPR imaging.

Discussion AD is one of the most common neurodegenerative diseases that cause progressive dementia. In 2013, there were estimated 44 million people with dementia worldwide, and AD constituted 50% to 75% of the dementia cases [37]. This number will continue to increase in the future, thus fundamental therapy for AD is necessary. However, the etiology of sporadic AD remains unknown and effective treatment 14

has not been reported. Therefore, basic study using a mouse model of AD is necessary and important for the development of new therapeutic strategies for AD. A variety of genetic models for Alzheimer’s disease research have been developed [38-40]. Among them, APdE9 mice used in the present study express mutated genes that are involved in early-onset AD and secretion of human Aβ in the brain [11, 38]. Extracellular deposition of Aβ is considered to be the pathophysiological hallmark of AD. In autopsied brains from AD patients or brains of AD-Tg mice, accumulation of activated microglia and astrocytes has been detected around Aβ deposits [2-7, 11, 41-43], and are considered to be associated with Aβ clearance or release of factors such as ROS and inflammatory cytokines. ROS accelerate the production of Aβ by activating amyloid precursor protein processing enzymes [16, 23]. Thus, the vicious spiral of Aβ increase and ROS generation may occur in the brain of AD patients. As is shown in many studies, oxidative stress induced by ROS plays an important role in the pathogenesis of AD, and is related to an early event involved in the cascade of AD pathology [16, 18, 44-46]. Therefore, we focused on redox state under oxidative stress as a marker for early diagnosis in AD model mice. To assess the effect of oxidative stress induced by ROS in AD animal models, most of the previous studies employed in vitro tests using antioxidant markers, but a noninvasive method to measure the change in redox status in living mice together with behavioral evaluation is preferable. Therefore, together with in vitro biochemical assay of SOD activity, we employed in vivo EPR imaging to evaluate noninvasively the change in redox status in the brain of AD model mice. Using EPR imaging, the rate constant of the reduction reaction of the intravenously injected MCP was measured in living mice. Since the reduction rate increases with increasing antioxidant capacity [47-50], reduction rates have been used as an index 15

of in vivo redox status, indicating the balance of oxidation-reduction reaction in vivo [26, 27, 51, 52]. In the present study, Aβ deposition was clearly detected in the hippocampus, but not in the midbrain, of APdE9 mice. Therefore, in each individual mouse, MCP reduction rate obtained in the hippocampus was normalized by the reduction rate measured in the midbrain where there was no Aβ deposition. The ratio obtained, RRHM, was used as an index of redox status associated with Aβ deposition for comparison among the mice studied. To examine if the redox status begins to change before Aβ deposition, changes of RRHM with age in WT and APdE9 mice were compared. Although ANOVA detected no significant difference in RRHM among different ages in both APdE9 and WT mice, RRHM was significantly lower in APdE9 mice than in age-matched WT mice at 9, 12 and 18 months of age, suggesting that antioxidant capacity began to decrease in APdE9 mice from 9 months of age. As shown in Fig. 3, a drastic increase in Aβ deposition and accumulation of microglia/astrocytes occurred at 12 months of age in the hippocampus of APdE9 mice, suggesting that Aβ deposition and accumulation of microglia/astrocytes began after the onset of change in redox status detected by EPR imaging. Previous reports have shown that the activities of microglia and astrocytes increase significantly from 9 months of age [11] and that these activated cells generate ROS in AD [2, 12, 20, 21, 53-56]. Thus, it is possible that significantly increased activities of microglia and astrocytes in APdE9 mice from 9 months of age may result in increased generation of ROS, which may explain the significant differences in redox status in the hippocampus of APdE9 mice compared to age-matched WT mice from 9 months to 18 months of age. A large number of biological markers of oxidative stress have been developed and used to assess redox state in AD model mice [57-64]. Some of them are markers of oxidative metabolism such as 16

proteins, DNA and lipids; and the others are markers of enzymatic (such as SOD and catalase) and nonenzymatic (such as vitamin C and vitamin E) antioxidant defense systems. In many studies of AD model mice, temporal changes in those makers were discussed with progressive Aβ deposition in the brain [57-60, 62, 63]. In the present study, the activity of antioxidant enzyme SOD was evaluated in brain homogenates from AD model mice. On the other hand, EPR imaging combined with a redoxsensitive nitroxide probe can monitor in vivo redox status; i.e., the change in the balance of antioxidants and oxidants, since nitroxides can participate in cellular redox reactions in vivo. Therefore, the timing of the increase in oxidative stress detected by EPR imaging in AD models is not necessarily the same as that detected by biological makers, because the former indicates the balance between antioxidants and oxidants while the latter reflects either antioxidants or oxidants. Unexpectedly, in the present study, the timing of the increase in oxidative stress detected by EPR imaging was nearly the same to that estimated by the activity of SOD, but the change in balance between antioxidants and oxidants should be evaluated by either in vivo or in vitro assay. Since ROS-mediated imbalance of antioxidants and oxidants is related to the development of Aβ deposition and progression of AD pathology [16, 19-21, 65, 66], EPR imaging that can detect changes in the redox status in vivo may be suitable for monitoring the pathological changes in AD model mice. Therefore, EPR imaging may contribute to the development of new drugs for neurodegenerative diseases such as AD and Parkinson’s disease, in which oxidative stress plays an important role. EPR imaging is a potentially powerful tool to elucidate the etiology of AD and facilitate the development of new therapeutic strategies for AD.

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Acknowledgments We are especially grateful to Dr. Kazuyuki Takata, Dr. Yoshihisa Kitamura, Dr. Masanori Sasaki, Dr. Osamu Honmou and Dr. Nobuhiro Mikuni for their assistance throughout this study. This study was supported in part by the Grant-in-Aid for Challenging Exploratory Research No. 23659460 (S.S.) and 24659352 (A.M.) by Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research (B) No. 22390180 (S.S.) and No. 26293280 (H.G.F) by JSPS, Grant-in-Aid for Young Scientists (B) No. 24791318 (M.C.E) by JSPS, and grants by the Smoking Research Foundation (S.S.).

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References

[1]

Hardy, J.; Selkoe, D. J. The amyloid hypothesis of Alzheimer's disease: progress and

problems on the road to therapeutics. Science 297:353-356; 2002. [2]

Akiyama, H.; Barger, S.; Barnum, S.; Bradt, B.; Bauer, J.; Cole, G. M.; Cooper, N. R.;

Eikelenboom, P.; Emmerling, M.; Fiebich, B. L.; Finch, C. E.; Frautschy, S.; Griffin, W. S.; Hampel, H.; Hull, M.; Landreth, G.; Lue, L.; Mrak, R.; Mackenzie, I. R.; McGeer, P. L.; O'Banion, M. K.; Pachter, J.; Pasinetti, G.; Plata-Salaman, C.; Rogers, J.; Rydel, R.; Shen, Y.; Streit, W.; Strohmeyer, R.; Tooyoma, I.; Van Muiswinkel, F. L.; Veerhuis, R.; Walker, D.; Webster, S.; Wegrzyniak, B.; Wenk, G.; Wyss-Coray, T. Inflammation and Alzheimer's disease. Neurobiol. Aging 21:383-421; 2000. [3]

Dickson, D. W.; Lee, S. C.; Mattiace, L. A.; Yen, S. H.; Brosnan, C. Microglia and cytokines

in neurological disease, with special reference to AIDS and Alzheimer's disease. Glia 7:75-83; 1993. [4]

McGeer, P. L.; McGeer, E. G. The inflammatory response system of brain: implications for

therapy of Alzheimer and other neurodegenerative diseases. Brain. Res. Rev 21:195-218; 1995. [5]

Paresce, D. M.; Ghosh, R. N.; Maxfield, F. R. Microglial cells internalize aggregates of the

Alzheimer's disease amyloid beta-protein via a scavenger receptor. Neuron 17:553-565; 1996. [6]

Paresce, D. M.; Chung, H.; Maxfield, F. R. Slow degradation of aggregates of the

Alzheimer's disease amyloid beta-protein by microglial cells. J. Biol. Chem. 272:29390-29397; 1997. [7]

Akiyama, H.; Mori, H.; Saido, T.; Kondo, H.; Ikeda, K.; McGeer, P. L. Occurrence of the

diffuse amyloid beta-protein (Abeta) deposits with numerous Abeta-containing glial cells in the cerebral cortex of patients with Alzheimer's disease. Glia 25:324-331; 1999. 19

[8]

Kakimura, J.; Kitamura, Y.; Takata, K.; Umeki, M.; Suzuki, S.; Shibagaki, K.; Taniguchi, T.;

Nomura, Y.; Gebicke-Haerter, P. J.; Smith, M. A.; Perry, G.; Shimohama, S. Microglial activation and amyloid-beta clearance induced by exogenous heat-shock proteins. FASEB J. 16:601-603; 2002. [9]

Kitamura, Y.; Shibagaki, K.; Takata, K.; Tsuchiya, D.; Taniguchi, T.; Gebicke-Haerter, P. J.;

Miki, H.; Takenawa, T.; Shimohama, S. Involvement of Wiskott-Aldrich syndrome protein family verprolin-homologous protein (WAVE) and Rac1 in the phagocytosis of amyloid-beta(1-42) in rat microglia. J. Pharmacol. Sci. 92:115-123; 2003. [10]

Takata, K.; Kitamura, Y.; Yanagisawa, D.; Morikawa, S.; Morita, M.; Inubushi, T.; Tsuchiya,

D.; Chishiro, S.; Saeki, M.; Taniguchi, T.; Shimohama, S.; Tooyama, I. Microglial transplantation increases amyloid-beta clearance in Alzheimer model rats. FEBS Lett. 581:475-478; 2007. [11]

Matsumura, A.; Suzuki, S.; Iwahara, N.; Hisahara, S.; Kawamata, J.; Suzuki, H.; Yamauchi,

A.; Takata, K.; Kitamura, Y.; Shimohama, S. Temporal Changes of CD68 and alpha7 Nicotinic Acetylcholine Receptor Expression in Microglia in Alzheimer's Disease-Like Mouse Models. J. Alzheimers Dis. 44:409-423; 2015. [12]

Combs, C. K.; Karlo, J. C.; Kao, S. C.; Landreth, G. E. beta-Amyloid stimulation of

microglia and monocytes results in TNFalpha-dependent expression of inducible nitric oxide synthase and neuronal apoptosis. J. Neurosci. 21:1179-1188; 2001. [13]

Markesbery, W. R. Oxidative stress hypothesis in Alzheimer's disease. Free Radic. Biol.

Med. 23:134-147; 1997. [14]

Floyd, R. A. Antioxidants, oxidative stress, and degenerative neurological disorders. Proc.

Soc. Exp. Biol. Med. 222:236-245; 1999. 20

[15]

Moreira, P. I.; Siedlak, S. L.; Aliev, G.; Zhu, X.; Cash, A. D.; Smith, M. A.; Perry, G.

Oxidative stress mechanisms and potential therapeutics in Alzheimer disease. J. Neural Transm. 112:921-932; 2005. [16]

Guglielmotto, M.; Giliberto, L.; Tamagno, E.; Tabaton, M. Oxidative stress mediates the

pathogenic effect of different Alzheimer's disease risk factors. Front. Aging Neurosci. 2:3; 2010. [17]

Li, J.; O, W.; Li, W.; Jiang, Z. G.; Ghanbari, H. A. Oxidative stress and neurodegenerative

disorders. Int J Mol Sci 14:24438-24475; 2013. [18]

Nunomura, A.; Chiba, S.; Lippa, C. F.; Cras, P.; Kalaria, R. N.; Takeda, A.; Honda, K.; Smith,

M. A.; Perry, G. Neuronal RNA oxidation is a prominent feature of familial Alzheimer's disease. Neurobiol. Dis. 17:108-113; 2004. [19]

Mattson, M. P. Pathways towards and away from Alzheimer's disease. Nature 430:631-639;

2004. [20]

Zhu, X.; Su, B.; Wang, X.; Smith, M. A.; Perry, G. Causes of oxidative stress in Alzheimer

disease. Cell. Mol. Life Sci. 64:2202-2210; 2007. [21]

Dumont, M.; Beal, M. F. Neuroprotective strategies involving ROS in Alzheimer disease.

Free Radic. Biol. Med. 51:1014-1026; 2011. [22]

Yu, L.; Wang, S.; Chen, X.; Yang, H.; Li, X.; Xu, Y.; Zhu, X. Orientin alleviates cognitive

deficits and oxidative stress in Abeta1-42-induced mouse model of Alzheimer's disease. Life Sci. 121:104-109; 2015. [23]

Tamagno, E.; Guglielmotto, M.; Aragno, M.; Borghi, R.; Autelli, R.; Giliberto, L.; Muraca,

G.; Danni, O.; Zhu, X.; Smith, M. A.; Perry, G.; Jo, D. G.; Mattson, M. P.; Tabaton, M. Oxidative stress 21

activates a positive feedback between the gamma- and beta-secretase cleavages of the beta-amyloid precursor protein. J. Neurochem. 104:683-695; 2008. [24]

Caia, G. L.; Efimova, O. V.; Velayutham, M.; El-Mahdy, M. A.; Abdelghany, T. M.;

Kesselring, E.; Petryakov, S.; Sun, Z.; Samouilov, A.; Zweier, J. L. Organ specific mapping of in vivo redox state in control and cigarette smoke-exposed mice using EPR/NMR co-imaging. J. Magn. Reson. 216:21-27; 2012. [25]

Yamato, M.; Kudo, W.; Shiba, T.; Yamada, K. I.; Watanabe, T.; Utsumi, H. Determination of

reactive oxygen species associated with the degeneration of dopaminergic neurons during dopamine metabolism. Free Radic. Res. 44:249-257; 2010. [26]

Zhu, X.; Zuo, L.; Cardounel, A. J.; Zweier, J. L.; He, G. Characterization of in vivo tissue

redox status, oxygenation, and formation of reactive oxygen species in postischemic myocardium. Antioxidants & redox signaling 9:447-455; 2007. [27]

Yokoyama, H.; Ueda, Y.; Itoh, O.; Ikeda, T.; Noor, J. I.; Ikenoue, T. EPR imaging to estimate

the in vivo intracerebral reducing ability of mature rats after neonatal hypoxic-ischemic brain injury. Magn. Reson. Imaging 22:1305-1309; 2004. [28]

Utsumi, H.; Yamada, K. In vivo electron spin resonance-computed tomography/nitroxyl

probe technique for non-invasive analysis of oxidative injuries. Arch. Biochem. Biophys. 416:1-8; 2003. [29]

Samuni, A.; Goldstein, S.; Russo, A.; Mitchell, J. B.; Krishna, M. C.; Neta, P. Kinetics and

mechanism of hydroxyl radical and OH-adduct radical reactions with nitroxides and with their hydroxylamines. J. Am. Chem. Soc. 124:8719-8724; 2002. [30]

Krishna, M. C.; Russo, A.; Mitchell, J. B.; Goldstein, S.; Dafni, H.; Samuni, A. Do nitroxide 22

antioxidants act as scavengers of O2-. or as SOD mimics? J. Biol. Chem. 271:26026-26031; 1996. [31]

Takeshita, K.; Saito, K.; Ueda, J.; Anzai, K.; Ozawa, T. Kinetic study on ESR signal decay of

nitroxyl radicals, potent redox probes for in vivo ESR spectroscopy, caused by reactive oxygen species. Biochim. Biophys. Acta 1573:156-164; 2002. [32]

Emoto, M. C.; Sato-Akaba, H.; Hirata, H.; Fujii, H. G. Dynamic changes in the distribution

and time course of blood-brain barrier-permeative nitroxides in the mouse head with EPR imaging: visualization of blood flow in a mouse model of ischemia. Free Radic. Biol. Med. 74:222-228; 2014. [33]

Takata, K.; Kitamura, Y.; Tsuchiya, D.; Kawasaki, T.; Taniguchi, T.; Shimohama, S. High

mobility group box protein-1 inhibits microglial Abeta clearance and enhances Abeta neurotoxicity. J. Neurosci. Res. 78:880-891; 2004. [34]

McCord, J. M.; Fridovich, I. Superoxide dismutase. An enzymic function for erythrocuprein

(hemocuprein). J. Biol. Chem. 244:6049-6055; 1969. [35]

Fujii, H.; Sato-Akaba, H.; Kawanishi, K.; Hirata, H. Mapping of redox status in a brain-

disease mouse model by three-dimensional EPR imaging. Magn. Reson. Med. 65:295-303; 2011. [36]

Sato-Akaba, H.; Fujii, H.; Hirata, H. Improvement of temporal resolution for three-

dimensional continuous-wave electron paramagnetic resonance imaging. Rev. Sci. Instrum. 79:123701; 2008. [37]

Prince, M.; Albanese, E.; Guerchet, M.; Prina, M.; Prince, M.; Albanese, E.; Guerchet, M.;

Prina, M. World Alzheimer Report 2014. London: Alzheimer's Disease International; 2014. [38]

Jankowsky, J. L.; Fadale, D. J.; Anderson, J.; Xu, G. M.; Gonzales, V.; Jenkins, N. A.;

Copeland, N. G.; Lee, M. K.; Younkin, L. H.; Wagner, S. L.; Younkin, S. G.; Borchelt, D. R. Mutant 23

presenilins specifically elevate the levels of the 42 residue beta-amyloid peptide in vivo: evidence for augmentation of a 42-specific gamma secretase. Hum. Mol. Genet. 13:159-170; 2004. [39]

Oddo, S.; Caccamo, A.; Shepherd, J. D.; Murphy, M. P.; Golde, T. E.; Kayed, R.; Metherate,

R.; Mattson, M. P.; Akbari, Y.; LaFerla, F. M. Triple-transgenic model of Alzheimer's disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron 39:409-421; 2003. [40]

Hsiao, K.; Chapman, P.; Nilsen, S.; Eckman, C.; Harigaya, Y.; Younkin, S.; Yang, F.; Cole, G.

Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science 274:99102; 1996. [41]

Ruan, L.; Kang, Z.; Pei, G.; Le, Y. Amyloid deposition and inflammation in

APPswe/PS1dE9 mouse model of Alzheimer's disease. Curr Alzheimer Res 6:531-540; 2009. [42]

Zhang, W.; Bai, M.; Xi, Y.; Hao, J.; Zhang, Z.; Su, C.; Lei, G.; Miao, J.; Li, Z. Multiple

inflammatory pathways are involved in the development and progression of cognitive deficits in APPswe/PS1dE9 mice. Neurobiol. Aging 33:2661-2677; 2012. [43]

Luccarini, I.; Grossi, C.; Traini, C.; Fiorentini, A.; Ed Dami, T.; Casamenti, F. Abeta plaque-

associated glial reaction as a determinant of apoptotic neuronal death and cortical gliogenesis: a study in APP mutant mice. Neurosci. Lett. 506:94-99; 2012. [44]

Keller, J. N.; Schmitt, F. A.; Scheff, S. W.; Ding, Q.; Chen, Q.; Butterfield, D. A.;

Markesbery, W. R. Evidence of increased oxidative damage in subjects with mild cognitive impairment. Neurology 64:1152-1156; 2005. [45]

Cutler, R. G.; Kelly, J.; Storie, K.; Pedersen, W. A.; Tammara, A.; Hatanpaa, K.; Troncoso, J.

C.; Mattson, M. P. Involvement of oxidative stress-induced abnormalities in ceramide and cholesterol 24

metabolism in brain aging and Alzheimer's disease. Proc. Natl. Acad. Sci. U. S. A. 101:2070-2075; 2004. [46]

Markesbery, W. R.; Carney, J. M. Oxidative alterations in Alzheimer's disease. Brain Pathol.

9:133-146; 1999. [47]

Kuppusamy, P.; Li, H.; Ilangovan, G.; Cardounel, A. J.; Zweier, J. L.; Yamada, K.; Krishna,

M. C.; Mitchell, J. B. Noninvasive imaging of tumor redox status and its modification by tissue glutathione levels. Cancer Res. 62:307-312; 2002. [48]

Fujii, H. G.; Sato-Akaba, H.; Emoto, M. C.; Itoh, K.; Ishihara, Y.; Hirata, H. Noninvasive

mapping of the redox status in septic mouse by in vivo electron paramagnetic resonance imaging. Magn. Reson. Imaging 31:130-138; 2013. [49]

Utsumi, H.; Yasukawa, K.; Soeda, T.; Yamada, K.; Shigemi, R.; Yao, T.; Tsuneyoshi, M.

Noninvasive mapping of reactive oxygen species by in vivo electron spin resonance spectroscopy in indomethacin-induced gastric ulcers in rats. J. Pharmacol. Exp. Ther. 317:228-235; 2006. [50]

Lee, M. C.; Shoji, H.; Miyazaki, H.; Yoshino, F.; Hori, N.; Toyoda, M.; Ikeda, Y.; Anzai, K.;

Ikota, N.; Ozawa, T. Assessment of oxidative stress in the spontaneously hypertensive rat brain using electron spin resonance (ESR) imaging and in vivo L-Band ESR. Hypertens. Res. 27:485-492; 2004. [51]

Yokoyama, H.; Itoh, O.; Ohya-Nishiguchi, H.; Kamada, H. Reducing ability of the striatum

and cerebral cortex in rats following acute administration of risperidone or haloperidol: an estimation by in vivo electron paramagnetic resonance imaging. Neurochem. Res. 27:243-248; 2002. [52]

Lee, M. C. Assessment of oxidative stress and antioxidant property using electron spin

resonance (ESR) spectroscopy. J. Clin. Biochem. Nutr. 52:1-8; 2013. 25

[53]

Block, M. L. NADPH oxidase as a therapeutic target in Alzheimer's disease. BMC Neurosci.

9 Suppl 2:S8; 2008. [54]

Wilkinson, B. L.; Landreth, G. E. The microglial NADPH oxidase complex as a source of

oxidative stress in Alzheimer's disease. J. Neuroinflammation 3:30; 2006. [55]

Johnstone, M.; Gearing, A. J.; Miller, K. M. A central role for astrocytes in the inflammatory

response to beta-amyloid; chemokines, cytokines and reactive oxygen species are produced. J. Neuroimmunol. 93:182-193; 1999. [56]

Shimohama, S.; Tanino, H.; Kawakami, N.; Okamura, N.; Kodama, H.; Yamaguchi, T.;

Hayakawa, T.; Nunomura, A.; Chiba, S.; Perry, G.; Smith, M. A.; Fujimoto, S. Activation of NADPH oxidase in Alzheimer's disease brains. Biochem. Biophys. Res. Commun. 273:5-9; 2000. [57]

Manczak, M.; Anekonda, T. S.; Henson, E.; Park, B. S.; Quinn, J.; Reddy, P. H. Mitochondria

are a direct site of A beta accumulation in Alzheimer's disease neurons: implications for free radical generation and oxidative damage in disease progression. Hum. Mol. Genet. 15:1437-1449; 2006. [58]

Yao, J.; Irwin, R. W.; Zhao, L.; Nilsen, J.; Hamilton, R. T.; Brinton, R. D. Mitochondrial

bioenergetic deficit precedes Alzheimer's pathology in female mouse model of Alzheimer's disease. Proc. Natl. Acad. Sci. U. S. A. 106:14670-14675; 2009. [59]

Pratico, D.; Uryu, K.; Leight, S.; Trojanoswki, J. Q.; Lee, V. M. Increased lipid peroxidation

precedes amyloid plaque formation in an animal model of Alzheimer amyloidosis. J. Neurosci. 21:4183-4187; 2001. [60]

Resende, R.; Moreira, P. I.; Proenca, T.; Deshpande, A.; Busciglio, J.; Pereira, C.; Oliveira, C.

R. Brain oxidative stress in a triple-transgenic mouse model of Alzheimer disease. Free Radic. Biol. 26

Med. 44:2051-2057; 2008. [61]

Hyun, D. H.; Mughal, M. R.; Yang, H.; Lee, J. H.; Ko, E. J.; Hunt, N. D.; de Cabo, R.;

Mattson, M. P. The plasma membrane redox system is impaired by amyloid beta-peptide and in the hippocampus and cerebral cortex of 3xTgAD mice. Exp. Neurol. 225:423-429; 2010. [62]

Zhang, W.; Bai, M.; Xi, Y.; Hao, J.; Liu, L.; Mao, N.; Su, C.; Miao, J.; Li, Z. Early memory

deficits precede plaque deposition in APPswe/PS1dE9 mice: involvement of oxidative stress and cholinergic dysfunction. Free Radic. Biol. Med. 52:1443-1452; 2012. [63]

Zhang, C.; Rodriguez, C.; Spaulding, J.; Aw, T. Y.; Feng, J. Age-dependent and tissue-related

glutathione redox status in a mouse model of Alzheimer's disease. J. Alzheimers Dis. 28:655-666; 2012. [64]

Ghosh, D.; LeVault, K. R.; Barnett, A. J.; Brewer, G. J. A reversible early oxidized redox

state that precedes macromolecular ROS damage in aging nontransgenic and 3xTg-AD mouse neurons. J. Neurosci. 32:5821-5832; 2012. [65]

Glabe, C. Intracellular mechanisms of amyloid accumulation and pathogenesis in

Alzheimer's disease. J. Mol. Neurosci. 17:137-145; 2001. [66]

Butterfield, D. A.; Reed, T.; Newman, S. F.; Sultana, R. Roles of amyloid beta-peptide-

associated oxidative stress and brain protein modifications in the pathogenesis of Alzheimer's disease and mild cognitive impairment. Free Radic. Biol. Med. 43:658-677; 2007.

Figure Legends

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Figure 1. ROS in the amyloid cascade hypothesis. (1) In the brain of patients with AD, activated β- and γ-secretase catalyze proteolysis of amyloid precursor protein (APP) to produce Aβ monomeric peptides. (2) Aβ monomers are oligomerized and accumulate in extracellular spaces. (3) Aβ oligomers and/or deposits activate microglia and astrocytes. (4) Activated microglia and astrocytes produce and release ROS. (5) ROS released from activated microglia or astrocytes may activate β-secretase and γ-secretase. (6) Activated β-secretase and γ-secretase accelerate the production of Aβ. The vicious spiral from (1) to (6) may increase the production of Aβ and ROS. (7) Consequently, increased Aβ and ROS worsen the pathology of AD.

Figure 2. Immunostaining of coronal sections containing hippocampus and quantitative analysis of amyloid plaque burden, Iba1-positive area and GFAP-positive area in the hemi-brains of APdE9 mice. Triple-staining immunofluorescent images of FSB for amyloid (blue), Iba1 for microglia (red) and GFAP for astrocytes (green) in the hippocampus (A-E), and representative photomicrographs of Aβ immunoreactivity (F-O), Iba1-immunopositive microglia (P-T), and GFAP-immunopositive astrocytes (U-Y) in hemi-brains of APdE9 mice. Aβ (graph 1 (g1)), Iba1 (g2) and GFAP (g3) positive areas in the hippocampus of 4 sections/animal were assessed using Image J analysis software as Aβ burden, microglial and astrocytic activation respectively. Each data are expressed as mean percentage of positively stained area in a high power microscopic field of the hippocampus (areas surrounded by red squares; Aβ in Fig. 2F-J, Iba1 in Fig. 2P-T and GFAP in Fig. 2U-Y). (g1): Mean percentage of Aβpositive area at various age groups were compared by ANOVA [F(4,20) = 19.4567, P < 0.0001] followed by post hoc Tukey-Kramer HSD test: *P < 0.0001 vs. 3 month-old group, #P < 0.0005, ##P < 28

0.0001 vs. 6monthold group, &P < 0.005, &&P = 0.001 vs. 9 month-old group. (g2): Mean percentage of Iba1-positive area were compared by ANOVA [F(4,20) = 20.9219, P < 0.0001] followed by post hoc Tukey-Kramer HSD test : *P < 0.05, **P< 0.0001 vs. 3 month-old group, #P < 0.0005, ##P < 0.0001 vs. 6 month-old group, &P < 0.005 vs. 9 month-old group. (g3): Mean percentage of GFAP-positive area were compared by ANOVA [F(4,20) = 18.2337, P < 0.0001] followed by post hoc Tukey-Kramer HSD test : *P < 0.001, **P < 0.0005, ***P < 0.0001 vs. 3 month-old group, #P = 0.005, ##P < 0.005, ###P < 0.0001 vs. 6 month-old group. Scale bars = 100 µm in A (for A-E); 1 mm in F (for F-Y).

Figure 3. Age-related change in the activity of SOD in the brain of APdE9 mice. The SOD activity of brain tissue homogenates from APdE9 mice was evaluated spectrophotometrically by the reported method [34]. The values were the means  S.D. of four separate experiments. The data were analyzed by ANOVA followed by post hoc Tukey-Kramer HSD test: *P < 0.05, **P < 0.01 vs. 3 month-old group.

Figure 4. Temporal changes in EPR images of redox-sensitive MCP in WT mouse heads and redox map of MCP. (A): Photograph of a mouse head. (B): The chemical structure of MCP. (C): Sliceselective 2D EPR images of a WT mouse head after intravenous injection of MCP. 2D images are shown in the sagittal direction (x-y), the plane of which was chosen at the center of the field of view, at Z = 64. 3D EPR images were obtained at intervals of 30 s under a field scanning of 70 ms and 181 projections. The image matrix was 128 × 128 × 128. 2D slice images at 5, 38, 71 and 104 sec after MCP injection are shown. (D): Redox map of WT mouse head. Two-dimensional spatial mapping of the 29

reduction rate constant (min-1) of MCP was obtained from temporal image data shown in C. (E): T1weighted MR image of the mouse head. (F): Co-registration of redox map shown in D and MRI of the same mouse head shown in E.

Figure 5. Co-registration of redox map and the anatomical MRI in a WT mouse (A) and an APdE9 mouse (B) mice at 9 months of age. ROI in the hippocampus (ROI-1; 6 x 4 pixels) and the midbrain (ROI-2; 6 × 6 pixels) are marked by blue-outlined and yellow-outlined squares, respectively.

Figure 6. Ratio of rate constant in hippocampus / rate constant in midbrain (RRHM) in WT (A) and APdE9 (B) mice at various ages from 3 to 18 months. Data are expressed as mean ± SEM. (A): For WT mice, mean RRHM in different age groups (n = 5 at 3 months of age, n = 8 at 6 months of age, n = 6 at 9 months of age, n = 8 at 12 months of age, n = 6 at 18 months of age) were analyzed by ANOVA [F(4,28) = 0.4995, P = 0.7363]. (B): For APdE9 mice, mean RRHM in different age groups (n = 5 at 3 months of age, n = 8 at 6 months of age, n = 6 at 9 months of age, n = 6 at 12 months of age, n = 5 at 18 months of age) were analyzed by ANOVA [F(4,25) = 1.0854, P = 0.3850].

Figure 7. Comparison of the ratio of rate constant in hippocampus / rate constant in midbrain (RRHM) between APdE9 and age-matched WT mice. (A): 3 months, (B): 6 months, (C): 9 months, (D): 12 months, (E): 18 months of age. Mean RRHM in APdE9 and age-matched WT mice were compared by Student’s t-test: *P < 0.05.

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Highlights ●Histological changes of Aβ and glia in the brain were measured in AD model mice. ●Redox status of AD mouse brains was evaluated noninvasively by in vivo EPR imaging. ●EPR imaging detected redox change earlier than drastic increase in Aβ deposition. ●EPR detected accelerated redox change in AD model mice compared to WT littermates.

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