Early Onset of Learning Deficit in APP⁺-ob/ob Mice.

To assess whether a diabetic condition affects cognitive function, we performed the Morris water maze test. At the early age of 8 weeks, APP⁺-ob/ob mice showed severe learning deficit in the hidden-platform test whereas APP⁺ mice did not exhibit learning impairment (Fig. 2A). We also confirmed that ob/ob mice showed normal learning at this age (Fig. 2A). In the probe test, although APP⁺ and ob/ob mice searched preferentially in the trained quadrant (Fig. 2D) and crossed over the previous platform location at levels comparable to those in WT mice (Fig. 2C), only APP⁺-ob/ob mice showed significantly poor performance (Fig. 2 C and D). In the visible-platform test, there was no significant difference in escape latency among all groups (Fig. 2B), indicating that visual function did not differ among them. Difference in body weight itself could not have affected learning ability and performance in the test, because ob/ob mice (which gained more body weight than APP⁺-ob/ob mice; Fig. 1B) showed normal learning in these tests (Fig. 2 A–D).

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Fig. 2.

Exacerbation of learning and memory deficit in APP⁺-ob/ob mice, without increase in brain Aβ load. (A–D) Morris water maze test at 8 weeks. Escape latencies in hidden-platform (A) and visible-platform (B) test, number of annulus crossings (C), and representative swim paths (D) during the probe test are shown (n = 11–17 per group). **P < 0.01 for APP⁺-ob/ob mice versus other genotypes. “Target” indicates the area where the platform was constantly located in the hidden-platform test. (E and F) Morris water maze test at 12 weeks. Escape latencies in hidden-platform (E) and visible-platform (F) test (n = 11–13). *P < 0.05, **P < 0.01. (G and H) Quantification of brain Aβ40 and Aβ42 concentrations. Both Triton-X–soluble (G) and -insoluble (guanidine extract) (H) Aβ were measured (n = 6–7). (I) Aβ immunostaining (6E10) in brain of APP⁺ and APP⁺-ob/ob mice. There was no detectable amyloid plaque at this early age (12 weeks) in either genotype. (Scale bar, 200 μm.)

At 12 weeks of age, the severe learning deficit in APP⁺-ob/ob mice was sustained, although APP⁺ mice showed mild learning impairment (Fig. 2E). Notably, at this age, APP⁺-ob/ob mice displayed an atypical pattern of performance in the visible-platform test (Fig. 2F), in which they performed poorly only in the early phase of the test (sessions 1 and 2), suggesting emotional disturbance in these mice. This impaired performance of APP⁺-ob/ob mice reflected neither visual dysfunction nor poor swimming ability caused by obesity, because they performed well in the later phase of the test (Fig. 2F), and ob/ob mice showed nearly normal performance throughout the sessions (Fig. 2F). Emotional alterations associated with dementia (so-called behavioral and psychological symptoms of dementia) are also common problems in clinical practice. It is noteworthy that a diabetic condition exacerbated behavior reminiscent of behavioral and psychological symptoms of dementia in the AD mouse model.

To examine whether the impaired cognitive function in APP⁺-ob/ob mice might be related to an increase in Aβ load in the brain, Aβ content in the brain-soluble and -insoluble fractions was quantified. Although the levels of Aβ40 and Aβ42 in APP⁺ and APP⁺-ob/ob mouse brain were significantly higher than those in APP transgene negative mice, no significant difference was observed between APP⁺ and APP⁺-ob/ob mice (Fig. 2 G and H). In this early stage of disease (12 weeks), no obvious amyloid plaque was detected in the brain of either group (Fig. 2I). Therefore, the exacerbation of cognitive impairment in APP⁺-ob/ob mice might not be caused by an increase in brain Aβ burden.

Effects of Diabetic Symptoms on Brain Pathology in APP⁺-ob/ob Mice.

At 12 months of age, the brain weight of APP⁺-ob/ob mice was significantly decreased compared with that in mice with other genotypes (Fig. S2A), suggesting that some kind of degenerative changes had occurred in the brain. At this age, amyloid plaques had not developed in the hippocampus of either APP⁺ or APP⁺-ob/ob mice (Fig. S2B Left), whereas only faint amyloid plaques were seen in the entorhinal cortex (Fig. S2B Right). We quantified brain Aβ levels at this time point and found no significant difference between APP⁺ and APP⁺-ob/ob mice (Fig. S2C).

Many patients with AD present with cerebrovascular Aβ deposition (i.e., cerebral amyloid angiopathy), another pathological marker of this disease (17). Given the high prevalence of vascular complications in DM (18), severe pathological changes in the cerebral vasculature could be detected in APP⁺-ob/ob mice and potentially impact on cognitive function. Thus, we isolated the microvessels from mouse brains (19) and immunostained them with anti-Aβ40 antibody. At 12 months of age, faint amyloid deposits had appeared in blood vessels in the brain of APP⁺ mice (Fig. 3A). In APP⁺-ob/ob mice, dense amyloid deposits were observed in small arteries (Fig. 3A Upper) as well as in arterioles and capillaries (Fig. 3A Lower). Different from the whole-brain Aβ level, the amount of Aβ40 in these isolated microvessels was significantly increased in APP⁺-ob/ob mice compared with APP⁺ mice (Fig. 3B), consistent with the immunohistochemical data.

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Fig. 3.

Increased vascular amyloid deposition and inflammation in APP⁺-ob/ob mouse brain. (A) Immunohistochemical detection of Aβ40 deposition in isolated brain microvessels of 12-month-old mice. Brain microvessels were also stained for anti–α-smooth muscle actin (a vascular smooth muscle cell marker) and CD31 (endothelial cell marker). (Scale bar, 100 μm.) (B) Quantification of Aβ40 level in isolated brain microvessels by ELISA (n = 3 per group). **P < 0.01. (C) Cerebrovascular amyloid deposition in APP⁺-ob/ob mice was age-dependent and appeared after 6 months of age. (Scale bar, 100 μm.) (D) Immunohistochemical staining for RAGE in brain sections of young (3-month-old) mice. Strong immunoreactivity was detected in brain vessels (cerebral cortex) of APP⁺-ob/ob mice. (Scale bar, 30 μm.) (E) Brain section of 3-month-old APP⁺-ob/ob mouse immunolabeled for RAGE and CD31 and counterstained with DAPI. Colocalization of RAGE and CD31 in cerebral vessel is denoted by arrow and magnified (Inset). (Scale bars, 100 μm; 10 μm for Inset.) (F) IL-6–positive microvessels (cerebral cortex) in 3-month-old mouse (Left) and quantitative image analysis of IL-6–positive vessels (percent occupied; Right, n = 3). (Scale bar, 100 μm.) *P < 0.05 for APP⁺-ob/ob mice versus other genotypes.

This cerebrovascular amyloid deposition was age-dependent and appeared after 6 months of age in APP⁺-ob/ob mice (Fig. 3C). As recent studies demonstrated that RAGE, which is well known to play an important role in the pathogenesis of diabetes (12), bound to soluble Aβ and mediated pathophysiologically relevant cellular responses in AD (13, 14), we focused on RAGE in the cerebral vasculature. At 3 months of age, even before the development of amyloid deposition in the cerebral vasculature, RAGE immunoreactivity was markedly increased in blood vessels of the APP⁺-ob/ob mouse brain (Fig. 3D). Up-regulation of RAGE was relatively limited to the blood vessels labeled for CD31 (Fig. 3E), whereas no obvious signals were detected in neuronal cells (pyramidal cell layer of hippocampus, Fig. 3E). As the activation of RAGE induced a potent inflammatory response (13, 14), we examined the induction of inflammatory markers in the brain. Using immunostaining, a significant increase in IL-6 (Fig. 3F) and TNF-α (Fig. S3) was observed in the brain microvessels of APP⁺-ob/ob mice compared with other genotypes.

To assess reactive astrogliosis, we quantified the immunoreactivity of GFAP in the hippocampal area. Although APP⁺ mice showed increased GFAP burden compared with WT mice, APP⁺-ob/ob mice exhibited more marked reactive astrogliosis (Fig. S4A). Furthermore, we quantified choline acetyltransferase (ChAT)–immunoreactive fibers (i.e., cholinergic fibers) in the hippocampus. Aged APP⁺-ob/ob mice exhibited a significant decrease in cholinergic nerve fibers compared with other genotypes (Fig. S4B).

To analyze the underlying mechanisms of these degenerative pathological changes, we investigated neuronal insulin signaling. Recently, it has been shown that insulin signaling plays an important role in synapse formation and regeneration of neurons in the brain (20). First, we quantified the amount of brain insulin by ELISA and found that brain insulin level was markedly decreased in APP⁺-ob/ob mice compared with other genotypes (Fig. 4A). We also assessed the insulin sensitivity in brain neurons using an in vivo insulin stimulation assay (21). Although insulin stimulated formation of phosphatidylinositol 3,4,5-triphosphate (PIP3)—a major downstream marker of insulin signaling—in the arcuate nucleus of WT mice, the number of PIP3-positive cells was significantly decreased in APP⁺-ob/ob mice compared with APP⁺ mice and ob/ob mice (Fig. 4B). We also examined insulin stimulated Akt phosphorylation (Ser473) in the brain (hypothalamus), and found that Akt phosphorylation was significantly suppressed in APP⁺-ob/ob mice compared with other genotypes (Fig. 4C), suggesting that brain insulin signaling was disturbed in APP⁺-ob/ob mice.

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Fig. 4.

Alteration in brain insulin signaling in APP⁺-ob/ob mice. (A) Quantification of brain insulin concentration by ELISA (n = 5–9). (B) Insulin sensitivity in brain neurons. Insulin-stimulated (5.0 U/kg, i.p.) PIP3 formation in arcuate cells was assessed by immunostaining with anti-PIP3 antibody (Left). (Scale bar, 50 μm.) PIP3-positive cell number in arcuate nucleus of insulin-injected mice is shown in the graph (Right, n = 3). (C) Immunoblot analysis of insulin-stimulated phosphorylation of Akt (pAkt) and total Akt in the brain (Left) and densitometric quantification of them (Right; n = 3–4). *P < 0.05 for APP⁺-ob/ob mice versus other genotypes. 3V, third ventricle; Arc, arcuate nucleus.

Metabolic Features of APP⁺-NSY Mice.

To further investigate the possible effect of Alzheimer-like pathology on diabetic phenotypes, we created another fusion mouse model between APP23 and diabetic NSY mice. We successfully generated such fusion mouse lines and selected three lines with mutually different brain Aβ levels (lines 16 and 17 and congenic mice; Fig. 5 A and B). All these fusion APP⁺-NSY mice showed marked glucose intolerance in GTT compared with nondiabetic APP23 mice at 12 weeks of age (Fig. S5C). Although the APP⁺-NSY mice showed mild obesity compared with the APP23 mice, their body weights were slightly, but significantly, decreased compared with those of the NSY mice, especially in the lines that have relatively high brain Aβ levels (line 16 and congenic mice) (Fig. S5A). There was no significant difference in food intake among these groups (Fig. S5B). To exclude the possible confounding effect of reduced body weights in APP⁺-NSY mice on the results of GTT, we used body weight–matched mice groups (Fig. S5D). In these groups, APP⁺-NSY (congenic) mice showed significantly severe glucose intolerance compared with NSY mice (Fig. 5C). Furthermore, we examined the correlation between the brain Aβ levels and the severity of glucose intolerance (Fig. 5D). We compared areas under the curve (AUCs) of glucose levels in GTT and levels of brain Aβ40 in the body weight–matched groups and observed a significant positive correlation between these parameters (Fig. 5D). In addition, we also found that the APP⁺-NSY (congenic) mice exhibited severe insulin resistance compared with the NSY mice in insulin tolerance test (ITT) (Fig. 5E). These findings also support the possibility that amyloid pathology could adversely affect diabetic symptoms.

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Fig. 5.

Metabolic features of APP⁺-NSY mice. (A) Appearance of APP⁺-NSY mice (mice 16 and 17 and congenic mice) at 12 weeks. (B) Brain Aβ levels of each APP⁺-NSY mice lines (12-week-old age). (C) GTT in body weight–matched mice groups. Body weight–matched NSY and APP⁺-NSY mice were used for the experiment (n = 3–5). *P < 0.05 for APP⁺-NSY congenic mice compared with NSY mice. (D) Significant positive correlation between brain Aβ levels and glucose intolerance (AUC during GTT) in body weight–matched mice groups. P < 0.01, Spearman rank test. (E) Blood glucose levels during ITT (1.0 U/kg, 12 weeks, n = 4–7). *P < 0.05 for APP⁺-NSY congenic mice compared with NSY mice. Cong., APP⁺-NSY congenic mice.

Animal Experiments.

All animal experiments were performed in compliance with the Guidelines for the Care and Use of Laboratory Animals of the Osaka University School of Medicine. Animals were maintained at room temperature (25 ± 2 °C) under a standard 12-h/12-h light-dark cycle, with free access to water and ND or HF diet. See SI Materials and Methods for details of measurement of food intake, water consumption, and urine volume.

Metabolic Measurements.

Blood glucose and plasma insulin determinations were performed in fasted (for 16 h) and randomly fed states. See SI Materials and Methods for details of blood glucose and plasma insulin measurement, GTT, and ITT. Metabolic parameters were measured at approximately the same time (early light phase).

Western Blotting.

Tissue samples were lysed and processed for immunoblot analysis as described in SI Materials and Methods.

Behavioral Analysis.

Hippocampus-dependent learning and memory function were investigated with the Morris water maze test, as detailed in SI Materials and Methods. To assess basal activity of animals, the open field test was carried out (SI Materials and Methods).

Measurement of Aβ.

Fresh-frozen mouse brain was serially homogenized into detergent-soluble and guanidine HCl-soluble fractions, as detailed in SI Materials and Methods. The amounts of Aβ X-40 and Aβ X-42 in each fraction were determined by BNT-77/BA-27 and BNT-77/BC-05 sandwich ELISA (Wako Pure Chemical), respectively, according to the manufacturer's instructions.

Immunohistochemical Staining.

Mouse brains were paraformaldehyde fixed, paraffin-embedded, and cut into sections 10 μm thick. For immunodetection of amyloid plaque, we used anti-Aβ (6E10) antibody coupled with secondary horseradish peroxidase-conjugated antibody (Vectastain ABC-kit; Vector Laboratories) and diaminobenzidine reaction. We also stained the sections with rabbit anti-GFAP antibody (1:80, G9269; Sigma), goat anti-ChAT polyclonal antibody (1:100, AB144P; Chemicon), rabbit anti-RAGE polyclonal antibody (1:100, ab3611; Abcam), rat anti-CD31 (PECAM-1) monoclonal antibody (1:50; BD Pharmingen), goat anti–IL-6 polyclonal antibody (1:100, sc1265; Santa Cruz Biotechnology), and goat anti–TNF-α polyclonal antibody (1:100, sc1351; Santa Cruz Biotechnology), and visualized immunoreactions using a fluorescent secondary antibody or horseradish peroxidase–conjugated antibody with diaminobenzidine reaction.

Image Analysis.

A detailed description of image analysis is provided in the SI Materials and Methods.

Measurement of Brain Insulin Level.

The amount of insulin was determined by ELISA (Morinaga Seikagaku) in a fasted state. See SI Materials and Methods for details.

In Vivo Insulin Stimulation Assay.

We assessed insulin sensitivity of each organ (muscle, liver, and brain) using an in vivo insulin stimulation assay as described previously (21, 34). See also SI Materials and Methods for details.

Isolation of Brain Microvessels and Immunohistochemical Staining.

Brain microvessels were isolated and characterized as described previously (19). A detailed description of these techniques is also provided in SI Materials and Methods.

We thank M. Staufenbiel (Novartis Institutes for BioMedical Research, Basel, Switzerland) for providing APP23 mice and Y. Ueda (Molecular Endocrinology, Graduate School of Medicine, Osaka University, Osaka, Japan) and T. Fujisawa (Department of Geriatric Medicine, Osaka University, Osaka, Japan) for helpful discussion. This work was supported in part by grants-in-aid from Japan Promotion of Science; the Japanese Ministry of Education, Culture, Sports, Science and Technology (R.M., N.S.); and the Japan Science and Technology Agency (N.S.).