Brain Advance Access originally published online on November 16, 2008
Brain 2008 131(12):3311-3334; doi:10.1093/brain/awn288
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Intranasal insulin prevents cognitive decline, cerebral atrophy and white matter changes in murine type I diabetic encephalopathy
1Department of Clinical Neurosciences and the Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada, 2Alzheimer's Research Center at Regions Hospital, HealthPartners Research Foundation, St. Paul, MN, USA and 3Department of Pharmacology and Therapeutics, Division of Neurodegenerative Disorders, University of Manitoba, St. Boniface Hospital Research Centre, Winnipeg, Manitoba, Canada
Correspondence to: Dr C. Toth, University of Calgary, Department of Clinical Neurosciences, Room 155, 3330 Hospital Drive, N.W., Calgary, Alberta, Canada T2N 4N1 E-mail: corytoth{at}shaw.ca
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Insulin deficiency in type I diabetes may lead to cognitive impairment, cerebral atrophy and white matter abnormalities. We studied the impact of a novel delivery system using intranasal insulin (I-I) in a mouse model of type I diabetes (streptozotocin-induced) for direct targeting of pathological and cognitive deficits while avoiding potential adverse systemic effects. Daily I-I, subcutaneous insulin (S-I) or placebo in separate cohorts of diabetic and non-diabetic CD1 mice were delivered over 8 months of life. Radio-labelled insulin delivery revealed that I-I delivered more rapid and substantial insulin levels within the cerebrum with less systemic insulin detection when compared with S-I. I-I delivery slowed development of cognitive decline within weekly cognitive/behavioural testing, ameliorated monthly magnetic resonance imaging abnormalities, prevented quantitative morphological abnormalities in cerebrum, improved mouse mortality and reversed diabetes-mediated declines in mRNA and protein for phosphoinositide 3-kinase (PI3K)/Akt and for protein levels of the transcription factors cyclic AMP response element binding protein (CREB) and glycogen synthase kinase 3β (GSK-3β) within different cerebral regions. Although the murine diabetic brain was not subject to cellular loss, a diabetes-mediated loss of protein and mRNA for the synaptic elements synaptophysin and choline acetyltransferase was prevented with I-I delivery. As a mechanism of delivery, I-I accesses the brain readily and slows the development of diabetes-induced brain changes as compared to S-I delivery. This therapy and delivery mode, available in humans, may be of clinical utility for the prevention of pathological changes in the diabetic human brain.
Key Words: diabetes; insulin; leukoencephalopathy; white matter abnormalities; brain atrophy; cognitive decline
Abbreviations: APP, amyloid precursor protein; CSF, cerebrospinal fluid; DW, diffusion-weighted; EMSA, electrophoretic mobility shift assay; IGF-1, insulin-like growth factor; IR, insulin receptor; NGF, nerve growth factor; SNMTS, spatial non-matching-to-sample; WMAs, white matter abnormalities
Received May 27, 2008. Revised October 3, 2008. Accepted October 8, 2008.
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Introduction |
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Diabetes has been associated with cognitive dysfunction, an elevated risk of dementia, cerebral atrophy and presence of heightened white matter abnormalities (WMAs). Diabetes-associated cognitive dysfunction, first described nearly a century ago (Miles and Root, 1922
), occurs in both type of diabetes. In type I diabetes, impaired learning, memory, problem solving skills, and intellectual development have been described (Ryan, 1988; Ryan et al., 1993; Ryan and Williams, 1993; McCarthy et al., 2002; Schoenle et al., 2002). For patients with type I diabetes, the greatest impact of diabetes upon brain structure and function seems to occur at the extremes of age, with little observable effect during the middle adult years (Wessels et al., 2007, 2008; Biessels et al., 2008; Kloppenborg et al., 2008). Also, cognitive dysfunction does not appear to relate to hypoglycaemic episodes in diabetes (Kramer et al., 1998; Schoenle et al., 2002; Jacobson et al., 2007). Similar cognitive deficits occur in type II diabetic adult patients, with impaired performance on abstract reasoning and complex psychomotor functioning (Reaven et al., 1990; Strachan et al., 1997; Ryan and Geckle, 2000). Diabetes-mediated cognitive changes seem to occur at the two extremes of life: either in childhood (Northam et al., 2001; Schoenle et al., 2002; Fox et al., 2003) or during later stages of life (Stewart and Liolitsa, 1999; Awad et al., 2004; van Harten et al., 2006) when neurodegenerative processes may initiate (Biessels et al., 2008). There are less clear indications that diabetes impacts upon cognitive functioning in middle-age adults (Stewart and Liolitsa, 1999; Awad et al., 2004; Jacobson et al., 2007; Weinger et al., 2008).
In animal models of diabetes, cognitive dysfunction has been demonstrated by impaired performances in the Morris water maze by streptozotocin (STZ)-induced diabetic rats (Biessels et al., 1996, 1998). Both pre- and post-synaptic deficits have been associated with impaired long-term potentiation in the diabetic hippocampus (Biessels et al., 1996; Kamal et al., 2006). Short-term replacement of insulin in STZ-treated rats from the onset of diabetes prevents cognitive decline and protects against hippocampal potentiation deficits, but cannot reverse these electrophysiological changes (Biessels et al., 1998). Long-term protection against development of diabetic encephalopathy via locally delivered insulin has not yet been attempted.
Structural defects within the diabetes-exposed brain include cerebral atrophy identified with neuroimaging techniques (Schmidt et al., 2004; Manschot et al., 2006; Musen et al., 2006; Ikram et al., 2008; Last et al., 2007). Cerebral atrophy, possibly acting in concert with WMA, is associated with cognitive decline (Whitman et al., 2001; Manschot et al., 2006). Diabetes is a risk factor for WMA presence in some studies (Pantoni and Garcia, 1997; Murray et al., 2005; Akisaki et al., 2006; Manschot et al., 2006; Musen et al., 2006; van Harten et al., 2007), but not in others (Schmidt et al., 2004). By themselves, WMAs in humans are a risk factor for stroke (Knopman et al., 2001), cognitive deficits (Pantoni et al., 2007) and abnormalities in gait associated with falling (Schwartz et al., 2008). The presence of cerebral atrophy or WMA has been linked to cognitive dysfunction in a number of human studies (Manschot et al., 2006; Verdelho et al., 2007). Rodent models of diabetes have also demonstrated cerebral atrophy (Lupien et al., 2006; Toth et al., 2006) and WMAs (Toth et al., 2006) due to long-term diabetes. Such pathological changes have been associated with cognitive decline over time in mouse models of diabetes (Toth et al., 2006) and in diabetic rats where hippocampal electrophysiological changes were present (Biessels et al., 1996; Kamal et al., 2000). One pathogenic factor related to presence of brain atrophy and WMA in experimental diabetes is the presence of the receptor for advanced glycation end products (RAGE) (Toth et al., 2006). However, another important factor may be relative impaired insulin levels and activity in the brain exposed to diabetes (Li et al., 2005; Haan, 2006), as described in the human Alzheimer's disease brain (Craft et al., 1998; Hoyer, 2004). Insulin receptors (IRs) are present at central neurons, synapses, and upon glia (Adamo et al., 1989; Unger et al., 1989; Wickelgren, 1998; Abbott et al., 1999; Zhao et al., 2004a); therefore, it is assumed that insulin and its signalling play an important role in neuronal, glial, and overall cognitive and memory functioning. Insulin replacement within the central nervous system may prevent or even reverse such diabetes-associated changes, although its systemic delivery is complicated by hypoglycaemia. Also, potentially impaired function of the blood–brain barrier may prevent insulin transport from achieving sufficient cerebral levels (Cohen, 1993; Mooradian, 1997; Hattori et al., 2000; Kaiyala et al., 2000). An alternative method of delivering insulin to the brain could be instrumental in preventing diabetes-accelerated neurodegeneration.
Intranasal administration permits insulin or similar peptides to bypass the periphery and the blood–brain barrier (Dhanda et al., 2005), reaching the brain and entering the cerebrospinal fluid (CSF) within minutes. Proteins with size of up to 20 kDa, including insulin, insulin-like growth factor (IGF)-1 and nerve growth factor (NGF), have been successfully delivered to the brain using this method (Chen et al., 1998; Liu et al., 2004; Ross et al., 2004; Thorne et al., 2004; Reger et al., 2006, 2008; Vig et al., 2006). Transport of molecules delivered intranasally occurs through extracellular bulk flow transport along olfactory and trigeminal perivascular channels, as well as possibly through axonal transport pathways (Benedict et al., 2004; Thorne et al., 2004; Reger et al., 2006). This technique permits targeted delivery to the brain to assess the direct effect of insulin upon its receptors without significant changes in plasma insulin or glycaemic levels (Patti et al., 1995; White and Yenush, 1998; Leinninger et al., 2004; Reger et al., 2006, 2008; Yu et al., 2006).
We hypothesized that long-term replacement of insulin within the experimental type I diabetic mouse brain could slow or prevent such changes. Insulin's ligation to highly expressed IR in brain regions including the hippocampus and upon synapses (Abbott et al., 1999), may promote learning and memory (Zhao et al., 2004a). We used daily intranasal delivery of insulin over a life span while performing behavioural and neuroimaging measures to monitor progression. These studies were also performed to assist in delineation of insulin's trophic and anti-hyperglycaemic effects upon development of diabetic encephalopathy. Given the absence of neuronal loss in prior studies of the diabetic murine brain (Toth et al., 2006), we also examined for evidence of synaptic loss, as well as the previously detected myelin loss. We postulated that intranasal insulin delivery would sustain the diabetic nervous system, potentially limiting cognitive decline, brain atrophy and WMAs, while limiting serious systemic side-effects that could occur with systemic insulin delivery.
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Materials and Methods |
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Animals
We studied a total of 484 male Swiss Webster wild-type (wt) mice with initial weight of 20–30 g, in strict pathogen-free plastic sawdust-covered cages with a normal light–dark cycle and free access to mouse chow and water. All protocols were reviewed and approved by the University of Calgary Animal Care Committee using the Canadian Council of Animal Care guidelines. Mice were anaesthetized with pentobarbital (60 mg/kg) prior to all procedures. At the age of 1 month, 304 mice were injected with streptozotocin (Sigma, St. Louis, MO) intraperitoneally with once daily doses with each of 60 mg/kg, 50 mg/kg and then 40 mg/kg over three consecutive days, while the remaining 180 mice were injected with volume-equated placebo carrier (sodium citrate) for 3 consecutive days. One hundred and forty-four mice injected with STZ and 80 mice injected with carrier were held aside for morphological studies to be performed at 1, 3 and 5 months after injections; the remaining mice were followed for the entire length of the study (8 months of diabetes or equivalent for carrier-injected mice) as mortality permitted. Monthly weights were obtained and monthly whole-blood glucose measurements were performed using the tail vein and a blood glucometer, (OneTouch Ultra Meter, LifeScan Canada, Burnaby, BC, Canada) with hyperglycaemia verified 1 week after STZ injection; a fasting whole-blood glucose level of
16 mmol/l (normal 5–8 mmol/l) was our criterion for experimental diabetes. In all cases, those mice that did not develop diabetes as defined above following STZ injections were excluded from further assessment. Animals were inspected twice daily, and examined for signs of depressed level of consciousness, ataxia or general malaise. When such signs were identified, whole-blood glucose testing was performed, with a measurement of < 3.5 mmol/l defined to represent hypoglycaemia. No intervention was performed at any time with regards to additional insulin, glucose or fluid delivery. In situations where the mouse was obviously ill, euthanasia was performed. In circumstances where severe hyperglycaemia was found (>33 mmol/l) in an ill mouse, euthanasia was again performed. We studied cohorts with a maximum of eight mice in each group initially due to resource limitations. After the initial cohorts containing eight mice each were studied, a second cohort was used to obtain additional mouse data for mouse cohorts with higher levels of mortality. For any animal that experienced mortality after the 20-week point of the cognitive studies, their data were carried through using the last obtainable data point.
Intranasal insulin or saline delivery
125I-labelled I-I and subcutaneous insulin (S-I) administration were performed at the University of Minnesota for determination of targeting of insulin delivery methods. This procedure was approved by the institutional animal care and use committee at Regions Hospital. Prior to experimentation, 21 non-diabetic animals were acclimated to handling for awake intranasal delivery over 
2 weeks. 125I-labelled I-I was provided to 12 Swiss Webster mice (male, 6–8 weeks, Charles River) and 125I-labelled subcutaneous insulin S-I was provided to nine mice under pentobarbital anaesthesia (60 mg/kg). Insulin (Humulin R, Eli Lilly, Toronto, Canada) with an initial concentration of 100 U/ml or 4033.98 mg/ml was dissolved in PBS and custom-labelled with 125I (GE Healthcare, Piscataway, NJ, USA). Synthesized radiolabelled insulin solution contained 344.3 µCi/ug. 125I-labelled I-I delivery was performed in a fume hood behind a lead-impregnated shield, with anaesthetized mice placed supine. A mixture of 125I insulin (15.8 µCr) and unlabeled insulin (3.3 µg) were administered as I-I or S-I. 125I I-I was delivered over alternating nares as eight 3-µl drops with an Eppendorf pipetter every 2 min, for a total volume of 24 µl. This schedule of delivery has been modified from a previously used method in rats to quantify radiolabelled delivery of molecules within the Frey laboratory (Thorne et al., 2004). For subcutaneous delivery, 125I S-I was delivered with a single subcutaneous injection of 24 µl in a fume hood behind a lead-impregnated shield. Each desired dose contained a calculated radioactive dose of 30 µCi.
At each of 1, 2 and 6 h after initiating 125I I-I or S-I delivery, cardiocentesis was performed for blood extraction, followed by performance of euthanasia via transcardial perfusion using 120 ml of 4% paraformaldehyde while the mouse was maintained under anaesthesia. To quantify 125I distribution, blood, urine, lymphatic and visceral organ structures, as well as portions of the central and peripheral nervous systems were harvested. Gamma signal was recorded for each body region with autoradiographic imaging using a phosphor screen. Concentrations of 125I insulin were calculated based upon the gamma counting data, tissue weight, specific activity of the insulin administered and standards measured. Results were studied for penetration into peripheral nervous system tissues (reported elsewhere) and central nervous system tissues.
Daily I-I (Humulin R, Eli Lilly, Toronto, ON) or intranasal saline (I-S) was administered to both diabetic and non-diabetic male Swiss Webster mice over 8 months of diabetes. A total of 24 µl containing either a total of 0.87 U of insulin or 0.9% saline only was provided as four 6-µl drops by an Eppendorf pipetter over alternating nares every minute while each mouse was held in supine position with neck in extension. Daily S-I (0.87 U/d, Humulin R, Eli Lilly, Toronto, ON) and subcutaneous saline (S-S) were also administered to either diabetic or non-diabetic male Swiss Webster mice. All therapies began immediately after confirmation of presence of diabetes for each cohort. In the first week, daily glucometer testing was performed for all mice, followed by once-a-month testing. In this work, mice with diabetes were indicated with a ‘D’, while mice without diabetes (control mice) are indicated with a ‘C’. Delivery of subcutaneous saline is indicated as ‘S-S’, subcutaneous insulin as ‘S-I’, intranasal saline as ‘I-S’ and intranasal insulin as ‘I-I’.
We attempted to use other control groups, but their utility was limited in each case. First, we attempted to use subcutaneous insulin via a sliding scale approach in six diabetic mice in order to maintain normal or mildly high glycaemia levels. This approach required daily checks of whole-blood glucose using a tail vein; over the span of 1 month, all of the six diabetic mice developed infection over the tail, leading to amputation in three mice (50%) and was probable cause of death in two mice (33%). During the course of an 8-month-long study, the morbidity associated with this procedure would be unacceptable and confounding. We also attempted to maintain a protected venous catheter in the tail vein for obtaining whole-blood glucose, but this was associated with auto-removal of the catheter and failure at re-insertions due to fibrosis of tail tissues. We also studied six diabetic mice receiving a half dose of the desired I-I dose (0.43 U/d) over 1 month. One mouse (17%) died of confirmed hypoglycaemia, with the other five mice surprisingly had no statistical difference in glycaemic levels when compared to a complementary group of six diabetic mice receiving subcutaneous placebo injections. Therefore, we selected the S-I dose to be equivalent to the I-I dose for the cohorts studied.
Behavioural testing
A minimum of eight mice in each cohort [32 diabetic (D I-I, D I-S, D S-I and D S-S) and 32 control mice (C I-I, C I-S, C S-I and C S-S)] had cognitive behavioural testing performed once weekly for evaluation of procedural, visuospatial and recognition memory. All behavioural tests were conducted under regular light between 09:00 and 15:00 h after fasting overnight from 19:00 onwards. Every mouse was trained in each test paradigm for 3 weeks before initiation of test recording and prior to diabetes initiation, beginning after 2 weeks of diabetes at 1.5 months of age. Behavioural equipment was maintained in the identical position and climate on each occasion and was recorded by the same observers in order to ensure stability of distant navigational cues provided by objects around the testing. Testing always occurred in the order of Holeboard test, Radial arm test, Object Recognition test (each performed while fasting) followed by feeding and then the Morris Water-Maze test 1 h later. While the Holeboard and Radial Arm tests evaluate spatial information processing and memory, the Morris Water Maze also evaluates procedural memory and aversive motivation. In contrast, the Object Recognition test evaluates novelty seeking and exploratory behaviour. Each mouse performed one trial of each test per week. Due to the possibility of motor limitations confounding the results of cognitive testing, concurrent testing of linear swim speed and linear running speed were performed monthly; once measurable differences in motor function occurred between interventional groups in swim or run speed, cognitive testing was discontinued.
The Radial Arm test maze consists of a central platform (35 cm in diameter) and eight arms (each 76 cm long and 12 cm wide) constructed of black plastic projecting radially from the platform with adjacent arms separated by 45° (Schwabe et al., 2006). A food reward (Cheerio) is placed in the same arm each occasion at 180° from the starting point of the mouse placed in the middle of the central platform. A mouse was recorded as entering an arm when it passed the midpoint of the arm in a centrifugal fashion. Each trial ended when the reward was collected or when 720 s expired. Variables recorded during each test were latency for collecting reward and the number of errors made, defined as a re-entry into an arm previously entered, classified as a reference memory error.
The Holeboard test was modified from a previous reported design (File and Wardill, 1975), and was composed of a rectangular open field (60 x 90 cm) made of opaque white acrylic surrounded by opaque walls 60 cm high. Eight holes (2.5 cm diameter) were placed in two lines of four, equidistant from each other and from the walls. Each mouse was started in the same corner while the food reward (Cheerio) was placed in the same hole (second hole in the far row, kitty-corner from the starting point). The latency to collect the reward and the number of times the mouse placed its head in each individual hole was recorded, with errors defined as repeat visit of a previously visited hole, classified as a reference memory error.
The Object Recognition task was performed in an open wooden box (60 x 60 x 60 cm) with unique objects to be discriminated constructed from children's blocks. On the day of the test, at the first 2-min sample trial (T1), two identical objects (termed as sample objects) were presented in two corners of the box. Then, in the second 2-min choice trial (T2) performed 30 min later, one of the objects presented in T1 was replaced by a new object. Objects were cleaned between trials and between mouse to prevent the possibility of scent traces forming an olfactory cue. The time (in seconds) as well as the number of visits taken by mice in exploring objects in the two trials were recorded, with exploration considered as directing the nose to the object at a distance 
2 m and/or touching it with the nose. This paradigm has been termed delayed ‘spatial non-matching-to-sample’ (SNMTS) testing (Rothblat and Kromer, 1991).
A mouse-adapted Morris water-maze task (Morris, 1984; Crawley, 2000; Whishaw and Kolb, 2005) was performed after feeding and used a solid-coloured circular pool 88 cm in diameter and 20 cm in height filled with water at 25°C. The position of the 10 cm radius hidden platform remained fixed for all testing over the entire study period, and each mouse was placed at an identical starting position opposite the hidden platform. Animals were left to swim until either they located the platform, climbing upon it and staying for at least 2 s, or when 300 s elapsed. Post-testing, mice were placed under a heating lamp to warm. Variables recorded during each test were latency to reach the platform (escape latency) and the fraction of time spent within the hemisphere of the pool containing the platform (thigmotaxis).
Magnetic resonance imaging
At each month of diabetes, four mice from each cohort [16 diabetic (D I-I, D I-S, D S-I and D S-S) and 16 control mice (C I-I, C I-S, C S-I and C S-S)] underwent magnetic resonance (MR) scanning at the Experimental Imaging Centre at the University of Calgary. MR images were obtained in animals anaesthetized by mask with isoflurane using a quadrature volume coil and a Bruker 9.4 Tesla MR imaging system. Respiration and temperature were monitored and inner core temperature was maintained to be within 36–37°C with a heated air feedback system. The head was restrained using ear pins. Three different sets of MR scans were performed using sequences that acquired T1-weighted images, diffusion-weighted (DW) images for calculating an apparent diffusion coefficient of water (ADC) map and T2-weighted images for determining T2 maps within a total of 24 slices through the cerebrum. T1-weighted images were acquired using a spin echo sequence with a repetition time (TR) of 500 ms and an echo time (TE) of 8 ms. Diffusion-weighted (DW) images were acquired using a spin echo sequence with TR/TE = 1200/49 ms and b values of 46 and 767 s/mm2, respectively. T2 maps were obtained from multi-spin-echo images at TR = 1200 ms, 12 echoes and TE = 12.5 ms. The field of view was 2 x 2 cm, with an acquisition matrix of 256 x 256 and a slice thickness of 0.75 mm. MR images of brain were analysed using locally available software (Marevisi, IBD) by an observer blinded to the treatment group. Calculation of T2 values, perfusion values, and ADC values within brain regions of interest were performed bilaterally for each of the control and diabetic animals. Apparent visualized abnormalities in T1- and T2-weighted images were also recorded for each animal. In addition, MR images were used to calculate brain widths at pre-determined anatomical landmarks as well as to measure overall brain volume. Volumetric brain measurements were calculated as a summation of cross-sectional areas for each slice multiplied by the thickness of the MR slices.
Tissue harvesting
Prior to sacrifice after 1, 3, 5, 7 or 9 months of diabetes, animal weights and blood glucoses were determined. A total of 0.5 ml of whole intracardiac blood was obtained for glycated haemoglobin measurements to be performed with affinity chromatography (Procedure 422; Sigma Diagnostics). Euthanasia for animals was performed with an overdose of pentobarbital intraperitoneally, followed by harvesting of brain tissues, placement of half of all brain tissues in 2% formaldehyde and embedding in paraffin. For these specimens, 10 µm sections were cut for morphological and immunohistochemical studies. The other half of mouse brain tissues were placed in Trizol reagent (Life Technologies Inc., Rockville MD, USA) or liquid nitrogen for quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blot studies respectively with storage at –80°C for a maximum of 1 month.
Brain sectioning and staining
Degrees of myelination were determined by staining paraffin brain sections for either Luxol Fast Blue (LFB) or myelin basic protein (MBP) (1:100, Stemcell Technologies Inc., Vancouver). For LFB staining, slides were de-waxed and stained in LFB overnight at 37°C followed by alcohol washing and subsequent differentiation of the stain with 0.05% lithium carbonate and then alcohol. Slides used for MBP detection were incubated in methanol for 20 min and washed in phosphate-buffered solution (PBS), then incubated in Triton-X for 30 min before blocking with 10% normal bovine serum for 1 h. Following PBS washes, slides were incubated with mouse anti-MBP overnight followed by incubation with the secondary antibody (bovine anti-mouse IgG Cy3, 1:100 Zymed Inc., San Francisco) for 1 h.
Brain sections stained for LFB were chosen to reflect pre-defined regions of interest (Appendix 1), representing those regions known to be abnormal within diabetic human brains, as well as cortical and subcortical regions important in memory and cognition (Munoz et al., 1993; de Groot et al., 2000; Tullberg et al., 2004; Toth et al., 2006). Assessment of MBP labelling was performed using Image Pro Plus software (Image Pro Plus 5.0, MediaCybernetics, Silver Spring, MD) in order to measure the optical density or degree of immunofluorescence within each brain region of interest. LFB staining was assessed using optical density measurements with Photoshop software for quantification of blue. All assessments of brain sections were performed by an investigator blinded to the experimental conditions.
Additional immunohistochemistry was performed to identify neurons with microtubule-associated protein (MAP)-2, and to identify oligodendrocytes with PDGFR
immunohistochemistry. Background staining was blocked using 1% bovine serum albumin for 1 h, and then slides were stained with monoclonal mouse anti-MAP-2 (1:100, Abcam, Cambridge, MA) or PDGFR (1:100, Abcam, Cambridge, MA) for neuron and oligodendrocyte detection, respectively. The secondary antibody used was anti-mouse IgG Cy3 (1:100, Zymed Inc., San Francisco) in both cases.
Detailed counts of both neuronal and oligodendroglial cell numbers within grey matter areas of interest (Appendix 1) were performed using standard unbiased stereological methods for those slides stained with the neural marker MAP-2 (Gundersen et al., 1988; Toth et al., 2006) and the oligodendroglial marker PDGFR. Volume and total cell number were performed with the examiner blinded to the condition and treatment of each mouse brain. Twelve sampled areas were counted for each brain region in each brain, with neurons distinguished based upon nuclear size and appearance.
Quantitative real-time PCR
Total RNA was extracted from brain regions stored in Trizol reagent (Life Technologies Inc., Rockville, MD). Total RNA (1 µg) was processed directly to cDNA synthesis using the TaqMan\Reverse Transcription Reagents kit (Applied Biosystems). All PCR primers and TaqMan probes were designed using software PrimerExpress (Applied Biosystem) and published sequence data from the NCBI database. PI3K primer sequences were: forward, 5'-AACCCGGCACTGTGCATAAA-3'; reverse 5'-GCCCATTGGATTAGCATTGATG-3'. Akt primer sequences were: forward, 5'-TCTGCCCTGGACTACTTGCACT-3', reverse, 5'-GCCCGAAGTCCGTTATCTTGA-3'. NFkBp65 primer sequences were: forward, 5'-TGTGCGACAAGGTGCAGAAA-3'; and reverse, 5'-ACAATGGCCACTTGCCGAT-3'. β-actin primer sequences were: forward, 5'-TGTTGTCCCTGTATGCCTCTGGTC-3'; reverse, 5'-ATGTCACGCACGATTTCCCTCTCTC-3'. SYP primer sequences were: forward, 5'-AAAGGCCTGTCCGATGTGAAG-3'; reverse, 5'-TCCCTCAGTTCCTTGCATGTG -3'. ChAT primer sequences were: forward, 5'-CTATGAGAGTGCATCCATCCGC-3'; reverse, 5'-GGTCAGTCATGGCTTGCACAA-3'.
RT-PCR was performed using SYBR Green dye. All reactions were performed in triplicate in an ABI PRISM 7000 Sequence Detection System. Data were calculated by the 2–
CT method and are presented as the fold induction of mRNA for RAGE in diabetic tissues normalized to 18S for comparison to non-diabetic tissues (defined as 1.0-fold).
Western blot
Thalami and sensorimotor cortices from brains for each cohort were homogenized using a RotorStator Homogenizer in ice-cold lysis buffer (10% glycerol, 2% SDS, 25 mM Tris–HCl, pH 7.4, Roche Mini-Complete Protease Inhibitors). Samples were then centrifuged at 10 000 g for 15 min. Supernatant was stored at –20°C prior to SDS–PAGE and immunoblotting analysis. Equal amounts (150 µg) of protein were loaded and samples were separated by SDS–PAGE using 10% polyacrylamide gels with 800 V-h of current applied. Separated proteins were transferred onto nitrocellulose paper (BioRad) over 16 h at 200 mA in Towbin transfer buffer (25 mM Tris, 192 mM glycine, 20% v/v methanol, 0.1% v/v SDS). The blot was blocked for 1 h in 7.5% (w/v) milk (Nestle, Carnation) in TBS [50 mM Tris, 137 mM NaCl, 51 mM KCL, 0.05% (v/v) Tween-20]. The PI3K and Akt pathway were investigated with PI3K (1:1000), PKB/Akt (1:1000), pAkt (1:1000). The nuclear signalling transcription factor NFkB p65 and p50 subunits (1:1000 each) were also examined, and additional immunohistochemistry was performed for CREB (1:200, Abcam Inc., Cambridge, MA) and glycogen synthase kinase 3β (GSK3β) (1:200, Abcam Inc., Cambridge, MA). Quantification of synaptic presence was performed using anti-synaptophysin (SYP) (1:1000; Santa Cruz, Santa Cruz, CA, USA, polyclonal) and Anti-Choline Acetyltransferase (ChAT) (1:500, Abcam, Cambridge, UK, polyclonal). Identification of proteins for IRβ (C-19) (1:500, Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA) and insulin (1:500, Abcam, Cambridge, UK, polyclonal) were also performed using Western blotting. For a housekeeping protein, anti-β-actin (1:100, Biogenesis Ltd. Poole, UK) was applied to separate blots. Secondary anti-rabbit, anti-mouse or anti-human IgG HRP Linked antibody (Cell Signaling) was applied at 1:5000 in each case as appropriate. Signal detection was performed by exposing of the blot to enhanced chemi-luminescent reagents ECL (Amersham) for 2 min. The blots were subsequently exposed and captured on Kodak X-OMAT K film. In each case, three blots were performed, and analysed with Adobe Photoshop (Adobe Photoshop 9.0, Adobe, San Jose, CA, 2005) for quantification of relative protein content.
Analysis of Western blots used a ratio of protein of interest to β-actin protein for each region of brain tissue and each cohort. Quantification of the luminosity of each identified protein band was performed using Adobe Photoshop software (Adobe Photoshop 7.0, Adobe, San Jose, CA, 2002).
Additional immunohistochemistry
Immunohistochemistry was performed using PI3K (1:200, Santa Cruz Inc., Santa Cruz, CA), PKB/Akt [1:200, anti-protein kinase B (Akt), Stressgen, Victoria, Canada], pAkt [1:200, anti-phospho-Akt (Ser473), Cell Signaling Technologies, Danvers, MA] and the nuclear signalling transcription factor NFkB p65 subunit (1:200, anti-NFkB p65, Santa Cruz, Santa Cruz, CA) and p50 subunit (1:200, anti-NFkB p50, Santa Cruz, Santa Cruz, CA). For synaptic identification, anti-synaptophysin (1:200; Santa Cruz, Santa Cruz, CA, USA, polyclonal) and Anti-Choline Acetyltransferase (ChAT) (1:100, Abcam, Cambridge, UK, polyclonal) were used. Identification of IR and insulin was performed with immunohistochemistry using antibodies to IRβ (C-19) (1:100, Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA).
Tissue specimens were examined under fluorescence microscopy (Zeiss Axioskope, Axiovision and Axiocam, Zeiss Canada, Toronto, Canada) at 400x and images obtained were examined based upon brain regions of interest sectioned at 10 µm (Appendix 1). Calculation of the number of immunofluorescent profiles as well as the relative luminosity was performed using Adobe Photoshop (Adobe Photoshop 9.0, Adobe, San Jose, CA, 2005). In grey matter regions, the total numbers of neurons per transverse section, as well as the numbers of neurons with positive immunolabelling for the above markers, and their potential nuclear activation, were recorded. Luminosity was classified as none-low (luminosity value of 0–150), moderate (150–250) or high (>250) using Adobe Photoshop software (scale of 0–255 with arbitrary units). An additional measurement of neuronal nuclear immunolabelling for pAkt and NF
B was also performed using a pre-determined luminosity measurement threshold of 150 (no units), below which negative nuclear reactivity was assigned for both neurons and glia. All measurements were performed by a single examiner blinded to the group identity. For synaptic presence, cortical sections immunostained with synaptophysin and ChAT were examined with densitometry using Image-Pro Plus image analysis (Media Cybemetics). A total of 25 randomly chosen areas of cortex, thalamus, and hippocampus from 10 animals per cohort group were examined at 400x.
Electrophoretic mobility shift assays
For evaluation of CREB binding to DNA, brain tissue was obtained and placed in Totex buffer (20 mM HEPES pH 7.9, 350 mM NaCl, 20% glycerol, 1% igepal, 1 mM MgCl2, 0.5 mM EDTA, 0.1 mM EGTA, 0.1 mM PMSF, 5 µg/ml aprotinin, 50 µM DTT), followed by cell lysis on ice for 30 min, centrifugation at 14 000 r.p.m. for 15 min at 4°C, with supernatant retained. Protein levels were determined by the Bradford method (Biorad) and samples stored at –80°C. Equal amounts of protein were incubated in a 20-µl reaction mixture containing 20 µg of bovine serum albumin; 1 µg of poly (dI–dC); 2 µl of buffer containing 20% glycerol, 100 mM KCl, 0.5 mM EDTA, 0.25% NP-40, 2 mM dithiothreitol, 0.1% phenylmethylsulphonyl fluoride and 20 mM HEPES, at pH 7.9; 4 µl of buffer containing 20% Ficoll 400, 300 mM KCl, 10 mM dithiothreitol, 0.1% phenylmethylsulphonyl fluoride and 100 mM HEPES, pH 7.9; and 20 000–50 000 c.p.m. of 32P-labelled oligonucleotide (S) corresponding to a CREB-binding site (5'-CAA TGA CAT GCG GCT ACG TCA CGG CGC AGT GCC C-3'). After 20 min at room temperature, reaction products were separated on a 12% non-denaturing polyacrylamide gel. Radioactivity of dried gels was detected by exposure to Kodak X-Omat film, and images on the developed film were scanned into a computer using a UMAX 1200s scanner. Densitometry was performed using Scion Image software (Scion Corp., Frederick, MD).
For evaluation of NFB binding to DNA, nuclear proteins were extracted with NE-PERTM Nuclear and Cytoplasmic Extraction Reagents (Pierce, Rockford, IL). Protein–DNA complexes were detected using biotin end-labelled double-stranded DNA probes prepared with the Biotin 3' End DNA Labeling Kit (Pierce). The binding probe used was 5'-TCGACAGA[GGGACTTTCC]GAGAGGC-3', with the binding site indicated in square brackets, and bold letters indicating regions of variable nucleotides. Electrophoretic mobility shift assay (EMSA) was performed with a LightShift Chemiluminescent EMSA Kit (Pierce). Briefly, nuclear extracts (10 µg protein) and the 10 x binding buffer with 2.5% glycerol, 5 mM MgCl2, 50 ng/µl poly(dI-dC), 0.05% NP-40, 1 mM DTT and 20 fmol biotin 3'-end labelled double-stranded oligonucleotide were incubated at room temperature for 1 h in a volume of 20 µl. For NFB supershift analysis, an anti–NFBp65 polyclonal antibody (Santa Cruz; 1 µg per reaction) was incubated with the nuclear proteins on ice for 1 h before labelled oligonucleotide was added. Reaction products were separated by electrophoresis [5% acrylamide (29:1 acryl/bis)] in 0.5 x TBE. After electrophoresis, the protein–DNA complexes were transferred onto nylon membranes and detected using chemiluminescence (LightShift kit; Pierce).
Analysis
All statistical comparisons were intended between the following groups: D I-I and D S-I; D I-I and D I-S; D I-I and C I-I; D S-I and D S-S; D S-I and C S-I; C I-I and C S-I; C I-I and C I-S; and C S-I and C S-S. Comparison testing was not performed between other grouped cohorts, with Bonferroni corrections applied as appropriate for the above group comparisons.
Data collected in the groups were expressed as mean ± standard error. One-way matched/unmatched ANOVA and Student's t-tests were performed to compare means between diabetic and control groups. The Repeated Measures ANOVA assessment was performed for data obtained during the four cognitive studies, as individual scoring during 1 week partially depended upon performance of the prior week, with the D I-I group compared to the D S-I and D I-S groups, and the D S-I group compared to the D I-S and D S-S groups. Also, Area Under The Curve statistical testing was performed for cognitive testing other than object recognition tasks. Again, only the groups intended to have statistical comparisons were analysed as such. For the purposes of molecular studies and comparisons, one control (non-diabetic) group was used as a control value, with subsequent comparisons to other diabetic groups for the molecular test studied.
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Intranasal insulin delivery quantification
Quantification of radiolabelled insulin delivery identified peak delivery to the brain within 1 h after I-I delivery and around 6 h with S-I. Systemic insulin concentrations with intranasal delivery were limited as compared with subcutaneous delivery (Fig. 1). Mice receiving I-I treatment did not suffer adverse effects throughout the 1-, 2- and 6-h monitoring periods before sacrifice. S-I delivery led to much higher concentrations of whole blood insulin and development of hypoglycaemia-induced illness in approximately one-third of mice. Hepatic and kidney insulin levels were overall two to three times higher in mice administered S-I.
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Diabetes
After STZ injection, mice developed diabetes within 2 weeks in 262/304 (86%) of animals. Diabetic mice were smaller than non-diabetic mice throughout life beginning 1 month after STZ injection (Table 1), with D I-I mice maintaining weight better than D I-S mice. Hyperglycaemia was identical in D I-I or D I-S mice, but D S-I mice had less hyperglycaemia and developed hypoglycaemia associated with mortality in some instances. Non-diabetic (C) S-I mice also had increased mortality levels relative to C S-S or C I-I mice (Table 1). Mouse glycated haemoglobin levels were increased in all diabetic mice at 9 months of life, and were identical between I-I and I-S mice, but reduced in S-I mice. The mortality rate in diabetic mice was significantly higher than in non-diabetic mice, although mice receiving I-I had improved mortality relative to I-S, S-S and S-I mice (Table 1) (Kaplan–Meier survival statistics).
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The second cohort groups used to complete data within each intervention group consisted of four mice in each of the C S-I, D S-S, D S-I, D I-S and D I-I groups. This led to a data with a minimum of eight mice in each intervention group (n = 9 D I-I, n = 10 D I-S, n = 9 D S-I, n = 10 D S-S, n = 8 C I-I, n = 11 C S-I, n = 8 C S-S, n = 8 C I-S).
Cognitive behavioural data
Cognitive testing continued until 33 weeks of diabetes. All cognitive data was based upon a minimum of eight mice in each cohort group at all time points. Learning processes for each of the tasks appeared to be similar between diabetic and non-diabetic mice over the first several weeks (Fig. 2). Diabetic mice performed better than non-diabetic mice in the first weeks of the Radial Arm Test, as demonstrated previously (Toth et al., 2006), hypothesized to be due to hyperphagia contributing to greater exploratory behaviour. In general, diabetic mice demonstrated waning performances on each of the behavioural tasks after 7–10 weeks of diabetes, with impaired performances continuing throughout the remainder of the 33 weeks of testing. Both D I-I and D S-I mice performed better than diabetic cohorts (D I-S and D S-S) in the Morris Water Maze, Holeboard Test and Radial Arm Test tasks (Fig. 2), although D I-I mice consistently outperformed D S-I mice, particularly in the Morris Water-Maze task. In the Morris Water Maze, diabetic mice also spent less time in the hemisphere of the hidden platform (target zone) than non-diabetic mice, although D I-I mice continued to spend time in the target zone similar to that of the non-diabetic mice (Supplementary Fig. 1). Mistakes made in either of the Holeboard or Radial Arm Tests were also magnified with diabetes and increased with duration of diabetes, although D I-I mice made similar numbers of mistakes as non-diabetic mice (Supplementary Fig. 1). Mouse performance in the Object Recognition task demonstrated novelty-seeking behaviour in control mice and D I-I mice, but not in other diabetic cohort groups (Fig. 2, Supplementary Fig. 1). Additional assessments using the Area Under the Curve for each intervention cohort revealed statistically different performances on cognitive testing as described in the figure legends. Analysis provided by the Repeated Measures ANOVA testing revealed early and late time points for differences in intervention groups, as demonstrated in Fig. 2 and Supplementary Fig. 1.
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Taken together, these behavioural experiments demonstrated better maintenance of visuospatial, procedural and objection recognition memory functioning in the diabetes-exposed brain receiving intranasal insulin as compared to the diabetic mouse brain not receiving intranasal insulin.
MRI and brain weight data
Volumetric measurements of brain demonstrated diffuse cerebral atrophy after 5 months of diabetes (Fig. 3), with protection demonstrated in D I-I mice after 8 months of diabetes. Although not identified within individual brain regions at earlier time points, diabetes-associated atrophy was detected in the sensorimotor cortex, caudate/putamen, corpus callosum, internal capsule, CA3 portion of hippocampus and cerebral peduncle (Fig. 3) after 8 months of diabetes. In each of these brain regions, D I-I mice had measurable protection from atrophy (Fig. 3). Measurement of brain mass showed evidence of brain atrophy after 5 months of diabetes, with protection against loss of brain mass first detected in D I-I mice at 8 months of diabetes (Fig. 3).
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indicates a significant difference (P < 0.0125 using Bonferroni corrections) between the D I-I mouse group and the D I-S and D S-S cohort groups for the respective time points. Finally, 
indicates a significant difference (P < 0.0125 using Bonferroni corrections) between the D I-I mouse group and all other diabetic mouse cohort groups for the respective time points (n = 4-6 mice in each mouse cohort for each time point).As found previously (Toth et al., 2006
), there were no changes in MR T1 or perfusion-weighted imaging measurements identified. Although initial changes could be seen after 5 months, evidence of diabetes-associated leukoencephalopathy was more easily detected after 8 months of diabetes in all diabetic mice using quantitative T2 map values. Although D I-I mice were protected from heightened T2 map values after 8 months, there were still diabetes-mediated WMA present in numerous regions of brain described as white matter regions including corpus callosum and internal capsule, while similar T2 changes could be identified in grey matter regions, such as cortex and hippocampus (Fig. 3). These changes were heterogenous, and were not identified in other brain regions of interest (Appendix 1).
White matter analysis
Quantitative evaluations of histological sections were performed to determine myelin presence in brain regions of interest (Appendix 1). Both LFB preparations and MBP immunohistochemistry detected reductions in myelin quantity within a number of brain regions of interest (Fig. 4). As determined previously (Toth et al., 2006), none of the identified WMA had a pattern which could be attributed to large vessel infarction. Lost MBP expression closely resembled abnormalities also identified with LFB staining and with T2 measurement changes found with MR imaging (Fig. 4).
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As identified previously (Toth et al., 2006
), there were no differences in neuronal density over grey matter regions of interest after detailed stereological counts. For example, neuronal densities within the CA1 region of hippocampus were 1.73 x 106/mm3 in diabetic mice as compared to 1.79 x 106/mm3 in control mice (P = NS). Neuronal densities within other grey matter brain regions (Appendix 1) were similar between diabetic and non-diabetic mouse cohort groups. Oligodendrocyte counts were performed by examination of immunohistochemistry for PDGFR within both regions of white and grey matter (Appendix 1) and revealed a 44% loss of oligodendrocytes within the internal capsule and corpus callosum regions in D I-S brains as compared to C I-S brains, with oligodendrocyte loss protected in D I-I brains, only demonstrating 17% loss (ANOVA, P < 0.01).
mRNA and protein quantification
A relative loss of intraneuronal pAkt and decreased nuclear pAkt presence (Fig. 5) was associated with diabetic encephalopathy. Insulin provision, however, led to amelioration of this loss in D S-I mice, and particularly in D I-I mice. Amongst non-diabetic mouse cohorts, there was no significant difference in pAkt presence in either cortical or hippocampal neurons. Quantification of Akt and PI3K mRNA demonstrated downregulation with diabetes in general, while a near return to normal for both PI3K and Akt mRNA levels occurred with I-I delivery in diabetic mice (Fig. 5) in cortex (also seen in hippocampus). Protein quantification in the hippocampus and cortex of diabetic mice revealed generalized suppression with diabetes, with partial protection against loss of PI3K, pAkt, GSK3β, pGSK3β and pCREB (no significant difference for Akt and CREB) identified in D I-I mice (Fig. 5). Ratios of phosphorylated to non-phosphorylated downstream markers revealed increased activation (phosphorylation) of Akt and CREB, along with increased phosphorylation (inactivation) of GSK3β in the hippocampus for diabetic mice receiving I-I (Fig. 5). EMSAs demonstrated maintained DNA binding for CREB in D I-I mice as compared to D I-S mice (Fig. 5).
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Protein and mRNA for portions of the IR, IRβ and IR subsrate (IRS)-1, were also downregulated in the diabetic murine brain except when I-I was provided (Fig. 6). Both IRβ and IRS-1 were expressed over the neurolemma of cortical and hippocampal and cortical neurons, with decreased levels of expression in diabetes, except in D I-I mice (Fig. 6). For non-diabetic mice, intranasal insulin provision also led to elevated IRβ levels (Fig. 6).
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Important components of the synaptic complex, the vesicular protein synaptophysin (SYP) and the enzyme choline acetyltransferase (ChAT), were both downregulated in diabetic hippocampus and cortex (Fig. 7). Again, D I-I mice were partially spared from loss of synaptic components within the cerebrum based upon immunofluorescence quantification, protein blotting and qRT-PCR studies (Fig. 7). There were no differences between non-diabetic cohort groups despite the provision of I-I or S-I (Fig. 7), and no loss of synaptic components was demonstrated in the thalamus in any cohort.
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Diabetes led to greater accumulation of NF
B and its greater nuclear presence (activation) (Fig. 8). Both neurons and oligodendrocytes in cortical, hippocampal and subcortical regions demonstrated NFB activation, with suppressed levels of activation demonstrated in D I-I mice. As well, D I-I mice also demonstrated partial suppression of overall NFB mRNA and protein elevation occurring in both cortex and hippocampus, which exhibited age-dependent increases over time for both diabetic and non-diabetic mice (Fig. 8), but greatest in diabetic mice. Finally, EMSAs demonstrated depressed levels of DNA binding for NFB in D I-I mice as compared to D I-S mice, but levels remained higher in D I-I mice when compared to non-diabetic mice (Fig. 8). There were no differences in NFB levels between non-diabetic cohorts.
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Discussion |
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TopSummaryIntroductionMaterials and MethodsResultsDiscussionConclusionsSupplementary materialFundingAppendix 1References |
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Intranasal insulin prevented diabetes-mediated cerebral neurodegeneration without leading to prominent systemic effects or modification of glycaemia levels. Replacement of insulin reversed the downregulated PI3K/Akt pathway to slow or diminish the development of brain atrophy, WMA and cognitive decline.
Systemic and neural effects of subcutaneous and intranasal insulin
Insulin delivered through an intranasal route led to improvements in behavioural (Fig. 2), morphological (Figs 3 and 4), and molecular abnormalities (Figs 5–8
) within the diabetes-exposed brain. I-I did not confer the risks of systemic hypoglycaemia identified with S-I delivery in this long-term experimental model. Not only did S-I delivery in either of diabetic or non-diabetic mice lead to greater mortality (Table 1) and higher systemic delivery than I-I (Fig. 1), but failed to improve a number of morphological and molecular deficits identified with diabetic encephalopathy. While subcutaneous delivery of insulin led to improved glycated haemoglobin levels at sacrifice, intranasal insulin delivery did not, suggesting that the beneficial effects of I-I in diabetic mice was not due to effects upon hyperglycaemia, which occurred in the D S-I cohort (Table 1). Whereas systemic insulin enters the brain via a receptor-mediated, saturable form of transport (Woods et al., 2003), I-I directly enters the brain bypassing the blood–brain barrier and travelling by extra-cellular bulk flow transport along olfactory and trigeminal perivascular channels, as well as axonal transport pathways (Benedict et al., 2004; Thorne et al., 2004), leading to faster uptake and less systemic insulin presence.
The role of insulin as a neuroprotective trophic factor
Insulin, a highly conserved peptide that is no longer thought of as solely a promoter of glucose turnover, has now emerged as a key neurotrophic factor in the nervous system alongside and interacting with the IGF-I receptor system, also important in maintaining cognitive function (Trejo et al., 2008). Insulin is a potent trophic factor which becomes lost within type I diabetes. The major site of insulin's activity, IR, is found in high concentration in the brain, particularly in the cerebral cortex, olfactory bulb, hippocampus (Fig. 6), amygdala and septum (Havrankova et al., 1978a, b; Baskin et al., 1987; Unger et al., 1991). Reduced levels of insulin and its signalling molecules occur in the CSF and brain of Alzheimer disease patients (Craft et al., 1998; Hoyer, 2004). Also, IRs are present at synapses for both astrocytes and neurons (Abbott et al., 1999). As demonstrated in our study, diabetic rodents also demonstrate a loss of insulin transduction machinery (Fig. 6), which has previously been linked to the increased expression of amyloid precursor protein (APP), APP's cleavage enzyme β-secretase, and other abnormalities typical of the Alzheimer disease brain (Ho et al., 2004; Salkovic-Petrisic et al., 2006; Li et al., 2007). It has also been demonstrated that peripheral hyperinsulinaemia and reduced insulin signalling increase levels of amyloid (Aβ) and tau hyperphosphorylation, leading to the formation of both senile plaques and neurofibrillary tangles (Zhao et al., 2004b; Freude et al., 2005). In addition, insulin promotes physiologic processes critical for memory, including long-term potentiation, expression of glutamate receptors, and modulation of neurotransmitter levels (Craft and Watson, 2004). Finally, insulin diminishes hypothalamic–pituitary–adrenal-axis activity (Hallschmid et al., 2008), recently speculated to contribute to diabetes-mediated cognitive dysfunction (Stranahan et al., 2008).
Potentially preventable changes in diabetic encephalopathy
Our experiments have demonstrated that long-term intranasal insulin delivery protected against brain atrophy (Fig. 3). Although other studies have reported evidence of cerebral neuronal loss in diabetes (Li et al., 2007), we could not detect any loss of neuronal density in this experimental diabetic brain model, similar to other recent studies (Stranahan et al., 2008), but we did determine oligodendroglial loss occurs and likely relates to the development of WMA. One potential cause for our detected diabetes-associated brain atrophy (Fig. 3) is the presence of large degree of synaptic loss (Fig. 7), also detected in type II diabetic rat models (Li et al., 2007). Synaptic loss may precede other forms of pathology in some models of Alzheimer disease (Yoshiyama et al., 2007), including neuronal loss. Diabetes also leads to a synergistic potentiation of synaptic loss in transgenic models of Alzheimer disease (Burdo et al., 2008). This may certainly be impacted by the presence of insulin receptor at central synapses (Heidenreich et al., 1983; Matsumoto and Rhoads, 1990; Wan et al., 1997; Zhao et al., 1999). Signal transduction by neuronal IRs is exquisitely sensitive to soluble Aβ oligomer-mediated disruption in vitro, and neuronal response to insulin is also inhibited (Zhao et al., 2008). Such synaptic loss identified in our experiments of the diabetic brain may herald subsequent neuronal loss, but other models need to be investigated, and longer duration studies may be necessary to conclude this.
Insulin's downstream signalling pathways
Insulin is critical for maintenance of numerous downstream intracellular signalling pathways. Insulin stimulation upregulates protein–tyrosine phosphorylation (Mahadev et al., 2004) through downstream activation of IRS-2 (Huang et al., 2005a). Insulin presence leads to activation of Akt and phosphorylation of Akt substrates (Fig. 5) (Bruss et al., 2005). In addition, insulin modulates the inner mitochondrial membrane potential through activation of the PI3K pathway, stimulating phosphorylation of Akt and cAMP response element-binding protein CREB (Marshall, 1995; Yao and Cooper, 1995; Fernyhough et al., 2003; Viard et al., 2004; Huang et al., 2005b), as well as supporting neuritic extension and branching (Jones et al., 2003). PI3K also enhances voltage-dependent calcium channel current functioning in diabetic neurons (Viard et al., 2004). In our studies, downregulation of PI3K/Akt occurred throughout the diabetic murine brain (Fig. 5), while insulin delivered intranasally, and to a lesser extent, subcutaneously, prevented such downregulation while concurrently leading to improvements in behaviour and morphology.
Insulin's benefits in the diabetic brain may relate to inactivation of GSK-3β and activation of CREB. Besides regulating the transcriptional activities of CREB (Cohen and Frame, 2001; Grimes and Jope, 2001), GSK-3β is also a neuron-specific (Leroy and Brion, 1999) apoptosis promoter in the non-phosphorylated, or active state (Hetman et al., 2000); Akt-mediated phosphorylation of GSK-3β renders it inactive, giving anti-apoptotic properties (Pap and Cooper, 1998; Bijur et al., 2000; Hetman et al., 2000). Similar to insulin in our study, IGF-I also activates the PI3K/Akt pathway (Dudek et al., 1997; Zheng et al., 2002), leading to phosphorylation of CREB and GSK-3β (Leinninger et al., 2004). IGF-I provision also induces oligodendrocyte progenitor proliferation via Akt activation (Cui and Almazan, 2007), with GSK-3β phosphorylation in oligodendrocyte progenitor cells affecting oligodendrocyte stability (Frederick et al., 2007). pGSK-3β may also regulate gene expression and activity of transcriptional factor binding to the MAG promoter region (Ogata et al., 2004), promoting myelination and possibly explaining insulin-mediated protection against WMA development in the experimental diabetic murine brain (Figs 3 and 4). While CREB phosphorylation inhibits apoptosis in neurons (Walton et al., 1999), the loss of CREB results in impaired axonal growth (Lonze et al., 2002), suggesting that CREB is neuroprotective. Intranasal insulin led to heightened pCREB levels as well as greater CREB DNA binding indicating transcription (Fig. 5). Overall, we hypothesize that insulin's benefits in the diabetic murine brain are due to maintained phosphorylation of CREB and GSK-3β.
The utility of intranasal delivery in diabetic encephalopathy
In the case of diabetic encephalopathy, and likely the Alzheimer disease brain, insulin's trophic effects are lacking. I-I delivery without modifying systemic glucose or glycated haemoglobin (Table 1) (Tomlinson and Gardiner, 2008) appears to be essential to insulin's long-term benefits in brain exposed to diabetes. Human studies have already demonstrated safe administration of intranasal insulin in patients with Alzheimer disease, leading to some improvement in cognition and modulating markers of Alzheimer disease (Reger et al., 2006, 2008). These studies have concentrated upon the potential benefits of intranasal insulin delivery upon clinical and pathological markers of Alzheimer disease. Other clinical studies examining intranasal insulin delivery have also demonstrated effects upon the CNS, such as improvement in memory (Benedict et al., 2007, 2008), lowering of food intake (Tomlinson et al., 2008), and improvement in mood (Hallschmid et al., 2008). In humans, plasma glucose levels may be minimally impacted by intranasal insulin delivery (Born et al., 2002; Reger et al., 2006, 2008; Tomlinson et al., 2008). As of yet, intranasal insulin delivery to diabetic subjects for the intent of improving memory or other diabetic complications has not yet been described, although intranasal insulin delivery has been examined as a potential method for the treatment of diabetes itself (Owens et al., 2003; Khafagy et al., 2007).
Our study results must be considered under the limitations of working in a murine model, and the inability to achieve a long-term model of murine type I diabetes with optimal glycaemic management as a suitable control group. The mouse cohorts were subjected to intensive testing throughout their lifetime, with the possibility of stressful impacts upon the results obtained. The use of multiple cognitive studies, often needed as part of a battery of tests, may have led to crossover effects affecting results from one cognitive test based upon the preceding test. It is also possible that hypoglycaemia may have impacted some of the results of cognitive testing, and the impact of hypoglycaemia upon the D I-S and C I-S cohort groups was anticipated, but difficult to avoid. As well, performance of behavioural testing within multiple cohorts of mice within each intervention group may have contributed to performance disparities. Based upon our studies, it is difficult to develop a more appropriate control group of diabetic mice with long-term glycaemic control based upon the STZ-induced diabetic model. Despite these difficulties, D S-I mice performed better than D S-S cohort mice during portions of cognitive testing. Although cognitive changes in our mice also seem to occur mainly during the younger and older age time points (similar to expected changes in type I diabetic patients), explanations for a relative plateau of function during the middle-aged years are unknown. (Wessels et al., 2007, 2008; Biessels et al., 2008; Kloppenborg et al., 2008;) At this time, our results are limited to murine models of type I diabetes, and other forms of diabetes, including models of type II diabetes, will need study in the future to confirm our results in other models of diabetes.
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Conclusions |
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TopSummaryIntroductionMaterials and MethodsResultsDiscussionConclusionsSupplementary materialFundingAppendix 1References |
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Intranasal insulin delivery is a potential therapy to ameliorate behavioural, morphological and molecular changes occurring in brain exposed to diabetes over time. Our results provide strong evidence for benefits of insulin without impact upon serum glucose levels, indicating that insulin is an important neurotrophic factor in the management of diabetes-mediated brain disease. These data support the development of clinical studies for the prevention and slowing of the adverse effects of diabetes upon the brain using intranasal delivery of insulin.
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Supplementary material |
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TopSummaryIntroductionMaterials and MethodsResultsDiscussionConclusionsSupplementary materialFundingAppendix 1References |
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Supplementary material is available at Brain online.
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Funding |
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TopSummaryIntroductionMaterials and MethodsResultsDiscussionConclusionsSupplementary materialFundingAppendix 1References |
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This study was supported by an operating grant from the Alberta Heritage Foundation for Medical Research and the Canadian Diabetes Association. C.T. is a Clinical Investigator of the Alberta Heritage Foundation for Medical Research and D.W.Z. is a Scientist of the Alberta Heritage Foundation for Medical Research.
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Appendix 1 |
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TopSummaryIntroductionMaterials and MethodsResultsDiscussionConclusionsSupplementary materialFundingAppendix 1References |
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The following brain regions were chosen as areas for close inspection within this study for MRI and myelin quantification portions of the experiment:
Caudate putamen
Primary motor/sensory cortex
Internal capsule
Cerebral peduncle
CA1 region of hippocampus
CA2/3 region of hippocampus
Ventroposterior region of thalamus
Corpus callosum
Amygdala
Substantia nigra pars reticulata
Subiculum
Lentiform nuclear region
Primary visual cortex
Cerebellum
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