APOE4 rat model of Alzheimer’s disease: sex differences, genetic risk and diet

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A high fat diet also adds to the risk of dementia and AD. In addition, there are sex differences as women carriers have a higher risk of an earlier onset and rapid decline in memory than men. The present study looked at the effect of the genetic risk of ApoE ɛ4 together with a high fat/high fructose diet (HFD/HSD) on brain function in male and female rats using magnetic resonance imaging. We hypothesized female carriers would present with deficits in cognitive behavior together with changes in functional connectivity as compared to male carriers. Four-month-old wildtype and human ApoE ɛ4 knock-in (TGRA8960), male and female Sprague Dawley rats were put on a HFD/HSD for four months. Afterwards they were imaged for changes in function using resting state BOLD functional connectivity. Images were registered to, and analyzed, using a 3D MRI rat atlas providing site-specific data on 173 different brain areas. Resting state functional connectivity showed male wildtype had greater connectivity between areas involved in feeding and metabolism while there were no differences between female and male carriers and wildtype females. The data were unexpected. The genetic risk was overshadowed by the diet. Male wildtype rats were most sensitive to the HFD/HSD presenting with a deficit in cognitive performance with enhanced functional connectivity in neural circuitry associated with food consumption and metabolism. diffusion weighted imaging functional connectivity MRI high fat/high fructose diet graph theory sex difference Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Alzheimer's disease (AD) is the primary contributor to dementia among older individuals, impacting more than 35 million individuals globally 11 . Age stands out as the most influential factor in developing AD, as the likelihood of experiencing the disease increases twofold every five years after reaching the age of 65 1 . Another notable risk factor, ranking second in importance, is the apolipoprotein E ( ApoE ) ɛ4 allele 1 . A majority of AD patients carry at least one of the two ApoE ɛ4 alleles with women having a greater risk for future problems 2 . Indeed, there are several clinical studies on ApoE ɛ4 carriers reporting sex differences in cognition with aging. Females ApoE ɛ4 carriers are more likely to develop Alzheimer’s disease than male carriers 3 – 5 and females have a faster rate in declining memory as compared to males 6 – 8 . ApoE ɛ4 , primarily synthesized by glial cells, is involved in lipid metabolism and cholesterol transport 9 – 11 . Dysregulation in energy utilization associated with metabolic homeostasis that occurs with aging is a contributing factor to the pathophysiology of AD 12 . Age brings a gradual disruption in metabolism, something enhanced by obesity. Indeed, obesity caused by dietary habits is widely acknowledged as a significant contributor to the development and physiological mechanisms of AD. 13 – 15 . Preclinical studies show the “Western” diet, composed of high fat and sugar contributes to this pathology 16 – 19 . Disease progression in rodent models of AD is exacerbated when a genetic background of ApoE ɛ4 is combined with the protracted consumption of a high fat/high fructose diet (HFD/HSD) 18 , 20 , 21 . This model combining ApoE ɛ4 plus HFD/HSD was used to develop sensors to analyze exhaled gas for small volatile lipids associated with AD 22 and image progression of neurovascular dysfunction with aging 23 . In the present study we hypothesized prolonged exposure to HFD/HSD would exacerbate disease progression in the human ApoE ɛ4 knock-in (TGRA8960) rat. In a previous study, we reported 6-month-old male ApoE ɛ4 knock-in rats, present with altered gray matter microarchitecture in the sensorimotor and limbic cortices with a decrease in cognitive function; however, 6-month-old female carriers showed little changes in water diffusivity and cognitive behavior but did show enhanced functional connectivity 24 . In this study, looking at the added risk of a high fat, high sugar diet there was no evidence of cognitive dysfunction or functional connectivity in female or male ApoE ɛ4 carriers. Instead, male wild-type rats were most affected by the HFD/HSD. Methods Animals Male wildtype (n = 4), female wildtype (n = 5) and human ApoE ɛ4 knock-in (TGRA8960) male (n = 5) and female (n = 6) Sprague Dawley rats, ca. four months of age, were a gift from Inotiv (West Lafayette, Indiana, USA). All genotypes were studied on high fat, high sucrose diet. Rats were placed in Plexiglas cages, with one or two rats per cage, and were kept in a room with a temperature range of 22–24°C and a 12-hour light-dark cycle (lights on at 07:00 a.m.). They had free access to food and water throughout the study. Following a week of acclimatization to the animal quarters, all rats were fed a high-fat, high-sucrose diet (HFD/HSD) for a duration of 120 days before undergoing testing, at which time they were approximately 240 days old. The specific diet used (TD.88137) was obtained from Envigo (South Easton, MA) and had the following composition by weight: 48.5% carbohydrates (with 34% of it being sucrose), 21.2% fat, 17.3% protein, and 0.2% cholesterol. Shown in Supplementary Fig S1 are the change in body weights (mean ± SD) for each of the experimental groups collected weekly over a ten-week period. The acquisition and welfare of all rats followed the guidelines outlined in the NIH Guide for the Care and Use of Laboratory Animals. The methods and procedures described in this study were approved in advance by the Northeastern University Institutional Animal Care and Use Committee, under protocol number 20-0627R. Northeastern University's animal care and use program and housing facilities have received full accreditation from AAALAC, International. The protocols employed in this research adhered to the ARRIVE guidelines, which provide recommendations for reporting in vivo experiments in animal research 25 . Barnes Maze The Barnes Maze has been utilized to evaluate spatial learning and memory in different rodent models. A description of the assay as performed in our lab has been published 26 , 27 . In brief, the maze consists of a circular platform with 18 escape holes located around its perimeter. Beneath the platform, there was a removable goal box, positioned consistently across all trials. Before each trial, the rat was placed inside the goal box for 1 minute and then placed under a covered container at the center of the platform for 30 seconds. The container was then lifted to start the trial. During the acquisition trials, if the animals were unable to locate the goal box within the 4-minute test period, they were gently guided into the goal box and allowed to remain there for 1 minute. Subsequently, they were returned to their home cages between the three trials conducted each day over a span of four days. In evaluating the acquisition trials, all animals were assessed based on parameters such as goal box latency (the time taken for animals to enter the goal box), errors (defined as instances where animals investigated any non-goal box hole within 2 cm with their head directed towards the hole), error duration (the duration spent exploring non-goal box holes within 2 cm), and the distance traveled before entering the goal box. All animal behavior was recorded on video and analyzed for the time it took to find the goal box. The analysis was conducted manually by experimenters who were unaware of the treatment condition, and the results were further confirmed using ANY-maze® software for automated scoring (Stoelting, Wood Dale, IL, USA). Neuroimaging Imaging sessions were performed using a Bruker Biospec 7.0T/20-cm USR horizontal magnet (Bruker, Billerica, MA, USA) equipped with a 2 T/m magnetic field gradient insert (12 cm inner diameter) that had a rise time of 120 µs. The radio frequency signals were transmitted and received through a quadrature volume coil integrated into the animal restrainer (Ekam Imaging, Boston MA, USA) 28 . The animal restrainer was designed with a padded head support, eliminating the need for ear bars, thereby reducing animal discomfort and minimizing motion artifacts. All rats were imaged under 1–2% isoflurane anesthesia, maintaining a respiratory rate of 40–50 breaths per minute. At the start of each imaging session, a high-resolution anatomical dataset was acquired using the Rapid Acquisition, Relaxation Enhanced (RARE) pulse sequence with the following parameters: 35 slices with a thickness of 0.7 mm, a field of view (FOV) of 3 cm, matrix size of 256 × 256, a repetition time (TR) of 3900 msec, an effective echo time (TE) of 48 msec, a number of excitations (NEX) of 3, and an acquisition time of 6 minutes and 14 seconds. Resting State Functional Connectivity Scans were acquired using a spin-echo triple-shot EPI sequence with the following imaging parameters: matrix size of 96 x 96 x 20 (height x width x depth), a repetition time (TR) of 1000 msec, an echo time (TE) of 15 msec, voxel size of 0.312 x 0.312 x 1.2 mm, slice thickness of 1.2 mm, 200 repetitions, and a total acquisition time of 10 minutes. Preprocessing steps involved the combined use of Analysis of Functional NeuroImages (AFNI_17.1.12), FMRIB Software Library (FSL, v5.0.9), Deformable Registration via Attribute Matching and Mutual-Saliency Weighting (DRAMMS 1.4.1), and MATLAB software. Brain tissue masks were manually drawn using 3DSlicer and applied for skull-stripping. Motion outliers and spikes were identified and regressed out, followed by slice timing correction. Head motion correction was performed using the first volume as a reference, and normalization was achieved through affine registration to the 3D MRI Rat Brain Atlas. A total of 173 annotated brain regions from the atlas were used for segmentation. Subsequent steps included quality assurance, band-pass filtering (0.01Hz ~ 0.1Hz) to reduce drift and noise, detrending, spatial smoothing (full width at half maximum = 0.8mm), and nuisance regression using motion outliers, motion parameters, mean white matter, and cerebrospinal fluid time series as regressors. The region-to-region functional connectivity analysis involved calculating correlations in spontaneous BOLD fluctuations. Nodes represented specific brain regions of interest (ROIs), and edges represented connections between regions. Voxel time series data were averaged within each node based on residual images obtained from nuisance regression. Pearson's correlation coefficients were computed across all pairs of nodes (14535 pairs) for each subject in all three groups to assess interregional temporal correlations. The resulting correlation values (ranging from − 1 to 1) were transformed using Fisher's Z transform. Symmetric connectivity matrices of size 166 x 166 were constructed, with each entry representing the strength of an edge. Group-level analysis was conducted to examine functional connectivity in the experimental groups. Z-score matrices from one-group t-tests were subjected to K-nearest neighbors clustering to identify node clusters and resting state networks. A threshold of |Z|=2.3 was applied to remove weak or spurious connections between nodes for visualization purposes. Resting State BOLD Functional Connectivity Analysis . Degree Centrality The network analysis was conducted using Gephi, which is an open-source software for network analysis and visualization (Bastian et al., 2009). The symmetric connectivity matrices of both the CBD and vehicle groups, consisting of absolute values, were imported into Gephi, and the edges were treated as undirected networks. Degree centrality analysis was employed to measure the number of connections each node had within the overall network. The formula for degree centrality (C_D) is defined as the sum of A_ij, which represents the number of edges between nodes i and j, with n representing the number of rows in the adjacency matrix A. $${\text{C}}_{\text{D}}\left(\text{j}\right)=\sum _{\text{j}=1}^{\text{n}}{\text{A}}_{\text{i}\text{j}}$$ Statistics Statistical analysis for the graph theory analysis was performed using GraphPad Prism version 9.0.0 (86) software from GraphPad Software, San Diego, California, USA ( www.graphpad.com ). Normality tests, such as Shapiro-Wilk's test, were conducted to assess the normality assumption between group subregions. If the p-values for subregion degree centrality were greater than 0.05, it was assumed that the data followed a normal distribution. In such cases, paired t-tests were used to compare the degree centrality between the CBD and vehicle groups in different subregions. If there was evidence against the normality assumption, a nonparametric Wilcoxon signed-rank (WSR) test was performed instead. Results Cognition Shown in Fig. 1 are data on cognitive performance in the Barnes Maze following four months of HFD/HSD for transgenic and wildtype rats. The bar graphs are the mean ± SD for the latency to enter the goal box. The scores are the pooled average of all four test periods. There were no significant differences between male and female ApoE ɛ4 carriers; neither was there any significant differences between wildtype males and females. A one-way ANOVA with multiple comparisons found a significant difference between the female ApoE ɛ4 and male wildtype (p = 0.045). Functional Connectivity Global brain connectivity as expressed in Degrees or number of connections (mean ± SD) for each of the experimental conditions is shown in Fig. 2 . There was a significant main effect for genotype (two-way ANOVA, F (3,498) = 166.1; p < 0.0001). Tukey’s post hoc multiple comparison test showed male wildtype (M/WT) on HFD/HSD was significantly greater than all other experimental conditions (p < 0.0001). Female ApoE ɛ4 (F/AE), presented with the next highest number of Degrees that was significantly greater than male ApoE ɛ4 and female wildtype (p < 0.0001). There was no significant difference between male ApoE ɛ4 and female wildtype. Global brain hippocampal connectivity is shown on Fig. 2 . There was a significant main effect for genotype (two-way ANOVA, F (3,24) = 13.61; p < 0.0001). The male wildtype were significantly greater than male ApoE ɛ4 (p < 0.0001) and female wildtype (< 0.01), while female ApoE ɛ4 were significantly greater than male ApoE ɛ4 (p < 0.01) and female wildtype (p < 0.05). Given the hyperconnectivity of the male wildtype on HFD/HSD as compared to the other experimental conditions we analyzed the connectivity in the context of feeding behavior. Table 1 is a list of brain areas taken from recent review by Alcantara et al., on the neural circuits governing the different phases of feeding Alcantara, Tapia, Aponte and Krashes 29 . The global connectivity for this neural circuit for each of the experimental conditions (mean ± SD) is shown in Fig. 3 . There was a significant main effect for genotype (two-way ANOVA, F (3,51) = 21.53; p < 0.0001). Tukey’s post hoc test showed male wildtype on HFD/HSD was significantly greater than male ApoE ɛ4 (p < 0.0001), female wildtype (< 0.0001), and (p < 0.01), while female ApoE ɛ4 was significantly great than male ApoE ɛ4 (p < 0.01). A key region of the brain controlling feeding behavior is the hypothalamus shown in Fig. 3 . Again, there was a main effect for genotype (F (3,45) = 11.08; p < 0.0001). Post hoc tests showed male wildtype was significantly greater than male ApoE ɛ4 (p < 0.0001), females wildtype (p < 0.01) and female ApoE ɛ4 (p < 0.05), while female ApoE ɛ4 was significantly greater than male ApoE ɛ4 (p < 0.05). The cerebellum and the deep cerebellar nuclei have also been identified as contributing to the organization of feeding behavior and metabolism (Fig. 3 ). There is a main effect for genotype (F (3,57) = 52.30; p < 0.0001) with male wildtype connectivity is significantly (p < 0.0001) greater than the other experimental conditions. Table 1 Degrees for brain areas forming the neural circuit regulating feeding and metabolism Table 1 Degrees of Connectivity Brains areas involved in the three phases of eating behavior: procurement, consumption and termination Brain Areas Male WT Male APOE4 Female WT Female APOE4 accumbens core 15 7 7 11 accumbens shell 20 14 7 16 arcuate nucleus 6 4 3 4 bed nucleus stria terminalis 27 5 11 9 central amygdaloid nucleus 13 7 9 7 dorsal raphe 13 6 7 20 insular ctx 19 5 5 8 lateral hypothalamus 22 11 16 17 locus coeruleus 23 6 9 10 intermediate cerebellar nucleus 32 12 7 13 lateral cerebellar nucleus 29 6 6 9 medial cerebellar nucleus fastigial 34 9 10 11 parabrachial nucleus 33 13 13 21 paraventricular nucleus hypothalamus 19 11 15 11 paraventricular nucleus thalamus 4 7 7 11 periaqueductal gray thalamus 29 9 7 22 substantia innominata 25 8 13 10 ventral tegmental area 18 9 12 15 zona incerta 15 6 17 16 The arcuate, lateral, and paraventricular nuclei of the hypothalamus and the deep cerebellar nuclei have a major role in controlling feeding 29 . The connectivity of these three hypothalamic and cerebellar nuclei is shown in Fig. 4 . The hypothalamic connectivity in male wildtype are not significantly different from the other experimental groups. In contrast the connectivity of the deep cerebellar nuclei are significantly greater than the other experimental groups. The intra and extra hypothalamic and cerebellar connectivity can be visualized by the network maps below the bar graphs. The circles are nodes, and the lines are edges. The inner blue nodes are the functional connections of the different nuclei to their immediate surroundings i.e. either other hypothalamic or cerebellar nuclei. The black nodes are functional connections to other brain areas. Discussion The present study examined the intersection of both aging and diet as risk factors for AD with both male and female wildtype and ApoE ɛ4 knock-in rats after four months on HFD/HSD or “Western” diet. At four months of age, all rats were put on the HFD/HSD diet ad libitum. Four months later a period equivalent to ca 8.7 human years 30 they were tested for cognitive behaviors and imaged for differences in resting state BOLD functional connectivity (rsFC). To our surprise male and female ApoE ɛ4 carriers were unaffected by the HFD/HSD diet as compared to wild-type rats; instead, it was the male wild-type, but not the female that showed behavioral and neuroradiological changes. These finding are discussed below with respect to preclinical and clinical studies on the behavior and neurobiology of ApoE ɛ4 carriers and the influence of diet. Behavior Eight-month-old male wildtype rats on HFD/HSD showed a modest deficit in cognitive function when evaluated in the Barnes maze while the male and female ApoE ɛ4 carriers and female wildtype showed no deficits. In a previous study using the same genetic rat model we reported 6-month-old human ApoE ɛ4 knock-in rats feed a normal diet were more likely to have cognitive and behavioral problems as compared to female carriers early in life 24 . In the same rat model, we reported 8-month-old female carriers on normal diet show enhanced microvascular density in the hippocampus hypothesized to be a neuroadaptive response helping to spare cognitive function 23 . These and other studies on rodent models of ApoE ɛ4 show genotype-specific changes in behavior and brain structure characteristics of early neurodegenerative pathology 22 , 31 – 34 . Given the risk associated with HFD/HSD for cardiovascular disease, Alzheimer’s disease, and early dementia, we hypothesized ApoE ɛ4 male and female rats would show exacerbated signs of cognitive dysfunction. Instead, ApoE ɛ4 male and female rats were spared the anticipated negative effects of the HFD/HSD, while wildtype males, but not females showed the most changes. Was the HFD/HSD protective in these 8-month-old ApoE ɛ4 rats, evidence of antagonistic pleiotropy, i.e., genes that provide resilience for developmental maturation and reproduction but are detrimental in old age 35 ? Indeed, Janssen et al., reported female ApoE ɛ4 mice feed HFD/HSD showed no deficits in spatial learning together with a reduction in neuroinflammation in the hippocampus as compared to wildtype controls on HFD/HSD 36 . In a recent review on feeding behavior and metabolism, Alcantara and colleagues argue that evolution has driven a neurobiology that favors the overconsumption of calories during times of plenty to offset the dearth of calories during times of famine 29 . ApoE ɛ4’s role in lipid metabolism, transport of cholesterol and complex lipids needed in neural development, membrane maintenance, and repair would be essential in handling the lipid load in HFD/HSD 11 . Jones et al., studied the behavioral and metabolic changes in male and female human ApoE ɛ3 and ApoE ɛ4 knock-in mice fed HFD/HSD as compared to low fat diet and reported male ApoE ɛ4 mice were more susceptible to metabolic disturbances but not female ApoE ɛ3 and ApoE ɛ4 mice 21 . This is in contrast to our data that showed male ApoE ɛ4 were unaffected by the HFD/HSD. The metabolic sensitivity of the male ApoE ɛ4 mice to HFD/HSD but not female ApoE ɛ4 mice was corroborated by Matter et al., with the added distinction that females showed impairment in cognitive function 20 . In a subsequent study, Jones, and coworkers feed ApoE ɛ3 and ApoE ɛ4 mice HFD/HSD for 12 weeks and found the ApoE ɛ3 genotype but not ApoE ɛ4 presented with significant neuroinflammation in the hippocampus as measured by activated microglia and astrocytes 37 . Interestingly, they argued the neuroinflammation was neuroprotective in the ApoE ɛ3 mice creating a neuroadaptive response to the HFD/HSD that would be beneficial in the future. Unfortunately, in our studies on ApoE ɛ4 rats we did not do postmortem histology looking for evidence of gliosis and neuroinflammation. Functional Connectivity - Neural circuitry of feeding and metabolism Male wildtype showed whole brain hyperconnectivity as compared to the male carrier while the female ApoE ɛ4 showed greater connectivity as compared to the female wildtype. The hyperconnectivity for the male wildtype on HFD/HSD was unexpected. However, in a previous study we reported female ApoE ɛ4 rats at six months of age show hyperconnectivity in amygdala, paraventricular nucleus of the hypothalamus and ascending reticular activating system 24 . In this study the male wildtype and female carrier both showed greater global hippocampal connectivity as compared to the male ApoE ɛ4 carrier. As noted above this connectivity was not reflected in any change in cognitive function for females but may be associated with the deficit in learning for the male wildtype. In the latter case, the hyperconnectivity may reflect neuroplastic compensation in response to the early stages of brain injury and loss of function 38 , 39 The sensitivity of the male wildtype to the HFD/HSD as measured by alterations in cognitive function and functional connectivity suggested the risk factor was not ApoE ɛ4 , but instead, a metabolic disorder. While body weights were only recorded through the first 8–9 weeks of HFD/HSD there were no significant changes between wildtype and carriers for either sex ( Supplementary Fig S1 ). So obesity was not a contributing factor. Metabolism involves a balance in appetite and energy utilization. In a recent review conducted by Alcantara et al., a model was proposed that describes the interconnected neural circuitry responsible for regulating the different phases of feeding, including appetitive, consummatory, and terminating phases. 29 . The circuits that control feeding are complex and involve multiple regions of the brain, most notably the hypothalamus. Within the hypothalamus, various nuclei host distinct populations of neurons that have significant roles in controlling appetite and energy balance 40 – 42 . These include neurons that respond to or produce orexigenic peptides such as ghrelin 41 , and neuropeptide Y 43 , and those that respond to or produce anorexigenic signaling molecules e.g. leptin 44 and melanocortin 45 . More specifically, the arcuate nucleus is home to a specific group of neurons known as agouti-related peptide (agRP) neurons in the arcuate nucleus that play a central role 46 in regulating all aspects of feeding in coordination with other hypothalamic areas 29 , 47 . When the many brain areas controlling feeding (Table 1 ) are combined as a single hub it was the wild-type males on HFD/HSD that showed a significant global increase in connectivity exceeding all other experimental conditions. The global connectivity of the hypothalamus as a single node is also extensive in wildtype males and significantly greater than the other experimental conditions. However, the global connectivity of the three key hypothalamic areas i.e., acuate, lateral, and paraventricular nuclei, noted for their role in controlling the distinct phases of feeding present with only a modest number of connections and are not significantly different between experimental groups. A seminal paper by Low and colleagues identified neurons in the cerebellar nuclei, which are characterized by their unique molecular and topographical properties, were found to be activated in response to feeding and nutrient infusion resulting a decrease in food intake 48 . Activation of the deep cerebellar nuclei terminates feeding by altering dopaminergic signaling to the striatum. Our study looking at the interaction between genes and diet spotlighted these cerebellar nuclei e.g. lateral (dentate) intermediate (interposed) and medial (fastigial) and analyzed their connectivity. Indeed these cerebellar nuclei had an extensive network of connections far exceeding the hypothalamic nuclei but only in the male wildtype rats. How this hyperconnectivity is affecting feeding and metabolism in male wildtype is unknown. Limitations The study was not designed to follow feeding and metabolism, points of interest only raised after analyzing the connectivity data. Circadian measures of feeding, metabolism, blood and urine chemistry for each experimental group would have enhanced our understanding of the effect of HFD/HSD on wild type and ApoE ɛ4 carriers and why this genetic rat model is resilient - an example of antagonistic pleiotropy? Equally important would have been the same four experimental groups but maintained on normal rat chow. Unfortunately the study had only a limited number of ApoE ɛ4 rats preventing the study of controls on a normal diet. Hence all comparisons are with respect to HFD/HSD. What would be typical behavior or connectivity is uncertain. As noted above, there was no post-mortem histology to confirm the presence or absence of neuroinflammation as reported by Jones et al., 21 . Still another limitation was the collection of functional connectivity data under light isoflurane anesthesia to minimize motion and physiological stress 49 . What constitutes a “resting state” condition in a head restrained, awake rodent could be debated. The administration of anesthesia can decrease the strength of the BOLD signal; however, it does not disrupt the connectivity between brain regions. This has been observed in various species and under different physiological conditions. 50 – 54 . Summary The present study examined the effect of high fat, high sugar diet on male and female, wildtype and ApoE ɛ4 knock-in rats with the expectation that carriers would present with deficits in cognition and functional connectivity. The results were unexpected. The genetic risk was overshadowed by the diet. Male wildtype rats were most sensitive to the HFD/HSD presenting with a deficit in cognitive performance and enhanced functional connectivity in neural circuitry associated with food consumption and metabolism. The deep cerebellar nuclei key in the regulation of feeding behavior showed hyperconnectivity in male wildtype but not in female wildtype or female and male ApoE ɛ4 rats. Declarations Conflict of Interest: CFF has a financial interest in Ekam Imaging, a company that makes radiofrequency electronics and holders for awake animal imaging. CFF and PK have a partnership interest in Ekam Solutions a company that develops 3D MRI atlases for animal research. Ethical Approval and consent to participate: NA Consent to Publication: NA Data Availability statement: The dataset(s) supporting the conclusions of this article are included within the article and its additional Supplementary files Author information Colarusso, Yeboah, and Gupta responsible for data acquisition, Ortiz, Chang, Kulkarni responsible for data analysis, Ferris manuscript preparation. Funding Source: Inotiv, West Lafayette, Indiana, USA: Ekam Imaging, Boston MA USA Acknowledgement We extended our gratitude to Inotiv for providing ApoE ɛ4 rats and Ekam Imaging for supporting these imaging studies. References Association, A.s. Alzheimer's Disease Facts and Figures. (2022). Ungar, L., Altmann, A. & Greicius, M.D. Apolipoprotein E, gender, and Alzheimer's disease: an overlooked, but potent and promising interaction. Brain imaging and behavior 8 , 262-273 (2014). Neu, S.C. , et al. Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease: A Meta-analysis. 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Morrison, T.R. , et al. Treating head injury using a novel vasopressin 1a receptor antagonist. Neurosci Lett 714 , 134565 (2020). Ferris, C.F. Applications in Awake Animal Magnetic Resonance Imaging. Frontiers in neuroscience 16 , 854377 (2022). Alcantara, I.C., Tapia, A.P.M., Aponte, Y. & Krashes, M.J. Acts of appetite: neural circuits governing the appetitive, consummatory, and terminating phases of feeding. Nat Metab 4 , 836-847 (2022). Sengupta, P. The Laboratory Rat: Relating Its Age With Human's. Int J Prev Med 4 , 624-630 (2013). Zerbi, V. , et al. Resting-state functional connectivity changes in aging apoE4 and apoE-KO mice. J Neurosci 34 , 13963-13975 (2014). van Meer, P., Acevedo, S. & Raber, J. Impairments in spatial memory retention of GFAP-apoE4 female mice. Behav Brain Res 176 , 372-375 (2007). Raber, J. , et al. Isoform-specific effects of human apolipoprotein E on brain function revealed in ApoE knockout mice: increased susceptibility of females. Proc Natl Acad Sci U S A 95 , 10914-10919 (1998). Hartman, R.E. , et al. Behavioral phenotyping of GFAP-apoE3 and -apoE4 transgenic mice: apoE4 mice show profound working memory impairments in the absence of Alzheimer's-like neuropathology. Exp Neurol 170 , 326-344 (2001). Alexander, D.M. , et al. The contribution of apolipoprotein E alleles on cognitive performance and dynamic neural activity over six decades. Biological psychology 75 , 229-238 (2007). Janssen, C.I. , et al. The Effect of a High-Fat Diet on Brain Plasticity, Inflammation and Cognition in Female ApoE4-Knockin and ApoE-Knockout Mice. PLoS One 11 , e0155307 (2016). Jones, N.S., Watson, K.Q. & Rebeck, G.W. High-fat diet increases gliosis and immediate early gene expression in APOE3 mice, but not APOE4 mice. Journal of neuroinflammation 18 , 214 (2021). Nakamura, T., Hillary, F.G. & Biswal, B.B. Resting network plasticity following brain injury. PLoS One 4 , e8220 (2009). Roy, A. , et al. The evolution of cost-efficiency in neural networks during recovery from traumatic brain injury. PLoS One 12 , e0170541 (2017). Cone, J.J. , et al. Physiological state gates acquisition and expression of mesolimbic reward prediction signals. Proc Natl Acad Sci U S A 113 , 1943-1948 (2016). Cowley, M.A. , et al. The distribution and mechanism of action of ghrelin in the CNS demonstrates a novel hypothalamic circuit regulating energy homeostasis. Neuron 37 , 649-661 (2003). Krashes, M.J. , et al. Rapid, reversible activation of AgRP neurons drives feeding behavior in mice. The Journal of clinical investigation 121 , 1424-1428 (2011). Ste Marie, L., Luquet, S., Cole, T.B. & Palmiter, R.D. Modulation of neuropeptide Y expression in adult mice does not affect feeding. Proc Natl Acad Sci U S A 102 , 18632-18637 (2005). Grill, H.J. Leptin and the systems neuroscience of meal size control. Front Neuroendocrinol 31 , 61-78 (2010). Fan, W., Boston, B.A., Kesterson, R.A., Hruby, V.J. & Cone, R.D. Role of melanocortinergic neurons in feeding and the agouti obesity syndrome. Nature 385 , 165-168 (1997). Aponte, Y., Atasoy, D. & Sternson, S.M. AGRP neurons are sufficient to orchestrate feeding behavior rapidly and without training. Nat Neurosci 14 , 351-355 (2011). Gropp, E. , et al. Agouti-related peptide-expressing neurons are mandatory for feeding. Nat Neurosci 8 , 1289-1291 (2005). Low, A.Y.T. , et al. Reverse-translational identification of a cerebellar satiation network. Nature 600 , 269-273 (2021). Gorges, M. , et al. Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI. Front Neurol 8 , 200 (2017). Liang, Z., King, J. & Zhang, N. Intrinsic organization of the anesthetized brain. J Neurosci 32 , 10183-10191 (2012). Vincent, J.L. , et al. Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447 , 83-86 (2007). Gozzi, A. & Schwarz, A.J. Large-scale functional connectivity networks in the rodent brain. NeuroImage 127 , 496-509 (2016). Guilfoyle, D.N. , et al. Functional connectivity fMRI in mouse brain at 7T using isoflurane. Journal of neuroscience methods 214 , 144-148 (2013). Jonckers, E. , et al. Different anesthesia regimes modulate the functional connectivity outcome in mice. Magn Reson Med 72 , 1103-1112 (2014). Additional Declarations Competing interest reported. CFF has a financial interest in Ekam Imaging, a company that makes radiofrequency electronics and holders for awake animal imaging. CFF and PK have a partnership interest in Ekam Solutions a company that develops 3D MRI atlases for animal research. Supplementary Files FigS1.ChangeinWeight.jpg Cite Share Download PDF Status: Published Journal Publication published 06 Nov, 2024 Read the published version in BMC Neuroscience → Version 1 posted Editorial decision: Revision requested 14 May, 2024 Editor assigned by journal 06 May, 2024 Submission checks completed at journal 06 May, 2024 First submitted to journal 28 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4339838","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":299143979,"identity":"adca3706-4e98-4d7c-b102-9f25e2385030","order_by":0,"name":"Bradley Colarusso","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Bradley","middleName":"","lastName":"Colarusso","suffix":""},{"id":299143982,"identity":"dd493f0d-2ad2-4ae5-8065-288675662f15","order_by":1,"name":"Richard Ortiz","email":"","orcid":"","institution":"New Mexico State University","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"","lastName":"Ortiz","suffix":""},{"id":299143985,"identity":"d665450f-422e-4184-96f3-e05560ac3dd0","order_by":2,"name":"Julian Yeboah","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"","lastName":"Yeboah","suffix":""},{"id":299143988,"identity":"a48d2b6a-6e3f-439f-841c-52878c2b4b99","order_by":3,"name":"Arnold Chang","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Arnold","middleName":"","lastName":"Chang","suffix":""},{"id":299143991,"identity":"6d0054d6-75a6-41d0-a2b6-6a5460134525","order_by":4,"name":"Megha Gupta","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Megha","middleName":"","lastName":"Gupta","suffix":""},{"id":299143994,"identity":"ed5d38c8-41d0-49e1-b351-f4479b832164","order_by":5,"name":"Praveen Kulkarni","email":"","orcid":"","institution":"Northeastern University","correspondingAuthor":false,"prefix":"","firstName":"Praveen","middleName":"","lastName":"Kulkarni","suffix":""},{"id":299143995,"identity":"4029a0ad-0769-4ac1-9c83-aeaaa708cf32","order_by":6,"name":"Craig F. Ferris","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIie3OIWsDMRTA8Rce3MxBbCpKv8KVwJjoel9lR+DUxORqRuDg6qZTKu4rRI2JiRyBqM4XNjEozJeqqS4XNdGMwsxE/uIRwvvBA0il/mXkww8GNLzlj395ajuERSCjYaMfRnYeASjMuYRKJLvFy1XJ3xp32D/PJpPOP+5gNtbmNGEGcbr5ZNXTuxOq39RT7TKxVlDzGCmAupE07OZye8uhby3RWc4xB1vFCV58eVJyFcix7Fp68OT4G8mIJ0SzQEwlXY6emChhFnE4rFLbWsBrK4R2tT+sEHwVIXTZkL00DyVVwsKinV93jd1hfj8fP0YIYOzgVCqVSv2hb4MGWgmI7IZLAAAAAElFTkSuQmCC","orcid":"","institution":"Northeastern University","correspondingAuthor":true,"prefix":"","firstName":"Craig","middleName":"F.","lastName":"Ferris","suffix":""}],"badges":[],"createdAt":"2024-04-29 02:45:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4339838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4339838/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12868-024-00901-z","type":"published","date":"2024-11-06T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":56477217,"identity":"f6c72291-b47c-4e68-875e-6016b52cdbca","added_by":"auto","created_at":"2024-05-14 17:46:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41148,"visible":true,"origin":"","legend":"\u003cp\u003eBarnes maze\u003c/p\u003e\n\u003cp\u003eShown is the time in sec (mean ± SD) or latency to find the goal box. Male wildtype (M/WT) were significantly slower than female \u003cem\u003eApoE ɛ4 \u003c/em\u003e(F/e4)\u003cem\u003e. \u003c/em\u003e* p \u0026lt;0.05\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4339838/v1/3b1ad398bf46b6da59fd7c0a.png"},{"id":56477220,"identity":"816bfe0e-4eb1-432d-a182-184259d17445","added_by":"auto","created_at":"2024-05-14 17:46:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":58665,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal connectivity\u003c/p\u003e\n\u003cp\u003eShown are bar graphs for the mean ± SD number of Degrees of functional connections for the whole brain and hippocampus together with a scatter plot of all brain areas represented in each. Male wildtype (M/WT) was significantly greater than all other experimental groups while female \u003cem\u003eApoE ɛ4 \u003c/em\u003e(F/e4) was significantly greater than male \u003cem\u003eApoE ɛ4 \u003c/em\u003e(M/e4) and female wildtype (F/WT). ** p\u0026lt;0.01; **** p\u0026lt;0.0001. \u0026nbsp;Brain areas comprising the whole brain and hippocampus can be found in the Supplementary Excel File S1.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4339838/v1/ca2b57a7340f7e486bee6446.png"},{"id":56477219,"identity":"77a03a90-d78c-44d4-a7c1-cd2461cf1bce","added_by":"auto","created_at":"2024-05-14 17:46:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73824,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal connectivity around feeding\u003c/p\u003e\n\u003cp\u003eShown are bar graphs for the mean ± SD number of Degrees of functional connections for the feeding neural circuit, hypothalamus and cerebellum together with a scatter plot of all brain areas represented in each. Labels are the same as Fig 2. * p\u0026lt;0.05; ** p\u0026lt;0.01; *** p\u0026lt;0.001; **** p\u0026lt;0.0001. Brain areas comprising the feeding circuit, hypothalamus and cerebellum can be found in the Supplementary Excel File S1.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4339838/v1/c040aea7e72bd0bba586bff5.png"},{"id":56477221,"identity":"b283e25f-61ed-49b5-afbc-ae3c3644cee4","added_by":"auto","created_at":"2024-05-14 17:46:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1865619,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal connectivity to select feeding nuclei\u003c/p\u003e\n\u003cp\u003eShown are bar graphs for the mean ± SD for the number of Degrees of functional connections for the three hypothalamic and cerebellar nuclei found to be key in regulating feeding behavior in rodents together with a scatter plot of their individual values. A network maps for the male wildtype (M/WT) of each is shown below. The three red circles represent the three brain areas from each brain region. The blue circles are the intra or within connections from these three nodes to their respective brain region, i.e. hypothalamus and cerebellum. The outer black dots are the extra or outside connections from these nodes to other brain areas. Nonsignificant (ns); * p\u0026lt;0.05; ** p\u0026lt;0.01; *** p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4339838/v1/f44c47f26d7f012b2969f513.png"},{"id":68749900,"identity":"65144621-adcc-4904-9098-2cf00ab13b4d","added_by":"auto","created_at":"2024-11-11 16:07:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2994794,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4339838/v1/ce6181da-c0b5-4d92-9d1f-526b806321c3.pdf"},{"id":56478785,"identity":"f09a01e6-33d6-4433-bd6b-e601f31aac87","added_by":"auto","created_at":"2024-05-14 17:54:53","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":99242,"visible":true,"origin":"","legend":"","description":"","filename":"FigS1.ChangeinWeight.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4339838/v1/ab67497f002cdcc5b57cb218.jpg"}],"financialInterests":"Competing interest reported. CFF has a financial interest in Ekam Imaging, a company that makes radiofrequency electronics and holders for awake animal imaging. CFF and PK have a partnership interest in Ekam Solutions a company that develops 3D MRI atlases for animal research.","formattedTitle":"APOE4 rat model of Alzheimer’s disease: sex differences, genetic risk and diet","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlzheimer's disease (AD) is the primary contributor to dementia among older individuals, impacting more than 35\u0026nbsp;million individuals globally \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Age stands out as the most influential factor in developing AD, as the likelihood of experiencing the disease increases twofold every five years after reaching the age of 65 \u003csup\u003e1\u003c/sup\u003e. Another notable risk factor, ranking second in importance, is the apolipoprotein E (\u003cem\u003eApoE\u003c/em\u003e) \u003cem\u003eɛ4\u003c/em\u003e allele \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. A majority of AD patients carry at least one of the two \u003cem\u003eApoE ɛ4\u003c/em\u003e alleles with women having a greater risk for future problems \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Indeed, there are several clinical studies on \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers reporting sex differences in cognition with aging. Females \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers are more likely to develop Alzheimer\u0026rsquo;s disease than male carriers \u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and females have a faster rate in declining memory as compared to males \u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eApoE ɛ4\u003c/em\u003e, primarily synthesized by glial cells, is involved in lipid metabolism and cholesterol transport \u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDysregulation in energy utilization associated with metabolic homeostasis that occurs with aging is a contributing factor to the pathophysiology of AD \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Age brings a gradual disruption in metabolism, something enhanced by obesity. Indeed, obesity caused by dietary habits is widely acknowledged as a significant contributor to the development and physiological mechanisms of AD. \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Preclinical studies show the \u0026ldquo;Western\u0026rdquo; diet, composed of high fat and sugar contributes to this pathology \u003csup\u003e\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Disease progression in rodent models of AD is exacerbated when a genetic background of \u003cem\u003eApoE ɛ4\u003c/em\u003e is combined with the protracted consumption of a high fat/high fructose diet (HFD/HSD) \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This model combining \u003cem\u003eApoE ɛ4\u003c/em\u003e plus HFD/HSD was used to develop sensors to analyze exhaled gas for small volatile lipids associated with AD \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and image progression of neurovascular dysfunction with aging \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the present study we hypothesized prolonged exposure to HFD/HSD would exacerbate disease progression in the human \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in (TGRA8960) rat. In a previous study, we reported 6-month-old male \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in rats, present with altered gray matter microarchitecture in the sensorimotor and limbic cortices with a decrease in cognitive function; however, 6-month-old female carriers showed little changes in water diffusivity and cognitive behavior but did show enhanced functional connectivity \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this study, looking at the added risk of a high fat, high sugar diet there was no evidence of cognitive dysfunction or functional connectivity in female or male \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers. Instead, male wild-type rats were most affected by the HFD/HSD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eAnimals\u003c/h2\u003e\n \u003cp\u003eMale wildtype (n\u0026thinsp;=\u0026thinsp;4), female wildtype (n\u0026thinsp;=\u0026thinsp;5) and human \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in (TGRA8960) male (n\u0026thinsp;=\u0026thinsp;5) and female (n\u0026thinsp;=\u0026thinsp;6) Sprague Dawley rats, ca. four months of age, were a gift from Inotiv (West Lafayette, Indiana, USA). All genotypes were studied on high fat, high sucrose diet. Rats were placed in Plexiglas cages, with one or two rats per cage, and were kept in a room with a temperature range of 22\u0026ndash;24\u0026deg;C and a 12-hour light-dark cycle (lights on at 07:00 a.m.). They had free access to food and water throughout the study. Following a week of acclimatization to the animal quarters, all rats were fed a high-fat, high-sucrose diet (HFD/HSD) for a duration of 120 days before undergoing testing, at which time they were approximately 240 days old. The specific diet used (TD.88137) was obtained from Envigo (South Easton, MA) and had the following composition by weight: 48.5% carbohydrates (with 34% of it being sucrose), 21.2% fat, 17.3% protein, and 0.2% cholesterol. Shown in \u003cstrong\u003eSupplementary Fig \u003cspan\u003eS1\u003c/span\u003e\u003c/strong\u003e are the change in body weights (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) for each of the experimental groups collected weekly over a ten-week period. The acquisition and welfare of all rats followed the guidelines outlined in the NIH Guide for the Care and Use of Laboratory Animals. The methods and procedures described in this study were approved in advance by the Northeastern University Institutional Animal Care and Use Committee, under protocol number 20-0627R. Northeastern University\u0026apos;s animal care and use program and housing facilities have received full accreditation from AAALAC, International. The protocols employed in this research adhered to the ARRIVE guidelines, which provide recommendations for reporting in vivo experiments in animal research \u003csup\u003e\u003cspan\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003eBarnes Maze\u003c/h2\u003e\n \u003cp\u003eThe Barnes Maze has been utilized to evaluate spatial learning and memory in different rodent models. A description of the assay as performed in our lab has been published \u003csup\u003e\u003cspan\u003e26\u003c/span\u003e, \u003cspan\u003e27\u003c/span\u003e\u003c/sup\u003e. In brief, the maze consists of a circular platform with 18 escape holes located around its perimeter. Beneath the platform, there was a removable goal box, positioned consistently across all trials. Before each trial, the rat was placed inside the goal box for 1 minute and then placed under a covered container at the center of the platform for 30 seconds. The container was then lifted to start the trial. During the acquisition trials, if the animals were unable to locate the goal box within the 4-minute test period, they were gently guided into the goal box and allowed to remain there for 1 minute. Subsequently, they were returned to their home cages between the three trials conducted each day over a span of four days. In evaluating the acquisition trials, all animals were assessed based on parameters such as goal box latency (the time taken for animals to enter the goal box), errors (defined as instances where animals investigated any non-goal box hole within 2 cm with their head directed towards the hole), error duration (the duration spent exploring non-goal box holes within 2 cm), and the distance traveled before entering the goal box. All animal behavior was recorded on video and analyzed for the time it took to find the goal box. The analysis was conducted manually by experimenters who were unaware of the treatment condition, and the results were further confirmed using ANY-maze\u0026reg; software for automated scoring (Stoelting, Wood Dale, IL, USA).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003eNeuroimaging\u003c/h2\u003e\n \u003cp\u003eImaging sessions were performed using a Bruker Biospec 7.0T/20-cm USR horizontal magnet (Bruker, Billerica, MA, USA) equipped with a 2 T/m magnetic field gradient insert (12 cm inner diameter) that had a rise time of 120 \u0026micro;s. The radio frequency signals were transmitted and received through a quadrature volume coil integrated into the animal restrainer (Ekam Imaging, Boston MA, USA) \u003csup\u003e\u003cspan\u003e28\u003c/span\u003e\u003c/sup\u003e. The animal restrainer was designed with a padded head support, eliminating the need for ear bars, thereby reducing animal discomfort and minimizing motion artifacts. All rats were imaged under 1\u0026ndash;2% isoflurane anesthesia, maintaining a respiratory rate of 40\u0026ndash;50 breaths per minute. At the start of each imaging session, a high-resolution anatomical dataset was acquired using the Rapid Acquisition, Relaxation Enhanced (RARE) pulse sequence with the following parameters: 35 slices with a thickness of 0.7 mm, a field of view (FOV) of 3 cm, matrix size of 256 \u0026times; 256, a repetition time (TR) of 3900 msec, an effective echo time (TE) of 48 msec, a number of excitations (NEX) of 3, and an acquisition time of 6 minutes and 14 seconds.\u003c/p\u003e\n \u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003eResting State Functional Connectivity\u003c/h2\u003e\n \u003cp\u003eScans were acquired using a spin-echo triple-shot EPI sequence with the following imaging parameters: matrix size of 96 x 96 x 20 (height x width x depth), a repetition time (TR) of 1000 msec, an echo time (TE) of 15 msec, voxel size of 0.312 x 0.312 x 1.2 mm, slice thickness of 1.2 mm, 200 repetitions, and a total acquisition time of 10 minutes. Preprocessing steps involved the combined use of Analysis of Functional NeuroImages (AFNI_17.1.12), FMRIB Software Library (FSL, v5.0.9), Deformable Registration via Attribute Matching and Mutual-Saliency Weighting (DRAMMS 1.4.1), and MATLAB software. Brain tissue masks were manually drawn using 3DSlicer and applied for skull-stripping. Motion outliers and spikes were identified and regressed out, followed by slice timing correction. Head motion correction was performed using the first volume as a reference, and normalization was achieved through affine registration to the 3D MRI Rat Brain Atlas. A total of 173 annotated brain regions from the atlas were used for segmentation. Subsequent steps included quality assurance, band-pass filtering (0.01Hz\u0026thinsp;~\u0026thinsp;0.1Hz) to reduce drift and noise, detrending, spatial smoothing (full width at half maximum\u0026thinsp;=\u0026thinsp;0.8mm), and nuisance regression using motion outliers, motion parameters, mean white matter, and cerebrospinal fluid time series as regressors.\u003c/p\u003e\n \u003cp\u003eThe region-to-region functional connectivity analysis involved calculating correlations in spontaneous BOLD fluctuations. Nodes represented specific brain regions of interest (ROIs), and edges represented connections between regions. Voxel time series data were averaged within each node based on residual images obtained from nuisance regression. Pearson\u0026apos;s correlation coefficients were computed across all pairs of nodes (14535 pairs) for each subject in all three groups to assess interregional temporal correlations. The resulting correlation values (ranging from \u0026minus;\u0026thinsp;1 to 1) were transformed using Fisher\u0026apos;s Z transform. Symmetric connectivity matrices of size 166 x 166 were constructed, with each entry representing the strength of an edge. Group-level analysis was conducted to examine functional connectivity in the experimental groups. Z-score matrices from one-group t-tests were subjected to K-nearest neighbors clustering to identify node clusters and resting state networks. A threshold of |Z|=2.3 was applied to remove weak or spurious connections between nodes for visualization purposes.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eResting State BOLD Functional Connectivity Analysis\u003c/em\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003eDegree Centrality\u003c/h2\u003e\n \u003cp\u003eThe network analysis was conducted using Gephi, which is an open-source software for network analysis and visualization (Bastian et al., 2009). The symmetric connectivity matrices of both the CBD and vehicle groups, consisting of absolute values, were imported into Gephi, and the edges were treated as undirected networks. Degree centrality analysis was employed to measure the number of connections each node had within the overall network. The formula for degree centrality (C_D) is defined as the sum of A_ij, which represents the number of edges between nodes i and j, with n representing the number of rows in the adjacency matrix A.\u003c/p\u003e\n \u003cdiv id=\"Equa\"\u003e\n \u003cdiv id=\"FileID_Equa\" name=\"EquationSource\"\u003e$${\\text{C}}_{\\text{D}}\\left(\\text{j}\\right)=\\sum _{\\text{j}=1}^{\\text{n}}{\\text{A}}_{\\text{i}\\text{j}}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eStatistics\u003c/h2\u003e\n \u003cp\u003eStatistical analysis for the graph theory analysis was performed using GraphPad Prism version 9.0.0 (86) software from GraphPad Software, San Diego, California, USA (\u003cspan\u003e\u003cspan\u003ewww.graphpad.com\u003c/span\u003e\u003c/span\u003e). Normality tests, such as Shapiro-Wilk\u0026apos;s test, were conducted to assess the normality assumption between group subregions. If the p-values for subregion degree centrality were greater than 0.05, it was assumed that the data followed a normal distribution. In such cases, paired t-tests were used to compare the degree centrality between the CBD and vehicle groups in different subregions. If there was evidence against the normality assumption, a nonparametric Wilcoxon signed-rank (WSR) test was performed instead.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCognition\u003c/h2\u003e \u003cp\u003eShown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e are data on cognitive performance in the Barnes Maze following four months of HFD/HSD for transgenic and wildtype rats. The bar graphs are the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD for the latency to enter the goal box. The scores are the pooled average of all four test periods. There were no significant differences between male and female \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers; neither was there any significant differences between wildtype males and females. A one-way ANOVA with multiple comparisons found a significant difference between the female \u003cem\u003eApoE ɛ4\u003c/em\u003e and male wildtype (p\u0026thinsp;=\u0026thinsp;0.045).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFunctional Connectivity\u003c/h2\u003e \u003cp\u003eGlobal brain connectivity as expressed in Degrees or number of connections (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) for each of the experimental conditions is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There was a significant main effect for genotype (two-way ANOVA, F\u003csub\u003e(3,498)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;166.1; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Tukey\u0026rsquo;s post hoc multiple comparison test showed male wildtype (M/WT) on HFD/HSD was significantly greater than all other experimental conditions (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Female \u003cem\u003eApoE ɛ4\u003c/em\u003e (F/AE), presented with the next highest number of Degrees that was significantly greater than male \u003cem\u003eApoE ɛ4\u003c/em\u003e and female wildtype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). There was no significant difference between male \u003cem\u003eApoE ɛ4\u003c/em\u003e and female wildtype. Global brain hippocampal connectivity is shown on Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There was a significant main effect for genotype (two-way ANOVA, F\u003csub\u003e(3,24)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;13.61; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The male wildtype were significantly greater than male \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and female wildtype (\u0026lt;\u0026thinsp;0.01), while female \u003cem\u003eApoE ɛ4\u003c/em\u003e were significantly greater than male \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and female wildtype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Given the hyperconnectivity of the male wildtype on HFD/HSD as compared to the other experimental conditions we analyzed the connectivity in the context of feeding behavior. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e is a list of brain areas taken from recent review by Alcantara et al., on the neural circuits governing the different phases of feeding Alcantara, Tapia, Aponte and Krashes \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The global connectivity for this neural circuit for each of the experimental conditions (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. There was a significant main effect for genotype (two-way ANOVA, F\u003csub\u003e(3,51)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;21.53; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Tukey\u0026rsquo;s post hoc test showed male wildtype on HFD/HSD was significantly greater than male \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), female wildtype (\u0026lt;\u0026thinsp;0.0001), and (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while female \u003cem\u003eApoE ɛ4\u003c/em\u003e was significantly great than male \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). A key region of the brain controlling feeding behavior is the hypothalamus shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Again, there was a main effect for genotype (F\u003csub\u003e(3,45)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;11.08; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Post hoc tests showed male wildtype was significantly greater than male \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), females wildtype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and female \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while female \u003cem\u003eApoE ɛ4\u003c/em\u003e was significantly greater than male \u003cem\u003eApoE ɛ4\u003c/em\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The cerebellum and the deep cerebellar nuclei have also been identified as contributing to the organization of feeding behavior and metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). There is a main effect for genotype (F\u003csub\u003e(3,57)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;52.30; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) with male wildtype connectivity is significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) greater than the other experimental conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDegrees for brain areas forming the neural circuit regulating feeding and metabolism\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Degrees of Connectivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eBrains areas involved in the three phases of eating behavior: procurement, consumption and termination\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain Areas\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale WT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale APOE4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale WT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFemale APOE4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eaccumbens core\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eaccumbens shell\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003earcuate nucleus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ebed nucleus stria terminalis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ecentral amygdaloid nucleus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003edorsal raphe\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003einsular ctx\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003elateral hypothalamus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003elocus coeruleus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eintermediate cerebellar nucleus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003elateral cerebellar nucleus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emedial cerebellar nucleus fastigial\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eparabrachial nucleus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eparaventricular nucleus hypothalamus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eparaventricular nucleus thalamus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eperiaqueductal gray thalamus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003esubstantia innominata\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eventral tegmental area\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ezona incerta\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe arcuate, lateral, and paraventricular nuclei of the hypothalamus and the deep cerebellar nuclei have a major role in controlling feeding \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The connectivity of these three hypothalamic and cerebellar nuclei is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The hypothalamic connectivity in male wildtype are not significantly different from the other experimental groups. In contrast the connectivity of the deep cerebellar nuclei are significantly greater than the other experimental groups. The intra and extra hypothalamic and cerebellar connectivity can be visualized by the network maps below the bar graphs. The circles are nodes, and the lines are edges. The inner blue nodes are the functional connections of the different nuclei to their immediate surroundings i.e. either other hypothalamic or cerebellar nuclei. The black nodes are functional connections to other brain areas.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study examined the intersection of both aging and diet as risk factors for AD with both male and female wildtype and \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in rats after four months on HFD/HSD or \u0026ldquo;Western\u0026rdquo; diet. At four months of age, all rats were put on the HFD/HSD diet ad libitum. Four months later a period equivalent to ca 8.7 human years \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e they were tested for cognitive behaviors and imaged for differences in resting state BOLD functional connectivity (rsFC). To our surprise male and female \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers were unaffected by the HFD/HSD diet as compared to wild-type rats; instead, it was the male wild-type, but not the female that showed behavioral and neuroradiological changes. These finding are discussed below with respect to preclinical and clinical studies on the behavior and neurobiology of \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers and the influence of diet.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBehavior\u003c/h2\u003e \u003cp\u003eEight-month-old male wildtype rats on HFD/HSD showed a modest deficit in cognitive function when evaluated in the Barnes maze while the male and female \u003cem\u003eApoE ɛ4\u003c/em\u003e carriers and female wildtype showed no deficits. In a previous study using the same genetic rat model we reported 6-month-old human \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in rats feed a normal diet were more likely to have cognitive and behavioral problems as compared to female carriers early in life \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In the same rat model, we reported 8-month-old female carriers on normal diet show enhanced microvascular density in the hippocampus hypothesized to be a neuroadaptive response helping to spare cognitive function \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. These and other studies on rodent models of \u003cem\u003eApoE ɛ4\u003c/em\u003e show genotype-specific changes in behavior and brain structure characteristics of early neurodegenerative pathology \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Given the risk associated with HFD/HSD for cardiovascular disease, Alzheimer\u0026rsquo;s disease, and early dementia, we hypothesized \u003cem\u003eApoE ɛ4\u003c/em\u003e male and female rats would show exacerbated signs of cognitive dysfunction. Instead, \u003cem\u003eApoE ɛ4\u003c/em\u003e male and female rats were spared the anticipated negative effects of the HFD/HSD, while wildtype males, but not females showed the most changes. Was the HFD/HSD protective in these 8-month-old \u003cem\u003eApoE ɛ4\u003c/em\u003e rats, evidence of antagonistic pleiotropy, i.e., genes that provide resilience for developmental maturation and reproduction but are detrimental in old age\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e? Indeed, Janssen et al., reported female \u003cem\u003eApoE ɛ4\u003c/em\u003e mice feed HFD/HSD showed no deficits in spatial learning together with a reduction in neuroinflammation in the hippocampus as compared to wildtype controls on HFD/HSD \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In a recent review on feeding behavior and metabolism, Alcantara and colleagues argue that evolution has driven a neurobiology that favors the overconsumption of calories during times of plenty to offset the dearth of calories during times of famine\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eApoE ɛ4\u0026rsquo;s\u003c/em\u003e role in lipid metabolism, transport of cholesterol and complex lipids needed in neural development, membrane maintenance, and repair would be essential in handling the lipid load in HFD/HSD \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Jones et al., studied the behavioral and metabolic changes in male and female human \u003cem\u003eApoE ɛ3\u003c/em\u003e and \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in mice fed HFD/HSD as compared to low fat diet and reported male \u003cem\u003eApoE ɛ4\u003c/em\u003e mice were more susceptible to metabolic disturbances but not female \u003cem\u003eApoE ɛ3\u003c/em\u003e and \u003cem\u003eApoE ɛ4\u003c/em\u003e mice \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. This is in contrast to our data that showed male \u003cem\u003eApoE ɛ4\u003c/em\u003e were unaffected by the HFD/HSD. The metabolic sensitivity of the male \u003cem\u003eApoE ɛ4\u003c/em\u003e mice to HFD/HSD but not female \u003cem\u003eApoE ɛ4\u003c/em\u003e mice was corroborated by Matter et al., with the added distinction that females showed impairment in cognitive function \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In a subsequent study, Jones, and coworkers feed \u003cem\u003eApoE ɛ3\u003c/em\u003e and \u003cem\u003eApoE ɛ4\u003c/em\u003e mice HFD/HSD for 12 weeks and found the \u003cem\u003eApoE ɛ3\u003c/em\u003e genotype but not \u003cem\u003eApoE ɛ4\u003c/em\u003e presented with significant neuroinflammation in the hippocampus as measured by activated microglia and astrocytes \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Interestingly, they argued the neuroinflammation was neuroprotective in the \u003cem\u003eApoE ɛ3\u003c/em\u003e mice creating a neuroadaptive response to the HFD/HSD that would be beneficial in the future. Unfortunately, in our studies on \u003cem\u003eApoE ɛ4\u003c/em\u003e rats we did not do postmortem histology looking for evidence of gliosis and neuroinflammation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFunctional Connectivity - Neural circuitry of feeding and metabolism\u003c/h2\u003e \u003cp\u003eMale wildtype showed whole brain hyperconnectivity as compared to the male carrier while the female \u003cem\u003eApoE ɛ4\u003c/em\u003e showed greater connectivity as compared to the female wildtype. The hyperconnectivity for the male wildtype on HFD/HSD was unexpected. However, in a previous study we reported female \u003cem\u003eApoE ɛ4\u003c/em\u003e rats at six months of age show hyperconnectivity in amygdala, paraventricular nucleus of the hypothalamus and ascending reticular activating system \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this study the male wildtype and female carrier both showed greater global hippocampal connectivity as compared to the male \u003cem\u003eApoE ɛ4\u003c/em\u003e carrier. As noted above this connectivity was not reflected in any change in cognitive function for females but may be associated with the deficit in learning for the male wildtype. In the latter case, the hyperconnectivity may reflect neuroplastic compensation in response to the early stages of brain injury and loss of function \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe sensitivity of the male wildtype to the HFD/HSD as measured by alterations in cognitive function and functional connectivity suggested the risk factor was not \u003cem\u003eApoE ɛ4\u003c/em\u003e, but instead, a metabolic disorder. While body weights were only recorded through the first 8\u0026ndash;9 weeks of HFD/HSD there were no significant changes between wildtype and carriers for either sex (\u003cb\u003eSupplementary Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). So obesity was not a contributing factor. Metabolism involves a balance in appetite and energy utilization. In a recent review conducted by Alcantara et al., a model was proposed that describes the interconnected neural circuitry responsible for regulating the different phases of feeding, including appetitive, consummatory, and terminating phases. \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The circuits that control feeding are complex and involve multiple regions of the brain, most notably the hypothalamus. Within the hypothalamus, various nuclei host distinct populations of neurons that have significant roles in controlling appetite and energy balance\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. These include neurons that respond to or produce orexigenic peptides such as ghrelin \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, and neuropeptide Y \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, and those that respond to or produce anorexigenic signaling molecules e.g. leptin \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e and melanocortin \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. More specifically, the arcuate nucleus is home to a specific group of neurons known as agouti-related peptide (agRP) neurons in the arcuate nucleus that play a central role \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e in regulating all aspects of feeding in coordination with other hypothalamic areas \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhen the many brain areas controlling feeding (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) are combined as a single hub it was the wild-type males on HFD/HSD that showed a significant global increase in connectivity exceeding all other experimental conditions. The global connectivity of the hypothalamus as a single node is also extensive in wildtype males and significantly greater than the other experimental conditions. However, the global connectivity of the three key hypothalamic areas i.e., acuate, lateral, and paraventricular nuclei, noted for their role in controlling the distinct phases of feeding present with only a modest number of connections and are not significantly different between experimental groups. A seminal paper by Low and colleagues identified neurons in the cerebellar nuclei, which are characterized by their unique molecular and topographical properties, were found to be activated in response to feeding and nutrient infusion resulting a decrease in food intake \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Activation of the deep cerebellar nuclei terminates feeding by altering dopaminergic signaling to the striatum. Our study looking at the interaction between genes and diet spotlighted these cerebellar nuclei e.g. lateral (dentate) intermediate (interposed) and medial (fastigial) and analyzed their connectivity. Indeed these cerebellar nuclei had an extensive network of connections far exceeding the hypothalamic nuclei but only in the male wildtype rats. How this hyperconnectivity is affecting feeding and metabolism in male wildtype is unknown.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe study was not designed to follow feeding and metabolism, points of interest only raised after analyzing the connectivity data. Circadian measures of feeding, metabolism, blood and urine chemistry for each experimental group would have enhanced our understanding of the effect of HFD/HSD on wild type and \u003cem\u003eApoE ɛ4 carriers\u003c/em\u003e and why this genetic rat model is resilient - an example of antagonistic pleiotropy? Equally important would have been the same four experimental groups but maintained on normal rat chow. Unfortunately the study had only a limited number of \u003cem\u003eApoE ɛ4\u003c/em\u003e rats preventing the study of controls on a normal diet. Hence all comparisons are with respect to HFD/HSD. What would be typical behavior or connectivity is uncertain. As noted above, there was no post-mortem histology to confirm the presence or absence of neuroinflammation as reported by Jones et al., \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Still another limitation was the collection of functional connectivity data under light isoflurane anesthesia to minimize motion and physiological stress \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. What constitutes a \u0026ldquo;resting state\u0026rdquo; condition in a head restrained, awake rodent could be debated. The administration of anesthesia can decrease the strength of the BOLD signal; however, it does not disrupt the connectivity between brain regions. This has been observed in various species and under different physiological conditions. \u003csup\u003e\u003cspan additionalcitationids=\"CR51 CR52 CR53\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSummary\u003c/h2\u003e \u003cp\u003eThe present study examined the effect of high fat, high sugar diet on male and female, wildtype and \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in rats with the expectation that carriers would present with deficits in cognition and functional connectivity. The results were unexpected. The genetic risk was overshadowed by the diet. Male wildtype rats were most sensitive to the HFD/HSD presenting with a deficit in cognitive performance and enhanced functional connectivity in neural circuitry associated with food consumption and metabolism. The deep cerebellar nuclei key in the regulation of feeding behavior showed hyperconnectivity in male wildtype but not in female wildtype or female and male \u003cem\u003eApoE ɛ4\u003c/em\u003e rats.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u0026nbsp;\u003c/strong\u003eCFF has a financial interest in Ekam Imaging, a company that makes radiofrequency electronics and holders for awake animal imaging. CFF and PK have a partnership interest in Ekam Solutions a company that develops 3D MRI atlases for animal research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and consent to participate: NA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publication: NA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability statement:\u0026nbsp;\u003c/strong\u003eThe dataset(s) supporting the conclusions of this article are included within the article and its additional Supplementary files\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u0026nbsp;\u003c/strong\u003eColarusso, Yeboah, and Gupta responsible for data acquisition, Ortiz, Chang, Kulkarni responsible for data analysis, Ferris manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Funding Source: \u0026nbsp;\u003c/strong\u003eInotiv,\u0026nbsp;West Lafayette, Indiana, USA:\u0026nbsp;Ekam Imaging, Boston MA USA\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extended our gratitude to Inotiv for providing\u0026nbsp;\u003cem\u003eApoE ɛ4\u003c/em\u003e rats and Ekam Imaging for supporting these imaging studies.\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAssociation, A.s. 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A high fat diet also adds to the risk of dementia and AD. In addition, there are sex differences as women carriers have a higher risk of an earlier onset and rapid decline in memory than men. The present study looked at the effect of the genetic risk of \u003cem\u003eApoE ɛ4\u003c/em\u003e together with a high fat/high fructose diet (HFD/HSD) on brain function in male and female rats using magnetic resonance imaging. We hypothesized female carriers would present with deficits in cognitive behavior together with changes in functional connectivity as compared to male carriers. Four-month-old wildtype and human \u003cem\u003eApoE ɛ4\u003c/em\u003e knock-in (TGRA8960), male and female Sprague Dawley rats were put on a HFD/HSD for four months. Afterwards they were imaged for changes in function using resting state BOLD functional connectivity. Images were registered to, and analyzed, using a 3D MRI rat atlas providing site-specific data on 173 different brain areas. Resting state functional connectivity showed male wildtype had greater connectivity between areas involved in feeding and metabolism while there were no differences between female and male carriers and wildtype females. The data were unexpected. The genetic risk was overshadowed by the diet. Male wildtype rats were most sensitive to the HFD/HSD presenting with a deficit in cognitive performance with enhanced functional connectivity in neural circuitry associated with food consumption and metabolism.\u003c/p\u003e","manuscriptTitle":"APOE4 rat model of Alzheimer’s disease: sex differences, genetic risk and diet","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-14 17:46:49","doi":"10.21203/rs.3.rs-4339838/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-14T22:31:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-06T08:37:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-06T08:37:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Neuroscience","date":"2024-04-29T02:43:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-neuroscience","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nros","sideBox":"Learn more about [BMC Neuroscience](http://bmcneurosci.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nros/default.aspx","title":"BMC Neuroscience","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"48d5015b-6229-426e-bcc8-f172d64df8db","owner":[],"postedDate":"May 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-11T16:01:15+00:00","versionOfRecord":{"articleIdentity":"rs-4339838","link":"https://doi.org/10.1186/s12868-024-00901-z","journal":{"identity":"bmc-neuroscience","isVorOnly":false,"title":"BMC Neuroscience"},"publishedOn":"2024-11-06 15:57:32","publishedOnDateReadable":"November 6th, 2024"},"versionCreatedAt":"2024-05-14 17:46:49","video":"","vorDoi":"10.1186/s12868-024-00901-z","vorDoiUrl":"https://doi.org/10.1186/s12868-024-00901-z","workflowStages":[]},"version":"v1","identity":"rs-4339838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4339838","identity":"rs-4339838","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}