Browsing by Author "Ingraham, Cynthia"

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    Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging
    (Frontiers Media, 2022-08-17) Maharjan, Surendra; Tsai, Andy P.; Lin, Peter B.; Ingraham, Cynthia; Jewett, Megan R.; Landreth, Gary E.; Oblak, Adrian L.; Wang, Nian; Radiology and Imaging Sciences, School of Medicine
    Purpose: To evaluate the age-dependent microstructure changes in 5xFAD mice using high-resolution diffusion tensor imaging (DTI). Methods: The 5xFAD mice at 4, 7.5, and 12 months and the wild-type controls at 4 months were scanned at 9.4T using a 3D echo-planar imaging (EPI) pulse sequence with the isotropic spatial resolution of 100 μm. The b-value was 3000 s/mm2 for all the diffusion MRI scans. The samples were also acquired with a gradient echo pulse sequence at 50 μm isotropic resolution. The microstructure changes were quantified with DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD). The conventional histology was performed to validate with MRI findings. Results: The FA values (p = 0.028) showed significant differences in the cortex between wild-type (WT) and 5xFAD mice at 4 months, while hippocampus, anterior commissure, corpus callosum, and fornix showed no significant differences for either FA and MD. FA values of 5xFAD mice gradually decreased in cortex (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) and fornix (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) with aging. Both FA (p = 0.029) and MD (p = 0.037) demonstrated significant differences in corpus callosum between 4 and 12 months age old. FA and MD were not significantly different in the hippocampus or anterior commissure. The age-dependent microstructure alterations were better captured by FA when compared to MD. Conclusion: FA showed higher sensitivity to monitor amyloid deposition in 5xFAD mice. DTI may be utilized as a sensitive biomarker to monitor beta-amyloid progression for preclinical studies.
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    Comprehensive Evaluation of the 5XFAD Mouse Model for Preclinical Testing Applications: A MODEL-AD Study
    (Frontiers Media, 2021-07-23) Oblak, Adrian L.; Lin, Peter B.; Kotredes, Kevin P.; Pandey, Ravi S.; Garceau, Dylan; Williams, Harriet M.; Uyar, Asli; O’Rourke, Rita; O’Rourke, Sarah; Ingraham, Cynthia; Bednarczyk, Daria; Belanger, Melisa; Cope, Zackary A.; Little, Gabriela J.; Williams, Sean-Paul G.; Ash, Carl; Bleckert, Adam; Ragan, Tim; Logsdon, Benjamin A.; Mangravite, Lara M.; Sukoff Rizzo, Stacey J.; Territo, Paul R.; Carter, Gregory W.; Howell, Gareth R.; Sasner, Michael; Lamb, Bruce T.; Radiology and Imaging Sciences, School of Medicine
    The ability to investigate therapeutic interventions in animal models of neurodegenerative diseases depends on extensive characterization of the model(s) being used. There are numerous models that have been generated to study Alzheimer’s disease (AD) and the underlying pathogenesis of the disease. While transgenic models have been instrumental in understanding AD mechanisms and risk factors, they are limited in the degree of characteristics displayed in comparison with AD in humans, and the full spectrum of AD effects has yet to be recapitulated in a single mouse model. The Model Organism Development and Evaluation for Late-Onset Alzheimer’s Disease (MODEL-AD) consortium was assembled by the National Institute on Aging (NIA) to develop more robust animal models of AD with increased relevance to human disease, standardize the characterization of AD mouse models, improve preclinical testing in animals, and establish clinically relevant AD biomarkers, among other aims toward enhancing the translational value of AD models in clinical drug design and treatment development. Here we have conducted a detailed characterization of the 5XFAD mouse, including transcriptomics, electroencephalogram, in vivo imaging, biochemical characterization, and behavioral assessments. The data from this study is publicly available through the AD Knowledge Portal.
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    Corrigendum: Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging
    (Frontiers Media, 2022-10-13) Maharjan, Surendra; Tsai, Andy P.; Lin, Peter B.; Ingraham, Cynthia; Jewett, Megan R.; Landreth, Gary E.; Oblak, Adrian L.; Wang, Nian; Radiology and Imaging Sciences, School of Medicine
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    Corrigendum: Uncovering Disease Mechanisms in a Novel Mouse Model Expressing Humanized APOEε4 and Trem2*R47H
    (Frontiers Media, 2022-02-07) Kotredes, Kevin P.; Oblak, Adrian; Pandey, Ravi S.; Lin, Peter Bor-Chian; Garceau, Dylan; Williams, Harriet; Uyar, Asli; O’Rourke, Rita; O’Rourke, Sarah; Ingraham, Cynthia; Bednarczyk, Daria; Belanger, Melisa; Cope, Zackary; Foley, Kate E.; Logsdon, Benjamin A.; Mangravite, Lara M.; Sukoff Rizzo, Stacey J.; Territo, Paul R.; Carter, Gregory W.; Sasner, Michael; Lamb, Bruce T.; Howell, Gareth R.; Pharmacology and Toxicology, School of Medicine
    An author name was incorrectly spelled as “Daria Bednarycek”. The correct spelling is “Daria Bednarczyk”. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
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    Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer's Disease-Relevant Phenotypes in Mice
    (Frontiers Media, 2022-06-24) Oblak, Adrian L.; Kotredes, Kevin P.; Pandey, Ravi S.; Reagan, Alaina M.; Ingraham, Cynthia; Perkins, Bridget; Lloyd, Christopher; Baker, Deborah; Lin, Peter B.; Soni, Disha M.; Tsai, Andy P.; Persohn, Scott A.; Bedwell, Amanda A.; Eldridge, Kierra; Speedy, Rachael; Meyer, Jill A.; Peters, Johnathan S.; Figueiredo, Lucas L.; Sasner, Michael; Territo, Paul R.; Sukoff Rizzo, Stacey J.; Carter, Gregory W.; Lamb, Bruce T.; Howell, Gareth R.; Radiology and Imaging Sciences, School of Medicine
    Obesity is recognized as a significant risk factor for Alzheimer's disease (AD). Studies have supported the notion that obesity accelerates AD-related pathophysiology in mouse models of AD. The majority of studies, to date, have focused on the use of early-onset AD models. Here, we evaluate the impact of genetic risk factors on late-onset AD (LOAD) in mice fed with a high fat/high sugar diet (HFD). We focused on three mouse models created through the IU/JAX/PITT MODEL-AD Center. These included a combined risk model with APOE4 and a variant in triggering receptor expressed on myeloid cells 2 (Trem2R47H ). We have termed this model, LOAD1. Additional variants including the M28L variant in phospholipase C Gamma 2 (Plcg2M28L ) and the 677C > T variant in methylenetetrahydrofolate reductase (Mthfr 677C > T ) were engineered by CRISPR onto LOAD1 to generate LOAD1.Plcg2M28L and LOAD1.Mthfr 677C > T . At 2 months of age, animals were placed on an HFD that induces obesity or a control diet (CD), until 12 months of age. Throughout the study, blood was collected to assess the levels of cholesterol and glucose. Positron emission tomography/computed tomography (PET/CT) was completed prior to sacrifice to image for glucose utilization and brain perfusion. After the completion of the study, blood and brains were collected for analysis. As expected, animals fed a HFD, showed a significant increase in body weight compared to those fed a CD. Glucose increased as a function of HFD in females only with cholesterol increasing in both sexes. Interestingly, LOAD1.Plcg2M28L demonstrated an increase in microglia density and alterations in regional brain glucose and perfusion on HFD. These changes were not observed in LOAD1 or LOAD1.Mthfr 677C > T animals fed with HFD. Furthermore, LOAD1.Plcg2M28L but not LOAD1.Mthfr 677C > T or LOAD1 animals showed transcriptomics correlations with human AD modules. Our results show that HFD affects the brain in a genotype-specific manner. Further insight into this process may have significant implications for the development of lifestyle interventions for the treatment of AD.
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    Uncovering Disease Mechanisms in a Novel Mouse Model Expressing Humanized APOEε4 and Trem2*R47H
    (Frontiers Media, 2021-10-11) Kotredes, Kevin P.; Oblak, Adrian; Pandey, Ravi S.; Lin, Peter Bor-Chian; Garceau, Dylan; Williams, Harriet; Uyar, Asli; O’Rourke, Rita; O’Rourke, Sarah; Ingraham, Cynthia; Bednarczyk, Daria; Belanger, Melisa; Cope, Zackary; Foley, Kate E.; Logsdon, Benjamin A.; Mangravite, Lara M.; Sukoff Rizzo, Stacey J.; Territo, Paul R.; Carter, Gregory W.; Sasner, Michael; Lamb, Bruce T.; Howell, Gareth R.; Radiology and Imaging Sciences, School of Medicine
    Late-onset Alzheimer’s disease (AD; LOAD) is the most common human neurodegenerative disease, however, the availability and efficacy of disease-modifying interventions is severely lacking. Despite exceptional efforts to understand disease progression via legacy amyloidogenic transgene mouse models, focus on disease translation with innovative mouse strains that better model the complexity of human AD is required to accelerate the development of future treatment modalities. LOAD within the human population is a polygenic and environmentally influenced disease with many risk factors acting in concert to produce disease processes parallel to those often muted by the early and aggressive aggregate formation in popular mouse strains. In addition to extracellular deposits of amyloid plaques and inclusions of the microtubule-associated protein tau, AD is also defined by synaptic/neuronal loss, vascular deficits, and neuroinflammation. These underlying processes need to be better defined, how the disease progresses with age, and compared to human-relevant outcomes. To create more translatable mouse models, MODEL-AD (Model Organism Development and Evaluation for Late-onset AD) groups are identifying and integrating disease-relevant, humanized gene sequences from public databases beginning with APOEε4 and Trem2*R47H, two of the most powerful risk factors present in human LOAD populations. Mice expressing endogenous, humanized APOEε4 and Trem2*R47H gene sequences were extensively aged and assayed using a multi-disciplined phenotyping approach associated with and relative to human AD pathology. Robust analytical pipelines measured behavioral, transcriptomic, metabolic, and neuropathological phenotypes in cross-sectional cohorts for progression of disease hallmarks at all life stages. In vivo PET/MRI neuroimaging revealed regional alterations in glycolytic metabolism and vascular perfusion. Transcriptional profiling by RNA-Seq of brain hemispheres identified sex and age as the main sources of variation between genotypes including age-specific enrichment of AD-related processes. Similarly, age was the strongest determinant of behavioral change. In the absence of mouse amyloid plaque formation, many of the hallmarks of AD were not observed in this strain. However, as a sensitized baseline model with many additional alleles and environmental modifications already appended, the dataset from this initial MODEL-AD strain serves an important role in establishing the individual effects and interaction between two strong genetic risk factors for LOAD in a mouse host.