Browsing by Author "Burton, Charles P."

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    Assessment of Neurovascular Uncoupling: APOE Status is a Key Driver of Early Metabolic and Vascular Dysfunction
    (bioRxiv, 2024-03-13) Onos, Kristen; Lin, Peter B.; Pandey, Ravi S.; Persohn, Scott A.; Burton, Charles P.; Miner, Ethan W.; Eldridge, Kierra; Nyandu Kanyinda, Jonathan; Foley, Kate E.; Carter, Gregory W.; Howell, Gareth R.; Territo, Paul R.; Neurology, School of Medicine
    Background: Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein ε4 (APOEε4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection. Methods: PET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology. Results: All hAPOE strains showed AD phenotype progression by 8 mo, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (↓ glucose uptake, ↑ perfusion) at 8 and 12 mo, while APOEε3/ε4 demonstrated Type-2 uncoupling (↑ glucose uptake, ↓ perfusion), while immunopathology confirmed cell specific contributions. Discussion: This work highlights APOEε4 status in AD progression manifest as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker.
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    Assessment of neurovascular uncoupling: APOE status is a key driver of early metabolic and vascular dysfunction
    (Wiley, 2024) Onos, Kristen D.; Lin, Peter B.; Pandey, Ravi S.; Persohn, Scott A.; Burton, Charles P.; Miner, Ethan W.; Eldridge, Kierra; Nyandu Kanyind, Jonathan; Foley, Kate E.; Carter, Gregory W.; Howell, Gareth R.; Territo, Paul R.; Neurology, School of Medicine
    Background: Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein Eε4 (APOEε4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection. Methods: PET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology. Results: All hAPOE strains showed AD phenotype progression by 8 months, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (↓ glucose uptake, ↑ perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated Type-2 uncoupling (↑ glucose uptake, ↓ perfusion), while immunopathology confirmed cell specific contributions. Discussion: This work highlights APOEε4 status in AD progression manifests as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker. Highlights: We developed a novel analytical method to analyze PET imaging of 18F-FDG and 64Cu-PTSM data in both sexes of aging C57BL/6J, and hAPOEε3/ε3, hAPOEε4/ε4, and hAPOEε3/ε4 mice to assess metabolism-perfusion profiles termed neurovascular uncoupling. This analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (decreased glucose uptake, increased perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated significant Type-2 uncoupling (increased glucose uptake, decreased perfusion) by 8 months which aligns with immunopathology and transcriptomic signatures. This work highlights that there may be different mechanisms underlying age related changes in APOEε4/ε4 compared with APOEε3/ε4. We predict that these changes may be driven by immunological activation and response, and may serve as an early diagnostic biomarker.
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    Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease
    (Wiley, 2024) Chumin, Evgeny J.; Burton, Charles P.; Silvola, Rebecca; Miner, Ethan W.; Persohn, Scott C.; Veronese, Mattia; Territo, Paul R.; Medicine, School of Medicine
    Introduction: Alzheimer's disease (AD), the leading cause of dementia worldwide, represents a human and financial impact for which few effective drugs exist to treat the disease. Advances in molecular imaging have enabled assessment of cerebral glycolytic metabolism, and network modeling of brain region have linked to alterations in metabolic activity to AD stage. Methods: We performed 18 F-FDG positron emission tomography (PET) imaging in 4-, 6-, and 12-month-old 5XFAD and littermate controls (WT) of both sexes and analyzed region data via brain metabolic covariance analysis. Results: The 5XFAD model mice showed age-related changes in glucose uptake relative to WT mice. Analysis of community structure of covariance networks was different across age and sex, with a disruption of metabolic coupling in the 5XFAD model. Discussion: The current study replicates clinical AD findings and indicates that metabolic network covariance modeling provides a translational tool to assess disease progression in AD models.
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    Characterizing Molecular and Synaptic Signatures in mouse models of Late-Onset Alzheimer’s Disease Independent of Amyloid and Tau Pathology
    (bioRxiv, 2023-12-20) Kotredes, Kevin P.; Pandey, Ravi S.; Persohn, Scott; Elderidge, Kierra; Burton, Charles P.; Miner, Ethan W.; Haynes, Kathryn A.; Santos, Diogo Francisco S.; Williams, Sean-Paul; Heaton, Nicholas; Ingraham, Cynthia M.; Lloyd, Christopher; Garceau, Dylan; O’Rourke, Rita; Herrick, Sarah; Rangel-Barajas, Claudia; Maharjan, Surendra; Wang, Nian; Sasner, Michael; Lamb, Bruce T.; Territo, Paul R.; Sukoff Rizzo, Stacey J.; Carter, Gregory W.; Howell, Gareth R.; Oblak, Adrian L.; Medical and Molecular Genetics, School of Medicine
    Introduction: MODEL-AD is creating and distributing novel mouse models with humanized, clinically relevant genetic risk factors to more accurately mimic LOAD than commonly used transgenic models. Methods: We created the LOAD2 model by combining APOE4, Trem2*R47H, and humanized amyloid-beta. Mice aged up to 24 months were subjected to either a control diet or a high-fat/high-sugar diet (LOAD2+HFD) from two months of age. We assessed disease-relevant outcomes, including in vivo imaging, biomarkers, multi-omics, neuropathology, and behavior. Results: By 18 months, LOAD2+HFD mice exhibited cortical neuron loss, elevated insoluble brain Aβ42, increased plasma NfL, and altered gene/protein expression related to lipid metabolism and synaptic function. In vivo imaging showed age-dependent reductions in brain region volume and neurovascular uncoupling. LOAD2+HFD mice also displayed deficits in acquiring touchscreen-based cognitive tasks. Discussion: Collectively the comprehensive characterization of LOAD2+HFD mice reveal this model as important for preclinical studies that target features of LOAD independent of amyloid and tau.
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    Levetiracetam modulates brain metabolic networks and transcriptomic signatures in the 5XFAD mouse model of Alzheimer’s disease
    (Frontiers Media, 2024-01-24) Burton, Charles P.; Chumin, Evgeny J.; Collins, Alyssa Y.; Persohn, Scott A.; Onos, Kristen D.; Pandey, Ravi S.; Quinney, Sara K.; Territo, Paul R.; Radiology and Imaging Sciences, School of Medicine
    Introduction: Subcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer's disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core. Methods: Chronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling. Results: Pharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e., positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling. Discussion: This study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value toward informing clinical study design.
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    Levetiracetam Modulates Brain Metabolic Networks and Transcriptomic Signatures in the 5XFAD Mouse Model of Alzheimer’s disease
    (bioRxiv, 2023-12-07) Burton, Charles P.; Chumin, Evgeny J.; Collins, Alyssa Y.; Persohn, Scott A.; Onos, Kristen D.; Pandey, Ravi S.; Quinney, Sara K.; Territo, Paul R.; Radiology and Imaging Sciences, School of Medicine
    Introduction: Subcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer's disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core. Methods: Chronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling. Results: Pharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e. positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling. Discussion: This study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration- dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value towards informing clinical study design.