Brain metabolic network covariance and aging in a mouse model of Alzheimer's disease

In vivo reactive astrocyte imaging using [18F]SMBT-1 in tauopathy and familial Alzheimer's disease mouse models: A multi-tracer study

BACKGROUND

Reactive astrocytes play an important role in the development of Alzheimer's disease and primary tauopathies. Here, we aimed to investigate the relationships between reactive astrocytes. Microgliosis and glucose metabolism with Tau and amyloid beta pathology by using multi-tracer imaging in widely used tauopathy and familial Alzheimer's disease mouse models.

RESULTS

Positron emission tomography imaging using [18F]PM-PBB3 (tau), [18F]florbetapir (amyloid-beta), [18F]SMBT-1 (monoamine oxidase-B), [18F]DPA-714 (translocator protein) and [18F]fluorodeoxyglucose was carried out in 3- and 7-month-old rTg4510 tau mice, 5 × FAD familial Alzheimer's disease mice and wild-type mice. Immunofluorescence staining was performed to validate the pathological distribution in the mouse brain after in vivo imaging. We found increased regional levels of [18F]PM-PBB3, [18F]SMBT-1, and [18F]DPA-714 and hypoglucose metabolism in the brains of 7-month-old rTg4510 mice compared to age-matched wild-type mice. Increased [18F]SMBT-1 uptake was observed in the brains of 3, 7-month-old 5 × FAD mice, with elevated regional [18F]florbetapir and [18F]DPA-714 uptakes in the brains of 7-month-old 5 × FAD mice, compared to age-matched wild-type mice. Positive correlations were shown between [18F]SMBT-1 and [18F]PM-PBB3, [18F]DPA-714 and [18F]PM-PBB3 in rTg4510 mice, and between [18F]florbetapir and [18F]DPA-714 SUVRs in 5 × FAD mice.

CONCLUSION

In summary, these findings provide in vivo evidence that reactive astrocytes, microglial activation, and cerebral hypoglucose metabolism are associated with tau and amyloid pathology development in animal models of tauopathy and familial Alzheimer's disease.

Levetiracetam modulates brain metabolic networks and transcriptomic signatures in the 5XFAD mouse model of Alzheimer's disease

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.