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,
imaging, biochemical characterization, and behavioral assessments. The data from this study is publicly available through the AD Knowledge Portal.
Isolated proteins, especially membrane proteins, are susceptible to aggregation and activity loss after purification. For therapeutics and biosensors usage, protein stability and longevity are ...especially important. It has been demonstrated that photosystem I (PSI) can be successfully integrated into biohybrid electronic devices to take advantage of its strong light-driven reducing potential (−1.2V vs. the Standard Hydrogen Electrode). Most devices utilize PSI isolated in a nanosize detergent micelle, which is difficult to visualize, quantitate, and manipulate. Isolated PSI is also susceptible to aggregation and/or loss of activity, especially after freeze/thaw cycles. CaCO3 microspheres (CCMs) have been shown to be a robust method of protein encapsulation for industrial and pharmaceutical applications, increasing the stability and activity of the encapsulated protein. However, CCMs have not been utilized with any membrane protein(s) to date. Herein, we examine the encapsulation of detergent-solubilized PSI in CCMs yielding uniform, monodisperse, mesoporous microspheres. This study reports both the first encapsulation of a membrane protein and also the largest protein to date stabilized by CCMs. These microspheres retain their spectral properties and lumenal surface exposure and are active when integrated into hybrid biophotovoltaic devices. CCMs may be a robust yet simple solution for long-term storage of large membrane proteins, showing success for very large, multisubunit complexes like PSI.
Membrane proteins represent >25% of most genomes. The largest membrane protein with a known structure is photosystem I (PSI), which is of interest for biotechnological applications for its photogenerated reducing potential. Most membrane proteins are isolated using detergents, rendering them prone to activity loss and degradation. We report a method for stabilization of PSI in uniform, non-aggregating mesoporous microspheres based on CaCO3 templates with retained photochemical activity and improved stability and activity when incorporated in biohybrid photovoltaic devices. Display omitted
Introduction
Alzheimer's disease (AD) is the most common form of dementia. Beta‐secretase (BACE) inhibitors have been proposed as potential therapeutic interventions; however, initiating treatment ...once disease has significantly progressed has failed to effectively stop or treat disease. Whether BACE inhibition may have efficacy when administered prophylactically in the early stages of AD has been under‐investigated. The present studies aimed to evaluate prophylactic treatment of the BACE inhibitor verubecestat in an AD mouse model using the National Institute on Aging (NIA) resources of the Model Organism Development for Late‐Onset Alzheimer's Disease (MODEL‐AD) Preclinical Testing Core (PTC) Drug Screening Pipeline.
Methods
5XFAD mice were administered verubecestat ad libitum in chow from 3 to 6 months of age, prior to the onset of significant disease pathology. Following treatment (6 months of age), in vivo imaging was conducted with 18F‐florbetapir (AV‐45/Amyvid) (18F‐AV45) and 18‐FDG (fluorodeoxyglucose)–PET (positron emission tomography)/MRI (magnetic resonance imaging), brain and plasma amyloid beta (Aβ) were measured, and the clinical and behavioral characteristics of the mice were assessed and correlated with the pharmacokinetic data.
Results
Prophylactic verubecestat treatment resulted in dose‐ and region‐dependent attenuations of 18F‐AV45 uptake in male and female 5XFAD mice. Plasma Aβ40 and Aβ42 were also dose‐dependently attenuated with treatment. Across the dose range evaluated, side effects including coat color changes and motor alterations were reported, in the absence of cognitive improvement or changes in 18F‐FDG uptake.
Discussion
Prophylactic treatment with verubecestat resulted in attenuated amyloid plaque deposition when treatment was initiated prior to significant pathology in 5XFAD mice. At the same dose range effective at attenuating Aβ levels, verubecestat produced side effects in the absence of improvements in cognitive function. Taken together these data demonstrate the rigorous translational approaches of the MODEL‐AD PTC for interrogating potential therapeutics and provide insight into the limitations of verubecestat as a prophylactic intervention for early‐stage AD.
Abstract
Background
The failure of most clinical Alzheimer’s disease (AD) trials has been partially attributed to the lack of translatability of current AD mouse models to human patients. A recently ...developed model of familial AD (fAD), expressing Swedish, Arctic and Austrian mutations in App (hAbeta
SAA
), has been shown to be a useful amyloidogenic model which recapitulates many aspects of human AD, including plaque distribution and microglial transcriptional changes. Our aim is to further characterize the hAbeta
SAA
model and compare it to the widely used 5xFAD transgenic model.
Method
Motion Sequencing (MoSeq) software was used to model the underlying structure of spontaneous behaviors recorded in an open field in hAbeta
SAA
and 5xFAD mice longitudinally from 10 to 18 months of age. Aged hAbeta
SAA
and 5xFAD brain tissue was used for spatial transcriptomic/proteomic profiling, performed by Nanostring’s GeoMx®, which allowed for quantification of gene and protein expression in plaque‐associated and non‐plaque‐associated regions of interest. A fluorophore‐conjugated amyloid antibody (Methoxy‐X04) was administered to cohorts of hAbeta
SAA
and 5xFAD prior to harvest at various ages. An additional fluorophore‐conjugated antibody (lectin Dylight®594) was administered to 19‐month‐old cohorts permitting visualization of cerebral amyloid angiopathy (CAA). Whole brains were sectioned/imaged using Serial Two‐Photon Tomography on the TissueCyte (TissueVision), creating indexed tissue sections and high‐resolution 3D models of each brain. Subsequent rounds of staining permitted characterization of disease‐associated microglia (DAM) and dystrophic neurites. An independent cohort was evaluated for EEG telemetry.
Result
MoSeq revealed divergent behaviors of 5xFAD and hAbeta
SAA
mice suggesting differences in behavioral phenotypes of these two models. Preliminary GeoMx data shows upregulation of DAM genes localized to plaques in hAbeta
SAA
homozygotes as identified by RNA‐seq; correlating 5xFAD data is in progress. Further assessments of bulk RNA‐Seq, amyloid distribution, CAA burden and cortical EEG spectral analysis are underway.
Conclusion
Comparison of hAbeta
SAA
and 5xFAD using innovative modes of assessment showcase hAbeta
SAA
as an amyloidogenic mouse model of fAD that aligns more closely with human than 5xFAD. This model is available for preclinical research with no licensing restrictions and is devoid of artifacts related to transgenic overexpression, positioning it as an improved mouse model for studying fAD mutations.
Background
The failure of most clinical Alzheimer’s disease (AD) trials has been partially attributed to the lack of translatability of current AD mouse models to human patients. A recently developed ...model of familial AD (fAD), expressing Swedish, Arctic and Austrian mutations in App (hAbetaSAA), has been shown to be a useful amyloidogenic model which recapitulates many aspects of human AD, including plaque distribution and microglial transcriptional changes. Our aim is to further characterize the hAbetaSAA model and compare it to the widely used 5xFAD transgenic model.
Method
Motion Sequencing (MoSeq) software was used to model the underlying structure of spontaneous behaviors recorded in an open field in hAbetaSAA and 5xFAD mice longitudinally from 10 to 18 months of age. Aged hAbetaSAA and 5xFAD brain tissue was used for spatial transcriptomic/proteomic profiling, performed by Nanostring’s GeoMx®, which allowed for quantification of gene and protein expression in plaque‐associated and non‐plaque‐associated regions of interest. A fluorophore‐conjugated amyloid antibody (Methoxy‐X04) was administered to cohorts of hAbetaSAA and 5xFAD prior to harvest at various ages. An additional fluorophore‐conjugated antibody (lectin Dylight®594) was administered to 19‐month‐old cohorts permitting visualization of cerebral amyloid angiopathy (CAA). Whole brains were sectioned/imaged using Serial Two‐Photon Tomography on the TissueCyte (TissueVision), creating indexed tissue sections and high‐resolution 3D models of each brain. Subsequent rounds of staining permitted characterization of disease‐associated microglia (DAM) and dystrophic neurites. An independent cohort was evaluated for EEG telemetry.
Result
MoSeq revealed divergent behaviors of 5xFAD and hAbetaSAA mice suggesting differences in behavioral phenotypes of these two models. Preliminary GeoMx data shows upregulation of DAM genes localized to plaques in hAbetaSAA homozygotes as identified by RNA‐seq; correlating 5xFAD data is in progress. Further assessments of bulk RNA‐Seq, amyloid distribution, CAA burden and cortical EEG spectral analysis are underway.
Conclusion
Comparison of hAbetaSAA and 5xFAD using innovative modes of assessment showcase hAbetaSAA as an amyloidogenic mouse model of fAD that aligns more closely with human than 5xFAD. This model is available for preclinical research with no licensing restrictions and is devoid of artifacts related to transgenic overexpression, positioning it as an improved mouse model for studying fAD mutations.
Background
The ability to effectively translate therapeutic efficacy from the bench to clinical success for Alzheimer’s disease (AD) has been hampered in part due to limited recapitulation of the ...complexity of the disease in animal models. While analogous AD risk mutations have been engineered into animal models and have dominated the research field, these have primarily been familial, early onset risk alleles which do not capture the risk for AD for the majority of patients that present with sporadic late onset AD (LOAD).
Method
The IU/JAX/PITT MODEL‐AD consortium is focused on developing mouse models with genetic risk variants associated with LOAD, in combination with environmental risk factors and aging to enable improved translation. The present studies aimed to characterize mice expressing humanized Aβ in combination with multiple genetic risk factors (APOE4 and the R47H risk variant in the Trem2 gene; LOAD2) and aged in the presence of a high‐fat, high‐sugar diet (HFD).
Result
LOAD2 mice exposed to HFD from adolescence (LOAD2+HFD) demonstrated aging changes relative to LOAD2 mice in the absence of HFD, including presentation of insoluble Aβ42 in brain and plasma, and increased inflammatory cytokines. 12‐month aged LOAD2+HFD mice also demonstrated increased NfL in CSF, as well as vascular and perfusion changes as measured by PET/MRI. By 18 months, LOAD2+HFD mice demonstrated reductions in hippocampal neurons as well as cognitive impairment relative to LOAD2 mice in the absence of HFD on a translational touchscreen task. Intriguingly, gene expression profiles and proteomic signatures of aged LOAD2+HFD mice aligned with ‘omics signatures of AD patients in the absence of core neuritic plaques, which were not detected up to 24 months of age.
Conclusion
Mice with genetic risk for LOAD coupled with environmental risk factors demonstrate aging‐dependent changes in line with a spectrum and trajectory of features of clinical LOAD. From a precision medicine approach, our MODEL‐AD Preclinical Testing Core and our TREAT‐AD colleagues are prioritizing LOAD2+HFD mice as an important model system for evaluating the therapeutic potential of non‐amyloid targeting therapeutics as well as for prophylactic interventions initiated prior to significant amyloid accumulation.
Background
The Preclinical Testing Core (PTC) of the Model Organism Development for Evaluation of Late Onset Alzheimer’s Disease (MODEL‐AD) consortium established a rigorous preclinical drug testing ...strategy with go/no‐go decision points that permits unbiased assessments of therapeutic agents. As part of the pipeline validation, the chimeric murinized therapeutic antibody aducanumab (chAducanumab), was selected for evaluation in 5XFAD mice.
Methods
Initial PK modeling and simulation was guided by literature and Aβ reductions from a pilot cohort of 9 month aged 5XFAD mice following 1x/week treatment of 30 mg/kg chAducanumab for 4 weeks. These pilot data were used to inform the chronic dosing regimen for the PD study which started at an age in 5XFAD mice where significant amyloid plaque accumulation was present (9 mos). PD endpoints (n=10‐12/sex/genotype/treatment) were assessed at the conclusion of chronic treatment, and included: 18‐FDG and 18F‐AV45 PET/CT, autoradiography, immunohistochemistry, AB40 and AB42 in plasma and brain fractions, and a behavioral battery. An additional cohort was enrolled for comprehensive cognitive testing using touchscreen learning and pattern separation tasks and evaluated for electroencephalography (EEG) activity using wireless telemetry.
Results
PK/PD modeling revealed slow clearance of chAducanumab following IP dosing with a T1/2 of ∼2.5 days. Therefore, the dose regimen for chronic PD studies included 0.1, 1.56, and 30 mg/kg administered 1x weekly for 12 weeks. Treatment with chAducanumab resulted in dose‐ and sex‐dependent reduction in amyloid deposition via 18F‐AV45 PET. Glucose uptake via 18F‐FDG PET similarly showed a dose dependent reversal of glycolytic loss in key brain regions. Cognitive assessments indicated no effect on learning however an improvement in pattern separation was observed with chAducanumab in females but not males. EEG analysis revealed improvements in delta, alpha, and beta oscillations with chAducanumab treatment. Multi‐omics analysis are in progress.
Conclusions
chAducanumab treatment in 5XFAD mice resulted in the expected reductions in brain amyloid consistent with clinical findings. Moreover, chAducanumab showed a unique glycolytic restoration profile in 5XFAD mice and improvements in some aspects of cognitive function. Together these data positively support pipeline validation of the MODEL‐AD PTC for evaluating therapeutic antibodies.
Several professional organizations recommend conducting genetic testing as part of the autism diagnosis process, as it can provide additional information and benefits for autistic people and their ...families. However, there is disagreement among autism communities about whether genetic testing reflects autistic people's best interests. In practice, rates of clinical genetic testing for autism are much lower than diagnoses, creating a large gap between clinical guidelines and real clinical encounters. To investigate one potential source of this gap, we interviewed 14 healthcare providers about the autism diagnostic process and their actions related to autism genetic testing. We recruited a sample of primarily Ph.D. level-psychologists and analyzed our qualitative data using a five-step framework analysis method. Participants generally had positive or mixed views of genetic testing in autism. They described their current experiences of implementation of genetic testing, including that they did not often find it changed their clinical practice. Only some providers recommended it to everyone receiving an autism diagnosis. They also listed factors which discourage families from getting testing, including high costs, families feeling overwhelmed, other support needs taking priority, and ethical implications. Notably, providers highlighted a trend of referring patients to research genetic testing rather than clinical testing, which may provide a cheaper and easier alternative but is not likely to return results to participants. Finally, participants felt they needed more training in genetics and listed specific topics of uncertainty. Our research highlights a need to further educate clinicians in the uses and limitations of genetic testing for autism and suggests content areas of focus for genetics educators.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The inability to accurately, efficiently label large, open-access medical imaging datasets limits the widespread implementation of artificial intelligence models in healthcare. There have been few ...attempts, however, to automate the annotation of such public databases; one approach, for example, focused on labor-intensive, manual labeling of subsets of these datasets to be used to train new models. In this study, we describe a method for standardized, automated labeling based on similarity to a previously validated, explainable AI (xAI) model-derived-atlas, for which the user can specify a quantitative threshold for a desired level of accuracy (the probability-of-similarity, pSim metric). We show that our xAI model, by calculating the pSim values for each clinical output label based on comparison to its training-set derived reference atlas, can automatically label the external datasets to a user-selected, high level of accuracy, equaling or exceeding that of human experts. We additionally show that, by fine-tuning the original model using the automatically labelled exams for retraining, performance can be preserved or improved, resulting in a highly accurate, more generalized model.
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