Alzheimer’s Disease (AD) has a strong spatial-temporal component to its progression, where different brain regions are affected by amyloid-beta (Aβ) plaque deposition at varying time points and in distinct cell types. Standard imaging and analysis platforms can neglect these details, as they lack the ability to pair high-yield whole-brain imaging with region-specific or high-resolution analysis. Here we describe a novel high-throughput whole-brain imaging pipeline to quantitatively track plaque progression as a function of brain region across time, while also producing indexed tissue sections for secondary staining and analysis that can be registered back to the original brain image. Aβ plaques in novel knock-in mouse models of familial AD were labeled with Methoxy-X04, an Aβ plaque-specific compound. In some cases, brain vasculature was also labelled with DyLight. The brains were processed on the TissueCyte Serial Two-Photon Plus (STP+) imaging platform to produce fully aligned multi-channel volumetric datasets, yielding high resolution 3D models of each brain. Registration to the Allen Mouse Brain Common Coordinate Framework (CCFv3) and region-specific plaque analysis were conducted to determine plaque size, density, and total number per brain region. By correlating Methoxy and DyLight signals, cerebral amyloid angiopathy (CAA) was also quantified. Indexed brain sections were then used for iterative immunolabeling (IBEX; see Radtke et al, Nat Protocols 2022) to detect vascular and cellular responses to amyloid on representative sections and remapped to the original 3D whole-brain dataset. The analysis of whole-brain plaque distribution in familial AD mouse models revealed distinct spatial-temporal changes across the brains. STP+ imaging, combined with CCFv3 mapping and secondary analysis of microglial and astrocytic markers allowed for targeted evaluation of Aβ plaques, vascular pathology, and a comparison of regional molecular changes between models. We demonstrate here that the high sensitivity and precision of the STP+ platform coupled with secondary analysis of cellular responses can facilitate mechanistic understanding of amyloid deposition and cellular responses associated with specific therapeutic approaches. This approach could be very useful to study amyloid-related imaging abnormalities (ARIA) in preclinical models.

Amyloid-beta (Aß) plaque deposition in the brain represents a significant hallmark of Alzheimer’s Disease (AD). Standard laboratory approaches assessing Aß lack the ability to pair high-throughput whole-organ imaging with region-specific quantitation, and often require tissue homogenization. To analyze changes in Aß spatiotemporally, we developed a novel Serial Two-Photon Plus (STP2) pipeline to quantify plaque progression and depression as a function of brain region, resulting in indexed brain sections for secondary analysis using MALDI HiPLEX-IHC with imaging mass spectrometry (IMS). Plaques in the well characterized 5XFAD mouse model of AD were labeled with Methoxy-X04, an Aß plaque-specific compound, prior to transcardial perfusion and whole-brain excision. The STP2 platform uses a TissueCyte system to produce high-resolution multi-channel datasets, yielding 3D models of each brain. The Allen Mouse Brain Common Coordinate Framework (CCFv3) was registered to each brain, and our automated pipeline quantified plaque load and density per brain region. Select resulting sections were analyzed using AmberGen MALDI HiPLEX-IHC and Bruker Daltonics IMS for Aß42, pTau, GFAP, GLUT1, MBP, NeuN, NF-L, PVALB, SNCA and SYN-I. Quantifying baseload plaque distribution in the 5XFAD model at 2, 3, 4, and 6-months revealed significant changes in density of Aß plaques both spatially and temporally. STP2 imaging, combined with CCFv3 mapping and secondary proteomic analysis allows for targeted evaluation of compound treatment on the Aß plaques. The STP2 pipeline produces translational high-throughput pre-clinical AD data with enhanced sensitivity and precision, with resulting sections remaining in-tact for further secondary analysis of spatial proteomics and pharmacodynamics in the brain.

Alzheimer’s Disease (AD) has a strong spatial-temporal component to its progression, where different brain regions are affected by amyloid-beta (Aβ) plaque deposition at varying time points. Standard imaging and analysis platforms can neglect these details, as they lack the ability to pair high-yield whole-brain imaging with region-specific quantitation. Furthermore, many Aβ analyses require homogenization of tissue, prohibiting secondary analysis. To address this gap, we have developed a novel high-throughput whole-brain imaging pipeline for pre-clinical AD models to quantitatively track plaque progression as a function of brain region across time while producing indexed tissue sections for secondary staining and analysis. Aβ plaques in the well characterized 5XFAD mouse model of AD were labeled with Methoxy-X04, an Aβ plaque-specific compound, prior to transcardial perfusion and whole-brain excision. The brains were processed on the TissueCyte Serial Two-Photon Plus (STP 2 ) imaging platform to produce fully aligned multi-channel volumetric datasets, yielding high resolution 3D models of each brain. Registration to the Allen Mouse Brain Common Coordinate Framework (CCFv3) and region-specific plaque analysis were conducted to determine plaque size, density, and total number per animal brain. The regional density of dystrophic neurites (Lamp1) and microglia (Iba1) were segmented and quantified through secondary analysis to evaluate the signal in high and low Aβ growth rate regions for select sections and remapped to the original 3D whole-brain dataset. The analysis of whole-brain plaque distribution in the 5XFAD mouse model revealed distinct spatial-temporal changes across the brains (Figure 1, Figure 2). STP 2 imaging, combined with CCFv3 mapping and secondary analysis of Lamp1 and Iba1 allowed for targeted evaluation of Aβ plaques, and a comparison of regional molecular changes between models. Our novel technology has great promise for quantifying the spatial-temporal Aβ plaque efficacy of AD animal models, and the production of translatable pre-clinical AD drug discovery data. The high sensitivity and precision of the STP 2 platform can benefit region-specific disease progression compared to standard laboratory approaches.

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. 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. 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. 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.

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.

Behavioral aggression is a common neuropsychiatric symptom that coincides with progressive cognitive decline in adults with Alzheimer's disease (AD). One of the key hallmarks of AD is progressive accumulation of amyloid-beta (Aβ) throughout the brain. The present study was aimed at measuring non-cognitive behaviors such as aggression and relevant pathologies such as plaque load and distribution in mutant mice expressing human APP, namely the APP/PS1 (APPsw/PS1 (m146L)) and TASD41 (hAPP751 with the London V717I9/Swedish double mutation K670M/N671L). In the current study, we were interested in examining progression of behavioral manifestations in male mice of both the APP/PS1 and TASD41 lines. The resident-intruder paradigm was used to assess aggression in AD mice. We also utilized proprietary algorithm-based behavioral platform, the SmartCube® System, to assess whole animal behavior longitudinally. To compliment these behavioral outputs, we additionally performed Serial Two-Photon whole brain imaging and analysis of the distribution, size and density of Aβ-plaques in young and aged AD mice using the TissueCyte® imaging platform. The present findings demonstrate increased aggressive behavior in aged APP/PS1 and TASD41 male mice compared to wild-type littermates. We also demonstrate pharmacological attenuation of aggression in AD mice with acute administration of either antipsychotic (Risperidone) or anxiolytic (Busipirone). Using sophisticated algorithm-based system, SmartCube®, we were able to identify a phenotype effect and distinct behavioral changes in male AD mice as early as 5 months of age that progressed over time. In line with the behavioral data, our whole brain TissueCyte® based analyses suggests that younger mice (∼4-5 months) exhibit very sparse parenchymal plaques while aged mice (>7 months) show a clear progression in the number/size of plaques and display differential increases in regional plaque load number/size. In summary, we demonstrate clear aggressive behavior and pharmacological validation in aged, male mouse models of amyloidosis, with more advanced computer vision systems identifying distinctive behavioral patterns and discriminating the phenotype at early disease stages. Together with the region-specific progression of plaque densities, these models present a valuable tool for early intervention and improved assessment of potential therapeutic approaches for AD and in particular AD-induced aggression.