Assessment of neurovascular uncoupling: APOE status is a key driver of early metabolic and vascular dysfunction.

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.

Characterizing molecular and synaptic signatures in mouse models of late-onset Alzheimer's disease independent of amyloid and tau pathology.

INTRODUCTION: MODEL-AD (Model Organism Development and Evaluation for Late-Onset Alzheimer's Disease) is creating and distributing novel mouse models with humanized, clinically relevant genetic risk factors to capture the trajectory and progression of late-onset Alzheimer's disease (LOAD) more accurately. METHODS: We created the LOAD2 model by combining apolipoprotein E4 (APOE4), Trem2*R47H, and humanized amyloid-beta (Aß). Mice were subjected to a control diet or a high-fat/high-sugar diet (LOAD2+HFD). We assessed disease-relevant outcome measures in plasma and brain including neuroinflammation, Aß, neurodegeneration, neuroimaging, and multi-omics. RESULTS: By 18 months, LOAD2+HFD mice exhibited sex-specific neuron loss, elevated insoluble brain Aß42, increased plasma neurofilament light chain (NfL), and altered gene/protein expression related to lipid metabolism and synaptic function. Imaging showed reductions in brain volume and neurovascular uncoupling. Deficits in acquiring touchscreen-based cognitive tasks were observed. DISCUSSION: The comprehensive characterization of LOAD2+HFD mice reveals that this model is important for preclinical studies seeking to understand disease trajectory and progression of LOAD prior to or independent of amyloid plaques and tau tangles. HIGHLIGHTS: By 18 months, unlike control mice (e.g., LOAD2 mice fed a control diet, CD), LOAD2+HFD mice presented subtle but significant loss of neurons in the cortex, elevated levels of insoluble Ab42 in the brain, and increased plasma neurofilament light chain (NfL). Transcriptomics and proteomics showed changes in gene/proteins relating to a variety of disease-relevant processes including lipid metabolism and synaptic function. In vivo imaging revealed an age-dependent reduction in brain region volume (MRI) and neurovascular uncoupling (PET/CT). LOAD2+HFD mice also demonstrated deficits in acquisition of touchscreen-based cognitive tasks.

Metabolomics profiling reveals distinct, sex-specific signatures in serum and brain metabolomes in mouse models of Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species can facilitate translation. METHODS: We investigated differences in serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at 6 months of age. RESULTS: We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum. DISCUSSION: Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of apolipoprotein E (apoE) ε4 carriers and replicating the serum metabolic imprint of the APOE ε4 genotype. Our work thus represents a significant step toward translating metabolic dysregulation from model organisms to human AD. HIGHLIGHTS: This was a metabolomic assessment of two mouse models relevant to Alzheimer's disease. Mouse models exhibit broad sex-specific metabolic differences, similar to human study cohorts. The early-onset 5XFAD mouse model primarily alters brain metabolites while the late-onset LOAD1 model primarily changes serum metabolites. Apolipoprotein E (apoE) ε4 mice recapitulate glycerophospolipid signatures of human APOE ε4 carriers in both brain and serum.

In vivo validation of late-onset Alzheimer's disease genetic risk factors.

INTRODUCTION: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. METHODS: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. RESULTS: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. DISCUSSION: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics. HIGHLIGHTS: A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

Assessment of Neurovascular Uncoupling: APOE Status is a Key Driver of Early Metabolic and Vascular Dysfunction.

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.

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 towards informing clinical study design.

3D bioengineered neural tissue generated from patient-derived iPSCs mimics time-dependent phenotypes and transcriptional features of Alzheimer's disease.

Several iPSC-derived three-dimensional (3D) cultures have been generated to model Alzheimer's disease (AD). While some AD-related phenotypes have been identified across these cultures, none of them could recapitulate multiple AD-related hallmarks in one model. To date, the transcriptomic features of these 3D models have not been compared with those of human AD brains. However, these data are crucial to understanding the pertinency of these models for studying AD-related pathomechanisms over time. We developed a 3D bioengineered model of iPSC-derived neural tissue that combines a porous scaffold composed of silk fibroin protein with an intercalated collagen hydrogel to support the growth of neurons and glial cells into complex and functional networks for an extended time, a fundamental requisite for aging studies. Cultures were generated from iPSC lines obtained from two subjects carrying the familial AD (FAD) APP London mutation, two well-studied control lines, and an isogenic control. Cultures were analyzed at 2 and 4.5 months. At both time points, an elevated Aß42/40 ratio was detected in conditioned media from FAD cultures. However, extracellular Aß42 deposition and enhanced neuronal excitability were observed in FAD culture only at 4.5 months, suggesting that extracellular Aß deposition may trigger enhanced network activity. Remarkably, neuronal hyperexcitability has been described in AD patients early in the disease. Transcriptomic analysis revealed the deregulation of multiple gene sets in FAD samples. Such alterations were strikingly similar to those observed in human AD brains. These data provide evidence that our patient-derived FAD model develops time-dependent AD-related phenotypes and establishes a temporal relation among them. Furthermore, FAD iPSC-derived cultures recapitulate transcriptomic features of AD patients. Thus, our bioengineered neural tissue represents a unique tool to model AD in vitro over time.

Differential splicing of neuronal genes in a Trem2*R47H mouse model mimics alterations associated with Alzheimer's disease.

BACKGROUND: Molecular characterization of late-onset Alzheimer's disease (LOAD), the leading cause of age-related dementia, has revealed transcripts, proteins, and pathway alterations associated with disease. Assessing these postmortem signatures of LOAD in experimental model systems can further elucidate their relevance to disease origins and progression. Model organisms engineered with human genetic factors further link these signatures to disease-associated variants, especially when studies are designed to leverage homology across species. Here we assess differential gene splicing patterns in aging mouse models carrying humanized APOE4 and/or the Trem2*R47H variant on a C57BL/6J background. We performed a differential expression of gene (DEG) and differential splicing analyses on whole brain transcriptomes at multiple ages. To better understand the difference between differentially expressed and differentially spliced genes, we evaluated enrichment of KEGG pathways and cell-type specific gene signatures of the adult brain from each alteration type. To determine LOAD relevance, we compared differential splicing results from mouse models with multiple human AD splicing studies. RESULTS: We found that differentially expressed genes in Trem2*R47H mice were significantly enriched in multiple AD-related pathways, including immune response, osteoclast differentiation, and metabolism, whereas differentially spliced genes were enriched for neuronal related functions, including GABAergic synapse and glutamatergic synapse. These results were reinforced by the enrichment of microglial genes in DEGs and neuronal genes in differentially spliced genes in Trem2*R47H mice. We observed significant overlap between differentially spliced genes in Trem2*R47H mice and brains from human AD subjects. These effects were absent in APOE4 mice and suppressed in APOE4.Trem2*R47H double mutant mice relative to Trem2*R47H mice. CONCLUSIONS: The cross-species observation that alternative splicing observed in LOAD are present in Trem2*R47H mouse models suggests a novel link between this candidate risk gene and molecular signatures of LOAD in neurons and demonstrates how deep molecular analysis of new genetic models links molecular disease outcomes to a human candidate gene.

Reduction in GABAB on glia induce Alzheimer's disease related changes.

Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by beta-amyloid plaques (Aß), neurofibrillary tangles (NFT), and neuroinflammation. Data have demonstrated that neuroinflammation contributes to Aß and NFT onset and progression, indicating inflammation and glial signaling is vital to understanding AD. A previous investigation demonstrated a significant decrease of the GABAB receptor (GABABR) in APP/PS1 mice (Salazar et al., 2021). To determine if changes in GABABR restricted to glia serve a role in AD, we developed a mouse model with a reduction of GABABR restricted to macrophages, GAB/CX3ert. This model exhibits changes in gene expression and electrophysiological alterations similar to amyloid mouse models of AD. Crossing the GAB/CX3ert mouse with APP/PS1 resulted in significant increases in Aß pathology. Our data demonstrates that decreased GABABR on macrophages leads to several changes observed in AD mouse models, as well as exacerbation of AD pathology when crossed with existing models. These data suggest a novel mechanism in AD pathogenesis.

In vivo validation of late-onset Alzheimer's disease genetic risk factors.

Introduction: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Methods: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. Results: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. Discussion: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

Metabolomics profiling reveals distinct, sex-specific signatures in the serum and brain metabolomes in the mouse models of Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species provides a promising entry point for translation. METHODS: We investigated differences of serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at six months of age. RESULTS: We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum. DISCUSSION: Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of APOE4 carriers and replicating the serum metabolic imprint of the APOE4 genotype. Our work thus represents a significant step towards translating metabolic dysregulation from model organisms to human AD.

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.

Characterizing Molecular and Synaptic Signatures in mouse models of Late-Onset Alzheimer's Disease Independent of Amyloid and Tau Pathology.

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 Aß42, 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.

Single-Cell RNA Sequencing Reveals Molecular Features of Heterogeneity in the Murine Retinal Pigment Epithelium.

Transcriptomic analysis of the mammalian retinal pigment epithelium (RPE) aims to identify cellular networks that influence ocular development, maintenance, function, and disease. However, available evidence points to RPE cell heterogeneity within native tissue, which adds complexity to global transcriptomic analysis. Here, to assess cell heterogeneity, we performed single-cell RNA sequencing of RPE cells from two young adult male C57BL/6J mice. Following quality control to ensure robust transcript identification limited to cell singlets, we detected 13,858 transcripts among 2667 and 2846 RPE cells. Dimensional reduction by principal component analysis and uniform manifold approximation and projection revealed six distinct cell populations. All clusters expressed transcripts typical of RPE cells; the smallest (C1, containing 1-2% of total cells) exhibited the hallmarks of stem and/or progenitor (SP) cells. Placing C1-6 along a pseudotime axis suggested a relative decrease in melanogenesis and SP gene expression and a corresponding increase in visual cycle gene expression upon RPE maturation. K-means clustering of all detected transcripts identified additional expression patterns that may advance the understanding of RPE SP cell maintenance and the evolution of cellular metabolic networks during development. This work provides new insights into the transcriptome of the mouse RPE and a baseline for identifying experimentally induced transcriptional changes in future studies of this tissue.

Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer's Disease-Relevant Phenotypes in Mice.

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.

Prophylactic evaluation of verubecestat on disease- and symptom-modifying effects in 5XFAD mice.

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 (Aß) 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 Aß40 and Aß42 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 Aß 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.

Factors That Influence the Choice of Markov Model Order in Discriminating DNA Sequences from Different Sources.

Markov models have frequently been used in genetic sequence analysis. The number of parameters of a Markov model increases exponentially with model order, so it is often recommended that the order be chosen based on the size of data being modeled, lower orders for small and higher orders for large dataset sizes. Approaches based on model selection criterion have also been proposed. An important problem in microbiology and evolutionary biology is to decipher chimeric genomes of microbes, particularly, identify segments of distinct ancestries in genomes and reconstruct the plausible evolutionary scenarios that might have shaped the chimeric genomes in the microbial world. In this study, we assessed a Markov model-based segmentation method for its ability to detect compositionally disparate segments in chimeric sequence constructs as a function of model order, sequence length, and phylogenetic divergence. Our results show that the choice of Markov model order depends on both sequence size and composition. Higher order Markov models were found to be more effective in delineating sequence segments arising from closely related organisms in longer constructs; on the other hand, lower order Markov models were found to be more appropriate in delineating sequence segments arising from distantly related organisms in shorter constructs. These findings are important and timely, with broad implications in fields such as epidemiology that has to deal with the emergence of novel pathogenic chimeras that arise by foreign DNA acquisition, and ecology where chimeric structures may arise in various ecosystems, necessitating more robust approaches for their deconstruction and interpretation.

Corrigendum: Uncovering Disease Mechanisms in a Novel Mouse Model Expressing Humanized APOEε4 and Trem2*R47H.

[This corrects the article DOI: 10.3389/fnagi.2021.735524.].

A Protocol for Horizontally Acquired Metabolic Gene Detection in Algae.

Horizontal gene transfer (HGT) or lateral gene transfer (LGT), the exchange of genetic materials among organisms by means of other than parent-to-offspring (vertical) inheritance, plays a major role in prokaryotic genome evolution, facilitating adaptation of prokaryotes to changes in the environment. Phylogenetic methods have been frequently invoked to catalog horizontally acquired genes; however, these methods are often constrained by the paucity of sequenced genomes of close relatives (and even distant relatives) for a robust analysis and reliable inference. In this chapter, we describe a HGT quantification protocol that exploits the complementary strengths of the integrative segmentation and clustering method and the comparative genomics approach to identify foreign genes. Users can use this pipeline in combination with phylogenetic tree reconstruction to identify foreign genes that are supported by multiple lines of evidence, that is, atypical composition, atypical distribution in close relatives, and aberrant phylogenetic pattern.

Uncovering Disease Mechanisms in a Novel Mouse Model Expressing Humanized APOEε4 and Trem2*R47H.

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.