Abstract Background The complement cascade is increasingly implicated in development of a variety of diseases with strong immune contributions such as Alzheimer’s disease and Systemic Lupus Erythematosus. Mouse models have been used to determine function of central components of the complement cascade such as C1q and C3. However, species differences in their gene structures mean that mice do not adequately replicate human complement regulators, including CR1 and CR2 . Genetic variation in CR1 and CR2 have been implicated in modifying disease states but the mechanisms are not known. Results To decipher the roles of human CR1 and CR2 in health and disease, we engineered C57BL/6J (B6) mice to replace endogenous murine Cr2 with human complement receptors, CR1 and CR2 (B6. CR2CR1 ). CR1 has an array of allotypes in human populations and using traditional recombination methods ( Flp-frt and Cre-loxP ) two of the most common alleles (referred to here as CR1 long and CR1 short ) can be replicated within this mouse model, along with a CR1 knockout allele ( CR1 KO ). Transcriptional profiling of spleens and brains identified genes and pathways differentially expressed between mice homozygous for either CR1 long , CR1 short or CR1 KO . Gene set enrichment analysis predicts hematopoietic cell number and cell infiltration are modulated by CR1 long , but not CR1 short or CR1 KO . Conclusion The B6. CR2CR1 mouse model provides a novel tool for determining the relationship between human-relevant CR1 alleles and disease.
Abstract Background Numerous AD risk loci and variants have been identified by large‐scale genetic studies, but few have been functionally verified and models to study their mechanism of action are lacking. The Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Center was created to develop, characterize, and distribute more precise preclinical models for late‐onset AD (LOAD) by engineering these disease‐associated variants into mouse models, and characterizing the resulting phenotypes using clinically relevant assays. Method Diverse criteria including replication in multiple studies, predicted pathogenicity of variant, sequence conservation between human and mouse, and expression in relevant cell types were used to prioritize risk variants, which were then engineered into a mouse model that expresses the AD risk variants APOE4 and Trem2*R47H. Primary screening was done by transcriptomic analysis using the nanoString Mouse AD Panel at 4, 8, and 12 months. Result Bioinformatics studies enabled us to prioritize coding variants in the Abca7, Clasp2, Mthfr, Mtmr4, Plcg2, Shc2, Slc6a17, Snx1, and Sorl1 loci. Knockouts of Abca7 , Ceacam1 , Il1rap , and Plcg2 have also been created to model human loss of function variants. Transcriptomic analysis demonstrated that the Abca7*A1527G and Mthfr*C677T models exhibited some age‐dependent similarities to transcriptomic changes seen in post‐mortem samples from the AMP‐AD cohort. These will move on to deep phenotyping out to 24 months of age. Analysis of other models are still in progress and will be presented. Humanized APP and Tau ( MAPT ) models are also in progress. Conclusion We have prioritized Abca7*A1527G and Mthfr*C677T models to be comprehensively characterized up to 24 months of age in the MODEL‐AD program. We will discuss our approach to prioritize genetic variants, develop novel models relevant to LOAD, and use clinically relevant measures to determine which models are most useful for translational studies. All models are made available for both academic and for‐profit use from The Jackson Laboratory, and all validation data will be shared via the AMP‐AD knowledge portal. For more information see www.model‐ad.org.
Abstract Background As research efforts to discover and develop promising future therapeutics continues, the necessity to develop clinically significant Alzheimer’s disease (AD) mouse models and analysis is more important than ever. Method The study utilizes a novel MODEL‐AD (Model Organism Development and Evaluation for Late‐onset AD) mouse model that incorporates APOE4, Trem2 * R47H, and humanized amyloid‐beta (Aβ) allele into C57BL/6J (B6) mice to produce LOAD2. Two cohorts of male and female LOAD2 mice received either control or high fat diet (HFD) followed by brain metabolism imaging using 18F‐FDG PET/CT. Brain regions were segmented using the Paxinos‐Franklin atlas and analyzed using a whole brain neurovascular uncoupling and connectivity approach. To do this, we computed z‐score statistics for all mice relative their control diet group, and conducted hierarchical modularization of all 28 brain regions and statically compared results across sex and high‐risk diet in 12‐month‐old mice. Result An initial network analysis detected metabolic hypo‐perfusion and metabolism for female mice, while males showed neurovascular uncoupling. Hierarchical analysis revealed primary modules within the whole brain network. These primary modules were then further modularized to yield a final breakdown of six secondary sub‐modules consisting of 3‐7 brain regions. Predominate functional associations of the sub‐modules’ brain regions were sensory (S) and learning (L), while sub‐module 2.1 had the strongest visual (V) representation. Statistical analysis of the six sub‐modules exhibited significant, module‐, sex‐, and dietary‐dependent effect for LOAD2 mice on high fat diet (HFD) by 12mo. Conclusion The incorporation of APOE4, Trem2 * R47H, and humanized Ab sequence in combination with HFD induced age‐dependent LOAD‐relevant changes in neurovascular coupling and whole brain network connectivity consistent with known brain circuit variations observed clinically. These findings support application of this newer LOAD2 mouse model to improve knowledge regarding disease mechanism. Additionally, our connectivity analysis approach shows promise for implementation in future therapeutic development and testing.
Abstract Background Late‐onset Alzheimer’s disease (LOAD) is the most common form of dementia without an approved therapy. Transgenic overexpression animal models do not effectively produce the heterogeneity observed clinically in LOAD patients and thus are not ideal for therapy development. Hence, the Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Center is developing, characterizing, and distributing novel mouse models expressing humanized, clinically relevant risk factors. Analysis of aging LOAD2 mice that better phenocopy human disease will inform the further development of subsequent generations of models and reveal more appropriate molecular targets useful in the treatment of LOAD. Method Two risk factors of LOAD, APOEe4 and Trem2 * R47H, were incorporated into C57BL/6J mice along with humanized amyloid‐beta to produce the LOAD2 model. Mice were aged up to 24 months. In some mice, high‐fat diet replaced normal mouse chow. An animal phenotyping pipeline was employed to qualify and align with neurodegenerative disease states and phenotypes observed in human patients. In vivo imaging in addition to behavior and wellness assays were performed, as were analyses of blood and brain tissue for risk‐factor‐related alterations in neuropathology, transcriptomics, metabolomics, and proteomics. Result Aged LOAD2 mice on high‐fat diet present altered cytokine profiles in the brain, and peripherally, however no overt hippocampal pathology nor differences in long‐term potentiation were observed. Expression of human amyloid did not yield plaque formation in 18‐month mice. High‐fat diet was a strong determinant during behavioral phenotyping. Correlation of transcriptional profiling with human AMP‐AD modules determined individual and synergistic effects between genetic and environmental risk factors compared to human data. Continuing efforts to dissect the clinically‐relevant downstream effects of sex, age, genotype, and diet in these animals remain. Conclusion The MODEL‐AD consortium has established the LOAD2 mouse model to study the effects of genetic and environmental risk factors of LOAD. This strain serves as a platform for the incorporation of additional AD risk factors (both genetic and environmental) to more closely align phenotypes in the mouse to outcomes observed in the clinic. Here we show the evidence of emerging disease pathology in an animal model exposed to genetic and environmental risk factors.
Aging is the major risk factor for neurodegenerative diseases such as Alzheimer's disease, but little is known about the processes that lead to age-related decline of brain structures and function. Here we use RNA-seq in combination with high resolution histological analyses to show that aging leads to a significant deterioration of neurovascular structures including basement membrane reduction, pericyte loss, and astrocyte dysfunction. Neurovascular decline was sufficient to cause vascular leakage and correlated strongly with an increase in neuroinflammation including up-regulation of complement component C1QA in microglia/monocytes. Importantly, long-term aerobic exercise from midlife to old age prevented this age-related neurovascular decline, reduced C1QA+ microglia/monocytes, and increased synaptic plasticity and overall behavioral capabilities of aged mice. Concomitant with age-related neurovascular decline and complement activation, astrocytic Apoe dramatically decreased in aged mice, a decrease that was prevented by exercise. Given the role of APOE in maintaining the neurovascular unit and as an anti-inflammatory molecule, this suggests a possible link between astrocytic Apoe, age-related neurovascular dysfunction and microglia/monocyte activation. To test this, Apoe-deficient mice were exercised from midlife to old age and in contrast to wild-type (Apoe-sufficient) mice, exercise had little to no effect on age-related neurovascular decline or microglia/monocyte activation in the absence of APOE. Collectively, our data shows that neurovascular structures decline with age, a process that we propose to be intimately linked to complement activation in microglia/monocytes. Exercise prevents these changes, but not in the absence of APOE, opening up new avenues for understanding the complex interactions between neurovascular and neuroinflammatory responses in aging and neurodegenerative diseases such as Alzheimer’s disease.
Abstract Background Alzheimer’s disease (AD) is the most common form of dementia without an effective treatment. Animal models of AD have been valuable tools to understand familial or early onset AD, but to date have not been predictive for translational research. The Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Center is developing, validating, and distributing novel mouse models of late‐onset AD (LOAD) that can be used to develop novel therapeutics. Using the 5XFAD model of early onset AD, we have established pipelines to characterize models across multiple sites using biochemistry, histology, functional assays, in vivo MRI and PET imaging, and Serial Two‐Photon (STP) tomography whole brain imaging. Methods At designated time points, animals were subjected to the following assays: Functional ‐ behavioral testing paradigms, and in vivo MRI and PET scanning followed by secondary validation with autoradiography. Biochemistry/Histology ‐ mice were sacrificed, perfused, and tissue harvested, with half of the brain frozen and the other half fixed. On frozen tissue samples we performed bulk RNA‐seq. On fixed tissue samples, we assessed AD relevant changes using the following stains and antibodies: X34 (plaques and NFTs), Lamp1 (dystrophic neurites), Iba1 (microglia). STP Whole Brain Imaging ‐ on additional fixed tissue samples we performed whole brain imaging and regional analysis of Methoxy‐X04 labeled plaques using the TissueCyte® imaging platform. Results Combined assessment of the 5XFAD model revealed systematic neurodegenerative changes in the mouse brain. Multiple data sets including histology, biochemistry, RNA‐seq, transcriptomics, in vivo imaging, and STP whole brain analysis show differences throughout disease progression. Conclusions We utilized the well characterized 5XFAD model of AD to develop an integrated pipeline for deep phenotyping of novel mouse models of AD. This pipeline combines novel functional and anatomical assays across sites to track the ontology of AD progression, and targeted understanding of the molecular, biochemical and functional progression of AD pathology. Together, this pipeline provides a novel platform for greater understanding of LOAD mouse models and potential therapeutic approaches for AD.
Brain myeloid cells have been strongly implicated in Alzheimer's Disease (AD) and related dementias. To understand their role, incorporating genetic diversity into AD models is indispensable to enhance human relevance. The Diversity Outbred (DO) mouse panel has been established by outcrossing incipient inbred Collaborative Cross (CC) strains, derived from eight founder strains including C57BL/6J (B6), PWK/PhJ, WSB/EiJ and CAST/EiJ. These genetically diverse mouse resources provide a promising tool to study the complex etiology of AD. First, 6–8 month male and female mice from four genetically distinct AD models were created (B6, PWK, WSB and CAST each carrying APP/PS1) and assessed by behavioral and metabolic assays. Brain tissue was assessed postmortem by transcriptomics, immunofluorescence and biochemistry. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify differential gene modules across the strains. Second, myeloid cells were isolated from 8 month female brains from these four genetically distinct APP/PS1 strains using magnetic activated cell sorting (by CD11b-microbeads) and profiled using single-cell RNA-seq. Third, to begin to understand myeloid cell variation, microglia cell counts and morphology were determined in brains from 120 young DO mice. Finally, myeloid cell responses are being assessed in CC lines carrying APP/PS1 and APOEE4. Transcriptomics and cell counts showed a significant variation in myeloid cell numbers across B6, PWK, WSB and CAST strains. Also, differential plaque-associated myeloid cell responses were observed in this APP/PS1 panel. Myeloid cell responses correlated with variation in cognitive decline, neurodegeneration, and cerebral amyloid angiopathy across the strains. WGCNA identified myeloid cell-associated gene modules as the greatest difference across the strains with differential expression of Trem2, Tyrobp, Ctss and Csf1r. Protocols for single myeloid cell isolation from genetically distinct strains were established along with a pipeline to determine allelic-specific gene expression. Genetic diversity significantly modifies myeloid cell responses and AD-relevant phenotypes in mice. Mechanistic studies are now underway to understand myeloid cell responses in the founder strains, as well as the DO and CC strains. Projecting the findings to human myeloid cell datasets will facilitate the identification of translatable myeloid-cell based therapies for AD and related dementias.
BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein e4 (APOEe4) 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 APOEe4/e4 exhibited significant Type-1 uncoupling (decreased glucose uptake, increased perfusion) at 8 and 12 mo, while APOEe3/e4 demonstrated Type-2 uncoupling (increased glucose uptake, decreased perfusion), while immunopathology confirmed cell specific contributions. DISCUSSION: This work highlights APOEe4 status in AD progression manifest as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker.
Abstract Background The Model Organism Development and Evaluation for Late‐onset AD (MODEL‐AD) Consortium was established to generate and characterize more translatable animal models for late‐onset Alzheimer’s disease (LOAD) based on human genetic risk variants. While numerous genetic risk loci for LOAD have been identified, few have been experimentally verified in vivo and in many cases the risk variants have not been validated. The development of new models incorporating LOAD genetic risk should improve our understanding of disease mechanisms and improve preclinical testing of potential therapeutics. Method Coding and non‐coding LOAD risk variants were prioritized based on human data sets, with the goal of targeting diverse pathways (e.g., neuroinflammation, vascular risk, metabolic function, lipid homeostasis). Risk variants in Abca7, Adamts4, Bin1, Erc2, Mthfr, Mtmr4, Plcg2, Ptk2b, Slc6a17, Snx1, Sorl1 and other loci were engineered into mouse models expressing humanized APOE4 and the Trem2*R47H risk variant; in more recent models, a humanized Abeta allele was also included. A novel transcriptomic panel, based on clinical LOAD samples (Preuss et al, 2020) was used to evaluate how well each model replicated clinical transcriptomic changes with disease. Models were aligned to ROSMAP clinical subtypes. Result We have identified specific human AD‐related pathways disrupted in an age‐dependent manner in these novel mouse models. Specifically, mouse models carrying human AD risk variants Abca7*A1527G, Mthfr*C677T , and Plcg2*M28L exhibited transcriptomics changes similar to those seen in LOAD patients. Most models could be readily matched to either the inflammatory or non‐inflammatory subtype. Conclusion We have prioritized mouse models expressing LOAD risk variants in Abca7 , Mthfr , and Plcg2 for comprehensive phenotyping using clinically relevant measures including transcriptomics and proteomics, biomarkers, neuropathology and in vivo imaging at advanced ages (24 months). Ongoing projects will use human data to guide how to combine alleles to create models that match multi‐omic signatures of AD subtypes and test the effects of environmental risk factors such as high‐fat diet. Through this effort we aim to develop improved models for testing targeted therapeutics.
Abstract Background Data from human and model organism studies suggest that genetic background influences susceptibility and resilience to Alzheimer’s Disease (AD) neuropathology. We previously showed that, wild‐derived PWK/PhJ (PWK) mice carrying the APP/PS1 transgene (PWK.APP/PS1) exhibit cognitive and synaptic resilience compared to traditionally‐studied B6.APP/PS1 inbred mice in presence of amyloid beta (Aβ) plaque deposition. PWK.APP/PS1 mice also contain different proportions of transcriptionally‐defined microglia compared to B6.APP/PS1. The precise molecular mechanisms underlying these differences between strains remain unknown. In this study, we aim to identify and characterize cell populations in the hippocampi of genetically distinct B6 and PWK mouse strains, and investigate cell‐type specific gene expression patterns associated with cognitive resilience in presence of amyloid deposition. Method We generated cohorts of B6. APP/PS1 and PWK. APP/PS1 transgenic female mice and wild‐type (WT) littermates as controls (n = 4 per strain/genotype group). At 8 months of age mice were euthanized, hippocampi collected, and single nuclear RNA sequencing (snRNAseq) was performed using 10x Genomics Chromium platform. Seurat R package (version 5.0.1) was used for major data analysis. Result We identified subpopulations of microglial cells characterized by varying expression patterns of a set of genes including Hk2, Itgam and Dock8. Neuronal subtypes were clustered by top marker genes Plk5 and Adarb2. Oligodendrocytes, oligodendrocyte progenitor cells, and endothelial cells were marked by expression of Mog, Neu4 and Abcc9, respectively. Differential expression and pathway enrichment analysis revealed strain‐specific immune and cell signaling pathways altered in distinct cell populations in response to amyloid pathogenesis. Cross‐species mapping of these transcriptomic signatures with human hippocampal gene modules identified AD‐relevant molecular mechanisms observed in mouse models of AD at the cell‐type level. Conclusion This study suggests that cell‐type specific transcriptomic response to amyloid is modulated by genetic background and our findings re‐iterate the importance of incorporating genetic diversity to model phenotypic and molecular heterogeneity in AD. Since the nuclei enriched in this dataset are enriched for neurons, future interrogations will provide evidence for specific neuronal populations and molecular mechanisms that differentiate cognitively resilient PWK from susceptible B6 mice, providing insights into mechanisms that can be leveraged to promote AD resilience.
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