The Apolipoprotein E (APOE) isoforms APOE2, APOE3 and APOE4 differentially modulate risk of Alzheimer's disease (AD). Despite established evidence for APOE's impact on Aβ deposition, the differential effects of APOE genotypes on distinct forms of amyloid pathology remain poorly understood. The three primary types of amyloid pathology in the brain are dense-cored fibrillar plaques, diffuse Aβ deposits, and vascular deposits in the form of cerebral amyloid angiopathy (CAA) and their relative distribution is thought to be important in determining the phenotypic outcomes in AD and related dementias. Here, we used different mouse models of AD-amyloidosis to ask two main questions: (1) does human APOE4 promote the deposition of all these subtypes of types of amyloid pathology, and (2) does presence of APOE4 influence the morphological transformation of diffuse Aβ deposits into dense-core neuritic plaques? In the SAA-APP knock-in model of dense-cored Aβ deposits resulting from accumulation of protofibrillar-favoring Aβ42, we observed that crossing in human APOE reduced amyloid burden. Among the three human APOE alleles, APOE4 produced the highest plaque burden and size, relative to APOE3 and APOE2 in the SAA-APP mice. Though all three human APOE isoforms showed comparable levels of colocalization with individual plaques, focused genomic analysis at early stages of pathology revealed that neural connectivity pathways were affected in mice with human APOE4 compared to human APOE3, implicating mechanisms of early neuronal dysfunction. In the slowly-developing APPsi model, characterized by predominantly diffuse Aβ deposits and cerebral amyloid angiopathy (CAA) emerging at older ages, we also found that mouse Apoe showed the greatest amyloid burden, followed by human APOE4 and APOE3. CAA deposition was noted in aged APPsi mice with mouse Apoe or human APOE4 mice but rarely in APPsi mice with human APOE3. Finally, neonatal Aβ seeding in APPsi mice revealed that APOE4 accelerated parenchymal Aβ deposition compared to APOE3 mice, though seeding in the presence of APOE4 did not alter the inherent diffuse morphology of the Aβ deposits. Collectively, these results demonstrate that APOE genotype influences the deposition of all types of amyloid pathology, including dense-cored, diffuse and vascular pathology. Notably, only the amount of amyloid was modified by APOE variants, while the type of amyloid pathology inherent in each model was not altered. Together these findings implicate a key role for apoE as a modifier of all types of Aβ deposition with limited potential to modify plaque compaction or morphology.

Genetic mutations underlying familial Alzheimer's disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain. We engineered a novel App knock-in mouse model (AppSAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene. Amyloid-β pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous AppSAA mice at different ages in brain and/ or biofluids. Wild type littermate mice were used as experimental controls. We used in situ imaging technologies to define the whole-brain distribution of amyloid plaques and compare it to other AD mouse models and human brain pathology. To further explore the microglial response to AD relevant pathology, we isolated microglia with fibrillar Aβ content from the brain and performed transcriptomics and metabolomics analyses and in vivo brain imaging to measure energy metabolism and microglial response. Finally, we also characterized the mice in various behavioral assays. Leveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aβ content. The AppSAA knock-in mouse model recapitulates key pathological features of AD such as a progressive accumulation of parenchymal amyloid plaques and vascular amyloid deposits, altered astroglial and microglial responses and elevation of CSF markers of neurodegeneration. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged. Our findings demonstrate that fibrillar Aβ in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology.

Alzheimer's disease (AD), the most common cause of dementia, is characterized by the progressive deposition of amyloid-β (Aβ) peptides and neurofibrillary tangles. Mouse models of Aβ amyloidosis generated by knock-in (KI) of a humanized Aβ sequence provide distinct advantages over traditional transgenic models that rely on overexpression of amyloid precursor protein (APP). In App-KI mice, three familial AD-associated mutations were introduced into the endogenous mouse App locus to recapitulate Aβ pathology observed in AD: the Swedish (NL) mutation, which elevates total Aβ production; the Beyreuther/Iberian (F) mutation, which increases the Aβ42/Aβ40 ratio; and the Arctic (G) mutation, which promotes Aβ aggregation. AppNL-G-F mice harbor all three mutations and develop progressive Aβ amyloidosis and neuroinflammatory response in broader brain areas, whereas AppNL mice carrying only the Swedish mutation exhibit no overt AD-related pathological changes. To identify behavioral alterations associated with Aβ pathology, we assessed emotional and cognitive domains of AppNL-G-F and AppNL mice at different time points, using the elevated plus maze, contextual fear conditioning, and Barnes maze tasks. Assessments of emotional domains revealed that, in comparison with wild-type (WT) C57BL/6J mice, AppNL-G-F/NL-G-F mice exhibited anxiolytic-like behavior that was detectable from 6 months of age. By contrast, AppNL/NL mice exhibited anxiogenic-like behavior from 15 months of age. In the contextual fear conditioning task, both AppNL/NL and AppNL-G-F/NL-G-F mice exhibited intact learning and memory up to 15-18 months of age, whereas AppNL-G-F/NL-G-F mice exhibited hyper-reactivity to painful stimuli. In the Barnes maze task, AppNL-G-F/NL-G-F mice exhibited a subtle decline in spatial learning ability at 8 months of age, but retained normal memory functions. AppNL/NL and AppNL-G-F/NL-G-F mice exhibit behavioral changes associated with non-cognitive, emotional domains before the onset of definitive cognitive deficits. Our observations consistently indicate that AppNL-G-F/NL-G-F mice represent a model for preclinical AD. These mice are useful for the study of AD prevention rather than treatment after neurodegeneration.