The identification of a plaque-induced gene signature (PIG) partially overlapping with gene expression changes observed in AD brain samples using an App KI model further supports the relevance of these new models and provides incentive to continue their utilization to better define disease mechanisms and test candidate therapeutics. Other pathologies associated with amyloid deposition have been observed, including immune responses and neurodegenerative processes. In those models, the App gene has been humanized for the Aβ sequence and harbored fAD mutations resulting in progressive accumulation of amyloid deposits. Recently, a new generation of mouse models using knock-in (KI) approaches have been developed to avoid some of the limitations of transgenesis, including random genetic integration, ectopic expression and non-physiological protein levels. Transgenic mouse models overexpressing human amyloid precursor protein (hAPP) with familial AD (fAD) mutations, sometimes in combination with PSEN1 fAD mutations, have furthered our understanding of disease mechanisms, but also have the potential to introduce artifacts associated with App overexpression. In particular, mouse models recapitulating some aspects of this complex disease are instrumental in gaining insight into the neurobiology of AD. Research using preclinical AD models has been an essential step towards the development of therapies and discovery of disease-related biomarkers. 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.Īlzheimer’s disease (AD) is a devastating neurological condition. 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. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged. The App SAA 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. 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. Finally, we also characterized the mice in various behavioral assays. 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. 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. Wild type littermate mice were used as experimental controls. Amyloid-β pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous App SAA mice at different ages in brain and/ or biofluids. We engineered a novel App knock-in mouse model ( App SAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene.

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. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations.

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. Genetic mutations underlying familial Alzheimer’s disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients.

Molecular Neurodegeneration volume 17, Article number: 41 ( 2022) Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia

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