Background: Late-onset Alzheimer’s Disease (AD) (LOAD) is the most common neurodegenerative disease. Despite extensive efforts to understand disease progression there are currently no approved disease modifying interventions to delay or reverse neurodegeneration caused by AD. Repeated failures in human trials, despite promising preclinical results in amyloidogenic mouse models, highlight the need for animals that better model human AD. MODEL-AD (Model organism development and evaluation for late-onset AD) are identifying and integrating disease-relevant, humanized gene sequences identified from public AD data repositories to create more translatable mouse models relevant to AD.
Methods: Strong risk factors for LOAD, APOEε4 and Trem2*R47H, were expressed alone or in combination on a congenic C57BL/6J (B6) background, in cohorts of mice established on multiple sites and aged to between 4-24 months. A deep phenotyping approach was employed to assess phenotypes relative to human AD.
Results: The LOAD1 mouse strain, expressing humanized APOEε4 and Trem2*R47H alleles, was designed to elucidate the disease state of animals expressing the two strongest genetic risk factors of LOAD at endogenous levels. 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, but not genotype, 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, these two alleles together form a sensitized, background strain which will serve as a platform for the characterization of additional genetic and environmental LOAD risk factors.
Conclusions: Comprehensive phenotyping provided key insights into genetic and environmental effects aimed at modeling human disease, critical to understand the complex intergenic interactions and subsequent molecular signaling cascades. The data provided by these assays are important for understanding the relative contributions of subsequent risk factors amended to LOAD1.