Many transgenic mouse models exist that mimic a range of Alzheimer’s disease (AD)—related pathologies. They play a key role in both basic research and preclinical testing of potential therapeutics for AD. Although they have contributed greatly to the pathophysiology of β-amyloid toxicity, none fully replicates the human disease.

A group from the Jackson Laboratory sought to test the hypothesis that incorporating genetic diversity into AD mouse models would improve translational potential. The researchers note that “an individual’s genetic makeup plays a large role in determining susceptibility to AD but has largely been ignored in preclinical studies.” They combined a well-established mouse model of AD with a genetically diverse reference panel to generate mice that harbor identical high-risk human mutations but differ across the remainder of their genome. The incorporation of genetic diversity resulted in greater overlap with the genetic, molecular, and clinical features of this pervasive human disease.

This study was published online Dec. 27 in a paper titled, “Harnessing Genetic Complexity to Enhance Translatability of Alzheimer’s Disease Mouse Models: A Path toward Precision Medicine” in the journal Neuron.

“This is the first study to show that you can replicate many of the molecular features of Alzheimer’s disease in a genetically diverse mouse model,” says NIA director Richard J. Hodes, M.D. “It points to a strategy for better use of mouse models for precision medicine research—both basic and translational—for Alzheimer’s disease.”

The research group, led by Catherine Kaczorowski, Ph.D., associate professor at the Jackson Laboratory, combined the well-established mouse model of familial AD (5XFAD) with a genetically diverse set of mice. All members of this family of transgenic mice, therefore, carry the high-risk human familial AD genes but otherwise have very different genetic make-ups. The detailed analysis of this new panel of mice (referred collectively as AD-BXD), showed a high degree of overlap with the genetic, molecular, pathologic, and cognitive features of AD. Moreover, in the presence of identical AD risk genes, the differences in genetic background led to profound differences in the onset and severity of the pathologic and cognitive symptoms of AD.

Through a series of comparative analyses, the research team also discovered that one mouse strain, C57BL/6J, commonly used to generate AD transgenic mouse models, harbors resilience factors that lessen the impact of AD risk factor genes. This new finding has two important implications. First, it suggests that AD mouse models with this genetic background may not be suitable for testing of novel therapeutic agents and may explain the poor predictive power of drug screening studies using the current AD transgenic mouse models. Second, by using the AD-BXD panel, the protective genes from the C57BL/6J strain and their mechanisms can be precisely identified leading to new candidate targets for AD prevention.

The authors note that the AD-BXD panel represents a new tool for better understanding the heterogeneous nature of normal aging and AD, and for precisely identifying molecular factors that lead to resilience to genetic and environmental disease risk factors.

“The ability to model genetic diversity and its impact on multiple aspects of disease risk and resilience in transgenic mice in a robust and reproducible way will enable the research community to learn a lot more about the complex nature of Alzheimer’s a lot faster,” says Suzana Petanceska, Ph.D., program director in the NIA division of neuroscience, who oversees the Resilience-AD program. “This new resource adds to the series of new NIA/NIH programs generating data, analytical, and research tools needed to enable more efficient and predictive drug development for Alzheimer’s.”

Not only did the authors show that genetic variation profoundly modifies the impact of human AD mutations on both cognitive and pathological phenotypes and validate this complex AD model by demonstrating high degrees of genetic, transcriptomic, and phenotypic overlap with human AD. They introduce a novel AD mouse population as an innovative and reproducible resource for the study of mechanisms underlying AD and provides evidence that preclinical models incorporating genetic diversity may better translate to human disease, increasing their usability for precision medicine research for AD.

AD is an irreversible, progressive brain disorder that slowly destroys memory and thinking skills and, eventually, the ability to carry out simple tasks. As many as 5.5 million Americans age 65 and older are estimated to be living with AD, the most common form of dementia.

Dr. Kaczorowski’s team is one of 10 multidisciplinary and multi-institutional research teams supported through the Resilience-AD program, one of a series of NIA-supported open-science consortia. Resilience-AD, launched in 2017, aims to address why and how some individuals remain dementia-free despite being at high genetic or biomarker risk of AD. The program was developed to generate a deeper mechanistic understanding of how genetic and environmental factors interact and lead to cognitive resilience in individuals who are at high risk for AD and to identify novel therapeutic targets for pharmacologic and nonpharmacologic prevention strategies.



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