Tuesday, February 7, 2023
2/7/2023
PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is the most common form of dementia and the sixth leading cause of death in the United States. Currently no treatments are available that prevent or slow the disease. Genetics is thought to account for up to 70% of risk for developing AD. Apolipoprotein E (APOE) is the greatest genetic risk factor with inheritance of the e4 allele of APOE (APOEe4) contributing approximately 15-50% of late-onset AD (LOAD) genetic risk. More than twenty other genes have been consistently associated with AD through next generation sequencing and genome-wide association studies (GWAS). Therefore in most cases, AD is likely caused by interactions between combinations of genetic factors. However, for many genes, the causative risk variants have not been identified and the mechanisms by which these genes contribute to AD are not known. This knowledge gap makes it extremely difficult to predict risk for and develop new strategies for treating AD. To bridge this gap, we propose a systems genetics approach in mice to identify combinations of genetic factors that modulate risk for AD. In particular we will focus on identifying genetic interactors of APOEe4. We aim to identify genetic factors that modify APOE-dependent processes most relevant to AD including lipid and amyloid clearance, APP processing, synaptic maintenance, vascular health and immune cell activation. Previous attempts to model AD in mice have utilized only a tiny fraction of the available genetic diversity and we believe this is one of the main reasons why mouse models have failed to recapitulate key aspects of human AD contributing to the lack of success in clinical trials. At The Jackson Laboratory (JAX), we have access to mouse strains that capture as much genetic diversity as is present in the human population and the expertise to maximize their potential. Our approach incorporates four classical inbred strains (C57BL/6J (B6), WSB/EiJ, CAST/Ei and NZO/HILtJ) and a recently developed panel of recombinant inbred lines (The Collaborative Cross, CC). We will use a combination of cutting edge genetic, genomic and computational methods to formulate and validate predictions about how specific AD-relevant genes interact to affect AD- related phenotypes. In Aim 1, we will determine the extent by which diverse genetic contexts modulate APOEe4-dependent processes. To achieve this we have crossed APOEe4, APPswe and PS1de9 from C57BL/6J to WSB/EiJ, CAST/EiJ and NZO/HILtJ. Our data show these strains provide variation in AD-relevant outcomes including cognitive ability, immune cell activation, body composition and metabolism. In Aim 2, we will determine how known LOAD genes modify the effects of APOEe4. We have identified 10 CC lines that together harbor an allelic series for at least 12 GWAS genes such as TREM2, ABCA7, BIN1, CLU, PICALM and CD33. We will determine specific variants that, in combination with APOEe4, affect AD phenotypes. In Aim 3 we will validate specific combinations of variants in different genetic contexts to more precisely define the role of genetic interactors of APOEe4 in AD.
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