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 ?4 allele of APOE (APOE?4) 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 APOE?4.
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 APOE?4-dependent processes. To achieve this we have crossed APOE?4, 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 APOE?4. 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 APOE?4, 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 APOE?4 in AD.
Alzheimer's disease (AD) is a leading cause of dementia worldwide and there is no known cure. The greatest genetic risk factor for AD is DNA variations in the APOE gene but alone, these DNA variations do not cause disease. Additional genetic and environmental risk factors (such as poor diet and physical inactivity) contribute to disease susceptibility. In this proposal we will use systems genetic approaches in mouse and humans to understand the complex interactions between variations in APOE, additional genetic risk factors and diet/exercise. Our work aims to provide a deeper understanding of the biological processes altered to increase risk for AD and novel genes/pathways for therapeutic testing.
