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Sex and APOE genotype interact to alter immune regulated metabolism in AD

$5,785,588RF1FY2019AGNIH

Duke University, Durham NC

Investigators

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Abstract

The timing of onset and the severity of the disease process in Alzheimer?s disease (AD) are varied and involve risk factors that include the expression of gene alleles of APOE4. Biological female sex is also implicated as a strong risk factor for AD. However, despite accumulating evidence supporting this association, recent large population-based analyses indicate that this association is complex. Immunity, like sex and APOE genotype, is a primary disease factor in AD and impacts both the onset and pathological features of neurodegenerative events. The impact of sex hormones on immunity suggests that this additional interaction may contribute to the role APOE4 plays in AD. How sex, APOE genotype and immunity interact to initiate or amplify AD pathology, however, remains essentially unknown. Our preliminary data point to a shift in metabolic pathways that is directly controlled by immunity, is impacted by sex and by APOE genotype and which may serve as an underlying and unifying mechanism defining the disease process. In this proposal we will identify these metabolic pathways and test if changing estrogen levels as found in menopause alters these metabolic outcomes to worsen disease and in an APOE genotype dependent manner. To accomplish these goals we have developed a series of mouse models that permit direct analysis and comparisons of changes in brain metabolism under conditions where APOE genotype and female sex interact in a more-human like immune background. To fully characterize these models, we will use advanced phenotyping techniques that include unbiased proteomics, transcriptomics and metabolomics The use of laser capture microdissection combined with genomic or proteomic analysis will permit regional and/or cellular localization of changed pathways. Measuring pathway flux with heavy labeled isotopes allows us to directly confirm specific pathway differences based on biological sex, genotype or age. Initiating estrogen depletion in our mouse models using ovarian chemical disruption allows us to determine and compare the effect of lack of estrogen (menopause) on the pathological phenotypes. Overall, our research plan will allow us to identify critical pathways and to widen our knowledge of the impact of AD-like pathology on multiple brain functions, including immunity. Importantly, using bioinformatics tools we will be able to compare across the experimental data sets generated from our analyses of the mice models, to human tissue metabolites and finally to corresponding available human data sets outside of Duke, enabling us to confirm and extend our results.

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