Alzheimer's disease (AD) is a common neurodegenerative disorder affecting more than 10% of the population over age 65, and almost 50% of those over age 85. Early onset familial AD is typically caused by mutations in one of just three autosomal genes. In contrast, the more common, late-onset sporadic AD (LOAD), which is associated with amyloid ? accumulation, tau hyperphosphorylation, and mitochondrial dysfunction, appears to be influenced by a very large number of genes, most of which are unidentified. Genome-wide association studies of LOAD point to genome-wide epistasis and gene--environment interactions contributing to overall risk. Both the genetic basis and the downstream effects of AD are system-wide and complex. To parse this complexity in both causes and consequences of AD, here we create a novel Systems Biology Pipeline and apply it to a powerful genetic model of AD using the fruit fly, Drosophila melanogaster. With three complementary aims, our pipeline enables us to create a comprehensive genotype-phenotype map of AD.
Our first aim uses the fully sequenced Drosophila Genetic Reference Panel (DGRP) to identify fly strains that amplify or ameliorate the effects of A? and tau on age-related neurodegeneration, and characterizes the metabolomic and single-cell brain transcriptomic networks associated with this amplification and protection.
The second aim develops the fly as a powerful model for downstream systems-wide phenotypes, from electrophysiological measures of specific single cell types in the brain, to machine-vision analysis of walking gait dynamics. To help us understand how upstream variation in genes and molecular networks (Aim 1) translates to downstream cellular and behavioral phenotypes (Aim 2), Aim 3 examines the protein dynamics of A? and tau, including their turnover, aggregation and abundance, and the influence of A? and tau on mitochondrial integrity, including mitochondrial morphology, trafficking and turnover.
Aim 3 will then compare these elements in strains that are most sensitive to the deleterious effects of A? and tau with those that are most resistant, delineating molecular and cellular mechanisms that influence A? and tau toxicity. To accomplish these aims, we have constructed an outstanding team of researchers with highly complementary skills. Our published and preliminary data presented here establish our ability to measure genotypic variation in AD risk in Drosophila and construct and analyze large-scale molecular networks associated with that risk, to study the phenotypic consequences of AD from electrical pulses in a single neuron to intricate behaviors in a whole fly, and to discover the underlying biochemical mechanisms that link genotype to phenotype. Previous work with Drosophila has played an important role in our understanding of both basic biology and of disease mechanism, including neurodegenerative diseases. The studies proposed here have the potential to shed new insight on the complex, interacting pathways that influence AD pathogenesis in natural populations, potentially leading to new biomarkers and new opportunities for therapeutic intervention in AD.

Public Health Relevance

The risk that a person develops late-onset Alzheimer's Disease (AD) is influenced by a large number of genes, interacting in large, complex networks. To identify new pathways that cause AD, and to better understand how and why these pathways affect AD risk, this study uses a naturally variable population of fruit flies (the Drosophila Genome Reference Panel) to create a Systems Biology Pipeline for studying AD. This Pipeline will identify strains that are unusually resistant or sensitive to the toxic effects of proteins associated with AD, will use cutting edge technology to examine how molecular networks vary among these lines, and will study the biochemical, cellular, physiological and behavioral consequences of AD risk. Taken together, results from this study should lead to the discovery of novel causes and mechanisms of AD risk.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Multi-Year Funded Research Project Grant (RF1)
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Special Emphasis Panel (ZAG1)
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Kohanski, Ronald A
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University of Washington
Schools of Medicine
United States
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Rangaraju, Srikant; Dammer, Eric B; Raza, Syed Ali et al. (2018) Quantitative proteomics of acutely-isolated mouse microglia identifies novel immune Alzheimer's disease-related proteins. Mol Neurodegener 13:34