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A systems biology approach in Drosophila to identify novel factors that influence AD pathogenicity

A systems biology approach in Drosophila to identify novel factors that influence AD pathogenicity
果蝇系统生物学方法识别影响 AD 致病性的新因素
批准号:
9413012
负责人:
Daniel Edward Promislow
金额:
$335.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-15 至 2022-08-31
关键词:
AffectAgeAgingAllelesAlpha CellAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAlzheimer&aposs disease riskAmyloid beta-ProteinAnimal ModelBehaviorBehavioralBindingBiochemicalBiochemical PathwayBioenergeticsBiological MarkersBiologyBrainCellsComplexDataDiseaseDisease ResistanceDrosophila genomeDrosophila genusDrosophila melanogasterEarly Onset Familial Alzheimer&aposs DiseaseElderlyElectrophysiology (science)ElementsExhibitsEyeFoundationsGaitGenesGeneticGenetic EpistasisGenetic ModelsGenetic StructuresGenetic VariationGenotypeGoalsHumanIndividualLate Onset Alzheimer DiseaseLeadLinkMapsMeasurementMeasuresMediatingMetabolismMitochondriaModelingMolecularMorphologyMutationNerve DegenerationNeurodegenerative DisordersNeurofibrillary TanglesNeuronsPathogenesisPathogenicityPathologyPathway interactionsPersonsPhenotypePhysiologic pulsePhysiologicalPlayPopulationProtein BiochemistryProtein DynamicsProteinsPublishingResearch PersonnelResistanceRiskRisk FactorsRoleSeveritiesSpecificityStressStructureSystemSystems BiologyTauopathiesTechnologyTestingTherapeutic InterventionToxic effectTranslatingVariantVisionWalkingWorkabeta accumulationage relatedage related neurodegenerationbrain cellcell typediagnostic biomarkerflygene environment interactiongenome wide association studygenome-widein vivoinsightkinematicsmetabolomicsmitochondrial dysfunctionmolecular scalemortalityneurodegenerative phenotypenovelpredictive markerreference genomeskillstau Proteinstau expressiontraffickingtraittranscriptomics

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英文摘要
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 β 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 Aβ 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 Aβ and tau, including their turnover, aggregation and abundance, and the influence of Aβ 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 Aβ and tau with those that are most resistant, delineating molecular and cellular mechanisms that influence Aβ 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.
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