Systems Genetics Analysis of Alzheimer's Disease-Related Sleep Loss and the Transition to Dementia
Systems Genetics Analysis of Alzheimer's Disease-Related Sleep Loss and the Transition to Dementia
批准号:
10554420
负责人:
CATHERINE COOK KACZOROWSKI
金额:
$84.27万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-02-01 至 2023-02-28
关键词:
AgeAgingAlzheimer disease preventionAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAlzheimer&aposs disease pathologyAlzheimer&aposs disease patientAlzheimer&aposs disease related dementiaAlzheimer&aposs disease riskAlzheimer&aposs disease therapeuticAmyloidAutopsyBehaviorBiologicalBiological ModelsBrainClinicalCognitionCognitiveCognitive agingCognitive deficitsCohort StudiesCommunitiesComplementDNADataData SetDementiaDetectionDisease ProgressionElderlyElectroencephalographyGene TargetingGenesGeneticGenetic VariationGenomic SegmentHereditary DiseaseHeritabilityHeterogeneityHumanHuman GeneticsImageImpaired cognitionIndividualIndividual DifferencesKnowledgeKnowledge PortalLaboratoriesLate Onset Alzheimer DiseaseLinkMediatingMedicalMemoryMemory impairmentMeta-AnalysisMetadataModelingMolecularMusMutationNerve DegenerationNeurobehavioral ManifestationsOutcomePathologyPathway interactionsPatientsPhenotypePlayPopulationPredispositionPublicationsQuality of lifeQuantitative Trait LociQuestionnairesRNAResearchResearch PersonnelResourcesRiskRoleSamplingSeverity of illnessSleepSleep DeprivationSleep DisordersSymptomsSystemSystems BiologyTestingThe Jackson LaboratoryTranslatingValidationVariantVisualWorkactigraphyburden of illnesscohortdata integrationfamilial Alzheimer diseasegene therapygenetic analysisgenetic resourcegenome editinghigh riskhuman datahuman modelhumanized mouseimprovedinnovationinsightmachine learning classifiermild cognitive impairmentmouse modelmultidimensional dataneuropathologynon rapid eye movementnovelpre-clinicalresiliencesegregationsynergismtherapeutically effectivetooltraittranslational potentialusability
中文摘要
项目总结
我们提议的研究有望确定导致睡眠障碍的遗传因素。
阿尔茨海默病(AD),并确定它们是否可以干预以延缓认知症状。检测
对这些基因的验证将通过发现新的靶点和生物学特性来促进可能的治疗
可能有助于减轻人类疾病负担和提高生活质量的途径。数据
本提案中生成的数据还将与人类队列中的可用数据集进行交叉核对,并
身体样本,这样我们目前对网络和机制的了解的进展
可以在人类阿尔茨海默病的背景下理解老鼠。我们将利用先进的鼠标型号来
识别
阿尔茨海默病病理与细胞双向关系的分子和细胞机制
睡眠障碍。在目标1中,我们将识别与睡眠不足有关的基因和分子网络
更好地模拟人类阿尔茨海默病的大量AD小鼠。在目标2中,我们将翻译基因和网络
人类阿尔茨海默病队列中睡眠缺失的潜在差异。最后,在目标3中,我们将验证遗传和
与睡眠缺失和功能障碍相关的可修改因素,并确定它们对发病和功能障碍的影响
功能强大的AD模型中记忆缺陷的进展。
英文摘要
PROJECT SUMMARY
Our proposed research is expected to identify genetic factors that underlie disordered sleep associated with
Alzheimer's disease (AD), and determine if they are intervenable to stave off cognitive symptoms. Detection
and validation of these genes will promote possible treatments through discovery of new targets and biological
pathways that may aid in alleviating disease burden and improving quality of life in humans. The data
generated in this proposal will also be cross-checked with available datasets from human cohorts and
postmortem samples, such that advances in our current understanding of the networks and mechanisms in
mice can be understood in the context of human AD. We will leverage advanced mouse models to
identify
molecular and cellular mechanisms underlying the bidirectional relationship between AD pathology and
disruptions in sleep. In Aim 1, we will identify genes and molecular networks associated with sleep loss in a
large population of AD mice that better model human AD. In Aim 2, we will translate genes and networks
underlying variation in sleep loss to human AD cohorts. Finally, in Aim 3, we will validate genetic and
modifiable factors associated with sleep loss and dysfunction, and determine their effects on onset and
progression of memory deficits in powerful AD models.
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