Integrative translational discovery of vascular risk factors in aging and dementia
Integrative translational discovery of vascular risk factors in aging and dementia
批准号:
9421402
负责人:
GUOJUN BU
金额:
$357.77万
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 2020-05-31
关键词:
AddressAgeAgingAllelesAlzheimer&aposs DiseaseAlzheimer&aposs Disease PathwayAlzheimer&aposs disease riskAmyloid beta-ProteinApolipoprotein EAutopsyBiochemicalBiologicalBiological ModelsBlood VesselsBrainBrain DiseasesCellsChIP-seqChromatinClinicClinicalCognitiveComplexDataData SetDementiaDiseaseDrug TargetingElderlyEnvironmental Risk FactorEpigenetic ProcessEtiologyEventFundingGene ProteinsGenerationsGenesGeneticGenetic RiskGenetic TranscriptionGenotypeGoalsGonadal Steroid HormonesGrantHeterogeneityHumanInflammatoryKnowledgeLeadMeasurementMeasuresMedicineMeta-AnalysisMethylationModelingMolecularMusNerve DegenerationNeurofibrillary TanglesOutcomeParentsParticipantPathologicPathway AnalysisPathway interactionsPatientsPhenotypePlasmaProspective cohortProtein IsoformsRNA SequencesRiskRisk FactorsRoleSamplingScienceSenile PlaquesTestingTissue SampleTissuesUnited States National Institutes of Healthapolipoprotein E-3biomarker discoverycohortdata sharingdrug discoveryendophenotypefunctional genomicsfunctional outcomesgenome-widehuman datalipid metabolismmetabolomemetabolomicsmethylomemouse modelnetwork modelsneuroimagingneuropathologynew therapeutic targetnovelparent grantprogramsproteostasisresponsesextargeted biomarkertau Proteinstranscriptome
中文摘要
点击翻译按钮获取中文摘要
英文摘要
PROJECT SUMMARY/ABSTRACT
Alzheimer's disease (AD) is the most common cause of dementia characterized by brain accumulation of
senile plaques and neurofibrillary tangles. AD risk is likely influenced by a multitude of genetic and
environmental risk factors and their complex interplay, which subsequently lead to cascades of downstream
pathophysiologic events that include but are not limited to aberrant proteostasis and lipid metabolism, as well
as inflammatory, vascular, and oxidative mechanisms. The array of risk factors that lead to AD and their
downstream influences are likely to be heterogeneous amongst AD patients, which complicates the search for
drug targets, biomarkers and their potential downstream beneficial use in any given AD patient. For this
reason, drug target and biomarker discovery efforts in AD have to focus on identification of both molecular
mechanisms that are commonly perturbed in AD patients, as well as those mechanisms that may underlie
heterogeneity in AD. To overcome this massive challenge, team-science efforts, including the NIH initiatives,
Accelerating Medicines Partnership-AD (AMP-AD) and Molecular Mechanisms of the Vascular Etiology of AD
(M2OVE-AD) Consortia, have launched large-scale generation and analyses of multi-omics data from well-
phenotyped human cohorts and model systems. These consortia aim to integrate multi-omics and clinical
endophenotype data to build a model(s) of AD that captures these common and heterogeneous
pathomechanisms. Our teams are leading participants of both AMP-AD and M2OVE-AD. The initial findings
from these consortia reveal concerted changes in networks of expressed genes and proteins in AD subjects
and model systems, with biological significance. Despite this progress and wide and immediate sharing of the
data generated by these programs, significant gaps remain in the available –omics data, and the ability to
integrate, harmonize and annotate these datasets. Our proposal is in response to the RFA-AG-17-054, which
aims to close these gaps. In this proposal, we maintain the overall objective of our parent funded M2OVE-AD
project (RF1 AG51504), which is to determine APOE- and sex-dependent effects, and uncover novel genes
and pathways that influence vascular risk in aging, AD and other dementias. Our specific aims are: 1.
Integrative functional genomic analysis of human brains to discover novel pathways in AD. 2. Integrative
functional genomic analysis in a prospective cohort to validate and discover AD pathways. 3. Investigate the
impact of APOE genotype and sex on transcriptional networks and the metabolome in model systems. 4.
Perform single-cell profiling to annotate the transcriptome data from AMP-AD and M2OVE-AD. These studies
will add key epigenetic data (H3K9Ac and RRBS methylome) to the human and transcriptome and
metabolomics data to the mouse cohorts, generate human and mouse single cell transcriptome data, and
perform integrative network analyses. We expect this proposal to fill key gaps in knowledge and further
enhance the AMP-AD and M2OVE-AD initiatives in their drug and biomarker discovery goals.
期刊论文(0)
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科研奖励(0)
会议论文
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