Genetic Association Between Alzheimer's Disease and Cardio-Cerebrovascular Risk Factors
Project Number1K01AG084849-01A1
Former Number1K01AG084849-01
Contact PI/Project LeaderLEE, ANNIE J
Awardee OrganizationCOLUMBIA UNIVERSITY HEALTH SCIENCES
Description
Abstract Text
PROJECT SUMMARY
Research. Cardio and cerebrovascular risk factors (CVRFs) such as hypertension and diabetes increase the
risk of Alzheimer's disease (AD). The prevalence of CVRFs and dementia are higher among African Americans
and Hispanics than Whites. However, the etiological interaction between CVRFs and AD remains unclear.
Elucidating how genes and CVRFs interplay to influence AD risk will have the potential to reveal novel molecular
targets for prevention strategies and effective treatment for AD. To date, there is no accurate method to identify
genes or genetic variants that interact with CVRFs in AD. My overarching goal is to become an independent
investigator and interdisciplinary biostatistician on elucidating genetic architecture between AD and CVRFs in
diverse race/ethnic populations to aid in diagnosis, prevention, and treatment strategies in AD. The objective of
this proposal is to 1) identify genes that interact with CVRFs to confer AD risk and 2) identify epigenomic and
transcriptomic signatures that interact with vascular pathologies to confer AD risk and investigate integrated
pathways across two omics profiles. The completion of these aims will generate harmonized CVRF data, genes
that interact with CVRFs in AD, epigenomic and transcriptomic profiles, and integrative pathways in AD that
interacts with vascular pathologies. Our findings will pinpoint the our understanding of the underlying molecular
mechanisms of CVRFs, cerebrovascular pathologies, and AD with the potential to reveal novel molecular targets
for developing effect drugs for prevention and treatment for AD that can be better tailored to the individual
Career development plan. The proposed career development plan will build upon my previous training in
statistical genetics and transcriptomics data analysis with the following training goals to enhance my trajectory
toward becoming an independent investigator: Training in 1) Clinical, epidemiological, and biological aspects of
AD, vascular disease, and aging; 2) Multi-omics Integrative data analysis techniques and interpretation of
molecular pathways; and 3) Develop leadership and professional skills to become a NIH-funded independent
investigator. To achieve these goals, I have assembled a mentoring and advisory team of internal and external
scientists with expertise in Neurology (Dr. Richard Mayeux), Computational Biology (Dr. Yufeng Shen),
Bioinformatics (Drs. Badri Vardarajan, Lana Garmire), and Biostatistics (Dr. Iuliana Ionita-Laza). I will broaden
my knowledge and proficiency through coursework, workshops, meetings, and hands-on training.
Environment. The research environment at Columbia University is ideal for my transition into an independent
`big data' AD/CVRFs scientist and a biostatistician. In years 4-5, I plan to develop and submit an R01 to conduct
a longitudinal investigation of gene-CVRFs interactions to track progression from CVRFs, vascular pathologies
to AD using a multi-omics analysis. Skills and findings from this K01 will be broadly applicable to communities.
Public Health Relevance Statement
PROJECT NARRATIVE
Cardio and cerebrovascular risk factors (CVRFs) such as hypertension, diabetes, heart disease, obesity, and stroke
increase the risk of Alzheimer's disease (AD). This project uses cutting-edge multi-omics data in humans with advanced
statistical methods to identify novel genes that interact with CVRFs in AD using GWAS and to identify epigenomic and
transcriptomic profiles, and integrative pathways in AD that interacts with vascular pathologies. My findings may elucidate
how genes and CVRFs interplay to influence AD risk, provide insights into the racial/ethnic disparities in AD, suggest
personalized strategies for preventing AD in elderly individuals with CVRFs, and reveal novel molecular targets for potential
AD treatment.
NIH Spending Category
No NIH Spending Category available.
Project Terms
Advisory CommitteesAfrican American populationAgeAgingAlzheimer's DiseaseAlzheimer's disease diagnosisAlzheimer's disease related dementiaAlzheimer's disease riskAutopsyBig DataBioinformaticsBiologicalBiometryBlood VesselsBody mass indexBrainCandidate Disease GeneCase/Control StudiesClinicalCommunitiesCompensationComplexComputational BiologyDNA MethylationDataData AnalysesData SetDementiaDevelopment PlansDiabetes MellitusDiagnosisDiseaseEducational workshopElderlyEnvironmentEpidemiologyEpigenetic ProcessEthnic PopulationEtiologyFMNL2 geneFundingGene ExpressionGenesGeneticGoalsHeart DiseasesHeritabilityHispanic PopulationsHumanHypertensionImmune systemIndividualInvestigationKnowledgeLeadershipMeasurementMeasuresMediationMemoryMentorsMeta-AnalysisMethodsMethylationMolecularMolecular TargetMultiomic DataNeurologyNeuronsNot Hispanic or LatinoObesityPathologicPathologyPathway interactionsPatient Self-ReportPharmaceutical PreparationsPopulationPrefrontal CortexPrevalencePreventionPrevention strategyProcessQuantitative Trait LociResearchResearch PersonnelResearch Project SummariesRisk FactorsSNP genotypingSample SizeSampling StudiesScientistSignal TransductionStatistical MethodsStrokeTechniquesTestingTrainingTranscriptUnited States National Institutes of HealthUniversitiesVascular Diseasesancestry analysiscareer developmentcausal variantcerebrovascularcerebrovascular pathologycohortdementia riskeffective therapyepigenomicsethnic disparityethnic diversitygene discoverygene interactiongenetic architecturegenetic associationgenetic variantgenome wide association studygenome-widehigh riskimprovedinsightmeetingsmulti-ethnicmultiple omicsnovelpersonalized diagnosticspersonalized strategiespreventracial disparityracial diversityreligious order studysexskillstranscriptomicstreatment strategy
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