grant

Core C: Data Management and Statistical Core

Organization UNIVERSITY OF MICHIGAN AT ANN ARBORLocation ANN ARBOR, UNITED STATESPosted 1 Sept 2021Deadline 30 Jun 2026
NIHUS FederalResearch GrantFY2025AD dementiaAD related dementiaADRDAlzheimer Type DementiaAlzheimer disease dementiaAlzheimer sclerosisAlzheimer syndromeAlzheimer'sAlzheimer's DiseaseAlzheimer's and related dementiasAlzheimer's dementia and related dementiaAlzheimer's dementia or related dementiaAlzheimer's disease and related dementiaAlzheimer's disease and related disordersAlzheimer's disease or a related dementiaAlzheimer's disease or a related disorderAlzheimer's disease or related dementiaAlzheimer's disease related dementiaAlzheimers DementiaApplications GrantsAreaBig DataBigDataBioinformaticsBiological MarkersCharacteristicsClinicalCollaborationsCommunicationCommunitiesComplexConsultationsDataData AnalysesData AnalysisData Base ManagementData Base Management SystemsData BasesData CollectionData Management CoreData Management and Analysis CoreData Management and Statistical Analysis CoreData Management and Statistical CoreData SecurityData awarenessDatabase Management SystemsDatabasesDevelopmentDisciplineEpidemiologyExposure toFacultyFundingGenerationsGeneticGenomicsGoalsGrantGrant ProposalsHIPAAHealth Insurance Portability and Accountability ActIRBIRBsImageInstitutionInstitutional Review BoardsInternationalInvestigatorsKennedy Kassebaum ActKnowledgeLinkMR ImagingMR TomographyMRIMRIsMagnetic Resonance ImagingMeasuresMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMethodsMichiganNMR ImagingNMR TomographyNeuropsychologiesNeuropsychologyNuclear Magnetic Resonance ImagingOperations ResearchPL 104-191PL104-191ParticipantPathologicPatient RecruitmentsPhenotypePreventionPrimary Senile Degenerative DementiaProbabilistic ModelsProbability ModelsProceduresProcessProteomicsPublic Law 104-191ReproducibilityResearchResearch PersonnelResearchersRisk FactorsScientistSecureSeminalStatistical Data AnalysesStatistical Data AnalysisStatistical Data InterpretationStatistical ModelsTechniquesTechnologyTelemedicineTimeTrainingUnited States Health Insurance Portability and Accountability ActVisitWorkZeugmatographybio-markersbiologic markerbiomarkerclassroom environmentcohortcollege atmospherecollegial atmospherecollegiate atmospherecomplex dataconsultationdata basedata integrationdata integritydata interpretationdata managementdata management and coordinating centerdata management centerdata sharingdata visualizationdatabase managementdatabase systemsdesigndesigningdevelopmentaleducation atmosphereeducation researcheducational atmosphereeducational environmentelectronic dataenvironment enrichmentenvironment enrichment for laboratory animalsenvironmental enrichmentenvironmental enrichment for laboratory animalsepidemiologicepidemiologicalexperienceflexibilityflexibleimagingimprovedinformation securityinnovateinnovationinnovativeintellectual atmosphereinvestigator traininglearning atmospherelearning environmentmachine learning based prediction modelmachine learning based predictive modelmachine learning predictionmachine learning prediction modelmeetingmeetingsmembermultiomicsmultiple data sourcesmultiple omicsneural imagingneuro-imagingneuroimagingneurological imagingneuropathologicneuropathologicalneuropathologyneuropsychologicnext generationoutreachpanomicsparticipant recruitmentpolygenetic risk scorespolygenic risk scoreprimary degenerative dementiaquery toolsrelational database management systemsschool atmosphereschool climatesenile dementia of the Alzheimer typeskillsstatistical analysisstatistical linear mixed modelsstatistical linear modelsstatisticstraining atmospheretraining opportunityuniversity atmosphereuser-friendly
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Full Description

ABSTRACT – CORE C: DATA MANAGEMENT AND STATISTICAL CORE
Research on prevention and treatment of heterogeneous Alzheimer’s disease and related dementias (ADRD)

requires knowledge and information that varies by domain, scale and time. Thus, meeting the challenge of

ADRD necessitates big data integrated across disciplines, shared data and collaboration across the Michigan

Alzheimer’s Disease Research Center (MADRC) and the entire ADRC network, deployment of appropriate

statistical models, and training of scientists in data methods and statistics. The MADRC Data Management and

Statistical Core (DMSC) will continue to meet these critical needs as it oversees data and statistical analyses

for the MADRC. Data types include clinical/neuropsychological measures, participant recruitment/engagement

metrics, genetics, neuropathologic measures, neuroimaging, and biomarker data that will be integrated by the

DMSC. The DMSC will continue to ensure that the data meet enhanced Health Insurance Portability and

Accountability Act (HIPAA) compliance and National Institute Standards and Technology (NIST) safeguards,

IRB compliance and data security. The DMSC works closely with the Research Education Component (REC)

to assist, train and support junior faculty members in becoming independent investigators by providing an

enriched learning environment to increase their statistical and research skills. The overarching goals of the

DMSC are to integrate, share, and scale data through reproducible pipelines, guide data analyses, and train

investigators in these processes. Corresponding to these areas of importance, the DMSC proposes five

Specific Aims: Aim 1: Provide an automated, user friendly, integrated, and secure data collection and

management platform; Aim 2: Provide accessible, integrated, and informative big data and summary scores for

MADRC research needs; Aim 3: Share data, pipelines, and analytic expertise with NACC and related Centers;

Aim 4: Provide data analysis support and consultation at every stage of the research process; Aim 5: Provide

an enriched environment for MADRC investigators to expand their data visualization, analytical, and statistical

knowledge. The DMSC will enhance the comprehensive and state-of-the-art data generated by the MADRC

Cores by informing streamlined data collection and data integration across Cores, our three institutions, and

with the NACC. In the initial funding period, we succeeded in building a reproducible database platform that

combined historic cohort information with new longitudinal participant information. We will expand our activities

to support two new Cores (Biomarker and Neuroimaging) and we will support new and ongoing research

operations. DMSC activities will enhance research collaboration and analytic training across the community of

ADRD researchers. With our highly experienced team, the DMSC is exceptionally well-equipped to ensure that

the MADRC makes seminal contributions to innovative research, outreach, and training across the region and

nationally.

Grant Number: 5P30AG072931-05
NIH Institute/Center: NIH

Principal Investigator: Kelly Bakulski

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