grant

Multi-cohort study of factors that influence Alzheimer's disease biomarker and dementia timing

Organization UNIVERSITY OF WISCONSIN-MADISONLocation MADISON, UNITED STATESPosted 1 Feb 2023Deadline 30 Nov 2027
NIHUS FederalResearch GrantFY2025AD dementiaAD pathologyAD preventionAPOE e4APOE-ε4APOEε4AccelerationAccountingAffectAgeAge of OnsetAgingAlzheimer Type DementiaAlzheimer beta-ProteinAlzheimer disease dementiaAlzheimer disease preventionAlzheimer preventionAlzheimer risk factorAlzheimer sclerosisAlzheimer syndromeAlzheimer'sAlzheimer's Amyloid beta-ProteinAlzheimer's DiseaseAlzheimer's amyloidAlzheimer's biomarkerAlzheimer's brainAlzheimer's disease biological markerAlzheimer's disease brainAlzheimer's disease pathologyAlzheimer's disease patientAlzheimer's disease riskAlzheimer's pathologyAlzheimer's patientAlzheimers DementiaAlzheimer’s biological markerAlzheimer’s disease biomarkerAmentiaAmyloidAmyloid Alzheimer's Dementia Amyloid ProteinAmyloid Beta-PeptideAmyloid Protein A4Amyloid SubstanceAmyloid beta-ProteinAmyloid depositionAmyloid βAmyloid β-PeptideAmyloid β-ProteinAssayAutopsyBioassayBiologic FactorBiologicalBiological AgingBiological AssayBiological FactorsBiological MarkersBrainBrain Nervous SystemBrain scanCerebrospinal FluidClinicClinicalClinical TrialsClinical Trials DesignCognitionCognitive DisturbanceCognitive ImpairmentCognitive ManifestationsCognitive SymptomsCognitive declineCognitive function abnormalCohort StudiesCombined Modality TherapyConcurrent StudiesDataDementiaDemographic FactorsDetectionDiseaseDisease ProgressionDisorderDisturbance in cognitionEconomic ConditionsEconomical ConditionsEducationEducational aspectsEncephalonEnvironmental FactorEnvironmental Risk FactorEventGeneticHealthHealth behaviorHeterogeneityImageImpaired cognitionIndividualInterventionInvestigationLinkLiquid substanceMR ImagingMR TomographyMRIMRIsMT-bound tauMagnetic Resonance ImagingMeasurableMeasuresMediatorMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMemoryMethodsModelingModificationMonitorMultimodal TherapyMultimodal TreatmentNMR ImagingNMR TomographyNerve DegenerationNeurobehavioral ManifestationsNeurobehavioral Signs and SymptomsNeurofibrillary TanglesNeuron DegenerationNuclear Magnetic Resonance ImagingOnset of illnessPETPET ScanPET imagingPETSCANPETTParticipantPathologicPathologyPatientsPersonsPhasePositron Emission Tomography Medical ImagingPositron Emission Tomography ScanPositron-Emission TomographyPredicting RiskPrevention therapyPrimary Senile Degenerative DementiaProteinsPublic HealthRad.-PETRegistriesResearchResearch DesignRiskRisk FactorsSamplingShapesSocial ConditionsSocietal ConditionsSourceStandardizationStereotypingStudy TypeSumSymptomsTechniquesTestingThinkingTimeTranslatingTranslationsUniversitiesVariantVariationVascular DiseasesVascular DisorderWashingtonWisconsinWorkZeugmatographya beta peptideabetaagesalzheimer riskamyloid betaamyloid-b proteinapo E-4apo E4apo epsilon4apoE epsilon 4apoE-4apoE4apolipoprotein E epsilon 4apolipoprotein E-4apolipoprotein E4beta amyloid fibrilbio-markersbiologicbiologic markerbiological process of agebiomarkerblood vessel disorderbrain basedbrain volumecerebral spinal fluidco-morbidco-morbiditycognitive dysfunctioncognitive losscohortcombination therapycombined modality treatmentcombined treatmentcommunity level disadvantagecomorbiditycostdementia riskdemographicsdisadvantaged communitydisease onsetdisorder onseteffective therapyeffective treatmentenvironmental riskexperiencefluidforecasting riskhealth related behaviorimagingimprovedinsightliquidmicrotubule bound taumicrotubule-bound taumulti-modal therapymulti-modal treatmentnecropsyneighborhood barrierneighborhood disadvantageneighborhood-level barrierneighborhood-level disadvantageneural degenerationneural imagingneuro-imagingneurobehavioral symptomneurodegenerationneurodegenerativeneurofibrillary degenerationneurofibrillary lesionneurofibrillary pathologyneuroimagingneuroimaging biomarkerneuroimaging markerneurological degenerationneurological imagingneuronal degenerationneuropathologicneuropathologicalneuropathologynew approachesnovelnovel approachesnovel strategiesnovel strategyoptimal therapiesoptimal treatmentspatient living with Alzheimer's diseasepatient suffering from Alzheimer's diseasepatient with Alzheimer'spatient with Alzheimer's diseasepolygenetic risk scorespolygenic risk scorepositron emission tomographic (PET) imagingpositron emission tomographic imagingpositron emitting tomographypostmortempre-clinicalpreclinicalpredict riskpredict riskspredicted riskpredicted riskspredicting riskspredictive riskpredicts riskpreventpreventingprimary degenerative dementiarecruitresponserisk factor for dementiarisk for dementiarisk predictionrisk predictionssenile dementia of the Alzheimer typesexsocial cultural factorsocial culture determinantsocial factorssocial health determinantssocio-demographicssociocultural determinantsociocultural factorsociodemographicssoluble amyloid precursor proteinspinal fluidstudy designtangletautau Proteinstau factorthoughtstimelinetooltranslationuptakevascular dysfunctionvasculopathyτ Proteins
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Full Description

PROJECT SUMMARY/ABSTRACT
Advances in imaging and fluid-based biomarkers of Alzheimer’s disease (AD) including amyloid (A), tau (T) and

neurodegeneration (N), allow detection of underlying disease pathology decades before the onset of dementia.

Despite over a decade of AD biomarker research, the field still lacks the ability to accurately predict if and when

individuals with preclinical AD (those with biomarker detectable pathology in the absence of cognitive symptoms)

will experience dementia. Identifying factors that slow or quicken this preclinical timeframe is needed to improve

dementia risk prediction for preclinical AD patients and to inform optimal treatment windows for clinical trials

aiming to slow or prevent cognitive decline and impairment. Until recently, studying these factors was precluded

by observing different people for short periods of time that began studies in different disease stages with no way

to identify when disease began for individual participants. Our team developed and validated new methods that

provide individualized estimated amyloid onset age (EAOA) from amyloid biomarkers. EAOA can be used to

rearrange biomarker and clinical observations along an AD-specific timeline (i.e., an Amyloid Clock) anchored

to the start of preclinical AD. This project will apply this novel approach to existing data from that Washington

University Knight ADRC, the Wisconsin Alzheimer’s Disease Research Center, the Wisconsin Registry for

Alzheimer’s Prevention, the, the Mayo Clinic Study of Aging and the Alzheimer’s Disease Neuroimaging Initiative

to investigate factors across cohorts that influence the timing and trajectories of AD biomarkers and dementia.

This study was initiated based on our preliminary findings showing considerable differences between individuals

and cohorts regarding 1) when amyloid onset occurs, 2) the time between amyloid onset and dementia onset,

and 3) factors that affect AD biomarker and dementia trajectories in AD. In addition, studies from our center and

others have begun to link AD pathology, change in brain volume, and changes in cognition to social determinants

of health (SDoH) like neighborhood disadvantage. However, possible links between SDoH and the timing and

trajectories of AD biomarkers and dementia are not well-understood. Our hypothesis is that observed individual

and cohort differences in AD trajectories are due to a combination of demographic, environmental, sociocultural,

and biologic factors, and study design and sample composition. We will test this overall hypothesis in three

specific aims: 1) identify common factors across multiple cohorts that influence the timing and trajectories of ATN

biomarkers; 2) identify common factors across multiple cohorts that affect the time from amyloid onset to

dementia; and 3) explore inter-cohort differences in AD biomarker and dementia trajectories. This study will

leverage existing data in several well-characterized studies to provide new insights into mechanisms that explain

when preclinical AD begins and how long this preclinical phase lasts. This is expected to improve AD dementia

risk prediction for individuals and identify optimal windows for disease modifying and prevention therapies.

Grant Number: 5R01AG080766-03
NIH Institute/Center: NIH

Principal Investigator: TOBEY BETTHAUSER

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