Characterization of relationship between tau pathology and neurodegeneration in Alzheimer's disease using multimodal imaging
Characterization of relationship between tau pathology and neurodegeneration in Alzheimer's disease using multimodal imaging
批准号:
10604287
负责人:
Sandhitsu Das
金额:
$80.59万
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:
未结题
起止时间:
2022-04-15 至 2027-01-31
关键词:
AffectAgeAlzheimer&aposs DiseaseAlzheimer&aposs disease pathologyAlzheimer&aposs disease riskAmyloidApolipoprotein EAtrophicAutopsyBiologicalBiological MarkersBrainBrain InjuriesBrain regionCategoriesClassificationClinicalClinical ManagementCognitionCognitiveCollectionDataData SetDemographic FactorsDissociationEvaluationFunctional disorderFutureGenderGenotypeHeterogeneityHistopathologyImageImpaired cognitionIndividualInstitutionLifeLinear RegressionsMagnetic Resonance ImagingMeasuresMediatingMethodsModelingMultimodal ImagingNerve DegenerationNeuroanatomyNeurofibrillary TanglesOutcomePathologicPathologyPatternPersonsPharmaceutical PreparationsPhenotypePositron-Emission TomographyProcessResearchResidual stateRisk FactorsSamplingSenile PlaquesSourceSpecimenSubgroupTechniquesTestingThickTissuesVariantVascular DiseasesVulnerable PopulationsWhite Matter Hyperintensityalpha synucleinbrain tissueclinical phenotypecognitive performancecohortcomorbidityconvolutional neural networkdigitalgray matterimaging modalityimprovedin vivoin vivo imagingmultimodalitymultiple datasetsprotein TDP-43regional atrophyresiliencesexstatistical and machine learningtau Proteinstau aggregationtoolvascular risk factor
中文摘要
项目总结
英文摘要
Project Summary
The pathophysiology of Alzheimer’s disease (AD) is characterized by the accumulation of Amyloid (Aβ) plaques
and tau neurofibrillary tangles (NFT). While the presence of both plaques (A+) and tangles (T+) are essential to
the biological definition of AD as recently codified in the ATN research classification framework, tau (T) is thought
to be the primary driver of downstream neurodegeneration (N) and the resulting cognitive impairment. However,
there is substantial variability in the T-N relationship – manifested in higher or lower atrophy than expected for
the level of tau in a given brain region, even in carefully curated research cohorts. What does this variability
represent? In this study, we explore the idea that a quantitative measure of the variability in the canonical
relationship between T and N is itself a “mismatch metric” that can help characterize different underlying
phenotypes and modulatory factors. We will examine this by modeling region-wise measures of T vs. N obtained
from in-vivo imaging in a cohort A+ symptomatic individuals. SUVR from tau-PET imaging and cortical thickness
from structural MRI will serve as regional measures of T and N respectively. We will then use data-driven
clustering for phenotype discovery based on the model residuals. Region-wise model residuals capture spatial
variation in the T-N relationship, conceptually extending the ATN framework from the dichotomous T/N +/-
designations to a richer description that may reflect differing spatial topography of underlying co-pathologies.
The concept of the T-N mismatch metric and its ability to identify underlying phenotypes will be evaluated
in multiple publicly available and institutional datasets, each of which will provide a diverse collection of
phenotypes. We will also perform evaluation in a dataset of ex-vivo specimens of A+ individuals. We will obtain
quantitative measures of N from ex-vivo MRI as a semi-automated cortical thickness estimate, and of T using
digital histopathology techniques, in multiple brain regions. Gold standard histopathology measures (e.g. TDP-
43, alpha-synuclein, non-AD tau, vascular disease) obtained in these samples will help evaluate whether T-N
mismatch metric can help identify phenotypes with non-AD co-pathology. Finally, we will evaluate if the T-N
mismatch metric is predictive of future cognitive decline as well as rates of longitudinal neurodegenerative
changes in the brain.
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Characterization of relationship between tau pathology and neurodegeneration in Alzheimer's disease using multimodal imaging
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批准号:10391754
-
项目类别:
-
资助金额:$83.07万
-
财政年份:2022
-
负责人:Sandhitsu Das
-
依托单位:
Ultra-high resolution BOLD fMRI of medial temporal lobe at 7 Tesla
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依托单位:
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项目类别:
-
资助金额:$8.0万
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财政年份:2014
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负责人:Sandhitsu Das
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依托单位:
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