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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Charles D Chen1, Cinthya Aguero2, Alexandra N Melloni2

  • 1Massachusetts General Hospital, Charlestown, MA, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

Positron emission tomography (PET) biomarkers for amyloid-β and tau predict brain pathology, but tau PET requires careful interpretation due to outliers. Individualized tau PET metrics may improve prediction of neuropathologic assessments in aging and preclinical Alzheimer's disease (AD).

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Area of Science:

  • Neuroimaging
  • Neuropathology
  • Alzheimer's Disease Research

Background:

  • The Harvard Aging Brain Study (HABS) investigates differences between normal aging and preclinical Alzheimer's Disease (AD).
  • Sixteen HABS participants donated their brains for neuropathologic assessment.
  • This study evaluates the predictive power of antemortem PET biomarkers for neuropathologic findings.

Purpose of the Study:

  • To compare antemortem PET biomarkers with postmortem neuropathologic assessments of amyloid-β and tau.
  • To determine the extent to which PET imaging can predict the spatial distribution and density of neuropathologic changes.
  • To identify potential discrepancies between PET imaging and neuropathology, particularly for tau PET.

Main Methods:

  • Neuropathologic assessments included amyloid-β plaques (Thal phase/A score), tau tangles (Braak NFT stage/B score), and neuritic plaques (CERAD NP score/C score).
  • Amyloid-β PET (PiB) metrics included frontal, lateral temporal, parietal, and retrosplenial cortex distribution volume ratio (DVR) and spatial extent (EXT).
  • Tau PET (flortaucipir, FTP) metrics included standardized uptake value ratios (SUVRs) in the whole temporal lobe, medial temporal lobe (MTL), and temporal neocortex (NEO-T), analyzed bilaterally and laterally.

Main Results:

  • Amyloid-β PET (PiB) metrics (DVR and EXT) significantly correlated with amyloid-β plaque scores (A and C).
  • Initial tau PET (FTP) SUVRs did not significantly correlate with Braak NFT stage (B score).
  • After excluding outliers, whole temporal and NEO-T SUVRs correlated significantly with B score; lateralized SUVRs further strengthened these correlations.

Conclusions:

  • Amyloid-β PET metrics accurately reflect amyloid plaque distribution and density.
  • Tau PET metrics correlate with tau tangle distribution, but require outlier removal, suggesting potential discrepancies.
  • Individualized tau PET metrics accounting for heterogeneity are proposed to enhance prediction of neuropathologic assessments.