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

Haochun Huang1, Zexu Li2, Christina B Young3

  • 1Bioinformatics Program, Faculty of Computing and Data Science, Boston University, Boston, MA, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Speech analysis reveals linguistic features correlate with Alzheimer's Disease (AD) biomarkers, suggesting potential for early detection. These digital biomarkers, including content complexity and pauses, show promise for preclinical AD identification.

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Area of Science:

  • Neuroscience
  • Computational Linguistics
  • Biomarker Discovery

Background:

  • Speech features from cognitive tests may indicate mild cognitive impairment and Alzheimer's Disease (AD) risk.
  • Validation of speech features against established AD biomarkers is limited.
  • This study validates linguistic features from digital audio recordings against AD biomarkers.

Purpose of the Study:

  • To validate linguistic features extracted from verbal responses against Alzheimer's Disease (AD) biomarkers.
  • To explore the association between speech characteristics and amyloid and tau pathology.
  • To assess the potential of linguistic features as digital biomarkers for preclinical AD.

Main Methods:

  • Analysis of data from 238 cognitively intact participants from the Framingham Heart Study.
  • Extraction of 52 linguistic features (lexical density, syntactic complexity, speech fluency) using NLP and spaCy from Logical Memory delayed recall (LMd) test responses.
  • Validation against beta-amyloid status and Tau PET signals in key brain regions using multiple linear regression and Lasso regression, adjusting for age, sex, and education.

Main Results:

  • No association found between standardized LMd test scores and AD biomarkers.
  • Decreased content complexity (ideaDensity) linked to amyloid positivity and increased tau burden in entorhinal, inferior temporal (IT), and amygdala regions.
  • Reduced syntactic complexity (Yngve_avg) and longer pause durations associated with higher tau burden in inferior parietal (IP) and IT regions.

Conclusions:

  • Linguistic-based speech features demonstrate significant associations with amyloid positivity and tau accumulation.
  • These features show potential as digital biomarkers for preclinical Alzheimer's Disease (AD).
  • Further validation is required to confirm their utility in early AD detection.