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

Vangelis P Oikonomou1, Ioulietta Lazarou1, Kostas Geordiadis1

  • 1Centre for Research & Technology Hellas, Thessaloniki, Greece.

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

Resting EEG functional connectivity, specifically betweenness centrality in the alpha band, shows progressive decreases across the Alzheimer's disease (AD) spectrum, from healthy controls to mild cognitive impairment and AD. This EEG biomarker may help detect early AD network disruptions.

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Neurodegenerative Diseases

Background:

  • Alzheimer's disease (AD) involves progressive neuronal dysfunction and cognitive decline.
  • Early detection of AD spectrum conditions is crucial for timely intervention.
  • Resting electroencephalography (EEG) offers a non-invasive method to assess brain function.

Purpose of the Study:

  • To investigate the utility of resting EEG functional connectivity in differentiating healthy controls (HC) from preclinical stages of the AD spectrum.
  • To examine network alterations across the AD spectrum using EEG-derived metrics.
  • To assess the potential of betweenness centrality as a biomarker for AD progression.

Main Methods:

  • Utilized the CAUEEG dataset comprising EEG recordings from 1155 participants.
  • Applied functional connectivity analysis, focusing on betweenness centrality as a network metric.
  • Compared betweenness centrality in the alpha band across HC, subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD groups using ANCOVA and post-hoc tests.

Main Results:

  • A significant main effect of diagnosis on betweenness centrality in the alpha band was observed (p < .01).
  • Post-hoc analyses revealed a progressive decrease in alpha band betweenness centrality from HC to SCD, MCI, and AD.
  • These findings suggest significant alterations in brain network connectivity across the AD spectrum.

Conclusions:

  • EEG-based functional connectivity, particularly alpha band betweenness centrality, can identify significant network changes in the AD spectrum.
  • This approach holds promise for detecting preclinical AD and monitoring disease progression.
  • Further research can leverage these findings for developing novel diagnostic and prognostic tools for Alzheimer's disease.