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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
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Related Experiment Video

Updated: Jan 7, 2026

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

Giordano Cecchetti1, Giulia Rugarli2,3, Luca Zanchi1

  • 1IRCCS San Raffaele Scientific Institute, Milan, MI, Italy.

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

Resting-state EEG theta and alpha power correlate with Alzheimer's disease (AD) plasma biomarkers. Distinct EEG patterns emerged across biomarker groups, highlighting EEG's potential for non-invasive AD diagnosis and monitoring.

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Electroencephalography

Background:

  • Alzheimer's disease (AD) is a neurodegenerative disorder causing cognitive decline.
  • Resting-state electroencephalography (EEG) offers insights into AD-related neurophysiological changes.
  • This study explores links between 32-channel resting-state EEG and AD plasma biomarkers in memory clinic patients.

Purpose of the Study:

  • To investigate associations between 32-channel resting-state EEG parameters and plasma biomarkers for AD.
  • To identify distinct EEG patterns in patients stratified by AD biomarker levels.

Main Methods:

  • A cross-sectional study of 193 patients with cognitive disturbances.
  • Collected resting-state 32-channel EEG and Lumipulse plasma biomarkers (pTau217, pTau181, NfL, Ab42/40 ratio).
  • Patients stratified into three groups based on pTau217 cutoffs; linear regression and ANCOVA used to analyze associations.

Main Results:

  • Positive associations found between AD plasma biomarkers (pTau217, pTau181, pTau217/Ab42 ratio) and theta/delta power.
  • Negative associations observed between these biomarkers and alpha amplitude/power, and beta power.
  • Stratification by pTau217 revealed distinct EEG patterns, with higher theta and lower alpha power in intermediate/high biomarker groups.

Conclusions:

  • Resting-state EEG parameters, especially theta and alpha power, are strongly linked to AD plasma biomarkers.
  • EEG can capture disease-specific neurophysiological alterations, supporting AD diagnosis.
  • EEG presents a scalable, non-invasive method for AD diagnosis and monitoring.