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Related Concept Videos

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

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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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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Alberto Jaramillo-Jimenez1,2,3,4, Yorguin Jose Mantilla-Ramos2,4,5, Diego Tovar1,6

  • 1Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.

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

Resting-state EEG analysis reveals distinct patterns in neurodegenerative diseases. Lewy Body Dementia shows slowed brain waves and increased aperiodic activity, while Alzheimer's disease exhibits milder abnormalities.

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Electroencephalography

Background:

  • Resting-state EEG (rsEEG) alpha rhythm alterations are potential biomarkers for neurodegenerative diseases (NDDs).
  • The aperiodic component of rsEEG is often overlooked in spectral analysis.
  • Multicenter studies face challenges with batch effects, necessitating harmonization for robust analysis.

Purpose of the Study:

  • To differentiate rsEEG oscillatory and aperiodic alterations across various NDDs.
  • To mitigate batch effects in multicenter rsEEG data through harmonization.
  • To identify specific EEG signatures for conditions like Lewy Body Dementia (LBD) and Alzheimer's Disease (AD).

Main Methods:

  • rsEEG data from 1750 subjects across 12 sites were preprocessed and harmonized using reComBat.
  • Oscillatory and aperiodic parameters were extracted using specparam from the harmonized posterior power spectrum.
  • Group differences were analyzed using bootstrap pairwise comparisons, permutation tests, and logistic regression.

Main Results:

  • Harmonization effectively reduced batch effects in the rsEEG posterior power spectrum.
  • Lewy Body Dementia (LBD) was characterized by steeper aperiodic parameters and lower oscillatory center frequency compared to other groups.
  • Alzheimer's Disease (AD) showed reduced oscillatory alpha power compared to healthy controls (HC) and Parkinson's Disease (PD).

Conclusions:

  • Data harmonization is effective in mitigating batch effects in rsEEG spectral analysis.
  • LBD exhibits significant oscillatory slowing and increased aperiodic activity.
  • AD presents with both oscillatory and aperiodic abnormalities, albeit with smaller effect sizes compared to LBD.