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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.

Stefan de Vries1, Katalin Farkas1, Mara Ten Kate1

  • 1Department of Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, Amsterdam, Netherlands.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 25, 2025
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Summary
This summary is machine-generated.

Brain age gap (BAG) predicts dementia progression in individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). BAG offers added value over visual rating scales (VRS) in early disease stages.

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence in Medicine
  • Dementia Research

Background:

  • Early dementia detection is critical for intervention.
  • Visual rating scales (VRS) assess brain atrophy on MRI for dementia prediction.
  • VRS limitations exist in early disease stages like mild cognitive impairment (MCI).
  • Brain age gap (BAG), derived from AI-analyzed MRI, shows potential for detecting dementia-related brain changes.

Purpose of the Study:

  • To evaluate if brain age gap (BAG) can predict dementia progression in individuals with subjective cognitive decline (SCD) and MCI.
  • To compare the predictive value of BAG against traditional visual rating scales (VRS).

Main Methods:

  • Utilized MRI data from 757 participants (391 SCD, 366 MCI) with over 2 years of follow-up.
  • Calculated BAG using BrainageR software on T1-weighted MRI scans.
  • Employed Cox regression to model dementia progression risk, including BAG, age, sex, and MMSE.
  • Assessed the added predictive value of BAG by incorporating VRS (medial temporal lobe, global, parietal atrophy).

Main Results:

  • 224 participants progressed to dementia (38 SCD, 186 MCI).
  • BAG significantly predicted dementia progression, showing added value beyond VRS.
  • BAG's predictive power was strongest in the SCD group, where VRS offered no additional benefit.
  • In the MCI group, BAG's predictive value diminished and became insignificant when VRS were included.

Conclusions:

  • Brain age gap (BAG) is a significant predictor of dementia progression in both SCD and MCI.
  • BAG provides added predictive value over VRS, particularly in the early stages of cognitive decline (SCD).
  • BAG demonstrates potential as a sensitive biomarker for dementia risk assessment, especially when traditional VRS are less effective.