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Related Concept Videos

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

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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.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
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Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers01:19

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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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Cardiac myocytes produce these hormones in response to ventricular stretching...
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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.

Jonathan Gallego Rudolf1,2, Alex I Wiesman2, Sylvain Baillet2,3

  • 1Douglas Research Centre, McGill University, Montreal, QC, Canada.

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

Biomarker accuracy for predicting mild cognitive impairment (MCI) progression varies with time. Neurophysiological activity and tau PET are accurate up to 4 years prior, while Aβ PET and plasma biomarkers remain accurate up to 6 years before diagnosis.

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Area of Science:

  • Neuroscience
  • Biomarker Research
  • Cognitive Decline

Background:

  • Predicting progression from asymptomatic to mild cognitive impairment (MCI) is crucial.
  • Existing biomarkers need characterization regarding accuracy over time.
  • Neurophysiological activity's role in MCI risk prediction is underexplored.

Purpose of the Study:

  • To assess the dynamic accuracy of various biomarkers for predicting MCI progression.
  • To evaluate the contribution of neurophysiological activity alongside established biomarkers.
  • To establish a timeline for biomarker efficacy in MCI risk assessment.

Main Methods:

  • Assessed spectral power from magnetoencephalography (MEG), MRI hippocampal volumes, plasma biomarkers, and PET for amyloid-beta (Aβ) and tau.
  • Used logistic regression to model temporal accuracy of biomarkers in predicting MCI.
  • Included 102 cognitively unimpaired older adults with a family history of Alzheimer's disease (AD).

Main Results:

  • Neurophysiological activity and tau PET added value up to ~4 years before MCI diagnosis.
  • Aβ PET and plasma biomarkers maintained accuracy up to 6 years pre-diagnosis.
  • Age, sex, plasma p-tau217, Aβ/tau PET, and neurophysiological activity were significant predictors.

Conclusions:

  • Biomarker accuracy for predicting MCI progression is time-dependent.
  • Different biomarkers have varying temporal sensitivities.
  • Findings are critical for optimizing biomarker use in clinical trials for MCI screening.