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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

Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers

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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.
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
516

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Related Experiment Video

Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
07:20

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Biomarkers.

Xiao-Yu He1, Jin-Tai Yu2

  • 1Huashan Hospital, Fudan University, Shanghai, China.

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

This study reveals dynamic multi-omics changes years before dementia onset, identifying key biomarkers and potential drug targets for early intervention. Advanced machine learning improved dementia risk prediction using integrated omics data.

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Area of Science:

  • Genomics
  • Proteomics
  • Metabolomics
  • Neuroscience
  • Biomarker Discovery

Background:

  • Dementia is a major cause of disability with significant socioeconomic impact.
  • Understanding molecular mechanisms and identifying early biomarkers are critical for effective dementia interventions.
  • Multi-omics approaches provide a comprehensive framework to study dementia pathogenesis.

Purpose of the Study:

  • To conduct a longitudinal multi-omics analysis to unravel the complex molecular underpinnings of dementia.
  • To identify dementia-related genetic variants, proteins, and metabolites.
  • To develop advanced machine learning models for improved dementia risk prediction and identify potential therapeutic targets.

Main Methods:

  • Longitudinal multi-omics analysis integrating whole-genome sequencing, proteomics, metabolomics, and clinical data from a large cohort (N=320,226).
  • Single-omics association analyses followed by cross-omics integration using machine learning.
  • Mediation analysis and Mendelian randomization to assess causal relationships and identify drug targets.

Main Results:

  • Identified 203 lead genetic variants and 228 candidate genes associated with dementia subtypes.
  • Revealed distinct biological modules, including lipid metabolism dysregulation and synaptic dysfunction.
  • Demonstrated dynamic changes in blood multi-omics profiles up to 15 years before diagnosis, with specific proteins and metabolites showing early elevation.
  • An FT-Transformer model significantly improved dementia risk prediction by integrating multi-omics data.
  • Identified 258 mediators, including GDF15, IGFBP2, and NEFL, and 24 potential drug targets, with 8 having existing drugs.

Conclusions:

  • A comprehensive multi-omics framework was established for understanding dementia molecular mechanisms.
  • Dynamic evolution of multi-omics profiles before dementia onset was highlighted, offering avenues for early intervention.
  • Identified predictive biomarkers and potential therapeutic targets, including novel targets and opportunities for drug repurposing.