Blood-Based and Imaging Biomarkers of Atherosclerosis

Kashan Ali1, Chim C Lang1, Jeffrey T J Huang2

  • 1From the Division of Molecular & Clinical Medicine, School of Medicine, Ninewells Hospital & Medical School, University of Dundee, Dundee, UK.

Cardiology in Review
|February 17, 2022
PubMed

Insights

Atherosclerosis risk prediction can be improved by incorporating novel blood and imaging biomarkers. Research is ongoing to identify and validate these biomarkers for better cardiovascular event prediction and therapy guidance.

Area of Science:

  • Cardiovascular Medicine
  • Biomarker Discovery
  • Medical Imaging

Background:

  • Atherosclerosis is a primary cause of arterial thrombosis and acute cardiovascular events.
  • Current cardiovascular risk prediction models often lack pathophysiologically relevant biomarkers.
  • Emerging biomarkers, including blood-based and imaging markers, show promise for improving risk assessment.

Purpose of the Study:

  • To review existing literature on blood-based and imaging biomarkers for atherosclerosis.
  • To explore the potential of these biomarkers in enhancing cardiovascular risk prediction models.
  • To discuss future directions in biomarker research for cardiovascular disease.

Main Methods:

  • Literature review of studies investigating blood-based biomarkers (cardiac stress, inflammation, matrix remodeling, endothelial dysfunction).
  • Review of studies on imaging biomarkers for atherosclerosis detection and event prediction.
  • Analysis of the potential clinical applicability and pathophysiological relevance of identified biomarkers.

Main Results:

  • Numerous blood-based biomarkers targeting known pathophysiological pathways have been investigated.
  • Imaging biomarkers demonstrate promising results for atherosclerosis detection and cardiovascular event prediction.
  • Multifactorial nature of cardiovascular disease suggests that multiple biomarkers are needed for improved risk models.

Conclusions:

  • Blood-based and imaging biomarkers hold significant potential to enhance current cardiovascular risk prediction models.
  • Further research into emerging biomarkers is crucial for improving therapy decision-making.
  • Integrating multiple biomarkers is likely key to improving discrimination and reclassification in risk prediction.

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