Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases

Rui-Sheng Wang1,2, Bradley A Maron1, Joseph Loscalzo1,2

  • 1Division of Cardiovascular Medicine (R.-S.W., B.A.M., J.L.), Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

Insights

Cardiovascular diseases (CVD) are complex, requiring multiomics data beyond genomics for personalized medicine. Network medicine integrates these diverse data types to understand CVD mechanisms and develop targeted therapies.

Area of Science:

  • Integrative biology
  • Network medicine
  • Precision medicine

Background:

  • Cardiovascular diseases (CVD) are a leading global cause of death with complex heterogeneity.
  • Genetic factors alone do not fully explain CVD mechanisms, necessitating multi-level molecular data.
  • Understanding CVD requires integrating genomics with epigenomics, transcriptomics, proteomics, and metabolomics.

Purpose of the Study:

  • To review multiomics technologies and their role in advancing precision medicine for CVD.
  • To highlight the application of network medicine for integrating multiomics data in CVD research.
  • To discuss challenges and future directions for multiomics network medicine in CVD therapeutics.

Main Methods:

  • Review of current multiomics technologies (bulk and single-cell).
  • Exploration of network medicine principles for data integration.
  • Analysis of applications in cardiovascular precision medicine.

Main Results:

  • Multiomics technologies offer new avenues for precise CVD diagnosis and personalized treatment.
  • Network medicine provides a framework for systematic integration of diverse omics data.
  • Integration facilitates a deeper understanding of CVD's complex molecular underpinnings.

Conclusions:

  • Multiomics data, integrated via network medicine, are crucial for advancing precision cardiovascular medicine.
  • This approach holds promise for developing novel therapeutics and improving patient outcomes.
  • Further research is needed to overcome current challenges and fully realize the potential of these methods.

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