Multiomics approaches to cardiovascular disease: technological innovations and clinical translation

Binte Zehra1, Nidhina Vinod1, Shuhd BinEshaq1

  • 1College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Health, Dubai, United Arab Emirates.

Insights

Emerging multi-omics technologies are revolutionizing cardiovascular disease (CVD) research by revealing complex molecular mechanisms. These advanced tools enable a deeper understanding of CVD, paving the way for precision cardiovascular medicine.

Area of Science:

  • Cardiovascular Biology
  • Genomics
  • Proteomics
  • Metabolomics

Background:

  • Cardiovascular diseases (CVDs) are a leading cause of death globally.
  • A gap exists between clinical understanding and the molecular basis of CVD.
  • Existing research often overlooks the complex molecular drivers of CVD.

Purpose of the Study:

  • To review how emerging multi-omic and functional genomics technologies are redefining cardiovascular disease research.
  • To highlight innovations in single-cell, spatial, and long-read sequencing, proteomics, metabolomics, and integrative data modeling.
  • To frame omics-enabled strategies for translating molecular insights into clinical applications for precision cardiovascular medicine.

Main Methods:

  • Utilizing high-resolution, cross-layer profiling (genomic, epigenomic, transcriptomic, proteomic, metabolomic, lipidomic, glycomic, fluxomic) at single-cell and spatial resolutions.
  • Applying computational and functional genomics, including genome-scale perturbation screens and single-cell perturbation frameworks.
  • Synthesizing data from emerging technologies to dissect regulatory circuits and identify disease drivers.

Main Results:

  • Multi-omic approaches reveal CVD as a multi-layered process involving dynamic interactions among cell types, regulatory programs, and metabolic states.
  • Innovations enable mechanistic dissection of regulatory circuits, distinguishing primary disease drivers from secondary adaptations.
  • These platforms advance the field from associative biomarker discovery to mechanism-guided target prioritization.

Conclusions:

  • Emerging omics technologies provide a unified, physiologically grounded framework for understanding CVD.
  • Integrating technological innovation with computational rigor and functional validation is key.
  • These strategies are crucial for translating molecular insights into clinically meaningful cardiovascular phenotypes and advancing precision cardiovascular medicine.

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