Network-Guided Multiomic Mapping of Aortic Valve Calcification

Mark C Blaser1, Simon Kraler2, Thomas F Lüscher2,3,4

  • 1Center for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (M.C.B., E.A.).

Insights

Molecular insights into calcific aortic valve disease (CAVD) are limited, hindering new drug development. This review integrates multi-omics data and systems biology to identify potential therapeutic targets for CAVD, aiming to move beyond valve replacement.

Area of Science:

  • Cardiovascular Biology
  • Genomics and Systems Biology
  • Translational Medicine

Background:

  • Calcific aortic valve disease (CAVD) causes severe heart conditions, including heart failure and death, yet lacks effective drug therapies.
  • The complex and heterogeneous nature of valvular calcification presents significant challenges for research and treatment development.

Purpose of the Study:

  • To review current research on the molecular mechanisms underlying CAVD initiation and progression.
  • To explore the integration of multi-omics data (genomics, transcriptomics, proteomics, metabolomics) with network medicine and systems biology approaches.
  • To identify and prioritize druggable targets for potential pharmacotherapies for CAVD.

Main Methods:

  • Comprehensive review of studies investigating (epi-)genomic, transcriptomic, proteomic, and metabolomic profiles in aortic valve calcification.
  • Application of network medicine and systems biology strategies to integrate diverse omics datasets.
  • Prioritization of potential therapeutic targets based on integrated data analysis for experimental validation.

Main Results:

  • Multi-omics data reveal complex molecular pathways involved in the fibrocalcific spectrum of CAVD.
  • Systems biology approaches enable the identification of interconnected molecular networks driving disease progression.
  • Several prioritized druggable targets warrant further investigation for therapeutic potential.

Conclusions:

  • A holistic, multi-omics approach is crucial for understanding CAVD pathobiology.
  • Integrating diverse datasets through systems biology can uncover novel therapeutic strategies.
  • This research may pave the way for pharmacotherapies to treat CAVD, offering an alternative to valve replacement.